Psychological Features of Police Officers’ Conflict Behavior: Gender Aspect

To date, there are no scientifically sound recommendations for resolving conflicts in law enforcement activity, there are no methods for resolving conflicts, and there are no means for managing the conflict behavior of police officers taking into account the gender aspect. The purpose of the work is to conduct a comprehensive study of psychological characteristics of conflict behavior of police officers taking into account the gender aspect. Theoretical and empirical methods were used in the work. According to the results of conducted theoretical analysis the author has noted the psychological and moral preconditions for conflict prevention with the participation of police officers taking into account the gender aspect. According to the method of “Personal Aggression and Conflict” the highest rates in the first group (police officers – women) were obtained on the scale of “conflict”. The lowest rates among women are on the scale of “negative aggression”. The highest rates in the second group (police officers – men) – were on the scales of “conflict” and “positive aggression”. The lowest rates were on the “negative aggression” scale. The highest rate on the scale of “adaptation” according to the method of “Diagnosis of Style of Behavior in Conflicts” (K. Thomas) is both among women and men. Women and men according to the “rivalry” scale have a low rate. The highest rate for women according to the method of “Diagnosis of Conflict Resolution Strategies" was on the “adaptation” scale. The highest rate among men was the scale of “cooperation”. Prevention rates among women are low. Men have the lowest rate on the “competition” scale. Analyzing the results of the study of the style of behavior of police officers in conflict situations within the gender aspect, it was found out that the higher the tendency to avoid conflict, the less are manifestations of styles of rivalry, cooperation and adaptation. At the same time, as the length of service increases, the tendency to adaptive style of behavior in conflict situations increases, which may be associated with manifestations of professional deformation and burnout; strategies of compromise and avoidance in conflict situations are in the lead.

Sparse self-attention aggregation networks for neural sequence slice interpolation

Background Microscopic imaging is a crucial technology for visualizing neural and tissue structures. Large-area defects inevitably occur during the imaging process of electron microscope (EM) serial slices, which lead to reduced registration and semantic segmentation, and affect the accuracy of 3D reconstruction. The continuity of biological tissue among serial EM images makes it possible to recover missing tissues utilizing inter-slice interpolation. However, large deformation, noise, and blur among EM images remain the task challenging. Existing flow-based and kernel-based methods have to perform frame interpolation on images with little noise and low blur. They also cannot effectively deal with large deformations on EM images. Results In this paper, we propose a sparse self-attention aggregation network to synthesize pixels following the continuity of biological tissue. First, we develop an attention-aware layer for consecutive EM images interpolation that implicitly adopts global perceptual deformation. Second, we present an adaptive style-balance loss taking the style differences of serial EM images such as blur and noise into consideration. Guided by the attention-aware module, adaptively synthesizing each pixel aggregated from the global domain further improves the performance of pixel synthesis. Quantitative and qualitative experiments show that the proposed method is superior to the state-of-the-art approaches. Conclusions The proposed method can be considered as an effective strategy to model the relationship between each pixel and other pixels from the global domain. This approach improves the algorithm’s robustness to noise and large deformation, and can accurately predict the effective information of the missing region, which will greatly promote the data analysis of neurobiological research.

Pengembanagn Model E-Learning Adaptif untuk Materi Pembelajaran Jaringan Komputer pada Amik Almuslim

