Network autoregression model with grouped factor structures

Network autoregression and factor model are effective methods for modeling network time series data.In this study,we propose a network autoregression model with a factor structure that incorporates a latent group structure to address nodal heterogeneity within the network.An iterative algorithm is employed to minimize a least-squares objective function,allowing for simultaneous estimation of both the parameters and the group structure.To determine the unknown number of groups and factors,a PIC criterion is introduced.Additionally,statistical inference of the estimated parameters is presented.To assess the validity of the proposed estimation and inference procedures,we conduct extensive numerical studies.We also demonstrate the utility of our model using a stock dataset obtained from the Chinese A-Share stock market.

Variations in leaf functional traits among plant species grouped by growth and leaf types in Zhenjiang,China

Leaf functional traits are adaptations that enable plants to live under various environmental conditions. This study aims to determine the differences in leaf functional traits among plants grouped by growth habit, leaf life span,leaf lifestyle, leaf form, and origin. Specific leaf area（SLA） of perennial or evergreen species was lower than that of annual or deciduous species because longer-lived leaves of perennial or evergreen species require more investment in structural integrity and/or defense against disturbances, especially with any resource constraint. SLA of large individuals was lower than that of small individuals. The low SLA in large individuals can improve their response to changing light and water conditions because increasing plant height is advantageous for light competition, but it can also impose a cost in terms of structural support and water transport. Petioles of plants with compound leaves were significantly longer than those of simple leaves because branching is expensive in terms of gaining height. SLA of plants increased with increasing invasiveness accordingly, and SLA of invasive plants was higher than that of their native congeners because invasive plants should invest more biomass on leaf growth rather than leaf structures per unit area to achieve a higher growth rate.Overall, variation in leaf functional traits among different groups may play an adaptive role in the successful survival of plants under diverse environments because leaf functional traits can lead to pronounced effects on leaf function,especially the acquisition and use of light. Plant species with different growth and leaf traits balance resource acquisition and leaf construction to minimize trade-offs and achieve fitness advantages in their natural habitat.

STATISTICAL INFERENCE FOR A BIVARIATE EXPONENTIAL DISTRIBUTION BASED ON GROUPED DATA

Consider the bivariate exponential distribution due to Marshall and Olkin[2], whose survival function is F(x, g) = exp[-λ1x-λ2y-λ12 max(x, y)] (x 0,y 0)with unknown Parameters λ1 > 0, λ2 > 0 and λ12 0.Based on grouped data, a newestimator for λ1, λ2 and λ12 is derived and its asymptotic properties are discussed.Besides, some test procedures of equal marginals and independence are given. Asimulation result is given, too.

On the Power Performance of Test Statistics for the Generalized Rayleigh Interval Grouped Data

In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.

Novel Grouped Probability Data Association Algorithm for MIMO Detection

To bridge the performance gap between original probability data association （PDA） algorithm and the optimum maximum a posterior （MAP） algorithm for multi-input multi-output （MIMO） detection, a grouped PDA （GP-PDA） detection algorithm is proposed. The proposed GP-PDA method divides all the transmit antennas into groups, and then updates the symbol probabilities group by group using PDA computations. In each group, joint a posterior probability （APP） is computed to obtain the APP of a single symbol in this group, like the MAP algorithm. Such new algorithm combines the characters of MAP and PDA. MAP and original PDA algorithm can be regarded as a special case of the proposed GP-PDA. Simulations show that the proposed GP-PDA provides a performance and complexity trade, off between original PDA and MAP algorithm.

Parameters estimation and application of generalized exponential distribution under grouped and right-censored data

Generalized exponential distribution is a class of important distribution in lifedata analysis,especially in some skewed lifedata.The Parameter estimation problem for generalized exponential distribution model with grouped and right-censored data is considered.The maximum likelihood estimators are obtained using the EM algorithm.Some simulations are carried out to illustrate that the proposed algorithm is effective for the model.Finally,a set of medicine data is analyzed by generalized exponential distribution.

