Yavuz Yasul | Health Sciences | Best Scholar Award

Published on by Research Scientist

Dr. Yavuz Yasul | Health Sciences | Best Scholar Award

Dr. Yavuz Yasul, Ondokuz Mayis University, Turkey

Yavuz Yasul is a dedicated researcher and academic, currently serving as a lecturer at Ondokuz Mayıs University, Bafra Vocational School, in the Department of Property Protection and Security. He specializes in exercise physiology, metabolic health, and sports sciences. With a solid academic background and consistent research output, Yasul plays a vital role in advancing knowledge in the intersections of physical activity, supplementation, and biochemical adaptations.

Professional Profile

ORCID

🎓 Education and Experience

Yavuz Yasul earned his Ph.D. in Physical Education and Sports from Inonu University in 2021, where his dissertation focused on the effects of Coenzyme Q10 supplementation on serum, cardiac, and skeletal muscle tissue in rats subjected to various exercise regimes. Prior to this, he completed his Master’s degree (M.Sc.) in 2016 at Kahramanmaraş Sütçü İmam University, where his thesis explored the psychological needs of physical education students. He began his academic journey with a Bachelor’s degree in Physical Education and Sports Teaching from Mustafa Kemal University in 2014. Yasul has been serving as a Lecturer at Ondokuz Mayıs University since April 2019 and was appointed Head of Department in August 2020. In his current role, he teaches a variety of courses, including Physical Activity and Health, Strength Training, and Behavioral Sciences, while also supervising graduate research and contributing to academic program coordination.

📈 Professional Development

Yasul is continuously involved in professional growth through national and international academic collaborations, research projects, and teaching innovations. He integrates current trends in exercise science with applied research in physiology, helping students and professionals understand emerging practices in health and performance.

In 2024, Yasul was nominated for the 3rd International Food Scientist Awards by the Ministry of Corporate Affairs, Government of India, for his contributions to scientific research related to exercise metabolism and supplementation.

🔬 Research Focus

Yasul’s research spans multiple dimensions of sports science, with a primary focus on exercise physiology and training adaptations. He is particularly interested in the role of Coenzyme Q10 supplementation in enhancing physical performance and recovery. His work also delves into oxidative stress and inflammation, exploring how these processes interact with physical training and nutritional interventions. He investigates the microbiota-gut-brain axis to understand its impact on mental and physical health, as well as the biological mechanisms underlying aging and telomere dynamics in relation to physical activity. Through his studies, Yasul aims to uncover how exercise and dietary supplements modulate molecular pathways, ultimately contributing to disease prevention, healthy aging, and athletic performance optimization.

🏅Awards and Honors 

Yasul has served as both Principal Investigator and Collaborator on several nationally funded research grants, contributing significantly to the advancement of sports science and exercise physiology. He is a regular peer reviewer for reputable journals in the fields of sports medicine and nutritional science, reflecting his active engagement with the academic community. In addition to his research contributions, he frequently delivers lectures and seminars on topics such as supplementation strategies, training periodization, and oxidative stress biomarkers. At Ondokuz Mayıs University, he plays a key role in academic curriculum design and is deeply involved in student mentorship, fostering both academic growth and research development among his students.

📚Publication Top Notes

1. Core Exercise as a Non-Pharmacological Strategy for Improving Metabolic Health in Prediabetic Women
Medicina, 2025-05-21
DOI: 10.3390/medicina61050942
Authors: Nuray Yiğiter, Faruk Akçınar, Yavuz Yasul, Vedat Çınar, Taner Akbulut, Gian Mario Migliaccio

Summary:
This study investigates the effects of a core-focused exercise regimen on metabolic health parameters in prediabetic women. The researchers aimed to determine whether targeted core exercises could serve as an effective non-pharmacological intervention to improve insulin sensitivity and lipid profiles. The findings suggest that incorporating core exercises into regular physical activity routines may significantly enhance metabolic health, offering a viable alternative to medication for managing prediabetes.

2. Evaluating the Impact of Coenzyme Q10 and High-Intensity Interval Training on Lactate Threshold and Plasma Blood Gases in Rats: A Randomized Controlled Trial
European Journal of Applied Physiology, 2025-03-18
DOI: 10.1007/s00421-025-05756-8
Authors: Yavuz Yasul, Büşra Yılmaz, Ömer Şenel, Dursun Kurt, Taner Akbulut, Ayşen Çalıkuşu, Elvan Anadol, Canan Yılmaz

Summary:
This randomized controlled trial examined the combined effects of Coenzyme Q10 supplementation and high-intensity interval training (HIIT) on lactate threshold and plasma blood gases in rats. The study found that the combination of CoQ10 and HIIT significantly improved lactate clearance and enhanced oxygen transport capacity, indicating improved metabolic efficiency and recovery post-exercise. These results suggest potential benefits of CoQ10 supplementation in conjunction with HIIT for enhancing athletic performance and recovery.

3. Moderate/High-Intensity Exercise and Coenzyme Q10 Supplementation May Reduce Tumstatin and Improve Lipid Dynamics and Body Mass in Rats
Applied Sciences, 2025-02-28
DOI: 10.3390/app15052618
Authors: Yavuz Yasul, Faruk Akçınar, Vedat Çınar, Taner Akbulut, İsa Aydemir, Mehmet Hanifi Yalçın, Emsal Çağla Avcu, Suna Aydın, Süleyman Aydın

Summary:
This study explored the effects of varying intensities of exercise combined with Coenzyme Q10 supplementation on tumstatin levels, lipid profiles, and body mass in rats. The findings revealed that both moderate and high-intensity exercise, when paired with CoQ10 supplementation, led to significant reductions in tumstatin levels and improvements in lipid metabolism and body mass. These results highlight the potential of combining exercise with CoQ10 supplementation as a strategy for managing obesity and related metabolic disorders.

4. The Regulatory Effects of Exercise and Metformin on Biomarkers in Obesity: A Focus on Uric Acid, Irisin, Adiponutrin, Adropin, and Copeptin
Medicina, 2025-02-25
DOI: 10.3390/medicina61030399
Authors: Taner Akbulut, Vedat Çınar, Emsal Çağla Avcu, Yavuz Yasul, İsa Aydemir, Tuncay Kuloğlu, Gökhan Artaş, Süleyman Aydın

Summary:
This research focused on the combined effects of exercise and metformin treatment on various biomarkers associated with obesity, including uric acid, irisin, adiponutrin, adropin, and copeptin. The study demonstrated that the integration of physical exercise with metformin therapy resulted in favorable modulations of these biomarkers, suggesting enhanced metabolic regulation and potential benefits in obesity management. The findings support the synergistic use of pharmacological and lifestyle interventions in treating obesity.

5. Effects of Short-Term Pre-Competition Weight Loss on Certain Physiological Parameters and Strength Change in Elite Boxers
PLOS ONE, 2024
DOI: 10.1371/journal.pone.0304267
Authors: Yavuz Yasul, Faruk Akçınar, Muhammet Enes Yasul, Ahmet Kurtoğlu, Özgür Eken, Georgian Badicu, Luca Paolo Ardigò

Summary:
This study assessed the impact of rapid weight loss strategies commonly employed by elite boxers before competitions on physiological parameters and strength levels. The results indicated that short-term weight reduction led to significant decreases in strength and alterations in physiological markers, potentially compromising athletic performance. The research underscores the need for carefully managed weight loss protocols to minimize adverse effects on athletes’ health and performance.

🔚Conclusion

Yavuz Yasul’s scientific work embodies the synergy between academic excellence and applied research. By integrating his interests in exercise physiology, nutrition, and biochemistry, he contributes to a deeper understanding of health optimization and performance. His efforts continue to shape modern perspectives in sports science and health promotion.

