In recent years,significant insights have been gathered into the effectiveness of lifestyle interventions in the treatment of chronic non-communicable diseases(NCD).To speed up the implementation of evidence-based lif...In recent years,significant insights have been gathered into the effectiveness of lifestyle interventions in the treatment of chronic non-communicable diseases(NCD).To speed up the implementation of evidence-based lifestyle medicine,we developed a research agenda in collaboration with Dutch experts in treating NCD,using a hybrid Delphi approach.The research agenda focuses on four key themes:(1)promoting sustainable behavioural change at patient,healthcare professional and organisational levels;(2)optimising research designs,methodology and outcomes for the evaluation of effectiveness and implementation of lifestyle medicine modalities in healthcare practice;(3)elucidating biological mechanisms underlying successful lifestyle interventions and(4)advancing data infrastructure to ensure accessible data for citizens,healthcare professionals,researchers and health insurers for monitoring and evaluation of health and lifestyle outcomes.Collectively,the identified knowledge questions across these four themes provide guidance for(applied)research towards lifestyle medicine in healthcare.展开更多
Objective:To determine the safety and the role of modulating cytokines and proteases in the immune response to intravesical Bacillus Calmette-Guérin(BCG)when primed with systemic intradermal BCG.Methods:Phase 1 a...Objective:To determine the safety and the role of modulating cytokines and proteases in the immune response to intravesical Bacillus Calmette-Guérin(BCG)when primed with systemic intradermal BCG.Methods:Phase 1 and mechanistic longitudinal,prospective,single-blind randomized study(NCT04806178).Twenty-one non-muscle invasive urothelial bladder cancer patients undergoing intravesical adjuvant BCG after transurethral resection of bladder tumor(TURBT)in a teaching hospital between September 2021 and April 2023 were randomized to 0.1 mL of intradermal BCG vaccine or placebo(0.9%saline)administered 15 days before the start of intravesical BCG therapy.Blood samples were evaluated mechanistically regarding eight cytokines serum levels interferon-induced transmembrane protein 3 Gene(IFITM3),Interleukin 1 beta(IL1-BETA),interleukin-2 receptor alpha chain(IL2 RA),Interleukin 6(IL 6),Interleukin 10(IL 10),Tumor necrosis factor alpha(TNF-α),Interferon-β,AXL,and one protease CASPASE 8.Results:After 1 exclusion,twenty patients were randomized to intradermal BCG(n=11)and intradermal placebo(n=9).There was no difference in adverse effects emerging from the intravesical Onco-BCG therapy,and no difference in the expression of the cytokines and proteases analyzed between control and intervention,and over time.Conclusions:Intradermal BCG administration before intravesical application was safe,with no increase in adverse effects.It also does not seem to change the analyzed targets during the intravesical induction-phase BCG.Other immune targets should be explored in the future.The Brazilian tuberculosis-endemic status,where BCG vaccination is mandatory,might have affected the results.展开更多
There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reac...There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reactive coating processes,but existing work is not uncharacteristically remiss regarding viscoelasticity,radiative heating,viscous dissipation,and homogeneous–heterogeneous reactions within a single scheme that is calibrated.This research investigates the flow of Williamson nanofluid across a dynamically wedged surface under conditions that include viscous dissipation,thermal radiation,and homogeneous-heterogeneous reactions.The paper develops a detailed mathematical approach that utilizes boundary layers to transform partial differential equations into ordinary differential equations using similarity transformations.RK4 is the technique for gaining numerical solutions,but with the addition of ANNs,there is an improvement in prediction accuracy and computational efficiency.The study investigates the influence of wedge angle parameter,along with Weissenberg number,thermal radiation parameter and Brownian motion parameter,and Schmidt number,on velocity distribution,temperature distribution,and concentra-tion distribution.Enhanced Weissenberg numbers enhance viscoelastic responses that modify velocity patterns,but radiation parameters and thermophoresis have key impacts on thermal transfer phenomena.This research develops findings that are of enormous application in aerospace,biomedical(artificial hearts and drug delivery),and industrial cooling technology applications.New findings on non-Newtonian nanofluids under full flow systems are included in this work to enhance heat transfer methods in novel fluid-based systems.展开更多
The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates ...The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.展开更多
