Transcriptional regulation in the development and dysfunction of neocortical projection neurons

Glutamatergic projection neurons generate sophisticated excitatory circuits to integrate and transmit information among different cortical areas,and between the neocortex and other regions of the brain and spinal cord.Appropriate development of cortical projection neurons is regulated by certain essential events such as neural fate determination,proliferation,specification,differentiation,migration,survival,axonogenesis,and synaptogenesis.These processes are precisely regulated in a tempo-spatial manner by intrinsic factors,extrinsic signals,and neural activities.The generation of correct subtypes and precise connections of projection neurons is imperative not only to support the basic cortical functions(such as sensory information integration,motor coordination,and cognition)but also to prevent the onset and progression of neurodevelopmental disorders(such as intellectual disability,autism spectrum disorders,anxiety,and depression).This review mainly focuses on the recent progress of transcriptional regulations on the development and diversity of neocortical projection neurons and the clinical relevance of the failure of transcriptional modulations.

Diagnosis of indirectly driven double shell targets with point-projection hard x-ray radiography

We present an application of short-pulse laser-generated hard x rays for the diagnosis of indirectly driven double shell targets. Coneinserted double shell targets were imploded through an indirect drive approach on the upgraded SG-II laser facility. Then, based on thepoint-projection hard x-ray radiography technique, time-resolved radiography of the double shell targets, including that of their near-peakcompression, were obtained. The backlighter source was created by the interactions of a high-intensity short pulsed laser with a metalmicrowire target. Images of the target near peak compression were obtained with an Au microwire. In addition, radiation hydrodynamicsimulations were performed, and the target evolution obtained agrees well with the experimental results. Using the radiographic images, arealdensities of the targets were evaluated.

Accelerated Primal-Dual Projection Neurodynamic Approach With Time Scaling for Linear and Set Constrained Convex Optimization Problems

The Nesterov accelerated dynamical approach serves as an essential tool for addressing convex optimization problems with accelerated convergence rates.Most previous studies in this field have primarily concentrated on unconstrained smooth con-vex optimization problems.In this paper,on the basis of primal-dual dynamical approach,Nesterov accelerated dynamical approach,projection operator and directional gradient,we present two accelerated primal-dual projection neurodynamic approaches with time scaling to address convex optimization problems with smooth and nonsmooth objective functions subject to linear and set constraints,which consist of a second-order ODE(ordinary differential equation)or differential conclusion system for the primal variables and a first-order ODE for the dual vari-ables.By satisfying specific conditions for time scaling,we demonstrate that the proposed approaches have a faster conver-gence rate.This only requires assuming convexity of the objective function.We validate the effectiveness of our proposed two accel-erated primal-dual projection neurodynamic approaches through numerical experiments.

敲除大肠杆菌Lpp基因对动脉粥样硬化的抑制作用研究

为探究大肠杆菌Lpp基因敲除对动脉粥样硬化作用,取8周龄ApoE^(-/-)小鼠分为Control组、Chow_Lpp^(+/+)(C_Lpp^(+/+))组、Chow_Lpp^(-/-)(C_Lpp^(-/-))组、Western Diet_Lpp^(+/+)(W_Lpp^(+/+))组和Western Diet Lpp^(-/-)(W_Lpp^(-/-))组,每周灌胃3次,持续16周后,取小鼠心脏与主动脉;油红及H&E染色主动脉及心脏,观察脂质沉积及炎性变化。研究结果显示,成功构建了动脉粥样硬化小鼠模型;相较于W_Lpp^(+/+)组,W_Lpp^(-/-)组动脉粥样硬化斑块的面积显著减少;小鼠主动脉根部脂质及炎性细胞浸润程度显著降低。这表明敲除Lpp基因后的大肠杆菌对小鼠动脉粥样硬化具有缓解作用。

REFINEMENTS OF THE NORM OF TWO ORTHOGONAL PROJECTIONS

In this paper,some refinements of norm equalities and inequalities of combination of two orthogonal projections are established.We use certain norm inequalities for positive contraction operator to establish norm inequalities for combination of orthogonal projections on a Hilbert space.Furthermore,we give necessary and sufficient conditions under which the norm of the above combination of o`rthogonal projections attains its optimal value.

