Search Results (1,793)

This study assessed the effects of a family function (FF) program on excessive digital behaviors—smartphone overuse (SO) and phubbing—and psychological needs—anxiety, loneliness, and fear of missing out (FoMO)—among 28 Thai female Muslim adolescents randomly assigned to the experimental (M_age = 15.7) and control (M_age = 15.2) groups. The experimental group received two 1.5 h morning sessions of the FF program weekly over four weeks (eight sessions in total). Baseline assessments confirmed group homogeneity. Using repeated-measures ANOVA with Bonferroni correction (p < 0.008), the results indicated a significant improvement in family function for the intervention group (F (1,26) = 11.91, p = 0.002, η²_p = 0.31), with a strong time-by-group interaction (F (1,26) = 19.51, p < 0.001, η²_p = 0.43). While the program did not significantly reduce SO overall, a notable interaction effect suggested group differences (F (1,26) = 10.31, p = 0.004, η²_p = 0.28). Phubbing remained unaffected. For psychological outcomes, interaction effects were found for the FoMO (F = 10.00, p = 0.004) and loneliness (F = 8.67, p = 0.007), though no main effects emerged. Anxiety levels did not significantly change after correction. These findings suggest that the program effectively enhances family functioning and partially alleviates psychosocial risks, but further refinements are needed to address digital overuse and anxiety more effectively. Full article

Magnetite (Fe₃O₄) provides a protective corrosion layer in the steam generators of nuclear power plants. The presence of monoethanolamine (MEA) in coolant water has a beneficial effect on corrosion processes. In that context, the adsorption of MEA and ethanol–ammonium cation on the {111} surface of magnetite was studied using the molecular dynamics (MD) method. A modified version of the mechanical force field (ClayFF) was used. The systems were simulated at different temperatures (423 K; 453 K; 503 K). Surface coverage data were obtained from adsorption simulations; the root-mean-square deviation (RMSD) of the target molecules were calculated, and their minimum distance to the magnetite surface was traced. The potential and adsorption energies of MEA were calculated as a function of temperature. It has been established that the interaction between MEA and magnetite is due to electrostatic phenomena and the adsorption rate increases with temperature. A comparison was made with existing experimental results and similar MD simulations. Full article

This research investigated the impact of corn–soybean meal-based fermented feed on the growth performance, pork quality, and fatty acid profiles of lean-type finishing pigs. A total of 80 lean-type growing DLY (Duroc × Landrace–Yorkshire) pigs were randomly assigned to 2 groups, with 5 replicates of 8 pigs per pen. The pigs in control group (CON group) were fed a basal diet, while the pigs in fermented feed group (FF group) were fed a diet supplemented with 10% fermented feed. The experimental period lasted 70 days. Results exhibited that pigs in FF group had a significant increase in final body weight and average daily gain (ADG) (p < 0.05) and had a significant decrease in the feed-to-gain ratio (F/G) (p < 0.05). The FF group also exhibited significant promotion in muscle intramuscular fat content, marbling score, and meat color and significantly reduced the meat shear force and drip loss (p < 0.05). Serum analysis indicated that fermented feed significantly elevated blood glucose, total cholesterol, triglyceride levels, and serum hormones such as insulin, leptin, and IGF-1 (p < 0.05). Additionally, fermented feed significantly elevated the levels of polyunsaturated fatty acids (PUFAs) and monounsaturated fatty acids (MUFAs), whereas it decreased the saturated fatty acids (SFAs) contents (p < 0.05). The fermented feed also significantly enhanced pork nutritional values (p < 0.05). The fermented feed increased the expression of IGF-1, SREBP1c, PDE3, PPARγ, SCD5, and FAT/CD36 mRNA (p < 0.05). Furthermore, microbial 16S rDNA analysis uncovered that FF supplementation significantly reduced the Campilobacterota phylum abundance, while increasing the genus abundances of Clostridium_sensu_stricto, norank_f_Oscillospiraceae, unclassified_c_Clostridia, and V9D2013 (p < 0.05). In summary, the results indicated that the microbial fermented feed exhibited the regulation effects on pork quality and nutritional values of lean-type pigs through regulating lipid metabolism and gut microbial composition. Full article