Background:Recent evidence suggests continuous bouts of physical activity(PA)are associated with longevity.We hypothesized the risk of mortality would be lower when the most active minutes of the day were in a continu...Background:Recent evidence suggests continuous bouts of physical activity(PA)are associated with longevity.We hypothesized the risk of mortality would be lower when the most active minutes of the day were in a continuous bout.Methods:PA was assessed using accelerometery in UK Biobank participants.The intensity of the most active continuous(MXCONT)and accumulated(MX)X min of the day,and their ratio(MXRATIO=MXCONT/MX),were determined.MXRATIO indicates how the most active minutes of the day are accumulated,ranging from a single continuous bout through to sporadic accumulation spread across the day.Durations(X)considered ranged from 1 to 20 min.The outcome was mortality.Results:In total,94,541 participants(56.5% female)were included.Over a median(interquartile range)follow-up of 6.9(6.3,7.4)years,2649(2.8%)deaths occurred.Intensity moderated the association between how the most active minutes of the day were accumulated and mortality risk,expressed relative to sporadically accumulated moderate PA.If the most active minutes were of moderate intensity,the risk of mortality was halved for continuous compared to sporadic accumulation,irrespective of duration;if the most active minutes were of vigorous intensity,a continuous bout was associated with the lowest risk for durations under 5 min(e.g.,3 min:hazard ratio(HR)=0.27,95% confidence interval(95%CI):0.21-0.34),while sporadic accumulation was associated with the lowest risk for durations beyond 5 min(HR=0.11,95%CI:0.08-0.15 for the most active 20 min).Conclusion:Optimal PA patterns for reducing mortality differ by intensity and duration.For moderate-intensity PA,a lower mortality risk may be optimized by prioritizing continuous PA for up to 20 min.However,for vigorous-intensity PA,multiple short bouts(<5 min)may be optimal.This suggests tailored PA recommendations may enhance longevity benefits.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these netw...Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.展开更多
Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often f...Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often fail to capture the non-linear relationships among concrete constituents,especially with the growing use of supple-mentary cementitious materials and recycled aggregates.This study presents an integrated machine learning framework for concrete strength prediction,combining advanced regression models—namely CatBoost—with metaheuristic optimization algorithms,with a particular focus on the Somersaulting Spider Optimizer(SSO).A comprehensive dataset encompassing diverse mix proportions and material types was used to evaluate baseline machine learning models,including CatBoost,XGBoost,ExtraTrees,and RandomForest.Among these,CatBoost demonstrated superior accuracy across multiple performance metrics.To further enhance predictive capability,several bio-inspired optimizers were employed for hyperparameter tuning.The SSO-CatBoost hybrid achieved the lowest mean squared error and highest correlation coefficients,outperforming other metaheuristic approaches such as Genetic Algorithm,Particle Swarm Optimization,and Grey Wolf Optimizer.Statistical significance was established through Analysis of Variance and Wilcoxon signed-rank testing,confirming the robustness of the optimized models.The proposed methodology not only delivers improved predictive performance but also offers a transparent framework for mix design optimization,supporting data-driven decision making in sustainable and resilient infrastructure development.展开更多
A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or l...A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.展开更多
The increasing number of interconnected devices and the incorporation of smart technology into contemporary healthcare systems have significantly raised the attack surface of cyber threats.The early detection of threa...The increasing number of interconnected devices and the incorporation of smart technology into contemporary healthcare systems have significantly raised the attack surface of cyber threats.The early detection of threats is both necessary and complex,yet these interconnected healthcare settings generate enormous amounts of heterogeneous data.Traditional Intrusion Detection Systems(IDS),which are generally centralized and machine learning-based,often fail to address the rapidly changing nature of cyberattacks and are challenged by ethical concerns related to patient data privacy.Moreover,traditional AI-driven IDS usually face challenges in handling large-scale,heterogeneous healthcare data while ensuring data privacy and operational efficiency.To address these issues,emerging technologies such as Big Data Analytics(BDA)and Federated Learning(FL)provide a hybrid framework for scalable,adaptive intrusion detection in IoT-driven healthcare systems.Big data techniques enable processing large-scale,highdimensional healthcare data,and FL can be used to train a model in a decentralized manner without transferring raw data,thereby maintaining privacy between institutions.This research proposes a privacy-preserving Federated Learning–based model that efficiently detects cyber threats in connected healthcare systems while ensuring distributed big data processing,privacy,and compliance with ethical regulations.To strengthen the reliability of the reported findings,the resultswere validated using cross-dataset testing and 95%confidence intervals derived frombootstrap analysis,confirming consistent performance across heterogeneous healthcare data distributions.This solution takes a significant step toward securing next-generation healthcare infrastructure by combining scalability,privacy,adaptability,and earlydetection capabilities.The proposed global model achieves a test accuracy of 99.93%±0.03(95%CI)and amiss-rate of only 0.07%±0.02,representing state-of-the-art performance in privacy-preserving intrusion detection.The proposed FL-driven IDS framework offers an efficient,privacy-preserving,and scalable solution for securing next-generation healthcare infrastructures by combining adaptability,early detection,and ethical data management.展开更多
