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The diseases caused by excessive sodium intake derived from NaCl consumption have attracted widespread attention worldwide, and many researchers are committed to finding suitable ways to reduce sodium intake during the dietary process. Salt substitute is considered an effective way to reduce sodium intake by replacing all/part of NaCl in food without reducing the saltiness while minimizing the impact on the taste and acceptability of the food. Plant-derived natural ingredients are generally considered safe and reliable, and extensive research has shown that certain plant extracts or specific components are effective salt substitutes, which can also give food additional health benefits. However, these plant-derived salt substitutes (PSS) have not been systematically recognized by the public and have not been well adopted in the food industry. Therefore, a comprehensive review of PSS, including its material basis, flavor characteristics, and taste mechanism is helpful for a deeper understanding of PSS, accelerating its research and development, and promoting its application.

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Amides are an important type of synthetic intermediate used in the chemical, agrochemical, pharmaceutical, and nutraceutical industries. The traditional chemical process of converting nitriles into the corresponding amides is feasible but is restricted because of the harsh conditions required. In recent decades, nitrile hydratase (NHase, EC 4.2.1.84) has attracted considerable attention because of its application in nitrile transformation as a prominent biocatalyst. In this review, we provide a comprehensive survey of recent advances in NHase research in terms of natural distribution, enzyme screening, and molecular modification on the basis of its characteristics and catalytic mechanism. Additionally, industrial applications and recent significant biotechnology advances in NHase bioengineering and immobilization techniques are systematically summarized. Moreover, the current challenges and future perspectives for its further development in industrial applications for green chemistry were also discussed. This study contributes to the current state-of-the-art, providing important technical information for new NHase applications in manufacturing industries.

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Clostridium bacteria were already known to Hippocrates many years before Christ. The name of the Clostridium species is owed to the Polish microbiologist, Adam Prazmowski. It is now known that these Clostridium bacteria are widespread in the natural environment, and their presence in food products is a threat to human health and life. According to European Food Safety Authority (EFSA) reports, every year, there are poisonings or deaths due to ingestion of bacterial toxins, including those of the Clostridium spp. The strengthening of consumer health awareness has increased interest in consuming products with minimal processing in recent years, which has led to a need to develop new techniques to ensure the safety of microbiological food, including elimination of bacteria from the Clostridium genera. On the other hand, the high biochemical activity of Clostridium bacteria allows them to be used in the chemical, pharmaceutical, and medical industries. Awareness of microbiological food safety is very important for our health. Unfortunately, in 2022, an increase in infections with Clostridium bacteria found in food was recorded. Knowledge about food contamination should thus be widely disseminated.

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Single metal atom catalysts (SACs) have garnered considerable attention as promising agents for catalyzing important industrial reactions, particularly the electrochemical synthesis of hydrogen peroxide (H2O2) through the two-electron oxygen reduction reaction (ORR). Within this field, the metal atom-support interaction (MASI) assumes a decisive role, profoundly influencing the catalytic activity and selectivity exhibited by SACs, and triggers a decade-long surge dedicated to unraveling the modulation of MASI as a means to enhance the catalytic performance of SACs. In this comprehensive review, we present a systematic summary and categorization of recent advancements pertaining to MASI modulation for achieving efficient electrochemical H2O2 synthesis. We start by introducing the fundamental concept of the MASI, followed by a detailed and comprehensive analysis of the correlation between the MASI and catalytic performance. We describe how this knowledge can be harnessed to design SACs with optimized MASI to increase the efficiency of H2O2 electrosynthesis. Finally, we distill the challenges that lay ahead in this field and provide a forward-looking perspective on the future research directions that can be pursued.

