bluuebunny/crossref_metadata_2025 huggingface dataset:
Ontogenetic development of energy-supplying enzymes in rat and guinea-pig heart
Authors: Bass A , Stejskalová M , Stieglerová A , Ošťádal B , Šamánek M
Published: June 2024

The purpose of the present study was to compare the ontogenetic development of the activity of myocardial energy-supplying enzymes in two mammalian species, differing significantly in their level of maturation at birth. The animals were investigated during the late prenatal period and 2, 7, 14, 21, 25, 30, 63, 120 and 730 days after birth in the rat and 2, 21, 84 and 175 days in the guinea-pig. The following enzymes were assayed in the right and left ventricular myocardium: lactate dehydrogenase (LDH, lactate uptake and/or formation), triose phosphate dehydrogenase (TPDH, carbohydrate metabolism), glycerol phosphate dehydrogenase (GPDH, glycerol-P shuttle)), hexokinase (HK, glucose phosphorylation), malate dehydrogenase (MDH, tricarboxylic cycle), citrate synthase (CS, tricarboxylic cycle) and hydroxyacyl-CoA dehydrogenase (HOADH, fatty acid breakdown). The rat heart, highly immature at birth, exhibits three different developmental patterns of energy-supplying enzymes, identical in both ventricles: (i) two mitochondrial enzymes of aerobic metabolism (CS, HOADH) and GPDH have a relatively low activity at the end of prenatal life; thereafter their activity steadily increases, approaching the adult levels between the 3rd and 4th postnatal weeks. A significant decrease was observed between the 4th and 24th months. (ii) MDH and LDH: prenatal values were significantly higher as compared with the 2nd postnatal day; after this period the activities increased up to adulthood (4 months) and decreased during senescence. (iii) The activities of HK and TPDH are characterized by only moderate changes during development. HK differs from all other enzymes by the highest prenatal values, which exceed even adult values. In contradiction to the rat heart, the developmental differences in more mature guinea-pig heart were significantly less pronounced. The only ontogenetic differences observed were the lower activities of enzymes connected with aerobic metabolism at the end of the prenatal period. Our results point to possible differences in the development of adaptive metabolic pathways in animals with different levels of maturation at birth.
Training of Convolutional Neural Networks for Image Classification with Fully Decoupled Extended Kalman Filter
Authors: Gaytan Armando , Begovich-Mendoza Ofelia , Arana-Daniel Nancy
Published: June 2024

First-order algorithms have long dominated the training of deep neural networks, excelling in tasks like image classification and natural language processing. Now there is a compelling opportunity to explore alternatives that could outperform current state-of-the-art results. From the estimation theory, the Extended Kalman Filter (EKF) arose as a viable alternative and has shown advantages over backpropagation methods. Current computational advances offer the opportunity to review algorithms derived from the EKF, almost excluded from the training of convolutional neural networks. This article revisits an approach of the EKF with decoupling and it brings the Fully Decoupled Extended Kalman Filter (FDEKF) for training convolutional neural networks in image classification tasks. The FDEKF is a second-order algorithm with some advantages over the first-order algorithms, so it can lead to faster convergence and higher accuracy, due to a higher probability of finding the global optimum. In this research, experiments are conducted on well-known datasets that include Fashion, Sports, and Handwritten Digits images. The FDEKF shows faster convergence compared to other algorithms such as the popular Adam optimizer, the sKAdam algorithm, and the reduced extended Kalman filter. Finally, motivated by the finding of the highest accuracy of FDEKF with images of natural scenes, we show its effectiveness in another experiment focused on outdoor terrain recognition.
Numerical Study on the Internal Flow Field Characteristics of a Novel High-Speed Switching Control Valve
Authors: Ji Hexi , Han Jiazhen , Wang Yong , Wang Qixian , Yang Sen , Xie Yudong , Song Yilong , Wang Haibo
Published: June 2024

Modern laver fluffiness is achieved by applying high-speed gas to a laver, which is generated by the opening and closing of a laver fluffiness control valve in a fluffiness system. To address the problems of the slow response speed and poor stability of valves used in the laver processing industry at present, this paper proposes a novel principle of a high-speed switching control valve, which has the advantages of a fast response speed, high stability, and long service life. The structure and working principle of the control valve are introduced, and the calculation equation of the valve’s flow area is established. The flow field inside the control valve with different openings was numerically calculated in this study using Fluent. The flow regulation characteristics and flow field performance of the control valve were also analyzed. The results show that, with an increase in the valve opening, the influence of the flow area at the valve throttle on the valve flow rate was weakened. When the valve was opened, a vortex appeared in both the upper and lower cavities, and jet flow occurred at the throttle of the middle flow channel. As the valve opening increased, the pressure in the upper cavity reduced, while the pressure in the lower cavity increased. The vortex in the flow field intensified, and the jet phenomenon at the valve throttle gradually disappeared. At the same time, the main stream in the lower cavity gradually changed from an annular flow to a direct flow toward the valve outlet. Furthermore, the impact, collision, and vortex formation of the fluid caused energy loss of the fluid, leading to a decrease in the outlet flow of the control valve.
Compositional Nutrient Diagnosis Methodology and Its Effectiveness to Identify Nutrient Levels in Yerba Mate (Ilex paraguariensis)
Authors: Lisboa Bruno Britto , Abichequer André Dabdab , de São José Jackson Freitas Brilhante , Moura-Bueno Jean Michel , Brunetto Gustavo , Vargas Luciano Kayser
Published: June 2024

