Attention-relation network for mobile phone screen defect classification via a few samples

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

Effect of inorganic salt impurities on seeded precipitation of silica hydrate from sodium silicate solution

To clarify the precipitation of silica hydrate from the real desilication solutions of aluminosilicate solid wastes by adding seeds and improve integrated waste utilization,the seeded precipitation was studied using synthesized sodium silicate solution containing different inorganic salt impurities.The results show that sodium chloride,sodium sulfate,sodium carbonate,or calcium chloride can change the siloxy group structure.The number of high-polymeric siloxy groups decreases with increasing sodium chloride or sodium sulfate concentration,which is detrimental to seeded precipitation.Calcium chloride favors the polymerization of silicate ions,and even the chain groups precipitate with the precipitation of high-polymeric sheet and cage-like siloxy groups.The introduced sodium cations in sodium carbonate render a more open network structure of high-polymeric siloxy groups,although the carbonate ions favor the polymerization of siloxy groups.No matter how the four impurities affect the siloxy group structure,the precipitates are always amorphous opal-A silica hydrate.

Natural Silicate as a Solid Support for the Calix[4]Thiophosphorus Derivative for Removal Mercury (II), as Picrate from Water

Currently a technique widely used for gold extraction is mercury by amalgamation technique, the tailing produced pollutes water of all kinds, so it is necessary to develop a form of selective mitigation, for which it is necessary to use complexing agents based on calixarene functionalized with mercury sequestering agents. These are immobilized by adding supports based on natural silica to form polymers and make them insoluble in all types of solvents, so that they can be used as an extractor and at the same time regenerate to their original properties for continuous reuse.

Carbonation of Dicalcium Silicate Enhanced by Ammonia Bicarbonate and Its Mechanism

The strength development law of γ-type dicalcium silicate (γ-C_(2)S) under different carbonation processes was investigated,and the carbonation mechanism of γ-C_(2)S under the action of NH_(4)HCO_(3) was clarified by using a wide range of test methods,including XRD and SEM.A method of saturated NH_(4)HCO_(3) solution as a curing agent was identified to improve the carbonation efficiency and enhance the carbonation degree of γ-C_(2)S,and then a high-strength carbonated specimen was obtained.Microhardness analysis and SEM morphology analysis were conducted on the carbonised specimens obtained under atmospheric pressure carbonisation conditions using the curing agent.It was found that γ-C_(2)S could perform carbonisation well under atmospheric pressure,which promoted the carbonisation efficiency and decreased the carbonisation cost simultaneously.Therefore,a new carbonisation process solution was proposed for the rapid carbonisation of γ-C_(2)S.

Research on the Encapsulation Device for Lunar Samples

The encapsulation of lunar samples is a core research area in the third phase of the Chinese Lunar Exploration Program.The seal assembly,opening and closing mechanism(OCM),and locking mechanism are the core components of the encapsulation device of the lunar samples,and the requirements of a tight seal,lightweight,and low power make the design of these core components difficult.In this study,a combined sealing assembly,OCM,and locking mechanism were investigated for the device.The sealing architecture consists of rubber and an Ag-In alloy,and a theory was built to analyze the seal.Experiments of the electroplate Au coating on the knife-edge revealed that the hermetic seal can be significantly improved.The driving principle for coaxial double-helical pairs was investigated and used to design the OCM.Moreover,a locking mechanism was created using an electric initiating explosive device with orifice damping.By optimizing the design,the output parameters were adjusted to meet the requirements of the lunar explorer.The experimental results showed that the helium leak rate of the test pieces were not more than 5×10^(-11) Pa·m^(3)·s^(-1),the minimum power of the OCM was 0.3 W,and the total weight of the principle prototype was 2.9 kg.The explosive driven locking mechanism has low impact.This investigation solved the difficulties in achieving tight seal,light weight,and low power for the lunar explorer,and the results can also be used to explore other extraterrestrial objects in the future.

