Airport SMS Software Analysis

Historically, high risk industries such as aviation have attempted to respond to accidents by fixing what they find after the investigation is complete and therefore represents a reactive approach to an accident event. For many years, the industry has tried to become more proactive to these events by seeking out problems and correcting them before an accident occurs. A Safety Management System is a detailed and regimented process by which any high risk industry can try to become proactive in accident prevention. There are many tools that can be utilized to help develop this framework and accomplish this preventative goal. One such tool is SMS software. The goal of this research is to gain an understanding of the variety of software being used by airports as part of their respective Airport Safety Management Systems (SMS) strategies with the goal of providing the FAA with guidance towards recommending the use of SMS software at airports, including minimum functionality standards. We report here our initial findings

Estimation of trace gas fluxes with objectively determined basis functions using reversible-jump Markov chain Monte Carlo

Atmospheric trace gas inversions often attempt to attribute fluxes to a high-dimensional grid using observations. To make this problem computationally feasible, and to reduce the degree of under-determination, some form of dimension reduction is usually performed. Here, we present an objective method for reducing the spatial dimension of the parameter space in atmospheric trace gas inversions. In addition to solving for a set of unknowns that govern emissions of a trace gas, we set out a framework that considers the number of unknowns to itself be an unknown. We rely on the well-established reversible-jump Markov chain Monte Carlo algorithm to use the data to determine the dimension of the parameter space. This framework provides a single-step process that solves for both the resolution of the inversion grid, as well as the magnitude of fluxes from this grid. Therefore, the uncertainty that surrounds the choice of aggregation is accounted for in the posterior parameter distribution. The posterior distribution of this transdimensional Markov chain provides a naturally smoothed solution, formed from an ensemble of coarser partitions of the spatial domain. We describe the form of the reversible-jump algorithm and how it may be applied to trace gas inversions. We build the system into a hierarchical Bayesian framework in which other unknown factors, such as the magnitude of the model uncertainty, can also be explored. A pseudo-data example is used to show the usefulness of this approach when compared to a subjectively chosen partitioning of a spatial domain. An inversion using real data is also shown to illustrate the scales at which the data allow for methane emissions over north-west Europe to be resolved

Shocking Results: A Case of Malignant Catatonia

INTRODUCTION: Malignant catatonia is a life threatening disease and can be difficult to distinguish from other disorders including delirium, neuroleptic malignant syndrome, or exacerbation of mood and psychotic disorders. Catatonia includes three or more of the following symptoms: stupor, catalepsy, waxy flexibility, mutism, negativism, posturing, mannerism, stereotypy, agitation, grimacing, echolalia and echopraxia. Malignant catatonia can include autonomic instability (fever, hypertension, tachycardia), severe muscle rigidity, and nonspecific laboratory findings of leukocytosis and elevated creatinine kinase. This syndrome can lead to severe morbidity and mortality if not promptly treated. CASE DESCRIPTION: An 18 year old African American male with no past psychiatric history and a family history of schizophrenia presented with new onset of mania and psychotic symptoms including bizarre, disorganized behavior and emotional outbursts. He initially responded to olanzapine for control of his symptoms, but over time stopped the medication due to side effects. As a result, he had a return of his psychotic symptoms along with waxy flexibility, sleeping for nearly 20 hours each day, restricted affect with minimal speech, and a refusal to eat or drink. The patient responded to a lorazepam challenge putting catatonia on the differential. The patient needed high doses of lorazepam to help with catatonia and severe symptoms of mania and psychosis, including hypersexual behavior, agitation, combativeness, and bizarre and disorganized thought content. With his symptoms, hypertension, and elevated creatine kinase, electroconvulsive therapy (ECT) was initiated for treatment of malignant catatonia. He responded well to six sessions with total resolution of symptoms. After discharge, he was admitted to our community assertiveness program and he continued to do well with low dose lorazepam, mood stabilizer and antipsychotic which were added for maintenance treatment of his mood and psychotic symptoms. Over several months, his outpatient psychiatrist slowly tapered the lorazepam and he continues to have good control of his mood and psychotic symptoms with no return of catatonia symptoms. DISCUSSION: First line treatment of catatonia is scheduled doses of lorazepam. However, in severe cases such as malignant catatonia, ECT should be initiated as soon as possible. The response rate to malignant catatonia is higher with ECT versus treatment with lorazepam alone. On review of case reports, it is beneficial to start ECT within five days of onset of symptoms to lower mortality rates. It is important to have catatonia on a differential diagnosis for patients presenting with mental status changes to ensure timely treatment is initiated.N

Advancing Scientific Understanding of the Global Methane Budget in Support of the Paris Agreement

