Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure

The learning classifier system XCS is an iterative rule-learning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classification and reinforcement learning tasks, XCS was applied as an effective function approximator. Hereby, XCS learns space partitions to enable a maximally accurate and general function approximation. Recently, the function approximation approach was improved by replacing (1) hyperrectangular conditions with hyper-ellipsoids and (2) iterative linear approximation with the recursive least squares method. This paper combines the two approaches assessing the usefulness of each. The evolutionary process is further improved by changing the mutation operator implementing an angular mutation that rotates ellipsoidal structures explicitly. Both enhancements improve XCS performance in various non-linear functions. We also analyze the evolving ellipsoidal structures confirming that XCS stretches and rotates the evolving ellipsoids according to the shape of the underlying function. The results confirm that improvements in both the evolutionary approach and the gradient approach can result in significantly better performance.
Chapter 5 . 1 – Protecting Data in Outsourcing Scenarios

Goal of this chapter is to describe the main solutions being devised for protecting data confidentiality and integrity in outsourcing scenarios. In particular, we illustrate approaches that guarantee data confidentiality by applying encryption or a combination of encryption and fragmentation. We then focus on approaches that aim at guaranteeing data integrity in storage and in query computation. Finally, we present some issues that still need to be investigated for ensuring privacy and security of data outsourced to external
Book Reviews: Statistical Language Learning

The $64,000 question in computational linguistics these days is: "What should I read to learn about statistical natural language processing? " I have been asked this question over and over, and each time I have given basically the same reply: there is no text that addresses this topic directly; the best one can do is find a good probability-theory textbook and a good information-theory textbook and supplement those texts with an assortment of conference papers and journal articles. Understanding the disappointment this answer provoked, I was delighted to hear that someone had finally written a book directly addressing this topic. However, after reading Eugene Charniak's Statistical Language Learning, I have very mixed feelings about the impact this book might have on the ever-growing field of statistical NLP. The book begins with a very brief description of the classic artificial intelligence approach to NLP (Chapter 1), including morphology, syntax, semantics, and pragmatics. It presents a few definitions from probability theory and information theory (Chapter 2), then proceeds to introduce hidden Markov models (Chapters 3 and 4) and probabilistic context-free grammars (Chapters 5 and 6). The book concludes with a few chapters discussing advanced topics in statistical language learning, such as grammar induction (Chapter 7), syntactic disambiguation (Chapter 8), word clustering (Chapter 9), and word sense disambiguation (Chapter 10). To its credit, the book serves as an interesting popular discussion of statistical modeling in NLP. It is well written and entertaining and very accessible to the reader with a limited mathematical background. It presents a good selection of statistical NLP topics to introduce the reader to the field. And the descriptions of the forwardbackward algorithm for hidden Markov models and the inside-outside algorithm for probabilistic context-free grammars are intuitive and easy to follow. However, as a resource for someone interested in entering this area of research, this book falls far short of its author's goals. These goals are clearly stated in the preface:
Transcriptome of Cultured Lung Fibroblasts in Idiopathic Pulmonary Fibrosis: Meta-Analysis of Publically Available Microarray Datasets Reveals Repression of Inflammation and Immunity Pathways

Heritable profibrotic differentiation of lung fibroblasts is a key mechanism of idiopathic pulmonary fibrosis (IPF). Its mechanisms are yet to be fully understood. In this study, individual data from four independent microarray studies comparing the transcriptome of fibroblasts cultured in vitro from normal (total n = 20) and IPF (total n = 20) human lung were compiled for meta-analysis following normalization to z-scores. One hundred and thirteen transcripts were upregulated and 115 were downregulated in IPF fibroblasts using the Significance Analysis of Microrrays algorithm with a false discovery rate of 5%. Downregulated genes were highly enriched for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classes related to inflammation and immunity such as Defense response to virus, Influenza A, tumor necrosis factor (TNF) mediated signaling pathway, interferon-inducible absent in melanoma2 (AIM2) inflammasome as well as Apoptosis. Although upregulated genes were not enriched for any functional class, select factors known to play key roles in lung fibrogenesis were overexpressed in IPF fibroblasts, most notably connective tissue growth factor (CTGF) and serum response factor (SRF), supporting their role as drivers of IPF. The full data table is available as a supplement.
Getting the Cocktail Party Started: Masking Effects in Speech Perception

