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.

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.

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.

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.

选择性催化氧化H_(2)S的富氮碳催化剂研究进展

近年来,能高效净化H_(2)S并回收硫资源的选择性催化氧化技术(H_(2)S-SCO)受到了广泛关注.开发高性能、高选择性及低成本的催化剂是H_(2)S-SCO技术的研究重点,其中富氮碳基催化剂(RNCC)具有高活性、无金属、易制备、低成本且易再生等优点,被认为是一类极具潜力的H_(2)S-SCO催化剂.本文介绍了金属基催化剂的发展,总结和归纳RNCC的制备方法、催化活性和物化性质,系统地讨论RNCC的构-效关系及影响RNCC性能的关键因素,并总结了RNCC的H_(2)S-SCO反应机理.最后指出RNCC目前存在机遇和挑战,并展望了未来的发展方向.

基于改进D-S证据理论选择性集成的边坡稳定性评价

针对边坡稳定性预测算法选择困难和单个模型误判风险大的问题,建立了基于改进D-S证据理论选择性集成的边坡稳定性评价方法,为边坡稳定性初步评价提供方法依据。基于边坡稳定性主要影响因素,通过极限平衡法构建了大型边坡稳定性评价数据集。引入基于边界距离最小化的基学习器选择技术,提升选择性集成模型的泛化能力。提出了改进D-S证据理论融合基学习器信息,降低了选择性集成模型决策过程中的不确定性和模糊性,解决了现有边坡稳定性评价模型易误判和结果非一致性问题。仿真试验结果表明:改进D-S证据理论选择性集成方法无需复杂的数值建模与计算迭代过程,可直接客观地评判边坡稳定性状态,并从信息论角度给出边坡失稳概率。对比传统机器学习方法,该方法有效提高了边坡稳定性的预测准确率,同时降低了预测结果的不确定性,实现了速度快、精度高、稳健性好的广域尺度边坡稳定性评价。

一种S波段超宽带能量选择表面设计

设计了一种工作在S波段的能量选择表面,可实现超宽带自适应强电磁防护。该结构由两层金属周期结构组成,顶层为两个对称分布的金属条和一个金属片,金属条与金属片间加载两个PIN二极管;底层为十字架结构。当入射电磁波场强低于阈值时,能量选择表面工作在透波状态,电磁波可以传播;当入射电磁波场强超过阈值时,金属条和金属片之间产生的感应电压使得PIN二极管导通,此时能量选择表面进入防护状态,电磁波被屏蔽。通过对能量选择表面在PIN二极管导通和截止状态下的表面电流和电场分布以及等效电路模型进行分析,解释了该结构的工作原理。采用PCB制作工艺加工了实物样板并对弱场入射下的插入损耗以及强场入射下的防护效能进行测试。实验和仿真结果匹配性良好,表明该能量选择表面在透波状态下的工作中心频率为2.7 GHz,插入损耗小于1 dB的工作频带为2.2~3.5 GHz;在防护状态下,工作频带的防护效能大于10 dB,达到了超宽带的要求。

Research on the Development of Kindergarten-Based Curriculum with Tongyu New Year’s Paintings as Curriculum Resource

With the rapid development of modern society,the protection and inheritance of traditional culture are becoming increasingly important.As a part of Chinese traditional culture,Tongyu New Year’s Paintings,with their unique artistic style and rich cultural connotation,have become an excellent resource for exploring the beauty of tradition and inspiring creativity.Based on this,LH Kindergarten in Baicheng City,Jilin Province,has utilized Tongyu New Year’s Paintings as a curriculum resource to develop a school-based curriculum,“The Beauty of Tongyu New Year’s Paintings:Artistic Exploration for Teachers and Children.”Through diversified learning styles,teachers and children will learn about the history of New Year’s paintings,incorporate certain features of the paintings into their art activities,and cultivate creativity and the spirit of teamwork,so as to pass on the precious essence of traditional culture to children and carry forward the spirit of teamwork in their hearts.This program will lead children to experience the treasures of traditional culture and the rich connotations behind Chinese New Year’s paintings,laying a solid foundation for their growth and lifelong learning.

Research on the Teaching Optimization Path in Children’s Creative Art Curriculum Under the Perspective of“Sanquan Education”

Children’s creative art curriculum is a professional course supported by art materials and techniques and facilitated through creative activities,aiming at cultivating students’ability to organize creative art activities using various art materials and techniques.In light of the evolving focus in China’s colleges and universities from“what to know”to“how to apply,”the pivotal question for educators is how to maximize the value of children’s creative art curriculum.Based on this,this article takes“Sanquan education”as the starting point,combines factual and theoretical arguments,and analyzes the teaching optimization path of children’s creative art curriculum under the perspective of Sanquan education,to improve the quality and efficiency of teaching.

