This paper deals with the analysis of the inelastic response of buildings originally damaged by earthquakes and subjected to earthquake aftershock and wind loading. The overall aim is to establish the effect of wind actions on structural stability. To that end, one four-story bare frame benchmarked by the European Laboratory for Structural Assessment, is subject to various levels of winds and earthquake joint load while monitoring changes on the ductility demand. In this paper is shown that the combined action of strong winds and earthquakes, however its low probability of occurrence, would cause a decrease of strength reduction factors and considerably increase the ductility demand of damaged infrastructure hence inducing additional risks that would otherwise remain unquantified. The paper examines the non-linear performance of Multi-degree of freedom systems subject to various levels of winds and earthquake load and deals with the estimation of strength reduction factors. This is a relatively unexplored area of research which builds on past developments whereby inelastic performance of buildings has been discussed. It also links to various other paths of development such as structural reliability, forensic and control systems engineering.

This study is one of the first works which examined the assessment of heavy metal contamination of pavement-side soils in Algeria. It deals with the section of National Highway 3 (RN3), which crosses the wilaya of Batna. In the environment of sampling sites there is no industry or dangerous activity on the environment, the heavy metals addressed in this study are (Pb, Cu, Cr, Fe, Ni, Zn), their origin being road traffic. The objectives of this study were to: (1) Determine the concentrations of heavy metals in road dust; (2) Identify the sources of different heavy metals in soils and road dust; (3) Exploring the extent of heavy metal pollution in neighbouring soils. To this end, 33 samples were collected, including 03 road dust and 30 soil samples over different distances from 1m to 80m. The samples were analyzed by FRX. Results indicated that concentrations in road dust were higher than in soil. The distribution of heavy metal concentrations in dust is Fe>Pb>Zn>Cu>Cr>Ni, and the distribution in the ground is Fe>Pb>Cu>Zn>Cr>Ni in the direction of Biskra and in the opposite direction and decreases away from the road, while the distribution in the central solid ground is Fe> Cu>Cr>Pb>Zn>Ni. Climatic conditions such as wind, rainfall, temperature, humidity and the nature of the terrain were also significantly related to their enrichment in these roadside soils. The enrichment factor (EF) and the geo-accumulation index (Igeo) were calculated, as well as all elements with a (EF) that ranges from moderate to high to extremely contaminated, reflecting the high anthropogenic load of these metals in the study area and the results of the Igéo accumulation indices confirm the results obtained for the enrichment factor (EF).

This article is particularly interested in the numerical modeling of water hammer in a hydraulic circuit, taking into account the prevailing water temperature. The study concerns the propagation velocity of the wave and the amplitude of unsteady phenomena encountered in the circuit, as well as the severity and collapse of cavitations that are also considered as major risks. To conjecture the consequences of these phenomena, we were led to simulate a single-phase and two-phase transient flows in a hydraulic copper pipe system in a temperature range of 4–95 °C. To do this, we have developed a solver for the dynamic and continuity equations’ resolution. The method of characteristics is chosen for its capacities to solve these equations. Its application shows that it is robust and adapted to the problem studied. Two cavitations’ models and column separation have been incorporated; in this case, the Discrete Vapor Cavity Model (DVCM) and the Discrete Gas Cavity Model (DGCM). Moreover, in addition to the classic models of quasi-stable friction, of which the models of unsteady friction have been included, like the one based on the instantaneous acceleration proposed by Brunone and the one proposed by Vardy & Brown based on the convolution integral. Although single-phase and two-phase water hammers do not behave in the same way, the results obtained with these models show that the temperature produces a great effect on the hammer.

The Bouteldja coastal aquifer is one of the most important groundwater resources in North eastern of Algeria. The region is under a sub-humid climate with an average rainfall of 600-880 mm/y. The unconfined aquifer is constituted of Quaternary sands formations. The hydrogeological characteristics were determined based on previous reports. A very important inflow recharges the sandy aquifer in the Southeastern boundary, in relation to a fault network system linking the aquifer and the Obeira Lake area. Another inflow is observed at the Southern boundary in relation to the exchanges with the alluvial aquifer of Bouteldja. The purpose of the present study is to provide an initial assessment of the groundwater flow and water budget of this aquifer. To achieve this goal, a one-layer groundwater flow numerical model was developed using the MODFLOW-2005 code and the FREEWAT software, using the available data. The model was run in steady state conditions. Calibration was achieved using the piezometric measurements of May 2018 as calibration target. After several trials of manual calibrations, the model successfully simulated the groundwater flows directions and heads. Calibration efforts lead to an acceptable concordance (for the purpose of this study) between the estimated and calculated hydraulic conductivity and piezometric heads, except at the Eastern border. The analyses of the simulated inflow budget shows that aside the rainfall infiltration, exchanges with surface water bodies, the adjoining alluvial aquifer and the fault system provide a relevant amount of water. This significant recharge needs additional investigations. This numerical modeling exercise using MODFLOW, the FREEWAT software and GIS reached the objective of a preliminary description of the groundwater flow and it represents an acceptable starting point for more thorough hydrodynamic characterization of the Bouteldja coastal aquifer.

