Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Algorithm for Vehicle Routing Problems with Capacity Limited Based on Minimum Spanning Tree

An optimized strategy is proposed to investigate the vehicle routing problems. We build here a Conversion of the Complex road network with minimum spanning trees and decision to search the nearest approach. An algorithm is developed to obtain min-spanning from spanning trees. By tagging the min-spanning tree, we obtain the optimized route such that the cycle capacity keeps minimum value. The corresponding algorithm is realized with the Development tool of Jbuilder 9, which shows that our algorithm proposed here is valid and concise, and simplifies the complexity of previous results.
Inertial parameter identification including friction and motor dynamics

Identification of inertial parameters is fundamental for the implementation of torque-based control in humanoids. At the same time, good models of friction and actuator dynamics are critical for the low-level control of joint torques. We propose a novel method to identify inertial, friction and motor parameters in a single procedure. The identification exploits the measurements of the PWM of the DC motors and a 6-axis force/torque sensor mounted inside the kinematic chain. The partial least-square (PLS) method is used to perform the regression. We identified the inertial, friction and motor parameters of the right arm of the iCub humanoid robot. We verified that the identified model can accurately predict the force/torque sensor measurements and the motor voltages. Moreover, we compared the identified parameters against the CAD parameters, in the prediction of the force/torque sensor measurements. Finally, we showed that the estimated model can effectively detect external contacts, comparing it against a tactile-based contact detection. The presented approach offers some advantages with respect to other state-of-the-art methods, because of its completeness (i.e. it identifies inertial, friction and motor parameters) and simplicity (only one data collection, with no particular requirements).
Noncommutative Cohomological Field Theories and Topological Aspects of Matrix models

We study topological aspects of matrix models and noncommutative cohomological field theories (N.C.CohFT). N.C. CohFT have symmetry under an arbitrary infinitesimal deformation with noncommutative parameter �. This fact implies that N.C. CohFT are topologically less sensitive than K-theory, but the classification of manifolds by N.C. CohFT opens the possibility to get a new view point for global characterization of noncommutative manifolds. To investigate the properties of N.C. CohFT, we construct some models whose fixed point loci are given by sets of projection operators. In particular, the partition function on the Moyal plane is calculated by using a matrix model. The moduli space of the matrix model is a union of Grassman manifolds. The partition function of the matrix model is calculated using the Euler number of the Grassman manifold. Identifying the N.C. CohFT with the matrix model, we obtain the partition function of the N.C. CohFT. To check the independence of the noncommutative parameters, we also study the moduli space
Real-time crowd motion analysis

Video-surveillance systems are becoming more and more autonomous in the detection and the reporting of abnormal events. In this context, this paper presents an approach to detect abnormal situations in crowded scenes by analyzing the motion aspect instead of tracking subjects one by one. The proposed approach estimates sudden changes and abnormal motion variations of a set of points of interest (POI). The number of tracked POIs is reduced using a mask that corresponds to hot areas of the built motion heat map. The approach detects events where local motion variation is important compared to previous events. Optical flow techniques are used to extract information such as density, direction and velocity. To demonstrate the interest of the approach, we present the results on the detection of collapsing events in real videos of airport escalator exits.
Refractive error, axial dimensions, and primary open-angle glaucoma: the Singapore Malay Eye Study.

