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Unveiling abrocitinib: A thorough examination of the 2022 USFDA-approved treatment for atopic dermatitis (AD)
No full textAbrocitinib stands as a targeted therapy, functioning as an inhibitor of Janus kinase (JAK) 1. This pharmaceutical advancement has been meticulously crafted to address the challenges of moderate to severe atopic dermatitis (AD), a prevalent skin ailment in developed nations. Introduced in 2022, Abrocitinib emerged as a cutting-edge addition to its therapeutic category, gaining approval for utilization within the United States. Diverging from its predecessors in the realm of moderate to severe AD treatment, Abrocitinib distinguishes itself through its heightened specificity. Moreover, its tablet formulation facilitates straightforward administration, offering diverse dosage options. An additional noteworthy feature is its applicability to individuals aged 12 and above, making it an option for alleviating symptoms in this demographic. Within this comprehensive assessment, key aspects such as the biological target of the drug, developmental strategies, mode of operation, pharmacokinetics, pharmacodynamics, clinical trial insights, contraindications, potential interactions with other medications, and adverse reactions are examined. In light of the overarching perspective and available clinical evidence, Abrocitinib emerges as a promising orally bioavailable therapeutic, authorized for treating AD. Notably, it gained its initial approval in Japan for patients aged 12 years and older, marking a significant advancement in the realm of dermatological care
Policy semantic networks associated with ICT utilization in Africa
No full textInformation and communications technology (ICT) research finds that greater utilization of ICTs leads to economic growth. This effect has led developing countries to implement initiatives to increase available infrastructure and its use. While ICT policy is a likely facilitator of increased ICT use, analysis of policy documents has been limited due to the difficulties of manual content analysis. Semantic network analysis of policy documents enables the identification of concepts associated with greater ICT use, which contributes to theory and offers policy guidance. This study combined text analysis with structural equation modeling to identify the semantic correlates of greater ICT utilization for 605 policy documents across 51 African countries. Our findings show that more abstract, analytical content is associated with greater ICT utilization, consistent with a communication and information processing model
Designing of Te-doped ZnO and S-g-C3N4 /Te-ZnO nano-composites as excellent photocatalytic and antimicrobial agents
No full textToday, it is crucial but challenging to develop a narrow bandgap photo-catalyst that can eliminate contaminants when exposed to visible light. In this work, we synthesized the ZnO, Te-doped ZnO, and s-g- C3N4 assisted Te-doped ZnO nanoparticles by a susceptible and economical co-precipitation method. Different techniques were employed to characterize the compounds like XRD confirms the formation of pure wurtzite phase present within ZnO nanoparticles. The morphology of produced nanoparticles was studied using FESEM, which reveals that ZnO nanoparticles develop into spherical particles whereas doped particles take the form of nano-sheets with a regular hexagonal pattern. The FT-IR and UV visible spectrum was used to measure the functional groups and optical properties of compounds. The doped compound shows the maximum efficiency of degradation against methylene blue dye under sunlight exposure. Furthermore, E. coli and S. aureus were used as test subjects for the antibacterial activity of these synthetic compounds. On the other hand, the greatest antifungal activity of S-g-C3N4/Te-ZnO against C. albicans was calculated to be 44.6 mm, and 26.5 mm against E. salmonicolor. Te-doped ZnO nanoparticles with the aid of S-g-C3N4 showed remarkable photocatalytic and antimicrobial activities
Application of electrically conductive membrane contactor in the carbon dioxide stripping process for mitigation of fouling induced by flue gas
No full textCarbon capture utilization & storage (CCUS) process is a promising technology for reducing greenhouse gas emissions. However, the biggest challenge in commercializing CCUS is reducing energy consumption during the CO2 stripping stage. Membrane contactors have been developed to reduce energy consumption and improve CO2 stripping performance. However, traditional polymer-based membranes are vulnerable to damage by combustion residues such as oil and grease. To address this problem, electrically conductive membranes (ECMs) have been developed to enable efficient electrochemical reactions for anti-fouling purposes. This study investigated the anti-fouling performance of an electrically conductive membrane contactor (ECMC) for CO2 stripping. Surface modification with a two-layered ECM resulted in the superior electrical conductivity and CO2 stripping flux compared to other ECMs. Electrostatic repulsion effectively mitigated fouling by 92.1 % compared to non-charged ECMC by preventing the attachment of oil and grease, but it was not observed a significant effect in high oil and grease concentrations. The electrochemical oxidation process when applying a high voltage improved anti-fouling performance, and the O2 sweep gas mode greatly maintained the CO2 stripping flux at 95.2 % with high oil and grease concentrations. Furthermore, the feasibility of the ECMC was demonstrated by comparing the predicted total energy consumption per CO2 amount under actual operating conditions. In conclusion, ECMC improved the energy efficiency of CO2 stripping by providing high anti-fouling performance in CCUS
AO-HRCNN: archimedes optimization and hybrid region-based convolutional neural network for detection and classification of diabetic retinopathy
