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
The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials off...The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.展开更多
The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(...The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis routes.This review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and nanocrystals.Through a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread implementation.In addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection systems.This review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.展开更多
Friction stir welding(FSW)is a relatively new welding technique that has significant advantages compared to the fusion welding techniques in joining non weld able alloys by fusion,such as aluminum alloys.Three FSW sea...Friction stir welding(FSW)is a relatively new welding technique that has significant advantages compared to the fusion welding techniques in joining non weld able alloys by fusion,such as aluminum alloys.Three FSW seams of AA6061-T6 plates were made us-ing different FSW parameters.The structure of the FSW seams was investigated using X-ray diffraction(XRD),scanning electron mi-croscope(SEM)and non destructive testing(NDT)techniques and their hardness was also measured.The dominated phase in the AA6061-T6 alloy and the FSW seams was theα-Al.The FSW seam had lower content of the secondary phases than the AA6061-T6 al-loy.The hardness of the FSW seams was decreased by about 30%compared to the AA6061-T6 alloy.The temperature distributions in the weld seams were also studied experimentally and numerically modeled and the results were in a good agreement.展开更多
Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulc...Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulching is commonly used in the Loess Plateau region.Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity.Combining these techniques represents a novel agricultural approach in semi-arid areas.However,the impact of this integration on soil carbon storage(SOCS),carbon footprint(CF),and economic benefits has received limited research attention.Therefore,we conducted an eight-year study(2015-2022)in the semi-arid northwestern region to quantify the effects of four treatments[urea supplied without plastic film mulching(CK-U),slow-release fertilizer supplied without plastic film mulching(CK-S),urea supplied with plastic film mulching(PM-U),and slow-release fertilizer supplied with plastic film mulching(PM-S)]on soil fertility,economic and environmental benefits.The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions(≥71.97%).Compared to other treatments,PM-S increased average grain yield by 12.01%-37.89%,water use efficiency by 9.19%-23.33%,nitrogen accumulation by 27.07%-66.19%,and net return by 6.21%-29.57%.Furthermore,PM-S decreased CF by 12.87%-44.31%and CF per net return by 14.25%-41.16%.After eight years,PM-S increased SOCS(0-40 cm)by 2.46%,while PM-U decreased it by 7.09%.These findings highlight the positive effects of PM-S on surface soil fertility,economic gains,and environmental benefits in spring maize production on the Loess Plateau,underscoring its potential for widespread adoption and application.展开更多
Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental chall...Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental challenges.The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain,Iran,focusing on quantifying subsidence resulting from groundwater extraction.Using Sentinel-1 satellite data(2014–2019)and monthly piezometric measurements(1996–2018),the analysis revealed an average deformation velocity of–6.3 cm yr–1,with accumulated subsidence of–32 cm over the 2014–2019 period.The maximum subsidence rate reached 10.3 cm yr–1 in areas of intensive agricultural activity.A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends.Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75%of the variance(R2=0.75),indicating that intermediate-scale groundwater declines were the primary drivers of subsidence.Furthermore,land use analysis using Landsat data(1999–2021)revealed a 6230-ha increase in irrigated farmland,contributing to heightened groundwater extraction and subsidence rates.These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.展开更多
For the first time,the linear and nonlinear vibrations of composite rectangular sandwich plates with various geometric patterns of lattice core have been analytically examined in this work.The plate comprises a lattic...For the first time,the linear and nonlinear vibrations of composite rectangular sandwich plates with various geometric patterns of lattice core have been analytically examined in this work.The plate comprises a lattice core located in the middle and several homogeneous orthotropic layers that are symmetrical relative to it.For this purpose,the partial differential equations of motion have been derived based on the first-order shear deformation theory,employing Hamilton’s principle and Von Kármán’s nonlinear displacement-strain relations.Then,the nonlinear partial differential equations of the plate are converted into a time-dependent nonlinear ordinary differential equation(Duffing equation)by applying the Galerkin method.From the solution of this equation,the natural frequencies are extracted.Then,to calculate the non-linear frequencies of the plate,the non-linear equation of the plate has been solved analytically using the method of multiple scales.Finally,the effect of some critical parameters of the system,such as the thickness,height,and different angles of the stiffeners on the linear and nonlinear frequencies,has been analyzed in detail.To confirmthe solution method,the results of this research have been compared with the reported results in the literature and finite elements in ABAQUS,and a perfect match is observed.The results reveal that the geometry and configuration of core ribs strongly affect the natural frequencies of the plate.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
Manganese-based chalcogenides have significant potential as anodes for sodium-ion batteries(SIBs) due to their high theoretical specific capacity, abundant natural reserves, and environmental friendliness. However, th...Manganese-based chalcogenides have significant potential as anodes for sodium-ion batteries(SIBs) due to their high theoretical specific capacity, abundant natural reserves, and environmental friendliness. However, their application is hindered by poor cycling stability, resulting from severe volume changes during cycling and slow reaction kinetics due to their complex crystal structure. Here, an efficient and straightforward strategy was employed to in-situ encapsulate single-phase porous nanocubic MnS_(0.5)Se_(0.5) into carbon nanofibers using electrospinning and the hard template method, thus forming a necklace-like porous MnS_(0.5)Se_(0.5)-carbon nanofiber composite(MnS_(0.5)Se_(0.5)@N-CNF). The introduction of Se significantly impacts both the composition and microstructure of MnS_(0.5)Se_(0.5), including lattice distortion that generates additional defects, optimization of chemical bonds, and a nano-spatially confined design. In situ/ex-situ characterization and density functional theory calculations verified that this MnS_(0.5)Se_(0.5)@N-CNF allevi- ates the volume expansion and facilitates the transfer of Na+/electron. As expected, MnS_(0.5)Se_(0.5)@N-CNF anode demonstrates excellent sodium storage performance, characterized by high initial Coulombic efficiency(90.8%), high-rate capability(370.5 m Ahg^(-1) at 10 Ag^(-1)) and long durability(over 5000 cycles at 5 Ag^(-1)). The MnS_(0.5)Se_(0.5)@N-CNF//NVP@C full cell, assembled with MnS_(0.5)Se_(0.5)@N-CNF as anode and Na_(3)V_(2)(PO_4)_(3)@C as cathode, exhibits a high energy density of 254 Wh kg^(-1) can be provided. This work presents a novel strategy to optimize the design of anode materials through structural engineering and Se substitution, while also elucidating the underlying reaction mechanisms.展开更多
The sedimentary geochemistry of St.Martin’s Island is important to determine the origin of the source rock,paleo weathering,tectonic setting,sediment recycling,maturity,sorting,redox condition,and paleo salinity of t...The sedimentary geochemistry of St.Martin’s Island is important to determine the origin of the source rock,paleo weathering,tectonic setting,sediment recycling,maturity,sorting,redox condition,and paleo salinity of the sediments.Major oxides,trace elements,and rare earth elements(REEs)obtained from the INAA technique are presented by analyzing the sediment samples collected from the shoreline of St.Martin’s Island,Bangladesh.The elemental ratios,comparison with average upper continental crust(UCC),binary diagrams(Th/Sc vs.Sc,La/Th vs.Hf,Th/Co vs.La/Sc),and chondrite normalized REE patterns exhibit substantial LREE enrichment,relatively fl at HREE fractionation,considerable negative Eu anomalies(average:0.72),indicates the derivation from a source dominated by felsic rock,with contribution from intermediate source and mafi c component.Sediments from St.Martin’s Island exhibit the deposition of sediments in transitional environments of active and passive continental margin settings.Weathering indices value of CIA,PIA,CIW,CIX,and K 2 O/Rb ratio show moderate chemical weathering,indicating that the sediments are chemically mature.Sedimentary redox indicative proxies,such as U/Th,V/Cr,and V/Sc,show an oxic depositional environment during sediment deposition.The intermediate CIA and other weathering index values of the St.Martin’s sediments show that the area had semiarid and humid climatic conditions throughout the deposition.The Rb/K ratio of the St.Martin’s sediments suggests that the development and deposition of the sedimentary sequence of St.Martin’s Island mainly occurred in a brackish water environment during the geological past.展开更多
