Miracle-dz/UniFAR-FTUs huggingface dataset:
Superfluids and superconductors: quantum mechanics on a macroscopic scale

Superfluidity or superconductivity – which is the preferred term if the fluid is made up of charged particles like electrons – is a fascinating phenomenon that allows us to observe a variety of quantum mechanical effects on the macroscopic scale. Besides being of tremendous interest in themselves and vehicles for developing key concepts and methods in theoretical physics, superfluids have found important applications in modern society. For instance, superconducting magnets are able to create strong enough magnetic fields for the magnetic resonance imaging technique (MRI) to be used for diagnostic purposes in medicine, for illuminating the structure of complicated molecules by nuclear magnetic resonance (NMR), and for confining plasmas in the context of fusion-reactor research. Superconducting magnets are also used for bending the paths of charged particles moving at speeds close to the speed of light into closed orbits in particle accelerators like the Large Hadron Collider (LHC) under construction at CERN.
Inflammatory Aetiology of Human Myometrial Activation Tested Using Directed Graphs

There are three main hypotheses for the activation of the human uterus at labour: functional progesterone withdrawal, inflammatory stimulation, and oxytocin receptor activation. To test these alternatives we have taken information and data from the literature to develop causal pathway models for the activation of human myometrium. The data provided quantitative RT-PCR results on key genes from samples taken before and during labour. Principal component analysis showed that pre-labour samples form a homogenous group compared to those during labour. We therefore modelled the alternative causal pathways in non-labouring samples using directed graphs and statistically compared the likelihood of the different models using structural equations and D-separation approaches. Using the computer program LISREL, inflammatory activation as a primary event was highly consistent with the data (p = 0.925), progesterone withdrawal, as a primary event, is plausible (p = 0.499), yet comparatively unlikely, oxytocin receptor mediated initiation is less compatible with the data (p = 0.091). DGraph, a software program that creates directed graphs, produced similar results (p = 0.684, p = 0.280, and p = 0.04, respectively). This outcome supports an inflammatory aetiology for human labour. Our results demonstrate the value of directed graphs in determining the likelihood of causal relationships in biology in situations where experiments are not possible.
Generative Embeddings based on Rician Mixtures - Application to Kernel-based Discriminative Classification of Magnetic Resonance Images

Most approaches to classifier learning for structured objects (such as images or sequences) are based on probabilistic generative models. On the other hand, state-of-the-art classifiers for vectorial data are learned discriminatively. In recent years, these two dual paradigms have been combined via the use of generative embeddings (of which the Fisher kernel is arguably the best known example); these embeddings are mappings from the object space into a fixed dimensional score space, induced by a generative model learned from data, on which a (maybe kernel-based) discriminative approach can then be used. This paper proposes a new semi-parametric approach to build generative embeddings for classification of magnetic resonance images (MRI). Based on the fact that MRI data is well described by Rice distributions, we propose to use Rician mixtures as the underlying generative model, based on which several different generative embeddings are built. These embeddings yield vectorial representations on which kernel-based support vector machines (SVM) can be trained for classification. Concerning the choice of kernel, we adopt the recently proposed nonextensive information theoretic kernels. The methodology proposed was tested on a challenging classification task, which consists in classifying MRI images as belonging to schizophrenic or non-schizophrenic human subjects. The classification is based on a set of regions of interest (ROIs) in each image, with the classifiers corresponding to each ROI being combined via boosting. The experimental results show that the proposed methodology outperforms the previous state-of-the-art methods on the same dataset.
Preserving privacy when preference searching in e-commerce

The idea of using user preferences to assist with information filtering and with providing the most "relevant" answers to queries has recently received some attention from the research community. This has resulted in the proposition of several frameworks for formulating preferences and their direct embedding into relational query languages. In this paper we discuss major exploitation issues and privacy concerns inherent in the basic paradigm used by these proposed approaches when used with e-businesses not implicitly trusted by the user. We then outline an alternative approach geared specifically towards using user preferences when interacting with e-businesses.
Effects of Early-Onset Artificial Strabismus on Pursuit Eye Movements and on Neuronal Responses in Area MT of Macaque Monkeys

