Search Results (116)

Debit and credit card payments have become the preferred method of payment for consumers, replacing paper checks and cash. However, this shift has also led to an increase in concerns regarding identity theft and payment security. To address these challenges, it is crucial to develop an effective, secure, and reliable payment system. This research presents a comprehensive study on payment card fraud detection using deep learning techniques. The introduction highlights the significance of a strong financial system supported by a quick and secure payment system. It emphasizes the need for advanced methods to detect fraudulent activities in card transactions. The proposed methodology focuses on the conversion of a comma-separated values (CSV) dataset into quick response (QR) code images, enabling the application of deep neural networks and transfer learning. This representation allows leveraging pre-trained image-based architectures to provide a layer of privacy by encoding numeric transaction attributes into visual patterns. The feature extraction process involves the use of a convolutional neural network, specifically a residual network architecture. The results obtained through the under-sampling dataset balancing method revealed promising performance in terms of precision, accuracy, recall, and F1 score for the traditional models such as K-nearest neighbors (KNN), Decision tree, Random Forest, AdaBoost, Bagging, and Gaussian Naive Bayes. Furthermore, the proposed deep neural network model achieved high precision, indicating its effectiveness in detecting card fraud. The model also achieved high accuracy, recall, and F1 score, showcasing its superior performance compared to traditional machine learning models. In summary, this research contributes to the field of payment card fraud detection by leveraging deep learning techniques. The proposed methodology offers a sophisticated approach to detecting fraudulent activities in card payment systems, addressing the growing concerns of identity theft and payment security. By deploying the trained model in an Android application, real-time fraud detection becomes possible, further enhancing the security of card transactions. The findings of this study provide insights and avenues for future advancements in the field of payment card fraud detection. Full article

Forest ecological compensation policies (FECPs) are a key institutional arrangement for balancing ecological conservation and farmers’ development needs in national parks. Existing research has often treated such policies as a homogeneous whole, failing to clearly reveal the mechanisms through which different policy types affect farmers’ livelihoods, while also paying insufficient attention to complex property-rights settings. This study takes Wuyi Mountain National Park—a typical representative of collective forest regions in southern China—as a case study. Based on 239 micro-survey datasets from farming households and employing the mprobit model and moderating effect models, it investigates the influence, mechanisms, and heterogeneity of farmers’ livelihood capital in terms of their livelihood strategy choices under the moderating roles of “blood-transfusion” and “blood-making” FECPs. The results show the following: (1) Among the sample farmers, livelihood strategies are distributed as follows: pure agricultural type (31.8%), out-migration for work type (20.5%), and commercial operation type (47.7%). (2) Farmers’ livelihood capital has a significant impact on their livelihood strategy choice, with different dimensions of capital playing distinct roles. (3) FECPs follow differentiated moderating pathways. “Blood-transfusion” policies emphasize compensation and buffering functions, reducing farmers’ livelihood transition pressure through direct cash transfers; “blood-making” policies reflect empowerment and restructuring characteristics, activating physical assets and reshaping the role of social capital through productive investment. Together, they constitute a complementary system of protective security and transformative empowerment. Accordingly, this study proposes policy insights such as building a targeted ecological compensation system that is categorized, dynamically linked, and precise; innovating compensation fund allocation mechanisms that integrate collective coordination with household-level benefits; optimizing policy design oriented toward enhancing productive capital; and establishing robust monitoring, evaluation, and adaptive management mechanisms for dynamic FECPs. Full article

The article presents a blockchain-based architecture for decentralized electricity trading that tokenizes energy delivery rights and cash-flows. Energy Attribute Certificates (EACs) are implemented as NFTs, while buy/sell orders are encoded as ERC-1155 tokens whose tokenId packs a time slot and price, enabling precise matching across hours. A clearing smart contract (Matcher) burns filled orders, mints an NFT option, and issues two ERC-20 assets: PT, the right to consume kWh within a specified interval, and YT, the producer’s claim on revenue. We propose a simple, linearly increasing discounted buyback for YT within the slot and introduce an aggregating token, IndexYT, which accumulates YTs across slots, redeems them at par at maturity, and gradually builds on-chain reserves—turning IndexYT into a liquid, yield-bearing instrument. We outline the PT/YY lifecycle, oracle-driven policy controls for DSO (e.g., transfer/splitting constraints), and discuss transparency, resilience, and capital efficiency. The contribution is a Pendle-inspired split of electricity into Principal/Yield tokens combined with a time-stamped on-chain order book and IndexYT, forming a programmable market for short-term delivery rights and yield derivatives with deterministic settlement. Full article

