Search Results (4,249)

One of the most common problems in drilling operations is lost circulation, which can significantly increase well costs and lead to issues such as pipe sticking, blowouts, and even well closures. Identifying thief zones using analytical models is especially difficult, and there are no robust equations available in the literature due to a wide range of influential parameters, both controllable and uncontrollable. These parameters include operational factors, as well as the physical properties of the rock and drilling fluid. This study presents an artificial intelligence-based model designed to predict lost circulation zones. It investigates the underexplored potential of WV-curves for feature selection. Traditionally used to represent the spectral characteristics of training data, their role in feature selection has not been widely examined in the literature. The presentation of WV-curves is modified, and their effectiveness in identifying the optimal number of input and hidden neurons is evaluated. In this research study, a total of 15,000 data points were used and collected from oil wells in the Middle East. The artificial neural network (ANN) model exhibited a remarkable ability to accurately predict the locations of lost circulation zones based on the collected data, achieving an impressive accuracy of 94.5%. This is a significant achievement when compared to existing ANN models in the literature. The results highlight the strength of the ANN model in predicting lost circulation locations across a wide range of data collected from various wells in the Middle East. In addition, this model takes into account a diverse set of drilling operational parameters, as well as rock characteristics and fluid properties, offering a broader approach compared to other available ANN models. This advancement will also greatly facilitate future studies, enabling the prediction of lost circulation zones, and enabling advanced planning of appropriate prevention and remediation methods during the well planning phase to reduce the risk of lost circulation. Nevertheless, it should be noted that one limitation of the proposed methodology relates to data availability, as comprehensive formation parameters were not fully accessible; the inclusion of additional formation data may offer opportunities for further improvement in future studies. Full article

The volatility of renewable energy generation and nodal electricity prices provides an arbitrage opportunity for Mobile Battery Energy Storage Systems (MBESS) leveraging both temporal and spatial advantages. However, the inherent high complexity and strong randomness of both power and transportation systems lead to complex risks for MBESS control. Existing works mainly consider the market price risk and ignore the transportation system risk caused by traffic congestion. Specifically, they are constrained by two critical limitations: (1) decisions can only be made upon arrival at a destination, making the agent unresponsive on the road, and (2) traffic congestion risk is neither quantified nor controlled, leading to suboptimal routing strategies. To address these limitations, the MBESS needs more flexible “on the road” decision making and multiple risk management capabilities. Guided by this objective, a flexible deep reinforcement learning-based MBESS control framework is proposed, considering both market and traffic congestion risk. First, dynamic routing ability is integrated with the MBESS agent to provide more flexibility in making decisions, regardless of whether the agent has reached the designated location or not. Second, two risk metrics are proposed to quantitatively assess the traffic congestion risk based on moving time, and then the agent can make decisions considering both market and traffic congestion risk. Finally, considering the inefficiency of learning caused by introducing multiple risks, a risk curriculum learning method is proposed to improve the training efficiency and reduce learning costs. These components are unified in the Multiple Risk Estimation SDDPG (MRE-SDDPG) algorithm, which jointly maximizes profitability while controlling electricity price and traffic congestion risk. Simulations in the IEEE 30 bus environment show that the proposed framework can increase profit by 8.6% while reducing the traffic time by 15.8% on average, demonstrating the superiority of our design in considering traffic congestion risk. Full article

There is renewed interest in local sourcing, regional supply chains, and the rebuilding of fiber-to-fashion systems. However, limited attention has been paid to the upstream role of fiber farmers and the infrastructure that enables or constrains regional textile economies. This study investigates the opportunities and challenges of fiber farming in West Virginia and explores the motivations that drive participation in this sector. Using a qualitative approach, semi-structured interviews were conducted with 16 fiber farmers across West Virginia. The findings revealed five interconnected themes: heterogeneous actants, the translation of wool, regional network breakdown, festivals and social media as network hubs, and institutional gaps and network fragility. The results indicate that fiber farming persists through strong community networks, adaptive entrepreneurial strategies, and deep attachments to place. However, its economic viability is constrained by declining processing infrastructure, labor shortages, weakened institutional support, and fragmented supply chains. These challenges also have important sustainability implications. Most notably, wool is often discarded because processing and transportation costs exceed its market value, resulting in the waste of a renewable and biodegradable fiber that could otherwise remain in productive use. This study contributes to the literature on local sourcing, rural entrepreneurship, and sustainable and circular economies by highlighting the relational infrastructures required to rebuild regionally embedded textile systems in Appalachia and beyond. Full article

