Search Results (2,190)

To accurately analyze the dynamic response and driving mechanism of forest carbon sequestration in the core area of the Loess Plateau’s Returning Farmland to Forestry Project, this study takes the Beiluo River Basin as the research area. Using spatial autocorrelation, gravity model, a geodetector, and spatiotemporal geographically weighted regression models, it analyzes the spatiotemporal evolution of forest carbon sequestration and the spatial heterogeneity of its influencing factors based on 2000–2023 data. The results show the following: (1) Forest carbon sequestration in the basin increased by 13.55% from 2000 to 2023; its spatial pattern shifted from “middle reaches concentration” to “stable middle reaches core plus significant upper reaches growth”, with the gravity center moving “southeast then northwest”. (2) Forest carbon sequestration had significant positive spatial correlation, with hotspots in soil–rock mountain forest areas and cold spots in ecologically fragile or high-human-activity areas. (3) Natural ecological factors dominated forest carbon sequestration evolution, socioeconomic factors enhanced synergy, and evapotranspiration and NDVI had significant impacts. (4) Factor impacts had spatiotemporal heterogeneity, such as the decaying positive effect of precipitation and the “positive-negative-equilibrium” change in forestry value-added. This study provides scientific guidance for basin and Loess Plateau ecological restoration and “double carbon” goal achievement. Full article

The new availability of powerful Artificial Intelligence (AI) as an everyday copilot has instigated a new wave of attack techniques, especially in the area of Social Engineering (SE). The possibility of generating a multitude of different templates within seconds in order to carry out an SE-attack lowers the entry barrier for potential threat actors. Still, the question remains whether this can be done using openly available tools without specialized expert skill sets on the attacker side, and how these compare to each other. This paper conducts three experiments based on a blueprint from a real-world CFO fraud attack, which utilized two of the most used social engineering attacks, phishing and vishing, and investigates the success rate of these SE attacks based on utilizing different available LLMs. The third experiment centers around the training of an AI-powered chatbot to act as a social engineer and gather sensitive information from interacting users. As this work focuses on the offensive side of SE, all conducted experiments return promising results, proving not only the ability and effectiveness of AI technology to act unethically, but also the little to no implied restrictions. Based on a reflection on the findings and potential countermeasures available, this research provides a deeper understanding of the development and deployment of AI-enhanced SE attacks, further highlighting potential dangers, as well as mitigation methods against this “upgraded” type of threat. Full article

In order to ensure the stability of the gravity heat pipe (GHP) heat exchanger in the mine return air waste heat recovery project and to explore the influence of the working fluid and filling ratio of the GHP on the heat transfer performance, this paper establishes a computational fluid dynamics (CFD) model of the GHP for mine return air waste heat recovery. The heat transfer characteristics and multiphase flow mechanism of the GHP with R22 and R410a working fluids at 30% to 80% filling ratios were studied using the VOF model from three aspects: two-phase flow, wall temperature, and thermal resistance. The validity of the model was verified through experimental data. The findings of the research indicate that the physical property parameters of the working fluid and the alterations in the filling ratio exert a substantial influence on the liquid-phase boiling heat transfer and the condensation process on the condenser wall. The CFD operation results demonstrate a high degree of congruence with the experimental data. The maximum deviation in the wall temperature is 2.9%. When the filling ratio is in the range of 50% to 60%, the axial distribution of the wall temperature tends to be flat. With regard to thermal resistance, both CFD and experimental results demonstrate a tendency of initially decreasing and subsequently increasing with increasing filling ratio. The average wall temperature of R410a GHP with a 50% filling ratio reached the highest value (20.3 °C), and the thermal resistance reached the lowest value (0.021 K/W), demonstrating superior heat transfer performance and excellent isothermal characteristics. Full article

