bluuebunny/crossref_metadata_2025 huggingface dataset:
Establishing Quality Assurance for HIV-1 Rapid Test for Recent Infection in Thailand through the Utilization of Dried Tube Specimens
Authors: Suparak Supaporn , Unpol Petai , Ngueanchanthong Kanokwan , Chisholm Sirilada Pimpa , Jomjunyoung Siriphailin , Thanyacharern Wipawee , Smanthong Nitis , Pinrod Pojaporn , Srithanaviboonchai Kriengkrai , Yingyong Thitipong , Tasaneeyapan Theerawit , Nookhai Somboon , Rojanawiwat Archawin , Northbrook Sanny
Published: June 2024

The present study focuses on establishing the quality assurance of laboratories for recent infections (RTRI) in Thailand. We developed a cold-chain independent method, using fully characterized plasma obtained from the Thai Red Cross Society, and prepared as dried tube specimens (DTS). Twenty microliters of HIV-seronegative, recent, and long-term infected samples were aliquoted into individual tubes and dried at room temperature, 20–30 degrees Celsius, in a biosafety cabinet overnight to ensure optimal preservation. The DTS external quality control and external quality assessment were tested for homogeneity and stability following the ISO/Guide 35 guidelines. The DTS panels were distributed to 48 sites (FY 2022) and 27 sites (FY 2023) across 14 and 9 provinces, respectively, in Thailand. The results from participating laboratories were collected and evaluated for performance. The results were scored, and acceptable performance criteria were defined as the proportion of panels correctly tested, which was set at 100%. The satisfactory performance ranged from 96% to 100% and was not significantly different among the 13 health regions. The developed and implemented DTS panels can be used to monitor the quality of RTRI testing in Thailand.
Modelling Heterogeneous Anomalous Dynamics of Radiation-Induced Double-Strand Breaks in DNA during Non-Homologous End-Joining Pathway
Authors: Korabel Nickolay , Warmenhoven John W. , Henthorn Nicholas T. , Ingram Samuel , Fedotov Sergei , Heaven Charlotte J. , Kirkby Karen J. , Taylor Michael J. , Merchant Michael J.
Published: June 2024

The process of end-joining during nonhomologous repair of DNA double-strand breaks (DSBs) after radiation damage is considered. Experimental evidence has revealed that the dynamics of DSB ends exhibit subdiffusive motion rather than simple diffusion with rare directional movement. Traditional models often overlook the rare long-range directed motion. To address this limitation, we present a heterogeneous anomalous diffusion model consisting of subdiffusive fractional Brownian motion interchanged with short periods of long-range movement. Our model sheds light on the underlying mechanisms of heterogeneous diffusion in DSB repair and could be used to quantify the DSB dynamics on a time scale inaccessible to single particle tracking analysis. The model predicts that the long-range movement of DSB ends is responsible for the misrepair of DSBs in the form of dicentric chromosome lesions.
Curriculum Middle Leader Practices and Teachers Perceptions of Their Effectiveness: A Study in New Zealand Secondary Schools
Authors: Highfield Camilla , Thompson Pauline , Woods Rachel
Published: June 2024

This study reports the quantitative results of middle leaders’ self-reported practices and compares their responses to the perceptions of the teachers who report to them (n = 158). Likert scale questionnaires were used to measure the extent to which middle leaders focused on goal orientation, professional collaboration, effective instructional practices, and supporting teacher development within their department. The analysis provides insight into this phenomenon within six different state-funded secondary schools, with results showing middle leaders almost always rate their practices more effectively than the teachers who report to them. Common areas identified as requiring increased effectiveness were middle leaders’ use of resources to support learning, use of data to support the instructional programme, and identification of effective professional learning opportunities for teachers. Reported levels of effectiveness compared with student academic achievement in the senior secondary school setting align with agreement ratings and the socio-economic status of students who attend the school. This paper highlights the need for the ongoing support of middle leaders to be provided with deliberate support and development for leading teachers.
A Patient-Centered Approach to Communication during Endoscopic Procedures: The Importance of Providing Information to Patients
Authors: Bashkin Osnat , Boltean Rita , Ben-Lulu Revaya , Aharon Mor , Elhayany Ruhama , Yitzhak Avraham , Guterman Revital , Abu-Freha Naim
Published: June 2024

The study aimed to explore patients’ experiences and perceptions throughout the various stages of endoscopic procedures and examine the association between patient-centered communication and the patient’s experience. A total of 191 patients responded to pre- and post-procedure surveys that inquired about fear and pain, patients’ satisfaction regarding the information provided to them, perceptions and experience. Pain was associated with post-procedure fear (r = 0.63, p < 0.01) and negatively associated with reported patient experience at the end of the visit (r = −0.17, p < 0.01). Significant positive associations were found between patient experience and satisfaction from the information provided before (r = 0.47, p < 0.01) and the information provided after the procedure (r = 0.51, p < 0.001). A predictive model found that perceptions toward the physicians, satisfaction from information provided before discharge, and feelings of trust are predictors of the patient experience (F = 44.9, R2 = 0.61, p < 0.001). Patients’ satisfaction with information provided before and after the procedure can positively affect the patients’ experience, leading to a decrease in fear and anxiety and increasing compliance with medical recommendations. Strategies for PCC with endoscopic patients should be developed and designed in a participatory manner, taking into account the various aspects associated with the patient experience.
Enhancing Distribution Grid Efficiency and Congestion Management through Optimal Battery Storage and Power Flow Modeling
Authors: Taltavull-Villalonga Víctor , Bullich-Massagué Eduard , Saldaña-González Antonio E. , Sumper Andreas
Published: June 2024

