Traditional Process Research Articles

Effects of Mebyakaonan Marriage Law in the Perspective of Balinese Customary Law: Study on Balinese Community, Rantau Jaya Village, Ilir District, Putra Rumbia, Central Lampung Regency

Marriage is the outward and inner bond between a man and a woman as husband and wife to continue their lineage. Marriage in Balinese customs is called pawiwahan. Pawiwahan is a sacred thing in the process of human life from the status of brahmacari to the time of grhasta. Mebyakaon marriage is marriage under the hand. The problem in this study is why mebyakaon marriage is taken by the parties to form a marriage and the legal consequences of mebyakaon marriage on their marital status in the community and the status of children born from this marriage in Rantau Jaya Ilir Village, Putra Rumbia District, Central Lampung Regency. This research is normative-empirical legal research with a descriptive research type. The problem approach used sociological juridical approach with data sources is primary data and secondary data. Data collection techniques with literature studies and field studies are interviews with informants and respondents who carry out marriage mebyakaon. Data analysis is qualitative analysis. The results of research and discussion show that the reason for the marriage is caused by several factors, namely economic factors, educational factors, mutual demen, parental desire factors, and the factor of men who are still legally married to other women. The marital status of mebyakaon is not the same as traditional Balinese marriage in general, what distinguishes it from mebyakaon marriage is that it lies in a traditional procession that has not been carried out completely. Based on the decisions and decrees of Parisadha Hindu Dharma Indonesia (PHDI), the validity of marriage is determined on condition that Tri Upasaksi. The legal position of mebyakaon marriage does not have a strong binding force so that this marriage may not have the same legal status as traditional Balinese married couples in general. Similarly, the legal consequences of marriage will be different. Couples who perform mebyakaon marriage may not enter the temple and participate in the massacre in the village because mebyakaon marriage is valid according to the parties only but, according to Balinese customary law this marriage is invalid and children born from mebyakaon marriage are extramarital children (anak astra) and marital property in mebyakaon marriage There is no legal certainty and there is no mixing of property between husband and wife.

Fermentation Kinetics, Potability, and Sensory Compounds of Joubidwi: An Ethnic Alcoholic Beverage

Background: Fermentation is a metabolic pathway of the breakdown of carbohydrate molecules like glucose, fructose to ethanol and various volatile and non-volatile congeners. The production of alcoholic beverages from foodstuffs like rice, cereals, fruits, maize etc., is an age-old traditional protocol. In this study, we adapted the traditional protocol of preparation of the ethnic beverage Joubidwi, with a fermentation time of 6 days, i.e., aliquots from the fermented mash (cooked rice) were collected on a daily basis from day 1 to day 6. Objectives: This study aimed to get insight into fermentation kinetics, ethanol content, carbohydrate content, antioxidant activities, bitterness, protein content, pH, colour, and turbidity of the ethnic alcoholic beverage Joubidwi and to identify the sensory compounds and polyphenol molecules. Method: UV-Visible spectroscopic methods, GC-FID and GC-MS analytics methods were used for the estimation and identification of carbohydrates, proteins, ethanol contents, and sensory compounds, respectively. Reverse phase HPLC was adapted for the identification of polyphenol molecules in Joubidwi. Results: A pseudo-first-order fermentation kinetics was observed from day 1 to day 6 fermentation of Joubidwi. Apart from ethanol content (60.48 ± 1.36 mg/mL after 72 h fermentation to 78.80 ± 1.48 mg/mL after 144 h fermentation), the beverage had nutritional values and good antioxidant properties with 22.38 to 35.11% Radical Scavenging Effect (RSE) from 1 to 6th day of fermented Joubidwi. The beverage also contained 12 sensory compounds. Gallic acid was identified as polyphenol in Joubidwi samples. Conclusion: Joubidwi is an alcoholic beverage prepared by Bodos using rice and certain herbs through a traditional fermentation process. The fermentation process follows pseudo-first-order kinetics. The beverage is potable.

