bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification of Muscular Dystrophies from MR Images Improves Using the Swin Transformer Deep Learning Model
Authors: Mastropietro Alfonso , Casali Nicola , Taccogna Maria , D’Angelo Maria , Rizzo Giovanna , Peruzzo Denis
Published: June 2024

Muscular dystrophies present diagnostic challenges, requiring accurate classification for effective diagnosis and treatment. This study investigates the efficacy of deep learning methodologies in classifying these disorders using skeletal muscle MRI scans. Specifically, we assess the performance of the Swin Transformer (SwinT) architecture against traditional convolutional neural networks (CNNs) in distinguishing between healthy individuals, Becker muscular dystrophy (BMD), and limb–girdle muscular Dystrophy type 2 (LGMD2) patients. Moreover, 3T MRI scans from a retrospective dataset of 75 scans (from 54 subjects) were utilized, with multiparametric protocols capturing various MRI contrasts, including T1-weighted and Dixon sequences. The dataset included 17 scans from healthy volunteers, 27 from BMD patients, and 31 from LGMD2 patients. SwinT and CNNs were trained and validated using a subset of the dataset, with the performance evaluated based on accuracy and F-score. Results indicate the superior accuracy of SwinT (0.96), particularly when employing fat fraction (FF) images as input; it served as a valuable parameter for enhancing classification accuracy. Despite limitations, including a modest cohort size, this study provides valuable insights into the application of AI-driven approaches for precise neuromuscular disorder classification, with potential implications for improving patient care.
Abdominal MRI Unconditional Synthesis with Medical Assessment
Authors: Gonçalves Bernardo , Silva Mariana , Vieira Luísa , Vieira Pedro
Published: June 2024

Current computer vision models require a significant amount of annotated data to improve their performance in a particular task. However, obtaining the required annotated data is challenging, especially in medicine. Hence, data augmentation techniques play a crucial role. In recent years, generative models have been used to create artificial medical images, which have shown promising results. This study aimed to use a state-of-the-art generative model, StyleGAN3, to generate realistic synthetic abdominal magnetic resonance images. These images will be evaluated using quantitative metrics and qualitative assessments by medical professionals. For this purpose, an abdominal MRI dataset acquired at Garcia da Horta Hospital in Almada, Portugal, was used. A subset containing only axial gadolinium-enhanced slices was used to train the model. The obtained Fréchet inception distance value (12.89) aligned with the state of the art, and a medical expert confirmed the significant realism and quality of the images. However, specific issues were identified in the generated images, such as texture variations, visual artefacts and anatomical inconsistencies. Despite these, this work demonstrated that StyleGAN3 is a viable solution to synthesise realistic medical imaging data, particularly in abdominal imaging.
Association between Chronic Misophonia-Induced Stress and Gastrointestinal Pathology in Children—A Hypothesis
Authors: Bodo Cristina Raluca , Salcudean Andreea , Nirestean Aurel , Lukacs Emese , Lica Maria Melania , Muntean Daniela Lucia , Anculia Ramona Camelia , Popovici Ramona Amina , Neda Stepan Oana , Enătescu Virgil Radu , Strete Elena Gabriela
Published: June 2024

Misophonia is a neurophysiological disorder with behavioral implications, is complex and multifactorial in origin, and is characterized by an atypical and disproportionate emotional response to specific sounds or associated visual stimuli. Triggers include human-generated sounds, mainly sounds related to feeding and breathing processes, and repetitive mechanical sounds. In response to the triggering stimulus, the patient experiences immediate, high-intensity, disproportionate physical and emotional reactions that affect their quality of life and social functioning. The symptoms of misophonia can occur at any age, but onset in childhood or adolescence is most common. Affected children live in a constant state of anxiety, suffer continuous physical and emotional discomfort, and are thus exposed to significant chronic stress. Chronic stress, especially during childhood, has consequences on the main biological systems through the dysregulation of the hypothalamic–pituitary–adrenal axis, including the gastrointestinal tract. Here, we provide arguments for a positive correlation between misophonic pathology and gastrointestinal symptoms, and this hypothesis may be the starting point for further longitudinal studies that could investigate the correlations between these childhood vulnerabilities caused by misophonia and their effect on the gastrointestinal system. Further research to study this hypothesis is essential to ensure correct and timely diagnosis and optimal psychological and pharmacological support.
Visual Object Tracking Based on the Motion Prediction and Block Search in UAV Videos
Authors: Sun Lifan , Li Xinxiang , Yang Zhe , Gao Dan
Published: June 2024

