Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were freque...Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.展开更多
The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more e...The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.展开更多
Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without val...Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.展开更多
BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited rese...BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.展开更多
Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundati...Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to f...On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.展开更多
Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is cha...Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is characterized by bleeding within the brain.Stroke is a lifethreatening cerebrovascular condition characterized by intricate pathophysiological mechanisms,including oxidative stress,inflammation,mitochondrial dysfunction,and neuronal injury.Critical transcription factors,such as nuclear factor erythroid 2-related factor 2 and nuclear factor kappa B,play central roles in the progression of stroke.Nuclear factor erythroid 2-related factor 2 is sensitive to changes in the cellular redox status and is crucial in protecting cells against oxidative damage,inflammatory responses,and cytotoxic agents.It plays a significant role in post-stroke neuroprotection and repair by influencing mitochondrial function,endoplasmic reticulum stress,and lysosomal activity and regulating metabolic pathways and cytokine expression.Conversely,nuclear factor-kappa B is closely associated with mitochondrial dysfunction,the generation of reactive oxygen species,oxidative stress exacerbation,and inflammation.Nuclear factor-kappa B contributes to neuronal injury,apoptosis,and immune responses following stroke by modulating cell adhesion molecules and inflammatory mediators.The interplay between these pathways,potentially involving crosstalk among various organelles,significantly influences stroke pathophysiology.Advancements in single-cell sequencing and spatial transcriptomics have greatly improved our understanding of stroke pathogenesis and offer new opportunities for the development of targeted,individualized,cell typespecific treatments.In this review,we discuss the mechanisms underlying the involvement of nuclear factor erythroid 2-related factor 2 and nuclear factor-kappa B in both ischemic and hemorrhagic stroke,with an emphasis on their roles in oxidative stress,inflammation,and neuroprotection.展开更多
Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic ...Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic orbits or limit cycles.Interesting normal forms could be derived through a generalization of the concept'resonance',which offers nontrivial analytic approximations.Compared with traditional techniques such as multi-scale methods,the current scheme proceeds in a very straightforward and simple way,delivering not only the period and the amplitude but also the transient path to limit cycles.The method is demonstrated with several examples including the Duffing oscillator,van der Pol equation and Lorenz equation.The obtained solutions match well with numerical results and with those derived by traditional analytic methods.展开更多
In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of ...In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of tumor regions in Magnetic Resonance Imaging(MRI).However,BTS remains a challenging task because of noise,non-uniform object texture,diverse image content and clustered objects.To address these challenges,a novel model is implemented in this research.The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN,which effectively captures the fine-grained tumor features to enhance segmentation precision.MRI images are initially acquired from three online datasets:Dataset 1—Brain Tumor Segmentation(BraTS)2018,Dataset 2—BraTS 2019,and Dataset 3—BraTS 2020.Subsequently,the Switchable Normalization-based Faster Regions with Convolutional Neural Networks(SNFRC)model is proposed for improved BTS in MRI images.In the proposed model,Switchable Normalization is integrated into the conventional architecture,enhancing generalization capability and reducing overfitting to unseen image data,which is essential due to the typically limited size of available datasets.The network depth is increased to obtain discriminative semantic features that improve segmentation performance.Specifically,Switchable Normalization captures the diverse feature representations from the brain images.The Faster R-CNN model develops end-to-end training and effective regional proposal generation,with an enhanced training stability using Switchable Normalization,to perform an effective segmentation in MRI images.From the experimental results,the proposed model attains segmentation accuracies of 99.41%,98.12%,and 96.71%on Datasets 1,2,and 3,respectively,outperforming conventional deep learning models used for BTS.展开更多
This systematic review synthesizes empirical research on external risk factors for adolescent smartphone addiction.Scopus and Web of Science were searched for English peer-reviewed empirical articles from 2008 onward;...This systematic review synthesizes empirical research on external risk factors for adolescent smartphone addiction.Scopus and Web of Science were searched for English peer-reviewed empirical articles from 2008 onward;28 met inclusion criteria(excluding non-adolescents,generic internet addiction,non-empirical work,or non-English).Thematic synthesis organized findings into three external risk domains—family,school,and peers—considering cultural/contextual mechanisms.Family dynamics(parental phubbing,harsh parenting,dysfunction),school stressors,and adverse peer relationships were identified as accumulating,direct and indirect contributors to smartphone addiction.These operate within a techno-ecological framework,where digital technologies amplify vulnerabilities and create new pathways for maladaptive use.Evidence favors an ecological,multi-level perspective.Future research should use longitudinal designs,standardize measures across cultures,and examine understudied regions—especially Africa—to guide culturally sensitive interventions.展开更多