For the chip integration of MEMS(micro-electromechanical system) safety and arming device, a miniature detonator needs to be developed to reduce the weight and volume of explosive train. A Si-based micro-detonator is ...For the chip integration of MEMS(micro-electromechanical system) safety and arming device, a miniature detonator needs to be developed to reduce the weight and volume of explosive train. A Si-based micro-detonator is designed and fabricated, which meets the requirement of MEMS safety and arming device. The firing sensitivity of micro-detonator is tested according to GJB/z377A-94 sensitivity test methods:Langlie. The function time of micro-detonator is measured using wire probe and photoelectric transducer. The result shows the average firing voltage is 6.4 V when the discharge capacitance of firing electro-circuit is 33 mF. And the average function time is 5.48 ms. The firing energy actually utilized by Si-based micro-detonator is explored.展开更多
Colorectal cancer is the third most common cancer and is highly fatal. During the last several years, research has been primarily based on the study of expression profiles using microarray technology. But now, investi...Colorectal cancer is the third most common cancer and is highly fatal. During the last several years, research has been primarily based on the study of expression profiles using microarray technology. But now, investigators are putting into practice proteomic analyses of cancer tissues and cells to identify new diagnostic or therapeutic biomarkers for this cancer. Because the proteome reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumor markers for disease diagnosis and therapy monitoring. This review summarizes the most relevant applications of proteomics the biomarker discovery for colorectal cancer.展开更多
This paper summarizes the results of the researches on the middle and upper atmosphere obtained by Chinese scientists in 2008-2010.The focuses are specifically placed on the researches being associated with ground-bas...This paper summarizes the results of the researches on the middle and upper atmosphere obtained by Chinese scientists in 2008-2010.The focuses are specifically placed on the researches being associated with ground-based observation capability development,dynamical processes,the property of atmospheric circulation and the chemistry-climate coupling of the middle atmospheric layers.展开更多
Therapeutic experiments are commonly performed on laboratory animals to inves-tigate the possible mechanism(s)of action of toxic agents as well as drugs or sub-stances under consideration.The use of toxins in laborato...Therapeutic experiments are commonly performed on laboratory animals to inves-tigate the possible mechanism(s)of action of toxic agents as well as drugs or sub-stances under consideration.The use of toxins in laboratory animal models,including rats,is intended to cause toxicity.This study aimed to investigate different models of hepatotoxicity and nephrotoxicity in laboratory animals to help researchers advance their research goals.The current narrative review used databases such as Medline,Web of Science,Scopus,and Embase and appropriate keywords until June 2021.Nephrotoxicity and hepatotoxicity models derived from some toxic agents such as cisplatin,acetaminophen,doxorubicin,some anticancer drugs,and other materials through various signaling pathways are investigated.To understand the models of renal or hepatotoxicity in laboratory animals,we have provided a list of toxic agents and their toxicity procedures in this review.展开更多
An algorithm of broadband minimum variance distortionless response(MVDR) based on the frequency energy normalization is proposed.First,every narrowband frequency component of the broadband signal is normalized by the ...An algorithm of broadband minimum variance distortionless response(MVDR) based on the frequency energy normalization is proposed.First,every narrowband frequency component of the broadband signal is normalized by the total narrowband energy of all array elements,and the narrowband power is calculated by MVDR.Finally,final spatial energy spectrum can be obtained by averaging or summing all results of every narrowband frequency bin.Any prior-information about the noise or the signal is unnecessary for the proposed method in this paper.The processing gain of the proposed method compared to the conventional broadband MVDR can be obtained as long as the amplitude fluctuation of the array noise frequency spectrum is severer than that of the target signal.The validity of the method is validated by the optimal signal detection theory.Simulation and real data are used to validate the performance of the method.Analysis results show that about 4 dB processing gain compared to the general broadband MVDR can be reached by the proposed method.展开更多
