A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques inclu...A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.展开更多
In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis...In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.展开更多
The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination ...The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination tracker dashboard. GIS-based exploratory analysis was conducted to select four variables (poverty, black race, population density, and vaccination) to explain COVID-19 occurrence during the study period. Consequently, spatial statistical techniques such as Moran’s I, Hot Spot Analysis, Spatial Lag Model (SLM), and Spatial Error Model (SEM) were used to explain the COVID-19 occurrence and vaccination rate across the 88 counties in Ohio. The result of the Local Moran’s I analysis reveals that the epicenters of COVID-19 and vaccination followed the same patterns. Indeed, counties like Summit, Franklin, Fairfield, Hamilton, and Medina were categorized as epicenters for both COVID-19 occurrence and vaccination rate. The SEM seems to be the best model for both COVID-19 and vaccination rates, with R2 values of 0.68 and 0.70, respectively. The GWR analysis proves to be better than Ordinary Least Squares (OLS), and the distribution of R2 in the GWR is uneven throughout the study area for both COVID-19 cases and vaccinations. Some counties have a high R2 of up to 0.70 for both COVID-19 cases and vaccinations. The outcomes of the regression analyses show that the SEM models can explain 68% - 70% of COVID-19 cases and vaccination across the entire counties within the study period. COVID-19 cases and vaccination rates exhibited significant positive associations with black race and poverty throughout the study area.展开更多
To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these me...To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.展开更多
This work aims at the mathematical modeling of a parabolic trough concentrator, the numerical resolution of the resulting equation, as well as the simulation of the heat transfer fluid heating process. To do this, a t...This work aims at the mathematical modeling of a parabolic trough concentrator, the numerical resolution of the resulting equation, as well as the simulation of the heat transfer fluid heating process. To do this, a thermal balance was established for the heat transfer fluid, the absorber and the glass. This allowed us to establish an equation system whose resolution was done by the finite difference method. Then, a computer program was developed to simulate the temperatures of the heat transfer fluid, the absorber tube and the glass as a function of time and space. The numerical resolution made it possible to obtain the temperatures of the heat transfer fluid, the absorber and the glass. The simulation of the fluid heating process was done in one-hour time steps, from six in the morning to six in the afternoon. The results obtained show that the temperature difference between the inlet and the outlet of the sensor is very significant. These results obtained, regarding the variation of the temperatures of the heat transfer fluid, the absorber and the glass, as well as the powers and efficiency of the parabolic trough concentrator and various factors, allow for the improvement of the performances of our prototype.展开更多
Foam structures have been attracting many scientists for a long time. However, the physics behind these structures is very complicated, and complete modeling has not yet been achieved. In this paper, a phase-field mod...Foam structures have been attracting many scientists for a long time. However, the physics behind these structures is very complicated, and complete modeling has not yet been achieved. In this paper, a phase-field modeling of the rearrangement process of foam structures was proposed, and simulations were conducted to show its effectiveness. Adjacent foam cells were assumed to interact with each other through the pressure difference, and four different conditions were introduced. When the cells had identical inner pressures at the initial state, they were stabilized, keeping the initial volume. In contrast, a volumetric change occurred when the amount of the substance in the initial cells was provided. Other models to regenerate small-cell distribution were also proposed, and the foam structures observed in real liquid foam were successfully reproduced.展开更多
In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In...In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.展开更多
The conversion of forest land to other types of land cover is one of the major issues in the global fight against climate change. Understanding the direct and indirect factors of these conversions from local studies i...The conversion of forest land to other types of land cover is one of the major issues in the global fight against climate change. Understanding the direct and indirect factors of these conversions from local studies in the tropics is essential to project the future impact of human activities on the preservation of tropical forests in general and the forests of the Republic of Congo in particular. This study, conducted in five localities with different socioeconomic contexts in the Republic of Congo, aims to analyze the variability of drivers of deforestation and forest degradation linked to urbanization in the Congo Basin. Using a series of land cover maps from the years 1986, 2003 and 2019 for the cities of Ouesso, Pokola, Ngombe, Impfondo and Dongou, as well as