1.Background The United Nations(UN)2030 Agenda for Sustainable Development,adopted in 2015,established the Sustainable Development Goals(SDGs)as a comprehensive framework to address global challenges through interconn...1.Background The United Nations(UN)2030 Agenda for Sustainable Development,adopted in 2015,established the Sustainable Development Goals(SDGs)as a comprehensive framework to address global challenges through interconnected social,economic,and environmental targets.展开更多
With the proliferation of Internet of Things(IoT)devices,securing these interconnected systems against cyberattacks has become a critical challenge.Traditional security paradigms often fail to cope with the scale and ...With the proliferation of Internet of Things(IoT)devices,securing these interconnected systems against cyberattacks has become a critical challenge.Traditional security paradigms often fail to cope with the scale and diversity of IoT network traffic.This paper presents a comparative benchmark of classic machine learning(ML)and state-of-the-art deep learning(DL)algorithms for IoT intrusion detection.Our methodology employs a twophased approach:a preliminary pilot study using a custom-generated dataset to establish baselines,followed by a comprehensive evaluation on the large-scale CICIoTDataset2023.We benchmarked algorithms including Random Forest,XGBoost,CNN,and StackedLSTM.The results indicate that while top-performingmodels frombothcategories achieve over 99%classification accuracy,this metric masks a crucial performance trade-off.We demonstrate that treebased ML ensembles exhibit superior precision(91%)in identifying benign traffic,making them effective at reducing false positives.Conversely,DL models demonstrate superior recall(96%),making them better suited for minimizing the interruption of legitimate traffic.We conclude that the selection of an optimal model is not merely a matter of maximizing accuracy but is a strategic choice dependent on the specific security priority either minimizing false alarms or ensuring service availability.Thiswork provides a practical framework for deploying context-aware security solutions in diverse IoT environments.展开更多
Dry fig is a traditional healthy snack and has important economic value in a number of Mediterranean and Middle Eastern countries.Cultivars with no anthocyanin accumulation in the fruit peel are preferred for dry fig ...Dry fig is a traditional healthy snack and has important economic value in a number of Mediterranean and Middle Eastern countries.Cultivars with no anthocyanin accumulation in the fruit peel are preferred for dry fig production.R2R3-MYB transcription factors have promotive or repressive regulatory roles in plant anthocyanin biosynthesis.In this study,113 R2R3-MYB genes were identified in Ficus carica,3 of which were assigned to the S4 subfamily of flavonoid-biosynthesis repressors.FcMYB57 was further recruited as a candidate anthocyaninbiosynthesis repressor based on its sequence features and expression,which was significantly negatively correlated with that of anthocyanin-biosynthesis structural genes.Transient overexpression of FcMYB57 in strawberry totally inhibited fruit pigmentation and significantly increased fruit firmness.The metabolomic analysis confirmed a significant reduction in the contents of cyanidin-3-O-glucoside and pelargonidin-3-O-glucoside,as well as other flavonoids,and transmission electron microscopy revealed an increment in cell-wall thickness.Transcriptome analysis showed downregulation of anthocyanin-biosynthesis structural genes and upregulation of genes related to xylan synthesis.Yeast one-hybrid and dual luciferase assays demonstrated a negative regulatory effect of FcMYB57 on the promoter of FcUFGT3(UDP glucose-flavonoid 3-O-glcosyl-transferase).Yeast two-hybrid assay showed that FcMYB57 does not interact with FcbHLH42,3,14,MYC2,or FcTTG1,all of which have a previously identified or predicted role in flavonoid biosynthesis,however,interaction was detected with FcTPL(Topless),suggesting that FcMYB57 serves as an active repressor of anthocyanin biosynthesis.This is the first identification of an anthocyaninbiosynthesis repressor in fig,with a possible role in fig fruit quality.展开更多
