nils-herrmann/clean_scirepeval huggingface dataset:
Cerebral Atrophy in a Vitamin B12-deficient Infant of a Vegetarian Mother

In developed countries, vitamin B12 (cobalamin) deficiency usually occurs in children, exclusively breastfed ones whose mothers are vegetarian, causing low body stores of vitamin B12. The haematologic manifestation of vitamin B12 deficiency is pernicious anaemia. It is a megaloblastic anaemia with high mean corpuscular volume and typical morphological features, such as hyperlobulation of the nuclei of the granulocytes. In advanced cases, neutropaenia and thrombocytopaenia can occur, simulating aplastic anaemia or leukaemia. In addition to haematological symptoms, infants may experience weakness, fatigue, failure to thrive, and irritability. Other common findings include pallor, glossitis, vomiting, diarrhoea, and icterus. Neurological symptoms may affect the central nervous system and, in severe cases, rarely cause brain atrophy. Here, we report an interesting case, a 12-month old infant, who was admitted with neurological symptoms and diagnosed with vitamin B12 deficiency.
Learning to crawl: Comparing classification schemes

Topical crawling is a young and creative area of research that holds the promise of benefiting from several sophisticated data mining techniques. The use of classification algorithms to guide topical crawlers has been sporadically suggested in the literature. No systematic study, however, has been done on their relative merits. Using the lessons learned from our previous crawler evaluation studies, we experiment with multiple versions of different classification schemes. The crawling process is modeled as a parallel best-first search over a graph defined by the Web. The classifiers provide heuristics to the crawler thus biasing it towards certain portions of the Web graph. Our results show that Naive Bayes is a weak choice for guiding a topical crawler when compared with Support Vector Machine or Neural Network. Further, the weak performance of Naive Bayes can be partly explained by extreme skewness of posterior probabilities generated by it. We also observe that despite similar performances, different topical crawlers cover subspaces on the Web with low overlap.
Role of virtual reality for cerebral palsy management.

Virtual reality is the use of interactive simulations to present users with opportunities to perform in virtual environments that appear, sound, and less frequently, feel similar to real-world objects and events. Interactive computer play refers to the use of a game where a child interacts and plays with virtual objects in a computer-generated environment. Because of their distinctive attributes that provide ecologically realistic and motivating opportunities for active learning, these technologies have been used in pediatric rehabilitation over the past 15 years. The ability of virtual reality to create opportunities for active repetitive motor/sensory practice adds to their potential for neuroplasticity and learning in individuals with neurologic disorders. The objectives of this article is to provide an overview of how virtual reality and gaming are used clinically, to present the results of several example studies that demonstrate their use in research, and to briefly remark on future developments.
Learning Dynamic Generator Model by Alternating Back-Propagation Through Time

This paper studies the dynamic generator model for spatialtemporal processes such as dynamic textures and action sequences in video data. In this model, each time frame of the video sequence is generated by a generator model, which is a non-linear transformation of a latent state vector, where the non-linear transformation is parametrized by a top-down neural network. The sequence of latent state vectors follows a non-linear auto-regressive model, where the state vector of the next frame is a non-linear transformation of the state vector of the current frame as well as an independent noise vector that provides randomness in the transition. The non-linear transformation of this transition model can be parametrized by a feedforward neural network. We show that this model can be learned by an alternating back-propagation through time algorithm that iteratively samples the noise vectors and updates the parameters in the transition model and the generator model. We show that our training method can learn realistic models for dynamic textures and action patterns.
On the Provable Security of (EC)DSA Signatures