field data and socio-economic information collected from local and central administrations, a unique model has been developed to understand the explanatory patterns of forest loss. Deforestation around urban centers is mainly due to urban agriculture due to population growth, as well as the spatial expansion of cities, which have a major impact on the stability and integrity of forests. Shifting agriculture is the main direct cause of deforestation and forest degradation, representing 48% of the total sample, followed by the collection of wood fuel (22%), the collection of construction wood (19%), illegal logging (6%) and urban expansion (5%). Forecasts indicate that forest loss around major cities will increase by 487, 20 ha to 5266, 73 ha by 2050 compared to the base year of 2019. This study highlights the need for a new system of land management and poverty alleviation of local populations to ensure the stability of the Congo Basin tropical forests around large and small African cities.展开更多
This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high bl...This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.展开更多
Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force...To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force distribution,deformation development,and crack propagation characteristics of a framed anti-sliding structure(FAS)under landslide thrust up to the point of failure.Results show that the maximum bending moment and its increase rate in the fore pile are greater than those in the rear pile,with the maximum bending moment of the fore pile approximately 1.1 times that of the rear pile.When the FAS fails,the displacement at the top of the fore pile is significantly greater,about 1.27 times that of the rear pile in the experiment.Major cracks develop at locations corresponding to the peak bending moments.Small transverse cracks initially appear on the upper surface at the intersection between the primary beam and rear pile and then spread to the side of the structure.At the failure stage,major cracks are observed at the pil-beam intersections and near the anchor points.Strengthening flexural stiffness at intersections where major cracks occur can improve the overall thrust-deformation coordination of the FAS,thereby maximizing its performance.展开更多
This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a ...This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.展开更多
This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergen...This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.展开更多
Angiosperms experienced one of the most remarkable radiations of land plants and are now the dominant autotrophs in terrestrial ecosystems.Recent phylogenomic studies based on large-scale data from plastid,mitochondri...Angiosperms experienced one of the most remarkable radiations of land plants and are now the dominant autotrophs in terrestrial ecosystems.Recent phylogenomic studies based on large-scale data from plastid,mitochondrial,or nuclear transcriptomes/genomes and increased taxon sampling have provided unprecedent resolution into the phylogeny of flowering plants.However,owing to ancient rapid radiations,the interrelationships among the five lineages of Mesangiospermae,the vast majority of angiosperms,remain contentious.Here we show that,although plastid and mitochondrial genomes lack sufficient phylogenetic signal for resolving deeper phylogeny,the relationships among five mesangiosperm lineages can be confidently resolved under better-fitting models using genome-scale data.According to our Bayesian cross-validation and model test in a maximum likelihood framework,siteheterogeneous models(e.g.,CAT-GTR+G4,LG+C20+F+G)outperform site-homogeneous or partition models often used in previous studies.Under site-heterogeneous models,the approximately unbiased test favored our preferred tree recovered from various datasets:Ceratophyllales(coontails)are robustly recovered as sister to monocots,and they together are sister to the clade comprising magnoliids,Chloranthales,and eudicots.Our phylogenomic analyses resolve the last enigma of the deeper phylogeny of angiosperms and emphasize the efficacy of modeling compositional heterogeneity in resolving rapid radiations of plants.展开更多
Erosion in slurry pumps presents a persistent challenge in industrial applications.This study examines the erosion of the static components of a 150ZJ-C42 centrifugal slurry pump,currently in operation at a beneficiat...Erosion in slurry pumps presents a persistent challenge in industrial applications.This study examines the erosion of the static components of a 150ZJ-C42 centrifugal slurry pump,currently in operation at a beneficiation plant,under varying particle conditions.Utilizing high-precision three-dimensional reverse engineering,the pump’s flow passage geometry was reconstructed to facilitate detailed erosion analysis.Focusing on the front and rear baffles of the pump chamber,as well as the volute,erosion patterns were analyzed for different particle volume concentrations and sizes.The results reveal that the highest erosion damage consistently occurs near the volute tongue,with wear being most severe in regions adjacent to the partition plate near the rear cover.Erosion damage intensity in this area correlates positively with particle diameter.Notably,the average erosion rate in the volute surpasses that of the front and rear chamber liners,reaching a value as high as 6.03×10^(-7)kg·m^(-2)·s^(-1)at a particle concentration of 9%and diameter of 0.1 mm,adversely impacting pump stability.For the pump chamber baffles,increased erosion is observed at a particle diameter of 0.05 mm under constant volume concentration conditions,while higher particle concentrations exacerbate localized erosion.展开更多
BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the para...BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the paradoxical role of C.albicans in CRC,aiming to determine whether it promotes or suppresses tumor development,with a focus on the mechanistic basis linked to its metabolic profile.AIM To investigate the dual role of C.albicans in the development and progression of CRC through metabolite profiling and to establish a prognostic model that integrates the microbial and metabolic interactions in CRC,providing insights into potential therapeutic strategies and clinical outcomes.METHODSA prognostic model integrating C. albicans with CRC was developed, incorporating enrichment analysis, immuneinfiltration profiling, survival analysis, Mendelian randomization, single-cell sequencing, and spatial transcriptomics.The effects of the C. albicans metabolite mixture on CRC cells were subsequently validated in vitro. Theprimary metabolite composition was characterized using liquid chromatography-mass spectrometry.RESULTSA prognostic model based on five specific mRNA markers, EHD4, LIME1, GADD45B, TIMP1, and FDFT1, wasestablished. The C. albicans metabolite mixture significantly reduced CRC cell viability. Post-treatment analysisrevealed a significant decrease in gene expression in HT29 cells, while the expression levels of TIMP1, EHD4, andGADD45B were significantly elevated in HCT116 cells. Conversely, LIME1 expression and that of other CRC celllines showed reductions. In normal colonic epithelial cells (NCM460), GADD45B, TIMP1, and FDFT1 expressionlevels were significantly increased, while LIME1 and EHD4 levels were markedly reduced. Following metabolitetreatment, the invasive and migratory capabilities of NCM460, HT29, and HCT116 cells were reduced. Quantitativeanalysis of extracellular ATP post-treatment showed a significant elevation (P < 0.01). The C. albicans metabolitemixture had no effect on reactive oxygen species accumulation in CRC cells but led to a reduction in mitochondrialmembrane potential, increased intracellular lipid peroxidation, and induced apoptosis. Metabolomic profilingrevealed significant alterations, with 516 metabolites upregulated and 531 downregulated.CONCLUSIONThis study introduced a novel prognostic model for CRC risk assessment. The findings suggested that the C.albicans metabolite mixture exerted an inhibitory effect on CRC initiation.展开更多
This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC)...This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.展开更多
Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of shor...Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of short-term temporal dependencies of lip-shape variations between adjacent frames,which leaves space for further improvement in feature extraction.Methods This article presents a spatiotemporal feature fusion network(STDNet)that compensates for the deficiencies of current lip-reading approaches in short-term temporal dependency modeling.Specifically,to distinguish more similar and intricate content,STDNet adds a temporal feature extraction branch based on a 3D-CNN,which enhances the learning of dynamic lip movements in adjacent frames while not affecting spatial feature extraction.In particular,we designed a local–temporal block,which aggregates interframe differences,strengthening the relationship between various local lip regions through multiscale convolution.We incorporated the squeeze-and-excitation mechanism into the Global-Temporal Block,which processes a single frame as an independent unitto learn temporal variations across the entire lip region more effectively.Furthermore,attention pooling was introduced to highlight meaningful frames containing key semantic information for the target word.Results Experimental results demonstrated STDNet's superior performance on the LRW and LRW-1000,achieving word-level recognition accuracies of 90.2% and 53.56%,respectively.Extensive ablation experiments verified the rationality and effectiveness of its modules.Conclusions The proposed model effectively addresses short-term temporal dependency limitations in lip reading,and improves the temporal robustness of the model against variable-length sequences.These advancements validate the importance of explicit short-term dynamics modeling for practical lip-reading systems.展开更多
The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with clim...The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with climate change and environmental fluctuations.The potential distribution of I.argentinus was modeled with various environmental variables including sea surface temperature(SST),sea surface height(SSH),chlorophyll a,sea surface salinity(SSS),net primary productivity(NPP),mixed layer depth(MLD),eddy kinetic energy(EKE),and photosynthetically active radiation(PAR)using the maximum entropy(MaxEnt)approach during the peak fishing seasons(January–April).The habitat suitability index(HSI)was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable.Results indicate that the predicted habitat correlated with the actual fishing position,with similar trends in the percentages of suitable habitats and catch per unit effort(CPUE)of I.argentinus from January to April.Moreover,SST,SSH,PAR,and MLD were identified critical environmental variables for the distribution of I.argentinus.In addition,the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I.argentinus.The Area under the Receiver Operating Characteristic Curve(AUC)was greater than 0.96 for all four months.Variations in latitudinal and longitudinal gravity centers(LATG and LONG)of fishing effort were consistent with latitudinal and longitudinal gravity centers(LATG_H and LONG_H)of the HSI.Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I.argentinus.Meanwhile,SST,SSH,PAR,and MLD should be given with more extensive attention in predicting the potential distribution of I.argentinus,as they are important environmental indicators that can help decision-makers search for the fishing ground of I.argentinus in the Southwest Atlantic.展开更多
