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It is a hard task to strike a balance between extents of control a learner exercises and the amount of guidance, active or passive, afforded by the learning environment to guide, support, and motivate the learner. Adaptive systems strive to find the right balance in a spectrum that spans between self-control and system-guidance. They also concern a smoother shifting of the balance point during learning episodes in light of competing requirements from learning goals, learner capacity, instructional affordances, and educational theories, among others. This research investigates one of the extremes of this spectrum, where learners actively assume control and take responsibility for their own learning, while catering to individual preferences with little or no guidance from the e-learning environment. In this study, one unit material from an online Introduction to Java Programming course has been redesigned based on the proposed Learner-Directed Model for the experimental design study. The model is developed based on the exploration of two educational theories--Experiential-Learning Theory (ELT) and Self-Regulated Learning (SRL) Theory. The study involved a total of 35 participants (N = 35) divided randomly into one Experimental Group and one Control Group. They were assigned to either a Learner-Directed Model (Experimental Group) or a linear model (Control Group). Pre/post tests, survey, follow-up interview as well as log file analysis were instruments used for assessing students' domain knowledge, meta-knowledge, and their attitudes for their overall learning experience. The results of the study have revealed that there is a statistically significant higher level of overall learning experience and better learning attitudes compared to Control Group students who studied with e-learning components that are linear in nature and are without explicit associations with educational theories.

The purpose of this research is to deal with effective block chain framework for secure transactions. The rate of effective data transactions and the interoperability of the ledger are the two major obstacles involved in Blockchain and to tackle this issue, Cross-Chain based Transaction (CCT) is introduced. Traditional industries have been restructured by the introduction of Internet of Things (IoT) to become smart industries through the feature of data-driven decision-making. Still, there are a few limitations, like decentralization, security vulnerabilities, poor interoperability, as well as privacy concerns in IoTs. To overcome this limitation, Blockchain has been employed to assure a safer transaction process, especially in asset exchanges. In recent decades, scalable local ledgers implement Blockchains, simultaneously sustaining peer validations of transactions which can be at local or global levels. From the single Hyperledger-based blockchains system, the CCT takes the transaction amid various chains. In addition, the most significant factor for this registration processing strategy is the Signature to ensure security. The application of the Quantum cryptographic algorithm amplifies the proposed Hyperledger-based blockchains, to strengthen the safety of the process. The key has been determined by restricting the number of transactions that reach the global Blockchain using the quantum-based hash function and accomplished by scalable local ledgers, and peer validations of transactions at local and global levels without any issues. The rate of transaction processing for entire peers has enhanced with the ancillary aid of the proposed solution, as it includes the procedure of load distribution. Without any boosted enhancement, the recommended solution utilizes the current transaction strategy, and also, it's aimed at scalability, resource conservation, and interoperability. The experimental results of the system have been evaluated using the metrics like block weight, ledger memory, the usage of the central processing unit, and the communication overhead. [ABSTRACT FROM AUTHOR]

Background. To describe the existing pharmacological managements for Multisystem Inflammatory Syndrome in Children (MIS-C) in a systematic way, to identify the available pharmacological managements in MIS-C, evaluate its safety and efficacy and identify the best treatment procedures for practice recommendation. Methods. A systematic search using six databases was conducted on August 18, 2021, updated in January 26th 2023. Terminologies that were used in this search are children, MIS-C/PIMS and SARS-CoV-2. A PRISMA flow diagram was used to report the study selection process. Quality analysis was done based on NOS and GRADE tools. Data synthesis was conducted by extracting the information on drugs used, efficacy and side effects. Results. From the 32 articles included, a total of 2331 children with MIS-C were studied. The main pharmacological approaches were immunomodulatory therapy, i.e., intravenous immunoglobulin (IVIG) (77.3%), steroids (60.5%), and a combination of IVIG and steroids (41.3%). IVIG and steroids were found to be potentially effective and safe treatments for MIS-C. Combination of IVIG and steroids was found favorable in severe cases with higher recovery rate. Refractory treatments include second dose of initial treatment and biological response modifier drugs like anakinra, tocilizumab, infliximab. A small number of studies investigating supportive treatment consisted of vasoactive, inotropic and anticoagulation. The mortality rate was 1.28% and only three studies reported side effects from the treatment. Evidence of outcome from GRADE were mostly at moderate, low and very low levels. Conclusions. This review provides preliminary evidence to support the current standard treatment practices in managing MIS-C pharmacologically. However, comprehensive investigation is required using clinical trials to provide stronger outcome evidence. [ABSTRACT FROM AUTHOR]

Coronavirus 2 virus is responsible for the spread of the infectious disease COVID-19 (also known as Coronavirus disease). People around the globe who got infected with the virus experienced a respiratory illness that could become as serious as leading someone to lose their life. However, the upside of the pandemic is that it has led to numerous types of research and explorations, majorly in the medical science field. Since a systematic survey of previous research activities and bibliometric analysis gives a brief idea about such contributions and acts as a reference to future research, this study aims to cover the research related to COVID-19 in the computer technology domain. It is limited to the works accepted and accessible with the keywords – Covid-19, prediction, and pandemic, in the Scopus search engine to justify the scope of this survey. Further, the paper highlights a few prior works used for predictive analysis and presents a quantitative angle on their algorithms. Earlier works showcase Time Series Analysis using ARIMA/SARIMA models for predicting the vaccination rates, and Extreme Gradient Boosting (XGBoost), Xtremely Boosted Network (XBNet) Regression, and Recurrent Neural Network (RNN) for Confirmed, Cured, and Death cases. Amongst the algorithms used in the latter use case, XBNet regression performed better than XGBoost regressor. [ABSTRACT FROM AUTHOR]

Urolithiasis affects a significant portion of the global population, causing discomfort and pain. Unfortunately, effective drugs to treat this disorder are currently unavailable due to multiple mechanisms and an incomplete understanding of its causes. Consequently, drugs with multiple targets could be a safer and more effective remedy for treating urolithiasis. Moreover, the current treatment options are expensive and come with a risk of complications and stone recurrence. Therefore, an alternative treatment that can prevent stone recurrence and reduce associated symptoms is necessary. Seaweeds are a rich source of beneficial metabolites, like antioxidants, anti-inflammatory, analgesic, and enzyme-inhibitory properties. Advances in nanotechnology hold great promise for improving the therapeutic potential of these metabolites. However, the use of nanoparticles for treating urolithiasis has yet to be explored well, and only a few reports exist on the use of terrestrial plant-based nanoparticles. This review examines the therapeutic properties of seaweed bioactive compounds and their possible applications in treating urolithiasis. We propose that seaweeds could be an excellent source of essential dietary minerals and other bioactive compounds with multiple targets to treat renal calculus naturally. Additionally, the review highlights the potential of nanomedicine in treating urolithiasis, proposing seaweed-based nanoparticles as a promising treatment option.