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3,764 results on '"Hossain, S."'

1. Social media polarization during conflict: Insights from an ideological stance dataset on Israel-Palestine Reddit comments

Author

Ali, Hasin Jawad, Abrar, Ajwad, Hossain, S. M. Hozaifa, and Mridha, M. Firoz

Subjects
Computer Science - Computation and Language
Abstract

In politically sensitive scenarios like wars, social media serves as a platform for polarized discourse and expressions of strong ideological stances. While prior studies have explored ideological stance detection in general contexts, limited attention has been given to conflict-specific settings. This study addresses this gap by analyzing 9,969 Reddit comments related to the Israel-Palestine conflict, collected between October 2023 and August 2024. The comments were categorized into three stance classes: Pro-Israel, Pro-Palestine, and Neutral. Various approaches, including machine learning, pre-trained language models, neural networks, and prompt engineering strategies for open source large language models (LLMs), were employed to classify these stances. Performance was assessed using metrics such as accuracy, precision, recall, and F1-score. Among the tested methods, the Scoring and Reflective Re-read prompt in Mixtral 8x7B demonstrated the highest performance across all metrics. This study provides comparative insights into the effectiveness of different models for detecting ideological stances in highly polarized social media contexts. The dataset used in this research is publicly available for further exploration and validation.

Published
2025

2. Leveraging Large Language Models and Machine Learning for Smart Contract Vulnerability Detection

Author

Hossain, S M Mostaq, Altarawneh, Amani, and Roberts, Jesse

Subjects
Computer Science - Cryptography and Security
Abstract

As blockchain technology and smart contracts become widely adopted, securing them throughout every stage of the transaction process is essential. The concern of improved security for smart contracts is to find and detect vulnerabilities using classical Machine Learning (ML) models and fine-tuned Large Language Models (LLM). The robustness of such work rests on a labeled smart contract dataset that includes annotated vulnerabilities on which several LLMs alongside various traditional machine learning algorithms such as DistilBERT model is trained and tested. We train and test machine learning algorithms to classify smart contract codes according to vulnerability types in order to compare model performance. Having fine-tuned the LLMs specifically for smart contract code classification should help in getting better results when detecting several types of well-known vulnerabilities, such as Reentrancy, Integer Overflow, Timestamp Dependency and Dangerous Delegatecall. From our initial experimental results, it can be seen that our fine-tuned LLM surpasses the accuracy of any other model by achieving an accuracy of over 90%, and this advances the existing vulnerability detection benchmarks. Such performance provides a great deal of evidence for LLMs ability to describe the subtle patterns in the code that traditional ML models could miss. Thus, we compared each of the ML and LLM models to give a good overview of each models strengths, from which we can choose the most effective one for real-world applications in smart contract security. Our research combines machine learning and large language models to provide a rich and interpretable framework for detecting different smart contract vulnerabilities, which lays a foundation for a more secure blockchain ecosystem., Comment: 7 pages, 4 figures, 1 table. This paper has accepted in 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC)

Published
2025

3. Evidence of random spin-singlet state in a three-dimensional quantum spin liquid candidate Sr$_3$CuNb$_2$O$_9$

Author

Hossain, S. M., Rahaman, S. S., Gujrati, H., Bhoi, Dilip, Matsuo, A., Kindo, K., Kumar, M., and Majumder, M.

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

Disorder is ubiquitous in any quantum many-body system and is usually considered to be an obstacle to the elucidation of the underlying physics of complex systems, but its presence can often introduce exotic phases of matter that cannot generally be realized in a clean system. We report here a detailed experimental and theoretical study of magnetic properties of highly disordered Sr$_3$CuNb$_2$O$_9$ material which exhibits random site mixing between Cu and Nb. The magnetic moments (Cu$^{2+}$) are arranged in a quasi-cubic (three-dimensional) manner, leading to a high degree of frustration with a Curie-Weiss temperature ($\theta_{CW}$) of about -60 K without any long-range magnetic ordering down to 466 mK. These observations suggest that Sr$_3$CuNb$_2$O$_9$ is a candidate for a quantum spin liquid. More interestingly, the susceptibility ($\chi = M/\mu_0H$) and the $C_m/T$ ($C_m$ is the magnetic part of the heat capacity) follow a power-law behavior with decreasing temperature. In addition, $M(T,\mu_0H)$ and $C_m(T,\mu_0H)/T$ show scaling relationships over a wide temperature and field range. This unusual behavior with respect to the conventional behavior of a QSL can be discussed qualitatively as the coexistence of a disorder-induced random spin singlet (RSS) state and a QSL state. A quantitative description has been given by numerical calculations considering a power-law probability distribution $P(J) \propto J^{-\gamma}$ ($J$ is the exchange interaction) of random spin singlets. The parameters extracted from the numerical calculations are in excellent agreement with the experimental data. Furthermore, the analytical results are also consistent with the power-law and scaling behavior of $\chi$ and $C_m(T,\mu_0H)/T$ as a whole. Thus, our comprehensive experimental and theoretical analysis provides evidence for the stabilization of the RSS state in a three-dimensional lattice., Comment: 7 pages, 4 figures. Accepted at Physical Review B (Letter)

Published
2024
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8. The burden of atrial fibrillation in the Asia–Pacific region

Author

Wong, Christopher X., Tse, Hung Fat, Choi, Eue-Kuen, Chao, Tze-Fan, Inoue, Koichi, Poppe, Katrina, Tan, Eugene, Yuniadi, Yoga, Fadreguilan, Erdie, Johar, Sofian, Chan, Ngai Yin, Namboodiri, Narayan, Hossain, S. Mokaddas, He, Huang, Chantrarat, Thoranis, Bin Abd Ghani, Abdul Raqib, Davaakhuu, Narantuya, Nwe, Nwe, Irfan, Ghazala, Ton, Minh That, Gunawardena, Rohan, and Sanders, Prashanthan

Published
2024
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10. Progression and Challenges of IoT in Healthcare: A Short Review

