An integrative computational, in silico, model of C1 metabolism is developed from molecular pathway systems identified from a recent, comprehensive systematic bioinformatics review of C1 metabolism. C1 metabolism is e...An integrative computational, in silico, model of C1 metabolism is developed from molecular pathway systems identified from a recent, comprehensive systematic bioinformatics review of C1 metabolism. C1 metabolism is essential for all organisms to provide one-carbon units for methylation and other types of modifications, as well as for nucleic acid, amino acid, and other biomolecule syntheses. C1 metabolism consists of three important molecular pathway systems: 1) methionine biosynthesis, 2) methylation cycle, and 3) formaldehyde detoxification. Each of the three molecular pathway systems is individually modeled using the CytoSolve?? Collaboratory?, a proven and scalable computational systems biology platform for in silico modeling of complex molecular pathway systems. The individual models predict the temporal behavior of formaldehyde, formate, sarcosine, glutathione (GSH), and many other key biomolecules involved in C1 metabolism, which may be hard to measure experimentally. The individual models are then coupled and integrated dynamically using CytoSolve to produce, to the authors’ knowledge, the first comprehensive computational model of C1 metabolism. In silico modeling of the individual and integrated C1 metabolism models enables the identification of the most sensitive parameters involved in the detoxification of formaldehyde. This integrative model of C1 metabolism, giving its systems-based nature, can likely serve as a platform for: 1) generalized research and study of C1 metabolism, 2) hypothesis generation that motivates focused and specific in vitro and in vivo testing in perhaps a more efficient manner, 3) expanding a systems biology understanding of plant bio-molecular systems by integrating other known molecular pathway systems associated with C1 metabolism, and 4) exploring and testing the potential effects of exogenous inputs on the C1 metabolism system.展开更多
Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fiel...Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fields.This paper presents a systematic review of this subject with special emphasis on the multi-physics governing it.First,we elucidate the interdependent mechanisms and governing equations,highlighting the nonlinear,path-dependent,and evolving nature of the relationship between stress and permeability.Next,mainstream modeling approaches,including equivalent continuum,discrete fracture network(DFN),and dual-porosity/dual-permeability methods,are critically evaluated,and a strategy for model selection based on project scale and geological context is proposed accordingly.Moreover,experimental insights from single-fracture and triaxial flow studies are synthesized,revealing how effective stress,shear displacement,and fracture roughness control permeability evolution.In particular,the practical significance of THMC coupling is demonstrated through case studies on nuclear waste disposal,Enhanced Geothermal Systems,and tunneling projects.The reviewfurther explores AI-and machine learning-driven innovations,particularly physics-informed neural networks and hybrid modeling,which address limitations in computational efficiency,data scarcity,and physical consistency.Finally,persistent challenges,including multi-scale coupling,parameter uncertainty,and complex fracture network representation are identified and critically discussed while paying attention to future developments.展开更多
The study of the development cost of general aviation aircraft is limited by small samples with many cost-driven factors. This paper investigates a parametric modeling method for prediction of the development cost of ...The study of the development cost of general aviation aircraft is limited by small samples with many cost-driven factors. This paper investigates a parametric modeling method for prediction of the development cost of general aviation aircraft. The proposed technique depends on some principal components, acquired by utilizing P value analysis and gray correlation analysis. According to these principal components, the corresponding linear regression and BP neural network models are established respectively. The feasibility and accuracy of the P value analysis are verified by comparing results of model fitting and prediction. A sensitivity analysis related to model precision and suitability is discussed in detail. Results obtained in this study show that the proposed method not only has a certain degree of versatility, but also provides a preliminary prediction of the development cost of general aviation aircraft.展开更多
Starting from a philosophical perspective,which states that the living structures are actually a combination between matter and information,this article presents the results on an analysis of the bipolar information-m...Starting from a philosophical perspective,which states that the living structures are actually a combination between matter and information,this article presents the results on an analysis of the bipolar information-matter structure of the human organism,distinguishing three fundamental circuits for its survival,which demonstrates and supports this statement,as a base for further development of the informational model of consciousness to a general informational model of the human organism.For this,it was examined the Informational System of the Human Body and its components from the perspective of the physics/information/neurosciences concepts,showing specific functions of each of them,highlighting the correspondence of these centers with brain support areas and with their projections in consciousness,which are:Center of Acquisition and Storing of Information(CASI)reflected in consciousness as memory,Center of Decision and Command(CDC)(decision),Info-Emotional Center(IES)(emotions),Maintenance Informational System(MIS)(personal status),Genetic Transmission System(GTS)(associativity/genetic transmission)and Info Genetic Generator(IGG)related by the body development and inherited behaviors.The Info Connection(IC),detected in consciousness as trust and confidence can explain the Near-Death Experiences(NDEs)and associated phenomena.This connection is antientropic and informational,because from the multitude of uncertain possibilities is selected a certain one,helping/supporting the survival