Beyond Expectation: Deep Joint Mean and Quantile Regression for Spatiotemporal Problems.

Spatiotemporal problems are ubiquitous and of vital importance in many research fields. Despite the potential already demonstrated by deep learning methods in modeling spatiotemporal data, typical approaches tend to focus solely on conditional expectations of the output variables being modeled. In this article, we propose a multioutput multiquantile deep learning approach for jointly modeling several conditional quantiles together with the conditional expectation as a way to provide a more complete "picture" of the predictive density in spatiotemporal problems.

A Bayesian Additive Model for Understanding Public Transport Usage in Special Events.

Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinate. The problem highly increases when several events happen concurrently.

Learning Supervised Topic Models for Classification and Regression from Crowds.

The growing need to analyze large collections of documents has led to great developments in topic modeling. Since documents are frequently associated with other related variables, such as labels or ratings, much interest has been placed on supervised topic models. However, the nature of most annotation tasks, prone to ambiguity and noise, often with high volumes of documents, deem learning under a single-annotator assumption unrealistic or unpractical for most real-world applications.

Competing risks mixture model for traffic incident duration prediction.

Traffic incident duration is known to result from a combination of multiple factors, including covariates such as spatial and temporal characteristics, traffic conditions, and existence of secondary accidents but also the clearance method itself. In this paper, a competing risks mixture model is used to investigate the influence of clearance methods and various covariates on the duration of traffic incidents and predict traffic incident duration. The proposed mixture model considers the uncertainty in any of five clearance methods that occurred.

Gold nanoelectrode ensembles for direct trace electroanalysis of iodide.

A procedure for the standardization of ensembles of gold nanodisk electrodes (NEE) of 30 nm diameter is presented, which is based on the analytical comparison between experimental cyclic voltammograms (CV) obtained at the NEEs in diluted solutions of redox probes and CV patterns obtained by digital simulation. Possible origins of defects sometimes found in NEEs are discussed. Selected NEEs are then employed for the study of the electrochemical oxidation of iodide in acidic solutions.

Transplantation of Schwann cells and/or olfactory ensheathing glia into the contused spinal cord: Survival, migration, axon association, and functional recovery.

Schwann cells (SCs) and olfactory ensheathing glia (OEG) have shown promise for spinal cord injury repair. We sought their in vivo identification following transplantation into the contused adult rat spinal cord at 1 week post-injury by: (i) DNA in situ hybridization (ISH) with a Y-chromosome specific probe to identify male transplants in female rats and (ii) lentiviral vector-mediated expression of EGFP. Survival, migration, and axon-glia association were quantified from 3 days to 9 weeks post-transplantation.

Inhibition of tumour necrosis factor-alpha by antisense targeting produces immunophenotypical and morphological changes in injury-activated microglia and macrophages.

Microglia respond in a stereotypical pattern to a diverse array of pathological states. These changes are coupled to morphological and immunophenotypical alterations and the release of a variety of reactive species, trophic factors and cytokines that modify both microglia and their cellular environment. We examined whether a microglial-produced cytokine, tumour necrosis factor-alpha (TNF-alpha), was involved in the maintenance of microglial activation after spinal cord injury by selective inhibition using TNF-alpha antisense deoxyoligonucleotides (ASOs).

cAMP and Schwann cells promote axonal growth and functional recovery after spinal cord injury.

Central neurons regenerate axons if a permissive environment is provided; after spinal cord injury, however, inhibitory molecules are present that make the local environment nonpermissive. A promising new strategy for inducing neurons to overcome inhibitory signals is to activate cAMP signaling. Here we show that cAMP levels fall in the rostral spinal cord, sensorimotor cortex and brainstem after spinal cord contusion.

Voltammetric characteristics of miconazole and its cathodic stripping voltammetric determination.

Miconazole is reduced at mercury electrode above pH 6 involving organometallic compound formation, responsible for an anomalous polarographic behavior. The electrodic process presents a large contribution of the adsorption effects. The drug can be determined by cathodic stripping voltammetry from 8.

The Use of Antisense-Mediated Inhibition to Delineate The Role of Inflammatory Agents in The Pathophysiology of Spinal Cord Injury.

Injuries to the central nervous system (CNS) usually lead to a potent and acute inflammatory response[1]. During this period, glia and immune cells respond to chemical cues associated with the debris of lysed neurons, disrupted axons, and a broken blood-brain-barrier by releasing a battery of cytokines including tumor necrosis factor- (TNF-) and, interleukin-β (IL-1β) as well as reactive oxygen species such as nitric oxide (NO)[2]. The secretion of these factors may be primarily responsible for secondary damage to surrounding uninjured tissue that potentiates the initial injury[3].