Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions

Distance weighted discrimination (DWD) is an appealing classification method that is capable of overcoming data piling problems in high-dimensional settings. Especially when various sparsity structures are assumed in these settings, variable selection in multicategory classification poses great challenges. In this paper, we propose a multicategory generalized DWD (MgDWD) method that maintains intrinsic variable group structures during selection using a sparse group lasso penalty. Theoretically, we derive minimizer uniqueness for the penalized MgDWD loss function and consistency properties for the proposed classifier. We further develop an efficient algorithm based on the proximal operator to solve the optimization problem. The performance of MgDWD is evaluated using finite sample simulations and miRNA data from an HIV study.     

H2S gas sensor based on integrated resonant dual-microcantilevers with high sensitivity and identification capability

Detection of trace-level hydrogen sulfide (H₂S) gas is of great importance whether in industrial production or disease diagnosis. This research presents a novel H₂S gas sensor based on integrated resonant dual-microcantilevers which can identify and detect trace-level H₂S in real-time. The sensor consists of two integrated resonant microcantilever sensors with different functions. One cantilever sensor can identify H₂S by outputting positive frequency shift signals, while the other cantilever sensor will detect H₂S as a normally used cantilever sensor with negative frequency shifts. Combined the two cantilever sensors, the proposed gas sensor can distinguish H₂S from a variety of common gases, and the detection limit to H₂S of the sensor is as sensitive as below 1 ppb.     

Water‐Soluble Luminescent Hybrid Composites Consisting of Oligosilsesquioxanes and Lanthanide Complexes and their Sensing Ability for Cu2+

Water‐soluble hybrid composites with great potential for selective and sensitive sensing and that are obtained through simple, rapid, and environmentally friendly methods are highly desirable and remain a challenging task. Herein, we present luminescent hybrid composites that were realized by linking Na₃[Ln(dpa)₃] (dpa=2,6‐pyridinedicarboxylic acid) to octa‐amino functionalized polyhedral oligomeric silsesquioxane (POSS‐NH₂) through hydrogen‐bonding interactions between the oxygen atoms of the carboxylate groups of dpa and the hydrogen‐bond‐donor amino groups. The resulting hybrid composites Ln(dpa)₃@POSS‐NH₂ are highly soluble in aqueous solutions and the quantum yield of Eu(dpa)₃@POSS‐NH₂ is as high as 56.5 % or 46.3 % in the solid state and in aqueous solution, respectively, as determined by using the integrating sphere method. The novel water‐soluble luminescent hybrid composites exhibit high thermal and photostability, and the emitted colors of the resulting hybrid composite can be finely tuned by changing the Eu³⁺/Tb³⁺ ratio. Interestingly, Eu(dpa)₃@POSS‐NH₂ hybrid composites exhibited an effective switch‐off fluorescence response to Cu²⁺ over other common metal ions in aqueous media.     

不同抗凝比例对凝血四项检测结果的影响

目的观察并分析凝血四项检测结果与不同比例下的全血与抗凝剂之间的关系。方法研究对象取2015年6月来湖北省宜昌市第二人民医院参加体检的110例健康人员,抽取全血血液样本后按照不同比例与抗凝剂混匀,常规分离血浆并测定受试者凝血酶时间(TT)、凝血酶原时间(PT)、激活部分促凝血酶原激酶时间(APTT)以及纤维蛋白原(FIB),并对研究结果相关数据作统计学处理。结果当血液量与抗凝剂比例为1∶5时,标本TT、PT、APTT以及FIB各项指标较1∶9时差异显著而具有统计学意义(P0.05);抗凝比例1∶7的情况下,TT指标差异与1∶9抗凝比例标本相比差异具有统计学意义(P0.05),而PT、FIB以及APTT三项指标差异并无统计学意义(P0.05);抗凝比例为1∶11与1∶13的情况下,TT指标与1∶9抗凝比例标本相比差异具有统计学意义(P0.05),而PT、FIB以及APTT三项指标差异并无统计学意义(P0.05)。结论凝血四项检测工作中,标本质量检测控制最关键的环节在于准确采集血液量,倘若采集血量过多或过少,导致与抗凝剂比例失调往往会影响测定结果准确性,检验科工作人员应予以重视。     

