Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing word prosody—behavioral and neuroimaging evidence for heterogeneous performance in a language with variable stress

In the present behavioral and fMRI study, we investigated for the first time interindividual variability in word stress processing in a language with variable stress position (German) in order to identify behavioral predictors and neural correlates underlying these differences. It has been argued that speakers of languages with variable stress should perform relatively well in tasks tapping into the representation and processing of word stress, given that this is a relevant feature of their language. Nevertheless, in previous studies on word stress processing large degrees of interindividual variability have been observed but were ignored or left unexplained. Twenty-five native speakers of German performed a sequence recall task using both segmental and suprasegmental stimuli. In general, the suprasegmental condition activated a subcortico-cortico-cerebellar network including, amongst others, bilateral inferior frontal gyrus, insula, precuneus, cerebellum, the basal ganglia, pre-SMA and SMA, which has been suggested to be dedicated to the processing of temporal aspects of speech. However, substantial interindividual differences were observed. In particular, main effects of group were observed in the left middle temporal gyrus (below vs. above average performance in stress processing) and in the left precuneus (above vs. below average). Moreover, condition (segmental vs. suprasegmental) and group (above vs. below average) interacted in the right hippocampus and cerebellum. At the behavioral level, differences in word stress processing could be partly explained by individual performance in basic auditory perception including duration discrimination and by working memory performance (WM). We conclude that even in a language with variable stress, interindividual differences in behavioral performance and in the neuro-cognitive foundations of stress processing can be observed which may partly be traced back to individual basic auditory processing and WM performance.
Application of Bayesian Inference to Operational Risk Management

Bayesian inference that is able to combine statistical measurement approach and scenario analysis is effective exceedingly for measuring operational risk. In choosing the prior distribution, taking indicators that may be predictive of the risk of future losses, external circumstance and so forth into consideration makes it possible to obtain more realistic risk amount, this process itself is an important for enhancing operational risk management. This paper proposes the examples of application of Bayesian inference to banking
A Gene Expression Signature of Invasive Potential in Metastatic Melanoma Cells

Background We are investigating the molecular basis of melanoma by defining genomic characteristics that correlate with tumour phenotype in a novel panel of metastatic melanoma cell lines. The aim of this study is to identify new prognostic markers and therapeutic targets that might aid clinical cancer diagnosis and management. Principal Findings Global transcript profiling identified a signature featuring decreased expression of developmental and lineage specification genes including MITF, EDNRB, DCT, and TYR, and increased expression of genes involved in interaction with the extracellular environment, such as PLAUR, VCAN, and HIF1a. Migration assays showed that the gene signature correlated with the invasive potential of the cell lines, and external validation by using publicly available data indicated that tumours with the invasive gene signature were less melanocytic and may be more aggressive. The invasion signature could be detected in both primary and metastatic tumours suggesting that gene expression conferring increased invasive potential in melanoma may occur independently of tumour stage. Conclusions Our data supports the hypothesis that differential developmental gene expression may drive invasive potential in metastatic melanoma, and that melanoma heterogeneity may be explained by the differing capacity of melanoma cells to both withstand decreased expression of lineage specification genes and to respond to the tumour microenvironment. The invasion signature may provide new possibilities for predicting which primary tumours are more likely to metastasize, and which metastatic tumours might show a more aggressive clinical course.
R&D networks: an evaluation framework

R&D networks have been studied and promoted by scholars and policy makers as a way to increase the performance of innovation systems. At the same time, limited attention has been devoted to evaluate their performances. This paper reviews the literature that studied R&D networks from different approaches and suggests a framework to help developing evaluation systems for R&D networks. The framework is based on a network model that highlights the main elements and characteristics of an R&D network, underlines the opportunity of three different perspectives of evaluation and has been applied and tested on three case studies.
An adaptive time-stepping semi-Lagrangian method for incompressible flows

Abstract The semi-Lagrangian method is widely applied to solving the advection term of the Navier–Stokes (N–S) equations whereas the role of time step is often unclear. This article proposed an adaptive time-stepping method, which first calculates local adaptive time step based on truncation error coefficient functions, and then to obtain global time step based on an averaging function for all grid points. The new method was tested for solving 1-D and 2-D advections with different initial time steps and grid resolutions, and the transient incompressible N–S equations. Better simulation accuracy can be achieved than the cases with constant time steps.
Quantifying user experience in using learning gamification website