The significant growth in demand for electricity has led to increasing congestion on distribution networks. The challenge is twofold: it is needed to expand and modernize our grid to meet this increased demand but also to implement smart grid technologies to improve the efficiency and reliability of electricity distribution. In order to mitigate these congestions, novel approaches by using flexibility sources such as battery energy storage can be used. This involves the use of battery storage systems to absorb excess energy at times of low demand and release it at peak times, effectively balancing the load and reducing the stress on the grid. In this paper, two optimal power flow formulations are discussed: the branch flow model (non-convex) and the relaxed bus injection model (convex). These formulations determine the optimal operation of the flexibility sources, i.e., battery energy storage, with the objective of minimizing power losses while avoiding congestions. Furthermore, a comparison of the performance of these two formulations is performed, analyzing the objective function results and the flexibility operation. For this purpose, a real Spanish distribution network with its corresponding load data for seven days has been used.
Artificial Intelligence, Immersive Technologies, and Neurotechnologies in Breathing Interventions for Mental and Emotional Health: A Systematic Review
Authors: Mitsea Eleni , Drigas Athanasios , Skianis Charalabos
Published: June 2024

Breathing is one of the most vital functions for being mentally and emotionally healthy. A growing number of studies confirm that breathing, although unconscious, can be under voluntary control. However, it requires systematic practice to acquire relevant experience and skillfulness to consciously utilize breathing as a tool for self-regulation. After the COVID-19 pandemic, a global discussion has begun about the potential role of emerging technologies in breath-control interventions. Emerging technologies refer to a wide range of advanced technologies that have already entered the race for mental health training. Artificial intelligence, immersive technologies, biofeedback, non-invasive neurofeedback, and other wearable devices provide new, but yet underexplored, opportunities in breathing training. Thus, the current systematic review examines the synergy between emerging technologies and breathing techniques for improving mental and emotional health through the lens of skills development. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology is utilized to respond to the objectives and research questions. The potential benefits, possible risks, ethical concerns, future directions, and implications are also discussed. The results indicated that digitally assisted breathing can improve various aspects of mental health (i.e., attentional control, emotional regulation, mental flexibility, stress management, and self-regulation). A significant finding of this review indicated that the blending of different technologies may maximize training outcomes. Thus, future research should focus on the proper design and evaluation of different digital designs in breathing training to improve health in different populations. This study aspires to provide positive feedback in the discussion about the role of digital technologies in assisting mental and emotional health-promoting interventions among populations with different needs (i.e., employees, students, and people with disabilities).
Improving Training Dataset Balance with ChatGPT Prompt Engineering
Authors: Kochanek Mateusz , Cichecki Igor , Kaszyca Oliwier , Szydło Dominika , Madej Michał , Jędrzejewski Dawid , Kazienko Przemysław , Kocoń Jan
Published: June 2024

The rapid evolution of large language models, in particular OpenAI’s GPT-3.5-turbo and GPT-4, indicates a growing interest in advanced computational methodologies. This paper proposes a novel approach to synthetic data generation and knowledge distillation through prompt engineering. The potential of large language models (LLMs) is used to address the problem of unbalanced training datasets for other machine learning models. This is not only a common issue but also a crucial determinant of the final model quality and performance. Three prompting strategies have been considered: basic, composite, and similarity prompts. Although the initial results do not match the performance of comprehensive datasets, the similarity prompts method exhibits considerable promise, thus outperforming other methods. The investigation of our rebalancing methods opens pathways for future research on leveraging continuously developed LLMs for the enhanced generation of high-quality synthetic data. This could have an impact on many large-scale engineering applications.
Localization of Coordinated Cyber-Physical Attacks in Power Grids Using Moving Target Defense and Machine Learning
Authors: Yu Jian , Li Qiang , Li Lei
Published: June 2024

Coordinated cyber-physical attacks (CCPAs) are dangerously stealthy and have considerable destructive effects against power grids. The problem of stealthy CCPA (SCCPA) localization, specifically identifying disconnected lines in attack, is a nonlinear multi-classification problem. To the best of our knowledge, only one paper has studied the problem; nevertheless, the total number of classifications is not appropriate. In the paper, we propose several methods to solve the problem of SCCPA localization. Firstly, considering the practical constraints and abiding by one of our previous studies, we elaborately determine the total number of classifications and design an approach for generating training and testing datasets. Secondly, we develop two algorithms to solve multiple classifications via the support vector machine (SVM) and random forest (RF), respectively. Similarly, we also present a one-dimensional convolutional neural network (1D-CNN) architecture. Finally, extensive simulations are carried out for IEEE 14-bus, 30-bus, and 118-bus power system, respectively, and we verify the effectiveness of our approaches in solving the problem of SCCPA localization.
An Overview of Electric Vehicle Load Modeling Strategies for Grid Integration Studies
Authors: Huaman-Rivera Anny , Calloquispe-Huallpa Ricardo , Luna Hernandez Adriana C. , Irizarry-Rivera Agustin
Published: June 2024

