Computing server power modeling in a data center: survey,taxonomy and performance evaluation

Data centers are large scale, energy-hungry infrastructure serving the increasing computational demands as the world is becoming more connected in smart cities. The emergence of advanced technologies such as cloud-based services, internet of things (IoT) and big data analytics has augmented the growth of global data centers, leading to high energy consumption. This upsurge in energy consumption of the data centers not only incurs the issue of surging high cost (operational and maintenance) but also has an adverse effect on the environment. Dynamic power management in a data center environment requires the cognizance of the correlation between the system and hardware level performance counters and the power consumption. Power consumption modeling exhibits this correlation and is crucial in designing energy-efficient optimization strategies based on resource utilization. Several works in power modeling are proposed and used in the literature. However, these power models have been evaluated using different benchmarking applications, power measurement techniques and error calculation formula on different machines. In this work, we present a taxonomy and evaluation of 24 software-based power models using a unified environment, benchmarking applications, power measurement technique and error formula, with the aim of achieving an objective comparison. We use different servers architectures to assess the impact of heterogeneity on the models' comparison. The performance analysis of these models is elaborated in the paper

Metaverse: A Vision, Architectural Elements, and Future Directions for Scalable and Realtime Virtual Worlds

With the emergence of Cloud computing, Internet of Things-enabled Human-Computer Interfaces, Generative Artificial Intelligence, and high-accurate Machine and Deep-learning recognition and predictive models, along with the Post Covid-19 proliferation of social networking, and remote communications, the Metaverse gained a lot of popularity. Metaverse has the prospective to extend the physical world using virtual and augmented reality so the users can interact seamlessly with the real and virtual worlds using avatars and holograms. It has the potential to impact people in the way they interact on social media, collaborate in their work, perform marketing and business, teach, learn, and even access personalized healthcare. Several works in the literature examine Metaverse in terms of hardware wearable devices, and virtual reality gaming applications. However, the requirements of realizing the Metaverse in realtime and at a large-scale need yet to be examined for the technology to be usable. To address this limitation, this paper presents the temporal evolution of Metaverse definitions and captures its evolving requirements. Consequently, we provide insights into Metaverse requirements. In addition to enabling technologies, we lay out architectural elements for scalable, reliable, and efficient Metaverse systems, and a classification of existing Metaverse applications along with proposing required future research directions

The Relationship Between Instructors’ Transformational Leadership Style And Their Job Satisfaction In Nursing Science Faculty, University Of Somalia

This study investigated the relationship between instructors’ transformational leadership style and their job satisfaction in nursing science faculty, University of Somalia. This study aimed (1) to identify the degree in which transformational leadership style is used by the instructors; (2) to determine the satisfaction level of the instructors; and lastly (3) to examine the relationship between instructors’ transformational leadership style and job satisfaction of the nursing science instructors at University of Somalia. The study had 76 respondents, all full time instructors at the nursing science faculty and 100% of them responded to the survey. This research design was a quantitative and relationship study. A previously developed descriptive survey was used to investigate the Nursing Science department. The researcher used a statistical software program to analyze the collected data. This study found that the degree in which instructors use transformational leadership style was high, the instructors were overall highly satisfied with their job, and that there was a positive significant relationship between instructors’ transformational leadership style and their job satisfaction in nursing science faculty at the University of Somalia

The Relationship Of Family Educationship To Drug Abuse "Theoretical Study"

 The current research problem sheds light on family socialization and its relation to drug abuse by presenting the concept of social upbringing in general and family in particular, and identifying the forms of this formation that may contribute to its erroneous models in the emergence of many phenomena of deviation such as drug abuse. The aim of the research is to: Recognize the functions of social upbringing in order to activate its role in the treatment of phenomena of deviation. This research has reached a number of results, the most important of which is that the form of family formation in which the individual is exposed plays an important role in predicting the normal or abnormal behavior patterns that the individual will exercise in the future. This research ended with a number of proposals reached through the theoretical framework of this research as well as an analysis of the results of previous studies related to the subjec

The satisfactory growth and development at 2 years of age of the INTERGROWTH-21st Fetal Growth Standards cohort support its appropriateness for constructing international standards.

