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Online engineering practice is offering nowadays new potentials for training of measurement technologies and experimental procedures. In a laboratory mainly devoted to Instrumentation for Measurement by hands-on activity in engineering fields, students and engineering professionals are using, at present, online experiments in a blended-learning approach. A set of experiments has been designed and developed as well as some virtual simulators. The experiments integrated in a Moodle platform are using a web-server system based on LabVIEW 7.1, linked to them by data acquisition interface cards, a video server, and a booking system developed as an extension of the Moodle platform. This paper reports a particular setup specially designed for remotely measuring and determining mechanical material properties and its combination with the design of a highly interactive user interface. The user may remotely conduct the experiment, getting numerical, graphical, and live video output information and receiving e-mailed experimental results. [ABSTRACT FROM AUTHOR]

Background: Handgrip strength (HGS) is a marker of nutrition status. Many factors are associated with HGS. Age, height, body mass index, number of diagnoses, and number and type of drugs have been shown to modify the association between undernutrition and HGS. Nevertheless, other patient characteristics that could modify this association and its joint modifier effect have not been studied yet., Objective: To evaluate the association of inpatients' HGS and undernutrition considering the potential modifier effect of cognitive status, functional activity, disease severity, anthropometrics, and other patient characteristics on HGS., Methods: A cross-sectional study was conducted in a university hospital. Sex, age, abbreviated mental test score, functional activity score, Charlson index, number of drugs, Patient-Generated Subjective Global Assessment (PG-SGA) score, body weight, mid-arm muscle circumference, adductor pollicis muscle thickness, body height, wrist circumference, hand length, and palm width were included in a linear regression model to identify independent factors associated with HGS (dependent variable)., Results: The study sample was composed of 688 inpatients (18-91 years old). All variables included in the model were associated with HGS (β, -0.16 to 0.38; P ≤ .049) and explained 68.5% of HGS. Age, functional activity decline, Charlson index, number of drugs, PG-SGA score, body weight, and wrist circumference had a negative association with HGS. All other studied variables were positively associated with HGS., Conclusion: Nutrition status evaluated by PG-SGA was still associated with HGS after considering the joint effect of other patient characteristics, which reinforces the value of HGS as an indicator of undernutrition., (© 2013 American Society for Parenteral and Enteral Nutrition.)