bluuebunny/crossref_metadata_2025 huggingface dataset:
Injuries and Associated Factors in Swedish Sporting and Utility Trial Dogs—A Cross-Sectional Study
Authors: Essner Ann , Kjellerstedt Catarina , Hesbach Amie L. , Igelström Helena
Published: January 2024

Canine sporting competitions, e.g., agility, obedience, rally obedience, and utility trials, e.g., protection, tracking, search, and messenger, are physically and mentally demanding disciplines. This study aimed to describe the types and frequencies of injuries experienced amongst Swedish sporting and utility trial dogs and to explore associations between discipline, breed, sex, neuter status, age, and injury history. Dog handlers provided information on competition-level dogs (n = 1582) through a cross-sectional survey. The overall proportion of dogs sustaining any injury during their lifetime, whether it was during competition, training, or outside of sport, was 58.7% (n = 928). Muscular, joint, and dermatologic injuries were most commonly reported and the most common injury locations were the thoracic, lumbar and lumbosacral spine, paw, head, shoulder, and stifle. According to multivariate analysis, Border Collie (adjusted OR 1.93), Belgian Malinois (adjusted OR 2.51) and higher age at the time of report (adjusted OR 1.81–9.67) increased the odds of injury history. Our results provide more understanding of injuries in sporting and utility dogs and contribute to injury prevention strategies that potentially enhance canine welfare.
Proteomics Analysis of Pregnancy in Ewes under Heat Stress Conditions and Melatonin Administration
Authors: Bouroutzika Efterpi , Proikakis Stavros , Theodosiadou Ekaterini K. , Vougas Konstantinos , Katsafadou Angeliki I. , Tsangaris George T. , Valasi Irene
Published: January 2024

Melatonin is an indoleamine with broad spectrum properties that acts as a regulator of antioxidant and immune response in organisms. In our previous studies, melatonin improved redox status and inflammatory response in pregnant ewes under heat stress conditions. In the present study, using proteomics, the proteins regulated by melatonin during different stages of pregnancy and lambing were assessed. Twenty-two ewes equally divided into two groups, the melatonin (M) (n = 11) and control (C) group (n = 11), participated in the study and were exposed to heat stress during the first months of pregnancy. In the M group, melatonin implants were administered throughout pregnancy, every 40 days, until parturition (a total of four implants per ewe). Blood samples were collected at the beginning of the study simultaneously with the administration of the first melatonin implant (blood samples M1, C1), mating (M2, C2), second implant (M3, C3), fourth implant (M4, C4) and parturition (M5, C5), and MALDI-TOF analysis was performed. The results revealed the existence of 42 extra proteins in samples M2, M3 and M4 and 53 in M5 (sample at parturition) that are linked to melatonin. The biological processes of these proteins refer to boosted immune response, the alleviation of oxidative and endoplasmic reticulum stress, energy metabolism, the protection of the maternal organism and embryo development. This proteomics analysis indicates that melatonin regulates protective mechanisms and controls cell proliferation under exogenous or endogenous stressful stimuli during pregnancy and parturition.
Survival Estimation Using Multistate Cormack–Jolly–Seber Models—The Case of the Bearded Vulture Gypaetus barbatus in Spain
Authors: Navarro Inmaculada , Farfán Miguel Ángel , Gil Juan Antonio , Muñoz Antonio Román
Published: January 2024

The bearded vulture (Gypaetus barbatus) is an endangered species with a specialist osteophagous (bone) diet. We estimated the survival and productivity of this vulture in the Aragonese Pyrenees, where the main population of the species in Europe is found. We used a database covering a period of 33 years (1987–2020). To estimate the probability of survival, we used Cormack–Jolly–Seber models with a Bayesian approach. Our models estimated a survival rate of 0.90 ± 0.08 in juveniles, 0.95 ± 0.04 in subadults and 0.92 ± 0.05 in adults. The survival probability increased over the study period in adults and subadults but not in juveniles. By contrast, productivity decreased over the same period. Our study provides updated information on the status of two demographic parameters of great importance to the species and allows us to identify the most vulnerable age classes and to plan conservation actions to improve the situation of the species in a territory that is a donor of specimens for reintroduction projects. The estimated survival values suggest that more caution should be exercised when planning these feeding points according to the use the species makes of them.
Effects of Photoperiod on Survival, Growth, Physiological, and Biochemical Indices of Redclaw Crayfish (Cherax quadricarinatus) Juveniles
Authors: Nie Xiangxing , Huang Cuixue , Wei Jie , Wang Yakun , Hong Kunhao , Mu Xidong , Liu Chao , Chu Zhangjie , Zhu Xinping , Yu Lingyun
Published: January 2024

