Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Inverse Control under (h,ø)-Entropy Criterion

Recent research suggested that the error entropy (EE) criteria could be used to achieve a better error distribution in estimation, adaptation and learning. In this paper, we formulated the adaptive inverse control under a generalized error entropy criterion, i.e. (h, ø)-entropy criterion, and derived the associated error-entropy minimization algorithm. Several detailed schemes of adaptive filtering and inverse control under (h, ø)-entropy criterion were also presented. Finally, a simple simulation example has illustrated the effectiveness and advantages of this new method.
Real time obstacle detection and navigation planning for a humanoid robot in an indoor environment

This paper describes a stereo vision guided humanoid that can perform real time obstacle detection, path analysis and navigation planning on a carpet floor. The real time obstacle detection algorithm uses the two dimensional disparity gradients approach to detect the obstacle on the floor without constructing the floor plane and affine adjustment even though the baseline of the camera system is not parallel with the floor. The size of the obstacle that can be detected is as small as 30 mm in diameter. The navigation planning is performed by using a distance transform method in which a shortest path is found and then the number of footsteps required to reach the destination is calculated.
Hoxb1 neural crest preferentially form glia of the PNS

The vertebrate cranial neural crest cells give rise to many complex derivatives of the head, neck, and face, including neuronal and glial cells that act in concert for proper development of the anterior–peripheral nervous system. Several genes have been implicated in the processes of neural crest specification, migration, and differentiation; among these are the hox gene clusters. To determine the fates of hox‐expressing cranial neural crest, we describe the results of a genetic lineage analysis by using the Cre/loxP system to drive the activation of different ROSA26 reporter alleles under the regulation of the hoxb1 locus. By targeting the 3′ untranslated region of the hoxb1 gene, we have preserved endogenous gene activity and have been able to accurately follow the fates of the cells derived from the hoxb1 expression domain. Emphasis was placed on identifying the cell and tissue types that arise from the rhombomere 4‐derived neural crest. Our results demonstrate that, in addition to forming much of the cartilage, bones, and muscle of the ears and neck, a significant population of rhombomere 4‐derived neural crest is fated to generate the glial component of the seventh cranial nerve. Developmental Dynamics 227:379–386, 2003. © 2003 Wiley‐Liss, Inc.
Agile Language Engineering

Language engineering is software engineering concerned with computer languages. In this paper, we apply agile principles for software engineering to language engineering, analyse the technological premises and work out the methodical implications. The result is an agile language engineering process that is geared to ever changing requirements and fosters higher language quality, software quality, and developer productivity. It provides short iteration cycles, intensive user integration, control over frequent changes, and continuous delivery of valuable language tools. We investigate, how well-known techniques and tools from language and software engineering can be instrumented in this process. As discussed in the paper, agile language engineering is particular useful for the development of domain-specific languages.
Detection of Masses in Digital Mammogram Using Second Order Statistics and Artificial Neural Network

When researchers are studying the detection of breast tumors, there has been great attention to the modern textural features analysis of breast tissues on mammograms. Detecting of masses in digital mammogram based on second order statistics has not been investigated in depth. During this study, the breast cancer detection was based on second order statistics. The extraction of the textural features of the segmented region of interest (ROI) is done by using gray level co-occurrence matrices (GLCM) which is extracted from four spatial orientations; horizontal, left diagonal, vertical and right diagonal corresponding to (0 o , 45 o , 90 o and 135 o ) and two pixel distance for three different block size windows (8x8, 16x16 and 32x32) . The results show that the GLCM at 0 o , 45 o , 90 o and 135 o with a window size of 8X8 produces informative features to classify between masses and non-masses. Our method was able to achieve an accuracy of 91.67% sensitivity and 84.17% specificity which is comparable to what has been reported using the state-of-the-art Computer-Aided Detection system.
A demonstration of BIM-enabled quantitative circulation analysis using BERA language

