Miracle-dz/UniFAR-FTUs huggingface dataset:
Tonotopic Organization of the Cat Auditory Cortex for Some Complex Stimuli

There is psychophysical evidence that both spectrum and periodicity of acoustic signals may be cues for pitch judgments. At the level of the auditory nerve, these stimulus characteristics seem to be coded in terms of place and time pattern. Very little is known of their representation higher levels of the nervous system. Tonotopic organization of the auditory cortex has been demonstrated in anesthetized cats by the evoked strychnine potential technique. In these demonstrations only tonal stimuli were used. We use similar physiological preparations but employ acoustic stimuli that permit independent manipulation of spectrum and periodicity. The results show that the previously reported tonotopic organization is based only upon spectral characteristics of the stimulus.
Tensor Networks in Condensed Matter

This thesis is devoted to the study of quantum many-body systems. This investigation is performed in the framework of Matrix Product States (MPS) and their generalization to higher dimensions, Projected Entangled Pair States (PEPS). In the first part of the work, we discuss the mathematical properties of such tensor network states in depth. In the first chapters we deal with one-dimensional systems, for which we use the connections between MPS and completely positive maps to prove several new results, such as the quantum version of the Wielandt's inequality or the construction of locally invariant states under a symmetry group. Chapters 5-7 are dedicated to higher-dimensional systems, for which we provide the conditions to construct invariant PEPS. The second part of the thesis is dedicated to applications in condensed matter. In chapter 8 we provide several methods of constructing quasi-solvable Hamiltonians with two-body interactions, while in chapter 9 we show that these tensor network states can be used as a laboratory for theoretical condensed matter in, for instance, the characterization of the string-order, the generalization of the Lieb-Schultz-Mattis theorem, the demonstration of new theorems relating entanglement to magnetisation or to long-range interactions, etc.
Error bound of hypothesis testing with data compression

We discuss hypothesis testing with data compression in a multiterminal system. This case is different from the usual statistical case which can be solved using Stein's lemma. We give a lower bound on the exponent of hypothesis testing error which is better than the bounds which have been previously derived, and give the sufficient rate for achieving Stein's lemma. The lower-bound is obtained by constructing an encoding-decoding system. <<ETX>>
Multiplicative Adjustment Method for Semiparametric Regression with Mixing Dependent Data

In this article, we extend a semiparametric regression estimator with multiplicative adjustment to time series context. The asymptotic theory and results from a simulation study are discussed. Theoretical results and numerical comparison show that, in the time series case, the semiparametric estimator is better than the traditional local polynomial estimator in a wide neighbourhood around the true regression function.
Disturbance Attenuation for Beam Equations Using Stiffness Control

The paper presents a control method for disturbance attenuation of a rotating flexible beam using strain feedback. It is shown that the strain feedback, if appropriately used, can increase the stiffness of the flexible beam and, thus, attenuate external disturbances. The disturbance responses of the feedback controlled closed‐loop equation are also derived, and simulation results are provided to demonstrate the effect of the proposed control law.
A new model for the amplitude statistics of SAR imagery

We introduce a new statistical distribution for modeling nonRayleigh amplitude statistics. We call the new model the Rician Inverse Gaussian (RiIG) distribution. The theoretical basis of the model is briefly presented, and we give an EM-type algorithm for estimating its parameters from data. Finally, we include some modeling examples, where we have tested the ability to fit to histograms of segments of single-look SAR data.
Experimental investigation of jets in a crossflow

The paper reports on measurements in the flow generated by a jet issuing from a circular outlet in a wall into a cross-stream along this wall. For the jet-to-crossflow velocity ratios R of 0.5, 1 and 2, the mean and fluctuating velocity components were measured with a three-sensor hot-wire probe. The hot-wire signals were evaluated to yield the three mean-velocity components, the turbulent kinetic energy, the three turbulent shear stresses and, in the case of R = 0.5, the terms in the turbulent-kinetic-energy equation. The results give a quantitative picture of the complex three-dimensional mean flow and turbulence field, and the various phenomena as well as their dependence on the velocity ratio R are discussed in detail.
Variational and Gibbs Inference for Generative Human Body Tracking

