Aims: Non-alcoholic fatty liver disease is strongly linked to obesity and insulin resistance. The triglyceride-glucose index (TyG index) has been proposed as a reliable biomarker of insulin resistance. Our aims is to study the contribution of the TyG index as a marker in the association of non-alcoholic fatty liver disease, obesity and insulin resistance. Material and method:This was a cross-sectional study of obese women (age>18years,BMI≥29.9Kg/m2). Non-alcoholic hepatitis steatosis was confirmed by abdominal ultrasound. The viral origin of the liver disease was eliminated by microbiological test. A lipid profile was performed. The TyG index was calculated according to the formula Ln[fasting triglycerides(mg/dL)×fasting glucose(mg/dL)/2. The relations between TyG index body composition and lipid profile was measured. Results: 42 obese women participated in our work. Age=50.80±10.33 years. BMI=40.80±5.09 Kg/m2; weight=98.1±15.99 Kg. Fasting blood sugar was 1.18±0.34 g/L. Triglycerides were 1.37±0.47 g/L. Our study demonstrated that 83% (n= 35) have, in addition to nonalcoholic fatty liver disease, a high TyG index (4.75+/-0.25) in favour of insulin resistance. The TyG index is strongly linked to fasting glucose (rs=0.83) and fasting triglycerides (rs=0.78). A statistically significant link was found between the TyG index and age (τ = 0.21, p=0.04), the TyG index and total cholesterol (τ = 0.33, p=0.001). Conclusions: The TyG index is a topical biomarker. This clue is practical. It appears to have a place in the association, obesity, non-alcoholic fatty liver disease and insulin resistance. Keywords: TyG index, insulin resistance, obesity, non-alcoholic fatty liver disease
Nowadays, different kinds of Industrial Control Systems (ICS) are used in heavy industries like oil and gas industry to monitor and control production and operation processes. In a same industrial plant, major engineering and design efforts are made during each system implementation, to comply with process requirements and features. Moreover, other efforts are made regarding to operation and maintenance issues due to diverse hardware and software architectures of such systems. This paper aim is to make a comparative study between most used control systems by highlighting their strengths and features, each according to its preferred domain of process control. Then to discuss how to develop a unified system that will have core features to monitor and control different kinds of processes. This approach is applied for the design of an oilfield telemetry project. The purpose is to propose technically optimized and cost-effective hardware and software solution.
Wetlands are present within intricate ecological settings, exhibiting dynamic changes over time and across different areas with regard to their functional and structural diversity. Several approaches have been introduced for ecosystem analysis and management since 1990s, where Driver – Pressure – State – Impact – Response (DPSIR) framework is one of the widely used approaches for assessing and managing environmental problems. In this study, we proposed a DPSIR framework as a model in the Sebkhates of Aures wetland complex (SAWC, Northeast of Algeria), in order to create a regional wetland observatory to deliver ecosystem services within current state of changes resulted from socioeconomic drivers. DPSIR facilitates the identification of essential indicators to detect threats to the Sebkahtes of Aures wetlands complex (SAWC), influencing policymakers to enhance the protection and management of these wetlands. In line with the established DPSIR framework. This same approach and methodology could be applied to the other 15 wetlands complexes known in Algeria, culminating in the creation of a national wetland observatory. Furthermore, DPSIR can be employed as an analytical tool for policy making in the context of sustainable management of wetland ecosystems and can serve as a model in the establishment and development of various observatory programs in Algeria.
Wetlands are present within intricate ecological settings, exhibiting dynamic changes over time and across different areas with regard to their functional and structural diversity. Several approaches have been introduced for ecosystem analysis and management since 1990s, where Driver – Pressure – State – Impact – Response (DPSIR) framework is one of the widely used approaches for assessing and managing environmental problems. In this study, we proposed a DPSIR framework as a model in the Sebkhates of Aures wetland complex (SAWC, Northeast of Algeria), in order to create a regional wetland observatory to deliver ecosystem services within current state of changes resulted from socioeconomic drivers. DPSIR facilitates the identification of essential indicators to detect threats to the Sebkahtes of Aures wetlands complex (SAWC), influencing policymakers to enhance the protection and management of these wetlands. In line with the established DPSIR framework. This same approach and methodology could be applied to the other 15 wetlands complexes known in Algeria, culminating in the creation of a national wetland observatory. Furthermore, DPSIR can be employed as an analytical tool for policy making in the context of sustainable management of wetland ecosystems and can serve as a model in the establishment and development of various observatory programs in Algeria.
Studies on drying of the watermelon seeds or rinds are available, but not on drying of the fruit flesh. Data on the sorption of watermelon fruit (Citrullus Lanatus), which are useful and important when identifying optimal food drying and storage conditions, are also not available. Therefore, the main goal of this study is to investigate the water desorption behavior of watermelon using the dynamic method requiring the automated dynamic vapor sorption (DVS) technique based on a humidity-generating device. The moisture desorption isotherms are determined at three different temperatures (20°C, 30°C and 40°C) over a relative humidity range of 0-80%. In addition, 11 different models are applied to the experimental data in order to select the appropriate desorption curve equation. The models are compared using the correlation coefficient, the coefficient of determination, the standard error, the reduced chi-squared, the mean bias error and the root mean square error; they are predicted by a non-linear regression analysis using the Curve Expert software and MS Excel computer program. The effect of the temperature on the constants of the found equation is also examined. Besides, the desorption isosteric heat of watermelon is determined using the Clausius-Clapeyron relation. Contrary to long times taken in the static method, the results show that 4.5 days are widely sufficient to reach the equilibrium via the DVS device. In addition, the obtained curves are of the type III and the Henderson model best fits the experimental data. In the interval 0.05-0.45 kg water.kg dry matter-1 of equilibrium moisture, the values of the isosteric heat vary from 65.02 to 113.25 kJ mol-1. Finally, the equation giving the isosteric heat of desorption v.s. the equilibrium moisture content is obtained.
