1,065 research outputs found

    Characteristic Plain Radiographic and Intravenous Urographic Findings of Bladder Calculi Formed over a Hair Nidus: A Case Report

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    We present the characteristic plain radiographic and intravenous urographic (IVU) findings of calculus formed over a hair. A 66-year-old man who had been quadriplegic for 40 years because of vertebral injury was admitted for further evaluation of frequent urinary tract infection. Plain radiography showed a linear, serpiginous calcification in the lower abdomen, and IVU revealed a round filling defect with linear radiopacity in the bladder, suggesting calculus. The gross appearance of the stone after extraction demonstrated that calcification had formed over a hair

    The 750 GeV Diphoton Excess May Not Imply a 750 GeV Resonance

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    We discuss non-standard interpretations of the 750 GeV diphoton excess recently reported by the ATLAS and CMS Collaborations which do not involve a new, relatively broad, resonance with a mass near 750 GeV. Instead, we consider the sequential cascade decay of a much heavier, possibly quite narrow, resonance into two photons along with one or more invisible particles. The resulting diphoton invariant mass signal is generically rather broad, as suggested by the data. We examine three specific event topologies - the antler, the sandwich, and the 2-step cascade decay, and show that they all can provide a good fit to the observed published data. In each case, we delineate the preferred mass parameter space selected by the best fit. In spite of the presence of invisible particles in the final state, the measured missing transverse energy is moderate, due to its anti- correlation with the diphoton invariant mass. We comment on the future prospects of discriminating with higher statistics between our scenarios, as well as from more conventional interpretations.Comment: Discussion about the ATLAS Moriond EW2016 added. Matched to PRL accepted versio

    Association between polymorphisms of arachidonate 12-lipoxygenase (ALOX12) and schizophrenia in a Korean population

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    Arachidonic acid (AA), an essential polyunsaturated fatty acid, is one of the major components of neural membranes, which show an altered phospholipid composition in schizophrenia. Arachidonate 12-lipoxygenase (ALOX12), an important enzyme, metabolizes AA to 12-HPETE, which affects catecholamine synthesis. However, research has yet to show the genetic association between ALOX12 and schizophrenia. Therefore, we investigated single nucleotide polymorphisms (SNP) of the ALOX12 gene in schizophrenia, recruiting patients with schizophrenia (n = 289) and normal controls (n = 306) from a Korean population. We selected three SNPs (rs1126667, rs434473, and rs1042357) of the ALOX12 gene and genotyped them by direct sequencing. We reviewed the schizophrenic patients' medical records and assessed them clinically using the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Operational Criteria Checklist (OPCRIT). Then we statistically analyzed the genetic associations between the SNPs and schizophrenia, finding a genetic association between both rs1126667 and rs1042357 and schizophrenia, in the recessive model (p = 0.015 and 0.015, respectively). We also found an association between rs434473 and negative symptoms, defined through a factor analysis of the OPCRIT data (p = 0.040). Consequently, we suggest that SNPs of the ALOX12 gene might be associated with schizophrenia and negative symptoms in this Korean population. These weak positives require additional study

    Automated Brittle Fracture Rate Estimator for Steel Property Evaluation Using Deep Learning After Drop-Weight Tear Test

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    This study proposes an automated brittle fracture rate (BFR) estimator using deep learning. As the demand for line-pipes increases in various industries, the need for BFR estimation through dropweight tear test (DWTT) increases to evaluate steel's property. Conventional BFR or ductile fracture rate (DFR) estimation methods require an expensive 3D scanner. Alternatively, a rule-based approach is used with a single charge-coupled device (CCD) camera. However, it is sensitive to the hyper-parameter. To solve these problems, we propose an approach based on deep learning that has recently been successful in the fields of computer vision and image processing. The method proposed in this study is the first to use deep learning approach for BFR estimation. The proposed method consists of a VGG-based U-Net (VU-Net) which is inspired by U-Net and fully convolutional network (FCN). VU-Net includes a deep encoder and a decoder. The encoder is adopted from VGG19 and transferred with a pre-trained model with ImageNet. In addition, the structure of the decoder is the same as that of the encoder, and the decoder uses the feature maps of the encoder through concatenation operation to compensate for the reduced spatial information. To analyze the proposed VU-Net, we experimented with different depths of networks and various transfer learning approaches. In terms of accuracy used in real industrial application, we compared the proposed VU-Net with U-Net and FCN to evaluate the performance. The experiments showed that VU-Net was the accuracy of approximately 94.9 %, and was better than the other two, which had the accuracies of about 91.8 % and 93.7 %, respectively.11Ysciescopu

    Ultrasound of the Urinary Bladder, Revisited

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    Urine-filled bladder can be evaluated easily with ultrasound, and bladder tumors are usually well shown at ultrasound. Although ultrasound is not a primary imaging modality for staging of bladder tumors, it can provide general information regarding depth of tumor invasion into the proper muscle or perivesical adipose tissue. Ultrasound is also useful in showing nonneoplastic lesions of the bladder, such as stone, cystitis, diverticulum and ureterocele. Color Doppler ultrasound can show vascularity of the tumor. It also shows urine flow from the ureteral orifice or through the diverticular neck. As compared with transabdominal ultrasound, transrectal ultrasound shows bladder lesions more markedly in the dorsal wall or neck of the bladder
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