The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Her...The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Herein,we report a CrO_(x)-engineered nickel-based oxide catalyst(FeCoCrO_(x)/NF)that achieves exceptional activity and stability through a dual-functional interfacial mechanism.Combing in situ Raman spectroscopy,18O isotopic labeling,and electrochemical analysis,we demonstrate that the oxygen evolution reaction follows a lattice oxygen-mediated mechanism.The CrO_(x)layer selectively adsorbs hydroxide ions,forming a dynamic interfacial barrier that electrostatically repels Cl^(-)ingress,thereby mitigating Cl^(-)corrosion.Through enthalpy-based analysis,we demonstrate that electronic redistribution via Cr-O-Fe bonding increases the vacancy formation energy of Fe,thereby suppressing its dissolution.In alkaline electrolyte containing 0.5 M Cl^(-)(1.0 M KOH),the catalyst is operating continuously for 1400 h at an industrial current density of 1000 mA cm^(-2).Furthermore,the catalyst retains 99.5%of its initial activity under fluctuating current density(100-1000 mA cm^(-2)),demonstrating robustness required for industrial electrolyzers.This study establishes a paradigm for designing corrosion-resistant electrocatalysts through the synergistic modulation of interfacial ion selectivity and bulk lattice oxygen activation,advancing the application of green hydrogen production in Cl^(-)-rich alkaline water.展开更多
Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we presen...Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we present novel experimental and theoretical evidence revealing the hybrid nature and optical tunability of STE state in Cs_(2)Ag_(0.4)Na_(0.6)InCl_(6).The detection of the Fano resonance in laser energy-dependent Raman and photoluminescence spectra indicates the emergence of an exciton-phonon hybrid state,arising from robust quantum interference between the discrete phonon and continuum exciton states.Moreover,we demonstrate continuous tuning of this hybrid state with the energy and intensity of the laser field.These findings lay the foundation for a comprehensive understanding of the nature of STE and their potential for state control.展开更多
Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improv...Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improved mass transfer and stability.Herein,self-supported crystalline/amorphous NiO/Ni(OH)_(2)nanosheet arrays on nickel foam(NF)are fabricated via an in-situ dissolution-deposition hydrothermal growing of Ni(OH)_(2)nanosheets without additional metal sources assisted by a common Lewis base,EDTA,followed by a rapid calcination at 300℃in air.The as-prepared EDTA-NF-12 h exhibits high OER and HER performance under alkaline conditions,requiring 235 mV and 158 mV,respectively,to reach 10 mA cm^(-2),and the decent performance can be maintained for 24 h without obvious degradation.The dual interfaces,i.e.,the dense crystalline/amorphous interfaces within the NiO/Ni(OH)_(2)nanosheet arrays,as well as the intimate interfaces between nanoarrays and NF,both serve as reaction active sites,facilitate electron transfer,and endow the catalyst with high activity and stability.Furthermore,by applying EDTA-Ni^(2+)and other Lewis bases with varying basicities instead of EDTA,the interfaces with the NF substrate are found to promote the formation of crystalline/amorphous interfaces within the nanosheets.This study offers appealing opportunities for tailoring the electrocatalytic performance of self-supported electrodes via dual interface engineering.展开更多
[Objectives] To study the protective effects of self-made Compound Taoren Danshen Decoction( CTDD) on acute liver injury induced by D-galactosamine in rats,and to explore its mechanism. [Methods]An acute liver injury ...[Objectives] To study the protective effects of self-made Compound Taoren Danshen Decoction( CTDD) on acute liver injury induced by D-galactosamine in rats,and to explore its mechanism. [Methods]An acute liver injury model was established by intraperitoneal injection of 500 mg/kg of D-galactosamine. The ALT,AST,MDA,SOD and GSH-Px in serum,as well as serum TNF-α,IL-1β and IL-6 levels were measured,and liver tissue lesions were observed under microscope. [Results] CTDD can significantly reduce ALT,AST and MDA levels,increase SOD,GSH-Px activity,and significantly reduce serum TNF-α,IL-1β and IL-6 levels,and improve liver tissue lesions.[Conclusions]CTDD has a protective effect on D-galactosamine-induced acute liver injury in rats,and its mechanism may be related to inhibition of oxidative stress and inflammatory reaction.展开更多
In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind,...In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.展开更多
Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric lea...Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.展开更多
Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global featu...Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global feature.The transformer can extract the global information well but adapting it to small medical datasets is challenging and its computational complexity can be heavy.In this work,a serial and parallel network is proposed for the accurate 3D medical image segmentation by combining CNN and transformer and promoting feature interactions across various semantic levels.The core components of the proposed method include the cross window self-attention based transformer(CWST)and multi-scale local enhanced(MLE)modules.The CWST module enhances the global context understanding by partitioning 3D images into non-overlapping windows and calculating sparse global attention between windows.The MLE module selectively fuses features by computing the voxel attention between different branch features,and uses convolution to strengthen the dense local information.The experiments on the prostate,atrium,and pancreas MR/CT image datasets consistently demonstrate the advantage of the proposed method over six popular segmentation models in both qualitative evaluation and quantitative indexes such as dice similarity coefficient,Intersection over Union,95%Hausdorff distance and average symmetric surface distance.展开更多
Second language(L2)motivation has been a topic which receives intensive attention.However,the peer effect on L2 motivation is insufficiently researched,although it is considered a crucial factor which may significantl...Second language(L2)motivation has been a topic which receives intensive attention.However,the peer effect on L2 motivation is insufficiently researched,although it is considered a crucial factor which may significantly mediate learners’L2 motivation.Hence,the current study adopted Dörnyei’s L2 Motivational Self System(L2MSS)as a theoretical framework and investigated in which specific aspects peers might affect the learners’L2 motivation and whether such effect was long-lasting.The research was designed as a small-scale qualitative study which was located in a language-focused experimental class project in China.Ten participants were recruited and individual interviews were conducted.The results demonstrated that,first,peers could remarkably influence the L2 motivation possessed by the students in the experimental class since they tended to create a clearer ideal L2 self and a more powerful ought-to L2 self.Second,although they had both positive and negative views towards the curriculum,a motivated peer climate could alleviate the pressure caused by the curriculum and reinforce positive attitudes.Third,such peer effect was not long-lasting.Based on the research results,pedagogical implications were proposed in terms of establishing a positive peer group and adjusting the emphasis of the curriculum.展开更多
Everyone is busy.But it's easy to be too busy.Then you may feel anxious or stressed.You need to take care of yourself.How can you do that?First,make time to text or call your family and friends.They care about you...Everyone is busy.But it's easy to be too busy.Then you may feel anxious or stressed.You need to take care of yourself.How can you do that?First,make time to text or call your family and friends.They care about you and can support you.Get regular exercise.展开更多
Are you tred of regular selfies?Try a self-photo studio!The lights and camera are ready for you.At the studio,you can fix your hair.There are clothes and props.You can use those and take fun photos.Bring your friends ...Are you tred of regular selfies?Try a self-photo studio!The lights and camera are ready for you.At the studio,you can fix your hair.There are clothes and props.You can use those and take fun photos.Bring your friends with you.Then you can take photos together.Pose in silly ways and have fun!You can take the photos home and remember your good time.展开更多
The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineerin...The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineering,Jiangxi Provincial Key Laboratory of Advanced Signal Processing and Intelligent Communications,Nanchang University,Nanchang 330031,China",and"School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China",respectively.The order of the two affiliations are not correct.展开更多
Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,...Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,line 14(PDF version,same below),there is a spelling mistake of“sui,”.It should be changed to“suitable”.The denominator“dt”in the Equation(3)should be changed to“dt”.展开更多