The adoption of electric vehicles (EVs) has emerged as a solution to reduce greenhouse gas emissions in the transportation sector, which has motivated the implementation of public policies to promote their use in several countries. However, the high adoption of EVs poses challenges for the electricity sector, as it would imply an increase in energy demand and possible impacts on the power quality (PQ) of the power grid. Therefore, it is important to conduct EV integration studies in the power grid to determine the amount that can be incorporated without causing problems and identify the areas of the power sector that will require reinforcements. Accurate EV load patterns are required for this type of study that, through mathematical modeling, reflect both the dynamic behavior and the factors that influence the decision to recharge EVs. This article aims to present an overview of EVs, examine the different factors considered in the literature for modeling EV load patterns, and review modeling methods. EV load modeling methods are classified into deterministic, statistical, and machine learning. The article shows that each modeling method has its advantages, disadvantages, and data requirements, ranging from simple load modeling to more accurate models requiring large datasets.
Analysis of Vulnerabilities in College Web-Based System
Authors: Nam Younsu , Choi Sunoh
Published: June 2024

Web-based systems are used extensively in Korea because web standards have been adapted by the law (e.g., Electronic Government Act). Users can easily access web-based systems if they are connected to the Internet. However, distinguishing between malicious and benign access is very difficult and many potential vulnerabilities exist. In this study, we attempt to leak the information of other users without permission using a non-encrypted API and web source code analysis in a college web-based system. An experiment demonstrates that the information (e.g., other students’ course grades) can be leaked and abnormal data can be embedded in the request. In addition, we discuss methods for preventing such vulnerability attacks.
HR-YOLO: A Multi-Branch Network Model for Helmet Detection Combined with High-Resolution Network and YOLOv5
Authors: Lian Yuanfeng , Li Jing , Dong Shaohua , Li Xingtao
Published: June 2024

Automatic detection of safety helmet wearing is significant in ensuring safe production. However, the accuracy of safety helmet detection can be challenged by various factors, such as complex environments, poor lighting conditions and small-sized targets. This paper presents a novel and efficient deep learning framework named High-Resolution You Only Look Once (HR-YOLO) for safety helmet wearing detection. The proposed framework synthesizes safety helmet wearing information from the features of helmet objects and human pose. HR-YOLO can use features from two branches to make the bounding box of suppression predictions more accurate for small targets. Then, to further improve the iterative efficiency and accuracy of the model, we design an optimized residual network structure by using Optimized Powered Stochastic Gradient Descent (OP-SGD). Moreover, a Laplace-Aware Attention Model (LAAM) is designed to make the YOLOv5 decoder pay more attention to the feature information from human pose and suppress interference from irrelevant features, which enhances network representation. Finally, non-maximum suppression voting (PA-NMS voting) is proposed to improve detection accuracy for occluded targets, using pose information to constrain the confidence of bounding boxes and select optimal bounding boxes through a modified voting process. Experimental results demonstrate that the presented safety helmet detection network outperforms other approaches and has practical value in application scenarios. Compared with the other algorithms, the proposed algorithm improves the precision, recall and mAP by 7.27%, 5.46% and 7.3%, on average, respectively.
GNN-Based Network Traffic Analysis for the Detection of Sequential Attacks in IoT
Authors: Altaf Tanzeela , Wang Xu , Ni Wei , Yu Guangsheng , Liu Ren Ping , Braun Robin
Published: June 2024

This research introduces a novel framework utilizing a sequential gated graph convolutional neural network (GGCN) designed specifically for botnet detection within Internet of Things (IoT) network environments. By capitalizing on the strengths of graph neural networks (GNNs) to represent network traffic as complex graph structures, our approach adeptly handles the temporal dynamics inherent to botnet attacks. Key to our approach is the development of a time-stamped multi-edge graph structure that uncovers subtle temporal patterns and hidden relationships in network flows, critical for recognizing botnet behaviors. Moreover, our sequential graph learning framework incorporates time-sequenced edges and multi-edged structures into a two-layered gated graph model, which is optimized with specialized message-passing layers and aggregation functions to address the challenges of time-series traffic data effectively. Our comparative analysis with the state of the art reveals that our sequential gated graph convolutional neural network achieves substantial improvements in detecting IoT botnets. The proposed GGCN model consistently outperforms the conventional model, achieving improvements in accuracy ranging from marginal to substantial—0.01% for BoT IoT and up to 25% for Mirai. Moreover, our empirical analysis underscores the GGCN’s enhanced capabilities, particularly in binary classification tasks, on imbalanced datasets. These findings highlight the model’s ability to effectively navigate and manage the varying complexity and characteristics of IoT security threats across different datasets.
P2P Federated Learning Based on Node Segmentation with Privacy Protection for IoV
Authors: Zhao Jia , Guo Yating , Yang Bokai , Wang Yanchun
Published: June 2024