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Bacterial pigments stand out as exceptional natural bioactive compounds with versatile functionalities. The pigments represent molecules from distinct chemical categories including terpenes, terpenoids, carotenoids, pyridine, pyrrole, indole, and phenazines, which are synthesized by diverse groups of bacteria. Their spectrum of physiological activities encompasses bioactive potentials that often confer fitness advantages to facilitate the survival of bacteria amid challenging environmental conditions. A large proportion of such pigments are produced by bacterial pathogens mostly as secondary metabolites. Their multifaceted properties augment potential applications in biomedical, food, pharmaceutical, textile, paint industries, bioremediation, and in biosensor development. Apart from possessing a less detrimental impact on health with environmentally beneficial attributes, tractable and scalable production strategies render bacterial pigments a sustainable option for novel biotechnological exploration for untapped discoveries. The review offers a comprehensive account of physiological role of pigments from bacterial pathogens, production strategies, and potential applications in various biomedical and biotechnological fields. Alongside, the prospect of combining bacterial pigment research with cutting-edge approaches like nanotechnology has been discussed to highlight future endeavours.

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Silica sand is an essential industrial mineral composed predominantly of quartz, formed through the weathering of rocks. In Ethiopia, silica deposits are geologically widespread, including the Lemi area in the Blue Nile Basin. This study investigates the physicochemical and mineralogical properties of silica sand from the Lemi region to determine its suitability for industrial applications. Samples from four villages in Lemi were collected, prepared, and analyzed using various techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), grain size analysis, bulk density measurement, and geochemical analysis. The results indicate that Lemi silica sand is predominantly composed of medium-sized, well-sorted, sub-rounded to rounded quartz grains with high silica purity (average SiO2 content of 96.13 %). Mineralogical analysis confirms high crystallinity and a low presence of contaminants. The grain size distribution and bulk density of Lemi silica sand meet industry standards for glass, foundry, and abrasive applications. Comparative analysis shows that Lemi silica sand has comparable or superior qualities to other Ethiopian deposits, making it a promising resource for industrial use. The study estimates a total resource of approximately 6.94 billion tons of silica sand in the Lemi area, highlighting its significant economic potential.

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Xylanases have broad applications in the food industry to decompose the complex carbohydrate xylan. This is applicable to enhance juice clarity, improve dough softness, or reduce beer turbidity. It can also be used to produce prebiotics and increase the nutritional value in foodstuff. However, the low yield and poor stability of most natural xylanases hinders their further applications. Therefore, it is imperative to explore higher-quality xylanases to address the potential challenges that appear in the food industry and to comprehensively improve the production, modification, and utilization of xylanases. Xylanases, due to their various sources, exhibit diverse characteristics that affect production and activity. Most fungi are suitable for solid-state fermentation to produce xylanases, but in liquid fermentation, microbial metabolism is more vigorous, resulting in higher yield. Fungi produce higher xylanase activity, but bacterial xylanases perform better than fungal ones under certain extreme conditions (high temperature, extreme pH). Gene and protein engineering technology helps to improve the production efficiency of xylanases and enhances their thermal stability and catalytic properties.

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Biodegradation stands as an eco-friendly and effective approach for organic contaminant remediation. However, research on microorganisms degrading sodium benzoate contaminants in extreme environments remains limited. In this study, we report to display the isolation of a novel hot spring enriched cultures with sodium benzoate (400 mg/L) as the sole carbon source. The results revealed that the phylum Pseudomonadota was the potential sodium benzoate degrader and a novel genus within the family Geminicoccaceae of this phylum. The isolated strain was named Benzoatithermus flavus SYSU G07066T and was isolated from HNT-2 hot spring samples. Genomic analysis revealed that SYSU G07066T carried benABC genes and physiological experiments indicated the ability to utilize sodium benzoate as a sole carbon source for growth, which was further confirmed by transcriptomic data with expression of benABC. Phylogenetic analysis suggested that Horizontal Gene Transfer (HGT) plays a significant role in acquiring sodium benzoate degradation capability among prokaryotes, and SYSU G07066T might have acquired benABC genes through HGT from the family Acetobacteraceae. The discovery of the first microorganism with sodium benzoate degradation function from a hot spring enhances our understanding of the diverse functions within the family Geminicoccaceae. This study unearths the first novel genus capable of efficiently degrading sodium benzoate and its evolution history at high temperatures, holding promising industrial applications, and provides a new perspective for further exploring the application potential of hot spring "microbial dark matter".