The significant variation in plant regeneration efficiency between indica and japonica rice poses a major challenge for crop improvement.However,the molecular basis for this divergence remains largely unclear.In this ...The significant variation in plant regeneration efficiency between indica and japonica rice poses a major challenge for crop improvement.However,the molecular basis for this divergence remains largely unclear.In this study,we investigated the role of Oryza sativa AUXIN RESPONSE FACTOR 13(OsARF13),a transcription factor involved in callus-related processes.We observed that OsARF13 expression is significantly higher in japonica rice callus than in indica rice callus.This differential expression might be associated with an allelic variation in the promoter region of OsARF13,where a deletion commonly found in indica rice corresponds to the loss of a conserved auxin-responsive element(AuxRE)motif.To functionally characterize OsARF13,we generated CRISPR/Cas9-mediated knockout mutants.These mutants exhibited a substantial reduction in callus fresh weight,demonstrating that OsARF13 is required for efficient callus induction.Transcriptome analysis of the osarf13 mutant further showed that OsARF13 influences the expression of genes involved in hormone signal transduction and stress responses.Our findings suggest that OsARF13 is a key component of the regulatory network governing callus induction and that natural variation in its promoter might provide a potential explanation for the differential regenerative capacity between japonica and indica rice subspecies.展开更多
BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and dep...BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and depression(PSD)do not receive sufficient attention.AIM To systematically evaluate risk factors and early identification markers for PSD for more precise screening and intervention strategies in clinical practice.METHODS This retrospective study analyzed clinical data from 112 patients with ischemic stroke admitted between January 2022 and December 2024.Based on assessments using the Hamilton Rating Scale for Anxiety(HAMA)and Hamilton Rating Scale for Depression(HAMD)at 2 weeks(±3 days)post-stroke,patients were classified into the PSD group(HAMA≥7 and/or HAMD≥7)and the non-PSD group(HAMA<7 and HAMD<7).Observation indicators included psychological assessment,demographic and clinical characteristics,stroke-related clinical indicators,neuroimaging assessments,and laboratory biomarkers.Multivariate logistic regression analysis was used to identify independent risk factors for PSD,and receiver operating characteristic curve analysis was used to evaluate the diagnostic value of potential biomarkers.RESULTS Of the 112 patients,46(41.1%)were diagnosed with PSD.Multivariate analysis identified five independent risk factors:Female gender[Odds ratio(OR)=2.32,95%confidence interval(CI):1.56-3.45],history of mental disorders prior to stroke(OR=3.17,95%CI:1.89-5.32),infarct location in the frontal lobe or limbic system(OR=2.86,95%CI:1.73-4.71),stroke severity with National Institutes of Health Stroke Scale≥8 at admission(OR=2.54,95%CI:1.62-3.99),and low social support(Social Support Rating Scale<35,OR=2.18,95%CI:1.42-3.36).Subgroup analysis showed that depression patients more commonly had left hemisphere lesions(68.4%vs 45.2%),while anxiety patients more frequently presented with right hemisphere lesions(59.5%vs 39.5%).The PSD group exhibited larger infarct volumes(8.7 cm^(3) vs 5.3 cm^(3)),more severe white matter hyperintensities,and more pronounced frontal lobe atrophy.Analysis of inflammatory markers showed significantly elevated levels of interleukin-6(7.8 pg/mL vs 4.5 pg/mL)and tumor necrosis factor-alpha(15.6 pg/mL vs 9.8 pg/mL)in the PSD group,while hypothalamicpituitary-adrenal axis function assessment revealed higher cortisol levels(386.5±92.3 nmol/L vs 328.7±75.6 nmol/L)and flattened diurnal rhythm in the PSD group.CONCLUSION PSD is a complex neuropsychiatric consequence of stroke involving disruption of the frontal-limbic circuitry,neuroinflammatory responses,and dysfunction of the hypothalamic-pituitary-adrenal axis.展开更多
Nursing education in Indonesia experienced a number of changes during the new normal.The biopsychosocial health status reveals how students can complete their studies well at nursing school in the new normal.A quantit...Nursing education in Indonesia experienced a number of changes during the new normal.The biopsychosocial health status reveals how students can complete their studies well at nursing school in the new normal.A quantitative,descriptive correlational study sampled 368 student nurses from2 universities.This study used a biopsychosocial questionnaire,which included biological,physiological,and social dimensions.In this study,there was no significant demographic student nurse relationship with the biological,psychological,and social dimensions of health,at P-value 0.05(Age P=0.70,P=0.27,P=0.93)sex(P=1,P=0.919,P=0.5),as well as grade level(P=0.9,P=0.37,P=0.64).Student nurses were dynamic,such as process input,resulting in coping adaptation and the ability to care for themselves.There was a relationship between both universities with a psychological dimension and a P-value of 0.049.In terms of Generation Z technology,both universities played a role.Lifestyle influences can lead to intense feelings of isolation and loneliness in some teens,including self-negativity,fear of missing out on information,and shame about not meeting appropriate standards for social media.The influence of an unhealthy lifestyle impacts stress and anxiety.The student nurses assigned considered themselves to be“healthy”in terms of their biopsychosocial health status.Student nurses continued to develop in their biopsychosocial health by utilizing different coping strategies to adapt and adjust to their environment in their school of nursing.展开更多
Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divide...Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divides the order of a group G.In this paper,some characterizations of G being p-solvable or p-supersolvable were obtained by analyzing the normal index of certain subgroups of G.These results can be viewed as local version of recent results in the literature.展开更多
BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making ...BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making it a signifi cant public health concern.This study is to determine the prevalence and factors associated with acute pain among emergency trauma patients.METHODS:A multicenter cross-sectional study was conducted.Data were collected via interviewer-administered questionnaires and patient chart review.The data were analyzed via the statistical package for social science version 25.Bivariable and multivariable logistic regression analyses were used.Variables with a P-value<0.05 were considered statistically signifi cant.RESULTS:A total of 397 patients were included in the study,for a response rate of 96.8%.The prevalence of pain during admission was 91.9%(95%confi dence intervals[95%CIs]:88.8%-94.4%).Blunt trauma(adjusted odds ratio[aOR]=2.82;95%CI:1.23-6.45),analgesia before admission to the emergency department(aOR=2.71;95%CI:1.16-6.36),documentation of pain severity in the chart(aOR=2.71;95%CI:1.16-6.36),analgesia provided within two hours after admission(aOR=7.60;95%CI:2.79-20.68),use of non-pharmacological pain management methods(aOR=3.09;95%CI:1.35-7.08)and availability of analgesia(aOR=3.95;95%CI:1.36-11.43)were associated with acute pain experience.CONCLUSION:The prevalence of acute pain among emergency trauma patients was high in the study area.Analgesia should be administered prior to admission,and non-pharmacological pain management should be implemented.Moreover,training on pain assessment and management should be provided for healthcare providers in the emergency department.展开更多
A model for dynamic frictionless contact between a viscoelastic body and foundation is considered.The viscoelastic constitutive law is assumed to be nonlinear and the contact is modelled with the normal compliance con...A model for dynamic frictionless contact between a viscoelastic body and foundation is considered.The viscoelastic constitutive law is assumed to be nonlinear and the contact is modelled with the normal compliance condition.We obtain the well-posedness using nonlinear semigroup theory arguments.Moreover,the exponential stability result of the solution is shown by using the energy method to produce a suitable Lyapunov function.展开更多
Intermittent joints are common in rock masses and are subjected to cyclic shear loads from seismic events,environmental factors,and human activities.In this study,we conducted cyclic shear tests to investigate the eff...Intermittent joints are common in rock masses and are subjected to cyclic shear loads from seismic events,environmental factors,and human activities.In this study,we conducted cyclic shear tests to investigate the effect of joint geometry(persistence,overlap,and spacing)on the cyclic shear behavior of intermittent joints under constant normal stiffness conditions.Our results revealed step‐path failure surfaces comprising tensile and shear failure surfaces.Shear failure surface controlled the degradation of shear properties,with shear strength decreasing progressively with cycles,ranging from 74.07%to 97.94%.Intermittent joints exhibited significant compressibility,with dilation predominant in early cycles and compression in later ones.Shear strength and dilation were more sensitive to joint persistence and spacing than overlap.Friction coefficients showed nonmonotonic variations with cycle number.High persistence,moderate overlap,and small spacing were identified as the most destabilizing combination.These findings offer valuable insights for stability assessment and deformation characterization in deep rock engineering.展开更多
Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability...Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability. Even without apparent inflammation, injury sites are associated with increased inflammatory markers. This review focuses on how it might be possible to reduce neuropathic pain by reducing inflammation. Physiologically, pain is resolved by a combination of the out-migration of pro-inflammatory cells from the injury site, the down-regulation of the genes underlying the inflammation, up-regulating genes for anti-inflammatory mediators, and reducing nociceptive neuron hyperexcitability. While various techniques reduce chronic neuropathic pain, the best are effective on < 50% of patients, no technique reliably or permanently eliminates neuropathic pain. This is because most techniques are predominantly aimed at reducing pain, not inflammation. In addition, while single factors reduce pain, increasing evidence indicates significant and longer-lasting pain relief requires multiple factors acting simultaneously. Therefore, it is not surprising that extensive data indicate that the application of platelet-rich plasma provides more significant and longer-lasting pain suppression than other techniques, although its analgesia is neither complete nor permanent. However, several case reports indicate that platelet-rich plasma can induce permanent neuropathic pain elimination when the platelet concentration is significantly increased and is applied to longer nerve lengths. This review examines the primary triggers of the development and maintenance of neuropathic pain and techniques that reduce chronic neuropathic pain. The application of plateletrich plasma holds great promise for providing complete and permanent chronic neuropathic pain elimination.展开更多
基金supported by the National Institute of Environmental Research(NIER)funded by the Ministry of Environment(No.NIER-2019-04-02-039)supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry&Technology Institute(KEITI)funded by the Ministry of Environment(MOE).
