Search Results (14,427)

The construction industry is a major consumer of raw materials and a significant contributor to environmental emissions. Life cycle assessment (LCA) using digital models is a valuable tool for conducting a science-based analysis to reduce these impacts. However, transferring data from environmental product declarations (EPDs) to BIM for the purpose of sustainability assessment requires significant resources for its interpretation and integration. This study is founded on a comprehensive review of the scientific literature and standards, an analysis of published digital EPDs, and a thorough evaluation of IFC (industry foundation classes), identifying twenty gaps for the automated incorporation of LCA data from construction products into BIM. The identified limitations were assessed using the digital model of a building pilot, applying simplifications to incorporate actual EPD data. This paper presents the identified barriers to the automated incorporation of digital EPDs into BIM, and proposes eleven concrete actions to improve IFC 4.3. While prior studies have analyzed the environmental data in IFC, this research is significant in two key areas. Firstly, it focuses on the direct machine interpretation of environmental information without human intervention. Secondly, it is intended to be directly applicable to a revision of the IFC standards. Full article

Nanotechnologies bring a rapid paradigm shift in hard and soft bone tissue regeneration (BTR) through unprecedented control over the nanoscale structures and chemistry of biocompatible materials to regenerate the intricate architecture and functional adaptability of bone. This review focuses on the transformative analyses and prospects of current and next-generation nanomaterials in designing bioactive bone scaffolds, emphasizing hierarchical architecture, mechanical resilience, and regenerative precision. Mainly, this review elucidated the innovative findings, new capabilities, unmet challenges, and possible future opportunities associated with biocompatible inorganic ceramics (e.g., phosphates, metallic oxides) and the United States Food and Drug Administration (USFDA) approved synthetic polymers, including their nanoscale structures. Furthermore, this review demonstrates the newly available approaches for achieving customized standard porosity, mechanical strengths, and accelerated bioactivity to construct an optimized nanomaterial-oriented scaffold. Numerous strategies including three-dimensional bioprinting, electro-spinning techniques and meticulous nanomaterials (NMs) fabrication are well established to achieve radical scientific precision in BTR engineering. The contemporary research is unceasingly decoding the pathways for spatial and temporal release of osteoinductive agents to enhance targeted therapy and prompt healing processes. Additionally, successful material design and integration of an osteoinductive and osteoconductive agents with the blend of contemporary technologies will bring radical success in this field. Furthermore, machine learning (ML) and artificial intelligence (AI) can further decode the current complexities of material design for BTR, notwithstanding the fact that these methods call for an in-depth understanding of bone composition, relationships and impacts on biochemical processes, distribution of stem cells on the matrix, and functionalization strategies of NMs for better scaffold development. Overall, this review integrated important technological progress with ethical considerations, aiming for a future where nanotechnology-facilitated bone regeneration is boosted by enhanced functionality, safety, inclusivity, and long-term environmental responsibility. Therefore, the assimilation of a specialized research design, while upholding ethical standards, will elucidate the challenge and questions we are presently encountering. Full article