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Lipases are remarkable biocatalysts, adept at catalyzing the breakdown of diverse compounds into glycerol, fatty acids, and mono- and di-glycerides via hydrolysis. Beyond this, they facilitate esterification, transesterification, alcoholysis, acidolysis, and more, making them versatile in industrial applications. In industrial processes, lipases that exhibit high stability are favored as they can withstand harsh conditions. However, most native lipases are unable to endure adverse conditions, making them unsuitable for industrial use. Protein engineering proves to be a potent technology in the development of lipases that can function effectively under challenging conditions and fulfill criteria for various industrial processes. This review concentrated on new trends in protein engineering to enhance the diversity of lipase genes and employed in silico methods for predicting and comprehensively analyzing target mutations in lipases. Additionally, key molecular factors associated with industrial characteristics of lipases, including thermostability, solvent tolerance, catalytic activity, and substrate preference have been elucidated. The present review delved into how industrial traits can be enhanced through directed evolution (epPCR, gene shuffling), rational design (FRESCO, ASR), combined engineering strategies (i.e. CAST, ISM, and FRISM) as protein engineering methodologies in contexts of biodiesel production, food processing, and applications of detergent, pharmaceutics, and plastic degradation.

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Hemicellulose is one of the most important natural polysaccharides in nature. Hemicellulose from different sources varies in chemical composition and structure, which in turn affects the modification effects and industrial applications. Grain and oil by-products (GOBPs) are important raw materials for hemicellulose. This article reviews the modification methods of hemicellulose in GOBPs. The effects of chemical and physical modification methods on the properties of GOBP hemicellulose biomaterials are evaluated. The potential applications of modified GOBP hemicellulose are discussed, including its use in film production, hydrogel formation, three-dimensional (3D) printing materials, and adsorbents for environmental remediation. The limitations and future recommendations are also proposed to provide theoretical foundations and technical support for the efficient utilization of these by-products.

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Metabolic engineering enables oilseed crops to be more competitive by having more attractive properties for oleochemical industrial applications. The aim of this study was to increase the erucic acid level and to produce wax ester (WE) in seed oil by genetic transformation to enhance the industrial applications of B. carinata. Six transgenic lines for high erucic acid and fifteen transgenic lines for wax esters were obtained. The integration of the target genes for high erucic acid (BnFAE1 and LdPLAAT) and for WEs (ScWS and ScFAR) in the genome of B. carinata cv. 'Derash' was confirmed by PCR analysis. The qRT-PCR results showed overexpression of BnFAE1 and LdPLAAT and downregulation of RNAi-BcFAD2 in the seeds of the transgenic lines. The fatty acid profile and WE content and profile in the seed oil of the transgenic lines and wild type grown in biotron were analyzed using gas chromatography and nanoelectrospray coupled with tandem mass spectrometry. A significant increase in erucic acid was observed in some transgenic lines ranging from 19% to 29% in relation to the wild type, with a level of erucic acid reaching up to 52.7%. Likewise, the transgenic lines harboring ScFAR and ScWS genes produced up to 25% WE content, and the most abundant WE species were 22:1/20:1 and 22:1/22:1. This study demonstrated that metabolic engineering is an effective biotechnological approach for developing B. carinata into an industrial crop.

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Sodium-ion batteries (SIBs) have significant potential for applications in portable electric vehicles and intermittent renewable energy storage due to their relatively low cost. Currently, hard carbon (HC) materials are considered commercially viable anode materials for SIBs due to their advantages, including larger capacity, low cost, low operating voltage, and inimitable microstructure. Among these materials, renewable biomass-derived hard carbon anodes are commonly used in SIBs. However, the reports about biomass hard carbon from basic research to industrial applications are very rare. In this paper, we focus on the research progress of biomass-derived hard carbon materials from the following perspectives: (1) sodium storage mechanisms in hard carbon; (2) optimization strategies for hard carbon materials encompassing design, synthesis, heteroatom doping, material compounding, electrolyte modulation, and presodiation; (3) classification of different biomass-derived hard carbon materials based on precursor source, a comparison of their properties, and a discussion on the effects of different biomass sources on hard carbon material properties; (4) challenges and strategies for practical of biomass-derived hard carbon anode in SIBs; and (5) an overview of the current industrialization of biomass-derived hard carbon anodes. Finally, we present the challenges, strategies, and prospects for the future development of biomass-derived hard carbon materials.

