744 research outputs found
Droits et appartenances dans une société fragilisée : Analyse de la légitimité populaire de l'Etat social suisse (rapport final/PNR45).
Machine learning techniques for identifying railroad ballast degradation
Railroad ballast is a layer of uniform sized crushed aggregate particles placed between, below and around the crossties. Railroad ballast transfers the load from crossties to the subgrade layer, provides lateral track stability and facilitates the drainage of water. Repeated traffic loading and environmental factors cause particle breakage, abrasion and polishing, which eventually degrade the ballast and result in fouling conditions. Traditional ballast fouling assessment includes manual sampling and identifying particle size distributions using sieve analysis. Recently, automatic ballast sampling (ABS) methods have been introduced to the railroad industry to obtain a sample of ballast and underlying layers using an approximately 1 m (3.28 ft.) long heavy duty steel tube driven into the ballast layer to depths of up to 2 m (6.56 ft.). Currently, visual-manual classification methods are used by experts to identify fouling conditions and degradation trends in the collected ballast samples. This thesis presents multiple approaches developed for the objective classification of ballast degradation using a combination of advanced machine vision and machine learning techniques. Initially, various computer vision algorithms are used to generate features associated with images of ballast cross sections at different degradation levels. Next, the generated features are used alongside a visual classification database provided by experts to develop, train, validate, and test a feedforward artificial neural network (ANN) using a supervised learning method. This work is further extended by implementing convolutional neural networks (CNNs) to serve as automatic feature generators. Finally, this approach is used on another cross-sectional ballast dataset that more closely resembles the type of ballast cross sections that can be found in the field. The findings of this study show that the proposed CNNs with an optimized topology can successfully classify ballast fouling in an effective and repeatable fashion with reasonable error levels. Further improvement of this technology holds the potential to provide a tool for consistent and automated ballast inspection and life cycle analysis intended to improve the safety and network reliability of US railroad transportation systems
Leadership Strategies for Developing and Implementing Organizational Change
Leaders in some narcotics treatment programs struggle with change development and implementation. The objective of this single-case study was to explore strategies used by leaders in a narcotics treatment program to develop and implement organizational change initiatives successfully. Participants included 4 leaders who had developed and implemented successful change initiatives repeatedly for more than 10 years in a narcotics treatment program in the southeastern United States. Bertalanffy\u27s general systems theory was the basis for the conceptual framework. Data collection included semistructured interviews of leaders of a narcotics treatment program and collection of archival data, such as reports relating to strategic planning, core value analysis, and risk assessments. Data analysis, using qualitative analysis software revealed 3 themes: communication, education through research, and resistance. The identified themes aligned with the conceptual framework, as the themes work together as a unit. Recommendations for action include further research for the application of social media in the treatment of patients. Leaders of narcotics treatment programs may use the findings to improve the success of social change development and implementation. Successful social change within these programs could result in the betterment of community relations and an increase in productive members of society who contribute to the economic health of the community
What is required to end the AIDS epidemic as a public health threat by 2030? The cost and impact of the fast-track approach
In 2011 a new Investment Framework was proposed that described how the scale-up of key HIV interventions could dramatically reduce new HIV infections and AIDS-related deaths in low and middle income countries by 2015. This framework included ambitious coverage goals for prevention and treatment services for 2015, resulting in a reduction of new HIV infections by more than half, in line with the goals of the declaration of the UN High Level Meeting in June 2011. However, the approach suggested a leveling in the number of new infections at about 1 million annually-far from the UNAIDS goal of ending AIDS by 2030. In response, UNAIDS has developed the Fast-Track approach that is intended to provide a roadmap to the actions required to achieve this goal. The Fast-Track approach is predicated on a rapid scale-up of focused, effective prevention and treatment services over the next 5 years and then maintaining a high level of programme implementation until 2030. Fast-Track aims to reduce new infections and AIDS-related deaths by 90% from 2010 to 2030 and proposes a set of biomedical, behavioral and enabling intervention targets for 2020 and 2030 to achieve that goal, including the rapid scale-up initiative for antiretroviral treatment known as 90-90-90. Compared to a counterfactual scenario of constant coverage for all services at early-2015 levels, the Fast-Track approach would avert 18 million HIV infections and 11 million deaths from 2016 to 2030 globally. This paper describes the analysis that produced these targets and the estimated resources needed to achieve them in low- and middle-income countries. It indicates that it is possible to achieve these goals with a significant push to achieve rapid scale-up of key interventions between now and 2020. The annual resources required from all sources would rise to US8.2Bn in lower middle-income countries and US$10.5Bn in upper-middle-income-countries by 2020 before declining approximately 9% by 2030
Gluing construction of initial data with Kerr-de Sitter ends
We construct initial data sets which satisfy the vacuum constraint equa-
tions of General Relativity with positive cosmologigal constant. More pre-
silely, we deform initial data with ends asymptotic to Schwarzschild-de Sitter
to obtain non-trivial initial data with exactly Kerr-de Sitter ends. The method
is inspired from Corvino's gluing method. We obtain here a extension of a
previous result for the time-symmetric case by Chru\'sciel and Pollack.Comment: 27 pages, 3 figure
On the uniqueness and global dynamics of AdS spacetimes
We study global aspects of complete, non-singular asymptotically locally AdS
spacetimes solving the vacuum Einstein equations whose conformal infinity is an
arbitrary globally stationary spacetime. It is proved that any such solution
which is asymptotically stationary to the past and future is itself globally
stationary.
