Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection,a fundamental process that enables the transfer of mass,energy,and momentum from the solar wind into the magnetosphere.The spatial and temporal properties of the magnetopause,under varying solar and magnetospheric conditions,remain largely unknown because empirical studies using in-situ observations are challenging to interpret.Global wide field-of-view(FOV)imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and,subsequently,quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere.Two upcoming missions,ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays,an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms.High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary,the magnetopause,and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation.This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and,with this,identify the location of the magnetopause over the Sun−Earth line.To do so,we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information.Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images.Also,our proposed methodology shows that the accuracy of both three-dimensional(3-D)estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Effects of Chlorine and Chlorine Monoxide on Stratospheric Ozone Depletion

This paper presents a system approach of mass balance calculations of ozone and other species under diffusion-convection-reaction processes to study the impacts of major ozone-depleting chemicals, chlorine (Cl) and chlorine monoxide (ClO), and the effect of photolysis on ozone concentrations, ozone depletion, total ozone abundance, and ozone layer along the altitude in the stratosphere. The calculated ozone concentrations and profile of the layer followed a similar trend and were generally in good agreement with the measurements above the tropical area. The calculated peak of the layer was at the same mid-stratosphere at Z = 30 km with a peak concentration and total ozone abundance about 20% higher than the measured peak concentration of 8.0 ppm and total abundance of 399 DU. In the presence of Cl and ClO, the calculated ozone concentrations and total abundance were substantially reduced. Cl generally depleted more uniformly of ozone across the altitude, while ClO reduced substantially the ozone in the upper stratosphere and thus shifted the peak of the layer to a much lower elevation at Z = 14 km. Although both ClO and Cl are active ozone-depleting chemicals, ClO was found to have a more pronounced impact on ozone depletion and distribution than Cl. The possible explanations of these interesting phenomena were discussed and elaborated. The approach and calculations in this paper were shown to be useful in providing an initial insight into the structure and behavior of the complex ozone layer.

Calculations and Sensitivity Analysis of Chlorine-,NO_(x)-,and Bromine-Depleting Cycles of Stratospheric Ozone

This paper presents an engineering system approach using a 2D model of conservation of mass to study the dynamics of ozone and concerned chemical species in the stratosphere.By considering all fourteen photolysis,ozone-generating,and-depleting chemical reactions,the model calculated the transient,spatial changes of ozone under different physical-chemical-radiative conditions.Validation against the measured data demonstrated good accuracy,close match of our model with the observed ozone concentrations at both 20°S and 90°N locations.The deviation in the average concentration was less than 1% and in ozone profiles less than 17%.The impacts of various chlorine-(Cl),nitrogen oxides-(NO_(x)),and bromine-(Br)depleting cycles on ozone concentrations and distribution were investigated.The chlorine catalytic depleting cycle was found to exhibit the most significant impact on ozone dynamics,confirming the key role of chlorine in the problem of ozone depletion.Sensitivity analysis was conducted with levels of 25%,50%,100%,200%,and 400% of the baseline value.The combined cycles(Cl+NO_(x)+Br)showed the most significant influence on ozone behavior.The total ozone abundance above the South Pole could decrease by a small 3%,from 281 DU(Dubson Units)to 273 DU for the 25% level,or by a huge thinning of 60%to 114 DU for the 400% concentration level.When the level of chlorine gases increased beyond 200%,it would cause ozone depletion to a level of ozone hole(below 220 DU).The 2D Ozone Model presented in this paper demonstrates robustness,convenience,efficiency,and executability for analyzing complex ozone phenomena in the stratosphere.

2-D Modeling and Calculations of Stratospheric Ozone and Influences of Convection, Diffusion, and Time

An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone DO3 and active atomic oxygen DO on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen DO was found to be more sensitive and important than that of ozone DO3 on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .

Alcohol-induced alterations of the hepatocyte cytoskeleton

The hepatocyte cytoskeleton consists of three fi lamentous networks: microtubules, actin microfi laments and keratin intermediate filaments. Because of the abundance of the proteins that comprise each system and the central role each network plays in a variety of cellular processes, the three fi lament systems have been the focus of a host of studies aimed at understanding the progression of alcohol-induced liver injury. In this review, we will briefly discuss the hepatic organization of each cytoskeletal network and highlight some components of each system. We will also describe what is known about ethanol-induced changes in the dynamics and distributions of each cytoskeletal system and discuss what is known about changes in protein expression levels and post-translational modifi cations. Finally, we will describe the possible consequences of these cytoskeletal alterations on hepatocyte function and how they might contribute to the progression of liver disease.

An overview of a unified theory of dynamics of vehicle–pavement interaction under moving and stochastic load

This article lays out a unified theory for dynamics of vehicle-pavement interaction under moving and stochastic loads. It covers three major aspects of the subject： pavement surface, tire-pavement contact forces, and response of continuum media under moving and stochastic vehicular loads. Under the subject of pavement surface, the spectrum of thermal joints is analyzed using Fourier analysis of periodic function. One-dimensional and two-dimensional random field models of pavement surface are discussed given three different assumptions. Under the subject of tire-pavement contact forces, a vehicle is modeled as a linear system. At a constant speed of travel, random field of pavement surface serves as a stationary stochastic process exciting vehicle vibration, which, in turn, generates contact force at the interface of tire and pavement. The contact forces are analyzed in the time domain and the frequency domains using random vibration theory. It is shown that the contact force can be treated as a nonzero mean stationary process with a normal distribution. Power spectral density of the contact force of a vehicle with walking-beam suspension is simulated as an illustration. Under the subject of response of continuum media under moving and stochastic vehicular loads, both time-domain and frequency-domain analyses are presented for analytic treatment of moving load problem. It is shown that stochastic response of linear continuum media subject to a moving stationary load is a nonstationary process. Such a nonstationary stochastic process can be converted to a stationary stochastic process in a follow-up moving coordinate.

Exact Statistical Distribution of the Body Mass Index (BMI): Analysis and Experimental Confirmation

Body Mass Index (BMI), defined as the ratio of individual mass (in kilograms) to the square of the associated height (in meters), is one of the most widely discussed and utilized risk factors in medicine and public health, given the increasing obesity worldwide and its relation to metabolic disease. Statistically, BMI is a composite random variable, since human weight (converted to mass) and height are themselves random variables. Much effort over the years has gone into attempts to model or approximate the BMI distribution function. This paper derives the mathematically exact BMI probability density function (PDF), as well as the exact bivariate PDF for human weight and height. Taken together, weight and height are shown to be correlated bivariate lognormal variables whose marginal distributions are each lognormal in form. The mean and variance of each marginal distribution, together with the linear correlation coefficient of the two distributions, provide 5 nonadjustable parameters for a given population that uniquely determine the corresponding BMI distribution, which is also shown to be lognormal in form. The theoretical analysis is tested experimentally by gender against a large anthropometric data base, and found to predict with near perfection the profile of the empirical BMI distribution and, to great accuracy, individual statistics including mean, variance, skewness, kurtosis, and correlation. Beyond solving a longstanding statistical problem, the significance of these findings is that, with knowledge of the exact BMI distribution functions for diverse populations, medical and public health professionals can then make better informed statistical inferences regarding BMI and public health policies to reduce obesity.

Validation of Novel Model for Identification of Thermal Conditions in the Low Corona

The electron density and temperature key properties of the neutral-magnetized plasma in the solar corona, which are predicted with a novel model, provide an interesting window along the whole solar cycle. In this work, we test the quantitative validity of the model and prove that the Coronal Density and Temperature (CODET) is reliable. Furthermore, this work contrasts the CODET model results with alternative observational remote and in-situ datasets during the simplest conditions of the quiescent corona near the solar minimum. This successful outcome/validation of the CODET model allowed a good qualitative density and temperature retrieval in the solar corona covering a large portion of time interval from solar cycles 23 and 24.