The current usage of federated learning in applications relies on the existence of servers. To address the inability to conduct federated learning for IoV (Internet of Vehicles) applications in serverless areas, a P2P (peer-to-peer) architecture for federated learning is proposed in this paper. Following node segmentation based on limited subgraph diameters, an edge aggregation mode is employed to propagate models inwardly, and a mode for propagating the model inward to the C-node (center node) while aggregating is proposed. Simultaneously, a personalized differential privacy scheme was designed under this architecture. Through experimentation and verification, the approach proposed in this paper demonstrates the combination of both security and usability.
Analysis of Potential Use of Freezing Boreholes Drilled for an Underground Mine Shaft as Borehole Heat Exchangers for Heat and/or Cooling Applications
Authors: Sliwa Tomasz , Jaszczur Marek , Drosik Jakub , Assadi Mohsen , Kalantar Adib
Published: June 2024

Borehole engineering encompasses the part of mining that involves the process of drilling boreholes and their utilization (e.g., for research, exploration, exploitation, and injection purposes). According to legal regulations, mining pits must be closed after their use, and this applies to pits in the form of boreholes as well. The Laboratory of Geoenergetics at AGH University of Krakow is involved in adapting old, exploited and already closed boreholes for energetic purposes. This includes geothermal applications, as well as energy storage in rock formations and boreholes. Geoenergetics is a relatively new concept that combines geothermal energy with energy storage in rock formations (including boreholes). One type of analysed borehole is a freezing borehole. They are used, for example, in drilling mining shafts that are in the vicinity of aquifers and are drilled using the rotary drilling method with a reverse circulation of drilling mud, or in peat bogs. For borehole heat exchangers based on freezing boreholes for long-term mathematical modelling, several heating scenarios were considered with several thermal loads. The maximum average power obtained after one year of usage of four boreholes with variable temperatures was 11 kW. With the usage of 10 boreholes the power reached over 27 kW. The heat-carrying temperature was assumed to be 22 °C during early summer (June and July) and 2 °C during the rest of the year. When considering stable exploitation during a 10-year period with four boreholes with the same temperatures, a heating power of over 12 kW was obtained, as well as a power of over 28 kW when considering using 10 boreholes. The maximum amount of heat obtained during the 10-year period using 10 boreholes was over 8.8 thousand GJ. Once they have fulfilled their function, these boreholes lose their technological significance. In the paper, the concept is outlined, and the results of the analysis are described using the numerical program BoHEx.
Cost-Effective Target Capacity Assessment in the Energy Transition: The Italian Methodology
Authors: Carlini Enrico Maria , Gadaleta Corrado , Migliori Michela , Ferretti Francesca , Vailati Riccardo , Venturini Andrea , Puglisi Cinzia
Published: June 2024

Long-term transmission expansion planning has to face the energy transition in a restructured electricity market environment. Increased transmission capacity within and between Member States is likely to play an essential role in maintaining the secure and economic operation of the whole European power system and ensuring the integration of growing renewable generation. This paper proposes a novel iterative methodology aimed at assessing an optimal level of interconnection between relevant bidding zones, simultaneously investigating different potential alternatives. Starting from a reference grid, a multi-criteria analysis is adopted to select the additional transmission capacities to be tested in each iteration via network and market simulations in order to confirm that transmission expansion benefits outweigh the estimated realization costs. The proposed approach is applied to the Italian case in two contrasting energy scenarios for the mid-term 2030 and very-long-term 2040 horizons: different development strategies are derived, and the least regret criterion is applied to define the most cost-effective as the target development strategy for the Transmission System Operator (TSO). Furthermore, sensitivity analyses on relevant input data variation are performed to test the robustness of the results obtained.
Skin and Proximity Effect Calculation of a System of Rectangular Conductors Using the Proper Generalized Decomposition Technique
Authors: Tabei Barzan , Gole Aniruddha M. , Kordi Behzad
Published: June 2024

This paper presents the application of a numerical approach known as proper generalized decomposition (PGD) to calculate the per-unit length (PUL) ac resistance of rectangular conductors. PGD has been successfully used in areas such as fluid mechanics and biomedical applications. It solves a partial differential equation (PDE) by decomposing the answer into a set of unknown one-dimensional (1D) functions in an iterative approach until it reaches a predetermined convergence. In this paper, a frequency-dependent meshing scheme is employed in the PGD technique at each frequency to properly take skin and proximity effects into account. One of the main advantages of PGD over traditional numerical approaches such as finite element or finite difference methods is that it confines the answers within a set of one-dimensional functions, which require fewer computational resources. Different examples of single and multiple rectangular conductors are considered to study skin and proximity effects. The PGD results are compared with those obtained using a commercial finite element method (FEM) software to verify the accuracy of the model. This approach can be used in applications such as white box modeling of transformers, EMC analysis, hairpin winding design used in electric vehicles, and busbar simulation.
Modeling Pressure Gradient of Gas–Oil–Water Three-Phase Flow in Horizontal Pipes Downstream of Restrictions
Authors: Zhou Denghong , Fan Yilin
Published: June 2024