As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additi...As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additionally,there is a growing need to address the alternating magnetic fields produced by the spacecraft itself.This paper introduces a novel modeling method for spacecraft magnetic dipoles using an integrated self-attention mechanism and a transformer combined with Kolmogorov-Arnold Networks.The self-attention mechanism captures correlations among globally sparse data,establishing dependencies b.etween sparse magnetometer readings.Concurrently,the Kolmogorov-Arnold Network,proficient in modeling implicit numerical relationships between data features,enhances the ability to learn subtle patterns.Comparative experiments validate the capability of the proposed method to precisely model magnetic dipoles,achieving maximum Root Mean Square Errors of 24.06 mA·m^(2)and 0.32 cm for size and location modeling,respectively.The spacecraft magnetic model established using this method accurately computes magnetic fields and alternating magnetic fields at designated surfaces or points.This approach facilitates the rapid and precise construction of individual and complete spacecraft magnetic models,enabling the verification of magnetic specifications from the spacecraft design phase.展开更多
文摘A 3D crustal model was constructed using a combination of cutting-edge techniques,which were integrated to provide a density model for Egypt and address the sporadic distribution of seismic data.These techniques include obtaining gravity data from the Gravity Field and Steady-State Ocean Circulation Explorer(GOCE),creating seismic profiles,analyzing the receiver functions of seismic data,obtaining information from boreholes,and providing geological interpretations.GOCE satellite gravity data were processed to construct a preliminary model based on nonlinear inversions of the data.A regional crustal thickness model was developed using receiver functions,seismic refraction profiles,and geological insights.The inverted model was validated using borehole data and compared with seismic estimates.The model exhibited strong consistency and revealed a correlation between crustal thickness,geology,and tectonics of Egypt.It showed that the shallowest depths of the Moho are located in the north along the Mediterranean Sea and in the eastern part along the Red Sea,reflecting an oceanic plate with a thin,high-density crust.The deepest Moho depths are located in the southwestern part of Egypt,Red Sea coastal mountains,and Sinai Peninsula.The obtained 3D model of crustal thickness provided finely detailed Moho depth estimates that aligned closely with geology and tectonic characteristics of Egypt,contributing valuable insights into the subsurface structure and tectonic processes of region.
文摘In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.
文摘The study aims to investigate county-level variations of the COVID-19 disease and vaccination rate. The COVID-19 data was acquired from usafact.org, and the vaccination records were acquired from the Ohio vaccination tracker dashboard. GIS-based exploratory analysis was conducted to select four variables (poverty, black race, population density, and vaccination) to explain COVID-19 occurrence during the study period. Consequently, spatial statistical techniques such as Moran’s I, Hot Spot Analysis, Spatial Lag Model (SLM), and Spatial Error Model (SEM) were used to explain the COVID-19 occurrence and vaccination rate across the 88 counties in Ohio. The result of the Local Moran’s I analysis reveals that the epicenters of COVID-19 and vaccination followed the same patterns. Indeed, counties like Summit, Franklin, Fairfield, Hamilton, and Medina were categorized as epicenters for both COVID-19 occurrence and vaccination rate. The SEM seems to be the best model for both COVID-19 and vaccination rates, with R2 values of 0.68 and 0.70, respectively. The GWR analysis proves to be better than Ordinary Least Squares (OLS), and the distribution of R2 in the GWR is uneven throughout the study area for both COVID-19 cases and vaccinations. Some counties have a high R2 of up to 0.70 for both COVID-19 cases and vaccinations. The outcomes of the regression analyses show that the SEM models can explain 68% - 70% of COVID-19 cases and vaccination across the entire counties within the study period. COVID-19 cases and vaccination rates exhibited significant positive associations with black race and poverty throughout the study area.
基金supported by University of Macao,China,Nos.MYRG2022-00054-FHS and MYRG-GRG2023-00038-FHS-UMDF(to ZY)the Macao Science and Technology Development Fund,China,Nos.FDCT0048/2021/AGJ and FDCT0020/2019/AMJ and FDCT 0011/2018/A1(to ZY)Natural Science Foundation of Guangdong Province of China,No.EF017/FHS-YZ/2021/GDSTC(to ZY)。
文摘To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.
