Serum cystatin C,monocyte/high-density lipoprotein-C ratio,and uric acid for the diagnosis of coronary heart disease and heart failure

BACKGROUND Coronary heart disease(CHD)and heart failure(HF)are the major causes of morbidity and mortality worldwide.Early and accurate diagnoses of CHD and HF are essential for optimal management and prognosis.However,conventional diagnostic methods such as electrocardiography,echocardiography,and cardiac biomarkers have certain limitations,such as low sensitivity,specificity,availability,and cost-effectiveness.Therefore,there is a need for simple,noninvasive,and reliable biomarkers to diagnose CHD and HF.AIM To investigate serum cystatin C(Cys-C),monocyte/high-density lipoprotein cholesterol ratio(MHR),and uric acid(UA)diagnostic values for CHD and HF.METHODS We enrolled 80 patients with suspected CHD or HF who were admitted to our hospital between July 2022 and July 2023.The patients were divided into CHD(n=20),HF(n=20),CHD+HF(n=20),and control groups(n=20).The serum levels of Cys-C,MHR,and UA were measured using immunonephelometry and an enzymatic method,respectively,and the diagnostic values for CHD and HF were evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Serum levels of Cys-C,MHR,and UA were significantly higher in the CHD,HF,and CHD+HF groups than those in the control group.The serum levels of Cys-C,MHR,and UA were significantly higher in the CHD+HF group than those in the CHD or HF group.The ROC curve analysis showed that serum Cys-C,MHR,and UA had good diagnostic performance for CHD and HF,with areas under the curve ranging from 0.78 to 0.93.The optimal cutoff values of serum Cys-C,MHR,and UA for diagnosing CHD,HF,and CHD+HF were 1.2 mg/L,0.9×10^(9),and 389μmol/L;1.4 mg/L,1.0×10^(9),and 449μmol/L;and 1.6 mg/L,1.1×10^(9),and 508μmol/L,respectively.CONCLUSION Serum Cys-C,MHR,and UA are useful biomarkers for diagnosing CHD and HF,and CHD+HF.These can provide information for decision-making and risk stratification in patients with CHD and HF.

Tandem hydroalkylation and deoxygenation of lignin-derived phenolics to synthesize high-density fuels

Lignin is the most abundant naturally phenolic biomass,and the synthesis of high-performance renewable fuel from lignin has attracted significant attention.We propose the efficient synthesis of high-density fuels using simulated lignin cracked oil in tandem with hydroalkylation and deoxygenation reactions.First,we investigated the reaction pathway for the hydroalkylation of phenol,which competes with the hydrodeoxygenation form cyclohexane.And then,we investigated the effects of metal catalyst types,the loading amount of metallic,acid dosage,and reactant ratio on the reaction results.The phenol hydroalkylation and hydrodeoxygenation were balanced when 180℃ and 5 MPa H_(2)with the alkanes yield of 95%.By extending the substrate to other lignin-derived phenolics and simulated lignin cracked oil,we obtained the polycyclic alkane fuel with high density of 0.918 g·ml^(-1)and calorific value of41.2 MJ·L^(-1).Besides,the fuel has good low-temperature properties(viscosity of 9.3 mm^(2)·s^(-1)at 20℃ and freezing point below-55℃),which is expected to be used as jet fuel.This work provides a promising way for the easy and green production of high-density fuel directly from real lignin oil.

Kinetic-Thermodynamic Promotion Engineering toward High-Density Hierarchical and Zn-Doping Activity-Enhancing ZnNiO@CF for High-Capacity Desalination

Despite the promising potential of transition metal oxides(TMOs)as capacitive deionization(CDI)electrodes,the actual capacity of TMOs electrodes for sodium storage is significantly lower than the theoretical capacity,posing a major obstacle.Herein,we prepared the kinetically favorable Zn_(x)Ni_(1−x)O electrode in situ growth on carbon felt(Zn_(x)Ni_(1−x)O@CF)through constraining the rate of OH^(−)generation in the hydrothermal method.Zn_(x)Ni_(1−x)O@CF exhibited a high-density hierarchical nanosheet structure with three-dimensional open pores,benefitting the ion transport/electron transfer.And tuning the moderate amount of redox-inert Zn-doping can enhance surface electroactive sites,actual activity of redox-active Ni species,and lower adsorption energy,promoting the adsorption kinetic and thermodynamic of the Zn_(0.2)Ni_(0.8)O@CF.Benefitting from the kinetic-thermodynamic facilitation mechanism,Zn_(0.2)Ni_(0.8)O@CF achieved ultrahigh desalination capacity(128.9 mgNaCl g^(-1)),ultra-low energy consumption(0.164 kW h kgNaCl^(-1)),high salt removal rate(1.21 mgNaCl g^(-1) min^(-1)),and good cyclability.The thermodynamic facilitation and Na^(+)intercalation mechanism of Zn_(0.2)Ni_(0.8)O@CF are identified by the density functional theory calculations and electrochemical quartz crystal microbalance with dissipation monitoring,respectively.This research provides new insights into controlling electrochemically favorable morphology and demonstrates that Zn-doping,which is redox-inert,is essential for enhancing the electrochemical performance of CDI electrodes.

