Miracle-dz/UniFAR-FTUs huggingface dataset:
How prenatal head ultrasound reference ranges affect evaluation of possible fetal microcephaly

Abstract Objectives Different fetal ultrasound (US) nomograms of the head circumference (HC) have been established; however, comparisons between the detection rates of microcephaly among US nomograms are few and inconsistent. We aimed to compare the prenatal diagnostic rate of fetal microcephaly (FM) among four widely used US nomograms of the fetal HC, when applied to the same group of fetuses. Methods We retrospectively identified singleton pregnancies complicated by fetal HC < 5th percentile for gestational age (GA) by US, without other risk factors for FM and with normal fetal brain MRI. Raw values of HC by US were converted to z-scores using four nomograms (Chervenak = A, Hadlock = B, Gelber = C, Papageorghiou = D). Z-scores value of the HC were classified as normal, possible normal, or microcephaly if values were >−2, ≤ −2 and >−3, or ≤ −3, respectively and compared among the four nomograms. Results Fifty one fetuses at a mean (±SD) GA of 28 (±4) weeks were included. The four nomograms resulted in different z-score values of the fetal HC for the same subject (p < .001) and none of them showed 100% agreement. Reference C and D showed the highest agreement in classifying subjects as normal, possible normal, or with microcephaly (simple Kappa = 0.8915, % agreement = 94.1%), while A and B had the lowest agreement (simple Kappa = 0.0977, % agreement = 51.0%). Conclusions Despite the use of similar prenatal cutoff z-score values of the fetal HC, the four nomograms led to different diagnostic rates of FM. More consistent diagnostic criteria are therefore needed to define FM, especially in the absence of other risk factors for FM and normal fetal brain MRI, since the prenatal diagnosis can affect pregnancy management.
BK Polyomavirus Virus Glomerular Tropism: Implications for Virus Reactivation from Latency and Amplification during Immunosuppression

BK polyomavirus (BKPyV), or BKV infection, is ubiquitous and usually non-pathogenic, with subclinical infections in 80–90% of adults worldwide. BKV infection is often associated with pathology in immunocompromised individuals. BKV infection often is associated with renal impairment, including ureteral stenosis, hemorrhagic cystitis, and nephropathy. BKV infection is less commonly associated with pneumonitis, retinitis, liver disease, and meningoencephalitis. BKV is known to replicate, establish latency, undergo reactivation, and induce clinical pathology in renal tubular epithelial cells. However, recent in vitro studies support the notion that BKV has expanded tropism-targeting glomerular parenchymal cells of the human kidney, which could impact glomerular function, enhance inflammation, and serve as viral reservoirs for reactivation from latency during immunosuppression. The implications of BKV expanded tropism in the glomerulus, and how specific host and viral factors that would contribute to glomerular inflammation, cytolysis, and renal fibrosis are related to BKV associated nephropathy (BKVAN), have not been explored. The pathogenesis of BKV in human glomerular parenchymal cells is poorly understood. In this review, I examine target cell populations for BKV infectivity in the human glomerulus. Specifically, I explore the implications of BKV expanded tropism in the glomerulus with regard viral entry, replication, and dissemination via cell types exposed to BKV trafficking in glomerulus. I also describe cellular targets shown to be permissive in vitro and in vivo for BKV infection and lytic replication, the potential role that glomerular parenchymal cells play in BKV latency and/or reactivation after immunosuppression, and the rare occurrence of BKV pathology in glomerular parenchymal cells in patients with BKVAN.
Antimicrobial Blue Light Inactivation of Microbial Isolates in Biofilms

Biofilms cause more than 80% of infections in humans, including more than 90% of all chronic wound infections and are extremely resistant to antimicrobials and the immune system. The situation is exacerbated by the fast spreading of antimicrobial resistance, which has become one of the biggest threats to current public health. There is consequently a critical need for the development of alternative therapeutics. Antimicrobial blue light (aBL) is a light‐based approach that exhibits intrinsic antimicrobial effect without the involvement of exogenous photosensitizers. In this study, we investigated the antimicrobial effect of this non‐antibiotic approach against biofilms formed by microbial isolates of multidrug‐resistant bacteria.
Hegemonic Masculinity Attitudes Toward Female Genital Mutilation/Cutting Among a Sample of College Students in Northern and Southern Sierra Leone

