Here we complete our work on the asymptotics of Hankel determinants studying the case wherein the entries are “ultrarapidly”-varying functions in the sense that their logarithms are rapidly varying. Moreover, the la...Here we complete our work on the asymptotics of Hankel determinants studying the case wherein the entries are “ultrarapidly”-varying functions in the sense that their logarithms are rapidly varying. Moreover, the last results in the paper highlight analogies between algebraic identities for Hankelians with special entries and asymptotic relations valid for large classes of entries.展开更多
We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, wher...We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, where the lower and the upper value functions are defined through this BSDE. The existence and the uniqueness theorem and comparison theorem are proved for such equations with the help of an iteration method. We also show that the lower and the upper value functions satisfy the dynamic programming principle. Moreover, we study the associated Hamilton-Jacobi-Bellman-Isaacs(HJB-Isaacs)equations, which are nonlocal, and strongly coupled with the lower and the upper value functions. Using a new method, we characterize the pair(W, U) consisting of the lower and the upper value functions as the unique viscosity solution of our nonlocal HJB-Isaacs equation. Furthermore, the game has a value under the Isaacs’ condition.展开更多
Motivated by a general theory of finite asymptotic expansions in the real domain for functions f of one real variable, a theory developed in a previous series of papers, we present a detailed survey on the classes of ...Motivated by a general theory of finite asymptotic expansions in the real domain for functions f of one real variable, a theory developed in a previous series of papers, we present a detailed survey on the classes of higher-order asymptotically-varying functions where “asymptotically” stands for one of the adverbs “regularly, smoothly, rapidly, exponentially”. For order 1 the theory of regularly-varying functions (with a minimum of regularity such as measurability) is well established and well developed whereas for higher orders involving differentiable functions we encounter different approaches in the literature not linked together, and the cases of rapid or exponential variation, even of order 1, are not systrematically treated. In this semi-expository paper we systematize much scattered matter concerning the pertinent theory of such classes of functions hopefully being of help to those who need these results for various applications. The present Part I contains the higher-order theory for regular, smooth and rapid variation.展开更多
In this second part, we thoroughly examine the types of higher-order asymptotic variation of a function obtained by all possible basic algebraic operations on higher-order varying functions. The pertinent proofs are s...In this second part, we thoroughly examine the types of higher-order asymptotic variation of a function obtained by all possible basic algebraic operations on higher-order varying functions. The pertinent proofs are somewhat demanding except when all the involved functions are regularly varying. Next, we give an exposition of three types of exponential variation with an exhaustive list of various asymptotic functional equations satisfied by these functions and detailed results concerning operations on them. Simple applications to integrals of a product and asymptotic behavior of sums are given. The paper concludes with applications of higher-order regular, rapid or exponential variation to asymptotic expansions for an expression of type f(x+r(x)).展开更多
BACKGROUND Schizophrenia presents complex challenges in older patients due to cognitive and social decline.Existing drug treatments offer limited benefits and pose risks,while aerobic exercise shows promise as a nonin...BACKGROUND Schizophrenia presents complex challenges in older patients due to cognitive and social decline.Existing drug treatments offer limited benefits and pose risks,while aerobic exercise shows promise as a noninvasive intervention whose impact remains underexplored.AIM To investigate the effects of aerobic exercise on cognitive and social function in older patients with schizophrenia.METHODS A retrospective study was conducted in 158 older patients with schizophrenia treated at The First Affiliated Hospital of Chongqing Medical and Pharmaceutical College(June 2023 and December 2024).The patients were divided into an observation group(n=86),which received 3 months of aerobic rehabilitation alongside routine treatment,and a control group(n=72),which received routine treatment alone.Cognitive function was assessed using the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery,social function using the Inpatient Psychiatric Rehabilitation Outcome Scale(IPROS),and psychotic symptoms using the Positive and Negative Syndrome Scale.RESULTS Post-treatment,Positive and Negative Syndrome Scale total scores were lower in the observation group than in the controls(P<0.001),with significant improvements in positive,negative,and general symptoms.Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery domain scores were improved in processing speed,working memory,verbal/visual learning,and executive function(all P<0.05).IPROS total scores were decreased(P<0.001),indicating better social functioning.Longer exercise duration correlated with greater cognitive gains and lower social function deficits.Body mass index declined(P<0.001),and adverse events were mild and transient(9.3%).Multivariate linear regression confirmed that aerobic exercise was independently associated with a significant reduction in IPROS scores(Adjustedβ=-4.57,95%confidence intervals:-6.08 to-3.05,P<0.001).CONCLUSION Aerobic exercise effectively improves cognitive function,social function,and psychotic symptoms in older patients with schizophrenia,is safe,and serves as a valuable adjunctive intervention.展开更多
