bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Sustainability of Miscanthus and Willow as Global Bioenergy Crops: Current and Future Climate Conditions (Part 1)
Authors: Abdalla Mohamed , Hastings Astley , Campbell Grant , Chen Heyu , Smith Pete
Published: December 2024

Miscanthus (Miscanthus × giganteus) and Willow (Salix spp.) are promising bioenergy crops due to their high biomass yields and adaptability to diverse climatic conditions. This study applies the MiscanFor/SalixFor models to assess the sustainability of these crops under current and future climate scenarios, focusing on biomass productivity, carbon intensity (CI), and energy use efficiency (EUE). Under present conditions, both crops show high productivity in tropical and subtropical regions, with Miscanthus generally outperforming Willow. Productivity declines in less favourable climates, emphasising the crops’ sensitivity to environmental factors at the regional scale. The average productivity for Miscanthus and Willow was 19.9 t/ha and 10.4 t/ha, respectively. Future climate scenarios (A1F1, representing world markets and fossil-fuel-intensive, and B1, representing global sustainability) project significant shifts, with northern and central regions becoming more viable for cultivation due to warmer temperatures and extended growing seasons. However, southern and arid regions may experience reduced productivity, reflecting the uneven impacts of climate change. Miscanthus and Willow are predicted to show productivity declines of 15% and 8% and 12% and 7% under A1F1 and B1, respectively. CI analysis reveals substantial spatial variability, with higher values in industrialised and temperate regions due to intensive agricultural practices. Future scenarios indicate increased CI in northern latitudes due to intensified land use, while certain Southern Hemisphere regions may stabilise or reduce CI through mitigation strategies. Under climate change, CI for Miscanthus is projected to increase by over 100%, while Willow shows an increase of 64% and 57% for A1F1 and B1, respectively. EUE patterns suggest that both crops perform optimally in tropical and subtropical climates. Miscanthus shows a slight advantage in EUE, though Willow demonstrates greater adaptability in temperate regions. Climate change is expected to reduce EUE for Miscanthus by 10% and 7% and for Willow by 9% and 6%. This study underscores the need for region-specific strategies to optimise the sustainability of bioenergy crops under changing climate conditions.
Soil Physicochemical and Metagenomic Analyses of Bacteria and Fungi: Toward Desert Truffle Cultivation in Saudi Arabia
Authors: Alhuthali Sakhr , Bello Suleiman K. , Bageel Ahmed M. , Shori Amal Bakr , Bataweel Noor M. , Al-Hejin Ahmed M. , Al-Qarawi Abdulaziz A. , Thomas Paul W.
Published: December 2024

Researchers are exploring plant-based protein sources to address both malnutrition and climate change. Desert truffles are rich in protein (i.e., ≈20%) and offer a cheaper and more environmentally friendly option. However, desert truffle cultivation is limited by environmental factors like rainfall and soil properties. This study was conducted to understand the soil conditions and microbiomes associated with desert truffles growing in parts of Saudi Arabia. Based on yield, the truffle fields were categorized into high-yield (≈50 kg/ha annually) and low-yield (≈2 kg/ha annually) truffle farms. Truffle yield differences were not significantly influenced by most soil physicochemical variables except for total nitrogen (negatively correlated). However, low soil nitrogen alone did not explain yield disparities, as wild truffle fields with low nitrogen also produced fewer truffles. In contrast, truffle yield showed a strong positive correlation with calcium carbonate content. We hypothesized that the unmeasured irrigation schedule was most likely behind the truffle yield differences especially during fruiting season. Furthermore, the high-yield farms had lower bacteria richness and diversity than the low-yield farms. Environmentally important bacteria genera such as Geodermatophilus and Rubrobacter were found in both farms, although more were found in the low-yield one, whereas more Streptomyces were found in the high-yield farm. In addition, fungal alpha diversity was higher in the high-yield farm with the dominance of Sordariomycetes, Dothideomycetes, Eurotiomycetes, and Glomeromycetes.
Carbon and Nitrogen Accumulation in Roots of Signal Grass–Forage Peanut Intercropped Pastures at Varying Planting Spacings
Authors: dos Anjos Albert José , de Souza Igor Alexandre , Coutinho Danielle Nascimento , da Silveira Tâmara Chagas , Macêdo Alberto Jefferson da Silva , Alves Wagner Sousa , Pereira Odilon Gomes , Dubeux José Carlos Batista , Ribeiro Karina Guimarães
Published: December 2024

