Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer-aided diagnosis in medical imaging: Review of legal barriers to entry for the commercial systems

The goal of this paper is to explore whether the premarket regulatory system of the United States functions ideally in facing the emergence of commercial computer-aided diagnosis (CAD) systems for medical imaging. To outline the commercial CAD systems available in the United States, clinical trials published in PubMed and EMBASE from 2012 to 2016 that investigated the clinical competence of commercial CAD products were obtained, and the product information provided in these studies was searched in the Establishment Registration & Device Listing database, the Releasable 510(k) Premarket Notification database, and the Premarket Approval (PMA) database of the FDA to trace the processes through which such CAD systems entered the healthcare market. A review of current premarket regulatory system for medical devices, and the potential problems that may hinder the social and clinical integration of CAD systems are presented. We noticed expansion of regulatory definition and variation of device classes and product codes among CAD systems with similar clinical uses, which may compromise the efficacy of such regulatory controls. The results suggested ineffectiveness of current premarket regulatory controls for CAD systems in the United States.
Evaluation of the respiratory route as a viable portal of entry for Salmonella in poultry via intratracheal challenge of Salmonella Enteritidis and Salmonella Typhimurium1

Experimental and epidemiological evidence suggests that primary infection of Salmonella is by the oral-fecal route for poultry. However, the airborne transmission of Salmonella and similar enteric zoonotic pathogens has been historically neglected. Increasing evidence of Salmonella bioaerosol generation in production facilities and studies suggesting the vulnerabilities of the avian respiratory architecture together have indicated the possibility of the respiratory system being a potential portal of entry for Salmonella in poultry. Presently, we evaluated this hypothesis through intratracheal (IT) administration of Salmonella Enteritidis and Salmonella Typhimurium, as separate challenges, in a total of 4 independent trials, followed by enumeration of cfu recovery in ceca-cecal tonsils and recovery incidence in liver and spleen. In all trials, both Salmonella Enteritidis and Salmonella Typhimurium, challenged IT colonized cecae to a similar or greater extent than oral administration at identical challenge levels. In most trials, chickens cultured for cfu enumeration from IT-challenged chicks at same dose as orally challenged, resulted in an increase of 1.5 log higher Salmonella Enteritidis from ceca-cecal tonsils and a much lower dose IT of Salmonella Enteritidis could colonize ceca to the same extent than a higher oral challenge. This trend of increased cecal colonization due to IT challenge was observed with all trails involving week-old birds (experiment 2 and 3), which are widely considered to be more difficult to infect via the oral route. Liver-spleen incidence data showed 33% of liver and spleen samples to be positive for Salmonella Enteritidis administered IT (106 cfu/chick), compared with 0% when administered orally (experiment 2, trial 1). Collectively, these data suggest that the respiratory tract may be a largely overlooked portal of entry for Salmonella infections in chickens.
Design of capacity-approaching irregular low-density parity-check codes

We design low-density parity-check (LDPC) codes that perform at rates extremely close to the Shannon capacity. The codes are built from highly irregular bipartite graphs with carefully chosen degree patterns on both sides. Our theoretical analysis of the codes is based on the work of Richardson and Urbanke (see ibid., vol.47, no.2, p.599-618, 2000). Assuming that the underlying communication channel is symmetric, we prove that the probability densities at the message nodes of the graph possess a certain symmetry. Using this symmetry property we then show that, under the assumption of no cycles, the message densities always converge as the number of iterations tends to infinity. Furthermore, we prove a stability condition which implies an upper bound on the fraction of errors that a belief-propagation decoder can correct when applied to a code induced from a bipartite graph with a given degree distribution. Our codes are found by optimizing the degree structure of the underlying graphs. We develop several strategies to perform this optimization. We also present some simulation results for the codes found which show that the performance of the codes is very close to the asymptotic theoretical bounds.
The prosody of question tags in English

The prosodic realization of English question tags (QTs) has received some interest in the literature; yet corpus studies on the factors affecting their phrasing and intonational realization are very rare or limited to a certain aspect. This article presents a quantitative corpus study of 370 QTs from the International Corpus of English that were annotated for prosodic phrasing and intonational realization of the QT and the host. Factors tested were polarity, position in the sentence and the turn as well as verb type. Generally, prosodic phrasing and intonational realization were highly correlated: separate QTs were mostly realized with a falling contour, while integrated QTs were mostly rising. Results from regression models showed a strong effect of polarity: QTs with an opposite polarity were more often phrased separately compared to QTs with constant polarity, but the phrasing of opposite polarity QTs was further dependent on whether the QT was negative or positive (more separate phrasing in negative QTs). Furthermore, prosodic separation was more frequent at the end of syntactic phrases and clauses compared to phrase-medial QTs. At the end of a turn, speakers realized more rising contours compared to QTs within a speaker’s turn. Verb type also had an effect on the phrasing of the tag. Taken together, our results confirm some of the claims previously held for QTs, while others are modified and new findings are added.
Design of a Control Lyapunov Function for Stabilizing Specified States