Background and Objectives: Despite global commitment to the World Health Organization triple elimination initiative, evidence on integrated antenatal service delivery models that simultaneously address human immunodeficiency virus (HIV), syphilis, and hepatitis B virus (HBV) remains fragmented, particularly across diverse health-system contexts. Eliminating vertical transmission of HIV, syphilis, and HBV is a global priority. Pregnant women are disproportionately affected by these infections, and untreated maternal disease leads to significant infant morbidity. Integrating antenatal screening and treatment provides an opportunity to address all three conditions simultaneously. Purpose: This systematic review and meta-analysis aimed to identify and synthesise evidence on integrated antenatal service delivery models addressing HIV, syphilis, and HBV simultaneously within maternal health services. It specifically examined model characteristics, screening uptake, treatment and follow-up outcomes, implementation barriers and facilitators, and evidence on cost-effectiveness. Methods: This systematic review and meta-analysis followed PRISMA 2020 guidelines and was registered in PROSPERO (CRD420261342186). We searched Scopus, PubMed, Web of Science, and Dimensions for studies published between January 2007 and January 2026. Of 423 records identified, 11 met the inclusion criteria after excluding two studies that did not provide empirical results for an integrated service model addressing all three target infections simultaneously. Data on study characteristics, service delivery, diagnostics, outcomes, and implementation factors were extracted. A random-effects meta-analysis of proportions was conducted using the DerSimonian–Laird estimator with logit transformation. Results: Eleven studies covered Asia, Africa, Europe, and Latin America, mostly in low- and lower-middle-income countries. Integration ranged from rapid test packages in community clinics to comprehensive programmes including STI treatment, malaria testing, and HBV birth-dose vaccination. Pooled triple testing uptake was 97% (95% CI 92 to 100%). Large programmes achieved over 99% coverage and reduced HIV vertical transmission to below 3%. Pilot studies showed feasibility but noted stockouts, data gaps, and weak treatment linkage. Economic analyses supported cost-effectiveness. Conclusions: Integrated antenatal services appear feasible and can achieve high testing uptake, particularly in well-supported programmes. However, evidence remains uneven regarding treatment completion, infant follow-up, HBV prophylaxis, long-term transmission outcomes, and sustainability in resource-constrained settings. Key challenges include supply constraints, workforce limitations, and follow-up gaps. Future research should evaluate the full care cascade, not screening uptake alone. Full article

Three-dimensional printed concrete (3DPC) has received growing attention as digital fabrication technologies continue to influence construction workflows. This study presents a systematic review of research published between 2015 and 2026, following PRISMA guidelines. Based on the reviewed literature, six opportunity categories and six challenge categories were identified. The opportunities include design optimization, construction speed, materials innovation, labor reduction, remote area construction, and circular economy. The findings show that material innovation is the most extensively researched category; a substantial proportion of the literature focuses on materials, rheology, printability, and structural behavior, reflecting an emphasis on improving fresh-state properties, interlayer bonding, and mechanical performance. The second most researched opportunity is design optimization, followed by the circular economy. Research in the remaining three categories of construction speed, labor reduction, and remote area construction appears to be limited. The main challenges identified include reinforcement integration, structural performance, mixing and curing, high equipment costs, durability, and the lack of standards. High equipment costs and the lack of standards appear to be the least researched challenges, while the four remaining challenge categories are actively addressed by the research community. Full article

