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Methanolic extract from Lespedeza bicolor： potential candidates for natural antioxidant and anticancer agent

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Journal of Traditional Chinese Medicine 2017年第4期37卷 444-451页

作者： sami Ullah Department of Botany University of PeshawarPeshawar 24420 Pakistan

OBJECTIVE: To evaluate the anticancer, antioxidant and antimicrobial activities along with total phenolic and flavonoids contents extracted from Lespedeza bicolor indigenous to Khyber Pukhtoonkhwa ***: Anticancer activity against human lung carcinoma(LU-1) and human prostate carcinoma(Ln Cap), antimicrobial against Aspergillus fumigates, Aspergillus niger, Fusarium solani, Mucor sp Klebsiella pneumonia and Enterococcus and antioxidant activity on 1,1-Diphenyl-2-picryl-hydrazy(DPPH) and Hydrogen peroxide radicals scavenging activity were assessed in methanol extract o Lespedeza ***: Lespedeza bicolor aerial parts and root extract showed IC_(50)value of 12.5 and 50 μg/m L against LU-1 whereas, ≤ 12.5 and 12 μg/m L were calculated against Ln Cap cell line. Minimum inhibition concentration(MIC) value of 20-35 μg/m L has been observed against Aspergillus fumigates, Aspergillus niger, Fusarium solani and Mucor sp in comparision with 1-2.5 μg/m L of Terbinafine used as a standard fungicide. MIC value of 20 and 35 μg/m L of Lespedeza bicolor aerial parts and root extract against bacterial pathogen Klebsiella pneumonia and 20-50 μg/m L against Enterococcus has been measured. DPPH radical scavenging activity of Lespedeza bicolor with IC_(50)values of ≤ 50 μg/m L and ≤ 200 μg/m L was observed whereas, hydrogen peroxide scavenging activity with IC_(50)values of ≤25 μg/m L for aerial parts and ≤ 50 μg/m L for the root extract of Lespedeza bicolor has been ***: These data suggested that the methanolic extract of Lespedeza bicolor could be potential candidates for natural antioxidants and anticancer.

关键词： Lespedeza Antineoplastic agents Antioxidants Anti-infective agents

Hydrostatic pressure and temperature effects on the binding energy and optical absorption of a multilayered quantum dot with a parabolic confinement

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Chinese Physics B 2016年第12期25卷 408-417页

作者： sami Ortakaya Muharrem Kirak Department of Physics Erciyes University 38039 Kayseri Turkiye Faculty of Education Bozok University 66200 Yozgat Turkiye

The influence of hydrostatic pressure, temperature, and impurity on the electronic and optical properties of spherical core/shell/well/shell （CSWS） nanostructure with parabolic confinement potential is investigated theoretically. The energy levels and wave functions of the structure are calculated by using shooting method within the effective-mass approximation. The numerical results show that the ground state donor binding energy as a function layer thickness very sensitively depends on the magnitude of pressure and temperature. Also, we investigate the probability distributions to understand clearly electronic properties. The obtained results show that the existence of the pressure and temperature has great influence on the electronic and optical properties.

关键词： multilayers impurity pressure nonlinear optics

Semantic Document Layout Analysis of Handwritten Manuscripts

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Computers, Materials & Continua 2023年第5期75卷 2805-2831页

作者： Emad sami Jaha Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

A document layout can be more informative than merely a document’s visual and structural ***,document layout analysis(DLA)is considered a necessary prerequisite for advanced processing and detailed document image analysis to be further used in several applications and different *** research extends the traditional approaches of DLA and introduces the concept of semantic document layout analysis(SDLA)by proposing a novel framework for semantic layout analysis and characterization of handwritten *** proposed SDLA approach enables the derivation of implicit information and semantic characteristics,which can be effectively utilized in dozens of practical applications for various purposes,in a way bridging the semantic gap and providingmore understandable high-level document image analysis and more invariant characterization via absolute and relative *** approach is validated and evaluated on a large dataset ofArabic handwrittenmanuscripts comprising complex *** experimental work shows promising results in terms of accurate and effective semantic characteristic-based clustering and retrieval of handwritten *** also indicates the expected efficacy of using the capabilities of the proposed approach in automating and facilitating many functional,reallife tasks such as effort estimation and pricing of transcription or typing of such complex manuscripts.

