A critical review towards the causes of the iron-based catalysts deactivation mechanisms in the selective oxidation of hydrogen sulfide to elemental sulfur from biogas

Hydrogen sulfide(H_(2)S) not only presents significant environmental concerns but also induces severe corrosion in industrial equipment,even at low concentrations.Among various technologies,the selective oxidation of hydrogen sulfide(SOH_(2)S) to elemental sulfur(S) has emerged as a sustainable and environmentally friendly solution.Due to its unique properties,iron oxide has been extensively investigated as a catalyst for SOH_(2)S;however,rapid deactivation has remained a significant drawback.The causes of iron oxide-based catalysts deactivation mechanisms in SOH_(2)S,including sulfur or sulfate deposition,the transformation of iron species,sintering and excessive oxygen vacancy formation,and active site loss,are thoroughly examined in this review.By focusing on the deactivation mechanisms,this review aims to provide valuable insights into enhancing the stability and efficiency of iron-based catalysts for SOH_(2)S.

Configuration Selection for Reconfigurable Manufacturing Systems by Means of Characteristic State Space

The configuration selection for reconfigurable manufacturing systems（RMS） have been tackled in a number of studies by using analytical or simulation models. The simulation models are usually based on fewer assumptions than the analytical models and therefore are more wildly used in modeling complex RMS. But in the absence of an efficient gradient analysis method of the objective function, it is time-consuming in solving large-scale problems by using a simulation model coupled with a meta-heuristics algorithm. In this paper, a new approach by means of characteristic state space is presented to improve the efficiency of the configuration selection for an RMS. First, a characteristic state equation is set up to represent the input and the output resources of each basic activity in an RMS. A production process model in terms of matrix equations is established by iterating the equations of basic activities according to the resource flows. This model introduces the production process into a characteristic state space for further analysis. Second, the properties of the characteristic state space are presented. On the basis of these properties, the configuration selection in an RMS is considered as a path-planning problem, and the gradient of the objective function is computed. Modified simulated annealing（SA） is also presented, in which neighborhood generation is guided by the gradient to accelerate convergence and reduce the run time of the optimization procedure. Finally, several case studies on the configuration selection for some actual reconfigurable assembly job-shops are presented and compared to the classical SA. The comparison shows relatively positive results. This study provides a more efficient configuration selection approach by using the gradient of the objective function and presents the relevant theories on which it is based.

Effects of geometrical characteristics on defect distributions in alloy components produced by selective laser melting

Selective laser melting(SLM)has been applied to manufacture various alloy components with excellent properties,but its further application is restricted by the intrinsic defects.In this work,the internal defect distributions in samples of three alloys(316L stainless steel,AlSi10Mg and Inconel 718)were investigated respectively,considering the effects of geometrical characteristics of the samples.The defects in the 316L stainless steel sample tend to be formed densely in the central part with large wall thickness,indicating a strong sensitivity to heat accumulation.Contrarily,the Inconel 718 sample shows a higher relative density with homogeneous defect distribution,indicating better formability for the SLM process.For the AlSi10Mg sample,the defect density keeps increasing as the deposition goes on.Typically,the defect density located at sample edges shows an abnormally high level comparing with the inner part,especially in the top sections of AlSi10Mg and Inconel 718 samples.The results are helpful for the geometrical design,the adjustment of building orientation and the further optimization of process parameters in the SLM process.

Analysis on Characteristics of Typical Syndromes of Acquired Immune Deficiency Syndrome Based on the Feature Selection Method

Objective:To discover the population characteristics of the syndrome types of Acquired Immune Deficiency Syndrome.Methods:Data mining method for feature selection was used.Results:Main symptoms based on feature selection are as follows,deficiency of both qi and blood(pale complexion,fear of cold,easy to catch a cold,pale tongue,weak pulse);liver depression and qi stagnation with effulgent fire(anxiety,insomnia,chest and hypochondrium,irregular menstruation,thin and whitish coating on the tongue,stringy pulse);dual deficiency of qi and yin(low-grade fever and night sweating,yellow urine,pale complexion,dysphoria with feverish sensation in chest,dry cough with less phlegm,weakness,dizziness,dry and red tongue,little coating,thread and rapid pulse);deficiency of spleen and kidney,dampness pathogen blockage(diarrhea,loose stool,eat less and abdominal nausea,abdominal pain,sallow complexion,nausea,vomiting,loss of hair,deafness and tinnitus,pale tongue with whitish coating,deep and thready pulse,slippery and rapid pulse);qi deficiency with blood stasis(weakness,spontaneous sweating,dry mouth without desire to drink,easy to catch a cold,shortness of breath,sallow complexion,eat less and loose stools,dim tongue quality,hesitant pulse).Conclusion:Based on the feature selection method,we can find the main characteristics of Acquired Immune Deficiency Syndrome,and provide objective reference for clinical diagnosis and treatment.