Identification Of Traditional Foods In West Pasaman District

This study aims to learn more about traditional food in West Pasaman District. The research was conducted August-December 2023 in West Pasaman District.The purpose of this study was to identify the types of food, ingredients used and traditional food processing techniques in West Pasaman District. The type of research used is a mix method (qualitative and quantitative). This research data was obtained from two ways, namely primary data and secondary data. Primary data was conducted to identify the types of traditional food, ingredients used and traditional food processing techniques in West Pasaman District. While secondary data is in the form of demographics of West Pasaman District. Data collection techniques are carried out by observation, interviews, and documentation. Data analysis is done by reducing data, presenting data, and concluding. The conclusion of the research results is that traditional food in West Pasaman Regency is a typical food that has existed for a long time. The ingredients used are food ingredients developed by yourself. As well as traditional food processing techniques that are typical in West Pasaman District. 

Adat Teka Ra Ne’e dalam Kajian Hukum Islam di Desa Tanah Putih Kecamatan Sape Kabupaten Bima

The Teka Ra Ne’e tradition is a custom carried out by the community when going to school carry out the marriage process. The aim of the Teka Ra Ne'e tradition is to lighten burden on the owner. The aim of this research is to find out the Teka Ra Ne'e traditional procession in the Tanah Putih Village community and to identify how the law views it Islam towards the Teka Ra Ne'e custom in traditional marriages in the Tanah Putih Village community Sape District, Bima Regency. The research method used is research qualitative with a descriptive approach, the collection used is observation, interviews, and documentation. The research subjects were community leaders, traditional leaders and the government Village. Data analysis using interactive models. The results of this research can be concluded that implementation of Teka Ra Ne'e in the Bima traditional wedding procession, especially in Tanah Putih Village Sape District, Bima Regency, namely: (1) Deliberation between families and community leaders, (2) Kaboro haju ka'a, (3) Ti'a haju ka'a, (4) Ndua invitation (dividing invitations), (5) Choosing Ina pangaha, (6) Ndawi Pangaha, (7) Ka eli swamp mbojo, (8) Teka Ra Ne'e, (9) Rice Shedding. Teka Ra Ne'e does not conflict with Islamic law, because it has more benefits rather than the disadvantages such as teaching cooperation (mutual cooperation), friendship, relationship close ties of brotherhood, as well as lightening the burden between people who have a celebration

Analyzing the Architecture of All Saints Cathedral at Allahabad, India: Building Study and Heritage Potential

Heritage conservation is a major factor in promoting tourism. It helps to understand previous tradition, used materials, architecture style and evolution process. The link between heritage and tourism is the most visible aspect of the contribution of culture to local development. Due to the preservation of heritage many new jobs can be generated in the truism sector. When heritage tourism is done right the biggest beneficiaries not the visitors only but the local residents who experience a renewable appreciation in for and pride in their local city and its history. Art and architecture have the ability to transport us into different time and place it allows us to gain historical perspective and understanding. The All-Saints’ Cathedral in Allahabad stands as an epitome of architectural brilliance, religious heritage, and cultural significance. This research delves into the profound architectural attributes of the cathedral, offering insights into its historical context, structural design, and socio-cultural impact. Drawing upon architectural analysis and historical documentation, the study examines the evolution of the cathedral’s design, from its inception to its present form. Through a comparative analysis of architectural elements, including facade, interior layout, and ornamentation, the research delineates the cathedral’s adherence to prevailing architectural styles and its unique deviations. In conclusion, this research underscores the All Saints’ Cathedral in Allahabad as not merely a physical structure but a testament to architectural innovation, cultural heritage, and spiritual resilience. By elucidating its architectural intricacies and socio-cultural implications, the study contributes to a deeper understanding of the cathedral's enduring legacy in the architectural landscape of Allahabad.This study explores the transformative impact of architectural elements on the spiritual experience within All Saints' Cathedral, Allahabad. Analyzing furniture, lighting, flooring, ceiling, fans, and roofing, it unveils how these components contribute to the cathedral's upliftment of worshippers. Through a nuanced examination, it elucidates the intricate balance between structural design and spiritual elevation, shedding light on the cathedral's role as a sacred haven in the hearts of believers.

