Starkey Research & Clinical Blog

Do the benefits of tinnitus therapy increase with time?

Hearing Aids Alone can be Adjusted to Help with Tinnitus Relief

– noise reduction should be disabled;

– fixed activation of omnidirectional microphones introduce more environmental noise;

– lower compression knee points increase amplification for softer sounds;

Hearing Aid Behavior in the Real World

You’re getting older. Are your listening demands decreasing?

1.              Conversation in small group (3 or fewer people)

2.              Conversation in large group (more than four people)

3.              Conversation on the phone

4.              Speech listening – live talker

5.              Speech listening – media

6.              Little or no conversation

There were five environment categories:

1.              Outdoors – traffic

2.              Outdoors – other than traffic

3.              Home – 10 people or fewer

4.              Indoors other than home – 10 people or fewer

5.              Crowd of people (more than 11 people)

Does lip reading take the effort out of speech understanding?

For many people with hearing loss, visual cues from lip-reading are a valuable cue that has been proven to improve speech recognition across a variety of listening conditions (Sumby & Pollock, 1954; Erber, 1975; Grant, et al., 1998). To date is has remained unclear how visual cues, background noise, and hearing aid use interact with each other to affect listening effort.

Listening effort is often described as the allocation of additional cognitive resources to the task of understanding speech. If cognitive resources are finite or limited, then two or more simultaneous tasks will be in competition with each other for cognitive resources. Decrements in performance on one task can be interpreted as an allocation of resources away from the task and toward another concurrent task. Therefore, listening effort is often measured with dual-task paradigms, in which listeners respond to speech stimuli while simultaneously performing another task or responding to another kind of stimulus. Allocation of cognitive resources in this way is thought to represent a competition for working memory resources (Baddeley & Hitch, 1974; Baddeley, 2000).

The Ease of Language Understanding (ELU) model states that the process of understanding language involves matching phonological, syntactic, semantic and prosodic information to stored templates in long-term memory. When there is a mismatch between the incoming sensory information and the stored template, additional effort must be exerted to resolve the ambiguity of the message. This additional listening effort taxes working memory resources and may require the listener to allocate fewer resources to other tasks. Several studies have identified conditions that degrade a speech signal, such as background noise (Murphy, et al., 2000; Larsby et al., 2005; Zekveld et al., 2010) and hearing loss (Rabbitt, 1990; McCoy et al., 2005) in a manner that increases listening effort.

Individuals with reduced working memory capacity may be more negatively affected by conditions that degrade a speech signal. Previous reports have suggested that differences in working memory capacity hold a relationship to speech recognition in noise and performance with hearing aids in noise (Lunner, 2003; Foo et al., 2007).  The speed of retrieval from long-term memory may also affect performance and listening effort in adverse listening conditions (Van Rooij et al., 1989; Lunner, 2003). Because sensory inputs decay rapidly (Cowan, 1984), listeners with slow processing speed might not be able to fully process incoming information and match it to long term memory stores before it decays. Therefore, they would have to allocate more effort and resources to the task of matching sensory input to long-term memory templates.

Just as some listener traits might be expected to increase listening effort, some factors might offset adverse listening conditions by providing more information to support the matching of incoming sensory inputs to long-term memory. The use of visual cues is well known to improve speech recognition performance and some studies indicate that individuals with large working memory capacities are better able to make use of visual cues from lipreading (Picou et al., 2011).  Additionally, listeners who are better lipreaders may require fewer cognitive resources to understand speech, allowing them to make better use of visual cues in noisy environments (Hasher & Zacks, 1979; Picou et al., 2011).

The purpose of Picou, Ricketts and Hornsby’s study was to examine how listening effort is affected by hearing aid use, visual cues and background noise. A secondary goal of the study was to determine how specific listener traits such as verbal processing speed, working memory and lipreading ability would affect the measured changes in listening effort.

Twenty-seven hearing-impaired adults participated in the study. All were experienced hearing aid users and had corrected binocular vision of 20/40 or better. Participants were fitted with bilateral behind-the-ear hearing aids with non-occluding, non-custom eartips. Advanced features such as directionality and noise reduction were turned off, though feedback management was left on in order to maximize usable gain. Hearing aids were programmed with linear settings to eliminate any potential effect of amplitude compression on listening effort, a relationship which is as of yet unestablished.

A dual-task paradigm with a primary speech recognition task and secondary visual reaction time task was used to measure listening effort. The speech recognition task used monosyllabic words spoken by a female talker (Picou, 2011), presented at 65dB in the presence of multi-talker babble. Prior to the speech recognition task, individual SNRs for auditory only (AO) and auditory-visual (AV) conditions were determined at levels that yielded performance between 50-70% correct, because scores in this range are most likely to show changes in listening effort (Gatehouse & Gordon, 1990).

The reaction time task required participants to press a button in response to a rectangular visual probe that occurred prior to presentation of the speech token. The visual probe was presented prior to the speech tokens, so that the probe would not distract from the use of visual cues during the speech recognition task. The visual and speech stimuli were presented within a narrow enough interval (less than 500 msec) so that cognitive resources would have to be expended for both tasks at the same time (Hick & Tharpe, 2002).

Three listener traits were examined with regard to listening effort in quiet and noisy conditions, with and without visual cues. Visual working memory was evaluated with the Automated Operation Span (AOSPAN) test (Unsworth et al., 2005). The AOSPAN requires subjects to solve math equations and memorize letters. After seeing a math equation and identifying the answer, subjects are shown a letter which disappears after 800 msec. Following a series of equations they are then asked to identify the letters that they saw, in the order that they appeared. Scores are based on the number of letters that are recalled correctly.

Verbal processing speed was assessed with a lexical decision task (LDT) in which subjects were presented with a string of letters and were asked to indicate, as quickly as possible, if the letters formed a real word.  The test consisted of 50 common monosyllabic English words and 50 monosyllabic nonwords. The task reflects verbal processing speed because it requires the participant to match the stimuli to representations of familiar words stored in long-term memory (Meyer & Schvaneveldt, 1971; Milberg & Blumstein, 1981; Van Rooij et al., 1989). The reaction time to respond to the stimuli was used as a measure of verbal processing speed.

Finally, lipreading ability was measured with the Revised Shortened Utley Sentence Lipreading Test (ReSULT; Updike, 1989). The test required participants to repeat sentences spoken by a female talker, when the talker’s face was visible but speech was inaudible. Responses were scored based on the number of words repeated correctly in each sentence.

Subjects participated in two test sessions. At the first session, vision and hearing was tested, individual SNR levels were determined for the speech recognition task and AOSPAN, LDT and ReSULT scores were obtained.  At the second session, subjects completed practice sequences with AO and AV stimuli, then the dual speech recognition and visual reaction time tests were administered in eight counterbalanced conditions listed below. Due to the number of experimental conditions, only select outcomes of this study will be reviewed.

1.         auditory only in quiet, unaided

2.         auditory only in noise, unaided

3.         auditory-visual in quiet, unaided

4.         auditory-visual in noise, unaided

5.         auditory only in quiet, aided

6.         auditory only in noise, aided

7.         auditory-visual in quiet, aided

8.         auditory-visual in noise, aided

The main analysis showed that background noise impaired performance in all conditions and hearing aid use and visual cues improved performance. However, there were significant interactions between hearing aid use and visual cues, hearing aids and background noise, and visual cues and background noise, indicating that the effect of hearing aid use depended on the test modality (AV or AO), and background noise (present or absent), and the effect of visual cues depended on background noise (present or absent).  Hearing aid benefit proved to be larger in AO conditions than in AV conditions and was larger in quiet conditions than in noisy conditions.  The effect of noise was greater in the AV conditions than in the AO conditions, but the authors suggest that this could have been related to the individualized SNRs chosen for the test procedure.

On the reaction time task, background noise increased listening effort and hearing aid use reduced listening effort, though there was high variability and the effects of both variables were small. Additional analysis determined that the individual SNRs chosen for the dual task did not affect the hearing aid benefits that were measured. The availability of visual cues did not change overall reaction times and it was therefore determined that visual cues did not affect listening effort in this task of reaction time.

With regard to listening effort benefits derived from hearing aid use, the performance in quiet conditions was strongly related to performance in noise. In other words, subjects who obtained benefit from hearing aid use in quiet also obtained benefit in noise and individuals with slower verbal processing speed were more likely to derive benefit from hearing aid use. With regard to visual cues, there were several correlations with listener traits. Subjects who were better lipreaders derived more benefit from visual cues and those with smaller working memory capacities also showed more benefit from visual cues. These correlations were significant in quiet and noisy conditions. For quiet conditions, there was a positive correlation between verbal processing speed and benefit from visual cues, with better verbal processors showing more benefit from visual cues. There were no correlations between background noise and any of the measured listener traits.

The overall findings that visual cues and hearing aid use had positive effects and background noise had a negative effect on speech perception performance were not surprising. Similarly, the findings that hearing aid benefit was reduced for AV conditions versus AO conditions and for noisy versus quiet conditions were consistent with previous reports (Cox & Alexander, 1991; Walden et al., 2001; Duquesnoy & Plomp, 1983).  Because hearing aid use improves audibility, visual cues might not have been needed as much as they were in unaided conditions and the presence of noise may have counteracted the improved audibility by masking a portion of the speech cues needed for correct understanding, especially with the omnidirectional, linear instruments used in this study.