甘肃积石山 M_(s)6.2级地震的震害特征与启示

2023年12月18日,甘肃省临夏回族自治州积石山保安族东乡族撒拉族自治县(35.70°N,102.79°E)发生了6.2级地震,震中烈度为VIII度。地震发生后,通过实地烈度评估与科学考察,对震区VI~VIII度区不同建(构)筑物与生命线工程的震害特点进行了统计分析;从抗震设计与施工管理、场地放大效应与地震次生灾害对建筑结构抗震性能的影响等角度,提出了此次地震的震害启示。结果表明:1)严重破坏和毁坏的建筑结构主要集中在老旧的土木结构、砖木结构和无设防或设防不规范的砖混结构。2)造成建筑结构破坏的主要原因是少量自建房抗震设计和施工的不规范、场地放大效应和地震次生灾害。3)优化和改良生土砌筑材料,改进纵横墙间的拉结措施,强化结构整体性是提高土木结构抗震的有效方法;普及“上下圈梁与构造柱”等基本抗震设防措施,规范水泥砂浆强度,提升农村工匠的施工水平,可有效提高砌体结构的整体性,避免房屋出现整体性垮塌;室内洗手间的墙体应该与房顶、纵横墙间建立有效联接,提高结构的抗震性能。4)孤突斜坡、河流高阶地与岸边为抗震不利地带。当建造用地极为匮乏,不得不选址在这些场地之上时,应该综合考虑场地的地形地貌特征、岩土体物理力学特性、水文地质条件、抗震设防目标、建筑结构类型等影响因素,做好地震灾害风险评估,根据评估结果进行科学设防。灾后重建过程中,应由政府统一规划选址、统一设计,规范施工。

K-S变换及其电网超谐波时频分析应用

依据FFT→优化窗→IFFT思路,突破线性时频变换的窗函数积分性能桎梏,实现高性能优化窗函数的线性时频变换应用,建立新型时频变换算法——K-S变换.对信号x(t)的FFT频谱向量进行频移处理后,与该频移点下Kaiser优化窗的频谱向量进行Hadamard乘积,再将乘积结果进行FFT逆变换(IFFT),构造出K-S变换复时频矩阵,由此获得x(t)的时间-频率-幅值、时间-频率-相位三维信息;给出逆变换的数学推导与局部性质、线性性质和变分辨率特性;0~150 kHz电网的稳态与时变超谐波信号仿真实验表明,K-S变换的时域、频域分辨能力均优于流行的短时傅里叶变换、S变换,具有优良的变分辨率性能;0~40 kHz超谐波信号的实测证明,基于K-S变换的超谐波电压幅值测量绝对误差均小于0.032 3 V.

改变导叶翼型对水泵水轮机“S”特性的影响

针对水泵水轮机“S”特性区域的不稳定性问题,提出使用改型活动导叶翼型进行性能提升.以某水泵水轮机模型为研究对象,采用SST k-ω湍流模型对水泵水轮机全流道进行三维数值计算,通过对活动导叶翼型的改型设计,得出流量-转速模拟曲线,分析水泵水轮机组“S”特性改善情况.将计算与试验结果进行对比,并对改型活动导叶翼型前后机组的无叶区进行压力脉动分析.结果表明:在保证整体效率依然保持在92%附近的前提下,新的活动导叶翼型对机组的“S”特性依旧具有改善效果;无叶区压力脉动主要是受到活动导叶叶栅区域的分流在此重新聚集影响,并且与转轮叶片的动静相互扰动引起的;改型后的活动导叶降低了无叶区的压力脉动幅值,提升了水泵水轮机运行中的并网稳定性.