Gas–oil–water three-phase slug flows in pipes commonly exist in the oil and gas industry as oil fields are becoming mature and water production is becoming inevitable. Although studies on multiphase flows in pipes have been ongoing for decades, most previous research has focused on gas–liquid or oil–water two-phase flows, with limited studies on gas–liquid–liquid flows. This leads to limited modeling studies on gas–liquid–liquid flows. One factor contributing to the complexity of the gas–liquid–liquid flow is the mixing between the oil and water phases, which have closer fluid properties and low interfacial tension. Restrictions or piping components play a crucial role in altering phase mixing. Unfortunately, modeling studies that consider the effects of these restrictions are limited due to the scarcity of experimental research. To address this gap, we conducted experimental studies on a gas–liquid–liquid flow downstream of a restriction and developed a new mechanistic modeling approach to predict the pressure gradient. Our model focuses on the flow pattern where the oil and water phases are partially mixed. This work emphasizes the modeling approach. The model evaluation results show that the model outperforms other existing models, with an average absolute relative error of 6.71%. Additionally, the parametric study shows that the new modeling approach effectively captures the effects of restriction size, water cut, and gas and liquid flow rates on the three-phase slug flow pressure gradient in horizontal pipes. Most previous slug flow modeling work assumes either a stratified flow or fully dispersed flow between the oil and water phases. This work provides a novel perspective in modeling a three-phase slug flow in which the oil and water phases are partially mixed. In addition, this novel approach to modeling the restriction effects on the pressure gradient paves the way for future modeling for different types of piping components or restrictions.
Insect Protein as a Component of Meat Analogue Burger
Authors: Krawczyk Anna , Fernández-López Juana , Zimoch-Korzycka Anna
Published: June 2024

Researchers are exploring solutions to meet the growing demand for protein due to the expected increase in global population by 2050. Interest in alternative protein sources like insects has risen, driven by concerns about environmental impact and the need for sustainable food production. This study aimed to develop and evaluate the physicochemical properties of soy-protein-based burgers enriched with insect protein from Alphitobius diaperinus. Three formulations were developed: a control (B0) and burgers with 5% (B5) and 10% (B10) insect protein—Whole Buffalo Powder (WBP). The results showed that adding insect protein decreased the burger analogue’s pH. A clear trend was observed of increasing total lipids and saturated fatty acids (SFA) and decreasing monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) as the WBP concentration increased from 0% to 10%. No significant differences with increasing WBP concentration in the protein content of the burger analogue, as well as the cooking yield, were noted. The WBP addition had a notable effect on the color change, especially a decrease in brightness (L*). It was shown that as the WBP concentration increased, there were no significant differences in the texture profile of the burger analogues. The formulation with 5% WBP concentration was the most acceptable in sensory analysis.
Exploring Red Wine Aging: Comparative Analysis of Cellar and Sea Underwater Aging on Chemical Composition and Quality
Authors: Mercanti Nicola , Pieracci Ylenia , Macaluso Monica , Fedel Massimo , Brazzarola Francesco , Palla Fabrizio , Verdini Piero Giorgio , Zinnai Angela
Published: June 2024

The aging process of wine is influenced by various factors, including the presence of oxygen, the temperature, and the storage conditions. While oxygen can have both positive and negative effects on wine quality, temperature fluctuations during storage can impact its chemical composition. This study has investigated the aging of Merlot and Sangiovese wines under traditional cellar conditions and underwater, exploring the influence of storage parameters on their chemical evolution. Analyzing parameters such as temperature, pressure, and chemical composition, the research revealed subtle but significant changes in the wines over time. Both wines showed a gradual reduction in total phenols, anthocyanins, non-flavonoid compounds, and total sulfur dioxide, irrespective of the storage conditions. Preliminary findings suggested that aging wine underwater does not induce significant alterations in its fundamental characteristics compared to traditional cellar aging. These results contribute to a deeper understanding of wine aging processes and highlight the importance of storage conditions in preserving wine quality. Further research is needed to fully elucidate the complexities of underwater aging and its broader implications for wine production.
Liposomes as Carriers of Bioactive Compounds in Human Nutrition
Authors: Rudzińska Magdalena , Grygier Anna , Knight Geoffrey , Kmiecik Dominik
Published: June 2024

This article provides an overview of the literature data on the role of liposomal structures and encapsulated substances in food technology and human nutrition. The paper briefly describes how liposomes are created and how they encapsulate food ingredients, which can either be individual compounds or plant extracts. Another very interesting application of liposomes is their use as antimicrobial carriers to protect food products from spoilage during storage. The encapsulation of food ingredients in liposomes can increase their bioavailability, which is particularly important for compounds with health-promoting properties but low bioavailability. Particular attention was paid to compounds such as phytosterols, which lower blood cholesterol levels but have very low absorption in the human body. In addition, consumer expectations and regulations for liposomes in food are discussed. To date, no in vivo human studies have been conducted to indicate which encapsulation methods give the best results for gastrointestinal effects and which food-added substances are most stable during food storage and processing. The paper identifies further lines of research that are needed before liposomes can be introduced into food.
Can Non-farm Employment Improve Dietary Diversity of Left-Behind Family Members in Rural China?
Authors: Zhang Yonghu , Zhang Yifeng , Wang Tingjin
Published: June 2024