and life.The human body appears therefore as a bipolar structure,connected to two poles:information and matter.It is argued that the survival,which is the main objective of the organism,is complied in three main ways,by means of:(i)the reactive operation for adaptation by attitude;(ii)the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival,both circuits(i)and(ii)being associated to the information pole;(iii)maintenance of the material body(defined as informed matter)and its functions,associated to the matter pole of the organism.It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems,the cognitive centers,the sensors,transducers and execution(motor/mobile)elements.The fundamental informational circuits assuring the survival are the reactive circuit,expressible by attitude,the epigenetic/genetic circuit,absorbing and codifying information to be transmitted to the next generations,and the metabolic circuit,connected to matter(matter pole).The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism,fully describing the composition/functions of the organism in terms of information/matter and neurosciences concepts.展开更多
Pathogenic mutations involving DNA repeat expansions are responsible for over 20 different neuronal and neuromuscular diseases. All result from expanded tracts of repetitive DNA sequences(mostly microsatellites) that ...Pathogenic mutations involving DNA repeat expansions are responsible for over 20 different neuronal and neuromuscular diseases. All result from expanded tracts of repetitive DNA sequences(mostly microsatellites) that become unstable beyond a critical length whentransmitted across generations. Nearly all are inherited as autosomal dominant conditions and are typically associated with anticipation. Pathologic unstable repeat expansions can be classified according to their length, repeat sequence, gene location and underlying pathologic mechanisms. This review summarizes the current contribution of mutant pluripotent stem cells(diseased human embryonic stem cells and patient-derived induced pluripotent stem cells) to the research of unstable repeat pathologies by focusing on particularly large unstable noncoding expansions. Among this class of disorders are Fragile X syndrome and Fragile X-associated tremor/ataxia syndrome, myotonic dystrophy type 1 and myotonic dystrophy type 2, Friedreich ataxia and C9 related amyotrophic lateral sclerosis and/or frontotemporal dementia, Facioscapulohumeral Muscular Dystrophy and potentially more. Common features that are typical to this subclass of conditions are RNA toxic gain-of-function, epigenetic loss-of-function, toxic repeat-associated non-ATG translation and somatic instability. For each mechanism we summarize the currently available stem cell based models, highlight how they contributed to better understanding of the related mechanism, and discuss how they may be utilized in future investigations.展开更多
The scientific article examines the physical and mechanical properties of raw cotton stored in buntings in cotton palaces. Because during the storage of raw cotton in bunts, some of its properties deteriorate, some im...The scientific article examines the physical and mechanical properties of raw cotton stored in buntings in cotton palaces. Because during the storage of raw cotton in bunts, some of its properties deteriorate, some improvements. Therefore, the mathematical modeling of storage conditions of raw cotton in bunts and the physical and mechanical conditions that occur in it is of great importance. In the developed mathematical model, the main factor influencing the physical and mechanical properties of raw cotton is the change in temperature. Due to the temperature, kinetic and biological processes accumulated in the raw cotton in Bunt, it can spread over a large surface, first in a small-local state, over time with a nonlinear law. As a result, small changes in temperature lead to a qualitative change in physical properties. In determining the law of temperature distribution in the raw cotton in Bunt, Laplace’s differential equation of heat transfer was used. The differential equation of heat transfer in Laplace’s law was replaced by a system of ordinary differential equations by approximation. Conditions are solved in MAPLE-17 program by numerical method. As a result, graphs of temperature changes over time in raw cotton were obtained. In addition, the table shows the changes in density, pressure and mass of cotton, the height of the bun. As the density of the cotton raw material increases from the top layer of the bunt to the bottom layer, an increase in the temperature in it has been observed. This leads to overheating of the bottom layer of cotton and is the main reason for the deterioration of the quality of raw materials.展开更多
Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuo...Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.展开更多
This paper deals with the increasing safety of working in aggressive potential locations, having SCADA system and WSN sensors, using a “probabilistic strategy” in comparison with a “deterministic” one, modeling/si...This paper deals with the increasing safety of working in aggressive potential locations, having SCADA system and WSN sensors, using a “probabilistic strategy” in comparison with a “deterministic” one, modeling/simulation and application in underground coal mining. In general, three conditions can be considered: 1) an unfriendly environment that facilitates the risk of accidents, 2) aggressive equipments that can compete to cause accidents and 3) the work security breaches that can cause accidents. These conditions define the triangle of accidents and are customized for an underground coal mining where the methane gas is released with the exploitation of the massive coal. In this case, the first two conditions create an explosive potential atmosphere. To allow people to work in a safe location it needs: first, a continuing monitoring through SCADA system of the explosive potential atmosphere and second, the use of antiexplosive equipment. This method, named “deterministic strategy”, increases the safety of working, but the explosions have not been completely eliminated. In order to increase the safety of working, the paper continues with the presentation of a new method based on hazard laws, named “probabilistic strategy”. This strategy was validated through modeling/simulation using CupCarbon software platform, and application of WSN networks implemented on Arduino equipments. At the end of the paper the interesting conclusions are emphases which are applicable to both strategies.展开更多
