bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of a Vendor-Agnostic Deep Learning Model for Noise Reduction and Image Quality Improvement in Dental CBCT
Authors: Kazimierczak Wojciech , Wajer Róża , Komisarek Oskar , Dyszkiewicz-Konwińska Marta , Wajer Adrian , Kazimierczak Natalia , Janiszewska-Olszowska Joanna , Serafin Zbigniew
Published: October 2024

Background/Objectives: To assess the impact of a vendor-agnostic deep learning model (DLM) on image quality parameters and noise reduction in dental cone-beam computed tomography (CBCT) reconstructions. Methods: This retrospective study was conducted on CBCT scans of 93 patients (41 males and 52 females, mean age 41.2 years, SD 15.8 years) from a single center using the inclusion criteria of standard radiation dose protocol images. Objective and subjective image quality was assessed in three predefined landmarks through contrast-to-noise ratio (CNR) measurements and visual assessment using a 5-point scale by three experienced readers. The inter-reader reliability and repeatability were calculated. Results: Eighty patients (30 males and 50 females; mean age 41.5 years, SD 15.94 years) were included in this study. The CNR in DLM reconstructions was significantly greater than in native reconstructions, and the mean CNR in regions of interest 1-3 (ROI1-3) in DLM images was 11.12 ± 9.29, while in the case of native reconstructions, it was 7.64 ± 4.33 (p < 0.001). The noise level in native reconstructions was significantly higher than in the DLM reconstructions, and the mean noise level in ROI1-3 in native images was 45.83 ± 25.89, while in the case of DLM reconstructions, it was 35.61 ± 24.28 (p < 0.05). Subjective image quality assessment revealed no statistically significant differences between native and DLM reconstructions. Conclusions: The use of deep learning-based image reconstruction algorithms for CBCT imaging of the oral cavity can improve image quality by enhancing the CNR and lowering the noise.
Saturated Fats: Time to Assess Their Beneficial Role in a Healthful Diet
Authors: Lawrence Glen D.
Published: October 2024

Saturated fats are widely seen as undesirable components of a healthy diet, as a result of their illusory association with elevated serum cholesterol. The regulation of serum cholesterol is now better understood and a lack of polyunsaturated fatty acids, rather than an abundance of saturated fatty acids, is responsible. Palmitic acid was shown to incite inflammation at unnaturally high concentrations in tissue culture, but later was found to play an auxiliary role as a precursor to ceramide biosynthesis and possibly in the palmitoylation of membrane receptors involved in the initiation of inflammation. Studies of arthritic inflammation in lab animals showed that dietary saturated fats are anti-inflammatory, whereas polyunsaturated oils are pro-inflammatory. Inflammation plays a role in numerous metabolic diseases, including insulin resistance, fatty liver disease and metabolic syndrome, among others. Fat, as triglycerides in adipose tissue, is an efficient way for living organisms to store energy and reduce the toxicity of other macronutrients. Macronutrients, such as excess carbohydrates and polyunsaturated fatty acids, are converted to saturated and monounsaturated fatty acids for storage as triglycerides in adipose tissue. Fatty acids are released from adipose tissue during fasting and as a result of some metabolic disorders, where elevated levels of nonesterified fatty acids in blood can lead to hepatic lipid accumulation, inflammation and insulin resistance. Although most serum nonesterified fatty acids may be saturated fatty acids, they are not necessarily derived from the diet. This paper will attempt to clarify the role of saturated fatty acids, and palmitic acid in particular, with regard to certain adverse health conditions.
Biogenesis and Regulation of the Freeze–Thaw Responsive microRNA Fingerprint in Hepatic Tissue of Rana sylvatica
Authors: Hadj-Moussa Hanane , Ingelson-Filpula W. Aline , Storey Kenneth B.
Published: October 2024

Background: Freeze-tolerant animals undergo significant physiological and biochemical changes to overcome challenges associated with prolonged whole-body freezing. In wood frog Rana sylvatica (now Lithobates sylvaticus), up to 65% of total body water freezes in extracellular ice masses and, during this state of suspended animation, it is completely immobile and displays no detectable brain, heart, or respirometry activity. To survive such extensive freezing, frogs integrate various regulatory mechanisms to ensure quick and smooth transitions into or out of this hypometabolic state. One such rapid and reversible regulatory molecule capable of coordinating many aspects of biological functions is microRNA. Herein, we present a large-scale analysis of the biogenesis and regulation of microRNAs in wood frog liver over the course of a freeze–thaw cycle (control, 24 h frozen, and 8 h thawed). Methods/Results: Immunoblotting of key microRNA biogenesis factors showed an upregulation and enhancement of microRNA processing capacity during freezing and thawing. This was followed with RT-qPCR analysis of 109 microRNA species, of which 20 were significantly differentially expressed during freezing and thawing, with the majority being upregulated. Downstream bioinformatics analysis of miRNA/mRNA targeting coupled with in silico protein–protein interactions and functional clustering of biological processes suggested that these microRNAs were suppressing pro-growth functions, including DNA replication, mRNA processing and splicing, protein translation and turnover, and carbohydrate metabolism. Conclusions: Our findings suggest that this enhanced miRNA maturation capacity might be one key factor in the vital hepatic miRNA-mediated suppression of energy-expensive processes needed for long-term survival in a frozen state.
A Review on Deep Learning for UAV Absolute Visual Localization
Authors: Couturier Andy , Akhloufi Moulay A.
Published: October 2024

