nils-herrmann/clean_scirepeval huggingface dataset:
Social TV: Linking TV Content to Buzz and Sales

“Social TV” is a term that broadly describes the online social interactions occurring between viewers while watching television. In this paper, we show that TV networks can derive value from social media content placed in shows because it leads to increased word of mouth via online posts, and it highly correlates with TV show related sales. In short, we show that TV event triggers change the online behavior of viewers. In this paper, we first show that using social media content on the televised American reality singing competition, The Voice, led to increased social media engagement during the TV broadcast. We then illustrate that social media buzz about a contestant after a performance is highly correlated with song sales from that contestant’s performance. We believe this to be the first study linking TV content to buzz and sales in real time.
Unusual association between cheilitis glandularis and actinic cheilitis

our aim is to report the simultaneous occurence of cheilitis glandularis and actinic cheilitis on the lower lip of a middle-aged female patient.  the patient presented clinical features compatible with these two lesions, confirmed by histopathological exam.  the importance of the present case is the rare concomitant occurrence of both conditions, with special concern towards the malignancy potential related to both diseases.
Sizing Equations for Electrical Machinery

Sizing equations for electrical machinery are developed from basic principles. The technique provides new insights into: 1. The effect of stator inner and outer diameters. 2. The amount of copper and steel used. 3. A maximizing function. 4. Equivalent slot dimensions in terms of diameters and flux density distribution. 5. Pole number effects. While the treatment is analytical, the scope is broad and intended to assist in the design of electrical machinery. Examples are given showing how the machine's internal geometry can assume extreme proportions through changes in basic variables.
New diagnostic criteria and severity assessment of acute cholangitis in revised Tokyo guidelines

The Tokyo Guidelines for the management of acute cholangitis and cholecystitis were published in 2007 (TG07) and have been widely cited in the world literature. Because of new information that has been published since 2007, we organized the Tokyo Guidelines Revision Committee to conduct a multicenter analysis to develop the updated Tokyo Guidelines (TG13).



We retrospectively analyzed 1,432 biliary disease cases where acute cholangitis was suspected. The cases were collected from multiple tertiary care centers in Japan. The 'gold standard' for acute cholangitis in this study was that one of the three following conditions was present: (1) purulent bile was observed; (2) clinical remission following bile duct drainage; or (3) remission was achieved by antibacterial therapy alone, in patients in whom the only site of infection was the biliary tree. Comparisons were made for the validity of each diagnostic criterion among TG13, TG07 and Charcot's triad.



The major changes in diagnostic criteria of TG07 were re-arrangement of the diagnostic items and exclusion of abdominal pain from the diagnostic list. The sensitivity improved from 82.8 % (TG07) to 91.8 % (TG13). While the specificity was similar to TG07, the false positive rate in cases of acute cholecystitis was reduced from 15.5 to 5.9 %. The sensitivity of Charcot's triad was only 26.4 % but the specificity was 95.6 %. However, the false positive rate in cases of acute cholecystitis was 11.9 % and not negligible. As for severity grading, Grade II (moderate) acute cholangitis is defined as being associated with any two of the significant prognostic factors which were derived from evidence presented recently in the literature. The factors chosen allow severity assessment to be performed soon after diagnosis of acute cholangitis.



TG13 present a new standard for the diagnosis, severity grading, and management of acute cholangitis.
NON-rigid structure from motion via sparse self-expressive representation

To simultaneously recover 3D shapes of non-rigid object and camera motions from 2D corresponding points is a difficult task in computer vision. This task is called Non-rigid Structure from motion(NRSfM). To solve this ill-posed problem, many existing methods rely on low rank assumption. However, the value of rank has to be accurately predefined because incorrect value can largely degrade the reconstruction performance. Unfortunately, these is no automatic solution to determine this value. In this paper, we present a self-expressive method that models 3D shapes with a sparse combination of other 3D shapes from the same structure. One of the biggest advantages is that it doesn't need the rank to be predefined. Also, unlike other learning-based methods, our method doesn't need learning step. Experimental results validate the efficiency of our method.
Multi-line acquisition with minimum variance beamforming in medical ultrasound imaging

In recent years, multiple-line acquisition (MLA) has been introduced to increase frame rate in cardiac ultrasound medical imaging. However, this method induces blocklike artifacts in the image. One approach suggested, synthetic transmit beamforming (STB), involves overlapping transmit beams which are then interpolated to remove the MLA blocking artifacts. Independently, the application of minimum variance (MV) beamforming has been suggested in the context of MLA. We demonstrate here that each approach is only a partial solution and that combining them provides a better result than applying either approach separately. This is demonstrated by using both simulated and real phantom data, as well as cardiac data. We also show that the STB-compensated MV beamfomer outperforms single-line acquisition (SLA) delay- and-sum in terms of lateral resolution.
A proof of image Euler Number formula