Mr. Mohammed Abdalla | Intelligent Transportation | Best Paper Award

Published on by Research Scientist

Mr. Mohammed Abdalla | Intelligent Transportation | Best Paper Award

Mr. Mohammed Abdalla, Beni-Suef University, Egypt

Dr. Mohammed Abdalla Mahmoud Youssif 🇪🇬 is a seasoned technology leader and current Head of Development at Giza Systems 🏢. With over 15 years of experience in software development 💻, he has excelled in managing teams, leading innovative projects, and delivering smart solutions 🌐. He holds B.Sc., M.Sc., and Ph.D. degrees from Cairo University 🎓 in computer science and engineering. His expertise includes big data 📊, machine learning 🤖, and smart city applications 🏙️. Passionate about future tech, Dr. Youssif is also active in academia with 20+ research publications 📚 and an online presence via YouTube and LinkedIn 🎥💼.

Professional Profile

GOOGLE SCHOLAR

Education and Experience 

Dr. Mohammed Abdalla earned his B.Sc., M.Sc., and Ph.D. in Computer Science and Engineering from Cairo University 🎓. With more than 15 years of hands-on software development experience 💻, he has contributed to a wide variety of business projects ranging from enterprise platforms to smart city solutions 🌐. He currently leads development teams at Giza Systems 🏢, where he focuses on innovation, resource management, and technical excellence 🚀. His academic background is strongly tied to real-world applications, enabling him to bridge research and industry with a practical edge 🔗.

Professional Development 

Dr. Youssif’s career reflects consistent professional growth in both technical and leadership domains 🔧👨‍💼. Starting as a software developer 💻, he quickly climbed the ranks through a combination of innovation, problem-solving, and people management. As Development Head at Giza Systems 🏢, he now mentors engineers, allocates project resources 📅, and drives the development of cutting-edge solutions 🚀. His commitment to continuous learning and application of emerging technologies, such as big data 📊 and AI 🤖, has positioned him as a key contributor in Egypt’s digital transformation journey 🇪🇬.

Research Focus 

Dr. Mohammed Abdalla’s research is deeply rooted in cutting-edge technologies, especially big data management 📊, artificial intelligence 🤖, and machine learning algorithms 🧠. He places a particular focus on smart city applications 🌆, developing analytics tools and intelligent systems to enhance urban efficiency and sustainability 🚦🏙️. His work bridges academic research and practical implementation, ensuring innovations can be adopted in real-world scenarios. His 20+ publications 📚 reflect a commitment to solving complex societal problems through technology 💡. He aims to harness data and digital intelligence for smarter urban environments and better quality of life 🏘️.

Awards and Honors 

While Dr. Mohammed Abdalla is still building his list of formal recognitions, his contributions to smart city tech and software innovation are widely respected 🌍. As a speaker, team leader, and contributor to international journals and conferences 📘, he is regarded as a thought leader in big data and machine learning fields 🧠. His position as Development Head at Giza Systems is a testament to his technical and managerial excellence 🏢. His active online presence via YouTube and LinkedIn helps mentor younger professionals 📽️💼, adding to his community impact and informal recognition within the tech ecosystem 👏.

Publication Top Notes

1. Crisis Management Art from the Risks to the Control: A Review of Methods and Directions

📚 Authors: A.H. Mohammed Abdalla, Louai Alarabi
📘 Journal: Information (Vol. 42, 2021)
📈 Citations: 42
📄 Summary:
This review outlines the landscape of crisis management frameworks, emphasizing how organizations can transition from identifying risks to establishing control mechanisms. It evaluates methodologies for risk assessment, communication, and coordination, providing a comprehensive guide for practitioners and researchers seeking to improve resilience and decision-making in crises. The paper synthesizes real-world implementations with theoretical models to chart future research directions in crisis response systems.

2. TraceAll: A Real-Time Processing for Contact Tracing Using Indoor Trajectories

📚 Authors: Louai Alarabi, S. Basalamah, A. Hendawi, Mohammed Abdalla
📘 Journal: Information (Vol. 12, No. 5, 2021)
📈 Citations: 21
📄 Summary:
This study presents TraceAll, an innovative real-time contact tracing system that leverages indoor trajectory data to identify potential exposure events. It uses spatial indexing and real-time analytics to provide fast and scalable tracing, crucial during health crises like COVID-19. The paper discusses system architecture, algorithms, and a deployment case study, demonstrating its effectiveness in high-density areas.

3. DeepMotions: A Deep Learning System for Path Prediction Using Similar Motions

📚 Authors: Mohammed Abdalla, Abdeltawab Hendawi, Hoda M.O. Mokhtar, Neveen ElGamal
📘 Journal: IEEE Access, 2020
📈 Citations: 16
📄 Summary:
DeepMotions is a path prediction framework that applies deep learning to movement data, identifying similar motion patterns to predict future trajectories of moving objects. It integrates convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to model spatial-temporal patterns. Applications range from pedestrian prediction to intelligent transportation systems.

4. FraudMove: Fraud Drivers Discovery Using Real-Time Trajectory Outlier Detection

📚 Authors: E.O. Eldawy, A. Hendawi, Mohammed Abdalla, Hoda M.O. Mokhtar
📘 Journal: ISPRS International Journal of Geo-Information (Vol. 10, No. 11, Article 767, 2021)
📈 Citations: 13
📄 Summary:
FraudMove introduces a real-time framework for detecting fraudulent behavior based on vehicle movement anomalies. Using trajectory outlier detection, the system identifies unexpected routes or suspicious driving patterns that may indicate fraud, such as in ride-sharing or insurance claims. The framework blends spatio-temporal clustering and machine learning models for accurate fraud detection.

5. HarmonyMoves: A Unified Prediction Approach for Moving Object Future Path

📚 Authors: Mohammed Abdalla, Hoda M.O. Mokhtar
📘 Journal: International Journal of Advanced Computer Science and Applications, pp. 637–644, 2020
📈 Citations: 7
📄 Summary:
This research proposes HarmonyMoves, a hybrid model that integrates historical trajectory data with environmental context to predict the future paths of moving entities (e.g., vehicles, pedestrians). Unlike previous models that relied solely on movement data, this approach harmonizes contextual and historical data for robust, real-time trajectory prediction.

Conclusion

Dr. Mohammed Abdalla’s contributions meet and exceed the standards typically required for Best Paper Awards at prestigious conferences and journals. His research is characterized by technical innovation, interdisciplinary applications, practical impact, and high citation potential. He is especially commendable for producing systems that combine machine learning with real-world problem solving, such as contact tracing and mobility analytics.

Prof. Dr .Gianluigi Bacchetta | Botanica | Lifetime achievement Award

Published on by Research Scientist

Prof. Dr .Gianluigi Bacchetta | Botanica | Lifetime achievement Award

Director , University of Cagliari , Italy  

🌿 Professor Gianluigi Bacchetta is an internationally renowned botanist and conservation biologist 🌍. Currently a full professor at the University of Cagliari 🇮🇹, he also serves as an adjunct professor at the University of Tehran 🇮🇷. He directs the Conservation Centre of Biodiversity and the Germplasm Bank of Sardinia 🌱. With over 700 publications 📚 and global collaborations, Bacchetta has made remarkable contributions to Mediterranean biodiversity research 🌸. He is an editor, reviewer, and project leader in several international conservation initiatives 🌐, making a lasting impact on plant science and ecosystem protection 🏞️.

Professional Profile

GOOGLE SCHOLAR

SCOPUS

Education & Experience 

🎓 Gianluigi Bacchetta earned his degree in Life Sciences in 1996 🧬, followed by multiple master’s degrees in Landscape Planning (1997) 🗺️ and Vegetation Analysis (2000) 🌳. He completed his PhD in Geomorphology and Geobotany in 2000 🪨, and later achieved a European PhD in Plant Biology from the University of Valencia 🇪🇸. His academic career includes roles from Lecturer to Full Professor at the University of Cagliari 🏛️. He served as director of Hortus Botanicus Karalitanus 🌺 and now leads major biodiversity and germplasm conservation centers in Sardinia 🌾.

