Design methodology of smart photovoltaic plant

In this article, we present a new methodology to design an intelligent photovoltaic power plant connected to an electrical grid with storage to supply the laying hen rearing centers. This study requires a very competent design methodology in order to optimize the production and consumption of electrical energy. Our contribution consists in proposing a robust dimensioning synthesis elaborated according to a data flow chart. To achieve this objective, the photovoltaic system was first designed using a deterministic method, then the software "Homer" was used to check the feasibility of the design. Then, controllers (fuzzy logic) were used to optimize the energy produced and consumed. The power produced by the photovoltaic generator (GPV) is optimized by two fuzzy controllers: one to extract the maximum energy and another to control the batteries. The energy consumed by the load is optimized by a fuzzy controller that regulates the internal climate of the livestock buildings. The proposed control strategies are developed and implemented using MATLAB/Simulink

Bioindication of Urban Air Polycyclic Aromatic Hydrocarbons Using Petunia Hybrida

Different ways can be used to determinate the effects of hydrocarbons on plants: the bioindication with plants is one of these methods. It consists of using sensitive plants like Petunia hybrida to evaluate the urban levels of hydrocarbon pollution. The sensitivity shows physiological and morphological modifications. In this context, this research aims to characterize the level of exposure to air pollutants resulting from anthropogenic activities in urban area of Bejaia (Algeria) by measuring the morphological impacts induced on Petunia hybrida using 11 parameters detailing the morphological development of this plant. During 7 weeks (March 23- May 11, 2017), ten monitoring stations were chosen in this city. The results showed that the most important morphological changes are directly associated with the stations closest to the main atmospheric emission zones. It is by moving away from these sources of exposure that the morphological changes observed in this bioindicating plant become less important. These results coincide with those found for particle matter concentrations including PM10 and PM2.5 which indicate that Daouadji and Aamriw stations are the most polluted sites in Bejaia. Analyzes carried out on research station located in rural area (more than 30 km from the studied city) revealed a greater general development compared to other stations

Assessment of Air Pollution Impacts on Population Health in Bejaia City, Northern Algeria.

To assess the health impact of air pollution on Bejaia population in the north of Algeria, we carried out a descriptive epidemiologic inquiry near the medical establishments of three areas.From hospital admissions registers, we collected data on the hospital mortality and admissions relating to the various cardiorespiratory pathologies generated by this type of pollution. In parallel, data on the automobile fleet of Bejaia and other measurements were exploited to show that the pollutants concentrations are strongly correlated with the urban traffic concentration.This study revealed that the whole of the population is touched, but the sensitivity to pollution can show variations according to the age, the sex and the residence place. Population of Bejaia town marked the most raised death and morbidity rates, followed by that of Kherrata. Weak rates are recorded for the rural population of Feraoun. Stronger correlation (>0.9) is evident amongst CO and deaths due to asthma and COPD in Béjaia city.This approach enables us to conclude that the population of Béjaia could not escape the urban pollution generated by her old automobile fleet. Installation of a monitoring and measuring site of air pollution in this city could provide a beneficial tool to protect its inhabitants by informing on air quality they breathe and the measures to following order to minimize the impacts on their health and by alerting the authorities during the critical situations

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Oscillation Tests for Conformable Fractional Differential Equations with Damping

his article concerns existence of oscillatory solutions of theconformable fractional equations with damping of the form(`(y(α))γ)(β)(s) +g(s, xγμ(s))= 0,for alls∈J0,wherey(α)denotes conformable fractional,y(s) =x(s) +h(s)xξ(x),xμ=x◦μ,xξ=x◦ξ,γ:=2k+ 12m+1, withk, m∈N,J0= [0,∞)andα, β∈(0,1

Safety Integrity Level of Shut-Off Valve in a Burner Management System

The safety control and command system, such as the burner manage-ment system, requires that the system must be reliable, available and safe. The reliability is based on choosing equipment, with a high level of safety and which is suitable for the safety system. The availability and security are provided, among others, by redundancy. It is presented by M-Canal out of N-Canal (MooN) architecture, the (N-M) indicates how many dangerous faults are possible, with-out the performance of the systems being impeded. An essential quantitative analysis based on the evaluation of the PFDavg is part to give high trust in the BMS. This paper will discuss how a quantitative method can be used to select the appropriate SIL according to shutdown system for Burner Management System (BMS). This system is a part of a safety solution that manages a combustion sys-tem; it allows the safe start-up operation, and the shutdown of multiple burner furnace section of a boiler, and main flame detection

Development and evaluation of a 2oo3 safety controller in FPGA using fault tree analysis and Markov models

The Safety integrity level (SIL) is a measure of the reliability and availability of a safety instrumented system. SIL determination involves qualitative and quantitative analysis based on international standards such as IEC 61508 and IEC 61511. Several techniques can be used to analyze safety instrumented systems, including reliability block diagrams, fault tree analysis, and Markov models. The aim of this paper is to design and evaluate a pressure control system for a compressed nitrogen tank using a PID controller implemented in a field programmable gate array with 2 out of 3 architecture. This architecture ensures the safety of measurements and command of the system through a voting arrangement. The availability of the system is determined by the redundancy and the one hardware failure tolerance. The quantitative analysis is performed by calculating the probability of failure on demand per hour using Markov models or a relevant probabilistic approach based on fault tree analysis. The Markov model method gives the probability of failure of the system in different states during the system life cycle. The fault tree analysis method determines the probability of failure of the system using its equivalent failure rate. Furthermore, this paper compares the SIL result obtained by each model