Search Results (12,419)

This study investigated the effects of different additives on the fermentation quality and bacterial community of silage prepared from Giant Juncao grass (Cenchrus fungigraminus) grown in saline–alkali soil. Four treatments were compared: a control group (CK), wheat bran (WB), fermented Juncao grass juice (FJGJ), and a combined wheat bran + fermented Juncao grass juice treatment (WB + FJGJ). Dynamic changes in physicochemical characteristics—including dry matter (DM), pH, lactic acid (LA), acetic acid (AA), propionic acid (PA), and total volatile fatty acids (TVFA)—were monitored together with shifts in bacterial community structure. Quantitative results showed that FJGJ and WB + FJGJ significantly improved fermentation performance. Compared with the control, the WB + FJGJ treatment reduced the final pH to 3.61 (p < 0.05) and increased lactic acid concentration to 48 g/kg DM. Concentrations of acetic acid and TVFA were also higher in additive-treated silages than in the control. Redundancy analysis indicated that pH and lactic acid were the main environmental factors associated with changes in bacterial community composition, whereas ether extract and acetic acid showed weaker but detectable effects. Bacterial community profiling revealed that genera such as Secundilactobacillus and Lacticaseibacillus dominated in the additive-treated groups, and that the additives significantly altered microbial community structure compared with the control. Overall, the combined application of wheat bran and fermented Juncao grass juice improved the fermentation quality of Giant Juncao grass silage grown on saline–alkali soil and promoted a bacterial community dominated by beneficial lactic acid–producing taxa. Full article

Hierarchical Federated Learning (HFL) alleviates the trade-off between communication overhead and privacy protection in mobile scenarios via multi-level aggregation and mobility consideration. However, its idealized convex loss assumption and full-dimension parameter upload deviate from real-world non-convex tasks and edge channel constraints, causing excessive energy consumption, high communication cost, and compromised convergence that hinder practical deployment. To address these issues in mobile/UAV networks, this paper proposes an energy-efficient optimization scheme for HFL under non-convex loss, integrating a dynamically adjustable partial-dimension model upload mechanism. By screening key update dimensions, the scheme reduces uploaded data volume. We construct a total energy minimization model that incorporates communication/computation energy formulas related to upload dimensions and introduces an attendance rate constraint to guarantee learning performance. Using Lyapunov optimization, the long-term optimization problem is transformed into single-round solvable subproblems, with a step-by-step strategy balancing minimal energy consumption and model accuracy. Simulation results show that compared with the original HFL algorithm, our proposed scheme achieves significant energy reduction while maintaining high test accuracy, verifying the positive impact of mobility on system performance. Full article

With socioeconomic development, cities face increasingly complex and diverse disaster risks, making the construction of resilient cities an inevitable choice. However, the driving forces and tactical approaches behind urban resilience development remain unclear for urban safety development, thus posing challenges to cities urgently needing to enhance their resilience. Therefore, this paper investigates this issue, covering the following aspects: (1) Eighteen influencing factors within the complex system of urban resilience were identified and summarized from five perspectives: Economic, Social, Environmental, Infrastructure, and Organizational & Institutional. The attributes of the influencing factors were analyzed using the Decision-Making Experimentation and Evaluation Laboratory (DEMATEL) method, and key factors were identified accordingly. (2) The Total Adversarial Interpretive Structure Model (TAISM) method was applied to construct a multi-perspective adversarial recursive structural model with integrated impact values. This model illustrates the interrelationships among the influencing factors and clarifies their hierarchical structure. (3) A Fuzzy Reachability Matrix (FR) was introduced to handle uncertain relationships between factors in the comprehensive influence matrix, enabling an explicit analysis of the hierarchical structure of the urban resilience complex coupling giant system, clearly showing the impact of factor hierarchical changes on the system structure. (4) Building upon the analysis of factors affecting urban resilience, the specific pathways and mechanisms were articulated, followed by recommended measures formulated from both internal (governmental) and external (community) perspectives. The results can provide theoretical support for resilient city construction and serve as a practical cornerstone. Full article