With the development of computer vision and Unmanned Aerial Vehicles (UAVs) technology, visual object tracking has become an indispensable core technology for UAVs, and it has been widely used in both civil and military fields. Visual object tracking from the UAV perspective experiences interference from various complex conditions such as background clutter, occlusion, and being out of view, which can easily lead to tracking drift. Once tracking drift occurs, it will lead to almost complete failure of the subsequent tracking. Currently, few trackers have been designed to solve the tracking drift problem. Thus, this paper proposes a tracking algorithm based on motion prediction and block search to address the tracking drift problem caused by various complex conditions. Specifically, when the tracker experiences tracking drift, we first use a Kalman filter to predict the motion state of the target, and then use a block search module to relocate the target. In addition, to improve the tracker’s ability to adapt to changes in the target’s appearance and the environment, we propose a dynamic template updating network (DTUN) that allows the tracker to make appropriate template decisions based on various tracking conditions. We also introduce three tracking evaluation metrics: namely, average peak correlation energy, size change ratio, and tracking score. They serve as prior information for tracking status identification in the DTUN and the block prediction module. Extensive experiments and comparisons with many competitive algorithms on five aerial benchmarks, UAV20L, UAV123, UAVDT, DTB70, and VisDrone2018-SOT, demonstrate that our method achieves significant performance improvements. Especially in UAV20L long-term tracking, our method outperforms the baseline in terms of success rate and accuracy by 19.1% and 20.8%, respectively. This demonstrates the superior performance of our method in the task of long-term tracking from the UAV perspective, and we achieve a real-time speed of 43 FPS.
Purported Self-Organized Criticality of the Cardiovascular Function: Methodological Considerations for Zipf’s Law Analysis
Authors: Fortrat Jacques-Olivier
Published: June 2024

Self-organized criticality is a universal theory for dynamical systems that has recently been applied to the cardiovascular system. Precise methodological approaches are essential for understanding the dynamics of cardiovascular self-organized criticality. This study examines how the duration and quality of data recording affect the analysis of cardiovascular self-organized criticality, with a focus on the beat-by-beat heart rate variability time series obtained from seven healthy subjects in a standing position. Drawing a Zipf diagram, we evaluated the distribution of cardiovascular events of bradycardia and tachycardia. We identified tipping points for the distribution of both bradycardia and tachycardia events. By varying the recording durations (1, 2, 5, 10, 20, 30, and 40 min) and sampling frequencies (500, 250, and 100 Hz), we investigated their influence on the observed distributions. While shorter recordings can effectively capture cardiovascular events, they may underestimate the variables describing their distribution. Additionally, the tipping point of the Zipf distribution differs between bradycardia and tachycardia events. Comparisons of the distribution of bradycardia and tachycardia events should be conducted using long data recordings. Utilizing devices with lower sampling frequencies may compromise data fidelity. These insights contribute to refining experimental protocols and advancing our understanding of the complex dynamics underlying cardiovascular regulation.
Finite-Time Dynamics of an Entanglement Engine: Current, Fluctuations and Kinetic Uncertainty Relations
Authors: Bourgeois Jeanne , Blasi Gianmichele , Khandelwal Shishir , Haack Géraldine
Published: June 2024

Entanglement engines are autonomous quantum thermal machines designed to generate entanglement from the presence of a particle current flowing through the device. In this work, we investigate the functioning of a two-qubit entanglement engine beyond the steady-state regime. Within a master equation approach, we derive the time-dependent state, the particle current, as well as the associated current correlation functions. Our findings establish a direct connection between coherence and internal current, elucidating the existence of a critical current that serves as an indicator for entanglement in the steady state. We then apply our results to investigate kinetic uncertainty relations (KURs) at finite times. We demonstrate that there is more than one possible definition for KURs at finite times. Although the two definitions agree in the steady-state regime, they lead to different parameter ranges for violating KUR at finite times.
A Semiparametric Bayesian Approach to Heterogeneous Spatial Autoregressive Models
Authors: Liu Ting , Xu Dengke , Ke Shiqi
Published: June 2024

Many semiparametric spatial autoregressive (SSAR) models have been used to analyze spatial data in a variety of applications; however, it is a common phenomenon that heteroscedasticity often occurs in spatial data analysis. Therefore, when considering SSAR models in this paper, it is allowed that the variance parameters of the models can depend on the explanatory variable, and these are called heterogeneous semiparametric spatial autoregressive models. In order to estimate the model parameters, a Bayesian estimation method is proposed for heterogeneous SSAR models based on B-spline approximations of the nonparametric function. Then, we develop an efficient Markov chain Monte Carlo sampling algorithm on the basis of the Gibbs sampler and Metropolis–Hastings algorithm that can be used to generate posterior samples from posterior distributions and perform posterior inference. Finally, some simulation studies and real data analysis of Boston housing data have demonstrated the excellent performance of the proposed Bayesian method.
Turkish Physical Education Teachers’ Use of Technology: Application and Diffusion of Technological Innovations
Authors: Konukman Ferman , Filiz Bijen
Published: June 2024

The purpose of this study was to determine Turkish physical education (PE) teachers’ level of technological innovation use and attitudes regarding their applications and diffusion. This study consisted of 678 Turkish PE teachers. In total, 265 (39.1%) of the PE teachers were female, and 413 (60.9%) were male. A sequential explanatory mixed-methods design was used in this study. “The Applying and Diffusing Technological Innovations Scale for Teachers” was used for data collection. The results showed that the main obstacles the PE teachers face in using technological innovations were the cost of products; security and privacy problems; the need for new versions and technical support; the lack of time; the lack of interest; difficulty in accessing technology; and the lack of understanding. Moreover, there was a significant difference in the tendency to apply and diffuse technological innovations in terms of gender, school type, and school level. We found that the “ability to use innovations” sub-dimension affects the PE teachers’ tendencies to apply and diffuse technology. As a result, we recommend providing various training programs on technological innovations to the older/longer-serving PE teachers, especially those working in public schools and secondary schools.
ANN for Temperature and Irradiation Prediction and Maximum Power Point Tracking Using MRP-SMC
Authors: Jlidi Mokhtar , Barambones Oscar , Hamidi Faiçal , Aoun Mohamed
Published: June 2024

