Search Results (12,482)

The European Environment Agency believes that circular economy strategies could substantially contribute to CO₂ emissions reduction. Therefore, it is necessary that the agro-industrial sector identifies sustainable technologies for side-stream management. The scope of this review was to compare the sustainability of available biological treatments for by-product biomasses and organic waste. A total of 147 studies, all Life Cycle Assessments (LCAs) and Techno-Economic Analyses (TEAs), were selected through PRISMA-ScR methodology, on Scopus and Web of Science, and were bibliographically mapped on VOSviewer (Version 1.6.20) Anaerobic digestion and integrated energy recovery systems were found to be the most environmentally robust options. Integrated biorefineries and multi-product systems have emerged as the highest long-term sustainability potential, especially when process integration and co-product recovery were also implemented. Importantly, the most sustainable systems were found to have required considerable start-up investments. Thus, sustainable deployment of biological treatment technologies was clearly dependent on time-consistent policy frameworks that have been fertile to capital-intensive infrastructures via incentives and fiscal measures and that have embraced circular bioeconomy systems. Finally, this paper has demonstrated that the sustainability of biological treatments has resulted from optimal relationships between biomass characteristics, system boundaries, process integration, and market value of co-product, while no single technology has been sufficient in isolation. Full article

Produced-water (PW) management in the Permian Basin faces tightening injection constraints, induced seismicity concerns, and volatile saltwater disposal (SWD) costs. At the same time, chemistry-rich PW contains dissolved constituents (e.g., Li, B, and Sr) that may be valorized if SWD recovery performance and market conditions support favorable techno-economics. Here, we develop an integrated decision-support framework that couples (i) chemistry-informed surrogate models for unit process performance (recovery, effluent quality, and energy/chemical intensity) with (ii) a network-based allocation model that routes PW from sources through pretreatment, optional treatment and mineral-recovery modules (e.g., desalination and direct lithium extraction), and end-use nodes (beneficial reuse, hydraulic fracturing reuse, mineral recovery/valorization, or Class II disposal). This is a screening-level demonstration using publicly available chemistry percentiles and representative pilot-reported performance windows; it is not a site-specific facility design or a bankable TEA for a particular operator. The optimization is posed as a tri-objective problem—to maximize expected net present value, minimize SWD, and minimize an injection-risk indicator R—subject to mass balance, capacity, quality, and regulatory constraints. Uncertainty in commodity prices, recovery fractions, and operating costs is propagated via Monte Carlo scenario sampling, yielding PARETO-efficient portfolios that quantify trade-offs between profitability and risk mitigation. Using the PW chemistry percentiles reported by the Texas Produced Water Consortium for the Delaware and Midland Basins, we derive screening-level break-even lithium concentrations and illustrate how lithium-carbonate-equivalent price and recovery govern the extent to which mineral revenue can offset SWD expenditures. Comparative brine benchmarks (Smackover Formation and Salton Sea geothermal systems) contextualize the Permian’s generally lower-Li PW and highlight transferability of the workflow across brine types. The proposed framework provides a transparent, extensible basis for design matrix planning under evolving injection limits, enabling risk-aware PW management strategies that reduce disposal dependence while improving water resilience. Full article

This work explores the effect of nitrogen ion implantation on the wettability of the cemented tungsten carbide–cobalt (WC–Co) tool surface used for wood-based panel machining. Nitrogen ions with an energy of 50 keV and a fluence of 1 × 10¹⁷ and 5 × 10¹⁷ cm⁻² were implanted into the surface layer of commercially available WC–Co indexable knives using the implanter without a mass-separated ion beam. The wettability was characterized by a contact angle instrument. The implantation of nitrogen ions into WC–Co tools caused a statistically significant and practically useful decrease in the contact angle. This obtained effect was dependent on the fluence of the implanted ions, and it changed over time. This effect may also explain the transfer from the workpiece and the surface capture of carbon atoms in the secondary structure formed during the machining of wood materials on tools with ion implantation. On the other hand, the layer of carbon on the surface of the tool formed during machining explains the reduction in friction coefficient observed in experiments and the increase in tool life during cutting. Full article