Climate change is impacting forests in Central Europe,causing increased mortality and degradation of forest ecosystem services(FES).As global warming intensifies,these effects are likely to worsen,particularly through...Climate change is impacting forests in Central Europe,causing increased mortality and degradation of forest ecosystem services(FES).As global warming intensifies,these effects are likely to worsen,particularly through more severe droughts and increased biotic disturbances.Understanding how forests respond to different levels of warming is essential for adaptation planning.Therefore,this study analyzed changes in forest structure and FES,including timber production,climate change mitigation,recreation,and structural diversity,under three global warming scenarios.Using the LandClim model,we compared warming levels of 1.5,2,and 3℃above preindustrial temperatures,based on 30-year periods from RCP data,to historical climate.Our research focused on Freiburg's forests in southwestern Germany,characterized by diverse tree species and an elevation range of 200–1,250 m a.s.l.A warming of 1.5℃could temporarily increase productivity,but at 2℃,biomass losses of up to 10%would occur below elevations of 450 m due to drought mortality.Under 3℃,losses would intensify below 650 m up to 40%,with even drought-resistant species like pedunculate oak experiencing mortality.At higher elevations,bark beetle outbreaks caused mortality of Norway spruce,while European beech capitalized on the changing ecological conditions.Higher warming levels significantly deteriorated FES,particularly timber production,climate change mitigation,and structural diversity,while recreation was less affected.These findings emphasize the urgency of meeting Paris Agreement targets,as limiting warming below 2℃can reduce severe impacts.If warming exceeds this critical threshold,even species presently considered drought-resistant,such as native sessile and pedunculate oaks and non-native red oak,could face serious threats at lower elevations.This would undermine the effectiveness of current management strategies,as these tree species are key to providing multiple FES.展开更多
Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyz...Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers infl...Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest.However,studying shortterm drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth,i.e.,heterogeneous growth around the stem.In this study,we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology,short-term growth rates,and growth eccentricity.To this end,we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions.Our results show that eccentricity generated high temporal autocorrelation between successive samples,and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability.We observed consistent short-term patterns in the model residuals,suggesting the influence of an unaccounted-for environmental variable on cell production.The proposed models offer several advantages over traditional methods,including robust confidence intervals around predictions,consistency with phenology,and reduced sensitivity to extreme observations at the end of the growing season,often linked to eccentric growth.These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.展开更多
Titanium exhibits outstanding properties,particularly,high specific strength and resistance to both high and low temperatures,earning it a reputation as the metal of the future.However,because of the highly reactive n...Titanium exhibits outstanding properties,particularly,high specific strength and resistance to both high and low temperatures,earning it a reputation as the metal of the future.However,because of the highly reactive nature of titanium,metallic titanium production involves extensive procedures and high costs.Considering its advantages and limitations,the European Union has classified titanium metal as a critical raw material(CRM)of low category.The Kroll process is predominantly used to produce titanium;however,molten salt electrolysis(MSE)is currently being explored for producing metallic titanium at a low cost.Since 2000,electrolytic titanium production has undergone a wave of technological advancements.However,because of the intermediate and disproportionation reactions in the electrolytic titanium production process,the process efficiency and titanium purity according to industrial standards could not be achieved.Consequently,metallic titanium production has gradually diversified into employing technologies such as thermal reduction,MSE,and titanium alloy preparation.This study provides a comprehensive review of research advances in titanium metal preparation technologies over the past two decades,highlighting the challenges faced by the existing methods and proposing potential solutions.It offers useful insights into the development of low-cost titanium preparation technologies.展开更多
