Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Phone Log-Likelihood Ratio Features for the Detection of the Native Language of Non-Native English Speakers

Detecting the native language (L1) of non-native English speakers may be of great relevance in some applications, such as computer assisted language learning or IVR services. In fact, the L1 detection problem closely resembles the problem of spoken language and dialect recognition. In particular, log-likelihood ra-tios of phone posterior probabilities, known as Phone LogLike-lihood Ratios (PLLR), have been recently introduced as features for spoken language recognition systems. This representation has proven to be an effective way of retrieving acoustic-phonotactic information at frame-level, which allows for its use in state-of-the-art systems, that is, in i-vector systems. In this paper, we explore the use of PLLR-based i-vector systems for L1 native language detection. We also investigate several linear and non-linear L1 classiﬁcation schemes on top of the PLLR i-vector front-ends. Moreover, we compare PLLR based systems with both conventional phonotactic systems based on n-gram modelling of phoneme sequences and acoustic-based i-vector systems. Finally, the potential complementarity of the different approaches is investigated based on a set of system fusion experiments.
Robust 3D Line Extraction from Stereo Point Clouds

The paper describes a robust method to extract 3D lines from stereo point clouds. This method combines 2D image information with 3D point clouds from a stereo camera. 2D lines are first extracted from the image in the stereo pair, followed by 3D line regression from the back-projected 3D point set of the images points in the detected 2D lines. In this paper, random sample consensus (RANSAC) is used to estimate 3D line from the 3D point set, the Mahalanobis distance from each 3D point to the 3D line is derived, and the statistically motivated distance measure is used to compute the support for the detected 3D line. Experimental results on real environment with high level of clutter, occlusion, and noise demonstrate the robustness of the algorithm.
An advanced local offset matching strategy for object proposal matching

Image correspondence problem is very challenging due to the complexity of real-world scenes, especially in the presence of deformation, outliers, and other intra-class variations. Semantic flow methods are used for finding image correspondences, but the prevalent ones are mainly depended on pixel-level or regularly local-region sampled operation that are easily confused by image-specific details and element-specific scenes to individual objects, e.g. background, clutter, and they rarely care about the relationships between proposals. Therefore, we propose an advanced local offset matching strategy for object proposals, which is in term of naive Bayesian model, considering both appearance and the local spatial pattern with preprocessing. It not only builds reliable region relationships using object proposals, but also explores consistency between appearance and spatial pattern among proposals. In addition, two evaluation metrics, seven features are applied to experiments. The comparison and analysis, along with adequate experiments on standard benchmark, present that our proposed method effectively outperforms other matching strategies in diverse settings.
Lifelong motor development

1. Introduction to the Developmental Perspective. 2. Heredity and Neurological Changes. 3. Physical Growth Changes. 4. Physiological Changes. 5. Factors Affecting Growth and Development. 6. Perceptual Development. 7. Information Processing and Motor Control. 8. Early Movement Behavior. 9. Motor Behavior during Early Childhood. 10. Motor Behavior during Later Childhood and Adolescence. 11. Motor Behavior in the Adult Years. 12. Assessment. 13. Sociocultural Influences on Motor Development.
Using intron position conservation for homology-based gene prediction

Annotation of protein-coding genes is very important in bioinformatics and biology and has a decisive influence on many downstream analyses. Homology-based gene prediction programs allow for transferring knowledge about protein-coding genes from an annotated organism to an organism of interest. Here, we present a homology-based gene prediction program called GeMoMa. GeMoMa utilizes the conservation of intron positions within genes to predict related genes in other organisms. We assess the performance of GeMoMa and compare it with state-of-the-art competitors on plant and animal genomes using an extended best reciprocal hit approach. We find that GeMoMa often makes more precise predictions than its competitors yielding a substantially increased number of correct transcripts. Subsequently, we exemplarily validate GeMoMa predictions using Sanger sequencing. Finally, we use RNA-seq data to compare the predictions of homology-based gene prediction programs, and find again that GeMoMa performs well. Hence, we conclude that exploiting intron position conservation improves homology-based gene prediction, and we make GeMoMa freely available as command-line tool and Galaxy integration.
Noise reduction for low-dose single-slice Helical CT sinogram

