In this paper, we define an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, desc...In this paper, we define an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. The key is to start with a non-elementary integral function, differentiating and inverting, and then define a set of functions. Differentiating these functions twice give second-order nonlinear ODEs that have the defined set of functions as solutions.展开更多
In this paper, we define a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We will also define a group of solutions x(t) that are ...In this paper, we define a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We will also define a group of solutions x(t) that are equal to the amplitude. This is a generalized amplitude function. We are using Abel’s methods, described by Armitage and Eberlein. And finally, we define an exponential function whose exponent is the product of a complex number and the upper limit of integration in a non-elementary integral that can be arbitrary. At least three groups of non-elementary functions are special cases of this complex function.展开更多
Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the m...Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.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
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
In this paper,we investigate the uniqueness of meromorphic functions and their derivatives in the unit disc and consider the relations between the Borel points and the shared-values of meromorphic functions in an angu...In this paper,we investigate the uniqueness of meromorphic functions and their derivatives in the unit disc and consider the relations between the Borel points and the shared-values of meromorphic functions in an angular domain by Nevanlinna value distribution theory.An admissible meromorphic function with orde or precise order has Borel point and shares IM common values with its derivative in an angular domain of the unit disc,then the meromorphic function and its derivative are unique.The obtained results improve and generalize some existing results and enrich the uniqueness theory of meromorphic functions.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
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
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
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
Zinc,an essential trace element,plays a pivotal role in maintaining animal health and physiological functions.This review comprehensively examines zinc metabolism—including absorption dynamics across species(poultry,...Zinc,an essential trace element,plays a pivotal role in maintaining animal health and physiological functions.This review comprehensively examines zinc metabolism—including absorption dynamics across species(poultry,ruminants,and non-ruminants),transport mechanisms,storage in tissues,e.g.,the liver,and excretion pathways—and its multifaceted effects on animal health.Zinc critically regulates aspects of growth and development,particularly bone formation,as its deficiency induces skeletal deformities in young animals.It modulates immune function through zinc finger proteins,influencing immune organ integrity,lymphocyte proliferation,and cytokine expression.Reproductive performance is significantly affected by zinc,with its deficiency causing impaired spermatogenesis;delayed sexual maturity in males;and reduced litter size,embryonic survival,and placental function in females.At the molecular level,zinc regulates the activity of enzymes(e.g.,SOD),signaling pathways(MAPK,NF-κB),and transcription factors(MTF-1,Sp1)to maintain homeostasis.Both zinc deficiency(due to dietary insufficiency,malabsorption,or physiological stress)and zinc excess(from environmental pollution or feed oversupplementation)adversely affect health,disrupting mineral balance,enzyme function,and gut microbiota.In animal production,inorganic(zinc oxide,zinc sulfate)and organic(zinc methionine)sources of zinc increase growth,immunity,and productivity,although sustainable strategies are needed to mitigate environmental risks.Future research should focus on novel zinc formulations,precision nutrition,and interactions with gut microbiota to optimize livestock health and sustainable husbandry.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
In this paper, we define some non-elementary amplitude functions that are giving solutions to some well-known second-order nonlinear ODEs and the Lorenz equations, but not the chaos case. We are giving the solutions a...In this paper, we define some non-elementary amplitude functions that are giving solutions to some well-known second-order nonlinear ODEs and the Lorenz equations, but not the chaos case. We are giving the solutions a name, a symbol and putting them into a group of functions and into the context of other functions. These solutions are equal to the amplitude, or upper limit of integration in a non-elementary integral that can be arbitrary. In order to define solutions to some short second-order nonlinear ODEs, we will make an extension to the general amplitude function. The only disadvantage is that the first derivative to these solutions contains an integral that disappear at the second derivation. We will also do a second extension: the two-integral amplitude function. With this extension we have the solution to a system of ODEs having a very strange behavior. Using the extended amplitude functions, we can define solutions to many short second-order nonlinear ODEs.展开更多