• The study of the phenomenon of flooding in an urban environment requires the integration of the city in its physical context, in this case the entire impluvium. Thus, the consideration of all the hydrological, morphometric and physical characteristics (topography, lithology, land cover...). In order to put in place appropriate measures to improve urban resilience and protect the population and their property in the capital of Algeria (City of Algiers), a hydrological modeling must be carried out upstream to evaluate the hydrological response of the watershed. This modeling was done using the auxiliary tool HEC-GEO HMS, an extension that works in a GIS environment (ArcGIS).
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The main objective of this study is to establish a perspective orientation of urban growth in an arid region (Biskra and its neighboring oases) in south east Algeria by mobilizing the capacities of attractiveness. Taking into account climatic parameters (wind speed and temperatures) and physical parameters (land cover, slopes, and distance from roads), our approach is based on remote sensing techniques of satellite data classification and Geographic Information Systems for spatial analysis. By means of a multi-criteria analysis a decision support map of sites suitable for future urban dynamics was carried out. The results obtained show that 48% (or 71,782.25 ha) of the study area is located on land with very low sensitivity to urbanization. 9.45% at high sensitivity, 29.13% at medium sensitivity, while 13.41% at low sensitivity. The medium sensitivity zone occupies a considerable area estimated at 29.13% (a total of 43,577.58 ha). Spatially, this is reflected in uncontrolled urban sprawl to the detriment of oases and agricultural land, or land not suited to the requirements of climatic comfort in arid regions. This urbanization sensitivity map forms the basis of the prospective design of an urban model adapted and appropriate to the conditions of the oasis ecosystem through the integration of other climatic parameters.

Modern wind turbines operate in continuously transient conditions, with varying speed, torque, and power based on the stochastic nature of the wind resource. This variability affects not only the operational performance of the wind power system, but can also affect its integrity under service conditions. Condition monitoring continues to play an important role in achieving reliable and economic operation of wind turbines. This paper reviews the current advances in wind turbine condition monitoring, ranging from conventional condition monitoring and signal processing tools to machine-learning-based condition monitoring and usage of big data mining for predictive maintenance. A systematic review is presented of signal-based and data-driven modeling methodologies using intelligent and machine learning approaches, with the view to providing a critical evaluation of the recent developments in this area, and their applications in diagnosis, prognosis, health assessment, and predictive maintenance of wind turbines and farms.

Closed greenhouse systems optimize internal climatic conditions for both reducing energy loss and high-quality yields. Nevertheless, careful monitoring of the parameters of the microclimate requires a better understanding of the thermal phenomena that coexist at the same time inside the greenhouses. In the present study, the surface radiation effect on the natural convection in the greenhouse was investigated numerically based a turbulent unsteady model. The k-ε model was adopted for the turbulent flow and the discrete ordinate (DO) method for the radiation heat transfer. Assuming a no isotherm conditions at the floor and roof faces of the greenhouse and for a Rayleigh number ranges from 0.6×10¹⁰ to 2.3×10¹⁰. The results showed a strong radiation effect on the thermal behavior near the walls and considerably reduces the flow dynamics within the greenhouse. The contribution of the radiation heat transfer on the total Nusselt number at least 50% greater than that without. The results obtained for the selected values of Rayleigh numbers are in good agreement with the experimental data of the literature.

In this paper, we propose a full-wave analysis for characterizing the resonant frequencies and bandwidths of high-temperature superconductor inverted microstrip printed on anisotropic substrates. Our proposed approach is based on Galerkin procedure in the Fourier transform domain (FTD) combining with the complex resistive boundary condition. With the use of suitable Green's functions in the FTD, the analysis is performed for the case where the superconducting rectangular patches printed on anisotropic substrate. The numerical results obtained using the proposed approach are compared with previously published numerical results computed by means of the electromagnetic simulator “IE3D software”. These comparisons were very good, which prove the correctness and the validity of the proposed method. It is found that the optical properties combined with optimally chosen structural parameters of anisotropic materials can be maintaining control of the resonant frequency and exhibiting wider bandwidth characteristics.

