Industrial Components Research Articles

Genome-Wide Identification and Biochemical Characterization of Alcohol Acyltransferases for Aroma Generation in Wickerhamomyces subpelliculosus Isolates from Fermented Food.

The importance of nonconventional yeasts has increasingly been highlighted, particularly for aroma formation in fermented foods. Here, we performed de novo whole-genome sequencing of Wickerhamomyces subpelliculosus, which produces a variety of volatile flavor compounds, leading to the identification of the alcohol acyltransferase (AATase) family of genes. The genome of W. subpelliculosus contains seven AATase genes, encoding alcohol-O-acetyltransferases (ATFs) and ethanol acetyltransferase 1 (EAT1) for acetate ester formation, along with ethanol hexanoyl transferase 1 (EHT1) for ethyl ester formation. Among five ATF homologues, only WsATF5 showed acetyltransferase activity toward myriocin, a structural analogue of sphingosine. In contrast, heterologous expression of WsEHT1 and WsEAT1 in Saccharomyces cerevisiae promoted the production of ethyl decanoate and ethyl acetate, respectively, supporting their AATase activity. The enzymatic activity analyses revealed the additional alcoholysis activity of WsEAT1 and the thioesterase activity of WsEHT1. Subcellular localization analysis indicated that WsEAT1 was localized in the mitochondria, WsEHT1 in the endoplasmic reticulum and lipid droplets (LDs), and WsATF5 in the LDs. The novel W. subpelliculosus AATases could be usefully applied to produce flavor components in various food industries.

Methane Adsorption Energy Variation Affected by Industrial Components in Deep and Thick Coal Reservoirs

The relevant literature indicates that coal facies have a significant impact on the pore structure and adsorption properties of deep coal reservoirs. The content of submicroscopic components is used to calculate the parameters of coal facies. Based on traditional coal phase parameters and ash content, the coal phases of the coal samples in the study area were divided. Based on the adsorption potential theory, the differences in methane adsorption energy changes between different coal phases were compared. The results are as follows. The wet herbaceous swamp facies (type A) could be divided into two subtypes by using the ash yield: subtype A-1 (with an ash yield lower than 20% and a gel index (GI) lower than 5), and subtype A-2 (with an ash yield larger than 20% and a GI lower than 5). With the increase in micro-pore volume shown in A-1 samples, cumulative surface free energy increases linearly and the maximum rate of decline decreases linearly. Coal facies have an important effect on adsorption parameters: VL increases and PL decreases with higher structural preservation index (TPI). The effect of a low ash yield and different Ro,max on methane adsorption energy parameters is stronger.

Revealing the γ′ and γ″ Phase Fractions of Additively Manufactured and Differently Heat‐Treated Nickel‐Base Superalloy IN718 by Atom Probe Tomography and Their Impact on Mechanical Properties

Powder bed fusion using a laser beam (PBF‐LB) has great potential for the production of geometrically complex industrial components, allowing for unprecedented geometrical optimization and freedom of design. This potential is particularly relevant in the case of turbine components, whose microstructure and properties are directly affected by the extreme PBF‐LB processing conditions. In this context, this study aims to investigate the impact of PBF‐LB on the microstructure and mechanical behavior of Inconel alloy 718 (IN718) when heat treated according to different sequences. Atom probe tomography is used to analyze the composition, morphology, configuration, and volume fraction of γ′ and γ″ precipitates as a function of heat treatment conditions. Their impact on the material is evaluated using compression tests under different build orientations. It is shown that when PBF‐LB IN718 is subject to solution annealing at 930 °C and subsequently aged, δ needles form in its microstructure at the expense of γ′ and γ″, thus reducing mechanical strength. Such is not the case when the solution annealing step is omitted or when its temperature is increased to 1000 °C, conditions whose superior mechanical behavior have been attributed to a high dislocation density and a large volume fraction of aging phases, respectively.