This gives certain rigidity or uniqueness results for exact AdS and related
spacetimes.Comment: 18pp, significant revision of v
Assessing the effect of flood restoration on surface–subsurface interactions in Rohrschollen Island (Upper Rhine river – France) using integrated hydrological modeling and thermal infrared imaging
Rohrschollen Island is an artificial island of the large Upper Rhine river
whose geometry and hydrological dynamics are the result of engineering works
during the 19th and 20th centuries. Before its channelization, the Rhine
river was characterized by an intense hydromorphological activity which
maintained a high level of biodiversity along the fluvial corridor. This
functionality considerably decreased during the two last centuries.
In 2012, a restoration project was launched to reactivate typical alluvial
processes, including bedload transport, lateral channel dynamics, and
surface–subsurface water exchanges. An integrated hydrological model has been
applied to the area of Rohrschollen Island to assess the efficiency of the
restoration regarding surface and subsurface flows. This model is calibrated
using measured piezometric heads. Simulated patterns of water exchanges
between the surface and subsurface compartments of the island are checked
against the information derived from thermal infrared (TIR) imaging. The simulated
results are then used to better understand the evolutions of the
infiltration–exfiltration zones over time and space and to determine the
physical controls of surface–subsurface interactions on the hydrographic
network of Rohrschollen Island. The use of integrated hydrological modeling
has proven to be an efficient approach to assess the efficiency of
restoration actions regarding surface and subsurface flows.</p
The Intrinsic Origin of Spin Echoes in Dipolar Solids Generated by Strong Pi Pulses
In spectroscopy, it is conventional to treat pulses much stronger than the
linewidth as delta-functions. In NMR, this assumption leads to the prediction
that pi pulses do not refocus the dipolar coupling. However, NMR spin echo
measurements in dipolar solids defy these conventional expectations when more
than one pi pulse is used. Observed effects include a long tail in the CPMG
echo train for short delays between pi pulses, an even-odd asymmetry in the
echo amplitudes for long delays, an unusual fingerprint pattern for
intermediate delays, and a strong sensitivity to pi-pulse phase. Experiments
that set limits on possible extrinsic causes for the phenomena are reported. We
find that the action of the system's internal Hamiltonian during any real pulse
is sufficient to cause the effects. Exact numerical calculations, combined with
average Hamiltonian theory, identify novel terms that are sensitive to
parameters such as pulse phase, dipolar coupling, and system size.
Visualization of the entire density matrix shows a unique flow of quantum
coherence from non-observable to observable channels when applying repeated pi
pulses.Comment: 24 pages, 27 figures. Revised from helpful referee comments. Added
new Table IV, new paragraphs on pages 3 and 1
Pathways to Belonging and Engagement: Testing a Tailored Social Belonging Intervention for University Students
Background
Prominent theories of motivation suggest that belonging plays a critical role in student success (Connell & Wellborn, 1991). Social-belonging interventions have been shown to improve student belonging, well-being, engagement, and more—especially those from traditionally disadvantaged backgrounds (Walton & Brady, 2017). The current study aimed to explore the effects of a tailored social-belonging intervention delivered in introductory classes at VCU on students’ belonging, engagement, persistence, and achievement.
Methods
A diverse sample of first-year undergraduate students at VCU participated. To create authentic intervention materials, we collaborated with a diverse group of upper-level undergraduate student researchers who wrote narratives to present vivid stories of how they personally experienced and overcame struggles to belong. Prior to and following the intervention, students completed a survey that assessed student belonging, engagement, and social and academic fit. We also collected student demographics, achievement, and additional data from institutional records.
Results
Following the implementation of the belonging intervention, data was collected on students’ sense of belonging, their social and academic fit at the university, and other related outcomes. While most students felt as though they belonged at VCU and had the potential to succeed, there were still some students who worried whether they belonged in college.
Conclusions
From students’ responses, faculty and advisors of first-year students were given an overview on students’ current states of belonging at VCU. As an implication for future research, we argue that including diverse upper-level students as fellow researchers in this work strengthens the authenticity and effectiveness of the belonging intervention.https://scholarscompass.vcu.edu/gradposters/1171/thumbnail.jp
Calibration of the Milagro Cosmic Ray Telescope
The Milagro detector is an air shower array which uses the water Cherenkov
technique and is capable of continuously monitoring the sky at energies near 1
TeV. The detector consists of 20000 metric tons of pure water instrumented with
723 photo-multiplier tubes (PMTs). The PMTs are arranged in a two-layer
structure on a lattice of 3 m spacing covering 5000 area. The direction
of the shower is determined from the relative timing of the PMT signals,
necessitating a common time reference and amplitude slewing corrections to
improve the time resolution. The calibration system to provide these consists
of a pulsed laser driving 30 diffusing light sources deployed in the pond to
allow cross-calibration of the PMTs. The system is capable of calibrating times
and the pulse-heights from the PMTs using the time-over-threshold technique.
The absolute energy scale is provided using single muons passing through the
detector. The description of the calibration system of the Milagro detector and
its prototype Milagrito will be presented.Comment: 4 pages, submitted to the XXVI International Cosmic Ray Conferenc
- …