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Atypical Renal Cysts: Is MRI a Compulsory Examination in 2020 before Therapeutic Management?

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Open Journal of Urology 2020年第10期10卷 253-262页

作者： idriss ziani Ahmed Ibrahimi Hamza Dergamoun Omar Belouki Hachem El Sayegh Lounis Benslimane Yassine Nouini Urological Surgery Department “A” IBN Sina University Hospital CHU RABAT Rabat Morocco RABAT Faculty of Medicine Mohammed V University Rabat Morocco

Introduction: Kidney cancer represents 2% to 3% of malignant tumors, with an incidence of 5.8/100,000 in Western countries, a very specific subgroup of renal tumors that are cystic tumors. In fact, almost 50% of the population over 50 has a renal cyst. Materials and Methods: The objective of this study is to establish a correlation between the preoperative Bosniak score and the postoperative anatomopathological analysis in order to answer this question, the use of contrast ultrasound or MRI should be systematically performed before an atypical renal cyst? This is a retrospective study of 50 patients treated for renal cysts between January 2010 and March 2016. All patients have an abdominopelvic ultrasound and an abdominal scanner. Cysts have been classified according to the Bosniak classification. We treated our patients based on the radiological examination urocsanner and we classified our patients according to the classification of Bosniak, and uro MRI was performed in cases of atypical cysts or diagnostic doubt before considering a therapeutic attituderding to the classification of Bosniak. Results: In our work, the Uro MRI was sharper for atypical cysts (type IIF and Type III cyst) with sensitivity greater than that of the scanner but with a specificity similar to that of the scanner. And therefore be a key examination in the atypical kidney cysts. Conclusions: URO MRI is currently in 2020 a key examination of atypical bonsiak IIf and III cysts before management of the therapeutic load.

关键词： Atypical Cyst BosniaK Cystic Tumors URO MRI

GIS Application in Urban Flood Risk Analysis: Midar as a Case Study

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Open Journal of Ecology 2024年第2期14卷 148-164页

作者： Adil Akallouch Ayoub Al Mashoudi Mouloud ziani Rachid Elhani Sidi Mohamed Ben Abdellah University Fez Morocco Abdelmalek Essaadi University Tetouan Morocco

The significance of this study lies in its exploration of the advanced applications of Geographic Information Systems (GIS) in assessing urban flood risks, with a specific focus on Midar, Morocco. This research is pivotal as it showcases that GIS technology is not just a tool for mapping, but a critical component in urban planning and emergency management strategies. By meticulously identifying and mapping flood-prone areas in Midar, the study provides invaluable insights into the potential vulnerabilities of urban landscapes to flooding. Moreover, this research demonstrates the practical utility of GIS in mitigating material losses, a significant concern in flood-prone urban areas. The proactive approach proposed in this study, centered around the use of GIS, aims to safeguard Midar’s population and infrastructure from the devastating impacts of floods. This approach serves as a model for other urban areas facing similar challenges, highlighting the indispensable role of GIS in disaster preparedness and response. Overall, the study underscores the transformative potential of GIS in enhancing urban resilience, making it a crucial tool in the fight against natural disasters like floods.

关键词： Geographic Information Systems Risk Assessment Models Hydrological Modeling Urban Planning Decision-Making Methods Urban Centers

Cotton Leafhoppers, Amrasca biguttula (Ishida, 1913) (Hemiptera: Cicadellidae), Identified as a New Species on Okra and Guinea Sorrel in Niger

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Advances in Entomology 2024年第3期12卷 183-194页

作者： Zinsou François-Xavier Akonde Ousmane Zakari Moussa Sanoussi Atta idriss Hamidou Leyo Iro Dan Guimbo Agricultural Zoology Laboratory AGRHYMET Regional Center Niamey Niger Faculty of Agronomy Abdou Moumouni University Niamey Niger

