Search results for: nutrient dynamics

Authors: Md. Jahoor Alam

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Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.

Keywords: oscillation, temporal behavior, p53, glucose

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Authors: Mingyu Xie, Mietek Brdys

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The paper develops a non-linear model predictive control (NMPC) of water quality in drinking water distribution systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives

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Authors: Byung Cheol Kim

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This study explores a method for the signal-noise separation challenge in project control, focusing on the limitations of traditional deterministic approaches that use single-point performance metrics to predict project outcomes. We detail how traditional methods often overlook future uncertainties, resulting in tracking biases when reliance is placed solely on immediate data without adjustments for predictive accuracy. Our investigation led to the development of the Predictive Tracking Project Control (PTPC) framework, which incorporates network simulation and Bayesian control models to adapt more effectively to project dynamics. The PTPC introduces controlled disturbances to better identify and separate tracking biases from useful predictive signals. We will demonstrate the efficacy of the PTPC with examples, highlighting its potential to enhance real-time project monitoring and decision-making, marking a significant shift towards more accurate project management practices.

Keywords: predictive tracking, project control, signal-noise separation, Bayesian inference

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Authors: Baoshan Huang, Fanbiao Bao, Bing Li, Lianghua Zeng, Yi Zheng

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Parameter control strategy based on statistical characteristics can analyze the choice of the transmission ratio of an automobile transmission. According to the difference of the transmission gear, the number and spacing of the gear can be determined. Transmission ratio distribution of transmission needs to satisfy certain distribution law. According to the statistic characteristics of driving parameters, the shift control strategy of the vehicle is analyzed. CVT shift schedule adjustment algorithm based on statistical characteristic parameters can be seen from the above analysis, if according to the certain algorithm to adjust the size of, can adjust the target point are in the best efficiency curve and dynamic curve between the location, to alter the vehicle characteristics. Based on the dynamic characteristics and the practical application of the vehicle, this paper presents the setting scheme of the transmission ratio.

Keywords: vehicle dynamics, transmission ratio, transmission parameters, statistical characteristics

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Authors: V. Markogianni, D. Kalivas, G. Petropoulos, E. Dimitriou

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Lake water quality monitoring in combination with the use of earth observation products constitutes a major component in many water quality monitoring programs. Landsat 8 images of Trichonis Lake (Greece) acquired on 30/10/2013 and 30/08/2014 were used in order to explore the possibility of Landsat 8 to estimate water quality parameters and particularly CDOM absorption at specific wavelengths, chlorophyll-a and nutrient concentrations in this oligotrophic freshwater body, characterized by inexistent quantitative, temporal and spatial variability. Water samples have been collected at 22 different stations, on late August of 2014 and the satellite image of the same date was used to statistically correlate the in-situ measurements with various combinations of Landsat 8 bands in order to develop algorithms that best describe those relationships and calculate accurately the aforementioned water quality components. Optimal models were applied to the image of late October of 2013 and the validation of the results was conducted through their comparison with the respective available in-situ data of 2013. Initial results indicated the limited ability of the Landsat 8 sensor to accurately estimate water quality components in an oligotrophic waterbody. As resulted by the validation process, ammonium concentrations were proved to be the most accurately estimated component (R = 0.7), followed by chl-a concentration (R = 0.5) and the CDOM absorption at 420 nm (R = 0.3). In-situ nitrate, nitrite, phosphate and total nitrogen concentrations of 2014 were measured as lower than the detection limit of the instrument used, hence no statistical elaboration was conducted. On the other hand, multiple linear regression among reflectance measures and total phosphorus concentrations resulted in low and statistical insignificant correlations. Our results were concurrent with other studies in international literature, indicating that estimations for eutrophic and mesotrophic lakes are more accurate than oligotrophic, owing to the lack of suspended particles that are detectable by satellite sensors. Nevertheless, although those predictive models, developed and applied to Trichonis oligotrophic lake are less accurate, may still be useful indicators of its water quality deterioration.