Professional Development 

🔬 Prof. Bacchetta has evolved through diverse academic and leadership roles in botany, ecology, and conservation 🌲. As editor of Plant Sociology and associate editor for several journals 📖, he actively shapes scientific communication 🌐. His role in doctoral education as deputy director of a PhD program 🎓, along with memberships in international scientific councils 🌍, showcases his dedication to professional excellence. He has authored 24 scientific books 📘 and mentors upcoming researchers. As president of GENMEDA and leader of multiple EU-funded projects 💡, Bacchetta exemplifies continuous professional growth and collaborative leadership 🌱.

Research Focus 

🧪 Prof. Bacchetta’s research specializes in plant diversity, conservation biology, geobotany, and Mediterranean ecosystem studies 🌿. His work encompasses phytoclimatology, phytogeography, and island plant biodiversity 🏝️. He leads germplasm conservation efforts 🌾, with a focus on endemic and endangered Mediterranean species 🏵️. His integrative studies connect vegetation science with climate, soil, and land use patterns 🌍. The outcomes support environmental planning and ecological restoration 🔄. With emphasis on genetic resource preservation and sustainable development 🌱, Bacchetta’s research bridges field biology, conservation policy, and ecosystem services 🏞️.

Awards & Honors 

🏅 Prof. Bacchetta has received national and international recognition for his work in plant biodiversity and conservation biology 🌍. He has led prestigious European projects such as LIFE+, Interreg, and Erasmus+ 🌐. As president of GENMEDA and deputy president of the CBNC scientific council 🇫🇷, his leadership is widely respected. He is regularly invited to contribute to international conservation strategies 🌿. His contributions as a reviewer, editor, and academic mentor have earned him high esteem in the global scientific community 📚. His prolific publication record and active collaboration networks are testaments to his exceptional achievements 🥇.

Publication Top Notes

1. Assessing Eco-Physiological Patterns of Ailanthus altissima (Mill.) Swingle and Differences with Native Vegetation Using Copernicus Satellite Data on a Mediterranean Island

Authors: F. Marzialetti, V. Lozano, A. Große-Stoltenberg, L. Podda, G. Brundu
Journal: Ecological Informatics, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This study uses high-resolution Copernicus satellite data to evaluate the eco-physiological behavior of the invasive tree Ailanthus altissima compared to native vegetation on a Mediterranean island. The research highlights significant differences in vegetation indices, phenological traits, and water-use patterns. The findings provide critical insight into the invasive potential of A. altissima and suggest targeted remote-sensing approaches for early detection and management in Mediterranean ecosystems.

2. Functional and Habitat Characteristics Associated with Nativeness, Rarity, and Invasiveness in the Aquatic Vascular Flora of Sardinia

Authors: M. Fois, A. Cuena-Lombraña, J.N. Boyd, L. Podda, G. Bacchetta
Journal: Global Ecology and Conservation, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This research investigates the ecological traits and habitat preferences of aquatic vascular plants in Sardinia. By analyzing traits linked with nativeness, rarity, and invasiveness, the authors aim to support conservation and management efforts. The study reveals that invasive species tend to exhibit broader ecological tolerances and reproductive strategies, posing threats to native aquatic ecosystems. This functional trait analysis offers a framework for assessing plant behavior in freshwater habitats under changing environmental pressures.

3. Tracing the Emergence of Domesticated Grapevine in Italy

Authors: M. Ucchesu, S. Ivorra, V. Bonhomme, A. Usai, L. Bouby
Journal: PLoS ONE, 2025
DOI/Link: Link not available
Citations: 0
Summary:
This archaeobotanical study employs molecular and morphometric evidence to trace the early domestication of grapevine (Vitis vinifera) in Italy. Through analysis of ancient seeds and plant remains, the authors provide evidence for independent domestication events and early viticulture practices. The interdisciplinary approach connects cultural practices with evolutionary plant biology, offering a new timeline and geographic perspective on grape domestication in the western Mediterranean.

4. The First Inventory of Sardinian Mining Vascular Flora

Authors: M.E. Boi, M. Sarigu, M. Fois, M. Casti, G. Bacchetta
Journal: Plants, 2025 (Open Access)
DOI/Link: Link not available
Citations: 0
Summary:
This paper presents the first systematic inventory of vascular plants in mining areas across Sardinia. Mining landscapes are often biodiversity hotspots due to their unique soil chemistry and disturbance regimes. The study identifies species adapted to metal-rich and degraded soils, including several endemic and threatened taxa. This inventory contributes to ecological restoration planning and highlights the conservation value of post-industrial habitats.

Conclusion

Prof. Gianluigi Bacchetta embodies the values of scientific excellence, global collaboration, and lifelong commitment to biodiversity conservation. His exceptional academic record, mentorship legacy, and leadership in both national and international conservation efforts make him a prime candidate for a Lifetime Achievement Award.

 

 

Prof. Dr Mokhtar Hjiri | Metal oxide gas sensors | Best Researcher Award

Published on by Research Scientist

Prof. Dr . Mokhtar Hjiri | Metal Oxide Gas Sensors | Best Researcher Award

Associate Professor ,  Imam Mohammad Ibn Saud Islamic University , best researcher award

Mokhtar Hjiri is an associate professor at Imam Mohammed Ibn Saud Islamic University, Riyadh, specializing in nanomaterials synthesis for gas sensors and wastewater treatment. 🎓 He earned his PhD in 2016 from the University of Monastir in collaboration with the University of Messina. 🇹🇳🇮🇹 With teaching and research experience in Tunisia, Saudi Arabia, and Italy, he is skilled in spin coating, hydrothermal synthesis, and gas sensing techniques. 🔬 His work advances environmental safety and sensor technology. 🌿⚙️ He speaks Arabic, English, French, and Italian, bridging international research communities. 🌍

Professional Profile

GOOGLE SCHOLAR

Education and Experience

Mokhtar Hjiri completed his Master’s degree in Materials and Nanomaterials at University of Monastir in 2010 🎓 and earned his PhD in 2016 jointly with University of Monastir and University of Messina. 🇹🇳🇮🇹 He worked as assistant professor at King Abdulaziz University (2016-2020) and advanced to associate professor there until 2022. Currently, he holds an associate professor role at Imam Mohammed Ibn Saud Islamic University. 🏫 His expertise spans from lecturing physics to supervising nanomaterial synthesis projects, contributing to international research collaborations. 🌐

Professional Development

Mokhtar continuously develops expertise in nanomaterials and gas sensor technologies. 🔬 He has trained extensively in Italy, learning advanced hydrothermal and green chemistry methods. 🇮🇹 His research proficiency includes spin coating, X-ray diffraction, and gas sensing systems. 🧪 He mentors Master’s students in innovative projects on spinel ferrite and doped ZnO nanoparticles. 🎓 Proficient in Matlab, LaTeX, and Microsoft Office, he balances research with teaching general physics and semiconductors. 💻 Multilingual skills (Arabic, English, French, Italian) enable global collaboration. 🌍

Research Focus

Mokhtar’s research centers on the synthesis of metal oxide nanomaterials for gas sensor applications and wastewater treatment. 🧫 He specializes in hydrothermal synthesis, green chemistry, and spin coating techniques to create functional thin films and nanopowders. 🌱 His work targets environmental monitoring and pollution control via advanced chemoresistive sensors and heavy metal adsorption. ⚗️ Combining materials science with applied physics, his research contributes to safer industrial processes and sustainable technologies. 🌿🔧

Awards and Honors

Mokhtar Hjiri has earned recognition for his pioneering research in nanomaterials and sensor technology. 🏅 His papers published in top journals and presentations at IEEE workshops highlight his contributions. 📚 His commitment to innovative methods for environmental safety has gained academic respect and collaborative opportunities. 🌐 He is known for successfully supervising graduate theses and promoting cross-disciplinary knowledge exchange. 🎓 His growing impact in materials science and engineering reflects his leadership and dedication to advancing nanotechnology applications. 🔝✨

Publication Top Notes

1. Al-doped ZnO for highly sensitive CO gas sensors

Authors: M. Hjiri, L. El Mir, S.G. Leonardi, A. Pistone, L. Mavilia, G. Neri
Journal: Sensors and Actuators B: Chemical, Volume 196, Pages 413-420, 2014
Citations: 441
Summary:
This study reports on the development of aluminum-doped zinc oxide (Al-ZnO) nanomaterials tailored for detecting carbon monoxide (CO) gas with high sensitivity. Using advanced synthesis methods, the authors optimized the doping concentration to enhance sensor performance, improving response time and selectivity. The Al doping effectively modulates the electrical properties of ZnO, leading to superior detection capabilities suitable for environmental monitoring and industrial safety applications.