文摘Fine particulatematter(PM_(2.5))samples were collected in two neighboring cities,Beijing and Baoding,China.High-concentration events of PM_(2.5) in which the average mass concentration exceeded 75μg/m^(3) were frequently observed during the heating season.Dispersion Normalized Positive Matrix Factorization was applied for the source apportionment of PM_(2.5) as minimize the dilution effects of meteorology and better reflect the source strengths in these two cities.Secondary nitrate had the highest contribution for Beijing(37.3%),and residential heating/biomass burning was the largest for Baoding(27.1%).Secondary nitrate,mobile,biomass burning,district heating,oil combustion,aged sea salt sources showed significant differences between the heating and non-heating seasons in Beijing for same period(2019.01.10–2019.08.22)(Mann-Whitney Rank Sum Test P<0.05).In case of Baoding,soil,residential heating/biomass burning,incinerator,coal combustion,oil combustion sources showed significant differences.The results of Pearson correlation analysis for the common sources between the two cities showed that long-range transported sources and some sources with seasonal patterns such as oil combustion and soil had high correlation coefficients.Conditional Bivariate Probability Function(CBPF)was used to identify the inflow directions for the sources,and joint-PSCF(Potential Source Contribution Function)was performed to determine the common potential source areas for sources affecting both cities.These models facilitated a more precise verification of city-specific influences on PM_(2.5) sources.The results of this study will aid in prioritizing air pollution mitigation strategies during the heating season and strengthening air quality management to reduce the impact of downwind neighboring cities.
文摘The rapid rise of cyberattacks and the gradual failure of traditional defense systems and approaches led to using artificial intelligence(AI)techniques(such as machine learning(ML)and deep learning(DL))to build more efficient and reliable intrusion detection systems(IDSs).However,the advent of larger IDS datasets has negatively impacted the performance and computational complexity of AI-based IDSs.Many researchers used data preprocessing techniques such as feature selection and normalization to overcome such issues.While most of these researchers reported the success of these preprocessing techniques on a shallow level,very few studies have been performed on their effects on a wider scale.Furthermore,the performance of an IDS model is subject to not only the utilized preprocessing techniques but also the dataset and the ML/DL algorithm used,which most of the existing studies give little emphasis on.Thus,this study provides an in-depth analysis of feature selection and normalization effects on IDS models built using three IDS datasets:NSL-KDD,UNSW-NB15,and CSE–CIC–IDS2018,and various AI algorithms.A wrapper-based approach,which tends to give superior performance,and min-max normalization methods were used for feature selection and normalization,respectively.Numerous IDS models were implemented using the full and feature-selected copies of the datasets with and without normalization.The models were evaluated using popular evaluation metrics in IDS modeling,intra-and inter-model comparisons were performed between models and with state-of-the-art works.Random forest(RF)models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86%and 96.01%,respectively,whereas artificial neural network(ANN)achieved the best accuracy of 95.43%on the CSE–CIC–IDS2018 dataset.The RF models also achieved an excellent performance compared to recent works.The results show that normalization and feature selection positively affect IDS modeling.Furthermore,while feature selection benefits simpler algorithms(such as RF),normalization is more useful for complex algorithms like ANNs and deep neural networks(DNNs),and algorithms such as Naive Bayes are unsuitable for IDS modeling.The study also found that the UNSW-NB15 and CSE–CIC–IDS2018 datasets are more complex and more suitable for building and evaluating modern-day IDS than the NSL-KDD dataset.Our findings suggest that prioritizing robust algorithms like RF,alongside complex models such as ANN and DNN,can significantly enhance IDS performance.These insights provide valuable guidance for managers to develop more effective security measures by focusing on high detection rates and low false alert rates.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences(No.KSCX2-EW-G-12B)the Knowledge Innovation Program of the Chinese Academy of Sciences(No.KZCX2-EW-Q213)the National High Technology Research and Development Program of China (863 Program)(No.2012AA10A412)
文摘Quantitative real-time reverse transcription-polymerase chain reaction （qRT-PCR） is widely used in studies of gene expression. In most of these studies, housekeeping genes are used as internal references without validation. To identify appropriate reference genes for qRT-PCR in Pacific abalone Haliotis discus hannai, we examined the transcription stability of six housekeeping genes in abalone tissues in the presence and absence of bacterial infection. For this purpose, abalone were infected with the bacterial pathogen Fibrio anguillarum for 12 h and 48 h. The mRNA levels of the housekeeping genes in five tissues （digestive glands, foot muscle, gill, hemocyte, and mantle） were determined by qRT-PCR. The PCR data was subsequently analyzed with the geNorm and NormFinder algorithms. The results show that in the absence of bacterial infection, elongation factor-l-alpha and beta-actin were the most stably expressed genes in all tissues, and thus are suitable as cross-tissue type normalization factors. However, we did not identify any universal reference genes post infection because the most stable genes varied between tissue types. Furthermore, for most tissues, the optimal reference genes identified by both algorithms at 12 h and 48 h post-infection differed. These results indicate that bacterial infection induced significant changes in the expression of abalone housekeeping genes in a manner that is dependent on tissue type and duration of infection. As a result, different normalization factors must be used for different tissues at different infection points.