In the past few years, the use of Unmanned Aerial Vehicles (UAVs) has expanded and now reached mainstream levels for applications such as infrastructure inspection, agriculture, transport, security, entertainment, real estate, environmental conservation, search and rescue, and even insurance. This surge in adoption can be attributed to the UAV ecosystem’s maturation, which has not only made these devices more accessible and cost effective but has also significantly enhanced their operational capabilities in terms of flight duration and embedded computing power. In conjunction with these developments, the research on Absolute Visual Localization (AVL) has seen a resurgence driven by the introduction of deep learning to the field. These new approaches have significantly improved localization solutions in comparison to the previous generation of approaches based on traditional computer vision feature extractors. This paper conducts an extensive review of the literature on deep learning-based methods for UAV AVL, covering significant advancements since 2019. It retraces key developments that have led to the rise in learning-based approaches and provides an in-depth analysis of related localization sources such as Inertial Measurement Units (IMUs) and Global Navigation Satellite Systems (GNSSs), highlighting their limitations and advantages for more effective integration with AVL. The paper concludes with an analysis of current challenges and proposes future research directions to guide further work in the field.
Expenditure Rules: Limiting the Level or the Variation of Public Expenditure?
Authors: Menguy Séverine
Published: October 2024

The main goal of the first-generation expenditure rules was to ensure fiscal discipline: preserving a sound fiscal framework and public debt sustainability. Regarding this goal, analytically as well as empirically, limiting the share of public expenditure in GDP would be more appropriate in case of weak potential economic growth or if the public expenditure-to-GDP ratio is high. On the contrary, limiting the variation of public expenditure would be more appropriate for countries with high potential economic growth or with a weak public expenditure-to-GDP ratio. The second goal of expenditure rules is to contribute to sustaining economic activity. Regarding this goal, limiting the level of public expenditure appears as more favorable than limiting the variation of public expenditure. Indeed, a rule in terms of variation could hamper economic growth, especially for countries with a high public expenditure-to-GDP ratio.
Instructors’ Perceptions of the Use of Learning Analytics for Data-Driven Decision Making
Authors: Hershkovitz Arnon , Ambrose G. Alex , Soffer Tal
Published: October 2024

In recent years, much effort has been put into developing dedicated dashboards for instructors, in which data about students’ activity are presented. However, in many cases, such endeavors take a top-down approach and do not involve instructors in the design process. In this paper, we present a study of instructors and teaching assistants in a research university in Israel (N = 253) who responded to an online questionnaire regarding their perceptions of data on students’ activity on course websites. Specifically, they were asked about the types of data they were most interested in, the aspects of student learning that they would consider important, and the actions they would take upon viewing the data. Overall, we found that participants’ scores were medium-high (2.5–3.5 on a 5-point Likert scale), with scores being higher for women compared with men and positively correlated with experience with Moodle. An overarching theme arises from our analyses of instructors’ interests and intentions, which portrays their idea of teaching as somewhat traditional and instructor-centered; however, their declared actions make it clear that they are willing to make some desirable changes to the benefits of students. Finally, we found that instructors’ perceptions of data use and data importance are positive predictors of taking action upon viewing student data.
Transmit Power Optimization in Multihop Amplify-and-Forward Relay Systems with Simultaneous Wireless Information and Power Transfer
Authors: Kim Kunju , Asiedu Derek Kwaku Pobi , Anokye Prince , Kim Eunkyung , Lee Kyoung-Jae
Published: October 2024

In this paper, we study a multi-hop amplify-and-forward (AF) simultaneous wireless information and power transmission (SWIPT) relay system. Each relay node harvests power using a power split (PS) method from a portion of the received signal, amplifies the remaining received signal, and passes it to the next relay. Based on this system model and signal flow, we derived and solved the convex power minimization problem with the optimal PS ratio. In this case, it was found that using the optimal PS ratio consumed a lower amount of power than when using a fixed PS ratio (0.5). We then investigated the impact of processing cost on the AF-SWIPT system using decoding and forwarding SWIPT as benchmarks, and found that AF-SWIPT was superior.
Optimization of Hybrid Energy Systems Based on MPC-LSTM-KAN: A Case Study of a High-Altitude Wind Energy Work Umbrella Control System
Authors: Gong Shuoqi , Chen Wenbo , Jing Xuedong , Wang Chun , Pan Kangyi , Cai Hongjun
Published: October 2024

