Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—esp...Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.展开更多
A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportion...A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportional feedforward controller based on fuzzy set-point weighting following and a limited semi-integrator（LSI）, are designed respectively. LSI is used to limit output signal and to prevent wind up at the low frequency of the spectrum. By using a range camera and an electronic feedback control, the tip damping on the HCBS can be adjusted artificially. A collaborative control simulation technique of HOPSAN and MATLAB/SIMULINK is applied to the controller design. Simulation results show that the proposed PI control system has less overshoot as well as faster response. The tip damping on the HCBS during operation is improved.展开更多
The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission ...The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).展开更多
As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for s...As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for solving FJSP in the literature are population-based evolutionary algorithms,which are complex and time-consuming.In this paper,we propose a fast effective singlesolution based local search algorithm with an innovative adaptive weighting-based local search(AWLS)technique for solving FJSP.The adaptive weighting technique assigns weights to each operation and adaptively updates them during the exploration.AWLS integrates a Tabu Search strategy and the adaptive weighting technique to smooth the landscape of the search space and enhance the exploration diversity.Computational experiments on 313 well-known benchmark instances demonstrate that AWLS is highly competitive with state-of-the-art algorithms in terms of both solution quality and computational efficiency,despite of its simplicity.Specifically,AWLS improves the previous best-known results in the literature on 33 instances and match the best-known results on the remaining ones except for only one under the same time limit of up to 300 s.As a strongly non-deterministic polynomia(NP)-hard problem which has been extensively studied for nearly half a century,breaking the records on these classic instances is an arduous task.Nevertheless,AWLS establishes new records on 8 challenging instances whose previous best records were established by a state-of-the-art meta-heuristic algorithm and a famous industrial solver.展开更多
Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesit...Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesity drug alone or combined with exercise training on body weight,body fat,fat-free mass and cardiorespiratory fitness in obese patients were retrieved from Pubmed and EMBASE up to May 2024.Risk of bias assessment was performed with RoB 2.0,and the GRADE approach assessed the certainty of evidence(CoE)of each main outcome.We included four publications summing up 202 patients.Two publications used orlistat as an anti-obesity drug treatment,while the other two adopted GLP-1 receptor agonist(liraglutide or tirzepatide)as a pharmacotherapy for weight management.Orlistat combined with exercise was superior to change body weight(mean difference(MD):−2.27 kg;95%CI:−2.86 to−1.69;CoE:very low),fat mass(MD:−2.89;95%CI:−3.87 to−1.91;CoE:very low),fat-free mass(MD:0.56;95%CI:0.40–0.72;CoE:very low),and VO_(2)Peak(MD:2.64;95%CI:2.52–2.76;CoE:very low).GLP-1 receptor agonist drugs combined with exercise had a great effect on body weight(MD:−3.96 kg;95%CI:−5.07 to−2.85;CoE:low),fat mass(MD:−1.76;95%CI:−2.24 to−1.27;CoE:low),fat-free mass(MD:0.50;95%CI:−0.98 to 1.98;CoE:very low)and VO_(2)Peak(MD:2.47;95%CI:1.31–3.63;CoE:very low).The results reported here suggest that exercise training remains an important approach in weight management when combined with pharmacological treatment.展开更多
In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilizati...In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.展开更多
The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland syst...The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland systems.Taking the typical black soil region in Northeast China(TBSN)as an example,this paper combined the concept of‘quantity-quality-ecology as a whole’protection with crop-land systems health,constructed a health assessment model for cropland systems,and used Google Earth Engine to conduct a quantitat-ive analysis of the temporal and spatial evolution of cropland systems health in TBSN during 2003–2023.By coupling the geographical detector and the Multi-scale Geographically Weighted Regression(MGWR)model,the driving factors of cropland health changes were explored.The study finds that during the research period,the health status of cropland systems in TBSN showed a slight downward trend,and the distribution pattern of cropland systems health gradually shifted from‘better in the east’to‘high in the northeast and low in the southwest’.Changes in average annual sunshine duration,relative humidity,and precipitation had a significant impact on the spa-tial differentiation of cropland systems health in the early stages,and were considered as dominant factors.Meanwhile,the influence of dual dominant factors in the natural environment on cropland systems health is increasing.Furthermore,the MGWR model performed better in revealing the complex relationships between natural and social factors and changes in cropland systems health,demonstrating the significant spatial heterogeneity of the impacts of natural environment and human activities on cropland systems health.The re-search can provide scientific guidance for the sustainable development of TBSN and formulate more precise and effective cropland pro-tection policies.展开更多
Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small targe...Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.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
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
In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heati...In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.展开更多
Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in...Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.展开更多
Human pose estimation is a challenging task in computer vision.Most algorithms perform well in regular scenes,but lack good performance in occlusion scenarios.Therefore,we propose a multi-type feature fusion network b...Human pose estimation is a challenging task in computer vision.Most algorithms perform well in regular scenes,but lack good performance in occlusion scenarios.Therefore,we propose a multi-type feature fusion network based on importance weighting,which consists of three modules.In the first module,we propose a multi-resolution backbone with two feature enhancement sub-modules,which can extract features from different scales and enhance the feature expression ability.In the second module,we enhance the expressiveness of keypoint features by suppressing obstacle features and compensating for the unique and shared attributes of keypoints and topology.In the third module,we perform importance weighting on the adjacency matrix to enable it to describe the correlation among nodes,thereby improving the feature extraction ability.We conduct comparative experiments on the keypoint detection datasets of common objects in Context 2017(COCO2017),COCO-Wholebody and CrowdPose,achieving the accuracy of 78.9%,67.1%and 77.6%,respectively.Additionally,a series of ablation experiments are designed to show the performance of our work.Finally,we present the visualization of different scenarios to verify the effectiveness of our work.展开更多
