The Art of Saying Goodbye

This paper contains a memoir and artist statement. I determined my relationship to a small town in Iowa, my personal tragedy and friendship. I chose to focus the story on the course of one year in my life, specifically, my senior year of high school. During this time, two defining moments of my life happened in rapid succession, which quickly led to the downfall of several close friendships. After leaving and removing myself from this situation, I came to realize those I blamed, my friends and the town as whole, perhaps deserved more credit than I was giving them. Throughout the course of this project, I also set about researching what makes a person connected to their town and how this connectedness determines desire to leave. These themes tied into my story by informing the background and reasoning used to categorize groups of people. These themes are place attachment, which is the relationship and bond one shares with the place they live, and solastalgia, which is the feeling of nostalgia for a place of lost solace. During the course of this project I found memoir and nonfiction story telling effective tools for explaining an experience that may not be universal but present a universally recognized feeling

Health Information Technology (HIT)

This history for the Health Information Technology (HIT) program was written to commemorate DMACC\u27s 50th anniversary celebration during the 2015-16 academic year

Preliminary Solar Sail Design and Fabrication Assessment: Spinning Sail Blade, Square Sail Sheet

Blade design aspects most affecting producibility and means of measurement and control of length, scallop, fullness and straightness requirements and tolerances were extensively considered. Alternate designs of the panel seams and edge reinforcing members are believed to offer advantages of seam integrity, producibility, reliability, cost and weight. Approaches to and requirements for highly specialized metalizing methods, processes and equipment were studied and identified. Alternate methods of sail blade fabrication and related special machinery, tooling, fixtures and trade offs were examined. A preferred and recommended approach is also described. Quality control plans, inspection procedures, flow charts and special test equipment associated with the preferred manufacturing method were analyzed and are discussed

Closing the gap: Optimizing Guidance and Control Networks through Neural ODEs

We improve the accuracy of Guidance & Control Networks (G&CNETs), trained to represent the optimal control policies of a time-optimal transfer and a mass-optimal landing, respectively. In both cases we leverage the dynamics of the spacecraft, described by Ordinary Differential Equations which incorporate a neural network on their right-hand side (Neural ODEs). Since the neural dynamics is differentiable, the ODEs sensitivities to the network parameters can be computed using the variational equations, thereby allowing to update the G&CNET parameters based on the observed dynamics. We start with a straightforward regression task, training the G&CNETs on datasets of optimal trajectories using behavioural cloning. These networks are then refined using the Neural ODE sensitivities by minimizing the error between the final states and the target states. We demonstrate that for the orbital transfer, the final error to the target can be reduced by 99% on a single trajectory and by 70% on a batch of 500 trajectories. For the landing problem the reduction in error is around 98-99% (position) and 40-44% (velocity). This step significantly enhances the accuracy of G&CNETs, which instills greater confidence in their reliability for operational use. We also compare our results to the popular Dataset Aggregation method (DaGGER) and allude to the strengths and weaknesses of both methods

Guidance and Control Networks with Periodic Activation Functions

Inspired by the versatility of sinusoidal representation networks (SIRENs), we present a modified Guidance & Control Networks (G&CNETs) variant using periodic activation functions in the hidden layers. We demonstrate that the resulting G&CNETs train faster and achieve a lower overall training error on three different control scenarios on which G&CNETs have been tested previously. A preliminary analysis is presented in an attempt to explain the superior performance of the SIREN architecture for the particular types of tasks that G&CNETs excel on

Prevalence of Problem Drug Use and Injecting Drug Use in Luxembourg: A Longitudinal and Methodological Perspective.

To estimate the prevalence of problem drug use (PDU) and injecting drug use (IDU) in Luxembourg and analyze trends between 1997 and 2009. To assess the feasibility of prevalence estimations based on drug use surveillance systems. Methods: Serial multi-method PDU/IDU prevalence estimations based upon capture-recapture, Poisson regression, multiplier and back-calculation methods. Comparative analysis of methods and assessment of their robustness to variations of external factors. Results: National PDU and IDU prevalence rates were estimated at 6.16/1,000 (95% CI 4.62/1,000 to 7.81/1,000) and 5.68/1,000 (95% CI 4.53/1,000 to 6.85/1,000) inhabitants aged 15–64 years, respectively. Absolute prevalence and prevalence rates of PDU increased between 1997 and 2000 and declined from 2003 onwards, whereas IDU absolute prevalence and prevalence rates witnessed an increasing trend between 1997 and 2007. Conclusions: Drug use surveillance systems can be valuable instruments for the estimation and trend analysis of drug misuse prevalence given multiple methods are applied that rely on serial and representative data from different sources and different settings, control multiple counts and build upon standardized and sustained data collection routines. The described institutional contact indicator revealed to be a useful tool in the context of PDU/IDU prevalence estimations and thus contributes to enhancing evidence-based drug policy planning