We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP)...We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.展开更多
This article describes how the cartographic depth-to-water (DTW) index in combination with other variables can be used to quantify, model and map the distribution of common forest floor bryophytes, at 1 m resolution. ...This article describes how the cartographic depth-to-water (DTW) index in combination with other variables can be used to quantify, model and map the distribution of common forest floor bryophytes, at 1 m resolution. This was done by way of a case study, using 12 terrain and climate representative locations across New Brunswick, Canada. The presence/absence by moss species was determined at each location along upland-to-wetland transects within >10-m spaced 1-m2 forest floor plots. It was found that Bazzania trilobata, Dicranum polysetum, Polytrichum commune, Hylocomium splendens, and Pleurozium schreberi had greater probabilities of occurrence in well-drained forested areas, whereas Sphagnum fuscum and Sphagnum girgensohnii dominated in low-lying wet areas. The presence/absence of each species was quantified by way of logistic regression analyses, using DTW, slope, canopy closure, forest litter depth, ecosite type (8 classes), nutrient regime (4 classes, poor to rich);vegetation type (deciduous, coniferous, mixed, and shrubs), and macro- and micro-topography (upland, wetland;mounds, pits) as predictor variables. Among these, log10DTW and forest litter depth were the most consistent predictor variables, followed by mound versus pit. For the mapping purpose, only log10DTW and already mapped classifications for upland versus wetland and vegetation type were used to predict the probability of occurrences for the most frequent moss species, namely, D. polysetum, P. schreberi and Sphagnum spp. The overall accuracy for doing this ranged from 67% to 83%, with false positives and negatives amounting to 18% to 42%. The overall classification accuracy exceeded the probability by chance alone at 76.8%, with the significance level reached at 75.3%. The average level of probability by chance alone was 60.3%.展开更多
The large excess of solid waste generated in cities is a result of population growth and economic development. Properly managing this municipal solid waste (MSW) is a challenge, mainly in underdeveloped and developing...The large excess of solid waste generated in cities is a result of population growth and economic development. Properly managing this municipal solid waste (MSW) is a challenge, mainly in underdeveloped and developing countries where financial concerns are an added problem. From the environmental point of view, a major issue is properly disposing MSW taking into consideration a wide range of factors, and working with different spatial data. In this study, we used geographic information system (GIS) to perform multi-criteria decision analysis (MCDA) conducted by analytical hierarchy process (AHP). The development of the environmental impact susceptibility model (EISM) for municipal solid waste disposal sites (MSWDS) applied to the state of Sao Paulo, Brazil considered factors such as geology, pedology, geomorphology, water resources, and climate represented by fifteen associated sub-factors. The results indicated that more than 82% of Sao Paulo’s territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 18% of the state land area, 85 landfills are located in areas with high and very high environmental impact susceptibility categories. These results are alarming because these 85 landfills receive approximately 17,886 tons of MSW on a daily basis, which corresponds to 46% of all municipal solid waste disposed in Sao Paulo state. Therefore, decision makers, urban planners and policymakers could use the findings of the EISM towards mitigating the environmental impacts caused by MSWDS.展开更多
The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir upli...The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.展开更多
Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other a...Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).展开更多
Mathematical modeling of surface deformations caused by underground mining operation is commonly carried out with use of empirical,numerical or stochastic models.One of the most frequently applied model for prediction...Mathematical modeling of surface deformations caused by underground mining operation is commonly carried out with use of empirical,numerical or stochastic models.One of the most frequently applied model for prediction of ground deformation in many countries is Knothe model.The model developed by Knothe belongs to the stochastic methods and is based on the influence function.In China a prediction method named Probability Integration Method(PIF)was established by Liu Baochen and Liao Guohua based on the stochastic medium theory.Modified version of that model allows to predict ground movements caused by mining operation in extremely complex technical and geological conditions.That model is commonly applied for coal,metal ore and salt deposits.The article presents several modifications of the mathematical model used in China and Poland.This model is very widespread in the world,therefore the generalizations proposed in the article can be implemented for the purposes of prediction surface deformations for various types of deposits in many countries.The presented generalizations were then tested on specific examples of coal mining,copper ore mining and rock salt deposit.The obtained results indicate high efficiency of methods based on the influence function in complex geological and mining conditions.展开更多
Recently, velocity prediction and modeling have been focus of the geophysical exploration in the high temperature and high pressure of the south China sea area, especially for new offshore exploratory areas. The error...Recently, velocity prediction and modeling have been focus of the geophysical exploration in the high temperature and high pressure of the south China sea area, especially for new offshore exploratory areas. The error is large with great difficulty owing to fewer exploratory wells and misunderstanding. Firstly, on the basis of three typical velocity prediction and modeling examples in Ying-Qiong basin, it’s easy to put forward the corresponding not common but urgent problem in each instance, then combined with the velocity problem and misunderstanding to expand method discussion and solution, which include geological model to guide the velocity interpretation and analysis, the establishment of forward velocity of the auxiliary model explaining and constructing high precision velocity model. This research basically solves existing velocity problems in gas exploration of south China sea in recent years, and proposes corresponding solution and application, which is of great significance to the further exploration and productive practice.展开更多
