In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge pr...In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge process in the wastewater treatment. By the way of trend map, keyword knowledge map, and co-cited knowledge map, specific visualization analysis and identification of the authors, institutions and regions were concluded. Furthermore, the topics and hotspots of water quality prediction in activated sludge process through the literature-co-citation-based cluster analysis and literature citation burst analysis were also determined, which not only reflected the historical evolution progress to a certain extent, but also provided the direction and insight of the knowledge structure of water quality prediction and activated sludge process for future research.展开更多
In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the in...In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.展开更多
Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentime...Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.展开更多
Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However...Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.展开更多
To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean d...To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.展开更多
Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness.They can be produced at room temperature by the electrohydraulic for...Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness.They can be produced at room temperature by the electrohydraulic forming process.In the present study,the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed.In particular,the orthogonal experimental design(OED)and central composite design(CCD)methods have been used.Through the range analysis and variance analysis of the experimental data,the influence degree of wire diameter(WD)and discharge energy(DE)on the forming quality was determined.Multiple regression analysis was performed using the response surface methodology.A prediction model for the attaching-die state coefficient was established accordingly.The following optimal arrangement of parameters was obtained(WD=0.759 mm,DE=2.926 kJ).The attaching-die state coefficient reached the peak value of 0.001.Better optimized wire diameter and discharge energy for a better attaching-die state could be screened by CCD compared with OED.The response surface method in CCD was more suitable for the design and optimization of the considered process parameters.展开更多
A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adh...A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.展开更多
Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodo...Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.展开更多
[Objectives] This study was conducted to solve the prominent problems in the treatment of domestic sewage in southern rural areas of China. [Methods] An integrated process treatment mode of anaerobic/anoxic/aerobic mo...[Objectives] This study was conducted to solve the prominent problems in the treatment of domestic sewage in southern rural areas of China. [Methods] An integrated process treatment mode of anaerobic/anoxic/aerobic moving bed biofilm reactor (A 2O-MBBR) was proposed to analyze and study its operating effect and influencing factors. [Results] The A^(2)O-MBBR mode had good COD removal efficiency and nitrogen and phosphorus removal performance, and the water quality index of the effluent met the Class A standard of GB181918-2002. This mode is suitable for treating rural domestic sewage, and has high treatment effects in different operating periods. In spring, the average removal rates of COD, NH_(4)^(+)-N, TN, TP and SS reached (83.53 ± 2.15)%, (89.44 ± 4.97)%, (67.36±18.53)%, (88.22±11.21)% and (91.73±2.25)%, respectively;In the autumn period, the average removal rates of COD, NH_(4)^(+)-N, TN, TP and SS were (83.49±2.64)%, (89.26±9.19)%, (66.05±17.00)%, (87.48±9.68)%, and (91.13±2.35)%. [Conclusions] This study provides theoretical reference and technical support for the popularization and application of A^(2)O-MBBR integrated process.展开更多
Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardwar...Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardware system.This literature review focuses on calculating WCET for multi-core processors,providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms.This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis.By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation,this review aims to serve as a valuable resource for researchers and practitioners in the field.展开更多
Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results s...Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results show that this was a type Ⅱ snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone.The main period of snowfall can be divided into two time stages,and the total snowfall was more in the south and less in the north,which was consistent with that of average specific humidity field.Water vapor conditions provided by strong water vapor transport and convergence,strong upward movement shown by large vertical velocity field,and the suction action of high-and low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18^(th).During the process,radar echoes were mainly sheet-shaped,and composite reflectivity was 15-25 dBZ in most areas.The zero speed line in the first period was positively"S"-shaped,and there was warm advection and southwest wind.On the morning of the 18^(th),after the cold front transited the city,Ulanqab City was gradually controlled by northwest wind,and the snow tended to end.展开更多
The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,...The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.展开更多