In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab C...In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–2047.DOI:10.32604/cmc.2023.043687,URL:https://www.techscience.com/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.展开更多
Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and...Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.展开更多
Extreme weather events,such as floods and droughts,are expected to rise significantly worldwide as a result of climate change.Investigating future drought patterns is therefore a key approach for elaborating anticipat...Extreme weather events,such as floods and droughts,are expected to rise significantly worldwide as a result of climate change.Investigating future drought patterns is therefore a key approach for elaborating anticipatory water resources management responses to climate change.In this paper,future meteorological drought conditions are investigated based on the SPEI(Standardised Precipitation Evapotranspiration Index).This study makes use of observed and projected data.The simulated data were retrieved from the CMIP6(Coupled Model Intercomparison Project Phase 6)over the period 2025-2050,and the Delta change method was adopted to remove the bias in the dataset.Then SPEI at various scales has been estimated under four future scenarios(SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5).The trend analysis of the projected SPEI was performed at p<0.05 using the MMK(Modified Mann-Kendall)test in order to detect the statistically significant trend of the drought against the null hypothesis of no trend.Results show large variability in the magnitude of drought in the past and future.Based on SPEI at 24 months accumulation,the result shows that under SSP1-2.6,the basin will experience a wet period during the first decade(SPEI=0.60),the second decade will be dry(SPEI24=-0.43).The remaining years will be also dry(SPEI=-0.34).Under SSP2-4.5,SSP3-7.0 and SSP5-8.5 scenarios,the district will experience a wet period during the first two decades with SPEI ranging from 0.38 to 0.59.This wet period will be followed by a dry period under these scenarios ranging from-0.14 to-0.06.Overall,under SSPs scenarios,two main periods characterized by a rainfall recovery spanning from followed by a moderately prolonged drought are identified within the study area.The findings of this study may provide valuable information for developing proactive measures to reduce water insecurity in Fada N’Gourma through effective drought mitigation.展开更多
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.
基金supported by the IITP(Institute of Information & Communications Technology Planning & Evaluation)-ITRC(Information Technology Research Center) grant funded by the Korea government(Ministry of Science and ICT) (IITP-2025-RS-2024-00437191, and RS-2025-02303505)partly supported by the Korea Basic Science Institute (National Research Facilities and Equipment Center) grant funded by the Ministry of Education. (No. 2022R1A6C101A774)the Deanship of Research and Graduate Studies at King Khalid University, Saudi Arabia, through Large Research Project under grant number RGP-2/527/46
文摘The growing global energy demand and worsening climate change highlight the urgent need for clean,efficient and sustainable energy solutions.Among emerging technologies,atomically thin two-dimensional(2D)materials offer unique advantages in photovoltaics due to their tunable optoelectronic properties,high surface area and efficient charge transport capabilities.This review explores recent progress in photovoltaics incorporating 2D materials,focusing on their application as hole and electron transport layers to optimize bandgap alignment,enhance carrier mobility and improve chemical stability.A comprehensive analysis is presented on perovskite solar cells utilizing 2D materials,with a particular focus on strategies to enhance crystallization,passivate defects and improve overall cell efficiency.Additionally,the application of 2D materials in organic solar cells is examined,particularly for reducing recombination losses and enhancing charge extraction through work function modification.Their impact on dye-sensitized solar cells,including catalytic activity and counter electrode performance,is also explored.Finally,the review outlines key challenges,material limitations and performance metrics,offering insight into the future development of nextgeneration photovoltaic devices encouraged by 2D materials.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.RS-2022–00165798)Anhui Natural Science Foundation(No.2308085MF211)The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under Grant Number(R.G.P.2/491/45).
文摘The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection applications.These materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis routes.This review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and nanocrystals.Through a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread implementation.In addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection systems.This review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.