Effectiveness of Histopathological Examination of Ultrasound-guided Puncture Biopsy Samples for Diagnosis of Extrapulmonary Tuberculosis

Objective To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis(EPTB).Methods This study was conducted at the Shanghai Public Health Clinical Center.A total of 115patients underwent ultrasound-guided puncture biopsy,followed by MGIT 960 culture(culture),smear,Gene Xpert MTB/RIF(Xpert),and histopathological examination.These assays were performed to evaluate their effectiveness in diagnosing EPTB in comparison to two different diagnostic criteria:liquid culture and composite reference standard(CRS).Results When CRS was used as the reference standard,the sensitivity and specificity of culture,smear,Xpert,and histopathological examination were(44.83%,89.29%),(51.72%,89.29%),(70.11%,96.43%),and(85.06%,82.14%),respectively.Based on liquid culture tests,the sensitivity and specificity of smear,Xpert,and pathological examination were(66.67%,72.60%),(83.33%,63.01%),and(92.86%,45.21%),respectively.Histopathological examination showed the highest sensitivity but lowest specificity.Further,we found that the combination of Xpert and histopathological examination showed a sensitivity of 90.80%and a specificity of 89.29%.Conclusion Ultrasound-guided puncture sampling is safe and effective for the diagnosis of EPTB.Compared with culture,smear,and Xpert,histopathological examination showed higher sensitivity but lower specificity.The combination of histopathology with Xpert showed the best performance characteristics.

Synergistic strengthening mechanism of Ca^(2+)-sodium silicate to selective separation of feldspar and quartz

Inhibitors are important for flotation separation of quartz and feldspar.In this study,a novel combined inhibitor was used to separate quartz and feldspar in near-neutral pulp.Selective inhibition of the combined inhibitor was assessed by micro-flotation experiments.And a series of detection methods were used to detect differences in the surface properties of feldspars and quartz after flotation reagents and put forward the synergistic strengthening mechanism.The outcomes were pointed out that pre-mixing combined inhibitors were more effective than the addition of Ca^(2+)and SS in sequence under the optimal proportion of 1:5.A concentrate from artificial mixed minerals that was characterized by a high quartz grade and a high recovery was acquired,and was found to be 90.70wt% and 83.70%,respectively.It was demonstrated that the combined inhibitor selectively prevented the action of the collector and feldspar from Fourier-transform infrared(FT-IR)and adsorption capacity tests.The results of X-ray photoelectron spectroscopy(XPS)indicated that Ca^(2+)directly interacts with the surface of quartz to increase the adsorption of collectors.In contrast,the chemistry property of Al on the feldspar surface was altered by combined inhibitor due to Na^(+)and Ca^(2+)taking the place of K^(+),resulting in the composite inhibitor forms a hydrophilic structure,which prevents the adsorption of the collector on the surface of feldspar by interacting with the Al active site.The combination of Ca^(2+)and SS synergically strengthens the difference of collecting property between quartz and feldspar by collector,thus achieving the effect of efficient separation.A new strategy for flotation to separate quartz from feldspar in near-neutral pulp was provided.

Exploring device physics of perovskite solar cell via machine learning with limited samples

Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.

A Fault Detection Method for Electric Vehicle Battery System Based on Bayesian Optimization SVDD Considering a Few Faulty Samples

Accurate and reliable fault detection is essential for the safe operation of electric vehicles.Support vector data description(SVDD)has been widely used in the field of fault detection.However,constructing the hypersphere boundary only describes the distribution of unlabeled samples,while the distribution of faulty samples cannot be effectively described and easilymisses detecting faulty data due to the imbalance of sample distribution.Meanwhile,selecting parameters is critical to the detection performance,and empirical parameterization is generally timeconsuming and laborious and may not result in finding the optimal parameters.Therefore,this paper proposes a semi-supervised data-driven method based on which the SVDD algorithm is improved and achieves excellent fault detection performance.By incorporating faulty samples into the underlying SVDD model,training deals better with the problem of missing detection of faulty samples caused by the imbalance in the distribution of abnormal samples,and the hypersphere boundary ismodified to classify the samplesmore accurately.The Bayesian Optimization NSVDD(BO-NSVDD)model was constructed to quickly and accurately optimize hyperparameter combinations.In the experiments,electric vehicle operation data with four common fault types are used to evaluate the performance with other five models,and the results show that the BO-NSVDD model presents superior detection performance for each type of fault data,especially in the imperceptible early and minor faults,which has seen very obvious advantages.Finally,the strong robustness of the proposed method is verified by adding different intensities of noise in the dataset.

