6,802 research outputs found
Exhumation of the Sierra de Cameros (Iberian Range, Spain): constraints from low-temperature thermochronology
We present new fission-track and (U–Th)/He data from apatite and zircon in order to
reconstruct the exhumation of the Sierra de Cameros, in the northwestern part of Iberian Range,
Spain. Zircon fission-track ages from samples from the depocentre of the basin were reset
during the metamorphic peak at approximately 100 Ma. Detrital apatites from the uppermost sediments
retain fission-track age information that is older than the sediment deposition age, indicating
that these rocks have not exceeded 110 8C. Apatites from deeper in the stratigraphic sequence of
the central part of the basin have fission-track ages of around 40 Ma, significantly younger than
the stratigraphic age, recording the time of cooling after peak metamorphic conditions. Apatite
(U–Th)/He ages in samples from these sediments are 31–40 Ma and record the last period of
cooling during Alpine compression. The modelled thermal history derived from the uppermost
sediments indicates that the thermal pulse associated with peak metamorphism was rapid, and
that the region has cooled continuously to the present. The estimated palaeogeothermal gradient
is around 86 8C km21 and supports a tectonic model with a thick sedimentary fill (c. 8 km) and
explains the origin of the low-grade metamorphism observed in the oldest sediments
New Perspectives for Pancreatic Cancer Treatment. Will We Be Able to Ensure Equity to Care?
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Editorial: New Frontiers for Artificial Intelligence in Surgical Decision Making and its Organizational Impacts
The purpose of the research topic call “New Frontiers for Artificial Intelligence in Surgical Decision Making and its Organizational Impacts “ was to collect the recent developments and undergoing studies in AI in surgery and surgical oncology. More in detail, the aim was to gather contributions on the advancement, deployment, use, and implementation of AI-based applications in surgical practice, understanding their potential contribution to clinical decision making. Moreover, the idea was to assess the potential impacts of such a technology on surgeons, other clinicians, patients, medical institutions, developers, and policy-makers, with an eye open to the organizational and educational consequences and opportunities
Reconciling long-term cultural diversity and short-term collective social behavior
An outstanding open problem is whether collective social phenomena occurring
over short timescales can systematically reduce cultural heterogeneity in the
long run, and whether offline and online human interactions contribute
differently to the process. Theoretical models suggest that short-term
collective behavior and long-term cultural diversity are mutually excluding,
since they require very different levels of social influence. The latter
jointly depends on two factors: the topology of the underlying social network
and the overlap between individuals in multidimensional cultural space.
However, while the empirical properties of social networks are well understood,
little is known about the large-scale organization of real societies in
cultural space, so that random input specifications are necessarily used in
models. Here we use a large dataset to perform a high-dimensional analysis of
the scientific beliefs of thousands of Europeans. We find that inter-opinion
correlations determine a nontrivial ultrametric hierarchy of individuals in
cultural space, a result unaccessible to one-dimensional analyses and in
striking contrast with random assumptions. When empirical data are used as
inputs in models, we find that ultrametricity has strong and counterintuitive
effects, especially in the extreme case of long-range online-like interactions
bypassing social ties. On short time-scales, it strongly facilitates a
symmetry-breaking phase transition triggering coordinated social behavior. On
long time-scales, it severely suppresses cultural convergence by restricting it
within disjoint groups. We therefore find that, remarkably, the empirical
distribution of individuals in cultural space appears to optimize the
coexistence of short-term collective behavior and long-term cultural diversity,
which can be realized simultaneously for the same moderate level of mutual
influence
Image-based Recommendations on Styles and Substitutes
Humans inevitably develop a sense of the relationships between objects, some
of which are based on their appearance. Some pairs of objects might be seen as
being alternatives to each other (such as two pairs of jeans), while others may
be seen as being complementary (such as a pair of jeans and a matching shirt).
This information guides many of the choices that people make, from buying
clothes to their interactions with each other. We seek here to model this human
sense of the relationships between objects based on their appearance. Our
approach is not based on fine-grained modeling of user annotations but rather
on capturing the largest dataset possible and developing a scalable method for
uncovering human notions of the visual relationships within. We cast this as a
network inference problem defined on graphs of related images, and provide a
large-scale dataset for the training and evaluation of the same. The system we
develop is capable of recommending which clothes and accessories will go well
together (and which will not), amongst a host of other applications.Comment: 11 pages, 10 figures, SIGIR 201
Dispatcher3 D4.2 - Prototype package (first release) - User manual
This deliverable along with deliverable D4.1. Technical documentation first release consists of the release of the first prototype of Dispatcher3. The release consists of the binaries and Docker version of the prototype (sent to the Topic Manager).
The first release prototype package consists of a set on individual machine learning models which can be executed using Jupyter notebooks. It also includes the integration of the outcome of some of these individual models into a visualisation which would be part of the advice generator to provide high-level information to the end users. All models described in the Deliverable D4.1 will be available and
executable in this release.
Data required to run the models (with some examples) are also provided. If data are public raw sample values are provided, otherwise pre-computed features are delivered so that the models can be run on individual flight examples. The prototypes can be run using local data (provided in the release) or with data stored in cloud storage (Amazon Web Services (AWS)).
This deliverable serves as a manual for the execution of the first release prototype software
One size does not fit all - Translating knowledge to bridge the gaps to diversity and inclusion of surgical teams
Diverse teams have proven their ability to reach superior performance and improve patients' outcomes. Nevertheless, differences in race, gender, age, nationality, skills, education, and experience act as powerful barriers to diversity and inclusion, which negatively impacts multiple healthcare organizations and limit the potential outcome of diverse teams. Knowledge Translation (KT) can help to bridge the gaps among all the various individuals involved, whether they be members of the surgical team or surgical patients
Clinical Case Management for Patients with Schizophrenia with High Care Needs
The aim of this study is to establish the effectiveness of a clinical case management (CM) programme compared to a standard treatment programme (STP) in patients with schizophrenia. Patients for the CM programme were consecutively selected among patients in the STP with schizophrenia who had poor functioning. Seventy-five patients were admitted to the CM programme and were matched to 75 patients in the STP. Patients were evaluated at baseline and at 1 year follow-up. At baseline, patients in the CM programme showed lower levels of clinical and psychosocial functioning and more care needs than patients in the STP. Both treatment programmes were effective in maintaining contact with services but the CM programme did not show advantages over the STP on outcomes. Differences between groups at baseline may be masking the effects of CM at one year follow-up. A longer follow-up may be required to evaluate the real CM practices effect
Effective Free Energy for Individual Dynamics
Physics and economics are two disciplines that share the common challenge of
linking microscopic and macroscopic behaviors. However, while physics is based
on collective dynamics, economics is based on individual choices. This
conceptual difference is one of the main obstacles one has to overcome in order
to characterize analytically economic models. In this paper, we build both on
statistical mechanics and the game theory notion of Potential Function to
introduce a rigorous generalization of the physicist's free energy, which
includes individual dynamics. Our approach paves the way to analytical
treatments of a wide range of socio-economic models and might bring new
insights into them. As first examples, we derive solutions for a congestion
model and a residential segregation model.Comment: 8 pages, 2 figures, presented at the ECCS'10 conferenc
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