EFFECT OF THE UNIFORM FISSION SOURCE METHOD ON LOCAL POWER VARIANCE IN FULL CORE SERPENT CALCULATION

One of challenges of the Monte Carlo full core simulations is to obtain acceptable statistical variance of local parameters throughout the whole reactor core at a reasonable computation cost. The statistical variance tends to be larger in low-power regions. To tackle this problem, the Uniform-Fission-Site method was implemented in Monte Carlo code MC21 and its effectiveness was demonstrated on NEA Monte Carlo performance benchmark. The very similar method is also implemented in Monte Carlo code Serpent under the name Uniform Fission Source (UFS) method. In this work the effect of UFS method implemented in Serpent is studied on the BEAVRS benchmark which is based on a real PWR core with relatively flat radial power distribution and also on 3x3 PWR mini-core simulated with thermo-hydraulic and thermo-mechanic feedbacks. It is shown that the application of the Uniform Fission Source method has no significant effect on radial power variance but equalizes axial distribution of variance of local power.

Data Visualization on Crime Against Women

Visualization ensures the modern expectation of all forms of data. It is important to understand the data and its statistical variance graphically. Visualization on crime data would be supportive to analyze and prevent the threats in society. According to recent surveys and records, India has undergone many crime issues which occur on women. In order to prevent and analyze the crime issues against women, Data visualization is a useful approach to deal with it. The current data technologies available are appropriate to accomplish the task of visualization for women safety. Efficient visualization with effective machine learning algorithm and its performance finds the response for data related requests in the field of data science. This paper clarifies the details of crime against women through a graphical approach and illustrates about how to notify the unsafe levels by alert to safeguard the women

Primate prefrontal neurons signal economic risk derived from the statistics of recent reward experience

Risk derives from the variation of rewards and governs economic decisions, yet how the brain calculates risk from the frequency of experienced events, rather than from explicit risk-descriptive cues, remains unclear. Here, we investigated whether neurons in dorsolateral prefrontal cortex process risk derived from reward experience. Monkeys performed in a probabilistic choice task in which the statistical variance of experienced rewards evolved continually. During these choices, prefrontal neurons signaled the reward-variance associated with specific objects (‘object risk’) or actions (‘action risk’). Crucially, risk was not derived from explicit, risk-descriptive cues but calculated internally from the variance of recently experienced rewards. Support-vector-machine decoding demonstrated accurate neuronal risk discrimination. Within trials, neuronal signals transitioned from experienced reward to risk (risk updating) and from risk to upcoming choice (choice computation). Thus, prefrontal neurons encode the statistical variance of recently experienced rewards, complying with formal decision variables of object risk and action risk.

Reporting Characteristics in Sports Nutrition

Purpose: To examine data reporting characteristics in sports nutrition. Methods: We examined 236 papers from ten journals published in 2016. The primary outcome was statistical variance associated with treatment (SD (correct) vs. SEM or CI). Secondary outcomes included the reporting of: (a) effect sizes (Y/N); (b) outcome prioritization (Y/N; primary, secondary, etc.) and (c) statistical variance relative to change from baseline (CI (correct) vs. SD or SEM). As tertiary/exploratory outcome, we examined whether authors stated a directed hypothesis. Statistical evaluation was performed using chi-square analyses. Results: We observed significant trends for all analyses (p < 0.001) and between category comparisons (p < 0.002). For the primary outcome, 128 (59%) articles correctly used SD to denote treatment variance, while 79 (36%) and 11 (5%) used SEM and CI, respectively. For secondary outcomes, 63 articles (29%) reported effect sizes, while 155 (71%) did not. Additionally, 188 articles (86%) did not prioritize outcomes, 134 articles (61%) stated no hypotheses and 40 (19%, out of 100) articles used CI to denote change scores vs. SD (19%, n = 41) and SEM (n = 10, 5%). Eight articles (4%) reported no variance terms. Conclusions: Overall, there are gaps regarding reporting in sports nutrition. Editors, journal publishers, and the field of exercise science alike should consider these outcomes and provide editorial staff, reviewers and authors with more concrete guidelines.