Three and Four Region Multi-sector Linear Modelling Using UK Data : Some Preliminary Results

Scotland and Wales have relatively up-to-date, independently generated, IO tables. These can be separated out from a UK national IO table to construct an inter-regional table. We therefore undertake the detailed analysis at this three-region (Scotland, Wales and the Rest of the UK (RUK)) level, where the Rest of the UK is England and Northern Ireland. However, we also construct a more rudimentary four-region (Scotland, Wales, England and Ireland) set of IO and SAM accounts by constructing a separate Northern Ireland accounts. The inter-regional IO and SAM models are produced for the year 1999. This was determined by the availability of consistent data. In Section II we describe the construction of a three-region Input-Output model for the United Kingdom, which includes the regions of Scotland, Wales and the Rest of the UK (RUK). In Section III we extend the three-region model to construct an inter-regional Social Accounting Matrix. Section IV reports some results using the three-region IO and SAM models. In Section V, we generate a four-region IO and SAM model for the UK, which disaggregates Northern Ireland from the Rest of the UK, and provide some results using the four-region IO and SAM models. Section VI offers our conclusions

Experiencing discrimination increases risk taking.

Prior research has revealed racial disparities in health outcomes and health-compromising behaviors, such as smoking and drug abuse. It has been suggested that discrimination contributes to such disparities, but the mechanisms through which this might occur are not well understood. In the research reported here, we examined whether the experience of discrimination affects acute physiological stress responses and increases risk-taking behavior. Black and White participants each received rejecting feedback from partners who were either of their own race (in-group rejection) or of a different race (out-group rejection, which could be interpreted as discrimination). Physiological (cardiovascular and neuroendocrine) changes, cognition (memory and attentional bias), affect, and risk-taking behavior were assessed. Significant participant race × partner race interactions were observed. Cross-race rejection, compared with same-race rejection, was associated with lower levels of cortisol, increased cardiac output, decreased vascular resistance, greater anger, increased attentional bias, and more risk-taking behavior. These data suggest that perceived discrimination is associated with distinct profiles of physiological reactivity, affect, cognitive processing, and risk taking, implicating direct and indirect pathways to health disparities

Securearray: Improving WiFi security with fine-grained physical-layer information

Despite the important role that WiFi networks play in home and enterprise networks they are relatively weak from a security standpoint. With easily available directional antennas, attackers can be physically located off-site, yet compromise WiFi security protocols such as WEP, WPA, and even to some extent WPA2 through a range of exploits specific to those protocols, or simply by running dictionary and human-factors attacks on users' poorly-chosen passwords. This presents a security risk to the entire home or enterprise network. To mitigate this ongoing problem, we propose SecureArray, a system designed to operate alongside existing wireless security protocols, adding defense in depth against active attacks. SecureArray's novel signal processing techniques leverage multi-antenna access point (AP) to profile the directions at which a client's signals arrive, using this angle-of-arrival (AoA) information to construct highly sensitive signatures that with very high probability uniquely identify each client. Upon overhearing a suspicious transmission, the client and AP initiate an AoA signature-based challenge-response protocol to confirm and mitigate the threat. We also discuss how SecureArray can mitigate direct denial-of-service attacks on the latest 802.11 wireless security protocol. We have implemented SecureArray with an eight-antenna WARP hardware radio acting as the AP. Our experimental results show that in a busy office environment, SecureArray is orders of magnitude more accurate than current techniques, mitigating 100% of WiFi spoofing attack attempts while at the same time triggering false alarms on just 0.6% of legitimate traffic. Detection rate remains high when the attacker is located only five centimeters away from the legitimate client, for AP with fewer numbers of antennas and when client is mobile

Leveraging Electromagnetic Polarization in a Two-Antenna Whiteboard in the Air

Wireless sensing, tracking, and drawing technologies are enabling exciting new possibilities for human-machine interaction. They primarily rely on measurements of backscattered phase, amplitude, and Doppler signal distortions, and often require many measurements of these quantities---in time, or from multiple antennas. In this paper we present the design and implementation of PolarDraw, the first whiteboard in the air that sends differentially-polarized wireless signals to glean more precise tracking information from a tag. Leveraging information received from each polarization angle, our novel algorithms infer orientation and position of an RFID-tagged pen using just two antennas, when the user writes in the air or on a physical whiteboard. An experimental comparison in a cluttered indoor office environment compares two-antenna PolarDraw with recent state-of-the-art object tracking systems that use double the number of antennas, demonstrating comparable centimeter-level tracking accuracy and character recognition rates (88--94%), thus making a case for the use of polarization in many other tracking systems