This study highlights the potential of grass–legume intercropping systems in enhancing soil carbon sequestration and cycling nutrients, providing ecological support for sustainable agriculture. This study evaluated the chemical composition and root biomass of signal grass (Urochloa decumbens cv. Basilisk) pasture grown in monoculture or intercropped with forage peanut (Arachis pintoi cv. Belmonte) under different row spacings (40, 50, 60, 70, and 80 cm), 4–5 years after establishment. The experiment was conducted in a randomized block design with four replicates under intermittent sheep grazing. Results (p < 0.05) indicated that root biomass was higher in the intercropped pastures (6752 to 11,167 kg OM ha−1) than in the monoculture (3696 kg OM ha−1). Carbon (C) and N stored in root biomass were also influenced by the row spacings, with narrower spacings, particularly 40 cm (1282 kg C ha−1) and 50 cm (1424 kg C ha−1), showing higher C storage than in the monoculture (509 kg C ha−1). Similarly, the 40 cm (122 kg N ha−1) and 50 cm (138 kg N ha−1) spacings showed higher N accumulation in root biomass than the monoculture (38.9 kg N ha−1). These spacing also reduced C/N and lignin/ADIN ratios, which enhanced nitrogen cycling efficiency. Based on these results, 40 and 50 cm spacings are recommended for intercropped pastures, as they optimize C and N accumulation and nutrient cycling, and support sustainable pasture management.
Frailty and Mortality Risk Among Dogs with Extreme Longevity: Development and Predictive Validity of a Clinical Frailty Index in the Exceptional Aging in Rottweilers Study
Authors: Waters David J. , Maras Aimee H. , Fu Rong , Carrillo Andres E. , Chiang Emily C. , Suckow Cheri L.
Published: December 2024

Frailty refers to a state of increased vulnerability to mortality and other adverse outcomes as a consequence of age-related decline in physiologic reserve and function. Comparative biomedical scientists are relied upon to innovate approaches to enhance understanding of the similarities and differences between humans and other animal species that can impact healthy aging. The research aim of this study was to develop a clinical frailty index (FI) in the Exceptional Aging in Rottweilers Study (EARS) and test its ability to predict all-cause mortality in elderly dogs. EARS is an ongoing lifetime cohort study of pet dogs with extreme longevity living in North America. Living 30% longer than the breed average, these dogs represent the canine counterpart to human centenarians. A 34-item FI (EARS-FI) was constructed to assess deficit accumulation using clinical data collected by telephone interviews with owners of 93 dogs with extreme longevity. Health deficits across multiple domains, including cognitive and sensory, cardiovascular and endocrine, and mobility, were included. The association between EARS-FI and subsequent mortality was tested in Kaplan-Meier survival analysis and in age-adjusted Cox proportional hazard models. Median (interquartile range) EARS-FI was 0.43 (0.38–0.50), and the estimated frailty limit was 0.68, consistent with data reported in humans with extreme longevity. Frailty index increased with increasing chronological age (p < 0.001). Deficit accumulation was significantly associated with increased mortality risk. Age-adjusted hazard ratio for mortality per 0.01 unit increase in FI was 1.05 (95%CI, 1.02–1.08; p = 0.001). This work provides the first demonstration of a strong association between frailty and mortality risk in pet dogs with extreme longevity. Notably, EARS-FI showed key features observed in the evaluation of frailty in aging human populations: heterogeneity, increase with chronological age, and estimated limit of <0.7. Validated here as a predictor of mortality in aged pet dogs, EARS-FI offers a useful tool for further comparative analyses of the linkages between deficit accumulation, mortality, and other adverse health outcomes.
Methane Emission of Italian Mediterranean Buffaloes Measured Using a Laser Detector During a Lactation Cycle
Authors: Meo Zilio David , Iacurto Miriam , Cenci Francesco , Steri Roberto
Published: December 2024

In Italy, the number of farmed dairy buffaloes rose up to approximately 436,000 heads in 2023 (+22% in the last 15 years), a fourfold increase compared to the 1980s, due to the growing market interest in mozzarella cheese. The increased demand for mozzarella cheese, in turn, requires higher production, which can result in increased methane emission from the sector. Therefore, it is necessary to establish mitigation and selection schemes for low-emission strategies. The current study aimed to highlight sources of variation in methane emission from lactating Italian Mediterranean buffaloes measured using a laser methane detector in order to identify practical and methodological aspects to consider when designing experiments focused on methane emission evaluation. Methane (CH4), exhaled from 60 cows, was recorded twice a day during milking, over two weeks per month for at least three months throughout a whole lactation cycle. The animal (individual), days in milk, parity, month, operator, milking entry order, and milking session effects were significant for methane emission (p < 0.0001). Our results showed that laser methane detector may be used as a rapid tool for methane emission studies and highlighted which factors can account for individual measures. This instrument is easy to use, fast, versatile, and not too expensive. These characteristics make it suitable for large-scale herd screening and monitoring.
Understanding the Causes of Keel Bone Damage and Its Effects on the Welfare of Laying Hens
Authors: Li Xin , Cai Xia , Wang Xiaoliang , Zhu Lihui , Yan Huaxiang , Yao Junfeng , Yang Changsuo
Published: December 2024

Keel bone damage (KBD) is a prominent concern within the realm of the egg-laying industry, exerting substantial impacts on the welfare and productivity of laying hens. This comprehensive review undertakes a detailed exploration of the diverse factors contributing to KBD, such as inadequate calcium sources in the medullary bone, genetic factors, nutritional deficiencies, and physical stressors. The consequences of KBD on production performance, stress and inflammation levels, and the physical and chemical properties of the keel are meticulously examined. Additionally, the review evaluates the existing methods for assessing KBD, including keel curvature scoring, imaging techniques, palpation, biomechanical testing, behavioral observations, and biochemical markers. Finally, management strategies, including nutritional adjustments, genetic selection, and environmental modifications, are proposed to potentially mitigate the prevalence and severity of KBD, thereby aiming to enhance the welfare and productivity of laying hens.
The Bacterial Cell Wall Components Lipopolysaccharide and Peptidoglycan Initiate Divergent Local Tissue and Systemic Inflammatory Response Profiles in the Chicken Model
Authors: Byrne Kristen A. , Erf Gisela F.
Published: December 2024