Background/Objectives: Adult Spinal Deformity (ASD) is a pathologic malalignment of the spine that can lead to significant reductions in quality of life, functional limitations, and increased morbidity. While poor mental health is commonly observed among patients undergoing ASD surgery, its impact on surgical outcomes remains poorly understood. We conducted a systematic review and meta-analysis to examine the association between preoperative mental health and outcomes following surgical correction for ASD. Methods: A comprehensive search of MEDLINE, Embase, Web of Science, and Scopus was performed from inception to April 2025 to identify studies investigating the relationship between preoperative mental health and postoperative health-related quality of life outcomes or complications. Data was pooled using a restricted maximum likelihood (REML) random-effects model. Heterogeneity was assessed using Cochran’s Q statistic, and between-study variance was reported as τ². Study quality was assessed with the Newcastle–Ottawa Scale, and risk of bias was evaluated using the ROBINS-I tool. Results: Twenty-four studies comprising a total of 248,427 patients met inclusion criteria. In pooled analyses, patients with poor preoperative mental health showed comparable improvements in health-related quality of life measures after surgery (standardized mean difference [SMD] −0.04, 95% CI −0.30 to 0.22; I² = 91.5%, τ² = 0.42) and in pain scores (SMD −0.15, 95% CI −0.42 to 0.11; I² = 71.8%, τ² = 0.09). However, patients with poor mental health had significantly higher odds of postoperative complications (odds ratio [OR] 1.44, 95% CI 1.23 to 1.67; I² = 97.4%, τ² = 0.08). These patients also demonstrated worse preoperative disease severity (SMD –0.94, 95% CI −1.41 to −0.47; I² = 95.5%, τ² = 1.64) and worse postoperative disease severity (SMD –0.34, 95% CI −0.44 to −0.25; I² = 48.9%, τ² = 0.03). Conclusions: While patients with poor preoperative mental health have a greater disease severity both before and after ASD surgery, they appear to experience comparable benefits from surgical intervention compared to those without. Recognizing and managing mental health may be useful in preoperative management of ASD patients. Further prospective studies to further elucidate these associations are necessary. Full article

Degradable fluorescent sensors present a promising portable approach for heavy metal ion detection, aiming to prevent secondary environmental pollution. Additionally, the excessive intake of ferric ions (Fe³⁺), an essential trace element for human health, poses critical health risks that urgently require effective monitoring. In this study, we developed a thermally degradable fluorescent hydrogel sensor (Eu-CDs@DPPG) based on europium-doped carbon dots (Eu-CDs). The Eu-CDs, synthesized via a hydrothermal method, exhibited selective fluorescence quenching by Fe³⁺ through the inner filter effect (IFE). Embedding Eu-CDs into the hydrogel significantly enhanced their stability and dispersibility in aqueous environments, effectively resolving issues related to aggregation and matrix interference in traditional sensing methods. The developed sensor demonstrated a broad linear detection range (0–2.5 µM), an extremely low detection limit (1.25 nM), and rapid response (<40 s). Furthermore, a smartphone-assisted LAB color analysis allowed portable, visual quantification of Fe³⁺ with a practical LOD of 6.588 nM. Importantly, the hydrogel was thermally degradable at 80 °C, thus minimizing environmental impact. The sensor’s practical applicability was validated by accurately detecting Fe³⁺ in spinach and human urine samples, achieving recoveries of 98.7–108.0% with low relative standard deviations. This work provides an efficient, portable, and sustainable sensing platform that overcomes the limitations inherent in conventional analytical methods. Full article

With the advance of digital transformation, the assessment of the environmental impact of digital tools and technologies grows more relevant. Considering the inflated expectations of environmental responsibility in higher education, this study analyses how websites of Polish universities conform to sustainable web design criteria. The sustainability audit employed a methodology encompassing carbon emissions measurement, technical website analysis, and SEO evaluation. The author analysed 63 websites of public universities in Poland using seven independent audit tools, including an original AI Custom GPT agent preconfigured in the ChatGPT ecosystem. The results revealed a substantial differentiation in CO₂ emissions and website optimisation, with an average EcoImpact Score of 66.41/100. Nearly every fourth website exhibited a significant carbon footprint and excessive component sizes, which indicates poor asset optimisation and energy-intensive design techniques. The measurements exposed considerable variability in emission intensities and resource intensity among the university websites, suggesting the need for standardised digital sustainability practices. Regulations on the carbon footprint of public institutions’ websites and mobile applications could become vital strategic components for digital climate neutrality. Promoting green hosting, “Green SEO” practices, and sustainability audits could help mitigate the environmental impact of digital technologies and advance sustainable design standards for the public sector. The proposed auditing methodology can effectively support the institutional transition towards sustainable management of digital infrastructure by integrating technical, sustainability, and organisational aspects. Full article

