bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulation and optimization of a broadband reflective far ultraviolet polarimeter
Authors: Le Gal Maëlle , López Ariste Arturo , Neiner Coralie , Pertenais Martin 
Published: September 2020

Traditional transmissive polarimetric methods can be used for wavelengths above 123 nm where birefringent materials transmit light and create significant birefringence. Below 123 nm, no suitable solution is known to measure the four Stokes parameters on a large wavelength range. Therefore, we study here an innovative reflective (rather than transmissive) polarimeter working in the far ultraviolet (FUV) range from 90 to 130 nm. We take advantage of the phase shift created by reflections as well as the different reflectivities for

p

(orthogonal

⊥

) and

s

(parallel

∥

to the plane of incidence) polarizations to design an FUV polarimeter. Simulation of the analyzer and modulator using Mueller matrices coupled to polarimetric efficiencies calculations allowed optimization of reflective polarimeters for the first time, to the best of our knowledge. This opens up a new perspective for FUV polarimetry below 123 nm.
Machine Learning and Law and Economics: A Preliminary Overview
Authors: Park Sangchul , Ko Haksoo 
Published: September 2020

Abstract
This paper provides an overview of machine learning models, as compared to traditional economic models. It also lays out emerging issues in law and economics that the machine learning methodology raises. In doing so, Asian contexts are considered. Law and economics scholarship has applied econometric models for statistical inferences, but law as social engineering often requires forward-looking predictions rather than retrospective inferences. Machine learning can be used as an alternative or supplementary tool to improve the accuracy of legal prediction by controlling out-of-sample variance along with in-sample bias and by fitting diverse models to data with non-linear or otherwise complex distribution. In the legal arena, the past experience of using economic models in antitrust and other high-stakes litigation provides a clue as to how to introduce artificial intelligence into the legal decision-making process. Law and economics is also expected to provide useful insights as to how to balance the development of the artificial intelligence technology with fundamental social values such as human rights and autonomy.
Revisiting the First Monastery of Apa Phoibammon A Prosopography and Relative Chronology of Its Connections to the Monastery of Apa Ezekiel within the Monastic Network of Hermonthis during the 6th Century
Authors: Krueger Frederic 
Published: September 2020

Abstract
A reevaluation of the ostraca and graffiti from the First Monastery of Apa Phoibammon-known in scholarship as the original home of bishop Abraham but for little else-reveals close ties to the monastic network of Hermonthis visible in the newly discovered ostraca dossier from the Monastery of Apa Ezekiel, led by Abraham’s predecessor Andrew of Hermonthis in the later 6th century.
Reversine and herbal Xiang–Sha–Liu–Jun–Zi decoction ameliorate thioacetamide-induced hepatic injury by regulating the RelA/NF-κB/caspase signaling pathway
Authors: Mai Zhen-Hao , Huang Yu , Huang Di , Huang Zi-Sheng , He Zhi-Xiang , Li Pei-Lin , Zhang Shuai , Weng Jie-Feng , Gu Wei-Li 
Published: September 2020

AbstractThis study investigated the anti-fibrotic effects of reversine and Chinese medicine Xiang–Sha–Liu–Jun–Zi decoction (XSLJZD) on thioacetamide (TAA)-induced hepatic injury. Sprague-Dawley rats were intraperitoneally administered with TAA, then injected with reversine intraperitoneally, and/or orally provided with XSLJZD. TAA resulted in liver injury with increases in the liver index and levels of serum aspartate aminotransferase (AST) and alanine aminotransferase. Reversine alleviated the liver index and AST level and improved TAA-induced pathological changes but decreased TAA-induced collagen deposition, and α-smooth muscle actin and transforming growth factor-β1 expression. Reversine also modulated the mRNA levels of inflammatory cytokines, such as RelA, interleukin (IL)-17A, IL-22, IL-1β, IL-6, NLR family pyrin domain containing 3, platelet-derived growth factor, and monocyte chemoattractant protein, and suppressed nuclear factor (NF)-κB (p65) phosphorylation and caspase 1 activation. Meanwhile, XSLJZD protected TAA-injured liver without increasing fibrosis and enhanced the regulating effect of reversine on RelA, IL-17A, IL-1β, and MCP-1 cytokines. In conclusion, reversine ameliorates liver injury and inhibits inflammation reaction by regulating NF-κB, and XSLJZD protects the liver through its synergistic effect with reversine on regulating inflammatory cytokines.
A novel calibration phantom for combining echocardiography with electromagnetic tracking
Authors: Kreher Robert , Groscheck Thomas , Qarri Kristjan , Preim Bernhard , Schmeisser Alexander , Rauwolf Thomas , Braun-Dullaeus Rüdiger Christian , Engelhardt Sandy 
Published: September 2020