Yerba mate is a forest species of both cultural and economic importance growing in the subtropical regions of South America, especially in the south of Brazil. Despite its importance, yerba mate has never received enough attention from researchers, so the nutritional sufficiency ranges and critical levels have not yet been determined. This research aimed to establish these parameters for yerba mate to enable its foliar diagnosis. A total of 167 leaf samples were collected from production fields located in the five yerba mate-growing regions in Rio Grande do Sul, and the leaf nutrients were determined by standard chemical methods. The yield of each production field was accessed, and the cutoff value separating low- and high-yield groups was calculated in 16.75 Mg ha−1. The multivariate compositional nutrient diagnosis (CND) standards were determined, and nutrient interactions were estimated by correlation and principal component analyses. There was no positive correlation between any single nutrient and yield, even in the high-yield population, evidencing that a higher yield is the outcome of the balance among all nutrients. Excess of B occurred in one-third of the low-yield samples, while deficiency of Cu and K occurred in one-fourth of these samples. Finally, we established the adequate leaf nutrient levels for yerba mate.
Digital Technology Increases the Sustainability of Cross-Border Agro-Food Supply Chains: A Review
Authors: Wang Gaofeng , Li Shuai , Yi Yang , Wang Yingying , Shin Changhoon
Published: June 2024

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the ‘antecedent–practice–performance’ conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier.
Real-Time Camera Operator Segmentation with YOLOv8 in Football Video Broadcasts
Authors: Postupaiev Serhii , Damaševičius Robertas , Maskeliūnas Rytis
Published: June 2024

Using instance segmentation and video inpainting provides a significant leap in real-time football video broadcast enhancements by removing potential visual distractions, such as an occasional person or another object accidentally occupying the frame. Despite its relevance and importance in the media industry, this area remains challenging and relatively understudied, thus offering potential for research. Specifically, the segmentation and inpainting of camera operator instances from video remains an underexplored research area. To address this challenge, this paper proposes a framework designed to accurately detect and remove camera operators while seamlessly hallucinating the background in real-time football broadcasts. The approach aims to enhance the quality of the broadcast by maintaining its consistency and level of engagement to retain and attract users during the game. To implement the inpainting task, firstly, the camera operators instance segmentation method should be developed. We used a YOLOv8 model for accurate real-time operator instance segmentation. The resulting model produces masked frames, which are used for further camera operator inpainting. Moreover, this paper presents an extensive “Cameramen Instances” dataset with more than 7500 samples, which serves as a solid foundation for future investigations in this area. The experimental results show that the YOLOv8 model performs better than other baseline algorithms in different scenarios. The precision of 95.5%, recall of 92.7%, mAP50-95 of 79.6, and a high FPS rate of 87 in low-volume environment prove the solution efficacy for real-time applications.
Effects of Acetic Acid and Morphine in Shore Crabs, Carcinus maenas: Implications for the Possibility of Pain in Decapods
Authors: Barr Stuart , Elwood Robert W.
Published: June 2024

Noxious chemicals, coupled with morphine treatment, are often used in studies on pain in vertebrates. Here we show that injection of morphine caused several behavioural changes in the crab, Carcinus maenas, including reduced pressing against the sides of the enclosure and more rubbing and picking at the mouth parts and, at least for a short time, more defensive displays. Subsequent injection of acetic acid into one rear leg caused rubbing of the injected leg and the injected leg was held vertically off the ground. These activities directed at or involving the specific leg are consistent with previous observations of directed behaviour following noxious stimuli and are consistent with the idea that decapods experience pain. Further, acetic acid but not injection of water induced autotomy of the injected leg in these animals. Because autotomy is temporally associated with directed behaviour, it is possible that the autotomy is a pain-related response. Acetic acid is clearly a noxious substance when applied to decapods. However, morphine had no effect on the activities associated with acetic acid injection and thus there is no evidence for an analgesic effect. Further, the injection of acetic acid did not interfere with behavioural effects of morphine. The activities directed towards the site of injection are like those observed with injection, or with external application, of various noxious substances and the present study adds to a growing body of knowledge about possible pain in decapods.
Exploration of Molecular Mechanisms of Immunity in the Pacific Oyster (Crassostrea gigas) in Response to Vibrio alginolyticus Invasion
Authors: Zhang Enshuo , Li Zan , Dong Luyao , Feng Yanwei , Sun Guohua , Xu Xiaohui , Wang Zhongping , Cui Cuiju , Wang Weijun , Yang Jianmin
Published: June 2024