The ability of hearing aids to decrease listening effort was significant, in keeping with previously published results, but the improvements were lesser than than those reported in some previous studies. This could be related to the non-simultaneous timing of the tasks in the dual-task paradigm, but the authors surmise that it could be related to the way their subjects’ hearing aids were programmed. In most previous studies, individuals used their own hearing aids, set to individually prescribed and modified settings. In the current study, all participants used the same hearing aid circuit set to linear, unmodified targets. Advanced features like directionality and noise reduction, which are likely to impact listening effort (Sarampalis, 2009), speech discrimination ability and perceived ease of listening in everyday situations, were turned off.

There was a significant relationship between verbal processing speed and hearing aid benefit, in that subjects with slower processing speed were more likely to benefit from hearing aid use.  Sensory input decays rapidly and requires additional cognitive effort when it is mismatched with long-term memory stores. Any factor that improves the sensory input may facilitate the matching process. The authors posited that slow verbal processors might benefit more from amplification because hearing aids improved the quality of the sensory input, thereby reducing the cognitive effort and time that would otherwise be required to match the input to long-term memory templates.

On average, the availability of visual cues did not have a significant effect on listening effort. This may be a surprising result given the well-known positive effects of visual cues for speech recognition. However, there was high variability among subjects and it was apparent that better lipreaders were more able to make use of visual cues, especially in quiet conditions without hearing aids. Working memory capacity was negatively correlated with benefit from visual cues, indicating that subjects with better working memory capacity derived less benefit from visual cues on average. The relationship between these variables is unclear, but the authors suggest that individuals with lower working memory capacities may be more susceptible to changes in listening effort and therefore more likely to benefit from additional sensory information such as visual cues.

Understanding how individual traits affect listening effort and susceptibility to noise is important to audiologists for a number of reasons, partly because we often work with older individuals. Working memory declines as a result of the normal aging process and may begin in middle age (Wang, et al., 2011).  Similarly, the speed of cognitive processing slows and visual impairment becomes more likely with increasing age (Clay, et al., 2009). Many patients seeking audiological care may also suffer from these deficits in working memory, verbal processing, and visual acuity. Though more research is needed to understand how these variables relate to one another, they should be considered in clinical evaluations and hearing aid fittings.  Advanced hearing aid features that counteract the degrading effects of noise and reverberation may be particularly important for elderly or visually impaired hearing aid users. As shown in the reviewed study, these patients will benefit significantly from face-to-face conversation, slow speaking rates and reduced environmental distractions. Counseling sessions should include discussion of these issues so that patients and family members understand how they can use strategic listening techniques, in addition to hearing aids, to improve speech recognition and reduce cognitive effort.

Clay, O., Edwards, J., Ross, L., Okonkwo, O., Wadley, V., Roth, D. & Ball, K. (2009). Visual function and cognitive speed of processing mediate age-related decline in memory span and fluid intelligence. Journal of Aging and Health 21(4), 547-566.

Cox, R.M. & Alexander, G.C. (1991).  Hearing aid benefit in everyday environments. Ear and Hearing 12, 127-139.

Downs, D.W. (1982). Effects of hearing aid use on speech discrimination and listening effort. Journal of Speech and Hearing Disorders 47, 189-193.

Duquesnoy, A.J. & Plomp, R. (1983). The effect of a hearing aid on the speech reception threshold of hearing impaired listeners in quiet and in noise. Journal of the Acoustical Society of America 73, 2166-2173.

Erber, N.P. (1975). Auditory-visual perception of speech. Journal of Speech and Hearing Disorders 40, 481-492.

Foo, C., Rudner, M. & Ronnberg, J. (2007). Recognition of speech in noise with new hearing instrument compression release settings requires explicit cognitive storage and processing capacity. Journal of the American Academy of Audiology 18, 618-631.

Gatehouse, S., Naylor, G. & Elberling, C. (2003). Benefits from hearing aids in relation to the interaction between the user and the environment. International Journal of Audiology 42 Suppl 1, S77-S85.

Gatehouse, S. & Gordon, J. (1990). Response times to speech stimuli as measures of benefit from amplification. British Journal of Audiology 24, 63-68.

Grant, K.W., Walden, B.F. & Seitz, P.F. (1998).  Auditory visual speech recognition by hearing impaired subjects. Consonant recognition, sentence recognition and auditory-visual integration. Journal of the Acoustical Society of America 103, 2677-2690.

Hick, C.B. & Tharpe, A.M. (2002). Listening effort and fatigue in school-age children with and without hearing loss. Journal of Speech, Language and Hearing Research 45, 573-584.

Hornsby, B.W.Y. (2013).  The Effects of Hearing Aid Use on Listening Effort and Mental Fatigue Associated with Sustained Speech Processing Demands. Ear and Hearing, in press.

Meyer, D.E. & Schvaneveldt, R.W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology 90, 227-234.

Milberg, W. & Blumstein, S.E. (1981). Lexical decision and aphasia: Evidence for semantic processing. Brain and Language 14, 371-385.

Picou, F.M., Ricketts, T.A. & Hornsby, B.W.Y (2011). Visual cues and listening effort: Individual variability. Journal of Speech, Language and Hearing Research 54, 1416-1430.

Rudner, M., Foo, C. & Ronnberg, J. (2009). Cognition and aided speech recognition in noise: Specific role for cognitive factors following nine week experience with adjusted compression settings in hearing aids. Scandinavian Journal of Psychology 50, 405-418.

Sarampalis, A., Kalluri, S., Edwards, B. & Hafter, E. (2009) Objective measures of listening effort: effects of background noise and noise reduction. Journal of Speech, Language, and Hearing Research 52, 1230–1240.

Sumby, W.H. & Pollock, I. (1954). Visual contribution to speech intelligibility in noise. Journal of the Acoustical Society of America 26, 212-215.

Unsworth, N., Heitz, R.P. & Schrock, J.C. (2005). An automated version of the operation span task. Behavioral Research Methods 37, 498-505.

Van Rooij, J.C., Plomp, R. & Orlebeke, J.F. (1989).  Auditive and cognitive factors in speech perception by elderly listeners. I: Development of test battery. Journal of the Acoustical Society of America 86, 1294-1309.

Walden, B.F., Grant, K.W. & Cord, M.T. (2001). Effects of amplification and speechreading on consonant recognition by persons with impaired hearing. Ear and Hearing 22, 333-341.

Wang, M., Gamo, N., Yang, Y., Jin, L., Wang, X., Laubach, M., Mazer, J., Lee, D. & Arnsten, A. (2011). Neuronal basis of age-related working memory decline. Nature 476, 210-213.

Can hearing aids reduce listening fatigue?

Hornsby, B.W.Y. (2013). The Effects of Hearing Aid Use on Listening Effort and Mental Fatigue Associated with Sustained Speech Processing Demands. Ear and Hearing, Published Ahead-of-Print.

A patient recently told me that he wanted to put on his glasses so he could hear me better.  He was joking, but was correct in understanding that visual cues help facilitate speech understanding. When engaged in conversation, a listener uses many sources of information to supplement the auditory stimulus. Visual cues from lip-reading, gestures and expressions as well as situational cues, conversational context and the listener’s knowledge of grammar all help limit the possible interpretations of the message. Conditions that degrade the auditory stimulus, such as reverberation, background noise and hearing loss cause increased reliance on other cues in order for the listener to “fill in the blanks” and understand the spoken message. The use of these additional information sources amounts to an increased allocation of cognitive resources, which has also been referred to as increased “listening effort” (Downs, 1982; Hick & Tharpe, 2002; McCoy et al., 2005).

Research suggests that the increased cognitive effort required for hearing-impaired individuals to understand speech may lead to subjective reports of mental fatigue (Hetu et al., 1988; Ringdahl & Grimby, 2000; Kramer et al., 2006). This may be of particular concern to elderly people and those with cognitive, memory or other sensory deficits. The increased listening effort caused by hearing loss is associated with self-reports of stress, tension and fatigue (Copithorne 2006; Edwards 2007). In a study of factory workers, Hetu et al. (1988) reported that individuals with difficulty hearing at work needed increased attention, concentration and effort, leading to increased stress and fatigue. It is reasonable to conclude that listening effort as studied in the laboratory should be linked to subjective associations of hearing loss with mental fatigue, but the relationship is not clear. Dr. Hornsby points out that laboratory studies typically evaluate short-term changes in resource allocation as listening ease is manipulated in the experimental task. However, perceived mental fatigue is more likely to result from sustained listening demands over a longer period of time, e.g., a work day or social engagement lasting several hours (Hetu et al., 1988; Kramer et al., 2006).

The purpose of Dr. Hornsby’s study was to determine if hearing aids, with and without advanced features like directionality and noise reduction, reduce listening effort and subsequent susceptibility to mental fatigue. He also investigated the relationship between objective measures of speech discrimination and listening effort in the laboratory with subjective self-reports of mental fatigue.