The purpose of this paper is to investigate the firm-level determinants of the cost of debt in a bank-based emerging economy, where debt serves as the primary external financing mechanism, enabling firms to maintain operations, pursue growth opportunities, and ensure long-term financial sustainability. Using panel data from non-financial firms listed on the Casablanca Stock Exchange over the period 2018–2024, we document a robust nonlinear relationship between financial leverage and the cost of debt, whereby low and moderate debt levels reduce borrowing costs by signaling creditworthiness and financing capacity, while excessive indebtedness reverses this effect, with an optimal threshold estimated at approximately 34.8% of total assets. Firms with stronger growth prospects further benefit from more favorable financing conditions, as creditors interpret sustained asset expansion as a signal of financial strength and long-term viability. Financial performance is also found to reduce the cost of debt, although this effect is not fully robust to endogeneity controls. In contrast, asset tangibility, firm size, firm age, and liquidity do not emerge as significant determinants, suggesting that creditors in the Moroccan market adopt a financial health-oriented approach when assessing credit risk, placing greater emphasis on leverage and growth prospects than on collateral-based or reputational signals. Overall, the study highlights the coexistence of linear and nonlinear dynamics in debt pricing, thereby enriching the corporate finance literature and providing insights for managers and policymakers seeking to reduce borrowing costs, enhance access to debt financing, and support sustainable value creation. Full article

The potential for the use of antimicrobial peptides (AMPs) as anticancer agents has garnered much interest because of their selective cytotoxicity to tumor cells and ability to evade multidrug resistance mechanisms. AMPs are shorter cationic amphiphilic molecules, part of our innate immune system, with direct membrane-disruptive activity and immunomodulatory effects. Anticancer peptides (ACPs) can be derived from natural biophysical sources or synthetically engineered, taking advantage of the unique biophysical properties of cancer cell membranes to exert their anti-tumor activities rapidly and often without significant effects on normal tissues. Advances in peptide engineering, such as D-amino acid substitution, cyclization, and PEGylation, combined with nanocarrier systems, have provided opportunities to improve peptide stability, bioavailability, and delivery to targeted sites. Studies in preclinical and clinical models show promise, indicating that AMPs and ACPs can induce immunogenic cell death, modify tumor microenvironments, and be used in combination with more conventional therapies. While the promise of AMPs and ACPs as relatively novel cancer therapeutics is substantial, challenges such as proteolytic degradation, dose-dependent toxicity, costs for production, and regulatory hurdles are notable. This review organizes the current literature on classification, mechanism(s) of action, delivery strategies, preclinical and clinical data, and provides areas for future work to improve and help speed their clinical translation as new cancer therapies. Full article

To improve the low-carbon economic operation of integrated energy systems under wind power uncertainty, this paper develops an optimal scheduling model for an integrated energy system coupling oxygen-enriched combustion with hydrogen–ammonia–carbon utilization pathways. The proposed framework integrates oxygen-enriched combustion, electrolysis-based hydrogen production, methanation, hydrogen fuel cells, ammonia synthesis, urea synthesis, captured CO₂ utilization, reward–penalty ladder-type carbon trading, and IGDT-based wind power uncertainty scheduling. A deterministic scheduling model is first established to minimize the total operating cost, and Information Gap Decision Theory is then introduced to formulate risk-averse and opportunity-seeking scheduling strategies under wind power uncertainty. Simulation results show that, compared with the post-combustion carbon capture scenario and the conventional coal-fired scenario, the proposed system reduces the total operating cost by 3.37% and 8.03%, respectively, and reduces the wind curtailment cost by 40.2% and 57.0%, respectively. Compared with the post-combustion carbon capture scenario, carbon emissions are reduced by 17.7%. The hydrogen–ammonia–urea chain generates approximately 15.68 × 10⁴ CNY of urea revenue and improves carbon resource utilization. Under an IGDT deviation factor of 0.03, the risk-averse strategy increases the total operating cost by approximately 10.30 × 10⁴ CNY to enhance operational robustness, while the opportunity-seeking strategy reduces the total operating cost by approximately 10.30 × 10⁴ CNY and decreases carbon emissions by 19.6 t. These simulation results verify the effectiveness of the proposed scheduling framework under the designed case study. The proposed framework can improve the low-carbon economy, renewable energy accommodation, carbon resource utilization, and adaptability to wind power uncertainty of the studied integrated energy system. Full article