Calculations of Stratospheric Ozone and Effects of Diffusivity

This paper presents a system approach of mass balance of ozone and other species under diffusion-convection-reaction processes to study the ozone layer along the altitude in the stratosphere. The ozone abundance and general distribution above the tropical area were calculated and compared to the published measured data. The peak ozone layer was found to be 21 mPa at 22 km or 9.7 ppm at 30 km, and the involved competing processes depicting the ozone layer were explained in details. In the entire stratosphere from 10 km to 50 km, the calculated ozone distribution displayed a similar profile and trend to the observational data, with the calculation in ppm slightly above the measurement by 12%. The standard deviation of the differences between calculated and measured data was close to 0.25. A sensitivity study of gas diffusivities of molecular ozone D3 and atomic oxygen D1 on changing the ozone abundance and profile in the stratosphere showed that in the upper two-third of the stratosphere, D1 evidently exhibited a pronounced impact on ozone, as much as 24-fold larger than D3. The mechanism leading to this finding was also elaborated. The approach and calculations in this paper are shown to be useful for providing an initial insight into the structure and behavior of the complex ozone layer.

Modelling,Validation,and Calculations of Stratospheric Ozone Dynamics and Latitudinal Changes

This paper presents an engineering system approach of 2-D cylindrical model of mass balance calculations with convection,diffusion,and all potential photolysis,ozone generating and depleting chemical reactions considered.This model was developed,validated,and tested under different conditions for the stratospheric ozone.The calculated ozone concentrations and profile in the stratosphere at both the Equator and mid-latitudinal location of 40°S were found to exhibit a similar and close profile and peak value of the published measured data.The discrepancy between the calculations and measurements for the average ozone concentration was shown to be less than 1%and the variation of distributions to be less than 19%.The latitudinal changes of ozone concentrations,distribution,and peak of the layer were found to shift from 9.41 ppm at mid-altitude of z=30 km at the Equator,to 7.81 ppm at z=34.5 km at 40°S,to 5.78 ppm at higher altitude z=39 km at the South Pole.The total ozone abundances at strategic latitudes at 0°S,20°S,40°S,60°S,and 90°S,were found to remain stable and not much changed,from 305 DU to 335 DU,except a smaller value of 288 DU at the South Pole.The possible explanations of ozone profile change and peak shifting as affected by solar/UV radiation,latitudinal locations,and ozone-depleting reactions were discussed and elaborated.The 2-D ozone Model presented in this paper is a robust,efficient,executable,and validated model for studying the complex ozone phenomena in the stratosphere.

Thermodynamic Interpretation of Electron Density and Temperature Description in the Solar Corona

We reach a thermodynamic interpretation of the CODET model and its accurate electron density and temperature prediction, grounded on the physics of hydro magnetism in global equilibrium. The thermodynamic interpretation finds consistency with the model of a magneto-matter medium possessing a 3-D Langmuir structure. That medium is diamagnetic in the context of ideal magnetohydrodynamic (MHD). It is shown that this magneto-matter has unusual characteristics consistent with assuming that the low quiescent solar corona possesses a nature-state, non yet studied. It is further noticed that this is wholly consistent with the CODET model prediction of a polytropic anomalous index for the electron gas of the Sun’s corona. Constitutive properties are derived from this novel state of nature, like magnetic permeability properties and non-dispersive acoustic speed. This non-dispersive acoustic speed is also expected to predict the observed equilibration time for the 1.1 to 1.3R⊙ quiescent corona during the solar minimum from 2008 to 2009.

Designand development of highway tunnel maintenance and management system

In order to solve the urgent problem of how to manage and sustain highway tunnels with advanced information technology with the background of the rapid development in the modem traffic, and achieve the cost- effectiveness optimal principle objectives under the premise of guaranteeing a smooth flow of traffic; a highway tunnel maintenance and management system framework and the key modules were proposed. First, the determined highway tunnel condition assessment index system was established according to the result of expert consulting forms. Secondly, the tunnel diseases, the corresponding maintenance measurements, and many-to-many relationship between diseases and maintenance measurements were introduced. Then, three kinds of 0-1 integer programming models were built according to different tunnel operators＇ needs in the optimization decision module. Finally, the further development and implementation of the system was prospected. The research results can provide references to tunnel researchers and managers.

