Search Results (109)

Stable, homogeneous, and internationally comparable gravimetric reference systems are fundamental components of modern geodetic infrastructure, supporting height system realization, geoid modeling, geodynamics, and the integration of national gravity networks into global reference frames. This paper reviews the historical development of gravity reference systems, from early pendulum-based realizations to modern absolute gravimetry, with particular emphasis on their application in the Republic of Croatia. The evolution of international gravity datums is presented through the Vienna Gravity System, the Potsdam Gravity System, and the International Gravity Standardization Network 1971 (IGSN71), outlining their methodological foundations, accuracy levels, and limitations. The role of IGSN71 in harmonizing national gravity networks is discussed in the context of international cooperation. Within this framework, the development of gravimetric research in present-day Croatia is outlined, from surveys conducted during the Yugoslav period to the establishment of an independent national gravimetric datum. The realization of the Croatian gravimetric reference system through absolute gravity measurements between 1996 and 2000, the formation of the Zero-Order Gravimetric Network, and the establishment and densification of the First- and Second-Order Gravimetric Networks are described. The Croatian Gravimetric Reference System 2003 (HGRS03), based on IGSN71, is presented as the official national gravity reference. In addition to documenting its historical development, the paper provides a critical assessment of the current status of HGRS03, including limitations inherited from its historical reference framework, the absence of repeated absolute observations, and the uneven spatial distribution of Zero-Order stations. The paper also discusses future modernization perspectives, particularly in the context of advances in absolute gravimetry and the long-term maintenance of the Croatian gravimetric reference infrastructure. Full article

The present study aimed to characterize the vegetative growth and phenology of hop cultivars grown in successive seasons with artificial supplementation in a subtropical region. The experiment was conducted in Palotina, Paraná, Brazil (24° S) during the summer 2023–2024, winter 2024, and fall 2024–2025 growing seasons. LED lamps were used to extend the daily photoperiod to 17 h during the vegetative phase. The following hop cultivars were assessed: (a) Alpharoma; (b) Cascade; (c) Chinook; (d) Comet; (e) Dr. Rudi; (f) Hallertau Magnum; (g) Hallertau Mittelfruher; (h) Nugget; (i) Saaz; (j) Smooth; (k) Sorachi Ace; (l) Southern Cross; (m) Triple Pearl; (n) Yakima Gold; (o) Zeus. The assessed variables included plant height (Ht), hop growth rate (HGR), classification of four growth stages, number of lateral shoots, plant fresh mass, and phenology. Ht and HGR were analyzed by means of Gompertz and Gaussian regression models, respectively. The number of lateral shoots per plant and fresh mass were subjected to analysis of variance (ANOVA), and means were grouped using the Scott-Knott test (p < 0.01). Seasonal temperature fluctuations, associated with advancing age and plant establishment throughout successive cycles, acted as important modulating factors in vegetative growth and phenology. In the summer season (2023–2024), Cascade and Hallertau Magnum were characterized as early cultivars. In the winter season (2024), Chinook, Nugget, Saaz, and Zeus were classified as early cultivars, while in the fall season (2024–2025), Dr. Rudi, Sorachi Ace, and Zeus were also considered early hops. The vegetative growth Stage I was found to be critical for earliness classification. The phenological cycle variability was amplified during seasons with higher temperatures. The ‘Sorachi Ace’, ‘Triple Pearl’, and ‘Zeus’ hops were the only ones capable of completing the phenological cycle in all three harvest seasons, with ‘Sorachi Ace’ standing out due to its uniform, stable growth pattern regardless of the season. It is concluded that successive hop cultivation is technically viable for specific hop cultivars grown under subtropical conditions with supplemental lighting. Full article

