Strengthening production plants and process control functions contribute to a global improvement of manufacturing systems because of their cross-functional characteristics in the industry. Companies established various innovative and operational strategies; there is increasing competitiveness among them and increasing companies’ value. Machine learning (ML) techniques become an intelligent enticing option to address industrial issues in the current manufacturing sector since the emergence of Industry 4.0 and the extensive integration of paradigms such as big data and high computational power. Implementing a system able to identify faults early to avoid critical situations in the production line and its environment is crucial. Therefore, powerful machine learning algorithms are performed for fault diagnosis, real-time data classification, and predicting the state of functioning of the production line. Random forests proved to be a better classifier with an accuracy of 97%, compared to the SVM model’s accuracy which is 94.18%. However, the K-NN model’s accuracy is about 93.83%. An accuracy of 80.25% is achieved by the logistic regression model. About 83.73% is obtained by the decision tree’s model. The excellent experimental results reached on the random forest model demonstrated the merits of this implementation in the production performance, ensuring predictive maintenance and avoiding wasting energy.

In the context of the industrial process safety, the domino effect has become a topical issue for scientists and managers of companies given the diversity of factors that contributed to the aggravation of this phenomenon such as; proximity to industrial facilities, transport networks, development of industrial complexes, storage of hazardous substances and population growth. The purpose of this article is the MICDE method (Method of Identification and Characterization of Domino Effects) application on industrial zone of LPG storage in SONATRACH-Algeria Group for analyzes the domino effects caused by a major industrial accident.

Our study is adopted on the MICDE method which constitutes an aid in the integration of the domino effects problem in hazard studies and safety studies. In our application, it aims to formalize the points relating to the domino effects due to the BLEVE (Boiling Liquid Expanding Vapor Explosion) phenomenon of an LPG storage sphere.

The results obtained show that the hazardous equipment in the vicinity is seriously affected by the thermal and overpressure effect of the main accident, and may be seats in a new accident. The MICDE method is a promising method can be applied in several fields since it studies the phenomenon. This method facilitates decision-making in the prevention of domino effects for the sustainability facilities

Sebkha soils are defined as problem soils located in arid, semi-arid, and coastal areas. Generally, they are fine soil, composed of silt, sand, and clay, which are cemented by different salts (e.g., halite, gypsum, and calcite). In nature, sebkha saline soils are exposed to different drying and wetting (D-W) cycles. However, these cycles have a significant effect on the mechanical behavior of these soils. This study aims to characterize the chemical, mineralogical, and geotechnical properties of sebkha soil using an experimental approach. We focus on the effects of D-W cycles on the unconfined compressive strength (UCS) and salinity of sebkha soils from Ain M'Lila, Algeria. In addition, these D-W cycles were applied to the samples dried in the open air to achieve the targeted water content (water content values of 7%, 11.4%, and 13%). The results obtained show that the UCS increases with decrease in water content and decreases with an increase in the number of D-W cycles. In addition, these cycles affect the salinity of the sebkha soil. Indeed, a significant decrease in soil salinity was recorded with an increase in the number of D-W cycles. Finally, a relationship was found between the salinity of the soil and UCS. The latter decreases with a decrease in soil salinity; this relationship becomes very significant for low water content values of 7% or less.

Antibiotic-resistant bacteria can leave hospitals and therefore contaminate the environment and, most likely, humans and animals, through different routes, among which wastewater discharge is of great importance. This study aims to assess the possible role of hospital sewage as reservoir and dissemination pathway of carbapenem-resistant Gram-negative bacilli (GNB). Carbapenem-resistant GNB were selectively isolated from wastewater collected from a public hospital in Batna, Algeria. Species identification was carried out using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry, and antibiotic susceptibility was evaluated by the disc diffusion method. β-Lactamase production was investigated phenotypically using the double-disk synergy assay and the modified CarbaNP test, then the molecular mechanisms of β-lactam-resistance were studied by PCR and sequencing. Ten Enterobacteriaceae and 14 glucose-nonfermenting GNB isolates were obtained. All Enterobacteriaceae isolates were positive for OXA-48 and TEM-1D β-lactamases, where seven of them coproduced an extended-spectrum β-lactamase. VIM-2 carbapenemase was detected in six glucose-nonfermenting GNB isolates. However, three Pseudomonas aeruginosa, one Comamonas jiangduensis and one Acinetobacter baumannii isolates were positive for VIM-4 variant. In addition, NDM-1 enzyme was detected in four A. baumannii isolates. Our findings highlight the potential impact of hospital wastewater in the spread of drug resistance mechanisms outside of hospitals.

