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In general, the lower prosthesis consists of socket, leg, ankle, and foot. The socket is the crucial part for connecting the remaining part of the limb and the prosthesis, as it is essential to distribute the load to the amputation patient to provide comfort and add to the proper appearance of the amputation patient. A research that was included methods of manufacturing it, choosing the composite materials necessary for the design, higher durability, lighter weight, and less cost. Previous research used polymer composites reinforced with fibers as glass fibers, carbon fiber, and Kevlar. Other researchers have studied natural fibers' use as reinforcement fiber by mixing resin materials or adding nanomaterials to modify the mechanical properties and reduce costs. After calculating performing the required mechanical tests such as tensile, fatigue, and impact testing, the required properties of the composite material are found, where the prosthesis socket is manufactured below the knee with the application of different loads of the socket. A review of socket models used in developing countries was performed with regard to design, modeling, and finite element analysis (FEA). This review aims to study the material's behavior and mechanical properties by using natural fibers for manufacturing prosthetic sockets. The review discusses the socket manufacture methods proposed to develop the socket industry based on natural fibers to reduce the hot and humid environment using Kenaf and other natural fibers.

One of the most important preliminary tasks in a transcription system of historical document images is text line segmentation. Nevertheless, this task remains complex due to the idiosyncrasies of ancient document images. In this article, we present a complete framework for text line segmentation in historical Arabic or Latin document images. A two-step procedure is described. First, a deep fully convolutional networks (FCN) architecture has been applied to extract the main area covering the text core. In order to select the highest performing FCN architecture, a thorough performance benchmarking of the most recent and widely used FCN architectures for segmenting text lines in historical Arabic or Latin document images has been conducted. Then, a post-processing step, which is based on topological structure analysis is introduced to extract complete text lines (including the ascender and descender components). This second step aims at refining the obtained FCN results and at providing sufficient information for text recognition. Our experiments have been carried out using a large number of Arabic and Latin document images collected from the Tunisian national archives as well as other benchmark datasets. Quantitative and qualitative assessments are reported in order to firstly pinpoint the strengths and weaknesses of the different FCN architectures and secondly to illustrate the effectiveness of the proposed post-processing method.

Ni0.4Cd0.3Zn0.3Fe2O4 ferrites have been prepared through the use of sol-gel method at 900 °C and 1100 °C. Rietveld refinements of XRD patterns indicate that the prepared samples crystallize in the cubic spinel structure. Lattice constant and grain size are found to increase with sintering temperature. Magnetic measurements show that the maximum magnetization (Ms) rises, whereas both coercivity (Hc) and remanence (Mr) decrease when increasing the sintering temperature. Frequency and temperature dependence of electrical conductivity, electrical modulus, and electrical impedance have been studied using impedance spectroscopy technique. As the sintering temperature increases, the conductivity of the samples increases. The variation of imaginary part of modulus (M″) displays the presence of an electrical relaxation phenomenon and non-Debye nature. Nyquist representations have been analyzed using an electrical equivalent circuit. The obtained results reveal that the conduction mechanism of the samples is achieved basically of the grain boundary contribution.

In this article, a theoretical study was performed in order to elucidate the adsorption mechanism of methylene blue (MB) on Cortaderia selloana flower spikes (FSs) and on Cortaderia selloana flower spikes derived carbon fibers (CFs). For this objective, the Hill model developed using grand canonical ensemble was successfully applied. This model represents the general case of Langmuir model assuming that the receptor sites of CFs and FSs accepts a variable number of MB molecules and is defined by the number of molecules captured per adsorbent site (n). Based on the model parameters, the MB adsorption geometry was described at different temperatures indicating that the MB molecules were fixed by an angled position on the investigated adsorbents. The elucidation of the adsorption capacity showed that CFs was more effective for removing MB from wastewater than FSs. This behavior was detailed and corroborated by an energetic investigation. Moreover, the adsorption energy varies from 22.187 to 25.378 kJ mol−1 for FSs and from 24.503 to 27.412 kJ mol−1 for the CFs reflecting a physisorption process. Interestingly, and based on this energetic investigation, it was deduced that the adsorption mechanism of MB was endothermic. Excellent correlation between the number of molecules captured by the receptor site, the adsorption capacity, and the adsorption energy was observed.

