Search Results (6,212)

To reduce the high computational cost and lengthy design cycles of traditional solid rocket motor (SRM) development, this paper proposes an efficient surrogate-assisted multi-objective optimization approach. A comprehensive performance model was first established, integrating internal ballistics, grain structural integrity, and cost estimation, to enable holistic assessment of the coupled effects of key motor components. A parametric analysis framework was then developed to automate the model, facilitating seamless data exchange and coordination among sub-models through chain coupling. Leveraging this framework, a large-scale, high-fidelity dataset was generated via uniform sampling of the design space. The Kriging surrogate model with the highest global fitting accuracy was subsequently employed to replicate the integrated model’s complex responses and reveal underlying design principles. Finally, an enhanced NSGA-III algorithm incorporating a phased hybrid crossover operator was applied to improve global search performance and guide solution evolution along the Pareto front. Applied to a specific SRM, the proposed method achieved a 4.72% increase in total impulse and a 6.73% reduction in cost compared with the initial design, while satisfying all constraints. Full article

Block caving is a cost-effective mining method that enables the highly efficient mining of thick and large ore bodies. During ore extraction in block caving operations, the ore-drawing roadways require especially high safety standards. However, the complex in situ stress conditions and cyclic loading from caved ore significantly deteriorate the stability of the surrounding rock. This makes rock mass control particularly challenging, such that it is crucial to study an effective method for maintaining the long-term stability of the roadways. This research proposes a comprehensive approach combining laboratory rock mechanics testing, numerical simulation, and field engineering validation to design effective support strategies for disturbance-affected roadways. Laboratory tests provide accurate mechanical parameters for the rock mass, the numerical simulations allow for the comprehensive analysis of deformation–failure mechanisms under disturbance conditions, and field validation ensures the reliability and practical applicability of the proposed support method. This study focuses on a −285 m ore-drawing roadway in the western section of the Yanqianshan Iron Mine. The in situ stress distribution was characterized through rock mechanics testing and acoustic emission monitoring. The propagation mechanisms of ore-drawing disturbance waves within the rock mass were analyzed, and numerical simulations revealed the deformation patterns and failure modes under dynamic disturbance, upon which the support scheme was designed. The results demonstrate that the designed bolt–mesh–shotcrete support scheme can effectively control surrounding rock deformation within 5 mm and resists the deformation induced by cyclic disturbances. This study provides valuable technical support for stability management in block caving mines with similar conditions. Full article

The transition toward renewable-powered greenhouse agriculture offers opportunities for reducing operational costs and environmental impacts, yet challenges remain in managing fluctuating energy loads and optimizing agricultural inputs. While second-life lithium-ion batteries provide a cost-effective energy storage option, their thermal and electrical characteristics under real-world greenhouse conditions are poorly documented. Similarly, although plasma-activated water (PAW) shows potential to reduce chemical fertilizer usage, its integration with renewable-powered systems requires further investigation. This study develops an adaptive monitoring and modeling framework to estimate the thermal resistances (R_u, R_c) and internal resistance (R_int) of second-life lithium-ion batteries using operational data from greenhouse applications, alongside a field trial assessing PAW effects on beefsteak tomato cultivation. The adaptive control algorithm accurately estimated surface temperature (T_s) and core temperature (T_c), achieving a root mean square error (RMSE) of 0.31 °C, a mean absolute error (MAE) of 0.25 °C, and a percentage error of 0.31%. Thermal resistance values stabilized at R_u ≈ 3.00 °C/W (surface to ambient) and R_c ≈ 2.00 °C/W (core to surface), indicating stable thermal regulation under load variations. Internal resistance (R_int) maintained a baseline of ~1.0–1.2 Ω, with peaks up to 12 Ω during load transitions, confirming the importance of continuous monitoring for performance and degradation prevention in second-life applications. The PAW treatment reduced chemical nitrogen fertilizer use by 31.2% without decreasing total nitrogen availability (69.5 mg/L). The NO₃⁻-N concentration in PAW reached 134 mg/L, with an initial pH of 3.04 neutralized before application, ensuring no adverse effects on germination or growth. Leaf nutrient analysis showed lower nitrogen (1.83% vs. 2.28%) and potassium (1.66% vs. 2.17%) compared to the control, but higher magnesium content (0.59% vs. 0.37%), meeting Japanese adequacy standards. The total yield was 7.8 kg/m², with fruit quality comparable between the PAW and control groups. The integration of adaptive battery monitoring with PAW irrigation demonstrates a practical pathway toward energy efficient and sustainable greenhouse operations. Full article

