A microsatellite study in the Łęgucki Młyn/Popielno hybrid zone reveals no genetic differentiation between two chromosome races of the common shrew (Sorex araneus)

This study investigated a chromosome hybrid zone between two chromosomal races of the common shrew (Sorex araneus). Gene flow and genetic structure of the hybrid zone, located in the northeast of Poland, were studied using seven polymorphic autosomal microsatellite loci (L9, L14, L33, L45, L67, L68, L97) and a Y-linked microsatellite locus (L8Y). Seventy-five animals (46 of the Łęgucki Młyn race and 29 of the Popielno race) from nine different localities were examined and the data were analyzed using hierarchical AMOVA and F-statistic. The studied microsatellite loci and races (divided into nine geographical populations) were characterized by observed heterozygosity (HO), expected heterozygosities within (HS), and between (HT) populations, inbreeding coefficient (FIS), fixation index (FST), and average allelic richness (A). We found that genetic structuring within and between the two chromosome races were weak and non-significant. This finding and unconstrained gene flow between the races indicates a high level of migration within the Łęgucki Młyn/Popielno hybrid zone, suggesting that evolutionarily important genetic structuring does not occur in interracial zones where races which are not genetically distinct come into contact

Squealer Dealers: The Market for Information in Federal Drug Trafficking Prosecutions

Federal data on drug trafficking sentences are used to determine factors that affect market quantities of providing information against other defendants (i.e., defendant probabilities of receiving testimony-related sentence reductions) and market prices of information (i.e., the sizes of such sentence reductions). Women and better-educated defendants experience high demand (higher quantities and prices) for information. Blacks, Hispanics, and non-U.S. citizens experience low demand. Defendants expecting longer sentences have higher supply of information. Conditional on expected sentence, crack dealers, high-level dealers, and dealers with long criminal histories experience low demand, while low-level dealers experience high demand. Women of all races experience high demand for information

Squealer Dealers: The Market for Information in Federal Drug Trafficking Prosecutions

Federal data on drug trafficking sentences are used to determine factors that affect market quantities of providing information against other defendants (i.e., defendant probabilities of receiving testimony-related sentence reductions) and market prices of information (i.e., the sizes of such sentence reductions). Women and better-educated defendants experience high demand (higher quantities and prices) for information. Blacks, Hispanics, and non-U.S. citizens experience low demand. Defendants expecting longer sentences have higher supply of information. Conditional on expected sentence, crack dealers, high-level dealers, and dealers with long criminal histories experience low demand, while low-level dealers experience high demand. Women of all races experience high demand for information

Attitude and Willingness to Pay for Green Products

Attitude towards environmental issue is beginning to attract a lot of consumers in Malaysia. However the contribution towards environmental activities such as recycling, buying biodegradable product and buying other green products is still small. The main objectives of this research is to determine the level of consumer willingness to pay for green products, to determine the differences in willingness to pay between gender and races and to determine the relationship between personality, lifestyle, attitude, income and willingness to pay. Independent variables consist of demographic factors, attitude, lifestyle and personality. Dependent variable for this research is willingness to pay for green products. Data is gathered through questionnaire containing five parts (demographic, attitude, lifestyle, personality and willingness to pay) using six point Likert scales :( l-strongly disagree to 6-strongly agree). Data is analyzed using descriptive analysis, T-test, ANOVA, correlation and regression stepwise. Results show that the level of willingness to pay for green products is high. There is also no significance difference in willingness to pay between gender and races, and there is a significant relationship on willingness to pay for attitude, personality and income. Discussion and recommendation are discussed

Champion-level drone racing using deep reinforcement learning

First-person view (FPV) drone racing is a televised sport in which professional competitors pilot high-speed aircraft through a 3D circuit. Each pilot sees the environment from the perspective of their drone by means of video streamed from an onboard camera. Reaching the level of professional pilots with an autonomous drone is challenging because the robot needs to fly at its physical limits while estimating its speed and location in the circuit exclusively from onboard sensors. Here we introduce Swift, an autonomous system that can race physical vehicles at the level of the human world champions. The system combines deep reinforcement learning (RL) in simulation with data collected in the physical world. Swift competed against three human champions, including the world champions of two international leagues, in real-world head-to-head races. Swift won several races against each of the human champions and demonstrated the fastest recorded race time. This work represents a milestone for mobile robotics and machine intelligence, which may inspire the deployment of hybrid learning-based solutions in other physical systems

Efficient System-Enforced Deterministic Parallelism

Deterministic execution offers many benefits for debugging, fault tolerance, and security. Current methods of executing parallel programs deterministically, however, often incur high costs, allow misbehaved software to defeat repeatability, and transform time-dependent races into input- or path-dependent races without eliminating them. We introduce a new parallel programming model addressing these issues, and use Determinator, a proof-of-concept OS, to demonstrate the model's practicality. Determinator's microkernel API provides only “shared-nothing” address spaces and deterministic interprocess communication primitives to make execution of all unprivileged code—well-behaved or not—precisely repeatable. Atop this microkernel, Determinator's user-level runtime adapts optimistic replication techniques to offer a private workspace model for both thread-level and process-level parallel programing. This model avoids the introduction of read/write data races, and converts write/write races into reliably-detected conflicts. Coarse-grained parallel benchmarks perform and scale comparably to nondeterministic systems, on both multicore PCs and across nodes in a distributed cluster

Bullying among U.S. school children: An examination of race/ethnicity and school-level variables on bullying

