Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results.

The prevalence of project-based learning (PBL) has increased significantly, contributing to serious discussions about its advent. PBL’s critics doubt whether accentuating the practice supports teachers in using a technocratic method in education, instead of promoting instruction that is responsive to students’ ideas. Thus, this study aims to develop on using the effectiveness of the PBL approach, as a way to engage students in learning as well as to incorporate literature on the PBL method for educational purposes. The research hypotheses therefore measure the influence of the PBL method on collaborative learning, disciplinary subject learning, iterative learning, and authentic learning, which, in turn, engage students in learning. To achieve the research purpose, a questionnaire was employed as the main method of collecting data and dispensed to 124 teachers who were using the PBL approach. Structural equation modeling (SEM), a quantitative research method, was employed to obtain the findings. A significant relation was found between the PBL method and collaborative learning, disciplinary subject learning, iterative learning, and authentic learning, which, in turn, produced student engagement. The results show that the PBL technique improves student engagement by enabling knowledge and information sharing and discussion. Thus, the PBL approach is highly recommended for educational use by students and should be encouraged in universities.

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BackgroundFamilial breast cancer (BC) represents 5 to 10% of all BC cases. Mutations in two high susceptibility BRCA1 and BRCA2 genes explain 16–40% of familial BC, while other high, moderate and low susceptibility genes explain up to 20% more of BC families. The Lebanese reported prevalence of BRCA1 and BRCA2 deleterious mutations (5.6% and 12.5%) were lower than those reported in the literature.MethodsIn the presented study, 45 Lebanese patients with a reported family history of BC were tested using Whole Exome Sequencing (WES) technique followed by Sanger sequencing validation.ResultsNineteen pathogenic mutations were identified in this study. These 19 mutations were found in 13 different genes such as: ABCC12, APC, ATM, BRCA1, BRCA2, CDH1, ERCC6, MSH2, POLH, PRF1, SLX4, STK11 and TP53.ConclusionsIn this first application of WES on BC in Lebanon, we detected six BRCA1 and BRCA2 deleterious mutations in seven patients, with a total prevalence of 15.5%, a figure that is lower than those reported in the Western literature. The p.C44F mutation in the BRCA1 gene appeared twice in this study, suggesting a founder effect. Importantly, the overall mutation prevalence was equal to 40%, justifying the urgent need to deploy WES for the identification of genetic variants responsible for familial BC in the Lebanese population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-017-0244-7) contains supplementary material, which is available to authorized users.