Author

Rahman, S M Atikur, Ibtisum, Sifat, Podder, Priya, and Hossain, S. M. Saokat

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Smart healthcare, an integral element of connected living, plays a pivotal role in fulfilling a fundamental human need. The burgeoning field of smart healthcare is poised to generate substantial revenue in the foreseeable future. Its multifaceted framework encompasses vital components such as the Internet of Things (IoT), medical sensors, artificial intelligence (AI), edge and cloud computing, as well as next-generation wireless communication technologies. Many research papers discuss smart healthcare and healthcare more broadly. Numerous nations have strategically deployed the Internet of Medical Things (IoMT) alongside other measures to combat the propagation of COVID-19. This combined effort has not only enhanced the safety of frontline healthcare workers but has also augmented the overall efficacy in managing the pandemic, subsequently reducing its impact on human lives and mortality rates. Remarkable strides have been made in both applications and technology within the IoMT domain. However, it is imperative to acknowledge that this technological advancement has introduced certain challenges, particularly in the realm of security. The rapid and extensive adoption of IoMT worldwide has magnified issues related to security and privacy. These encompass a spectrum of concerns, ranging from replay attacks, man-in-the-middle attacks, impersonation, privileged insider threats, remote hijacking, password guessing, and denial of service (DoS) attacks, to malware incursions. In this comprehensive review, we undertake a comparative analysis of existing strategies designed for the detection and prevention of malware in IoT environments., Comment: 7 pages

Published
2023
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11. Survey on Security Attacks in Connected and Autonomous Vehicular Systems

Author

Hossain, S M Mostaq, Banik, Shampa, Banik, Trapa, and Shibli, Ashfak Md

Subjects
Computer Science - Cryptography and Security, Computer Science - Networking and Internet Architecture
Abstract

Connected and autonomous vehicles, also known as CAVs, are a general trend in the evolution of the automotive industry that can be utilized to make transportation safer, improve the number of mobility options available, user costs will go down and new jobs will be created. However, as our society grows more automated and networked, criminal actors will have additional opportunities to conduct a variety of attacks, putting CAV security in danger. By providing a brief review of the state of cyber security in the CAVs environment, this study aims to draw attention to the issues and concerns associated with security. The first thing it does is categorize the multiple cybersecurity threats and weaknesses in the context of CAVs into three groups: attacks on the vehicles network, attacks on the Internet at large, and other attacks. This is done in accordance with the various communication networks and targets under attack. Next, it considers the possibility of cyber attacks to be an additional form of threat posed by the environment of CAVs. After that, it details the most uptodate defense tactics for securing CAVs and analyzes how effective they are. In addition, it draws some conclusions about the various cyber security and safety requirements of CAVs that are now available, which is beneficial for the use of CAVs in the real world. At the end, we discussed some implications on Adversary Attacks on Autonomous Vehicles. In conclusion, a number of difficulties and unsolved issues for future research are analyzed and explored., Comment: 6 pages, 1 figure, 1 table, Conference info: 2023 IEEE International Conference on Computing (ICOCO)

Published
2023

12. Anomaly Detection Techniques in Smart Grid Systems: A Review

Author

Banik, Shampa, Saha, Sohag Kumar, Banik, Trapa, and Hossain, S M Mostaq

Subjects
Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

Smart grid data can be evaluated for anomaly detection in numerous fields, including cyber-security, fault detection, electricity theft, etc. The strange anomalous behaviors may have been caused by various reasons, including peculiar consumption patterns of the consumers, malfunctioning grid infrastructures, outages, external cyber-attacks, or energy fraud. Recently, anomaly detection of the smart grid has attracted a large amount of interest from researchers, and it is widely applied in a number of high-impact fields. One of the most significant challenges within the smart grid is the implementation of efficient anomaly detection for multiple forms of aberrant behaviors. In this paper, we provide a scoping review of research from the recent advancements in anomaly detection in the context of smart grids. We categorize our study from numerous aspects for deep understanding and inspection of the research challenges so far. Finally, after analyzing the gap in the reviewed paper, the direction for future research on anomaly detection in smart-grid systems has been provided briefly., Comment: 7 pages, 3 figures and conference paper (accepted for publication in 2023 IEEE World AI IOT Congress (AIIOT)

Published
2023

14. Implementing Man-in-the-Middle Attack to Investigate Network Vulnerabilities in Smart Grid Test-bed

Author

Banik, Shampa, Banik, Trapa, Hossain, S. M. Mostaq, and Saha, Sohag Kumar

Subjects
Computer Science - Cryptography and Security
Abstract

The smart-grid introduces several new data-gathering, communication, and information-sharing capabilities into the electrical system, as well as additional privacy threats, vulnerabilities, and cyber-attacks. In this study, Modbus is regarded as one of the most prevalent interfaces for control systems in power plants. Modern control interfaces are vulnerable to cyber-attacks, posing a risk to the entire energy infrastructure. In order to strengthen resistance to cyber-attacks, this study introduces a test bed for cyber-physical systems that operate in real-time. To investigate the network vulnerabilities of smart power grids, Modbus protocol has been examined combining a real-time power system simulator with a communication system simulator and the effects of the system presented and analyzed. The goal is to detect the vulnerability in Modbus protocol and perform the Man-in-the-middle attack with its impact on the system. This proposed testbed can be evaluated as a research model for vulnerability assessment as well as a tool for evaluating cyber-attacks and enquire into any detection mechanism for safeguarding and defending smart grid systems from a variety of cyberattacks. We present here the preliminary findings on using the testbed to identify a particular MiTM attack and the effects on system performance. Finally, we suggest a cyber security strategy as a solution to address such network vulnerabilities and deploy appropriate countermeasures., Comment: 7 pages, 10 figures, Conference paper, Accepted in publication for 2023 IEEE World AI IoT Congress (AIIoT)

Published
2023

15. A New Era of Mobility: Exploring Digital Twin Applications in Autonomous Vehicular Systems

Author

Hossain, S M Mostaq, Saha, Sohag Kumar, Banik, Shampa, and Banik, Trapa

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence
Abstract

Digital Twins (DTs) are virtual representations of physical objects or processes that can collect information from the real environment to represent, validate, and replicate the physical twin's present and future behavior. The DTs are becoming increasingly prevalent in a variety of fields, including manufacturing, automobiles, medicine, smart cities, and other related areas. In this paper, we presented a systematic reviews on DTs in the autonomous vehicular industry. We addressed DTs and their essential characteristics, emphasized on accurate data collection, real-time analytics, and efficient simulation capabilities, while highlighting their role in enhancing performance and reliability. Next, we explored the technical challenges and central technologies of DTs. We illustrated the comparison analysis of different methodologies that have been used for autonomous vehicles in smart cities. Finally, we addressed the application challenges and limitations of DTs in the autonomous vehicular industry., Comment: 7 pages, conference paper, accepted for publication in IEEE AIIoT 2023 conference