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Photoelectrochemical (PEC) water splitting is an effective and sustainable method for solar energy harvesting. However, the technology is still far away from practical application because of the high cost and low efficiency. Here, we report a low-cost, stable and high-performing industrial-Si-based photoanode (n-Indus-Si/Co-2mA-xs) that is fabricated by simple electrodeposition. Systematic characterizations such as scanning electron microscopy, X-ray photoelectron spectroscopy have been employed to characterize and understand the working mechanisms of this photoanode. The uniform and adherent dispersion of co-catalyst particles result in high built-in electric field, reduced charge transfer resistance, and abundant active sites. The core-shell structure of co-catalyst particles is formed after the activation process. The reconstructed morphology and modified chemical states of the surface co-catalyst particles improve the separation and transfer of charges, and the reaction kinetics for water oxidation greatly. Our work demonstrates that large-scale PEC water splitting can be achieved by engineering the industrial-Si-based photoelectrode, which shall guide the development of solar energy conversion in the industry.

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Black rice (Oryza sativa) stands out for its high content of bioactive compounds with functional properties that play an important role in health benefits. The phytochemical level is affected by industrial processing due to its instability to the hydrothermal process. Studies about the influence of industrial processing on the phytochemical profile of black-rice-based foods are still scarce. This study carried out a comprehensive review of the influence of industrial applications on the bioactive compounds in food products based on black rice and their health-promoting effects. Most industrial processes such as drying, storage, cooking, and extrusion affect phytochemical content and antioxidant capacity. Alternatively, technologies such as fermentation, UV-C irradiation, and sprouting can maintain or improve the phytochemical content in black rice products.

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Soft sensors are increasingly being used to provide important information about production processes that is otherwise only available through off-line laboratory analysis. However, usually, they are developed for a specific application, for which thorough process analysis is performed to provide information for the appropriate selection of model type and model structure. Wide industrial application of soft sensors, however, requires a method for soft sensor development that has a high level of automatism and is applicable to a significant number of industrial processes. A class of processes that is very common in the industry are processes with distinct operating conditions. In this paper, an algorithm that is suitable for the development of soft sensors for this class of processes is presented. The algorithm possesses a high level of automatism, as it requires minimal user engagement regarding the structure of the model, which makes it suitable for implementation as a customary industrial solution. The algorithm is based on a radial basis function artificial neural network, and it enables the automatic selection of the model structure and the determination of model parameters, only based on the training data set. The testing of the presented algorithm is done on the cement production process, since it represents a process with distinct operating conditions. The results of the test show that, besides providing a high level of automatism in model development, the presented algorithm generates a soft sensor with high estimation performance.

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With the industrialization and development of modern science, the application of enzymes as green and environmentally friendly biocatalysts in industry has been increased widely. Among them, lipase (EC. 3.1.1.3) is a very prominent biocatalyst, which has the ability to catalyze the hydrolysis and synthesis of ester compounds. Many lipases have been isolated from various sources, such as animals, plants and microorganisms, among which microbial lipase is the enzyme with the most diverse enzymatic properties and great industrial application potential. It therefore has promising applications in many industries, such as food and beverages, waste treatment, biofuels, leather, textiles, detergent formulations, ester synthesis, pharmaceuticals and medicine. Although many microbial lipases have been isolated and characterized, only some of them have been commercially exploited. In order to cope with the growing industrial demands and overcome these shortcomings to replace traditional chemical catalysts, the preparation of new lipases with thermal/acid-base stability, regioselectivity, organic solvent tolerance, high activity and yield, and reusability through excavation and modification has become a hot research topic.

