Plurality of characteristic peaks observed in number density distribution of galaxy redshift reveals that extent of physical space has been finite. Significant portion of observed celestial objects is found pair-wise ...Plurality of characteristic peaks observed in number density distribution of galaxy redshift reveals that extent of physical space has been finite. Significant portion of observed celestial objects is found pair-wise associated, i.e., the observed lights were emitted from one and same luminescent source but seen at different sky directions of observer, which is a unique phenomenon that can occur but only in finite space. Cosmic microwave radiation has always been interpreted as afterglow of Big Bang event. However, such radiation is shown unobservable to current observer if Hubble-Lemaître Correlation is interpreted as caused by receding motion of celestial objects. On the other hand, cosmic radiation can be understood as a common and ordinary phenomenon due to space lens, a unique property only of finite space. From Sloan Digital Sky Survey data, internal diameter of physical space is measured as 2.0 billion light years. If celestial objects were receding, hence physical space was expanding, then characteristic peaks of finite physical space should not appear evenly in number density distribution of redshift of the objects but more sparsely with respect to redshift increase. However, as revealed by the data, locations of the characteristic peaks in the distributions are rather even that do not match the locations as required by receding motion of object. Therefore, as evidenced by the data, physical space was not expanding, at least during the recent 18 billion years. In addition, considerable portion of observed quasars is found sharing a common factor of ~1/2 for their respective gravitation redshifts.展开更多
Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was u...Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.展开更多
Background:Prolonged sitting and reduced physical activity lead to low energy expenditures.However,little is known about the joint impact of daily sitting time and physical activity on body fat distribution.We investi...Background:Prolonged sitting and reduced physical activity lead to low energy expenditures.However,little is known about the joint impact of daily sitting time and physical activity on body fat distribution.We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults.Methods:This was a cross-sectional analysis of U.S.nationally representative data from the National Health and Nutrition Examination Survey2011-2018 among adults aged 20 years or older.Daily sitting time and leisure-time physical activity(LTPA)were self-reported using the Global Physical Activity Questionnaire.Body fat(total and trunk fat percentage)was determined via dual X-ray absorptiometry.Results:Among 10,808 adults,about 54.6%spent 6 h/day or more sitting;more than one-half reported no LTPA(inactive)or less than 150 min/week LTPA(insufficiently active)with only 43.3%reported 150 min/week or more LTPA(active)in the past week.After fully adjusting for sociodemographic data,lifestyle behaviors,and chronic conditions,prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes.When stratifying by LTPA,the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insuufficiently active.In the joint analyses,inactive/insuufficiently active adults who reported sitting more than 8 h/day had the highest total(female:3.99%(95%confidence interval(95%CI):3.09%-4.88%);male:3.79%(95%CI:2.75%-4.82%))and trunk body fat percentages(female:4.21%(95%CI:3.09%-5.32%);male:4.07%(95%CI:2.95%-5.19%))when compared with those who were active and sitting less than 4 h/day.Conclusion:Prolonged daily sitting time was associated with increased body fat among U.S.adults.The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.展开更多
Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the r...Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.展开更多
In multiple sclerosis,only immunomodulato ry and immunosuppressive drugs are recognized as disease-modifying therapies.Howeve r,in recent years,several data from pre-clinical and clinical studies suggested a possible ...In multiple sclerosis,only immunomodulato ry and immunosuppressive drugs are recognized as disease-modifying therapies.Howeve r,in recent years,several data from pre-clinical and clinical studies suggested a possible role of physical exe rcise as disease-modifying therapy in multiple sclerosis.Current evidence is sparse and often conflicting,and the mechanisms underlying the neuroprotective and antinflammatory role of exercise in multiple sclerosis have not been fully elucidated.Data,mainly derived from pre-clinical studies,suggest that exe rcise could enhance longterm potentiation and thus neuroplasticity,could reduce neuroinflammation and synaptopathy,and dampen astrogliosis and microgliosis.In humans,most trials focused on direct clinical and MRI outcomes,as investigating synaptic,neuroinflammato ry,and pathological changes is not straightfo rward compared to animal models.The present review analyzed current evidence and limitations in research concerning the potential disease-modifying therapy effects of exercise in multiple sclerosis in animal models and human studies.展开更多
Purpose This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence(AI)applications in physical activity(PA)interventions;introduce them to prevalent machine learning(M...Purpose This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence(AI)applications in physical activity(PA)interventions;introduce them to prevalent machine learning(ML),deep learning(DL),and reinforcement learning(RL)algorithms;and encourage the adoption of AI methodologies.Methods A scoping review was performed in PubMed,Web of Science,Cochrane Library,and EBSCO focusing on AI applications for promoting PA or predicting related behavioral or health outcomes.AI methodologies were summarized and categorized to identify synergies,patterns,and trends informing future research.Additionally,a concise primer on predominant AI methodologies within the realm of PA was provided to bolster understanding and broader application.Results The review included 24 studies that met the predetermined eligibility criteria.AI models were found effective in detecting significant patterns of PA behavior and associations between specific factors and intervention outcomes.Most studies comparing AI models to traditional statistical approaches reported higher prediction accuracy for AI models on test data.Comparisons of different AI models yielded mixed results,likely due to model performance being highly dependent on the dataset and task.An increasing trend of adopting state-of-the-art DL and RL models over standard ML was observed,addressing complex human–machine communication,behavior modification,and decision-making tasks.Six key areas for future AI adoption in PA interventions emerged:personalized PA interventions,real-time monitoring and adaptation,integration of multimodal data sources,evaluation of intervention effectiveness,expanding access to PA interventions,and predicting and preventing injuries.Conclusion The scoping review highlights the potential of AI methodologies for advancing PA interventions.As the field progresses,staying informed and exploring emerging AI-driven strategies is essential for achieving significant improvements in PA interventions and fostering overall well-being.展开更多