Published
2023

19. Dynamic Treatment Regimes using Bayesian Additive Regression Trees for Censored Outcomes

Author

Li, Xiao, Logan, Brent R, Hossain, S M Ferdous, and Moodie, Erica E M

Subjects
Statistics - Methodology
Abstract

To achieve the goal of providing the best possible care to each patient, physicians need to customize treatments for patients with the same diagnosis, especially when treating diseases that can progress further and require additional treatments, such as cancer. Making decisions at multiple stages as a disease progresses can be formalized as a dynamic treatment regime (DTR). Most of the existing optimization approaches for estimating dynamic treatment regimes including the popular method of Q-learning were developed in a frequentist context. Recently, a general Bayesian machine learning framework that facilitates using Bayesian regression modeling to optimize DTRs has been proposed. In this article, we adapt this approach to censored outcomes using Bayesian additive regression trees (BART) for each stage under the accelerated failure time modeling framework, along with simulation studies and a real data example that compare the proposed approach with Q-learning. We also develop an R wrapper function that utilizes a standard BART survival model to optimize DTRs for censored outcomes. The wrapper function can easily be extended to accommodate any type of Bayesian machine learning model.

Published
2022

20. Binary Orthogonal Non-negative Matrix Factorization

Author

Hafshejani, S. Fathi, Gaur, D., Hossain, S., and Benkoczi, R.

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

We propose a method for computing binary orthogonal non-negative matrix factorization (BONMF) for clustering and classification. The method is tested on several representative real-world data sets. The numerical results confirm that the method has improved accuracy compared to the related techniques. The proposed method is fast for training and classification and space efficient.

Published
2022

21. ThoraX-PriorNet: A Novel Attention-Based Architecture Using Anatomical Prior Probability Maps for Thoracic Disease Classification

Author

Hossain, Md. Iqbal, Zunaed, Mohammad, Ahmed, Md. Kawsar, Hossain, S. M. Jawwad, Hasan, Anwarul, and Hasan, Taufiq

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Objective: Computer-aided disease diagnosis and prognosis based on medical images is a rapidly emerging field. Many Convolutional Neural Network (CNN) architectures have been developed by researchers for disease classification and localization from chest X-ray images. It is known that different thoracic disease lesions are more likely to occur in specific anatomical regions compared to others. This article aims to incorporate this disease and region-dependent prior probability distribution within a deep learning framework. Methods: We present the ThoraX-PriorNet, a novel attention-based CNN model for thoracic disease classification. We first estimate a disease-dependent spatial probability, i.e., an anatomical prior, that indicates the probability of occurrence of a disease in a specific region in a chest X-ray image. Next, we develop a novel attention-based classification model that combines information from the estimated anatomical prior and automatically extracted chest region of interest (ROI) masks to provide attention to the feature maps generated from a deep convolution network. Unlike previous works that utilize various self-attention mechanisms, the proposed method leverages the extracted chest ROI masks along with the probabilistic anatomical prior information, which selects the region of interest for different diseases to provide attention. Results: The proposed method shows superior performance in disease classification on the NIH ChestX-ray14 dataset compared to existing state-of-the-art methods while reaching an area under the ROC curve (%AUC) of 84.67. Regarding disease localization, the anatomy prior attention method shows competitive performance compared to state-of-the-art methods, achieving an accuracy of 0.80, 0.63, 0.49, 0.33, 0.28, 0.21, and 0.04 with an Intersection over Union (IoU) threshold of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, and 0.7, respectively., Comment: Accepted to IEEE ACCESS

Published
2022
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29. Structural and Magnetic Characterization of CuxMn1-xFe2O4 (x= 0.0, 0.25) Ferrites Using Neutron Diffraction and Other Techniques

Author

Elius, I. B., Zakaria, A. K. M., Maudood, J., Hossain, S., Islam, M. M., Nahar, A., Hossain, Md Sazzad, and Kamal, I.

Subjects
Condensed Matter - Materials Science
Abstract

Manganese ferrite (MnFe2O4) and copper doped manganese ferrite (Mn0.75Cu0.25Fe2O4) soft materials were synthesized through solid-state sintering method. The phase purity and quality were confirmed from x-ray diffraction patterns. Then the samples were subjected to neutron diffraction experiment and the diffraction data were analyzed using FullProf software package. The surface morphology of the soft material samples was studied using a scanning electron microscope (SEM). Crystal parameters, crystallite parameters, occupancy at A and B sites of the spinel structure, magnetic moments of the atoms at various locations, symmetries, oxygen position parameters, bond lengths etc. were measured and compared with the reference data. In MnFe2O4, both octahedral (A) and tetrahedral (B) positions are shared by Mn2+ and Fe2+/3+ cations, here A site is predominantly occupied by Fe2+ and B site is occupied by Mn at 0.825 occupancy. The Cu2+ ions in Cu0.25Mn0.75Fe2O4 mostly occupy the B site. Copper mostly occupy the Octahedral (16d) sites. The length of the cubic lattice decreases with the increasing Copper content. The magnetic properties, i.e. A or B site magnetic moments, net magnetic moment etc. were measured using neutron diffraction analysis and compared with the bulk magnetic properties measured with VSM studies.

Published
2020

30. Synthesis and Characterization of Strontium Doped Barium Titanates using Neutron Diffraction Technique

Author

Elius, I. B., Asif, B. M., Maudood, J., Datta, T. K., Zakaria, A. K. M., Hossain, S., Aktar, M. S., and Kamal, I.

Subjects
Condensed Matter - Materials Science
Abstract

In the present study, structural changes due to gradual doping of Sr in BaTiO3 were investigated by both x-ray and neutron powder diffraction techniques. Ba1-xSrxTiO3 (x=0.0, 0.5 and 1.0) samples were synthesized by PVA evaporation method and purity was confirmed by x-ray diffraction experiment. After that, neutron diffraction experiments were carried out and diffraction data were analyzed by Rietveld least-square data refinement method using the computer program RIETAN-2000 and FullProf to determine various crystallographic structural parameters. The cation and anion position coordinates were also determined from the data refinement method which confirmed that Ba and Sr atoms possess tetrahedral A site and Ti atoms possess octahedral B site for all three samples BaTiO3, Ba0.5Sr0.5TiO3, and SrTiO3, respectively. Moreover, the lattice parameter values indicate, Ba1-xSrxTiO3 structure undergoes a phase transition from tetragonal to cubic somewhere before x=0.5. The concurrences between observed and calculated profiles were excellent and well consistent with the previously reported values. Furthermore, MEM based analysis was done for charge density measurement.