Background: Alterations in peripheral red blood cell (RBC) indices have been proposed as potential biomarkers for Parkinson’s disease (PD), but their diagnostic utility and relation to clinical features remain uncertain. Methods: We conducted a pilot case–control study involving 70 PD patients and 122 controls from two neurology centers in Mexico. Standardized hematology analyses provided RBC indices, and neuropsychiatric assessments included the Hamilton Depression Rating Scale (HAM-D) and Mini-Mental State Examination (MMSE). Associations between RBC indices and PD were tested using multivariable logistic regression adjusted for age, sex, and smoking. Diagnostic performance was evaluated by receiver operating characteristic (ROC) curve analysis. Subgroup analyses stratified PD patients by age at onset, disease duration, and Hoehn and Yahr (HY) stage. Results: PD patients exhibited significantly higher mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC) than controls. Elevated MCHC was independently associated with PD (OR = 1.68, 95% CI 1.35–2.09; p < 0.001). Sex-stratified models confirmed consistent associations in women (OR = 1.57) and men (OR = 1.79). ROC analysis demonstrated fair diagnostic accuracy for MCHC (AUC 0.72, 95% CI 0.65–0.80; cutoff 33.9 g/dL, sensitivity 62.9%, specificity 72.1%). Sex-specific thresholds improved sensitivity in women (90.6%) and specificity in men (74.6%). Within the PD group, MCHC did not differ by HY stage or disease duration, and showed no correlation with UPDRS, HAM-D, or MMSE scores. Early-onset cases (<50 years) showed numerically higher MCHC, though numbers were limited. Conclusions: This pilot study confirms that an elevated MCHC is independently associated with PD, a finding consistent across both sexes and independent of disease severity. MCHC demonstrates fair diagnostic performance, supporting its potential as a low-cost, accessible biomarker. Larger longitudinal studies integrating RBC indices with inflammatory and iron-regulatory markers are warranted to establish their role in the diagnosis and differential diagnosis of PD. Elevated MCHC was associated with PD, and an MCHC-based index (cutoff 33.9 g/dL; AUC 0.72, sensitivity 62.9%, specificity 72.1%) showed potential as a simple diagnostic marker. Full article

Due to the necessity of decarbonising and transforming the Polish energy mix, topic of using nuclear power plants as one of the key low-carbon generation sources is returning to the public debate. This paper compares a large, system-wide AP1000 nuclear power plant with a new concept based on small modular reactors (SMRs), specifically NuScale 60 MW_e. Computer models of secondary loops of the generating units were used for the analysis, and basic operating parameters were determined. A consistent modelling approach was used to evaluate technical, thermodynamic, and economic indicators. As a result, a relationship between total capital expenditures and unit electricity generation cost was developed. For example, if the investment outlays, taking into account the freeze, for a large-scale nuclear power plant are USD 8 billion, then the investment outlays for an SMR power plant should be below USD 0.4 billion in order to ultimately ensure a lower or equal unit discounted cost of electric energy generation. Assuming stable power demand, the AP1000 reactor power plant remains the most cost-effective technology, offering favourable economies of scale. However, modular units are characterised by shorter lead times and greater flexibility of application in different areas of the energy industry. Therefore, in the decarbonisation process, it is essential to develop both analysed technologies in parallel. Full article

