Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multi...Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role.Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.Methods:We used a series of different detectors(i.e.,specific detector,risk detector,ecological detector and interaction detector)to evaluate separate and interactive effects of the environmental factors on schistosomiasis prevalence.Specifically,(i)specific detector quantifies the impact of a risk factor on an observed spatial disease pattern,which were ranked statistically by a value of Power of Determinate(PD)calculation;(ii)risk detector detects high risk areas of a disease on the condition that the study area is stratified by a potential risk factor;(iii)ecological detector explores whether a risk factor is more significant than another in controlling the spatial pattern of a disease;(iv)interaction detector probes whether two risk factors when taken together weaken or enhance one another,or whether they are independent in developing a disease.Infection data of schistosomiasis based on conventional surveys were obtained at the county level from the health authorities in Anhui Province,China and used in combination with information from Chinese weather stations and internationally available environmental data.Results:The specific detector identified various factors of potential importance as follows:Proximity to Yangtze River(0.322)>Land cover(0.285)>sunshine hours(0.256)>population density(0.109)>altitude(0.090)>the normalized different vegetation index(NDVI)(0.077)>land surface temperature at daytime(LST_(day))(0.007).The risk detector indicated that areas of schistosomiasis high risk were located within a buffer distance of 50 km from Yangtze River.The ecological detector disclosed that the factors展开更多
From the case study of Evening Bell Ringing at Nanping Hill,one of the West Lake Cultural Landscapes in Hangzhou,China,we investigated the soundscape of a scenic area with a profound cultural background.First,we condu...From the case study of Evening Bell Ringing at Nanping Hill,one of the West Lake Cultural Landscapes in Hangzhou,China,we investigated the soundscape of a scenic area with a profound cultural background.First,we conducted the soundscape physical index of the area in both winter and spring seasons to analyze its objective graphical expression.Second,we focused on people's reactions to the soundscape in order to obtain a subjective evaluation of each component in the soundscape and integrated environment.Then,the relationship between the objective data and the subjective evaluation was analyzed.Finally,the impacts of the natural environment,history,and cultural factors on the evaluation of the Jingci Temple soundscape were studied.It was found that natural sounds,cultural sounds,and historic sounds were widely acclaimed in people's subjective feelings,which indicated the close relationships among historical and cultural background,soundscape,and natural environment.Thus,the conclusion was made that soundscape should be consistent with the local natural environment and the historical and cultural background.展开更多
Objective To compare the cognitive effects of guqin （the oldest Chinese instrument） music and piano music. Methods Behavioral and event-related potential （ERP） data in a standard two-stimulus auditory oddball task...Objective To compare the cognitive effects of guqin （the oldest Chinese instrument） music and piano music. Methods Behavioral and event-related potential （ERP） data in a standard two-stimulus auditory oddball task were recorded and analyzed. Results This study replicated the previous results of culture-familiar music effect on Chinese subjects： the greater P300 amplitude in frontal areas in a culture-familiar music environment. At the same time, the difference between guqin music and piano music was observed in NI and later positive complex （LPC： including P300 and P500）： a relatively higher participation of right anterior-temporal areas in Chinese subjects. Conclusion The results suggest that the special features of ERP responses to guqin music are the outcome of Chinese tonal language environments given the similarity between Guqin＇s tones and Mandarin lexical tones.展开更多
In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitiv...In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitivity for regional level has been well studied. However, the uncertainty analysis for project level running emissions has not been well understood. In this research, the MOVES model project level sensitivity tests on running emissions were conducted thru the analysis of vehicle specific power （VSP）, scaled tractive power （STP）, and MOVES emission rates versus speed curves. This study tested the speed, acceleration, and grade-three most critical variables for vehicle specific power for light duty vehicles and scaled tractive power for heavy duty vehicles. For the testing of STP, four regulatory classes of heavy duty vehicles including light heavy duty （LHD）, medium heavy duty （MHD）, heavy heavy duty （HHD） and bus were selected. MOVES project running emission rates were also tested for CO, PM2.5, NOx, and VOC versus the operating speeds. A Latin Hypercube （LH） sampling based on method for estimation of the ＂Sobal＂ sensitivity indices shows that the speed is the most critical variable among the three inputs for both VSP and STP. Acceleration and grades show lower response to the main effects and sensitivity indices. MOVES emission rates versus speeds curves for light duty vehicles show that highest emission occurs at lower speed range. No significant differences on emission rates among the regulatory classes of heavy duty vehicles are identified.展开更多
The components of the rock, the pigments, the gold foils and the adhesive of One Thousand Hand Buddha in Dazu stone sculptures, Chongqing, China, have been analyzed by X-ray diffraction (XRD), X-ray fluorescence (XRF)...The components of the rock, the pigments, the gold foils and the adhesive of One Thousand Hand Buddha in Dazu stone sculptures, Chongqing, China, have been analyzed by X-ray diffraction (XRD), X-ray fluorescence (XRF), infrared spectroscopy (IR), energy dispersive X-ray analysis (EDX) and fiber optics reflectance spectros-copy (FORS). Furthermore, the weathering and degeneration of One Thousand Hand Buddha have been discussed and the protective methods have been provided. In this work some useful information to study on conservation of stone relics is given.展开更多
Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sec...Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.展开更多
The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascen...The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.展开更多