Published
2020

31. Trends in Annual Maximum Flood Data in New South Wales Australia

Author

Anwar Hossain, S. M., Rahman, Ataur, Ouarda, Taha B. M. J., Singh, V. P., Editor-in-Chief, Berndtsson, R., Editorial Board Member, Rodrigues, L. N., Editorial Board Member, Sarma, Arup Kumar, Editorial Board Member, Sherif, M. M., Editorial Board Member, Sivakumar, B., Editorial Board Member, Zhang, Q., Editorial Board Member, Sherif, Mohsen, editor, Singh, Vijay P., editor, Sefelnasr, Ahmed, editor, and Abrar, M., editor

Published
2023
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34. IJCM_219A: A 'One Health' Model for Prevention and Control of Anthrax in Koraput, Odisha, India

Author

Biswal Sangram, Sahoo P, Satpathy S, Tripathy GK, Papanna M, Sahoo N, and Hossain S

Subjects
bacillus-anthracis, one-health-framework, intersectoral coordination, Public aspects of medicine, RA1-1270
Abstract

Background: Anthrax, a neglected zoonotic disease caused by Bacillus anthracis, poses a significant threat in Odisha, India, particularly in the tribal district of Koraput, which has reported numerous human cases and deaths but lacks consistent robust surveillance. Objectives: This study aimed to pilot a “One Health” surveillance model in Koraput, involving community health workers, para-veterinarians, and block- level teams in outbreak investigations. Methodology: As part of the “One Health Approach to Anthrax Control in India (OHAI)” project Odisha University of Agriculture and Technology (OUAT), in collaboration with the Departments of Animal Husbandry and Health and Family Welfare, Government of Odisha, initiated prospective laboratory-based anthrax surveillance in three blocks of Koraput. Confirmed cases in animals were identified via microscopic, culture, or PCR testing for Bacillus anthracis. Community awareness programs and rapport-building exercises were conducted with human and veterinary officials at the block and district levels following the detection of outbreaks. Results: Between March and June 2023, five anthrax outbreaks were detected in Koraput, with four involving both cutaneous human and animal deaths and one in animals only. Livestock losses included cattle (27), goats (2), and buffalo (1). Of the 38 samples collected (blood, bone, tissue, and soil), 11 (35%) tested positive for anthrax by RT-PCR. OUAT rapidly communicated results (

Published
2024
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35. Coherency and Online Signal Selection Based Wide Area Control of Wind Integrated Power Grid

Author

Thakallapelli, Abilash, Hossain, S J, and Kamalasadan, Sukumar

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

This paper introduces a novel method of designing wide area control (WAC) based on a discrete linear quadratic regulator and Kalman filtering based state-estimation that can be applied for real-time damping of interarea oscillations of wind integrated power grid. The main advantages of the proposed method are that the architecture provides online coherency grouping that properly characterizes real-time changes in the power grid and online wide-area signal selection based on residue method for proper selection of the WAC signals. The proposed architecture can, thus, accurately monitors changes in the power grid and select the appropriate control signal for more effectively damping the interarea oscillation when compared to the conventional local signal based power system stabilizers or offline based WAC designs. The architecture is tested on a wind integrated two-area system and the IEEE 39 bus system in order to show the capability of the proposed method.

Published
2019
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38. High-Utility Pattern Mining Using ULB-Miner

Author

Fageeri, Sallam Osman, Hossain, S. M. Emdad, Arockiasamy, S., Al-Salmi, Taiba Yousef, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Aurelia, Sagaya, editor, Hiremath, Somashekhar S., editor, Subramanian, Karthikeyan, editor, and Biswas, Saroj Kr., editor

Published
2022
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39. Residual Stress Analysis in Large Water Quenched Stainless Steels

Author

Hossain, S., Shirahatti, A. M., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Jonnalagadda, Krishna, editor, Alankar, Alankar, editor, Balila, Nagamani Jaya, editor, and Bhandakkar, Tanmay, editor

Published
2022
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40. Towards Finite Element Modelling of Electrical Activity in Cardiac Tissue Based on Greenstein–Winslow Ventricular Myocyte Model

Author

Mythri, T. G., Hossain, S. J., Bhattacharya, Baidurya, Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, di Mare, Francesca, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Maiti, D. K., editor, Jana, P., editor, Mistry, C. S., editor, Ghoshal, R., editor, Afzal, M. S., editor, Patra, P. K., editor, and Maity, D., editor

Published
2022
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43. High-Performance Bi-2212 Round Wires Made With Recent Powders

Author

Jiang, Jianyi, Bradford, Griffin, Hossain, S Imam, Brown, Michael D, Cooper, Jonathan, Miller, Evan, Huang, Yibing, Miao, Hanping, Parrell, Jeff A, White, Marvis, Hunt, Andrew, Sengupta, Suvankar, Revur, Rao, Shen, Tengming, Kametani, Fumitake, Trociewitz, Ulf P, Hellstrom, Eric E, and Larbalestier, David C

Subjects
Physical Sciences, Condensed Matter Physics, Bi-2212 wire, Superconductor, critical current density, superconducting magnet, Electrical and Electronic Engineering, Materials Engineering, General Physics, Electrical engineering, Condensed matter physics
Abstract

Multifilamentary Bi2Sr2CaCu2Ox (Bi-2212) wire made by the powder-in-tube technique is the only high temperature superconductor made in the round shape preferred by magnet builders. The critical current density (J C ) of Bi-2212 round wire was improved significantly by the development of overpressure heat treatment in the past few years. Bi-2212 wire is commercially available in multiple architectures and kilometer-long pieces and a very promising conductor for very high field NMR and accelerator magnets. We studied the effects of precursor powder and heat treatment conditions on the superconducting properties and microstructure of recent Bi-2212 wires. Short samples of recent wire with optimized overpressure processing showed J C (4.2 K, 15 T) = 6640 A/mm2 and J C (4.2 K, 30 T) = 4670 A/mm2, which correspond to engineering critical current densities J E (4.2 K, 15 T) = 1320 A/mm2 and J E (4.2 K, 30 T) = 930 A/mm2.