A survey on brain MRI segmentation

Neurological disorders pose a significant challenge in medical diagnostics, requiring accurate and efficient analysis of brain Magnetic Resonance Imaging (MRI) scans. This study introduces a novel approach for enhanced neurological diagnosis through the application of deep learning techniques to automate the segmentation of brain structures in MRI images. The proposed method leverages the power of convolutional neural networks (CNNs) to extract intricate patterns and features from complex neuro imaging data. The research involves the development and training of a deep learning model capable of accurately delineating key anatomical regions, such as the cortex, hippocampus, and ventricles. The model is trained on a large data set of annotated MRI scans, optimizing its performance through rigorous validation processes. The utilization of deep learning enables the algorithm to learn and generalize from diverse imaging data, improving its adaptability to variations in patient demographics and scanner characteristics. To evaluate the effectiveness of the proposed approach, comprehensive experiments are conducted on a diverse set of MRI datasets, encompassing various neurological conditions. Quantitative metrics, including Dice coefficient and Hausdorff distance, are employed to assess the segmentation accuracy compared to ground truth annotations. Additionally, the clinical relevance of the automated segmentation is validated through collaboration with neurologists and radiologists. The results demonstrate that the deep learning- enabled segmentation method consistently outperforms traditional image processing techniques, providing more accurate and reliable segmentation results. The proposed approach not only streamlines the diagnostic process but also has the potential to uncover subtle abnormalities that may be overlooked by manual inspection. In conclusion, the integration of deep learning into the segmentation of brain MRI scans presents a promising avenue for enhancing neurological diagnosis. The automated and precise delineation of brain structures contributes to the efficiency and accuracy of diagnostic workflows, ultimately improving patient outcomes and facilitating timely interventions in the realm of neurological disorders.

Advancing subsurface analysis: Integrating computer vision and deep learning for the near real-time interpretation of borehole image logs in the Illinois Basin-Decatur Project

The accurate quantification and mapping of subsurface natural fracture systems using borehole imaging logs are critical for the success of CO2 sequestration in geologic formations, optimization of engineered geothermal systems, and hydrocarbon production enhancement. However, traditional interpretation processes suffer from time-consuming procedures and human bias. To address these challenges and expedite fracture analysis, we investigated the application of integrated computer vision and DL workflows to automate image log analysis. Specifically, the design of our workflow was crafted to swiftly detect fractures and baffles by using actual electrical resistivity of borehole wall from microresistivity imaging device alongside their binary representation. This novel approach significantly reduces computational time while providing invaluable insights. By incorporating conventional logging and microseismic data, we present a regional subsurface natural fracture mapping technique. Through the minimization of human bias in image log analysis, our automated workflow achieves reduced fracture interpretation time and costs while ensuring robust and reproducible results. We demonstrated the efficacy of our approach by applying the workflow to the Illinois Basin-Decatur Project site. The automated workflow successfully identified major fractured zones, multiple baffles, and an interbedded layer with a high resolution of 0.01 ft or 0.12 in. (0.3 cm) and can be upscaled to any desired resolution. Validation through microseismic and image log interpretations allows for accurate and near-real-time mapping of fractures and baffles, significantly enhancing CO2 pressure forecasting and postinjection site care. Our approach stands out due to its robustness, consistency, and reduced computational cost compared with alternative feature extraction technologies. It presents exciting possibilities for advancing CO2 sequestration and engineered geothermal efforts by offering comprehensive and efficient fracture mapping solutions. This technology can contribute significantly to the optimization of CO2 sequestration projects, facilitating sustainable environmental practices, and combating climate change.

Synthesis of Integrated Material with Activation and Oxidation Functions by Mechanical Milling of Activated Carbon and Persulfate for Enhanced Tetracycline Degradation over Non-Radical Mechanism