Over the years, oysters have faced recurring mass mortality issues during the summer breeding season, with Vibrio infection emerging as a significant contributing factor. Tubules of gill filaments were confirmed to be in the hematopoietic position in Crassostrea gigas, which produce hemocytes with immune defense capabilities. Additionally, the epithelial cells of oyster gills produce immune effectors to defend against pathogens. In light of this, we performed a transcriptome analysis of gill tissues obtained from C. gigas infected with Vibrio alginolyticus for 12 h and 48 h. Through this analysis, we identified 1024 differentially expressed genes (DEGs) at 12 h post-injection and 1079 DEGs at 48 h post-injection. Enrichment analysis of these DEGs revealed a significant association with immune-related Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. To further investigate the immune response, we constructed a protein–protein interaction (PPI) network using the DEGs enriched in immune-associated KEGG pathways. This network provided insights into the interactions and relationships among these genes, shedding light on the underlying mechanisms of the innate immune defense mechanism in oyster gills. To ensure the accuracy of our findings, we validated 16 key genes using quantitative RT-PCR. Overall, this study represents the first exploration of the innate immune defense mechanism in oyster gills using a PPI network approach. The findings provide valuable insights for future research on oyster pathogen control and the development of oysters with enhanced antimicrobial resistance.
Blood Fluke Infection (Spirorchidiasis) and Systemic Granulomatous Inflammation: A Case Study of Green Sea Turtles (Chelonia mydas) on Jeju Island, South Korea
Authors: Park Da Sol , Hong Won Hee , Kim Jae Hoon , Yuen Adams Hei Long , Giri Sib Sankar , Lee Sung Bin , Jung Won Joon , Lee Young Min , Jo Su Jin , Hwang Mae Hyun , Park Jae Hong , Park Eun Jae , Park Se Chang
Published: June 2024

Despite the precarious state of marine turtles as a highly endangered species, our understanding of their diseases remains limited. This case report presents a detailed pathological investigation of spirorchiidiasis, a blood fluke infection that poses a substantial threat to marine turtles. This retrospective study examined three cases of spirorchiid-infected sea turtles, specifically, green sea turtles stranded on Jeju Island, South Korea. Premortem examination of the three spirorchiid-infected green sea turtles demonstrated nonspecific clinical symptoms; blood analysis revealed dehydration, malnutrition, and anemia. Computed tomography scans provided insights into severe pulmonary and extrapulmonary manifestations, including the mass present in the joint region. Post-mortem examinations consistently indicated severe lung lesions and systemic manifestations, with histopathological examination confirming the presence of spirorchiid ova across various organs. Despite the global prevalence of spirorchiidiasis in sea turtles, disease severity varies regionally. This report provides a detailed demonstration of the pathology of spirorchiidiasis in sea turtles from Northeast Asia.
Comparison of the Impact of VRP-034 and Polymyxin B upon Markers of Kidney Injury in Human Proximal Tubule Monolayers In Vitro
Authors: Pye Keith , Tasinato Elena , Shuttleworth Siannah , Devlin Claire , Brown Colin
Published: June 2024

In this study, we assessed the impact of commercially available polymyxin B against VRP-034 (novel formulation of polymyxin B) using a validated in vitro human renal model, aProximateTM. Freshly isolated primary proximal tubule cells (PTCs) were cultured in Transwell plates and treated with various concentrations of the formulations for up to 48 h. The functional expression of megalin–cubilin receptors in PTC monolayers was validated using FITC-conjugated albumin uptake assays. Polymyxin B and VRP-034 were evaluated at six concentrations (0.3, 1, 3, 10, 30, and 60 µM), and nephrotoxicity was assessed through measurements of transepithelial electrical resistance (TEER), intracellular adenosine triphosphate (ATP) levels, lactate dehydrogenase (LDH) release, and novel injury biomarkers [kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and clusterin]. Additionally, histological analysis using annexin V apoptosis staining was performed. Our results indicated a significant decrease in TEER with polymyxin B at concentrations ≥10 μM compared to VRP-034. Toxic effects were observed from ATP and LDH release only at concentrations ≥30 μM for both formulations. Furthermore, injury biomarker release was higher with polymyxin B compared to VRP-034, particularly at concentrations ≥10 µM. Histologically, polymyxin B-treated PTCs showed increased apoptosis compared to VRP-034-treated cells. Overall, VRP-034 demonstrated improved tolerance in the aProximateTM model compared to polymyxin B, suggesting its potential as a safer alternative for renal protection.
Obstructive Sleep Apnea and Acute Lower Respiratory Tract Infections: A Narrative Literature Review
Authors: Nemet Marko , Vukoja Marija
Published: June 2024