Rural residents in China are still at risk of malnutrition, and increasing dietary diversity is crucial to improving their health. This study empirically analyzed the impact of non-farm employment on the dietary diversity of rural left-behind family members based on the China Land Economy Survey (CLES) 2020–2021 panel data at the farm and village levels. Dietary diversity was measured using the dietary diversity score (DDS) and the Chinese Food Guide Pagoda Score (CFGPS). The empirical results show that non-farm employment significantly enhances the dietary diversity of rural left-behind household members, including animal food diversity and plant food diversity. This result verifies the altruism phenomenon of non-farm employment in family diet. Mechanism analysis shows that non-farm employment enhances the dietary diversity of rural left-behind family members by increasing the level of family income, Internet accessibility, and family education. Heterogeneity analysis shows that non-farm employment does not enhance the dietary diversity of rural empty nesters and even has a negative impact. This reminds us that the nutritional health of rural empty nesters needs attention in the context of rapid urbanization and aging.
Selenium-Chelating Peptide Derived from Wheat Gluten: In Vitro Functional Properties
Authors: Hou Yinchen , Chen Xinyang , Zhang Mingyi , Yang Shengru , Liao Aimei , Pan Long , Wang Zhen , Shen Xiaolin , Yuan Xiaoqing , Huang Jihong
Published: June 2024

The efficacy of selenium-chelating polypeptides derived from wheat protein hydrolysate (WPH-Se) includes enhancing antioxidant capacity, increasing bioavailability, promoting nutrient absorption, and improving overall health. This study aimed to enhance the bioavailability and functional benefits of exogenous selenium by chelating with wheat gluten protein peptides, thereby creating bioactive peptides with potentially higher antioxidant capabilities. In this study, WPH-Se was prepared with wheat peptide and selenium at a mass ratio of 2:1, under a reaction system at pH 8.0 and 80 °C. The in vitro antioxidant activity of WPH-Se was evaluated by determining the DPPH, OH, and ABTS radical scavenging rate and reducing capacity under different conditions, and the composition of free amino acids and bioavailability were also investigated at various digestion stages. The results showed that WPH-Se possessed significant antioxidant activities under different conditions, and DPPH, OH, and ABTS radical scavenging rates and reducing capacity remained high at different temperatures and pH values. During gastrointestinal digestion in vitro, both the individual digestate and the final digestate maintained high DPPH, OH, and ABTS radical scavenging rates and reducing capacity, indicating that WPH-Se was able to withstand gastrointestinal digestion and exert antioxidant effects. Post-digestion, there was a marked elevation in tryptophan, cysteine, and essential amino acids, along with the maintenance of high selenium content in the gastrointestinal tract. These findings indicate that WPH-Se, with its enhanced selenium and amino acid profile, serves as a promising ingredient for dietary selenium and antioxidant supplementation, potentially enhancing the nutritional value and functional benefits of wheat gluten peptides.
The Impact of Climatic Warming on Earlier Wine-Grape Ripening in Northeastern Slovenia
Authors: Vršič Stanko , Pulko Borut , Vodovnik-Plevnik Tadeja , Perko Andrej
Published: June 2024

In this study, the development trends of bioclimatic parameters recorded at the Maribor and Murska Sobota climate stations from 1952 to 2022 and the dynamics of grape ripening in early-, medium-, and late-ripening grape varieties in the Podravje wine-growing region in Slovenia (north-eastern Slovenia) from 1980 to 2022 were investigated. Based on the data on soluble solids content, total acidity, and the recommended harvest date per year (until the technological ripeness of the grapes; 76°Oe), trends for shortening the growing period of the vines were calculated. Temperature changes have been more pronounced since 1980. The number of so-called hot days (with a maximum of T > 30 °C) has increased the most, which has the greatest impact on other bioclimatic parameters, e.g., the average temperature and growing degree days (GDDs) and the Huglin index (HI). For the period of 1980 to 2022, the trends were 0.44 °C (Murska Sobota) and 0.51 °C (Maribor) per decade, respectively. The trends were more pronounced for the average temperature in the period of May–June (TMJ). After 1980, the HI increased by about 10 units per year. As a result of the climate warming, grapes in north-eastern Slovenia ripened 26 (‘Sauvignon Blanc’) to 35 (‘Welschriesling’) days earlier. The trends showed a decrease in total acidity, which can be attributed to the higher temperatures during the growing season period, especially during the ripening period of the grapes (véraison). After 2010, the average temperatures during the growing season (1 April to 31 October) in Podravje were 1.6 °C higher than in the 1980s. In line with the earlier ripening of the grapes, the actual average temperature from 1 April to the harvest date was a further 1.0 °C higher. The higher temperatures in the late-ripening varieties ‘Riesling’ and ‘Furmint’ had a positive effect on the lower total acidity. Total annual precipitation and precipitation in the growing season for the period 1980 to 2022 in the Maribor area show decreasing trends of 6 mm/m2 (p = 0.001) and 4 mm/m2 (p = 0.012), respectively. In the eastern sub-wine-growing region of Podravje (Murska Sobota), the trends in precipitation were not significant.
Comparative Cell Wall Polysaccharide Analyses and Transcriptome Profiling during Fruit Ripening Reveal the Molecular Basis of Mealiness in Peach
Authors: Wang Hongmei , Li Ang , Zeng Wenfang , Yao Zhenyu , Badrunnesa Akhi , Meng Junren , Miao Yule , Niu Liang , Pan Lei , Cui Guochao , Duan Wenyi , Sun Shihang , Li Guohuai , Wang Zhiqiang
Published: June 2024