The innate immune system plays an important role in the defense against pathogens, whereby the ability to rapidly mount an effective inflammatory response is critical in the elimination/containment of the infection. To better understand the nature of the inflammatory responses to bacterial components in chickens, we used the growing feather (GF) cutaneous bioassay together with blood sampling to examine the local and systemic inflammatory responses initiated by intradermal (i.d.) GF-pulp injection of lipopolysaccharide (LPS) from Salmonella Typhimurium or peptidoglycan (PGN) from Staphylococcus aureus. Three studies were conducted in egg-type chickens between 9 and 15 weeks of age; Study 1 and 2 examined the leukocyte response profiles to a 100-fold dose range of LPS or PGN over 24 h or 7 d, respectively; Study 3 examined the leukocyte- and cytokine mRNA-profiles in pulps in response to LPS and PGN concurrently over 72 h. I.d. injection of LPS stimulated a heterophil and monocyte/macrophage dominated response in both GF-pulps and blood that was resolved by 48–72 h and differed based on dose administered. The inflammatory response stimulated by PGN was characterized by rapid infiltration of lymphocytes in GF-pulps with sustained high levels of T and B cells over 5–7 d and was neither affected by PGN dose nor reflected in the blood. Limited cytokine transcriptome analyses did not reveal differences that could explain the divergent response profiles to LPS versus PGN. More research is needed to understand the mechanisms underlying the divergent inflammatory responses to LPS and PGN in chickens.
Treatment of Periprosthetic Joint Infection with Intravenous Vancomycin: Do We Hit the Target?
Authors: Haglund Rasmus , Tornberg Ulrika , Claesson Ann-Charlotte , Freyhult Eva , Hailer Nils P.
Published: December 2024

Background/objectives: Vancomycin is commonly used in the treatment of periprosthetic joint infection (PJI), and trough concentrations are measured to ascertain that they are within the therapeutic range. It has not been investigated what proportion of vancomycin concentrations during treatment of PJI patients is accurately within this range, how many dose adjustments are commonly needed, and which patient factors predispose towards aberrations from the desired range. Method: In this single-center cohort study, we investigated vancomycin trough concentrations in 108 patients with surgically treated PJI who received IV administered vancomycin treatment post-operatively. Patients were identified in our local arthroplasty register, and data beyond what was available in the register were collected from electronic medical charts. Results: Of the final study cohort, 41% were women, and the median age was 71 (IQR 63–79) years. Most patients had PJI of the hip (73%), the majority (54%) underwent a debridement, antibiotics and implant retention (DAIR) procedure prior to vancomycin treatment, and 39% received vancomycin-loaded bone cement during the preceding revision procedure. Of 791 vancomycin trough measurements, only 58.2% were within the target range of 15–20 mg/L, 18.5% were below, and 23.4% were above. A total of 71% of all patients required at least one dose adjustment, and the median length of vancomycin treatment was 8 days. We observed positive correlations of vancomycin trough concentrations with both age (Spearman’s rho = 0.35, p < 0.001) and pre-treatment creatinine concentrations (Spearman’s rho = 0.34, p < 0.001), but no statistically significant difference between patients who had received vancomycin-loaded bone cement and those who had not. Conclusions: In our PJI patients, a high proportion of vancomycin trough concentrations were outside the therapeutic range, despite adherence to local and national guidelines. We can also confirm that caution needs to be exerted in patients of advanced age and those with compromised kidney function. Alternative broad-spectrum antibiotics that do not require as extensive therapeutic drug monitoring should be further explored.
Striking Cardioprotective Effects of an Adiponectin Receptor Agonist in an Aged Mouse Model of Duchenne Muscular Dystrophy
Authors: Abou-Samra Michel , Dubuisson Nicolas , Marino Alice , Selvais Camille M. , Romain Versele , Davis-López de Carrizosa Maria A. , Noel Laurence , Beauloye Christophe , Brichard Sonia M. , Horman Sandrine
Published: December 2024

Adiponectin (ApN) is a hormone with potent effects on various tissues. We previously demonstrated its ability to counteract Duchenne muscular dystrophy (DMD), a severe muscle disorder. However, its therapeutic use is limited. AdipoRon, an orally active ApN mimic, offers a promising alternative. While cardiomyopathy is the primary cause of mortality in DMD, the effects of ApN or AdipoRon on dystrophic hearts have not been investigated. Our recent findings demonstrated the significant protective effects of AdipoRon on dystrophic skeletal muscle. In this study, we investigated whether AdipoRon effects could be extended to dystrophic hearts. As cardiomyopathy develops late in mdx mice (DMD mouse model), 14-month-old mdx mice were orally treated for two months with AdipoRon at a dose of 50 mg/kg/day and then compared with untreated mdx and wild-type (WT) controls. Echocardiography revealed cardiac dysfunction and ventricular hypertrophy in mdx mice, which were fully reversed in AdipoRon-treated mice. AdipoRon also reduced markers of cardiac inflammation, oxidative stress, hypertrophy, and fibrosis while enhancing mitochondrial biogenesis via ApN receptor-1 and CAMKK2/AMPK pathways. Remarkably, treated mice also showed improved skeletal muscle strength and endurance. By offering protection to both cardiac and skeletal muscles, AdipoRon holds potential as a comprehensive therapeutic strategy for better managing DMD.
Polyphenol-Derived Microbiota Metabolites and Cardiovascular Health: A Concise Review of Human Studies
Authors: da C. Pinaffi-Langley Ana Clara , Tarantini Stefano , Hord Norman G. , Yabluchanskiy Andriy
Published: December 2024

