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Bayesian Inference and Sensitivity Analysis of Dengue Transmission in Sudan
Get PDFBackground: Dengue fever is a significant public health concern in Sudan as well as tropical regions. Mathematical and statistical methodologies are crucial for comprehending its transmission dynamics and informing effective control tactics.
Methods: We developed a two-population compartmental model to capture dengue transmission between humans (susceptible, infected, recovered and disease- induced mortality) and mosquito vectors (susceptible and infected). Using the next-generation matrix approach, we derive an explicit expression for the basic re- production number (R0). For the assessment of critical epidemiological parameters such as the mosquito biting rate, probability of human to vector transmission, recovery rate, and dengue-induced fatality rate, Bayesian inference was employed. To evaluate the robustness of these findings, a global sensitivity analysis was performed utilizing Latin hypercube sampling and partial rank correlation coefficients.
Results: Posterior estimates indicated R0 1.25 (95% credible interval: 1.11– 1.40), with the model showing strong agreement with case report data (R2 = 0.93). Sensitivity analysis showed that the mosquito biting rate as well as the transmission probability were the main drivers of epidemic potential with recovery and dengue- induced mortality exhibiting inhibiting negative effects on transmission.
Conclusions: The results suggest that transmissible vector factors are an important component for dengue transmission in East Sudan. The preferred method for the control of future outbreaks is expected to concentrate on mosquito bites/human vector transmission
Advances in Fire Retardancy of Polymeric Nanocomposites and Applications
Get PDFEmerging advancement in nanotechnology have facilitated the embedment of nanomaterials (NMs) such as graphene and derivatives, carbon nanotubes and derivatives, nanowires, and so on, within polymeric matrices to attain enhanced properties, especially fire retardancy, in polymeric nanoarchitectures (PNC) for multifarious applications. In thermal interface materials (TIM) for electronic gadgets, notable fire hazards are often ignored, whereas PNC exhibiting electromagnetic interference (EMI) shielding are frequently subjected to accidental fires. Furthermore, fire warning sensors with capability of rapidly exposing fire dangers in combustible materials plays a key role in mitigating or entirely eliminating fire disasters in most scenarios. Moreover, the escalating evolution of electronic gadgets in the fifth-generation (5G) era has made superlative fire safety, thermal stability and high-performance of PNC highly imperative. Nanowires are one-dimensional (1-D) nanostructures possessing a high length to diameter aspect ratios, unique flame retardant (FR), mechanical, electrical, thermal, and optical properties. The inclusion of different forms of nanowires within polymeric matrices has tremendously enhanced the flame retardancy (F-R) of nanowire@polymeric nanoarchitectures (N-PNC) thereby enlarging their scope of applications. Therefore, this paper presents advances in flame retardancy of nanowire polymeric nanoarchitectures
Doodly-Based Multimedia Instructional Intervention and Academic Achievement of Undergraduate Students with Learning Disabilities in Educational Technology
Get PDFTraditional instructional strategies may not provide the essential elements necessary for students with learning disabilities (LDs) to learn effectively. This ultimately leads to decreased motivation and underachievement. Since Doodly-based multimedia has been scientifically proven to enhance learning outcomes, one wonders if such effects could be replicated on the academic achievement of students with LDs. The study explored the impact of Doodly-based multimedia instructional intervention (DBMII) on the academic achievement of undergraduate students with LDs in Educational Technology (EdTech). The research employed a 2x2 quasi-experimental factorial design, with pre- and post-tests to explore the effects of DBMII. The census sampling technique was used to draw a sample of 38 (22 males and 16 females) third-year special education students with confirmed cases of LDs. The data collection used the Educational Technology Achievement Test (ETAT). The validation was conducted by three specialists and had a reliability coefficient of 0.82 using the Kuder-Richardson 21 formula, before it was administered, marked, scored, coded, and analyzed. Analysis of Co-Variance (ANCOVA) was employed to test the hypotheses, setting the significance threshold at the 0.05 level. The findings revealed a statistically significant beneficial effect of DBMII on the academic achievement of undergraduate students with learning disabilities in EdTech. Also, gender did not significantly influence educational achievement, and no interaction effects between gender and Doodly-based multimedia instructions were observed. It was concluded that Doodly-based multimedia instructions have a statistically significant beneficial effect on the academic achievement of undergraduate students with LDs in EdTech, without any significant influence of gender
Can Crypto Currencies Challenge Sovereign Currencies? A Multidisciplinary Overview of Opportunities and Risks