Most approaches to high-dimensional (circa 30D) human body tracking cast the problem as one of approximate inference in a statistical time-series system. In turn, most of these approaches utilise particle filtering (also known as Sequential Monte Carlo sampling) to perform approximate inference. However, filtering estimates the posture state at time t by taking into account only those observations leading up to t. In contrast, it is possible to perform inference for time t using both the past and future observations, such as by introducing a small lag or processing off-line. Incorporating future evidence into a filtered estimate is called smoothing, and is in fact the norm for many other fields such as speech recognition or action recognition. However, aside from particle-based smoothers, existing smoothed-inference algorithms face obstacles in being applied to generative body tracking, notably the high cost and heuristic nature of evaluating the observations. This paper proposes a method to overcome these obstacles by approximating the observation likelihood function with a more manageable Gaussian mixture, and derives mixture-based body tracking systems for two popular approximate inference algorithms: variational methods and Gibbs sampling.
A NEW PRECONDITIONING STRATEGY FOR SOLVING A CLASS OF TIME-DEPENDENT PDE-CONSTRAINED OPTIMIZATION PROBLEMS *

In this paper, by exploiting the special block and sparse structure of the coefficient matrix, we present a new preconditioning strategy for solving large sparse linear systems arising in the time-dependent distributed control problem involving the heat equation with two different functions. First a natural order-reduction is performed, and then the reduced-order linear system of equations is solved by the preconditioned MINRES algorithm with a new preconditioning techniques. The spectral properties of the preconditioned matrix are analyzed. Numerical results demonstrate that the preconditioning strategy for solving the large sparse systems discretized from the time-dependent problems is more effective for a wide range of mesh sizes and the value of the regularization parameter.
Divergent selection in Mediterranean pine stands on local spatial scales

The effects of selection on an organism’s genome are hard to detect on small spatial scales, as gene flow can erase signatures of local adaptation. Most genome scans to detect signatures of environmental selection are performed on large spatial scales, however divergent selection on the local scale (e.g. between contrasting soil conditions) has also been demonstrated, in particular for herbaceous plants. Here we hypothesize that in topographically complex landscapes, microenvironment variability is strong enough to leave a selective footprint in genomes of long-lived organisms. To test this, we investigated paired south- versus north-facing Pinus pinaster stands in a Mediterranean mountain area. While north-facing (mesic) stands experience less radiation, south facing (xeric) stands represent especially harsh conditions, particularly during the dry summer season. Outlier detection revealed five putatively adaptive loci out of 4,034, two of which encoded non-synonymous substitutions. Additionally, one locus showed consistent allele frequency differences in all three stand pairs indicating divergent selection despite high gene flow on the local scale. Functional annotation of these candidate genes revealed biological functions related to abiotic stress response in other species. Our study highlights how divergent selection shapes the functional genetic variation within populations of long-lived forest trees on local spatial scales.
A critical role of VEGFR2 in lymphatic tumor metastasis

Vascular endothelial growth factor receptor-2 (VEGFR2) transduces crucial signals for blood vessel growth but its role in the lymphatic system remains incompletely elucidated. By employing genetic mouse models targeting Vegfr2 in either pan-endothelial cells (ECs) or lymphatic endothelial cells (LECs), we examined roles of VEGFR2 in lymphangiogenesis and in tumor progression. VEGFR2 was differentially expressed in the murine lymphatic system and particularly marked in valves of collecting vessels. The pan-endothelial Vegfr2 deletion (Vegfr2iECKO) reduced the dermal lymphatic growth, and a significant decrease in lymphatic valves of pre-collectors was observed in mice with the LEC-specific attenuation of VEGFR2 (Vegfr2iLECKO). Furthermore, while the primary growth of subcutaneously implanted Lewis lung carcinoma was unaffected in the Vegfr2iLECKO mouse model, the tumor metastasis to sentinel lymph nodes was efficiently suppressed. In accordance, the tumor-associated lymphangiogenesis was decreased in the Vegfr2iLECKO mice compared with the control. Findings from this study imply that the lymphatic VEGFR2 regulates valve morphogenesis and promotes lymph node metastasis by regulating the tumor-associated lymphatic formation.
Small Chamber Ideal Point Estimation

Ideal point estimation is a topic of central importance in political science. Published work relying on the ideal point estimates of Poole and Rosenthal for the U.S. Congress is too numerous to list. Recent work has applied ideal point estimation to the state legislatures, Latin American chambers, the Supreme Court, and many other chambers. Although most existing ideal point estimators perform well when the number of voters and the number of bills is large, some important applications involve small chambers. We develop an estimator that does not suffer from the incidental parameters problem and, hence, can be used to estimate ideal points in small chambers. Our Monte Carlo experiments show that our estimator offers an improvement over conventional estimators for small chambers. We apply our estimator to estimate the ideal points of Supreme Court justices in a multidimensional space.
Parental partnership and joblessness in childhood and their influence on young people's outcomes

