Abstract:

Transitioning to low-emission technologies for carriers needs a huge investment, and subsidies have proven to be efficient tools in overcoming cost barriers. In this paper, we formulate game-theoretical models to study the impact of subsidies on carbon emission reduction with green shippers in a price-competitive environment. Equilibrium solutions for three scenarios are derived and numerical analysis is conducted. Results indicate that (1) Government subsidies are effective and advantageous for decarbonization with carriers’ competition, but will lower service prices, profits and social welfare; (2) Intensified price competition leads to the increase in carbon emission, service prices and social welfare, while decreasing demands and profits in some scenarios; (3) Shippers’ green preferences have a positive effect on carbon emission reduction, profits and social welfare. Our findings can provide valuable managerial insights for both the government and shipping companies in promoting a more sustainable environment.

Abstract:

Background and Objective: Alzheimer’s disease (AD) is a challenging neurodegenerative disorder to diagnose, necessitating innovative solutions for early detection and classification. Traditional diagnostic methods often lack sensitivity or scalability, highlighting the need for advanced approaches. This study proposes a dual-model framework integrating an Artificial Neural Network (ANN) and a Convolutional Neural Network (CNN) to enhance diagnostic accuracy. Methods: The framework combines two AI models. The ANN was trained on clinical data from 1,200 patients, incorporating 31 demographic, symptomatic, and behavioral features, to assess Alzheimer’s risk. The CNN analyzed 4,876 Magnetic Resonance Imaging (MRI) images to confirm the diagnosis and classify the disease into four stages: mild demented, moderate demented, very mild demented, and non-demented. Grad-CAM visualizations enhanced interpretability, offering clinically relevant insights. Results: The ANN model achieved an accuracy of 87.08% in assessing Alzheimer’s risk, while the CNN model excelled with a 97% accuracy in disease staging. Grad-CAM visualizations highlighted critical regions in the MRI images, enhancing the transparency and reliability of the diagnostic process. The results demonstrate the complementary strengths of both models in providing a comprehensive diagnostic solution. Conclusion: The integrated ANN-CNN framework shows promise in revolutionizing Alzheimer’s diagnostics by combining clinical and imaging data for accurate detection. While limited by MRI availability and variability in clinical data, the framework underscores AI's potential in advancing neurodegenerative disease diagnosis. Future directions include integrating wearable technology and lightweight CNNs to improve scalability, accessibility, and early intervention.

Abstract:

Introduction: In Ethiopia, there has been considerable recent investment and prioritization in the maternal health program. However, coverage rates have been low and stagnant for a long time, indicating the existence of systemic utilization barriers. Therefore, it is fundamental to synthesize the current body of knowledge to successfully address these problems and enhance program effectiveness to increase antenatal care (ANC) uptake. Methods: We conducted a scoping review of the literature. Using various combinations of search strategies, we searched Pubmed/Medline, WHO Library, ScienceDirect, Cochrane Library, Google Scholar, and Google for this review. Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) were used to conduct the review. We included studies that used any study design, data collection, and analysis methods related to antenatal care utilization. Results: A total of 76 studies, national surveys and estimates were included in this review. The analysis revealed that ANC utilization coverage varied greatly by region, from 27% in Somali to 90.6% in the Oromia region, with significant disparities in socioeconomic status, access to healthcare, and vaccination knowledge. Ten priority research areas covering various aspects of the national ANC services were identified through a comprehensive review of the existing body of knowledge led by experts using the Delphi method. Conclusion: The barriers to recommended ANC service utilization differ depending on the context, suggesting that evidence-based, locally customized interventions must be developed and implemented. This review also identified evidence gaps, focusing on health system-related utilization barriers at the lower level, and identified additional research priorities in Ethiopia’s ANC service. The first step in developing and executing targeted program approaches could be identifying coverage of ANC services utilization among those with disadvantages.