Urban forest has undergone rapid development in China over the last three decades because of the acceleration of urbanization.Urban forest thus plays an increasingly important role in carbon sequestration at a regiona...Urban forest has undergone rapid development in China over the last three decades because of the acceleration of urbanization.Urban forest thus plays an increasingly important role in carbon sequestration at a regional and national scale.As one of the most urbanized cities in China,Shanghai showed an increase of forest coverage from 3% in the 1990s to 13% in 2009.Based on CITY-green model and the second soil survey of Shanghai,the forest biomass carbon(FBC) was estimated to be 0.48 Tg in the urban area and,forest soil organic carbon(SOC)(0-100 cm soil depth) is 2.48 Tg in the urban and suburban areas,respectively.These values are relatively within the median and lower level compared with other Chinese megacities,with the FBC of 0.02 Tg in Harbin to 47.29 Tg in Chongqing and the forest SOC of 1.74 Tg in Nanjing to 418.67 Tg in Chongqing.For the different land-use types in Shanghai,the SOC density ranges from 13.8(tidal field) to 38.6 t ha-1(agricultural land).On average,the forest SOC density(31.5 t ha-1) in Shanghai is lower than that in agricultural lands(38.6 t ha-1) and higher than that in lawns(26.5 t ha-1) and gardens(21.3 t ha-1).In Shanghai,the SOC density in newly established urban parks is generally lower than that in older parks.In the northern and southeastern suburban areas(e.g.,Baoshan,Yangpu,and Nanhui districts),greenspace SOC density is higher than that in the central commercial areas(Hongkou,Putuo,Changning,and Zhabei districts) and in newly developed district(Pudong District).Uncertainties still exist in the estimation of urban forest carbon in Shanghai,as well as in other Chinese cities.Thus,future research directions are also discussed in this paper.展开更多
Here,we report the production of 3D-printed MoS_(2)/Ni electrodes(3D-MoS_(2)/Ni)with longterm stability and excellent performance by the selective laser melting(SLM)technique.As a cathode,the obtained 3D-MoS_(2)/Ni co...Here,we report the production of 3D-printed MoS_(2)/Ni electrodes(3D-MoS_(2)/Ni)with longterm stability and excellent performance by the selective laser melting(SLM)technique.As a cathode,the obtained 3D-MoS_(2)/Ni could maintain a degradation rate above 94.0%for forfenicol(FLO)when repeatedly used 50 times in water.We also found that the removal rate of FLO by 3D-MoS_(2)/Ni was about 12 times higher than that of 3D-printed pure Ni(3D-Ni),attributed to the improved accessibility of H^(*).In addition,the electrochemical characterization results showed that the electrochemically active surface area of the 3D-MoS_(2)/Ni electrode is about 3-fold higher than that of the 3D-Ni electrode while the electrical resistance is 4 times lower.Based on tert-butanol suppression,electron paramagnetic resonance and triple quadrupole mass spectrometer experiments,a“dual path”mechanism and possible degradation pathway for the dechlorination of FLO by 3D-MoS_(2)/Ni were proposed.Furthermore,we also investigated the impacts of the cathode potential and the initial pH of the solution on the degradation of FLO.Overall,this study reveals that the SLM 3D printing technique is a promising approach for the rapid fabrication of high-stability metal electrodes,which could have broad application in the control of water contaminants in the environmental field.展开更多
Drought can greatly impact the biodiversity of an ecosystem and play a crucial role in regulating its functioning.However,the specific mechanisms by which drought mediate the biodiversity effect(BE)on community biomas...Drought can greatly impact the biodiversity of an ecosystem and play a crucial role in regulating its functioning.However,the specific mechanisms by which drought mediate the biodiversity effect(BE)on community biomass in above-and belowground through functional traits remain poorly understood.Here,we conducted a common garden experiment in a greenhouse,which included two plant species richness levels and two water addition levels,to analyze the effects of biodiversity on aboveground biomass(AGB),belowground biomass(BGB)and total biomass(TB),and to quantify the relationship between BEs and functional traits under drought conditions.Our analysis focused on partitioning BEs into above-and belowground complementarity effect(CE)and selection effect(SE)at the species level,which allowed us to better understand the impacts of biodiversity on community biomass and the underlying mechanisms.Our results showed that plant species richness stimulated AGB,BGB and TB through CEs.Drought decreased AGB,BGB and TB,simultaneously.In addition,the aboveground CE was positively associated with the variation in plant height.SEs in above-and belowground were negatively correlated with the community mean plant height and root length,respectively.Furthermore,drought weakened the aboveground CE by decreasing variation in plant height,resulting in a reduction in AGB and TB.Our findings demonstrate that the complementarity of species is an important regulator of community biomass in above-and belowground,the dynamics of biomass under environmental stress are associated with the response of sensitive compartments.展开更多
Owing to the rapid increase in the interchange of text information through internet networks,the reliability and security of digital content are becoming a major research problem.Tampering detection,Content authentica...Owing to the rapid increase in the interchange of text information through internet networks,the reliability and security of digital content are becoming a major research problem.Tampering detection,Content authentication,and integrity verification of digital content interchanged through the Internet were utilized to solve a major concern in information and communication technologies.The authors’difficulties were tampering detection,authentication,and integrity verification of the digital contents.This study develops an Automated Data Mining based Digital Text Document Watermarking for Tampering Attack Detection(ADMDTW-TAD)via the Internet.The DM concept is exploited in the presented ADMDTW-TAD technique to identify the document’s appropriate characteristics to embed larger watermark information.The presented secure watermarking scheme intends to transmit digital text documents over the Internet securely.Once the watermark is embedded with no damage to the original document,it is then shared with the destination.The watermark extraction process is performed to get the original document securely.The experimental validation of the ADMDTW-TAD technique is carried out under varying levels of attack volumes,and the outcomes were inspected in terms of different measures.The simulation values indicated that the ADMDTW-TAD technique improved performance over other models.展开更多
The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live sel...The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.展开更多
With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has enhanced.This evolution has brought significant changes from conventional medicine-base...With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has enhanced.This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare.Biomedical Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in nature.Due to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients.In such scenario computer-assisted automated diagnostic tools are important for classification of ECG signals.The current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)approach.To accomplish this,the proposed IBADL-BECGC model initially pre-processes the input signals.Besides,IBADL-BECGC model applies NasNet model to derive the features from test ECG signals.In addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet approach.Finally,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification method.The presented IBADL-BECGC model was experimentally validated utilizing benchmark dataset.The comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.展开更多