In this report we summarize the research results by Chinese scientists in 2012–2014. The focuses are placed on the researches of the middle and upper atmosphere, specifically the researches related to ground-based ob...In this report we summarize the research results by Chinese scientists in 2012–2014. The focuses are placed on the researches of the middle and upper atmosphere, specifically the researches related to ground-based observation capability development, dynamical processes, the property of circulation and chemistry-climate coupling of the middle atmospheric layers.展开更多
Rheumatoid arthritis(RA)is a common autoimmune disease characterized by progressive joint inflammation and destruction,deformity,loss of mobility,and permanent disability.Although the cellular and molecular mechanisms...Rheumatoid arthritis(RA)is a common autoimmune disease characterized by progressive joint inflammation and destruction,deformity,loss of mobility,and permanent disability.Although the cellular and molecular mechanisms involved in RA are understood in detail,no drugs or therapies can completely cure RA.Many long-term efforts have been directed towards a better understanding of RA pathogenesis and the development of new classes of therapeutics.Thus,the ongoing elucidation of pathogenic events underlying RA mostly relies on studies of animal models.Herein,we comprehensively review and discuss the characteristics,challenges,and unresolved of issues of various experimental models of RA to provide a basis and reference for the rational selection of experimental RA models for basic investigations into traditional Chinese medicine(TCM).展开更多
The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a wat...The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.展开更多
During the past two years,space environment has achieved great development in space environment monitoring,model research,system developing and space environment service in China.In this paper,we mainly introduce spac...During the past two years,space environment has achieved great development in space environment monitoring,model research,system developing and space environment service in China.In this paper,we mainly introduce space environment safety support for Shenzhou-7 manned spacecraft,two typical space environment operation platforms,and the advance of Re-locatable Atmospheric Observatory(RAO).At the last part of this paper,the Sub-committee on Space Environment(SSE) which was set up in 2009 under the Technical Committee on Space Technology and Operation of Standardization Administration of China is briefly introduced.展开更多
基金funded by a special programof the Dutch Ministry of Health, Welfare and Sport (Ministerie van Volksgezondheid,Welzijn en SportGrant Number N/A).
文摘In recent years,significant insights have been gathered into the effectiveness of lifestyle interventions in the treatment of chronic non-communicable diseases(NCD).To speed up the implementation of evidence-based lifestyle medicine,we developed a research agenda in collaboration with Dutch experts in treating NCD,using a hybrid Delphi approach.The research agenda focuses on four key themes:(1)promoting sustainable behavioural change at patient,healthcare professional and organisational levels;(2)optimising research designs,methodology and outcomes for the evaluation of effectiveness and implementation of lifestyle medicine modalities in healthcare practice;(3)elucidating biological mechanisms underlying successful lifestyle interventions and(4)advancing data infrastructure to ensure accessible data for citizens,healthcare professionals,researchers and health insurers for monitoring and evaluation of health and lifestyle outcomes.Collectively,the identified knowledge questions across these four themes provide guidance for(applied)research towards lifestyle medicine in healthcare.
基金National Council for Scientific and Technological Development,CNPq,Research Productivity,grant numbers:304747/2018-1/310135/2022-2(Reis LO).
文摘Objective:To determine the safety and the role of modulating cytokines and proteases in the immune response to intravesical Bacillus Calmette-Guérin(BCG)when primed with systemic intradermal BCG.Methods:Phase 1 and mechanistic longitudinal,prospective,single-blind randomized study(NCT04806178).Twenty-one non-muscle invasive urothelial bladder cancer patients undergoing intravesical adjuvant BCG after transurethral resection of bladder tumor(TURBT)in a teaching hospital between September 2021 and April 2023 were randomized to 0.1 mL of intradermal BCG vaccine or placebo(0.9%saline)administered 15 days before the start of intravesical BCG therapy.Blood samples were evaluated mechanistically regarding eight cytokines serum levels interferon-induced transmembrane protein 3 Gene(IFITM3),Interleukin 1 beta(IL1-BETA),interleukin-2 receptor alpha chain(IL2 RA),Interleukin 6(IL 6),Interleukin 10(IL 10),Tumor necrosis factor alpha(TNF-α),Interferon-β,AXL,and one protease CASPASE 8.Results:After 1 exclusion,twenty patients were randomized to intradermal BCG(n=11)and intradermal placebo(n=9).There was no difference in adverse effects emerging from the intravesical Onco-BCG therapy,and no difference in the expression of the cytokines and proteases analyzed between control and intervention,and over time.Conclusions:Intradermal BCG administration before intravesical application was safe,with no increase in adverse effects.It also does not seem to change the analyzed targets during the intravesical induction-phase BCG.Other immune targets should be explored in the future.The Brazilian tuberculosis-endemic status,where BCG vaccination is mandatory,might have affected the results.