As a core component of childbearing costs, women’s opportunity costs provide a crucial perspective for explaining the current decline in fertility rates. Recognizing the reciprocal causality between women’s opportunity costs and fertility decisions, this study examines their statistical correlation using micro-level data from the China Family Panel Studies (CFPS). Building on these empirical insights, we develop a household fertility decision-making model that incorporates women’s opportunity costs, calibrating the parameters through structural estimation to quantitatively explore its impact on fertility choices. The quantitative empirical findings reveal a significantly negative correlation between women’s opportunity costs and the actual number of children in a household. The theoretical analysis demonstrates that an intensifying motherhood penalty and prolonged career interruptions due to childbirth both lead to a reduction in the equilibrium number of children. Furthermore, higher educational attainment and increasing child-rearing costs exert a pronounced inhibitory effect on fertility intentions. Policy simulations further indicate that, compared to short-term or one-off incentives, continuous fertility subsidies and the implementation of free childcare policies are more effective in offsetting opportunity costs and boosting household fertility intentions. Full article

Background: The transition from linear to circular supply chains (CSC) is critical for advancing sustainability, resilience, and resource efficiency, while supporting the UN Sustainable Development Goals (SDGs). However, existing studies rarely integrate internal operational performance with external PESTEL factors under the Benefits, Opportunities, Costs, and Risks (BOCR) perspective, limiting the ability to prioritize circular strategies holistically. Methods: This study develops a decision-making framework that combines the Best-Worst Method (BWM) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), enabling reliable prioritization of interdependent sustainability criteria. Results: A case analysis in the chemical industry demonstrates the applicability of the framework, enhancing transparency and reducing subjectivity in CSC evaluation. Findings highlight quality as the key operational attribute and social as the dominant PESTEL dimension, reinforcing the integration of internal and external factors toward SDG-oriented strategies. Conclusions: The study contributes theoretically by bridging operational and contextual dimensions in CSC evaluation under the BOCR perspective, and methodologically by advancing hybrid MCDM applications to address uncertainty. Managerially, the framework provides a structured tool for aligning circular supply chain strategies with organizational objectives and SDGs, supporting decision-making that strengthens environmental sustainability, stakeholder legitimacy, and resilience. Full article

Intelligence tests predict academic achievement, but their use in educational decision-making remains contested. We develop a decision-analytic framework, centered on a staged decision architecture, to determine when, for whom, and for which educational decisions intelligence testing adds value beyond grades, achievement measures, and contextual evidence. Drawing on psychometric scholarship, a generative account of achievement, and illustrative decision scenarios, we distinguish incremental validity from decision utility. Incremental validity refers to the predictive gain obtained by adding cognitive measures, whereas decision utility refers to the net benefit of using those measures once base rates, capacity constraints, error costs, fairness, and legitimacy are considered. We use the framework to identify conditions in which intelligence testing is expected to be most informative, especially educational transitions, contexts with uneven opportunity, and discrepancy-focused decisions such as underachievement or twice-exceptionality. We also specify minimum conditions for responsible use, including intended use, construct representation, reliability or precision, measurement comparability, predictive bias checks, and monitoring of distributional impact. We conclude that intelligence testing should be used conditionally and sequentially, with achievement and contextual indicators used first and cognitive assessment added only when it is likely to change the decision. Full article

