In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with l...In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.展开更多
With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy...With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.展开更多
Weight loss,whether resulting from disease-related conditions or intentional interventions,has been increasingly recognized as a significant risk factor for compromised skeletal integrity.While moderate weight reducti...Weight loss,whether resulting from disease-related conditions or intentional interventions,has been increasingly recognized as a significant risk factor for compromised skeletal integrity.While moderate weight reduction may yield metabolic benefits,rapid or sustained weight loss is frequently associated with decreased bone mineral density,deterioration of bone microarchitecture,and heightened fracture risk.The mechanisms underlying weight loss–induced bone loss are complex and multifactorial.Emerging evidence highlights a range of contributing factors,including reduced mechanical loading,increased bone marrow adiposity,hormonal and endocrine alterations,nutritional deficiencies,and disruptions in energy metabolism.These mechanisms are intricately interconnected,ultimately impairing bone remodeling and homeostatic balance.In this review,we provide a comprehensive analysis of the current literature on the mechanistic pathways,clinical consequences,and therapeutic strategies related to weight loss–induced bone loss.We further differentiate the skeletal effects of disease-associated versus interventioninduced weight loss,with a focus on their distinct molecular underpinnings.Our goal is to offer novel insights into the optimization of bone health management in the context of weight loss,guided by a translational medicine perspective.展开更多
The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore how young people respond to the increasing focus on body weight management.As obesity rates climb,body weigh...The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore how young people respond to the increasing focus on body weight management.As obesity rates climb,body weight management has become a growing concern in China.The government is introducing targeted policies,hospitals are setting up dedicated clinics,and health experts are speaking out.But weight is no longer just a medical issue-it’s increas-ingly tied to identity,confidence,and social image.We examine the cultural forces shaping how young people in China and Africa approach weight-what drives their choices,how ideals are formed,and where health meets appearance in today’s shifting societies.展开更多
In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,...In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,and artificial weak negative anomalies form around the positive anomalies in the horizontal direction,resulting in a reduction in the overall resolution.To fully utilize the model weighting function,this study constructs a combined model weighting function.First,a new depth weighting function is constructed by adding a regulator into the conventional depth weighting function to overcome the skin eff ect and inhibit the divergence at the deep area of the inversion results.A horizontal weighting function is then constructed by extracting information from the observation data;this function can suppress the formation of artificial weak anomalies and improve the horizontal resolution of the inversion results.Finally,these two functions are coupled to obtain the combined model weighting function,which can replace the conventional depth weighting function in 3D inversion.It improves the vertical and horizontal resolution of the inversion results without increasing the algorithm complexity and calculation amount,is easy to operate,and adapts to any 3D inversion method.Two model experiments are designed to verify the effectiveness,practicability,and anti-noise of the combined model weighting function.Then the function is applied to the 3D inversion of the measured aeromagnetic data in the Jinchuan area in China.The obtained inversion results are in good agreement with the known geological data.展开更多
We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training ph...We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.展开更多
Rice grain yield is primarily determined by three key agronomic traits:panicle number,grain number per panicle,and grain weight(GW).However,the inherent tradeoffs among these yield components remain a persistent chall...Rice grain yield is primarily determined by three key agronomic traits:panicle number,grain number per panicle,and grain weight(GW).However,the inherent tradeoffs among these yield components remain a persistent challenge in rice breeding programs.Notably,compared with GW,brown rice weight(BRW)provides a more direct metric associated with actual grain yield potential.In this study,we conducted a two-year replicated genome-wide association study to elucidate the genetic architecture of BRW and identify new loci regulating GW.Among seven consistently detected loci across experimental replicates,four were not co-localized with previously reported genes associated with BRW or GW traits.BRW1.1,one of the four newly identified loci,was found to encode a novel RNA-binding protein.Functional characterization revealed that BRW1.1 acts as a negative regulator of BRW,potentially through modulating mRNA translation processes.Intriguingly,through integrated analysis of mutant phenotypes and haplotype variations,we demonstrated that BRW1.1 mediates the physiological tradeoff between GW and panicle number.This study not only delineates the genetic determinants of BRW but also identifies BRW1.1 as a promising molecular target for breaking the yield component tradeoff in precision rice breeding.展开更多
