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Computer security competitions have been playing a significant role in encouraging students to get into cybersecurity, as well as enhancing the cybersecurity education system. The level of difficulty of the computer security tasks could be intimidating for most students and learners, one of the reasons there has been a shortage of cybersecurity professionals, in addition to that the lack of technical training and materials. The risks posed by the cyberattacks keep constantly evolving that positions the cybersecurity education as constantly changing area, which are at times hard to teach. Furthermore, the cybersecurity laboratories are hard to setup and the assessment tools are not accurate. This obviously impacts the proper engagement of students and the learning outcomes. To address these issues, we propose a game-based learning platform to enhance cybersecurity education. The platform applies an adapted ARCS motivational model to design and evaluate different challenges, it includes a virtual lab for students with the necessary tools for practice and a web portal where all challenges and learning materials are hosted. The aim is to help students learn at their own pace about different cybersecurity challenges, give them the opportunity to gain hacking skills with ethics taken in mind in a much safer environment. Learning by solving fun puzzles and playing educational games has a huge impact on students' performances in cybersecurity. Although the contributed solution is developed for UAE University, we believe it imparts same gains in similar educational institutes.

Basically the current study sought to assess the perception of students regarding the role of teacher communication skills in their academics success. Comprehensive questionnaire carrying information including social economic and demographic aspects of the study was designed by the researcher to achieve the set objectives. All those universities where sports sciences & physical education programs were offering were taken as population of the study. The empirical data regarding the role of a teacher communication skills in students' academic success were obtained from (418, thirty percent 30 from each university) samples of 14 universities of Pakistan. The data were collected from the respondents through personally contact and by using the developed scale. After collection of data, the data were finally classified in the form of tables and regression was employed for the analysis of data. After analysis of data the researcher arrived at conclusion that teacher communication skills have significant role in the academic achievement of the students.

Subjects with initially extreme observations upon remeasurement are found closer to the population mean. This tendency of observations toward the mean is called regression to the mean (RTM) and can make natural variation in repeated data look like real change. Studies, where subjects are selected on a baseline criterion, should be guarded against the RTM effect to avoid erroneous conclusions. In an intervention study, the difference between pre-post variables is the combined effect of intervention/treatment and RTM. Thus, accounting for RTM is essential to accurately estimate the intervention effect. Many real-life examples are better modeled by a bivariate binomial model with varying probability of success. In this article, a bivariate beta-binomial distribution is used that allows the probability of success to vary from subject to subject. Expressions for the total, RTM, and treatment effect are derived, and their behavior is demonstrated graphically. Maximum likelihood estimators of RTM are derived, and their statistical properties are studied via Monte Carlo simulation. The proposed techniques are employed to estimate the RTM effect by utilizing data related to the Countway WM-class circulation. [ABSTRACT FROM AUTHOR]

Regression to the mean occurs when an unusual observation is followed by a more typical outcome closer to the population mean. In pre- and post-intervention studies, treatment is administered to subjects with initial measurements located in the tail of a distribution, and a paired sample t -test can be utilized to assess the effectiveness of the intervention. The observed change in the pre-post means is the sum of regression to the mean and treatment effects, and ignoring regression to the mean could lead to erroneous conclusions about the effectiveness of the treatment effect. In this study, formulae for regression to the mean are derived, and maximum likelihood estimation is employed to numerically estimate the regression to the mean effect when the test statistic follows the bivariate t -distribution based on a baseline criterion or a cut-off point. The pre-post degrees of freedom could be equal but also unequal such as when there is missing data. Additionally, we illustrate how regression to the mean is influenced by cut-off points, mixing angles which are related to correlation, and degrees of freedom. A simulation study is conducted to assess the statistical properties of unbiasedness, consistency, and asymptotic normality of the regression to the mean estimator. Moreover, the proposed methods are compared with an existing one assuming bivariate normality. The p -values are compared when regression to the mean is either ignored or accounted for to gauge the statistical significance of the paired t -test. The proposed method is applied to real data concerning schizophrenia patients, and the observed conditional mean difference called the total effect is decomposed into the regression to the mean and treatment effects. [ABSTRACT FROM AUTHOR]

