Month: January 2025

Abstract

The increasing complexity and demands of modern power grids necessitate advanced solutions for real-time monitoring and control. This paper presents a novel cross-domain optimization framework designed to enhance the reliability and cost-efficiency of smart grid monitoring systems through strategic IoT sensor placement and communication network design. Utilizing the IEEE 57-bus system and utilizing MATPOWER for power grid simulations alongside NS-3 for communication network modeling, the framework integrates both domains to achieve optimal deployment configurations. Our approach ensures extensive grid observability and robust data transmission by iteratively refining sensor placement based on communication link costs and customizing routing policies. The proposed framework, Synergistic Optimization Framework for Enhanced Reliability (SOFER), demonstrates significant improvements in key performance metrics. Specifically, we achieve 99.5% system reliability, measured by Mean Time Between Failures (MTBF) exceeding 10,000 h. The system exhibits exceptional robustness, maintaining full functionality with tolerance to single component failures and 80% functionality during multi-component failures. Network performance metrics indicate an average data transmission latency of 50 milliseconds, bandwidth utilization efficiency of 85%, and a packet loss rate of less than 0.5%. The optimization algorithm converges rapidly within 30 iterations, providing high-quality solutions that ensure grid observability with 100% coverage and effective redundancy. Comparative analysis with existing methods highlights a 25% improvement in cost reduction and 20% enhancement in reliability. These results underscore the efficacy of the integrated approach, making it a optimal solution for modern smart grid systems. Compared to traditional approaches, SOFER demonstrates a 20% improvement in system reliability, a 25% reduction in overall deployment costs, and a 28.6% decrease in data latency, positioning it as a high-performance solution for modern smart grids. This framework paves the way for future advancements in smart grid monitoring, emphasizing the critical interplay between IoT sensor networks and communication infrastructure.

Abstract

Oropouche fever is an increasingly significant health concern in tropical and subtropical areas of South and Central America, and is primarily spread by midge vectors. The Oropouche virus (OROV) was first identified in 1955 and has been responsible for numerous outbreaks, particularly in urban environments. Despite its prevalence, the disease is often under-reported, making it difficult to fully understand its impact. OROV typically causes febrile illness characterized by symptoms such as headaches, muscle pain, and, occasionally, neurological issues such as meningitis. The ability of the virus to thrive in both forested and urban areas has raised concerns regarding its potential spread to new regions, particularly in the context of climate change. This paper delves into the epidemiology, clinical features, and transmission patterns of OROV, shedding light on the difficulties in diagnosing and managing the disease. The absence of specific treatments and vaccines highlights the urgent need for continued research and development of targeted public health strategies. Advancements in molecular diagnostics and vector control strategies can mitigate Oropouche fever’s impact. However, a comprehensive public health approach involving increased surveillance, public education, and cross-border collaboration is needed, especially as the global climate crisis may expand vector habitats, posing risks to previously unaffected regions.

Abstract

Mergers and acquisitions (M&A) with financial technology (fintech) companies can be an effective way for firms to obtain new technologies and capabilities. However, the market reaction to fintech M&A announcements has received limited attention in the empirical academic literature. This study assesses the impact of fintech M&As on stock returns and examines whether macroeconomic variables influence the abnormal return of fintech M&As. Using event study analysis, we found that fintech M&A announcements generate a significant positive short-term abnormal return. Furthermore, we demonstrated that macroeconomic parameters, including Gross domestic product (GDP) growth, inflation rate, the share of services in GDP, and aggregate export growth, positively affect abnormal returns. In contrast, private investment, consumer spending, and an economy’s size negatively influence fintech M&As’ abnormal returns.