Text line localization in document images is still considered an open research task. The state-of-the-art methods in this regard that are only based on the classical image analysis techniques mostly have unsatisfactory performances especially when the document images i) contain significant degradations and different noise types and scanning defects, and ii) have touching and/or multi-skewed text lines or overlapping words/characters and non-uniform inter-line space. Moreover, localizing text in ancient handwritten Arabic document images is even more complex due to the morphological particularities related to the Arabic script. Thus, in this paper, we propose a hybrid method combining a deep network with classical document image analysis techniques for text line localization in ancient handwritten Arabic document images. The proposed method is firstly based on using the U-Net architecture to extract the main area covering the text core. Then, a modified RLSA combined with topological structural analysis are applied to localize whole text lines (including the ascender and descender components). To analyze the performance of the proposed method, a set of experiments has been conducted on many recent public and private datasets, and a thorough experimental evaluation has been carried out.

Porous materials constitute an attractive research field due to their high specific surfaces; high chemical stabilities; abundant pores; special electrical, optical, thermal, and mechanical properties; and their often higher reactivities. These materials are currently generating a great deal of enthusiasm, and they have been used in large and diverse applications, such as those relating to sensors and biosensors, catalysis and biocatalysis, separation and purification techniques, acoustic and electrical insulation, transport gas or charged species, drug delivery, and electrochemistry. Porous carbons are an important class of porous materials that have grown rapidly in recent years. They have the advantages of a tunable pore structure, good physical and chemical stability, a variable specific surface, and the possibility of easy functionalization. This gives them new properties and allows them to improve their performance for a given application. This review paper intends to understand how porous carbons involve the removal of pollutants from water, e.g., heavy metal ions, dyes, and organic or inorganic molecules. First, a general overview description of the different precursors and the manufacturing methods of porous carbons is illustrated. The second part is devoted to reporting some applications such using porous carbon materials as an adsorbent. It appears that the use of porous materials at different scales for these applications is very promising for wastewater treatment industries.

The statistical physics approach has been well studied by our research team for liquid and gaseous adsorption systems. This treatment is based on the grand canonical partition function to give new interpretations of the adsorption process at molecular level for chemical senses: olfaction and taste. This work represents a contribution to understand the olfaction mechanism of four of enantiomeric terpenes by applying a statistical physics treatment that allows giving a physico-chemical meaning to parameters involved in the analytical model. It is possible to estimate the number of adsorbed molecules per site, the anchorage number, the receptor density, the concentration at half saturation and the molar adsorption energy. Through this selection of the best fitting model and through fitted values of these parameters, we showed that the adsorption of carvone and limonene enantiomers is not a multilayer process but a monolayer monosite process (monolayer adsorption model with identical and independent sites (n ≠ 1)). The physico-chemical model parameters can be used for the energetic characterization of the interactions between the carvone and the limonene enantiomers and the human olfactory receptor OR1A1 and the determination of an olfactory band of order of 14 kJ/mol, 7 kJ/mol, 9 kJ/mol, 8 kJ/mol for (R)-(−)-carvone, (S)-(+)-carvone, (R)-(+)-limonene and (S)-(−)-limonene, respectively, through the determination of the adsorption energy values and the adsorption energy distributions (AEDs). Thanks to the grand canonical formalism in statistical physics, the negative values of the Gibbs free enthalpy indicate that the adsorption process of the four enantiomeric terpenes onto the human olfactory receptor OR1A1 was spontaneous. The exothermic adsorption mechanism involved in the olfactory perception was explained via the negative values of the internal energy.

Steric and energetic characterizations were performed for the adsorption of eugenol (EG), vanillin and ethyl vanillin (EV) onto the mouse eugenol olfactory receptor mOR-EG by using a proposed model expression established by statistical physics methods. We started with a modeling of dose-response curves. The calculated curves fit well the experimental data and the physico-chemical model parameters can be used for the characterization of the interactions between the eugenol, vanillin and ethyl vanillin molecules and the mouse eugenol receptor and the determination of the olfactory band for these three odorant molecules through the determination of the adsorption energy values and the adsorption energy distributions. Furthermore, thermodynamic functions of the odorant adsorption such as the configurational entropy, Gibbs free enthalpy and internal energy were calculated and their negative values indicate that the adsorption process included in the olfaction mechanism was exothermic and spontaneous nature.