Purpose–To systematically characterize and objectively evaluate basic railway safety management capability,creating a closed-loop management approach which allows continuous improvement and optimization.Design/method...Purpose–To systematically characterize and objectively evaluate basic railway safety management capability,creating a closed-loop management approach which allows continuous improvement and optimization.Design/methodology/approach–A basic railway safety management capability evaluation index system based on a comprehensive analysis of national safety management standards,railway safety rules and regulations and existing safety data from railway transport enterprises is presented.The system comprises a guideline layer including safety committee formation,work safety responsibility,safety management organization and safety rules and regulations as its components,along with an index layer consisting of 12 quantifiable indexes.Game theory combination weighting is utilized to integrate subjective and objective weight values derived using AHP and CRITIC methods and further combined using the TOPSIS method in order to construct a comprehensive basic railway safety management capability evaluation model.Findings–The case study presented demonstrates that this evaluation index system and comprehensive evaluation model are capable of effectively characterizing and evaluating basic railway safety management capability and providing directional guidance for its sustained improvement.Originality/value–Construction of an evaluation index system that is quantifiable,generalizable and accessible,accurately reflects the main aspects of railway transportation enterprises’basic safety management capability and provides interoperability across various railway transportation enterprises.The application of the game theoretic combination weighting method to derive composite weights which combine experts’subjective evaluations with the objectivity of data.展开更多
BACKGROUND Cotadutide(MEDI0382)is a twincretin that acts as an agonist for both the glucagon-like peptide-1 and glucagon receptors.Several randomized controlled trials(RCTs)have been published evaluating the use of co...BACKGROUND Cotadutide(MEDI0382)is a twincretin that acts as an agonist for both the glucagon-like peptide-1 and glucagon receptors.Several randomized controlled trials(RCTs)have been published evaluating the use of cotadutide in individuals with type 2 diabetes(T2D),showing promising results.However,the efficacy and safety of the drug use have been inadequately explored by systematic reviews and meta-analyses.AIM To assess the clinical efficacy and safety of cotadutide in individuals with T2D having overweight or obesity.METHODS The systematic reviews and meta-analyses have been registered with International Prospective Register of Systematic Reviews(CRD42024511703),and the protocol summary can be accessed online.Several databases and registries,including MEDLINE(via PubMed),Scopus,Web of Science,the Cochrane Central Register of Controlled Trials,and ClinicalTrials.gov,were systematically searched using related terms from their inception to May 15,2025,for RCTs involving individuals with T2D receiving cotadutide in the intervention group.Review Manager web was used to conduct meta-analysis using random-effects models.The co-primary outcomes of interest were the changes in glycated hemoglobin(HbA1c)and the percent changes in body weight from baseline.The results of the outcomes were expressed as mean differences(MDs)or risk ratios(RRs)with 95%confidence intervals(CIs).The analysis of outcomes was stratified according to whether the control group received a placebo,denoted as the placebo control group(PCG),or an active comparator,referred to as the active control group(ACG).RESULTS Nine RCTs(mostly phase 2 RCTs,n=1525)with study durations varying from 28 days to 54 weeks that met all the inclusion criteria were analyzed;five studies had a low overall risk of bias,while the other four had some concerns.Compared to the PCG,greater reductions in HbA1c were achieved with cotadutide 100μg(MD-0.77%,95%CI:-1.06 to-0.47),200μg(MD-0.68%,95%CI:-1.12 to-0.23),300μg(MD-0.67%,95%CI:-0.79 to-0.56),and 600μg(MD-0.69%,95%CI:-0.97 to-0.41).Cotadutide 100μg(MD-1.74%,95%CI:-3.23 to-0.25),200μg(MD-2.56%,95%CI:-3.37 to-1.75),300μg(MD-3.49%,95%CI:-4.14 to-2.84),and 600μg(MD-5.45%,95%CI:-7.17 to-3.73)achieved greater percent reductions in body weight from baseline.However,the certainty of evidence for HbA1c and percent body weight reductions was very low to low.Cotadutide,at all doses,also outperformed PCG in reducing fasting plasma glucose and absolute body weight.The changes in HbA1c,percent body weight,fasting plasma glucose,and absolute body weight were similar between the cotadutide group and the ACG.Compared to PCG,pooled doses of cotadutide increased the risks of treatment-emergent adverse events(AEs),treatment-related AEs,and discontinuation of the study drug due to AEs,but not for serious AEs.More subjects experienced overall gastrointestinal AEs,dyspepsia,nausea,vomiting,constipation,and decreased appetite with cotadutide than with PCG.Compared to the ACG,none of the AEs showed increased risk in the cotadutide group.CONCLUSION Cotadutide demonstrated glycemic control and weight-loss benefits in short-term,small RCTs(mostly phase 2).However,small sample sizes,very low to low certainty of evidence,and the absence of data on long-term cardiovascular and renal outcomes highlight substantial uncertainties,warranting cautious interpretation and further investigation in larger,longer-term trials to establish its safety and efficacy profile.展开更多
The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associa...The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associations between exposure to PM_(2.5) and PM10 and birth weight.A total of 74 studies were identified through searches in Web of Science,PubMed,Embase,and Ovid Medline,as well as manual searches,up to October 2024.We found that for each 10μg/m^(3) increase in PM_(2.5),the risk of low birth weight(LBW)increased significantly during the entire pregnancy(odds ratio[OR]=2.41,95%confidence interval[CI]:1.99–2.91)and in all trimesters.Similarly,for every 10μg/m^(3) increase in PM10 concentration,the risk of LBW increased significantly during the entire pregnancy(OR=1.46,95%CI:1.16–1.84).Subgroup analysis by maternal age for PM_(2.5) showed that mothers aged 30 and above had a significantly higher risk of LBW(OR=3.69,95%CI:2.81–4.84),compared with those under 30.In conclusion,maternal exposure to PM_(2.5) and PM_(10) is associated with an increased risk of LBW across all trimesters.Additionally,mothers aged 30 and above are at a higher risk of LBW,compared with younger mothers.Further research is needed to clarify the biological mechanisms by which PM pollution may contribute to LBW.展开更多
Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extracti...Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extraction of numerous repetitive features,thereby reducing the accuracy of image retrieval.This article proposes an indoor visual localization method based on semantic segmentation and adaptive weight fusion to address the issue of ground texture interference with retrieval results.During the positioning process,an indoor semantic segmentation model is established.Semantic segmentation technology is applied to accurately delineate the ground portion of the images.Fea-ture extraction is performed on both the original database and the ground-segmented database.The vector of locally aggregated descriptors(VLAD)algorithm is then used to convert image features into a fixed-length feature representation,which improves the efficiency of image retrieval.Simul-taneously,a method for adaptive weight optimization in similarity calculation is proposed,using a-daptive weights to compute similarity for different regional features,thereby improving the accuracy of image retrieval.The experimental results indicate that this method significantly reduces ground interference and effectively utilizes ground information,thereby improving the accuracy of image retrieval.展开更多
BACKGROUND Attention-deficit hyperactivity disorder(ADHD)and its pharmacological treatments may influence growth in children and adolescents.This meta-analysis aimed to clarify their effects on the physical developmen...BACKGROUND Attention-deficit hyperactivity disorder(ADHD)and its pharmacological treatments may influence growth in children and adolescents.This meta-analysis aimed to clarify their effects on the physical development,especially weight and height.AIM To investigate the effects of ADHD and its treatment on growth in children and adolescents.METHODS Researchers reviewed 18 studies published up to September 2023 from databases such as PubMed,EMBASE,Cochrane,and Web of Science.They analyzed changes in body weight,height,and body mass index(BMI)before and after ADHD treatment,along with the risks of overweight and obesity.RESULTS Children with ADHD undergoing long-term medication therapy showed decreased actual weight[weighted mean difference(WMD)=-9.50]and height(WMD=-0.15),along with a slight increase in weight standard deviation scores(WMD=0.23)and height z scores(WMD=0.10).BMI showed a non-significant downward trend(WMD=-1.72).Regarding overweight and obesity risks,the pooled odds ratios were 1.37 and 1.16,respectively,but these were not statistically significant.CONCLUSION Overall,the study suggests that long-term pharmacological treatment for ADHD may be associated with reduced growth in weight and height among young patients.However,no clear link was found between ADHD and increased risk of overweight or obesity.These findings highlight the importance of monitoring growth in children receiving medication for ADHD.展开更多
BACKGROUND Type 2 diabetes(T2D)is a major health concern globally and its prevalence is expected to continue to escalate.Lifestyle intervention is an integral part of T2D management.Meal replacements are often used as...BACKGROUND Type 2 diabetes(T2D)is a major health concern globally and its prevalence is expected to continue to escalate.Lifestyle intervention is an integral part of T2D management.Meal replacements are often used as part of lifestyle intervention programs in T2D and weight management programs.There are various trials being carried out to date;however,a thorough review regarding the usage of meal replacement on its types,dosage and associated outcomes and adverse events is still lacking.AIM To provide a comprehensive overview on existing studies regarding meal replacement usage among patients with T2D,and map out glycemic and weightrelated outcomes along with adverse effects incidences.METHODS This scoping review is conducted based on Arksey and O’Malley’s seminal framework for scoping reviews.A systematic search has been done for studies published between January 2020 and January 2024 across six online databases(Cochrane Library,PubMed,Science Direct,Scopus,Web of Science and Ebscohost Discovery)using specific keywords.Two researchers independently assessed the eligibility of the studies and extracted the data.The selected articles and extracted data were reviewed by all researchers.RESULTS The initial search resulted in an initial count of 53922 articles from which 133 articles were included in this review after eligibility screening.Included studies were categorized based on meal replacement type into low calorie/energy,low glycemic index,protein-rich,low-fat,diabetes-specific formulas,and combined lifestyle intervention programs.Fifty-nine studies reported improvements on hemoglobin A1c,and 70 studies reported positive changes in weight or BMI after the meal replacement intervention.The combination of meal replacements with education,counseling or structured lifestyle interventions has proved to be effective.Only 13 studies reported occurrence of adverse events related to the intervention.Most of the reported incidents were of mild occurrences with constipation being the most reported adverse event.CONCLUSION The results suggest that meal replacements,especially when combined with lifestyle intervention programs and counseling,are an effective and safe strategy in glycemic and weight management among patients with T2D.展开更多
Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets.Biometric authentication systems offer a strong solution.However,choosi...Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets.Biometric authentication systems offer a strong solution.However,choosing the best security system requires a structured decision-making framework,especially in complex scenarios involving multiple criteria.To address this problem,we develop a novel quantum spherical fuzzy technique for order preference by similarity to ideal solution(QSF-TOPSIS)methodology,integrating quantum mechanics principles and fuzzy theory.The proposed approach enhances decision-making accuracy,handles uncertainty,and incorporates criteria relationships.Criteria weights are determined using spherical fuzzy sets,and alternatives are ranked through the QSFTOPSIS framework.This comprehensive multi-criteria decision-making(MCDM)approach is applied to identify the optimal gate security system for an organization,considering critical factors such as accuracy,cost,and reliability.Additionally,the study compares the proposed approach with other established MCDM methods.The results confirm the alignment of rankings across these methods,demonstrating the robustness and reliability of the QSF-TOPSIS framework.The study identifies the infrared recognition and identification system(IRIS)as the most effective,with a score value of 0.5280 and optimal security system among the evaluated alternatives.This research contributes to the growing literature on quantum-enhanced decision-making models and offers a practical framework for solving complex,real-world problems involving uncertainty and ambiguity.展开更多
基金funded by the National Natural Science Foundation of China(NSFC)under Grant Number 72071209.