Get PDFConsidered as a niche phenomenon, a kind of technological folklore, which could disappear overnight, cryptocurrency has been the subject of few multidisciplinary analyses to understand how a series of numbers, supported by no power to impose its use, could constitute a currency? The review of the available literature reveals a state of knowledge scattered in the different disciplines that are interested in it. The objective of this article is to remedy this by aggregating essential historical, economic, legal and technological knowledge developed in the study and analysis of this technical-financial innovation. The aim is to examine the opportunities, challenges and risks of using cryptocurrencies as an alternative to sovereign currency, through a nuance between the optimism of those who see in cryptocurrencies liberation from the monetary constraints of States, and the hostility of those who see in these innovations a utopian monetary system or a lever of incitement to crime. A concluding discussion will expose the trend and some recommendations for supporting eventual implementation with the least criminogenic effect
Removal of Acid Fuchsin Dyem from Industrial Effluents Using Green Synthesized Copper Oxide Nanoparticles and their Characterization
No full textNanoparticles are the spearheads of the rapidly expanding field of nanotechnology. Development of the green synthesis has gained extensive attention as a reliable, sustainable and eco-friendly protocol for synthesizing a wide range of metal and metal oxide nanoparticles. The synthesized copper oxide nanoparticles were characterized by ultraviolet visible spectroscopy (UV-Vis), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FT-IR), Scanning Electron Microscope (SEM), Transmission Electron Microscope (TEM), Energy Dispersive X-ray (EDX). Adsorption parameters such as Initial dye concentration, Adsorbent dosage, pH, contact time, and temperature have also beenstudied. Adsorption isotherms namely Langmuir, Freundlich, Temkin are used to test the adsorption data; Kinetic studies such as pseudo first order, pseudo second order and thermodynamic parameters were also evaluated. To synthesis copper oxide nanoparticles, a green chemical strategy is employed in the current work. It is an easy, affordable, and effective alternative method. The green copper oxide nanoparticles that were made may be a good choice for removing dye from coloured aqueous solution due to their strong dye adsorption ability. CuO nanoparticle prepared from above mentioned routes is expected to have more extensive applications such as chemical sensor, catalytic, gas sensor, semiconductor etc. This method is the most viable in terms of energy, time, and simplicity. This procedure resulted in the production of copper Oxide nanoparticles on a huge scale
Comparative Analysis of Machine Learning Models for Early Heart Disease Diagnosis
Get PDFHeart disease remains among the leading causes of death worldwide, and its early detection ability can be the difference between life and death. In this research, we investigate the capability of machine learning—namely Support Vector Machines (SVM)—to predict the occurrence of heart disease based on regular clinical information. We used the Cleveland Heart Disease dataset, which contains critical patient data like age, gender, blood pressure, cholesterol level, type of chest pain, and other crucial health factors. Prior to creating our model, we pre-processed and cleaned the data by dealing with missing values, changing categorical variables into numerical form, and scaling the features for uniformity. We then optimized the SVM model using grid search and cross-validation to make it run at its optimal level. The resulting model had an accuracy of 86.41% in the test set and performed better than other popular models such as logistic regression and random forest.
The significant about this work is the potential for applying it in practical situations. An SVM-based program such as this could be a second opinion for physicians or integrated into early diagnostic tools—most helpful in clinics with limited access to specialists. It's progress toward smarter, data-driven healthcare that enables faster and more precise diagnoses.
There's still potential for expansion, using bigger, more varied datasets or incorporating real-time patient information could further enhance the model. But this research demonstrates that with the proper data and methodology, machine learning can be a useful tool in the early diagnosis of heart disease
Inclusion of Students with Borderline Cognitive Impairment in Secondary Schools: Challenges and Coping Strategies
No full textBackground: The challenges of managing students with borderline cognitive impairment in an inclusive classroom are enormous. Therefore, there is a need for appropriate coping strategies to foster the successful inclusion of students with borderline cognitive impairment in the day-to-day classroom activities.
Aim: This study examines the challenges facing the inclusion of students with Borderline Cognitive Impairment (BCI) and the coping strategies often adopted by these students in the Ogoja Education Zone of Cross River State, Nigeria.
Method: The study adopted a descriptive survey design. One hundred and sixty-nine students with BCI in twenty (2) regular secondary schools were selected, using the purposive sampling technique. The instrument for the study was a questionnaire titled "Academic Challenges and Coping Mechanism of Students with Borderline Cognitive Impairment Questionnaire (ACCMSBCIQ 0.67).
