Search Results (2,830)

The growing global consumption of concrete is driving up the demand for cement, which has a negative environmental impact due to intensive CO₂ emissions. This impact can be reduced by replacing cement with reactive mineral industrial waste, simultaneously addressing the issue of waste accumulation in landfills. However, to ensure the effective use of such materials, it is essential to comprehensively investigate their influence on concrete durability. This study analyzes glass processing waste (GPW) generated during glass grinding. The waste is removed using water, resulting in the formation of glass processing waste. In the experiment, CEM I 42.5 R cement, GPW, sand, crushed dolomite stone, concrete sludge (CS), chemical admixtures, and water were used. In the tests, cement was replaced with glass processing waste in amounts ranging from 5% to 30%, analyzing a total of seven different compositions. The properties of the sustainable concrete mixture were evaluated, and the mechanical–physical properties of the hardened concrete were determined. Resistance to alkali–silica reaction was tested according to the RILEM AAR-4 methodology, while the environmental impact of glass processing waste was assessed using Life Cycle Assessment (LCA). The results showed that glass processing waste increases the concrete’s resistance to alkali corrosion: as the amount of waste increased, a smaller change in the linear dimensions of the specimens was recorded, and the lowest mass loss was found in the composition where 20% of the cement was replaced by glass processing waste. The environmental impact assessment confirmed a direct correlation—as the amount of glass waste increases, CO₂ emissions decrease proportionally. To produce sustainable concrete, it is recommended to use up to 20% glass processing waste: this allows for the maximum reduction in environmental impact while maintaining mechanical properties and high resistance to alkali–silica reaction. Full article

Nutrition is one of the main challenges facing honey bees, especially during autumn and winter. This work aimed to evaluate the effects of feeding Apis mellifera with a protein-enriched diet (YCPC) compared to a control diet. Development of the hypopharyngeal glands (HPGs), dimensions of the second wax mirror, and the stinging apparatus were measured in the two groups. Additionally, key biochemical parameters were assessed in homogenized worker honey bees. No significant differences were observed in hypopharyngeal gland (HPG), acini diameters or surface area, or in the measurement of the stinging apparatus and poison sac, except for a slight decrease in the newly emerged bees. YCPC supplementation significantly elevated total soluble protein content in newly emerged and nurse bees. Lower lipid levels were observed in newly emerged and nurse bees from the supplemented group and higher lipid reserves in were observed in supplemented foragers. No significant variation was observed in total carbohydrate content, except for a significant reduction in supplemented newly emerged bees. Acetyl cholinesterase activity was higher in younger bees and lower in foragers. A slight elevation in α and β-esterase expression was detected in the supplemented group, supporting enhanced detoxification capacity. YCPC enhances the biochemical capacity of honey bees, particularly in the early adult stages. However, glandular and morphological development were not affected. Full article

Mangrove ecosystems are critical for climate change mitigation; however, monitoring these environments in high-precipitation regions, such as the Colombian Pacific coast, is often hindered by persistent cloud cover and complex terrain. This study addresses these challenges by implementing the novel Google AlphaEarth Foundations (AEF) technology, leveraging 64-dimensional embeddings integrated with Digital Elevation Models (DEM) and Slope data. For classification, a Random Forest (RF) algorithm was deployed using a subset of only 7 embedding dimensions alongside topographical variables. The model estimated a mangrove extent of 209,262 ha, compared to a reference baseline of 137,732 ha. This discrepancy is hypothesized to stem from the model’s ability to map changes in the mangrove forest due to anthropogenic and natural factors and species migrating upstream, areas frequently overlooked in traditional inventories. The classification performance, evaluated on a spatially independent hold-out validation set, yielded an Overall Accuracy of 0.9844 and a Kappa Index of 0.9747. Regarding biomass estimation, the RF algorithm utilized 4 embedding dimensions plus DEM and Slope to achieve a Coefficient of Determination ($R^2$) of 0.5844, a Root Mean Square Error (RMSE) of 18.99 Mg/ha, and a Mean Absolute Error (MAE) of 14.88 Mg/ha within a range of 100–300 Mg/ha. These metrics represent a notable advancement, successfully mitigating the physical signal saturation that typically constrains traditional single-sensor remote sensing models at high biomass thresholds. Significant advantages of this methodology include the complete elimination of cloud interference and a drastic reduction in processing time. These findings demonstrate that the synergy between foundational models and machine learning provides a robust, scalable, and efficient framework for managing blue carbon stocks in critical tropical regions. Full article

