Static and dynamic XY-like short-range order in a frustrated magnet with exchange disorder

A single crystal of the Co2+ based pyrochlore NaCaCo2F7 was studied by inelastic neutron scattering. This frustrated magnet with quenched exchange disorder remains in a strongly correlated paramagnetic state down to one 60th of the Curie-Weiss temperature. Below T_f = 2.4 K, diffuse elastic scattering develops and comprises 30 +/- 10% of the total magnetic scattering, as expected for J_{eff} = 1/2 moments frozen on a time scale that exceeds \hbar/\delta E=3.8 ps. The diffuse scattering is consistent with short range XY antiferromagnetism with a correlation length of 16 \AA. The momentum (Q) dependence of the inelastic intensity indicates relaxing XY-like antiferromagnetic clusters at energies below ~ 5.5 meV, and collinear antiferromagnetic fluctuations above this energy. The relevant XY configurations form a continuous manifold of symmetry-related states. Contrary to well-known models that produce this continuous manifold, order-by-disorder does not select an ordered state in NaCaCo2F7 despite evidence for weak (~12 %) exchange disorder. Instead, NaCaCo2F7 freezes into short range ordered clusters that span this manifold.Comment: 9 pages, 9 figures. This updated version features modified figures and some new discussio

Evidence of Titan's Climate History from Evaporite Distribution

Water-ice-poor, 5-$\mu$m-bright material on Saturn's moon Titan has previously been geomorphologically identified as evaporitic. Here we present a global distribution of the occurrences of the 5-$\mu$m-bright spectral unit, identified with Cassini's Visual Infrared Mapping Spectrometer (VIMS) and examined with RADAR when possible. We explore the possibility that each of these occurrences are evaporite deposits. The 5-$\mu$m-bright material covers 1\% of Titan's surface and is not limited to the poles (the only regions with extensive, long-lived surface liquid). We find the greatest areal concentration to be in the equatorial basins Tui Regio and Hotei Regio. Our interpretations, based on the correlation between 5-$\mu$m-bright material and lakebeds, imply that there was enough liquid present at some time to create the observed 5-$\mu$m-bright material. We address the climate implications surrounding a lack of evaporitic material at the south polar basins: if the south pole basins were filled at some point in the past, then where is the evaporite

Time series classification with ensembles of elastic distance measures

Several alternative distance measures for comparing time series have recently been proposed and evaluated on time series classification (TSC) problems. These include variants of dynamic time warping (DTW), such as weighted and derivative DTW, and edit distance-based measures, including longest common subsequence, edit distance with real penalty, time warp with edit, and move–split–merge. These measures have the common characteristic that they operate in the time domain and compensate for potential localised misalignment through some elastic adjustment. Our aim is to experimentally test two hypotheses related to these distance measures. Firstly, we test whether there is any significant difference in accuracy for TSC problems between nearest neighbour classifiers using these distance measures. Secondly, we test whether combining these elastic distance measures through simple ensemble schemes gives significantly better accuracy. We test these hypotheses by carrying out one of the largest experimental studies ever conducted into time series classification. Our first key finding is that there is no significant difference between the elastic distance measures in terms of classification accuracy on our data sets. Our second finding, and the major contribution of this work, is to define an ensemble classifier that significantly outperforms the individual classifiers. We also demonstrate that the ensemble is more accurate than approaches not based in the time domain. Nearly all TSC papers in the data mining literature cite DTW (with warping window set through cross validation) as the benchmark for comparison. We believe that our ensemble is the first ever classifier to significantly outperform DTW and as such raises the bar for future work in this area

An assessment of pediatric residency applicant perceptions of Fit during the virtual interview era

PURPOSE: Residency recruitment events and interviews are widely considered an integral component of the residency match experience. Due to the COVID-19 pandemic, residency recruitment and interviewing throughout the 2020-2021 academic year were performed virtually, which created challenges for applicants\u27 ability to discern fit to a program. Given this change, it is reasonable to suspect that applicants would be less able to discern program fit. Therefore, this study evaluated how virtual interviews impacted pediatric residency applicants\u27 ability to assess factors contributing to fit and subsequently how applicants assessed their self-perceived fit to their top-ranked programs. METHODS: An online, anonymous survey was distributed to all residency applicants who applied to any specialty at our large academic institution. The survey utilized a 5-point Likert-type scale to evaluate qualities of fit as well as the applicants\u27 self-perceived ability to assess these qualities through a virtual platform. RESULTS: 1,840 surveys were distributed, of which 473 residency applicants responded (25.7% response rate). Among these responses, 81 were pediatric applicants (27.6%). Factors deemed most important in determining fit included how well the residents get along with one another (98.8%), how much the program appeared to care about its trainees (97.5%), and how satisfied residents were with their program (97.5%). Qualities deemed most difficult for applicants to discern included the quality of facilities (18.6%), patient diversity (29.4%), and how well the residents got along with one another (30.2%). When compared to all other residency applicants, pediatric applicants placed more value on whether a program was family-friendly (p = 0.015), the quality of the facilities (p = 0.009), and the on-call system (p = 0.038). CONCLUSION: This study highlights factors that influence pediatric applicants\u27 perception of fit into a program. Unfortunately, many factors deemed most important for pediatric applicants were also among the most difficult to assess virtually. These include resident camaraderie, whether a program cares about its residents, and overall resident satisfaction. Taken together, these findings and the recommendations presented should be considered by all residency program leaders to ensure the successful recruitment of a pediatric residency class

Balanced and Restored Cross-Sections Representing Post-Miocene Crustal Extension of Fluvial Deposits, North-Central Montana to Southeast Idaho

This research is part of a larger project based on the theory of the existence of a pre-ice age, Amazon-scale river that had headwaters in the southern Colorado Plateau and flowed north through the western United States and Canada before discharging into the Labrador Sea. Stream-rounded fluvial deposits in Montana and Idaho provide evidence of sediment provenance in Nevada and Utah, as there are no confirmed bedrock sources for these sediments in Montana or Idaho. The Miocene river bed has been offset and tilted by dozens of extensional faults in the region. Some faults bound large mountain ranges including the Lost River, Lemhi, Beaverhead, Tendoy, Blacktail Deer, Ruby, Madison, and Big Belt Mountains. The reconstructed trend of the Miocene river bed provides a reference line against which to measure active faulting. We constructed five balanced cross-sections of the deformed subsurface along the Miocene river bed from north-central Montana to southeast Idaho across the faulted mountain ranges and restored the cross-sections to represent an un-deformed subsurface. This provided valuable insight into crustal deformation in these regions. Knowing the timing and extent of crustal deformation has many scientific and societal benefits. Western Montana and adjacent Idaho occupy the Inter-mountain Seismic Zone and have the potential for large earthquakes. Detailed cross-sections through this zone can provide information for development projects in faulted areas, and target potential aquifer locations where the thick river gravel has been down-faulted into the sub-surface. This research will be an important contribution to understanding the evolution of the tectonic landscape of Montana and Idaho

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve