1,005 research outputs found
Resources in the British Isles of interest to language arts and dramatic teachers
Thesis (Ed.M.)--Boston Universit
MATISSE: an ArcGIS tool for monitoring and nowcasting meteorological hazards
Abstract. Adverse meteorological conditions are one of the major causes of accidents in aviation, resulting in substantial human and economic losses. For this reason it is crucial to monitor and early forecast high impact weather events. In this context, CIRA (Italian Aerospace Research Center) has implemented MATISSE (Meteorological AviaTIon Supporting SystEm), an ArcGIS Desktop Plug-in able to detect and forecast meteorological aviation hazards over European airports, using different sources of meteorological data (synoptic information, satellite data, numerical weather prediction models data). MATISSE presents a graphical interface allowing the user to select and visualize such meteorological conditions over an area or an airport of interest. The system also implements different tools for nowcasting of meteorological hazards and for the statistical characterization of typical adverse weather conditions for the airport selected
Mechanical Systems: Symmetry and Reduction
Reduction theory is concerned with mechanical systems with symmetries. It constructs a
lower dimensional reduced space in which associated conservation laws are taken out and
symmetries are \factored out" and studies the relation between the dynamics of the given
system with the dynamics on the reduced space. This subject is important in many areas,
such as stability of relative equilibria, geometric phases and integrable systems
Building vicarious bridges through colour workshops for pupils with visual impairment
he inclusion of pupils with visual impairment, within Italian mainstream schools, is
an area of interest for the field of special education that is involved in identifying the
most effective teaching strategies to promote the teaching-learning process. The
perceptive difficulties that the pupils with visual impairment encounter in the first step
of development can be a significant obstacle to learning and to the development of
representative thinking. For this reason, it is fundamental that the teaching style
adopted is oriented to promote learning through strategies that exploit the natural
vicarious activity of the brain. With this aim, the present paper describes the potential
of a hands-on activity with high inclusive value, which is based on a theoretical
framework, that brings together contributions from different scientific domains and
which, from an interdisciplinary perspective, explores the concept of "vicariance" as
proposed by the physiologist of perception Alain Bertho
A competitive cell-permeable peptide impairs Nme-1 (NDPK-A) and Prune-1 interaction: therapeutic applications in cancer.
The understanding of protein–protein interactions is crucial in order to generate a second level of functional genomic analysis in human disease. Within a cellular microenvironment, protein–protein interactions generate new functions that can be defined by single or multiple modes of protein interactions. We outline here the clinical importance of targeting of the Nme-1 (NDPK-A)–Prune-1 protein complex in cancer, where an imbalance in the formation of this protein–protein complex can result in inhibition of tumor progression. We discuss here recent functional data using a small synthetic competitive cell-permeable peptide (CPP) that has shown therapeutic efficacy for impairing formation of the Nme-1–Prune-1 protein complex in mouse preclinical xenograft tumor models (e.g., breast, prostate, colon, and neuroblastoma). We thus believe that further discoveries in the near future related to the identification of new protein–protein interactions will have great impact on the development of new therapeutic strategies against various cancers
A rock physics and seismic tomography study to characterize the structure of the Campi Flegrei caldera
The Campi Flegrei (CF) caldera experiences dramatic ground deformations
unsurpassed anywhere in the world. The source responsible for this
phenomenon is still debated. With the aim of exploring the structure of the caldera
as well as the role of hydrothermal fluids on velocity changes, a multidisciplinary
approach dealing with 3-D delay-time tomography and rock physics
characterization has been followed. Selected seismic data were modeled by
using a tomographic method based on an accurate finite-difference travel-time
computation which simultaneously inverts P-wave and S-wave first-arrival times
for both velocity model parameters and hypocenter locations.