Through a 30-day experiment, this study investigated the effects of five photoperiods (0L:24D, 6L:18D, 12L:12D, 18L:6D, and 24L:0D) on the survival, enzyme activity, body color, and growth-related gene expression of redclaw crayfish (Cherax quadricarinatus) juveniles. The results showed that C. quadricarinatus juveniles under 18L:6D and 24L:0D photoperiods exhibited the highest survival rate, which was significantly higher than the survival rates of juveniles under the other three photoperiods (p < 0.05). However, the 0L:24D group had the highest final body weight and weight gain rate, significantly surpassing those of the 12L:12D, 18L:6D, and 24L:0D groups (p < 0.05). Regarding enzyme activity and hormone levels, juveniles under the 18L:6D photoperiod exhibited relatively higher activity of superoxide dismutase (SOD), acid phosphatase (ACP), and lysozyme (LZM) enzymes than those under other photoperiods, but their levels of melatonin and cortisol were relatively low. In addition, the 24L:0D group showed the highest malondialdehyde (MDA) content. Analysis of gene expression levels revealed that retinoid X receptor (RXR) and α-amylase (α-AMY) genes in C. quadricarinatus juveniles exhibited significantly higher expression levels under the 18L:6D photoperiod than those under the other four photoperiods (p < 0.05). With increasing daylight exposure, the body color of C. quadricarinatus changed from pale blue to yellow–brown. In summary, C. quadricarinatus juveniles achieved high survival rates, good growth performance, strong antioxidant stress response, and immune defense capabilities under an 18 h photoperiod. Therefore, in the industrial seedling cultivation of redclaw crayfish, it is recommended to provide 18 h of daily light. Further, the study demonstrated the ability to manipulate the body color of C. quadricarinatus through controlled artificial photoperiods. These findings provide essential technical parameters needed for the industrial cultivation of C. quadricarinatus juveniles.
Efficacy and Experience of Bacteriophages in Biofilm-Related Infections
Authors: Gordon Monica , Ramirez Paula
Published: January 2024

Bacterial infection has always accompanied human beings, causing suffering and death while also contributing to the advancement of medical science. However, the treatment of infections has become more complex in recent times. The increasing resistance of bacterial strains to antibiotics has diminished the effectiveness of the therapeutic arsenal, making it less likely to find the appropriate empiric antibiotic option. Additionally, the development and persistence of bacterial biofilms have become more prevalent, attributed to the greater use of invasive devices that facilitate biofilm formation and the enhanced survival of chronic infection models where biofilm plays a crucial role. Bacteria within biofilms are less susceptible to antibiotics due to physical, chemical, and genetic factors. Bacteriophages, as biological weapons, can overcome both antimicrobial resistance and biofilm protection. In this review, we will analyze the scientific progress achieved in vitro to justify their clinical application. In the absence of scientific evidence, we will compile publications of clinical cases where phages have been used to treat infections related to biofilm. The scientific basis obtained in vitro and the success rate and safety observed in clinical practice should motivate the medical community to conduct clinical trials establishing a protocol for the proper use of bacteriophages.
In Vitro Activity of “Old” and “New” Antimicrobials against the Klebsiella pneumoniae Complex
Authors: Sękowska Alicja
Published: January 2024

The Klebsiella pneumoniae complex is a commonly isolated bacteria in human infections. These opportunistic pathogens pose a serious threat to public health due to their potential transmission to the human population. Resistance to carbapenems is a significant antimicrobial resistance mechanism, leading to limited therapeutic options. Therefore, the aim of this study was to evaluate the in vitro activity of fosfomycin, colistin, ceftazidime–avibactam, and meropenem–vaborbactam against multidrug-resistant K. pneumoniae complex strains. This study involved 160 strains of Gram-negative rods, comprising 138 K. pneumoniae and 22 K. variicola. The minimal inhibitory concentration of fosfomycin was estimated using the agar dilution method, and for colistin, the microdilution method was employed. Susceptibility to ceftazidime–avibactam and meropenem–vaborbactam was determined using the gradient strip method. All analyzed K. pneumoniae complex isolates produced extended-spectrum β-lactamases, and 60.0% exhibited carbapenemases. The majority of the analyzed strains were susceptible to fosfomycin and colistin (62.5%). Among pandrug-resistant K. pneumoniae complex isolates, the highest susceptibility was observed with colistin (43.9%). Fosfomycin demonstrated good activity against ESβLs- and VIM-positive isolates from this complex. Colistin also exhibited satisfactory in vitro activity against VIM- and KPC-positive isolates from the K. pneumoniae complex. Ceftazidime–avibactam displayed good activity against K. pneumoniae complex strains producing ESβLs, KPC, and OXA enzymes. Additionally, meropenem–vaborbactam showed satisfactory in vitro activity against ESβLs- and KPC-positive isolates from this complex.
Oxidative Damage and Telomere Length as Markers of Lung Cancer Development among Chronic Obstructive Pulmonary Disease (COPD) Smokers
Authors: Córdoba-Lanús Elizabeth , Montuenga Luis M. , Domínguez-de-Barros Angélica , Oliva Alexis , Mayato Delia , Remírez-Sanz Ana , Gonzalvo Francisca , Celli Bartolomé , Zulueta Javier J. , Casanova Ciro
Published: January 2024