Keywords: landsat 8, oligotrophic lake, remote sensing, water quality

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Authors: Prashant G. Metri

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A numerical model is developed to study nano liquid film flow over an unsteady stretching sheet in the presence of hydromagnetic have been investigated. Similarity transformations are used to convert unsteady boundary layer equations to a system of non-linear ordinary differential equations. The resulting non-linear ordinary differential equations are solved numerically using Runge-Kutta-Fehlberg and Newton-Raphson schemes. A relationship between film thickness β and the unsteadiness parameter S is found, the effect of unsteadiness parameter S, and the hydromagnetic parameter S, on the velocity and temperature distributions are presented. The present analysis shows that the combined effect of magnetic field and viscous dissipation has a significant influence in controlling the dynamics of the considered problem. Comparison with known results for certain particular cases is in excellent agreement.

Keywords: boundary layer flow, nanoliquid, thin film, unsteady stretching sheet

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Authors: M. Fozan Ur Rab, Mahrukh, M. Alam, N. Sheikh

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The purpose of this study is to analyze various high lift low Reynolds number airfoils using two-dimensional Computational Fluid Dynamics (CFD) code in the isolated flow field and select optimum airfoil to suit the motorsports application. The airfoil is selected after comparing the stall behavior, transition location, pressure recovery, pressure distribution and boundary layer characteristics of various airfoils. The prime consideration while selecting airfoil is highest Cl while achieving the sustainable performance over a range of Reynolds numbers encountered on the race track. The increase in Cl is always accompanied by the increase in Cd but this must be compromised since the main goal is to increase an aerodynamic grip. It is always desirable to increase the down-force in Formula One (F1)/Formula Student (FS) to gain reduction in lap time. This paper establishes the criteria for selection of high lift low Reynolds number airfoil while considering various parameters which affect the performance of airfoils.

Keywords: aerodynamics, airfoil, downforce, formula student, lap time

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Authors: Alla V. Goncharova, Tatyana A. Karpenyuk, Yana S. Tsurkan, Rosa U. Beisembaeva, Togzhan D. Mukasheva, Ludmila V. Ignatova, Ramza Z. Berzhanova

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In this work the effect of culturing conditions of filamentous fungi Penicillium raistrickii, Penicillium anatolicum, Fusarium sp. on biomass yield, the content of total lipids and fatty acids was studied. It has been established that in time the process of lipids accumulation correlated with biomass growth of cultures, reaching maximum values in stationary growth phase. Biomass yield and accumulation of general lipids was increased by adding zinc to the culture medium. The more intensive accumulation of biomass and general lipids was observed at temperature 18°C. Lowering the temperature of culturing has changed the ratio of saturated: Unsaturated fatty acids in the direction of increasing the latter.

Keywords: biomass, culturing conditions, fungi, fatty acids (FA), growth dynamics, lipids

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Authors: Jagbir Singh Kadyan, C. A. Suman Kadyan

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The researchers attempts to establish whether a relationship exists between the social activities undertaken & the funds that has been spent by the selected corporate organisations. Corporate listed on the (NSE) National Stock Exchange of India, under different categories shall be selected as a sample for the purpose of this study. The researches shall also study the dynamics of corporate social responsibility funding, financing & management of corporate social responsibility funds by the above selected organisations in the Indian context. The rationale behind selecting & undertaking specific corporate social responsibility activities shall be analysed & interpreted to discover the real drivers of corporate social responsibility. Besides above, an attempt shall further make an effort to understand & analyse the nature of impact on the selected corporate organisations on its overall performances due to the activities undertaken under their specific corporate social responsibility programs.

