Search Everything
Tip: Search using "First Name + Last Name", e.g.
János Kiss instead of
Kiss János.
Authors - 9813
Publications - 6374
Comprehensive Analysis of Radial- and Axial Flux Synchronous Reluctance Machines for Electric Vehicle Applications
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2026-01-01
Volume: 1768 LNNS
Issue: Unknown
Page Range: 399-420
Description:
Synchronous Reluctance Machines (SRMs) have been gaining considerable research interest recently because of the absence of the permanent magnets (no rare-earth materials), their robust construction and high partial load efficiency. Their inherently lower torque density compared to permanent magnet synchronous machines remains a challenge. However, adopting an axial flux topology could potentially improve this feature. This paper analyzes the properties of the axial flux configuration and compares them with those of the traditional radial flux topology for synchronous reluctance machines used in electric vehicles. The paper focuses on the differences in the torque-production, in the efficiency, in the torque densities and in the weight and the physical dimensions. Additionally, this paper examines the material costs for the two machine types and investigates their predicted future prices to determine the more cost-effective solution for electric vehicle applications. Simulation investigations will be carried out to examine these properties. It will be shown that the axial flux topology is an attractive alternative to the nowadays widely used radial flux one in the case of synchronous reluctance machines of electric vehicles.
Open Access: Yes
Assessing and evaluating potential systems resilience
Publication Name: 2024 IEEE 15th International Conference on Cognitive Infocommunications Coginfocom 2024
Publication Date: 2024-01-01
Volume: Unknown
Issue: Unknown
Page Range: 43-50
Description:
The hierarchy of semantic networks can also be observed in the functioning of economic systems. There are uncertainties in semantic networks, meaning that the classification of different attributes is not always clear. The same uncertainty is also present, for example, in the design of logistics strategies as a sub-strategy of the economy, which can lead to inconsistencies between the parameters of the system. It is important for a system to be resilient to both internal and external influences, and it is, therefore, necessary to develop a hierarchy of system parameters based on the semantic network's method and to examine the relationship between parameters in order to achieve resilience and long-term sustainability.
Open Access: Yes
Global, regional, and national sepsis incidence and mortality, 1990–2021: a systematic analysis
Usha Adiga
Samah W. Al-Jabi
Meriem Abdoun
Quique Bassat
Zulfiqar A. Bhutta
Hany Aly
Ashish Bhargava
Hasan Yaser Alniss
Razique Anwer
Abdul Monim Batiha
Asrat Agalu Abejew
Samar Abd ElHafeez
Mahwish Arooj
Matteo Bauckneht
Mohammad R. Alqudimat
Alok Atreya
Abdelazeem M. Algammal
Saeid Anvari
Auwal Abdullahi
Tahira Ashraf
Shereen M. Aleidi
Mohammad R. Alosta
Senthilkumar Balakrishnan
Zarrin Basharat
Montaha Al-Iede
Nasir Abbas
Syed Shujait Ali
Williams Agyemang-Duah
Sahel Majed Alrousan
Lucien R. Swetschinski
Sonu Bhaskar
Anayochukwu Edward Anyasodor
Lisa C. Adams
Ahmad Naoras Bitar
Madineh Abbasi
Habib Benzian
Intima Alrimawi
Nicole Davis Weaver
Mohammed Albashtawy
Meshack Achore
Domenico Azzolino
Eve E. Wool
Kamoru Ademola Adedokun
Fahad A. Alhumaydhi
Ahmad Alrawashdeh
Aqeel Ahmad
Simachew Animen Bante
Nelson Alvis-Guzman
Umar Muhammad Bello
Rafat Ali
Kevin S. Ikuta
Qorinah Estiningtyas Sakilah Adnani
Rajon Banik
Amadou Barrow
Mina Borran
Wondu Feyisa Balcha
Chieh Han
Gasha Salih Ahmed
Aanuoluwapo Adeyimika Afolabi
Alaa Aboelnour Badran
Anna Gershberg Hayoon
Hamed Borhany
Nikha Bhardwaj
Ahmad Rajeh Al-Qudimat
Najim Z. Alshahrani
Fentahun Alemnew
Mesfin Abebe
Md Akib Al-Zubayer
Ema Akter
