Examination of Ni-based superalloy/intermetallic diffusion couples containing multiphase regions

Increasing gas turbine operating temperatures are driving the development of novel coatings for niche applications. One such application is as an anchor phase material for use in the high-pressure turbine stage, for which NiAlTa alloys are a promising candidate. Extended exposure to the high temperatures of this environment can cause interdiffusion of elements between the coating and the underlying blade material. In this study, NiAlTa/CMSX-4 diffusion couples were investigated experimentally and computationally. The couples initially contained two two-phase regions (γ + γ′) and (β + τ1). After heat treatment at 1100 °C, interdiffusion had caused the τ1 Laves phase in the coating to transform to the τ2 Heusler phase, and TCP precipitation was observed in the CMSX-4. A CALPHAD-based model, using Thermo-Calc and DICTRA, developed for this system was able to predict the concentration profiles across the diffusion couple at 1000 °C, with the presence of the predicted phases in the interdiffusion zone verified by x-ray diffraction. However, due to the limited diffusion data for intermetallic phases available in the kinetic database, the model predictions were poor at higher temperatures. In order for the development of intermetallic coatings to be aided by CALPHAD-based simulations, more kinetic data is needed for intermetallic phases than is available at present

Exploring attention in vr:Effects of visual and auditory modalities

Attention requires the ability to stay concentrated and alert to stimuli over prolonged periods of time. Virtual reality (VR) can be used in various training situations where attention plays a major role (e.g. system operators). Here, we investigate the effects of visual and auditory stimuli on attention performance in a VR aquarium (Nesplora Aquarium). Participants pay attention to the main fish tank and respond by pressing a button. The stimuli are different species of fish that are delivered either via visual or auditory channels. Thirty-seven participants completed the VR test and paper questionnaires. We found that attention is influenced differently by sensory modalities. Attention performance measured by the reaction time to correct targets and the number of errors of omission were better in the visual condition, while the number of errors of commission were lower in the auditory condition. The human factors’ role in attention tasks is also discussed.</p

Automation in human-machine networks: how increasing machine agency affects human agency

© 2018, Springer International Publishing AG. Efficient human-machine networks require productive interaction between human and machine actors. In this study, we address how a strengthening of machine agency, for example through increasing levels of automation, affect the human actors of the networks. Findings from case studies within air traffic management, emergency management, and crowd evacuation are presented, shedding light on how automation may strengthen the agency of human actors in the network through responsibility sharing and task allocation, and serve as a needed prerequisite of innovation and change

Addressing accountability in highly autonomous virtual assistants

Building from a survey specifically developed to address the rising concerns of highly autonomous virtual assistants; this paper presents a multi-level taxonomy of accountability levels specifically adapted to virtual assistants in the context of Human-Human-Interaction (HHI). Based on research findings, the authors recommend the integration of the variable of accountability as capital in the development of future applications around highly automated systems. This element inserts a sense of balance in terms of integrity between users and developers enhancing trust in the interactive process. Ongoing work is being dedicated to further understand to which extent different contexts affect accountability in virtual assistants

The CACCC-binding protein KLF3/BKLF represses a subset of KLF1/EKLF target genes and is required for proper erythroid maturation in vivo

The CACCC-box binding protein erythroid Kruppel-like factor (EKLF/KLF1) is a master regulator that directs the expression of many important erythroid genes. We have previously shown that EKLF drives transcription of the gene for a second KLF, basic Kruppel-like factor, or KLF3. We have now tested the in vivo role of KLF3 in erythroid cells by examining Klf3 knockout mice. KLF3-deficient adults exhibit a mild compensated anemia, including enlarged spleens, increased red pulp, and a higher percentage of erythroid progenitors, together with elevated reticulocytes and abnormal erythrocytes in the peripheral blood. Impaired erythroid maturation is also observed in the fetal liver. We have found that KLF3 levels rise as erythroid cells mature to become TER119(+). Consistent with this, microarray analysis of both TER119(-) and TER119(+) erythroid populations revealed that KLF3 is most critical at the later stages of erythroid maturation and is indeed primarily a transcriptional repressor. Notably, many of the genes repressed by KLF3 are also known to be activated by EKLF. However, the majority of these are not currently recognized as erythroid-cell-specific genes. These results reveal the molecular and physiological function of KLF3, defining it as a feedback repressor that counters the activity of EKLF at selected target genes to achieve normal erythropoiesis

Trust in an autonomously driven simulator and vehicle performing maneuvers at a T-junction with and without other vehicles

Autonomous vehicle (AV) technology is developing rapidly. Level 3 automation assumes the user might need to respond to requests to retake control. Levels 4 (high automation) and 5 (full automation) do not require human monitoring of the driving task or systems [1]: the AV handles driving functions and makes decisions based on continuously updated information. A gradual switch in the role of the human within the vehicle from active controller to passive passenger comes with uncertainty in terms of trust, which will likely be a key barrier to acceptability, adoption and continued use [2]. Few studies have investigated trust in AVs and these have tended to use driving simulators with Level 3 automation [3, 4]. The current study used both a driving simulator and autonomous road vehicle. Both were operating at Level 3 autonomy although did not require intervention from the user; much like Level 4 systems. Forty-six participants completed road circuits (UK-based) with both platforms. Trust was measured immediately after different types of turns at a priority T-junction, increasing in complexity: e.g., driving left or right out of a T-junction; turning right into a T-junction; presence of oncoming/crossing vehicles. Trust was high across platforms: higher in the simulator for some events and higher in the road AV for others. Generally, and often irrespective of platform, trust was higher for turns involving an oncoming/crossing vehicle(s) than without traffic, possibly because the turn felt more controlled as the simulator and road AVs always yielded, resulting in a delayed maneuver. We also found multiple positive relationships between trust in automation and technology, and trust ratings for most T-junction turn events across platforms. The assessment of trust was successful and the novel findings are important to those designing, developing and testing AVs with users in mind. Undertaking a trial of this scale is complex and caution should be exercised about over-generalizing the findings

In Vivo, In Vitro, and In Silico Characterization of Peptoids as Antimicrobial Agents

Bacterial resistance to conventional antibiotics is a global threat that has spurred the development of antimicrobial peptides (AMPs) and their mimetics as novel anti-infective agents. While the bioavailability of AMPs is often reduced due to protease activity, the non-natural structure of AMP mimetics renders them robust to proteolytic degradation, thus offering a distinct advantage for their clinical application. We explore the therapeutic potential of N-substituted glycines, or peptoids, as AMP mimics using a multi-faceted approach that includes in silico, in vitro, and in vivo techniques. We report a new QSAR model that we developed based on 27 diverse peptoid sequences, which accurately correlates antimicrobial peptoid structure with antimicrobial activity. We have identified a number of peptoids that have potent, broad-spectrum in vitro activity against multi-drug resistant bacterial strains. Lastly, using a murine model of invasive S. aureus infection, we demonstrate that one of the best candidate peptoids at 4 mg/kg significantly reduces with a two-log order the bacterial counts compared with saline-treated controls. Taken together, our results demonstrate the promising therapeutic potential of peptoids as antimicrobial agents