Among the signature schemes most widely deployed in practice are the DSA (Digital Signature Algorithm) and its elliptic curves variant ECDSA. They are represented in many international standards, including IEEE P1363, ANSI X9.62, and FIPS 186-4. Their popularity stands in stark contrast to the absence of rigorous security analyses: Previous works either study modified versions of (EC)DSA or provide a security analysis of unmodified ECDSA in the generic group model. Unfortunately, works following the latter approach assume abstractions of non-algebraic functions over generic groups for which it remains unclear how they translate to the security of ECDSA in practice. For instance, it has been pointed out that prior results in the generic group model actually establish strong unforgeability of ECDSA, a property that the scheme de facto does not possess. As, further, no formal results are known for DSA, understanding the security of both schemes remains an open problem. In this work we propose GenericDSA, a signature framework that subsumes both DSA and ECDSA in unmodified form. It carefully models the "modulo q" conversion function of (EC)DSA as a composition of three independent functions. The two outer functions mimic algebraic properties in the function's domain and range, the inner one is modeled as a bijective random oracle. We rigorously prove results on the security of GenericDSA that indicate that forging signatures in (EC)DSA is as hard as solving discrete logarithms. Importantly, our proofs do not assume generic group behavior.
Generic Graphical User Interfaces

It is important to be able to program GUI applications in a fast and easy manner. Current GUI tools for creating visually attractive applications offer limited functionality. In this paper we introduce a new, easy to use method to program GUI applications in a pure functional language such as Clean or Generic Haskell. The method we use is a refined version of the model-view paradigm. The basic component in our approach is the Graphical Editor Component (GECτ ) that can contain any value of any flat data type τ and that can be freely used to display and edit its value. GECτ s can depend on others, but also on themselves. They can even be mutually dependent. With these components we can construct a flexible, reusable and customizable editor. For the realization of the components we had to invent a new generic implementation technique for interactive applications.
Sequence Transduction with Recurrent Neural Networks

Many machine learning tasks can be expressed as the transformation—or transduction—of input sequences into output sequences: speech recognition, machine translation, protein secondary structure prediction and text-to-speech to name but a few. One of the key challenges in sequence transduction is learning to represent both the input and output sequences in a way that is invariant to sequential distortions such as shrinking, stretching and translating. Recurrent neural networks (RNNs) are a powerful sequence learning architecture that has proven capable of learning such representations. However RNNs traditionally require a pre-defined alignment between the input and output sequences to perform transduction. This is a severe limitation since finding the alignment is the most difficult aspect of many sequence transduction problems. Indeed, even determining the length of the output sequence is often challenging. This paper introduces an end-to-end, probabilistic sequence transduction system, based entirely on RNNs, that returns a distribution over output sequences of all possible lengths and alignments for any input sequence. Experimental results are provided on the TIMIT speech corpus.
Fast defocus map estimation

This paper presents a fast algorithm for deriving the defocus map from a single image. Existing methods of defocus map estimation often include a pixel-level propagation step to spread the measured sparse defocus cues over the whole image. Since the pixel-level propagation step is time-consuming, we develop an effective method to obtain the whole-image defocus blur using oversegmentation and transductive inference. Oversegmentation produces the superpixels and hence greatly reduces the computation costs for subsequent procedures. Transductive inference provides a way to calculate the similarity between superpixels, and thus helps to infer the defocus blur of each superpixel from all other superpixels. The experimental results show that our method is efficient and able to estimate a plausible superpixel-level defocus map from a given single image.
Speculative trading in mean reverting markets

Mean reversion is a feature largely recognized for the price processes of many financial securities and especially commodities. In the literature there are examples where some simple speculative strategies, before transaction costs, were devised to earn excess returns from such price processes. Actually, the gain opportunities of mean reversion must be corrected to account for transaction costs, which may represent a major issue. In this work we try to determine sufficient conditions for the parameters of a mean reverting price process as a function of transaction costs, to allow a speculative trader to have positive expectations when deciding to take a position. We estimate the mean reverting parameters for some commodities and correct them for transaction costs to assess whether the potential inefficiency is actually relevant for speculative purposes.
Characterizing Geographic Variation in Well-Being Using Tweets