Polyphenols, plant-derived secondary metabolites, play crucial roles in plant stress responses, growth regulation, and environmental interactions. In humans, polyphenols are associated with various health benefits, particularly in cardiometabolic health. Despite growing evidence of polyphenols’ health-promoting effects, their mechanisms remain poorly understood due to high interindividual variability in bioavailability and metabolism. Recent research highlights the bidirectional relationship between dietary polyphenols and the gut microbiota, which can influence polyphenol metabolism and, conversely, be modulated by polyphenol intake. In this concise review, we summarized recent advances in this area, with a special focus on isoflavones and ellagitannins and their corresponding metabotypes, and their effect on cardiovascular health. Human observational studies published in the past 10 years provide evidence for a consistent association of isoflavones and ellagitannins and their metabotypes with better cardiovascular risk factors. However, interventional studies with dietary polyphenols or isolated microbial metabolites indicate that the polyphenol–gut microbiota interrelationship is complex and not yet fully elucidated. Finally, we highlighted various pending research questions that will help identify effective targets for intervention with precision nutrition, thus maximizing individual responses to dietary and lifestyle interventions and improving human health.
Polylactic Acid/Bamboo Leaf Extract Electrospun Mats with Antioxidant Activity for Food Packaging Applications
Authors: Lopresti Francesco , Capuana Elisa , Serio Graziella , Gentile Carla , Botta Luigi
Published: December 2024

This study focuses on developing an active and biodegradable packaging using electrospinning, with polylactic acid (PLA) as the matrix and bamboo leaf extract (BLE) as the antioxidant compound. The research systematically evaluates the relationship among process parameters, material properties, and structure. The electrospun membranes were produced using different BLE contents (10 wt%, 20 wt%, 30 wt%, and 40 wt%) and characterized by their morphology, mechanical properties, wettability, and antioxidant activity. Scanning electron microscopy (SEM) revealed BLE’s influence on fiber morphology, with a slight increase in diameter in PLA/BLE at 10% and 20%, attributed to higher viscosity. Conversely, PLA/BLE 30% and 40% showed a mild reduction in fiber diameter likely due to polyphenols’ capacity to enhance PLA chain mobility. Mechanical tests indicated proportional reductions in modulus, maximum stress, and strain at break, upon increasing the BLE concentration, although these parameters are still suitable for packaging applications. The decrease in modulus is attributed to polyphenol capacity to increase PLA chain mobility, while increased fragility results from embedded particles acting as local defects. Wettability tests demonstrated increased hydrophilicity with higher BLE content. Total polyphenol content, estimated through FOLIN assay, increased proportionally with incorporated BLE, impacting antioxidant properties assessed via FRAP assay.
The Potential of Artificial Intelligence in Predicting Post-Stroke Rehabilitation Outcomes: Statistical Analysis Considering Rivermead Motor Assessment and Activities of Daily Living Indicators and Selected Demographic Variables
Authors: Kuźnar Małgorzata , Lorenc Augustyn
Published: December 2024

Strokes are currently the third most common cause of death worldwide and the leading cause of disability in people over 50 years of age. The functioning of post-stroke patients depends primarily on well-conducted rehabilitation, both in stationary conditions and at home. The aim of this study was to evaluate the functional outcomes of patients after ischemic stroke who underwent home rehabilitation. The RMA (Rivermead Motor Assessment) and ADL (activities of daily living) scales were used for evaluation. A total of 20 patients underwent a 4-week home rehabilitation program in Cracow. In the studied group, most patients showed functional improvement after the 4-week rehabilitation period. Predictive models were created (Net1, Net2, Net3) using artificial intelligence algorithms, including regression and classification methods. The analysis results indicate that the best outcomes in predicting the RMA and ADL indicators. For Net2, the prediction accuracy for the ADL indicator was 94.4%, which is significantly higher compared to the other indicators. The RMA1-3 indicators achieved relatively low accuracy rates of 38.9–44.4%. In contrast, for Net3, the RMA1-3 indicators showed high accuracy, achieving 89.1–91.3% correct results. The conclusions of the study suggest that using a combination of the Net2 and Net3 models can contribute to optimizing the rehabilitation process, allowing therapy to be tailored to the individual needs of patients. The research proves that it is possible to predict the effect of rehabilitation by using AI. The implementation of such solutions can increase the effectiveness of post-stroke rehabilitation, particularly through the personalization of therapy and dynamic monitoring of patient progress.
Experimental Study of the Influence of Even Harmonics on Flame Extinguishing by Low-Frequency Acoustic Waves with the Use of High-Power Extinguisher
Authors: Wilk-Jakubowski Jacek Lukasz
Published: December 2024

