Integration of Mechatronics Design Approach into Teaching of Modeling Practices

Engineering design has transformed significantly due to advances in embedded system design and computer technologies. Almost every mechanical design today has some electrical and electronic components. Many products manufactured today contain both electrical and mechanical components and systems. Mechatronics is a design process that is multi-disciplinary in nature and integrates principles of many engineering disciplines including, but not limited to, mechanical engineering and mechanical engineering technology, electrical engineering and electrical engineering technology, and controls engineering. Mechatronic systems can be found in many different places today. These range from computer hard drives and robotic assembly systems, to washing machines, coffee makers, printers, and medical devices, as well as to various advanced manufacturing machines and devices that are numerically controlled, such as additive manufacturing machines, rapid prototyping machines and multi-axis CNC machines. The main purpose for integrating a mechatronics themed activity into a computer-modeling course is to engage students in project-based learning through hands-on activities related to modeling a mechatronic device. Students learn the basics of electromechanical systems, the integration of machine elements (gear reducer) and the basics of actuators (electrical motor), all of which are fundamental to understanding mechatronic systems through activities related to the mechatronic design principles. Hence, engineering design for mechanical engineers and mechanical engineering technologists have to involve embedded multi-disciplinary knowledge with the understanding of both mechanical and electrical systems. This paper will focus on presenting the use of modeling as a vehicle to teaching more complex engineering concepts, such as gears, linkage analysis, animation and the solid modelling course content

Impairments in reinforcement learning do not explain enhanced habit formation in cocaine use disorder

Abstract: Rationale: Drug addiction has been suggested to develop through drug-induced changes in learning and memory processes. Whilst the initiation of drug use is typically goal-directed and hedonically motivated, over time, drug-taking may develop into a stimulus-driven habit, characterised by persistent use of the drug irrespective of the consequences. Converging lines of evidence suggest that stimulant drugs facilitate the transition of goal-directed into habitual drug-taking, but their contribution to goal-directed learning is less clear. Computational modelling may provide an elegant means for elucidating changes during instrumental learning that may explain enhanced habit formation. Objectives: We used formal reinforcement learning algorithms to deconstruct the process of appetitive instrumental learning and to explore potential associations between goal-directed and habitual actions in patients with cocaine use disorder (CUD). Methods: We re-analysed appetitive instrumental learning data in 55 healthy control volunteers and 70 CUD patients by applying a reinforcement learning model within a hierarchical Bayesian framework. We used a regression model to determine the influence of learning parameters and variations in brain structure on subsequent habit formation. Results: Poor instrumental learning performance in CUD patients was largely determined by difficulties with learning from feedback, as reflected by a significantly reduced learning rate. Subsequent formation of habitual response patterns was partly explained by group status and individual variation in reinforcement sensitivity. White matter integrity within goal-directed networks was only associated with performance parameters in controls but not in CUD patients. Conclusions: Our data indicate that impairments in reinforcement learning are insufficient to account for enhanced habitual responding in CUD

Understanding Greenland ice sheet hydrology using an integrated multi-scale approach

Improved understanding of Greenland ice sheet hydrology is critically important for assessing its impact on current and future ice sheet dynamics and global sea level rise. This has motivated the collection and integration of in situ observations, model development, and remote sensing efforts to quantify meltwater production, as well as its phase changes, transport, and export. Particularly urgent is a better understanding of albedo feedbacks leading to enhanced surface melt, potential positive feedbacks between ice sheet hydrology and dynamics, and meltwater retention in firn. These processes are not isolated, but must be understood as part of a continuum of processes within an integrated system. This letter describes a systems approach to the study of Greenland ice sheet hydrology, emphasizing component interconnections and feedbacks, and highlighting research and observational needs

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed

Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer.