The language used in tweets from 1,300 different US counties was found to be predictive of the subjective well-being of people living in those counties as measured by representative surveys. Topics, sets of cooccurring words derived from the tweets using LDA, improved accuracy in predicting life satisfaction over and above standard demographic and socio-economic controls (age, gender, ethnicity, income, and education). The LDA topics provide a greater behavioural and conceptual resolution into life satisfaction than the broad socio-economic and demographic variables. For example, tied in with the psychological literature, words relating to outdoor activities, spiritual meaning, exercise, and good jobs correlate with increased life satisfaction, while words signifying disengagement like ’bored’ and ’tired’ show a negative association.
A Minimal Closed-form Solution for the Perspective Three Orthogonal Angles (P3oA) Problem: Application To Visual Odometry

We provide a simple closed-form solution to the Perspective three orthogonal angles (P3oA) problem: given the projection of three orthogonal lines in a calibrated camera, find their 3D directions. Upon this solution, an algorithm for the estimation of the camera relative rotation between two frames is proposed. The key idea is to detect triplets of orthogonal lines in a hypothesize-and-test framework and use all of them to compute the camera rotation in a robust way. This approach is suitable for human-made environments where numerous groups of orthogonal lines exist. We evaluate the numerical stability of the P3oA solution and the estimation of the relative rotation with synthetic and real data, comparing our results to other state-of-the-art approaches.
A Wide-Angle E-Plane Scanning Linear Array Antenna With Wide Beam Elements

In order to improve the wide-angle scanning performance of the phased array antennas, a wide-beam microstrip antenna with metal walls is proposed in this letter. The beamwidth of the antenna is broadened by the horizontal current on the radiating patch and the vertical current on the metal walls. The half-power beamwidth of the E- and H-planes is 221° and 168° at 4.0 GHz. Furthermore, the wide-beam antenna element is employed in a nine-element E-plane linear array antenna. The main beam of the E-plane scanning linear array antenna can scan from −70° to +70° in the frequency band from 3.7 to 4.3 GHz with a gain fluctuation less than 2.7 dB and variation in maximum sidelobe level less than −5.8 dB. The E-plane scanning linear array antenna with nine elements is fabricated and tested. The measured results achieve a good agreement with the simulated results.
Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns

Recent systems have been developed for sentiment classification, opinion recogni­ tion, and opinion analysis (e.g., detect­ ing polarity and strength). We pursue an­ other aspect of opinion analysis: identi­ fying the sources of opinions, emotions, and sentiments. We view this problem as an information extraction task and adopt a hybrid approach that combines Con­ ditional Random Fields (Lafferty et al., 2001) and a variation of AutoSlog (Riloff, 1996a). While CRFs model source iden­ tification as a sequence tagging task, Au­ toSlog learns extraction patterns. Our re­ sults show that the combination of these two methods performs better than either one alone. The resulting system identifies opinion sources with precision and recall using a head noun matching measure, and precision and recall using an overlap measure.
Extracellular vesicles – biogenesis, composition, function, uptake and therapeutic applications

Extracellular vesicles are heterogenous, nano-sized, membrane-limited structures which not only represent a specific way of intercellular communication but also endow cells with many capabilities. Apoptotic bodies created during apoptosis, microvesicles shed from the plasma membrane, and exosomes originated inside the cell and released to extracellular space upon fusion with the plasma membrane, they all belong to extracellular vesicles. Extracellular vesicles contain lipids, proteins, and nucleic acids. In this review, we describe their biogenesis, release and uptake by recipient cells, their composition, functions and potential therapeutic and diagnostic applications.
Browsing a Digital Library: A New Approach for the New Zealand Digital Library

Browsing is part of the information seeking process, used when information needs are ill-defined or unspecific. Browsing and searching are often interleaved during information seeking to accommodate changing awareness of information needs. Digital Libraries often support full-text search, but are not so helpful in supporting browsing. Described here is a novel browsing system created for the Greenstone software used by the New Zealand Digital Library that supports users in a more natural approach to the information seeking process.
Perianal abscess.