基于哨兵函数和S变换的风力机叶片材料损伤特性研究

利用声发射检测技术研究玻璃纤维增强环氧树脂复合材料的损伤特性,在此过程中,采用哨兵函数来表征该材料的损伤程度,并通过S变换和模糊C均值(FCM)聚类来分析声发射信号,从而获得材料的损伤特征。三点弯曲实验结束后对试件断口进行扫描电子显微镜(SEM)拍照来验证,可得:通过对SEM照片的分析得到基体开裂、纤维脱粘、分层破坏、纤维断裂4种损伤模式;对整个声发射事件进行哨兵函数分析,观察到试件在弯曲过程中哨兵函数曲线呈明显下降趋势;对依据哨兵函数划分的不同阶段的信号进行VMD降噪处理,然后采用S变换进行时频分析得到不同损伤的特征频率,最后采用FCM聚类进行验证。结果表明:哨兵函数值的突变可作为材料断裂的预警信号,材料损伤类型的识别可依据S变换的频率分布结果进行确定。

电液3-UPS/S并联稳定平台参数振动特性分析

针对电液3-UPS/S并联稳定平台驱动液压缸的压力脉动所产生的参数振动,建立了稳定平台的参数振动方程并利用多尺度法求解了主共振响应与组合共振响应的一次近似解;分析了主共振与组合共振响应特性以及振动幅值在初始工作空间内的变化规律,最后采用四阶龙格库塔法与模态试验对参数振动模型进行验证。结果表明:数值解与理论解之间的最大误差为4.20%,固有频率理论值与试验值之间的最大误差为4.66%,可验证参数振动模型的正确性。

Flexible nest site selection of the endangered Oriental Storks(Ciconia boyciana):Trade-off from adaptive strategies

Nest site selection is a vital component of bird reproduction success,and an adaptive behavior conducted to decrease nest predation risk with avoiding external disturbances.Understanding patterns of nest site selection can provide insights into how species adapt to changes in their habitat and has important conservation implications.In this study,we used microhabitat variables and multi-scale data with a field survey of nest occurrence to determine nest site selection patterns and adaptive strategies of the breeding Oriental Storks(Ciconia boyciana)in different nest areas.Results demonstrate that the nest site microhabitat characteristics of the breeding Oriental Storks significantly differed among the three nesting areas,and nest height was higher in the middle and lower Yangtze River floodplain than in the Northeast China and Bohai Bay nest areas.The food resources and intensity of human disturbance had the greatest effects on the nest site selection of the breeding Oriental Storks.The intensity of human disturbance was positively correlated with the nest height of the breeding Oriental Storks in Bohai Bay and the middle and lower Yangtze River floodplain;however,nest height decreased with the abundance of food resources in the Northeast China nest area.Our findings indicate that the nest site selection patterns of Oriental Storks showed flexible adaptive strategies.In safer environments,nests were lower and closer to food resources,which allows parent storks to invest more in the nestlings.However,in areas where human activity was intense,nests were higher to ensure the safety of their offspring.Some measures that could be taken to improve the breeding habitat of Oriental Storks include increasing the percentage of wetland areas in nesting areas to enhance food resources availability and setting artificial nests at suitable heights in potential nesting grounds to encourage nesting.Finally,the establishment of soft barriers around the nesting areas could increase the safety of nests.

Dual-functional marigold-like Zn_(x)Cd_(1-x)S homojunction for selective glucose photoreforming with remarkable H_(2)coproduction

The global commitment to pivoting to sustainable energy and products calls for technology development to utilize solar energy for hydrogen(H_(2))and value-added chemicals production by biomass photoreforming.Herein,a novel dual-functional marigold-like Zn_(x)Cd_(1-x)S homojunction has been the production of lactic acid with high-yield and H_(2)with high-efficiency by selective glucose photoreforming.The optimized Zn_(0.3)Cd_(0.7)S exhibits outstanding H_(2)generation(13.64 mmol h^(-1)g^(-1)),glucose conversion(96.40%),and lactic acid yield(76.80%),over 272.80 and 19.21 times higher than that of bare ZnS(0.05 mmol h^(-1)g^(-1))and CdS(0.71 mmol h^(-1)g^(-1))in H_(2)generation,respectively.The marigold-like morphology provides abundant active sites and sufficient substrates accessibility for the photocatalyst,while the specific role of the homojunction formed by hexagonal wurtzite(WZ)and cubic zinc blende(ZB)in photoreforming biomass has been demonstrated by density functional theory(DFT)calculations.Glucose is converted to lactic acid on the WZ surface of Zn_(0.3)Cd_(0.7)S via the photoactive species·O_(2)^(-),while the H_(2)is evolved from protons(H^(+))in H_(2)O on the ZB surface of Zn_(0.3)Cd_(0.7)S.This work paves a promising road for the production of sustainable energy and products by integrating photocatalysis and biorefine.