文摘Friction stir welding(FSW)is a relatively new welding technique that has significant advantages compared to the fusion welding techniques in joining non weld able alloys by fusion,such as aluminum alloys.Three FSW seams of AA6061-T6 plates were made us-ing different FSW parameters.The structure of the FSW seams was investigated using X-ray diffraction(XRD),scanning electron mi-croscope(SEM)and non destructive testing(NDT)techniques and their hardness was also measured.The dominated phase in the AA6061-T6 alloy and the FSW seams was theα-Al.The FSW seam had lower content of the secondary phases than the AA6061-T6 al-loy.The hardness of the FSW seams was decreased by about 30%compared to the AA6061-T6 alloy.The temperature distributions in the weld seams were also studied experimentally and numerically modeled and the results were in a good agreement.
基金supported by the National Natural Science Foundation of China(No.32071980)the Key Projects of Shaanxi Agricultural Collaborative Innovation and Extension Alliance(No.LMZD202201)+1 种基金the Key R&D Project in Shaanxi Province(No.2021LLRH-07)Shaanxi Natural Scientific Basic Research Program project(No.2022JQ-157).
文摘Agricultural practices significantly contribute to greenhouse gas(GHG)emissions,necessitating cleaner production technologies to reduce environmental pressure and achieve sustainable maize production.Plastic film mulching is commonly used in the Loess Plateau region.Incorporating slow-release fertilizers as a replacement for urea within this practice can reduce nitrogen losses and enhance crop productivity.Combining these techniques represents a novel agricultural approach in semi-arid areas.However,the impact of this integration on soil carbon storage(SOCS),carbon footprint(CF),and economic benefits has received limited research attention.Therefore,we conducted an eight-year study(2015-2022)in the semi-arid northwestern region to quantify the effects of four treatments[urea supplied without plastic film mulching(CK-U),slow-release fertilizer supplied without plastic film mulching(CK-S),urea supplied with plastic film mulching(PM-U),and slow-release fertilizer supplied with plastic film mulching(PM-S)]on soil fertility,economic and environmental benefits.The results revealed that nitrogen fertilizer was the primary contributor to total GHG emissions(≥71.97%).Compared to other treatments,PM-S increased average grain yield by 12.01%-37.89%,water use efficiency by 9.19%-23.33%,nitrogen accumulation by 27.07%-66.19%,and net return by 6.21%-29.57%.Furthermore,PM-S decreased CF by 12.87%-44.31%and CF per net return by 14.25%-41.16%.After eight years,PM-S increased SOCS(0-40 cm)by 2.46%,while PM-U decreased it by 7.09%.These findings highlight the positive effects of PM-S on surface soil fertility,economic gains,and environmental benefits in spring maize production on the Loess Plateau,underscoring its potential for widespread adoption and application.
文摘Population growth leads to increased utilization of water resources.One of these resources is groundwater,which has steadily declined each year.The depletion of these resources brings about various environmental challenges.The present study aimed to explore the relationship between groundwater fluctuations and land subsidence in the Malayer Plain,Iran,focusing on quantifying subsidence resulting from groundwater extraction.Using Sentinel-1 satellite data(2014–2019)and monthly piezometric measurements(1996–2018),the analysis revealed an average deformation velocity of–6.3 cm yr–1,with accumulated subsidence of–32 cm over the 2014–2019 period.The maximum subsidence rate reached 10.3 cm yr–1 in areas of intensive agricultural activity.A wavelet-PCA spatiotemporal analysis of groundwater fluctuations identified critical multi-scale patterns strongly correlated with subsidence trends.Regression analysis between subsidence rates and groundwater fluctuations at various wavelet decomposition levels explained 75%of the variance(R2=0.75),indicating that intermediate-scale groundwater declines were the primary drivers of subsidence.Furthermore,land use analysis using Landsat data(1999–2021)revealed a 6230-ha increase in irrigated farmland,contributing to heightened groundwater extraction and subsidence rates.These findings highlight the critical need for sustainable groundwater management to mitigate the risks of continued subsidence in the region.
