Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural Language Processing

Summary form only given. Natural language processing (NLP) is a major area of artificial intelligence research, which in its turn serves as a field of application and interaction of a number of other traditional AI areas. Until recently, the focus in AI applications in NLP was on knowledge representation, logical reasoning, and constraint satisfaction - first applied to semantics and later to the grammar. In the last decade, a dramatic shift in the NLP research has led to the prevalence of very large scale applications of statistical methods, such as machine learning and data mining. Naturally, this also opened the way to the learning and optimization methods that constitute the core of modern AI, most notably genetic algorithms and neural networks. In this paper we give an overview of the current trends in NLP and discuss the possible applications of traditional AI techniques and their combination in this fascinating area.
REVS – A ROBUST ELECTRONIC VOTING SYSTEM

There are many protocols proposed for electronic voting, but only a few of them have prototypes implemented. Usually the prototypes are focused in the characteristics of the protocol and do not handle properly some real world issues, such as fault tolerance. This paper presents REVS, a robust electronic voting system designed for distributed and faulty environments, namely the Internet. The goal of REVS is to be an electronic voting system that accomplishes the desired characteristics of traditional voting systems, such as accuracy, democracy, privacy and verifiability. In addition, REVS deals with failures in real world scenarios, such as machine or communication failures, witch can lead to protocol interruptions. REVS robustness has consequences at three levels: (i) the voting process can be interrupted and recovered without weakening the voting protocol; (ii) it allows a certain degree of failures, with server replication; and (iii) none of the servers conducting the election, by its own or to a certain level of collusion, can corrupt the election outcome.
Nonresponders to clopidogrel: pharmacokinetics and interactions involved

Importance of the field: The use of clopidogrel and aspirin has become standard therapy in patients with acute coronary syndromes and stent implantation. However, concern arises because about 25% of subjects are nonresponders to clopidogrel. This nonresponsiveness is associated with a threefold increase in adverse outcomes. Clopidogrel resistance is multifactorial, but genetic polymorphisms in clopidogrel's metabolic activation (e.g., cytochrome P450 2C19) and drug–drug interactions at this level (e.g., between proton pump inhibitors (PPIs) and clopidogrel) are both associated with decreased clopidogrel efficacy. Despite all PPIs being potent inhibitors of CYP2C19, evidence about their clinical impact is controversial. Areas covered in this review: Pharmacogenomic and pharmacokinetic aspects of clopidogrel nonresponsiveness were considered in detail. What the reader will gain: The reader will gain an exhaustive review of the current state of the controversial issues regarding genetic polymorphisms and drug–drug interactions affecting clopidogrel efficacy. Take home message: It is important to consider clopidogrel resistance in some patients and establish strategies to handle this problem (e.g., genotyping, platelet aggregability tests, new antiplatelet drugs). The combined use of PPIs and clopidogrel is at present regulated by the FDA and EMEA; however, the risk/benefit balance should be made for each patient individually.
Analyzing User Retweet Behavior on Twitter

This paper provides a deep analysis of user retweet behavior on Twitter. While previous works about analyzing retweet have mainly focused on predicting the retweetability of each tweet, they lacked interpretations at an individual level. In this paper, we perform a general analysis of retweet behavior from the perspective of individual users. Specifically, we train a prediction model to forecast whether a tweet will be retweeted by a given user, leveraging four different types of features: social-based, content-based, tweet-based and author-based features. By performing “leave-one-feature-out” comparisons, we identify factors that are strongly associated with user retweet behavior.
SPH-based Fluid Simulation with a New Surface Tension Formulation

In this paper, we present an approach of a new surface tension formulation for Smoothed particle hydrodynamics (SPH). Our method of the surface tension formulation is decomposed into three main processes: (1) mesh smoothing, (2) surface tension computation and (3) surface tension transfer. Firstly, we exploit a Lagrangian operator to smooth an initial three-dimensional discrete interfacial surface mesh generated from the fluid particles using the Marching Cubes method, and then the surface mesh should be scaled in a volume-preserved way and its center should make a translation motion to its original position, thus we gain a new volume-preserved smoothed mesh which is abbreviated as smoothed mesh. Secondly, surface tensions strengths on the vertices of the interfacial surface mesh are computed according to the offsets from the original surface mesh to the smoothed mesh. Finally, we transfer the surface tension strengths above from the mesh vertices onto their neighbor particles of SPH in a conservation way. The proposed approach of surface tension solver is simple and straightforward to be plugged into a standard SPH solver. Experimental results show that it is effective and efficient to produce realistic fluid simulations, especially the phenomena associated with strong surface tension.
Robust People Detection and Tracking in a Multi-Camera Indoor Visual Surveillance System

