Tunis University

About: Tunis University is a education organization based out in Tunis, Tunisia. It is known for research contribution in the topics: Population & Thin film. The organization has 11745 authors who have published 15400 publications receiving 154900 citations. The organization is also known as: University of Tunis & UT.

On the Use of Machine Learning and Search-Based Software Engineering for Ill-Defined Fitness Function: A Case Study on Software Refactoring

Abstract: The most challenging step when adapting a search-based technique for a software engineering problem is the definition of the fitness function. For several software engineering problems, a fitness function is ill-defined, subjective, or difficult to quantify. For example, the evaluation of a software design is subjective. This paper introduces the use of a neural network-based fitness function for the problem of software refactoring. The software engineers evaluate manually the suggested refactoring solutions by a Genetic Algorithm (GA) for few iterations then an Artificial Neural Network (ANN) uses these training examples to evaluate the refactoring solutions for the remaining iterations. We evaluate the efficiency of our approach using six different open-source systems through an empirical study and compare the performance of our technique with several existing refactoring studies.

Alarming coastal vulnerability of the deltaic and sandy beaches of North Africa.

Abstract: The arid coasts of North Africa, extending over 4633 km from the Gulf of Tunis to the Nile Delta, are undergoing pronounced shoreline retreats and coastal floodings that are reported as a consequence of the ongoing sea level rise resulting from global warming. Of particular interest are the abnormal shoreline dynamics for deltaic and sandy beaches, which are severely impacted by abrupt decadal variabilities in both climatic and anthropogenic drivers resulting in their increased vulnerability to disturbances from coastal hazards. Unfortunately, the evolution, distribution and impacts of these drivers remain largely unquantified, let alone understood, for these extensive arid coasts that harbor the major portion of North Africa’s population as well as unique and fragile marine ecosystems. To address this deficiency, we use GIS-based multi-criteria approaches combined with analytic hierarchy process to map the Coastal Vulnerability Index and the Socioeconomic Vulnerability Index along these coasts to investigate the amplitude and extent of shoreline deterioration resulting from sudden fluctuations in sediment transport to the coastline. We use the western bay of the Gulf of Tunis, the coasts of Tripoli and the Nile Delta as three validation sites for our vulnerability assessment. The statistical Integrated Coastal Vulnerability Index map reveals that 47% of arid North African coasts are characterized by high to very high vulnerability. In particular, we observe that the densely populated deltaic coasts in both Tunisia and Egypt are 70% more vulnerable than any others coast in the eastern Mediterranean Basin. These abnormally high-vulnerability extensive areas are also correlated with significant deterioration of coastal aquifers and hence in crop production, compromising local food security and resulting in increasing outflow migration trends. Both Tunisia and Egypt observed dramatic increases in the net population outflow migration by respectively 62% and 248% between 2000 and 2016, mostly from coastal areas. Our source analysis of the amplitude and extent of these high coastal vulnerabilities suggests that they result from the anthropogenic drivers of damming and rapid urban growth over the last few decades rather than the effects of global warming.

Dispersal of linezolid-resistant enterococci carrying poxtA or optrA in retail meat and food-producing animals from Tunisia.

Abstract: Objectives The epidemiology of Enterococcus resistant to priority antibiotics including linezolid has mainly been investigated in developed countries and especially in hospitals. We aimed to evaluate the contribution of different non-human reservoirs for the burden of MDR enterococci in Tunisia, where scarce data are available. Methods Samples (n = 287) were collected from urban wastewater (n = 57), retail meat (n = 29; poultry/bovine/ovine), milk (n = 89; bovine/ovine), farm animal faeces (n = 80; poultry/bovine/ovine) and pets (n = 32; rabbit/dogs/cats/birds) in different Tunisian regions (2014-17). They were plated onto Slanetz-Bartley agar after pre-enrichment without antibiotics. Standard methods were used for bacterial identification and characterization of antibiotic resistance and virulence genes (PCR), antibiotic susceptibility testing (disc diffusion/broth microdilution; EUCAST/CLSI) and clonality (SmaI-PFGE/MLST). Results All samples carried Enterococcus (n = 377 isolates) resistant to antibiotics considered to be critical or highly important by WHO. Even without antibiotic selection, 38% of Enterococcus faecalis (Efs) and 22% of Enterococcus faecium (Efm) were identified as MDR. Linezolid-resistant isolates (5%; MIC = 8 mg/L) comprised six poxtA-carrying Efm (cow milk), seven optrA-carrying Efs (chicken faeces/meat) and five Efm lacking cfr/optrA/poxtA (poultry/bovine/ovine/wastewater). Clinically relevant Efm clones (clade A1) were identified in animal/meat sources. Ampicillin resistance (1%) was confined to ST18/ST78-like MDR Efm clones from bovine meat/milk samples carrying relevant virulence markers (e.g. ptsD/IS16). Conclusions This study provides evidence of the contribution of livestock and foodstuffs to the dispersal of acquired linezolid resistance genes including poxtA and optrA. We report the first poxtA-carrying Efm in Tunisia, and for the first time in bovine samples, stressing the urgent need for alternative measures to counteract the spread of linezolid-resistant enterococci globally.