Miracle-dz/UniFAR-FTUs huggingface dataset:
Discovering Latent Information By Spreading Activation Algorithm For Document Retrieval

Syntactic search relies on keywords contained in a query to find suitable documents. So, documents that do not contain the keywords but contain information related to the query are not retrieved. Spreading activation is an algorithm for finding latent information in a query by exploiting relations between nodes in an associative network or semantic network. However, the classical spreading activation algorithm uses all relations of a node in the network that will add unsuitable information into the query. In this paper, we propose a novel approach for semantic text search, called query-oriented-constrained spreading activation that only uses relations relating to the content of the query to find really related information. Experiments on a benchmark dataset show that, in terms of the MAP measure, our search engine is 18.9% and 43.8% respectively better than the syntactic search and the search using the classical constrained spreading activation.
Parsimonious rule generation for a nature-inspired approach to self-assembly

Most construction of artificial, multicomponent structures is based upon an external entity that directs the assembly process, usually following a script/blueprint under centralized control. In contrast, recent research has focused increasingly on an alternative paradigm, inspired largely by the nest building behavior of social insects, in which components “self-assemble” into a given target structure. Adapting such a nature-inspired approach to precisely self-assemble artificial structures (bridge, building, etc.) presents a formidable challenge: one must create a set of local control rules to direct the behavior of the individual components/agents during the self-assembly process. In recent work, we developed a fully automated procedure that generates such rules, allowing a given structure to successfully self-assemble in a simulated environment having constrained, continuous motion; however, the resulting rule sets were typically quite large. In this article, we present a more effective methodology for automatic rule generation, which makes an attempt to parsimoniously capture both the repeating patterns that exist within a structure, and the behaviors necessary for appropriate coordination. We then empirically show that the procedure developed here generates sets of rules that are not only correct, but significantly reduced in size, relative to our earlier approach. Such rule sets allow for simpler agents that are nonetheless still capable of performing complex tasks, and therefore demonstrate the problem-solving potential of self-organized systems.
The onset of star formation in primordial haloes

Context. Star formation remains an unsolved problem in astrophysics. Numerical studies of large-scale structure simulations c annot resolve the process and their approach usually assumes that only gas denser than a typical threshold can host and form stars. Aims. We investigate the onset of cosmological star formation and compare several very-high-resolution, three-dimensional, Nbody/SPH simulations that include non-equilibrium, atomic and molecular chemistry, star formation prescriptions, and fee dback effects. Methods. We study how primordial star formation depends on gas density threshold, cosmological parameters, and initial set-ups . Results. For mean-density initial conditions, we find that standard l ow-density star-formation threshold (0.2 h 2 cm −3 ) models predict the onset of star formation at z∼ 25− 31, depending on the adopted cosmology. In these models, stars are formed automatically when the gas density increases above the adopted threshold, regardless of the time between the moment when the threshold is reached and the effective runaway collapse. While this is a reasonable approximation at low redshift, at high redshift this time interval r epresents a significant fraction of the Hubble time and thus this assump tion can induce large artificial o ffsets to the onset of star formation. Choosing higher density thresholds (135 h 2 cm −3 ) allows the entire cooling process to be followed, and the onset of star formation is then estimated to be at redshift z∼ 12− 16. When isolated, rare, high-density peaks are considered, the chemical evolution is much faster and the first star formation episodes occur at z& 40, almost regardless of the choice of the density threshold. Conclusions. These results could have implications for the formation redshift of the first cosmological objects, as inferred from dir ect numerical simulations of mean-density environments and studies of the reionization history of the universe.
Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex

Simple cells in the primary visual cortex process incoming visual information with receptive fields localized in space and time, bandpass in spatial and temporal frequency, tuned in orientation, and commonly selective for the direction of movement. It is shown that performing independent component analysis (ICA) on video sequences of natural scenes produces results with qualitatively similar spatio-temporal properties. Whereas the independent components of video resemble moving edges or bars, the independent component filters, i.e. the analogues of receptive fields, resemble moving sinusoids windowed by steady Gaussian envelopes. Contrary to earlier ICA results on static images, which gave only filters at the finest possible spatial scale, the spatio–temporal analysis yields filters at a range of spatial and temporal scales. Filters centred at low spatial frequencies are generally tuned to faster movement than those at high spatial frequencies.
An Ontology-Based Approach to Software Comprehension - Reasoning about Security Concerns

There exists a large variety of techniques to detect and correct software security vulnerabilities at the source code level, including human code reviews, testing, and static analysis. In this article, we present a static analysis approach that supports both the identification of security flaws and the reasoning about security concerns. We introduce an ontology-based program representation that lets security experts and programmers specify their security concerns as part of the ontology. Within our tool implementation, we support complex queries on the underlying program model using either predefined or user-defined concepts and relations. Queries regarding security concerns, such as exception handling, object accessibility etc. are demonstrated in order to show the applicability and flexibility of our approach
PCR detection of HIV proviral DNA (gag) in the brains of patients with AIDS: comparison between results using fresh frozen and paraffin wax embedded specimens.

