scholarly journals Precise quantification of behavioral individuality from 80 million decisions across 183,000 flies

2021 ◽  
Author(s):  
Benjamin L de Bivort ◽  
Seaan M Buchanan ◽  
Kyobi J Skutt-Kakaria ◽  
Erika Gajda ◽  
Chelsea J O'Leary ◽  
...  
Keyword(s):  
Large Data ◽  
Behavioral Variability ◽  
Biological Mechanisms ◽  
Behavioral Experiments ◽  
Behavioral Measures ◽  
Data Set ◽  
Precise Quantification ◽  
Heterogametic Sex ◽  
High Throughput Experiments ◽  
The Relationship

Individual animals behave differently from each other. This variability is a component of personality and arises even when genetics and environment are held constant. Discovering the biological mechanisms underlying behavioral variability depends on efficiently measuring individual behavioral bias, a requirement that is facilitated by automated, high-throughput experiments. We compiled a large data set of individual locomotor behavior measures, acquired from over 183,000 fruit flies walking in Y-shaped mazes. With this data set we first conducted a "computational ethology natural history" study to quantify the distribution of individual behavioral biases with unprecedented precision and examine correlations between behavioral measures with high power. We discovered a slight, but highly significant, left-bias in spontaneous locomotor decision-making. We then used the data to evaluate standing hypotheses about biological mechanisms affecting behavioral variability, specifically: the neuromodulator serotonin and its precursor transporter, heterogametic sex, and temperature. We found a variety of significant effects associated with each of these mechanisms that were behavior-dependent. This indicates that the relationship between biological mechanisms and behavioral variability may be highly context dependent. Going forward, automation of behavioral experiments will likely be essential in teasing out the complex causality of individuality.

scholarly journals Exploring the relationship between avalanche hazard and large-scale terrain choices at a helicopter skiing operation – Insight from run list ratings

2019 ◽  
Author(s):  
Reto Sterchi ◽  
Pascal Haegeli ◽  
Patrick Mair
Keyword(s):  
Large Scale ◽  
Selection Process ◽  
Decision Aids ◽  
Large Data ◽  
Limited Attention ◽  
Data Set ◽  
Linear Mixed Effects Model ◽  
Linear Mixed Effects ◽  
Avalanche Hazard ◽  
The Relationship

Abstract. While guides in mechanized skiing operations use a well-established terrain selection process to limit their exposure to avalanche hazard and keep the residual risk at an acceptable level, the relationship between the open/closed status of runs and environmental factors is complex and has so far only received limited attention from research. Using a large data set of over 25 000 operational run list codes from a mechanized skiing operation, we applied a general linear mixed effects model to explore the relationship between acceptable skiing terrain (i.e., status open) and avalanche hazard conditions. Our results show that the magnitude of the effect of avalanche hazard on run list codes depends on the type of terrain that is being assessed by the guiding team. Ski runs in severe alpine terrain with steep lines through large avalanche slopes are much more susceptible to increases in avalanche hazard than less severe terrain. However, our results also highlight the strong effects of recent skiing on the run coding and thus the importance of prior first-hand experience. Expressing these relationships numerically provides an important step towards the development of meaningful decision aids, which can assist commercial operations to manage their avalanche risk more effectively and efficiently.

scholarly journals Chikungunya Virus RNA and Antibody Testing at a National Reference Laboratory since the Emergence of Chikungunya Virus in the Americas

2014 ◽  
Vol 22 (3) ◽  
pp. 291-297 ◽  
Author(s):  
Harry E. Prince ◽  
Brent L. Seaton ◽  
Jose L. Matud ◽  
Hollis J. Batterman
Keyword(s):  
Chikungunya Virus ◽  
Large Data ◽  
Nucleic Acid Amplification ◽  
Antibody Detection ◽  
Reference Laboratory ◽  
Antibody Testing ◽  
Data Set ◽  
Rna Detection ◽  
Antibody Titers ◽  
The Relationship

