This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Consi...This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.展开更多
Seismic intensity is critical for post-earthquake hazard assessment and response,but is often delayed because field surveys are required.Here,we propose a simple scheme for quick prediction of earthquake ground shakin...Seismic intensity is critical for post-earthquake hazard assessment and response,but is often delayed because field surveys are required.Here,we propose a simple scheme for quick prediction of earthquake ground shaking intensity using high-rate Global Navigation Satellite System(GNSS)data.In the scheme,high-rate GNSS displacement waveforms and static GNSS coseismic offsets are first used to invert the fault rupture process based on a one-fault model.The kinematic slip model is then employed as input for kinematic forward simulation to predict strong ground motion,which is subsequently convert into seismic intensities according to the China seismic intensity scale(GB/T 17742–2020).We take the 2021 Mw 7.3 Maduo Earthquake as a case study to illustrate the feasibility of this scheme.Our results show that the seismic intensity produced by the one-fault model is consistent with that from field investigations,especially in meizoseismal zones,suggesting that the scheme may serve as a potential solution for quick prediction of seismic intensity,which helps to disaster relief efforts after strong earthquakes.展开更多
As underground mining advances to greater depths,cemented paste backfill(CPB)is increasingly subjected to complex thermo-mechanical loading conditions,including multiaxial stress states and elevated temperatures.This ...As underground mining advances to greater depths,cemented paste backfill(CPB)is increasingly subjected to complex thermo-mechanical loading conditions,including multiaxial stress states and elevated temperatures.This study investigates the coupled effects of field-representative vertical self-weight and horizontal rockwall closure stresses,along with in-situ temperatures,on the mechanical behavior and pore water pressure(PWP)evolution of CPB.Experiments were conducted using a novel apparatus capable of controlling multiaxial stress and temperature during curing,replicating in-situ stress paths and thermal profiles typical of deep mine environments.Results show that multiaxial stress enhances CPB strength and stiffness by promoting denser particle packing,reducing porosity,and increasing frictional resistance.Elevated temperatures independently accelerate early-age cement hydration,further improving bond strength and stiffness.When combined,multiaxial stress and elevated temperature produce a synergistic enhancement in unconfined compressive strength(UCS)and elastic modulus,as confirmed by two-way ANOVA and synergy index analysis.PWP responses were also highly sensitive to thermo-mechanical conditions.The evolution of positive and negative PWP was governed by the interplay of thermal expansion,hydration-induced desaturation,and mechanical compaction.Multiaxial stress amplified early positive PWP and delayed its dissipation,whereas elevated temperature accelerated hydration and reduced pore pressure,leading to enhanced suction at later ages.A transient“stress-induced resaturation”effect was observed under late-stage excessive horizontal stress but was mitigated by elevated temperatures.These findings provide critical insights into the coupled mechanical and hydraulic behavior of CPB under realistic field conditions and offer guidance for optimizing backfill design,binder content,and barricade stability in deep mining applications.展开更多
This study aimed to investigate the effects of infant feces-derived Bifidobacterium breve CCFM1078 on rheumatoid cachexia(RC).Twenty-four female Wistar rats were assigned to 3 groups:CON group(normal saline by gavage)...This study aimed to investigate the effects of infant feces-derived Bifidobacterium breve CCFM1078 on rheumatoid cachexia(RC).Twenty-four female Wistar rats were assigned to 3 groups:CON group(normal saline by gavage),CIA group(collagen-induced arthritis(CIA),normal saline by gavage),and CCFM1078 group(CIA,3×10^(9)CFU/(rat·day)B.breve CCFM1078 gavage).The results demonstrated that B.breve CCFM1078 not only improved skeletal muscle function in CIA rats,but also modulated the gut microbiota,skeletal muscle metabolism and hormone levels,reduced inflammation in the knee joint and skeletal muscles,decreased activity of the nuclear factor κB(NF-κB)inflammatory signaling pathway,enhanced the insulin receptor substrate 1(IRS1)/phosphatidylinositol 3-kinase/protein kinase(PI3K/Akt)signaling pathway,promoted skeletal muscle differentiation,and maintained skeletal muscle fiber diameter,consequently slowing down the progression of RC.These findings suggested that B.breve CCFM1078 may have a beneficial role as part of a dietary intervention for RC,enhancing overall therapeutic effects.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
Qingke,a staple crop grown on the high-altitude Tibetan Plateau,has evolved a metabolomic profile providing both environmental stress resilience and human nutrition.We review the hypothesis that the metabolites that c...Qingke,a staple crop grown on the high-altitude Tibetan Plateau,has evolved a metabolomic profile providing both environmental stress resilience and human nutrition.We review the hypothesis that the metabolites that confer cold and UV resistance on the crop also facilitate human adaptation to high-altitude stresses.Specifically,β-glucans regulate blood glucose primarily via short-chain fatty acids(SCFAs)produced through gut microbiota fermentation,which directly mediate glucose homeostasis.Phenolamides accumulate via the phenylpropanoid pathway,with chalcone isomerase(CHI)serving as a key enzyme in flavonoid biosynthesis and enhancing UV-B resistance.Under low temperatures,β-glucans improve frost tolerance by modulating osmotic balance and inhibiting ice-nucleating proteins,while lipids maintain membrane fluidity to sustain cellular function during cold stress.Importantly,we explore the hypothesis that these same metabolites,upon consumption,may facilitate human adaptation to high-altitude stresses.This hypothesis is supported by preliminary epidemiological associations between Qingke consumption and favorable health outcomes in high-altitude populations,as well as established bioactivities of the implicated metabolites in vitro and in animal models.However,direct causal evidence in humans and a comprehensive understanding of the underlying molecular mechanisms remain key knowledge gaps that warrant future investigation.Qingke as a unique resource at the interface of agricultural resilience and human nutrition.Understanding its metabolic blueprint will inform the development of functional foods and climate-resilient crops.展开更多