Helical computed tomography (HCT) offers several advantages on conventional step-and-shoot CT for imaging a relatively large object, especially in dynamic studies. However, it may increase the X-ray exposure significantly. This work aims to reduce the radiation by noise reduction on low-dose (or mA) sinogram of HCT. The noise reduction method is based on three observations on HCT: (1) the axial sampling of HCT projections is nearly continuous as the detector system rotates; (2) the noise distribution in the sinogram space is nearly a Gaussian after system calibration (including logarithmic transform); and (3) the relationship of calibrated data mean and variance can be expressed as an exponential functional across the field-of-view. Based on the second and third observations, a penalized weighted least-square (PWLS) solution was chosen, where the weight is given by the data mean-variance relationship. The first observation encourages the use of Karhunen-Loeve (KL) strategy along the axial direction. In the KL domain, the eigenvalue of each principal component was used for an adaptive noise smoothing via the penalty. The KL-PWLS noise-reduction method was implemented analytically for efficient reconstruction of large volume HCT images. Simulation studies demonstrated noticeable improvement, in terms of image quality measures and abnormal detectability observer studies, of the proposed noise-reduction method over conventional low-pass noise filtering with an optimal cutoff frequency and/or other filter parameters
Generalized predictive control tuning by controller matching

The tuning of state-space model predictive control (MPC) based on reverse engineering has been investigated in literature using the inverse optimality problem ( [1] and [2]). The aim of the inverse optimality is to find the tuning parameters of MPC to obtain the same behavior as an arbitrary linear-time-invariant (LTI) controller (favorite controller). This requires equal control horizon and prediction horizon, and loop-shifting is often used to handle non-strictly-proper favorite controllers. This paper presents a reverse-engineering tuning method for MPC based on transfer function formulation, also known as generalized predictive control (GPC). The feasibility conditions of the matching of a GPC with a favorite controller are investigated. This approach uses a control horizon equal to one and does not require any loop-shifting techniques to deal with non-strictly-proper favorite controllers. The method is applied to a binary distillation column example.
Obesity and Co-morbid Conditions Are Associated with Specific Neuropsychiatric Symptoms in Mild Cognitive Impairment

Background: Neuropsychiatric symptoms (NPSs) in MCI, and midlife obesity increase the likelihood of developing Alzheimer’s disease. It is unknown whether obesity or related health conditions modify the risk of NPS or severity of cognitive impairment in MCI. Methods: One hundred and thirteen subjects with MCI were assessed near the time of MCI diagnosis. The sample was divided by BMI and related disorders, type-2 diabetes (T2D) and obstructive sleep apnea (OSA) to measure the relationship of these groups with NPS and severity of MCI. NPSs scores were evaluated based on the Neuropsychiatric Inventory-Questionnaire (NPI-Q) and Geriatric Depression Scale, along with NPI-Q clusters. MCI-severity was estimated based on a composite z-score of neuropsychological tests. Results: Obese and overweight subjects represented 65% of the sample and were on average 7 years younger than normal weight subjects. The presence of obesity, T2D and OSA status modified the prevalence and severity of specific NPI-Q symptom clusters, specifically affective symptoms were more frequent across groups and severe in OB and T2D. Total NPS scores were higher for subjects with T2D and OSA although MCI-severity did not differ across groups. Conclusion: MCI subjects with obesity, T2D and OSA demonstrated a higher susceptibility to psychopathologic changes.
Semi-automatic skin lesion segmentation via fully convolutional networks