Background:Weight stigma is prevalent and has multiple sources,which have significant effects on individual,social,physical,and psychological health.This study evaluated the psychometric properties of the Thai version...Background:Weight stigma is prevalent and has multiple sources,which have significant effects on individual,social,physical,and psychological health.This study evaluated the psychometric properties of the Thai version of WeSEI to provide a valid tool to assess weight stigma in Thai young adults.Methods:A cross-sectional online survey recruited 517 Thai university students from October 2024 to May 2025.All participants completed demographic information and standardized self-reported instruments,including WeSEI,Depression,Anxiety,and Stress scale 21(DASS-21),Weight Self-Stigma Questionnaire(WSSQ),and Perceived Weight Stigma Scale(PWSS).The psychometric properties of the Thai version of WeSEI were examined via confirmatory factor analysis(CFA)with some validity indices.Results:The 7-factor structure of the Thai version of the WeSEI was supported across sex and weight status subgroups,indicating good construct validity.In addition,internal consistency(Cronbach’sα=0.972;McDonald’sω=0.972),convergent,and discriminant validity also indicated that the Thai version of the WeSEI had good psychometric properties and assessed weight stigma among young people in Thailand.Conclusions:Sound psychometric properties of the Thai adaptation of WeSEI allows the identification of various sources contributing to weight stigma and to identify those experiencing high levels of weight stigma.It also provides evidence to support targeted interventions to reduce weight stigma and its associated mental health impacts in further research.Further studies are necessary to explore the utilization of WeSEI for weight stigma in Thailand.展开更多
The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show...The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.展开更多
Growing regulatory demands for industrial safety and environmental protection in the chemical sector necessitate robust operational risk assessment to enhance management efficacy.Here,the HS Chemical Company is evalua...Growing regulatory demands for industrial safety and environmental protection in the chemical sector necessitate robust operational risk assessment to enhance management efficacy.Here,the HS Chemical Company is evaluated through a multidimensional framework encompassing market dynamics,macroeconomic factors,financial stability,governance,supply chains,and production safety.By integrating the Analytic Hierarchy Process(AHP)with entropy weighting,a hybrid weighting model that mitigates the limitations of singular methods is established.The analysis of this study identifies financial risk(weight:0.347)and production safety(weight:0.298)as dominant risk drivers.These quantitative insights offer a basis for resource prioritization and targeted risk mitigation strategies in chemical enterprises.展开更多
BACKGROUND The global incidence of metabolic dysfunction-associated steatotic liver disease(MASLD)has increased in recent years.It has already been demonstrated that exercise and weight change are associated with the ...BACKGROUND The global incidence of metabolic dysfunction-associated steatotic liver disease(MASLD)has increased in recent years.It has already been demonstrated that exercise and weight change are associated with the occurrence of MASLD;however,the association between weight fluctuation caused by different exercise intensities and the risk of MASLD remains to be studied.AIM To investigate the impact of weight fluctuation and physical activity intensity on the risk of MASLD prevalence.METHODS Data from the National Health and Nutrition Examination Survey database including five cycles from 2009 to 2018 were analyzed.The model included variables such as age,sex,and poverty income ratio.Weighted multivariate logistic regression was used to examine the influence of different weight fluctuation patterns within the two time intervals on the prevalence of MASLD.Nonparametric restricted cubic spline curves were used to analyze the non-linear relationship between net weight change and MASLD prevalence.RESULTS Among 3183 MASLD cases,the risk of MASLD increased with age for individuals transitioning from non-obese to obese or maintaining obesity,with odds ratio(OR)changing from 8.91(95%CI:7.40-10.88)and 11.87(95%CI:9.65-14.60)at 10 years before baseline to 9.58(95%CI:8.08-11.37)and 12.51(95%CI:9.33-16.78)at 25 years.Stable obesity correlated with age-dependent MASLD prevalence escalation,whereas increased physical activity attenuated MASLD risk in this group,with an OR changing from 13.64(95%CI:10.59-17.57)to 6.42(95%CI:4.24-9.72).Further analysis of the net weight changes revealed a paradoxical risk elevation with intensified physical activity during different time periods.CONCLUSION The risk of MASLD increases in individuals transitioning from non-obese to obese or maintaining obesity.Highintensity physical activity is beneficial for MASLD among individuals with stable obesity.展开更多
The weighted Drazin invertibility of rectangular matrixs over an arbitrary ring are studied.Some equivalent conditions and Characterizations are given for existence of the weighted Drazin inverse of a rectangular matr...The weighted Drazin invertibility of rectangular matrixs over an arbitrary ring are studied.Some equivalent conditions and Characterizations are given for existence of the weighted Drazin inverse of a rectangular matrix over an arbitrary ring.Moreover,the weighted Drazin inverse of a rectangular matrices product PAQ can be characterized and computed.This generalizes results obtained for the Drazin inverse of such product of square matrices.The results also apply to morphisms in(additive)categories.展开更多