In this paper, we define some new sets of non-elementary functions in a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We are usi...In this paper, we define some new sets of non-elementary functions in a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. The key is to start with a non-elementary integral function, differentiating and inverting, and then define a set of three functions that belong together. Differentiating these functions twice gives second-order nonlinear ODEs that have the defined set of functions as solutions. We will study some of the second-order nonlinear ODEs, especially those that exhibit limit cycles. Using the methods described in this paper, it is possible to define many other sets of non-elementary functions that are giving solutions to some second-order nonlinear autonomous ODEs.展开更多
In this paper, we define four new examples of the non-elementary expo-elliptic functions. This is an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elem...In this paper, we define four new examples of the non-elementary expo-elliptic functions. This is an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. We will study some of the second-order nonlinear ODEs, especially those that exhibit limit cycles, and systems of nonlinear ODEs that these functions are giving solutions to.展开更多
The non-elementary integrals involving elementary exponential, hyperbolic and trigonometric functions, <img src="Edit_699140d3-f569-463e-b835-7ccdab822717.png" width="290" height="22" ...The non-elementary integrals involving elementary exponential, hyperbolic and trigonometric functions, <img src="Edit_699140d3-f569-463e-b835-7ccdab822717.png" width="290" height="22" alt="" /><img src="Edit_bdd10470-9b63-4b2d-9cec-636969547ca5.png" width="90" height="22" alt="" /><span style="white-space:normal;">and <img src="Edit_e9cd6876-e2b8-45cf-ba17-391f054679b4.png" width="90" height="21" alt="" /></span>where <span style="white-space:nowrap;"><em>α</em>,<span style="white-space:nowrap;"><em>η</em></span><em></em></span> and <span style="white-space:nowrap;"><em>β</em></span> are real or complex constants are evaluated in terms of the confluent hypergeometric function <sub>1</sub><em>F</em><sub>1</sub> and the hypergeometric function <sub>1</sub><em>F</em><sub>2</sub>. The hyperbolic and Euler identities are used to derive some identities involving exponential, hyperbolic, trigonometric functions and the hypergeometric functions <sub style="white-space:normal;">1</sub><em style="white-space:normal;">F</em><sub style="white-space:normal;">1</sub> and <sub style="white-space:normal;">1</sub><em style="white-space:normal;">F</em><sub style="white-space:normal;">2</sub>. Having evaluated, these non-elementary integrals, some new probability measures generalizing the gamma-type and Gaussian distributions are also obtained. The obtained generalized probability distributions may, for example, allow to perform better statistical tests than those already known (e.g. chi-square (<span style="white-space:nowrap;"><em>x</em><sup>2</sup></span>) statistical tests and other statistical tests constructed based on the central limit theorem (CLT)), while avoiding the use of computational approximations (or methods) which are in general expensive and associated with numerical errors.展开更多
Accurately revealing the spatial heterogeneity in the trade-offs and synergies of land use functions(LUFs)and their driving factors is imperative for advancing sustainable land utilization and optimizing land use plan...Accurately revealing the spatial heterogeneity in the trade-offs and synergies of land use functions(LUFs)and their driving factors is imperative for advancing sustainable land utilization and optimizing land use planning.This is especially critical for ecologically vulnerable inland river basins in arid regions.However,existing methods struggle to effectively capture complex nonlinear interactions among environmental factors and their multifaceted relationships with trade-offs and synergies of LUFs,especially for the inland river basins in arid regions.Consequently,this study focused on the middle reaches of the Heihe River Basin(MHRB),an arid inland river basin in northwestern China.Using land use,socioeconomic,meteorological,and hydrological data from 2000 to 2020,we analyzed the spatiotemporal patterns of LUFs and their trade-off and synergy relationships from the perspective of production,living,ecological functions.Additionally,we employed an integrated Extreme Gradient Boosting(XGBoost)-SHapley Additive exPlanations(SHAP)framework to investigate the environmental factors influencing the spatial heterogeneity in the trade-offs and synergies of LUFs.Our findings reveal that from 2000 to 2020,the production,living,and ecological functions of land use within the MHRB exhibited an increasing trend,demonstrating a distinct spatial pattern of''high in the southwest and low in the northeast''.Significant spatial heterogeneity defined the trade-off and synergistic relationships,with trade-offs dominating human activity-intensive oasis areas,while synergies prevailed in other areas.During the study period,synergistic relationships between production and living functions and between production and ecological functions were relatively robust,whereas synergies in living-ecological functions remained weaker.Natural factors(digital elevation model(DEM),annual mean temperature,Normalized Difference Vegetation Index(NDVI),and annual precipitation)emerged as the primary factors driving the trade-offs and synergies of LUFs,followed by socioeconomic factors(population density,Gross Domestic Product(GDP),and land use intensity),while distance factors(distance to water bodies,distance to residential areas,and distance to roads)exerted minimal influence.Notably,the interactions among NDVI,annual mean temperature,DEM,and land use intensity exerted the most substantial impacts on the relationships among LUFs.This study provides novel perspectives and methodologies for unraveling the mechanisms underlying the spatial heterogeneity in the trade-offs and synergies of LUFs,offering scientific insights to inform regional land use planning and sustainable natural resource management in inland river basins in arid regions.展开更多
