针对细微特征进行K-means聚类的电台分选识别技术

现代战场中的无线通信设备日益增多，精准获取个体信息已成为研究热点，但也是难点。针对通信电台，提出了一种分选识别技术。该技术从电台物理层特性出发，对其辐射信号的细微特征进行K-means聚类以实现分选，分选的同时提取各个个体的特征属性值，未知信号通过与特征属性值相关运算实现个体识别。该技术无需先验知识，无需训练运算，通过实验验证，其可行、高效，易于工程实现。     

Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications. Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.     

认知双向中继网络在κ-μ衰落信道下的中断性能分析

针对认知双向中继网络在进行数据传输时面临的复杂无线信道场景问题,采用广义κ-μ分布构建认知双向中继网络中的视距和非视距无线传输信道,推导次网络在κ-μ衰落信道下的统一中断概率,并分析次网络在多种单一和混合衰落信道情况下的中断性能。仿真结果表明,无线信道的衰落程度对次网络的中断概率影响显著,依据衰落信道类型合理设置网络参数将有助于提升次网络中断性能。     

Mitochondrial and Autophagic Regulation of Adult Neurogenesis in the Healthy and Diseased Brain

Adult neurogenesis is a highly regulated process during which new neurons are generated from neural stem cells in two discrete regions of the adult brain: the subventricular zone of the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Defects of adult hippocampal neurogenesis have been linked to cognitive decline and dysfunction during natural aging and in neurodegenerative diseases, as well as psychological stress-induced mood disorders. Understanding the mechanisms and pathways that regulate adult neurogenesis is crucial to improving preventative measures and therapies for these conditions. Accumulating evidence shows that mitochondria directly regulate various steps and phases of adult neurogenesis. This review summarizes recent findings on how mitochondrial metabolism, dynamics, and reactive oxygen species control several aspects of adult neural stem cell function and their differentiation to newborn neurons. It also discusses the importance of autophagy for adult neurogenesis, and how mitochondrial and autophagic dysfunction may contribute to cognitive defects and stress-induced mood disorders by compromising adult neurogenesis. Finally, I suggest possible ways to target mitochondrial function as a strategy for stem cell-based interventions and treatments for cognitive and mood disorders.     

Cognitive and affective processes for learning science in immersive virtual reality

As immersive virtual reality (IVR) systems proliferate in classrooms, it is important to understand how they affect learning outcomes and the underlying affective and cognitive processes that may cause these outcomes. Proponents argue that IVR could improve learning by increasing positive affective and cognitive processing, thereby supporting improved performance on tests of learning outcome, whereas opponents of IVR contend that it could hurt learning by increasing distraction, thereby disrupting cognitive learning processes and leading to poorer learning outcomes. In a media comparison study, students viewed a biology lesson either as an interactive animated journey in IVR or as a slideshow on a desktop monitor. Those who viewed the IVR lesson performed significantly worse on transfer tests, reported higher emotional arousal, reported more extraneous cognitive load and showed less engagement based on EEG measures than those who viewed the slideshow lesson, with or without practice questions added to the lessons. Mediational analyses showed that the lower retention scores for the IVR lesson were related to an increase in self-reported extraneous cognitive load and emotional arousal. These results support the notion that immersive environments create high affective and cognitive distraction, which leads to poorer learning outcomes than desktop environments.     

Improving the shelf life stability of vacuum-packed fresh-cut peaches (Prunus persica L.) by radio frequency heating in water