This paper describes a BIM-enabled spatial analysis approach that enables us to compute specific quantitative data using BERA (Building Environment Rule and Analysis) Language and its tool. By comparing design alternatives for an actual building model, this paper also demonstrates building circulation and its associated properties of numeric data. The conventional software-driven approaches have intrinsic limitations that include limited interfaces, restricted parameters, closed rules except pre-defined rules, etc. A script language-based approach, however, is strongly necessary for various and flexible design review tasks especially for retrieving and computing specific dataset. This paper specifically demonstrates actual design review tasks as follows: 1) comparison and visualization of the differences between design alternatives in terms of their different spatial allocations; 2) analyzing numeric data result, NDBC (Numeric Data of Building Circulation), for evaluation of building circulation factors in each department of building; and as a result, 3) overall quantitative analysis and its result will be reported on given actual BIM models in order to support design decision making among various spatial allocation scenarios. For the actual demonstration presented in this paper, we modified some part of BERA language applications and defined appropriate BERA program code and Java code that are executable on given BIM models.
Modeling and estimation of networked control systems with time delays based on CTHMM

Network-induced delays in a networked control system (NCS) are stochastic continuous variables that depend on the current network state, which, as an abstract and hidden variable, can not be well defined but can be perceived by the observation of the packet-delay process. We model the network in an NCS as a hidden Markov chain and the network delay as stochastic variable whose probability density function depends on the Markov chain state (i.e. network state). Thus, the network state estimation is a continuous-time hidden Markov model (CTHMM) estimation problem. To derive the CTHMM of the NCS under study, we propose the Expectation Maximization (EM) algorithm to learn the parameters of the CTHMM based on the packet delay observations. The derived CTHMM make it possible in the future for us to predict the next network state and then choose a proper one from several control laws, which have been designed in advance to guarantee the performance of the NCS.
Effects of Motion on Infants' Negativity Bias in Emotion Perception

The negativity bias is a phenomenon that is characterized by infants being more influenced by, attending more to, and responding to more negative emotion information from the environment than positive emotion information. This study used a Tobii© T60 eye-tracking system to examine differences in 8to 12-month-old infants’ latencies to disengage from a centrallypresented face for three different emotion conditions-happy, sad, and fear. The events also varied by motion type-static versus dynamic. Additionally, infants’ locomotor experience and parental affect served as two additional measures of experience, and assessed for their contributions to the infants’ negativity bias. It was expected that infants would show longer latencies to disengage from the negative emotion events (fear or sad) compared to the positive emotion event (happy), but also that the latencies would be augmented by event type (dynamic > static), locomotion experience (high > low), and parental affect (higher negativity > lower negativity). Although infants showed more attention to dynamic than static emotion displays (especially on the speaker’s mouth), and more attention to happy and sad compared to fear displays, no consistent effect of emotion type was found on infants’ attention disengagement. Thus, no evidence for a negativity bias was seen. The results are interpreted with respect to possible contributions of the bimodal nature of emotion expression in the current study as well as age-related attentional differences in responding to a wide range of emotion cues.
Highly comparative fetal heart rate analysis

A database of fetal heart rate (FHR) time series measured from 7 221 patients during labor is analyzed with the aim of learning the types of features of these recordings that are informative of low cord pH. Our `highly comparative' analysis involves extracting over 9 000 time-series analysis features from each FHR time series, including measures of autocorrelation, entropy, distribution, and various model fits. This diverse collection of features was developed in previous work [1]. We describe five features that most accurately classify a balanced training set of 59 `low pH' and 59 `normal pH' FHR recordings. We then describe five of the features with the strongest linear correlation to cord pH across the full dataset of FHR time series. The features identified in this work may be used as part of a system for guiding intervention during labor in future. This work successfully demonstrates the utility of comparing across a large, interdisciplinary literature on time-series analysis to automatically contribute new scientific results for specific biomedical signal processing challenges.
Using statistics to model the vowel spaceMatthew