Keywords: corporate social responsibility, organisational performance, national stock exchange, sustainability, society, health, education, sanitation, environment

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Authors: Divya Singh, Avinash Parashar

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Due to superior mechanical, creep and nuclear cross section, zirconium and niobium (Zr-Nb) based alloys are commonly used as nuclear materials for the manufacturing of fuel cladding and pressure tubes in nuclear power plants. In this work, symmetrical tilt grain boundary (STGB) structures in α-Zr are studied for their structure and energies along two tilt axes- [0001] and [0-110] using MD based simulations. Tilt grain boundaries are obtained along [0001] tilt axis, and special twin structures are obtained along [0-110] tilt axis in α-Zr. For Nb, STGBs are constructed along [100] and [110] axis using atomistic simulations. The correlation between GB structures and their energies is subsequently examined. A close relationship is found to exist between individual GB structure and its energy in both α-Zr and Nb. It is also concluded that the energies of the more coherent twin grain boundaries are lower than the symmetrical tilt grain boundaries.

Keywords: grain boundaries, molecular dynamics, grain boundary energy, hcp crystal

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Authors: Loren S. Bernal., Catalina Castillo, Carel E. Carvajal, José F. Ibla

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Plastic pollution, specifically microplastics, has become a significant issue in aquatic ecosystems worldwide. The large amount of plastic waste carried by water tributaries has resulted in the accumulation of microplastics in water bodies. The polymer aging process caused by environmental influences such as photodegradation and chemical degradation of additives leads to polymer embrittlement and properties change that require degradation or reduction procedures in rivers. However, there is a lack of such procedures for freshwater entities that develop over extended periods. The aim of this study is evaluate the potential of Pleurotus ostreatus a fungus, in reducing lowdensity polyethylene microplastics present in freshwater samples collected from the middle basin of the Magdalena River in Colombia. The study aims to evaluate this process both in vitro and in silico by identifying the growth capacity of Pleurotus ostreatus in the presence of microplastics and identifying the most likely interactions of Pleurotus ostreatus enzymes and their affinity energies. The study follows an engineering development methodology applied on an experimental basis. The in vitro evaluation protocol applied in this study focused on the growth capacity of Pleurotus ostreatus on microplastics using enzymatic inducers. In terms of in silico evaluation, molecular simulations were conducted using the Autodock 1.5.7 program to calculate interaction energies. The molecular dynamics were evaluated by using the myPresto Portal and GROMACS program to calculate radius of gyration and Energies.The results of the study showed that Pleurotus ostreatus has the potential to degrade low-density polyethylene microplastics. The in vitro evaluation revealed the adherence of Pleurotus ostreatus to LDPE using scanning electron microscopy. The best results were obtained with enzymatic inducers as a MnSO4 generating the activation of laccase or manganese peroxidase enzymes in the degradation process. The in silico modelling demonstrated that Pleurotus ostreatus was able to interact with the microplastics present in LDPE, showing affinity energies in molecular docking and molecular dynamics shown a minimum energy and the representative radius of gyration between each enzyme and its substract. The study contributes to the development of bioremediation processes for the removal of microplastics from freshwater sources using the fungus Pleurotus ostreatus. The in silico study provides insights into the affinity energies of Pleurotus ostreatus microplastic degrading enzymes and their interaction with low-density polyethylene. The study demonstrated that Pleurotus ostreatus can interact with LDPE microplastics, making it a good agent for the development of bioremediation processes that aid in the recovery of freshwater sources. The results of the study suggested that bioremediation could be a promising approach to reduce microplastics in freshwater systems.

Keywords: bioremediation, in silico modelling, microplastics, Pleurotus ostreatus

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Authors: Imane Khalil, Quinn Pratt

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In a nuclear reactor, an array of fuel rods containing stacked uranium dioxide pellets clad with zircalloy is the heat source for a thermodynamic cycle of energy conversion from heat to electricity. After fuel is used in a nuclear reactor, the assemblies are stored underwater in a spent nuclear fuel pool at the nuclear power plant while heat generation and radioactive decay rates decrease before it is placed in packages for dry storage or transportation. A computational model of a Boiling Water Reactor spent fuel assembly is modeled using FLUENT, the computational fluid dynamics package. Heat transfer simulations were performed on the two-dimensional 9x9 spent fuel assembly to predict the maximum cladding temperature for different input to the FLUENT model. Uncertainty quantification is used to predict the heat transfer and the maximum temperature profile inside the assembly.