Background:Information on the association between physical activity(PA)and the risk of chronic kidney disease(CKD)is limited.We aimed to explore the associations of total,domain-specific,and intensity-specific PA with...Background:Information on the association between physical activity(PA)and the risk of chronic kidney disease(CKD)is limited.We aimed to explore the associations of total,domain-specific,and intensity-specific PA with CKD and its subtypes in China.Methods:The study included 475,376 adults from the China Kadoorie Biobank aged 30-79 years during 2004-2008 at baseline.An interviewer-administered questionnaire was used to collect the information about PA,which was quantified as metabolic equivalent of task hours per day(MET-h/day)and categorized into 4 groups based on quartiles.Cox regression was used to analyze the association between PA and CKD risk.Results:During a median follow-up of 12.1 years,5415 incident CKD cases were documented,including 1159 incident diabetic kidney disease(DKD)cases and 362 incident hypertensive nephropathy(HTN)cases.Total PA was inversely associated with CKD risk,with an adjusted hazard ratio(HR,95%confidence interval(95%CI))of 0.83(0.75-0.92)for incident CKD in the highest quartile of total PA as compared with participants in the lowest quartile.Similar results were observed for risk of DKD and HTN,and the corresponding HRs(95%CIs)were 0.75(0.58-0.97)for DKD risk and 0.56(0.37-0.85)for HTN risk.Increased nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA were significantly associated with a decreased risk of CKD,with HRs(95%CIs)of 0.80(0.73-0.88),0.85(0.77-0.94),and 0.85(0.76-0.95)in the highest quartile,respectively.Conclusion:PA,including nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA,was inversely associated with the risk of CKD,including DKD,HTN,and other CKD,and such associations were dose dependent.展开更多
Purpose:To examine the effects of a school-based karate intervention on academic achievement,psychosocial functioning,and physical fitness in children aged 7-8 years.Methods:Twenty schools in 5 different European coun...Purpose:To examine the effects of a school-based karate intervention on academic achievement,psychosocial functioning,and physical fitness in children aged 7-8 years.Methods:Twenty schools in 5 different European countries(2 second-grade classrooms per school)participated in a cluster randomized controlled trial(Sport at School trial).Participants were assigned to either a control group,which continued with their habitual physical education lessons,or to an intervention group,which replaced these lessons with a 1-year karate intervention(Karate Mind and Movement program).A total of 721 children(344 girls and 377 boys,7.4±0.5 years old,mean±SD)completed the study,of which 333 and 388 were assigned to the control group and intervention group,respectively.Outcomes included academic performance(average grade),psychosocial functioning(Strengths and Difficulties Questionnaire for parents),and different markers of physical fitness(cardiorespiratory fitness,balance,and flexibility).Results:The intervention provided small but significant benefits compared to the control group for academic achievement(d=0.16;p=0.003),conduct problems(d=-0.28;p=0.003),cardiorespiratory fitness(d=0.36;p<0.001),and balance(d=0.24;p=0.015).There was a trend towards significant benefits for flexibility(d=0.24;p=0.056).No significant benefits were observed for other variables,including psychosocial difficulties,emotional symptoms,hyperactivity/inattention,peer problems,or prosocial behaviour(all p>0.05).Conclusion:A 1-year school-based karate intervention was effective in improving academic achievement,conduct problems,and physical fitness in primary school children.The results support the inclusion of karate during physical education lessons.展开更多
The shear behavior of backfill-rock composites is crucial for mine safety and the management of surface subsidence.For exposing the shear failure mechanism of backfill-rock composites,we conducted shear tests on backf...The shear behavior of backfill-rock composites is crucial for mine safety and the management of surface subsidence.For exposing the shear failure mechanism of backfill-rock composites,we conducted shear tests on backfill-rock composites under three constant normal loads,compared with the unfilled rock.To investigate the macro-and meso-failure characteristics of the samples in the shear tests,the cracking behavior of samples was recorded by a high-speed camera and acoustic emission monitoring.In parallel with the experimental test,the numerical models of backfill-rock composites and unfilled rock were established using the discrete element method to analyze the continuous-discontinuous shearing process.Based on the damage mechanics and statistics,a novel shear constitutive model was proposed to describe mechanical behavior.The results show that backfill-rock composites had a special bimodal phenomenon of shearing load-deformation curve,i.e.the first shearing peak corresponded to rock break and the second shearing peak induced by the broken of aeolian sand-cement/fly ash paste backfill.Moreover,the shearing characteristic curves of the backfill-rock composites could be roughly divided into four stages,i.e.the shear failure of the specimens experienced:stage I:stress concentration;stage II:crack propagation;stage III:crack coalescence;stage IV:shearing friction.The numerical simulation shows that the existence of aeolian sand-cement/fly ash paste backfill inevitably altered the coalescence type and failure mode of the specimens and had a strengthening effect on the shear strength of backfillrock composites.Based on damage mechanics and statistics,a shear constitutive model was proposed to describe the shear fracture characteristics of specimens,especially the bimodal phenomenon.Finally,the micro-and meso-mechanisms of shear failure were discussed by combining the micro-test and numerical results.The research can advance the better understanding of the shear behavior of backfill-rock composites and contribute to the safety of mining engineering.展开更多
The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structur...The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structure,thermal and mechanical properties,and crystallization behavior changes were investigated by nuclear magnetic resonance spectrometer,Fourier-transform infrared spectro-photometer,X-ray diffractometer,differential scanning calorimetry and field emission scanning electron microscope measurements.The change of Q^(n)in glass structures reveals the glass network connectivity decreases due to the increasing content of Fe_(2)O_(3)addition,resulting in the increasing of non-bridging number in glass structure.The glass densities slightly rise from 2.644 to 2.681 g/cm^(3),while Vickers’s hardness increases at first,from 6.469 to 6.901 GPa,then slightly drops to 6.745 GPa,with Fe_(2)O_(3)content increase.There is almost no thermal expansion coefficient change from different Fe_(2)O_(3)content.The glass transmittance in visible range gradually decreases with higher Fe_(2)O_(3)content,resulting from the strong absorption of Fe^(2+)and Fe^(3+)ions.The calculated activation energy from thermal analysis results first decreases from 282.70 to 231.18 kJ/mol,and then increases to 244.02 kJ/mol,with the Fe_(2)O_(3)content increasing from 0.10wt%to 1.30wt%.Meanwhile,the maximum Avrami constant of 2.33 means the CAS glasses exhibit two-dimensional crystallization.All of the CAS glass-ceramics samples contain main crystal phase of anorthite,the microstructure appears lamellar and columnar crystals.展开更多
Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and cou...Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.展开更多
