Exact Ground States of the Periodic Anderson Model in D=3 Dimensions

We construct a class of exact ground states of three-dimensional periodic Anderson models (PAMs) -- including the conventional PAM -- on regular Bravais lattices at and above 3/4 filling, and discuss their physical properties. In general, the f electrons can have a (weak) dispersion, and the hopping and the non-local hybridization of the d and f electrons extend over the unit cell. The construction is performed in two steps. First the Hamiltonian is cast into positive semi-definite form using composite operators in combination with coupled non-linear matching conditions. This may be achieved in several ways, thus leading to solutions in different regions of the phase diagram. In a second step, a non-local product wave function in position space is constructed which allows one to identify various stability regions corresponding to insulating and conducting states. The compressibility of the insulating state is shown to diverge at the boundary of its stability regime. The metallic phase is a non-Fermi liquid with one dispersing and one flat band. This state is also an exact ground state of the conventional PAM and has the following properties: (i) it is non-magnetic with spin-spin correlations disappearing in the thermodynamic limit, (ii) density-density correlations are short-ranged, and (iii) the momentum distributions of the interacting electrons are analytic functions, i.e., have no discontinuities even in their derivatives. The stability regions of the ground states extend through a large region of parameter space, e.g., from weak to strong on-site interaction U. Exact itinerant, ferromagnetic ground states are found at and below 1/4 filling.Comment: 47 pages, 10 eps figure

Comparison Non-Parametric Machine Learning Algorithms for Prediction of Employee Talent

Classification of ordinal data is part of categorical data. Ordinal data consists of features with values based on order or ranking. The use of machine learning methods in Human Resources Management is intended to support decision-making based on objective data analysis, and not on subjective aspects. The purpose of this study is to analyze the relationship between features, and whether the features used as objective factors can classify, and predict certain talented employees or not. This study uses a public dataset provided by IBM analytics. Analysis of the dataset using statistical tests, and confirmatory factor analysis validity tests, intended to determine the relationship or correlation between features in formulating hypothesis testing before building a model by using a comparison of four algorithms, namely Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Artificial Neural Networks. The test results are expressed in the Confusion Matrix, and report classification of each model. The best evaluation is produced by the SVM algorithm with the same Accuracy, Precision, and Recall values, which are 94.00%, Sensitivity 93.28%, False Positive rate 4.62%, False Negative rate 6.72%,  and AUC-ROC curve value 0.97 with an excellent category in performing classification of the employee talent prediction model

Assessment of Antarctic moss health from multi-sensor UAS imagery with Random Forest Modelling

Moss beds are one of very few terrestrial vegetation types that can be found on the Antarctic continent and as such mapping their extent and monitoring their health is important to environmental managers. Across Antarctica, moss beds are experiencing changes in health as their environment changes. As Antarctic moss beds are spatially fragmented with relatively small extent they require very high resolution remotely sensed imagery to monitor their distribution and dynamics. This study demonstrates that multi-sensor imagery collected by an Unmanned Aircraft System (UAS) provides a novel data source for assessment of moss health. In this study, we train a Random Forest Regression Model (RFM) with long-term field quadrats at a study site in the Windmill Islands, East Antarctica and apply it to UAS RGB and 6-band multispectral imagery, derived vegetation indices, 3D topographic data, and thermal imagery to predict moss health. Our results suggest that moss health, expressed as a percentage between 0 and 100% healthy, can be estimated with a root mean squared error (RMSE) between 7 and 12%. The RFM also quantifies the importance of input variables for moss health estimation showing the multispectral sensor data was important for accurate health prediction, such information being essential for planning future field investigations. The RFM was applied to the entire moss bed, providing an extrapolation of the health assessment across a larger spatial area. With further validation the resulting maps could be used for change detection of moss health across multiple sites and seasons

A Standardized Ecosystem Classification for the Coordination and Design of Long-term Terrestrial Ecosystem Monitoring in Arctic-Subarctic Biomes

