Application of Prunus amygdalus By-products in Eco-friendly Dyeing of Textile Fabrics

Natural dyes have become an interesting subject of study because of their better ecological properties in comparison to their synthetic counterparts.This article concerns the dyeing of wool,silk,and polyamide fabrics with natural dyes extracted from almond shells and stems.The developed method of dyeing by these extracts is interesting and very attractive for several reasons:firstly,the extracts used are the black liquor discharged from the industries of delignification,which is a chemical process for removing lignin from agricultural wastes to produce a cellulosic fiber;(ii)these natural dyes are renewable and available in large quantities;(iii)this method is economical;and(iv)lastly,the dyeing performances of the obtained dyed textiles are very promising.The color of each dyed material was investigated in terms of the CIELAB coordinates and their fastness properties measured by washing,rubbing,and light.

A Challenging Approach to Improve the Low Affinity of Acrylic Fibres to Be Successfully Dyed with a Bio-Colorant Extracted from Grape Marc

Acrylic fibres are highly crystalline and non-polar polymers,which makes their dyeing a very difficult step that poses real technical challenges.In order to overcome this concern,it is intended in this paper to modify acrylic fibers by different methods namely cationisation using the Crosscolor DRT then amidoximation using hydroxylamine hydrochloride and ammonium acetate.The resulted samples were dyed then with the bio-colorant extracted from grape marc.The effect of the pretreatment on fibers fine structure using X-ray diffraction and the scanning electron microscope(SEM)images and its correlation with the colour strength of the dyed fabrics was investigated.The dyeing parameters,such as dye bath pH and temperature on the performances of this dyeing process were studied.Good dyeing qualities and new shades varying from brown to grey and dark green have been obtained following process optimization,mordanting and modification of acrylic fibers by the technique of cationisation.

Structural Characterization and Antioxidant Activity of Lignin Extracted from Ficus Carica L.

The most abundant phenolic biopolymer in the biosphere is the lignin.This phenolic biopolymer commonly exists in combination with polysaccharides and other cell wall components.In this study,the solvent system dioxane-water is used to extract lignin,which is considered as unaltered native lignin.The dioxane lignin extracted from fig stems was characterized regarding to its structural feature,quantification of its functional groups,molecular weight,and evaluation of its thermal properties.Purity and molecular weight distribution of the studied lignin indicated that isolated lignin contained a low amount of sugar(c.a.19%)and had a high weight-average molecular weight(10068 g.mol-1).Lignin sample had approximately the same amounts of guaiacyl(G)and p-hydroxyphenyl(H)units with relatively fewer syringyl(S)units.The isolated lignin revealed good antioxidant properties.Therefore,it proved to have a high potential of application in new antioxidants formulations.

Removal of Cu(II),Pb(II),Mg(II),and Fe(II) by Adsorption onto Alginate/Nanocellulose Beads as Bio-Sorbent

Alginate blended with cellulose nanocrystals(CNC),cellulose nanofibers(CNF),and tri-carboxylate cellulose nanofibers(TPC-CNF)prepared and encapsulated in the form of microcapsules(bio-polymeric beads).The cellulosic nanomaterials that used in this study were investigated as nanomaterials for wastewater treatment applications.Batch experiments were performed to study the removal of copper,lead,magnesium,and iron from aqueous solutions by the prepared beads.The effects of the sorbent dosage and the modified polymers on the removing efficiency of the metal cations were examined.Atomic absorption was used to measure the metal ions concentrations.The modified bio-polymeric beads(Alg-CNF,Alg-CNC,and Alg-TPC-CNF)exhibited high-efficiency towards removing of the metal cations;Cu^(2+),Pb^(2+),Mg^(2+),and Fe^(2+).The Alg-TPC-CNF composite was exhibited excellent removing efficiency which around 95%for Pb,92%for Cu,43%for Fe and 54%for Mg.These outcomes affirm that the utilization of nanomaterials giving higher adsorption capacities contrasted with similar material in its micro or macrostructure form.

Performance Estimation of HEVC/h.265 Decoder in a Co-Design Flow with SADF-FSM Graphs

Multiprocessor System on Chip (MPSoC) technology presents an interesting solution to reduce the computational time of complex applications such as multimedia applications. Implementing the new High Efficiency Video Coding (HEVC/h.265) codec on the MPSoC architecture becomes an interesting research point that can reduce its algorithmic complexity and resolve the real time constraints. The implementation consists of a set of steps that compose the Co-design flow of an embedded system design process. One of the first anf key steps of a Co-design flow is the modeling phase which allows designers to make best architectural choices in order to meet user requirements and platform constraints. Multimedia applications such as HEVC decoder are complex applications that demand increasing degrees of agility and flexibility. These applications are usually modeling by dataflow techniques. Several extensions with several schedules techniques of dataflow model of computation have been proposed to support dynamic behavior changes while preserving static analyzability. In this paper, the HEVC/h.265 video decoder is modeled with SADF based FSM in order to solve problems of placing and scheduling this application on an embedded architecture. In the modeling step, a high-level performance analysis is performed to find an optimal balance between the decoding efficiency and the implementation cost, thereby reducing the complexity of the system. The case study in this case works with the HEVC/h.265 decoder that runs on the Xilinx Zedboard platform, which offers a real environment of experimentation.

