Distributed Binary Detection over Fading Channels: Cooperative and Parallel Architectures

This paper considers the problem of binary distributed detection of a known signal in correlated Gaussian sensing noise in a wireless sensor network, where the sensors are restricted to use likelihood ratio test (LRT), and communicate with the fusion center (FC) over bandwidth-constrained channels that are subject to fading and noise. To mitigate the deteriorating effect of fading encountered in the conventional parallel fusion architecture, in which the sensors directly communicate with the FC, we propose new fusion architectures that enhance the detection performance, via harvesting cooperative gain (so-called decision diversity gain). In particular, we propose: (i) cooperative fusion architecture with Alamouti's space-time coding (STC) scheme at sensors, (ii) cooperative fusion architecture with signal fusion at sensors, and (iii) parallel fusion architecture with local threshold changing at sensors. For these schemes, we derive the LRT and majority fusion rules at the FC, and provide upper bounds on the average error probabilities for homogeneous sensors, subject to uncorrelated Gaussian sensing noise, in terms of signal-to-noise ratio (SNR) of communication and sensing channels. Our simulation results indicate that, when the FC employs the LRT rule, unless for low communication SNR and moderate/high sensing SNR, performance improvement is feasible with the new fusion architectures. When the FC utilizes the majority rule, such improvement is possible, unless for high sensing SNR

Assessment and Analysis of the Consequences of Climate Change on the Spatial-Biological Resilience of Ahvaz Metropolis

The speed of drought in the world has increased during the last 10 years, but its effects in Iran and Khuzestan province have been much more severe than usual. On the other hand, the intensification of rainfall and the occurrence of floods, the exploitation of water resources and the occurrence of widespread subsidence and the phenomenon of long-term dust as the consequences of climate change will have a negative impact on the pattern of residence and activity in Ahvaz metropolis and will change the structure and function of this metropolis in the future. Based on this, the necessity of paying attention and applying the resilience approach and synchronizing it with the consequences of climate change and future problems will be able to protect the citizens and the fabric of the city in relation to natural disasters and adapt to the existing conditions in the long term. The purpose of this research is to evaluate and analyze the consequences of climate change on the spatial-biological resilience of Ahvaz metropolis. In terms of the purpose, the present research is of an applied type, which was carried out by descriptive-analytical method and field surveys and within the framework of analytical-case model. The studied community includes the statistical block and the land use layer of the city's current state, the available documents including the comprehensive and detailed plan have been obtained. In order to achieve the objectives of the research, spatial-biological dimensions were extracted in 14 indicators

Magnetized inulin by Fe3O4 as a bio-nano adsorbent for treating water contaminated with methyl orange and crystal violet dyes

Current work focuses on fabricating a new bio-nano adsorbent of Fe3O4@inulin nanocomposite via an in-situ co-precipitation procedure to adsorb methyl orange (MO) and crystal violet (CV) dyes from aqueous solutions. Different physical characterization analyses verified the successful fabrication of the magnetic nanocomposite. The adsorbent performance in dye removal was evaluated by varying initial dye concentration, adsorbent dosage, pH and temperature in 5110 mg/L, 0.10.8 g/L, 111 and 283 – 338 K, respectively. Due to the pH of zero point of charge and intrinsic properties of dyes, the optimum pHs were 5 and 7 for MO and CV adsorption, respectively. The correlation of coefficient (R2) and reduced chi-squared value were the criteria in order to select the best isotherm and kinetics models. The Langmuir model illustrated a better fit for the adsorption data for both dyes, demonstrating the maximum adsorption capacity of 276.26 and 223.57 mg/g at 338 K for MO and CV, respectively. As well, the pseudo-second-order model showed a better fitness for kinetics data compared to the pseudo-first-order and Elovich models. The thermodynamic parameters exhibited that the dye adsorption process is endothermic and spontaneous, which supported the enhanced adsorption rate by increasing temperature. Moreover, the nanocomposite presented outstanding capacity and stability after 6 successive cycles by retaining more than 87% of its initial dye removal efficiency. Overall, the magnetized inulin with Fe3O4 could be a competent adsorbent for eliminating anionic and cationic dyes from water

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20\%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors

Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990-2019 : a systematic analysis from the Global Burden of Disease Study 2019