In humans, esotropia of early onset is associated with a profound asymmetry in smooth pursuit eye movements. When viewing is monocular, targets are tracked well only when they are moving nasally with respect to the viewing eye. To determine whether this pursuit abnormality reflects an anomaly in cortical visual motion processing, we recorded eye movements and cortical neural responses in nonamblyopic monkeys made strabismic by surgery at the age of 10–60 d. Eye movement recordings revealed the same asymmetry in the monkeys’ pursuit eye movements as in humans with early-onset esotropia. With monocular viewing, pursuit was much stronger for nasalward motion than for temporalward motion, especially for targets presented in the nasal visual field. However, for targets presented during ongoing pursuit, temporalward and nasalward image motion was equally effective inmodulating eye movement. Single-unit recordings made from the same monkeys, under anesthesia, revealed that MT neurons were rarely driven binocularly, but otherwise had normal response properties. Most were directionally selective, and their direction preferences were uniformly distributed. Our neurophysiological and oculomotor measurements both suggest that the pursuit defect in these monkeys is not due to altered cortical visual motion processing. Rather, the asymmetry in pursuit may be a consequence of imbalances in the two eyes’ inputs to the “downstream” areas responsible for the initiation of pursuit.
Integration and evaluation of emotion in an articulatory speech synthesis system

We convey a tremendous amount of information vocally. In addition to the obvious exchange of semantic information, we unconsciously vary a number of acoustic properties of the speech wave to provide information about our emotions, thoughts, and intentions. [Cahn 1990] Advances in understanding of human physiology combined with increases in the computational power available in modern computers have made the simulation of the human vocal tract a realistic option for creating artificial speech. Such systems can, in principle, produce any sound that a human can make. Here we present two experiments examining the expression of emotion using prosody (i.e., speech melody) in human recordings and an articulatory speech synthesis system.
Synchronous dataflow scenarios

The Synchronous Dataflow (SDF) model of computation by Lee and Messerschmitt has become popular for modeling concurrent applications on a multiprocessor platform. It is used to obtain a guaranteed, predictable performance. The model, on the other hand, is quite restrictive in its expressivity, making it less applicable to many modern, more dynamic applications. A common technique to deal with dynamic behavior is to consider different scenarios in separation. This analysis is, however, currently limited mainly to sequential applications. In this article, we present a new analysis approach that allows analysis of synchronous dataflow models across different scenarios of operation. The dataflow graphs corresponding to the different scenarios can be completely different. Execution times, consumption and production rates and the structure of the SDF may change. Our technique allows to derive or prove worst-case performance guarantees of the resulting model and as such extends the model-driven approach to designing predictable systems to significantly more dynamic applications and platforms. The approach is illustrated with three MP3 and MPEG-4 related case studies.
Selecting Near-Optimal Learners via Incremental Data Allocation

We study a novel machine learning (ML) problem setting of sequentially allocating small subsets of training data amongst a large set of classifiers. The goal is to select a classifier that will give near-optimal accuracy when trained on all data, while also minimizing the cost of misallocated samples. This is motivated by large modern datasets and ML toolkits with many combinations of learning algorithms and hyper-parameters. Inspired by the principle of "optimism under uncertainty," we propose an innovative strategy, Data Allocation using Upper Bounds (DAUB), which robustly achieves these objectives across a variety of real-world datasets. We further develop substantial theoretical support for DAUB in an idealized setting where the expected accuracy of a classifier trained on $n$ samples can be known exactly. Under these conditions we establish a rigorous sub-linear bound on the regret of the approach (in terms of misallocated data), as well as a rigorous bound on suboptimality of the selected classifier. Our accuracy estimates using real-world datasets only entail mild violations of the theoretical scenario, suggesting that the practical behavior of DAUB is likely to approach the idealized behavior.
Interest-point Based Face Recognition from Range Images

