Allozyme variation in Rattus rattus (Rodentia: Muridae) in Turkey, with particular emphasis on the taxonomy

WOS: 000261906600003The Turkish black rat "Rattus rattus" shows variation in coat colour corresponding to the occurrence of three subspecies with intermediate colour stages: Rattus rattus rattus, Rattus r. alexandrinus and Rattus r. frugivorus. Turkish black rat populations were divided geographically into six sub-populations: Rr1 = Northwest Anatolia, Rr2 = Central Anatolia, Rr3 = Eastern Mediterranean, Rr4 = Western Mediterranean, Rr5 = Turkish Thrace, and Rr6 = Black Sea region. Genetic variation was assessed using twenty two isoenzyme systems. Seven of twenty-two loci (Pgm-1, Hk, Ale-M, G3pdh, Gpdh-1, Gpi, Fum-1) were found to be polymorphic. The mean Value of F(ST) is found to be 0.073, indicating 7.3 % genetic variation among groups and suggesting the existence of a moderate differentiation between sub-populations of the Turkish black rat. Overall mean heterozygosity (Ho = direct count) for sub-populations was Ho = 0.020, ranging from 0.008 to 0.031. Nei's measure of genetic distance showed that Rr2 and Rr6 were the most identical and sub-populations Rr1 and Rr5 had diverged the most.BAP of Ankara UniversityAnkara University [97.05.03.04, 2000.07.05.037]We wish to thank Dr Ben BRILOT for comments on the text. This study was supported by BAP (97.05.03.04 and 2000.07.05.037) of Ankara University

Malicious code detection in android : the role of sequence characteristics and disassembling methods

The acceptance and widespread use of the Android operating system drew the attention of both legitimate developers and malware authors, which resulted in a significant number of benign and malicious applications available on various online markets. Since the signature-based methods fall short for detecting malicious software effectively considering the vast number of applications, machine learning techniques in this field have also become widespread. In this context, stating the acquired accuracy values in the contingency tables in malware detection studies has become a popular and efficient method and enabled researchers to evaluate their methodologies comparatively. In this study, we wanted to investigate and emphasize the factors that may affect the accuracy values of the models managed by researchers, particularly the disassembly method and the input data characteristics. Firstly, we developed a model that tackles the malware detection problem from a Natural Language Processing (NLP) perspective using Long Short-Term Memory (LSTM). Then, we experimented with different base units (instruction, basic block, method, and class) and representations of source code obtained from three commonly used disassembling tools (JEB, IDA, and Apktool) and examined the results. Our findings exhibit that the disassembly method and different input representations affect the model results. More specifically, the datasets collected by the Apktool achieved better results compared to the other two disassemblers

A global experiment on motivating social distancing during the COVID-19 pandemic

Finding communication strategies that effectively motivate social distancing continues to be a global public health priority during the COVID-19 pandemic. This cross-country, preregistered experiment (n = 25,718 from 89 countries) tested hypotheses concerning generalizable positive and negative outcomes of social distancing messages that promoted personal agency and reflective choices (i.e., an autonomy-supportive message) or were restrictive and shaming (i.e., a controlling message) compared with no message at all. Results partially supported experimental hypotheses in that the controlling message increased controlled motivation (a poorly internalized form of motivation relying on shame, guilt, and fear of social consequences) relative to no message. On the other hand, the autonomy-supportive message lowered feelings of defiance compared with the controlling message, but the controlling message did not differ from receiving no message at all. Unexpectedly, messages did not influence autonomous motivation (a highly internalized form of motivation relying on one’s core values) or behavioral intentions. Results supported hypothesized associations between people’s existing autonomous and controlled motivations and self-reported behavioral intentions to engage in social distancing. Controlled motivation was associated with more defiance and less long-term behavioral intention to engage in social distancing, whereas autonomous motivation was associated with less defiance and more short- and long-term intentions to social distance. Overall, this work highlights the potential harm of using shaming and pressuring language in public health communication, with implications for the current and future global health challenges

A multi-country test of brief reappraisal interventions on emotions during the COVID-19 pandemic.

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world