In much experimental phonetics the concept of a vowel space is discussed. The density of points within this vowel space can be modelled using a mixture gaussian density function. There are a number of advantages in modelling the vowel space in this way. The model can generalise, producing a smooth representation of sometimes noisy data. The model can be used to normalise vowel spaces produced by diierent speakers. It can be used to categorise diierent vowels. It can be used to categorise and compare diierent types of speech, such as citation speech against running speech. To further improve the model a parametric curve tting technique is applied. This paper describes the technique in detail, reports some tentative results and nally discusses the use of the model as a normalisation technique and as a method for measuring care of articulation.
A comparison of the lower stratospheric age spectra derived from a general circulation model and two data assimilation systems

[1] We use kinematic and diabatic back trajectory calculations, driven by winds from a general circulation model (GCM) and two different data assimilation systems (DAS), to compute the age spectrum at three latitudes in the lower stratosphere. The age spectra are compared to chemical transport model (CTM) calculations, and the mean ages from all of these studies are compared to observations. The age spectra computed using the GCM winds show a reasonably isolated tropics, in good agreement with observations; however, the age spectra determined from the DAS differ from the GCM spectra. For the DAS diabatic trajectory calculations there is too much exchange between the tropics and midlatitudes. The age spectrum is thus too broad, and the tropical mean age is too old as a result of mixing older midlatitude air with tropical air. Likewise, the midlatitude mean age is too young because of the in-mixing of tropical air. The DAS kinematic trajectory calculations show excessive vertical dispersion of parcels in addition to excessive exchange between the tropics and midlatitudes. Because air is moved rapidly to the troposphere from the vertical dispersion, the age spectrum is shifted toward the young side. The excessive vertical and meridional dispersion compensate in the kinematic case, giving a reasonable tropical mean age. The CTM calculation of the age spectrum using the DAS winds shows the same vertical and meridional dispersive characteristics of the kinematic trajectory calculation. These results suggest that the current DAS products will not give realistic trace gas distributions for long integrations; they also help explain why the extratropical mean ages determined in a number of previous DAS-driven CTMs are too young compared with observations. Finally, we note that trajectory-generated age spectra show significant age anomalies correlated with the seasonal cycles. These anomalies can be linked to year-to-year variations in the tropical heating rate. The anomalies are suppressed in the CTM spectra, suggesting that the CTM transport scheme is too diffusive.
Neurology out-patients with symptoms unexplained by disease: illness beliefs and financial benefits predict 1-year outcome

Background Patients whose symptoms are ‘unexplained by disease’ often have a poor symptomatic outcome after specialist consultation, but we know little about which patient factors predict this. We therefore aimed to determine predictors of poor subjective outcome for new neurology out-patients with symptoms unexplained by disease 1 year after the initial consultation. Method The Scottish Neurological Symptom Study was a 1-year prospective cohort study of patients referred to secondary care National Health Service neurology clinics in Scotland (UK). Patients were included if the neurologist rated their symptoms as ‘not at all’ or only ‘somewhat explained’ by organic disease. Patient-rated change in health was rated on a five-point Clinical Global Improvement (CGI) scale (‘much better’ to ‘much worse’) 1 year later. Results The 12-month outcome data were available on 716 of 1144 patients (63%). Poor outcome on the CGI (‘unchanged’, ‘worse’ or ‘much worse’) was reported by 482 (67%) out of 716 patients. The only strong independent baseline predictors were patients' beliefs [expectation of non-recovery (odds ratio [OR] 2.04, 95% confidence interval [CI] 1.40–2.96), non-attribution of symptoms to psychological factors (OR 2.22, 95% CI 1.51–3.26)] and the receipt of illness-related financial benefits (OR 2.30, 95% CI 1.37–3.86). Together, these factors predicted 13% of the variance in outcome. Conclusions Of the patients, two-thirds had a poor outcome at 1 year. Illness beliefs and financial benefits are more useful in predicting poor outcome than the number of symptoms, disability and distress.
STATIC ENVIRONMENT RECOGNITION USING OMNI-CAMERA FROM A MOVING VEHICLE

