nils-herrmann/clean_scirepeval huggingface dataset:
A case of acquired renal cystic disease (ACDK) with oncocytosis, a dominant nodule (oncocytoma) multiple adenomas and a microscopic papillary renal cell carcinoma associated with crescentic glomerulonephritis
Venue: Virchows Archiv
Year: 2006

Sir, A 76 year old female patient suffering from long term arterial hypertension had a nephrotic syndrome in 1997, being diagnosed of membranous glomerulonephritis clinically and with biopsy. She was resistant to steroids and azathioprine. Then, her treatment was changed to Mycophenolate Mofetil. In 2005, she had anuria, abdominal discomfort and acral edema. Serologic studies were negative. Hemodyalisis, besides steroids and cyclofosphamide treatment were started. Her renal function was worsening and a new biopsy showed a crescentic glomerulonephritis with epithelial crescents, severe tubulointerstitial changes and focal tubular hyperplasia. IF studies were identical to the previous biopsy and consistent with membranous glomerulonephritis (granular peripheral glomerular deposits of Ig G, C3 and C1q) EM is not available. CT scan and MRI displayed multiple renal cysts suggesting ACDK with a 2.5 cm solid nodule and a total right nephrectomy was performed. The removed kidney  had multiple cysts, numerous minute nodules and a tangreen 2.5 cm mass. Studied by routine methods and immunohistochemistry (cytogenetics and EM are not available) a crescentic GN with many obsolescent glomeruli was found  There were prominent tubulointerstitial changes: severe tubular atrophy, frequent tubular hyperplasia and oncocytic changes, sometimes papillary; Virchows Arch (2007) 450:365 367 DOI 10.1007/s00428 006 0324 0
Postmodern Cinema of Seduction: Subaltern/Folk Inspired Hindi Film Song and Dance, and the Art of Deferral and Play
Year: 2017

If there is one phrase that has been used most often by Western audiences for popular Indian cinema, it is the phrase "musicals." The description gestures both at the fixation of Indian cinema on an earlier stage of cinematic evolution and the simple and uncomplicated pleasure derived by the audience from popular Hindi films that have an audience all over the world. This essay examines Hindi film "song and dance" spectacles as the art of deferment in the postmodern cinema of seduction, a notion derived from the work of Jean Baudrillard and the insights of Freud Lacan Zizek and Baudrillard himself on deferral and seduction. This chapter makes this claim not as an overarching theoretical nomenclature for all song and dance sequences in Hindi films. Instead the author argues for the primacy of the art of deferment and play in a postmodern cinema of seduction within the limited scope of her reading of a North Indian subaltern/folk inspired song and dance Hindi film, Amol Palekar and Sandhya Gokhale directed Paheli (Riddle, 2005) Reena Dube Indiana University of Pennsylvania, USA Postmodern Cinema of Seduction
Determinants of specific trade concerns raised on technical barriers to trade EU versus non EU
Year: 2018

This contribution evaluates determining factors of Specific Trade Concerns (STCs) raised on Technical Barriers to Trade (TBT) notifications over the period 1995 2011. While multilateral and international agreements bind countries concerning the imposition of tariffs on imports, TBTs have been used as trade policy instruments, which conceal the true motivations of governments. The main legitimate reasons behind the imposition of TBTs are to increase environmental qualities and human health, or to improve market efficiencies. However, in addition to these reasons, governments are also in pursuit of protecting their domestic industries. In fact, this contribution analyses how trade protectionist motives and legitimate public policy objectives induce these specific trade measures. Various effective factors of TBT STC notifications are considered in the econometric analysis using fixed effect Poisson estimation as the main technique, and Poisson GMM as robustness specification. Separate estimations on the European Union block in this study points at the determining factors of TBTs harmonized by heterogeneous member states. Results suggest that bilateral trade and tariffs are one of the forces of TBT STC notifications, acknowledging the protectionist behaviour of authorities. Moreover, countries with high quality of humans' health related environmental issues, and low environmental vitalities, are more likely to impose new TBTs. Overall, this study confirms the complex nature of TBT STCs affected by economic, technological, institutional, and health and environmental issues.
Analisis Regresi Logistik terhadap Keputusan Penerimaan Beasiswa PPA di FMIPA Unnes Menggunakan Software Minitab
Year: 2018

