With the development of information technology, DSS can be used to resolve the complex process of the feasible reasoning and scientific decision-making of projects. This paper offers 7 exploiting principles for the co...With the development of information technology, DSS can be used to resolve the complex process of the feasible reasoning and scientific decision-making of projects. This paper offers 7 exploiting principles for the computer support system on feasible reasoning and scientific decision-making of projects, that is, the principles of standardization, procedure, specification, agility, currency, practicability and development. On the basis of analysis on systematic procedure, the computer support system on feasible reasoning and scientific decision-making of projects is formed based on WEB, and its general structure, system function and the methods to be realized are introduced. The data composition of this system is analyzed following the principles of integrality, development, perspicuity and consistency. Also, the model-base management system is designed for the management of model storage and management of model operation.展开更多
The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientif...The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientific decision-making of education policies.Therefore,based on this view and through shaping reasonable education policy values,this research gives full play to the driving force of educational scientific research on education policies and designs effective education decision-making information content and running agenda,thus optimizing the weigh principle of education policy proposals,advocating risk assessment and practice of education decisions,constructing institutional rationality of educational scientific decision-making,and finally realizing the rationality and scientificity of education policy decision-making.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a pati...The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.展开更多
Large language models(LLMs)have emerged as powerful tools for addressing a wide range of problems,including those in scientific computing,particularly in solving partial differential equations(PDEs).However,different ...Large language models(LLMs)have emerged as powerful tools for addressing a wide range of problems,including those in scientific computing,particularly in solving partial differential equations(PDEs).However,different models exhibit distinct strengths and preferences,resulting in varying levels of performance.In this paper,we compare the capabilities of the most advanced LLMs—DeepSeek,ChatGPT,and Claude—along with their reasoning-optimized versions in addressing computational challenges.Specifically,we evaluate their proficiency in solving traditional numerical problems in scientific computing as well as leveraging scientific machine learning techniques for PDE-based problems.We designed all our experiments so that a nontrivial decision is required,e.g,defining the proper space of input functions for neural operator learning.Our findings show that reasoning and hybrid-reasoning models consistently and significantly outperform non-reasoning ones in solving challenging problems,with ChatGPT o3-mini-high generally offering the fastest reasoning speed.展开更多
To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforce...To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.展开更多
This paper examines the establishment of the North China Branch of the Royal Asiatic Society(NCBRAS),which was initially known as the Shanghai Literary and Scientific Society,focusing on its merits and drawbacks from ...This paper examines the establishment of the North China Branch of the Royal Asiatic Society(NCBRAS),which was initially known as the Shanghai Literary and Scientific Society,focusing on its merits and drawbacks from the perspective of scientific imperialism.It analyzes the founders’motivations and their affiliation with the Royal Asiatic Society of Great Britain and Ireland(RAS),framing NCBRAS as a product of scientific imperialism.Unlike previous sinology-centric research,this study explores the benefits derived from scientific institutions,Orientalist traditions,and Europe’s overseas expansion.Despite the opportunity provided by all the merits,the NCBRAS also faced challenges due to Chinese and foreign hostilities,financial inadequacies,and cultural differences.This dual situation played a pivotal role in shaping the future trajectory of the NCBRAS.This inquiry into the context and drawbacks contributes to a deeper understanding of NCBRAS and offers new perspectives on natural history research in 1850s China.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective to...Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.展开更多
This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear i...This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear industry.Sino-British scientific interactions took place across multiple dimensions,involving various institutions and individuals.Around 1949,UK-trained Chinese nuclear scientists returned to China,bringing advanced technological knowledge and extensive practical experience.The PRC regarded the UK as a crucial gateway to overcoming the technological blockade imposed by the United States(and later the Soviet Union)and sought to establish scientific relations with the UK through semi-official and unofficial channels.Specifically,these connections manifested in the interactions between the Chinese Academy of Sciences(CAS)and the Royal Society of London,the guiding role of the Chinese Charge d'Affaires Office in London in facilitating scientific and technological exchanges,and the technology investigations led by the Ministry of Foreign Trade in the name of trade.Additionally,the Sino-British scientific network extended to the international arena,allowing China to engage in nuclear-related global organizations and events.This study highlights the significant British influence on the early development of China's nuclear industry,revealing the extent of its British influence.It argues that China's urgent need for nuclear science and industrial advancement was a key driver of its scientific engagement withthe UK.展开更多
BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpfu...BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using the χ^(2) test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.展开更多
The entomofauna in the Republic of Congo is very little known. Studies carried out in natural forests are few. It is in this context that this inventory of entomofauna was carried out from April to July 2022 in the Sc...The entomofauna in the Republic of Congo is very little known. Studies carried out in natural forests are few. It is in this context that this inventory of entomofauna was carried out from April to July 2022 in the Scientific City Forest. The general objective is to contribute to the knowledge of the trapping, mowing and sight hunting;the three types of traps used are: Barber pots, colored plates and aerial traps. This study made it possible to invent 1523 specimens belonging to 106 species, 99 genera, 59 families and 12 orders. The order Diptera is the most abundant and richest in species (47% and 26%). This order is followed by Hymenoptera (23% and 23%). Formicidae (14%) and Calliphoridae (13%) are the most abundant families. The Formicidae family presents the greatest species richness (7%), Calliphora sp and Polyrhachis cyaniventris present the highest specific relative abundance of the entire collection. These preliminary results of the entomofauna of Scientific City constitute a database. However, this study must be continued and extended to other areas of Brazzaville, using other capture techniques and taking into account the seasons.展开更多
1.Introduction Since the publication of our original study comparing large language models(LLMs)in scientific computing and scientific machine learning tasks,Anthropic has released Claude 4.0[1],a major upgrade in its...1.Introduction Since the publication of our original study comparing large language models(LLMs)in scientific computing and scientific machine learning tasks,Anthropic has released Claude 4.0[1],a major upgrade in its Claude family of LLMs.Claude 4.0 is designed to introduce substantial improvements in reasoning,coding,and mathematical capabilities.展开更多
Objectives This study aimed to clarify the relationship between the content of proxy decision-making made by families of patients with malignant brain tumors regarding treatment policies and daily care and the cues le...Objectives This study aimed to clarify the relationship between the content of proxy decision-making made by families of patients with malignant brain tumors regarding treatment policies and daily care and the cues leading to those decisions.Methods Semi-structured personal interviews were used to collect data.Seven family members of patients with malignant brain tumors were selected to participate in the study by purposive sampling method from June to August 2022 in the Patient Family Association of Japan.Responses were content analyzed to explore the relationship between the content of decisions regarding“treatment policies”and“daily care”and the cues influencing those decisions.Semi-structured interviews were analyzed by using thematic analysis.Results The contents of proxy decisions regarding“treatment policies”included implementation,interruption,and termination of initial treatments,free medical treatments,use of respirators,and end-of-life sedation and included six cues:treatment policies suggested by the primary physician,information and knowledge about the disease and treatment obtained by the family from limited resources,perceived life threat from symptom worsening,words and reactions from the patient regarding treatment,patient’s personality and way of life inferred from their treatment preferences,family’s thoughts and values hoping for better treatment for the patient.Decisions for“daily care”included meal content and methods,excretion,mobility,maintaining cleanliness,rehabilitation,continuation or resignation from work,treatment settings(outpatient or inpatient),and ways to spend time outside and included seven cues:words and thoughts from the patient about their way of life,patient’s reactions and life history inferred from their preferred way of living,things the patient can do to maintain daily life and roles,awareness of the increasing inability to do things in daily life,family’s underlying thoughts and values about how to spend the remaining time,approval from family members regarding the care setting,advice from medical professionals on living at home.Conclusions For“treatment policies,”guidelines from medical professionals were a key cue,while for“daily care,”the small signs from the patients in their daily lives served as cues for proxy decision-making.This may be due to the lack of information available to families and the limited time available for discussion with the patient.Families of patients with malignant brain tumors repeatedly use multiple cues to make proxy decision-making under high uncertainty.Therefore,nurses supporting proxy decision-making should assess the family’s situation and provide cues that facilitate informed and confident decisions.展开更多