Sixteen adult subjects participated in the study. All had bilateral, symmetrical, mild-to-severe sensorineural hearing loss. Twelve subjects were employed full-time and reported being communicatively active about 65% of the time during the day. The remaining subjects were not employed but reported being communicatively active about 61% of the day. Twelve subjects were bilateral hearing aid users and four subjects were non-users. Subjects were screened to rule out cognitive dysfunction. All participants were fitted with bilateral behind-the-ear hearing aids with slim tubes and dome ear tips.  Hearing aids were programmed in basic and advanced modes. In basic mode, the microphones were omnidirectional and all advanced features except feedback suppression were turned off. In advanced mode, the hearing aids were set to manufacturer’s defaults with automatically adaptive directionality, noise reduction, reverberation reduction and wind noise reduction. All subjects wore the study hearing aids for at least 1-2 weeks before the experimental sessions began.

For the objective measurements of listening effort, subjects completed a word recognition in noise task paired with an auditory word recall task and a measure of visual reaction time.  Subjects heard random sets of 8 to 12 monosyllabic words preceded by the carrier phrase, “Say the word…” They were asked to repeat the words aloud and the percentage of correct responses was scored. In addition, subjects were asked to remember the last 5 words of each list. The end of the list was indicated by the word “STOP” on a screen in front of the speaker. Subjects were instructed to press a button as quickly as possible when the visual prompt appeared. Because the lists varied from 8 to 12 items, subjects never knew when to expect the visual prompt.  To control for variability in motor function, visual reaction time was measured alone in a separate session, during which subjects were instructed to simply ignore the speech and noise.

Subjective ratings of listening effort and fatigue were obtained with a five-item scale, administered prior to the experimental sessions. Three questions were adapted from the Speech Spatial and Qualities of Hearing Questionnaire (SSQ: Gatehouse & Noble, 2004) and the remaining items were formulated specifically for the study. Questions were phrased to elicit responses related to that particular day (“Did you have to put in a lot of effort to hear what was being said in conversation today?”, “How mentally/physically drained are you right now?”).  The final two questions were administered before and after the dual-task session and measured changes in attention and fatigue due to participation in the experimental tasks.

The word recognition in noise test yielded significantly better results in both aided conditions than in the unaided condition, though there was no difference between the basic and advanced aided conditions. The differences between unaided and aided scores varied considerably, suggesting that listening effort for individual subjects varied across conditions.  Unaided word recall was significantly poorer than basic or advanced aided performance. There was a small, significant difference between the two aided conditions, with advanced settings outperforming basic settings. In follow-up planned comparison tests, the aided vs. unaided difference was maintained though there was not a significant difference between the two aided conditions.

The reaction time measurement also assessed listening effort or the cognitive resources required for the word recognition test.  Reaction times were analyzed according to listening condition as well as block, which compared the first three trials (initial block) to the last three trials (final block).  Increases in reaction time by block represented the effect of task-related fatigue.  Analysis by listening condition showed that unaided reaction times increased more than reaction times for the advanced aided condition but not the basic aided condition. In other words, subjects required more time to react to the visual stimulus in the unaided condition than they did in the advanced aided condition. There was no significant difference between the two aided conditions.  There was a significant main effect for block; reaction times increased over the duration of the task. There was no interaction between listening condition and block; changes in performance over time were consistent across unaided and aided conditions.

One purpose of the study was to investigate the effect of hearing aid use on mental fatigue. Interestingly, comparison of initial and final blocks indicated that word recognition scores increased about 1-2% over time but improvement over time did not vary across listening conditions. There was no decrease in performance on word recall over time, nor did changes in performance over time vary significantly across listening conditions.  But reaction time did increase over time for all conditions, indicating a shift in cognitive resources away from the reaction time task and toward the primary word recognition task. Though the effect of hearing aid use was not significant, a trend appeared suggesting that fewer aided listeners had increased reaction.

The questionnaires administered before the session probed perceived effort and fatigue throughout the day, whereas the questions administered before and after the task probed focus, attention and mental fatigue before and after the test session. In all listening conditions there was a significant increase in mental fatigue and difficulty maintaining attention after completion of the test session. A non-significant trend suggested some difference between unaided and aided conditions.

To identify other factors that may have contributed to variability, correlations for age, pure tone average, high frequency pure tone average, unaided word recognition score, SNR during testing, employment status and self-rated percentage of daily communicative activity were calculated with the subjective and objective measurements. None of the correlations were significant, indicating that none of these factors contributed substantially to the variability observed in the study.

Cognitive resource allocation is often studied with dual-task paradigms like the one used in this study. Decrements in performance on the secondary task indicate a shift in cognitive resources to the primary task. Presumably, factors that increase difficulty in the primary task will increase allocation of resources to the primary task.  In these experiments, the primary task was a word recognition test and the secondary tasks were word recall and reaction time measurements. Improved word recall and quicker reaction times in aided conditions indicate that the use of hearing aids made the primary word recognition task easier, allowing listeners to allocate more cognitive resources to the secondary tasks. Furthermore, reaction times increased less over time in aided conditions than in unaided conditions.  These findings specifically suggest that decreased listening effort with hearing aid use may have made listeners less susceptible to fatigue as the dual-task session progressed.

Though subjective reports in this study showed a general trend toward reduced listening effort and concentration in aided conditions, there was not a significant improvement with hearing aid use. This contrasts with previous work that has shown reductions in subjective listening effort with the use of hearing aids (Humes et al., 1999; Hallgren et al., 2005; Noble & Gatehouse, 2006). The author notes that auditory demands vary widely and that participants were asked to rate their effort and fatigue based on “today”, which didn’t assess perceptions of sustained listening effort over a longer period of time may not have detected subtle differences among subjects.  For instance, working in a quiet office environment may not highlight the benefit of hearing aids or the difference between an omnidirectional or directional microphone program, simply because the acoustic environment did not trigger the advanced features often enough. In contrast, working in a school or restaurant might show a more noticeable difference between unaided listening, basic amplification and advanced signal processing. Though subjects reported being communicatively active about the same proportion of the day, this inquiry didn’t account for sustained listening effort over long periods of time, or varying work and social environments. These differences would likely affect overall listening effort and fatigue, as well as the value of advanced hearing aid features.

Clinical observations support the notion that hearing aid use can reduce listening effort and fatigue.  Prior to hearing aid use, hearing-impaired patients often report feeling exhausted from trying to keep up with social interactions or workplace demands. After receiving hearing aids, patients commonly report being more engaged, more able to participate in conversation and less drained at the end of the day. Though previous reports have supported the value of amplification on reduced listening effort, Hornsby’s study is the first to provide experimental data for the potential ability of hearing aid use to reduce mental fatigue.

These findings have important implications for all hearing aid users, but may have particular importance for working individuals with hearing loss as well as elderly hearing impaired individuals.  It is important for any working person to maintain a high level of job performance and to establish their value at work. Individuals with hearing loss face additional challenges in this regard and often take pains to prove that their hearing loss is not adversely affecting their work.  Studies in workplace productivity underscore the importance of reducing distractions for maintaining focus, reducing stress and persisting at difficult tasks (Clements-Croome, 2000; Hua et al., 2011). Studies indicating that hearing aids reduce listening effort and fatigue, presumably by improving audibility and reducing the potential distraction of competing sounds, should provide additional encouragement for employed hearing-impaired individuals to pursue hearing aids.

Baldwin, C.L. & Ash, I.K. (2011). Impact of sensory acuity on auditory working memory span in young and older adults. Psychology of Aging 26, 85-91.

Clements-Croome, D. (2000). Creating the productive workplace. Publisher: London, E & FN Spon.

Edwards, B. (2007). The future of hearing aid technology. Trends in Amplification 11, 31-45.

Gatehouse, S. & Noble, W. (2004). The speech, Spatial and Qualities of Hearing Scale (SSQ). International Journal of Audiology 43, 85-99.

Hua, Y., Loftness, V., Heerwagen, J. & Powell, K. (2011). Relationship between workplace spatial settings and occupant-perceived support for collaboration. Environment and Behavior 43, 807-826.

Humes, L.E., Christensen, L. & Thomas, T. (1999). A comparison of the aided performance and benefit provided by a linear and a two-channel wide dynamic range compression hearing aid. Journal of Speech, Language and Hearing Research 42, 65-79.

Kramer, S.E., Kapteyn, T.S. & Houtgast, T. (2006). Occupational performance: comparing normal-hearing and hearing-impaired employees using the Amsterdam Checklist for Hearing and Work. International Journal of Audiology 45, 503-512.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: Downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A 58, 22-33.

Picou, E.M., Ricketts, T.A. & Hornsby, B.W. (2011). Visual cues and listening effort: Individual variability. Journal of Speech, Language and Hearing Research 54, 1416-1430.

Sarampalis,  A., Kalluri, S. & Edwards, B. (2009). Objective measures of listening effort: Effects of background noise and noise reduction. Journal of Speech, Language and Hearing Research 52, 1230-1240.

Valente, M. & Mispagel, K. (2008) Unaided and aided performance with a directional open-fit hearing aid. International Journal of Audiology 47(6), 329-336.

Evidence for the Value of Real-Ear Measurement

The Top 5 Audiology Research Articles from 2012

3. NAL-NL2 Empirical Adjustments

5. Conducting qualitative research in audiology: A tutorial

Quartile           Category                       Total THI Score

1st                   No handicap                       0-16

2nd                  Mild handicap                     18-36

3rd                   Moderate handicap              38-56

4th                   Severe handicap                 58-100


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Language Knowledge Base for the Development of Chinese Information Processing

Release time：2017-10-05

Language information processing aims to enable computers to understand and use human languages. The Comprehensive Language Knowledge Base (CLKB) is the infrastructure of language information processing techniques and industry, which provides formalized and standardized language knowledge as well as core softwares for new generation information technologies such as smart search, machine translation and man-machine conversation.