基金supported by the Korea Institute of Energy Technology Evaluation and Planning(KETEP)and the Ministry of Trade,Industry&Energy(MOTIE)of the Republic of Korea(No.RS-2025-02315209).
文摘There is a need for accurate prediction of heat and mass transfer in aerodynamically designed,non-Newtonian nanofluids across aerodynamically designed,high-flux biomedical micro-devices for thermal management and reactive coating processes,but existing work is not uncharacteristically remiss regarding viscoelasticity,radiative heating,viscous dissipation,and homogeneous–heterogeneous reactions within a single scheme that is calibrated.This research investigates the flow of Williamson nanofluid across a dynamically wedged surface under conditions that include viscous dissipation,thermal radiation,and homogeneous-heterogeneous reactions.The paper develops a detailed mathematical approach that utilizes boundary layers to transform partial differential equations into ordinary differential equations using similarity transformations.RK4 is the technique for gaining numerical solutions,but with the addition of ANNs,there is an improvement in prediction accuracy and computational efficiency.The study investigates the influence of wedge angle parameter,along with Weissenberg number,thermal radiation parameter and Brownian motion parameter,and Schmidt number,on velocity distribution,temperature distribution,and concentra-tion distribution.Enhanced Weissenberg numbers enhance viscoelastic responses that modify velocity patterns,but radiation parameters and thermophoresis have key impacts on thermal transfer phenomena.This research develops findings that are of enormous application in aerospace,biomedical(artificial hearts and drug delivery),and industrial cooling technology applications.New findings on non-Newtonian nanofluids under full flow systems are included in this work to enhance heat transfer methods in novel fluid-based systems.
基金supported by grants PID2020-120308RB-I00 and PID2023-147802OB-I00 funded by MICIU/AEI/10.13039/501100011033FEDER,UE,by Aligning Science Across Parkinson’s(ref.ASAP-020505)through the Michael J.Fox Foundation for Parkinson’s Research+1 种基金by CiberNed Intramural Collaborative Projects(ref.PI2020/09)by the Spanish Fundación Mutua Madrile?a de Investigación Médica(to JLL)。
文摘The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.
基金funded by UK Research and Innovation(research which commenced between October 1,2020-March 31,2021,Grant ref MC_PC_20029April 1,2021-September 31,2022,Grant ref MC_PC_20058)supported by the National Institute for Health Research(NIHR)Leicester Biomedical Research Centre and NIHR Applied Research CollaborationEast Midlands(ARC-EM)。
文摘Background:Recent evidence suggests continuous bouts of physical activity(PA)are associated with longevity.We hypothesized the risk of mortality would be lower when the most active minutes of the day were in a continuous bout.Methods:PA was assessed using accelerometery in UK Biobank participants.The intensity of the most active continuous(MXCONT)and accumulated(MX)X min of the day,and their ratio(MXRATIO=MXCONT/MX),were determined.MXRATIO indicates how the most active minutes of the day are accumulated,ranging from a single continuous bout through to sporadic accumulation spread across the day.Durations(X)considered ranged from 1 to 20 min.The outcome was mortality.Results:In total,94,541 participants(56.5% female)were included.Over a median(interquartile range)follow-up of 6.9(6.3,7.4)years,2649(2.8%)deaths occurred.Intensity moderated the association between how the most active minutes of the day were accumulated and mortality risk,expressed relative to sporadically accumulated moderate PA.If the most active minutes were of moderate intensity,the risk of mortality was halved for continuous compared to sporadic accumulation,irrespective of duration;if the most active minutes were of vigorous intensity,a continuous bout was associated with the lowest risk for durations under 5 min(e.g.,3 min:hazard ratio(HR)=0.27,95% confidence interval(95%CI):0.21-0.34),while sporadic accumulation was associated with the lowest risk for durations beyond 5 min(HR=0.11,95%CI:0.08-0.15 for the most active 20 min).Conclusion:Optimal PA patterns for reducing mortality differ by intensity and duration.For moderate-intensity PA,a lower mortality risk may be optimized by prioritizing continuous PA for up to 20 min.However,for vigorous-intensity PA,multiple short bouts(<5 min)may be optimal.This suggests tailored PA recommendations may enhance longevity benefits.