基金Supported by Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Special Project,No.YN2023WSSQ01State Key Laboratory of Traditional Chinese Medicine Syndrome.
文摘BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.
基金Mid-term Results of the 2024 Langfang Normal University Special Teaching Reform Project on Innovation and Entrepreneurship Education Reform,“Research on the Evaluation System of Innovation and Entrepreneurship Ability for Normal University Students Based on Big Data Application-A Case Study of Langfang Normal University”(Project No.:CXJG2024-06)。
文摘Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
基金supported by the National Research Foundation of Korea(NRF)grant for RLRC funded by the Korea government(MSIT)(No.2022R1A5A8026986,RLRC)supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2020-0-01304,Development of Self-Learnable Mobile Recursive Neural Network Processor Technology)+3 种基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the Grand Information Technology Research Center support program(IITP-2024-2020-0-01462,Grand-ICT)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)supported by the Korea Technology and Information Promotion Agency for SMEs(TIPA)supported by the Korean government(Ministry of SMEs and Startups)’s Smart Manufacturing Innovation R&D(RS-2024-00434259).
文摘On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.
基金supported by grants from the Zhejiang Provincial TCM Science and Technology Plan Project,No.2023ZL156(to YH)Ningbo Top Medical and Health Research Program,No.2022020304(to XG)+1 种基金the Natural Science Foundation of Ningbo,No.2023J019(to YH)Key Laboratory of Precision Medicine for Atherosclerotic Diseases of Zhejiang Province,No.2022E10026(to YH)。
文摘Strokes include both ischemic stroke,which is mediated by a blockade or reduction in the blood supply to the brain,and hemorrhagic stroke,which comprises intracerebral hemorrhage and subarachnoid hemorrhage and is characterized by bleeding within the brain.Stroke is a lifethreatening cerebrovascular condition characterized by intricate pathophysiological mechanisms,including oxidative stress,inflammation,mitochondrial dysfunction,and neuronal injury.Critical transcription factors,such as nuclear factor erythroid 2-related factor 2 and nuclear factor kappa B,play central roles in the progression of stroke.Nuclear factor erythroid 2-related factor 2 is sensitive to changes in the cellular redox status and is crucial in protecting cells against oxidative damage,inflammatory responses,and cytotoxic agents.It plays a significant role in post-stroke neuroprotection and repair by influencing mitochondrial function,endoplasmic reticulum stress,and lysosomal activity and regulating metabolic pathways and cytokine expression.Conversely,nuclear factor-kappa B is closely associated with mitochondrial dysfunction,the generation of reactive oxygen species,oxidative stress exacerbation,and inflammation.Nuclear factor-kappa B contributes to neuronal injury,apoptosis,and immune responses following stroke by modulating cell adhesion molecules and inflammatory mediators.The interplay between these pathways,potentially involving crosstalk among various organelles,significantly influences stroke pathophysiology.Advancements in single-cell sequencing and spatial transcriptomics have greatly improved our understanding of stroke pathogenesis and offer new opportunities for the development of targeted,individualized,cell typespecific treatments.In this review,we discuss the mechanisms underlying the involvement of nuclear factor erythroid 2-related factor 2 and nuclear factor-kappa B in both ischemic and hemorrhagic stroke,with an emphasis on their roles in oxidative stress,inflammation,and neuroprotection.