Both obstructive sleep apnea (OSA) and acute lower respiratory tract infections (LRTIs) are important global health issues. The pathophysiological links between OSA and LRTIs include altered immune responses due to chronic intermittent hypoxia and sleep fragmentation, increased aspiration risk, and a high burden of comorbidities. In this narrative review, we evaluated the current evidence on the association between OSA and the incidence and outcomes of acute LRTIs in adults, specifically community-acquired pneumonia and viral pneumonia caused by influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Studies have demonstrated that OSA patients are more likely to develop bacterial pneumonia and exhibit a higher risk of invasive pneumococcal disease. The risk intensifies with the severity of OSA, influencing hospitalization rates and the need for intensive care. OSA is also associated with an increased risk of contracting influenza and suffering more severe disease, potentially necessitating hospitalization. Similarly, OSA contributes to increased COVID-19 disease severity, reflected by higher rates of hospitalization, longer hospital stays, and a higher incidence of acute respiratory failure. The effect of OSA on mortality rates from these infections is, however, somewhat ambiguous. Finally, we explored antibiotic therapy for OSA patients with LRTIs, addressing care settings, empirical regimens, risks, and pharmacokinetic considerations. Given the substantial burden of OSA and its significant interplay with acute LRTIs, enhanced screening, targeted vaccinations, and optimized management strategies for OSA patients should be prioritized.
A Systemic Model for Resilience and Time Management in Healthcare Academia: Application in a Dental University Setting
Authors: Antoniadou Maria , Antoniadis Rallis
Published: June 2024

The primary aim of this study was to provide a sustainable and systemic solution to the prevalent time management challenges within healthcare academia. The secondary aim was to explore the correlations between various factors influencing time management in a dental university setting. To achieve these objectives, a predictive model, the Timebooster Academic Systemic Model (TASM), was developed. This model was crafted through systemic analysis software and a systemic management approach, utilizing three fundamental pillars: teaching, research, and administrative tasks. Soft skill cultivation, automation implementation, the delegation of administrative responsibilities, and the role of resilient academic manager–leaders were also examined. The study found that prioritizing administrative tasks often consumes valuable academic time, resulting in excessive costs and lowered resilience levels among academicians. TASM proposes solutions such as soft skill cultivation, full automation, delegation, and the mitigation of time-consuming elements, emphasizing the role of resilient academic manager–leaders in enhancing collaboration and teamwork. Time management challenges significantly impact academic well-being and resilience. In conclusion, systemic models like TASM provide a valuable framework to address prioritization concerns, identify administrative obstacles, and manage low-value time-consuming tasks within academia in a systemic manner.
New Approach for Brain Tumor Segmentation Based on Gabor Convolution and Attention Mechanism
Authors: Cao Yuan , Song Yinglei
Published: June 2024

In the treatment process of brain tumors, it is of great importance to develop a set of MRI image segmentation methods with high accuracy and low cost. In order to extract the feature information for each region of the brain tumor more effectively, this paper proposes a new model Ga-U-Net based on Gabor convolution and an attention mechanism. Based on 3D U-Net, Gabor convolution is added at the shallow layer of the encoder, which is able to learn the local structure and texture information of the tumor better. After that, the CBAM attention mechanism is added after the output of each layer of the encoder, which not only enhances the network’s ability to perceive the brain tumor boundary information but also reduces some redundant information by allocating the attention to the two dimensions of space and channel. Experimental results show that the model performs well for multiple tumor regions (WT, TC, ET) on the brain tumor dataset BraTS 2021, with Dice coefficients of 0.910, 0.897, and 0.856, respectively, which are improved by 0.3%, 2%, and 1.7% compared to the base network, the U-Net network, with an average Dice of 0.887 and an average Hausdorff distance of 9.12, all of which are better than a few other state-of-the-art deep models for biomedical image segmentation.
New Design of Personal Protective Equipment for Handling Contagious Viruses: Evaluation of Comfort and Physiological Responses
Authors: Totong Totong , Soetisna Herman Rahadian , Wijayanto Titis , Iridiastadi Hardianto
Published: June 2024

The use of personal protective equipment (PPE) for virus handling has the side effect of heat stress, which requires intervention to improve. This study aimed to evaluate the comfort of a newly designed PPE ensemble for virus handling. Three types of PPE ensembles were tested: reg-ular PPE as a control, PPE plus breathable cooling wear (cooling wear), and PPE plus a portable airflow cooling device (cooling device). Twelve participants simulated six activities, including physical activities, activities requiring concentration, and manual dexterity activities, for one hour. The microclimate conditions, perceived discomfort, and physiological responses were measured after each experimental activity. The results show that the use of cooling wear and a cooling device had a significant effect on the microclimate conditions, perceived comfort, and physiological responses of users, proving superior to the use of regular PPE. A cooling device can improve the microclimate more than cooling wear, thereby directly increasing perceived comfort and decreasing physiological responses. It can be concluded that the use of cooling wear and a cooling device effectively increases the comfort of wearing PPE. The cooling device is more suitable for use in tropical climates with hot and humid characteristics, so it is a better choice than cooling wear.
Using Machine Learning to Predict Pedestrian Compliance at Crosswalks in Jordan
Authors: Taamneh Madhar M. , Alomari Ahmad H. , Taamneh Salah M.
Published: June 2024