This study investigates the relationship between capital intensity, debt financing, and profitability in non-financial firms in Oman over the period 2012–2022. Using a robust panel dataset of 76 firms, the research explores how capital structure dynamics influence firm performance across different firm sizes and industries. The findings reveal that capital intensity significantly enhances profitability, and debt financing further strengthens this effect, with variations observed across firm size and sector. The analysis also identifies a non-linear (concave) relationship between capital intensity and profitability, indicating that while moderate capital investment improves firm performance, excessive capital accumulation may lead to diminishing returns. Larger firms, with better access to financial resources, exhibit a stronger positive relationship between debt financing and profitability, while smaller firms face more challenges due to limited access to capital. Industry-specific results indicate that capital-intensive sectors, such as Energy and Industrials, demonstrate a more pronounced effect of capital intensity on profitability compared to less capital-intensive sectors. The study also incorporates the effects of the COVID-19 pandemic, showing its significant influence on firm performance, particularly in sectors with high debt exposure. By integrating non-linear effects, firm size, industry heterogeneity, and pandemic shocks, this study provides novel insights into capital structure management in emerging economies, offering implications for both corporate decision-makers and policymakers aiming to enhance financial access and optimize debt strategies across sectors. Full article

In this study, I used regression analysis to examine the relation between stock return dispersion from the market returns and market portfolio returns as a measure of herding behaviour in opportunistic insider traders from 2014 to 2024 in the USA. Opportunistic insiders place a trade in the same calendar month for at least three consecutive years. I found no evidence of statistically significant and negative relationship between return dispersions and market returns, either absolute or squared. This result implies that there is no herding behaviour. The results are robust to large stock price movements and changes in market volatility. My results are important for regulators and investors. Future research may involve the herding behaviour of insiders who follow trading plans. Full article

Background: Padel is currently played in more than 150 countries, leading to a substantial increase in performance analysis research in recent years. Examining shot effectiveness (winners vs. errors) provides valuable information for players and coaches to better understand match and competition performance. Objectives: This study aimed to (i) analyze winners, forced errors, unforced errors, and forced error generators according to set results and serving situation; (ii) examine differences in shot types and effectiveness between set-winning and set-losing pairs; and (iii) identify differences in shot types that generate forced errors between set-winning and set-losing pairs. Methods: Data were collected from 41 professional matches (men’s and women’s) available on the World Padel Tour Finland Padel Open website. Descriptive (frequency and percentage) and inferential analyses (chi-square (χ²), Cramer’s V coefficient (Vc), subsequent Z-tests, and corrected standardized residuals (CSR)) were performed. Results: Pairs produced more winners and forced error generators when serving, while forced errors were more frequent when returning. Winning pairs achieved more winners (men: CSR = 7.7; women: CSR = 7.4), whereas losing pairs committed more errors (men: forced errors, CSR = 4.3; unforced errors, CSR = 3.8; women: forced errors, CSR = 4.8; unforced errors, CSR = 2.8). Additionally, winning pairs generated a higher proportion of forced errors (men: 56.5%; women: 60.0%) compared with losing pairs (men: 43.5%; women: 40.0%). Conclusions: These findings are crucial for coaches and players, as they provide insights into sex-specific technical and tactical patterns, thereby enhancing the effectiveness of training design and match preparation strategies. Full article

Investment in equity assets is characterized by high volatility, both in prices and returns, which poses a constant challenge for the efficient management of risk and profitability. In this context, investors continuously seek innovative strategies that enable them to maximize their returns within acceptable risk levels, in accordance with their investment profile. The purpose of this research is to develop a model with a high predictive capacity for equity asset returns through the application of artificial intelligence techniques that integrate genetic algorithms and neural networks. The methodology is framed within a technical analysis-based investment approach, using the Relative Strength Index as the main indicator. The results show that more than 58% of the predictions generated with the proposed methodology outperformed the results obtained through the traditional technical analysis approach. These findings suggest that the incorporation of genetic algorithms and neural networks constitutes an effective alternative for optimizing investment strategies in equity assets, by providing superior returns and more accurate predictions in most of the analyzed cases. Full article