文摘Modern battlefields exhibit high dynamism,where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values,leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command,where static weights cannot reflect the operational value decay or surge of key indicators.To address this issue,this study proposes a dynamic adaptive weightingmethod for evaluation indicators based onG1-CRITIC-PIVW.First,theG1(Sequential Relationship Analysis Method)subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via sequential relationship ranking,while the CRITIC(Criteria Importance Through Intercriteria Correlation)objective weighting method—derives weights from data characteristics by integrating variability and inter-correlations—calculates weights by integrating indicator variability and inter-indicator correlations,ensuring data-driven objectivity.These two sets of weights are then fused using a deviation coefficient optimization model,minimizing the squared deviation from a reference weight and adjusting the fusion coefficient via Spearman’s rank correlation to resolve potential conflicts between subjective and objective judgments.Subsequently,the PIVW(Punishment-Incentive VariableWeight)theory—adapts weights to realtime indicator performance via penalty/incentive rules—is applied for dynamic adjustment.Scenario-specific penalty λ_(1) and incentive λ_(2) thresholds are set based on operational priorities and indicator volatility,penalizing indicators with values below λ_(1) and incentivizing those exceeding λ_(2) to reflect real-time indicator performance.Experimental validation was conducted using an Air Defense and Anti-Missile(ADAM)system effectiveness assessment framework,with data covering 7 indicators across 3 combat scenarios.Results show that compared to static weighting methods,the proposed method reduces MAE(Mean Absolute Error)by 15%-20% and weighted decision error rate by 84.2%,effectively reducing overestimation/underestimation of combat effectiveness in dynamic scenarios;compared to Entropy-TOPSIS,it lowers MAE by 12% while achieving a weighted Kendall’sτconsistency coefficient of 0.85,ensuring higher alignment with expert judgment.This method enhances the accuracy and scenario adaptability of effectiveness assessment,providing reliable decision support for dynamic battlefield environments.
基金This work was supported by the Natural Science Foundation of Hunan Province(No.04JJ6033) and Scientific Research Fund of Hunan ProvincialEducation Department(No. 03C066).
文摘A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportional feedforward controller based on fuzzy set-point weighting following and a limited semi-integrator（LSI）, are designed respectively. LSI is used to limit output signal and to prevent wind up at the low frequency of the spectrum. By using a range camera and an electronic feedback control, the tip damping on the HCBS can be adjusted artificially. A collaborative control simulation technique of HOPSAN and MATLAB/SIMULINK is applied to the controller design. Simulation results show that the proposed PI control system has less overshoot as well as faster response. The tip damping on the HCBS during operation is improved.
文摘The paper demonstrates the possibility to enhance the damping of inter-area oscillations using Wide Area Measurement (WAM) based adaptive supervisory controller (ASC) which considers the wide-area signal transmission delays. The paper uses an LMI-based iterative nonlinear optimization algorithm to establish a method of designing state-feedback controllers for power systems with a time-varying delay. This method is based on the delay-dependent stabilization conditions obtained by the improved free weighting matrix (IFWM) approach. In the stabilization conditions, the upper bound of feedback signal’s transmission delays is taken into consideration. Combining theoriesof state feedback control and state observer, the ASC is designed and time-delay output feedback robust controller is realized for power system. The ASC uses the input information from Phase Measurement Units (PMUs) in the system and dispatches supplementary control signals to the available local controllers. The design of the ASC is explained in detail and its performance validated by time domain simulations on a New England test power system (NETPS).
基金supported in part by the National Natural Science Foundation of China(NSFC)(62202192 and 72101094)the National Science Fund for Distinguished Young Scholars of China(51825502).
