69 research outputs found

    The thermal stability of alkanethiol self-assembled monolayers on copper for fluxless soldering applications

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    The ability of alkanethiol monolayers deposited on copper to prevent surface oxidation has suggested their application as preservatives for fluxless soldering. However, the utility of such coatings for this purpose will critically depend on their ability to continue to preserve the substrate during exposure to elevated temperatures throughout the electronics manufacturing process. Consequently, the aim of this paper is to systematically determine the effect of storage temperature and duration on the ability of alkanethiol coated copper samples to undergo fluxless soldering. Similarly, the effect of pre-heating copper immediately prior to soldering is also investigated. The effect of reducing atmospheric oxygen concentration during storage and soldering is also considered as a potential route to improve the thermal resilience of the coatings. Parallel to ascertaining these industrially relevant performance parameters, a quantitative correlation between surface chemistry and solder wetting is established, and the temperature dependence of the kinetics of surface oxidation through an alkanethiol barrier layer is discussed

    Automated Gaze-Based Mind Wandering Detection during Computerized Learning in Classrooms

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    We investigate the use of commercial off-the-shelf (COTS) eye-trackers to automatically detect mind wandering—a phenomenon involving a shift in attention from task-related to task-unrelated thoughts—during computerized learning. Study 1 (N = 135 high-school students) tested the feasibility of COTS eye tracking while students learn biology with an intelligent tutoring system called GuruTutor in their classroom. We could successfully track eye gaze in 75% (both eyes tracked) and 95% (one eye tracked) of the cases for 85% of the sessions where gaze was successfully recorded. In Study 2, we used this data to build automated student-independent detectors of mind wandering, obtaining accuracies (mind wandering F1 = 0.59) substantially better than chance (F1 = 0.24). Study 3 investigated context-generalizability of mind wandering detectors, finding that models trained on data collected in a controlled laboratory more successfully generalized to the classroom than the reverse. Study 4 investigated gaze- and video- based mind wandering detection, finding that gaze-based detection was superior and multimodal detection yielded an improvement in limited circumstances. We tested live mind wandering detection on a new sample of 39 students in Study 5 and found that detection accuracy (mind wandering F1 = 0.40) was considerably above chance (F1 = 0.24), albeit lower than offline detection accuracy from Study 1 (F1 = 0.59), a finding attributable to handling of missing data. We discuss our next steps towards developing gaze-based attention-aware learning technologies to increase engagement and learning by combating mind wandering in classroom contexts

    Next generation neural population models

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    Low-dimensional neural mass models are often invoked to model the coarse-grained activity of large populations of neurons and synapses and have been used to help understand the coordination of large scale brain rhythms. However, they are phenomenological in nature and, although motivated by neurobiological considerations, the absence of a direct link to an underlying biophysical reality is a weakness that means they may not be best suited to capturing some of the rich behaviors seen in real neuronal tissue. In this perspective article I discuss a simple spiking neuron network model that has recently been shown to admit to an exact mean-field description for synaptic interactions. This has many of the features of a neural mass model coupled to an additional dynamical equation that describes the evolution of population synchrony. This next generation neural mass model is ideally suited to understanding the patterns of brain activity that are ubiquitously seen in neuroimaging recordings. Here I review the mean-field equations, the way in which population synchrony, firing rate, and average voltage are intertwined, together with their application in large scale brain modeling. As well as natural extensions of this new approach to modeling the dynamics of neuronal populations I discuss some of the open mathematical challenges in developing a statistical neurodynamics that can generalize the one discussed here