This study employs machine learning (ML) techniques to predict pedestrian compliance at crosswalks in urban settings in Jordan, aiming to enhance pedestrian safety and traffic management. Utilizing data from 2437 pedestrians at signalized intersections in Amman, Irbid, and Zarqa, four models based on different ML algorithms were developed: an artificial neural network (ANN), a support vector machine (SVM), a decision tree (ID3), and a random forest (RF). The results have shown that local infrastructure and traffic conditions influence pedestrian behavior. The RF model, with its excellent accuracy and precision, has proven to be an excellent choice for accurately predicting pedestrian behavior. This research provides valuable insights into the demographic and spatial aspects that influence pedestrian compliance with laws and regulations in the local environment. Additionally, this work highlights the ability of ML algorithms to improve urban traffic dynamics. Policymakers and urban planners, particularly with the rise of theories and trends toward the humanization of urban roads, should firmly establish this understanding among themselves to create environments that make pedestrians safer. This strategy could be a measurable solution for international urban situations if future research focuses on integrating these prediction models with real-time traffic management systems to improve pedestrian safety dynamically.
DFD-SLAM: Visual SLAM with Deep Features in Dynamic Environment
Authors: Qian Wei , Peng Jiansheng , Zhang Hongyu
Published: June 2024

Visual SLAM technology is one of the important technologies for mobile robots. Existing feature-based visual SLAM techniques suffer from tracking and loop closure performance degradation in complex environments. We propose the DFD-SLAM system to ensure outstanding accuracy and robustness across diverse environments. Initially, building on the ORB-SLAM3 system, we replace the original feature extraction component with the HFNet network and introduce a frame rotation estimation method. This method determines the rotation angles between consecutive frames to select superior local descriptors. Furthermore, we utilize CNN-extracted global descriptors to replace the bag-of-words approach. Subsequently, we develop a precise removal strategy, combining semantic information from YOLOv8 to accurately eliminate dynamic feature points. In the TUM-VI dataset, DFD-SLAM shows an improvement over ORB-SLAM3 of 29.24% in the corridor sequences, 40.07% in the magistrale sequences, 28.75% in the room sequences, and 35.26% in the slides sequences. In the TUM-RGBD dataset, DFD-SLAM demonstrates a 91.57% improvement over ORB-SLAM3 in highly dynamic scenarios. This demonstrates the effectiveness of our approach.
Reliability Analysis of Small-Sample Failure Data for Random Truncation High-Voltage Relay
Authors: Zhang Yingzhi , Han Feng , Yang Fang , Wang Xiaofeng , Zhou Yutong
Published: June 2024

In order to model and evaluate the reliability of long-life high-voltage relays with small-sample fault data characteristics, a reliability analysis method integrating average rank, the minimum mean square distance empirical distribution function, and total least squares estimation is proposed. In the random truncation experiment, considering the influence of random truncation data, the average rank method is used to correct the rank of small-sample fault data; then, the optimal empirical distribution function for small-sample fault data is obtained through the minimum average square distance, which can overcome the impact of small-sample fault data randomness. Under the assumption of the Weibull distribution model, the total least squares estimation method is used for reliability model parameter estimations, and the linear correlation coefficient and d-test method are used for model hypothesis testing. If two or more distribution models pass the linear correlation coefficient test and the d-test simultaneously, the root mean square error and relative root mean square error are applied to determine the optimal reliability model. The effectiveness of this method is verified by comparing it with the maximum likelihood estimation method.
Impact of Visual Disturbances on the Trend Changes of COP Displacement Courses Using Stock Exchange Indices
Authors: Wodarski Piotr , Chmura Marta , Jurkojć Jacek
Published: June 2024

This work aims to define a strategy for maintaining a vertical posture of the human body under conditions of conflicting sensory stimuli using a method of trend change analysis. The investigations involved 28 healthy individuals (13 females, 15 males, average age = 21, SD = 1.3 years). Measurements were conducted with eyes opened and closed and in the virtual environment with two sceneries oscillating at two frequencies. Values in the time domain were calculated—the mean center of pressure (COP) velocity and movement range in the AP direction—as well as values based on the moving average convergence divergence (MACD) computational algorithm—the trend change index (TCI), MACD_dT, MACD_dS, and MACD_dV. After dividing the analysis into distinct time periods, an increase in TCI values was identified in the oscillating scenery at 0.7 and 1.4 Hz during the 0.5–1 and 0.2–0.5 s time periods, respectively. Statistically significant differences were observed between measurements with an oscillation frequency of 0.7 Hz and those with an oscillation frequency of 1.4 Hz during the 0.2–0.5 s and 0.5–1 s periods. The use of stock exchange indices in the assessment of the ability to keep a stable body posture supplements and extends standard analyses in the time and frequency domains.
Vibrational Rarefaction Waves Excited by Laser-Induced Bubble within Confined Cuvettes and Their Feedback on Cavitation Dynamics: Influence of Wall and Liquid
Authors: Fu Lei , Peng Ziyao , Du Xiaofan , Zhang Zhenxi , Wang Jing , Yao Cuiping
Published: June 2024