In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the PO...In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.展开更多
The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands o...The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands of years. Our working hypothesis is that some of those warming episodes at least partially might have been caused by dynamics of the Antarctic Ice Sheet, which, in turn, might have caused strong changes of sea surface salinity in the Miocene Southern Ocean. Feasibility of this hypothesis is explored in a series of offline-coupled ocean-atmosphere computer experiments. The results suggest that relatively small and geologically short-lived changes in freshwater balance in the Southern Ocean could have significantly contributed to at least two prominent warming episodes in the Miocene. Importantly, the scenario-based experiments also suggest that the Southern Ocean was more sensitive to the salinity changes in the Miocene than today, which can attributed to the opening of the Central American Isthmus as a major difference between the Miocene and the present-day ocean-sea geometry.展开更多
Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields...Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields using good observations is considered. The regularity of the emission processes of acoustic emission, which manifests itself in the form of discrete spectra of signals similar to oscillations of nonlinearly coupled oscillators, is shown. Spectra have special characteristics for each type of rock. Applied method and design: An algorithm for modeling the process of resonant acoustic response of a porous fluid-saturated reservoir with hierarchical structure and plastic properties on acoustic frequency excitation is developed. That algorithm is developed as an iterative process for the solution integral and integral-differential equations. The frequencies that are parameters of the direct problem are used from the spectra of observed data of acoustic emission in the oil wells. Typical results: For the first time, it had been found the relation between resonant frequencies of the acoustic emission and plastic properties, these values of frequencies had been used in the algorithm of modeling distribution of longitudinal waves in the fluid saturated nonlinear plastic environment. Concluding note (Practical value/implications): The analysis of these emission processes can serve as a source of information about the filtration-capacitive properties of productive reservoirs of a porous type with a hierarchical structure. It is used by practical data of oil fields of Western Siberia.展开更多
Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important a...Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.展开更多
In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is pr...In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is proposed from the genetic algorithm with important additional strategies, and consequently yields a faster convergence and a more accurate search. Firstly, MGA-based identification method is used to identify the parameters of the nonlinear PAM manipulator described by an ARX model in the presence of white noise and this result will be validated by MGA and compared with the simple genetic algorithm (GA) and LMS (Least mean-squares) method. Secondly, the intrinsic features of the hysteresis as well as other nonlinear disturbances existing intuitively in the PAM system are estimated online by a Modified Recursive Least Square (MRLS) method in identification experiment. Finally, a highly efficient self-tuning control algorithm Minimum Variance Control (MVC) is taken for tracking the joint angle position trajectory of this PAM manipulator. Experiment results are included to demonstrate the excellent performance of the MGA algorithm in the NARX model-based MVC control system of the PAM system. These results can be applied to model, identify and control other highly nonlinear systems as well.展开更多
文摘An integrative computational, in silico, model of C1 metabolism is developed from molecular pathway systems identified from a recent, comprehensive systematic bioinformatics review of C1 metabolism. C1 metabolism is essential for all organisms to provide one-carbon units for methylation and other types of modifications, as well as for nucleic acid, amino acid, and other biomolecule syntheses. C1 metabolism consists of three important molecular pathway systems: 1) methionine biosynthesis, 2) methylation cycle, and 3) formaldehyde detoxification. Each of the three molecular pathway systems is individually modeled using the CytoSolve?? Collaboratory?, a proven and scalable computational systems biology platform for in silico modeling of complex molecular pathway systems. The individual models predict the temporal behavior of formaldehyde, formate, sarcosine, glutathione (GSH), and many other key biomolecules involved in C1 metabolism, which may be hard to measure experimentally. The individual models are then coupled and integrated dynamically using CytoSolve to produce, to the authors’ knowledge, the first comprehensive computational model of C1 metabolism. In silico modeling of the individual and integrated C1 metabolism models enables the identification of the most sensitive parameters involved in the detoxification of formaldehyde. This integrative model of C1 metabolism, giving its systems-based nature, can likely serve as a platform for: 1) generalized research and study of C1 metabolism, 2) hypothesis generation that motivates focused and specific in vitro and in vivo testing in perhaps a more efficient manner, 3) expanding a systems biology understanding of plant bio-molecular systems by integrating other known molecular pathway systems associated with C1 metabolism, and 4) exploring and testing the potential effects of exogenous inputs on the C1 metabolism system.