Spoken conversations typically take place in noisy environments, and different kinds of masking sounds place differing demands on cognitive resources. Previous studies, examining the modulation of neural activity associated with the properties of competing sounds, have shown that additional speech streams engage the superior temporal gyrus. However, the absence of a condition in which target speech was heard without additional masking made it difficult to identify brain networks specific to masking and to ascertain the extent to which competing speech was processed equivalently to target speech. In this study, we scanned young healthy adults with continuous fMRI, while they listened to stories masked by sounds that differed in their similarity to speech. We show that auditory attention and control networks are activated during attentive listening to masked speech in the absence of an overt behavioral task. We demonstrate that competing speech is processed predominantly in the left hemisphere within the same pathway as target speech but is not treated equivalently within that stream and that individuals who perform better in speech in noise tasks activate the left mid-posterior superior temporal gyrus more. Finally, we identify neural responses associated with the onset of sounds in the auditory environment; activity was found within right lateralized frontal regions consistent with a phasic alerting response. Taken together, these results provide a comprehensive account of the neural processes involved in listening in noise.
Up-Regulation of P2X4 Receptors in Spinal Microglia after Peripheral Nerve Injury Mediates BDNF Release and Neuropathic Pain

ATP is a known mediator of inflammatory and neuropathic pain. However, the mechanisms by which specific purinergic receptors contribute to chronic pain states are still poorly characterized. Here, we demonstrate that in response to peripheral nerve injury, P2X4 receptors (P2X4R) are expressed de novo by activated microglia in the spinal cord. Using in vitro and in vivo models, we provide direct evidence that P2X4R stimulation leads to the release of BDNF from activated microglia and, most likely phosphorylation of the NR1 subunit of NMDA receptors in dorsal horn neurons of the spinal cord. Consistent with these findings, P2X4-deficient mice lack mechanical hyperalgesia induced by peripheral nerve injury and display impaired BDNF signaling in the spinal cord. Furthermore, ATP stimulation is unable to stimulate BDNF release from P2X4-deficient mice microglia in primary cultures. These results indicate that P2X4R contribute to chronic pain through a central inflammatory pathway. P2X4R might thus represent a potential therapeutic target to limit microglia-mediated inflammatory responses associated with brain injury and neurodegenerative disorders.
Generation of mice with a conditional null allele for Tbx2

The T‐box transcription factor Tbx2 plays important roles in patterning and development, and has been implicated in cell‐cycle regulation and cancer. Conventional disruption of Tbx2 results in abnormalities of the heart, limbs, eye and other structures, and early fetal lethality. To gain insight into the role of Tbx2 in different tissues and at different stages of development, we have generated a conditional null allele of Tbx2 by flanking Exon 2 with loxP sites (Tbx2fl2). Homozygous Tbx2fl2 mice are viable and fertile, indicating that the Tbx2fl2 allele is a fully functional Tbx2 allele. Cre‐mediated recombination, using a ubiquitously active CMV‐Cre line, results in deletion of Exon 2 and loss of protein expression. Embryos homozygous for the recombined allele (Tbx2Δ2) show the same heart and limb defects as conventional Tbx2‐deficient embryos. This Tbx2 conditional null allele will be a valuable tool to uncover tissue‐specific roles of Tbx2 in development and disease. genesis 48:195–199, 2010. © 2010 Wiley‐Liss, Inc.
Carbon Fibre Reinforced Polypropylene: An Electrical Conductivity Model

This Extrusion permit in controlling electrical conductivity before composite materials undergo the manufacturing process. However, studies on electrical conductivity in high conductive polymer composite materials are still in preliminary stage. Thus, the studies on electrical conductivity model are crucial as it able in predicting the electrical conductivity hence minimizing the experimental conducted. In this study, conductivity model was conducted to validate the series of experiment. The electrical conductivity increases as shear rate decrease and the highest electrical conductivity of 3 S/cm is obtained which indicated that the shear rate is crucial in increasing the electrical conductivity of the composites compared to extrusion temperature hence it is consider in the modelling.
BogusBiter: A transparent protection against phishing attacks

Many anti-phishing mechanisms currently focus on helping users verify whether a Web site is genuine. However, usability studies have demonstrated that prevention-based approaches alone fail to effectively suppress phishing attacks and protect Internet users from revealing their credentials to phishing sites. In this paper, instead of preventing human users from “biting the bait,” we propose a new approach to protect against phishing attacks with “bogus bites. ” We develop BogusBiter, a unique client-side anti-phishing tool, which transparently feeds a relatively large number of bogus credentials into a suspected phishing site. BogusBiter conceals a victim's real credential among bogus credentials, and moreover, it enables a legitimate Web site to identify stolen credentials in a timely manner. Leveraging the power of client-side automatic phishing detection techniques, BogusBiter is complementary to existing preventive anti-phishing approaches. We implemented BogusBiter as an extension to the Firefox 2 Web browser, and evaluated its efficacy through real experiments on both phishing and legitimate Web sites. Our experimental results indicate that it is promising to use BogusBiter to transparently protect against phishing attacks.
Involved field radiotherapy for limited stage Hodgkin lymphoma: balancing treatment efficacy against long‐term toxicities