Fiberboards were manufactured from filled phenolic resins (lignin-formaldehyde or glyoxal) and petiole date palm fibers. Lignin was obtained from paper industry waste black liquor. To improve lignin reactivity and increase the bonding strength between matrix and fiber, phosphogypsum (PG) was used as a filler in the resin formulation from 1 to 3 wt%. Phosphogypsum exhibited excellent performance as binder; this was verified by a decrease in the gelation time and an increase in internal bond (IB) in fiberboards. The analysis confirmed that resin reactivity depends on aldehyde types (glyoxal or formaldehyde) and PG proportion. Most of the obtained boards were of good quality [modulus of elasticity (MOE) up to 1230 MPa; modulus of rupture (MOR) up to 25 MPa; internal bond (IB) up to 0.23 MPa; water absorption (WA) up to 28%].

The Mg 50 Ni 45 Cr 5 alloy for hydrogen storage is prepared by mechanical alloying. First, using the X-ray diffraction (XRD) and the scanning electron microscopy (SEM) we examine the morphology and the structure of the substrate. The obtained results highlight the effectiveness of this alloy in loading hydrogen as it is a nanocrystalline and a ductile one. Second, we attempt to justify these expectations using the statistical physic, precisely the model monolayer with two levels of energy, in modeling a hydrogen absorption and desorption isotherms on Mg 50 Ni 45 Cr 5 alloy at four temperatures T = 275 K, T = 300 K, T = 325 K and T = 350 K. The model has six physicochemical parameters deduced from the fitting of the isotherms, they are divided by two categories of steric and energetic parameters. Thanks to these parameters we compare the absorption and desorption processes, in order to highlight the hysteresis phenomenon encountered during the hydrogen sorption.

Different composites panels were prepared using two granulometrys of fibers from date palm petiole (PDPF) and bio-matrix from lignin-glyoxal-resin (LGR). The composites panels were manufactured at different PDPF percentages ranging from 10 to 70 wt%. Mechanical properties of the prepared samples were evaluated by measuring tensile strength, Young`s modulus and elongation. The obtained results showed that the sample made from fibers/thermo pressed resin 50/50 wt% has the best mechanical properties. The increase of the granulometry of the fibers from 250 to 500 µm results in an improvement of the tensile strength and Young`s modulus values. However, the LGR matrix reinforced with PDPF showed high values of water diffusion coefficient when compared to the unreinforced LGR.

We have investigated the correlation between magnetocaloric and electrical properties of La0.47Pr0.2Pb0.33MnO3 perovskite prepared using the sol–gel method. Rietveld analysis of X-ray diffr...

Based on statistical physics elements, the equilibrium adsorption of diclofenac (DFC) and nimesulide (NM) on activated carbon was analyzed by a multilayer model with saturation. The paper aimed to describe experimentally and theoretically the adsorption process and study the effect of adsorbate size using the model parameters. From numerical simulation, the number of molecules per site showed that the adsorbate molecules (DFC and NM) were mostly anchored in both sides of the pore walls. The receptor sites density increase suggested that additional sites appeared during the process, to participate in DFC and NM adsorption. The description of the adsorption energy behavior indicated that the process was physisorption. Finally, by a model parameters correlation, the size effect of the adsorbate was deduced indicating that the molecule dimension has a negligible effect on the DFC and NM adsorption.

International audience; Large mineral fillers have long been used in papermaking for many reasons. The finish of the writing and printing paper depends on using the fillers as internal or surface treatments. During this study, Tamarisk sp. and Prunus amygdalus pulp-filled papers with raw phosphogypsum (PG) and calcined PG (CPG) at different percentages were studied. First, the prepared minerals (treated and untreated ones) were characterized by different analytical methods such as SEM and EDS. Subsequently, different handsheets with a basis weight 60 g−2 were prepared on a Rapid Khöten sheet former following the standard method. The added amounts of PG and CPG fillers were included from 0% to 15% based on the pulp. The effects of incorporation as well as the quality fillers into physical and optical properties were assessed. It can be deduced that the incorporation of CPG at 800 °C improved filler retention by as high as 92%, and the optical properties of the filled paper was strikingly enhanced, while the strength properties were practically negatively influenced. It was clear that calcinationstepsreduce the fiber–filler–fiber bond. Thus, results are in accordance with the SEM observation, which confirmed the obtained physical properties.