The Potential of Microalgae in Chitosan and Cellulose as Sustainable Materials for Edible Bioplastic Applications: A Review

The demand for eco-friendly food packaging options with additional features to prolong shelf life has continuously increased since 1940. Bioplastic is gaining popularity as a viable replacement for plastics based on fossil fuels due to fluctuating oil prices. Therefore, technological innovation is required to resolve the issue. This study aimed to review the distinct characteristics of integrating chitosan and cellulose alongside exploring the capabilities of microalgae in bioplastic production. The potential techniques and applications for future development were also suggested. The unique growth yield of microalgae makes them a compelling option for producing bioplastics. Hence, utilizing microalgae for bioplastic production offers a significant opportunity to enhance moisture barrier capacity, alter the structural properties, and adjust the flow behaviour. Moreover, these materials can also serve as the key nanocomposites components in the food packaging industry. The potential for chitosan/cellulose/microalgae-based bioplastic and the key themes and obstacles for future research into these composites for bioplastic production were also reviewed.

Research on the Entrance Damage of Carbon Fiber-Reinforced Polymer/Ti6Al4V Stacks in Six-Degrees-of-Freedom Robot Drilling

Carbon fiber-reinforced polymer (CFRP)/titanium alloy (Ti6Al4V) stacks are widely used in the aerospace industry due to their excellent physical properties. The substantial demand for drilling components in the aerospace industry necessitates the implementation of enhanced processing efficiency and drilling quality standards. Six-degrees-of-freedom robots are commonly used in the aerospace industry due to their high production efficiency, high flexibility, and low labor costs. However, due to the weak stiffness, chatter is prone to occur during processing, which has a detrimental impact on the quality of the finished product. As an advanced processing technology, ultrasonic-assisted machining technology can effectively reduce the cutting force and suppress the chatter in the drilling process, so it is widely used in production. In this paper, first, the robot kinematic (dexterity) and stiffness performance is analyzed. Then, the appropriate range of the machining plane and the posture of the robot in the workspace are selected. Finally, the vibration and CFRP entrance damage during the machining process are compared and studied in conventional robotic drilling (CRD) and ultrasonic-assisted robotic drilling (UARD). The experimental results demonstrate that the UARD is an effective method for reducing vibration during the machining process. Compared with the CRD, the CFRP entrance delamination damage in UARD is reduced. Under the appropriate processing parameters, the entrance delamination factor could be reduced by 15%, and the burr height could be reduced by 45%. Obviously, the UARD is a promising process to improve the CFRP entrance delamination damage.

Augmented Reality Enhanced Image Processing Systems for Interactive Worker Training in Industrial Automation

This paper explores the integration of augmented reality (AR) with image processing systems to enhance interactive worker training in industrial automation environments. The proposed system leverages AR technology to overlay real-time visual information, such as instructional graphics and step-by-step guidance, onto physical workspaces, improving the learning experience for workers. By incorporating advanced image processing techniques, the system ensures precise recognition of industrial tools, components and machinery, facilitating context aware training that adapts to the real-time actions of the trainee. This approach aims to accelerate the onboarding process, reduce human error, and increase efficiency in manufacturing settings, providing workers with immersive, hands-on learning opportunities while enhancing safety and operational effectiveness. The paper discusses the design, implementation and potential benefits of AR – enhanced image processing systems in industrial training programs, with a focus on scalability and practical deployment in diverse industrial environments. Keywords— Augmented Reality (AR), Image Processing, algorithms, Interactive Training, Industrial automation.

Life Cycle and Water Footprint Assessment in the Geothermal Energy Sector

The transformation of energy systems toward renewable energy sources necessitates a responsible approach to understanding and mitigating their impact on the natural environment. While previous research has primarily focused on operational aspects, a more holistic approach—such as life cycle assessment (LCA)—is crucial, as it encompasses energy installations’ production, operation, and disposal phases. This review article aims to fill this gap by comprehensively analysing the geothermal energy sector, covering electricity generation, central heating, and hot water preparation. This study emphasises the need for rigorous life cycle and water footprint assessments to understand geothermal systems’ sustainability better. Key conclusions are drawn from an extensive literature review, highlighting the sector’s challenges and opportunities. Furthermore, this article identifies innovations and research directions essential for advancing geothermal energy as an integral component of the renewable energy industry, underscoring its potential to contribute to global sustainability goals.