Abstrak: Perkembangan teknologi e-learning sudah sangat pesat, hal ini ditandai dengan munculnya sejumlah perangkat lunak seperti: moodle, Atutor, LRN, Dukeos dan lain sebagainya, disisi lain adanya keterbatasan e-learning dapat menghambat kemajuan proses pembelajaran, dimana hambatan yang muncul adalah dalam mengoperasionalkan proses pembelajaran dan proses kognitif mahasiswa. Sistem e-learning adaptif dikembangkan atas asumsi bahwa model pembelajaran individual mampu memberikan hasil yang lebih baik dari pada model pembelajaran lainnya. Digunakan Jaringan Bayesian dalam menentukan model pengguna dan dipilih Model Gaya Belajar Dunn & Dunn untuk menentukan ke-adaptif-an sebuah e-learning. Dalam pengembangan aplikasi digunakan model pengembangan perangkat lunak sequencial linear, tahap analisa digunakan Unifed Modelling Language (UML), seperti : Use Case Diagram, Activity Diagram dan Deployment Diagram, sedangkan tahap pemberian kodenya menggunakan PHP. Penentuan model pengguna dengan Jaringan Bayesian ditetapkan 4 parameter, yaitu : Persepsi kemudahan penggunaan (C1), Motivasi (C2), Sikap dalam penggunaan (C3) dan Penerimaan terhadap e-learning (C4). Hasil dari perhitungan terhadap paramater-parameter ini mengarah ke model gaya belajar Dunn & Dunn yang mendasarkan kepada kesamaan fungsionalnya. Hasil dari analisa dihasilkan 9 page dalam mendukung tercapainya e-learning adaptif ini, dimana ada 3 page utama, yaitu : page model perkuliahan berbasis teks, page model perkuliahan berbasis visual & suara dan page model perkuliahan berbasis image & teks yang dapat menjadi pilihan mahasiswa dalam belajar. Pengujian untuk sistem ini dilakukan dengan menggunakan Blackbox Testing bertipe Functional Testing. Penelitian ini telah berhasil memodelkan e-learning adaptif dengan menentukan model pengguna menggunakan Jaringan Bayesian dan model Dunn & Dunn untuk model gaya belajar mahasiswa. Pengembangan e-learning adaptif ini perlu dilakukan penelitian lebih lanjut dengan berbagai model gaya belajar seperti : Felder Silverman atau Kolb. Kata kunci: e-learning adaptive, style learning.

Research on Tibetan Folk’s Contemporary Tibetan Cultural Adaptive Differences and Its Influencing Factors—Taking ShigatseCity, Tibet, China as an Example

Using qualitative research methods and mathematical statistical analysis, taking Shigatse city in Tibet as a case study area, and based on the affective, behavioral, and cognitive (ABC) model and cultural distance theory, we explore the Tibetan people’s cultural adaptive types, differences, and its influencing factors. The results show that there are seven Tibetans’ cultural adaptive kinds: Integration, assimilation, isolation, marginalization, tending to Tibetan modern culture, adaptation to Tibetan traditional culture, and unclassified cultural adaptive style. The Tibetans’ cultural adaptive tendency mainly integrates between modern and traditional parts in the contemporary Tibetan local cultures. Meanwhile, the Tibetan folk still has a large proportion of modifying to traditional culture. Moreover, the Tibetans’ cultural adjusted differences in the affective and cognitive dimensions are smaller than the acculturate features in the behavioral side. However, the cultural adjusted distinctions in the affective and cognitive aspects compared to that in the behavioral field are more complex. Moreover, there are direct and mediating effects that impact the Tibetan folks’ cultural adaptability. Studying Tibetan people’s cultural adaptation may be conducive to understanding the evolution of Tibetan locality’s meaning and the mutual game between the two different parts in local culture as well as comprehending the Tibetan folks’ real cultural appeal. The conclusions have important practical significance of the harmony, stability, unity, progress, and information in China ethnic areas’ economy, society, and culture.

Dynamic Nosology and Clinical Assessment of Fragmented Personality

This chapter introduces a dynamic, personalized, context- and time-sensitive diagnosis of personality in health and disorder. Adaptive flexibility of the mind implies that its component subsystems and functions must also be flexible and semistable, including healthy personality and personality disorder. The model defines a 3D diagnostic space, in which each individual is uniquely and flexibly positioned. “Vertical diagnosis” is based on the duration, pervasiveness, and frequency of periods of fragmented functioning. It is cross-matched with “horizontal diagnosis,” based on the predominant adaptive style. Such dynamic nosology accounts for fluctuations in mental functioning as the individual “moves” in the diagnostic space. The approach captures the flexibility of the mind, self-reorganizing to adapt to changing conditions, and champions the positive connotation of change, challenging the widespread therapeutic nihilism about severe personality pathology. Clinical diagnosis of personality disorder, notably interpersonal (relational), behavioral, and intrapersonal approaches, together with psychological testing are discussed in detail.

Rethinking How We Think About Cognitive Interventions for Depression: An Example From Research on Second-Language Acquisition

One of the primary goals of cognitive therapy for depression is to teach an individual a new, more adaptive way of thinking about stressful life experiences. We argue that this process of supplanting a deeply engrained way of negative thinking with a more adaptive style of thinking is similar to learning a second language. The purpose of this article was to use a second-language acquisition framework to evaluate the strategies typically used in cognitive therapy for changing depressogenic cognitive patterns and to propose new strategies that may make the therapy more effective.