Low Stress TSV Arrays for High-Density Interconnection

In three-dimensional(3D)stacking,the thermal stress of through-silicon via(TSV)has a significant influence on chip performance and reliability,and this problem is exacerbated in high-density TSV arrays.In this study,a novel hollow tungsten TSV(W-TSV)is presented and developed.The hollow structure provides space for the release of thermal stress.Simulation results showed that the hollow W-TSV structure can release 60.3%of thermal stress within the top 2 lm from the surface,and thermal stress can be decreased to less than 20 MPa in the radial area of 3 lm.The ultra-high-density(1600 TSV∙mm2)TSV array with a size of 640×512,a pitch of 25 lm,and an aspect ratio of 20.3 was fabricated,and the test results demonstrated that the proposed TSV has excellent electrical and reliability performances.The average resistance of the TSV was 1.21 X.The leakage current was 643 pA and the breakdown voltage was greater than 100 V.The resistance change is less than 2%after 100 temperature cycles from40 to 125℃.Raman spectroscopy showed that the maximum stress on the wafer surface caused by the hollow W-TSV was 31.02 MPa,which means that there was no keep-out zone(KOZ)caused by the TSV array.These results indicate that this structure has great potential for applications in large-array photodetectors and 3D integrated circuits.

Predictive value of intracranial high-density areas in neurological function

BACKGROUND Intracranial high-density areas(HDAs)have attracted considerable attention for predicting clinical outcomes;however,whether HDAs predict worse neurological function and mental health remains controversial and unclear,which requires further investigation.In this prospective study,96 patients with acute ischemic stroke(AIS)who accepted endovascular mechanical thrombectomy(EMT)were included.The enrolled patients underwent cranial computed tomography(CT)examination within 24 hours after EMT.Clinical data in terms of National Institutes of Health Stroke Scale(NIHSS),the 3-month modified Rankin Scale(mRS),self-rating depression scale(SDS),and self-rating anxiety scale(SAS)scores were collected and compared between patients with HDAs and non-HDAs and between patients with good and poor clinical prognosis.Compared to patients without HDAs,patients with HDAs presented severe neurological deficits(admission NIHSS score:18±3 vs 19±4),were more likely to have post-stroke disabilities(mRS<3:35%vs 62%),and suffered more severe depression(SDS score:58±16 vs 64±13)and anxiety disorder(SAS score:52±8 vs 59±10).Compared to patients with a good prognosis,patients with a poor prognosis presented severe neurological deficits(admission NIHSS score:17±4 vs 20±3),were more likely to have HDAs on CT images(64%vs 33%),and suffered more severe depression(SDS score:55±19 vs 65±11)and anxiety(SAS score:50±8 vs 58±12).Multivariate analysis revealed that HDAs were independent nega-tive prognostic factors.CONCLUSION In conclusion,HDAs on CT images predicted poor prognosis and severe depressive and anxiety symptoms in patients with AIS who underwent EMT.

基于深度学习的PCB缺陷检测技术

印刷电路板(printed circuit board,PCB)是电子产品的关键部件。在实际生产过程中,PCB难免会产生多种缺陷,对缺陷进行及时、精准检测具有一定的研究意义与应用价值。传统的检测方法存在速度慢、成本高、精度低的问题。针对PCB缺陷检测问题,开展基于YOLO系列算法研究,在相同的实验环境下,以平均精度、精确率、召回率、每秒传输帧数作为评价性能指标。实验研究发现,YOLOv7在精度方面比YOLOv5有一定的提升,而YOLOv5在训练和推理的速度上比YOLOv7更快。提出融合CBAM(convolutional block attention module)注意力机制模块的YOLOv5改进算法用于PCB缺陷检测。经实验验证,改进算法在PCB缺陷检测的精确性和速度性能上均得到提升,其中,平均精度、精确度和召回率分别提升了7.40%,3.57%和5.63%。