Background: The World Health Organization recommends that human growth should be monitored with the use of international standards. However, in obstetric practice, we continue to monitor fetal growth using numerous local charts or equations that are based on different populations for each body structure. Consistent with World Health Organization recommendations, the INTERGROWTH-21st Project has produced the first set of international standards to date pregnancies; to monitor fetal growth, estimated fetal weight, Doppler measures, and brain structures; to measure uterine growth, maternal nutrition, newborn infant size, and body composition; and to assess the postnatal growth of preterm babies. All these standards are based on the same healthy pregnancy cohort. Recognizing the importance of demonstrating that, postnatally, this cohort still adhered to the World Health Organization prescriptive approach, we followed their growth and development to the key milestone of 2 years of age. Objective: The purpose of this study was to determine whether the babies in the INTERGROWTH-21st Project maintained optimal growth and development in childhood. Study Design: In the Infant Follow-up Study of the INTERGROWTH-21st Project, we evaluated postnatal growth, nutrition, morbidity, and motor development up to 2 years of age in the children who contributed data to the construction of the international fetal growth, newborn infant size and body composition at birth, and preterm postnatal growth standards. Clinical care, feeding practices, anthropometric measures, and assessment of morbidity were standardized across study sites and documented at 1 and 2 years of age. Weight, length, and head circumference age- and sex-specific z-scores and percentiles and motor development milestones were estimated with the use of the World Health Organization Child Growth Standards and World Health Organization milestone distributions, respectively. For the preterm infants, corrected age was used. Variance components analysis was used to estimate the percentage variability among individuals within a study site compared with that among study sites. Results: There were 3711 eligible singleton live births; 3042 children (82%) were evaluated at 2 years of age. There were no substantive differences between the included group and the lost-to-follow up group. Infant mortality rate was 3 per 1000; neonatal mortality rate was 1.6 per 1000. At the 2-year visit, the children included in the INTERGROWTH-21st Fetal Growth Standards were at the 49th percentile for length, 50th percentile for head circumference, and 58th percentile for weight of the World Health Organization Child Growth Standards. Similar results were seen for the preterm subgroup that was included in the INTERGROWTH-21st Preterm Postnatal Growth Standards. The cohort overlapped between the 3rd and 97th percentiles of the World Health Organization motor development milestones. We estimated that the variance among study sites explains only 5.5% of the total variability in the length of the children between birth and 2 years of age, although the variance among individuals within a study site explains 42.9% (ie, 8 times the amount explained by the variation among sites). An increase of 8.9 cm in adult height over mean parental height is estimated to occur in the cohort from low-middle income countries, provided that children continue to have adequate health, environmental, and nutritional conditions. Conclusion: The cohort enrolled in the INTERGROWTH-21st standards remained healthy with adequate growth and motor development up to 2 years of age, which supports its appropriateness for the construction of international fetal and preterm postnatal growth standards

Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

Diabetes Mellitus, one of the leading causes of death worldwide, has no cure to date and can lead to severe health complications, such as retinopathy, limb amputation, cardiovascular diseases, and neuronal disease, if left untreated. Consequently, it becomes crucial to take precautionary measures to avoid/predict the occurrence of diabetes. Machine learning approaches have been proposed and evaluated in the literature for diabetes prediction. This paper proposes an IoT-edge-Artificial Intelligence (AI)-blockchain system for diabetes prediction based on risk factors. The proposed system is underpinned by the blockchain to obtain a cohesive view of the risk factors data from patients across different hospitals and to ensure security and privacy of the user's data. Furthermore, we provide a comparative analysis of different medical sensors, devices, and methods to measure and collect the risk factors values in the system. Numerical experiments and comparative analysis were carried out between our proposed system, using the most accurate random forest (RF) model, and the two most used state-of-the-art machine learning approaches, Logistic Regression (LR) and Support Vector Machine (SVM), using three real-life diabetes datasets. The results show that the proposed system using RF predicts diabetes with 4.57% more accuracy on average compared to LR and SVM, with 2.87 times more execution time. Data balancing without feature selection does not show significant improvement. The performance is improved by 1.14% and 0.02% after feature selection for PIMA Indian and Sylhet datasets respectively, while it reduces by 0.89% for MIMIC III

Lifestyle Interventions for Prevention and Management of Diet-Linked Non-Communicable Diseases among Adults in Arab Countries

