Search Results (88)

(1) Background: The aim of this study is to investigate whether the application of adaptive sports programs, initially designed for children with disabilities, can have a positive effect on physical fitness and body composition in healthy primary school children; (2) Methods: The sample comprised 80 participants, equally divided by gender (50% male, 50% female), with a mean age of 11.5 (SD = 0.03). They were divided into two groups, an experimental and a control group, with an even gender distribution. The research lasted 12 weeks, with additional classes allocated for the initial and the final measurements. The Eurofit test battery assessed physical fitness; (3) Results: ANCOVA revealed significant group differences in body composition variables within the total sample and gender distribution (p < 0.001). Significant differences were observed in handgrip strength (HGR), flamingo balance test (FBL), shuttle run 10 × 5 m (SHR) (p < 0.001), and also hand tapping (HTP) (p = 0.01). Participants in the experimental group outperformed the control group, highlighting the effectiveness of the intervention program. Specifically, boys in the experimental group showed significant improvements in HGR and SHR (p < 0.001), while girls improved significantly in HGR, FBL, and SHR (p < 0.001); (4) Conclusions: The experimental program, which incorporates sports elements for disabled individuals, led to significant improvements in the physical fitness parameters of children. Full article

Hand gesture recognition (HGR) heavily relies on high-quality annotated datasets. However, annotating hand landmarks in video sequences is a time-intensive challenge. In this work, we introduce IPN HandS, an enhanced version of our IPN Hand dataset, which now includes approximately 700,000 hand skeleton annotations and corrected gesture boundaries. To generate these annotations efficiently, we propose a novel annotation tool that combines automatic detection, inter-frame interpolation, copy–paste capabilities, and manual refinement. This tool significantly reduces annotation time from 70 min to just 27 min per video, allowing for the scalable and precise annotation of large datasets. We validate the advantages of the IPN HandS dataset by training a lightweight LSTM-based model using these annotations and comparing its performance against models trained with annotations from the widely used MediaPipe hand pose estimators. Our model achieves an accuracy that is 12% higher than the MediaPipe Hands model and 8% higher than the MediaPipe Holistic model. These results underscore the importance of annotation quality in training generalization and overall recognition performance. Both the IPN HandS dataset and the annotation tool will be released to support reproducible research and future work in HGR and related fields. Full article

This study examines the influence of gravity on different height systems by integrating Global Navigation Satellite Systems (GNSS), leveling, and gravimetric measurements. Although the theoretical influence of gravity on height systems is well known, empirical studies that quantify these effects along steep terrain are rare—particularly within the Croatian reference systems. Geometric leveling, recognized for its precision in geodesy, was employed alongside gravimetric data to analyze the relationship between gravity variations and height differences. The research was conducted along Sljeme Road on Mt. Medvednica, Croatia, where altitude-dependent gravity effects were systematically investigated along an elevation profile with a height difference of about 650 m. GNSS measurements provided positional coordinates referenced to the Croatian Terrestrial Reference System 1996 (HTRS96) (EPSG:4888), while leveling and gravimetric data were analyzed within the Croatian Height Reference System 1971 (HVRS71) (EPSG:5610) and Croatian Gravimetric Reference System 2003 (HGRS03), respectively. The results demonstrate that differences between geometric and normal–orthometric heights become more pronounced at higher elevations but remain at the millimeter level. Notably, the impact of gravity is evident in normal and orthometric heights, with differences from geometric heights reaching up to 3.7 cm at the highest points. Additionally, a comparison between normal and orthometric heights reveals that at the beginning of the leveling line, the difference is around 4 mm. However, as the elevation increases, this difference grows, reaching over 1 cm at the end of the leveling line. The study also confirms the theoretical correlation between the geoid–quasigeoid height difference and terrain elevation, with increasing differences observed at higher altitudes. To examine the consistency of different height determination methods, two approaches were applied: one based on adjustment within the geopotential system, and the other involving direct adjustment in the desired height system, with specific height corrections applied. The results confirmed that the height differences between the two methods were 0, to the tenth of a millimeter, indicating that both methods provided identical results. These findings contribute to a deeper understanding of geodetic height systems and the role of gravity in height determination. Full article

