Epiconvergence of a Sequence of Level Sums of Convex Functions

We consider the problem of minimizing the max of two convex functions from both approximation and sensitivity point of view.This lead up to study the epiconvergence of a sequence of level sums of convex functions and the related dual problems

Infection par le VIH chez les patientes atteintes de cancer du sein en Guinée (Afrique de l’Ouest)

L'objectif était de déterminer la prévalence de l'infection à VIH chez les patientes atteintes de cancer du sein et de comparer les caractéristiques anatomocliques et thérapeutiques de ces cancers du sein par rapports aux patientes non infectées par le VIH. Il s'agissait d'une étude rétrospective et analytique comparant les dossiers de patientes atteintes de cancers du sein histologiquement confirmés, infectées ou non par le VIH à l'unité de chirurgie oncologique de Donka, CHU de Conakry, de 2007 à 2012. Nous avons colligé 278 patientes présentant un cancer du sein dont 14 (5,0%) infectées par le VIH et 264 (95,0%) non infectées par le VIH. Les différences observées entre ces deux groupes de patientes étaient respectivement: âge médian (36,8 vs 49,0 ans), la ménopause (21,4% vs 53,4%), le nombre des patientes traitées (50,0% contre 77,1%) et la survenue de décès (78,6% vs 50,8%). Aucune différence n'a été notée dans la présentation clinique, histologique et le retard de consultation. Dans notre étude, la prévalence de l'infection à VIH chez les patients atteints de cancer du sein est élevée. L'âge jeune des patients, la faible accessibilité au traitement et la mortalité élevée doivent être confirmés par une étude sur un échantillon plus large

Influence des herbicides sur l'infestation par les adventices, la densité et la matière sèche des blés tendres (Triticum aestivum L.) et durs (Triticum durum Desf.).

Objectif: L’objectif de cette étude est d’évaluer les effets de la combinaison des herbicides 2,4-D®-sel d’amine + Lontrel® et du Quartz- super® (diflufénicanil-50 g/l+isoproturon-500 g/l) sur l’évolution de la flore adventice, sa densité et biomasse ainsi que la formation de matière sèche des variétés de blés tendres et durs d’écologies différentes dans la région de Moscou.Méthodologie et résultats : Le dispositif expérimental utilisé est un Split plot à quatre répétitions comprenant chacune un témoin (sans herbicide) et trois traitements herbicides : le Quartz- super (dose 1,0 l ha-1 m.a.) appliqué deux jours après semis et au tallage des blés, la combinaison 2,4-D (dose 1,8 kg ha-1 m.a.) + Lontrel (dose 0,3 kg ha-1 m a.) utilisée seulement au tallage. Les analyses de variance et de Hierarchical Column Prime Order (HCPO) ont été effectuées avec le logiciel Minitab 13.0 pour une comparaison des moyennes. Les résultats ont montré la présence de 18 espèces toutes dicotylédones appartenant à 10 familles botaniques qui sont regroupées en 03 groupes biologiques. Parmi celles–ci, 08 espèces (44,4%) sont annuelles de levée précoce et apparaissent très tôt au printemps, début du cycle végétatif des blés ; 09 (50%) sont des espèces facultatives de levée tardive en milieu du cycle de végétation des blés ou très souvent plus tardivement en fin été. Seule une espèce éphémère (5,6%) a été enregistrée au cours de l’étude. Les espèces facultatives tardives de l’été ont prédominé aussi bien par leur densité que par la matière sèche au cours de l’étude.Conclusion et application des résultats : L’herbicide Quartz-super en pré-levée s’est montré plus efficace avec une élimination de 81,7%-85,2% des adventices pour 29,6%-30,9% de matière sèche enregistrée à la récolte. Aucune différence significative n’a été observée entre les blés pour les densités enregistrées à maturité (81,7%- 84,5%). La matière sèche augmentait en moyenne de 8,7%-11% (Lyba), 14,8%-18,7% (Scham-2), 7,7%-8,5% (Bykhys-1) et Homari-9,6% -12%. L’étude recommande le 2,4-D + Lontrel ou le Quartz-super au tallage des blés lorsque des adventices de levée précoce sont prédominants. Au contraire, en présence d’adventices de levée tardive, de meilleurs résultats sont obtenus avec le Quartz super appliqué en pré-levée au deuxième jour des semis.Mots clés : blés, herbicides, densité, matière sèche.