文摘For the first time,the linear and nonlinear vibrations of composite rectangular sandwich plates with various geometric patterns of lattice core have been analytically examined in this work.The plate comprises a lattice core located in the middle and several homogeneous orthotropic layers that are symmetrical relative to it.For this purpose,the partial differential equations of motion have been derived based on the first-order shear deformation theory,employing Hamilton’s principle and Von Kármán’s nonlinear displacement-strain relations.Then,the nonlinear partial differential equations of the plate are converted into a time-dependent nonlinear ordinary differential equation(Duffing equation)by applying the Galerkin method.From the solution of this equation,the natural frequencies are extracted.Then,to calculate the non-linear frequencies of the plate,the non-linear equation of the plate has been solved analytically using the method of multiple scales.Finally,the effect of some critical parameters of the system,such as the thickness,height,and different angles of the stiffeners on the linear and nonlinear frequencies,has been analyzed in detail.To confirmthe solution method,the results of this research have been compared with the reported results in the literature and finite elements in ABAQUS,and a perfect match is observed.The results reveal that the geometry and configuration of core ribs strongly affect the natural frequencies of the plate.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
基金financially supported by the National Natural Science Foundation of China (No. 22225902, U22A20436, 22209185)National Key Research&Development Program of China (2022YFE0115900, 2023YFA1507101, 2021YFA1501500)+1 种基金the Self-deployment Project Research Program of Haixi Institutes,Chinese Academy of Sciences (No. CXZX-2022-GH04, CXZX-2023-JQ08)Science and Technology Program of Fuzhou (2023-P-009)。
文摘Manganese-based chalcogenides have significant potential as anodes for sodium-ion batteries(SIBs) due to their high theoretical specific capacity, abundant natural reserves, and environmental friendliness. However, their application is hindered by poor cycling stability, resulting from severe volume changes during cycling and slow reaction kinetics due to their complex crystal structure. Here, an efficient and straightforward strategy was employed to in-situ encapsulate single-phase porous nanocubic MnS_(0.5)Se_(0.5) into carbon nanofibers using electrospinning and the hard template method, thus forming a necklace-like porous MnS_(0.5)Se_(0.5)-carbon nanofiber composite(MnS_(0.5)Se_(0.5)@N-CNF). The introduction of Se significantly impacts both the composition and microstructure of MnS_(0.5)Se_(0.5), including lattice distortion that generates additional defects, optimization of chemical bonds, and a nano-spatially confined design. In situ/ex-situ characterization and density functional theory calculations verified that this MnS_(0.5)Se_(0.5)@N-CNF allevi- ates the volume expansion and facilitates the transfer of Na+/electron. As expected, MnS_(0.5)Se_(0.5)@N-CNF anode demonstrates excellent sodium storage performance, characterized by high initial Coulombic efficiency(90.8%), high-rate capability(370.5 m Ahg^(-1) at 10 Ag^(-1)) and long durability(over 5000 cycles at 5 Ag^(-1)). The MnS_(0.5)Se_(0.5)@N-CNF//NVP@C full cell, assembled with MnS_(0.5)Se_(0.5)@N-CNF as anode and Na_(3)V_(2)(PO_4)_(3)@C as cathode, exhibits a high energy density of 254 Wh kg^(-1) can be provided. This work presents a novel strategy to optimize the design of anode materials through structural engineering and Se substitution, while also elucidating the underlying reaction mechanisms.
基金Supporting Program for funding this work under Project number(RSP2024R328),King Saud University,Riyadh,Saudi Arabia.