When micro/nano-scale gradient coatings are subject to large thermal gradients or high heat fluxes,the spatial size effect cannot be ignored.It is important to understand how the size effect influences the thermal fra...When micro/nano-scale gradient coatings are subject to large thermal gradients or high heat fluxes,the spatial size effect cannot be ignored.It is important to understand how the size effect influences the thermal fracture behavior of functionally graded coating/substrate structures.This study aims at analyzing the transient thermal fracture behavior of collinear interface cracks in functionally graded coating/substrate structures based on the nonlocal dual-phase-lag heat conduction model.By means of integral transform techniques,the mixed boundary problem is transformed into a set of singular integral equations,which are solved by the Chebyshev polynomials.The effects of the nonlocal parameter,coating thickness,crack spacing,and non-homogeneous parameters on the temperature and stress intensity factors(SIFs)are examined.The numerical results show that these parameters play an essential role in controlling the thermal fracture behavior of the structures,especially at micro/nano-scales.展开更多
Objective:To analyze factors affecting the utilization of human immunodeficiency virus counseling and testing(HCT)service among human immunodeficiency virus risk groups at Hessa Air Genting Health Center,Asahan Regenc...Objective:To analyze factors affecting the utilization of human immunodeficiency virus counseling and testing(HCT)service among human immunodeficiency virus risk groups at Hessa Air Genting Health Center,Asahan Regency,North Sumatera,Indonesia.Methods:This quantitative unmatched case-control study was conducted from April 2024 to April 2025 at Hessa Air Genting Health Center,Asahan Regency,North Sumatra Province,Indonesia.Female sex workers and men who have sex with men were selected using purposive sampling based on predefined inclusion and exclusion criteria.Data were collected via questionnaires and analyzed using SPSS version 18.0,with univariate analysis,bivariate analysis(Chi-square test),and multivariate analysis(logistic regression analysis).Results:Comprehensive analysis of 75 cases and 75 controls was conducted to identify factors affecting the utilization of HCT services.Specifically,this study identified significant effects of knowledge(OR 3.2,95%CI 1.5-7.0,P=0.003),perception(OR 5.6,95%CI 2.5-12.5,P<0.001),information media(OR 3.1,95%CI 1.4-6.8,P=0.005),and health workers encouragement(OR 4.0,95%CI 1.5-10.4,P=0.005).In contrast,access to health services did not have a significant effect.Conclusions:Knowledge,perception,information media,and health worker encouragement had significant effects on HCT service utilization,with perception identified as the dominant factor.To improve utilization,strengthening positive perceptions,targeted training for healthcare workers,strengthened partnerships with local non-governmental organizations,and the use of social media for health promotion are recommended.展开更多
Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-through...Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-throughput sequencing technology have become prominent in biomedical research,and they reveal molecular aspects of cancer diagnosis and therapy.Despite the development of advanced sequencing technology,the presence of high-dimensionality in multi-omics data makes it challenging to interpret the data.Methods:In this study,we introduce RankXLAN,an explainable ensemble-based multi-omics framework that integrates feature selection(FS),ensemble learning,bioinformatics,and in-silico validation for robust biomarker detection,potential therapeutic drug-repurposing candidates’identification,and classification of SC.To enhance the interpretability of the model,we incorporated explainable artificial intelligence(SHapley Additive exPlanations analysis),as well as accuracy,precision,F1-score,recall,cross-validation,specificity,likelihood ratio(LR)+,LR−,and Youden index results.Results:The experimental results showed that the top four FS algorithms achieved improved results when applied to the ensemble learning classification model.The proposed ensemble model produced an area under the curve(AUC)score of 0.994 for gene expression,0.97 for methylation,and 0.96 for miRNA expression data.Through the integration of bioinformatics and ML approach of the transcriptomic and epigenomic multi-omics dataset,we identified potential marker genes,namely,UBE2D2,HPCAL4,IGHA1,DPT,and FN3K.In-silico molecular docking revealed a strong binding affinity between ANKRD13C and the FDA-approved drug Everolimus(binding affinity−10.1 kcal/mol),identifying ANKRD13C as a potential therapeutic drug-repurposing target for SC.Conclusion:The proposed framework RankXLAN outperforms other existing frameworks for serum biomarker identification,therapeutic target identification,and SC classification with multi-omics datasets.展开更多
文摘1.Background The United Nations(UN)2030 Agenda for Sustainable Development,adopted in 2015,established the Sustainable Development Goals(SDGs)as a comprehensive framework to address global challenges through interconnected social,economic,and environmental targets.