The retrieved P-wave and S-wave velocity images as well as the deduced
Vp/Vs images were interpreted by using experimental measurements of rock
physical properties on CF samples, to take into account steam/water phase
transition mechanisms affecting P-wave and S-wave velocities. Also, modelling
of petrophysical properties for site-relevant rocks constrains the role of overpressured
fluids on velocity. A flat and low Vp/Vs anomaly lies at 4 km depth
under the city of Pozzuoli. Earthquakes are located at the top of this anomaly.
This anomaly implies the presence of fractured over-pressured gas-bearing
formations and excludes the presence of melted rocks. At shallow depth, a
high Vp/Vs anomaly located at 1 km suggests the presence of rocks containing
fluids in the liquid phase. Finally, maps of the Vp*Vs product show a high
Vp*Vs horse-shoe shaped anomaly located at 2 km depth. It is consistent with
gravity data and well data and might constitute the on-land remainder of the
caldera rim, detected below sea level by tomography using active source seismic
data. For a more exhaustive description of the utilized methodologies, of
synthetic tests for spatial resolution and uncertainty assessment and, the interpretation
of results, the reader may refer to the paper Vanorio et al. (2005)
Variability and Trends in Streamflow in Northeast United States
Abstract There is general consensus that climate is undergoing change but whether climate change is occurring or not is still being debated in certain scientific, political, and religious quarters. Hydrologic variability influences the design of civil works and assessment of long-term climate change would help improve design criteria. To this end, long-term variability of streamflow was estimated using Shannon entropy. Three statistical tests were applied to determine trends in annual and seasonal daily streamflow with 5% two-sided confidence limit. Daily streamflow data spanning 70 years (from 1943 to 2012) from 669 stream gauge stations located in 23 states in the northeastern part of United States of America, covering six different water regions were employed. The time variability of annual and seasonal daily streamflow was assessed using the Mean Decadal Apportionment Disorder Index ( MDADI ). Analysis showed that in all cases minimum and maximum streamflows had higher variability than average and median streamflows. A significant number of stations exhibited trends. Considering annual minimum, average and median daily streamflows, approximately 50% of the stations followed trends and for almost all these stations trends were increasing. Only for annual maximum daily streamflow, 15% of the stations showed increasing trend and 10% decreasing trend. In terms of geographical distribution, the stations with increasing trend were essentially located along the Atlantic coast and near Great Lakes and in the Upper Mississippi Water Region. Similar considerations apply for seasonal time series as well
From sustainability to business strategy: how the role of the Chief Sustainability Officer is evolving to shape business strategies
Distribution-Free Statistical Dispersion Control for Societal Applications
Explicit finite-sample statistical guarantees on model performance are an
important ingredient in responsible machine learning. Previous work has focused
mainly on bounding either the expected loss of a predictor or the probability
that an individual prediction will incur a loss value in a specified range.
However, for many high-stakes applications, it is crucial to understand and
control the dispersion of a loss distribution, or the extent to which different
members of a population experience unequal effects of algorithmic decisions. We
initiate the study of distribution-free control of statistical dispersion
measures with societal implications and propose a simple yet flexible framework
that allows us to handle a much richer class of statistical functionals beyond
previous work. Our methods are verified through experiments in toxic comment
detection, medical imaging, and film recommendation.Comment: Accepted by NeurIPS as spotlight (top 3% among submissions
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions
Rigorous guarantees about the performance of predictive algorithms are
necessary in order to ensure their responsible use. Previous work has largely
focused on bounding the expected loss of a predictor, but this is not
sufficient in many risk-sensitive applications where the distribution of errors
is important. In this work, we propose a flexible framework to produce a family
of bounds on quantiles of the loss distribution incurred by a predictor. Our
method takes advantage of the order statistics of the observed loss values
rather than relying on the sample mean alone. We show that a quantile is an
informative way of quantifying predictive performance, and that our framework
applies to a variety of quantile-based metrics, each targeting important
subsets of the data distribution. We analyze the theoretical properties of our
proposed method and demonstrate its ability to rigorously control loss
quantiles on several real-world datasets.Comment: 24 pages, 4 figures. Code is available at
https://github.com/jakesnell/quantile-risk-contro
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