bluuebunny/crossref_metadata_2025 huggingface dataset:
Transcriptome and Metabolome Insights into Key Genes Regulating Fat Deposition and Meat Quality in Pig Breeds
Authors: Kumar Suthar Teerath , Zheng Yunlong , Xu Jing , Zhao Ziyi , Zhang Qi , Zhang Yunpeng , Li Min , Zou Hong , Azeem Riaz Muhammad , Sun Wu-Sheng , Zhao Yuan , Zhang Shu-Min
Published: December 2024

Meat quality is a complex trait that exhibits significant variation across pig breeds, and the regulatory mechanisms governing pork meat quality are not fully elucidated. We compared the transcriptomics and metabolomics of the longissimus dorsi (LD) muscle between the Songliao Black Pig (SBP) and Large White × Landrace Pig (LWLDP) to investigate breed-specific differences in meat quality and underlying regulatory pathways. The results showed that SBP meat had a higher marbling score and backfat thickness, a richer color, a lower shear force, and reduced drip loss. Fatty acid (FA) analysis identified 15 significant FAs in the LWLDP, with docosahexaenoic acid (DHA) in the SBP, while amino acid (AA) analysis revealed no breed-based differences. Transcriptome analysis identified 134 upregulated and 362 downregulated genes in the SBP. Protein–protein interaction (PPI) network analysis found 25 key genes, which are associated with muscle development, fat deposition, and overall meat quality, while genes in the insulin signaling pathway, such as PPP1R3B, PPARGC1A, SOCS1, EIF4E, PRKAR2A, PRKAG2, and FASN, play a crucial role in balancing fat metabolism and catabolism. Metabolomic analysis identified 89 upregulated and 10 downregulated metabolites in the SBP, primarily involved in fructose and mannose metabolism, amino acid biosynthesis, nucleotide sugar metabolism, and glucagon signaling pathways. Gene–metabolite association analysis found that the PPP1R3B gene had a strong association with Thr-Leu, Maltol, D-myo-Inositol-4-phosphate, and Fructose-6-phosphate, while MYOG correlated with Mannose-6-phosphate, Fructose-1-phosphate, Mannose-1-phosphate, and Glucose-6-phosphate. In contrast, NR4A3 and PPARGC1A showed a strong negative correlation with most upregulated metabolites. In conclusion, this study identified functional genes, elucidated the mechanisms associated with meat quality traits, and identified gene–metabolite associations involved in energy metabolism, muscle development, and fat deposition, providing valuable insights into the molecular mechanisms that regulate meat quality between pig breeds.
Comparison of Development and Antioxidative Ability in Fertilized Crossbred (Yorkshire × Landrace × Duroc) Oocytes Using Duroc and Landrace Sperm
Authors: Lee Hayoung , Kim Hyewon , An Jisoon , Cheong Hee-Tae , Lee Sang-Hee
Published: December 2024

Pig production through crossbreeding methods is a pillar of the swine industry; however, research on the fertilization ability of male pigs in crossbreeds is lacking. Therefore, this study investigated the effects of Duroc sperm (DS) and Landrace sperm (LS) on fertility in Yorkshire × Landrace × Duroc (YLD) oocytes. Sperm were collected from the Duroc and Landrace species, and sperm characteristics, viability, and acrosome reactions were analyzed using flow cytometry. Oocytes were collected from YLD ovaries, and the fertility of DS and LS was determined using in vitro fertilization (IVF). Reactive oxygen species (ROS) and antioxidative abilities were analyzed using H2DCFDA and a Cell Tracker Red assay. Pluripotency (OCT4, SOX2, and NANOG), antioxidative (SOD1, SOD2, CAT, and GPx1), apoptotic (Bax and Bcl-2), and cell cycle-related (Cdc2 and CCNB1) genes were detected using quantitative reverse transcription polymerase chain reaction (qRT-PCR) in oocytes fertilized with sperm. The results showed no significant difference in viability or acrosome reaction between DS and LS. ROS levels were significantly lower in the LS group than in the DS group, whereas glutathione (GSH) levels in the embryo did not significantly differ between the DS and LS groups. The OCT4, GPx1, and Cdc2 mRNA expression levels were significantly higher in the LS than DS groups. Blastocyst formation was significantly higher in the LS than DS groups. ROS levels were reduced, and blastocyte formation was increased in LS-obtained embryos. In conclusion, these results provide a fundamental understanding of using Landrace semen in the three-way crossbreeding of YLD pigs.
Artemisia annua Residue Regulates Immunity, Antioxidant Ability, Intestinal Barrier Function, and Microbial Structure in Weaned Piglets
Authors: Hu Jinjie , Bai Miaomiao , Xing Yueyao , Liu Junhong , Xu Kang , Xiong Xia , Liu Hongnan , Yin Yulong
Published: December 2024