This study proposes a technoeconomic model for assessing the profitability of modern greenhouses, with emphasis on hydroponic systems and the integration of combined heat and power (CHP) technology. Given the high share of energy costs in total operating expenses (~35%), the model includes both cultivation and energy subsystems and is implemented in a spreadsheet environment for ease of use. The model calculates Return on Investment (ROI) under various scenarios, considering geographical latitude, CHP capacity, cultivation settings, and energy prices. In the baseline case, the greenhouse ROI is 12%, rising to 14% when CHP is integrated, with CHP itself achieving 24%. Key findings include the identification of optimum CHP sizing (0.5–1.5 MW/ha, depending on latitude) and critical inflection points in ROI behavior associated with latitude and cultivation temperature, driven by the depletion of cooling demand and redistribution of operating modes. The analysis confirms that CHP becomes economically attractive when the Spark Ratio (the electricity price to the natural gas price) exceeds 3, offering enhanced profitability and resilience against energy price volatility. The proposed method is simple, transparent, and suitable for preliminary investment analysis and policy planning in sustainable agri-energy systems. Full article

The transition to low-carbon energy systems requires efficient hydrogen production methods that minimise CO₂ emissions. This study presents a techno-economic assessment of hydrogen production via methane pyrolysis, utilising a novel liquid metal bubble column reactor (LMBCR) designed for CO₂-free hydrogen and solid carbon outputs. Operating at 20 bar and 1100 °C, the reactor employs a molten nickel-bismuth alloy as both catalyst and heat transfer medium, alongside a sodium bromide layer to enhance carbon purity and facilitate separation. Four operational scenarios were modelled, comparing various heating and recycling configurations to optimise hydrogen yield and process economics. Results indicate that the levelised cost of hydrogen (LCOH) is highly sensitive to methane and electricity prices, CO₂ taxation, and the value of carbon by-products. Two reactor configurations demonstrate competitive LCOHs of 1.29 $/kgH₂ and 1.53 $/kgH₂, highlighting methane pyrolysis as a viable low-carbon alternative to steam methane reforming (SMR) with carbon capture and storage (CCS). This analysis underscores the potential of methane pyrolysis for scalable, economically viable hydrogen production under specificmarket conditions. Full article