The sound reduction index R is commonly determined using standardized laboratory procedures developed primarily for full-size building elements. However, in many research and development applications, including technical enclosures, lightweight panels, modular components, and new acoustic materials, only reduced-size specimens are available. In such cases, the influence of specimen dimensions and test-opening geometry on the measured sound insulation is not yet fully understood. This study investigates the effect of specimen size and geometry on the measured sound reduction index using a dedicated small-scale coupled reverberation room stand. Measurements were performed for five materials with different mechanical and structural properties: steel, polymethyl methacrylate (PMMA), medium-density fiberboard (MDF), gypsum board, and Sylomer. Six test openings were analyzed, including three square openings, one quasi-square opening, and two rectangular openings. The results show that specimen dimensions can significantly affect the measured values of R, especially in the low-frequency range, where modal behavior, boundary conditions, and the relationship between specimen dimensions and acoustic wavelength are important. The influence of specimen size was material-dependent and was more pronounced for stiff plate-like materials than for the highly compliant Sylomer specimen. Comparisons between square and rectangular openings with similar surface areas suggest that, within the investigated range of materials, specimen geometries, and measurement conditions, specimen surface area had a greater influence on R than specimen shape, although geometry can still contribute to the measured differences. The repeatability analysis confirmed that the measurement stand is sensitive to differences related to material type, specimen dimensions, and installation conditions. The proposed methodology may be particularly useful for comparative studies of novel acoustic materials and prototype building elements when only reduced-size specimens are available during the early stages of material development. The results support the use of small coupled reverberation rooms for comparative testing and preliminary material screening, while also showing that reduced-size sound insulation measurements require careful interpretation and cannot be treated as direct substitutes for full-scale standardized tests. Full article

This study examines how the strategic integration of digital transformation and national innovation capacity contributes to accelerating sustainable development in Saudi Arabia by focusing on six Sustainable Development Goals (SDGs): SDG 4—Quality Education, SDG 7—Affordable and Clean Energy, SDG 8—Decent Work and Economic Growth, SDG 9—Industry, Innovation and Infrastructure, SDG 12—Responsible Consumption and Production, and SDG 13—Climate Action. Using annual data on ICT use, ICT access, R&D expenditure, and patent applications, the analysis evaluates both the direct and joint relationships between these indicators and SDG performance. Digital transformation is captured through ICT use and ICT access, while national innovation capacity is represented by R&D expenditure and patent applications, reflecting the input and output dimensions of formal innovation activity. The findings indicate that the direct long-run effects of digital transformation and national innovation capacity on the six SDGs are not statistically significant, suggesting that these domains have not yet become standalone drivers of educational advancement, clean-energy adoption, economic performance, industrial upgrading, sustainable resource management, or emissions reduction. In contrast, their interaction produces substantial positive effects on SDG 4, SDG 7, SDG 8, and SDG 9, highlighting improvements in educational quality, renewable energy transition, productivity, and industrial innovation. The interaction also has significant negative effects on SDG 12 and SDG 13, as reflected by reductions in CO₂ intensity and environmental pressures. These results indicate that meaningful progress toward the SDGs emerges when digital capabilities and national innovation capacity evolve jointly, rather than through isolated improvements in ICT infrastructure or innovation inputs. Robustness checks using a composite SDG index confirm the stability of these complementary effects. These findings suggest that Saudi Arabia can accelerate progress toward the SDGs by adopting integrated policies that link ICT expansion with stronger R&D systems, patent commercialization, technological innovation, and sustainability-oriented industrial transformation across education, energy, industry, resource efficiency, and climate action. Full article