Abstract This paper focuses on the design of control Lyapunov function for control affine systems to guarantee the stability for the states of interest in a specified region. Without restrictive assumptions found in previous approaches, a min-max optimization problem is formulated to solve for a quadratic Lyapunov function. A derivative-free coordinate search method is employed to optimize a non-differentiable objective function. Approximation of the objective function as a piecewise linear function gradually reduces search space, leading to an effective Lyapunov function. A CSTR example with actuator saturation is illustrated to demonstrate the efficacy of the proposed approach.
Towards a hybrid algorithm for extracting maximal frequent conceptual links in social networks

One of the most common tasks in the area of social network mining is the extraction of frequent patterns from social networks. Although traditional approaches have been mainly focused on subgraphs occurring frequently in a network or a set of networks, new approaches have attempted to exploit network structure and node properties in order to elicit new kinds of patterns. One of these news approaches is the extraction of conceptual links, a solution that combines both structure and node properties for providing knowledge on the groups of nodes the most connected in a social network. However, if the extraction of conceptual links offers a great potential in terms of knowledge discovery as well as network visualization, the search for these kinds of patterns remains a computationally intensive problem. Thus, the efficiency of the extraction processes highly depends on the efficiency of the underlying algorithm. In this paper, we focus on the extraction of maximal frequent conceptual links (MFCL) and we propose a hybrid algorithm that applies a filter on the nodes for reducing the search space to the most frequent groups of nodes. Although our solution potentially causes loss of some patterns, we demonstrate its efficiency by comparison with the MFCLMin algorithm. We investigate the potential loss of patterns, the gain on the runtime, and the gain on the number of comparisons.
Linköping University Electronic Press Report Ml Estimation of Process Noise Variance in Dynamic Systems Ml Estimation of Process Noise Variance in Dynamic Systems Estimation of Process Noise Variance in Dynamic Systems

The performance of a non-linear lter hinges in the end on the accuracy of the assumed non-linear model of the process. In particular, the process noise covariance Q is hard to get by physical modeling and dedicated system identication experiments. We propose a variant of the expectation maximization (EM) algorithm which iteratively estimates the unobserved state sequence and Q based on the observations of the process. The extended Kalman smoother (EKS) is the instrument to nd the unobserved state sequence. Our contribution lls a gap in literature, where previously only the linear Kalman smoother and particle smoother have been applied. The algorithm will be important for future industrial robots with more ex-ible structures, where the particle smoother cannot be applied due to the high state dimension. The proposed method is compared to two alternative methods on a simulated robot. Abstract: The performance of a non-linear filter hinges in the end on the accuracy of the assumed non-linear model of the process. In particular, the process noise covariance Q is hard to get by physical modeling and dedicated system identification experiments. We propose a variant of the expectation maximization (EM) algorithm which iteratively estimates the unobserved state sequence and Q based on the observations of the process. The extended Kalman smoother (EKS) is the instrument to find the unobserved state sequence. Our contribution fills a gap in literature, where previously only the linear Kalman smoother and particle smoother have been applied. The algorithm will be important for future industrial robots with more flexible structures, where the particle smoother cannot be applied due to the high state dimension. The proposed method is compared to two alternative methods on a simulated robot.
Automatic Detection of Cognates Using Orthographic Alignment

Words undergo various changes when entering new languages. Based on the assumption that these linguistic changes follow certain rules, we propose a method for automatically detecting pairs of cognates employing an orthographic alignment method which proved relevant for sequence alignment in computational biology. We use aligned subsequences as features for machine learning algorithms in order to infer rules for linguistic changes undergone by words when entering new languages and to discriminate between cognates and non-cognates. Given a list of known cognates, our approach does not require any other linguistic information. However, it can be customized to integrate historical information regarding language evolution.
Personal Choice or Political Provocation: Examining the Visual Framing and Stereotyping of the Burkini Debate

The burkini, a modest swimsuit marketed to Muslim women, was at the center of controversy in France when it was banned from the beaches in dozens of cities. This research examines how the three leading international newswires (Agence France-Presse/Getty Images, Associated Press, and Reuters) visually framed this debate and whether they visually stereotyped women wearing the burkini. Using a mixed-method approach, this study unpacks the role of news agency photography in visual representation. The analysis examines four visual frames: Mediated Solidarity, Administrative Response, Symbolic Fashion, and Active Liberation.
Combination of Correlation Measures for Dense Stereo Matching

