Miracle-dz/UniFAR-FTUs huggingface dataset:
Anomalous aortic origin of right and circumflex coronary arteries - procedural risks during combined aortic valve replacement and coronary artery bypass grafting

SUMMARYIntroduction Anomalous aortic origin of the right and the circumflex coronary arteries presents extremely rare and potentially dangerous combination in patients scheduled for combined coronary bypass grafting and aortic valve replacement surgery. We report this illustrative case to emphasize the importance of meticulous diagnostic setup enabling the surgeon to anticipate and avoid numerous possible pitfalls. Case outline A 74-year-old woman, with anterior-wall myocardial infarction and aortic valve stenosis, underwent successful combined coronary artery bypass grafting and aortic valve replacement. Preoperative coronary angiography revealed unusually high take-off of the right main coronary trunk and anomalous origin and course of the circumflex coronary artery. Anatomy of both anomalous coronary arteries in the light of underlying surgical pathology necessitated a meticulous preparation and caution during successive phases of surgical treatment. Conclusion Estimating potential procedural risk should be standard practice for each patient with known congenital coronary artery anomalies, regardless of the natural risk imposed by a particular anomaly. Preoperative evaluation of coronary circulation, with high surgical awareness and knowledge of different congenital coronary artery anomalies, should be a standard approach in cardiac surgical practice. This would add a predictive value for an actual procedural risk in cases of previously unrecognized anomalies.
A SURVEY ON FEATURE SELECTION FOR CHRONIC DISEASES CLASSIFICATION SYSTEMS

: The mortality rate due to chronic diseases is increasing day by day. Timely diagnosis at an early stage can help in taking appropriate measures for prevention and mitigation of these diseases along with better prognosis. In this paper we present a survey on various approaches of feature selection and classification techniques used for prediction and identification of these diseases. We shall discuss the importance of feature selection methodologies for improving the accuracy and performance of classification systems. Feature selection, a dimensionality reduction technique can help deal with the problem of “curse of dimensionality” as large data sets means huge number of records and even greater number of features and also enhance its computational efficiency. The results and performance yielded by various classification algorithms after application of these pre-processing techniques gives us promising results.
Student and instructor attitudes toward CALL and MALL in the L2 classroom

As part of an ongoing study focusing on language learner and instructor attitudes toward the use of computers and mobile devices in second language (L2) learning contexts, the authors attempt to identify to what degree language instructors value the use of computers and mobile devices in their teaching. We compare the responses of a survey administered to an “in-house” group of instructors within two faculties of a private university in Tokyo, Japan, with the responses collected from a similar survey administered to instructors solicited through various CALL organizations. The number of respondents of the “in-house” survey during the first three years was relatively low; however, in the final year was considerably much higher, with the number from both full-time and part-time staff totaling 34. The total number of survey respondents from the CALL organizations totaled 121, with the participants’ places of employment ranging from Europe to the Asia Pacific Rim. In addition to offering an interpretation of a sampling of the Likert scale items found on the surveys, the authors focus on comparing the responses offered by both groups of instructors regarding which skills they focused on in the CALL classroom, as well as what mobile applications they encouraged their students to use.
Interactions between complement and cellular mediated mechanisms of monoclonal antibody therapy

Antibody dependent cellular cytotoxicity (ADCC) and complement fixation both appear to play a role in mediating anti-tumor effects of monoclonal antibodies (mAbs), including rituximab. I evaluated the relationship between rituximab-induced complement fixation, NK cell activation, and NK cell mediated ADCC. Down-modulation of NK cell CD16 and NK cell activation induced by rituximab-coated target cells was blocked by human serum but not heat-inactivated serum. This inhibition was also observed in the absence of viable target cells. C1q and C3 in the serum were required for these inhibitory effects, while C5 was not. An antibody that stabilizes C3b on the target cell surface enhanced the inhibition of NK cell activation induced by rituximab-coated target cells. Binding of NK cells to rituximab-coated plates through CD16 was inhibited by the fixation of complement. C5-depleted serum failed to induce complement-mediated lysis but blocked NK cell-mediated ADCC. These data suggest that C3b deposition induced by rituximab-coated target cells inhibits the interaction between the rituximab Fc and NK cell CD16, thereby limiting the ability of rituximab-coated target cells to induce NK activation and ADCC. Introduction Monoclonal antibodies (mAbs) are now a mainstay of therapy for a number of cancers. Rituximab was the first chimeric mAb to be approved for clinical use and remains the most extensively utilized mAb in cancer therapy. Rituximab binding of CD20 has been shown to signal apoptosis in a subset of lymphoma cell lines (121). However, there is little evidence that signaling plays an important role in clinical
Multisensor online 3D view planning for autonomous underwater exploration

