Dynamic resource allocation for opportunistic software-defined IoT networks: stochastic optimization framework

Several wireless technologies have recently emerged to enable efficient and scalable internet-of-things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved

Measurement and ab initio Investigation of Structural, Electronic, Optical, and Mechanical Properties of Sputtered Aluminum Nitride Thin Films

We report our results on highly textured aluminum nitride (AlN) thin films deposited on glass substrates, oriented along the c-axis, using DC-magnetron sputtering technique for different values of back pressure. The structural, electronic, optical, piezoelectric, dielectric, and elastic properties of sputtered AlN thin films are measured and characterized. In particular, X-ray powder diffraction (XRD) technique shows that AlN thin films exhibit a hexagonal structure. Moreover, we employed ab initio simulations of AlN using the Vienna Ab Initio Simulation Package (VASP) to investigate the structural and the electronic properties of hexagonal AlN structures. The experimental lattice parameters of the as-prepared thin films agree well with those calculated using the total energy minimization approach. The optical parameters of AlN thin films, such as transmittance and refractive index, were measured using UV–vis measurements. Our measurements of refractive index, n, of AlN thin films yield a value of 2.2. Furthermore, the elastic, piezoelectric, and dielectric tensors of AlN crystal are calculated using VASP. The dynamical Born effective charge tensor is reported for all atoms in the unit cell of AlN. Interestingly, ab initio simulations indicate that AlN has a static dielectric constant approximately equal to 4.68, which is in good agreement with the reported experimental value. In addition, the clamped-ion piezoelectric tensor is calculated. The diagonal components of the piezoelectric tensor are found to be e33=1.79 C/m2 and e31=−0.80 C/m2. The large values of the piezoelectric coefficients show that a polar AlN crystal exhibits a strong microwave piezoelectric effect. Additionally, the components of the elastic moduli tensor are calculated. The extraordinary electronic, optical, piezoelectric, and elastic properties make AlN thin films potential candidates for several optoelectronic, elastic, dielectric, and piezoelectric applications

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings: In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding: Bill & Melinda Gates Foundation

Structural, Optoelectrical, Linear, and Nonlinear Optical Characterizations of Dip-Synthesized Undoped ZnO and Group III Elements (B, Al, Ga, and In)-Doped ZnO Thin Films

Undoped ZnO and group III (B, Al, Ga, and In)-doped ZnO thin films at 3% doping concentration level are dip-coated on glass substrates using a sol-gel technique. The optical properties of the as-prepared thin films are investigated using UV–Vis spectrophotometer measurements. Transmittance of all investigated thin films is found to attain high values of ≥80% in the visible region. We found that the index of refraction of undoped ZnO films exhibits values ranging between 1.6 and 2.2 and approximately match that of bulk ZnO. Furthermore, we measure and interpret nonlinear optical parameters and the electrical and optical conductivities of the investigated thin films to obtain a deeper insight from fundamental and practical points of view. In addition, the structural properties of all studied thin film samples are investigated using the XRD technique. In particular, undoped ZnO thin film is found to exhibit a hexagonal structure. Due to the large difference in size of boron and indium compared with that of zinc, doping ZnO thin films with these two elements is expected to cause a phase transition. However, Al-doped ZnO and Ga-doped ZnO thin films preserve the hexagonal phase. Moreover, as boron and indium are introduced in ZnO thin films, the grain size increases. On the other hand, grain size is found to decrease upon doping ZnO with aluminum and gallium. The drastic enhancement of optical properties of annealed dip-synthesized undoped ZnO thin films upon doping with group III metals paves the way to tune these properties in a skillful manner, in order to be used as key candidate materials in the fabrication of modern optoelectronic devices