Introduction: Female genital mutilation or cutting (FGM/C) is a public health problem. Approximately three million women and girls undergo FGM/C every year, worldwide. The purpose of the study was to assess the influence of education on hegemonic masculinity attitudes between male and female students and whether parental education differentiated the groups. Method: A cross-section design was used. Data were collected through a survey response from 338 students in May 2017. The data were analyzed using chi-square and correlational tests. Results: Education did not change the attitudes of students toward FGM/C (χ2 = 3.64, p = .16); however, parental education had an influence on both male and female students’ attitudes toward FGM/C. Discussion: The study suggests that education alone may not be sufficient to end FGM/C practice. A comprehensive community-led strategy incorporating culturally congruent health care to involve multiple parties of health professionals, religious leaders, government, and policy makers may be needed to address the problem.
Automatic Identification of Individual rpoB Gene Mutations Responsible for Rifampin Resistance in Mycobacterium tuberculosis by Use of Melting Temperature Signatures Generated by the Xpert MTB/RIF Ultra Assay

Molecular surveillance of rifampin-resistant Mycobacterium tuberculosis can help to monitor the transmission of the disease. The Xpert MTB/RIF Ultra assay detects mutations in the rifampin resistance-determining region (RRDR) of the rpoB gene by the use of melting temperature (Tm) information from 4 rpoB probes which can fall in one of the 9 different assay-specified Tm windows. ABSTRACT Molecular surveillance of rifampin-resistant Mycobacterium tuberculosis can help to monitor the transmission of the disease. The Xpert MTB/RIF Ultra assay detects mutations in the rifampin resistance-determining region (RRDR) of the rpoB gene by the use of melting temperature (Tm) information from 4 rpoB probes which can fall in one of the 9 different assay-specified Tm windows. The large amount of Tm data generated by the assay offers the possibility of an RRDR genotyping approach more accessible than whole-genome sequencing. In this study, we developed an automated algorithm to specifically identify a wide range of mutations in the rpoB RRDR by utilizing the pattern of the Tm of the 4 probes within the 9 windows generated by the Ultra assay. The algorithm builds a RRDR mutation-specific “Tm signature” reference library from a set of known mutations and then identifies the RRDR genotype of an unknown sample by measuring the Tm distances between the test sample and the reference Tm values. Validated using a set of clinical isolates, the algorithm correctly identified RRDR genotypes of 93% samples with a wide range of rpoB single and double mutations. Our analytical approach showed a great potential for fast RRDR mutation identification and may also be used as a stand-alone method for ruling out relapse or transmission between patients. The algorithm can be further modified and optimized for higher accuracy as more Ultra data become available.
Teaching QSEN Competencies through High-Risk Newborn Simulation: A Case Study

The Quality and Safety Education for Nurses (QSEN) project calls for all nurses to be competent in collaboration and teamwork, patient-centered care, and patient safety. The following collective case study examines the implementation and outcomes of a high-risk newborn simulation on knowledge, skills, and attitudes of junior BSN students enrolled in a maternal-child nursing course. The analysis revealed major themes of fragmentation, overconfidence with medication administration, and appreciation for the role of the registered nurse.
UvA-DARE ( Digital Academic Repository ) Fingermarks , more than just a ridge pattern

Obtaining full DNA profiles from latent fingermarks is a difficult task. DNA levels in fingermarks are typically below or close to detection limits and highly variable between fingermarks. Currently, methods which can estimate in situ the DNA content non-destructively are lacking. In order to determine whether the intensity of autofluorescence light can be used to indicate the DNA content in fingermarks, in this pilot study, the relationship between DNA content and autofluorescence of fresh fingermarks is investigated. Thereto, fingermarks were left half on white tiles and half on plastic sheets. The partial marks on white tiles were used to evaluate the intensity of autofluorescence of the fingermarks using a UV crime-lite® torch. The part of the fingermark left on plastic sheets was used for human-specific DNA quantification. Autofluorescence images were digitally recorded and their intensities were off-line determined subjectively by multiple observers. For statistical analysis a Spearman’s rank correlation analysis was performed. In two of the three series a moderate, but significant correlation could be found between the DNA content and the autofluorescence of the fingermarks. However, this correlation is too weak to guide the forensic investigator reliably to the fingermarks with a substantial DNA content.
Parkinson ’ s disease-associated human ATP 13 A 2 ( PARK 9 ) deficiency causes zinc dyshomeostasis and mitochondrial dysfunction