Turnout irregularity significantly affects the stochastic vibration behavior of vehicle-turnout structures.This study proposes a fitting formula for the turnout irregularity spectrum and develops a turnout irregularit...Turnout irregularity significantly affects the stochastic vibration behavior of vehicle-turnout structures.This study proposes a fitting formula for the turnout irregularity spectrum and develops a turnout irregularity full information expression model(TIFIEM)using a stochastic harmonic function.The model is applied to vehicle-turnout structure stochastic vibration and reliability analysis.Findings suggest that the Hamming window method,with a window length of 4096 points,is optimal for estimating the turnout irregularity spectrum.It is recommended to fit the power spectral density(PSD)using a 5th-order polynomial for better accuracy.The TIFIEM effectively addresses randomness in amplitude,frequency,and phase.An analysis of 250 irregularity samples is sufficient for the desired accuracy.Additionally,the PSD amplitude at various frequency points follows a Chi-square distribution with 2°of freedom.Regions 3-7 m from the tip of the switch rail on the straight switch rail and 53-54 m on the point rail are most susceptible to wear.When the vehicle passes through the turnout at 300 km/h,the reliability of vehicle-turnout structures at the crossing panel decreases to 95.8%.展开更多
In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov ...In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov processes,non-stationary signals,and other mathematical disciplines.The aim of the current research article is to first improve the bounds of coefficient-related problems by employing the well-known Carathéodory function.The problems that we are going to improve were obtained by Tang et al.The sharp estimates of the most difficult problem of geometric function theory known as the third-order Hankel determinant are also contributed here.Zalcman and Fekete-Szegöinequalities are also studied here for the defined family of holomorphic functions.展开更多
Over the past two decades,UFMylation,a crucial post-translational modification mediated by a canonical E1—E2—E3 enzymatic cascade and specific deUFMylation enzymes,has emerged as an essential component for maintaini...Over the past two decades,UFMylation,a crucial post-translational modification mediated by a canonical E1—E2—E3 enzymatic cascade and specific deUFMylation enzymes,has emerged as an essential component for maintaining cellular homeostasis.It plays indispensable regulatory roles in fundamental processes,including protein quality control,genome stability maintenance,cell fate determination,and modulation of immune responses.These functions are achieved by precisely regulating key protein substrates and their associated signaling pathways.Consequently,dysregulation of these UFMylationregulated processes directly drives the pathogenesis of a broad spectrum of human diseases.This review summarizes current insights into the UFMylation machinery,its enzymatic cascade,and related fundamental cellular processes.We systematically explain the molecular mechanisms by which UFMylation regulates cellular functions and discuss how its dysfunction contributes to the pathogenesis of a wide range of human diseases,including cancers,skeletal dysplasias,hematological disorders,nervous system disorders,metabolic-associated liver disease,silicosis,and cardiovascular diseases.Deciphering the precise molecular mechanisms underlying these pathologies is crucial for identifying diagnostic biomarkers and developing targeted therapeutic strategies.Furthermore,we highlight future perspectives on targeting the UFMylation system for therapeutic intervention in these diseases.展开更多
Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the bi...Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the biosynthetic pathway of saikosaponins,we identified two cytochrome P450 monooxygenases,CYP716A41 and CYP716Y4,in Bupleurum chinense.These enzymes catalyze the C-28 oxidation and C-16 hydroxylation of oleanane-type triterpene skeletons,respectively.The catalytic efficiency of CYP716A41 from a southern B.chinense variety was significantly higher than that from a northern variety.Molecular docking and mutagenesis experiments revealed that amino acid residues at sites 9 and 35 may contribute to this difference in catalytic efficiency.Additionally,under cold stress,the expression levels of both CYP450 genes and the saikosaponin contents in the leaves of southern varieties were significantly higher compared to those in northern varieties.The variation in the catalytic efficiency of CYP716A41 and the differential expression of the two CYP450 genes under cold stress during winter are associated with the differences in saikosaponin biosynthesis in the leaves of southern and northern B.chinense varieties.This is consistent with the distinct medicinal usage practices observed between southern and northern China.展开更多
Accurate classification of brain tumors from medical images is essential for enabling timely diagnosis and effective treatment.This study aimed to develop an innovative method for the diagnosis of brain tumors through...Accurate classification of brain tumors from medical images is essential for enabling timely diagnosis and effective treatment.This study aimed to develop an innovative method for the diagnosis of brain tumors through a Fuzzy Richards Functions-based Ensemble Network(FRE-Net).The parameters of the Richards function are optimized through Grid Search(GS)for selecting an optimal set of parameters.Our proposed method integrates three well-established pre-trained Convolutional Neural Networks(CNNs):MobileNetV1,MobileNetV2,ResNet50V2.To increase the robustness of these models,we incorporate a novel Lightweight Multiscale with Squeeze and Excitation(LiteMSSE)Block,which improves performance by enhancing multi-scale feature extraction and enabling the network to capture more detailed spatial information for focusing on the most relevant features to improve overall diagnostic performance.Additionally,probabilities from the individual models are aggregated using a Fuzzy Richards Functions approach,which reduces the error between observed and ground truth data,further enhancing detection accuracy.The key innovation of this study lies in the design of novel LiteMSSE Block and use of Fuzzy Richard Function,which together enhance multi-scale feature extraction and combines diverse model predictions intelligently.The proposed FRE-Net method achieves an impressive accuracy of 98.47%on the four-class Kaggle dataset and 99.00%on the BR35H dataset by highlighting its potential as a powerful tool for diagnosis of brain MRI more precisely.Through extensive evaluations,we determine that our proposed ensemble method outperforms individual backbone models and existing methods.展开更多