Lung cancer (LC) constitutes an important cause of death among patients with Chronic Obstructive Pulmonary Disease (COPD). Both diseases may share pathobiological mechanisms related to oxidative damage and cellular senescence. In this study, the potential value of leucocyte telomere length, a hallmark of aging, and 8-OHdG concentrations, indicative of oxidative DNA damage, as risk biomarkers of LC was evaluated in COPD patients three years prior to LC diagnosis. Relative telomere length measured using qPCR and serum levels of 8-OHdG were determined at the baseline in 99 COPD smokers (33 with LC and 66 age-matched COPD without LC as controls). Of these, 21 COPD with LC and 42 controls had the biomarkers measured 3 years before. Single nucleotide variants (SNVs) in TERT, RTEL, and NAF1 genes were also determined. COPD cases were evaluated, which showed greater telomere length (p < 0.001) and increased serum 8-OHdG levels (p = 0.004) three years prior to LC diagnosis compared to the controls. This relationship was confirmed at the time of LC diagnosis. No significant association was found between the studied SNVs in cases vs. controls. In conclusion, this preliminary study shows that longer leucocyte telomere length and increased 8-OHdG serum levels can be useful as early biomarkers of the risk for future lung cancer development among COPD patients.
EGCG, a Green Tea Compound, Increases NO Production and Has Antioxidant Action in a Static and Shear Stress In Vitro Model of Preeclampsia
Authors: Bertozzi-Matheus Mariana , Bueno-Pereira Thaina Omia , Nunes Priscila Rezeck , Sandrim Valeria Cristina
Published: January 2024

Preeclampsia (PE) is a gestational hypertensive disease characterized by endothelial dysfunction. Epigallocatechin-3-gallate (EGCG), the main compound in green tea, is a promising therapeutic target for the disease. By activating eNOS, EGCG increased NO production and exerted an important antioxidant action, but its specific impact in the context of PE remains understudied. The aim of this study is to evaluate the effects of EGCG on endothelial function in static and shear stress in in vitro models of PE. Endothelial cells were incubated with healthy (HP) and preeclamptic (PE) pregnant women’s plasma, and the latter group was treated with EGCG. Additionally, NOS (L-NAME) and PI3K protein (LY249002) inhibitors were also used. The levels of NO, ROS, and O2•− were evaluated, as well as the antioxidant potential. These investigations were also carried out in a shear stress model. We found that EGCG increases the NO levels, which were reduced in the PE group. This effect was attenuated with the use of L-NAME and LY249002. Furthermore, EGCG increased the antioxidant capacity of PE, but its action decreased with LY294002. In cells subjected to shear stress, EGCG increased nitrite levels in the PE group and maintained its action on the antioxidant capacity. This is the first study of the effects of EGCG in this experimental model, as well as the investigation of its effects along with shear stress. Our findings suggest that EGCG improves parameters of endothelial dysfunction in vitro, making it a promising target in the search for treatments for the disease.
Selenium Compounds Affect Differently the Cytoplasmic Thiol/Disulfide State in Dermic Fibroblasts and Improve Cell Migration by Interacting with the Extracellular Matrix
Authors: Kreindl Christine , Soto-Alarcón Sandra A. , Hidalgo Miltha , Riveros Ana L. , Añazco Carolina , Pulgar Rodrigo , Porras Omar
Published: January 2024

Deficient wound healing is frequently observed in patients diagnosed with diabetes, a clinical complication that compromises mobility and leads to limb amputation, decreasing patient autonomy and family lifestyle. Fibroblasts are crucial for secreting the extracellular matrix (ECM) to pave the wound site for endothelial and keratinocyte regeneration. The biosynthetic pathways involved in collagen production and crosslinking are intimately related to fibroblast redox homeostasis. In this study, two sets of human dermic fibroblasts were cultured in normal (5 mM) and high (25 mM)-glucose conditions in the presence of 1 µM selenium, as sodium selenite (inorganic) and the two selenium amino acids (organic), Se-cysteine and Se-methionine, for ten days. We investigated the ultrastructural changes in the secreted ECM induced by these conditions using scanning electron microscopy (SEM). In addition, we evaluated the redox impact of these three compounds by measuring the basal state and real-time responses of the thiol-based HyPer biosensor expressed in the cytoplasm of these fibroblasts. Our results indicate that selenium compound supplementation pushed the redox equilibrium towards a more oxidative tone in both sets of fibroblasts, and this effect was independent of the type of selenium. The kinetic analysis of biosensor responses allowed us to identify Se-cysteine as the only compound that simultaneously improved the sensitivity to oxidative stimuli and augmented the disulfide bond reduction rate in high-glucose-cultured fibroblasts. The redox response profiles showed no clear association with the ultrastructural changes observed in matrix fibers secreted by selenium-treated fibroblasts. However, we found that selenium supplementation improved the ECM secreted by high-glucose-cultured fibroblasts according to endothelial migration assessed with a wound healing assay. Direct application of sodium selenite and Se-cysteine on purified collagen fibers subjected to glycation also improved cellular migration, suggesting that these selenium compounds avoid the undesired effect of glycation.
Molecular Docking Studies and In Vitro Activity of Paliurus spina-christi Mill Extracts as Pancreatic Lipase Inhibitors
Authors: Grande Fedora , Marrelli Mariangela , Amodeo Valentina , Occhiuzzi Maria Antonietta , Pinzaru Iulia , Fucile Mary , Dehelean Cristina Adriana , Alexa Ersilia , Conforti Filomena , Statti Giancarlo
Published: January 2024