文摘This work aims at the mathematical modeling of a parabolic trough concentrator, the numerical resolution of the resulting equation, as well as the simulation of the heat transfer fluid heating process. To do this, a thermal balance was established for the heat transfer fluid, the absorber and the glass. This allowed us to establish an equation system whose resolution was done by the finite difference method. Then, a computer program was developed to simulate the temperatures of the heat transfer fluid, the absorber tube and the glass as a function of time and space. The numerical resolution made it possible to obtain the temperatures of the heat transfer fluid, the absorber and the glass. The simulation of the fluid heating process was done in one-hour time steps, from six in the morning to six in the afternoon. The results obtained show that the temperature difference between the inlet and the outlet of the sensor is very significant. These results obtained, regarding the variation of the temperatures of the heat transfer fluid, the absorber and the glass, as well as the powers and efficiency of the parabolic trough concentrator and various factors, allow for the improvement of the performances of our prototype.
文摘Foam structures have been attracting many scientists for a long time. However, the physics behind these structures is very complicated, and complete modeling has not yet been achieved. In this paper, a phase-field modeling of the rearrangement process of foam structures was proposed, and simulations were conducted to show its effectiveness. Adjacent foam cells were assumed to interact with each other through the pressure difference, and four different conditions were introduced. When the cells had identical inner pressures at the initial state, they were stabilized, keeping the initial volume. In contrast, a volumetric change occurred when the amount of the substance in the initial cells was provided. Other models to regenerate small-cell distribution were also proposed, and the foam structures observed in real liquid foam were successfully reproduced.
基金supported by Ministry of Science and Technology of the People’s Republic of China(2020YFB1808101)the Project“5G evolution wireless air interface intelligent R&D and verification public platform project”supported by Ministry of Industry and Information Technology of the People’s Republic of China(TC220A04M).
文摘In this paper,a physical model of RIS of bistatic polarized radar cross section is derived starting from the Stratton-Chu equations under the assumptions of physical optics,PEC,far field and rectangular RIS element.In the context of important physical characteristics of the backscattering polarization of RIS,the modeling of the RIS wireless channel requires a tradeoff between complexity and accuracy,as well as usability and simplicity.For channel modeling of RIS systems,RIS is modelled as multi-equivalent virtual base stations(BSs)induced by multi polarized electromagnetic waves from different incident directions.The comparison between test and simulation results demonstrates that the proposed algorithm effectively captures the key characteristics of the general RIS element polarization physical model and provides accurate results.
文摘The conversion of forest land to other types of land cover is one of the major issues in the global fight against climate change. Understanding the direct and indirect factors of these conversions from local studies in the tropics is essential to project the future impact of human activities on the preservation of tropical forests in general and the forests of the Republic of Congo in particular. This study, conducted in five localities with different socioeconomic contexts in the Republic of Congo, aims to analyze the variability of drivers of deforestation and forest degradation linked to urbanization in the Congo Basin. Using a series of land cover maps from the years 1986, 2003 and 2019 for the cities of Ouesso, Pokola, Ngombe, Impfondo and Dongou, as well as field data and socio-economic information collected from local and central administrations, a unique model has been developed to understand the explanatory patterns of forest loss. Deforestation around urban centers is mainly due to urban agriculture due to population growth, as well as the spatial expansion of cities, which have a major impact on the stability and integrity of forests. Shifting agriculture is the main direct cause of deforestation and forest degradation, representing 48% of the total sample, followed by the collection of wood fuel (22%), the collection of construction wood (19%), illegal logging (6%) and urban expansion (5%). Forecasts indicate that forest loss around major cities will increase by 487, 20 ha to 5266, 73 ha by 2050 compared to the base year of 2019. This study highlights the need for a new system of land management and poverty alleviation of local populations to ensure the stability of the Congo Basin tropical forests around large and small African cities.
文摘This study examines hemodynamic behavior in particular cases of pulmonary hypertension without treatment. Pulmonary hypertension represents an anomalous hemodynamic state and is characterized by an excessively high blood pressure in the pulmonary artery. To simulate the hemodynamic abnormalities in pulmonary hypertension under different causes and pathologies, we construct a localized parameter circuit model governed by nonlinear ordinary derivative equations of the human circulatory system. Thus, two special cases are considered, namely pulmonary the artery stenosis and the left ventricular diastolic dysfunction. For each case of pulmonary hypertension development, we determine the relationships between blood pressure and chamber and vessel pressure-volume. When the pulmonary hypertension is due to pulmonary artery stenosis, it appears that the right ventricular pressure increases up to 90 mm Hg, likewise the rise in pulmonary artery resistance induces direct increment in pulmonary artery pressure. However, when the pulmonary hypertension is due to left ventricular diastolic dysfunction, we note that the left atrial pressure and the pulmonary vein pressure augment, leading to the growth of the pulmonary artery blood pressure. The established results within this paper are useful for understanding the hemodynamic mechanism of particular pulmonary hypertension.
