Electrical Investigation of the Oblique Hanle Effect in Ferromagnet/Oxide/Semiconductor Contacts

We have investigated the electrical Hanle effect with magnetic fields applied at an oblique angle ({\theta}) to the spin direction (the oblique Hanle effect, OHE) in CoFe/MgO/semiconductor (SC) contacts by employing a three-terminal measurement scheme. The electrical oblique Hanle signals obtained in CoFe/MgO/Si and CoFe/MgO/Ge contacts show clearly different line shapes depending on the spin lifetime of the host SC. Notably, at moderate magnetic fields, the asymptotic values of the oblique Hanle signals (in both contacts) are consistently reduced by a factor of cos^2({\theta}) irrespective of the bias current and temperature. These results are in good agreement with predictions of the spin precession and relaxation model for the electrical oblique Hanle effect. At high magnetic fields where the magnetization of CoFe is significantly tilted from the film plane to the magnetic field direction, we find that the observed angular dependence of voltage signals in the CoFe/MgO/Si and CoFe/MgO/Ge contacts are well explained by the OHE, considering the misalignment angle between the external magnetic field and the magnetization of CoFe.Comment: 19 pages, 8 figure

Click-aware purchase prediction with push at the top

Eliciting user preferences from purchase records for performing purchase prediction is challenging because negative feedback is not explicitly observed, and because treating all non-purchased items equally as negative feedback is unrealistic. Therefore, in this study, we present a framework that leverages the past click records of users to compensate for the missing user-item interactions of purchase records, i.e., non-purchased items. We begin by formulating various model assumptions, each one assuming a different order of user preferences among purchased, clicked-but-not-purchased, and non-clicked items, to study the usefulness of leveraging click records. We implement the model assumptions using the Bayesian personalized ranking model, which maximizes the area under the curve for bipartite ranking. However, we argue that using click records for bipartite ranking needs a meticulously designed model because of the relative unreliableness of click records compared with that of purchase records. Therefore, we ultimately propose a novel learning-to-rank method, called P3Stop, for performing purchase prediction. The proposed model is customized to be robust to relatively unreliable click records by particularly focusing on the accuracy of top-ranked items. Experimental results on two real-world e-commerce datasets demonstrate that P3STop considerably outperforms the state-of-the-art implicit-feedback-based recommendation methods, especially for top-ranked items.Comment: For the final published journal version, see https://doi.org/10.1016/j.ins.2020.02.06

Image Scale Estimation Using Surface Textures for Quantitative Visual Inspection

In this study, a learning-based scale estimation technique is proposed to enable quantitative evaluation of inspection regions. The underlying idea is that surface texture of structures (i.e. bridges or buildings) captured on images contains the scale information of the corresponding images, which is represented by pixel per physical dimension (e.g., mm, inch). This allows training a regression model that provides a relationship between surface textures on images and their corresponding scales. Deep convolutional neural network is used to extract scale-related features from the texture patches and estimate their scales. The trained model can be exploited to estimate scales for all images captured from structure surfaces that have similar textures. The capability of the proposed technique is fully demonstrated using data collected from surface textures of three different structures and achieves an overall average scale estimation error of less than 15%

Automated Image Classification for Post-Earthquake Reconnaissance Images

In the aftermath of earthquake events, many reconnaissanceteams are dispatched to collect as much data as possible, movingquickly to capture the damages and failures on our built environments before they are recovered. Unfortunately, only a tiny portionof these images are shared, curated, and utilized. There is a pressing need for a viable visual data organizing or categorizing tool witha minimal manual effort. In this study, we aim to build a system toautomate classifying and analyzing a large volume of post-disastervisual data. Our system called Automated Reconnaissance ImageOrganizer (ARIO) is a web-based tool to automatically categorizing reconnaissance images using a deep convolutional neural net-work and generate a summary report combined with useful metadata. Automated classifiers trained using our ground-truth visualdatabase classify images into various categories that are useful toreadily analyze and document reconnaissance images from post-disaster buildings in the field

Minimally invasive surgery for deep endometriosis

Deep endometriosis (DE) is endometriotic tissue that invades the peritoneum by >5 mm. Surgery is the treatment of choice for symptomatic DE, and laparoscopic surgery is preferred over laparotomy due to better vision and postoperative pain. In this review, we aimed to collect and summarize recent literature on DE surgery and share laparoscopic procedures for rectovaginal and bowel endometriosis

Evaluation of a specific diagnostic marker for rheumatoid arthritis based on cyclic citrullinated peptide

AbstractA specific peptide marker for diagnosing rheumatoid arthritis (RA) was found based on cyclic citrullinated peptide (CCP) using the following three steps: (1) analysis of the binding epitope of autoimmune antibodies using ϵ-aminocaproic acid-modified peptides; (2) RA diagnosis using sequence-modified peptides; and (3) evaluation of the peptides’ diagnostic performance for RA diagnosis. Ninety-five serum samples were analyzed by ELISA and compared using MedCalc (version 15.2.1). Microplate binding ϵ-aminocaproic acid was added to the N- or C-terminal of the CCP sequence. The N-terminal anchoring peptide assay showed 15% higher specificity compared with the C-terminal anchoring peptide assay. Based on this result, the hydrophilic C-terminal sequence of CCP was substituted with a hydrophobic amino acid. Among the sequence-modified peptides, CCP11A (in which alanine was substituted for the 11th amino acid of CCP) assay showed the highest sensitivity (87%) and specificity (100%) for RA diagnosis. Thus, CCP11A was selected as a possible specific marker peptide for RA diagnosis and further analyzed. The results of this analysis indicated that CCP11A showed better specificity than the CCP assay in both healthy individuals (11% better) and OA cohort (20% better). From these results, CCP11A was evaluated as a specific marker for diagnosing RA with higher diagnostic performance

Ectopic adrenal gland tissue in the left ovary of an elderly woman: a case report

Ectopic adrenal gland in the ovary is very rare case, and even more rarer in older women. We reported a case of ectopic adrenal tissue as an incidental finding in left ovary from a 68-year-old woman. She presented with bearing down sensation due to uterine prolapse for 5 years. Upon physical examination, uterine prolapse grade III, cystocele, and rectocele were observed. Ultrasonography findings showed 0.69 cm intramural myoma, and no specific findings were found in the bilateral adnexae. She underwent a total laparoscopic hysterectomy, bilateral salpingo-oophorectomy, and anterior-posterior repair. The final pathologic diagnosis of the case was ectopic adrenal gland tissue in the left ovary and uterine leiomyoma. No eventful reactions were observed during hospitalization and after discharge. Although ectopic adrenal gland rarely occurs in elderly women and in the pelvic ovaries, it has a risk of neoplastic transformation and accompanying germ cell tumor and sex cord tumor. Hence, if the ectopic adrenal gland tissue is suspected during surgery, the tissue should be removed. Additionally, by closely examining the contralateral ovary, determining whether other lesions are suspected is necessary. If the other lesions including germ cell tumor or sex cord tumor are suspected, a biopsy of the contralateral ovarian tissue should be performed. Thus, gynecologists must have knowledge about ectopic adrenal gland tissues