Adhesively bonded joints are widely used in modern lightweight structures due to their high strengthto-weight ratio and design flexibility.However,the reliable non-destructive evaluation of bond integrity remains a si...Adhesively bonded joints are widely used in modern lightweight structures due to their high strengthto-weight ratio and design flexibility.However,the reliable non-destructive evaluation of bond integrity remains a significant challenge.This study presents a numerical investigation of adhesively bonded joints with different adhesive properties using ultrasonic guided waves.The main focus of the investigation is to evaluate the feasibility of using guided waves to assess bond integrity,particularly for detecting challenging weak bonds.For this purpose,a theoretical analysis of dispersion curves was conducted,revealing that the S0 Lamb wave mode is significantly sensitive to variations in adhesive properties in the 300-700 kHz frequency range.Finite element modelling was used to analyse the propagation of guided waves in two scenarios:an adhesively bonded aluminum structure and a more complex configuration-adhesively bonded lap joints.The Short-Time Fourier Transform(STFT)was used to process the obtained results and determine the group velocities of guided waves.By analysing the group velocity characteristics,their dependence on the adhesive properties was identified.In the first scenario,a clear separation of S0 modes from A0 modes was observed in the STFT analysis,with a decrease in group velocity as adhesive stiffness increased.For the more complex lap joint scenario,the separation between A0 and S0 modes was less distinct.However,the analysis of the average group velocity shows a dependence of average group velocity on adhesive properties.This is similar to the first scenario.There is a decrease in average group velocity as adhesive stiffness increases.The results obtained demonstrate that guided wavebased methods have a high potential for non-destructive evaluation of adhesively bonded structures,including the detection of weak bonds.展开更多
Mechanical tension is widely recognized as the primary stimulus underlying the molecular mechanisms that influence muscle hypertrophy induced by resistance training.Despite this,several outdated or overstated concepts...Mechanical tension is widely recognized as the primary stimulus underlying the molecular mechanisms that influence muscle hypertrophy induced by resistance training.Despite this,several outdated or overstated concepts continue to persist,both in the scientific literature and in the practical application of resistance training coaching and program design.Claims that acute hormonal responses,metabolic stress,cell swelling or“the pump”meaningfully contribute to hypertrophy are not supported by scientific evidence.Additionally,the concept of sarcoplasmic hypertrophy as a distinct and functionally meaningful contributor to hypertrophy lacks strong evidence.In this review,we critically evaluate several persistent misconceptions and contrast them with evidence-based mechanistic insights into load-induced hypertrophy.Specifically,we discuss the role(or lack thereof)of systemic hormones,metabolites,and cell swelling in promoting muscle hypertrophy.We also critically review the concept of sarcoplasmic hypertrophy and propose that it is not a meaningful contributor to muscle hypertrophy.Lastly,to translate knowledge for trainees and coaches,we discuss the upper limit of muscle hypertrophy and provide readers with evidence-based,reasonable expectations for muscle hypertrophy.We aimed,through this review,to use scientific evidence to enhance our understanding of what drives muscle hypertrophy and provide an evidence-based framework for resistance exercise training.展开更多
This study proposes a multi-scale simplified residual convolutional neural network(MS-SRCNN)for the precise prediction of Mg-Nd binary alloy compositions from scanning electron microscope(SEM)images.A multi-scale data...This study proposes a multi-scale simplified residual convolutional neural network(MS-SRCNN)for the precise prediction of Mg-Nd binary alloy compositions from scanning electron microscope(SEM)images.A multi-scale data structure is established by spatially aligning and stacking SEM images at different magnifications.The MS-SRCNN significantly reduces computational runtime by over 90%compared to traditional architectures like ResNet50,VGG16,and VGG19,without compromising prediction accuracy.The model demonstrates more excellent predictive performance,achieving a>5%increase in R^(2) compared to single-scale models.Furthermore,the MS-SRCNN exhibits robust composition prediction capability across other Mg-based binary alloys,including Mg-La,Mg-Sn,Mg-Ce,Mg-Sm,Mg-Ag,and Mg-Y,thereby emphasizing its generalization and extrapolation potential.This research establishes a non-destructive,microstructure-informed composition analysis framework,reduces characterization time compared to traditional experiment methods and provides insights into the composition-microstructure relationship in diverse material systems.展开更多
Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite...Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.展开更多