In our country, formal research on language information processing emerged in mid 1980s when there are very few Chinese language resources in the world. Different from English and Japanese, a lack of formalized annotation in Chinese makes it difficult to construct a Chinese language knowledge base that is badly needed for Chinese information processing. The research group in the Institute of Computational Linguistics at Peking University, who is erudite on Chinese and Chinese culture, have studied computational models for Chinese and methodologies for language knowledge bases since 1986. The comprehensive language knowledge base that has been developed for 30 years strongly supports the original scientific research and application development for Chinese information processing.

CKLB is novel in the following aspects: (1) it serves as a practical Chinese language resource for information processing, which never existed before; (2) it builds language knowledge description system and computational models for Chinese; (3) it formulates serialized language knowledge construction standard which has partially adopted by China's national bureau of standards; (4) it presents a word sense based integration solution, breaking the technical bottleneck of heterogeneous knowledge base integration; (5) it proposes an engineering method for building a language knowledge base.

The CLKB, which won the national scientific and technological progress award in 2011, includes 6 language knowledge bases, 10 standards, 4 core softwares and 4 application systems. They support each other, forming a closely connected organic whole.

Language knowledge base is the core of CKLB, including:

1) The grammatical knowledge base of contemporary Chinese, containing 3.6 million grammatical attributes description for 80,000 words.

2)    The bank of Chinese phrase structure rules, containing more than 600 grammatical rules.

3) The multistage processing corpus of contemporary Chinese, which has word segmentation and part-of-speech tags for 150 million Chinese characters of which 52 million Chinese characters are annotated in fine grain and 28 million Chinese characters are tagged with their senses.

4) Multi-lingual concept dictionary, containing 100 thousand synset concept

5) Parallel corpus, containing 1 million English-Chinese parallel sentence pairs.

6) Multi-domain term bank, containing 350,000 Chinese-English bilingual terms.

The serialized language knowledge base provided by CLKB includes a variety knowledge such as words, phrases, sentences, discourses and lexical, syntactical and even semantic knowledge, which can be used in both general and specialized domains in multiple languages including Chinese. CLKB is the largest and most widely acknowledged Chinese language knowledge resource.

CLKB not only has a profound effect in academia and but also have produced substantial social and economic effects. Its manual and proposed standards have been widely cited and two excellent doctorate theses focused on CLKB. Both of the two projects that won the first prize of Qian weichang Chinese information processing science and technology award (top award in the field of Chinese information processing) in 2010 states that all the linguistic knowledge in their systems is from CLKB. CLKB has more than 10,000 free users and its contract users since 1996 spread all over the world, including Apple, Google, IBM, Intel, Microsoft and Huawei. CLKB also contributes to processing of minority languages in China, gesture language translation and international communication of Chinese. The lifecycle of CKLB is incredibly long in IT field.

The grammatical knowledge base of contemporary Chinese, which serves as the core part of CKLB, won the second prize of the ministry of education's technology progress award in 1998. Prof. Shiwen Yu, the first inventor of CLKB, won the first Lifetime Achievement Award by Chinese information processing society in the 30th anniversary of Chinese information processing society in 2011. In addition, CLKB and its inventors won many other awards. After winning the national scientific and technological progress award in 2011, CLKB was awarded the special contribution prize of combination of production, education and scientific research by Peking University in 2013.

Language knowledge resources in CLKB, which are based on the grammatical knowledge base of contemporary Chinese, have started negotiating transfer since 1996. By 2017, the transfer has never stopped. It is uncommon that a research achievement has such a long life in IT field.


Two different lot of RLD in 2WC steady state study due to short shelf-life [Study Performance]

posted by Mithu – India, 2019-01-30 12:22  – Posting: # 19828
Views: 388

(edited by mittyri on 2019-01-30 12:52)

Dear Member

We are at the edge of start one of the injection study where we have to give six injections to subject in each period to achieve steady state. now each injection will be administer with the gap of 1 month. total duration of single period is around six month and same for the period II.

Now the actual challenge is, dosing date of each subject is different based on their availability and willingness to participate in the study. due to this reason, we are going to use two different lot of RLD in same study due to having very short self-life of RLD product.

My question is, how FDA will take this usage of 02 different lot of RLD in single study? do we need to normalize the data of all the subjects based on the differences of the RLD lot? does the usage of two different lot will be taken as treatment effect and will it be justified?

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If debugging is the process of removing bugs,

BEBAC Ing. Helmut Schütz


13401The NIGERIA RUGBY FOOTBALL FEDERATION (NRFF) has blamed the national team’s (Black Stallions) failure to qualify for next year’s Olympic Games on inadequate funding by the government and the private sector.

The vice president of the Federation, TUNJI FASIMOYE told journalists yesterday that the team’s desire to excel at the just concluded Olympics qualifier in South Africa could not be attained because other Africa teams in the championship were adequately funded and exposed to more sophisticated facilities than the Nigerian team.

FASIMOYE pleaded with the newly appointed MINISTER FOR YOUTH AND SPORTS, SOLOMON DALUNG, to pay attention to RUGBY and other sports in the country, nothing that rugby could bring as much recognition to Nigeria as football if properly funded.


Click here for Part One.

This is the second of a two-part post in which I describe four broad research trends that I observed at ACL 2017. In Part One I explored the shifting assumptions we make about language, both at the sentence and the word level, and how these shifts are prompting both a comeback of linguistic structure and a re-evaluation of word embeddings.

In this part, I will discuss two more very inter-related themes: interpretability and attention.

Throughout, green links are ordinary hyperlinks, while blue links lead to papers, and offer bibliographic information when you hover over them (not supported on mobile).

Trend 3: Interpretability

I’ve been thinking about interpretability a lot recently, and I’m not alone – among deep learning practitioners, the dreaded “black box” quality of neural networks makes them notoriously hard to control, hard to debug and thus hard to develop. From a non-researcher perspective however, there is an even more important reason to desire interpretability: trust.

A sinister black box hovering over a spike

One of many unsettling images used to depict AI in the media. By Keith Rankin.

The public, the media and some researchers are expressing increased anxiety about whether AI can be trusted if it cannot be understood. While some of these anxieties are ill-founded (see the “Facebook chatbots invent their own language” story), others are very real. For example, if AI systems absorb unwanted biases present in their training data, but we are unable to check the system for those biases, then we have a recipe for disaster. Second, as AI systems are imperfect and sometimes fail, then we must be able to check how they make their decisions – especially for more complex tasks. Third, even if AI systems operate perfectly, humans may always need the reassurance of explanation.

Even among researchers, “interpretability” can have many possible definitions – for an exploration of those definitions I highly recommend Zachary Lipton’s essay The Mythos of Model Interpretability. In particular, Lipton identifies two broad approaches to interpretability: post-hoc explanations and transparency. Post-hoc explanations take a learned model and draw some kind of useful insights from it; typically these insights provide only a partial or indirect explanation of how the model works. Transparency asks more directly “how does the model work?” and seeks to provide some way to understand the core mechanisms of the model itself. I think this is a useful distinction, so I’ll use it to explore the following ACL work.

Post-hoc explainability

At ACL, I saw many papers presenting a variety of creative methods to gain post-hoc insights into neural systems.

Visualization is probably the most common type of post-hoc interpretability, with particular types of visualizations – such as saliency maps and 2D projections of word embeddings – becoming standard. These visualizations are certainly useful (and I’m always grateful to see them in a paper), but they can be misleading if read incorrectly. In Visualizing and Understanding Neural Machine Translation, Ding et al. compute relevance scores that quantify how much a particular neuron or hidden state contributes to another neuron or hidden state. At first glance, the visualizations provided in the paper (which essentially give an importance score to each hidden state and its associated token) look very similar to the visualizations commonly produced from the attention distribution. However, the method of computation is very different. The relevance scores are a direct measure of how much one neuron affects a downstream neuron, calculated post-hoc on the trained model. By contrast the attention distribution is learned and computed by the network itself; it is an intermediate representation that affects the rest of the computation in complex ways. Though attention often plays the role of word alignment in NMT, Koehn and Knowles note that it learns to play other, harder-to-understand roles too; thus it is not always as understandable as we might hope. Ding et al.’s relevance scores provide a useful alternative way to measure word-level relevance in sequence-to-sequence models.

A visualization of the attention distribution, in which it's one step shifted from expected word alignment

Koehn and Knowles show attention is sometimes off-by-one from word alignment. How should we interpret this behavior?

Transfer learning is another popular post-hoc analysis technique, in which the representations learned for task A (typically a high-level task) are applied to task B (typically a lower-level task). The degree of success at task B indicates how much the task A model has learned about task B. At ACL 2017, researchers asked what NMT models know about morphology, what Language Models know about NER and chunking, and what speech+vision representations know about various semantic tasks. These studies, which are often carefully repeated with different layers and various configurations of the task A model, can yield useful and unexpected insights that guide the development of better models for task A. For example, in What do Neural Machine Translation Models Learn about Morphology? Belinkov et al. find that while attention increases the quality of morphological information in the encoder representations, it decreases the quality for the decoder representations. I was surprised to read about this unintended side-effect of attention, and overall I really like how the paper thoughtfully and thoroughly addresses its research questions.

