Hydraulic Fracture Propagation in Pre-structured Media: Stress Field and Fracture Network Topology - Adrian V. Garcia; Rached M. Rached; Carlos D. Rodriguez-Hernandez; J. Carlos Santamarina (Rock Mechanics and Rock Engineering, 2026)

Effects of Phosphate-rock Mining Wastewater Fertigation on Chickpea (Cicer arietinum) Cultivation and Soil Microbial Diversity - Hammami Imran; Ferchichi Nouha; Toukebri Wael; M.’sehli Wissal; Ben Hammouda Thouraya; Ajengui Arwa; Guiga Cyrine; Salhi Hanen; Ben Hassen Rached; Trabelsi Darine (International Journal of Environmental Research, 2025)

Bio-nanoremediation of olive oil mill wastewater by Alternaria alternata fungi coupled with Ag-doped TiO2 nanoparticles and its use as biofertilizer for cereal crops - Mouna Messaoud; Rached Salhi; Narjes Baazaoui; Sofiene B. M. Hammami; Ameni Ezzine; Rania Mosbeh; Ridha Elleuch; Sonia Labidi; Karim Ounallah; Asma Maazoun; Ali A. Shati; Mohammad Alfaifi; et al. (Euro-Mediterranean Journal for Environmental Integration, 2024)

A numerical study on the impact of thermal alterations in porous media during hot fluid injection process employing a modified Boussinesq model - Abiola D. Obembe; M. Enamul Hossain; Ben-Mansour Rached (Computational Geosciences, 2018)

Genomic resources and their influence on the detection of the signal of positive selection in genome scans - S. Manel; C. Perrier; M. Pratlong; L. Abi‐Rached; J. Paganini; P. Pontarotti; D. Aurelle (Molecular Ecology, 2016)
Genome scans represent powerful approaches to investigate the action of natural selection on the genetic variation of natural populations and to better understand local adaptation. This is very useful, for example, in the field of conservation biology and evolutionary biology. Thanks to Next Generation Sequencing, genomic resources are growing exponentially, improving genome scan analyses in non‐model species. Thousands of SNP s called using Reduced Representation Sequencing are increasingly used in genome scans. Besides, genome sequences are also becoming increasingly available, allowing better processing of short‐read data, offering physical localization of variants, and improving haplotype reconstruction and data imputation. Ultimately, genome sequences are also becoming the raw material for selection inferences. Here, we discuss how the increasing availability of such genomic resources, notably genome sequences, influences the detection of signals of selection. Mainly, increasing data density and having the information of physical linkage data expand genome scans by (i) improving the overall quality of the data, (ii) helping the reconstruction of demographic history for the population studied to decrease false‐positive rates and (iii) improving the statistical power of methods to detect the signal of selection. Of particular importance, the availability of a high‐quality reference genome can improve the detection of the signal of selection by (i) allowing matching the potential candidate loci to linked coding regions under selection, (ii) rapidly moving the investigation to the gene and function and (iii) ensuring that the highly variable regions of the genomes that include functional genes are also investigated. For all those reasons, using reference genomes in genome scan analyses is highly recommended.

International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes - Anna Bal-Price; Kevin M. Crofton; Marcel Leist; Sandra Allen; Michael Arand; Timo Buetler; Nathalie Delrue; Rex E. FitzGerald; Thomas Hartung; Tuula Heinonen; Helena Hogberg; Susanne Hougaard Bennekou; et al. (Archives of Toxicology, 2015)

Comparative study of pikeperch Sander lucioperca (Percidae; Linnaeus, 1758) eggs and larvae from wild females or from captive females fed chopped marine fish - I. Ben Khemis; N. Hamza; N. Ben Messaoud; S. Ben Rached; M. M’Hetli (Fish Physiology and Biochemistry, 2014)

Natural variation at position 45 in the D1 domain of lineage III killer cell immunoglobulin-like receptors (KIR) has major effects on the avidity and specificity for MHC class I - Anastazia M. Older Aguilar; Lisbeth A. Guethlein; Laurent Abi-Rached; Peter Parham (Immunogenetics, 2011)