Background/Objectives: Jumping is a common movement pattern, often used in testing for both performance monitoring and decision-making in return to sport. Current methods of assessing movement coordination are time-, technology- and expertise-dependent. The use of force–time curves to analyse the execution of the movement would provide an accessible and detailed analysis of movement. Methods: Thirty endurance runners and triathletes (18–40 years) completed five maximal countermovement jumps (CMJs) and five maximal standing broad jumps (SBJs). Participants were grouped (HIGH, MOD and LOW) according to the magnitude of the time interval between peak hip and peak knee extension velocity. A separate grouping according to the magnitude of the time interval between peak knee and peak ankle extension velocity was created. A one-way Statistical non-Parametric Mapping ANOVA, with alpha set at 0.05 and iterations at 10,000, was used to compare vertical ground reaction force (CMJ and SBJ), horizontal ground reaction force (SBJ) and resultant ground reaction force (SBJ) between the three hip–knee groups and a separate analysis for the three knee–ankle groups. Results: Significant differences were observed between time interval groups in both hip–knee coordination and knee–ankle coordination for both jump types (p < 0.001) at several regions of the force–time curves. Conclusions: The results suggest there is potential for statistical parametric mapping analysis to detect differences in movement coordination patterns from force curves. Further research is needed to help explain the differences observed in the curves for the kinematic groupings, to explore different combinations of hip–knee and knee–ankle kinematic patterns and to associate curve characteristics with performance indicators. Full article

Agrivoltaic (AV) systems are increasingly recognized as a strategy to enhance sustainable land management, yet their application in post-conflict settings remains underexplored. This study addresses this gap by evaluating AV deployment in two Colombian municipalities located in PDET/ZOMAC regions, using an integrated framework that expands the conventional Water–Energy–Food (WEF) nexus into the Water–Energy–Food–Soil–Climate–Communities (WEFSCC) nexus. The research combined GIS-based site characterization, crop yield and water balance modeling (contrasting traditional irrigation with hydroponics), and photovoltaic performance simulations for 30 kW systems, under conservative and moderate scenarios. Economic analyses included Net Present Value (NPV), Internal Rate of Return (IRR), and Free Cash Flow (FCL), with sensitivity tests for crop prices, yields, tariffs, and costs. Results indicate that AV can reduce crop irrigation demand by up to 40%, while generating 17 MWh/month of electricity per site. Cabrera exhibited higher profitability than Pisba, explained by yield differences and site-specific energy outputs. Comparative analysis confirmed consistency with experiences in Africa and Europe, while emphasizing local socio-environmental benefits. Conclusions highlight AV systems as resilient tools for sustainable land management in Colombia’s post-conflict regions, with actionable implications for land-use regulation, fiscal incentives, and international cooperation programs targeting rural development. Full article

The oil layers in the Dongying Formation offshore oilfield are severely contaminated. The near-wellbore reservoir pore throats are blocked, which seriously affects the development effect. It has become urgent to implement acidizing stimulation measures. However, the target reservoir is deeply buried, has high reservoir pressure, and is highly sensitive. These factors result in high pressure during acidizing operations, a long single-trip time for raising and lowering the tubing string, and high costs. Moreover, acid that is not promptly returned to the surface after acidizing can cause secondary pollution to the reservoir. This work proposes an integrated tubing string to perform reverse displacement and reverse squeeze. With this, acid can be injected into the formation through the annulus between the casing and tubing. The residual acid and its post-acidizing derivative residues are rapidly lifted to the surface by the reciprocating suction action of the return pump. Based on this, the structure and specifications of the acidizing-flowback tubing string are designed through the flow rate analysis method. The tubing string is mainly affected by mechanical effects, including buoyancy, piston effect, flow viscosity effect, helical bending effect, temperature difference effect, and expansion effect. The maximum deformations are 1.4 m, 1.9 m, 0.18 m, 2.7 m, 1.8 m, and 2.5 m, respectively. The total deformation is less than 3 m. Simulation results from three groups of oil wells at different depths indicate that the axial force of the tubing string ranges from 400 to 600 kN. The stress ranges from 260 to 350 MPa, deformation is 1.1–2.4 mm, and the safety factor exceeds 3.0. This can effectively ensure the safety of on-site operations. Based on the actual field conditions, the acidizing-flowback tubing string is evaluated. This verifies the effectiveness of the acidizing-flowback tubing string. This research provides an economical and efficient operation process for acidizing operations in the Dongying Formation offshore oilfield. It achieves the goal of removing reservoir contamination and provides guidance for the unblocking and stimulation of low-permeability and sensitive reservoirs in the middle and deep layers of offshore oilfields. Full article