On most document image transcription, indexing and retrieval systems, text line segmentation remains one of the most important preliminary task. Hence, the research community working in document image analysis is particularly interested in providing reliable text line segmentation methods. Recently, an increasing interest in using deep learning-based methods has been noted for solving various sub-fields and tasks related to the issues surrounding document image analysis. Thanks to the computer hardware and software evolution, several methods based on using deep architectures continue to outperform the pattern recognition issues and particularly those related to historical document image analysis. Thus, in this paper we present a novel deep learning-based method for text line segmentation of historical documents. The proposed method is based on using an adaptive U-Net architecture. Qualitative and numerical experiments are given using a large number of historical document images collected from the Tunisian national archives and different recent benchmarking datasets provided in the context of ICDAR and ICFHR competitions. Moreover, the results achieved are compared with those obtained using the state-of-the-art methods.

In this paper, an adsorption modeling has been presented to describe the interactions of a binary mixture of l-muscone and d-muscone with the mouse muscone receptor MOR215-1. The formulation of the 2-dimensional monolayer models with identical and two types of sites for the perceived response of odor binary mixture odor are based on statistical physics and some theoretical hypothesis, in order to model pure and binary mixture dose-response curves. Thanks to the grand canonical ensemble of statistical physics, some pertinent physico-chemical parameters describing the adsorption process were introduced in the analytical model expressions. The results showed a high correlation of the 2-dimensional monolayer model using two types of sites with binary mixture of l-muscone and d-muscone response curve. In this model, six physico-chemical parameters derived from the fitting of the experimental data by a numerical simulation were discussed. Furthermore, these statistical physics models include physico-chemical parameters specific to the respective effects of each compound in the binary mixture, which may help to clarify the inhibitory effects that are often seen in l-muscone and d-muscone mixture through the determination of the involved new steric parameters. In addition, the calculation of the molar adsorption energies showed that the two muscone enantiomers and their racemic were physisorbed onto cell surface neurons.

Using the grand canonical ensemble in statistical physics, a hydrogen absorption and desorption isotherms on LaNi4.85 Al0.15 alloy have been modeled by a monolayer model with two level of energy. The model has six physicochemical parameters which are deduced from the fitting of the isotherms at three temperatures T = 298 K, T = 303 K and T = 313 K. These parameters were used to better understand and compare between the absorption and desorption phenomena. A macroscopic study is achieved through thermodynamic functions as the internal energy, the entropy, the free enthalpy, the chemical potential, the enthalpy, and the free energy. We proved the coexistence of the α and β phases during absorption process.

Modeling of absorption and desorption isotherms of hydrogen on LaNi4.85Al0.15 alloy at 298 K, 303 K and 313 K has been achieved through the use of grand canonical ensemble in statistical physics. In fact, a monolayer model with two levels of energy has been adopted to better fit the experimental data. Besides, six physicochemical parameters have been used to better describe the absorption and desorption processes from the point of view of α and β phases. These parameters are divided into two types. The first type of parameters contains four main parameters, namely the number of atoms per site, nα and nβ, and the densities of hydrogen receptor sites Nmα as well as Nmβ. The second type of parameters are mainly the two energetic parameters Pα and Pβ which respectively refer to the pressures at half saturations for the α phase and the β phase. Thanks to these steric and energetic parameters, we could compare the absorption and desorption processes to highlight the evolution of these parameters during hysteresis encountered in the desorption isotherms.

The olfactory response curves of muscone enantiomers on the mouse muscone receptor MOR215-1 modeling by a statistical physics treatment led us to better understand the olfactory phenomenon. Our objective in this modeling is to select an adequate model that presents a significant correlation with the olfactory response curves. The application of the grand canonical ensemble in statistical thermodynamics introduces some physico-chemical parameters in the theoretical model which allows to attain an expression of the single olfactory response Rsin. Fitting results showed that the muscone enantiomers ( l -muscone and d -muscone) followed an adsorption model with one monolayer onto identical sites. The calculation of the molar adsorption energy showed that the two muscone enantiomers were physisorbed onto cell surface neurons. Then, the configurational entropy which gave an idea about order and disorder, was calculated according to the appropriate model.

In this work, statistical physics treatment has been employed to understand the olfaction mechanism through the study of the dose-olfactory response of putative adsorption process of key food odorants onto the human olfactory receptor OR2W1. This is in order to obtain new steric and energetic characterizations at the molecular level of this chemical sense system. Three models have been proposed: a monolayer, a double layer and a three layers model. The monolayer model with identical and independent receptor sites has been chosen as an appropriate one to present a good correlation with the experimental dose-response curves. Indeed, the numerical values of the three fitted parameters (RM, n, C1/2) are used to characterize the size of the human olfactory receptor binding sites and the interactions between eight key food odorants i.e., (R)-(−)-carvone, (S)-(−)-limonene, (R)-(+)-limonene, 2-phenylethanthiol, 3-mercaptohexyl acetate, methyl cinnamate, cinnamyl acetate and 2-phenylethyl acetate and OR2W1 through the receptor site size distribution (RSD) and to determine an olfactory band of these odorants through the determination of the adsorption energy values and the adsorption energy distributions (AEDs).