We establish global-posedness in time for the viscous Boussinesq equations in two dimensions of space with temperature-dependent diffusivity in the framework of a smooth vortex patch. We also provide the inviscid limit for velocity, temperature, and associated flow toward the system studied very recently in \cite{Paicu-Zhu} as soon as the viscosity goes to zero, and quantify the rate of convergence.

The main purpose of this study was to compare and evaluate the performance of two multicriteria models for landslide susceptibility assessment in Constantine, north-east of Algeria. The landslide susceptibility maps were produced using the analytic hierarchy process (AHP) and Fuzzy AHP (FAHP) via twelve landslides conditioning factors, including the slope gradient, lithology, land cover, distance from drainage network, distance from the roads, distance from faults, topographic wetness index, stream power index, slope curvature, Normalized Difference Vegetation Index, slope aspect and elevation. In this study, the mentioned models were used to derive the weighting value of the conditioning factors. For the validation process of these models, the receiver operating characteristic analysis, and the area under the curve (AUC) were applied by comparing the obtained results to The landslide inventory map which prepared using the archives of scientific publications, reports of local authorities, and field survey as well as analyzing satellite imagery. According to the AUC values, the FAHP model had the highest value (0.908) followed by the AHP model (0.777). As a result, the FAHP model is more consistent and accurate than the AHP in this case study. The outcome of this paper may be useful for landslide susceptibility assessment and land use management.

Using first-principles calculations, we study the structural, electronic and optical properties of the monolayer, bilayer and trilayer germanium monosulfide GeS. The results reveal an indirect semiconducting band gap for the monolayer and trilayer GeS, whereas the gap is direct for the bilayer GeS. Both the generalized gradient approximation and the screened hybrid functionals assess a decrease in band energy as the number of layers is improved. Furthermore, due to the high buckling of lattice structures, the optical spectra show significant degree of anisotropy. The number of layers engineers key optical parameters including the refractive index, the reflectivity absorption and provides the layered GeS with excellent absorption in the low energy region, namely the visible and UV range of the electromagnetic spectrum. Accordingly, 2D hexagonal GeS few-layers can be used as a highly promising material in the optoelectronic, ultraviolet optical nanodevices and photovoltaics.

Since bearing deterioration patterns are difficult to collect from real, long lifetime scenarios, data-driven research has been directed towards recovering them by imposing accelerated life tests. Consequently, insufficiently recovered features due to rapid damage propagation seem more likely to lead to poorly generalized learning machines. Knowledge-driven learning comes as a solution by providing prior assumptions from transfer learning. Likewise, the absence of true labels was able to create inconsistency related problems between samples, and teacher-given label behaviors led to more ill-posed predictors. Therefore, in an attempt to overcome the incomplete, unlabeled data drawbacks, a new autoencoder has been designed as an additional source that could correlate inputs and labels by exploiting label information in a completely unsupervised learning scheme. Additionally, its stacked denoising version seems to more robustly be able to recover them for new unseen data. Due to the non-stationary and sequentially driven nature of samples, recovered representations have been fed into a transfer learning, convolutional, long–short-term memory neural network for further meaningful learning representations. The assessment procedures were benchmarked against recent methods under different training datasets. The obtained results led to more efficiency confirming the strength of the new learning path.

In this paper, a new approach being different from the concept of DTC and IFOC for a robust torque control design for induction motor is addressed. The design is based on the framework of singularly perturbed system theory and linear varying parameter systems. In these systems, the rotor flux is considered to be a time-varying parameter in order to guarantee a robust torque control with LPV flux observer with respect to the speed and resistance variations. In fact, this observer is designed to estimate the rotor flux as well as an MRAS observer is introduced to estimate the mechanical speed and rotor resistance. The main feature of this proposed structure is the enhancement of robustness with flux, speed and rotor resistance variation. This improvement leads to a considerable decrease of the torque ripples and ensures the stability for the entire operating range. The obtained simulations and experimental results are used to validate the effectiveness of the proposed control strategy.

Tunnel FET is one of the promising devices advocated as a replacement of conventional MOSFET to be used for low power applications. Temperature is an important factor affecting the performance of circuits or system, so temperature associated reliability issues of double gate Tunnel FET and its impact on essential circuit design components have been addressed here. The temperature reliability investigation is based on double gate Tunnel FET, containing Si_1-xGe _x /Si, source/channel and HfO₂ high-k gate dielectric material. During investigation, it has been found that at high temperature application range ~ 300 K - to - 600 K,the Tunnel FET device design parameters exhibit weak temperature dependency with switching current (I_ON), while the off-state current (I_OFF) is slightly varying ~10⁻¹⁷A/μm-to-10⁻¹⁰A/μm. In addition, the impact of temperature on various device design element such as V_TH(i.e.,switching voltage),on-current (I_ON), off-current (I_OFF), switching ratio (I_ON/I_OFF) and average subthreshold slope (i.e., SS_avg), ambipolar current (I_AMB) have been done in this research work.The essential circuit design components for digital and analog/RF applications, such as current amplification factor(g_m) and its derivative (g_m’),the C-V components of device design, Cgg, Cgd and C_gs, cut - off frequency (ƒ_T) and gain band width (GBW) product have deeply investigated. In conclusion, the obtained results show that the designed double gate Tunnel FET device configuration and its circuit design components are suitable for ultra-low power circuit,system applications and reliable for hazardous temperature environment.

