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Silver Inhibits the Biofilm Formation of <i>Pseudomonas aeruginosa</i>

Advances in Microbiology 2015年第10期5卷 677-685页

作者： Bipin Kumar Sharma Animesh Saha lovely rahaman Surajit Bhattacharjee Prosun Tribedi Department of Microbiology Tripura University Suryamaninagar Tripura India Department of Molecular Biology and Bioinformatics Tripura University Suryamaninagar Tripura India

Biofilm is the assemblage of microbial cells that are irreversibly associated with biotic and abiotic surfaces and is usually enclosed in the self secreted extracellular polymeric substances (EPS). The presence of EPS in biofilm makes the microbial population resistance against antibiotics and other drugs. Biofilms are considered as a serious challenge to pharmaceutical industries because most of the microbial diseases are now associated with biofilm. In this context, we have addressed the biofilm potentialities of Pseudomonas aeruginosa, which has been found to be associated with several deadly diseases including septicemia, urinary tract infections, and gastrointestinal infections, and wherein biofilm plays a crucial role in pathogenesis. Since silver had been used globally for a long time for treating a wide range of illnesses from burn wounds, typhoid, and anthrax to bacterial conjunctivitis in newborns, but its antibiofilm activity is still unknown. Thus, in this current study, we have tried to examine the antibiofilm potentiality of silver against the biofilm of Pseudomonas aeruginosa. Our result showed that silver exhibited considerable antimicrobial property against Pseudomonas aeruginosa where the minimum inhibitory concentration (MIC) was found at 25 μg/ml. Biofilm inhibition by silver against Pseudomonas aeruginosa was then evaluated by crystal violet (CV) staining, estimation of total biofilm protein and microscopy based microbial adherence test using the sub MIC doses of silver. The results showed that all the tested sub MIC doses of silver exhibited considerable antibiofilm activity against P. aeruginosa, wherein the maximum biofilm attenuation was showed by a silver concentration of 20 μg/ml. We also observed that all these sub MIC doses of silver neither interfere with the growth cycle of the bacteria nor affect the cell viability but only attenuates biofilm formation property of the bacteria. The current study deciphers a new axis in biofilm biology

关键词： Pseudomonas Silver Antimicrobial Antibiofilm

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Isolation and Partial Evaluation of a Potential Indigenous Yeast Strain <i>Pichia kudriavzevii</i>from a Traditional Rice Beer—“Gora” Prepared by the Koloi Tribes of Tripura

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Advances in Microbiology 2019年第9期9卷 824-841页

作者： Sushanta Ghosh Surajit De Mandal Nandita Nath David L. Kaipeng lovely rahaman Senthil Kumar Nachimuthu Bipin Kumar Sharma Department of Microbiology Tripura University Suryamaninagar India Department of Biotechnology Mizoram University Aizawl India

As per tradition from hundreds of years the Koloi tribes of Tripura are preparing “Gora”-therice based fermented beer which is very good in taste and aroma applying their traditional indigenous brewing techniques. In this study, an attempt has been made to identify the indigenous yeast which is the main causative agent for fermentation and to investigate its fermentation ability with an industrial Saccharomyces cerevisiaes train. After investigation based on culture dependent phenotypic characteristics like-staining and biochemical characterization, primarily the responsible yeast species was determined as Pichia kudriavzevii and further confirmed followed by 18S rRNA ribotyping and the sequences was deposited at Gene bank and NCBI bearing specific accession number. In the comparative analysis, it has been found a significant similarities in all aspects of nutritional and alcohol percentages with the industrial strain in laboratory condition. The alcohol percentage in the rice beer “Gora” measured 6.40 ± 0.008% v/v. The study may be the first scientific investigation of its kind about this indigenous yeast strain isolated from “Gora” of this Indo-Burma biodiversity region and may provide sufficient background and potentiality for promoting these kinds of indigenous alcoholic beverages for small scale commercialization to strengthen the rural livelihood as well as to maintain immaterial cultural heritage.