Background:Irritable bowel syndrome(IBS)substantially affects quality of life and requires early prevention.This study aimed to elucidate the relationships between IBS and daily behaviors,including sedentary behavior(...Background:Irritable bowel syndrome(IBS)substantially affects quality of life and requires early prevention.This study aimed to elucidate the relationships between IBS and daily behaviors,including sedentary behavior(SB),physical activity(PA),and sleep.In particular,it seeks to identify healthy behaviors to reduce IBS risk,which previous studies have rarely addressed.Methods:Daily behaviors were retrieved from self-reported data of 362,193 eligible UK Biobank participants.Incident cases were determined by self-report or health care data according to RomeⅣcriteria.Results:A total of 345,388 participants were IBS-free at baseline,during a median follow-up of 8.45 years,19,885 incident IBS cases were recorded.When examined individually,SB and shorter(≤7 h/day)or longer(>7 h/day)sleep duration were each positively associated with increased IBS risk,and PA was associated with lower IBS risk.The isotemporal substitution model suggested that replacing SB with other activities could provide further protective effects against IBS risk.Among people sleeping≤7 h/day,replacing 1 h of SB with equivalent light PA,vigorous PA,or sleep was associated with 8.1%(95%confidence interval(95%CI):0.901-0.937),5.8%(95%CI:0.896-0.991),and 9.2%(95%CI:0.885-0.932)reduced IBS risk,respectively.For people sleeping>7 h/day,light and vigorous PA were associated with a 4.8%(95%CI:0.926-0.978)and a 12.0%(95%CI:0.815-0.949)lower IBS risk,respectively.These benefits were mostly independent of genetic risk for IBS.Conclusion:SB and unhealthy sleep duration are risk factors for IBS.A promising way to mitigate IBS risk for individuals sleeping≤7 h/day and for those sleeping>7 h/day appears to be by replacing SB with adequate sleep or vigorous PA,respectively,regardless of the genetic predisposition of IBS.展开更多
The Makran accretionary wedge has the smallest subduction angle among any accretionary prism in the world. The factors controlling the spacing and morphological development of its deep thrust faults, as well as the fo...The Makran accretionary wedge has the smallest subduction angle among any accretionary prism in the world. The factors controlling the spacing and morphological development of its deep thrust faults, as well as the formation mechanism of shallow normal faults, remain unclear. Meanwhile, the factors affecting the continuity of plane faults must be comprehensively discussed. Clarifying the development characteristics and deformation mechanisms of the Makran accretionary wedge is crucial to effectively guide the exploration of gas hydrate deposits in the area. This study aims to interpret seismic data to identify typical structures in the Makran accretionary wedge, including deep imbricate thrust faults, shallow and small normal faults, wedge-shaped piggyback basins, mud diapirs with fuzzy and disorderly characteristics of reflection, décollements with a northward tilt of 1° – 2°, and large seamounts. Physical simulation-based experiments are performed to comprehensively analyze the results of the plane, section, and slices of the wedge. Results reveal that the distances between and shapes of thrust faults in the deep parts of the Makran accretionary wedge are controlled by the bottom décollement. The uplift of the thrust fault-related folds and the upwelling of the mud diapirs primarily contribute to the formation of small normal faults in the shallow part of the area. The mud diapirs originate from plastic material at the bottom, while those that have developed in the area near the trench are larger. Seamounts and mud diapirs break the continuity of fault plane distribution.展开更多
Purpose:The aim of the current study was to investigate the association of accelerometer-measured sleep duration and different intensities of physical activity(PA)with the risk of incident type 2 diabetes in a populat...Purpose:The aim of the current study was to investigate the association of accelerometer-measured sleep duration and different intensities of physical activity(PA)with the risk of incident type 2 diabetes in a population-based prospective cohort study.Methods:Altogether,88,000 participants(mean age=62.2±7.9 years,mean±SD)were included from the UK Biobank.Sleep duration(short:<6 h/day;normal:6-8 h/day;long:>8 h/day)and PA of different intensities were measured using a wrist-won accelerometer over a 7-day period between 2013 and 2015.PA was classified according to the median or World Health Organization-recommendation:total volume of PA(high,low),moderate-to-vigorous PA(MVPA)(recommended,not recommended),and light-intensity PA(high,low).Incidence of type 2diabetes was ascertained using hospital records or death registries.Results:During a median follow-up of 7.0 years,1615 incident type 2 diabetes cases were documented.Compared with normal sleep duration,short(hazard ratio(HR)=1.21,95%confidence interval(95%CI):1.03-1.41)but not long sleep duration(HR=1.01,95%CI:0.89-1.15)was associated with excessive type 2 diabetes risk.This increased risk among short sleepers seems to be protected against by PA.Compared with normal sleepers with high or recommended PA,short sleepers with low volume of PA(HR=1.81,95%CI:1.46-2.25),not recommended(below the World Health Organization-recommended level of)MVPA(HR=1.92,95%CI:1.55-2.36),or low light-intensity PA(HR=1.49,95%CI:1.13-1.90)had a higher risk of type 2 diabetes,while short sleepers with a high volume of PA(HR=1.14,95%CI:0.88-1.49),recommended MVPA(HR=1.02,95%CI:0.71-1.48),or high light-intensity PA(HR=1.14,95%CI:0.92-1.41)did not.Conclusion:Accelerometer-measured short but not long sleep duration was associated with a higher risk of incident type 2 diabetes.A higher level of PA,regardless of intensity,potentially ameliorates this excessive risk.展开更多
Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell t...Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.展开更多
Inflammatory bowel disease(IBD),including Crohn’s disease and ulcerative colitis,showed a wide spectrum of intestinal and extra-intestinal manifestations,which rendered the patients physically inactive and impaired t...Inflammatory bowel disease(IBD),including Crohn’s disease and ulcerative colitis,showed a wide spectrum of intestinal and extra-intestinal manifestations,which rendered the patients physically inactive and impaired their quality of life.It has been found that physical activity is a non-pharmacological intervention that improves the quality of life for those patients.Irisin is one member of the myokines secreted by muscle contraction during exercise and could be used as an antiinflammatory biomarker in assessing the physical activity of IBD patients.In addition,experimental studies showed that exogenous irisin significantly decreased the inflammatory markers and the histological changes of the intestinal mucosa observed in experimental colitis.Furthermore,irisin produces changes in the diversity of the microbiota.Therefore,endogenous or exogenous irisin,via its anti-inflammatory effects,will improve the health of IBD patients and will limit the barriers to physical activity in patients with IBD.展开更多
Alzheimer's disease is a neurodegenerative disease with complex etiology.Gut microbiota influences the gutbrain axis,which may affect pathways related to the pathogenesis of Alzheimer's disease.Additionally,di...Alzheimer's disease is a neurodegenerative disease with complex etiology.Gut microbiota influences the gutbrain axis,which may affect pathways related to the pathogenesis of Alzheimer's disease.Additionally,diet and physical activity are likely to affect the pathology of Alzheimer's disease as well as the gut microbiota.This demonstrates that it may be possible to prevent or halt the progression of Alzheimer's disease by regulating the gut microbiota using diet and physical activity strategies.Therefore,the present study reviews the association between these two interventions and gut microbiota in the human body.It also summarizes how these two interventions benefit Alzheimer's disease.Furthermore,the primary limitations of these two interventions are discussed and promising strategies are proposed,which may be beneficial to further study and develop the intervening measure for the progression of Alzheimer's disease.展开更多