Leafhoppers (jassids) are well-known pests of vegetable crops in Niger. They are often part of a parasitic complex that causes varying degrees of damage. Over the last two crop years, the Niamey region has seen a heavy outbreak of leaf hoppers on okra and guinea sorrel. These insects alone have caused spectacular damage, resulting in losses ranging from 50% to 100% of unharvested plants. Following this observation, infested fields were surveyed, specimens sampled, and the responsible species identified. Two sites were surveyed in the city of Niamey. At each site, two plots of okra and two of guinea sorrel were visited. Fifty (50) plants were randomly sampled using the double “W” method per plot. The sampled plants were used for active and passive leaf hopper capture, damage description and loss assessment. Captured leaf hoppers were identified based on their morphology observed with a binocular magnifying glass and compared with the data in the identification keys. The symptoms observed in the plots were yellowing, leaf curling and drying, stunting, abortion of flowers and immature fruit and very low production. Identification results revealed the single species Amrasca biguttula (Ishida, 1913), which can be considered a new invasive species in Niger. Further confirmation of this identification by molecular tests, the distribution of the pest in Niger and the development of appropriate control methods would yield good prospects.

关键词： Amrasca biguttula Guinea Sorrel Niger Okra Survey

Tuberculosis in the Carcinal Environment in Chad Due to the Mycobacterium Tuberculosis Circulante Complex

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Journal of Biosciences and Medicines 2024年第2期12卷 214-224页

作者： Ahmat idriss Ahmat Mahamat Tahir Ngaré Hassan Ngandolo Bongo Nare Richard Mahamat Adanao Adoudou Mbah Ntepe Leonel Javeres Hamidou Yacoubou Ali Mahamat Moussa Laboratory for Diagnostic Research and Scientific Expertise University of N’Djamena N’Djamena Chad Veterinary and Zootechnical Research Laboratory of Farcha N’Djamena Livestock and Development Research Institute N’Djamena Chad Institute of Medical Research and Medicinal Plant Studies (IMPM) Ministry of Scientific Research and Innovation Yaoundé Cameroon Cameroon Ministry of Public Health Yaoundé Cameroon Faculty of Human Health Sciences University of N’Djamena N’Djamena Chad

Tuberculosis (TB) is a serious infectious disease and its control is considered a challenge, particularly among vulnerable populations such as prisoners. The prevalence of TB in prisons is an alarming public health problem in many countries. The aim of this study is to describe the epidemiology of tuberculosis and the strategies for controlling this disease in the Chadian prison population. During the course of our study, the prevalence of tuberculosis in prisons was 9.64%. The age group between 55 years and over (43.33%) was the most represented in this study, and all patients were men with a frequency of 62.66%. The cross-tabulation of Culture_7H9G and Culture_7H9P showed that out of our total positive sample, we found a total of 87 positive strains and 63 negative strains. Our study shows that it is essential to know the prevalence of tuberculosis in all the country’s prisons. Indeed, this can serve as an indication of the need for action in prisons to reduce TB rates, in particular by improving the structure of prison environments, diagnosing new cases quickly and accurately, identifying drug-resistant strains and implementing effective, direct treatment observed in people with tuberculosis.

关键词： Mycobacterium Prison Tuberculosis and Chad

Extraction of Fetal Electrocardiogram by Combining Deep Learning and SVD-ICA-NMF Methods

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Big Data Mining and Analytics 2023年第3期6卷 301-310页

作者： Said ziani Yousef Farhaoui Mohammed Moutaib Research Group in Biomedical Engineering and Pharmaceutical Sciences ENSAMMohammed V UniversityRabat 10090Moroccoand the High School of Technology ESTCUniversity of Hassan IICasablanca 20153Morocco. High School of Technology ESTC University of Hassan IICasablanca 20153Morocco. STI Laboratory T-IDMSFaculty of Sciences and TechniquesMoulay Ismail University of MeknesErrachidia 52000Morocco. IMAGE Laboratory University of Moulay IsmailMeknes 50000Morocco.