This paper presents an optimization method for hybrid energy systems based on Model Predictive Control (MPC), Long Short-Term Memory (LSTM) networks, and Kolmogorov–Arnold Networks (KANs). The proposed method is applied to a high-altitude wind energy work umbrella control system, where it aims to enhance the stability and efficiency of energy utilization. The work umbrella system integrates wind and solar energy sources, with energy stored in a battery and used to control the umbrella’s operations. The MPC framework is employed to optimize control actions by solving a finite-horizon optimization problem, ensuring the battery State of Charge (SOC) remains within an optimal range. The LSTM network provides accurate predictions of environmental conditions, including wind speed and solar irradiance, which are essential for MPC’s decision-making process. To address complex nonlinearities in the system, the KAN is utilized to model and approximate these dynamics, refining the LSTM predictions. The integration of these advanced control strategies enables the system to handle varying operational conditions and maintain optimal performance. The case study demonstrates the effectiveness of the MPC-LSTM-KAN approach, revealing improvements in the SOC stability, energy efficiency, and operational endurance of the high-altitude wind energy work umbrella system. The results indicate that this hybrid optimization method offers a robust solution for managing hybrid energy systems in dynamic environments.
A Practical Pole-to-Ground Fault Current Calculation Method for Symmetrical Monopole DC Grids
Authors: Xu Ying , Kuang Wei , Li Baohong , Li Xiaopeng , Zou Tierui , Jiang Qin , Luo Yiping
Published: October 2024

At present, DC grid fault current analyses are usually based on numerical analyses and/or simulations. To make fault current analyses more practical and convenient, this study proposes a fast fault current level assessment methodology that is applicable when a symmetrical monopole DC (SMDC) system encounters a pole-to-ground (PTG) fault. To further clarify how PTG faults develop in SMDC systems, fault current analysis is implemented in the frequency domain rather than the time domain. Specifically, we find the key factors that impact the high-frequency domain, as these factors have a high correlation with fault currents in the initial milliseconds. Based on simplified SMDC fault circuits and a high-frequency characteristic analysis, a practical index to assess PTG faults is ultimately proposed. It is proved that the index can be used for various SMDC systems with different topologies. With the proposed method, the topology of a DC grid can be optimized to decrease the fault current level, which can help with the design and construction of practical DC grid projects.
Stochastic Decision-Making Optimization Model for Large Electricity Self-Producers Using Natural Gas in Industrial Processes: An Approach Considering a Regret Cost Function
Authors: Leonel Laís Domingues , Balan Mateus Henrique , Camargo Luiz Armando Steinle , Ramos Dorel Soares , Castro Roberto , Clemente Felipe Serachiani
Published: October 2024

In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of USD 3.98 millions over a six-month analysis period.
The 1H HR-NMR Methods for the Evaluation of the Stability, Quality, Authenticity, and Shelf Life of Foods
Authors: Picone Gianfranco
Published: October 2024

1H High-Resolution Nuclear Magnetic Resonance (1H HR-NMR) spectroscopy is a powerful analytical methodology used in various fields, including food science. In the food science field, NMR combined with the principles of metabolomics can provide detailed information about a food’s molecular composition, structure, dynamics, and interactions within food matrices, making it invaluable for assessing changes during storage, processing, and shelf life. This entry aims to list the main applications of one-dimensional 1H HR-NMR methods in the field of food science, such as their use in the assessment of the stability, quality, authenticity, and shelf life of food samples. Several kinds of foods are taken into consideration to give a huge overview of the potentiality of the methods.
National Forest City Policy and Urban Ecological Resilience: Evidence from 292 Cities in China
Authors: Xu Xinkuo , Song Zenglu
Published: October 2024

The process of sustainable urban development faces complex and severe environmental problems. Therefore, enhancing urban ecological resilience (UER) has become an urgent and critical goal. In this study, the establishment of national forest cities (NFCs) in China is regarded as an exogenous shock event, and the impact of NFCs on UER and its mechanisms are investigated based on data from 292 cities spanning 2003 to 2021 using a difference-in-difference method. It is found that NFCs can significantly enhance UER, and this conclusion holds after a series of robustness tests. Mechanism analysis shows that NFCs can effectively strengthen environmental regulations, upgrade industrial structures, promote green innovation, and thus enhance UER. Heterogeneity analysis indicates that the effect of NFC on UER is more significant in low-carbon non-pilot cities, cities with higher levels of industrial development, and cities in central and western China. Spatial spillover analysis shows that NFCs can effectively improve the ecological resilience of neighboring cities. Therefore, NFCs should be continuously implemented and optimized to establish a long-term mechanism for urban forests to enhance ecological resilience.
Thermal Decomposition and Kinetic Analysis of Amazonian Woods: A Comparative Study of Goupia glabra and Manilkara huberi
Authors: Junior Mark Dany Veloso , Guerrero Fidel , da Silva Felipe Moura Araújo , Ramos Glenda Quaresma , Matos Robert Saraiva , Țălu Ștefan , Trong Dung Nguyen , da Fonseca Filho Henrique Duarte
Published: October 2024

This study presents a detailed analysis of the thermal degradation and kinetic behavior of two Amazonian wood species, Goupia glabra (cupiúba) and Manilkara huberi (maçaranduba), using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR-ATR), and direct infusion mass spectrometry (DIMS). Wood samples were subjected to controlled heating rates of 20, 40, and 60 °C/min from 25 to 800 °C under an argon atmosphere. TGA revealed moisture evaporation below 120 °C, with hemicellulose degradation occurring between 220 and 315 °C, cellulose decomposition between 315 and 400 °C, and lignin breakdown over a broader range from 180 to 900 °C. The highest rate of mass loss occurred at 363.99 °C for G. glabra and 360.27 °C for M. huberi at a heating rate of 20 °C/min, with shifts to higher temperatures at faster heating rates. Activation energies were calculated using Arrhenius and Kissinger models, yielding values between 53.46–61.45 kJ/mol for G. glabra and 58.18–62.77 kJ/mol for M. huberi, confirming their stable thermal profiles. DSC analysis identified a significant endothermic peak related to moisture evaporation below 100 °C, followed by two exothermic peaks. For G. glabra, the first exothermic peak appeared at 331.45 °C and the second at 466.08 °C, while for M. huberi, these occurred at 366.41 °C and 466.08 °C, indicating the decomposition of hemicellulose, cellulose, and lignin. Enthalpy values for G. glabra were 12,633.37 mJ and 18,652.66 mJ for the first and second peaks, respectively, while M. huberi showed lower enthalpies of 9648.04 mJ and 14,417.68 mJ, suggesting a higher energy release in G. glabra. FTIR-ATR analysis highlighted the presence of key functional groups in both species, with strong absorption bands in the 3330–3500 cm−1 region corresponding to O-H stretching vibrations, indicative of hydroxyl groups in cellulose and hemicellulose. The 1500–1600 cm−1 region, representing aromatic C=C vibrations, confirmed the presence of lignin. Quantitatively, these results suggest a high content of cellulose and lignin in both species. DIMS analysis further identified polyphenolic compounds and triterpenoids in M. huberi, with major ions at m/z 289 and 409, while G. glabra showed steroidal and polyphenolic compounds with a base peak at m/z 395. These findings indicate the significant presence of bioactive compounds, contributing to the wood’s resistance to microbial degradation. This comprehensive thermal and chemical characterization suggests that both species have potential industrial applications in environments requiring high thermal stability.
Assessment of Ecosystem Characteristics and Fishery Carbon Sink Potential of Qianxiahu Reservoir Based on Trophic Level and Carbon Content Methods
Authors: Liu Mei , Shu Mengxia , Lian Qingping , Guo Aihuan , Zhou Dan , Zou Songbao , Yuan Julin , Chen Guangmei
Published: October 2024

Optimizing biological carbon sequestration has become a primary strategy in global low-carbon-emission initiatives. Freshwater fisheries in reservoirs play an important role in aquatic biological carbon sequestration. However, a standard method for evaluating the carbon sink capacity of inland fisheries has not been developed. Therefore, this study aimed to assess and compare the carbon sequestration potential of the Qianxiahu Reservoir’s fisheries using the trophic level and mass-balance methodologies. The Ecopath model was employed to determine the trophic levels of aquatic organisms within the Qianxiahu Reservoir ecosystem, with input parameters sourced from in situ surveys and the literature on reservoirs. The model includes 21 functional groups, with trophic levels ranging from 1.000 to 3.281. The key species identified are silver carp, bighead carp, and crucian carp. The indices of Finn’s cycling index (FCI), connectivity index (CI), system omnivory index (SOI), and total primary production/total respiration (TPP/TR) for the Qianxiahu Reservoir are 11.35, 0.27, 0.196, and 1.540, respectively. These values indicate a high degree of material recycling and complex interconnections among functional groups. The fishery carbon sink potential of the Qianxiahu Reservoir, calculated using the trophic level and carbon content methods, yielded values of 261.8362 tons/km2 and 66.6818 tons/km2, respectively. The trophic level method showed a notable increase of 195,1544 tons/km2 compared to the carbon content method, underscoring significant differences in results between the two methods. The study concludes with recommendations for research on methods to assess the carbon sink capacity of freshwater fisheries, aiming to establish a scientific framework for this evaluation.
Distribution Characteristics of Trichiurus japonicus and Their Relationships with Environmental Factors in the East China Sea and South-Central Yellow Sea
Authors: Shi Xinyu , Lu Zhanhui , Wang Zhongming , Li Jianxiong , Gao Xin , Kong Zhuang , Zhu Wenbin
Published: October 2024

The largehead hairtail (Trichiurus japonicus) is the most productive fish caught in China. In order to understand the seasonal distribution of T. japonicus in the East China Sea and the central and southern parts of the Yellow Sea, three species distribution models were used in this study, namely the random-forest model, K-nearest-neighbor algorithm, and gradient-ascending decision-tree model, based on the data of trawling surveys in the East China Sea and central and southern parts of the Yellow Sea from 2008 to 2009. Combined with a variance inflation factor and cross-check, a distribution model of T. japonicus was screened and constructed to analyze the influence of environmental factors on the distribution of T. japonicus in the East China Sea and central and southern parts of the Yellow Sea. The results showed that the random-forest model had the advantages of fitting effect and prediction ability among the three models. The analysis of this model showed that the water depth, bottom water temperature, and surface salinity had a great influence on the habitat distribution of T. japonicus. The relative resources of T. japonicus increased with the increase of bottom water temperature, reached the maximum at 23.8 °C, and first increased and then decreased with the increase of water depth and surface salinity, reaching the maximum when water depth is 72 m and surface salinity is 31.2%. This study also used the random-forest model to predict the spatial distribution of T. japonicus in the central and southern waters of the East China Sea and south-central Yellow Sea from 2008 to 2009, and the results showed that the predicted results were close to the actual situation. The research results can provide a reference for the exploitation and protection of T. japonicus resources in the East China Sea and the south-central Yellow Sea.
Insights into Decapod Sentience: Applying the General Welfare Index (GWI) for Whiteleg Shrimp (Penaeus vannamei—Boone, 1931) Reared in Aquaculture Grow-Out Ponds
Authors: Pedrazzani Ana Silvia , Cozer Nathieli , Quintiliano Murilo Henrique , Ostrensky Antonio
Published: October 2024

