Direct Relationship Between Electrokinetic Surface-charge Measurement of Effluents and Coagulant Type and Dose

AbstractColloidal stability due to rejection between particles with identical charge is a severe problem in water treatment. Pretreatment of industrial effluents such as olive mill or cowshed dairy wastewater includes the addition of “coagulants” aimed at neutralizing the colloids and reducing their rejection. However, the amount and type of coagulant are usually determined by “trial-and-error” jar tests due to the lack of an efficient method to evaluate the effluents' charge. This study presents a method for direct evaluation of the efficiency of type and dose of coagulants based on particle charge detector (PCD) measurements of the colloidal effluents and the coagulant to be used as the neutralizing compound. This presumably trivial procedure is not common, apparently due to the fact that measuring colloidal charge with a PCD is less widely used than ζ potential measurements. A few examples of the effective use of this procedure are presented

Trick or treat: the effect of placebo on the power of pharmacogenetic association studies

The genetic mapping of drug-response traits is often characterised by a poor signal-to-noise ratio that is placebo related and which distinguishes pharmacogenetic association studies from classical case-control studies for disease susceptibility. The goal of this study was to evaluate the statistical power of candidate gene association studies under different pharmacogenetic scenarios, with special emphasis on the placebo effect. Genotype/phenotype data were simulated, mimicking samples from clinical trials, and response to the drug was modelled as a binary trait. Association was evaluated by a logistic regression model. Statistical power was estimated as a function of the number of single nucleotide polymorphisms (SNPs) genotyped, the frequency of the placebo 'response', the genotype relative risk (GRR) of the response polymorphism, the strategy for selecting SNPs for genotyping, the number of individuals in the trial and the ratio of placebo-treated to drug-treated patients. We show that: (i) the placebo 'response' strongly affects the statistical power of association studies--even a highly penetrant drug-response allele requires at least a 500-patient trial in order to reach 80 per cent power, several-fold more than the value estimated by standard tools that are not calibrated to pharmacogenetics; (ii) the power of a pharmacogenetic association study depends primarily on the penetrance of the response genotype and, when this penetrance is fixed, power decreases for larger placebo effects; (iii) power is dramatically increased when adding markers; (iv) an optimal study design includes a similar number of placebo- and drug-treated patients; and (v) in this setting, straightforward haplotype analysis does not seem to have an advantage over single marker analysis

Almost-Euclidean subspaces of ℓ1N\ell_1^N via tensor products: a simple approach to randomness reduction

It has been known since 1970's that the N-dimensional $\ell_1$-space contains nearly Euclidean subspaces whose dimension is $\Omega(N)$. However, proofs of existence of such subspaces were probabilistic, hence non-constructive, which made the results not-quite-suitable for subsequently discovered applications to high-dimensional nearest neighbor search, error-correcting codes over the reals, compressive sensing and other computational problems. In this paper we present a "low-tech" scheme which, for any $a > 0$, allows to exhibit nearly Euclidean $\Omega(N)$-dimensional subspaces of $\ell_1^N$ while using only $N^a$ random bits. Our results extend and complement (particularly) recent work by Guruswami-Lee-Wigderson. Characteristic features of our approach include (1) simplicity (we use only tensor products) and (2) yielding "almost Euclidean" subspaces with arbitrarily small distortions.Comment: 11 pages; title change, abstract and references added, other minor change

Closed-loop acoustic stimulation during sedation with dexmedetomidine (CLASS-D): Protocol for a within-subject, crossover, controlled, interventional trial with healthy volunteers

Introduction: The relative power of slow-delta oscillations in the electroencephalogram (EEG), termed slow-wave activity (SWA), correlates with level of unconsciousness. Acoustic enhancement of SWA has been reported for sleep states, but it remains unknown if pharmacologically induced SWA can be enhanced using sound. Dexmedetomidine is a sedative whose EEG oscillations resemble those of natural sleep. This pilot study was designed to investigate whether SWA can be enhanced using closed-loop acoustic stimulation during sedation (CLASS) with dexmedetomidine. Methods: Closed-Loop Acoustic Stimulation during Sedation with Dexmedetomidine (CLASS-D) is a within-subject, crossover, controlled, interventional trial with healthy volunteers. Each participant will be sedated with a dexmedetomidine target-controlled infusion (TCI). Participants will undergo three CLASS conditions in a multiple crossover design: in-phase (phase-locked to slow-wave upslopes), anti-phase (phase-locked to slow-wave downslopes) and sham (silence). High-density EEG recordings will assess the effects of CLASS across the scalp. A volitional behavioral task and sequential thermal arousals will assess the anesthetic effects of CLASS. Ambulatory sleep studies will be performed on nights immediately preceding and following the sedation session. EEG effects of CLASS will be assessed using linear mixed-effects models. The impacts of CLASS on behavior and arousal thresholds will be assessed using logistic regression modeling. Parametric modeling will determine differences in sleepiness and measures of sleep homeostasis before and after sedation. Results: The primary outcome of this pilot study is the effect of CLASS on EEG slow waves. Secondary outcomes include the effects of CLASS on the following: performance of a volitional task, arousal thresholds, and subsequent sleep. Discussion: This investigation will elucidate 1) the potential of exogenous sensory stimulation to potentiate SWA during sedation; 2) the physiologic significance of this intervention; and 3) the connection between EEG slow-waves observed during sleep and sedation