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘Wireless Sensor Networks(WSNs)have become foundational in numerous real-world applications,ranging from environmental monitoring and industrial automation to healthcare systems and smart city development.As these networks continue to grow in scale and complexity,the need for energy-efficient,scalable,and robust communication protocols becomes more critical than ever.Metaheuristic algorithms have shown significant promise in addressing these challenges,offering flexible and effective solutions for optimizing WSN performance.Among them,the Grey Wolf Optimizer(GWO)algorithm has attracted growing attention due to its simplicity,fast convergence,and strong global search capabilities.Accordingly,this survey provides an in-depth review of the applications of GWO and its variants for clustering,multi-hop routing,and hybrid cluster-based routing in WSNs.We categorize and analyze the existing GWO-based approaches across these key network optimization tasks,discussing the different problem formulations,decision variables,objective functions,and performance metrics used.In doing so,we examine standard GWO,multi-objective GWO,and hybrid GWO models that incorporate other computational intelligence techniques.Each method is evaluated based on how effectively it addresses the core constraints of WSNs,including energy consumption,communication overhead,and network lifetime.Finally,this survey outlines existing gaps in the literature and proposes potential future research directions aimed at enhancing the effectiveness and real-world applicability of GWO-based techniques for WSN clustering and routing.Our goal is to provide researchers and practitioners with a clear,structured understanding of the current state of GWO in WSNs and inspire further innovation in this evolving field.
文摘Accurate prediction of concrete compressive strength is fundamental for optimizing mix designs,improving material utilization,and ensuring structural safety in modern construction.Traditional empirical methods often fail to capture the non-linear relationships among concrete constituents,especially with the growing use of supple-mentary cementitious materials and recycled aggregates.This study presents an integrated machine learning framework for concrete strength prediction,combining advanced regression models—namely CatBoost—with metaheuristic optimization algorithms,with a particular focus on the Somersaulting Spider Optimizer(SSO).A comprehensive dataset encompassing diverse mix proportions and material types was used to evaluate baseline machine learning models,including CatBoost,XGBoost,ExtraTrees,and RandomForest.Among these,CatBoost demonstrated superior accuracy across multiple performance metrics.To further enhance predictive capability,several bio-inspired optimizers were employed for hyperparameter tuning.The SSO-CatBoost hybrid achieved the lowest mean squared error and highest correlation coefficients,outperforming other metaheuristic approaches such as Genetic Algorithm,Particle Swarm Optimization,and Grey Wolf Optimizer.Statistical significance was established through Analysis of Variance and Wilcoxon signed-rank testing,confirming the robustness of the optimized models.The proposed methodology not only delivers improved predictive performance but also offers a transparent framework for mix design optimization,supporting data-driven decision making in sustainable and resilient infrastructure development.
基金The authors extend their appreciation to King Saud University,Saudi Arabia for funding this work through the Ongoing Research Funding Program(ORF-2025-704),King Saud University,Riyadh,Saudi Arabia.
文摘A novel siphon-based divide-and-conquer(SbDaC)policy is presented in this paper for the synthesis of Petri net(PN)based liveness-enforcing supervisors(LES)for flexible manufacturing systems(FMS)prone to deadlocks or livelocks.The proposed method takes an uncontrolled and bounded PN model(UPNM)of the FMS.Firstly,the reduced PNM(RPNM)is obtained from the UPNM by using PN reduction rules to reduce the computation burden.Then,the set of strict minimal siphons(SMSs)of the RPNM is computed.Next,the complementary set of SMSs is computed from the set of SMSs.By the union of these two sets,the superset of SMSs is computed.Finally,the set of subnets of the RPNM is obtained by applying the PN reduction rules to the superset of SMSs.All these subnets suffer from deadlocks.These subnets are then ordered from the smallest one to the largest one based on a criterion.To enforce liveness on these subnets,a set of control places(CPs)is computed starting from the smallest subnet to the largest one.Once all subnets are live,this process provides the LES,consisting of a set of CPs to be used for the UPNM.The live controlled PN model(CPNM)is constructed by merging the LES with the UPNM.The SbDaC policy is applicable to all classes of PNs related to FMS prone to deadlocks or livelocks.Several FMS examples are considered from the literature to highlight the applicability of the SbDaC policy.In particular,three examples are utilized to emphasize the importance,applicability and effectiveness of the SbDaC policy to realistic FMS with very large state spaces.