Limited stage Hodgkin lymphoma (HL) refers to patients with stage IA or IIA disease in the absence of any bulky mass or unfavourable prognostic factors. In this group, the long‐term disease control with treatment can be expected in more than 90%, and management has now been directed to make strategies to reduce late morbidities related to therapy. With the advent of very effective chemotherapy, the role of radiation therapy has evolved from a first line single modality treatment, to an adjuvant therapy following brief cycles of chemotherapy. Optimal radiation volume and dose parameters have been refined in the combined modality setting. Furthermore, with the progress in diagnostic functional imaging and advances in radiotherapy, it is possible to accurately deliver low to moderate doses of radiation to defined regions resulting in durable control of disease. This review will evaluate the literature that shapes the current standard of care in limited stage Hodgkin lymphoma with special emphasis on the use of limited field radiotherapy. Copyright © 2009 John Wiley & Sons, Ltd.
Separating a Colour Texture from an Arbitrary Background

Partially supervised segmentation, that is, segmentation with always incomplete training data has many practical applications in image analysis and retrieval. This paper proposes a new algorithm for finding regions of a single texture in an arbitrary colour image. The texture is specified by a given training sample. The algorithm exploits colour space vector quantization, colour thresholding, and similarity between characteristic grey level cooccurrence histograms over a moving window around each pixel and over the whole training sample. Experiments show this algorithm effectively finds various homogeneous textures in complex backgrounds.
Wake-Up in a Hf0.5Zr0.5O2 Film: A Cycle-by-Cycle Emergence of the Remnant Polarization via the Domain Depinning and the Vanishing of the Anomalous Polarization Switching

The mechanism of the remnant polarization (Pr) growth during the first stage of ferroelectric HfO2-based memory cell operation (the wake-up effect) is still unclear. In this work, we reveal the microscopic nature of the Pr growth in functional ferroelectric capacitors based on a polycrystalline 10 nm thick (111) out-of-plane textured Hf0.5Zr0. 5O2 film during electric cycling. We observe the cycle-by-cycle evolution of the domain structure with the piezoresponse force microscopy (PFM). During the early stage of the wake-up, three types of domains are found: (i) normal domains (polarization aligned along the applied electric field), (ii) nonswitchable domains with upward and downward polarization, and (iii) domains with anomalous polarization switching (polarization aligned against the applied electric field) that are commonly surrounded by nonswitchable domains. Initially, nonswitchable and “anomalous” domains are 200–300 nm in width, and they occupy ∼70% of the capacitor area. During electric field cyclin.
The Piezoelectric PZT Thin Films Deposited on Metal Substrates

In this study, we deposited PZT thin films directly on various kinds of metal substrates by rf-magnetron sputtering, and measured their crystal structure, and ferroelectric and piezoelectric properties. We used metal substrates of austenitic stainless steel (ASS), ferritic stainless steel (FSS), Ti, Ni, Zr and W for the PZT deposition. From the x-ray diffraction (XRD) measurements, we confirmed the PZT thin film was directly grown on each substrate with a perovskite phase. The dielectric constant of the PZT thin films showed obvious dependence on the coefficient of thermal expansion (CTE) of substrates. This result suggests that the dielectric constant, which is one of the important parameters for the piezoelectric vibration energy harvesters (PVEHs), can be controlled by the CTE of the substrates. The PZT film deposited on the FSS showed the best piezoelectric coefficient e31,f of -2.4 [C/m2], which was comparable to that of the PZT film formed on the platinum-coated metal substrates.
Communication restriction in adults who stutter: Part II

ABSTRACT This article presents a follow-up study to Lee, van Dulm, Robb, and Ormond (2015). The aim was to explore communication restriction in adults with stuttering (AWS) using typical language measures and systemic functional linguistics (SFL) analyses. The article compared the pre- and post-treatment performance of AWS in language productivity and complexity, transitivity, modality, appraisal, and theme. Ten-minute conversational samples were obtained from 20 AWS before and after participation in intensive stuttering treatment. Transcripts were analysed for quantity and complexity of verbal output, and frequency of transitivity, modality, appraisal and theme resources. Between pre- and post-treatment, the following differences were observed: (1) a significant increase in frequency of modal operators, and trends approaching significance for (2) increased language complexity (3) increased language expressing appraisal. These changes suggest increased flexibility of language use in AWS following treatment, particularly towards interpersonal engagement. The value of SFL to this area of research is discussed.
Association between complete response and outcomes in transplant‐eligible myeloma patients in the era of novel agents

Achieving complete response (CR) has been linked to improved progression‐free (PFS) and overall (OS) survival in myeloma. A meta‐analysis was conducted to investigate whether this holds true in the era of novel agents (bortezomib, lenalidomide, thalidomide).
Sentiment Classification based on Piecewise Pooling Convolutional Neural Network