Published
2019

47. Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author

Steinmetz, J, Seeher, K, Schiess, N, Nichols, E, Cao, B, Servili, C, Cavallera, V, Cousin, E, Hagins, H, Moberg, M, Mehlman, M, Abate, Y, Abbas, J, Abbasi, M, Abbasian, M, Abbastabar, H, Abdelmasseh, M, Abdollahi, M, Abdollahifar, M, Abd-Rabu, R, Abdulah, D, Abdullahi, A, Abedi, A, Abedi, V, Abeldano Zuniga, R, Abidi, H, Abiodun, O, Aboagye, R, Abolhassani, H, Aboyans, V, Abrha, W, Abualhasan, A, Abu-Gharbieh, E, Aburuz, S, Adamu, L, Addo, I, Adebayo, O, Adekanmbi, V, Adekiya, T, Adikusuma, W, Adnani, Q, Adra, S, Afework, T, Afolabi, A, Afraz, A, Afzal, S, Aghamiri, S, Agodi, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, S, Ahmadzade, A, Ahmed, A, Ahmed, H, Ahmed, J, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Aji, B, Ajumobi, O, Akade, S, Akbari, M, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemi, R, Akonde, M, Al Hasan, S, Alahdab, F, Al-Ahdal, T, Al-Amer, R, Albashtawy, M, Albataineh, M, Aldawsari, K, Alemi, H, Alemi, S, Algammal, A, Al-Gheethi, A, Alhalaiqa, F, Alhassan, R, Ali, A, Ali, E, Ali, L, Ali, M, Ali, R, Ali, S, Shujait Ali, S, Ali, Z, Alif, S, Alimohamadi, Y, Aliyi, A, Aljofan, M, Aljunid, S, Alladi, S, Almazan, J, Almustanyir, S, Al-Omari, B, Alqahtani, J, Alqasmi, I, Alqutaibi, A, Al-Shahi Salman, R, Altaany, Z, Al-Tawfiq, J, Altirkawi, K, Alvis-Guzman, N, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Amani, R, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, M, Amu, H, Amugsi, D, Amusa, G, Amzat, J, Ancuceanu, R, Anderlini, D, Anderson, D, Andrei, C, Androudi, S, Angappan, D, Angesom, T, Anil, A, Ansari-Moghaddam, A, Anwer, R, Arafat, M, Aravkin, A, Areda, D, Ariffin, H, Arifin, H, Arkew, M, Arnlov, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, R, Asadi-Pooya, A, Asena, T, Asghari-Jafarabadi, M, Ashraf, M, Ashraf, T, Atalell, K, Athari, S, Atinafu, B, Atorkey, P, Atout, M, Atreya, A, Aujayeb, A, Avan, A, Ayala Quintanilla, B, Ayatollahi, H, Ayinde, O, Mohammad Ayyoubzadeh, S, Azadnajafabad, S, Azizi, Z, Azizian, K, Azzam, A, Babaei, M, Badar, M, Badiye, A, Baghdadi, S, Bagherieh, S, Bai, R, Baig, A, Balakrishnan, S, Balalla, S, Baltatu, O, Banach, M, Bandyopadhyay, S, Banerjee, I, Baran, M, Barboza, M, Barchitta, M, Bardhan, M, Barker-Collo, S, Barnighausen, T, Barrow, A, Bashash, D, Bashiri, H, Bashiru, H, Basiru, A, Basso, J, Basu, S, Batiha, A, Batra, K, Baune, B, Bedi, N, Begde, A, Begum, T, Behnam, B, Behnoush, A, Beiranvand, M, Bejot, Y, Bekele, A, Belete, M, Belgaumi, U, Bemanalizadeh, M, Bender, R, Benfor, B, Bennett, D, Bensenor, I, Berice, B, Bettencourt, P, Beyene, K, Bhadra, A, Bhagat, D, Bhangdia, K, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, R, Bijani, A, Bikbov, B, Bilalaga, M, Biswas, A, Bitaraf, S, Bitra, V, Bjorge, T, Bodolica, V, Bodunrin, A, Boloor, A, Braithwaite, D, Brayne, C, Brenner, H, Briko, A, Bringas Vega, M, Brown, J, Budke, C, Buonsenso, D, Burkart, K, Burns, R, Bustanji, Y, Butt, M, Butt, N, Butt, Z, Cabral, L, dos Santos, F, Calina, D, Campos-Nonato, I, Cao, C, Carabin, H, Cardenas, R, Carreras, G, Carvalho, A, Castaneda-Orjuela, C, Casulli, A, Catala-Lopez, F, Catapano, A, Caye, A, Cegolon, L, Cenderadewi, M, Cerin, E, Chacon-Uscamaita, P, Chan, J, Chanie, G, Charan, J, Chattu, V, Chekol Abebe, E, Chen, H, Chen, J, Chi, G, Chichagi, F, Chidambaram, S, Chimoriya, R, Ching, P, Chitheer, A, Chong, Y, Chopra, H, Choudhari, S, Chowdhury, E, Chowdhury, R, Christensen, H, Chu, D, Chukwu, I, Chung, E, Coberly, K, Columbus, A, Comachio, J, Conde, J, Cortesi, P, Costa, V, Couto, R, Criqui, M, Cruz-Martins, N, Dabbagh Ohadi, M, Dadana, S, Dadras, O, Dai, X, Dai, Z, D'Amico, E, Danawi, H, Dandona, L, Dandona, R, Darwish, A, Das, S, Dascalu, A, Dash, N, Dashti, M, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Dean, F, Dehghan, A, Dejene, H, Demant, D, Demetriades, A, Demissie, S, Deng, X, Desai, H, Devanbu, V, Dhama, K, Dharmaratne, S, Dhimal, M, Dias da Silva, D, Diaz, D, Dibas, M, Ding, D, Dinu, M, Dirac, M, Diress, M, Do, T, Doan, K, Dodangeh, M, Doheim, M, Dokova, K, Dongarwar, D, Dsouza, H, Dube, J, Duraisamy, S, Durojaiye, O, Dutta, S, Dziedzic, A, Edinur, H, Eissazade, N, Ekholuenetale, M, Ekundayo, T, El Nahas, N, El Sayed, I, Elahi Najafi, M, Elbarazi, I, Elemam, N, Elgar, F, Elgendy, I, Elhabashy, H, Elhadi, M, Elilo, L, Ellenbogen, R, Elmeligy, O, Elmonem, M, Elshaer, M, Elsohaby, I, Emamverdi, M, Emeto, T, Endres, M, Esezobor, C, Eskandarieh, S, Fadaei, A, Fagbamigbe, A, Fahim, A, Faramarzi, A, Fares, J, Farjoud Kouhanjani, M, Faro, A, Farzadfar, F, Fatehizadeh, A, Fathi, M, Fathi, S, Fatima, S, Feizkhah, A, Fereshtehnejad, S, Ferrari, A, Ferreira, N, Fetensa, G, Firouraghi, N, Fischer, F, Fonseca, A, Force, L, Fornari, A, Foroutan, B, Fukumoto, T, Gadanya, M, Gaidhane, A, Galali, Y, Galehdar, N, Gan, Q, Gandhi, A, Ganesan, B, Gardner, W, Garg, N, Gau, S, Gautam, R, Gebre, T, Gebrehiwot, M, Gebremeskel, G, Gebreslassie, H, Getacher, L, Ghaderi