CVD grown GaSbxN1-x films as visible-light active photoanodes.

The III-V semiconductor GaN is a promising material for photoelectrochemical (PEC) cells, however the large bandgap of 3.45 eV is a considerable hindrance for the absorption of visible light. Therefore, the substitution of small amounts of N anions by isovalent Sb is a promising route to lower the bandgap and thus increase the PEC activity under visible light. Herein we report a new chemical vapor deposition (CVD) process utilizing the precursors bis(N,N'-diisopropyl-2-methyl-amidinato)-methyl gallium (III) and triphenyl antimony (TPSb) for the growth of GaSbxN1-x alloys. X-ray diffraction (XRD) and scanning electron microscopy (SEM) measurements show crystalline and homogeneous thin films at deposition temperatures in the range of 500-800 °C. Rutherford backscattering spectrometry (RBS) combined with nuclear reaction analysis (NRA) shows an incorporation of 0.2-0.7 at% antimony into the alloy, which results in a slight bandgap decrease (up to 0.2 eV) accompanied by enhanced sub-bandgap optical response. While the resulting photoanodes are active under visible light, the external quantum efficiencies remained low. Intriguingly, the best performing films exhibits the lowest charge carrier mobility according to time resolved THz spectroscopy (TRTS) and microwave conductivity (TRMC) measurements, which showed mobilities of up to 1.75 cm2 V-1 s-1 and 1.2 × 10-2 cm2 V-1 s-1, for each timescale, respectively.

Automatable Distributed Regression Analysis of Vertically Partitioned Data Facilitated by PopMedNet: Feasibility and Enhancement Study.

BACKGROUND: In clinical research, important variables may be collected from multiple data sources. Physical pooling of patient-level data from multiple sources often raises several challenges, including proper protection of patient privacy and proprietary interests. We previously developed an SAS-based package to perform distributed regression-a suite of privacy-protecting methods that perform multivariable-adjusted regression analysis using only summary-level information-with horizontally partitioned data, a setting where distinct cohorts of patients are available from different data sources. We integrated the package with PopMedNet, an open-source file transfer software, to facilitate secure file transfer between the analysis center and the data-contributing sites. The feasibility of using PopMedNet to facilitate distributed regression analysis (DRA) with vertically partitioned data, a setting where the data attributes from a cohort of patients are available from different data sources, was unknown. OBJECTIVE: The objective of the study was to describe the feasibility of using PopMedNet and enhancements to PopMedNet to facilitate automatable vertical DRA (vDRA) in real-world settings. METHODS: We gathered the statistical and informatic requirements of using PopMedNet to facilitate automatable vDRA. We enhanced PopMedNet based on these requirements to improve its technical capability to support vDRA. RESULTS: PopMedNet can enable automatable vDRA. We identified and implemented two enhancements to PopMedNet that improved its technical capability to perform automatable vDRA in real-world settings. The first was the ability to simultaneously upload and download multiple files, and the second was the ability to directly transfer summary-level information between the data-contributing sites without a third-party analysis center. CONCLUSIONS: PopMedNet can be used to facilitate automatable vDRA to protect patient privacy and support clinical research in real-world settings.

Distributed Regression Analysis Application in Large Distributed Data Networks: Analysis of Precision and Operational Performance.

BACKGROUND: A distributed data network approach combined with distributed regression analysis (DRA) can reduce the risk of disclosing sensitive individual and institutional information in multicenter studies. However, software that facilitates large-scale and efficient implementation of DRA is limited. OBJECTIVE: This study aimed to assess the precision and operational performance of a DRA application comprising a SAS-based DRA package and a file transfer workflow developed within the open-source distributed networking software PopMedNet in a horizontally partitioned distributed data network. METHODS: We executed the SAS-based DRA package to perform distributed linear, logistic, and Cox proportional hazards regression analysis on a real-world test case with 3 data partners. We used PopMedNet to iteratively and automatically transfer highly summarized information between the data partners and the analysis center. We compared the DRA results with the results from standard SAS procedures executed on the pooled individual-level dataset to evaluate the precision of the SAS-based DRA package. We computed the execution time of each step in the workflow to evaluate the operational performance of the PopMedNet-driven file transfer workflow. RESULTS: All DRA results were precise (<10-12), and DRA model fit curves were identical or similar to those obtained from the corresponding pooled individual-level data analyses. All regression models required less than 20 min for full end-to-end execution. CONCLUSIONS: We integrated a SAS-based DRA package with PopMedNet and successfully tested the new capability within an active distributed data network. The study demonstrated the validity and feasibility of using DRA to enable more privacy-protecting analysis in multicenter studies.