The rapid growth of shrimp farming, particularly of Penaeus vannamei, accounts for about 80% of the global production of farmed shrimp and involves the cultivation of approximately 383 to 977 billion individuals annually, which highlights the urgent need to address the ethical and technical implications of raising potentially sentient beings. This study builds on the state-of-the-art assessment of sentience, consciousness, stress, distress, nociception, pain perception, and welfare to adapt the General Welfare Index (GWI) for farmed shrimp. The GWI is a quantitative index developed by our research group to measure the degree of welfare in aquaculture, and it has been previously applied to grass carp and tilapia. Using the PRISMA methodology and the creation of a hypothetical shrimp farm, the GWI, with 31 specific and measurable indicators across various welfare domains, is adapted to P. vannamei, offering a comprehensive assessment framework. The inclusion of quantitative welfare indicators promises to improve living conditions in alignment with legislation adopted on decapods’ sentience and contemporary scientific advances.
A Review of Biomechanical Studies of Heart Valve Flutter
Authors: Chen Lu , Zhang Zhuo , Li Tao , Chen Yu
Published: October 2024

This paper reviews recent biomechanical studies on heart valve flutter. The function of the heart valves is essential for maintaining effective blood circulation. Heart valve flutter is a kind of small vibration phenomenon like a flag fluttering in the wind, which is related to many factors such as a thrombus, valve calcification, regurgitation, and hemolysis and material fatigue. This vibration phenomenon is particularly prevalent in valve replacement patients. The biomechanical implications of flutter are profound and can lead to micro-trauma of valve tissue, accelerating its degeneration process and increasing the risk of thrombosis. We conducted a systematic review along with a critical appraisal of published studies on heart valve flutter. In this review, we summarize and analyze the existing literature; discuss the detection methods of frequency and amplitude of heart valve flutter, and its potential effects on valve function, such as thrombosis and valve degeneration; and discuss some possible ways to avoid flutter. These findings are important for optimizing valve design, diagnosing diseases, and developing treatment strategies.
Evaluation of Physiological Activity of Long-Term Ripened Gouda Water Extract
Authors: Ki Woojin , Renchinkhand Gereltuya , Bae Hyoungchurl , Nam Myoung Soo
Published: October 2024

This study investigated peptide changes and their bioactive functions through the long-term ripening of Gouda. Young Gouda (YG), medium Gouda (MG), and extra-sharp Gouda (EG) water extracts were prepared and functional peptides were recognized using liquid chromatography–high-resolution mass spectrometry. Two peptides with ACE-inhibitory effects (IQP and LQP) were identified in YG, while in MG and EG were identified eight (EL, IVP, VP, LPP, VIP, IPP, VPP, and VVPP) and six (EL, YL, VP, IR, YPEL, and DKIHPF) functional peptides, respectively. MG (70.26%) and EG (46.81%) showed stronger antioxidant activity than YG (25.99%) in ABTS (2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic) acid) inhibition, though the DPPH (2,2-diphenyl-1-picrylhydrazyl) inhibition rate decreased with ripening. The antihypertensive effect increased in MG (79.76%) and EG (94.50%) due to ACE-inhibitory peptides. Measurements of inflammatory mRNA expression levels and immunoblotting were conducted to assess the anti-inflammatory properties. MG and EG suppressed the transcription of IL-1β and IL-6 mRNA. Immunoblotting indicated that EG suppressed IκBα phosphorylation to 57%. The enhancement of bioactive function in the water-soluble part of long-term ripened Gouda cheese may have affected identified peptides as well as unknown peptides. Further studies are expected to aid in discovering these novel bioactive peptides.
Investigation of Various Toxigenic Genes and Antibiotic and Disinfectant Resistance Profiles of Staphylococcus aureus Originating from Raw Milk
Authors: Bayrakal Gulay Merve , Aydin Ali
Published: October 2024

This study investigated the toxigenic genes and antimicrobial resistance profiles of Staphylococcus aureus strains isolated from 260 raw milk samples collected from dairy farms in Türkiye. The results indicated that 60.7% of staphylococcal enterotoxin genes (sea, seb, sed, seg, sei, sej, sek, seq, sem, seo, and seu) and 21.4% of the tst and eta genes were positive, with most enterotoxin-positive samples carrying more than one gene. The sec, see, seh, sel, sen, sep, and etb genes were not identified in any samples. The prevalence of antibiotic resistance genes (mecA, blaR, blaI, blaZ, vanA, ermT, tetK, aac/aph, ant, dfrA, tcaR, IS256, and IS257) was high at 89.2%, with bla being the most frequently detected gene (75%). The mecA gene was present in 14.2% of samples, while tcaR was detected in 78.5%. Nevertheless, the mecC was not identified. Disinfectant resistance genes (qacA/B, qacC, qacJ, smr) were detected in 21.4% of the samples. The results of the disk diffusion test showed that 64.2% of strains were resistant to penicillin G and ampicillin, with additional resistance found for cefoxitin, teicoplanin, levofloxacin, norfloxacin, and other antibiotics. These findings highlight a significant public health and food safety risk associated with raw milk due to the presence of S. aureus strains with toxigenic genes and high antimicrobial resistance.
Upcycling Milk Industry Byproducts into Tenebrio molitor Larvae: Investigation on Fat, Protein, and Sugar Composition
Authors: Brai Annalaura , Neri Cassia , Tarchi Franca , Poggialini Federica , Vagaggini Chiara , Frosinini Riccardo , Simoni Sauro , Francardi Valeria , Dreassi Elena
Published: October 2024