基于自适应LPP特征降维和改进VPMCD的滚动轴承故障诊断

针对机械系统状态监测与故障诊断中存在的故障特征维数较高及模式识别导致的耗时较高问题,提出了一种基于自适应局部保持投影(Locality Preserving Projection,LPP)特征降维和改进多变量预测模型(Variable Predictive Model based Class Discriminate,VPMCD)的故障诊断方法。首先,从滚动轴承振动信号中提取时频域特征、能量特征,以及复杂度特征组成高维故障特征数据集;其次,利用自适应LPP方法对高维故障特征数据集进行降维处理,得到低维敏感故障特征;最后,采用改进VPMCD方法对低维敏感故障特征进行分类识别,进而判断故障类型。通过滚动轴承故障诊断试验分析表明,自适应LPP方法克服了传统LPP方法需要人工选取参数的缺陷,在获得低维敏感故障特征的基础上具有较少计算时间,相比主成分分析(Principal Component Analysis,PCA)、局部切空间排列(Local Tangent Space Alignment,LTSA)、线性局部切空间排列(Linear Local Tangent Space Alignment,LLTSA)、等距特征映射(Isometric Mapping,Isomap),以及局部线性嵌入(Locally Linear Embedding,LLE)等算法具有明显的优势;改进VPMCD方法可克服人工选择模型的偶然性和片面性,在滚动轴承10种故障状态的识别中获得了99.4%的诊断精度,相比优化参数支持向量机方法提高了故障诊断效率,大大降低了识别时间,具有一定的优越性。

Cascading multi-segment rupture process of the 2023 Turkish earthquake doublet on a complex fault system revealed by teleseismic P wave back projection method

In this study,the vertical components of broadband teleseismic P wave data recorded by China Earthquake Network are used to image the rupture processes of the February 6th,2023 Turkish earthquake doublet via back projection analysis.Data in two frequency bands(0.5-2 Hz and 1-3 Hz)are used in the imaging processes.The results show that the rupture of the first event extends about 200 km to the northeast and about 150 km to the southwest,lasting~90 s in total.The southwestern rupture is triggered by the northeastern rupture,demonstrating a sequential bidirectional unilateral rupture pattern.The rupture of the second event extends approximately 80 km in both northeast and west directions,lasting~35 s in total and demonstrates a typical bilateral rupture feature.The cascading ruptures on both sides also reflect the occurrence of selective rupture behaviors on bifurcated faults.In addition,we observe super-shear ruptures on certain fault sections with relatively straight fault structures and sparse aftershocks.

How do lateral septum projections to the ventral CA1 influence sociability?

Social dysfunction is a risk factor for several neuropsychiatric illnesses.Previous studies have shown that the lateral septum(LS)-related pathway plays a critical role in mediating social behaviors.Howeve r,the role of the connections between the LS and its downstream brain regions in social behavio rs remains unclea r.In this study,we conducted a three-chamber test using electrophysiological and chemogenetic approaches in mice to determine how LS projections to ventral CA1(vCA1)influence sociability.Our res ults showed that gamma-aminobutyric acid(GABA)-e rgic neuro ns were activated following social experience,and that social behavio rs were enhanced by chemogenetic modulation of these neurons.Moreover,LS GABAergic neurons extended their functional neural connections via vCA1 glutamatergic pyramidal neurons,and regulating LSGABA→vCA1Gluneural projections affected social behaviors,which were impeded by suppressing LSprojecting vCA1 neuronal activity or inhibiting GABAAreceptors in vCA1.These findings support the hypothesis that LS inputs to the vCA1 can control social prefe rences and social novelty behaviors.These findings provide new insights rega rding the neural circuits that regulate sociability.

Computational Quantification of Map Projection Distortion by Fractal Dimension of Coastlines

Maps, essential tools for portraying the Earth’s surface, inherently introduce distortions to geographical features. While various quantification methods exist for assessing these distortions, they often fall short when evaluating actual geographic features. In our study, we took a novel approach by analyzing map projection distortion from a geometric perspective. We computed the fractal dimensions of different stretches of coastline before and after projection using the divide-and-conquer algorithm and image processing. Our findings revealed that map projections, even when preserving basic shapes, inevitably stretch and compress coastlines in diverse directions. This analysis method provides a more realistic and practical way to measure map-induced distortions, with significant implications for cartography, geographic information systems (GIS), and geomorphology. By bridging the gap between theoretical analysis and real-world features, this method greatly enhances accuracy and practicality when evaluating map projections.