Spatial memory is crucial for survival within external surroundings and wild environments.The hippocampus,a critical hub for spatial learning and memory formation,has received extensive investigations on how neuromodu...Spatial memory is crucial for survival within external surroundings and wild environments.The hippocampus,a critical hub for spatial learning and memory formation,has received extensive investigations on how neuromodulators shape its functions(Teixeira et al.,2018;Zhang et al.,2024).However,the landscape of neuromodulations in the hippocampal system remains poorly understood because most studies focus on classical monoamine neuromodulators,such as acetylcholine,serotonin,dopamine,and noradrenaline.The neuropeptides,comprising the most abundant neuromodulators in the central nervous system,play a pivotal role in neural information processing in the hippocampal system.Cholecystokinin(CCK),one of the most abundant neuropeptides,has been implicated in regulating various physiological and neurobiological statuses(Chen et al.,2019).CCK-A receptor(CCK-AR)and CCK-B receptors(CCK-BR)are two key receptors mediating the biological functions of CCK,both of which belong to class-A sevenfold transmembrane G protein-coupled receptors(Nishimura et al.,2015).CCK-AR preferentially reacts to sulfated CCK,whereas CCK-BR binds both CCK and gastrin with similar affinities(Ding et al.,2022).The expression patterns of CCK-AR and CCK-BR are distinct,implying that CCK has various functions in target regions.For instance,CCK-AR is widely expressed in the GI and brain subregions and is hence implicated in the control of digestive function and satiety regulation.Conversely,CCK-BR is abundantly and widely distributed in the central nervous system,which majorly regulates anxiety,learning,and memory(Ding et al.,2022).However,the roles of endogenous CCK and CCK receptors in regulating hippocampal function at electrophysiological and behavioral levels have received less attention.展开更多
Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively ...Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively studied over the past few decades,there has been limited research on the construction of almost optimal five-valued spectra vectorial Boolean functions.In this paper,we present a construction method for even-variable 2-output almost optimal five-valued spectra balanced Boolean functions,whose Walsh spectra values belong to the set{0,±2^(n/2),±2^(n/2+1)},at the same time,we discuss the existence of sufficient conditions in the construction.Additionally,this paper presents a novel construction method for balanced single-output Boolean functions with even variables featuring a special five-valued spectral structure,whose Walsh spectra values are constrained to the set{0,±2^(n/2),±3·2^(n/2)}.These functions provide new canonical examples for the study of Boolean function spectral theory.展开更多
The Red Sea-Gulf of Suez-Cairo-Alexandria Clysmic-Trend in northern Egypt is the main earthquake zone in the country,with a moderate-to-high seismic hazard and a history of significant earthquakes caused by rifting an...The Red Sea-Gulf of Suez-Cairo-Alexandria Clysmic-Trend in northern Egypt is the main earthquake zone in the country,with a moderate-to-high seismic hazard and a history of significant earthquakes caused by rifting and active faulting.To improve our understanding of the tectonic and seismic processes in this area,more comprehensive imaging of the crustal structure is required.This can be achieved by increasing the number of receiver functions(RFs)recorded by the seismic stations in northern Egypt and the southeastern Mediterranean.Data handling and processing should also be automated to increase process efficiency.In this study,we developed a capsule neural network for automated selection of RFs.The model was trained on a dataset containing RFs(both selected and unselected)from five broadband stations in northern Egypt.Stations SLM,SIWA,KOT,NBNS,and NKL are located in the unstable shelf region of Egypt,where limited knowledge of the deep crustal structure is available.The proposed capsule neural network achieved an average precision of 80%on the test set.The automated selection of RFs using a capsule neural network has the potential to significantly improve the efficiency and accuracy of RF analysis,as demonstrated by the stacking test.This could lead to a better understanding of crustal structure and tectonic processes in northern Egypt and the southeastern Mediterranean.展开更多
文摘In this paper, we define an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. The key is to start with a non-elementary integral function, differentiating and inverting, and then define a set of functions. Differentiating these functions twice give second-order nonlinear ODEs that have the defined set of functions as solutions.
