Computer simulation of flow and mixing at the duodenal stump after gastric resection

AIM: To investigate the flow and mixing at the duodenal stump after gastric resection, a computer simulation was implemented

3D Modeling of Plaque Progression in the Human Coronary Artery

The inflammation and lipid accumulation in the arterial wall represents a progressive disease known as atherosclerosis. In this study, a numerical model of atherosclerosis progression was developed. The wall shear stress (WSS) and blood analysis data have a big influence on the development of this disease. The real geometry of patients, and the blood analysis data (cholesterol, HDL, LDL, and triglycerides), used in this paper, was obtained within the H2020 SMARTool project. Fluid domain (blood) was modeled using Navier-Stokes equations in conjunction with continuity equation, while the solid domain (arterial wall) was modeled using Darcy’s law. For the purpose of modeling low-density lipoprotein (LDL) and oxygen transport, convection-diffusion equations were used. Kedem-Katchalsky equations were used for coupling fluid and solid dynamics

Mapping cyclic stretch in the postpneumonectomy murine lung

In many mammalian species, the removal of one lung [pneumonectomy (PNX)] is associated with the compensatory growth of the remaining lung. To investigate the hypothesis that parenchymal deformation may trigger lung regeneration, we used respiratorygated micro-computed tomography scanning to create threedimensional finite-element geometric models of the murine cardiac lobe with cyclic breathing. Models were constructed of respiratorygated micro-computed tomography scans pre-PNX and 24 h post- PNX. The computational models demonstrated that the maximum stretch ratio map was patchy and heterogeneous, particularly in subpleural, juxta-diaphragmatic, and cephalad regions of the lobe. In these parenchymal regions, the material line segments at peak inspiration were frequently two- to fourfold greater after PNX; some regions of the post-PNX cardiac lobe demonstrated parenchymal compression at peak inspiration. Similarly, analyses of parenchymal maximum shear strain demonstrated heterogeneous regions of mechanical stress with focal regions demonstrating a threefold increase in shear strain after PNX. Consistent with previously identified growth patterns, these subpleural regions of enhanced stretch and shear strain are compatible with a mechanical signal, likely involving cyclic parenchymal stretch, triggering lung growth. Copyright © 2013 the American Physiological Society

Experimental Analysis of Handcart Pushing and Pulling Safety in an Industrial Environment by Using IoT Force and EMG Sensors: Relationship with Operators’ Psychological Status and Pain Syndromes

Non-ergonomic execution of repetitive physical tasks represents a major cause of work-related musculoskeletal disorders (WMSD). This study was focused on the pushing and pulling (P&P) of an industrial handcart (which is a generic physical task present across many industries), with the aim to investigate the dependence of P&P execution on the operators’ psychological status and the presence of pain syndromes of the upper limbs and spine. The developed acquisition system integrated two three-axis force sensors (placed on the left and right arm) and six electromyography (EMG) electrodes (placed on the chest, back, and hand flexor muscles). The conducted experiment involved two groups of participants (with and without increased psychological scores and pain syndromes). Ten force parameters (for both left and right side), one EMG parameter (for three different muscles, both left and right side), and two time-domain parameters were extracted from the acquired signals. Data analysis showed intergroup differences in the examined parameters, especially in force integral values and EMG mean absolute values. To the best of our knowledge, this is the first study that evaluated the composite effects of pain syndromes, spine mobility, and psychological status of the participants on the execution of P&P tasks—concluding that they have a significant impact on the P&P task execution and potentially on the risk of WMSD. The future work will be directed towards the development of a personalized risk assessment system by considering more muscle groups, supplementary data derived from operators’ poses (extracted with computer vision algorithms), and cognitive parameters (extracted with EEG sensors)