Gastric cancer (GC) is the fifth most common cancer worldwide, with the highest incidence in East Asia. Although H. pylori is a well-known risk factor, carcinogenesis can occur independently of H. pylori infection, and approximately 43% of adults carry H. pylori as part of their native microbiota. This study aimed to identify potential oral and gastric microbial markers across different histological stages of GC in both H. pylori-positive and -negative patients. Buccal swabs and gastric mucosa samples were collected from patients with intestinal metaplasia, low-grade dysplasia, high-grade dysplasia, early GC, or advanced GC. Total DNA was extracted, and 16S rRNA gene amplicon sequencing was performed. Microbiome diversity generally remained stable across histological stages, with no directional shifts in community structure. Differential abundance analysis revealed higher relative abundances of Anaerostipes, Phocaeicola, and Collinsella in the gastric antrum of cancerous samples. Anaerostipes and Phocaeicola are typically enriched in the intestinal microbiota but are rarely observed in the stomach, suggesting their potential ecological and pathological relevance in gastric carcinogenesis. In H. pylori-negative patients, however, a different stage-associated abundance pattern was observed, in which Faecalibacterium, a genus predominantly associated with the intestinal environment, was less abundant in advanced gastric cancer samples than in earlier histological stages within the gastric body. These findings suggest that microbial changes during gastric cancer progression may follow different trajectories depending on H. pylori infection status. In oral samples, Haemophilus and Prevotella were more abundant in intestinal metaplasia than in low-grade dysplasia, and network analysis indicated links between Neisseria and Filifactor at oral and gastric sites. However, as the study population was limited to a single country and ethnicity, the applicability of these microbial markers should be carefully considered. Full article

The continuous degradation of mangrove ecosystems, considered among the most vulnerable worldwide, reveals multiple threats driven by human activities and climate change. In the Peruvian context, particularly in the Tumbes Mangrove ecosystem, these pressures are intensified by the absence of integrated spatial and educational infrastructures capable of supporting conservation efforts while engaging local communities. In response, this research proposes a Sustainable Interpretation Center for Conservation and Environmental Education in Ecologically Sensitive Areas of the Tumbes Mangrove, Peru. The methodology includes climate data analysis, identification of local flora and fauna, and site topography characterization, supported by digital tools such as Google Earth, AutoCAD 2025, Revit 2025, and 3D Sun Path. The results are reflected in an architectural proposal that incorporates sustainable materials compatible with sensitive ecosystems, including eco-friendly structural solutions based on algarrobo timber, together with resilient strategies addressing climatic variability, such as lightweight structures, elevated platforms, and passive environmental solutions that minimize impact on the mangrove. Furthermore, the proposal integrates a photovoltaic energy system consisting of 12 solar panels with a unit capacity of 450 W, providing a total installed capacity of 5.4 kWp, complemented by a 48 V LiFePO₄ battery storage system designed to ensure energy autonomy during periods of low solar availability. In conclusion, the proposal adheres to principles of sustainability and energy efficiency and aligns with the Sustainable Development Goals (SDGs) 7, 8, 12, 14, and 15, reinforcing the use of clean energy, responsible tourism, sustainable resource management, and the conservation of marine and terrestrial ecosystems. Full article

Glycerol fatty acid esters (GFAEs) exhibit potential applications in ruminant production, including enhancing animal performance, improving nutrient utilization, and modulating rumen function. However, studies on indigenous Dabieshan beef cattle are lacking. This study aimed to evaluate GFAE’s effects on their performance, meat quality, and rumen function. Thirty 2-year-old cattle (294.73 ± 3.21 kg; mean ± SD), were randomly divided into three groups (n = 10): on a dry matter (DM) basis, CON (basal diet), 0.05 GFAE (basal + 0.05% GFAE), 0.1 GFAE (basal + 0.1% GFAE), fed for 60 days. The crude protein (CP) digestibility of the 0.05 GFAE group showed a significant 4.55% increase compared with the CON group, while that of the 0.1 GFAE group was significantly elevated by 2.76% relative to the CON group. For key meat quality indices of Dabieshan beef cattle, compared with the CON group, the 0.05 GFAE and 0.1 GFAE groups showed increases in L value by 10.14% and 7.11%, respectively (p = 0.042); decreases in shear force by 5.24% and 1.48%, respectively (p = 0.024); and increases in ether extract(EE) content by 10.91% and 2.33%, respectively (p = 0.019). Compared with the CON group, the 0.05 GFAE and 0.1 GFAE groups showed significant alterations in key serum biochemical indices of Dabieshan beef cattle: TP (total protein) levels elevated significantly by 6.44% and 13.04%, respectively (p = 0.010); total antioxidant capacity (T-AOC) increased significantly by 33.96% and 46.23%, respectively (p = 0.001); UREA concentrations decreased significantly, by 22.67% and 33.53%, respectively (p = 0.002); superoxide dismutase (SOD) activity rose significantly, by 7.30% and 7.99%, respectively (p = 0.020); and malondialdehyde (MDA) content declined significantly, by 20.25% and 28.03%, respectively (p = 0.040). Relative to the CON group, dietary supplementation with GFAE significantly increased ruminal butyrate concentrations, with the 0.05 GFAE and 0.1 GFAE supplemented groups exhibiting respective increments of 17.38% and 18.03% (p = 0.025). Both Groups 0.05 GFAE and 0.1 GFAE reduced CH4 emissions (p = 0.005) and elevated Prevotella abundance (p = 0.001). The study findings revealed that dietary supplementation with GFAE at concentrations of 0.05% and 0.1% of dry matter resulted in substantial decreases in daily methane emissions, representing respective reductions of 6.91% and 11.63% compared to the control group (p = 0.005). At the species level of the rumen microbial community, the relative abundance of the genus Prevotella_sp. was significantly elevated by 60.52% and 38.48% in the 0.05 GFAE and 0.1 GFAE groups, respectively, when contrasted with the CON group (p = 0.001). Collectively, these results demonstrate that the inclusion of dietary 0.05% GFAE supplementation conferred multifaceted benefits to Dabieshan beef cattle, thereby highlighting its potential as a viable strategy to enhance the sustainability of beef cattle production systems. Full article