Obesity is a risk factor for the onset of chronic diseases. One of the most promising approaches to treating obesity consists of reducing dietary fat absorption using extracts from plants because they contain phenolic compounds, especially flavonoids. Paliurus spina-christi, belonging to the Rhamnaceae family, is one of the five species belonging to the Paliurus genus. Herein, the aerial parts of the plant were extracted with methanol through the pressurized cyclic solid-liquid extraction using the Naviglio extractor®. The extracts were analyzed with High Performance Thin Layer Chromatography and investigated for their in vitro biological potential. The phytochemical analysis revealed that rutin has been shown to be the most abundant flavonoid component. The best antiradical activity was observed for the fruit extract with an IC50 value of 53.41 ± 1.24 µg/mL. This extract also has a better inhibitory capacity on lipid peroxidation evaluated at a different time of incubation. Potent lipase inhibitor activity of the extract from fruits was also demonstrated with in vitro experiments. This property can be attributed to a direct interaction of main components of P. spina-christi extract with the human pancreatic enzyme as demonstrated by the results of molecular docking experiments conducted on the crystallographic structures of lipase.
High-Fat Diet-Induced Obesity Increases Brain Mitochondrial Complex I and Lipoxidation-Derived Protein Damage
Authors: Berdún Rebeca , Obis Èlia , Mota-Martorell Natàlia , Bassols Anna , Valent Daniel , Serrano José C. E. , Martín-Garí Meritxell , Rodríguez-Palmero María , Moreno-Muñoz José Antonio , Tibau Joan , Quintanilla Raquel , Pamplona Reinald , Portero-Otín Manuel , Jové Mariona
Published: January 2024

Obesity is a risk factor for highly prevalent age-related neurodegenerative diseases, the pathogenesis of whichinvolves mitochondrial dysfunction and protein oxidative damage. Lipoxidation, driven by high levels of peroxidizable unsaturated fatty acids and low antioxidant protection of the brain, stands out as a significant risk factor. To gain information on the relationship between obesity and brain molecular damage, in a porcine model of obesity we evaluated (1) the level of mitochondrial respiratory chain complexes, as the main source of free radical generation, by Western blot; (2) the fatty acid profile by gas chromatography; and (3) the oxidative modification of proteins by mass spectrometry. The results demonstrate a selectively higher amount of the lipoxidation-derived biomarker malondialdehyde-lysine (MDAL) (34% increase) in the frontal cortex, and positive correlations between MDAL and LDL levels and body weight. No changes were observed in brain fatty acid profile by the high-fat diet, and the increased lipid peroxidative modification was associated with increased levels of mitochondrial complex I (NDUFS3 and NDUFA9 subunits) and complex II (flavoprotein). Interestingly, introducing n3 fatty acids and a probiotic in the high-fat diet prevented the observed changes, suggesting that dietary components can modulate protein oxidative modification at the cerebral level and opening new possibilities in neurodegenerative diseases’ prevention.
Flavone Hybrids and Derivatives as Bioactive Agents
Authors: Hazai László , Zsoldos Bernadett , Halmai Mónika , Keglevich Péter
Published: January 2024

Hybrid molecules can be defined as chemical entities with two or more structural domains, namely pharmacophores, having a specific biological effect. In many cases, when at least one of the components is biologically inactive, it is rather correct to call them “derivatives”, despite the fact that in the literature they are often mentioned also as hybrids. We have summarized such types of molecules, in which one of the components is mostly a real pharmacophore, i.e., flavone, which is one of the best-known natural bioactive substances. Structures, synthetic methods, medicinal indications, and more important activity data are presented.
Investigation of the Inverse Magnus Effect on a Rotating Sphere in Hypersonic Rarefied Flow
Authors: Jiang Yazhong , Ling Yuxing , Zhang Shikang
Published: January 2024

Explorations involving long-endurance and maneuvering flights in the upper atmosphere, as well as research on atmospheric entries of space debris or asteroids, call for a full understanding of hypersonic rarefied flows. The inverse Magnus effect occurs in the hypersonic rarefied flow past a rotating sphere, but the aerodynamic behavior is contrary to the Magnus effect in the continuum flow regime. In this article, a series of such flows are numerically studied using the direct simulation Monte Carlo (DSMC) method. By analyzing the flow fields, as well as the distributions of pressure and shear stress on the sphere, the formation of the inverse Magnus force can be attributed to the tangential momentum transfer between incident gas molecules and the windward surface. The variation laws of aerodynamic parameters with the rotation rate are presented and discussed.
Preventive Effects of Laser Irradiation and Dentin Bonding Agent Application on Tooth Discoloration Induced by Mineral Trioxide Aggregate
Authors: Sesen Uslu Yesim , Arıcan Alpay Burçin , Sesen Pınar , Özyürek Taha
Published: January 2024