文摘Fluid flow through fractured rock masses is a key process controlling the safety and performance of deep geoengineering systems,shaped by the complex interactions of thermal,hydraulic,mechanical and chemical(THMC)fields.This paper presents a systematic review of this subject with special emphasis on the multi-physics governing it.First,we elucidate the interdependent mechanisms and governing equations,highlighting the nonlinear,path-dependent,and evolving nature of the relationship between stress and permeability.Next,mainstream modeling approaches,including equivalent continuum,discrete fracture network(DFN),and dual-porosity/dual-permeability methods,are critically evaluated,and a strategy for model selection based on project scale and geological context is proposed accordingly.Moreover,experimental insights from single-fracture and triaxial flow studies are synthesized,revealing how effective stress,shear displacement,and fracture roughness control permeability evolution.In particular,the practical significance of THMC coupling is demonstrated through case studies on nuclear waste disposal,Enhanced Geothermal Systems,and tunneling projects.The reviewfurther explores AI-and machine learning-driven innovations,particularly physics-informed neural networks and hybrid modeling,which address limitations in computational efficiency,data scarcity,and physical consistency.Finally,persistent challenges,including multi-scale coupling,parameter uncertainty,and complex fracture network representation are identified and critically discussed while paying attention to future developments.
基金supported by the National Postdoctoral Program for Innovative Talents, Postdoctoral Science Foundation of China (No. 2017M610740)supports from Hefei General Aviation Research Institute, Beihang University
文摘The study of the development cost of general aviation aircraft is limited by small samples with many cost-driven factors. This paper investigates a parametric modeling method for prediction of the development cost of general aviation aircraft. The proposed technique depends on some principal components, acquired by utilizing P value analysis and gray correlation analysis. According to these principal components, the corresponding linear regression and BP neural network models are established respectively. The feasibility and accuracy of the P value analysis are verified by comparing results of model fitting and prediction. A sensitivity analysis related to model precision and suitability is discussed in detail. Results obtained in this study show that the proposed method not only has a certain degree of versatility, but also provides a preliminary prediction of the development cost of general aviation aircraft.
文摘Starting from a philosophical perspective,which states that the living structures are actually a combination between matter and information,this article presents the results on an analysis of the bipolar information-matter structure of the human organism,distinguishing three fundamental circuits for its survival,which demonstrates and supports this statement,as a base for further development of the informational model of consciousness to a general informational model of the human organism.For this,it was examined the Informational System of the Human Body and its components from the perspective of the physics/information/neurosciences concepts,showing specific functions of each of them,highlighting the correspondence of these centers with brain support areas and with their projections in consciousness,which are:Center of Acquisition and Storing of Information(CASI)reflected in consciousness as memory,Center of Decision and Command(CDC)(decision),Info-Emotional Center(IES)(emotions),Maintenance Informational System(MIS)(personal status),Genetic Transmission System(GTS)(associativity/genetic transmission)and Info Genetic Generator(IGG)related by the body development and inherited behaviors.The Info Connection(IC),detected in consciousness as trust and confidence can explain the Near-Death Experiences(NDEs)and associated phenomena.This connection is antientropic and informational,because from the multitude of uncertain possibilities is selected a certain one,helping/supporting the survival and life.The human body appears therefore as a bipolar structure,connected to two poles:information and matter.It is argued that the survival,which is the main objective of the organism,is complied in three main ways,by means of:(i)the reactive operation for adaptation by attitude;(ii)the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival,both circuits(i)and(ii)being associated to the information pole;(iii)maintenance of the material body(defined as informed matter)and its functions,associated to the matter pole of the organism.It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems,the cognitive centers,the sensors,transducers and execution(motor/mobile)elements.The fundamental informational circuits assuring the survival are the reactive circuit,expressible by attitude,the epigenetic/genetic circuit,absorbing and codifying information to be transmitted to the next generations,and the metabolic circuit,connected to matter(matter pole).The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism,fully describing the composition/functions of the organism in terms of information/matter and neurosciences concepts.
文摘Pathogenic mutations involving DNA repeat expansions are responsible for over 20 different neuronal and neuromuscular diseases. All result from expanded tracts of repetitive DNA sequences(mostly microsatellites) that become unstable beyond a critical length whentransmitted across generations. Nearly all are inherited as autosomal dominant conditions and are typically associated with anticipation. Pathologic unstable repeat expansions can be classified according to their length, repeat sequence, gene location and underlying pathologic mechanisms. This review summarizes the current contribution of mutant pluripotent stem cells(diseased human embryonic stem cells and patient-derived induced pluripotent stem cells) to the research of unstable repeat pathologies by focusing on particularly large unstable noncoding expansions. Among this class of disorders are Fragile X syndrome and Fragile X-associated tremor/ataxia syndrome, myotonic dystrophy type 1 and myotonic dystrophy type 2, Friedreich ataxia and C9 related amyotrophic lateral sclerosis and/or frontotemporal dementia, Facioscapulohumeral Muscular Dystrophy and potentially more. Common features that are typical to this subclass of conditions are RNA toxic gain-of-function, epigenetic loss-of-function, toxic repeat-associated non-ATG translation and somatic instability. For each mechanism we summarize the currently available stem cell based models, highlight how they contributed to better understanding of the related mechanism, and discuss how they may be utilized in future investigations.