The integration of truck platooning and electrification presents a promising avenue for improving operational efficiency and environmental sustainability in freight transportation. Realizing the energy and cost saving as well as emission reduction benefits requires a holistic design of truck routing, scheduling, and platooning strategies that account for practical operational constraints. This study investigates the integrated planning problem of routing, scheduling, and platooning for a mixed fleet of conventional trucks (CTs) and electric trucks (ETs), referred to as mixed fleet truck platooning (MFTP) problem. The MFTP incorporates charging scheduling and key operational factors, such as platooning leader–follower positioning under the battery constraints of ETs, charging station availability and capacity, and the positional configuration of trucks within a platoon. The objective is to minimize the total operation cost of the MFTP system, including charging cost, fuel cost, travel labor cost, charging labor cost, and platoon formation labor cost, while ensuring timely arrivals across multiple origin–destination (OD) pairs. The proposed MFTP is formulated as a novel mixed-integer linear program (MILP). Extensive numerical experiments on the simplified Illinois interstate highway network are conducted to examine the effectiveness and efficiency of the proposed model. Numerical results show that incorporating platooning reduces the total operational cost by 7.6% relative to the non-platooning scenario. The findings also shed some light on planning mixed fleets of CTs and ETs with platooning, offering valuable managerial insights for decision-makers. Full article

Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, currently represent one of the major challenges in contemporary medicine and geriatrics. Progressive degeneration of the nervous system affects not only patients’ physical functioning but also their psychosocial well-being, often leading to social isolation and disruption of interpersonal relationships. These processes are most strongly associated with individuals over 65 years of age, in whom metabolic syndrome is frequently diagnosed and constitutes a significant factor predisposing them to the exacerbation of neuropathological changes. This review analyzes the role of selected vitamins in modulating the course of neurodegenerative disorders, with particular emphasis on their neuroprotective potential. Specific attention is given to their involvement in antioxidant defense mechanisms, regulation of inflammatory pathways, prevention of abnormal protein aggregation, participation in neurotransmitter synthesis, and support of mitochondrial function and cellular energy metabolism. The review also considers key interactions between vitamins and coenzyme Q10, which synergistically enhance neuroprotective mechanisms. Deficiencies in certain vitamins may exacerbate oxidative stress, impair synaptic transmission, and intensify neuroinflammatory responses, thereby contributing to disease progression. The study analyzes the available data on therapeutic doses of vitamins and compares them with the recommended dietary intake and the upper tolerable intake levels (UL). The available evidence suggests that personalized vitamin supplementation, when integrated with a well-balanced and nutrient-dense diet, may constitute a valuable adjunctive therapeutic strategy. Such an approach may help attenuate disease progression, support neuronal integrity, and improve functional outcomes. Ultimately, targeted nutritional interventions may enhance overall well-being and quality of life in patients affected by neurodegenerative diseases. Full article

Anchored in the strategic framework of Vision 2030, the research departs from anecdotal or survey-based approaches by exclusively leveraging publicly available, auditable data from national ministries, international university rankings, and scholarly publication databases. An original Integrated Green Transformation Framework (IGTF) is operationalized through fixed-effects regression modeling, longitudinal policy document analysis, and cross-sectional benchmarking of sustainability performance indicators across twelve Saudi universities. The findings demonstrate a statistically significant and temporally coherent association between national green policy milestones, such as the Saudi Green Initiative and the National Renewable Energy Program 2018, and measurable improvements in university-level sustainability strategies, operational efficiency, and research output. The average share of renewable energy utilization across sampled institutions increased from 2.1 percent in 2016 to 18.7 percent in 2023, representing substantial progress yet remaining below the Vision 2030 national target of 50%, while per-student water consumption declined by 34 percent over the same period. Scholarly publications in green economy domains rose by 638 percent, with a strong positive correlation (r = 0.76, p < 0.001) between research intensity and curriculum integration of sustainability content. Despite these advances, persistent disparities exist in resource allocation and implementation depth, particularly between historically endowed universities and newer regional institutions, highlighting a “sustainability divide” that requires targeted policy intervention. Full article

The deployment of distributed renewable energy systems at the neighborhood scale is a key lever for urban decarbonization. In Europe, the regulatory framework now enables collective self-consumption, allowing multiple end-users to share locally produced energy. However, the complexity and early-stage uncertainties of such projects, especially in new district development, pose challenges for feasibility assessment and investor confidence. This study proposes a method to identify the impact of numerous technical, economic, and social parameters that may affect the feasibility of a project and that are uncertain at the early design stage, across multiple key performance indicators, thus addressing the concerns of various stakeholders. A key objective is to provide an integrated method applicable during the early stages of district development, when the integration of a collective self-consumption scheme is under consideration. The developed tools and methods are compatible with the available data at this stage and provide a basis for multi-criteria analysis. The simulation workflow was built around URBANopt and enhanced with probabilistic occupancy modeling, energy sharing mechanisms, and financial analysis modules. It was further complemented by sensitivity and risk analysis layers. The method was applied to a pre-design case study, illustrating how key design and operational uncertainties influence project viability. The results showed that despite the uncertainties on a wide array of parameters, reliable risk assessment per KPI could be performed on only a handful of parameters, which were identified through a sensitivity analysis using the Morris screening method. Full article

