Is Police Misconduct Contagious? Non-trivial Null Findings from Dallas, Texas

Objectives Understanding if police malfeasance might be “contagious” is vital to identifying efficacious paths to police reform. Accordingly, we investigate whether an officer’s propensity to engage in misconduct is associated with her direct, routine interaction with colleagues who have themselves engaged in misbehavior in the past. Methods Recognizing the importance of analyzing the actual social networks spanning a police force, we use data on collaborative responses to 1,165,136 “911” calls for service by 3475 Dallas Police Department (DPD) officers across 2013 and 2014 to construct daily networks of front-line interaction. And we relate these cooperative networks to reported and formally sanctioned misconduct on the part of the DPD officers during the same time period using repeated-events survival models. Results Estimates indicate that the risk of a DPD officer engaging in misconduct is not associated with the disciplined misbehavior of her ad hoc, on-the-scene partners. Rather, a greater risk of misconduct is associated with past misbehavior, officer-specific proneness, the neighborhood context of patrol, and, in some cases, officer race, while departmental tenure is a mitigating factor. Conclusions Our observational findings—based on data from one large police department in the United States—ultimately suggest that actor-based and ecological explanations of police deviance should not be summarily dismissed in favor of accounts emphasizing negative socialization, where our study design also raises the possibility that results are partly driven by unobserved trait-based variation in the situations that officers find themselves in. All in all, interventions focused on individual officers, including the termination of deviant police, may be fruitful for curtailing police misconduct—where early interventions focused on new offenders may be key to avoiding the escalation of deviance.

Power Allocation for 5G Mobile Multiuser Cooperative Networks

With the fifth generation (5G) communication technology, the mobile multiuser networks have developed rapidly. In this paper, the performance analysis of mobile multiuser networks which utilize decode-and-forward (DF) relaying is considered. We derive novel outage probability (OP) expressions. To improve the OP performance, we study the power allocation optimization problem. To solve the optimization problem, we propose an intelligent power allocation optimization algorithm based on grey wolf optimization (GWO). We compare the proposed GWO approach with three existing algorithms. The experimental results reveal that the proposed GWO algorithm can achieve a smaller OP, thus improving system efficiency. Also, compared with other channel models, the OP values of the 2-Rayleigh model are increased by 81.2% and 66.6%, respectively.

A science mapping of studies on courtroom discourse with CiteSpace

The courtroom, as the most dramatic setting of legal language, is a rich linguistic domain for research; therefore, a science mapping study of the state of the art of this emerging field is of necessity. By CiteSpace V, the present study provides a comprehensive and up-to-date systematic review of the research on courtroom discourse, as presented by 379 article publications and their 10,538 references in the Web of Science (WoS) Core Collection from 1979 to 2021. According to statistics on publications by year, it appears that courtroom discourse research has experienced a period of silence (1979–1992), followed by an emergent period (1993–2005), before entering a period of considerable growth since 2006. Weak cooperative networks, extensive information base, multiple research fronts, and dynamic hotspots of courtroom discourse research have been discovered. Courtroom discourse research focuses on three core topics: courtroom interpreting, the interaction between law, language, power, and ideology, and the investigation of courtroom trial structures. Linguistic communication issues are prominent in courtroom discourse. As far as courtroom subjects are concerned, there is an audience-oriented turn in the latest research front of courtroom discourse. The research hotspots have shifted from language ontology during the emergent period to consolidating and developing the theoretical foundations of courtroom discourse during the rapid development period. According to keyword clustering, stance studies and miscommunication research are significant research hotspots of courtroom discourse.

Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight

Electricity demand forecasting plays a fundamental role in the operation and planning procedures of power systems, and the publications related to electricity demand forecasting have attracted more and more attention in the past few years. To have a better understanding of the knowledge structure in the field of electricity demand forecasting, we applied scientometric methods to analyze the current state and the emerging trends based on the 831 publications from the Web of Science Core Collection during the past 20 years (1999–2018). Employing statistical description analysis, cooperative network analysis, keyword co-occurrence analysis, co-citation analysis, cluster analysis, and emerging trend analysis techniques, this study gives a comprehensive overview of the most critical countries, institutions, journals, authors, and publications in this field, cooperative networks relationships, research hotspots, and emerging trends. The results can provide meaningful guidance and helpful insights for researchers to enhance the understanding of crucial research, emerging trends, and new developments in electricity demand forecasting.

Multi-Controller Load Balancing Algorithm for Test Network Based on IACO

With the rapid increase of volume and complexity in the projectile flight test business, it is becoming increasingly important to improve the quality of the service and efficiency of multi-domain cooperative networks. The key for these improvements is to solve the problem of asymmetric load of multi-controllers in multi-domain networks. However, due to the current reality, it is difficult to meet the demands of future tests, and there is not guarantee of subnet multi-domain test load balancing. Most recent works have used a heuristic approach to seek the optimal dynamic migration path, but they may fall into the local optimum. This paper proposes an improved ant colony algorithm (IACO) that can transform the modeling of the mapping relationship between the switch and the controller into a traveling salesman problem by combining the ant colony algorithm and artificial fish swarm algorithm. The IACO not only ensures the load balancing of multi-controllers but also improves the reliability of the cluster. The simulation results show that compared to other algorithms such as traditional ant colony algorithms and distributed decision mechanisms, this IACO achieves better load balancing, improves the average throughput of multi-controller clusters, and effectively reduces the response time of controller request events.

Computational design of highly signaling active membrane receptors through de novo solvent-mediated allosteric networks

Protein catalysis and allostery require the atomic-level orchestration and motion of residues, ligand, solvent and protein effector molecules, but the ability to design protein activity through precise protein-solvent cooperative interactions has not been demonstrated. Here, we report the design of a dozen novel membrane receptors catalyzing G-protein nucleotide exchange through diverse de novo engineered allosteric pathways mediated by cooperative networks of intra-protein, protein-ligand and solvent molecule interactions. Consistent with the predictions, designed protein activities strongly correlated with the level of solvent-mediated interaction network plasticity at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared to related natural receptors. The most stable and active variant crystallized in an unforeseen signaling active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal a space of allosteric interactions larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein catalytic and signaling activities.

Single allele loss-of-function mutations select and sculpt conditional cooperative networks in breast cancer

The most common events in breast cancer (BC) involve chromosome arm losses and gains. Here we describe identification of 1089 gene-centric common insertion sites (gCIS) from transposon-based screens in 8 mouse models of BC. Some gCIS are driver-specific, others driver non-specific, and still others associated with tumor histology. Processes affected by driver-specific and histology-specific mutations include well-known cancer pathways. Driver non-specific gCIS target the Mediator complex, Ca++ signaling, Cyclin D turnover, RNA-metabolism among other processes. Most gCIS show single allele disruption and many map to genomic regions showing high-frequency hemizygous loss in human BC. Two gCIS, Nf1 and Trps1, show synthetic haploinsufficient tumor suppressor activity. Many gCIS act on the same pathway responsible for tumor initiation, thereby selecting and sculpting just enough and just right signaling. These data highlight ~1000 genes with predicted conditional haploinsufficient tumor suppressor function and the potential to promote chromosome arm loss in BC.