BACKGROUND Prevalence of the main rheumatic diseases in the Republic of Sakha(Yakutia)[RS(Y)],one of the regions of the Russian Federation,differs from the other regions of the Russian Federation due to its ethnic and...BACKGROUND Prevalence of the main rheumatic diseases in the Republic of Sakha(Yakutia)[RS(Y)],one of the regions of the Russian Federation,differs from the other regions of the Russian Federation due to its ethnic and geographic features.Knowledge regarding the prevalence and structure of juvenile idiopathic arthritis(JIA)allows us to shape the work of the pediatric rheumatology service in the region correctly,and optimize the healthcare system and the need for medica-tions.AIM To describe the epidemiological,demographic,clinical,and laboratory characteristics of children with JIA in the RS(Y)and evaluate the main outcomes.METHODS This retrospective cohort study assessed all the data from the medical histories of the patients(n=225)diagnosed with JIA(2016-2023)in the Cardiorheumatology Department of the M.E.Nikolaev National Center of Medicine.Pearson'sχ²test,Fisher's exact test,Mann–Whitney and Kruskal-Wallis tests were used for statistical analyses.RESULTS The ethnic prevalence of JIA is higher in Sakha than in Russian children at 110.1 per 100000 children and 69.4 per 100000 children,respectively.The prevalence of JIA among boys and girls in Sakha was similar,unlike in Russians,where the number of girls predominated.The JIA categories were as follows:(1)Systemic arthritis:3.5%;(2)Oligoarthritis(persistent and extended):33.8%;(3)Rheumatoid factor(RF)(+)polyarthritis:0.9%;(4)RF(-)polyarthritis:14.7%;(5)Enthesitis-related arthritis(ERA):44%;and(6)Psoriatic arthritis:3.1%.Prevalence of the ERA category was 4.4 times higher in Sakha children,but the prevalence of systemic arthritis was 2.9 times lower compared to Russians(P=0.0005).The frequency of uveitis was 10.2%,and the frequency of human leukocyte antigen(HLA)B27 was 39.6%in JIA children.Biologic treatment was received by 40.4%of JIA children and 45.3%achieved remission.CONCLUSION Higher JIA prevalence,male and ERA predominance,related to a higher frequency of HLA B27 are typical in RS(Y).These data might improve the pediatric rheumatology health service.展开更多
BACKGROUND Acute kidney injury(AKI)is a common and serious complication following heart transplantation,significantly impacting patient outcomes and survival rates.AKI after transplantation can lead to prolonged hospi...BACKGROUND Acute kidney injury(AKI)is a common and serious complication following heart transplantation,significantly impacting patient outcomes and survival rates.AKI after transplantation can lead to prolonged hospital stays,increased morbidity,and even mortality.AIM To identify and quantify significant risk factors associated with AKI following heart transplantation through a systematic review and meta-analysis.This study aims to distinguish predictive variables that may inform perioperative risk stratification and clinical decision-making.METHODS Electronic searches on MEDLINE,Google Scholar,ScienceDirect,Clinical-Trials.gov,and Cochrane databases were conducted from inception up till September 1.Included studies were randomized controlled trials,clinical trials,retrospective cohort,and observational studies.Exclusion criteria encompassed studies with pediatric populations,non-English publications,case reports,and studies lacking sufficient data on AKI outcomes.Statistical analysis was performed using RevMan 5.4,reporting dichotomous outcomes as odds ratios(OR)and continuous outcomes as mean differences(MD)with 95%confidence intervals(CI).Quality assessment of the included studies was performed using the New Castle Ottawa Scale.RESULTS Out of 1345 articles,13 studies with 3330 patients were included.Significant risk factors included age[overall MD=2.27 years(95%CI:0.13 to 4.41)],body mass index(BMI)[MD=1.42(95%CI:0.60 to 2.24)],diabetes[overall OR=1.47(95%CI:1.16 to 1.85)],chronic kidney disease(CKD)[OR=2.67(95%CI:1.73 to 4.14)],chronic obstructive pulmonary disorder(COPD)[OR=0.49(95%CI:0.27 to 0.89)],previous thoracic surgery[(OR)=1.27,95%CI:(1.05 to 1.54)],cardio-pulmonary bypass time[(MD)=17.10,95%CI:(6.12 to 28.08)],mechanical ventilation duration[(MD)=30.87 hours,95%CI:(10.69 to 51.05)]and extracorporeal membrane oxygenation[(OR)=2.31,95%CI:(1.25 to 4.26)].Factors not associated with AKI after heart transplantation included Recipients’male sex(P=0.55),donor sex(P=0.11),hypertension(P=0.13),smoking(P=0.20),coronary artery disease(P=0.90),pulmonary artery disease(P=0.81),dilated cardiomyopathy(P=0.79),ventilation duration(P=0.24),ischemic time(P=0.06),use of intra-aortic balloon pump(P=0.14),LVAD transplantation(P=0.83),and Inotropes use(P=0.78).CONCLUSION Age,BMI,diabetes,CKD,COPD,previous thoracic surgery,prolonged CPB time,extended mechanical ventilation,and ECMO use are significant predictors of AKI following heart transplantation,necessitating vigilant monitoring and individualized risk assessment.Conversely,factors such as LVAD implantation and inotrope use showed no significant association,highlighting the need for further investigation into their roles.Future prospective studies are essential to validate these findings,elucidate underlying mechanisms,and develop targeted interventions to mitigate AKI risk and improve patient outcomes.展开更多
Slow Slip Events(SSEs)are critical for understanding subduction zone tectonics and earthquake prediction;however their detection is challenged by low-magnitude-offsets and data gaps.To address these challenges,this pa...Slow Slip Events(SSEs)are critical for understanding subduction zone tectonics and earthquake prediction;however their detection is challenged by low-magnitude-offsets and data gaps.To address these challenges,this paper introduces an optimization-based signal decomposition(OSD)fra mework capable of automatically processing signals with missing data.We applied and validated this framework with GNSS coordinate time series in the Cascadia subduction zone,benchmarking its perfo rmance against the existing SSEs catalog.The proposed high-magnitude-offset detection method achieved an accuracy of67.21%in single-station SSE detection,significantly outperforming traditional methods such as the Relative Strength Index(RSI;32.24%)and deep learning methods like bidirectional Long Short-Term Memory(bi-LSTM;44.41%).Additionally,we proposed a complementary velocity-based screening strategy that successfully identified low-magnitude-offset SSEs and events obscured by data gaps.Through cluster analysis of single-station detection results,we successfully identified the spatiotemporal boundary of the majority of SSEs.Finally,we established an anomaly catalog for uncataloged period from 2018 to 2024,which further demonstrates the method's efficacy in characterizing the spatiotemporal features of SSEs.The OSD-based SSEs detection framework identified SSEs with diverse kinematic patterns using raw geodetic data,facilitating the construction of high-quality SSEs catalogs.These advancements enhance our understanding of subduction zone dynamics and provide a robust technical foundation for seismic hazard assessment.展开更多
Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyz...Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.展开更多
