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International students’ collective resilience in crisis: Sense of community reduced anxiety via social contact and social support during lockdown
No full textObjectives: The role of community in individuals\u27 well-being has been extensively examined in the Western context. However, little is known about how the host community is related to sojourners\u27 well-being in a crisis in an Asian context. The current study aims at exploring international students’ sense of community in the Chinese context under the direct threat of a global health crisis. Methods: Using a cross-sectional sample of 102 international students staying in Wuhan during the 76-day lockdown at the earliest stage of the COVID-19 pandemic, the current study explored the relationship between international students’ sense of community and anxiety, and the mediating role of social contact, social support from three key sources in the host community (host university, international students, and Chinese friends). Results: Results showed that participants’ stronger sense of community indirectly reduced anxiety via the role of sources of contact and support from the host community. Conclusions: This study provided further evidence to support the nurturance of the sense of community in community resilience and provided implications on how the host community can help to enhance sojourners’ psychological well-being in a global crisis
Medical cannabis and the effects of cannabinoids on fighting cancer, multiple sclerosis, epilepsy, Parkinson\u27s, and other neurodegenerative diseases
No full textResearch on the therapeutic efficacy of cannabinoids has demonstrated that cannabidiol (CBD), either alone or in 1:1 mixtures with delta-9-tetrahydrocannabinol (THC), can effectively treat animals in experimental models of neuroinflammatory, demyelinative, neurodegenerative, neuropsychiatric, and neoplastic diseases. Short-term, small-scale, human cohorts, observational studies, randomized, non-randomized, placebo-controlled, and uncontrolled clinical trials have provided low-certainty and moderate-certainty evidence that medical marijuana can reduce spasticity, neuropathic pain, neuroinflammation, anxiety, sleep disturbance, urinary bladder dysfunction, frequency and duration of seizure, tumor size, and metastasis as well as promote overall cancer survival. Medical Cannabis and the Effects of Cannabinoids on Fighting Cancer, Multiple Sclerosis, Epilepsy, Parkinson\u27s, and Other Neurodegenerative Diseases presents the findings from clinical and basic medical scientists who are investigating the cellular and molecular mechanisms of cannabinoid-mediated inhibition of innate and adaptive immune responses, mobilization of myeloid-derived immunosuppressive cells, enhancement of neuroprotection, facilitation of oligodendrocyte survival, promotion of CNS progenitor cell differentiation to support regeneration and remyelination, arrest of tumor cell proliferation, decrease in tumor cell adhesion, disruption of tumor angiogenesis, inhibition of endothelial cells, and prevention of cancer metastasis by inhibition of cell migration. The chapters further discuss pharmacologic challenges and precisely how the delicate balance between the opposing effects of various types of cannabinoid receptors can be controlled by manipulating specific membrane channels and signaling pathways to achieve favorable long-term clinicopathologic outcomes in oncology and neurology. Covering topics such as neurodegenerative diseases, spectroscopic applications, and ethical issues, this premier reference source is an essential resource for medical professionals, pharmacists, hospital administrators, government officials, students and faculty of higher education, librarians, researchers, and academicians
North of America: Loyalists, Indigenous Nations, and the Borders of the Long American Revolution by Jeffers Lennox (review)
No full textThe Cheng-Minkowycz problem for quadratic convective and radiative heat transfer in a nanofluid saturated porous medium: A revised model
No full textThe characteristics of heat transport in a porous medium saturated by a nanoliquid subject to non-linear variations of density-temperature relation and a novel quadratic thermal radiation are studied. For the first time, the well-known Cheng-Minkowycz problem was revisited by nonlinear convection and radiation. The governing equations, based on Darcy\u27s law and Buongiorno\u27s model, are simplified using boundary layer theory, which is further solved by the finite element method. The parameterization of the problem is used to describe the characteristics of the Boussinesq quadratic approximation, Brownian diffusion, quadratic radiation, thermophoretic diffusion, and no-mass flux conditions on the rheological and heat transport features. Our results demonstrate that the rate of heat transport (Nusselt number) is reduced due to thermophoretic diffusion, and the rate of reduction increases with increasing Lewis number values. The Nusselt number is improved due to increasing the values of the Brownian motion parameter at the rate of 0.00616835 and 0.00113362 for the cases of linear thermal radiation and quadratic thermal radiation, respectively. The improvement/reduction rate of the Nusselt number is higher for the case of quadratic thermal convection than for linear thermal convection. Furthermore, the heat transfer rate is achieved for the convection parameter, temperature ratio, and radiation parameter
Energy cryptocurrencies: Assessing connectedness with other asset classes
No full textWe investigate connectedness between energy cryptocurrencies and common asset classes, including oil, using TVP-VAR modeling, evidencing that energy cryptocurrencies, as diversifiers, normally have strong connections with bitcoin and nothing else. However, their connectedness to other assets changes rapidly during shocks such as COVID-19 and the start of the Russian-Ukraine war. Connectedness spiked in April 2020, when WTI oil prices fell to negative pricing. Economic policy uncertainty, Twitter-based uncertainty, and infectious disease-related uncertainty all have significant impact on the system\u27s total connectedness. Energy cryptocurrencies, while normally diversifiers, are highly sensitive to shocks and changes in uncertainty
