Urban Scale Modeling of Atmospheric Carbon Dioxide and Validation of Emission Inventories

There exists a pressing need for high resolution emissions inventories for cities. For greenhouse gases, cities and regions need a careful analysis of their carbon footprint to design effective policies to control and mitigate emissions. High resolution emissions inventories can be used in conjunction with meteorology models and atmospheric measurements to place top-down constraints on emissions. High resolution emissions inventories for criteria pollutants like NOx, CO, and O3 enable urban-scale air pollution modeling down to the neighborhood level. For example, the Vulcan project estimates CO2 using county-scale vehicle miles traveled (VMT) from the National Mobile Inventory Model (NMIM) County Database (NCD). The Hestia Project similarly allocates CO2 from Vulcan’s county-level inventory down to the building scale using eQUEST and building footprints. On-road transport is the most important sector for anthropogenic CO2, 38% in Portland, 32% nationally. Here we show a new model of CO2 emissions for the Portland, OR metropolitan region. The backbone is traffic counter recordings made by the Portland Bureau of Transportation at 9,352 sites over 21 years (1986-2006), augmented with PORTAL (The Portland Regional Transportation Archive Listing) freeway data. We constructed a regression model to fill in traffic network gaps using GIS data such as road class and population density. EPA MOVES was used to estimate transportation CO2 emissions. Our transportation emissions served as input into WRF meteorological modeling to simulate atmospheric CO2 at sites where frequent CO2 measurements are made. We show preliminary model results

The experience of young people receiving cognitive behavioural therapy for major depression : A qualitative study

Aim Major depressive disorder (MDD) has far reaching impacts for young people, their families and society. Cognitive behavioural therapy (CBT) is one of the first-line treatments for young people experiencing MDD; however, there is limited research examining how young people with MDD experience CBT. The aim of this study was to explore their experience and their views of this intervention. Methods We employed a qualitative research design, with semi-structured interviews and thematic analysis. Eight participants aged between 17 and 24 years who received CBT for MDD in a randomized controlled trial were recruited. Results Five themes were identified: the importance of relationship with clinician; the range of useful components within CBT; the ability for CBT to accommodate different techniques and presenting issues; the importance of checking in with clients during the process of therapy; and the impacts of MDD on therapy. Conclusions The findings highlight the importance of clinicians having a youth friendly and collaborative approach that allows a modular delivery of a range of CBT techniques to suit the client's presenting issue and formulation. There is a need to continually check how young people are responding to interventions, and to be aware of potential cognitive deficits and adjust therapy accordingly. This is a small study that provides insight into how young people with MDD experience CBT and avenues to explore for tailoring provision of CBT to enhance the therapeutic experience for this population

Digital Holography Experiments with Degraded Temporal Coherence

To simulate the effects of multiple-longitudinal modes and rapid fluctuations in center frequency, we use sinusoidal phase modulation and linewidth broadening, respectively. These effects allow us to degrade the temporal coherence of our master-oscillator laser, which we then use to conduct digital holography experiments. In turn, our results show that the coherence efficiency decreases quadratically with fringe visibility and that our measurements agree with our models to within 1.8% for sinusoidal phase modulation and 6.9% for linewidth broadening

Estimation of Atmospheric Turbulence Using Differential Motion of Extended Features in Time-lapse Imagery

We address the design, development, and testing of a pointer/tracker as a probe beam for the purpose of making high-speed, aero-optical measurements of the flow over a scaled beam director turret. The tracker uses retro-reflection of the probe beam off of a Reflexite annulus surrounding the turret. The constraints of the design required a near-total-commercial off the shelf system that could be quickly installed and removed in a rented aircraft. Baseline measurements of environmental vibrations are used to predict pointing performance; mitigation of line-of-sight jitter on the probe beam is achieved through passive isolation and the design of relay optics. Accommodation of ambient light is made with the use of wavelength filters and track algorithms. Postanalysis of measured data is compared to design estimates

Update to the Vitamin C, Thiamine and Steroids in Sepsis (VICTAS) protocol: statistical analysis plan for a prospective, multicenter, double-blind, adaptive sample size, randomized, placebo-controlled, clinical trial.