Segmentation of skin lesions is considered as an important step in computer aided diagnosis (CAD) for melanoma diagnosis. There have many attempts to segment skin lesions in a semi- or fully-automated manner. Existing methods, however, have problems with over- or under-segmentation and do not perform well with challenging skin lesions such as when a lesion is partially connected to the background or when image contrast is low. To overcome these limitations, we propose a new semi-automated skin lesion segmentation method that incorporates fully convolutional networks (FCNs) with multi-scale integration. We leverage the use of FCNs to derive high-level semantic information with simple user interaction e.g., a single click to accurately segment skin lesions of various complexity. Our experiments with 379 skin lesion images show that our proposed method achieves better segmentation results when compared to the state-of-the-art skin lesion segmentation methods for challenging skin lesions.
Turning an Urban Scene Video into a Cinemagraph

This paper proposes an algorithm that turns a regular video capturing urban scenes into a high-quality endless animation, known as a Cinemagraph. The creation of a Cinemagraph usually requires a static camera in a carefully configured scene. The task becomes challenging for a regular video with a moving camera and objects. Our approach first warps an input video into the viewpoint of a reference camera. Based on the warped video, we propose effective temporal analysis algorithms to detect regions with static geometry and dynamic appearance, where geometric modeling is reliable and visually attractive animations can be created. Lastly, the algorithm applies a sequence of video processing techniques to produce a Cinemagraph movie. We have tested the proposed approach on numerous challenging real scenes. To our knowledge, this work is the first to automatically generate Cinemagraph animations from regular movies in the wild.
Mutations in the ANKRD1 gene encoding CARP are responsible for human dilated cardiomyopathy.

AIMS Dilated cardiomyopathy (DCM) is familial in approximately 30% of cases, and mutations have been identified in several genes. However, in a majority of familial cases, the responsible genes are still to be discovered. The ANKRD1 gene is over-expressed in heart failure in human and animal models. The encoded protein CARP interacts with partners such as myopalladin or titin, previously shown to be involved in DCM. We hypothesized that mutations in ANKRD1 could be responsible for DCM. METHODS AND RESULTS We sequenced the coding region of ANKRD1 from 231 independent DCM cases. We identified five missense mutations (three sporadic and two familial) absent from 400 controls and affecting highly conserved residues. Expression of the mutant CARP proteins after transfection in rat neonate cardiomyocytes indicated that most of them led to both significantly less repressor activity measured in a reporter gene assay and greater phenylephrin-induced hypertrophy, suggesting altered function of CARP mutant proteins. CONCLUSION On the basis of genetic and functional analysis of CARP mutations, we have identified ANKRD1 as a new gene associated with DCM, accounting for approximately 2% of cases.
A Discussion of Disutility of Waiting

In this paper, we have considered a linear disutility of waiting, i.e., the disutility increases linearly in t, the expected time to have an order filled. The idea that customers are delaysensitive and that the disutility of waiting is linear has been expressed by several other authors. For example, Van Ackere and Ninios (1993), Hassin (1986), Li (1992), Li and Lee (1994) and Stidham (1970) model the disutility of waiting in a similar, but more limited, manner compared to our model. Specifically, they assume that all customers have the same unit waiting cost, b, per unit time (i.e., customers are homogeneous and the disutility is
Information technology team achievement: An analysis of success factors and development of a team success model (TSM)

Purpose – This paper sets out o determine influences on team performance processes and develop an overall team success model (TSM). Design/methodology/approach – A total of 55 individual students grouped in 18 teams, ranging in size from two to five, were measured at several stages in semester‐long team projects. Forty‐four separate questions were studied in each measurement stage. These 44 questions were reduced to five factors through exploratory factor analysis (EFA). Structural equation modeling (SEM) was then used to determine the significance and interrelationships of these factors, as well as the influence of gender and grade point average (GPA). Findings – This research develops and validates a series of factors that lead to IT team success. The factors include emotions, personal processes, and team processes. The overall R2 of the final model was high at 0.601. Significant relationships were found between many factors. GPA had a positive impact on team processes, while negative emotions showed a ne.
Improving the distance properties of turbo codes using a third component code: 3D turbo codes - [transactions letters]

