CONSISTENT LEAST SQUARES ESTIMATOR FOR CO-ARRAY-BASED DOA ESTIMATION

Sparse linear arrays (SLAs), such as nested and co-prime arrays, have the attractive capability of providing enhanced degrees of freedom by exploiting the co-array model. Accordingly, co-array-based Direction of Arrivals (DoAs) estimation has recently gained considerable interest in array processing. The literature has suggested applying MUSIC on an augmented sample covariance matrix for co-array-based DoAs estimation. In this paper, we propose a Least Squares (LS) estimator for co-array-based DoAs estimation employing the covariance fitting method as an alternative to MUSIC. We show that the proposed LS estimator provides consistent estimates of DoAs of identifiable sources for SLAs. Additionally, an analytical expression for the large sample performance of the proposed estimator is derived. Numerical results illustrate the finite sample behavior in relation to the derived analytical expression. Moreover, the performance of the proposed LS estimator is compared to the co-array-based MUSIC

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

Atomistic Modelling and Prediction of Glass Forming Ability in Bulk Metallic Glasses

Atomistic modeling (via molecular dynamics with EAM interaction potentials) was conducted for the detailed investigation of kinetics, thermodynamics, structure, and bonding in Ni-Al and Cu-Zr metallic glasses. This work correlates GFA with the nature of atomic-level bonding and vibrational properties, with results potentially extensible to the Transition Metal – Transition Metal and Transition Metal – Metalloid alloy classes in general. As a first step in the development of a liquid-only GFA tuning approach, an automated tool has also been created for the broad compositional sampling of liquid and glassy phase properties in multicomponent (binary, ternary, quaternary) alloy systems. Its application to the Cu-Zr alloy system shows promising results, including the successful identification of the two highest GFA compositions, Cu50Zr50 and Cu64Zr36. Combined, the findings of this work highlight the critical importance of incorporating more complex alloy-specific information regarding the nature of bonding and ordering at the atomic level into such an approach.M.A.S

“Give My Daughter the Shot!”: A Content Analysis of the Depiction of Patients with Cancer Pain and Their Management in Hollywood Films

Introduction: Cinemeducation, the pedagogical use of films, has been used in a variety of clinical disciplines. To date, no studies have looked at the use of film depictions of cancer pain and its management in clinical education. We investigated how patients with cancer pain and their management are depicted in Hollywood films to determine whether there is content that would be amenable to use for cancer pain assessment and management education. Methods: A qualitative content analysis was performed. Films that contained characters with or references to cancer pain were searched for using the International Movie Database, the Literature Arts Medicine Database, the History of Medicine and Medical Humanities Database, and Medicine on Screen. After review, 4 films were identified for review and analysis. Results: Themes that emerged from the analysis concerned the films’ depictions of characters with pain, their healthcare providers, the therapies used for pain management, and the setting in which pain management was provided. Conclusions: This study demonstrates that patients with cancer pain are depicted in a compassionate manner. Pain management focused on the use of opioids. The settings in which patients received pain management was depicted as not being amenable to providing holistic care. This variety of topics related to pain management covered in the films make them amenable to use in cinemeducation. This study therefore forms the basis for future work developing film-based cancer education modules

Multi-Target Localization in Asynchronous MIMO Radars Using Sparse Sensing

Multi-target localization, warranted in emerging applications like autonomous driving, requires targets to be perfectly detected in the distributed nodes with accurate range measurements. This implies that high range resolution is crucial in distributed localization in the considered scenario. This work proposes a new framework for multi-target localization, addressing the demand for the high range resolution in automotive applications without increasing the required bandwidth. In particular, it employs sparse stepped frequency waveform and infers the target ranges by exploiting sparsity in target scene. The range measurements are then sent to a fusion center where direction of arrival estimation is undertaken. Numerical results illustrate the impact of range resolution on multi-target localization and the performance improvement arising from the proposed algorithm in such scenarios