This study proposes a reinforcement learning-based link selection method for Low Earth Orbit satellite networks, aiming to reduce handover frequency while extending link duration under highly dynamic orbital environments. The proposed approach relies solely on basic satellite positional information, namely latitude, longitude, and altitude, to construct compact state representations without requiring complex sensing or prediction mechanisms. Using relative satellite and terminal geometry, each state is represented as a vector consisting of azimuth, elevation, range, and direction difference. To validate the feasibility of policy learning under realistic conditions, a total of 871,105 orbit based data samples were generated through simulations of 300 LEO satellite orbits. The reinforcement learning environment was implemented using the OpenAI Gym framework, in which an agent selects an optimal communication target from a prefiltered set of candidate satellites at each time step. Three reinforcement learning algorithms, namely SARSA, Q-Learning, and Deep Q-Network, were evaluated under identical experimental conditions. Performance was assessed in terms of smoothed total reward per episode, average handover count, and average link duration. The results show that the Deep Q-Network-based approach achieves approximately 77.4% fewer handovers than SARSA and 49.9% fewer than Q-Learning, while providing the longest average link duration. These findings demonstrate that effective handover control can be achieved using lightweight state information and indicate the potential of deep reinforcement learning for future LEO satellite communication systems. Full article

This paper presents a comprehensive techno-economic assessment of a community battery energy storage system (BESS) participating concurrently in energy arbitrage and frequency control ancillary services (FCAS) markets, while also providing customer savings through coordinated demand management. The proposed framework employs a mixed-integer linear programming (MILP) model to co-optimize the charging, discharging, and reserve scheduling of the battery under dynamic market conditions. The model explicitly incorporates key operational and economic factors such as round-trip efficiency, degradation cost, market-participation constraints, and revenue from multiple value streams. By formulating the optimization problem within this MILP structure, both the operational feasibility and the economic profitability of the system are evaluated over annual market cycles. Simulation results demonstrate that integrating FCAS participation with conventional energy arbitrage substantially enhances total revenue potential and improves asset utilization, compared with single-service operation. Furthermore, the coordinated management of community demand contributes to additional cost savings and supports local grid reliability. The findings highlight the critical role of co-optimized control and multi-market participation strategies in improving the financial viability and grid-support capabilities of community-scale BESS deployments. Full article

Monitoring epibiotic communities on the invasive red king crab (Paralithodes camtschaticus) in the Barents Sea is crucial for understanding the co-adaptation between this species and the local benthic fauna. Red king crabs were collected during regular diving surveys conducted in the coastal Barents Sea in 2015, 2021, and 2022. A detailed examination revealed the presence of two amphipod species, Metopa pusilla and Crassicorophium bonellii, which were not previously documented as epibionts on this host. With these additions, the total number of epibiotic amphipods on Barents Sea red king crabs rises to nine species (versus two in the native Sea of Okhotsk). Amphipod colonization was skewed toward large males, likely reflecting their greater migratory behavior. The prevalence of Metopa pusilla ranged from 1.9% to 4.3%, with a mean intensity of one individual per infested crab; Crassicorophium bonellii exhibited prevalence of 4.7–14.3% and mean intensity of 1.3–3.3 individuals. The primary colonization sites were the carapace and limbs. Given the low infestation parameters and the epibionts’ localization away from critical structures like the gills and egg clutches, it is concluded that these amphipods pose a negligible risk to host health. Full article