AIMS--To adapt the polymerase chain reaction (PCR) technique of HIV detection to paraffin wax embedded brain tissue and to compare the results with those obtained using frozen tissue. METHODS--HIV antigen and HIV proviral DNA were detected in specimens of frontal lobe using immunohistochemistry and PCR, respectively. DNA was extracted from fresh tissue using standard methods whereas the technique for extracting DNA from paraffin wax embedded tissue was partly modified. RESULTS--Twenty cases were examined. HIV DNA was detected in 16 cases in frozen specimens. Of these, 15 were also positive when paraffin wax embedded material was analysed. CONCLUSIONS--This study shows that HIV proviral DNA can be detected in formalin fixed, paraffin wax embedded brain tissue by PCR. The results obtained from paraffin wax embedded specimens showed a similar degree of reliability to those from fresh frozen brain. Factors such as fixative, fixation time, and delay in performing post mortem examinations did not seem to influence PCR amplification as positive results were obtained with specimens left in fixative for up to eight months, as well as in cases where post mortem examinations had been delayed for up to four days.
A Monthly Struggle for Self-Control? Hyperbolic Discounting, Mental Accounting, and the Fall in Consumption Between Paydays

An alternative conception of consumer choice has recently gained the attention of economists, which allows for two closely related departures from the standard model. First, consumers may have dynamically inconsistent preferences. Second, as a rational response to this dynamic inconsistency, the consumer may use external commitment devices or personal rules in an attempt to limit overspending. We use data from a large, representative sample of households in the UK to test the relevance of these twin predictions in the field. We find evidence that consumption spending declines between paydays, and jumps back to its initial level on the next payday. The decline is too steep to be explained by dynamically consistent (exponential) impatience, and does not appear to be driven by stockpiling or other rational motives. On the other hand a model with dynamically inconsistent (quasi-hyperbolic) time preference can explain the decline, for reasonable short-term and long-term discount rates. We also investigate whether households in our sample appear to make an effort at self-control, using a strategy emphasized in the literature: a mental accounting rule that limits borrowing during the pay period and thus puts a cap on overspending. We find that households who are able to borrow, in the sense that they own a credit card, nevertheless exhibit the spending profile characteristic of credit constraints. Investigating their behavior in more detail, we find that these households treat funds from the current and future income accounts very differently during the pay period. In combination, these facts suggest the use of a mental accounting rule limiting borrowing. Overall, our findings are difficult to explain in the standard economic framework, whereas the self-control problem framework offers a relatively parsimonious, unified explanation.
Crowding is unlike ordinary masking: distinguishing feature integration from detection.

A letter in the peripheral visual field is much harder to identify in the presence of nearby letters. This is "crowding. " Both crowding and ordinary masking are special cases of "masking," which, in general, refers to any effect of a "mask" pattern on the discriminability of a signal. Here we characterize crowding, and propose a diagnostic test to distinguish it from ordinary masking. In ordinary masking, the signal disappears. In crowding, it remains visible, but is ambiguous, jumbled with its neighbors. Masks are usually effective only if they overlap the signal, but the crowding effect extends over a large region. The width of that region is proportional to signal eccentricity from the fovea and independent of signal size, mask size, mask contrast, signal and mask font, and number of masks. At 4 deg eccentricity, the threshold contrast for identification of a 0.32 deg signal letter is elevated (up to six-fold) by mask letters anywhere in a 2.3 deg region, 7 times wider than the signal. In ordinary masking, threshold contrast rises as a power function of mask contrast, with a shallow log-log slope of 0.5 to 1, whereas, in crowding, threshold is a sigmoidal function of mask contrast, with a steep log-log slope of 2 at close spacing. Most remarkably, although the threshold elevation decreases exponentially with spacing, the threshold and saturation contrasts of crowding are independent of spacing. Finally, ordinary masking is similar for detection and identification, but crowding occurs only for identification, not detection. More precisely, crowding occurs only in tasks that cannot be done based on a single detection by coarsely coded feature detectors. These results (and observers' introspections) suggest that ordinary masking blocks feature detection, so the signal disappears, while crowding (like "illusory conjunction") is excessive feature integration - detected features are integrated over an inappropriately large area because there are no smaller integration fields - so the integrated signal is ambiguous, jumbled with the mask. In illusory conjunction, observers see an object that is not there made up of features that are. A survey of the illusory conjunction literature finds that most of the illusory conjunction results are consistent with the spatial crowding described here, which depends on spatial proximity, independent of time pressure. The rest seem to arise through a distinct phenomenon that one might call "temporal crowding," which depends on time pressure ("overloading attention"), independent of spatial proximity.
Scale Selection of Adaptive Kernel Regression by Joint Saliency Map for Nonrigid Image Registration

