Software-defined sphere decoding for FPGA-based MIMO detection

Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with relatively low computational complexity as compared to the ideal ML detector. Despite this, the computational demands of even low-complexity SD variants, such as Fixed Complexity SD (FSD), remains such that implementation on modern software-defined network equipment is a highly challenging process, and indeed real-time solutions for MIMO systems such as 4 4 16-QAM 802.11n are unreported. This paper overcomes this barrier. By exploiting large-scale networks of fine-grained softwareprogrammable processors on Field Programmable Gate Array (FPGA), a series of unique SD implementations are presented, culminating in the only single-chip, real-time quasi-optimal SD for 44 16-QAM 802.11n MIMO. Furthermore, it demonstrates that the high performance software-defined architectures which enable these implementations exhibit cost comparable to dedicated circuit architectures.

Polysaccharide co-polymerases:the enigmatic conductors of the O-antigen assembly orchestra

The O-antigen lipopolysaccharides on bacterial surface contain variable number of oligosaccharide repeat units with their length having a modal distribution specific to the bacterial strain. The polysaccharide length distribution is controlled by the proteins called polysaccharide co-polymerases (PCPs), which are embedded in the inner membrane in Gram-negative bacteria and form homo oligomers. The 3D structures of periplasmic domains of several PCPs have been determined and provided the first insights into the possible mechanism of polysaccharide length determination mechanism. Here we review the current knowledge of structure and function of these polysaccharide length regulators.

Interceptive skills in children aged 9-11 years, diagnosed with Autism Spectrum Disorder

Growing evidence suggests that significant motor problems are associated with a diagnosis of Autism Spectrum Disorders (ASD), particularly in catching tasks. Catching is a complex, dynamic skill that involves the ability to synchronise one's own movement to that of a moving target. To successfully complete the task, the participant must pick up and use perceptual information about the moving target to arrive at the catching place at the right time. This study looks at catching ability in children diagnosed with ASD (mean age 10.16 ± 0.9 years) and age-matched non-verbal (9.72 ± 0.79 years) and receptive language (9.51 ± 0.46) control groups. Participants were asked to "catch" a ball as it rolled down a fixed ramp. Two ramp heights provided two levels of task difficulty, whilst the sensory information (audio and visual) specifying ball arrival time was varied. Results showed children with ASD performed significantly worse than both the receptive language (p =.02) and non-verbal (p =.02) control groups in terms of total number of balls caught. A detailed analysis of the movement kinematics showed that difficulties with picking up and using the sensory information to guide the action may be the source of the problem. © 2013 Elsevier Ltd.

Physical Activity, Gender, Weight Status, and Wellbeing in 9- to 11-Year-Old Children: A Cross-Sectional Survey

Background: The aim of this study was to examine the relationship between physical activity and wellbeing in children, and to further explore the extent to which this may vary by gender and weight status. Method: A representative sample of 1424 9- to 11-year-olds completed a self-report measure of physical activity, the Child Health and Illness Profile, KIDSCREEN, and a self-esteem scale. Body Mass Index (BMI) measurements were also obtained. Results: 24% of children achieved the recommended level of 60 minutes of moderate-tovigorous intensity physical activity (MVPA) per day, with more boys than girls achieving this level. Children achieving the recommended level of MVPA scored significantly higher on measures of the Child Health and Illness Profile (F(5, 1354) = 5.03; P < .001), KIDSCREEN (F(3, 1298) = 4.68; P = .003), and self-esteem (F(1,1271) = 18.73; P = .003) than less active children although the effect sizes were small (ηp2 ≈ .01). Substantial gender differences in wellbeing were found reflecting gender specific behaviors and socialization. Weight status had negligible influence on wellbeing. Conclusions: Children who meet the recommended guidelines of MVPA were more likely to have better wellbeing. When attempting to raise children’s physical activity levels consideration should be given to the specific relationships between wellbeing and physical activity.