In ground-source heat-pump (GSHP) systems equipped with a single U-tube borehole heat exchanger (BHE), the heat-carrier fluid in the return leg may release heat to the surrounding ground in the shallow part of the borehole. From a fluid energy balance perspective, this is an exothermic process; however, it is detrimental during heating operation: It lowers the effective source temperature available to the heat pump and therefore degrades the overall coefficient of performance (COP). This study proposes a measurement-driven procedure to determine the exothermic transition depth $z_{\uparrow }^{*}$ from temperature profiles recorded at multiple depths along the ascending (return) pipe. The borehole is discretized into axial segments and, assuming a constant mass flow rate, the linear heat-exchange rate is estimated from the segment-wise enthalpy change. Time integration yields the segment-wise net energy exchange $Q_{\uparrow ,i}$, which is then classified as exothermic or endothermic using an uncertainty-based threshold derived from the standard uncertainty of the temperature sensors. The exothermic transition depth $z_{\uparrow }^{*}$ is defined as the first statistically stable sign change in the integrated segment energy (from exothermic to endothermic) and is obtained by linear interpolation between adjacent segment centres. By summing the exothermic energy exchange and the corresponding average loss power, an equivalent change in source-side outlet temperature $∆T_{out}$ is estimated and interpreted in terms of COP impact using a Carnot-scaled surrogate model. For two representative operating conditions, $z_{\uparrow }^{*}$ was found at $31.17 \mathrm{m}$ and $24.01 \mathrm{m}$, respectively, while the average exothermic loss power remained approximately 0.48 kW. The estimated $∆T_{out}$ ranged from $0.52$ to $0.75 \mathrm{K}$, corresponding to a diagnostic COP improvement if this parasitic exothermic exchange could be mitigated. The present results should therefore be interpreted as a case study-based demonstration of the method on one instrumented borehole rather than as a universal quantitative prediction for other sites or borehole fields. Full article

Extracellular vesicles (EVs), particularly exosomes, have emerged as critical mediators of intercellular communication, yet the metabolite fraction of their cargo remains substantially underexplored relative to proteins and nucleic acids. This review synthesizes current knowledge on the exosomal metabolome as a functionally distinct intercellular signaling system with unique biophysical properties. We review the mechanisms proposed to govern metabolite encapsulation into exosomes, encompassing membrane transporter involvement, lipid raft partitioning, and binding to luminal proteins, and discuss the unresolved question of whether metabolite loading is selective or stochastic. Critically, we present a quantitative framework evaluating whether delivered metabolite quantities are sufficient to alter recipient cell metabolic pools, distinguishing receptor-mediated signaling from bulk substrate delivery. We also address methodological considerations including contamination artifacts and isolation-method biases that complicate interpretation of EV metabolomics data. Exosomal metabolites are reviewed across four functional categories: energy substrates (ATP, lactate, amino acids), signaling molecules (TCA cycle intermediates, eicosanoids, nucleotides), redox cofactors and antioxidants (NADH, glutathione), and oncometabolites. For each category, available evidence is critically appraised, distinguishing metabolites with direct mass spectrometric detection from those whose roles are inferred from parent-cell biology. The review examines the roles of exosomal metabolites in tumor-stroma metabolic symbiosis, immunometabolic regulation, inter-organ crosstalk in metabolic diseases including type 2 diabetes and non-alcoholic fatty liver disease, cancer metastasis, viral infections, and immune evasion. A quantitative framework is discussed to evaluate whether delivered metabolite quantities are sufficient to alter recipient cell metabolic pools, distinguishing receptor-mediated signaling from bulk substrate delivery. Technical challenges in exosomal metabolomics are reviewed, including the impact of isolation method on data quality, contamination artifacts, and current standardization gaps. Therapeutic implications of exosomal metabolite signaling are discussed, encompassing metabolite-loaded exosomes as therapeutic vehicles and exosomal metabolite loading as a pharmacological target. Integration of single-vesicle technologies with systems biology approaches is highlighted as a promising direction for advancing this field toward precision medicine applications in oncological and metabolic disorders. Full article

