Miracle-dz/UniFAR-FTUs huggingface dataset:
Music genre classification using modulation spectral features and multiple prototype vectors representation

In this paper, we will propose an automatic music genre classification approach based on long-term modulation spectral analysis of spectral (OSC and MPEG-7 NASE) as well as cepstral (MFCC) features. A modulation spectrogram corresponding to the collection of modulation spectra of MFCC/OSC/NASE will be constructed. The modulation spectrum is then decomposed into several logarithmically spaced modulation subbands. For each modulation subband, a new set of modulation spectral features, including modulation spectral contrast (MSC), modulation spectral valley (MSV), modulation spectral energy (MSE), modulation spectral centroid (MSCEN) and modulation spectral flatness (MSF) are then computed from each modulation subband. To cope with the problem that the feature vectors extracted from the music tracks of identical music genre might differ significantly, each music genre is modeled with a number of representative prototype vectors generated by c-means clustering algorithm. An information fusion approach which integrates both feature level fusion method and decision level combination method is then employed to improve the classification accuracy. Experiments conducted on ISMIR 2004 music dataset have shown that our proposed approach can achieve higher classification accuracy than other approaches with the same experimental setup.
Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle

MOTIVATION To understand the behaviour of complex biological regulatory networks, a proper integration of molecular data into a full-fledge formal dynamical model is ultimately required. As most available data on regulatory interactions are qualitative, logical modelling offers an interesting framework to delineate the main dynamical properties of the underlying networks. RESULTS Transposing a generic model of the core network controlling the mammalian cell cycle into the logical framework, we compare different strategies to explore its dynamical properties. In particular, we assess the respective advantages and limits of synchronous versus asynchronous updating assumptions to delineate the asymptotical behaviour of regulatory networks. Furthermore, we propose several intermediate strategies to optimize the computation of asymptotical properties depending on available knowledge. AVAILABILITY The mammalian cell cycle model is available in a dedicated XML format (GINML) on our website, along with our logical simulation software GINsim (http://gin.univ-mrs.fr/GINsim). Higher resolution state transitions graphs are also found on this web site (Model Repository page).
Object Tracking For Content-Based Functionalities

This paper presents a new technique for object tracking. Object tracking methods usually rely on the motion homogeneity of the object to be tracked. The proposed method does not assume that the selected objects present either motion or spatial homogeneity. It is therefore a very powerful tool for enabling content-based functionalities. This object tracking technique is based on the concept of partition projection which is implemented by means of a double partition approach. The projection of the previous partition is directly imposed in the current image so that temporal stability is improved. Several examples in different scenarios are finally presented in order to assess the performance of the method.
Handling interactions between real and virtual worlds

When compositing computer generated images and photographs or video images, interactions between real and virtual worlds must be taken into account in order to have a good visual result. These interactions are of three kinds: occluding object determination, specular inter-reflection and shadow computation. We first determine which real objects need to be geometrically and/or photometrically modelled for the three sets of interactions. Indeed, not all real surfaces need to be kept for the simulation and rendering steps. The unuseful real surfaces would just increase the rendering time. A rough photometric model can be sufficient for the surface properties, but colour computation has to be made in a particular colour model. Then for each kind of interactions, we take the real surfaces into account in a view-independent illumination step or in the rendering step.
Modeling of cross-regulation in converters containing coupled inductors

A general model of the multiple-winding coupled inductor is described, in which all parameters can be directly measured. This model is employed in a tutorial explanation of the mechanisms by which leakage inductances and effective turns ratios affect cross regulation and discontinuous conduction mode boundaries in a multiple-output converter. Three basic approaches to coupled-inductor design are compared: near-ideal coupling, practical moderate coupling, and the zero-ripple approach. Near-ideal coupling results in good cross-regulation even when some outputs become discontinuous; however, realization of near-ideal coupling may be difficult in practice, and the resulting circulating currents can also lead to increased output voltage ripples and reduced efficiency. The best cross regulation can be obtained via the zero-ripple approach with relatively loose coupling in applications where there is at least one output whose load current variations are relatively small so that all windings can always operate in the continuous conduction mode. The conclusions are supported by experimental results.
Evidence that intravenously derived murine pulmonary melanoma metastases can originate from the expansion of a single tumor cell.