Energy efficiency and ratio performance are two key parameters for the analysis of the performance of photovoltaic (PV) modules. The present paper focusses on the assessment of the efficiency of four different photovoltaic module technologies based on energy efficiency and ratio performance. These PV modules were installed at the Applied Research Unit in Renewable Energy (URAER) in Algeria and were used to provide experimental data to help local and international economical actors with performance enhancement and optimal choice of different technologies subject to arid outdoor conditions. The modules studied in this paper are: two thin-film modules of copper indium selenide (CIS), hetero-junction with intrinsic thin-layer silicon (HIT) and two crystalline silicon modules (polycrystalline (poly-Si), monocrystalline (mono-Si)). These technologies were initially characterized using a DC regulator based on their measured I-V characteristics under the same outdoor climate conditions as the location where the monitoring of the electrical energy produced from each PV module was carried out. The DC regulator allows for extracting the maximum electrical power. At the same time, the measurements of the solar radiation and temperature were obtained from a pyranometer type Kipp & ZonenTM CMP21 and a Pt-100 temperature sensor (Kipp & Zonen, Delft, Netherlands). These measurements were performed from July 2020 to June 2021. In this work, the monthly average performance parameters such as energy efficiency are given and analyzed. The average efficiency of the modules over 12 months was evaluated at 4.74%, 7.65%, 9.13% and 10.27% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The calculated percentage deviations in the efficiency of the modules were 8.49%, 18.88%, 19.74% and 23.57% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The low variation in the efficiency of the HIT module can be attributed to the better operation of this module under arid outdoor conditions, which makes it a promising module for adaptation to the region concerned.

Abstract

In this chapter, we have conducted a statistical study of the annual extreme precipitation (AMP) for 856 grid cells and during the period of 1979–2012 in Algeria. In the first step, we compared graphically the forecasts of the three parameters of the generalized extreme value (GEV) distribution (location, scale and shape) which are estimated by the Spherical model. We used the Cross validation method to compare the two methods kriging and Co-kriging, based on the based on some statistical indicators such as Mean Errors (ME), Root Mean Square Errors (RMSE) and Squared Deviation Ratio (MSDR). The Kriging forecast error map shows low errors expected near the stations, while co-Kriging gives the lowest errors on average at the national level, which means that the method of co-Kriging is the best. From the results of the return periods, we calculate that after 50 years the estimated of the annual extreme precipitation will exceed the maximum AMP is observed in the 33-year.

Purpose

Workplace violence is a universal phenomenon that is constantly increasing. In this regard, this study aims to investigate the prevalence of violence committed against Algerian health professionals.

Design/methodology/approach

A cross-sectional survey, based on an anonymous, self-administered questionnaire, was conducted in healthcare settings of eastern Algeria (where 144 respondents participated in this study). Besides, socio-demographic characteristics and data related to violence, including its prevalence, different forms, perpetrators, reporting and the way it is handled, were analyzed using descriptive and inferential statistics.

Findings

Half of the respondents were victims of violence. More specifically, 90.1% of them were verbally abused. Compared to physical violence, verbal violence was significantly perpetrated against women and young health professionals (p < 0.05). However, nurses and those with less than or equal to five years of work experience were the most vulnerable to both types of violence (p < 0.05). Moreover, the main perpetrators were the patients' relatives (70%) followed by the patients themselves (51.4%). In terms of risk treatment, aggressors were verbally warned (60%). For violence reporting, 31% of the respondents observe such a fact as not being important. Finally, 65.7% of the participants reported that their employers had provided them with security measures (guards).

Originality/value

This is the first study conducted in Algeria that examines the prevalence of violence and its relationship with socio-demographic characteristics. Authorities must react effectively to solve this problem by implementing preventive and anticipatory strategies.

The Emergency Shutdown System (ESD) is a type of Safety Instrumented Systems (SIS) used to shut down the system in the event of anomalous conditions, it consists of sensors, logic solvers, and final elements. Reliability databases such as OREDA (Offshore and Onshore Reliability Data) and expert judgment indicate that Emergency Shutdown Valve (ESDV) failures are the most common cause of the unavailability of ESDs. Therefore, proper diagnostic is essential to prevent the failure risks of these valves. ESDV problems are of a different nature and difficult to treat with mathematical models because of their non-linear behavior, the imprecision of information, and the appearance of many failure modes that arise from many failure causes. Therefore, failure diagnostic mechanism based on heuristic knowledge of ESDV parameters must be established. In this paper, the problem of diagnosing ESDV failures is addressed based on the fault-symptom tree model and the Multiple Input-Multiple Output (MIMO) fuzzy inference system. The latter is built on a set of linguistic rules “if-then” provided by the fault-symptom tree model. the proposed approach was applied and verified on an ESDV subsystem in the petrochemical industry.