GR-40 Design and Implementation of a Microservices Web-based Architecture for Code Deployment and Testing

Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing IoT technologies. Since the IoT industry has exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job market. That can be done by using containerization. There are many approaches in the containerization field, but they can be difficult to use without depth knowledge in virtualization and code encapsulation. After a deep analysis of the containerization challenges, we came with an idea of a microservice infrastructure based on Docker, which is an open- platform for developing, testing, and running applications using containers, to solve the virtualization and code-encapsulation problem. Our infrastructure will provide a code development and testing web-based platform that allows users to securely go in the process of containerization without spending research time in learning virtualization. So, students and researchers can focus more on the development and testing of algorithms and codes. For example, it will be easy to develop containers that allow sensors to connect to an external server in few cliques, or to run a python code in a total isolate process in minutes without downloading any containerization software.Advisors(s): Dr. Maria Valero [email protected] Dr Hossain Shahriar [email protected](s): IoT/Cloud/Networkin

Understanding soil fertility management under cereal cropping systems in southern Mali

For decades, Malian stakeholders, including farm households and scientists, have increasingly recognized soil-nutrient depletion as one of the major constraints to sustainable agricultural development. Farming systems in the country are diverse due to variations in climate, soils, and production goals. Many complex factors influence the level of soil nutrient depletion and include nutrient management, regeneration and plant protection, livestock integration, soil and water conservation, biodiversity, agricultural policies, and marketing structures. Farm households are confronted with declining price relations between farm inputs and outputs resulting in a net exploitation of soil nutrients. Due to prevailing poverty, farm households have limited options for investment in nutrient adding or nutrient saving technologies. Nowadays, this situation is worsening due to climate change and variability. Climate smart technologies such as using organic manure and micro dosing have been implemented by various actors to address soil nutrient depletion and the effects of climate change, but questions about the sustainability of this system remain. In this progress report we explore farm characterization for understanding the management strategies regarding soil fertility. This activity is the first of a series of four monitoring steps for assessing nutrient flow at farm scale in the Koutiala District of southern Mali

Secure Cloud-based IoT Water Quality Gathering for Analysis and Visualization

Water quality refers to measurable water characteristics, including chemical, biological, physical, and radiological characteristics usually relative to human needs. Dumping waste and untreated sewage are the reasons for water pollution and several diseases to the living hood. The quality of water can also have a significant impact on animals and plant ecosystems. Therefore, keeping track of water quality is a substantial national interest. Much research has been done for measuring water quality using sensors to prevent water pollution. In summary, those systems are built based on online and reagent-free water monitoring SCADA systems in wired networks. However, centralized servers, transmission protocols, and data access can present challenges and disadvantages for those systems. This paper proposes a secure Cloud-based IoT water quality gathering architecture for water quality analysis and visualization to address the limitations of the current systems. The proposed architecture will send, analyze and visualize water quality data in the Cloud by utilizing specialized sensors and IoT-based gateways to capture water measurements (Dioxygen concentration, and temperature, among others). Then, they communicate securely to the Cloud-based server through a high-speed wireless network. We evaluated the performance of the proposed framework on a process-oriented approach to success metrics for cyberinfrastructures. The experiments were conducted in a laboratory and focused on network security and resiliency, the IoT prototype performance in dropping real-time data transmission, and remote access. The results demonstrate higher data collection and transmission effectiveness with minimal data loss and low energy usage over time. The accompanying cloud-based platform provided the flexibility needed for water quality monitoring and laboratory studies

GR-182 - IoT Clusters Platform for Data Collection, Analysis, and Visualization Use Case

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season\u27s unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part of the world. Since we have completed the first part, we are implementing a study case for a field used by the platform. Thus, we are implementing an environment monitoring technology base on weather data. For this study, the platform will collect real-time environmental data using sensors (Temperature, humidity, light and ultraviolet sensors, and other sensors). We are setting those sensors in relatively limited superficies due to resources problem. Next, we will use this data to find patterns in weather changes using Machine and Deep learning techniques since these environmental data come from a designated area. The main objective of this part is to find a weather pattern using collected data specific to this area. Data collected during this research and the IoT platform are available on campus for students to use for their class projects or future research. Currently, we are in the data collection process. We also evaluate the degradation and environmental effects on devices and sensors used. This study case is a needed step in the IoT Clusters Platform for Data Collection, Analysis, and Visualization research project. At the end of the project, the data collection framework will be efficient and cost less