文摘The increasing number of interconnected devices and the incorporation of smart technology into contemporary healthcare systems have significantly raised the attack surface of cyber threats.The early detection of threats is both necessary and complex,yet these interconnected healthcare settings generate enormous amounts of heterogeneous data.Traditional Intrusion Detection Systems(IDS),which are generally centralized and machine learning-based,often fail to address the rapidly changing nature of cyberattacks and are challenged by ethical concerns related to patient data privacy.Moreover,traditional AI-driven IDS usually face challenges in handling large-scale,heterogeneous healthcare data while ensuring data privacy and operational efficiency.To address these issues,emerging technologies such as Big Data Analytics(BDA)and Federated Learning(FL)provide a hybrid framework for scalable,adaptive intrusion detection in IoT-driven healthcare systems.Big data techniques enable processing large-scale,highdimensional healthcare data,and FL can be used to train a model in a decentralized manner without transferring raw data,thereby maintaining privacy between institutions.This research proposes a privacy-preserving Federated Learning–based model that efficiently detects cyber threats in connected healthcare systems while ensuring distributed big data processing,privacy,and compliance with ethical regulations.To strengthen the reliability of the reported findings,the resultswere validated using cross-dataset testing and 95%confidence intervals derived frombootstrap analysis,confirming consistent performance across heterogeneous healthcare data distributions.This solution takes a significant step toward securing next-generation healthcare infrastructure by combining scalability,privacy,adaptability,and earlydetection capabilities.The proposed global model achieves a test accuracy of 99.93%±0.03(95%CI)and amiss-rate of only 0.07%±0.02,representing state-of-the-art performance in privacy-preserving intrusion detection.The proposed FL-driven IDS framework offers an efficient,privacy-preserving,and scalable solution for securing next-generation healthcare infrastructures by combining adaptability,early detection,and ethical data management.
文摘For the chip integration of MEMS(micro-electromechanical system) safety and arming device, a miniature detonator needs to be developed to reduce the weight and volume of explosive train. A Si-based micro-detonator is designed and fabricated, which meets the requirement of MEMS safety and arming device. The firing sensitivity of micro-detonator is tested according to GJB/z377A-94 sensitivity test methods:Langlie. The function time of micro-detonator is measured using wire probe and photoelectric transducer. The result shows the average firing voltage is 6.4 V when the discharge capacitance of firing electro-circuit is 33 mF. And the average function time is 5.48 ms. The firing energy actually utilized by Si-based micro-detonator is explored.
文摘Colorectal cancer is the third most common cancer and is highly fatal. During the last several years, research has been primarily based on the study of expression profiles using microarray technology. But now, investigators are putting into practice proteomic analyses of cancer tissues and cells to identify new diagnostic or therapeutic biomarkers for this cancer. Because the proteome reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumor markers for disease diagnosis and therapy monitoring. This review summarizes the most relevant applications of proteomics the biomarker discovery for colorectal cancer.
基金Supported by the National Natural Sciences Foundation of China under grant (40830102,40333034)the Knowledge Innovation Project of Chinese Academy of Sciences under Grant (KZCX2-YW-123)
文摘This paper summarizes the results of the researches on the middle and upper atmosphere obtained by Chinese scientists in 2008-2010.The focuses are specifically placed on the researches being associated with ground-based observation capability development,dynamical processes,the property of atmospheric circulation and the chemistry-climate coupling of the middle atmospheric layers.
文摘Therapeutic experiments are commonly performed on laboratory animals to inves-tigate the possible mechanism(s)of action of toxic agents as well as drugs or sub-stances under consideration.The use of toxins in laboratory animal models,including rats,is intended to cause toxicity.This study aimed to investigate different models of hepatotoxicity and nephrotoxicity in laboratory animals to help researchers advance their research goals.The current narrative review used databases such as Medline,Web of Science,Scopus,and Embase and appropriate keywords until June 2021.Nephrotoxicity and hepatotoxicity models derived from some toxic agents such as cisplatin,acetaminophen,doxorubicin,some anticancer drugs,and other materials through various signaling pathways are investigated.To understand the models of renal or hepatotoxicity in laboratory animals,we have provided a list of toxic agents and their toxicity procedures in this review.