Privacy-sensitive electricity scene classification requires robust models under data localization constraints, making federated learning (FL) a suitable framework. Existing FL frameworks face two critical challenges in multi-label electricity scene classification: (1) Label correlations and their strengths significantly impact classification performance. (2) Electricity scene data and labels show distributional inconsistencies across regions. However, current FL frameworks lack explicit modeling of label correlation strengths, and locally trained regional models naturally capture these differences, leading to regional differences in their model parameters. In this scenario, the server’s standard single-stage aggregation often over-averages the global model’s parameters, reducing its discriminative ability. To address these issues, we propose FMMAN, a federated multi-stage attention neural network for multi-label electricity scene classification. The main contributions of this FMMAN lie in label correlation learning and the stepwise model aggregation. It splits the client–server interaction into multiple stages: (1) Clients train models locally to encode features and label correlation strengths after receiving the server’s initial model. (2) The server clusters these locally trained models into K groups to ensure that models within a group have more consistent parameters and generates K prototype models via intra-group aggregation to reduce over-averaging. The K models are then distributed back to the clients. (3) Clients refine their models using the K prototypes with contrastive group-specific consistency regularization to further mitigate over-averaging, and sends the refined model back to the server. (4) Finally, the server aggregates the models into a global model. Experiments on multi-label benchmarks verify that FMMAN outperforms baseline methods. Full article

The cosmetic industry is growing at an impressive rate worldwide. In the cosmetic field, natural-origin ingredients represent the new frontier in this industry. Among the main components of cosmetics, lipids, emulsifiers, rheological modifiers, preservatives, colorants, and antioxidants can be found. These compounds form emulsions, which are among the main cosmetic formulations. An important aspect in this regard is the evaluation of emulsions’ stability over time and emulsions’ production methodology. In this paper, a comparison is made between two emulsion production technologies, the Standard and the “One-Pot” methods, through the characterization of the raw material ABWAX^® Revomul, a multifunctional wax for cosmetic use which consists of a low-melting structuring wax of vegetal origin (Rhus wax) and a natural emulsifier (Polyglyceril-3 Stearate). First, we evaluated the affinity between the wax raw materials and emollients of different chemical nature; then, we analyzed the impact of the production method on the emulsions to identify similarities and differences. ABWAX^® Revomul demonstrated a high level of effectiveness in regard to stabilizing water-in-oil emulsions. This study suggests that from an industrial point of view, the application of the two procedures allows products with different characteristics to be obtained, consequently allowing a specific method to be chosen to obtain the desired product. Full article

Background and Objectives: Spinopelvic alignment may affect the outcomes of total hip arthroplasty (THA), with pelvic version influencing the risk of mechanical complications occurring after surgery. On the other hand, THA surgery itself may contribute to the modification of pelvis version. The sacro-femoro-pubic (SFP) angle is measured on anteroposterior (AP) radiographs of the pelvis in a supine position, and is used to estimate pelvic tilt (PT), representative of pelvic version, which requires lateral views of the sacrum for its calculation; however, these X rays are not routinely performed in the preoperative setting of hip surgery. This study aims to analyze how THA determines changes in the pelvic version of operated patients; the SFP angle will be used to assess pelvic version on standard AP radiographs. Materials and Methods: This retrospective study included 182 consecutive patients undergoing THA for unilateral primary degenerative hip osteoarthritis (HOA-study group, n = 104) or femoral neck fracture (FNF-control group, n = 78) at the author’s institution. The SFP angle was measured on AP pelvic radiographs of the non-replaced hip preoperatively, postoperatively, and at the last follow-up. PT values were derived from SFP angles. Pre- and postoperative PT and its variations ΔPT were assessed. Study groups were compared in terms of native and postoperative variations of pelvic version. Results: The average absolute value of ΔPT was 2.99° ± 3.07° in the HOA group and 3.57° ± 2.92° in FNF group. There was no significant overall difference in preoperative or postoperative PT values between groups. In both groups, THA surgery led to a certain improvement, still not significant, in pelvic orientation, with FNF patients presenting a greater tendency toward retroversion. No significant differences in complication rates were found comparing patients with different pelvic orientations. Conclusions: THA can lead to a “normalization” of pelvic version in a certain number of patients with preoperative anteversion or retroversion. Although statistically non-significant, this observation may have clinical implications for spinopelvic balance and could support prioritizing THA in patients with concurrent spinal disease. Further research is needed to confirm these findings and to evaluate the long-term impact of THA on spinopelvic alignment. Full article

