Stormwater runoff is a leading cause of nitrogen (N) transport to water bodies and hence one means of water quality deterioration. Stormwater runoff was monitored in an urban residential catchment (drainage area 3.89 hectares) in Florida, United States to investigate the concentrations, forms, and sources of N. Runoff samples were collected over 22 storm events (May to September 2016) at the end of a stormwater pipe that delivers runoff from the catchment to the stormwater pond. Various N forms such as ammonium (NH4-N), nitrate (NOx-N), dissolved organic nitrogen (DON), and particulate organic nitrogen (PON) were determined and isotopic characterization tools were used to infer sources of NO3-N and PON in collected runoff samples. The DON was the dominant N form in runoff (47%) followed by PON (22%), NOx-N (17%), and NH4-N (14%). Three N forms (NOx-N, NH4-N, and PON) were positively correlated with total rainfall and antecedent dry period, suggesting longer dry periods and higher rainfall amounts are significant drivers for transport of these N forms. Whereas DON was positively correlated to only rainfall intensity indicating that higher intensity rain may flush out DON from soils and cause leaching of DON from particulates present in the residential catchment. We discovered, using stable isotopes of NO3-, a shifting pattern of NO3- sources from atmospheric deposition to inorganic N fertilizers in events with higher and longer duration of rainfall. The stable isotopes of PON confirmed that plant material (oak detritus, grass clippings) were the primary sources of PON in stormwater runoff. Our results demonstrate that practices targeting both inorganic and organic N are needed to control N transport from residential catchments to receiving waters.Early onset, intensive and repetitive, gait training may improve outcome after stroke but for patients with severe limitations in walking, rehabilitation is a challenge. The Hybrid Assistive Limb (HAL) is a gait machine that captures voluntary actions and support gait motions. Previous studies of HAL indicate beneficial effects on walking, but these results need to be confirmed in blinded, randomized controlled studies. This study aimed to explore effects of incorporating gait training with HAL as part of an inpatient rehabilitation program after stroke. Thirty-two subacute stroke patients with severe limitations in walking were randomized to incorporated HAL training (4 days/week for 4 weeks) or conventional gait training only. Blinded assessments were carried out at baseline, after the intervention, and at 6 months post stroke. The primary outcome was walking independence according to the Functional Ambulation Categories. Secondary outcomes were the Fugl-Meyer Assessment, 2-Minute Walk Test, Berg Balance Scale, and the Barthel Index. No significant between-group differences were found regarding any primary or secondary outcomes. At 6 months, two thirds of all patients were independent in walking. Prediction of independent walking at 6 months was not influenced by treatment group, but by age (OR 0.848, CI 0.719-0.998, p = 0.048). This study found no difference between groups for any outcomes despite the extra resources required for the HAL training, but highlights the substantial improvements in walking seen when evidence-based rehabilitation is provided to patients, with severe limitations in walking in the subacute stage after stroke. In future studies potential subgroups of patients who will benefit the most from electromechanically-assisted gait training should be explored.Over the past decade, outbreaks of new or reemergent viruses such as severe acute respiratory syndrome (SARS) virus, Middle East respiratory syndrome (MERS) virus, and Zika have claimed thousands of lives and cost governments and healthcare systems billions of dollars. Because the appearance of new or transformed diseases is likely to continue, the detection and characterization of emergent diseases is an important problem. We describe a Bayesian statistical model that can detect and characterize previously unknown and unmodeled diseases from patient-care reports and evaluate its performance on historical data.Experience can lead to faster exploitation of food patches through spatial learning or other parallel processes. Past studies have indicated that hungry animals either search more intensively for food or learn better how to detect it.  https://www.selleckchem.com/products/mlt-748.html  However, fewer studies have examined the contribution of non-spatial information on the presence of food nearby to maze solving, as a parallel process to spatial learning. We exposed Cataglyphis niger ant workers to a food reward and then let them search for food in a maze. The information that food existed nearby, even without spatial information, led to faster maze solving compared to a control group that was not exposed to the food prior to the experiment. Faster solving is probably achieved by a higher number of workers entering the maze, following the information that food is present nearby. In a second experiment, we allowed the ants to make successive searches in the maze, followed by removing them after they had returned to the nest and interacted with their naïve nestmates. This procedure led to a maze-solving time in-between that displayed when removing the workers immediately after they had reached the food and preventing their return to the colony, and that of no removal. The workers that interacted upon returning to the nest might have transferred to naïve workers information, unrelated to spatial learning, that food existed nearby, and driven them to commence searching. Spatial learning, or an increase in the correct movements leading to the food reward relative to those leading to dead-ends, was only evident when the same workers were allowed to search again in the same maze. However, both non-spatial information on the presence of food that elevated search intensity and spatial learning led to faster maze solving.Research into the ability to coordinate one's movements with external cues has focussed on the use of simple rhythmic, auditory and visual stimuli, or interpersonal coordination with another person. Coordinating movements with a virtual avatar has not been explored, in the context of responses to temporal cues. To determine whether cueing of movements using a virtual avatar is effective, people's ability to accurately coordinate with the stimuli needs to be investigated. Here we focus on temporal cues, as we know from timing studies that visual cues can be difficult to follow in the timing context. Real stepping movements were mapped onto an avatar using motion capture data. Healthy participants were then motion captured whilst stepping in time with the avatar's movements, as viewed through a virtual reality headset. The timing of one of the avatar step cycles was accelerated or decelerated by 15% to create a temporal perturbation, for which participants would need to correct to, in order to remain in time. Step onset times of participants relative to the corresponding step-onsets of the avatar were used to measure the timing errors (asynchronies) between them.