Abstrak Penelitian ini dilatarbelakangi oleh masalah biaya yang dialami masyarakat menengah ke bawah dalam melanjutkan ke pendidikan tinggi. Namun, saat ini di setiap perguruan tinggi telah tersedia beasiswa khususnya di FMIPA Unnes seperti beasiswa PPA. Penentuan menjadi penerima beasiswa PPA dapat ditentukan oleh IPK tertinggi, SKS terbanyak, memiliki prestasi, dan memiliki keterbatasan kemampuan ekonomi. Tujuan dari penelitian ini untuk mengetahui pengaruh faktor IPK, SKS rata rata, kemahasiswaan (keikutsertaan/prestasi mahasiswa dalam organisasi maupun lomba lomba) dan tingkat penghasilan orang tua terhadap keputusan penerimaan beasiswa PPA tahun 2016, dan mengetahui seberapa besar faktor faktor tersebut mempengaruhi keputusan penerimaan beasiswa PPA tahun 2016. Analisis data yang digunakan adalah analisis regresi logistik, karena analisis regresi logistik merupakan analisis yang digunakan untuk mencari pengaruh antara variabel bebas yang bersifat kategori maupun kontinu terhadap variabel terikat yang bersifat kategori, yang dalam penelitian ini adalah kategori diterima dan tidak dterima. Penelitian ini menggunakan data sekunder dengan jumlah populasi sebanyak 538 mahasiswa yang kemudian dilakukan pengambilan sampel dengan menggunakan metode proportional random sampling, sehingga didapatkan jumlah sampel sebanyak 237 mahasiswa. Data sampel tersebut dilakukan pengolahan data menggunakan software Minitab 17. Hasil pengolahan data menunjukkan bahwa dari keempat variabel yaitu IPK, SKS rata rata, kemahasiswaan, dan tingkat penghasilan orang tua hanya variabel IPK yang berpengaruh secara signifikan terhadap keputusan penerimaan beasiswa PPA tahun 2016, dan variabel IPK mempengaruhi keputusan penerimaan beasiswa PPA sebesar 19,11 persen, sedangkan sisanya 80,89 persen dipengaruhi oleh faktor lain.
PREVALENCE AND DETERMINANTS OF ANAEMIA IN THIRD TRIMESTER PREGNANCY IN FAYOUM GOVERNORATE EGYPT
Year: 2014

It is estimated that prevalence of anaemia by the third trimester of pregnancy is higher than that in early pregnancy despite routine intake of iron supplementation with higher incidence of low birth weight and preterm delivery. The aim of the current study is to measure the prevalence of anaemia in third trimester of pregnancy and identify its risk factors.  This study is a cross sectional design carried out in antenatal clinic at Fayoum teaching Hospital. A total of 381 pregnant women in third trimester pregnancy were enrolled in the study. All enrolled subjects were interviewed using a structured questionnaire inquiring about age, education level, occupation, family income, pregnancy history, medical history, vitamin intake and nutritional history. A blood sample was examined for haemoglobin concentration from each enrolled woman and anaemia was diagnosed with haemoglobin level below 11g/dl.  Prevalence of anaemia in third trimester was 67% in the current study. Among many risk factors identified, yet the main independent predictors of anaemia in third trimester of pregnancy were multiparity, infrequent antenatal visits, irregular intake of iron supplement, low weekly intake of meat and fruits and frequent daily tea consumption.  Anaemia by third trimester of pregnancy represents major health problem in this geographical area of Egypt. Its risk factors include personal, dietary and some aspects related to outcome healthcare delivered at this stage. Further researches are recommended to be carried out to study quality and compliance of antenatal services as well innovative approaches for iron supplementation.
The Effect of Knowledge Management Integration on E Learning System toward Lecturers Performance at University Institutions
Year: 2020