文摘The scientific article examines the physical and mechanical properties of raw cotton stored in buntings in cotton palaces. Because during the storage of raw cotton in bunts, some of its properties deteriorate, some improvements. Therefore, the mathematical modeling of storage conditions of raw cotton in bunts and the physical and mechanical conditions that occur in it is of great importance. In the developed mathematical model, the main factor influencing the physical and mechanical properties of raw cotton is the change in temperature. Due to the temperature, kinetic and biological processes accumulated in the raw cotton in Bunt, it can spread over a large surface, first in a small-local state, over time with a nonlinear law. As a result, small changes in temperature lead to a qualitative change in physical properties. In determining the law of temperature distribution in the raw cotton in Bunt, Laplace’s differential equation of heat transfer was used. The differential equation of heat transfer in Laplace’s law was replaced by a system of ordinary differential equations by approximation. Conditions are solved in MAPLE-17 program by numerical method. As a result, graphs of temperature changes over time in raw cotton were obtained. In addition, the table shows the changes in density, pressure and mass of cotton, the height of the bun. As the density of the cotton raw material increases from the top layer of the bunt to the bottom layer, an increase in the temperature in it has been observed. This leads to overheating of the bottom layer of cotton and is the main reason for the deterioration of the quality of raw materials.
文摘Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.
文摘This paper deals with the increasing safety of working in aggressive potential locations, having SCADA system and WSN sensors, using a “probabilistic strategy” in comparison with a “deterministic” one, modeling/simulation and application in underground coal mining. In general, three conditions can be considered: 1) an unfriendly environment that facilitates the risk of accidents, 2) aggressive equipments that can compete to cause accidents and 3) the work security breaches that can cause accidents. These conditions define the triangle of accidents and are customized for an underground coal mining where the methane gas is released with the exploitation of the massive coal. In this case, the first two conditions create an explosive potential atmosphere. To allow people to work in a safe location it needs: first, a continuing monitoring through SCADA system of the explosive potential atmosphere and second, the use of antiexplosive equipment. This method, named “deterministic strategy”, increases the safety of working, but the explosions have not been completely eliminated. In order to increase the safety of working, the paper continues with the presentation of a new method based on hazard laws, named “probabilistic strategy”. This strategy was validated through modeling/simulation using CupCarbon software platform, and application of WSN networks implemented on Arduino equipments. At the end of the paper the interesting conclusions are emphases which are applicable to both strategies.
文摘We consider a problem from stock market modeling, precisely, choice of adequate distribution of modeling extremal behavior of stock market data. Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are the classical distributions for this problem. However, from 2004, [1] and many other researchers have been empirically showing that generalized logistic (GL) distribution is a better model than GEV and GP distributions in modeling extreme movement of stock market data. In this paper, we show that these results are not accidental. We prove the theoretical importance of GL distribution in extreme value modeling. For proving this, we introduce a general multivariate limit theorem and deduce some important multivariate theorems in probability as special cases. By using the theorem, we derive a limit theorem in extreme value theory, where GL distribution plays central role instead of GEV distribution. The proof of this result is parallel to the proof of classical extremal types theorem, in the sense that, it possess important characteristic in classical extreme value theory, for e.g. distributional property, stability, convergence and multivariate extension etc.
文摘This article describes how the cartographic depth-to-water (DTW) index in combination with other variables can be used to quantify, model and map the distribution of common forest floor bryophytes, at 1 m resolution. This was done by way of a case study, using 12 terrain and climate representative locations across New Brunswick, Canada. The presence/absence by moss species was determined at each location along upland-to-wetland transects within >10-m spaced 1-m2 forest floor plots. It was found that Bazzania trilobata, Dicranum polysetum, Polytrichum commune, Hylocomium splendens, and Pleurozium schreberi had greater probabilities of occurrence in well-drained forested areas, whereas Sphagnum fuscum and Sphagnum girgensohnii dominated in low-lying wet areas. The presence/absence of each species was quantified by way of logistic regression analyses, using DTW, slope, canopy closure, forest litter depth, ecosite type (8 classes), nutrient regime (4 classes, poor to rich);vegetation type (deciduous, coniferous, mixed, and shrubs), and macro- and micro-topography (upland, wetland;mounds, pits) as predictor variables. Among these, log10DTW and forest litter depth were the most consistent predictor variables, followed by mound versus pit. For the mapping purpose, only log10DTW and already mapped classifications for upland versus wetland and vegetation type were used to predict the probability of occurrences for the most frequent moss species, namely, D. polysetum, P. schreberi and Sphagnum spp. The overall accuracy for doing this ranged from 67% to 83%, with false positives and negatives amounting to 18% to 42%. The overall classification accuracy exceeded the probability by chance alone at 76.8%, with the significance level reached at 75.3%. The average level of probability by chance alone was 60.3%.