文摘Renormalization group analysis has been proposed to eliminate secular terms in perturbation solutions of differential equations and thus expand the domain of their validity.Here we extend the method to treat periodic orbits or limit cycles.Interesting normal forms could be derived through a generalization of the concept'resonance',which offers nontrivial analytic approximations.Compared with traditional techniques such as multi-scale methods,the current scheme proceeds in a very straightforward and simple way,delivering not only the period and the amplitude but also the transient path to limit cycles.The method is demonstrated with several examples including the Duffing oscillator,van der Pol equation and Lorenz equation.The obtained solutions match well with numerical results and with those derived by traditional analytic methods.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT(NRF-2022R1A2C2012243).
文摘In recent decades,brain tumors have emerged as a serious neurological disorder that often leads to death.Hence,Brain Tumor Segmentation(BTS)is significant to enable the visualization,classification,and delineation of tumor regions in Magnetic Resonance Imaging(MRI).However,BTS remains a challenging task because of noise,non-uniform object texture,diverse image content and clustered objects.To address these challenges,a novel model is implemented in this research.The key objective of this research is to improve segmentation accuracy and generalization in BTS by incorporating Switchable Normalization into Faster R-CNN,which effectively captures the fine-grained tumor features to enhance segmentation precision.MRI images are initially acquired from three online datasets:Dataset 1—Brain Tumor Segmentation(BraTS)2018,Dataset 2—BraTS 2019,and Dataset 3—BraTS 2020.Subsequently,the Switchable Normalization-based Faster Regions with Convolutional Neural Networks(SNFRC)model is proposed for improved BTS in MRI images.In the proposed model,Switchable Normalization is integrated into the conventional architecture,enhancing generalization capability and reducing overfitting to unseen image data,which is essential due to the typically limited size of available datasets.The network depth is increased to obtain discriminative semantic features that improve segmentation performance.Specifically,Switchable Normalization captures the diverse feature representations from the brain images.The Faster R-CNN model develops end-to-end training and effective regional proposal generation,with an enhanced training stability using Switchable Normalization,to perform an effective segmentation in MRI images.From the experimental results,the proposed model attains segmentation accuracies of 99.41%,98.12%,and 96.71%on Datasets 1,2,and 3,respectively,outperforming conventional deep learning models used for BTS.
基金supported by the 2025 Fujian Provincial Social Science Foundation Project(FJ2025C074).
文摘This systematic review synthesizes empirical research on external risk factors for adolescent smartphone addiction.Scopus and Web of Science were searched for English peer-reviewed empirical articles from 2008 onward;28 met inclusion criteria(excluding non-adolescents,generic internet addiction,non-empirical work,or non-English).Thematic synthesis organized findings into three external risk domains—family,school,and peers—considering cultural/contextual mechanisms.Family dynamics(parental phubbing,harsh parenting,dysfunction),school stressors,and adverse peer relationships were identified as accumulating,direct and indirect contributors to smartphone addiction.These operate within a techno-ecological framework,where digital technologies amplify vulnerabilities and create new pathways for maladaptive use.Evidence favors an ecological,multi-level perspective.Future research should use longitudinal designs,standardize measures across cultures,and examine understudied regions—especially Africa—to guide culturally sensitive interventions.
基金supported by the National Natural Science Foundation of China(Grant Nos.32201834 and 32201814)the Hainan Provincial Natural Science Foundation of China(Grant No.324RC530)+1 种基金the Hainan Provincial‘Nanhai NewStar’Science and Technology Innovation Platform Project,China(Grant No.NHXXRCXM-202362)the Research Startup Funding from Hainan Institute of Zhejiang University,China(Grant No.0201-6602-A12202).
文摘The significant variation in plant regeneration efficiency between indica and japonica rice poses a major challenge for crop improvement.However,the molecular basis for this divergence remains largely unclear.In this study,we investigated the role of Oryza sativa AUXIN RESPONSE FACTOR 13(OsARF13),a transcription factor involved in callus-related processes.We observed that OsARF13 expression is significantly higher in japonica rice callus than in indica rice callus.This differential expression might be associated with an allelic variation in the promoter region of OsARF13,where a deletion commonly found in indica rice corresponds to the loss of a conserved auxin-responsive element(AuxRE)motif.To functionally characterize OsARF13,we generated CRISPR/Cas9-mediated knockout mutants.These mutants exhibited a substantial reduction in callus fresh weight,demonstrating that OsARF13 is required for efficient callus induction.Transcriptome analysis of the osarf13 mutant further showed that OsARF13 influences the expression of genes involved in hormone signal transduction and stress responses.Our findings suggest that OsARF13 is a key component of the regulatory network governing callus induction and that natural variation in its promoter might provide a potential explanation for the differential regenerative capacity between japonica and indica rice subspecies.