Joint saliency map (JSM) [1] was developed to assign high joint saliency values to the corresponding saliency structures (called Joint Saliency Structures, JSSs) but zero or low joint saliency values to the outliers (or mismatches) that are introduced by missing correspondence or local large deformations between the reference and moving images to be registered. JSM guides the local structure matching in nonrigid registration by emphasizing these JSSs' sparse deformation vectors in adaptive kernel regression of hierarchical sparse deformation vectors for iterative dense deformation reconstruction. By designing an effective superpixel-based local structure scale estimator to compute the reference structure's structure scale, we further propose to determine the scale (the width) of kernels in the adaptive kernel regression through combining the structure scales to JSM-based scales of mismatch between the local saliency structures. Therefore, we can adaptively select the sample size of sparse deformation vectors to reconstruct the dense deformation vectors for accurately matching the every local structures in the two images. The experimental results demonstrate better accuracy of our method in aligning two images with missing correspondence and local large deformation than the state-of-the-art methods.
Themed Issue Article: Stress in Vertebrates Sex, scarring, and stress: understanding seasonal costs in a cryptic marine mammal

We investigated variation in adrenal activity in the dugong, a vulnerable cryptic marine mammal species, in a population inhabiting the lower thermal limit of their range. We sampled 319 live wild dugongs and examined faecal glucocorticoid (fGC) concentrations in relationship to sex, reproductive state (immature, sexually mature, or pregnant), and season, as well as associations with body condition, male-induced aggressive conspecific interactions, and environmental temperature. Physiological validations with apparently healthy and unhealthy animals indicated that fGC levels reliably reflect adrenal activation in dugongs. Glucocorticoid levels and body condition varied seasonally, with individuals expressing lowest fGC levels and an improving body condition over summer and autumn. Best body condition was observed in winter, which may have enhanced the ability of the animals to cope with thermal and nutritional challenges and helped to sustain the subsequent costs of reproduction (including mating activity in spring). Immature dugongs, especially those recently estranged from their mothers, may be particularly vulnerable to stress during winter, and also at risk of injury from adult conspecifics. During the spring mating period, mature and sexually active males with large erupted tusks had high fGC and poorer body condition compared with all dugongs, except pregnant females, in all other seasons. This finding was consistent with high levels of body scarring on adults of both sexes, resulting from agonistic behav iour by mature males. Competitive reproductive behaviour, inherent in a promiscuous mating system, may have stressful consequences for male dugongs, especially given that strenuous mating activity follows unfavourable thermal and nutritional conditions. Overall, fGC levels appear to be a good proxy for stressors in dugongs associated with season and/or temperature, intra-specific aggression, and pregnancy, but not lactation and/or maternal care. Understanding baseline fGC levels will allow wildlife managers to identify additional and/or unusual stressors that may threaten wild dugong populations.
Multimodal Human-Robot Interaction Framework for a Personal Robot

This paper presents a framework for multimodal human-robot interaction. The proposed framework is being implemented in a personal robot called Maggie, developed at RoboticsLab of the University Carlos III of Madrid for social interaction research. The control architecture of this personal robot is a hybrid control architecture called AD (automatic-deliberative) that incorporates an emotion control system (ECS). Maggie's main goal is to interact establish a peer-to-peer relationship with humans. To achieve this goal, a set of human-robot interaction skills are developed based on the proposed framework. The human-robot interaction skills imply tactile, visual, remote voice and sound modes. The multi-modal fusion and synchronization are also presented in this paper
Small-size relative (p,ε)-approximations for well-behaved range spaces