Edible insects represent a growing sector of the food industry and have a low carbon footprint. Noteworthy, insects can upcycle different leftovers and byproducts into high-quality nutrients. Herein, the larvae of the edible insect Tenebrio molitor (TML) were fed using local milk industry byproducts. Mozzarella whey and whey permeate obtained in cheese production were used to formulate three alternative diets. Both byproducts are rich in sugars, in particular the disaccharide lactose and the monosaccharides glucose and galactose. Two of the three diets did not interfere with biometric data and vitality, while the use of whey permeate alone significantly reduced development. At the end of the trial, the proximate composition of TML was strongly affected, with an increased protein content of up to +7% and a favorable fat composition. The analysis of secondary metabolites revealed the accumulation of different compounds, in particular monounsaturated fatty acids (MUFAs), amino acids, and the disaccharide trehalose, essential for the correct larval development and pupation. In conclusion, the present study demonstrates that milk industry byproducts can be upcycled as feed for TML, maintaining an optimal nutrient composition and favorably increasing the protein content.
Effects of Five Different Withering Methods on the Composition and Quality of Congou Black Tea
Authors: Wu Yamin , Wang Xinghua , Chen Lijiao , Li Qiang , He Junjie , Deng Xiujuan , Xu Jiayi , Che Raoqiong , Zhou Jianyun , Yuan Wenxia , Wu Tianyu , Tian Juan , Chen Yaping , Wang Baijuan
Published: October 2024

To explore the effects of different withering methods on the quality of Congou black tea, this study focused on five different withering methods: natural withering, warm-air withering, sun–natural combined withering, sun withering, and shaking withering. Gas chromatography‒mass spectrometry (GC‒MS), high-performance liquid chromatography (HPLC), and ion-exchange chromatography techniques were used to analyze the nonvolatile and volatile components and composition of the tea. The results revealed significant differences (p < 0.05) in the contents of nonvolatile constituents including caffeine, polyphenols, soluble sugars, free amino acids and their components, theaflavins, thearubigins, and catechins among the five different withering methods, with varying degrees of correlation between these components. A total of 227 aroma compounds were detected, and significant differences in the contents of alcohols, aldehydes, and ketones were observed. A relative odor activity value (ROVA) analysis of the aroma compounds revealed that 19 compounds had an ROVA > 1. Among them, benzylaldehyde, trans-2-decenal, decanal, benzaldehyde, nonanal, hexanal, trans-linalool, and geraniol from the shaking withering method had significantly higher ROVA values than those from the other withering methods, which may be the reason for the prominent floral and fruity aroma of shaking withering. This study revealed the impact of different withering methods on the quality of Congou black tea, providing a scientific basis for the development of Congou black tea with different flavors and the improvement of Congou black tea processing techniques.
Effect of pH-Shift Treatment on IgE-Binding Capacity and Conformational Structures of Peanut Protein
Authors: Geng Qin , Zhou Wenlong , Zhang Ying , Wu Zhihua , Chen Hongbing
Published: October 2024

Hypoallergenic processing is an area worthy of continued exploration. In the treatment of the peanut protein (PP), pH shift was applied by acidic (pH 1.0–4.0) and alkaline (pH 9.0–12.0) treatment, after which the pH was adjusted to 7.0. Following pH-shift treatment, PP showed a larger particle size than in neutral solutions. SDS-PAGE, CD analysis, intrinsic fluorescence, UV spectra, and surface hydrophobicity indicated the protein conformation was unfolded with the exposure of more buried hydrophobic residues. Additionally, the IgE-binding capacity of PP decreased after pH-shift treatment on both sides. Label-free LC–MS/MS results demonstrated that the pH-shift treatment induced the structural changes on allergens, which altered the abundance of peptides after tryptic digestion. Less linear IgE-binding epitopes were detected in PP with pH-shift treatment. Our results suggested the pH-shift treatment is a promising alternative approach in the peanut hypoallergenic processing. This study also provides a theoretical basis for the development of hypoallergenic food processing.
The Uniqueness and Iterative Properties of Positive Solution for a Coupled Singular Tempered Fractional System with Different Characteristics
Authors: Chen Peng , Zhang Xinguang , Wang Ying , Wu Yonghong
Published: October 2024

