Towards Data-Driven Policymaking for the Urban Heat Transition in The Netherlands: Barriers to the Collection and Use of Data

2020 ◽  
pp. 361-373
Author(s):  
Devin Diran ◽  
Anne Fleur van Veenstra
Keyword(s):  
The Netherlands ◽  
Data Driven ◽  
Use Of Data ◽  
Urban Heat ◽  
Heat Transition

scholarly journals On the Experimental, Numerical and Data-Driven Methods to Study Urban Flows

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1310
Author(s):  
Pablo Torres ◽  
Soledad Le Clainche ◽  
Ricardo Vinuesa
Keyword(s):  
Physical Phenomenon ◽  
Urban Pollution ◽  
Pollutant Dispersion ◽  
Urban Environments ◽  
Machine Learning Algorithms ◽  
Data Driven ◽  
Thermal Fields ◽  
Use Of Data ◽  
Sustainability Challenges ◽  
New Research

Understanding the flow in urban environments is an increasingly relevant problem due to its significant impact on air quality and thermal effects in cities worldwide. In this review we provide an overview of efforts based on experiments and simulations to gain insight into this complex physical phenomenon. We highlight the relevance of coherent structures in urban flows, which are responsible for the pollutant-dispersion and thermal fields in the city. We also suggest a more widespread use of data-driven methods to characterize flow structures as a way to further understand the dynamics of urban flows, with the aim of tackling the important sustainability challenges associated with them. Artificial intelligence and urban flows should be combined into a new research line, where classical data-driven tools and machine-learning algorithms can shed light on the physical mechanisms associated with urban pollution.

scholarly journals A Physical Organic Approach to Tuning Reagents for Selective and Stable Methionine Bioconjugation

2019 ◽  
Author(s):  
Alec Christian ◽  
Shang Jia ◽  
Patricia Zhang ◽  
Arismel Tena Meza ◽  
Matthew S. Sigman ◽  
...  
Keyword(s):  
Structural Features ◽  
Data Driven ◽  
Live Cells ◽  
Design And Synthesis ◽  
Use Of Data ◽  
Physical Organic ◽  
Driving Stability ◽  
Peptide Stapling ◽  
Insight Into ◽  
Unique Chemical

We report a data-driven, physical organic approach to the development of new methionine-selective bioconjugation reagents with tunable adduct stabilities. Statistical modeling of structural features described by intrinsic physical organic parameters was applied to the development of a predictive model and to gain insight into features driving stability of adducts formed from the chemoselective coupling of oxaziridine and methionine thioether partners through Redox Activated Chemical Tagging (ReACT). From these analyses, a correlation between sulfimide stabilities and sulfimide  (C=O) stretching frequencies was revealed. We ex-ploited the rational gains in adduct stability exposed by this analysis to achieve the design and synthesis of a bis-oxaziridine reagent for peptide stapling. Indeed, we observed that a macrocyclic peptide formed by ReACT stapling at methionine exhibited improved uptake into live cells compared to an unstapled congener, highlighting the potential utility of this unique chemical tool for thioether modification. This work provides a template for the broader use of data-driven approaches to bioconjugation chemistry and other chemical biology applications.

scholarly journals Analysis of Decision Making Process in Moneyball: The Art of Winning an Unfair Game

The Winners ◽  
2015 ◽  
Vol 16 (1) ◽  
pp. 57
Author(s):  
Mochamad Sandy Triady ◽  
Ami Fitri Utami
Keyword(s):  
Decision Making ◽  
Excellent Result ◽  
Data Driven ◽  
Decision Making Process ◽  
Data Driven Decision Making ◽  
General Manager ◽  
Use Of Data ◽  
Bottom Position ◽  
Using Data ◽  
Baseball Team

Billy Beanes’s success in using data-driven decision making in baseball industry is wonderfully written by Michael Lewis in Moneyball. As a general manager in baseball team that were in the bottom position of the league from the financial side to acquire the players, Beane, along with his partner, explored the use of data in choosing the team’s player. They figured out how to determine the worth of every player.The process was not smooth, due to the condition of baseball industry that was not common with using advanced statistic in acquiring   players. Many teams still use the old paradigm that rely on experts’ judgments, intuition, or experience in decision making process. Moneyball approached that using data-driven decision making gave excellent result for Beane’s team. The team won 20 gamessequently in the 2002 season and also spent the lowest cost per win than other teams.This paper attempts to review the principles of Moneyball – The Art of Winning an Unfair Game as a process of decision making and gives what we can learn from the story in order to win the games, the unfair games.