Abstract
Ultrasound compounding techniques offer the possibility to enlarge the otherwise limited field of view of ultrasound. However, existing works mainly rely on larger ultrasound sensors. In this work, we attach electromagnetic (EM) tracking sensors to small tubular echo probes, namely an intracardiac echocardiographic (ICE) probe and a transesophageal echocardiographic (TEE) transducer. The EM tracking allows, when synchronized to the ultrasound, localization of the probes in either 5 DOF (Degrees of Freedom) or 6 DOF without line-of-sight requirement. For computation of the references between the two systems, we developed a novel customized 3D-printable phantom, which is especially convenient for tubular probes that acquire images laterally. Calibration with the phantom and 3D volume reconstruction was conducted in the Plus Toolkit. The volume reconstructor uses the captured position and orientation information to fuse 2D ultrasound slices into a compounded volume. Mean calibration error is below 2.5 mm for ICE and TEE. An accuracy evaluation of the 3D reconstruction using an object of known geometry revealed that tracking with 5 DOF provides unsatisfactory results, while the combination of 6 DOF and TEE achieved a mean absolute difference of 3.08 mm. Our calibration phantom fCal-Echo1.0 is openly available at http://perk-software.cs.queensu.ca/plus/doc/nightly/modelcatalog/.
Data augmentation for computed tomography angiography via synthetic image generation and neural domain adaptation
Authors: Seemann Malte , Bargsten Lennart , Schlaefer Alexander 
Published: September 2020

Abstract
Deep learning methods produce promising results when applied to a wide range of medical imaging tasks, including segmentation of artery lumen in computed tomography angiography (CTA) data. However, to perform sufficiently, neural networks have to be trained on large amounts of high quality annotated data. In the realm of medical imaging, annotations are not only quite scarce but also often not entirely reliable. To tackle both challenges, we developed a two-step approach for generating realistic synthetic CTA data for the purpose of data augmentation. In the first step moderately realistic images are generated in a purely numerical fashion. In the second step these images are improved by applying neural domain adaptation. We evaluated the impact of synthetic data on lumen segmentation via convolutional neural networks (CNNs) by comparing resulting performances. Improvements of up to 5% in terms of Dice coefficient and 20% for Hausdorff distance represent a proof of concept that the proposed augmentation procedure can be used to enhance deep learning-based segmentation for artery lumen in CTA images.
Fluoroscopy-guided robotic biopsy intervention system
Authors: Özbek Yusuf , Vogele Michael , Plattner Christian , Costa Pedro , Griesser Mario , Wieczorek Matthias 
Published: September 2020

Abstract
Fluoroscopy-guided percutaneous biopsy interventions are mostly performed with traditional free-hand technique. The practical experience of the surgeon influences the duration of the intervention and the radiation exposure for patients and him-/herself. Especially when the placement of heavy and long instruments in double oblique angles is required, manual techniques reach their technical limitations very fast. The system presented herein automatizes the needle positioning using only two 2D scans while the robotic platform guides the intervention. These two images were used to plan the needle pathway and to estimate the pose of the robot using a custom-made end-effector with embedded registration fiducials. The estimated pose was subsequently used to transfer the planed needle path to the robot’s coordinate system and finally to compute the movement parameters in order to align the robot with this plan. To evaluate the system, two phantoms with 11 different targets on it were developed. The targets were punctured, and the application accuracy was measured quantitatively. The solution achieved sub-millimetric accuracy for needle placement (min. 0.23, max. 1.04 in mm). Our approach combines the advantages of fluoroscopic imaging and ensures automatic needle alignment with highly reduced X-ray radiation. The proposed system shows promising potential to be a guidance platform that is easy to combine with available fluoroscopic imaging systems and provides valuable help to the physician in more difficult interventions.
Improving endoscopic smoke detection with semi-supervised noisy student models
Authors: Reiter Wolfgang 
Published: September 2020