Ridwan Olamilekan Adesola
Ali Azargoonjahromi
Authia P. Gray
Mahsa Ahadi
Mohammed Usman Ali
Zelalem Asmare
Hana J. Abukhadijah
Alemwork Abie
Amani Alansari
Asnake Gashaw Belayneh
Yaser Mohammed Al-Worafi
Filippos Anagnostakis
Daniel T. Araki
Hassan Abolhassani
Sabah Al-Marwani
Gokce Belge Bilgin
Mohammad Mahdi Bastan
Meqdad Saleh Ahmed
Rebecca L. Hsu
Abiye Assefa Berihun
Erin Chung
Hiba Jawdat Barqawi
Julie Alaere Atta
Nurila Aryntayeva
Wakgari Mosisa Abdisa
Qorinah Estiningtyas Sakilah Adnani
Redeat Libanos Assefa
Syed Anees Ahmed
Haroon Ahmed
Sadat Abdulla Aziz
Avinash Aujayeb
Tomislav Mestrovic
Publication Name: Lancet Global Health
Publication Date: 2025-12-01
Volume: 13
Issue: 12
Page Range: e2013-e2026
Description:
Background: The global burden of sepsis, a life-threatening dysregulated host response to infection leading to organ dysfunction, remains challenging to quantify. We aimed to comprehensively estimate the global, regional, and national burden of sepsis, including the impact of the COVID-19 pandemic and underlying causes of sepsis-related deaths with co-occurring infectious syndromes. Methods: We used multiple cause-of-death, hospital, minimally invasive tissue sampling, and linked death certificate and hospital record data representing 149 million deaths, covering 4290 location-years with mortality estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 to capture explicit and implicit sepsis cases and deaths. We estimated age-location-sex-specific fractions of sepsis-related deaths from 195 underlying causes of death and 22 infectious syndromes from 1990 to 2021 using binomial logistic regression models, and estimated sepsis-related deaths using GBD cause-specific mortality estimates. Using 250 million hospital admissions and 7·82 million deaths from hospital data, representing 1310 location-years, we modelled case fatality rates by use of binomial logistic regression, applied to sepsis death estimates to estimate sepsis incidence by age, location, and year. Findings: In 2021, we estimated 166 million (95% uncertainty interval 135–201) sepsis cases and 21·4 million (20·3–22·5) all-cause sepsis-related deaths globally, representing 31·5% of total global deaths. Sepsis-related deaths decreased between 1990 and 2019, followed by a surge in 2020 and 2021. As of 2021, individuals aged 15 years and older experienced increases across incidence (230%) and mortality (26·3%) since 1990. Those aged 70 years and older had the highest sepsis-related mortality in 2021 (9·28 million [8·74–9·86] deaths). Sepsis-related deaths from infectious underlying causes decreased from 11·8 million (11·1–12·5) in 1990 to 8·34 million (7·72–9·01) in 2019, then increased by 86·4% to 15·5 million (14·7–16·4) in 2021. Sepsis-related mortality due to non-infectious underlying causes of death increased from 4·69 million (4·35–5·05) in 1990 to 5·81 million (5·40–6·25) in 2021; the leading non-infectious underlying causes of death with sepsis were stroke, chronic obstructive pulmonary disease, and cirrhosis. In 2021, bloodstream infections inclusive of HIV and malaria (3·08 million [2·83–3·35]) and lower respiratory infections inclusive of COVID-19 (11·33 million [1·20–1·47]) were the most prominent infectious syndromes complicating sepsis-related deaths from non-infectious underlying causes, representing a consistent trend since 1990. Interpretation: The global burden of sepsis increased in 2020 and 2021, reversing progress from 1990. Sepsis incidence and mortality increased in people aged 15 years and older, especially those aged 70 years and older, and as a complication of non-infectious underlying causes of death such as stroke, primarily through bloodstream infections and lower respiratory infections. The global burden of sepsis is substantial, and sepsis is increasingly a complication of non-infectious causes of death. Funding: Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.