Currently, artificial intelligence (AI) is emerging as a dominant force in various technologies, owing to its unparalleled efficiency. Among the plethora of AI techniques available, neural networks (NNs) have garnered significant attention due to their adeptness in addressing diverse challenges, particularly for prediction tasks. This study offers a comprehensive review of predominant AI-based approaches to photovoltaic (PV) energy forecasting, with a particular emphasis on artificial neural networks (ANNs). We introduce a revolutionary methodology that amalgamates the predictive capabilities of ANN with the precision control afforded by the minimum-risk problem and sliding mode control (MRP-SMC), thereby revolutionizing the PV panel performance enhancement. Building upon this methodology, our hybrid approach utilizes the ANN as a proficient weather forecaster, accurately predicting the temperature and solar radiation levels impacting the panels. These forecasts serve as guiding principles for the MRP-SMC algorithm, enabling the proactive determination of the Maximum Power Point (MPP). Unlike conventional methods that grapple with weather unpredictability, the MRP-SMC algorithm transforms stochastic optimization challenges into controllable deterministic risk problems. Our method regulates the boost converter’s work cycle dynamically. This dynamic adaptation, guided by environmental predictions from ANNs, unlocks the full potential of PV panels, maximizing energy recovery efficiency. To train the model, we utilized a large dataset comprising 60,538 temperature and solar radiation readings from the Department of Systems Engineering and Automation at the Faculty of Engineering in Vitoria (University of the Basque Country). Our approach demonstrates a high regression coefficient (R = 0.99) and low mean square error (MSE = 0.0044), underscoring its exceptional ability to predict real energy values. In essence, this study proposes a potent fusion of artificial intelligence and control mechanisms that unleash the untapped potential of photovoltaic panels. By utilizing forecasts to guide the converter, we are paving the way for a future where solar energy shines brighter than ever.
Thermodynamics of Halite Scaling in Superhot Geothermal Systems
Authors: Ellingsen Lodin , Haug-Warberg Tore
Published: June 2024

Over the past decades, considerable research has been conducted on extracting energy from superhot geothermal reservoirs, where temperatures are higher than at the critical point of water. A major challenge when operating wells under such conditions is managing scaling in an effective manner. In this study, the thermodynamics of the precipitation and scaling of crystalline NaCl (halite) under superhot conditions is explored using the H2O–NaCl system as a proxy. Phase diagrams in pressure–enthalpy and pressure–entropy coordinates are used to illustrate how scaling occurs in idealized processes, such as the isenthalpic expansion of geothermal fluid to the wellhead or the isentropic power generation of a steam turbine. Particular emphasis is placed on explaining the non-trivial graphical composition of these phase diagrams in an accessible manner. A wellhead sample and an estimate of the downhole conditions are used as points of reference in the discussion of scaling. All thermodynamic properties, including the solubility of NaCl in water vapor, are calculated using a newly developed equation of state by the same authors as in this article.
Influence of Fish Species and Wood Type on Polycyclic Aromatic Hydrocarbons Contamination in Smoked Fish Meat
Authors: Savin Raul-Lucian , Ladoși Daniela , Ladoși Ioan , Păpuc Tudor , Becze Anca , Cadar Oana , Torök Iulia , Simedru Dorina , Mariș Ștefania Codruța , Coroian Aurelia
Published: June 2024

Despite the numerous sensory, organoleptic and nutritional qualities, fish meat may also contain some toxic compounds with negative effects on human health. Polycyclic aromatic hydrocarbons (PAHs) are a class of chemicals resulting from incomplete combustion, found at high levels in thermally processed foods, especially in smoked fish. This research studied the influence of wood type (beech, plum and oak) and fish species (rainbow trout, carp and Siberian sturgeon) on PAH contamination in hot smoked fish. Benzo(a)Piren, Σ4PAHs and Σ15PAHs were considered as main indicators of PAH contamination. All-PAHs was quantified in all samples, indicating a specific dynamic of values due to the influence of variables. Generally, BaP (benzo(a)pyrene) content in the samples ranged from 0.11 µg/kg to 8.63 µg/kg, Σ4PAHs from 0.70 µg/kg to 45.24 µg/kg and Σ15PAHs from 17.54 µg/kg to 450.47 µg/kg. Thus, plum wood promoted the highest levels of PAHs, followed by oak and beech. Carp and Siberian sturgeon presented the highest concentrations of PAHs. Some of these parameters had levels that exceeded the limits allowed by legislation via Commission Regulation (EU) No 835/2011. Results revealed BaP levels > 2 µg/kg when plum wood was used in rainbow trout (4.04 µg/kg), carp (4.47 µg/kg) and Siberian sturgeon (8.63 µg/kg). Moreover, the same trend was found for Σ4PAHs, which exceeded 12 µg/kg in rainbow trout (17.57 µg/kg), carp (45.24 µg/kg) and Siberian sturgeon (44.97 µg/kg).
Fabrication and Characterization of Chitosan and Gelatin-Based Antimicrobial Films Incorporated with Different Essential Oils
Authors: Asghar Laiba , Sahar Amna , Khan Muhammad Issa , Shahid Muhammad
Published: June 2024