Keywords: spent nuclear fuel, conduction, heat transfer, uncertainty quantification

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Authors: Kang Sungjae

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This research proposes a gait stability evaluation technique based on the linear inverted pendulum model and moving support foot Zero Moment Point. With this, an improvement towards the gait analysis of the orthosis walk is validated. The application of Lagrangian mechanics approximation to the solutions of the dynamics equations for the linear inverted pendulum does not only simplify the solution, but it provides a smooth Zero Moment Point for the double feet support phase. The Zero Moment Point gait analysis techniques mentioned above validates reference trajectories for the center of mass of the gait orthosis, the timing of the steps and landing position references for the swing feet. The stability evaluation technique are tested with a 6 DOF powered gait orthosis. The results obtained are promising for implementations.

Keywords: locomotion, center of mass, gait stability, linear inverted pendulum model

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Authors: José Carlos Rodríguez, Mario Gómez

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The aim of this paper is to get insight on the nature of university-industry technology transfer (UITT) and technology transfer offices (TTOs) activity at universities in the case of emerging economies. In relation to the process of transferring knowledge/technology in the case of emerging economies, knowledge/technology transfer in these economies are more reactive than in developed economies due to differences in maturity of technologies. It is assumed in this paper that knowledge/technology transfer is a complex phenomenon, and thus the paper contributes to get insight on the nature of UITT and TTOs creation in the case of emerging economies by using a system dynamics model of knowledge/technology transfer in these countries. The paper recognizes the differences between industrialized countries and emerging economies on these phenomena.

Keywords: university-industry technology transfer, technology transfer offices, technology transfer models, emerging economies

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Authors: Dimitrios Triantakonstantis, Demetris Stathakis

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Urban areas have been expanded throughout the globe. Monitoring and modeling urban growth have become a necessity for a sustainable urban planning and decision making. Urban prediction models are important tools for analyzing the causes and consequences of urban land use dynamics. The objective of this research paper is to analyze and model the urban change, which has been occurred from 1990 to 2000 using CORINE land cover maps. The model was developed using drivers of urban changes (such as road distance, slope, etc.) under an Artificial Neural Network modeling approach. Validation was achieved using a prediction map for 2006 which was compared with a real map of Urban Atlas of 2006. The accuracy produced a Kappa index of agreement of 0,639 and a value of Cramer's V of 0,648. These encouraging results indicate the importance of the developed urban growth prediction model which using a set of available common biophysical drivers could serve as a management tool for the assessment of urban change.

Keywords: artificial neural networks, CORINE, urban atlas, urban growth prediction

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Authors: Jenn-Yih Chen, Bean-Yin Lee, Yuan-Chuan Hsu, Jui-Cheng Lin, Kuang-Chyi Lee

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In this paper, a sliding mode control method based on the passivity approach is proposed to control the position of surface-mounted permanent magnet synchronous motors (PMSMs). Firstly, the dynamics of a PMSM was proved to be strictly passive. The position controller with an adaptive law was used to estimate the load torque to eliminate the chattering effects associated with the conventional sliding mode controller. The stability analysis of the overall position control system was carried out by adopting the passivity theorem instead of Lyapunov-type arguments. Finally, experimental results were provided to show that the good position tracking can be obtained, and exhibit robustness in the variations of the motor parameters and load torque disturbances.

