Anti‑algal activity of the 12‑5‑12 gemini surfactant results from its impact on the photosynthetic apparatus

A rapid amplification of algal population has a negative impact on the environment and the global economy. Thus, control of algal proliferation is an important issue and effective procedures which reduce algal blooms and control algal fouling are highly desired. Gemini surfactants are considered to have a low environmental impact, therefore they seem to be a promising group of detergents which could reduce algal blooms in water systems. Furthermore, due to their emulsifying properties they could replace algaecides added to antifouling paints and decrease algae adhesion to various surfaces. In this study the toxic effect of the 12-5-12 gemini surfactant was investigated on Chlorella cells and close attention was paid to a potential mechanism of its action. At the high cell density (10.05 × 107 cells/mL) a dose-dependent cell death was found and the IC50 value was reached at the concentration of 19.6 µmol/L after 72-h exposure to the surfactant. The decrease in chlorophyll autofluorescence shows that the photosynthetic apparatus seems to be the target of the tested compound. The presented studies indicate that gemini surfactants could effectively reduce algal blooms in water systems, and if added to paints, they could decrease algal growth on external building walls or other water immersed surfaces

Wastewater reuse for micro-irrigation : impact of hydrodynamic conditions and materials on biofilm development

Dans le cadre du présent travail, nous nous intéressons à l'étude de l'impact des conditions hydrodynamiques et des matériaux utilisés sur le développement de biofilm au niveau des conduites des systèmes de micro-irrigation. Cette étude contribue à l'amélioration de la compréhension de l'impact de ces paramètres dans la mise en place et la croissance du biofilm. Pour ceci, un montage expérimental aux conditions d'écoulement maîtrisées a été mis en place au laboratoire avec une eau usée modèle de forte concentration en DCO (200 mg.L-1). Le suivi des paramètres de qualité d'eau (COT et oxygène dissous) ont été réalisés au cours des expérimentations. La masse du biofilm récupéré dans les conduites a été mesurée après un séchage à l'étuve à 105°C pendant 24 heures. Les résultats montrent une cinétique de développement du biofilm dans les conduites et confirment l'influence de l'hydrodynamique sur le développement de biofilm. Trois vitesses d'écoulement ont été testées (0,4, 0,8 et 1,2 m. s-1), le biofilm a tendance à se développer dans les conduites à plus faible vitesse. Une valeur seuil, à partir de laquelle la croissance du biofilm est observée tardivement, a été également identifiée. Les résultats obtenus ont été utilisés pour paramétrer un modèle cinétique simple qui permet de décrire le développement de biofilm en fonction des conditions hydrodynamiques. D'autres expérimentations ont été réalisées en parallèle pour étudier l'impact des matériaux plastiques (PE et PVC) et la configuration des conduites du montage expérimental sur le développement de biofilm.This work aims to improve our understanding on how these parameters impact biofilm establishment and growth. For this purpose, we carried out an experiment in controlled hydrodynamic conditions using a synthetic effluent (200 mg.L-1 of COD concentration). Some water quality parameters (TOC and dissolved oxygen) were monitored . Moreover, biofilm was removed from pipes and then weighed after drying at 105°C for 24 hours. The obtained results confirmed the influence of hydrodynamic on biofilm development. Three flow rates were tested (0,4 ; 0,8 and 1,2 m.s-1) and it was observed that biofilm tends to develop in pipes at lower velocities. A threshold velocity value, from which biofilm growth was observed later, was also identified. The experimental results were used to build a simple model to describe biofilm development as a function of hydrodynamic conditions. Additionnal experiments were performed to study the impact of plastic materials (PE and PVC) and pipes configuration on biofilm growt