文摘BACKGROUND Ischemic stroke is one of the leading global causes of disability and death.Despite advances in modern medical technology that improve acute treatment and rehabilitation measures,post-stroke anxiety and depression(PSD)do not receive sufficient attention.AIM To systematically evaluate risk factors and early identification markers for PSD for more precise screening and intervention strategies in clinical practice.METHODS This retrospective study analyzed clinical data from 112 patients with ischemic stroke admitted between January 2022 and December 2024.Based on assessments using the Hamilton Rating Scale for Anxiety(HAMA)and Hamilton Rating Scale for Depression(HAMD)at 2 weeks(±3 days)post-stroke,patients were classified into the PSD group(HAMA≥7 and/or HAMD≥7)and the non-PSD group(HAMA<7 and HAMD<7).Observation indicators included psychological assessment,demographic and clinical characteristics,stroke-related clinical indicators,neuroimaging assessments,and laboratory biomarkers.Multivariate logistic regression analysis was used to identify independent risk factors for PSD,and receiver operating characteristic curve analysis was used to evaluate the diagnostic value of potential biomarkers.RESULTS Of the 112 patients,46(41.1%)were diagnosed with PSD.Multivariate analysis identified five independent risk factors:Female gender[Odds ratio(OR)=2.32,95%confidence interval(CI):1.56-3.45],history of mental disorders prior to stroke(OR=3.17,95%CI:1.89-5.32),infarct location in the frontal lobe or limbic system(OR=2.86,95%CI:1.73-4.71),stroke severity with National Institutes of Health Stroke Scale≥8 at admission(OR=2.54,95%CI:1.62-3.99),and low social support(Social Support Rating Scale<35,OR=2.18,95%CI:1.42-3.36).Subgroup analysis showed that depression patients more commonly had left hemisphere lesions(68.4%vs 45.2%),while anxiety patients more frequently presented with right hemisphere lesions(59.5%vs 39.5%).The PSD group exhibited larger infarct volumes(8.7 cm^(3) vs 5.3 cm^(3)),more severe white matter hyperintensities,and more pronounced frontal lobe atrophy.Analysis of inflammatory markers showed significantly elevated levels of interleukin-6(7.8 pg/mL vs 4.5 pg/mL)and tumor necrosis factor-alpha(15.6 pg/mL vs 9.8 pg/mL)in the PSD group,while hypothalamicpituitary-adrenal axis function assessment revealed higher cortisol levels(386.5±92.3 nmol/L vs 328.7±75.6 nmol/L)and flattened diurnal rhythm in the PSD group.CONCLUSION PSD is a complex neuropsychiatric consequence of stroke involving disruption of the frontal-limbic circuitry,neuroinflammatory responses,and dysfunction of the hypothalamic-pituitary-adrenal axis.
文摘Nursing education in Indonesia experienced a number of changes during the new normal.The biopsychosocial health status reveals how students can complete their studies well at nursing school in the new normal.A quantitative,descriptive correlational study sampled 368 student nurses from2 universities.This study used a biopsychosocial questionnaire,which included biological,physiological,and social dimensions.In this study,there was no significant demographic student nurse relationship with the biological,psychological,and social dimensions of health,at P-value 0.05(Age P=0.70,P=0.27,P=0.93)sex(P=1,P=0.919,P=0.5),as well as grade level(P=0.9,P=0.37,P=0.64).Student nurses were dynamic,such as process input,resulting in coping adaptation and the ability to care for themselves.There was a relationship between both universities with a psychological dimension and a P-value of 0.049.In terms of Generation Z technology,both universities played a role.Lifestyle influences can lead to intense feelings of isolation and loneliness in some teens,including self-negativity,fear of missing out on information,and shame about not meeting appropriate standards for social media.The influence of an unhealthy lifestyle impacts stress and anxiety.The student nurses assigned considered themselves to be“healthy”in terms of their biopsychosocial health status.Student nurses continued to develop in their biopsychosocial health by utilizing different coping strategies to adapt and adjust to their environment in their school of nursing.
基金Supported by the National Natural Science Foundation of China(Grant No.12071092)Guangdong Basic and Applied Basic Research Foundation(Grant No.2025A1515012072)+1 种基金the Natural Science Research Project of Anhui Educational Committee(Grant No.2024AH051298)the Scientific Research Foundation of Bozhou University(Grant No.BYKQ202419).