In this work, within finite liquid spaces confined by elastic walls and the free surface, we investigated the influence of wall and liquid on laser bubble-excited vibrational rarefaction waves, via the dynamics of the laser-induced plasma-mediated bubble and its accompanying small secondary bubble clouds. We observed the modulation of the rebound maximum radius (Rmax2) relative to the first oscillation period (Tosc1) for the laser bubble and the periodic appearance of secondary bubble clouds, which were caused by extra rarefaction waves. We found an approximate constant modulation period of Rmax2 (Tosc1) and increased time intervals between the adjacent secondary bubble clouds with increasing liquid height in the same cuvette, while both of them were remarkably increased with increasing inner size of cuvettes within the same liquid height. This indicated that the cuvette geometry and liquid volume alter the key characteristics of the vibrational rarefaction waves. It was further confirmed that extra rarefaction waves within the liquid are excited by wall vibrations linked to laser bubble expansion and its induced liquid-mass oscillations. Our study provides a better understanding of the interactions of laser-induced cavitation with liquid and elastic walls in confined geometry, which is essential for intraluminal laser surgery.
Fluoride Release by Restorative Materials after the Application of Surface Coating Agents: A Systematic Review
Authors: Tokarczuk Dominik , Tokarczuk Oskar , Kiryk Jan , Kensy Julia , Szablińska Magdalena , Dyl Tomasz , Dobrzyński Wojciech , Matys Jacek , Dobrzyński Maciej
Published: June 2024

Background: Fluoride is vital in dentistry for caries prevention, enhancing remineralization, and inhibiting bacteria. Incorporating fluoride into restorative materials like glass-ionomer cements, compomers, and giomers has significantly increased fluoride availability in the oral cavity. This review assesses how surface coatings influence fluoride release from various dental restorative materials. Methods: In December 2023, we conducted electronic searches in PubMed, Scopus, and Web of Science (WoS) databases. In the Scopus database, the results were refined to titles, abstracts, and keywords, while in PubMed, they were narrowed down to titles and abstracts. In WoS, the results were refined only to abstracts. The search criteria were based on the terms fluoride AND release AND (coating OR glaze OR layer OR film OR varnish) AND (composite OR glass OR compomer), following PRISMA guidelines and the PICO framework. Twenty-three studies were rigorously selected and analyzed for fluoride release from coated versus uncoated materials. Results: Surface coatings typically reduce the rate of fluoride release. Glass-ionomer cements had the highest release, followed by giomers and compomers. The initial release was greater in uncoated materials but stabilized over time, influenced by variables like artificial saliva and deionized water. Conclusions: Surface coatings generally decrease fluoride release rates from dental materials. Although initial rates are high, contributing to caries prevention, more standardized research is needed to better understand the impact of coatings and optimize materials for maximum preventive benefits.
Techno-Economic Assessment of Anaerobic Digestion Technology for Small- and Medium-Sized Animal Husbandry Enterprises
Authors: Eftaxias Alexandros , Kolokotroni Iliana , Michailidis Christos , Charitidis Panagiotis , Diamantis Vasileios
Published: June 2024

Investments in small and medium-sized anaerobic digestion facilities have the potential to boost biogas production in Greece and other EU countries. This study aimed to evaluate the economic feasibility of anaerobic digestion facilities equipped with combined heat and power (CHP) units ranging from 50 to 400 kW, while treating livestock waste. For this purpose, data were gathered from various livestock operations (dairy cattle, poultry, swine, dairy sheep and goats) regarding their annual production, revenues, electricity and fuel usage, and waste generation. Waste samples were then collected and analyzed to assess their biochemical methane production potential. The capital and operational costs of anaerobic digestion facilities, from 50 and 400 kW, were calculated using the equations developed within the “eMT cluster” project. Findings indicate that current feed-in tariffs (FITs) of 0.21 € kWh−1 are insufficient to incentivize investment in anaerobic digestion facilities with capacities below 250 kW, highlighting the need for increased FIT rates or capital expenditure subsidies. Recommendations include shifting towards simplified technology and business models with reduced farmer involvement, coupled with supportive legislative framework and long-term electricity price guarantees. These measures are expected to foster the implementation of anaerobic digestion projects in the animal husbandry sector.
Data-Driven Weather Forecasting and Climate Modeling from the Perspective of Development
Authors: Wu Yuting , Xue Wei
Published: June 2024