Water quality is a critical global issue,especially in urban and semi-urban regions where natural and anthropogenic factors significantly influence surface water systems.This study evaluates the hydrochemical characte...Water quality is a critical global issue,especially in urban and semi-urban regions where natural and anthropogenic factors significantly influence surface water systems.This study evaluates the hydrochemical characteristics of surface water in the North of Tehran Rivers(NTRs),an essential water resource in a rapidly urbanizing region,using advanced clustering techniques,including Hierarchical Clustering Analysis(HCA),Fuzzy CMeans(FCM),Genetic Algorithm Fuzzy C-Means(GAFCM),and Self-Organizing Map(SOM).The research aims to address the scientific challenge of understanding spatial and temporal variability in water quality,focusing on physicochemical parameters,hydrochemical facies,and contamination sources.Water samples from six rivers collected over four seasons in 2020 were analyzed and classified into distinct clusters based on their chemical composition,revealing significant seasonal and spatial differences.Results showed that FCM and GAFCM consistently categorized the NTRs into two clusters during winter and spring and three in summer and autumn.These findings were supported by HCA and SOM,which identified clusters corresponding to specific river segments and contamination levels.The primary hydrochemical processes identified were mineral dissolution and weathering,with calcite,dolomite,and aragonite significantly influencing water chemistry.Additionally,human activities,such as wastewater discharge,were shown to contribute to elevated sulfate,nitrate,and phosphate concentrations,further corroborated by microbial analyses.By integrating HCA,FCM,and GAFCM with an artificial neural network(ANN)-based clustering method(SOM),this study provides a robust framework for evaluating surface water quality.The findings,supported by Gibbs diagrams,Hounslow ion ratio,and saturation indices,highlight the dominance of rock weathering and human impacts in shaping the hydrochemical dynamics of the NTRs.These insights contribute to the scientific understanding of water quality dynamics and offer practical guidance for sustainable water resource management and environmental protection in developing urban areas.展开更多
Self-healing hydrogels utilize inherent intermolecular forces to autonomously heal physical damage resulting from excessive strain,pressure,or tearing.Applying these materials in soft robotics and tissue engineering c...Self-healing hydrogels utilize inherent intermolecular forces to autonomously heal physical damage resulting from excessive strain,pressure,or tearing.Applying these materials in soft robotics and tissue engineering could be beneficial.On the other hand,their efficacy in stretchable and mechanically resistant circuits is hindered by their limited electrical conductivity.展开更多
The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based t...The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based techniques with Self-Organizing Maps.展开更多
On April 2,U.S.President Trump slapped“reciprocal tariffs”on over 100 global trading partners,hitting nine ASEAN member states hard.Alarmingly,even the UN-designated Least Developed Countries(LDCs)were not spared.Th...On April 2,U.S.President Trump slapped“reciprocal tariffs”on over 100 global trading partners,hitting nine ASEAN member states hard.Alarmingly,even the UN-designated Least Developed Countries(LDCs)were not spared.These included Cambodia,where nearly 20 percent of the population lives below the poverty line,facing a 49 percent tariff;Laos,with a poverty rate near 20 percent,facing 48 percent;and Myanmar,which recently suffered a devastating earthquake,facing 44 percent.展开更多
In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the d...In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.展开更多
基金supported by the National Nature Science Foundation of China under Grant No.22269021the Tianshan Talent Project of Xinjiang Uygur Autonomous Region:2023TSYCQNTJ0039the Open project of Key Laboratory in Xinjiang Uygur Autonomous Region of China:2023D04027。
文摘The development of electrocatalysts that both work effectively at industrial current density and resist chloride ion(Cl^(-))corrosion remains a key challenge for hydrogen production from Cl^(-)-rich alkaline water.Herein,we report a CrO_(x)-engineered nickel-based oxide catalyst(FeCoCrO_(x)/NF)that achieves exceptional activity and stability through a dual-functional interfacial mechanism.Combing in situ Raman spectroscopy,18O isotopic labeling,and electrochemical analysis,we demonstrate that the oxygen evolution reaction follows a lattice oxygen-mediated mechanism.The CrO_(x)layer selectively adsorbs hydroxide ions,forming a dynamic interfacial barrier that electrostatically repels Cl^(-)ingress,thereby mitigating Cl^(-)corrosion.Through enthalpy-based analysis,we demonstrate that electronic redistribution via Cr-O-Fe bonding increases the vacancy formation energy of Fe,thereby suppressing its dissolution.In alkaline electrolyte containing 0.5 M Cl^(-)(1.0 M KOH),the catalyst is operating continuously for 1400 h at an industrial current density of 1000 mA cm^(-2).Furthermore,the catalyst retains 99.5%of its initial activity under fluctuating current density(100-1000 mA cm^(-2)),demonstrating robustness required for industrial electrolyzers.This study establishes a paradigm for designing corrosion-resistant electrocatalysts through the synergistic modulation of interfacial ion selectivity and bulk lattice oxygen activation,advancing the application of green hydrogen production in Cl^(-)-rich alkaline water.