Though transfer learning and attention-like visualizations can tell you “how much”, they do not tell you “what” or “why”. To answer the latter, some researchers directly study the geometry of the representation spaces themselves. In Emergent Predication Structure in Hidden State Vectors of Neural Readers, Wang et al. provide evidence that in RNN-based reading comprehension models, the hidden vector space can be decomposed into two orthogonal subspaces: one containing representations of entities, and the other containing representations of statements (or predicates) about those entities. Though it is not a focus of the paper, I wonder whether these component parts of the hidden state could be further interpreted. In Parameter Free Hierarchical Graph-Based Clustering for Analyzing Continuous Word Embeddings, Trost and Klakow perform clustering on word embeddings, then cluster those clusters, and so on to obtain a hierarchical tree-like structure. Judging by the examples provided in the paper, the hierarchy could provide a more human-readable way to explore the neighborhood structure of word embeddings.

A graph showing the hierarchy of words below 'dropped'

Trost and Klakow

Another approach to direct post-hoc interpretation is to treat interpretation itself as a translation task. In Translating Neuralese, Andreas et al. take the vector messages (“neuralese”) passed between two machines trained to perform a collaborative task, and translate them into natural language utterances. To overcome the absence of neuralese-to-English parallel data, Andreas et al. consider a pair of messages equivalent if they are used in similar scenarios by human and machine agents. The authors raise important questions about whether these translations can be trusted. What happens if the neuralese messages encode concepts that are impossible to capture in English? If humans and machines have different biases about what they choose to communicate, how can we be sure that crowdsourced training data contains English examples that correspond to the neuralese? In any case, this was one of my favorite papers of the conference, and I’m excited to see where this research goes next.

English translations of messages passed in various scenarios

Andreas et al.

Despite all the work gleaning post-hoc insight from uninterpretable neural models, some researchers argue that (notwithstanding finding the odd sentiment neuron) staring into the neurons will only get us so far. True interpretability requires transparency – models that are constructed and trained to be interpretable in themselves.

Linguistically-structured representations are by definition more interpretable than unstructured ones – thus Trend 1 (structure is back) could also be viewed as a move towards more transparent neural models. However, a core challenge with these, and other attempts to create transparent neural models is the tension between discreteness and continuousness. Neural networks are powerful because they can learn arbitrary continuous representations, but humans find discrete information – like language itself – easier to understand.

We might be concerned that imposing discreteness constraints on our neural models diminishes their expressive power – that interpretability comes at the price of effectiveness. However, for some types of discreteness, like sparsity, the opposite can be true. For example, sparsity-inducing regularization is known to improve rather than impair neural models, and sparsified word embeddings can be more effective than the original dense ones. In Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling, Gábor Berend demonstrates the effectiveness of sparse word embeddings for NER and POS-tagging, particularly in low-training-data settings. Though interpretability is not the focus of Berend’s paper, he kindly answered my questions on the subject and even wrote a follow-up blog post, which shows that some of the basis vectors in the sparse representation seem to correspond to human-understandable concepts. This is very cool, and raises the question: if we have high-performing word embeddings with interpretable dimensions, can we use them to build more complex neural systems that are also interpretable?

Closest concepts for several basis vectors.

Gábor Berend

For AI systems that compute answers to complicated questions, transparency is especially important if humans are to trust the answers. These systems should ideally produce a proof or derivation of the answer – for a semantic parsing question answering system, this might be the semantic parse itself, or a relevant excerpt from the knowledge base. For a system that solves mathematical problems, the proof should be a step-by-step natural language derivation of the final answer. This is exactly what Ling et al. provide in Program Induction for Rationale Generation: Learning to Solve and Explain Algebraic Word Problems. Rather than directly and uninterpretably producing the final answer, their system jointly learns to generate the underlying sequence of mathematical transformations, and the natural language solution that explains it.

Rationale and corresponding chain of mathematical computations to solve a mathematical word problem

Ling et al.

Looking forward

I’m unsure which type of interpretability – post hoc explainability or transparency – is the right way forward. Post hoc techniques tend to give restricted explanations that, while fascinating, but are often cryptic themselves. I think that more flexible explanation techniques, like the translation-based approach, hold a lot of potential – though they raise tough new questions about trust. Transparency, on the other hand, is attractive because interpretability should really be a design choice, not an afterthought. Though we are far from building neural systems that are transparent end-to-end, efforts to make small parts of the system transparent are hugely useful – note, for example, how useful the attention mechanism has been as a sanity check and debugging tool for developing attentional systems. Which leads us to Trend 4…

Trend 4: Attention

Widely acknowledged as a game-changer for the sequence-to-sequence model, the attention mechanism is quickly becoming a favorite technique, and it’s easy to see why. It can be used to bypass bottlenecks in information flow, it enables a key-value lookup function that can’t be achieved with feed-forward layers, and it provides some much-needed interpretability. The attention mechanism had an increased presence at ACL this year, with fifteen occurrences of “attention” in paper titles (an increase from nine the previous year).

More attention everywhere

The attention mechanism is the most interpretable and therefore most manipulable part of the sequence-to-sequence framework. Accordingly, researchers are finding success by designing increasingly complex attention models that aim to solve particular task-specific problems. This “mini-industry of model extensions” (as described by Alexander Rush in his NMT workshop keynote) was thriving at ACL 2017.

Three papers presented models for Question Answering that, in addition to the usual question-to-document attention, add document-to-question attention. Of these models (attention-over-attention, cross-attention and gated-attention reader), the third also incorporates multi-hop attention, which allows the model to iteratively attend to different sections before coming to an answer. This seems like a core ability, and the appendix of the paper contains several examples that demonstrate both the necessity and the effectiveness of multi-hop reasoning.

Attention visualizations for each iteration of computation

Over multiple iterations, attention settles on the correct answer. Dhingra et al.

Attention has also emerged as the standard way to weight and combine information from multiple, potentially multi-modal, sources. Libovicky et al. attend to both text and an image to translate a caption, Lin et al. attend to multi-lingual data to extract relations, and Kim et al. attend to the representations from an ensemble of domain experts to perform domain adaptation on a case-by-case basis. Attention is convenient in these cases because it offers a general way to obtain a fixed-size representation from an arbitrary number of sources.

Others find that applying attention at multiple granularities is useful for certain tasks. For example, grammatical error correction requires nested attention: word-level attention to detect word order errors, and character-level attention to detect spelling errors.

So is attention all you need?

The enthusiasm for increasingly complex, attentionattention mechanisms may seem to confirm recent bold claims that attention is all you need. However, at ACL I noticed several researchers deliver cautionary messages about the potential pitfalls or misapplications of attention.

For example, there are some scenarios in which attention doesn’t work as well as we might hope. Tan et al. argue that for abstractive document summarization, the attention distribution does not effectively model the saliency of source sentences. Instead, they find more success by using a pre-deep-learning extractive summarization algorithm (PageRank-based sentence ranking) to model saliency. This result serves as an important reminder that we should not throw away decades of accumulated NLP knowledge – though unfashionable, these techniques may provide the key to improving our neural systems.

Second, there may be some scenarios in which attention is redundant. Bollman et al. find that when they introduce an auxiliary task for multi-task learning, the addition of an attention mechanism becomes harmful rather than helpful. As explanation, they provide evidence that the auxiliary task enables the model to learn to focus attention, which makes the attention mechanism redundant. Though I don’t fully understand this interaction between attention and multi-task learning, we should take note of the phenomenon as it poses a potential pitfall for the development of future systems.

Lastly, there are some simpler tasks for which attention may be more than you need. Aharoni et al. argue that for morphological inflection generation, which typically requires focusing on just one character at a time, the standard “soft” attention is overkill – they find the simpler “hard” attention sufficient.

2D visualization of embeddings produced by hard and soft attention.

Hard attention produces more clearly-defined clusters than soft attention. Aharoni et al.

Looking forward

Although attention was originally conceived as a fix to the bottleneck problem in sequence-to-sequence NMT, it has turned out to be a much more fundamental and generally useful technique. By thinking about why attention is so popular, we might identify some of the current needs of the deep learning community – for example the need for interpretability, for long distance dependencies, and for dynamic structure. I hope that attention is just the first step towards achieving these things.

Though this is only the second ACL I’ve attended, I was really impressed by this year’s organizing committee, who did an amazing job of being transparent, listening to the community’s concerns, and proactively addressing them. This year’s conference featured an extensive open discussion of preprint servers and the submission process, as well as a strong emphasis on diversity, accessibility and ethics. In this era of very empirical-driven work, I was also glad to see multiple reminders that we should aspire to do good, hypothesis-driven science that is replicable and reproducible.

Just a few years after the deep learning tidal wave, the NLP community has reason to feel both excited and anxious – excited about where deep learning will lead next, and anxious about whether that’s the right direction. But I have confidence in this community to get the best out of both deep learning and NLP; to change with the times while retaining its collective wisdom. So, no need for hype nor fear. Deep learning is neither the ultimate solution nor the death of NLP.

Thanks to my advisor Chris Manning who read several drafts of this post, as well as the following people who gave me their opinions and/or answered my questions about their work: David Jurgens, Lucy Li, Gábor Berend, Yang Liu, Jiwei Tan.

What themes and trends did you observe at ACL 2017? Discuss in the comments.