This study was performed to check the effect of different essential oils on chitosan and gelatin-based antimicrobial films. Films prepared from biopolymers contain better mechanical strength but lack in moisture barrier properties. In order to increase the moisture barrier properties of chitosan and gelatin-based films in the current research work, different essential oils, i.e., thyme, cinnamon, basil, ginger, and cumin, at varying concentrations (1.0, 1.5, and 2.0%) were incorporated. Moreover, the concentrations of glycerol (plasticizer) and emulsifier (Tween 20) were kept constant to maintain homogeneity in the research. Antimicrobial films composed of gelatin and chitosan infused with essential oils were evaluated for their physicochemical (emulsion stability, particle size, and viscosity), FT-IR, microstructural (scanning electron microscopy), moisture barrier (water vapor permeability), and antimicrobial properties (E. coli, Salmonella, and S. aureus). Study outcomes elucidated significant variations (p < 0.05) as the concentration of essential oil was increased in the film solutions. An increased concentration of essential oil (2.0%) significantly enhanced the moisture barrier properties (1.12 ± 0.03 g.mm/kPa.h.m2). Nevertheless, the tensile strength decreased (38.60 ± 1.4 to 31.50 ± 1.5 MPa) from 1 to 2%. The increase in essential oil concentration in the emulsion-based films also influenced their physicochemical characteristics, such as droplet size, viscosity, and emulsion stability. At lower concentrations (1.0%), films exhibited a uniform microstructure but lacked moisture barrier properties. Antimicrobial properties against E. coli, Salmonella, and S. aureus showed an increased inhibition effect as the concentration of essential oil was increased. Of the essential oil-based films, ginger- and basil-based films showed greater inhibition effects as compared to the other essential oils. Overall, antimicrobial films containing a 1.5% concentration of ginger and basil oil showed better results as compared to the other treatments for mechanical, moisture barrier, and antimicrobial properties, while films with a 2.0% oil concentration showed better antimicrobial and moisture barrier properties but lacked in mechanical properties. Essential oil-based antimicrobial films have prospective applications in foods, specifically in fresh and processed food items such as seafood, meat, chicken, and sausages.
Fractal Tent Map with Application to Surrogate Testing
Authors: Kopets Ekaterina , Rybin Vyacheslav , Vasilchenko Oleg , Butusov Denis , Fedoseev Petr , Karimov Artur
Published: June 2024

Discrete chaotic maps are a mathematical basis for many useful applications. One of the most common is chaos-based pseudorandom number generators (PRNGs), which should be computationally cheap and controllable and possess necessary statistical properties, such as mixing and diffusion. However, chaotic PRNGs have several known shortcomings, e.g., being prone to chaos degeneration, falling in short periods, and having a relatively narrow parameter range. Therefore, it is reasonable to design novel simple chaotic maps to overcome these drawbacks. In this study, we propose a novel fractal chaotic tent map, which is a generalization of the well-known tent map with a fractal function introduced into the right-hand side. We construct and investigate a PRNG based on the proposed map, showing its high level of randomness by applying the NIST statistical test suite. The application of the proposed PRNG to the task of generating surrogate data and a surrogate testing procedure is shown. The experimental results demonstrate that our approach possesses superior accuracy in surrogate testing across three distinct signal types—linear, chaotic, and biological signals—compared to the MATLAB built-in randn() function and PRNGs based on the logistic map and the conventional tent map. Along with surrogate testing, the proposed fractal tent map can be efficiently used in chaos-based communications and data encryption tasks.
Our New Normal: Pediatric Nurse Residents’ Experiences with Transition to Practice during the COVID-19 Pandemic
Authors: Hinderer Katherine A. , Klima Dennis W. , Kellogg Marni B. , Morello Cecelia , Myers Karen , Wentland Beth A.
Published: June 2024

This phenomenological qualitative study examined the lived experience of pediatric nurse residents’ transition to practice during the COVID-19 pandemic. The purposive sample included nine pediatric nurses, participating in a nurse residency program, who entered the nursing profession during the first year of the pandemic. The setting was a free-standing, Magnet-recognized, pediatric academic medical center in the Northeastern U.S. Individual interviews were audio recorded and transcribed. Narratives were analyzed using a hermeneutic phenomenological approach. Five themes emerged from the data: Our New Normal; The Rules Keep Changing; I’m Not Ready for This (transition to practice); The Toll of COVID; and Shattered Family-Centered Care. Sub-themes emerged in The Toll of COVID theme: COVID and the Nursing Care Environment, Emotional Toll of COVID, Burnout: A Universal Truth, and The Pandemic within the Pandemic. The nurse residents’ narratives uncovered the essence of their uncertainty, sorrow, growth, and resilience. Through the eyes of pediatric nurse residents, this study illuminated the experiences of these novices as they entered the nursing profession amid a pandemic.
Efficacy of Human Recombinant Growth Hormone in Females of a Non-Obese Hyperglycemic Mouse Model after Birth with Low Birth Weight
Authors: Tokunaga Wataru , Nagano Nobuhiko , Matsuda Kengo , Nakazaki Kimitaka , Shimizu Shoichi , Okuda Koh , Aoki Ryoji , Fuwa Kazumasa , Murakami Hitohiko , Morioka Ichiro
Published: June 2024

