Identifying quantum topological phases through statistical correlation

We theoretically examine the use of a statistical distance measure, the indistinguishability, as a generic tool for the identification of topological order. We apply this measure to the toric code and two fractional quantum Hall models. We find that topologically ordered states can be identified with the indistinguishability for both models. Calculations with the indistinguishability also underscore a key distinction between symmetries that underlie topological order in the toric code and quantum Hall models. © 2011 American Physical Society.published_or_final_versio

Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status

Portal Vein Thrombosis after Restorative Proctocolectomy for Familial Adenomatous Polyposis and Sigmoid Cancer

Postoperative portal vein thrombosis (PVT) is rare, but has been described after various open as well as minimal access abdominal operations, especially splenectomy and colorectal surgical procedures. We report the case of a 39-year-old female who underwent restorative proctocolectomy and ileal pouch-anal anastomosis for familial adenomatous polyposis with sigmoid cancer. She presented 14 days later with vague upper abdominal pain, nausea, vomiting and high output stoma. Doppler ultrasonography confirmed PVT and therefore anticoagulant therapy was started. Her condition improved dramatically and she underwent closure of ileostomy after finishing adjuvant chemotherapy. She remained well at 3-year follow-up with good pouch function and no local or distant recurrence. A high index of suspicion is essential for early diagnosis and prompt treatment of postoperative PVT after restorative proctocolectomy. Early anticoagulation is essential to avoid subsequent complications

Expanding genotype/phenotype of neuromuscular diseases by comprehensive target capture/NGS

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GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

<p>Abstract</p> <p>Background</p> <p>Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits.</p> <p>Findings</p> <p>Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run.</p> <p>Conclusions</p> <p>GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from <url>http://www.cceb.upenn.edu/~mli/software/GENIE/</url>.</p

Association of decreased mitochondrial DNA content with ovarian cancer progression

Mitochondrial DNA (mtDNA) content in ovarian carcinomas was assessed by quantitative PCR. Results show that mtDNA content in tumour cell was significantly higher than that in normal ovary. Change in mtDNA content was not related with patients' age or tumour stages. However, the average mtDNA copy number in pathological low-grade tumours was over two-fold higher than that in high-grade carcinomas (P=0.012). Moreover, type I carcinomas also had a significantly higher mtDNA copy number than in type II carcinomas (P=0.019). Change in mtDNA content might be an important genetic event in the progression of ovarian carcinomas

Origin of the energy bandgap in epitaxial graphene

We studied the effect of quantum confinement on the size of the band gap in single layer epitaxial graphene. Samples with different graphene terrace sizes are studied by using low energy electron microscopy (LEEM) and angle-resolved photoemission spectroscopy (ARPES). The direct correlation between the terrace size extracted from LEEM and the gap size extracted from ARPES shows that quantum confinement alone cannot account for the large gap observed in epitaxial graphene samples

Fractional quantum Hall effect in a quantum point contact at filling fraction 5/2

Recent theories suggest that the excitations of certain quantum Hall states may have exotic braiding statistics which could be used to build topological quantum gates. This has prompted an experimental push to study such states using confined geometries where the statistics can be tested. We study the transport properties of quantum point contacts (QPCs) fabricated on a GaAs/AlGaAs two dimensional electron gas that exhibits well-developed fractional quantum Hall effect, including at bulk filling fraction 5/2. We find that a plateau at effective QPC filling factor 5/2 is identifiable in point contacts with lithographic widths of 1.2 microns and 0.8 microns, but not 0.5 microns. We study the temperature and dc-current-bias dependence of the 5/2 plateau in the QPC, as well as neighboring fractional and integer plateaus in the QPC while keeping the bulk at filling factor 3. Transport near QPC filling factor 5/2 is consistent with a picture of chiral Luttinger liquid edge-states with inter-edge tunneling, suggesting that an incompressible state at 5/2 forms in this confined geometry

Mapping Dirac quasiparticles near a single Coulomb impurity on graphene

The response of Dirac fermions to a Coulomb potential is predicted to differ significantly from how non-relativistic electrons behave in traditional atomic and impurity systems. Surprisingly, many key theoretical predictions for this ultra-relativistic regime have not been tested. Graphene, a two-dimensional material in which electrons behave like massless Dirac fermions, provides a unique opportunity to test such predictions. Graphene’s response to a Coulomb potential also offers insight into important material characteristics, including graphene’s intrinsic dielectric constant, which is the primary factor determining the strength of electron–electron interactions in graphene. Here we present a direct measurement of the nanoscale response of Dirac fermions to a single Coulomb potential placed on a gated graphene device. Scanning tunnelling microscopy was used to fabricate tunable charge impurities on graphene, and to image electronic screening around them for a Q = +1|e| charge state. Electron-like and hole-like Dirac fermions were observed to respond differently to a Coulomb potential. Comparing the observed electron–hole asymmetry to theoretical simulations has allowed us to test predictions for how Dirac fermions behave near a Coulomb potential, as well as extract graphene’s intrinsic dielectric constant: ε[subscript g] = 3.0±1.0. This small value of ε[subscript g] indicates that electron–electron interactions can contribute significantly to graphene properties.United States. Office of Naval Research. Multidisciplinary University Research Initiative (Award N00014-09-1-1066)United States. Dept. of Energy. Office of Science (Contract DE-AC02-05CH11231)National Science Foundation (U.S.) (Award DMR-0906539