752 research outputs found
Information-rich Task Allocation and Motion Planning for Heterogeneous Sensor Platforms
This paper introduces a novel stratified planning algorithm for teams of heterogeneous mobile sensors that maximizes information collection while minimizing resource costs. The main contribution of this work is the scalable unification of effective algorithms for de- centralized informative motion planning and decentralized high-level task allocation. We present the Information-rich Rapidly-exploring Random Tree (IRRT) algorithm, which is amenable to very general and realistic mobile sensor constraint characterizations, as well as review the Consensus-Based Bundle Algorithm (CBBA), offering several enhancements to the existing algorithms to embed information collection at each phase of the planning process. The proposed framework is validated with simulation results for networks of mobile sensors performing multi-target localization missions.United States. Air Force. Office of Scientific Research (Grant FA9550-08-1-0086)United States. Air Force. Office of Scientific Research. Multidisciplinary University Research Initiative (FA9550-08-1-0356
What Helps, What Hinders? Undergraduate Nursing Students' Perceptions of Clinical Placements Based on a Thematic Synthesis of Literature.
Introduction: Clinical placements are a mandatory component of nursing students' education internationally. Despite clinical education being a key to nursing students' achievement of nursing competencies, few studies have reviewed students' narratives to describe their experiences of learning during clinical placement. Such studies may be important in offering a deeper insight into clinical learning experiences than quantitative surveys. Methods: A systematic thematic synthesis of qualitative studies between 2010 and June 2020 was conducted. English language studies that offered a thematic analysis of undergraduate nursing students' experiences of learning during placement were sought. A search was made of five databases PubMed, Ovid Medline, CinahlPlus, SCOPUS, and Google Scholar. The study was guided by the ENTREQ statement for enhancing transparency in reporting the synthesis of qualitative research. Results: Twenty-seven qualitative studies were included in the review. A thematic synthesis showed over 100 themes and subthemes across the studies. A cluster analysis revealed positive elements and others that were seen in the studies as a barrier (hindrance) to clinical learning. Positive elements included supportive instructors, close supervision, and belonging (in the team). Unsupportive instructors, a lack of supervision and not being included were seen as a hindrance. Three key overarching themes that could describe a successful placement were revealed as "Preparation," "Welcomed and wanted" and "Supervision experiences". A conceptual model of clinical placement elements conducive to nursing students' learning was developed to enhance understanding of the complexities associated with supervision. The findings and model are presented and discussed. Conclusion: The conceptual model presents positive elements that influence students' clinical placement experiences of learning. This model may provide a framework to guide professional development programs and strategies to support students and supervisors alike, an important step forward in moving beyond the current clinical placement rhetoric
Probabilistically Safe Avoidance of Dynamic Obstacles with Uncertain Motion Patterns
This paper presents a real-time path planning algorithm which can guarantee
probabilistic feasibility for autonomous robots subject to process noise and an
uncertain environment, including dynamic obstacles with uncertain motion
patterns. The key contribution of the work is the
integration of a novel method for modeling dynamic obstacles with uncertain future
trajectories. The method, denoted as RR-GP, uses a learned motion pattern model
of the dynamic obstacles to make long-term predictions of their future paths. This is done by combining the
flexibility of Gaussian processes (GP) with the efficiency of RRT-Reach,
a sampling-based reachability computation method which ensures dynamic
feasibility. This prediction model is then utilized within chance-constrained rapidly-exploring random
trees (CC-RRT), which uses chance constraints to explicitly achieve probabilistic
constraint satisfaction while maintaining the computational
benefits of sampling-based algorithms. With RR-GP embedded in the CC-RRT framework, theoretical guarantees
can be demonstrated for linear systems subject to Gaussian uncertainty,
though the extension to nonlinear systems is also considered. Simulation results
show that the resulting approach can be used in real-time to efficiently and
accurately execute safe paths
Thermodynamics of the superconducting state in Calcium at 200 GPa
The thermodynamic parameters of the superconducting state in Calcium under
the pressure at 200 GPa were calculated. The Coulomb pseudopotential values
() from 0.1 to 0.3 were taken into consideration. It has been
shown, that the specific heat's jump at the critical temperature and the
thermodynamic critical field near zero Kelvin strongly decrease with
. The dimensionless ratios and
significantly differ from the predictions based on the BCS model. In
particular, decreases from 2.64 to 1.97 with the Coulomb
pseudopotential; whereas increases from 0.140 to 0.157. The numerical
results have been supplemented by the analytical approach.Comment: 7 pages, 6 figure
Quantum Fields on the Groenewold-Moyal Plane
We give an introductory review of quantum physics on the noncommutative
spacetime called the Groenewold-Moyal plane. Basic ideas like star products,
twisted statistics, second quantized fields and discrete symmetries are
discussed. We also outline some of the recent developments in these fields and
mention where one can search for experimental signals.Comment: 50 pages, 3 figures. v2: published versio
Recommended from our members
Searching for life with rovers: exploration methods and science results from the 2004 field campaign of the “Life in the Atacama” project and applications to future Mars Missions
LITA develops and field tests a long-range automated rover and a science payload to search for microbial life in the Atacama. The Atacama's evolution provides a unique training ground for designing and testing exploration strategies and life detection methods for the search for life on Mars
Sampling-based Algorithms for Optimal Motion Planning
During the last decade, sampling-based path planning algorithms, such as
Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have
been shown to work well in practice and possess theoretical guarantees such as
probabilistic completeness. However, little effort has been devoted to the
formal analysis of the quality of the solution returned by such algorithms,
e.g., as a function of the number of samples. The purpose of this paper is to
fill this gap, by rigorously analyzing the asymptotic behavior of the cost of
the solution returned by stochastic sampling-based algorithms as the number of
samples increases. A number of negative results are provided, characterizing
existing algorithms, e.g., showing that, under mild technical conditions, the
cost of the solution returned by broadly used sampling-based algorithms
converges almost surely to a non-optimal value. The main contribution of the
paper is the introduction of new algorithms, namely, PRM* and RRT*, which are
provably asymptotically optimal, i.e., such that the cost of the returned
solution converges almost surely to the optimum. Moreover, it is shown that the
computational complexity of the new algorithms is within a constant factor of
that of their probabilistically complete (but not asymptotically optimal)
counterparts. The analysis in this paper hinges on novel connections between
stochastic sampling-based path planning algorithms and the theory of random
geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics
Researc
Normal tau polarisation as a sensitive probe of CP violation in chargino decay
CP violation in the spin-spin correlations in chargino production and
subsequent two-body decay into a tau and a tau-sneutrino is studied at the ILC.
From the normal polarisation of the tau, an asymmetry is defined to test the
CP-violating phase of the higgsino mass parameter \mu. Asymmetries of more than
\pm70% are obtained, also in scenarios with heavy first and second generation
sfermions. Bounds on the statistical significances of the CP asymmetries are
estimated. As a result, the normal tau polarisation in the chargino decay is
one of the most sensitive probes to constrain or measure the phase \phi_\mu at
the ILC, motivating further detailed experimental studies.Comment: 20 pages, 10 figures, gzipped tar fil
Adolescent brain maturation and cortical folding: evidence for reductions in gyrification
Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development
ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors
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