Synthetic Environments as design tool - A case study

Successful product design requires intensive communication between all stakeholders of the product or service in the very beginning of the development process. In this stage of the development, often communication is inefficient due to the absence of a prototype. We propose the use of a synthetic environment as a methodology and tool to support communication about a concept design among stakeholders; e.g., designers, end-users, and manufacturers. A case study with industrial partners revealed that a low-cost, easy accessible setup, consisting of haptic and visual simulation only, was sufficient for a realistic evaluation of a product and to provide meaningful information to improve its design

Comparing the effectiveness of the 0.018-inch versus the 0.022-inch bracket slot system in orthodontic treatment:study protocol for a randomized controlled trial

BACKGROUND: Edgewise fixed orthodontic appliances are available in two different bracket slot sizes (0.018 and 0.022 inch). Both systems are used by clinicians worldwide with some orthodontists claiming the superiority and clinical advantages of one system over the other. However, the scientific evidence supporting this area is scarce and weak. This leaves the clinician’s choice of bracket slot system to clinical preference. We aim to compare the 0.018-inch and 0.022-inch pre-adjusted bracket slot systems in terms of the effectiveness of orthodontic treatment. METHODS/DESIGN: This is a prospective, multicenter, randomized clinical trial, undertaken in the secondary care hospital environment in the NHS Tayside region of Scotland (United Kingdom). A total of 216 orthodontic patients will be recruited in three centers in secondary care hospitals in NHS Tayside. The participants will be randomly allocated to treatment with either the 0.018-inch or 0.022-inch bracket slot systems (n = 108 for each group) using Victory series™ conventional pre-adjusted bracket systems (3 M Unitek, Monrovia, United States). Baseline records and outcome data collected during and at the end of orthodontic treatment will be assessed. The primary outcome measures will be the duration of orthodontic treatment in the maxillary and mandibular arches. The secondary outcome measures will be the number of scheduled appointments for orthodontic treatment in the maxillary and mandibular arches, treatment outcome using Peer Assessment Rating index (PAR), orthodontically induced inflammatory root resorption (as measured using periapical radiographs) and the patient’s perception of wearing orthodontic appliances. DISCUSSION: The results from the current study will serve as evidence to guide the clinician in deciding whether the difference in bracket slot size has a significant impact on the effectiveness of orthodontic treatment. TRIAL REGISTRATION: Registered with ClinicalTrials.gov on 5 March 2014, registration number: NCT02080338

Ethnoracial Disparities in SARS-CoV-2 Seroprevalence in a Large Cohort of Individuals in Central North Carolina from April to December 2020

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths around the world within the past 2 years. Transmission within the United States has been heterogeneously distributed by geography and social factors with little data from North Carolina. Here, we describe results from a weekly cross-sectional study of 12,471 unique hospital remnant samples from 19 April to 26 December 2020 collected by four clinical sites within the University of North Carolina Health system, with a majority of samples from urban, outpatient populations in central North Carolina. We employed a Bayesian inference model to calculate SARS-CoV-2 spike protein immunoglobulin prevalence estimates and conditional odds ratios for seropositivity. Furthermore, we analyzed a subset of these seropositive samples for neutralizing antibodies. We observed an increase in seroprevalence from 2.9 (95% confidence interval [CI], 1.8 to 4.5) to 12.8 (95% CI, 10.6 to 15.2) over the course of the study. Latinx individuals had the highest odds ratio of SARS-CoV-2 exposure at 6.56 (95% CI, 4.66 to 9.44). Our findings aid in quantifying the degree of asymmetric SARS-CoV-2 exposure by ethnoracial grouping. We also find that 49% of a subset of seropositive individuals had detectable neutralizing antibodies, which was skewed toward those with recent respiratory infection symptoms

Advances in Vehicular Ad-hoc Networks (VANETs): challenges and road-map for future development

Recent advances in wireless communication technologies and auto-mobile industry have triggered a significant research interest in the field of vehicular ad-hoc networks (VANETs) over the past few years. A vehicular network consists of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications supported by wireless access technologies such as IEEE 802.11p. This innovation in wireless communication has been envisaged to improve road safety and motor traffic efficiency in near future through the development of intelligent transportation system (ITS). Hence, governments, auto-mobile industries and academia are heavily partnering through several ongoing research projects to establish standards for VANETs. The typical set of VANET application areas, such as vehicle collision warning and traffic information dissemination have made VANET an interesting field of mobile wireless communication. This paper provides an overview on current research state, challenges, potentials of VANETs as well as the ways forward to achieving the long awaited ITS

A collaborative artefact reconstruction environment

A novel collaborative artefact reconstruction environment design is presented that is informed by experimental task observation and participatory design. The motivation for the design was to enable collaborative human and computer effort in the reconstruction of fragmented cuneiform tablets: millennia-old clay tablets used for written communication in early human civilisation. Thousands of joining cuneiform tablet fragments are distributed within and between worldwide collections. The reconstruction of the tablets poses a complex 3D jigsaw puzzle with no physically tractable solution. In reconstruction experiments, participants collaborated synchronously and asynchronously on virtual and physical reconstruction tasks. Results are presented that demonstrate the difficulties experienced by human reconstructors in virtual tasks compared to physical tasks. Unlike computer counterparts, humans have difficulty identifying joins in virtual environments but, unlike computers, humans are averse to making incorrect joins. A successful reconstruction environment would marry the opposing strengths and weaknesses of humans and computers, and provide tools to support the communications and interactions of successful physical performance, in the virtual setting. The paper presents a taxonomy of the communications and interactions observed in successful physical and synchronous collaborative reconstruction tasks. Tools for the support of these communications and interactions were successfully incorporated in the “i3D” virtual environment design presented

AUTONOMOUS ROBOTIC INSPECTION IN TUNNELS

In this paper, an automatic robotic inspector for tunnel assessment is presented. The proposed platform is able to autonomously navigate within the civil infrastructures, grab stereo images and process/analyse them, in order to identify defect types. At first, there is the crack detection via deep learning approaches. Then, a detailed 3D model of the cracked area is created, utilizing photogrammetric methods. Finally, a laser profiling of the tunnel’s lining, for a narrow region close to detected crack is performed; allowing for the deduction of potential deformations. The robotic platform consists of an autonomous mobile vehicle; a crane arm, guided by the computer vision-based crack detector, carrying ultrasound sensors, the stereo cameras and the laser scanner. Visual inspection is based on convolutional neural networks, which support the creation of high-level discriminative features for complex non-linear pattern classification. Then, real-time 3D information is accurately calculated and the crack position and orientation is passed to the robotic platform. The entire system has been evaluated in railway and road tunnels, i.e. in Egnatia Highway and London underground infrastructure