We examined whether the administration of growth hormone (GH) improves insulin resistance in females of a non-obese hyperglycemic mouse model after birth with low birth weight (LBW), given that GH is known to increase muscle mass. The intrauterine Ischemia group underwent uterine artery occlusion for 15 min on day 16.5 of gestation. At 4 weeks of age, female mice in the Ischemia group were divided into the GH-treated (Ischemia-GH) and non-GH-treated (Ischemia) groups. At 8 weeks of age, the glucose metabolism, muscle pathology, and metabolome of liver were assessed. The insulin resistance index improved in the Ischemia-GH group compared with the Ischemia group (p = 0.034). The percentage of type 1 muscle fibers was higher in the Ischemia-GH group than the Ischemia group (p < 0.001); the muscle fiber type was altered by GH. In the liver, oxidative stress factors were reduced, and ATP production was increased in the Ischemia-GH group compared to the Ischemia group (p = 0.014), indicating the improved mitochondrial function of liver. GH administration is effective in improving insulin resistance by increasing the content of type 1 muscle fibers and improving mitochondrial function of liver in our non-obese hyperglycemic mouse model after birth with LBW.
Preparation of Esterified Starches with Different Amylose Content and Their Blending with Polybutylene Succinate
Authors: Liu Shuning , Tang Shi , Lu Yuanhao , Su Tingting , Wang Zhanyong
Published: June 2024

Three types of starch with different amylose content were esterified and blended with polybutylene succinate (PBS) to obtain esterified manioc starch/PBS (EMS/PBS), esterified corn starch/PBS (ECS/PBS), and esterified waxy corn starch/PBS (EWS/PBS) composites. The EMS/PBS and ECS/PBS composites with high amylose content displayed typical V-type crystal structures. The original crystals of EWS, which had low amylose content, were disrupted during the esterification process. EWS exhibited the strongest interaction with PBS and the most favorable interface compatibility. The pyrolysis temperature was in order of EMS/PBS < ECS/PBS < EWS/PBS. The elongation at break of the three blends was higher than that of pure PBS. The esterification and plasticization of the EWS/PBS composite were the most comprehensive. The EWS/PBS composite showed the lowest storage modulus (G’) and complex viscosity (η*). The interfacial bonding force of the composite materials increased with more amylopectin, decreasing intermolecular forces and destroying crystal structures, which decreased G’ and η* and increased toughness. The EWS/PBS composite, with the least amylose content, had the best hydrophobicity and degradation performance.
SARS-CoV-2 Viroporin E Induces Ca2+ Release and Neuron Cell Death in Primary Cultures of Rat Hippocampal Cells Aged In Vitro
Authors: López-Vázquez Sara , Villalobos Carlos , Núñez Lucía
Published: June 2024

The COVID-19 pandemic was caused by infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which may lead to serious respiratory, vascular and neurological dysfunctions. The SARS-CoV-2 envelope protein (E protein) is a structural viroporin able to form ion channels in cell membranes, which is critical for viral replication. However, its effects in primary neurons have not been addressed. Here we used fluorescence microscopy and calcium imaging to study SARS-CoV-2 viroporin E localization and the effects on neuron damage and intracellular Ca2+ homeostasis in a model of rat hippocampal neurons aged in vitro. We found that the E protein quickly enters hippocampal neurons and colocalizes with the endoplasmic reticulum (ER) in both short-term (6–8 days in vitro, DIV) and long-term (20–22 DIV) cultures resembling young and aged neurons, respectively. Strikingly, E protein treatment induces apoptosis in aged neurons but not in young neurons. The E protein induces variable increases in cytosolic Ca2+ concentration in hippocampal neurons. Ca2+ responses to the E protein are due to Ca2+ release from intracellular stores at the ER. Moreover, E protein-induced Ca2+ release is very small in young neurons and increases dramatically in aged neurons, consistent with the enhanced Ca2+ store content in aged neurons. We conclude that the SARS-CoV-2 E protein quickly translocates to ER endomembranes of rat hippocampal neurons where it releases Ca2+, probably acting like a viroporin, thus producing Ca2+ store depletion and neuron apoptosis in aged neurons and likely contributing to neurological damage in COVID-19 patients.
The Importance of Molecular Genetic Testing for Precision Diagnostics, Management, and Genetic Counseling in MODY Patients
Authors: Butnariu Lăcrămioara Ionela , Bizim Delia Andreia , Oltean Carmen , Rusu Cristina , Pânzaru Monica Cristina , Păduraru Gabriela , Gimiga Nicoleta , Ghiga Gabriela , Moisă Ștefana Maria , Țarcă Elena , Starcea Iuliana Magdalena , Popa Setalia , Trandafir Laura Mihaela
Published: June 2024

