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
A series of transparent,intrinsically flame-retardant,and impact-resistant poly(carbonates-b-siloxanes)were synthesized by incorporating Schiff-base modified polysiloxanes(DMS-Schiff)and naphthalene-sulfonate units in...A series of transparent,intrinsically flame-retardant,and impact-resistant poly(carbonates-b-siloxanes)were synthesized by incorporating Schiff-base modified polysiloxanes(DMS-Schiff)and naphthalene-sulfonate units into the polycarbonate(PC)chain.In addition to high transparency,the resultant copolymers(SS-co-PC5,SS-co-PC9,SS-co-PC14,and SS-co-PC20)exhibited remarkable improvements in fire safety and mechanical performance.Compared to pure PC,these copolymers demonstrated significantly enhanced limiting oxygen index(LOI,up to 34.5%)and a UL-94 V-0 rating under a thickness of only 1.6 mm.The incorporation of the polysiloxane blocks not only improved flame retardancy but also enhanced the impact strength,with SS-co-PC9 showing a 48%increase in elongation at break and a 38%rise in impact toughness compared to pure PC.In addition,SS-co-PC9 presented high mechanical strength.The synergistic effects between the naphthalene-sulfonate and polysiloxane blocks,along with the well-controlled polysiloxane phase separation(sulfonate units enabled lower processing viscosity of copolymers),led to superior comprehensive performance.These findings provide a promising pathway to create high-performance copolycarbonates for real-world applications.展开更多
Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shif...Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar energy.However,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban environment.To overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric energy.Current TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar panels.In this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve transparency.Figures of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV technology.Then we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic PVs.The applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and facades.Finally,current challenges and future opportunities in TPV research are pointed out.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
The ultrafast laser-matter interaction is explored to induce new pioneering principles and technologies into the realms of fundamental science and industrial production.The local thermal melting and connection propert...The ultrafast laser-matter interaction is explored to induce new pioneering principles and technologies into the realms of fundamental science and industrial production.The local thermal melting and connection properties of the ultrafast laser welding technology offer a novel method for welding of diverse transparent materials,thus having wide range of potential applications in aerospace,opto-mechanical systems,sensors,microfluidic,optics,etc.In this comprehensive review,tuning the transient electron activation processes,high-rate laser energy deposition,and dynamic evolution of plasma morphology by the temporal/spatial shaping methods have been demonstrated to facilitate the transition from conventional homogeneous transparent material welding to the more intricate realm of transparent/metal heterogeneous material welding.The welding strength and stability are also improvable through the implementation of real-time,in-situ monitoring techniques and the prompt diagnosis of welding defects.The principles of ultrafast laser welding,bottleneck problems in the welding,novel welding methods,advances in welding performance,in-situ monitoring and diagnosis,and various applications are reviewed.Finally,we offer a forward-looking perspective on the fundamental challenges within the field of ultrafast laser welding and identify key areas for future research,underscoring the imperative need for ongoing innovation and exploration.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
Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,a...Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,and soft robotics.Conducting meshes represent a promising alternative to traditional,brittle,metal oxide conductors due to their high electrical conductivity,optical transparency,and enhanced mechanical flexibility.In this paper,we present a simple method for fabricating an ultra-transparent conducting metal oxide mesh electrode using selfcracking-assisted templates.Using this method,we produced an electrode with ultra-transparency(97.39%),high conductance(Rs=21.24Ωsq^(−1)),elevated work function(5.16 eV),and good mechanical stability.We also evaluated the effectiveness of the fabricated electrodes by integrating them into organic photovoltaics,organic light-emitting diodes,and flexible transparent memristor devices for neuromorphic computing,resulting in exceptional device performance.In addition,the unique porous structure of the vanadium-doped indium zinc oxide mesh electrodes provided excellent flexibility,rendering them a promising option for application in flexible optoelectronics.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