The current research aims to use plants as substituent of chemical additives in the elimination of pollutants, therefore making polluting industries environmentally friendly. In the present work, the potential use of Stipa tenacissima (cultivated in the dry region of North Africa) in the removal of H2S in aqueous solution was investigated. The obtained experimental results showed successful elimination of H2S through reaction with Stipa tenacissima fibers in an alkaline aqueous medium. The effect of Stipa tenacissima’s mass, temperature ranging 20–60 °C, and aeration on sulfide removal efficiency was examined. The study clearly revealed that the aeration processes enhanced the removal reaction, and the increase in temperature gave a better removal rate with an optimal mass ratio of Stipa tenacissima of 0.1 g to eliminate 0.2 mg H2S.

The segmentation and classification of Lymph Nodes (LNs) is a fundamental but challenging step in the analysis of medical images of cervical cancer. Both tasks can leverage morphological features such as size, shape, contour, and heterogeneous appearance. However, these features might vary with the progressive state of LNs. Hence, accurate detection of LNs boundary is an essential step sing to classify LN as suspect (malignant) and non-suspect (benign). However, manual delineation of LNs might produce classification errors due to the inter and intra-observer variability. Semi-automatic and automatic LNs segmentation methods are greatly desired as they would help improve patient diagnosis and treatment processes. Currently, Magnetic Resonance Imaging (MRI) is widely used to diagnose cervical cancer and LN involvement. Diffusion Weighted (DW)-MRI exhibits metastatic LN as bright regions. This paper presents a semi-automatic segmentation and classification method of LNs. Specifically, we propose a novel approach which leverages (1) the complementarity of structural and diffusion MR images through a fusion step and (2) morphological features of the segmented metastatic LNs for classification. The contribution of our proposed algorithm is threefold. First, we fuse the axial T2-Weighted (T2-w) anatomical image and the DW image. Second, we detect LNs using region-growing method in order to compute the final classification. Third, segmentation results are then used to classify LNs based on a gray level dependency matrix technique which extracts LN features. We evaluated our method using 10 MR images T2-w and DW with 47 metastatic LNs. We obtained an average accuracy of 70.21% for cervical cancer nodule classification.

This work presents a promising way to investigate the valorization of natural residual from Tunisian industrial wastes. In fact, large quantities of phosphogypsum which are obtained from Tunisian Chemical Group "TCG" are accumulated every year in Tunisia. The rational valorization of these available renewable resources fits very well with the recent sustainable approach, established nowadays. This work aims at ascertaining the chemical composition of this inorganic residue and structural characterization for use as a reinforced plaster. Several thermal treatments from 100°C to 800°C were established to prepare from phosphogypsum various qualities of this material to be characterized by numerous techniques such as the FTIR, XRD, SEM, DSC, DTG and TGA in order to apply in potential application. Calcination temperature that gave the best value for the beginning and the end of setting was 200°C. The experimental tests showed height values of flexural strength for thecalcined PG at 200°C (0.45 MPa). Original Research Article Mechi et al.; BJAST, 16(3): 1-10, 2016; Article no.BJAST.25728 2

During the production of hydrocarbons from subterranean reservoirs, scaling with calcium carbonate and barium sulfate causes flux decline and dangerous problems in production facilities. This work is intended to study the effect of calcium ions on the precipitation of barium sulfate (barite); then, the effect of the formed barite on calcium carbonate crystallization. The conductometric and pH methods were used to follow the progress of the precipitation reaction in aqueous medium. The obtained precipitates were characterized by FTIR, RAMAN, SEM, and XRD. It was shown that Ca2+ in the reaction media does not affect the microstructure of barite even for higher calcium–barium molar ratio. It influences the precipitation kinetics and the solubility of barite by the formation of CaSO4° ion pairing as a predominant role of complex formation (CaSO4) and the increase of the ionic strength. In Ca(HCO3)2-BaSO4-NaCl aqueous system, experiments have showed that added or formed barite in the reaction media accelerates calcite precipitation. No effect on the microstructure of heterogeneous formed calcite which remain calcite shape. However the presence of carbonate ions affects slightly the microstructure of barite.