The importance of organic geochemistry and basin modeling is widely recognized and used to understand the source rock potential and hydrocarbon generation history of the Mangahewa Formation,and thereby given the found...The importance of organic geochemistry and basin modeling is widely recognized and used to understand the source rock potential and hydrocarbon generation history of the Mangahewa Formation,and thereby given the foundational role in the petroleum exploration.This study utilized the total organic carbon(TOC)content and hydrogen index(HI)to investigate the dominant kerogen type and hydrogen richness for the significance of petroleum generative potential.The Mangahewa coals and carbonaceous shales exhibit an excellent source rocks,with high total organic content(TOC)of more than 22%.The coals and carbonaceous shales were also characterised by Type Ⅱ‒Ⅲ kerogen with Type Ⅲ kerogen,promising oiland gas-prones.The Mangahewa Formation reached the main oil generation,with vitrinite reflectances between 0.53%and 1.01%.Vitrinite reflectance was also used in developing themal models and reveal the transformation(TR)of 10‒50%kerogen to oil during the Late Miocene.The models also showed that the Mangahewa source rock has a significant oil generation and little expulsion competency,with a TR of up to 54%.These findings support the substantial oil-generating potential in the Taranaki Basin's southern graben and can be used as a guide when developing strategies for an oil exploration program.展开更多
Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcemen...Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcement corrosion.To address these limitations,this study proposes an improved design framework for low-carbon slag concrete that simultaneously incorporates carbonation durability and cover scaling effects into the mix proportioning process.Based on experimental data,a linear predictive model was developed to estimate the 28-day compressive strength of slag concrete,achieving a correlation coefficient of R=0.87711 and a root mean square error(RMSE)of 7.55 MPa.The mechanism-based equation exhibits strong physical interpretability,as each parameter corresponds to a clear physical process,satisfying the requirements of design codes for physical significance.By integrating the strength and carbon-emission models,the carbon-emission efficiency was further analyzed.Across all water–binder ratios(0.3,0.4,0.5),CO_(2) emissions per unit strength decreased steadily with increasing slag content,indicating that carbon efficiency is primarily governed by slag replacement rather than the water/binder ratio.Four design cases,all with a design strength of 30 MPa,were then evaluated to illustrate the combined effects of carbonation and scaling.In Case 1,without considering carbonation durability,the carbonation depth after 50 years exceeded the 25 mm cover,leading to potential corrosion.In Case 2,when carbonation durability was considered,the required actual strength increased to 31.28 MPa.When mild cover scaling of 3 mm was introduced(Case 3),the required strength rose to 34.59 MPa,and under severe scaling of 10 mm(Case 4),it increased to 45.73 MPa.These results indicate that intensified scaling demands higher strength and lower water/binder ratios to maintain durability.Overall,the proposed framework quantitatively balances strength,durability,and embodied carbon,supporting sustainable low-carbon concrete design.展开更多
This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and...This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both classifiers.With BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke predictions.The findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.展开更多
This study investigates the dark side of the non-fungible token(NFT)marketplace,with a focus on understanding the risks,and underlying factors driving fraud in the NFT ecosystem.Using the fraud triangle framework,this...This study investigates the dark side of the non-fungible token(NFT)marketplace,with a focus on understanding the risks,and underlying factors driving fraud in the NFT ecosystem.Using the fraud triangle framework,this study examines pressure,opportunity,and rationalization from individual and organizational perspectives.The research provides a comprehensive understanding of the contributing factors to NFT marketplace fraud by analyzing the reasons behind fraudulent actions.A conceptual framework is developed that includes ten propositions to aid in understanding the complexity of this issue.This study’s outcomes will assist policymakers in crafting efficient approaches to mitigate fraud within the NFT marketplace.展开更多
基金supported by the National Natural Science Foundation of China(62333011,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20222012)+1 种基金the Fundamental Research Funds for the Central Universities(NE2024005)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0594)。
文摘This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.
基金supported by the Basic Scientific Funding of the Institute of Geology,China Earthquake Administration(No.IGCEA2120)the National Natural Science Foundation of China(Nos.U2139202 and 42104007)the Innovation Fund Project for College Teachers of Gansu Provincial Education Department(No.2025A-041)。
文摘Seismic intensity is critical for post-earthquake hazard assessment and response,but is often delayed because field surveys are required.Here,we propose a simple scheme for quick prediction of earthquake ground shaking intensity using high-rate Global Navigation Satellite System(GNSS)data.In the scheme,high-rate GNSS displacement waveforms and static GNSS coseismic offsets are first used to invert the fault rupture process based on a one-fault model.The kinematic slip model is then employed as input for kinematic forward simulation to predict strong ground motion,which is subsequently convert into seismic intensities according to the China seismic intensity scale(GB/T 17742–2020).We take the 2021 Mw 7.3 Maduo Earthquake as a case study to illustrate the feasibility of this scheme.Our results show that the seismic intensity produced by the one-fault model is consistent with that from field investigations,especially in meizoseismal zones,suggesting that the scheme may serve as a potential solution for quick prediction of seismic intensity,which helps to disaster relief efforts after strong earthquakes.
