基于.NET架构高校教学资源库系统研究

.NET的架构下的高校教师信息管理的实现,接着讲解.NET的架构下的学生信息管理的实现,最后说明.NET的架构的学生作业管理系统的实现,还介绍了NET的架构的跨校区合作、交流的实现。     

Forest harvesting in rural properties: Risks and worsening to the worker’s health under the ergonomics approach

Through an ergonomic approach, this study aimed to evaluate whether workers involved in forest harvesting activities in rural properties are subject to the development of work-related diseases, as well as their consequences. A cross-sectional study with 267 forest workers in rural properties in the Brazilian Central region was used. The following evaluations were performed for each of the activities (felling, delimbing, tracing, manual extraction and manual loading): physical workload evaluation; biomechanical evaluation; risk of repetitive strain injuries/work-related musculoskeletal disorders; environmental noise and vibration factors, where relevant, and thermal overload through the Wetbulb Globe Temperature index. The results showed that in general the physical workload was very high, exceeding the cardiovascular load limits and adding to the need for work reorganization. All activities exposed workers to serious and imminent risks of developing injuries to the spine and lower limbs. Likewise, in general the risk of the appearance of RSI/WMSDs was very high for all activities evaluated. Such results are due to the combination of organizational work factors and factors of the work environment such as exposure to bad weather, uneven terrain, lifting and handling loads above tolerable limits, excessive noise and thermal overload. All of this allows to conclude that ergonomic risks and workers’ health hazards in forest harvesting in rural properties are latent and very worrying, and that these workers are exposed to a form of labor exploitation that invariably leads to physical and emotional exhaustion and therefore to their decreased labor capacity and useful working life.     

A CALPHAD-type Young's modulus database of Ti-rich Ti–Nb–Zr–Mo system

Accurate Young's modulus is the necessity for the design of biomedical Ti alloys. A combinatorial method of the diffusion couple, nanoindentation, electron probe microanalysis (EPMA), and CALculation of PHAse Diagrams (CALPHAD) techniques has been utilized to construct the Young's modulus database of Ti alloys with various compositions in the present work. Two groups of body-centered cubic (bcc) Ti–Nb–Zr–Mo quaternary diffusion couples annealed at 1273 K for 25 h were experimentally prepared. Subsequently, the composition-dependent mechanical properties in the wide compositional range of Ti-based alloys were obtained by using EPMA and nanoindentation probes. Finally, on the basis of the measured Young's moduli in the present and previous work and the modeling parameters of Young's modulus of Ti–Nb–Zr system, the Young's modulus database of bcc Ti–Nb–Zr–Mo system was established through the CALPHAD approach. The CALPHAD-type database of bcc Ti–Nb–Zr–Mo system can provide the accurate Young's moduli of Ti alloys with wide compositions.     

A new time invariant fuzzy time series forecasting method based on particle swarm optimization

In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignored. Thus, in defiance of fuzzy set theory, fuzzy sets’ elements with the highest membership value are only considered. This situation causes information loss and decrease in the explanation power of the model. To deal with these problems, a novel time invariant fuzzy time series forecasting approach is proposed in this study. In the proposed method, membership values in the fuzzy relationship matrix are computed by using particle swarm optimization technique. The method suggested in this study is the first method proposed in the literature in which particle swarm optimization algorithm is used to determine fuzzy relations. In addition, in order to increase forecasting accuracy and make the proposed approach more systematic, the fuzzy c-means clustering method is used for fuzzification of time series in the proposed method. The proposed method is applied to well-known time series to show the forecasting performance of the method. These time series are also analyzed by using some other forecasting methods available in the literature. Then, the results obtained from the proposed method are compared to those produced by the other methods. It is observed that the proposed method gives the most accurate forecasts.     

Probability densities for conditional statistics in the cubic sensor problem

This paper applies the techniques of Malliavin’s stochastic calculus of variations to Zakai’s equation for the one-dimensional cubic sensor problem in order to study the existence of densities of conditional statistics. Let {X _t} be a Brownian motion observed by a cubic sensor corrupted by white noise, and let denote the unnormalized conditional estimate of φ(X _i ). If φ₁,...,φ _n are linearly independent, and if , it is shown that the probability distribution of admits a density with respect to Lebesgue measure for anyn. This implies that, at any fixed time, the unnormalized conditional density cannot be characterized by a finite set of sufficient statistics. Research supported in part by NSF Grant No. MCS-8301880 and by the Institute for Mathematics and It Applications, Minneapolis, Minnesota.     