Forest mortality (FM) is influenced by several independent factors, including forest fragmentation (FF) at different spatial scales and multi-scales, site conditions, and stand characteristics. The aim of this study was to investigate the relationship and effect of FF at various spatial scales on the probability of Scots pine FM. The presented study also analyzed the relationship of the multi-scale fragmentation index effect on forest dieback. The relationship between multiple stressors emphasizes the distinct role of FF in influencing pine FM probability. Data on forest cover, deadwood volume of Scots pine forest, and environmental variables were obtained from the Forest Information System for Europe, the Polish National Forest Inventory, and existing databases, respectively. A generalized additive model approach was used to develop models. The results showed that, at small (50–600 m), large (800–3000 m), and multi spatial scales, the FF effect on Scots pine FM probabilities was statistically significant. There is a partial effect of multi-scale fragmentation on the probability of Scots pine FM, given a holistic view of the fragmentation effect that captures both small and large-scale effects. The study concludes that to calculate FF for a particular area, analyzing different scales and capturing multi-scale level fragmentation indices is crucial to studying the cumulative effect of fragmentation on the probability of Scots pine FM. Full article

Background/Objectives: Cystic fibrosis (CF) is a multi-system disorder characterized by chronic respiratory failure, malnutrition, and impaired growth. Achieving linear growth above the 50th percentile is associated with better pulmonary outcomes. Since October 2022, Elexacaftor/Tezacaftor/Ivacaftor (ETI) has been approved in Italy for children aged ≥6 years. However, data on its impact on height velocity (HV) remain lacking. This study aims to evaluate growth patterns by HV and explore differences according to the CFTR variant genotype. Methods: We conducted a prospective single-center study at the CF Unit of Bambino Gesù Children’s Hospital involving 24 children aged 6–11 years eligible for ETI treatment. Baseline assessments included height, weight, body mass index (BMI), bone mineral density (BMD), body composition (via bioelectrical impedance analysis, BIA), and muscle strength (one-minute sit-to-stand test (1STST)). Height, weight, HV, and BMI standard deviation scores (SDS) were calculated for the 6 months before and after ETI initiation. Results: The mean age of the cohort was 8.7 ± 1.9 years (F/M: 12/12), with most patients naïve to CFTR modulators. A significant increase in HV was observed post-ETI: from 4.2 ± 2.0 cm/year (−1.96 ± 2.4 SDS) in the 6 months before treatment to 7.1 ± 3.0 cm/year (+1.5 ± 3.7 SDS) after treatment initiation (p < 0.0001). Patients with F508del/minimal function (F/MF) genotypes (n = 11) showed significantly greater HV compared to those with F508del/F508del (F/F, n = 5) and F508del/residual function (F/RF, n = 8) genotypes (p < 0.0001). No significant differences were observed among genetic groups in baseline BMD or lean mass. Conclusions: ETI treatment significantly and rapidly improves HV in children with CF, particularly in those with F/MF genotypes. These findings underscore the role of CFTR modulator therapy in promoting linear growth, a key indicator of health in pediatric CF populations. Full article