Group living is widespread across diverse taxa,and the mechanisms underlying collective decision-making in contexts of variable role division are critical for understanding the dynamics of group stability.While studie...Group living is widespread across diverse taxa,and the mechanisms underlying collective decision-making in contexts of variable role division are critical for understanding the dynamics of group stability.While studies on collective behavior in small animals such as fish and insects are well-established,similar research on large wild animals remains challenging due to the limited availability of sufficient and systematic field data.Here,we aimed to explore the collective decision-making pattern and its sexual difference for the dimorphic Tibetan antelopes Pantholops hodgsonii(chiru)in Xizang Autonomous Region,China,by analyzing individual leadership distribution,as well as the joining process,considering factors such as calving stages and joining ranks.The distinct correlations of decision participants’ratio with group size and decision duration underscore the trade-off between accuracy and speed in decision-making.Male antelopes display a more democratic decision-making pattern,while females exhibit more prompt responses after calving at an early stage.This study uncovers a partially shared decision-making strategy among Tibetan antelopes,suggesting flexible self-organization in group decision processes aligned with animal life cycle progression.展开更多
Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined ma...Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined mathematical models that often fail to capture equipment-specific degradation,(2)offline optimization methods that assume access to future data,and(3)the absence of component-level guidance.To address these challenges,we propose a data-driven framework for component-level decision-making.The framework leverages streaming sensor data to predict the remaining useful life(RUL)without relying on mathematical models,employs an online optimization algorithm suitable for practical settings,and,through remanufacturing simulations,provides guidance on which components should be replaced.In a case study on gas-insulated switchgear,the proposed framework achieved RUL prediction performance comparable to an oracle model in an online setting without relying on predefined mathematical models.Furthermore,by employing online optimization,it determined a remanufacturing timing close to the global optimum using only past and current data.In addition,unlike previous studies,the framework enables component-level decision-making,allowing for more detailed and actionable remanufacturing guidance in practical applications.展开更多
Based on the core principles of General Secretary Xi Jinping's important speech on July 9^(th),this article explores the relationship between Party-building and scientific innovation/technology services in researc...Based on the core principles of General Secretary Xi Jinping's important speech on July 9^(th),this article explores the relationship between Party-building and scientific innovation/technology services in research institutions.Combining practical cases from Changli Institute of Pomology under Hebei Academy of Agriculture and Forestry Sciences,it proposes practical implementations and reflections on how Party-building brands can drive scientific innovation and technology services.The study demonstrates that Party-building brand development can effectively promote deep integration between Party-building and professional work,providing strong political assurance and organizational support for agricultural scientific innovation and technology services.展开更多
BACKGROUND Mesalamine is the recommended first-line treatment for inducing and maintaining remission in mild-to-moderate ulcerative colitis(UC).However,adherence in real-world settings is frequently suboptimal.Encoura...BACKGROUND Mesalamine is the recommended first-line treatment for inducing and maintaining remission in mild-to-moderate ulcerative colitis(UC).However,adherence in real-world settings is frequently suboptimal.Encouraging collaborative patient-provider relationships may foster better adherence and patient outcomes.AIM To quantify the association between patient participation in treatment decisionmaking and adherence to oral mesalamine in UC.METHODS We conducted a 12-month,prospective,non-interventional cohort study at 113 gastroenterology practices in Germany.Eligible patients were aged≥18 years,had a confirmed UC diagnosis,had no prior mesalamine treatment,and provided informed consent.At the first visit,we collected data on demographics,clinical characteristics,patient preference for mesalamine formulation(tablets or granules),and disease knowledge.Self-reported adherence and disease activity were assessed at all visits.Correlation analyses and logistic regression were used to examine associations between adherence and various factors.RESULTS Of the 605 consecutively screened patients,520 were included in the study.The median age was 41 years(range:18-91),with a male-to-female ratio of 1.1:1.0.Approximately 75%of patients reported good adherence at each study visit.In correlation analyses,patient participation in treatment decision-making was significantly associated with better adherence across all visits(P=0.04).In the regression analysis at 12 months,this association was evident among patients who both preferred and received prolonged-release mesalamine granules(odds ratio=2.73,P=0.001).Patients reporting good adherence also experienced significant improvements in disease activity over 12 months(P<0.001).CONCLUSION Facilitating patient participation in treatment decisions and accommodating medication preferences may improve adherence to mesalamine.This may require additional effort but has the potential to improve long-term management of UC.展开更多
Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt pro...Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt protective measures.However, whether to disseminate specific information is also a behavioral decision. In light of this understanding, we develop a coupled information–vaccination–epidemic model to depict these co-evolutionary dynamics in a three-layer network. Negative information dissemination and vaccination are treated as separate decision-making processes. We then examine the combined effects of herd and risk motives on information dissemination and vaccination decisions through the lens of game theory. The microscopic Markov chain approach(MMCA) is used to describe the dynamic process and to derive the epidemic threshold. Simulation results indicate that increasing the cost of negative information dissemination and providing timely clarification can effectively control the epidemic. Furthermore, a phenomenon of diminishing marginal utility is observed as the cost of dissemination increases, suggesting that authorities do not need to overinvest in suppressing negative information. Conversely, reducing the cost of vaccination and increasing vaccine efficacy emerge as more effective strategies for outbreak control. In addition, we find that the scale of the epidemic is greater when the herd motive dominates behavioral decision-making. In conclusion, this study provides a new perspective for understanding the complexity of epidemic spreading by starting with the construction of different behavioral decisions.展开更多
文摘With the development of information technology, DSS can be used to resolve the complex process of the feasible reasoning and scientific decision-making of projects. This paper offers 7 exploiting principles for the computer support system on feasible reasoning and scientific decision-making of projects, that is, the principles of standardization, procedure, specification, agility, currency, practicability and development. On the basis of analysis on systematic procedure, the computer support system on feasible reasoning and scientific decision-making of projects is formed based on WEB, and its general structure, system function and the methods to be realized are introduced. The data composition of this system is analyzed following the principles of integrality, development, perspicuity and consistency. Also, the model-base management system is designed for the management of model storage and management of model operation.
基金This paper is funded by the youth project of education of the National Social Science Foundation“Research on the value foundation of educational policy from the perspective of political philosophy”(CAA150123).
文摘The scientific decision-making of education policies is not absolutely a complete rational process.The bounded rationality which takes rationality as the judgement standard is the essential connotation of the scientific decision-making of education policies.Therefore,based on this view and through shaping reasonable education policy values,this research gives full play to the driving force of educational scientific research on education policies and designs effective education decision-making information content and running agenda,thus optimizing the weigh principle of education policy proposals,advocating risk assessment and practice of education decisions,constructing institutional rationality of educational scientific decision-making,and finally realizing the rationality and scientificity of education policy decision-making.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
文摘The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.
基金supported by the ONR Vannevar Bush Faculty Fellowship(Grant No.N00014-22-1-2795).
文摘Large language models(LLMs)have emerged as powerful tools for addressing a wide range of problems,including those in scientific computing,particularly in solving partial differential equations(PDEs).However,different models exhibit distinct strengths and preferences,resulting in varying levels of performance.In this paper,we compare the capabilities of the most advanced LLMs—DeepSeek,ChatGPT,and Claude—along with their reasoning-optimized versions in addressing computational challenges.Specifically,we evaluate their proficiency in solving traditional numerical problems in scientific computing as well as leveraging scientific machine learning techniques for PDE-based problems.We designed all our experiments so that a nontrivial decision is required,e.g,defining the proper space of input functions for neural operator learning.Our findings show that reasoning and hybrid-reasoning models consistently and significantly outperform non-reasoning ones in solving challenging problems,with ChatGPT o3-mini-high generally offering the fastest reasoning speed.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFE0117100)National Science Foundation of China(Grant No.52102468,52325212)Fundamental Research Funds for the Central Universities。
文摘To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.
文摘This paper examines the establishment of the North China Branch of the Royal Asiatic Society(NCBRAS),which was initially known as the Shanghai Literary and Scientific Society,focusing on its merits and drawbacks from the perspective of scientific imperialism.It analyzes the founders’motivations and their affiliation with the Royal Asiatic Society of Great Britain and Ireland(RAS),framing NCBRAS as a product of scientific imperialism.Unlike previous sinology-centric research,this study explores the benefits derived from scientific institutions,Orientalist traditions,and Europe’s overseas expansion.Despite the opportunity provided by all the merits,the NCBRAS also faced challenges due to Chinese and foreign hostilities,financial inadequacies,and cultural differences.This dual situation played a pivotal role in shaping the future trajectory of the NCBRAS.This inquiry into the context and drawbacks contributes to a deeper understanding of NCBRAS and offers new perspectives on natural history research in 1850s China.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
文摘Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.