Euler Number is one of the most important characteristics in topology. In two-dimension digital images, the Euler characteristic is locally computable. The form of Euler Number formula is different under 4-connected and 8-connected conditions. Based on the definition of the Foreground Segment and Neighbor Number, a formula of the Euler Number computing is proposed and is proved in this paper. It is a new idea to locally compute Euler Number of 2D image.
Data lifetime is a systems problem

As sensitive data lifetime (i.e. propagation and duration in memory) increases, so does the risk of exposure. Unfortunately, this issue has been largely overlooked in the design of most of today's operating systems, libraries, languages, etc. As a result, applications are likely to leave the sensitive data they handle (passwords, financial and military information, etc.) scattered widely over memory, leaked to disk, etc. and left there for an indeterminate period of time. This greatly increases the impact of a system compromise.Dealing with data lifetime issues is currently left to application developers, who largely overlook them. Security-aware developers who attempt to address them (e.g. cryptographic library writers) are stymied by the limitations of the operating systems, languages, etc. they rely on. We argue that data lifetime is a systems issue which must be recognized and addressed at all layers of the software stack.
Glanuloplasty with urethral flap after partial penectomy.

We describe a surgical technique to reconstruct the glans secondary to partial penectomy or traumatic partial amputation as well as its complications. We assessed urethral flap vitality and the tumor recurrence rate using this technique.



Glanuloplasty with a urethral flap was done in 10 patients who underwent partial penectomy for penile squamous cell carcinoma. We reconstructed the neoglans with a urethral flap at the same surgical resection. Mean patient age was 61 years (range 18 to 71). Mean followup was 11 months (range 5 to 17).



We noted no neomeatal stenosis or flap necrosis secondary to the technique. The early tumor recurrence rate was 10% and the penile curvature rate was 10%. Penile curvature was ventral with no associated penetration difficulty.



This simple, reproducible technique has satisfactory functional and cosmetic results, and an acceptable complication rate for this type of pathological condition.
The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching

We consider a basic cache network, in which a single server is connected to multiple users via a shared bottleneck link. The server has a database of files (content). Each user has an isolated memory that can be used to cache content in a prefetching phase. In a following delivery phase, each user requests a file from the database, and the server needs to deliver users’ demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of the rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the bottleneck link for a given cache size available at each user. In particular, we propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without any coordination.
A Deep Learning Model for Epigenomic Studies

Epigenetics is the study of heritable changesin gene expression that does not involve changes to theunderlying DNA sequence, i.e. a change in phenotype notinvolved by a change in genotype. At least three mainfactor seems responsible for epigenetic change including DNAmethylation, histone modification and non-coding RNA, eachone sharing having the same property to affect the dynamicof the chromatin structure by acting on Nucleosomes position. A nucleosome is a DNA-histone complex, where around150 base pairs of double-stranded DNA is wrapped. Therole of nucleosomes is to pack the DNA into the nucleusof the Eukaryote cells, to form the Chromatin. Nucleosomepositioning plays an important role in gene regulation andseveral studies shows that distinct DNA sequence featureshave been identified to be associated with nucleosomepresence. Starting from this suggestion, the identificationof nucleosomes on a genomic scale has been successfullyperformed by DNA sequence features representation andclassical supervised classification methods such as SupportVector Machines, Logistic regression and so on. Taking inconsideration the successful application of the deep neuralnetworks on several challenging classification problems, inthis paper we want to study how deep learning network canhelp in the identification of nucleosomes.
Structural evolution during the reduction of chemically derived graphene oxide.

The excellent electrical, optical and mechanical properties of graphene have driven the search to find methods for its large-scale production, but established procedures (such as mechanical exfoliation or chemical vapour deposition) are not ideal for the manufacture of processable graphene sheets. An alternative method is the reduction of graphene oxide, a material that shares the same atomically thin structural framework as graphene, but bears oxygen-containing functional groups. Here we use molecular dynamics simulations to study the atomistic structure of progressively reduced graphene oxide. The chemical changes of oxygen-containing functional groups on the annealing of graphene oxide are elucidated and the simulations reveal the formation of highly stable carbonyl and ether groups that hinder its complete reduction to graphene. The calculations are supported by infrared and X-ray photoelectron spectroscopy measurements. Finally, more effective reduction treatments to improve the reduction of graphene oxide are proposed.
The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo - A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data