    Overmoulding of electronics for end of life recovery

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    With the increasing use of electronic control systems in automotive applications, the environments in which they are required to operate are becoming evermore demanding. For improved functionality and to reduce the number of interconnections it is desirable to place the electronic control units (ECUs) as close as possible to the sensors and actuators they interact with, and they can increasingly be found mounted on engine, transmission and chassis components. The electronics are therefore exposed to high/low temperatures, high humidity, vibration and corrosive fluids. In order to protect the electronics and maintain reliability in safety critical areas, great lengths are taken to mount the devices in ways that will prevent the ingress of moisture, cushion shocks and dissipate heat. Potting of electrical devices with thermosetting polymers has been a commonplace method to install a protective layer over the circuit assemblies, which are often mounted in separate boxes within the vehicle. However, with the drive to reduce vehicle weight and increase recyclability, there has been much interest in the use of overmoulding with thermoplastic polymers, not only to provide protection, but to enable the electronics to be mounted into a structural component of the vehicle thereby saving space and weight and eliminating a level of packaging. While this has been shown to be a practical way forward in terms of reliability, the recyclability of the thermoplastic polymer is compromised by the intermixed electronics that are hard to separate economically

    Using routine inpatient data to identify patients at risk of hospital readmission

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    Background: A relatively small percentage of patients with chronic medical conditions account for a much larger percentage of inpatient costs. There is some evidence that case-management can improve health and quality-of-life and reduce the number of times these patients are readmitted. To assess whether a statistical algorithm, based on routine inpatient data, can be used to identify patients at risk of readmission and who would therefore benefit from case-management

    A reassessment of Kelmayisaurus petrolicus, a large theropod dinosaur from the Early Cretaceous of China

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    The Early Cretaceous fossil record of large−bodied theropods from Asia is poor, hindering comparison of Asian predatory dinosaur faunas with those from other continents. One of the few large Asian theropod specimens from this interval is a partial skull (maxilla and dentary) from the Lianmugin Formation (?Valanginian–Albian), the holotype of Kelmayisaurus petrolicus. Most authors have either considered this specimen as an indeterminate basal tetanuran or a nomen dubium. Weredescribe K. petrolicus and note that it possesses a single autapomorphy (a deep accessory groove on the lateral surface of the anterior dentary), as well as a unique combination of characters that differentiates it from other theropods, affirming its validity. A phylogenetic analysis recovers K. petrolicus as a basal carcharodontosaurid, which is supported by various features: very deep interdental plates (a carcharodontosaurid synapomorphy), fused interdental plates (present in carchardontosaurids and a limited number of other theropods), and the absence of diagnostic features of other clades of large−bodied theropods such as abelisaurids, megalosauroids, and coelurosaurs. As such, Kelmayisaurus is the second known carcharodontosaurid from Asia, and further evidence that this clade represented a global radiation of large−bodied predators during the Early–mid Cretaceous

    Early T Cell Recognition of B Cells following Epstein-Barr Virus Infection: Identifying Potential Targets for Prophylactic Vaccination

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    Epstein-Barr virus, a B-lymphotropic herpesvirus, is the cause of infectious mononucleosis, has strong aetiologic links with several malignancies and has been implicated in certain autoimmune diseases. Efforts to develop a prophylactic vaccine to prevent or reduce EBV-associated disease have, to date, focused on the induction of neutralising antibody responses. However, such vaccines might be further improved by inducing T cell responses capable of recognising and killing recently-infected B cells. In that context, EBNA2, EBNA-LP and BHRF1 are the first viral antigens expressed during the initial stage of B cell growth transformation, yet have been poorly characterised as CD8+ T cell targets. Here we describe CD8+ T cell responses against each of these three "first wave" proteins, identifying target epitopes and HLA restricting alleles. While EBNA-LP and BHRF1 each contained one strong CD8 epitope, epitopes within EBNA2 induced immunodominant responses through several less common HLA class I alleles (e.g. B*3801 and B*5501), as well as subdominant responses through common class I alleles (e.g. B7 and C*0304). Importantly, such EBNA2-specific CD8+ T cells recognised B cells within the first day post-infection, prior to CD8+ T cells against well-characterised latent target antigens such as EBNA3B or LMP2, and effectively inhibited outgrowth of EBV-transformed B cell lines. We infer that "first wave" antigens of the growth-transforming infection, especially EBNA2, constitute potential CD8+ T cell immunogens for inclusion in prophylactic EBV vaccine design
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