In this paper we describe the analysis component of an indoor, real-time, multi-camera surveillance system. The analysis includes: (1) a novel feature-level foreground segmentation method which achieves efficient and reliable segmentation results even under complex conditions, (2) an efficient greedy search based approach for tracking multiple people through occlusion, and (3) a method for multi-camera handoff that associates individual trajectories in adjacent cameras. The analysis is used for an 18 camera surveillance system that has been running continuously in an indoor business over the past several months. Our experiments demonstrate that the processing method for people detection and tracking across multiple cameras is fast and robust.
The conversion of mouse skin squamous cell carcinomas to spindle cell carcinomas is a recessive event

Squamous carcinomas of both human and rodent origin can undergo a transition to a more invasive, metastatic phenotype involving reorganization of the cytoskeleton, loss of cell adhesion molecules such as E-cadherin and acquisition of a fibroblastoid or spindle cell morphology. We have developed a series of cell lines from mouse skin tumors which represent different stages of carcinogenesis, including benign papillomas, and clonally related squamous and spindle carcinomas derived from the same primary tumor. Some spindle cells continue to express keratins, but with a poorly organized keratin filament network, whereas in others no keratin expression is detectable. All of the spindle cells lack expression of the cell adhesion molecule E-cadherin and the desmosomal component desmoplakin. Loss of these cell surface proteins therefore appears to precede the destabilization of the keratin network. At the genetic level, it is not known whether such changes involve activation of dominantly acting oncogenes or loss of a suppressor function which controls epithelial differentiation. To examine this question, we have carried out a series of fusion experiments between a highly malignant mouse skin spindle cell carcinoma and cell lines derived from premalignant or malignant mouse skin tumors, including both squamous and spindle carcinoma variants. The results show that the spindle cell phenotype as determined by cell morphology and lack of expression of keratin, E-cadherin, and desmoplakin proteins, is recessive in all hybrids with squamous cells. The hybrids expressed all of these differentiation markers, and showed suppression of tumorigenicity to a variable level dependent upon the tumorigenic properties of the less malignant fusion partner. Our results suggest that acquisition of the spindle cell phenotype involves functional loss of a gene(s) which controls epithelial differentiation.
Rich Context-multiple Representations or Rich Context – Good Prototype?

Introduction We are cognitively functioning in a rich context of stimuli. Whether supplied by our mere life experiences or by education, the variety and complexity of the surrounding world is a fact. The capacity of manipulating, producing and communicating upon these stimuli is based on the general assumption of the existence of mental representations. Are these mental representations specific to humans through their organization, form and content? And, since we can communicate with each other about these stimuli, does this mean we all necessarily share the same representations? The existence of the verbal communication system (c.q. language) in humans may make us believe the answer to the first question is rather positive (since language is only present in humans). I will not doubt on it here. However, sharing the same communication system and, within the system, the same language, may not necessarily implicate we all have the same representations. This is the main issue I will try to discuss in the following. To address this question, we shall take a look at theories of representation. Theories of representation would refer in general to language development, concept formation, categorization and symbol use, all putting concept acquisition at its heart (Fodor, 1998). The way they address these correlative issues depends on a basic distinction of the way information is processed: although all theories assume context as departure point, concepts would be acquired through an abstract/amodal way OR a modality-specific way. Abstract theories of representation assume that in the process of the acquisition of concepts, non-essential elements are eliminated, and the essential elements are selected, memorised and consolidated. Concepts, as a form of generalized knowledge, will be found at the basis of higher cognition, being also linguistically labelled. The operations through which concepts are achieved would be abstractisation /generalisation, analysis/synthesis and the similarity/analogy mechanism (Goswami, 1998), so far. Categories will differ from concepts in the sense that concepts have content, i.e. " lexical definition " , while categories do not have a content in themselves, but represent rather a theoretical space as " an extension of a concept ". Categories would have an index function, by relating similar exemplars experienced, and would use the linguistic label of the concept subscribed (my assumption). Further, traditional logic shows that the more restricted the content of a concept is, the larger the extension of the category, and vice-versa, the more essential features put together, the lower …
COINs change leaders - Lessons Learned from a Distributed Course

In this paper we analyze the communication network of 50 students from five universities in three countries participating in a joint course on Collaborative Innovation Networks (COINs). Students formed ten teams. Interaction variables calculated from the e-mail archive of individual team members predict the level of creativity of the team. Oscillating leadership, where members switch between central and peripheral roles is the best predictor of creativity, it is complemented by the variance in the amount of sending or receiving information, and by answering quickly, and positive language. We verify our automatically generated creativity metrics with interviews.
Eradication of Yaws: Historical Efforts and Achieving WHO's 2020 Target