There is an increased global demand for activated carbon(AC)in application of water treatment and purification.Water pollutants that have exhibited a greater removal efficiency by AC included but not limited to heavy ...There is an increased global demand for activated carbon(AC)in application of water treatment and purification.Water pollutants that have exhibited a greater removal efficiency by AC included but not limited to heavy metals,pharmaceuticals,pesticides,natural organic matter,disinfection by-products,and microplastics.Granular activated carbon(GAC)is mostly used in aqueous so-lutions and adsorption columns for water treatment.Commercial AC is not only costly,but also obtained from non-renewable sources.This has prompted the search for alternative renewable materials for AC production.Biomass wastes present a great potential of such materials because of their availability and carbonaceous nature.This in turn can reduce on the adverse environmental effects caused by poor disposal of these wastes.The challenges associated with biomass waste based GAC are their low strength and attrition resistance which make them easily disintegrate under aqueous phase.This paper provides a comprehensive review on recent advances in production of biomass waste based GAC for water treatment and highlights future research directions.Production parameters such as granulation conditions,use of binders,carbonization,activation methods,and their effect on textural properties are discussed.Factors influencing the adsorption capacities of the derived GACs,adsorption models,adsorption mechanisms,and their regeneration potentials are reviewed.The literature reveals that biomass waste materials can produce GAC for use in water treatment with possibilities of being regenerated.Nonetheless,there is a need to explore 1)the effect of preparation pathways on the adsorptive properties of biomass derived GAC,2)sustainable production of biomass derived GAC based on life cycle assessment and techno-economic analysis,and 3)adsorption mechanisms of GAC for removal of contaminants of emerging concerns such as microplastics and unregulated disinfection by-products.展开更多
Presently,smart cities play a vital role to enhance the quality of living among human beings in several ways such as online shopping,e-learning,ehealthcare,etc.Despite the benefits of advanced technologies,issues are ...Presently,smart cities play a vital role to enhance the quality of living among human beings in several ways such as online shopping,e-learning,ehealthcare,etc.Despite the benefits of advanced technologies,issues are also existed from the transformation of the physical word into digital word,particularly in online social networks(OSN).Cyberbullying(CB)is a major problem in OSN which needs to be addressed by the use of automated natural language processing(NLP)and machine learning(ML)approaches.This article devises a novel search and rescue optimization with machine learning enabled cybersecurity model for online social networks,named SRO-MLCOSN model.The presented SRO-MLCOSN model focuses on the identification of CB that occurred in social networking sites.The SRO-MLCOSN model initially employs Glove technique for word embedding process.Besides,a multiclass-weighted kernel extreme learning machine(M-WKELM)model is utilized for effectual identification and categorization of CB.Finally,Search and Rescue Optimization(SRO)algorithm is exploited to fine tune the parameters involved in the M-WKELM model.The experimental validation of the SRO-MLCOSN model on the benchmark dataset reported significant outcomes over the other approaches with precision,recall,and F1-score of 96.24%,98.71%,and 97.46%respectively.展开更多
This study aimed to understand disruptive thinking and how its ideas can change the food industry. This was achieved by identifying, studying, and understanding the impacts, current trends, and different disruptive id...This study aimed to understand disruptive thinking and how its ideas can change the food industry. This was achieved by identifying, studying, and understanding the impacts, current trends, and different disruptive ideas and innovations emerging in the food industry. The study was conducted through interpretive research philosophy by carrying out secondary data collection processes, where both qualitative and quantitative information was presented. Deductive approaches were also selected to apply existing theories and models, which were used to construct research hypotheses and present detailed findings. The study finds that, with disruptive thinking, enhancements in the product life cycle, new flavors, and improvements in food packaging have been possible. The supply chain, which is always considered a complex part of the food industry, has been streamlined, offering greater transparency and real-time tracking and improving quality control across distribution systems.展开更多
It is essential to better integrate wilderness representations of different stakeholders into wilderness conservation.The way in which local residents and other stakeholders frame the construction of wilderness of pro...It is essential to better integrate wilderness representations of different stakeholders into wilderness conservation.The way in which local residents and other stakeholders frame the construction of wilderness of protected areas in developing countries are poorly understood.In these areas,land use policy and decision may lead to conflicts.This study aims to explore existing public wilderness representations using a questionnaire survey(n=514)administered amongst tourists and other stakeholders in the Wuyishan National Park,in southeast China.The spatial differences in public representations of wilderness across different stakeholder groups were compared against expert knowledge.We found that integrated wilderness representation maps of different stakeholder groups were consistent,namely'area where wild animals live','area with no human influence','a barren and lonely area'.However,three sub-representations of the individual stakeholders varied significantly.Moreover,expert-based wilderness mapping did not reflect public representations accurately,and an integrated wilder-ness quality map considering wilderness representations across both stakeholders and experts can better identify detailed wilderness areas.Our study provides new insights and technical support for future exploration of wilder-ness conservation and mapping in China and other countries with insufficient awareness of wilderness values and investigations in a regional scale.展开更多
Background： This study was to establish a disease differentiation model for ST-segment elevation myocardial infarction （STEMI） youth patients experiencing ischemia and reperfusion via ultra-performance liquid chrom...Background： This study was to establish a disease differentiation model for ST-segment elevation myocardial infarction （STEMI） youth patients experiencing ischemia and reperfusion via ultra-performance liquid chromatography and mass spectrometry （UPLC/MS） platform, which searches for closely related characteristic metabolites and metabolic pathways to evaluate their predictive value in the prognosis after discharge. Methods： Forty-seven consecutive STEMI patients （23 patients under 45 years of age, referred to here as ＂youth,＂ and 24 elderly patients） and 48 healthy control group members （24 youth, 24 elderly） were registered prospectively. The youth patients were required to provide a second blood draw during a follow-up visit one year after morbidity （n - 22, one lost）. Characteristic metabolites and relative metabolic pathways were screened via UPLC/MS platform base on the Kyoto encyclopedia of genes and genomes （KEGG） and Human Metabolome Database. Receiver operating characteristic （ROC） curves were drawn to evaluate the predictive value of characteristic metabolites in the prognosis after discharge. Results： We successfully established an orthogonal partial least squares discriminated analysis model （R2X = 71.2%, R2Y = 79.6%, and Q2 55.9%） and screened out 24 ions; the sphingolipid metabolism pathway showed the most drastic change. The ROC curve analysis showed that ceramide [Cer（dl 8：0/16：0）, Cer（t 18：0/12：0）] and sphinganine in the sphingolipid pathway have high sensitivity and specificity on the prognosis related to major adverse cardiovascular events after youth patients were discharged. The area under curve （AUC） was 0.67 1, 0.750, and 0.711, respectively. A follow-up validation one year after morbidity showed corresponding AUC of 0.778, 0.833, and 0.806. Conclusions： By analyzing the plasma metabolism of myocardial infarction patients, we successfully established a model that can distinguish two different factors simultaneously： patholog展开更多