We present a novel approach to interest-point detection tailored to range images. A range image is represented by two images with blob-like patterns that have easily detectable peaks and can be efficiently extracted using convolution kernels. These kernels were designed to produce repeatable and independent blob-like patterns when convolved with the range image. The interest-points correspond to peaks of the patterns after dropping the unstable ones and performing Non-Maximal Suppression (NMS) on their union. The approach was applied to facial range images from the FRGC V2.0 dataset and about 88% repeatability was achieved. Face recognition was also performed by matching the local range regions around the interest-points. An approach based on three levels of matching combined with RANSAC algorithm was used to increase the correct matches and reduce the false ones. Preliminary recognition results for a database of 466 subjects and 1765 probes were 96.33% identification rate and 90% verification rate at 0.1% False Accept Rate (FAR) for faces under neutral expression.
Reemergence of St. Louis Encephalitis Virus, California, 2015

St. Louis encephalitis virus infection was detected in summer 2015 in southern California after an 11-year absence, concomitant with an Arizona outbreak. Sequence comparisons showed close identity of California and Arizona isolates with 2005 Argentine isolates, suggesting introduction from South America and underscoring the value of continued arbovirus surveillance.
Cooperative TDOA estimation with trigger relay

In this paper, we investigate the relaying issue of Zero-Padding (ZP) Orthogonal Frequency Division Multiplexing (OFDM) technique to estimate Time Difference of Arrival (TDOA) for locationing applications. In order to benefit from the easy processing of Amplify-and-Forward (AF) relay as well as the noise and interference cancellation of Decode-and-Forward (DF) relay schemes, we introduce the trigger relay technique for TDOA estimation. The trigger relay possesses the merit of bandwidth efficiency, since only a short pilot or preamble needs to be sent. Compared to its counterparts AF and DF relays, trigger relay achieves a better performance in terms of system complexity and TDOA accuracy. Gaining from multipath diversity, the trigger relay TDOA resolution can be improved further.
Quantitative and qualitative assessment of left ventricular volume with ECG-gated multislice spiral CT: value of different image reconstruction algorithms in comparison to MRI

Purpose: To assess the value of different image reconstruction algorithms for assessment of the left ventricular function using retrospectively ECG-gated multislice spiral computed tomography (MSCT) of the heart. Material and Methods: MSCT and cine magnetic resonance (MR) imaging of the heart were performed in 15 patients. For MSCT, standard and multisegmental image reconstruction with improved temporal resolution were used. Standardized multiplanar reformats in the short axis and long axis views were reconstructed from MSCT data. End-systolic (ESV) and end-diastolic volume (EDV), stroke volume (SV), ejection fraction (EF) and myocardial mass (MM) were calculated. Left ventricular wall motion was assessed qualitatively. Results: MSCT was in acceptable agreement with MR imaging for quantification of the ventricular function. According to the Bland–Altman approach the mean differences for the left ventricular volumes (ESV, EDV, SV) ranged from −9.6 ml to 3.1 ml with standard image reconstruction and from −0.6 ml to 1.9 ml utilizing multisegmental image reconstruction with limits of agreement ranging from −26.6 ml to 12.5 ml and −15.6 ml to 15.0 ml, respectively. Applying the multisegmental image reconstruction algorithm, a significantly improved agreement with the MR data was found for EDV, SV and EF. For wall motion analysis, standard image reconstruction showed a significant difference to MR imaging with a correspondence in 83.75% of the 240 assessed segments, while multisegmental image reconstruction agreed with MR imaging in 92.5% of the segments. Conclusion: Multisegmental image reconstruction improves the quantitative assessment of left ventricular function when compared to standard image reconstruction. Multisegmental image reconstruction allows qualitative wall motion analysis.
PROOFS: a fast, memory-efficient sequential circuit fault simulator