Isolation and algae-lysing characteristics of the algicidal bacterium B5

Water blooms have become a worldwide environmental problem. Recently, algicidal bacteria have attracted wide attention as possible agents for inhibiting algal water blooms. In this study, one strain of algicidal bacterium B5 was isolated from activated sludge. On the basis of analysis of its physiological characteristics and 16S rDNA gene sequence, it was identified as Bacillusfusiformis. Its algaelysing characteristics on Microcystis aeruginosa, Chlorella and Scenedesmus were tested. The results showed that： （1） the algicidal bacterium B5 is a Gram-negative bacterium. The 16S rDNA nucleotide sequence homology of strain B5 with 2 strains of B. fusiformis reached 99.86%, so B5 was identified as B. fusiformis; （2） the algal-lysing effects of the algicidal bacterium B5 on M. aeruginosa, Chlorella and Scenedesrnus were pronounced. The initial bacterial and algal cell densities strongly influence the removal rates of chlorophyll-a. The greater the initial bacterial cell density, the faster the degradation of chlorophyll-a. The greater the initial algal cell density, the slower the degradation of chlorophyll-a. When the bacterial cell density was 3.6 × 10^7 cells/ml, nearly 90% of chlorophyll-a was removed. When the chlorophyll-a concentration was less than 550 μg/L, about 70% was removed; （3） the strain B5 lysed algae by secreting metabolites and these metabolites could bear heat treatment.

Kinematic and Dynamic Characteristics Analysis of Bennett's Linkage

Bennett's linkage is a spatial fourlink linkage,and has an extensive application prospect in the deployable linkages.Its kinematic and dynamic characteristics analysis has a great significance in its synthesis and application. According to the geometrical conditions of Bennett 's linkage,the motion equations are established,and the expressions of angular displacement,angular velocity and angular acceleration of the followers and the displacement,velocity and acceleration of mass center of link are shown. Based on Lagrange's equation,the multi-rigid-body dynamic model of Bennett's linkage is established. In order to solve the reaction forces and moments of joint,screw theory and reciprocal screw method are combined to establish the computing method.The number of equations and unknown reaction forces and moments of joint are equal through adding link deformation equations. The influence of the included angle of adjacent axes on Bennett 's linkage 's kinematic characteristics,the dynamic characteristics and the reaction forces and moments of joint are analyzed.Results show that the included angle of adjacent axes has a great effect on velocity,acceleration,the reaction forces and moments of Bennett's linkage. The change of reaction forces and moments of joint are apparent near the singularity configuration.

Call Characteristics of Two Sympatric and Morphologically Similar Tree Frogs Species, Polypedates megacephalus and Polypedates mutus(Anura: Rhacophoridae), from Hainan, China

Anuran calls are usually species-specific and therefore valued as a tool for species identification. Call characteristics are a potential honest signal in sexual selection because they often reflect male body size. Polypedates megacephalus and P. mutus are two sympatric and morphologically similar tree frogs, but it remains unknown whether their calls are associated with body size. In this study, we compared call characteristics of these two species and investigated any potential relationships with body size. We found that P. megacephalus, males produced six call types which consisting of three distinct notes, while P. mutus males produced five types consisting of two types of notes. Dominant frequency, note duration, pulse duration, and call duration exhibited significant interspecific differences. In P. megacephalus, one note exhibited a dominant frequency that was negatively correlated with body mass, snout-vent length, head length, and head width. In P. mutus, the duration of one note type was positively correlated with body mass and head width. These differences in call characteristics may play an important role in interspecific recognition. Additionally, because interspecific acoustic variation reflects body size, calls may be relevant for sexual selection. Taken together, our results confirmed that calls are a valid tool for distinguishing between the two tree-frog species in the field.

RITT-WU'S CHARACTERISTIC SET METHOD FOR ORDINARY DIFFERENCE POLYNOMIAL SYSTEMS WITH ARBITRARY ORDERING

In this paper, a Ritt-Wu＇s characteristic set method for ordinary difference systems is proposed, which is valid for any admissible ordering. New definition for irreducible chains and new zero decomposition algorithms are also proposed.

Hybrid Feature Selection Method for Predicting Alzheimer’s Disease Using Gene Expression Data