South Africa’s land reform program is a cornerstone of efforts to redress historical injustices, guided by the 1997 White Paper on Land Reform Policy and structured around restitution, redistribution, and tenure reform. Three decades into implementation, this study systematically reviews the policy performance from 1994 to 2024, focusing on these pillars and related governance measures. Despite repeated policy revisions and extensive public debate, significant gaps persist between objectives, such as equitable access, tenure security, and poverty reduction—and actual outcomes. Using PRISMA guidelines, 94 peer-reviewed articles were selected from Scopus (1994–2024) alongside key policy documents and official reports. Evidence shows that land reform has consistently fallen short of its targets. Restitution claims remain largely cash-based, undermining tenure security, while redistribution has transferred less than 14% of agricultural land, far below the 30% target. Beneficiaries under the Proactive Land Acquisition Strategy (PLAS) often hold insecure lease agreements, and most households in former homelands lack title deeds, perpetuating vulnerability. The weak institutional capacity, poor coordination, and inadequate post-settlement support further constrain progress. The review concludes that the most fundamental policy priority is establishing a unified national framework that guarantees secure land tenure through the issuance of title deeds, complemented by integrated post-settlement support and transparent beneficiary selection. Strengthening tenure security is essential for enabling investment, improving livelihoods, and achieving equitable and sustainable land reform. Full article

Convertible bond financing has gained significant traction in China’s capital market, yet it poses financial risks, particularly for highly leveraged firms. This study investigates how corporate financial traits influence the decision to issue convertible bonds, challenging the direct applicability of Western theoretical frameworks in China’s unique institutional context. We employ a natural experiment design, constructing a binary logistic regression model to analyze data from Chinese A-share listed companies that issued convertible bonds, corporate bonds, seasoned equity offerings, or rights offerings between 2022 and 2023. Our results reveal a paradox: contrary to risk-transfer theory, firms with lower leverage exhibit a stronger propensity to issue convertible bonds. Instead, motives are driven by high profitability, operational inefficiencies, and robust operating cash flow generation—traits that align with signaling and backdoor equity theories. The study identifies China’s convertible bond market as a dual-track system where regulatory screening distorts classical motives while market frictions amplify the role of convertible bonds in resolving information asymmetry. We conclude with targeted policy implications for regulators and corporate treasurers to enhance market efficiency and governance. Full article

Carbon programs often assume that uniform cash transfers are sufficient to change land use, yet the design of benefits may be the controlling factor. We test payment complementarity—the coordinated use of cash and community benefits—in the International Small Group and Tree Planting Program across Kenya, Tanzania, Uganda, and India. Using administrative and survey data from 8432 participants, we classify realized mechanisms into cash-only, alternative-only, and mixed categories, and examine their associations with conservation adoption and land-use intensity. Mixed arrangements are associated with 73% higher conservation farming adoption (68.4% vs. 36.6% under cash-only) and greater tree density (281 vs. 215 and 115 trees/ha for cash-only and alternative-only, respectively). Formal tests reject simple averaging, consistent with super-additive effects. Adoption of mixed mechanisms clusters in districts that exceed an organizational participation threshold (approximately 38.9%), suggesting peer exposure and social learning. Gender-disaggregated patterns indicate that women receiving alternatives (predominantly in mixed regimes) manage nearly three times as many trees as their cash-only peers and are the only subgroup surpassing the USD 2/day poverty threshold. Each alternative arrangement benefits an average of 167 community members; accounting for spillovers implies an approximate 191-times village-level multiplier. Mixed designs require greater administrative effort but deliver larger community returns. We report associations, not causal effects, and employ controls, fixed effects, matching, and stability checks to probe our selection. Policy implications are immediately clear: outcome-based standards that permit mixed payments, credit spillovers, and paired flexibility with safeguards (transparent negotiation, verified delivery, documented consent) can multiply the land-use impact of climate finance. The results are associative rather than causal and generalize primarily to contexts with similar institutional prerequisites, including established organizational capacity and program rules permitting benefit negotiation. Full article