Abstract
Laparoscopic surgery consists of many tasks that have to be handled by the surgeon and the operating room personnel. Recognition of situations where action is required enables automatic handling by the integrated OR or notifying the surgical team with a visual reminder. As a byproduct of some surgical actions, electrosurgical smoke needs to be evacuated to keep the vision clear for the surgeon. Building on the success of convolutional neural networks (CNNs) for image classification, we utilize them for image based detection of surgical smoke. As a baseline we provide results for an image classifier trained on the publicly available smoke annotions of the Cholec80 dataset. We extend this evaluation with a self-training approach using teacher and student models. A teacher model is created with the labeled dataset and used to create pseudo labels. Multiple datasets with pseudo labels are then used to improve robustness and accuracy of a noisy student model. The experimental evaluation shows a performance benefit when utilizing increasing amounts of pseudo-labeled data. The state of the art with a classification accuracy of 0.71 can be improved to an accuracy of 0.85. Surgical data science often has to cope with minimal amounts of labeled data. This work proposes a method to utilize unlabeled data from the same domain. The good performance in standard metrics also shows the suitability for clinical use.
Localization of endovascular tools in X-ray images using a motorized C-arm: visualization on HoloLens
Authors: Chen Yenjung , Shah Nilay Yatinkumar , Goswami Subhra Sundar , Lange Annkristin , von Haxthausen Felix , Sieren Malte Maria , Hagenah Jannis , Ernst Floris , García-Vázquez Verónica 
Published: September 2020

Abstract
C-arms are medical devices widely used for image-guided minimally invasive endovascular procedures. This technology requires considerable experience for the physicians to position the C-arm to obtain X-ray images of the endovascular tools. In addition, this image-guided therapy is based on two-dimensional images which lack depth information. The purpose of this study was to develop a system that controls the C-arm movements based on the previous position of the tip of a guide wire and the vessel information, and also displays the estimated tip position (specifically, the virtual line that would join the X-ray source and the projected tip in the flat-panel detector) on an augmented reality device (HoloLens). A phantom study was conducted to evaluate the system using intraoperative cone-beam computed tomography scans to obtain the reference tip position. The mean distance between the tip position (ground truth) and the virtual three-dimensional line was 1.18 mm. The proposed system was able to control the C-arm movements based on the position of the tip of the guide wire. The visualization on HoloLens also allowed a more intuitive understanding of the position of the endovascular tool related to the patient’s anatomy during the intervention.
Robotized ultrasound imaging of the peripheral arteries – a phantom study
Authors: von Haxthausen Felix , Hagenah Jannis , Kaschwich Mark , Kleemann Markus , García-Vázquez Verónica , Ernst Floris 
Published: September 2020

Abstract
The first choice in diagnostic imaging for patients suffering from peripheral arterial disease (PAD) is 2D ultrasound (US). However, for a proper imaging process, a skilled and experienced sonographer is required. Additionally, it is a highly user-dependent operation. A robotized US system that autonomously scans the peripheral arteries has the potential to overcome these limitations. In this work, we extend a previously proposed system by a hierarchical image analysis pipeline based on convolutional neural networks (CNNs) in order to control the robot. The system was evaluated by checking its feasibility to keep the vessel lumen of a leg phantom within the US image while scanning along the artery. In 100% of the images acquired during the scan process the whole vessel lumen was visible. While defining an insensitivity margin of 2.74 mm, the mean absolute distance between vessel center and the horizontal image center line was 2.47 mm and 3.90 mm for an easy and complex scenario, respectively. In conclusion, this system presents the basis for fully automatized peripheral artery imaging in humans using a radiation-free approach.
Surgical phase recognition by learning phase transitions
Authors: Sahu Manish , Szengel Angelika , Mukhopadhyay Anirban , Zachow Stefan 
Published: September 2020