Background Ending the global tobacco epidemic is a defining challenge in global health. Timely and comprehensive estimates of the prevalence of smoking tobacco use and attributable disease burden are needed to guide tobacco control efforts nationally and globally. Methods We estimated the prevalence of smoking tobacco use and attributable disease burden for 204 countries and territories, by age and sex, from 1990 to 2019 as part of the Global Burden of Diseases, Injuries, and Risk Factors Study. We modelled multiple smoking-related indicators from 3625 nationally representative surveys. We completed systematic reviews and did Bayesian meta-regressions for 36 causally linked health outcomes to estimate non-linear dose-response risk curves for current and former smokers. We used a direct estimation approach to estimate attributable burden, providing more comprehensive estimates of the health effects of smoking than previously available. Findings Globally in 2019, 1.14 billion (95% uncertainty interval 1.13-1.16) individuals were current smokers, who consumed 7.41 trillion (7.11-7.74) cigarette-equivalents of tobacco in 2019. Although prevalence of smoking had decreased significantly since 1990 among both males (27.5% [26. 5-28.5] reduction) and females (37.7% [35.4-39.9] reduction) aged 15 years and older, population growth has led to a significant increase in the total number of smokers from 0.99 billion (0.98-1.00) in 1990. Globally in 2019, smoking tobacco use accounted for 7.69 million (7.16-8.20) deaths and 200 million (185-214) disability-adjusted life-years, and was the leading risk factor for death among males (20.2% [19.3-21.1] of male deaths). 6.68 million [86.9%] of 7.69 million deaths attributable to smoking tobacco use were among current smokers. Interpretation In the absence of intervention, the annual toll of 7.69 million deaths and 200 million disability-adjusted life-years attributable to smoking will increase over the coming decades. Substantial progress in reducing the prevalence of smoking tobacco use has been observed in countries from all regions and at all stages of development, but a large implementation gap remains for tobacco control. Countries have a dear and urgent opportunity to pass strong, evidence-based policies to accelerate reductions in the prevalence of smoking and reap massive health benefits for their citizens. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe

Molecular typing and antibiotic resistance patterns among clinical isolates of Acinetobacter baumannii recovered from burn patients in Tehran, Iran

Acinetobacter baumannii (A. baumannii) is now considered a highly resistant pathogen to various types of antibiotics. Therefore, tracking the source of its prevalence and continuous control is crucial. This study aimed to determine antibiotic resistance and perform various molecular typing methods on clinical isolates of A. baumannii isolated from hospitalized burn patients in Shahid Motahari Burn Hospital, Tehran, Iran. Hospital isolates were confirmed by phenotypic and molecular methods. Then the sensitivity to different antibiotics was determined using the minimum inhibitory concentration (MIC) method. In order to perform molecular typing, three-locus dual assay multiplex polymerase chain reaction (PCR), multiple-locus variable-number tandem repeat analysis (MLVA), and multilocus sequence typing (MLST) methods were used. Among the 60 isolates collected, the frequencies of multidrug-resistant (MDR) and extensively drug-resistant (XDR) isolates were 90 and 10%, respectively. The most effective antibiotics were colistin with 100% and tigecycline with 83.33% sensitivity. Isolates were 100% resistant to piperacillin/tazobactam and cephalosporins, and 68.3% were resistant to carbapenem. The results of multiplex PCR showed five groups that international clone I (IC I) and IC II were the most common. The MLVA method identified 34 MLVA types (MTs), 5 clusters, and 25 singletons. Multilocus sequence typing results for tigecycline-resistant isolates showed seven different sequence types (STs). Increasing antibiotic resistance in A. baumannii isolates requires careful management to control and prevent the occurrence of the pre-antibiotic era. The results of this study confirm that the population structure of A. baumannii isolates has a high diversity. More extensive studies are needed in Iran to better understand the epidemiology of A. baumannii

Comparison of volumetric and 2D-based response methods in the PNOC-001 pediatric low-grade glioma clinical trial

Background: Although response in pediatric low-grade glioma (pLGG) includes volumetric assessment, more simplified 2D-based methods are often used in clinical trials. The study’s purpose was to compare volumetric to 2D methods. Methods: An expert neuroradiologist performed solid and whole tumor (including cyst and edema) volumetric measurements on MR images using a PACS-based manual segmentation tool in 43 pLGG participants (213 total follow-up images) from the Pacific Pediatric Neuro-Oncology Consortium (PNOC-001) trial. Classification based on changes in volumetric and 2D measurements of solid tumor were compared to neuroradiologist visual response assessment using the Brain Tumor Reporting and Data System (BT-RADS) criteria for a subset of 65 images using receiver operating characteristic (ROC) analysis. Longitudinal modeling of solid tumor volume was used to predict BT-RADS classification in 54 of the 65 images. Results: There was a significant difference in ROC area under the curve between 3D solid tumor volume and 2D area (0.96 vs 0.78, P = .005) and between 3D solid and 3D whole volume (0.96 vs 0.84, P = .006) when classifying BT-RADS progressive disease (PD). Thresholds of 15–25% increase in 3D solid tumor volume had an 80% sensitivity in classifying BT-RADS PD included in their 95% confidence intervals. The longitudinal model of solid volume response had a sensitivity of 82% and a positive predictive value of 67% for detecting BT-RADS PD. Conclusions: Volumetric analysis of solid tumor was significantly better than 2D measurements in classifying tumor progression as determined by BT-RADS criteria and will enable more comprehensive clinical management.ISSN:2632-249