关键词： Semantic characteristics semantic labeling document layout analysis semantic document layout analysis handwritten manuscripts clustering retrieval image processing computer vision machine learning

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典型草原两种菊科植物生长对道路建设的响应

生态学报 2025年

作者：王星奇赵欣周 GULRAIZ ahmad 张育文李佳欣 BHARELDIN Adam MERGA Daba Tuli 侯扶江草种创新与草地农业生态系统全国重点实验室兰州大学草地农业科技学院国家林业草原局西北退化草原生态修复与利用工程技术研究中心农业农村部草牧业创新重点实验室

近几十年来，由于道路网络的扩张和城市化的蓬勃发展，道路建设对典型草原的影响引起了广泛的关注。然而，道路类型和距离对植物种群生长的综合影响仍然知之甚少。因此，本研究以陇东黄土高原微温微干典型草原为研究对象，探讨了道路建... 详细信息

近几十年来，由于道路网络的扩张和城市化的蓬勃发展，道路建设对典型草原的影响引起了广泛的关注。然而，道路类型和距离对植物种群生长的综合影响仍然知之甚少。因此，本研究以陇东黄土高原微温微干典型草原为研究对象，探讨了道路建设（道路类型、距离）对菊科优势种茵陈蒿（Artemisia capillaris）和伴生种阿尔泰狗娃花（Aster altaicus）生长繁殖影响的驱动因素及其作用机制。结果表明，道路建设促进茵陈蒿的横向生长和无性繁殖，促进阿尔泰狗娃花的垂直生长和有性繁殖。阿尔泰狗娃花具有更强的更新潜力。普通公路茵陈蒿和阿尔泰狗娃花的地上生物量分别比其它两种道路平均高49%和27%，因此其对普通公路建设的响应更加敏感。此外，道路建设主要通过影响土壤进一步影响两个种群的地上生物量在群落中的占比。阿尔泰狗娃花的地上生物量及其在群落中的占比在距离20—35 m的范围存在明显阈值。因此需要注意将此范围内的植被保护和恢复措施与道路管理动态结合，影响植物生长繁殖，调控群落构建过程，以应对道路建设对种群和群落关系扰动的巨大挑战。

关键词：道路建设道路生态地上生物量生长权衡繁殖策略种间关系

Relativistic Treatment of Spinless Particles Subject to a q-Deformed Morse Potential

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Communications in Theoretical Physics 2013年第6期59卷 689-692页

作者： sami Ortakaya Erciyes niversitesi Fen Bilimleri Enstits

The approximate analytical solutions of the Klein-Gordon equation with equal scalar and vector q-deformed Morse potential are presented for arbitrary e-states by using Laplace integral transform. The energy eigenvalues and corresponding wave functions are obtained for n and e values. In this study, in the non-relativistic limit c →∞, it has been also provided that the energy eigenfunetions for Klein-Gordon system turn into those for Schrodinger one.

关键词： Bound states approximate solutions Klein-Gordon equation integral transform

Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

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Computers, Materials & Continua 2023年第6期75卷 5213-5228页

作者： Sobia Nawaz Sidra Rasheed Wania sami Lal Hussain Amjad Aldweesh Elsayed Tag eldin Umair ahmad Salaria Mohammad Shahbaz Khan Basic Health Unit Sumra Lodhran59320Pakistan Basic Health Unit 20-G ChishtianBahawalnagar62300Pakistan Doctor’s Hospital Lahore54590Pakistan Department of Computer Science&IT Neelum CampusThe University of Azad Jammu and KashmirAthmuqam13230Azad KashmirPakistan Department of Computer Science&IT King Abdullah CampusThe University of Azad Jammu and KashmirMuzaffarabad13100Azad KashmirPakistan College of Computer science and information technology Shaqra UniversityShaqra15273Saudi Arabia Faculty of Engineering and Technology Future University in EgyptNew Cairo11835Egypt Department of Electrical Engineering University of Azad Jammu and KashmirChehla CampusMuzaffarabad13100Azad KashmirPakistan Department of Electrical Engineering Mirpur University of Science&TechnologyMirpurMuzaffarabad10250Azad KashmirPakistan Children’s National Hospital 111 Michigan AVE NWWashingtonDC20854USA

This study is designed to develop Artificial Intelligence(AI)based analysis tool that could accurately detect COVID-19 lung infections based on portable chest x-rays(CXRs).The frontline physicians and radiologists suffer from grand challenges for COVID-19 pandemic due to the suboptimal image quality and the large volume of *** this study,AI-based analysis tools were developed that can precisely classify COVID-19 lung *** available datasets of COVID-19(N=1525),non-COVID-19 normal(N=1525),viral pneumonia(N=1342)and bacterial pneumonia(N=2521)from the Italian Society of Medical and Interventional Radiology(SIRM),Radiopaedia,The Cancer Imaging Archive(TCIA)and Kaggle repositories were taken.A multi-approach utilizing deep learning ResNet101 with and without hyperparameters optimization was ***,the fea-tures extracted from the average pooling layer of ResNet101 were used as input to machine learning(ML)algorithms,which twice trained the learning *** ResNet101 with optimized parameters yielded improved performance to default *** extracted features from ResNet101 are fed to the k-nearest neighbor(KNN)and support vector machine(SVM)yielded the highest 3-class classification performance of 99.86%and 99.46%,*** results indicate that the proposed approach can be bet-ter utilized for improving the accuracy and diagnostic efficiency of *** proposed deep learning model has the potential to improve further the efficiency of the healthcare systems for proper diagnosis and prognosis of COVID-19 lung infection.