Advanced Computing for Cardiovascular Disease Prediction

Developing a predictive model for detecting cardiovascular diseases (CVDs) is crucial due to its high global fatality rate. With the advancements in artificial intelligence, the availability of large-scale data, and increased access to computational capability, it is feasible to create robust models that can detect CVDs with high precision. This study aims to provide a promising method for early diagnosis by employing various machine learning and deep learning techniques, including logistic regression, decision trees, random forest classifier, extreme gradient boosting (XGBoost), and a sequential model from Keras. Our evaluation identifies the random forest classifier as the most effective model, achieving an accuracy of 0.91, surpassing other machine learning and deep learning approaches. Close behind are XGBoost (accuracy: 0.90), decision tree (accuracy: 0.86), and logistic regression (accuracy: 0.70). Additionally, our deep learning sequential model demonstrates promising classification performance, with an accuracy of 0.80 and a loss of 0.425 on the validation set. These findings underscore the potential of machine learning and deep learning methodologies in advancing cardiovascular disease prediction and management strategies.

Relationship between oxidative stress and hepatic glutathione levels in ethanol-mediated apoptosis of polarized hepatic cells

AIM： To investigate the role of reactive oxygen species （ROS） in ethanol-mediated cell death of polarized hepatic （WlF-B） cells.METHODS： In this work, WIF-B cultures were treated with pyrazole （inducer of cytochrome P4502E1, CYP2E1） and/or L-buthionine sulfoximine （BSO）, a known inhibitor of hepatic glutathione （GSH）, followed by evaluation of ROS production, antioxidant levels, and measures of cell injury （apoptosis and necrosis）.RESULTS： The results revealed that ethanol treatment alone caused a significant two-fold increase in the activation of caspase-3 as well as a similar doubling in ROS. When the activity of the CYP2E1 was increased by pyrazole pretreatment, an additional two-fold elevation in ROS was detected. However, the CYP2EIrelated ROS elevation was not accompanied with a correlative increase in apoptotic cell injury, but rather was found to be associated with an increase in necrotic cell death. Interestingly, when the thiol status of the cells was manipulated using BSO, the ethanol-induced activation of caspase-3 was abrogated. Additionally, ethanol-treated cells displayed enhanced susceptibility to Fas-mediated apoptosis that was blocked by GSH depletion as a result of diminished caspase-8 activity.CONCLUSION： Apoptotic cell death induced as a consequence of ethanol metabolism is not completely dependent upon ROS status but is dependent on sustained GSH levels,

A comparative study of name resolution and routing mechanisms in 网 information-centric networks

Information-Centric Networking (ICN) is an innovative paradigm for the future internet architecture, which addresses IP network limitations in supporting content distribution and information access by decoupling content from hosts and providing the ability to retrieve a content object by its name (identifier), rather than its storage location (IP address). Name resolution and routing is critical for content retrieval in ICN networks. In this research, we perform a comparative study of two widely used classes of ICN name resolution and routing schemes, namely flooding and Distributed Hash Table (DHT). We consider the flooding-based routing in Content-Centric Networks due to its wide acceptance. For the DHT scheme, we design a multi-level DHT that takes into account the underlying network topology and uses name aggregation to further reduce control overhead and improve network efficiency. Then, we compare the characteristics and performance of these two classes of name resolution and routing through extensive simulations. The evaluation results show that the performances of these two approaches are reliant on several factors, including network size, content location dynamics, and content popularity. Our study reveals insights into the design tradeoffs and offers guidelines for design strategies.

Effects of ORC Working Fluids on Combined Cycle Integrated with SOFC and ORC for Stationary Power Generation

The purpose of this study is to explore the effects of working fluid on conventional combined cycle integrated with pressurized solid oxide fuel cell (SOFC) and waste heat recovery organic Rankine cycle (ORC) for stationary utility power generation. The mathematical model of a natural gas fueled design configuration is developed in Matlab and Simulink and simulated with 14 working fluids. The effluent gases of SOFC undergo combustion in the combustion chamber and it is utilized in the gas turbine, steam turbine cycle and ORC. The model is compared with those found in literature and the parametric studies of temperature, flow rate, fuel utilization factor and exhaust gas on the system efficiency are examined. Results revealed that working fluids show a closely related behavior in efficiency at low pressure ratio and high flow fraction, fuel utilization, and temperature. R-123 was found to perform the best among 14 working fluids studied, yielding a system energy efficiency of 70% in the combined cycle integrated with SOFC and ORC.