The purpose of these studies was to determine whether hematogenous clonal pulmonary melanoma metastases originate from the expansion of a single cell and if so, by extrapolation, metastasis can be considered a cloning process. Three different cell lines of murine K-1735 melanoma with different metastatic properties and unique karyotypes were injected i.v. into syngeneic C3H/HeN mice as multicell aggregates of individual cell lines or combinations of cell lines. Resultant solitary lung metastases were isolated in culture as individual lines and then karyotyped. Even when heterogeneous clumps of tumor cells were injected, the individual metastases exhibited a karyotype unique to one metastatic cell type. Furthermore, when cellular aggregates were composed of metastatic cells admixed with cells that were tumorigenic but nonmetastatic, the resultant metastases exhibited only the karyotype of the metastatic cells. This finding suggests that the presence of metastatic cells did not change the inability of nonmetastatic cells to proliferate in a distant organ. Collectively, the results indicate that the resultant metastases were of clonal origin owing to the expansion of a single metastatic tumor cell in the lung parenchyma.
Comparison of ionic currents expressed in immature and mature muscle cells of an ascidian larva

We have compared the voltage-gated ion channels present in larval ascidian muscle at two developmental stages: muscle precursor cells just after the terminal cell division and mature contractile muscle, 7- 11 hr later. All precursor cells express a high-threshold transient Ca current and a slowly activating delayed K current, and about half the cells express a low-threshold transient Ca current. An inwardly rectifying K current, which had been present from fertilization until just before the terminal cell division, is absent. Mature muscle retains two of the tailbud currents: the low-threshold transient Ca current and the slow delayed K current, although at larger densities, and also expresses a high-threshold Ca current that is similar in most respects to the precursor cell current but that lacks inactivation. In addition, mature muscle expresses two rapidly activating outward K currents, one voltage and one Ca dependent, that generate a composite outward K current that is eight times larger and activates eight times faster than the tailbud K current. Mature muscle also reexpresses the inward rectifier. We propose that the transient absence of the inward rectifier and the slow activation of the delayed K current early in development create a window of developmental time when spontaneous electrical activity is likely.
Local texture based optical flow for complex brightness variations

In real-world scenarios, complex brightness variations are commonly seen, due to shadows, global illumination changes and nonlinear camera responses, etc. Classical optical flow methods based on brightness or gradient constancy assumption tends to fail under these circumstances. This work proposes an image texture descriptor called LSOT, based on the local spatial structure of a pixel and the relative ordinal information. Then a texture constancy assumption is embedded into a variational optical flow estimation framework as a data term, in order to cope with complex brightness variations. In addition, a non-local regularization term is used to improve the accuracy of the obtained flow fields. The energy functional is optimized using a primal-dual algorithm in a coarse-to-fine warping fashion. Experimental results on synthetic and real image sequences demonstrate the superior performance of the proposed method.
Detecting problematic message sequences and frequencies in distributed systems

Testing the components of a distributed system is challenging as it requires consideration of not just the state of a component, but also the sequence of messages it may receive from the rest of the system or the environment. Such messages may vary in type and content, and more particularly, in the frequency at which they are generated. All of these factors, in the right combination, may lead to faulty behavior. In this paper we present an approach to address these challenges by systematically analyzing a component in a distributed system to identify specific message sequences and frequencies at which a failure can occur. At the core of the analysis is the generation of a test driver that defines the space of message sequences to be generated, the exploration of that space through the use of dynamic symbolic execution, and the timing and analysis of the generated tests to identify problematic frequencies. We implemented our approach in the context of the popular Robotic Operating System and investigated its application to three systems of increasing complexity.
Facile One-Step Microwave-Assisted Route towards Ni Nanospheres/Reduced Graphene Oxide Hybrids for Non-Enzymatic Glucose Sensing