User experience is all about the user (which is why personas are important) because it deals with our users’ needs such as learn programming languages course. Currently, all new students always suffering to learn programming languages course in computer science departments. The preliminary investigation has showed that students have experienced ineffective learning, lack of interest towards this course and lack of motivation. In order to encourage user to interact with a learning website, adding game elements such as a challenge. Gamification has to be implemented well and has to be adequate for good user experiences. Previous studies have shown that applying Gamification elements in websites engages users. Gamification refers to the use of game elements in a non-game context to increase engagement between human and computer. Gamification Website was designed based on the gamification framework that has been constructed. This paper is discussing on quantifying user experience in term of usability and motivation in using the learning gamification website. The result of evaluation have shown that the gamification website has good (mean > 4.00) for all usability elements. On the other hand has a positive motivation in students’ performance. Finally, the finding of evaluation suggested that gamification website can be used as a motivation tool to promote students learning programming language subject.
High Optical Properties and Rectifying Behavior of ZnO (Nano and Microstructures)/Si Heterostructures

— We investigated a modified thermal evaporation method in the growth process of ZnO nanowires. ZnO nanowires were fabricated on p-type silicon substrates without using a metal catalyst. A simple horizontal double-tube system along with chemical vapor diffusion of the precursor was used to grow the ZnO nanowires. The substrates were placed in different temperature zones, and ZnO nanowires with different diameters were obtained for the different substrate temperatures. In addition to the nanowires, ZnO microdiscs with different diameters were obtained on another substrate, which was placed at a lower temperature than the other substrates. The optical properties and crystalline quality of the ZnO nanowires and microdiscs were characterized by room temperature photoluminescence (PL) and Raman spectrometers. The PL and Raman studies demonstrated that the ZnO nanowires and microdiscs grown using such set-up had good crystallinity with excellent optical properties. Rectifying behavior of ZnO/Si heterostructures was characterized by a simple DC circuit.
Evolving Amorphous Robots

Research in evolutionary robotics has traditionally been limited to morphologies comprising rigid and discrete components, such as links connected with rotational or linear joints and actuators. Here, we demonstrate the evolution of robots with continuous and amorphous morphologies composed of multiple materials. Actuation is accomplished by periodic volumetric expansion and contraction of one or more of these materials. The challenges of representing evolvable multi-material freeform shapes and evaluation (simulation) of the resulting soft bodies are discussed. Several genotypic representations are explored which use a level-set threshold to generate the material distribution in the phenotype. Soft body simulation of the robot is accomplished using a relaxation algorithm to model the dynamics of the resulting amorphous machines under the actuation material expansion, gravity forces, and non-linear ground friction. These results open the door to a new design space that more closely mimics the freeform, amorphous and continuous nature of biological systems.
Framework of Group Decision Making With Intuitionistic Fuzzy Preference Information

Group decision making is an essential activity in various fields of operations research and management science. This paper focuses on the intuitionistic fuzzy group decision making problem in which all the experts use the intuitionistic fuzzy preference relations (IFPRs) to express their preferences. To start our discussion, we first propose the novel framework of intuitionistic fuzzy group decision making and clarify the difficulties in deriving the final result which is accepted by all individuals in the group. Next, a consistency checking method, which is based on the multiplicative consistency, is developed to check the consistency of each IFPR furnished by the group of experts. For those IFPRs that do not have the acceptable consistency, an iterative procedure is proposed to improve the consistency. Furthermore, after introducing a novel consensus measure, an interesting consensus-reaching procedure is developed to help the group to find a solution which is accepted by most members in the group. Finally, in order to make our approaches more applicable, a step-by-step algorithm is given. A numerical example concerning the selection of outstanding Ph.D. students for the China Scholarship Council is given to illustrate and validate the proposed approaches.
Analysis of the relationships between oxidative stress, DNA damage and sperm vitality in a patient population: development of diagnostic criteria.