Hand gesture recognition (HGR) is a critical area in computer vision that supports intuitive human–computer interaction and sign language communication, yet existing systems remain sensitive to lighting variations, background clutter, and diverse hand postures. This study introduces two contributions to address these limitations: a Gradient-Based Augmentation Validation (GBAV) framework that establishes structurally safe augmentation ranges before training, and a multi-backbone Convolutional Neural Network (CNN) architecture combining ResNet50 and InceptionV3 with optional attention-based pooling. GBAV uses magnitude-weighted gradient orientation histograms with Pearson correlation and Kullback–Leibler divergence thresholds to verify label invariance under spatial transformations, providing a classifier-agnostic pre-training calibration mechanism. The proposed framework is evaluated on three static gesture datasets, Indonesian Sign Language (BISINDO), American Sign Language (ASL), and Hand Gesture 14 (HG14), yielding validation accuracies of 96.87%, 99.92%, and 95.25%, respectively, with 5-fold cross-validation on HG14 confirming result stability (93.51% ± 2.31%). Quantitative attention localization, cross-dataset transfer evaluation, and computational efficiency analysis (26.8 ms per image, ~37 FPS) further support the framework’s robustness and practical deployability. These findings establish GBAV-calibrated augmentation as the principal performance driver, which complements the multi-backbone architecture for robust hand gesture recognition across diverse visual contexts. Full article

Efficient, low-cost catalysts are required for on-demand H₂ generation from chemical hydrides. This study utilized piezoelectric poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers (NFs) as a support to encapsulate bimetallic Co–Mo nanoparticles (NPs) for H₂ production via sodium borohydride (SBH) methanolysis. The PVDF-HFP membranes were synthesized through electrospinning, followed by in situ SBH reduction, which resulted in the uniform dispersion of amorphous Co–Mo NPs within the nanofibrous matrix. The optimized CoMo-0.2@PVDF-HFP membrane exhibited a hydrogen generation rate (HGR) of 1.9 × 10³ mL·min⁻¹·g⁻¹ (Co) at 298 K, indicating a 3.6-fold improvement relative to monometallic Co. Kinetic studies showed a nearly first-order relationship with catalyst dose and a nearly zero-order relationship with respect to SBH concentration, suggesting kinetics controlled by surface saturation. The activation energy (E_a) was determined to be 14.03 kJ·mol⁻¹. Moreover, the catalyst maintained over 80% of its original activity after five cycles. This enhanced performance is attributed to the combined effects of Co and Mo, the amorphous nature of the active sites, and the piezoelectric polarization of PVDF-HFP during mechanical stirring, which together improve charge transfer and reduce NP agglomeration. Full article

Existing Q-Learning-based path planning methods face significant bottlenecks in large-scale collaboration, dynamic interference adaptation, and regional value differentiation, failing to meet the practical needs of mountain search and rescue. This study proposes HGR-QL, an optimized Q-Learning method for large-scale multi-UAV operations. Referencing remote sensing datasets, a 50 × 50 dynamic grid environment is constructed by integrating 20% fixed obstacles and 10 moving interference sources, highly simulating real mountain features. Integrating the individual Q-tables and the regional shared Q-tables, the hierarchical independent Q-table architecture is designed, balancing local autonomy and global collaboration. To guide UAVs focusing on remote sensing-identified high-value areas, an innovative multi-level gradient collision avoidance reward function is constructed, avoiding task deviation. Comparative experiments across three scenarios with four baselines and ablation tests validate the core modules. Results show HGR-QL outperforms peers in key metrics: in the dynamic interference scenario, it achieves a 74.47% task completion rate, 25.44 collisions, and a stable 100.00 ms communication delay. HGR-QL provides a lightweight, scalable solution, effectively enhancing the efficiency, safety, and stability of mountain search and rescue and supporting the “golden 72 h” rescue window. Full article

The nickel-derived metal–organic framework (MOF), Ni-BTB, synthesized from 4,4′,4″-benzene-1,3,5-tribenzoic acid (H₃BTB), was investigated as a multifunctional platform for enhanced energy applications including production and storage. In catalytic hydrogen generation by NaBH₄ hydrolysis, Ni-BTB attained a hydrogen generation rate (HGR) of 4640 mL H₂/g•min with 1 mg of catalyst, with an activation energy of 76.44 kJ/mol. Under optimized reaction conditions (60 °C, 20 mg catalyst, and 1 g NaBH₄), the HGR increased to 9542 mL H₂/g•min, while exhibiting high recyclability throughout four successive cycles. As a supercapacitor electrode, Ni-BTB achieved a specific capacitance of 156 F/g at 1 A/g and showed remarkable cycling stability, maintaining its capacitance after 10,000 charge–discharge cycles. Furthermore, Ni-BTB exhibited exceptional electrocatalytic activity for oxygen evolution reaction (OER), requiring only 106 mV overpotential to achieve 10 mA/cm², offering a time-of-flight (TOF) of 0.0585 s⁻¹ and demonstrating significant operational longevity of at least 12 h. These findings underscore Ni-BTB as a durable, reusable, and adaptable material for hydrogen production, energy storage, and electrocatalytic applications. Full article