The acoustic technique appears to be a novel and innovative way to extinguish flames, in which properly generated waves emitted by a high-power sound source are used for extinguishing purposes. The highest extinguishing efficiency is demonstrated by low-frequency waves. In practice, changing the parameters of the acoustic signal results in the possibility of universal and reusable use of the extinguisher, which is limited only by access to the power supply, unlike the currently known traditional methods of fighting fire (such as gases, foams, and extinguishing powders). The purpose of this paper is to analyze whether flame extinguishing by low-frequency acoustic waves is possible using signals containing higher harmonics with the use of large and very large powers delivered to the sound source, which is a scientific novelty. Analyzing the extinguishing capabilities of low-frequency acoustic waves allows one to fill the gap in the literature. This paper presents the results of research in the range of the influence of even sinusoidal harmonics on the extinguishing of flames originating from organic substances. For this purpose, in the experimental part, a high-power acoustic extinguisher and a point source of flames, i.e., a candle containing paraffin wax, were applied. The capabilities of the acoustic method in flame extinguishing have been experimentally demonstrated. The results address both the power that had to be delivered to the sound source of a high-power acoustic extinguisher to extinguish flames and the sound pressure level at which this phenomenon was observed. The added value is also to analyze how the order of even harmonics affects the process of acoustic extinguishment of flames (the order of harmonics for each fundamental frequency was varied from two to ten). Furthermore, the potential benefits and limitations of this method are explained, and future research directions are presented.
Research on Key Technologies of 260 °C/210 MPa Ultra-Deep Logging Equipment
Authors: Chen Zhanglong , Chen Wenhui , You Zhanhua , Wang Shuihang , Liu Xiao , Wu Dan , Deng Rui
Published: December 2024

Deep and ultra-deep oil, which are unconventional oil reservoirs have become an important field for increasing reserves and production in China’s oil and gas exploration and development, and pose higher requirements for ultra-deep logging technology and equipment. For addressing the technical challenges faced in the development of 260 °C/210 MPa ultra-high temperature and high-pressure logging equipment, based on the CPLog fast and imaging series instruments, this article originally proposes key core technologies and solutions such as 260 °C/210 MPa electromechanical sensors, 13,000 m cable communication, and large borehole correction processing. Through the design indoor testing of a BS-PT-based ultra-high temperature acoustic transducer, 260 °C/210 MPa instrument pressure-bearing housing components, and field testing of large borehole environment testing and 13,000-m cable 8000-m deep well data transmission, it will help develop a prototype of 260 °C/210 MPa ultra-high temperature and high pressure logging equipment. The key technology research of 260 °C/210 MPa logging equipment has laid the foundation for the development of ultra-deep logging equipment and provided technical support for the exploration and development of ultra-deep oil and gas at a depth of 10,000 m.
Research on Reducing the Energy Intensity of the Drive System of a Wheelchair Equipped with an Assisted Uphill Module
Authors: Wieczorek Bartosz , Warguła Łukasz
Published: December 2024

This study examines the impact of the reversing interlock module on the energy intensity of manual wheelchair propulsion while considering the need for the module to cooperate with wheels exhibiting significant roundness deviations. The aim was to determine the additional energy demand caused by the module and analyze the effect of the number of one-sided ribs in flexible rollers on energy consumption. Experiments were conducted on a specially designed test bench to measure the torque, power, and energy required to rotate the wheels. The results show that the use of flexible rollers reduces energy consumption compared to rigid rollers—by 8% at a clamping force of 10 N and by 13% at 100 N. A linear relationship between the clamping force and energy savings, along with a significant influence of the roller rotation direction, was observed. When rotating in the less rigid direction, a 17% reduction in energy intensity was achieved. These findings suggest that incorporating flexible rollers in the reversing interlock module can significantly enhance the energy efficiency of wheelchairs.
Assessing Energy Efficiency in Desktop-Size FFF 3D Printers
Authors: Wichniarek Radosław , Osiński Filip
Published: December 2024

This study investigates the energy consumption characteristics of desktop-sized Fused Filament Fabrication (FFF) 3D printers, focusing on variations in energy usage and operational efficiency across different models. The results demonstrate a correlation between machine parameters and energy efficiency during the processing of PLA material. Notably, machines capable of producing identical components in shorter durations tend to consume more electricity, despite utilizing a lower volume of thermoplastic material. Furthermore, the research underscores the substantial impact of specific technological factors, such as the use of rafts, on energy consumption assessments. Relying solely on estimated manufacturing time and material volume to determine manufacturing costs may yield imprecise results, especially amid rising electricity prices. This study emphasizes the need for standardized energy metrics to enable more informed comparisons for consumers.
The Influence of Rubber Hysteresis on the Sliding Friction Coefficient During Contact Between Viscoelastic Bodies and a Hard Substrate
Authors: Nikolić Milan , Banić Milan , Stamenković Dušan , Simonović Miloš , Miltenović Aleksandar , Pavlović Vukašin
Published: December 2024