文摘As one of the most classical scheduling problems,flexible job shop scheduling problems(FJSP)find widespread applications in modern intelligent manufacturing systems.However,the majority of meta-heuristic methods for solving FJSP in the literature are population-based evolutionary algorithms,which are complex and time-consuming.In this paper,we propose a fast effective singlesolution based local search algorithm with an innovative adaptive weighting-based local search(AWLS)technique for solving FJSP.The adaptive weighting technique assigns weights to each operation and adaptively updates them during the exploration.AWLS integrates a Tabu Search strategy and the adaptive weighting technique to smooth the landscape of the search space and enhance the exploration diversity.Computational experiments on 313 well-known benchmark instances demonstrate that AWLS is highly competitive with state-of-the-art algorithms in terms of both solution quality and computational efficiency,despite of its simplicity.Specifically,AWLS improves the previous best-known results in the literature on 33 instances and match the best-known results on the remaining ones except for only one under the same time limit of up to 300 s.As a strongly non-deterministic polynomia(NP)-hard problem which has been extensively studied for nearly half a century,breaking the records on these classic instances is an arduous task.Nevertheless,AWLS establishes new records on 8 challenging instances whose previous best records were established by a state-of-the-art meta-heuristic algorithm and a famous industrial solver.
基金supported by Brazilian agencies CAPES(Finance Code 001)CNPq through PQ productivity scholarship.
文摘Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesity drug alone or combined with exercise training on body weight,body fat,fat-free mass and cardiorespiratory fitness in obese patients were retrieved from Pubmed and EMBASE up to May 2024.Risk of bias assessment was performed with RoB 2.0,and the GRADE approach assessed the certainty of evidence(CoE)of each main outcome.We included four publications summing up 202 patients.Two publications used orlistat as an anti-obesity drug treatment,while the other two adopted GLP-1 receptor agonist(liraglutide or tirzepatide)as a pharmacotherapy for weight management.Orlistat combined with exercise was superior to change body weight(mean difference(MD):−2.27 kg;95%CI:−2.86 to−1.69;CoE:very low),fat mass(MD:−2.89;95%CI:−3.87 to−1.91;CoE:very low),fat-free mass(MD:0.56;95%CI:0.40–0.72;CoE:very low),and VO_(2)Peak(MD:2.64;95%CI:2.52–2.76;CoE:very low).GLP-1 receptor agonist drugs combined with exercise had a great effect on body weight(MD:−3.96 kg;95%CI:−5.07 to−2.85;CoE:low),fat mass(MD:−1.76;95%CI:−2.24 to−1.27;CoE:low),fat-free mass(MD:0.50;95%CI:−0.98 to 1.98;CoE:very low)and VO_(2)Peak(MD:2.47;95%CI:1.31–3.63;CoE:very low).The results reported here suggest that exercise training remains an important approach in weight management when combined with pharmacological treatment.
文摘In the context of power generation companies, vast amounts of specialized data and expert knowledge have been accumulated. However, challenges such as data silos and fragmented knowledge hinder the effective utilization of this information. This study proposes a novel framework for intelligent Question-and-Answer (Q&A) systems based on Retrieval-Augmented Generation (RAG) to address these issues. The system efficiently acquires domain-specific knowledge by leveraging external databases, including Relational Databases (RDBs) and graph databases, without additional fine-tuning for Large Language Models (LLMs). Crucially, the framework integrates a Dynamic Knowledge Base Updating Mechanism (DKBUM) and a Weighted Context-Aware Similarity (WCAS) method to enhance retrieval accuracy and mitigate inherent limitations of LLMs, such as hallucinations and lack of specialization. Additionally, the proposed DKBUM dynamically adjusts knowledge weights within the database, ensuring that the most recent and relevant information is utilized, while WCAS refines the alignment between queries and knowledge items by enhanced context understanding. Experimental validation demonstrates that the system can generate timely, accurate, and context-sensitive responses, making it a robust solution for managing complex business logic in specialized industries.
基金Under the auspices of National Natural Science Foundation Youth Fund Project(No.41701424)Open Research Fund of State Key Laboratory of Remote Sensing Science(No.OFSLRSS201716)+1 种基金Jilin Province Science and Technology Development Plan Project(No.20240701167FG)Science and Technology Research Project of Education Department of Jilin Province(No.JJKH20230502KJ)。
文摘The health of cropland systems is directly related to the degree of food security guarantee,and the‘quantity-quality-ecology as a whole’protection is of great significance for maintaining the health of cropland systems.Taking the typical black soil region in Northeast China(TBSN)as an example,this paper combined the concept of‘quantity-quality-ecology as a whole’protection with crop-land systems health,constructed a health assessment model for cropland systems,and used Google Earth Engine to conduct a quantitat-ive analysis of the temporal and spatial evolution of cropland systems health in TBSN during 2003–2023.By coupling the geographical detector and the Multi-scale Geographically Weighted Regression(MGWR)model,the driving factors of cropland health changes were explored.The study finds that during the research period,the health status of cropland systems in TBSN showed a slight downward trend,and the distribution pattern of cropland systems health gradually shifted from‘better in the east’to‘high in the northeast and low in the southwest’.Changes in average annual sunshine duration,relative humidity,and precipitation had a significant impact on the spa-tial differentiation of cropland systems health in the early stages,and were considered as dominant factors.Meanwhile,the influence of dual dominant factors in the natural environment on cropland systems health is increasing.Furthermore,the MGWR model performed better in revealing the complex relationships between natural and social factors and changes in cropland systems health,demonstrating the significant spatial heterogeneity of the impacts of natural environment and human activities on cropland systems health.The re-search can provide scientific guidance for the sustainable development of TBSN and formulate more precise and effective cropland pro-tection policies.