The 2015 Paris Agreement of the United Nations Framework Convention on Climate Change aims to keep global average temperature increases well below 2 °C of preindustrial levels in the Year 2100. Vital to its success is achieving a decrease in the abundance of atmospheric methane (CH4), the second most important anthropogenic greenhouse gas. If this reduction is to be achieved, individual nations must make and meet reduction goals in their nationally determined contributions, with regular and independently verifiable global stock taking. Targets for the Paris Agreement have been set, and now the capability must follow to determine whether CH4 reductions are actually occurring. At present, however, there are significant limitations in the ability of scientists to quantify CH4 emissions accurately at global and national scales and to diagnose what mechanisms have altered trends in atmospheric mole fractions in the past decades. For example, in 2007, mole fractions suddenly started rising globally after a decade of almost no growth. More than a decade later, scientists are still debating the mechanisms behind this increase. This study reviews the main approaches and limitations in our current capability to diagnose the drivers of changes in atmospheric CH4 and, crucially, proposes ways to improve this capability in the coming decade. Recommendations include the following: (i) improvements to process‐based models of the main sectors of CH4 emissions—proposed developments call for the expansion of tropical wetland flux measurements, bridging remote sensing products for improved measurement of wetland area and dynamics, expanding measurements of fossil fuel emissions at the facility and regional levels, expanding country‐ specific data on the composition of waste sent to landfill and the types of wastewater treatment systems implemented, characterizing and representing temporal profiles of crop growing seasons, implementing parameters related to ruminant emissions such as animal feed, and improving the detection of small fires associated with agriculture and deforestation; (ii) improvements to measurements of CH4 mole fraction and its isotopic variations—developments include greater vertical profiling at background sites, expanding networks of dense urban measurements with a greater focus on relatively poor countries, improving the precision of isotopic ratio measurements of 13CH4, CH3D, 14CH4, and clumped isotopes, creating isotopic reference materials for international‐scale development, and expanding spatial and temporal characterization of isotopic source signatures; and (iii) improvements to inverse modeling systems to derive emissions from atmospheric measurements—advances are proposed in the areas of hydroxyl radical quantification, in systematic uncertainty quantification through validation of chemical transport models, in the use of source tracers for estimating sector‐level emissions, and in the development of time and spaceresolved national inventories. These and other recommendations are proposed for the major areas of CH4 science with the aim of improving capability in the coming decade to quantify atmospheric CH4 budgets on the scales necessary for the success of climate policies. Plain Language Summary Methane is the second largest contributor to climate warming from human activities since preindustrial times. Reducing human‐made emissions by half is a major component of the 2015 Paris Agreement target to keep global temperature increases well below 2 °C. In parallel to the methane emission reductions pledged by individual nations, new capabilities are needed to determine independently whether these reductions are actually occurring and whether methane concentrations in the atmosphere are changing for reasons that are clearly understood. At present significant challenges limit the ability of scientists to identify the mechanisms causing changes in atmospheric methane. This study reviews current and emerging tools in methane science and proposes major advances needed in the coming decade to achieve this crucial capability. We recommend further developing the models that simulate the processes behind methane emissions, improving atmospheric measurements of methane and its major carbon and hydrogen isotopes, and advancing abilities to infer the rates of methane being emitted and removed from the atmosphere from these measurements. The improvements described here will play a major role in assessing emissions commitments as more cities, states, and countries report methane emission inventories and commit to specific emission reduction targets. </div

Quasi-normal frequencies: Key analytic results

The study of exact quasi-normal modes [QNMs], and their associated quasi-normal frequencies [QNFs], has had a long and convoluted history - replete with many rediscoveries of previously known results. In this article we shall collect and survey a number of known analytic results, and develop several new analytic results - specifically we shall provide several new QNF results and estimates, in a form amenable for comparison with the extant literature. Apart from their intrinsic interest, these exact and approximate results serve as a backdrop and a consistency check on ongoing efforts to find general model-independent estimates for QNFs, and general model-independent bounds on transmission probabilities. Our calculations also provide yet another physics application of the Lambert W function. These ideas have relevance to fields as diverse as black hole physics, (where they are related to the damped oscillations of astrophysical black holes, to greybody factors for the Hawking radiation, and to more speculative state-counting models for the Bekenstein entropy), to quantum field theory (where they are related to Casimir energies in unbounded systems), through to condensed matter physics, (where one may literally be interested in an electron tunelling through a physical barrier).Comment: V1: 29 pages; V2: Reformatted, 31 pages. Title changed to reflect major additions and revisions. Now describes exact QNFs for the double-delta potential in terms of the Lambert W function. V3: Minor edits for clarity. Four references added. No physics changes. Still 31 page

Lewy Body Dementia Association\u27s Research Centers of Excellence Program: Inaugural Meeting Proceedings.

The first Lewy Body Dementia Association (LBDA) Research Centers of Excellence (RCOE) Investigator\u27s meeting was held on December 14, 2017, in New Orleans. The program was established to increase patient access to clinical experts on Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson\u27s disease dementia (PDD), and to create a clinical trials-ready network. Four working groups (WG) were created to pursue the LBDA RCOE aims: (1) increase access to high-quality clinical care, (2) increase access to support for people living with LBD and their caregivers, (3) increase knowledge of LBD among medical and allied (or other) professionals, and (4) create infrastructure for a clinical trials-ready network as well as resources to advance the study of new therapeutics

Is treatment "intensity" associated with healthier lifestyle choices?:An application of the dose response function

Healthy lifestyle choices and doctor consultations can be substitutes or complements in the health production function. In this paper we consider the relation between the number of doctor consultations and the frequency of patient physical activity. We use a novel application of the Dose-Response Function model proposed by Hirano and Imbens (2004) to deal with treatment endogeneity under the no unmeasured confounding assumption. Our application takes account of unobserved heterogeneity and uses dynamic non-linear models for the treatment and outcome variables of interest. Using seven waves of the British Household Panel Survey, we find that higher treatment intensity and frequency of physical activity are inversely related. We show that accounting for both treatment selection and unobserved heterogeneity halves the size of this relationship. An additional doctor consultation is associated with a 0.5 percentage point reduction in the probability of undertaking vigorous physical activity. Our results hold for a sub-sample visiting the doctor for health check-ups, and are shown to be robust using instrumental variables