Beer is one of the oldest and most widely consumed fermented beverages in the world. However, barley production is increasingly vulnerable to agricultural and socioeconomic pressures, particularly in temperate growing regions where rising temperatures threaten yield stability. In contrast, rice is projected to experience comparatively smaller yield declines, highlighting its potential as a more climate-resilient starch source for brewing. This opportunity is especially relevant in the United States, where Arkansas produces approximately half of the nation’s rice supply. Large commercial breweries have successfully incorporated rice through the use of cereal cookers, but these systems are often impractical for smaller operations because of their cost and space requirements. In addition, rice supplied to the brewing industry is often sourced as a byproduct of the edible rice market, where multiple cultivars may be blended, reducing consistency and obscuring cultivar-specific effects that influence brewing performance. This manuscript reviews variation among rice cultivars in the physical, chemical, and agronomic properties relevant to brewing and examines how these differences affect extract yield and processability. Particular emphasis is placed on practical strategies to overcome technical barriers, including alternative mashing approaches and the use of heat-stable exogenous enzymes to facilitate the use of milled rice without dedicated cereal-cooking infrastructure. Full article

Background: Adenovirus-vectored vaccines played an important role in the global response to SARS-CoV-2. Adenovirus platforms have many advantages including a simple and readily transferred manufacturing process, low cost, and thermostability. Speed of production of an initial Good Manufacturing Practice (GMP)-compliant batch has, however, been viewed as a limitation of adenovirus vectors relative to mRNA platforms. Production of the initial viral starting material and release testing are key rate-limiting steps. Methods: Production of viral starting material from DNA, and release testing in accordance with regulatory expectations, for first-in-human trials of adenovirus-vectored vaccines. Results: We describe experience of these stages in the production of the first GMP batches for multiple adenovirus-vectored candidates and the adaptations made for ChAdOx1 nCoV-19 (the Oxford COVID-19 vaccine) in early 2020. We also report development of a streamlined approach to starting material generation, enabling initial GMP batch availability within c. 60 days of publication of a new pathogen sequence. Using a New World arenavirus vaccine construct as a proof of concept, we demonstrate reproducible execution of this pipeline, maintaining acceptable infectivity and other quality attributes. Conclusions: We discuss opportunities for additional time savings in the future. This work demonstrates suitability of an adenovirus platform to contribute to the “100 Days Mission” for vaccines against “Disease X”. Full article

The growing adoption of electric vehicles (EVs) and the rapid expansion of public charging infrastructure pose new challenges and opportunities for energy systems, particularly in urban settings. This study presents an optimization-based evaluation of different EV charging strategies including direct charging, average-based methods, smart charging, and vehicle-to-grid (V2G) at public parking lots using real-world charging session data. This data-driven model is set to optimize the public EV charging of vehicles in Gothenburg, without sacrificing on the energy requirement while minimizing charging costs for the operators. Results indicate that direct charging scenarios lead to significantly higher peak loads (up to 1286 kW) and costs (around 370 k€), highlighting their inefficiency under unmanaged operation. In contrast, smart charging reduces peak loads by approximately 47% and overall costs by around 74%, showcasing its potential for cost-effective grid-friendly operation. Two different V2G scenarios were tested based on the impact of discharged power accounted for in peak costs, though it enables energy discharge back to the grid, the benefits remain modest under current assumptions due to tight operational constraints and limited incentives. The study emphasizes the value of smart optimization and appropriate market design in enhancing the flexibility and cost efficiency of public EV charging systems. Full article

With an exploratory survey administered to 101 alumni who voluntarily and anonymously participated, since its inception in 1999, in the social service program at the Yunus Center, at the Mexican public Autonomous University of Baja California (UABC), five core dimensions of entrepreneurship were assessed: learning, entrepreneurial intention, skill development, inspiration and confidence, and opportunity recognition. The findings indicate that engagement with social microentrepreneurs (marginalized and impoverished) during social service served as a facility for developing entrepreneurial skills and intentions. Over 87% reported increased inspiration, motivation, and confidence, and more than 88% identified entrepreneurial opportunities through their participation. That suggests that interaction with necessity-driven microentrepreneurs as role models can create an innovative, inclusive learning environment among university students, and a possible low-cost method approach for fostering social and economic entrepreneurship, according to the UN’s sustainable development goals SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth). Full article