Orotic acid (OA) is a natural component of milk and is found in many biological fluids such as human ovarian follicular fluid. However, its effect on ovarian cells is unknown. Some studies suggest that OA may alter lipid metabolism and energy production in cells. In the present study, we determine the effect of OA on mitochondrial function and lipid droplet content in the human granulosa cell line. The effect of OA on in vitro mouse oocyte maturation and mitochondrial activity was also investigated. We found that repeated exposure to OA (0.01–1000 µM) did not alter the viability of human epithelial (HOSEpiC) and granulosa (HGrC1) ovarian cells. HGrC1 cells treated with a high dose of OA (500 µM) showed a more aerobic and energetic phenotype than control cells, whereas this effect was not observed after treatment with lower doses (0.01 and 100 µM) of OA. In addition, OA at a high dose (500 µM) reduced lipid droplet (LD) content without altering glucose (GLUT1, GLUT4) and fatty acid transporter (SLC27A1) gene expression in HGrC1 cells. At the same time, OA at 100 µM did not disrupt mouse in vitro oocyte maturation, whereas OA at 500 µM inhibited this process by arresting oocytes at the germinal vesicle (GV) stage with a reduction in mitochondrial activity. Our results show that OA at high doses can disrupt female reproduction, but normal dietary orotate intake does not have a negative effect on ovarian function. Full article

The aim of this study was to characterize the vegetative growth development of hop plants grown in the subtropics under a two-crop-a-year system with artificial supplementation lighting. The development of ‘Mapuche’ and ‘Spalter’ hops was compared during the summer 2022–2023, fall 2023, summer 2023–2024 and fall 2024 harvest seasons, considering the effects of the air temperature on the vegetative growth of plants from thermal sums in a subtropical climate region. The experiment was conducted in Palotina, Paraná, Brazil (24°17′40.05″ S, 55°50′23.16″ W, at 332 m elevation). The hops were trained on a 5.5 m high vertical trellis, using a ‘V’-shaped training system. Vegetative growth was evaluated based on the plant height development (m), hop growth rate (HGR), and classification of four growth stages based on the HGR. The phenology of the hop cultivars was determined visually according to the duration in days of the phenological stages. The development of the plant height and HGR was analyzed by nonlinear regressions of the Gompertz model and Gaussian function, respectively. ‘Mapuche’ and ‘Spalter’ hops had complete vegetative growth and phenological phases in the summer and fall seasons, with greater precocity in plant development in the summer season. The growth model based on the air temperature demonstrated that under subtropical conditions, the growth was maximized in seasons with higher temperatures. The duration of the phenological phases and the complete cycle of the plants was influenced by the vegetative growth of each cultivar in each harvest season. Therefore, double annual crop production of the hop cultivars ‘Mapuche’ and ‘Spalter’ is possible in a subtropical climate with artificial light supplementation. Full article

Aging drives excessive ovarian oxidative stress (OS), impairing fertility and affecting granulosa cells (GCs), which are involved in folliculogenesis. This study aims to clarify the relationship between OS and autophagy in GCs and to identify compounds that enhance OS resistance. We identified Rubicon, an autophagy suppressor, as a key mediator of DNA damage in GCs under OS. Hydrogen peroxide (H₂O₂) compromised cell viability via DNA damage in the human GC cell line, HGrC1, without affecting autophagic activity. However, autophagy activation increased OS resistance in HGrC1 cells, and vice versa. Among clinically safe materials, trehalose, a disaccharide, protected cells as an autophagy activator against H₂O₂-induced cytotoxicity. Trehalose significantly increased autophagic activity, accompanied by reduced Rubicon expression, compared to other carbohydrates. It also reduced the expression of DNA damage-responsive proteins and the production of reactive oxygen species. Rubicon knockdown mitigated OS-induced DNA damage, while Rubicon overexpression enhanced DNA damage and decreased HGrC1 cell viability. Trehalose enhanced OS resistance by activating autophagy and suppressing Rubicon in a bidirectional manner. As Rubicon expression increases in aged human ovaries, trehalose may improve ovarian function in patients with infertility and other OS-related diseases. Full article

