Improvement of Radar Quantitative Precipitation Estimation Based on Real-Time Adjustments to Z-R Relationships and Inverse Distance Weighting Correction Schemes

The errors in radar quantitative precipitation estimations consist not only of systematic biases caused by random noises but also spatially nonuniform biases in radar rainfall at individual rain-gauge stations. In this study, a real-time adjustment to the radar reflectivity rainfall rates （Z R） relationship scheme and the gauge-corrected, radar-based, estimation scheme with inverse distance weighting interpolation was devel- oped. Based on the characteristics of the two schemes, the two-step correction technique of radar quantitative precipitation estimation is proposed. To minimize the errors between radar quantitative precipitation es- timations and rain gauge observations, a real-time adjustment to the Z R relationship scheme is used to remove systematic bias on the time-domain. The gauge-corrected, radar-based, estimation scheme is then used to eliminate non-uniform errors in space. Based on radar data and rain gauge observations near the Huaihe River, the two-step correction technique was evaluated using two heavy-precipitation events. The results show that the proposed scheme improved not only in the underestimation of rainfall but also reduced the root-mean-square error and the mean relative error of radar-rain gauge pairs.

Understanding the Variability of Z-R Relationships Caused by Natural Variations in Raindrop Size Distributions(DSD):Implication of Drop Size and Number

In the issue of rainfall estimation by radar through the necessary relationship between radar reflectivity Z and rain rate R (Z-R), the main limitation is attributed to the variability of this relationship. Indeed, several pre-vious studies have shown the great variability of this relationship in space and time, from a rainfall event to another and even within a single rainfall event. Recent studies have shown that the variability of raindrop size distributions and thereby Z-R relationships is therefore, more the result of complex dynamic, thermody-namic and microphysical processes within rainfall systems than a convective/stratiform classification of the ground rainfall signature. The raindrop number and size at ground being the resultant of various processes mentioned above, a suitable approach would be to analyze their variability in relation to that of Z-R relation-ship. In this study, we investigated the total raindrop concentration number NT and the median volume di-ameter D0 used in numerous studies, and have shown that the combination of these two ‘observed’ parame-ters appears to be an interesting approach to better understand the variability of the Z-R relationships in the rainfall events, without assuming a certain analytical raindrop size distribution model (exponential, gamma, or log-normal). The present study is based on the analysis of disdrometer data collected at different seasons and places in Africa, and aims to show the degree of the raindrop size and number implication in regard to the Z-R relationships variability.

What diameter?What height?Influence of measures of average tree size on area-based allometric volume relationships

Volume is an important attribute used in many forest management decisions.Data from 83 fixed-area plots located in central New Brunswick,Canada,are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer's(1967)volume equation.When density was included in the models(Volume=f(Diameter,Height,Density))choice of diameter measure was more important than choice of height measure.When density was not included(Volume=f(Diameter,Height)),the opposite was true.For models with density included,moment-based estimators of stand diameter and height performed better than all other measures.For models without density,largest tree estimators of stand diameter and height performed better than other measures.The overall best equation used quadratic mean diameter,Lorey's height,and density(root mean square error=5.26 m^3·ha^(-1);1.9%relative error).The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha(root mean square error=32.08 m^(3)·ha^(-1);11.8%relative error).The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.

Three anti-inflammatory polysaccharides from Lonicera japonica Thunb.:insights into the structure-function relationships

This study demonstrates the feasibility of producing three polysaccharides(neutral LJP-1,acidic LJP-2 and acidic LJP-3)with significant in vitro and in vivo anti-inflammatory activities from the flowers of Lonicera japonica.The three polysaccharides differed in chemical composition,molecular weight(Mw)distribution,glycosidic linkage pattern,functional groups and morphology.They exhibited excellent protective effects(in a dose-dependent manner)in lipopolysaccharide-injured RAW264.7 macrophages and Cu SO4-damaged zebrafish via reducing NO production and inhibiting the overexpressions of inflammation-related transcription factors,inflammatory proteins and cytokines in the NF-κB/MAPK signaling pathways.Their antiinflammatory effects varied owing to their different molecular characteristics and chemical compositions.Overall,LJP-2 at 400μg/m L was the most effective.LJP-2 consisted mainly of→5)-α-L-Araf(1→,→4)-α-LGalp A(1→and→2)-α-L-Rhap(1→residues with terminal T-β-D-Glcp.Thus,honeysuckle flowers are good sources of anti-inflammatory polysaccharides,and precise fractionation enables the production of potent antiinflammatory agents for the development of functional foods and healthcare products.