scholarly journals A data-driven approach to the semantics of iconicity in American Sign Language and English

2020 ◽  
Vol 12 (1) ◽  
pp. 182-202 ◽  
Author(s):  
BILL THOMPSON ◽  
MARCUS PERLMAN ◽  
GARY LUPYAN ◽  
ZED SEVCIKOVA SEHYR ◽  
KAREN EMMOREY
Keyword(s):  
American Sign Language ◽  
Sign Language ◽  
Negative Relationship ◽  
Semantic Space ◽  
Data Driven ◽  
American Sign ◽  
Use Of Data ◽  
Text Corpora ◽  
Data Driven Approach ◽  
Iconic Signs

abstractA growing body of research shows that both signed and spoken languages display regular patterns of iconicity in their vocabularies. We compared iconicity in the lexicons of American Sign Language (ASL) and English by combining previously collected ratings of ASL signs (Caselli, Sevcikova Sehyr, Cohen-Goldberg, & Emmorey, 2017) and English words (Winter, Perlman, Perry, & Lupyan, 2017) with the use of data-driven semantic vectors derived from English. Our analyses show that models of spoken language lexical semantics drawn from large text corpora can be useful for predicting the iconicity of signs as well as words. Compared to English, ASL has a greater number of regions of semantic space with concentrations of highly iconic vocabulary. There was an overall negative relationship between semantic density and the iconicity of both English words and ASL signs. This negative relationship disappeared for highly iconic signs, suggesting that iconic forms may be more easily discriminable in ASL than in English. Our findings contribute to an increasingly detailed picture of how iconicity is distributed across different languages.

scholarly journals Data-Driven Campaigning in the 2015 United Kingdom General Election

2017 ◽  
Vol 22 (3) ◽  
pp. 294-313 ◽  
Author(s):  
Nick Anstead
Keyword(s):  
United Kingdom ◽  
The United States ◽  
General Election ◽  
Data Driven ◽  
British Politics ◽  
Use Of Data ◽  
The Uk ◽  
Depth Interviews

While we know something of data-driven campaigning practices in the United States, we know much less about the role of data in other national contexts. The 2015 United Kingdom General Election offers an important case study of how such practices are evolving and being deployed in a different setting. This article draws on thirty-one in-depth interviews with political practitioners involved in the use of data for six major UK parties and electoral regulators. These interviews are employed to explore the perceived importance of data in contemporary British campaigns, to understand the data-based campaign techniques being used by UK parties, and to assess how data-driven practices are interacting with the preexisting institutional context of British politics. Going beyond the specifics of the UK case, this study raises questions about the comparative, theoretical, and normative dimensions of data-driven politics.

Guiding teaching with assessments: high school chemistry teachers’ use of data-driven inquiry

2015 ◽  
Vol 16 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Jordan Harshman ◽  
Ellen Yezierski
Keyword(s):  
High School ◽  
Subject Area ◽  
Data Driven ◽  
Structured Interviews ◽  
High School Chemistry ◽  
Pedagogical Strategies ◽  
Chemistry Teachers ◽  
Classroom Assessments ◽  
Use Of Data ◽  
Specificity Of Learning

Data-driven inquiry (DDI) is the process by which teachers design and implement classroom assessments and use student results to inform/adjust teaching. Although much has been written about DDI, few details exist about how teachers conduct this process on a day-to-day basis in any specific subject area, let alone chemistry. Nineteen high school chemistry teachers participated in semi-structured interviews regarding how they used assessments to inform teaching. Results are reported for each step in the DDI process. Goals – there was a lack in specificity of learning and instructional goals and goals stated were not conducive to informing instruction. Evidence – at least once, all teachers determined student learning based solely on scores and/or subscores, suggesting an over-reliance on these measures. Conclusions – many teachers claimed that students either did or did not “understand” a topic, but the teachers did not adequately describe what this means. Actions – very few teachers listed a specific action as a result of analyzing student data, while the majority gave multiple broad pedagogical strategies to address content deficiencies. The results of this study show the limitations of teachers' DDI practices and inform how professional development on DDI should have a finer grain size and be based in disciplinary content.

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