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Stroke (cerebrovascular accident)

Until recently, it was thought that strokes were very rare in domestic pets. In the last few years, with the advance and increased availability of more specialist tests strokes are being recognised more often in pets. The thought of your pet suffering a stroke may be frightening - but you should not be alarmed - strokes are often not as debilitating in animals as they are in people. With appropriate care your pet may do very well.

Your questions answered

What is a stroke?

(1) Ischaemic stroke is caused by a sudden lack of blood supply to the brain and
(2) Haemorrhagic stroke (or bleeding within the brain) is caused by a burst blood vessel.

More than any other organ, the brain relies on a constant blood supply to bring oxygen and nutrients and to remove waste products.  If the blood supply to the brain fails brain function is severely disrupted (ischaemia) or parts of the brain destroyed (infarct) in a specific region of the brain fed by the affected artery.  The diseases causing ischaemic stroke can be broadly divided into those diseases causing narrowing of an artery (thrombosis) and diseases causing clogging of an artery by material coming from somewhere else in the body (embolism).

How do I know if my pet has had a stroke?

How will my vet know that my pet has had a stroke?

What causes strokes in cats?

Ischaemic strokes have been associated with many medical conditions in cats: kidney disease, heart disease, over-active thyroid glands, migrating worms (cuterebra), and high blood pressure (hypertension). Other less common causes of blockage of the blood vessels supplying the brain include clogging by a fragment of tumour, fat, parasites or spinal cartilage. Despite thorough investigations, an underlying cause is often not found. Haemorrhagic strokes can be seen with diseases that interfere with blood clotting (some rodent poisons (warfarin-like products), immune-mediated thrombocytopenia, and congenital clotting diseases), disease causing high blood pressure (kidney disease, heart disease, Cushings or thyroid disease), inflammation of the arteries (vasculitis) or abnormal development of the blood vessel in the brain. Other causes of bleeding in the brain include head trauma, bleeding from a brain tumour or from a tumour spreading to the brain.

Is there any treatment for stroke?

Will my pet get better?

Related topics


The Forgiveness Essay: Can You Say My sympathies?

May 14, 2019

The Forgiveness Essay: Can You Say My sympathies?

Every person can insult one other people, despite that he/she will not want to do this. It is well-known fact, that will some minor insults may be changed into the ones it will create a great deal of conflicts in between people including between the many years. The more thorough information you can receive in the documents on forgiveness, which are prospective to be purchased on our site. Some people quite possibly do not plan to understand, them to were not suitable and the causes of it will be shown within the forgiveness works. But it can be quite easy to affront someone, for the reason that, unfortunately, if we said a thing, it is unfeasible to change. Thanks to it, the actual fact, that the someone can say ‘Sorry’ shows significantly about this man or woman. If you wish to purchase the forgive and overlook the fact essay, you can use it below.

Everyone knows, the fact that the apologies is the best way for you to forget about the quarrels and to continue the welcoming relationships. Nonetheless sometimes, your only word ‘Sorry’ is not ample. It is is required to spend some time in order to beg around the forgiveness, in cases where, for example , this insult appeared to be very serious.

If you don’t do it, the owner even can won’t communicate with an individual, because he will keep in mind the situation, where you offended him/his. Some people may also academized cupon find the techniques how to avenge and because of the usb ports, you can be inside danger. To avoid these situations, you should believe that a lot in what you are doing and exactly what you are telling the other people. You should regard the other many people and realize, that you do not have got any directly to offend these folks.

Also, issue situation occurred, you should discover it and have about forgiveness. You should take action sincerely, if you are fictitious, the other many people will feel the idea and this basic fact can make this challenge only deeper. You should just think, how the other individuals feel on and try to understand the situation on the other party.

Because of this, there are some plans, which can help one to get the forgiveness of the other people and you should rely on them, when you realize, that you were not right.

‘Sorry’ – might be the first step to access the forgiveness

These types of few keywords and phrases will be a sufficient amount of only for they, if they, for example , took the car or the doll in the several other children with no permission. Sorry to say, for the parent people, a common this words that are will not be adequate. People should understand, which they made the mistake and should decide their actions. Also, they should understand the effects, which their particular actions already have caused. They will admit, it turned out their failing and to avert it at some point. Also, it is best to explain one other people, what are you wanting information about the forgiveness for, considering that the situation can be different and they can understand this in the drastically wrong way or simply just will not appreciate at all.

a few ways in the successful forgiveness

The forgiveness is the art work and it carries of the your five steps

  1. You should sincerely understand as well as accept your mistake.
  2. It is best to understand, exactly why exactly an individual did in this way, but not inside the other method.
  3. To show another people that you happen to be really suggesting about the forgiveness and you really need it.
  4. You must ask if it is possible to try something from the side to vary the situation.
  5. To know the point for view of the other person.

Do we really need to be honest?

It really is needed to be straightforward in just about everything, it will be the best selection, if there happens any fault. But there are some things like ‘strategic apologies’. The main fact is, you should lie, as a way not to affront the other folks. For example , that people tell the best quality friend, that her new dress really is awful. Or perhaps you cannot tell your boss, that he or she looks like this idiot obtained in this suit.

This forgiveness requires some time

Its needed to fully understand, that oftentimes, the forgiveness requires time and it is unachievable for the other individuals just to forget about your blunders. You even cannot presume, that this challenge can be sorted out immediately. Make sure you discuss the circumstance and ask, if you experience something you can to be executed from your component. If you cannot make a change, you should only wait, as it will be the best advice in this situation.

There is no any term for any apologies

It was needed to pardon at that time, once you understood, for you to were not appropriate. But also, you observe a lot of state of affairs, when the persons ask about the particular forgiveness a few weeks, months or just years. It is advisable to avoid such mistakes, but if you act like you made all of them, you should ask about the forgiveness. It does not matter the time it was: yesterday or a three years or so ago.

The causes of these situations

1 ) The pleasure

Sometimes, it really is difficult to say ‘Sorry’, because you think, that you are currently always best and do not just want to understand your personal mistakes.

2 . not The idea of the situation

You can think, that it really is needed to pardon only for the circumstance, when you are possibly not right. Many individuals are of course, that when they may not be right, it is very easy for these types of ask about the forgiveness. But once 2 folks are erroneous, it is very challenging to say ‘Sorry’, because you are certainly not understand, why you should do it, in the event the other person developed a lot of glitches too.

additional. The family

Moreover, a lot of the scenarios depend on the household, which you have. If it is definitely not common within your family apologizing for something very often in no way to accept the mistakes, it can be natural, that you’ll do all things in this way.

What you can do?

4. Adhere to the feelings of some other people

It is best to understand, what the other people can easily feel during these situations. Thanks to it, in case you respect his or her feelings, you must apologize.

quite a few. Do not delay

You should not wait for a long time to apologize. It absolutely was needed to do at that time, should the situation made an appearance. You should fully grasp, that the period can make the way it is more complicated.

6. You should be straightforward

You should show the other people, for you to understand the scenario and your really mistakes and can avoid them at some point.

Every person contains the right to make the mistake, because no-one is perfect. Because of it, we ought to understand the other individuals. Also, if we understand, that enables us to are not suitable, we should apologize for our steps. The simple single word ‘Sorry’ can change a lot in our life.

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Two ways to react on the Electron ‘close’ event

As you probably know, Electron has one main process and several renderer process for the browser windows. The main.ts file hosts the main process implementation. There, we create a new BrowserWindow instance, defining a minimal size, initial width, and height.

The use of show: false first and later-on makes the startup smoother.

The screen size is saved to a yaml file and read into a model class at start-up.

In the following, I will present both approaches I tried.

Solution 1: Renderer Process

The BrowserWindow emits events when an App Command is invoked. The ones we are interested in are ‘close’ and ‘resize’. The BrowserWindow instance is part of the main electron process. From the renderer process, we can access it via the remote interface.

By adding a listener on the resize event, the screen resolution is written to a file every time the application is resized – which is a bit of an overhead. What we actually want to achieve is that these values are written once, right when the application is to be closed.

The Electron API for Browser Window mentions a close event, but it seems this is done by the main process, not the renderer process. Listening on this event in the renderer process was not successful, the event was never triggered.

On application start up, we read in our configuration from the configuration file. The BrowserWindow’s size can be set using the setSize() method.

Solution 2: IPC between main and renderer process

The second approach is to use both the main and the renderer process. On the main process, the BrowserWindow listens on the close event. When it happens, it sends a message via webContents to the renderer process. It also prevents the application from being immediately closed by calling event.preventDefault().

The renderer process is always listening on IPC messages from the main process. The ipcRenderer module provides a few methods to send synchronous and asynchronous messages from the render (web page) to the main process. When it receives the app-close event notification, it saves the data, then sends the main process an IPC message (e.g. closed);

The main process has previously set a hook to listen to the renderer IPC messages (ipcMain.on), so when the closed message arrives, it finally closes the program (e.g. via app.quit()). The ipcMain module handles asynchronous and synchronous messages sent from a renderer process.

Calling app.quit() sends another close event to the BrowserWindow, so it will loop unless you prevent it!

Overall, I prefer the second solution as it feels cleaner and the file is only written once and not every time the application is resized. This is also the way I implemented it.


