Design Configurations and Operating Limitations of an Oscillating Heat Pipe

Passive and compact heat dissipation systems are and will remain vital for the successful operation of modern electronic systems. Oscillating heat pipes (OHPs) have been a part of this research area since their inception due to their ability to passively manage high heat fluxes. In the current investigation, different designs of tubular, flat plate, and multiple layer oscillating heat pipes are studied by using different operating parameters to investigate the operating limitations of each design. Furthermore, selective laser melting was demonstrated as a new OHP manufacturing technique and was used to create a compact multiple layer flat plate OHP. A 7-turn tubular oscillating heat pipe (T-OHP) was created and tested experimentally with three working fluids (water, acetone, and n-pentane) and different orientations (horizontal, vertical top heating, and vertical bottom heating). For vertical, T-OHP was tested with the condenser at 0°, 45° and 90° bend angle from the y-axis (achieved by bending the OHP in the adiabatic) in both bottom and top heating modes. The results show that T-OHP thermal performance depends on the bend angle, working fluid, and orientation. Another design of L-shape closed loop square microchannel (750 x 750 microns) copper heat pipe was fabricated from copper to create a thermal connector with thermal resistance \u3c 0.09 ˚C/W for electronic boards. The TC-OHP was able to manage heat rates up to 250 W. A laser powder bed fusion (L-PBF) additive manufacturing (AM) method was employed for fabricating a multi-layered, Ti-6Al-4V oscillating heat pipe (ML-OHP). The 50.8 x 38.1 x 15.75 mm3 ML-OHP consisted of four inter-connected layers of circular mini-channels, as well an integrated, hermetic-grade fill port. A series of experiments were conducted to characterize the ML-OHP thermal performance by varying power input (up to 50 W), working fluid (water, acetone, NovecTM 7200, and n-pentane), and operating orientation (vertical bottom-heating, horizontal, and vertical top-heating). The ML-OHP was found to operate effectively for all working fluids and orientations investigated, demonstrating that the OHP can function in a multi-layered form, and further indicating that one can ‘stack’ multiple, interconnected OHPs within flat media for increased thermal management

Human Resources Practices in Non-profit Organizations: Evidence from the Kingdom of Saudi Arabia

Non-profit organizations (NPOs) are essential to the economic planning process in Saudi Arabia. This study examines the Human Resource (HR) practices of Saudi Arabian non-profit organizations. It is based on a primary survey administered to 201 employees of the four types of existing non-profit organizations (NPOs) in Saudi Arabia (Qur'an Memorization Society, Dawah Society, Specialized Society, and Development Committee) using a structured questionnaire. The questionnaire was intended for the eight existing HR practices: work design, HR planning, polarization, selection, training and development, motivation, performance evaluation, and job satisfaction. The ANOVA and Pearson correlation tests were performed on the eight segments of the HR instruments to investigate the perspectives of HR professionals in the NPO sector. The findings of the study indicate that the HR practices are moderated by the gender, age, education, and years of experience of the employees. The work design has the highest awareness among the employees, with a mean of 4.05, while job satisfaction has the lowest awareness, with a mean of 3.18 on a 5-point scale. A correlation between HR practices shows that work design improves performance evaluation, polarization affects HR planning, and training and development influence performance evaluation

Exploring the potential of artificial intelligence and machine learning to combat COVID-19 and existing opportunities for LMIC: A scoping review

Background: In the face of the current time-sensitive COVID-19 pandemic, the limited capacity of healthcare systems resulted in an emerging need to develop newer methods to control the spread of the pandemic. Artificial Intelligence (AI), and Machine Learning (ML) have a vast potential to exponentially optimize health care research. The use of AI-driven tools in LMIC can help in eradicating health inequalities and decrease the burden on health systems.Methods: The literature search for this Scoping review was conducted through the PubMed database using keywords: COVID-19, Artificial Intelligence (AI), Machine Learning (ML), and Low Middle-Income Countries (LMIC). Forty-three articles were identified and screened for eligibility and 13 were included in the final review. All the items of this Scoping review are reported using guidelines for PRISMA extension for scoping reviews (PRISMA-ScR).Results: Results were synthesized and reported under 4 themes. (a) The need of AI during this pandemic: AI can assist to increase the speed and accuracy of identification of cases and through data mining to deal with the health crisis efficiently, (b) Utility of AI in COVID-19 screening, contact tracing, and diagnosis: Efficacy for virus detection can a be increased by deploying the smart city data network using terminal tracking system along-with prediction of future outbreaks, (c) Use of AI in COVID-19 patient monitoring and drug development: A Deep learning system provides valuable information regarding protein structures associated with COVID-19 which could be utilized for vaccine formulation, and (d) AI beyond COVID-19 and opportunities for Low-Middle Income Countries (LMIC): There is a lack of financial, material, and human resources in LMIC, AI can minimize the workload on human labor and help in analyzing vast medical data, potentiating predictive and preventive healthcare.Conclusion: AI-based tools can be a game-changer for diagnosis, treatment, and management of COVID-19 patients with the potential to reshape the future of healthcare in LMIC

Mitochondrial Dysfunction Increases Arrhythmic Triggers and Substrates; Potential Anti-arrhythmic Pharmacological Targets.

Incidence of cardiac arrhythmias increases significantly with age. In order to effectively stratify arrhythmic risk in the aging population it is crucial to elucidate the relevant underlying molecular mechanisms. The changes underlying age-related electrophysiological disruption appear to be closely associated with mitochondrial dysfunction. Thus, the present review examines the mechanisms by which age-related mitochondrial dysfunction promotes arrhythmic triggers and substrate. Namely, via alterations in plasmalemmal ionic currents (both sodium and potassium), gap junctions, cellular Ca2+ homeostasis, and cardiac fibrosis. Stratification of patients' mitochondrial function status permits application of appropriate anti-arrhythmic therapies. Here, we discuss novel potential anti-arrhythmic pharmacological interventions that specifically target upstream mitochondrial function and hence ameliorates the need for therapies targeting downstream changes which have constituted traditional antiarrhythmic therapy

Spatial variation of the levels of deprivation in the Sultanate of Oman

In recent decades indicators and statistical methods have been developed to measure the levels of multiple deprivations in economic and social aspects. The aim is to identify the geographical areas which suffer from deprivation in some of these aspects, in order to know their developmental needs, and then to focus the support and development processes there. The most important indices that have evolved in this context are; the Jarman index, also known as the «Underprivileged Area Score», the «Townsend deprivation index», and the «Carstairs deprivation Index». Since the 1980s, the Carstairs deprivation index has become well-known, especially after it was used - with some modification - in the measurement of indices of deprivation in the countries of the United Kingdom by the «Social Disadvantages Research Center-SDRS» at the University of Oxford. This study aims to measure the levels of deprivation in the Sultanate of Oman using the Carstairs index, to discover the more and less deprived wilayates in the seven domains reflecting the social and economic status of the population, namely: education, skills, employment, health, housing, living environment, facilities and household appliances. These domains include fourteen variables, with data derived from the population census of Oman in 2010. The Carstairs index was calculated separately for every domain, which made it possible to determine the wilayats that are suffering from deprivation in these domains. Through the compilation of the Carstairs index values for all domains, it was possible to calculate the «Index of multiple deprivation in Oman». The results show that the most disadvantaged wilayats, according to this index are: Al Mazyounah, Mahawt, Ad Duqm, Al Jazer, Hayma, Shalim Wa Juzor Al Hallaniyat, Rakhyut, Dalkut, all of which are located in the Governorates of Al Wusta and Dhofar