A chromatic transient visual evoked potential based encoding/decoding approach for brain-computer interface

This paper presents a new encoding/decoding approach to brain-computer interface (BCI) based on chromatic transient visual evoked potential (CTVEP). The proposed CTVEP-based encoding/decoding approach is designed to provide a safer and more comfortable stimulation method than the conventional VEP-based stimulation methods for BCI without loss of efficiency. For this purpose, low-frequency isoluminant chromatic stimuli are time-encoded to serve as different input commands for BCI control, and the superior comfortableness of the proposed stimulation method is validated by a survey. A combination of diversified signal processing techniques are further employed to decode the information from CTVEP. Based on experimental results, a properly designed configuration of the CTVEP-based stimulation method and a tailored signal processing framework are developed. It is demonstrated that high performance (at information transfer rate: 58.0 bits/min, accuracy: 94.9%, false alarm rate: 1.3%) for BCI can be achieved by means of the CTVEP-based encoding/decoding approach. It turns out that to achieve such good performance, only simple signal processing algorithms with very low computational complexity are required, which makes the method suitable for the development of a practical BCI system. A preliminary prototype of such a system has been implemented with demonstrated applicability. © 2011 IEEE.published_or_final_versio

Microalgae biomass from swine wastewater and its conversion to bioenergy

© 2018 Elsevier Ltd Ever-increasing swine wastewater (SW) has become a serious environmental concern. High levels of nutrients and toxic contaminants in SW significantly impact on the ecosystem and public health. On the other hand, swine wastewater is considered as valuable water and nutrient source for microalgae cultivation. The potential for converting the nutrients from SW into valuable biomass and then generating bioenergy from it has drawn increasing attention. For this reason, this review comprehensively discussed the biomass production, SW treatment efficiencies, and bioenergy generation potentials through cultivating microalgae in SW. Microalgae species grow well in SW with large amounts of biomass being produced, despite the impact of various parameters (e.g., nutrients and toxicants levels, cultivation conditions, and bacteria in SW). Pollutants in SW can effectively be removed by harvesting microalgae from SW, and the harvested microalgae biomass elicits high potential for conversion to valuable bioenergy

Weak coordination among petiole, leaf, vein, and gas-exchange traits across Australian angiosperm species and its possible implications.

Close coordination between leaf gas exchange and maximal hydraulic supply has been reported across diverse plant life forms. However, it has also been suggested that this relationship may become weak or break down completely within the angiosperms. We examined coordination between hydraulic, leaf vein, and gas-exchange traits across a diverse group of 35 evergreen Australian angiosperms, spanning a large range in leaf structure and habitat. Leaf-specific conductance was calculated from petiole vessel anatomy and was also measured directly using the rehydration technique. Leaf vein density (thought to be a determinant of gas exchange rate), maximal stomatal conductance, and net CO 2 assimilation rate were also measured for most species (n = 19-35). Vein density was not correlated with leaf-specific conductance (either calculated or measured), stomatal conductance, nor maximal net CO 2 assimilation, with r (2) values ranging from 0.00 to 0.11, P values from 0.909 to 0.102, and n values from 19 to 35 in all cases. Leaf-specific conductance calculated from petiole anatomy was weakly correlated with maximal stomatal conductance (r (2) = 0.16; P = 0.022; n = 32), whereas the direct measurement of leaf-specific conductance was weakly correlated with net maximal CO 2 assimilation (r (2) = 0.21; P = 0.005; n = 35). Calculated leaf-specific conductance, xylem ultrastructure, and leaf vein density do not appear to be reliable proxy traits for assessing differences in rates of gas exchange or growth across diverse sets of evergreen angiosperms