基金the University of Ottawa, the China Scholarship Council and the Natural Sciences and Engineering Research Council of Canada (NSERC) for their financial support.
文摘As underground mining advances to greater depths,cemented paste backfill(CPB)is increasingly subjected to complex thermo-mechanical loading conditions,including multiaxial stress states and elevated temperatures.This study investigates the coupled effects of field-representative vertical self-weight and horizontal rockwall closure stresses,along with in-situ temperatures,on the mechanical behavior and pore water pressure(PWP)evolution of CPB.Experiments were conducted using a novel apparatus capable of controlling multiaxial stress and temperature during curing,replicating in-situ stress paths and thermal profiles typical of deep mine environments.Results show that multiaxial stress enhances CPB strength and stiffness by promoting denser particle packing,reducing porosity,and increasing frictional resistance.Elevated temperatures independently accelerate early-age cement hydration,further improving bond strength and stiffness.When combined,multiaxial stress and elevated temperature produce a synergistic enhancement in unconfined compressive strength(UCS)and elastic modulus,as confirmed by two-way ANOVA and synergy index analysis.PWP responses were also highly sensitive to thermo-mechanical conditions.The evolution of positive and negative PWP was governed by the interplay of thermal expansion,hydration-induced desaturation,and mechanical compaction.Multiaxial stress amplified early positive PWP and delayed its dissipation,whereas elevated temperature accelerated hydration and reduced pore pressure,leading to enhanced suction at later ages.A transient“stress-induced resaturation”effect was observed under late-stage excessive horizontal stress but was mitigated by elevated temperatures.These findings provide critical insights into the coupled mechanical and hydraulic behavior of CPB under realistic field conditions and offer guidance for optimizing backfill design,binder content,and barricade stability in deep mining applications.
基金supported by the National Natural Science Foundation of China(32021005)111 project(BP0719028)the Collaborative Innovation Center of Food Safety and Quality Control in Jiangsu Province.
文摘This study aimed to investigate the effects of infant feces-derived Bifidobacterium breve CCFM1078 on rheumatoid cachexia(RC).Twenty-four female Wistar rats were assigned to 3 groups:CON group(normal saline by gavage),CIA group(collagen-induced arthritis(CIA),normal saline by gavage),and CCFM1078 group(CIA,3×10^(9)CFU/(rat·day)B.breve CCFM1078 gavage).The results demonstrated that B.breve CCFM1078 not only improved skeletal muscle function in CIA rats,but also modulated the gut microbiota,skeletal muscle metabolism and hormone levels,reduced inflammation in the knee joint and skeletal muscles,decreased activity of the nuclear factor κB(NF-κB)inflammatory signaling pathway,enhanced the insulin receptor substrate 1(IRS1)/phosphatidylinositol 3-kinase/protein kinase(PI3K/Akt)signaling pathway,promoted skeletal muscle differentiation,and maintained skeletal muscle fiber diameter,consequently slowing down the progression of RC.These findings suggested that B.breve CCFM1078 may have a beneficial role as part of a dietary intervention for RC,enhancing overall therapeutic effects.
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.
基金supported by the Financial Special Fund,grant number XZ202401JD0027National Barley Industry Technology System(CARS-05-01A-08)+3 种基金the Xizang Agri-Tech Innovation Project(XZNKY-2025-CXGC-T01)the Joint Funds of the National Natural Science Foundation of China(No.U20A2026)the Financial Special Fund,grant number(32401784,2017CZZX001/2,XZNKY-2018-C-021 and NYSTC202401)the China Agriculture Research System of Barley(CARS-05).
文摘Qingke,a staple crop grown on the high-altitude Tibetan Plateau,has evolved a metabolomic profile providing both environmental stress resilience and human nutrition.We review the hypothesis that the metabolites that confer cold and UV resistance on the crop also facilitate human adaptation to high-altitude stresses.Specifically,β-glucans regulate blood glucose primarily via short-chain fatty acids(SCFAs)produced through gut microbiota fermentation,which directly mediate glucose homeostasis.Phenolamides accumulate via the phenylpropanoid pathway,with chalcone isomerase(CHI)serving as a key enzyme in flavonoid biosynthesis and enhancing UV-B resistance.Under low temperatures,β-glucans improve frost tolerance by modulating osmotic balance and inhibiting ice-nucleating proteins,while lipids maintain membrane fluidity to sustain cellular function during cold stress.Importantly,we explore the hypothesis that these same metabolites,upon consumption,may facilitate human adaptation to high-altitude stresses.This hypothesis is supported by preliminary epidemiological associations between Qingke consumption and favorable health outcomes in high-altitude populations,as well as established bioactivities of the implicated metabolites in vitro and in animal models.However,direct causal evidence in humans and a comprehensive understanding of the underlying molecular mechanisms remain key knowledge gaps that warrant future investigation.Qingke as a unique resource at the interface of agricultural resilience and human nutrition.Understanding its metabolic blueprint will inform the development of functional foods and climate-resilient crops.
基金supported by the Research Council of Lithuania(LMTLT),agreement no.S-MIP-22-5.