This study was designed to 1) measure the effect of knowledge integration and e learning on lecturers' performance and 2) examine the effect of work procedures and information technology on the performance of lecturers at State University of Malang, Indonesia. Anchored by a survey study and document analysis, the present study revealed that knowledge management indirectly affects lecturers' performance. Our findings also uncovered that there is a significant influence between personal knowledge on work procedures, and the most dominant factor affecting their performance is information technology. Based on the findings, this study can be a catalyst for improving the quality of higher education through the application of knowledge management on e learning. Furthermore, the results are worthwhile to be used as lecturers' performance enhancement in university levels.
A Co Culture System with an Organotypic Lung Slice and an Immortal Alveolar Macrophage Cell Line to Quantify Silica Induced Inflammation
Venue: PloS one
Year: 2015

There is growing evidence that amorphous silica nanoparticles cause toxic effects on lung cells in vivo as well as in vitro and induce inflammatory processes. The phagocytosis of silica by alveolar macrophages potentiates these effects. To understand the underlying molecular mechanisms of silica toxicity, we applied a co culture system including the immortal alveolar epithelial mouse cell line E10 and the macrophage cell line AMJ2 C11. In parallel we exposed precision cut lung slices (lacking any blood cells as well as residual alveolar macrophages) of wild type and P2rx7 mice with or without AMJ2 C11 cells to silica nanoparticles. Exposure of E10 cells as well as slices of wild type mice resulted in an increase of typical alveolar epithelial type 1 cell proteins like T1a, caveolin 1 and 2 and PKC b1, whereas the co culture with AMJ2 C11 showed mostly a slightly lesser increase of these proteins. In P2rx7 mice most of these proteins were slightly decreased. ELISA analysis of the supernatant of wild type and P2rx7 mice precision cut lung slices showed decreased amounts of IL 6 and TNF a when incubated with nano silica. Our findings indicate that alveolar macrophages influence the early inflammation of the lung and also that cell damaging reagents e.g. silica have a smaller impact on P2rx7 mice than on wild type mice. The co culture system with an organotypic lung slice is a useful tool to study the role of alveolar macrophages during lung injury at the organoid level.
GCNNMatch: Graph Convolutional Neural Networks for Multi Object Tracking via Sinkhorn Normalization
Venue: ArXiv
Year: 2020

This paper proposes a novel method for online Multi Object Tracking (MOT) using Graph Convolutional Neural Network (GCNN) based feature extraction and end to end feature matching for object association. The Graph based approach incorporates both appearance and geometry of objects at past frames as well as the current frame into the task of feature learning. This new paradigm enables the network to leverage the "context" information of the geometry of objects and allows us to model the interactions among the features of multiple objects. Another central innovation of our proposed framework is the use of the Sinkhorn algorithm for end to end learning of the associations among objects during model training. The network is trained to predict object associations by taking into account constraints specific to the MOT task. Experimental results demonstrate the efficacy of the proposed approach in achieving top performance on the MOT16 17 Challenge problems among state of the art online and supervised approaches. The code is available at this https URL.
The Glasgow School of Art fashion show, 1947 2017
Venue: Art Libraries Journal
Year: 2017

Introduced in 1947 as an event during Charities Week, the Glasgow School of Art (GSA) Fashion Show provided an opportunity to present student designs and fundraise around the City of Glasgow. Over the years, the format, location and emphasis of the event have changed, although creativity, collaboration, team working and the Students Union remain central to organization. To commemorate the 70th anniversary of the fashion show, the development of this event has recently been re visited and an exhibition developed. This project posed the questions: What GSA Archives and Collections' holdings relate to the event? Are there gaps within the collection and if so can items be accessioned? What can be understood about the evolution of the GSA fashion show from this material? Is there potential for further research from this local event? These questions form the basis of this article.
Latent3DU net: Multi level Latent Shape Space Constrained 3D U net for Automatic Segmentation of the Proximal Femur from Radial MRI of the Hip
Venue: MLMI@MICCAI
Year: 2018

