Electronic structure of Zr-Ni-Sn systems: role of clustering and nanostructures in Half-Heusler and Heusler limits

Half-Heusler and Heusler compounds have been of great interest for several decades for thermoelectric, magnetic, half-metallic and many other interesting properties. Among these systems, Zr-Ni-Sn compounds are interesting thermoelectrics which can go from semiconducting half-Heusler (HH) limit, ZrNiSn, to metallic Heusler (FH) limit, ZrNi$_2$Sn. Recently Makogo et al. [J. Am. Chem. Soc. 133, 18843 (2011)] found that dramatic improvement in the thermoelectric power factor of HH can be achieved by putting excess Ni into the system. This was attributed to an energy filtering mechanism due to the formation of FH nanostructures in the HH matrix. Using density functional theory we have investigated clustering and nanostructure formation in HH$_{1-x}$FH$_x$ systems near the HH and FH ends and found that excess Ni atoms in HH tend to stay close to each other and form nanoclusters of FH. On the other hand, there is competing interaction between Ni-vacancies in FH which prevent them from forming HH nano clusters. Effects of nano inclusions on the electronic structure at both HH and FH ends will be discussed.Comment: Published in J. Phys.: Condens. Matte

Glucocorticoid receptor expression in 20 solid tumor types using immunohistochemistry assay.

BackgroundGlucocorticoid receptor (GR) activity plays a role in many aspects of human physiology and may play a crucial role in chemotherapy resistance in a wide variety of solid tumors. A novel immunohistochemistry (IHC) based assay has been previously developed and validated in order to assess GR immunoreactivity in triple-negative breast cancer. The current study investigates the standardized use of this validated assay to assess GR expression in a broad range of solid tumor malignancies.MethodsArchived formalin-fixed paraffin-embedded tumor bank samples (n=236) from 20 different solid tumor types were analyzed immunohistochemically. Nuclear staining was reported based on the H-score method using differential intensity scores (0, 1+, 2+, or 3+) with the percent stained (out of at least 100 carcinoma cells) recorded at each intensity.ResultsGR was expressed in all tumor types that had been evaluated. Renal cell carcinoma, sarcoma, cervical cancer, and melanoma were those with the highest mean H-scores, indicating high levels of GR expression. Colon, endometrial, and gastric cancers had lower GR staining percentages and intensities, resulting in the lowest mean H-scores.ConclusionA validated IHC assay revealed GR immunoreactivity in all solid tumor types studied and allowed for standardized comparison of reactivity among the different malignancies.ImpactBaseline expression levels of GR may be a useful biomarker when pharmaceutically targeting GR in research or clinical setting

Secondary School Athletic Trainers’ Perceived Confidence In Providing Independent Medical Care Within Differing Healthcare Delivery Models

ABSTRACT Purpose: The aim of this study was to evaluate athletic trainers’ confidence and ability to deliver independent medical care in the secondary school setting. Methods: A cross-sectional survey design was used with open- and closed-ended questions using a tool that was modified from a previously validated tool used within the collegiate setting; the tool was adapted through content expert validation. Results: Athletic trainers perceived themselves as confident in providing independent medical care through the school district healthcare delivery model (n=109/121, 90%) more often than those functioning within the hospital/clinic outreach model (n=85/130, 65%). Conclusions: Despite not having nationalized legislation and having variable support structures in place, secondary school athletic trainers are confident in providing independent medical care even when their direct supervisor may not be a healthcare provider. This is contradictory to similar findings within the collegiate setting governed by National Collegiate Athletics Association legislation enforcing independent medical care

Simultaneous ranging and velocimetry of fast moving targets using oppositely chirped pulses from a mode-locked laser

A lidar system based on the coherent detection of oppositely chirped pulses generated using a 20 MHz mode locked laser and chirped fiber Bragg gratings is presented. Sub millimeter resolution ranging is performed with \u3e 25 dB signal to noise ratio. Simultaneous, range and Doppler velocity measurements are experimentally demonstrated using a target moving at \u3e 330 km/h inside the laboratory

Dynamic parabolic pulse generation using temporal shaping of wavelength to time mapped pulses