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Due to its characteristic aroma and diverse therapeutic properties, lemongrass essential oil (LEO) has garnered increased attention in the pharmaceutical, food, and cosmetic industries. However, LEO's volatile nature, low chemical stability, and limited solubility in water limits its applications in the industry. Micro- and nanoencapsulation technologies emerge as a promising solution to overcome these challenges. A systematic methodology involving keyword searches in databases was employed to gather relevant literature on LEO micro- and nanoencapsulation, providing an extensive overview of techniques, processes, encapsulating materials, and possible applications. Beyond established methods, emerging techniques were explored. This review highlights the critical role of encapsulation in enhancing the thermal and chemical stability, applicability, bioavailability, and controlled release of LEO.

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Nigella sativa is one of the nutraceuticals that has gained popularity and studied extensively in recent decades as it is considered a safe medicinal plant for use as a dietary supplement. N. sativa contains a wide variety of bioactive substances, which include polyphenols, volatile oils (thymoquinone and p-cymene), proteins, and peptides. The biological attributes of N. sativa include antioxidant, antimicrobial, antifungal, anti-inflammatory, anticancer, antidiabetic, antihypertensive, hypolipidemic, and antioxidant activities, which have potential applications for the prevention of a variety of chronic diseases. In the food industry, N. sativa improves the sensory qualities, shelf life, strength, and freshness of foods, such as bread, pizza, biscuits, cookies, and cakes. This review discusses the industrial use of N. sativa, which includes processing technologies to enhance its health-promoting properties as well as the isolation of nutraceutical components.

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In the past few decades, organic solvent nanofiltration (OSN) has attracted numerous researchers and broadly applied in various fields. Unlike conventional nanofiltration, OSN always faced a broad spectrum of solvents including polar solvents and non-polar solvents. Among those recently developed OSN membranes in lab-scale or widely used commercial membranes, researchers preferred to explore intrinsic materials or introduce nanomaterials into membranes to fabricate OSN membranes. However, the hydrophilicity of the membrane surface towards filtration performance was often ignored, which was the key factor in conventional aqueous nanofiltration. The influence of surface hydrophilicity on OSN performance was not studied systematically and thoroughly. Generally speaking, the hydrophilic OSN membranes performed well in the polar solvents while the hydrophobic OSN membranes work well in the non-polar solvent. Many review papers reviewed the basics, problems of the membranes, up-to-date studies, and applications at various levels. In this review, we have focused on the relationship between the surface hydrophilicity of OSN membranes and OSN performances. The history, theory, and mechanism of the OSN process were first recapped, followed by summarizing representative OSN research classified by surface hydrophilicity and types of membrane, which recent OSN research with its contact angles and filtration performance were listed. Finally, from the industrialization perspective, the application progress of hydrophilic and hydrophobic OSN membranes was introduced. We started with history and theory, presented many research and application cases of hydrophilic and hydrophobic OSN membranes, and discussed anticipated progress in the OSN field. Also, we pointed out some future research directions on the hydrophilicity of OSN membranes to deeply develop the effect made by membrane hydrophilicity on OSN performance for future considerations and stepping forward of the OSN industry.

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Generating synthetic data is a promising solution to the challenge of limited training data for industrial deep learning applications. However, training on synthetic data and testing on real-world data creates a sim-to-real domain gap. Research has shown that the combination of synthetic and real images leads to better results than those that are generated using only one source of data. In this work, the generation of synthetic training images via physics-based rendering is combined with deep active learning for an industrial object detection task to iteratively improve model performance over time. Our experimental results show that synthetic images improve model performance, especially at the beginning of the model's life cycle with limited training data. Furthermore, our implemented hybrid query strategy selects diverse and informative new training images in each active learning cycle, which outperforms random sampling. In conclusion, this work presents a workflow to train and iteratively improve object detection models with a small number of real-world images, leading to data-efficient and cost-effective computer vision models.