An Assessment of Disinfection-Related Water Chemistry at Public Pools and Spas in Louisville, Kentucky

The growth in the number of pools to more than 7.4 million in the U.S. has been accompanied by a rise in recreational water illnesses (RWIs). Effective pool management, though, can mitigate RWI risks. Inadequate management presumably occurs more frequently where training is less formalized and/or pool operation is a minor aspect of the job of the responsible pool manager(s). During summer 2018, weekly evaluations were performed at public venues in Louisville, Kentucky. Disinfectant levels and other items were monitored and compared with venue-specific (pool or spa) criteria. Among 1,312 venue surveys, 1,173 (89.4%) met criteria and 139 (10.6%) did not meet criteria. Overall, multivariable logistic regression showed a significant association between the likelihood of a venue meeting criteria and setting type. Specifically, hotels had 120% increased odds of not meeting criteria (adjusted odds ratio = 2.2; 95% confidence interval [1.3, 3.8]) compared with other settings. Despite spas having an 80% elevated odds of not meeting criteria compared with pools in a univariate analysis, upon adjusting for setting, spas were not associated with an increased risk of not meeting criteria. Research identifying reasons for these differences in meeting criteria between settings would be beneficial for informing public health interventions for aquatic environments

4,5-Dimethoxy-2-nitrobenzohydrazides and 1-(1-Benzylpiperidin-4-yl)ethan-1-ones as Potential Antioxidant/Cholinergic Endowed Small Molecule Leads

The objective of this research is to generate leads for developing our ultimate poly-active molecules with utility in central nervous system (CNS) diseases. Indeed, poly-active molecules capable of mitigating brain free radical damage while enhancing acetylcholine signaling (via cholinesterase inhibition) are still being sought for combating Alzheimer’s disease (AD). We differentiate “poly-active” agents from “multi-target” ones by defining them as single molecular entities designed to target only specific contributory synergistic pharmacologies in a disease. For instance, in AD, free radicals either initiate or act in synergy with other pharmacologies, leading to disease worsening. For this preliminary report, a total of 14 (i.e., 4,5-dimethoxy-2-nitrobenzohydrazide plus 1-(1-benzylpiperidin-4-yl)ethan-1-one) derivatives were synthesized and screened, in silico and in vitro, for their ability to scavenge free radicals and inhibit acetylcholinesterase (AChE)/butyrylcholinesterase (BuChE) enzymes. Overall, six derivatives (4a, 4d, 4e, 4f, 4g, 9b) exhibited potent (\u3e30%) antioxidant properties in the oxygen radical absorbance capacity (ORAC) assay. The antioxidant values were either comparable or more potent than the comparator molecules (ascorbic acid, resveratrol, and trolox). Only three compounds (4d, 9a, 9c) yielded modest AChE/BuChE inhibitions (\u3e10%). Please note that a SciFinder substance data base search confirmed that most of the compounds reported herein are new, except 9a and 9c which are also commercially available

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Carbon Monoxide Exposure Potential Associated With the Use of Recreational Watercraft

Carbon monoxide (CO) is a colorless and odorless gas generated from incomplete combustion of hydrocarbon-based fuels. Exposure to elevated CO concentrations can cause an array of health problems or even death. Of increasing concern are CO-related poisonings and fatalities associated with recreational watercraft. From 2005–2018, there were 78 known deaths of people due to CO associated with the use of recreational watercraft in the U.S. The incidence, however, is likely higher due to many CO poisoning-related deaths being inaccurately attributed to drowning instead of CO poisoning. To examine the significance of this public health hazard, a range of plausible exposures were characterized by measuring instantaneous CO concentrations at 17 sampling locations on or near the stern of four recreational boats. Observed CO concentrations were highest in samples proximal to the engine exhaust manifold, with maximum concentrations for the four boats being 42,600 ppm, 2,550 ppm, 6,100 ppm, and 3,700 ppm, respectively. Continuous CO monitoring was performed at a fixed location near the passenger seat in the back of each boat. Comparing our monitoring results with thresholds set by the U.S. Environmental Protection Agency, National Institute for Occupational Safety and Health, and World Health Organization demonstrates that many CO concentrations exceed or nearly exceed established exposure thresholds. Thus, environmental health and public safety professionals must remain aware of this hazard and examine administrative and engineering controls that reduce watercraft-related CO exposures and prevent injuries and drowning related to CO

The regulatory dilemma: an agent-based approach to policy making within innovation systems

Government regulation plays a pivotal role in influencing the innovation activities of companies, industries and whole economies. However, sound regulation must be based on an understanding of how a policy change will affect the behaviour of various actors in the market. This implies that some form of predictive modelling is necessary for intelligent policy formation. With this in mind, an ‘almost zerointelligent’ agent-based model is developed to represent typical market dynamics. The agents make price and production decisions and decide whether or not to develop or imitate a product based on a pre-defined ‘research’ and ‘imitation” ratings. The findings illustrate a Pareto Optimal line where both consumers and companies prefer the development of new products; however, different imitation rates create opposite results. Interestingly, policy changes in environments where imitation is already low, seems to cause larger impacts on the system. Furthermore, the findings also suggest that when regulation encourages imitation, improvements to consumers or companies can be made without hurting the other as much. These preliminary results set the foundation for future models that use regulation to steer the system of innovation towards these preferred outcomes

Mesogenic behaviour of isomeric bent-core 6-oxoverdazyls: 1,3-vrs 1,5-substitution pattern

<p>Two series of isomeric bent-core derivatives of 6-oxoverdazyl, with alkyl and partially fluorinated alkyl chains, were investigated by thermo-optical, powder X-ray diffraction and electron paramagnetic resonance methods in the pure state and binary mixtures. The results revealed that the substitution position of the arms at the verdazyl ring (1,5 vs. 1,3) strongly affects mesogenic behaviour. Steric (torsion and bending angles) and dipolar factors in both isomers are considered.</p