Over the past several decades,much research effort has been dedicated to the study of optical windows,with two primary themes emerging as key focuses.The first of these centers on investigating the optical properties ...Over the past several decades,much research effort has been dedicated to the study of optical windows,with two primary themes emerging as key focuses.The first of these centers on investigating the optical properties of typical transparent single crystals under shock or ramp compression,which helps in the selection of appropriate optical windows for high-pressure experiments.The second involves the exploration of novel optical windows,particularly transparent polycrystalline ceramics,which not only match the shock impedance of the samples,but also preserve transparency under dynamic compression.In this study,we first integrate existing research on the evolution of optical properties in transparent single crystals and polycrystalline ceramics subjected to shock or ramp loading,proposing a mechanism that links mesoscopic damage to macroscopic optical transparency.Subsequently,through a systematic integration of experiments and computational analyses on polycrystalline transparent ceramics,we demonstrate that shock transparency can be enhanced by optimizing grain size and that shock impedance can be designed via compositional tuning.Notably,our results reveal that nano-grained MgAl_(2)O_(4) ceramics exhibit outstanding optical transparency under high shock pressures,highlighting a promising strategy for designing optical windows that retain transparency under extreme dynamic loading conditions.展开更多
Sc_(2)O_(3),as a host for solid-state laser gain materials,has advantage of high thermal conductivity and easy matching with activating ions,which is promising in high-power laser applications.Currently,Yb-doped Sc_(2...Sc_(2)O_(3),as a host for solid-state laser gain materials,has advantage of high thermal conductivity and easy matching with activating ions,which is promising in high-power laser applications.Currently,Yb-doped Sc_(2)O_(3) ceramics have been fabricated at very high sintering temperatures,but their optical quality and sintering process still need further improvement.In this work,5%Yb:Sc_(2)O_(3)(in mass)nano-powders were obtained by co-precipitation,and then transparent ceramics were fabricated by vacuum pre-sintering and hot isostatic pressing(HIP)post-treatment.The cubic Yb:Sc_(2)O_(3) nano-powders with good dispersity and an average crystallite of 29 nm were obtained.Influence of pre-sintering temperatures(1500-1700℃)on densification process,microstructure changes,and optical transmittance of Yb:Sc_(2)O_(3) ceramics was detected.Experimental data revealed that all samples have a uniform microstructure,while the average grain sizes increase with the increase of the sintering temperatures.Impressively,the optimum in-line transmittance of Yb:Sc_(2)O_(3) ceramics,pre-sintered at 1550℃after HIP post-treatment,reaches 78.1%(theoretical value of 80%)at 1100 nm.Spectroscopic properties of the Yb:Sc_(2)O_(3) ceramics reveal that the minimum population inversion parameterβ2 and the luminescence decay time of 5%Yb:Sc_(2)O_(3) ceramics are 0.041 and 0.49 ms,respectively,which demonstrate that the optical quality of the Yb:Sc_(2)O_(3) has been improved.Meanwhile,their best vacuum sintering temperature can be controlled down to a lower temperature(1550℃).In conclusion,Yb:Sc_(2)O_(3) nano-powders are successfully synthesized by co-precipitation method,and good optical quality transparent ceramics are fabricated by vacuum pre-sintering at 1550℃and HIP post-treatment.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
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
Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements...Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements.Deep reinforcement learning(DRL)exhibits excellent capability of real-time decision-making and adaptability to complex scenarios,and generalization abilities.However,it is arduous to guarantee complete driving safety and efficiency under the constraints of training samples and costs.This paper proposes a Mixture of Expert method(MoE)based on Soft Actor-Critic(SAC),where the upper-level discriminator dynamically decides whether to activate the lower-level DRL expert or the heuristic expert based on the features of the input state.To further enhance the performance of the DRL expert,a buffer zone is introduced in the reward function,preemptively applying penalties before insecure situations occur.In order to minimize collision and off-road rates,the Intelligent Driver Model(IDM)and Minimizing Overall Braking Induced by Lane changes(MOBIL)strategy are designed by heuristic experts.Finally,tested in typical simulation scenarios,MOE shows a 13.75%improvement in driving efficiency compared with the traditional DRL method with continuous action space.It ensures high safety with zero collision and zero off-road rates while maintaining high adaptability.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