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
基金The National Natural Science Foundation of China(No.52078427).
文摘To ensure the operational safety of railways in the landslide-prone areas of mountainous regions,a large-scale model test and numerical simulation were conducted to study the bending moment distribution,internal force distribution,deformation development,and crack propagation characteristics of a framed anti-sliding structure(FAS)under landslide thrust up to the point of failure.Results show that the maximum bending moment and its increase rate in the fore pile are greater than those in the rear pile,with the maximum bending moment of the fore pile approximately 1.1 times that of the rear pile.When the FAS fails,the displacement at the top of the fore pile is significantly greater,about 1.27 times that of the rear pile in the experiment.Major cracks develop at locations corresponding to the peak bending moments.Small transverse cracks initially appear on the upper surface at the intersection between the primary beam and rear pile and then spread to the side of the structure.At the failure stage,major cracks are observed at the pil-beam intersections and near the anchor points.Strengthening flexural stiffness at intersections where major cracks occur can improve the overall thrust-deformation coordination of the FAS,thereby maximizing its performance.
基金supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region,China(Project No.HKU 17207518).
文摘This paper presents a dynamic modeling method to test and examine the minimum mass of pressurized pore-gas for triggering landslides in stable gentle soil slopes.A stable gentle soil slope model is constructed with a dry cement powder core,a saturated clay middle layer,and a dry sand upper layer.The test injects H_(2)O_(2)solution into the cement core to produce new pore-gas.The model test includes three identical H_(2)O_(2)injections.The small mass of generated oxygen gas(0.07%of slope soil mass and landslide body)from the first injection can build sufficient pore-gas pressure to cause soil upheaval and slide.Meanwhile,despite the first injection causing leak paths in the clay layer,the generated small mass of gas from the second and third injections can further trigger the landslide.A dynamic theoretical analysis of the slope failure is carried out and the required minimum pore-gas pressure for the landslide is calculated.The mass and pressure of generated gas in the model test are also estimated based on the calibration test for oxygen generation from H_(2)O_(2)solution in cement powder.The results indicate that the minimum mass of the generated gas for triggering the landslide is 2 ppm to 0.07%of the landslide body.Furthermore,the small mass of gas can provide sufficient pressure to cause soil upheaval and soil sliding in dynamic analysis.
文摘This paper develops a comprehensive computational modeling and simulation framework based on Complex Adaptive Systems(CAS)theory to unveil the underlying mechanisms of self-organization,nonlinear evolution,and emergence in social systems.By integrating mathematical models,agent-based modeling,network dynamic analysis,and hybrid modeling approaches,the study applies CAS theory to case studies in economic markets,political decision-making,and social interactions.The experimental results demonstrate that local interactions among individual agents can give rise to complex global phenomena,such as market fluctuations,opinion polarization,and sudden outbreaks of social movements.This framework not only provides a more robust explanation for the nonlinear dynamics and abrupt transitions that traditional models often fail to capture,but also offers valuable decision-support tools for public policy formulation,social governance,and risk management.Emphasizing the importance of interdisciplinary approaches,this work outlines future research directions in high-performance computing,artificial intelligence,and real-time data integration to further advance the theoretical and practical applications of CAS in the social sciences.
基金supported by the National Natural Science Foundation of China(42222201,42288201)。
文摘Angiosperms experienced one of the most remarkable radiations of land plants and are now the dominant autotrophs in terrestrial ecosystems.Recent phylogenomic studies based on large-scale data from plastid,mitochondrial,or nuclear transcriptomes/genomes and increased taxon sampling have provided unprecedent resolution into the phylogeny of flowering plants.However,owing to ancient rapid radiations,the interrelationships among the five lineages of Mesangiospermae,the vast majority of angiosperms,remain contentious.Here we show that,although plastid and mitochondrial genomes lack sufficient phylogenetic signal for resolving deeper phylogeny,the relationships among five mesangiosperm lineages can be confidently resolved under better-fitting models using genome-scale data.According to our Bayesian cross-validation and model test in a maximum likelihood framework,siteheterogeneous models(e.g.,CAT-GTR+G4,LG+C20+F+G)outperform site-homogeneous or partition models often used in previous studies.Under site-heterogeneous models,the approximately unbiased test favored our preferred tree recovered from various datasets:Ceratophyllales(coontails)are robustly recovered as sister to monocots,and they together are sister to the clade comprising magnoliids,Chloranthales,and eudicots.Our phylogenomic analyses resolve the last enigma of the deeper phylogeny of angiosperms and emphasize the efficacy of modeling compositional heterogeneity in resolving rapid radiations of plants.