Yazdi, B, Ghadirian, F, Ghaffarpasand, F, Ghanbari, R, Ghasemi, M, Ghazy, R, Ghimire, S, Gholami, A, Gholamrezanezhad, A, Ghotbi, E, Ghozy, S, Gialluisi, A, Gill, P, Glasstetter, L, Gnedovskaya, E, Golchin, A, Golechha, M, Goleij, P, Golinelli, D, Gomes-Neto, M, Goulart, A, Goyal, A, Gray, R, Grivna, M, Guadie, H, Guan, B, Guarducci, G, Guicciardi, S, Gunawardane, D, Guo, H, Gupta, B, Gupta, R, Gupta, S, Gupta, V, Gutierrez, R, Habibzadeh, F, Hachinski, V, Haddadi, R, Hadei, M, Hadi, N, Haep, N, Haile, T, Haj-Mirzaian, A, Hall, B, Halwani, R, Hameed, S, Hamiduzzaman, M, Hammoud, A, Han, H, Hanifi, N, Hankey, G, Hannan, M, Hao, J, Harapan, H, Hareru, H, Hargono, A, Harlianto, N, Haro, J, Hartman, N, Hasaballah, A, Hasan, F, Hasani, H, Hasanian, M, Hassan, A, Hassan, S, Hassanipour, S, Hassankhani, H, Hassen, M, Haubold, J, Hay, S, Hayat, K, Hegazy, M, Heidari, G, Heidari, M, Heidari-Soureshjani, R, Hesami, H, Hezam, K, Hiraike, Y, Hoffman, H, Holla, R, Hopf, K, Horita, N, Hossain, M, Hossain, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, S, Hu, C, Huang, J, Huda, M, Hussain, J, Hussein, N, Huynh, H, Hwang, B, Ibitoye, S, Ilaghi, M, Ilesanmi, O, Ilic, I, Ilic, M, Immurana, M, Iravanpour, F, Islam, S, Ismail, F, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iyer, M, Jaan, A, Jacob, L, Jadidi-Niaragh, F, Jafari, M, Jafarinia, M, Jafarzadeh, A, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jaiswal, A, Jakovljevic, M, Jamora, R, Jana, S, Javadi, N, Javed, S, Javeed, S, Jayapal, S, Jayaram, S, Jiang, H, Johnson, C, Johnson, W, Jokar, M, Jonas, J, Joseph, A, Joseph, N, Joshua, C, Jurisson, M, Kabir, A, Kabir, Z, Kabito, G, Kadashetti, V, Kafi, F, Kalani, R, Kalantar, F, Kaliyadan, F, Kamath, A, Kamath, S, Kanchan, T, Kandel, A, Kandel, H, Kanmodi, K, Karajizadeh, M, Karami, J, Karanth, S, Karaye, I, Karch, A, Karimi, A, Karimi, H, Karimi Behnagh, A, Kasraei, H, Kassebaum, N, Kauppila, J, Kaur, H, Kaur, N, Kayode, G, Kazemi, F, Keikavoosi-Arani, L, Keller, C, Keykhaei, M, Khadembashiri, M, Khader, Y, Khafaie, M, Khajuria, H, Khalaji, A, Khamesipour, F, Khammarnia, M, Khan, M, Khan, Y, Suheb, M, Khanmohammadi, S, Khanna, T, Khatab, K, Khatatbeh, H, Khatatbeh, M, Khateri, S, Khatib, M, Khayat Kashani, H, Khonji, M, Khorashadizadeh, F, Khormali, M, Khubchandani, J, Kian, S, Kim, G, Kim, J, Kim, M, Kim, Y, Kimokoti, R, Kisa, A, Kisa, S, Kivimaki, M, Kochhar, S, Kolahi, A, Koly, K, Kompani, F, Koroshetz, W, Kosen, S, Kourosh Arami, M, Koyanagi, A, Kravchenko, M, Krishan, K, Krishnamoorthy, V, Defo, B, Kuddus, M, Kumar, A, Kumar, G, Kumar, M, Kumar, N, Kumsa, N, Kundu, S, Kurniasari, M, Kusuma, D, Kuttikkattu, A, Kyu, H, La Vecchia, C, Ladan, M, Lahariya, C, Laksono, T, Lal, D, Lallukka, T, Lam, J, Lami, F, Landires, I, Langguth, B, Lasrado, S, Latief, K, Latifinaibin, K, Lau, K, Laurens, M, Lawal, B, Le, L, Le, T, Ledda, C, Lee, M, Lee, S, Lee, W, Lee, Y, Leonardi, M, Lerango, T, Li, M, Li, W, Ligade, V, Lim, S, Linehan, C, Liu, C, Liu, J, Liu, W, Lo, C, Lo, W, Lobo, S, Logroscino, G, Lopes, G, Lopukhov, P, Lorenzovici, L, Lorkowski, S, Loureiro, J, Lubinda, J, Lucchetti, G, Saute, R, Ma, Z, Mabrok, M, Machoy, M, Madadizadeh, F, El Razek, M, Maghazachi, A, Maghbouli, N, Mahjoub, S, Mahmoudi, M, Majeed, A, Malagon-Rojas, J, Malakan Rad, E, Malhotra, K, Malik, A, Malik, I, Mallhi, T, Malta, D, Manilal, A, Mansouri, V, Mansournia, M, Marasini, B, Marateb, H, Maroufi, S, Martinez-Raga, J, Martini, S, Martins-Melo, F, Martorell, M, Marz, W, Marzo, R, Massano, J, Mathangasinghe, Y, Mathews, E, Maude, R, Maugeri, A, Maulik, P, Mayeli, M, Mazaheri, M, Mcalinden, C, Mcgrath, J, Meena, J, Mehndiratta, M, Mendez-Lopez, M, Mendoza, W, Mendoza-Cano, O, Menezes, R, Merati, M, Meretoja, A, Merkin, A, Mersha, A, Mestrovic, T, Mi, T, Miazgowski, T, Michalek, I, Mihretie, E, Minh, L, Mirfakhraie, R, Mirica, A, Mirrakhimov, E, Mirzaei, M, Misganaw, A, Misra, S, Mithra, P, Mizana, B, Mohamadkhani, A, Mohamed, N, Mohammadi, E, Mohammadi, H, Mohammadi, S, Mohammadshahi, M, Mohammed, M, Mohammed, S, Mohan, S, Mojiri-Forushani, H, Moka, N, Mokdad, A, Molinaro, S, Moller, H, Monasta, L, Moniruzzaman, M, Montazeri, F, Moradi, M, Moradi, Y, Moradi-Lakeh, M, Moraga, P, Morovatdar, N, Morrison, S, Mosapour, A, Mosser, J, Mossialos, E, Motaghinejad, M, Mousavi, P, Ehsan Mousavi, S, Mubarik, S, Muccioli, L, Mughal, F, Mukoro, G, Mulita, A, Mulita, F, Musaigwa, F, Mustafa, A, Mustafa, G, Muthu, S, Nagarajan, A, Naghavi, P, Naik, G, Nainu, F, Nair, T, Najmuldeen, H, Nakhostin Ansari, N, Nambi, G, Namdar Areshtanab, H, Nargus, S, Nascimento, B, Naser, A, Nashwan, A, Nasoori, H, Nasreldein, A, Natto, Z, Nauman, J, Nayak, B, Nazri-Panjaki, A, Negaresh, M, Negash, H, Negoi, I, Negoi, R, Negru, S, Nejadghaderi, S, Nematollahi, M, Nesbit, O, Newton, C, Nguyen, D, Nguyen, H, Nguyen, N, Nguyen, P, Nguyen, V, Niazi, R, Nikolouzakis, T, Niranjan, V, Nnyanzi, L, Noman, E, Noroozi, N, Norrving, B, Noubiap, J, Nri-Ezedi, C, Ntaios, G, Nunez-Samudio, V, Nurrika, D, Oancea, B, Odetokun, I, O'Donnell, M, Ogunsakin, R, Oguta, J, Oh, I, Okati-Aliabad, H, Okeke, S, Okekunle, A, Okonji, O, Okwute, P, Olagunju, A, Olaiya, M, Olana, M, Olatubi, M, Oliveira, G, Olufadewa, I, Olusanya, B, Bali, A, Ong, S, Onwujekwe, O, Ordak, M, Orji, A, Ortega-Altamirano, D, Osuagwu, U, Otstavnov, N, Otstavnov, S, Ouyahia, A, Owolabi, M, Mahesh Padukudru, P, Pacheco-Barrios, K, Padubidri, J, Pal, P, Palange, P, Palladino, C, Palladino, R, Palma-Alvarez, R, Pan, F, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Pandian, J, Pangaribuan, H, Pantazopoulos, I, Pardhan, S, Parija, P, Parikh, R, Park, S, Parthasarathi, A, Pashaei, A, Patel, J, Patil, S, Patoulias, D, Pawar, S, Pedersini, P, Pensato, U, Pereira, D, Pereira, J, Pereira, M, Peres, M, Perico, N, Perna, S, Petcu, I, Petermann-Rocha, F, Pham, H, Phillips, M, Pinilla-Monsalve, G, Piradov, M, Plotnikov, E, Poddighe, D, Polat, B, Poluru, R, Pond, C, Poudel, G, Pouramini, A, Pourbagher-Shahri, A, Pourfridoni, M, Pourtaheri, N, Prakash, P, Prakash, S, Prakash, V, Prates, E, Pritchett, N, Purnobasuki, H, Qasim, N, Qattea, I, Qian, G, Radhakrishnan, V, Raee, P, Shahraki, H, Rafique, I, Raggi, A, Raghav, P, Rahati, M, Rahim, F, Rahimi, Z, Rahimifard, M, Rahman, M, Rahmani, A, Rahmani, S, Youshanlouei, H, Rahmati, M, Raj