Multifunctional fibrous wound dressings for refractory wound healing

Refractory wounds have always been an important issue to healthcare systems, whose healing process is always delayed by multiple factors, including bacterial infections, chronic inflammation, and excessive exudates, etc. Employing multifunctional wound dressings is recognized as an effective strategy to deal with refractory wounds, which has yielded promising outcomes in recent years. Among these advanced wound dressings, fibrous dressings have gained growing attention due to their unique merits. Such wound dressings have demonstrated great potential in delivering theranostic agents, such as antibacterial agents, anti-inflammatory drugs, growth factors, and diagnostic probes, etc., for the purposes of accelerating wound healing. This paper reviews the development of multifunctional fibrous dressings and their applications in treating refractory wounds. The construction approaches of novel fibrous dressing with capabilities of antibacterial, anti-inflammation, exudate management and diagnosis were also introduced. Furthermore, the existing problems and challenges are also discussed briefly.     

高校实验室计算机网络故障诊断技术研究

为了提升高校实验数据处理水平,高校实验室的相关建设工作已经步入正轨,但层出不穷的信息安全问题也向高校实验室计算机网络维护工作提出了新的挑战。文章从现阶段高校实验室计算机网络的相关建设工作出发,简要论述引发网络故障的具体原因,并对其诊断技术进行探讨。     

A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

多传感器目标的模糊识别

根据模糊理论，采用信息融合技术和模糊识别技术，讨论了在多类传感器网内进行多目标模糊识别的一般原理和方法。     

平面近场测试系统在天线测试和诊断中的应用

介绍了天线近场测量的基本原理和HD-1型平面近场测试系统,并对近场测量在实际天线测试中的应用情况、发展方向和应用前景等作了简单的描述。     

蓝牙技术在某型飞机机载火控故障诊断系统中的应用研究

蓝牙技术是一种短距离无线通信技术,具有低成本、低功耗、灵活、快速、抗干扰能力强等特点,目的是取代终端的连接电缆.为提高部队的作战效能,采用蓝牙技术和计算机测量与控制技术,研制了机载火控故障诊断系统;该系统在实际应用中取得了良好效果,并具有诊断结果准确、自动化程度高、工作稳定可靠、操作简便、易于转移和维护等优点,为技术人员进行机载火控系统的性能检测与故障诊断提供了便利.     

多目标优化发射层析算法在等离子体场光谱诊断中的应用

提出一种基于多目标优化原理的发射光谱层析(EST)图像重建新算法MCIRT.通过计算机数值 模拟，考察了该算法对非对称发射系数场分布的重建效果.结果表明，与传统层析算法相比 ，MCIRT算法具有收敛快，重建精度高的优势，适合于非完全数据情况下的等离子体发射系 数场重建，并且实时性更好.作为一个应用实例, 运用谱线相对强度法重建了自由电弧等离 子体的三维温度及粒子数密度分布. 关键词： 等离子体诊断 图像重建     

利用相干渡越辐射测量电子束团长度的分析与计算

利用相干渡越辐射(CTR)测量短和超短电子束团长度是国际上束测领域新发展的频域测量技术.文中理论分析和数值计算了北京自由电子激光装置的皮秒级的射频电子束团序列产生的CTR,当辐射波长在长于束长(4ps)时,渡越辐射发生相干增强效应;与非相干渡越辐射相比,当λ≥2πσz时,增强的倍数约等于束团中粒子的数目(10⁸);CTR从亚毫米波到毫米波段呈宽带连续谱特性;渡越辐射能量主要集中在轴线附近,宏脉冲辐射能量高达几毫焦.设计采用偏振型束团长度测量系统,利用CTR自相关技术,实验测量该束团序列的纵向长度,并藉助傅里叶变换光谱法,推求束团电子分布.     

心理素质诊断模型的建立与应用

综合运用国内外多种测量量表对大学生的心理素质进行诊断与测试 ,并应用多元统计分析方法对其心理素质结构主因素进行定量分析 ,在此基础上建立了心理素质诊断模型 ,并运用该模型对实际问题进行了分析 .