Processing Methods Research Articles

Influence of (ultra-)processing methods on aquatic proteins and product quality.

Aquatic products are a high-quality source of protein for humans, and the changes in protein during aquatic product processing are crucial for nutritional value, product performance, and consumer health. With the advancement of science and technology, aquatic product processing methods have become increasingly diverse. In addition to traditional methods such as thermal processing (steaming, roasting, and frying) and pickling, emerging non-thermal processing technologies, such as high pressure, ultrasound, and irradiation, are also being applied. During (ultra-)processing, aquatic products undergo complex biochemical reactions, among which protein oxidation significantly affects the quality of aquatic products. Protein oxidation can alter the molecular structure of proteins, thereby changing their functional properties and ultimately impacting product quality. This paper primarily explored the effects of protein changes under different processing methods on aquatic product quality and human health, as well as techniques for controlling protein oxidation. It aims to provide a theoretical basis for selecting appropriate processing methods, improving aquatic product quality, and controlling protein oxidation in aquatic products, and to offer scientific guidance for practical production.

Effect of Processing Methods on Amino Acid and Fatty Acid Composition of Parkia biglobosa Seeds

Parkia biglobosa (PB) is among the various underexploited nutritious plants. A comparative study was conducted on the effect processing PB has on the amino and fatty acid composition. Fermented (FPB), defatted (DPB), and protein isolates (PI) samples were prepared from Parkia biglobosa seeds using various processing methods, and evaluated using standard analytical protocols. The PI showed the highest significant total non-essential amino acids, essential amino acids, and conditionally essential amino acids when compared with FPB and DPB. In addition, the PI showed the highest significant (p < 0.05) total neutral amino acids, basic amino acids, total aromatic amino acids, and the lowest percentage cystine ratio of total sulphur amino acids and total amino acids in comparison with FPB and DPB. The PI also showed a better-predicted protein efficient ratio, essential amino acid index, biological value, protein content, and nutritional index than FPB and DPB. Furthermore, PI amino acid composition was compared favourably with the reference scores for a whole hen’s egg, preschool child, and provisional scoring pattern. Arginine and histidine values of PI were higher than the recommended values. The FPB (42.29%) showed the highest polyunsaturated fatty acids compared with the DPB (41.94%) and PI (26.7%). The dominant saturated, monounsaturated, and polyunsaturated fatty acids were stearic acid (15.1 DPB), linoleic acid (42.29 DPB), and oleic acid (14.05 PI). The DPB (1.84) showed a better polyunsaturated to saturated (P:S) ratio than FPB (1.74) and PI (0.91). The results revealed that the processing methods improved the relative amino acid composition, whereas the fatty acid composition improved in DPB. Therefore, PI could serve as an alternative in the formulation of complementary foods.

High-Speed and Low-Noise Gear Finishing by Gear Grinding and Honing: A Review

AbstractGears are important mechanical parts for transmitting power and play an increasingly important role in the machinery industry. The electric vehicle industry developed rapidly and became a vital development field of the automotive industry over the past few years. The conversion of energy increases the requirements for electric vehicle transmissions, which promotes the development of high-speed and low-noise transmission gear. This paper elaborates on the research progress of high-speed and low-noise gear finishing methods. Firstly, this review analyses the machining requirements, finishing, and specific machining technologies of high-speed and low-noise gears. The importance of gear grinding and honing in high-speed and low-noise gear machining is highlighted. Secondly, the applications of gear grinding and honing in gear modification, error compensation, and texture control are analyzed. Furthermore, the role of precision machining technology in improving gear performance is clarified. Finally, the design and processing methods of the modified tooth flank for gear modification are summarized. In addition, the influence of tooth surface texture on noise is described, and the texture change methods are explored. The well-known open problems of gear finishing are finally identified, and some new research interests are also pointed out. This review will provide valuable references for further research on gear finishing.

Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition

Imaging through dense fog presents unique challenges, with essential visual information crucial for applications like object detection and recognition, thereby hindering conventional image processing methods. Despite improvements through neural network-based approaches, these techniques falter under extremely low visibility conditions exacerbated by inhomogeneous illumination, which degrades deep learning performance due to inconsistent signal intensities. We introduce in this paper a novel method that adaptively filters background illumination based on Structural Differential and Integral Filtering (SDIF) to enhance only the vital signal information. The grayscale banding is eliminated by incorporating a visual optimization strategy based on image gradients. Maximum Histogram Equalization (MHE) is used to achieve high contrast while maintaining fidelity to the original content. We evaluated our algorithm using data collected from both a fog chamber and outdoor environments and performed comparative analyses with existing methods. Our findings demonstrate that our proposed method significantly enhances signal clarity under extremely low visibility conditions and out-performs existing techniques, offering substantial improvements for deep fog imaging applications.

The Influence of Labor Expenses on Current Year Profit of PT Bank Rakyat Indonesia Tbk 2003-2022

This study aims to analyze the impact of Labor expenses on the annual net income of PT BRI (Bank Rakyat Indonesia, Tbk) from 2003 to 2022. Quantitative methods are the core of the scientific rigor of this study. Library and document-based methods are used to collect data. Financial statements serve as secondary sources of information. Data processing methods based on linear regression analysis are used to test the financial statements of PT BRI Tbk for 2003-2022 with a focus on labor cost and profit data. According to the findings of the study, PT BRI Tbk's current year profit is positively and significantly affected by Labor expenses. Based on the data provided, we can conclude that this is the case because t-count = 6.6072> t-table = 1.734 and 0.00 0.05 or sig 0.05 is statistically significant.

Time-encoded photonic quantum states: Generation, processing, and applications

Encoding and processing quantum information in the time-of-arrival of photons offer significant advantages for quantum information science and technology. These advantages include ease of experimental realization, robustness over photon state transmission, and compatibility with existing telecommunication infrastructure. Additionally, time-of-arrival encoding has the potential for high-rate quantum communication and holds promise for the future development of quantum internet. This review explores the generation, processing, and applications of time-encoded quantum states, focusing on both single-photon states, energy–time entanglement, and time-bin entanglement. We summarize the nonlinear optics platforms and advanced laser and modulation techniques utilized for photon sources that enable quantum information encoding onto the photons' time-of-arrival. We also highlight advanced quantum state processing methods in the time domain, including the Franson interferometry, optical switch-based schemes, and state-of-the-art measurement and detection schemes that allow for high-speed and multi-dimensional quantum operations. Finally, we review the mainstream implementations mainly including the quantum communication demonstrations and outline future directions for developing practical quantum networks leveraging time-encoded photon states.

The Use of Interactive Teaching Methods in Educational Institutions

The article is dedicated to the study of the use of interactive teaching methods in educational institutions and their impact on the effectiveness of the learning process. In the context of dynamic changes in society and the rapid development of information technologies, the education system requires new approaches to teaching that foster active student engagement and the development of critical thinking, creative abilities, and communication skills. Interactive teaching methods, which involve dialogic interaction between participants in the educational process, open new opportunities for improving the quality of knowledge acquisition and the development of practical skills among young people. The article analyzes theoretical and practical approaches to the implementation of interactive methods in the educational process. In particular, various forms of interactive work are considered, such as group and paired activities, discussions, role-playing games, problem-based learning, and the use of interactive technologies (multimedia tools, online platforms), among others. Special attention is given to methods that enhance learning by promoting student collaboration, teamwork skills, decision-making under uncertainty, and problem-solving abilities. The article also emphasizes the advantages of interactive methods compared to traditional teaching approaches. It has been found that interactive learning leads to deeper comprehension of the material, increases student motivation, reduces passivity in the learning process, and develops the ability to apply knowledge in practice. However, it also highlights the need to adapt interactive methods to specific educational conditions and student populations, as well as the importance of adequate teacher preparation. The article provides recommendations for the effective use of interactive methods in the educational process, including the integration of interactive technologies in school and higher education, teacher professional development, and the incorporation of modern information technologies.

Phenolics in soymilk manufactured from black and Proto soybeans by two continuous-ultrahigh-temperature-processing technologies inhibit DU145-prostate cancer cell proliferation through apoptosis.