A wide-bandgap AgInGaSe₂ (AIGS) thin film was fabricated using molecular beam epitaxy (MBE) via a three-stage method. The influence of Selenium (Se) pressure on the properties of AIGS films and solar cells was studied in detail. It was found that Se pressure played a very important role during the fabrication process, whereby Se pressure was varied from 0.8 × 10⁻³ Torr to 2.5 × 10⁻³ Torr in order to specify the effect of Se pressure. A two-stage mechanism during the production of AIGS solar cells was concluded according to the experimental results. With an increase in Se pressure, the grain size significantly increased due to the supply of the Ag–Se phase; the superficial roughness also increased. When Se pressure was increased to 2.1 × 10⁻³ Torr, the morphology of AIGS changed abruptly and clear grain boundaries were observed with a typical grain size of over 1.5 μm. AIGS films fabricated with a low Se pressure tended to show a higher bandgap due to the formation of anti-site defects such as In and Ga on Ag sites as a result of the insufficient Ag–Se phase. With an increase in Se pressure, the crystallinity of the AIGS film changed from the (220)-orientation to the (112)-orientation. When Se pressure was 2.1 × 10⁻³ Torr, the AIGS solar cell demonstrated its best performance of about 9.6% (Voc: 810.2 mV; Jsc: 16.7 mA/cm²; FF: 71.1%) with an area of 0.2 cm². Full article

Recent deep learning models, including GPT-4, have achieved remarkable performance using the back-propagation (BP) algorithm. However, the mechanism of BP is fundamentally different from how the human brain processes learning. To address this discrepancy, the Forward-Forward (FF) algorithm was introduced. Although FF enables deep learning without backward passes, it suffers from instability, dependence on artificial input construction, and limited generalizability. To overcome these challenges, we propose Local Back-Propagation (LBP), a method that integrates layer-wise unsupervised learning with standard inputs and conventional loss functions. Specifically, LBP demonstrates high training stability and competitive accuracy, significantly outperforming FF-based training methods. Moreover, LBP reduces memory usage by up to 48% compared to convolutional neural networks trained with back-propagation, making it particularly suitable for resource-constrained environments such as federated learning. These results suggest that LBP is a promising biologically inspired training method for decentralized deep learning. Full article

Surfactants are widely utilized in agriculture as emulsifying, dispersing, anti-foaming, and wetting agents. In these adjuvant roles, the inherent biological activity of the surfactant is secondary to the active ingredients. Here, the hydrophilic non-ionic surface-active tri-block copolymer Pluronic^® F68 is investigated for direct biological activity in wheat. F68 binds to and inserts into lipid membranes, which may benefit crops under abiotic stress. F68’s interactions with Triticum aestivum (var Juniper) seedlings and a seed-borne Bacillus spp. endophyte are presented. At concentrations below 10 g/L, F68-primed wheat seeds exhibited unchanged emergence. Root-applied fluorescein-F68 (fF68) was internalized in root epidermal cells and concentrated in highly mobile endosomes. The potential benefit of F68 in droughted wheat was examined and contrasted with wheat treated with the osmolyte, glycine betaine (GB). Photosystem II activity of droughted plants dropped significantly below non-droughted controls, and no clear benefit of F68 (or GB) during drought or rehydration was observed. However, F68-treated wheat exhibited increased transpiration values (for watered plants only) and enhanced shoot dry mass (for watered and droughted plants), not observed for GB-treated or untreated plants. The release of seed-borne bacterial endophytes into the spermosphere of germinating seeds was not affected by F68 (for F68-primed seeds as well as F68 applied to roots), and the planktonic growth of a purified Bacillus spp. seed endophyte was not reduced by F68 applied below the critical micelle concentration. These studies demonstrated that F68 entered wheat root cells, concentrated in endosomes involved in transport, significantly promoted shoot growth, and showed no adverse effects to plant-associated bacteria. Full article

The diversification of plant protein sources is a strategic priority for European food systems, particularly under the EU Green Deal and Farm to Fork strategies. In this study, dual production of full-fat soy (FFS) and expanded soybean cake (ESC) was evaluated using non-GMO soybeans cultivated under semi-organic conditions in Central Poland. Two agronomic systems—post-emergence mechanical weeding with rotary harrow weed control (P1) and conventional herbicide-based control (P2)—were compared over a four-year period. The P1 system produced consistently higher yields (e.g., 35.6 dt/ha in 2024 vs. 33.4 dt/ha in P2) and larger seed size (TSW: up to 223 g). Barothermal and press-assisted processing yielded FFS with protein content of 32.4–34.5% and oil content of 20.8–22.4%, while ESC exhibited enhanced characteristics: higher protein (37.4–39.0%), lower oil (11.6–13.3%), and elevated dietary fiber (15.8–16.3%). ESC also showed reduced anti-nutritional factors (e.g., trypsin inhibitors and phytic acid) and remained microbiologically and oxidatively stable over six months. The semi-organic P1 system offers a scalable, low-input approach to local soy production, while the dual-product model supports circular, zero-waste protein systems aligned with EU sustainability targets. Full article