Dans le cadre de la mise en correspondance dense de pixels, nous etudions la fusion de differentes mesures de correlation. En s'appuyant sur les travaux precedents, nous utilisons les mesures les plus representatives parmi 5 familles de mesures : correlation croisee, mesures classiques, similarite de gradients, statistiques non-parametriques et statistiques robustes. Plus precisement, notre etude met en evidence la possibilite d'ameliorer la mise en correspondance en combinant differentes mesures de correlation que l'on souhaite complementaires. En particulier, nous demontrons la superiorite de la combinaison des mesures de correlation suivantes : Gradient Correlation (GC) et Smooth Median Absolute Deviation measure (SMAD). Enfin, nous introduisons un algorithme de fusion qui permet de combiner automatiquement ces 2 mesures.
A HYBRID TABU-SA ALGORITHM FOR LOCATION-INVENTORY MODEL WITH CONSIDERING CAPACITY LEVELS AND UNCERTAIN DEMANDS

In this paper, we present a complex distribution network design problem in supply chain system which includes location and inventory decisions. Customers' demand is generated randomly and each distribution center maintains a certain amount of safety stock in order to achieve a certain service level for the customers it services. Unlike most of past research, our model allows for multiple levels of capacities available to the distribution centers. This consideration helps to achieve the capacity utilization to a high level as our computational results show this fact. We show that this problem can be formulated as a non-linear integer programming model. A hybrid heuristic combining Tabu search with Simulated Annealing (SA) sharing the same tabu list is developed for solving the problem. We comprise the hybrid algorithm with the optimal solution, Simulated Annealing algorithm and Tabu search algorithm. The results indicate that the method is efficient for a wide variety of problem sizes.
CD4+ T Cells and Gamma Interferon in the Long-Term Control of Persistent Friend Retrovirus Infection

ABSTRACT We have used the Friend virus model to determine the basic mechanisms by which the immune system can control persistent retroviral infections. Previously we showed that CD4+ T cells play an essential role in keeping persistent retrovirus in check. The present in vitro experiments with a Friend virus-specific CD4+T-cell clone revealed that these cells produce gamma interferon (IFN-γ), which acts with two distinct mechanisms of antiviral activity. First, IFN-γ had a direct inhibitory effect on virus production. This inhibitory effect was noncytolytic and, interestingly, was not associated with decreased cell surface expression of viral antigens. The second mechanism of IFN-γ-mediated antiviral activity was an enhancement of CD4+ T-cell-mediated cytolytic activity. We also found an in vivo role for IFN-γ in the control of persistent Friend virus infections. Neutralization of IFN-γ in persistently infected mice resulted in significantly increased levels of virus in the spleen, and a significant percentage of IFN-γ-deficient mice were unable to maintain long-term control over Friend virus infections.
ACCURATE 3D TEXTURED MODELS OF VESSELS FOR THE IMPROVEMENT OF THE EDUCATIONAL TOOLS OF A MUSEUM

Besides the demonstration of the findings, modern museums organize educational programs which aim to experience and knowledge sharing combined with entertainment rather than to pure learning. Toward that effort, 2D and 3D digital representations are gradually replacing the traditional recording of the findings through photos or drawings. The present paper refers to a project that aims to create 3D textured models of two lekythoi that are exhibited in the National Archaeological Museum of Athens in Greece; on the surfaces of these lekythoi scenes of the adventures of Odysseus are depicted. The project is expected to support the production of an educational movie and some other relevant interactive educational programs for the museum. The creation of accurate developments of the paintings and of accurate 3D models is the basis for the visualization of the adventures of the mythical hero. The data collection was made by using a structured light scanner consisting of two machine vision cameras that are used for the determination of geometry of the object, a high resolution camera for the recording of the texture, and a DLP projector. The creation of the final accurate 3D textured model is a complicated and tiring procedure which includes the collection of geometric data, the creation of the surface, the noise filtering, the merging of individual surfaces, the creation of a c-mesh, the creation of the UV map, the provision of the texture and, finally, the general processing of the 3D textured object. For a better result a combination of commercial and in-house software made for the automation of various steps of the procedure was used. The results derived from the above procedure were especially satisfactory in terms of accuracy and quality of the model. However, the procedure was proved to be time consuming while the use of various software packages presumes the services of a specialist.
Wavelet Transform based Broken Rotor-bar Fault detection and Diagnosis Performance Evaluations

paper presents the performances evaluation of different wavelet transform under broken rotor bars fault diagnosis. In this report, stator phase current was used for wavelet analysis. Discrete wavelet transform (DWT) coefficients of stator current in a specific frequency band are derived and analyzed. Wavelets db8, db9, db10, sym7 and sym8 are employed to analyze broken bar distorted stator current. The sensitivities of these wavelets to fault signal are compared and assessed to select the most optimal one. This approach facilitates the detection and diagnosis of broken rotor bar occurrence or even number of broken bars under load variation. Simulation and experimental tests on induction motors with 1, 2, and 3 broken bars cases are conducted and demonstrate the effectiveness of the proposed approach for fault detection. Keywordsmachine, broken rotor bar, DWT, stator current
Titanium Nitride and Nitrogen Ion Implanted Coated Dental Materials