2. Harnessing bacterial endophytes for promotion of plant growth and biotechnological applications: an overview

Authors: A.M. Eid, A. Fouda, M.A. Abdel-Rahman, S.S. Salem, A. Elsaied, R. Oelmüller, et al.
Journal: Plants, Volume 10, Issue 5, Article 935, 2021
Citations: 198
Summary:
This comprehensive review highlights the role of bacterial endophytes—microorganisms living within plants—in enhancing plant growth and their diverse biotechnological applications. While not authored solely by Hjiri, this work involves him as a co-author contributing expertise on the microbial interactions and applications in agriculture and environmental science. The article emphasizes sustainable agricultural practices and future potential for biofertilizers and biocontrol agents.

3. Enhanced performance of novel calcium/aluminum co-doped zinc oxide for CO2 sensors

Authors: R. Dhahri, S.G. Leonardi, M. Hjiri, L. El Mir, A. Bonavita, N. Donato, et al.
Journal: Sensors and Actuators B: Chemical, Volume 239, Pages 36-44, 2017
Citations: 120
Summary:
This research presents the synthesis and testing of zinc oxide sensors co-doped with calcium and aluminum for improved detection of carbon dioxide (CO2). The co-doping strategy enhances sensitivity and selectivity by modifying the surface properties and electrical conductivity of ZnO nanostructures. The sensors demonstrate fast response and recovery times, making them promising for environmental monitoring and industrial gas detection systems.

4. CO and NO2 Selective Monitoring by ZnO-Based Sensors

Authors: M. Hjiri, L. El Mir, S.G. Leonardi, N. Donato, G. Neri
Journal: Nanomaterials, Volume 3, Issue 3, Pages 357-369, 2013
Citations: 116
Summary:
This paper investigates zinc oxide-based sensors engineered for selective detection of carbon monoxide (CO) and nitrogen dioxide (NO2). By tailoring the material properties and sensor architecture, the authors achieve selective sensing capabilities critical for air quality control. The study also examines sensor response under varying environmental conditions, confirming the robustness and potential of ZnO nanomaterials for real-world applications.

5. Effect of indium doping on ZnO based-gas sensor for CO

Authors: M. Hjiri, R. Dhahri, K. Omri, L. El Mir, S.G. Leonardi, N. Donato, G. Neri
Journal: Materials Science in Semiconductor Processing, Volume 27, Pages 319-325, 2014
Citations: 110
Summary:
This article explores how indium doping influences the gas sensing performance of zinc oxide sensors targeting carbon monoxide. Indium incorporation enhances ZnO’s electrical conductivity and surface reactivity, leading to improved sensor sensitivity and selectivity. The research includes detailed characterization of material morphology and electronic properties, contributing to optimized gas sensor design.

Conclusion

Mokhtar Hjiri’s focused contributions on enhancing gas sensor technology using innovative nanomaterials and doping methods position him as a leading researcher in the field of materials science and sensor engineering. His impactful research directly supports environmental safety and sustainability, key priorities in modern science and technology. Given his high citation record, continuous scientific output, and mentorship roles, he is an excellent candidate for a Best Researcher Award, recognizing both his scientific excellence and societal relevance.

Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

Published on by Research Scientist

Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

Author , Ferdowsi university of Mashhad , Iran

Vahideh Bafandegan Emroozi is a passionate Iranian researcher specializing in industrial management and optimization. 🎓 With a Ph.D. from Ferdowsi University of Mashhad, her work bridges technology and human-centric approaches. 📊 Her research spans supply chain innovation, IoT applications, and human error analysis. 🤖🧠 She has published in esteemed journals and held research fellowships at Ferdowsi and Sanabad Universities. 📚✍️ Known for her analytical skills and academic dedication, Vahideh continues to contribute significantly to industrial systems and decision sciences. 🔍📈 Her collaborative spirit and teaching experience further highlight her dynamic role in academia. 👩‍🏫🌐

Professional Profile:

SCOPUS

Education & Experience:

Vahideh earned her Ph.D. in Industrial Management (2019–2024) 🎓 from Ferdowsi University, where her thesis focused on IoT-based maintenance and human error modeling. 📡🛠️ She also completed an M.Sc. in Industrial Management (2014–2017) with a high GPA of 18.96/20 📚 and a B.Sc. in Industrial Engineering (2008–2012). 🏗️ Her academic journey led to research fellow roles at Ferdowsi University (2021–2023) and Sanabad University (2023–2024). 🔬🏛️ In addition to research, she has taught Operations Research, Strategic Management, and Multi-Criteria Decision Making. 👩‍🏫 Her experience reflects a strong foundation in both theory and application. 💼🧮

Professional Development:

Vahideh continually builds her academic and technical skills through professional development. 📈💡 She has mastered analytical and modeling tools such as Python, MATLAB, GAMS, LINGO, LaTeX, and Vensim. 💻📐 Her commitment to research excellence is evident in her publications in Scopus-indexed journals 📄🔍 and her work on complex topics like green supply chain management and pandemic response strategies. 🌍📦 She actively contributes to knowledge dissemination through teaching, collaborative research, and methodological innovation. 📊🧠 Her engagement with multidisciplinary topics ensures she remains at the forefront of industrial and systems engineering. 🚀📘

Research Focus:

Vahideh’s research spans across multiple domains in industrial management. 🏭🔍 Her core interests include supply chain management, optimization, and maintenance planning. 🧾🛠️ She also explores the effects of human error, reliability analysis, and inventory control systems. ⚙️🧠📦 A significant part of her work integrates the Internet of Things (IoT) 🌐 with system dynamics and mathematical modeling 📊📉 to improve industrial decision-making. Her goal is to create smarter, more resilient, and sustainable industrial systems. 🌱💡 Her innovative contributions are driving progress in operational efficiency and risk reduction. 🚚📈

Awards & Honors:

While specific awards were not listed, Vahideh’s academic record speaks to her excellence. 🌟 She achieved outstanding GPAs in both her Ph.D. (19.49/20) and M.Sc. (18.96/20) programs. 🥇📘 Her research has been recognized with publications in high-impact international journals like Process Integration and Optimization for Sustainability and Journal of Industrial and Management Optimization. 📚✨ She has contributed novel methodologies in green supplier selection, VIKOR optimization, and system dynamics during COVID-19. 🧪🌐 Her roles as research fellow at top Iranian universities also reflect her academic merit and potential. 🏛️🔬

Publication Top Notes

1. Markov Chain-Based Model for IoT-Driven Maintenance Planning with Human Error and Spare Part Considerations

Authors: Bafandegan Emroozi, Vahideh; Doostparast, Mahdi
Journal: Reliability Engineering and System Safety
Year: 2025
Access: Open Access
Citations: 0 (as of now)