Maturity-onset diabetes of the young (MODY) is part of the heterogeneous group of monogenic diabetes (MD) characterized by the non-immune dysfunction of pancreatic β-cells. The diagnosis of MODY still remains a challenge for clinicians, with many cases being misdiagnosed as type 1 or type 2 diabetes mellitus (T1DM/T2DM), and over 80% of cases remaining undiagnosed. With the introduction of modern technologies, important progress has been made in deciphering the molecular mechanisms and heterogeneous etiology of MD, including MODY. The aim of our study was to identify genetic variants associated with MODY in a group of patients with early-onset diabetes/prediabetes in whom a form of MD was clinically suspected. Genetic testing, based on next-generation sequencing (NGS) technology, was carried out either in a targeted manner, using gene panels for monogenic diabetes, or by analyzing the entire exome (whole-exome sequencing). GKC-MODY 2 was the most frequently detected variant, but rare forms of KCNJ11-MODY 13, specifically, HNF4A-MODY 1, were also identified. We have emphasized the importance of genetic testing for early diagnosis, MODY subtype differentiation, and genetic counseling. We presented the genotype–phenotype correlations, especially related to the clinical evolution and personalized therapy, also emphasizing the particularities of each patient in the family context.
A Cross-Sectional Exploratory Study of Cardiovascular Risk Biomarkers in Non-Obese Women with and without Polycystic Ovary Syndrome: Association with Vitamin D
Authors: Nandakumar Manjula , Das Priya , Sathyapalan Thozhukat , Butler Alexandra E. , Atkin Stephen L.
Published: June 2024

Vitamin D is proposed to have a protective effect against cardiovascular disease, though the mechanism is unclear. Vitamin D deficiency is common in polycystic ovary syndrome (PCOS), where it is strongly related to obesity, insulin resistance (IR) and risk of cardiovascular disease. To determine if the inherent pathophysiology of PCOS or vitamin D levels are linked to dysregulation of cardiovascular risk proteins (CVRPs), a study in non-obese women with PCOS and without IR was undertaken. Our hypothesis was that the levels of vitamin D3 and its active metabolite would be associated with CVRPs comparably in women with and without PCOS. In women with PCOS (n = 29) and controls (n = 29), 54 CVRPs were determined by Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement and correlated to 25-hydroxyvitamin D3 (25(OH)D3) and the active 1,25-dihydroxyvitamin D3 (1,25(OH)2D3) measured by gold standard isotope-dilution liquid chromatography tandem mass spectrometry. Women with PCOS had comparable IR and systemic inflammation (normal C-reactive protein) to control women, though had higher free androgen index and anti-Mullerian hormone levels. 25(OH)D3 and 1,25(OH)2D3 levels did not differ between groups. Nine CVRPs were higher in PCOS (p < 0.05) (Galectin-9, Brother of CDO, C-motif chemokine 3, Interleukin-18 receptor-1, Thrombopoietin, Interleukin-1 receptor antagonist protein, Programmed cell death 1 ligand-2, Low-affinity immunoglobulin gamma Fc-region receptor II-b and human growth hormone), whilst 45 CVRPs did not differ. 25(OH)D3 correlated with five CVRPs in PCOS and one in controls (p < 0.05). Despite the women with PCOS not exhibiting overt systemic inflammation, 9 of 54 CVRPs were elevated, all relating to inflammation, and 5 of these correlated with 25(OH)D3, suggesting an ongoing underlying inflammatory process in PCOS even in the absence of obesity/IR.
Ruthenium Antivenom Inhibits the Defibrinogenating Activity of Crotalus adamanteus Venom in Rabbits
Authors: Nielsen Vance G.
Published: June 2024

Eastern Diamondback Rattlesnake (Crotalus adamanteus) envenomation is a medical emergency encountered in the Southeastern United States. The venom contains a snake venom thrombin-like enzyme (SVTLE) that is defibrinogenating, causing coagulopathy without effects on platelets in humans. This investigation utilized thrombelastographic methods to document this coagulopathy kinetically on the molecular level in a rabbit model of envenomation via the analyses of whole blood samples without and with platelet inhibition. Subsequently, the administration of a novel ruthenium compound containing site-directed antivenom abrogated the coagulopathic effects of envenomation in whole blood without platelet inhibition and significantly diminished loss of coagulation in platelet-inhibited samples. This investigation provides coagulation kinetic insights into the molecular interactions and results of SVTLE on fibrinogen-dependent coagulation and confirmation of the efficacy of a ruthenium antivenom. These results serve as a rationale to investigate the coagulopathic effects of other venoms with this model and assess the efficacy of this site-directed antivenom.
What Can Be Learned from the Partitioning Behavior of Proteins in Aqueous Two-Phase Systems?
Authors: Uversky Vladimir N. , Madeira Pedro P. , Zaslavsky Boris Y.
Published: June 2024

