Red cell distribution width-to-albumin ratio is a simple promising prognostic marker in acute cholangitis requiring biliary drainage

Background: It is crucial to assess the severity of acute cholangitis(AC). There are currently several prognostic markers. However, the accuracies of these markers are not satisfied. The present study aimed to investigate the predictive value of the red cell distribution width(RDW)-to-albumin ratio(RAR) for the prognosis of AC. Methods: We retrospectively evaluated consecutive patients diagnosed with AC between May 2019 and March 2022. RAR was calculated, and its predictive ability for in-hospital mortality, intensive care unit(ICU) admission, bacteremia, and the length of hospitalization were analyzed. Results: Out of 438 patients, 34(7.8%) died. Multivariate analysis showed that malignant etiology [odds ratio(OR) = 4.816, 95% confidence interval(CI): 1.936-11.980], creatinine(OR = 1.649, 95% CI: 1.095-2.484), and RAR(OR = 2.064, 95% CI: 1.494-2.851) were independent risk factors for mortality. When adjusted for relevant covariates, including age, sex, malignant etiology, Tokyo severity grading(TSG), Charlson comorbidity index, and creatinine, RAR significantly predicted mortality(adjusted OR = 1.833, 95% CI: 1.280-2.624). When the cut-off of RAR was set to 3.8, its sensitivity and specificity for mortality were 94.1% and 56.7%, respectively. Patients with an RAR of > 3.8 had a 20.9-fold(OR = 20.9, 95% CI: 4.9-88.6) greater risk of mortality than the remaining patients. The area under the curve value of RAR for mortality was 0.835(95% CI: 0.770-0.901), which was significantly higher than that of TSG and the other prognostic markers, such as C-reactive protein-to-albumin ratio, and procalcitonin-to-albumin ratio. Lastly, RAR was not inferior to TSG in predicting ICU admission, bacteremia, and the length of hospitalization. Conclusions: RAR successfully predicted the in-hospital mortality, ICU admission, bacteremia, and the length of hospitalization of patients with AC, especially in-hospital mortality. RAR is a promising marker that is more convenient than TSG and other prognostic markers for predicting the prognosis of patients with AC.

Modeling load distribution for rural photovoltaic grid areas using image recognition

Expanding photovoltaic(PV)resources in rural-grid areas is an essential means to augment the share of solar energy in the energy landscape,aligning with the“carbon peaking and carbon neutrality”objectives.However,rural power grids often lack digitalization;thus,the load distribution within these areas is not fully known.This hinders the calculation of the available PV capacity and deduction of node voltages.This study proposes a load-distribution modeling approach based on remote-sensing image recognition in pursuit of a scientific framework for developing distributed PV resources in rural grid areas.First,houses in remote-sensing images are accurately recognized using deep-learning techniques based on the YOLOv5 model.The distribution of the houses is then used to estimate the load distribution in the grid area.Next,equally spaced and clustered distribution models are used to adaptively determine the location of the nodes and load power in the distribution lines.Finally,by calculating the connectivity matrix of the nodes,a minimum spanning tree is extracted,the topology of the network is constructed,and the node parameters of the load-distribution model are calculated.The proposed scheme is implemented in a software package and its efficacy is demonstrated by analyzing typical remote-sensing images of rural grid areas.The results underscore the ability of the proposed approach to effectively discern the distribution-line structure and compute the node parameters,thereby offering vital support for determining PV access capability.

Fish Assemblage and Abundance Distribution in Nanji Islands Marine Nature Reserve in Relation to Season Change