Cellulose Nanocrystal-Templated Tin Dioxide Thin Films for Gas Sensing.

Porous tin dioxide is an important low-cost semiconductor applied in electronics, gas sensors, and biosensors. Here, we present a versatile template-assisted synthesis of nanostructured tin dioxide thin films using cellulose nanocrystals (CNCs). We demonstrate that the structural features of CNC-templated tin dioxide films strongly depend on the precursor composition. The precursor properties were studied by using low-temperature nuclear magnetic resonance spectroscopy of tin tetrachloride in solution. We demonstrate that it is possible to optimize the precursor conditions to obtain homogeneous precursor mixtures and therefore highly porous thin films with pore dimensions in the range of 10-20 nm (ABET = 46-64 m2 g-1, measured on powder). Finally, by exploiting the high surface area of the material, we developed a resistive gas sensor based on CNC-templated tin dioxide. The sensor shows high sensitivity to carbon monoxide (CO) in ppm concentrations and low cross-sensitivity to humidity. Most importantly, the sensing kinetics are remarkably fast; both the response to the analyte gas and the signal decay after gas exposure occur within a few seconds, faster than in standard SnO2-based CO sensors. This is attributed to the high gas accessibility of the very thin porous film.

A Query Workflow Design to Perform Automatable Distributed Regression Analysis in Large Distributed Data Networks.

INTRODUCTION: Patient privacy and data security concerns often limit the feasibility of pooling patient-level data from multiple sources for analysis. Distributed data networks (DDNs) that employ privacy-protecting analytical methods, such as distributed regression analysis (DRA), can mitigate these concerns. However, DRA is not routinely implemented in large DDNs. OBJECTIVE: We describe the design and implementation of a process framework and query workflow that allow automatable DRA in real-world DDNs that use PopMedNet™, an open-source distributed networking software platform. METHODS: We surveyed and catalogued existing hardware and software configurations at all data partners in the Sentinel System, a PopMedNet-driven DDN. Key guiding principles for the design included minimal disruptions to the current PopMedNet query workflow and minimal modifications to data partners' hardware configurations and software requirements. RESULTS: We developed and implemented a three-step process framework and PopMedNet query workflow that enables automatable DRA: 1) assembling a de-identified patient-level dataset at each data partner, 2) distributing a DRA package to data partners for local iterative analysis, and 3) iteratively transferring intermediate files between data partners and analysis center. The DRA query workflow is agnostic to statistical software, accommodates different regression models, and allows different levels of user-specified automation. DISCUSSION: The process framework can be generalized to and the query workflow can be adopted by other PopMedNet-based DDNs. CONCLUSION: DRA has great potential to change the paradigm of data analysis in DDNs. Successful implementation of DRA in Sentinel will facilitate adoption of the analytic approach in other DDNs.

Facile Uptake and Release of Ammonia by Nickel Halide Ammines.

Although major difficulties are experienced for hydrogen- storage materials to meet performance requirements for mobile applications, alternative fuel cell feedstocks such as ammonia can be stored in the solid state safely at high capacity. We herein describe the NiX2 -NH3 (X=Cl, Br, I) systems and demonstrate their exceptional suitability for NH3 storage (up to 43 wt % NH3 with desorption that begins at 400 K). The structural effects that result from the uptake of NH3 were studied by powder X-ray diffraction (PXD), FTIR spectroscopy and SEM. NH3 release at elevated temperatures was followed by in situ PXD. The cycling capabilities and air stability of the systems were also explored. NH3 is released from the hexaammines in a three-step process to yield the diammine, monoammine and NiX2 dihalides respectively and (re)ammoniation occurs readily at room temperature. The hexaammines do not react with air after several hours of exposure.

Near real-time adverse drug reaction surveillance within population-based health networks: methodology considerations for data accrual.

