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  1. Article ; Online: Powered mobility in low- and middle-income countries: Caregivers' perspective from Bangladesh.

    Jahan, Israt / Islam, Shafiul

    Developmental medicine and child neurology

    2023  Volume 66, Issue 3, Page(s) 276–277

    MeSH term(s) Humans ; Caregivers ; Bangladesh ; Developing Countries ; Surveys and Questionnaires
    Language English
    Publishing date 2023-08-03
    Publishing country England
    Document type Journal Article
    ZDB-ID 80369-8
    ISSN 1469-8749 ; 0012-1622
    ISSN (online) 1469-8749
    ISSN 0012-1622
    DOI 10.1111/dmcn.15728
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Comprehensive Analysis of

    Jahan, Israt / Wang, Yihan / Li, Ping / Hussain, Sarfaraz / Song, Jiayi / Yan, Jian

    Journal of agricultural and food chemistry

    2024  

    Abstract: The filamentous ... ...

    Abstract The filamentous fungus
    Language English
    Publishing date 2024-04-22
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 241619-0
    ISSN 1520-5118 ; 0021-8561
    ISSN (online) 1520-5118
    ISSN 0021-8561
    DOI 10.1021/acs.jafc.3c09866
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  3. Article: The Effects of Silver Nanoparticles (AgNPs) on Thermophilic Bacteria: Antibacterial, Morphological, Physiological and Biochemical Investigations.

    Jahan, Israt / Matpan Bekler, Fatma / Tunç, Ahmed / Güven, Kemal

    Microorganisms

    2024  Volume 12, Issue 2

    Abstract: Since thermophilic microorganisms are valuable sources of thermostable enzymes, it is essential to recognize the potential toxicity of silver nanoparticles used in diverse industrial sectors. Thermophilic ... ...

    Abstract Since thermophilic microorganisms are valuable sources of thermostable enzymes, it is essential to recognize the potential toxicity of silver nanoparticles used in diverse industrial sectors. Thermophilic bacteria
    Language English
    Publishing date 2024-02-17
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2720891-6
    ISSN 2076-2607
    ISSN 2076-2607
    DOI 10.3390/microorganisms12020402
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A comprehensive evaluation of large Language models on benchmark biomedical text processing tasks.

    Jahan, Israt / Laskar, Md Tahmid Rahman / Peng, Chun / Huang, Jimmy Xiangji

    Computers in biology and medicine

    2024  Volume 171, Page(s) 108189

    Abstract: Recently, Large Language Models (LLMs) have demonstrated impressive capability to solve a wide range of tasks. However, despite their success across various tasks, no prior work has investigated their capability in the biomedical domain yet. To this end, ...

    Abstract Recently, Large Language Models (LLMs) have demonstrated impressive capability to solve a wide range of tasks. However, despite their success across various tasks, no prior work has investigated their capability in the biomedical domain yet. To this end, this paper aims to evaluate the performance of LLMs on benchmark biomedical tasks. For this purpose, a comprehensive evaluation of 4 popular LLMs in 6 diverse biomedical tasks across 26 datasets has been conducted. To the best of our knowledge, this is the first work that conducts an extensive evaluation and comparison of various LLMs in the biomedical domain. Interestingly, we find based on our evaluation that in biomedical datasets that have smaller training sets, zero-shot LLMs even outperform the current state-of-the-art models when they were fine-tuned only on the training set of these datasets. This suggests that pre-training on large text corpora makes LLMs quite specialized even in the biomedical domain. We also find that not a single LLM can outperform other LLMs in all tasks, with the performance of different LLMs may vary depending on the task. While their performance is still quite poor in comparison to the biomedical models that were fine-tuned on large training sets, our findings demonstrate that LLMs have the potential to be a valuable tool for various biomedical tasks that lack large annotated data.
    MeSH term(s) Female ; Humans ; Benchmarking ; Language ; Uterus
    Language English
    Publishing date 2024-02-20
    Publishing country United States
    Document type Journal Article
    ZDB-ID 127557-4
    ISSN 1879-0534 ; 0010-4825
    ISSN (online) 1879-0534
    ISSN 0010-4825
    DOI 10.1016/j.compbiomed.2024.108189
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  5. Article: Natural Polymer-Based Electrospun Nanofibrous Membranes for Wastewater Treatment: A Review

    Jahan, Israt / Zhang, Lifeng

    Journal of polymers and the environment. 2022 May, v. 30, no. 5

    2022  

    Abstract: Electrospun nanofibrous membranes (ENMs) from natural polymers have earned considerable interest over past years for the purpose of wastewater treatment. This review addressed the most recent research advances in sustainable membrane technology of ... ...