The fishing survey station located in the warm waters of the East China Sea is one of the abundant fishery resources of waters;with a large number of economic fish breeding grounds and economic juvenile feeding grounds. Several fish species according to this bottom trawl survey results which appear in the annual survey from winter to autumn give us a total of 58 species, which have appeared throughout the year. But the vast majority of species appears only in certain seasons, according to the sea fish survey and based on seasonal migratory species or species mainly small endemic species. The survey of fish is tropical and subtropical warm water species and warm temperate species, and the history of the area has several types of 397 different species. There are many reasons, in addition to recent years, human disturbance and adverse consequences of environmental changes brought about, but also with the relevant sampling methods and sampler time, the survey sampled only trawl based, from Ping yang Ocean and Fisheries Bureau, the waters are still other jobs method net, gill nets, fishing industry, etc. Survey results show that the type of fish in the summer (58 species) > spring (55 species) > winter (51 species) > autumn (42 species). The type of season was among spring to summer rose, summer to autumn decline. The survey found that in the reef area of the Nanji Islands, no one species of fish is the dominant species throughout the year (according to the dominant species, each species is dominant only in one season). From the dominant species turnover accounting for the four seasons, in winter it has 53.72% of the total biomass or annual biomass, spring it has 41.53% of the overall biomass, summer it has 31.85% and autumn it has 38.56% of total biomass. Visible, seasonal succession of dominant species of fish phenomenon is very obvious, especially in the spring and winter, summer transfers dominate species at this stage show the greatest change, but winter, the transfer of this dominant species changes in minimal. Seasonal changes from biomass and the average annual marine fish survey biomass were 4832.25 g/h. From different seasons, the average biomass in winter (10779.88 g/h) > of the average biomass in spring (3624.1 g/hour) > of the mean biomass in autumn (3158 g/h) > the average Biomass in summer (1767 g/h). All of them show significant seasonal variation of the biomass, in winter and spring, the biomass is generally not high, but significantly higher than in the summer and autumn seasons. Each season, around the coast of southern Zhejiang, is less than the biomass and other catches off, which involves investigating sea location, size range, and the survey ship different network related tools. Another change from the area of biomass, some studies found that the survey of four-season fish of waters above the biological capacity of several kilograms only in some stations, namely stations and the highest biomass in summer appeared in stations 3, 7 and 11. In autumn the highest biomass appeared in stations 3, 6, 20 and 23.

Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

Distributed photovoltaic(PV)is one of the important power sources for building a new power system with new energy as the main body.The rapid development of distributed PV has brought new challenges to the operation of distribution networks.In order to improve the absorption ability of large-scale distributed PV access to the distribution network,the AC/DC hybrid distribution network is constructed based on flexible interconnection technology,and a coordinated scheduling strategy model of hydrogen energy storage(HS)and distributed PV is established.Firstly,the mathematical model of distributed PV and HS system is established,and a comprehensive energy storage system combining seasonal hydrogen energy storage(SHS)and battery(BT)is proposed.Then,a flexible interconnected distribution network scheduling optimization model is established to minimize the total active power loss,voltage deviation and system operating cost.Finally,simulation analysis is carried out on the improved IEEE33 node,the NSGA-II algorithm is used to solve specific examples,and the optimal scheduling results of the comprehensive economy and power quality of the distribution network are obtained.Compared with the method that does not consider HS and flexible interconnection technology,the network loss and voltage deviation of this method are lower,and the total system cost can be reduced by 3.55%,which verifies the effectiveness of the proposed method.

Probability Distribution of China Aviation Network Average Degree of Edge Vertices and Its Evolutionary Trace Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network, the probability distribution and evolution trace of average degree of edge vertices of China aviation network were studied based on the statistics data of China civil aviation network in 1988, 1994, 2001, 2008 and 2015. According to the theory and method of complex network, the network system was constructed with the city where the airport was located as the network node and the route between cities as the edge of the network. Based on the statistical data, the average degrees of edge vertices in China aviation network in 1988, 1994, 2001, 2008 and 2015 were calculated. Using the probability statistical analysis method and regression analysis approach, it was found that the average degree of edge vertices had the probability distribution of normal function and the position parameters and scale parameters of the probability distribution had linear evolution trace.

High Resolution ID-TIMS Redefines the Distribution and Age of the Main Mesozoic Lacustrine Hydrocarbon Source Rocks in the Ordos Basin,China

Using high-precision zircon U-Pb ID-TIMS geochronology,tuffs from the Chang 9 shale and the Chang 7 shale were dated.The tuff in the Chang 9 shale is 241.47±0.17 Ma,which falls between the top tuff age of 241.06±0.12 Ma and the bottom tuff age of 241.558±0.093 Ma in the Chang 7 shale.These reveal that the Chang 9 and Chang 7 shales are contemporaneous,belonging to the Ladinian stage of the Middle Triassic.This insight expands the region of the main source rock of Chang 7 to the northeast and will inform the search for the deep Chang 9 shale petroleum system,increasing the scope for exploring the Chang 7 shale system in northern Shaanxi.The research results clarify the relationship between the two sets of shale in the Yanchang Formation and redefine the distribution range of the Chang 7 shale in the Ordos Basin.At the same time,it shows that there is a cross-layer problem in the stratigraphic division of the Yanchang Formation in different regions,the high-precision U-Pb dating technology providing a reference for the fine stratigraphic correlation of other continental basins in the world.