No full textDiabetic Retinopathy (DR) primarily affects a set of lesions in the eyes, causing retinal degeneration and loss of vision. The DR features serve as a crucial component for ophthalmologists to diagnose DR at an earlier stage. This paper presents an automatic DR screening tool using a hybrid GAN-RCNN architecture formulated to categorize and identify different DR grades from the fundus images captured at various resolutions. The hybrid GAN-RCNN architecture is formulated by replacing the discriminator in the GAN with the RCNN classifier. The RCNN model can handle the complex inter-class and intra-class variations present in the fundus retina images and classify them into different classes such as mild, moderate, severe, and nonproliferative DR. The RCNN model not only extracts the pixels present in the fundus image but also focuses on the significant relationship that exists between different DR classes. The Archimedes optimization Algorithm (AOA) is used to optimize the different GAN and RCNN hyperparameters. When compared to the existing techniques the proposed model offers an accuracy of 99%, 98.5%, and 99.4% in the APTOS, Kaggle, and Messidor datasets which is comparatively high. The experimental outcome reveals that the introduced model serves as a concrete baseline for the diagnosis and treatment of DR patients
The impact of the SVB collapse on global financial markets: Substantial but narrow
No full textWe investigate the impact of the collapse of Silicon Valley Bank on global financial markets, identifying significant but narrow impacts. Abnormal returns are significant and negative for US equities, global banks, Bitcoin, as well as GCC equities. However, abnormal returns are insignificant for most fiat currencies, metals, and energy markets. That the SVB collapse had minimal effects on these markets suggests that the SVB event had a major but constrained effect on the global financial system, affecting significantly a small number of markets while largely ignoring others. Results highlight possible contagion points with regard to reactions to banking stress
The role of blockchain-enabled traceability, task technology fit, and user self-efficacy in mobile food delivery applications
No full textThe working pattern of the food industry has entirely changed with the emergence of mobile food delivery apps (MFDAs), which deliver an innovative method to interact with and offer high-quality services to customers. This study pinpoints the imperative factors affecting the customer\u27s attitude and continued intention in light of the task technology fit (TTF) model. The required data were collected from MFDA users and analyzed by the structural equation modeling technique via Amos-23 and SPSS-22. The results confirm that customer rating, ordering review, food tracking, navigational design, and user self-efficacy positively impact TTF. Further, self-efficacy positively moderates the relationship between visual design and TTF, navigational design and TTF, and food tracking and TTF. Moreover, TTF positively influences attitude and continued intention, and in turn, attitude positively influences continued intention. Additionally, blockchain technology (BT) enabled traceability positively moderates the relationship between TTF, attitudes, and continued intention to use MFDAs. The developers of MFDAs should consider how customers perceive BT-enabled traceability and take steps to embrace it to increase customer trust in MFDAs. Furthermore, the theoretical and managerial applications are explained in detail so that developers can offer what MFDA users need
Guest editorial: Digital transformation in supply chains: challenges, strategies and implementations
No full text“Energize your life” virtually: Lessons learned from online gardening workshops
No full textVirtual gardening classes that started in response to the COVID-19 pandemic continue to attract participants. Little is known about characteristics that improve their effectiveness and enable participants to continue gardening. The purpose of this project was to pilot test a nutrition-focused, virtual container gardening program, obtain feedback on its content and delivery, and identify features that may impact the long-term effectiveness of virtual gardening interventions. Gardening curricula were adapted for a virtual program offering adults five, 1-h sessions. At baseline, participants (n = 12) were very interested in consuming produce (mean score 4.6 ± 1.0 out of 5) and consumed fruit and vegetables at a mean of 2.6 ± 1.4 times/day. There were no significant differences in consumption based on prior gardening experience (p =.6). Participants requested recipes that were inexpensive, quick, and easy to adapt. They suggested resources on storing and preparing produce, garden care, and getting seeds as support. Although the ability to rewatch recorded workshops and participate remotely were convenient, follow-up with asynchronous participants, inadequate lighting, over-watering, indoor pests, and failure of seeds to germinate indoors were challenges. Future work should identify ways to enhance social support and interaction among virtual workshop participants and determine how virtual gardening programs affect produce consumption among those with limited intake
Spillovers between positively and negatively affected service sectors from the COVID-19 health crisis: Implications for portfolio management
No full textThis study empirically investigates and contributes new evidence to the ongoing topic of potential volatility spillover, efficient portfolio management, and hedging strategies. We investigate the connectedness between the travel and leisure sector (which was negatively affected by the COVID-19 pandemic) and healthcare, technology, and telecommunications sectors (which were positively impacted by the pandemic). We selected these four service sectors because they have been impacted by the pandemic and are also crucial for the world\u27s economy. We separately perform a connectedness analysis for four regions: Europe, Eastern Europe, Asia-Pacific, and North America. The main findings indicate a rise in return and volatility spillovers during the COVID-19 outbreak in the selected sectors. Healthcare, telecommunications, and technology sectors are major transmitters of volatility shocks to the travel and leisure sector during the crisis. The portfolio analysis shows that investors should include healthcare, telecommunications, and technology sectors in their equity portfolios to reduce investment risk and protect expected returns during the pandemic. Hedge ratios vary over crisis and non-crisis periods, highlighting the option of adjusting hedging strategies during turbulent and stable periods. The study also evaluates efficient portfolio management strategies shaped during the COVID-19 pandemic using the estimated results of the DCC-GARCH approach