Callistemon citrinus has shown antioxidant and anti-inflammatory properties in certain tissues. However, its impact on the brain remains unproven. This study investigates the effect of C. citrinus extract and phytosomes on the oxidative status of the brains of rats fed a high-fat–fructose diet (HFD). Fifty-four male Wistar rats were randomly divided into nine groups (n = 6). Groups 1, 2, and 3 received a standard chow diet; Group 2 also received the vehicle, and Group 3 was supplemented with C. citrinus extract (200 mg/kg). Groups 4, 5, 6, 7, 8, and 9 received a high-fat diet (HFD). Additionally, groups 5, 6, 7, 8, and 9 were supplemented with orlistat at 5 mg/kg, C. citrinus extract at 200 mg/kg, and phytosomes loaded with C. citrinus at doses of 50, 100, and 200 mg/kg, respectively. Administration was oral for 16 weeks. Antioxidant enzymes, biomarkers of oxidative stress, and fatty acid content in the brain were determined. A parallel artificial membrane permeability assay (PAMPA) was employed to identify compounds that can cross the intestinal and blood–brain barriers. The HFD group (group 4) increased body weight and adipose tissue, unlike the other groups. The brain fatty acid profile showed slight variations in all of the groups. On the other hand, group 4 showed a decrease in the activities of antioxidant enzymes SOD, CAT, and PON. It reduced GSH level, while increasing GPx activity as well as MDA, 4-HNE, and AOPP levels. C. citrinus extract and phytosomes restore the antioxidant enzyme activities and mitigate oxidative stress in the brain. C. citrinus modulates oxidative stress in brain tissue through 1.8-cineole and α-terpineol, which possess antioxidant and anti-inflammatory properties. Full article

The safety of lithium-ion batteries during transportation is critically important. However, current standards exhibit limitations, as their environmental testing parameter thresholds fail to fully encompass actual transportation conditions. To enhance both safety and standard applicability, in this study, we focused on four representative environmental conditions: temperature, vibration, shock, and low atmospheric pressure. Field measurements were conducted across road, rail, and air transport modes using a self-developed data acquisition system based on the NearLink communication technology. The measured data were then compared with the threshold values defined in current international and national standards. The results reveal that certain measured values exceeded the upper limits prescribed by existing standards, indicating limitations in their applicability under extreme transport conditions. Based on these findings, we propose revised testing parameters that better reflect actual transport risks, including a temperature cycling range of 72 ± 2 °C (high) and −40 ± 2 °C (low), a shock acceleration limit of 50 gn, adjusted peak frequencies in the vibration PSD profile, and a minimum pressure threshold of 11.6 kPa. These results provide a scientific basis for optimising safety standards and improving the safety of lithium-ion battery transportation. Full article

Some of nuclear power’s primary detractors are the unique environmental challenges and impacts of radioactive wastes generated during fuel cycle operations. Key benefits of spent fuel reprocessing (SFR) are reductions in primary high active waste (HAW) masses, volumes, and lengths of radiotoxicity at the expense of secondary waste generation and high capital and operational costs. By employing advanced waste management and resource recovery concepts in SFR beyond the existing standard PUREX process, such as minor actinide and fission product partitioning, these challenges could be mitigated, alongside further reductions in HAW volumes, masses, and duration of radiotoxicity. This work assesses various current and proposed SFR and fuel cycle options as base cases, with further options for fission product partitioning of the high heat radionuclides (HHRs), rare earths, and platinum group metals investigated. A focus on primary waste outputs and the additional energy that could be generated by the reprocessing of high-burnup PWR fuel from Gen III(+) reactors using a simple fuel cycle model is used; the effects of 5- and 10-year spent fuel cooling times before reprocessing are explored. We demonstrate that longer cooling times are preferable in all cases except where short-lived isotope recovery may be desired, and that the partitioning of high-heat fission products (Cs and Sr) could allow for the reclassification of traditional raffinates to intermediate level waste. Highly active waste volume reductions approaching 50% vs. PUREX raffinate could be achieved in single-target partitioning of the inactive and low-activity rare earth elements, and the need for geological disposal could potentially be mitigated completely if HHRs are separated and utilised. Full article