Colorectal cancer is the most common cancer with a second mortality rate.Polyp lesion is a precursor symptom of colorectal cancer.Detection and removal of polyps can effectively reduce the mortality of patients in the...Colorectal cancer is the most common cancer with a second mortality rate.Polyp lesion is a precursor symptom of colorectal cancer.Detection and removal of polyps can effectively reduce the mortality of patients in the early period.However,mass images will be generated during an endoscopy,which will greatly increase the workload of doctors,and long-term mechanical screening of endoscopy images will also lead to a high misdiagnosis rate.Aiming at the problem that computer-aided diagnosis models deeply depend on the computational power in the polyp detection task,we propose a lightweight model,coordinate attention-YOLOv5-Lite-Prune,based on the YOLOv5 algorithm,which is different from state-of-the-art methods proposed by the existing research that applied object detection models or their variants directly to prediction task without any lightweight processing,such as faster region-based convolutional neural networks,YOLOv3,YOLOv4,and single shot multibox detector.The innovations of our model are as follows:First,the lightweight EfficientNetLite network is introduced as the new feature extraction network.Second,the depthwise separable convolution and its improved modules with different attention mechanisms are used to replace the standard convolution in the detection head structure.Then,theα-intersection over union loss function is applied to improve the precision and convergence speed of the model.Finally,the model size is compressed with a pruning algorithm.Our model effectively reduces parameter amount and computational complexity without significant accuracy loss.Therefore,the model can be successfully deployed on the embedded deep learning platform,and detect polyps with a speed above 30 frames per second,which means the model gets rid of the limitation that deep learning models must rely on high-performance servers.展开更多
Obesity affects over 1 billion people worldwide and is linked to more than 230 health complications,with cardiovascular disease being a leading cause of mortality.Losing 5%-10%of body weight is considered clinically s...Obesity affects over 1 billion people worldwide and is linked to more than 230 health complications,with cardiovascular disease being a leading cause of mortality.Losing 5%-10%of body weight is considered clinically significant for improving health.This weight loss can be achieved through pharmacotherapy,including glucagon-like peptide 1(GLP-1)receptor agonists,GLP-1/glucosedependent insulinotropic peptide dual receptor agonists,and GLP-1/glucosedependent insulinotropic peptide/glucagon triple receptor agonists(such as semaglutide,tirzepatide,and retatrutide,respectively).While much of the weight loss comes from fat mass,these treatments also result in the loss of lean mass,including muscle.This loss of muscle may contribute to difficulties in maintaining weight over the long term and can lead to sarcopenia.Therefore,the focus of new anti-obesity treatments should be primarily on reducing fat mass while minimizing the loss of muscle mass,ideally promoting muscle gain.Research focusing on human myocytes has identified more than 600 myokines associated with muscle contraction,which may play a crucial role in preserving both muscle mass and function.We explored the potential of new anti-obesity agents and their combinations with incretin-based therapies to achieve these outcomes.Further studies are needed to better understand the functional implications of lean mass expansion during weight loss and weight maintenance programs.展开更多
An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the ...An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0. 1 to 0. 3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density paritycheck（QC-LDPC） codes.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart ...Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid.It also possesses a better impact on averting overloading and permitting effective energy storage.Even though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized loss.To overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning algorithms.To accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data features.Then,the pre-processed data are taken for training and testing.Following that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in SG.Since PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed characteristics.The hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on prediction.Regression results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.展开更多
The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV imag...The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV images,which is inspired by the Retinex theory and guided by a light weighted map.Firstly,we propose a new network for reflectance component processing to suppress the noise in images.Secondly,we construct an illumination enhancement module that uses a light weighted map to guide the enhancement process.Finally,the processed reflectance and illumination components are recombined to obtain the enhancement results.Experimental results show that our method can suppress the noise in images while enhancing image brightness,and prevent over enhancement in bright regions.Code and data are available at https://gitee.com/baixiaotong2/uav-images.git.展开更多
Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia r...Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2500 g),normal birth weight(2500-3999 g),and macrosomia(≥4000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.展开更多
In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequen...In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.展开更多
文摘In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.