Background Yaws, one of the 17 neglected tropical diseases (NTDs), is targeted for eradication by 2020 in resolution WHA66.12 of the World Health Assembly (2013) and the WHO roadmap on NTDs (2012). The disease frequently affects children who live in poor socioeconomic conditions. Between 1952 and 1964, WHO and the United Nations Children's Fund (UNICEF) led a global eradication campaign using injectable benzathine penicillin. Recent developments using a single dose of oral azithromycin have renewed optimism that eradication can be achieved through a comprehensive large-scale treatment strategy. We review historical efforts to eradicate yaws and argue that this goal is now technically feasible using new tools and with the favorable environment for control of NTDs. We also summarize the work of WHO's Department of Control of Neglected Tropical Diseases in leading the renewed eradication initiative and call on the international community to support efforts to achieve the 2020 eradication goal. The critical factor remains access to azithromycin. Excluding medicines, the financial cost of yaws eradication could be as little as US$ 100 million. Conclusions The development of new tools has renewed interest in eradication of yaws; with modest support, the WHO eradication target of 2020 can be achieved.
CREBBP and EP300 mutational spectrum and clinical presentations in a cohort of Swedish patients with Rubinstein–Taybi syndrome

Rubinstein–Taybi syndrome (RTS) is a rare autosomal dominant congenital disorder characterized by distinctive facial features, broad thumbs and halluces, growth retardation, and a variable degree of cognitive impairment. CREBBP is the major causative gene and mutations in EP300 are the cause of RTS in a minority of patients. In this study, 17 patients with a clinical diagnosis of RTS were investigated with direct sequencing, MLPA, and array‐CGH in search for mutations in these two genes. Eleven patients (64.7%) had disease‐causing point mutations or a deletion in CREBBP and in one patient (5.9%) a causal de novo frameshift mutation in EP300 was identified. This patient had broad thumbs, mild intellectual disability, and autism. In addition, an inherited missense mutation of uncertain clinical significance was identified in EP300 in one patient and his healthy father, and three patients had intronic nucleotide changes of uncertain clinical significance in CREBBP. Snoring and sleep apnea were common in both groups and four of the patients' mothers had preeclampsia during pregnancy. Importantly, difficulties associated with anesthesia were frequently reported and included delayed or complicated emergency in 53.3% of patients.
Die Apache Flink Plattform zur parallelen Analyse von Datenströmen und Stapeldaten

Die Menge an analysierbaren Daten steigt aufgrund fallen- der Preise fur Speicherlosungen und der Erschlieung neuer Datenquellen rasant. Da klassische Datenbanksysteme nicht ausreichend parallelisier- bar sind, konnen sie die heute anfallenden Datenmengen haug nicht mehr verarbeiten. Hierdurch ist es notwendig spezielle Programme zur parallelen Datenanalyse zu verwenden. Die Entwicklung solcher Pro- gramme fur Computercluster ist selbst fur erfahrene Systemprogram- mierer eine komplexe Herausforderung. Frameworks wie Apache Hadoop MapReduce sind zwar skalierbar, aber im Vergleich zu SQL schwer zu programmieren. Die Open-Source Plattform Apache Flink schliet die Lucke zwischen herkommlichen Datenbanksystemen und Big-Data Analyseframeworks. Das Top Level Projekt der Apache Software Foundation basiert auf einer fehlertoleranten Laufzeitumgebung zur Datenstromverarbeitung, welche die Datenverteilung und Kommunikation im Cluster  Verschiedene Schnittstellen erlauben die Implementierung von Daten- analyseablaufen fur unterschiedlichste Anwendungsfalle. Die Plattform wird von einer aktiven Community kontinuierlich weiter entwickelt. Sie ist gleichzeitig Produkt und Basis vieler Forschungsarbeiten im Bereich Datenbanken und Informationsmanagement. Stichworter: Big-Data, Datenstromverarbeitung, Stapelverarbeitung, Datenanalyse, Datenbanken, Datenanalyseablaufe
Agricultural Productivity in China and India: A Comparative Analysis

China and India are the world's two most populous countries; together they comprise more than one-third of the total population. For a thousand years, most people in both countries lived in rural areas. Even today the rural population in each nation accounts for about 80 percent of its population. Although China and India differ greatly in economic, social, and political circumstance, both emerged as net exporters of agricultural products after more than three decades of development.1 Each country, however, employed different strategies and reforms and, therefore, they have been great interest to economists for many years.
Recurrent neural network models for disease name recognition using domain invariant features

