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The Hassi Abyad kaolin deposit is in the southern part of Mauritania, around 45 km east of the town of M'Bout. Hassi Abyad lies in the middle of the Mauritanides Shield, which consists of deformed and metamorphosed Precambrian and Paleozoic formations. Complementary geological, mineralogical, and geochemical studies have been carried out to help answer questions linked to the origin of these kaolin and to determine the potential suitability for different industrial applications. The mineralogical compositions showed that Hassi Abyad kaolin is mainly composed of kaolinite (61–96%) and other minerals such as chlorite, illite, muscovite, cronstedtite, quartz, rutile, magnetite, laumontite, and gibbsite. The average chemical composition of the kaolin samples is 35.84% Al₂O₃, 45.27% SiO₂, and 14.19% LOI. Other oxides occur in low concentrations (less than1%). The higher chemical indices of alteration CIA (99.5%) and CIW (99.6%) indicate that this kaolin deposit underwent a high degree of alteration during the process of kaolinization of the source rock. The absence of high temperature minerals such as pyrite, topaz and dickite, and the presence of high Ce + Y + La and Cr + Nb contents signifies that the development and evolution of this deposit are affiliated with supergene processes. This kaolin is derived from a lateritic material, proving that they are the source rock of this deposit. The geochemical and mineralogical characteristics indicate that Hassi Abyad kaolin is applicable in ceramics, paper, cosmetics, pharmaceutics, bricks making, and pottery. • Hassi Abyad kaolin is composed of kaolinite, quartz, chlorite, illite and gibbsite. • Lacking high temperature minerals, high Ce, Y, La, Cr, Nb indicate supergene origin. • High CIA and CIW indicate that the deposit formed underwent high alteration degree. • The deposit is applicable for ceramics, paper, pharmaceutics, bricks, and pottery. [ABSTRACT FROM AUTHOR]

Thanks to their superior performance including greater cohesion, good mechanical and delamination behaviors, and excellent formability properties, 3D warp interlock woven fabrics (3DWIFs) have emerged as promising fibrous reinforcement structure for composite material. The current paper explores the innovations, advanced developments, and varied applications of 3DWIFs and its composites. Initially, the paper discusses the fabric's versatile potential, revealing its exceptional structural integrity, formability, manufacturing techniques, broad spectrum of applications and other parameters compared to conventional two-dimensional woven fabric reinforcements. Furthermore, the potential benefits and challenges of the 3DWIFs and its composite materials are explained to highlight their prospects in current and future industrial applications. Subsequently, the paper further explores the reinforcement's distinctive structural characteristics emphasizing its classifications and designing techniques. The discussion extends to the extensive and versatile applications of 3DWIFs and its composites across diverse sectors, including defence and security, the automotive and aerospace industry, and the civil and architectural sectors. By synthesizing and critically analyzing the existing research, this paper will serve as a valuable resource, enlightening the 3DWIF's present status and projecting its promising prospects both as dry fabric and composite reinforcing material for diverse industrial applications. [ABSTRACT FROM AUTHOR]

The natural interactions between various bacteria, fungi, and other cellulolytic microorganisms destroy lignocellulosic polymers. The efficacy of this process is determined by the combined action of three main enzymes: endoglucanases, exo -glucanases, and β-glucosidase. The enzyme attacks the polymeric structure's β-1,4-linkages during the cellulose breakdown reaction. This mechanism is crucial for the environment as it recycles cellulose in the biosphere. However, there are problems with enzymatic cellulose breakdown, including complex cellulase structure, insufficient degradation efficacy, high production costs, and post-translational alterations, many of which are closely related to certain unidentified cellulase properties. These issues impede the practical use of cellulases. A developing area of research is the application of this similar paradigm for industrial objectives. Cellulase enzyme exhibits greater promise in many critical industries, including biofuel manufacture, textile smoothing and finishing, paper and pulp manufacturing, and farming. However, the study on cellulolytic enzymes must move forward in various directions, including increasing the activity of cellulase as well as designing peptides to give biocatalysts their desired attributes. This manuscript includes an overview of current research on different sources of cellulases, their production, and biochemical characterization. [ABSTRACT FROM AUTHOR]