文摘This study investigates the establishment of scientific links between the People's Republic of China(PRC)and the United Kingdom(UK)in the mid-2Oth century,focusing on the early development of China's nuclear industry.Sino-British scientific interactions took place across multiple dimensions,involving various institutions and individuals.Around 1949,UK-trained Chinese nuclear scientists returned to China,bringing advanced technological knowledge and extensive practical experience.The PRC regarded the UK as a crucial gateway to overcoming the technological blockade imposed by the United States(and later the Soviet Union)and sought to establish scientific relations with the UK through semi-official and unofficial channels.Specifically,these connections manifested in the interactions between the Chinese Academy of Sciences(CAS)and the Royal Society of London,the guiding role of the Chinese Charge d'Affaires Office in London in facilitating scientific and technological exchanges,and the technology investigations led by the Ministry of Foreign Trade in the name of trade.Additionally,the Sino-British scientific network extended to the international arena,allowing China to engage in nuclear-related global organizations and events.This study highlights the significant British influence on the early development of China's nuclear industry,revealing the extent of its British influence.It argues that China's urgent need for nuclear science and industrial advancement was a key driver of its scientific engagement withthe UK.
文摘BACKGROUND Understanding a patient's clinical status and setting priorities for their care are two aspects of the constantly changing process of clinical decision-making.One analytical technique that can be helpful in uncertain situations is clinical judgment.Clinicians must deal with contradictory information,lack of time to make decisions,and long-term factors when emergencies occur.AIM To examine the ethical issues healthcare professionals faced during the coronavirus disease 2019(COVID-19)pandemic and the factors affecting clinical decision-making.METHODS This pilot study,which means it was a preliminary investigation to gather information and test the feasibility of a larger investigation was conducted over 6 months and we invited responses from clinicians worldwide who managed patients with COVID-19.The survey focused on topics related to their professional roles and personal relationships.We examined five core areas influencing critical care decision-making:Patients'personal factors,family-related factors,informed consent,communication and media,and hospital administrative policies on clinical decision-making.The collected data were analyzed using the χ^(2) test for categorical variables.RESULTS A total of 102 clinicians from 23 specialties and 17 countries responded to the survey.Age was a significant factor in treatment planning(n=88)and ventilator access(n=78).Sex had no bearing on how decisions were made.Most doctors reported maintaining patient confidentiality regarding privacy and informed consent.Approximately 50%of clinicians reported a moderate influence of clinical work,with many citing it as one of the most important factors affecting their health and relationships.Clinicians from developing countries had a significantly higher score for considering a patient's financial status when creating a treatment plan than their counterparts from developed countries.Regarding personal experiences,some respondents noted that treatment plans and preferences changed from wave to wave,and that there was a rapid turnover of studies and evidence.Hospital and government policies also played a role in critical decision-making.Rather than assessing the appropriateness of treatment,some doctors observed that hospital policies regarding medications were driven by patient demand.CONCLUSION Factors other than medical considerations frequently affect management choices.The disparity in treatment choices,became more apparent during the pandemic.We highlight the difficulties and contradictions between moral standards and the realities physicians encountered during this medical emergency.False information,large patient populations,and limited resources caused problems for clinicians.These factors impacted decision-making,which,in turn,affected patient care and healthcare staff well-being.
文摘The entomofauna in the Republic of Congo is very little known. Studies carried out in natural forests are few. It is in this context that this inventory of entomofauna was carried out from April to July 2022 in the Scientific City Forest. The general objective is to contribute to the knowledge of the trapping, mowing and sight hunting;the three types of traps used are: Barber pots, colored plates and aerial traps. This study made it possible to invent 1523 specimens belonging to 106 species, 99 genera, 59 families and 12 orders. The order Diptera is the most abundant and richest in species (47% and 26%). This order is followed by Hymenoptera (23% and 23%). Formicidae (14%) and Calliphoridae (13%) are the most abundant families. The Formicidae family presents the greatest species richness (7%), Calliphora sp and Polyrhachis cyaniventris present the highest specific relative abundance of the entire collection. These preliminary results of the entomofauna of Scientific City constitute a database. However, this study must be continued and extended to other areas of Brazzaville, using other capture techniques and taking into account the seasons.