The concept of equivalent morphology has received much consideration in recent decades. The importance of this concept is reflected in the fact that an inclusion of any morphology can be replaced by a circular one in simulation. If this concept is confirmed, it will facilitate the modeling and simulation of complex configuration microstructures.

To decide on this concept, an in–depth study is carried out in this work, trying to answer it in a clear and definitive way by trying to identify all the possible situations. For this the two types of composites, namely, periodic interpreted by an elementary cell and random interpreted by a Representative Volume Element (RVE) with 200 inclusions are considered. To be sure that the isotropy is provided by the RVE of the periodic microstructure, two types of elementary cells were treated: one circular and the other square. In order to cover all possible situations, the inclusion of the elementary cell is considered with several situations, centered position with different orientations at constant and random steps, random position with orientation at constant steps and random position and orientation at random steps. For each situation, the effective property is determined by the average of 20 cases are processed for elementary cells, while for the large RVE, the properties are obtained by a unit realization. To take into account the effect of contrast, two situations are considered, namely, rigid inclusion case and rigid matrix case. Several results are obtained and given in the conclusion.

This study presents an idea inspired by an industrial site (Global Company of Lafargeholcim) which suffers from several protection problems. Firstly, the effects of the distributed generator (DG) on the protection of the radial grid in the event of a symmetric three-phase short circuit with several scenarios (varying in size and location of the DG) are presented. The study of these effects allows to observe problems on protection, especially, sensitivity and selectivity. Secondly, in order to have well-optimized protection, taking into account both the size and the location of a distributed generator in a radial grid, we propose an algorithm with a new formula. The effectiveness of the new idea can be demonstrated through simulation results.

Bioinformatics as a newly emerging discipline is considered nowadays a reference to characterize the physicochemical and pharmacological properties of the actual biocompounds contained in plants, which has helped the pharmaceutical industry a lot in the drug development process. In this study, a bioinformatics approach known as in silico was performed to predict, for the first time, the physicochemical properties, ADMET profile, pharmacological capacities, cytotoxicity, and nervous system macromolecular targets, as well as the gene expression profiles, of four compounds recently identified from Centaurea tougourensis via the gas chromatography–mass spectrometry (GC–MS) approach. Thus, four compounds were tested from the n-butanol (n-BuOH) extract of this plant, named, respectively, Acridin-9-amine, 1,2,3,4-tetrahydro-5,7-dimethyl- (compound 1), 3-[2,3-Dihydro-2,2-dimethylbenzofuran-7-yl]-5-methoxy-1,3,4-oxadiazol-2(3H)-one (compound 2), 9,9-Dimethoxybicyclo[3.3.1]nona-2,4-dione (compound 3), and 3-[3-Bromophenyl]-7-chloro-3,4-dihydro-10-hydroxy-1,9(2H,10H)-acridinedione (compound 4). The insilico investigation revealed that the four tested compounds could be a good candidate to regulate the expression of key genes and may also exert significant cytotoxic effects against several tumor celllines. In addition, these compounds could also be effective in the treatment of some diseases related to diabetes, skin pathologies, cardiovascular, and central nervous system disorders. The bioactive compounds of plant remain the best alternative in the context of the drug discovery and development process.

In this work, an inverted PTB7:PC₇₀BM bulk heterojunction solar cells with the configuration of ITO/ZnO/ PTB7:PC₇₀BM / HTMs/Ag for various inorganic materials as a hole transport layer (ZnO, MoO₃, NiO, PEDOT: PSS, V₂O₅ and Cu₂O) are simulated by using the GPVDM software which is a free general-purpose tool for the simulation of opto-electronic devices. The influence of the thickness of both PTB7:PC₇₀BM and HTMs layers on the performance of the solar cell are investigated. The obtained results indicated that on regardless on the type of the inorganic material constituted the Hole Transport Material (HTM), the solar cell parameters can be improved by reducing the HTM thickness while the active layer optimum thickness is around 90 nm. The performance of the device with all inorganic materials used as HTM reaches the same levels as the PEDOT/PSS for the lower thickness (10 nm). As the thickness is increased, the electrical parameters are significantly enhanced by inserting cuprous oxide (Cu₂O) compared to the conventional PEDOT: PSS.