Hand gesture recognition (HGR) systems play a critical role in modern intelligent transportation frameworks by enabling reliable communication between pedestrians, traffic operators, and autonomous vehicles. This work presents a novel traffic hand gesture recognition method that combines nine grayscale radar images captured from multiple millimeter-wave radar nodes into a single RGB representation through an optimized rotation–shift fusion strategy. This transformation preserves complementary spatial information while minimizing inter-image interference, enabling deep learning models to more effectively utilize the distinctive micro-Doppler and spatial patterns embedded in radar measurements. Extensive experimental studies were conducted to verify the model’s performance, demonstrating that the proposed RGB fusion approach provides higher classification accuracy than single-sensor or unfused representations. In addition, the proposed model outperformed state-of-the-art methods in the literature with an accuracy of 92.55%. These results highlight its potential as a lightweight yet powerful solution for reliable gesture interpretation in future intelligent transportation and human–vehicle interaction systems. Full article

Objectives: This study investigated whether CoQ10 supplementation enhances physical adaptations to high-intensity interval training (HIIT) in muscular strength, power, and physical function in older adults. Method: In a double-blind, randomized controlled trial, 38 adults aged 65–75 were assigned to either a CoQ10 (Females: 8; Males: 11) or placebo (Females: 8; Males: 11) group and completed an 8-week supervised HIIT program. Lower- and upper-body strength (30s 5-repetition chair stand [5XSST], chair standing [30CST], handgrip strength [HGR/L]), balance (single-leg stand [SLS], timed up and go [TUG]), mobility (25-foot walk [25FW]), and aerobic endurance (6-minute walk [6MWT]) were assessed pre- and post-intervention. Results: The CoQ10 group demonstrated significantly greater improvements in 5XSST and 30CST compared to the placebo group (p < 0.05). Both groups showed significant within-group improvements in right and left handgrip strength, SLS, 6MWT, and TUG (all p < 0.001), with no significant between-group differences observed for these outcomes (p > 0.05). No adverse events were reported. Conclusion: While CoQ10 supplementation enhanced improvements in lower-body strength and power, as indicated by the greater gains in 5XSST and 30CST performance compared to the placebo, no between-group differences were observed in TUG, grip strength, or other functional outcomes. This suggests that the performance-related effects of CoQ10 may be more specific to muscular power output and fatigue resistance, rather than general mobility or balance-related tasks. These findings highlight the potential of CoQ10 as a targeted adjunct in exercise for supporting lower-body function and physical performance in older adults. Full article

In this study, we report the preparation of platinum nanoparticles (Pt NPs) deposited on HTiNbO₅ and the application of the resultant material in the catalytic decomposition of sodium borohydride (NaBH₄) to generate hydrogen. The starting material, KTiNbO₅, was prepared through a solid-state process involving Nb₂O₅, K₂CO₃, and TiO₂. The subsequent treatment with HNO₃ resulted in the exchange of potassium by protons, rendering HTiNbO₅. This material served as support for Pt nanoparticles (3.6 ± 0.7 nm), producing Pt NPs/HTiNbO₅. All compounds were characterized using TGA, FTIR, XRD, Raman, SEM-EDS, and HRTEM. The influence of different factors on the reaction kinetics was evaluated, resulting in a hydrogen generation rate (HGR) of 22,790.18 $\mathrm{m}\mathrm{L} {\mathrm{m}\mathrm{i}\mathrm{n}}^{-1}{\mathrm{g}}_{\mathrm{c}\mathrm{a}\mathrm{t}}^{-1}$ at 50 °C. The activation energy (41.83 kJ mol⁻¹) was also determined. A mechanistic study with deuterated water revealed a kinetic isotopic effect (KIE) value of 1.27, indicating the dissociation of B-H from BH₄⁻ as the rate-determining step of the process. Furthermore, the reuse and durability of the material were evaluated, revealing a catalyst performance close to 100% over the 10 tested cycles. Therefore, it can be concluded that the synthesized material, Pt-nanoparticles dispersed on HTiNbO₅, exhibits excellent performance and is suitable for hydrogen evolution from NaBH₄. Full article