Gene expression(GE)classification is a research trend as it has been used to diagnose and prognosis many diseases.Employing machine learning(ML)in the prediction of many diseases based on GE data has been a flourishing research area.However,some diseases,like Alzheimer’s disease(AD),have not received considerable attention,probably owing to data scarcity obstacles.In this work,we shed light on the prediction of AD from GE data accurately using ML.Our approach consists of four phases:preprocessing,gene selection(GS),classification,and performance validation.In the preprocessing phase,gene columns are preprocessed identically.In the GS phase,a hybrid filtering method and embedded method are used.In the classification phase,three ML models are implemented using the bare minimum of the chosen genes obtained from the previous phase.The final phase is to validate the performance of these classifiers using different metrics.The crux of this article is to select the most informative genes from the hybrid method,and the best ML technique to predict AD using this minimal set of genes.Five different datasets are used to achieve our goal.We predict AD with impressive values forMultiLayer Perceptron(MLP)classifier which has the best performance metrics in four datasets,and the Support Vector Machine(SVM)achieves the highest performance values in only one dataset.We assessed the classifiers using sevenmetrics;and received impressive results,allowing for a credible performance rating.The metrics values we obtain in our study lie in the range[.97,.99]for the accuracy(Acc),[.97,.99]for F1-score,[.94,.98]for kappa index,[.97,.99]for area under curve(AUC),[.95,1]for precision,[.98,.99]for sensitivity(recall),and[.98,1]for specificity.With these results,the proposed approach outperforms recent interesting results.With these results,the proposed approach outperforms recent interesting results.

Strategic Renewable Energy Resource Selection Using a Fuzzy Decision-Making Method

Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and wind.Energy resources are vital for all countries in terms of their economies and politics.As a result,selecting the optimal option for any country is critical in terms of energy investments.Every country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global warming.In the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous data.This study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp numbers.The hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective characteristics.The best-suited renewable energy alternative is discovered using the approach presented.

水泵水轮机S特性区能量损失及流动特性研究

为了调节电网的稳定性,抽水蓄能电站需要频繁启停和变换工况运行,导致水泵水轮机容易进入S特性区,机组振动增加,并网失败。本文以模型水泵水轮机为研究对象,采用熵产理论详细分析了S特性区不同工况下的能量损失规律,明确了熵产率分布与内部流动结构的关系。结果表明:S特性区内近飞逸工况总熵产最大,约为设计工况的5.1倍,脉动熵产占据的比例接近80%,随着流量的减小,转轮熵产占比逐渐降低,活动导叶和尾水管的熵产占比增加。小流量工况转轮进口靠近下环位置首先出现了明显的漩涡,导致了活动导叶出口和转轮进口的高熵产区,随着流量进一步减小,漩涡逐渐向上冠转移,并且切向速度增大,在转轮进口形成挡水环,阻碍水流进入转轮,在无叶区内出现了环状分布的高熵产区。反水泵工况,水流在低压边与逆时针旋转的叶片撞击,导致水流很难进入叶片内部,形成了大尺度的回流涡结构;双列叶栅内充满大量涡结构,导致活动导叶吸力面的熵产率增大,并且向固定导叶传播。

SSTA SIGNAL CHARACTERISTIC ANALYSIS OVER THE INDIAN OCEAN DURING RAINY SEASON IN CHINA

The teleconnection distribution characteristics of sea surface temperature (SST) over the India Ocean and the precipitation during rainy season in China were studied by using the methods of EOF and CCA. The results indicate that the change of SST field will affect the change of rain belt during rainy seasons in China, and greatly affect the precipitation in northwest and southwest China, the Yangzi and Yellow River downstream basins. Strong signal phenomena of SSTA over India Ocean were revealed that showed the anoma-lous distribution of drought and flood in China. It shows that the precipitation during rainy seasons in China may be forecast by analyzing SST distribution characteristics over the India Ocean.

Parkinson’s Disease Classification Using Random Forest Kerb Feature Selection

Parkinson’s disease(PD)is a neurodegenerative disease cause by a deficiency of dopamine.Investigators have identified the voice as the underlying symptom of PD.Advanced vocal disorder studies provide adequate treatment and support for accurate PD detection.Machine learning(ML)models have recently helped to solve problems in the classification of chronic diseases.This work aims to analyze the effect of selecting features on ML efficiency on a voice-based PD detection system.It includes PD classification models of Random forest,decision Tree,neural network,logistic regression and support vector machine.The feature selection is made by RF mean-decrease in accuracy and mean-decrease in Gini techniques.Random forest kerb feature selection(RFKFS)selects only 17 features from 754 attributes.The proposed technique uses validation metrics to assess the performance of ML models.The results of the RF model with feature selection performed well among all other models with high accuracy score of 96.56%and a precision of 88.02%,a sensitivity of 98.26%,a specificity of 96.06%.The respective validation score has an Non polynomial vector(NPV)of 99.47%,a Geometric Mean(GM)of 97.15%,a Youden’s index(YI)of 94.32%,and a Matthews’s correlation method(MCC)90.84%.The proposed model is also more robust than other models.It was also realised that using the RFKFS approach in the PD results in an effective and high-performing medical classifier.