Thanks to the probabilistic message passing performed between its component decoders, a turbo decoder is able to provide strong error correction close to the theoretical limit. However, the minimum Hamming distance (dmin) of a turbo code may not be sufficiently large to ensure large asymptotic gains at very low error rates (the so-called flattening effect). Increasing the dmin of a turbo code may involve using component encoders with a large number of states, devising more sophisticated internal permutations, or increasing the number of component encoders. This paper addresses the latter option and proposes a modified turbo code in which a fraction of the parity bits are encoded by a rate-1, third encoder. The result is a noticeably increased dmin, which improves turbo decoder performance at low error rates. Performance comparisons with turbo codes and serially concatenated convolutional codes are given.
111-Gb/s PolMux-Quadrature Duobinary for Robust and Bandwidth Efficient Transmission

We investigate, by means of simulations, polarization-multiplexed (PolMux) quadrature duobinary (QDB) as a modulation format for transmitting 111-Gb/s signals with high spectral efficiency (SE) and acceptable system complexity. We show that PolMux-QDB can be used to transmit 111-Gb/s signals with an SE of 4-b/s/Hz, but at the same time has a higher tolerance to nonlinear transmission effects and local oscillator laser linewidth compared to PolMux-16QAM at the same data rate and SE.
[CT-free image guided acetabulum navigation in clinical routine].

After experimental and preclinical evaluation (HAP Paul Award 2001) of the CT-free image-guided surgical navigation system for acetabular cup placement (SurgiGATE C-arm cup" by Medivision, Switzerland), the system was introduced into clinical routine. The computation of the angular orientation of the cup is based on reference coordinates from the anterior pelvic plane concept. A hybrid strategy for pelvic landmark acquisition has been introduced involving percutaneous pointer-based digitization with the noninvasive biplanar landmark reconstruction using multiple registered fluoroscopy images. From January 2001 to December 2002, a total of 256 consecutive patients with primary osteoarthrosis (mean age 69 years, 161 male, 95 female, 132 left, and 124 right hip joints) were operated on with the hybrid CT-free navigation system. During each operation the angular orientation of the inserted implant was recorded. To determine the placement accuracy of the acetabular components, 50 consecutive patients underwent a CT scan 7-10 days postoperatively to analyze the cup position related to the anterior pelvic plane. This was all done blinded by the same investigator with the planning software of the CT-based navigation system of Medivision. There was no significant learning curve observed for the use of the system. The mean value for postoperative inclination was 43 degrees (SD 3.0, range: 37 degrees -49 degrees ) and for anteversion 19 degrees (SD 3.9, range: 10 degrees -28 degrees ). The resulting system accuracy, i.e., the difference between intraoperatively calculated cup orientation and postoperatively measured implant position showed a mean error of 1.5 degrees for the inclination (maximum 5 degrees, SD 1.1) and 2.4 degrees for the anteversion (maximum 6 degrees, SD 1.3). An accuracy of better than 5 degrees inclination and 6 degrees anteversion was achieved under clinical conditions, which implies that there is no significant difference in performance from the established CT-based navigation methods. Image-guided CT-free cup navigation provides a reliable solution for future THA.
Infection with Influenza and Parainfluenza Viruses in Chronic Bronchitis