Accurate and rapid weather forecasting and climate modeling are universal goals in human development. While Numerical Weather Prediction (NWP) remains the gold standard, it faces challenges like inherent atmospheric uncertainties and computational costs, especially in the post-Moore era. With the advent of deep learning, the field has been revolutionized through data-driven models. This paper reviews the key models and significant developments in data-driven weather forecasting and climate modeling. It provides an overview of these models, covering aspects such as dataset selection, model design, training process, computational acceleration, and prediction effectiveness. Data-driven models trained on reanalysis data can provide effective forecasts with an accuracy (ACC) greater than 0.6 for up to 15 days at a spatial resolution of 0.25°. These models outperform or match the most advanced NWP methods for 90% of variables, reducing forecast generation time from hours to seconds. Data-driven climate models can reliably simulate climate patterns for decades to 100 years, offering a magnitude of computational savings and competitive performance. Despite their advantages, data-driven methods have limitations, including poor interpretability, challenges in evaluating model uncertainty, and conservative predictions in extreme cases. Future research should focus on larger models, integrating more physical constraints, and enhancing evaluation methods.
Application of Machine Learning Algorithms in Predicting Extreme Rainfall Events in Rwanda
Authors: Kagabo James , Kattel Giri Raj , Kazora Jonah , Shangwe Charmant Nicolas , Habiyakare Fabien
Published: June 2024

Precipitation is an essential component of the hydrological cycle that directly affects human lives. An accurate and early detection of a future rainfall event can help prevent social, environmental, and economic losses. Traditional methods for accurate rainfall prediction have faltered due to their weakness in quantifying nonlinear climatic conditions as they involve numerical weather prediction using radar to solve complex mathematical equations based on contemporary meteorological data. This study aims to develop a precise rainfall forecast model using machine learning (ML), and this model focuses on long short-term memory (LSTM) to enhance rainfall prediction accuracy. In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting extreme weather phenomena worldwide. For instance, long short-term memory (LSTM) is a forecast model that effectively estimates the amount of precipitation based on historical data. We analyzed 85,470 pieces of daily rainfall data from 1983 to 2021 collected from each of four synoptic stations in Rwanda (Kigali Aero, Ruhengeri Aero, Kamembe Aero, and Gisenyi Aero). Advanced ML algorithms, including convolutional neural networks (CNNs), gated recurrent units (GRUs), and LSTM, were applied to predict extreme rainfall events. LSTM outperforms the CNN and GRU with 99.7%, 99.8%, and 99.7% accuracy. LSTM’s ability to filter out noise showed important patterns by handling irregularities in rainfall data to improve forecast results. Our outcomes have significant implications for disaster preparedness and risk mitigation efforts in Rwanda, where frequent natural disasters, including floods, pose a challenge. Our research also demonstrates the superiority of LSTM-based ML algorithms in predicting extreme rainfall events, highlighting their potential to enhance disaster risk resilience and preparedness strategies in Rwanda.
Tetranuclear Polypyridylruthenium(II) Complexes as Selective Nucleic Acid Stains for Flow Cytometric Analysis of Monocytic and Epithelial Lung Carcinoma Large Extracellular Vesicles
Authors: Wardhani Kartika , Levina Aviva , Sun Biyun , Zou Haipei , Grau Georges E. R. , Keene F. Richard , Collins J. Grant , Lay Peter A.
Published: June 2024

Selective staining of extracellular vesicles (EVs) is a major challenge for diagnostic and therapeutic applications. Herein, the EV labeling properties of a new class of tetranuclear polypyridylruthenium(II) complexes, Rubb7-TNL and Rubb7-TL, as phosphorescent stains are described. These new stains have many advantages over standard stains to detect and characterize EVs, including: high specificity for EV staining versus cell staining; high phosphorescence yields; photostability; and a lack of leaching from EVs until incorporation with target cells. As an example of their utility, large EVs released from control (basal) or lipopolysaccharide (LPS)-stimulated THP-1 monocytic leukemia cells were studied as a model of immune system EVs released during bacterial infection. Key findings from EV staining combined with flow cytometry were as follows: (i) LPS-stimulated THP-1 cells generated significantly larger and more numerous large EVs, as compared with those from unstimulated cells; (ii) EVs retained native EV physical properties after staining; and (iii) the new stains selectively differentiated intact large EVs from artificial liposomes, which are models of cell membrane fragments or other lipid-containing debris, as well as distinguished two distinct subpopulations of monocytic EVs within the same experiment, as a result of biochemical differences between unstimulated and LPS-stimulated monocytes. Comparatively, the staining patterns of A549 epithelial lung carcinoma-derived EVs closely resembled those of THP-1 cell line-derived EVs, which highlighted similarities in their selective staining despite their distinct cellular origins. This is consistent with the hypothesis that these new phosphorescent stains target RNA within the EVs.
Combination of Hydrolysable Tannins and Zinc Oxide on Enterocyte Functionality: In Vitro Insights
Authors: Ciaramellano Francesca , Scipioni Lucia , Belà Benedetta , Pignataro Giulia , Giacovazzo Giacomo , Angelucci Clotilde Beatrice , Giacominelli-Stuffler Roberto , Gramenzi Alessandro , Oddi Sergio
Published: June 2024