This study examines how energy-security shocks shape macroeconomic resilience in import-dependent economies and which energy-management strategies remain robust under alternative shock conditions. Using a balanced panel of 18 mainly European energy-importing economies and Türkiye for 2000–2024, the study constructs a Macroeconomic Resilience Index (MRI) from five dimensions: GDP growth, inflation, unemployment, current account balance, and industrial production growth. Inflation and unemployment are treated as inverse resilience indicators, and a Principal Component Analysis (PCA)-based alternative index is used as a robustness check. Methodologically, the study develops a hybrid framework that first applies a Shock-Augmented Cross-Sectionally Dependent Panel Quantile ARDL model to estimate heterogeneous shock effects across resilience levels, and then translates the econometric evidence into a Shock-Conditioned Bayesian Network–Regret MCDM model for strategy prioritization. The findings show that exchange-rate pressure is the most consistent long-run vulnerability channel, while energy intensity weakens resilience across short-run, benchmark, and quantile robustness results. The renewable energy share supports resilience under some conditions, but its effect depends on complementary investments in storage, grid flexibility, and demand-side capacity. Scenario results indicate that exchange-rate pressure produces the weakest resilience profile. The positive MRI value observed during combined-crisis years should be interpreted cautiously, as additional sensitivity evidence indicates that it mainly reflects the 2021–2022 post-pandemic rebound rather than a beneficial effect of shocks. Bayesian Network results identify macro-financial stabilization, import-dependency reduction, energy efficiency, and grid reliability as key resilience drivers. The regret-based MCDM results rank energy efficiency improvement as the most robust strategy, followed by energy import diversification. The study contributes by linking dynamic macroeconometric shock analysis with probabilistic scenario modeling and regret-sensitive decision support, offering an evidence-informed framework for prioritizing energy-security strategies in the sampled import-dependent economies. Full article

Human-computer interaction (HCI) exploits various input methods to improve user experience, but those without visual access suffer more than the mainstream. In this context, this paper proposes a novel Gesture-based Human-Computer Interaction (GCI) system for visually impaired people (VIP). However, a large set of gestures introduces complexity, which poses challenges for VIP to interact with computers. Therefore, an accessible assistive application with a minimal set of gestures is designed here. Nineteen (19) participants engaged, and several dimensions were evaluated, including skin conductance, NASA-TLX, and performance indicators. The gesture response time revealed that the proposed GCI technique is 39% faster than the existing technique. In addition, the skin conductance revealed a modest reduction, which means GCI caused a more relaxed reaction than the existing technique. GCI demonstrated significant statistical advantages in gesture response time, skin conductance, and forgot word count, while other measures showed comparable performance between the two techniques. GCI provides a more efficient and cognitively favorable interaction experience which opens a new era in the design and development of assistive technologies for VIP. Full article

In this study, four types of anti-ultraviolet aging agents—layered double hydroxides (LDHs), organic montmorillonite (OMMT), titanium dioxide (TiO₂), and ultraviolet absorber (UV326)—were employed to modify asphalt. The modified asphalt samples underwent Rolling Thin Film Oven Test (RTFOT) and xenon-lamp aging treatments, and we examined the evolution of their physical properties, rheological performance, and chemical composition. A principal component analysis (PCA) model built on representativeness, discriminative power, and non-redundancy reduced the multidimensional data to two principal components, which together captured 87.540% of the total variance. The dynamic principal component trajectories, plotted from the reduced-dimension data for the unaged–short-term-aged–xenon-lamp-aged process, revealed that anti-aging agents sharing the same protection mechanism led to comparable rates of high- and low-temperature performance deterioration during xenon-lamp aging, whereas agents with different mechanisms resulted in distinctly different patterns of performance deterioration. In the critical xenon-lamp aging stage, the neat asphalt exhibited a trajectory vector change of ΔPC1 = 0.92 and ΔPC2 = 1.25, corresponding to an angle of 54°, reflecting a low-temperature degradation. By contrast, the physical shielding agents LDHs and OMMT produced much steeper trajectories with angles of approximately −80°, where ΔPC2 values rose to as high as 3.67 and 2.19 respectively despite modest reductions in overall aging. The reflective agent TiO₂ showed a more moderate angle of 84°, with ΔPC1 and ΔPC2 values of 0.16 and 1.45, indicating a slight retardation of high-temperature performance loss. Notably, the UV absorber UV326 maintained the same trajectory angle of 56° as the neat asphalt but with reduced magnitudes of ΔPC1 = 0.63 and ΔPC2 = 0.94, suggesting a balanced delay in aging without altering its relative progression. This study proposes a novel analytical framework for mechanism-based clustering analysis and the precise selection of anti-aging agents for asphalt. Full article