Floristic composition and edaphic relationships in ferruginous campo rupestre reference ecosystems

Land use change and occupation have led to modifications in the environment causing loss of biodiversity and ecosystem services throughout the planet.Some environments with high economic relevance,such as the ferruginous campo rupestre(rupestrian grassland known as Canga in Brazil),are even more susceptible to severe impacts due to their extreme habitat conditions and low resilience.The determination of reference ecosystems based on the intrinsic characteristics of the ecosystem is essential for conservation as well as to the implementation of ecological restoration.We proposed the reference ecosystem of the three main types of habitats of the ferruginous campo rupestre based on their floristic composition.We described the floristic composition of each habitat and evaluated the physicochemical properties of the soils and the relationship between plants and soils.All three habitats showed high diversity of plant species and many endemic species,such as Chamaecrista choriophylla,Cuphea pseudovaccinium,Lychnophora pinaster,and Vellozia subalata.The distribution of vegetation was strongly related with the edaphic characteristics,with a set of species more adapted to high concentration of base saturation,fine sand,organic carbon,and iron,while another set of species succeeded in more acidic soils with higher S and silt concentration.We provide support for the contention that the ferruginous campo rupestre is a mosaic of different habitats shaped by intrinsic local conditions.Failure to recognize the floristic composition of each particular habitat can lead to inappropriate restoration,increased habitat homogenization and increased loss of biodiversity and ecosystem services.This study also advances the knowledge base for building the reference ecosystem for the different types of ferruginous campo rupestre habitats,as well as a key database for highlighting those species contribute most to community assembly in this diverse and threatened tropical mountain ecosystem.

Different mechanisms underlie similar species-area relationships in two tropical archipelagoes

Despite much research in the field of island biogeography,mechanisms regulating insular diversity remain elusive.Here,we aim to explore mechanisms underlying plant species-area relationships in two tropical archipelagoes in the South China Sea.We found positive plant species-area relationships for both coral and continental archipelagoes.However,our results showed that different mechanisms contributed to similar plant species-area relationships between the two archipelagoes.For coral islands,soil nutrients and spatial distance among communities played major roles in shaping plant community structure and species diversity.By contrast,the direct effect of island area,and to a lesser extent,soil nutrients determined plant species richness on continental islands.Intriguingly,increasing soil nutrients availability(N,P,K)had opposite effects on plant diversity between the two archipelagoes.In summary,the habitat quality effect and dispersal limitation are important for regulating plant diversity on coral islands,whereas the passive sampling effect,and to a lesser extent,the habitat quality effect are important for regulating plant diversity on continental islands.More generally,our findings indicate that island plant species-area relationships are outcomes of the interplay of both niche and neutral processes,but the driving mechanisms behind these relationships depends on the type of islands.

Research on the Evaluation System of Community Daycare Center Planning and Implementation from the Perspective of Subject-Object Relationships

Through literature review,we found that evaluations of urban planning implementation often focus narrowly on either the subject(stakeholders)or the object(projects),while micro-level aspects such as site selection and construction are primarily considered within the context of planning implementation.There is insufficient research on the evaluation of implementation.Community daycare centers play a crucial role in the community home care model,yet there is relatively little research on their usage efficiency,satisfaction levels,and spatial evaluation of planning implementation.Based on the theoretical understanding of the human environment,including the subject,object,and their interactions,an evaluation system for the planning and implementation of community day care centers was constructed,incorporating subjective evaluation,objective evaluation,and comparative analysis.

Evaluation on Radar Reflectivity-Rainfall Rate (Z-R) Relationships for Guyana

The constant development of science and technology in weather radar results in high-resolution spatial and temporal rainfall estimates and improved early warnings of meteorological phenomena such as flood [1]. Weather radars do not measure the rainfall amount directly, so a relationship between the reflectivity (Z) and rainfall rate (R), called the Z-R relationship (Z = aRb), where a and b are empirical constants, can be used to estimate the rainfall amount. In this research, mathematical techniques were used to find the best climatological Z-R relationships for the Low Coastal Plain of Guyana. The reflectivity data from the S-Band Doppler Weather Radar for February 17 and 21, 2011 and May 8, 2012 together with the daily rainfall depths at 29 rainfall stations located within a 150 km radius were investigated. A climatological Z-R relationship type Z = 200R1.6 (Marshall-Palmer) configured by default into the radar system was used to investigate the correlation between the radar reflectivity and the rainfall by gauges. The same data sets were used with two distinct experimental Z-R relationships, Z = 300R1.4 (WSR-88D Convective) and Z = 250R1.2 (Rosenfeld Tropical) to determine if any could be applicable for area of study. By comprehensive regression analysis, New Z-R and R-Z relationships for each of the three events aforementioned were developed. In addition, a combination of all the samples for all three events were used to produce another relationship called “All in One”. Statistical measures were then applied to detect BIAS and Error STD in order to produce more evidence-based results. It is proven that different Z-R relationships could be calibrated into the radar system to provide more accurate rainfall estimation.

