Solving Large Scale Instances of the Distribution Design Problem Using Data Mining

In this paper we approach the solution of large instances of the distribution design problem. The traditional approaches do not consider that the instance size can significantly reduce the efficiency of the solution process. We propose a new approach that includes compression methods to transform the original instance into a new one using data mining techniques. The goal of the transformation is to condense the operation access pattern of the original instance to reduce the amount of resources needed to solve the original instance, without significantly reducing the quality of its solution. In order to validate the approach, we tested it proposing two instance compression methods on a new model of the replicated version of the distribution design problem that incorporates generalized database objects. The experimental results show that our approach permits to reduce the computational resources needed for solving large instances by at least 65%, without significantly reducing the quality of its solution. Given the encouraging results, at the moment we are working on the design and implementation of efficient instance compression methods using other data mining techniques

COVID‑19 mitigation by digital contact tracing and contact prevention (app‑based social exposure warnings)

A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20–56%.publishedVersionFil: Soldano, Germán J. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina.Fil: Soldano, Germán J. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina.Fil: Fraire Juan A. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Fraire Juan A. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Estudios Avanzados en ingeniería y Tecnología; Argentina.Fil: Fraire Juan A. Saarland University. Saarland Informatics Campus; Saarbrücken, Germany.Fil: Finochietto, Jorge M. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.Fil: Finochietto, Jorge M. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Estudios Avanzados en ingeniería y Tecnología; Argentina.Fil: Quiroga; Rodrigo. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas; Argentina.Fil: Quiroga; Rodrigo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina

External stimuli help restore post-partum ovarian activity in Pelibuey sheep

Post-partum anestrus is a problem on farms, and its duration depends on the frequency and intensity of suckling which affects reproduction and production efficiency to become a determining economic factor. The aim of this study was to determine the post-partum reproductive response in ewe to a "male effect" with an ovulation induction protocol of five days using progesterone and the application of a metabolic restorative (MR; Metabolase ®). One hundred and twenty females were randomly assigned to one of four treatments: T1: Continuous suckling (CS; n = 29), T2: CS + MR (n = 29), T3: CS + Male Effect (ME; n = 32), and T4: CS + MR + ME. The percentage of females in ovulation, weight changes among females and lambs, the onset of estrus, calving, fecundity, and prolificacy were also determined. The ovulation percentage was higher in CS + ME and CS + MR + ME (75.0 and 73.3%) than in the other treatments. Weight changes in females and lambs were different among periods. The onset of estrus was similar for CS and CS + MR (25.9 ± 1.9 and 25.7 ± 0.7 h, respectively). The calving percentage was higher for CS + MR (86.2%) than other treatments. Male presence positively affected the postpartum cyclic ovarian re-establishment and the metabolic restorative could even improve the fertility of hair ewes in continuous suckling with similar hormone protocolKeywords: Male effect, metabolic stimulation, post-partum anestru

Simulating New Drop Test Vehicles and Test Techniques for the Orion CEV Parachute Assembly System

The Crew Exploration Vehicle Parachute Assembly System (CPAS) project is engaged in a multi-year design and test campaign to qualify a parachute recovery system for human use on the Orion Spacecraft. Test and simulation techniques have evolved concurrently to keep up with the demands of a challenging and complex system. The primary simulations used for preflight predictions and post-test data reconstructions are Decelerator System Simulation (DSS), Decelerator System Simulation Application (DSSA), and Drop Test Vehicle Simulation (DTV-SIM). The goal of this paper is to provide a roadmap to future programs on the test technique challenges and obstacles involved in executing a large-scale, multi-year parachute test program. A focus on flight simulation modeling and correlation to test techniques executed to obtain parachute performance parameters are presented

Summary of CPAS Gen II Parachute Analysis

The Orion spacecraft is currently under development by NASA and Lockheed Martin. Like Apollo, Orion will use a series of parachutes to slow its descent and splashdown safely. The Orion parachute system, known as the CEV Parachute Assembly System (CPAS), is being designed by NASA, the Engineering and Science Contract Group (ESCG), and Airborne Systems. The first generation (Gen I) of CPAS testing consisted of thirteen tests and was executed in the 2007-2008 timeframe. The Gen I tests provided an initial understanding of the CPAS parachutes. Knowledge gained from Gen I testing was used to plan the second generation of testing (Gen II). Gen II consisted of six tests: three singleparachute tests, designated as Main Development Tests, and three Cluster Development Tests. Gen II required a more thorough investigation into parachute performance than Gen I. Higher fidelity instrumentation, enhanced analysis methods and tools, and advanced test techniques were developed. The results of the Gen II test series are being incorporated into the CPAS design. Further testing and refinement of the design and model of parachute performance will occur during the upcoming third generation of testing (Gen III). This paper will provide an overview of the developments in CPAS analysis following the end of Gen I, including descriptions of new tools and techniques as well as overviews of the Gen II tests

JESÚS GARCÍA, REGINA [Material gráfico]

Copia digital. Madrid : Ministerio de Educación, Cultura y Deporte, 201

Summary of CPAS EDU Testing Analysis Results

The Orion program's Capsule Parachute Assembly System (CPAS) project is currently conducting its third generation of testing, the Engineering Development Unit (EDU) series. This series utilizes two test articles, a dart-shaped Parachute Compartment Drop Test Vehicle (PCDTV) and capsule-shaped Parachute Test Vehicle (PTV), both of which include a full size, flight-like parachute system and require a pallet delivery system for aircraft extraction. To date, 15 tests have been completed, including six with PCDTVs and nine with PTVs. Two of the PTV tests included the Forward Bay Cover (FBC) provided by Lockheed Martin. Advancements in modeling techniques applicable to parachute fly-out, vehicle rate of descent, torque, and load train, also occurred during the EDU testing series. An upgrade from a composite to an independent parachute simulation allowed parachute modeling at a higher level of fidelity than during previous generations. The complexity of separating the test vehicles from their pallet delivery systems necessitated the use the Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulator for modeling mated vehicle aircraft extraction and separation. This paper gives an overview of each EDU test and summarizes the development of CPAS analysis tools and techniques during EDU testing