架空线路故障快速自动研判系统研究及应用*

基于输电线路雷击故障跳闸频发,而线路运行环境恶劣,导致故障跳闸后巡线工作量大、效率低的问题,开发了一套架空线路故障快速自动研判系统,通过在线监测故障行波的方式快速定位线路故障.该系统已应用于商洛供电公司,并成功诊断了一起故障跳闸事件.     

基于多源多维度用能数据的用户标签萃取方法研究

随着电力行业数字化、智能化水平稳步提升,电力公司利用大数据技术精准识别用户需求、掌握用户用能规律,进而满足用户多样化的用能需求成为营造良好用电体验的关键.为此提出一种基于多源多维度用能数据的用户标签萃取方法,旨在通过采用模糊C均值聚类算法进行标签聚类、用户智能画像,更好支撑用户用电行为掌握、精准营销策略执行,辅助制定电力需求侧响应策略,推动电力服务质效提升.     

外饰喷涂件用基材与底漆特性对橘皮的影响

分别从底漆粗糙度、溶剂溶解度参数、塑料基材耐溶剂性等方面对外饰件漆膜橘皮的影响因素进行了分析和讨论,提出了相应的优化措施.     

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Toona sinensis Leaves Using Terahertz Imaging Combined with Deep Learning

Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in plants, it poses great challenges for practical identification. This study proposed a state-of-the-art method for the rapid identification of trace (10 mg·L⁻¹) and multiple similar benzimidazole pesticide residues on the surface of Toona sinensis leaves, mainly including benzoyl (BNL), carbendazim (BCM), thiabendazole (TBZ), and their mixtures. The new method combines high-throughput terahertz (THz) imaging technology with a deep learning framework. To further improve the model reliability beyond the THz fingerprint peaks (BNL: 0.70, 1.07, 2.20 THz; BCM: 1.16, 1.35, 2.32 THz; TBZ: 0.92, 1.24, 1.66, 1.95, 2.58 THz), we extracted the absorption spectra in frequencies of 0.2–2.2 THz from images as the input to the deep convolution neural network (DCNN). Compared with fuzzy Sammon clustering and four back-propagation neural network (BPNN) models (TrainCGB, TrainCGF, TrainCGP, and TrainRP), DCNN achieved the highest prediction accuracies of 100%, 94.51%, 96.26%, 94.64%, 98.81%, 94.90%, 96.17%, and 96.99% for the control check group, BNL, BCM, TBZ, BNL + BCM, BNL + TBZ, BCM + TBZ, and BNL + BCM + TBZ, respectively. Taking advantage of THz imaging and DCNN, the image visualization of pesticide distribution and residue types on leaves was realized simultaneously. The results demonstrated that THz imaging and deep learning can be potentially adopted for rapid-sensing detection of trace multi-residues on leaf surfaces, which is of great significance for agriculture and food safety.     

Inhalational Anesthetics Inhibit Neuroglioma Cell Proliferation and Migration via miR-138, -210 and -335

Inhalational anesthetics was previously reported to suppress glioma cell malignancy but underlying mechanisms remain unclear. The present study aims to investigate the effects of sevoflurane and desflurane on glioma cell malignancy changes via microRNA (miRNA) modulation. The cultured H4 cells were exposed to 3.6% sevoflurane or 10.3% desflurane for 2 h. The miR-138, -210 and -335 expression were determined with qRT-PCR. Cell proliferation and migration were assessed with wound healing assay, Ki67 staining and cell count kit 8 (CCK8) assay with/without miR-138/-210/-335 inhibitor transfections. The miRNA downstream proteins, hypoxia inducible factor-1α (HIF-1α) and matrix metalloproteinase 9 (MMP9), were also determined with immunofluorescent staining. Sevoflurane and desflurane exposure to glioma cells inhibited their proliferation and migration. Sevoflurane exposure increased miR-210 expression whereas desflurane exposure upregulated both miR-138 and miR-335 expressions. The administration of inhibitor of miR-138, -210 or -335 inhibited the suppressing effects of sevoflurane or desflurane on cell proliferation and migration, in line with the HIF-1α and MMP9 expression changes. These data indicated that inhalational anesthetics, sevoflurane and desflurane, inhibited glioma cell malignancy via miRNAs upregulation and their downstream effectors, HIF-1α and MMP9, downregulation. The implication of the current study warrants further study.     

Biomarkers for Cancer Cachexia: A Mini Review

Cancer cachexia is a common condition in many cancer patients, particularly those with advanced disease. Cancer cachexia patients are generally less tolerant to chemotherapies and radiotherapies, largely limiting their treatment options. While the search for treatments of this condition are ongoing, standards for the efficacy of treatments have yet to be developed. Current diagnostic criteria for cancer cachexia are primarily based on loss of body mass and muscle function. However, these criteria are rather limiting, and in time, when weight loss is noticeable, it may be too late for treatment. Consequently, biomarkers for cancer cachexia would be valuable adjuncts to current diagnostic criteria, and for assessing potential treatments. Using high throughput methods such as “omics approaches”, a plethora of potential biomarkers have been identified. This article reviews and summarizes current studies of biomarkers for cancer cachexia.     

Vibrational Spectroscopy in Assessment of Early Osteoarthritis—A Narrative Review

Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.     

A Dual Physical Cross-Linking Strategy to Construct Tough Hydrogels with High Strength,Excellent Fatigue Resistance,and Stretching-Induced Strengthening Effect

Hydrogels with excellent stiffness, toughness, anti-fatigue, and self-recovery properties are regarded as promising water-containing materials. In this work, a dual physically cross-linked (DPC) sodium alginate (SA)/poly[acrylamide (AAm)-acrylic acid (AAc)-octadecyl methacrylate (OMA)]-Fe³⁺ hydrogel is reported, which is constructed by hydrophobic association (HA) and ionic coordination (IC). The optimal DPC hydrogel demonstrates excellent mechanical performance: tensile modulus of 0.65 MPa, tensile strength of 3.31 MPa, elongation at break of 1547%, and toughness of 27.8 MJ m^–3. SA/P(AAm-AAc-OMA)-Fe³⁺ DPC hydrogels also exhibit prominent anti-fatigue and self-recovery performance (99.1–109.7% modulus recovery and 90.4–108.9% dissipated energy recovery after resting for 5 min without additional stimuli at ambient temperature) through the reconstruction of reversible physical cross-linking. Some of the SA/P(AAm-AAc-OMA)-Fe³⁺ DPC hydrogels even exhibit a stretching-induced strengthening effect, which is similar to the performance of muscle—“the more training, the more strength.” Hence, the combination of HA and IC will provide an effective approach to design DPC hydrogels with desirable mechanical performances and a longer service life for wider applications of soft materials.