Cyprus International University (CIU; Turkish: Uluslararası Kıbrıs Üniversitesi) is an English-language private university in Northern Cyprus. It is located in the capital, North Nicosia and was established in 1997..
This study examines the relationship between currency devaluation and the volatility of Bitcoin returns and mining profitability from 2015 to 2025 in major mining hubs characterized by significant exchange-rate exposure and cost sensitivity. While prior literature has focused on demand-side volatility drivers, this research places greater attention on supply-side fluctuations through the exchange rates channel. Applying DCC-GARCH and Regime-Switching Copula methods, we demonstrate that depreciation of the local currency reduced mining costs, increased the Bitcoin return volatility, and its responsiveness to macro-financial linkages. These results underline the importance of USD hedging and dynamic taxation regimes for Bitcoin miners. The study progresses the modeling of volatility through incorporating the exchange rate elasticity into the analysis of market interdependence in the crypto-asset sector.
Nigeria is undergoing a rapid epidemiological transition marked by a growing burden of non-communicable diseases (NCDs) alongside persistent communicable diseases. This shift poses substantial challenges for population health, health system capacity, and socioeconomic development. This review aims to synthesize contemporary epidemiological evidence on the burden of NCDs in Nigeria, with emphasis on prevalence, mortality, disability adjusted life years (DALYs), temporal trends, and major risk factors. A structured narrative review was conducted using 127 peer reviewed articles and 15 national or authoritative reports (total N = 142 sources) sourced from PubMed, Scopus, Web of Science, African Journals Online, World Health Organization publications, and Global Burden of Disease studies published between January 2000 and December 2025. From 142 included sources (127 peer reviewed articles; 15 grey literature reports), we identified substantial heterogeneity in NCD prevalence estimates, with hypertension ranging from 18.6
In millimeter wave massive MIMO systems, hybrid beamforming and optimal antenna selection are essential for maximizing spectral efficiency and minimizing system latency. However, conventional beamforming approaches face challenges related to computational complexity and real-time performance. This paper proposes a novel deep learning framework using Long Short-Term Memory (LSTM) networks to streamline hybrid beamformer design and antenna selection. By framing the problem as a prediction and classification task, the LSTM processes the channel matrix to determine optimal subarray configurations and hybrid beamformers design, enhancing both efficiency and accuracy. To ensure robustness, the LSTM is trained on noisy channel matrices, addressing real-world variability in channel conditions. Experimental results demonstrate that the proposed LSTM-based approach achieves substantial improvements in spectral efficiency and computational complexity reduction compared to traditional beamforming methods, positioning it as a viable solution for high-performance millimeter wave MIMO systems.
This research has presented a discussion of related literature on decision support systems (DSS) and its role in production systems. The first part of the research presents DSS and how this has evolved until 2010. The next part of the research provides a discussion of the decision making process and the data mining phases as these relate to DSS. The last part of the research presents further discussion of DSS and various perspectives on the criteria that could be used for DSS. The criteria in the classification of DSS includes the following: user relationship; orientation; scope of use; type and frequency of decision making; mode of assistance; focus area; objective; capacity; degree of guidance; and, degree of non-procedurality. The research also included a discussion of industry 4.0, which is known as the fourth revolution in the industry.
Background/Objectives: Cervical cancer remains a major cause of morbidity and mortality among women worldwide, marked by stark geographic and socioeconomic disparities. Preventable via HPV vaccination and screening, progress toward elimination varies widely across and within countries. This narrative review synthesizes the epidemiology, including incidence, mortality, survival, and stage distribution, as well as risk factors and the coverage/equity of HPV screening and vaccination programs. Methods: Comprehensive searches were performed in PubMed, Web of Science, Scopus, and Google Scholar (no date restrictions; English only). Included were original epidemiological studies, systematic reviews, meta-analyses, and international reports on burden, risk factors, or prevention indicators. Data were qualitatively synthesized into three themes: epidemiological patterns, risk factors, and screening/prevention programs. Results: Persistent high-risk HPV infection causes nearly all cervical cancers, predominantly HPV16/18, with regional variation in other types. Strong co-factors include HIV immunosuppression, early sexual debut, multiple partners, high parity, long-term oral contraceptive use, and smoking. Inequalities in incidence, late diagnosis, and survival are driven by socioeconomic disadvantages, low education, rural residence, and poor health system access. Screening ranges from cytology/VIA to primary HPV testing, but coverage is low and inequitable in high-burden settings. HPV vaccination has expanded yet faces major gaps in low- and middle-income countries. Conclusions: Cervical cancer burden concentrates in low-resource and marginalized populations. Global elimination demands accelerated, equitable scale-up of HPV vaccination and screening, alongside health system strengthening and barrier reduction.
