Diatom and Diatomite: Different Focus on Natural Media to Material Science Path

Bio-silica issued from diatom, a microalgae, is attracted increasing attention in material science thanks to its peculiar nanoarchitecture and related properties with versatile applications. The present work is a deep analysis on morphological and chemical properties of bio-silica issued from fossil origin (diatomaceous earth) and living one (algal paste). An optimization in purification protocol was performed to obtain multiparous bio-silica from its raw media with keeping its original shape entirely. Multiple characterization methods as scanning electronic microscopy (SEM), infrared spectroscopy, x-ray diffraction (DRX), X-ray photoelectron spectroscopy (XPS), energy dispersive X-ray spectroscopy (EDX), nitrogen adsorption and inverse gas chromatography (IGC), were used to check the purification protocol efficiency as well as to gather accurate information on morphology and chemical composition of diatom material obtained in large amount.

Dietary Surveys Carried out among Diabetic Patients Hospitalized in the Metabolic and Endocrine Diseases Department of the C.H.U-B

A varied and balanced diet has always been essential in the optimal management of diabetes. The objective of this work was to evaluate dietary surveys among 50 diabetic patients hospitalized in the metabolic and endocrine diseases department of the Brazzaville Hospital and University Center. This survey was carried out using two methods: dietary history and 24-hour recall. The results relating to the dietary history revealed in the patients a dietary imbalance characterized by snacking at meals, non-compliance with a balanced diet and a high frequency of consumption of foods rich in simple sugar. and saturated fats. Regarding the 24-hour recall, the survey showed that the average blood sugar levels of hospitalized patients increased depending on the number of meals. This meant that these hyperglycemias (2 to 5 g/L) observed in these patients exceeded three meals per day and required, among other things, an increase in insulin intake or doses. The age groups of diabetic patients were also divided. These age groups had partly defined the types of diabetes encountered. Regarding body mass index, women had a body mass index greater than 30 kg/m2 compared to men. This increase in body mass index was explained by being overweight or even obese due to excess body fat.

Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

Stochastic seismic response of multi-layered soil with random layer heights

This paper deals with the effect of layer height randomness on the seismic response of a layered soil. These parameters are assumed to be lognormal random variables. The analysis is carried out via Monte Carlo simulations coupled with the stiffness matrix method. A parametric study is conducted to derive the stochastic behavior of the peak ground acceleration and its response spectrum,the transfer function and the amplification factors. The input soil characteristics correspond to a site in Mexico City and the input seismic accelerations correspond to the Loma Prieta earthquake. It is found that the layer height heterogeneity causes a widening of the frequency content and a slight increase in the fundamental frequency of the soil profile,indicating that the resonance phenomenon is a concern for a large number of structures. Variation of the layer height randomness acts as a variation of the incident angle,i.e.,a decrease of the amplitude and a shift of the resonant frequencies.

Fault Diagnosis in Robot Manipulators Using SVM and KNN

In this paper,Support Vector Machine(SVM)and K-Nearest Neighbor(KNN)based methods are to be applied on fault diagnosis in a robot manipulator.A comparative study between the two classifiers in terms of successfully detecting and isolating the seven classes of sensor faults is considered in this work.For both classifiers,the torque,the position and the speed of the manipulator have been employed as the input vector.However,it is to mention that a large database is needed and used for the training and testing phases.The SVM method used in this paper is based on the Gaussian kernel with the parametersγand the penalty margin parameter“C”,which were adjusted via the PSO algorithm to achieve a maximum accuracy diagnosis.Simulations were carried out on the model of a Selective Compliance Assembly Robot Arm(SCARA)robot manipulator,and the results showed that the Particle Swarm Optimization(PSO)increased the per-formance of the SVM algorithm with the 96.95%accuracy while the KNN algo-rithm achieved a correlation up to 94.62%.These results showed that the SVM algorithm with PSO was more precise than the KNN algorithm when was used in fault diagnosis on a robot manipulator.

Quasi-Local Energy Distribution and Thermodynamics of Reissner-Nordstrom Black Hole Surrounded by Quintessence

We investigate quasi-local energy distribution and thermodynamics of the Reissner-Nordstr6m black hole space-time surrounded by quintessence. We use the quasi-local energy distribution from Einstein energy-momentum complex. We plot the variation of the energies, temperature and heat capacity with the state parameter related to the quintessence ωq. We show that due to the presence of quintessence, the total energy of the outer region as well as the temperature and heat capacity decreases with the increase of the density of quintessence, while the total energy of the black hole region increases.