ABSTRACTSince first reported in the Americas in December 2013, chikungunya virus (CHIKV) infections have been documented in travelers returning from the Caribbean, with many cases identified by CHIKV antibody and/or RNA testing at our laboratory. We used our large data set to characterize the relationship between antibody titers and RNA detection and to estimate IgM persistence. CHIKV RNA was measured by nucleic acid amplification and CHIKV IgG/IgM by indirect immunofluorescence. Of the 1,306 samples submitted for RNA testing in January through September 2014, 393 (30%) were positive; for 166 RNA-positive samples, CHIKV antibody testing was also ordered, and 84% were antibody negative. Of the 6,971 sera submitted for antibody testing in January through September 2014, 1,811 (26%) were IgM positive; 1,461 IgM positives (81%) were also IgG positive. The relationship between the CHIKV antibody titers and RNA detection was evaluated using 376 IgM-positive samples (138 with RNA testing ordered and 238 deidentified and tested for RNA). RNA detection showed no significant association with the IgM titer but was inversely related to the IgG titer; 63% of the IgG negative sera were RNA positive, compared to 36% of sera with low IgG titers (1:10 to 1:80) and 16% with IgG titers of ≥1:160. Using second-sample results from 62 seroconverters, we estimated that CHIKV IgM persists for 110 days (95% confidence interval, 78 to 150 days) after the initial antibody-negative sample. These findings indicate that (i) RNA detection is more sensitive than antibody detection early in CHIKV infection, (ii) in the absence of RNA results, the IgG titer of the IgM-positive samples may be a useful surrogate for viremia, and (iii) CHIKV IgM persists for approximately 4 months after symptom onset.

Examining the Relevance of Intellectual Capital in Improving the Entrepreneurial Propensity Among Indians

2020 ◽  
Vol 16 (1) ◽  
pp. 123-140 ◽  
Author(s):  
Ahmed Musa Khan ◽  
Mohd Yasir Arafat ◽  
Mohd Anas Raushan ◽  
Imran Saleem
Keyword(s):  
Intellectual Capital ◽  
Adult Population ◽  
Large Data ◽  
Entrepreneurial Intention ◽  
Data Set ◽  
Structural Capital ◽  
Large Data Set ◽  
Start Up ◽  
The Relationship

Intellectual capital is considered as knowledge which can transform into value. Recently, it has gained currency in the field of innovation and entrepreneurship. Only a handful of studies have been conducted to examine the role of intellectual capital in explaining the venture creation process. The main aim of this study is to examine the influence of intellectual capital on start-up. A large data set of Adult Population Survey (APS) provided by the Global Entrepreneurship Monitor (GEM) used. The logistic regression technique was used to analyze the effect of intellectual capital on entrepreneurial intention. The finding suggests that policymakers should frame policy and programs focused on developing human capital, structural capital and encourage interaction between existing and potential entrepreneurs so that entrepreneurship can be boosted. This study is also among the few studies measuring the relationship between intellectual capital and entrepreneurial intention. A systematic literature survey shows that only small numbers of researches, based on large data set, have been conducted in developing countries like India.

A Multivariate, Multilevel Analysis of the Relationship Between Cognitive Abilities and Scholastic Achievement

2007 ◽  
Vol 28 (4) ◽  
pp. 188-197 ◽  
Author(s):  
Philipp Alexander Freund ◽  
Heinz Holling ◽  
Franzis Preckel
Keyword(s):  
Social Sciences ◽  
Cognitive Abilities ◽  
Large Data ◽  
Natural Sciences ◽  
Scholastic Achievement ◽  
School Type ◽  
Data Set ◽  
Student Gender ◽  
Composite Scores ◽  
The Relationship

Abstract. This study investigates the relationship between scholastic achievement (teacher-assigned grades) and cognitive abilities while explicitly modeling the multilevel structure of a large data set from an educational context. A multivariate analysis of composite scores in three subject domains (math and natural sciences, languages, and social sciences) was conducted using as predictors reasoning capacity, creativity, memory, and speed as well as student gender and type of school attended. The results showed meaningful differences in the relationships between the different abilities and school grades, and also significant contributions from student gender and school type. Specifically, reasoning capacity had the largest impact on achievement in math and natural sciences, whereas creativity explained more variability in performance for social sciences. Furthermore, girls outperformed boys. There was significant random variation in the intercepts at the between-classroom level, indicating that students sharing a common educational and ecological background tend to have more similar teacher-assigned grades when compared to students in other classrooms. Yet, there was no significant slope variation between the classrooms, which points to stable relationships between cognitive abilities and scholastic achievement.

scholarly journals Examining the Presence of Symmetry within Acheulean Handaxes: A Case Study in the British Palaeolithic