Recently,computer aided diagnosis(CAD)model becomes an effective tool for decision making in healthcare sector.The advances in computer vision and artificial intelligence(AI)techniques have resulted in the effective d...Recently,computer aided diagnosis(CAD)model becomes an effective tool for decision making in healthcare sector.The advances in computer vision and artificial intelligence(AI)techniques have resulted in the effective design of CAD models,which enables to detection of the existence of diseases using various imaging modalities.Oral cancer(OC)has commonly occurred in head and neck globally.Earlier identification of OC enables to improve survival rate and reduce mortality rate.Therefore,the design of CAD model for OC detection and classification becomes essential.Therefore,this study introduces a novel Computer Aided Diagnosis for OC using Sailfish Optimization with Fusion based Classification(CADOC-SFOFC)model.The proposed CADOC-SFOFC model determines the existence of OC on the medical images.To accomplish this,a fusion based feature extraction process is carried out by the use of VGGNet-16 and Residual Network(ResNet)model.Besides,feature vectors are fused and passed into the extreme learning machine(ELM)model for classification process.Moreover,SFO algorithm is utilized for effective parameter selection of the ELM model,consequently resulting in enhanced performance.The experimental analysis of the CADOC-SFOFC model was tested on Kaggle dataset and the results reported the betterment of the CADOC-SFOFC model over the compared methods with maximum accuracy of 98.11%.Therefore,the CADOC-SFOFC model has maximum potential as an inexpensive and non-invasive tool which supports screening process and enhances the detection efficiency.展开更多
This research was to investigate the intervention effect of art-making on the anxiety symptoms of college students. A sample of 400college students took part in this research. They were assigned to the experiment grou...This research was to investigate the intervention effect of art-making on the anxiety symptoms of college students. A sample of 400college students took part in this research. They were assigned to the experiment group (n = 200) and the control group (n = 200)according to Self-Rating Anxiety Scale (SAS) scores. Unlike the control group, the experiment group received a standard artmaking program under the supervision of trained instructors for a period of twelve sessions two times weekly which wascontinued for six weeks. Self-Rating Anxiety Seale (SAS) and Hamilton Anxiety Scale (HAMA) were used to assess anxietysymptoms level. Significant decreases in anxiety symptoms (p < 0.05) were found in the experiment group compared with thecontrol group. Using the art-making program to relieve anxiety, the shortest intervention period is three weeks. Art-makingcan effectively alleviate college students’ anxiety, and also can effectively improve the physical health, mental health, and socialhealth levels of college students.展开更多
基金This research was supported by the National Natural Science Foundation of China(81673239)the National Science Fund for Distinguished Young Scholars(No.81325017)+1 种基金Chang Jiang Scholars Program(No.T2014089)the Fourth Round of Three-Year Public Health Action Plan of Shanghai,China(15GWZK0202,15GWZK0101).
文摘Background:Schistosomiasis is a water-borne disease caused by trematode worms belonging to genus Schistosoma,which is prevalent most of the developing world.Transmission of the disease is usually associated with multiple biological characteristics and social factors but also factors can play a role.Few studies have assessed the exact and interactive influence of each factor promoting schistosomiasis transmission.Methods:We used a series of different detectors(i.e.,specific detector,risk detector,ecological detector and interaction detector)to evaluate separate and interactive effects of the environmental factors on schistosomiasis prevalence.Specifically,(i)specific detector quantifies the impact of a risk factor on an observed spatial disease pattern,which were ranked statistically by a value of Power of Determinate(PD)calculation;(ii)risk detector detects high risk areas of a disease on the condition that the study area is stratified by a potential risk factor;(iii)ecological detector explores whether a risk factor is more significant than another in controlling the spatial pattern of a disease;(iv)interaction detector probes whether two risk factors when taken together weaken or enhance one another,or whether they are independent in developing a disease.Infection data of schistosomiasis based on conventional surveys were obtained at the county level from the health authorities in Anhui Province,China and used in combination with information from Chinese weather stations and internationally available environmental data.Results:The specific detector identified various factors of potential importance as follows:Proximity to Yangtze River(0.322)>Land cover(0.285)>sunshine hours(0.256)>population density(0.109)>altitude(0.090)>the normalized different vegetation index(NDVI)(0.077)>land surface temperature at daytime(LST_(day))(0.007).The risk detector indicated that areas of schistosomiasis high risk were located within a buffer distance of 50 km from Yangtze River.The ecological detector disclosed that the factors
基金Project supported by the National Natural Science Foundation of China (No. 51078325)the State Key Lab of Subtropical Building Science,South China University of Technology,China
文摘From the case study of Evening Bell Ringing at Nanping Hill,one of the West Lake Cultural Landscapes in Hangzhou,China,we investigated the soundscape of a scenic area with a profound cultural background.First,we conducted the soundscape physical index of the area in both winter and spring seasons to analyze its objective graphical expression.Second,we focused on people's reactions to the soundscape in order to obtain a subjective evaluation of each component in the soundscape and integrated environment.Then,the relationship between the objective data and the subjective evaluation was analyzed.Finally,the impacts of the natural environment,history,and cultural factors on the evaluation of the Jingci Temple soundscape were studied.It was found that natural sounds,cultural sounds,and historic sounds were widely acclaimed in people's subjective feelings,which indicated the close relationships among historical and cultural background,soundscape,and natural environment.Thus,the conclusion was made that soundscape should be consistent with the local natural environment and the historical and cultural background.