Discussed is research to develop a sensor system capable of recognizing city area environments from a moving vehicle. A cluttered city area outdoor man-made environment requires different recognition methods from indoor or highway environments. An omni-directional camera and vehicle odometry were developed for better recognition in the total sensing system to estimate geometrical information that was fed back to image processing. This paper provides the first progress report for the research by explaining the study's approach of using omni-camera on a vehicle and setup of a platform. Also shown is an experimental result of two dimensional static environment recognition from a moving vehicle.
Phytoplankton dynamics in contrasting early stage North Atlantic spring blooms: composition, succession, and potential drivers

Abstract. The spring bloom is a key annual event in the phenology of pelagic ecosystems, making a major contribution to the oceanic biological carbon pump through the production and export of organic carbon. However, there is little consensus as to the main drivers of spring bloom formation, exacerbated by a lack of in situ observations of the phytoplankton community composition and its evolution during this critical period. We investigated the dynamics of the phytoplankton community structure at two contrasting sites in the Iceland and Norwegian basins during the early stage (25 March–25 April) of the 2012 North Atlantic spring bloom. The plankton composition and characteristics of the initial stages of the bloom were markedly different between the two basins. The Iceland Basin (ICB) appeared well mixed down to >400 m, yet surface chlorophyll a (0.27–2.2 mg m−3) and primary production (0.06–0.66 mmol C m−3 d−1) were elevated in the upper 100 m. Although the Norwegian Basin (NWB) had a persistently shallower mixed layer ( Diatoms dominated the ICB, with the genus Chaetoceros (1–166 cells mL−1) being succeeded by Pseudo-nitzschia (0.2–210 cells mL−1). However, large diatoms (>10 μm) were virtually absent (
Brazilin Limits Inflammatory Responses through Induction of Prosurvival Autophagy in Rheumatoid Fibroblast-Like Synoviocytes

Brazilin is an active compound of Caesalpinia sappan L. (Leguminosae), which possesses pro-apoptotic and anti-inflammation potentials depending on the specific cell type. However, it is largely unknown whether autophagy is implicated in the mechanism underlying its chemotherapeutic and anti-inflammatory effects in rheumatoid arthritis (RA). Here, we show that treatment of RA fibroblast-like synoviocytes (FLS) with brazilin results in enhanced level of autophagic flux, evidenced by accumulation of autophagosome and increased level of lipidated LC3 (LC3-II), which is mainly mediated by enhanced production of reactive oxygen species (ROS). Interestingly, long-term exposure of brazilin was able to restore cell survival against the cytotoxity, exclusively in RA FLS, but not in normal fibroblast. Importantly, such a restoration from brazilin-induced cytotoxity in RA FLS was completely abrogated after co-treatment with autophagy inhibitors including NH4Cl or chloroquine. Furthermore, we found that the pretreatment of RA FLS with brazilin reduced LPS- or TNF-induced NF-κB activation and the secretion of inflammatory cytokines in parallel with the enhanced autophagic flux. Such anti-NF-κB potentials of brazilin were drastically masked in RA FLS when autophagy was suppressed. These results suggest that brazilin is capable of activating autophagy exclusively in RA FLS, and such inducible autophagy promotes cell survival and limits inflammatory response.
EXTRINSIC PARAMETERS CALIBRATION OF A STRUCTURED LIGHT SYSTEM VIA PLANAR HOMOGRAPHY BASED ON A REFERENCE SOLID