Background/Objective: The overnight 1-mg dexamethasone suppression test (DST) represents the conventional/standard tool for endogenous hypercortisolemia screening, typically in relationship with adrenal and pituitary masses. Nevertheless, an associated spectrum of challenges and pitfalls is found in daily practice. This analysis aimed to evaluate: (I.) the diagnosis relevance of 1-mg DST in patients with adrenal incidentalomas (AIs) with/without mild autonomous cortisol secretion (MACS) exploring different cutoffs of the second-day plasma cortisol after dexamethasone administration (cs-DST) with respect to cardio-metabolic outcomes; (II.) the potential utility of adding other biomarkers to DST [plasma morning adrenocorticotropic hormone (ACTH), 24-h urinary free cortisol (UFC), late-night salivary cortisol (LNSC), dehydroepiandrosterone sulfate (DHEAS)]; and (III.) DST variability in time. Methods: This narrative analysis was based on searching full-text, English articles in PubMed (between January 2023 and April 2025) via using different term combinations: “dexamethasone suppression test” (n = 239), “diagnosis test for autonomous cortisol secretion” (n = 22), “diagnosis test for mild autonomous cortisol secretion” (n = 13) and “diagnosis test for Cushing Syndrome” (n = 61). We manually checked the title and abstract and finally included only the studies that provided hormonal testing results in adults with non-functional adenomas (NFAs) ± MACS. We excluded: reviews, meta-analyses, editorials, conference abstracts, case reports, and case series; non-human research; studies that did not provide clear criteria for distinguishing between Cushing syndrome and MACS; primary aldosteronism. Results: The sample-focused analysis (n = 13 studies) involved various designs: cross-sectional (n = 4), prospective (n = 1), retrospective (n = 7), and cohort (n = 1); a total of 4203 patients (female-to-male ratio = 1.45), mean age of 59.92 years. I. Cs-DST cutoffs varied among the studies (n = 6), specifically, 0.87, 0.9, 1.2, and 1.4 µg/dL in relationship with the cardio-metabolic outcomes. After adjusting for age (n = 1), only the prevalence of cardiovascular disease remained significantly higher in >0.9 µg/dL vs. ≤0.9 group (OR = 2.23). Multivariate analysis (n = 1) found cs-DST between 1.2 and 1.79 µg/dL was independently associated with hypertension (OR = 1.55, 95%CI: 1.08–2.23, p = 0.018), diabetes (OR = 1.60, 95%CI: 1.01–2.57, p = 0.045), and their combination (OR = 1.96, 95%CI:1.12–3.41, p = 0.018) after adjusting for age, gender, obesity, and dyslipidemia. A higher cs-DST was associated with a lower estimated glomerular filtration rate (eGFR), independently of traditional cardiovascular risk factors. Post-adrenalectomy eGFR improvement was more pronounced in younger individuals, those with lower eGFR before surgery, and with a longer post-operative follow-up. Cs-DST (n = 1) was strongly associated with AIs size and weakly associated with age, body mass index and eGFR. Cortisol level increased by 9% (95% CI: 6–11%) for each 10 mL/min/1.73 m² decrease in eGFR. A lower cs-DST was associated with a faster post-adrenalectomy function recovery; the co-diagnosis of diabetes reduced the likelihood of this recovery (OR = 24.55, p = 0.036). II. Additional biomarkers assays (n = 5) showed effectiveness only for lower DHEAS to pinpoint MACS amid AIs (n = 2, cutoffs of <49.31 µg/dL, respectively, <75 µg/dL), and lower ACTH (n = 1, <12.6 pmol/L). III. Longitudinal analysis of DST’s results (n = 3): 22% of NFAS switch to MACS after a median of 35.7 months (n = 1), respectively, 29% (n = 1) after 48.6 ± 12.5 months, 11.8% (n = 1) after 40.4 ± 51.17 months. A multifactorial model of prediction showed the lowest risk of switch (2.4%) in individuals < 50 years with unilateral tumor and cs-DST < 0.45 µg/dL. In the subgroup of subjects without cardio-metabolic comorbidities at presentation, 25.6% developed ≥1 comorbidities during surveillance. Conclusions: The importance of exploring the domain of AIs/NFAs/MACS relates to an increasing detection in aging population, hence, the importance of their optimum hormonal characterization and identifying/forestalling cardio-metabolic consequences. The spectrum of additional biomarkers in MACS (other than DST) remains heterogeneous and still controversial, noting the importance of their cost-effectiveness, and availability in daily practice. Cs-DST serves as an independent predictor of cardio-metabolic outcomes, kidney dysfunction, while adrenalectomy may correct them in both MACS and NFAs, especially in younger population. Moreover, it serves as a predictor of switching the NFA into MACS category during surveillance. Changing the hormonal behavior over time implies awareness, since it increases the overall disease burden. Full article

The burgeoning economic relationship between Türkiye and Poland, marked by a targeted $10 billion trade volume, has catalyzed significant Turkish engagement in the Polish construction sector. Ranked second globally in international contracting, Turkish firms are increasingly undertaking complex infrastructure projects in Poland, making it a critical European market to analyze. This study develops a comprehensive framework to identify and evaluate the sources of sustainable competitive advantage for Turkish contractors operating in this dynamic environment. The research adopts a qualitative, single-case study methodology, centered on the extensive project portfolio of a leading Turkish firm in Poland. The analytical approach is twofold. First, it employs Porter’s Diamond Framework to deconstruct the existing competitive advantages, revealing a shift from traditional low-cost models to a sophisticated synergy of superior labor management capabilities, strategic local partnerships, and expertise in complex project delivery. These strengths are shown to align directly with Poland’s critical needs, particularly its skilled labor shortage and ambitious infrastructure agenda. Second, a Foresight Analysis is conducted to map plausible future scenarios through 2035, addressing key uncertainties such as geopolitical shifts and the pace of technological adoption. The findings demonstrate that the sustained success of Turkish contractors hinges on their ability to deliver targeted value. The study concludes by proposing a set of “no-regrets” strategies—including accelerated ESG and digital up-skilling, forging deep local partnerships, and developing financial engineering capabilities—designed to secure and enhance their competitive positioning. The results provide an actionable roadmap for industry practitioners and valuable insights for policymakers fostering bilateral economic collaboration. Full article