Engineering asymmetric electronic structure of cobalt coordination on CoN_(3)S active sites for high performance oxygen reduction reaction

The efficacy of the oxygen reduction reaction(ORR) in fuel cells can be significantly enhanced by optimizing cobalt-based catalysts,which provide a more stable alternative to iron-based catalysts.However,their performance is often impeded by weak adsorption of oxygen species,leading to a 2e^(-)pathway that negatively affects fuel cell discharge efficiency.Here,we engineered a high-density cobalt active center catalyst,coordinated with nitrogen and sulfur atoms on a porous carbon substrate.Both experimental and theoretical analyses highlighted the role of sulfur atoms as electron donors,disrupting the charge symmetry of the original Co active center and promoting enhanced interaction with Co 3d orbitals.This modification improves the adsorption of oxygen and reaction intermediates during ORR,significantly reducing the production of hydrogen peroxide(H_(2)O_(2)).Remarkably,the optimized catalyst demonstrated superior fuel cell performance,with peak power densities of 1.32 W cm^(-2) in oxygen and 0.61 W cm^(-2) in air environments,respectively.A significant decrease in H_(2)O_(2) by-product accumulation was observed during the reaction process,reducing catalyst and membrane damage and consequently improving fuel cell durability.This study emphasizes the critical role of coordination symmetry in Co/N/C catalysts and proposes an effective strategy to enhance fuel cell performance.

Understanding the individual with Alzheimer’s disease: Can socioemotional selectivity theory guide us?

Individuals often get lost behind the diagnosis of Alzheimer’s disease (AD) while widespread differences between these patients are morecommon than similarities. Socioemotional Selectivity Theory (SST) suggests that as we age our goals change from future-oriented (acquiringnew information) to present-oriented (enhancing the emotional, especially positive, meaning of encounters). The goal of the current article is to examine whether the principles of SST might also apply for people with AD. Some aspects of SST are found especially in the early stages of AD when awareness is often intact and cognitive impairment is relatively limited. This review has clinical significance for the treatment of AD because it focuses on what is important to the individual rather than treating patients as a homogenous group. It also highlights the importance of social networks and emphasizes the role of the proxy in AD care. Lastly, it suggests that if those with AD (like the healthy elderly) have a positivity bias then positive emotional stimuli/wording/instructions could usefully be employed in their daily treatment. I suggest that SST may be a useful starting point when attempting to address what matters to individuals with AD and conclude by providing a few suggestions for future studies.

Effect of twine thickness on size-selectivity of driftnet for the yellow croaker Larimichthys polyactis in southwestern Sea of Korea

In order to determine the effect of twine thickness on the size-selectivity of the driftnet used for the yellow croaker, size-selectivity tests were conducted with three different twine thicknesses(monofi lament diameters of 0.279 mm(number's method; No. 3), 0.321 mm(No. 4), and 0.360 mm(No. 5)) of driftnets for the yellow croaker in the seas around Chooja-do, Jeju Islands. The selectivity curve was estimated by using Kitahara's method. In order to determine the physical properties of the twine used in the experimental fi shing nets, we measured the breaking load, elongation, and stiffness under both dry and wet conditions. In terms of physical properties, the thinnest twine(No. 3) had the strongest breaking strength per unit cross-sectional area, along with good elongation and excellent fl exibility. The thickest twine(No. 5) had the lowest fl exibility. In terms of selectivity, the net of No. 3 twine showed the broadest selection range and, thus, a relatively low selectivity compared with the other nets, while the less fl exible net of No. 5 twine showed the narrowest selectivity range and high selectivity. In addition, it was found that a thicker twine resulted in a smaller haul of small fi sh. Therefore, it can be inferred that the thickness of the twine affects the size of the catch and selectivity, and thus the size composition of the catch as well.

Analysis of New Senior English for China Student’s Book 1

This article will firstly discuss the context overview of English teaching and learning in China. Under thiscircumstance, a problematic element will be examined of the New Senior English for China Student’s Book 1 and critical appraisal ofhow this element relates to other elements of curriculum development will be analyzed. The recommended changes and demonstrationmechanisms for evaluating the changes are put forward in the last two parts.