Two-Dimensional Bi2Se3 Nanosheets Synthesis for Efficient Electrocatalytic Production of Ammonia from Nitrate

Ammonia (NH3), a critical component for various industries, is produced through the Haber-Bosch process, which, despite its importance, is a significant source of carbon emissions and operates on a centralized model, emphasizing the need for innovative solutions to decarbonize and decentralize its production. Electrochemical nitrate (NO3–) reduction to NH3 presents a promising alternative to the Haber-Bosch process for NH3 synthesis, with the added advantage of transforming waste into a valuable resource while mitigating water pollution concerns. However, achieving a well-defined active center and catalytic selectivity in the electrochemically driven reaction remains a significant challenge. In this study, we successfully fabricated a highly selective and active 2D Bi2Se3 catalyst, which demonstrated better performance in reducing NO3– to NH3 with a Faradaic efficiency (FE) of approximately 80% (−0.3V (RHE)) and a significant yield rate of 45mgh−1mgcat−1 (0.46 mmolh−1cm−2). Furthermore, the fabricated material exhibited exceptional stability and durability, maintaining a high NO3– reduction of 80% FE even after 10 consecutive cycles of extended use and continuous operation, demonstrating its remarkable resilience and reliability. Our findings show that the prepared catalyst selectively promotes the electrochemical reduction of NO3– to NH3 while suppressing the competing hydrogen evolution reaction (HER). The charge density profile indicates a pronounced charge localization around the Se atoms, implying that the Se active sites in the 2D Bi2Se3 catalyst act as the active center for the NO3– reduction mechanism, playing a crucial role in facilitating the reaction kinetics.

Redefining Newsrooms: The Role of Artificial Intelligence in Shaping Journalism's Future

This paper seeks to justify why journalism is at the cutting edge of this revolution with Artificial Intelligence (AI); it has become an essential component of various industries. In this study, the author examines the effects of the integration of AI into the current news media industry with an emphasis on the use of AI in executing analytic functions such as writing and verification of information. As for strong points and prospects, AI contributes improvements in terms of effectiveness and time efficiency, yet it brings into focus certain drawbacks concerning ethical aspects of carrying fake news, distorted information, etc., alongside the problem of algorithms’ credibility of algorism-based journalism. In this empirical qualitative case study, the author examines the benefits and limitations of AI’s implementation in journalism. On this point, it presents literature gaps that exist on the effects of AI on ethical considerations and looks at how such organizations can balance the need to use technology and still produce work of the highest ethical standards. According to the findings, while AI may step up the accuracy and credibility that is required in news dissemination, its abuse may also lead to increased biased and fake news. Overall, this research calls for adopting AI technologies in newsrooms, but only after putting this article’s findings into practice alongside human oversight and ethics. Finally, the paper concludes the future of AI journalism and emphasizes sustainable and more responsible ways to create technological advancement within the field of Journalism to make more truthful and reliable news.

Decomposition framework for long term load forecasting on temperature insensitive area

Long-term load forecasting (LTLF) with hourly resolution provides more information for power system planning and becomes increasingly important as the growing penetration of renewable energy sources intensifies system uncertainties. In most LTLF literature, temperature is used as the main driving factor. However, the system load in an area with a high proportion of industrial energy consumption or rich diversity of climate zones is less meteorologically sensitive, which makes it challenging to implement LTLF. To address this issue, we propose a decomposition framework with industrial and temperature-sensitive components separated from the electric load and modeled, respectively. For the industrial component, a seldom-used macroeconomic variable, industrial gross products, is fed into modeling. For the temperature-sensitive component, temperature and its variants are input for modeling via variable selection. With serial and parallel modeling schemes, we further propose two decomposition models under this framework, where one, denoted as DeSerial, models two components serially, while the other, denoted as DeParallel, models them in a parallel way. Compared with representative models, the proposed two decomposition models produce more accurate monthly and annual load forecasts for the selected region, whose system load is less sensitive to temperature but more to the industries.

