Orbital control in strained ultra-thin LaNiO3_3/LaAlO3_3 superlattices

In pursuit of rational control of orbital polarization, we present a combined experimental and theoretical study of single unit cell superlattices of the correlated metal LaNiO$_3$ and the band insulator LaAlO$_3$. Polarized x-ray absorption spectra show a distinct asymmetry in the orbital response under strain. A splitting of orbital energies consistent with octahedral distortions is found for the case of compressive strain. In sharp contrast, for tensile strain, no splitting is found although a strong orbital polarization is present. Density functional theory calculations including a Hubbard U term reveal that this asymmetry is a result of the interplay of strain and confinement induces octahedral rotations and distortions and altered covalency in the bonding across the interfacial Ni-O-Al apical oxygen, leading to a charge disporportionation at the Ni sites for tensile strain.Comment: 4 pages. 5 figure

Strain-mediated metal-insulator transition in epitaxial ultra-thin films of NdNiO3

We have synthesized epitaxial NdNiO$_{3}$ ultra-thin films in a layer-by-layer growth mode under tensile and compressive strain on SrTiO$_{3}$ (001) and LaAlO$_3$ (001), respectively. A combination of X-ray diffraction, temperature dependent resistivity, and soft X-ray absorption spectroscopy has been applied to elucidate electronic and structural properties of the samples. In contrast to the bulk NdNiO$_{3}$, the metal-insulator transition under compressive strain is found to be completely quenched, while the transition remains under the tensile strain albeit modified from the bulk behavior.Comment: 4 pages, 4 figure

Statistical Physics Modeling of Disordered Metallic Alloys

The great majority of metallic alloys in use are disordered. The material property of a disordered alloy changes on exposure to thermal, chemical, or mechanical forcing; the changes are often irreversible. We present a new first principle method for modeling disordered metallic alloys suitable for predicting how the morphology, strength, and transport property would evolve under arbitrary forcing conditions. Such a predictive capability is critically important in designing new alloys for applications, such as in new-generation fission and fusion reactors, where unrelenting harsh thermal loading conditions exist. The protocol is developed for constructing a coarse-grained model that can be specialized for the evolution of thermophysical properties of an arbitrary disordered alloy under thermal, stress, nuclear, or chemical forcing scenarios. We model a disordered binary alloy as a randomly close-packed (RCP) assembly of constituent atoms at given composition. As such, a disordered alloy specimen is an admixture of nanocrystallites and glassy matter. For the present purpose, we first assert that interatomic interactions are by repulsion only, but the contributions from the attractive part of the interaction are restored by treating the nanocrystallites as nanoscale pieces of a single crystalline solid composed of the same constituent atoms. Implementation of the protocol is discussed for heating of disordered metals, and results are compared to the known melting point data

Mucin Hypersecreting Intraductal Papillary Neoplasm of the Pancreas

Mucin Hypersecreting Intraductal Papillary Neoplasm is a rare neoplasm that arises from ductal epithelial cells. This entity is distinct from the more commonly known Mucinous Cystadenoma or Mucinous Cystadenocarcinoma. Despite this distinction, it has been erroneously categorized with these more common cystic neoplasms. Characteristic clinical presentation, radiographic, and endoscopic findings help distinguish this neoplasm from the cystadenomas and cystadenocarcinomas. Histopathologic identification is not crucial to the preoperative diagnosis. This neoplasm is considered to represent a premalignant condition and, therefore, surgical resection is warranted. Prognosis, following resection, is felt to be curative for the majority of patients

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is the use of computational algorithms that mimic human cognitive functions to analyze complex medical data. AI technologies like machine learning (ML) support the integration of biological, psychological, and social factors when approaching diagnosis, prognosis, and treatment of disease. This paper serves to acquaint clinicians and other stakeholders with the use, benefits, and limitations of AI for predicting, diagnosing, and classifying mild and major neurocognitive impairments, by providing a conceptual overview of this topic with emphasis on the features explored and AI techniques employed. We present studies that fell into six categories of features used for these purposes: (1) sociodemographics; (2) clinical and psychometric assessments; (3) neuroimaging and neurophysiology; (4) electronic health records and claims; (5) novel assessments (e.g., sensors for digital data); and (6) genomics/other omics. For each category we provide examples of AI approaches, including supervised and unsupervised ML, deep learning, and natural language processing. AI technology, still nascent in healthcare, has great potential to transform the way we diagnose and treat patients with neurocognitive disorders

Surface effects on the orbital order in the single layered manganite La0.5Sr1.5MnO4

We report the first observation of `orbital truncation rods' -- the scattering arising from the termination of bulk orbital order at the surface of a crystal. The x-ray measurements, performed on a cleaved, single-layered perovskite, La0.5Sr1.5MnO4, reveal that while the crystallographic surface is atomically smooth, the orbital `surface' is much rougher, with an r.m.s. deviation from the average `surface' of ~0.7nm. The temperature dependence of this scattering shows evidence of a surface-induced second order transition.Comment: 13 pages, 4 figure