Abstract

All African countries participate in the African Continental Free Trade Area (AfCFTA) to boost intra-African trade to accelerate structural transformation. At the same time, increasing geopolitical tensions around the world are pressuring countries to ‘reshore’ by retreating from engagement in Global Value Chains (GVCs) towards Regional Value Chains (RVCs). High values for RVC indices would indicate that African exports have a high import content of intermediates originating in Africa and that exports destined to other African countries undergo further processing, an indication of structural transformation. The paper uses the EORA Multi-regional Input–Output (MRIO) data over 1995–2022 to present new, more comprehensive measures of participation in supply chains at several levels: across countries, regions, and sectors. Comparisons are with countries (e.g. China or India) and aggregates of countries (e.g. Europe, Americas, Asia) engaged in deep market integration. Measures for 50 African countries are compared with those for other regions. On average, African exports have a low content of imported intermediates and undergo further transformation in importing countries before reaching final consumers. Compared with other regions, African countries mostly engage in supply chain trade with countries outside Africa, displaying low values of RVC indices. In sum, compared to other regions, African Regional Economic Communities (RECs) and other regional trade agreements across the continent have failed to launch intra-African trade. The paper then explores the determinants of participation in supply chains. At the world level, from 1995 to 2022, geography factors and policy-related instruments like openness (captured by tariffs) and Foreign Direct Investment (FDI) stimulate GVC trade. For Africa, low tariffs and FDI are positively associated with regional supply chain activity, an indication that AfCFTA implementation should stimulate intra-African trade.

Abstract

The drought-prone left bank of river Ganges (Padma) in the north-western part of Bangladesh is facing challenges of water scarcity. Unfortunately, here the study on insightful numerical modeling for interaction for surface water (SW) of rivers and nearby groundwater (GW) of aquifer system is lacking. So, present study has been carried out on simulation of GW flow characteristics, its dynamic exchanges with SW and prediction of long-run scenario using Visual MODFLOW software. The study reveals that groundwater level (GWL) follows topography of the area, and discharge capacity varies with time due to reduction in the river water flow immediately after the rainy season, and the over-exploitation of groundwater due to increasing irrigation demand. Higher GWL head reveals higher discharging rate and its maximum velocity vectors also reflects major outflow towards river basins. At present, the simulated total deficit of water resource is 2,044,000 L/year. Higher declining rate of GWL also happens due to reducing amount of groundwater recharge due to rainfall scarcity in comparison to demand. The groundwater scenario for the period 1980–2020 and predicted up to 2050 reveals the steadily declining trend (nearly four times) along with irrigation demand for country’s food security, and the area will face severe water scarcity if appropriate adaptation measures will be not be taken timely. Finally, this river and the aquifer model presents a window for stronger understanding the relationship of Surface Water-Ground water system and thereby finding the potential causes of groundwater depletion in this drought prone area that will help to develop appropriate water resources management strategy in this region. It differs with the concept of supply-demand scenario from widely marked nature-based solution to seasonal freshwater storage capture dubbed the ‘Bengal Water Machine - GWM’.

Abstract

There are huge differences in the levels of social and economic development among the world’s regions, and the gaps between regions have not narrowed despite rapid economic development. Understanding the impact of factors other than political factors on socioeconomic development can help all countries to find solutions that go beyond ideology. To test this hypothesis, we selected 295 Chinese cities at the same administrative level and used the entropy weighting method, a spatial econometric model, and a geographical and temporal weighted regression model to identify the reasons for regional development differences. Unlike the methods used in previous studies, this approach let us identify the relative importance of many forces that are simultaneously driving development and their variation among regions. We found that industrial upgrading, industrialization, fiscal decentralization, marketization, and education were important factors to promote regional economic growth, whereas economic growth decreased with increasing elevation and environmental pollution. These were the primary factors that explained why some places were more highly developed and other places lagged behind. To narrow the regional development gap, it will be necessary to upgrade a region’s industrial structure, improve market mechanisms, improve the education system, and implement targeted and differentiated development policies that account for each region’s unique needs. Our results will provide a reference not only for China but also for the world to support efforts to eradicate poverty and achieve more regionally balanced development.

Abstract