IoT Device Integration and Payment via an Autonomic Blockchain-Based Service for IoT Device Sharing

The Internet of Things (IoT) incorporates billions of IoT devices (e.g., sensors, cameras, wearables, smart phones, as well as other internet-connected machines in homes, vehicles, and industrial plants), and the number of such connected IoT devices is currently growing rapidly. This paper proposes a novel Autonomic Global IoT Device Discovery and Integration Service (which we refer to as aGIDDI) that permits IoT applications to find IoT devices that are owned and managed by other parties in IoT (which we refer to as IoT device providers), integrate them, and pay for using their data observations. aGIDDI incorporates a suite of interacting sub-services supporting IoT device description, query, integration, payment (via a pay-as-you-go payment model), and access control that utilise a special-purpose blockchain to manage all information needed for IoT applications to find, pay and use the IoT devices they need. The paper describes aGIDDI's novel protocol that allows any IoT application to discover and automatically integrate and pay for IoT devices and their data that are provided by other parties. The paper also presents aGIDDI's architecture and proof-of-concept implementation, as well as an experimental evaluation of the performance and scalability of aGIDDI in variety of IoT device integration and payment scenarios

Multiple large enteroliths associated with an incisional hernia: a rare case

The surgeon frequently encounters renal and biliary stones but rarely may also encounter enteric stones or enteroliths. An enterolith is a stony foreign body that is formed in the gastrointestinal tract. We present a rare case of multiple, large enteroliths found associated with a longstanding incarcerated incisional hernia. </jats:p

Efficient range-doppler processing for random stepped frequency radar in sutomotive applications

Stepped frequency radar technology, where the transmit waveform consists of a sequence of tones, has long been suggested for cost-effective and high-resolution applications. One recent use of this technology is in automotive application where, in addition to cost-effectiveness, a random stepped frequency (RSF) waveform can significantly reduce the interference between vehicles. In this paper we provide a generic framework for the range and Doppler measurements for multiple targets. We further suggest two possible methods for reducing the computational complexity of RSF waveforms processing, which is important for future automotive applications

Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences

The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework

Interference mitigation in automotive radars using pseudo-random cyclic orthogonal sequences

The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radarradar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework

Farnesoid X Receptor - A molecular predictor of weight loss after vertical sleeve gastrectomy?

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/osp4.337Abstract Objective To determine the expression of the bile acid receptor, farnesoid X (FXR), in human gastric mucosa and investigate correlations between expression and body-mass index (BMI) and in patients with obesity, with changes in weight and BMI following vertical sleeve gastrectomy (VSG). Methods Human gastric mucosa was obtained from normal/ overweight individuals (macroscopically-normal tissue following surgery for malignancy) or from patients with obesity (VSG). The expression of FXR and its isoforms (FXRα, FXRβ) were examined by quantitative PCR and compared with the G protein-coupled bile acid receptor, GPBA. In patients with obesity, changes in BMI and weight loss were determined following VSG. Results FXRα was the predominant isoform in normal/overweight individuals. FXR expression was higher in patients with obes but GPBA receptor expression was unchanged. For those with obesity (n=19), no correlation was found between FXR expression and change in Body-Mass Index (BMI)/month or weight loss/month, taken 3±1 months after surgery, or in BMI or weight at surgery. Conclusions Obesity is associated with increased FXR expression in the gastric mucosa. The findings are preliminary but suggest that this increase in FXR expression is a consequence of obesity, rather than its cause.This study was conducted as part of a series of studies funded by Takeda Pharmaceutical