Detection of temporally correlated primary user signal with multiple antennas

In this paper, we address the problem of multiple antenna spectrum sensing in cognitive radios (CRs) when the samples of the primary user (PU) signal as well as samples of noise are assumed to be temporally correlated. We model and formulate this multiple antenna spectrum sensing problem as a hypothesis testing problem. First, we derive the optimum Neyman-Pearson (NP) detector for the scenario in which the channel gains, the PU signal and noise correlation matrices are assumed to be known. Then, we derive the sub-optimum generalized likelihood ratio test (GLRT)-based detector for the case when the channel gains and aforementioned matrices are assumed to be unknown. Approximate analytical expressions for the false-alarm probabilities of the proposed detectors are given. Simulation results show that the proposed detectors outperform some recently-purposed algorithms for multiple antenna spectrum sensing. Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015.This publication was made possible by the National Priorities Research Program (NPRP) award NPRP 6-1326-2-532 from the Qatar National Research Fund (QNRF) (a member of the Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Detection of Temporally Correlated Primary User Signal with Multiple Antennas

In this paper, we address the problem of multiple antenna spectrum sensing in cognitive radios (CRs) when the samples of the primary user (PU) signal as well as samples of noise are assumed to be temporally correlated. We model and formulate this multiple antenna spectrum sensing problem as a hypothesis testing problem. First, we derive the optimum Neyman-Pearson (NP) detector for the scenario in which the channel gains, the PU signal and noise correlation matrices are assumed to be known. Then, we derive the sub-optimum generalized likelihood ratio test (GLRT)-based detector for the case when the channel gains and aforementioned matrices are assumed to be unknown. Approximate analytical expressions for the false-alarm probabilities of the proposed detectors are given. Simulation results show that the proposed detectors outperform some recently-purposed algorithms for multiple antenna spectrum sensing

Swelling-Based Distributed Chemical Sensing with Standard Acrylate Coated Optical Fibers

Distributed chemical sensing is demonstrated using standard acrylate coated optical fibers. Swelling of the polymer coating induces strain in the fiber’s silica core provoking a local refractive index change which is detectable all along an optical fiber by advanced distributed sensing techniques. Thermal effects can be discriminated from strain using uncoated fiber segments, leading to more accurate strain readings. The concept has been validated by measuring strain responses of various aqueous and organic solvents and different chain length alkanes and blends thereof. Although demonstrated on a short range of two meters using optical frequency-domain reflectometry, the technique can be applied to many kilometer-long fiber installations. Low-cost and insensitive to corrosion and electromagnetic radiation, along with the possibility to interrogate thousands of independent measurement points along a single optical fiber, this novel technique is likely to find applications in environmental monitoring, food analysis, agriculture, water quality monitoring, or medical diagnostics

Impact of soil compaction and irrigation practices on salt dynamics in the presence of a saline shallow groundwater:An experimental and modelling study

Soil salt accumulation is a widespread problem leading to diminished crop yield and threatening food security in many regions of the world. The soil salinization problem is particularly acute in areas that lack adequate soil water drainage and where a saline shallow water table (WT) is present. In this study, we present laboratory-scale column experiments, extending over a period of more than 400 days that focus on the processes contributing to soil salinization. We specifically examine the combined impact of soil compaction, surface water application model and water quality on salt dynamics in the presence of a saline shallow WT. The soil columns (60 cm height and 16 cm diameter) were packed with an agricultural soil with bulk densities of 1.15 and 1.34 g/cm−3 for uncompacted and compacted layers, respectively, and automatically monitored for water content, salinity and pressure. Two surface water compositions are considered: fresh (deionized, DI) and saline water (~3.4 mS/cm). To assess the sensitivity of compaction on salt dynamics, the experiments were numerically modelled with the HYDRUS-1D computer program. The results show that the saline WT led to rapid salinization of the soil column due to capillarity, with the salinity reaching levels much higher than that at the WT. However, compaction layer provided a barrier that limited the downwards moisture percolation and solute transport. Furthermore, the numerical simulations showed that the application of freshwater can temporarily reverse the accumulation of salts in agricultural soils. This irrigation strategy can help, in the short-term, alleviate soil salinization problem. The soil hydraulic properties, WT depth, water quality, evaporation demand and the availability of freshwater all play a role in the practicability of such short-term solutions. The presence of a saline shallow WT would, however, rapidly reverse these temporary measures, leading to the recurrence of topsoil salinization