Landslide is the second largest natural disaster after earthquake. It is of significance to study the evolution laws and failure mechanism of landslides based on its surface 3D deformation information. Based on the ra...Landslide is the second largest natural disaster after earthquake. It is of significance to study the evolution laws and failure mechanism of landslides based on its surface 3D deformation information. Based on the rainfall-triggered waste dump instability model test, we studied the failure mechanisms of the waste dump by integrating surface deformation and internal slope stress and proposed novel parameters for identifying landslide stability. We developed a noncontact measurement device, which can obtain millimeter-level 3D deformation data for surface scene in physical model test;Then we developed the similar materials and established a test model for a waste dump. Based on the failure characteristics of slope surface, internal stress of slope body and displacement contours during the whole process, we divided the slope instability process in model test into four stages: rainfall infiltration and surface erosion, shallow sliding, deep sliding, and overall instability. Based on the obtained surface deformation data, we calculated the volume change during slope instability process and compared it with the point displacement on slope surface. The results showed that the volume change can not only reflect the slow-ultra acceleration process of slope failure, but also fully reflect the above four stages and reduce the fluctuations caused by random factors. Finally, this paper proposed two stability identification parameters: the volume change rate above the slip surface and the relative velocity of volume change rate. According to the calculation of these two parameters in model test, they can be used for study the deformation and failure mechanism of slope stability.展开更多
Physical-layer secret key generation(PSKG)provides a lightweight way for group key(GK)sharing between wireless users in large-scale wireless networks.However,most of the existing works in this field consider only grou...Physical-layer secret key generation(PSKG)provides a lightweight way for group key(GK)sharing between wireless users in large-scale wireless networks.However,most of the existing works in this field consider only group communication.For a commonly dual-task scenario,where both GK and pairwise key(PK)are required,traditional methods are less suitable for direct extension.For the first time,we discover a security issue with traditional methods in dual-task scenarios,which has not previously been recognized.We propose an innovative segment-based key generation method to solve this security issue.We do not directly use PK exclusively to negotiate the GK as traditional methods.Instead,we generate GK and PK separately through segmentation which is the first solution to meet dual-task.We also perform security and rate analysis.It is demonstrated that our method is effective in solving this security issue from an information-theoretic perspective.The rate results of simulation are also consistent with the our rate derivation.展开更多
In this paper,we aim to design a practical low complexity low-density parity-check(LDPC)coded scheme to build a secure open channel and protect information from eavesdropping.To this end,we first propose a punctured L...In this paper,we aim to design a practical low complexity low-density parity-check(LDPC)coded scheme to build a secure open channel and protect information from eavesdropping.To this end,we first propose a punctured LDPC coded scheme,where the information bits in a codeword are punctured and only the parity check bits are transmitted to the receiver.We further propose a notion of check node type distribution and derive multi-edge type extrinsic information transfer functions to estimate the security performance,instead of the well-known weak metric bit error rate.We optimize the check node type distribution in terms of the signal-to-noise ratio(SNR)gap and modify the progressive edge growth algorithm to design finite-length codes.Numerical results show that our proposed scheme can achieve a lower computational complexity and a smaller security gap,compared to the existing scrambling and puncturing schemes.展开更多
文摘Plurality of characteristic peaks observed in number density distribution of galaxy redshift reveals that extent of physical space has been finite. Significant portion of observed celestial objects is found pair-wise associated, i.e., the observed lights were emitted from one and same luminescent source but seen at different sky directions of observer, which is a unique phenomenon that can occur but only in finite space. Cosmic microwave radiation has always been interpreted as afterglow of Big Bang event. However, such radiation is shown unobservable to current observer if Hubble-Lemaître Correlation is interpreted as caused by receding motion of celestial objects. On the other hand, cosmic radiation can be understood as a common and ordinary phenomenon due to space lens, a unique property only of finite space. From Sloan Digital Sky Survey data, internal diameter of physical space is measured as 2.0 billion light years. If celestial objects were receding, hence physical space was expanding, then characteristic peaks of finite physical space should not appear evenly in number density distribution of redshift of the objects but more sparsely with respect to redshift increase. However, as revealed by the data, locations of the characteristic peaks in the distributions are rather even that do not match the locations as required by receding motion of object. Therefore, as evidenced by the data, physical space was not expanding, at least during the recent 18 billion years. In addition, considerable portion of observed quasars is found sharing a common factor of ~1/2 for their respective gravitation redshifts.
文摘Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.
文摘Background:Prolonged sitting and reduced physical activity lead to low energy expenditures.However,little is known about the joint impact of daily sitting time and physical activity on body fat distribution.We investigated the independent and joint associations of daily sitting time and physical activity with body fat among adults.Methods:This was a cross-sectional analysis of U.S.nationally representative data from the National Health and Nutrition Examination Survey2011-2018 among adults aged 20 years or older.Daily sitting time and leisure-time physical activity(LTPA)were self-reported using the Global Physical Activity Questionnaire.Body fat(total and trunk fat percentage)was determined via dual X-ray absorptiometry.Results:Among 10,808 adults,about 54.6%spent 6 h/day or more sitting;more than one-half reported no LTPA(inactive)or less than 150 min/week LTPA(insufficiently active)with only 43.3%reported 150 min/week or more LTPA(active)in the past week.After fully adjusting for sociodemographic data,lifestyle behaviors,and chronic conditions,prolonged sitting time and low levels of LTPA were associated with higher total and trunk fat percentages in both sexes.When stratifying by LTPA,the association between daily sitting time and body fat appeared to be stronger in those who were inactive/insuufficiently active.In the joint analyses,inactive/insuufficiently active adults who reported sitting more than 8 h/day had the highest total(female:3.99%(95%confidence interval(95%CI):3.09%-4.88%);male:3.79%(95%CI:2.75%-4.82%))and trunk body fat percentages(female:4.21%(95%CI:3.09%-5.32%);male:4.07%(95%CI:2.95%-5.19%))when compared with those who were active and sitting less than 4 h/day.Conclusion:Prolonged daily sitting time was associated with increased body fat among U.S.adults.The higher body fat associated with 6 h/day sitting may not be offset by achieving recommended levels of physical activity.