文摘In this paper, we define a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We will also define a group of solutions x(t) that are equal to the amplitude. This is a generalized amplitude function. We are using Abel’s methods, described by Armitage and Eberlein. And finally, we define an exponential function whose exponent is the product of a complex number and the upper limit of integration in a non-elementary integral that can be arbitrary. At least three groups of non-elementary functions are special cases of this complex function.
基金Supported by the National Basic Research Program of China(2012CB025904)Zhengzhou Shengda University of Economics,Business and Management(SD-YB2025085)。
文摘Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.
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).
文摘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.
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).
文摘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.
文摘In this paper,we investigate the uniqueness of meromorphic functions and their derivatives in the unit disc and consider the relations between the Borel points and the shared-values of meromorphic functions in an angular domain by Nevanlinna value distribution theory.An admissible meromorphic function with orde or precise order has Borel point and shares IM common values with its derivative in an angular domain of the unit disc,then the meromorphic function and its derivative are unique.The obtained results improve and generalize some existing results and enrich the uniqueness theory of meromorphic functions.
基金supported by the National Natural Science Foundation of China(Grant nos.42476264,41976224).
文摘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Project supported by the National Natural Science Foundation of China(Grant No.12204128)。
文摘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)。
文摘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supported by the National Natural Science Foundation of China(NSFC)under Grant number:82171965.
文摘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 Natural Science Foundation of Heilongjiang Province(LH2023C028)。
文摘Zinc,an essential trace element,plays a pivotal role in maintaining animal health and physiological functions.This review comprehensively examines zinc metabolism—including absorption dynamics across species(poultry,ruminants,and non-ruminants),transport mechanisms,storage in tissues,e.g.,the liver,and excretion pathways—and its multifaceted effects on animal health.Zinc critically regulates aspects of growth and development,particularly bone formation,as its deficiency induces skeletal deformities in young animals.It modulates immune function through zinc finger proteins,influencing immune organ integrity,lymphocyte proliferation,and cytokine expression.Reproductive performance is significantly affected by zinc,with its deficiency causing impaired spermatogenesis;delayed sexual maturity in males;and reduced litter size,embryonic survival,and placental function in females.At the molecular level,zinc regulates the activity of enzymes(e.g.,SOD),signaling pathways(MAPK,NF-κB),and transcription factors(MTF-1,Sp1)to maintain homeostasis.Both zinc deficiency(due to dietary insufficiency,malabsorption,or physiological stress)and zinc excess(from environmental pollution or feed oversupplementation)adversely affect health,disrupting mineral balance,enzyme function,and gut microbiota.In animal production,inorganic(zinc oxide,zinc sulfate)and organic(zinc methionine)sources of zinc increase growth,immunity,and productivity,although sustainable strategies are needed to mitigate environmental risks.Future research should focus on novel zinc formulations,precision nutrition,and interactions with gut microbiota to optimize livestock health and sustainable husbandry.
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)。
文摘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.
文摘In this paper, we define some non-elementary amplitude functions that are giving solutions to some well-known second-order nonlinear ODEs and the Lorenz equations, but not the chaos case. We are giving the solutions a name, a symbol and putting them into a group of functions and into the context of other functions. These solutions are equal to the amplitude, or upper limit of integration in a non-elementary integral that can be arbitrary. In order to define solutions to some short second-order nonlinear ODEs, we will make an extension to the general amplitude function. The only disadvantage is that the first derivative to these solutions contains an integral that disappear at the second derivation. We will also do a second extension: the two-integral amplitude function. With this extension we have the solution to a system of ODEs having a very strange behavior. Using the extended amplitude functions, we can define solutions to many short second-order nonlinear ODEs.