文摘With the increasing complexity of vehicular networks and the proliferation of connected vehicles,Federated Learning(FL)has emerged as a critical framework for decentralized model training while preserving data privacy.However,efficient client selection and adaptive weight allocation in heterogeneous and non-IID environments remain challenging.To address these issues,we propose Federated Learning with Client Selection and Adaptive Weighting(FedCW),a novel algorithm that leverages adaptive client selection and dynamic weight allocation for optimizing model convergence in real-time vehicular networks.FedCW selects clients based on their Euclidean distance from the global model and dynamically adjusts aggregation weights to optimize both data diversity and model convergence.Experimental results show that FedCW significantly outperforms existing FL algorithms such as FedAvg,FedProx,and SCAFFOLD,particularly in non-IID settings,achieving faster convergence,higher accuracy,and reduced communication overhead.These findings demonstrate that FedCW provides an effective solution for enhancing the performance of FL in heterogeneous,edge-based computing environments.
文摘Weight loss,whether resulting from disease-related conditions or intentional interventions,has been increasingly recognized as a significant risk factor for compromised skeletal integrity.While moderate weight reduction may yield metabolic benefits,rapid or sustained weight loss is frequently associated with decreased bone mineral density,deterioration of bone microarchitecture,and heightened fracture risk.The mechanisms underlying weight loss–induced bone loss are complex and multifactorial.Emerging evidence highlights a range of contributing factors,including reduced mechanical loading,increased bone marrow adiposity,hormonal and endocrine alterations,nutritional deficiencies,and disruptions in energy metabolism.These mechanisms are intricately interconnected,ultimately impairing bone remodeling and homeostatic balance.In this review,we provide a comprehensive analysis of the current literature on the mechanistic pathways,clinical consequences,and therapeutic strategies related to weight loss–induced bone loss.We further differentiate the skeletal effects of disease-associated versus interventioninduced weight loss,with a focus on their distinct molecular underpinnings.Our goal is to offer novel insights into the optimization of bone health management in the context of weight loss,guided by a translational medicine perspective.
文摘The Double Take column looks at a single topic from an African and Chinese perspective.This month,we explore how young people respond to the increasing focus on body weight management.As obesity rates climb,body weight management has become a growing concern in China.The government is introducing targeted policies,hospitals are setting up dedicated clinics,and health experts are speaking out.But weight is no longer just a medical issue-it’s increas-ingly tied to identity,confidence,and social image.We examine the cultural forces shaping how young people in China and Africa approach weight-what drives their choices,how ideals are formed,and where health meets appearance in today’s shifting societies.
基金jointly funded by the National Natural Science Foundation of China(No.U2244220,No.42004125)the China Geological Survey Projects(No.DD20240119,No.DD20243245,No.DD20230114,No.DD20243244)the China Postdoctoral Science Foundation(No.2020M670601)。
文摘In the 3D inversion modeling of gravity and magnetic potential field data,the model weighting function is often applied to overcome the skin eff ect of inversion results.However,divergence occurs at the the deep area,and artificial weak negative anomalies form around the positive anomalies in the horizontal direction,resulting in a reduction in the overall resolution.To fully utilize the model weighting function,this study constructs a combined model weighting function.First,a new depth weighting function is constructed by adding a regulator into the conventional depth weighting function to overcome the skin eff ect and inhibit the divergence at the deep area of the inversion results.A horizontal weighting function is then constructed by extracting information from the observation data;this function can suppress the formation of artificial weak anomalies and improve the horizontal resolution of the inversion results.Finally,these two functions are coupled to obtain the combined model weighting function,which can replace the conventional depth weighting function in 3D inversion.It improves the vertical and horizontal resolution of the inversion results without increasing the algorithm complexity and calculation amount,is easy to operate,and adapts to any 3D inversion method.Two model experiments are designed to verify the effectiveness,practicability,and anti-noise of the combined model weighting function.Then the function is applied to the 3D inversion of the measured aeromagnetic data in the Jinchuan area in China.The obtained inversion results are in good agreement with the known geological data.