Drone-borne hyperspectral imaging is a new and promising technique for fast and precise acquisition, as well as delivery of high-resolution hyperspectral data to a large variety of end-users. Drones can overcome the scale gap between field and air-borne remote sensing, thus providing high-resolution and multi-temporal data. They are easy to use, flexible and deliver data within cm-scale resolution. So far, however, drone-borne imagery has prominently and successfully been almost solely used in precision agriculture and photogrammetry. Drone technology currently mainly relies on structure-from-motion photogrammetry, aerial photography and agricultural monitoring. Recently, a few hyperspectral sensors became available for drones, but complex geometric and radiometric effects complicate their use for geology-related studies. Using two examples, we first show that precise corrections are required for any geological mapping. We then present a processing toolbox for frame-based hyperspectral imaging systems adapted for the complex correction of drone-borne hyperspectral imagery. The toolbox performs sensorand platform-specific geometric distortion corrections. Furthermore, a topographic correction step is implemented to correct for rough terrain surfaces. We recommend the c-factor-algorithm for geological applications. To our knowledge, we demonstrate for the first time the applicability of the corrected dataset for lithological mapping and mineral exploration.
Connoisseur : Can GANs Learn Simple 1 D Parametric Distributions ?

Generative Adversarial Network (GAN) has been shown to possess the capability to learn distributions of data, given infinite capacity of models [1, 2]. Empirically, approximations with deep neural networks seem to have “sufficiently large” capacity and lead to several success in many applications, such as image generation. However, most of the results are difficult to evaluate because of the curse of dimensionality and the unknown distribution of the data. To evaluate GANs, in this paper, we consider simple one-dimensional data coming from parametric distributions circumventing the aforementioned problems. We formulate rigorous techniques for evaluation under this setting. Based on this evaluation, we find that many state-ofthe-art GANs are very difficult to train to learn the true distribution and can usually only find some of the modes. If the GAN has learned, such as MMD GAN, we observe it has some generalization capabilities.
Characteristics of online and offline health information seekers and factors that discriminate between them.

Increasing number of individuals are using the internet to meet their health information needs; however, little is known about the characteristics of online health information seekers and whether they differ from individuals who search for health information from offline sources. Researchers must examine the primary characteristics of online and offline health information seekers in order to better recognize their needs, highlight improvements that may be made in the arena of internet health information quality and availability, and understand factors that discriminate between those who seek online vs. offline health information. This study examines factors that differentiate between online and offline health information seekers in the United States. Data for this study are from a subsample (n = 385) of individuals from the 2000 General Social Survey. The subsample includes those respondents who were asked Internet and health seeking module questions. Similar to prior research, results of this study show that the majority of both online and offline health information seekers report reliance upon health care professionals as a source of health information. This study is unique in that the results illustrate that there are several key factors (age, income, and education) that discriminate between US online and offline health information seekers; this suggests that general "digital divide" characteristics influence where health information is sought. In addition to traditional digital divide factors, those who are healthier and happier are less likely to look exclusively offline for health information. Implications of these findings are discussed in terms of the digital divide and the patient-provider relationship.
Placental Drug Transport-on-a-Chip: A Microengineered In Vitro Model of Transporter-Mediated Drug Efflux in the Human Placental Barrier.

The current lack of knowledge about the effect of maternally administered drugs on the developing fetus is a major public health concern worldwide. The first critical step toward predicting the safety of medications in pregnancy is to screen drug compounds for their ability to cross the placenta. However, this type of preclinical study has been hampered by the limited capacity of existing in vitro and ex vivo models to mimic physiological drug transport across the maternal-fetal interface in the human placenta. Here the proof-of-principle for utilizing a microengineered model of the human placental barrier to simulate and investigate drug transfer from the maternal to the fetal circulation is demonstrated. Using the gestational diabetes drug glyburide as a model compound, it is shown that the microphysiological system is capable of reconstituting efflux transporter-mediated active transport function of the human placental barrier to limit fetal exposure to maternally administered drugs. The data provide evidence that the placenta-on-a-chip may serve as a new screening platform to enable more accurate prediction of drug transport in the human placenta.
Smart, Sparse Contours to Represent and Edit Images

We study the problem of reconstructing an image from information stored at contour locations. We show that highquality reconstructions with high fidelity to the source image can be obtained from sparse input, e.g., comprising less than 6% of image pixels. This is a significant improvement over existing contour-based reconstruction methods that require much denser input to capture subtle texture information and to ensure image quality. Our model, based on generative adversarial networks, synthesizes texture and details in regions where no input information is provided. The semantic knowledge encoded into our model and the sparsity of the input allows to use contours as an intuitive interface for semantically-aware image manipulation: local edits in contour domain translate to long-range and coherent changes in pixel space. We can perform complex structural changes such as changing facial expression by simple edits of contours. Our experiments demonstrate that humans as well as a face recognition system mostly cannot distinguish between our reconstructions and the source images.
Genetic diversity in cowpea [Vigna unguiculata (L.) Walp.] as revealed by RAPD markers