OBJECTIVE To explore the relationship of refractive error and ocular biometry with primary open-angle glaucoma (POAG) in the Malay population. METHODS The Singapore Malay Eye Study is a population-based cross-sectional survey that examined 3280 persons (78.7% response) aged 40 to 80 years. Participants underwent a standardized clinical examination including slitlamp biomicroscopy, Goldmann applanation tonometry, refraction, dilated optic disc assessment, and measurement of axial length (AL) and central corneal thickness (CCT). Glaucoma was defined according to International Society for Geographical and Epidemiological Ophthalmology criteria. RESULTS After adjusting for possible confounders, persons with moderate or high myopia (less than -4.0 diopters, right eyes) were more likely to have POAG (odds ratio [OR], 2.87; 95% confidence interval, 1.09-7.53); this association remained significant after controlling for CCT (2.80; 1.07-7.37). Longer AL was associated with POAG (ORs, 2.49, 3.61, and 2.88, comparing quartiles 2, 3, and 4, respectively, with quartile 1 of AL; P = .03 for trend). If CCT was controlled for, persons with AL in quartile 4 were 3 times more likely to have POAG (OR, 3.00; 95% confidence interval, 1.09-8.24) than those in quartile 1. CONCLUSION This population-based study in Singapore shows an association of moderate myopia and increasing AL with POAG independent of other factors, including CCT.
IONIZED GAS IN THE FIRST 10 kpc OF THE INTERSTELLAR GALACTIC HALO: METAL ION FRACTIONS

We present direct measures of the ionization fractions of several sulfur ions in the Galactic warm ionized medium (WIM). We obtained high-resolution ultraviolet absorption-line spectroscopy of post-asymptotic giant branch stars in the globular clusters Messier 3 [(l, b) = (42.°2, +78.°7), d = 10.2 kpc, and z = 10.0 kpc] and Messier 5 [(l, b) = (3.°9, +46.°8), d = 7.5 kpc, and z = +5.3 kpc] with the Hubble Space Telescope and Far Ultraviolet Spectroscopic Explorer to measure, or place limits on, the column densities of S i, S ii, S iii, S iv, S vi, and H i. These clusters also house millisecond pulsars, whose dispersion measures give an electron column density from which we infer the H ii column in these directions. We find fractions of S+2 in the WIM for the M 3 and M 5 sight lines x(S+2) ≡ N(S+2)/N(S) = 0.33 ± 0.07 and 0.47 ± 0.09, respectively, with variations perhaps related to location. With negligible quantities of the higher ionization states, we conclude that S+ and S+2 account for all of the S in the WIM. We extend the methodology to study the ion fractions in the warm and hot ionized gas of the Milky Way, including the high ions Si+3, C+3, N+4, and O+5. The vast majority of the Galactic ionized gas is warm (T ∼ 104 K) and photoionized (the WIM) or very hot (T > 4 × 105 K) and collisionally ionized. The common tracer of ionized gas beyond the Milky Way, O+5, traces <1% of the total ionized gas mass of the Milky Way.
Split-Belt Walking Alters the Relationship between Locomotor Phases and Cycle Duration across Speeds in Intact and Chronic Spinalized Adult Cats

During overground or treadmill walking, the stance phase and cycle durations are reduced as speed increases, whereas swing phase duration remains relatively invariant. When the speed of the left and right sides is unequal, as is the case during split-belt locomotion or when walking along a circular path, adjustments in stance and swing phases are observed, which could alter the phase/cycle duration relationships. Here, we tested this hypothesis in the left and right hindlimbs of four intact and two chronic spinal-transected adult cats during tied-belt (i.e., equal left and right speeds) and split-belt (i.e., unequal left and right speeds) walking. During split-belt walking, one side (i.e., constant limb) walked at a constant speed while the other side (varying limb) varied its speed from 0.3 to 1.0 m/s. We show that the phase/cycle duration relationships differed in both hindlimbs concurrently during split-belt walking. Specifically, the slope of the phase/cycle duration relationships for the stance/extension phase increased in the varying limb from tied-belt to split-belt walking, whereas that of the swing/flexion phase decreased. In contrast, in the constant limb, the slope of the phase/cycle duration relationships for the stance/extension phase decreased, whereas that of the swing/flexion phase increased. The results were qualitatively similar in intact and spinal-transected cats, indicating that the modulation was mediated within the spinal cord. In conclusion, we propose that neuronal networks within the spinal cord that control left and right hindlimb locomotion can differentially and simultaneously modulate phase variations when the two sides walk at different speeds.
Aligning freebase with the YAGO ontology