Keywords: adaptive law, passivity theorem, permanent magnet synchronous motor, sliding mode control

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Bo Kampmann Walther

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This essay examines the narratives of the Book of Genesis through the lens of game theory, a mathematical framework for analyzing strategic interactions among rational actors. By treating key figures in Genesis as players in a game, this analysis sheds light on their decisions and the resulting consequences. Focusing primarily on the story of Adam and Eve, the essay utilizes concepts such as game state, saddle point, optimal strategy, and Nash equilibrium to explore the dynamics at play and scrutinize the existence of two kinds of game rules in Genesis: one being global and post-Fall oriented, the other being local and relegated to life in the Garden. The serpent's intervention and the subsequent actions of Adam and Eve are modeled as strategic moves, revealing the complexities and shifts in the game state from harmony in Eden to a world marked by toil and mortality post-Fall.

Keywords: game theory, Genesis, strategy, saddle point, nash equilibrium, New Game State

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Authors: Tanu Aneja, Harsha Malaviya

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Capturing pose information in cricket shots poses several challenges, such as low-resolution videos, noisy data, and joint occlusions caused by the nature of the shots. In response to these challenges, we propose a CondDGConv-based framework specifically for cricket shot prediction. By analyzing the spatial-temporal relationships in batsman shot sequences from an annotated 2D cricket dataset, our model achieves a 97% accuracy in predicting shot types. This performance is made possible by conditioning the graph network on batsman 2D poses, allowing for precise prediction of shot outcomes based on pose dynamics. Our approach highlights the potential for enhancing shot prediction in cricket analytics, offering a robust solution for overcoming pose-related challenges in sports analysis.

Keywords: action recognition, cricket. sports video analytics, computer vision, graph convolutional networks

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Authors: G. Carrero, C. Contreras, M. J. Hendzel

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Linker histones or histones H1 are highly mobile nuclear proteins that regulate the organization of chromatin and limit DNA accessibility by binding to the chromatin structure (DNA and associated proteins). It is known that this binding process is driven by both slow (strong binding) and rapid (weak binding) interactions. However, the exact binding mechanism has not been fully described. Moreover, the existing models only account for one type of bound population that does not distinguish explicitly between the weakly and strongly bound proteins. Thus, we propose different systems of reaction-diffusion equations to describe explicitly the rapid and slow interactions during a FRAP (Fluorescence Recovery After Photobleaching) experiment. We perform a model comparison analysis to characterize the binding mechanism of histone H1 and provide new meaningful biophysical information on the kinetics of histone H1.

Keywords: FRAP (Fluorescence Recovery After Photobleaching), histone H1, histone H1 binding kinetics, linker histone, reaction-diffusion equation

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Mohammad Nazififard, Reihane Faghihi

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This paper is aimed at understanding convective heat transfer of enclosed phase change material (PCM) in the solar and low-temperature hot water radiant floor heating geometry. In order to obtain the best performance of PCM, a radiant heating structure of the energy storage floor is designed which places heat pipes in the enclosed phase change material (PCM) layer, without concrete in it. The governing equations are numerically solved. The PCM thermal storage time is considered in relation to the floor surface temperature under different hot water temperatures. Moreover the PCM thermal storage time is numerically estimated under different supply water temperatures and flow rate. Results show the PCM floor heating system has a potential of making use of the daytime solar energy for heating at night efficiently.

Keywords: solar floor, heating system, phase change material, computational fluid dynamics

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model

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Authors: Lesley Clack, Rachel Ellison, Elizabeth Chambers

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A belief exists that there are huge gender and racial disparities among hospital CEO’s in the United States, and historically, male, Caucasian healthcare executives have made significantly larger salaries than females and other races. With a recent focus on reducing barriers and disparities in healthcare, it remains to be seen whether there have been changes in these disparities over time. The purpose of this study was to explore disparities among salaries of hospital executives in the United States. Analysis of salary data was conducted utilizing online hospital salary databases. Statistical analysis was conducted to examine the significance of the differences. Results indicated that there had been improvements in disparities among some ethnicities. Gender disparities remain the largest gap. The implications of this study are significant for the field of healthcare management as disparities can affect both social dynamics and organizational culture. Understanding where disparities lie is the first step towards bridging the gap and reducing barriers for cultural diversity within healthcare management.