基金funding support from the National Natural Science Foundation of China(Grant No.12525405)funding support from the National Natural Science Foundation of China(Grant No.12393831)the CAS Project for Young Scientists in Basic Research(Grant No.YSBR-120)。
文摘Self-trapped excitons(STEs),known for their unique radiative properties,have been harnessed in diverse photonic devices;however,their comprehensive understanding and manipulation remain elusive.In this study,we present novel experimental and theoretical evidence revealing the hybrid nature and optical tunability of STE state in Cs_(2)Ag_(0.4)Na_(0.6)InCl_(6).The detection of the Fano resonance in laser energy-dependent Raman and photoluminescence spectra indicates the emergence of an exciton-phonon hybrid state,arising from robust quantum interference between the discrete phonon and continuum exciton states.Moreover,we demonstrate continuous tuning of this hybrid state with the energy and intensity of the laser field.These findings lay the foundation for a comprehensive understanding of the nature of STE and their potential for state control.
基金the foundation of Guangdong Engineering Technology Research Center for Hydrogen Energy and Fuel Cells,the Guangdong Provincial Department of Education Innovation Project(No.2022KQNCX056)the Guangdong Basic and Applied Basic Research Foundation(Nos.2022A1515110354 and 2021A1515110582)。
文摘Self-supported nanoarrays have emerged as a promising alternative electrocatalyst for alkaline H_(2)O splitting,owing to their accessible active sites and strongly coupled interfaces with current collectors for improved mass transfer and stability.Herein,self-supported crystalline/amorphous NiO/Ni(OH)_(2)nanosheet arrays on nickel foam(NF)are fabricated via an in-situ dissolution-deposition hydrothermal growing of Ni(OH)_(2)nanosheets without additional metal sources assisted by a common Lewis base,EDTA,followed by a rapid calcination at 300℃in air.The as-prepared EDTA-NF-12 h exhibits high OER and HER performance under alkaline conditions,requiring 235 mV and 158 mV,respectively,to reach 10 mA cm^(-2),and the decent performance can be maintained for 24 h without obvious degradation.The dual interfaces,i.e.,the dense crystalline/amorphous interfaces within the NiO/Ni(OH)_(2)nanosheet arrays,as well as the intimate interfaces between nanoarrays and NF,both serve as reaction active sites,facilitate electron transfer,and endow the catalyst with high activity and stability.Furthermore,by applying EDTA-Ni^(2+)and other Lewis bases with varying basicities instead of EDTA,the interfaces with the NF substrate are found to promote the formation of crystalline/amorphous interfaces within the nanosheets.This study offers appealing opportunities for tailoring the electrocatalytic performance of self-supported electrodes via dual interface engineering.
文摘[Objectives] To study the protective effects of self-made Compound Taoren Danshen Decoction( CTDD) on acute liver injury induced by D-galactosamine in rats,and to explore its mechanism. [Methods]An acute liver injury model was established by intraperitoneal injection of 500 mg/kg of D-galactosamine. The ALT,AST,MDA,SOD and GSH-Px in serum,as well as serum TNF-α,IL-1β and IL-6 levels were measured,and liver tissue lesions were observed under microscope. [Results] CTDD can significantly reduce ALT,AST and MDA levels,increase SOD,GSH-Px activity,and significantly reduce serum TNF-α,IL-1β and IL-6 levels,and improve liver tissue lesions.[Conclusions]CTDD has a protective effect on D-galactosamine-induced acute liver injury in rats,and its mechanism may be related to inhibition of oxidative stress and inflammatory reaction.
基金supported by The National Key Research and Development Program of China(Grant No.2023YFB2604600).
文摘In energy constrained application scenarios, self‐powered systems (SPSs) are gradually emerging as a core technological pathway for enabling distributed intelligent sensing. High‐entropy energy, such as micro‐wind, vibrations, water motion, and human activity, is widely available but difficult to harness due to its low density, randomness, and spatiotemporal fragmentation. Triboelectric nanogenerators (TENGs), with high efficiency to low‐frequency and irregular mechanical stimuli, offer a promising solution for efficient energy harvesting, driving the advancement of SPSs with high‐entropy distribution. This review outlines the basic concepts and recent developments of TENG‐driven SPSs, focusing on strategies for energy harvesting, power management, and system integration. It highlights structural optimization and performance enhancement under typical highentropy scenarios and analyzes key challenges in energy conversion, power regulation, and load management. Finally, the potential applications of TENG‐driven SPSs are discussed in emerging smart fields such as infrastructure monitoring, lowaltitude economy, mobile intelligent devices, and ocean sensing networks.