文摘1.Introduction Since the publication of our original study comparing large language models(LLMs)in scientific computing and scientific machine learning tasks,Anthropic has released Claude 4.0[1],a major upgrade in its Claude family of LLMs.Claude 4.0 is designed to introduce substantial improvements in reasoning,coding,and mathematical capabilities.
文摘Objectives This study aimed to clarify the relationship between the content of proxy decision-making made by families of patients with malignant brain tumors regarding treatment policies and daily care and the cues leading to those decisions.Methods Semi-structured personal interviews were used to collect data.Seven family members of patients with malignant brain tumors were selected to participate in the study by purposive sampling method from June to August 2022 in the Patient Family Association of Japan.Responses were content analyzed to explore the relationship between the content of decisions regarding“treatment policies”and“daily care”and the cues influencing those decisions.Semi-structured interviews were analyzed by using thematic analysis.Results The contents of proxy decisions regarding“treatment policies”included implementation,interruption,and termination of initial treatments,free medical treatments,use of respirators,and end-of-life sedation and included six cues:treatment policies suggested by the primary physician,information and knowledge about the disease and treatment obtained by the family from limited resources,perceived life threat from symptom worsening,words and reactions from the patient regarding treatment,patient’s personality and way of life inferred from their treatment preferences,family’s thoughts and values hoping for better treatment for the patient.Decisions for“daily care”included meal content and methods,excretion,mobility,maintaining cleanliness,rehabilitation,continuation or resignation from work,treatment settings(outpatient or inpatient),and ways to spend time outside and included seven cues:words and thoughts from the patient about their way of life,patient’s reactions and life history inferred from their preferred way of living,things the patient can do to maintain daily life and roles,awareness of the increasing inability to do things in daily life,family’s underlying thoughts and values about how to spend the remaining time,approval from family members regarding the care setting,advice from medical professionals on living at home.Conclusions For“treatment policies,”guidelines from medical professionals were a key cue,while for“daily care,”the small signs from the patients in their daily lives served as cues for proxy decision-making.This may be due to the lack of information available to families and the limited time available for discussion with the patient.Families of patients with malignant brain tumors repeatedly use multiple cues to make proxy decision-making under high uncertainty.Therefore,nurses supporting proxy decision-making should assess the family’s situation and provide cues that facilitate informed and confident decisions.
基金supported by the National Natural Science Foundation of China(Grant no.32101237)the China Postdoctoral Science Foundation(Grant no.2021M691522)+1 种基金the National Key Research and Development Program(Grant no.2022YFC3202104)the Tibet Major Science and Technology Project(Grant no.XZ201901-GA-06).
文摘Group living is widespread across diverse taxa,and the mechanisms underlying collective decision-making in contexts of variable role division are critical for understanding the dynamics of group stability.While studies on collective behavior in small animals such as fish and insects are well-established,similar research on large wild animals remains challenging due to the limited availability of sufficient and systematic field data.Here,we aimed to explore the collective decision-making pattern and its sexual difference for the dimorphic Tibetan antelopes Pantholops hodgsonii(chiru)in Xizang Autonomous Region,China,by analyzing individual leadership distribution,as well as the joining process,considering factors such as calving stages and joining ranks.The distinct correlations of decision participants’ratio with group size and decision duration underscore the trade-off between accuracy and speed in decision-making.Male antelopes display a more democratic decision-making pattern,while females exhibit more prompt responses after calving at an early stage.This study uncovers a partially shared decision-making strategy among Tibetan antelopes,suggesting flexible self-organization in group decision processes aligned with animal life cycle progression.