The aim of the present study was to evaluate the effect of the pre-application of dentin bonding agent and laser application on the prevention of tooth discoloration caused by (MTA) in the presence of blood. Fifty extracted human anterior teeth were prepared by standardizing root lengths to 10 mm and shaping root canals. Specimens were divided into five groups (n = 10) based on the treatment applied to the pulp chamber dentin wall: Group 1/no surface treatment; Group 2/Optibond FL; Group 3/Clearfil SE; Group 4/Optibond Universal adhesive application; Group 5/Nd:YAG laser application. Root canals were filled with fresh human blood below the cemento-enamel junction (CEJ), followed by ProRoot MTA, and collagen barrier placement. Color changes were monitored using a spectrophotometer at 0, 7, 30, 90, and 180 days post MTA placement. Color differences (∆E) were calculated and analyzed using two-factor mixed-design ANOVA with Sidak adjustment at p = 0.05. The degree of coloration increased with time within each group (p < 0.05). No significant differences were observed between Optibond FL and Optibond Universal within each time interval, or between Clearfill SE Bond and the control group (p > 0.05). When compared to the control group, the Nd YAG group exhibited the least degree of discoloration in all time intervals (p < 0.05). Although the Nd:YAG laser had promising results, none of the methods can guarantee a 100% prevention of discoloration resulting from tooth discoloration caused by MTA-blood contact.
Sulforaphane Target Protein Prediction: A Bioinformatics Analysis
Authors: Lagunas-Rangel Francisco Alejandro
Published: January 2024

Sulforaphane, a phytochemical found in cruciferous vegetables and various nutraceutical foods, plays a crucial role in promoting well-being and combating various diseases. Its remarkable effects are due to its intricate interactions with a wide range of proteins, some of which remain unidentified. In this study, taking advantage of bioinformatics tools for protein target prediction, we identified 11 proteins as potential targets of sulforaphane. Due to its biological relevance and their correlation with transcriptomic changes observed in sulforaphane-treated cells, the possible interaction between sulforaphane and nicotinamide phosphoribosyltransferase (NAMPT) was further investigated. A docking analysis suggested that sulforaphane is strategically positioned at the entrance of the channel through which substrates enter, thus bypassing the active site of the enzyme. By forming hydrogen bonds with residues K189, R349, and S275, sulforaphane establishes a linkage with NAMPT. Dynamic molecular analyses further corroborated these observations, illustrating that these bonds allow sulforaphane to associate with NAMPT, mimicking the behavior of a NAMPT activator (NAT), a known activating compound of this enzyme. This collective evidence suggests that sulforaphane may activate NAMPT, providing valuable insights into a possible mechanism underlying its diverse biological effects.
NAGNE: Node-to-Attribute Generation Network Embedding for Heterogeneous Network
Authors: Zhang Zheding , Xu Huanliang , Li Yanbin , Zhai Zhaoyu , Ding Yu
Published: January 2024

Heterogeneous network embedding aims to project multiple types of nodes into a low-dimensional space, and has become increasingly ubiquitous. However, several challenges have not been addressed so far. First, existing heterogeneous network embedding techniques typically rely on meta-paths to deal with the complex heterogeneous network. Using these meta-paths requires prior knowledge from domain experts for optimal meta-path selection. Second, few existing models can effectively consider both heterogeneous structural information and heterogeneous node attribute information. Third, existing models preserve the structure information by considering the first- and/or the second-order proximities, which cannot capture long-range structural information. To address these limitations, we propose a novel attributed heterogeneous network embedding model referred to as Node-to-Attribute Generation Network Embedding (NAGNE). NAGNE comprises two major components, the attributed random walk which samples node sequences in attributed heterogeneous network, and the node-to-attribute generation which learns the mapping that translates each node sequence itself from the node sequence to the node attribute sequence. Extensive experiments on three heterogeneous network datasets demonstrate that NAGNE outperforms state-of-the-art baselines in various data mining tasks.
Analysis of the Relationship between Step Angle and Step Rate during Running: Implication for Rehabilitation
Authors: Kiernan Barry , Arnold Graham , Nasir Sadiq , Wang Weijie
Published: January 2024

In running, step rate and step angle are important, but the relationship between the two parameters is not clear in the literature. This study aimed to investigate the effect of step rate manipulation on step angle in running. A group of twenty healthy recreational runners aged between 30 and 59 years who regularly run 15–90 km per week were recruited. Kinematic data were recorded using a motion capture system while running on a treadmill. Participants maintained a self-selected speed and then altered their step rate using a metronome and completed three thirty-second trials at the preferred step rate, 10% above the preferred step rate and 10% below the preferred step rate. The results showed that the step angle is not significantly correlated with the step rate and kept at roughly 37 degrees at the preferred step rate and 10% lower than the preferred step rate but increased to 42 deg when the step rate increased to 10% of the preferred step rate. The step angles were not significantly different between the male and female or between sides. This finding provides an understanding of the association of step rate re-training on swing phase parameters.
Computer-Aided Analysis of the Formation of the Deformation Zone in the Burnishing Process
Authors: Piotrowski Andrzej , Zaborski Andrzej , Tyliszczak Artur
Published: January 2024

The study presents the use of spatial imaging of the shape of the deformation formation area occurring at the point of contact between the burnished tool and the processed material surface in the burnishing process. In the analysis of changes in the shape of surfaces processed by ball and disc pressure burnishing, an integrated measurement station was used to measure surface stereometry (New Form Talysurf 2D/3D 120 by Taylor Hobson) and to carry out a series of axially shifted roundness measurements (Talyrond 365 by Taylor Hobson). The geometric parameters of the deformation zone determined in the direction of the circumference of the cylindrical surface (direction of the main movement) and in the axial direction (in the feed plane) are presented. The data obtained as a result of metrological measurements were analysed using specialized computer software.
A Simple Unsupervised Knowledge-Free Domain Adaptation for Speaker Recognition
Authors: Lin Wan , Li Lantian , Wang Dong
Published: January 2024