only Painful initially, patient preference No cost Digitation Pilot RCTs 28 Potential risk of premature closure No cost Open wound (fig 4⇓) RCT = randomised controlled trial. For personal use only: See rights and reprints http://www.bmj.com/permissions Subscribe: http://www.bmj.com/subscribe BMJ 2017;356:j475 doi: 10.1136/bmj.j475 (Published 2017 February 21) Page 4 of 6
Updates on Sorting of Fully Homomorphic Encrypted Data

In this paper, we show implementation results of various algorithms that sort data encrypted with Fully Ho-momorphic Encryption scheme based on Integers. We analyze the complexities of sorting algorithms over encrypted data by considering Bubble Sort, Insertion Sort, Bitonic Sort and Odd-Even Merge sort. Our complexity analysis together with implementation results show that Odd-Even Merge Sort has better performance than the other sorting techniques. We observe that complexity of sorting in homomorphic domain will always have worst case complexity independent of the nature of input. In addition, we show that combining different sorting algorithms to sort encrypted data does not give any performance gain when compared to the application of sorting algorithms individually.
Using Constraint Programming to Reason on Feature Models

Feature models have been cited as one of the main contributions to model software product families. However, there is still a gap in product family engineering which is the automated reasoning on feature models. In this paper we describe how to reason on feature models using constraint programming. Although, there are a few attempts to reason on feature models there are two main drawbacks in these proposals: none of them associate parameters to features none of them use constraint programming as the reasoning base. Using constraint programming endows our proposal with a more powerful reasoning capacity and greater expressiveness than others.
BOKP: A DNA Barcode Reference Library for Monitoring Herbal Drugs in the Korean Pharmacopeia

Herbal drug authentication is an important task in traditional medicine; however, it is challenged by the limitations of traditional authentication methods and the lack of trained experts. DNA barcoding is conspicuous in almost all areas of the biological sciences and has already been added to the British pharmacopeia and Chinese pharmacopeia for routine herbal drug authentication. However, DNA barcoding for the Korean pharmacopeia still requires significant improvements. Here, we present a DNA barcode reference library for herbal drugs in the Korean pharmacopeia and developed a species identification engine named KP-IDE to facilitate the adoption of this DNA reference library for the herbal drug authentication. Using taxonomy records, specimen records, sequence records, and reference records, KP-IDE can identify an unknown specimen. Currently, there are 6,777 taxonomy records, 1,054 specimen records, 30,744 sequence records (ITS2 and psbA-trnH) and 285 reference records. Moreover, 27 herbal drug materials were collected from the Seoul Yangnyeongsi herbal medicine market to give an example for real herbal drugs authentications. Our study demonstrates the prospects of the DNA barcode reference library for the Korean pharmacopeia and provides future directions for the use of DNA barcoding for authenticating herbal drugs listed in other modern pharmacopeias.
Concerted microRNA control of Hedgehog signalling in cerebellar neuronal progenitor and tumour cells.

MicroRNAs (miRNA) are crucial post-transcriptional regulators of gene expression and control cell differentiation and proliferation. However, little is known about their targeting of specific developmental pathways. Hedgehog (Hh) signalling controls cerebellar granule cell progenitor development and a subversion of this pathway leads to neoplastic transformation into medulloblastoma (MB). Using a miRNA high-throughput profile screening, we identify here a downregulated miRNA signature in human MBs with high Hh signalling. Specifically, we identify miR-125b and miR-326 as suppressors of the pathway activator Smoothened together with miR-324-5p, which also targets the downstream transcription factor Gli1. Downregulation of these miRNAs allows high levels of Hh-dependent gene expression leading to tumour cell proliferation. Interestingly, the downregulation of miR-324-5p is genetically determined by MB-associated deletion of chromosome 17p. We also report that whereas miRNA expression is downregulated in cerebellar neuronal progenitors, it increases alongside differentiation, thereby allowing cell maturation and growth inhibition. These findings identify a novel regulatory circuitry of the Hh signalling and suggest that misregulation of specific miRNAs, leading to its aberrant activation, sustain cancer development.
Essential Oils Loaded in Nanosystems: A Developing Strategy for a Successful Therapeutic Approach