La_(2)FeMO_(6)双钙钛矿中的不对称氧空位用于促进氧活化和H2S选择性氧化

金属氧化物催化剂表面O_(2)分子的活化对于多相催化中氧化还原反应具有重要意义.硫化氢(H_(2)S)选择性氧化是一个典型的氧化反应,通常用于去除克劳斯工艺尾气中有害的H_(2)S,同时回收化工产品硫磺.受克劳斯反应的热力学限制,工艺尾气中仍有近1%的H_(2)S残留,在焚烧炉中会转化为有害的SO_(x),造成不必要的硫损失以及严重的环境问题.研究表明,氧分子活化解离产生的活性氧物种是H_(2)S选择氧化的关键活性物种.然而,受限于氧分子的低效活化,传统催化剂需提高反应温度以获得令人满意的H_(2)S转化率,这也促进了副反应的进行并生成有害副产物SO_(2).因此,迫切需要在较低温度下实现氧分子的高效活化以促进H_(2)S选择氧化反应的进行,从而最大限度地提高克劳斯工艺硫回收效率并降低运营成本.目前,大多数研究通过引入更多的氧空位促进氧分子的活化及氧化反应的进行,但很少有人考虑氧空位本身结构的影响.近年来,研究者更多地关注不对称氧/空位(M_(1)-O-M_(2)或M_(1)-VO-M_(2)),该特殊结构可以有效地优化氧分子的活化,提高催化性能.本文报道了一种简单的氧空位调控策略用于H_(2)S选择氧化,通过过渡金属(M=Mn,Co和Mo)取代策略在LaFeO_(3)钙钛矿催化剂中引入不对称氧空位,从而激发氧分子活化以促进H_(2)S选择氧化的进行.X射线粉末衍射、Raman光谱及透射电镜结果表明,Mn和Co的引入形成了均匀的La_(2)FeMO_(6)以及La_(2)FeCoO_(6)双钙钛矿相,而Mo的引入则形成了La_(2)Mo_(2)O_(9)和LaFeO_(3)钙钛矿的混相.X射线光电子能谱及M?ssbauerr谱结果表明,Mn取代形成的La_(2)FeMO_(6)双钙钛矿催化剂由于其结构中Mn与Fe的完全交替取代形成了丰富的不对称Fe-VO-Mn位点,结合H_(2)程序升温还原及O_(2)程序升温解吸结果,可以推断不对称空位促进了催化剂上氧分子的活化,进而提高了催化剂的氧迁移率和还原性.模拟计算了氧分子在LaFeO_(3)及La_(2)FeMO_(6)催化剂上的吸附及解离过程,结果表明,氧分子在对称的Fe-VO-Fe位点上具有较高的吸附能及解离能,在不对称的Fe-VO-Mn位点上不存在稳定的吸附态,倾向于直接解离形成活性氧物种.具有丰富不对称Fe-VO-Mn位点的La_(2)FeMO_(6)催化剂的H_(2)S选择氧化低温活性和稳定性显著提高,在较宽的温度窗口内均可保持较好的H_(2)S转化率(>90%)与硫选择性(接近100%).综上,本文通过取代策略实现了对催化剂氧空位结构的调控,揭示了不对称氧空位对氧分子活化行为的促进机制.研究结果不仅为合理设计高效氧化催化剂探明了一条可行的途径,还对氧分子活化过程中氧空位结构的促进机制提供了深入的见解,有望激发更多关于开发氧化还原反应高效催化材料的研究.

基层选调生激励差异及行为选择研究--基于S-O-R理论视角的双案例对比分析

基层选调生作为助力乡村发展的高学历、高层次人力资本,能否有效激发其工作积极性直接关系到乡村振兴管理维度的持续增益与产出。基于此,本文以湖南省岳阳市A村与株洲市B村的选调生为例,基于S-O-R理论提出刺激构成-承载有机体-行为反应的分析框架,对所在市区政策环境、村庄产业建设情况、基层选调生行为选择展开对比分析。同质化政策工具未能吸纳差异性环境要素,致使基层选调生异质性行为选择。不同刺激构成通过承载有机体传导至行动者,并由此产生异质性行为选择模式。一元行政手段未能将多元价值纳入考量维度,应建立均衡制激励机制,增加微观层面的具体激励占比,实现基层人力资本的有效开发与利用。

Comparative Analysis of Improving Effects of 12 Maize Populations with Improved S_1 Selection Method

ln this study, 12 maize populations were improved with the improved S1 selection method, aiming to increase the improvement efficiency of maize popula-tions. The results showed that number of rows per spike, number of grains per row and 100-grain weight were the three important component traits of maize yield. The highest genetic increment was found in Mengqun 2, fol owed by Mengqun 4, Mengqun 1 and other 7 maize populations. Negative genetic increment was shown in Mengqun 3 and 3 introduced foreign maize populations. Some changes were shown in spikes, plant traits and genetic diversity of maize populations. Based on our results, we concluded that Mengqun 2, Mengqun 4, Zhongzong 7, Mengqun C and Mengqun A could be directly used for the line breeding by selfing for their higher genetic increment of yield and better improvement effects of other agricultural traits. Compared with these 5 populations, the improvement potential of other maize populations was limited for their lower genetic increment.