文摘With the proliferation of Internet of Things(IoT)devices,securing these interconnected systems against cyberattacks has become a critical challenge.Traditional security paradigms often fail to cope with the scale and diversity of IoT network traffic.This paper presents a comparative benchmark of classic machine learning(ML)and state-of-the-art deep learning(DL)algorithms for IoT intrusion detection.Our methodology employs a twophased approach:a preliminary pilot study using a custom-generated dataset to establish baselines,followed by a comprehensive evaluation on the large-scale CICIoTDataset2023.We benchmarked algorithms including Random Forest,XGBoost,CNN,and StackedLSTM.The results indicate that while top-performingmodels frombothcategories achieve over 99%classification accuracy,this metric masks a crucial performance trade-off.We demonstrate that treebased ML ensembles exhibit superior precision(91%)in identifying benign traffic,making them effective at reducing false positives.Conversely,DL models demonstrate superior recall(96%),making them better suited for minimizing the interruption of legitimate traffic.We conclude that the selection of an optimal model is not merely a matter of maximizing accuracy but is a strategic choice dependent on the specific security priority either minimizing false alarms or ensuring service availability.Thiswork provides a practical framework for deploying context-aware security solutions in diverse IoT environments.
基金supported by the key research project for fig development of Weiyuan County(Grant No.1002-69199007),China.
文摘Dry fig is a traditional healthy snack and has important economic value in a number of Mediterranean and Middle Eastern countries.Cultivars with no anthocyanin accumulation in the fruit peel are preferred for dry fig production.R2R3-MYB transcription factors have promotive or repressive regulatory roles in plant anthocyanin biosynthesis.In this study,113 R2R3-MYB genes were identified in Ficus carica,3 of which were assigned to the S4 subfamily of flavonoid-biosynthesis repressors.FcMYB57 was further recruited as a candidate anthocyaninbiosynthesis repressor based on its sequence features and expression,which was significantly negatively correlated with that of anthocyanin-biosynthesis structural genes.Transient overexpression of FcMYB57 in strawberry totally inhibited fruit pigmentation and significantly increased fruit firmness.The metabolomic analysis confirmed a significant reduction in the contents of cyanidin-3-O-glucoside and pelargonidin-3-O-glucoside,as well as other flavonoids,and transmission electron microscopy revealed an increment in cell-wall thickness.Transcriptome analysis showed downregulation of anthocyanin-biosynthesis structural genes and upregulation of genes related to xylan synthesis.Yeast one-hybrid and dual luciferase assays demonstrated a negative regulatory effect of FcMYB57 on the promoter of FcUFGT3(UDP glucose-flavonoid 3-O-glcosyl-transferase).Yeast two-hybrid assay showed that FcMYB57 does not interact with FcbHLH42,3,14,MYC2,or FcTTG1,all of which have a previously identified or predicted role in flavonoid biosynthesis,however,interaction was detected with FcTPL(Topless),suggesting that FcMYB57 serves as an active repressor of anthocyanin biosynthesis.This is the first identification of an anthocyaninbiosynthesis repressor in fig,with a possible role in fig fruit quality.
基金funded by the HORIZON EUROPE's project"eco2adapt"(Ecosystem-based Adaptation and Changemaking to Shape,Project,and Sustain the Resilience of Tomorrow's Forests,Grant no:101059498)。
文摘Climate change is impacting forests in Central Europe,causing increased mortality and degradation of forest ecosystem services(FES).As global warming intensifies,these effects are likely to worsen,particularly through more severe droughts and increased biotic disturbances.Understanding how forests respond to different levels of warming is essential for adaptation planning.Therefore,this study analyzed changes in forest structure and FES,including timber production,climate change mitigation,recreation,and structural diversity,under three global warming scenarios.Using the LandClim model,we compared warming levels of 1.5,2,and 3℃above preindustrial temperatures,based on 30-year periods from RCP data,to historical climate.Our research focused on Freiburg's forests in southwestern Germany,characterized by diverse tree species and an elevation range of 200–1,250 m a.s.l.A warming of 1.5℃could temporarily increase productivity,but at 2℃,biomass losses of up to 10%would occur below elevations of 450 m due to drought mortality.Under 3℃,losses would intensify below 650 m up to 40%,with even drought-resistant species like pedunculate oak experiencing mortality.At higher elevations,bark beetle outbreaks caused mortality of Norway spruce,while European beech capitalized on the changing ecological conditions.Higher warming levels significantly deteriorated FES,particularly timber production,climate change mitigation,and structural diversity,while recreation was less affected.These findings emphasize the urgency of meeting Paris Agreement targets,as limiting warming below 2℃can reduce severe impacts.If warming exceeds this critical threshold,even species presently considered drought-resistant,such as native sessile and pedunculate oaks and non-native red oak,could face serious threats at lower elevations.This would undermine the effectiveness of current management strategies,as these tree species are key to providing multiple FES.