    Abstract Electrospun nanofibrous membranes (ENMs) from natural polymers have earned considerable interest over past years for the purpose of wastewater treatment. This review addressed the most recent research advances in sustainable membrane technology of electrospinning natural polymers for wastewater treatment. Preparation of ENMs from the most abundant natural polymers including cellulose, chitosan, lignin and their derivatives as well as others like cyclodextrin, alginate, and protein and their applications in wastewater treatment are discussed. The strategies to design natural polymer-based ENMs toward adsorption/degradation of water contaminants including heavy metal ions, dyes, oils, and pharmaceutical compounds are emphasized. The intention of this review is to provide an overall picture of current research progress as well as future perspectives on natural polymer-based ENMs in the field of wastewater treatment from viewpoint of a material scientist.
    Keywords adsorption ; alginates ; cellulose ; chitosan ; cyclodextrins ; environment ; heavy metals ; lignin ; nanofibers ; scientists ; wastewater treatment ; water pollution
    Language English
    Dates of publication 2022-05
    Size p. 1709-1729.
    Publishing place Springer US
    Document type Article
    Note Review
    ZDB-ID 2017207-2
    ISSN 1572-8919 ; 1572-8900 ; 1566-2543
    ISSN (online) 1572-8919 ; 1572-8900
    ISSN 1566-2543
    DOI 10.1007/s10924-021-02312-1
    Database NAL-Catalogue (AGRICOLA)

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  6. Article ; Online: Data-Driven Diabetes Risk Factor Prediction Using Machine Learning Algorithms with Feature Selection Technique

    Israt Jahan Kakoly / Md. Rakibul Hoque / Najmul Hasan

    Sustainability, Vol 15, Iss 4930, p

    2023  Volume 4930

    Abstract: As type 2 diabetes becomes more prevalent across the globe, predicting its sources becomes more important. However, there is a big void in predicting the risk factors of this disease. Thus, the purpose of this study is to predict diabetes risk factors by ...

    Abstract As type 2 diabetes becomes more prevalent across the globe, predicting its sources becomes more important. However, there is a big void in predicting the risk factors of this disease. Thus, the purpose of this study is to predict diabetes risk factors by applying machine learning (ML) algorithms. Two-fold feature selection techniques (i.e., principal component analysis, PCA, and information gain, IG) have been applied to boost the prediction accuracy. Then, the optimal features are fed into five ML algorithms, namely decision tree, random forest, support vector machine, logistic regression, and KNN. The primary data used to train the ML model were collected based on the safety procedure described in the Helsinki Declaration, 2013, and 738 records were included in the final analysis. The result has shown an accuracy level of over 82.2%, with an AUC (area under the ROC curve) value of 87.2%. This research not only identified the most important clinical and nonclinical factors in diabetes prediction, but it also found that the clinical risk factor (glucose) is the most relevant for diabetes prediction, followed by dietary factors. The noteworthy contribution of this research is the identification of previously unclassified factors left over from the previous study that considered both clinical and non-clinical aspects.
    Keywords diabetes ; feature selection ; risk factors ; machine learning ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Language English
    Publishing date 2023-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Environmental Sustainability of Industrial Waste-Based Cementitious Materials

    Satheeskumar Navaratnam / Quddus Tushar / Israt Jahan / Guomin Zhang

    Sustainability, Vol 15, Iss 1873, p

    A Review, Experimental Investigation and Life-Cycle Assessment

    2023  Volume 1873

    Abstract: Wall plaster production induces significant environmental impacts during its entire life as it consumes a high amount of cement and natural resources. Therefore, in sustainable development, industrial wastes are partially replaced to produce cementitious ...

    Abstract Wall plaster production induces significant environmental impacts during its entire life as it consumes a high amount of cement and natural resources. Therefore, in sustainable development, industrial wastes are partially replaced to produce cementitious material to reduce environmental impacts. This study aims to identify the optimal environmental benefits from the waste-based cementitious materials that are used to produce wall plaster. Thus, this study involved conducting a comprehensive review of the mechanical and sustainable performance of industrial waste-based cementitious materials focused on wall construction. Then, an experimental test was conducted to ensure the appropriate mix design to enable the required compressive strength. A comparative analysis of mortar showed that it contained 15% (by weight) of fly ash, blast furnace slag, bottom ash, recycled glass, ferronickel slag, expanded polystyrene and wood ash using life-cycle assessment. The results show that mortar containing fly ash has lower environmental impacts in almost all impact categories (i.e., human health, the ecosystem and natural resources). Endpoint damage assessment of mortar mixtures expresses resource extraction cost as the most affected impact criteria. The replacement of globally consumed cement with 15% fly ash can contribute to monetary savings of up to USD 87.74 billion. The assessment clarifies the advantage of incorporating waste products in cement mortar, which allows policymakers to interpret the analysis for decision making. This study also found that the production of industrial wastes for mortar mixes has a significant impact on the environment.
    Keywords blast furnace slag ; fly ash ; recycled glass ; life-cycle analysis ; environmental impacts ; compressive strength ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 690
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Book ; Online: IoTWarden

    Alam, Md Morshed / Jahan, Israt / Wang, Weichao

    A Deep Reinforcement Learning Based Real-time Defense System to Mitigate Trigger-action IoT Attacks

    2024  

    Abstract: In trigger-action IoT platforms, IoT devices report event conditions to IoT hubs notifying their cyber states and let the hubs invoke actions in other IoT devices based on functional dependencies defined as rules in a rule engine. These functional ... ...