文摘In this paper, we define some new sets of non-elementary functions in a group of solutions x(t) that are sine and cosine to the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. The key is to start with a non-elementary integral function, differentiating and inverting, and then define a set of three functions that belong together. Differentiating these functions twice gives second-order nonlinear ODEs that have the defined set of functions as solutions. We will study some of the second-order nonlinear ODEs, especially those that exhibit limit cycles. Using the methods described in this paper, it is possible to define many other sets of non-elementary functions that are giving solutions to some second-order nonlinear autonomous ODEs.
文摘In this paper, we define four new examples of the non-elementary expo-elliptic functions. This is an exponential function whose exponent is the product of a real number and the upper limit of integration in a non-elementary integral that can be arbitrary. We are using Abel’s methods, described by Armitage and Eberlein. We will study some of the second-order nonlinear ODEs, especially those that exhibit limit cycles, and systems of nonlinear ODEs that these functions are giving solutions to.
文摘The non-elementary integrals involving elementary exponential, hyperbolic and trigonometric functions, <img src="Edit_699140d3-f569-463e-b835-7ccdab822717.png" width="290" height="22" alt="" /><img src="Edit_bdd10470-9b63-4b2d-9cec-636969547ca5.png" width="90" height="22" alt="" /><span style="white-space:normal;">and <img src="Edit_e9cd6876-e2b8-45cf-ba17-391f054679b4.png" width="90" height="21" alt="" /></span>where <span style="white-space:nowrap;"><em>α</em>,<span style="white-space:nowrap;"><em>η</em></span><em></em></span> and <span style="white-space:nowrap;"><em>β</em></span> are real or complex constants are evaluated in terms of the confluent hypergeometric function <sub>1</sub><em>F</em><sub>1</sub> and the hypergeometric function <sub>1</sub><em>F</em><sub>2</sub>. The hyperbolic and Euler identities are used to derive some identities involving exponential, hyperbolic, trigonometric functions and the hypergeometric functions <sub style="white-space:normal;">1</sub><em style="white-space:normal;">F</em><sub style="white-space:normal;">1</sub> and <sub style="white-space:normal;">1</sub><em style="white-space:normal;">F</em><sub style="white-space:normal;">2</sub>. Having evaluated, these non-elementary integrals, some new probability measures generalizing the gamma-type and Gaussian distributions are also obtained. The obtained generalized probability distributions may, for example, allow to perform better statistical tests than those already known (e.g. chi-square (<span style="white-space:nowrap;"><em>x</em><sup>2</sup></span>) statistical tests and other statistical tests constructed based on the central limit theorem (CLT)), while avoiding the use of computational approximations (or methods) which are in general expensive and associated with numerical errors.
基金funded by the University Teachers Innovation Fund Project of Gansu Province(2025A-001)the Northwest Normal University Young Teachers'Scientific Research Ability Improvement Plan(NWNULKQN2024-20).
文摘Accurately revealing the spatial heterogeneity in the trade-offs and synergies of land use functions(LUFs)and their driving factors is imperative for advancing sustainable land utilization and optimizing land use planning.This is especially critical for ecologically vulnerable inland river basins in arid regions.However,existing methods struggle to effectively capture complex nonlinear interactions among environmental factors and their multifaceted relationships with trade-offs and synergies of LUFs,especially for the inland river basins in arid regions.Consequently,this study focused on the middle reaches of the Heihe River Basin(MHRB),an arid inland river basin in northwestern China.Using land use,socioeconomic,meteorological,and hydrological data from 2000 to 2020,we analyzed the spatiotemporal patterns of LUFs and their trade-off and synergy relationships from the perspective of production,living,ecological functions.Additionally,we employed an integrated Extreme Gradient Boosting(XGBoost)-SHapley Additive exPlanations(SHAP)framework to investigate the environmental factors influencing the spatial heterogeneity in the trade-offs and synergies of LUFs.Our findings reveal that from 2000 to 2020,the production,living,and ecological functions of land use within the MHRB exhibited an increasing trend,demonstrating a distinct spatial pattern of''high in the southwest and low in the northeast''.Significant spatial heterogeneity defined the trade-off and synergistic relationships,with trade-offs dominating human activity-intensive oasis areas,while synergies prevailed in other areas.During the study period,synergistic relationships between production and living functions and between production and ecological functions were relatively robust,whereas synergies in living-ecological functions remained weaker.Natural factors(digital elevation model(DEM),annual mean temperature,Normalized Difference Vegetation Index(NDVI),and annual precipitation)emerged as the primary factors driving the trade-offs and synergies of LUFs,followed by socioeconomic factors(population density,Gross Domestic Product(GDP),and land use intensity),while distance factors(distance to water bodies,distance to residential areas,and distance to roads)exerted minimal influence.Notably,the interactions among NDVI,annual mean temperature,DEM,and land use intensity exerted the most substantial impacts on the relationships among LUFs.This study provides novel perspectives and methodologies for unraveling the mechanisms underlying the spatial heterogeneity in the trade-offs and synergies of LUFs,offering scientific insights to inform regional land use planning and sustainable natural resource management in inland river basins in arid regions.