This paper deals with detecting fetal electrocardiogram FECG signals from single-channel abdominal *** is based on the Convolutional Neural Network(CNN)combined with advanced mathematical methods,such as Independent Component Analysis(ICA),Singular Value Decomposition(SVD),and a dimension-reduction technique like Nonnegative Matrix Factorization(NMF).Due to the highly disproportionate frequency of the fetus’s heart rate compared to the mother’s,the time-scale representation clearly distinguishes the fetal electrical activity in terms of ***,we can disentangle the various components of fetal ECG,which serve as inputs to the CNN model to optimize the actual FECG signal,denoted by FECGr,which is recovered using the SVD-ICA *** findings demonstrate the efficiency of this innovative approach,which may be deployed in real-time.

关键词： Convolutional Neural Network(CNN) feature extraction Deep Learning(DL) fetal electrocardiogram

Neural Transfer Learning for Soil Liquefaction Tests New Approach to Evaluate Soil Liquefaction based on a Pre-trained Model

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Neural Transfer Learning for Soil Liquefaction Tests New App...

作者： idriss Jairi 西南石油大学

学位级别：硕士

Feature selection on probabilistic symbolic objects

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Frontiers of Computer Science 2014年第6期8卷 933-947页

作者： Djamal ziani Information Systems Department College of Computer and Information Sciences King Saud University Riyadh 11543 Saudi Arabia

In data analysis tasks, we are often confronted to very high dimensional data. Based on the purpose of a data analysis study, feature selection will find and select the relevant subset of features from the original features. Many feature selection algorithms have been proposed in classical data analysis, but very few in symbolic data analysis （SDA） which is an extension of the classical data analysis, since it uses rich objects instead to simple matrices. A symbolic object, compared to the data used in classical data analysis can describe not only individuals, but also most of the time a cluster of individuals. In this paper we present an unsupervised feature selection algorithm on probabilistic symbolic objects （PSOs）, with the purpose of discrimination. A PSO is a symbolic object that describes a cluster of individuals by modal variables using relative frequency distribution associated with each value. This paper presents new dissimilarity measures between PSOs, which are used as feature selection criteria, and explains how to reduce the complexity of the algorithm by using the discrimination matrix.

关键词： symbolic data analysis feature selection probabilistic symbolic object discrimination criteria data and knowledge visualization.

New Time-varying Fuzzy Sets Based on a PSO Midpoint of the Universe of Discourse

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International Journal of Automation and computing 2016年第4期13卷 392-400页

作者： Salim ziani Automatic and Robotics Laboratory Department of Electronics University of Constantine 1 Constantine 25000 Algeria

The paper presents a robust parallel distributed compensation （PDC） fuzzy controller for a nonlinear and certain system in continuous time described by the Tal^gi-Sugeno （T-S） fuzzy model. This controller is based on a new type of time-varying fuzzy sets （TVFS）. These fuzzy sets are characterized by displacement of the kernels to the right or left of the universe of discourse, and they are directed by a well-defined criterion. In this work, we only focused on the movement of midpoint of the universe. The movements of this midpoint are optimized by particle swarm optimization （PSO） approach.

关键词： Fuzzy sets fuzzy system membership function parallel distributed compensation (PDC) fuzzy controller particle swarmoptimization (PSO) approach linear matrix inequality (LMI).

Robust Estimators for Poisson Regression

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Open Journal of Statistics 2023年第1期13卷 112-118页

作者： idriss Abdelmajid idriss Weihu Cheng College of Applied Science Department of Statistics Beijing University of Technology Beijing China

The present paper proposes a new robust estimator for Poisson regression models. We used the weighted maximum likelihood estimators which are regarded as Mallows-type estimators. We perform a Monte Carlo simulation study to assess the performance of a suggested estimator compared to the maximum likelihood estimator and some robust methods. The result shows that, in general, all robust methods in this paper perform better than the classical maximum likelihood estimators when the model contains outliers. The proposed estimators showed the best performance compared to other robust estimators.

关键词： Poisson Regression Model Maximum Likelihood Estimator Robust Estimation Contaminated Model Weighted Maximum Likelihood Estimator