Regression to the mean (RTM) occurs when extreme observations upon remeasurement are found closer to the population mean. Interventions are usually applied to subjects based on a cut-off point to check it effectiveness. The average difference of the pre-post observations called the total effect is the sum of RTM and intervention effects and needs to be accounted for RTM to avoid incorrect conclusions and unbiasedly estimate the intervention effect. The existing methods assume equidispersion and strict positive correlation for bivariate count data. This study considers a bivariate Poisson distribution which takes both the dispersion and negative correlation into consideration. Expressions for the total effect are derived and partitioned into RTM and intervention effects. The maximum likelihood estimators of the RTM and intervention effects are found numerically, and their asymptotic properties are verified via simulations. Data on the English premier league are used to estimate the RTM and intervention effects. [ABSTRACT FROM AUTHOR]

Heritage conservation, often referred to as historic preservation or heritage preservation, is the process of safeguarding and maintaining objects, buildings, landscapes, and other artifacts that hold cultural, historical, or architectural importance. This encompasses a diverse array of both physical and non-physical cultural assets, including but not limited to, ancient structures, archaeological locations, monuments, artifacts, customs, and cultural environments. A bibliometric analysis was conducted to ascertain research tendencies and contributions in the field of Heritage Conservation. The study primarily investigated themes, authors, publications, and organizations. The Scopus database was employed to retrieve the data, resulting in the identification of 357 papers after applying filters. The five leading journals in the field of heritage conservation from 2003 to 2023 were "Sustainability Switzerland" (with 69 published articles), "Geoheritage" (with 55 published articles), "Journal of Sustainable Tourism" (with 13 published articles), "Geojournal of Tourism and Geosites" (with 10 published articles), and "Journal of Heritage Tourism" (with nine published articles). The most commonly used keywords in the analyzed papers were "Tourism," "Geotourism," "Conservation," "Heritage tourism," "Heritage," "Geoheritage," "Heritage Conservation," "Cultural Heritage," "sustainable development," "Sustainability," "Geoconservation," "Heritage Management," "Geopark," "Sustainable Tourism," "China," "Geosites," and "Tourism Development." [ABSTRACT FROM AUTHOR]

Objective: Sphingosine 1 Phosphate (S1P) is a key regulator of inflammation, angiogenesis, vessel permeability, and immune processes, acting through S1P receptors. Fingolimod (FTY720), an S1P receptor analog Fingolimod, was initially approved for multiple sclerosis treatment and has shown potential for application in infectious and inflammatory disorders, including COVID-19. Study Design: Comprehensive Literature Review. Setting: Northwest School of Medicine. Period: 1st March 2023 to 3rd July 2023. Methods: Examining S1P pathways, S1P receptor analogs, and their potential in treating inflammatory and infectious disorders, particularly COVID-19, utilizing Fingolimod. Results: S1P analogs have demonstrated therapeutic benefits in autoimmune diseases. In COVID-19, these analogs modulate the inflammatory response, reduce tissue damage, and promote viral clearance. Fingolimod, in particular, affects S1PR1, S1PR4, and S1PR5, blunting the inflammatory response and mitigating lung tissue injury. Early administration may prevent excessive inflammation without interfering with viral clearance. Potential risks include disturbance of cytokine homeostasis and delayed administration. Limited human studies and concerns about off-target effects need addressing. Conclusion: Fingolimod shows promise in treating COVID-19 by reducing inflammation and lung damage. Further research is needed to address limitations and ensure safety for clinical application. Sphingosine 1 Phosphate (S1P) plays a key role in regulating inflammation and immune responses, with Fingolimod being a potential treatment option. [ABSTRACT FROM AUTHOR]

Gold wash through panning or washing in the fluvial sediments or sands is doneon the river banks in Skardu, Hunza and other places. The method of gold washing is very crude, primitive and most of the gold is washed away back into the river. The current study mainly focused on extraction of placer gold deposits. Pneumatic machines from Passu to Shimshal (Hunza valley) Gilgit-Baltistan. The mercury amalgamation and cyanide leached methodshavebeen used for placer gold deposits extraction from the concentrate obtained from shaking table. The amount of gold recovered from amalgamation method with mercury was 30.9%. The alloyed gold with other metals, gold dust, and fine gold was recovered by chemical process. The reagent consumption, i.e. 1.4 kg/ton of NACN and 6 Kg / ton of CaO were used forextraction ofplacer gold deposits.The extracted gold is 10.24 g /t and silver 22 g /t and the remaining gold like the amalgamation residue, tailings and middlings are extracted by cyanidation leached method. The extraction of gold by cyanidation process was compared graphically, and study results revealed that extraction of gold using cyanidation leached method was91.40% and silver 100%, respectively