Security of earthquake disaster reduction system

No matter whether a system is operated manually or automatically controlled by computer, the system’s vulnerability always exists. Earthquake Disaster Reduction System (EDRS) belongs to the category of information system. According to the features of security for EDRS, the steps and the methods on how to build the EDRS security were analyzed. The EDRS security features, security strategies and security measures were also given through a distributed EDRS skeleton that has been applied. Because there was still no appointed and authoritative agency or organization to certify and test EDRS security in China, a national information technology security certification center was introduced and suggested for the certification of the EDRS security. Finally, several discussions and tendencies for the EDRS development were presented.

Redevelopment of Daqing Oil Field distributed earthquake disaster reduction system skeleton

Through investigation on the international development trend of earthquake disaster reduction system(EDRS)researches,a well finished Daqing Oilfield EDRS is introduced.Based on the PC System,redevelopment of the EDRS skeleton is well discussed,including the technical skeleton,function composition,structures of software and hardware,redevelopment languages,database,and remote linking and calling of analysis modules.Meanwhile,it is pointed out that extending and utilizing the function of remote sensing information on the basis of the current distributed EDRS skeleton will become another study direction of EDRS.

KBH_4/BiCl_3──A New and Facile Reduction System for the Conversion of Aromatic Nitro Compounds to Primary Ammes

s: Vinous aromatic nitro compounds could be selectively and rapidly reduced to the corresponding amines in excellent yields by potassium borohydride - bismuth chloride/ethanol-water, a new and facile reductive system.

Biodegradability of Formulated Enzymatic Solution: An Alternative Waste Reduction System

Solid waste and air pollution are never ending environmental problems that can be partially solved by turning waste into useful bio-products. In this study, enzymatic solutions were developed by formulating enzymatic solutions from fish intestines and fruit peels. This aimed to help in biodegradation of organic solid wastes. Organic waste samples were treated with formulated enzymatic solutions for 7 days in aerated set-up for aerobic degradation. Biodegradability and odor of the waste samples were compared with commercial enzymatic solution. Determination of evolved carbon dioxide (CO2) using gravimetric analysis (GA) was used to determine the percent biodegradability, Dt, of organic solid waste and odor-ranking method was used to determine the odor intensity of the organic waste samples. The result showed that the weight loss and percentage biodegradability of organic waste sample treated with formulated enzymatic solution is comparable with that of the commercial enzymatic solution. In terms of odor intensity, waste treated with the product, formulated enzymatic solution (FES) is also comparable to the waste treated with commercial enzymatic solution. Thus, implying that the developed FES is as efficient as that of the commercial enzymatic solution. These significant results will be helpful to future researchers in providing ways on improving the degradation of organic solid waste and mitigating the increasing glitches on our environment. Enzyme kinetics, physical and chemical properties studies of the solution were recommended for future researchers to accurately determine the effectiveness of the formulated enzymatic solution in the degradation of organic solid waste.

Single-atom catalysis for advanced oxidation and reduction systems in water decontamination

Water scarcity is an escalating global crisis,posing a severe threat to populations worldwide.Consequently,exploring various materials to remove emerging contaminants from freshwater sources has garnered significant attention.In this regard,single-atom catalysis(SACs) has emerged as a catalyst of scientific progress in water purification and treatment methodologies during recent decades.SACs exhibit exceptional catalytic activity,selectivity and stability,due to their near-perfect atom utilization,highly unsaturated coordination environment and uniform reaction centers.However,a comprehensive and critical review encompassing the successful integration of SACs into water purification processes needs to be completed.This review aims to accentuate recent trends by presenting the synthesis,structure,and environment and energy application-relevant properties of SACs.The results show that a comprehensive and multi-perspective summary of the advantages of SACs in environmental remediation can have significant benefits,such as fast kinetics,costeffectiveness,selectivity.The oxidation and reduction processes of SACs and functional SACs materials in water purification were emphasized.Furthermore,the last section is devoted to the current research gaps and further perspectives on the application of SACs in water treatment,which are summarized and analyzed.