Despite the great success of speaker recognition models based on deep neural networks, deploying a pre-trained model in real-world scenarios often leads to significant performance degradation due to the domain mismatch between training and testing conditions. Various adaptation methods have been developed to address this issue by modifying either the front-end embedding network or the back-end scoring model. However, existing methods typically rely on knowledge of the network, scoring model, or even the source data. In this study, we introduce a knowledge-free adaptation approach that only necessitates the unlabeled target data. Our core concept is based on the assumption that domain mismatch primarily stems from distributional distortion in the embedding space, such as shifting, rotation, and scaling while maintaining inter-speaker discrimination for data from unknown domains. Building on this assumption, we propose clustering LDA (C-LDA), a full-rank linear discriminant analysis (LDA) based on agglomerative hierarchical clustering (AHC) to compensate for this distortion. This approach does not need any human labels and does not rely on any knowledge of the model in the source domain, making it suitable for real-world applications. Theoretical analysis indicates that with cosine scoring, C-LDA is capable of eliminating distributional distortion related to global shift and within-speaker covariance rotation and scaling. Surprisingly, our experiments demonstrated that this simple approach can outperform more complex methods that require full or partial knowledge, including front-end approaches such as fine-tuning and distribution alignment, and back-end approaches such as unsupervised probabilistic linear discriminant analysis (PLDA) adaptation. Additional experiments demonstrated that C-LDA is insensitive to hyperparameters and works well in both multi-domain and single-domain adaptation scenarios.
Basic Composition, Antioxidative Properties, and Selected Mineral Content of the Young Shoots of Nigella (Nigella sativa L.), Safflower (Carthamus tinctorius L.), and Camelina (Camelina sativa L.) at Different Stages of Vegetation
Authors: Kapusta-Duch Joanna , Smoleń Sylwester , Jędrszczyk Elżbieta , Leszczyńska Teresa , Borczak Barbara
Published: January 2024

Young shoots are a completely new and rapidly growing group of foodstuffs. Also known as “vegetable confetti”, they are a useful addition to commonly consumed meals and often serve a decorative purpose, especially when paired with traditional dishes. Most users are unaware of their invaluable properties as a source of bioactive compounds and add them simply as a dish garnish. Hence, the aim of this study is to evaluate and compare selected health quality parameters of the young shoots of rare oilseed plants (Nigella sativa L., Carthamus tinctorius L., and Camelina sativa L.), which have not been studied in the literature. They are examined for proximate composition (dry matter, total protein, crude fat, ash, digestible carbohydrates, dietary fiber), antioxidative properties (vitamin C, total carotenoids, and total polyphenol content), the content of sixteen selected minerals (calcium, potassium, magnesium, sodium, phosphorus, sulphur, selenium, barium, iron, lithium, beryllium, nickel, gallium, indium, bismuth, silver) as well as antioxidant activity at two harvest dates. The ready-to-eat young shoots in the phase of intensive growth are characterized by a very high content of the examined components and antioxidant properties, which differ depending on the harvest date and plant species. Significantly higher contents of protein, fat, and some minerals have been found in the young shoots from the first harvest compared to those from the second harvest. The antioxidant properties of the young shoots generally increase with maturity. It was not possible, however, to conclusively assess which species of young shoots show the highest health quality.
Effects of a 6-Week Agility Training Program on Emotional Intelligence and Attention Levels in Adolescent Tennis Players
Authors: Selmi Walid , Hammami Achraf , Hammami Raouf , Ceylan Halil İbrahim , Morgans Ryland , Simenko Jozef
Published: January 2024

Tennis can be a mentally challenging sport, and emotional intelligence (EI) contributes significantly to an athlete’s psychological well-being. Thus, this study investigated the effects of 6 weeks of a combined Change of Direction (CoD) and reactive agility (RA) intervention program on emotional intelligence (EI) in pubertal tennis players. A total of 28 youth tennis players, aged 11 to 14 years, were randomly assigned to an experimental group (EXP-G, n = 15, 13 boys [age = 13.34 ± 0.98 years, maturity offset (MO) = −0.19 ± 0.96], and 2 girls [age = 12.77 ± 0.23 years, MO = 0.78 ± 0.04]) or a control group (CON-G, n = 13, 8 boys [age = 13.37 ± 0.75 years, MO = 0.00 ± 0.71], and 5 girls [age = 13.50 ± 0.92 years, MO = 1.41 ± 1.07]). The EXP-G performed combined CoD and RA training across the 6-week intervention period. The CON-G continued with the normal five 20 min regular tennis-specific training sessions per week, including technical and tactical drills and a small-sided games format. The overall training volume was similar between groups. Pre- and post-training, Profile of Emotional Competence (PEC, [EC TOTAL: global score of emotional competence level; EC INTRA: score of intra-personal emotional competence; EC INTER: score of inter-personal emotional competence]) and d2 attention tests were assessed. The present study employed an Analysis of Covariance (ANCOVA) with pre-test covariance to assess between-group differences (EXP-G vs. CON-G) at the post-test phase, utilizing baseline values as covariates. Noteworthy outcomes were observed, indicating statistically significant and substantial between-group disparities at post-test for various measures. Specifically, these differences were evident in the attention domain (effect size, d = 1.08 [Large], p = 0.001), the EC TOTAL test (effect size, d = 0.70 [Medium], p = 0.017), the EC INTA (effect size, d = 1.35 [Large], p = 0.001), and the EC INTER (effect size, d = 0.83 [Large], p = 0.009) tests. Due to the importance of agility training for overall competitive performance in tennis, our results suggest that young players should perform such training programs as part of conditioning training if the goal is to improve emotional intelligence and mental well-being.
Investigating the Effect of Patient-Related Factors on Computed Tomography Radiation Dose Using Regression and Correlation Analysis
Authors: AlShurbaji Mohammad , El Haout Sara , Chanchal Akchunya , Dhou Salam , Dalah Entesar
Published: January 2024