基金supported by the Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)grant funded by the Korea government Ministry of Knowledge Economy(No.RS-2023-00244330)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF RS-2023-00219052RS-2024-00352587)。
文摘Accurately determining when and what to remanufacture is essential for maximizing the lifecycle value of industrial equipment.However,existing approaches face three significant limitations:(1)reliance on predefined mathematical models that often fail to capture equipment-specific degradation,(2)offline optimization methods that assume access to future data,and(3)the absence of component-level guidance.To address these challenges,we propose a data-driven framework for component-level decision-making.The framework leverages streaming sensor data to predict the remaining useful life(RUL)without relying on mathematical models,employs an online optimization algorithm suitable for practical settings,and,through remanufacturing simulations,provides guidance on which components should be replaced.In a case study on gas-insulated switchgear,the proposed framework achieved RUL prediction performance comparable to an oracle model in an online setting without relying on predefined mathematical models.Furthermore,by employing online optimization,it determined a remanufacturing timing close to the global optimum using only past and current data.In addition,unlike previous studies,the framework enables component-level decision-making,allowing for more detailed and actionable remanufacturing guidance in practical applications.
文摘Based on the core principles of General Secretary Xi Jinping's important speech on July 9^(th),this article explores the relationship between Party-building and scientific innovation/technology services in research institutions.Combining practical cases from Changli Institute of Pomology under Hebei Academy of Agriculture and Forestry Sciences,it proposes practical implementations and reflections on how Party-building brands can drive scientific innovation and technology services.The study demonstrates that Party-building brand development can effectively promote deep integration between Party-building and professional work,providing strong political assurance and organizational support for agricultural scientific innovation and technology services.
文摘BACKGROUND Mesalamine is the recommended first-line treatment for inducing and maintaining remission in mild-to-moderate ulcerative colitis(UC).However,adherence in real-world settings is frequently suboptimal.Encouraging collaborative patient-provider relationships may foster better adherence and patient outcomes.AIM To quantify the association between patient participation in treatment decisionmaking and adherence to oral mesalamine in UC.METHODS We conducted a 12-month,prospective,non-interventional cohort study at 113 gastroenterology practices in Germany.Eligible patients were aged≥18 years,had a confirmed UC diagnosis,had no prior mesalamine treatment,and provided informed consent.At the first visit,we collected data on demographics,clinical characteristics,patient preference for mesalamine formulation(tablets or granules),and disease knowledge.Self-reported adherence and disease activity were assessed at all visits.Correlation analyses and logistic regression were used to examine associations between adherence and various factors.RESULTS Of the 605 consecutively screened patients,520 were included in the study.The median age was 41 years(range:18-91),with a male-to-female ratio of 1.1:1.0.Approximately 75%of patients reported good adherence at each study visit.In correlation analyses,patient participation in treatment decision-making was significantly associated with better adherence across all visits(P=0.04).In the regression analysis at 12 months,this association was evident among patients who both preferred and received prolonged-release mesalamine granules(odds ratio=2.73,P=0.001).Patients reporting good adherence also experienced significant improvements in disease activity over 12 months(P<0.001).CONCLUSION Facilitating patient participation in treatment decisions and accommodating medication preferences may improve adherence to mesalamine.This may require additional effort but has the potential to improve long-term management of UC.
基金Project supported by the National Natural Science Foundation of China (Grant No. 72174121)the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning, and the Soft Science Research Project of Shanghai (Grant No. 22692112600)。
文摘Information plays a crucial role in guiding behavioral decisions during public health emergencies. Individuals communicate to acquire relevant knowledge about an epidemic, which influences their decisions to adopt protective measures.However, whether to disseminate specific information is also a behavioral decision. In light of this understanding, we develop a coupled information–vaccination–epidemic model to depict these co-evolutionary dynamics in a three-layer network. Negative information dissemination and vaccination are treated as separate decision-making processes. We then examine the combined effects of herd and risk motives on information dissemination and vaccination decisions through the lens of game theory. The microscopic Markov chain approach(MMCA) is used to describe the dynamic process and to derive the epidemic threshold. Simulation results indicate that increasing the cost of negative information dissemination and providing timely clarification can effectively control the epidemic. Furthermore, a phenomenon of diminishing marginal utility is observed as the cost of dissemination increases, suggesting that authorities do not need to overinvest in suppressing negative information. Conversely, reducing the cost of vaccination and increasing vaccine efficacy emerge as more effective strategies for outbreak control. In addition, we find that the scale of the epidemic is greater when the herd motive dominates behavioral decision-making. In conclusion, this study provides a new perspective for understanding the complexity of epidemic spreading by starting with the construction of different behavioral decisions.