基金financially supported by the National Natural Science Foundation of China(No.52125201)Beijing Natural Science Foundation(No.Z240025)and the Beijing Municipal Science and Technology(No.Z221100002722015).
文摘Flexible and wearable electronics are attracting surging attention due to their potential applications in human health monitoring and precision therapies.Safety hazards including strong magnetic field and electric leakage are big risk factors for human health.It remains challenging to develop self‐powered and wearable safety hazard sensors that could not only be able to monitor human motions but also have functions for detecting potential hazards.In this work,we fabricated a self‐powered,shapeable,and wearable magnetic triboelectric nanogenerator(MTENG)based on ferrofluid,Ecoflex,and carbonized silk fabric that possessed effective hazard prevention and biomechanical motion sensing ability.A peak open‐circuit voltage of 0.7 V and short‐circuit current of 10μA m^(−2)can be achieved when magnetic field is changed between 3.5 and 37.1 mT.As a component of triboelectric layer of the MTENG,ferrofluid can substantially extend the range of its sensing capabilities to many hazardous cues such as dangerous magnetic field.Furtherly,the developed multifunctional and self‐powered sensor can be used to monitor human activities such as drinking water and bending finger.This effort opens up a new design opportunity for hazard avoidance wearable electronics and self‐powered sensors.
基金National Key Research and Development Program of China,Grant/Award Number:2018YFE0206900China Postdoctoral Science Foundation,Grant/Award Number:2023M731204+2 种基金The Open Project of Key Laboratory for Quality Evaluation of Ultrasound Surgical Equipment of National Medical Products Administration,Grant/Award Number:SMDTKL-2023-1-01The Hubei Province Key Research and Development Project,Grant/Award Number:2023BCB007CAAI-Huawei MindSpore Open Fund。
文摘Convolutional neural network(CNN)with the encoder-decoder structure is popular in medical image segmentation due to its excellent local feature extraction ability but it faces limitations in capturing the global feature.The transformer can extract the global information well but adapting it to small medical datasets is challenging and its computational complexity can be heavy.In this work,a serial and parallel network is proposed for the accurate 3D medical image segmentation by combining CNN and transformer and promoting feature interactions across various semantic levels.The core components of the proposed method include the cross window self-attention based transformer(CWST)and multi-scale local enhanced(MLE)modules.The CWST module enhances the global context understanding by partitioning 3D images into non-overlapping windows and calculating sparse global attention between windows.The MLE module selectively fuses features by computing the voxel attention between different branch features,and uses convolution to strengthen the dense local information.The experiments on the prostate,atrium,and pancreas MR/CT image datasets consistently demonstrate the advantage of the proposed method over six popular segmentation models in both qualitative evaluation and quantitative indexes such as dice similarity coefficient,Intersection over Union,95%Hausdorff distance and average symmetric surface distance.
文摘Second language(L2)motivation has been a topic which receives intensive attention.However,the peer effect on L2 motivation is insufficiently researched,although it is considered a crucial factor which may significantly mediate learners’L2 motivation.Hence,the current study adopted Dörnyei’s L2 Motivational Self System(L2MSS)as a theoretical framework and investigated in which specific aspects peers might affect the learners’L2 motivation and whether such effect was long-lasting.The research was designed as a small-scale qualitative study which was located in a language-focused experimental class project in China.Ten participants were recruited and individual interviews were conducted.The results demonstrated that,first,peers could remarkably influence the L2 motivation possessed by the students in the experimental class since they tended to create a clearer ideal L2 self and a more powerful ought-to L2 self.Second,although they had both positive and negative views towards the curriculum,a motivated peer climate could alleviate the pressure caused by the curriculum and reinforce positive attitudes.Third,such peer effect was not long-lasting.Based on the research results,pedagogical implications were proposed in terms of establishing a positive peer group and adjusting the emphasis of the curriculum.
文摘Everyone is busy.But it's easy to be too busy.Then you may feel anxious or stressed.You need to take care of yourself.How can you do that?First,make time to text or call your family and friends.They care about you and can support you.Get regular exercise.
文摘Are you tred of regular selfies?Try a self-photo studio!The lights and camera are ready for you.At the studio,you can fix your hair.There are clothes and props.You can use those and take fun photos.Bring your friends with you.Then you can take photos together.Pose in silly ways and have fun!You can take the photos home and remember your good time.