Radial 2D MRI scans of the hip are routinely used for the diagnosis of the cam type of femoroacetabular impingement (FAI) and of avascular necrosis (AVN) of the femoral head, which are considered causes of hip joint osteoarthritis in young and active patients. However, for computer assisted planning of surgical treatment, it is highly desired to have 3D models of the proximal femur. In this paper, we propose a novel volumetric convolutional neural network (CNN) based framework to fully automatically extract 3D models of the proximal femur from sparsely hip radial slices. Our framework starts with a spatial transform to interpolate sparse 2D radial MR images to a densely sampled 3D volume data. Automated segmentation of the interpolated 3D volume data is very challenging due to the poor image quality and the interpolation artifact. To tackle these challenges, we introduce a multi level latent shape space constrained 3D U net, referred as Latent3DU net, to incorporate prior shape knowledge into voxelwise semantic segmentation of the interpolated 3D volume. Comprehensive results obtained from 25 patient data demonstrated the effectiveness of the proposed framework.
Sparsity based GPR blind deconvolution and wavelet estimation 7 Sparsity based GPR blind deconvolution and wavelet estimation
Year: 2016

Improving the vertical resolution of Ground Penetrating Radar (GPR) data by blind deconvolution technique is an approach we target here. Sometimes geologic situations such as presence of clay or humidity lead to blurred sections. Advanced processing steps, that are so common in seismic reflection, such as deconvolution are needed. In this approach the sparse deconvolution algorithm on GPR data has been used in a novel way. It is often assumed that reflectivity series are sparse and noise is random. Generalized Cross Validation (GCV) method has been used to estimate the desired wavelet and to find the optimum iteration in the deconvolution algorithm. To examine the efficacy of the method, it is applied to synthetic data. The GCV and MSE curves versus iteration are then plotted in order to determine the optimal point. The final deconvolved section shows a satisfying result for GPR field data and the speed and accuracy of this robust algorithm to reconstruct reflectivity series is considerable.
Optically pumped rare gas lasers
Venue: Advanced High Power Lasers and Applications
Year: 2019

There have been concerted efforts to develop high energy diode pumped alkali vapor lasers (DPAL) These hybrid gas phase solid state laser systems offer possibilities for constructing high powered lasers that have high beam quality. Considerable progress has been made, but there are technical challenges associated with the reactivity of the metal atoms. Rare gas atoms (Rg) excited to the np5 (n+1)s 3P2 configuration are metastable and have spectral properties that are closely similar to those of the alkali metals. Optically pumped lasers have been constructed using excitation of the np5 (n+1)p np5 (n+1)s transitions. Pulsed lasing has been observed for Ne* Ar* Kr* and Xe* Helium was used as the collisional energy transfer agent that established population inversions. These systems have the advantage using inert reagents that are gases at room temperature, with excellent potential for closed cycle, multi wavelength operation. The primary technical difficulty for the rare gas laser is the discharge production of sufficient Rg* metastables in the presence of >200 Torr of He. We have developed a high frequency pulsed discharge that yields >1013 cm 3 Ar* in the presence of He at pressures up to 730 Torr. Using this discharge, a diode pumped Ar* laser providing 4.1 W of continuous wave output has been demonstrated, with an optical conversion efficiency of 31% Development of the pulsed discharge system and CW lasing demonstrations with Xe* are reported.
Collaborative Sensor Network Localization: Algorithms and Practical Issues
Venue: Proceedings of the IEEE
Year: 2018

Emerging communication network applications including fifth generation (5G) cellular and the Internet of Things (IoT) will almost certainly require location information at as many network nodes as possible. Given the energy requirements and lack of indoor coverage of Global Positioning System (GPS) collaborative localization appears to be a powerful tool for such networks. In this paper, we survey the state of the art in collaborative localization with an eye toward 5G cellular and IoT applications. In particular, we discuss theoretical limits, algorithms, and practical challenges associated with collaborative localization based on range based as well as range angle based techniques.
A Complex Network Based Broad Learning System for Detecting Driver Fatigue From EEG Signals
Venue: IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year: 2021