Abstract
Automatic recognition of surgical phases is an important component for developing an intra-operative context-aware system. Prior work in this area focuses on recognizing short-term tool usage patterns within surgical phases. However, the difference between intra- and inter-phase tool usage patterns has not been investigated for automatic phase recognition. We developed a Recurrent Neural Network (RNN), in particular a state-preserving Long Short Term Memory (LSTM) architecture to utilize the long-term evolution of tool usage within complete surgical procedures. For fully automatic tool presence detection from surgical video frames, a Convolutional Neural Network (CNN) based architecture namely ZIBNet is employed. Our proposed approach outperformed EndoNet by 8.1% on overall precision for phase detection tasks and 12.5% on meanAP for tool recognition tasks.
Wall enhancement segmentation for intracranial aneurysm
Authors: Niemann Annika , Larsen Naomi , Preim Bernhard , Saalfeld Sylvia 
Published: September 2020

Abstract
We present a tool for automatic segmentation of wall enhancement of intracranial aneurysms in black blood MRI. The results of the automatic segmentation with several configurations is compared to manual expert segmentations. While the manual segmentation includes some voxels of lower intensity not present in the automatic segmentation, overall the volume of the automatic segmentation is higher.
Integrative analysis with a system of semiparametric projection non-linear regression models
Authors: Yuan Ao , Wu Tianmin , Fang Hong-Bin , Tan Ming T. 
Published: September 2020

Abstract
In integrative analysis parametric or nonparametric methods are often used. The former is easier for interpretation but not robust, while the latter is robust but not easy to interpret the relationships among the different types of variables. To combine the advantages of both methods and for flexibility, here a system of semiparametric projection non-linear regression models is proposed for the integrative analysis, to model the innate coordinate structure of these different types of data, and a diagnostic tool is constructed to classify new subjects to the case or control group. Simulation studies are conducted to evaluate the performance of the proposed method, and shows promising results. Then the method is applied to analyze a real omics data from The Cancer Genome Atlas study, compared the results with those from the similarity network fusion, another integrative analysis method, and results from our method are more reasonable.
The effect of the stale bread flour addition on flour and bread quality
Authors: Meral Hacer , Karaoğlu M. Murat 
Published: September 2020

Abstract
In this study, the effect of the flour, which was obtained from stale bread, on flour and bread quality was investigated. The bread that was staled at refrigerator for 7 days was prepared as whole and crumb, and was grinded to convert into flour. The staled whole and crumb bread flours were stored at −18 °C and used to replace 0, 15, 30 and 45% of wheat flour. Then microbiological and physicochemical properties of flours; physical, textural and sensory properties of bread obtained from these composite flours were investigated. We concluded that stale bread flour could be used for bread production at the level of 15%. If the total bread production and consumption is considered, this addition level could provide a significant amount of waste bread recycling each year.
Evaluation of efficacy of Bombax ceiba extract and its major constituent, mangiferin in streptozotocin (STZ)-induced diabetic rats
Authors: Bhargava Sushil , Shah Mamta B. 
Published: September 2020

Abstract

Objectives
Based on the ethno-medicinal use of Bombax ceiba leaf, in the treatment of diabetes, the present study is aimed at evaluation of antidiabetic potential of leaf extract and its major constituent mangiferin.

Methods
Efficacy of hydroalcoholic extract of Bombax ceiba leaf (BCL, 200 and 400 mg/kg body wt.) and mangiferin (MF, 20 mg/kg body wt) was studied in streptozotocin (STZ)-induced diabetic rats and associated complications visually, retinopathy, cardiopathy and nephropathy. After 20 days, serum glucose, lipid profiles, glycol-hemoglobin % (HbA1c%), liver enzymes activity and glycogen content, and histopathology of the pancreas were corroborated. The study was coxswained for development of validated RP-HPLC method for the estimation of MF in BCL.

Results
The results demonstrated significant reductions in the levels of glucose (p<0.001), glycated hemoglobin (HbA1c%, p<0.001), cholesterol, triglycerides and low-density lipoproteins, and concurrent elevation of high density lipoproteins level in the groups administered BCL and MF relative to the controls. It significantly reversed most of the altered metabolic and oxidative stress parameters and histopathological changes. Mangiferin content in BCL was found to be 0.04%w/w.