Aqueous gel-casting provides a cost-effective and scalable approach for synthesizing nano-spherical Co₃O₄ powders, enabling precise control over particle morphology. In this study, Co₃O₄ powders were prepared using this method and evaluated as a catalyst precursor for the hydrolysis of sodium borohydride (NaBH₄). The effects of the monomer (acrylamide, AM)-to-metal molar ratio and initiator content (ammonium persulphate, APS) on particle size and catalytic performance were systematically explored. X-ray diffraction (XRD) analysis confirmed the formation of the Co₃O₄ phase at 400 °C, while transmission electron microscopy (TEM) images revealed particle sizes ranging from 16 to 85 nm, with higher AM and APS concentrations promoting finer particles. The optimized catalyst achieved a high hydrogen generation rate (HGR) of 28.13 L min⁻¹·cat.⁻¹, demonstrating excellent catalytic activity. Moreover, in situ-formed cobalt boride, derived from Co₃O₄ calcined at 600 °C for 2 h, exhibited an activation energy of 51.81 kJ mol⁻¹, comparable to Ru-based catalysts. This study underscores the aqueous gel-casting technique as a promising strategy for synthesizing efficient and low-cost hydrogen generation catalysts, offering an alternative to noble metal-based materials. Full article

Hand gesture recognition (HGR) is a convenient and natural form of human–computer interaction. It is suitable for various applications. Much research has already focused on wearable device-based HGR. By contrast, this paper gives an overview focused on device-free HGR. That means we evaluate HGR systems that do not require the user to wear something like a data glove or hold a device. HGR systems are explored regarding technology, hardware, and algorithms. The interconnectedness of timing and power requirements with hardware, pre-processing algorithm, classification, and technology and how they permit more or less granularity, accuracy, and number of gestures is clearly demonstrated. Sensor modalities evaluated are WIFI, vision, radar, mobile networks, and ultrasound. The pre-processing technologies stereo vision, multiple-input multiple-output (MIMO), spectrogram, phased array, range-doppler-map, range-angle-map, doppler-angle-map, and multilateration are explored. Classification approaches with and without ML are studied. Among those with ML, assessed algorithms range from simple tree structures to transformers. All applications are evaluated taking into account their level of integration. This encompasses determining whether the application presented is suitable for edge integration, their real-time capability, whether continuous learning is implemented, which robustness was achieved, whether ML is applied, and the accuracy level. Our survey aims to provide a thorough understanding of the current state of the art in device-free HGR on edge devices and in general. Finally, on the basis of present-day challenges and opportunities in this field, we outline which further research we suggest for HGR improvement. Our goal is to promote the development of efficient and accurate gesture recognition systems. Full article

The submergence tolerance of rice is a key factor in promoting rice direct seeding technology and resisting flood disasters. Dongxiang wild rice (DXWR) has strong submergence tolerance, but its genetic basis is still unclear. Here, we report quantitative trait loci (QTLs) analysis for hypoxic germination rate (HGR), hypoxic seedling rate (HSR), budlet submergence survival rate (BSSR) and seedling submergence survival rate (SSSR) using a linkage map in the backcross recombinant inbred lines (BRILs) that were derived from a cross of DXWR, and an indica cultivar, GZX49. A total of 20 QTLs related to submergence tolerance of rice were detected, explaining phenotypic variations ranging from 2% to 8.5%. Furthermore, transcriptome sequencing was performed on the seeds and seedlings of DXWR before and after submergence. During the seed hypoxic germination and seedling submergence stages, 6306 and 3226 differentially expressed genes (DEGs) were detected respectively. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were conducted on these differentially expressed genes. Using genetic linkage analysis and transcriptome data, combined with qRT-PCR, sequence comparison, and bioinformatics, LOC_Os05g32820 was putatively identified as a candidate gene for qHGR5.2 co-located with HGR and SSSR. These results will provide insights into the mechanism of rice submergence tolerance and provide a basis for improving rice submergence tolerance. Full article