基于Pearson相关系数与广义S变换的低压直流微电网的故障选线方法

针对低压直流微电网线路的故障选线方法的研究有限,提出一种基于Pearson相关系数与广义S变换的故障选线方法。首先,介绍了低压直流微电网的一般组成。在此基础上,研究了低压直流微电网的单极故障以及极间故障的故障特征,提出选线方法,对各线路正负极首末端电流差进行Pearson相关系数计算来确定故障线路。然后对所选故障线路正负线路首端的电流量进行广义S变换,计算出其能量和的比值判别故障极性或者极间故障。最后,在PSCAD/EMTDC中搭建出低压直流微电网模型以输出各线路电流数据,并利用Matlab对数据进行仿真。结果表明,所提选线方法直接有效,且耐受过渡电阻的能力较强。

塔河油田H_(2)S-CO_(2)-O_(2)共存体系下伴生气管道选材和内涂层评价

研究伴生气管道常用3种管材在H_(2)S-CO_(2)-O_(2)3种气体共存体系下的腐蚀行为,可为塔河油田伴生气管道的腐蚀防控提供指导依据。基于塔河油田典型腐蚀工况,以20钢、L245NS钢和3Cr钢为研究对象,利用高温高压釜试验对3种钢材典型H_(2)S-CO_(2)-O_(2)共存工况下的腐蚀速率和腐蚀产物进行研究,得到20钢腐蚀速率最大,L245NS钢腐蚀速率次之,3Cr钢腐蚀速率最小,3种管材的腐蚀产物主要是Fe、FeS、FeCO_(3)和Fe_(2)O_(3)。对塔河油田4种典型内防腐涂层进行腐蚀前后增重法和附着力测试研究涂层的耐蚀行为,涂层2的抗腐蚀性能和附着力效果最好。考虑性价比,最后选用“L245NS+涂层2”作为塔河油田伴生气管线的防腐措施。

采用灰色关联和D⁃S证据理论的压射工艺参数选择方法

合理的压射工艺对于提高压铸生产效率和降低压铸件缺陷意义重大。本文针对压铸过程中的压射工艺参数的选择提出了基于灰色关联和D-S证据理论相融合的决策方法,摆脱了以往依托专家经验的试错法,使得压射工艺参数的选择更具有科学性。实验证明本文提出的方法在满足准确性的同时具有高效性。

Structural engineering of 3D hierarchical Cd0.8Zn0.2S for selective photocatalytic CO2 reduction

The solar-driven catalytic conversion of CO2 to useful chemical fuels is regarded as an environmentally friendly approach to reduce the consumption of fossil fuels and mitigate the greenhouse effect.However,it is highly intriguing and challenging to promote the selectivity and efficiency of visible-light-responsive photocatalysts that favor the adsorption of CO2 in photoreduction processes.In this work,three-dimensional hierarchical Cd0.8Zn0.2S flowers(C8Z2S-F)with ultrathin petals were successfully synthesized through an in-situ self-assembly growth process using sodium citrate as a morphology director.The flower-like Cd0.8Zn0.2S solid solution exhibited remarkable photocatalytic performance in the reduction of CO2,generating CO up to 41.4μmol g^−1 under visible-light illumination for 3 h;this was nearly three times greater than that of Cd0.8Zn0.2S nanoparticles(C8Z2S-NP)(14.7μmol g^−1).Particularly,a comparably high selectivity of 89.9%for the conversion of CO2 to CO,with a turnover number of 39.6,was obtained from the solar-driven C8Z2S-F system in the absence of any co-catalyst or sacrificial agent.Terahertz time-domain spectroscopy indicated that the introduction of flower structures enhanced the light-harvesting capacity of C8Z2S-F.The in situ diffuse reflectance infrared Fourier transform spectroscopy unveiled the existence of surface-adsorbed species and the conversion of photoreduction intermediates during the photocatalytic process.Empirical characterizations and predictions of the photocatalytic mechanism demonstrated that the flower-like Cd0.8Zn0.2S solid solution possessed desirable CO2 adsorption properties and an enhanced charge-transfer capability,thus providing a highly effective photocatalytic reduction of CO2.