Results: The study revealed that inclusive education for students with BCI at the secondary school level in the Ogoja Education Zone of Cross River State is hindered by a complex web of interconnected challenges. The study also revealed that students with BCI adopt several coping strategies to remain included in the secondary education program in the study area.
Recommendation: Based on the findings of the study, the researchers recommend that the government and other stakeholders should organize adequate training on the inclusion of students with BCI for all secondary school teachers in Cross River Stat
Algorithms of Air Law - Connecting the Dots
Get PDFRapid developments in the aviation industry bring to bear the compelling need to reexamine algorithms in air law. For example, the advent of advanced air mobility (AAM), typified by eVTOL aircraft and algorithm-driven systems, compels an evaluation of traditional air law. Rooted in treaties such as the Paris Convention of 1919 and the Chicago Convention of 1944, air law has evolved incrementally in response to the growth of global aviation. However, the rapid emergence of technologies such as autonomous aircraft, drones, and quantum computing necessitates a transformative approach. Algorithms, once peripheral to legal considerations, now lie at the heart of this evolution. These systems provide not only a means of optimizing safety and efficiency but also an avenue for addressing the intricate interplay of liability, governance, and ethical considerations.
The Council of the International Civil Aviation Organization (ICAO) stands at the forefront of this transformation. Leveraging its role as a global standard-setter, the Council can convene stakeholders to develop adaptive legal instruments, emphasizing cybersecurity protocols, liability apportionment, and equitable access. By fostering interdisciplinary collaboration and engaging in proactive governance, ICAO can ensure that AAM integrates innovation with fairness and resilience.
Ultimately, the integration of algorithms into air law represents more than a technological shift; it demands a philosophical reorientation. The algorithm emerges not only as a tool but also as a metaphor for interconnectedness and adaptability. Air law, in embracing this paradigm, must transcend prescriptive rules to become a living, dynamic framework capable of guiding aviation into an equitable, sustainable future. Only through such an approach can we ensure that the skies remain navigable, secure, and just, reflecting a balance between technological progress and human values. This article examines the issues involved
Possibilities of Desensitisation to Pet Allergens: Prevention of Allergic Reactions in Children and Adults
No full textPurpose: The article aimed to study modern approaches to the desensitization of pet allergens, focusing on advanced therapeutic and diagnostic methods for managing and preventing allergic reactions in children and adults.
Material and Methods: The study used a theoretical analysis of scientific sources covering the molecular mechanisms of allergy, modern diagnostic methods, and therapeutic strategies.
Results: Global trends in the prevalence of allergies were examined, the role of molecular diagnostics and the latest desensitization methods, such as allergen-specific immunotherapy (ASIT), was assessed, and a comparison of traditional and innovative treatment approaches was made. The findings of the study demonstrate that pet allergy is a globally widespread problem affecting 20-30% of the population of developed countries, with the highest rates among urban populations. It has been established that molecular mechanisms, in particular the role of Fel d 1 and Can f 1, are key to developing an allergic reaction, which opens up opportunities for developing new therapeutic approaches. Modern diagnostic approaches, including molecular component analysis, basophil activation test, and multiplex tests, accurately detect allergens and determine severe reaction risk. Numerous clinical researches have indicated that ASIT utilizing modified allergens reduces allergy symptoms in people with Fel d 1 and Can f 1 sensitization.
Conclusion: These results highlight the importance of introducing modern diagnostic methods and personalized therapy in the treatment of animal allergies. This opens up new prospects for improving patients’ lives and reducing the socioeconomic burden of allergic diseases
Assessing the Effectiveness of Compliance Programs Through the Use of the Metaverse and Blockchain
Get PDFThis paper examines how blockchain technology and the Metaverse can address persistent challenges in corporate compliance, with a focus on mitigating criminogenic asymmetries—such as regulatory arbitrage and opacity in cross-border transactions—through decentralized, transparent solutions. By contrasting the U.S. and Italian legal frameworks, we highlight the limitations of retrospective compliance evaluations and propose blockchain-enabled innovations, including immutable audit trails, smart contracts for automated enforcement, and Decentralized Autonomous Organizations (DAOs) to decentralize governance and embed compliance into protocol design. The Metaverse offers a simulated environment for stress-testing compliance protocols against emerging risks, while criminological theories (e.g., global anomie, legal-illegal interfaces) contextualize regulatory gaps in digital economies. We argue that DAOs, as digital-native entities, could revolutionize compliance by replacing hierarchical oversight with algorithmic governance, though challenges like jurisdictional fragmentation and identity verification persist. The study underscores the need for adaptive regulatory frameworks to harness these technologies while balancing transparency, accountability, and privacy