Mitochondria are essential organelles primarily described for their vital role in producing energy through oxidative phosphorylation(OxPhos).Due to the hypoxic environment of chondrocytes and their heavy reliance on g...Mitochondria are essential organelles primarily described for their vital role in producing energy through oxidative phosphorylation(OxPhos).Due to the hypoxic environment of chondrocytes and their heavy reliance on glycolysis,mitochondrial functions have long been considered of minimal relevance in these cells.However,as major suppliers of energy through the ATP they produce by OxPhos,mitochondria help to regulate the balance between anabolism and catabolism.In osteoarthritis(OA),the most prevalent joint disease,this balance is dysregulated.In addition,correlations between metabolic disorders and the risk of developing OA are also increasingly studied.In this context,mitochondrial dysfunctions in OA chondrocytes are emerging as a relevant area to propose efficient,yet unavailable,disease-modifying OA drugs(DMOADs).This narrative review examines the underlying mechanisms by which the mitochondrial functions become dysregulated in chondrocytes during OA.Drawing on up-to-date literature,it highlights how both structural and functional alterations of mitochondria contribute to OA pathology in chondrocytes.Finally,this review discusses the potential of mitochondria-targeted therapeutic strategies for OA,framed within a conceptual“repair or replace”approach.展开更多
This work begins by introducing the groundbreaking concept of log-p-analytic functions.Following this introduction,we proceed to delineate four distinct formulations of Landau-type theorems,specifically crafted for th...This work begins by introducing the groundbreaking concept of log-p-analytic functions.Following this introduction,we proceed to delineate four distinct formulations of Landau-type theorems,specifically crafted for the domain of poly-analytic functions.Among these,two theorems are distinguished by their exactitude,and a third theorem offers a refinement to the existing work of Abdulhadi and Hajj.Concluding the paper,we present four specialized versions of Landau-type theorems applicable to a subset of bounded log-p-analytic functions,resulting in the derivation of two precise outcomes.展开更多
We study the dependence of conditional stellar mass functions(CSMFs)on the cosmic-web environment using the TNG50 cosmological hydrodynamical simulation at z=0.By classifying host haloes into voids,sheets,filaments,an...We study the dependence of conditional stellar mass functions(CSMFs)on the cosmic-web environment using the TNG50 cosmological hydrodynamical simulation at z=0.By classifying host haloes into voids,sheets,filaments,and knots,we examine satellite and central galaxy populations over the host-mass range resolved in TNG50.Satellite CSMFs show systematic environment-dependent variations,with the clearest differences emerging at the faint end.In a representative low-mass host regime(log10(M200c/[M⊙h-1])∈[11.5,12.0]),the satellite faint-end slope is shallower in filaments(α■-0.38)than in sheets(α■-0.48),suggestive of a balance between anisotropic supply along filaments and subsequent environmental processing.For central galaxies,we observe a crossover-like trend in dwarf-scale hosts(log10(M200c/[M⊙h-1])∈[11.0,11.5]):knots and filaments exhibit a more extended high-M* tail,whereas voids and sheets host a higher fraction of low-mass centrals.Overall,our results suggest that the cosmic web environment imprints secondary,mass-dependent modulations on galaxy stellar mass distributions beyond halo mass alone,most clearly for faint satellites.展开更多
Small RNAs(sRNAs)are important non-coding RNAs that usually play crucial roles in gene expression at the post-transcriptional level.The sRNAs have mostly been investigated in model microorganisms such as Escherichia c...Small RNAs(sRNAs)are important non-coding RNAs that usually play crucial roles in gene expression at the post-transcriptional level.The sRNAs have mostly been investigated in model microorganisms such as Escherichia coli and some pathogens.Nevertheless,microbial sRNAs from extreme environments such as the polar regions and deep sea have recently been discovered and analyzed for their unique roles in stress response,metabolic regulation and adaptation to extreme environments.These sRNAs fine-tune gene expression during oxidative and radiation stress,and modulate temperature and osmotic pressure responses.Representative sRNAs and their functions in thermophilic,psychrophilic,halophilic and radiation-tolerant bacteria are summarized in this review.Despite challenges in sample collection,RNA isolation,and functional annotation,the study of sRNAs in extreme environments provides opportunities for discovering novel regulatory mechanisms,applying them to biotechnology,and advancing our understanding of evolutionary adaptations.Looking ahead,high-throughput sequencing,synthetic biology,and multi-omics integration will bring new breakthroughs in discovering novel sRNAs and their functions and regulatory mechanisms.Such advancements are poised to enable comprehensive characterization of sRNA-mediated regulatory networks in extremophiles and unlock their biotechnological potential through mechanism-driven applications.展开更多
Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning sc...Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.展开更多