文摘Objective To compare the cognitive effects of guqin （the oldest Chinese instrument） music and piano music. Methods Behavioral and event-related potential （ERP） data in a standard two-stimulus auditory oddball task were recorded and analyzed. Results This study replicated the previous results of culture-familiar music effect on Chinese subjects： the greater P300 amplitude in frontal areas in a culture-familiar music environment. At the same time, the difference between guqin music and piano music was observed in NI and later positive complex （LPC： including P300 and P500）： a relatively higher participation of right anterior-temporal areas in Chinese subjects. Conclusion The results suggest that the special features of ERP responses to guqin music are the outcome of Chinese tonal language environments given the similarity between Guqin＇s tones and Mandarin lexical tones.
基金support by U.S.Environmental Protection AgencyOhio Department of Transportation
文摘In order to understand how the uncertainties in the output can be apportioned to different sources of uncertainties in its inputs, it is critical to investigate the sensitivity of MOVES model. The MOVES model sensitivity for regional level has been well studied. However, the uncertainty analysis for project level running emissions has not been well understood. In this research, the MOVES model project level sensitivity tests on running emissions were conducted thru the analysis of vehicle specific power （VSP）, scaled tractive power （STP）, and MOVES emission rates versus speed curves. This study tested the speed, acceleration, and grade-three most critical variables for vehicle specific power for light duty vehicles and scaled tractive power for heavy duty vehicles. For the testing of STP, four regulatory classes of heavy duty vehicles including light heavy duty （LHD）, medium heavy duty （MHD）, heavy heavy duty （HHD） and bus were selected. MOVES project running emission rates were also tested for CO, PM2.5, NOx, and VOC versus the operating speeds. A Latin Hypercube （LH） sampling based on method for estimation of the ＂Sobal＂ sensitivity indices shows that the speed is the most critical variable among the three inputs for both VSP and STP. Acceleration and grades show lower response to the main effects and sensitivity indices. MOVES emission rates versus speeds curves for light duty vehicles show that highest emission occurs at lower speed range. No significant differences on emission rates among the regulatory classes of heavy duty vehicles are identified.
基金Project supported by the Natural Science Foundation of Shaanxi Province (No. 2001H12).
文摘The components of the rock, the pigments, the gold foils and the adhesive of One Thousand Hand Buddha in Dazu stone sculptures, Chongqing, China, have been analyzed by X-ray diffraction (XRD), X-ray fluorescence (XRF), infrared spectroscopy (IR), energy dispersive X-ray analysis (EDX) and fiber optics reflectance spectros-copy (FORS). Furthermore, the weathering and degeneration of One Thousand Hand Buddha have been discussed and the protective methods have been provided. In this work some useful information to study on conservation of stone relics is given.
文摘Objective:This study protocol identifies the basic research route and framework of psychological and behavioral surveys among Chinese residents,aims establishing a database through a multicenter,large-sample cross-sectional survey in China to provide strong data support for research development in various fields and a more comprehensive and systematic understanding of the physical and mental health status of the public.Method:The study was conducted from June 20,2022 to August 31,2022,using stratified sampling and quota sampling methods,a total of 148 cities,202 districts and counties,390 townships/towns/sub-districts,and 780 communities/villages(excluding Hong Kong,Macao,and Taiwan)from 23 provinces,5 autonomous regions,and 4 municipalities directly under the central government in China were selected.The questionnaire was distributed one-on-one and face-to-face to the public by trained investigators,and the questionnaire included eight aspects:personal basic information,personal health status,family basic information,social environment in which they were located,psychological level scale,behavioral level scale,other scales,and attitude towards social hot issues.Data analysis will be performed after questionnaire return.Results:Data collection is ongoing.These findings will support physical and mental health research and strategy development in China and even globally,guiding policy-makers and health care organizations to reform their programs to ensure the best interests of residents and their families.