As living standards improve,the energy consumption for regulating indoor temperature keeps increasing.Windows,in particular,enhance indoor brightness but also lead to increased energy loss,especially in sunny weather....As living standards improve,the energy consumption for regulating indoor temperature keeps increasing.Windows,in particular,enhance indoor brightness but also lead to increased energy loss,especially in sunny weather.Developing a product that can maintain indoor brightness while reducing energy consumption is a challenge.We developed a facile,spectrally selective transparent ultrahigh-molecular-weight polyethylene composite film to address this trade-off.It is based on a blend of antimony-doped tin oxide and then spin-coated hydrophobic fumed silica,achieving a high visible light transmittance(>70%)and high shielding rates for ultraviolet(>90%)and near-infrared(>70%).When applied to the acrylic window of containers and placed outside,this film can cause a 10℃ temperature drop compared to a pure polymer film.Moreover,in building energy simulations,the annual energy savings could be between 14.1%~31.9%per year.The development of energy-efficient and eco-friendly transparent films is crucial for reducing energy consumption and promoting sustainability in the window environment.展开更多
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financially supported by the National Natural Science Foundation of China(Nos.52403117,52173083,51991355,and 52173082)the 2024 Ningbo Yongjiang Talent Programme,the Natural Science Foundation of Zhejiang Province(No.LY24E030007)the Australian Research Council(No.DE230100616).
文摘A series of transparent,intrinsically flame-retardant,and impact-resistant poly(carbonates-b-siloxanes)were synthesized by incorporating Schiff-base modified polysiloxanes(DMS-Schiff)and naphthalene-sulfonate units into the polycarbonate(PC)chain.In addition to high transparency,the resultant copolymers(SS-co-PC5,SS-co-PC9,SS-co-PC14,and SS-co-PC20)exhibited remarkable improvements in fire safety and mechanical performance.Compared to pure PC,these copolymers demonstrated significantly enhanced limiting oxygen index(LOI,up to 34.5%)and a UL-94 V-0 rating under a thickness of only 1.6 mm.The incorporation of the polysiloxane blocks not only improved flame retardancy but also enhanced the impact strength,with SS-co-PC9 showing a 48%increase in elongation at break and a 38%rise in impact toughness compared to pure PC.In addition,SS-co-PC9 presented high mechanical strength.The synergistic effects between the naphthalene-sulfonate and polysiloxane blocks,along with the well-controlled polysiloxane phase separation(sulfonate units enabled lower processing viscosity of copolymers),led to superior comprehensive performance.These findings provide a promising pathway to create high-performance copolycarbonates for real-world applications.
基金supported by the National Natural Science Foundation of China(Grant number W2432035)financial support from the EPSRC SWIMS(EP/V039717/1)+3 种基金Royal Society(RGS\R1\221009 and IEC\NSFC\211201)Leverhulme Trust(RPG-2022-263)Ser Cymru programme–Enhancing Competitiveness Equipment Awards 2022-23(MA/VG/2715/22-PN66)the financial support from Kingdom of Saudi Arabia Ministry of Higher Education.
文摘Electrical energy is essential for modern society to sustain economic growths.The soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar energy.However,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban environment.To overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric energy.Current TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar panels.In this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve transparency.Figures of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV technology.Then we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic PVs.The applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and facades.Finally,current challenges and future opportunities in TPV research are pointed out.
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.
基金supports from National Key R&D Program of China(Grant No.2023YFB4605500)National Natural Science Foundation of China(Grant No.52105498)+3 种基金Natural Science Foundation of Hunan Province(Grant No.2022JJ40597)the Science and Technology Innovation Program of Hunan Province(Grant No.2022RC1132)State Key Laboratory of Precision Manufacturing for Extreme Service Performance(Grant No.ZZYJKT2023-08)support in analyzing the status of ultrafast laser welding applications,as well as the corresponding project support(Grant No.HKF202400595).