Food waste is one of the most pressing obstacles to sustainable development. Reducing food waste in schools and kindergartens constitutes an important component of sustainable waste management. To achieve this reduction, various interventions targeting food waste can deliver multiple benefits across environmental, social, and economic dimensions. Among these, behavioral “nudges” aim to steer consumer choices without restricting options. This study evaluated a novel nudging intervention in the canteens of two primary schools and one kindergarten, with the goal of reducing plate waste. The nudging intervention consisted of a simple, interactive installation designed to encourage children to reflect on their food consumption and portion choices. The installation was integrated into routine lunch service and it combined ball-based voting with visual prompts: the emptier the returned plate, the greater the voting weight for the pupil. Across all institutions the food waste level (soup and second dish combined) was significantly decreased during the nudging intervention: by 31% for primary school no. 84, 18% for school no. 1, and 33% for kindergarten no. 56, although part of this reduction was attributable to lower food production volumes. Plate waste for the second dish decreased in all the considered schools: by 10 g/meal (11%), 19 g/meal (22%), and 52 g/meal (51%), respectively. After the intervention a larger share of the second dish served was consumed than was left on the plates compared to the situation during the baseline monitoring. A shift from plate waste to unserved food, which was one of the goals of the study, could not be unambiguously confirmed. Overall, the new nudging installation appears effective. Substantial changes in food production complicate the possibility of determining the effects of the nudging intervention. Future research should maintain constant production levels across the baseline and intervention periods. In addition, pupils should be given maximum freedom to determine their portion sizes during the nudging intervention. The long-term effects of the nudging approach should also be evaluated. Full article

Transitioning to sustainable, plant-forward diets, such as the Planetary Health Diet is a global priority; however, the palatability gap remains a formidable barrier, as consumers often perceive low-sodium, plant-centric diets as sensory-deficient. While aromatic herbs could bridge this gap, the current literature rarely integrates their sensory, ecological, phytochemical, and cultural dimensions. This narrative review explores how Mediterranean aromatic plants indigenous to the Maltese Islands function as sensory and molecular catalysts to bridge this gap. Through a thematic synthesis (2005–2026) integrating ethnobotanical evidence with molecular nutrition and sensory science, the Maltese archipelago is examined as a small-island ecological model. Chronic abiotic stressors, including high salinity and intense solar exposure, induce phytochemical priming, significantly enhancing secondary metabolites like polyphenols and terpenoids. These compounds establish a folk–medicine bridge, where traditional culinary practices align with modern biochemical validation. These bioactives demonstrate a capacity to modulate the NF-κB inflammatory axis, mitigate systemic inflammaging, and support the gut–microbiome–brain axis. Furthermore, these aromatics serve as translational tools for EAT-Lancet 2025 targets by facilitating cross-modal sensory compensation for sodium reduction and improving nutrient bioaccessibility via the culinary entourage effect. The TASTE-MED framework positions culinary nutrition as a vital translational bridge, asserting that flavour is a prerequisite for dietary sustainability and aligning individual molecular resilience with broader planetary health goals. Full article

While geotechnical parameter determination is fundamental to foundation engineering, traditional approaches often suffer from data fragmentation and subjective safety assessments. This research introduces an integrated framework that synthesizes multivariable regression with the Effective Random Dimension (ERD) method to bridge the gap between raw laboratory indices and structural design. By analyzing datasets from the stable Suceava Moldavian Platform (68 samples) and the tectonized Subcarpathian Flysch (50 samples), the study demonstrates that granulometric fractions, moisture content, and carbonate content can predict consistency limits with high statistical fidelity, achieving R² = 0.98 for the Liquid Limit at Suceava and R² ≈ 0.90 for the Plasticity Index at Doftana. The novelty of the approach lies in the generation of continuous vertical profiles transformed into code-compliant characteristic values (X_k) via Taylor series linearization and the ERD framework. The derived characteristic interval for the Plasticity Index (58.66–70.15%) quantitatively demonstrates the reduction in hyper-conservative bias compared with discrete sampling. This methodology eliminates subjective judgment and ensures a mathematically rigorous transition to Eurocode 7 and NP 122:2010 standards, optimizing both safety and economic efficiency in variable geological strata. Full article