Exacerbations of chronic bronchitis are often preceded by symptoms of infection of the upper respiratory tract, but little is known of the frequency with which they are precipitated by virus infections. There is evidence that bronchitics develop severe illness when infected with influenza A virus (Tyrrell, 1952; Walker, Douglas, Leckie, Pines, and Grant, 1958; Louria, Blumenfeld, Ellis, Kilbourne, and Rogers, 1959) and that the features of the influenzal illness may be modified by the pre-existing chronic bronchitis. Hennessy (1962) and Jack and Gandevia (1960) failed to demonstrate a viral aetiology for the exacerbations of bronchitis in the patients they studied. More recently, Sommerville (1963) found serological evidence of infection with respiratory syncytial virus in bronchitics in exacerbation. Carilli, Gohd, and Gordon (1964) obtained evidence of infection with many respiratory viruses, including influenza and parainfluenza, during a six-month study of 30 bronchitics. However, both virus infections and exacerbations of bronchitis are common occurrences, and some studies, such as that of Carilli et al. (1964), though demonstrating a high incidence of virus infections in bronchitics, have not shown that such infections are more frequent at the time of exacerbation. The parainfluenza viruses were first isolated from children with acute respiratory disease in 1955 and 1957, and the clinical syndromes associated with them in childhood have been well defined (Parrott, Vargosko, Luckey, Kim, Cumming, and Chanock, 1959). They probably account for a high proportion of all acute respiratory infections of children, but less is known of the frequency and effect of infection in adults. In most cases a mild upper respiratory illness seems to occur, but acute bronchitis and pneumonia have been reported (Evans, 1960; Evans and Brobst, 1961). In this investigation we have tried to assess the importance of the influenza and parainfluenza viruses in causing acute illness among a group of typical chronic bronchitics during the winter of 1961-62.
Large margin optimization of ranking measures

Most ranking algorithms, such as pairwise ranking, are based on the optimization of standard loss functions, but the quality measure to test web page rankers is often different. We present an algorithm which aims at optimizing directly one of the popular measures, the Normalized Discounted Cumulative Gain. It is based on the framework of structured output learning, where in our case the input corresponds to a set of documents and the output is a ranking. The algorithm yields improved accuracies on several public and commercial ranking datasets.
Using Targeted Spirometry to Reduce Non-Diagnosed Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is increasing worldwide and thus its associated morbidity and mortality. However, COPD often goes undiagnosed. Objectives: We evaluated the rate of non-diagnosed irreversible airway obstruction (AO) and characterized this patient group. We further assessed the possible effects of conducting targeted spirometry in a population sample in Salzburg, Austria, as part of the Burden of Obstructive Lung Disease (BOLD) study. Methods: 1,258 adults ≧40 years of age completed a questionnaire and performed spirometry before and after bronchodilator therapy (post-BD). Irreversible AO was defined as post-BD FEV1/FVC below the lower limit of normal; we used the FEV1% predicted (pred.) to further grade the disease. Participants without a physician diagnosis of COPD who reported respiratory symptoms and a history of risk factors (ever smoking or occupational risk) were defined as eligible for targeted spirometry. Results: 85.9% (171/199) of the participants with irreversible AO did not report a prior diagnosis of COPD. Non-diagnosed AO was inversely related to severity, age, self-reported prior respiratory diseases and cough as a respiratory symptom. 343 participants were eligible for targeted spirometry and irreversible AO was present in 86 (25.1%) participants. Therefore, targeted spirometry could reduce the underdiagnosis of irreversible AO of any severity by 50.3% (86 of 171). The diagnosis of 1 person with FEV1 <80% pred. would require spirometry in 8.4 subjects (95% confidence interval 6.2–11.1). Conclusion: Although several factors are associated with non-diagnosed AO, spirometry in individuals with respiratory symptoms and exposure to risk factors could reduce undiagnosed irreversible AO by half.
Evaluating Uplink Schedulers in LTE in Mixed Traffic Environments

3GPP's Long Term Evolution is defined by the standardization body's Release 8 and 9, and provides more than a substrate for 3GPP's IMT-Advanced candidate, namely LTE-Advanced, which is due to be defined in Release 10. Both LTE and LTE-Advanced have SC-FDMA in their uplink, a multi-carrier access technique requiring contiguous subcarriers allocations for each UE. No scheduling algorithm, however, is dictated by the standard and several proposals have hence been presented to implemented by vendors. A definite scheduling requirement is the support of QoS attributes of different types of uplink traffic. Our intent in this study is evaluate the connection-level performance of representative scheduling proposals, with focus on QoS aspects. Specifically, we utilize a mixed type of traffic flows and evaluate the schedulers in terms of per-user throughput, delay, packet loss and fairness.