A Dynamical System-Based Framework for Dimension Reduction

We propose a novel framework for learning a low-dimensional representation of data based on nonlinear dynamical systems,which we call the dynamical dimension reduction(DDR).In the DDR model,each point is evolved via a nonlinear flow towards a lower-dimensional subspace;the projection onto the subspace gives the low-dimensional embedding.Training the model involves identifying the nonlinear flow and the subspace.Following the equation discovery method,we represent the vector field that defines the flow using a linear combination of dictionary elements,where each element is a pre-specified linear/nonlinear candidate function.A regularization term for the average total kinetic energy is also introduced and motivated by the optimal transport theory.We prove that the resulting optimization problem is well-posed and establish several properties of the DDR method.We also show how the DDR method can be trained using a gradient-based optimization method,where the gradients are computed using the adjoint method from the optimal control theory.The DDR method is implemented and compared on synthetic and example data sets to other dimension reduction methods,including the PCA,t-SNE,and Umap.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

Operationally Simple Enantioselective Silane Reduction of Ketones by the [Ir(OMe)(cod)]2/Azolium Catalytic System

An operationally simple protocol was designed for the enantioselective silane reduction (ESR) of ketones using air- and moisture-stable [Ir(OMe)(cod)]2 (cod = 1,5-cyclooctadiene) (3) as a metal catalyst precursor. This reaction was driven by chiral hydroxyamide-functionalized azolium salt 2. The catalytic ESR reaction could be performed under benchtop conditions at room temperature. Treatment of 2 with 3 in THF yielded the monodentate IrCl(NHC)(cod) (NHC = N-heterocyclic carbene) complex 4 in 93% yield, herein the anionic methoxy ligand of 3 serves as an internal base that deprotonates the azolium ring of 2. The well-defined Ir complex 4 catalyzed the ESR reaction of propiophenone (6) with (EtO)2MeSiH using the pre-mixing reaction procedure. Based on this success, the catalytic ESR reaction was designed and implemented using an in situ-generated NHC/Ir catalyst derived from 2 and 3. Thus, a wide variety of aryl ketones could be reduced to the corresponding optically active alcohols in moderate to excellent stereoselectivities at room temperature without temperature control. Since the high catalytic activity of 3 was observed, we next evaluated several other transition metal catalyst precursors for the catalytic ESR reaction under the influence of 2. This evaluation revealed that Ir(acac)(cod) (acac = acetylacetonate) (28) and [IrCl(cod)]2 (5) can be successfully used as metal catalyst precursors in the ESR reaction.

Electro-enzyme coupling systems for selective reduction of CO_(2)

To address the energy crisis and alleviate the rising level of CO_(2)in the atmosphere,various CO_(2)capture and utilization(CCU)technologies have been developed.The use of electro-enzyme coupling systems is a promising strategy for the sustainable production of fuels,chemicals and materials using CO_(2)as the feedstock.In this review,the recent progresses in the development of electro-enzyme coupling systems for the selective reduction of CO_(2)are systematically summarized.We first provide a brief background about the significance and challenges in the direct conversion of CO_(2)into value-added chemicals.Next,we describe the materials and strategies in the design of electrodes,as well as the common enzymes used in the electro-enzyme coupling systems.Then,we focus on the state-of-the-art routes for the electro-enzyme coupling conversion of CO_(2)into a variety of compounds(formate,CO,methanol,C≥2chemicals)by a single enzyme or multienzyme systems.The emerging approaches and materials used for the construction of electro-enzyme coupling systems to enhance the electron transfer efficiency and the catalytic activity/stability are highlighted.The main challenges and perspectives in the integration of enzymatic and electrochemical strategies are also discussed.