Open Access: Yes
Green Marketing in the Digital Age: A Systematic Literature Review
Publication Name: Sustainability Switzerland
Publication Date: 2023-08-01
Volume: 15
Issue: 16
Page Range: Unknown
Description:
This research aims to analyze and synthesize the research articles published over the past ten years, from 2012 to 2022, that deal with green marketing and digital marketing. The objective is to track the evolution of research in the field and to understand the trends on which the area has been researched during that period. The paper is based on a database of 54 research articles published in the specified period. This paper is not limited to specific journals; only the topics and the period are specified. The database analysis describes the topic and perspective of the article, the methodology used, and the themes, in addition to other factors of the given research. The main finding of this research is the identification of five main themes or categories within the research area: strategies, challenges, promotion, consumers, and digital media. These themes provide valuable insights for practitioners and scholars and ultimately benefit the broader community by providing information on decision-making and promoting sustainability in digital marketing and green marketing. This paper will help researchers better understand the research trends in the field and acquire some up-to-date knowledge about the research related to digital marketing and green marketing.
Open Access: Yes
DOI: 10.3390/su151612369
Legal Challenges for Automated Decision-Making in Self-Driving Vehicles—Liability Issues and Remedies †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Rapid advancements in technology have resulted in the proliferation of self-driving vehicles, which have already presented significant challenges to the field of legal science. In the context of automated decision-making, the question of liability is invariably pertinent. The question of whether liability should be assigned to a non-human entity or to a group of people is a contentious one. Furthermore, the question of which entity should be held liable for compensation for damage caused and which entity should be criminally liable remains unresolved. In the context of self-driving vehicles operating at a lower level of automation, the identification of the driver’s liability, ostensibly a straightforward undertaking, gives rise to a multitude of intricate ethical dilemmas. In addition to the prevailing assumptions regarding liability, which have previously been discussed in detail in the literature, the study also addresses the issue of transparency in automated decision-making related to legal remedies.
Open Access: Yes
Creep model to determine rut development by autonomous truck axles on pavement
Publication Name: Pollack Periodica
Publication Date: 2022-04-30
Volume: 17
Issue: 1
Page Range: 66-71
Description:
Impacts of autonomous truck's passes on pavement have been analyzed in this research. Two types of lateral positioning namely zero wander and uniform wander along with a super single wide tire and a dual tire have been analyzed with variable traffic speeds in ABQUS. The study concludes with the results in favor of usage of a super single wide tire under a uniform wander mode. The highest amount of pavement damage in terms of maximum rut depth is caused by the dual wheel assembly moving under a zero-wander mode. The magnitude of rut depth increases by a factor of two when a dual tire assembly is used instead of a wide tire assembly. At a uniform wander mode, rut depth increases by 0.2 mm for every 10 km/h decrease in traffic speed within 90 km/h to 70 km/h range.
Open Access: Yes
Multibody Simulation of Helical Gear Noise and Vibration Behavior Using MSC ADAMS †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
The premium electric-vehicle market demands exceptionally quiet transmissions because the absence of engine masking makes gearbox noise more perceptible. Virtual NVH (noise, vibration, and harshness) evaluation requires coupling elastic deformation, gear–tooth contact, and vibration transmission through bearings and housing within a single environment. This study develops an integrated workflow in MSC ADAMS for predicting the NVH behavior of a 23/81-tooth helical gear pair. Finite element-based flank stiffness is imported, and a nonlinear contact model is applied to flexible teeth. Baseline simulation at 50 Nm and 200 rpm yields a static transmission error (TE) of 7.5 µm and a dynamic peak-to-peak TE of 0.7 µm, with the fundamental mesh tone at 77 Hz. Increasing tip relief by +0.10 mm lowers RMS TE by 31% and the first mesh order by 3.1 dB while raising the flank pressure from 1.65 GPa to 1.88 GPa. The workflow efficiently supports early-stage gear-noise optimization prior to the development of physical prototypes.