Computed tomography (CT) is a widely utilized diagnostic imaging modality in medicine. However, the potential risks associated with radiation exposure necessitate investigating CT exams to minimize unnecessary radiation. The objective of this study is to evaluate how patient-related parameters impact the CT dose indices for different CT exams. In this study, a dataset containing CT dose information for a cohort of 333 patients categorized into four CT exams, chest, cardiac angiogram, cardiac calcium score and abdomen/pelvis, was collected and retrospectively analyzed. Regression analysis and Pearson correlation were applied to estimate the relationships between patient-related factors, namely body mass index (BMI), weight and age as input variables, and CT dose indices, namely the volume CT dose index (CTDIvol), dose length product (DLP), patient effective dose (ED) and size-specific dose estimate (SSDE), as output variables. Moreover, the study investigated the correlation between the different CT dose indices. Using linear regression models and Pearson correlation, the study found that all CT dose indices correlate with BMI and weight in all CT exams with varying degrees as opposed to age, which did not demonstrate any significant correlation with any of the CT dose indices across all CT exams. Moreover, it was found that using multiple regression models where multiple input variables are considered resulted in a higher correlation with the output variables than when simple regression was used. Investigating the relationships between the different dose indices, statistically significant relationships were found between all dose indices. A stronger linear relationship was noticed between CTDIvol and DLP compared to the relationships between each pair of the other dose indices. The findings of this study contribute to understanding the relationships between patient-related parameters and CT dose indices, aiding in the development of optimized CT exams that ensure patient safety while maintaining the diagnostic efficacy of CT imaging.
A New Car-Body Structure Design for High-Speed EMUs Based on the Topology Optimization Method
Authors: Liu Chunyan , Ma Kai , Zhu Tao , Ding Haoxu , Sun Mou , Wu Pingbo
Published: January 2024

In recent years, the research and development of high-speed trains has advanced rapidly. The main development trends of high-speed trains are higher speeds, lower energy consumption, higher safety, and better environmental protection. The realization of a lightweight high-speed car body is one of the key features in the development trend of high-speed trains. Firstly, the basic dimensions of the car body’s geometric model are determined according to the external dimensions of the body of a CRH EMU, and the specific topology optimization design domain is selected to establish the finite element analysis model; secondly, the strength and modal analyses of the topology optimization design domain are carried out to check the accuracy of the design domain and provide a comparative analysis for subsequent design. Then, the variables, constraints, and objective functions of the topology optimization design are determined to establish the mathematical model of topology optimization, and the design domain is calculated for topology optimization under single and multiple conditions, respectively. Finally, based on the topology optimization calculation results, truss-type reconstruction modeling is carried out for the car body’s side walls, roof, underframe, end walls, and other parts. Compared with the conventional EMU body structure, the weight of the reconstructed body structure is reduced by about 18%. The results of the finite element analysis of the reconstructed car-body structure prove the reliability and safety of the structure, indicating that the reconstructed car-body scheme meets the corresponding performance indicators.
Automated Text Annotation Using a Semi-Supervised Approach with Meta Vectorizer and Machine Learning Algorithms for Hate Speech Detection
Authors: Saifullah Shoffan , Dreżewski Rafał , Dwiyanto Felix Andika , Aribowo Agus Sasmito , Fauziah Yuli , Cahyana Nur Heri
Published: January 2024

Text annotation is an essential element of the natural language processing approaches. The manual annotation process performed by humans has various drawbacks, such as subjectivity, slowness, fatigue, and possibly carelessness. In addition, annotators may annotate ambiguous data. Therefore, we have developed the concept of automated annotation to get the best annotations using several machine-learning approaches. The proposed approach is based on an ensemble algorithm of meta-learners and meta-vectorizer techniques. The approach employs a semi-supervised learning technique for automated annotation to detect hate speech. This involves leveraging various machine learning algorithms, including Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbors (KNN), and Naive Bayes (NB), in conjunction with Word2Vec and TF-IDF text extraction methods. The annotation process is performed using 13,169 Indonesian YouTube comments data. The proposed model used a Stemming approach using data from Sastrawi and new data of 2245 words. Semi-supervised learning uses 5%, 10%, and 20% of labeled data compared to performing labeling based on 80% of the datasets. In semi-supervised learning, the model learns from the labeled data, which provides explicit information, and the unlabeled data, which offers implicit insights. This hybrid approach enables the model to generalize and make informed predictions even when limited labeled data is available (based on self-learning). Ultimately, this enhances its ability to handle real-world scenarios with scarce annotated information. In addition, the proposed method uses a variety of thresholds for matching words labeled with hate speech ranging from 0.6, 0.7, 0.8, to 0.9. The experiments indicated that the DT-TF-IDF model has the best accuracy value of 97.1% with a scenario of 5%:80%:0.9. However, several other methods have accuracy above 90%, such as SVM (TF-IDF and Word2Vec) and KNN (Word2Vec), based on both text extraction methods in several test scenarios.
Spatiotemporal Analysis of Urban Heat Islands and Vegetation Cover Using Emerging Hotspot Analysis in a Humid Subtropical Climate
Authors: Ghanghermeh Abdolazim , Roshan Gholamreza , Asadi Kousar , Attia Shady
Published: January 2024