基金Supported by the Key Laboratory Fund for Equipment Pre-Research(6142207210202)。
文摘Aiming at the problem that infrared small target detection faces low contrast between the background and the target and insufficient noise suppression ability under the complex cloud background,an infrared small target detection method based on the tensor nuclear norm and direction residual weighting was proposed.Based on converting the infrared image into an infrared patch tensor model,from the perspective of the low-rank nature of the background tensor,and taking advantage of the difference in contrast between the background and the target in different directions,we designed a double-neighborhood local contrast based on direction residual weighting method(DNLCDRW)combined with the partial sum of tensor nuclear norm(PSTNN)to achieve effective background suppression and recovery of infrared small targets.Experiments show that the algorithm is effective in suppressing the background and improving the detection ability of the target.
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.
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 the National Natural Science Foundation of China(32072352)。
文摘In order to improve the quality of 3D printed raspberry preserves after post-processing,microwave ovens combining infrared and microwave methods were utilized.The effects of infrared heating temperature,infrared heating time,microwave power,microwave heating time on the center temperature,moisture content,the chroma(C*),the total color difference(ΔE*),shape fidelity,hardness,and the total anthocyanin content of 3D printed raspberry preserves were analyzed by response surface method(RSM).The results showed that under combining with the two methods,infrared heating improved the fidelity and quality degradation of printed products,while microwave heating enhanced the efficiency of infrared heating.Infrared-microwave combination cooking could maintain relatively stable color appearance and shape of 3D printed raspberry preserves.The AHP–CRITIC hybrid weighting method combined with the response surface test to determine the comprehensive weights of the evaluation indicators optimized the process parameters,and the optimal process parameters were obtained:infrared heating temperature of 190℃,infrared heating time of 10 min and 30 s,microwave power of 300 W,and microwave heating time of 2 min and 6 s.The 3D printed raspberry cooking methods obtained under the optimal conditions seldom had color variation,porous structure,uniform texture,and high shape fidelity,which retained the characteristics of personalized manufacturing by 3D printing.This study could provide a reference for the postprocessing and quality control of 3D cooking methods.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82174259 and 82304997)China Postdoctoral Followship Program of CPSF(Grant No.:GZC20233202)+4 种基金China Postdoctoral Science Foundation(Grant No.:2024M753698)the Key Research and Development Program of Hunan Province of China(Grant Nos.:2023SK2021 and 2022SK2015)the Natural Science Foundation of Hunan Province,China(Grant Nos.:2024JJ6632,2022JJ40853,and 2021JJ31117)the Hunan Traditional Chinese Medicine Scientific Research Program,China(Grant Nos.:B2024113,B2024114,and 2021032)the Fundamental Research Funds for the Central Universities of Central South University,China(Grant No.:1053320232786).
文摘Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the characteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.
基金supported by Ministry of Education Industry-University Cooperation and Collaborative Education Project(China)(220603231024713).
文摘Human pose estimation is a challenging task in computer vision.Most algorithms perform well in regular scenes,but lack good performance in occlusion scenarios.Therefore,we propose a multi-type feature fusion network based on importance weighting,which consists of three modules.In the first module,we propose a multi-resolution backbone with two feature enhancement sub-modules,which can extract features from different scales and enhance the feature expression ability.In the second module,we enhance the expressiveness of keypoint features by suppressing obstacle features and compensating for the unique and shared attributes of keypoints and topology.In the third module,we perform importance weighting on the adjacency matrix to enable it to describe the correlation among nodes,thereby improving the feature extraction ability.We conduct comparative experiments on the keypoint detection datasets of common objects in Context 2017(COCO2017),COCO-Wholebody and CrowdPose,achieving the accuracy of 78.9%,67.1%and 77.6%,respectively.Additionally,a series of ablation experiments are designed to show the performance of our work.Finally,we present the visualization of different scenarios to verify the effectiveness of our work.
基金supported by the China National Railway Group Co.,Ltd.Research and Development Project(P2023T002).
文摘Purpose–To systematically characterize and objectively evaluate basic railway safety management capability,creating a closed-loop management approach which allows continuous improvement and optimization.Design/methodology/approach–A basic railway safety management capability evaluation index system based on a comprehensive analysis of national safety management standards,railway safety rules and regulations and existing safety data from railway transport enterprises is presented.The system comprises a guideline layer including safety committee formation,work safety responsibility,safety management organization and safety rules and regulations as its components,along with an index layer consisting of 12 quantifiable indexes.Game theory combination weighting is utilized to integrate subjective and objective weight values derived using AHP and CRITIC methods and further combined using the TOPSIS method in order to construct a comprehensive basic railway safety management capability evaluation model.Findings–The case study presented demonstrates that this evaluation index system and comprehensive evaluation model are capable of effectively characterizing and evaluating basic railway safety management capability and providing directional guidance for its sustained improvement.Originality/value–Construction of an evaluation index system that is quantifiable,generalizable and accessible,accurately reflects the main aspects of railway transportation enterprises’basic safety management capability and provides interoperability across various railway transportation enterprises.The application of the game theoretic combination weighting method to derive composite weights which combine experts’subjective evaluations with the objectivity of data.