In this paper, we focus on the uniqueness and iterative properties of positive solution for a coupled p-Laplacian system of singular tempered fractional equations with differential order and characteristics. Firstly, the system is converted to an integral equation, and then, a coupled iterative technique and some suitable growth conditions are proposed; furthermore, some elaborate results about the uniqueness and iterative properties of positive solutions of the system are established, which include the uniqueness, the convergence analysis, the asymptotic behavior, and error estimation, as well as the convergence rate of the positive solution. The interesting points of this paper are that the order of the system of equations is different and the nonlinear terms of the system possess the opposite monotonicity and allow for stronger singularities at space variables.
Fractal-Fractional-Order Modeling of Liver Fibrosis Disease and Its Mathematical Results with Subinterval Transitions
Authors: Hamza Amjad E. , Osman Osman , Ali Arshad , Alsulami Amer , Aldwoah Khaled , Mustafa Alaa , Saber Hicham
Published: October 2024

In this paper, we study human liver disease with a different approach of interval-based investigation by introducing subintervals. This investigation may be referred to as a short memory investigation. Such concepts are useful in problems where a transition is observed when transitioning from one subinterval to the other one. We use the classical and fractal-fractional-order derivative in each subinterval. We study the existence of solutions by using Banach’s and Krasnoselskii’s fixed-point theorems. Their stability is analyzed by adopting the Hyers–Ulam (H-U) stability approach. Also, using the extended Adams–Bashforth–Moulton (ABM) method, we simulate the results that visually present the numerical solutions for different fractal-fractional-order values.
A Local Radial Basis Function Method for Numerical Approximation of Multidimensional Multi-Term Time-Fractional Mixed Wave-Diffusion and Subdiffusion Equation Arising in Fluid Mechanics
Authors: Kamran  , Gul Ujala , Khan Zareen A. , Haque Salma , Mlaiki Nabil
Published: October 2024

This article develops a simple hybrid localized mesh-free method (LMM) for the numerical modeling of new mixed subdiffusion and wave-diffusion equation with multi-term time-fractional derivatives. Unlike conventional multi-term fractional wave-diffusion or subdiffusion equations, this equation features a unique time–space coupled derivative while simultaneously incorporating both wave-diffusion and subdiffusion terms. Our proposed method follows three basic steps: (i) The given equation is transformed into a time-independent form using the Laplace transform (LT); (ii) the LMM is then used to solve the transformed equation in the LT domain; (iii) finally, the time domain solution is obtained by inverting the LT. We use the improved Talbot method and the Stehfest method to invert the LT. The LMM is used to circumvent the shape parameter sensitivity and ill-conditioning of interpolation matrices that commonly arise in global mesh-free methods. Traditional time-stepping methods achieve accuracy only with very small time steps, significantly increasing the computational time. To overcome these shortcomings, the LT is used to provide a more powerful alternative by removing the need for fine temporal discretization. Additionally, the Ulam–Hyers stability of the considered model is analyzed. Four numerical examples are presented to illustrate the effectiveness and practical applicability of the method.
The Application of Information Theory to Interpret Shore Platform Erosion Rates
Authors: Gauci Ritienne , Inkpen Rob
Published: October 2024

Advancements in information physics have recently introduced the application of information theory to investigate physical systems. The behaviour of erosion at the granular scale is to date still a complex system to unpack, and therefore geomorphology research requires novel approaches to better inform the interpretation of temporal and spatial erosion patterns at different scales. This paper applies information theory concepts to re-evaluate erosional data that were measured on limestone surfaces of two shore platforms in Malta with a traversing micro-erosion meter (TMEM). By representing erosion rates through their information content using a Box-Cox style transformation of the raw data (application of an inverse normal distribution function to fractionally ranked data), it is possible to identify points and measurement periods that contribute to a disproportionately large share of unexpected erosion rates that could provide more insight into the causes of erosion rates. Despite the variations in the information content from erosion rates at individual measurement points, most points consistently contribute to a similar amount of information. These findings illuminate the importance of considering the informational value of erosion data to further understand the underlying physical processes and potentially improve predictive models.
Revising Gerty MacDowell’s Identity and Agency: An Intersectional Feminist Disability Perspective
Authors: Gallego-Ortiz Maria
Published: October 2024

Gerty MacDowell’s initial, albeit brief, appearance in James Joyce’s Ulysses has sparked debates regarding her identity and agency. In the critical literature, there are interpretations that characterize Gerty as a woman and disabled person whose actions conform to patriarchal beauty standards that objectify her. This paper argues for revising such readings by applying an intersectional feminist disability perspective attuned to the interconnections between her womanhood and disability. Rather than positing Gerty’s identities as inherently conflicting, I illustrate how her disability and feminine social position co-constitute and transform one another. Her self-care practices aimed at securing a husband, though partly conforming to norms, also foster confidence and counter pervasive cultural assumptions of disabled women as ugly, useless, and asexual. Gerty’s exhibition of sexual desire and pursuit of pleasure likewise contest views of disabled women as unsuitable for romance or unable to be agentic sexual subjects. Furthermore, conceptualizing agency beyond neoliberal notions of rational autonomy acting against all constraints upholds Gerty’s agentic power. She makes strategic use of available discourses and resources to expand her precarious options given material and ideological limitations. Overall, analyzing Gerty’s intersectional experience denaturalizes the reductive models of identity and agency that have dominated Ulysses criticism. Applying fresh perspectives opens new symbolic interpretations of embodied identity and sexuality.
Exploring Social Support Strategies and Socio-Cultural Factors Influencing Social Isolation and Loneliness: The Role of Digital Literacy
Authors: Batra Ravi , Flatt Jason D. , Pharr Jennifer R. , Sharma Manoj , Khubchandani Jagdish , Kanekar Amar , Chirico Francesco , Batra Kavita
Published: October 2024