金融机构ESG投资的“漂绿”与“反漂绿”——基于DWSGroup的案例分析

深化绿色金融发展、助力经济绿色发展,是实现“双碳”目标的重要途径,特别是在ESG理念盛行的今天,金融机构的ESG投资行为因其深远影响而颇受投资者青睐,但层出不穷的“漂绿”现象也牢牢制约着绿色金融的发展,制约着ESG投资的发展。西方国家作为绿色金融发展先驱,从信息披露、制度监管、实践探索等方面对“漂绿”现象进行了研究和治理。本文在学习其先进经验的基础上,基于舞弊三角理论对DWSGroup案例进行分析,从压力、机会和自我合理化因素角度对金融机构ESG投资“漂绿”行为的动因进行分析,并据此提出我国“反漂绿”体系框架,以期为绿色金融的平稳发展和“双碳”目标的实现作出贡献。

SARS-CoV-2 Pooled Testing Methodology for PCR Testing Applied in Private Laboratory in Armenia

Since the beginning of COVID-19 pandemics many countries were facing challenges with testing capacity recourse limitations. Throughout the waves of the pandemic countries were trying to address the existing constrains exploring solutions to increase the testing capacity with more cost-effective approaches. Pooled methodology was one of the methods which many have validated and used. It is evident that in case of pooled sample testing the sensitivity becomes lower, however the variation highly depends on the pool size as well as the incidence rate at the certain point. Armenia as well as many other countries has adopted regulations for mandatory COVID-19 PCR testing for all the travelers. Current study aimed to explore the efficiency of COVID-19 pooled PCR testing for nasopharyngeal swabs of individuals with no symptoms in a time period with good epidemiological state of the infection. Nasopharingeal swab samples from individuals were collected. The manual extraction of RNAs of samples was performed after pooling up to 5 samples. The pools with Cycle Threshold (CT) of < 37 were considered positive and were retested individually. In total 28,015 samples were grouped in 667 pools of which 57 were positive. The total number of positive samples was 65. The median difference (CT-pool–CT samples) was 2.4 (ranging from–3.0 to 8.9). The correlation of CT of pools and positive samples was positive. The correlation coefficient r = 0.84, P < 0.000, 95% CI range 0.7423 to 0.9243). The total economic saving when using pools compared to the individual testing was 72%. The minor difference between CT values of pools and samples can be explained by the dilution effect in the pool. However, the positive correlation between the values as well as the amount of cost saving demonstrate that pooling on nasopharyngeal samples for COVID-19 PCR testing can be a good method for efficient screening with significant resource saving. One of the most important advantages of the proposed method is the fact that samples are pooled prior extraction, which avoids the possibilities with misinterpretation of IC due to low yield of RNA in the extraction process.

Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

Introducing hydroxyl groups to tailor the d-band center of Ir atom through side anchoring for boosted ORR and HER

Tuning the coordination atoms of central metal is an effective means to improve the electrocatalytic activity of atomic catalysts.Herein,iridium(Ir) is proposed to be asymmetrically anchored by sp-N and pyridinic N of hydrogen-substituted graphdiyne(HsGDY),and coordinated with OH as an Ir atomic catalyst(Ir_(1)-N-HsGDY).The electron structures,especially the d-band center of Ir atom,are optimized by these specific coordination atoms.Thus,the as-synthesized Ir_(1)-N-HsGDY exhibits excellent electrocatalytic performances for oxygen reduction and hydrogen evolution reactions in both acidic and alkaline media.Benefiting from the unique structure of HsGDY,IrN_(2)(OH)_(3) has been developed and demonstrated to act as the active site in these electrochemical reactions.All those indicate the fresh role of the sp-N in graphdiyne in producing a new anchor way and contributing to promote the electrocatalytic activity,showing a new strategy to design novel electrochemical catalysts.