Multi-Criteria Wildfire Risk Hazard Assessment in GIS Environment: Projection for the Future and Impact on RES Projects Installation Planning

It is alarming for the fact that Wildfires number, severity and consequently impact have significantly increased during the last years, an aftermath of the Climate Change. One of the most affected areas worldwide is Mediterranean, due to the unique combination of its type of vegetation and demanding climatic conditions. This research is focused on the Region of Epirus in Greece, an area with significant natural vegetation and a range of geomorphological aspects. In order to estimate the Wildfire Risk Hazard, several factors have been used: geomorphological (slope, aspect, elevation, TWI, Hydrographic network), social (Settlements and landfils, roads, overhead lines and substations), environmental (land cover) and climatic (Fire Weather Index). Through a multi-criteria decision analysis (MCDA) and an analytic hierarchy process (AHP) in a GIS environment, the Wildfire Risk Hazard has been estimated not only for current conditions but also for future projections for the near future (2031-2060) and the far future (2071-2100). The selected case study includes the potential impact of the Wildfires to the installed (or targeted to be installed) RES projects in the studied region.

基于KLPP-K-means-BiLSTM的台区短期电力负荷预测

随着智能电网的发展,各场景的用电更加多元化,而准确的台区负荷预测是确保相关电力部门制定合适检修任务的关键,同时为有序用电、电网经济运行提供重要参考。为了挖掘台区负荷的特征以提高台区负荷预测的精度,提出了一种基于核主元分析与局部保持投影降维、K均值聚类算法(K-means)以及双向长短时记忆网络(BiLSTM)的台区电力负荷预测方法。首先利用核局部保持投影(KLPP)对台区多特征负荷数据进行降维以提取主要特征信息;然后采取K-means聚类算法将相似特征的数据归类成各自的簇集;最后针对聚类后的各典型类型,有针对性地训练BiLSTM,并选取中国某高校低压台区负荷作为算例与其他经典预测方法进行对比分析,结果表明所提方法更拟合实际负荷走向,有效提升了预测效果。

基于RMDLPP的雷达空中目标分类

针对鉴别局部保持投影(discriminant locality preserving projections, DLPP)在窄带雷达目标数据降维时出现的类内离散度矩阵奇异和对孤立点敏感进而导致类别之间可分性弱的问题,提出了基于鲁棒性边界DLPP(robust margin DLPP, RMDLPP)的窄带雷达空中目标分类方法。首先,在计算样本之间距离时将两样本点的欧氏距离与同类样本均值相关联。然后,挑选一定数量的边界样本点进行处理并对优化DLPP目标函数进行降维。最后,使用高性能分类器对降维后的数据进行区分,实现对空中目标的分类。通过对X波段对空警戒雷达实测数据的对比实验表明,所提方法具有更好的分类准确率和对孤立点的鲁棒性。

基于Projection VOF方法的熔模铸造蜡模充型过程数值模拟

针对熔模铸造蜡模充型过程数值模拟软件自主开发,建立了流动场和温度场数学模型,采用Cross-WLF粘度模型描述蜡料的流变性能,基于Projection VOF方法进行蜡料流动过程速度场、压力场以及自由表面的求解。通过试验测量获取了K512型蜡料的热物理性能和流变性能的相关数据,拟合得到粘度模型参数。分别在蜡料常粘度和变粘度模型两种条件下对扳机铸件蜡模充型过程进行模拟,结果表明,所建立蜡模充型过程数学模型能较好地描述蜡料的动态流变特性和传热行为。

KLPP特征约简与RELM的高压隔膜泵单向阀故障诊断

为此提出基于核局部保持投影(KLPP)和正则化极限学习机(RELM)的高压隔膜泵单向阀故障诊断方法。首先,提取单向阀振动信号的时域、频域、时频域特征,构建多域特征集;然后,通过KLPP算法对构建的多域特征集进行维数约简;最后,建立基于RELM的故障诊断模型,用于识别单向阀运行状态。实验结果表明,基于多域特征的故障诊断方法检测精度高于单域特征识别方法;KLPP约简多域特征集,可以有效消除信息冗余;建立的RELM故障诊断模型识别精度达到98.89%,能够有效识别高压隔膜泵单向阀故障类型。

多信息融合的LPP算法

针对原始局部保持投影(LPP:Local Preserving Projection)算法难以准确获取非均匀高维数据的局部流形结构且未利用样本类别信息的缺陷,提出一种多信息融合的局部保持投影算法(MIF-LPP:Multi-Information Fusion Local Preserving Projection)。该算法使用改进后的标准欧氏距离获取样本的近邻和互邻信息,降低了样本点分布不均和不同维度数据量纲差异的影响。通过融合样本的类别信息构造权值矩阵,进而获得数据的低维本质流形。最后,分别在CWRU(Case Western Reserve University)数据集和本实验室轴承数据集上验证该算法的有效性。实验结果表明,MIF-LPP算法的特征提取性能明显优于其他算法,并且对邻域值具有鲁棒性。