文摘Adhesively bonded joints are widely used in modern lightweight structures due to their high strengthto-weight ratio and design flexibility.However,the reliable non-destructive evaluation of bond integrity remains a significant challenge.This study presents a numerical investigation of adhesively bonded joints with different adhesive properties using ultrasonic guided waves.The main focus of the investigation is to evaluate the feasibility of using guided waves to assess bond integrity,particularly for detecting challenging weak bonds.For this purpose,a theoretical analysis of dispersion curves was conducted,revealing that the S0 Lamb wave mode is significantly sensitive to variations in adhesive properties in the 300-700 kHz frequency range.Finite element modelling was used to analyse the propagation of guided waves in two scenarios:an adhesively bonded aluminum structure and a more complex configuration-adhesively bonded lap joints.The Short-Time Fourier Transform(STFT)was used to process the obtained results and determine the group velocities of guided waves.By analysing the group velocity characteristics,their dependence on the adhesive properties was identified.In the first scenario,a clear separation of S0 modes from A0 modes was observed in the STFT analysis,with a decrease in group velocity as adhesive stiffness increased.For the more complex lap joint scenario,the separation between A0 and S0 modes was less distinct.However,the analysis of the average group velocity shows a dependence of average group velocity on adhesive properties.This is similar to the first scenario.There is a decrease in average group velocity as adhesive stiffness increases.The results obtained demonstrate that guided wavebased methods have a high potential for non-destructive evaluation of adhesively bonded structures,including the detection of weak bonds.
基金supported this work,but the SMP acknowledges support from the Canada Research Chairs Program(CRC-2021-00495)MJL is supported by a Canadian Institutes of Health Research(CIHR)Postdoctoral Fellowship award(Funding Reference No.187773).
文摘Mechanical tension is widely recognized as the primary stimulus underlying the molecular mechanisms that influence muscle hypertrophy induced by resistance training.Despite this,several outdated or overstated concepts continue to persist,both in the scientific literature and in the practical application of resistance training coaching and program design.Claims that acute hormonal responses,metabolic stress,cell swelling or“the pump”meaningfully contribute to hypertrophy are not supported by scientific evidence.Additionally,the concept of sarcoplasmic hypertrophy as a distinct and functionally meaningful contributor to hypertrophy lacks strong evidence.In this review,we critically evaluate several persistent misconceptions and contrast them with evidence-based mechanistic insights into load-induced hypertrophy.Specifically,we discuss the role(or lack thereof)of systemic hormones,metabolites,and cell swelling in promoting muscle hypertrophy.We also critically review the concept of sarcoplasmic hypertrophy and propose that it is not a meaningful contributor to muscle hypertrophy.Lastly,to translate knowledge for trainees and coaches,we discuss the upper limit of muscle hypertrophy and provide readers with evidence-based,reasonable expectations for muscle hypertrophy.We aimed,through this review,to use scientific evidence to enhance our understanding of what drives muscle hypertrophy and provide an evidence-based framework for resistance exercise training.
基金funded by the National Natural Science Foundation of China(No.52204407)the Natural Science Foundation of Jiangsu Province(No.BK20220595)the China Postdoctoral Science Foundation(No.2022M723689).
文摘This study proposes a multi-scale simplified residual convolutional neural network(MS-SRCNN)for the precise prediction of Mg-Nd binary alloy compositions from scanning electron microscope(SEM)images.A multi-scale data structure is established by spatially aligning and stacking SEM images at different magnifications.The MS-SRCNN significantly reduces computational runtime by over 90%compared to traditional architectures like ResNet50,VGG16,and VGG19,without compromising prediction accuracy.The model demonstrates more excellent predictive performance,achieving a>5%increase in R^(2) compared to single-scale models.Furthermore,the MS-SRCNN exhibits robust composition prediction capability across other Mg-based binary alloys,including Mg-La,Mg-Sn,Mg-Ce,Mg-Sm,Mg-Ag,and Mg-Y,thereby emphasizing its generalization and extrapolation potential.This research establishes a non-destructive,microstructure-informed composition analysis framework,reduces characterization time compared to traditional experiment methods and provides insights into the composition-microstructure relationship in diverse material systems.
基金supported in part by the National Natural Science Foundation of China under Grants 62025110,62271093sponsored by Natural Science Foundation of Chongqing,China,under Grant CSTB2023NSCQ-LZX0108.
文摘Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.
文摘BACKGROUND Prevalence of the main rheumatic diseases in the Republic of Sakha(Yakutia)[RS(Y)],one of the regions of the Russian Federation,differs from the other regions of the Russian Federation due to its ethnic and geographic features.Knowledge regarding the prevalence and structure of juvenile idiopathic arthritis(JIA)allows us to shape the work of the pediatric rheumatology service in the region correctly,and optimize the healthcare system and the need for medica-tions.AIM To describe the epidemiological,demographic,clinical,and laboratory characteristics of children with JIA in the RS(Y)and evaluate the main outcomes.METHODS This retrospective cohort study assessed all the data from the medical histories of the patients(n=225)diagnosed with JIA(2016-2023)in the Cardiorheumatology Department of the M.E.Nikolaev National Center of Medicine.Pearson'sχ²test,Fisher's exact test,Mann–Whitney and Kruskal-Wallis tests were used for statistical analyses.RESULTS The ethnic prevalence of JIA is higher in Sakha than in Russian children at 110.1 per 100000 children and 69.4 per 100000 children,respectively.The prevalence of JIA among boys and girls in Sakha was similar,unlike in Russians,where the number of girls predominated.The JIA categories were as follows:(1)Systemic arthritis:3.5%;(2)Oligoarthritis(persistent and extended):33.8%;(3)Rheumatoid factor(RF)(+)polyarthritis:0.9%;(4)RF(-)polyarthritis:14.7%;(5)Enthesitis-related arthritis(ERA):44%;and(6)Psoriatic arthritis:3.1%.Prevalence of the ERA category was 4.4 times higher in Sakha children,but the prevalence of systemic arthritis was 2.9 times lower compared to Russians(P=0.0005).The frequency of uveitis was 10.2%,and the frequency of human leukocyte antigen(HLA)B27 was 39.6%in JIA children.Biologic treatment was received by 40.4%of JIA children and 45.3%achieved remission.CONCLUSION Higher JIA prevalence,male and ERA predominance,related to a higher frequency of HLA B27 are typical in RS(Y).These data might improve the pediatric rheumatology health service.