Driver fatigue detection is of great significance for guaranteeing traffic safety and further reducing economic as well as societal loss. In this article, a novel complex network (CN) based broad learning system (CNBLS) is proposed to realize an electroencephalogram (EEG) based fatigue detection. First, a simulated driving experiment was conducted to obtain EEG recordings in alert and fatigue state. Then, the CN theory is applied to facilitate the broad learning system (BLS) for realizing an EEG based fatigue detection. The results demonstrate that the proposed CNBLS can accurately differentiate the fatigue state from an alert state with high stability. In addition, the performances of the four existing methods are compared with the results of the proposed method. The results indicate that the proposed method outperforms these existing methods. In comparison to directly using EEG signals as the input of BLS, CNBLS can sharply improve the detection results. These results demonstrate that it is feasible to apply BLS in classifying EEG signals by means of CN theory. Also, the proposed method enriches the EEG analysis methods.
The function of dart shooting in helicid snails*
Year: 2007

Some stylommatophoran species, including several helicid snails common to Europe and North America, drive sharp, calcareous darts into their sexual partners prior to copulation. Why any animal would treat a prospective mate in this manner has been the subject of considerable speculation. One widely held belief is that the dart stimulates the partner. Here, I review evidence showing that this hypothesis, along with several others, is almost certainly incorrect. On the other hand, there is strong empirical support for the idea that the dart increases the reproductive fitness of the successful shooter by promoting the survival and utilization of its sperm. How the dart works to produce this effect is an open question; current evidence indicates that it injects a chemical agent into the recipient and that this substance contracts the female tract in such a manner as to facilitate the passage of allosperm to the spermatheca. Although successful dart shooting clearly benefits the shooter, there is little evidence to suggest either a cost or a benefit to the recipient.
AVADHAN: System for Open Domain Telugu Question Answering
Venue: COMAD/CODS
Year: 2020

This paper presents the Question Answering (QA) system for a low resource language like 'Telugu' named 'AVADHAN' This work started with preparing a pre tagged data set for Telugu Question Classification (QC) We also explained the ambiguities and complexities involved in the data set. AVADHAN exhibits the comparisons between Support Vector Machine (SVM) Logistic Regression (LR) and Multi Layer Perceptron (MLP) classifiers for achieving the plausible answers. After performing various experiments the overall accuracies obtained, for both 'exact match' and 'partial match' based approaches, were for SVM (31.6% 68.5% LR (31% 66.6% and for MLP (30% 67% respectively.
Factores predictores de la violencia filio parental
Year: 2019

En los ultimos anos se han venido incrementando la frecuencia y gravedad de la violencia filio parental (VFP) (Nowakowski Sims y Rowe, 2015).El objetivo de esta investigacion fue analizar, en una muestra de estudiantes de educacion secundaria, las relaciones del estilo educativo empleado por los padres, el estres y el consumo de alcohol y drogas por parte de los participantes con la comision de VFP.
Deep Spectral Clustering Using Dual Autoencoder Network
Venue: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2019

The clustering methods have recently absorbed even increasing attention in learning and vision. Deep clustering combines embedding and clustering together to obtain optimal embedding subspace for clustering, which can be more effective compared with conventional clustering methods. In this paper, we propose a joint learning framework for discriminative embedding and spectral clustering. We first devise a dual autoencoder network, which enforces the reconstruction constraint for the latent representations and their noisy versions, to embed the inputs into a latent space for clustering. As such the learned latent representations can be more robust to noise. Then the mutual information estimation is utilized to provide more discriminative information from the inputs. Furthermore, a deep spectral clustering method is applied to embed the latent representations into the eigenspace and subsequently clusters them, which can fully exploit the relationship between inputs to achieve optimal clustering results. Experimental results on benchmark datasets show that our method can significantly outperform state of the art clustering approaches.