Moolambally, S, Rajabpour-Sanati, A, Ramadan, H, Ramasamy, S, Ramasubramani, P, Ramazanu, S, Rancic, N, Rao, I, Rao, S, Rapaka, D, Rashedi, V, Rashid, A, Rashidi, M, Rashidi Alavijeh, M, Rasouli-Saravani, A, Rawaf, S, Razo, C, Redwan, E, Bana, A, Remuzzi, G, Rezaei, N, Rezaeian, M, Rhee, T, Riad, A, Robinson, S, Rodrigues, M, Rodriguez, J, Roever, L, Rogowski, E, Romoli, M, Ronfani, L, Roy, P, Pramanik, K, Rubagotti, E, Ruiz, M, Russ, T, Sunnerhagen, K, Saad, A, Saadatian, Z, Saber, K, Saberikamarposhti, M, Sacco, S, Saddik, B, Sadeghi, E, Sadeghian, S, Saeed, U, Safdarian, M, Safi, S, Sagar, R, Sagoe, D, Saheb Sharif-Askari, F, Saheb Sharif-Askari, N, Sahebkar, A, Sahoo, S, Sahraian, M, Sajedi, S, Sakshaug, J, Saleh, M, Salehi Omran, H, Salem, M, Salimi, S, Samadi Kafil, H, Samadzadeh, S, Samargandy, S, Samodra, Y, Samuel, V, Samy, A, Sanadgol, N, Sanjeev, R, Sanmarchi, F, Santomauro, D, Santri, I, Santric-Milicevic, M, Saravanan, A, Sarveazad, A, Satpathy, M, Saylan, M, Sayyah, M, Scarmeas, N, Schlaich, M, Schuermans, A, Schwarzinger, M, Schwebel, D, Selvaraj, S, Sendekie, A, Sengupta, P, Senthilkumaran, S, Serban, D, Sergindo, M, Sethi, Y, Seyedalinaghi, S, Seylani, A, Shabani, M, Shabany, M, Shafie, M, Shahabi, S, Shahbandi, A, Shahid, S, Shahraki-Sanavi, F, Shahsavari, H, Shahwan, M, Shaikh, M, Shaji, K, Sham, S, Shama, A, Shamim, M, Shams-Beyranvand, M, Shamsi, M, Shanawaz, M, Sharath, M, Sharfaei, S, Sharifan, A, Sharma, M, Sharma, R, Shashamo, B, Shayan, M, Sheikhi, R, Shekhar, S, Shen, J, Shenoy, S, Shetty, P, Shiferaw, D, Shigematsu, M, Shiri, R, Shittu, A, Shivakumar, K, Shokri, F, Shool, S, Shorofi, S, Shrestha, S, Siankam Tankwanchi, A, Siddig, E, Sigfusdottir, I, Silva, J, Silva, L, Sinaei, E, Singh, B, Singh, G, Singh, P, Singh, S, Sirota, S, Sivakumar, S, Sohag, A, Solanki, R, Soleimani, H, Solikhah, S, Solomon, Y, Song, S, Song, Y, Sotoudeh, H, Spartalis, M, Stark, B, Starnes, J, Starodubova, A, Stein, D, Steiner, T, Stovner, L, Suleman, M, Abdulkader, R, Sultana, A, Sun, J, Sunkersing, D, Sunny, A, Susianti, H, Swain, C, Szeto, M, Tabares-Seisdedos, R, Tabatabaei, S, Tabatabai, S, Tabish, M, Taheri, M, Tahvildari, A, Tajbakhsh, A, Tampa, M, Lukenze Tamuzi, J, Tan, K, Tang, H, Tareke, M, Tarigan, I, Tat, N, Tat, V, Tavakoli Oliaee, R, Tavangar, S, Tavasol, A, Tefera, Y, Tehrani-Banihashemi, A, Temesgen, W, Temsah, M, Teramoto, M, Tesfaye, A, Tesfaye, E, Tesler, R, Thakali, O, Thangaraju, P, Thapa, R, Thapar, R, Thomas, N, Thrift, A, Ticoalu, J, Tillawi, T, Toghroli, R, Tonelli, M, Tovani-Palone, M, Traini, E, Tran, N, Van Tran, P, Tromans, S, Truelsen, T, Truyen, T, Tsatsakis, A, Tsegay, G, Tsermpini, E, Tualeka, A, Tufa, D, Ubah, C, Udoakang, A, Ulhaq, I, Umair, M, Umakanthan, S, Umapathi, K, Unim, B, Unnikrishnan, B, Vaithinathan, A, Vakilian, A, Tahbaz, S, Valizadeh, R, Van den Eynde, J, Vart, P, Varthya, S, Vasankari, T, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Verras, G, Vervoort, D, Villafane, J, Villani, L, Veloz, A, Viskadourou, M, Vladimirov, S, Vlassov, V, Volovat, S, Vu, L, Vujcic, I, Wagaye, B, Waheed, Y, Wahood, W, Walde, M, Wang, F, Wang, S, Wang, Y, Waqas, M, Waris, A, Weerakoon, K, Weintraub, R, Weldemariam, A, Westerman, R, Whisnant, J, Wickramasinghe, D, Wickramasinghe, N, Willekens, B, Wilner, L, Winkler, A, Wolfe, C, Wu, A, Wulf Hanson, S, Xu, S, Xu, X, Yadollahpour, A, Yaghoubi, S, Yahya, G, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yehualashet, S, Yeshaneh, A, Yesiltepe, M, Yi, S, Yigit, A, Yigit, V, Yon, D, Yonemoto, N, You, Y, Younis, M, Yu, C, Yusuf, H, Zadey, S, Zahedi, M, Zakham, F, Zaki, N, Zali, A, Zamagni, G, Zand, R, Zandieh, G, Zangiabadian, M, Zarghami, A, Zastrozhin, M, Zeariya, M, Zegeye, Z, Zeukeng, F, Zhai, C, Zhang, C, Zhang, H, Zhang, Y, Zhang, Z, Zhao, H, Zhao, Y, Zheng, P, Zhou, H, Zhu, B, Zhumagaliuly, A, Zielinska, M, Zikarg, Y, Zoladl, M, Murray, C, Ong, K, Feigin, V, Vos, T, Dua, T, Steinmetz J. D., Seeher K. M., Schiess N., Nichols E., Cao B., Servili C., Cavallera V., Cousin E., Hagins H., Moberg M. E., Mehlman M. L., Abate Y. H., Abbas J., Abbasi M. A., Abbasian M., Abbastabar H., Abdelmasseh M., Abdollahi M., Abdollahifar M. -A., Abd-Rabu R., Abdulah D. M., Abdullahi A., Abedi A., Abedi V., Abeldano Zuniga R. A., Abidi H., Abiodun O., Aboagye R. G., Abolhassani H., Aboyans V., Abrha W. A., Abualhasan A., Abu-Gharbieh E., Aburuz S., Adamu L. H., Addo I. Y., Adebayo O. M., Adekanmbi V., Adekiya T. A., Adikusuma W., Adnani Q. E. S., Adra S., Afework T., Afolabi A. A., Afraz A., Afzal S., Aghamiri S., Agodi A., Agyemang-Duah W., Ahinkorah B. O., Ahmad A., Ahmad D., Ahmad S., Ahmadzade A. M., Ahmed A., Ahmed H., Ahmed J. Q., Ahmed L. A., Ahmed M. B., Ahmed S. A., Ajami M., Aji B., Ajumobi O., Akade S., Akbari M., Akbarialiabad H., Akhlaghi S., Akinosoglou K., Akinyemi R. O., Akonde M., Al Hasan S. M., Alahdab F., Al-Ahdal T. M. A., Al-Amer R. M., Albashtawy M., AlBataineh M. 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Abstract