Rice Storage Proteins:Focus on Composition,Distribution,Genetic Improvement and Effects on Rice Quality

Rice storage proteins(RSPs)are plant proteins with high nutritional quality.As the second largest type of storage substance in rice,it is the main source of protein intake for people who consume rice as a staple food.The content and type of RSPs affect the appearance,processing quality and eating quality of rice.These effects involve the distribution of RSPs in rice grains as well as the interactions of RSPs with other components such as starch in rice grains.In the past two decades,some progress has been made in the genetic improvement of RSPs.However,the determination mechanism of protein content and composition in rice is still unclear,and the mechanism of the effect of RSPs on rice quality has not been elucidated.In this review,the composition,biosynthesis and distribution of RSPs,and quantitative trait loci mapping and cloning of RSP genes are summarized,the research progress of the influence of RSPs and their components on rice quality are reviewed,and the research directions in the future are proposed.

Coordinated planning for flexible interconnection and energy storage system in low-voltage distribution networks to improve the accommodation capacity of photovoltaic

The increasing proportion of distributed photovoltaics(DPVs)and electric vehicle charging stations in low-voltage distribution networks(LVDNs)has resulted in challenges such as distribution transformer overloads and voltage violations.To address these problems,we propose a coordinated planning method for flexible interconnections and energy storage systems(ESSs)to improve the accommodation capacity of DPVs.First,the power-transfer characteristics of flexible interconnection and ESSs are analyzed.The equipment costs of the voltage source converters(VSCs)and ESSs are also analyzed comprehensively,considering the differences in installation and maintenance costs for different installation locations.Second,a bilevel programming model is established to minimize the annual comprehensive cost and yearly total PV curtailment capacity.Within this framework,the upper-level model optimizes the installation locations and capacities of the VSCs and ESSs,whereas the lower-level model optimizes the operating power of the VSCs and ESSs.The proposed model is solved using a non-dominated sorting genetic algorithm with an elite strategy(NSGA-II).The effectiveness of the proposed planning method is validated through an actual LVDN scenario,which demonstrates its advantages in enhancing PV accommodation capacity.In addition,the economic benefits of various planning schemes with different flexible interconnection topologies and different PV grid-connected forms are quantitatively analyzed,demonstrating the adaptability of the proposed coordinated planning method.

Sub-stand diameter distribution types vary along an old-growth Douglas-fir chronosequence into the horizontal diversification development stage

Managing mature Douglas-fir[Pseudotsuga menziesii(Mirb.)Franco]stands to emulate the structural complexity of natural old-growth forest requires identifying structural targets at the sub-stand level at which neighborhood dynamics and patchy disturbance shape structure.We therefore sought to describe the archetypal shapes of predominant sub-stand diameter distribution types(DDTs)observed in natural tree neighborhoods in stands comprising a chronosequence(ca.120-450+yrs)encompassing mature,vertical diversification,and horizontal diversification development stages.The ten 1.0 ha stands are located in the southcentral Oregon Cascades,USA.Building on the known spatial position of each tree,natural tree neighborhoods were identified using the floating neighborhood approach based on spatial tessellation connecting neighboring trees at the first-(mean 61 m2)through fifth-(mean 2058 m2)order scales.Cluster analysis was then used to objectively identify the most predominant DDTs among the relative tree size distributions observed in the trans-scale neighborhoods within each stand.Repeated measures regression was used to classify each DDT to one of six observed archetypal shapes:negative exponential,unimodal,rotated sigmoid,bimodal,concave,or multi-modal.Only three of the 81 observed DDTs deviated by<10%from the stand average,while every stand had at least one DDT that deviated by>50%(maximum 83%).Within each stand,five to ten predominant DDTs were observed,which deviated from the stand average by 30-48%and were characterized by two to five different archetypal shapes.Consequently,in some stands the majority of tree neighborhoods were best characterized by a different shape from that assigned at the stand level.Deviation from the stand average increased from the youngest stand in the mature development stage through the middle stands in the vertical diversification stage to the oldest stands in the horizontal diversification stage.The complexity of DDT shapes tended to increase along the chronosequence(from negative exponential and uniform toward concave and multi-modal),with shape richness highest mid-sequence and evenness peaking in the oldest stands.The high diversity of sub-stand structural complexity reduces the utility of standlevel diameter distributions as old-growth restoration targets.However,the presence in early-sequence stands of sub-stand diameter distributions common to later-sequence stands may facilitate active management at the neighborhood level to promote future old-growth condition.Restoration of substand diameter structures would likely require combining spatial perspectives,such as by augmenting tree-level croptree management with diameter distribution targets for the resulting tree neighborhoods.

Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

Age-specific differences in the association between prediabetes and cardiovascular diseases in China:A national cross-sectional study

BACKGROUND Cardiovascular disease(CVD)is a leading cause of morbidity and mortality worldwide,the global burden of which is rising.It is still unclear the extent to which prediabetes contributes to the risk of CVD in various age brackets among adults.To develop a focused screening plan and treatment for Chinese adults with prediabetes,it is crucial to identify variations in the connection between prediabetes and the risk of CVD based on age.AIM To examine the clinical features of prediabetes and identify risk factors for CVD in different age groups in China.METHODS The cross-sectional study involved a total of 46239 participants from June 2007 through May 2008.A thorough evaluation was conducted.Individuals with prediabetes were categorized into two groups based on age.Chinese atherosclerotic CVD risk prediction model was employed to evaluate the risk of developing CVD over 10 years.Random forest was established in both age groups.SHapley Additive exPlanation method prioritized the importance of features from the perspective of assessment contribution.RESULTS In total,6948 people were diagnosed with prediabetes in this study.In prediabetes,prevalences of CVD were 5(0.29%)in the younger group and 148(2.85%)in the older group.Overall,11.11%of the younger group and 29.59% of the older group were intermediate/high-risk of CVD for prediabetes without CVD based on the Prediction for ASCVD Risk in China equation in ten years.In the younger age group,the 10-year risk of CVD was found to be more closely linked to family history of CVD rather than lifestyle,whereas in the older age group,resident status was more closely linked.CONCLUSION The susceptibility to CVD is age-specific in newly diagnosed prediabetes.It is necessary to develop targeted approaches for the prevention and management of CVD in adults across various age brackets.

Spatial and Temporal Variations in the Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in China

The aging timescale of particles is a key parameter in determining their impacts on air quality,human health,and climate.In this study,a one-year simulation of the age distributions of the primary and secondary inorganic fine particulate matter(PM_(2.5))components was conducted over China using an age-resolved Community Multiscale Air Quality(CMAQ)model.The results indicate that primary PM_(2.5)(PPM)and ammonium mainly originate from fresh local emissions,with approximately 60%-80%concentrated in 0-24 h age bins in most of China throughout the year.The average age is about15-25 h in most regions in summer,but increases to 40-50 h in southern region of China and the Sichuan Basin(SCB)in winter.Sulfate is more aged than PPM,indicating an enhanced contribution from regional transport.Aged sulfate with atmospheric age>48 h account for 30%-50%of total sulfate in most regions and seasons,and the concentrations in the>96 h age bin can reach up to 15μg·m-3 in SCB during winter.Dramatic seasonal variations occur in the Yangtze River Delta,Pearl River Delta,and SCB,with highest average age of 60-70 h in winter and lowest of 40-45 h in summer.The average age of nitrate is 20-30 h in summer and increases to 40-50 h in winter.The enhanced deposition rate of nitric acid vapor combined with the faster chemical reaction rate of nitrogen oxides leads to a lower atmospheric age in summer.Additionally,on pollution days,the contributions of old age bins(>24 h)increase notably for both PPM and secondary inorganic aerosols in most cities and seasons,suggesting that regional transport plays a vital role during haze events.The age information of PM_(2.5),provided by the age-resolved CMAQ model,can help policymakers design effective emergent emission control measures to eliminate severe haze episodes.

Climate change impacts the distribution of Quercus section Cyclobalanopsis(Fagaceae),a keystone lineage in East Asian evergreen broadleaved forests

East Asian evergreen broadleaved forests(EBFLs) harbor high species richness,but these ecosystems are severely impacted by global climate change and deforestation.Conserving and managing EBLFs requires understanding dominant tree distribution dynamics.In this study,we used 29 species in Quercus section Cyclobalanopsis-a keystone lineage in East Asian EBLFs-as proxies to predict EBLF distribution dynamics using species distribution models(SDMs).We examined climatic niche overlap,similarity,and equivalency among seven biogeographical regions’ species using’ecospat’.We also estimated the effectiveness of protected areas in the predicted range to elucidate priority conservation regions.Our results showed that the climatic niches of most geographical groups differ.The western species under the Indian summer monsoon regime were mainly impacted by temperature factors,whereas precipitation impacted the eastern species under the East Asian summer monsoon regime.Our simulation predicted a northward range expansion of section Cyclobalanopsis between 2081 and 2100,except for the ranges of the three Himalayan species analyzed,which might shrink significantly.The greatest shift of highly suitable areas was predicted for the species in the South Pacific,with a centroid shift of over 300 km.Remarkably,only 7.56% of suitable habitat is currently inside protected areas,and the percentage is predicted to continue declining in the future.To better conserve Asian EBLFs,establishing nature reserves in their northern distribution ranges,and transplanting the populations with predicted decreasing numbers and degraded habitats to their future highly suitable areas,should be high-priority objectives.