Abstract:

Background: Previous primary studies reported controversial findings on the association between predictors and antenatal care (ANC) service use. Therefore, we aimed to provide pooled predictors of ANC service use among women of reproductive age in Ethiopia.Methods: All observational studies done in Ethiopia between 2002 and 2022 were included in this review. Studies were systematically searched from PubMed, Medline, CINAHL, EMBASE, Google Scholar, and Google. We conducted a database search from June 1-31, 2023. The Newcastle-Ottawa scale (NOS) tool was utilized for quality assessment (risk of bias). The review was registered in the PROSPERO register with the registration number CRD42022322940. All data analyses were conducted by utilizing Stata version 17. A random-effects model was used to get the pooled predictors of ANC use. The publication bias was checked using a funnel plot and Egger's regression test. Results: A total of twenty-two studies with a total sample size of 25,671 were comprised for this review. Based on the NOS checklist assessment, we classified eight studies as low quality. The identified predictors of ANC use were highest wealth rank (AOR 1.92 [95% CI: 1.53 - 2.31]), formal women education (AOR 2.40 [95% CI: 1.75 - 3.06]), formal husband education (AOR 1.49 [95% CI: 1.36 - 1.66]), women age > 20 (AOR 1.75 [95% CI: 1.47 - 2.17]), mass media exposure (AOR 1.44 [95% CI: 1.21 - 1.66]), good maternal knowledge about the pregnancy complication (AOR 1.49 [95% CI: 1.11 - 1.88]), planned pregnancy (AOR 1.59 [95% CI: 1.28 - 1.91]), women autonomy (AOR 1.42 [95% CI: 1.23 - 1.62]), and positive husband attitude about the ANC service use (AOR 2.63 [95% CI: 1.47 - 3.79]). Conclusions: Several predictors have increased the ANC utilization, like wealth status, women's and their husbands' education, older/increasing women's age, media exposure, maternal knowledge about the pregnancy complications, planned pregnancy, women's autonomy to decide on household health care, and positive husband attitude about the ANC service utilization. Thus, the government and stakeholders should create women-focused economic reforms such as encouraging women's involvement in rural saving and credit cooperative organizations and productive safety net programs to increase their income, advocate ANC in mass media, and increase the mechanism of ANC service messages to reach the largest women of reproductive age groups.

Abstract: Background/Objectives: Dartmoor Estate Tea plantation in Devon, UK, is renowned for its unique microclimate and varied soil conditions, which contribute to the distinctive flavours and chemical profiles of tea. The chemical diversity of fresh leaf samples from different were assessed via samples collected from various garden locations within the plantation. Methods: Fresh leaf, which differed by location, cultivar, time of day, and variety, were analysed using Flow Infusion Electrospray Ionisation Mass Spectrometry (FIE-MS). Results: Random forest classification revealed no significant differences between Georgian N2 cultivar garden locations. However, a significant degree of variability was observed within four tri-clonal variants (Tocklai Variety) with TV9 exhibiting greater similarity to the Georgian N2 cultivar compared to TV8 and TV11, while TV11 was found to be most like TV1. The intraclass variability in leaf composition was similar between the varieties. We explored the metabolic changes over the day in one variant (Camellia assamica Masters), yielding a model with a significant R2 value of 0.617 (p < 0.01, 3000 permutations). Starch and sucrose metabolism was found to be significant where the abundance of these chemical features increased throughout the day and then began to decrease at night.Conclusion: This research highlights the complex interplay of cultivars, geographical location, and temporal factors on the chemical composition of tea. It provides insightful data on the metabolic pathways influencing tea cultivation and production and underscores the importance of these variables in determining the final chemical profile and organoleptic characteristics of tea products.

Abstract: In Namibia, informal settlements are usually upgraded by a participatory process that works to provide inhabitants with land tenure security through the Flexible Land Tenure Act (FLTA), followed by the provision of access to basic services. The pilot FLTA implementation case is the upgrading of Freedom Square settlement in Gobabis, which was a unique woman-led process. This research analyzes both the experiences of the women participating during the process as well as the immediate and long-term perceived impacts on their lives. The empirical data was collected through interviews and a focus group discussion with experts and key participants in the development process. Findings shed light on the unresolved socio-economic challenges that the participating women had faced including the influence of other stakeholders on their involvement and changing family dynamics throughout. The main goals of receiving land tenure and service provision were partially fulfilled. However, the long-term impact of the process on women is widely varied from how it was initially envisioned. The results show that in order for participatory land tenure processes to become inclusive a stronger gender-mainstreaming becomes necessary. It also emphasizes the alignment of goals of all stakeholders as a key factor for long term success.

