This study explored how mental health professionals collaborate with peer supporters with mental disabilities in a community mental health institution.From January 19 to February 23,2021,three 60 min interviews were c...This study explored how mental health professionals collaborate with peer supporters with mental disabilities in a community mental health institution.From January 19 to February 23,2021,three 60 min interviews were conducted with six mental health professionals working at a Korean community center.The results were qualitatively analyzed and divided into four themes and eight categories.The four themes were the perceptions of and challenges in working with peer supporters with mental disabilities,conflict and confusion about working with peer supporters,forming partnerships with peer supporters,and policy support for peer supporters’job security.Participants reported vague anxiety about working with a peer supporter and difficulties with the trial-and-error process of adjusting to the role as challenging.Over time,however,they realized that they needed to make an effort to develop meaningful relationships with peer supporters and mental health professionals.Thus,through this study,we realized that there was a need to improve the system,such as building infrastructure for job stability for peer support workers and capacity building tailored to the mental disorders.Although peer supporters play various roles while working with mental health professionals,this study showed the possibility of mutual growth through communication and cooperation.These findings will help prepare systems necessary for collaboration between the two teams amidst the increasing institutionalization of peer support for mental disorders.展开更多
A new catalyst support, Ce-Mg-O, was prepared in a novel way macromolecule surfactant modified method and was used as a catalyst support for low-temperature methane combustion. The results indicate that the new type o...A new catalyst support, Ce-Mg-O, was prepared in a novel way macromolecule surfactant modified method and was used as a catalyst support for low-temperature methane combustion. The results indicate that the new type of FeOx/Ce- Mg-O catalyst exhibits high activity in low-temperature methane combustion, such that the T90 at which 90% conversion of methane occurs can be obtained at 560 ℃. The structure of the catalyst and the effect of the supporter on catalytic activity were characterized by transmission electronic microscopy （TEM）, X-ray diffraction （XRD）, and temperature-programmed reduction （TPR）. The results indicate that the high catalytic activity of FeOx/Ce-Mg-O over methane combustion is strongly dependent on the particle size, typical crystal phase of the Ce-Mg-O, and the interaction of FeOx and Ce-Mg-O.展开更多
Background: This study assessed treatment interruption of tuberculosis (TB) patients managed by treatment supporters and health care workers and other predictors of treatment interruption. Methods: A descriptive cross...Background: This study assessed treatment interruption of tuberculosis (TB) patients managed by treatment supporters and health care workers and other predictors of treatment interruption. Methods: A descriptive cross-sectional study was conducted. Four hundred and seventy new smear positive TB patients above 14 years of age were consecutively recruited between October 1 and December 31 2012 from 34 (23 public and 11 private) directly observed treatment short course (DOTS) facilities that offered TB treatment and microscopy services. They were followed up till treatment was completed. Logistic regression was used to assess the predictors of treatment interruption. Results: A significantly higher proportion of smokers (58.6% vs 38.3%, p = 0.030), patients supervised by treatment supporters (44.4% vs 34.7%, p = 0.032), patients not counselled before initiation of treatment (55.6% vs 38.2%, p = 0.041), patients managed at private DOTS facilities (50% vs 36.3%, p = 0.010) and TB/HIV co-infected patients (54.2% vs 38.6%, p = 0.038) had treatment interruption. Predictors of treatment interruption were supervision by treatment supporters, smoking, lack of pre-treatment counselling and TB/HIV co-infection. Conclusion: A higher proportion of patients supervised by treatment supporters had treatment interruption than those supervised by health care workers. There may be a need to review the concept of treatment supervision by treatment supporters in Lagos state Nigeria.展开更多
Beloved and A Mercy are widely regarded as a companion piece to each other.This thesis intends to employ Gerard Genette’s narrow-sense intertextuality to study Two Black male Characters in Beloved&A Mercy:Paul D&...Beloved and A Mercy are widely regarded as a companion piece to each other.This thesis intends to employ Gerard Genette’s narrow-sense intertextuality to study Two Black male Characters in Beloved&A Mercy:Paul D&the Blacksmith.It is hoped that this thesis will reveal the deep concern of Morrison not only for the future of women of her own race,but also for the black men.And by the creation of Paul D and the blacksmith,Morrison wants to show us her definition of ideal relationships between man and woman:Male participation is indispensable in a female’s growth and redemption.Only in the process of jointly conquering the shadows and tribulations of the past,can they reach real mutual understanding and harmony.展开更多
Since 2004, a total of 23 members have given their financial support to CREIC. Here we wish to express our sincere thanks to them. The names of our sponsors are listed below.
Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex int...Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.展开更多
Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductiv...Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.展开更多
Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effe...Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.展开更多
To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃...To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃induced vibration response data of a three⁃span four⁃row double⁃layer cable PV support system.The wind⁃induced vibration characteristics with different PV module tilt angles,wind speeds,and wind direction angles were analyzed.The results showed that the double⁃layer cable large⁃span flexible PV support can effectively control the wind⁃induced vibration response and prevent the occur⁃rence of flutter under strong wind conditions.The maxi⁃mum value of the wind⁃induced vibration displacement of the flexible PV support system occurs in the windward first row.The upstream module has a significant shading effect on the downstream module,with a maximum effect of 23%.The most unfavorable wind direction angles of the structure are 0°and 180°.The change of the wind direction angle in the range of 0°to 30°has little effect on the wind vi⁃bration response.The change in the tilt angle of the PV modules has a greater impact on the wind vibration in the downwind direction and a smaller impact in the upwind di⁃rection.Special attention should be paid to the structural wind⁃resistant design of such systems in the upwind side span.展开更多
The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limite...The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.展开更多
Structural regulation of Pd-based electrocatalytic hydrodechlorination(EHDC)catalyst for constructing high-efficient cathode materials with low noble metal content and high atom utilization is crucial but still challe...Structural regulation of Pd-based electrocatalytic hydrodechlorination(EHDC)catalyst for constructing high-efficient cathode materials with low noble metal content and high atom utilization is crucial but still challenging.Herein,a support electron inductive effect of Pd-Mn/Ni foam catalyst was proposed via in-situ Mn doping to optimize the electronic structure of the Ni foam(NF),which can inductive regulation of Pd for improving the EHDC performance.The mass activity and current efficiency of Pd-Mn/NF catalyst are 2.91 and 1.34 times superior to that of Pd/NF with 2,4-dichlorophenol as model compound,respectively.The Mn-doped interlayer optimized the electronic structure of Pd by bringing the d-state closer to the Fermi level than Pd on the NF surface,which optimizied the binding of EHDC intermediates.Additionally,the Mn-doped interlayer acted as a promoter for generating H∗and accelerating the EHDC reaction.This work presents a simple and effective regulation strategy for constructing high-efficient cathode catalyst for the EHDC of chlorinated organic compounds.展开更多
BACKGROUND Hepatocellular carcinoma ranks among the most prevalent malignant neoplasms.Surgical intervention constitutes a critical therapeutic approach for this condition.Nonetheless,postoperative recovery is frequen...BACKGROUND Hepatocellular carcinoma ranks among the most prevalent malignant neoplasms.Surgical intervention constitutes a critical therapeutic approach for this condition.Nonetheless,postoperative recovery is frequently influenced by the patient's nutritional status and the quality of nursing care provided.AIM To examine the comprehensive impact of personalized nutritional support and nursing strategies on the postoperative rehabilitation of patients with liver cancer.METHODS In this study,a retrospective comparative analysis was conducted involving 60 post-operative liver cancer patients.The subjects were selected as subjects and divided into two groups based on differing nursing interventions,with each group comprising 30 patients.The control group received standard nutritional support and care,whereas the experimental group received individualized nutritional support and nursing strategies.The study aimed to evaluate the impact of individualized nutrition by comparing the rehabilitation indices,nutritional status,quality of life(QoL),and complication rates between the two groups.RESULTS The results showed that the recovery index of the experimental group was significantly better than that of the control group 2 weeks after surgery,and the average liver function recovery index of the experimental group was 85.significantly higher than that of the control group(73.67±7.19).In terms of nutritional status,the serum albumin level and body weight stabilization rate of the experimental group were also significantly higher than those of the control group,which were 42.33±2.4 g/L and 93.3%,respectively,compared with 36.01±3.85 g/L and 76.7%of the control group.In addition,the average QoL score of the experimental group was 84.66±3.7 