In Brazil, snakebites are a critical health issue, particularly in the state of Roraima, where Bothrops species account for the majority of cases. Snake venoms contain multifunctional toxins that cause life-threatening systemic complications and complex wounds, often resulting in permanent disabilities. Although antivenoms have reduced lethality, they fail to prevent the rapid and prolonged action of tissue-damaging toxins at the bite site. As a result, snakebite management is characterized by prolonged hospitalizations and high healthcare costs. Therefore, effective management of these complex wounds is crucial to improving patient outcomes. This article presents a series of four clinical cases involving Bothrops snakebite patients treated at the General Hospital of Roraima. Each case describes the progression of the injury, clinical challenges, interventions, and outcomes. Vacuum-Assisted Wound Therapy (VAWT) was employed as a key component of treatment in all cases, promoting faster granulation tissue formation, infection control, and reduced risk of amputation. The use of VAWT demonstrated significant improvements in wound healing compared to conventional treatment approaches. These findings highlight the potential benefits of VAWT in managing complex snakebite-related wounds, especially in severe cases with high risks of complications. However, barriers such as the high cost of therapy and limited access in remote and resource-poor regions must be addressed to enable broader clinical application. Full article

Hand Gesture Recognition (HGR) is a vital technology that enables intuitive human–computer interaction in various domains, including augmented reality, smart environments, and assistive systems. Achieving both high accuracy and real-time performance remains challenging due to the complexity of hand dynamics, individual morphological variations, and computational limitations. This paper presents a lightweight and efficient skeleton-based HGR framework that addresses these challenges through an optimized multi-stream Convolutional Neural Network (CNN) architecture and a trainable ensemble tuner. Dynamic 3D gestures are transformed into structured, noise-minimized 2D spatiotemporal representations via enhanced data-level fusion, supporting robust classification across diverse spatial perspectives. The ensemble tuner strengthens semantic relationships between streams and improves recognition accuracy. Unlike existing solutions that rely on high-end hardware, the proposed framework achieves real-time inference on consumer-grade devices without compromising accuracy. Experimental validation across five benchmark datasets (SHREC2017, DHG1428, FPHA, LMDHG, and CNR) confirms consistent or superior performance with reduced computational overhead. Additional validation on the SBU Kinect Interaction Dataset highlights generalization potential for broader Human Action Recognition (HAR) tasks. This advancement bridges the gap between efficiency and accuracy, supporting scalable deployment in AR/VR, mobile computing, interactive gaming, and resource-constrained environments. Full article

Hydrogen has been explored as a greener alternative for greenhouse gas emissions reduction. Sodium borohydride (NaBH₄) is a favorable hydrogen carrier due to its high hydrogen content, safe handling, and rapid hydrogen release. This work presents a novel synthesis of the catalyst CoFe₂O₄/Fe₂O₃ using nanocellulose fibers (TCNF) as reactive templates for metal adsorption and subsequent calcination. The resulting material was tested for H₂ production from basic NaBH₄ aqueous solutions (10–55 °C). The catalyst’s composition is 74.8 wt% CoFe₂O₄, 25 wt% Fe₂O₃, and 0.2 wt% Fe₂(SO₄)₃ with agglomerated spheroidal particles (15–20 nm) and homogeneous Fe and Co distribution. The catalyst produced 1785 mL of H₂ in 15 min at 25 °C (50 mg catalyst, 4.0% NaBH₄, and 2.5 wt% NaOH), close to the stoichiometric maximum (2086 mL). The maximum H₂ generation rate (HGR) reached 3.55 L min⁻¹ g_cat⁻¹ at 40 °C. Activation energies were determined using empirical (38.4 ± 5.3 kJ mol⁻¹) and Langmuir–Hinshelwood (L–H) models (42.2 ± 5.8 kJ mol⁻¹), consistent with values for other Co-ferrite catalysts. Kinetic data fitted better to the L–H model, suggesting that boron complex adsorption precedes H₂ evolution. Full article