This paper describes research aimed at the experimental determination of the influence of rubber hysteresis on the friction coefficient between rubber samples for making soles and granite tiles. In the experiments, four types of shoe rubber with similar hardness and different hysteresis properties and two granite tiles with different roughnesses (smooth and anti-slip) were used. The determination of rubber hysteresis was carried out experimentally on a uniaxial testing machine. The friction coefficient was measured using a device specially developed for this type of test, which was based on the pulling force method, while the measurement conditions were based on the EN 13893:2011 standard. The friction coefficient was measured at two different speeds, 50 mm/s and 300 mm/s, with different surface conditions. Using regression analysis and the Taguchi method, the data obtained from the experiments were analyzed to determine the influence of parameters on the friction coefficient. The experimental research shows that different rubber mixtures with the same or similar hardness could have different hysteresis properties but also different friction properties.
Exploring Generative Adversarial Network-Based Augmentation of Magnetic Resonance Brain Tumor Images
Authors: Mahnoor Mahnoor , Rainio Oona , Klén Riku
Published: December 2024

Background: A generative adversarial network (GAN) has gained popularity as a data augmentation technique in the medical field due to its efficiency in creating synthetic data for different machine learning models. In particular, the earlier literature suggests that the classification accuracy of a convolutional neural network (CNN) used for detecting brain tumors in magnetic resonance imaging (MRI) images increases when GAN-generated images are included in the training data together with the original images. However, there is little research about how the exact number of GAN-generated images and their ratio to the original images affects the results obtained. Materials and methods: Here, by using 1000 original images from a public repository with MRI images of patients with or without brain tumors, we built a GAN model to create synthetic brain MRI images. A modified U-Net CNN is trained multiple times with different training datasets and its classification accuracy is evaluated from a separate test set of another 1000 images. The Mann–Whitney U test is used to estimate whether the differences in the accuracy caused by different choices of training data are statistically significant. Results: According to our results, the use of GAN augmentation only sometimes produces a significant improvement. For instance, the classification accuracy significantly increases when 250–750 GAN-generated images are added to 1000 original images (p-values ≤ 0.0025) but decreases when 10 GAN-generated images are added to 500 original images (p-value: 0.03). Conclusions: Whenever GAN-based augmentation is used, the number of GAN-generated images should be carefully considered while accounting for the number of original images.
Humanoid Robots in Tourism and Hospitality—Exploring Managerial, Ethical, and Societal Challenges
Authors: Skubis Ida , Mesjasz-Lech Agata , Nowakowska-Grunt Joanna
Published: December 2024

The paper evaluates the benefits and challenges of employing humanoid robots in tourism and hospitality, examining their roles, decision-making processes, human-centric approaches, and oversight mechanisms. Data will be collected from a variety of sources, including academic journals, websites of the companies where the robots operate, case studies, and news articles. Specific attention will be given to concrete examples of humanoid robots deployed in the tourism and hospitality sector, such as Connie, Spencer, and Henn-na Hotel’s robots. Robots highlight the potential to assume roles traditionally occupied by humans. The presence of humanoid robots also influences cultural practices and social interactions within the hospitality context. Humanoid robots also have the potential to improve equity and accessibility in the tourism and hospitality industry. The interaction between humans and humanoid robots can have psychological and emotional effects on both guests and employees. Finally, the usage of humanoid robots intersects with broader sustainability operational efficiency and customer satisfaction across various sectors within the tourism and hospitality industry. Introducing humanoid robots represents a challenge in innovation that holds promise for revolutionizing service delivery and guest experiences.
Monitoring of Training Load and Body Composition in Elite Male Kayakers
Authors: dos Santos José Augusto Rodrigues , Boppre Giorjines , Zacca Rodrigo
Published: December 2024

Background: Elite kayaking demands peak conditioning, and tracking these athletes reveals the science behind world-class performance. Physiological demands and body composition changes in elite male kayakers were tracked during the preparatory and transition periods of a kayaking competitive season. Methods: Laboratory (body composition assessment and a 4 min all-out test in a kayak ergometer) on-field tests (4 × 1500 m incremental intermittent protocol with 30 s rest intervals in a kayaking/rowing track) were applied on separate days to follow eight elite male kayakers (23.1 ± 5.6 y; 80 ± 8.8 kg; 177.0 ± 6.8 cm) at the beginning of the kayaking season (preparatory period, M1; first week of October), 22 weeks later, at the beginning of the transition period (M2; last week of February), and 5 weeks later, at the end of the transition period, i.e., beginning of the competitive period of the season (M3; first week of April). M3 corresponded to the participation in international competitions. Results: Distance at peak oxygen uptake (V˙O2peak) on the kayak ergometer improved by 36.7 m from M1 to M3, the pace at V4 (aerobic capacity) was reduced (improved) by 25.2 s·km−1 from M1 to M2, and 25.6 s·km−1 by M3. Body weight decreased by 2.3 kg from M1 to M2, and fat mass percentage and kilograms decreased by 1.8% and 3.1%, respectively. Fat-free mass increased by 1.9% and 3.1%, respectively. Skinfold measurements showed a decrease in subscapular, suprailiac, abdominal, and geminal skinfold. Aerobic power (V˙O2peak) in absolute values (in L·min−1) improved by 0.7 L·min−1 from M1 to M2, and by 1.1 L·min−1 by M3, and from M2 to M3 was ~0.5 L·min−1. Aerobic power in relative values improved by 15.0 from M1 to M2, and by 6.4 mL·kg−1·min−1 from M2 to M3. Conclusions: Elite male kayakers improved their physiological performance and body composition during the preparatory and transition phases of the competitive season. Notable gains in performance were mainly due to enhanced aerobic power, and positive body composition changes. These findings provide insights for optimizing training strategies and boosting competitive performance.
Recent Advances in Hydrothermal Oxidation Technology for Sludge Treatment
Authors: Yu Hang , Liu Yuanyuan , Guo Nana , Piao Weiling , Pan Zonglin , Zhu Bin , Zhu Yimin , Wu Libo , Wan Jinling , Wei Huangzhao
Published: December 2024