文摘The sedimentary geochemistry of St.Martin’s Island is important to determine the origin of the source rock,paleo weathering,tectonic setting,sediment recycling,maturity,sorting,redox condition,and paleo salinity of the sediments.Major oxides,trace elements,and rare earth elements(REEs)obtained from the INAA technique are presented by analyzing the sediment samples collected from the shoreline of St.Martin’s Island,Bangladesh.The elemental ratios,comparison with average upper continental crust(UCC),binary diagrams(Th/Sc vs.Sc,La/Th vs.Hf,Th/Co vs.La/Sc),and chondrite normalized REE patterns exhibit substantial LREE enrichment,relatively fl at HREE fractionation,considerable negative Eu anomalies(average:0.72),indicates the derivation from a source dominated by felsic rock,with contribution from intermediate source and mafi c component.Sediments from St.Martin’s Island exhibit the deposition of sediments in transitional environments of active and passive continental margin settings.Weathering indices value of CIA,PIA,CIW,CIX,and K 2 O/Rb ratio show moderate chemical weathering,indicating that the sediments are chemically mature.Sedimentary redox indicative proxies,such as U/Th,V/Cr,and V/Sc,show an oxic depositional environment during sediment deposition.The intermediate CIA and other weathering index values of the St.Martin’s sediments show that the area had semiarid and humid climatic conditions throughout the deposition.The Rb/K ratio of the St.Martin’s sediments suggests that the development and deposition of the sedimentary sequence of St.Martin’s Island mainly occurred in a brackish water environment during the geological past.
文摘In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,Muhammad Imran Sharif,Ahmed Naeem,Muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham E.Ragab Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–2047.DOI:10.32604/cmc.2023.043687,URL:https://www.techscience.com/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.
基金National Natural Science Foundation of China(32201491)Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)The authors extend their appreciation to the Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FPEJ-2024-1101-02”.
文摘Research efforts on electromagnetic interference(EMI)shielding materials have begun to converge on green and sustainable biomass materials.These materials offer numerous advantages such as being lightweight,porous,and hierarchical.Due to their porous nature,interfacial compatibility,and electrical conductivity,biomass materials hold significant potential as EMI shielding materials.Despite concerted efforts on the EMI shielding of biomass materials have been reported,this research area is still relatively new compared to traditional EMI shielding materials.In particular,a more comprehensive study and summary of the factors influencing biomass EMI shielding materials including the pore structure adjustment,preparation process,and micro-control would be valuable.The preparation methods and characteristics of wood,bamboo,cellulose and lignin in EMI shielding field are critically discussed in this paper,and similar biomass EMI materials are summarized and analyzed.The composite methods and fillers of various biomass materials were reviewed.this paper also highlights the mechanism of EMI shielding as well as existing prospects and challenges for development trends in this field.
文摘Extreme weather events,such as floods and droughts,are expected to rise significantly worldwide as a result of climate change.Investigating future drought patterns is therefore a key approach for elaborating anticipatory water resources management responses to climate change.In this paper,future meteorological drought conditions are investigated based on the SPEI(Standardised Precipitation Evapotranspiration Index).This study makes use of observed and projected data.The simulated data were retrieved from the CMIP6(Coupled Model Intercomparison Project Phase 6)over the period 2025-2050,and the Delta change method was adopted to remove the bias in the dataset.Then SPEI at various scales has been estimated under four future scenarios(SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5).The trend analysis of the projected SPEI was performed at p<0.05 using the MMK(Modified Mann-Kendall)test in order to detect the statistically significant trend of the drought against the null hypothesis of no trend.Results show large variability in the magnitude of drought in the past and future.Based on SPEI at 24 months accumulation,the result shows that under SSP1-2.6,the basin will experience a wet period during the first decade(SPEI=0.60),the second decade will be dry(SPEI24=-0.43).The remaining years will be also dry(SPEI=-0.34).Under SSP2-4.5,SSP3-7.0 and SSP5-8.5 scenarios,the district will experience a wet period during the first two decades with SPEI ranging from 0.38 to 0.59.This wet period will be followed by a dry period under these scenarios ranging from-0.14 to-0.06.Overall,under SSPs scenarios,two main periods characterized by a rainfall recovery spanning from followed by a moderately prolonged drought are identified within the study area.The findings of this study may provide valuable information for developing proactive measures to reduce water insecurity in Fada N’Gourma through effective drought mitigation.