文摘The realization of an interoperable and scalable virtual platform, currently known as the “metaverse,” is inevitable, but many technological challenges need to be overcome first. With the metaverse still in a nascent phase, research currently indicates that building a new 3D social environment capable of interoperable avatars and digital transactions will represent most of the initial investment in time and capital. The return on investment, however, is worth the financial risk for firms like Meta, Google, and Apple. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the creation of an entire alternate virtual universe of 3D avatars, objects, and otherworldly cityscapes calls for a new development pipeline and workflow. Existing 3D modeling and digital twin processes, already well-established in industry and gaming, will be ported to support the need to architect and furnish this new digital world. The current development pipeline, however, is cumbersome, expensive and limited in output capacity. This paper proposes a new and innovative immersive development pipeline leveraging the recent advances in artificial intelligence (AI) for 3D model creation and optimization. The previous reliance on 3D modeling software to create assets and then import into a game engine can be replaced with nearly instantaneous content creation with AI. While AI art generators like DALL-E 2 and DeepAI have been used for 2D asset creation, when combined with game engine technology, such as Unreal Engine 5 and virtualized geometry systems like Nanite, a new process for creating nearly unlimited content for immersive reality is possible. New processes and workflows, such as those proposed here, will revolutionize content creation and pave the way for Web 3.0, the metaverse and a truly 3D social environment.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05050200)the National Key Basic Research and Development Program of China (2011CB403201)+3 种基金the Committee of Agriculture,Shanghai Municipal Government,China (2010-6-1)the National Key Technology R&D Program of China (2010BAK69B18)the Science and Technology Commission of Shanghai Municipality (10JC1407000)the 2010 Shanghai Jiao Tong University Polytechnic Cross-Fund
文摘Urban forest has undergone rapid development in China over the last three decades because of the acceleration of urbanization.Urban forest thus plays an increasingly important role in carbon sequestration at a regional and national scale.As one of the most urbanized cities in China,Shanghai showed an increase of forest coverage from 3% in the 1990s to 13% in 2009.Based on CITY-green model and the second soil survey of Shanghai,the forest biomass carbon(FBC) was estimated to be 0.48 Tg in the urban area and,forest soil organic carbon(SOC)(0-100 cm soil depth) is 2.48 Tg in the urban and suburban areas,respectively.These values are relatively within the median and lower level compared with other Chinese megacities,with the FBC of 0.02 Tg in Harbin to 47.29 Tg in Chongqing and the forest SOC of 1.74 Tg in Nanjing to 418.67 Tg in Chongqing.For the different land-use types in Shanghai,the SOC density ranges from 13.8(tidal field) to 38.6 t ha-1(agricultural land).On average,the forest SOC density(31.5 t ha-1) in Shanghai is lower than that in agricultural lands(38.6 t ha-1) and higher than that in lawns(26.5 t ha-1) and gardens(21.3 t ha-1).In Shanghai,the SOC density in newly established urban parks is generally lower than that in older parks.In the northern and southeastern suburban areas(e.g.,Baoshan,Yangpu,and Nanhui districts),greenspace SOC density is higher than that in the central commercial areas(Hongkou,Putuo,Changning,and Zhabei districts) and in newly developed district(Pudong District).Uncertainties still exist in the estimation of urban forest carbon in Shanghai,as well as in other Chinese cities.Thus,future research directions are also discussed in this paper.
基金supported by the Guangdong Province Youth Innovative Talents Project in Higher Education (No.2018KQNCX257)the Guangdong Province Enterprise Science and Technology Commissioner Project (No.GDKTP2021048000)+4 种基金the Key-Area Research and Development Program of Guangdong Province (No.2020B090923002)the Guangdong-Dongguan Joint Fund (No.2019B151530005)the Guangdong Basic and Applied Basic Research Foundation (No.2019A1515110497)the National Natural Science Foundation of China (No.41907292)the National Natural Science Foundation of China (No.21876130)。
文摘Here,we report the production of 3D-printed MoS_(2)/Ni electrodes(3D-MoS_(2)/Ni)with longterm stability and excellent performance by the selective laser melting(SLM)technique.As a cathode,the obtained 3D-MoS_(2)/Ni could maintain a degradation rate above 94.0%for forfenicol(FLO)when repeatedly used 50 times in water.We also found that the removal rate of FLO by 3D-MoS_(2)/Ni was about 12 times higher than that of 3D-printed pure Ni(3D-Ni),attributed to the improved accessibility of H^(*).In addition,the electrochemical characterization results showed that the electrochemically active surface area of the 3D-MoS_(2)/Ni electrode is about 3-fold higher than that of the 3D-Ni electrode while the electrical resistance is 4 times lower.Based on tert-butanol suppression,electron paramagnetic resonance and triple quadrupole mass spectrometer experiments,a“dual path”mechanism and possible degradation pathway for the dechlorination of FLO by 3D-MoS_(2)/Ni were proposed.Furthermore,we also investigated the impacts of the cathode potential and the initial pH of the solution on the degradation of FLO.Overall,this study reveals that the SLM 3D printing technique is a promising approach for the rapid fabrication of high-stability metal electrodes,which could have broad application in the control of water contaminants in the environmental field.
基金supported by the Natural Science Foundation of Beijing Municipality(5232006)the Beijing Academy of Agriculture and Forestry Sciences Special Project on Hi-Tech Innovation Capacity(QNJJ202217 and KJCX20230305).
文摘Drought can greatly impact the biodiversity of an ecosystem and play a crucial role in regulating its functioning.However,the specific mechanisms by which drought mediate the biodiversity effect(BE)on community biomass in above-and belowground through functional traits remain poorly understood.Here,we conducted a common garden experiment in a greenhouse,which included two plant species richness levels and two water addition levels,to analyze the effects of biodiversity on aboveground biomass(AGB),belowground biomass(BGB)and total biomass(TB),and to quantify the relationship between BEs and functional traits under drought conditions.Our analysis focused on partitioning BEs into above-and belowground complementarity effect(CE)and selection effect(SE)at the species level,which allowed us to better understand the impacts of biodiversity on community biomass and the underlying mechanisms.Our results showed that plant species richness stimulated AGB,BGB and TB through CEs.Drought decreased AGB,BGB and TB,simultaneously.In addition,the aboveground CE was positively associated with the variation in plant height.SEs in above-and belowground were negatively correlated with the community mean plant height and root length,respectively.Furthermore,drought weakened the aboveground CE by decreasing variation in plant height,resulting in a reduction in AGB and TB.Our findings demonstrate that the complementarity of species is an important regulator of community biomass in above-and belowground,the dynamics of biomass under environmental stress are associated with the response of sensitive compartments.