points,which was significantly higher than that of the control group(70.92±4.28 points).At the psychological level,the average anxiety score of the experimental group was 1.17±0.29,and the average depression score was 1.47±0.4,which were significantly lower than the 2.26±0.42 and 2.57±0.45 of the control group.This showed that patients in the experimental group were better relieved of anxiety and depression under the individualized nutrition support and nursing strategy.More importantly,the complication rate in the experimental group was only 10%,much lower than the 33.3%in the control group.CONCLUSION Personalized nutritional support and tailored nursing strategies significantly enhance the postoperative rehabilitation of liver cancer patients.Consequently,it is recommended to implement and advocate for these individualized approaches to improve both the recovery outcomes and QoL for these patients.展开更多
Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain c...Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.展开更多
The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approach...The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approaches rely heavily on subjective interpretations and variable expertise,machine learning(ML)has emerged as a transformative tool in healthcare.We conducted a comprehensive review of published literature on ML applications in esophageal diseases,analyzing technical approaches,validation methods,and clinical outcomes.ML demonstrates superior performance:In gastroesophageal reflux disease,ML models achieve 80%-90%accuracy in potential of hydrogen-impedance analysis and endoscopic grading;for Barrett’s esophagus,ML-based approaches show 88%-95% accuracy in invasive diagnostics and 77%-85% accuracy in non-invasive screening.In esophageal cancer,ML improves early detection and survival prediction by 6%-10% compared to traditional methods.Novel applications in achalasia and esophageal varices demonstrate promising results in automated diagnosis and risk stratification,with accuracy rates exceeding 85%.While challenges persist in data standardization,model interpretability,and clinical integration,emerging solutions in federated learning and explainable artificial intelligence offer promising pathways forward.The continued evolution of these technologies,coupled with rigorous validation and thoughtful implementation,may fundamentally transform our approach to esophageal disease management in the era of precision medicine.展开更多
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(2019R1F1A1A0057735).
文摘This study explored how mental health professionals collaborate with peer supporters with mental disabilities in a community mental health institution.From January 19 to February 23,2021,three 60 min interviews were conducted with six mental health professionals working at a Korean community center.The results were qualitatively analyzed and divided into four themes and eight categories.The four themes were the perceptions of and challenges in working with peer supporters with mental disabilities,conflict and confusion about working with peer supporters,forming partnerships with peer supporters,and policy support for peer supporters’job security.Participants reported vague anxiety about working with a peer supporter and difficulties with the trial-and-error process of adjusting to the role as challenging.Over time,however,they realized that they needed to make an effort to develop meaningful relationships with peer supporters and mental health professionals.Thus,through this study,we realized that there was a need to improve the system,such as building infrastructure for job stability for peer support workers and capacity building tailored to the mental disorders.Although peer supporters play various roles while working with mental health professionals,this study showed the possibility of mutual growth through communication and cooperation.These findings will help prepare systems necessary for collaboration between the two teams amidst the increasing institutionalization of peer support for mental disorders.
基金Project supported bythe Natural Science Foundation of Zhejiang Province (Y505285)
文摘A new catalyst support, Ce-Mg-O, was prepared in a novel way macromolecule surfactant modified method and was used as a catalyst support for low-temperature methane combustion. The results indicate that the new type of FeOx/Ce- Mg-O catalyst exhibits high activity in low-temperature methane combustion, such that the T90 at which 90% conversion of methane occurs can be obtained at 560 ℃. The structure of the catalyst and the effect of the supporter on catalytic activity were characterized by transmission electronic microscopy （TEM）, X-ray diffraction （XRD）, and temperature-programmed reduction （TPR）. The results indicate that the high catalytic activity of FeOx/Ce-Mg-O over methane combustion is strongly dependent on the particle size, typical crystal phase of the Ce-Mg-O, and the interaction of FeOx and Ce-Mg-O.