The eight papers included in this special issue represent a selection of extended contributions presented at the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2022 held in Salamanca, Spain, September 6th-8th, 2022, and organized by the BISITE group at University of Salamanca. SOCO 2022 international conference represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines which investigate, simulate, and analyse very complex issues and phenomena. This special issue is aimed at practitioners, researchers, and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solve real-world problems in the mentioned fields. [ABSTRACT FROM AUTHOR]

[Display omitted] • Progress in membranes for CO 2 capture and separation has been thoroughly reviewed. • Membrane materials for CO 2 separation has been summarized. • Industrial application of CO 2 separation membranes has been discussed. • Future development of CO 2 separation membranes materials and membrane processes have been proposed. Industry interest in CO 2 capture and separation has grown almost exponentially over the past decades. This paper aims to promote membrane technology as a viable solution for this application and provide a reference for the industry seeking efficient CO 2 separation solutions. First, a brief summary of the basics of mass transport mechanisms, various membrane materials, and module configurations is presented as the basis for the discussion. Special focus has been paid on different membrane materials developed in the past few years. Then, the latest advances in CO 2 separation membranes and processes in the context of industrial applications are outlined, including pilot tests carried out all over the world, as well as commercially available CO 2 separation membrane materials and modules. Afterwards, the application of big data and machine learning on CO 2 separation membranes have also been reviewed. Finally, challenges and gaps that hinder the implementation of membrane technology and future directions for membrane development from laboratory to industry are discussed. [ABSTRACT FROM AUTHOR]

This research article demonstrates how to get a precise lithium-ion battery (LIB) model using one of the artificial intelligence algorithms called the Walrus optimization algorithm (WaOA). The model's accuracy affects several transient and dynamic analysis simulations, which are carried out for power systems, electric vehicles, and many transportation applications. The LIB model may have one, two, or three resistance-capacitance (RC) models, signifying the complexity of the optimization challenge. Therefore, the WaOA is used to minimize the cost function that relies on an integral square error criterion. This criterion calculates the error between the estimated and experimental voltages. The proposed method is validated under several conditions, taking into account load variation, battery degradation, temperature fluctuation, and different RC models. The numerical results of the WaOA method are compared with their experimental results for a 2.6 Ah LIB. In addition, the proposed WaOA model has undergone validation alongside numerous optimization algorithms-based models. It is worth noting that utilization WaOA with battery modeling stands as a reliable tool for attaining precise model. • This paper presents a novel optimal lithium-ion battery model in the industry. • The model can be used with electric vehicles and power grid applications. • Practical measurements are implemented to verify the battery model. • The WaOA methodology is proposed to solve the optimization problem. • The effectiveness of the proposed method is compared with other methods. [ABSTRACT FROM AUTHOR]

• The targeted improvement of EHLC's four core equipment are summarized. • The process characteristics and control methods of EHLC are summarized. • The forming characteristics and performance advantages of material systems commonly used in EHLC are summarized. • The application status of EHLC in surface manufacturing and additive manufacturing are summarized. • The current situation, shortcomings, and future development trends of EHLC are fully summarized and prospected. As a new surface engineering technology, extreme high-speed laser cladding technology (EHLC), which originated from conventional laser cladding technology, has presented extraordinary characteristics, such as high cladding efficiency, excellent powder utilization rate, superior surface accuracy of the cladding layer, and a small heat-affected zone on the substrate. Compared with other surface technologies, it exhibits dominant advantages and extensive application prospects in the fields of surface manufacturing and additive manufacturing. In this paper, we first introduce the structure of the core equipment of the EHLC, including the laser device, the laser cladding head, the powder feeder, and the processing platform. Next, the research status of EHLC process control is summarized from three aspects: optimization of the coating forming process parameters, numerical simulation of the forming process, and external field-assisted technology. Third, we comprehensively review the coating systems of common metal alloys and metal matrix composites prepared by EHLC and their excellent properties. Additionally, the application status of EHLC in surface manufacturing and additive manufacturing is summarized in this paper. Finally, the research progress of EHLC in equipment, process, material, and application is also concluded, and its further development trend is proposed. [ABSTRACT FROM AUTHOR]