Numerical-Experimental Updating Identification of Elastic Behavior of a Composite Plate Using New Multi-Objective Optimization Procedure

This work focuses on the updating-based identification of the three-dimensional orthotropic elastic behavior of a thin carbon fiber reinforced plastic multilayer composite plate. This consists in identifying the engineering constants that minimize the relative deviations between the first eight experimental and three-dimensional finite element frequencies of the vibrating free plate. For this purpose, a multi-objective optimization procedure is applied;it exploits a Particle Swarm Optimizer algorithm (PSO) that is coupled to a metamodeling by the new response surfaces method procedure (NRSMP);the latter is based on numerical design experiments. The conducted sensitivity analyses indicate that the four engineering constants of the two-dimensional elasticity are the most influent.

Evaluation and Simulation of the Effect of the Types of Glazing and the Choice of Materials on the Energy Efficiency of a Building

Tunisia is one of the pioneering developing countries in terms of energy efficiency policy initiated since the mid-1980s.Indeed,energy efficiency has become one of the main pillars of the country’s energy strategy,especially with the increase in energy prices.The main objective of this work is to give an idea of the impact that certain choices made during the design of a building can have on its energy balance,namely the orientation of the facades,the types of glazing and their surfaces,the choice of materials,etc.The calculation of the building’s energy requirement was determined using the transient systems simulation program TRNSYS(version 18)with a modular structure.

New Biobased Polyurethane Materials from Modified Vegetable Oil

Bio-based polyurethanes(PUs)have been occurred a large attention nowadays.It was found to be an alternative to the petrochemical based materials to the fact of their weak environmental influence,availability,good price and biodegradability.In addition,the nature shows several bio-derived compounds as raw materials for the synthesis of polyols,including the vegetable oils,polyphenol,terpene,and other bio-renewable sources.With the aim to develop a new family of biobased polyurethanes(PUs)via vegetable oils,the elaboration of new Jojoba-based PUs was performed by catalyst-free polycondensation reaction of a synthesized Jojoba diol with various diisocyanates such us toluene diisocyanate(TDI)and isophorone diisocyanate(IPDI).All the compounds were characterized by FTIR and NMR spectroscopies,and their properties were determined by gel permeation chromatography,differential scanning calorimetry and thermogravimetric analysis.The obtained results show renewable vegetable oils-based PUs materials can be preparing using a new environmentally ways and giving various good properties performances.

Cellulose Nanocrystal from Washingtonia Fibre and Its Characterization

Cellulose nanocrystal(CNC)is a biomaterial derived from plant lignocellulosic components,widely applied in various industrial fields.Concurrently,with the growth of awareness in developing green nanomaterial,the explored Washingtonia fibre could be alternative biomass for obtaining CNC products.In the present work,different acid concentrations of 5%,15%,and 25%hydrochloric solutions were employed to produce CNCs from Washingtonia fibre.With the chemical treatments,the yield of the CNC product was successfully retained at 21.6%-25.1%.Individually separated and needle-shaped CNC particles could be observed under the microscopic viewing with the increased acid concentrations.From elemental analysis,a relatively pure cellulose compartment was produced for all CNC samples.The zeta potential values between-10 to-16 mV proved that each nanoparticle sample possessed dispersion ability within an aqueous solution.Meanwhile,the degree of crystallinity and the thermal behavior of CNCs were enhanced with the increased acidic concentrations.Hence,the isolated CNCs(with 15%)from Washingtonia fibre lead a CNC with the highest aspect ratio(30).This parameter is so important that these structures show empowering points of view as nanomaterials for reinforced polymer composites,and it could be a reliable nano-filler for the composite fabrication process in the future.

Towards Securing Machine Learning Models Against Membership Inference Attacks

From fraud detection to speech recognition,including price prediction,Machine Learning(ML)applications are manifold and can significantly improve different areas.Nevertheless,machine learning models are vulnerable and are exposed to different security and privacy attacks.Hence,these issues should be addressed while using ML models to preserve the security and privacy of the data used.There is a need to secure ML models,especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage.In this paper,we present an overview of ML threats and vulnerabilities,and we highlight current progress in the research works proposing defence techniques againstML security and privacy attacks.The relevant background for the different attacks occurring in both the training and testing/inferring phases is introduced before presenting a detailed overview of Membership Inference Attacks(MIA)and the related countermeasures.In this paper,we introduce a countermeasure against membership inference attacks(MIA)on Conventional Neural Networks(CNN)based on dropout and L2 regularization.Through experimental analysis,we demonstrate that this defence technique can mitigate the risks of MIA attacks while ensuring an acceptable accuracy of the model.Indeed,using CNN model training on two datasets CIFAR-10 and CIFAR-100,we empirically verify the ability of our defence strategy to decrease the impact of MIA on our model and we compare results of five different classifiers.Moreover,we present a solution to achieve a trade-off between the performance of themodel and the mitigation of MIA attack.