Recently, the effectiveness of neural networks, especially convolutional neural networks, has been validated in the field of natural language processing, in which, sentiment classification for online reviews is an important and challenging task. Existing convolutional neural networks extract important features of sentences without local features or the feature sequence. Thus, these models don’t perform well, especially for transition sentences. To this end, we propose a Piecewise Pooling Convolutional Neural Network (PPCNN) for sentiment classification. Firstly, with a sentence presented by word vectors, convolution operation is introduced to obtain the convolution feature map vectors. Secondly, these vectors are segmented according to the positions of transition words in sentences. Thirdly, the most significant feature of each local segment is extracted using max pooling mechanism, and then the different aspects of features can be extracted. Specifically, the relative sequence of these features is preserved. Finally, after processed by the dropout algorithm, the softmax classifier is trained for sentiment classification. Experimental results show that the proposed method PPCNN is effective and superior to other baseline methods, especially for datasets with transition sentences.
Increased Risk for Coeliac Disease in Paediatric Patients with Migraine

The aim was to determine the prevalence of coeliac disease (CD) in paediatric patients with migraine. Serum tissue transglutaminase IgA (tTGA) antibodies and IgA concentrations were measured in 73 patients with migraine (age range 6-17 years) and the control group (n = 147). Patients having positive tTGA antibodies underwent duedonal biopsy. Four patients (5.5%) from the study group and one (0.6%) from the control group had positive tTGA antibody titres (P < 0.05). Three patients with migraine had normal duedonal histology and were considered as potential CD. One patient from the study group and one from the control group declined to have biopsy. tTGA antibody is considered as a reliable indicator for the presence of CD. However, some patients with positive antibodies may have normal biopsy initially and are classified as having potential CD. Our finding of a higher prevalance of tTGA antibodies in paediatric migraine patients suggests that an association between migraine and CD might exist.
SolarCastalia: Solar Energy Harvesting Wireless Sensor Network Simulator

Most existing simulators for WSNs (wireless sensor networks) model battery-powered sensors and provide MAC and routing protocols designed for battery-powered WSNs. Recently, however, increasingly extensive studies of energy harvesting sensor systems require the development of appropriate simulators, but there are few related studies on such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy harvesting, rechargeable battery, and energy consuming models. Additionally, the new model must enable applications of the well-known MAC and routing protocols designed for energy harvesting WSNs and have a convenient user-friendly interface. In this work, we design and implement a user-friendly simulator for solar energy harvesting WSNs.
Fighting Web Spam

High ranking of a Web site in search engines can be directly correlated to high revenues. This amplifies the phenomenon of Web spamming which can be defined as preparing or manipulating any features of Web documents or hosts to mislead search engines’ ranking algorithms to gain an undeservedly high position in search results. Web spam remarkably deteriorates the information quality available on the Web and thus affects the whole Web community including search engines. The struggle between search engines and spammers is ongoing: both sides apply increasingly sophisticated techniques and counter-techniques against each other. In this paper, we first present a general background concerning the Web spam phenomenon. We then explain why the machine learning approach is so attractive for Web spam combating. Finally, we provide results of our experiments aiming at verification of certain open questions. We investigate the quality of data provided as the Web Spam Reference Corpus, widely used by the research community as a benchmark, and propose some improvements. We also try to address the question concerning parameter tuning for cost-sensitive classifiers and we delve into the possibility of using linguistic features for distinguishing spam from non-spam.
Medical emergency team involvement in patients hospitalized with acute myeloid leukemia

Abstract Patients with acute myeloid leukemia (AML) are at risk for sudden clinical deterioration. We aimed to describe the incidence of medical emergency team (MET) activation, intensive care unit (ICU) admissions and outcomes for patients with AML. We performed a 5-year retrospective cohort study of patients hospitalized with AML. One hundred and seventy patients were divided into three groups: (1) MET activated (n = 34); (2) MET criteria present but MET not activated (n = 17); and (3) all other patients with AML (n = 119). MET activation incidence was 200 calls/1000 admissions (95% confidence interval [CI], 138–279), compared with a hospital-wide rate of 29.3 calls/1000 admissions (95% CI, 28.2–30.4) (relative risk 6.90; 95% CI, 4.77–9.67, p < 0.0001). Some 77% (n = 26) were triaged to the ICU. Hospital mortality was higher in MET activated and MET fulfilled without activation groups compared with all others (27% vs. 12% vs. 7%, p = 0.007). Changes to goals of care were more common with MET activation. Patients with AML commonly receive MET activation. Approximately one in 10 fulfill MET criteria, however do not receive MET activation.