This review covers the analytical applications of protein partitioning in aqueous two-phase systems (ATPSs). We review the advancements in the analytical application of protein partitioning in ATPSs that have been achieved over the last two decades. Multiple examples of different applications, such as the quality control of recombinant proteins, analysis of protein misfolding, characterization of structural changes as small as a single-point mutation, conformational changes upon binding of different ligands, detection of protein–protein interactions, and analysis of structurally different isoforms of a protein are presented. The new approach to discovering new drugs for a known target (e.g., a receptor) is described when one or more previous drugs are already available with well-characterized biological efficacy profiles.
Limited Domain SnSb@N-PC Composite Material as a High-Performance Anode for Sodium Ion Batteries
Authors: Liu Zhaomeng , Ren Hailong , Fu Shizheng , Yang Wentao , Li Yihua , Jiao Yang , Zhang Botao
Published: June 2024

Anode materials have a vital influence on the performance of sodium ion batteries. In this paper, SnSb nanoparticles were distributed uniformly in N-doped three-dimensional porous carbon (SnSb@N-PC), which effectively avoided the agglomeration of alloy nanoparticles and greatly improved the capacity retention rate of SnSb@N-PC. At the same time, the porous carbon substrate brings higher conductivity, larger specific surface area, and more sodium storage sites, which makes the material obtain excellent sodium storage properties. The first discharge-specific capacity of SnSb@N-PC was 846.3 mAh g−1 at the current density of 0.1 A g−1, and the specific capacity remained at 483 mAh g−1 after 100 cycles. Meanwhile, the specific capacity of SnSb@N-PC was kept at 323 mAh g−1 after 400 cycles at a high current density of 1.5 A g−1, which indicated that the recombination of SnSb with porous carbon played a key role in the electrochemical performance of SnSb. The contribution of capacitance contrast capacity was able to reach more than 90% by the cyclic voltammetry (CV) test at high sweep speed, and larger Na+ diffusivity was obtained by the constant current intermittent titration technique (GITT) test, which explains the good rate performance of SnSb@N-PC.
A Study of the Moisture Absorption Characteristics of Vinyl Ester Polymer and Unidirectional Glass Fibre Vinyl Ester Laminates
Authors: Thomason James , Xypolias Georgios
Published: June 2024

Vinyl esters are increasingly being used as the matrix polymer in fibre-reinforced composites for demanding large applications which experience long-term exposure to moist and wet conditions. This paper presents the results of a study of ageing due to moisture absorption in vinyl ester polymer and glass fibre–vinyl ester laminates. The moisture uptake kinetics of the two neat VE polymers, cured at different conditions, and their glass-reinforced composites has been characterised by gravimetric methods. These studies have been carried out using submersion in water at 23 °C and 50 °C and exposure to high relative humidity moisture conditions at room temperature. A dynamic mechanical analysis characterisation of the glass transition temperatures of both the aged matrix and the composite is also presented.
Friction Stir Processed AA5754-Al2O3 Nanocomposite: A Study on Tribological Characteristics
Authors: Rohim M. Nafea M. , Abdullah Mahmoud E. , Mohammed Moustafa M. , Kubit Andrzej , Aghajani Derazkola Hamed
Published: June 2024

This study investigates the tribological properties of an AA 5754 aluminum alloy composite reinforced with the nanopowder of Al2O3, fabricated using the friction stir processing (FSP) technique with blind holes. The aim is to analyze the effects of varying the tool rotational speed (rpm) and blind hole diameter on the wear and friction behavior of the produced composite. A pin-on disk test is conducted under dry conditions and room temperature to assess the tribological properties against steel. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDS) is employed to examine the worn and wear surfaces of the produced composites post test. The results indicate that increasing the applied load results in a decrease in the coefficient of friction (COF), with values ranging from 0.775 to 0.852 for 10 N and 0.607 to 0.652 for 20 N. Moreover, the wear rate diminishes with higher Al2O3 content and optimal FSP tool rotation (1280 rpm). Hardness analysis reveals variations between 33–42 HV and 35–39 HV, influenced by nanoparticle distribution. The composite demonstrates superior wear resistance compared to raw AA5754 aluminum due to its reinforced nature. However, high FSP tool rotation rates lead to abrasive wear and surface cracks. These findings offer insights into optimizing FSP parameters to enhance the tribological performance of nano-reinforced aluminum alloys.
Physiological and Biochemical Responses of the Green Tide-Forming Algae, Ulva Species, under Different Nutrient Conditions on Jeju Island, Korea
Authors: Moon Kyeonglim , Choi Sun Kyeong , Ham Seong Bin , Son Young Baek , Kang Yun Hee , Park Sang Rul
Published: June 2024

In this study, we investigated the physiological and biochemical responses of Ulva species to variation in nutrient availability. Sampling was conducted at two sites on Jeju Island, Korea, namely, Handong, which is close to seven intensive land-based fish farms, and Hado, which has no apparent nearby nutrient sources. We examined the water column nutrient concentrations, nitrate reductase (NR) activity, nitrate uptake efficiency, tissue C, N, and P content, and stable isotope ratios of Ulva species. Water column NH4+, NO3− + NO2−, and PO43− concentrations were significantly higher at Handong than at Hado. NR activity and tissue N content of Ulva species were significantly higher at Handong than at Hado. Notably, nitrate uptake efficiency was inversely proportional to NR activity and tissue N content. The physiological and biochemical responses of Ulva species were closely related to dissolved inorganic nitrogen, which stimulates Ulva species to regulate growth. Additionally, the δ15N values of Ulva tissues at both sites were within the previously reported range for fresh groundwater. Therefore, the main nitrogen source for Ulva growth may be submerged groundwater with high nutrient concentrations. Our results provide invaluable information for estimating dissolved inorganic nitrogen levels in water, which may facilitate development of management policies.
Deep-Learning-Based Stereo Matching of Long-Distance Sea Surface Images for Sea Level Monitoring Systems
Authors: Yang Ying , Lu Cunwei , Li Zhenhua
Published: June 2024