关键词： Beer Yeast Fermentation 18S rRNA

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Anisotropic quintessence compact star in f(T)gravity with Tolman–Kuchowicz metric potentials

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Communications in Theoretical Physics 2024年第1期76卷 61-75页

作者： Piyali Bhar Farook rahaman Shyam Das Somi Aktar Abdelghani Errehymy Department of Mathematics Government General Degree College SingurHooghlyWest Bengal 712409India Department of Mathematics Jadavpur UniversityKolkata 700032West BengalIndia Department of Physics Malda College MaldaWest Bengal 732101India Astrophysics Research Centre School of MathematicsStatistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X54001Durban 4000South Africa

To obtain analytically relativistic quintessence anisotropic spherical solutions in the f(T)paradigm is the primary objective of this *** do this,the pressure anisotropy condition is imposed,and we employ a metric potential of the Tolman–Kuchowicz(TK)*** also suppose that our current model incorporates a quintessence field characterized by a parameterωq,in addition to the anisotropic matter *** the presence of the parameterα,the field equations are modified by the choice of the f(T)*** f(T)gravity parameterαadds new components to the basic physical characteristics,such as density,pressure,subliminal sound velocity,surface redshift,etc,of the present *** selecting the compact star Her X-1 and varyingαfrom 0.5 to 2.5,we examined all the physical characteristics of the model parameter of the *** graphical process demonstrates that a more compact item is produced with greater values ofα.The hydrostatic equilibrium condition of the model is discussed,as well as the mass-radius relationship for our current model is obtained.

关键词： quintessence star f(T)gravity stability condition

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Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis:Evidence from Shimla district of North-west Indian Himalayan region

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Journal of Mountain Science 2024年第7期21卷 2368-2393页

作者： SHARMA Aastha SAJJAD Haroon rahaman Md Hibjur SAHA Tamal Kanti BHUYAN Nirsobha Department of Geography Faculty of SciencesJamia Millia IslamiaNew Delhi-110025India

The Indian Himalayan region is frequently experiencing climate change-induced ***,landslide susceptibility assessment assumes greater significance for lessening the impact of a landslide *** paper makes an attempt to assess landslide susceptibility in Shimla district of the northwest Indian Himalayan *** examined the effectiveness of random forest(RF),multilayer perceptron(MLP),sequential minimal optimization regression(SMOreg)and bagging ensemble(B-RF,BSMOreg,B-MLP)models.A landslide inventory map comprising 1052 locations of past landslide occurrences was classified into training(70%)and testing(30%)*** site-specific influencing factors were selected by employing a multicollinearity *** relationship between past landslide occurrences and influencing factors was established using the frequency ratio *** effectiveness of machine learning models was verified through performance *** landslide susceptibility maps were validated by the area under the receiver operating characteristic curves(ROC-AUC),accuracy,precision,recall and *** key performance metrics and map validation demonstrated that the BRF model(correlation coefficient:0.988,mean absolute error:0.010,root mean square error:0.058,relative absolute error:2.964,ROC-AUC:0.947,accuracy:0.778,precision:0.819,recall:0.917 and F-1 score:0.865)outperformed the single classifiers and other bagging ensemble models for landslide *** results show that the largest area was found under the very high susceptibility zone(33.87%),followed by the low(27.30%),high(20.68%)and moderate(18.16%)susceptibility *** factors,namely average annual rainfall,slope,lithology,soil texture and earthquake magnitude have been identified as the influencing factors for very high landslide *** texture,lineament density and elevation have been attributed to high and moderate ***,the study calls for devising suitable landslide mitig

关键词： Landslide susceptibility Site-specific factors Machine learning models Hybrid ensemble learning Geospatial techniques Himalayan region

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Vision Intelligence for Smart Sheep Farming: Applying Ensemble Learning to Detect Sheep Breeds

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ARTIFICIAL INTELLIGENCE IN AGRICULTURE 2024年第1期11卷 1-12页