This paper proposes a fast quality control strategy for P-wave receiver functions based on AlexNet and wiggle plots.Receiver functions are essential tools in seismology,particularly for analyzing seismic wave propagat...This paper proposes a fast quality control strategy for P-wave receiver functions based on AlexNet and wiggle plots.Receiver functions are essential tools in seismology,particularly for analyzing seismic wave propagation and subsurface structures,such as the crust and upper mantle.However,the quality control of receiver functions is often a tedious,time-consuming process.In this study,we transform the time series classification problem of receiver function quality control problem into an image classification task by plotting receiver functions as wiggle diagrams and using the deep learning model AlexNet for binary classification to distinguish between“good”and“bad”receiver functions.The model achieved an accuracy of 92.55%on the testing set and demonstrated strong generalization performance with an accuracy of 89.23%on receiver functions of another seismic network(Sichuan Provincial Permanent Seismic Network).While maintaining strong performance,the model is capable of processing approximately 32 receiver function wiggle plots per second on an NVIDIA GeForce RTX 4050.The results show that the proposed feature mapping strategy significantly improves the efficiency and accuracy of receiver function quality control,making it a valuable tool for practical applications.Future work will focus on expanding the dataset and optimizing model performance for broader seismic data applications.展开更多
Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardwar...Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardware implementations face two main problems,including wasted area resources and excessive critical path delay.These issues limit the energy efficiency and integration level of stream cipher chips.To address these problems,this paper proposes an energy-efficient design method for a 64-bit Boolean function reconfigurable operation unit(BFROU),aiming to improve the computational efficiency of Boolean functions in stream ciphers.To optimize the design of BFROU,this paper takes the NPN equivalence theory as a guide.First,customized designs at the transistor level were performed for both 2-and 3-variable RM logic units(denoted as TRM).On this basis,this paper uses the port sharing strategy to further optimize the design of 4-to-6-variable TRM logic units and construct a multi-variable TRM process library.Then,by combining multi-variable TRM logic units with the mathematical definition of Boolean functions,this paper proposes a theoretical model of BFROU.Based on this model and combined with the statistical analysis results of Boolean functions,the optimal TRM unit configuration is determined,and the overall optimization of the 64-bit BFROU is finally completed.Experimental results show that when TRM-3 and TRM-4 units are mixed as the first-level operation module of BFROU,its area-delay product(ADP)reaches the minimum.The 64-bit BFROU unit implemented according to this scheme has an actual measured area of 137.28μm2 and a critical path delay of 0.278 ns under the SMIC 40 nm typical process corner.This unit supports Boolean function operations with up to 64 variables,and 94.4%of the functions can complete mapping within 2 iterations.Compared with existing schemes such as look-up table(LUT)architecture and And-Inverter Cone(AIC)array,the BFROU proposed in this paper has obvious advantages in area,delay,ADP and number of iterations,providing effective hardware support for the design of high-energy-efficiency stream cipher chips.展开更多
This study investigates the effects of ocean boundaries on modal shapes in very-low-frequency(VLF,1–10 Hz)sound propagation through the deep ocean.Utilizing a normal mode solution formulated in terms of parabolic cyl...This study investigates the effects of ocean boundaries on modal shapes in very-low-frequency(VLF,1–10 Hz)sound propagation through the deep ocean.Utilizing a normal mode solution formulated in terms of parabolic cylinder functions(PCF),we demonstrate that boundary interactions induce a phase change reduction below-πat frequencies of several hertz.This reduction,in turn,forces a key transition in the solution,shifting the order of the PCF from integer to non-integer values.Analysis of the characteristic shape of the PCF versus its order reveals that these boundary-influenced modes exhibit an energy shift toward deeper regions and a weakened axial convergence of the underwater sound field.展开更多
Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicate...Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.展开更多
Firstly,we obtain a Cauchy integral formula for inframonogenic functions which are solutions to the sandwich equation DfD=0 in the framework of parameter-depending Cliffordtype algebras.Secondly,the properities relati...Firstly,we obtain a Cauchy integral formula for inframonogenic functions which are solutions to the sandwich equation DfD=0 in the framework of parameter-depending Cliffordtype algebras.Secondly,the properities relating to Cauchy integral operators are discussed.Finally,the decompositions of the inframonogenic function are given.展开更多
摘要Here we complete our work on the asymptotics of Hankel determinants studying the case wherein the entries are “ultrarapidly”-varying functions in the sense that their logarithms are rapidly varying. Moreover, the last results in the paper highlight analogies between algebraic identities for Hankelians with special entries and asymptotic relations valid for large classes of entries.
基金supported by the NSF of China(11071144,11171187,11222110 and 71671104)Shandong Province(BS2011SF010,JQ201202)+4 种基金SRF for ROCS(SEM)Program for New Century Excellent Talents in University(NCET-12-0331)111 Project(B12023)the Ministry of Education of Humanities and Social Science Project(16YJA910003)Incubation Group Project of Financial Statistics and Risk Management of SDUFE
摘要We establish a new type of backward stochastic differential equations(BSDEs)connected with stochastic differential games(SDGs), namely, BSDEs strongly coupled with the lower and the upper value functions of SDGs, where the lower and the upper value functions are defined through this BSDE. The existence and the uniqueness theorem and comparison theorem are proved for such equations with the help of an iteration method. We also show that the lower and the upper value functions satisfy the dynamic programming principle. Moreover, we study the associated Hamilton-Jacobi-Bellman-Isaacs(HJB-Isaacs)equations, which are nonlocal, and strongly coupled with the lower and the upper value functions. Using a new method, we characterize the pair(W, U) consisting of the lower and the upper value functions as the unique viscosity solution of our nonlocal HJB-Isaacs equation. Furthermore, the game has a value under the Isaacs’ condition.