The Design and Implementation of a Mobile RFID Tag Sorting Robot

Libraries, manufacturing lines, and offices of the future all stand to benefit from knowing the exact spatial order of RFID-tagged books, components, and folders, respectively. To this end, radio- based localization has demonstrated the potential for high accuracy. Key enabling ideas include motion-based synthetic aperture radar, multipath detection, and the use of different frequencies (channels). But indoors in real-world situations, current systems often fall short of the mark, mainly because of the prevalence and strength of "multipath" reflections of the radio signal off nearby objects. In this paper we describe the design and implementation of MobiTagbot, an autonomous wheeled robot reader that conducts a roving survey of the above such areas to achieve an exact spatial order of RFID- tagged objects in very close (1–6 cm) spacings. Our approach leverages a serendipitous correlation between the changes in multipath reflections that occur with motion and the effect of changing the carrier frequency (channel) of the RFID query. By carefully observing the relationship between channel and phase, MobiTagbot detects if multipath is likely prevalent at a given robot reader location. If so, MobiTagbot excludes phase readings from that reader lo- cation, and generates a final location estimate using phase readings from other locations as the robot reader moves in space. Experimentally, we demonstrate that cutting-edge localization algorithms including Tagoram are not accurate enough to exactly order items in very close proximity, but MobiTagbot is, achieving nearly 100% ordering accuracy for items at low (3–6 cm) spacings and 86% accuracy for items at very low (1–3 cm) spacings

First- or second-generation antihistamines: which are more effective at controlling pruritus?

For urticarial itch, first- and second-generation antihistamines have similar clinical benefit and are superior to placebo (strength of recommendation [SOR]: A, systematic review of randomized trials [RCT]). For itch related to atopic dermatitis, antihistamines are no better than placebo (SOR: B, small RCTs and other studies). Other categories of pruritus are best treated with non-antihistamine agents (SOR: C, based on expert opinion and disease-oriented research)

Caring for continence in stroke care settings: a qualitative study of patients’ and staff perspectives on the implementation of a new continence care intervention

Objectives: Investigate the perspectives of patients and nursing staff on the implementation of an augmented continence care intervention after stroke. Design: Qualitative data were elicited during semi-structured interviews with patients (n = 15) and staff (14 nurses; nine nursing assistants) and analysed using thematic analysis. Setting: Mixed acute and rehabilitation stroke ward. Participants: Stroke patients and nursing staff that experienced an enhanced continence care intervention. Results: Four themes emerged from patients’ interviews describing: (a) challenges communicating about continence (initiating conversations and information exchange); (b) mixed perceptions of continence care; (c) ambiguity of focus between mobility and continence issues; and (d) inconsistent involvement in continence care decision making. Patients’ perceptions reflected the severity of their urinary incontinence. Staff described changes in: (i) knowledge as a consequence of specialist training; (ii) continence interventions (including the development of nurse-led initiatives to reduce the incidence of unnecessary catheterisation among patients admitted to their ward); (iii) changes in attitude towards continence from containment approaches to continence rehabilitation; and (iv) the challenges of providing continence care within a stroke care context including limitations in access to continence care equipment or products, and institutional attitudes towards continence. Conclusion: Patients (particularly those with severe urinary incontinence) described challenges communicating about and involvement in continence care decisions. In contrast, nurses described improved continence knowledge, attitudes and confidence alongside a shift from containment to rehabilitative approaches. Contextual components including care from point of hospital admission, equipment accessibility and interdisciplinary approaches were perceived as important factors to enhancing continence care

FlexCore: Massively Parallel and Flexible Processing for Large MIMO Access Points

Large MIMO base stations remain among wireless network designers’ best tools for increasing wireless throughput while serving many clients, but current system designs, sacrifice throughput with simple linear MIMO detection algorithms. Higher-performance detection techniques are known, but remain off the table because these systems parallelize their computation at the level of a whole OFDM subcarrier, sufficing only for the less demanding linear detection approaches they opt for. This paper presents FlexCore, the first computational architecture capable of parallelizing the detection of large numbers of mutually-interfering information streams at a granularity below individual OFDM subcarriers, in a nearly-embarrassingly parallel manner while utilizing any number of available processing elements. For 12 clients sending 64-QAM symbols to a 12-antenna base station, our WARP testbed evaluation shows similar network throughput to the state-of-the-art while using an order of magnitude fewer processing elements. For the same scenario, our combined WARP-GPU testbed evaluation demonstrates a 19x computational speedup, with 97% increased energy efficiency when compared with the state of the art. Finally, for the same scenario, an FPGA-based comparison between FlexCore and the state of the art shows that FlexCore can achieve up to 96% better energy efficiency, and can offer up to 32x the processing throughput