文摘Background: This study assessed treatment interruption of tuberculosis (TB) patients managed by treatment supporters and health care workers and other predictors of treatment interruption. Methods: A descriptive cross-sectional study was conducted. Four hundred and seventy new smear positive TB patients above 14 years of age were consecutively recruited between October 1 and December 31 2012 from 34 (23 public and 11 private) directly observed treatment short course (DOTS) facilities that offered TB treatment and microscopy services. They were followed up till treatment was completed. Logistic regression was used to assess the predictors of treatment interruption. Results: A significantly higher proportion of smokers (58.6% vs 38.3%, p = 0.030), patients supervised by treatment supporters (44.4% vs 34.7%, p = 0.032), patients not counselled before initiation of treatment (55.6% vs 38.2%, p = 0.041), patients managed at private DOTS facilities (50% vs 36.3%, p = 0.010) and TB/HIV co-infected patients (54.2% vs 38.6%, p = 0.038) had treatment interruption. Predictors of treatment interruption were supervision by treatment supporters, smoking, lack of pre-treatment counselling and TB/HIV co-infection. Conclusion: A higher proportion of patients supervised by treatment supporters had treatment interruption than those supervised by health care workers. There may be a need to review the concept of treatment supervision by treatment supporters in Lagos state Nigeria.
文摘Beloved and A Mercy are widely regarded as a companion piece to each other.This thesis intends to employ Gerard Genette’s narrow-sense intertextuality to study Two Black male Characters in Beloved&A Mercy:Paul D&the Blacksmith.It is hoped that this thesis will reveal the deep concern of Morrison not only for the future of women of her own race,but also for the black men.And by the creation of Paul D and the blacksmith,Morrison wants to show us her definition of ideal relationships between man and woman:Male participation is indispensable in a female’s growth and redemption.Only in the process of jointly conquering the shadows and tribulations of the past,can they reach real mutual understanding and harmony.
文摘Since 2004, a total of 23 members have given their financial support to CREIC. Here we wish to express our sincere thanks to them. The names of our sponsors are listed below.
基金funded by the Pyramid Talent Training Project of Beijing University of Civil Engineering and Architecture under Grant GJZJ20220802。
文摘Accurately estimating the State of Health(SOH)and Remaining Useful Life(RUL)of lithium-ion batteries(LIBs)is crucial for the continuous and stable operation of battery management systems.However,due to the complex internal chemical systems of LIBs and the nonlinear degradation of their performance,direct measurement of SOH and RUL is challenging.To address these issues,the Twin Support Vector Machine(TWSVM)method is proposed to predict SOH and RUL.Initially,the constant current charging time of the lithium battery is extracted as a health indicator(HI),decomposed using Variational Modal Decomposition(VMD),and feature correlations are computed using Importance of Random Forest Features(RF)to maximize the extraction of critical factors influencing battery performance degradation.Furthermore,to enhance the global search capability of the Convolution Optimization Algorithm(COA),improvements are made using Good Point Set theory and the Differential Evolution method.The Improved Convolution Optimization Algorithm(ICOA)is employed to optimize TWSVM parameters for constructing SOH and RUL prediction models.Finally,the proposed models are validated using NASA and CALCE lithium-ion battery datasets.Experimental results demonstrate that the proposed models achieve an RMSE not exceeding 0.007 and an MAPE not exceeding 0.0082 for SOH and RUL prediction,with a relative error in RUL prediction within the range of[-1.8%,2%].Compared to other models,the proposed model not only exhibits superior fitting capability but also demonstrates robust performance.