Background/Objectives: Chronic home oxygen therapy—long-term oxygen therapy (LTOT)—improves survival and quality of life in chronic respiratory failure when used ≥15 h/day, but adherence is frequently suboptimal and specific patient-reported outcome measures (PROMs) are scarce. To develop, validate and apply a specific PROM for patients on LTOT. Methods: A prospective observational cohort study was conducted at San Juan de Alicante University Hospital (April 2024–December 2025) following a four-stage process: conceptual framework definition and expert workshop, content validation and item reduction, cognitive interviews with pilot reliability testing (n = 25), and field application to 120 consecutive chronic LTOT users. The LTOT-PROM was designed to capture the patient-perceived impact attributable to LTOT during the previous 4 weeks. Internal consistency was assessed with Cronbach’s α and test–retest reproducibility with the intraclass correlation coefficient (ICC). Results: The final instrument comprises 15 scored items in two dimensions—Daily Activity (9 items) and Adverse Effects (6 items)—plus one ambulatory-only mobility item excluded from the total score. Cronbach’s α was 0.814 (95% CI 0.681–0.906) for Daily Activity, 0.743 (95% CI 0.548–0.872) for Adverse Effects and 0.808 (95% CI 0.677–0.902) for the total scale; total ICC(A,1) was 0.890 (95% CI 0.767–0.950). Among the 120 patients (62 men, 58 women; mean age 78 ± 13 years; mean therapy duration 40 ± 32 months), 68% reported reduced effort for daily activities, 66% reported a reduction in dyspnoea and 67% reported improved self-confidence; 49% reported morning airway dryness and 7% abandoned the equipment due to nasal dryness or rhinitis. Conclusions: The LTOT-PROM is a brief, reliable and reproducible oxygen-specific instrument for assessing the recent patient-perceived impact of LTOT in routine clinical practice. Further studies should evaluate structural validity, external validity and the relationship between LTOT-PROM scores and objective adherence measures. The construct was predefined as the patient-perceived impact attributable to LTOT during a standardised 4-week recall window, and cognitive interviews confirmed that respondents interpreted the items as experienced benefit/burden during that period rather than as week-to-week symptom change. Full article

Objectives: Local positioning systems (LPSs) used in indoor team sports generate a large number of external load variables, often exceeding practical monitoring capacity. The redundancy and overlap among these variables make it difficult to identify the most informative metrics for performance analysis and load management. This study aimed to reduce the dimensionality of external load variables derived from LPS data and to identify data-driven external-load observation profiles using principal component analysis and clustering techniques. Methods: A total of 188 observations from indoor team sports (basketball, handball, and futsal) were analyzed. Continuous external load variables were standardized and subjected to principal component analysis (PCA), with component retention based on a ≥90% cumulative explained variance threshold. K-means clustering was applied in both the full standardized feature space and the PCA-reduced space. The optimal number of clusters was determined using silhouette analysis and the elbow method. Agreement between clustering solutions was assessed using Adjusted Rand Index (ARI) and Normalized Mutual Information (NMI). Cluster characteristics were further examined using descriptive statistics and variable separation analysis. Results: The first two principal components explained 53.7% of the total variance, representing high-intensity external load and neuromuscular load dimensions, while 12 components were required to exceed 90% cumulative explained variance. Clustering analysis consistently identified three moderately separated clusters in both the full and PCA-reduced spaces. The PCA-based solution demonstrated improved separation (silhouette = 0.362) compared to the full-space solution (silhouette = 0.319). Agreement between clustering approaches was high (ARI = 0.981; NMI = 0.971), indicating that dimensionality reduction largely preserved the main clustering structure within the analyzed dataset. The most discriminative variables included jump load, acceleration load, metabolic power, and anaerobic activity distance. Conclusions: A large set of external load variables can be reduced into interpretable latent dimensions that support exploratory external-load profile identification. The combination of PCA and clustering provides an exploratory and structure-preserving framework for summarizing complex external-load datasets and identifying latent load dimensions. These findings may assist future monitoring strategies; however, the practical utility of the identified profiles requires prospective validation before implementation in training-load management. Full article