文摘BACKGROUND Acute kidney injury(AKI)is a common and serious complication following heart transplantation,significantly impacting patient outcomes and survival rates.AKI after transplantation can lead to prolonged hospital stays,increased morbidity,and even mortality.AIM To identify and quantify significant risk factors associated with AKI following heart transplantation through a systematic review and meta-analysis.This study aims to distinguish predictive variables that may inform perioperative risk stratification and clinical decision-making.METHODS Electronic searches on MEDLINE,Google Scholar,ScienceDirect,Clinical-Trials.gov,and Cochrane databases were conducted from inception up till September 1.Included studies were randomized controlled trials,clinical trials,retrospective cohort,and observational studies.Exclusion criteria encompassed studies with pediatric populations,non-English publications,case reports,and studies lacking sufficient data on AKI outcomes.Statistical analysis was performed using RevMan 5.4,reporting dichotomous outcomes as odds ratios(OR)and continuous outcomes as mean differences(MD)with 95%confidence intervals(CI).Quality assessment of the included studies was performed using the New Castle Ottawa Scale.RESULTS Out of 1345 articles,13 studies with 3330 patients were included.Significant risk factors included age[overall MD=2.27 years(95%CI:0.13 to 4.41)],body mass index(BMI)[MD=1.42(95%CI:0.60 to 2.24)],diabetes[overall OR=1.47(95%CI:1.16 to 1.85)],chronic kidney disease(CKD)[OR=2.67(95%CI:1.73 to 4.14)],chronic obstructive pulmonary disorder(COPD)[OR=0.49(95%CI:0.27 to 0.89)],previous thoracic surgery[(OR)=1.27,95%CI:(1.05 to 1.54)],cardio-pulmonary bypass time[(MD)=17.10,95%CI:(6.12 to 28.08)],mechanical ventilation duration[(MD)=30.87 hours,95%CI:(10.69 to 51.05)]and extracorporeal membrane oxygenation[(OR)=2.31,95%CI:(1.25 to 4.26)].Factors not associated with AKI after heart transplantation included Recipients’male sex(P=0.55),donor sex(P=0.11),hypertension(P=0.13),smoking(P=0.20),coronary artery disease(P=0.90),pulmonary artery disease(P=0.81),dilated cardiomyopathy(P=0.79),ventilation duration(P=0.24),ischemic time(P=0.06),use of intra-aortic balloon pump(P=0.14),LVAD transplantation(P=0.83),and Inotropes use(P=0.78).CONCLUSION Age,BMI,diabetes,CKD,COPD,previous thoracic surgery,prolonged CPB time,extended mechanical ventilation,and ECMO use are significant predictors of AKI following heart transplantation,necessitating vigilant monitoring and individualized risk assessment.Conversely,factors such as LVAD implantation and inotrope use showed no significant association,highlighting the need for further investigation into their roles.Future prospective studies are essential to validate these findings,elucidate underlying mechanisms,and develop targeted interventions to mitigate AKI risk and improve patient outcomes.
基金supported by the National Natural Science Foundation of China(Grant No.42274035)the Major Program(JD)of Hubei Province(Grant No.2023BAA026)the Hunan Provincial Land Surveying and Mapping Project(HNGTCH-2023-05)。
文摘Slow Slip Events(SSEs)are critical for understanding subduction zone tectonics and earthquake prediction;however their detection is challenged by low-magnitude-offsets and data gaps.To address these challenges,this paper introduces an optimization-based signal decomposition(OSD)fra mework capable of automatically processing signals with missing data.We applied and validated this framework with GNSS coordinate time series in the Cascadia subduction zone,benchmarking its perfo rmance against the existing SSEs catalog.The proposed high-magnitude-offset detection method achieved an accuracy of67.21%in single-station SSE detection,significantly outperforming traditional methods such as the Relative Strength Index(RSI;32.24%)and deep learning methods like bidirectional Long Short-Term Memory(bi-LSTM;44.41%).Additionally,we proposed a complementary velocity-based screening strategy that successfully identified low-magnitude-offset SSEs and events obscured by data gaps.Through cluster analysis of single-station detection results,we successfully identified the spatiotemporal boundary of the majority of SSEs.Finally,we established an anomaly catalog for uncataloged period from 2018 to 2024,which further demonstrates the method's efficacy in characterizing the spatiotemporal features of SSEs.The OSD-based SSEs detection framework identified SSEs with diverse kinematic patterns using raw geodetic data,facilitating the construction of high-quality SSEs catalogs.These advancements enhance our understanding of subduction zone dynamics and provide a robust technical foundation for seismic hazard assessment.