文摘The authors regret that there were errors in the affiliations and the funding declaration in the original published version.The affiliations a and b of the original manuscript are"School of Information Engineering,Jiangxi Provincial Key Laboratory of Advanced Signal Processing and Intelligent Communications,Nanchang University,Nanchang 330031,China",and"School of Internet of Things Engineering,Jiangnan University,Wuxi 214122,China",respectively.The order of the two affiliations are not correct.
文摘Yongtao Yu,Yuelin Yu et al.Solvent-Resistant Wearable Triboelectric Nanogenerator for Energy-Harvesting and Self-Powered Sensors.Energy Environ.Mater.2024,7,e12700.On page 4 of this article,the first paragraph of 2.4,line 14(PDF version,same below),there is a spelling mistake of“sui,”.It should be changed to“suitable”.The denominator“dt”in the Equation(3)should be changed to“dt”.
文摘Water quality is a critical global issue,especially in urban and semi-urban regions where natural and anthropogenic factors significantly influence surface water systems.This study evaluates the hydrochemical characteristics of surface water in the North of Tehran Rivers(NTRs),an essential water resource in a rapidly urbanizing region,using advanced clustering techniques,including Hierarchical Clustering Analysis(HCA),Fuzzy CMeans(FCM),Genetic Algorithm Fuzzy C-Means(GAFCM),and Self-Organizing Map(SOM).The research aims to address the scientific challenge of understanding spatial and temporal variability in water quality,focusing on physicochemical parameters,hydrochemical facies,and contamination sources.Water samples from six rivers collected over four seasons in 2020 were analyzed and classified into distinct clusters based on their chemical composition,revealing significant seasonal and spatial differences.Results showed that FCM and GAFCM consistently categorized the NTRs into two clusters during winter and spring and three in summer and autumn.These findings were supported by HCA and SOM,which identified clusters corresponding to specific river segments and contamination levels.The primary hydrochemical processes identified were mineral dissolution and weathering,with calcite,dolomite,and aragonite significantly influencing water chemistry.Additionally,human activities,such as wastewater discharge,were shown to contribute to elevated sulfate,nitrate,and phosphate concentrations,further corroborated by microbial analyses.By integrating HCA,FCM,and GAFCM with an artificial neural network(ANN)-based clustering method(SOM),this study provides a robust framework for evaluating surface water quality.The findings,supported by Gibbs diagrams,Hounslow ion ratio,and saturation indices,highlight the dominance of rock weathering and human impacts in shaping the hydrochemical dynamics of the NTRs.These insights contribute to the scientific understanding of water quality dynamics and offer practical guidance for sustainable water resource management and environmental protection in developing urban areas.
文摘Self-healing hydrogels utilize inherent intermolecular forces to autonomously heal physical damage resulting from excessive strain,pressure,or tearing.Applying these materials in soft robotics and tissue engineering could be beneficial.On the other hand,their efficacy in stretchable and mechanically resistant circuits is hindered by their limited electrical conductivity.
文摘The title of the online version of the original article was revised.The title of the original article has been revised to:Hydrochemical characterization of surface waters in Northern Tehran:Integrating cluster-based techniques with Self-Organizing Maps.
文摘On April 2,U.S.President Trump slapped“reciprocal tariffs”on over 100 global trading partners,hitting nine ASEAN member states hard.Alarmingly,even the UN-designated Least Developed Countries(LDCs)were not spared.These included Cambodia,where nearly 20 percent of the population lives below the poverty line,facing a 49 percent tariff;Laos,with a poverty rate near 20 percent,facing 48 percent;and Myanmar,which recently suffered a devastating earthquake,facing 44 percent.
文摘In order to identify the tilt direction of the self-mixing signals under weak feedback regime interfered by noise,a deep learning method is proposed.The one-dimensional U-Net(1D U-Net)neural network can identify the direction of the self-mixing fringes accurately and quickly.In the process of measurement,the measurement signal can be normalized and then the neural network can be used to discriminate the direction.Simulation and experimental results show that the proposed method is suitable for self-mixing interference signals with noise in the whole weak feedback regime,and can maintain a high discrimination accuracy for signals interfered by 5 dB large noise.Combined with fringe counting method,accurate and rapid displacement reconstruction can be realized.