Linked Open Data (LOD) has emerged as the de-facto standard for publishing data on the Web. The cross-domain large scale Freebase and YAGO datasets represent central hubs and reference points for the LOD cloud. Freebase is an open-world dataset, which contains about 22 million entities and more than 350 million facts in more than 100 domains. The scale of Freebase makes it difficult for the users to get an overview of the data and efficiently retrieve the desired information. Integration of Freebase with the YAGO ontology that contains more than 360,000 concepts enables us to provide more semantic information for Freebase and to facilitate novel applications, such as efficient query construction, over large scale data. In this paper we analyze the structure of YAGO in more depth and show how to match YAGO and Freebase categories. The new YAGO+F structure that results from our matching tightly connects both datasets and provides an important next step to systematically interconnect LOD subcollections. We make our YAGO+F structure available online in the hope that it can provide a good starting point for future applications, which can build upon a wide variety of Freebase data clearly arranged in the semantic categories of YAGO.
Immediate sleep: Reducing energy impact of peripheral circuits in STT-MRAM caches

Implementing last level caches (LLCs) with STT-MRAM is a promising approach for designing energy efficient microprocessors due to high density and low leakage power of its memory cells. However, peripheral circuits of an STT-MRAM cache still suffer from leakage power because large and leaky transistors are required to drive large write current to STT-MRAM element. To overcome this problem, we propose a new power management scheme called Immediate Sleep (IS). IS immediately turns off a subarray of an STT-MRAM cache if the next access is predicted to be not critical in performance. Thus, IS can effectively reduce leakage energy with little impact on performance. Our experimental results show that our technique can save the leakage energy of an STT-MRAM LLC by 32% compared to an STT-MRAM LLC with the conventional scheme at the same performance.
Representing Verbal Semantics with Diagrams - An Adaptation of the UML for Lexical Semantics

The paper presents a new way of accounting for the meaning of verbs in natural languages, using a diagrammatic notation based on the Unified Modeling Language (UML). We will introduce the new framework by outlining some modeling elements and indicating major differences to the UML. An extended example will be discussed in more detail. We will then focus on the cognitive background of the framework, and in particular address the question why the usage of graphical elements within a linguistic modeling language proves to be very fruitful. Finally, we will briefly indicate the potential of the new framework and its applicability.
Dimerization of SLX4 contributes to functioning of the SLX4-nuclease complex

Abstract The Fanconi anemia protein SLX4 assembles a genome and telomere maintenance toolkit, consisting of the nucleases SLX1, MUS81 and XPF. Although it is known that SLX4 acts as a scaffold for building this complex, the molecular basis underlying this function of SLX4 remains unclear. Here, we report that functioning of SLX4 is dependent on its dimerization via an oligomerization motif called the BTB domain. We solved the crystal structure of the SLX4BTB dimer, identifying key contacts (F681 and F708) that mediate dimerization. Disruption of BTB dimerization abrogates nuclear foci formation and telomeric localization of not only SLX4 but also of its associated nucleases. Furthermore, dimerization-deficient SLX4 mutants cause defective cellular response to DNA interstrand crosslinking agent and telomere maintenance, underscoring the contribution of BTB domain-mediated dimerization of SLX4 in genome and telomere maintenance.
Do syntopic host species harbour similar symbiotic communities? The case of Chaetopterus spp. (Annelida: Chaetopteridae)