The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its...The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .展开更多
Since 2008 a network of five sea-level monitoring stations was progressively installed in French Polynesia.The stations are autonomous and data,collected at a sampling rate of 1 or 2 min,are not only recorded locally,...Since 2008 a network of five sea-level monitoring stations was progressively installed in French Polynesia.The stations are autonomous and data,collected at a sampling rate of 1 or 2 min,are not only recorded locally,but also transferred in real time by a radio-link to the NOAA through the GOES satellite.The new ET34-ANA-V80 version of ETERNA,initially developed for Earth Tides analysis,is now able to analyze ocean tides records.Through a two-step validation scheme,we took advantage of the flexibility of this new version,operated in conjunction with the preprocessing facilities of the Tsoft software,to recover co rrected data series able to model sea-level variations after elimination of the ocean tides signal.We performed the tidal analysis of the tide gauge data with the highest possible selectivity(optimal wave grouping)and a maximum of additional terms(shallow water constituents).Our goal was to provide corrected data series and modelled ocean tides signal to compute tide-free sea-level variations as well as tidal prediction models with centimeter precision.We also present in this study the characteristics of the ocean tides in French Polynesia and preliminary results concerning the non-tidal variations of the sea level concerning the tide gauge setting.展开更多
To overcome the shortcomings of traditional degumming process,an efficient and environmentally friendly ethylene glycol(EG) degumming process was adopted to degum hemp fibers.The surface morphology,chemical compositio...To overcome the shortcomings of traditional degumming process,an efficient and environmentally friendly ethylene glycol(EG) degumming process was adopted to degum hemp fibers.The surface morphology,chemical composition,chemical structures,and mechanical properties of the fiber samples were analyzed to explore the mechanism of the degumming process.It was found that the EG degumming process could be divided into the main degumming stage(heating) and the supplementary degumming stage(insulation).The removal rates of hemicellulose and lignin in the main degumming stage were 70.56% and 60.17%,respectively.In the supplementary degumming stage,9.95% hemicellulose and 25.39% lignin were removed.It is confirmed that EG can separate hemp fibers effectively with less damage,which holds great potential for the biomass fiber separation technology.展开更多
A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-effi...A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.展开更多
Matrix swelling effect will cause the change of microstructure of coal reservoir and its permeability,which is the key factor affecting the engineering effect of CO_(2)-ECBM technology.The Sihe and Yuwu collieries are...Matrix swelling effect will cause the change of microstructure of coal reservoir and its permeability,which is the key factor affecting the engineering effect of CO_(2)-ECBM technology.The Sihe and Yuwu collieries are taken as research objects.Firstly,visualization reconstruction of coal reservoir is realized.Secondly,the evolution of the pore/fracture structures under different swelling contents is discussed.Then,the influence of matrix phase with different swelling contents on permeability is discussed.Finally,the mechanism of swelling effect during the CO_(2)-ECBM process is further discussed.The results show that the intra-matrix pores and matrix-edge fractures are the focus of this study,and the contacting area between matrix and pore/fracture is the core area of matrix swelling.The number of matrix particles decreases with the increase of size,and the distribution of which is isolated with small size and interconnected with large size.The swelling effect of matrix particles with larger size has a great influence on the pore/fracture structures.The number of connected pores/fractures is limited and only interconnected in a certain direction.With the increase of matrix swelling content,the number,porosity,width,fractal dimension,surface area and volume of pores/fractures decrease,and their negative contribution to absolute permeability increases from 0.368% to 0.633% and 0.868%-1.404%,respectively.With the increase of swelling content,the number of intra-matrix pores gradually decreases and the pore radius becomes shorter during the CO_(2)-ECBM process.The matrix continuously expands to the connected fractures,and the width of connected fractures gradually shorten.Under the influence of matrix swelling,the bending degree of fluid flow increases gradually,so the resistance of fluid migration increases and the permeability gradually decreases.This study shows that the matrix swelling effect is the key factor affecting CBM recovery,and the application of this effect in CO_(2)-ECBM process can be discussed.展开更多