As an alternative to the traditional advanced oxidation process of adding potassium persulfate (PS) and its activator to the solution separately, in this study, M(AC-PS), an integrated activator and catalyst, was synthesized by vacuum ball milling of PS and activated carbon (AC) to improve the PS’s utilization efficiency. The joint mechanical milling caused a change in the preferentially exposed crystal surface of the PS and the generation of more π-π* structures on the AC, leading to successful and stable connection of the PS onto the surface of the AC. Within 40 min, the M(AC-PS) achieved a degradation rate of 97.3% for tetracycline (TC, 20 mg/L), while the mixed system where AC and PS were separately ball milled achieved only a 53.1% removal of TC. Reactive oxygen species and electrochemical tests showed that M(AC-PS) mainly oxidized TC through non-free radical mechanisms. In M(AC-PS), AC provided oxygen-containing functional groups (e.g., C=O) to activate the PS and electron holes as an electron transfer medium, generating 1O2 and promoting electron donation from the TC to enhance the oxidation of the TC. Almost no catalytic components were detected in the solution, indicating that the obtained solid composite material avoids the limitations of solid–liquid interface contact and mass transfer, and then improves the efficiency of activation and catalysis. This study presents a simple and feasible method for obtaining efficient and convenient material for the advanced oxidation treatment of wastewater.

Effect of salting and dehydration treatments on the physicochemical and gel properties of hen and duck egg yolks, plasma and granules.

Salted hen egg yolks are less oily and less flavorful than salted duck egg yolks. However, hen eggs have a more adequate market supply and have a broader application prospect than duck eggs. In the present study, egg yolks, plasma, and granules were dehydrated by adding 1% NaCl to simulate traditional curing process of salted egg yolk. The changes in the pickling process of hen egg yolks (HEY) and duck egg yolks (DEY) plasma and granules were compared to reveal the gelation mechanism and the underlying causes of quality differences in salted HEY and DEY. Salted HEY can be compared with the changes in DEY during the pickling process to provide a theoretical basis for the quality improvement of salted HEY to salted DEY. The results showed that both plasma and granules were involved in gel formation, but exhibited different aggregation behaviors. Based on the intermolecular forces, the HEY proteins achieved aggregation mainly through hydrophobic interactions and DEY proteins mainly through covalent binding. According to spin-spin relaxation time, HEY gels immobilized a large amount of lipid and interacted strongly with lipids. DEY gels showed much free lipid and had weak interaction with lipid. The microstructure showed that HEY proteins were easily unfolded to form a homogeneous three-dimensional gel network structure after salting, whereas heterogeneous aggregates were formed to hinder the gel development in DEY. Changes in protein secondary structure content showed that pickling can promote the transformation of the α-helices to β-sheets structure in HEY gels, whereas more α-helices structure was formed in DEY gels. The present study has demonstrated that different gelation behaviors of hen and duck egg yolk proteins (especially in plasma) through salting treatment led to the difference in the quality of salted HEY and DEY. © 2024 Society of Chemical Industry.

Effect of solar radiation and full spectrum artificial sun light drying on the drying characteristics, ultra-structural and textural properties of white radish (Raphanus sativus L.)

Traditional sun drying has long been employed as a method for preserving radishes (Raphanus sativus L.) However, it suffers from various uncertainties, including weather-related factors such as rain and cloudy days, the pressing issue of climatic change can lead to an impact on the traditional drying process and texture of radish. In this research, the full spectrum artificial sunlight drying (FSASLD) has been implemented to simulate the traditional open sun drying of white radish slices which helps to prevent hygienic issues and unstable climatic conditions. Water activity (Aw) was measured and observed to decrease from 0.89 to 0.60 under both drying methods, indicating the removal of moisture from radish cells. Mathematical modelling and color kinetics models were studied with respect to drying time. Texture Profile Analysis (TPA) was employed to assess hardness, and results showed an increase in hardness following both SD (1018.24 g to 1327.67 g) and FSASLD (1018.24 g to 1731.04 g) salt treated radish slices. These findings suggest that FSASLD can serve as a viable alternative to the conventional drying method and contributes to agricultural innovation and the food industry, reducing drying time significantly from 270 min to 200 min and minimizing the impact of adverse weather conditions and interference from animals and microorganisms.

ASPIRE for excellence in curriculum development

The objective of the ASPIRE award programme of the International Association for Health Professions Education is to go beyond traditional accreditation processes. Working in partnership with the ASPIRE Academy, the programme aims to encourage and support excellence in health professions education, in part by showcasing and exemplifying best practices. Each year ASPIRE award applications received from institutions across the globe describe their greatest achievements in a variety of areas, one of which is curriculum development, where evaluation of applications is carried out using a framework of six domains. These are described in this paper as key elements of excellence, specifically, Organisational Structure and Curriculum Management; Underlying Educational Strategy; Content Specification and Pedagogy; Teaching and Learning Methods and Environment; Assessment, Monitoring and Evaluation; Scholarship. Using examples from the content of submissions of three medical schools from very different settings that have been successful in the past few years, achievements in education processes and outcomes of institutions around the world are highlighted in ways that are relevant to their local and societal contexts.