This study presents a novel octree‐based three‐dimensional (3D) exploration and coverage method for autonomous underwater vehicles (AUVs). Robotic exploration can be defined as the task of obtaining a full map of an unknown environment with a robotic system, achieving full coverage of the area of interest with data from a particular sensor or set of sensors. While most robotic exploration algorithms consider only occupancy data, typically acquired by a range sensor, our approach also takes into account optical coverage, so the environment is discovered with occupancy and optical data of all discovered surfaces in a single exploration mission. In the context of underwater robotics, this capability is of particular interest, since it allows one to obtain better data while reducing operational costs and time. This study expands our previous study in 3D underwater exploration, which was demonstrated through simulation, presenting improvements in the view planning (VP) algorithm and field validation. Our proposal combines VP with frontier‐based (FB) methods, and remains light on computations even for 3D environments thanks to the use of the octree data structure. Finally, this study also presents extensive field evaluation and validation using the Girona 500 AUV. In this regard, the algorithm has been tested in different scenarios, such as a harbor structure, a breakwater structure, and an underwater boulder.
Distributed stream-processing framework for graph-based sequence alignment

DISTRIBUTED STREAM-PROCESSING FRAMEWORK FOR GRAPH-BASED SEQUENCE ALIGNMENT Alim Şükrücan Gökkaya M.S. in Computer Engineering Advisor: Can Alkan January 2020 Optimized the sequence alignment pipelines are needed to minimize the time required to complete processing the short-read genomic data. Today there are many sequence alignment tools exist, yet few of them are capable of directly ingesting the streaming base-call data. The sequencing has to be entirely completed before the mainstream aligners can begin mapping the reads to the reference. The sequencing process can take days to complete. The output is then needs to be demultiplexed into individual reads and aligned to the reference, which can take several more hours. Overall time of a genomic analysis can be shortened significantly by progressively computing the alignments at the time when the reads are still being generated. It is important to have genomic analysis done as quickly as possible, especially in life critical situations. Here we introduce a distributed stream processing framework for aligning short-reads into a graph representation of the genome. The massively parallel nature of the genomic sequencing data requires a massively parallel computation architecture. Thus we have designed our pipeline called R2GFlow to align many reads to a de Bruijn graph in parallel. Our aligning method is specialized for the sequencing technologies that are based on base-call cycles, such as produced by Illumina. The results are made available soon after the final bases from the sequencing devices has been emitted. R2GFlow is available at https://github.com/BilkentCompGen/r2g2
Methods and Strategy for Monitoring Race Distribution and Identification of Resistance Genes to Bacterial Leaf Blight (Xanthomonas campestris pv. oryzae) in Rice

For controlling bacterial leaf blight of rice, caused by Xanthomonas campestris pv. oryzae, the use of resistant cul ti vars is the most economical and effective method due to the scarcity of effective bactericidal agents and to the need for preserving the environment. Against this background, the resistance genes to this disease so far identified will be reviewed. Under the collaboration between the Tropical Agriculture Research Center, Japan and the International Rice Research Institute, Philippines, the genes identified were rearranged from Xa-1 to Xa-12 based on the numbering system of rice gene symbols and them near-isogenic lines with single resistance genes were developed. By using these near-isogenic lines, the strategy for monitoring the race distribution and the methods of identification of new resistance genes are reviewed. Discipline: Pl an breeding Additional keywords: allelism test, differentials, near-isogenic line, plant disease
Shroom2 regulates endothelial morphogenesis and centrosome duplication through the specific sub-cellular recruitment of Rho-kinase