Artemisia annua residue (AR), as the byproduct of industrial extraction of artemisinin, contains rich nutrients and active ingredients. This study was conducted to determine the effects of AR as an unconventional feed material on growth performance, immunity, and intestinal health in weaned piglets. Thirty-two piglets weaned at 21 days (7.53 ± 0.31 kg average BW) were fed with a corn–soybean basal diet (BD) and a basal diet with 1% (LAR), 2% (MAR), and 4% (HAR) AR diets for 28 days. AR diets increased the serum IgA and complement component 3 levels, superoxide dismutase activity, and villus height in the duodenum (p < 0.05). The MAR group increased the ADG, serum total protein, and mRNA expression levels of Claudin-1 in the duodenum and zonula occludens-1 (ZO-1) and the mucin 2 (MUC2) in the colon, as well as colonic Romboutsia and Anaerostipes abundances, and decreased the Proteobacteria abundance (p < 0.05). To sum up, dietary AR supplementation may enhance growth performance by improving serum immunoglobulin and antioxidant enzyme activity, intestinal morphology, tight junction protein expression, and gut microbiota of weaned piglets. Regression analysis showed that the optimal AR supplemental level for growth performance, immunity, antioxidant ability, and intestinal health of weaned piglets was 2.08% to 4.24%.
In Vitro Protective Effects of a Standardized Extract of Opuntia ficus-indica (L.) Mill. Cladodes and Olea europaea L. Leaves Against Indomethacin-Induced Intestinal Epithelial Cell Injury
Authors: Salamone Federica Lina , Molonia Maria Sofia , Muscarà Claudia , Saija Antonella , Cimino Francesco , Speciale Antonio
Published: December 2024

Nonsteroidal anti-inflammatory drugs (NSAIDs) can induce serious adverse effects in gastrointestinal (GI) mucosa, increasing intestinal permeability and leading to mitochondrial dysfunction, oxidative stress, apoptosis and inflammation. As proton pump inhibitors are effective in protecting against NSAID-induced gastropathy but not NSAID-induced enteropathy, current research is focused on natural products as protective substances for therapy and prevention of intestinal injury. Herein, through the use of an in vitro model based on intestinal epithelial cell (Caco-2) damage caused by indomethacin (INDO), we examined the protective activity of a commercially available standardized extract (OFI+OE) from Opuntia ficus-indica (L.) Mill. cladodes and Olea europaea L. leaves. Pre-treatment with OFI+OE prevented INDO-induced intestinal epithelial barrier damage, as demonstrated by TEER measurement, fluorescein permeability, and tight junction protein expression. The extract showed positive effects against INDO-induced oxidative stress and correlated activation of apoptosis, decreasing pro-apoptotic markers BAX and Caspase-3 and increasing anti-apoptotic factor Bcl-2. Moreover, the extract inhibited the NF-κB pathway and pro-inflammatory cascade. In conclusion, these data support the use of OFI+OE extract as a natural strategy for therapy and prevention of intestinal mucosal damage, demonstrating its beneficial effects against INDO-induced intestinal damage, through modulation of oxidative, apoptotic, and inflammatory pathways.
The Role of Dietary Antioxidants, Food Supplements and Functional Foods for Energy Enhancement in Healthcare Professionals
Authors: Kalogerakou Theodora , Antoniadou Maria
Published: December 2024

Healthcare professionals frequently experience significant work overload, which often leads to substantial physical and psychological stress. This stress is closely linked to increased oxidative stress and a corresponding decline in energy levels. This scoping review investigates the potential impact of dietary antioxidants and food supplements in conjunction with diet in controlling these negative effects. Through an analysis of the biochemical pathways involved in oxidative stress and energy metabolism, the paper emphasizes the effectiveness of targeted dietary interventions. Key dietary antioxidants, such as vitamins C and E, polyphenols, and carotenoids, are evaluated for their ability to counteract oxidative stress and enhance energy levels. Additionally, the review assesses various food supplements, including omega-3 fatty acids, coenzyme Q10, and ginseng, and their mechanisms of action in energy enhancement. Practical guidelines for incorporating energy-boost dietary strategies into the routine of healthcare professionals are provided, emphasizing the importance of dietary modifications in reducing oxidative stress and improving overall well-being and performance in high-stress healthcare environments. The review concludes by suggesting directions for future research to validate these findings and to explore new dietary interventions that may further support healthcare professionals under work overload.
MuIm: Analyzing Music–Image Correlations from an Artistic Perspective
Authors: Ullah Ubaid , Choi Hyun-Chul
Published: December 2024

Cross-modality understanding is essential for AI to tackle complex tasks that require both deterministic and generative capabilities, such as correlating music and visual art. The existing state-of-the-art methods of audio-visual correlation often rely on single-dimension information, focusing either on semantic or emotional attributes, thus failing to capture the full depth of these inherently complex modalities. Addressing this limitation, we introduce a novel approach that perceives music–image correlation as multilayered rather than as a direct one-to-one correspondence. To this end, we present a pioneering dataset with two segments: an artistic segment that pairs music with art based on both emotional and semantic attributes, and a realistic segment that links music with images through affective–semantic layers. In modeling emotional layers for the artistic segment, we found traditional 2D affective models inadequate, prompting us to propose a more interpretable hybrid-emotional rating system that serves both experts and non-experts. For the realistic segment, we utilize a web-based dataset with tags, dividing tag information into semantic and affective components to ensure a balanced and nuanced representation of music–image correlation. We conducted an in-depth statistical analysis and user study to evaluate our dataset’s effectiveness and applicability for AI-driven understanding. This work provides a foundation for advanced explorations into the complex relationships between auditory and visual art modalities, advancing the development of more sophisticated cross-modal AI systems.
Optimization of the Monte Carlo Simulation to Improve the Calibration Uncertainty of Volume Meters for Hydrocarbons Custody Transfer
Authors: García-Berrocal Agustín , Montalvo Cristina , Carmona Pablo , García-Álvarez Raúl
Published: December 2024