🔍 Summary:
This article introduces a novel Markov chain-based framework that integrates the Internet of Things (IoT) into industrial maintenance planning. The model accounts for human error probabilities and spare part availability, creating a dynamic and realistic approach to predictive maintenance. 📈 The use of Markov chains enables the system to model stochastic transitions between equipment states, improving decision-making accuracy. 🤖📦 The study enhances reliability and safety in industrial systems by aligning IoT data with probabilistic risk and resource planning, offering a scalable tool for real-time maintenance strategy optimization. 🛠️📊

2. Enhancing Industrial Maintenance Planning: Optimization of Human Error Reduction and Spare Parts Management

Authors: Bafandegan Emroozi, Vahideh; Kazemi, Mostafa; Doostparast, Mahdi
Journal: Operations Research Perspectives
Year: 2025
Access: Open Access
Citations: 0 (as of now)

🔍 Summary:
This paper proposes an optimization model aimed at improving maintenance planning by focusing on human error mitigation and efficient spare parts management. 👷⚙️ It applies advanced operations research techniques to identify cost-effective strategies for minimizing failures and delays due to incorrect human actions or resource shortages. The model bridges the gap between human factors engineering and logistical planning, integrating real-time data and decision analysis. 🧠📦 It offers a comprehensive framework suitable for modern industries aiming to balance cost, reliability, and safety. 🧾📉

Conclusion

Vahideh Bafandegan Emroozi exemplifies the qualities celebrated by Women in Research Awards: innovation, impact, leadership, and academic excellence. 🌟 Her work addresses critical industrial challenges through smart technologies and rigorous modeling, while her dedication to teaching and mentoring amplifies her influence. As a pioneering female researcher in a highly technical and traditionally male-dominated field, she is not only technically accomplished but also a role model for aspiring women in STEM. 🧠🔬👩‍🏫 She is highly deserving of recognition through a Women Researcher Award.

 

Dr. Fei Huang | electronic textiles | Best Researcher Award

Published on by Research Scientist

Dr. Fei Huang | electronic textiles | Best Researcher Award

lecturer at Jiangsu College of Engineering and Technology , China

Fei Huang 👩‍🔬 is a dynamic researcher and lecturer in textile engineering, specializing in flexible and stretchable strain sensors 🧵🔋. She earned her PhD from Donghua University under the guidance of Prof. Jiyong Hu and Xiong Yan 🎓. Her cutting-edge work on wearable sensor technologies has led to several high-impact journal publications and innovative patents 📄💡. Currently teaching at Jiangsu College of Engineering and Technology 👩‍🏫, she blends scientific rigor with practical application. Fei is passionate about smart textiles, precision agriculture 🌿, and human-motion tracking 👟. Her skills in research, technology, and collaboration make her a rising star 🌟 in smart material science.

Professional Profile

SCOPUS

ORCID

Education & Experience 

Fei Huang began her academic career at Jiangnan University 🏫, where she earned a B.S. in Textile Science and Engineering 🎓 (2015–2019). She pursued a PhD at Donghua University in Shanghai 🧪, researching flexible and stretchable strain sensors under Professors Jiyong Hu and Xiong Yan (2019–2025) 📘. Following her doctorate, she joined Jiangsu College of Engineering and Technology in Nantong as a lecturer 👩‍🏫 in March 2025. Her academic journey reflects a strong foundation in textile science 🧵 and a commitment to advancing wearable sensor technology 🤖. Fei has evolved into an experienced researcher and educator in smart materials.

Professional Development 

Fei Huang has developed a diverse skill set combining textile engineering 🧵, materials science 🧬, and sensor technology 📊. She is proficient in software like MATLAB, SPSS, ABAQUS, CAD, and Photoshop 💻, supporting her deep technical analysis and design capabilities. Fluent in both Mandarin and English 🌐, she collaborates effectively on global research projects. She demonstrates strength in laboratory techniques, literature review, and data interpretation 🔍. With hobbies including running, hiking, and reading 🏃‍♀️📚, Fei maintains balance in her academic life. Her commitment to continuous learning and innovation 🔄 positions her as a forward-thinking researcher in wearable technology.

Research Focus 

Fei Huang’s research focuses on flexible, stretchable, and wearable strain sensors 🧵🔋. Her innovations target real-time motion monitoring 🦵, gait analysis 🚶‍♀️, and precision agriculture 🌾 through sensor integration into textiles. She designs yarn-based capacitive and resistive sensors with ultra-low detection limits and high responsiveness ⚙️. Her work explores encapsulation, structural design, and braiding technologies to improve sensor performance and durability 🔄. Fei also investigates graphene-based devices for environmental sensing 🌿. Her contributions lie at the intersection of smart textiles, wearable electronics, and functional materials, aiming to make textile-integrated electronics practical for health, sports, and agricultural use 🤖🌍.

Awards & Honors

Fei Huang has received notable awards for her academic and research achievements 🏆. She earned the National Scholarship (2017–2018) for outstanding performance 🌟 and was honored with First-Class (2015–2016) and Third-Class (2016–2017) Academic Scholarships 📘. In 2022, she received the Graduate Student Innovation Fund and Fundamental Research Funds for the Central Universities at Donghua University 💡—a testament to her innovative sensor work. These honors reflect her dedication to academic excellence and research impact 📖. With her track record of recognition and productivity, Fei stands out as a promising contributor to the future of smart material technologies 🧪.

Publication Top Notes

1. A Wide-linear-range and Low-hysteresis Resistive Strain Sensor Made of Double-threaded Conductive Yarn for Human Movement Detection

Journal: Journal of Materials Science & Technology
Publication Date: February 2024
DOI: 10.1016/j.jmst.2023.06.047
Authors: Fei Huang, Jiyong Hu, Xiong Yan

🔍 Summary:
This study introduces a novel resistive strain sensor composed of double-threaded conductive yarn engineered for wide linear range and minimal hysteresis. The sensor demonstrates high sensitivity and durability, making it ideal for human movement detection applications such as wearable health monitors and motion tracking suits. The work emphasizes material optimization and structural innovation to enhance repeatability and responsiveness, paving the way for smart textile integration in biomechanical systems.

2. High-linearity, Ultralow-detection-limit, and Rapid-response Strain Sensing Yarn for Data Gloves

Journal: Journal of Industrial Textiles
Publication Date: June 2022
DOI: 10.1177/15280837221084369
Authors: Fei Huang, Jiyong Hu, Xiong Yan, Fenye Meng

🔍 Summary:
This paper presents a strain sensing yarn with exceptional linearity, low detection threshold, and fast response time. Designed specifically for data gloves, this sensor enables accurate hand gesture recognition and real-time motion monitoring. The research blends material engineering and textile design to create a sensor with strong durability, making it suitable for immersive human–machine interface technologies, virtual reality, and robotic control applications.

3. Review of Fiber- or Yarn-Based Wearable Resistive Strain Sensors: Structural Design, Fabrication Technologies and Applications

Journal: Textiles
Publication Date: February 2022
DOI: 10.3390/textiles2010005
Authors: Fei Huang, Jiyong Hu, Xiong Yan

🔍 Summary:
This comprehensive review covers recent advancements in fiber- and yarn-based resistive strain sensors for wearable electronics. The authors analyze structural designs, material compositions, and fabrication techniques, along with their applications in health monitoring, sports, and robotics. The review serves as a valuable guide for researchers and engineers developing next-generation smart textiles, offering insight into performance optimization and integration strategies for flexible electronics.

Conclusion

Fei Huang’s originality, impact, and interdisciplinary contributions make her an ideal recipient for awards such as:
Best Researcher Award, AI and Smart Technology Innovation Awards, or Young Scientist Award.
Her commitment to creating intelligent wearable systems that address real-world needs places her at the forefront of next-generation sensor research.