文摘Let G be a finite group and H a subgroup of G.The normal index of H in G is defined as the order of K/H_(G),where K is a normal supplement of H in G such that|K|is minimal and H_(G)≤K■G.Let p be a prime which divides the order of a group G.In this paper,some characterizations of G being p-solvable or p-supersolvable were obtained by analyzing the normal index of certain subgroups of G.These results can be viewed as local version of recent results in the literature.
文摘BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making it a signifi cant public health concern.This study is to determine the prevalence and factors associated with acute pain among emergency trauma patients.METHODS:A multicenter cross-sectional study was conducted.Data were collected via interviewer-administered questionnaires and patient chart review.The data were analyzed via the statistical package for social science version 25.Bivariable and multivariable logistic regression analyses were used.Variables with a P-value<0.05 were considered statistically signifi cant.RESULTS:A total of 397 patients were included in the study,for a response rate of 96.8%.The prevalence of pain during admission was 91.9%(95%confi dence intervals[95%CIs]:88.8%-94.4%).Blunt trauma(adjusted odds ratio[aOR]=2.82;95%CI:1.23-6.45),analgesia before admission to the emergency department(aOR=2.71;95%CI:1.16-6.36),documentation of pain severity in the chart(aOR=2.71;95%CI:1.16-6.36),analgesia provided within two hours after admission(aOR=7.60;95%CI:2.79-20.68),use of non-pharmacological pain management methods(aOR=3.09;95%CI:1.35-7.08)and availability of analgesia(aOR=3.95;95%CI:1.36-11.43)were associated with acute pain experience.CONCLUSION:The prevalence of acute pain among emergency trauma patients was high in the study area.Analgesia should be administered prior to admission,and non-pharmacological pain management should be implemented.Moreover,training on pain assessment and management should be provided for healthcare providers in the emergency department.
文摘A model for dynamic frictionless contact between a viscoelastic body and foundation is considered.The viscoelastic constitutive law is assumed to be nonlinear and the contact is modelled with the normal compliance condition.We obtain the well-posedness using nonlinear semigroup theory arguments.Moreover,the exponential stability result of the solution is shown by using the energy method to produce a suitable Lyapunov function.
基金National Natural Science Foundation of China,Grant/Award Number:42172292Shandong Energy Group,Grant/Award Number:SNKJ2022A01-R26Taishan Scholars Project Special Funding。
文摘Intermittent joints are common in rock masses and are subjected to cyclic shear loads from seismic events,environmental factors,and human activities.In this study,we conducted cyclic shear tests to investigate the effect of joint geometry(persistence,overlap,and spacing)on the cyclic shear behavior of intermittent joints under constant normal stiffness conditions.Our results revealed step‐path failure surfaces comprising tensile and shear failure surfaces.Shear failure surface controlled the degradation of shear properties,with shear strength decreasing progressively with cycles,ranging from 74.07%to 97.94%.Intermittent joints exhibited significant compressibility,with dilation predominant in early cycles and compression in later ones.Shear strength and dilation were more sensitive to joint persistence and spacing than overlap.Friction coefficients showed nonmonotonic variations with cycle number.High persistence,moderate overlap,and small spacing were identified as the most destabilizing combination.These findings offer valuable insights for stability assessment and deformation characterization in deep rock engineering.
文摘Nerve trauma commonly results in chronic neuropathic pain. This is by triggering the release of proinflammatory mediators from local and invading cells that induce inflammation and nociceptive neuron hyperexcitability. Even without apparent inflammation, injury sites are associated with increased inflammatory markers. This review focuses on how it might be possible to reduce neuropathic pain by reducing inflammation. Physiologically, pain is resolved by a combination of the out-migration of pro-inflammatory cells from the injury site, the down-regulation of the genes underlying the inflammation, up-regulating genes for anti-inflammatory mediators, and reducing nociceptive neuron hyperexcitability. While various techniques reduce chronic neuropathic pain, the best are effective on < 50% of patients, no technique reliably or permanently eliminates neuropathic pain. This is because most techniques are predominantly aimed at reducing pain, not inflammation. In addition, while single factors reduce pain, increasing evidence indicates significant and longer-lasting pain relief requires multiple factors acting simultaneously. Therefore, it is not surprising that extensive data indicate that the application of platelet-rich plasma provides more significant and longer-lasting pain suppression than other techniques, although its analgesia is neither complete nor permanent. However, several case reports indicate that platelet-rich plasma can induce permanent neuropathic pain elimination when the platelet concentration is significantly increased and is applied to longer nerve lengths. This review examines the primary triggers of the development and maintenance of neuropathic pain and techniques that reduce chronic neuropathic pain. The application of plateletrich plasma holds great promise for providing complete and permanent chronic neuropathic pain elimination.