基金supported by the Natural Science Research Project of Colleges and Universities in Anhui Province (No.KJ2021A0479)the Science Research Program of Anhui University of Finance and Economics (No.ACKYC22082)。
文摘We present a gain adaptive tuning method for fiber Raman amplifier(FRA) using two-stage neural networks(NNs) and double weights updates. After training the connection weights of two-stage NNs separately in training phase, the connection weights of the unified NN are updated again in verification phase according to error between the predicted and target gains to eliminate the inherent error of the NNs. The simulation results show that the mean of root mean square error(RMSE) and maximum error of gains are 0.131 d B and 0.281 d B, respectively. It shows that the method can realize adaptive adjustment function of FRA gain with high accuracy.
基金supported by the National Natural Science Foundation of China(Grant Nos.32000377,32172037,and 32472211)the Biological Breeding-National Science and Technology Major Project,China(Grant No.2023ZD04068)+2 种基金the Fundamental Research Funds for the Central Universities,China(Grant No.KJQN202103)the open funds of the State Key Laboratory of Crop Genetics&Germplasm Enhancement and Utilization,China(Grant No.ZW202401)the Cyrus Tang Innovation Center for Crop Seed Industry,China.
文摘Rice grain yield is primarily determined by three key agronomic traits:panicle number,grain number per panicle,and grain weight(GW).However,the inherent tradeoffs among these yield components remain a persistent challenge in rice breeding programs.Notably,compared with GW,brown rice weight(BRW)provides a more direct metric associated with actual grain yield potential.In this study,we conducted a two-year replicated genome-wide association study to elucidate the genetic architecture of BRW and identify new loci regulating GW.Among seven consistently detected loci across experimental replicates,four were not co-localized with previously reported genes associated with BRW or GW traits.BRW1.1,one of the four newly identified loci,was found to encode a novel RNA-binding protein.Functional characterization revealed that BRW1.1 acts as a negative regulator of BRW,potentially through modulating mRNA translation processes.Intriguingly,through integrated analysis of mutant phenotypes and haplotype variations,we demonstrated that BRW1.1 mediates the physiological tradeoff between GW and panicle number.This study not only delineates the genetic determinants of BRW but also identifies BRW1.1 as a promising molecular target for breaking the yield component tradeoff in precision rice breeding.
基金Hualien Tzu-Chi Hospital of the Buddhist Tzu Chi Medical Foundation.
文摘Background:Weight stigma is prevalent and has multiple sources,which have significant effects on individual,social,physical,and psychological health.This study evaluated the psychometric properties of the Thai version of WeSEI to provide a valid tool to assess weight stigma in Thai young adults.Methods:A cross-sectional online survey recruited 517 Thai university students from October 2024 to May 2025.All participants completed demographic information and standardized self-reported instruments,including WeSEI,Depression,Anxiety,and Stress scale 21(DASS-21),Weight Self-Stigma Questionnaire(WSSQ),and Perceived Weight Stigma Scale(PWSS).The psychometric properties of the Thai version of WeSEI were examined via confirmatory factor analysis(CFA)with some validity indices.Results:The 7-factor structure of the Thai version of the WeSEI was supported across sex and weight status subgroups,indicating good construct validity.In addition,internal consistency(Cronbach’sα=0.972;McDonald’sω=0.972),convergent,and discriminant validity also indicated that the Thai version of the WeSEI had good psychometric properties and assessed weight stigma among young people in Thailand.Conclusions:Sound psychometric properties of the Thai adaptation of WeSEI allows the identification of various sources contributing to weight stigma and to identify those experiencing high levels of weight stigma.It also provides evidence to support targeted interventions to reduce weight stigma and its associated mental health impacts in further research.Further studies are necessary to explore the utilization of WeSEI for weight stigma in Thailand.