PURPOSE: This study describes practical considerations for implementation of near real-time medical product safety surveillance in a distributed health data network. METHODS: We conducted pilot active safety surveillance comparing generic divalproex sodium to historical branded product at four health plans from April to October 2009. Outcomes reported are all-cause emergency room visits and fractures. One retrospective data extract was completed (January 2002-June 2008), followed by seven prospective monthly extracts (January 2008-November 2009). To evaluate delays in claims processing, we used three analytic approaches: near real-time sequential analysis, sequential analysis with 1.5 month delay, and nonsequential (using final retrospective data). Sequential analyses used the maximized sequential probability ratio test. Procedural and logistical barriers to active surveillance were documented. RESULTS: We identified 6586 new users of generic divalproex sodium and 43,960 new users of the branded product. Quality control methods identified 16 extract errors, which were corrected. Near real-time extracts captured 87.5% of emergency room visits and 50.0% of fractures, which improved to 98.3% and 68.7% respectively with 1.5 month delay. We did not identify signals for either outcome regardless of extract timeframe, and slight differences in the test statistic and relative risk estimates were found. CONCLUSIONS: Near real-time sequential safety surveillance is feasible, but several barriers warrant attention. Data quality review of each data extract was necessary. Although signal detection was not affected by delay in analysis, when using a historical control group differential accrual between exposure and outcomes may theoretically bias near real-time risk estimates towards the null, causing failure to detect a signal.

Herpes zoster and postherpetic neuralgia surveillance using structured electronic data.

OBJECTIVE: To develop electronic algorithms for rapid, automated surveillance for herpes zoster and postherpetic neuralgia (PHN) using codified electronic health data. PATIENTS AND METHODS: We attempted to identify every case of herpes zoster and PHN arising between January 1 and December 31, 2008, within the electronic medical record of a 560,000-patient ambulatory practice using an array of diagnosis codes; intervals between herpes zoster encounters; and prescriptions for analgesics, anticonvulsants, and antidepressants. We assessed the sensitivity and positive predictive value (PPV) of each screening criterion by medical record review and then integrated multiple criteria into combination algorithms to optimize sensitivity and PPV. We applied the optimized algorithms to the practice's historical data spanning January 1, 1996, to December 31, 2008, to assess for changes in the annual incidence of PHN. RESULTS: The International Classification of Diseases, Ninth Revision, code 053 detected herpes zoster with 98% sensitivity and 93% PPV. A combination algorithm including diagnosis codes, visit intervals, and prescriptions detected PHN with 86% sensitivity and 78% PPV. Between 1996 and 2008, the age- and sex-adjusted annual incidence of PHN rose from 0.18 to 0.47 cases per 1000 patients, and the proportion of herpes zoster patients progressing to PHN rose from 5.4% to 17.6%. CONCLUSION: Novel algorithms incorporating multiple streams of electronic health data can reasonably detect herpes zoster and PHN. These algorithms could facilitate meaningful public health surveillance using electronic health data. The incidence of PHN may be increasing.

Uncontrolled asthma in a commercially insured population from 2002 to 2007: trends, predictors, and costs.

OBJECTIVE: Uncontrolled asthma leads to preventable morbidity and increased health care utilization. The authors examined trends, predictors, and costs of uncontrolled asthma over 5 years in a large health plan population. METHODS: The authors retrospectively examined administrative health claims data from mid-2000 to mid-2007 on patients with asthma aged 1 to 56 years (n = 54,653 patient-years, 28,595 unique patients). Uncontrolled asthma events were defined as > or =2 oral steroid fills or > or =5 short-acting beta(2)-agonist (SABA) fills over 12 months, or an asthma-related hospitalization or emergency department (ED) visit. Multivariate generalized mixed regression models determined patient- and neighborhood-level predictors for uncontrolled asthma events. The authors compared asthma-related costs for patients with and without uncontrolled asthma events. RESULTS: In 2002-2003, 39% of patients had > or =1 uncontrolled asthma event. Most frequent were high use of rescue asthma medications. Asthma-related hospitalizations and ED visits were infrequent. The percentage having uncontrolled asthma events decreased significantly over time to 27% in 2006-2007, due to a decreased rate of frequent SABA fills. Males and adults > or =24 years had higher odds of medication-based uncontrolled asthma events, whereas residence in neighborhoods with more minorities and lower educational attainment was associated with ED visits or hospitalizations. Patients with uncontrolled asthma events had significantly higher asthma-related costs. CONCLUSIONS: In this population, the proportion of patients with uncontrolled asthma, particularly as indicated by high SABA fills, decreased over a 5-year period. Several individual- and neighborhood-level characteristics were associated with uncontrolled asthma events. Clinicians and health plans can identify higher-risk patients in order to target asthma management strategies and reduce asthma-related morbidity and its associated costs.