Essential oils are complex blends of a variety of volatile molecules such as terpenoids, phenol-derived aromatic components, and aliphatic components having a strong interest in pharmaceutical, sanitary, cosmetic, agricultural, and food industries. Since the middle ages, essential oils have been widely used for bactericidal, virucidal, fungicidal, antiparasitical, insecticidal, and other medicinal properties such as analgesic, sedative, anti-inflammatory, spasmolytic, and locally anaesthetic remedies. In this review their nanoencapsulation in drug delivery systems has been proposed for their capability of decreasing volatility, improving the stability, water solubility, and efficacy of essential oil-based formulations, by maintenance of therapeutic efficacy. Two categories of nanocarriers can be proposed: polymeric nanoparticulate formulations, extensively studied with significant improvement of the essential oil antimicrobial activity, and lipid carriers, including liposomes, solid lipid nanoparticles, nanostructured lipid particles, and nano- and microemulsions. Furthermore, molecular complexes such as cyclodextrin inclusion complexes also represent a valid strategy to increase water solubility and stability and bioavailability and decrease volatility of essential oils.
Fast Solving of Influence Diagrams for Multiagent Planning on GPU-enabled Architectures

Planning under uncertainty in multiagent settings is highly intractable because of history and plan space complexities. Probabilistic graphical models exploit the structure of the problem domain to mitigate the computational burden. In this paper, we introduce the first parallelization of planning in multiagent settings on a CPU-GPU heterogeneous system. In particular, we focus on the algorithm for exactly solving interactive dynamic influence diagrams , which is a recognized graphical models for multiagent planning. Beyond parallelizing the standard Bayesian inference, the computation of decisions’ expected utilities are parallelized. The GPU-based approach provides significant speedup on two benchmark problems.
Priapism: pathogenesis, epidemiology, and management.

Priapism describes a persistent erection arising from dysfunction of mechanisms regulating penile tumescence, rigidity, and flaccidity. A correct diagnosis of priapism is a matter of urgency requiring identification of underlying hemodynamics.



To define the types of priapism, address its pathogenesis and epidemiology, and develop an evidence-based guideline for effective management.



Six experts from four countries developed a consensus document on priapism; this document was presented for peer review and debate in a public forum and revisions were made based on recommendations of chairpersons to the International Consultation on Sexual Medicine. This report focuses on guidelines written over the past decade and reviews the priapism literature from 2003 to 2009. Although the literature is predominantly case series, recent reports have more detailed methodology including duration of priapism, etiology of priapism, and erectile function outcomes.



Consensus recommendations were based on evidence-based literature, best medical practices, and bench research.



Basic science supporting current concepts in the pathophysiology of priapism, and clinical research supporting the most effective treatment strategies are summarized in this review.



Prompt diagnosis and appropriate management of priapism are necessary to spare patients ineffective interventions and maximize erectile function outcomes. Future research is needed to understand corporal smooth muscle pathology associated with genetic and acquired conditions resulting in ischemic priapism. Better understanding of molecular mechanisms involved in the pathogenesis of stuttering ischemic priapism will offer new avenues for medical intervention. Documenting erectile function outcomes based on duration of ischemic priapism, time to interventions, and types of interventions is needed to establish evidence-based guidance. In contrast, pathogenesis of nonischemic priapism is understood, and largely attributable to trauma. Better documentation of onset of high-flow priapism in relation to time of injury, and response to conservative management vs. angiogroaphic or surgical interventions is needed to establish evidence-based guidance.