文摘Purpose:The purpose of this study was to examine the associations between adherence to the 24-Hour Movement Guidelines and all-cause and cause-specific mortality in a large Spanish prospective cohort.Methods:We analyzed data from 14,288 participants of the Seguimiento Universidad de Navarra(SUN)Project,followed for a mean of 12.8 years(mean baseline age=38.3 years;60.1%women).Data were collected at baseline and through biennial follow-up questionnaires(up to 10 waves,depending on year of entry).The participants self-reported 24-h movement behaviors at baseline and were categorized based on the number of guidelines met(0-3).Behaviors were assessed at baseline only;changes in adherence during follow-up were not accounted for.Cox proportional hazards models were used to estimate hazard ratios(HRs)for all-cause and cause-specific mortality,adjusting for sociodemographic,lifestyle,and clinical covariates.Results:Meeting a greater number of 24-Hour Movement Guidelines at baseline was associated with a progressively lower risk of all-cause mortality.Compared with those meeting none,the multivariable-adjusted HRs were 0.52(95%confidence interval(95%CI):0.33-0.82)for meeting 1 guideline,0.47(95%CI:0.30-0.73)for meeting 2 guidelines,and 0.44(95%CI:0.28-0.71)for meeting all 3 guidelines.Only adherence to the physical activity guidelines was independently associated with a significantly lower mortality risk(HR=0.70;95%CI:0.55-0.89).A reduced risk was also observed for cancer and other-cause mortality among those meeting 2 or more guidelines.Conclusion:Adherence to the 24-Hour Movement Guidelines at baseline,particularly physical activity,was associated with a lower risk of mortality.Promoting an integrated approach to movement behaviors may be an effective strategy for improving population health and longevity.
基金Supporting Project number(RSP2025R92)at King Saud University,Riyadh,Saudi Arabia,for their support.
文摘The importance of organic geochemistry and basin modeling is widely recognized and used to understand the source rock potential and hydrocarbon generation history of the Mangahewa Formation,and thereby given the foundational role in the petroleum exploration.This study utilized the total organic carbon(TOC)content and hydrogen index(HI)to investigate the dominant kerogen type and hydrogen richness for the significance of petroleum generative potential.The Mangahewa coals and carbonaceous shales exhibit an excellent source rocks,with high total organic content(TOC)of more than 22%.The coals and carbonaceous shales were also characterised by Type Ⅱ‒Ⅲ kerogen with Type Ⅲ kerogen,promising oiland gas-prones.The Mangahewa Formation reached the main oil generation,with vitrinite reflectances between 0.53%and 1.01%.Vitrinite reflectance was also used in developing themal models and reveal the transformation(TR)of 10‒50%kerogen to oil during the Late Miocene.The models also showed that the Mangahewa source rock has a significant oil generation and little expulsion competency,with a TR of up to 54%.These findings support the substantial oil-generating potential in the Taranaki Basin's southern graben and can be used as a guide when developing strategies for an oil exploration program.
基金supported by the National Natural Science Foundation of China(No.52463034)supported by the Korea Institute of Energy Technology Evaluation and Planning funded by the Ministry of Trade,Industry and Energy(No.2025-02314098)of the Republic of Koreasupported by the Regional Innovation System&Education(RISE)program through the Gangwon RISE Center,funded by the Ministry of Education(MOE)and the Gangwon State(G.S.),Republic of Korea(2025-RISE-10-002).
文摘Conventional low-carbon concrete design approaches have often overlooked carbonation durability and the progressive loss of cover caused by surface scaling,both of which can increase the long-term risk of reinforcement corrosion.To address these limitations,this study proposes an improved design framework for low-carbon slag concrete that simultaneously incorporates carbonation durability and cover scaling effects into the mix proportioning process.Based on experimental data,a linear predictive model was developed to estimate the 28-day compressive strength of slag concrete,achieving a correlation coefficient of R=0.87711 and a root mean square error(RMSE)of 7.55 MPa.The mechanism-based equation exhibits strong physical interpretability,as each parameter corresponds to a clear physical process,satisfying the requirements of design codes for physical significance.By integrating the strength and carbon-emission models,the carbon-emission efficiency was further analyzed.Across all water–binder ratios(0.3,0.4,0.5),CO_(2) emissions per unit strength decreased steadily with increasing slag content,indicating that carbon efficiency is primarily governed by slag replacement rather than the water/binder ratio.Four design cases,all with a design strength of 30 MPa,were then evaluated to illustrate the combined effects of carbonation and scaling.In Case 1,without considering carbonation durability,the carbonation depth after 50 years exceeded the 25 mm cover,leading to potential corrosion.In Case 2,when carbonation durability was considered,the required actual strength increased to 31.28 MPa.When mild cover scaling of 3 mm was introduced(Case 3),the required strength rose to 34.59 MPa,and under severe scaling of 10 mm(Case 4),it increased to 45.73 MPa.These results indicate that intensified scaling demands higher strength and lower water/binder ratios to maintain durability.Overall,the proposed framework quantitatively balances strength,durability,and embodied carbon,supporting sustainable low-carbon concrete design.
基金funded by FCT/MECI through national funds and,when applicable,co-funded EU funds under UID/50008:Instituto de Telecomunicacoes.
文摘This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both classifiers.With BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke predictions.The findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.
文摘This study investigates the dark side of the non-fungible token(NFT)marketplace,with a focus on understanding the risks,and underlying factors driving fraud in the NFT ecosystem.Using the fraud triangle framework,this study examines pressure,opportunity,and rationalization from individual and organizational perspectives.The research provides a comprehensive understanding of the contributing factors to NFT marketplace fraud by analyzing the reasons behind fraudulent actions.A conceptual framework is developed that includes ten propositions to aid in understanding the complexity of this issue.This study’s outcomes will assist policymakers in crafting efficient approaches to mitigate fraud within the NFT marketplace.