Cellulose Fibre from Schinus molle and Its Characterization

The exploitation of biomass represents a major environmental challenge related to the protection of the environment and the progressive exhaust of fossil resources.In this perspective,the main objective of this work is the extraction and the characterization of natural lignocellulosic fibers from the Schinus molle.The cellulose fibre extraction was investigated employing conditions of alkali treatment.After the alkaline steps,a bleaching treatment was done and let to a yield about 45%pure cellulose.The identification of the chemical composition of Schinus molle reveals that this raw material contains a high level of biopolymers with a cellulose rate of 53.2%.Extracted cellulose fibers have been characterized by several techniques such as scanning electron microscopy,Fourier transform infrared,X-ray diffraction,Morfi,and by the determination of their degree of polymerization.FT-IR results confirm the purity of the cellulosic fibers,and XRD analysis reveals that the crystallinity increases after the delignification and bleaching treatments.

MED-BS Clustering Algorithm for the Small-Scale Wireless Sensor Networks

With the spectacular progress of technology, we have witnessed the appearance of wireless sensor networks (WSNs) in several fields. In a hospital for example, each patient will be provided with one or more wireless sensors that gather his physiological data and send them towards a base station to treat them on behalf of the clinicians. The WSNs can be integrated on a building surface to supervise the state of the structure at the time of a destroying event such as an earthquake or an explosion. In this paper, we presented a Mobility-Energy-Degree-Distance to the Base Station (MED-BS) Clustering Algorithm for the small-scale wireless Sensor Networks. A node with lower mobility, higher residual energy, higher degree and closer to the base station is more likely elected as a clusterhead. The members of each cluster communicate directly with their ClusterHeads (CHs) and each ClusterHead aggregates the received messages and transmits them directly to the base station. The principal goal of our algorithm is to reduce the energy consumption and to balance the energy load among all nodes. In order to ensure the reliability of MED-BS, we compared it with the LEACH (Low Energy Adaptive Clustering Hierarchy) clustering algorithm. Simulation results prove that MED-BS improves the energy consumption efficiency and constructs a stable structure which can support new sensors without returning to the clusters reconstruction phase.

Experimental and Numerical Analyses of the Pull-out Response of a Steel Post/Bovine Bone Cementless Fixation

Effect of initial interference fit on pull-out strength in cementless fixation between bovine tibia and smooth stainless steel post was investigated in this study. Compressive behavior of bovine spongious bone was studied using mechanical testing in order to evaluate the elastic-plastic properties in different regions of the proximal tibia. Friction tests were carried out in the aim to evaluate the friction behavior of the contact between bovine spongious bone and stainless steel. A cylindrical stainless steel post inserted in a pre-drilled bovine tibia with an initial interference fit was taken as an in vitro model to assess the contribution of post fixation to the initial stability of the Total Knee Arthroplasty （TKA） tibial component. Pull-out experiments were carried out for different initial interference fits. Finite Element Models （FEM） using local elastic-plastic properties of the bovine bone were developed for the analysis of the experimental ultimate pull-out force results. At the post/bone interface, Coulomb friction was considered in the FEM calculations with pressure-dependent friction coefficient. It was found that the FEM results of the ultimate force are in good agreement with the experimental results. The analysis of the FEM interfacial stresses indicates that the micro-slip initiation depends on the local bone properties.

Adaptive Fault Tolerant Control of Multi-time-scale Singularly Perturbed Systems

This paper studies the fault tolerant control, adaptive approach, for linear time-invariant two-time-scale and three-time-scale singularly perturbed systems in presence of actuator faults and external disturbances. First, the full order system will be controlled using v-dependent control law. The corresponding Lyapunov equation is ill-conditioned due to the presence of slow and fast phenomena. Secondly, a time-scale decomposition of the Lyapunov equation is carried out using singular perturbation method to avoid the numerical stiffness. A composite control law based on local controllers of the slow and fast subsystems is also used to make the control law ε-independent. The designed fault tolerant control guarantees the robust stability of the global closed-loop singularly perturbed system despite loss of effectiveness of actuators. The stability is proved based on the Lyapunov stability theory in the case where the singular perturbation parameter is sufficiently small. A numerical example is provided to illustrate the proposed method.