Sentiment analysis(SA)is the procedure of recognizing the emotions related to the data that exist in social networking.The existence of sarcasm in tex-tual data is a major challenge in the efficiency of the SA.Earlier...Sentiment analysis(SA)is the procedure of recognizing the emotions related to the data that exist in social networking.The existence of sarcasm in tex-tual data is a major challenge in the efficiency of the SA.Earlier works on sarcasm detection on text utilize lexical as well as pragmatic cues namely interjection,punctuations,and sentiment shift that are vital indicators of sarcasm.With the advent of deep-learning,recent works,leveraging neural networks in learning lexical and contextual features,removing the need for handcrafted feature.In this aspect,this study designs a deep learning with natural language processing enabled SA(DLNLP-SA)technique for sarcasm classification.The proposed DLNLP-SA technique aims to detect and classify the occurrence of sarcasm in the input data.Besides,the DLNLP-SA technique holds various sub-processes namely preprocessing,feature vector conversion,and classification.Initially,the pre-processing is performed in diverse ways such as single character removal,multi-spaces removal,URL removal,stopword removal,and tokenization.Secondly,the transformation of feature vectors takes place using the N-gram feature vector technique.Finally,mayfly optimization(MFO)with multi-head self-attention based gated recurrent unit(MHSA-GRU)model is employed for the detection and classification of sarcasm.To verify the enhanced outcomes of the DLNLP-SA model,a comprehensive experimental investigation is performed on the News Headlines Dataset from Kaggle Repository and the results signified the supremacy over the existing approaches.展开更多
The characteristics and causes of a drop in temperature during a cold wave process in the early winter of 2020/2021 were analyzed.The results show that the air temperature at 700-600 hPa over China was firstly and mos...The characteristics and causes of a drop in temperature during a cold wave process in the early winter of 2020/2021 were analyzed.The results show that the air temperature at 700-600 hPa over China was firstly and mostly influenced by the cold wave process,and then the cold air gradually extended to the lower layer,causing the most severe cooling in North China and its nearby areas.During the cold wave,the longitude of the upper-level jet over the Chinese mainland was larger;the Ural blocking high and the East Asian trough were stronger,so that the geopotential height gradient between the two was also significantly larger;the meridional air flow was abnormally strong,which was conducive to the southward transport of cold air from the middle and high latitudes.Results of the diagnostic analysis further show that the outbreak of the cold wave and the negative temperature tendency anomaly in the key area were mainly caused by the meridional temperature horizontal advection anomaly,while the temperature rise accompanied by abnormal air subsidence compensated for the abnormal decrease in temperature,which was conducive to the gradual rise of temperature in the key area.展开更多
Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To expl...Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.展开更多
文摘In this paper, CiteSpace, a bibliometrics software, was adopted to collect research papers published on the Web of Science, which are relevant to biological model and effluent quality prediction in activated sludge process in the wastewater treatment. By the way of trend map, keyword knowledge map, and co-cited knowledge map, specific visualization analysis and identification of the authors, institutions and regions were concluded. Furthermore, the topics and hotspots of water quality prediction in activated sludge process through the literature-co-citation-based cluster analysis and literature citation burst analysis were also determined, which not only reflected the historical evolution progress to a certain extent, but also provided the direction and insight of the knowledge structure of water quality prediction and activated sludge process for future research.
基金Supported by Heilongjiang Provincial Fruit Tree Modernization Agro-industrial Technology Collaborative Innovation and Promotion System Project(2019-13)。
文摘In order to obtain better quality cookies, food 3D printing technology was employed to prepare cookies. The texture, color, deformation, moisture content, and temperature of the cookie as evaluation indicators, the influences of baking process parameters, such as baking time, surface heating temperature and bottom heating temperature, on the quality of the cookie were studied to optimize the baking process parameters. The results showed that the baking process parameters had obvious effects on the texture, color, deformation, moisture content, and temperature of the cookie. All of the roasting surface heating temperature, bottom heating temperature and baking time had positive influences on the hardness, crunchiness, crispiness, and the total color difference(ΔE) of the cookie. When the heating temperatures of the surfac and bottom increased, the diameter and thickness deformation rate of the cookie increased. However,with the extension of baking time, the diameter and thickness deformation rate of the cookie first increased and then decreased. With the surface heating temperature of 180 ℃, the bottom heating temperature of 150 ℃, and baking time of 15 min, the cookie was crisp and moderate with moderate deformation and uniform color. There was no burnt phenomenon with the desired quality. Research results provided a theoretical basis for cookie manufactory based on food 3D printing technology.
文摘Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.
基金the financial support from the Strategic Priority Research Program of Chinese Academy of Sciences(XDA21010100)。
文摘Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.
基金the Sichuan Science and Technology Program(Nos.23ZHCG0049,2023YFG0078,23ZHCG0030,2021ZDZX0007)SCU-SUINING Project(2022CDSN-14).
文摘To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.
基金supported by National Natural Science Foundation of China(Grant Nos.51975202(Junjia Cui received the grant)and 52175315(Guangyao Li received the grant)).