Decarbonizing energy production is critical to slowing the effects of climate change and furthering global sustainability. Progress is often gauged via carbon dioxide (CO₂) emissions; however, sources of CO₂ vary beyond combustion, presenting a significant challenge to accurate tracking due to these various sources and sinks and the ubiquitous nature of CO₂ in the atmosphere. Nitrogen oxide (NO_X) emissions have previously been proposed as a surrogate for tracking sustainability, as they are primarily released from combustion processes. Facility-level data from Canada’s National Pollutant Release Inventory and Greenhouse Gas Reporting Program over a six-year period is used to assess the correlation between NO_X and CO₂ emissions from integrated facilities across Canada. Combustion-related CO₂ emissions accounting for approximately 94% of Canadian industrial emissions are examined, targeting eleven industries which together encompass over 90% of combustion emissions. Multiple linear regressions (MLRs) on each industry correlating NO_X, CO₂, and the inventory methods used (i.e., emission factors (EFs), source monitoring, mass balance, engineering estimates, and speciation) show R² values ranging from 0.81 to 0.96 for all but one industry. Several industries indicate that the methods used to calculate emissions influence the correlation of CO₂ to NO_X, highlighting issues in the current inventory techniques. The NO_X-to-CO₂ ratios calculated for the integrated facilities are similar to the ratios of the published main process-level EFs for NO_X to CO₂ (where available). These MLR models on NO_X could be used to predict CO₂ emissions with relative ease and accuracy in other jurisdictions, thereby simplifying large-scale emission inventory compilation while tracking sustainability. Full article

Climate change (CC) is widely recognized as a major human concern, affecting society across all aspects and activities. Among various economic sectors, aviation is one of the most affected due to its exposure to adverse weather events. Consequently, adaptation and mitigation actions are becoming increasingly important to reduce the negative effects of CC-driven extreme weather events on aviation operations. In this study, we analyzed 30 years of historical aerodrome meteorological routine reports (METARs) from several major Italian airports to assess multi-decadal changes in aviation weather-related hazards, based on observational evidence such as convection, visibility, and snow and freezing precipitation. Furthermore, we examined the ERA5 reanalysis dataset to assess potential anomalies in the synoptic circulation over the Euro-Mediterranean region that may drive fluctuations in local airport climatology. Our results reveal relevant trends for the considered aviation-related weather hazards, while also indicating meaningful links to variations in local and synoptic patterns. The observed increases in 500 hPa geopotential height, 850 hPa temperature, and convective available potential energy (CAPE) lead to changes in the climatology of the airports considered, including a general enhancement of thermoconvective phenomena, a reduction in events associated with synoptic-scale disturbances, an overall decrease in snowfall, and contrasting trends in fog occurrence depending on local factors. Full article

Objectives: Focal therapy (FT) is increasingly employed in selected patients with localized prostate cancer (PCa), aiming to balance oncologic control with preservation of urinary and sexual function. Among the available energy sources, prostate gland cryoablation (PGC) and high-intensity focused ultrasound (HIFU) are the most widely adopted techniques. However, comparative outcome data remain limited, and standardized composite endpoints are still lacking in this domain. Methods: We conducted a prospective, single-center study on 163 consecutive patients treated with FT, either HIFU (n = 49) or PGC (n = 114), for clinically localized PCa between 2019 and 2024. The primary aim was to compare baseline, perioperative, oncologic, and functional outcomes at 1-year follow-up. The secondary objective was to identify predictors of trifecta achievement, defined as: (1) absence of treatment failure; (2) urinary continence (no pads or one safety pad/day); and (3) recovery of erectile function comparable to baseline. Results: HIFU was associated with shorter operative time (p = 0.04) but required longer catheterization (p < 0.001). Compared with HIFU, primary whole-gland cryoablation (PGC) showed a higher overall complication rate (p < 0.001), mostly grade I–II events. Median follow-up was shorter for HIFU (12 vs. 23 months, p < 0.001). Further, 1-year treatment failure occurred in 8.1% of HIFU cases and 8.7% of PGC cases (p = 0.96), although failure-free survival was comparable between groups (p = 0.89). Functional outcomes were similar, with no significant differences in continence or potency recovery, and trifecta rates were 38.9% (HIFU) vs. 37.4% (PGC; p = 0.355). On multivariable analysis, hypertension, lower PSA, higher baseline erectile function, and unilateral ablation independently predicted trifecta achievement. Conclusions: In this prospective comparison between HIFU and PGC, we observed similar trifecta achievement rates, with no significant differences in continence or erectile function recovery at 1 year. Although treatment failure was slightly more frequent after HIFU, overall outcomes support the functional safety and oncologic feasibility of both approaches in selected patients. These findings suggest that adopting a standardized composite endpoint may be clinically useful, even if further refinement and validation are still needed to capture the specific goals and nuances of focal therapy. Full article