To assess whether closely related host species harbour similar symbiotic communities, we studied two polychaetes, Chaetopterus sp. (n = 11) and Chaetopterus cf. appendiculatus (n = 83) living in soft sediments of Nhatrang Bay (South China Sea, Vietnam). The former harboured the porcellanid crabs Polyonyx cf. heok and Polyonyx sp. , the pinnotherid crab Tetrias sp. and the tergipedid nudibranch Phestilla sp. The latter harboured the polynoid polychaete Ophthalmonoe pettiboneae, the carapid fish Onuxodon fowleri and the porcellanid crab Eulenaios cometes, all of which, except O. fowleri, seemed to be specialized symbionts. The species richness and mean intensity of the symbionts were higher in Chaetopterus sp. than in C. cf. appendiculatus (1.8 and 1.02 species and 3.0 and 1.05 individuals per host respectively). We suggest that the lower density of Chaetopterus sp. may explain the higher number of associated symbionts observed, as well as the 100% prevalence (69.5% in C. cf. appenciculatus). Most Chaetopterus sp. harboured two symbiotic species, which was extremely rare in C. cf. appendiculatus, suggesting lower interspecific interactions in the former. The crab and nudibranch symbionts of Chaetopterus sp. often shared a host and lived in pairs, thus partitioning resources. This led to the species coexisting in the tubes of Chaetopterus sp. , establishing a tightly packed community, indicating high species richness and mean intensity, together with a low species dominance. In contrast, the aggressive, strictly territorial species associated with C. cf. appendiculatus established a symbiotic community strongly dominated by single species and, thus, low species richness and mean intensity. Therefore, we suggest that interspecific interactions are determining species richness, intensity and dominance, while intraspecific interactions are influencing only intensity and abundance. It is possible that species composition may have influenced the differences in community structure observed. We hypothesize that both host species could originally be allopatric. The evolutionary specialization of the symbiotic communities would occur in separated geographical areas, while the posterior disappearance of the existing geographical barriers would lead to the overlapped distribution.
Detection of black hole attack in wireless sensor network using UAV

Recently, unmanned aerial vehicles (UAVs) has been proposed for effective data propagation and collection in wireless sensor networks (WSNs). In this paper, we use UAV for detecting black hole attack in WSN. Black hole attack is accomplished by malicious nodes that advertise their route to the intended destination as the shortest and optimized one, therefore, they gather most of the network traffic and then drop all packets. This attack results in loss of critical information on the network. We propose a method to overcome this problem with a shorter running time in comparison to other methods and detect malicious nodes with higher probability. UAV is used for checking nodes and Sequential Probability Ratio Test method as a dynamic threshold scheme for blocking malicious nodes. Simulations and analyses show that our proposed technique achieves effective and fast detection of black hole attack with acceptable energy consumption.
Sound Ontology for Computational Auditory Scence Analysis

This paper proposes that sound ontology should be used both as a common vocabulary for sound representation and as a common terminology for integrating various sound stream segregation systems. Since research on computational auditory scene analysis (CASA) focuses on recognizing and understanding various kinds of sounds, sound stream segregation which extracts each sound stream from a mixture of sounds is essential for CASA. Even if sound stream segregation systems use a harmonic structure of sound as a cue of segregation, it is not easy to integrate such systems because the definition of a harmonic structure differs or the precision of extracted harmonic structures differs. Therefore, sound ontology is needed as a common knowledge representation of sounds.Another problem is to interface sound stream segregation systems with applications such as automatic speech recognition systems. Since the requirement of the quality of segregated sound streams depends on applications, sound stream segregation systems must provide a flexible interface. Therefore, sound ontology is needed to fulfill the requirements imposed by them. In addition, the hierarchical structure of sound ontology provides a means of controlling top-down and bottom-up processing of sound stream segregation.
Geometrically Constrained RANSAC for Stereo Image Registration in Presence of High Ambiguity in Feature Correspondence

An approach for registration of sparse feature sets detected in two stereo image pairs taken from two different views is proposed. Analogously to many existing image registration approaches, our method consists of initial matching of features using local descriptors followed by a RANSAC-based procedure. The proposed approach is especially suitable for cases where there is a high percentage of false initial matches. The strategy proposed in this paper is to modify the hypothesis generation step of the basic RANSAC approach by performing a multiplestep procedure which uses geometric constraints in order to reduce the probability of false correspondences in the hypothesis. The algorithm needs approximate information about the relative camera pose between the two views obtained e.g. by odometry. However, the uncertainty of this information is allowed to be rather high. The presented technique is evaluated using both synthetic data and real data obtained by a stereo camera system.
Degrees of Freedom in the MISO BC with delayed-CSIT and finite coherence time: Optimization of the number of users

