Antimicrobial Photodynamic Coatings Reduce the Microbial Burden on Environmental Surfaces in Public Transportation - a Field Study in Buses

Millions of people use public transportation daily worldwide and frequently touch surfaces, thereby producing a reservoir of microorganisms on surfaces increasing the risk of transmission. Constant occupation makes sufficient cleaning difficult to achieve. Thus, an autonomous, perma-nent antimicrobial coating (AMC) could keep down the microbial burden on such surfaces. A photodynamic AMC was applied to frequently touched surfaces in buses. The microbial burden (colony forming units, cfu) was determined weekly and compared to equivalent surfaces in buses without AMC (references). The microbial burden ranged from 0 – 209 cfu/cm² on references and from 0 – 54 cfu/cm² on AMC. The means were 13.4 ± 29.6 cfu/cm² on references and 4.5 ± 8.4 cfu/cm² on AMC (p<0.001). The difference of microbial burden on AMC and references was al-most constant throughout the study. Considering a hygiene benchmark of 5 cfu/cm², the data yield an absolute risk reduction of 22.6 % and a relative risk reduction of 50.7 %. In conclusion, photo-dynamic AMC kept down the microbial burden, reducing the risk of transmission of microor-ganisms. AMC permanently and autonomously contributes to hygienic conditions on surfaces in public transportation. Photodynamic AMC therefore are suitable for reducing the microbial load and closing hygiene gaps in public transportation.

Impact assessment of climate change on groundnut yield of middle Gujarat region

The impact of projected climate change on groundnut (cv. Robut 33-1 and GG-2) yield have been studied for Anand station of middle Gujarat Agro-climatic region using PRECIS output of A2 scenario and base line data. Yield simulation study was performed by PNUTGRO (DSSAT v4.5) model. The field experiment data on groundnut cv. Robut 33-1 and GG-2 during the years 2008 to 2011 have been used to calibrate and validate the model. The weather condition as projected by A2 scenario (2070-2100) showed that there will be 13.7% higher rainfall as compared to base line (1961-90). The mean maximum and minimum temperature will be higher to the tune of 3.6 and 5.1 °C as compared to their base temperature of 19.1 and 29.8 °C respectively. Nearly 21 and 31% pod yield reduction was noted in Robut 33-1 and GG-2 as compared to their base yield during projected period. Highest yield reduction was recorded in late sowing (15th July) and cv. GG-2 and lowest yield reduction was noted in timely sowing (D1) and cv. Robut 33-1. Under projected period. 7.0 to 16.0% yield benefited by adaptation strategies, viz, fifteen days earlier shifting of sowing with one pre sowing irrigation and Application of organic manure instead of chemical fertilizer.

Anonymiced Shareable Data: Using mice to Create and Analyze Multiply Imputed Synthetic Datasets

Synthetic datasets simultaneously allow for the dissemination of research data while protecting the privacy and confidentiality of respondents. Generating and analyzing synthetic datasets is straightforward, yet, a synthetic data analysis pipeline is seldom adopted by applied researchers. We outline a simple procedure for generating and analyzing synthetic datasets with the multiple imputation software mice (Version 3.13.15) in R. We demonstrate through simulations that the analysis results obtained on synthetic data yield unbiased and valid inferences and lead to synthetic records that cannot be distinguished from the true data records. The ease of use when synthesizing data with mice along with the validity of inferences obtained through this procedure opens up a wealth of possibilities for data dissemination and further research on initially private data.

A New Mixed Estimator in Nonparametric Regression for Longitudinal Data

We introduce a new method for estimating the nonparametric regression curve for longitudinal data. This method combines two estimators: truncated spline and Fourier series. This estimation is completed by minimizing the penalized weighted least squares and weighted least squares. This paper also provides the properties of the new mixed estimator, which are biased and linear in the observations. The best model is selected using the smallest value of generalized cross-validation. The performance of the new method is demonstrated by a simulation study with a variety of time points. Then, the proposed approach is applied to a stroke patient dataset. The results show that simulated data and real data yield consistent findings.