The seven papers included in this special issue represent a selection of extended contributions presented at the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2021, held in Bilbao, Spain, September 22nd-24th, 2021, and organized by the BISITE group and the University of Deusto. The SOCO 2021 international conference represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines that investigate, simulate, and analyse very complex issues and phenomena. This special issue is aimed at practitioners, researchers, and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solve real-world problems in the mentioned fields. [ABSTRACT FROM AUTHOR]

• A novel time-dependent micromechanics model is proposed for dissolvable composites. • The performance of composite is linked to dissolution and diffusion rates. • A comprehensive parametric study revealing the impact of key factors is presented. • The model is successfully applied to literature data on single polymer composites. This paper proposes a novel micromechanics model tailored for dissolvable composites, where the inclusion undergoes dissolution and diffusion within the matrix, with the aim of analytically predicting the time-dependent properties of composites. The dissolution of inclusion leads to a reduction of its volume fraction and the formation of a growing interphase layer around the inclusion. This versatile model is applicable to both short-term dissolutions, as observed in the fabrication process of composites and long-term degradation occurring in high-temperature or corrosive environments, common in industrial and biological applications. Dimensionless expressions for time-dependent volume fractions of composite components are related to the dissolution and the diffusion rates, and a micromechanics three-phase model is established to evaluate the properties of the composite as a function of dissolution time. A detailed parametric study is performed to demonstrate the effect of all the parameters on the final properties. The model is successfully applied to the experimental data in the literature to show its capability and flexibility in predicting the practical dissolution examinations. The introduced model provides a pioneering framework for the future evolution of the dissolvable micromechanics concept. [Display omitted] [ABSTRACT FROM AUTHOR]

The lack of explicit and precise specifications of software interfaces between components often leads to integration issues during development and maintenance. To address this, we have developed a framework named ComMA (Component Modeling and Analysis) that supports model-based engineering of high-tech systems by precisely defining components and their interfaces. The framework is a family of Domain Specific Languages (DSLs) for modeling component interfaces, protocol state machines, time and data constraints, and constraints on relations between events of multiple interfaces. From these models a number of artifacts can be generated automatically to support analysis and various engineering tasks. ComMA has been developed in close collaboration with the Philips IGT business unit that develops minimally-invasive X-ray systems. This paper presents the experience we gained in creating the ComMA framework and its application in industrial practice. We describe and reflect on the technical, organizational and process-related aspects of deploying a non-trivial MDE solution in an industrial setting. [ABSTRACT FROM AUTHOR]

The industrial process is characterized by its multi-modal nature and complex spatial and temporal correlations. Despite the fact that several multi-modal methods have been proposed, few of them can effectively extract deep multi-modal representations and the highly intricate spatial and temporal relationships. In this paper, a novel multi-modal hybrid modeling strategy (GMVAE-STA) is proposed for industrial process prediction. This strategy combines the Gaussian Mixture Variational Autoencoder (GMVAE) and the spatial–temporal attention based Gated Recurrent Unit (STA-GRU). First, the GMVAE maps the raw data to the latent space, which follows a Gaussian Mixture distribution, and the data with the highest probability in each Gaussian are identified as a mode. Then, the STA-GRU captures the complex spatial and temporal relationships within each mode and makes predictions. Experimental results on the Tennessee Eastman process and a real-world fluid catalytic cracking process demonstrate the effectiveness of mode classification and prediction of the proposed method. • A novel multi-modal hybrid modeling strategy is proposed for industrial process. • The multi-modal information in the data is effectively extracted by the GMVAE. • A spatial and temporal based GRU is developed to capture the complex relationship. • Real-world fluid catalytic cracking data is used to validate the proposed method. [ABSTRACT FROM AUTHOR]