The study investigates the contribution of technology (TECH), quantified by Internet penetration, in influencing tourism performance (TP) among the top ten touristic nations in Europe: France, Spain, Italy, Turkey, the United Kingdom, Germany, Greece, Austria, Portugal, and the Netherlands. Using panel data from 2000–2022, the study includes additional structural controls like environment quality, gross domestic production (GDP) per capita, exchange rate (ER), and safety index (SI). The Method of Moments Quantile Regression (MMQR) is employed to capture heterogeneous effects at different levels of TP, and Driscoll–Kraay standard error (DKSE) correction is employed to make the analysis robust against autocorrelation as well as cross-sectional dependence. Spectral–Granger causality tests are also conducted to check short- and long-run dynamics in the relationships. Empirical results are that TECH and SI are important in TP at all quantiles, but with stronger effects for lower-performing countries. Environmental quality (EQ) and GDP per capita (GDPPC) exert increasing impacts at upper quantiles, suggesting their importance in sustaining high-level tourism economies. ER effects are limited and primarily short-term. The findings highlight the need for integrated digital, environmental, and economic policies to achieve sustainable tourism development. The paper contributes to tourism research by providing a comprehensive, frequency-sensitive, and distributional analysis of macroeconomic determinants of tourism in highly developed European tourist destinations. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

The application of extended reality (XR) in design education has grown substantially; however, empirical evidence on its educational benefits remains limited. This two-year study examines the impact of incorporating a virtual reality (VR) learning module into undergraduate landscape architecture (LA) construction courses, focusing on brick masonry instruction. A conventional learning sequence—lecture, sketching, CAD, and 3D modeling—was supplemented with an immersive VR experience developed using Unreal Engine 5 and deployed on Meta Quest devices. In Year 1, we piloted a preliminary version of the module with landscape architecture students (n = 15), and data on implementation feasibility and student perception were collected. In Year 2, we refined the learning module and implemented it with a new cohort (n = 16) using standardized VR evaluation metrics, knowledge retention tests, and self-efficacy surveys. The findings suggest that when sequenced after a theoretical introduction, VR serves as a pedagogical bridge between abstract construction principles and physical implementation. Moreover, the VR module enhanced student engagement and self-efficacy by offering experiential learning with immediate feedback. The findings highlight the need for intentional design, institutional support, and the continued development of tactile, collaborative simulations. Full article

Drought disturbances are becoming more frequent with global warming. Accurately assessing the regulatory effect of drought on vegetation phenology is key to understanding terrestrial ecosystem response mechanisms in the context of climate change. Previous studies on cumulative and lagged effects of drought on vegetation growth have mostly focused on a single vegetation type or the overall vegetation NDVI, overlooking the possible influence of different adaptation strategies of different vegetation types and differences in drought effects on different phenological nodes. This study investigates the cumulative and lagged effects of drought on vegetation phenology across a region of East Asia from 2001 to 2020 using NDVI data and the Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the start of growing season (SOS) and end of growing season (EOS) responses to drought across four vegetation types: deciduous needleleaf forests (DNFs), deciduous broadleaf forests (DBFs), shrublands, and grasslands. Results reveal contrasting phenological responses: drought delayed SOS in grasslands through a “drought escape” strategy but advanced SOS in forests and shrublands. All vegetation types showed earlier EOS under drought stress. Cumulative drought effects were strongest on DNFs, SOS, and shrubland SOS, while lagged effects dominated DBFs and grassland SOS. Drought impacts varied with moisture conditions: they were stronger in dry regions for SOS but more pronounced in humid areas for EOS. By confirming that drought effects vary by vegetation type and phenology node, these findings enhance our understanding of vegetation adaptation strategies and ecosystem responses to climate stress. Full article