基金supported by the National Natural Science Foundation of China(No.52127816),the National Key Research and Development Program of China(No.2020YFA0715000)the National Natural Science and Hong Kong Research Grant Council Joint Research Funding Project of China(No.5181101182)the NSFC/RGC Joint Research Scheme sponsored by the Research Grants Council of Hong Kong and the National Natural Science Foundation of China(No.N_PolyU513/18).
文摘Latent heat thermal energy storage(TES)effectively reduces the mismatch between energy supply and demand of renewable energy sources by the utilization of phase change materials(PCMs).However,the low thermal conductivity and poor shape stability are the main drawbacks in realizing the large-scale application of PCMs.Promisingly,developing composite PCM(CPCM)based on porous supporting mate-rial provides a desirable solution to obtain performance-enhanced PCMs with improved effective thermal conductivity and shape stability.Among all the porous matrixes as supports for PCM,three-dimensional carbon-based porous supporting material has attracted considerable attention ascribing to its high ther-mal conductivity,desirable loading capacity of PCMs,and excellent chemical compatibility with various PCMs.Therefore,this work systemically reviews the CPCMs with three-dimensional carbon-based porous supporting materials.First,a concise rule for the fabrication of CPCMs is illustrated in detail.Next,the experimental and computational research of carbon nanotube-based support,graphene-based support,graphite-based support and amorphous carbon-based support are reviewed.Then,the applications of the shape-stabilized CPCMs including thermal management and thermal conversion are illustrated.Last but not least,the challenges and prospects of the CPCMs are discussed.To conclude,introducing carbon-based porous materials can solve the liquid leakage issue and essentially improve the thermal conductivity of PCMs.However,there is still a long way to further develop a desirable CPCM with higher latent heat capacity,higher thermal conductivity,and more excellent shape stability.
基金funded by the National Natural Science Foundation of China (No. 52304133)the National Key R&D Program of China (No. 2022YFC3004605)the Department of Science and Technology of Liaoning Province (No. 2023-BS-083)。
文摘Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.
基金The National Natural Science Foundation of China(No.52338011).
文摘To investigate the wind⁃induced vibration re⁃sponse characteristics of multispan double⁃layer cable photo⁃voltaic(PV)support structures,wind tunnel tests using an aeroelastic model were carried out to obtain the wind⁃induced vibration response data of a three⁃span four⁃row double⁃layer cable PV support system.The wind⁃induced vibration characteristics with different PV module tilt angles,wind speeds,and wind direction angles were analyzed.The results showed that the double⁃layer cable large⁃span flexible PV support can effectively control the wind⁃induced vibration response and prevent the occur⁃rence of flutter under strong wind conditions.The maxi⁃mum value of the wind⁃induced vibration displacement of the flexible PV support system occurs in the windward first row.The upstream module has a significant shading effect on the downstream module,with a maximum effect of 23%.The most unfavorable wind direction angles of the structure are 0°and 180°.The change of the wind direction angle in the range of 0°to 30°has little effect on the wind vi⁃bration response.The change in the tilt angle of the PV modules has a greater impact on the wind vibration in the downwind direction and a smaller impact in the upwind di⁃rection.Special attention should be paid to the structural wind⁃resistant design of such systems in the upwind side span.
基金the National Key Research and Development Program of China(2021YFC2900300)the Natural Science Foundation of Guangdong Province(2024A1515030216)+2 种基金MOST Special Fund from State Key Laboratory of Geological Processes and Mineral Resources,China University of Geosciences(GPMR202437)the Guangdong Province Introduced of Innovative R&D Team(2021ZT09H399)the Third Xinjiang Scientific Expedition Program(2022xjkk1301).