文摘Background:There is mounting evidence that regular physical activity is an important prerequisite for healthy cognitive aging.Consequently,the finding that almost one-third of the adult population does not reach the recommended level of regular physical activity calls for further public health actions.In this context,digital and home-based physical training interventions might be a promising alternative to center-based intervention programs.Thus,this systematic review aimed to summarize the current state of the literature on the effects of digital and home-based physical training interventions on adult cognitive performance.Methods:In this pre-registered systematic review(PROSPERO;ID:CRD42022320031),5 electronic databases(PubMed,Web of Science,Psyclnfo,SPORTDiscus,and Cochrane Library)were searched by 2 independent researchers(FH and PT)to identify eligible studies investigating the effects of digital and home-based physical training interventions on cognitive performance in adults.The systematic literature search yielded 8258 records(extra17 records from other sources),of which 27 controlled trials were considered relevant.Two reviewers(FH and PT)independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise(TESTEX scale).Results:Of the 27 reviewed studies,15 reported positive effects on cognitive and motor-cognitive outcomes(i.e.,performance improvements in measures of executive functions,working memory,and choice stepping reaction test),and a considerable heterogeneity concerning study-related,population-related,and intervention-related characteristics was noticed.A more detailed analysis suggests that,in particular,interventions using online classes and technology-based exercise devices(i.e.,step-based exergames)can improve cognitive performance in healthy older adults.Approximately one-half of the reviewed studies were rated as having a high risk of bias with respect to completion adherence(≤85%)and monitoring of the level of regular physical activity in the control group.Conclusion:The current state of evidence concerning the effectiveness of digital and home-based physical training interventions is mixed overall,though there is limited evidence that specific types of digital and home-based physical training interventions(e.g.,online classes and step-based exergames)can be an effective strategy for improving cognitive performance in older adults.However,due to the limited number of available studies,future high-quality studies are needed to buttress this assumption empirically and to allow for more solid and nuanced conclusions.
文摘In multiple sclerosis,only immunomodulato ry and immunosuppressive drugs are recognized as disease-modifying therapies.Howeve r,in recent years,several data from pre-clinical and clinical studies suggested a possible role of physical exe rcise as disease-modifying therapy in multiple sclerosis.Current evidence is sparse and often conflicting,and the mechanisms underlying the neuroprotective and antinflammatory role of exercise in multiple sclerosis have not been fully elucidated.Data,mainly derived from pre-clinical studies,suggest that exe rcise could enhance longterm potentiation and thus neuroplasticity,could reduce neuroinflammation and synaptopathy,and dampen astrogliosis and microgliosis.In humans,most trials focused on direct clinical and MRI outcomes,as investigating synaptic,neuroinflammato ry,and pathological changes is not straightfo rward compared to animal models.The present review analyzed current evidence and limitations in research concerning the potential disease-modifying therapy effects of exercise in multiple sclerosis in animal models and human studies.
文摘Purpose This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence(AI)applications in physical activity(PA)interventions;introduce them to prevalent machine learning(ML),deep learning(DL),and reinforcement learning(RL)algorithms;and encourage the adoption of AI methodologies.Methods A scoping review was performed in PubMed,Web of Science,Cochrane Library,and EBSCO focusing on AI applications for promoting PA or predicting related behavioral or health outcomes.AI methodologies were summarized and categorized to identify synergies,patterns,and trends informing future research.Additionally,a concise primer on predominant AI methodologies within the realm of PA was provided to bolster understanding and broader application.Results The review included 24 studies that met the predetermined eligibility criteria.AI models were found effective in detecting significant patterns of PA behavior and associations between specific factors and intervention outcomes.Most studies comparing AI models to traditional statistical approaches reported higher prediction accuracy for AI models on test data.Comparisons of different AI models yielded mixed results,likely due to model performance being highly dependent on the dataset and task.An increasing trend of adopting state-of-the-art DL and RL models over standard ML was observed,addressing complex human–machine communication,behavior modification,and decision-making tasks.Six key areas for future AI adoption in PA interventions emerged:personalized PA interventions,real-time monitoring and adaptation,integration of multimodal data sources,evaluation of intervention effectiveness,expanding access to PA interventions,and predicting and preventing injuries.Conclusion The scoping review highlights the potential of AI methodologies for advancing PA interventions.As the field progresses,staying informed and exploring emerging AI-driven strategies is essential for achieving significant improvements in PA interventions and fostering overall well-being.
基金supported by National Natural Science Foundation of China(82192900,82192901,82192904,81941018,and 91846303)Peking University Medicine Seed Fund for Interdisciplinary Research(BMU2022MX025)+5 种基金the Fundamental Research Funds for the Central Universitiessupported by a grant from the Kadoorie Charitable Foundation in Hong Kongsupported by grants from the UK Wellcome Trust(212946/Z/18/Z,202922/Z/16/Z,104085/Z/14/Z,and 088158/Z/09/Z)the National Key R&D Program of China(2016YFC0900500)National Natural Science Foundation of China(81390540)Chinese Ministry of Science and Technology(2011BAI09B01)。
文摘Background:Information on the association between physical activity(PA)and the risk of chronic kidney disease(CKD)is limited.We aimed to explore the associations of total,domain-specific,and intensity-specific PA with CKD and its subtypes in China.Methods:The study included 475,376 adults from the China Kadoorie Biobank aged 30-79 years during 2004-2008 at baseline.An interviewer-administered questionnaire was used to collect the information about PA,which was quantified as metabolic equivalent of task hours per day(MET-h/day)and categorized into 4 groups based on quartiles.Cox regression was used to analyze the association between PA and CKD risk.Results:During a median follow-up of 12.1 years,5415 incident CKD cases were documented,including 1159 incident diabetic kidney disease(DKD)cases and 362 incident hypertensive nephropathy(HTN)cases.Total PA was inversely associated with CKD risk,with an adjusted hazard ratio(HR,95%confidence interval(95%CI))of 0.83(0.75-0.92)for incident CKD in the highest quartile of total PA as compared with participants in the lowest quartile.Similar results were observed for risk of DKD and HTN,and the corresponding HRs(95%CIs)were 0.75(0.58-0.97)for DKD risk and 0.56(0.37-0.85)for HTN risk.Increased nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA were significantly associated with a decreased risk of CKD,with HRs(95%CIs)of 0.80(0.73-0.88),0.85(0.77-0.94),and 0.85(0.76-0.95)in the highest quartile,respectively.Conclusion:PA,including nonoccupational PA,low-intensity PA,and moderate-to-vigorous-intensity PA,was inversely associated with the risk of CKD,including DKD,HTN,and other CKD,and such associations were dose dependent.