Conclusions
The anti-diabetic effects of BCL may be attributed to its ability to enhance insulin release, antioxidant and hypolipidemic potential.
Influence of different methods and anticoagulants on platelet parameter measurement
Authors: Mannuß Steffen 
Published: September 2020

Abstract
Platelets are the smallest and perhaps the most versatile components of human blood. Besides their role in coagulation and the maintenance of vascular integrity, they are involved in many physiological processes, ranging from immune response and leukocyte recruitment to the production of antimicrobial peptides and immune-suppressive factors like TGF-β. These versatile abilities make platelets interesting for researchers from different disciplines. However, beside profound investigation into platelets’ physiological role, there is a need for correct, standardized and thus reproducible quantification of platelet parameters. Mean platelet volume (MPV) is a widespread prognostic marker for several conditions, such as, acute coronary syndrome, chronic kidney disease and liver cirrhosis. Platelet activation is regarded as a marker for inflammatory processes, for example in autoimmune diseases such as type-1 diabetes, systemic lupus erythematosus and rheumatoid arthritis. The monitoring of platelet function is relevant for patients receiving antiplatelet medication. Platelet parameter measurement is affected by the choice of in vitro anticoagulant, the measurement technology and the time delay after sampling. This review focuses on the pre-analytical variability that arises as a result of the use of different in vitro anticoagulants and analyzer technologies when determining platelet parameters, since, even approximately 180 years after the discovery of platelets, there is still no standardized procedure.
Broadband dispersive free, large, and ultrafast nonlinear material platforms for photonics
Authors: Niu Xinxiang , Hu Xiaoyong , Lu Cuicui , Sheng Yan , Yang Hong , Gong Qihuang 
Published: September 2020

Abstract
Broadband dispersion free, large and ultrafast nonlinear material platforms comprise the essential foundation for the study of nonlinear optics, integrated optics, intense field optical physics, and quantum optics. Despite substantial research efforts, such material platforms have not been established up to now because of intrinsic contradictions between large nonlinear optical coefficient, broad operating bandwidth, and ultrafast response time. In this work, a broadband dispersion free, large and ultrafast nonlinear material platform based on broadband epsilon-near-zero (ENZ) material is experimentally demonstrated, which is designed through a novel physical mechanism of combining structural dispersion and material dispersion. The broadband ENZ material is constructed of periodically nanostructured indium tin oxide (ITO) films, and the structure is designed with the help of theoretical predictions combined with algorithm optimization. Within the whole broad ENZ wavelength range (from 1300 to 1500 nm), a wavelength-independent and large average nonlinear refractive index of −4.85 × 10−11 cm2/W, which is enlarged by around 20 times than that of an unstructured ITO film at its single ENZ wavelength, and an ultrafast response speed at the scale of Tbit/s are experimentally reached simultaneously. This work not only provides a new approach for constructing nonlinear optical materials but also lays the material foundation for the application of nanophotonics.
The effect of Plantago psyllium seed husk flour on the properties of cellulose sheet
Authors: Halász Katalin , Kóczán Zsófia , Tóth Annamária , Pásztory Zoltán , Preklet Edina 
Published: September 2020

Abstract
This study examined the use of Plantago psyllium seed husk flour as paper additive with the aim of improving the properties of cellulose sheet. The husk flour was added in 5 wt%, 10 wt%, 20 wt% and 30 wt% to the cellulose suspensions and its effect on the handsheet properties was studied. The results showed that the direct addition of husk flour highly improves the mechanical properties of the handsheets like tensile index (with up to 400 %), burst index (with up to 600 %) and tear index (with up to 1200 %). Cobb and contact angle tests with distilled water showed that the handsheets containing husk flour are more hydrophobic compared to the unmodified handsheets. The Cobb-Unger and contact angle tests with oil revealed that the additive reduces the oil absorbency of the handsheets as well, at the highest by 86 %. Additionally, the water vapor and especially the air barrier properties were improved. The 2,2-diphenyl-1-picrylhydrazyl (DPPH) antioxidant capacity test showed that the modified handsheets had free radical scavenging properties. The direct addition of Plantago psyllium seed husk flour can be a promising, easy and green method to improve the mechanical and barrier properties, oil and water resistance of cellulose sheets.