In this work, a facile one-step microwave-assisted method for deposition of monodisperse Ni nanospheres on reduced graphene oxide (rGO) sheets to form Ni-rGO nanohybrids is discussed. In the presence of hydrazine monohydrate, Ni nanospheres are grown onto rGO sheets using nickel precursor and GO as starting materials in ethylene glycol (EG) solution under a low level of microwave irradiation (300 W) for 20 min, during which GO is also reduced to rGO. The as-prepared nanohybrids exhibit well-dispersed Ni nanosphere (about 80 nm in diameter) loadings and effective reduction of graphene oxide. The resulting Ni-rGO nanohybrids-modified glassy carbon electrode (GCE) shows significantly improved electrochemical performance in nonenzymatic amperometric glucose detection. In addition, interference from the oxidation of common interfering species under physiological conditions, such as ascorbic acid (AA) and uric acid (UA), is effectively avoided.
Identification in Differentiated Products Markets

Empirical models of demand for -- and, often, supply of -- differentiated products are widely used in practice, typically employing parametric functional forms and distributions of consumer heterogeneity. We review some recent work studying identification in a broad class of such models. This work shows that parametric functional forms and distributional assumptions are not essential for identification. Rather, identification relies primarily on the standard requirement that instruments be available for the endogenous variables -- here, typically, prices and quantities. We discuss the kinds of instruments needed for identification and how the reliance on instruments can be reduced by nonparametric functional form restrictions or better data. We also discuss results on discrimination between alternative models of oligopoly competition.
Towards Robust Cross-Domain Domain Adaptation for Part-of-Speech Tagging

Most systems in natural language processing experience a substantial loss in performance when the data that the system is tested with differs significantly from the data that the system has been trained on. Systems for part-of-speech (POS) tagging, for example, are typically trained on newspaper texts but are often applied to texts of other domains such as medical texts. Domain adaptation (DA) techniques seek to improve such systems so that they are able to achieve consistently good performance - independent of the domains at hand. We investigate the robustness of domain adaptation representations and methods across target domains using part-of-speech tagging as a case study. We find that there is no single representation and method that works equally well for all target domains. In particular, there are large differences between target domains that are more similar to the source domain and those that are less similar.
Keratin 8 modulates &bgr;-cell stress responses and normoglycaemia

Summary Keratin intermediate filament (IF) proteins are epithelial cell cytoskeletal components that provide structural stability and protection from cell stress, among other cellular and tissue-specific functions. Numerous human diseases are associated with IF gene mutations, but the function of keratins in the endocrine pancreas and their potential significance for glycaemic control are unknown. The impact of keratins on &bgr;-cell organisation and systemic glucose control was assessed using keratin 8 (K8) wild-type (K8+/+) and K8 knockout (K8−/−) mice. Islet &bgr;-cell keratins were characterised under basal conditions, in streptozotocin (STZ)-induced diabetes and in non-obese diabetic (NOD) mice. STZ-induced diabetes incidence and islet damage was assessed in K8+/+ and K8−/− mice. K8 and K18 were the predominant keratins in islet &bgr;-cells and K8−/− mice expressed only remnant K18 and K7. K8 deletion resulted in lower fasting glucose levels, increased glucose tolerance and insulin sensitivity, reduced glucose-stimulated insulin secretion and decreased pancreatic insulin content. GLUT2 localisation and insulin vesicle morphology were disrupted in K8−/− &bgr;-cells. The increased levels of cytoplasmic GLUT2 correlated with resistance to high-dose STZ-induced injury in K8−/− mice. However, K8 deletion conferred no long-term protection from STZ-induced diabetes and prolonged STZ-induced stress caused increased exocrine damage in K8−/− mice. &bgr;-cell keratin upregulation occurred 2 weeks after treatments with low-dose STZ in K8+/+ mice and in diabetic NOD mice, suggesting a role for keratins, particularly in non-acute islet stress responses. These results demonstrate previously unrecognised functions for keratins in &bgr;-cell intracellular organisation, as well as for systemic blood glucose control under basal conditions and in diabetes-induced stress.
Detection of Application Layer DDoS attack by feature learning using Stacked AutoEncoder