A new method for predicting the Liquid-Vapor critical point of binary mixture, is presented, which is based in geometrical distances. Actually, the method is based on the minimization of the distance between the experimental and calculated values of the critical temperatures and critical pressures. The SRK and PR equations of state along with classical mixing rules of van der Waals were used as thermodynamic models to calculate the critical point of a given mixture. The proposed method requires that the mixture parameters a, b, and the covolume e = b/v of each equation of state be determined at each iteration by solving the resulting cubic equation. For nine binary mixtures containing: hydrocarbon derivatives, carbon dioxide and alcohols are studied. The AARE of the calculated values is about 0.86% for critical temperature and 2.07% for critical pressure. Good agreements are found between the calculated results and experimental data. The technique is a general purpose one and can be applied in connection with other thermodynamic models.

The risk related to embankment dam breaches needs to be evaluated in order to prepare emergency action plans. The physical and hydrodynamic parameters of the flood wave generated from the dam failure event correspond to various breach parameters, such as width, slope, and formation time. This study aimed to simulate the dam breach failure scenario of the Yabous dam (northeast Algeria) and analyze its influence on the related areas (urban and natural environments) downstream of the dam. The simulation was completed using the sensitivity analysis method to assess the impact of breach parameters and flooding on the dam break scenario. The flood wave propagation associated with the dam break was simulated using the one-dimensional HEC-RAS hydraulic model. This study applied a sensitivity analysis of three breach parameters (slope, width, and formation time) on five sites selected downstream of the embankment dam. The simulation showed that the maximum flow of the flood wave recorded at the level of the breach was 8768 m³/s, which gradually attenuated along the river course to reach 1972.7 m³/s at about 8.5 km downstream the dam. This study established the map of flood risk areas that illustrated zones threatened by the flooding wave triggered by the dam failure due to extreme rainfall events. The sensitivity analysis showed that flood wave flow, height, and width revealed positive and similar changes for the increases in adjustments (±25% and ±50%) of breach width and slope in the five sites. However, flood wave parameters of breach formation time showed significant trends that changed in the opposite direction compared to breach slope and width. Meanwhile, the adjustments (±25% and ±50%) of the flood hydrograph did not significantly influence the flood parameters downstream of the dam. In the present study, the HEC-RAS 1-D modeling demonstrated effectiveness in simulating the propagation of flood waves downstream of the dam in the event of dam failure and highlighted the impact of the breach parameters and the flood hydrographical pattern on flood wave parameters.

Turbulent flows are characterized by the presence of "scales of fluctuations", or "structures" of varying magnitudes, the effects in which the mixing, transfer and dissipation of energy are preponderant. Most importantly, dissipation determines the depth profile of the flow. This contribution aims to implement a model able to predict unsteady turbulent flows generated by the presence of obstacles in a channel with complex geometry and to report, where the complexity of the phenomena are observed, such as: the separation of the boundary layer, the succession of vortices, local heat transfers, and the recirculation zones in the wake of obstacles and the oscillatory regime of the hydraulic jump for which this research is of exclusive interest. The current work therefore, presents the numerical simulation in unsteady turbulent regime based on the resolution of balance equations, using the RANS (Reynolds-Averaged Navier–Stokes) approach with an RNG k−ε closure model. To solve the incompressible Navier–Stokes equations governing these flows, we appealed to the motivated finite volume method, and its ability to process complex geometries. The simulation software FLUENT we used is based on the finite volume method. It allows to explore, the velocity and pressure fields in the digital channel of the studied flows.

This paper deals with multi-agent energy management and fault tolerant control of the micro-grid powered by wind farm based on two doubly fed induction generators. The stator flux orientation has used to eliminate the active and reactive power coupling. The proposed control scheme is based on two cascades closed loops. The inner controllers concern the rotor currents. The outer controllers have a parallel configuration with the stator voltage or the stator power control. Switching between these two controllers is realized by the synchronization mechanism. All controllers are designed with Lyapunov approach associated with sliding-mode control, this solution shows good robustness against parameter variations, measurement errors and faults. The global asymptotic stability of the overall system is proven. After that, a Multi-agent energy management was proposed and tested in order to satisfy some objectives and overcome some constraints. The advantages of the wind energy integration associated with multi-agent energy management are: production cost minimization, reduction of the carbon emissions, increasing the energy autonomy and he robustness against weather conditions and faults that may occur during operation. The results confirm the effectiveness of the proposed control.