A Canadian Arctic-Subarctic Biogeoclimatic Ecosystem Classification (CASBEC) is proposed as a standardized classification approach for Subarctic and Arctic terrestrial ecosystems across Canada and potentially throughout the circumpolar area. The CASBEC is grounded in long-standing terrestrial ecosystem classification theory and builds on concepts developed for ecosystems in British Columbia, Quebec, and Yukon. The fundamental classification unit of the CASBEC, the plant association, is compatible with the lower-level classifications of the Arctic Vegetation Classification (AVC), the Canadian National Vegetation Classification (CNVC), and the United States National Vegetation Classification (USNVC) and is used to generate a classification and nomenclature for Arctic and Subarctic terrestrial ecological communities. The use of a multi-scalar ecosystem framework, such as that developed by the British Columbia Biogeoclimatic Ecosystem Classification, provides an ecological context to use classified plant associations to delineate and define climatically equivalent regional scale climate units (biogeoclimatic subzones) and ecologically equivalent local-scale site units within biogeoclimatic subzones. A standardized framework and taxonomy of ecosystem classification for Subarctic and Arctic terrestrial ecological communities will facilitate the planning, coordination, and applicability of terrestrial ecological monitoring and research. The CASBEC classification and high-resolution ecosystem mapping are being used to develop an effective experimental design, to select ecosite types for long-term monitoring, and to extrapolate results to landscape scales in the Experimental and Reference Area of the Canadian High Arctic Research Station (CHARS) in Cambridge Bay. Widespread adoption of the CASBEC could provide a spatial and functionally scalable framework and a common language for interpreting, integrating, coordinating, and communicating Arctic and Subarctic monitoring, research, and land management activities across the Canadian North and around the circumpolar area.Une classification biogéoclimatique arctique et subarctique canadienne (Canadian Arctic-Subarctic Biogeoclimatic Ecosystem Classification, ou CASBEC) est proposée en tant que méthode de classification standardisée pour les écosystèmes terrestres arctiques et subarctiques pancanadiens, et peut-être même pour les écosystèmes de la région circumpolaire. CASBEC s’appuie sur une théorie de classification des écosystèmes terrestres de longue date et sur des concepts mis au point pour les écosystèmes de la Colombie-Britannique, du Québec et du Yukon. L’unité de classification fondamentale de CASBEC, soit l’association végétale, est compatible avec les classifications de niveau inférieur de la classification de la végétation de l’Arctique (Arctic Vegetation Classification, ou AVC), de la Classification nationale de la végétation du Canada (CNVC) et de la classification nationale de la végétation des États-Unis (USNVC). Elle permet de produire une classification et une nomenclature pour les communautés écologiques terrestres arctiques et subarctiques. Le recours à un cadre écosystémique multiscalaire, comme celui élaboré par la classification écosystémique biogéoclimatique de la Colombie-Britannique, fournit un contexte écologique permettant d’utiliser les associations végétales classifiées pour délimiter et définir les unités climatiques régionales à l’échelle climatiquement équivalentes (sous-zones biogéoclimatiques) et les unités écologiquement équivalentes de sites d’envergure locale à l’intérieur des sous-zones biogéoclimatiques. La mise en place d’une taxonomie et d’un cadre standardisés de classification des écosystèmes des communautés écologiques terrestres arctiques et subarctiques facilitera la planification, la coordination et l’applicabilité des travaux de surveillance et de recherche écologique terrestre. La classification CASBEC et la cartographie des écosystèmes en haute résolution sont employées pour mettre au point une conception expérimentale efficace, pour sélectionner des types d’écosites à des fins de surveillance à long terme ainsi que pour extrapoler les résultats à l’échelle des paysages dans la zone d’expérimentation et de référence de la Station canadienne de recherche dans l’Extrême-Arctique (SCREA) à Cambridge Bay. L’adoption de CASBEC à grande échelle pourrait fournir un cadre spatial et fonctionnellement extensible de même qu’un langage commun pour interpréter, intégrer, coordonner et communiquer les activités de surveillance, de recherche et de gestion des terres arctiques et subarctiques à la grandeur du Nord canadien et de l’ensemble de la région circumpolaire

Direct experimental verification of applicability of single-site model for angle integrated photoemission of small TKT_{K} concentrated Ce compounds

Bulk-sensitive high-resolution Ce 4f spectra have been obtained from 3d $\to$ 4f resonance photoemission measurements on La$_{1-x}$Ce$_x$Al$_2$ and La$_{1-x}$Ce$_x$Ru$_2$ for $x = 0.0, 0.04, 1.0$. The 4f spectra of low-Kondo-temperature ($T_{K}$) (La,Ce)Al$_2$ are essentially identical except for a slight increase of the Kondo peak with $x$, which is consistent with a known increase of $T_{K}$ with $x$. In contrast, the 4f spectra of high-$T_{K}$ (La,Ce)Ru$_2$ show a Kondo-like peak and also a 0.5 eV structure which increases strongly with $x$. The resonance photon-energy dependences of the two contributions are different and the origin of the 0.5 eV structure is still uncertain.Comment: submitted to SCES 2001, two-columnn format, modified tex