Mediating role of physical activity in the relationship between psychological distress and intimate relationships among stroke patients

BACKGROUND Stroke patients often experience psychological distress,which can impact their intimate relationships with spouses,subsequently influencing their treatment and recovery.Physical activity is considered a key rehabilitation method for stroke patients.This paper aims to analyze whether psychological distress affects intimate relationship between spouses through physical activity.AIM To explore the mediating effect of physical activity between psychological distress and intimate relationship in stroke patients.METHODS A total of 256 stroke patients who underwent treatment at the First People’s Hospital of Shangqiu between July 2021 and July 2022 were enrolled in this study.The participants completed questionnaires,including the Kessler Psychological Distress Scale(K10),the Quality of Relationship Index(QRI),International Physical Activity Questionnaire,and a general information questionnaire.Data analysis were performed using SPSS 23.0.The Harman test was employed to detect common method deviations,and Spearman correlation was used for correlation analysis.The mediating effect was assessed using Process 3.4.1,with significance testing of the regression coefficients conducted using the bias-corrected percentile Bootstrap method(5000 iterations,95%confidence interval).Statistical significance was set at P<0.05.RESULTS The results showed that patients scored an average of 21.61±6.44 points on the K10,32.40±6.19 points on the QRI;the median physical activity level according to the International Physical Activity Questionnaire was 1861(566,2846)MET·min/w.The level of physical activity(the physical activity intensity of the patients reflected by the Interna-tional Physical Activity Questionnaire-Long Form scale)negatively correlated with psychological distress and intimacy(P<0.05),and positively correlated with each other(P<0.05),with the correlation stronger at lower physical activity levels compared to higher ones.The mediating effect of physical activity between psychological distress and intimate relationship was calculated to be 40.23%.Bootstrap analysis further validated the results.The mediating effect of psychological distress on intimate relationships through physical activity level was-0.284,with a confidence interval of-0.409 to-0.163,excluding 0,confirming a significant mediating effect of psychological distress on intimate relationships.CONCLUSION Physical activity significantly affects relationship between psychological distress and intimate relationships among stroke patients.Addressing the role of physical activity may have implications for improving patient outcomes and rehabilitation strategies.

Four new orientation relationships of Mg_(17)Al_(12) phase with magnesium matrix in Mg-8Al-0.5Zn alloys

Although the non-basal precipitates, those not parallel to the basal plane, are more effective to block basal slip in Mg-Al alloys, the crystallographic orientation relationship(OR) between these precipitates and the α-Mg matrix has not been well established. In this work, the crystallography of the non-basal Mg_(17)Al_(12) precipitates in AZ80 alloy was systematically investigated by transmission electron microscopy(TEM). By tilting to a suitable electron beam direction, different kinds of non-basal precipitates were recognized in TEM, and the following four new ORs between the non-basal Mg_(17)Al_(12) precipitates and the matrix were revealed: ■, and ■.Furthermore, these ORs and their habit planes were explained using the edge-to-edge matching model. The findings in this work can provide some guidelines for designing the microstructure of Mg-Al alloys to enhance their precipitation hardening potential.

Structure-guided Capacitance Relationships in Oxidized Graphene Porous Materials Based Supercapacitors

Supercapacitors formed from porous carbon and graphene-oxide(GO)materials are usually dominated by either electric double-layer capacitance,pseudo-capacitance,or both.Due to these combined features,reduced GO materials have been shown to offer superior capacitance over typical nanoporous carbon materials;however,there is a significant variation in reported values,ranging between 25 and 350 F g^(−1).This undermines the structure(e.g.,oxygen functionality and/or surface area)-performance relationships for optimization of cost and scalable factors.This work demonstrates important structure-controlled charge storage relationships.For this,a series of exfoliated graphene(EG)derivatives are produced via thermal-shock exfoliation of GO precursors and following controlled graphitization of EG(GEG)generates materials with varied amounts of porosity,redox-active oxygen groups and graphitic components.Experimental results show significantly varied capacitance values between 30 and 250 F g^(−1)at 1.0 A g^(−1)in GEG structures;this suggests that for a given specific surface area the redox-active and hydrophilic oxygen content can boost the capacitance to 250–300%higher compared to typical mesoporous carbon materials.GEGs with identical oxygen functionality show a surface area governed capacitance.This allows to establish direct structure-performance relationships between 1)redox-active oxygen functional concentration and capacitance and 2)surface area and capacitance.