 

 

 

Prof . Len Gelman | Artificial Intelligence | Best Researcher Award

Published on by Research Scientist

Prof . Len Gelman | Artificial Intelligence | Best Researcher Award

Prof. Len Gelman , University of Huddersfield , United Kingdom

Professor Len Gelman 🇬🇧 is a globally recognized expert in signal processing and condition monitoring 🔍. He currently serves as Chair Professor and Director at the University of Huddersfield 🏫. With over two decades of academic leadership, he has significantly contributed to vibro-acoustics and non-destructive testing 🔧. A Fellow of multiple prestigious organizations 🌐, Prof. Gelman’s international collaborations span across Europe, Asia, and the USA 🌏. His innovations have advanced aerospace and medical diagnostics ✈️🧬. He continues to lead global initiatives and research committees, shaping the future of engineering diagnostics and reliability technologies 🔬🛠️.

Professional Profile

SCOPUS

Education and Experience 

Prof. Len Gelman holds a PhD and Doctor of Science (Habilitation) 🎓, with BSc (Hons) and MSc (Hons) degrees in engineering 📘. He is a British citizen 🇬🇧. Since 2017, he has been a Professor and Chair at the University of Huddersfield 🏛️. Prior to that, he served at Cranfield University (2002–2017) as Chair in Vibro-Acoustical Monitoring 🔊. His distinguished academic journey includes visiting professorships in China 🇨🇳, Denmark 🇩🇰, Poland 🇵🇱, Spain 🇪🇸, Italy 🇮🇹, and the USA 🇺🇸. Prof. Gelman combines deep technical expertise with global educational outreach 🌍👨‍🏫.

Professional Development 

Prof. Gelman has held key international leadership roles including Chair of the International Scientific Committee of the Condition Monitoring Society 🌐. He is a Fellow of BINDT, IAENG, IDE, and HEA 🎖️, and an Academician of the Academy of Sciences of Applied Radio Electronics 🧠. He chairs award and honors committees for top acoustics and vibration institutions 🏅. As Visiting Professor at Tsinghua, Jiao Tong, and Aalborg Universities, among others 🎓, he mentors emerging researchers globally 🌎. Prof. Gelman’s commitment to professional excellence shapes the advancement of diagnostic technologies and engineering education 📈🔧.

Research Focus 

Prof. Gelman’s research focuses on signal processing, vibro-acoustics, and condition monitoring of engineering systems 🔍🔊. His work spans non-destructive testing (NDT), fault diagnostics, and performance optimization in sectors such as aerospace, healthcare, and manufacturing ✈️🏥🏭. He develops advanced algorithms for fault detection and predictive maintenance using machine learning and big data 🧠📊. His interdisciplinary approach benefits both industry and academia 🌐🔬. Prof. Gelman also pioneers applications in medical diagnostics and intelligent systems for real-time monitoring 🧬⚙️. His innovations contribute to safer, more efficient engineering systems across global platforms 🌍🚀.

Awards and Honors 

Prof. Gelman has received numerous prestigious awards for innovation and research excellence 🏅. These include the Rolls-Royce Innovation Award (2012, 2019) ✈️, William Sweet Smith Prize by IMechE 🛠️, and COMADIT Prize by BINDT for impactful contributions to condition monitoring 🧲. He also received Best Paper Awards at CM/MFPT conferences 📄 and recognition from the USA Navy and Acoustical Society of America 🇺🇸🔊. His European and UK fellowships support cutting-edge human capital projects 🧠🇪🇺. He has chaired international committees in NDT and acoustics, continuing to shape future technologies through global leadership and innovation 🌐👨‍🔬.

Publication Top Notes

1. Vibration Analysis of Rotating Porous Functionally Graded Material Beams Using Exact Formulation

  • Citation: Amoozgar, M.R., & Gelman, L.M. (2022). Vibration analysis of rotating porous functionally graded material beams using exact formulation. Journal of Vibration and Control, 28(21–22), 3195–3206. https://doi.org/10.1177/10775463211027883Nottingham Repository+1SAGE Journals+1

  • Summary: This study investigates the free vibration behavior of rotating functionally graded material (FGM) beams with porosity, employing geometrically exact fully intrinsic beam equations. The research considers both even and uneven porosity distributions to simulate manufacturing imperfections. Findings reveal that material gradation and porosity significantly influence natural frequencies and mode shapes, emphasizing the necessity of accounting for these factors in the design and analysis of rotating FGM structures. Huddersfield Research Portal+2SAGE Journals+2Nottingham Repository+2

2. Vibration Health Monitoring of Rolling Bearings Under Variable Speed Conditions by Novel Demodulation Technique

  • Citation: Zhao, D., Gelman, L.M., Chu, F., & Ball, A.D. (2021). Vibration health monitoring of rolling bearings under variable speed conditions by novel demodulation technique. Structural Control and Health Monitoring, 28(2), e2672. https://doi.org/10.1002/stc.2672Wiley Online Library

  • Summary: Addressing the challenges of diagnosing rolling bearing faults under variable speed conditions, this paper introduces an optimization-based demodulation transform method. The technique effectively estimates fault characteristic frequencies with weak amplitudes and adapts to time-varying rotational speeds. Validation through simulations and experimental data demonstrates the method’s superior diagnostic capabilities compared to existing approaches. Huddersfield Research Portal+1Wiley Online Library+1

3. Novel Method for Vibration Sensor-Based Instantaneous Defect Frequency Estimation for Rolling Bearings Under Non-Stationary Conditions

  • Citation: Zhao, D., Gelman, L.M., Chu, F., & Ball, A.D. (2020). Novel method for vibration sensor-based instantaneous defect frequency estimation for rolling bearings under non-stationary conditions. Sensors, 20(18), 5201. https://doi.org/10.3390/s20185201MDPI

  • Summary: This research presents a novel approach for estimating instantaneous defect frequencies in rolling bearings operating under non-stationary conditions. Utilizing vibration sensor data, the method enhances the accuracy of defect frequency estimation, facilitating improved fault diagnosis in dynamic operational environments. MDPI

4. Novel Fault Identification for Electromechanical Systems via Spectral Technique and Electrical Data Processing

  • Citation: Ciszewski, T., Gelman, L.M., & Ball, A.D. (2020). Novel fault identification for electromechanical systems via spectral technique and electrical data processing. Electronics, 9(10), 1560. https://doi.org/10.3390/electronics9101560MDPI

  • Summary: This paper introduces an innovative method for fault identification in electromechanical systems by integrating spectral analysis with electrical data processing. The approach enhances the detection and diagnosis of faults, contributing to the reliability and efficiency of electromechanical system operations. MDPI

5. Novel Prediction of Diagnosis Effectiveness for Adaptation of the Spectral Kurtosis Technology to Varying Operating Conditions

  • Citation: Kolbe, S., Gelman, L.M., & Ball, A.D. (2021). Novel prediction of diagnosis effectiveness for adaptation of the spectral kurtosis technology to varying operating conditions. Sensors, 21(20), 6913. https://doi.org/10.3390/s21206913PMC

  • Summary: This study proposes two novel consistency vectors combined with machine learning algorithms to adapt spectral kurtosis technology for optimal gearbox damage diagnosis under varying operating conditions. The approach enables computationally efficient online condition monitoring by predicting diagnosis effectiveness, thereby improving maintenance strategies.

Conclusion

Professor Len Gelman exemplifies the ideal candidate for the Best Researcher Award due to his groundbreaking contributions to condition monitoring, signal processing, and diagnostic technologies. His work not only advances academic knowledge but also addresses critical industry challenges in aerospace, healthcare, and manufacturing. With a sustained record of high-impact research, international leadership, and technological innovation, he stands out as a world-class researcher whose work continues to benefit both academia and society.