EXPERIMENTAL STUDY OF GAS—SOLID SUSPENSION FLOWS IN VORTEXING FLUIDIZED BED CHAMBER FREEBOARD

Gas flows and particle mass flux were measured and clutriation experimentswere conducted in two cold test models of vortexing fluidized bed(VFB).The experimen-tal results show that the secondary air injected tangentially creates strong vortexes,estab-lishes particle suspension layers and internal circulation,and suppresses the elutriation offine particles greatly.The vortexing fluidized bed combustion has bright prospect bccauseof its much higher combustion efficiency and desulphidation efficiency than bubblingfluidized bed combustion due to long particle residence time and high slip velocity betweengas and solid,and its simpler configuration and lower cost than circulating fluidized bedcombustion.

Cooperative spectrum sharing of multiple primary users and multiple secondary users

This paper proposes a multiple-input multiple-output （MIMO） based cooperative dynamic spectrum access （DSA） framework that enables multiple primary users （PUs） and multiple secondary users （SUs） to cooperate in spectrum sharing. By exploiting MIMO in cooperative DSA, SUs can relay the primary traffic and send their own data at the same time, which greatly improves the performance of both PUs and SUs when compared to the non- MIMO time-division spectrum sharing schemes. Especially, we focus on the relay selection optimization problem among multiple PUs and multiple SUs. The network-wide cooperation and competition are formulated as a bargaining game, and an algorithm is developed to derive the optimal PU-SU relay assignment and resource allocation. Evaluation results show that both primary and secondary users achieve significant utility gains with the proposed framework, which gives all of them incentive for cooperation.

CaCo_1-xRu_xO_y: Role of Ru/Co Ratio on Its Transport Properties

Calcium cobaltites, especially Ca3Co4O9 with a misfit layered structure, are promising thermoelectric materials due to their suitability for high temperature applications and low densities. The existence of low spin-state electronic configurations for both and species is one of the key parameter to explain the large thermopower values. Ruthenium oxide, with a layered structure, exhibits strong electron-electron correlation and the extended nature of their 4d electrons enhances orbital overlapping which is expected to influence the transport characteristics of CaCo1-xRuxOy (CCR) samples, by affecting the spin state of the 3d Co ions. The effect on thermopower and electrical resistivity due to partial substitution of Co by Ru ions, up to 0.33 moles, from 300 to 600 K was investigated. A sharp decline in resistivity and in thermopower was observed until a transition ion ratio (TIR), (Ru/(Ru + Co)), of 0.5 is reached, beyond which both the properties became less sensitive to TIR. These variations in the transport properties are explained by the presence of 4d Ru in close proximity to the Co, which could influence the spin and oxidation state of Co ions. The Co rich and Ru rich samples exhibit very distinct microstructures and phase assemblages.

Prediction of Wine Quality Using Machine Learning Algorithms

As a subfield of Artificial Intelligence (AI), Machine Learning (ML) aims to understand the structure of the data and fit it into models, which later can be used in unseen data to achieve the desired task. ML has been widely used in various sectors such as in Businesses, Medicine, Astrophysics, and many other scientific problems. Inspired by the success of ML in different sectors, here, we use it to predict the wine quality based on the various parameters. Among various ML models, we compare the performance of Ridge Regression (RR), Support Vector Machine (SVM), Gradient Boosting Regressor (GBR), and multi-layer Artificial Neural Network (ANN) to predict the wine quality. Multiple parameters that determine the wine quality are analyzed. Our analysis shows that GBR surpasses all other models’ performance with MSE, R, and MAPE of 0.3741, 0.6057, and 0.0873 respectively. This work demonstrates, how statistical analysis can be used to identify the components that mainly control the wine quality prior to the production. This will help wine manufacturer to control the quality prior to the wine production.