作者： Himel, Galib Muhammad Shahriar Islam, Md. Masudul rahaman, Mijanur Bangladesh Univ Business & Technol Dhaka Bangladesh

The ability to automatically recognize sheep breeds holds significant value for the sheep industry. Sheep farmers often require breed identification to assess the commercial worth of their flocks. However, many farmers specifically the novice one encounter difficulties in accurately identifying sheep breeds without experts in the field. Therefore, there is a need for autonomous approaches that can effectively and precisely replicate the breed identification skills of a sheep breed expert while functioning within a farm environment, thus providing considerable benefits the industry-specific to the novice farmers in the industry. To achieve this objective, we suggest utilizing a model based on convolutional neural networks (CNNs) which can rapidly and efficiently identify the type of sheep based on their facial features. This approach offers a cost-effective solution. To conduct our experiment, we utilized a dataset consisting of 1680 facial images which represented four distinct sheep breeds. This paper proposes an ensemble method that combines Xception, VGG16, InceptionV3, InceptionResNetV2, and DenseNet121 models. During the transfer learning using this pre-trained model, we applied several optimizers and loss functions and chose the best combinations out of them. This classification model has the potential to aid sheep farmers in precisely and efficiently distinguishing between various breeds, enabling more precise assessments of sector-specific classification for different businesses. (c) 2023 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Computer vision Sheep breed classification Image processing Transfer learning Ensemble learning Meta learner

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Computer vision-based six layered ConvNeural network to recognize sign language for both numeral and alphabet signs

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Biomimetic Intelligence & Robotics 2024年第1期4卷 45-58页

作者： Muhammad Aminur rahaman Kabiratun Ummi Oyshe Prothoma Khan Chowdhury Tanoy Debnath Anichur Rahman Md.Saikat Islam Khan Department of Computer Science and Engineering Green University of BangladeshDhakaBangladesh Department of Computer Science and Engineering National Institute of Textile Engineering and Research(NITER)Constituent Institute of Dhaka UniversityDhakaBangladesh Department of Computer Science and Engineering Mawlana Bhashani Science and Technology UniversityTangailBangladesh

People who have trouble communicating verbally are often dependent on sign language,which can be difficult for most people to understand,making interaction with them a difficult *** Sign Language Recognition(SLR)system takes an input expression from a hearing or speaking-impaired person and outputs it in the form of text or voice to a normal *** existing study related to the Sign Language Recognition system has some drawbacks,such as a lack of large datasets and datasets with a range of backgrounds,skin tones,and *** research efficiently focuses on Sign Language Recognition to overcome previous *** importantly,we use our proposed Convolutional Neural Network(CNN)model,“ConvNeural”,in order to train our ***,we develop our own datasets,“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”,both of which have ambiguous backgrounds.“BdSL_OPSA22_STATIC1”and“BdSL_OPSA22_STATIC2”both include images of Bangla characters and numerals,a total of 24,615 and 8437 images,***“ConvNeural”model outperforms the pre-trained models with accuracy of 98.38%for“BdSL_OPSA22_STATIC1”and 92.78%for“BdSL_OPSA22_STATIC2”.For“BdSL_OPSA22_STATIC1”dataset,we get precision,recall,F1-score,sensitivity and specificity of 96%,95%,95%,99.31%,and 95.78%***,in case of“BdSL_OPSA22_STATIC2”dataset,we achieve precision,recall,F1-score,sensitivity and specificity of 90%,88%,88%,100%,and 100%respectively.