Travelling Wave Solutions to Stretched Beam's Equation: Phase Portraits Survey

In this paper, following the phase portraits analysis, we investigate the integrability of a system which physically describes the transverse oscillation of an elastic beam under end-thrust. As a result, we find that this system actually comprises two families of travelling waves： the sub- and super-sonic periodic waves of positive- and negative- definite velocities, respectively, and the localized sub-sonic loop-shaped waves of positive-definite velocity. Expressing the energy-like of this system while depicting its phase portrait dynamics, we show that these multivaiued localized travelling waves appear as the boundary solutions to which the periodic travelling waves tend asymptotically

Dynamical System Approach to a Coupled Dispersionless System： Localized and Periodic Traveling Waves

We investigate the dynamical behavior of a coupled dispersionless system describing a current-conducting string with infinite length within a magnetic field. Thus, following a dynamical system approach, we unwrap typical miscellaneous traveling waves including localized and periodic ones. Studying the relative stabilities of such structures through their energy densities, we find that under some boundary conditions, localized waves moving in positive directions are more stable than periodic waves which in contrast stand for the most stable traveling waves in another boundary condition situation.

Physico-Chemical and Mineralogical Characterization of Two Clay Materials of the Far North Region of Cameroon(Makabaye,Maroua)

To contribute to the valorization of local materials, the physico-chemical and mineralogical characterization of two clay materials MJ and MN collected in the Mayo Tsanaga river which crosses the Makabaye district of Maroua (Cameroon) was carried out. For this purpose, various methods of characterization have been used, namely granulometric analysis, Atterberg limits, X-ray fluorescence spectrometry and X-ray diffraction. It is apparent from the granulometry that the clay materials studied titrate 33.77% of clays for MJ against 44.13% for MN. The plasticity indices Ip with values IpMJ = 19.27% and IpMN = 23.4% place the materials in the plastic domain and offer them the possibility to being shaped into objects. The chemical composition of the MJ and MN materials reveals that the silicon oxide SiO2, the aluminumoxide Al2O3 and iron oxide Fe2O3 are their main constituents. The X-ray diffraction of the MJ and MN materials shows that they consist mainly of quartz with associated kaolinite, illite, montmorillonite, perlialite, dickite, nacrite, amesite, albite, brookite and anorthite. In addition to these, 2/1 minerals such as muscovite, nontronite, glauconite, and phlogopite are also identified in the MJ material. The peaks of sanidine, microcline and gismondine are also found in the MN material. The materials being rich in clay minerals 2/1 can be valorized in the adsorption and the absorption of the oils and greases and in the waterproofing of the grounds. The presence of quartz, kaolinite and illite is undoubtedly favorable for the manufacture of ceramic products in terracotta. These products will be obtained at a relatively lower temperature due to illite, feldspars and iron minerals that provide vitrification during firing by forming eutectics. The aluminosilicate amorphous phases contained in the studied materials can be exploited to produce geopolymer cements and concretes.

Soliton Structure of a Higher Order （2＋1）-Dimensional Nonlinear Evolution Equation of Barothropic Relaxing Media beneath High-Frequency Perturbations

From the dynamical equation of barothopic relaxing media beneath pressure perturbations, followed with the reductive perturbative anadysis, we derive and investigate the soliton structure of a （2＋1）-dimensional nonlineax evolution equation describing high-frequency regime of perturbations. Thus, by means of the Hirota＇s bilinearization method, we unearth three typical patterns of loop-, cusp- and hump-like shapes depending strongly upon a dissipation parameter.

Reduction of the Additives Migration from Poly Vinyl Chloride Films by the Use of Permanent Plasticizers

This aim of this work is to study the partial replacement of the plasticizer ordinarily used di-octyl phtalate (DOP) by the permanent plasticizers ethylene-vinyl-acetate (EVA) and acrylonytrile-bu- tadiene-styrene (ABS) in order to reduce migration of additives initially contents in polyvinyl chloride (PVC) stabilized with expoxidized sunflower oil (ESO). Migration tests with agitation to 40°C in sunflower oil and ethanol at 15% were made. Migration phenomenon was studied on the basis of the PVC samples mass variations, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) analysis. The results showed the effectiveness of the approach consisting in the partial substitution of DOP by plasticizers of polymeric nature. The following order concerning the migration of additives was found: DOP (40) > DOP:EVA > (30/10) DOP:ABS (30/10). Furthermore, all the measured values of overall migrations were lower than the maximum allowable overall migration: 10 mg-dm-2.

Laboratory Evaluation of the Stiffness Modulus of a Modified Bituminous Concrete with PR PLAST Sahara

Uneven roads surface can be observed on bituminous pavements. This is due to moving loads and climate conditions. If the observed deformations exceed the elastic limit, important damages can occur, so new materials are used to improve the stiffness modulus of bituminous mixtures. To achieve this, a modified bituminous concrete by addition of the PR PLAST Sahara （produced by PR industries and PLAST for Plastic） mainly used in arid region has been studied. The use of this additive at various percentages 0.1, 0.3, 0.6 and 0.9 by weight of bituminous concrete has been investigated to determine its stiffness modulus. An experimental design using the Taguchi tables has been elaborated to reduce the number of tests. Marshall and NAT （Nottingham asphalt tester） tests have been carried out, and a mathematical model of the stiffness modulus has been proposed.