The ability of epithelial cells to change shape is essential to the patterning of tissues and organs during development of the vertebrate embryo. Epithelial morphogenesis is mediated by the molecular regulation of cytoskeletal dynamics which underlies cellular adhesion, motility, polarity, and proliferation. The Shroom family of proteins regulates epithelial morphogenesis by promoting MyosinII-dependent changes in epithelial morphology through the ability to bind both F-actin and Rho kinase (Rock). Shroom3 is necessary to induce apical constriction of the neural epithelium and is required for proper neural tube closure during development. However, the roles of other family members are unknown. This work seeks to determine the role and mechanism of action for Shroom2 in epithelial cell biology. Through RNAi, the loss of Shroom2 reduces contractility of endothelial cells. Shroom2 physically interacts with Rock and is necessary for its cortical localization. By impeding Rock localization and reducing contractility, Shroom2 knockdown alters cytoskeletal organization, adhesion, and motility which ultimately affects in vitro angiogenesis. During these studies, it also became clear that Shroom2 localizes to the centrosome where it is required to maintain efficient centrosome duplication in a Rock-dependent manner. The results described here expand a role for the Shroom proteins in the sub-cellular localization of Rock which mediates a subset of Rock functions within epithelial cells.
A performance comparison of convolutional neural network based anthropomorphic model observer and linear model observer for signal-known statistically detection tasks

Signal-known-statistically (SKS) detection task is more relevant to the clinical tasks compared to signal-knownexactly (SKE) detection task. However, anthropomorphic model observers for SKS tasks have not been studied as much as those for SKE tasks. In this study, we compare the ability of conventional model observers (i.e., channelized Hotelling observer and nonprewhitening observer with an eye-filter) and convolutional neural network (CNN) to predict human observer performance on SKS and background-known-statistically tasks in breast cone beam CT images. For model observers, we implement 1) the model which combines the responses of each signal template and 2) two-layer CNN. We implement two-layer CNN in linear and nonlinear schemes. Nonlinear CNN contains max pooling layer and nonlinear activation function which are not contained in linear CNN. Both linear and nonlinear CNN based model observers predict the rank of human observer performance for different noise structures better than conventional model observers.
Ecological status and threats of marsh crocodiles (Crocodilus palustris) in Manghopir Karachi.

This study represents survey data and reviews the threats and ecological status of Marsh crocodiles (Crocodylus palustris) in the captive habitat of Manghopir Karachi. In Pakistan, only one crocodilian species of Marsh crocodile recorded. The present study on threats and ecological status of Marsh crocodiles was carried out from 2006 to 2009 during which 116 crocodiles were recorded from MP Karachi. The observation revealed that total number of crocodiles were 116 in the studied areas of MP Karachi among them 80 were adult crocodile, 20 were juveniles and 16 were hatchlings. The most people consider them as a serious and potentially dangerous pest and so do not regret their disappearance from their neighborhood. In Pakistan, the concept of utilization of wildlife is still anathema to a large segment of the crocodile population and they can be ranched. Currently the crocodile population is threatened by environmental deterioration, hazard chemicals in water resources, hunting pressure and loss of habitat.
A 2-D Calibration Scheme for Resistive Nonvolatile Memories

Resistive nonvolatile memories (NVMs) promise significant performance improvement over existing NVM candidates. However, fabrication nonidealities and parasitics on the access path cause cell location-dependent variations in the total resistance received at the read circuitry. Write characteristics delivered to each cell, as well as the optimal write conditions for each cell, are also location-dependent. In this article, we propose a 2-D calibration scheme to address these variations. The proposed scheme joins row and column calibrations to create a correction grid at each crosspoint on the array and effectively cancels many spatial patterns. The enabling circuit and algorithmic modifications are described. We assess the 2-D calibration scheme in a 28-nm $256\times 256$ memory array, and show reduction in variability across multiple gradient patterns compared to conventional calibration methods. For the same calibration granularity, 2-D calibration achieves between 41% and 99% improvement depending on the amount of calibration bits. For the same amount of total calibration bits, the 2-D calibration scheme reduces the variability between 39% and 99%.
Circulating exosomes cause loss of immunological balance in multiple sclerosis