基金supported by the Erasmus+program of the European Union(567201-EPP-1-2015-2-IT-SPO-SCP)supported by the University of Alcala(FPI2016)。
文摘Purpose:To examine the effects of a school-based karate intervention on academic achievement,psychosocial functioning,and physical fitness in children aged 7-8 years.Methods:Twenty schools in 5 different European countries(2 second-grade classrooms per school)participated in a cluster randomized controlled trial(Sport at School trial).Participants were assigned to either a control group,which continued with their habitual physical education lessons,or to an intervention group,which replaced these lessons with a 1-year karate intervention(Karate Mind and Movement program).A total of 721 children(344 girls and 377 boys,7.4±0.5 years old,mean±SD)completed the study,of which 333 and 388 were assigned to the control group and intervention group,respectively.Outcomes included academic performance(average grade),psychosocial functioning(Strengths and Difficulties Questionnaire for parents),and different markers of physical fitness(cardiorespiratory fitness,balance,and flexibility).Results:The intervention provided small but significant benefits compared to the control group for academic achievement(d=0.16;p=0.003),conduct problems(d=-0.28;p=0.003),cardiorespiratory fitness(d=0.36;p<0.001),and balance(d=0.24;p=0.015).There was a trend towards significant benefits for flexibility(d=0.24;p=0.056).No significant benefits were observed for other variables,including psychosocial difficulties,emotional symptoms,hyperactivity/inattention,peer problems,or prosocial behaviour(all p>0.05).Conclusion:A 1-year school-based karate intervention was effective in improving academic achievement,conduct problems,and physical fitness in primary school children.The results support the inclusion of karate during physical education lessons.
文摘The shear behavior of backfill-rock composites is crucial for mine safety and the management of surface subsidence.For exposing the shear failure mechanism of backfill-rock composites,we conducted shear tests on backfill-rock composites under three constant normal loads,compared with the unfilled rock.To investigate the macro-and meso-failure characteristics of the samples in the shear tests,the cracking behavior of samples was recorded by a high-speed camera and acoustic emission monitoring.In parallel with the experimental test,the numerical models of backfill-rock composites and unfilled rock were established using the discrete element method to analyze the continuous-discontinuous shearing process.Based on the damage mechanics and statistics,a novel shear constitutive model was proposed to describe mechanical behavior.The results show that backfill-rock composites had a special bimodal phenomenon of shearing load-deformation curve,i.e.the first shearing peak corresponded to rock break and the second shearing peak induced by the broken of aeolian sand-cement/fly ash paste backfill.Moreover,the shearing characteristic curves of the backfill-rock composites could be roughly divided into four stages,i.e.the shear failure of the specimens experienced:stage I:stress concentration;stage II:crack propagation;stage III:crack coalescence;stage IV:shearing friction.The numerical simulation shows that the existence of aeolian sand-cement/fly ash paste backfill inevitably altered the coalescence type and failure mode of the specimens and had a strengthening effect on the shear strength of backfillrock composites.Based on damage mechanics and statistics,a shear constitutive model was proposed to describe the shear fracture characteristics of specimens,especially the bimodal phenomenon.Finally,the micro-and meso-mechanisms of shear failure were discussed by combining the micro-test and numerical results.The research can advance the better understanding of the shear behavior of backfill-rock composites and contribute to the safety of mining engineering.
基金Funded by the Key Research and Development Program of Han Nan province(No.ZDYF2021GXJS027)the Project of Sanya Yazhou Bay Science and Technology City(No.SCKJJYRC-2022-44)the Shenzhen Virtual University Park(SZVUP)Free Exploration Basic Research Project(No.2021Szvup107)。
文摘The calcium aluminosilicate-based glasses(CaO-Al_(2)O_(3)-SiO_(2),CAS)with different Fe_(2)O_(3)content(0.10wt%,0.50wt%,0.90wt%,and 1.30wt%)were prepared by traditional melt-quenching method.The glass network structure,thermal and mechanical properties,and crystallization behavior changes were investigated by nuclear magnetic resonance spectrometer,Fourier-transform infrared spectro-photometer,X-ray diffractometer,differential scanning calorimetry and field emission scanning electron microscope measurements.The change of Q^(n)in glass structures reveals the glass network connectivity decreases due to the increasing content of Fe_(2)O_(3)addition,resulting in the increasing of non-bridging number in glass structure.The glass densities slightly rise from 2.644 to 2.681 g/cm^(3),while Vickers’s hardness increases at first,from 6.469 to 6.901 GPa,then slightly drops to 6.745 GPa,with Fe_(2)O_(3)content increase.There is almost no thermal expansion coefficient change from different Fe_(2)O_(3)content.The glass transmittance in visible range gradually decreases with higher Fe_(2)O_(3)content,resulting from the strong absorption of Fe^(2+)and Fe^(3+)ions.The calculated activation energy from thermal analysis results first decreases from 282.70 to 231.18 kJ/mol,and then increases to 244.02 kJ/mol,with the Fe_(2)O_(3)content increasing from 0.10wt%to 1.30wt%.Meanwhile,the maximum Avrami constant of 2.33 means the CAS glasses exhibit two-dimensional crystallization.All of the CAS glass-ceramics samples contain main crystal phase of anorthite,the microstructure appears lamellar and columnar crystals.