文摘The ultrafast laser-matter interaction is explored to induce new pioneering principles and technologies into the realms of fundamental science and industrial production.The local thermal melting and connection properties of the ultrafast laser welding technology offer a novel method for welding of diverse transparent materials,thus having wide range of potential applications in aerospace,opto-mechanical systems,sensors,microfluidic,optics,etc.In this comprehensive review,tuning the transient electron activation processes,high-rate laser energy deposition,and dynamic evolution of plasma morphology by the temporal/spatial shaping methods have been demonstrated to facilitate the transition from conventional homogeneous transparent material welding to the more intricate realm of transparent/metal heterogeneous material welding.The welding strength and stability are also improvable through the implementation of real-time,in-situ monitoring techniques and the prompt diagnosis of welding defects.The principles of ultrafast laser welding,bottleneck problems in the welding,novel welding methods,advances in welding performance,in-situ monitoring and diagnosis,and various applications are reviewed.Finally,we offer a forward-looking perspective on the fundamental challenges within the field of ultrafast laser welding and identify key areas for future research,underscoring the imperative need for ongoing innovation and exploration.
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.
基金supported by a National Research Foundation of Korea(NRF)grant(No.2016R1A3B 1908249)funded by the Korean government.
文摘Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,and soft robotics.Conducting meshes represent a promising alternative to traditional,brittle,metal oxide conductors due to their high electrical conductivity,optical transparency,and enhanced mechanical flexibility.In this paper,we present a simple method for fabricating an ultra-transparent conducting metal oxide mesh electrode using selfcracking-assisted templates.Using this method,we produced an electrode with ultra-transparency(97.39%),high conductance(Rs=21.24Ωsq^(−1)),elevated work function(5.16 eV),and good mechanical stability.We also evaluated the effectiveness of the fabricated electrodes by integrating them into organic photovoltaics,organic light-emitting diodes,and flexible transparent memristor devices for neuromorphic computing,resulting in exceptional device performance.In addition,the unique porous structure of the vanadium-doped indium zinc oxide mesh electrodes provided excellent flexibility,rendering them a promising option for application in flexible optoelectronics.
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.
基金financially supported by the National Natural Science Foundation of China(Grant No.11872344)the Innovatory Development Foundation of the China Academy of Engineering Physics(Grant No.CX20210026).
文摘Over the past several decades,much research effort has been dedicated to the study of optical windows,with two primary themes emerging as key focuses.The first of these centers on investigating the optical properties of typical transparent single crystals under shock or ramp compression,which helps in the selection of appropriate optical windows for high-pressure experiments.The second involves the exploration of novel optical windows,particularly transparent polycrystalline ceramics,which not only match the shock impedance of the samples,but also preserve transparency under dynamic compression.In this study,we first integrate existing research on the evolution of optical properties in transparent single crystals and polycrystalline ceramics subjected to shock or ramp loading,proposing a mechanism that links mesoscopic damage to macroscopic optical transparency.Subsequently,through a systematic integration of experiments and computational analyses on polycrystalline transparent ceramics,we demonstrate that shock transparency can be enhanced by optimizing grain size and that shock impedance can be designed via compositional tuning.Notably,our results reveal that nano-grained MgAl_(2)O_(4) ceramics exhibit outstanding optical transparency under high shock pressures,highlighting a promising strategy for designing optical windows that retain transparency under extreme dynamic loading conditions.