The large-scale integration of wind power into coastal power systems introduces significant challenges to reserve planning, especially under the threat of typhoons, which can cause extensive generation loss and threaten system security. Conventional reserve planning methods often fail to account for such extreme typhoon events. To fill the gap, this paper proposes a novel two-stage reserve planning framework that integrates economic optimization with operational security verification. In the first stage, a diverse set of high-impact typhoon scenarios are generated using a multivariate Markov chain Monte Carlo (MMCMC)–based path reconstruction method, which captures the dynamic evolution of key typhoon characteristics. In the second stage, the economically optimal reserve capacity is identified through cost-benefit analysis and then validated against the typhoon scenarios via N − 1 security verification. A case study on the modified IEEE RTS79 test system indicates that economically optimal reserve may be inadequate for ensuring security under severe typhoon conditions. However, a small increase in reserve capacity can effectively enhance system resilience with minimal additional cost. These results highlight the importance of incorporating typhoon scenario-based security verification into reserve planning especially for high-penetration wind power systems in coastal regions. Full article

This study presents the development of a predictive system based on artificial neural networks (ANNs) and fuzzy logic to estimate losses in an agave liquor production and packaging plant. Currently, these losses are discharged into wastewater, generating not only finished product waste, but also greater environmental pollution and higher treatment costs. To address this, agave liquor waste is converted into methane biogas through anaerobic digestion and subsequently transformed into electrical energy. The system begins by collecting historical data from the production process, including production plans and shrinkage rates at each stage of the packaging line. These data are analyzed to identify behavioral patterns and correlations between process variables and losses, allowing a deeper understanding of the packaging process. Critical control points were identified throughout the production stages, and an ANN model was trained with historical data to predict losses. Outstanding results were achieved in the packaging and capping stage, where a significant impact on bottle loss was observed, with a 29% impact in the morning shift and a 35% impact in the afternoon shift. Fuzzy logic was used to manage the uncertainty and subjectivity associated with identifying the stages most susceptible to waste, translating qualitative assessments into quantitative metrics. Estimates allow for approximately 8% to 12% reductions by streamlining the process with this analysis obtained through the use of artificial intelligence tools. This integrated approach aims to optimize operational efficiency, reduce losses, minimize environmental impact, and promote sustainable practices within the agave liquor industry. Full article

Thursday Island, a remote administrative hub in Australia’s Torres Strait, exemplifies the socio-technical challenges of transitioning to sustainable energy amid diesel dependence and the intermittency of renewables. As Australia pursues Net Zero by 2050, innovative storage solutions are pivotal for enabling green innovation in isolated microgrids. This study evaluates Vanadium Redox Flow Batteries (VRFBs) and Lithium-Ion batteries as key enabling technologies, using a stochastic Monte Carlo simulation to assess their economic viability through Levelized Cost of Storage (LCOS), incorporating uncertainties in capital costs, operations, and performance over 20 years. Employing a stochastic Monte Carlo simulation with 10,000 iterations, this study provides a probabilistic assessment of LCOS, incorporating uncertainties in key parameters such as CAPEX, OPEX, efficiency, and discount rates, offering a novel, data-driven framework for evaluating storage viability in remote microgrids. Results indicate VRFBs’ superiority with a mean LCOS of 168.30 AUD/MWh versus 173.50 AUD/MWh for Lithium-Ion, driven by scalability, durability, and safety—attributes that address socio-economic barriers like high operational costs and environmental risks in tropical, off-grid settings. By framing VRFBs as an innovative green solution, this analysis highlights opportunities for new business models in remote energy sectors, such as reduced fossil fuel reliance (3.6 million litres diesel annually) and enhanced community resilience against energy poverty. It also underscores challenges, including capital uncertainties and policy needs for innovation uptake. This empirical case study contributes to the sustainable energy transition discourse, offering insights for policymakers on overcoming resistance to decarbonization in geographically constrained contexts, aligning with green innovation goals for systemic sustainability. Full article