星载海洋激光雷达最佳工作波长分析

星载激光雷达是实现海洋垂直剖面探测的有效工具,也是目前迫切需求的海洋光学遥感手段。对星载海洋激光雷达的波长参数进行评估对保证探测有效性具有重要意义。本文从探测深度和信噪比两方面分析了星载海洋激光雷达探测全球海洋的最佳波长。利用MODIS 10个波段的水体光学特性数据,估算全球海水探测深度及相应的最优波长;并根据太阳夫琅禾费暗线特性,对信号信噪比进行优化。结果表明:在探测深度方面,最优探测波长在488 nm波段的海洋占全球海洋面积的70%左右,并且全球95%以上的海域在488 nm波段的探测深度优于0.8倍的真光层深度;在信噪比方面,相对于488 nm波段,486.134 nm夫琅禾费暗线处采用0.1 nm带宽的滤光片可以将背景光强度降低70%,相应地回波信噪比整体提升了约5.0%。就全球海洋探测来说,使用486.134 nm作为探测波长可以提高探测深度,有效抑制太阳背景光,提高信噪比,因此,486.134 nm是星载海洋激光雷达的最佳工作波长。     

Novel synthesis of sensor for selective detection of Fe+3 ions under various solvents

Naked-eye colored chemo dosimeter based on vanilline based conjugated sensor was synthesized and characterized. The main point of this paper is that the solvent also affects on selectivity of metals. Vanilline based conjugate sensor exhibited high selectivity and sensitivity for detection of Ferric ions (Fe⁺³) in all (both polar and nonpolar) solvents according to absorbance which can be observed by naked eye. The selectivity was more prominent in nonpolar or less polar solvent due to solubility factor of ions and sensor but not for polar. The detection of limit of the synthesized probes was shown up to 0.84 ppm. The dielectric constant of solvents affected on the complex formation of ligand with transition metal ions. A filter paper strip system was used for rapid monitoring of detection by color variation.     

Determination of cobalt ion based on polyethyleneimine modified silver nanoclustersEI北大核心CSCD

PolyethyleneiminePEImodified silver nanoclustersAg NCswere synthesized through chemical reduction method by using PEI as stabilizerAgNO3 as silve source and ascorbic acid as reducing agentand it was applied to the detection of cobalt ions. It was found that the fluorescence of the silver nanoclusters was quenched by Co2+ for the aggregation of PEI-Ag NCs caused by the coordination between cobalt ion and amino group on polyethyleneimine. Under the optimized experimental conditionsthe fluorescence quenching degree of PEI-Ag NCs was piecewise linear with the concentration of cobalt ion in the range of 8.30×10-7-4.17×10-4 mol/L and the detection limit was 0.41 μµmol/L. © 2022, Youke Publishing Co.,Ltd. All rights reserved.     

基于级联卷积神经网络的前列腺磁共振图像分类

针对深度学习训练成本高，以及基于磁共振图像的前列腺癌临床诊断需要大量医学常识且极为耗时的问题，本文提出了一种基于级联卷积神经网络（Convolutional Neural Network，CNN）和磁共振图像的前列腺癌（Prostate Cancer，PCa）自动分类诊断方法，该网络以Faster-RCNN作为前网络，对前列腺区域进行提取分割，用于排除前列腺附近组织器官的干扰；以基于ResNet改进的网络结构CNN40_bottleneck作为后网络，用于对前列腺区域病变进行分类.后网络由瓶颈结构串联组成，其中使用批量标准化（Batch Normalization，BN）、全局平均池化（Global Average Pooling，GAP）进行优化.实验结果证明，本文方法对前列腺癌诊断结果较好，而且缩减了训练时间和参数量，有效降低了训练成本.     

Vertical copper oxide nanowire arrays attached three-dimensional macroporous framework as a self-supported sensor for sensitive hydrogen peroxide detection

A hierarchical nanostructure consisting of uniform copper oxide nanowires vertically grown on three-dimensional copper framework (CuO NWs/3D-Cu foam) was prepared by a two-step synthetic process. The uniform CuO NWs anchored onto the 3D foam exhibited outstanding electrocatalytic activity towards hydrogen peroxide reduction due to the unique one‐dimensional direction with its excellent catalytic activity and large surface area of 3D substrate, which enhanced electroactive sites and charge conductivity. As a result, a wide linear detection range of 1 µM–1 mM, good sensitivity of 8.87 µA/(mM ⋅ cm²), low detection limit of 0.98 µM, and rapid response time of 5 s to hydrogen peroxide were achieved under a working potential of −0.4 V in phosphate buffer solution (pH of 7.4). In addition, the CuO NWs/3D-Cu foam material showed excellent selectivity to hydrogen peroxide and good resistance against poisonous interferents, including ascorbic acid, dopamine, urea, uric acid, and potassium chloride. Furthermore, the CuO NWs/3D-Cu foam presented good reproducibility, stability, and accurate detection for hydrogen peroxide in real sample; therefore, it may be considered to be a potential free-standing hydrogen peroxide sensor in practical analysis applications.