The increased incidences of diet-related non-communicable diseases (NCDs) such as diabetes, obesity, and cardiovascular diseases among adults are becoming the chief public health concern in most Arab countries. Economic expansion has contributed to a nutrition shift from a traditional seasonal diet to Westernized eating habits coupled with a sedentary lifestyle. Despite the rising concern for NCD mortality, public health policies are inadequately addressed. This narrative review aims to discuss the effectiveness of nutritional interventions focusing on diet and physical activity in the management of NCDs among Arab adults. A comprehensive literature search was performed using different database platforms such as Cochrane reviews, Scopus, and PubMed for articles published between 1 December 2012 and 31 December 2021. Fifteen recent research articles addressing NCDs, mainly diabetes and obesity, from different Arab countries were included in this review. Structured lifestyle interventions involving behavioral therapy approaches and personalized goals for diet and physical activity were found to improve specific health outcomes in most studies. Significant improvements in health outcomes were reported for longer-duration interventions with follow-ups. A combination of both online and face-to-face sessions was found to be effective. It is important to identify barriers to physical activity for a culturally acceptable lifestyle intervention and conduct further studies to evaluate interventions for the long-term maintenance of health outcomes

Effect of High Fiber Cereal Intake on Satiety and Gastrointestinal Symptoms during Ramadan.

(1) Background: Fasting during Ramadan involves large changes in daily eating patterns which strongly impacts the daily biorhythm and challenges the regular function of the digestive tract. The aim of this study was to assess satiety, bowel habits, body composition, blood glycaemia, and blood lipidemia after the consumption of high fiber cereal at dawn (Sohor) during the month of Ramadan; (2) Methods: A two-arm randomized, controlled, single-blinded, parallel-design study was conducted in Ramadan month. Participants were randomized to consume either 90 g of high fiber cereal (11 g fiber/90 g) at Sohor for 20 consecutive days (intervention group, n = 45) or to maintain their habitual diet intake (control group; n = 36); (3) Results: The intervention group reported higher satiety rating scores, improved bowel habits and reduced bloating frequency after the 20-day intervention. Significantly higher intake of carbohydrates and dietary fiber were observed in the intervention group. Total cholesterol and low density lipoprotein (LDL) cholesterol were significantly lower among the intervention group compared to the control group (p-value = 0.043, and p-value = 0.033, respectively) at the end of the intervention. No significant differences in body weight, body fat percentage, waist circumference, body mass index, blood glucose, high density lipoprotein (HDL) cholesterol, and triglycerides were observed between the two groups; (4) Conclusions: Consuming high fiber cereal had a positive effect on health and well-being during the month of Ramadan with better satiety, improved bowel functions, and improved blood lipids

Neurodevelopmental milestones and associated behaviours are similar among healthy children across diverse geographical locations

It is unclear whether early child development is, like skeletal growth, similar across diverse regions with adequate health and nutrition. We prospectively assessed 1307 healthy, well-nourished 2-year-old children of educated mothers, enrolled in early pregnancy from urban areas without major socioeconomic or environmental constraints, in Brazil, India, Italy, Kenya and UK. We used a specially developed psychometric tool, WHO motor milestones and visual tests. Similarities across sites were measured using variance components analysis and standardised site differences (SSD). In 14 of the 16 domains, the percentage of total variance explained by between-site differences ranged from 1.3% (cognitive score) to 9.2% (behaviour score). Of the 80 SSD comparisons, only six were \u3e±0.50 units of the pooled SD for the corresponding item. The sequence and timing of attainment of neurodevelopmental milestones and associated behaviours in early childhood are, therefore, likely innate and universal, as long as nutritional and health needs are met

Performance comparison of CVD grown carbon nanofiber based on single- and multi-layer graphene oxides in melt-compounded PA6.6 nanocomposites

In the present study, newly design hybrid nanostructures were produced by growing long carbon nanofibers (CNF) on single- and multi-layer graphene oxide (GO) sheets in the presence of catalyst by chemical vapor deposition (CVD). Chemical composition analysis indicated the formation of Fe-C bonds by the deposition of carbon atoms on catalyst surface of Fe2O3 and increasing in C/O atomic ratio confirming CNF growing. These hybrid additives were distributed homogeneously through polyamide 6.6 (PA6.6) chains by high shear thermokinetic mixer in melt phase. Spectroscopic studies showed that the differences in the number of graphene layer in hybrid structures directly affected the crystalline behavior and dispersion state in polymer matrix. Flexural strength and flexural modulus of PA6.6 nanocomposites were improved up to 14.7% and 14% by the integration of 0.5 wt% CNF grown on multi-layer GO, respectively, whereas there was a significant loss in flexural properties of single-layer GO based nanocomposites. Also, the integration of 0.5 wt% multi-layer GO hybrid reinforcement in PA6.6 provided a significant increase in tensile modulus about 24%. Therefore, multi-layer GO with CNF increased the degree of crystallinity in nanocomposites by forming intercalated structure and acted as a nucleating agent causing the improvement in mechanical properties