关键词： Conv NeuralSign language CNN Static Feature extraction Convolution2D Fully connected layer Dropout

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Increasing the accuracy and reproducibility of positron emission tomography radiomics for predicting pelvic lymph node metastasis in patients with cervical cancer using 3D local binary pattern-based texture features

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智慧医学（英文） 2024年第3期04卷 153-160页

作者： Yu Yang Li Xiaoran Du Tianming rahaman Md Grzegorzek Marcin Jerzy Li Chen Sun Hongzan Department of Radiology Shengjing Hospital of China Medical University Shenyang Liaoning 110001 China Liaoning Provincial Key Laboratory of Medical Imaging School of Computer Science and Engineering Northeastern University Shenyang Liaoning 110169 China Department of Radiology Xuanwu Hospital Capital medical University Beijing 100053 China Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Peking University Health Science Center Beijing 100191 China College of Medicine and Biological Information Engineering Northeastern University Shenyang Liaoning 110169 China The University of New South Wales Australia University of Lübeck Germany

Background:The reproducibility of positron emission tomography (PET) radiomics features is affected by several factors, such as scanning equipment, drug metabolism time and reconstruction algorithm. We aimed to explore the role of 3D local binary pattern (LBP)-based texture in increasing the accuracy and reproducibility of PET radiomics for predicting pelvic lymph node metastasis (PLNM) in patients with cervical ***:We retrospectively analysed data from 177 patients with cervical squamous cell carcinoma. They underwent 18F-fluorodeoxyglucose ( 18F-FDG)whole-body PET/computed tomography (PET/CT), followed by pelvic 18F-FDG PET/magnetic resonance imaging (PET/MR). We selected reproducible and informative PET radiomics features using Lin’s concordance correlation coefficient, least absolute shrinkage and selection operator algorithm, and established 4 models, PET/CT, PET/CT-fusion, PET/MR and PET/MR-fusion, using the logistic regression algorithm. We performed receiver operating characteristic (ROC) curve analysis to evaluate the models in the training data set (65 patients who underwent radical hysterectomy and pelvic lymph node dissection) and test data set (112 patients who received concurrent chemoradiotherapy or no treatment). The DeLong test was used for pairwise comparison of the ROC curves among the models. Results:The distribution of age, squamous cell carcinoma (SCC), International Federation of Gynaecology and Obstetrics stage and PLNM between the training and test data sets were different ( P PET/MR = PET/MR-fusion (0.954). There was no statistical difference between the ROC curve of PET/CT and PET/MR models in both

关键词： Positron emission tomography Radiomics Cervical cancer Reproducibility Pelvic lymph node metastasis

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Insights into Manipulation: Unveiling Tampered Images Using Modified ELA, Deep Learning, and Explainable AI

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Journal of Computer and Communications 2024年第6期12卷 135-151页

作者： Md. Mehedi Hasan Md. Masud Rana Abu Sayed Md. Mostafizur rahaman Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Dhaka Bangladesh

Digital image forgery (DIF) is a prevalent issue in the modern age, where malicious actors manipulate images for various purposes, including deception and misinformation. Detecting such forgeries is a critical task for maintaining the integrity of digital content. This thesis explores the use of Modified Error Level Analysis (ELA) in combination with a Convolutional Neural Network (CNN), as well as, Feedforward Neural Network (FNN) model to detect digital image forgeries. Additionally, incorporation of Explainable Artificial Intelligence (XAI) to this research provided insights into the process of decision-making by the models. The study trains and tests the models on the CASIA2 dataset, emphasizing both authentic and forged images. The CNN model is trained and evaluated, and Explainable AI (SHapley Additive exPlanation— SHAP) is incorporated to explain the model’s predictions. Similarly, the FNN model is trained and evaluated, and XAI (SHAP) is incorporated to explain the model’s predictions. The results obtained from the analysis reveals that the proposed approach using CNN model is most effective in detecting image forgeries and provides valuable explanations for decision interpretability.