Since its publication by ISO in 1993, the GUM document has become the model to follow for the estimation of measurement uncertainty in the industry. However, the document itself recognizes its limitations in justifying the level of coverage. The calibration of volumetric meters for the custody transfer of liquid products can be affected by these limitations. The objective of this work is to calculate the calibration uncertainty of such meters by applying the Monte Carlo method of Supplement 1 of the GUM document (GUM-S1). In this way, the use of the classic GUM method is avoided. Therefore, the adaptive implementation of the Monte Carlo method (AMCM) has been applied to optimize the calibration uncertainty of a positive displacement meter against a standard tank in an ISO 17025 accredited volume laboratory. These meters are used for custody transfer in liquid hydrocarbon logistics where any reduction in the uncertainty estimation may have an important economic impact. Several innovations are proposed when applying AMCM; regulation of AMCM convergence by applying the Student’s t-distribution, validation of repeatability and filtering of outliers by performing 50 iterations of the AMCM, and characterization of the measurand’s Probability Density Function (PDF) which results in a Flatten–Gaussian. This work proves that the GUM method does not assign the correct PDF. The uncertainty estimation is reduced by 7.1% compared to the GUM method.
Moving Healthcare AI Support Systems for Visually Detectable Diseases to Constrained Devices
Authors: Watt Tess , Chrysoulas Christos , Barclay Peter J. , El Boudani Brahim , Kalliatakis Grigorios
Published: December 2024

Image classification usually requires connectivity and access to the cloud, which is often limited in many parts of the world, including hard-to-reach rural areas. Tiny machine learning (tinyML) aims to solve this problem by hosting artificial intelligence (AI) assistants on constrained devices, eliminating connectivity issues by processing data within the device itself, without Internet or cloud access. This study explores the use of tinyML to provide healthcare support with low-spec devices in low-connectivity environments, focusing on the diagnosis of skin diseases and the ethical use of AI assistants in a healthcare setting. To investigate this, images of skin lesions were used to train a model for classifying visually detectable diseases (VDDs). The model weights were then offloaded to a Raspberry Pi with a webcam attached, to be used for the classification of skin lesions without Internet access. It was found that the developed prototype achieved a test accuracy of 78% when trained on the HAM10000 dataset, and a test accuracy of 85% when trained on the ISIC 2020 Challenge dataset.
Integrated Spatio-Temporal Graph Neural Network for Traffic Forecasting
Authors: Singh Vandana , Sahana Sudip Kumar , Bhattacharjee Vandana
Published: December 2024

This research introduces integrated spatio-temporal graph convolutional networks (ISTGCN), designed to capture complex spatiotemporal traffic data patterns. The proposed model integrates multi-layer graph convolutional networks (GCNs) to address dependencies in temporal and spatial traffic dynamics. Specifically, ISTGCN integrates graph convolutional layers and convolutional sequence learning layers within multiple spatiotemporal convolutional blocks. For capturing the temporal aspect, predictive graph modeling for road network traffic at particular time stamps is performed. To integrate the spatial information, graph convolution operations are applied. The proposed model was validated on real-life datasets, and the experimental results demonstrate that ISTGCN achieves significantly lower error values across key metrics—RMSE, MAE, and MAPE.
The Reverse Lunge: A Descriptive Electromyographic Study
Authors: Hoogenboom Barbara J. , Ferguson Madison , Krauss Zac , Tran Stephanie
Published: December 2024

Limited studies exist examining the reverse lunge. The purpose of this study was to describe the activation of the rectus femoris (RF), biceps femoris (BF), gluteus medius (GMed), and gluteus maximus (GMax) of both limbs during a bodyweight reverse lunge movement. A secondary purpose was to describe the phases of the stationary (non-moving) and lead (moving) limbs during the reverse lunge. Surface electromyography (EMG) was used to record the activity of the target muscles in 20 healthy adults (10 male, 10 female; aged 22–25). Root mean squared values for mean maximum and average percent activation normalized to maximum voluntary isometric contraction (MVIC) activation were calculated. Descriptive terminology was created to describe the phases of the lunge for both limbs. The mean maximum percentage of muscle activation for the RF and BF was greater in the lead limb, while GMed and GMax activations were greater in the stationary limb. Only the lead limb RF and stationary limb GMed reached a strengthening stimulus in mean maximum percentage measurements. Clinically, it may be important to consider when each muscle is maximally active and at what percentage of its MVIC to properly prescribe the reverse lunge in a safe manner.
Predicting the Speed of Chinese Elite Cross-Country Skiers: A Neural Network Approach Based on the Measurement of Key Biomechanical and Physiological Parameters
Authors: Shi Huijuan , Zhu Xiaolan , Zhao Shuang , Holmberg Hans-Christer , Liu Hui
Published: December 2024