To investigate the influences of void defects of different sizes, molecular dynamics combined with ReaxFF-lg reactive force field was used to study the hot-spot formation mechanism and thermal decomposition behavior of 2,6-diamino-3,5-dinitropyrazine-1-oxide (LLM-105) crystals with different void defects at 2500 K. The results indicate that larger void defects are more conducive to the formation of hot-spots. The consistency of the trends in time evolution of the potential energy, species numbers, and small molecules amounts between the ideal and void-containing LLM-105 crystals demonstrates that the presence of the void defect does not alter the decomposition mechanism of the LLM-105 molecule. An increase in the size of the void defect significantly increases the degree of diffusion of the C, H, O, and N atoms in the crystals, which affects the effective collisions between the atoms and thus alters the occurrence frequency of relevant reactions and the production of relevant products. Full article

Precise extraction of rural settlements in alpine regions is critical for geographic data production, rural development, and spatial optimization. However, existing deep learning models are hindered by insufficient datasets and suboptimal algorithm structures, resulting in blurred boundaries and inadequate extraction accuracy. Therefore, this study uses high-resolution unmanned aerial vehicle (UAV) remote sensing images to construct a specialized dataset for the extraction of rural settlements in alpine mountainous areas, while introducing an innovative shadow mitigation technique that integrates multiple spectral characteristics. This methodology effectively addresses the challenges posed by intense shadows in settlements and environmental occlusions common in mountainous terrain analysis. Based on the comparative experiments with existing deep learning models, the Swin Transformer was selected as the baseline model. Building upon this, the Feature Fusion Swin Transformer (FF-SwinT) model was constructed by optimizing the data processing, loss function, and multi-view feature fusion. Finally, we rigorously evaluated it through ablation studies, generalization tests and large-scale image application experiments. The results show that the FF-SwinT has improved in many indicators compared with the traditional Swin Transformer, and the recognition results have clear edges and strong integrity. These results suggest that the FF-SwinT establishes a novel framework for rural settlement extraction in alpine mountain regions, which is of great significance for regional spatial optimization and development policy formulation. Full article

The advancement of Internet of Things (IoT) technology has enabled battery-powered devices to be deployed across a wide range of applications; however, it also introduces challenges such as high energy consumption and security vulnerabilities. To address these issues, adiabatic logic circuits offer a promising solution for achieving energy efficiency and enhancing the security of IoT devices. Adiabatic logic circuits are well suited for energy harvesting systems, especially in applications such as sensor nodes, RFID tags, and other IoT implementations. In these systems, the harvested bipolar sinusoidal RF power is directly used as the power supply for the adiabatic logic circuit. However, adiabatic circuits require a peak detector to provide bulk biasing for pMOS transistors. To meet this requirement, a diode-connected MOS transistor-based voltage doubler circuit is used to convert the sinusoidal input into a usable DC signal. In this paper, we propose a novel adiabatic logic design that maintains low power consumption while optimizing energy and current fluctuations across various input transitions. By ensuring uniform and complementary current flow in each transition within the logic circuit’s functional blocks, the design reduces energy variation and enhances resistance against power analysis attacks. Evaluation under different clock frequencies and load capacitances demonstrates that the proposed adiabatic logic circuit exhibits lower fluctuation and improved security, particularly at load capacitances of 50 fF and 100 fF. The results show that the proposed circuit achieves lower power dissipation compared to conventional designs. As an application example, we implemented an ultrasonic transmitter circuit within a LoRaWAN network at the end-node sensor level, which serves as both a communication protocol and system architecture for long-range communication systems. Full article