EyeMo: A Solution for Individuals with Disabilities to Use a Computer Through Eye Movements

The maintenance of an upright posture and the execution of desired movements by individuals necessitate the seamless and harmonious functioning of the muscular and skeletal systems. Neuromuscular diseases, spinal cord injuries, and related conditions can adversely impact individuals' motor functions, leading to a loss of muscle strength and, in severe cases, paralysis. Such health challenges may result in social isolation and detachment from one's social life. This study is focused on the development of a computer control application utilizing eye movements to aid users in navigating and interacting with computers. The system utilizes a lightweight eyeglass frame and a mini-USB camera to accurately capture images of the user's pupil. Pupil detection is achieved through a combination of traditional image processing and deep learning techniques, ensuring high accuracy under diverse conditions. Users have the ability to interactively calibrate the application to accommodate varying screen sizes, thereby enhancing system responsiveness. The user interface incorporates functionalities such as left-click, right-click, double-click, and scrolling, empowering users to perform tasks ranging from internet browsing to video watching. 
 After the development of the application, a request for research permission was submitted to the local institution to allow volunteers to test the application, adhering to ethical standards. Following the approval of ethical clearance, the application was made available for use by volunteers, and feedback was systematically collected. Volunteers generally reported that the application was beneficial, indicating its potential use by disadvantaged individuals. The upcoming versions of the application have the potential for integration with smart home systems. Additionally, the developed application can be used in games and for educational purposes.

Lamination of >21% Efficient Perovskite Solar Cells with Independent Process Control of Transport Layers and Interfaces.

Transport layer and interface optimization is critical for improving the performance and stability of perovskite solar cells (PSCs) but is restricted by the conventional fabrication approach of sequential layer deposition. While the bottom transport layer is processed with minimum constraints, the narrow thermal and chemical stability window of the halide perovskite (HP) layer severely restricts the choice of top transport layer and its processing conditions. To overcome these limitations, we demonstrate lamination of HPs─where two transport layer-perovskite half-stacks are independently processed and diffusion-bonded at the HP-HP interface─as an alternative fabrication strategy that enables self-encapsulated solar cells. Power conversion efficiencies (PCE) of >21% are realized using cells that incorporate a novel transport layer combination along with dual-interface passivation via self-assembled monolayers, both of which are uniquely enabled by the lamination approach. This is the highest reported PCE for any laminated PSC encapsulated between glass substrates. We further show that this approach expands the processing window beyond traditional fabrication processes and is adaptable for different transport layer compositions. The laminated PSCs retained >75% of their initial PCE after 1000 h of 1-sun illumination at 40 °C in air using an all-inorganic transport layer configuration without additional encapsulation. Furthermore, a laminated 1 cm2 device maintained a Voc of 1.16 V. The scalable lamination strategy in this study enables the implementation of new transport layers and interfacial engineering approaches for improving performance and stability.

Small object detection algorithm incorporating swin transformer for tea buds.

Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identification remains an enormous challenge. Current methods based on traditional image processing and machine learning fail to effectively extract subtle features and morphology of small tea buds, resulting in low accuracy and robustness. To achieve accurate identification, this paper proposes a small object detection algorithm called STF-YOLO (Small Target Detection with Swin Transformer and Focused YOLO), which integrates the Swin Transformer module and the YOLOv8 network to improve the detection ability of small objects. The Swin Transformer module extracts visual features based on a self-attention mechanism, which captures global and local context information of small objects to enhance feature representation. The YOLOv8 network is an object detector based on deep convolutional neural networks, offering high speed and precision. Based on the YOLOv8 network, modules including Focus and Depthwise Convolution are introduced to reduce computation and parameters, increase receptive field and feature channels, and improve feature fusion and transmission. Additionally, the Wise Intersection over Union loss is utilized to optimize the network. Experiments conducted on a self-created dataset of tea buds demonstrate that the STF-YOLO model achieves outstanding results, with an accuracy of 91.5% and a mean Average Precision of 89.4%. These results are significantly better than other detectors. Results show that, compared to mainstream algorithms (YOLOv8, YOLOv7, YOLOv5, and YOLOx), the model improves accuracy and F1 score by 5-20.22 percentage points and 0.03-0.13, respectively, proving its effectiveness in enhancing small object detection performance. This research provides technical means for the accurate identification of small tea buds in complex environments and offers insights into small object detection. Future research can further optimize model structures and parameters for more scenarios and tasks, as well as explore data augmentation and model fusion methods to improve generalization ability and robustness.

Changes in chemical components and hepatoprotective effect of red Panax notoginseng processed by aspartic acid impregnation treatment.

Red Panax notoginseng (RPN) is one of the major processed products of P. notoginseng (PN), with more effective biological activities. However, the traditional processing method of RPN has some disadvantages, such as low conversion rate of ginsenosides and long processing time. In this work, we developed a green, safe, and efficient approach for RPN processing by aspartic acid impregnation pretreatment. Our results showed that the optimized temperature, steaming time, and concentration of aspartic acid were 120 °C, 1 h, and 3% respectively. The original ginsenosides in PN treated by aspartic acid (Asp-PN) were completely converted to rare saponins at 120 °C within just 1 h. The concentration of the rare ginsenosides in Asp-PN was two times higher than that in untreated RPN. In addition, we examined the protective effect of RPN and Asp-PN on acetaminophen-induced liver injury in a mouse model. The results showed that Asp-PN has significantly more potent hepatoprotective action than the RPN. The hepatoprotection of Asp-PN in acetaminophen-induced hepatotoxicity may be due to its anti-oxidative stress, anti-apoptotic, and anti-inflammatory activities. These results indicated that aspartic acid impregnation pretreatment may provide an effective method to shorten the steaming time, improve the conversion rate of ginsenosides, and enhance hepatoprotective activity of RPN. © 2024 Society of Chemical Industry.

Enhancing value creation of operational management for small to medium manufacturer: A conceptual data-driven analytical system

This paper aims to explore the challenges and opportunities for Small and Medium-sized Manufacturing Enterprises (SMMEs) in implementing data-driven techniques in their operations. SMMEs are often considered to be low and medium–low tech companies, even if they have machinery, as they still rely on traditional processes and manpower and lack any digital technology. Previous research has shown that medium–high and high-tech companies perform better, with higher rates of growth, than low and medium–low ones by a sustainable and significant margin. Therefore, there is a need for further research on the implementation of data-driven analytical methods and technologies in SMMEs that are both cost-effective and easy to use. This study proposes a conceptual analytical system that combines Integration Definition for Function Modeling 0 (IDEF0) and the Cross Industry Standard Process for Data Mining (CRISP-DM) business analytics method to develop a practical and widely applicable framework for data-driven techniques in manufacturing. We then developed a case study of an Indonesian company, where we collected real and direct information about specific objects, events, and activities related to particular aspects, including showing their key performance indicators (KPIs) through data dashboards, to evaluate the effectiveness of the proposed conceptual analytical system in improving operational management in SMMEs. The findings of this study provide valuable insights that can be used to develop effective solutions for SMMEs to leverage data-driven techniques and improve their operations. We also highlight implications of the findings for future research and practical applications. The final framework can be converted into a system that can be continuously and flexibly updated and customized, based on specific needs.

Host cell proteins in monoclonal antibody processing: Control, detection, and removal.

Host cell proteins (HCPs) are process-related impurities in a therapeutic protein expressed using cell culture technology. This review presents biopharmaceutical industry trends in terms of both HCPs in the bioprocessing of monoclonal antibodies (mAbs) and the capabilities for HCP clearance by downstream unit operations. A comprehensive assessment of currently implemented and emerging technologies in the manufacturing processes with extensive references was performed. Meta-analyses of published downstream data were conducted to identify trends. Improved analytical methods and understanding of "high-risk" HCPs lead to more robust manufacturing processes and higher-quality therapeutics. The trend of higher cell density cultures leads to both higher mAb expression and higher HCP levels. However, HCP levels can be significantly reduced with improvements in operations, resulting in similar concentrations of approx. 10 ppm HCPs. There are no differences in the performance of HCP clearance between recent enhanced downstream operations and traditional batch processing. This review includes best practices for developing improved processes.