摘要Motivated by a general theory of finite asymptotic expansions in the real domain for functions f of one real variable, a theory developed in a previous series of papers, we present a detailed survey on the classes of higher-order asymptotically-varying functions where “asymptotically” stands for one of the adverbs “regularly, smoothly, rapidly, exponentially”. For order 1 the theory of regularly-varying functions (with a minimum of regularity such as measurability) is well established and well developed whereas for higher orders involving differentiable functions we encounter different approaches in the literature not linked together, and the cases of rapid or exponential variation, even of order 1, are not systrematically treated. In this semi-expository paper we systematize much scattered matter concerning the pertinent theory of such classes of functions hopefully being of help to those who need these results for various applications. The present Part I contains the higher-order theory for regular, smooth and rapid variation.
摘要In this second part, we thoroughly examine the types of higher-order asymptotic variation of a function obtained by all possible basic algebraic operations on higher-order varying functions. The pertinent proofs are somewhat demanding except when all the involved functions are regularly varying. Next, we give an exposition of three types of exponential variation with an exhaustive list of various asymptotic functional equations satisfied by these functions and detailed results concerning operations on them. Simple applications to integrals of a product and asymptotic behavior of sums are given. The paper concludes with applications of higher-order regular, rapid or exponential variation to asymptotic expansions for an expression of type f(x+r(x)).
摘要BACKGROUND Schizophrenia presents complex challenges in older patients due to cognitive and social decline.Existing drug treatments offer limited benefits and pose risks,while aerobic exercise shows promise as a noninvasive intervention whose impact remains underexplored.AIM To investigate the effects of aerobic exercise on cognitive and social function in older patients with schizophrenia.METHODS A retrospective study was conducted in 158 older patients with schizophrenia treated at The First Affiliated Hospital of Chongqing Medical and Pharmaceutical College(June 2023 and December 2024).The patients were divided into an observation group(n=86),which received 3 months of aerobic rehabilitation alongside routine treatment,and a control group(n=72),which received routine treatment alone.Cognitive function was assessed using the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery,social function using the Inpatient Psychiatric Rehabilitation Outcome Scale(IPROS),and psychotic symptoms using the Positive and Negative Syndrome Scale.RESULTS Post-treatment,Positive and Negative Syndrome Scale total scores were lower in the observation group than in the controls(P<0.001),with significant improvements in positive,negative,and general symptoms.Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery domain scores were improved in processing speed,working memory,verbal/visual learning,and executive function(all P<0.05).IPROS total scores were decreased(P<0.001),indicating better social functioning.Longer exercise duration correlated with greater cognitive gains and lower social function deficits.Body mass index declined(P<0.001),and adverse events were mild and transient(9.3%).Multivariate linear regression confirmed that aerobic exercise was independently associated with a significant reduction in IPROS scores(Adjustedβ=-4.57,95%confidence intervals:-6.08 to-3.05,P<0.001).CONCLUSION Aerobic exercise effectively improves cognitive function,social function,and psychotic symptoms in older patients with schizophrenia,is safe,and serves as a valuable adjunctive intervention.
基金supported by the National Key R&D Program of China(Grant No.2022YFB2602900)the National Natural Science Foundation of China(Grant No.52178405)the Project of Science and Technology Research and Development Program of China State Railway Group Co.,Ltd.(Grant No.K2022G038).
摘要Turnout irregularity significantly affects the stochastic vibration behavior of vehicle-turnout structures.This study proposes a fitting formula for the turnout irregularity spectrum and develops a turnout irregularity full information expression model(TIFIEM)using a stochastic harmonic function.The model is applied to vehicle-turnout structure stochastic vibration and reliability analysis.Findings suggest that the Hamming window method,with a window length of 4096 points,is optimal for estimating the turnout irregularity spectrum.It is recommended to fit the power spectral density(PSD)using a 5th-order polynomial for better accuracy.The TIFIEM effectively addresses randomness in amplitude,frequency,and phase.An analysis of 250 irregularity samples is sufficient for the desired accuracy.Additionally,the PSD amplitude at various frequency points follows a Chi-square distribution with 2°of freedom.Regions 3-7 m from the tip of the switch rail on the straight switch rail and 53-54 m on the point rail are most susceptible to wear.When the vehicle passes through the turnout at 300 km/h,the reliability of vehicle-turnout structures at the crossing panel decreases to 95.8%.
基金supported by the NSFC(11561001)the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(NJYT18-A14)+4 种基金the NSF of Inner Mongolia(2022MS01004,2020MS01011)the Higher School Foundation of Inner Mongolia(NJZY20200)the Program for Key Laboratory Construction of Chifeng University(CFXYZD202004)the Research and Innovation Team of Complex Analysis and Nonlinear Dynamic Systems of Chifeng University(cfxykycxtd202005)the Youth Science Foundation of Chifeng University(cfxyqn202133).