Review: revisiting the human cholinergic nucleus of the diagonal band of Broca

Although the nucleus of the vertical limb of the diagonal band of Broca (nvlDBB) is the second largest cholinergic nucleus in the basal forebrain, after the nucleus basalis of Meynert (nbM), it has not generally been a focus for studies of neurodegenerative disorders. However, the nvlDBB does have an important projection to the hippocampus and discrete lesions of the rostral basal forebrain have been shown to disrupt retrieval memory function, a major deficit seen in patients with Lewy body disorders. One reason for its neglect is that the anatomical boundaries of the nvlDBB are ill defined and this area of the brain is not part of routine diagnostic sampling protocols. We have reviewed the history and anatomy of the nvlDBB and now propose guidelines for distinguishing nvlDBB from other neighbouring cholinergic cell groups for standardising future clinicopathological work. Thorough review of the literature regarding neurodegenerative conditions reveals inconsistent results in terms of cholinergic neuronal loss within the nvlDBB. This is likely to be due to the use of variable neuronal inclusion criteria and omission of cholinergic immunohistochemical markers. Extrapolating from those studies showing significant nvlDBB neuronal loss in Lewy body dementia, we propose an anatomical and functional connection between the cholinergic component of the nvlDBB (Ch2) and the CA2 subfield in the hippocampus which may be especially vulnerable in Lewy body disorders. This article is protected by copyright. All rights reserved

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

Sharp Global Bounds for the Hessian on Pseudo-Hermitian Manifolds

We find sharp bounds for the norm inequality on a Pseudo-hermitian manifold, where the L^2 norm of all second derivatives of the function involving horizontal derivatives is controlled by the L^2 norm of the sub-Laplacian. Perturbation allows us to get a-priori bounds for solutions to sub-elliptic PDE in non-divergence form with bounded measurable coefficients. The method of proof is through a Bochner technique. The Heisenberg group is seen to be en extremal manifold for our inequality in the class of manifolds whose Ricci curvature is non-negative.Comment: 13 page

Reconstructing pedigrees: some identifiability questions for a recombination-mutation model

Pedigrees are directed acyclic graphs that represent ancestral relationships between individuals in a population. Based on a schematic recombination process, we describe two simple Markov models for sequences evolving on pedigrees - Model R (recombinations without mutations) and Model RM (recombinations with mutations). For these models, we ask an identifiability question: is it possible to construct a pedigree from the joint probability distribution of extant sequences? We present partial identifiability results for general pedigrees: we show that when the crossover probabilities are sufficiently small, certain spanning subgraph sequences can be counted from the joint distribution of extant sequences. We demonstrate how pedigrees that earlier seemed difficult to distinguish are distinguished by counting their spanning subgraph sequences.Comment: 40 pages, 9 figure

Risk factors for race-day fatality in flat racing Thoroughbreds in Great Britain (2000 to 2013)

A key focus of the racing industry is to reduce the number of race-day events where horses die suddenly or are euthanased due to catastrophic injury. The objective of this study was therefore to determine risk factors for race-day fatalities in Thoroughbred racehorses, using a cohort of all horses participating in flat racing in Great Britain between 2000 and 2013. Horse-, race- and course-level data were collected and combined with all race-day fatalities, recorded by racecourse veterinarians in a central database. Associations between exposure variables and fatality were assessed using logistic regression analyses for (1) all starts in the dataset and (2) starts made on turf surfaces only. There were 806,764 starts in total, of which 548,571 were on turf surfaces. A total of 610 fatalities were recorded; 377 (61.8%) on turf. In both regression models, increased firmness of the going, increasing racing distance, increasing average horse performance, first year of racing and wearing eye cover for the first time all increased the odds of fatality. Generally, the odds of fatality also increased with increasing horse age whereas increasing number of previous starts reduced fatality odds. In the ‘all starts’ model, horses racing in an auction race were at 1.46 (95% confidence interval (CI) 1.06–2.01) times the odds of fatality compared with horses not racing in this race type. In the turf starts model, horses racing in Group 1 races were at 3.19 (95% CI 1.71–5.93) times the odds of fatality compared with horses not racing in this race type. Identification of novel risk factors including wearing eye cover and race type will help to inform strategies to further reduce the rate of fatality in flat racing horses, enhancing horse and jockey welfare and safety

ELECTROCHEMICAL STUDIES ON MO - FE PROTEIN

The midpoint potentials and n values of Mo - Fe protein of azotobacter vinelandii ( Avl ) were determined by the coulometry at fixed potentials . The oxidation - reduction states of the Mo-Fe protein were discussed.The oxidation-reduction states of the Mo-Fe protein by the carrier ( methyl viologen ) is studied

P20-08. Glycosylation: an important factor in Env diversity

Supported by a CAVD Grant from the Bill and Melinda Gates Foundation