文摘Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness.They can be produced at room temperature by the electrohydraulic forming process.In the present study,the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed.In particular,the orthogonal experimental design(OED)and central composite design(CCD)methods have been used.Through the range analysis and variance analysis of the experimental data,the influence degree of wire diameter(WD)and discharge energy(DE)on the forming quality was determined.Multiple regression analysis was performed using the response surface methodology.A prediction model for the attaching-die state coefficient was established accordingly.The following optimal arrangement of parameters was obtained(WD=0.759 mm,DE=2.926 kJ).The attaching-die state coefficient reached the peak value of 0.001.Better optimized wire diameter and discharge energy for a better attaching-die state could be screened by CCD compared with OED.The response surface method in CCD was more suitable for the design and optimization of the considered process parameters.
基金the High-Performance Computing Platform of Beijing University of Chemical Technology(BUCT)for supporting this papersupported by the Fundamental Research Funds for the Central Universities(JD2319)+2 种基金the CNOOC Technical Cooperation Project(ZX2022ZCTYF7612)the National Natural Science Foundation of China(51775029,52004014)the Chinese Universities Scientific Fund(XK2020-04)。
文摘A rotating packed bed is a typical chemical process enhancement equipment that can strengthen micromixing and mass transfer.During the operation of the rotating packed bed,the nonreactants and products irregularly adhere to the wire mesh packing in the rotor,thus resulting in an imbalance in the vibration of the rotor,which may cause serious damage to the bearing and material leakage.This study proposes a model prediction for estimating the bearing residual life of a rotating packed bed based on rotor imbalance response analysis.This method is used to determine the influence of the mass on the imbalance in the vibration of the rotor on bearing damage.The major influence on rotor vibration was found to be exerted by the imbalanced mass and its distribution radius,as revealed by the results of orthogonal experiments.Through implementing finite element analysis,the imbalance response curve for the rotating packed bed rotor was obtained,and a correlation among rotor imbalance mass,distribution radius of imbalance mass,and bearing residue life was established via data fitting.The predicted value of the bearing life can be used as the reference basis for an early safety warning of a rotating packed bed to effectively avoid accidents.
文摘Floods are phenomenon with significant socio-economic implications mainly for human loss, agriculture, livestock, soil loss and land degradation, for which many researchers try to identify the most appropriate methodologies by analyzing their temporal and spatial development. This study therefore attempts to employ the GIS-based multi-criteria decision analysis and analytical hierarchy process techniques to derive the flood risks management on rice productivity in the Gishari Agricultural Marshland in Rwamagana district, Rwanda. Here, six influencing potential factors to flooding, including river slope, soil texture, Land Use Land Cover through Land Sat 8, rainfall, river distance and Digital Elevation Model are considered for the delineation of flood risk zones. Data acquisition like Landsat 8 images, DEM, land use land cover, slope, and soil class in the study area were considered. Results showed that if the DEM is outdated or inaccurate due to changes in the terrain, such as construction, excavation, or erosion, the predicted flood patterns might not reflect the actual water flow. This could result unexpected flood extents and depths, potentially inundating rice fields that were not previously at risk and this, expectedly explained that the increase 1 m in elevation would reduce the rice productivity by 0.17% due to unplanned flood risks in marshland. It was found that the change in rainfall distribution in Gishari agricultural marshland would also decrease the rice productivity by 0.0018%, which is a sign that rainfall is a major factor of flooding in rice scheme. Rainfall distribution plays a crucial role in flooding analysis and can directly impact rice productivity. Oppositely, another causal factor was Land Use Land Cover (LULC), where the Multivariate Logistic Regression Model Analysis findings showed that the increase of one unit in Land Use Land Cover would increase rice productivity by 0.17% of the total rice productivity from the Gishari Agricultural Marshland. Based on findings from these techniques, the Gishari Agricultural Marshlands having steeped land with grassland is classified into five classes of flooding namely very low, low, moderate, high, and very high which include 430%, 361%, 292%, 223%, and 154%. Government of Rwanda and other implementing agencies and major key actors have to contribute on soil and water conservation strategies to reduce the runoff and soil erosion as major contributors of flooding.