    Abstract In trigger-action IoT platforms, IoT devices report event conditions to IoT hubs notifying their cyber states and let the hubs invoke actions in other IoT devices based on functional dependencies defined as rules in a rule engine. These functional dependencies create a chain of interactions that help automate network tasks. Adversaries exploit this chain to report fake event conditions to IoT hubs and perform remote injection attacks upon a smart environment to indirectly control targeted IoT devices. Existing defense efforts usually depend on static analysis over IoT apps to develop rule-based anomaly detection mechanisms. We also see ML-based defense mechanisms in the literature that harness physical event fingerprints to determine anomalies in an IoT network. However, these methods often demonstrate long response time and lack of adaptability when facing complicated attacks. In this paper, we propose to build a deep reinforcement learning based real-time defense system for injection attacks. We define the reward functions for defenders and implement a deep Q-network based approach to identify the optimal defense policy. Our experiments show that the proposed mechanism can effectively and accurately identify and defend against injection attacks with reasonable computation overhead.

    Comment: 2024 IEEE Wireless Communications and Networking Conference (WCNC 2024)
    Keywords Computer Science - Cryptography and Security
    Subject code 006
    Publishing date 2024-01-16
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article: Total Knee Replacement in a Young Patient with Valgus Knee Osteoarthritis: A Case Report.

    Ahsan, Pervez / Ezaz, Md Shafiul / Jahan, Israt / Asma, Nusrat Sharmin / Anjoom, Maliha

    Journal of orthopaedic case reports

    2024  Volume 14, Issue 1, Page(s) 48–53

    Abstract: Introduction: Valgus deformity is characterized by an outward angulation of the knee joint. The most common cause of valgus deformity is osteoarthritis (OA), a prevalent progressive joint disease that causes chronic pain and functional limitations. ... ...

    Abstract Introduction: Valgus deformity is characterized by an outward angulation of the knee joint. The most common cause of valgus deformity is osteoarthritis (OA), a prevalent progressive joint disease that causes chronic pain and functional limitations. Total knee replacement (TKR) is rarely done in patients with grade-I valgus deformity and young age. To the best of our knowledge, this is the first case report of its kind.
    Case report: A 34-year-old man presented to us with 15 years of persistent, progressively worsening right knee pain that was interfering with his daily activities. No non-operative treatment could alleviate his severe pain. Physical examination revealed a positive valgus stress test, limited knee extension, and an asymmetrical gait. He was diagnosed with a grade-I valgus deformity of the right osteoarthritic knee. History, physical examination, and radiological findings confirmed the diagnosis. In consideration of severe pain and impaired quality of life, we opted to perform TKR using a medial parapatellar approach. Regular follow-ups were done after the procedure. He experienced no pain or recurrence of deformity. He was very satisfied with the result. His Western Ontario and McMaster Universities OA Index score at 12 months following surgery was 5, indicating a favorable outcome.
    Conclusion: This case exhibits the effectiveness of TKR in treating grade-I valgus deformity of the osteoarthritic knee with severe pain in a young adult, resulting in improved pain alleviation, mobility, joint alignment, and overall quality of life.
    Language English
    Publishing date 2024-01-23
    Publishing country India
    Document type Case Reports
    ZDB-ID 2658169-3
    ISSN 2250-0685
    ISSN 2250-0685
    DOI 10.13107/jocr.2024.v14.i01.4144
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Antifungal potential of lipopeptides produced by the

    Hussain, Sarfaraz / Tai, Bowen / Ali, Maratab / Jahan, Israt / Sakina, Suha / Wang, Gang / Zhang, Xinlong / Yin, Yixuan / Xing, Fuguo

    Microbiology spectrum

    2024  Volume 12, Issue 4, Page(s) e0400823

    Abstract: Biological control is a more sustainable and environmentally friendly alternative to chemical fungicides for ... ...

    Abstract Biological control is a more sustainable and environmentally friendly alternative to chemical fungicides for controlling
    MeSH term(s) Antifungal Agents/chemistry ; Fusarium/genetics ; Fungicides, Industrial/metabolism ; Fungicides, Industrial/pharmacology ; Antioxidants/pharmacology ; Antioxidants/metabolism ; Lipopolysaccharides/metabolism ; Lipopeptides/pharmacology ; DNA/metabolism ; Ergosterol ; Plant Diseases/prevention & control ; Plant Diseases/microbiology ; Bacillus
    Chemical Substances Antifungal Agents ; Fungicides, Industrial ; Antioxidants ; Lipopolysaccharides ; Lipopeptides ; DNA (9007-49-2) ; Ergosterol (Z30RAY509F)
    Language English
    Publishing date 2024-03-07
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2807133-5
    ISSN 2165-0497 ; 2165-0497
    ISSN (online) 2165-0497
    ISSN 2165-0497
    DOI 10.1128/spectrum.04008-23
    Database MEDical Literature Analysis and Retrieval System OnLINE

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