Estimation in high dimensions: a geometric perspective

This tutorial provides an exposition of a flexible geometric framework for high dimensional estimation problems with constraints. The tutorial develops geometric intuition about high dimensional sets, justifies it with some results of asymptotic convex geometry, and demonstrates connections between geometric results and estimation problems. The theory is illustrated with applications to sparse recovery, matrix completion, quantization, linear and logistic regression and generalized linear models.Comment: 56 pages, 9 figures. Multiple minor change

First report of generalized face processing difficulties in möbius sequence.

Reverse simulation models of facial expression recognition suggest that we recognize the emotions of others by running implicit motor programmes responsible for the production of that expression. Previous work has tested this theory by examining facial expression recognition in participants with Möbius sequence, a condition characterized by congenital bilateral facial paralysis. However, a mixed pattern of findings has emerged, and it has not yet been tested whether these individuals can imagine facial expressions, a process also hypothesized to be underpinned by proprioceptive feedback from the face. We investigated this issue by examining expression recognition and imagery in six participants with Möbius sequence, and also carried out tests assessing facial identity and object recognition, as well as basic visual processing. While five of the six participants presented with expression recognition impairments, only one was impaired at the imagery of facial expressions. Further, five participants presented with other difficulties in the recognition of facial identity or objects, or in lower-level visual processing. We discuss the implications of our findings for the reverse simulation model, and suggest that facial identity recognition impairments may be more severe in the condition than has previously been noted

Anderson localization and nonlinearity in one-dimensional disordered photonic lattices

We experimentally investigate the evolution of linear and nonlinear waves in a realization of the Anderson model using disordered one-dimensional waveguide lattices. Two types of localized eigenmodes, flat-phased and staggered, are directly measured. Nonlinear perturbations enhance localization in one type and induce delocalization in the other. In a complementary approach, we study the evolution on short time scales of delta-like wave packets in the presence of disorder. A transition from ballistic wave packet expansion to exponential (Anderson) localization is observed. We also find an intermediate regime in which the ballistic and localized components coexist while diffusive dynamics is absent. Evidence is found for a faster transition into localization under nonlinear conditions

FILTWAM and Voice Emotion Recognition

This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone data for a real-time and adequate interpretation of vocal expressions into emotional states were the software is calibrated with end users. FILTWAM already incorporates a valid face emotion recognition module and is extended with a voice emotion recognition module. This extension aims to provide relevant and timely feedback based upon learner's vocal intonations. The feedback is expected to enhance learner’s awareness of his or her own behavior. Six test persons received the same computer-based tasks in which they were requested to mimic specific vocal expressions. Each test person mimicked 82 emotions, which led to a dataset of 492 emotions. All sessions were recorded on video. An overall accuracy of our software based on the requested emotions and the recognized emotions is a pretty good 74.6% for the emotions happy and neutral emotions; but will be improved for the lower values of an extended set of emotions. In contrast with existing software our solution allows to continuously and unobtrusively monitor learners’ intonations and convert these intonations into emotional states. This paves the way for enhancing the quality and efficacy of game-based learning by including the learner's emotional states, and links these to pedagogical scaffolding.The Netherlands Laboratory for Lifelong Learning (NELLL) of the Open University of the Netherlands

Occlusion and Motion Reasoning for Long-Term Tracking

International audienceObject tracking is a reoccurring problem in computer vision. Tracking-by-detection approaches, in particular Struck (Hare et al., 2011), have shown to be competitive in recent evaluations. However, such approaches fail in the presence of long-term occlusions as well as severe viewpoint changes of the object. In this paper we propose a principled way to combine occlusion and motion reasoning with a tracking-by-detection approach. Occlusion and motion reasoning is based on state-of-the-art long-term trajectories which are labeled as object or background tracks with an energy-based formulation. The overlap between labeled tracks and detected regions allows to identify occlusions. The motion changes of the object between consecutive frames can be estimated robustly from the geometric relation between object trajectories. If this geometric change is significant, an additional detector is trained. Experimental results show that our tracker obtains state-of-the-art results and handles occlusion and viewpoints changes better than competing tracking methods