The present study, using RAPD analysis, was undertaken to characterize genetic variation in domesticated cowpea and its wild progenitor, as well as their relationships. The materials used consisted of 26 domesticated accessions, including accessions from each of the five cultivar-group, and 30 wild/weedy accessions, including accessions from West, East and southern Africa. A total of 28 primers generated 202 RAPD bands. One hundred and eight bands were polymorphic among the domesticated compared to 181 among wild/weedy cowpea accessions. Wild accessions were more diverse in East Africa, which is the likely area of origin of V. unguiculata var. spontanea. Var. spontanea is supposed to have spread westward and southward, with a loss of variability, loss counterbalanceed in southern Africa by introgressions with local perennial subspecies. Although the variabilty of domesticated cowpea was the highest ever recorded, cultivar-groups were poorly resolved, and several results obtained with isozyme data were not confirmed here. However primitive cultivars were more diverse than evolved cultivars, which still suggests two consecutive bottlenecks within domesticated cowpea evolution. As isozymes and AFLP markers, although with a larger number of markers, RAPD data confirmed the single domestication hypothesis, the gap between wild and domesticated cowpea, and the widespread introgression phenomena between wild and domesticated cowpea.
Caregiving and volunteering: are private and public helping behaviors linked?

The purpose of this study was to examine the relationship between two forms of helping behavior among older adults--informal caregiving and formal volunteer activity.



To evaluate our hypotheses, we employed Tobit regression models to analyze panel data from the first two waves of the Americans' Changing Lives survey.



We found that older adult caregivers were more likely to be volunteers than noncaregivers. Caregivers who provided a relatively high number of caregiving hours annually reported a greater number of volunteer hours than did noncaregivers. Caregivers who provided care to nonrelatives were more likely than noncaregivers to be a volunteer and to volunteer more hours. Finally, caregivers were more likely than noncaregivers to be asked to volunteer.



Our results provide support for the hypothesis that caregivers are embedded in networks that provide them with more opportunities for volunteering. Additional research on the motivations for volunteering and greater attention to the context and hierarchy of caregiving and volunteering are needed.
Bioequivalence of an ezetimibe/simvastatin combination tablet and coadministration of ezetimibe and simvastatin as separate tablets in healthy subjects.

To assess the bioequivalence of an ezetimibe/simvastatin (EZE/SIMVA) combination tablet compared to the coadministration of ezetimibe and simvastatin as separate tablets (EZE + SIMVA).



In this open-label, randomized, 2-part, 2-period crossover study, 96 healthy subjects were randomly assigned to participate in each part of the study (Part I or II), with each part consisting of 2 single-dose treatment periods separated by a 14-day washout. Part I consisted of Treatments A (EZE 10 mg + SIMVA 10 mg) and B (EZE/SIMVA 10/10 mg/mg) and Part II consisted of Treatments C (EZE 10 mg + SIMVA 80 mg) and D (EZE/SIMVA 10/80 mg/mg). Blood samples were collected up to 96 hours post-dose for determination of ezetimibe, total ezetimibe (ezetimibe + ezetimibe glucuronide), simvastatin and simvastatin acid (the most prevalent active metabolite of simvastatin) concentrations. Ezetimibe and simvastatin acid AUC(0-last) were predefined as primary endpoints and ezetimibe and simvastatin acid Cmax were secondary endpoints. Bioequivalence was achieved if 90% confidence intervals (CI) for the geometric mean ratios (GMR) (single tablet/coadministration) of AUC(0-last) and Cmax fell within prespecified bounds of (0.80, 1.25).



The GMRs of the AUC(0-last) and Cmax for ezetimibe and simvastatin acid fell within the bioequivalence limits (0.80, 1.25). EZE/ SIMVA and EZE + SIMVA were generally well tolerated.



The lowest and highest dosage strengths of EZE/SIMVA tablet were bioequivalent to the individual drug components administered together. Given the exact weight multiples of the EZE/SIMVA tablet and linear pharmacokinetics of simvastatin across the marketed dose range, bioequivalence of the intermediate tablet strengths (EZE/SIMVA 10/20 mg/mg and EZE/SIMVA 10/40 mg/mg) was inferred, although these dosages were not tested directly. These results indicate that the safety and efficacy profile of EZE + SIMVA coadministration therapy can be applied to treatment with the EZE/SIMVA tablet across the clinical dose range.