The construction industry faces significant payment processing challenges characterized by delays, disputes, and cash flow constraints affecting contractors. Traditional systems rely on fragmented, paper-based processes lacking transparency and real-time integration between project progress and financial transactions. This paper proposes a decentralized application that integrates BIM 5D capabilities with Solana blockchain technology for automated construction payment processing, called DB5D. The framework consists of several components: a web-based 3D viewer utilizing Autodesk Forge for BIM visualization, construction schedule integration from planning software, Solana blockchain programs using Program-Derived Address (PDA) and Cross-Program Invocation (CPI) for secure payment processing, and decentralized document management through InterPlanetary File System (IPFS) with Content Addressable Archives (CAR) compression. The system enables direct linkage between measurable project progress and automated payments by allowing stakeholders to extract quantities from BIM models, record construction task completion with supporting documentation, and trigger blockchain-based token transfers upon client approval. Comprehensive validation involving construction industry professionals confirms the framework’s practical viability. It demonstrates significant improvements in payment transparency, administrative efficiency, and scalability compared to existing blockchain implementations, while enabling economically feasible micro-payments throughout project lifecycles. Full article

This paper investigates the role of proportional reinsurance as a practical and flexible tool for managing demographic risk in life insurance, with a focus on its impact on both the Solvency Capital Requirement (SCR) and expected profitability. While much of the existing literature focuses on mortality modeling or longevity-linked reinsurance instruments, this paper proposes a novel framework for analyzing traditional proportional reinsurance structures within the Solvency II market-consistent valuation environment. The framework integrates proportional reinsurance into the valuation of liabilities and the calculation of Solvency Capital Requirement, beginning with an outline of cash flow structures and their valuation under Solvency II principles. A key contribution is the introduction and decomposition of the net of reinsurance Claims Development Result (CDR), which allows us to assess the dual impact of reinsurance on risk mitigation and profit transfer. Through numerical analysis, we show how proportional reinsurance can effectively reduce capital requirements while quantifying the trade-off in expected profit transferred to the reinsurance company, with insights into how different reinsurance treaties affect capital efficiency and profitability. Full article

The primary objective of this study is to assess the techno-economic feasibility of an innovative solar energy generation system with a rainwater collection feature to generate electrical energy and meet irrigation needs in agriculture. The proposed system is designed for an agricultural area (Gonyeli, North Cyprus) with high solar potential and limited rainfall. In the present study, global rainfall datasets are utilized to assess the potential of rainwater harvesting at the selected site. Due to the lack of the measured rainfall data at the selected site, the accuracy of rainfall of nine global reanalysis and analysis datasets (CHIRPS, CFSR, ERA5-LAND, ERA5, ERA5-AG, MERRA2, NOAA CPC CMORPH, NOAA CPC DAILY GLOBAL, and TerraClimate) are evaluated by using data from ground-based observations collected from the Meteorological Department located in Lefkoşa, Northern Cyprus from 1981 to 2023. The results demonstrate that ERA5 outperformed the other datasets, yielding a high R-squared value along with a low mean absolute error (MAE) and root mean square error (RMSE). Based on the best dataset, the potential of the rainwater harvesting system is estimated by analyzing the monthly and seasonal rainfall patterns utilizing 65 different probability distribution functions for the first time. Three goodness-of-fit tests are utilized to identify the best-fit probability distribution. The results show that the Johnson and Wakeby SB distributions outperform the other models in terms of fitting accuracy. Additionally, the results indicate that the rainwater harvesting system could supply between 31% and 38% of the building’s annual irrigation water demand (204 m³/year) based on average daily rainfall and between 285% and 346% based on maximum daily rainfall. Accordingly, the system might be able to collect a lot more water than is needed for irrigation, possibly producing an excess that could be stored for non-potable uses during periods of heavy rainfall. Furthermore, the techno-economic feasibility of the proposed system is evaluated using RETScreen software (version 9.1, 2023). The results show that household energy needs can be met by the proposed photovoltaic system, and the excess energy is transferred to the grid. Furthermore, the cash flow indicates that the investor can expect a return on investment from the proposed PV system within 2.4 years. Consequently, the findings demonstrate the significance of this system for promoting resource sustainability and climate change adaptation. Besides, the developed system can also help reduce environmental impact and enhance resilience in areas that rely on water and electricity. Full article