Bullying is unwanted aggressive behavior and a damaging experience that can violate a bullied child\u27s civil and human rights. To understand and reduce bullying in U.S. schools, it is important to recognize students\u27 self-reported experiences with and perceptions of bullying. This study responded to limited research on races/ethnicites and bullying among children and youth in U.S. schools, and to a relatively small focus on specific school-level variables (such as the densities of races/ethnicities in school, the school\u27s ethnic diversity, the overall poverty level of the school, student/teacher ratio, and school locations) and several other variables of interest (such as the likelihood of joining in bullying, students\u27 general satisfaction or dissatisfaction with school, and the size of a child\u27s social networks, school safety) by bullying researchers. This study utilized a combined data of the Olweus Bullying Questionnaire (OBQ) and the National Center for Education Statisitics (NCES) to examine the influence of races/ethnicities on bullying and generate multivariate regression models predicting bullying among 473,918 students attending 1,524 schools located in various communities in 45 states and the US Virgin Islands. Results revealed that students\u27 races/ethnicities were significantly associated with peer victimization (being bullied) and bullying perpetration (bullying others) and on students\u27 self-reported perceptions of how they liked school (i.e., general satisfaction or dissatisfaction with school), the likelihood of joining in bullying a student whom they did not like, how many friends they had in their class(es) (i.e., the size of a child\u27s social networks in school), and how often they were afraid of being bullied by other students in their school (i.e., school safety). In this study, multiracial students (i.e., those students who were identified as belonging to more than one racial/ethnic group) reported the highest rates of bullying involvement (30.6%), followed by those students who did not know their races/ethnicities (26.9%), African American (23.2%), White (20.6%), and Asian American students (18.5%). Hispanic students (17.9%) reported the lowest rates of involvement in bullying. Asian American students were more likely to be racially or ethnically bullied (e.g., were bullied with mean names or comments about their race or color) than their peers of other races/ethnicities in U.S. schools. In terms of the relationship between several key school-level variables (such as the densities of racial/ethnic groups, the ethnic diversity, the overall poverty level, student/teacher ratio, and school locale) and bullying, results showed that the ethnic densities of African American and multiracial students were associated with a greater likelihhod of being bullied, and the ethnic densities of Asian American and Hispanic students were associated with a less likelihood of being bullied. Students were less likely to be bullied within a school context with a moderately high rate of school ethnic diversity, but the likelihood of being bullied appeared to increase if the ethnic diversity was too high. Students in schools located in town and rural communities were more likely to be bullied than students in urban and suburban areas. The school\u27s overall poverty level moderated the relationship between races/etnicities and bullying. This study generated two multivariate regression models predicting bullying among children and youth. In the model predicting being bullied, the overall model was significant and explained 21.9% of the variance. The strongest predictor of being bullied in the model was school safety. The likelihood of joining in bullying, being in elementary school and high school, the size of a child\u27s social networks in school, general satisfaction or dissatisfaction with school, the school\u27s overall poverty level, being multiracial students, the ethnic density of Hispanic students, attending a school located in towns, and being a girl were also significant predictors. Student/teacher ratio did not predict being bullied. In the model predicting bullying others, the overall model was significant and explained 14.1% of the variance. The strongest predictor of bullying others in the model was the likelihood of joining in bullying. School safety, general satisfaction or dissatisfaction with school, the school\u27s overall poverty level, being in elementary school and high school, being African American and multiracial students, the density of Asian American students, attending a school located in towns, and the school\u27s ethnic diversity were also significant predictors. Gender and student/teacher ratio were not associated with the likelihood of bullying others. Research and practical implications of these findings are discussed

HOW CRITICAL IS THE CHOICE OF DISTANCE-BASED MEASURES IN STUDYING TUMBLE TURN PERFORMANCE?

The turn is a crucial part of swim races and therefore requires systematic investigation. Yet, many different measures of turn performance are used in the literature. This study aimed to examine the level of agreement and the sensitivity of six fixed-distance based performance measures of the tumble turn. Tumble turn data of 10 Dutch elite level swimmers were analysed using those measures. The overall level of agreement was high between all measures (R ranging from 0.91 to 0.99). However, if the swimmers were ranked according to each of those measures, not all performance measures resulted in the same ranking. In particular, the rankings for measures with an exist distance of 10 m deviated from those for measures with an exit distance of 5 or 15 m. This finding suggests that the performance measures of interest are sensitive to different phases of the turn

Characteristics of Public School Principals: Analysis of the National Teacher and Principal Survey

Gender and racial diversity in the principalship, or the lack thereof, has been a topic for research for several years. While the concerns about general disparity are widely discussed, it is equally important to consider where underrepresented groups are typically hired, such as urban schools with high-poverty levels. Discrepancies in hiring have implications for promotion into superintendent and other educational leadership positions, as well as for overall financial compensation, where minority groups such as females and races other than White are forced to take lower-level jobs or jobs at the same level for less pay than their White male counterparts. Existing data from the 2017-18 United States National Teacher and Principal Survey were used to perform Chi-Square Tests for Association to evaluate how the gender and race of public school principals are distributed across various factors. We found there is a statistically significant association between race and community type, race and school poverty levels, age and school level, gender and community type, gender and school level, and gender and school poverty level. Findings suggest Black and Hispanic teachers are more likely to be overrepresented in city schools that have high poverty levels, while females are more likely to be overrepresented in city primary schools with high poverty levels