文摘The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.
文摘Growing regulatory demands for industrial safety and environmental protection in the chemical sector necessitate robust operational risk assessment to enhance management efficacy.Here,the HS Chemical Company is evaluated through a multidimensional framework encompassing market dynamics,macroeconomic factors,financial stability,governance,supply chains,and production safety.By integrating the Analytic Hierarchy Process(AHP)with entropy weighting,a hybrid weighting model that mitigates the limitations of singular methods is established.The analysis of this study identifies financial risk(weight:0.347)and production safety(weight:0.298)as dominant risk drivers.These quantitative insights offer a basis for resource prioritization and targeted risk mitigation strategies in chemical enterprises.
基金Supported by National Natural Science Foundation of China,No.82474378Shanghai Natural Science Foundation,No.22ZR1455900+4 种基金Shanghai Municipal Health Planning Commission Clinical Research Specialized Face Project,No.201940449Key Project of Science and Technology Innovation Program of Shanghai Putuo District Health and Health System,No.ptkwws202201Reserve Excellent Chinese Medicine Talent Program of Shanghai University of Traditional Chinese Medicine,No.20D-RC-02Apricot Grove,Shanghai Putuo District Excellent Young Talent Training Program,No.ptxlyq2201Shanghai Putuo District Health and Health System Characteristic Specialty Disease Construction Project,No.2023tszb01.
文摘BACKGROUND The global incidence of metabolic dysfunction-associated steatotic liver disease(MASLD)has increased in recent years.It has already been demonstrated that exercise and weight change are associated with the occurrence of MASLD;however,the association between weight fluctuation caused by different exercise intensities and the risk of MASLD remains to be studied.AIM To investigate the impact of weight fluctuation and physical activity intensity on the risk of MASLD prevalence.METHODS Data from the National Health and Nutrition Examination Survey database including five cycles from 2009 to 2018 were analyzed.The model included variables such as age,sex,and poverty income ratio.Weighted multivariate logistic regression was used to examine the influence of different weight fluctuation patterns within the two time intervals on the prevalence of MASLD.Nonparametric restricted cubic spline curves were used to analyze the non-linear relationship between net weight change and MASLD prevalence.RESULTS Among 3183 MASLD cases,the risk of MASLD increased with age for individuals transitioning from non-obese to obese or maintaining obesity,with odds ratio(OR)changing from 8.91(95%CI:7.40-10.88)and 11.87(95%CI:9.65-14.60)at 10 years before baseline to 9.58(95%CI:8.08-11.37)and 12.51(95%CI:9.33-16.78)at 25 years.Stable obesity correlated with age-dependent MASLD prevalence escalation,whereas increased physical activity attenuated MASLD risk in this group,with an OR changing from 13.64(95%CI:10.59-17.57)to 6.42(95%CI:4.24-9.72).Further analysis of the net weight changes revealed a paradoxical risk elevation with intensified physical activity during different time periods.CONCLUSION The risk of MASLD increases in individuals transitioning from non-obese to obese or maintaining obesity.Highintensity physical activity is beneficial for MASLD among individuals with stable obesity.
文摘The weighted Drazin invertibility of rectangular matrixs over an arbitrary ring are studied.Some equivalent conditions and Characterizations are given for existence of the weighted Drazin inverse of a rectangular matrix over an arbitrary ring.Moreover,the weighted Drazin inverse of a rectangular matrices product PAQ can be characterized and computed.This generalizes results obtained for the Drazin inverse of such product of square matrices.The results also apply to morphisms in(additive)categories.