In the field of Hand Gesture Recognition (HGR), Electromyography (EMG) is used to detect the electrical impulses that muscles emit when a movement is generated. Currently, there are several HGR models that use EMG to predict hand gestures. However, most of these models have limited performance in real-time applications, with the highest recognition rate achieved being 65.78 ± 15.15%, without post-processing steps. Other non-generalizable models, i.e., those trained with a small number of users, achieved a window-based classification accuracy of 93.84%, but not in time-real applications. Therefore, this study addresses these issues by employing transformers to create a generalizable model and enhance recognition accuracy in real-time applications. The architecture of our model is composed of a Convolutional Neural Network (CNN), a positional encoding layer, and the transformer encoder. To obtain a generalizable model, the EMG-EPN-612 dataset was used. This dataset contains records of 612 individuals. Several experiments were conducted with different architectures, and our best results were compared with other previous research that used CNN, LSTM, and transformers. The findings of this research reached a classification accuracy of 95.25 ± 4.9% and a recognition accuracy of 89.7 ± 8.77%. This recognition accuracy is a significant contribution because it encompasses the entire sequence without post-processing steps. Full article

In this study, we aimed to evaluate physiological and agronomic traits in 120 sugarcane genotypes under early drought stress conditions in a field trial across various soil types. The experiment used a split-plot arrangement, with a randomized complete block design and two replications. Two different water regimes were assigned to the main plot: (1) non-water stress (CT) and (2) drought (DT) at the early growth stage, during which sugarcane was subjected to drought stress by withholding water for 4 months. The subplot consisted of 120 sugarcane genotypes. The stalk height, stalk diameter, number of stalks, photosynthetic traits including SPAD chlorophyll meter reading (SCMR) and maximum quantum efficiency of photosystem II photochemistry (Fv/Fm), and normalized difference vegetation index (NDVI) were measured at 3, 6, and 9 months after planting (MAP). Yield and yield component parameters were measured at 12 MAP. Drought treatments lead to significant changes in various physiological traits in the sugarcane. Clustering analysis classified 36 sugarcane varieties grown in sandy loam soil and 15 genotypes in loam soil into two main clusters. In sandy loam soils, Biotec4 and CO1287 exhibited outstanding performance in drought conditions, delivering high cane yields. Meanwhile, in loam soil, MPT13-118, MPT07-1, Q47, F174, MPT14-1-902, and UT1 exhibited the best drought tolerance. Under drought conditions, cluster 1 showed higher values for SCMR, NDVI, height growth rate (HGR), cane yield, and drought tolerance index compared to cluster 2. These findings suggest that breeders can utilize these genotypes to enhance drought resistance, and the identified physiological traits can assist in selecting stronger candidates for drought tolerance. Full article

The dynamic phosphorylation of the human RNA Pol II CTD establishes a code applicable to all eukaryotic transcription processes. However, the ability of these specific post-translational modifications to convey molecular signals through structural changes remains unclear. We previously explained that each gene can be modeled as a combination of n circuits connected in parallel. RNA Pol II accesses these circuits and, through a series of pulses, matches the resonance frequency of the DNA qubits, enabling it to extract genetic information and quantum teleport it. Negatively charged phosphates react under RNA Pol II catalysis, which increases the electron density on the deoxyribose acceptor carbon (2’C in the DNA sugar backbone). The phosphorylation effect on the stability of a carbon radical connects tyrosine to the nitrogenous base, while the subsequent pulses link the protein to molecular water through hydrogen bonds. The selective activation of inert C(sp³)–H bonds begins by reading the quantum information stored in the nitrogenous bases. The coupling of hydrogen proton transfer with electron transfer in water generates a supercurrent, which is explained by the correlation of pairs of the same type of fermions exchanging a boson. All these changes lead to the formation of a molecular protein–DNA–water transcriptional condensate. Full article