Mechanical behavior of 2G NPR bolt anchored rock samples under static disturbance loading

The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling large deformations in the surrounding rock effectively.This paper focuses on studying the mechanical properties of the NPR bolt under static disturbance load.The deep nonlinear mechanical experimental system was used to study the mechanical behavior of rock samples with different anchored types(unanchored/PR anchored/2G NPR anchored)under static disturbance load.The whole process of rock samples was taken by high-speed camera to obtain the real-time failure characteristics under static disturbance load.At the same time,the acoustic emission signal was collected to obtain the key characteristic parameters of acoustic emission such as acoustic emission count,energy,and frequency.The deformation at the failure of the samples was calculated and analyzed by digital speckle software.The findings indicate that the failure mode of rock is influenced by different types of anchoring.The peak failure strength of 2G NPR bolt anchored rock samples exhibits an increase of 6.5%when compared to the unanchored rock samples.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 62.16%and 62.90%,respectively.The maximum deformation of bearing capacity exhibits an increase of 59.27%,while the failure time demonstrates a delay of 42.86%.The peak failure strength of the 2G NPR bolt anchored ones under static disturbance load exhibits an increase of 5.94%when compared to the rock anchored by PR(Poisson's ratio)bolt.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 47.16%and 43.86%,respectively.The maximum deformation of the bearing capacity exhibits an increase of 50.43%,and the failure time demonstrates a delay of 32%.After anchoring by 2G NPR bolt,anchoring support effectively reduces the risk of damage caused by static disturbance load.These results demonstrate that the support effect of 2G NPR bolt materials surpasses that of PR bolt.

Effectiveness of Sodium Silicate on the Corrosion Protection of AA7075-T6 Aluminium Alloy in Sodium Chloride Solution

The influence of sodium silicate on the corrosion behaviour of aluminium alloy 7075-T6 in 0.1 M sodium chloride solution was studied by open circuit potential (OCP) and electrochemical impedance spectroscopy (EIS) techniques. Scanning electron microscopy (SEM) was used to characterize the AA7075-T6 surface. Silicate can significantly reduce corrosion deterioration and the inhibition efficiency increases with the concentration of Na2SiO3. The corrosion inhibition mechanism involves the formation of a protective film over the alloy surface by adsorption of aluminosilicate anions from solution, as has also been suggested by others in literature.

Adsorption of sodium polyacrylate at interface of dicalcium silicate-sodium aluminate solution

The adsorption isotherm of sodium polyacrylate on dicalcium silicate（2CaO-SiO2） in sodium aluminate solution at 80 ℃ was studied.The type of surface adsorption of sodium polyacrylate is saturated adsorption,and the adsorption behavior belongs to L-type,according with the monolayer adsorption model of Langmuir equation.The surface coverage of sodium polyacrylate is 1.06 mol/μm2.The relation curve between the surface pressure and the molecular area of adsorption film was obtained by Gibbs formula.The variation of interfacial energy caused by adsorption as well as the relationship between the relation curve and the type of adsorption was discussed.

Leaching kinetics of zinc silicate in ammonium chloride solution

The leaching kinetics of zinc silicate in ammonium chloride solution was investigated. The effects of stirring speed （150？400 r/min）, leaching temperature （95-108 ℃, particle size of zinc silicate （61-150 μm） and the concentration of ammonium chloride （3.5-5.5 mol/L） on leaching rate of zinc were studied. The results show that decreasing the particle size of zinc silicate and increasing the leaching temperature and concentration of ammonium chloride can obviously enhance the leaching rate of zinc. Among the kinetic models of the porous solids tested, the grain model with porous diffusion control can well describe the zinc leaching kinetics. The apparent activation energy of the leaching reaction is 161.26 kJ/mol and the reaction order with respect to ammonium chloride is 3.5.

Self-healing mechanism of composite coatings obtained by phosphating and silicate sol post-sealing

Silicate sol post-treatment was applied to form a complete composite coating on the phosphated zinc layer. The chemical compositions of the coatings were investigated using XPS. The coated samples were firstly scratched and then exposed to the neutral salt spray(NSS) chamber for different time. The microstructure and chemical compositions of the scratches were studied using SEM and EDS. And the non-scratched coated samples were compared. The self-healing mechanism of the composite coatings was discussed. The results show that during corrosion, the self-healing ions in composite coatings dissolve, diffuse and transfer to the scratches or the defects, and then recombine with Zn2+ to form insoluble compound, which deposits and covers the exposed zinc. The corrosion products on the scratches contain silicon, phosphorous, oxygen, chloride and zinc, and they are compact, fine, needle and flake, effectively inhibiting the corrosion formation and expansion of the exposed zinc layer. The composite coatings have good self-healing ability.