Human ATP13A2 (PARK9), a lysosomal type 5 P-type ATPase, has been associated with autosomal recessive early-onset Parkinson’s disease (PD). ATP13A2 encodes a protein that is highly expressed in neurons and is predicted to function as a cation pump, although the substrate specificity remains unclear. Accumulation of zinc and mitochondrial dysfunction are established aetiological factors that contribute to PD; however, their underlying molecular mechanisms are largely unknown. Using patient-derived human olfactory neurosphere cultures, which harbour loss-of-function mutations in both alleles of ATP13A2, we identified a low intracellular free zinc ion concentration ([Zn]i), altered expression of zinc transporters and impaired sequestration of Zn into autophagy-lysosomal pathway-associated vesicles, indicating that zinc dyshomeostasis occurs in the setting of ATP13A2 deficiency. Pharmacological treatments that increased [Zn]i also induced the production of reactive oxygen species and aggravation of mitochondrial abnormalities that gave rise to mitochondrial depolarization, fragmentation and cell death due to ATP depletion. The toxic effect of Zn was blocked by ATP13A2 overexpression, Zn chelation, antioxidant treatment and promotion of mitochondrial fusion. Taken together, these results indicate that human ATP13A2 deficiency results in zinc dyshomeostasis and mitochondrial dysfunction. Our data provide insights into the molecular mechanisms of zinc dyshomeostasis in PD and its contribution to mitochondrial dysfunction with ATP13A2 as a molecular link between the two distinctive aetiological factors of PD.
The de v il lies in details : reply to Stuart

As pointed out in Stuart Hurlbert’s recent article, ecologists still at times design their experiments sloppily, creating a situation where various forms of ‘non-demonic intrusion’ could account for the documented contrasts between treatments and controls. If such contrasts are nevertheless presented to the reader as if they were statistically demonstrated treatment effects, then pseudoreplication is not a pseudoissue and the use of a stigmatizing label of is entirely warranted, as pointed out by Hurlbert. The problems with Hurlbert’s concepts start in the context of studies, where the scope of the experiment is to provoke a chain of dramatic and a priori extremely unlikely events, which a given conjecture predicts to happen as a consequence of a given manipulation. As the essence of these experiments is to trigger large dynamical responses in a biological system, they often require much space and/or special conditions, allowing for efficient isolation of the experimental system from potential sources of contamination. These constraints can be incompatible with standard designs (randomization, replication and treatmentcontrol interspersion). In the context of experiments, where it has been necessary to sacrifice randomization, replication or treatment-control interspersion, the logic of inferring treatment effects is the same as used when interpreting causes of spontaneous events or events triggered by manipulations with practical purposes. The observed contrasts can be reasonably interpreted as effects of the treatment if and only if their magnitudes and the timing of their emergence makes alternative explanations utterly implausible (which is up to the reader to judge). If the logic of inference is clearly explained and no claim of statistically demonstrated treatment effect is made, the use of stigmatizing labels like ‘pseudoreplication’ is unwarranted. However, it might clarify the literature if such imperfectly designed experiments are referred to as experimental events, to be distinguished from perfectly designed experiments, where mechanical interpretation of contrasts between treatments and controls as treatment effects can be regarded as socially acceptable.
Radiological protection in security screening

The International Commission on Radiological Protection (ICRP) has developed and systematically updated the system of radiological protection, which now recommends optimisation of protection measures within or guided by appropriate restrictions, such as dose constraints or reference levels, in all circumstances. This applies to all exposure situations (planned, emergency and existing) and all categories of exposure (occupational, medical, and public). Optimisation of protection is intended to reduce exposures to levels that are as low as reasonably achievable, economic and societal considerations being taken into account, and to manage medical exposures commensurate with the medical purpose.
Natsume's book of friends