文摘Spatial memory is crucial for survival within external surroundings and wild environments.The hippocampus,a critical hub for spatial learning and memory formation,has received extensive investigations on how neuromodulators shape its functions(Teixeira et al.,2018;Zhang et al.,2024).However,the landscape of neuromodulations in the hippocampal system remains poorly understood because most studies focus on classical monoamine neuromodulators,such as acetylcholine,serotonin,dopamine,and noradrenaline.The neuropeptides,comprising the most abundant neuromodulators in the central nervous system,play a pivotal role in neural information processing in the hippocampal system.Cholecystokinin(CCK),one of the most abundant neuropeptides,has been implicated in regulating various physiological and neurobiological statuses(Chen et al.,2019).CCK-A receptor(CCK-AR)and CCK-B receptors(CCK-BR)are two key receptors mediating the biological functions of CCK,both of which belong to class-A sevenfold transmembrane G protein-coupled receptors(Nishimura et al.,2015).CCK-AR preferentially reacts to sulfated CCK,whereas CCK-BR binds both CCK and gastrin with similar affinities(Ding et al.,2022).The expression patterns of CCK-AR and CCK-BR are distinct,implying that CCK has various functions in target regions.For instance,CCK-AR is widely expressed in the GI and brain subregions and is hence implicated in the control of digestive function and satiety regulation.Conversely,CCK-BR is abundantly and widely distributed in the central nervous system,which majorly regulates anxiety,learning,and memory(Ding et al.,2022).However,the roles of endogenous CCK and CCK receptors in regulating hippocampal function at electrophysiological and behavioral levels have received less attention.
基金National Natural Science Foundation of China(62272360)。
文摘Five-valued Boolean functions play an important role in the design of symmetric cryptography.While the design and properties of single-output almost optimal five-valued spectra Boolean functions have been extensively studied over the past few decades,there has been limited research on the construction of almost optimal five-valued spectra vectorial Boolean functions.In this paper,we present a construction method for even-variable 2-output almost optimal five-valued spectra balanced Boolean functions,whose Walsh spectra values belong to the set{0,±2^(n/2),±2^(n/2+1)},at the same time,we discuss the existence of sufficient conditions in the construction.Additionally,this paper presents a novel construction method for balanced single-output Boolean functions with even variables featuring a special five-valued spectral structure,whose Walsh spectra values are constrained to the set{0,±2^(n/2),±3·2^(n/2)}.These functions provide new canonical examples for the study of Boolean function spectral theory.
文摘The Red Sea-Gulf of Suez-Cairo-Alexandria Clysmic-Trend in northern Egypt is the main earthquake zone in the country,with a moderate-to-high seismic hazard and a history of significant earthquakes caused by rifting and active faulting.To improve our understanding of the tectonic and seismic processes in this area,more comprehensive imaging of the crustal structure is required.This can be achieved by increasing the number of receiver functions(RFs)recorded by the seismic stations in northern Egypt and the southeastern Mediterranean.Data handling and processing should also be automated to increase process efficiency.In this study,we developed a capsule neural network for automated selection of RFs.The model was trained on a dataset containing RFs(both selected and unselected)from five broadband stations in northern Egypt.Stations SLM,SIWA,KOT,NBNS,and NKL are located in the unstable shelf region of Egypt,where limited knowledge of the deep crustal structure is available.The proposed capsule neural network achieved an average precision of 80%on the test set.The automated selection of RFs using a capsule neural network has the potential to significantly improve the efficiency and accuracy of RF analysis,as demonstrated by the stacking test.This could lead to a better understanding of crustal structure and tectonic processes in northern Egypt and the southeastern Mediterranean.