An Application Layer Distributed Denial of Service Attack (DDoS) is one of the biggest concerns for web security. Many detection methods are designed to mitigate DDoS attack based on IP and TCP layer instead of the Application layer. These methods are not suitable for detection of Application layer DDoS attack since most of the IP and TCP layer DDoS attacks are based on request flooding attack. But Application layer DDoS attacks consist of request flooding, session flooding, and asymmetric attack. The solutions available to detect Application layer DDoS attack, detect only limited number of Application layer DDoS attacks. The solutions that detect all types of Application layer DDoS attacks have huge algorithm complexity. One of the major challenges in the detection of an Application layer DDoS attack is the non-availability of features to detect such attacks. Hence it is difficult to model normal user behavior from attack behavior. In this paper, Deep learning architecture is introduced to learn deep features of Application layer DDoS attack. Deep learning architecture consist of very deep neural network, typically more than three layers. In the proposed work the concept of AutoEncoder is applied, which is one of the deep learning based models that learns deep useful features in the Application layer DDoS attack dataset. The Stacked AutoEncoder deep learning architecture, is aimed to receive high level features. The performance of the proposed method was evaluated in terms of the metrics such as false positive rate and detection rate. Comparison of the proposed method with the existing methods reveals that the proposed method performs better than the existing methods.
Born in the USA: national origin effects on time allocation in US and Spanish professional basketball

This paper examines national origin bias in professional basketball in both the North American National Basketball Association (NBA) and Spanish professional league (Liga ACB). Past studies into racial bias find mixed results. In contrast, our study provides consistent evidence that players born in the USA receive preferential treatment in both the USA and Spain in terms of receiving additional time on the court.
The twelve triangular matrix forms of the pascal triangle: a systematic approach with the set of circulant operators

This work is devoted to a systematic investigation of triangular matrix forms of the Pascal Triangle. To start, the twelve matrix forms (collectively referred to as G-matrices) are presented. To highlight one way in which the G-matrices relate to each other, a set of four operators named circulant operators is introduced. These operators provide a new insight into the structure of the space of square matrices.
On the Existence of (k,l)-Kernels in Infinite Digraphs: A Survey

Abstract Let D be a digraph, V (D) and A(D) will denote the sets of vertices and arcs of D, respectively. A (k, l)-kernel N of D is a k-independent (if u, v ∈ N, u 6= v, then d(u, v), d(v, u) ≥ k) and l-absorbent (if u ∈ V (D) − N then there exists v ∈ N such that d(u, v) ≤ l) set of vertices. A k-kernel is a (k, k −1)-kernel. This work is a survey of results proving sufficient conditions for the existence of (k, l)-kernels in infinite digraphs. Despite all the previous work in this direction was done for (2, 1)-kernels, we present many original results concerning (k, l)-kernels for distinct values of k and l. The original results are sufficient conditions for the existence of (k, l)- kernels in diverse families of infinite digraphs. Among the families that we study are: transitive digraphs, quasi-transitive digraphs, right/left pretransitive digraphs, cyclically k-partite digraphs, κ-strong digraphs, k-transitive digraphs, k-quasi-transitive digraphs
Detection of microbubble formation during radiofrequency ablation using phonocardiography.

