Telerobotic Sensor-based Tool Control Derived From Behavior-based Robotics Concepts

@font-face { font-family: TimesNewRoman ; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0in 0in 0.0001pt; font-size: 12pt; font-family: Times New Roman ; }div.Section1 { page: Section1; } Teleoperated task execution for hazardous environments is slow and requires highly skilled operators. Attempts to implement telerobotic assists to improve efficiency have been demonstrated in constrained laboratory environments but are not being used in the field because they are not appropriate for use on actual remote systems operating in complex unstructured environments using typical operators. This work describes a methodology for combining select concepts from behavior-based systems with telerobotic tool control in a way that is compatible with existing manipulator architectures used by remote systems typical to operations in hazardous environment. The purpose of the approach is to minimize the task instance modeling in favor of a priori task type models while using sensor information to register the task type model to the task instance. The concept was demonstrated for two tools useful to decontamination & dismantlement type operations—a reciprocating saw and a powered socket tool. The experimental results demonstrated that the approach works to facilitate traded control telerobotic tooling execution by enabling difficult tasks and by limiting tool damage. The role of the tools and tasks as drivers to the telerobotic implementation was better understood in the need for thorough task decomposition and the discovery and examination of the tool process signature. The contributions of this work include: (1) the exploration and evaluation of select features of behavior-based robotics to create a new methodology for integrating telerobotic tool control with positional teleoperation in the execution of complex tool-centric remote tasks, (2) the simplification of task decomposition and the implementation of sensor-based tool control in such a way that eliminates the need for the creation of a task instance model for telerobotic task execution, and (3) the discovery, demonstrated use, and documentation of characteristic tool process signatures that have general value in the investigation of other tool control, tool maintenance, and tool development strategies above and beyond the benefit sustained for the methodology described in this work

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Thermal Process Monitoring for Wire-Arc Additive Manufacturing using IR Cameras

Wire-arc additive manufacturing systems use robotic MIG welders to build parts using welding wire. As a part is built the temperature rises as energy is input and the thermal mass increases. While some pre-heat is ideal for welding, improper thermal management can lead to defects and negatively affect material properties. Thermal imaging allows for non-contact thermal monitoring and can be used to track thermal gradients as well as layer temperatures before and after deposition providing a method to ensure proper thermal management. A typical IR camera setup on an mBAAM system is discussed along with methods to use thermal monitoring to improve material properties and reduce defects in the final part.Mechanical Engineerin

Framework for CAD to Part of Large Scale Additive Manufacturing of Metal (LSAMM) in Arbitrary Directions

The purpose of this research is to provide a framework for Large Scale Additive Metals Manufacturing (LSAMM) in arbitrary directions. Traditionally, slicing and path planning is done along the gravity aligned direction of a part, causing more complex geometrical shapes to have unsupported overhangs. The overhangs can be managed using a part positioner or a powder bed process. A different framework for slicing and building parts out of gravity alignment could improve current capabilities of LSAMM processes. The presented research focuses on segmenting more complex geometrical parts into gravity aligned (GA), non-gravity aligned (NGA), and transition segments to help generate toolpaths. Initial research of segment planning for complex geometrical shapes will be presented, as well as current results from builds completed at the University of Tennessee-Knoxville. The completed builds show that more consistent thermal evolution of a part based on the path sequence and torch angle results in successful builds.Mechanical Engineerin

Oregon\u27s Fish and Wildlife in a Changing Climate

Chapter 7 in: The Oregon Climate Change Assessment Report Oregon\u27s fish and wildlife include animals on land, fish and other species in rivers and lakes, and various kinds of sea life in estuaries and coastal ocean. Oregon is one of the most ecologically diverse states in the country. The state’s robust biodiversity, some of which is already threatened or endangered -- inhabits complex and dynamic ecosystems that we have only begun to understand, let alone examine in terms of climate change.It is clear that the abundance and distribution of species are shifting already and will shift more rapidly as habitats on land, in freshwater, and in the sea are altered due to increasing temperatures and related environmental changes. It remains to be seen if past changes are all tied to global climate change or if they are a result of some other variability, but they represent a proxy for how species may shift in a warmer climate. Among the observed species changes: Insects are moving in from the south of Oregon, frogs are reproducing earlier in the year and land birds are shifting their distributions northward and migrating earlier. Freshwater fish are losing their cool-water habitats. In the marine environment, algal blooms have increased (figure 11) and the highly predatory Humboldt squid have shifted their distribution from subtropical and tropical regions, making an appearance off the coast of Oregon in the last few years. In a warmer climate, plant and animal species may have to shift upward or northward on land or deeper at sea for survival. Rare or endangered species may become less abundant or extinct; insect pests, invasive species and harmful algal blooms may become more abundant. Declines in the abundance of species may be caused directly by physiological stress related to changes in temperature, water availability, and other environmental shifts, and/or indirectly by habitat degradation and negative interactions with species that are benefited by climate change (diseases, parasites, predators, and competitors). Understanding the responses of Oregon’s fish and wildlife to climate change will require a better understanding of smaller organisms and insects and ocean species. Knowledge of ecological interactions will be crucial for understanding the related effects of climate change (increased predation or competition, for example). Management and natural resource polices that protect intact ecosystems are a tool for adaptation; native species can live and migrate to these safe refugia

Strategies for a scalable multi-robot large scale wire arc additive manufacturing system

Conventional robotic wire arc additive manufacturing technologies enable the rapid production of moderate-sized components using low-cost wire feedstocks and robotic welding systems. Efforts to date have primarily focused on single robot solutions. However, new configurations are possible with coordination of multiple robots and multi-degree of freedom positioners. This paper describes a new multi-agent control paradigm that enables multiple robots to work collaboratively on manufacturing a single component on a rotating platform. The advantages of this approach are increased deposition rate and productivity. This paper demonstrates this control strategy on a 19 degrees-of-freedom platform based on three wire arc additive systems surrounding a single rotating platform

Modelling the transmission of healthcare associated infections: a systematic review.

BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models

Preparing for a challenging winter 2020/21

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