文摘The application of machine learning for pyrite discrimination establishes a robust foundation for constructing the ore-forming history of multi-stage deposits;however,published models face challenges related to limited,imbalanced datasets and oversampling.In this study,the dataset was expanded to approximately 500 samples for each type,including 508 sedimentary,573 orogenic gold,548 sedimentary exhalative(SEDEX)deposits,and 364 volcanogenic massive sulfides(VMS)pyrites,utilizing random forest(RF)and support vector machine(SVM)methodologies to enhance the reliability of the classifier models.The RF classifier achieved an overall accuracy of 99.8%,and the SVM classifier attained an overall accuracy of 100%.The model was evaluated by a five-fold cross-validation approach with 93.8%accuracy for the RF and 94.9%for the SVM classifier.These results demonstrate the strong feasibility of pyrite classification,supported by a relatively large,balanced dataset and high accuracy rates.The classifier was employed to reveal the genesis of the controversial Keketale Pb-Zn deposit in NW China,which has been inconclusive among SEDEX,VMS,or a SEDEX-VMS transition.Petrographic investigations indicated that the deposit comprises early fine-grained layered pyrite(Py1)and late recrystallized pyrite(Py2).The majority voting classified Py1 as the VMS type,with an accuracy of RF and SVM being 72.2%and 75%,respectively,and confirmed Py2 as an orogenic type with 74.3% and 77.1%accuracy,respectively.The new findings indicated that the Keketale deposit originated from a submarine VMS mineralization system,followed by late orogenic-type overprinting of metamorphism and deformation,which is consistent with the geological and geochemical observations.This study further emphasizes the advantages of Machine learning(ML)methods in accurately and directly discriminating the deposit types and reconstructing the formation history of multi-stage deposits.
基金supported by the National Natural Science Foundation of China(Nos.22178388 and 22108306)Taishan Scholars Program of Shandong Province(No.tsqn201909065)Chongqing Science and Technology Bureau(No.cstc2019jscx-gksb X0032).
文摘Structural regulation of Pd-based electrocatalytic hydrodechlorination(EHDC)catalyst for constructing high-efficient cathode materials with low noble metal content and high atom utilization is crucial but still challenging.Herein,a support electron inductive effect of Pd-Mn/Ni foam catalyst was proposed via in-situ Mn doping to optimize the electronic structure of the Ni foam(NF),which can inductive regulation of Pd for improving the EHDC performance.The mass activity and current efficiency of Pd-Mn/NF catalyst are 2.91 and 1.34 times superior to that of Pd/NF with 2,4-dichlorophenol as model compound,respectively.The Mn-doped interlayer optimized the electronic structure of Pd by bringing the d-state closer to the Fermi level than Pd on the NF surface,which optimizied the binding of EHDC intermediates.Additionally,the Mn-doped interlayer acted as a promoter for generating H∗and accelerating the EHDC reaction.This work presents a simple and effective regulation strategy for constructing high-efficient cathode catalyst for the EHDC of chlorinated organic compounds.
文摘BACKGROUND Hepatocellular carcinoma ranks among the most prevalent malignant neoplasms.Surgical intervention constitutes a critical therapeutic approach for this condition.Nonetheless,postoperative recovery is frequently influenced by the patient's nutritional status and the quality of nursing care provided.AIM To examine the comprehensive impact of personalized nutritional support and nursing strategies on the postoperative rehabilitation of patients with liver cancer.METHODS In this study,a retrospective comparative analysis was conducted involving 60 post-operative liver cancer patients.The subjects were selected as subjects and divided into two groups based on differing nursing interventions,with each group comprising 30 patients.The control group received standard nutritional support and care,whereas the experimental group received individualized nutritional support and nursing strategies.The study aimed to evaluate the impact of individualized nutrition by comparing the rehabilitation indices,nutritional status,quality of life(QoL),and complication rates between the two groups.RESULTS The results showed that the recovery index of the experimental group was significantly better than that of the control group 2 weeks after surgery,and the average liver function recovery index of the experimental group was 85.significantly higher than that of the control group(73.67±7.19).In terms of nutritional status,the serum albumin level and body weight stabilization rate of the experimental group were also significantly higher than those of the control group,which were 42.33±2.4 g/L and 93.3%,respectively,compared with 36.01±3.85 g/L and 76.7%of the control group.In addition,the average QoL score of the experimental group was 84.66±3.7 points,which was significantly higher than that of the control group(70.92±4.28 points).At the psychological level,the average anxiety score of the experimental group was 1.17±0.29,and the average depression score was 1.47±0.4,which were significantly lower than the 2.26±0.42 and 2.57±0.45 of the control group.This showed that patients in the experimental group were better relieved of anxiety and depression under the individualized nutrition support and nursing strategy.More importantly,the complication rate in the experimental group was only 10%,much lower than the 33.3%in the control group.CONCLUSION Personalized nutritional support and tailored nursing strategies significantly enhance the postoperative rehabilitation of liver cancer patients.Consequently,it is recommended to implement and advocate for these individualized approaches to improve both the recovery outcomes and QoL for these patients.