BACKGROUND DNA damage in human spermatozoa is known to be associated with a variety of adverse clinical outcomes affecting both reproductive efficiency and the health and wellbeing of the offspring. However, the origin of this damage, its biochemical nature and strategies for its amelioration, still await resolution. METHODS Using novel methods to simultaneously assess DNA fragmentation (modified TUNEL assay), DNA-base adduct formation (8-hydroxy-2'-deoxyguanosine [8OHdG]) and cell vitality, spermatozoa from a cohort of 50 assisted conception patients were examined and compared with a group of donors. Receiver operating characteristic (ROC) curve analysis was then used to examine the frequency distribution of the data and to determine optimized thresholds for identifying patients exhibiting abnormally high levels of DNA damage. RESULTS 8OHdG formation and DNA fragmentation were highly correlated with each other and frequently associated with cell death. Percoll centrifugation improved sperm quality but, unexpectedly, increased 8OHdG formation in live cells, as did sperm fractionation using Puresperm gradients. ROC analysis indicated that the frequency distribution of 8OHdG and DNA fragmentation data were significantly different between patients and donors (P < 0.001), permitting the development of thresholds that would allow the accurate diagnosis of DNA damage in the male germ line. CONCLUSION The aetiology of DNA damage in spermatozoa involves a cascade of changes that progress from the induction of oxidative stress and oxidized DNA base adduct formation to DNA fragmentation and cell death. Preparation of spermatozoa on discontinuous density gradients aggravates the problem by stimulating the formation of 8OHdG in live cells. However, the development of novel methods and optimized thresholds for diagnosing oxidative DNA damage in human spermatozoa should assist in the clinical management of this pathology.
Backward adaptive transform coding of vectorial signals: A comparison between unitary and causal approaches

In a transform coding framework we compare the optimal unitary approach (Karhunen-Loeve Transform, KLT) to the optimal causal approach (LDU, Lower Diagonal-Upper). In absence of perturbations, both transforms have recently been shown to yield the same coding gain [2, 4]. The purpose of this paper is to compare the behavior of these two transformations when the ideal transform coding scheme gets perturbed, that is, when only a perturbed value Rxx + ΔR of Rxx is known at the encoder. In a real backward adaptive scheme, ΔR is due to two noise sources: estimation noise (finite set of available data at the encoder) and quantization noise (quantized data at the decoder) Furthermore, not only the transformation itself gets perturbed, but also the bit assignment. Theoretical expressions for the coding gains in both unitary and causal approaches are derived. Simulation results confirming the predicted behavior of the coding gains with perturbations are reported. This work is a follow-up of [1], where the influences of quantization and estimation noises were analyzed separately.
Formal models of visual perception based on cortical architectures

The objective of this thesis is to develop mathematical models of visual perception based on cortical architectures and to apply them to reproduce phenomenological experiments and to process natural images. We primarly focus on low level vision tasks and in particular we are interested in the problem of grouping and of individuation of perceptual units. In this setting we will face the problem of the reconstruction of illusory figures and the detection of retinal vessels in optical images. Then we consider the problem of encoding and decoding of the fMRI signal from in vivo acquired brain activity of visual cortex. This allows to estimate the structure of the cortex of a specific human patient and eventually to reconstruct the visual stimulus from fMRI activity, in a so called “brain reading” strategy. The difference between our approach and the state of the art literature consists in using previously defined neuromathematical models of the cortices as a-priori knowledge to regularise in vivo estimated structure. Even if it is a long term objective, we propose a first approach to improve the results in this field. The entire work of this thesis has been developed taking into account results from phenomenology of perception and results of neurophysiology.In the field of the phenomenology of perception, at the beginning of the last century, the theory of the Gestalt psychology [Wertheimer, 1938, Kohler, 1947, Kofka, 1935] defined the integration of contours and in particular they defined grouping laws underlying perception. These are crucial in the construction of visual objects: points with characteristics in common can be grouped together to form a new visual object. Many psychophysical experiments have been proposed to measure the quantitative parameters of these laws. A particular interest of this thesis is the concept of association fields introduced by Field et al. [1993] which encodes different Gestalt principles (as good continuation, proximity). They showed that stimulus co-linearity and co-circularity play an important role for the feature of grouping. Their study showed how chances of perceiving the curvilinear path were high if the orientation of its features was the one tangent at that point and collapsed as their relative orientation deviated from being tangent.
Improved ant colony optimization algorithm and its application to solve pipe routing design

Purpose As a kind of NP-hard combinatorial optimization problem, pipe routing design (PRD) is applied widely in modern industries. In the offshore oil and gas industry, a semi-submersible production platform is an important equipment for oil exploitation and production. PRD is one of the most key parts of the design of semi-submersible platform. This study aims to present an improved ant colony algorithm (IACO) to address PRD for the oil and gas treatment system when designing a semi-submersible production platform. Design/methodology/approach First, to simplify PRD problem, a novel mathematical model is built according to real constraints and rules. Then, IACO, which combines modified heuristic function, mutation mechanism and dynamical parameter mechanism, is introduced. Findings Based on a set of specific instances, experiments are carried out, and the experimental results show that the performance of IACO is better than that of two variants of ACO, especially in terms of the convergence speed and swarm diversity. Finally, IACO is used to solve PRD for the oil and gas treatment system of semi-submersible production platform. The simulation results, which include nine pipe paths, demonstrate the practicality and high-efficiency of IACO. Originality/value The main contribution of this study is the development of method for solving PRD of a semi-submersible production platform based on the novel mathematical model and the proposed IACO.
Clinical features of measles according to age in a measles epidemic