This study presents a detailed evaluation of the energy performance and design optimization of a novel four-stage indirect evaporative cooler (IEC) enhanced with a supplementary humidifier, examined under the summer design conditions of Riyadh. Although previous research has demonstrated the system’s high thermal effectiveness, its energy efficiency—expressed through the coefficient of performance (COP)—and the influence of key design parameters have not been thoroughly explored. To address this gap, we integrate a validated thermal model with a comprehensive energy consumption model to assess the COP of the system under varying operational and geometric conditions. Results show that the baseline design achieves a maximum COP of 14.3. Through parametric optimization of heat exchanger depth and air velocity, the maximum COP increases to 20.4—a 43% improvement, associated with a supply temperature of 13.2 °C and specific water consumption of 2.5 kg/kWh at a return ratio of 0.3. The optimal parameters—a heat exchanger depth of 1.5 m and a humid-path air velocity of 1 m/s—ensure both high efficiency and practical feasibility. Overall, the findings highlight the considerable potential of the optimized multistage IEC system as a highly energy-efficient and sustainable alternative to conventional vapor-compression cooling technologies, contributing to reduced energy consumption and enhanced environmental sustainability in hot and dry climates. Full article

As the importance of energy efficiency and smart readiness in the building sector has been on the rise, the financial evaluation of smart-ready technologies (SRTs) remains a gap in this field. This study introduces a methodology that comparatively evaluates the cost–benefit relationship between 11 different SRTs across three European countries—Cyprus, Italy and The Netherlands. Key performance indicators (KPIs) for energy-focused aspects such as Country-Specific Energy Savings Potential (CSESP) and Seasonal Smart Efficiency Coefficient (SSEC) and financial aspects such as Smart Readiness Cost Index (SRCI), Labor Cost Impact Factor (LCIF), Return on Smart Investment (RoSI), and Smart Investment Break-Even Period (SIBEP) were used to quantify the performance of the SRTs. The results indicate that regional labor rates, energy pricing, and climatic conditions—as well as relative technology cost–benefit tradeoffs—play a significant role in the economic viability of smart-ready devices. Having low labor costs and energy pricing, Cyprus exhibited the most cost-effective outcomes among the three countries. Italy showed strong returns although the initial investments were higher. The Netherlands was observed to benefit the most from heating-oriented technologies. The study comes to the conclusion that regionally specific methods are necessary for the adoption of SRTs and that techno-economic performance cannot be assessed separately from local market dynamics. The proposed framework supports stakeholders and policymakers in smart building investment and planning by offering a scalable method for device-level benchmarking. These indicators are developed specifically for this study and are not part of the official EU SRI (Smart Readiness Indicator) methodology. Their inclusion supports device-level evaluation and complements ongoing efforts toward SRI standardization. This research directly addresses Sustainable Development Goal (SDG) 7 on Affordable and Clean Energy, as well as SDG 11 on Sustainable Development, by evaluating how smart-ready technologies can contribute to energy efficiency and decarbonization in buildings. Based on the results, further research is needed to expand the indicator framework to additional technologies, include building typology effects, and integrate dynamic factors such as CO₂ pricing and real-time tariffs. Full article