CMIP6 Evaluation and Projection of Precipitation over Northern China:Further Investigation

Based on 20 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),this article explored possible reasons for differences in simulation biases and projected changes in precipitation in northern China among the allmodel ensemble(AMME),“highest-ranked”model ensemble(BMME),and“lowest-ranked”model ensemble(WMME),from the perspective of atmospheric circulations and moisture budgets.The results show that the BMME and AMME reproduce the East Asian winter circulations better than the WMME.Compared with the AMME and WMME,the BMME reduces the overestimation of evaporation,thereby improving the simulation of winter precipitation.The three ensemble simulated biases for the East Asian summer circulations are generally similar,characterized by a stronger zonal pressure gradient between the mid-latitudes of the North Pacific and East Asia and a northward displacement of the East Asian westerly jet.However,the simulated vertical moisture advection is improved in the BMME,contributing to the slightly higher performance of the BMME than the AMME and WMME on summer precipitation in North and Northeast China.Compared to the AMME and WMME,the BMME projects larger increases in precipitation in northern China during both seasons by the end of the 21st century under the Shared Socioeconomic Pathway 5-8.5(SSP5-8.5).One of the reasons is that the increase in evaporation projected by the BMME is larger.The projection of a greater dynamic contribution by the BMME also plays a role.In addition,larger changes in the nonlinear components in the BMME projection contribute to a larger increase in winter precipitation in northern China.

基于LPP特征空间重构的故障检测策略

针对多模态工业过程数据中存在方差差异显著的问题,提出了一种基于LPP特征空间重构的故障检测策略.首先,采用局部保持投影对过程数据进行降维处理,去除数据的冗余信息和噪声,降低计算复杂度;其次,将变分高斯混合模型应用于过程数据,确定操作模式的数量,并对每种模式下的数据进行聚类;再次,将每种模式下的数据利用所属模式的信息进行标准化处理,去除数据的多模态特征;最后,使用统计量T^(2)对过程进行监控.通过一个多模态数值例子和半导体蚀刻过程验证了所提方法的有效性.

融合PCA-LPP与DBSCAN的道路交通事故分类及风险等级预测方法

道路交通事故是全球范围内造成大量人员伤亡和财产损失的重大问题之一,通过对道路交通事故进行分类和风险等级预测,能够锁定高风险车辆,以减小事故的发生和人员伤亡的概率。交通事故往往由环境、天气、道路条件、路段设施等多维特征相互作用形成,现有的事故影响分析方法缺乏对交通事故数据的综合研究。为此本文提出1种交通事故分类模型,在传统PCA算法的基础上通过衡量各等级数据间的相似性对数据集进行二次降维,采用改进后降维算法PCA-LPP处理大规模交通事故数据集;利用DBSCAN算法对事故数据划分风险区域,根据迭代训练出的各等级空间对模拟车辆环境进行风险划分。试验结果表明:在大规模交通数据降至不同维度的对比实验中,证明PCA-LPP算法使降维后的特征与样本的类别相关程度更高;同时,利用基于密度的DBSCAN聚类算法处理复杂且伴有偶发性的交通事故数据时,算法的纯度为0.942 9、兰德指数为0.946 2,互信息指数为0.678 4,与K-means、谱聚类等传统算法结果相比,DBSCAN算法的各项评估指标均高于其他算法,从分类效果图发现该模型减少了噪声数据的影响;最后,通过消融实验验证了带有二次降维的PCA-LPP算法的各项评估指标均为最高。其预测结果的混淆矩阵显示该模型对各风险等级的精确率分别为85.77%、70.78%、80.65%,验证了模型的有效性与实用性。

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

Molecular mechanisms of lesion-induced axonal sprouting in the corticofugal projection:the role of glial cells

After injury of the central nervous system(CNS),neuronal circuits are known to remodel for functional recovery.In general,there are two strategies for the remodeling:axonal regeneration and sprouting(Figure 1A).Axonal regeneration is re-growth of injured neurons themselves,but axons hardly regenerate in the adult mammalian CNS(Silver and Miller,2004).On the other hand,axonal sprouting is new growth from intact or spared neurons to the denervated target by forming axon collaterals,compensating for damaged circuits.This process is a more effective way for circuit remodeling,as it does not necessarily require long axonal elongation.