基金funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Research Groups Program Grant No.(RGP-1443-0051).
文摘Owing to the rapid increase in the interchange of text information through internet networks,the reliability and security of digital content are becoming a major research problem.Tampering detection,Content authentication,and integrity verification of digital content interchanged through the Internet were utilized to solve a major concern in information and communication technologies.The authors’difficulties were tampering detection,authentication,and integrity verification of the digital contents.This study develops an Automated Data Mining based Digital Text Document Watermarking for Tampering Attack Detection(ADMDTW-TAD)via the Internet.The DM concept is exploited in the presented ADMDTW-TAD technique to identify the document’s appropriate characteristics to embed larger watermark information.The presented secure watermarking scheme intends to transmit digital text documents over the Internet securely.Once the watermark is embedded with no damage to the original document,it is then shared with the destination.The watermark extraction process is performed to get the original document securely.The experimental validation of the ADMDTW-TAD technique is carried out under varying levels of attack volumes,and the outcomes were inspected in terms of different measures.The simulation values indicated that the ADMDTW-TAD technique improved performance over other models.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under grant number(158/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R77)+1 种基金Princess Nourah bint Abdulrahman University,Riyadh,Saudi ArabiaThe authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR52).
文摘The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.
基金the Deanship of Scientific Research at King Khalid University for funding this work through Large Groups Project under Grant Number(71/43)Princess Nourah Bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R203)Princess Nourah Bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR29).
文摘With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has enhanced.This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare.Biomedical Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in nature.Due to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients.In such scenario computer-assisted automated diagnostic tools are important for classification of ECG signals.The current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)approach.To accomplish this,the proposed IBADL-BECGC model initially pre-processes the input signals.Besides,IBADL-BECGC model applies NasNet model to derive the features from test ECG signals.In addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet approach.Finally,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification method.The presented IBADL-BECGC model was experimentally validated utilizing benchmark dataset.The comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.
基金support from the Government of the Republic of Uganda through Makerere University Research and Innovations Fund(RIF1/CEDAT/015).
文摘There is an increased global demand for activated carbon(AC)in application of water treatment and purification.Water pollutants that have exhibited a greater removal efficiency by AC included but not limited to heavy metals,pharmaceuticals,pesticides,natural organic matter,disinfection by-products,and microplastics.Granular activated carbon(GAC)is mostly used in aqueous so-lutions and adsorption columns for water treatment.Commercial AC is not only costly,but also obtained from non-renewable sources.This has prompted the search for alternative renewable materials for AC production.Biomass wastes present a great potential of such materials because of their availability and carbonaceous nature.This in turn can reduce on the adverse environmental effects caused by poor disposal of these wastes.The challenges associated with biomass waste based GAC are their low strength and attrition resistance which make them easily disintegrate under aqueous phase.This paper provides a comprehensive review on recent advances in production of biomass waste based GAC for water treatment and highlights future research directions.Production parameters such as granulation conditions,use of binders,carbonization,activation methods,and their effect on textural properties are discussed.Factors influencing the adsorption capacities of the derived GACs,adsorption models,adsorption mechanisms,and their regeneration potentials are reviewed.The literature reveals that biomass waste materials can produce GAC for use in water treatment with possibilities of being regenerated.Nonetheless,there is a need to explore 1)the effect of preparation pathways on the adsorptive properties of biomass derived GAC,2)sustainable production of biomass derived GAC based on life cycle assessment and techno-economic analysis,and 3)adsorption mechanisms of GAC for removal of contaminants of emerging concerns such as microplastics and unregulated disinfection by-products.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under Grant Number(RGP 2/158/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2022R114),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Presently,smart cities play a vital role to enhance the quality of living among human beings in several ways such as online shopping,e-learning,ehealthcare,etc.Despite the benefits of advanced technologies,issues are also existed from the transformation of the physical word into digital word,particularly in online social networks(OSN).Cyberbullying(CB)is a major problem in OSN which needs to be addressed by the use of automated natural language processing(NLP)and machine learning(ML)approaches.This article devises a novel search and rescue optimization with machine learning enabled cybersecurity model for online social networks,named SRO-MLCOSN model.The presented SRO-MLCOSN model focuses on the identification of CB that occurred in social networking sites.The SRO-MLCOSN model initially employs Glove technique for word embedding process.Besides,a multiclass-weighted kernel extreme learning machine(M-WKELM)model is utilized for effectual identification and categorization of CB.Finally,Search and Rescue Optimization(SRO)algorithm is exploited to fine tune the parameters involved in the M-WKELM model.The experimental validation of the SRO-MLCOSN model on the benchmark dataset reported significant outcomes over the other approaches with precision,recall,and F1-score of 96.24%,98.71%,and 97.46%respectively.
文摘This study aimed to understand disruptive thinking and how its ideas can change the food industry. This was achieved by identifying, studying, and understanding the impacts, current trends, and different disruptive ideas and innovations emerging in the food industry. The study was conducted through interpretive research philosophy by carrying out secondary data collection processes, where both qualitative and quantitative information was presented. Deductive approaches were also selected to apply existing theories and models, which were used to construct research hypotheses and present detailed findings. The study finds that, with disruptive thinking, enhancements in the product life cycle, new flavors, and improvements in food packaging have been possible. The supply chain, which is always considered a complex part of the food industry, has been streamlined, offering greater transparency and real-time tracking and improving quality control across distribution systems.
基金funding from the Fujian Provincial Natural Science Foundation(Grant No.2022J01613)the Tsinghua University Initiative Scientific Research Program(Grant No.20223080018)the National Natural Science Foundation of China(Grants No.51978365,72241410).