基于SMT-YOLOv8的PCB缺陷检测研究

针对PCB缺陷检测中目标尺寸小、权重文件庞大难以部署的问题,提出一种改进的YOLOv8小目标缺陷检测方法。该方法将SE注意力机制融入C2f中,使网络能够根据通道域的信息给图像不同位置赋予不同的权重,获取更重要的特征信息;在SPPF中引入Basic RFB以增强网络感受野,提升网络的特征提取能力;新增小目标检测尺度,提升模型对微小缺陷的检测能力;舍弃大目标检测尺度,降低计算负荷并缩小权重文件。实验结果表明,在公开的PCB缺陷数据集,改进后的YOLOv8较原算法平均精度提升了2.6%、权重文件缩小了27.3%、FPS达到34.4 ms/帧。

PCB可靠性测试评估方法简述

印制电路板(PCB)技术向高密度、高集成化等方向发展,导致PCB可靠性问题日益凸显。针对PCB失效机理,并结合现有PCB标准及实践应用情况,详细介绍了3种PCB可靠性测试评估的方法——失效率预计法、加速试验预计法和试验鉴定法,以期为从业者开展PCB可靠性测试评估提供一定的帮助。

基于融合MBAM与YOLOv5的PCB缺陷检测方法

随着电子信息产业迅速发展,PCB行业作为电子信息产业的基础,其产品质量对后续生产的电子产品有着决定性影响。针对PCB缺陷目标较小,缺陷类型多,特征不明显,在实际生产过程中易产生误检、漏检等问题,提出了一种多分支注意力MBAM模块方法,在3个不同维度对特征图进行关注,以增强特征提取的能力,对缺陷区域给予更多的注意力表示。通过改进YOLOv5结构,将MBAM与YOLOv5网络结合,有效的提升了对PCB中小目标的检测性能。最后通过在网络不同位置添加MBAM模块进行对比实验,选取了最佳的添加位置。通过在PCB缺陷数据集上的实验结果表明,改进后的PCB缺陷检测算法具有良好的检测性能,优于其他对比算法,最终的AP达到了96.7%,对比标准YOLOv5的94.7%提高了2个百分点,其他项指标均有涨点,在保持检测速度基本不变的情况下,精准地识别PCB缺陷类型。

Conversion of lignin oil and hemicellulose derivative into high-density jet fuel

Synthesizing high-density fuel from lignocellulose can not only achieve green and low-carbon development,but also expand the feedstock source of hydrocarbon fuel.Here,we reported a route of producing high-density fuel from lignin oil and hemicellulose derivative cyclopentanol through alkylation and hydrodeoxygenation,HY with SiO_(2)/Al_(2)O_(3) molar ratio of 5.3 was screened as the alkylation catalyst in the reaction of model phenolic compounds and mixtures,and the reaction conditions were optimized to achieve conversion of phenolic compounds higher than 87%and selectivity of bicyclic and tricyclic products higher than 99%.Then two phenolic pools simulating the composition of two typic lignin oils were studied to validate the alkylation and analyze the competition mechanism of phenolic compounds in mixture system.Finally,real lignin oil from depolymerized of beech powder was tested,and notably80%of phenolic monomers in the oil were converted into fuel precursor.After hydrodeoxygenation,the alkylated product was converted to fuel blend with a density of 0.91 g/mL at 20℃and a freezing point lower than-60℃,very promising as high density fuel.This work provides a facile and energyefficient way of synthesizing high-performance jet fuel directly from lignocellulosic derivatives,which decreases processing energy consumption and improve the utilization rate of feedstock.

高功率微波电磁脉冲对铁路PCB类设备的危害影响及防护措施研究

随着我国铁路朝着电气化和信息化方向不断发展,各种由精密PCB设计集成的电力电子设备广泛应用于各种强弱电系统,当这些设备遭受高功率微波等强电磁脉冲武器照射攻击时,若自身防护能效不足,则会导致设备出现异常状态,直接或间接地影响行车安全。文章通过建模仿真分析高功率微波电磁脉冲对铁路PCB设备的辐射影响和危害评估,并从工程角度提出了一些针对铁路PCB设备应对强电磁冲击的防护建议。

QTL mapping for berry shape based on a high-density genetic map constructed by whole-genome resequencing in grape