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of preexisting subclones, remains unclear. In epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires Aurora kinase A (AURKA) activity. Nongenetic resistance through the activation of AURKA by its coactivator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in preclinical models. Treatment-induced activation of AURKA is associated with resistance to EGFR inhibitors in vitro, in vivo and in most individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a molecular path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA-driven residual disease and acquired resistance

Single-cell sequencing of iPSC-Dopamine neurons reconstructs disease progression and identifies HDAC4 as a regulator of Parkinson cell phenotypes

Induced pluripotent stem cell (iPSC)-derived dopamine neurons provide an opportunity to model Parkinson’s disease (PD), but neuronal cultures are confounded by asynchronous and heterogeneous appearance of disease phenotypes in vitro. Using high-resolution, single-cell transcriptomic analyses of iPSC-derived dopamine neurons carrying the GBA-N370S PD risk variant, we identified a progressive axis of gene expression variation leading to endoplasmic reticulum stress. Pseudotime analysis of genes differentially expressed (DE) along this axis identified the transcriptional repressor histone deacetylase 4 (HDAC4) as an upstream regulator of disease progression. HDAC4 was mislocalized to the nucleus in PD iPSC-derived dopamine neurons and repressed genes early in the disease axis, leading to late deficits in protein homeostasis. Treatment of iPSC-derived dopamine neurons with HDAC4-modulating compounds upregulated genes early in the DE axis and corrected PD-related cellular phenotypes. Our study demonstrates how single-cell transcriptomics can exploit cellular heterogeneity to reveal disease mechanisms and identify therapeutic targets

Neuraminidase-deficient Sendai virus HN mutants provide protection from homologous superinfection

Binding of hemagglutinin-neuraminidase proteins (HN) to sialylated receptors initiates the infection process of several paramyxoviruses, whereas later in the viral life cycle, the neuramindase (NA) activity of newly synthesized HN destroys all receptors. Prior to NA action, expressed HN has to bind the receptor. To evaluate this HN–receptor complex with respect to receptor inactivation, three temperature-sensitive Sendai virus HN mutants carrying amino acid exchanges at positions 262, 264 and/or 461 were created that uncoupled NA activity from receptor binding at 39°C. Interestingly, at elevated temperature, when there is no detectable neuramindase activity, all infected cells are protected against homologous superinfection. Mutated HN protein on the cell surface is mainly bound to sialylated cell-surface components but can be released by treatment with NA. Thus, continuous binding to HN already inactivates the receptors quantitatively. Furthermore, mutant HN bound to receptors is prevented from being incorporated into virus particles in the absence of NA. It is shown here for the first time that during paramyxoviral infection, quantitative receptor inactivation already occurs due to binding of receptors to expressed HN protein without involvement of NA and is independent of NA activity of viral progeny. NA subsequently functions in the release of HN from the complex, coupled with desialysation of receptors. These findings could have implications for further antiviral drug development

The 10th Biennial Hatter Cardiovascular Institute workshop: cellular protection—evaluating new directions in the setting of myocardial infarction, ischaemic stroke, and cardio-oncology

Due to its poor capacity for regeneration, the heart is particularly sensitive to the loss of contractile cardiomyocytes. The onslaught of damage caused by ischaemia and reperfusion, occurring during an acute myocardial infarction and the subsequent reperfusion therapy, can wipe out upwards of a billion cardiomyocytes. A similar program of cell death can cause the irreversible loss of neurons in ischaemic stroke. Similar pathways of lethal cell injury can contribute to other pathologies such as left ventricular dysfunction and heart failure caused by cancer therapy. Consequently, strategies designed to protect the heart from lethal cell injury have the potential to be applicable across all three pathologies. The investigators meeting at the 10th Hatter Cardiovascular Institute workshop examined the parallels between ST-segment elevation myocardial infarction (STEMI), ischaemic stroke, and other pathologies that cause the loss of cardiomyocytes including cancer therapeutic cardiotoxicity. They examined the prospects for protection by remote ischaemic conditioning (RIC) in each scenario, and evaluated impasses and novel opportunities for cellular protection, with the future landscape for RIC in the clinical setting to be determined by the outcome of the large ERIC-PPCI/CONDI2 study. It was agreed that the way forward must include measures to improve experimental methodologies, such that they better reflect the clinical scenario and to judiciously select combinations of therapies targeting specific pathways of cellular death and injury