Intrigues abound in the world of professional exorcism, and Natsume wants nothing to do with it. But he has no choice when Matoba, head of a prominent exorcist clan, blackmails him into coming to an exorcist meeting. Is Natsume's fate sealed when one of his special talents is exposed in front of Matoba?
Exploring the compositionand diversityofmicrobial communities atthe JanMayen hydrothermal vent ¢ eld usingRNA andDNA

Exploring the compositionand diversityofmicrobial communities atthe JanMayen hydrothermal vent¢eld usingRNA andDNA Anders Lanzén, Steffen L. Jørgensen, Mia M. Bengtsson, Inge Jonassen, Lise Øvreås & Tim Urich Department of Biology and Centre for Geobiology, University of Bergen, Bergen, Norway; Computational Biology Unit, Uni Computing, Uni Research AS, Bergen, Norway; Department of Informatics, University of Bergen, Bergen, Norway; and Department of Genetics in Ecology, Vienna Ecology Center, University of Vienna, Vienna, Austria
A SYSTEMATIC REVIEW ON THE RELATIONSHIP BETWEEN STOCK MARKET PREDICTION MODEL USING SENTIMENT ANALYSIS ON TWITTER BASED ON MACHINE LEARNING METHOD AND FEATURES SELECTION

This study is mainly a systematic review analysis which discusses studies related to the role of sentiment analysis, Twitter data, and features in predicting stock market returns. Studies show that it is not only the historical financial data of firms or stock markets that can predict the returns of the stock market, but sentiments and emotions of people can also help in predicting stock market returns. One primary source of information that is available now to everyone is Twitter, and tweets made by significant personals affect the emotions of people and which will ultimately affect their investment decisions. If the news is positive, then most probably it will affect people positively, and they will invest more in stocks of that firm. If the news is negative, the reaction of people is expected to be opposite. Besides the sentiments of people, there are features like spatial and temporal that can also affect the stock market returns. The spatial feature is a geographical division, it can either be different emotions of different people from different geographical regions, or they can be other stock markets which can affect the home stock market by any relation. Similarly, temporal effect shows the change in something over a span of time. People might have different opinions at different times, and they can behave differently according to their sentiments at that specific time. Finally, all these factors help us in predicting the future stock market returns.
EVALUATION OF FEATURE SELECTION AND ENCODING METHODS FOR SUPERPIXEL IMAGE PARSING SERCAN SÜNETCİ IŞIK UNIVERSITY 2017 EVALUATION OF FEATURE SELECTION AND ENCODING METHODS FOR SUPERPIXEL IMAGE PARSING

This thesis is about image parsing which is one of the important problems in computer vision. The goal of image parsing is segmentation of object and labeling of each object. Recently, a popular way of image segmentation and classification is superpixels. Image is segmented into visually logical small regions by using superpixel algorithm and then, superpixels are parsed into different classes. Classification performance is significantly affected by the properties of superpixel algorithm and parametric settings. SuperParsing is one of the superpixel-based image parsing algorithm and provides a succesful nonparametric solution for image segmentation and classification problem without any need for classifier training. SuperParsing labels each superpixel based on feature matching between the superpixel and a subset of the training superpixels. The training subset is determined by global matching between the test image and the training set. For superpixel matching the method makes use of a rich set of superpixel features. Class conditional log-likelihood is computed based on these matched features. The main objective of this thesis is to show improvements in labeling accuracy percentage by using feature encoding and selection methods, including learned features from Convolutional Neural Network (CNN) models. We perform two different encoding methods to selected features of superpixels and show that feature encoding improves parsing accuracy. The applied feature encoding methods are locality-constrained linear encoding (LLC) and kernel codebook encoding (KCB). LLC encoding method gives us 2.6% improvement on per-pixel accuracy for SIFT Flow dataset and 6.8% improvement on per-pixel accuracy for 19-class LabelMe dataset. KCB encoding method gives us 3.6% improvement on per-pixel accuracy for SIFT Flow dataset and 6.2% improvement on per-pixel accuracy for 19-class LabelMe dataset. All these results are overall improvement which are computed over original SuperParsing.
1915 EXCHANGE RATE SHOCKS AND QUALITY ADJUSTMENTS