This study aimed to identify key biomechanical and physiological parameters affecting cross-country skiing performance and develop a neural network model for predicting skiing speed. Biomechanical attributes (cycle length and rate, vertical displacement of the center of mass, and angular kinematics) and physiological factors (maximal oxygen uptake, 30 s anaerobic power), along with physical fitness (standing long jump, pull-ups) were assessed for 82 cross-country skiers (52 men and 30 women). Random forest analysis was utilized to identify the most influential parameters on skiing speed, which were subsequently used as input parameters to develop a neural network aimed at predicting this speed. The findings identified the primary predictors of skiing speed as the cycle length on both flat and uphill terrains, vertical displacement of the center of mass during the poling phase on uphill terrain, maximal oxygen uptake, and 30 s anaerobic power. The developed neural network model demonstrated high precision in predicting skiing speeds, evidenced by a strong correlation with actual speeds (correlation coefficient of 0.953) and 97.1% of predictions falling within the 95% Bland–Altman agreement limits, affirming the model’s reliability and effectiveness in forecasting skiing performance.
A Smart Motor Rehabilitation System Based on the Internet of Things and Humanoid Robotics
Authors: Moghbelan Yasamin , Esposito Alfonso , Zyrianoff Ivan , Spaletta Giulia , Borgo Stefano , Masolo Claudio , Ballarin Fabiana , Seidita Valeria , Toni Roberto , Barbaro Fulvio , Di Conza Giusy , Quartulli Francesca Pia , Di Felice Marco
Published: December 2024

The Internet of Things (IoT) is gaining increasing attention in healthcare due to its potential to enable continuous monitoring of patients, both at home and in controlled medical environments. In this paper, we explore the integration of IoT with human-robotics in the context of motor rehabilitation for groups of patients performing moderate physical routines, focused on balance, stretching, and posture. Specifically, we propose the I-TROPHYTS framework, which introduces a step-change in motor rehabilitation by advancing towards more sustainable medical services and personalized diagnostics. Our framework leverages wearable sensors to monitor patients’ vital signs and edge computing to detect and estimate motor routines. In addition, it incorporates a humanoid robot that mimics the actions of a physiotherapist, adapting motor routines in real-time based on the patient’s condition. All data from physiotherapy sessions are modeled using an ontology, enabling automatic reasoning and planning of robot actions. In this paper, we present the architecture of the proposed framework, which spans four layers, and discuss its enabling components. Furthermore, we detail the current deployment of the IoT system for patient monitoring and automatic identification of motor routines via Machine Learning techniques. Our experimental results, collected from a group of volunteers performing balance and stretching exercises, demonstrate that we can achieve nearly 100% accuracy in distinguishing between shoulder abduction and shoulder flexion, using Inertial Measurement Unit data from wearable IoT devices placed on the wrist and elbow of the test subjects.
The Influence of Grain Size on the Abrasive Wear Resistance of Hardox 500 Steel
Authors: Zemlik Martyna , Białobrzeska Beata , Stachowicz Mateusz , Hanszke Jakub
Published: December 2024

High-strength martensitic steels with boron are among the leading materials widely recognized for their exceptional resistance to abrasive wear. These steels exhibit some of the highest strength indices among bulk steels, a result of their specific chemical composition, thermomechanical rolling processes at the steel mill, and the use of pure, high-quality ores. With hardness values ranging from 400 to 650 HBW, they are ideal for demanding applications such as excavator buckets, plow blades, shafts, wear-resistant bars, and container liners. One critical microstructural property contributing to their high mechanical performance is the prior austenite grain size (PAG). A finer grain structure is associated with enhanced plasticity, and plastic deformation plays a significant role in abrasive wear mechanisms. However, this relationship between grain size and wear resistance is not well-documented in the literature, with few studies providing specific quantitative data. To address this gap, the authors conducted a study to examine the effect of prior austenite grain size on wear resistance when exposed to loose abrasive electrofused alumina no. 90. The findings indicate that applying targeted heat treatment can increase hardness by 58 Brinell units compared to the as-delivered condition. Moreover, as grain size increases from 18 µm to 130 µm, the relative abrasive wear resistance coefficient Kb decreases from 1.00 (for Hardox 500 steel in its as-delivered state) to 0.80 for austenitized material treated at 1200 °C.
Thermal Stability and Entropy Generation Analysis for Combustible Third-Grade Fluid Flow Through a Slant Channel: A Spectral Study
Authors: Thosago Kgomotshwana Frans , Banjo Peace Oluwalonimi , Rundora Lazarus , Adesanya Samuel Olumide
Published: December 2024

This paper addresses the mixed convective flow and heat transfer in combustible third-grade fluids through a slant porous channel filled with permeable materials. The fluid layer in contact with the channel wall is exposed to asymmetrical slippage and isothermal conditions. We employ the spectral Chebyshev collocation method (SCCM) to the coupled nonlinear flow governing equations and validate using the Shooting–Runge–Kutta method (RK4). Fluid velocity and temperature profiles, local entropy generation, and irreversibility ratio are computed and analyzed quantitatively and qualitatively. The convergence of the numerical method was demonstrated. The flow and thermal effects results, entropy generation rate, and Bejan number revealed fascinating manifestations that have profound implications in the design of thermo-mechanical systems. In particular, the thermal analysis results are pertinent to optimal system designs that achieve efficient energy utilization.
Cultivar-Dependent Effect of Silicon Foliar Application on Olive Fruit Yield, Morphology, and Olive Oil Quality Parameters
Authors: Franić Mario , Pasković Igor , Goreta Ban Smiljana , Marcelić Šime , Lukić Marina , Rončević Sanda , Nemet Ivan , Kosić Urška , Soldo Barbara , Polić Pasković Marija
Published: December 2024