Optimizing production logistics through advanced machine learning techniques: A study on resource allocation for small-batch and multi-variety challenges

In light of increasing consumer purchasing power and the growing diversification of demands, the emergence of small-batch and multi-variety requirements has posed substantial challenges to production manufacturing, particularly in on-site production logistics management. This study aims to address the issues of effective material flow and resource allocation in production logistics management by investigating a method for the rapid and accurate allocation of supply logistics resources. Leveraging the extensive logistics resource allocation data available in the Plan For Every Part system, this research utilizes the Term Frequency-Inverse Document Frequency algorithm to filter out less discriminative data. Additionally, a recommender system based on machine learning, specifically the Recsys (Recommender System) employing similarity algorithms, is employed to construct a logistics resource allocation recommendation model. The effectiveness of this approach is validated through a case study that involves material resource allocation recommendations in a specific remote control production workshop. The validation results indicate that, compared to traditional logistics resource allocation processes, the proposed model optimizes resource allocation recommendations in production logistics, resulting in a significant improvement in material delivery punctuality and overall operational efficiency in enterprises.

Research and development of Lycium barbarum compound beverage and preliminary verification of its efficacy

AbstractLycium barbarum contains a variety of phytochemicals, primarily polysaccharides, and other potent compounds. L. barbarum is a plant that has several uses in contemporary society, including food processing and everyday eating. However, through traditional processing methods the medicinal or edible value of L. barbarum cannot be fully exploited, to further improve the utilisation rate of L. barbarum and enrich the variety of L. barbarum market. The L. barbarum compound beverage, which uses L. barbarum as its primary ingredient, was created through a series of trials, including the creation of tea beverage recipes and research on the most suitable content of stabilisers, flavouring agent formulations and so on. In addition, several validation tests, including those involving hypoglycaemic and lipid-lowering were conducted. The results indicated that 0.1 g mL−1 stabiliser CMC-Na, 0.2 g mL−1 erythritol, 3 g mL−1 citric acid, 8% L. barbarum juice, and 6% chrysanthemum tea cold brew extract were the best combinations for food additive formulations. Additionally, compound beverages have hypoglycemic and lipid-lowering effects. In conclusion, the research and development of L. barbarum compound beverages can not only increase the rate at which L. barbarum is utilised but also offer fresh ideas for the research and development of L. barbarum as they transition from cash crop agricultural products to market-oriented standardised processed products.

A New Multi-Objective Optimization Strategy for Improved C3MR Liquefaction Process

In the traditional C3MR process (T-C3MR), the boiling gas (BOG) output from the last stage of the gas–liquid separator is directly discharged, in which the excellent low-temperature capability is not utilized, and the system efficiency is decreased. In liquefied natural gas (LNG), single-objective optimization methods are commonly used to optimize system parameters, which may result in incomplete system analysis. To solve the above problems, this paper proposes a multi-objective optimization strategy for the improved C3MR process(I-C3MR) based on a new multi-objective optimization algorithm called EHR-GWO-GA. Firstly, the main work proposes an I-C3MR structure. Secondly, an optimization strategy of the I-C3MR with the maximization of liquefaction amount, minimization of unit energy consumption and minimization of exergy loss as objective functions are proposed. Based on the optimization results, the influence of decision variables on liquefaction amount, unit energy consumption and exergy loss are analyzed, and the results show that the decision variables have good adaptability. Finally, a detailed exergy analysis of the equipment used is made, and the results show that the main exergy losses come from the water coolers and compressors, accounting for 32% and 34%, respectively. Compared to the T-C3MR, the improved C3MR based on EHR-GWO-GA(E-C3MR) has an approximate 8% increase in liquefaction amount—a roughly 23% decrease in unit energy consumption and a decrease of nearly 24% in exergy loss.