Background/Objectives: Social isolation (SI) and loneliness (L) are the long-standing critical concerns impacting the mental well-being of older adults. The COVID-19 pandemic has exacerbated existing vulnerabilities, leading to a notable rise in perceived social isolation (PSI) and its associated risks among an aging population. Reportedly, nearly 35% of older Americans felt lonely before the pandemic, with the pandemic further intensifying these feelings. This commentary examines the multifaceted factors contributing to PSI, including demographic and socio-economic characteristics. Methods: We outline the health risks associated with PSI, including cardiovascular diseases and mental health conditions. Results: This commentary addresses the potential of information and communication technology (ICT) to alleviate loneliness, despite significant barriers such as the digital divide and technological anxiety among older adults. Conclusions: This commentary advocates targeted digital literacy interventions and theoretical frameworks to enhance technology adoption and mitigate PSI, ultimately aiming to improve health outcomes and quality of life for the aging population.
The Effect of Self-Management on Patients with Chronic Diseases: A Systematic Review and Meta-Analysis
Authors: Huang Yanfang , Li Sijia , Lu Xiuli , Chen Weiqiang , Zhang Yun
Published: October 2024

Background: Chronic diseases significantly impact global morbidity and mortality, affecting millions. Self-management interventions are crucial for improving patient health outcomes. This study explores the effects of self-management interventions on the quality of life (QOL), self-efficacy, depression, and anxiety of patients with chronic diseases. Methods: Relevant studies were searched from PubMed, EMBASE, and Web of Science. Two reviewers independently screened the literature, evaluated the risk of bias assessment, and extracted characteristics and outcomes among patients with chronic diseases. For each included study, we calculated the standardized mean difference (SMD) and 95% confidence interval (CI) of the main outcomes. When deemed feasible, the heterogeneity of the study was explored by meta-analysis and subgroup analysis. Results: Thirty-four studies involving a total of 7603 patients with chronic diseases were included. Self-management interventions significantly improved quality of life (Higher-better QOL and Lower-better QOL), self-efficacy, and reduced depression symptoms compared to usual care (95%CI 0.01 to 0.15, p = 0.03; 95%CI −0.49 to −0.08, p = 0.006; 95%CI 0.19 to 0.62, p < 0.001; 95%CI −0.23 to −0.07, p < 0.001). However, no significant effect was found for anxiety (95%CI −0.18 to 0.03, p = 0.18). In the heterogeneity analysis, Lower-better QOL and self-efficacy were all higher than 50% (I2 = 80%, 87%). After the subgroup analysis, the heterogeneity of Lower-better QOL and self-efficacy was less than 50% (I2 = 0%, 16.1%). Subgroup analyses revealed that studies with mean age greater than 60 years old and follow-up times greater than 6 months were more effective in improving patients’ Lower-better QOL (p = 0.03, p = 0.004), whereas follow-up times less than 6 months were better at reducing patients’ anxiety symptoms (p = 0.03). Conclusions: Self-management interventions are more effective than routine care in managing chronic diseases, significantly improving patients’ quality of life, self-efficacy, and reducing depressive symptoms, but they did not show significant improvements in anxiety symptoms. Overall, self-management interventions for chronic diseases can help patients adapt to the changes brought about by the disease and self-manage diseases to prevent disease progression.
Relationship Between Instagram, Body Satisfaction, and Self-Esteem in Early Adulthood
Authors: Flores Mata Cristina , Castellano-Tejedor Carmina
Published: October 2024

Background/Objectives: This study aimed to explore the effects of Instagram use on body satisfaction and self-esteem in young adults 20 to 40 years (N = 95). Given the widespread use of social media and its potential influence on body image, we sought to understand how Instagram use may contribute to body dissatisfaction and self-esteem, particularly through quantitative analysis of self-report measures. Methods: A cross-sectional survey design in which the Rosenberg Self-Esteem Scale (RSES), the Body Shape Questionnaire (BSQ), and additional ad hoc questions designed to assess Instagram usage patterns were employed. Results: The results indicated that greater Instagram use is associated with increased body dissatisfaction (p = 0.005), although it did not significantly affect self-esteem (p = 0.211). Gender did not play a significant role in these relationships (p = 0.173). Notably, a significant positive correlation was found between body satisfaction and self-esteem, showing that individuals with higher body satisfaction also reported higher self-esteem (p < 0.001). Further analyses indicated that users exposed to appearance-centered content were more likely to report body dissatisfaction. Conclusions: These findings suggest that Instagram usage, particularly in the context of appearance-focused content, has a considerable impact on body dissatisfaction among young adults but does not appear to influence self-esteem. This highlights the importance of developing interventions focused on promoting healthy social media habits and critical content engagement to mitigate negative impacts on body image. Social media exposure should be a key component in future interventions designed to improve body image and overall psychological well-being.