一种改进的最小二乘回归子空间分割方法

最小二乘回归(LSR)算法是一种常见的子空间分割方法，由于LSR具有解析解，因此它的聚类性能较高。然而LSR算法是应用谱聚类方法聚类数据，谱聚类方法初始化聚类中心是随机的，会影响后面的聚类效果。针对这一问题，提出一种基于聚类中心局部密度和距离这2个特点的改进的LSR算法（LSR-DC）。在Extended Yale B数据集上进行实验，结果表明，该算法有较高的聚类精度，具有一定的鲁棒性，优于现有LSR等子空间分割方法。     

高速率通信网络下时变系统的有限时域H∞控制

针对高速率通信网络和Round-Robin（RR）协议影响下网络化时变系统的有限时域[H∞]控制问题，考虑到系统中存在乘性噪声、随机时滞和量化效应，提出了一种基于观测器的有限时域[H∞]控制器的设计方法。利用李雅普诺夫稳定性理论和线性矩阵不等式（Linear Matrix Inequality，LMI）技术得到有限时域[H∞]控制器存在的充分条件。基于锥补线性化（Cone Complementarity Linearization，CCL）方法通过求解一组递归矩阵不等式得到观测器和控制器参数。所设计的控制器保证闭环网络化时变系统在给定的时域内稳定，且满足预定的[H∞]性能指标。数值仿真验证了所提方法的有效性。     

Environmental Enrichment Enhances Cav 2.1 Channel-Mediated Presynaptic Plasticity in Hypoxic–Ischemic Encephalopathy

Hypoxic–ischemic encephalopathy (HIE) is a devastating neonatal brain condition caused by lack of oxygen and limited blood flow. Environmental enrichment (EE) is a classic paradigm with a complex stimulation of physical, cognitive, and social components. EE can exert neuroplasticity and neuroprotective effects in immature brains. However, the exact mechanism of EE on the chronic condition of HIE remains unclear. HIE was induced by a permanent ligation of the right carotid artery, followed by an 8% O₂ hypoxic condition for 1 h. At 6 weeks of age, HIE mice were randomly assigned to either standard cages or EE cages. In the behavioral assessments, EE mice showed significantly improved motor performances in rotarod tests, ladder walking tests, and hanging wire tests, compared with HIE control mice. EE mice also significantly enhanced cognitive performances in Y-maze tests. Particularly, EE mice showed a significant increase in Ca_v 2.1 (P/Q type) and presynaptic proteins by molecular assessments, and a significant increase of Ca_v 2.1 in histological assessments of the cerebral cortex and hippocampus. These results indicate that EE can upregulate the expression of the Ca_v 2.1 channel and presynaptic proteins related to the synaptic vesicle cycle and neurotransmitter release, which may be responsible for motor and cognitive improvements in HIE.     

跨行政区游憩空间柔性一体化研究 ——以高莱茵河沿岸地区为例

随着城市化与区域一体化的迅速发展,不同行政区之间的联动关系越来越紧密,这种联动关系在城市各功能空间的设计上有所体现,更渗透到了与市民息息相关的游憩空间建构之中。受制于行政管理等方面的原因,在跨行政区的游憩空间一体化实施过程中,往往会采取一系列柔性措施。以欧洲高莱茵河沿岸地区为研究对象,分析高莱茵河沿岸地区游憩空间的发展与现状,总结其游憩空间体系的构建特点,为中国跨城市河流沿岸的游憩空间柔性一体化建构提供策略与建议。     

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 Bark Beetle Dendroctonus rhizophagus (Curculionidae: Scolytinae) Has Digestive Capacity to Degrade Complex Substrates: Functional Characterization and Heterologous Expression of an α-Amylase

Dendroctonus-bark beetles are natural agents contributing to vital processes in coniferous forests, such as regeneration, succession, and material recycling, as they colonize and kill damaged, stressed, or old pine trees. These beetles spend most of their life cycle under stem and roots bark where they breed, develop, and feed on phloem. This tissue is rich in essential nutrients and complex molecules such as starch, cellulose, hemicellulose, and lignin, which apparently are not available for these beetles. We evaluated the digestive capacity of Dendroctonus rhizophagus to hydrolyze starch. Our aim was to identify α-amylases and characterize them both molecularly and biochemically. The findings showed that D. rhizophagus has an α-amylase gene (AmyDr) with a single isoform, and ORF of 1452 bp encoding a 483-amino acid protein (53.15 kDa) with a predicted signal peptide of 16 amino acids. AmyDr has a mutation in the chlorine-binding site, present in other phytophagous insects and in a marine bacterium. Docking analysis showed that AmyDr presents a higher binding affinity to amylopectin compared to amylose, and an affinity binding equally stable to calcium, chlorine, and nitrate ions. AmyDr native protein showed amylolytic activity in the head-pronotum and gut, and its recombinant protein, a polypeptide of ~53 kDa, showed conformational stability, and its activity is maintained both in the presence and absence of chlorine and nitrate ions. The AmyDr gene showed a differential expression significantly higher in the gut than the head-pronotum, indicating that starch hydrolysis occurs mainly in the midgut. An overview of the AmyDr gene expression suggests that the amylolytic activity is regulated through the developmental stages of this bark beetle and associated with starch availability in the host tree.     

Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.     

基于XGBoost算法的垃圾短信分层分级治理体系

为有效整治垃圾短信,不断提升不良信息治理的精准性,文章基于XGBoost算法构建了一套科学的分层分级垃圾短信治理体系。通过对用户入网、消费、通信行为等特征进行建模与运算,识别出用户发送垃圾短信的风险系数,并定义了六级用户。分级名单生成后,依托于垃圾短信拦截系统的分级策略管理功能,分别设置相匹配的拦截策略。在加大对中高危用户的识别和拦截力度的同时,有效降低了高价值用户因不良信息治理导致被误拦截的风险。该治理体系应用于辽宁移动管理实际以来,垃圾短信平均投诉量降幅34.82%。误关停投诉率稳定在0.1%以内。一至三级高价值客户群关停投诉量降幅27.43%。     

Model-Based Design Space Exploration for FPGA-based Image Processing Applications Employing Parameterizable Approximations

The increasing demand for low power consumption and high computational performance is outpacing available technological improvements in embedded systems. Approximate computing is a novel design paradigm trying to bridge this gap by leveraging the inherent error resilience of certain applications and trading in quality to achieve reductions in resource usage. Numerous approximation methods have emerged in this research field. While these methods are commonly demonstrated in isolation, their combination can increase the achieved benefits in complex systems. However, the propagation of errors throughout the system necessitates a global optimization of parameters, leading to an exponentially growing design space. Additionally, the parameterization of approximated components must consider potential cross-dependencies between them. This work proposes a systematic approach to integrate and optimally configure parameterizable approximate components in FPGA-based applications, focusing on low-level but high-bandwidth image processing pipelines. The design space is explored by a multi-objective genetic algorithm which takes parameter dependencies between different components into account. During the exploration, appropriate models are used to estimate the quality-resource trade-off for probed solutions without the need for time-consuming synthesis. We demonstrate and evaluate the effectiveness of our approach on two image processing applications that employ multiple approximations. The experimental results show that the proposed methods are able to produce a wide range of Pareto-optimal solutions, offering various choices regarding the desired quality-resource trade-off.