Background: Teamwork and effective communication are widely recognized as essential pillars for the safety and quality of healthcare. However, in Portugal, no validated instrument had previously been available to assess healthcare professionals’ attitudes toward teamwork. This study aimed to translate, culturally adapt, and validate the TeamSTEPPS^® Teamwork Attitudes Questionnaire (T-TAQ) for the Portuguese context, resulting in the Portuguese version of the instrument. Methods: A methodological study with a quantitative approach was developed. The translation and cultural adaptation process followed internationally recognized guidelines. The sample consisted of 162 healthcare professionals (136 nurses and 26 physicians) from a hospital in Lisbon. Exploratory and confirmatory factor analysis techniques were used to assess construct validity. The internal consistency of the scale was analyzed using Cronbach’s alpha coefficient. Results: The Portuguese version comprises 30 items distributed across five dimensions: Effective Leadership Support, Team Functional Performance, Teamwork Coordination, Willingness to Engage in Teamwork, and Team Functioning Supervision. The scale demonstrated a total explained variance of 53.9% and an overall internal consistency coefficient (α) of 0.86, indicating good reliability. Confirmatory factor analysis supported the five-factor structure of the scale (χ²/df = 1.461; CFI = 0.900; GFI = 0.821; RMSEA = 0.054; MECVI = 4.731). Conclusions: The T-TAQ-PT proved to be a valid, reliable, and robust instrument for assessing healthcare professionals’ individual attitudes toward teamwork, contributing to the development of research and clinical practice in the Portuguese context. Full article

To investigate the effects of different Trichosanthes kirilowii Maxim. varieties on leaf nutrients, soil nutrients, and microbial community composition, this study selected Yuelou No. 3 and Huiji No. 2, two major cultivars from the primary production area of Shishou City. The two varieties were cultivated at different locations under standardized agronomic management practices, and a systematic comparative analysis was carried out over a 10-month sampling period from March to December 2024. The analysis encompassed their leaf nutrients (total nitrogen, total phosphorus, total potassium, and relative chlorophyll content), soil nutrients (organic matter, alkali-hydrolyzable nitrogen, available phosphorus, and available potassium), and microbial community characteristics. The results revealed significant varietal differences in leaf nutrient content: the average total phosphorus content of Yuelou No. 3 (0.44%) was higher than that of Huiji No. 2 (0.39%), while Huiji No. 2 exhibited higher total nitrogen (3.73%), total potassium (3.86%), and SPAD (44.72). Leaf nutrient content in both varieties followed a pattern of nitrogen > potassium > phosphorus, with peak phosphorus and potassium demand occurring earlier in Yuelou No. 3. Additionally, Yuelou No. 3 contained higher organic matter (12.73 g/kg) and alkali-hydrolyzable nitrogen (103.02 mg/kg), while Huiji No. 2 showed enhanced soil pH (7.02), available phosphorus (6.96 mg/kg), and available potassium (180.00 mg/kg). Soil available nutrient dynamics displayed a pattern of slow change during the early stage, a rapid increase during the middle stage, and stabilization in the later stage. Microbial analysis revealed no significant differences in alpha diversity between the two varieties, although Yuelou No. 3 showed marginally higher diversity indices during early to mid-growth stages. In contrast, beta diversity showed significant separation in PCoA space. Proteobacteria, Acidobacteria, and Ascomycota were the dominant microbial phyla. Dominant genera included Kaistobacter, Mortierella, and Neocosmospora, among others, with variety-specific relative abundances. Redundancy analysis further supported the variety-specific influence of soil physicochemical properties on microbial community structure, with available phosphorus, available potassium, and alkali-hydrolyzable nitrogen identified as key factors shaping community composition. This study provides a theoretical basis for understanding the impact of different Trichosanthes kirilowii Maxim. varieties on soil–plant–microbe interactions and suggests potential directions for future research on fertilization and management strategies tailored to varietal differences. Full article