关键词： COVID-19 deep learning(DL) lung infection convolutional neural network(CNN)

An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

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Computer Systems Science & Engineering 2023年第7期46卷 897-911页

作者： Muhammad Zia Ur Rehman Jawad ahmad Emad sami Jaha Abdullah Marish Ali Mohammed A.Alzain Faisal Saeed Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City University15 Bartholomew RowBirminghamB55JUUK

Breast cancer is one of the leading cancers among *** has the second-highest mortality rate in women after lung *** detection,especially in the early stages,can help increase survival ***,manual diagnosis of breast cancer is a tedious and time-consuming process,and the accuracy of detection is reliant on the quality of the images and the radiologist’s ***,computer-aided medical diagnosis has recently shown promising results,leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early *** research presented in this paper is focused on the multi-class classification of breast *** deep transfer learning approach has been utilized to train the deep learning models,and a pre-processing technique has been used to improve the quality of the ultrasound *** proposed technique utilizes two deep learning models,Mobile-NetV2 and DenseNet201,for the composition of the deep ensemble *** learning models are fine-tuned along with hyperparameter tuning to achieve better ***,entropy-based feature selection is *** cancer identification using the proposed classification approach was found to attain an accuracy of 97.04%,while the sensitivity and F1 score were 96.87%and 96.76%,*** performance of the proposed model is very effective and outperforms other state-of-the-art techniques presented in the literature.

关键词： Breast cancer image enhancement ensemble model transfer learning feature selection

Post-operative visual outcomes based on morphological staging of idiopathic epiretinal membranes on OCT

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International Journal of Ophthalmology(English edition) 2022年第12期15卷 1966-1970页

作者： Sehrish Nizar Ali Momin Roha ahmad Choudhary MARehman Siddiqui Shiraz Hashmi Abdul sami Memon Haroon Tayyab Department of Ophthalmology and Visual Sciences the Aga Khan University HospitalKarachiSindh 74800Pakistan

AIM:To evaluate the recently described optical coherence tomography(OCT)based classification of epiretinal membrane(ERM)and its usefulness in predicting the functional ***:A retrospective observational review of OCT scans of patients with the diagnosis of idiopathic ERM was carried out from January 2016 to June *** consecutive images diagnosed with any stage of idiopathic ERM and fulfilled the eligibility criteria were included in the *** was identified on OCT scans as a thin hyperreflective layer over the inner layers of *** scans of patients with ERM who underwent vitrectomy,were independently staged as per the new classification by two independent retinal surgeons to form a consensus on *** corrected visual acuity(BCVA)in logMAR scale and central subfield thickness(CST)on pre-and post-operative spectral domain OCT scans were the variables noted for all patients at the time of diagnosis and at 6 and 12 mo follow up visit after undergoing *** correlation coefficient was computed between BCVA(logMAR)and CST by ERM stage adjusting by baseline ***:Clinical charts of 74 patients with idiopathic ERM were *** significant improvement in BCVA overtime was observed with significant difference in median visual acuity of patients with StageⅡ-ⅣERM with P0.3).CONCLUSION:Equally significant visual outcomes of patients with ERM stagedⅡ-Ⅳand therefore can be couns

关键词： optical coherence tomography epiretinal membrane cotton ball sign vitreoschisis vitrectomy

Application of machine learning algorithms to predict tubing pressure in intermittent gas lift wells

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Petroleum Research 2022年第2期7卷 246-252页

作者： Nagham Amer sami Department of Petroleum Engineering Faculty of Earth ScienceUniversity of Miskolc3515MiskolcHungary

Tubing pressure at gas injection depth in intermittent wells is one of the most critical parameters for production engineers to evaluate the performance of the ***,monitoring of the tubing pressure is not usually carried out in real *** has been realized that the generally used correlations are not effective enough due to complexity of the intermittent process which involve many parameters and assumptions to develop such *** focus of this study is to utilize machine learning(ML)algorithms to develop a model that can accurately predict tubing pressure in artificial intermittent gas lift *** algorithms built on the field data provide a solution that is easy to use and universally applicable to the complex *** non-linear regression ML methods are employed in this study,namely,Decision Tree-regression(DT),Random Forest-regression(RF)and K Nearest Neighbors-regression(KNN).All the tubing pressures obtained from ML models were compared with the actual values to ensure the effectiveness of the *** developed models show that it can predict the pressure with more than 99.9%*** is an interesting result,as such outcome accuracy has not been reported usually in the open literature.

关键词： Machine learning Artificial intelligence Intermittent gas lift Tubing pressure Random forest Decision tree KNN