Background: Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods: We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous s

Published
2024

50. Estimation of Rain Attenuation at EHF bands for Earth-to-Satellite Links in Bangladesh

Author

Hossain, S Md Sakir and Islam, Md Atiqul

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Due to heavy congestion in lower frequency bands, engineers are looking for new frequency bands to support new services that require higher data rates, which in turn needs broader bandwidths. To meet this requirement, extremely high frequency (EHF), particularly Q (36 to 46 GHz) and V (46 to 56 GHz) bands, is the best viable solution because of its complete availability. The most serious challenge the EHF band poses is the attenuation caused by rain. This paper investigates the effect of the rain on Q and V bands' performances in Bangladeshi climatic conditions. The rain attenuations of the two bands are predicted for the four main regions of Bangladesh using ITU rain attenuation model. The measured rain statistics is used for this prediction. It is observed that the attenuation due to rain in the Q/V band reaches up to 150 dB which is much higher than that of the currently used Ka band. The variability of the rain attenuation is also investigated over different sessions of Bangladesh. The attenuation varies from 40 dB to 170 dB depending on the months. Finally, the amount of rain fade required to compensate the high rain attenuation is also predicted for different elevation angles., Comment: Int'l Conf. on Electrical, Computer and Communication Engineering (IEEE sponsored), Cox's Bazar, Bangladesh, February 2017, pp. 589-593

Published
2017
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