Baseline-free damage identification method based on guided wave for tube structures

Abstract The tube structure is a crucial component in petrochemical industry or other chemical plants, any damage could lead to severe consequences. With the widespread adoption of guided wave technology in structural health monitoring, this study presents a novel guided wave-based, baseline-free approach for localizing damage in tube structures. The core concept of this methodology involves constructing a comprehensive guided wave pattern encompassing all potential guided waves within the tube structure using the Gabor pulse model, which adeptly captures both the frequency and time attributes of guided waves. Subsequently, the composition of wave packets within each receiving sensor is determined utilizing the block sparse Bayesian learning algorithm. By optimizing the sensor arrangement strategy, a damage wave packet identification algorithm is proposed to discern the damage wave packets effectively. This approach enables damage recognition without relying on traditional baseline data by utilizing parameters from the Gabor pulse model within the damage wave packet combined with probability density. Through rigorous evaluation utilizing simulation and experimental data, the efficacy of the baseline-free damage identification method is demonstrated, with the maximum error in damage prediction confined within 8 mm.

Design and Implementation of a Mcdm Model for Supply Chain Management

Objectives: The goal of this study is to investigate the extent to which different practices of SCM have been implemented by selected firms in India. The research is a multiple case study of automotive and automotive components industry and also electronic industry in India. Methods: For each organization 15 examiners were disseminated. To produce great reactions, a solitary poll is utilized to quantify different hypothetical builds of the review. The survey is separated into three fundamental areas, where, the principal segment manages general inquiries. In the subsequent segment, the respondents are mentioned to pick one explicit elective that presents the situation with given SCM practice in their organization. The ANP and TOPSIS was utilized in this review. Results: This outcome may be a sign that the greater part of the top administration knew nothing about this model. The organizations are all exceptionally incorporated inside their inward capabilities and furthermore with their outer providers. Nonetheless, the relationship with outer clients isn't coordinated as in the previous. Conclusions: Notwithstanding practical nature of SCM, the board ought to accept that a viable SCM can assist their organizations with flourishing in the present seriously cutthroat commercial center. They ought to change their perspectives toward execution of vital organization with upstream provider and downstream clients to acquire and more advantages.

Automating the manufacturing process of control cables for the automotive components industry

AbstractThe automotive industry is of great importance to the global economy for all the jobs it generates, the materials it exploits, or the technical and technological development it drives. The control cables provide essential functions for any car, such as the opening of doors and windows, or activating the handbrake and accelerator. The process of assembling control cables involves numerous steps and the manufacture of various components, e.g., the spiral, inner and outer coating, spiral terminal, and terminals. This work deals with the injection process of control cable terminals. There is a need to separate the injection set into its constituent parts, namely the terminals and the feeding system (gate), which is carried out manually, potentially leading to health problems, e.g., tendonitis. This paper presents the development of an automated pneumatic system for the separation of control cable terminals from the feeding system. The novel pneumatic system addresses a significant gap in the automation of Zamak terminal injection by handling seven different terminal types under strict spatial limitations. The automated solution resulted in a 39% reduction in production time, enhancing the process efficiency. Moreover, by adopting the Design Science Research (DSR) methodology, the work contributes not only to industrial practice but also to the theoretical understanding of the process. This approach to automating a repetitive and ergonomically challenging task represents a step forward in the field of manufacturing technology that can be extended to other fabrication processes, leading to process improvements and competitiveness.