Solubility study of hydrogen in direct coal liquefaction solvent based on quantitative structure–property relationships model

Direct coal liquefaction(DCL)is an important and effective method of converting coal into high-valueadded chemicals and fuel oil.In DCL,heating the direct coal liquefaction solvent(DCLS)from low to high temperature and pre-hydrogenation of the DCLS are critical steps.Therefore,studying the dissolution of hydrogen in DCLS under liquefaction conditions gains importance.However,it is difficult to precisely determine hydrogen solubility only by experiments,especially under the actual DCL conditions.To address this issue,we developed a prediction model of hydrogen solubility in a single solvent based on the machine-learning quantitative structure–property relationship(ML-QSPR)methods.The results showed that the squared correlation coefficient R^(2)=0.92 and root mean square error RMSE=0.095,indicating the model’s good statistical performance.The external validation of the model also reveals excellent accuracy and predictive ability.Molecular polarization(a)is the main factor affecting the dissolution of hydrogen in DCLS.The hydrogen solubility in acyclic alkanes increases with increasing carbon number.Whereas in polycyclic aromatics,it decreases with increasing ring number,and in hydrogenated aromatics,it increases with hydrogenation degree.This work provides a new reference for the selection and proportioning of DCLS,i.e.,a solvent with higher hydrogen solubility can be added to provide active hydrogen for the reaction and thus reduce the hydrogen pressure.Besides,it brings important insight into the theoretical significance and practical value of the DCL.

Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.

Relationship between Kawasaki disease and abdominal pain

This editorial presents an analysis of an article recently published in the World Journal of Clinical Cases.Kawasaki disease(KD)is a well-known pediatric vasculitis characterized by fever,rash,conjunctivitis,oral mucosal changes,and swelling of the extremities.This editorial aims to delve into the intricate relationship between KD and abdominal pain,drawing insights from recent research findings to provide a comprehensive understanding and potential avenues for future investigation.

Elucidating the structure-activity relationship of Cu-Ag bimetallic catalysts for electrochemical CO_(2) reduction

Developing bimetallic catalysts is an effective strategy for enhancing the activity and selectivity of electrochemical CO_(2) reduction reactions,where understanding the structure-activity relationship is essential for catalyst design.Herein,we prepared two Cu-Ag bimetallic catalysts with Ag nanoparticles attached to the top or the bottom of Cu nanowires.When tested in a flow cell,the Cu-Ag catalyst with Ag nanoparticles on the bottom achieved a faradaic efficiency of 54%for ethylene production,much higher than the catalyst with Ag nanoparticles on the top.The catalysts were further studied in the H-cell and zero-gap MEA cell.It was found that placing the two metals in the intensified reaction zone is crucial to triggering the tandem reaction of bimetallic catalysts.Our work elucidates the structure-activity relationship of bimetallic catalysts for CO_(2) reduction and demonstrates the importance of considering both catalyst structures and cell characteristics to achieve high activity and selectivity.

The Relationship between Father-Love Absence and Loneliness:Based on the Perspective of the Social Functionalist Theory and the Social Needs Theory

Fathers play an important role in adolescents’development,which is significant for their development and influences their mental health,including feeling of loneliness.However,the effects and mechanisms of father-love absence on individual loneliness are not clear.Based on the social functionalist theory and the social needs theory,this study examines the influence of individual fatherlove absence on loneliness and its underlying mechanisms.A questionnaire survey was administered to 319 junior high school students and 1,476 high school students.The results showed that adolescents with father-love absence had higher levels of loneliness,and that father-love absence affected loneliness levels through mediating pathways of individual gratitude,peer relationships,and gratitude to peer relationships.This study not only confirms the negative effects of father-love absence on adolescents’loneliness,but also explains the mediate roles of individual gratitude and peer relationships.It enriches the theoretical system related to family education and has important theoretical and practical implications for further interventions on adolescents’mental health from the perspective of fatherless parenting.

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.

Nonlinear Relationship and Its Evolutionary Trace between Node Degree and Average Path Length of China Aviation Network Based on Complex Network

In order to reveal the complex network characteristics and evolution principle of China aviation network,the relationship between the node degree and the average path length of China aviation network in 1988,1994,2001,2008 and 2015 was studied.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 airline as the edge of the network.On the basis of the statistical data,the node average path length of China aviation network in 1988,1994,2001,2008 and 2015 was calculated.Through regression analysis,it was found that the node degree had a logarithmic relationship with the average length of node path,and the two parameters of the logarithmic relationship had linear evolutionary trace.Key word:China aviation network,complex network,node degree,average length of node path,logarithmic relationship,evolutionary trace.

Male/Female Relationships in Strange Interlude

Strange Interlude has been considered the most complicated play ever written by Eugene O'Neill,not only because of it's great length,but also because of the complex in structure.The play conversal most the entire life of a woman,right from her girlhood to old age.This paper intends to analyze diverse male/fem ale relationships that are evident in thisplay.

Relationships between Regional Indian Summer Monsoon Rainfall and Eurasian Snow Cover

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