With the rapid development of urbanization and the widespread adoption of wastewater treatment facilities, the volume of sludge produced has steadily increased. Hydrothermal oxidation (HTO) technology offers an effective solution for sludge reduction, harmless disposal, and resource recovery, making it a highly promising method for sludge treatment. In recent years, HTO has attracted significant attention due to its efficiency and environmental benefits. This paper provides a detailed explanation of the fundamental principles of HTO in sludge treatment, with a focus on the removal of organic pollutants, nitrogen transformation, and phosphorus recovery. The influence of key operational parameters, such as reaction temperature, time, initial oxygen pressure, and pH, on the performance of HTO treatment is also explored. In addition, the research status of HTO sludge treatment and an example of product recovery after treatment are also discussed. It examines the challenges associated with scaling up HTO for large-scale sludge treatment, along with potential research directions for future work. Special attention is given to the innovation of catalysts, with the goal of achieving self-catalysis in sludge treatment. Moreover, considering that ammonia nitrogen (NH3-N) is a major intermediate product in HTO, its removal, as well as the prediction and planning of other unintended products, remains a key issue. Further areas of interest include improving sludge dewatering performance and enhancing the production of valuable single carboxylic acids, which can boost resource recovery efficiency. This paper also highlights the diversification of sludge applications after HTO treatment. By providing insights into future development trends, this review offers valuable references for further research and practical applications. The ultimate goal is to support the development of HTO as a sustainable and efficient solution for sludge treatment, addressing environmental concerns while maximizing resource recovery opportunities.
Mg-Doped Carbonated Hydroxyapatite and Tricalcium Phosphate Anodized Coatings on Titanium Implant Alloys
Authors: Parekh Amisha , Moore Maggie , Janorkar Amol V. , Roach Michael D.
Published: December 2024

The rising demand for dental and orthopedic implants and their frequent aseptic loosening failure mode necessitate the drive to continue modifying implant surfaces to improve osseointegration outcomes. Plasma-sprayed hydroxyapatite coatings are widely used but are prone to delamination. This study involves a single-step anodization process utilizing a novel electrolyte to produce Mg-doped carbonated hydroxyapatite and tricalcium phosphate-containing coatings on four titanium alloy surfaces. XRD confirmed hydroxyapatite and tricalcium phosphate formation, with FTIR examination revealing carbonate substitutions indicative of bone-like apatite formation in each oxide. SEM analyses revealed micro- and nano-scaled surface features on each oxide. SEM and EDS analyses of the oxide coating cross-sections showed each group to be bi-layered with an inner titanium dioxide-rich layer and an outer hydroxyapatite/tricalcium phosphate-rich layer. The oxide layer adhesion quality was shown to be good on CPTi, TAV, and TiMo α + β implant alloy surfaces. Unfortunately, the anodization process also resulted in an undesirable and embrittling omega phase at the substrate–oxide interface due to the migration of molybdenum into the inner oxide. Nonetheless, the anodized coatings on the CPTi and TAV alloy substrates, which are the most widely used titanium alloys for implant applications, show much potential for improving future patient outcomes.
AI-Based Analysis of Archery Shooting Time from Anchoring to Release Using Pose Estimation and Computer Vision
Authors: Lee Seungkeon , Moon Ji-Yeon , Kim Jinman , Lee Eui Chul
Published: December 2024

This study presents a novel method for automatically analyzing archery shooting time using AI and computer vision technologies, with a particular focus on the critical anchoring to release phase, which directly influences performance. The proposed approach detects the start of the anchoring phase using pose estimation and accurately measures the shooting time by detecting the bowstring within the athlete’s facial bounding box, utilizing Canny edge detection and the probabilistic Hough transform. To ensure stability, low-pass filtering was applied to both the facial bounding box and pose estimation results, and an algorithm was implemented to handle intermittent bowstring detection due to various external factors. The proposed method was validated by comparing its results with expert manual measurements obtained using Dartfish software v2022 achieving a mean absolute error (MAE) of 0.34 s and an R2 score of 0.95. This demonstrates a significant improvement compared to the bowstring-only method, which resulted in an MAE of 1.4 s and an R2 score of 0.89. Previous research has demonstrated a correlation between shooting time and arrow accuracy. Therefore, this method can provide real-time feedback to athletes, overcoming the limitations of traditional manual measurement techniques. It enables immediate technical adjustments during training, which can contribute to overall performance improvement.
Extending Generalized Explicit Terms and Applying Euler–Bernoulli Beam Theory to Enhance Dynamic Response Prediction in Receptance Coupling Method
Authors: Hamedi Behzad , Taheri Saied
Published: December 2024