Background/Objectives: Plexiform neurofibromas (pNFs) are one of the cardinal presentations of NF1 patients, often arising during early childhood. Since selumetinib was approved by the FDA in 2020, the long-term side effects and various responses of mitogen-activated protein kinase inhibitors (MEKi) in pediatric patients necessitate a new strategy. We propose that combining selumetinib with heat shock protein 90 inhibitors (HSP90i) can enhance the inhibitory effects as well as reduce the dosage of selumetinib in combination. We validated the synergistic effects and the significantly improved treatment effects of the combination of selumetinib and HSP90i in pNFs. Methods: We used drug screen data mining to predict the combination of selumetinib and HSP90i. Using cell lines and in vivo mouse models for pNFs, we tested a series of combinations with different concentrations. We validated the in vivo inhibitory effects using the transplanted tumors from DhhCreNf1^f/f mouse models. Results: We demonstrated that combining selumetinib and SNX-2112 or retaspimycin can achieve better tumor inhibition with synergistic effects. The combination significantly delays the progression of mouse pNFs. Conclusions: The combination of selumetinib and HSP90i has significant synergistic effects, provides therapeutic inhibitor effects, and reduces the selumetinib dosage in combination. Full article

Double ultrathin copper foils (DTH), widely used for producing conductive tracks in electronics, consist of an ultrathin copper functional foil (FF), a nanometric release layer (RL), and an ultrathin copper carrier foil (CF). Achieving stable release strength of the CF during DTH lamination remains a key challenge, largely due to limited knowledge about the structure of the RL. In this study, a comprehensive characterization methodology is proposed to investigate the physico-chemical structure of a chromium-based RL, both before and after thermal exposure at 230 °C. Peel-off testing, X-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and transmission electron microscopy (TEM) were employed. The main structural transformation identified is the oxidation of the RL at the FF–RL interface, resulting in the formation of a chromium oxide layer. This transformation may underlie the significant increase in release strength, which rises from 5.9 N/m before thermal exposure to 163 N/m afterward. Full article

Perovskite solar cells (PSCs) have already been reported as a promising alternative to traditional energy sources due to their excellent power conversion efficiency, affordability, and versatility, which is particularly relevant considering the growing worldwide demand for energy and increasing scarcity of natural resources. However, operational concerns under environmental stresses hinder its economic feasibility. Through the addition of cesium (Cs), this study investigates how to optimize perovskite solar cells (PSCs) based on methylammonium lead-iodide (MAPbI₃) by creating mixed-cation compositions of MA_1−xCs_xPbI₃ (x = 0, 0.25, 0.5, 0.75, 1) for devices A to E, respectively. The impact of cesium content on the following factors, such as open-circuit voltage (V_oc), short-circuit current density (J_sc), fill factor (FF), and power conversion efficiency (PCE), was investigated using simulation software, with ITO/TiO₂/MA_1−xCs_xPbI₃/Spiro-OMeTAD/Au as a device architecture. Due to diminished defect density, the device with x = 0.5 (MA_0.5Cs_0.5PbI₃) attains a maximum power conversion efficiency of 18.53%, with a V_oc of 0.9238 V, J_sc of 24.22 mA/cm², and a fill factor of 82.81%. The optimal doping density of TiO₂ is approximately 10²⁰ cm⁻³, while the optimal thicknesses of the electron transport layer (TiO₂, 10–30 nm), the hole-transport layer (Spiro-OMeTAD, about 10–20 nm), and the perovskite absorber (750 nm) were identified to maximize efficiency. The inclusion of a small amount of Cs may improve photovoltaic responses; however, at elevated concentrations (x > 0.5), power conversion efficiency (PCE) diminished due to the presence of trap states. The results show that mixed-cation perovskite solar cells can be a great commercially viable option because they strike a good balance between efficiency and performance. Full article