基金Supported by Scientific Research Project of Hunan Provincial Department of Education(22C0083)。
文摘[Objectives] This study was conducted to solve the prominent problems in the treatment of domestic sewage in southern rural areas of China. [Methods] An integrated process treatment mode of anaerobic/anoxic/aerobic moving bed biofilm reactor (A 2O-MBBR) was proposed to analyze and study its operating effect and influencing factors. [Results] The A^(2)O-MBBR mode had good COD removal efficiency and nitrogen and phosphorus removal performance, and the water quality index of the effluent met the Class A standard of GB181918-2002. This mode is suitable for treating rural domestic sewage, and has high treatment effects in different operating periods. In spring, the average removal rates of COD, NH_(4)^(+)-N, TN, TP and SS reached (83.53 ± 2.15)%, (89.44 ± 4.97)%, (67.36±18.53)%, (88.22±11.21)% and (91.73±2.25)%, respectively;In the autumn period, the average removal rates of COD, NH_(4)^(+)-N, TN, TP and SS were (83.49±2.64)%, (89.26±9.19)%, (66.05±17.00)%, (87.48±9.68)%, and (91.13±2.35)%. [Conclusions] This study provides theoretical reference and technical support for the popularization and application of A^(2)O-MBBR integrated process.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.2022ZTE09.
文摘Real-time system timing analysis is crucial for estimating the worst-case execution time(WCET)of a program.To achieve this,static or dynamic analysis methods are used,along with targeted modeling of the actual hardware system.This literature review focuses on calculating WCET for multi-core processors,providing a survey of traditional methods used for static and dynamic analysis and highlighting the major challenges that arise from different program execution scenarios on multi-core platforms.This paper outlines the strengths and weaknesses of current methodologies and offers insights into prospective areas of research on multi-core analysis.By presenting a comprehensive analysis of the current state of research on multi-core processor analysis for WCET estimation,this review aims to serve as a valuable resource for researchers and practitioners in the field.
文摘Based on the observation data of meteorological stations,Doppler radar observation data of Ulanqab City,and ERA-5 reanalysis data,a snowstorm process in Ulanqab City from March 17 to 18,2022 was analyzed.The results show that this was a type Ⅱ snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone.The main period of snowfall can be divided into two time stages,and the total snowfall was more in the south and less in the north,which was consistent with that of average specific humidity field.Water vapor conditions provided by strong water vapor transport and convergence,strong upward movement shown by large vertical velocity field,and the suction action of high-and low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18^(th).During the process,radar echoes were mainly sheet-shaped,and composite reflectivity was 15-25 dBZ in most areas.The zero speed line in the first period was positively"S"-shaped,and there was warm advection and southwest wind.On the morning of the 18^(th),after the cold front transited the city,Ulanqab City was gradually controlled by northwest wind,and the snow tended to end.
基金supported by Ministry of Science and Technology of the People's Republic of China(Grant No.:2022YFC3502300)Beijing Natural Science Foundation(Grant No.:L222150)+2 种基金the National Natural Science Foundation of China(Grant No.:82072247)the second batch of“Ten thousand plan”National High Level Talents Special Support Plan(Grant No.:W02020052)Beijing University of Chinese Medicine(Grant Nos.:XJYS21005,JY21024,MSGZF-202001,2022-syjs-05,and 2022-syjs-10).
文摘The automation of traditional Chinese medicine(TCM)pharmaceuticals has driven the development of process analysis from offline to online.Most of common online process analytical technologies are based on spectroscopy,making the identification and quantification of specific ingredients still a challenge.Herein,we developed a quality control(QC)system for monitoring TCM pharmaceuticals based on paper spray ionization miniature mass spectrometry(mini-MS).It enabled real-time online qualitative and quantitative detection of target ingredients in herbal extracts using mini-MS without chromatographic separation for the first time.Dynamic changes of alkaloids in Aconiti Lateralis Radix Praeparata(Fuzi)during decoction were used as examples,and the scientific principle of Fuzi compatibility was also investigated.Finally,the system was verified to work stably at the hourly level for pilot-scale extraction.This mini-MS based online analytical system is expected to be further developed for QC applications in a wider range of pharmaceutical processes.
基金This work was supported by Science and Technology Project of State Grid Corporation“Research on Key Technologies of Power Artificial Intelligence Open Platform”(5700-202155260A-0-0-00).
文摘The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .
基金funding from the“Talent Introduction Scientific Research Start-Up Fund”of Shandong University of Science and Technology(Grant number 0104060510217)the“Open Fund of State Key Laboratory of Geodesy and Earth’s Dynamics”(Grant number SKLGED2021-3-5)。
文摘Since 2008 a network of five sea-level monitoring stations was progressively installed in French Polynesia.The stations are autonomous and data,collected at a sampling rate of 1 or 2 min,are not only recorded locally,but also transferred in real time by a radio-link to the NOAA through the GOES satellite.The new ET34-ANA-V80 version of ETERNA,initially developed for Earth Tides analysis,is now able to analyze ocean tides records.Through a two-step validation scheme,we took advantage of the flexibility of this new version,operated in conjunction with the preprocessing facilities of the Tsoft software,to recover co rrected data series able to model sea-level variations after elimination of the ocean tides signal.We performed the tidal analysis of the tide gauge data with the highest possible selectivity(optimal wave grouping)and a maximum of additional terms(shallow water constituents).Our goal was to provide corrected data series and modelled ocean tides signal to compute tide-free sea-level variations as well as tidal prediction models with centimeter precision.We also present in this study the characteristics of the ocean tides in French Polynesia and preliminary results concerning the non-tidal variations of the sea level concerning the tide gauge setting.
基金Fundamental Research Funds for the Central Universities of Ministry of Education of China(No.2232020A-07)。
文摘To overcome the shortcomings of traditional degumming process,an efficient and environmentally friendly ethylene glycol(EG) degumming process was adopted to degum hemp fibers.The surface morphology,chemical composition,chemical structures,and mechanical properties of the fiber samples were analyzed to explore the mechanism of the degumming process.It was found that the EG degumming process could be divided into the main degumming stage(heating) and the supplementary degumming stage(insulation).The removal rates of hemicellulose and lignin in the main degumming stage were 70.56% and 60.17%,respectively.In the supplementary degumming stage,9.95% hemicellulose and 25.39% lignin were removed.It is confirmed that EG can separate hemp fibers effectively with less damage,which holds great potential for the biomass fiber separation technology.
基金funded by the National Natural Science Foundation of China(41971226,41871357)the Major Research and Development and Achievement Transformation Projects of Qinghai,China(2022-QY-224)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA28110502,XDA19030303).
文摘A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.
基金This work was financially supported by the National Natural Science Foundation of China(No.42102217)the University Synergy Innovation Program of Anhui Province(No.GXXT-2021-018)+3 种基金the Natural Science Research Project of Anhui University(No.KJ2020A0315No.KJ2020A0317)the Natural Science Foundation of Anhui Province(No.2108085MD134)the Foundation of State Key Laboratory of Petroleum Resources and Prospecting,China University of Petroleum,Beijing(No.PRP/open-2005).
文摘Matrix swelling effect will cause the change of microstructure of coal reservoir and its permeability,which is the key factor affecting the engineering effect of CO_(2)-ECBM technology.The Sihe and Yuwu collieries are taken as research objects.Firstly,visualization reconstruction of coal reservoir is realized.Secondly,the evolution of the pore/fracture structures under different swelling contents is discussed.Then,the influence of matrix phase with different swelling contents on permeability is discussed.Finally,the mechanism of swelling effect during the CO_(2)-ECBM process is further discussed.The results show that the intra-matrix pores and matrix-edge fractures are the focus of this study,and the contacting area between matrix and pore/fracture is the core area of matrix swelling.The number of matrix particles decreases with the increase of size,and the distribution of which is isolated with small size and interconnected with large size.The swelling effect of matrix particles with larger size has a great influence on the pore/fracture structures.The number of connected pores/fractures is limited and only interconnected in a certain direction.With the increase of matrix swelling content,the number,porosity,width,fractal dimension,surface area and volume of pores/fractures decrease,and their negative contribution to absolute permeability increases from 0.368% to 0.633% and 0.868%-1.404%,respectively.With the increase of swelling content,the number of intra-matrix pores gradually decreases and the pore radius becomes shorter during the CO_(2)-ECBM process.The matrix continuously expands to the connected fractures,and the width of connected fractures gradually shorten.Under the influence of matrix swelling,the bending degree of fluid flow increases gradually,so the resistance of fluid migration increases and the permeability gradually decreases.This study shows that the matrix swelling effect is the key factor affecting CBM recovery,and the application of this effect in CO_(2)-ECBM process can be discussed.