 

Dr. MD Shahjalal | cancer epidemiology | Young Researcher Award

Published on by Research Scientist

Dr. MD. Shahjalal | cancer epidemiology |Young Researcher Award

Dr. MD Shahjalal, North South University , Bangladesh

Md. Shahjalal is an accomplished public health researcher from Bangladesh 🇧🇩 with a strong academic and research background in cancer epidemiology 🎗️ and global health 🌍. He holds an MPH in Epidemiology from North South University 🎓 and a BUMS from the University of Dhaka 🏥. Currently serving as Research Coordinator at Research Rats, he has contributed to numerous international publications 📚, focusing on healthcare economics and cancer care. He is also an academic editor for PLoS ONE 🖋️ and recipient of national health research grants 🏅. His work aims to reduce disparities in cancer outcomes and improve population health 💡.

Professional Profile

ORCID

Education & Experience 

Md. Shahjalal earned his Master of Public Health (MPH) in Epidemiology 🧠 from North South University (2018–2019) and Bachelor of Unani Medicine & Surgery (BUMS) 🩺 from the University of Dhaka (2012–2017). His research journey includes roles as Research Assistant (2019–2020), Research Associate (2021–2022), and currently as Research Coordinator at Research Rats Bangladesh (2023–Present) 🔬. He also worked as a Teaching Assistant in Biostatistics at NSU 📊. Through these roles, he has developed expertise in grant writing, data analysis, and multi-disciplinary research coordination 🤝, contributing to impactful studies in cancer and public health.

Professional Development 

Shahjalal’s professional growth is rooted in continuous learning and hands-on research 📈. From coordinating multi-site cancer studies to assisting in international grant applications 💼, he has gained advanced skills in public health research, data modeling, and scientific writing 📄. His expertise spans SPSS, STATA, and EXCEL for complex analyses 📊. As an academic editor for PLoS ONE 🧑‍⚖️, he stays engaged with global research trends. His participation in peer-reviewed publications and collaborative projects reflects his commitment to evidence-based solutions in healthcare. With strong communication and leadership skills 💬, he thrives in multidisciplinary teams and policy-relevant research environments 🌐.

Research Focus 

Md. Shahjalal’s research primarily targets cancer epidemiology 🎗️, health-related quality of life, and health economics 💰. His work evaluates systemic and radiation therapy outcomes, mental health disparities 🧠, and economic burdens faced by cancer survivors in Bangladesh. He also explores nutritional issues among vulnerable populations 🥣 and investigates access disparities in cardio-oncology care ❤️. Utilizing statistical modeling and health metrics like EQ-5D-5L, he aims to inform policies for equitable healthcare access 🏥. His contributions support both national and international cancer care reforms 🌍, ensuring that scientific insights lead to real-world impact for underserved communities 📢.

Awards & Honors 

Md. Shahjalal has been recognized for his impactful research through competitive grants and editorial roles 🏆. He received the Bangladesh Health Research Grant (2024) as Principal Investigator for a TB-related nutrition project 🧪 and the General Pharmaceutical Health Research Grant (2023) as Co-Investigator on cardio-oncology care disparities ❤️. With an H-index of 8 on Scopus 📈, his scholarly influence is growing steadily. He serves as an Academic Editor for PLoS ONE 🖋️, a Scopus Q1 journal, reflecting peer recognition of his academic contributions. These honors mark him as a rising leader in public health and medical research 🌟.

Publication Top Notes

1.🎯 Radioimmunotherapy in Cancer Treatment

Title: Assessing the Clinical Effectiveness of Radioimmunotherapy with Combined Radionuclide/Monoclonal Antibody Conjugates in Cancer Treatment: Insights from Randomised Clinical Trials
Journal: Cancers (2025-04-23)
DOI: 10.3390/cancers17091413
➤ Examines advanced radioimmunotherapy effectiveness using combined agents in cancer trials.

2.💰 Cancer Treatment Costs in Bangladesh

Title: Cancer Driven Direct Medical Costs in Bangladesh: Evidence from Patient Perspective
Journal: Journal of Cancer Policy (2025-03)
DOI: 10.1016/j.jcpo.2025.100565
➤ Highlights patient-incurred medical costs and economic stress related to cancer care.

3.🏥 Unplanned Hospitalisation After Cancer Therapy

Title: Emerging Burden of Post-Cancer Therapy Complications on Unplanned Hospitalisation and Costs Among Australian Cancer Patients: A Retrospective Cohort Study Over 14 Years
Journal: Scientific Reports (2025-02-08)
DOI: 10.1038/s41598-025-89247-y
➤ Evaluates long-term health complications and hospital costs post cancer therapy in Australia.

4.🥗 Diet and Dyslipidemia in Type 2 Diabetes

Title: Association between Mediterranean Diet Adherence and Dyslipidemia Among Type-2 Diabetes Mellitus Patients in Dhaka, Bangladesh
Journal: Discover Public Health (2024-10-22)
DOI: 10.1186/s12982-024-00267-x
➤ Investigates the dietary impact on lipid profiles in diabetic patients.5.

5.💸 Economic Burden on Cancer Survivors

Title: Economic Burden of Healthcare Services on Cancer Survivors in Bangladesh
Journal: Cancer Reports (2024-08)
DOI: 10.1002/cnr2.2144
➤ Quantifies healthcare costs and financial strain on cancer survivors.

Conclusion

Md. Shahjalal demonstrates exceptional research potential and output in the interdisciplinary field of cancer epidemiology, public health, and health economics. His impactful publications, leadership in funded research, and commitment to health equity mark him as a leading candidate for the Best Researcher Award. His work not only contributes academically but also has tangible implications for national and global health policy.

 

 

 

 

Ms. Somaye Mohammadi | Vibration Analysis | Best Researcher Award

Published on by Research Scientist

Ms. Somaye Mohammadi | Vibration Analysis | Best Researcher Award

Assistant Professor , Sharif University of Technology, Best Researcher Award

Dr. S. Mohammadi is an accomplished mechanical engineer with a strong focus on vibration analysis, acoustics, and machine condition monitoring 🛠️🔍. He earned his Ph.D. from Amirkabir University of Technology, where he specialized in tire/road noise prediction and reduction 🔊🛣️. His research spans intelligent fault diagnosis, dynamic balancing, and advanced signal processing 📊🤖. With a deep commitment to industrial problem-solving and academic excellence, Dr. Mohammadi has published extensively in top-tier journals and conferences 🧠📚. His collaborative work with leading automotive and petrochemical industries demonstrates his practical impact in engineering innovation 🚗🏭.

Professional Profile

ORCID

Education and Experience

Dr. Mohammadi holds a Ph.D. (2016–2021), M.Sc. (2014–2016), and B.Sc. (2010–2014) in Mechanical Engineering from Amirkabir University of Technology 🎓🇮🇷. His doctoral research focused on modeling and predicting tire/road noise using semi-analytical and statistical methods 🔊📈. He has extensive experience in academia and industry, collaborating with IPCO and other companies on dynamic balancing, machine reliability, and condition monitoring ⚙️🏗️. He has published over 25 journal and conference papers and actively participates in technical events and applied engineering research, bridging theory and practice effectively 📚🛠️.

Professional Development

Dr. Mohammadi has significantly contributed to professional development in mechanical engineering through active involvement in research, publications, and conferences 🎤📄. He has attended numerous national and international events such as CMFD, ISAV, and IRNDT, presenting cutting-edge research on condition monitoring, acoustic diagnostics, and vibration analysis 🔍🧠. He continuously updates his skills in AI, machine learning, and signal processing for predictive maintenance and fault detection 🤖📊. His multidisciplinary approach enables practical solutions for complex industrial problems, making him a valuable contributor to academic and engineering communities 🌐🔧.

Research Focus

Dr. Mohammadi’s  research centers on mechanical vibrations, acoustics, and intelligent fault detection using AI and signal processing 🧠🔊. His work addresses real-world engineering challenges like tire noise reduction, gearbox diagnostics, and turbine reliability ⚙️🏭. He combines statistical methods with machine learning to predict failures and optimize performance in rotating machinery, engines, and industrial systems 🤖🔧. His interdisciplinary expertise bridges mechanical design, acoustics, and data analytics to improve machinery health monitoring and performance efficiency 📉📈. His research supports sustainable and cost-effective engineering operations 🔄💡.