Plant genotypes and processing technologies affect health properties of foods. How thermal processes with different sterilization values influence polyphenols in soymilk manufactured from different genotypes, particularly black soybean has not been well characterized. This study's aims were to investigate how one- and two-phase ultrahigh temperature (UHT) processing technologies, with wide differences of lethality (F0 158.5 and 6.35, respectively), affected anti-prostate cancer DU145-cell properties of black soymilk compared to light-yellow-Proto soymilk. Phenolics were extracted from soymilk and used for chemical, cell cycle and apoptosis analyses. Total isoflavones and genistein in black soymilk were significantly higher than Proto soymilk by either processing methods. Compared to one-phase processing, two-phase produced higher gallic acid in both soybeans, and higher oxygen radical absorbance capacity (ORAC) in black soymilk. Soymilk processed from both genotypes by both UHT methods inhibited DU145 cells. Two-phase-UHT processed black soymilk was more effective than one-phase UHT-processed soymilk. IC50 values (mg/mL) of black and yellow soy extracts against prostate cancer cells differed only by 11%-25%, which were lower than the differences of total isoflavone (29%-33%) or genistein (>50% between two beans). The mechanism by which soymilk inhibited DU145 cell proliferation was through apoptosis as evidenced by cell cycle analyses and expressions of caspase-3, Bcl-2, and PARP-1 proteins. Antioxidant properties, isoflavones, and phenolic acids were negatively correlated with prostate-cancer-cell inhibition IC50 (p<0.05) with ORAC having the highest coefficient (r=-0.98). Overall, two-phase-UHT processing of soybean would produce soymilk products with a higher health benefit than a one-phase UHT method. PRACTICAL APPLICATION: This study characterized the potential prostate cancer prevention effect of soymilk's phenolic extract in black soybean and compared with yellow soybean. The crude extract can be prepared much less costly than purified isoflavones and has potential to be developed into a dietary supplement. This study shows differences of soymilks made by continuous high-temperature processing of two soybean types and can serve as a scientific foundation for future clinical research and commercialization.

Designing the next generation of polymers with machine learning and physics-based models

Abstract The development of next-generation polymers necessitates optimizing several key properties simultaneously, a task that is expensive and infeasible using traditional trial-and-error experimental approaches. A promising alternative is employing a combination of machine learning and physics-based tools to rapidly screen the polymer design space and provide suggestions of new polymers that meet the critical properties required for industrial applications. In this study, we introduce a comprehensive workflow that utilizes machine learning and molecular modeling approaches to design new polymers with the focus on improving five polymer properties: (1) glass transition temperature, (2) dielectric constant, (3) refractive index, (4) stress optic coefficient, and (5) linear coefficient of thermal expansion. Using a small dataset ( &lt; 200 unique polymers), we developed quantitative structure-property relationships (QSPRs) models to accurately predict the experimental polymer properties for both homo- and co-polymer systems. We tested several ML algorithms and identified the best models for predicting these polymer properties, achieving test set R 2 greater than 0.77 across all properties. We then explored new polymers by creating a library of over ∼10 000 homopolymers using R-group enumeration tools and applied the trained QSPR models to rapidly predict the five polymer properties. The predictions of QSPR models were used to create a multi-parameter optimization score, which helped downselect the large polymer space to ∼10 promising candidates. The properties of these selected polymer candidates were subsequently validated with classical molecular dynamics simulations and density functional theory, revealing a strong correlation with the QSPR model predictions. Finally, one of the top candidates was validated by experiments, which showed good agreement against QSPR and physics-based models. Our workflow underscores the power of combining data-driven and theoretical methods in the polymer design process given a small dataset size, offering a valuable resource for experimentalists looking to leverage computer-aided strategies in materials innovation.