文摘Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
基金supported by the Discovery Grants program of the Natural Sciences and Engineering Research Council of Canada(No.RGPIN-2021-03553)the Canadian Research Chair in dendroecology and dendroclimatology(CRC-2021-00368)+3 种基金the Ministère des Ressources Naturelles et des Forèts(MRNF,Contract no.142332177-D)the Natural Sciences and Engineering Research Council of Canada(Alliance Grant No.ALLRP 557148-20,obtained in partnership with the MRNF and Resolute Forest Products)the Fonds de recherche du Qu ebec–Nature et technologies(Partnership Research Program on the Contribution of the Forestry Sector to Climate Change MitigationGrant No.2022-0FC-309064)。
文摘Xylogenesis,the process through which wood cells are formed,results in the long-term storage of carbon in woody biomass,making it a key component of the global carbon cycle.Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest.However,studying shortterm drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth,i.e.,heterogeneous growth around the stem.In this study,we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology,short-term growth rates,and growth eccentricity.To this end,we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions.Our results show that eccentricity generated high temporal autocorrelation between successive samples,and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability.We observed consistent short-term patterns in the model residuals,suggesting the influence of an unaccounted-for environmental variable on cell production.The proposed models offer several advantages over traditional methods,including robust confidence intervals around predictions,consistency with phenology,and reduced sensitivity to extreme observations at the end of the growing season,often linked to eccentric growth.These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.
基金financial support from the Yunnan Province Key Industries Science and Technology Special Project for Colleges and UniversitiesChina(No.FWCY-QYCT2024006)+6 种基金National Natural Science Foundation of China(Nos.52104351 and 52364051)Science and Technology Major Project of Yunnan Province,China(No.202202AG050007)the Yunnan Fundamental Research ProjectsChina(No.202401AT070314)the Key Technology Research and Development Program of Shandong Province,China(No.2023CXGC010903)Central Guidance Local Scientific and Technological Development Funds,China(No.202407AB110022)Yunnan Province Xingdian Talent Support Plan Project,China。
文摘Titanium exhibits outstanding properties,particularly,high specific strength and resistance to both high and low temperatures,earning it a reputation as the metal of the future.However,because of the highly reactive nature of titanium,metallic titanium production involves extensive procedures and high costs.Considering its advantages and limitations,the European Union has classified titanium metal as a critical raw material(CRM)of low category.The Kroll process is predominantly used to produce titanium;however,molten salt electrolysis(MSE)is currently being explored for producing metallic titanium at a low cost.Since 2000,electrolytic titanium production has undergone a wave of technological advancements.However,because of the intermediate and disproportionation reactions in the electrolytic titanium production process,the process efficiency and titanium purity according to industrial standards could not be achieved.Consequently,metallic titanium production has gradually diversified into employing technologies such as thermal reduction,MSE,and titanium alloy preparation.This study provides a comprehensive review of research advances in titanium metal preparation technologies over the past two decades,highlighting the challenges faced by the existing methods and proposing potential solutions.It offers useful insights into the development of low-cost titanium preparation technologies.