Mealy peaches are dry and flavorless, which reduces their consumer acceptance. A deeper understanding of the mechanism underlying mealiness is crucial to enhancing peach fruit quality. In this study, comparative profiling was conducted on CP13, CP14, CM, and RM peaches. Sensory evaluation indicated that CP13 and CM are non-mealy clingstone and freestone peaches, respectively, and CP14 and RM are mealy freestone peaches. Both CP13 and CP14, identified as stony hard (SH) peaches, exhibited minimal ethylene release, whereas CM and RM, identified as melting flesh (MF) peaches, released high amounts of ethylene during the ripening process. Scanning electron microscopy (SEM) microstructure observation indicated that cells in the flesh tissue of mealy peaches, CP14 (SH) and RM (MF), were intact and separated, with large intercellular spaces and irregular arrangements. The main factor that promotes mealiness is differences in pectin metabolism, which impact cell wall composition. The fluctuations in polygalacturonase (PG) and pectin methylesterase (PME) activity between mealy and non-mealy peaches were the main factor contributing to mealiness. However, the changes in cell wall metabolism that caused these fluctuations did not have a clear direction. Using transcriptome analysis and weighted gene co-expression network analysis (WGCNA), we were able to identify forty differentially expressed genes (DEGs) that are associated with mealy patterns. Among these DEGs, genes encoding PG were significantly upregulated in mealy peaches (CP14 and RM) compared to non-mealy peaches (CP13 and CM). PpPG1 was the main effector gene for mealiness, while PpPG2, PpEGase2, PpEXP1, PpEXP3, PpAGP2, PpIAA4, and PpABA2 were identified as candidate genes regulating peach mealiness. These findings provide a solid experimental basis for understanding the textual distinctions between mealy and non-mealy peaches.
Comparative Analysis of Transcriptomes to Identify Genes during Bud Dormancy of Pyrus pyrifolia ‘Huanghua’
Authors: Wang Huiquan , Liu Chunying , Ye Qinghua , Shen Yunyu , Wu Shaohua , Lin Lizhong
Published: June 2024

The study of pear dormancy mechanisms is currently a major research area in pear production and has high economic significance for agricultural production. We selected the southern sand pear cultivar Pyrus pyrifolia ‘Huanghua’ as the test material to study the pear dormancy process through microscopic observation of pear flower buds. The endodormancy period is abbreviated as D_bud. Similarly, the endodormancy release initiation period and the ecodormancy period are referred to as DB_bud and G_bud, respectively. Meanwhile, RNA sequencing was used to obtain the gene expression profile of Pyrus pyrifolia ‘Huanghua’ flower buds. The RNA sequencing results indicated that there were 224 differentially expressed genes (DEGs) in endodormancy (D) vs. endodormancy release initiation period (DB), while 975 were identified between endodormancy and ecodormancy (G). Finally, a total of 868 DEGs were found in the DB vs. G comparison. The expression levels of the genes Pbr009498.1 (LAX1-1), Pbr012348.1 (LAX1-2), Pbr021158.1 (GH35), and Pbr031621.1 (LAX2) encoding IAA were significantly higher during the DB_bud than during the D_bud. The expression level of Pbr025864.2 (IAA13) during the D_bud was significantly higher than the DB_bud and G_bud. The Pbr041942.1 (GID1B) gene also showed a significant increase during ecodormancy. Taken together, these results suggest that these genes, annotated as LAX1, GH35, LAX2, IAA13, and GID1C, are involved in endodormancy maintenance and in the transition from endodormancy to ecodormancy in Pyrus pyrifolia ‘Huanghua’.
Artificial Intelligence-Driven Innovations in Hydrogen Safety
Authors: Patil Ravindra R. , Calay Rajnish Kaur , Mustafa Mohamad Y. , Thakur Somil
Published: June 2024

This review explores recent advancements in hydrogen gas (H2) safety through the lens of artificial intelligence (AI) techniques. As hydrogen gains prominence as a clean energy source, ensuring its safe handling becomes paramount. The paper critically evaluates the implementation of AI methodologies, including artificial neural networks (ANN), machine learning algorithms, computer vision (CV), and data fusion techniques, in enhancing hydrogen safety measures. By examining the integration of wireless sensor networks and AI for real-time monitoring and leveraging CV for interpreting visual indicators related to hydrogen leakage issues, this review highlights the transformative potential of AI in revolutionizing safety frameworks. Moreover, it addresses key challenges such as the scarcity of standardized datasets, the optimization of AI models for diverse environmental conditions, etc., while also identifying opportunities for further research and development. This review foresees faster response times, reduced false alarms, and overall improved safety for hydrogen-related applications. This paper serves as a valuable resource for researchers, engineers, and practitioners seeking to leverage state-of-the-art AI technologies for enhanced hydrogen safety systems.
Proton-Coupled Electron Transfer and Hydrogen Tunneling in Olive Oil Phenol Reactions
Authors: Torić Jelena , Karković Marković Ana , Mustać Stipe , Pulitika Anamarija , Jakobušić Brala Cvijeta , Pilepić Viktor
Published: June 2024