Influence of sodium silicate on manganese electrodeposition in sulfate solution

The influences of sodium silicate on manganese electrodeposition in sulfate solution were investigated. Manganese electrodeposition experiments indicate that a certain amount of sodium silicate can improve cathode current efficiency and initial pH 7.0?8.0 is the optimized pH for high cathode current efficiency. The analyses of scanning electron microscopy (SEM) and X-ray diffraction (XRD) indicate the compact morphology and nanocrystalline structure of electrodeposits. X-ray photoelectron spectrometry (XPS) analysis shows that the elements of Mn, Si and O exist in the deposit. The solution chemistry calculations of sulfate electrolyte and sodium silicate solution indicate that species of Mn2+, MnSO4, Mn(SO4)2?2 , Mn2+, MnSiO3, Mn(NH3)2+, SiO32?and HSiO3? are the main active species during the process of manganese electrodeposition. The reaction trend between Mn2+ and Si-containing ions is confirmed by the thermodynamic analysis. In addition, polarization curve tests confirm that sodium silicate can increase the overpotential of hydrogen evolution reaction, and then indirectly improve the cathode current efficiency.

Local structure of calcium silicate melts from classical molecular dynamics simulation and a newly constructed thermodynamic model

The distributions of local structural units of calcium silicate melts were quantified by means of classical molecular dynamics simulation and a newly constructed structural thermodynamic model. The distribution of five kinds of Si-O tetrahedra Qi from these two methods was compared with each other and also with the experimental Raman spectra, an excellent agreement was achieved. These not only displayed the panorama distribution of microstructural units in the whole composition range, but also proved that the thermodynamic model is suitable for the utilization as the subsequent application model of spectral experiments for the thermodynamic calculation. Meanwhile, the five refined regions mastered by different disproportionating reactions were obtained. Finally, the distributions of two kinds of connections between Qi were obtained, denoted as Qi-Ca-Qj and Qi-[Ob]-Qj, from the thermodynamic model, and a theoretical verification was given that the dominant connections for any composition are equivalent connections.

轻度认知障碍老人与认知正常老人在不同单双任务下姿势控制能力的差异性

背景:老年人由于轻度认知障碍而引起姿势控制能力下降,导致跌倒风险增高。双任务是在接近真实生活场景下评估认知与姿势控制能力关系的主要研究范式,站立时足底压力中心位移样本熵可代表姿势控制的复杂程度。目的:基于压力中心位移样本熵分析轻度认知障碍老年人与认知正常老年人在姿势控制-空间工作记忆任务中姿势稳定性特征及控制策略的差异,探究认知功能损伤对站立姿势控制能力影响。方法:筛选出符合条件的16名轻度认知障碍老年人和17名认知正常老年人为研究对象,老年人分别完成5种测试任务,包括空间工作记忆、双脚平衡站立、Romberg站立、双脚平衡站立-空间工作记忆双任务、Romberg站立-空间工作记忆双任务,每个任务有效完成3次。使用Kistler三维测力台采集足底压力中心数据,测试指标包括认知行为学指标(认知得分与反应时长)、动力学指标(压力中心位移及样本熵)。结果与结论:①轻度认知障碍老年人在执行空间工作记忆任务时认知得分最大、反应时间最短,双脚平衡站立-空间工作记忆双任务居中,Romberg站立-空间工作记忆双任务认知得分最小、反应时长最长,任务间比较差异均有显著性意义(P<0.05);②与双脚平衡站立、Romberg站立任务相比,轻度认知障碍老年人在执行双任务时压力中心前后、内外方向位移显著更大,压力中心前后、内外方向位移样本熵值显著更小(P<0.05);③在空间工作记忆任务下,轻度认知障碍老年人与认知正常老年人的认知得分、反应时长差异均无显著性意义(P>0.05);在两种双任务下,与认知正常老年人相比,轻度认知障碍老年人的认知得分更小、反应时长更长(P<0.05),同时轻度认知障碍老年人压力中心前后、内外方向位移更大,压力中心前后、内外方向位移样本熵值更小(P<0.05);④结果表明:与认知正常老年人相比,轻度认知障碍老年人在执行双任务时姿势控制复杂度降低,系统适应性较差,自动调控能力下降,更容易受到空间工作记忆干扰,跌倒风险增大。