文摘The large excess of solid waste generated in cities is a result of population growth and economic development. Properly managing this municipal solid waste (MSW) is a challenge, mainly in underdeveloped and developing countries where financial concerns are an added problem. From the environmental point of view, a major issue is properly disposing MSW taking into consideration a wide range of factors, and working with different spatial data. In this study, we used geographic information system (GIS) to perform multi-criteria decision analysis (MCDA) conducted by analytical hierarchy process (AHP). The development of the environmental impact susceptibility model (EISM) for municipal solid waste disposal sites (MSWDS) applied to the state of Sao Paulo, Brazil considered factors such as geology, pedology, geomorphology, water resources, and climate represented by fifteen associated sub-factors. The results indicated that more than 82% of Sao Paulo’s territory is situated in areas with very low, low, and medium environmental impact susceptibility categories. However, in the remaining 18% of the state land area, 85 landfills are located in areas with high and very high environmental impact susceptibility categories. These results are alarming because these 85 landfills receive approximately 17,886 tons of MSW on a daily basis, which corresponds to 46% of all municipal solid waste disposed in Sao Paulo state. Therefore, decision makers, urban planners and policymakers could use the findings of the EISM towards mitigating the environmental impacts caused by MSWDS.
基金the Chinese Academy of Sciences Pioneer Hundred Talents Program and the Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0708)supported by a MEXT(Ministry of Education,Culture,Sports,Science and Technology)KAKENHI(Grants-in-Aid for Scientific Research)grant(Grant No.21H05203)Kobe University Strategic International Collaborative Research Grant(Type B Fostering Joint Research).
文摘The intracontinental subduction of a>200-km-long section of the Tajik-Tarim lithosphere beneath the Pamir Mountains is proposed to explain nearly 30 km of shortening in the Tajik fold-thrust belt and the Pamir uplift.Seismic imaging revealed that the upper slab was scraped and that the lower slab had subducted to a depth of>150 km.These features constitute the tectonic complexity of the Pamirs,as well as the thermal subduction mechanism involved,which remains poorly understood.Hence,in this study,high-resolution three-dimensional(3D)kinematic modeling is applied to investigate the thermal structure and geometry of the subducting slab beneath the Pamirs.The modeled slab configuration reveals distinct along-strike variations,with a steeply dipping slab beneath the southern Pamirs,a more gently inclined slab beneath the northern Pamirs,and apparent upper slab termination at shallow depths beneath the Pamirs.The thermal field reveals a cold slab core after delamination,with temperatures ranging from 400℃to 800℃,enveloped by a hotter mantle reaching~1400℃.The occurrence of intermediate-depth earthquakes aligns primarily with colder slab regions,particularly near the slab tear-off below the southwestern Pamirs,indicating a strong correlation between slab temperature and seismicity.In contrast,the northern Pamirs exhibit reduced seismicity at depth,which is likely associated with thermal weakening and delamination.The central Pamirs show a significant thermal anomaly caused by a concave slab,where the coldest crust does not descend deeply,further suggesting crustal detachment or mechanical failure.The lateral asymmetry in slab temperature possibly explains the mechanism of lateral tearing and differential slab-mantle coupling.
文摘Multinomial logistic regression (MNL) is an attractive statistical approach in modeling the vehicle crash severity as it does not require the assumption of normality, linearity, or homoscedasticity compared to other approaches, such as the discriminant analysis which requires these assumptions to be met. Moreover, it produces sound estimates by changing the probability range between 0.0 and 1.0 to log odds ranging from negative infinity to positive infinity, as it applies transformation of the dependent variable to a continuous variable. The estimates are asymptotically consistent with the requirements of the nonlinear regression process. The results of MNL can be interpreted by both the regression coefficient estimates and/or the odd ratios (the exponentiated coefficients) as well. In addition, the MNL can be used to improve the fitted model by comparing the full model that includes all predictors to a chosen restricted model by excluding the non-significant predictors. As such, this paper presents a detailed step by step overview of incorporating the MNL in crash severity modeling, using vehicle crash data of the Interstate I70 in the State of Missouri, USA for the years (2013-2015).
基金This paper is funded by the national key project"The Belt and Road"talent recruitment project named:Comparison of Mining Subsidence Research in China and Poland(No.G2017001).Part of the research was financed from the Grant for Statutory Research AGH-University of Science and Technology in Krakow,Poland No.16.16.150.545.