Low dietary diversity is a key driver of undernutrition and remains a significant public health challenge in low- and middle-income countries. This study evaluated the effect of nutritional counselling and the provision of livestock feed, aimed at sustaining milk production during dry periods, on the dietary diversity of women and children in a pastoralist setting. Methods: A cluster randomized controlled trial was conducted among households in Laisamis subcounty, north-eastern Kenya, which were assigned to one of three arms: (1) an intervention arm providing livestock feed during critically dry periods, (2) an intervention arm providing livestock feed plus enhanced nutritional counselling (provided once a week, covering topics including hygiene and sanitation, breastfeeding, maternal nutrition, immunization and complementary feeding) or (3) a control arm. The dietary diversity of mothers and children was assessed every six weeks over two years. Panel difference-in-difference regression models were used to estimate intervention effects on dietary outcomes including child minimum dietary diversity (MDD), minimum acceptable diet (MAD), women’s dietary diversity (MDD-W) and food security. Results: A total of 1734 households participated (639 in arm 1, 585 in arm 2, and 510 in the control arm). The provision of livestock feed alone had significant gains in child MAD (OR 1.20; 95% CI 1.08–1.34), child MDD (OR 1.15; 1.11–1.20), and MDD-W (OR 1.10; 1.01–1.19) whereas combined livestock feed with counselling, reduced child food poverty (OR 0.89; 95% CI 0.81–0.99), increased child MAD (OR 1.39; 1.22–1.52), and improved MDD-W (OR 1.21; 1.16–1.28) relative to control. Neither intervention increased child minimum meal frequency relative to control. Purchasing livestock was associated with higher odds of meeting dietary-diversity indicators but a lower meal frequency (OR 0.80; 0.80–0.90); in contrast, cash-transfer receipt was linked to reduced odds of achieving child MDD (OR 0.90; 0.87–0.94), child MAD (OR 0.95; 0.85–0.97), and women’s MDD (OR 0.73; 0.54–0.89). Conclusions: Livestock feed provision sustains milk consumption and improves dietary diversity in pastoralist populations. When combined with nutritional counselling, these interventions strengthen the link between animal and human health, with important implications for food security. Full article

In 2024, 28% of the global population experienced moderate or severe food insecurity. The State of Food Security and Nutrition in the World (SOFI) 2024 report underscores that adequate and sustained financing is critical to achieving global food security and improved nutrition outcomes. Grounded in the entitlement theory, this study examines how financial inclusion can reinforce the relationship between entitlements and food security. The study conducts a systematic review research methodology to collect, interpret, and integrate 84 studies. The findings of the paper include a thematic map and a conceptual framework. The thematic map highlights the major themes of the research area. The conceptual framework illustrates how financial inclusion enhances key entitlements such as production, trade, labor, and aid, which help achieve the four dimensions of food security: availability, accessibility, utilization, and stability. The study contributes theoretically by extending both entitlement and capability theory, showing how financial services improve access to food and strengthen people’s capabilities. On the policy front, the study recommends enhancing digital infrastructure in rural areas, promoting sustainable agriculture, empowering women, and encouraging millet production through targeted subsidies and cash transfer schemes. The study also suggests future research directions to help address its limitations, such as the lack of empirical testing of the proposed relationships. Full article

This study seeks to identify the factors driving household food insecurity in Cameroon during the COVID-19 pandemic, examine the effects of coping strategies on household resilience, and explore complementarities among these strategies. We used data from the COVID-19 panel surveys conducted by the National Institute of Statistics of Cameroon. Three models are estimated: an ordered logit model for food insecurity factors, a logit model for the impact of coping strategies, and a multivariate probit model for complementarities. The findings reveal that food insecurity is exacerbated by conflict, socio economic shocks (e.g., loss of employment, crop theft), and price hikes. About 28.59% of households are resilient, mainly due to past savings, cash transfers, free food, and in-kind transfers. The study emphasizes the importance of social and governmental support to mitigate food insecurity during crises, and underscores the need for monitoring socio-economic conditions during pandemics and other crises. Full article