摘要In recent years,researchers have extensively investigated the Hankel determinant,which consists of coefficients appearing in a holomorphic function’s Taylor-Maclaurin series.Hankel matrices are widely used in Markov processes,non-stationary signals,and other mathematical disciplines.The aim of the current research article is to first improve the bounds of coefficient-related problems by employing the well-known Carathéodory function.The problems that we are going to improve were obtained by Tang et al.The sharp estimates of the most difficult problem of geometric function theory known as the third-order Hankel determinant are also contributed here.Zalcman and Fekete-Szegöinequalities are also studied here for the defined family of holomorphic functions.
基金supported by the National Natural Science Foundation of China(82303478,82201030,823B2018)the Natural Science Foundation of Sichuan Province(2024NSFSC1184)West China Hospital of Stomatology(RCDWJS2026—10)。
摘要Over the past two decades,UFMylation,a crucial post-translational modification mediated by a canonical E1—E2—E3 enzymatic cascade and specific deUFMylation enzymes,has emerged as an essential component for maintaining cellular homeostasis.It plays indispensable regulatory roles in fundamental processes,including protein quality control,genome stability maintenance,cell fate determination,and modulation of immune responses.These functions are achieved by precisely regulating key protein substrates and their associated signaling pathways.Consequently,dysregulation of these UFMylationregulated processes directly drives the pathogenesis of a broad spectrum of human diseases.This review summarizes current insights into the UFMylation machinery,its enzymatic cascade,and related fundamental cellular processes.We systematically explain the molecular mechanisms by which UFMylation regulates cellular functions and discuss how its dysfunction contributes to the pathogenesis of a wide range of human diseases,including cancers,skeletal dysplasias,hematological disorders,nervous system disorders,metabolic-associated liver disease,silicosis,and cardiovascular diseases.Deciphering the precise molecular mechanisms underlying these pathologies is crucial for identifying diagnostic biomarkers and developing targeted therapeutic strategies.Furthermore,we highlight future perspectives on targeting the UFMylation system for therapeutic intervention in these diseases.
基金supported by CARS(CARS-21),the CAMS Innovation Fund for Medical Sciences(2021-I2M-1-032)the Science and Technology Department of Xizang(XZ202401ZY0020)+2 种基金the Science and Technology Department of Sichuan Province(2023YFH0044,2023YFH0018)the Sichuan Province Science Foundation for Distinguished Young Scholars(2022JDJQ0006)the Doctoral Fund of Southwest University of Science and Technology(19ZX7117,21ZX7116).
摘要Saikosaponins are the major pharmacologically active components in Bupleurum genus and exhibit significant application potential in multiple fields such as immune regulation and anti-tumor activity.To elucidate the biosynthetic pathway of saikosaponins,we identified two cytochrome P450 monooxygenases,CYP716A41 and CYP716Y4,in Bupleurum chinense.These enzymes catalyze the C-28 oxidation and C-16 hydroxylation of oleanane-type triterpene skeletons,respectively.The catalytic efficiency of CYP716A41 from a southern B.chinense variety was significantly higher than that from a northern variety.Molecular docking and mutagenesis experiments revealed that amino acid residues at sites 9 and 35 may contribute to this difference in catalytic efficiency.Additionally,under cold stress,the expression levels of both CYP450 genes and the saikosaponin contents in the leaves of southern varieties were significantly higher compared to those in northern varieties.The variation in the catalytic efficiency of CYP716A41 and the differential expression of the two CYP450 genes under cold stress during winter are associated with the differences in saikosaponin biosynthesis in the leaves of southern and northern B.chinense varieties.This is consistent with the distinct medicinal usage practices observed between southern and northern China.
摘要Accurate classification of brain tumors from medical images is essential for enabling timely diagnosis and effective treatment.This study aimed to develop an innovative method for the diagnosis of brain tumors through a Fuzzy Richards Functions-based Ensemble Network(FRE-Net).The parameters of the Richards function are optimized through Grid Search(GS)for selecting an optimal set of parameters.Our proposed method integrates three well-established pre-trained Convolutional Neural Networks(CNNs):MobileNetV1,MobileNetV2,ResNet50V2.To increase the robustness of these models,we incorporate a novel Lightweight Multiscale with Squeeze and Excitation(LiteMSSE)Block,which improves performance by enhancing multi-scale feature extraction and enabling the network to capture more detailed spatial information for focusing on the most relevant features to improve overall diagnostic performance.Additionally,probabilities from the individual models are aggregated using a Fuzzy Richards Functions approach,which reduces the error between observed and ground truth data,further enhancing detection accuracy.The key innovation of this study lies in the design of novel LiteMSSE Block and use of Fuzzy Richard Function,which together enhance multi-scale feature extraction and combines diverse model predictions intelligently.The proposed FRE-Net method achieves an impressive accuracy of 98.47%on the four-class Kaggle dataset and 99.00%on the BR35H dataset by highlighting its potential as a powerful tool for diagnosis of brain MRI more precisely.Through extensive evaluations,we determine that our proposed ensemble method outperforms individual backbone models and existing methods.
基金supported by the Agence Nationale de la Recherche(ANR)through the project KLOTHOA(ANR-18-CE14-0024-01)the“Programmes et Equipements Prioritaires de Recherche(PEPR)”-CARN project(ANR-22-PEBI-0004)Lucie Danet was a recipient of a fellowship from the French Ministry of Research.