基金Sponsored by New Century Excellent Talent Support Project (NCET-04-0545)
文摘An algorithm of broadband minimum variance distortionless response(MVDR) based on the frequency energy normalization is proposed.First,every narrowband frequency component of the broadband signal is normalized by the total narrowband energy of all array elements,and the narrowband power is calculated by MVDR.Finally,final spatial energy spectrum can be obtained by averaging or summing all results of every narrowband frequency bin.Any prior-information about the noise or the signal is unnecessary for the proposed method in this paper.The processing gain of the proposed method compared to the conventional broadband MVDR can be obtained as long as the amplitude fluctuation of the array noise frequency spectrum is severer than that of the target signal.The validity of the method is validated by the optimal signal detection theory.Simulation and real data are used to validate the performance of the method.Analysis results show that about 4 dB processing gain compared to the general broadband MVDR can be reached by the proposed method.
文摘In this report we summarize the research results by Chinese scientists in 2012–2014. The focuses are placed on the researches of the middle and upper atmosphere, specifically the researches related to ground-based observation capability development, dynamical processes, the property of circulation and chemistry-climate coupling of the middle atmospheric layers.
基金funding support from the Science and Technology Innovation Program of Hunan Province(No.XKJ[2021]43-2021RC4035)supported by the Hunan Furong Distinguished Scholar Program(No.XJT[2020]58)the Chinese Academy of Engineering Academician LIU Liang’s Workstation of Hunan(No.XKXT[2020]34)。
文摘Rheumatoid arthritis(RA)is a common autoimmune disease characterized by progressive joint inflammation and destruction,deformity,loss of mobility,and permanent disability.Although the cellular and molecular mechanisms involved in RA are understood in detail,no drugs or therapies can completely cure RA.Many long-term efforts have been directed towards a better understanding of RA pathogenesis and the development of new classes of therapeutics.Thus,the ongoing elucidation of pathogenic events underlying RA mostly relies on studies of animal models.Herein,we comprehensively review and discuss the characteristics,challenges,and unresolved of issues of various experimental models of RA to provide a basis and reference for the rational selection of experimental RA models for basic investigations into traditional Chinese medicine(TCM).
基金funded by King Saud University,Riyadh,Saudi Arabia,through the Ongo-ing Research Funding program—Research Chairs(ORF-RC-2025-0127)funded via Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R443).
文摘The present investigation inspects the unsteady,incompressible MHD-induced flow of a ternary hybrid nanofluid made of SiO_(2)(silicon dioxide),ZnO(zinc oxide),and MWCNT(multi-walled carbon nanotubes)suspended in a water-ethylene glycol base fluid between two perforated squeezing Riga plates.This problem is important because it helps us understand the complicated connections between magnetic fields,nanofluid dynamics,and heat transport,all of which are critical for designing thermal management systems.These findings are especially useful for improving the design of innovative cooling technologies in electronics,energy systems,and healthcare applications.No prior study has been done on the theoretical study of the flow of ternary nanofluid(SiO_(2)+ZnO+MWCNT/Water−EthylGl ycol,(60∶40))past a pierced squeezed Riga plates using the boundary value problem solver 4th-order collocation(BVP4C)numerical approach to date.So,the current work has been carried out to fill this gap,and the core purpose of this study is to explore the aspects that enhance the heat transfer of base fluids(H_(2)O/EG)suspended with three nanomaterials SiO_(2),ZnO,and MWCNT.The Riga plates introduce electromagnetic forcing through an embedded array of magnets and electrodes,generating Lorentz forces to regulate the flow.The squeezing effect introduces dynamic boundary movement,which enhances mixing;however,permeability,due to porosity,replicates the true material limits.Similarity transformations of the Navier-Stokes and energy equations result in a highly nonlinear set of ordinary differential equations that govern momentum and thermal energy transport.The subsequent boundary value problem is solved utilizing the BVP4C numerical approach.The study observes the impact of magnetic parameters,squeezing velocity,solid volume percentages of the three nanoparticles,and porous medium factors on velocity and temperature fields.Results show that magnetic fields reduce the velocity profile by 6.75%due to increased squeezing and medium effects.Tri-hybrid nanofluids notice a 9%rise in temperature with higher thermal radiation.
文摘During the past two years,space environment has achieved great development in space environment monitoring,model research,system developing and space environment service in China.In this paper,we mainly introduce space environment safety support for Shenzhou-7 manned spacecraft,two typical space environment operation platforms,and the advance of Re-locatable Atmospheric Observatory(RAO).At the last part of this paper,the Sub-committee on Space Environment(SSE) which was set up in 2009 under the Technical Committee on Space Technology and Operation of Standardization Administration of China is briefly introduced.