Structured light systems are widely used for three-dimensional shape reconstruction. The accurac y of the vision system parameters is of paramount importance for the accuracy of the 3D reconstruction. Often the extrin sic parameters change over time due to environmental conditions, in order to compensate for structured l ight parameters change, a self-recalibration method base d on planar homography is proposed in this paper. The method uses the planar homography of corresponding points in two camera views to identify the relative position and orientation between the two cameras: one is the "real" camera, while the other is a reference solid considered as a "pse udo- camera". The laser plane of the structured light vi sion system is the constraining plane for the two camera s corresponding points. In order to assess the metrological quality of the method an evaluation of the accuracy of the 3D reconstruct ion is performed by a two step Monte Carlo simulation. In a first step it is estimated the extrinsic parameters accur acy obtained by self-recalibration. In a second step th e intrinsic parameters accuracy and the extrinsic one previousl y computed are used to evaluate the accuracy of 3D sh ape reconstruction. In the final version of the paper, the overall accuracy will be verified experimentally by a prope r calibration setup.
Novel wide-band coplanar waveguide-to-rectangular waveguide transition

A new coplanar waveguide (CPW)-to-rectangular waveguide transition is proposed for wide-band millimeter-wave applications. The transition has an in-line structure, which provides easy fabrication of the CPW circuit and waveguide block. An X-band (8.2-12.4 GHz) model has been designed and tested. Measurements of a back-to-back double transition have yielded a return loss of over 17 dB and an insertion loss of less than 0.5 dB over the full X-band. These results agree well with the simulated results obtained with a commercial electromagnetic structure simulator. In addition, this type of a transition has been designed and used for a local oscillator feed with a full F-band (90-140 GHz) coverage of a submillimeter-wave general-purpose harmonic mixer.
Advantages of Deferred Approach for Time-Critical Tasks

This article discusses about ways of organizing and using the system for typical user behavior model construction within a distributed information system using Python servers. Much attention is paid to analysis of the issue of effective organization of the research process using the Python language in all its phases.Possibilities of using Python servers implement different policies for problems with strict limitations on the processing of incoming requests was reviewed. Along with the classical approach, we consider a new variant of the organization of the server: Deferred, which allowed to stay within the constraints of the target problem domain.
Mathematical Aspects of Numerical Solution of Hyperbolic Systems

A number of physical phenomena are described by nonlinear hyperbolic equations. Presence of discontinuous solutions motivates the necessity of development of reliable numerical methods based on the fundamental mathematical properties of hyperbolic systems. Construction of such methods for systems more complicated than the Euler gas dynamic equations requires the investigation of existence and uniqueness of the self-similar solutions to be used in the development of discontinuity-capturing high-resolution numerical methods. This frequently necessitates the study of the behavior of discontinuities under vanishing viscosity and dispersion. We discuss these problems in the application to the magnetohydrodynamic equations, nonlinear waves in elastic media, and electromagnetic wave propagation in magnetics.
Scaling dynamics of a cubic interval-exchange transformation

We study the dynamics of renormalization of a specific interval-exchange transformation which features exact scaling (the cubic Arnoux–Yoccoz model). Using a symbolic space that describes both dynamics and scaling, we characterize the periodic points of the scaling map in terms of generalized decimal expansions, where the base is the reciprocal of a Pisot number and the digits are algebraic integers. The set of periodic points has a rich arithmetic and geometric structure: we establish rigorously some facts, and use extensive numerical experimentation to formulate a conjecture.
Validation of an Automated Seizure Detection System on Healthy Babies - Histogram-based Energy Normalization for Montage Mismatch Compensation

Seizures in newborn babies are commonly caused by problems such as lack of oxygen, haemorrhage, meningitis, infection and strokes. The aim of an automated neonatal seizure detection system is to assist clinical staff in a neonatal intensive care unit to interpret the EEG. In this work, the automated neonatal seizure detection system is validated on a set of healthy patients and its performance is compared to the performance obtained on sick patients reported previously. The histogram-based energy normalization technique is designed and applied to EEG signals from healthy patients to cope with montage mismatch. The results on healthy babies compares favourably to those obtained on sick babies. Several useful observations are made which were not possible to obtain by testing on sick babies only such as a practically useful range of probabilistic thresholds, minimum detection duration restriction, and an influence of the database statistics on the system performance.