文摘BACKGROUND Cotadutide(MEDI0382)is a twincretin that acts as an agonist for both the glucagon-like peptide-1 and glucagon receptors.Several randomized controlled trials(RCTs)have been published evaluating the use of cotadutide in individuals with type 2 diabetes(T2D),showing promising results.However,the efficacy and safety of the drug use have been inadequately explored by systematic reviews and meta-analyses.AIM To assess the clinical efficacy and safety of cotadutide in individuals with T2D having overweight or obesity.METHODS The systematic reviews and meta-analyses have been registered with International Prospective Register of Systematic Reviews(CRD42024511703),and the protocol summary can be accessed online.Several databases and registries,including MEDLINE(via PubMed),Scopus,Web of Science,the Cochrane Central Register of Controlled Trials,and ClinicalTrials.gov,were systematically searched using related terms from their inception to May 15,2025,for RCTs involving individuals with T2D receiving cotadutide in the intervention group.Review Manager web was used to conduct meta-analysis using random-effects models.The co-primary outcomes of interest were the changes in glycated hemoglobin(HbA1c)and the percent changes in body weight from baseline.The results of the outcomes were expressed as mean differences(MDs)or risk ratios(RRs)with 95%confidence intervals(CIs).The analysis of outcomes was stratified according to whether the control group received a placebo,denoted as the placebo control group(PCG),or an active comparator,referred to as the active control group(ACG).RESULTS Nine RCTs(mostly phase 2 RCTs,n=1525)with study durations varying from 28 days to 54 weeks that met all the inclusion criteria were analyzed;five studies had a low overall risk of bias,while the other four had some concerns.Compared to the PCG,greater reductions in HbA1c were achieved with cotadutide 100μg(MD-0.77%,95%CI:-1.06 to-0.47),200μg(MD-0.68%,95%CI:-1.12 to-0.23),300μg(MD-0.67%,95%CI:-0.79 to-0.56),and 600μg(MD-0.69%,95%CI:-0.97 to-0.41).Cotadutide 100μg(MD-1.74%,95%CI:-3.23 to-0.25),200μg(MD-2.56%,95%CI:-3.37 to-1.75),300μg(MD-3.49%,95%CI:-4.14 to-2.84),and 600μg(MD-5.45%,95%CI:-7.17 to-3.73)achieved greater percent reductions in body weight from baseline.However,the certainty of evidence for HbA1c and percent body weight reductions was very low to low.Cotadutide,at all doses,also outperformed PCG in reducing fasting plasma glucose and absolute body weight.The changes in HbA1c,percent body weight,fasting plasma glucose,and absolute body weight were similar between the cotadutide group and the ACG.Compared to PCG,pooled doses of cotadutide increased the risks of treatment-emergent adverse events(AEs),treatment-related AEs,and discontinuation of the study drug due to AEs,but not for serious AEs.More subjects experienced overall gastrointestinal AEs,dyspepsia,nausea,vomiting,constipation,and decreased appetite with cotadutide than with PCG.Compared to the ACG,none of the AEs showed increased risk in the cotadutide group.CONCLUSION Cotadutide demonstrated glycemic control and weight-loss benefits in short-term,small RCTs(mostly phase 2).However,small sample sizes,very low to low certainty of evidence,and the absence of data on long-term cardiovascular and renal outcomes highlight substantial uncertainties,warranting cautious interpretation and further investigation in larger,longer-term trials to establish its safety and efficacy profile.
文摘The effect of prenatal exposure to ambient particulate matter(PM)on birth weight varies considerably across studies,and the findings remain inconclusive.In this study,we conducted a meta-analysis to assess the associations between exposure to PM_(2.5) and PM10 and birth weight.A total of 74 studies were identified through searches in Web of Science,PubMed,Embase,and Ovid Medline,as well as manual searches,up to October 2024.We found that for each 10μg/m^(3) increase in PM_(2.5),the risk of low birth weight(LBW)increased significantly during the entire pregnancy(odds ratio[OR]=2.41,95%confidence interval[CI]:1.99–2.91)and in all trimesters.Similarly,for every 10μg/m^(3) increase in PM10 concentration,the risk of LBW increased significantly during the entire pregnancy(OR=1.46,95%CI:1.16–1.84).Subgroup analysis by maternal age for PM_(2.5) showed that mothers aged 30 and above had a significantly higher risk of LBW(OR=3.69,95%CI:2.81–4.84),compared with those under 30.In conclusion,maternal exposure to PM_(2.5) and PM_(10) is associated with an increased risk of LBW across all trimesters.Additionally,mothers aged 30 and above are at a higher risk of LBW,compared with younger mothers.Further research is needed to clarify the biological mechanisms by which PM pollution may contribute to LBW.
基金Supported by the National Natural Science Foundation of China(No.61971162,61771186)the Natural Science Foundation of Heilongjiang Province(No.PL2024F025)+2 种基金the Open Research Fund of National Mobile Communications Research Laboratory Southeast University(No.2023D07)the Outstanding Youth Program of Natural Science Foundation of Heilongjiang Province(No.YQ2020F012)the Funda-mental Scientific Research Funds of Heilongjiang Province(No.2022-KYYWF-1050).