基金supported through the Annual Funding track by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Project No.AN000685].
文摘Sentiment analysis(SA)is the procedure of recognizing the emotions related to the data that exist in social networking.The existence of sarcasm in tex-tual data is a major challenge in the efficiency of the SA.Earlier works on sarcasm detection on text utilize lexical as well as pragmatic cues namely interjection,punctuations,and sentiment shift that are vital indicators of sarcasm.With the advent of deep-learning,recent works,leveraging neural networks in learning lexical and contextual features,removing the need for handcrafted feature.In this aspect,this study designs a deep learning with natural language processing enabled SA(DLNLP-SA)technique for sarcasm classification.The proposed DLNLP-SA technique aims to detect and classify the occurrence of sarcasm in the input data.Besides,the DLNLP-SA technique holds various sub-processes namely preprocessing,feature vector conversion,and classification.Initially,the pre-processing is performed in diverse ways such as single character removal,multi-spaces removal,URL removal,stopword removal,and tokenization.Secondly,the transformation of feature vectors takes place using the N-gram feature vector technique.Finally,mayfly optimization(MFO)with multi-head self-attention based gated recurrent unit(MHSA-GRU)model is employed for the detection and classification of sarcasm.To verify the enhanced outcomes of the DLNLP-SA model,a comprehensive experimental investigation is performed on the News Headlines Dataset from Kaggle Repository and the results signified the supremacy over the existing approaches.
基金Supported by the National Natural Science Foundation of China(42075053,41275099).
文摘The characteristics and causes of a drop in temperature during a cold wave process in the early winter of 2020/2021 were analyzed.The results show that the air temperature at 700-600 hPa over China was firstly and mostly influenced by the cold wave process,and then the cold air gradually extended to the lower layer,causing the most severe cooling in North China and its nearby areas.During the cold wave,the longitude of the upper-level jet over the Chinese mainland was larger;the Ural blocking high and the East Asian trough were stronger,so that the geopotential height gradient between the two was also significantly larger;the meridional air flow was abnormally strong,which was conducive to the southward transport of cold air from the middle and high latitudes.Results of the diagnostic analysis further show that the outbreak of the cold wave and the negative temperature tendency anomaly in the key area were mainly caused by the meridional temperature horizontal advection anomaly,while the temperature rise accompanied by abnormal air subsidence compensated for the abnormal decrease in temperature,which was conducive to the gradual rise of temperature in the key area.
文摘Background In early adolescence,youth are highly prone to suicidal behaviours.Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.Aims To explore the risk and protective factors of suicidal behaviours(ie,suicidal ideation,plans and attempts)in early adolescence in China using a social-ecological perspective.Methods Using data from the cross-sectional project‘Healthy and Risky Behaviours Among Middle School Students in Anhui Province,China',stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020.Network analysis was employed to examine the correlates of suicidal ideation,plans and attempts at four levels,namely individual(sex,academic performance,serious physical llness/disability,history of self-harm,depression,impulsivity,sleep problems,resilience),family(family economic status,relationship with mother,relationship with father,family violence,childhood abuse,parental mental illness),school(relationship with teachers,relationship with classmates,school-bullying victimisation and perpetration)and social(social support,satisfaction with society).Results In total,37.9%,19.0%and 5.5%of the students reported suicidal ideation,plans and attempts in the past 6 months,respectively.The estimated network revealed that suicidal ideation,plans and attempts were collectively associated with a history of self-harm,sleep problems,childhood abuse,school bullying and victimisation.Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse.Notably,the network also showed unique correlates of suicidal ideation(sex,weight=0.60;impulsivity,weight=0.24;family violence,weight=0.17;relationship with teachers,weight=-0.03;school-bullying perpetration,weight=0.22),suicidal plans(social support,weight=-0.15)and suicidal attempts(relationship with mother,weight=-0.10;parental mental llness,weight=0.61).Conclusions This study identified the correlates of suicidal ideation,plans and attempts,and provided practical implications for suicide prevention for young adolescents in China.Firstly,this study highlighted the importance of joint interventions across multiple departments.Secondly,the common risk factors of suicidal ideation,plans and attempts were elucidated.Thirdly,this study proposed target interventions to address the unique influencing factors of suicidal ideation,plans and attempts.