End-group modulation of phenazine based non-fullerene acceptors for efficient organic solar cells with high open-circuit voltage

Phenazine-based non-fullerene acceptors(NFAs)have demonstrated great potential in improving the power conversion efficiency(PCE)of organic solar cells(OSCs).Halogenation is known to be an effective strategy for increasing optical absorption,refining energy levels,and improving molecular packing in organic semiconductors.Herein,a series of NFAs(Pz IC-4H,Pz IC-4F,Pz IC-4Cl,Pz IC-2Br)with phenazine as the central core and with/without halogen-substituted(dicyanomethylidene)-indan-1-one(IC)as the electron-accepting end group were synthesized,and the effect of end group matched phenazine central unit on the photovoltaic performance was systematically studied.Synergetic photophysical and morphological analyses revealed that the PM6:Pz IC-4F blend involves efficient exciton dissociation,higher charge collection and transfer rates,better crystallinity,and optimal phase separation.Therefore,OSCs based on PM6:Pz IC-4F as the active layer exhibited a PCE of 16.48%with an open circuit voltage(Voc)and energy loss of 0.880 V and 0.53 e V,respectively.Accordingly,this work demonstrated a promising approach by designing phenazine-based NFAs for achieving high-performance OSCs.

Recent advances and perspectives in MXene-based cathodes for aqueous zinc-ion batteries

Aqueous zinc-ion batteries(AZIBs)show great potential for applications in grid-scale energy storage,given their intrinsic safety,cost effectiveness,environmental friendliness,and impressive electrochemical performance.However,strong electrostatic interactions exist between zinc ions and host materials,and they hinder the development of advanced cathode materials for efficient,rapid,and stable Zn-ion storage.MXenes and their derivatives possess a large interlayer spacing,excellent hydrophilicity,outstanding electronic conductivity,and high redox activity.These materials are considered“rising star”cathode candidates for AZIBs.This comprehensive review discusses recent advances in MXenes as AZIB cathodes from the perspectives of crystal structure,Zn-storage mechanism,surface modification,interlayer engineering,and conductive network design to elucidate the correlations among their composition,structure,and electrochemical performance.This work also outlines the remaining challenges faced by MXenes for aqueous Zn-ion storage,such as the urgent need for improved toxic preparation methods,exploration of potential novel MXene cathodes,and suppression of layered MXene restacking upon cycling,and introduces the prospects of MXene-based cathode materials for high-performance AZIBs.

Channel Correlation Based User Grouping Algorithm for Nonlinear Precoding Satellite Communication System

Low Earth Orbit(LEO)multibeam satellites will be widely used in the next generation of satellite communication systems,whose inter-beam interference will inevitably limit the performance of the whole system.Nonlinear precoding such as Tomlinson-Harashima precoding(THP)algorithm has been proved to be a promising technology to solve this problem,which has smaller noise amplification effect compared with linear precoding.However,the similarity of different user channels(defined as channel correlation)will degrade the performance of THP algorithm.In this paper,we qualitatively analyze the inter-beam interference in the whole process of LEO satellite over a specific coverage area,and the impact of channel correlation on Signal-to-Noise Ratio(SNR)of receivers when THP is applied.One user grouping algorithm is proposed based on the analysis of channel correlation,which could decrease the number of users with high channel correlation in each precoding group,thus improve the performance of THP.Furthermore,our algorithm is designed under the premise of co-frequency deployment and orthogonal frequency division multiplexing(OFDM),which leads to more users under severe inter-beam interference compared to the existing research on geostationary orbit satellites broadcasting systems.Simulation results show that the proposed user grouping algorithm possesses higher channel capacity and better bit error rate(BER)performance in high SNR conditions relative to existing works.

Responding of zooplankton to environmental factor changes in the Changjiang River estuarine regions in spring-summer from 2016 to 2020