AIMS To detect and characterize the acoustic energy generated by microbubble (MB) formation in an isolated tissue preparation. MB formation during radiofrequency (RF) ablation indicates excessive tissue heating and may precede explosive 'pops'. Currently, MB formation can only be detected with echocardiography. We hypothesized that MB formation can be detected with high-sensitivity phonocardiography. METHODS AND RESULTS In a saline bath, RF lesions were created in sections of porcine left ventricle, using a 4 mm tip irrigated catheter. MB formation was visualized with an echocardiography probe. In 20 preparations, RF energy was begun at 25 W and increased by 5 W every 20 s until a pop occurred. A high-sensitivity computerized phonocardiography transducer with frequency bandwidth of 2 kHz and system noise -90 dB (SonoMedica, Inc., Vienna, VA, USA) was coupled to the external glass wall of the bath. In 15 of 20 (75%) preparations, a characteristic acoustic signature corresponding to MB formation was noted before the pop. These signals were within the 600-2000 Hz range and had an intensity range of 10-40 dB. The earliest MB and acoustic signals occurred 51.3+/-51.5 s before the pop. The acoustic signals continued intermittently up to 10.3+/-12.9 s before the pop. CONCLUSION The acoustic energy created by MB formation can be detected in an isolated tissue preparation, using a computer-based phonocardiography system. Characteristic acoustic signatures are present before pops and correspond to MB formation. Acoustic monitoring for MB formation may allow for the titration of cooled RF ablation without echocardiography.
Analysis of Emittance Growth and Complex Impedance for Coherent Synchrotron Radiation Shielded by Two Parallel Plates

Self-interaction of electron bunch in circular motion is numerically studied. It has been shown that the selfinteraction is expressed in terms of Lienard-Wiechert potential formula and can be calculated with threedimensional particle tracking. The relation between shielded radiation force and complex impedance of beam pipe is also discussed.
Automatic Detection of the Fovea and Optic Disk in Digital Retinal Images by Combining Algorithms

Diabetic retinopathy (DR) is the damage to the eye’s retina that occurs with long-term diabetes, which can eventually lead to blind ness. Screening programs for DR are being introduced, however, an important prerequisite for automation is the accurate location of the main anatomical features in the image, notably the optic disc (OD) and the macula. A series of interesting algorithms have been proposed in the recent past and the performance is generally good, but each method has situations, where it fails. This paper presents a combining framework for automatic detection of optic disc and macula in retinal fundus images using a combination of different optic disc and macula detectors. The extensive tests have shown that combining the detectors is more accurate than any of the individual detectors making up the ensemble.
THE SPATIALLY RESOLVED COOLING LINE DEFICIT IN GALAXIES

We present [C ii] 158 μm measurements from over 15,000 resolved regions within 54 nearby galaxies of the Kingfish program to investigate the so-called [C ii] “line-cooling deficit” long known to occur in galaxies with different luminosities. The [C ii]/TIR ratio ranges from above 1% to below 0.1% in the sample, with a mean value of 0.48 ± 0.21%. We find that the surface density of 24 μm emission dominates this trend, with [C ii]/TIR dropping as increases. Deviations from this overall decline are correlated with changes in the gas-phase metal abundance, with higher metallicity associated with deeper deficits at a fixed surface brightness. We supplement the local sample with resolved [C ii] measurements from nearby luminous infrared galaxies and high-redshift sources from z = 1.8–6.4, and find that star formation rate density drives a continuous trend of deepening [C ii] deficit across six orders of magnitude in . The tightness of this correlation suggests that an approximate can be estimated directly from global measurements of [C ii]/TIR, and a relation is provided to do so. Several low-luminosity active galactic nucleus (AGN) hosts in the sample show additional and significant central suppression of [C ii]/TIR, but these deficit enhancements occur not in those AGNs with the highest X-ray luminosities, but instead those with the highest central starlight intensities. Taken together, these results demonstrate that the [C ii] line-cooling line deficit in galaxies likely arises from local physical phenomena in interstellar gas.