Strong synergy between physical and chemical properties:Insight into optimization of atomically dispersed oxygen reduction catalysts

Atomically dispersed catalysts exhibit significant influence on facilitating the sluggish oxygen reduction reaction(ORR)kinetics with high atom economy,owing to remarkable attributes including nearly 100%atomic utilization and exceptional catalytic functionality.Furthermore,accurately controlling atomic physical properties including spin,charge,orbital,and lattice degrees of atomically dispersed catalysts can realize the optimized chemical properties including maximum atom utilization efficiency,homogenous active centers,and satisfactory catalytic performance,but remains elusive.Here,through physical and chemical insight,we review and systematically summarize the strategies to optimize atomically dispersed ORR catalysts including adjusting the atomic coordination environment,adjacent electronic orbital and site density,and the choice of dual-atom sites.Then the emphasis is on the fundamental understanding of the correlation between the physical property and the catalytic behavior for atomically dispersed catalysts.Finally,an overview of the existing challenges and prospects to illustrate the current obstacles and potential opportunities for the advancement of atomically dispersed catalysts in the realm of electrocatalytic reactions is offered.

Numerical Study on Reduction in Aerodynamic Drag and Noise of High-Speed Pantograph

Reducing the aerodynamic drag and noise levels of high-speed pantographs is important for promoting environmentally friendly,energy efficient and rapid advances in train technology.Using computational fluid dynamics theory and the K-FWH acoustic equation,a numerical simulation is conducted to investigate the aerodynamic characteristics of high-speed pantographs.A component optimization method is proposed as a possible solution to the problemof aerodynamic drag and noise in high-speed pantographs.The results of the study indicate that the panhead,base and insulator are the main contributors to aerodynamic drag and noise in high-speed pantographs.Therefore,a gradual optimization process is implemented to improve the most significant components that cause aerodynamic drag and noise.By optimizing the cross-sectional shape of the strips and insulators,the drag and noise caused by airflow separation and vortex shedding can be reduced.The aerodynamic drag of insulator with circular cross section and strips with rectangular cross section is the largest.Ellipsifying insulators and optimizing the chamfer angle and height of the windward surface of the strips can improve the aerodynamic performance of the pantograph.In addition,the streamlined fairing attached to the base can eliminate the complex flow and shield the radiated noise.In contrast to the original pantograph design,the improved pantograph shows a 21.1%reduction in aerodynamic drag and a 1.65 dBA reduction in aerodynamic noise.

Single-atom catalysts for the electrochemical reduction of carbon dioxide into hydrocarbons and oxygenates

The electrochemical reduction of carbon dioxide offers a sound and economically viable technology for the electrification and decarbonization of the chemical and fuel industries.In this technology,an electrocatalytic material and renewable energy-generated electricity drive the conversion of carbon dioxide into high-value chemicals and carbon-neutral fuels.Over the past few years,single-atom catalysts have been intensively studied as they could provide near-unity atom utilization and unique catalytic performance.Single-atom catalysts have become one of the state-of-the-art catalyst materials for the electrochemical reduction of carbon dioxide into carbon monoxide.However,it remains a challenge for single-atom catalysts to facilitate the efficient conversion of carbon dioxide into products beyond carbon monoxide.In this review,we summarize and present important findings and critical insights from studies on the electrochemical carbon dioxide reduction reaction into hydrocarbons and oxygenates using single-atom catalysts.It is hoped that this review gives a thorough recapitulation and analysis of the science behind the catalysis of carbon dioxide into more reduced products through singleatom catalysts so that it can be a guide for future research and development on catalysts with industry-ready performance for the electrochemical reduction of carbon dioxide into high-value chemicals and carbon-neutral fuels.

Porous metal oxides in the role of electrochemical CO_(2) reduction reaction

The global energy-related CO_(2) emissions have rapidly increased as the world economy heavily relied on fossil fuels.This paper explores the pressing challenge of CO_(2) emissions and highlights the role of porous metal oxide materials in the electrocatalytic reduction of CO_(2)(CO_(2)RR).The focus is on the development of robust and selective catalysts,particularly metal and metal-oxide-based materials.Porous metal oxides offer high surface area,enhancing the accessibility to active sites and improving reaction kinetics.The tunability of these materials allows for tailored catalytic behavior,targeting optimized reaction mechanisms for CO_(2)RR.The work also discusses the various synthesis strategies and identifies key structural and compositional features,addressing challenges like high overpotential,poor selectivity,and low stability.Based on these insights,we suggest avenues for future research on porous metal oxide materials for electrochemical CO_(2) reduction.