Hand-crafted features based on linguistic and domain-knowledge play crucial role in determining the performance of disease name recognition systems. Such methods are further limited by the scope of these features or in other words, their ability to cover the contexts or word dependencies within a sentence. In this work, we focus on reducing such dependencies and propose a domain-invariant framework for the disease name recognition task. In particular, we propose various end-to-end recurrent neural network (RNN) models for the tasks of disease name recognition and their classification into four pre-defined categories. We also utilize convolution neural network (CNN) in cascade of RNN to get character-based embedded features and employ it with word-embedded features in our model. We compare our models with the state-of-the-art results for the two tasks on NCBI disease dataset. Our results for the disease mention recognition task indicate that state-of-the-art performance can be obtained without relying on feature engineering. Further the proposed models obtained improved performance on the classification task of disease names.
Test vector decompression via cyclical scan chains and its application to testing core-based designs

A novel test vector compression/decompression technique is proposed for reducing the amount of test data that must be stored on a tester and transferred to each core when testing a core-based design. A small amount of on-chip circuitry is used to reduce both the test storage and test time required for testing a core-based design. The fully specified test vectors provided by the core vendor are stored in compressed form in the tester memory and transferred to the chip where they are decompressed and applied to the core (the compression is lossless). Instead of having to transfer each entire test vector from the tester to the core, a smaller amount of compressed data is transferred instead. This reduces the amount of test data that must be stored on the tester and hence reduces the total amount of test time required for transferring the data with a given test data bandwidth.
The Role of Macrophages in Demyelinating Peripheral Nervous System of Mice Heterozygously Deficient in P0

Mice heterozygously deficient in the p0 gene (P0+/−) are animal models for some forms of inherited neuropathies. They display a progressive demyelinating phenotype in motor nerves, accompanied by mild infiltration of lymphocytes and increase in macrophages. We have shown previously that the T lymphocytes are instrumental in the demyelination process. This study addresses the functional role of the macrophage in this monogenic myelin disorder. In motor nerves of P0+/− mice, the number of macrophages in demyelinated peripheral nerves was increased by a factor of five when compared with motor nerves of wild-type mice. Immunoelectron microscopy, using a specific marker for mouse macrophages, displayed macrophages not only in the endoneurium of the myelin mutants, but also within endoneurial tubes, suggesting an active role in demyelination. To elucidate the roles of the macrophages, we crossbred the myelin mutants with a spontaneous mouse mutant deficient in macrophage colony-stimulating factor (M-CSF), hence displaying impaired macrophage activation. In the P0-deficient double mutants also deficient in M-CSF, the numbers of macrophages were not elevated in the demyelinating motor nerves and demyelination was less severe. These findings demonstrate an active role of macrophages during pathogenesis of inherited demyelination with putative impact on future treatment strategies.
New word learning in young children with Autism Spectrum Disorder

At least some children with Autism Spectrum Disorder (ASD) have sensory processing differences which are likely to impact on speech processing and early language development. There is limited research in this area with the population in this study, i.e., preschool children with ASD and minimal or no language. This study explores the effects of modified speech on fast mapping and learning new words using video modelling, based on evidence in ASD of particular difficulty processing speech in background noise, temporal speech processing and a potential multisensory integration deficit. A case series design with multiple measures was used to compare the impact of modified video modelling with control conditions on learning and fast mapping new words. Video modelling had an overall positive impact on fast mapping and learning new words compared to non-taught control words, but was not superior to live modelling. Artificially slowing speech and background noise had minimal or no effect on taught vocabulary, although this does not preclude effects in natural environments. The atypical effects on fast mapping new words from asynchronous audiovisual presentation was consistent with a multisensory integration deficit in ASD, but the extent to which this supports theories of autism such as an extended multisensory temporal binding window requires further research. Methodological limitations indicate caution generalising findings. There was wide variation in participant performance and profiles, including sensory processing. This suggests the need for detailed assessment of sensory processing alongside other abilities in order to tailor interventions supporting language development to each child’s unique profile. Given evidence of deficits in attention and positive associations between video modelling and attention in this study and the literature, video modelling may be helpful alongside other strategies in supporting young children with ASD fast map or learn new words when they are struggling to do so by other means.
An Improved MRWD Coding Algorithm

The MRWD (mathematical morphology of the wavelet data) algorithm utilizes morphological dilation in the wavelet domain to exploit the salient wavelet coefficient, with the appearance of a mass of long series of "0" code stream in the bit-plane. By studying the statistical characteristics of bit stream of wavelet coefficient of some typical images in bit-plane and MRWD code of some original code stream, an improved MRWD coding algorithm is presented to reduce tremendous redundancies existing in MRWD code. The improved MRWD algorithm is a lossless compressing algorithm vs MRWD algorithm, with the same SNR in both algorithms. Simulation results showed that the improved MRWD can reduce the lengths of encoded streams to increase the compression ratio of digital images, and also fully meet actual requirements for encoding of many images.