摘要Mitochondria are essential organelles primarily described for their vital role in producing energy through oxidative phosphorylation(OxPhos).Due to the hypoxic environment of chondrocytes and their heavy reliance on glycolysis,mitochondrial functions have long been considered of minimal relevance in these cells.However,as major suppliers of energy through the ATP they produce by OxPhos,mitochondria help to regulate the balance between anabolism and catabolism.In osteoarthritis(OA),the most prevalent joint disease,this balance is dysregulated.In addition,correlations between metabolic disorders and the risk of developing OA are also increasingly studied.In this context,mitochondrial dysfunctions in OA chondrocytes are emerging as a relevant area to propose efficient,yet unavailable,disease-modifying OA drugs(DMOADs).This narrative review examines the underlying mechanisms by which the mitochondrial functions become dysregulated in chondrocytes during OA.Drawing on up-to-date literature,it highlights how both structural and functional alterations of mitochondria contribute to OA pathology in chondrocytes.Finally,this review discusses the potential of mitochondria-targeted therapeutic strategies for OA,framed within a conceptual“repair or replace”approach.
基金supported by the University of Macao Development Foundation(UMDF)(MYRG-GRG2024-00290-FST-UMDF,MYRG-GRG2025-00250-FST).
摘要This work begins by introducing the groundbreaking concept of log-p-analytic functions.Following this introduction,we proceed to delineate four distinct formulations of Landau-type theorems,specifically crafted for the domain of poly-analytic functions.Among these,two theorems are distinguished by their exactitude,and a third theorem offers a refinement to the existing work of Abdulhadi and Hajj.Concluding the paper,we present four specialized versions of Landau-type theorems applicable to a subset of bounded log-p-analytic functions,resulting in the derivation of two precise outcomes.
基金supported by the Chongqing Natural Science Foundation(grant Nos.cstc2021jcyjmsxm X0553,CSTB2025NSCQ-GPX1306)the Science and Technology Research Program of the Chongqing Municipal Education Commission(grant No.KJQN202200633)+2 种基金support from the National Natural Science Foundation of China(grants No.12403008)the Beijing Academy of Science and Technology Budding Talent Program(grants No.24CE-BGS-18)The Young Data Scientist Program of the China National Astronomical Data Center(grants No.NADC2024YDS-03)。
摘要We study the dependence of conditional stellar mass functions(CSMFs)on the cosmic-web environment using the TNG50 cosmological hydrodynamical simulation at z=0.By classifying host haloes into voids,sheets,filaments,and knots,we examine satellite and central galaxy populations over the host-mass range resolved in TNG50.Satellite CSMFs show systematic environment-dependent variations,with the clearest differences emerging at the faint end.In a representative low-mass host regime(log10(M200c/[M⊙h-1])∈[11.5,12.0]),the satellite faint-end slope is shallower in filaments(α■-0.38)than in sheets(α■-0.48),suggestive of a balance between anisotropic supply along filaments and subsequent environmental processing.For central galaxies,we observe a crossover-like trend in dwarf-scale hosts(log10(M200c/[M⊙h-1])∈[11.0,11.5]):knots and filaments exhibit a more extended high-M* tail,whereas voids and sheets host a higher fraction of low-mass centrals.Overall,our results suggest that the cosmic web environment imprints secondary,mass-dependent modulations on galaxy stellar mass distributions beyond halo mass alone,most clearly for faint satellites.
基金supported by the National Natural Science Foundation of China(Grant nos.42476264,41976224).
摘要Small RNAs(sRNAs)are important non-coding RNAs that usually play crucial roles in gene expression at the post-transcriptional level.The sRNAs have mostly been investigated in model microorganisms such as Escherichia coli and some pathogens.Nevertheless,microbial sRNAs from extreme environments such as the polar regions and deep sea have recently been discovered and analyzed for their unique roles in stress response,metabolic regulation and adaptation to extreme environments.These sRNAs fine-tune gene expression during oxidative and radiation stress,and modulate temperature and osmotic pressure responses.Representative sRNAs and their functions in thermophilic,psychrophilic,halophilic and radiation-tolerant bacteria are summarized in this review.Despite challenges in sample collection,RNA isolation,and functional annotation,the study of sRNAs in extreme environments provides opportunities for discovering novel regulatory mechanisms,applying them to biotechnology,and advancing our understanding of evolutionary adaptations.Looking ahead,high-throughput sequencing,synthetic biology,and multi-omics integration will bring new breakthroughs in discovering novel sRNAs and their functions and regulatory mechanisms.Such advancements are poised to enable comprehensive characterization of sRNA-mediated regulatory networks in extremophiles and unlock their biotechnological potential through mechanism-driven applications.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant number:82171965.