文摘Mathematical modeling of surface deformations caused by underground mining operation is commonly carried out with use of empirical,numerical or stochastic models.One of the most frequently applied model for prediction of ground deformation in many countries is Knothe model.The model developed by Knothe belongs to the stochastic methods and is based on the influence function.In China a prediction method named Probability Integration Method(PIF)was established by Liu Baochen and Liao Guohua based on the stochastic medium theory.Modified version of that model allows to predict ground movements caused by mining operation in extremely complex technical and geological conditions.That model is commonly applied for coal,metal ore and salt deposits.The article presents several modifications of the mathematical model used in China and Poland.This model is very widespread in the world,therefore the generalizations proposed in the article can be implemented for the purposes of prediction surface deformations for various types of deposits in many countries.The presented generalizations were then tested on specific examples of coal mining,copper ore mining and rock salt deposit.The obtained results indicate high efficiency of methods based on the influence function in complex geological and mining conditions.
文摘Recently, velocity prediction and modeling have been focus of the geophysical exploration in the high temperature and high pressure of the south China sea area, especially for new offshore exploratory areas. The error is large with great difficulty owing to fewer exploratory wells and misunderstanding. Firstly, on the basis of three typical velocity prediction and modeling examples in Ying-Qiong basin, it’s easy to put forward the corresponding not common but urgent problem in each instance, then combined with the velocity problem and misunderstanding to expand method discussion and solution, which include geological model to guide the velocity interpretation and analysis, the establishment of forward velocity of the auxiliary model explaining and constructing high precision velocity model. This research basically solves existing velocity problems in gas exploration of south China sea in recent years, and proposes corresponding solution and application, which is of great significance to the further exploration and productive practice.
基金supported by the Aeronautical Science Foundation of China(20135153031 20135553035 2017ZC53033)
文摘In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law.
文摘The cooling of the Cenozoic, including the Miocene epoch, was punctuated by many geologically abrupt warming and cooling episodes— strong deviations from the cooling trend with time span of ten to hundred thousands of years. Our working hypothesis is that some of those warming episodes at least partially might have been caused by dynamics of the Antarctic Ice Sheet, which, in turn, might have caused strong changes of sea surface salinity in the Miocene Southern Ocean. Feasibility of this hypothesis is explored in a series of offline-coupled ocean-atmosphere computer experiments. The results suggest that relatively small and geologically short-lived changes in freshwater balance in the Southern Ocean could have significantly contributed to at least two prominent warming episodes in the Miocene. Importantly, the scenario-based experiments also suggest that the Southern Ocean was more sensitive to the salinity changes in the Miocene than today, which can attributed to the opening of the Central American Isthmus as a major difference between the Miocene and the present-day ocean-sea geometry.
文摘Problem statement: The results of the study of seism acoustic emission arising in a porous two-phase geological environment under acoustic influence are presented. Acoustic emission arising in reservoirs of oil fields using good observations is considered. The regularity of the emission processes of acoustic emission, which manifests itself in the form of discrete spectra of signals similar to oscillations of nonlinearly coupled oscillators, is shown. Spectra have special characteristics for each type of rock. Applied method and design: An algorithm for modeling the process of resonant acoustic response of a porous fluid-saturated reservoir with hierarchical structure and plastic properties on acoustic frequency excitation is developed. That algorithm is developed as an iterative process for the solution integral and integral-differential equations. The frequencies that are parameters of the direct problem are used from the spectra of observed data of acoustic emission in the oil wells. Typical results: For the first time, it had been found the relation between resonant frequencies of the acoustic emission and plastic properties, these values of frequencies had been used in the algorithm of modeling distribution of longitudinal waves in the fluid saturated nonlinear plastic environment. Concluding note (Practical value/implications): The analysis of these emission processes can serve as a source of information about the filtration-capacitive properties of productive reservoirs of a porous type with a hierarchical structure. It is used by practical data of oil fields of Western Siberia.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband networks.However,they consume important and scarce network resources such as bandwidth and processing power.There have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial losses.This paper draws its motivation from such real network disaster incidents attributed to signaling storms.In this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and countermeasures.We provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding solutions.Another important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a table.This paper presents an update and an extension of our earlier conference publication.To our knowledge,no similar survey study exists on the subject.
文摘In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is proposed from the genetic algorithm with important additional strategies, and consequently yields a faster convergence and a more accurate search. Firstly, MGA-based identification method is used to identify the parameters of the nonlinear PAM manipulator described by an ARX model in the presence of white noise and this result will be validated by MGA and compared with the simple genetic algorithm (GA) and LMS (Least mean-squares) method. Secondly, the intrinsic features of the hysteresis as well as other nonlinear disturbances existing intuitively in the PAM system are estimated online by a Modified Recursive Least Square (MRLS) method in identification experiment. Finally, a highly efficient self-tuning control algorithm Minimum Variance Control (MVC) is taken for tracking the joint angle position trajectory of this PAM manipulator. Experiment results are included to demonstrate the excellent performance of the MGA algorithm in the NARX model-based MVC control system of the PAM system. These results can be applied to model, identify and control other highly nonlinear systems as well.