基金National Key R&D Program of China(2023YFE3812005)International Partnership Program of Chinese Academy of Sciences(121631KYSB20200039)+1 种基金National Center for Research and Development(WPC2/1/SCAPOL/2021)Chinese Academy of Sciences President’s International Fellowship Initiative(2024VEA0005,2024VEA0014)。
文摘Sc_(2)O_(3),as a host for solid-state laser gain materials,has advantage of high thermal conductivity and easy matching with activating ions,which is promising in high-power laser applications.Currently,Yb-doped Sc_(2)O_(3) ceramics have been fabricated at very high sintering temperatures,but their optical quality and sintering process still need further improvement.In this work,5%Yb:Sc_(2)O_(3)(in mass)nano-powders were obtained by co-precipitation,and then transparent ceramics were fabricated by vacuum pre-sintering and hot isostatic pressing(HIP)post-treatment.The cubic Yb:Sc_(2)O_(3) nano-powders with good dispersity and an average crystallite of 29 nm were obtained.Influence of pre-sintering temperatures(1500-1700℃)on densification process,microstructure changes,and optical transmittance of Yb:Sc_(2)O_(3) ceramics was detected.Experimental data revealed that all samples have a uniform microstructure,while the average grain sizes increase with the increase of the sintering temperatures.Impressively,the optimum in-line transmittance of Yb:Sc_(2)O_(3) ceramics,pre-sintered at 1550℃after HIP post-treatment,reaches 78.1%(theoretical value of 80%)at 1100 nm.Spectroscopic properties of the Yb:Sc_(2)O_(3) ceramics reveal that the minimum population inversion parameterβ2 and the luminescence decay time of 5%Yb:Sc_(2)O_(3) ceramics are 0.041 and 0.49 ms,respectively,which demonstrate that the optical quality of the Yb:Sc_(2)O_(3) has been improved.Meanwhile,their best vacuum sintering temperature can be controlled down to a lower temperature(1550℃).In conclusion,Yb:Sc_(2)O_(3) nano-powders are successfully synthesized by co-precipitation method,and good optical quality transparent ceramics are fabricated by vacuum pre-sintering at 1550℃and HIP post-treatment.
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Supported by National Key R&D Program of China(Grant No.2022YFB2503203)National Natural Science Foundation of China(Grant No.U1964206).
文摘Decision-making of connected and automated vehicles(CAV)includes a sequence of driving maneuvers that improve safety and efficiency,characterized by complex scenarios,strong uncertainty,and high real-time requirements.Deep reinforcement learning(DRL)exhibits excellent capability of real-time decision-making and adaptability to complex scenarios,and generalization abilities.However,it is arduous to guarantee complete driving safety and efficiency under the constraints of training samples and costs.This paper proposes a Mixture of Expert method(MoE)based on Soft Actor-Critic(SAC),where the upper-level discriminator dynamically decides whether to activate the lower-level DRL expert or the heuristic expert based on the features of the input state.To further enhance the performance of the DRL expert,a buffer zone is introduced in the reward function,preemptively applying penalties before insecure situations occur.In order to minimize collision and off-road rates,the Intelligent Driver Model(IDM)and Minimizing Overall Braking Induced by Lane changes(MOBIL)strategy are designed by heuristic experts.Finally,tested in typical simulation scenarios,MOE shows a 13.75%improvement in driving efficiency compared with the traditional DRL method with continuous action space.It ensures high safety with zero collision and zero off-road rates while maintaining high adaptability.
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.
基金financially supported by the Natural Science Foundation of Henan(242300421010)National Natural Science Foundation of China(52403055).
文摘As living standards improve,the energy consumption for regulating indoor temperature keeps increasing.Windows,in particular,enhance indoor brightness but also lead to increased energy loss,especially in sunny weather.Developing a product that can maintain indoor brightness while reducing energy consumption is a challenge.We developed a facile,spectrally selective transparent ultrahigh-molecular-weight polyethylene composite film to address this trade-off.It is based on a blend of antimony-doped tin oxide and then spin-coated hydrophobic fumed silica,achieving a high visible light transmittance(>70%)and high shielding rates for ultraviolet(>90%)and near-infrared(>70%).When applied to the acrylic window of containers and placed outside,this film can cause a 10℃ temperature drop compared to a pure polymer film.Moreover,in building energy simulations,the annual energy savings could be between 14.1%~31.9%per year.The development of energy-efficient and eco-friendly transparent films is crucial for reducing energy consumption and promoting sustainability in the window environment.