Ultrasonic shot peening (USSP) post-treatment of Ni laser cladding on mild steel

The ultrasonic shot peening (USSP) technique serves as a reliable post-treatment method for various industrial components to prevent functional failures. This study aims to develop hybrid Ni claddings approximately 300 µm thick on mild steel using laser cladding (LC) and USSP techniques. Morphological studies reveal that the claddings exhibit enhanced closure of cracks, increased hardness, and improved scratch resistance after peening. XRD analysis confirms the presence of compressive residual stress, as well as grain refinement and texturing effects after the peening. Furthermore, the research endeavors to improve their mechanical and electrochemical properties by employing USSP's varied process parameters in a hybrid approach. After undergoing USSP treatment, the average surface roughness was increased by up to 6 µm due to the formation of dimples, while it was 8 µm in the as-cladded and only 1.5 µm after polishing. Furthermore, compared to the as-cladded and polished claddings, the hybrid claddings exhibit a hydrophobic character linked to improved corrosion resistance and better in-depth roughness profiles.

Predicting the S-ovalbumin content and determining the freshness of chicken eggs via transmittance spectroscopy

The quality and freshness of eggs deteriorate during storage, impacting their role as a crucial dietary and industrial component. This study utilizes transmittance spectroscopy (200–1000 nm) to predict the S-ovalbumin content and to identify optimal wavelengths for assessing egg freshness levels. Three hundred fresh eggs were evaluated over 21 days of storage at ambient (25 ± 2 °C, 45 ± 5% R.H.) and refrigerated (5 ± 0.5 °C, 75 ± 5% R.H.) conditions by measuring quality indicators (Haugh unit, air cell height, yolk index, S-ovalbumin, and albumin/yolk pH). The samples were divided into several clusters using the fuzzy C-means algorithm based on these parameters. The changes in the S-ovalbumin concentration increased significantly (p < 0.01) across the storage conditions. Employing the first three principal components of preprocessed transmittance spectra as inputs to artificial neural networks enabled the discrimination of fresh from old eggs with 92% accuracy and the prediction of S-ovalbumin content with R = 0.93 and RMSE = 0.09. The light transmittance at wavelengths of 228 and 280 nm, as determined via the RELIEF algorithm, was used to classify the eggs into fresh/old (74.43% accuracy) and fresh/semi-fresh/old (72.85% accuracy) groups, demonstrating the efficacy of spectroscopy for non-destructive egg quality evaluation.

Evaluation of electron beam irradiation on the microbiological, phytochemicals, and aromatic profiles of three paprika (Capsicum annuum L.) varieties

This study provides a comprehensive evaluation of the efficacy of electron beam irradiation (EBI) for microbial decontamination and its effects on the physicochemical properties of three paprika (Capsicum annuum L.) varieties. EBI significantly reduced the total populations of bacteria, yeasts, and molds, rendering them almost undetectable at an irradiation dose of 10 kGy (p < 0.05). The color properties of EBI-treated samples showed no significant changes compared to untreated controls (p > 0.05). The total carotenoid content in S17, H23, and QJ irradiated with 25 kGy decreased by 16.91 %, 22.09 %, and 24.76 %, respectively. There was a 10.82 % increase in DPPH scavenging activity in S17 paprika samples treated with 20 kGy of EBI. Notably, no significant difference in capsaicin content was observed in H23 and QJ varieties, regardless the EBI dose increased (p > 0.05). Additionally, analysis of volatile compounds suggested that the formation of new compounds (n-methyl pyrrole and dihydroactinidiolide) was increased as the radiation doses increased. The overall results suggested that EBI treatment up to 10 kGy demonstrated a high level of effectiveness in microbial inactivation while preserving the essential physicochemical properties of paprika. Industrial relevancePaprika is an indispensable condiment in people's diets and a crucial component of the chili industry. However, it is susceptible to microbial contamination during processing, leading to food safety concerns. Irradiation treatment can inactivate microorganisms and enhance the quality of paprika. This study demonstrates that EBI can effectively achieve microbial decontamination, reduce post-harvest losses, improve the hygienic quality of paprika, and provide a technical reference for the safety of paprika and other spices.