Titanium nitride and/or nitrogen ion implanted coated dental materials have been investigated since the mid-1980s and considered in various applications in dentistry such as implants, abutments, orthodontic wires, endodontic files, periodontal/oral hygiene instruments, and casting alloys for fixed restorations. Multiple methodologies have been employed to create the coatings, but detailed structural analysis of the coatings is generally lacking in the dental literature. Depending on application, the purpose of the coating is to provide increased surface hardness, abrasion/wear resistance, esthetics, and corrosion resistance, lower friction, as well as greater beneficial interaction with adjacent biological and material substrates. While many studies have reported on the achievement of these properties, a consensus is not always clear. Additionally, few studies have been conducted to assess the efficacy of the coatings in a clinical setting. Overall, titanium nitride and/or nitrogen ion implanted coated dental materials potentially offer advantages over uncoated counterparts, but more investigation is needed to document the structure of the coatings and their clinical effectiveness.
A novel fusion method of infrared and visual images based on Undecimated Discrete Wavelet Transform and saliency map

This paper proposes a new fusion approach of infrared (IR) and visual (VIS) images based on Undecimated Discrete Wavelet Transform (UDWT) and saliency map analysis. The proposed fusion method is composed of three steps. Firstly, IR and VIS images are decomposed into low-pass sub-band coefficients and high-pass sub-band coefficients by UDWT. Meanwhile, sub-band directional coefficients are extracted by Non-Subsampled Directional Filter Banks (NSDFB) from high-pass sub-band coefficients. Secondly, the coefficient combination rules are set based on saliency maps of original IR and VIS images, which are obtained by employing the Itti saliency computing model. Thirdly, fused images are re-built by the inverse UDWT. The results of the experiments indicate that the presented approach achieves better subjective fusion effects than some current popular fusion methods. Furthermore, the proposed method gets better objective assessments.
Semi-parametric Methods for Longitudinal Data Analysis

Self-modeling regression is a powerful semi-parametric tool for analysis of longitudinal data with time-invariant covariates. This paper explores the use of self-modelling regression for tting data from a designed experiment in which the response is a curve. Recent advances in mixed nonlinear models and nonparametric regression with time series errors has made the use of mixed model self-modeling regression a feasible extension of parametric mixed model methods for studies in which the response is a curve.
Affine invariant features and their application to speech recognition

This paper proposes a set of affine invariant features (AIFs) for sequence data. The proposed AIFs can be calculated directly from the sequence data, and their invariance to affine transformation is proved mathematically through algebraic calculation. We apply the AIFs to speech recognition. Since the vocal tract length (VTL) difference causes to frequency warping which can be approximated well by affine transform on cepstral features [1], the AIFs of cepstral sequence provide robust features for VTL variations. We experimentally examine the invariance of AIFs of speech signals, and apply AIFs for Japanese isolated word recognition. The experimental results show that the combination of AIFs with MFCC or MFCC+Δ can lead to higher recognition rates than MFCC or MFCC+Δ only. Especially in the mismatched experiments, the combination with AIFs can reduce the error rates about 30% when compared to MFCC or MFCC+Δ only. The AIFs are expected to have other applications than speech recognition, since their invariance is general.
A new method for obstacle detection based on Kinect depth image

Obstacle detection is a key technology of intelligent transportation and autonomous robot navigation. Aiming at the shortages of traditional obstacle detection technologies, the paper applies the Kinect depth camera as the sensor of obstacle detection system, and an obstacle detection method based on Kinect depth image is proposed on the theoretical basis of Kinect real-time 3D reconstruction and Meanshift segmentation. A series of experiments are carried out in different scenes, and the results show that the method can detect obstacles exactly in complex environments and it's robust to the affects of illumination, so it has a certain practical significance for the research of obstacle detection technology.
Acoustic control by wave field synthesis

The acoustics in auditoria are determined by the properties of both the direct sound and the later arriving reflections. If electroacoustic means are used to repair disturbing deficiencies in the acoustics, one has to cope with unfavorable side effects such as localization problems and artificial impressions of the reverberant field (electronic flavor). To avoid those side effects, the concept of electroacoustic wave front synthesis is introduced. The underlying theory is based on the Kirchhoff–Helmholtz integral. In this new concept the wave fields of the sound sources on stage are measured by directive microphones; next they are electronically extrapolated away from the stage, and finally they are re‐emitted in the hall by one or more loudspeaker arrays. The proposed system aims at emitting wave fronts that are as close as possible to the real wave fields. Theoretically, there need not be any differences between the electronically generated wave fields and the real wave fields. By using the image source.