Most techniques designed for the multi-input single-output (MISO) Broadcast Channel (BC) require accurate current channel state information at the transmitter (CSIT). A different approach has been proposed by Maddah-Ali and Tse (MAT), in which significant increase of the multiplexing gain can be obtained by solely relying on perfect but outdated CSIT. This approach is proven to yield the optimal multiplexing gain when the curent channel state is completely independent of the fed back channel state. Recent work focused on an intermediate case: channels exhibiting some temporal correlation, or equivalently in the block fading model, feedback delays being smaller than the coherence time. We propose modified versions of different schemes for the MISO BC with delayed CSIT in which the number of users to serve is optimized in order to maximize the multiplexing gain when accounting for (CSI acquisition) overhead. Indeed, as the coherence time decreases, CSI acquisition overhead starts to dominate and a reduced number of active users (and hence active Base Station antennas) leads to a better compromise. We consider the MAT scheme, the traditional Zero Forcing (ZF) beamforming scheme, and combinations such as MAT-ZF and TDMA-ZF.
Interactive visualization of the social network of research collaborations

Social networks have been evolving over the past few years, leading to a rapid increase in the number and complexity of relationships among their entities. In this paper, we focus on a large scale dataset known as the Digital Bibliography and Library Project (DBLP), which contains information on all publications that have been published in computer and information science related journals and conference proceedings. We model the DBLP dataset as a social network of research collaborations. DBLP is a structured and dynamic dataset stored in the XML file format; it contains over 850,000 authors and 2 million publications and the resulting collaboration social network is a scale-free network. We define DBLP collaboration social network as a graph that consists of researchers as nodes and links representing the collaboration among the researchers. In this work, we implement a data analysis algorithm called Multidimensional Scaling (MDS) to represent the degree of collaboration among the DBLP authors as Euclidean distances in order to analyze, mine and understand the relational information in this large scale network in a visual way. MDS requires a highly computational complexity for large scale graphs such as the DBLP graph. Therefore, we propose different solutions to overcome this problem, and improve the MDS performance. In addition, as the quality of the MDS result is measured by a metric known as the stress value, we use the steepest descent method to minimize the stress in an iterative process called stress optimization in order to generate the best geometric layout of the graph. We also propose a solution to further enhance the graph visualization by partitioning the graph into sub-graphs and using repelling forces among nodes within the same sub-graph.
Statistical modelling of causal effects in continuous time

This article studies the estimation of the causal effect of a time-varying treatment on time-to-an-event or on some other continuously distributed outcome. The paper applies to the situation where treatment is repeatedly adapted to time-dependent patient characteristics. The treatment effect cannot be estimated by simply conditioning on these time-dependent patient characteristics, as they may themselves be indications of the treatment effect. This time-dependent confounding is common in observational studies. Robins (1992, 1998) has proposed the so-called structural nested models to estimate treatment effects in the presence of time-dependent confounding. In this article we provide a conceptual framework and formalization for structural nested models in continuous time. We show that the resulting estimators are consistent and asymptotically normal. Moreover, as conjectured in Robins (1998), a test for whether treatment affects the outcome of interest can be performed without specifying a model for treatment effect. We illustrate the ideas in this article with an example.
Bearing Faults Classification Using THH and Neural Network

The induction machine has many advantages: its specific power, its strength, relatively low manufacturing cost and minimal maintenance. But despite all these qualities, a number of faults can affect the life of the machine showing premature failures. The purpose of preventive maintenance in real time, we introduce a new signal processing technique based on Hilbert-Huang Transform (HHT) and marginal spectrum. Firstly, the current signals are decomposed into several intrinsic mode function (IMFs) using the empirical mode decomposition (EMD). The Hilbert Huang spectrum for each IMF is an energy representation in the time-frequency domain using the instantaneous frequency. The marginal spectrum of each IMF can then be obtained. The next step is the classification of faults detected by the application of neural network on IMFs. Tests on real signals show that the marginal spectrum of the second IMFs can be used for the detection and classification of bearing faults. The proposed approach provides a viable signal processing tool for an online machine health status monitoring.