摘要Designing appropriate loss functions is critical to the success of supervised learning models.However,most conventional losses are fixed and manually designed,making them suboptimal for diverse and dynamic learning scenarios.In this work,we propose an Adaptive Meta-Loss Network(Adaptive-MLN)that learns to generate taskagnostic loss functions tailored to evolving classification problems.Unlike traditional methods that rely on static objectives,Adaptive-MLN treats the loss function itself as a trainable component,parameterized by a shallow neural network.To enable flexible,gradient-free optimization,we introduce a hybrid evolutionary approach that combines GeneticAlgorithms(GA)for global exploration and Evolution Strategies(ES)for local refinement.This co-evolutionary process dynamically adjusts the loss landscape,improvingmodel generalization without relying on analytic gradients or handcrafted heuristics.Experimental evaluations on synthetic tasks and the CIFAR-10 andMNIST datasets demonstrate that our approach consistently outperforms standard losses such as Cross-Entropy and Mean Squared Error in terms of accuracy,convergence,and adaptability.
基金supported by the National Natural Science Foundation of China(No.42174071)the National Key Research and Development Program of China(No.2022YFF0800601)Sichuan Key Research and Development Program(No.2023YFS0433)。
摘要This paper proposes a fast quality control strategy for P-wave receiver functions based on AlexNet and wiggle plots.Receiver functions are essential tools in seismology,particularly for analyzing seismic wave propagation and subsurface structures,such as the crust and upper mantle.However,the quality control of receiver functions is often a tedious,time-consuming process.In this study,we transform the time series classification problem of receiver function quality control problem into an image classification task by plotting receiver functions as wiggle diagrams and using the deep learning model AlexNet for binary classification to distinguish between“good”and“bad”receiver functions.The model achieved an accuracy of 92.55%on the testing set and demonstrated strong generalization performance with an accuracy of 89.23%on receiver functions of another seismic network(Sichuan Provincial Permanent Seismic Network).While maintaining strong performance,the model is capable of processing approximately 32 receiver function wiggle plots per second on an NVIDIA GeForce RTX 4050.The results show that the proposed feature mapping strategy significantly improves the efficiency and accuracy of receiver function quality control,making it a valuable tool for practical applications.Future work will focus on expanding the dataset and optimizing model performance for broader seismic data applications.
基金funded by the National Natural Science Foundation of China,grant number 62302519.
摘要Stream ciphers are simple to implement and fast at encrypting and decrypting data,making them very important in information security.Boolean functions are a core part of stream ciphers.However,their mainstream hardware implementations face two main problems,including wasted area resources and excessive critical path delay.These issues limit the energy efficiency and integration level of stream cipher chips.To address these problems,this paper proposes an energy-efficient design method for a 64-bit Boolean function reconfigurable operation unit(BFROU),aiming to improve the computational efficiency of Boolean functions in stream ciphers.To optimize the design of BFROU,this paper takes the NPN equivalence theory as a guide.First,customized designs at the transistor level were performed for both 2-and 3-variable RM logic units(denoted as TRM).On this basis,this paper uses the port sharing strategy to further optimize the design of 4-to-6-variable TRM logic units and construct a multi-variable TRM process library.Then,by combining multi-variable TRM logic units with the mathematical definition of Boolean functions,this paper proposes a theoretical model of BFROU.Based on this model and combined with the statistical analysis results of Boolean functions,the optimal TRM unit configuration is determined,and the overall optimization of the 64-bit BFROU is finally completed.Experimental results show that when TRM-3 and TRM-4 units are mixed as the first-level operation module of BFROU,its area-delay product(ADP)reaches the minimum.The 64-bit BFROU unit implemented according to this scheme has an actual measured area of 137.28μm2 and a critical path delay of 0.278 ns under the SMIC 40 nm typical process corner.This unit supports Boolean function operations with up to 64 variables,and 94.4%of the functions can complete mapping within 2 iterations.Compared with existing schemes such as look-up table(LUT)architecture and And-Inverter Cone(AIC)array,the BFROU proposed in this paper has obvious advantages in area,delay,ADP and number of iterations,providing effective hardware support for the design of high-energy-efficiency stream cipher chips.
基金Project supported by the National Natural Science Foundation of China(Grant No.12204128)。
摘要This study investigates the effects of ocean boundaries on modal shapes in very-low-frequency(VLF,1–10 Hz)sound propagation through the deep ocean.Utilizing a normal mode solution formulated in terms of parabolic cylinder functions(PCF),we demonstrate that boundary interactions induce a phase change reduction below-πat frequencies of several hertz.This reduction,in turn,forces a key transition in the solution,shifting the order of the PCF from integer to non-integer values.Analysis of the characteristic shape of the PCF versus its order reveals that these boundary-influenced modes exhibit an energy shift toward deeper regions and a weakened axial convergence of the underwater sound field.
基金Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。
摘要Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.
基金Supported by the Key Development Fund of Hebei Normal University(L2024ZD08)the Natural Science Foundation of Hebei Province(A2023205006)+1 种基金the National Natural Science Foundation of China(11871191)the Hebei Chemical and Pharmaceutical Vocational and Technical College Doctoral Research Project(YB2026014).
摘要Firstly,we obtain a Cauchy integral formula for inframonogenic functions which are solutions to the sandwich equation DfD=0 in the framework of parameter-depending Cliffordtype algebras.Secondly,the properities relating to Cauchy integral operators are discussed.Finally,the decompositions of the inframonogenic function are given.