Silicon is one of the most abundant elements in the Earth’s crust and, although it is not an essential element for plant growth, it is considered beneficial as it can help in defense against biotic and abiotic stresses. Research on the effects of foliar sprays containing silicon has been well documented for different plants. However, in olive plants there is considerably less research focused on silicon soluble foliar formulations, which differs from the application of inert materials, like kaolin. The purpose of this study was to evaluate the effects of three increasing levels of foliar-applied soluble silicon on the characteristics of olive fruit and olive oil parameters. Fruit morphology, contents of multiple polyphenols, fatty acid profiles and mineral content in olive oil, olive oil quality parameters, fruit yield, and olive oil production parameters were assessed. Results show significant effects of silicon treatments on palmitic, palmitoleic, and linoleic acids and on the content of mono- and polyunsaturated fatty acids. Polyphenols were generally more influenced by the cultivar rather than by silicon. Apigenin, phenolic acids, and flavonoids were impacted by silicon treatments. Fruit morphology was affected by silicon treatment and, generally, parameters (fruit and seed length, width, and mass) increased at higher silicon application. This was concomitantly seen in both fruit and extra virgin olive oil (EVOO) yield increase, but only for the Leccino cultivar, suggesting specific cultivar x treatment interplay for those traits. Increases in mineral contents in olive oil due to Si treatments were not found, except for silicon, where Si2 and Si3 treatments yielded higher silicon content in olive oil compared to control. Results of this study indicate that Silicon Foliar Application could be used to enhance olive yield and only slightly modifies the fatty acid composition of olive oil and the content of some of the phenols. Although silicon application did affect several parameters, the effect of cultivar was more pronounced in affecting most of the parameters. Further research could be driven towards the effect of foliar silicon on these parameters under environmental stress factors.
Effect of Spirulina Nigrita® on Exercise-Induced Oxidative Stress in Humans: A Breath Analysis Study
Authors: Krokidas Anastasios , Mikedi Katerina , Gakis Athanasios G. , Methenitis Spyridon , Nomikos Tzortzis , Krokida Magdalini
Published: December 2024

In the current work, the non-invasive approach of breath analysis is implemented for the first time in an eccentric exercise protocol that investigated the effect of spirulina supplementation on exercise-induced oxidative stress. We assessed whether volatile alkanes in exhaled breath can serve as alternative biomarkers of oxidative stress. A randomized, double-blinded, placebo-controlled, crossover supplementation study was carried out enrolling 14 participants. The volunteers consumed 42 mg·kg−1 body weight of either Spirulina Nigrita® or maltodextrin, as a placebo, daily for 15 days. Afterward, they followed a damaging eccentric exercise protocol of the upper limbs. Expired breath samples were collected from them just before supplementation (baseline measurement), prior to exercise, and 1 h, 24 h, 48 h, and 72 h after exercise. The samples were analyzed by Gas Chromatography/Mass Spectrometry (GC-MS) coupled with a thermal desorption unit (TDU) to determine the alveolar gradient (AG) of several alkanes, C5–C14, that are known to be related to oxidative stress. Apart from breath analysis, TBARSs were also determined as a crude marker of lipid peroxidation. Two-way repeated measures ANOVA tests were applied to the alkanes’ AGs between the spirulina (SPI) and placebo (PL) groups across time. In the PL group, a trend of increasing almost all alkanes immediately after exercise, with a gradual return to pre-exercise levels up to 72 h later was revealed. A statistically significant time effect was observed for 2-methylhexane, 3-methylhexane, heptane, octane, and undecane. The administration of spirulina appeared to reduce the increases in alkanes after exercise, and a statistically significant attenuation was observed for 2-methylpentane and 2-methylhexane. An examination of TBARSs confirmed that the reduced increases observed in the SPI group were due to changes in lipid peroxidation, while a positive correlation between the iAUC of TBARSs and that of 2-methylhexane and 3-methylhexane was revealed. In conclusion, the analysis of volatile alkanes in exhaled breath may serve as an attractive alternative for assessing redox changes after eccentric exercise compared to traditional blood biomarkers.
Governance and Dynamic Efficiency with Network Structure in the Brazilian Natural Gas Utilities
Authors: Marques Francisco Roldineli Varela , Barbosa Alexandro , Simões Pedro , de Oliveira Kelly Cristina
Published: December 2024