纤维肌痛综合征生物标记物的筛选及免疫细胞浸润分析

背景:纤维肌痛综合征作为常见风湿病,其发病与中枢敏化及免疫异常有关,但具体过程尚未阐明,缺乏特异性诊断标志物,不断探索该病的发病机制具有重要的临床意义。目的:基于加权基因共表达网络分析(WGCNA)等生物信息学方法和机器学习算法筛选纤维肌痛综合征潜在的诊断相关标志基因,并分析其免疫细胞浸润特征。方法:对来自基因表达综合数据库(GEO)的纤维肌痛综合征数据集转录谱进行差异分析和WGCNA分析,整合筛选出差异共表达基因,进一步采用机器学习套索回归(LASSO)算法、支持向量机递归特征消除(SVM-RFE)机器学习算法来识别核心生物标志物,并绘制受试者工作特征(ROC)曲线以评估诊断价值。最后,采用单样本基因集富集分析(ssGSEA)和基因集富集分析(GSEA)评估纤维肌痛综合征的免疫细胞浸润情况及通路富集。结果与结论:①对GSE67311数据集按照log2|(FC)|>0,P<0.05的条件进行差异分析后获得8个下调的差异表达基因;进行WGCNA分析后获得正相关性最高(r=0.22,P=0.04)的模块(MEdarkviolet)内含基因497个,负相关性最高(r=-0.41,P=6×10-5)的模块(MEsalmon2)内含基因19个;将差异表达基因与WGCNA的2个高相关性模块基因取交集,获得7个基因。②对上述7个基因进行LASSO回归算法筛选出4个基因,进行SVM-RFE机器学习算法筛选出5个基因,两者取交集后确定了3个核心基因,分别为重组1号染色体开放阅读框150蛋白(germinal center associated signaling and motility like,GCSAML)、整合素β8(Integrin beta-8,ITGB8)和羧肽酶A3(carboxypeptidase A3,CPA3);绘制3个核心基因的ROC曲线下面积分别为0.744,0.739,0.734,提示均具有很好的诊断价值,可作为纤维肌痛综合征的生物标志物。③免疫浸润分析结果显示,与对照组相比纤维肌痛综合征患者记忆B细胞、CD56 bright NK细胞和肥大细胞显著下调(P<0.05),且与上述3个生物标志物显著正相关(P<0.05)。④富集分析结果提示,纤维肌痛综合征的富集途径包括9条,主要与嗅觉传导、神经活性配体-受体相互作用及感染等通路密切相关。⑤上述结果显示,纤维肌痛综合征的发生发展与多基因参与、免疫调节异常及多个通路失调有关,但这些基因与免疫细胞之间的相互作用,以及它们与各通路之间的关系尚需进一步研究。

生物样品中汞的电感耦合等离子体质谱分析与干扰校正方法

电感耦合等离子体质谱法(ICP-MS)在测定生物样品中的Hg时,由于Hg元素的电离能高、电离效率低,且存在W的氧化物等多原子离子干扰,很难进行直接准确测定,加之生物样品中有机质含量高,基体复杂,也会导致分析结果产生偏差。本文通过比较标准模式(STD)和动能歧视模式(KED)下测定Hg的质谱干扰情况,表明在STD模式下200Hg、202Hg均受到W、Re、Os、Er、Dy等元素多原子离子的干扰,而KED模式有效地降低了干扰;在KED模式下选择202Hg作为分析同位素,Er、Dy、Re、Os等对Hg的干扰可以忽略不计,而W的氧化物干扰仍难以完全消除。进而详细研究了KED模式下W对Hg测定的质谱干扰,Hg所受干扰程度与W含量呈线性相关(R2=0.9997),可利用KED模式结合数学校正法消除W的质谱干扰;优选了样品稀释倍数和内标元素,选择稀释倍数为100倍,50μg/L的Rh作为内标补偿基体效应。在此基础上建立生物样品中Hg的ICP-MS分析与干扰校正方法,检出限为1.2ng/g。采用该方法对9个标准物质中Hg含量进行测定,测定值与标准值(或参考值)一致,尤其是国家标准物质GBW10028(黄芪)、GBW10025(螺旋藻)、GBW10015a(菠菜)的准确度显著提高,相对标准偏差(n=10)为0.7%~7.0%。该方法操作简便,适用于W含量范围在0~1000ng/g,Hg含量范围在3.2~670ng/g的生物样品的测试。

Selection of Test Samples for Monitoring Veterinary Drug Residue in Bred Animals

[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.