Households are the major contributor to food waste generation in the European Union according to the recently published data from Eurostat. Promoting food systems sustainability and aspiring to achieve the United Nations SDG 12.3 requires a better insight to the underlying drivers of the household food waste occurrence. The present study presents the combination of a well-established method of acquiring information, the questionnaire surveys, with a state-of-the-art technology for data imputation and interpretation using machine learning (ML). The Food Loss and Waste Prevention Unit (FLWPU) of the municipality of Halandri employed two surveys within the framework of the European funded projects Food Connections and FOODRUS. The first questionnaire was designed for rapid completion, to maximize response rates and minimize respondent burden, ensuring the collection of a consistent core dataset. A total of 154 replies were collected. The second questionnaire, associated with FOODRUS, was more detailed, enabling the participants to provide more in-depth information on their household food waste (HHFW) practices. In total, 43 responses were collected. ML algorithms were applied for data enhancement and data clustering. Specifically, ML and statistical techniques are applied for data imputations. An XGBoost algorithm was trained so as to capture complex relationships between variables. Behavioral intentions and effective strategies for reducing food waste at the community level are identified from the responses of both questionnaires, while a clustering of respondents in five groups emerged by using k-means, thus providing valuable insight into targeted HHFW prevention action plans. Full article

Understanding how plant community characteristics and soil properties vary along altitudinal gradients is essential for ecosystem conservation, restoration, and for predicting ecosystem responses to global environmental change. This study investigated altitudinal patterns and their potential drivers in mountain meadow communities on the southern slope of Wutai Mountain, Northern China. Community characteristics and soil physicochemical properties were measured along an altitudinal gradient ranging from 1800 to 3000 m a.s.l. Most community characteristics exhibited clear altitudinal trends. Species richness, Shannon–Wiener index, Simpson index, aboveground biomass and average plant height all declined significantly with increasing altitude. In contrast, vegetation cover showed a unimodal pattern, initially decreasing and then increasing at higher elevations. Soil physicochemical properties also varied significantly along the altitudinal gradient and were closely associated with changes in community characteristics. Variation partitioning analysis revealed that environmental factors, including altitude and soil properties, explained 71.9% of the total variation in mountain meadow communities. Altitude alone contributed more to community variation than soil factors, indicating its dominant role in shaping community structure. Nevertheless, specific soil properties, particularly soil depth, soil bulk density and soil pH, also exerted significant influences on community characteristics. Overall, our results demonstrate that altitude is a key driver of both vegetation and soil variation in mountain meadows on the southern slope of Wutai Mountain. In addition to altitudinal effects, soil physicochemical properties should be considered when developing conservation and management strategies for mountain meadow ecosystems. Full article

The study investigates repetitive and time-consuming professional activities performed by occupational health and safety (OHS) specialists in the construction sector in Poland and their attitudes toward the use of modern digital tools, including solutions based on artificial intelligence (AI). The research was conducted using a questionnaire survey, with a purposive sample and a snowball method. A total of 102 individuals participated in the study, of whom 94 valid responses were included in the analysis. The data were examined using descriptive statistics and chi-square tests. The results showed that the most repetitive and time-consuming activities include documentation analysis, report preparation, inspections, and communication. Nearly 46% of respondents indicated that selected elements of their work could be automated or supported by digital tools, while 33% reported using AI-based solutions in everyday practice. Statistically significant relationships were identified between respondents’ age and both their level of concern about new technologies and their perception of technological support potential. No significant relationships were found for enterprise ownership or size. The findings indicate substantial potential for the implementation of digital and AI-supported tools in routine OHS activities. Future research should involve larger and more homogeneous samples, incorporate probabilistic sampling, and explore organisational and competence-related factors influencing technology adoption. Full article

The study of energy needs in rural areas continues to be an active field of research. Although numerous gaps hinder the achievement of a sustainable energy transition in these areas, it is necessary to develop comprehensive strategies that integrate local participation with the implementation of efficient and appropriate energy technologies. This research analyzes local energy needs using a community participatory approach and considers four main stages, including a participatory diagnosis at the community level to identify energy needs, defining priority energy needs from the community’s viewpoint, estimating a baseline of the identified needs, their economic costs, and environmental impacts, constructing a scenario with a 20-year projection, and the benefits of implementing more efficient technologies. The results show that 98.9% of energy is destined for residential needs, 0.6% for community needs, and 0.5% for productive needs, and the economic expenditure follows the same hierarchy, while total emissions are estimated annually at just over 30,000 tCO_2e and 3 tPM_2.5. With the proposed scenario, at the end of year 20, a reduction in consumption of just over 200 TJ is estimated, together with present value savings of USD 490,000, and a decrease in emissions of approximately 27,000 tCO_2e and 2.7 tPM_2.5. This proposal is expected to contribute to encouraging research with broad community participation and to the formulation of strategies that enable a sustainable energy transition in rural contexts. Full article