Exosomes are small extracellular vesicles, which are secreted by various cell types and transferred into target cells. They contain nucleotides, proteins and lipids, which serve as intercellular signals. Among a wide range of cargoes, microRNAs (miRNA) are under intensive investigation in several diseases, such as cancer and neurodegeneration. Exosomal miRNAs are unique in that they can affect gene expression in target cells as extrinsic miRNAs. They are different from intrinsic miRNAs that are transcribed and function in the same cell. Although several intrinsic miRNAs are critically involved in the development and function of immune cells, and accordingly in autoimmune diseases, the roles of extracellular miRNAs had not yet been fully understood. Recently, we found that the expression profile of miRNAs in circulating exosomes was different in patients with multiple sclerosis (MS) compared with healthy controls (HC). Among them, let-7i, miR-19b, miR-25, and miR-92a were increased in exosomes from patients with MS (MS-exosome). After human primary T cells were cultured with exosomes, the frequency of regulatory T cells (Treg cell), that were determined as IFN-c IL-17A Foxp3CD4 T cells, was lower in the presence of MS-exosome than healthy control-exosome. Furthermore, transfection of let-7i similarly decreased the Treg cell frequency,
La hipertrigliceridemia como marcador temprano de resistencia a la insulina en obesidad infanto-juvenil

Introduccion: la obesidad en infantes y adolescentes constituye un problema de salud publica en aumento. La resistencia a la insulina es una reduccion de respuesta fisiologica de los tejidos diana a la accion de la insulina. Objetivo: determinar el valor de la hipertrigliceridemia e hiperglucemia como marcadores tempranos de resistencia a la insulina en ninos y adolescentes obesos. Metodos: el estudio fue de enfoque cuantitativo, diseno no experimental, corte transversal, de tipo observacional y correlacional. La poblacion la constituyeron ninos y adolescentes con sobrepeso u obesidad, atendidos en la consulta externa del Hospital "Dr. Francisco Icaza Bustamante". Resultados: se demostro la utilidad de parametros bioquimicos como predictores precoces de insulinorresistencia. El 37,4 % presento hipertrigliceridemia, 19,8 % hiperglucemia y el 51,6 % insulinorresistencia. El promedio mas elevado de trigliceridos fue encontrado en el grupo etario de 6 a 10 anos, y en el sexo masculino. El analisis estadistico demostro asociacion significativa entre hipertrigliceridemia e insulinorresistencia (p< 0,05). Conclusiones: la hipertrigliceridemia tiene valor predictivo de resistencia a la insulina en obesidad infanto-juvenil.
Identifying and Predicting Financial Earthquakes Using Hawkes Processes

This dissertation attempts to identify and predict earthquakes in the financial market (financial crashes) using Hawkes processes. Models based on Hawkes processes were first used in the earthquake literature. The dissertation shows Hawkes processes also match investors' self-exciting herding behavior around crashes, which has similar characteristics to the self-exciting behavior of seismic activity around earthquakes. In Chapter 2 an Early Warning System based on Hawkes models is developed that indicates the arrival of a crash within a trading week. EWS based Hawkes model outperform EWS based on well-known and commonly used volatility models, proving that these models do not capture all information that can be used to predict crashes. Specification tests for Hawkes models with a specific focus on testing for cross-excitation, are designed in Chapter 3. Chapter 3 as well as Chapter 4, indicate that shocks in one financial market affect the occurrence (and magnitude) of shocks in other financial markets. Moreover, comparing predictions of models with and without cross-excitation, more accurate predictions are obtained including cross-excitation. The last Chapter (Chapter 5) develops methods to estimate non-affine Hawkes models using the information in option prices with the aid of Machine Learning techniques.
Cigarette Smoking Is Correlated With the Periventricular Hyperintensity Grade on Brain Magnetic Resonance Imaging