Cloning SharePoint List Security (Freeware Security Tool)

I have run up into a cloning issue on other occasions, quite recently actually, since the project I am currently slated for has a really complex scheme in order to control user access to our local SharePoint instance and its related objects, as such sometimes rudimentary tasks like making two lists have identical user sets can prove to be a pain in the ass, so it would help to provide an automated way to do such tasks. Since this is always coming up, particularly during the initial provisioning process.

What lead to its creation was I was building a task management system that I am using some helper lists for, just storing some basic data that is pulled in by some sister WebParts. I was creating, deleting, recreating the lists and it became very, very tedious to keep setting the permissions. Although I could have changed the inheritance of the parent and just relied on feeding permissions, this unfortunately did not work for my particular situation due to some interesting trimming components that rely on certain security attributes from the parent. To complicate matters further, with the initial content provisioning that followed needed to ensure that sub-items (SPListItem’s and SPFolder’s) would if the names matched clone the item(s) security as well.

To make a long story short, it had to be done manually, there was really no native way to tackle the issue. And manually hurts.
From a project type standpoint, what I needed was a tiny WinForms application that would allow me to take a baseline stamp of existing permission sets as they are currently were bound to an SPList object, then take that and apply it to a new SPList object with just a couple clicks instead of having to wade through the plethora of SharePoint pages I otherwise would have to go through. This shouldn’t imply that it couldn’t be done in a WebPart or some other medium, however this was the quickest method. I will most likely look into a conversion of it later.
So, the process flow that I was looking to solve was a relatively simple one.

1) Locate / select a pre-existing list as it exists in SharePoint. This list should have the appropriate permissions on it representative of the set you would like to clone.

2) Find the secondary list that has a malformed / not yet set permission set.

3) Ensure that the permissions that are provided in the secondary do indeed represent the set that you would like to clone.

4) Begin the cloning taking into account checks like whether both objects inherit from the parent, which would definitively not represent an actionable function (other checks on inheritance are performed as well).
5) During the cloning, iterate through all SPListItem / SPFolder objects that are found. If the name matches, clone the permissions of the item as well.

So, without further hesitation, the SharePoint List Security Cloner, which is a very simple application taking to view URL’s that coordinate to the baseline list as well as the target list. All you have to do is put these two parameters into the application, and then following execute the application, the tracing of the operations will be written to the TextBox, following the adjustments to the list security should be accessible from the web interface.

Firstly, the main interface of the application:

As you can see in the above image, you are afforded to inputs into the application. The first is the source URL, or the SPList View URL of the list that you would like to use as a baseline. The second TextBox is the destination URL, which represents the target for the cloning as explained previously.Following, I am going to choose two URL’s of two different lists, cloning my Tasks list security attributes to my Calendar list. This is what the security of them looks like currently.Firstly, the baseline list permission settings:

Secondly, my Calendar list permission settings:

We can see that the variation between the two lists are development Members, Robert Lyon, and Viewers. I am going to now use the SharePoint List Security Cloner, and place the AllItems.aspx URL into the appropriate slots.

Once the execution starts, you will see a progress bar at the bottom of the main form that will disappear again when the execution is complete:

You can track the operations progress in the “Cloning Operations” section as well that will inform you of the specific progress that the application is making.

Afterwards, when I look at the permissions for the Calendar, I see that the security attributes were successfully cloned over!

Anyways, it was written for fun and my own utility more than anything, so I really can’t guarantee its going to work. Read the software disclaimer on the main site before downloading please! If you do run into errors or have feature suggestions to enhance it (posting such things in the comments generally motivates me to) please do post in the comments. I think my next version is still going to be a windows application but I am going to add the ability to toggle between sites, lists, etc.
Download SharePoint List Security Cloner (the interface might have moved around a little bit from the above screenshots but the functionality is consistent).


Introduction to Thermodynamics

Introduction and Summary

The study of thermodynamics is the study of systems that are too large to understand by mechanics alone. For many years, thermodynamics was understood vaguely, and many of the results had been determined only experimentally. Some results posed great theoretical challenges to physicists, who offered many unsuccessful attempts at explaining the origins of the formulas.

With the advent of quantum mechanics came the explanations for the results. The mechanics of individual particles is still too complicated, however. For this reason, statistical physics plays a significant role in the basis of thermodynamics. Instead of worrying about the exact values of properties for each particle in a system, we look at the average values statistically over quantum probabilities. Even fundamental concepts like the energy of a system are derived as averages.

New concepts arise as we talk about large systems, such as entropy and temperature. Defining these carefully from quantum mechanics allows us to make sense of the "3 Laws of Thermodynamics".

There is great symmetry in the structure of thermodynamics. The six variables we look at repeatedly parallel each other in formulations of the energy. We can use a mathematical tool known as the Legendre Transform to posit alternate definitions of energy. This symmetry allows us to derive numerous relationships between the variables, and the multiple definitions of energy greatly simplify problem solving throughout all of thermodynamics.

We can form the Partition Function as a measure of the total weighted probabilities of the various states of a system, and relate this quantum counting result to the energy of a the system. The spectrum of blackbody radiation is derived directly from this counting. For systems in thermal and diffusive contact with a reservoir, the Gibbs Sum replaces the Partition Function.

With the few tools developed up to that point, the entire ideal gas problem can be solved, including the derivation of expressions for all of the interesting variables that describe the gas. In the non-classical regime, an ideal gas behaves quite differently depending on the nature of its constituents . A gas comprised of fermions exhibits a regime of total occupation and a regime of zero occupation, while a gas comprised of bosons can form an Einstein condensate by crowding into the ground orbital of the system.

Heat engines and other devices were the historical motivation for the development of thermodynamics as a science. The devices can be well explained using the framework already developed, and illustrative diagrams can be drawn to make plain the energy and entropy flow involved. Real engines undergo repeated cycles to achieve their purpose. We look at a simplified model known as the Carnot cycle, and discuss different processes and how they relate to the various energies defined.


Home Europe Malta

Malta has a nearly legendary quality to it that originates from its spooky undersea caverns, spectacular temples, and middle ages architecture. The streets here wind around towns and towns taking you previous churches, markets, and museums, and some of the earliest structures in the world can be discovered on this beautiful island. The country is actually an island chain that sits in the Mediterranean Sea and is close to both neighboring Sicily and Africa.

There are 3 main islands here in the form of Malta appropriate, Gozo and Comino, and whichever one you select to visit you can anticipate to be surrounded by azure seas and clear blue skies. Whatever you are searching for, among the islands is sure to provide and you can select from museums, fishing expedition, and diving opportunities, or just unwind and take pleasure in the cafes and dining establishments that generally serve fresh seafood plucked directly from the ocean.


SGMA’s Impact to Water Management

Supply and Demand

At its core, water economics relies on a market participant’s ability to move water and incentivize conservation practices. SGMA allows Groundwater Sustainability Agencies to create and enforce a GSP. The GSP will include new fees on groundwater pumping and restrictions on pumping based on the estimated capacity of the underlying groundwater basin. GSPs are designed to reach a “sustainable yield” for the basin and avoid six “undesirable results” summarized as the “significant and unreasonable” lowering of groundwater elevations, reduced groundwater storage, saltwater intrusion, water quality degradation, land subsidence, and the open-ended adverse effects on beneficial uses of interconnected surface water.

Supply and demand are foundational to water management. Historically, California allowed unrestricted groundwater pumping. SGMA will cap that, and in areas like the Central Valley where groundwater offered an alternative source to drought-reduced surface supplies, available pumped groundwater will plummet. The rules promulgated by the GSAs will create risks and opportunities for all industries in the GSA and the broader region.

Gaining and Losing

A primary goal in the age of SGMA is to maintain a balance between surface water and groundwater supplies to reach sustainable yield targets that are forthcoming in GSPs; you must balance the budget. However, many of the basins supporting crucial agricultural operations are in deficit. The solution: recharge.

Risk and Opportunity

Often the term water manager is associated with water, irrigation, and now groundwater agencies. In reality, any business that touches water in some way needs to incorporate water management into their strategic thinking. At the core of water management is water risk. As water supplies increase in volatility, understanding the water risk is essential to forecast risk for your operation. While humans are working on solutions like groundwater recharge and demand-side market structures to mitigate risk, nature has a wicked curve that can throw us all off balance, unless you have done your research. Identify your water risk early, seek solutions to mitigate that risk, and take advantage of the strategic opportunities to position yourself for the future.

AQUAOSO Technologies provides a research platform capable of delivering actionable data to assist you in identifying, understanding, monitoring, and mitigating your water risk.


Walking While Texting

Texting while walking

Have you heard the statistics about the increase in texting deaths while walking?  People have walked in front of cars, walked off piers and run into walls because they are not watching where they are going.  While I hope you are not texting and walking, I wonder if this is a good analogy for what is happening at your business?

Is your head down, focused on the past or present?  Do you often find yourself getting mired in the detail and crises of the day?  How often are you looking ahead, scanning the horizon for what’s new and where your company should be heading?  The best leaders schedule time in their week for strategic thinking and long term planning.  They ensure they are making time to work on the most important things, rather than the urgent.

So the next time you see someone walking with their head down, distracted by their phone, use that as a reminder to schedule time in your week to focus on the future of your business.

Time Management

*Time Alone*

Do you often find yourself saying you are “too busy” or that there “just aren’t enough hours in the day”?  I often speak with people who tell me that time management is a challenge for them.  A wise Vistage speaker once suggested that we should call it “priority management” rather than time management.  I agree since we can all make choices as to how to spend our time.