2015 ◽  
Vol 25 (4) ◽  
pp. 713-732 ◽  
Author(s):  
James Cole
Keyword(s):  
Material Culture ◽  
Social Relationships ◽  
Large Data ◽  
Data Set ◽  
Large Data Set ◽  
The Relationship ◽  
Lower Palaeolithic

This paper examines the relationship between the presence of symmetry and the Acheulean biface within a predominantly British Lower Palaeolithic context. There has been a long-standing notion within Palaeolithic studies that Acheulean handaxes are symmetrical and become increasingly so as time progress as a reflection of increasing hominin cognitive and behavioural complexity. Specifically, the presence of symmetry within Acheulean handaxes is often seen as one of the first examples of material culture being used to mediate social relationships. However, this notion has never been satisfactorily tested against a large data set. This paper seeks to address the issue by conducting an analysis of some 2680 bifaces across a chronological and geographical span. The results from the sample presented here are that symmetrical bifaces do not appear to have a particularly strong presence in any assemblage and do not appear to increase as time progress. These results have significant implications for modern researchers assessing the cognitive and behavioural complexities of Acheulean hominins.

scholarly journals Bank diversity and SME innovation: evidence from China

2019 ◽  
Vol 38 (2) ◽  
pp. 265-282
Author(s):  
Hongyu Li ◽  
Junjie Wu ◽  
Zhiqiang Lu
Keyword(s):  
Large Data ◽  
Firm Innovation ◽  
Data Set ◽  
Content Type ◽  
Banking Deregulation ◽  
Positive Effects ◽  
Bank Deregulation ◽  
Research Bias ◽  
The Impact ◽  
The Relationship

Purpose The purpose of this paper is to examine the relationship between bank diversity and small- and medium-sized enterprise (SME) firm innovation in China to evaluate the impact of recent bank deregulation. Design/methodology/approach Using a large data set that includes 8,143 firm-year observations of 1,122 listed SME firms in China and baseline and robustness regression analyses, the authors identify how bank diversity affects firm innovation and via what economic mechanisms. Potential endogeneity problems are considered and addressed in the design and analysis to minimize research bias. Findings The authors find robust evidence that bank diversity improves firm innovation. Specifically, the findings suggest that the positive effects of bank diversity on firm innovation are only significant for the firms which are more external finance dependent, have fewer growth opportunities and/or located in the provinces having low financial market development. Originality/value This study provides novel evidence and insights into the relationship between banking market structure and the determinants of firm innovation in the Chinese context, as a result of China’s banking deregulation.

scholarly journals Under pressure: an international comparison of job security, social security, and extra effort

2017 ◽  
Vol 37 (13/14) ◽  
pp. 823-839
Author(s):  
Ferry Koster ◽  
Maria Fleischmann
Keyword(s):  
Social Security ◽  
Social Exchange ◽  
Social Exchange Theory ◽  
Large Data ◽  
Job Security ◽  
Data Set ◽  
Content Type ◽  
Extra Effort ◽  
The Social ◽  
The Relationship

Purpose Previous research leads to contrasting hypotheses about the relationship between extra effort of employees and the level of job security. According to agency theory, job security leads to lower levels of extra effort and social exchange theory argues that extra effort requires job security. The purpose of this paper is to formulate a set of hypotheses based on these theories. Besides considering them as mutually exclusive, they are integrated into a single theoretical framework that argues that both theories can apply, depending on the conditions and social context (in terms of the social security system). Design/methodology/approach Data from the International Social Survey Program (2005) including 22 countries from around the globe are analyzed using multilevel analysis. Findings The study provides evidence that social security moderates the relationship between job security and extra effort. Originality/value This study differs from previous research as it focuses on two sides of insecurity in the workplace and because it analyzes a large data set to include institutional factors.

Penerapan Algoritma C4.5 pada Analisis Kerusakan Barang Jadi

2016 ◽  
Vol 7 (1) ◽  
pp. 24-28
Author(s):  
Ivan Oktana ◽  
Seng Hansun
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Historical Data ◽  
Large Data ◽  
Data Set ◽  
Damage Data ◽  
Data Explosion ◽  
Index Terms ◽  
Relationship Of ◽  
The Relationship