The Neurovascular Unit Dysfunction in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disease worldwide. Histopathologically, AD presents with two hallmarks: neurofibrillary tangles (NFTs), and aggregates of amyloid β peptide (Aβ) both in the brain parenchyma as neuritic plaques, and around blood vessels as cerebral amyloid angiopathy (CAA). According to the vascular hypothesis of AD, vascular risk factors can result in dysregulation of the neurovascular unit (NVU) and hypoxia. Hypoxia may reduce Aβ clearance from the brain and increase its production, leading to both parenchymal and vascular accumulation of Aβ. An increase in Aβ amplifies neuronal dysfunction, NFT formation, and accelerates neurodegeneration, resulting in dementia. In recent decades, therapeutic approaches have attempted to decrease the levels of abnormal Aβ or tau levels in the AD brain. However, several of these approaches have either been associated with an inappropriate immune response triggering inflammation, or have failed to improve cognition. Here, we review the pathogenesis and potential therapeutic targets associated with dysfunction of the NVU in AD.     

Biflavonoid-Induced Disruption of Hydrogen Bonds Leads to Amyloid-β Disaggregation

Deposition of amyloid β (Aβ) fibrils in the brain is a key pathologic hallmark of Alzheimer’s disease. A class of polyphenolic biflavonoids is known to have anti-amyloidogenic effects by inhibiting aggregation of Aβ and promoting disaggregation of Aβ fibrils. In the present study, we further sought to investigate the structural basis of the Aβ disaggregating activity of biflavonoids and their interactions at the atomic level. A thioflavin T (ThT) fluorescence assay revealed that amentoflavone-type biflavonoids promote disaggregation of Aβ fibrils with varying potency due to specific structural differences. The computational analysis herein provides the first atomistic details for the mechanism of Aβ disaggregation by biflavonoids. Molecular docking analysis showed that biflavonoids preferentially bind to the aromatic-rich, partially ordered N-termini of Aβ fibril via the π–π interactions. Moreover, docking scores correlate well with the ThT EC₅₀ values. Molecular dynamic simulations revealed that biflavonoids decrease the content of β-sheet in Aβ fibril in a structure-dependent manner. Hydrogen bond analysis further supported that the substitution of hydroxyl groups capable of hydrogen bond formation at two positions on the biflavonoid scaffold leads to significantly disaggregation of Aβ fibrils. Taken together, our data indicate that biflavonoids promote disaggregation of Aβ fibrils due to their ability to disrupt the fibril structure, suggesting biflavonoids as a lead class of compounds to develop a therapeutic agent for Alzheimer’s disease.     

高空作业平台臂架伸缩运动的横向振动特性

为了探究高空作业平台做伸缩运动时变幅平面内的横向振动动力学特性,针对臂架的实际搭接和支承情况,将臂架等效为根部铰接、中间弹性支承且带有集中参数的变截面变长度梁. 基于牛顿第二定律建立各臂段的运动微分方程,采用模态叠加法、结合边界条件求解臂架一系列时刻的瞬态振型函数,曲线拟合时变参数以近似表示梁的振型,并依据伽辽金截断方法,得到广义坐标下的状态空间方程. 在Matlab/Simulink环境下进行动态仿真,得到伸缩过程中臂架头部的变幅平面横向振动动态响应. 结果表明,就横向振动振幅而言,搭接简化会带来15.63%计算结果误差;支承简化会加大臂架整体刚度、减小臂架振动响应,不可取。     

断层破裂过程对减隔震桥梁地震反应的影响

为了研究断层破裂过程对减隔震桥梁地震反应的影响,提出利用相位特性模拟方向性效应的改进随机格林函数法. 以1994年美国北岭地震的断层条件为例,通过与实际地震记录对比验证模拟方法的有效性;应用改进的随机格林函数法模拟相同震中距离的4组地震动时程作为输入条件,比较断层破裂过程对相同震中距离、不同方位的减隔震桥梁地震反应影响. 结果表明,利用持时包络曲线与相位差分分布的相似性可以方便模拟随机格林函数的地震动加速度时程;在相同震中距离条件下,断层破裂方向的观测点地震动以及对应位置的桥梁结构地震反应明显大于非破裂方向位置的观测点;当破裂方向上地震动时程不具有脉冲特性时,断层周围的减隔震桥梁地震反应主要受地震动强度的影响,桥梁方位的影响不明显.     

管线用钢氢致裂纹(HIC)影响因素分析

研究了管线用钢的化学成分和金相组织对钢的氢致裂纹(HIC)性能的影响。研究认为,带状组织和马氏体含量对HIC性能有很大影响,S含量及Cep对HIC有不同程度影响。含有少量Cu、Ni的钢更适合在酸性环境下使用。