Irrigation areas in arid regions are vital production areas for grain and cash crops worldwide. Grasping the temporal and spatial evolution of planting configurations across several years is crucial for effective regional agricultural and resource management. In view of problems such as insufficient optical images caused by cloudy weather in arid regions and the unclear spatiotemporal evolution patterns of the planting structures in irrigation areas over the years, in this study, we took the Santun River Irrigation Area, a typical arid region in Xinjiang, China, as an example. By leveraging long time-series remote sensing images from Sentinel-1 and Sentinel-2, the spectral, index, texture, and polarization features of the ground objects in the study area were extracted. When analyzing the index characteristics, we considered several widely used global vegetation indices, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), and Global Environment Monitoring Index (GEMI). Additionally, we integrated the vertical–vertical and vertical–horizontal polarization data obtained from synthetic aperture radar (SAR) satellite systems. Machine learning algorithms, including the random forest algorithm (RF), Classification and Regression Trees (CART), and Support Vector Machines (SVM), were employed for planting structure classification. The optimal classification model selected was subjected to inter-annual transfer to obtain the planting structures over multiple years. The research findings are as follows: (1) The RF classification algorithm outperforms CART and SVM algorithms in terms of classification accuracy, achieving an overall accuracy (OA) of 0.84 and a kappa coefficient of 0.805. (2) The cropland area classified by the RF algorithm exhibited a high degree of consistency with statistical yearbook data (R² = 0.82–0.91). Significant differences are observed in the estimated planting areas of cotton, maize, tomatoes, and wheat, while differences in other crops are not statistically significant. (3) From 2019 to 2024, cotton remained the dominant crop, although its proportional area fluctuated considerably, while the areas of maize and wheat tended to remain stable, and those of tomato and melon showed relatively minor changes. Overall, the region demonstrates a cotton-dominated, stable cropping structure for other crops. The newly developed framework exhibits exceptional precision in categorization while maintaining impressive adaptability, offering crucial insights for optimizing agricultural operations and sustainable resource allocation in irrigation-dependent arid zones. Full article

The present study examines the relationship between the cash conversion cycle (CCC) and profitability in major service sectors in Greece, including hotels, education, healthcare, transfer—rentals, and information technology. Using financial data from 343 public limited companies for the year 2023, the research applies descriptive statistics, Pearson correlation analysis, and ANOVA to evaluate how CCC components affect profitability, measured through return on assets (ROA). The results indicate that firms across all sectors maintain a negative CCC, suggesting efficient liquidity management, with the education sector exhibiting the most negative CCC due to upfront tuition payments. Additionally, the study finds a significant positive correlation between CCC and ROA, implying that firms with longer negative CCC values tend to achieve higher profitability. However, firm size, measured by total assets and sales, does not appear to influence CCC efficiency or profitability. These findings underscore the importance of industry-specific financial strategies and highlight the role of CCC optimization in enhancing financial performance. The study contributes to the literature on working capital management and provides practical implications for improving liquidity and profitability in service-oriented firms. Full article

This study investigates the potential contamination of cash register employees in the Slovak Republic with 148 selected pharmaceuticals, illicit drugs, and their metabolites. Of these, 42 substances were detected, and it was found that the target group—cashiers—regularly handle large volumes of banknotes, increasing their exposure to contaminants compared to the general population. This study revealed that commonly prescribed and over-the-counter medications significantly contribute to the contamination of cash registers. This study found that cashiers exhibited notably higher detection rates of antibiotics, including penicillin-V (2×), azithromycin (23×), and erythromycin (up to 64×), than the general population. Additionally, there was an alarming increase in illegal substances, with methamphetamine levels rising fivefold and cocaine up to fifteenfold. This study highlights a broader environmental concern, suggesting that routine handling of contaminated banknotes may lead to the transfer of micropollutants. Furthermore, personal hygiene practices, particularly handwashing, could play a role in introducing pharmaceuticals and narcotics into wastewater, potentially contributing several milligrams of contaminants daily. Full article