The objective of this work is to analyze the relevance of governance (corporate and ownership concentration) for the divisional inter-temporal dynamic efficiency in piped natural gas utilities in Brazil. The main innovative contribution of this work is the application of inter-temporal (dynamic) efficiency analysis with network structure in the first stage, in this case, the ‘Dynamic DEA (Data Envelopment Analysis) with network structure: A slacks-based–DNSBM (Dynamic Network Slacks-Based Measure)’, in which two divisional interactions δok∗ (technical–operational and economic–financial division) between τot∗ periods and divisional ρokt∗ periods are reflected in the overall efficiency scores θo∗, representing an approach not yet explored by the previous literature on the sector and subject investigated. The database used corresponds to 21 Brazilian natural gas utilities in the form of a balanced data panel, which were collected for the period 2014–2019. The second stage (explanatory) was estimated through the panel with random effects to identify the relationship between governance and efficiency, considering certain context factors. The results show that the average general efficiency was 74.96%, resulting from the interactions between the average efficiency rates of 72.21% of the technical–operational division and 82.03% of the economic–financial division, and suggest that the corporate governance index and ownership (public or private) are not relevant factors for the efficiency results studied.
Fermented Gold Kiwifruit Protects Mice Against Non-Alcoholic Fatty Liver Disease in a High-Fat Diet Model
Authors: Choi Jihye , Choi Hwal , Jang Yuseong , Paik Hyeon-Gi , Kwon Hyuck-Se , Kwon Jungkee
Published: December 2024

Gold kiwifruit is known for its high vitamin C content and various benefits. This study investigated the effects and molecular mechanisms of fermented gold kiwifruit (FGK) in a mouse model of high-fat diet (HFD)-induced obesity and hepatic steatosis. FGK powder was prepared using five strains of lactic acid bacteria: L. paracasei, Lc. lactis, L. acidophilus, L. casei, and L. helveticus. ICR mice were fed an HFD for 8 weeks to induce obesity and hepatic steatosis, and FGK supplementation was evaluated for its therapeutic potential. FGK administration significantly reduced serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total cholesterol, triglyceride, and glucose compared to the HFD-only group. Histopathological analysis showed that FGK reduced lipid accumulation and hepatic lesions, as confirmed by hematoxylin and eosin (H&E) staining. Furthermore, administration of FGK activated the sirtuin 1(SIRT1)/adenosine monophosphate-activated protein kinase (AMPK) pathway and inhibited expression of the pro-inflammatory cytokines such as IL-1β, IL-6, and TNF-α in liver tissue. These findings suggest that FGK could reduce the severity of non-alcoholic fatty liver disease (NAFLD) by inhibiting fat synthesis, promoting fat breakdown, and suppressing inflammation in HFD-induced obese mice.
Comprehensive Investigation of Partitioned Thermal Barrier Coating: Impact on Thermal and Mechanical Stresses, and Performance Enhancement in Diesel Engines
Authors: Topkaya Hüsna , Brewster M. Quinn , Aydın Hüseyin
Published: December 2024

The thermal barrier coating method is applied using materials with low thermal conductivity to increase the efficiency and improve the emissions of internal combustion engines. However, coated surfaces may be damaged due to the high thermal and pressure stresses encountered by the piston surface in the combustion chamber during engine operation. In this study, experiments and analysis were carried out for four piston models to analyze the coating layer and increase its strength: two partially coated piston surface models, a fully coated model, and an uncoated piston model. The results of the transient thermal analysis revealed that the fully coated piston model exhibited the highest surface temperature. Additionally, heat losses were observed to be lower in the fully coated model compared to the other piston models. Partially coated piston models exhibited lower heat flux on the coated surface but higher heat flux on the uncoated combustion chamber surfaces. Combustion analysis indicated that the fully coated piston model exhibited the highest in-cylinder temperature and pressure values, while the uncoated model had the lowest values. When comparing heat transfer rates on the walls, the uncoated piston model exhibited the highest transfer, whereas the fully coated piston model exhibited the lowest. Finally, the fully coated piston demonstrated the highest combustion efficiency.
Energy Trading in Local Energy Markets: A Comprehensive Review of Models, Solution Strategies, and Machine Learning Approaches
Authors: Khaskheli Sania , Anvari-Moghaddam Amjad
Published: December 2024

The increasing adoption of renewable energy sources and the emergence of distributed generation have significantly transformed the traditional energy landscape, leading to the rise of local energy markets. These markets facilitate decentralized energy trading among different market participants at the community level, fostering greater energy autonomy and sustainability. As local energy markets gain momentum, the application of artificial intelligence techniques, particularly reinforcement learning, has gained substantial interest in optimizing energy trading strategies by interacting with the environment and maximizing the rewards by addressing the decision complexities by learning. This paper comprehensively reviews the different energy trading projects initiated at the global level and machine learning approaches and solution strategies for local energy markets. State-of-the-art reinforcement learning algorithms are classified into model-free and model-based methods. This classification examines various algorithms for energy transactions considering the agent type, learning methods, policy, state space, action space, and action selection for state, action, and reward function outputs. The findings of this work will serve as a valuable resource for researchers, stakeholders, and policymakers to accelerate the adoption of the local energy market for a more efficient, sustainable, and resilient energy future.
Stability Analysis of the Landfill Slope with an Engineered Berm Under Composite Failure Mode
Authors: Ruan Xiaobo , Li Yulong , Luo Yu-Shan , Wang Hongwei , Chen Jiajia , Ding Zhongjun
Published: December 2024