Transfunctional Optical Thin Films via Bioinspired Engineering.

Advanced multifunctional optical films or substrates have continued to develop as essential components in the diverse optical industry. Several functions, including high transparency, self-cleaning ability, structural color, flexibility, and durability, are required to obtain versatile and practical optical films. Herein, we introduce a cicada-wing-inspired transfunctional optical thin film (CITOTF) with nanostructures on both surface nanostructures inspired by the cicada-wings. CITOTFs made of perfluoropolyether (PFPE), which has a low refractive index, low surface energy, and high robustness as a substrate material, are obtained by a well-designed sandwich lithography method. We fabricated two types of CITOTFs depending on the size (300 and 1000 nm) of the surface nanostructure. 300-CITOTF and 1000-CITOTF exhibit high transparency and structural color effects, respectively. Both samples demonstrate self-cleaning ability, flexibility, and long-term stability. The bioinspired transfunctional optical films developed in this study can be used in various optical applications.

Acid Resistance Engineering of Endoglucanase for the Degradation of Wine Lees.

Wine lees is a low value biomass resource rich in cellulose, with great potential for producing organic fertilizers and chemicals. However, the high acidity of wine lees limits the catalytic efficiency of the conversion tool endoglucanase. Here, we expressed endoglucanase tCel5A from Trichoderma reesei in Pichia pastoris, and the combination of promoter AOX1 and signal peptide SUC2 resulted in a highly active expression of 4632.81 U/mg. Subsequently, the catalytic center design and surface charge modification strategy resulted in mutants T88H/W255H and S45D/T55D/T59D exhibiting catalytic activity twice and three times higher than WT at pH 3.0, respectively. Finally, when the solid-liquid ratio was 1:15 (w/v), the degradation rate of wine lees was nearly double that of WT. The degradation products contained a variety of industrial and pharmaceutical raw components, including the antioxidant and anticonvulsant isopiperolein B. This study accelerates the green and sustainable management of wine lees.

High-precision non-contact online measurement and predictive analysis of geometric parameters in large industrial components

Obtaining precise geometric parameters is fundamental in industry but often proves challenging, particularly for large-scale and irregularly shaped industrial components. This study introduces an innovative measurement method enabling precise determination of chord length, arc length, and curvature radius in curved sections of such components, even within dynamic industrial environments. Our solution relies on the implementation of a LiDAR sensor and the utilization of data processing techniques, including outlier detection and removal, as well as customized digital filters. Additionally, we incorporate analytic geometry to address specific measurement challenges. Finally, Machine Learning techniques were applied to forecast time series data of the measurements. The proposed system was validated in a real-world wind turbine tower manufacturing environment, comparing them with manual measurements performed by experienced operators. This validation confirms its effectiveness of our approach, achieving the industry-required minimum tolerances of 5 millimeters, where precise geometric data acquisition is crucial to ensure product quality.

The Influence of the Amount of Technological Waste on the Performance Properties of Fibrous Polymer Composites

The objective of the experimental analysis was to assess the impact of the reuse of technological waste (recyclate) on the selected performance properties of the fibrous polymer composite used to produce components for the automotive industry by injection molding technology. Polyphthalamide (PPA), which belongs to a group of high-tech polymers, was chosen as the analyzed material. In accordance with the set goals, the rheological, mechanical, and structural properties of the material were evaluated using ANOVA analysis in the experimental part of the work, depending on the mass ratio of the recycled material added to the virgin material. The influence of the proportion of recycled material on the lifetime of moldings by the method of their exposure at an elevated temperature for a defined time was also assessed. During the research, it was found that at a concentration of up to 40 wt. % of recyclate, its mechanical properties do not change significantly. At a concentration of 50 wt. %, there is a rapid decrease in mechanical properties. In the long term, it can also be said that the addition of recyclate significantly affects the service life of the components. No significant changes in morphology were observed during the analysis of structural properties.