关键词： IFD DIF ELA CNN FNN XAI SHAP CASIA2.0

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Deep learning methods for noisy sperm image classification from convolutional neural network to visual transformer:a comprehensive comparative study

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Intelligent Medicine 2024年第2期4卷 114-127页

作者： Ao Chen Chen Li Md Mamunur rahaman Yudong Yao Haoyuan Chen Hechen Yang Peng Zhao Weiming Hu Wanli Liu Shuojia Zou Ning Xu Marcin Grzegorzek Microscopic Image and Medical Image Analysis Group College of Medicine and Biological Information EngineeringNortheastern UniversityShenyangLiaoning 110169China Department of Electrical and Computer Engineering Stevens Institute of TechnologyHobokenNJ 07030USA School of Arts and Design Liaoning Petrochemical UniversityFushunLiaoning 113001China Institute of Medical Informatics University of LübeckLüebeckGermany

Background With the gradual increase of infertility in the world,among which male sperm problems are the main factor for infertility,more and more couples are using computer-assisted sperm analysis(CASA)to assist in the analysis and treatment of ***,the rapid development of deep learning(DL)has led to strong results in image classification ***,the classification of sperm images has not been well studied in current deep learning methods,and the sperm images are often affected by noise in practical CASA *** purpose of this article is to investigate the anti-noise robustness of deep learning classification methods applied on sperm *** The SVIA dataset is a publicly available large-scale sperm dataset containing three *** this work,we used subset-C,which provides more than 125,000 independent images of sperms and impurities,including 121,401 sperm images and 4,479 impurity *** investigate the anti-noise robustness of deep learning classification methods applied on sperm images,we conducted a comprehensive comparative study of sperm images using many convolutional neural network(CNN)and visual transformer(VT)deep learning methods to find the deep learning model with the most stable anti-noise *** This study proved that VT had strong robustness for the classification of tiny object(sperm and impurity)image datasets under some types of conventional noise and some adversarial *** particular,under the influence of Poisson noise,accuracy changed from 91.45%to 91.08%,impurity precison changed from 92.7%to 91.3%,impurity recall changed from 88.8%to 89.5%,and impurity F1-score changed 90.7%to 90.4%.Meanwhile,sperm precision changed from 90.9%to 90.5%,sperm recall changed from 92.5%to 93.8%,and sperm F1-score changed from 92.1%to 90.4%.Conclusion Sperm image classification may be strongly affected by noise in current deep learning methods;the robustness with regard to noise of VT methods based

关键词： Computer-assisted sperm analysis Anti-noise Robustness Deep learning .Image classification Sperm image Conventional noise Adversarial attacks Convolutional neural network Visual transformer

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Integrated Approaches of Mechanical Barrier, Insecticide and Botanicals against Mango Mealybug (Drosicha mangiferae)

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Advances in Entomology 2024年第3期12卷 195-202页

作者： N. Akhter M. Z. Alam M. A. rahaman M. R. U. Miah I. H. Mian M. A. Latif Department of Entomology Faculty of Agriculture Sher-e-Bangla Agricultural University Dhaka Bangladesh Department of Entomology Faculty of Agriculture Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur Bangladesh Department of Plant Pathology Faculty of Agriculture Sher-e-Bangla Agricultural University Dhaka Bangladesh Department of Plant Pathology Bangabandhu Sheikh Mujibur Rahman Agricultural University Gazipur Bangladesh

An experiment was conducted to test the efficacy of a mechanical barrier around the tree trunk with one spray of Cypermethrin @ 1 ml/l and turmeric powder extract @ 15 g/500ml of water applied in integrated approaches against mango mealybug on mango tree. There were 7 treatments including a control. The treatments were Mechanical barrier, Cypermethrin spray @ 1 ml/l, Turmeric powder spray @ 15 g/500ml of water, Cypermethrin spray + Turmeric spray, Cypermethrin spray + Mechanical barrier, Turmeric + Mechanical barrier and untreated control. Three-year-old mango plants grafted from a 5-year-old mango tree (Variety Amropali) and planted in pots were used in the experiment. The treatment, Cypermethrin spray + Mechanical barrier gave the highest reduction of mango mealybug population 87.06% to 93.90% followed by Turmeric spray + Mechanical barrier and showed 81.13% to 86.04% and Mechanical barrier alone showed 81.13% to 84.59% population reduction. Turmeric powder extract showed only (8.42% to 23.77%) population reduction of mango mealybug which was lowest compared to other treatments.

关键词： Mango Mealybug Integrated Management

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