Hound:a parallel image distribution system for cluster based on Docker

Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on container startup(e.g.,distributed deep learning application),the image“warm-up”technique which prefetches images of these replicas to destination nodes in the cluster is proposed.However,the current image“warm-up”technique solely focuses on identical image distribution,which fails to take effect when distributing different images to destination nodes.To address this problem,this paper proposes Hound,a simple but efficient cluster image distribution system based on Docker.To support diverse image distribution requests of cluster nodes,Hound additionally adopts node-level parallelism(i.e.,downloading images to destination nodes in parallel)to further improve the efficiency of image distribution.The experimental results demonstrate Hound outperforms Docker,kubernetes container runtime interface(CRI-O),and Docker-compose in terms of image distribution performance when cluster nodes request different images.Moreover,the high scalability of Hound is evaluated in the scenario of ten nodes.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Predicting Ecological Distribution of the Toxic Dinoflagellate Alexandrium minutum in China Sea Using Ecological Niche Modeling

Alexandrium minutum from the China Sea produces a range of toxins and causes damage to the local ecosystems and aquaculture.This is essential to understand environmental factors affecting potential distribution.Potential distributions of A.minutum in the China Sea were predicted based on maximum entropy modeling,and dominant environmental variables were studied through analyses of variable contributions and response curves.The results showed that highly suitable areas were mainly located in the southwest of the Yellow Sea,the Laizhou Bay,and north of Haizhou Bay.The coast of the South China Sea was predicted as a low-suitability area,and the coast of the East China Sea as an unsuitable area.Mean temperature of the coldest month(T_min)had the largest drop in permutation importance but a low percent contribution.The probability of presence of A.minutum increased with increasing concentration of nitrate(NO3−)and annual mean temperature(T_ann)over a wide range of them.The response curves decreased with increasing concentration of phosphate(PO43−)and ratio of NO_(3)^(−)to PO_(4)^(3−)(N_P_ratio)when PO_(4)^(3)−is above 0.049μmolL^(-1) and N_P_ratio above 4,indicating that low values of PO_(4)^(3−) concentration and N_P_ratio favour the occurrence of A.minutum.As a predictor,the variance of annual temperature(T_Var)had the highest percent contribution and gains.PO_(4)^(3−) was predicted to have much more information than the other variables,and exhibited the second largest drop in permutation importance and percent contribution.The T_Var and PO_(4)^(3−) are the most important dominant predictor variables.

Extraction method of nanoparticles concentration distribution from magnetic particle image and its application in thermal damage of magnetic hyperthermia

Magnetic particle imaging(MPI)technology can generate a real-time magnetic nanoparticle(MNP)distribution image for biological tissues,and its use can overcome the limitations imposed in magnetic hyperthermia treatments by the unpredictable MNP distribution after the intratumoral injection of nanofluid.However,the MNP concentration distribution is generally difficult to be extracted from MPI images.This study proposes an approach to extract the corresponding concentration value of each pixel from an MPI image by a least squares method(LSM),which is then translated as MNP concentration distribution by an interpolation function.The resulting MPI-based concentration distribution is used to evaluate the treatment effect and the results are compared with the ones of two baseline cases under the same dose:uniform distribution and MPI-based distribution considering diffusion.Additionally,the treatment effect for all these cases is affected by the blood perfusion rate,which is also investigated deeply in this study.The results demonstrate that the proposed method can be used to effectively reconstruct the concentration distribution from MPI images,and that the weighted LSM considering a quartic polynomial for interpolation provides the best results with respect to other cases considered.Furthermore,the results show that the uniformity of MNP distribution has a positive correlation with both therapeutic temperature distribution and thermal damage degree for the same dose and a critical power dissipation value in the MNPs.The MNPs uniformity inside biological tissue can be improved by the diffusion behavior after the nanofluid injection,which can ultimately reflect as an improvement of treatment effect.In addition,the blood perfusion rate considering local temperature can have a positive effect on the treatment compared to the case which considers a constant value during magnetic hyperthermia.