The authors describe PROOFS, a fast fault simulator for synchronous sequential circuits, PROOFS achieves high performance by combining all the advantages of differential fault simulation, single fault propagation, and parallel fault simulation, while minimizing their individual disadvantages. The fault simulator minimizes the memory requirements, reduces the number of gate evaluations, and simplifies the complexity of the software implementation. PROOFS requires an average of one fifth the memory required for concurrent fault simulation and runs six to 67 times faster on the ISCAS-89 sequential benchmark circuits. >
A controlled experiment for the empirical evaluation of safety analysis techniques for safety-critical software

Context: Today's safety critical systems are increasingly reliant on software. Software becomes responsible for most of the critical functions of systems. Many different safety analysis techniques have been developed to identify hazards of systems. FTA and FMEA are most commonly used by safety analysts. Recently, STPA has been proposed with the goal to better cope with complex systems including software. Objective: This research aimed at comparing quantitatively these three safety analysis techniques with regard to their effectiveness, applicability, understandability, ease of use and efficiency in identifying software safety requirements at the system level. Method: We conducted a controlled experiment with 21 master and bachelor students applying these three techniques to three safety-critical systems: train door control, anti-lock braking and traffic collision and avoidance. Results: The results showed that there is no statistically significant difference between these techniques in terms of applicability, understandability and ease of use, but a significant difference in terms of effectiveness and efficiency is obtained. Conclusion: We conclude that STPA seems to be an effective method to identify software safety requirements at the system level. In particular, STPA addresses more different software safety requirements than the traditional techniques FTA and FMEA, but STPA needs more time to carry out by safety analysts with little or no prior experience.
A kinetic model for multidimensional opinion formation

In this paper, we deal with a kinetic model to describe the evolution of the opinion in a closed group with respect to a choice between multiple options, e.g. political parties, which takes into account two main mechanisms of opinion formation, namely the interaction between individuals and the eﬀect of the mass media. We provide an existence and uniqueness result for the model, and then we numerically test it in some relevant cases.
Self-calibrated quadrature generator for WLAN multistandard frequency synthesizer

A self-calibrated quadrature generator capable of generating local oscillator (LO) outputs for IEEE 802.11a-b is presented. The quadrature generator is embedded in a frequency synthesizer that generates reference frequencies at 2.4 and 5GHz. A new sequential calibration scheme maintains the quadrature at the 5-GHz output within a maximum phase error of 2/spl deg/, while a divide-by-two flip-flop generates the quadrature output at 2.4 GHz. The circuit is fabricated in a 0.25-/spl mu/m SiGe BiCMOS technology and occupies a silicon area of 2 mm/sup 2/; the quadrature generator consumes a current of 5 mA from a 2.5-V supply.
Role of EPS, Dispersant and Nutrients on the Microbial Response and MOS Formation in the Subarctic Northeast Atlantic