Background and Purpose A few studies have observed a significant inverse correlation between cigarette smoking or lipid abnormalities and periventricular hyperintensities (PVHs) on T2-weighted magnetic resonance imaging (MRI) scans of the brain, which is surprising because smoking and hyperlipidemia are considered risk factors for cerebrovascular disease. We investigated the relation between smoking and lipid abnormalities and PVHs on T2-weighted MRIs. Methods MRI scans were performed in 253 patients over the age of 40 years, and PVHs were assessed retrospectively by use of a five-point scale. Patients who were receiving medical treatment for hyperlipidemia were excluded. Serum levels of total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides were determined in the fasting state by an automated enzymatic procedure. The low-density lipoprotein (LDL) cholesterol level was calculated by use of Friedewald’s equation. Age, sex, hypertensive status, antihypertensive treatment, presence .
Cognitive computing tools in architectural project management education : approach, process and evaluation : research article

The teaching of Project and Practice Management to architecture students doing professional masters degree programmes at the University of Pretoria incorporates a variety of aspects related to planning, scheduling, finance, monitoring and control. In an effort to train future professionals in skills for the workplace, the module on Practice Management is using commercial off-the-shelf software (COTS) as cognitive tools for simulating real-world architectural management. This paper reports on and evaluates the process whereby students generate their own framework of inter-linked spreadsheets and scheduling charts and contextually apply it, within their personal thesis projects, to integrate key aspects of management and financial control. The tools are used to manipulate knowledge and their interactivity provides dynamic modelling for decision making and the exploration of alternatives. Use of these cognitive management tools synergistically fosters cognition, reflection and comprehension of project management principles. Students' perspectives on the venture are evaluated, the findings reported and discussed, and minor adjustments suggested for future offerings of the module. Die dosering van projekbestuur vir argitekuurstudente in die professionele meestersgraad-programme aan die Universiteit van Pretoria sluit 'n verskeidenheid aspekte in wat verband hou met beplanning, skedulering, finansiering, monitering en beheer. In 'n poging om toekomstige professionele praktisyns vir die werkplek te bekwaam, word kommersieel beskikbare programmatuur as kognitiewe gereedskap in hierdie module in Praktykbestuur aangewend om praktiese bestuur vir argitekte te simuleer. Hierdie artikel doen daaroor verslag. Die proses waar studente eie raamwerke van onderling verbinde spreitabelle en skeduleringskaarte formuleer, dit kontekstueel tot eie skripsieprojekte aanwend om sleutelkonsepte van bestuur en finansiele beheer te integreer, word evalueer. Die gereedskap word gebruik om kennis te verteenwoordig en hulle wisselwerking voorsien dinamiese modulering vir besluitneming en die soeke na alternatiewes. Die gebruik van hierdie kognitiewe gereedskap vir projekbestuur bevorder sinergetiese bewustheid, besinning en begrip vir die beginsels van projekbestuur. Persepsies van studente oor die module word evalueer, verslag word oor die bevindings gedoen en bespreek en verstellings vir toekomstige aanbieding van die module word voorgestel.
Special issue on user modeling for web-based learning

With the rapid development of online learning resources such as Massive Open Online Courses (MOOCs) and user-generated contents in Web 2.0 communities, user modeling techniques, having become increasingly important for web-based e-learning systems, are exploited to assist various e-learning applications (e.g., personalized search/recommendation of learning resources, identification of learning interests/styles, and facilitation of interactions between learners and instructors). Also, the design of a user model is believed to have influence on such function modules as the test module and the plan agent of users (Ciloglugil & Inceoglu, 2012). The users’ learning experiences and effectiveness may therefore be affected to a large extent by user models (Kay 2008; Cook, Kay, & Kummerfeld, 2015). As learning experiences and effectiveness is a critical issue for e-learning systems, this special issue aims to provide an insight into recent advancements of user models for promoting personalized learning according to users’ preferences, learning styles, background knowledge, etc.