In order to increase the capacity of landfills while ensuring a certain degree of stability of such structures, an engineered berm is typically constructed at the front slope of the landfill. For this type of landfill slopes, this paper primarily focuses on the construction and verification of stability assessment models for such structures. Initially, the calculation models of the safety factor were established, considering over and under berm failure modes separately. Subsequently, through error analysis, it was determined that it is feasible to evaluate the stability of this type of landfills by substituting the true safety factor with the average safety factor obtained from the calculation model. The analysis for parameters and slip surfaces was then conducted to investigate the impact of parameters associated with the engineered berm on the landfill slope stability. Finally, a visual comparison and brief discussion were conducted on the average safety factors under translational and composite failure modes. Thus, the critical failure modes under specific working conditions can be reasonably ascertained, which holds significant practical implications for enhancing the reliability of stability assessment of such landfill slopes.
Interdisciplinary Urban Interventions: Fostering Social Justice Through Collaborative Research-Led Design in Architectural Education
Authors: Mehan Asma , Dominguez Natalia
Published: December 2024

This study aims to examine how interdisciplinary urban interventions within architectural education can effectively address social justice issues. Motivated by the growing need for inclusive and equitable urban spaces, this research explores the potential of collaborative design and participatory research methods to foster social awareness and community engagement. Focusing on student-led projects in cities such as Houston, San Diego, and Amsterdam, this study addresses social justice challenges across themes like Art Activism, Tactical Urbanism, environmental justice, and gender equity. Using case study analysis, digital mapping, and poster creation as core methodologies, the research demonstrates the value of multi-scalar, interdisciplinary approaches in tackling complex urban problems. The key findings highlight that integrating these approaches into architectural education promotes critical engagement with social justice issues, equipping students with practical skills for future professional challenges. The implications suggest that expanding this framework to diverse urban contexts could enhance its impact, offering a foundation for further studies on interdisciplinary design as a tool for urban equity.
Impact of Nitrogen Dioxide (NO2) Pollution on Asthma: The Case of Louisiana State (2005–2020)
Authors: Bhattarai Keshav , Lamsal Lok , Gyawali Madhu , Neupane Sujan , Gautam Shiva P. , Bakshi Arundhati , Yeager John
Published: December 2024

This study explores the connection between tropospheric nitrogen dioxide (NO2) vertical column density levels and asthma hospitalization cases in Louisiana from 2005 to 2020. Utilizing NO2 data from NASA’s Ozone Measurement Instrument (OMI) aboard the Aura satellite, the research integrates these atmospheric measurements with socioeconomic data at the census tract level. This study employs a generalized linear mixed model (GLIMMIX) with a logit link and Beta distribution to analyze the relationship between seasonal NO2 levels and asthma hospitalization cases during winter, fall, spring, and summer. By analyzing OMI data, this research quantifies seasonal variations in NO2 levels and their corresponding impact on asthma hospitalizations. The findings reveal a relationship between NO2 levels and asthma hospitalizations, particularly in communities with high Black and/or low-income populations, with the strongest effects observed during winter. Specifically, the analysis shows that, for each unit increase in NO2 levels, the odds of asthma-related hospitalizations increase by approximately 26.3% (p < 0.0001), with a 95% confidence interval ranging from 23.3% to 29.5%. Assuming a causal link between NO2 and asthma, these findings suggest that reducing NO2 emissions could alleviate healthcare burdens associated with respiratory diseases such as asthma.
Construction of Heavy-Duty Diesel Vehicle Atmospheric Pollutant Emission Inventory Based on Onboard Diagnosis Data
Authors: Chen Ting , Xiong Yangxin , Zhao Weidong , Lin Bo , He Zehuang , Tao Feiyang , Hu Xiang
Published: December 2024

Motor vehicles emit a large amount of air pollutants. NOx and particulate matter (PM) account for 53.2% and 74.7%, respectively, of vehicle emissions in China. Using the technical guidelines for compiling road vehicle emission inventories, the emission factors based on the onboard diagnostics (OBD) system of heavy-duty diesel vehicles are obtained. The trajectory of heavy-duty diesel vehicles is corrected using big data interpolation, and the correction coefficients for different vehicle speeds are fitted to calculate the corresponding correction factors. Simultaneously, the Weather Research and Forecasting model is used for the meteorological correction of emissions, a heavy-duty diesel vehicle emission inventory under the community multiscale air quality model is established, and the distribution characteristics of pollution emissions from heavy-duty diesel vehicles in Chengdu are analyzed at the time and space levels. Overall, the pollutant gasses emitted by heavy-duty diesel vehicles in Chengdu are largely concentrated at the city center. In 2023, the total annual emissions of the pollutants NOx, CO, fine PM, and volatile organic compounds from heavy-duty diesel vehicles in Chengdu were 10,590.60, 28,852.90, 686.18, and 657.60 tons, respectively. NOx and CO have the highest proportions among the major pollutants, accounting for 70.7% and 26%, respectively.
Normative Data of Extended High Frequency Audiometry in Normal Hearing Subjects with Different Aged Groups
Authors: Luengrungrus Kittiphorn , Thanawirattananit Panida , Teeramatwanich Watchareporn
Published: December 2024