Research on the temporal and spatial changes of the urban heat island effect can help us better understand how urbanization, climate change, and the environment are interconnected. This study uses a spatiotemporal analysis method that couples the Emerging Hot Spot Analysis (EHSA) technique with the Mann–Kendall technique. The method is applied to determine the intensity of the heat island effect in humid subtropical climates over time and space. The data used in this research include thermal bands, red band (RED) and near-infrared band (NIR), and Landsat 7 and 8 satellites, which were selected from 2000 to 2022 for the city of Sari, an Iranian city on the Caspian Sea. Pre-processed spectral bands from the ‘Google Earth Engine’ database were used to estimate the land surface temperature. The land surface temperature difference between the urban environment and the outer buffer (1500 m) was modeled and simulated. The results of this paper show the accuracy and novelty of using Emerging Hotspot Analysis to evaluate the effect of vegetation cover on the urban heat island intensity. Based on the Normalized Difference Vegetation Index (NDVI), the city’s land surface temperature increased by approximately 0.30 °C between 2011 and 2022 compared to 2001 to 2010. However, the intensity of the urban heat island decreased during the study period, with r = −0.42, so an average −0.031 °C/decade decrease has been experienced. The methodology can be transferred to other cities to evaluate the role of urban green spaces in reducing heat stress and to estimate the heat budget based on historical observations.
Data-Driven Short-Term Load Forecasting for Multiple Locations: An Integrated Approach
Authors: Baul Anik , Sarker Gobinda Chandra , Sikder Prokash , Mozumder Utpal , Abdelgawad Ahmed
Published: January 2024

Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country’s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regions in Bangladesh. When making predictions for loads from multiple locations simultaneously, the overall accuracy of the forecast can be improved by incorporating features from the various areas while reducing the complexity of using multiple models. Accurate and timely load predictions for specific regions with distinct demographics and economic characteristics can assist transmission and distribution companies in properly allocating their resources. Bangladesh, being a relatively small country, is divided into nine distinct power zones for electricity transmission across the nation. In this study, we have proposed a hybrid model, combining the Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU), designed to forecast load demand seven days ahead for each of the nine power zones simultaneously. For our study, nine years of data from a historical electricity demand dataset (from January 2014 to April 2023) are collected from the Power Grid Company of Bangladesh (PGCB) website. Considering the nonstationary characteristics of the dataset, the Interquartile Range (IQR) method and load averaging are employed to deal effectively with the outliers. Then, for more granularity, this data set has been augmented with interpolation at every 1 h interval. The proposed CNN-GRU model, trained on this augmented and refined dataset, is evaluated against established algorithms in the literature, including Long Short-Term Memory Networks (LSTM), GRU, CNN-LSTM, CNN-GRU, and Transformer-based algorithms. Compared to other approaches, the proposed technique demonstrated superior forecasting accuracy in terms of mean absolute performance error (MAPE) and root mean squared error (RMSE). The dataset and the source code are openly accessible to motivate further research.
Exploring Diagnostic Precision and Triage Proficiency: A Comparative Study of GPT-4 and Bard in Addressing Common Ophthalmic Complaints
Authors: Zandi Roya , Fahey Joseph D. , Drakopoulos Michael , Bryan John M. , Dong Siyuan , Bryar Paul J. , Bidwell Ann E. , Bowen R. Chris , Lavine Jeremy A. , Mirza Rukhsana G.
Published: January 2024

In the modern era, patients often resort to the internet for answers to their health-related concerns, and clinics face challenges to providing timely response to patient concerns. This has led to a need to investigate the capabilities of AI chatbots for ophthalmic diagnosis and triage. In this in silico study, 80 simulated patient complaints in ophthalmology with varying urgency levels and clinical descriptors were entered into both ChatGPT and Bard in a systematic 3-step submission process asking chatbots to triage, diagnose, and evaluate urgency. Three ophthalmologists graded chatbot responses. Chatbots were significantly better at ophthalmic triage than diagnosis (90.0% appropriate triage vs. 48.8% correct leading diagnosis; p < 0.001), and GPT-4 performed better than Bard for appropriate triage recommendations (96.3% vs. 83.8%; p = 0.008), grader satisfaction for patient use (81.3% vs. 55.0%; p < 0.001), and lower potential harm rates (6.3% vs. 20.0%; p = 0.010). More descriptors improved the accuracy of diagnosis for both GPT-4 and Bard. These results indicate that chatbots may not need to recognize the correct diagnosis to provide appropriate ophthalmic triage, and there is a potential utility of these tools in aiding patients or triage staff; however, they are not a replacement for professional ophthalmic evaluation or advice.