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 ($\mu^{\star}$) 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 $\mu^{\star}$. The dimensionless ratios $r_{1}\equiv \Delta C(T_{C})/C^{N}(T_{C})$ and $r_{2}\equiv T_{C}C^{N}(T_{C})/H^{2}_{C}(0)$ significantly differ from the predictions based on the BCS model. In particular, $r_{1}$ decreases from 2.64 to 1.97 with the Coulomb pseudopotential; whereas $r_{2}$ 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

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