Do rms respond to cost shocks by reducing the quality of their products? Using microdata from a large Russian retailer that varies its o erings twice-yearly, we document that ruble devaluations are associated with a reduction in the observed material quality of products imported for resale, but that higher quality goods are also more pro table. We reconcile these facts using a simple multi-product sourcing model that features a demand system with expenditure switching, where more pro table products can be dropped more quickly after a cost shock. The estimated model shows that quality downgrading reduces average passthrough by 6% and has meaningful consequences for welfare. JEL Codes: E30, F14, F31, L11, L15, L16, L81, M11. ∗We are grateful to Mark Aguiar, Markus Brunnermeier, Vasco Carvalho, Giancarlo Corsetti, Jan de Loecker, Mikhail Golosov, Bo Honoré, Oleg Itskhoki, Myrto Kalouptsidi, Jakub Kastl, Atif Mian, Virgiliu Midrigan, David Sraer, Claudia Steinwender, Motohiro Yogo, as well as multiple seminar participants at the Barcelona GSE Summer Forum, University of Cambridge, the annual conference of the CEA, Princeton University, Stockholm School of Economics, and University of Toronto for valuable advice. Rodnyansky gratefully acknowledges nancial support from the Alfred P. Sloan Foundation, the CME Group Foundation, Fidelity Management & Research, and the MFM initiative. Goetz: Department of Management, Kane Centre, Rm 233, 1833 Inner Circle Rd., UTM, Mississauga, ON L5L 1C6, Canada. Email: daniel.goetz@rotman.utoronto. ca. Rodnyansky: Faculty of Economics, Austin Robinson Building, Sidgwick Avenue, Cambridge, CB3 9DD, UK. Email: a.rodnyansky@gmail.com.
Modular Verification in the Presence of Shared Objects and Concurrency

Aliasing presents a challenge because it complicates automated, modular verification. This paper presents a threepronged approach to addressing this challenge: (i) automated verification that leverages a promising notion of clean semantics in which objects in client code are decoupled by language and software design; (ii) verification for data abstraction implementations involving explicit (and unavoidable) aliasing using a concept that captures acyclic reference behavior; and (iii) specification of conditional effects clauses for verifying parallel execution of operations on a shared object without violating abstraction. This approach is presented in the context of the RESOLVE project, which aims to enable automated verification of sequential and parallel object-based programs.
Evaluating the experience of daylight through a virtual skylight

Citation for published version (APA): Meerbeek, B. W. , & Seuntiens, P. J. H. (2014). Evaluating the experience of daylight through a virtual skylight. In Y. A. W. Kort, de, M. P. J. Aarts, F. Beute, A. Haans, I. E. J. Heynderickx, L. M. Huiberts, I. Kalinauskaite, P. Khademagha, A. Kuijsters, D. Lakens, L. van Rijswijk, A. C. Schietecat, K. C. H. J. Smolders, M. G. M. Stokkermans, . W. A. Ijsselsteijn (Eds.), Proceedings of Experiencing Light 2014 : International Conference on the Effects of Light on Wellbeing, 10-11 November 2014, Eindhoven, The Netherlands (pp. 58-61). Eindhoven: Technische Universiteit Eindhoven.
Modified Filtering Scheme for Medical Image

Filtering and feature selection methods for characterization and enhancement of liver and chest images are presented in this paper . Our problem focuses on improvement of performance of classification of feature set by various selection algorithms like sequential forward search (SFS), sequential backward search algorithm (SBS) and sequential forward floating search algorithm (SFFS). Here the focus is on statistical texture features obtained from the computed tomography abdominal images taken by the radiologist. Symlet Wavelet is used for filtering and feature extraction. Wavelet transform decomposes the data in such a way that any hidden information in image can be retrieved. We have tried our best to reduce the feature set size as it is very necessary to limit the number of features or to have optimization of feature set, a design of compact classifier is required for improved classification of the selected problem(Liver Tumor, Chest abnormalities), based on the classification. Most and least significant features are identified on the basis of classification performance of the classifier and then unwanted features may be removed from the set of feature to get a feature subset, which is small in size. In this paper we have tried to characterize the hepatic, hepatoma, hemangeoma, hepatic masses using Symlet Wavelet. After comparing the performance of this technique to that of other approaches it is found to be superior and convenient for medical diagnosis.