Olive oil phenols are recognized as molecules with numerous positive health effects, many of which rely on their antioxidative activity, i.e., the ability to transfer hydrogen to radicals. Proton-coupled electron transfer reactions and hydrogen tunneling are ubiquitous in biological systems. Reactions of olive oil phenols, hydroxytyrosol, tyrosol, oleuropein, oleacein, oleocanthal, homovanillyl alcohol, vanillin, and a few phenolic acids with a DPPH• (2,2-diphenyl-1-picrylhydrazyl) radical in a 1,4-dioxane:water = 95:5 or 99:1 v/v solvent mixture were studied through an experimental kinetic analysis and computational chemistry calculations. The highest rate constants corresponding to the highest antioxidative activity are obtained for the ortho-diphenols hydroxytyrosol, oleuropein, and oleacein. The experimentally determined kinetic isotope effects (KIEs) for hydroxytyrosol, homovanillyl alcohol, and caffeic acid reactions are 16.0, 15.4, and 16.7, respectively. Based on these KIEs, thermodynamic activation parameters, and an intrinsic bond orbital (IBO) analysis along the IRC path calculations, we propose a proton-coupled electron transfer mechanism. The average local ionization energy and electron donor Fukui function obtained for the phenolic compounds show that the most reactive electron-donating sites are associated with π electrons above and below the aromatic ring, in support of the IBO analysis and proposed PCET reaction mechanism. Large KIEs and isotopic values of Arrhenius pre-exponential factor AH/AD determined for the hydroxytyrosol, homovanillyl alcohol, and caffeic acid reactions of 0.6, 1.3, and 0.3, respectively, reveal the involvement of hydrogen tunneling in the process.
Genetic Profiling of Sebaceous Carcinoma Arising from an Ovarian Mature Teratoma: A Case Report
Authors: Zaitsu Sumika , Aoyagi Yoko , Nishida Haruto , Nakamura Kohei , Yano Mitsutake , Kobayashi Eiji
Published: June 2024

Ovarian mature teratomas (OMTs) originate from post-meiotic germ cells. Malignant transformation occurs in approximately 1–2% of OMTs; however, sebaceous carcinoma arising from OMTs is rare. This is the first report of a detailed genomic analysis of sebaceous carcinoma arising from an OMT. A 36-year-old woman underwent evaluation for abdominal tumors and subsequent hysterectomy and salpingo-oophorectomy. Pathologically, a diagnosis of stage IA sebaceous carcinoma arising from an OMT was established. Eight months post-surgery, the patient was alive without recurrence. Immunohistochemically, the tumor was negative for mismatch repair proteins. A nonsense mutation in TP53 (p.R306*) and a deletion in PIK3R1 were identified. Single nucleotide polymorphisms across all chromosomes displayed a high degree of homozygosity, suggestive of uniparental disomy. Herein, the OMT resulting from the endoreduplication of oocytes underwent a malignant transformation to sebaceous carcinoma via TP53 as an early event and PIK3R1 as a late event.
Impact of Phosphorylation at Various Sites on the Active Pocket of Human Ferrochelatase: Insights from Molecular Dynamics Simulations
Authors: Guo Mingshan , Lin Yuhong , Obi Chibuike David , Zhao Peng , Dailey Harry A. , Medlock Amy E. , Shen Yong
Published: June 2024

Ferrochelatase (FECH) is the terminal enzyme in human heme biosynthesis, catalyzing the insertion of ferrous iron into protoporphyrin IX (PPIX) to form protoheme IX (Heme). Phosphorylation increases the activity of FECH, and it has been confirmed that the activity of FECH phosphorylated at T116 increases. However, it remains unclear whether the T116 site and other potential phosphorylation modification sites collaboratively regulate the activity of FECH. In this study, we identified a new phosphorylation site, T218, and explored the allosteric effects of unphosphorylated (UP), PT116, PT218, and PT116 + PT218 states on FECH in the presence and absence of substrates (PPIX and Heme) using molecular dynamics (MD) simulations. Binding free energies were evaluated with the MM/PBSA method. Our findings indicate that the PT116 + PT218 state exhibits the lowest binding free energy with PPIX, suggesting the strongest binding affinity. Additionally, this state showed a higher binding free energy with Heme compared to UP, which facilitates Heme release. Moreover, employing multiple analysis methods, including free energy landscape (FEL), principal component analysis (PCA), dynamic cross-correlation matrix (DCCM), and hydrogen bond interaction analysis, we demonstrated that phosphorylation significantly affects the dynamic behavior and binding patterns of substrates to FECH. Insights from this study provide valuable theoretical guidance for treating conditions related to disrupted heme metabolism, such as various porphyrias and iron-related disorders.
Radiation Damage in Biomolecules and Cells 3.0
Authors: Carante Mario P. , Ramos Ricardo L. , Ballarini Francesca
Published: June 2024

Ionizing radiation is widely used in medicine, not only as a diagnostic tool but also as a therapeutic agent, since about half of cancer patients are treated with ionizing radiation, while most of them are irradiated with X-rays [...]
Modern Strategies for Diagnosis and Treatment of Parasitic Diseases
Authors: Rolbiecki Leszek , Izdebska Joanna N.
Published: June 2024

Parasites are very widely distributed in the environment and form complex relationships with their hosts, forming host–parasite systems [...]