The purpose of this study was to retrospectively investigate the relationship between age and clinical manifestations and laboratory findings in patients with measles. The study included 216 patients admitted to a hospital in Daejeon, 1 of the largest cities in South Korea, during the 2000–2001 measles outbreak: very young children (<2 y old; 159 patients), school age children (9–11 y old; 34 patients), and young adults (>16 y old; 23 patients). Few of the very young children (9%), but most of the older children (86%) had a history of a prior measles-mumps-rubella vaccination. There were no statistical differences between the 3 groups in terms of the total duration of fever, length of hospitalization, occurrence of complications (defined as hospitalization for more than 7 d) or anti-measles IgM positivity. A reduction in the number of white blood cells and lymphocytes was observed in all age groups. The levels of C-reactive protein were not different between very young children and older children, but hepatic involvement was more prevalent in young adults. In conclusion, the clinical course including the complications experienced was similar in all the measles patients regardless of age.
Histogram Specification: A Fast and Flexible Method to Process Digital Images

Histogram specification has been successfully used in digital image processing over the years. Mainly used as an image enhancement technique, methods such as histogram equalization (HE) can yield good contrast with almost no effort in terms of inputs to the algorithm or the computational time required. More elaborate histograms can take on problems faced by HE at the expense of having to define the final histograms in innovative ways that may require some extra processing time but are nevertheless fast enough to be considered for real-time applications. This paper proposes a new technique for specifying a histogram to enhance the image contrast. To further evidence our faith on histogram specification techniques, we also discuss methods to modify images, e.g., to help segmentation approaches. Thus, as advocates of these techniques, we would like to emphasize the flexibility of this image processing approach to do more than enhancing images.
Attitude Recognition Using Multi-resolution Cochleagram Features

Attitudes play an important role in human communication. Models and algorithms for automatic recognition of attitudes therefore may have applications in areas where successful communication and interaction are crucial, such as health-care, education and digital entertainment. This paper focuses on the task of categorizing speaker attitudes using speech features. Data extracted from video recordings are employed in training and testing of predictive models consisting of different sets of speech features. A novel attitude recognition approach using Multi-Resolution Cochleagram (MRCG) features is proposed. The results show that MRCG feature set outperforms the feature sets most commonly used in computational paralinguistic tasks, including emobase, eGeMAPS and ComParE, in terms of attitude recognition accuracy for decision tree, 1-nearest neighbour and random forest classifiers. Analysis of the results suggests that MRCG features contribute information not captured by these existing feature sets. Indeed, while the ComParE feature set provides slightly better results than MRCG features for support vector machine classifiers, the fusion of the existing feature sets with the new MRCG features improves on those results. Overall, with the addition of MRCG, the attitude recognition method proposed in this study achieves accuracy scores approximately 11 points higher than reported in previous studies.
A Practical Relativistic Model for Microarcsecond Astrometry in Space

We develop a practical model for relativistic reduction of positional observations with an accuracy of 1 μas, which is expected to be attained in future space astrometry missions. All relativistic effects that are caused by the gravitational field of the solar system and are of practical importance for this accuracy level are thoroughly calculated and discussed. The model includes relativistic modeling of the motion of the observer and modeling of relativistic aberration and gravitational light deflection, as well as a relativistic treatment of parallax and proper motion suitable for the accuracy of 1 μas. The model is formulated both for remote sources (stars, quasars, etc.) and for solar system objects (asteroids, etc.). The suggested model is formulated within the framework of the parameterized post-Newtonian formalism, with parameters β and γ. However, for general relativity (β = γ = 1) the model is fully compatible with the year 2000 IAU resolutions on relativity in celestial mechanics, astrometry, and metrology. The model is presented in a form suitable for implementation in a software system for data processing or simulation. The changes that should be applied to the model to attain an accuracy of 0.1 μas are reviewed. Potentially important relativistic effects caused by additional gravitational fields that are generated outside of the solar system are also briefly discussed.