综放工作面风量及采空区漏风定量检测

通过对中煤塔山煤矿30509综放工作面采空区漏风及有害气体分析的研究，总结了通过定量连续释放SF₆示踪气体，来检测工作面风量与采空区漏风的方法，测定了沿工作面采空区的漏风分布及漏风流线的深度。采用定时测量法，确定了30509工作面随工作面不断推进，与对应地表发生了导通现象；采用定量测量法，确定了内部漏风量和外部漏风量较大，对综采工作面采空区自然发火存在较大风险，同时提出了防范措施，为减少综放工作面采空区漏风、防止自然发火的发生提供了参考。     

提高关联成像重构质量的研究

比较基于压缩感知关联成像(CGI)与伪逆关联成像(PGI)两者之间的成像效果差异,探讨形态学权重自适应对关联成像去除噪声的效果。选择不同的图像,通过MATLAB软件开展仿真实验,对目标图像分别采样64、256、512、1 024、2 048、3 000次,首先通过关联成像、基于压缩感知关联成像与伪逆关联成像三种方法重构图像,再对比压缩感知与伪逆两种方法重构图像的效果,以峰值信噪比(PSNR)、相关系数(CC)为量化指标,将基于压缩感知关联成像与伪逆关联成像在不同采样次数下进行对比分析。同时,通过实验分析形态学权重自适应去除关联成像中噪声的效果。伪逆关联成像在低次数采样的情况下比基于压缩感知关联成像的成像效果更好,在高采样次数下,基于压缩感知关联成像的成像效果更好。在实际重构中压缩感知关联成像重构的图像仍有噪声,形态学权重自适应可以有效去除关联成像实验中产生的噪声。     

固定化生物硅藻土强化CAST工艺处理含盐污水研究

采用9%聚乙烯醇+0.5%海藻酸钠包埋耐盐菌群的固定化生物硅藻土小球投加到循环式活性污泥(CAST)反应器中,对比传统CAST工艺和投加固定化小球的CAST工艺对含盐污水COD和氨氮的去除效果,考察固定化生物硅藻土小球强化CAST工艺处理含盐污水性能。试验结果表明:在相同运行条件下,投加固定化生物硅藻土小球的CAST工艺出水COD、氨氮去除率基本维持在88%和90%以上,与传统CAST工艺相比分别提高了15%和10%。同时,向CAST工艺添加固定化生物硅藻土有助于维持反应器中微生物浓度稳定,提高出水水质及其稳定性。     

支持规避设计的海量专利质量评价模型

专利规避设计需从现有专利中遴选具有核心竞争力的目标专利，以提升技术起点。针对设计领域的海量专利信息，提出了专利质量多指标主客观综合评价模型。分析专利书目信息与专利质量存在的正相关关系，甄选存活期、权利项数、同族专利数、引证数和被引证数等书目信息指标，构建了专利质量多指标综合评价指标体系，提升了评价方法的科学性和可操作性；提出将德尔菲法、层次分析法和均方差决策法相结合的主客观赋权法，确定专利质量评价指标权重，既保证了评价的权威性，又减小了个人偏见与从众妥协等因素的影响；建立了基于质量评价模型遴选目标专利的过程模型，并通过应用实例验证了该模型对遴选具有核心竞争力专利的有效性。     

一种基于压缩感知的运动目标检测技术

运动目标检测是计算机视觉、图像处理等相关领域的研究热点，其核心就是对视频图像中的每一帧图像进行相应的研究和处理。本文主要研究思路是从压缩感知技术采样信号的角度出发，将每一帧的二维图像压缩采样成具有少量信息的一维信号，再通过信号重构用少量数据量将图像重构出来，最后通过目标检测技术对每一帧的图像进行运动目标提取。仿真实验表明该方法是可行和有效的，同时可以大大减少目标检测中所记录的数据量，解决海量数据的存储与传输问题。     

Advancements in the Development of non-BET Bromodomain Chemical Probes

The bromodomain and extra terminal (BET) family of bromodomain-containing proteins (BCPs) have been the subject of extensive research over the past decade, resulting in a plethora of high-quality chemical probes for their tandem bromodomains. In turn, these chemical probes have helped reveal the profound biological role of the BET bromodomains and their role in disease, ultimately leading to a number of molecules in active clinical development. However, the BET subfamily represents just 8/61 of the known human bromodomains, and attention has now expanded to the biological role of the remaining 53 non-BET bromodomains. Rapid growth of this research area has been accompanied by a greater understanding of the requirements for an effective bromodomain chemical probe and has led to a number of new non-BET bromodomain chemical probes being developed. Advances since December 2015 are discussed, highlighting the strengths/caveats of each molecule, and the value they add toward validating the non-BET bromodomains as tractable therapeutic targets.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

基于DRGAN和支持向量机的合成孔径雷达图像目标识别

为解决SAR图像目标识别中样本缺乏和方位角敏感问题,提出了一种基于DRGAN和SVM的SAR图像目标识别算法。首先,采用多尺度分形特征对SAR图像进行增强,经过分割得到目标二值图像,基于Hu二阶矩估计目标的方位角。然后对估计得到的目标方位角进行量化编码,结合原始图像作为输入,对设计的DRGAN模型参数进行训练与优化。由于DRGAN中的深度生成模型将目标姿态与外观表示进行解耦设计,故可利用该模型将SAR图像样本变换到同一方位角区间。基于变换后的训练样本分别提取归一化灰度特征,利用SVM训练分类器。采用MSTAR数据集在多个不同操作条件下对提出的算法进行测试,实验结果表明,在带变体的标准操作条件下,能够达到97.97%的分类精度,优于部分基于CNN模型的分类精度,在4种扩展操作条件下的分类精度分别为97.83%,91.77%,97.11%和97.04%,均优于传统方法的分类精度。在SAR图像目标方位角估计存在一定误差的情况下,训练得到的GAN模型作为SAR图像目标旋转估计器,能够使得在不进行复杂样本预处理的前提下,仍然取得较高的SAR图像目标识别精度。     

基于目标跟踪的变电站隔离开关状态图像识别方法

为解决变电站中隔离开关状态的自动识别问题，提出了基于目标跟踪的开关分合状态图像识别方法。首先，基于隔离开关开合过程的动态视频，通过 Ｌａｓｓｏ正则化稀疏表示的目标跟踪模型对隔离开关运动轨迹进行识别；其次，利用隔离开关２个闸刀之间的距离自动识别算法获得开关的分合状态。实测结果表明，该方法可快速跟踪开关运行轨迹，实时对变电站中隔离开关状态进行准确识别。     

A Colorimetric Artificial Olfactory System for Airborne Improvised Explosive Identification

The detection of ultralow or nonvolatile target analytes remains a significant challenge for artificial olfactory systems even after decades of development, which severely limits their widespread application. To overcome this challenge, an artificial olfactory system based on a colorimetric hydrogel array is constructed for the first time as a universal representative. As an effective extension of conventional artificial olfactory systems that integrates the merits of its predecessors, the proposed system accurately mimics olfactory mucosa and specific odorant binding proteins using hydrogels endowed with specific colorimetric reagents for the detection of hypochlorite, chlorate, perchlorate, urea, and nitrate. Therefore, the proposed system is capable of detecting and discriminating between these five airborne improvised explosive microparticulates with a detection limit as low as 39.4 pg. Additionally, the system demonstrates good reusability over ten cycles, rapid response time of ≈0.2 s, and excellent discrimination properties, despite significant variation. This proof-of-concept study on colorimetric artificial olfactory systems yields a novel strategy for the direct and discriminative detection of nonvolatile airborne microparticulates.