unstructuredio/SCORE-Bench · Datasets at Hugging Face

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Principal Investigator: Mario Damiano (Renyu Hu is Co-PI)
Program: James Webb Space Telescope Cycle 1 Guest Observers
Funding Period: 2022 – 2024
Total Funding: $226,553
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A Search for Signatures of Volcanism and Geodynamics on the Hot Rocky Exoplanet LHS 3844b
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Principal Investigator: Laura Kreidberg (Renyu Hu is Co-PI)
Program: James Webb Space Telescope Cycle 1 Guest Observers
Funding Period: 2022 – 2024
Total Funding: $176,322
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Thermal Structure, Chemistry, and Observational Signatures of Cold Exoplanet Atmospheres
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Principal Investigator: Renyu Hu
Program: NASA Exoplanets Research Program
Funding Period: 2018 – 2022
Total Funding: $ 458,552
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Constraining Early Mars’s Atmosphere and Habitability with Isotopic Measurements
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Principal Investigator: Renyu Hu
Program: NASA Habitable Worlds
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Page 4 of 23
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Extending vehicle and fleet lifespan: Bird case study
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Scooters need to withstand frequent use, occasionally harsh weather conditions, and prevent tampering. Bird, the first company to offer shared electric scooters, has taken a number of steps to improve fleet durability and retention.


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DURABILITY: CUSTOM DESIGN AND REGULAR MAINTENANCE
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Bird invested in R&D to internally design its own e-scooters
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(Bird Zero, Bird One, and Bird Two) to improve on the consumer models used in earlier operations. The improvements included:
Custom battery with battery management system;
A frame more adapted to a shared used, with reinforced parts;
Long-lasting tires with flat protection;
Tamper-resistant components (i.e., no exposed cables);
A regenerative front brake and a rear drum brake with no electronic failure vulnerability.


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Regular maintenance also contributes to a longer usable life.
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Investment in local service centers and streamlined maintenance processes allowed for a reduction in the proportion of Bird Zero fleet damaged from 40% to 12%. Key features that contributed to this improvement include:
Staff presence on street, in-app reporting, and sensors that alert to maintenance needs;
Regular maintenance performed by in-house mechanics;
A stock of spare parts in service centers, with part reuse from retired vehicles;
Weather analytics to remove scooters in case of extreme weather.


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VEHICLE RETENTION
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The proprietary design in itself prevents risks from hacking and resale for parts. In addition, specific design developments are made to enhance retention: for instance installation of a superior GPS system, sensors, and algorithms that detect suspicious movement have improved retention of the Bird fleet to close to 90% retention after 6 months.
In the future, retention is expected to increase even more as the Bird proprietary models are becoming more numerous in the fleet: between September 2018 and July 2019, the proportion of consumer models went from 98% to 25% of the worldwide fleet, the fleet being now composed of 57% of Bird Zero, 19% of Bird One, and Bird Twos beginning to be deployed in Summer 2019.
There is wide variation among providers. Establishing an e-scooter business that is sustainable requires investment in vehicle R&D, technology, and personnel. It can be assumed that providers who have not made these investments have an environmental impact that is moderately to significantly higher than those companies who have.
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roughly two months after the survey was completed; participants were reminded how they had responded to particular questions and asked to elaborate, with follow-up questions aiming to gain more insight to the contexts and experiences their initial survey responses could only allude to. We close the results section with a brief walkthrough of 5 semi-structured interviews, as these interviews in conjunction with the survey results helped us determine what we believe to be the most useful recommendations for a sustained remote/hybrid approach to game development.
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Analysis
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With regard to analyzing our survey data, we took a mixed-methods approach, as we wanted to see both patterns from the quantitative and qualitative data and how they worked together to craft a fuller picture of varied remote work contexts in which participants were working. In addition to the relevant statistical tests, we also performed word frequency analysis and sentiment analysis on the responses to the first question of the survey, quantifying some of our qualitative results in order to see patterns standard qualitative methods might otherwise miss, though we performed the sentiment analysis by hand rather than using software. We began this process using a grounded theory approach by categorizing responses to our first qualitative survey question above as either positive, negative, or neutral, but soon added a mixed and undetermined category, as some responses such as “half down/half up” appeared both positive and negative, rather than neutral, and others such as “busy” or “intense” were clearly not neutral, but also clearly not positive or negative. Three researchers coded the responses individually and then the team compared results to test for reliability; our codes were the same in 92% of cases, and we then had a collaborative discussion to finalize the remaining 8%. In most cases, our coding differences were between the neutral and undetermined category, as there was often overlap or a case could be made for either interpretation more readily than for the other category combinations. The following table provides an example section of this process:
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Table 1. Sample Sentiment Coding
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Response Positive Neutral Negative Mixed Undetermined
Fine X
Prisoned X
Okay X
Good X
Quieter X
Up & Down X
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In our coding of the qualitative analysis, we categorized responses to each survey question based on common themes we noted while reading responses. For the second question
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Principal Investigator: Mario Damiano (Renyu Hu is Co-PI)

Program: James Webb Space Telescope Cycle 1 Guest Observers

Funding Period: 2022 – 2024

Total Funding: $226,553

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A Search for Signatures of Volcanism and Geodynamics on the Hot Rocky Exoplanet LHS 3844b

--------------------------------------------------- Unstructured Sub-Title End

Principal Investigator: Laura Kreidberg (Renyu Hu is Co-PI)