The rapid advancement of edge computing and Tiny Machine Learning (TinyML) has created new opportunities for deploying intelligence in resource-constrained environments. With the growing demand for intelligent Internet of Things (IoT) devices that can efficiently process complex data in real-time, there is an urgent need for innovative optimisation techniques that overcome the limitations of IoT devices and enable accurate and efficient computations. This study investigates a novel approach to optimising Convolutional Neural Network (CNN) models for Hand Gesture Recognition (HGR) based on Electrical Impedance Tomography (EIT), which requires complex signal processing, energy efficiency, and real-time processing, by simultaneously reducing input complexity and using advanced model compression techniques. By systematically reducing and halving the input complexity of a 1D CNN from 40 to 20 Boundary Voltages (BVs) and applying an innovative compression method, we achieved remarkable model size reductions of 91.75% and 97.49% for 40 and 20 BVs EIT inputs, respectively. Additionally, the Floating-Point operations (FLOPs) are significantly reduced, by more than 99% in both cases. These reductions have been achieved with a minimal loss of accuracy, maintaining the performance of 97.22% and 94.44% for 40 and 20 BVs inputs, respectively. The most significant result is the 20 BVs compressed model. In fact, at only 8.73 kB and a remarkable 94.44% accuracy, our model demonstrates the potential of intelligent design strategies in creating ultra-lightweight, high-performance CNN-based solutions for resource-constrained devices with near-full performance capabilities specifically for the case of HGR based on EIT inputs. Full article

Reducing dehydrogenation temperature while preserving high hydrogen generation capacity obstructs the hydrolysis of sodium borohydrides (NaBH₄). The two-dimensional (2D) MAX phase of titanium aluminum carbide (Ti₃AlC₂) and MXene (Ti₃C₂T_x) multilayers was investigated for hydrogen generation via NaBH₄ hydrolysis with and without light. The material was characterized using X-ray diffraction (XRD), Fourier transform infrared (FT-IR), transmission electron microscopy (TEM), high-resolution TEM (HR-TEM), scanning electron microscopy (SEM), and diffuse reflectance spectroscopy (DRS). The activity of Ti₃AlC₂ was significantly enhanced by the integration of UV light radiation during hydrolysis. Ti₃AlC₂/Ti₃C₂T_x improved the dehydrogenation rates of NaBH₄ at ambient conditions and maintained high hydrogen generation rates (HGRs) over time compared to a conventional method. It exhibited a HGR of 200–300 mL·min⁻¹·g⁻¹. Photo-assisted hydrolysis over the catalyst can be maintained for several times at ambient temperature. The catalyst demonstrated effective performance even after five cycles of usage. Full article

Although usually studied as separate processes, plant growth and plant development are strictly interrelated. The BBCH scale (“Biologische Bundesanstalt, Bundessortenamt, and CHemical industry”) has become one of the primary classification systems for documenting the growth and developmental stages of many plant species. Specifically, the BBCH scale for hops (Humulus lupulus L.) separately describes growth and development during the vegetative stage. This study aims to develop an integrated approach to better understand the interaction between vertical growth rates and vegetative development in hops. Growth rates and development patterns of the Cascade hop cultivar were assessed in semi-arid (Sicily, Italy) and subtropical (Florida, USA) climates. The Gompertz model accurately described vertical growth, while a modified Gaussian model effectively captured hop growth rates (HGRs). A strong correlation between growth and developmental stages was identified, allowing for the inference of growth dynamics from developmental observations during the vegetative phase. Growth and developmental stages showed a 71% match across both environments, with minor phase shifts influenced by growing conditions. From an applied perspective, understanding the growth characteristics associated with developmental stages is crucial for addressing challenges posed by pests and diseases in emerging hop-growing regions. This integrated approach offers valuable insights into optimizing cultivation practices for diverse environmental conditions. Full article