A hepatitis A, B, C and HIV prevalence and risk factor study in ever injecting and non-injecting drug users in Luxembourg associated with HAV and HBV immunisations

<p>Abstract</p> <p>Background</p> <p>In Luxembourg, viral hepatitis and HIV infection data in problem drug users (PDUs) are primarily based on self-reporting. Our study aimed to determine the prevalence of HAV, HBV, HCV and HIV infections in ever injecting (IDUs) and non-injecting drug users (nIDUs) including inherent risk factors analysis for IDUs. Secondary objectives were immunisation against HAV and HBV, referral to care and treatment facilities as well as reduction in risk behaviour.</p> <p>Methods</p> <p>A nationwide, cross-sectional multi-site survey, involving 5 in-, 8 out-treatment and 2 prison centres, included both an assisted questionnaire (n = 368) and serological detection of HIV and Hepatitis A, B, C (n = 334). A response rate of 31% resulted in the participation of 310 IDUs and 58 nIDUs.</p> <p>Risk factors such as drug use, sexual behaviour, imprisonment, protection and health knowledge (HAV, HBV status and immunisations, HCV, HIV), piercing/tattoo and use of social and medical services were studied by means of chi2 and logistic models.</p> <p>Results</p> <p>Seroprevalence results for IDUs were 81.3% (218/268, 95%CI=[76.6; 86.0]) for HCV, 29.1% (74/254, 95%CI=[25.5;34.7 ]) for HBV (acute/chronic infection or past cured infection), 2.5% (5/202, 95%CI=[0.3; 4.6]) for HIV-1 and 57.1% (108/189, 95%CI=[50.0; 64.1]) for HAV (cured infections or past vaccinations). Seroprevalence results for nIDUs were 19.1% (9/47, 95%CI=[7.9;30.3]) for HCV, 8.9% (4/45, 95%CI=[0.6;17.2]) for HBV (acute/chronic infection or past cured infection), 4.8% (2/42, 95%CI=[-1.7;11.3]) for HIV-1 and 65.9% (27/41, 95%CI=[51.4;80.4]) for HAV. Prisoners showed the highest rates for all infections. Age, imprisonment and setting of recruitment were statistically associated with HCV seropositivity. Age, speedball career and nationality were significantly associated with HBV seropositivity. Only 56% of the participants in outpatient centres collected their serology results and 43 doses of vaccine against HAV and/or HBV were administered.</p> <p>Conclusions</p> <p>Despite the existing national risk-reduction strategies implemented since 1993, high prevalence of HCV and HBV infections in injecting drug users is observed. Our study showed that implementing risk-prevention strategies, including immunisation remains difficult with PDUs. Improvement should be looked for by the provision of field healthcare structures providing tests with immediate results, advice, immunisation or treatment if appropriate.</p

Colorado Native Plant Society Newsletter, Vol. 3 No. 2, March-April 1979

The Colorado Native Plant Society Newsletter will be published on a bimonthly basis. The contents will consist primarily of a calendar of events, notes of interest, editorials, listings of new members and conservation news. Until there is a Society journal, the Newsletter will include short articles also. The deadline for the Newsletter is one month prior to its release.https://epublications.regis.edu/aquilegia/1013/thumbnail.jp

Optimality Principles in Spacecraft Neural Guidance and Control

Spacecraft and drones aimed at exploring our solar system are designed to operate in conditions where the smart use of onboard resources is vital to the success or failure of the mission. Sensorimotor actions are thus often derived from high-level, quantifiable, optimality principles assigned to each task, utilizing consolidated tools in optimal control theory. The planned actions are derived on the ground and transferred onboard where controllers have the task of tracking the uploaded guidance profile. Here we argue that end-to-end neural guidance and control architectures (here called G&CNets) allow transferring onboard the burden of acting upon these optimality principles. In this way, the sensor information is transformed in real time into optimal plans thus increasing the mission autonomy and robustness. We discuss the main results obtained in training such neural architectures in simulation for interplanetary transfers, landings and close proximity operations, highlighting the successful learning of optimality principles by the neural model. We then suggest drone racing as an ideal gym environment to test these architectures on real robotic platforms, thus increasing confidence in their utilization on future space exploration missions. Drone racing shares with spacecraft missions both limited onboard computational capabilities and similar control structures induced from the optimality principle sought, but it also entails different levels of uncertainties and unmodelled effects. Furthermore, the success of G&CNets on extremely resource-restricted drones illustrates their potential to bring real-time optimal control within reach of a wider variety of robotic systems, both in space and on Earth