Condition Monitoring of photovoltaic systems plays an important role in maintenance interventions due to its ability to solve problems of loss of energy production revenue. Nowadays, machine learning-based failure diagnosis is becoming increasingly growing as an alternative to various difficult physical-based interpretations and the main pile foundation for condition monitoring. As a result, several methods with different learning paradigms (e.g. deep learning, transfer learning, reinforcement learning, ensemble learning, etc.) have been used to address different condition monitoring issues. Therefore, the aim of this paper is at least, to shed light on the most relevant work that has been done so far in the field of photovoltaic systems machine learning-based condition monitoring.

To ensure the continuity of electric power generation for photovoltaic systems, condition monitoring frameworks are subject to major enhancements. The continuous uniform delivery of electric power depends entirely on a well-designed condition maintenance program. A just-in-time task to deal with several naturally occurring faults can be correctly undertaken via the cooperation of effective detection, diagnosis, and prognostic analyses. Therefore, the present review first outlines different failure modes to which all photovoltaic systems are subjected, in addition to the essential integrated detection methods and technologies. Then, data-driven paradigms, and their contribution to solving this prediction problem, are also explored. Accordingly, this review primarily investigates the different learning architectures used (i.e., ordinary, hybrid, and ensemble) in relation to their learning frameworks (i.e., traditional and deep learning). It also discusses the extension of machine learning to knowledge-driven approaches, including generative models such as adversarial networks and transfer learning. Finally, this review provides insights into different works to highlight various operating conditions and different numbers and types of failures, and provides links to some publicly available datasets in the field. The clear organization of the abundant information on this subject may result in rigorous guidelines for the trends adopted in the future.

We analyzed the influence of land use and water physical-chemical characteristics on the trait composition of benthic macroinvertebrates in arid-land streams of North-East Algeria. Macroinvertebrates were sampled in the spring season of 2015, 2017 and 2018 at 36 sampling sites distributed along 5 streams of the Belezma biosphere reserve. Samples were taken from the various substratum types using a Surber net. Most of the variability of the trait-environment relationship was explained by increasing temperature and conductivity along the downstream gradient. Whilst agriculture at higher elevations did not have a great influence on the functional trait composition of macroinvertebrate communities, agriculture and urbanization at lower elevations generated significant deviations from predictable functional structures. Owing to the natural downstream decrease in community diversity in streams of the study region, entire taxa and/or functional groups were more likely to be wiped out in response to anthropogenic perturbations at lower elevations. Despite human activities, climate-related variables in arid lands play a major role on hydrological regimes that effect instream habitats, water chemistry, and macroinvertebrate communities. Given the environmental constraints in arid-land streams of North Africa, even slight increases in anthropogenic pressure can have negative effects on the taxonomic and functional composition of macroinvertebrate communities.

The issue of robustness of stability has been prominent in the literature on control theory over the last two decades. An important state-space approach to robustness analysis is the stability radii theory. The robust stability problems of infinite dimensional systems subjected to stochastic bounded structured perturbations have been studied using the stability radius approach. In the applications it is important to study these problems in the case where the perturbations operator structure are unbounded, because it covers the case of partial differential equations with boundary and ..

This paper presents the first description of the mcr-5.1 gene in a colistin-resistant Cupriavidus gilardii isolate from well water that supplies a maternity hospital in Algeria. The whole-genome sequence of this strain showed the presence of putative β-lactamase, aac(3)-IVa, and multidrug efflux pump-encoding genes, which could explain the observed multidrug resistance phenotype. Our findings are of great interest, as we highlight a potential contamination route for the spread of mcr genes. 

IMPORTANCE Colistin resistance mediated by mcr genes in Gram-negative bacteria has gained significant attention worldwide. This is due to the ability of these genes to be horizontally transferred between different bacterial genera and species. Aquatic environments have been suggested to play an important role in the emergence and spread of this resistance mechanism. Here, we describe the first report of an mcr-5-positive Cupriavidus gilardii aquatic isolate through its isolation from well water in Algeria. The significance of our study is in shedding the light on an important environmental reservoir of mcr genes.