基金The authors gratefully acknowledge the filnancial support of the National Natural Science Foundation of China(Grant No.52369018)the Major Training Program of University Research and Innovation Platform of Gansu Provincial Department of Education(No.2024CXPT-09)+1 种基金the Administration of Central Funds Guiding the Local Science and Technology Development,China(Grant No.23ZYQA0320)the Double First-Class Key Program of Gansu Provincial Department of Education,Grant No.GCJ2022-38.
文摘Erosion in slurry pumps presents a persistent challenge in industrial applications.This study examines the erosion of the static components of a 150ZJ-C42 centrifugal slurry pump,currently in operation at a beneficiation plant,under varying particle conditions.Utilizing high-precision three-dimensional reverse engineering,the pump’s flow passage geometry was reconstructed to facilitate detailed erosion analysis.Focusing on the front and rear baffles of the pump chamber,as well as the volute,erosion patterns were analyzed for different particle volume concentrations and sizes.The results reveal that the highest erosion damage consistently occurs near the volute tongue,with wear being most severe in regions adjacent to the partition plate near the rear cover.Erosion damage intensity in this area correlates positively with particle diameter.Notably,the average erosion rate in the volute surpasses that of the front and rear chamber liners,reaching a value as high as 6.03×10^(-7)kg·m^(-2)·s^(-1)at a particle concentration of 9%and diameter of 0.1 mm,adversely impacting pump stability.For the pump chamber baffles,increased erosion is observed at a particle diameter of 0.05 mm under constant volume concentration conditions,while higher particle concentrations exacerbate localized erosion.
基金Supported by Gansu Province Joint Fund General Program,No.24JRRA878Gansu Provincial Science and Technology Program Project,No.24JRRA1020+2 种基金Gansu Province Key Talent Program,No.2025RCXM006Teaching Research and Reform Program for Postgraduate Education at Gansu University of Traditional Chinese Medicine(GUSTCM),No.YBXM-202406Special Fund for Mentors of“Qihuang Talents”in the First-Level Discipline of Chinese Medicine,No.ZYXKBD-202415。
文摘BACKGROUND Emerging evidence implicates Candida albicans(C.albicans)in human oncogenesis.Notably,studies have supported its involvement in regulating outcomes in colorectal cancer(CRC).This study investigated the paradoxical role of C.albicans in CRC,aiming to determine whether it promotes or suppresses tumor development,with a focus on the mechanistic basis linked to its metabolic profile.AIM To investigate the dual role of C.albicans in the development and progression of CRC through metabolite profiling and to establish a prognostic model that integrates the microbial and metabolic interactions in CRC,providing insights into potential therapeutic strategies and clinical outcomes.METHODSA prognostic model integrating C. albicans with CRC was developed, incorporating enrichment analysis, immuneinfiltration profiling, survival analysis, Mendelian randomization, single-cell sequencing, and spatial transcriptomics.The effects of the C. albicans metabolite mixture on CRC cells were subsequently validated in vitro. Theprimary metabolite composition was characterized using liquid chromatography-mass spectrometry.RESULTSA prognostic model based on five specific mRNA markers, EHD4, LIME1, GADD45B, TIMP1, and FDFT1, wasestablished. The C. albicans metabolite mixture significantly reduced CRC cell viability. Post-treatment analysisrevealed a significant decrease in gene expression in HT29 cells, while the expression levels of TIMP1, EHD4, andGADD45B were significantly elevated in HCT116 cells. Conversely, LIME1 expression and that of other CRC celllines showed reductions. In normal colonic epithelial cells (NCM460), GADD45B, TIMP1, and FDFT1 expressionlevels were significantly increased, while LIME1 and EHD4 levels were markedly reduced. Following metabolitetreatment, the invasive and migratory capabilities of NCM460, HT29, and HCT116 cells were reduced. Quantitativeanalysis of extracellular ATP post-treatment showed a significant elevation (P < 0.01). The C. albicans metabolitemixture had no effect on reactive oxygen species accumulation in CRC cells but led to a reduction in mitochondrialmembrane potential, increased intracellular lipid peroxidation, and induced apoptosis. Metabolomic profilingrevealed significant alterations, with 516 metabolites upregulated and 531 downregulated.CONCLUSIONThis study introduced a novel prognostic model for CRC risk assessment. The findings suggested that the C.albicans metabolite mixture exerted an inhibitory effect on CRC initiation.