Introduction: Opportunities for mentor transformation - The re-narration of effective mentorship for educational leaders in academia
No full textComprehensive Analysis of Various Big Data Classification Techniques: A Challenging Overview
No full textData over the internet has been increasing everyday, and automatic mining of essential information from an enormous amount of data has become a challenging task today for an organisation with a huge dataset. In recent years, the prominent technology in the domain of Information Technology (IT) is big data, which is unstructured data that solves the computational complexity of classical database systems. The data is fast and big and typically derived from multiple and independent sources. The three main challenges are data accessing, semantics, and domain knowledge for various big data utilisations and complexities raised by big data volumes. One of the major limitations is the classification of big data. This paper introduces well-defined classification methodologies employed for big data classification. This paper reviews 50 research papers based on classification methods of big data, and such methodologies are primarily categorised into six different categories, namely K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Fuzzy-based method, Bayesian-based method, Random Forest, and Decision Tree. In addition, detailed analysis and discussion are carried out by considering classification techniques, dataset utilised, evaluation metrics, semantic similarity measures, and publication year. In addition, research gaps and issues for several traditional big data classification techniques are explained to expand investigators\u27 works to provide effective big data management
Telemedicine as technoinnovation to tackle COVID-19: A bibliometric analysis
No full textTelemedicine has become fundamental for the challenges posed to healthcare. This set of instruments turns pivotal for facing one of the most relevant emergencies in human history: the COVID-19 pandemic. The multisectoral crisis led to a vigorously sustained adoption of innovations, including telemedicine technology. Telehealth was proven, in this context, to be a relevant tool to reduce healthcare costs, reduce not-needed hospitalizations, and improve the results in health care. Some barriers such as the costs of technologies, patient privacy and technical literacy have slowed down telemedicine adoption. Amidst the COVID-19 era, telemedicine calls for a managerial duty to change healthcare\u27s organizational models. The present work aims to explore the growing literature to illuminate the relationships between telemedicine, innovations and healthcare in the COVID-19 framework. A bibliometric analysis of the existing literature based on 285 published works in 2019–2020 is put forward with the aim to detect the relevant literature, themes and approaches on telemedicine and COVID-19. Making use of community detection on the co-occurrence keywords network, we identify the “semantic cores” in the literature representing the relevant results on critical themes. The sorting implications are important for researchers and policymakers by mapping the existing literature and results in evidence-based analysis. We provide the key communities as the “semantic core” of the publications and results for the considered period. This allows for future research to be oriented towards perduring health policies that could lead to the adoption of telemedicine technologies in a post-pandemic scenario
A novel secure cryptography model for data transmission based on Rotor64 technique
No full textIn recent years, there have been many Security vulnerabilities that threaten user security, these threats have led to the finding of user files, so the use of the Internet has become unlimited, and the number of digital network devices has increased,Therefore, maintaining the confidentiality and integrity of information has become an urgent necessity to preserve user information, due to the increase in hackers and intruders, and the innovation of modern methods of penetration every day. Data cryptography has proven to be a secure way to protect a user\u27s data. Many current cryptography algorithms are considered weak regarding data transmission over the Internet, so newly updated algorithms are in high demand. In this paper, we proposed to develop the ancient rotor machine depending on the base64 codding technique, in which we replaced the alphabets of the ancient rotor machine with the alphabets of base64 that contain 64 characters. Furthermore, we proposed a key exchange based on One-time password OTP code via SMS, OTP is mechanism for logging on to a network using unique password that can only be used once, to overcome the static password method that is least secure, and used it to generate the subkeys for rotor machines based on hash and random permutation techniques. MD5 algorithm function is used to authenticate the original message, Finally, we experimented with these techniques of secure sending e-mails by encrypting the contents of them with the proposed technique. However, the proposed security technique got promising results
Three Forms of Mutant Subsumption: Basic, Strict and Broad
No full textMutant subsumption is the property of a mutant to be more stubborn than another, i.e. to be harder to distinguish from the base program. The traditional definition of mutant subsumption distinguishes between three forms of subsumption, namely: true subsumption, static subsumption, and dynamic subsumption. Also, the traditional definition of mutant subsumption appears to assume that programs and their mutants converge for all test data, but in practice this is not the case: executions may lead to infinite loops or attempt illegal operations of all kinds. In this paper we revisit the definition of mutant subsumption by taking into consideration the possibility that executions may diverge, and we propose an orthogonal classification of subsumption