Self-phase modulation in fiber amplifiers can significantly degrade the quality of compressed pulses in chirped pulse amplification systems. Parabolic pulses with linear frequency chirp are suitable for suppressing nonlinearities, and to achieve high peak power pulses after compression. In this paper, we present an active time domain technique to generate parabolic pulses for chirped pulse amplification applications. Pulses from a mode-locked laser are temporally stretched and launched into an amplitude modulator, where the drive voltage is designed using the spectral shape of the input pulse and the transfer function of the modulator, resulting in the generation of parabolic pulses. Experimental results of pulse shaping with a pulse train from a mode-locked laser are presented, with a residual error of less than 5%. Moreover, an extinction ratio of 27 dB is achieved, which is ideal for chirped pulse amplification applications

ur-CAIM: Improved CAIM Discretization for Unbalanced and Balanced Data

Supervised discretization is one of basic data preprocessing techniques used in data mining. CAIM (Class- Attribute InterdependenceMaximization) is a discretization algorithm of data for which the classes are known. However, new arising challenges such as the presence of unbalanced data sets, call for new algorithms capable of handling them, in addition to balanced data. This paper presents a new discretization algorithm named ur-CAIM, which improves on the CAIM algorithm in three important ways. First, it generates more flexible discretization schemes while producing a small number of intervals. Second, the quality of the intervals is improved based on the data classes distribution, which leads to better classification performance on balanced and, especially, unbalanced data. Third, the runtime of the algorithm is lower than CAIM’s. The algorithm has been designed free-parameter and it self-adapts to the problem complexity and the data class distribution. The ur-CAIM was compared with 9 well-known discretization methods on 28 balanced, and 70 unbalanced data sets. The results obtained were contrasted through non-parametric statistical tests, which show that our proposal outperforms CAIM and many of the other methods on both types of data but especially on unbalanced data, which is its significant advantage

Simplified, standardized methods to assess the accuracy of clinical cancer staging

Background. Hospitals lack intuitive methods to monitor their accuracy of clinical cancer staging, which is critical to treatment planning, prognosis, refinements, and registering quality data. Methods. We introduce a tabulation framework to compare clinical staging with the reference-standard pathological staging, and quantify systematic errors. As an example, we analyzed 9,644 2016 U.S. National Cancer Institute SEER surgically-treated non-small cell lung cancer (NSCLC) cases, and computed concordance with different denominators to compare with incompatible past results. Results. The concordance for clinical versus pathological lymph node N-stage is very good, 83.4 ± 1.0%, but the tumor length-location T-stage is only 58.1 ± 0.9%. There are intuitive insights to the causes of discordance. Approximately 29% of the cases are pathological T-stage greater than clinical T-stage, and 12% lower than the clinical T-stage, which is due partly to the fact that surgically-treated NSCLC are typically lower-stage cancer cases, which results in a bounded higher probability for pathological upstaging. Individual T-stage categories Tis, T1a, T1b, T2a, T2b, T3, T4 invariant percent-concordances are 85.2 ± 9.7 + 10.3%; 72.7 ± 1.6 + 11.3%; 46.6 ± 1.8 + 10.9%; 54.6 ± 1.6 – 20.5%; 41.6 ± 3.3 – 0.1%; 54.7 ± 2.8 – 24.1%; 55.2 ± 4.7 + 2.6%, respectively. Each percent-concordance is referenced to an averaged number of pathological and clinical cases. The first error number quantifies statistical fluctuations; the second quantifies clinical and pathological staging biases. Lastly, comparison of over and under staging versus clinical characteristics provides further insights. Conclusions. Clinical NSCLC staging accuracy and concordance with pathological values can improve. As a first step, the framework enables standardizing comparing staging results and detecting possible problem areas. Cancer hospitals and registries can implement the efficient framework to monitor staging accuracy

Range resolved lidar for long distance ranging with sub-millimeter resolution

A lidar technique employing temporally stretched, frequency chirped pulses from a 20 MHz mode locked laser is presented. Sub-millimeter resolution at a target range of 10.1 km (in fiber) is observed. A pulse tagging scheme based on phase modulation is demonstrated for range resolved measurements. A carrier to noise ratio of 30 dB is observed at an unambiguous target distance of 30 meters in fiber

Semisimple types for p -adic classical groups

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