基金funded by the Natural Science Foundation of China(Grant No.52090084)was partially supported by the Sand Hazards and Opportunities for Resilience,Energy,and Sustainability(SHORES)Center,funded by Tamkeen under the NYUAD Research Institute Award CG013.
文摘This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.
基金Supported by the National Key Research and Development Program of China(2023YFC3306201)the National Natural Science Foundation of China(61772125)the Fundamental Research Funds for the Central Universities(N2317004).
文摘Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of short-term temporal dependencies of lip-shape variations between adjacent frames,which leaves space for further improvement in feature extraction.Methods This article presents a spatiotemporal feature fusion network(STDNet)that compensates for the deficiencies of current lip-reading approaches in short-term temporal dependency modeling.Specifically,to distinguish more similar and intricate content,STDNet adds a temporal feature extraction branch based on a 3D-CNN,which enhances the learning of dynamic lip movements in adjacent frames while not affecting spatial feature extraction.In particular,we designed a local–temporal block,which aggregates interframe differences,strengthening the relationship between various local lip regions through multiscale convolution.We incorporated the squeeze-and-excitation mechanism into the Global-Temporal Block,which processes a single frame as an independent unitto learn temporal variations across the entire lip region more effectively.Furthermore,attention pooling was introduced to highlight meaningful frames containing key semantic information for the target word.Results Experimental results demonstrated STDNet's superior performance on the LRW and LRW-1000,achieving word-level recognition accuracies of 90.2% and 53.56%,respectively.Extensive ablation experiments verified the rationality and effectiveness of its modules.Conclusions The proposed model effectively addresses short-term temporal dependency limitations in lip reading,and improves the temporal robustness of the model against variable-length sequences.These advancements validate the importance of explicit short-term dynamics modeling for practical lip-reading systems.
基金Supported by the Natural Science Foundation of Shanghai(No.23ZR1427100)the National Key R&D Program of China(No.2023YFD2401303)the Shanghai Talent Development Funding for the Project(No.2021078)。
文摘The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with climate change and environmental fluctuations.The potential distribution of I.argentinus was modeled with various environmental variables including sea surface temperature(SST),sea surface height(SSH),chlorophyll a,sea surface salinity(SSS),net primary productivity(NPP),mixed layer depth(MLD),eddy kinetic energy(EKE),and photosynthetically active radiation(PAR)using the maximum entropy(MaxEnt)approach during the peak fishing seasons(January–April).The habitat suitability index(HSI)was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable.Results indicate that the predicted habitat correlated with the actual fishing position,with similar trends in the percentages of suitable habitats and catch per unit effort(CPUE)of I.argentinus from January to April.Moreover,SST,SSH,PAR,and MLD were identified critical environmental variables for the distribution of I.argentinus.In addition,the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I.argentinus.The Area under the Receiver Operating Characteristic Curve(AUC)was greater than 0.96 for all four months.Variations in latitudinal and longitudinal gravity centers(LATG and LONG)of fishing effort were consistent with latitudinal and longitudinal gravity centers(LATG_H and LONG_H)of the HSI.Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I.argentinus.Meanwhile,SST,SSH,PAR,and MLD should be given with more extensive attention in predicting the potential distribution of I.argentinus,as they are important environmental indicators that can help decision-makers search for the fishing ground of I.argentinus in the Southwest Atlantic.
基金supported by the National Key Research and Development Program of China(2020YFC2200901)。
文摘As the complexity of scientific satellite missions increases,the requirements for their magnetic fields,magnetic field fluctuations,and even magnetic field gradients and variations become increasingly stringent.Additionally,there is a growing need to address the alternating magnetic fields produced by the spacecraft itself.This paper introduces a novel modeling method for spacecraft magnetic dipoles using an integrated self-attention mechanism and a transformer combined with Kolmogorov-Arnold Networks.The self-attention mechanism captures correlations among globally sparse data,establishing dependencies b.etween sparse magnetometer readings.Concurrently,the Kolmogorov-Arnold Network,proficient in modeling implicit numerical relationships between data features,enhances the ability to learn subtle patterns.Comparative experiments validate the capability of the proposed method to precisely model magnetic dipoles,achieving maximum Root Mean Square Errors of 24.06 mA·m^(2)and 0.32 cm for size and location modeling,respectively.The spacecraft magnetic model established using this method accurately computes magnetic fields and alternating magnetic fields at designated surfaces or points.This approach facilitates the rapid and precise construction of individual and complete spacecraft magnetic models,enabling the verification of magnetic specifications from the spacecraft design phase.