The fact is that each of us has the same number of hours in each day.  Some people seem to be able to find that perfect balance of time spent on various aspects of their lives and business.  Others struggle to find time for important but not urgent activities.  Have you talked to a leader recently who says they don’t have time to work out?  Or to take a day off?  Or to work “on” their business rather than “in” their business?  What they are actually saying is that those things are not a high enough priority right now.  If they were, they would be taking action to make time for them.

If you ever crammed for exams by pulling an all-nighter, you showed how you can shift your schedule to make time for high-priority activities.  Grades were more important than sleep that night.  Did you ever work so hard on a project that you realized you forgot to eat?  The work was more important than your awareness of hunger.  If you can put things higher on the priority list than sleep and food (which are pretty important!), then I know you can make time for those other things if you really want to.

Why not identify what you really want and then manage your time according to those priorities?

Emotional Intelligence

Conversation with a rescued owl

You may be smart, but are you emotionally intelligent?

Failure to Respond

Are you someone who fails to respond?  Not to cold-calls or blind solicitations, but rather to someone you contacted first?  I am curious what is causing you to behave in that manner?  Do you realize that when you reach out to someone else, they must spend time and energy to respond?  Your own lack of responsiveness when they reply to you creates more work for that person, who wonders if their message was actually delivered or tries another way to reach you, thus expending even more time and energy.  If you contact someone and then change your mind, it would seem to be common courtesy to let them know.  You could send a quick note or leave a voice mail message, anything that would enable the other person to take you off of their list of things to do.

Vistage is not for everyone, so I know that many of the people I speak with will not be a good fit for our organization.  However, I want to help people and will always try to respond in a timely manner when someone reaches out to me.  However, when they fail to respond to my offer to answer any of their questions or provide them with information, it becomes very frustrating.  I am left alternating between irritation, concern for their well-being, and curiosity as to why they reached out to me in the first place.

If you read this and realize you have been unresponsive to others, it’s not too late to change your behavior.  Just let them know you resolved the situation and no longer need their assistance.  Display some no-longer-so-common courtesy!

Why Do So Many Executives Work Without Assistants?

Sometimes, there shows a helping hand where you don\'t expect it - be grateful

Why do so many executives work without assistants?  Years ago, it was common for all executives to have a dedicated executive assistant to help them with scheduling, typing, travel arrangements and other tasks.  That enabled the executive to focus on the most important things, such as creating and executing company strategy.

During the economic downturn a few years ago, overhead cuts were made, and many administrative positions were eliminated.   Additionally, automation and computer literacy increased, with many executives doing much of their work from their phone or tablet.  As a result, fewer executives have assistants.

Now that the economy has improved, and business is on an upswing, why are people still not utilizing executive assistants?  When I ask that question, I am often told things such as, “It’s easier and faster to do everything myself.”  Or, “That is a luxury I can’t afford right now.”

Yet I see those same executives working very long hours and still not getting important things done.  They are not taking the time to think strategically because they are too busy doing all of the small stuff.  Their company likely will not be able to grow as efficiently and effectively because they have become the bottleneck for their business.  If they are already working long hours, they cannot take on any additional work.  Most importantly, they may be missing major market shifts that could either provide terrific opportunities or significant risks to their business.

My Vistage members who have hired executive assistants have been able to effectively train and delegate much of the busywork they were previously handling themselves.  Trained administrative personnel can often perform those same tasks in less time and with fewer mistakes.   They can create efficient systems and processes, streamlining operations, and reducing wasted time within the organization.  This increased efficiency often more than covers the cost of the added overhead.

Those executives now have time in their day to step back and evaluate market trends, and create and execute the appropriate strategies for their business.  Most importantly, they can scale their business and grow at a much more rapid pace than ever before, allowing the executive to achieve their dreams.

Imperfect action beats perfect inaction every time

  1. Delegate those tasks to someone who works for me

Stretch Goals

Miss Charley Leaping for Treats

What are your stretch goals for 2016? Make sure they are “SMART”: Specific, Measurable, Attainable, Results-Oriented, and Time-Specific. Then write them down, share them with others, and look at them daily or weekly.  If your goals can be broken down into milestones and you can establish target dates for those milestones, you have just increased your chance of success.

Along the way, if you are not achieving a particular goal, figure out why. Is it a limiting belief that is holding you back? If so, work on overcoming that limiting belief. Is it procrastination? Then make a point to tackle that goal first thing in the morning before doing anything else. Or establish mini-rewards for achieving milestones toward that goal. For example, once I have achieved “X” today, I’ll take a break and walk around the office, or get a latte, or go out to lunch today rather than eating at my desk.

If you are particularly challenged with a goal and you can’t figure out a strategy to overcome a roadblock, ask for help. Others might be able to brainstorm alternative approaches that would enable you to achieve that goal.

Lastly, sometimes outside forces make a goal no longer relevant or attainable. If you are a taxi company and your original goal was to continue to grow your business as you have done in the past, and now Uber has come into your area, your original strategy may not be working. Rather than focusing on your goal of doing more of what you did in the past, it’s likely you will need to revise your strategy to compete with Uber. If goals become impossible due to external factors, it’s fine to replace them with other goals that will help you to achieve your long-term vision.

Stay focused, and make 2016 a terrific year!

Gratitude Journaling

Wilson Lam {WLQ} / Foter.com / CC BY-NC-ND

At Thanksgiving, we are reminded to give thanks for what we have. However the remaining weeks of the year are often a stressful time for people and it’s easy to feel like you are in a slump or down in the dumps. If you are truly depressed, please get professional help. If you are just going through normal ebbs and flows in life and find yourself down in the dumps for more than a couple of weeks, I’d suggest that you try gratitude journaling.

What is a gratitude journal? It’s a notebook, diary or journal where you can jot down thoughts of gratitude each day. When you are feeling great, it is simple to think of things for which you are grateful. However when you are in pain (mentally or physically), worried, angry, or fearful, you don’t naturally think of appreciation or gratitude. Instead, you focus on the negative, and that negativity feeds on itself. That cycle can be hard to break. One way to break it is by forcing yourself to find something to appreciate each day. You can start by writing down all of the things that normally come to mind, such as family, friends, housing, etc. Then you should try to think of something new to add to the list each and every day.

It’s ok to start small. I’ve had someone tell me that all they could identify was that their car did not break down as they drove to work that day. Everything else that happened that day was awful. So if that’s the only thing they could come up with that day, it’s a start. However, I would suggest changing the wording to be more positive. In that example, it would be better to write, “I am grateful my car got me safely to work today.” Focus on making the journal a place for positive, grateful thoughts.

What typically happens after a week or so of gratitude journaling is that you become motivated to find more things you can appreciate, and therefore you start to see things in a different light. You’ll find yourself feeling better and more positive about everything, gradually leaving those dumps behind!

Please be aware, that sometimes you will have a truly awful day. On that day, it may be difficult to come up with anything new to write in your journal. On those days, I suggest you read back through your previous gratitude postings, and you will be amazed how far you have come. You may even be able to identify something new to write for that bad day!

Happy journaling…

Trust and Connectedness

Story Blog man hugging tiger

I had the pleasure last week of training new Vistage Chairs through our 6 day “boot camp”. It’s always fun for me to bring a group of strangers together and, in just a few days, create a tight-knit, bonded group of people. We do that intentionally to show them how quickly they should be able to bond their new Vistage groups once they are established, since creating an environment of confidentiality and trust is critical to the success of a new Vistage group. When people are truly connected on an emotional, caring level, they are willing to go above and beyond the call of duty to help one another.

Of course, Vistage is not the only environment where that works. Our military branches also do a great job of connecting people emotionally to one another, which is crucial when their lives are on the line. Survivors of trauma are often also connected on a deep level with one another. Even kids attending summer camp away from home also can create close friendships in a very short time. Perhaps you have experienced this type of connectedness with others. Isn’t it a terrific feeling?

What could that type of bonding and closeness do for your business? What if your employees truly cared for one another, and went above and beyond the call of duty to help one another succeed? What if you were able to create a culture of trust and camaraderie? Not only could your profits increase, you would also likely attract the best new employees. In this competitive marketplace, that would be a valuable differentiator. Why not give it a try?

Are We There Yet?

Entering Hyperspace
Are We There Yet?Éole / Foter / CC BY-NC-SA

“Are we there yet?” How many times have you heard those words in a car or on a plane? Of course, the most common response to that question is, “Not yet!” For little kids who have no concept of time, that’s probably an appropriate response. For older kids, it may be better to provide more information and give them perspective on how much time has passed, and how much longer you expect to be on the road so they can begin to better understand the concept of time. Hopefully, as a result, they will be more comfortable and feel the need to ask, “Are we there yet?” a little less frequently.

What about your business? Are your employees effectively asking you (or thinking), “Are we there yet?” Do they have a clue where you are in the process of achieving your goals and your vision for the future? Are they just along for the ride, impatiently wondering if you are ever going to reach the destination or even if you are on the right road? Or have you effectively and clearly communicated your vision and goals, and kept them informed on your progress? Consider how sharing more information with all levels of your organization might enable your employees to be more comfortable and better able to help you achieve your vision.

By the way, your goals and vision may change along the way. Enjoy the journey and do not hesitate to add onto the trip and pick the next destination and vision for the future. Share it with your employees to help them enjoy the ride!