Exploring local lignocellulosic substrates for the production of edible mushrooms in Northwestern Argentina

La Rioja province annually produces approximately 75,000 tons of agricultural residues and derived materials from agro-industrial activities, which could potentially be incorporated into oyster mushroom cultivation. This study aimed to evaluate the viability of this lignocellulosic biomass as a substrate for the cultivation of edible mushrooms belonging to the genus Pleurotus. Initially, the mycelial growth of two species (P. ostreatus and P. djamor) was assessed by formulating combinations of local substrates. Experimental crops were grown employing the most promising substrates, which were subsequently selected for chemical characterization. It was found that both strains exhibited maximum mycelial growth in the substrate formulated with jojoba leaf litter. A comparison of the two strains revealed no direct correlation between mycelium growth and productive performance. The highest biological efficiency (BE) values were obtained when P. ostreatus was cultivated in treatments combining jojoba leaf litter and grape pomace with olive pomace. Furthermore, these treatments showed suitable chemical properties and were formulated from problematic waste generated in large quantities in the region without proper processing and disposal methods. In this context, there is potential to ensure a continuous supply of this lignocellulosic biomass for cultivating these mushroom species over an extended period of time, thus providing a sustainable alternative for these regional by-products.

Climate-Driven Sustainable Energy Investments: Key Decision Factors for a Low-Carbon Transition Using a Multi-Criteria Approach

Currently, the need for a clean transition has made the upscaling of sustainable energy investment projects imperative. This paper addresses the increasing importance of sustainable energy investment projects in the context of climate change and the urgent need for a global energy transition. Given the complexity of decision-making in this field, a multi-criteria decision-making (MCDM) approach is employed to assess the main criteria considered by project developers and financial institutions. Using the Analytic Hierarchy Process (AHP) method, eight criteria are identified and evaluated. Results highlight differing priorities between project developers and investors, emphasizing the need for adaptable approaches to accelerate sustainable energy investments. The study underscores the importance of understanding diverse stakeholder preferences and priorities in formulating effective strategies and managing associated risks to effectively promote sustainable energy projects. Future research should focus on real-life case studies and policy assessments to further enhance the understanding of sustainable energy investment dynamics.

Analysis of sagittal plane cine magnetic resonance imaging for measurement of pancreatic tumor residual motion during breath hold and evaluation of gating margins used in radiotherapy treatment.

In pancreatic radiotherapy, residual tumor motion during treatment increases the risk of toxicity. Cine imaging acquired during magnetic resonance guided radiotherapy (MRgRT) enables real-time treatment gating in response to anatomical motion, which can reduce this risk; however, treatment gating can negatively impact the efficiency of treatment. This study aimed to quantify the extent of residual tumor motion during breath hold and evaluate the appropriateness of the treatment gating margins used in current clinical practice. Cine imaging acquired during pancreatic MRgRT of 11 patients on the ViewRay MRIdian was analyzed. The total duration of treatment analyzed was 12 h 13 min. Improved methods for processing and analyzing cine imaging were developed: breath holds were systematically separated with frequency analysis, residual motion was measured with consideration of both the tracking structure contour and centroid, and residual motion measurements were supported by phantom measurements of image scaling, resolution, and noise. Residual motion was measured at angles 0°, 45°, 90°, and 135° to the superior-inferior (SI) direction. Total residual motion was measured by combining directional measurements. The minimum tracking structure displacement resolvable through cine imaging was found to be 1.5mm; therefore, residual motion analysis was limited to 1.5mm spatial resolution. Total residual motion was contained within margins ±1.5, ±3, and ±4.5mm with mean percentage frequencies of 97.0%, 91.1%, and 67.8%. Most residual motion was observed in the SI direction, and significantly more residual motion was measured for the tracking structure contour than the centroid. The results demonstrate that patients are largely able to maintain breath hold positions to within a 3mm margin, thus provide evidence that supports the use of a 3mm gating margin in clinical practice. Residual motion frequently exceeded 1.5mm so a reduction in gating margin would have an undesirable impact on treatment efficiency.