Abstract: The Coffea canephora species has been gaining prominence in national coffee production due to its high productive potential, adaptability, and beverage quality potential. Productive genotypes and clones of Coffea canephora with sensory quality adapted to irrigated systems in the Savanna region are pressing demands, aligned with technological innovation. In this context, the aim of this study was to characterize Coffea canephora (Conilon) clones based on agronomic and chemical traits of the beans and to assist in selecting promising materials for use in the genetic improvement program of irrigated Coffea canephora in the Savanna. During the 2019/20 and 2020/21 harvest seasons, 33 and 35 Coffea canephora genotypes, respectively, were evaluated for productivity, morpho-agronomic traits, and concentrations of chlorogenic acid, sucrose, caffeine, citric acid, and trigonelline in raw beans. The data were subjected to cluster analysis based on the Canberra genetic distance matrix, and grouping was performed using Ward's method. The means were subjected to non-parametric univariate analysis using the Kruskal-Wallis test. In the first year, five groups were defined, with Group G1 showing the best rank numbers for the evaluated traits. In the second year, six groups were identified, with Group G6 standing out for morpho-agronomic traits associated with productivity and Group G5 excelling in the levels of chemical compounds evaluated, as well as productivity and physical grain characteristics. The genotypes L3.L16.P6 (22) and L4.L25.P123 (31), present in the groups that stood out in both years, were identified as promising, showing high potential for the genetic improvement program of irrigated conilon coffee in the Savanna, in both morphoagronomic and grain quality aspects.

Abstract:

This study explores the strategies employed by organizations to build resilience in global supply chains amidst disruptions. As global supply chains face increasing volatility due to factors such as geopolitical instability, natural disasters, and regulatory changes, it is critical for organizations to adopt strategies that ensure continuity and minimize the impact of such disruptions. The research adopts a qualitative approach, utilizing in-depth interviews with 27 supply chain professionals from various industries to understand the key factors contributing to supply chain resilience. The study identifies several key strategies that organizations use, including diversification of suppliers and production locations, the adoption of advanced technologies such as artificial intelligence, machine learning, and real-time monitoring tools, and the importance of strong collaboration and communication with stakeholders. Additionally, the research highlights the role of organizational culture, leadership, and risk management practices in fostering a resilient supply chain. The findings suggest that companies that proactively manage risks, invest in technology, and establish strong collaborative relationships are better equipped to respond to disruptions and ensure operational continuity. Furthermore, the study emphasizes the importance of external factors such as regulatory changes and environmental disruptions in shaping supply chain resilience. The research concludes that building resilience is an ongoing process that requires continuous adaptation, proactive risk management, and strategic foresight to ensure that organizations can navigate the complexities and uncertainties of the global supply chain environment.

Abstract: It has long been clear that mitochondria play important roles in metastatic disease, including regulatory contributions. Nonetheless, our knowledge in this area was too fragmentary to be of practical clinical use. However, over the last decade a robust community of investigators has extended our knowledge such that it is practical to begin to build testable theories. Moreover, these theories can plausibly give clinicians actionable opportunities to effectively attack advanced, currently treatment-resistant carcinomas. Our goal here is to contextualize and review important features of this recent new data base. We will also illustrate the kind of testable speculative theories that might be built on this foundation. Specifically, we will explore the evidence that many or most advanced, treatment-resistant tumors converge on a uniform state in which mitochondria play a universal, indispensable regulatory role (Figure 1 [1]). Speculative hypotheses of this form are robustly testable/falsifiable. Moreover, such theories suggest a specific novel approach to clinical attack on advanced, currently treatment-resistant carcinomas.

Abstract: Recurrent pregnancy loss (RPL) is defined as the occurrence of two or more consecutive pregnancy losses before 24 weeks of gestation. It affects 3-5% of women who are attempting to conceive. RPL can stem from a variety of causes and is frequently associated with psychological distress and a diminished quality of life. In contrast, recurrent implantation failure (RIF) refers to the inability to achieve a successful pregnancy after three or more high-quality embryo transfers or at least two instances of egg donation. RIF shares several causative factors with RPL. The immunological underpinnings of these conditions involve alterations in uterine NK cells, a reduction in M2 macrophages and myeloid-derived suppressor cells, an increased Th1/Th2 ratio, a decreased Treg/Th17 ratio, the presence of shared ≥3 HLA alleles between partners, and auto-immune disorders. Various therapeutic approaches have been employed to address these immunological concerns, achieving varying degrees of success, although some therapies remain contentious within the medical community. This review intends to explore the immunological factors implicated in RPL and RIF and to analyze the immunological treatments employed for these conditions, which may include steroids, intravenous immunoglobulins, calcineurin inhibitors, anti-TNF antibodies, intralipid infusions, granulocyte colony-stimulating factor, and lymphocyte immunotherapy