Summary. The paper estimates the relationship between several outcomes in early adulthood (education, inactivity, early birth, distress and smoking) and experiences of life in a single‐parent family and with jobless parent(s) during childhood. The analysis is performed using a sample of young adults, who are selected from the first nine waves of the British Household Panel Survey (1991–1999) and can be matched with at least one parent and one sibling over the same period. This sample allows us to estimate the relationship of interest by using sibling differences. We also use another sample of young adults from the British Household Panel Survey, matched to at least one parent, to estimate more conventional level models and to compute nonparametric bounds and point estimates. The estimates based on sibling differences require weaker assumptions (compared with the assumptions that are imposed by nonparametric estimators under conditional independence and level estimators) for the identification of the effects of family structure and parental joblessness on the outcomes under analysis. We find that experiences of life in a single‐parent family and with jobless parents during childhood are usually associated with disadvantageous outcomes for young adults, the effect of family structure is in general significantly greater (in absolute value) than the effect of parental worklessness and most of the unfavourable outcomes are linked to an early family disruption, when the child was aged 0–5 years, whereas the timing of parental joblessness during childhood has more complex effects, with different outcomes being more strongly influenced by parental worklessness at different ages of the child.
Closed-loop convex analysis of performance limits for linear control systems

Closed-loop convex analysis and design, in which the linear controller design problem is reformulated as a convex optimization problem that may be more easily solved than the problems resulting from conventional formulations, are discussed. This reformulation synthesizes control laws that have high degree, but nevertheless can be implemented using digital signal processors. The solution is rarely expressed in a closed form, but nevertheless is readily computable. Some of the basic ideas of closed-loop convex analysis and design are described in general terms. <<ETX>>
A multi-scale review of the dynamics of collective behaviour: from rapid responses to ontogeny and evolution

Collective behaviours, such as flocking in birds or decision making by bee colonies, are some of the most intriguing behavioural phenomena in the animal kingdom. The study of collective behaviour focuses on the interactions between individuals within groups, which typically occur over close ranges and short timescales, and how these interactions drive larger scale properties such as group size, information transfer within groups and group-level decision making. To date, however, most studies have focused on snapshots, typically studying collective behaviour over short timescales up to minutes or hours. However, being a biological trait, much longer timescales are important in animal collective behaviour, particularly how individuals change over their lifetime (the domain of developmental biology) and how individuals change from one generation to the next (the domain of evolutionary biology). Here, we give an overview of collective behaviour across timescales from the short to the long, illustrating how a full understanding of this behaviour in animals requires much more research attention on its developmental and evolutionary biology. Our review forms the prologue of this special issue, which addresses and pushes forward understanding the development and evolution of collective behaviour, encouraging a new direction for collective behaviour research. This article is part of a discussion meeting issue ‘Collective behaviour through time’.
A Turbulence Model for the Three-Dimensional Vortex Blob Method.

The purpose of this paper is to propose a turbulence model for the three-dimensional vortex blob method. This model uses a modified version of the core-spreading method introduced by Leonard and Chua (1989) in the spirit of the Smagorinsky type of eddy viscosity. The diffusion of vorticity by the molecular viscosity is represented by the core spreading whose rate is approximated by that of a rectilinear viscous vortex tube. The linear combination of the two viscosities yields a Lagrangian turbulence model, which includes the effects of Reynolds number. We apply each model to an impulsively started round jet forced by two helical disturbances rotating in counter directions and compare the vortical structures of the jet among the models to show that the combined model can be a reasonable turbulence model.
Use of SAW devices to monitor viscoelastic properties of materials

Preliminary data are presented which demonstrate the potential sensitivity of SAW (surface acoustic wave) to the elastic properties of polymer coatings. 158-MHz dual SAW devices were used to demonstrate the sensitivity of the SAW to changes in coating elastic properties, and to identify the T/sub g/ and/or T/sub m/ of several polymer coatings. Data for PCAP (poly(caprolactone)) and FPOL (fluoropolyol) indicate that the SAW frequency is sensitive to changes in the shear modulus of the coatings. The steady decrease in frequency with increased temperature observed for FPOL-coated devices may be the result of increased surface coverage due to expansion of the film. Increased surface coverage would result in an increase in surface wave interaction with the film and a corresponding steady decrease in frequency. This indicates that these polymer films may not be true lossless films. It is suggested that in light of this, previous assumptions made in the development of predictive equations using SAW data must be reevaluated. It is concluded that the sensitivity of SAWs to elastic properties is indicative of their potential as monitors for cure processes, or other applications where changes in the elasticity of materials are of interest. <<ETX>>
A Primal Barvinok Algorithm Based on Irrational Decompositions