基金supported by the National Key Research and Development Program (2022YFF0609504)the National Natural Science Foundation of China (61974126,51902273,62005230,62001405)the Natural Science Foundation of Fujian Province of China (No.2021J06009)
文摘Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.
基金supported by grants from China CDC Key Laboratory of Environment and Population Health(2022-CKL-03)Peking University(BMU2021YJ044)supported by the General Program of National Natural Science Foundation of China(32170898)。
文摘Background:Irritable bowel syndrome(IBS)substantially affects quality of life and requires early prevention.This study aimed to elucidate the relationships between IBS and daily behaviors,including sedentary behavior(SB),physical activity(PA),and sleep.In particular,it seeks to identify healthy behaviors to reduce IBS risk,which previous studies have rarely addressed.Methods:Daily behaviors were retrieved from self-reported data of 362,193 eligible UK Biobank participants.Incident cases were determined by self-report or health care data according to RomeⅣcriteria.Results:A total of 345,388 participants were IBS-free at baseline,during a median follow-up of 8.45 years,19,885 incident IBS cases were recorded.When examined individually,SB and shorter(≤7 h/day)or longer(>7 h/day)sleep duration were each positively associated with increased IBS risk,and PA was associated with lower IBS risk.The isotemporal substitution model suggested that replacing SB with other activities could provide further protective effects against IBS risk.Among people sleeping≤7 h/day,replacing 1 h of SB with equivalent light PA,vigorous PA,or sleep was associated with 8.1%(95%confidence interval(95%CI):0.901-0.937),5.8%(95%CI:0.896-0.991),and 9.2%(95%CI:0.885-0.932)reduced IBS risk,respectively.For people sleeping>7 h/day,light and vigorous PA were associated with a 4.8%(95%CI:0.926-0.978)and a 12.0%(95%CI:0.815-0.949)lower IBS risk,respectively.These benefits were mostly independent of genetic risk for IBS.Conclusion:SB and unhealthy sleep duration are risk factors for IBS.A promising way to mitigate IBS risk for individuals sleeping≤7 h/day and for those sleeping>7 h/day appears to be by replacing SB with adequate sleep or vigorous PA,respectively,regardless of the genetic predisposition of IBS.
基金funded by the National Natural Science Foundation of China(No.42076069).
文摘The Makran accretionary wedge has the smallest subduction angle among any accretionary prism in the world. The factors controlling the spacing and morphological development of its deep thrust faults, as well as the formation mechanism of shallow normal faults, remain unclear. Meanwhile, the factors affecting the continuity of plane faults must be comprehensively discussed. Clarifying the development characteristics and deformation mechanisms of the Makran accretionary wedge is crucial to effectively guide the exploration of gas hydrate deposits in the area. This study aims to interpret seismic data to identify typical structures in the Makran accretionary wedge, including deep imbricate thrust faults, shallow and small normal faults, wedge-shaped piggyback basins, mud diapirs with fuzzy and disorderly characteristics of reflection, décollements with a northward tilt of 1° – 2°, and large seamounts. Physical simulation-based experiments are performed to comprehensively analyze the results of the plane, section, and slices of the wedge. Results reveal that the distances between and shapes of thrust faults in the deep parts of the Makran accretionary wedge are controlled by the bottom décollement. The uplift of the thrust fault-related folds and the upwelling of the mud diapirs primarily contribute to the formation of small normal faults in the shallow part of the area. The mud diapirs originate from plastic material at the bottom, while those that have developed in the area near the trench are larger. Seamounts and mud diapirs break the continuity of fault plane distribution.
基金supported by the National Key R&D Program of China(2021YFC2501500)National Natural Science Foundation of China(82171476)。
文摘Purpose:The aim of the current study was to investigate the association of accelerometer-measured sleep duration and different intensities of physical activity(PA)with the risk of incident type 2 diabetes in a population-based prospective cohort study.Methods:Altogether,88,000 participants(mean age=62.2±7.9 years,mean±SD)were included from the UK Biobank.Sleep duration(short:<6 h/day;normal:6-8 h/day;long:>8 h/day)and PA of different intensities were measured using a wrist-won accelerometer over a 7-day period between 2013 and 2015.PA was classified according to the median or World Health Organization-recommendation:total volume of PA(high,low),moderate-to-vigorous PA(MVPA)(recommended,not recommended),and light-intensity PA(high,low).Incidence of type 2diabetes was ascertained using hospital records or death registries.Results:During a median follow-up of 7.0 years,1615 incident type 2 diabetes cases were documented.Compared with normal sleep duration,short(hazard ratio(HR)=1.21,95%confidence interval(95%CI):1.03-1.41)but not long sleep duration(HR=1.01,95%CI:0.89-1.15)was associated with excessive type 2 diabetes risk.This increased risk among short sleepers seems to be protected against by PA.Compared with normal sleepers with high or recommended PA,short sleepers with low volume of PA(HR=1.81,95%CI:1.46-2.25),not recommended(below the World Health Organization-recommended level of)MVPA(HR=1.92,95%CI:1.55-2.36),or low light-intensity PA(HR=1.49,95%CI:1.13-1.90)had a higher risk of type 2 diabetes,while short sleepers with a high volume of PA(HR=1.14,95%CI:0.88-1.49),recommended MVPA(HR=1.02,95%CI:0.71-1.48),or high light-intensity PA(HR=1.14,95%CI:0.92-1.41)did not.Conclusion:Accelerometer-measured short but not long sleep duration was associated with a higher risk of incident type 2 diabetes.A higher level of PA,regardless of intensity,potentially ameliorates this excessive risk.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number 223202.
