Compact low-power cortical recording architecture for compressive multichannel data acquisition

This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sparse biological signals. Still, any large-scale implementation of this technique faces critical issues caused by the increased hardware intensity. The cost of implementing compressive sensing in a multichannel system in terms of area usage can be significantly higher than a conventional data acquisition system without compression. To tackle this issue, a new multichannel compressive sensing scheme which exploits the spatial sparsity of the signals recorded from the electrodes of the sensor array is proposed. The analysis shows that using this method, the power efficiency is preserved to a great extent while the area overhead is significantly reduced resulting in an improved power-area product. The proposed circuit architecture is implemented in a UMC 0.18 [Formula: see text]m CMOS technology. Extensive performance analysis and design optimization has been done resulting in a low-noise, compact and power-efficient implementation. The results of simulations and subsequent reconstructions show the possibility of recovering fourfold compressed intracranial EEG signals with an SNR as high as 21.8 dB, while consuming 10.5 [Formula: see text]W of power within an effective area of 250 [Formula: see text]m × 250 [Formula: see text]m per channel.

Implicit Motives of Elite Athletes, Sport Students, and Non-Sport Students: Power, Affiliation, and Achievement

Research on performance and participation in (elite) sports has predominantly focused on variables relating to the achievement motive. However, some authors describe that athletes in interactive sports (e.g. tennis) are assumed to exhibit a strong power motive in order to win competitive matches, usually resulting in the demonstration of dominance or the experience of inferiority. The affiliation motive, by contrast, is not functional in elite sports due to their competitive rather than social character. In the present chapter we discuss how the three basic implicit motives of power, affiliation, and achievement relate to the sports field and describe how they can affect athletes’ performance. We present empirical evidence for the existence of different strengths of the three basic motives in three studies with elite athletes (Study 1), non-elite athletes (sport students, Study 2), and non-sport students infrequently involved in sports (Study 3). Our results suggest that elite athletes show higher levels of the implicit power motive compared to sport students, who in turn have higher power motives than non-sport students. Surprisingly, elite athletes do not differ from non-sport students regarding their implicit achievement motive. Moreover, non-sport students exhibit higher implicit affiliation motive scores than sport students and elite athletes. We propose that research on motivational processes of highly competitive athletes should – in addition to the achievement motive – focus more on motive themes like the implicit motives of power and affiliation.

A Passive WiFi Source Localization System based on Fine-grained Power-based Trilateration

Indoor localization systems become more interesting for researchers because of the attractiveness of business cases in various application fields. A WiFi-based passive localization system can provide user location information to third-party providers of positioning services. However, indoor localization techniques are prone to multipath and Non-Line Of Sight (NLOS) propagation, which lead to significant performance degradation. To overcome these problems, we provide a passive localization system for WiFi targets with several improved algorithms for localization. Through Software Defined Radio (SDR) techniques, we extract Channel Impulse Response (CIR) information at the physical layer. CIR is later adopted to mitigate the multipath fading problem. We propose to use a Nonlinear Regression (NLR) method to relate the filtered power information to propagation distances, which significantly improves the ranging accuracy compared to the commonly used log-distance path loss model. To mitigate the influence of ranging errors, a new trilateration algorithm is designed as well by combining Weighted Centroid and Constrained Weighted Least Square (WC-CWLS) algorithms. Experiment results show that our algorithm is robust against ranging errors and outperforms the linear least square algorithm and weighted centroid algorithm.

Genome-wide association studies based on sequence-derived genotypes reveal new QTL associated with conformation and performance traits in the Franches-Montagnes horse breed

To identify novel quantitative trait loci (QTL) within horses, we performed genome-wide association studies (GWAS) based on sequence-level genotypes for conformation and performance traits in the Franches-Montagnes (FM) horse breed. Sequence-level genotypes of FM horses were derived by re-sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de-regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence-derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.