Awards and Honors

Dr. Mohammadi has received multiple recognitions for his research excellence and technical contributions 🎖️📚. He has been invited to present at prestigious conferences like CMFD, ISAV, and IRNDT and collaborated with top engineers and institutions on vibration and fault diagnosis projects 🤝🔍. His publications in high-impact journals such as Applied Acoustics, Journal of Vibration and Control, and Machines have earned critical acclaim from the academic community 🌟📰. He was also involved in award-supported industrial collaborations, including projects with IPCO and petrochemical companies, showcasing practical impact and innovation 🏭🏅.

Publication Top Notes

1.🔍 Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning
📅 Published: April 2025 – Machines

📌 DOI: 10.3390/machines13050351

👥 Co-authors: Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Len Gelman

🧠 Key Contribution: Developed an innovative technique combining advanced signal processing (enhanced envelope detection) with transfer learning, significantly improving fault diagnosis accuracy across variable operating conditions in rolling bearings. This paper bridges AI and mechanical reliability – a cutting-edge intersection in engineering diagnostics.

2.📊 A Comprehensive Study on Statistical Prediction and Reduction of Tire/Road Noise
📅 Published: October 2022 – Journal of Vibration and Control

📌 DOI: 10.1177/10775463211013184

👥 Co-authors: Abdolreza Ohadi, Mostafa Irannejad-Parizi

🧠 Key Contribution: Offers a data-driven, statistical framework for predicting and mitigating tire/road interaction noise, addressing environmental and comfort challenges in vehicle design. The study integrates modeling, statistical methods, and experimental validation, making it valuable for the automotive industry.

3.🔉 Effect of Modeling Sidewalls on Tire Vibration and Noise

📅 Published: September 2022 – Journal of Automobile Engineering (IMechE Part D)

📌 DOI: 10.1177/09544070211052368

👥 Co-author: Abdolreza Ohad

🧠 Key Contribution: Investigated how sidewall modeling precision influences vibrational behavior and noise in tires. The research advanced numerical tire modeling techniques, which are essential for designing quieter, more stable vehicles.

Conclusion

Dr. Mohammadi’s blend of deep theoretical knowledge, strong publication output, practical industrial applications, and multidisciplinary research makes him a standout researcher. His work addresses real-world engineering challenges with smart solutions, reinforcing his eligibility for the Best Researcher Award. He not only contributes to advancing scientific understanding but also to improving industrial reliability and performance — hallmarks of a truly impactful researcher 🏅🚀.

Assoc. Prof. Dr .VietTran | Emergency Medicine | Excellence in Research

Published on by Research Scientist

Assoc. Prof. Dr. VietTran | Emergency Medicine | Excellence in Research

Director, Tasmanian Emergency Medicine Research Institute ,Tasmanian Emergency Medicine Research Institute , Australia


A/Prof Viet Tran 🇦🇺 is a distinguished Emergency Physician and academic leader based in Tasmania. As Associate Professor at the University of Tasmania and Deputy Director at Royal Hobart Hospital’s Emergency Department, he blends clinical excellence with impactful research. Founder of TASER and DoctorsWriting.com, he champions innovation in emergency care 🏥, knowledge translation 📚, and medical education 👩‍⚕️. With board roles and leadership across research and health governance, he shapes the future of emergency medicine both nationally and globally 🌏. His commitment to clinical advancement, policy influence, and teaching has earned him widespread respect and recognition 🏅.

Professional Profile:

ORCID

Education & Experience:

Dr. Viet Tran holds a Bachelor of Medical Science, Bachelor of Medicine & Surgery 🎓 from the University of Tasmania, and is a Fellow of the Australasian College for Emergency Medicine (FACEM) 🩺. With over a decade in emergency care, he currently serves as Deputy Director at Royal Hobart Hospital and Associate Professor at UTAS. His expertise spans clinical research, trauma care, and medical education 💉📘. He also leads state-level initiatives such as the Tasmanian Emergency Departments Network and the Health Senate, reflecting his deep commitment to system-wide healthcare improvement in Australia 🇦🇺.

Professional Development

A/Prof Tran is actively involved in professional leadership and governance 🏛️. He holds board positions with the Post Graduate Medical Council of Tasmania and the Emergency Medicine Foundation 🌐. As a founding chair of multiple research and clinical networks in Tasmania, he fosters collaboration across institutions 🧠. His work with national bodies like the Australasian College for Emergency Medicine highlights his role in shaping emergency medicine policy and clinical trials 🤝. Through mentoring PhD students and developing health pathways, he cultivates the next generation of clinician-researchers while advancing medical knowledge and innovation 🧬📊.

Research Focus

A/Prof Tran’s research spans emergency medicine systems, trauma care 🚑, infectious disease diagnostics (e.g., COVID-19 rapid testing 🧪), implementation science, and health services reform 🏥. As Director of the TASER institute and Chair of ACEM’s Research Committee, he champions data-driven clinical improvement. His work integrates epidemiology 📊, clinical trials, and knowledge translation with a focus on real-world impact—ranging from trauma outcomes to opioid prescribing and elder care 🧓. He also contributes to national surveillance systems and predictive analytics, ensuring timely, evidence-based interventions that enhance emergency care in Australia and beyond 🌏.

Awards & Honors

A/Prof Tran’s dedication to excellence has earned him prestigious accolades, including the 2023 Vice Chancellor’s Award for Teaching Excellence 🥇 and the College of Health and Medicine’s Teaching and Early Career Research Awards 🧠📖. His impactful work is backed by over $3 million in grants as Chief Investigator and $23 million as Associate Investigator 💰. Recognized for both leadership and innovation, he serves on editorial boards and research councils, and was named Oceanic Representative for the International Federation for Emergency Medicine Research 🌐. These honors reflect his influence in academic medicine, teaching, and global emergency care advancement 🚨.

Publication Top Notes:

📚 Notable Recent Publications (Selected)

1.Emergency Department Clinical Quality Registries: A Scoping Review
Healthcare, 2025
🔍 A comprehensive scoping review exploring the current landscape, challenges, and opportunities of clinical quality registries in emergency departments.
👉 DOI: 10.3390/healthcare13091022

2.Incidence and 12-Month Outcomes of Fracture Types Associated with Abuse in Children Under Three
Future, 2025
🧸 Investigates patterns and long-term outcomes of abuse-related fractures in young children, highlighting the critical role of emergency departments in early detection.
👉 DOI: 10.3390/future3010003

3.Making the Most of What We Have: The Future of Emergency Department Data
Emergency Medicine Australasia, 2024
📊 Discusses the strategic potential of ED data to enhance patient outcomes and system efficiency across Australasia.
👉 DOI: 10.1111/1742-6723.14475

4.Use and Impact of Clinical Pathways Across Healthcare Settings: Protocol for an Umbrella Review
Journal of Evaluation in Clinical Practice, 2024
🌐 Protocol for a high-level synthesis of global evidence regarding clinical pathways and their outcomes in diverse healthcare environments.
👉 DOI: 10.1111/jep.14201

5.Procedural Sedation and Analgesia in an Australian ED: Insights from a New Registry
Anesthesia Research, 2024
💉 Presents data from a novel sedation registry, enhancing understanding of practice patterns and safety in procedural sedation.
👉 DOI: 10.3390/anesthres1030015

Conclusion:

A/Prof Viet Tran exemplifies the qualities of a modern academic clinician-researcher: intellectually rigorous, clinically relevant, and impact-driven. His translational research, innovative leadership, and dedication to both scholarly excellence and public service make him a prime candidate for the Excellence in Research Award.