COMPARATIVE ANALYSIS OF DEEP LEARNING METHODS FOR PNEUMONIA DETECTION ON X-RAY IMAGES

Pneumonia is a potentially fatal bacterial illness that affects one or bothlungs in humans and is frequently caused by the bacterium Streptococcus pneumoniae.According to the World Health Organization, pneumonia accounts for one in everythree fatalities in India (WHO). Expert radiotherapists must evaluate chest X-raysused to diagnose pneumonia. Thus, establishing an autonomous method for identifyingpneumonia would be advantageous for treating the condition as soon as possible,especially in distant places. Convolutional Neural Networks (CNNs) have receiveda lot of interest for illness categorization due to the effectiveness of deep learningalgorithms in evaluating medical imagery. Furthermore, features gained by pre-trainedCNN models on large-scale datasets of X-ray pictures are extremely effective in imageclassification tasks. Several Convolutional Neural Networks were seen to categorizex-ray pictures into two groups, pneumonia and non-pneumonia, using various parameters,hyperparameters, and number of convolutional layers modified by the authors. Thestudy analyzes six different models. The first and second models each include two andthree convolutional layers. VGG16, VGG19, ResNet50 and Inception-v3 are the otherfour pre-trained models.Пневмония-бұл адамның бір немесе екі өкпесіне әсер ететін жәнекөбінесе стрептококк бактериясынан туындаған өлімге әкелетін бактериялықауру. Дүниежүзілік денсаулық сақтау ұйымының мәліметі бойынша (ДДҰ), әрбірүшіншіөлім себепшісі - пневмония. Тәжірибелі радиотерапевттер пневмонияныдиагностикалау үшін қолданылатын кеуде қуысының рентгенографиясын бағалауыкерек. Осылайша, пневмонияны анықтаудың автономды әдісін құру бұлауруды, әсіресе шалғай жерлерде ерте емдеу үшін тиімді болар еді. Конволюциялықнейрондық желілер (CNN) медициналық кескіндерді бағалау кезіндетерең оқыту алгоритмдерінің тиімділігіне байланысты ауруларды санаттарғабөлуге үлкен қызығушылық тудырды. Сонымен қатар, ауқымды рентгендікдеректержиынында алдын ала дайындалған CNN үлгілері арқылы алынғансипаттамаларкескіндерді жіктеу тапсырмаларында өте тиімді. Бірнешеконволюциялықнейрондық желі әртүрлі параметрлерді, гиперпараметрлердіжәне авторлар ұсынған конволюциялық қабаттардың санын қолдана отырып,рентген сәулелерін пневмония бар және пневмония жоқ деп екі топқа жіктейтінібайқалды. Ұсынылып отырған зерттеу пневмонияны анықтау мәселесі үшін алтытүрлі терең оқыту моделін талдайды. Бірінші және екінші модельдер әрқайсысыекі және үш конволюциялық қабаттарды қамтиды. Сонымен қатар, алдын-аламашықтандырылған VGG16, VGG19, ResNet50 және Inception-v3 модельдеріқарасырылады.Пневмония является потенциально смертельным бактериальнымзаболеванием, которое поражает одно или оба легких человека и часто вызываетсябактерией Streptococcus pneumoniae. По данным Всемирной организацииздравоохранения,на пневмонию приходится каждый третий смертельныйисход в Индии (ВОЗ). Опытные радиотерапевты должны оценивать рентгенгруднойклетки, используемый для диагностики пневмонии. Таким образом,создание автономного метода выявления пневмонии было бы выгодно дляскорейшего лечения заболевания, особенно в отдаленных районах. Сверточныенейронные сети (CNN) вызвали большой интерес для категоризации болезнейиз-за эффективности алгоритмов глубокого обучения при оценке медицинскихизображений. Кроме того, функции, полученные предварительно обученнымимоделями CNN на крупномасштабных наборах данных рентгеновских снимков,чрезвычайно эффективны в задачах классификации изображений. Было замечено,что несколько сверточных нейронных сетей классифицируют рентгеновскиеснимки на две группы, пневмонию и не пневмонию, используя различные параметры,гиперпараметры и количество сверточных слоев, модифицированныхавторами.В исследовании анализируются шесть различных моделей. Каждая изпервой и второй моделей включает в себя два и три сверточных слоя. VGG16,VGG19, ResNet50 и Inception-v3 — это четыре другие предварительно обученныемодели

Impacts of climate change and variability in the rains of the Sudan

Meeting: International Conference on CC and its Impacts on Water Resources Management in MENA Region, 2-4 Nov. 2008, Muscat, Sultanate of OmanDue to copyright restrictions, this item cannot be sharedStudies show that Sudan is facing water stress with a water availability of 1500 m3 /capita/annum. The situation is complicated due to the fact that most of the surface and ground water resources of the country are shared with the neighbouring countries. The paper recommends some adaptation measures to cope with the impacts of drought and climate change such as water harvesting, supplementary irrigation, and the use of improved irrigation techniques. Climate Change is likely to speed up the global hydrologic cycle, and lead to increased incidence of both floods and droughts

Impacts of climate change and variability in the rains of the Sudan

Meeting: International Conference on CC and its Impacts on Water Resources Management in MENA Region, 2-4 Nov. 2008, Muscat, Sultanate of OmanDue to copyright restrictions, this item cannot be sharedStudies show that Sudan is facing water stress with a water availability of 1500 m3 /capita/annum. The situation is complicated due to the fact that most of the surface and ground water resources of the country are shared with the neighbouring countries. The paper recommends some adaptation measures to cope with the impacts of drought and climate change such as water harvesting, supplementary irrigation, and the use of improved irrigation techniques. Climate Change is likely to speed up the global hydrologic cycle, and lead to increased incidence of both floods and droughts

Influences of the ENSO event on the rainfall of dry Sudan

One third of the world's population live in places where medium to high water stress is compounded by pollution, climate change, inefficient management approaches and governance issues. This study detects the El Nino Southern Oscillation (ENSO) events and signals, and the influences of the different ENSO stages in the rainfall of the dry zone in Sudan. Data from four meteorological stations were selected for analysis. Rainfall is found to be above normal during prolonged La Nina and below normal during prolonged El Nino. The ENSO event is examined in detail. Rehabilitation and establishment of new meteorological stations are crucially needed

Rainfall of the Sudan : characteristics and prediction

This journal article highlights challenges facing the water sector at the global and national levels and the impacts of rainfall variability on the environment and socioeconomic conditions of the Sudan, while outlining factors that influence rainfall distribution. The paper also reviews rainfall prediction studies that use both the El Nino Southern Oscillation (ENSO) event and global Sea Surface Temperatures (SSTs) as predictors. The use of SSTs gave satisfactory results, however a combination of forecast models is advocated to improve the quality of prediction

Effects of pipe materials on biofouling under controlled hydrodynamic conditions

International audienceExperiments were carried out to investigate pipe material impacts on biofouling, at high effluent concentration levels and under controlled hydrodynamic conditions. Two velocities (0.4 and 0.8 m s-1) were used to monitor biofilm growth on polyethylene (PE) and polyvinylchloride (PVC) pipe walls, respectively. These conditions were established based on wastewater irrigation practices. A decrease in biomass is observed after 49 days of experiments for both velocities and may be related to biofilm detachment. Biofilm growth is greater at 0.8 m s-1. For both velocities, PVC is less sensitive to biofilm growth than PE. Pipe straightness plays a primary role in biofilm growth control. This effect is more significant than pipe surface characteristics (roughness, hydrophobic/hydrophilic properties)