Open Access: Yes
Limit design of reinforced concrete haunched beams by the control of the residual plastic deformation
Publication Name: Structures
Publication Date: 2022-05-01
Volume: 39
Issue: Unknown
Page Range: 987-996
Description:
In this paper, a novel computational (optimization) model is presented to control the plastic behaviour of reinforced concrete haunched beams using complementary strain energy of residual forces formed inside the steel reinforcing bars. For this purpose, a numerical model validation process was held and then two non-linear optimization problems were outlined. In these optimization problems, different objective functions were considered applying the optimal elasto-plastic analysis and design of haunched reinforced concrete beams aiming to find the maximal loading or the minimum volume of the steel used to reinforce the beams as the plastic deformations are controlled by using constraints on the complementary strain energy of the residual internal forces of the steel bars. Moreover, the effect of these constraints on different haunch angle beams is studied. The applied method is described in terms of nonlinear mathematical programming and providing solutions when the plastic reserves of the body are not fully exhausted. It is worth mentioning that in this study a concrete damage plasticity constitutive model is applied in the numerical problems and calibrated in accordance with the data gained from laboratory tests. The optimal solutions of the nonlinear mathematical problems were calculated by MATLAB programming codes written by the authors taking into consideration different objective functions and equality and inequality constraints for each case. Finally, by performing a parametric study, the different optimization problems showed how beams behaved differently under different complementary strain energy limit values shifting from elastic into elasto-plastic state and then reaches the fully plastic state where results showed different comparisons taking into consideration the effect of the different complementary strain energy limit values on the maximum applied load, geometry of the beam and steel volume used to reinforce the beams. Thus, complementary strain energy limit value is used to control the plastic deformation inside steel bars during loading progress where avoiding the formation of the plastic deformation in the steel bars would reflect on the general behaviour of the haunched reinforced concrete beams.
Open Access: Yes
Trends and insights from bibliometric analysis for mapping artificial intelligence and machine learning in sustainable development
Publication Name: Discover Sustainability
Publication Date: 2026-12-01
Volume: 7
Issue: 1
Page Range: Unknown
Description:
Rapid population growth, environmental degradation and persistent urgency of climate change have intensified the global search for sustainable development solutions. Governments, researchers and institutions alike face the challenge of balancing economic progress with social equity and environmental protection. In response, recent scholarships have increasingly turned to digital technologies as potential enablers of sustainable transformation. This study addresses the need to understand how artificial intelligence (AI) and machine learning (ML) are being incorporated into sustainable development strategies, with a particular focus on mapping knowledge trends and research patterns. Using bibliometric analysis of SCOPUS data spanning 2015 to 2024, the study uncovers the evolution of research topics, highlights influential authors and institutions, and traces the diffusion of ideas across disciplines. The findings reveal that AI and ML are emerging as key drivers of sustainability, with strong applications in energy and emission management, environmental monitoring, climate change mitigation, precision agriculture and water resource management. Research in this area has grown rapidly over the past decade, shifting from theory to real applications. It also highlights that China's and the United States dual dominance in both publication volume and citation impact, while also recognizing the contributions of other countries like India, the United Kingdom and Australia in shaping global research landscapes. Three main implications arise from these results. For policymakers, the evidence underscores the urgency of designing inclusive policies, investing in digital infrastructure, and fostering global cooperation to ensure the equitable distribution of technological benefits. For the research community, the study points to opportunities for cross-disciplinary collaborations that link technological innovation with real-world sustainability challenges. From a broader societal perspective, the findings emphasize the importance of knowledge sharing and technology transfer, enabling both developed and developing countries to advance collectively toward achieving the Sustainable Development Goals.
Open Access: Yes