基金funded by the Natural Science Foundation of China(Grant Nos.42377164 and 41972280)the Badong National Observation and Research Station of Geohazards(Grant No.BNORSG-202305).
文摘Landslide susceptibility prediction(LSP)is significantly affected by the uncertainty issue of landslide related conditioning factor selection.However,most of literature only performs comparative studies on a certain conditioning factor selection method rather than systematically study this uncertainty issue.Targeted,this study aims to systematically explore the influence rules of various commonly used conditioning factor selection methods on LSP,and on this basis to innovatively propose a principle with universal application for optimal selection of conditioning factors.An'yuan County in southern China is taken as example considering 431 landslides and 29 types of conditioning factors.Five commonly used factor selection methods,namely,the correlation analysis(CA),linear regression(LR),principal component analysis(PCA),rough set(RS)and artificial neural network(ANN),are applied to select the optimal factor combinations from the original 29 conditioning factors.The factor selection results are then used as inputs of four types of common machine learning models to construct 20 types of combined models,such as CA-multilayer perceptron,CA-random forest.Additionally,multifactor-based multilayer perceptron random forest models that selecting conditioning factors based on the proposed principle of“accurate data,rich types,clear significance,feasible operation and avoiding duplication”are constructed for comparisons.Finally,the LSP uncertainties are evaluated by the accuracy,susceptibility index distribution,etc.Results show that:(1)multifactor-based models have generally higher LSP performance and lower uncertainties than those of factors selection-based models;(2)Influence degree of different machine learning on LSP accuracy is greater than that of different factor selection methods.Conclusively,the above commonly used conditioning factor selection methods are not ideal for improving LSP performance and may complicate the LSP processes.In contrast,a satisfied combination of conditioning factors can be constructed according to the proposed principle.
基金Supported by the Central Funds Guiding the Local Science and Technology Development,No.202207AB110017Key Research and Development Program of Yunnan,No.202302AD080004+1 种基金Yunnan Academician and Expert Workstation,No.202205AF150023the Scientific and Technological Innovation Team in Kunming Medical University,No.CXTD202215.
文摘The complex pathophysiology and diverse manifestations of esophageal disorders pose challenges in clinical practice,particularly in achieving accurate early diagnosis and risk stratification.While traditional approaches rely heavily on subjective interpretations and variable expertise,machine learning(ML)has emerged as a transformative tool in healthcare.We conducted a comprehensive review of published literature on ML applications in esophageal diseases,analyzing technical approaches,validation methods,and clinical outcomes.ML demonstrates superior performance:In gastroesophageal reflux disease,ML models achieve 80%-90%accuracy in potential of hydrogen-impedance analysis and endoscopic grading;for Barrett’s esophagus,ML-based approaches show 88%-95% accuracy in invasive diagnostics and 77%-85% accuracy in non-invasive screening.In esophageal cancer,ML improves early detection and survival prediction by 6%-10% compared to traditional methods.Novel applications in achalasia and esophageal varices demonstrate promising results in automated diagnosis and risk stratification,with accuracy rates exceeding 85%.While challenges persist in data standardization,model interpretability,and clinical integration,emerging solutions in federated learning and explainable artificial intelligence offer promising pathways forward.The continued evolution of these technologies,coupled with rigorous validation and thoughtful implementation,may fundamentally transform our approach to esophageal disease management in the era of precision medicine.