This paper presents a theoretical framework to enhance the prediction of dynamic responses in complex mechanical systems, such as vehicle structures, by incorporating both translational and rotational degrees of freedom. Traditional receptance coupling methods often neglect rotational effects, leading to significant inaccuracies at higher frequencies. Additionally, approaches that implicitly include full dynamics frequently result in redundancy of generalized coordinates, especially at connection points. To address these limitations, the generalized receptance coupling method using Frequency-Based Substructuring is extended to explicitly account for rotational dynamics resulting in a refined GRCFBS approach. This extension enhances both the understanding and prediction of system responses, which are represented through the receptance matrix or Frequency Response Function. Building on Jetmundsen’s foundational work, the proposed framework introduces a practical, generalized formulation that explicitly incorporates full translational and rotational dynamics at each substructure node. This explicit definition provides deeper insights into system behavior, particularly for complex interactions between substructures under weak and strong coupling scenarios at interface points. The Euler–Bernoulli beam theory is employed to model rotational behavior at critical points, yielding reduced-order and explicit receptance matrices for substructures in the coupling process. The methodology’s accuracy and applicability in capturing resonance and anti-resonance modes are validated through two case studies: the coupling of two flexible subsystems and the integration of flexible and rigid components. Results are benchmarked against numerical finite element analysis, and all limitations and potential improvements are discussed. By directly incorporating rotational dynamics directly, this approach enables more reliable dynamic response predictions under multi-directional loading conditions, particularly for vehicle and machinery system design. The GRCFBS method offers a versatile and reliable tool for dynamic system analysis, with significant potential for vibration analysis over a broad frequency range.
Retrievability of Fractured Abutment Screws and Damage to Implant–Abutment Connections: An In Vitro Comparative Analysis of Conventional vs. Drilling Techniques
Authors: Martínez-Alcaraz Paloma , Flores-Fraile Javier , Agustín-Panadero Rubén , Senent-Vicente Gisela , Gómez-Polo Cristina , de la Cruz-Jiménez Silvia , Zubizarreta-Macho Álvaro , Lobo Galindo Ana Belén
Published: December 2024

This study aimed to evaluate the retrievability and potential damage to implant–abutment connections caused by fractured abutment screw removal using conventional and drilling techniques. A total of forty abutment screws were randomly inserted into forty dental implants, and then they were fractured and extracted using different removal methods: Group A employed a conventional approach utilizing an exploration probe and an ultrasonic device without irrigation (n = 10) (conventional); Group B used the Phibo drilling removal system without irrigation (n = 10) (Phibo); Group C utilized the Rhein83® drilling removal system without irrigation (n = 10) (Rhein83); and Group D implemented the Sanhigia® drilling removal system without irrigation (n = 10) (Sanhigia). Pre- and postoperative micro-computed tomography (micro-CT) scans were performed on the dental implants, and Standard Tessellation Language (STL) digital files were generated for morphometric analysis to measure the wear volume. ANOVA was used to assess the volumetric differences (mm3) and percentage ratios of the internal thread volumes of the implant–abutment connections before and after the procedures. Results: This study found no statistically significant differences in the volumetric and percentage ratios of internal threads among the implant groups (Phibo, Rhein83, Sanhigia, and conventional). However, the success rate for retrieving fractured abutment screws was higher (90%) with the drilling systems compared to the conventional technique (50%). These results suggest that drilling systems are more effective for the retrieval of damaged screws. Although drilling techniques without irrigation demonstrated higher removal efficiency compared to the conventional method, both approaches resulted in similar wear volumes at the implant–abutment connections when used to extract fractured screws.
Application of Machine Learning Models to Multi-Parameter Maximum Magnitude Prediction
Authors: Zhang Jingye , Sun Ke , Han Xiaoming , Mao Ning
Published: December 2024

Magnitude prediction is a key focus in earthquake science research, and using machine learning models to analyze seismic data, identify pre-seismic anomalies, and improve prediction accuracy is of great scientific and practical significance. Taking the southern part of China’s North–South Seismic Belt (20° N~30° N, 96° E~106° E), where strong earthquakes frequently occur, as an example, we used the sliding time window method to calculate 11 seismicity indicators from the earthquake catalog data as the characteristic parameters of the training model, and compared six machine learning models, including the random forest (RF) and long short-term memory (LSTM) models, to select the best-performing LSTM model for predicting the maximum magnitude of an earthquake in the study area in the coming year. The experimental results show that the LSTM model performs exceptionally well in predicting earthquakes of magnitude 5 < ML ≤ 6 within the time window of the test set, with a prediction success rate of 85%. Additionally, the study explores how different time windows, spatial locations, and parameter choices affect model performance. It found that longer time windows and key seismicity parameters, such as the b-value and the square root of total seismic energy, are crucial for improving prediction accuracy. Finally, we propose a magnitude interval-based assessment method to better predict the actual impacts that different magnitudes may cause. This method demonstrates the LSTM model’s potential in predicting moderate to strong earthquakes and offers new approaches for earthquake early warning and disaster mitigation.