文摘Indoor visual localization relies heavily on image retrieval to ascertain location information.However,the widespread presence and high consistency of floor patterns across different images of-ten lead to the extraction of numerous repetitive features,thereby reducing the accuracy of image retrieval.This article proposes an indoor visual localization method based on semantic segmentation and adaptive weight fusion to address the issue of ground texture interference with retrieval results.During the positioning process,an indoor semantic segmentation model is established.Semantic segmentation technology is applied to accurately delineate the ground portion of the images.Fea-ture extraction is performed on both the original database and the ground-segmented database.The vector of locally aggregated descriptors(VLAD)algorithm is then used to convert image features into a fixed-length feature representation,which improves the efficiency of image retrieval.Simul-taneously,a method for adaptive weight optimization in similarity calculation is proposed,using a-daptive weights to compute similarity for different regional features,thereby improving the accuracy of image retrieval.The experimental results indicate that this method significantly reduces ground interference and effectively utilizes ground information,thereby improving the accuracy of image retrieval.
基金Supported by First-class Undergraduate Course Construction Project of Henan Province(Online and Offline Hybrid Course),No.[2021]21548and 2021 Pingdingshan Smart Nursing Key Laboratory.
文摘BACKGROUND Attention-deficit hyperactivity disorder(ADHD)and its pharmacological treatments may influence growth in children and adolescents.This meta-analysis aimed to clarify their effects on the physical development,especially weight and height.AIM To investigate the effects of ADHD and its treatment on growth in children and adolescents.METHODS Researchers reviewed 18 studies published up to September 2023 from databases such as PubMed,EMBASE,Cochrane,and Web of Science.They analyzed changes in body weight,height,and body mass index(BMI)before and after ADHD treatment,along with the risks of overweight and obesity.RESULTS Children with ADHD undergoing long-term medication therapy showed decreased actual weight[weighted mean difference(WMD)=-9.50]and height(WMD=-0.15),along with a slight increase in weight standard deviation scores(WMD=0.23)and height z scores(WMD=0.10).BMI showed a non-significant downward trend(WMD=-1.72).Regarding overweight and obesity risks,the pooled odds ratios were 1.37 and 1.16,respectively,but these were not statistically significant.CONCLUSION Overall,the study suggests that long-term pharmacological treatment for ADHD may be associated with reduced growth in weight and height among young patients.However,no clear link was found between ADHD and increased risk of overweight or obesity.These findings highlight the importance of monitoring growth in children receiving medication for ADHD.
文摘BACKGROUND Type 2 diabetes(T2D)is a major health concern globally and its prevalence is expected to continue to escalate.Lifestyle intervention is an integral part of T2D management.Meal replacements are often used as part of lifestyle intervention programs in T2D and weight management programs.There are various trials being carried out to date;however,a thorough review regarding the usage of meal replacement on its types,dosage and associated outcomes and adverse events is still lacking.AIM To provide a comprehensive overview on existing studies regarding meal replacement usage among patients with T2D,and map out glycemic and weightrelated outcomes along with adverse effects incidences.METHODS This scoping review is conducted based on Arksey and O’Malley’s seminal framework for scoping reviews.A systematic search has been done for studies published between January 2020 and January 2024 across six online databases(Cochrane Library,PubMed,Science Direct,Scopus,Web of Science and Ebscohost Discovery)using specific keywords.Two researchers independently assessed the eligibility of the studies and extracted the data.The selected articles and extracted data were reviewed by all researchers.RESULTS The initial search resulted in an initial count of 53922 articles from which 133 articles were included in this review after eligibility screening.Included studies were categorized based on meal replacement type into low calorie/energy,low glycemic index,protein-rich,low-fat,diabetes-specific formulas,and combined lifestyle intervention programs.Fifty-nine studies reported improvements on hemoglobin A1c,and 70 studies reported positive changes in weight or BMI after the meal replacement intervention.The combination of meal replacements with education,counseling or structured lifestyle interventions has proved to be effective.Only 13 studies reported occurrence of adverse events related to the intervention.Most of the reported incidents were of mild occurrences with constipation being the most reported adverse event.CONCLUSION The results suggest that meal replacements,especially when combined with lifestyle intervention programs and counseling,are an effective and safe strategy in glycemic and weight management among patients with T2D.
文摘Global security threats have motivated organizations to adopt robust and reliable security systems to ensure the safety of individuals and assets.Biometric authentication systems offer a strong solution.However,choosing the best security system requires a structured decision-making framework,especially in complex scenarios involving multiple criteria.To address this problem,we develop a novel quantum spherical fuzzy technique for order preference by similarity to ideal solution(QSF-TOPSIS)methodology,integrating quantum mechanics principles and fuzzy theory.The proposed approach enhances decision-making accuracy,handles uncertainty,and incorporates criteria relationships.Criteria weights are determined using spherical fuzzy sets,and alternatives are ranked through the QSFTOPSIS framework.This comprehensive multi-criteria decision-making(MCDM)approach is applied to identify the optimal gate security system for an organization,considering critical factors such as accuracy,cost,and reliability.Additionally,the study compares the proposed approach with other established MCDM methods.The results confirm the alignment of rankings across these methods,demonstrating the robustness and reliability of the QSF-TOPSIS framework.The study identifies the infrared recognition and identification system(IRIS)as the most effective,with a score value of 0.5280 and optimal security system among the evaluated alternatives.This research contributes to the growing literature on quantum-enhanced decision-making models and offers a practical framework for solving complex,real-world problems involving uncertainty and ambiguity.