基金the National Natural Science Foundation of China(Nos.81971767,62103263 and 62103267)the Shanghai Science and Technology Commission(Nos.19142203800,19441913800 and 19441910600)。
文摘Colorectal cancer is the most common cancer with a second mortality rate.Polyp lesion is a precursor symptom of colorectal cancer.Detection and removal of polyps can effectively reduce the mortality of patients in the early period.However,mass images will be generated during an endoscopy,which will greatly increase the workload of doctors,and long-term mechanical screening of endoscopy images will also lead to a high misdiagnosis rate.Aiming at the problem that computer-aided diagnosis models deeply depend on the computational power in the polyp detection task,we propose a lightweight model,coordinate attention-YOLOv5-Lite-Prune,based on the YOLOv5 algorithm,which is different from state-of-the-art methods proposed by the existing research that applied object detection models or their variants directly to prediction task without any lightweight processing,such as faster region-based convolutional neural networks,YOLOv3,YOLOv4,and single shot multibox detector.The innovations of our model are as follows:First,the lightweight EfficientNetLite network is introduced as the new feature extraction network.Second,the depthwise separable convolution and its improved modules with different attention mechanisms are used to replace the standard convolution in the detection head structure.Then,theα-intersection over union loss function is applied to improve the precision and convergence speed of the model.Finally,the model size is compressed with a pruning algorithm.Our model effectively reduces parameter amount and computational complexity without significant accuracy loss.Therefore,the model can be successfully deployed on the embedded deep learning platform,and detect polyps with a speed above 30 frames per second,which means the model gets rid of the limitation that deep learning models must rely on high-performance servers.
文摘Obesity affects over 1 billion people worldwide and is linked to more than 230 health complications,with cardiovascular disease being a leading cause of mortality.Losing 5%-10%of body weight is considered clinically significant for improving health.This weight loss can be achieved through pharmacotherapy,including glucagon-like peptide 1(GLP-1)receptor agonists,GLP-1/glucosedependent insulinotropic peptide dual receptor agonists,and GLP-1/glucosedependent insulinotropic peptide/glucagon triple receptor agonists(such as semaglutide,tirzepatide,and retatrutide,respectively).While much of the weight loss comes from fat mass,these treatments also result in the loss of lean mass,including muscle.This loss of muscle may contribute to difficulties in maintaining weight over the long term and can lead to sarcopenia.Therefore,the focus of new anti-obesity treatments should be primarily on reducing fat mass while minimizing the loss of muscle mass,ideally promoting muscle gain.Research focusing on human myocytes has identified more than 600 myokines associated with muscle contraction,which may play a crucial role in preserving both muscle mass and function.We explored the potential of new anti-obesity agents and their combinations with incretin-based therapies to achieve these outcomes.Further studies are needed to better understand the functional implications of lean mass expansion during weight loss and weight maintenance programs.
基金The National High Technology Research and Development Program of China (863Program) ( No2009AA01Z235,2006AA01Z263)the Research Fund of the National Mobile Communications Research Laboratory of Southeast University(No2008A10)
文摘An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0. 1 to 0. 3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density paritycheck（QC-LDPC） codes.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
基金Prince Sattam bin Abdulaziz University project number(PSAU/2023/R/1445)。
文摘Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid infrastructure.Analyzing the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the grid.It also possesses a better impact on averting overloading and permitting effective energy storage.Even though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized loss.To overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning algorithms.To accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data features.Then,the pre-processed data are taken for training and testing.Following that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in SG.Since PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed characteristics.The hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on prediction.Regression results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.
基金supported by the National Natural Science Foundation of China(Nos.62201454 and 62306235)the Xi’an Science and Technology Program of Xi’an Science and Technology Bureau(No.23SFSF0004)。
文摘The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV images,which is inspired by the Retinex theory and guided by a light weighted map.Firstly,we propose a new network for reflectance component processing to suppress the noise in images.Secondly,we construct an illumination enhancement module that uses a light weighted map to guide the enhancement process.Finally,the processed reflectance and illumination components are recombined to obtain the enhancement results.Experimental results show that our method can suppress the noise in images while enhancing image brightness,and prevent over enhancement in bright regions.Code and data are available at https://gitee.com/baixiaotong2/uav-images.git.
文摘Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2500 g),normal birth weight(2500-3999 g),and macrosomia(≥4000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.
基金Supported by the National Natural Science Foundation of China(12301101)the Guangdong Basic and Applied Basic Research Foundation(2022A1515110019 and 2020A1515110585)。
文摘In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.