Amniotic band syndrome (ABS) was first described by Montgomery in Montgomery (1832). It is a poorly known congenital malformation due to strangulation of the organs by an amniotic fibrous band. Several parts of the body can be affected: for instance, skull, face, neck, trunk and musculoskeletal system. It generally associates three types of anomalies namely, amputations, deformities, and malformations. There are two genuine theories covering this syndrome; the Intrinsic Theory associating the syndrome to a germline defect and the Purely Mechanical Extrinsic Theory related to the amniotic band. These theories have thoroughly tried to explain the disease and the organ involvement (Goldfarb et al., 2009). In the current study, we report a rare case of an open fracture of both leg bones with amniotic disease in a 10-day-old neonate who underwent surgical treatment. In our case, it is a surgical emergency where we try to explain its physiopathology and show how to operate it. We discuss likewise the appropriateness of using the expressions “leg fracture” and “congenital pseudarthrosis of the leg”. Finally, we describe a revised classification by Hall (1982) and Weinzweig (1994) of ABS incorporating a stage with bone involvement.

Hexavalent chromium (CrVI) compounds are potent toxicants commonly used in numerous industries. Thus, potential toxic effects and health hazards are of high relevance. Selenium (Se) and zinc (Zn) are known for their antioxidant and chemoprotective properties. However, little is known about their protective effects against CrVI-induced renal damage during pregnancy. In this context, the present study aimed to investigate the protective efficacy of these two essential elements against potassium dichromate-induced nephrotoxicity in pregnant Wistar Albino rats. Female rats were divided into control and four treated groups of six each receiving subcutaneously on the 3rd day of pregnancy, K₂Cr₂O₇ (10 mg/kg, s.c. single dose) alone, or in association with Se (0.3 mg/kg, s.c. single dose), ZnCl₂ (20 mg/kg, s.c. single dose) or both of them simultaneously. The nephrotoxic effects were monitored by the evaluation of plasma renal parameters, oxidative stress biomarkers, DNA damage, and renal Cr content. The obtained results showed that K₂Cr₂O₇ disturbed renal biochemical markers, induced oxidative stress and DNA fragmentation in kidney tissues, and altered renal histoarchitecture. The co-administration of Se and/or ZnCl₂ has exhibited pronounced chelative, antioxidant, and genoprotective effects against K₂Cr₂O₇-induced renal damage and attenuated partially the histopathological alterations. These results suggest that Se and Zn can be used as efficient nephroprotective agents against K₂Cr₂O₇-induced toxicity in pregnant Wistar Albino rats.

The aim of this study was to test the influence of nest site characteristics and food supplementation from rubbish dumps on reproductive parameters of white storks breeding in semi-arid habitats. A total of 148 nests were monitored in two colonies of white storks (control colony vs. colony that benefited from high food supply in rubbish dumps) in eastern Algeria over a six-year period (2011–2016) to measure nest characteristics and reproductive parameters (clutch size, number of hatchings, number of fledglings, breeding success). Results showed that pairs breeding at proximity from rubbish dumps had larger clutch sizes (5.1 ± 0.6 vs. 4.6 ± 0.6), hatched more chicks (4.7 ± 0.7 vs. 4.3 ± 0.7) and raised more fledglings (3.0 ± 0.9 vs. 2.6 ± 1.0) than pairs breeding far from rubbish dumps. Results also showed that clutch size was positively related to nest surface area, and that pairs nesting on electricity poles had a lower breeding success than those nesting in trees (48.9 ± 20.4% vs. 64.6 ± 17.6%). Our findings suggest that breeding outputs are strongly related to selective behavior in nest placement and food availability surrounding the nesting site.

This paper proposes a new approach for remaining useful life prediction that combines a bond graph, the Gaussian Mixture Model and similarity techniques to allow the use of both physical knowledge and the data available. The proposed method is based on the identification of relevant variables that carry information on degradation. To this end, the causal properties of the bond graph (BG) are first used to identify the relevant sensors through the fault observability. Then, a second stage of analysis based on statistical metrics is performed to reduce the number of sensors to only the ones carrying useful information for failure prognosis, thus, optimizing the data to be used in the prognosis phase. To generate data in the different system state, a simulator based on the developed BG is used. A Gaussian Mixture Model is then applied on the generated data for fault diagnosis and clustering. The Remaining Useful Life is estimated using a similarity technique. An application on a mechatronic system is considered for highlighting the effectiveness of the proposed approach.