The estuarine areas are under frequent influence from freshwater intrusion and ocean currents,in which zooplankton species are diversified and variable as they are sensitive to physio-chemical variations in water.Therefore,understanding the relationships between zooplankton and environmental factors help us know the water quality.To achieve co-existence with species in similar ecological group or habit,they could inevitably alter themselves to fit the ecology and adjust the function according to the competitive exclusion in ecological theory.However,information of the co-existence of dominant species in the Changjiang(Yangtze)River estuary(CRE)and adjacent waters remains scarce.We explored the relationships between dominant zooplankton and environmental factors in the study region in spring-summer from 2016 to 2020,involving particularly the composition of dominant species,ecological groups,their relationships with environmental factors,and co-existence of important species,using the non-multidimensional scale analysis(nMDS)method and redundancy analysis.Results show that Labidocera euchaeta and Tortanus vermiculus were dominant species in the study scope.The turnover rate of dominant zooplankton was greater(>50%)in spring while the species number was higher in summer.The dominant species were estuarine,offshore,and eurytopic based on the adaptation to salinity.In spring,the ecological groups were dominated by estuarine species,while in summer by estuarine and offshore species.In addition,the nMDS showed that the dominant species in the same ecological group were more dispersed and not prominently clustered;the dominant species were staggered among different ecological groups.The temperature,salinity,pH,dissolved oxygen,and chlorophyll a were the main environmental factors on the distribution of the dominant species in spring,while in summer were dissolved oxygen,temperature,salinity,and pH.The domination of medusae of Nemopsis bachei and Pleurobrachia globosa in zooplankton community in spring,and the continuous decrease in abundance of L.euchaeta reflected the effects of local climate change.The temperature and salinity changes in different years and the subsequent response of zooplankton reflected the influence of freshwater intrusion and/or ocean currents.Zooplankton in similar ecological habits exhibited the competitive exclusion in terms of co-existence.

MiR-142-3p Regulates ILC1s by Targeting HMGB1 via the NF-κB Pathway in a Mouse Model of Early Pregnancy Loss

Objective Innate lymphoid cells(ILCs)are a class of newly discovered immunocytes.Group 1 ILCs(ILC1s)are identified in the decidua of humans and mice.High mobility group box 1(HMGB1)is predicted to be one of the target genes of miR-142-3p,which is closely related to pregnancy-related diseases.Furthermore,miR-142-3p and HMGB1 are involved in regulating the NF-κB signaling pathway.This study aimed to examine the regulatory effect of miR-142-3p on ILC1s and the underlying mechanism involving HMGB1 and the NF-κB signaling pathway.Methods Mouse models of normal pregnancy and abortion were constructed,and the alterations of ILC1s,miR-142-3p,ILC1 transcription factor(T-bet),and pro-inflammatory cytokines of ILC1s(TNF-α,IFN-γand IL-2)were detected in mice from different groups.The targeting regulation of HMGB1 by miR-142-3p in ILC1s,and the expression of HMGB1 in normal pregnant mice and abortive mice were investigated.In addition,the regulatory effects of miR-142-3p and HMGB1 on ILC1s were detected in vitro by CCK-8,Annexin-V/PI,ELISA,and RT-PCR,respectively.Furthermore,changes of the NF-κB signaling pathway in ILC1s were examined in the different groups.For the in vivo studies,miR-142-3p-Agomir was injected in the uterus of abortive mice to evaluate the abortion rate and alterations of ILC1s at the maternal-fetal interface,and further detect the expression of HMGB1,pro-inflammatory cytokines,and the NF-κB signaling pathway.Results The number of ILC1s was significantly increased,the level of HMGB1 was significantly upregulated,and that of miR-142-3p was considerably downregulated in the abortive mice as compared with the normal pregnant mice(all P<0.05).In addition,miR-142-3p was found to drastically inhibit the activation of the NF-κB signaling pathway(P<0.05).The number of ILC1s and the levels of pro-inflammatory cytokines were significantly downregulated and the activation of the NF-κB signaling pathway was inhibited in the miR-142-3p Agomir group(all P<0.05).Conclusion miR-142-3p can regulate ILC1s by targeting HMGB1 via the NF-κB signaling pathway,and attenuate the inflammation at the maternal-fetal interface in abortive mice.