文摘It is essential to better integrate wilderness representations of different stakeholders into wilderness conservation.The way in which local residents and other stakeholders frame the construction of wilderness of protected areas in developing countries are poorly understood.In these areas,land use policy and decision may lead to conflicts.This study aims to explore existing public wilderness representations using a questionnaire survey(n=514)administered amongst tourists and other stakeholders in the Wuyishan National Park,in southeast China.The spatial differences in public representations of wilderness across different stakeholder groups were compared against expert knowledge.We found that integrated wilderness representation maps of different stakeholder groups were consistent,namely'area where wild animals live','area with no human influence','a barren and lonely area'.However,three sub-representations of the individual stakeholders varied significantly.Moreover,expert-based wilderness mapping did not reflect public representations accurately,and an integrated wilder-ness quality map considering wilderness representations across both stakeholders and experts can better identify detailed wilderness areas.Our study provides new insights and technical support for future exploration of wilder-ness conservation and mapping in China and other countries with insufficient awareness of wilderness values and investigations in a regional scale.
文摘Background： This study was to establish a disease differentiation model for ST-segment elevation myocardial infarction （STEMI） youth patients experiencing ischemia and reperfusion via ultra-performance liquid chromatography and mass spectrometry （UPLC/MS） platform, which searches for closely related characteristic metabolites and metabolic pathways to evaluate their predictive value in the prognosis after discharge. Methods： Forty-seven consecutive STEMI patients （23 patients under 45 years of age, referred to here as ＂youth,＂ and 24 elderly patients） and 48 healthy control group members （24 youth, 24 elderly） were registered prospectively. The youth patients were required to provide a second blood draw during a follow-up visit one year after morbidity （n - 22, one lost）. Characteristic metabolites and relative metabolic pathways were screened via UPLC/MS platform base on the Kyoto encyclopedia of genes and genomes （KEGG） and Human Metabolome Database. Receiver operating characteristic （ROC） curves were drawn to evaluate the predictive value of characteristic metabolites in the prognosis after discharge. Results： We successfully established an orthogonal partial least squares discriminated analysis model （R2X = 71.2%, R2Y = 79.6%, and Q2 55.9%） and screened out 24 ions; the sphingolipid metabolism pathway showed the most drastic change. The ROC curve analysis showed that ceramide [Cer（dl 8：0/16：0）, Cer（t 18：0/12：0）] and sphinganine in the sphingolipid pathway have high sensitivity and specificity on the prognosis related to major adverse cardiovascular events after youth patients were discharged. The area under curve （AUC） was 0.67 1, 0.750, and 0.711, respectively. A follow-up validation one year after morbidity showed corresponding AUC of 0.778, 0.833, and 0.806. Conclusions： By analyzing the plasma metabolism of myocardial infarction patients, we successfully established a model that can distinguish two different factors simultaneously： patholog
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under grant number(RGP 2/142/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R151)+1 种基金Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:22UQU4310373DSR13This research project was supported by a grant from the Research Center of the Female Scientific and Medical Colleges,Deanship of Scientific Research,King Saud University.
文摘Recently,computer aided diagnosis(CAD)model becomes an effective tool for decision making in healthcare sector.The advances in computer vision and artificial intelligence(AI)techniques have resulted in the effective design of CAD models,which enables to detection of the existence of diseases using various imaging modalities.Oral cancer(OC)has commonly occurred in head and neck globally.Earlier identification of OC enables to improve survival rate and reduce mortality rate.Therefore,the design of CAD model for OC detection and classification becomes essential.Therefore,this study introduces a novel Computer Aided Diagnosis for OC using Sailfish Optimization with Fusion based Classification(CADOC-SFOFC)model.The proposed CADOC-SFOFC model determines the existence of OC on the medical images.To accomplish this,a fusion based feature extraction process is carried out by the use of VGGNet-16 and Residual Network(ResNet)model.Besides,feature vectors are fused and passed into the extreme learning machine(ELM)model for classification process.Moreover,SFO algorithm is utilized for effective parameter selection of the ELM model,consequently resulting in enhanced performance.The experimental analysis of the CADOC-SFOFC model was tested on Kaggle dataset and the results reported the betterment of the CADOC-SFOFC model over the compared methods with maximum accuracy of 98.11%.Therefore,the CADOC-SFOFC model has maximum potential as an inexpensive and non-invasive tool which supports screening process and enhances the detection efficiency.
基金supported by 2023 Jiangsu Province University Philosophy and Social Science Research General Project:Research on the Comprehensive Management Model of One-Stop Student Community in Universities(Grant No.2023SJSZ0084)2023 Research Topic on Party Building and Ideological and Political Education of Nanjing Tech University Category II Funding Topic:Building a Practice Education System in Universities based on Red Cultural Resources(Grant No.SZ20230220)2023 Research Topic on Party Building and Ideological and Political Education of Nanjing Tech University Category III Funding Topic:Research on Comprehensive Management Mode of One-Stop Student Community in Universities(Grant No.SZ20230316).
文摘This research was to investigate the intervention effect of art-making on the anxiety symptoms of college students. A sample of 400college students took part in this research. They were assigned to the experiment group (n = 200) and the control group (n = 200)according to Self-Rating Anxiety Scale (SAS) scores. Unlike the control group, the experiment group received a standard artmaking program under the supervision of trained instructors for a period of twelve sessions two times weekly which wascontinued for six weeks. Self-Rating Anxiety Seale (SAS) and Hamilton Anxiety Scale (HAMA) were used to assess anxietysymptoms level. Significant decreases in anxiety symptoms (p < 0.05) were found in the experiment group compared with thecontrol group. Using the art-making program to relieve anxiety, the shortest intervention period is three weeks. Art-makingcan effectively alleviate college students’ anxiety, and also can effectively improve the physical health, mental health, and socialhealth levels of college students.
