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In this paper, several oscillation criteria are established for some nonlinear impulsive functional parabolic equations with several delays subject to boundary conditions. We shall mainly use the divergence theorem and some corresponding impulsive delayed differential inequalities. [ABSTRACT FROM AUTHOR]

We shall establish a necessary and sufficient condition under which we have the null controllability of some first order impulsive evolution equation in a Hilbert space. [ABSTRACT FROM AUTHOR]

During the last decades, the healthcare area has increasingly relied on medical imaging for the diagnosis of a growing number of pathologies. The different types of medical images are mostly manually processed by human radiologists for diseases detection and monitoring. However, such a procedure is time-consuming and relies on expert judgment. The latter can be influenced by a variety of factors. One of the most complicated image processing tasks is image segmentation. Medical image segmentation consists of dividing the input image into a set of regions of interest, corresponding to body tissues and organs. Recently, artificial intelligence (AI) techniques brought researchers attention with their promising results for the image segmentation automation. Among AI-based techniques are those that use the Multi-Agent System (MAS) paradigm. This paper presents a comparative study of the multi-agent approaches dedicated to the segmentation of medical images, recently published in the literature., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Coastal areas are frequently influenced by direct and/or indirect multiple anthropogenic pressures, which impacts marine life. Those perturbations may act in a heterogeneous way with a different intensity and are related to the complexity of coastal ecosystems. To visualize all these interactions at a local scale, a methodology inspired from many researches has been implemented in order to search, identify, and classify coastal ecosystems according to their sensitivity to anthropic pressure exerted by coastal cities. Thus, producing vulnerability maps will be essential tools to local coastal managers. We have applied this methodology on five coastal municipalities in Algiers. Firstly, the environmental sensitivity of coastal ecosystems was assessed by analyzing these four sub-indices: biological sensitivity, geomorphological sensitivity, hydrodynamic characteristics, and pollution intensity. Secondly, an assessment of the anthropogenic pressures presented by each municipality was carried out. Five sub-indexes have been taken into consideration when conducting this assessment: human activities, infrastructures, vectors of pollution, urbanization, and regulatory protection. Then, vulnerability maps were produced by the overlapping of sensitivity and anthropic pressure maps. The results assessed for the environmental vulnerability indicated that most areas are moderately to highly vulnerable, especially in the municipalities of Bab El Oued, Rais Hamidou, and Ain Bénian. The analysis of the obtained results shows the potential applicability of this methodology because they accurately reflect the reality. Therefore, these results can be useful to decision-makers by providing them with a relatively rational decision-making tool to prioritize future management and planning efforts.

According to functional or anatomical modalities, medical imaging provides a visual representation of complex structures or activities in the human body. One of the most common processing methods applied to those images is segmentation, in which an image is divided into a set of regions of interest. Human anatomical complexity and medical image acquisition artifacts make segmentation of medical images very complex. Thus, several solutions have been proposed to automate image segmentation. However, most existing solutions use prior knowledge and/or require strong interaction with the user. In this paper, we propose a multi-agent approach for the segmentation of 3D medical images. This approach is based on a set of autonomous, interactive agents that use a modified region growing algorithm and cooperate to segment a 3D image. The first organization of agents allows region seed placement and region growing. In a second organization, agent interaction and collaboration allow segmentation refinement by merging the over-segmented regions. Experiments are conducted on magnetic resonance images of healthy and pathological brains. The obtained results are promising and demonstrate the efficiency of our method., (Copyright © 2020 Elsevier B.V. All rights reserved.)

This paper introduces a new cooperative multi-agent approach for segmenting brain Magnetic Resonance Images (MRIs). MRIs are manually processed by human radiology experts for the identification of many diseases and the monitoring of their evolution. However, such a task is time-consuming and depends on expert decision, which can be affected by many factors. Therefore, various types of research were and are still conducted to automate MRI processing, mainly MRI segmentation. The approach presented in this paper, without any parametrization or prior knowledge, uses a set of situated agents, locally interacting to segment images according to two main phases: the detection of discontinuities and the detection of similarities. An implementation of this approach was tested on phantom brain MR images to assess the results and prove its efficiency. Experimental results ensure a minimum of 89% Dice coefficient with increasing values of the noise and the intensity non-uniformity.

Background: Behavioral and psychological symptoms in dementia (BPSD) are a major concern. The French government gave a consensual definition of reinforced intermediate-term care units for BPSD within the project "Plan Alzheimer 2008/2012"., Objective: Our aim was to report one of the first experiences of this unit in France., Results: Fifty-two patients (38 females, 14 males) were included, mean age 82.07±7.84 (73-97). About 80% of patients were improved and there was a high discharge rate to home of about 30%. Night-time behaviors, aberrant motor behaviors and agitation were the most frequent symptoms., Conclusion: Our study confirms that demented elderly patients greatly benefit from a specific BPSD care unit in agreement with the objective of Plan Alzheimer 2008/2012., (Copyright © 2010 Elsevier Masson SAS. All rights reserved.)