We present improved upper bounds for the size of relative (p,ε)-approximation for range spaces with the following property: For any (finite) range space projected onto (that is, restricted to) a ground set of size n and for any parameter 1 ≤ k ≤ n, the number of ranges of size at most k is only nearly-linear in n and polynomial in k. Such range spaces are called "well behaved". Our bound is an improvement over the bound O(log(1/p)/ε2 p) introduced by Li et. al. [17] for the general case (where this bound has been shown to be tight in the worst case), when p l ε. We also show that such small size relative (p,ε)-approximations can be constructed in expected polynomial time. Our bound also has an interesting interpretation in the context of "p-nets": As observed by Har-Peled and Sharir [13], p-nets are special cases of relative (p,ε)-approximations. Specifically, when ε is a constant smaller than 1, the analysis in [13, 17] implies that there are p-nets of size O(log{(1/p)}/p) that are also relative approximations. In this context our construction significantly improves this bound for well-behaved range spaces. Despite the progress in the theory of p-nets and the existence of improved bounds corresponding to the cases that we study, these bounds do not necessarily guarantee a bounded relative error. Lastly, we present several geometric scenarios of well-behaved range spaces, and show the resulting bound for each of these cases obtained as a consequence of our analysis. In particular, when ε is a constant smaller than 1, our bound for points and axis-parallel boxes in two and three dimensions, as well as points and "fat" triangles in the plane, matches the optimal bound for p-nets introduced in [3, 25].
Polarized activities of AMPK and BRSK in primary hippocampal neurons

In differentiated rodent hippocampal neurons, a FRET-based activity reporter reveals distinct spatiotemporal activity patterns of BRSK and AMPK, two homologous kinases that play important roles in neuronal polarity. AMPK exhibits maximal stimulated activity, whereas BRSK displays polarized basal activity in the distal region of the axon and axon tips.
Gmres: a Generalized Minimum Residual Algorithm for Solving

Overton, who showed us how the ideal Arnoldi and GMRES problems relate to more general problems of minimization of singular values of functions of matrices 17]. gmres and arnoldi as matrix approximation problems 9 least n + 1 equal maximal singular values. This follows from the fact that the degree n Chebyshev polynomial for a set in the complex plane always takes on its maximum absolute value in at least n+1 distinct points. In contrast, when A is not normal, our experiments indicate that after the initial phase with kq (A)k = 1 just mentioned, q (A) usually has only one maximal singular value. 7. Open questions. Our work on ideal GMRES and Arnoldi approximations has raised more questions than it has answered. We shall close with a list of ve questions that we consider particularly interesting. In each of the following A is a matrix, b is a vector normalized by kbk = 1, and the convergence curve is the curve of kp (A)bk or kq (A)k as a function of the step number n. The questions are posed for GMRES, but they all have Arnoldi analogues. 1. Is the envelope attained? Theorem 1 asserts that the GMRES convergence curve lies below the ideal GMRES convergence curve, as illustrated in Fig. 1. Given n, does there exist an initial vector b such that these two curves intersect at step n, i.e., such that kp (A)bk = kq (A)k ? The answer is known to be yes for symmetric matrices 5] and more generally for normal matrices 6,10], and for arbitrary matrices at step n = 1 6,10]. It is also yes in the \generic" non-normal case in which the maximal singular value of q (A) is simple. Whether it is yes in all cases is not known. If it is, then the ideal GMRES convergence curve can be described as the upper envelope of the GMRES convergence curves corresponding to all initial vectors b. 2. How close is the average case to the worst case? Assuming that the envelope is attained in the sense above, there is still the question of how closely the GMRES and ideal GMRES convergence curves agree for typical starting vectors. If A is normal, it is easily argued that two agree typically to within a factor on the order of p N. We do not know what can be said for general A. 3. …
Location by involution

In this paper, we propose an iterative method of 3D location of 2D parallelogram or 3D parallelepiped shapes by monocular vision from a single image. The method we propose assumes that the camera is calibrated and that the size of the polygonal object is known. The 3D location is obtained in the following way. First we try to find the orientation of a geometric model of the object imaged such that they share the same vanishing points. This property known as "involution" in the 17th century insures that the model and the object have the same orientation. Moreover this property in invariant to translation. This greatly simplifies the location problem by allowing to decouple rotation and translation assessments. The method is illustrated and tested with real scene images.
A restatement of the natural science evidence base relevant to the control of bovine tuberculosis in Great Britain†

Bovine tuberculosis (bTB) is a very important disease of cattle in Great Britain, where it has been increasing in incidence and geographical distribution. In addition to cattle, it infects other species of domestic and wild animals, in particular the European badger (Meles meles). Policy to control bTB is vigorously debated and contentious because of its implications for the livestock industry and because some policy options involve culling badgers, the most important wildlife reservoir. This paper describes a project to provide a succinct summary of the natural science evidence base relevant to the control of bTB, couched in terms that are as policy-neutral as possible. Each evidence statement is placed into one of four categories describing the nature of the underlying information. The evidence summary forms the appendix to this paper and an annotated bibliography is provided in the electronic supplementary material.