Due to the advantages of coastal areas in the fields of agriculture, transport, and fishing, increasingly more people are moving to these areas. Sea level information is important for these people to survive after extreme sea level events. With the recent improvements in computing and storage capacities, image analysis as a new measuring method is being rapidly developed and widely applied. In this paper, a multi-camera-based sea level height measuring system was built along Japan’s coast and a deep-learning-based stereo matching method has been proposed for this system to complete 3D measurements. In this system, cameras are set with long base distances to ensure the long-distance monitoring system’s precision, which causes a huge difference between the fields of view of the left and right cameras. Since most common network structures complete stereo matching by depth-wise cross-correlation between left and right images, they rely too much on the high-quality rectification of two images and fail on our long-distance sea surface images. We established a feature detection and matching network to realize sea wave extraction and sparse stereo matching for the system. Based on our previous result using the traditional method, the initial disparity was computed to reduce the search range of stereo matching. A training set with 785 pairs of sea surface images and 10,172 pairs of well-matched sea wave images was constructed to supervise the network. The experimental results verified that the proposed method can realize sea wave extraction and mask generation. It can also realize sparse matching of sea surface images regardless of poor rectification.
Theoretical and Numerical Analysis of Ocean Buoy Stability Using Simplified Stability Parameters
Authors: Zheng Huiyuan , Chen Yonghua , Liu Qingkui , Zhang Zhigang , Li Yunzhou , Li Min
Published: June 2024

The stability performance of the buoy is an important parameter that should be taken into account when designing marine buoys. This paper introduces a theoretical and numerical analysis method to examine the stability of marine buoys, including analysis of the initial stability and large inclination stability by calculating the natural period, metacentric height, static stability, and dynamic stability, deriving the calculation process of the static stability lever in detail to obtain the righting moment, and so on, showing that the designed buoy in this paper has sufficient stability performance with theoretically excellent resistance performance to the wind and waves. Additionally, the hydrodynamic performance of the buoy at different heights is also further analyzed for structural optimization, which concluded that the buoy would have a more balanced stability performance when the buoy’s width-to-height ratio is 0.375–0.5, hoping that the computational model and ideas used in this paper can provide a reference for the theoretical stability analysis and buoy design of other types of buoys.
Facial Recognition Technology in Policing and Security—Case Studies in Regulation
Authors: Lynch Nessa
Published: June 2024

Technology-enabled state surveillance has evolved rapidly to allow real-time remote tracking and surveillance of people and vehicles and the aggregation of vast amounts of data on people and their movements, networks, and relationships. Facial recognition technology (FRT) comprises a suite of technologies that allows verification, identification, and categorisation by analysing a person’s facial image. Such technologies impact fundamental rights, such as privacy, freedom of expression, and freedom of assembly, but can also be used to detect, investigate, and deter serious crime and harm and to counter threats to security, thus promoting collective interests in security and public safety. These impacts have been considered in terms of scholarship and advocacy, but the shape of principled regulation is less well traversed. This contribution examines three contemporary case studies of the regulation of FRT in policing and security to analyse the challenges in regulating this technology.
Monitoring Fatigue Damage of Orthotropic Steel Decks Using Nonlinear Ultrasonic Waves
Authors: Liu Jiahe , Zheng Fangtong , Shen Wei , Li Dongsheng
Published: June 2024

Orthotropic steel decks (OSDs) are commonly used in the construction of bridges due to their load-bearing capabilities. However, they are prone to fatigue damage over time due to the cyclic loads from vehicles. Therefore, the early structural health monitoring of fatigue damage in OSDs is crucial for ensuring bridge safety. Moreover, Lamb waves, as elastic waves propagating in OSD plate-like structures, are characterized by their long propagation distances and minimal attenuation. This paper introduces a method of emitting high-energy ultrasonic waves onto the OSD surface to capture the nonlinear Lamb waves formed, thereby calculating the nonlinear parameters. These parameters are then correlated with the fatigue damage endured, forming a damage index (DI) for monitoring the fatigue life of OSDs. Experimental results indicate that as fatigue damage increases, the nonlinear parameters exhibit a significant initial increase followed by a decrease. The behavior is distinct from the characteristic parameters of linear ultrasound (velocity and energy), which also exhibit changes but to a relatively smaller extent. The proposed DI and fatigue life based on nonlinear parameters can be fitted with a Gaussian curve, with the R-squared value of the fitting curve being close to 1. Additionally, this paper discusses the influence of rib welds within the OSDs on the DI, whereby as fatigue damage increases, it enlarges the value of the nonlinear parameters without altering their trend. The proposed method provides a more effective approach for monitoring early fatigue damage in OSDs.