Grape berry shape is an important agricultural trait.Clarifying its genetic basis is significant for cultivating grape varieties that meet market demands.However,the current study by forward genetics has not achieved in-depth results.Here,a high-density map was constructed to identify quantitative trait loci(QTLs)for berry shape.A total of 358709 polymorphic SNPs were obtained using whole-genome resequencing(WGS)based on 208 F2 individuals derived from round grape‘E42-6’and oblong grape‘Rizamat’.The 1635.65 cM high-density map was divided into 19 linkage groups with an average distance of 0.37 cM.Using this map,three significant QTLs for fruit shape index(ShI:ratio of berry length to berry width)identified over three years were mapped onto LG4 and LG5,including one stable QTL on Chr5 with the genomic region of 0.47–1.94 Mb.Combining with gene annotation and expression patterns based on RNA-seq data from two contrasting F2 individuals with round and oblong berry(their average ShI was 1.89 and 1.10,respectively)at four developmental stages,four candidate genes were selected from the above QTLs.They were mainly involved in DNA replication,cell wall modification,and phytohormone biosynthesis.Further analysis of RNA-seq data revealed that several important phytohormone synthesis and metabolic pathways were enriched based on differentially expressed genes(DEGs),which was consistent with the results of QTL mapping for genes related to plant hormone biosynthesis in the F2 population.Furthermore,a comparison of plant hormone content showed that there were significant differences in IAA and tZ content between the two contrasting F2 individuals at different developmental stages.Our findings provide molecular insights into the genetic variation in grape berry shape.Stable QTLs and their tightly linked markers offer the possibility of marker-assisted selection to accelerate berry shape breeding.

TIA组态控制功能在PCB组装工艺中的应用

针对印刷电路板(PCB)组装工艺装贴方式多样,生产线工艺切换需要改变硬件组态和优化工艺流程,导致生产线停机时间加长、维护成本升高、生产效率降低等问题。以西门子PLC和分布式IO模块为例,提出了组态控制功能在PCB组装系统中的应用方案。采用最大硬件方案组态形成标准机器项目。根据不同的生产工艺、不同的生产方案,存储在专门的组态控制数据块中。当需要切换PCB组装工艺时,加载相应的组态方案,就可以运行新的组态项目和生产工艺,达到快速完成生产工艺切换的目的。使用西门子TIA博途V17的仿真检验,验证了组态控制功能的有效性和可靠性。

基于改进YOLOv5的PCB缺陷检测方法研究

随着工业制造业的发展,印刷电路板(PCB)在电子产品制造中愈发重要。在PCB生产过程中,存在着各种各样的不良缺陷,因此急需一种高效的PCB缺陷检测方法。针对传统的YOLOv5目标检测算法中对于PCB图像检测中存在小目标缺陷检测准确率低的问题,提出了一种基于改进的YOLOv5的PCB缺陷检测方法。首先,针对小目标缺陷存在漏检的问题,在YOLOv5的特征提取网络中加入了高效通道注意力机制(SE)模块,提高对小目标缺陷的特征提取能力,从而提高小目标缺陷的检测精度;其次,为了优化和改进原YOLOv5算法,采用加权损失函数代替原来的损失函数,以充分学习图像的各种特征。在北京大学机器人实验室公开的PCB瑕疵数据集上进行测试,实验结果显示,改进后的模型提高了小目标缺陷检测效果,其mAP值为94.54%,比原算法模型提高了2.1%。可以准确地完成工业生产的印制电路板的缺陷检测任务。

基于轻量化的YOLOv5的PCB缺陷检测算法

针对在印刷电路板(printed circuit board,PCB)缺陷检测上网络模型过大且精度较低的缺点,使用Python在Windows上提出了一种基于YOLOv5l改进的PCB缺陷检测算法,并对六种常见的缺陷作为数据集进行检测。采用轻量化网络EfficientNetLite0作为模型的骨干网络﹐并通过对特征金字塔加入P2检测头来获取更小的目标特征。试验结果表明:所提算法对印刷电路板的缺陷有识别精度高、模型小和检测快速的特点;单张图片检测速度达到43.6 ms﹐模型大小为49.1 MB﹐所有类别精度指标达到98.9%。所提算法为未来部属在边缘设备上的工业缺陷检测提供了新思路。