The selection of the most economically advantageous tender (MEAT) in public procurement procedures requires transparent evaluation systems capable of integrating heterogeneous criteria, including qualitative ones, to reconcile quality and cost. This systematic review analyzes 74 studies published between 1998 and 2023 to explore the application of multi-criteria decision analysis (MCDA) methods in public construction procurement. The vast majority of MCDA applications focus on the award phase, with constant growth over the last 10 years. However, applications in the prequalification and verification phases are much less frequent and remain under-represented. Geographically, Europe is the most active area in terms of publications, followed by China and some countries in the Asia-Pacific area. In these regions, MCDA has been employed more systematically over time, while in other areas (e.g., Africa, Latin America), applications are sporadic or absent. Analytic Hierarchy Process (AHP) is confirmed as the most widely used technique. Emerging techniques (such as BWM, MABAC, EDAS, VIKOR, advanced TOPSIS) show greater computational rigor and in some cases better theoretical properties, but are less used due to complexity, less practical familiarity and the lack of accessible software tools. The operationalization of environmental and social criteria is still poorly standardized: clear indications on metrics, measurement scales and data sources are often lacking. In most cases, the criteria are treated in a generic or qualitative way, without common standards. Furthermore, the use of sensitivity analyses and procedures for aggregating judgments between evaluators is limited, with a consequent risk of poor robustness and transparency in the evaluation. In order to consider proposing a framework or guidelines based on the review findings, a six-step operational framework that connects selection of criteria and their operationalization, choice of method based on the context, robustness checks and standard minimum reporting, with clear assignment of roles and deliverables, is provided. The framework summarizes and makes the review evidence applicable. Full article

The integration of artificial intelligence (AI) and machine learning (ML) technologies in energy storage systems has emerged as a transformative approach in addressing the complex challenges of modern energy infrastructure. This comprehensive review examines current state of the art AI applications in energy storage, from battery management systems to grid-scale storage optimization. We analyze various AI techniques, including supervised learning, deep learning, reinforcement learning, and neural networks, and their applications in state estimation, predictive maintenance, energy forecasting, and system optimization. The review synthesizes findings from the recent literature demonstrating quantitative improvements achieved through AI integration: distributed reinforcement learning frameworks reducing grid disruptions by 40% and operational costs by 12.2%, LSTM models achieving state of charge estimations with a mean absolute error of 0.10, multi-objective optimization reducing power losses by up to 22.8% and voltage fluctuations by up to 71%, and real options analysis showing 45–81% cost reductions compared to conventional planning approaches. Despite remarkable progress, challenges remain in terms of data quality, model interpretability, and industrial implementation. This paper provides insights into emerging technologies and future research directions that will shape the evolution of intelligent energy storage systems. Full article

This study investigates the economic viability of a new composting station dedicated to the recycling of date palm by-products. A field experiential analysis was performed in the Figuig Oasis (Morocco), providing the first evidence on the agronomic quality of the compost. The compost produced from date palm by-product was compared to cattle manure and unamended soil and can be considered as a good-quality amendment, demonstrating its ability to enhance soil fertility. Second, a socio-economic survey was conducted to explore farmers’ perceptions and adoption of sustainable agricultural practices. A total of 201 farmers out of 450 farmers registered in Figuig’s municipal administration were surveyed. In terms of fertilisation, farmers preferred locally produced organic fertiliser when available in order to improve soil organic matter content and reduce dependence on chemical inputs. The selling price for the compost was set at 0.14 EUR/kg to reflect the current market price for compost and the willingness of about 38% of the farmers surveyed to buy it. Third, a detailed cost/benefit analysis was performed, with a breakdown of the station’s operational and investment expenses. This illustrates the minimum scale needed to generate a viable business model. Financial projections show that increasing production capacity from 350 tonnes/year to 3500 tonnes/year reduces unit production costs while increasing profits. As illustrated by the application of the Ecocanvas framework, the socio-economic analysis reveals the potential to generate positive environmental, economic, and social impacts, as the circular approach could be replicable and scalable in similar oases agro ecosystems. Full article