Quantification of Dendritic Spines Remodeling under Physiological Stimuli and in Pathological Conditions

Numerous brain diseases are associated with abnormalities in morphology and density of dendritic spines, small membranous protrusions whose structural geometry correlates with the strength of synaptic connections. Thus, the quantitative analysis of dendritic spines remodeling in microscopic images is one of the key elements towards understanding mechanisms of structural neuronal plasticity and bases of brain pathology. In the following article, we review experimental approaches designed to assess quantitative features of dendritic spines under physiological stimuli and in pathological conditions. We compare various methodological pipelines of biological models, sample preparation, data analysis, image acquisition, sample size, and statistical analysis. The methodology and results of relevant experiments are systematically summarized in a tabular form. In particular, we focus on quantitative data regarding the number of animals, cells, dendritic spines, types of studied parameters, size of observed changes, and their statistical significance.     

Reducing the complexity of distance measurement methods for circular turbo codes that use structured interleavers

The knowledge of turbo code's minimum Hamming distance (d_min) and its corresponding codeword multiplicity (A_min) is of a great importance because the error correction capability of a code is strongly tied to the values of d_min and A_min. Unfortunately, the computational complexity associated with the search for d_min and A_min can be very high, especially for a turbo code that has high d_min value. This paper introduces some useful properties of turbo codes that use structured interleavers together with circular encoding. These properties allow for a significant reduction of search space and thus reduce significantly the computational complexity associated with the determination of d_min and A_min values. © 2014 The Authors. International Journal of Communication Systems published by John Wiley & Sons, Ltd.     

Mimicking the Brain Extracellular Matrix in Vitro: A Review of Current Methodologies and Challenges

The brain's extracellular matrix (ECM), a 3-dimensional macromolecular network that supports cell growth and viability, has crucial roles in homeostasis and disease. Accurate recapitulation of the chemical, structural, and mechanical properties of the ECM in brain cell cultures is essential for the development of translatable in vitro models; however, thus far, this task has proven highly challenging. This review provides an in-depth discussion of this challenge, including an overview of the properties of the ECM that in vitro models should endeavour to capture, a survey of ECM analogues that are currently used for this purpose, and a discussion of the main hindrances to developing more effective ECM-like coating materials.     

Optimal weighed Holoentropy for video compression: an advanced HEVC

ABSTRACT

In recent times, the applications of multimedia are rising in a greedy mode and hence the amount of video transactions is also increasing exponentially. This has shouted great demands on effective models on video encoding and also for reducing the transmission channel congestion. This research work introduces a managing technique termed weighted encoding for High-Efficiency Video Coding (HEVC). HEVC, also termed as MPEG-H Part 2 and H.265 is a video compression standard that is widely utilized AVC (H.264 or MPEG-4 Part 10). When compared to AVC, HEVC grants double the ratio of data compression at a similar level of quality of the video or considerably enhanced video quality at a similar bit rate. This work intends to optimize the weight that adopted in HEVC for encoding. For this, this paper proposes a new Iterative based propagation update in the water wave Optimization Algorithm (IPU-WWO), which is the improved form of Water wave Optimization (WWO). The performance of proposed IPU-WWO is compared over other conventional methods like Artificial Bee Colony (ABC), Firefly (FF), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) with respect to Peak Signal to Noise Ratio (PSNR). By doing the encoding process, it minimizes the video size with perceptually better quality video or PSNR.     

工业雷管激光编码自动生产线的开发

按工业雷管编码生产工艺要求,采用先进的机电一体化技术设计制造工业雷管激光编码自动生产线。该生产线采用PLC和触摸屏控制操作,计算机配合管理,并备有多点视频监控。经调试及试生产,达到了设计要求。     

应用误吸风险评估及饮食分级护理预防听神经瘤术后误吸

目的：探讨饮食分级护理和预防听神经瘤术后患者进食误吸的护理效果。方法将100例听神经瘤术后患者按入院时间排序分为干预组（2015年7~12月,50例）和对照组（2015年1~6月,50例）。对照组按照常规护理,干预组术后采用吞误吸风险等级划分,并在此基础上根据误吸风险等级实施饮食分级护理。比较两组患者干预期间进食时误吸发生情况。结果在干预前,两组术后误吸风险比较,差异无统计学意义（P﹥0.05）。干预后,对照组共发生误吸20次,误吸发生率为5.60％,其中呛咳18次,噎食3次,窒息1次;干预组共发生误吸8次,误吸发生率为0.94％,其中呛咳5次,噎食2次,无窒息发生。两组误吸发生率比较差异有统计学意义（ P＜0.01）。结论对听神经瘤术后患者行误吸风险分级,并实施相应的饮食分级护理措施,可有效降低误吸风险,。     

二维码位流长度最小化算法

目的 快速响应矩阵码(quick response code,QR code)简称二维码,是一种由深色和浅色模块组成的正方形符号。给定输入数据,不同编码算法可能输出不同的位流。位流长度决定了二维码的版本,进而决定了二维码每条边上的模块数量。减小二维码的版本能够在不减小模块大小的前提下节省面积,或者在不改变面积的前提下增大模块大小。为了减小二维码面积、提高二维码识读率,本文提出了位流长度最小化算法。方法 首先,根据二维码位流可以分段切换编码模式的特点,归纳了6种编码状态;然后,根据二维码位流编码标准推导了状态转移关系,从而将位流长度最小化问题转换成动态规划问题;最后,通过求解动态规划问题,计算出最短位流。针对统一资源定位符(uniform resource locator,URL)类型数据,利用其部分字段对大小写不敏感、部分字段可以转义的性质,提出了统一资源定位符的最短位流计算算法,进一步缩短位流。结果 本文构建了一个测试集,包含603个编码了非URL数据的二维码,以及1 679个编码了URL数据的二维码。实验结果表明,本文算法与二维码标准相比,对于非URL测试集,位流长度减小的二维码占比9.1%,版本减小的二维码占比1.2%;对于URL测试集,位流长度减小的二维码占比98.4%,版本减小的二维码占比31.7%。结论 二维码位流长度最小化算法输出的位流长度最短,输出的二维码版本最小,能在兼容标准二维码解码器且不影响纠错能力的前提下提升二维码的数据容量。同时,本文算法运行速度快,易于使用,没有需要调节的参数。     

The Discovery of Potentially Selective Human Neuronal Nitric Oxide Synthase (nNOS) Inhibitors: A Combination of Pharmacophore Modelling,CoMFA, Virtual Screening and Molecular Docking Studies

Neuronal nitric oxide synthase (nNOS) plays an important role in neurotransmission and smooth muscle relaxation. Selective inhibition of nNOS over its other isozymes is highly desirable for the treatment of neurodegenerative diseases to avoid undesirable effects. In this study, we present a workflow for the identification and prioritization of compounds as potentially selective human nNOS inhibitors. Three-dimensional pharmacophore models were constructed based on a set of known nNOS inhibitors. The pharmacophore models were evaluated by Pareto surface and CoMFA (Comparative Molecular Field Analysis) analyses. The best pharmacophore model, which included 7 pharmacophore features, was used as a search query in the SPECS database (SPECS^®, Delft, The Netherlands). The hit compounds were further filtered by scoring and docking. Ten hits were identified as potential selective nNOS inhibitors.