Program: James Webb Space Telescope Cycle 1 Guest Observers

Funding Period: 2022 – 2024

Total Funding: $176,322

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Thermal Structure, Chemistry, and Observational Signatures of Cold Exoplanet Atmospheres

--------------------------------------------------- Unstructured Sub-Title End

Principal Investigator: Renyu Hu

Program: NASA Exoplanets Research Program

Funding Period: 2018 – 2022

Total Funding: $ 458,552

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Constraining Early Mars’s Atmosphere and Habitability with Isotopic Measurements

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Principal Investigator: Renyu Hu

Program: NASA Habitable Worlds

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Page 4 of 23

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Extending vehicle and fleet lifespan: Bird case study

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Scooters need to withstand frequent use, occasionally harsh weather conditions, and prevent tampering. Bird, the first company to offer shared electric scooters, has taken a number of steps to improve fleet durability and retention.

--------------------------------------------------- Unstructured Sub-Title Begin

DURABILITY: CUSTOM DESIGN AND REGULAR MAINTENANCE

--------------------------------------------------- Unstructured Sub-Title End

--------------------------------------------------- Unstructured Sub-Title Begin

Bird invested in R&D to internally design its own e-scooters

--------------------------------------------------- Unstructured Sub-Title End

(Bird Zero, Bird One, and Bird Two) to improve on the consumer models used in earlier operations. The improvements included:

Custom battery with battery management system;

A frame more adapted to a shared used, with reinforced parts;

Long-lasting tires with flat protection;

Tamper-resistant components (i.e., no exposed cables);

A regenerative front brake and a rear drum brake with no electronic failure vulnerability.

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Regular maintenance also contributes to a longer usable life.

--------------------------------------------------- Unstructured Sub-Title End

Investment in local service centers and streamlined maintenance processes allowed for a reduction in the proportion of Bird Zero fleet damaged from 40% to 12%. Key features that contributed to this improvement include:

Staff presence on street, in-app reporting, and sensors that alert to maintenance needs;

Regular maintenance performed by in-house mechanics;

A stock of spare parts in service centers, with part reuse from retired vehicles;

Weather analytics to remove scooters in case of extreme weather.

--------------------------------------------------- Unstructured Sub-Title Begin

VEHICLE RETENTION

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The proprietary design in itself prevents risks from hacking and resale for parts. In addition, specific design developments are made to enhance retention: for instance installation of a superior GPS system, sensors, and algorithms that detect suspicious movement have improved retention of the Bird fleet to close to 90% retention after 6 months.

In the future, retention is expected to increase even more as the Bird proprietary models are becoming more numerous in the fleet: between September 2018 and July 2019, the proportion of consumer models went from 98% to 25% of the worldwide fleet, the fleet being now composed of 57% of Bird Zero, 19% of Bird One, and Bird Twos beginning to be deployed in Summer 2019.

There is wide variation among providers. Establishing an e-scooter business that is sustainable requires investment in vehicle R&D, technology, and personnel. It can be assumed that providers who have not made these investments have an environmental impact that is moderately to significantly higher than those companies who have.

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19

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3

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roughly two months after the survey was completed; participants were reminded how they had responded to particular questions and asked to elaborate, with follow-up questions aiming to gain more insight to the contexts and experiences their initial survey responses could only allude to. We close the results section with a brief walkthrough of 5 semi-structured interviews, as these interviews in conjunction with the survey results helped us determine what we believe to be the most useful recommendations for a sustained remote/hybrid approach to game development.

--------------------------------------------------- Unstructured Sub-Title Begin

Analysis

--------------------------------------------------- Unstructured Sub-Title End

With regard to analyzing our survey data, we took a mixed-methods approach, as we wanted to see both patterns from the quantitative and qualitative data and how they worked together to craft a fuller picture of varied remote work contexts in which participants were working. In addition to the relevant statistical tests, we also performed word frequency analysis and sentiment analysis on the responses to the first question of the survey, quantifying some of our qualitative results in order to see patterns standard qualitative methods might otherwise miss, though we performed the sentiment analysis by hand rather than using software. We began this process using a grounded theory approach by categorizing responses to our first qualitative survey question above as either positive, negative, or neutral, but soon added a mixed and undetermined category, as some responses such as “half down/half up” appeared both positive and negative, rather than neutral, and others such as “busy” or “intense” were clearly not neutral, but also clearly not positive or negative. Three researchers coded the responses individually and then the team compared results to test for reliability; our codes were the same in 92% of cases, and we then had a collaborative discussion to finalize the remaining 8%. In most cases, our coding differences were between the neutral and undetermined category, as there was often overlap or a case could be made for either interpretation more readily than for the other category combinations. The following table provides an example section of this process:

--------------------------------------------------- Unstructured Caption Begin

Table 1. Sample Sentiment Coding

--------------------------------------------------- Unstructured Caption End

--------------------------------------------------- Unstructured Table Begin

Response Positive Neutral Negative Mixed Undetermined

Fine X

Prisoned X

Okay X

Good X

Quieter X

Up & Down X

--------------------------------------------------- Unstructured Table End

In our coding of the qualitative analysis, we categorized responses to each survey question based on common themes we noted while reading responses. For the second question

--------------------------------------------------- Unstructured Plain Text Format 1.0.4

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4

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