In this study we report the formation of marine oil snow (MOS), its associated microbial community, the factors influencing its formation, and the microbial response to crude oil in surface waters of the Faroe-Shetland Channel (FSC). The FSC is a subarctic region that is hydrodynamically complex located in the northeast Atlantic where oil extraction is currently occurring and where exploration is likely to expand into its deeper waters (>500 m). A major oil spill in this region may mirror the aftermath that ensued following the Deepwater Horizon (DWH) blowout in the Gulf of Mexico, where the massive influx of Macondo crude oil triggered the formation of copious quantities of rapidly sinking MOS and successional blooms of opportunistic oil-degrading bacteria. In laboratory experiments, we simulated environmental conditions in sea surface waters of the FSC using water collected from this site during the winter of 2015. We demonstrated that the presence of dispersant triggers the formation of MOS, and that nutrient amendments magnify this. Illumina MiSeq sequencing revealed the enrichment on MOS of associated oil-degrading (Cycloclasticus, Thalassolituus, Marinobacter) and EPS-producing (Halomonas, Pseudoalteromonas, Alteromonas) bacteria, and included major representation by Psychrobacter and Cobetia with putative oil-degrading/EPS-producing qualities. The formation of marine snow, in the absence of crude oil and dispersant, in seawater amended with nutrients alone indicated that the de novo synthesis of bacterial EPS is a key factor in MOS formation, and the glycoprotein composition of the MOS aggregates confirmed that its amorphous biopolymeric matrix was of microbial (likely bacterial) origin. The presence of dispersants and crude oil with/without nutrients resulted in distinct microbial responses marked by intermittent, and in some cases short-lived, blooms of opportunistic heterotrophs, principally obligate hydrocarbonoclastic (Alcanivorax, Cycloclasticus, Thalassolituus, Marinobacter) and EPS-producing (Halomonas, Alteromonas, Pseudoalteromonas) bacteria. Interestingly, members of the Vibrionales (principally the genus Vibrio) were strongly enriched by crude oil (with/without dispersant or nutrients), highlighting a putative importance for these organisms in crude oil biodegradation in the FSC. Our findings mirror those observed at DWH and hence underscore their broad relevance.
BUT-TYPED: Using domain knowledge for computing typed similarity

This paper deals with knowledge-based text processing which aims at an intuitive notion of textual similarity. Entities and relations relevant for a particular domain are identiﬁed and disambiguated by means of semi-supervised machine learning techniques and resulting annotations are applied for computing typed-similarity of individual texts. The work described in this paper particularly shows effects of the mentioned processes in the context of the *SEM 2013 pilot task on typed-similarity, a part of the Semantic Textual Similarity shared task. The goal is to evaluate the degree of semantic similarity be-tween semi-structured records. As the evaluation dataset has been taken from Europeana – a collection of records on European cultural heritage objects – we focus on computing a semantic distance on ﬁeld author which has the highest potential to beneﬁt from the domain knowledge. Speciﬁc features that are employed in our sys-tem BUT-TYPED are brieﬂy introduced together with a discussion on their efﬁcient acquisition. Support Vector Regression is then used to combine the features and to provide a ﬁnal similarity score. The system ranked third on the attribute author among 15 submitted runs in the typed-similarity task.
Solution of the vacuum Einstein equations in Synthetic Differential Geometry of Kock-Lawvere

The topos theory is a theory which is used for deciding a number of problems of theory of relativity, gravitation and quantum physics. It is known that topos-theoretic geometry can be successfully developed within the framework of Synthetic Differential Geometry of Kock-Lawvere (SDG), the models of which are serving the toposes, i.e. categories possessing many characteristics of traditional Theory of Sets. In the article by using ideas SDG, non-classical spherically symmetric solution of the vacuum Einstein equations is given.
US-guided percutaneous laser ablation of refractory metastatic retroperitoneal lesions

Rationale: Retroperitoneal metastatic lymph node is rare but severe, which has important structures like the gastrointestinal tract and large blood vessels around and may challenge excision, inducing serious complications like hemorrhage, intestinal adhesion, and even death after injury. Patient concerns: We described the case of a 60-year-old man with a history of right liver resection in 2010, pulmonary wedge resection in 2012, and transarterial chemoembolization twice in 2014, in which the postoperative pathology suggested the mixed liver cancer, and poorly differentiated lung cancer from liver metastasis. Diagnoses: Preoperative magnetic resonance (MR) imaging scan showed a refractory retroperitoneal metastatic lymph node. Interventions: Then this patient repeatedly received 4 ablations with US-guided laser ablation within a month. Outcomes: After 4 ablations due to residual tumor, MR, and CT images of 5-month follow-up showed the partial response. No obvious side effects were discovered in this case during these procedures. Lessons: This suggested US-guided laser ablation appears to be a useful technique for retroperitoneal metastatic lymph node with poor general condition or those refusing surgical therapy.