Data Services for Long Tail Science at the Integrated Earth Data Applications (IEDA) Data Facility

IEDA (Integrated Earth Data Applications) is a US-based data facility funded through a contract with the US National Science Foundation to operate data systems and data services for solid earth geoscience data. IEDA has developed a comprehensive suite of data services that are designed to address the concerns and needs of investigators, especially researchers working in the 'Long Tail of Science' (Heidorn 2008). IEDA provides a data publication service, registering datasets with DOI to ensure their proper citation and attribution. IEDA works with publishers on advanced linkages between datasets in the IEDA repository and scientific online articles to facilitate access to the data, enhance their visibility, and augment their use and citation. IEDA also developed a comprehensive investigator support that includes tools, tutorials, and virtual or face-to-face workshops that guide and assist investigators with data management planning, data submission, and data documentation. A critical aspect of IEDA's concept has been the disciplinary expertise within the team and its strong liaison with the science community, as well as a community-based governance. These have been fundamental to gain the trust and support of the scientists and have lead to significantly improved data preservation and access in the communities served by IEDA

Defining the type of surgeon volume that influences the outcomes for open abdominal aortic aneurysm repair

ObjectivePrior studies have reported improved clinical outcomes with higher surgeon volume, which is assumed to be a product of the surgeon's experience with the index operation. We hypothesized that composite surgeon volume is an important determinant of outcome. We tested this hypothesis by comparing the impact of operation-specific surgeon volume versus composite surgeon volume on surgical outcomes, using open abdominal aortic aneurysm (AAA) repair as the index operation.MethodsThe Nationwide Inpatient Sample was analyzed to identify patients undergoing open AAA repairs for 2000 to 2008. Surgeons were stratified into deciles based on annual volume of open AAA repairs (“operation-specific volume”) and overall volume of open vascular operations (“composite volume”). Composite volume was defined by the sum of several open vascular operations: carotid endarterectomy, aortobifemoral bypass, femoral-popliteal bypass, and femoral-tibial bypass. Multiple logistic regression analyses were used to examine the relationship between surgeon volume and in-hospital mortality for open AAA repair, adjusting for both patient and hospital characteristics.ResultsBetween 2000 and 2008, an estimated 111,533 (95% confidence interval [CI], 102,296-121,232) elective open AAA repairs were performed nationwide by 6,857 surgeons. The crude in-hospital mortality rate over the study period was 6.1% (95% CI, 5.6%-6.5%). The mean number of open AAA repairs performed annually was 2.4 operations per surgeon. The mean composite volume was 5.3 operations annually. As expected, in-hospital mortality for open AAA repair decreased with increasing volume of open AAA repairs performed by a surgeon. Mortality rates for the lowest and highest deciles of surgeon volume were 10.2% and 4.5%, respectively (P < .0001). A similar pattern was observed for composite surgeon volume, as the mortality rates for the lowest and highest deciles of composite volume were 9.8% and 4.8%, respectively (P < .0001). After adjusting for patient and hospital characteristics, increasing composite surgeon volume remained a significant predictor of lower in-hospital mortality for open AAA repair (odds ratio, 0.994; 95% CI, .992-.996; P < .0001), whereas increasing volume of AAA repairs per surgeon did not predict in-hospital deaths.ConclusionsThe current study suggests that composite surgeon volume—not operation-specific volume—is a key determinant of in-hospital mortality for open AAA repair. This finding needs to be considered for future credentialing of surgeons

Scientific Potential and Design Considerations for an Undulator Beam Line on Aladdin Storage Ring

The unique features of undulator radiation, i.e., high photon flux and brightness, partial coherence, small beam divergence, spectral tunability, etc., mandate that undulators be included in the future plans for Aladdin. This will make it possible to perform the next generation of experiments in photon-stimulated spectroscopies. A team of scientists (see Appendix) has now been assembled to build an insertion device (ID) and the associated beam line at Aladdin. In considering the specifications for the ID, it was assumed that the ID beamline will be an SRC user facility. Consequently, design parameters were chosen with the intent of maximizing experimental flexibility consistent with a conservative design approach. A tunable {open_quotes}clamshell{close_quotes} undulator device was Chosen with a first harmonic tunable from 35 to 110 eV to operate on a 1 GeV storage ring. Higher harmonics will be utilized for experiments needing higher photon energies