Image Dehazing Enhancement Strategy Based on Polarization Detection of Space Targets

In view of the fact that the technology of polarization detection performs better at identifying targets through clouds and fog, the recognition ability of the space target detection system under haze conditions will be improved by applying the technology. However, due to the low ambient brightness and limited target radiation information during space target detection, the polarization information of space target is seriously lost, and the advantages of polarization detection technology in identifying targets through clouds and fog cannot be effectively exerted under the condition of haze detection. In order to solve the above problem, a dehazing enhancement strategy specifically applied to polarization images of space targets is proposed. Firstly, a hybrid multi-channel interpolation method based on regional correlation analysis is proposed to improve the calculation accuracy of polarization information during preprocessing. Secondly, an image processing method based on full polarization information inversion is proposed to obtain the degree of polarization of the image after inversion and the intensity of the image after dehazing. Finally, the image fusion method based on discrete cosine transform is used to obtain the dehazing polarization fusion enhancement image. The effectiveness of the proposed image processing strategy is verified by carrying out simulated and real space target detection experiments. Compared with other methods, by using the proposed image processing strategy, the quality of the polarization images of space targets obtained under the haze condition is significantly improved. Our research results have important practical implications for promoting the wide application of polarization detection technology in the field of space target detection.

Motor Imagery Classification Improvement of Two-Class Data with Covariance Decentering Eigenface Analysis for Brain–Computer Interface Systems

This study is intended to improve the motor imagery classification performance of two-class data points using newly developed covariance decentering eigenface analysis (CDC-EFA). When extracting the classification for the given data points, it is necessary to precisely distinguish the classes because the left and right features are difficult to differentiate. However, when centering is performed, the unique average data of each feature are lost, making them difficult to distinguish. CDC-EFA reverses the centering method to enhance data characteristics, making it possible to assign weights to data with a high correlation with other data. In experiments with the BCI dataset, the proposed CDC-EFA method was used after preprocessing by filtering and selecting the electroencephalogram data. The decentering process was then performed on the covariance matrix calculated when acquiring the unique face. Subsequently, we verified the classification improvement performance via simulations using several BCI competition datasets. Several signal processing methods were applied to compare the accuracy results of the motor imagery classification. The proposed CDC-EFA method yielded an average accuracy result of 98.89%. Thus, it showed improved accuracy compared with the other methods and stable performance with a low standard deviation.

Pengaruh Bauran Pemasaran Terhadap Keputusan Menjadi Anggota di BMT Al-Ishlah Kota Jambi

The purpose of this study was to determine whether the marketing mix consisting of product, price, location, and promotion has a significant effect on the decision to become a member of BMT Al-Ishlah Jambi City. The method and type of research used is quantitative influence. The research was conducted at BMT Al-Ishlah Jambi City because it is easy to collect data and obtain research permits, support for academic research and a sufficient population of 564. The sampling method used was simple random sampling, so that 85 samples were obtained. The research instruments used documentation and questionnaires. The data processing and analysis methods used in this study include descriptive analysis, validity and reability tests, data analysis and hypotesis testing. The results showed that the product, location and promotion variables partially had No. significant effect on the decision to become a member of BMT Al-Ishlah Jambi City, while on the price variable partially had a positive and significant effect on the decision to become a member of BMT Al-Ishlah Jambi City. And simultaneously, the variables of product, price, location, and promotion affect the decision to become a member of BMT Al-Ishlah Jambi City.

Sustainable sentiment analysis on E-commerce platforms using a weighted parallel hybrid deep learning approach for smart cities applications

Sentiment analysis (SA) of several user evaluations on e-commerce platforms can be used to increase customer happiness. This method automatically extracts and identifies subjective data from product evaluations using natural language processing (NLP) and machine learning (ML) methods. These statistics may eventually reveal information on the favourable, neutral, or negative attitudes of the consumer base. Due to its capacity to grasp the complex links between words and phrases in reviews as well as the emotions they imply, deep learning (DL) is very useful for SA tasks. A unique approach termed Weighted Parallel Hybrid Deep Learning-based Sentiment Analysis on E-Commerce Product Reviews (WPHDL-SAEPR) is introduced by the proposed system. Accurately distinguishing between distinct sentiments found in online store reviews is the aim of the WPHDL-SAEPR technique. Additional data pre-processing processes are implemented within the WPHDL-SAEPR architecture to guarantee compatibility. Words are embedded into the paper using the word2vec model, while sentiment is classified using the WPHDL model. The Restricted Boltzmann Machine (RBM) and Singular Value Decomposition (SVD) models are combined in this model. The results of the WPHDL-SAEPR approach’s simulation were assessed using a consumer review database, with the results being emphasized at each stage.

Cold plasma technology: does it have a place in food processing?

In recent years, there has been a growing demand for alternative food processing technologies that can improve food safety while preserving the nutritional quality of food products. Traditional thermal processing methods can lead to nutrient loss and degradation, prompting the exploration of novel approaches. Cold plasma (CP) technology, an emerging non-thermal food processing technique, has gained significant attention for its potential in the food industry. We provide herein, an introduction to CP and an overview of the technology, highlighting its potential advantages in safety, efficiency, and environmental friendliness.

Analisis Penerapan Pajak Pertambahan Nilai pada PT. Quantum Mandiri International

The research was conducted using a mixed method between quantitative and qualitative to determine the relationship between inflation and Value Added Tax (VAT). In addition, this research was also conducted to find out how the application of VAT in terms of calculation, payment and reporting stated in the company's Periodic Notification Letter (PNL). This is done to avoid tax sanctions, one of which is the receipt of a Tax Collection Letter (TCL). The independent variable uses inflation and the dependent variable uses VAT. This study uses data on inflation and VAT reported as much as 36 data with the period 2021-2023. Simple linear regression analysis is used in the data processing method and processed using statistical data processing tools. The results of existing data processing show that inflation has a positive impact on VAT. In the February 2021 and March 2021 VAT Periodic Tax Returns there are still corrections caused by errors in making Tax Invoices (TI), resulting in delays in payment and reporting of VAT NPL. Due to this delay, it resulted in the receipt of STP from the Tax Service Office (TSO) and a response has been made by the company to the TCL that has been received. For the April 2021 to December 2023 VAT NPL, the company has paid and reported VAT so that no TCL has been received from the TSO.

A Simple Regeneration Process Using a CO2-Switchable-Polarity Solvent for Cellulose Hydrogels.

Cellulose is one of the main components of plant cell walls, abundant on earth, and can be acquired at a low cost. Furthermore, there has been increasing interest in its use in environmentally friendly, carbon-neutral, sustainable materials. It is expected that the applications of cellulose will expand with the development of a simple processing method. In this study, we dissolved cellulose in aqueous N-butyl-N-methylpyrrolidinium hydroxide solution ([C4mpyr][OH]/H2O) and investigated the cellulose regeneration process based on changes in solubility upon application of CO2 gas. We investigated the effect of transformation of the anion chemical structure on cellulose solubility by flowing CO2 gas into [C4mpyr][OH]/H2O and conducted pH, FT-IR, and 13C NMR measurements. We observed that the changes in anion structure allowed for the modulation of cellulose solubility in [C4mpyr][OH]/H2O, thus establishing a simple and safe cellulose regeneration process. This regeneration process was also applied to enable the production of cellulose hydrogels. The hydrogel formed using this method was revealed to have higher mechanical strength than an analogous hydrogel produced using the same dissolution solvent with the addition of a cross-linker. The ability to produce cellulose-based hydrogels of different mechanical properties is expected to expand the possible applications.

The effectiveness of the project method in teaching humanitarian disciplines

The purpose of this study was to identify the effectiveness of the project method as an innovative tool for the teaching of humanitarian subjects. The research used such methods as follows: questionnaire, observation, experiment, as well as statistical methods for data processing. In the course of the research, it was determined that the students who were engaged in the project activity, during the project, autonomously researched scientific, reference, educational, and methodological literature. A group of experts found that students’ participation in project activities influenced the development of creative activity, and creative systemic thinking contributed to their self-organization. During the survey, it was determined that students' independent work on creating projects ensures the development of personal and functional components of selforganization. The research's scientific novelty lies in its exclusive focus on students studying humanitarian disciplines. The restricted scope of the experiment facilitated the identification of the project approach as such that it can be integrated into the academic system to enhance students' personal and practical proficiencies, thereby promoting their overall growth. Further research can be aimed at determining the effectiveness of using game methods in the course of teaching humanitarian disciplines.