Keywords: health care, disparities, management, executives

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Authors: Jossitt Williams Vargas Cruz, Aura Jazmín Pérez Ríos

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The variations of solar dynamics have become a relevant topic of study due to the effects of climate changes generated on the earth. One of the most disconcerting aspects is the variability that the sun has on the climate is the role played by sunspots (extra-atmospheric variable) in the modulation of the Cosmic Rays CR (extra-atmospheric variable). CRs influence the earth's climate by affecting cloud formation (atmospheric variable), and solar cycle influence is associated with the presence of solar storms, and the magnetic activity is greater, resulting in less CR entering the earth's atmosphere. The different methods of climate prediction in Colombia do not take into account the extra-atmospheric variables. Therefore, correlations between atmospheric and extra-atmospheric variables were studied in order to implement a Python code based on neural networks to make the prediction of the extra-atmospheric variable with the highest correlation.

Keywords: correlations, cosmic rays, sun, sunspots and variations.

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

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Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks

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Authors: Sihame Amakrane, Zineb Ouahdi, Mohammed Salah, Said Belaaouad

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\This research explores the efficacy of novel pyrimidine derivatives on bacterial strains such as Escherichia coli, Staphylococcus aureus, and Myccobacterium tuberculosis, utilizing bending energy calculations. Of the 25 compounds examined, 13 displayed potent activity against all the bacterial strains under study, exhibiting bending energy measurements between -7.4 and -10.7 kcal/mol. The -7.4 kcal/mol value corresponds to the bending energy of the SA12 and SA13 compounds with the 2xct protein (Staphylococcus aureus), whereas the -10.7 kcal/molis linked with the bending energy of SA6 and SA11 compounds with the 6GAV protein (Myccobacterium tuberculosis). Further research will involve a QSAR (Quantitative Structure-Activity Relationship) study aimed at constructing a reliable model to combat the aforementioned bacterial strains and a molecular dynamics study to evaluate the stability of ligand-protein complexes.

Keywords: docking, QSAR, bending energy, e. coli

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Authors: Andrea Catorci, Federico Maria Tardella, Alessandro Brica, Muhammad Umair

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Climate change models predict for the Mediterranean region a strong increase of intensity and frequency of drought events, with an expected effect on grassland biodiversity and functioning. The research aim was to understand how the grassland species modulate their resource acquisition and conservation strategies to short-term variation of the pattern of summer water supply. The study area is mountain meadows located in the ‘‘Montagna di Torricchio’’ (1130 m a.s.l.) a Nature Reserve in central Italy. In 2017 we started a manipulative experiment for 2 year (2017-2018), and we defined two treatments, one with increasing water (watering condition) and the other with less water (drought condition). Then, we investigated how species change their resource strategies at different amount of water availability by measuring the specific leaf area (SLA) and leaf area (LA). We used ANOVAs to test the effect of treatment over time on leaf area and specific leaf area, considering all the species together and also separately according to their growth form (forb, grass, legume). Our results showed that species may respond differently depending on their growth form and that using all the species together may cover more detailed variation. Overall, resource retaining strategies (lower SLA, LA) are resulted by increase of drought condition, while increase in water amount and number of watering events fosters acquisitive strategies (higher SLA, LA). However, this pattern is not constant for all growth form. Grass species are able to maintain their strategies to variation of the pattern of water availability. Forb and legume species on the other side have shown decreasing trend of SLA, LA values with increasing drought condition, a pattern more marked for the latter growth form. These variations suggest not only an increase of slow-growing strategies for both growth form, but also a decrease of their nutrient pastoral values since their leaves are supposed to become harder. Local farmers should consider the effect of climate change on grassland and adapt their management practices to guarantee the cattle welfare.

Keywords: function strategies, grasslands, climate change, sub Mediterranean region

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

Abstract:

Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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