Background/Objectives: Conventional audiometry assesses hearing in the frequency range of 250–8000 Hz, while humans can detect sounds from 20 to 20,000 Hz. Hearing sensitivity above 8000 Hz can be assessed through “Extended high-frequency audiometry (EHFA)”, which is useful for early detection and monitoring of hearing loss and counseling for tinnitus patients. Despite its usefulness, age significantly affects hearing sensitivity. Currently, there are no standard hearing thresholds in the EHF range categorized by age groups in Thailand. In this study, the aim was to determine normative EHFA data across different age groups in a healthy Thai population. Methods: This study included 134 participants aged 18–70 years, categorized into five age groups. All participants had normal hearing thresholds and type A tympanograms bilaterally. Following this, EHFA measurement was performed. Results: Across all age groups, there was an observed increase in median hearing thresholds as age increased. In comparison, no significant difference in median hearing thresholds was found between individuals aged 18–30 and >30–40 years. However, those over 40 years had significantly higher median thresholds across all frequencies compared to those under 40 years (p < 0.05). Based on these findings, we propose two new subgroups of 18–40 years and >40–70 years. Median hearing thresholds for those aged 18–40 was ≤20 dB HL across most frequencies, except at 16,000 Hz (30 dB HL). In the >40–70 age group, thresholds ranged from 20 dB HL at 9000 Hz to 70 dB HL at 14,000 and 16,000 Hz. However, no significant differences were found in hearing thresholds between sexes and ear sides. Conclusions: In this study, normative EHFA data were established for healthy Thai adults, appropriately divided into two groups (18–40 and >40–70 years) for clinical use. Further studies with more participants per age group are also needed to validate the results.
Salivary Cortisol Concentration Is an Objective Measure of the Physiological Response to Loud Music
Authors: Tomljenović Robert , Košec Andro , Kalogjera Livije , Ćelap Ivana , Marijančević Domagoj , Vagić Davor
Published: December 2024

Purpose: This study examines the potential associations between salivary cortisol concentrations and subjective stress test scores in healthy individuals subjected to sound-related, psychological, and physical stressors. Methods: This study employed a single-center observational cross-sectional design, with a sample size of 36 subjects recruited from a tertiary referral audiology center. Between 2023 and 2024, the study recruited subjects with normal hearing, baseline salivary cortisol levels, and subjective stress levels. The participants were requested to complete an STAI-Y1 questionnaire and provide salivary cortisol samples before and following exposure to sound-related, psychological, and physical stress tests. Results: Exposure to psychological and physical stressors significantly increased STAI-Y1 scores (Friedman’s test, χ2 = 57.118, df = 2, p = 0.377). This increase was greater than that observed in response to loud, favorite music (Friedman’s test, χ2 = 57.118, df = 2, p < 0.0001). The salivary cortisol concentration significantly increased in all three provocation tests (Friedman’s test, χ2 = 95.264, df = 5, p < 0.0001). Furthermore, there is no significant difference in salivary cortisol concentrations between the three pre-test and post-test measurement intervals, indicating a comparable stress-inducing pattern regardless of the nature of the stimulus (Friedman’s test, χ2 = 95.264, df = 5, p > 0.05). Conclusions: Exposure to loud favorite music increases salivary cortisol concentrations, as does acute physical and psychological stress. Interestingly, unlike psychological and physical stress, loud music was not objectively perceived as stress, which may mask the physiological signs of stress, potentially increasing the risk of both acute and chronic stress-related health outcomes.
From Fact Drafts to Operational Systems: Semantic Search in Legal Decisions Using Fact Drafts
Authors: Csányi Gergely Márk , Lakatos Dorina , Üveges István , Megyeri  Andrea , Vadász János Pál , Nagy Dániel , Vági Renátó
Published: December 2024

This research paper presents findings from an investigation in the semantic similarity search task within the legal domain, using a corpus of 1172 Hungarian court decisions. The study establishes the groundwork for an operational semantic similarity search system designed to identify cases with comparable facts using preliminary legal fact drafts. Evaluating such systems often poses significant challenges, given the need for thorough document checks, which can be costly and limit evaluation reusability. To address this, the study employs manually created fact drafts for legal cases, enabling reliable ranking of original cases within retrieved documents and quantitative comparison of various vectorization methods. The study compares twelve different text embedding solutions (the most recent became available just a few weeks before the manuscript was written) identifying Cohere’s embed-multilingual-v3.0, Beijing Academy of Artificial Intelligence’s bge-m3, Jina AI’s jina-embeddings-v3, OpenAI’s text-embedding-3-large, and Microsoft’s multilingual-e5-large models as top performers. To overcome the transformer-based models’ context window limitation, we investigated chunking, striding, and last chunk scaling techniques, with last chunk scaling significantly improving embedding quality. The results suggest that the effectiveness of striding varies based on token count. Notably, employing striding with 16 tokens yielded optimal results, representing 3.125% of the context window size for the best-performing models. Results also suggested that from the models having 8192 token long context window the bge-m3 model is superior compared to jina-embeddings-v3 and text-embedding-3-large models in capturing the relevant parts of a document if the text contains significant amount of noise. The validity of the approach was evaluated and confirmed by legal experts. These insights led to an operational semantic search system for a prominent legal content provider.
Polyamine Metabolism and Functions: Key Roles in Cellular Health and Disease
Authors: Rossi Marianna Nicoletta , Cervelli Manuela
Published: December 2024

The polyamines putrescine, spermidine, and spermine are polycations ubiquitously present in cells, where they exert pleiotropic functions in cellular mechanisms like proliferation, protein synthesis (through the hypusination of the transcription factor EIF5a), redox balance, autophagy, and different forms of cell death [...]