文摘Recognizing human activity(HAR)from data in a smartphone sensor plays an important role in the field of health to prevent chronic diseases.Daily and weekly physical activities are recorded on the smartphone and tell the user whether he is moving well or not.Typically,smartphones and their associated sensing devices operate in distributed and unstable environments.Therefore,collecting their data and extracting useful information is a significant challenge.In this context,the aimof this paper is twofold:The first is to analyze human behavior based on the recognition of physical activities.Using the results of physical activity detection and classification,the second part aims to develop a health recommendation system to notify smartphone users about their healthy physical behavior related to their physical activities.This system is based on the calculation of calories burned by each user during physical activities.In this way,conclusions can be drawn about a person’s physical behavior by estimating the number of calories burned after evaluating data collected daily or even weekly following a series of physical workouts.To identify and classify human behavior our methodology is based on artificial intelligence models specifically deep learning techniques like Long Short-Term Memory(LSTM),stacked LSTM,and bidirectional LSTM.Since human activity data contains both spatial and temporal information,we proposed,in this paper,to use of an architecture allowing the extraction of the two types of information simultaneously.While Convolutional Neural Networks(CNN)has an architecture designed for spatial information,our idea is to combine CNN with LSTM to increase classification accuracy by taking into consideration the extraction of both spatial and temporal data.The results obtained achieved an accuracy of 96%.On the other side,the data learned by these algorithms is prone to error and uncertainty.To overcome this constraint and improve performance(96%),we proposed to use the fusion mechanisms.The last combines deep learning classifiers tomodel non-accurate and ambiguous data to obtain synthetic information to aid in decision-making.The Voting and Dempster-Shafer(DS)approaches are employed.The results showed that fused classifiers based on DS theory outperformed individual classifiers(96%)with the highest accuracy level of 98%.Also,the findings disclosed that participants engaging in physical activities are healthy,showcasing a disparity in the distribution of physical activities between men and women.
文摘Inflammatory bowel disease(IBD),including Crohn’s disease and ulcerative colitis,showed a wide spectrum of intestinal and extra-intestinal manifestations,which rendered the patients physically inactive and impaired their quality of life.It has been found that physical activity is a non-pharmacological intervention that improves the quality of life for those patients.Irisin is one member of the myokines secreted by muscle contraction during exercise and could be used as an antiinflammatory biomarker in assessing the physical activity of IBD patients.In addition,experimental studies showed that exogenous irisin significantly decreased the inflammatory markers and the histological changes of the intestinal mucosa observed in experimental colitis.Furthermore,irisin produces changes in the diversity of the microbiota.Therefore,endogenous or exogenous irisin,via its anti-inflammatory effects,will improve the health of IBD patients and will limit the barriers to physical activity in patients with IBD.
基金financially supported by National Natural Science Foundation of China(32171035)the major fund project of Ningbo Science and Technology Bureau(2019B10034)+4 种基金Opened-end Fund of Key Laboratory(KFJJ-202101,ZPKLP202202)Public Project of Ningbo(202002N3167)Project of Yinzhou(2022AS025)Ningbo Rehabilitation Hospital(2022KY02)sponsored by a K.C.Wong Magna Fund in Ningbo University。
文摘Alzheimer's disease is a neurodegenerative disease with complex etiology.Gut microbiota influences the gutbrain axis,which may affect pathways related to the pathogenesis of Alzheimer's disease.Additionally,diet and physical activity are likely to affect the pathology of Alzheimer's disease as well as the gut microbiota.This demonstrates that it may be possible to prevent or halt the progression of Alzheimer's disease by regulating the gut microbiota using diet and physical activity strategies.Therefore,the present study reviews the association between these two interventions and gut microbiota in the human body.It also summarizes how these two interventions benefit Alzheimer's disease.Furthermore,the primary limitations of these two interventions are discussed and promising strategies are proposed,which may be beneficial to further study and develop the intervening measure for the progression of Alzheimer's disease.
基金funded by the National Key R&D Program of China (Grant No. 2021YFB3901402)the Fundamental Research Funds for the Central Universities (Project No. 2022CDJKYJH037)。
文摘Landslide is the second largest natural disaster after earthquake. It is of significance to study the evolution laws and failure mechanism of landslides based on its surface 3D deformation information. Based on the rainfall-triggered waste dump instability model test, we studied the failure mechanisms of the waste dump by integrating surface deformation and internal slope stress and proposed novel parameters for identifying landslide stability. We developed a noncontact measurement device, which can obtain millimeter-level 3D deformation data for surface scene in physical model test;Then we developed the similar materials and established a test model for a waste dump. Based on the failure characteristics of slope surface, internal stress of slope body and displacement contours during the whole process, we divided the slope instability process in model test into four stages: rainfall infiltration and surface erosion, shallow sliding, deep sliding, and overall instability. Based on the obtained surface deformation data, we calculated the volume change during slope instability process and compared it with the point displacement on slope surface. The results showed that the volume change can not only reflect the slow-ultra acceleration process of slope failure, but also fully reflect the above four stages and reduce the fluctuations caused by random factors. Finally, this paper proposed two stability identification parameters: the volume change rate above the slip surface and the relative velocity of volume change rate. According to the calculation of these two parameters in model test, they can be used for study the deformation and failure mechanism of slope stability.
基金supported in part by the National Key R&D Program of China(No.2022YFB2902202)in part by the Fundamental Research Funds for the Central Universities(No.2242023K30034)+2 种基金in part by the National Natural Science Foundation of China(No.62171121,U22A2001),in part by the National Natural Science Foundation of China(No.62301144)in part by the National Natural Science Foundation of Jiangsu Province,China(No.BK20211160)in part by the Southeast University Startup Fund(No.4009012301)。
文摘Physical-layer secret key generation(PSKG)provides a lightweight way for group key(GK)sharing between wireless users in large-scale wireless networks.However,most of the existing works in this field consider only group communication.For a commonly dual-task scenario,where both GK and pairwise key(PK)are required,traditional methods are less suitable for direct extension.For the first time,we discover a security issue with traditional methods in dual-task scenarios,which has not previously been recognized.We propose an innovative segment-based key generation method to solve this security issue.We do not directly use PK exclusively to negotiate the GK as traditional methods.Instead,we generate GK and PK separately through segmentation which is the first solution to meet dual-task.We also perform security and rate analysis.It is demonstrated that our method is effective in solving this security issue from an information-theoretic perspective.The rate results of simulation are also consistent with the our rate derivation.
文摘In this paper,we aim to design a practical low complexity low-density parity-check(LDPC)coded scheme to build a secure open channel and protect information from eavesdropping.To this end,we first propose a punctured LDPC coded scheme,where the information bits in a codeword are punctured and only the parity check bits are transmitted to the receiver.We further propose a notion of check node type distribution and derive multi-edge type extrinsic information transfer functions to estimate the security performance,instead of the well-known weak metric bit error rate.We optimize the check node type distribution in terms of the signal-to-noise ratio(SNR)gap and modify the progressive edge growth algorithm to design finite-length codes.Numerical results show that our proposed scheme can achieve a lower computational complexity and a smaller security gap,compared to the existing scrambling and puncturing schemes.