Background/Objectives: Major Depressive Disorder (MDD) is a leading cause of disability, yet physical therapy (PT) is underrepresented in hospital-based psychiatric care. While exercise is a known adjunctive treatment, specific evidence on functional, task-oriented interventions in acute settings remains scarce. This study explored changes in quality of life, depressive symptoms, pain, and self-efficacy in patients with MDD following a specialized hospital-based PT program focused on functional movement and autonomy. Methods: We conducted a prospective pre–post case series in the Short-Stay Psychiatric Unit of the Royo Villanova University Hospital (Zaragoza, Spain). We recruited seven adult patients with MDD via convenience sampling. The intervention consisted of a group-based PT program (two 45 min sessions/week during the hospital stay) utilizing task-oriented functional exercises targeting progressive strength, balance, and motor control designed to enhance self-efficacy through activities of daily living (ADLs), combined with health education. Outcomes included the EQ-5D-3L (quality of life), MADRS (depression), NRS (pain), GSE (self-efficacy), and GCPC-UN-ESU (satisfaction). Results: All seven participants (100%) exhibited a positive upward trend in self-perceived health status via the EQ-VAS (mean increase of 35 points). Six cases (85.7%) showed preliminary positive trends in the anxiety/depression dimension of the EQ-5D-3L, with the mean Single Index Value increasing from 0.310 to 0.683. Reductions in depressive symptom severity were observed in six participants, with several transitioning toward moderate or mild levels. Additionally, four patients reported descriptive reductions in pain intensity and showed favorable shifts in self-efficacy scores. Six participants expressed high satisfaction with the intervention. Conclusions: Integrating a hospital-based functional PT program with standard care may offer preliminary benefits for quality of life and reduce depressive symptoms in MDD patients. These findings suggest that task-oriented PT presents a feasible complementary approach for acute psychiatric admissions, although larger controlled trials are needed to confirm these exploratory results. Full article

Degraded grey desert soils are characterized by severe nutrient deficiencies and structural compaction. This study elucidated how biogas slurry drip irrigation regulates the micro-pore architecture, fertility, and macroscopic hydraulic properties. A one-year field experiment was conducted using a completely randomized design with three replications. The experimentation included three irrigation levels (W1: 70% W, W2: 85% W, and W3: 100% W, where W is full irrigation) and three slurry ratios (S1: 60% S, S2: 80% S, and S3: 100% S, where S is the annual nitrogen application rate of 93 kg ha⁻¹), with undisturbed (CK) and chemical fertilizer (CF) controls. Surface soil samples (0–20 cm) were analyzed based on treatment averages using scanning electron microscopy and the van Genuchten (vG) model. The results indicated that W3S2 increased the total porosity to a peak of 42.39% compared with the CK baseline of 25.25%, while expanding the mean pore diameter to 9.24 μm. Concurrently, the application minimized the morphological pore fragmentation, reducing the fractal dimension from 1.82 under CK to 1.61 under W3S3. Although the macroscopic porosity expanded, the effective saturated water content decreased. We hypothesize that this reduction is driven by partial micropore clogging by organic coatings. This mitigated the excessive near-saturation water retention and accelerated drainage, while significantly increasing the specific water capacity at 100–1000 kPa suctions to delay moisture depletion. W2S3 (85% W, 100% S) performed favorably with regard to soil fertility and water retention stability. The W2S3 treatment optimized soil fertility and water retention stability by achieving peak concentrations of 17.69 g kg⁻¹ for SOM and 1.31 g kg⁻¹ for TN. Path analysis suggested that physical microstructural traits dominate macroscopic hydraulic regulation. In conclusion, biogas slurry drip irrigation provides a sustainable framework to optimize structural and hydraulic resilience in dryland agriculture. Full article