BACKGROUND: Observational research suggests that combined therapy with Vitamin C, thiamine and hydrocortisone may reduce mortality in patients with septic shock. METHODS AND DESIGN: The Vitamin C, Thiamine and Steroids in Sepsis (VICTAS) trial is a multicenter, double-blind, adaptive sample size, randomized, placebo-controlled trial designed to test the efficacy of combination therapy with vitamin C (1.5 g), thiamine (100 mg), and hydrocortisone (50 mg) given every 6 h for up to 16 doses in patients with respiratory or circulatory dysfunction (or both) resulting from sepsis. The primary outcome is ventilator- and vasopressor-free days with mortality as the key secondary outcome. Recruitment began in August 2018 and is ongoing; 501 participants have been enrolled to date, with a planned maximum sample size of 2000. The Data and Safety Monitoring Board reviewed interim results at N = 200, 300, 400 and 500, and has recommended continuing recruitment. The next interim analysis will occur when N = 1000. This update presents the statistical analysis plan. Specifically, we provide definitions for key treatment and outcome variables, and for intent-to-treat, per-protocol, and safety analysis datasets. We describe the planned descriptive analyses, the main analysis of the primary end point, our approach to secondary and exploratory analyses, and handling of missing data. Our goal is to provide enough detail that our approach could be replicated by an independent study group, thereby enhancing the transparency of the study. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03509350. Registered on 26 April 2018

Employing machine learning to predict adverse acute post-surgical outcomes following elective ulnar collateral ligament reconstruction

Background: Ulnar collateral ligament reconstruction ameliorates valgus elbow instability in various patient populations, including overhead athletes, patients with acute UCL rupture following high energy trauma, and those with chronic, subclinical elbow laxity. This study aims to explore machine learning algorithms to identify risk factors in patients undergoing elective UCL reconstruction in the ambulatory setting to predict postoperative outcomes. Methods: RStudio was used to create a filtering code to identify adult patients who underwent elective UCL reconstruction from 2008 to 2018 in the American college of surgeons national surgical quality improvement program database. Patients were analyzed using six ML algorithms, which were trained to predict outcomes such as extended length of stay, non-home discharge, and adverse events based on various patient characteristics and surgical variables. Algorithmic performance was then assessed and top performing algorithms underwent further analysis to determine relative feature importance using a permutation feature importance method. Results: ML exhibited excellent performance in predicting LOS, with an average AUC of 0.953, similar to that of logistic regression. Regarding NHD, ML demonstrated a 60.8% increase in AUC compared to LR. In predicting AAE, ML achieved an average AUC that was 12.7% higher than LR. Conclusions: The highly predictive capability of ML indicates the possibility to represent a procedure-specific complementary tool for the preoperative risk stratification process. This study provides a comprehensive analysis of UCL reconstruction in the management and outcomes of any patient, regardless of age or activity level

Fast room temperature lability of aluminosilicate zeolites

Charles University Centre of Advanced Materials (CUCAM) (OP VVV Excellent Re-search Teams, project number CZ.02.1.01/0.0/0.0/15_003/0000417) is acknowledged. PN acknowledges the Czech Science Foundation (19-21534S). This work was supported by The Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experi-mental Development and Innovations project “IT4Innovations National Supercomputing Center – LM2015070”. The UK 850 MHz solid-state NMR Facility used in this research was fund-ed by EPSRC and BBSRC (contract reference PR140003) as well as the University of Warwick including via part funding through Birmingham Science City Advanced Materials Projects 1 and 2 supported by Advantage West Midlands (AWM) and the European Regional Develop-ment Fund (ERDF). Collaborative assistance from the 850 MHz Facility Manager (Dinu Iuga, University of Warwick) is acknowledged. This work was also supported by the ERC (EU FP7 Consolidator Grant 614290 “EXONMR” and Advanced Grant 787073 “ADOR”) and the EPSRC (EP/N509759/1 and EP/N50936X/1). SEA would like to thank the Royal Society and the Wolfson Foundation for a merit award.Aluminosilicate zeolites are traditionally used in high-temperature applications at low water vapour pressures where the zeolite framework is generally considered to be stable and static. Increasingly, zeolites are being considered for applications under milder aqueous conditions. However, it has not yet been established how neutral liquid water at mild conditions affects the stability of the zeolite framework. Here, we show that covalent bonds in the zeolite chabazite (CHA) are labile when in contact with neutral liquid water, which leads to partial but fully reversible hydrolysis without framework degradation. We present ab initio calculations that predict novel, energetically viable reaction mechanisms by which Al-O and Si-O bonds rapidly and reversibly break at 300 K. By means of solid-state NMR, we confirm this prediction, demonstrating that isotopic substitution of 17O in the zeolitic framework occurs at room temperature in less than one hour of contact with enriched water.Publisher PDFPeer reviewe