Surface engineering of ZnO electrocatalyst by N doping towards electrochemical CO_(2) reduction

The discovery of efficient,selective,and stable electrocatalysts can be a key point to produce the largescale chemical fuels via electrochemical CO_(2) reduction(ECR).In this study,an earth-abundant and nontoxic ZnO-based electrocatalyst was developed for use in gas-diffusion electrodes(GDE),and the effect of nitrogen(N)doping on the ECR activity of ZnO electrocatalysts was investigated.Initially,a ZnO nanosheet was prepared via the hydrothermal method,and nitridation was performed at different times to control the N-doping content.With an increase in the N-doping content,the morphological properties of the nanosheet changed significantly,namely,the 2D nanosheets transformed into irregularly shaped nanoparticles.Furthermore,the ECR performance of Zn O electrocatalysts with different N-doping content was assessed in 1.0 M KHCO_(3) electrolyte using a gas-diffusion electrode-based ECR cell.While the ECR activity increased after a small amount of N doping,it decreased for higher N doping content.Among them,the N:ZnO-1 h electrocatalysts showed the best CO selectivity,with a faradaic efficiency(FE_(CO))of 92.7%at-0.73 V vs.reversible hydrogen electrode(RHE),which was greater than that of an undoped Zn O electrocatalyst(FE_(CO)of 63.4%at-0.78 V_(RHE)).Also,the N:ZnO-1 h electrocatalyst exhibited outstanding durability for 16 h,with a partial current density of-92.1 mA cm^(-2).This improvement of N:ZnO-1 h electrocatalyst can be explained by density functional theory calculations,demonstrating that this improvement of N:ZnO-1 h electrocatalyst comes from(ⅰ)the optimized active sites lowering the free energy barrier for the rate-determining step(RDS),and(ⅱ)the modification of electronic structure enhancing the electron transfer rate by N doping.

Exploring the impact of Nafion modifier on electrocatalytic CO_(2) reduction over Cu catalyst

Nafion as a universal polymer ionomer was widely applied for nanocatalysts electrode preparation.However,the effect of Nafion on electrocatalytic performance was often overlooked,especially for CO_(2)electrolysis.Herein,the key roles of Nafion for CO_(2)RR were systematically studied on Cu nanoparticles(NPs)electrocatalyst.We found that Nafion modifier not only inhibit hydrogen evolution reaction(HER)by decreasing the accessibility of H_(2)O from electrolyte to Cu NPs,and increase the CO_(2)concentration at electrocatalyst interface for enhancing the CO_(2)mass transfer process,but also activate CO_(2)molecule by Lewis acid-base interaction between Nafion and CO_(2)to accelerate the formation of^(*)CO,which favor of C–C coupling for boosting C_(2)product generation.Owing to these features,the HER selectivity was suppressed from 40.6%to 16.8%on optimal Cu@Nafion electrode at-1.2 V versus reversible hydrogen electrode(RHE),and as high as 73.5%faradaic efficiencies(FEs)of C_(2)products were achieved at the same applied potential,which was 2.6 times higher than that on bare Cu electrode(~28.3%).In addition,Nafion also contributed to the long-term stability by hinder Cu NPs morphology reconstruction.Thus,this work provides insights into the impact of Nafion on electrocatalytic CO_(2)RR performance.