The rapid growth of low-altitude air traffic demands airspace evaluation frameworks that are scalable, flexible, and efficient. However, existing airspace partitioning strategies, primarily designed for sparse, long-distance civil aviation, are ill-suited to the dense and complex low-altitude environment. Moreover, the heterogeneous nature of low-altitude conditions cannot be adequately captured. To address this challenge, we propose a novel low-altitude airspace evaluation framework centered on a hierarchical voxel-based partitioning strategy. This strategy explicitly accommodates the diverse operational requirements of drones across different airspace layers. We couple this with an efficient multi-resolution airspace unit encoding mechanism that dynamically aggregates and evaluates airspace availability. To demonstrate the practical utility of our framework, we further develop an energy-aware, multi-scale route-planning algorithm that operates seamlessly across the hierarchical representation. Simulation results show that our method significantly improves computational efficiency in airspace evaluation, while the proposed planner achieves higher energy efficiency compared to conventional approaches like A*. Full article

Accurate and stable acquisition of the spatial distribution of soybean planting areas is essential for supporting precision agricultural monitoring and ensuring food security. However, crop remote-sensing mapping for specific regions still faces critical data bottlenecks: high-precision, large-scale pixel-level annotation is costly, resulting in scarce available labeled samples that make it difficult to construct large-scale training datasets. Although parameter-intensive models such as FCN and SegNet can achieve sufficient end-to-end training on large-scale public remote sensing datasets like LoveDA, when directly applied to the data-limited dataset in this study area, the models are prone to overfitting, leading to a significant decline in generalization ability. To address these issues, this study proposes a lightweight U-shaped semantic segmentation model, SimSDRU-Net. The model utilizes a pre-trained VGG-16 backbone to extract shallow texture and deep semantic features. The pre-trained weights mitigate the impact of overfitting in data-limited settings. In the decoding stage, a parameter-free lightweight SimAM attention module enhances effective soybean features and suppresses soil background redundancy, while an embedded S-DRU unit fuses multi-scale features for deep complementary reconstruction to improve edge detail capture. A label dataset was constructed using Sentinel-2 images as the data source and Menard County (USA) as the study area. The USDA CDL was used as a foundation for the dataset, with Google high-resolution images serving as visual interpretation aids. In the context of the experiment, Deeplabv3+ and U-Net++ were compared with U-Net under identical conditions. The results demonstrated that SimSDRU-Net exhibited optimal performance, with MIoU of 89.03%, MPA of 93.81%, and OA of 95.96%. Specifically, SimSDRU-Net uses the SimAM attention module to generate spatial attention weights by analyzing feature statistical differences through an energy function, so as to adaptively enhance soybean texture features. Meanwhile, the S-DRU unit groups, dynamically weights, and cross-branch reconstructs multi-scale convolutional features to preserve fine boundary details and achieve accurate segmentation of soybean plots. The present study demonstrates that SimSDRU-Net integrates lightweight design and high precision in data-limited scenarios, thereby providing effective technical support for the rapid extraction of soybean planting areas in North America. Full article

This paper presents a qualitative sustainability assessment of an innovative, water-based, partially bio-based, and potentially removable screen-printing ink designed to replace conventional PVC-based inks in the textile industry. The assessment is conducted in alignment with the European Commission’s tiered Safe and Sustainable by Design (SSbD) framework, applying a simplified screening approach suitable for innovations with limited sustainability data availability. The evaluation is conducted using the LCBROM (Life Cycle Based Risk and Opportunity Mapping) methodology, which is a structured approach designed to identify potential environmental, economic, and social drawbacks and benefits throughout the product’s life cycle, from production and use to end of life. The screening incorporates the MET+Ec+S matrix (Material, Energy, Toxicity, and Economic and Social dimensions), providing a comprehensive overview of the sustainability performance of the removable PVC-free ink at each stage of its life cycle. The novel removable PVC-free ink formulation incorporates bio-based pigments, thickeners, and plasticisers, and is designed to facilitate recyclability and reuse in textile applications. Compared to traditional plastisol inks, the screening indicates potential reductions in toxicity and environmental persistence compared to PVC-based plastisol inks, subject to validation in future quantitative studies. However, key trade-offs include reliance on fossil-based ingredients (as bio-based alternatives are still being developed), increased material costs, and durability concerns. Despite these issues, the removable PVC-free ink’s compatibility with existing printing infrastructure and alignment with emerging EU sustainability regulations indicate its potential relevance for circular textile production, subject to validation through quantitative life-cycle assessment and pilot-scale implementation. The results do not constitute a quantitative life cycle assessment but instead provide a structured qualitative basis for guiding further development, data collection, and future LCA modeling. By explicitly positioning the work within a simplified SSbD tier, this study demonstrates how early-stage screening can support innovation design while transparently addressing uncertainty and trade-offs. Full article