The present study aimed to investigate the influence of radio frequency (RF) heating at 70 and 80 °C, in comparison with the traditional conventional heating. The RF heating technology was applied for maintaining the colour and textural quality as well as inactivating the enzymatic activity of polyphenol oxidase (PPO) and reducing the Escherichia coli growth in packaged fresh-cut peach samples. To evaluate this, 120 g of freshly cut peach fruit was placed in heat-resistant plastic bags, and 50 mL of sugar solution (12°Brix) was added to each bag and vacuum-packed for conventional heating and radio frequency (RF) heating. Our results demonstrated that the RF heating process could reduce the heating time by up to 83% at 70 and 80 °C as compared to conventional heating. Moreover, RF heating at 70 and 80 °C reduced the PPO enzymatic activity, which caused enzymatic browning, up to 85.46% and 93.5%, respectively, as compared to 40.86% reduction only for conventional heating. Furthermore, RF heating completely inhibited E. coli growth. Collectively, we demonstrated that RF heating is an emerging and promising technology for improving the quality of fresh-cut fruits such as peach during various storage conditions. The present study provides relatively novel information on the effectiveness of RF heating in maintaining the quality of fresh-cut peaches. In the future, we would like to investigate the effectiveness of RF heating on other agricultural products.     

采用信道估计法的基站VSWR实时检测

为解决无线基站宽带工作频带内电压驻波比(Voltage Standing Wave Ratio,VSWR)的实时测量，提出了一种采用信道估计法的测量方案。该方案实现简单，在基带处理单元高速率位置发送数据，依次抓取射频通道反馈和反射数据，分别求取信道响应序列，结合工厂装备测试数据，计算驻波反射系数和反射点位置。发送信号采用宽带正交频分复用信号，能检测到工作频段内任何频点处的驻波异常。有用信号前加循环前缀，并引入峰值抵消核，能正确检测到多个反射点驻波。仿真结果表明，该方案驻波测量精度和单回波点位置精度达到预期，多回波点测量能抓准外部主要故障点，在基站VSWR实时测量中具有良好的应用前景。     

Inhibition of Soluble Epoxide Hydrolase Ameliorates Phenotype and Cognitive Abilities in a Murine Model of Niemann Pick Type C Disease

Niemann–Pick type C (NPC) disease is a rare autosomal recessive inherited childhood neurodegenerative disease characterized by the accumulation of cholesterol and glycosphingolipids, involving the autophagy-lysosome system. Inhibition of soluble epoxide hydrolase (sEH), an enzyme that metabolizes epoxy fatty acids (EpFAs) to 12-diols, exerts beneficial effects in modulating inflammation and autophagy, critical features of the NPC disease. This study aims to evaluate the effects of UB-EV-52, an sEH inhibitor (sEHi), in an NPC mouse model (Npc) by administering it for 4 weeks (5 mg/kg/day). Behavioral and cognitive tests (open-field test (OF)), elevated plus maze (EPM), novel object recognition test (NORT) and object location test (OLT) demonstrated that the treatment produced an improvement in short- and long-term memory as well as in spatial memory. Furthermore, UB-EV-52 treatment increased body weight and lifespan by 25% and reduced gene expression of the inflammatory markers (i.e., Il-1β and Mcp1) and enhanced oxidative stress (OS) markers (iNOS and Hmox1) in the treated Npc mice group. As for autophagic markers, surprisingly, we found significantly reduced levels of LC3B-II/LC3B-I ratio and significantly reduced brain protein levels of lysosomal-associated membrane protein-1 (LAMP-1) in treated Npc mice group compared to untreated ones in hippocampal tissue. Lipid profile analysis showed a significant reduction of lipid storage in the liver and some slight changes in homogenated brain tissue in the treated NPC mice compared to the untreated groups. Therefore, our results suggest that pharmacological inhibition of sEH ameliorates most of the characteristic features of NPC mice, demonstrating that sEH can be considered a potential therapeutic target for this disease.     

The validation and further development of a multidimensional cognitive load scale for virtual environments

Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL) dimension into three sub-scales relevant for VLE: EL instructions, EL interaction, and EL environment. We investigated the validity of the measures using the Partial Credit Model (PCM), Confirmatory Factor Analysis (CFA), and correlations with retention tests. Study 1 (n = 73) investigated the adapted version of the CLS. Study 2 describes the development and validation of the Multidimensional Cognitive Load Scale for Virtual Environments (MCLSVE), with 140 students in higher education. Study 3 tested the generalizability of the results with 121 higher education students in a more complicated VLE. The results provide initial evidence for the validity and reliability of the MCLSVE.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.