基金Project supported by the Natural Science Foundation of Shandong Province of China(No.ZR2024MA085)the Fundamental Research Funds for Central Universities of China(No.27RA2515008)。
文摘When micro/nano-scale gradient coatings are subject to large thermal gradients or high heat fluxes,the spatial size effect cannot be ignored.It is important to understand how the size effect influences the thermal fracture behavior of functionally graded coating/substrate structures.This study aims at analyzing the transient thermal fracture behavior of collinear interface cracks in functionally graded coating/substrate structures based on the nonlocal dual-phase-lag heat conduction model.By means of integral transform techniques,the mixed boundary problem is transformed into a set of singular integral equations,which are solved by the Chebyshev polynomials.The effects of the nonlocal parameter,coating thickness,crack spacing,and non-homogeneous parameters on the temperature and stress intensity factors(SIFs)are examined.The numerical results show that these parameters play an essential role in controlling the thermal fracture behavior of the structures,especially at micro/nano-scales.
文摘Objective:To analyze factors affecting the utilization of human immunodeficiency virus counseling and testing(HCT)service among human immunodeficiency virus risk groups at Hessa Air Genting Health Center,Asahan Regency,North Sumatera,Indonesia.Methods:This quantitative unmatched case-control study was conducted from April 2024 to April 2025 at Hessa Air Genting Health Center,Asahan Regency,North Sumatra Province,Indonesia.Female sex workers and men who have sex with men were selected using purposive sampling based on predefined inclusion and exclusion criteria.Data were collected via questionnaires and analyzed using SPSS version 18.0,with univariate analysis,bivariate analysis(Chi-square test),and multivariate analysis(logistic regression analysis).Results:Comprehensive analysis of 75 cases and 75 controls was conducted to identify factors affecting the utilization of HCT services.Specifically,this study identified significant effects of knowledge(OR 3.2,95%CI 1.5-7.0,P=0.003),perception(OR 5.6,95%CI 2.5-12.5,P<0.001),information media(OR 3.1,95%CI 1.4-6.8,P=0.005),and health workers encouragement(OR 4.0,95%CI 1.5-10.4,P=0.005).In contrast,access to health services did not have a significant effect.Conclusions:Knowledge,perception,information media,and health worker encouragement had significant effects on HCT service utilization,with perception identified as the dominant factor.To improve utilization,strengthening positive perceptions,targeted training for healthcare workers,strengthened partnerships with local non-governmental organizations,and the use of social media for health promotion are recommended.
基金the Deanship of Research and Graduate Studies at King Khalid University,KSA,for funding this work through the Large Research Project under grant number RGP2/164/46.
文摘Background:Stomach cancer(SC)is one of the most lethal malignancies worldwide due to late-stage diagnosis and limited treatment.The transcriptomic,epigenomic,and proteomic,etc.,omics datasets generated by high-throughput sequencing technology have become prominent in biomedical research,and they reveal molecular aspects of cancer diagnosis and therapy.Despite the development of advanced sequencing technology,the presence of high-dimensionality in multi-omics data makes it challenging to interpret the data.Methods:In this study,we introduce RankXLAN,an explainable ensemble-based multi-omics framework that integrates feature selection(FS),ensemble learning,bioinformatics,and in-silico validation for robust biomarker detection,potential therapeutic drug-repurposing candidates’identification,and classification of SC.To enhance the interpretability of the model,we incorporated explainable artificial intelligence(SHapley Additive exPlanations analysis),as well as accuracy,precision,F1-score,recall,cross-validation,specificity,likelihood ratio(LR)+,LR−,and Youden index results.Results:The experimental results showed that the top four FS algorithms achieved improved results when applied to the ensemble learning classification model.The proposed ensemble model produced an area under the curve(AUC)score of 0.994 for gene expression,0.97 for methylation,and 0.96 for miRNA expression data.Through the integration of bioinformatics and ML approach of the transcriptomic and epigenomic multi-omics dataset,we identified potential marker genes,namely,UBE2D2,HPCAL4,IGHA1,DPT,and FN3K.In-silico molecular docking revealed a strong binding affinity between ANKRD13C and the FDA-approved drug Everolimus(binding affinity−10.1 kcal/mol),identifying ANKRD13C as a potential therapeutic drug-repurposing target for SC.Conclusion:The proposed framework RankXLAN outperforms other existing frameworks for serum biomarker identification,therapeutic target identification,and SC classification with multi-omics datasets.