Large-scale transitions to eco-friendly vehicle fleets present complex capital budgeting challenges, requiring the integration of extensive operational data with financial modeling while balancing economic profitability and environmental sustainability. Traditional approaches often struggle to manage this complexity and quantify the inherent trade-offs. This study develops and applies an innovative integrated accounting-and-finance framework to evaluate the economic and environmental implications of green fleet transition projects, explicitly quantifying the trade-off between profitability and sustainability. Focusing on waste vehicle replacement of Iren Spa, a leading European multi-utility company, we employ the recently developed Split-Screen Approach, a unified accounting-and-finance framework grounded in the laws of motion and conservation. It automatically reconciles pro forma financial statements and generates internally consistent valuation metrics, eliminating the manual adjustments and inconsistencies of traditional models. Its built-in diagnostic checks and scalability for highly complex datasets overcome the manual adjustments and inconsistencies inherent in traditional financial models. We process 2303 inputs across multiple “green” scenarios. This methodology integrates an Engineering Model, describing fleet evolution, operating costs, and CO₂ reduction, with a HookUp Model, which serves to transform scenarios into well-defined projects. The latter model is then integrated with a Financial Model that generates pro forma financial statements, incorporates financing and payout policies, and assesses economic profitability through Net Present Value (NPV) and consistent accounting rates of return. Together, these elements form a robust framework for managing complex data integration and analysis. Our research reveals a fundamental trade-off: enhanced environmental sustainability (measured by Net Green Value, NGV), which quantifies CO₂ reduction, is achieved at the expense of economic profitability, measured by NPV. This financial sacrifice is captured by the Net Value Curve, a Pareto frontier, while the NPV-to-NGV ratio provides “shadow prices” for CO₂ reduction, revealing the financial cost per unit of sustainability gained. Based on 21 project scenarios and additional sensitivity analyses on financial inputs and energy prices, the results confirm a decreasing relationship between NGV and NPV. This study makes three main contributions: (1) it demonstrates the practical application of the Split- Screen Approach for capital budgeting under complexity, (2) it introduces the Net Value Curve framework as a useful tool for visualizing and quantifying the trade-off between profitability and sustainability, (3) it provides managers and policymakers actionable insights, supporting more informed decisions in green fleet transition planning where economic and environmental objectives may conflict. The findings provide managers and policymakers with a rigorous and transparent accounting-and-finance framework that enhances the reliability of capital budgeting decisions compared with traditional financial modeling, while offering a Paretian frontier for evaluating environmental trade-offs. Full article

The COVID-19 pandemic has severely affected Thailand’s economy, forcing many workers to return to their hometowns and engage in agricultural activities. Community-Based Tourism (CBT) has become a significant strategy to mitigate these effects by leveraging local cultural resources. This study aims to (1) assess the potential of cultural resources for tourism development in Koh Perd fishing village, Chanthaburi, Thailand, and (2) examine the determinants of revisit intentions among Thai tourists. To address the first objective, qualitative research was conducted through in-depth interviews with 15 Thai tourists, analyzed using coding analysis, while a quantitative survey of 400 respondents assessed the perceptions of cultural resources. The findings indicate that the village’s historic houses (Ruen Ran Kha) are perceived as the most valuable tourism assets, followed by cultural authenticity and aesthetics, respectively. For the second objective, data from 400 Thai tourists were analyzed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and multiple regression. The results reveal that destination attractions, marketing and accessibility, and safety and security are significant factors influencing revisit intentions. Full article

Industrial heritage is increasingly becoming an important resource for sustainable urban renewal. With the acceleration of deindustrialization and urban transformation, Adaptive Reuse (AR) is regarded as the core path connecting heritage protection and functional renewal. Balancing the diverse value dimensions of AR has also become a key research focus. However, existing research mostly focuses on financial returns and investment efficiency, ignoring the long-term impact of community space and cultural dimensions on economic feasibility; at the same time, culture is often simplified into a tool for asset appreciation and urban branding, lacking a systematic model that reveals the structural role of culture in economic feasibility. Therefore, this study constructs a multi-attribute decision-making framework that integrates economic performance, community space, and cultural value. Using Guangzhou Guanggang New City as a representative case, the Fuzzy Delphi Method (FDM), Analytic Network Process (ANP), and Grey Relational Analysis (GRA) were employed to screen and rank the highest-priority reuse schemes. The results show that the economic dimension holds the highest overall weight, followed by the community and cultural dimensions. This suggests that economic feasibility remains a key prerequisite for industrial heritage renewal, while cultural and community factors play an important supporting role in achieving long-term sustainability. This study provides a quantifiable assessment path for the adaptive reuse of industrial heritage and offers a basis for decision making in other cities seeking a balance between economic rationality and cultural sustainability. Full article