The management of gastrointestinal disease in animals represents a significant challenge in veterinary and zootechnic practice. Traditionally, acute symptoms have been treated with antibiotics and high doses of zinc oxide (ZnO). However, concerns have been raised regarding the potential for microbial resistance and ecological detriment due to the excessive application of this compound. These concerns highlight the urgency of minimizing the use of ZnO and exploring sustainable nutritional solutions. Hydrolysable tannins (HTs), which are known for their role in traditional medicine for acute gastrointestinal issues, have emerged as a promising alternative. This study examined the combined effect of food-grade HTs and subtherapeutic ZnO concentration on relevant biological functions of Caco-2 cells, a widely used model of the intestinal epithelial barrier. We found that, when used together, ZnO and HTs (ZnO/HTs) enhanced tissue repair and improved epithelial barrier function, normalizing the expression and functional organization of tight junction proteins. Finally, the ZnO/HTs combination strengthened enterocytes’ defense against oxidative stress induced by inflammation stimuli. In conclusion, combining ZnO and HTs may offer a suitable and practical approach for decreasing ZnO levels in veterinary nutritional applications.
Advances in the Pathogenesis of Steroid-Associated Osteonecrosis of the Femoral Head
Authors: Zhang Jie , Cao Jianze , Liu Yongfei , Zhao Haiyan
Published: June 2024

Osteonecrosis of the femoral head (ONFH) is a refractory orthopedic condition characterized by bone cell ischemia, necrosis, bone trabecular fracture, and clinical symptoms such as pain, femoral head collapse, and joint dysfunction that can lead to disability. The disability rate of ONFH is very high, which imposes a significant economic burden on both families and society. Steroid-associated osteonecrosis of the femoral head (SANFH) is the most common type of ONFH. However, the pathogenesis of SANFH remains unclear, and it is an urgent challenge for orthopedic surgeons to explore it. In this paper, the pathogenesis of SANFH and its related signaling pathways were briefly reviewed to enhance comprehension of the pathogenesis and prevention of SANFH.
The Effect of Coping on the Relationship between Work-Family Conflict and Stress, Anxiety, and Depression
Authors: de Sousa Cristina , Viseu João , Pimenta Ana Cristina , Vinagre Helena , Ferreira João , Matavelli Rafaela , José Helena , Sousa Luís , Romana Fernando Acabado , Valentim Olga
Published: June 2024

The challenges experienced in the context of the pandemic have required a significant reconciliation between work and family domains due to confinement and the need to spend more time at home, which may have increased the levels of stress, anxiety, and depression, making it necessary to use resilient coping strategies to overcome the difficulties felt. This study examined the effect of resilient coping on the relationship between work-family conflict and stress, anxiety, and depression in this context. Data were collected using a self-report protocol from a sample of Portuguese workers (N = 476). The results indicated that work-family conflict was positively associated with stress, anxiety, and depression. Resilient coping established a negative relationship with stress, anxiety, and depression. The moderation effect was not corroborated; it was found that in the presence of the moderating variable (resilient coping), the relationship between the variables of work-family conflict and stress, anxiety, and depression was strengthened. This study reinforces the importance of appropriate interventions in resilient coping in the work-family context, which helps control stress, anxiety, and resilience levels.
Patient Adherence to a Real-World Digital, Asynchronous Weight Loss Program in Australia That Combines Behavioural and GLP-1 RA Therapy: A Mixed Methods Study
Authors: Talay Louis , Vickers Matt
Published: June 2024

Increasingly large numbers of people are using digital weight loss services (DWLSs) to treat being overweight and obesity. Although it is widely agreed that digital modalities improve access to care in general, obesity stakeholders remain concerned that many DWLSs are not comprehensive or sustainable enough to deliver meaningful health outcomes. This study adopted a mixed methods approach to assess why and after how long patients tend to discontinue Australia’s largest DWLS, a program that combines behavioural and pharmacological therapy under the guidance of a multidisciplinary care team. We found that in a cohort of patients who commenced the Eucalyptus DWLS between January and June 2022 (n = 5604), the mean program adherence was 171.2 (±158.2) days. Inadequate supplying of a patient’s desired glucose-like peptide-1 receptor agonist medication was the most common reason for discontinuation (43.7%), followed by program cost (26.2%), result dissatisfaction (9.9%), and service dissatisfaction (7.2%). Statistical tests revealed that ethnicity and age both had a significant effect on patient adherence. These findings suggest that DWLSs have the potential to improve access to comprehensive, continuous obesity care, but care models need to improve upon the one observed in the Eucalyptus Australia DWLS to mitigate common real-world program attrition factors.