The issue of reducing spatial disparities is one of the most pressing concerns for policymakers and planners, which consider a crucial focus in planning and public service, especially accessibility to healthcare. Accessibility and proximity are the principal keys to providing good public service. Therefore, a healthcare system that meets the requirements of availability and affordability will be useless if spatial accessibility is not provided equally to all demands (population). Many technics and methods exist to quantify accessibility, including the two-step floating catchment area (2SFCA) method, its widely used to measure healthcare accessibility based on the travel distance threshold. This research paper aims to use the 2SFCA method to measure the spatial healthcare accessibility in Batna City because the 2SFCA method offers to measure accessibility on both spatial and functional levels. The spatial level will consider the threshold distances between the health demand (population) and the health provider location (healthcare facilities); moreover, functional accessibility is measured based on facility to population ratio that will give a better overview of Batna's healthcare provider. As a result, the optimal threshold distance that offers balanced results between the spatial accessibility score and other WHO ratios will be a distance between 1000- and 1500-meters travel distance. In addition, the central census districts have a higher access score than the rest of the city's districts; most census districts that do not have accessibility (12% of the population) to healthcare facilities are concentrated in the southwest of Batna city.
In this paper, we present a novel hybrid meta-heuristic by enhancing the Basic Bees Algorithm through the integration of a local search method namely Simulated Annealing and Variable Neighbourhood Search like algorithm. The resulted hybrid bees algorithm (BASA) is used to solve the Single Machine Scheduling Problem with Early/Tardy jobs, where the generated outcomes are compared against the Basic Bees Algorithm (BA), and against some stat-of-the-art meta-heuristics. Computational results reveal that our proposed framework outperforms the Basic Bees Algorithm, and demonstrates a competitive performance compared with some algorithms extracted from the literature.
Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.
Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem.
Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems.
Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output.
Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.
Introduction. Constant increases in power consumption by both industrial and individual users may cause depletion of fossil fuels and environmental pollution, and hence there is a growing interest in clean and renewable energy resources. Photovoltaic power generation systems are playing an important role as a clean power electricity source in meeting future electricity demands.
Problem. All photovoltaic systems have two problems; the first one being the very low electric-power generation efficiency, especially under low-irradiation states; the second resides in the interdependence of the amount of the electric power generated by solar arrays and the ever changing weather conditions. Load mismatch can occur under these weather varying conditions such that maximum power is not extracted and delivered to the load. This issue constitutes the so-called maximum power point tracking problem.
Aim. Many methods have been developed to determine the maximum power point under all conditions. There are various methods, in most of them based on the well-known principle of perturb and observe. In this method, the operating point oscillates at a certain amplitude, no matter whether the maximum power point is reached or not. That is, this oscillation remains even in the steady state after reaching the maximum power point, which leads to power loss. This is an essential drawback of the previous method. In this paper, a cascade sliding mode maximum power point tracking control for a photovoltaic system is proposed to overcome above mentioned problems.
Methodology. The photovoltaic system is mainly composed of a solar array, DC/DC boost converter, cascade sliding mode controller, and an output load. Two sliding mode control design strategies are joined to construct the proposed controller. The primary sliding mode algorithm is designed for maximum power point searching, i.e., to track the output reference voltage of the solar array. This voltage is used to manipulate the setpoint of the secondary sliding mode controller, which is used via the DC-DC boost converter to achieve maximum power output.
Results. This novel approach provides a good transient response, a low tracking error and a very fast reaction against the solar radiation and photovoltaic cell temperature variations. The simulation results demonstrate the effectiveness of the proposed approach in the presence of environmental disturbances.
Let T ∈ B(H) be a bounded linear operator on a complex Hilbert space H. For n ∈ N, an operator T ∈ B(H) is said to be n-normal if T nT ∗ = T ∗T n. In this paper we investigate a necessary and sufficient condition for the n-normality of ST and T S, where S, T ∈ B(H). As a consequence, we generalize Kaplansky theorem for normal operators to n-normal operators. Also, In this paper, we provide new characterizations of n-normal operators by certain conditions involving powers of Moore-Penrose inverse.
The aim of this paper is to propose a new family of codes. We define this family over the ring R=∑4s=0vs5A4R=∑s=04v5sA4, with v55=v5v55=v5. We derive its properties, a generator matrix and Gray images. This new family of codes is illustrated by three applications.
Most road crashes at work are caused by Driver Behavioral Drift (DBD). This DBD has become a recurring issue on congested road sections. In this context, this study proposes a method called (MASOCU-DBD) which allows to analyze this DBD problem in two steps: assessment of the dynamics of DBD occurrence using a model called BM-NSA and analysis of DCC using a Cost-Benefit Analysis (CBA) weighted by the Analysis Hierarchical Process (AHP). The application of the MASOCU-DBD on a road section of an Algerian city’s entry highlighted the problem of the DBD in terms of its occurrence and uselessness in the studied section. The merit of the proposed method is that it uses multi-criteria analysis tools (AHP and CBA) as well as a mathematical model (BM-NSA) to analyze professional drivers’ behavioral deviations.