生活垃圾/废PCB板协同焚烧炉渣中氯的存在特性及影响机制

生活垃圾与一般工业固废协同焚烧处理是生活垃圾焚烧产业发展的重要趋势,协同焚烧处理对炉渣中氯存在特性的影响,尚无相关报道.本文以典型的一般工业固废PCB板为实验对象,聚焦生活垃圾/废PCB板协同焚烧过程,查明不同垃圾组分下,焚烧炉渣样品中的氯迁移行为、存在形态及长期稳定性.结果表明,废PCB板高温分解出的玻璃纤维比表面积大,能捕获部分挥发性的氯,使得其残留于炉渣中,从而造成炉渣总氯含量提高,但垃圾组分中塑料占比对该过程有重要影响.协同焚烧的炉渣水溶性氯含量在50~70wt%之间.淋溶结果显示大部分炉渣中氯的残留率在40%以下,而随着废PCB板投加量增加,炉渣中氯的残留率回升,最高达45.6%,这表明协同焚烧抑制了炉渣中氯的浸出.

磁沉淀工艺在PCB印制线路板废水处理中的应用

广东某PCB印制线路板园区集中污水处理站设计水量为12000 m^(3)/d,总磷排放标准为0.5 mg/L,由于污水中含有部分次磷,深度处理采用芬顿氧化澄清工艺。该污水处理站地处工业园核心区,用地紧张,芬顿氧化配套的常规澄清池由于面积不足,存在漂泥情况,TP和SS难以稳定达标。根据现场情况,将现有的澄清池改造为磁沉淀高效澄清池,提高芬顿氧化出水净化指标。长期运行结果表明:磁沉淀工艺对PCB印制线路板废水芬顿氧化出水具有良好的澄清效果,在进水悬浮物浓度≤1000 mg/L,总磷≤2.0 mg/L时,出水悬浮物浓度≤30 mg/L,总磷≤0.5 mg/L,磁沉淀系统占地面积76 m^(2),沉淀表面负荷≥12.5 m^(3)/(m^(2)·h),处理水量峰值可达15000 m^(3)/d,运行电耗成本0.042元/t水,运行磁粉损耗成本为0.0113元/t水,自动化运行程度高,水质波动适应性强,出水稳定。

基于注意力机制与多尺度融合的PCB缺陷检测

针对印制电路板(PCB)缺陷区域受背景干扰过多以及缺陷目标尺度较小导致缺陷检测精度低的问题,提出了一种基于注意力机制与多尺度融合的PCB缺陷检测方法。在YOLOv5模型的特征提取网络中,引入一种三维注意力模块,以增强缺陷目标特征的显著度,使模型更加注重目标特征;为充分利用微小缺陷目标的多尺度特征,在特征融合网络中引入加权双向特征金字塔网络(Bi-directional Feature Pyramid Network, BiFPN),减少缺陷目标特征信息的丢失,提高模型对微小缺陷目标的检测精度。实验结果表明,该方法能够准确检测出PCB图像中的缺陷目标,在保证实时性的同时,较原方法的平均检测精度提高了3.9%,表明了该方法的有效性。

一种改进YOLOv5模型的PCB板缺陷检测方法

针对传统PCB板检测方法中检测效率不高,检测精度较低等缺点,提出了一种改进YOLOv5模型的PCB板缺陷检测方法。为提升小目标缺陷检测精度,构建了基于BiFPN的网络连接方式,更加充分地利用了不同尺度的特征信息;为了更好地捕捉目标缺陷的位置,引入了Coordinate Attention注意力机制,使模型的定位和目标捕捉更加精准。实验结果表明,较原始的YOLOv5模型,所提出的针对PCB板表面缺陷检测方法的均值平均精度提高了3.2%。

基于深度学习的PCB焊锡缺陷检测

针对现有印刷电路板(PCB)缺陷检测算法具有体积大、精度差和漏检率高等问题,提出一种改进的YOLOv5s算法,利用迁移学习进行优化。在主干特征提取网络加入卷积块注意力模块(Convolutional Block Attention Module,CBAM)并引出一个新的蕴含更多丰富细节信息的浅层特征来提高模型信息感知能力,增强网络对小目标的检测。使用C3-CBAM替换加强特征提取网络的C3结构,为了在保障模型检测精度的同时减少模型参数量,使用深度可分离卷积替换下采样。去掉用于大目标的检测头(Yolo Head),避免数据不均衡带来的先验框分配问题。在自制PCB焊锡缺陷数据集上实验表明,改进后算法较原YOLOv5s算法的模型参数量减少24.8%,平均精度均值(mean Average Precision,mAP)达到99.46%,较原YOLOv5s提升了5.45%,证明了改进措施的有效性。