Comparative Study of the DTC-IM Speed Controller Based on Artificial Intelligence

Recently, artificial intelligence technique is increasingly receiving attention in solving complex and practical problem and they are widely applying in electrical machine domain. The authors consider also the direct torque control （DTC） as an alternative to conventional methods of control by pulse width modulation （PWM） and by Field oriented control （FOC）, so the application of the DTC based on artificial intelligence can show more advantages and simplified control algorithms with high performance. For this reason, the objectives of this paper can be divided into two parts, the first part is to apply neural networks and fuzzy logic techniques to the DTC control in the presence of a loop speed control comparing to the conventional regulators （as PI） to show the feasibility of these approaches, the second part is to further improve the performance of the neural network by using a neural-fuzzy regulator which combine the advantages of two techniques. Simulation results confirm the validity of the proposed techniques.

Theoretical Investigation of Electronic and Optical Properties of Si/SiGe Quantum Cascade Structures

This paper reviews the basic properties of the SiGe alloy, presents some new results on its electronic and optical properties, and discusses the approach that has been followed to model quantum wells containing SiGe layers for applications in quantum cascade lasers. The shape of the confining potential, the subband energies and their eigen envelope wave functions are calculated by solving a one-dimensional Schr?dinger equation. The calculations of optical parameters are used to optimize the Si/SiGe quantum cascade structures. Our results are found to be in good agreement with other calculations.

Comparative Study between Different Modulation Strategies for Five Levels NPC Topology Inverter

The object of this paper is the study of various modulation strategies applied to the five-level inverter neutral-point-clamped NPC topology. Firstly we presented the structure of the voltage inverter three-phase five-level NPC topology. After that we model the inverter and the inverter are controlled by different strategies and then we made a comparative study between the results given by different strategies.

Direct Power Control of Variable Wind Speed Based on the Doubly Fed Asynchronous Machine

In this work, the authors propose the study of a wind speed variable based on the DFAM （double fed asynchronous machine）. The model of the turbine is drawn from the classical equations describing the operation of a variable wind speed. The torque generated by the turbine is applied to the DFAM directly connected on the network side and the stator via a bidirectional converter side rotor. This configuration allows velocity variations of ±30% around the synchronous speed and the converter is then sized to one third of the rated power of the machine. The DFAM is controlled by a control vector ensuring operation of the wind turbine power coefficient maximum.

Implementation of Particle Swarm Optimization Algorithm in Matlab Code for Hyperelastic Characterization

The purpose of this paper is to demonstrate the applicability of Particle Swarm Optimization algorithm to determine material parameters in incompressible isotropic elastic strain-energy functions using combined tension and torsion loading. Simulation of rubber behavior was conducted from the governing equations of the deformation of a cylinder composed of isotropic hyperelastic incompressible materials. Four different forms of strain-energy function were considered based respectively on polynomial, exponential and logarithmic terms to reproduce load force (N) and torque (M) trends using natural rubber experimental data. After highlighting the minimization of the objective function generated in the fitting process, the study revealed that a particle swarm optimization algorithm could be successfully used to identify the best material parameters and characterize the behavior of rubber-like hyperelastic materials.

Dissipative Discrete System with Nearest-Neighbor Interaction for the Nonlinear Electrical Lattice

A generalized dissipative discrete complex Ginzburg-Landau equation that governs the wave propagation in dissipative discrete nonlinear electrical transmission line with negative nonlinear resistance is derived. This equation presents arbitrarily nearest-neighbor nonlinearities. We analyze the properties of such model both in connection to their modulational stability, as well as in regard to the generation of intrinsic localized modes. We present a generalized discrete Lange-Newell criterion. Numerical simulations are performed and we show that discrete breathers are generated through modulational instability.

The effects of step inclination and air injection on the water flow in a stepped spillway:A numerical study

In this work, we perform a numerical study of a water flow over a stepped spillway. This flow is described by the Reynolds averaged Navier-Stokes equation （RANS） associated with the turbulence k - model. These equations are solved using a commercial software based on the finite volume scheme and an unstructured mesh. The air-water flow was modeled using volume of fluid （VOF） and multiphasic methods. The characteristics of the profile, etc.. We analyze the effects on the flow structure of the flow were investigated including the total pressure, the velocity steps and countermarch inclination, the air injection through the countermarch into the water flow and the dynamics water discharges. Results show that the inclination of the countermarch relative to the vertical and the air injection into the water flow increase the total pressure in the neighbourhood of the steps.