Preferentially selective extraction of lithium from spent LiCoO_(2)cathodes by medium-temperature carbon reduction roasting

Lithium recovery from spent lithium-ion batteries(LIBs)have attracted extensive attention due to the skyrocketing price of lithium.The medium-temperature carbon reduction roasting was proposed to preferential selective extraction of lithium from spent Li-CoO_(2)(LCO)cathodes to overcome the incomplete recovery and loss of lithium during the recycling process.The LCO layered structure was destroyed and lithium was completely converted into water-soluble Li2CO_(3)under a suitable temperature to control the reduced state of the cobalt oxide.The Co metal agglomerates generated during medium-temperature carbon reduction roasting were broken by wet grinding and ultrasonic crushing to release the entrained lithium.The results showed that 99.10%of the whole lithium could be recovered as Li2CO_(3)with a purity of 99.55%.This work provided a new perspective on the preferentially selective extraction of lithium from spent lithium batteries.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

Optimum Profiles of Endwall Contouring for Enhanced Net Heat Flux Reduction and Aerodynamic Performance

Successfully utilized non-axisymmetric endwalls to enhance turbine efficiencies(aerodynamic and turbine inlet temperatures)by controlling the characteristics of the secondary flow in a blade passage.This is accomplished by steady-state numerical hydrodynamics and deep knowledge of the field of flow.Because of the interaction between mainstream and purge flow contributing supplementary losses in the stage,non-axisymmetric endwalls are highly susceptible to the inception of purge flow exit compared to the flat and any advantage rapidly vanishes.The conclusions reveal that the supreme endwall pattern could yield a lowering of the gross pressure loss at the design stage and is related to the size of the top-loss location being productively lowered.This has led to diminished global thermal exchange lowered in the passage of the vane alone.The reverse flow adjacent to the suction side corner of the endwall is migrated farther from the vane surface,as the deviated pressure spread on the endwall accelerates the flow and progresses the reverse flow core still downstream.The depleted association between the tornado-like vortex and the corner vortex adjacent to the suction side corner of the endwall is the dominant mechanism of control in the contoured end wall.In this publication,we show that the non-axisymmetric endwall contouring by selective numerical shape change method at most prominent locations is advantageous in lowering the thermal load in turbines to augment the net heat flux reduction as well as the aerodynamic performance using multi-objective optimization.

An efficient photocatalytic CO_(2) reduction system improved by emodin as a redox mediator

Solar-driven photoreduction of CO_(2)to value-added fuels such as CO,CH_(4),and CH_(3)OH is a promising approach for alleviating the greenhouse effect.Transition-metal-complex molecular catalysts exhibit high catalytic performance for CO_(2)reduction owing to their tunable structures.In this study,we developed an efficient,inexpensive,and noble-metal-free photocatalytic CO_(2)reduction system containing an organic photosensitizer proflavine,a cobalt molecular catalyst,and an organic electron transfer relay emodin in DMF/H_(2)O(DMF:N,N-dimethylformamide)solvent.In the presence of water,a turnover number(TON)of 1333 was achieved for CO_(2)-to-CO conversion under ambient conditions and visible light irradiation,which is a 1.7-fold improvement over the system without emodin.In addition,a high selectivity of 90%was obtained for CO production.Absorption spectroscopy and cyclic voltammetry confirmed the crucial role of emodin in facilitating electron transfer between the photosensitizer and catalyst.We expect that our system will promote the development of an effective homogenous photocatalytic solar-fuel production technology.

Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

An information system is a type of knowledge representation,and attribute reduction is crucial in big data,machine learning,data mining,and intelligent systems.There are several ways for solving attribute reduction problems,but they all require a common categorization.The selection of features in most scientific studies is a challenge for the researcher.When working with huge datasets,selecting all available attributes is not an option because it frequently complicates the study and decreases performance.On the other side,neglecting some attributes might jeopardize data accuracy.In this case,rough set theory provides a useful approach for identifying superfluous attributes that may be ignored without sacrificing any significant information;nonetheless,investigating all available combinations of attributes will result in some problems.Furthermore,because attribute reduction is primarily a mathematical issue,technical progress in reduction is dependent on the advancement of mathematical models.Because the focus of this study is on the mathematical side of attribute reduction,we propose some methods to make a reduction for information systems according to classical rough set theory,the strength of rules and similarity matrix,we applied our proposed methods to several examples and calculate the reduction for each case.These methods expand the options of attribute reductions for researchers.