Step‑by‑Step Modulation of Crystalline Features and Exciton Kinetics for 19.2%Efficiency Ortho‑Xylene Processed Organic Solar Cells

With plenty of popular and effective ternary organic solar cells(OSCs)construction strategies proposed and applied,its power conversion efficiencies(PCEs)have come to a new level of over 19%in single-junction devices.However,previous studies are heavily based in chloroform(CF)leaving behind substantial knowledge deficiencies in understanding the influence of solvent choice when introducing a third component.Herein,we present a case where a newly designed asymmetric small molecular acceptor using fluoro-methoxylated end-group modification strategy,named BTP-BO-3FO with enlarged bandgap,brings different morphological evolution and performance improvement effect on host system PM6:BTP-eC9,processed by CF and ortho-xylene(o-XY).With detailed analyses supported by a series of experiments,the best PCE of 19.24%for green solvent-processed OSCs is found to be a fruit of finely tuned crystalline ordering and general aggregation motif,which furthermore nourishes a favorable charge generation and recombination behavior.Likewise,over 19%PCE can be achieved by replacing spin-coating with blade coating for active layer deposition.This work focuses on understanding the commonly met yet frequently ignored issues when building ternary blends to demonstrate cutting-edge device performance,hence,will be instructive to other ternary OSC works in the future.

Regulating interfacial behavior of zinc metal anode via metal-organic framework functionalized separator

Aqueous zinc ion batteries(AZIBs)are one of the promising energy storage devices.However,uncontrolled dendrite and side reactions have seriously hindered its further application.In this study,the metal-organic framework(MOF)functionalized glass fiber separator(GF-PFC-31)was used to regulate interfacial behavior of zinc metal anode,enabling the development of high-performance AZIBs.In PFC-31,there areπ-πinteractions between two adjacent benzene rings with a spacing of 3.199 A.This spacing can block the passage of[Zn(H_(2)O)_6]^(2+)(8.6 A in diameter)through the GF-PFC-31 separator to a certain extent,which promotes the deposition process of Zn ions.In addition,the sulfonic acid group(-S03H)contained in GF-PFC-31 can form a hydrogen bonding network with H_(2)O,which can provide a desolvation effect and reduce the side reaction.Consequently,GF-PFC-31 separator achieves uniform deposition of Zn ions.The Zn‖GF-PFC-31‖Zn symmetric cell exhibits stable cycle life(3000 h at 1.2 mA cm^(-2),2000 h at 0.3 mA cm^(-2),and 2000 h at 5.0 mA cm^(-2)),and Zn‖GF-PFC-31‖MnO_(2) full cell with GF-PFC-31 separator can cycle for 1000 cycles at 1.2 A g^(-1)with capacity retention rate of 82.5%.This work provides a promising method to achieve high-performance AZIBs.

Fe-N-C core-shell catalysts with single low-spin Fe(Ⅱ)-N_(4)species for oxygen reduction reaction and high-performance proton exchange membrane fuel cells

Fe-N-doped carbon materials(Fe-N-C)are promising candidates for oxygen reduction reaction(ORR)relative to Pt-based catalysts in proton exchange membrane fuel cells(PEMFCs).However,the intrinsic contributions of Fe-N_(4)moiety with different chemical/spin states(e.g.D1,D2,D3)to ORR are unclear since various states coexist inevitably.In the present work,Fe-N-C core-shell nanocatalyst with single lowspin Fe(Ⅱ)-N_(4)species(D1)is synthesized and identified with ex-situ ultralow temperature Mossbauer spectroscopy(T=1.6 K)that could essentially differentiate various Fe-N_(4)states and invisible Fe-O species.By quantifying with CO-pulse chemisorption,site density and turnover frequency of Fe-N-C catalysts reach 2.4×10^(-9)site g^(-1)and 23 e site~(-1)s^(-1)during the ORR,respectively.Half-wave potential(0.915V_(RHE))of the Fe-N-C catalyst is more positive(approximately 54 mV)than that of Pt/C.Moreover,we observe that the performance of PEMFCs on Fe-N-C almost achieves the 2025 target of the US Department of Energy by demonstrating a current density of 1.037 A cm^(-2)combined with the peak power density of 0,685 W cm^(-2),suggesting the critical role of Fe(Ⅱ)-N_(4)site(D1).After 500 h of running,PEMFCs still deliver a power density of 1.26 W cm^(-2)at 1.0 bar H_(2)-O_(2),An unexpected rate-determining step is figured out by isotopic labelling experiment and theoretical calculation.This work not only offers valuable insights regarding the intrinsic contribution of Fe-N_(4)with a single spin state to alkaline/acidic ORR,but also provides great opportunities for developing high-performance stable PEMFCs.