Multifaceted Mechanisms of Action of Metformin Which Have Been Unraveled One after Another in the Long History

While there are various kinds of drugs for type 2 diabetes mellitus at present, in this review article, we focus on metformin which is an insulin sensitizer and is often used as a first-choice drug worldwide. Metformin mainly activates adenosine monophosphate-activated protein kinase (AMPK) in the liver which leads to suppression of fatty acid synthesis and gluconeogenesis. Metformin activates AMPK in skeletal muscle as well, which increases translocation of glucose transporter 4 to the cell membrane and thereby increases glucose uptake. Further, metformin suppresses glucagon signaling in the liver by suppressing adenylate cyclase which leads to suppression of gluconeogenesis. In addition, metformin reduces autophagy failure observed in pancreatic β-cells under diabetic conditions. Furthermore, it is known that metformin alters the gut microbiome and facilitates the transport of glucose from the circulation into excrement. It is also known that metformin reduces food intake and lowers body weight by increasing circulating levels of the peptide hormone growth/differentiation factor 15 (GDF15). Furthermore, much attention has been drawn to the fact that the frequency of various cancers is lower in subjects taking metformin. Metformin suppresses the mechanistic target of rapamycin (mTOR) by activating AMPK in pre-neoplastic cells, which leads to suppression of cell growth and an increase in apoptosis in pre-neoplastic cells. It has been shown recently that metformin consumption potentially influences the mortality in patients with type 2 diabetes mellitus and coronavirus infectious disease (COVID-19). Taken together, metformin is an old drug, but multifaceted mechanisms of action of metformin have been unraveled one after another in its long history.     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.     

Dynamic probe of ZnTe(110) surface by scanning tunneling microscopy

The reconstructed surface structure of the II–VI semiconductor ZnTe (110), which is a promising material in the research field of semiconductor spintronics, was studied by scanning tunneling microscopy/spectroscopy (STM/STS). First, the surface states formed by reconstruction by the charge transfer of dangling bond electrons from cationic Zn to anionic Te atoms, which are similar to those of IV and III–V semiconductors, were confirmed in real space. Secondly, oscillation in tunneling current between binary states, which is considered to reflect a conformational change in the topmost Zn–Te structure between the reconstructed and bulk-like ideal structures, was directly observed by STM. Third, using the technique of charge injection, a surface atomic structure was successfully fabricated, suggesting the possibility of atomic-scale manipulation of this widely applicable surface of ZnTe.     

OWL‐based acquisition and editing of computer‐interpretable guidelines with the CompGuide editor

Computer‐Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence‐based nature of their source material. Therefore, these machine‐readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine‐readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.     

Advances in bio-logging techniques and their application to study navigation in wild seabirds

ABSTRACT

This review summarizes the advances in bio-logging technology that enables us to monitor foraging behavior, movement, behavioral performance, physiological performance, and sociality in a wide range of bird species, as well as their habitat. Subsequently, navigation is discussed, using long-distance movements in streaked shearwaters as a case study. Moreover, challenges and future research directions in bio-logging science are presented, with focus on: multimodal recording, big data analysis, feedback logging, low-power consumption and power generation systems, logger effects, and capture–recapture methods.     

The World robot summit disaster robotics category – achievements of the 2018 preliminary competition

The World Robot Summit is a robot Olympics and aims to be held in a different country every four years from 2020. The concept of the Plant Disaster Prevention challenge is daily inspections, checks, and emergency response in industrial plants, and in this competition, robots must carry out these types of missions in a mock-up plant. The concept of the Tunnel Disaster Response and Recovery challenge is emergency response to tunnel disasters, and is a simulation competition whereby teams compete to show their ability to deal with disasters, by collecting information and removing debris. The Standard Disaster Robotics challenge assesses, in the form of a contest, the standard performance levels of a robot that are necessary for disaster prevention and emergency response. The World Robot Summit Preliminary Competition was held at Tokyo Big Sight in October 2018, and 36 teams participated in the Disaster Robotics Category. UGVs and UAVs contended the merits of new technology for solving complex problems, using core technologies such as mobility, sensing, recognition, performing operations, human interface, autonomous intelligence etc., as well as system integration and implementation of strategies for completing missions, gaining high-level results.     

Implicit Motor Learning in Parkinson's Disease.

Objective: This study examined whether disruption of performance is moderated in Parkinson's disease (PD) patients who acquire their motor behaviors in an implicit manner. Method: Twenty-seven patients with PD learned a hammering task in errorless (implicit) or errorful (explicit) conditions and were tested for robustness of motor performance under a secondary task load, which required them to continuously count backward as they performed the hammering task. Results: Patients in the errorless (implicit) motor learning condition exhibited robustness to secondary task loading, whereas patients in the errorful (explicit) motor learning condition did not. Conclusions: Implicit motor learning techniques should be considered by PD rehabilitation specialists in cases in which existing disruption to movements is exacerbated by conscious control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Understanding the differences between how novice and experienced designers approach design tasks

Research was undertaken to understand how to provide the most appropriate support for novice designers in engineering design. However, how designers apply their experience and knowledge is not understood and further research in this area is required. This paper describes an observational study to understand how novice and experienced designers approach design tasks. Electronic Publication