A Data mining is the activity that includes the collection, the use of historical data to discover regularity, patterns and relationship in a large data set. The usefulness of data mining is to specify a pattern to be found in the data mining task. The presences of data mining is motivated by the problem of data explosion which had been experienced lately these day where many organization or company collect so many years of data (purchasing data, sales data, damage data item, transaction data, and so on). In this paper data mining methods been used to analyze the damage data of finished products, with the goal of producing a pattern of the damage product. Based on the pattern from product’s damage, can be see and the aspects that affect to the damaged product. The purpose of this study is to show information about the relationship of damage data of finished goods using C4.5 algorithms in PT. Kayu Lapis Asli Murni, and display results in the form of a decision tree mining. Index Terms—data mining, C4.5 algorithms, decision tree, damage data of finished products, PT. Kayu Lapis Asli Murni

scholarly journals Perfectionism and therapeutic alliance: a review of the clinical research

2017 ◽  
Vol 20 (1) ◽  
Author(s):  
Racheli Miller ◽  
Mark J. Hilsenroth ◽  
Paul L. Hewitt
Keyword(s):  
Social Network ◽  
Therapeutic Alliance ◽  
Initial Level ◽  
Large Data ◽  
Strong Relationship ◽  
Future Research ◽  
Data Set ◽  
Measurement Issues ◽  
Pre Treatment ◽  
The Relationship

In this review, we synthesize findings regarding the relationship between perfectionism and therapeutic alliance, most of which come from analyses by Blatt and colleagues. Results suggest what follows. First, patients’ initial level of perfectionism negatively affects patients’ bond with therapists and perception of therapists’ Rogerian attributes (empathy, congruence, and regard) early in treatment and engagement in therapy later in treatment. Second, therapists’ contribution to alliance is not seemingly affected by patients’ initial perfectionism level. Third, individual patients of therapists who are perceived on average by their patients to be higher on Rogerian attributes experience greater decreases in perfectionism and symptoms. Fourth, more positive perceptions of therapists’ Rogerian attributes early in treatment lead to greater symptom decrease for patients with moderate perfectionism. Fifth, greater early patient engagement in therapy is related to greater decrease in perfectionism, but a strong relationship with the therapist may be necessary for an accompanied greater decrease in symptoms. The relationship between pre-treatment perfectionism and alliance is partially explained by higher levels of hostility and lower levels of positive affect. Sixth, the relationship between pre-treatment perfectionism and outcome is almost entirely explained by level of patient contribution to alliance and satisfaction with social network, highlighting the importance of focusing on social functioning for patients with high perfectionism (both in and outside of the session). Limitations include that most of the findings are from analyses of one large data set and a range of measurement issues. Future research should utilize different measures, perspectives, and populations and examine specific session process.

scholarly journals Revival of Legacy of Tooke and Gibson: Further Evidence and Implications for Monetary Policy

2017 ◽  
Vol 6 (3) ◽  
pp. 127-142
Author(s):  
Keyword(s):  
Interest Rate ◽  
Aggregate Demand ◽  
Correlation Coefficients ◽  
Large Data ◽  
Careful Analysis ◽  
Data Set ◽  
Long Run ◽  
Variable Bias ◽  
The Impact ◽  
The Relationship

AbstractTraditional economics assumes that interest rate effects inflation by changing the aggregate demand (Barth and Ramay, 2002). On the other hand, many economists in recent years have explored the cost side effects of monetary transmission and found very strong evidences in favour of cost channel. One of such studies is that by Rehman (2015) which explores the relationship between interest rate and inflation for a large data set comprising various measures of interest rate and inflation from countries around the globe. Rehman (2015) computes the correlation between two variables and he finds that the correlation between two variables is either positive or insignificant. Rehman argues that the finding is quite robust and does not change with a change in measure of interest rate and/or inflation. If the correlation between interest rate and inflation is positive then using interest rate to control inflation would be counterproductive. Thus it will endorse the warning of Wright Patman, a US congressman and Chairman of Joint Economic Committee who argues that “senseless of trying to fight inflation by raising interest rate, throwing the gasoline on fire to put out the flames would be as logical”. Findings of Rehman (2015) are based on correlation coefficients. The correlation without having control variables could only provide a clue and could be subject to serious missing variable bias. However, Rehman (2015) argues that thousands of similar clues from the entire globe collectively become very strong evidence. However, given the importance of the topic, it is necessary to do a more careful analysis and summarize the relationship between two variables which is not subject to missing variable bias. Therefore, this paper applies more sophisticated econometric techniques including Granger Causality and Static Long Run Solution to find the impact of interest rate and inflation.

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