Designing a Graphene Coating-Based Supercapacitor with Lithium Ion Electrolyte: An Experimental and Computational Study via Multiscale Modeling

Graphene electrodes are investigated for electrochemical double layer capacitors (EDLCs) with lithium ion electrolyte, the focus being the effect of the pore size distribution (PSD) of electrode with respect to the solvated and desolvated electrolyte ions. Two graphene electrode coatings are examined: a low specific surface area (SSA) xGNP-750 coating and a high SSA coating based on a-MWGO (activated microwave expanded graphene oxide). The study comprises an experimental and a computer modeling part. The experimental part includes fabrication, material characterization and electrochemical testing of an EDLC with xGNP-750 coating electrodes and electrolyte 1M LiPF6 in EC:DMC. The computational part includes simulations of the galvanostatic charge-discharge of each EDLC type, based on a continuum ion transport model taking into account the PSD of electrodes, as well as molecular modeling to determine the parameters of the solvated and desolvated electrolyte ions and their adsorption energies with each type of electrode pore surface material. Predictions, in agreement with the experimental data, yield a specific electrode capacitance of 110 F g−1 for xGNP-750 coating electrodes in electrolyte 1M LiPF6 in EC:DMC, which is three times higher than that of the high SSA a-MWGO coating electrodes in the same lithium ion electrolyte.

MULTIPLE IMPUTATION FOR ORDINARY COUNT DATA BY NORMAL DISTRIBUTION APPROXIMATION

Missing values are a problem that is often encountered in various fields and must be addressed to obtain good statistical inference such as parameter estimation. Missing values can be found in any type of data, included count data that has Poisson distributed. One solution to overcome that problem is applying multiple imputation techniques. The multiple imputation technique for the case of count data consists of three main stages, namely the imputation, the analysis, and pooling parameter. The use of the normal distribution refers to the sampling distribution using the central limit theorem for discrete distributions. This study is also equipped with numerical simulations which aim to compare accuracy based on the resulting bias value. Based on the study, the solutions proposed to overcome the missing values in the count data yield satisfactory results. This is indicated by the size of the bias parameter estimate is small. But the bias value tends to increase with increasing percentage of observation of missing values and when the parameter values are small.

An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches

As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT02915341.

Synsedimentary to Diagenetic Cu±Co Mineralization in Mesoproterozoic Pyritic Shale Driven by Magmatic-Hydrothermal Activity on the Edge of the Great Falls Tectonic Zone–Black Butte, Helena Embayment, Belt-Purcell Basin, USA: Evidence from Sulfide Re-Os Isotope Geochemistry

The ca. 1,500 to 1,325 Ma Mesoproterozoic Belt-Purcell Basin is an exceptionally preserved archive of Mesoproterozoic Earth and its paleoenvironmental conditions. The Belt-Purcell Basin is also host to world-class base metal sediment-hosted mineralization produced in a variety of settings from the rift stage of basin evolution through the subsequent influence of East Kootenay and Grenvillian orogenies. The mineral potential of this basin has not been fully realized yet. New rhenium-osmium (Re-Os) data presented here for chalcopyrite, pyrite, and black shale contribute to refine a robust genetic model for the origin of the Black Butte copper±cobalt±silver (Cu±Co±Ag) deposit hosted by the ca. >1,475 Ma Newland Formation in the Helena Embayment of the Belt-Purcell Basin in Montana, USA. Chalcopyrite Re-Os data yield an isochron age (1,488±34 Ma, unradiogenic initial 187Os/188Os composition Osi-chalcopyrite=0.13±0.11) that overlaps with the geological age of the Newland Formation. Further, the Re-Os data of synsedimentary to diagenetic massive pyrite yield evidence of resetting with an isochron age (1,358±42 Ma) coincident with the timing of the East Kootenay orogeny. The unradiogenic Osi-chalcopyrite at ca. 1,488 Ma (0.13±0.11) argues for derivation of Os from a magmatic source with a 187Os/188Os isotopic composition inherited from the upper mantle in the Mesoproterozoic (Osmantle 1,475 Ma=0.12±0.02). The unradiogenic Osi-chalcopyrite also suggests limited contamination from a continental crustal source. This source of Os and our new sulfur isotopic signatures of chalcopyrite (–4.1 to +2.1‰-VCDT) implies a dominantly magmatic source for metals. We integrate our new results and previously published geological and geochemical evidence to conceptualize a genetic model in which Cu and metals were largely contributed by moderate-temperature, reduced magmatic-hydrothermal fluids carrying reduced sulfur species with a magmatic origin and flowing as highly metalliferous fluids within the shale sequence. A subsidiary derivation of metals during thermally forced shale diagenesis is possible. Chalcopyrite mineralization replaced locally massive synsedimentary to diagenetic pyrite units close to the sediment-water interface, i.e., an ideal locus where magmatic-hydrothermal fluids could cool and the solubility of chalcopyrite would fall. We suggest that Cu mineralization was coeval with the timing of an enhanced thermal gradient in the Helena Embayment triggered until ca. 1,455 Ma by tholeiitic dike swarm that intruded into Archean basement rocks and intersected the NE-SW-trending Great Falls Tectonic Zone.