The initial stages of Li_(2)O_(2) formation during oxygen reduction reaction in Li-O_(2) batteries:The significance of Li_(2)O_(2) in charge-transfer reactions within devices

Lithium-oxygen batteries are a promising technology because they can greatly surpass the energy density of lithium-ion batteries.However,this theoretical characteristic has not yet been converted into a real device with high cyclability.Problems with air contamination,metallic lithium reactivity,and complex discharge and charge reactions are the main issues for this technology.A fast and reversible oxygen reduction reaction(ORR)is crucial for good performance of secondary batteries',but the partial knowledge of its mechanisms,especially when devices are concerned,hinders further development.From this perspective,the present work uses operando Raman experiments and electrochemical impedance spectroscopy(EIS)to assess the first stages of the discharge processes in porous carbon electrodes,following their changes cycle by cycle at initial operation.A growth kinetic formation of the discharge product signal(Li_(2)O_(2))was observed with operando Raman,indicating a first-order reaction and enabling an analysis by a microkinetic model.The solution mechanism in the evaluated system was ascribed for an equivalent circuit with three time constants.While the time constant for the anode interface reveals to remain relatively constant after the first discharge,its surface seemed to be more non-uniform.The model indicated that the reaction occurs at the Li_(2)O_(2) surface,decreasing the associated resistance during the initial discharge phase.Furthermore,the growth of Li_(2)O_(2) forms a hetero-phase between Li_(2)O_(2)/electrolyte,while creating a more compact and homogeneous on the Li_(2)O_(2)/cathode surface.The methodology here described thus offers a way of directly probing changes in surface chemistry evolution during cycling from a device through EIS analysis.

Monitoring the little fire ant,Wasmannia auropunctata(Roger 1863),in the early stage of its invasion in China:Predicting its geographical distribution pattern under climate change

Invasive alien ants(IAAs)are among the most aggressive,competitive,and widespread invasive alien species(IAS)worldwide.Wasmannia auropunctata,the greatest IAAs threat in the Pacific region and listed in“100 of the world’s worst IAS”,has established itself in many countries and on islands worldwide.Wild populations of W.auropunctata were recently reported in southeastern China,representing a tremendous potential threat to China’s agricultural,economic,environmental,public health,and social well-being.Estimating the potential geographical distribution(PGD)of W.auropunctata in China can illustrate areas that may potentially face invasion risk.Therefore,based on the global distribution records of W.auropunctata and bioclimatic variables,we predicted the geographical distribution pattern of W.auropunctata in China under the effects of climate change using an ensemble model(EM).Our findings showed that artificial neural network(ANN),flexible discriminant analysis(FDA),gradient boosting model(GBM),Random Forest(RF)were more accurate than categorical regression tree analysis(CTA),generalized linear model(GLM),maximum entropy model(MaxEnt)and surface distance envelope(SRE).The mean TSS values of ANN,FDA,GBM,and RF were 0.820,0.810,0.843,and 0.857,respectively,and the mean AUC values were 0.946,0.954,0.968,and 0.979,respectively.The mean TSS and AUC values of EM were 0.882 and 0.972,respectively,indicating that the prediction results with EM were more reliable than those with the single model.The PGD of W.auropunctata in China is mainly located in southern China under current and future climate change.Under climate change,the PGD of W.auropunctata in China will expand to higher-latitude areas.The annual temperature range(bio7)and mean temperature of the warmest quarter(bio10)were the most significant variables affecting the PGD of W.auropunctata in China.The PGD of W.auropunctata in China was mainly attributed to temperature variables,such as the annual temperature range(bio7)and the mean temperature of the warmest quarter(bio10).The populations of W.auropunctata in southern China have broad potential invasion areas.Developing strategies for the early warning,monitoring,prevention,and control of W.auropunctata in southern China requires more attention.

Integrative biogeography: Validating hypotheses of species distribution

DEAR EDITOR,Biogeography is a scientific field dedicated to the investigation of the origins and distribution patterns of organisms,as well as predicting future alterations in their geographical distributions(Cox&Moore,2005).However,the majority of conclusions drawn within the field of biogeography are hypothetical.Rigorous testing of these biogeographic hypotheses remains a considerable challenge.This paper presents the concept of“integrative biogeography”,which emphasizes the experimental testing of biogeographic hypotheses through studies on geological history,as well as biotic and abiotic factors(Figure 1).