We introduce variants of Barvinok’s algorithm for counting lattice points in polyhedra. The new algorithms are based on irrational signed decomposition in the primal space and the construction of rational generating functions for cones with low index. We give computational results that show that the new algorithms are faster than the existing algorithms by a large factor.
Stochastic stability of Bernoulli toral linked twist maps of finite and infinite entropy

Abstract We construct linked twist maps of the two-dimensional torus which are Bernoulli and possess infinite entropy. Inparticular, we construct a Bernoulli toral linked twist map B* of infinite entropy which has smooth, absolutely continuous local (un)stable manifolds and positive Lyapunov exponents defined almost everywhere. This map is continuous at each point save those on two line segments. B* is shown to be stochastically stable under the following random perturbation: apply the map to a point p and then jump (all points move the same distance and in the same direction) according to a B-process (not necessarily an independent process) such that the expected distance moved is equal to r. Stochastic stability means that given α > 0 if r > 0 is sufficiently small then the perturbed and unperturbed systems are α-congruent. We prove a similar stability result for B* under a perturbation in which the random jump described above is distributed according to a general stochastic process. These stability results are also shown to hold (in a slightly modified form) for a general class of finite-entropy toral linked twist maps under the same perturbations.
Inferring social influence in animal groups across multiple timescales

Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue ‘Collective behaviour through time’.
Inversion of controlled-source seismic tomography and gravity data with the self-adaptive wavelet parametrization of velocities and interfaces

SUMMARY A self-adaptive automated parametrization approach is suggested for the sequential inversion of controlled-source seismic tomography and gravity data. The velocities and interfaces are parametrized by their Haar wavelet expansion coefficients. Only those coefficients that are well constrained by the data, as measured by the number of rays that cross the corresponding wavelet function support area and their angular coverage, are inverted for, others are set to zero. This approach results in a reasonable distribution of resolution throughout the model even in cases of irregular ray coverage and does overcome the trade-off between different types of model parameters. A modified sequential inversion approach is suggested to join the traveltimes and gravity anomalies inversion. An algorithm is developed that inverts for smooth velocity and density variations inside the seismic layer, the position of its bottom interface as well as for optimal values of the velocity-to-density regression coefficients. The algorithm makes use of direct (diving), reflected and head (critically refracted) wave traveltimes. The algorithm workflow is demonstrated on a synthetic data example.
Turbulent velocity fields in smoothed particle hydrodymanics simulated galaxy clusters: scaling laws for the turbulent energy

We present a study of the turbulent velocity fields in the intracluster medium (ICM) of a sample of 21 galaxy clusters simulated by the smoothed particle hydrodynamics code GADGET2, using a new numerical scheme where the artificial viscosity is suppressed outside shocks. The turbulent motions in the ICM of our simulated clusters are detected with a novel method devised to better disentangle laminar bulk motions from chaotic ones. We focus on the scaling law between the turbulent energy content of the gas particles and the total mass, and find that the energy in the form of turbulence scales approximately with the thermal energy of clusters. We follow the evolution with time of the scaling laws and discuss the physical origin of the observed trends. The simulated data are in agreement with independent semi-analytical calculations, and the combination between the two methods allows one to constrain the scaling law over more than two decades in cluster mass.
Simulation of CFAR detection algorithms for arbitrary clutter distributions

Simulation and performance estimation methodologies are developed for constant false-alarm rate (CFAR) detection algorithms based on the powerful concept of importance sampling (IS). Such algorithms involve crossings of a random threshold. Compression of the threshold density function produces the required biasing to implement IS procedures. Adaptive optimisation of simulation estimators and estimation of detector threshold multipliers are described. Easily computable approximations for false-alarm probabilities (FAPs) of cell averaging (CA)-CFAR detectors are derived. Fast simulation results are described for examples with known clutter distributions. The practically important situation when clutter densities are unknown is dealt with. Algorithms blind to the density and having appreciable gains over conventional Monte Carlo simulation are demonstrated. In a limited experiment these are shown to track a step change in clutter distribution. It is argued, albeit tentatively, that the procedures could point the way to implementation of estimators for FAPs and their control through threshold adaptation.