For strip surface defect detection, the key is to achieve reliable detection results with high detection speed. This paper mainly focuses on the ability to distinguish defects with similar optical characteristics, and the balance between detection accuracy and speed. Firstly, the dataset with 2020 pictures containing 6 types of defects was established by the figures inspected in a rolled titanium strip production line. Then, a novel detection model named Yolo-SAGC was proposed by applying two strategies to the fast response Yolo-v5 model. One is to improve the feature recognition capability by combining self-attention and graphic convolution in the head module. The other is to make a thorough slim of the whole network architecture by using slim modules combined with depth-wise separable convolution (i.e., DWconv). Finally, the advancement of this novel detection model was verified by the self-established database. The results demonstrate a significant reduction in cases where detection is missed for the 6 types of defects, dropping from 32.75% to 6.67% when the two strategies are implemented. Notably, the most difficult-to-detect label "Pit" defect shows an 11.9% improvement in average precision with the introduction of self-attentional graphic convolution. Similarly, the densely distributed small target "Little_lightspot" exhibits a 5.0% increase in average precision when DWconv is applied. Furthermore, the mAP @0.5 of Yolo-SAGC is comparable to that of Yolo-v8, while the model parameters are decreased by 48.7% and FPS is increased by 3. These phenomena show the great potential of Yolo-SAGC in industrial applications. [ABSTRACT FROM AUTHOR]

Functionally graded WC-Co (FG WC-Co) offers enhanced property combinations and superior engineering performance compared to conventional homogeneous WC-Co. However, production methods face challenges in creating the graded microstructure, cost-effectiveness, and scalability. A versatile carburizing technique has been developed to address these challenges and to apply FG WC-Co to various WC-Co grades and applications. This paper reviews the carburizing technique's underlying principles and mechanisms of a one-step to a two-step process for treating off-the-shelf homogeneous products. Key two-step process parameters such as temperature, time, and carbon potential, which influence the control of the Co gradient, free carbon depth, and Co build-up, are highlighted. Both laboratory findings and field test data suggest that by optimizing these parameters, the carburizing technique can produce desired results, thus broadening the potential industrial applications of both the process itself and the FG WC-Co. • A viable carburizing heat treatment process for manufacturing functionally graded WC-Co (FG WC-Co) is described. • Co gradient structure can be effectively tailored by optimizing the carburizing process parameters. • The potential industrial applications of FG WC-Co materials were demonstrated. [ABSTRACT FROM AUTHOR]

Pepsin is one of the major enzymes with significant importance in the food industry, biomedicines, and pharmaceutical formulations. In this work, the main objective was to biochemically characterize a pepsin-like enzymatic extract obtained from Pygocentrus nattereri , a predatory freshwater fish, focusing on their potential industrial application. The obtained extract exhibited optimal activity at 45 °C and pH 1.0–2.0. These proteases remained stable after 2 h of incubation at temperatures ranging from 0° to 45 °C and within pH range of 1.0 to 7.0. Their activity was significantly affected in presence of pepstatin A and SDS, 10 μM and 3.46 mM respectively, while EDTA and PMSF showed partial inhibitory effects. Divalent cations (Ca2+ and Mg2+) did not inhibit the proteolytic activity of the extract; in fact, it improved at a 5 mM CaCl2 concentration. As the NaCl concentration increased, the enzyme activity decreased. However, after desalination, 90 % of the activity was recovered within the tested exposure time. Besides, this extract demonstrated exceptional versatility across diverse industrial applications, including collagen extraction augmentation, IgG hydrolysis facilitation, and silver and polyester recovery from X-ray films. Our results suggest that the obtained enzymatic extract has a wide range of potential applications. • Pygocentrus nattereri offers fishing by-products containing high value proteins • Simple extractive method like as acid precipitation yields an acidic protease-rich extract. • The proteolytic activity exhibit by the acid extract demonstrated a remarkable pH stability range (1.0-7.0). • The extract demonstrates versatility in industrial applications, including collagen extraction, IgG hydrolysis, and recovery of silver and polyester from X-ray films. [ABSTRACT FROM AUTHOR]