Human gait recognition (HGR) has been employed as a biometric technique for security purposes over the last decade. Various factors, including clothing, carrying items, and walking surfaces, can influence the performance of gait recognition. Additionally, identifying individuals from different viewpoints presents a significant challenge in HGR. Numerous conventional and deep learning techniques have been introduced in the literature for HGR, but traditional methods are not well suited to handling large datasets. This research explores the effectiveness of four deep learning models for gait identification in the CASIA B dataset: the convolutional neural network (CNN), multi-layer perceptron (MLP), self-organizing map (SOMs), and transfer learning with EfficientNet. The selected deep learning techniques offer robust feature extraction and the efficient handling of large datasets, making them ideal in enhancing the accuracy of gait recognition. The collection includes gait sequences from 10 individuals, with a total of 92,596 images that have been reduced to 64 × 64 pixels for uniformity. A modified model was developed by integrating sequential convolutional layers for detailed spatial feature extraction, followed by dense layers for classification, optimized through rigorous hyperparameter tuning and regularization techniques, resulting in an accuracy of 97.12% for the test set. This work enhances our understanding of deep learning methods in gait analysis, offering significant insights for choosing optimal models in security and surveillance applications. Full article

Background/Objectives: Clinical studies have demonstrated a correlation between alterations in the expression level of TRα and TRβ receptors in ovarian cancer cells and overall survival. Celecoxib and GW0742, commonly known as a COX-2 inhibitor and a PPARβ/δ agonist, are novel thyroid hormone receptor antagonists that bind to TRβ or both TRα and TRβ. Methods: The study was conducted on a non-luteinized ovarian granulosa cell line (HGrC1) and two rare ovarian cancer cell lines (COV434 and KGN). The expression of TRα and TRβ at the gene and protein levels was examined by real-time PCR and Western blot, respectively. The impact of GW0742 and celecoxib on the cell viability of the HGrC1, COV434 and KGN lines was evaluated using the PrestoBlue™ Cell Viability Reagent. The metabolic activity of the cells was analysed using the Seahorse XFp Analyzer. Results: Initially, we observed that the gene and protein expression levels of TRα and TRβ were higher in COV434 and KGN cells than in HGrC1 cells. Subsequently, it was demonstrated that T₃ enhances the viability of HGrC1, COV434 and KGN cells. Furthermore, autoregulatory feedback loops were not observed during TRα or TRβ signalling in ovarian cancer cells, in contrast to the findings in healthy granulosa cells. Finally, we demonstrated that GW0742 reduced the viability and metabolic activity of granulosa cell tumours (GCTs). Simultaneously, we observed that GW0742 upregulated the expression of TRβ in GCT. Conclusions: These findings suggest that GW0742 may be a novel adjuvant therapy for GCTs expressing TRα and TRβ. Full article

Green hydrogen (H₂) offers a sustainable alternative to non-renewable energy sources. This study focuses on enhancing H₂ generation from sodium borohydride (NaBH₄) using a platinum nanoparticle (Pt-NP) catalyst supported on a niobium-based coordination compound, [Nb(BDC)_0.9(PDC)_0.1]_n, synthesized via a solvothermal method with 1,4-benzenedicarboxylic acid (BDC) and 2,5-pyridinedicarboxylic acid (PDC). Characterization techniques including Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), Brunauer–Emmett–Teller (BET) analysis, Raman spectroscopy, and X-ray diffraction (XRD) confirm the morphology, composition, surface area (398.583 m²g⁻¹), and crystallinity of the material. The in situ synthesized Pt-NPs showed a hydrogen generation rate (HGR) of 86.588 mL min⁻¹ g⁻¹ when alone, while the supported catalyst achieved an enhanced HGR of 119.020 mL min⁻¹ g⁻¹ under optimal conditions (10 mmol% Pt, 0.5 mmol NaBH₄, 303.15 K). The low activation energy (E_a) of 16.38 kJ mol⁻¹ indicates efficient catalysis. The catalyst maintained stable performance in recycling tests, demonstrating its potential for practical applications in H₂ evolution from NaBH₄. Full article