Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Verification for Robust Computing

This paper argues for an integrated approach to verification, combining offline and online verification techniques used at different stages of a system’s lifetime, in order to detect and correct failures arising from design errors and program bugs. We propose a formal framework for online verification and recovery, including a fault model, within which such an integrated approach can be investigated. As a particular instance, we consider the problem of recovering a class of finite-state systems, at run-time, from failures of safety properties, while leveraging results of offline verification. This class comprises systems whose behavior can be divided into rounds such that each round is largely independent of the others. We give a randomized recovery strategy based on online learning for which the expected number of recovery actions performed in any state is at most logarithmic in the total number of actions, assuming perfect error localization. Results from design-time verification can be used to reduce the search space of the recovery algorithm and deal with imperfections in error localization. We illustrate our approach with case studies. Our results are a step towards building reactive systems that are robust to failures and self-evolve towards correct systems.
High-Order Topology Modeling of Visual Words for Image Classification

Modeling relationship between visual words in feature encoding is important in image classification. Recent methods consider this relationship in either image or feature space, and most of them incorporate only pairwise relationship (between visual words). However, in situations involving large variability in images, one cannot capture intrinsic invariance of intra-class images using low-order pairwise relationship. The result is not robust to larger variations in images. In addition, as the number of potential pairings grows exponentially with the number of visual words, the task of learning becomes computationally expensive. To overcome these two limitations, we propose an efficient classification framework that exploits high-order topology of visual words in the feature space, as follows. First, we propose a search algorithm that seeks dependence between the visual words. This dependence is used to construct higher order topology in the feature space. Then, the local features are encoded according to this higher order topology to improve the image classification. Experiments involving four common data sets, namely PASCAL VOC 2007, 15 Scenes, Caltech 101, and UIUC Sport Event, demonstrate that the dependence search significantly improves the efficiency of higher order topological construction, and consequently increases the image classification in all these data sets.
Single and Two-Scale Sharp-Interface Models for Concrete Carbonation - Asymptotics and Numerical Approximation

We investigate the fast-reaction asymptotics for a one-dimensional reaction-diffusion system describing the penetration of the carbonation reaction in concrete. The technique of matched-asymptotics is used to show that the reaction-diffusion system leads to two distinct classes of sharp-interface models. These correspond to different scalings of a small parameter $\epsilon$ representing the fast-reaction and defined here as the ratio between the characteristic scale of diffusion for the fastest species and the characteristic scale of the carbonation reaction. We explore three conceptually different diffusion regimes in terms of the behavior of the effective diffusivities for the driving chemical species. The limiting models include one-phase and two-phase generalized Stefan moving-boundary problems as well as a nonstandard two-scale (micro-macro) moving-boundary problem---the main result of the paper. Numerical results, supporting the asymptotics, illustrate the behavior of the concentration profiles for .
Language-mediated object categorization: A longitudinal study with 16- to 20-month-old Serbian-speaking children

Abstract This study addressed the development of language-mediated categorization longitudinally, on a sample of Serbian-speaking children aged 16–20 months. Twenty four children were tested 3 consecutive times on: categorization of unknown objects with a shared label and a similar shape; and categorization of unknown objects with a shared label, but no visual similarity. The task was embedded in a game-like activity which included real object manipulation, categorization of novel objects labeled with made-up names, and socio-pragmatic cues provided by the experimenter. Our results indicate that an average child develops the ability to categorize novel objects with a similar shape and a shared label around 16 months of age, whereas for novel objects with a shared label, but no visual similarity, this ability is acquired sometime between 18 and 20 months of age. Our results partly confirm research findings obtained in other languages, thus emphasizing the need for cross-linguistic and cross-cultural validation of all language-related developmental studies.
First evidence for the impact of implicit motives on flow experience

Theory The primary approach on flow-experience (Csikszentmihalyi, 1975) conceptualizes balance between challenge and skill as the most important precondition. However, in his compensatory model of work motivation and volition Kehr (2004) assumes that flowexperience results when (1) task related behaviour matches one’s implicit motives, (2) no competing explicit motives are aroused, and (3) perceived abilities are sufficient. In achievement related tasks, performance feedback provides information about success. This should arouse need for achievement and should therefore foster flow experience, particularly in subjects with high need achievement.
Emergency department crowding

Emergency department crowding is a significant international problem. The problem is on the edge of the emergency department and the departments where the patients will be subsequently admitted, provided they are not discharged. In this paper we present an analysis of the factors affecting waiting time in the emergency department of an eminent hospital in Israel as well as a suggested solution utilizing decision trees. The paper is based on the fourth year graduate project of a students' team in the department of industrial engineering at Tel Aviv University.
Diagnosis versus Detection of Caries

Caries diagnosis is the art or act of identifying a disease from its signs and symptoms. This is distinct from the detection of the signs and symptoms themselves. The diagnosis forms the basis for making informed treatment decisions. Hence, if there is no diagnostic step expressed in terms of the probability of present and future occurrence of disease, practitioners may resort to treatments guided by previous experiences with similar clinical manifestations. This paper reviews various methodological aspects of caries diagnostic testing. It is concluded that rather than continuing to search for the truth of the diagnosis, it may be more informative to consider the consequences of the diagnosis. This view is supported by results from caries-preventive trials in which the activity of carious lesions has been monitored longitudinally over years.
Phosphatase Wip1 in Immunity: An Overview and Update

Wild-type p53-induced phosphatase 1 (Wip1) is a newly identified serine/threonine phosphatase, which belongs to the PP2C family. Due to its involvement in stress-induced networks and overexpression in human tumors, primary studies have mainly focused on the role of Wip1 in tumorigenesis. It now has also been implicated in regulating several other physiological processes such as organism aging and neurogenesis. Recent evidence highlights a new role of Wip1 in controlling immune response through regulating immune cell development and function, as well as through the interplay with inflammatory signaling pathways such NF-κB and p38 mitogen-activated protein kinase. In this short review, we will give an overview of Wip1 in immunity to better understand this important phosphatase.
PRACTICAL SOLUTION OF THE DIOPHANTINE EQUATION

Let p be an odd prime and a, b positive integers. In this note we prove that the problem of the determination of the integer solutions to the equation y2 = x(x + 2apb)(x − 2apb) can be easily reduced to the resolution of the unit equation u + √ 2v = 1 over Q( √ 2, √ p). The solutions of the latter equation are given by Wildanger’s algorithm.
Confidence-based progress-driven self-generated goals for skill acquisition in developmental robots

A reinforcement learning agent that autonomously explores its environment can utilize a curiosity drive to enable continual learning of skills, in the absence of any external rewards. We formulate curiosity-driven exploration, and eventual skill acquisition, as a selective sampling problem. Each environment setting provides the agent with a stream of instances. An instance is a sensory observation that, when queried, causes an outcome that the agent is trying to predict. After an instance is observed, a query condition, derived herein, tells whether its outcome is statistically known or unknown to the agent, based on the confidence interval of an online linear classifier. Upon encountering the first unknown instance, the agent “queries” the environment to observe the outcome, which is expected to improve its confidence in the corresponding predictor. If the environment is in a setting where all instances are known, the agent generates a plan of actions to reach a new setting, where an unknown instance is likely to be encountered. The desired setting is a self-generated goal, and the plan of action, essentially a program to solve a problem, is a skill. The success of the plan depends on the quality of the agent's predictors, which are improved as mentioned above. For validation, this method is applied to both a simulated and real Katana robot arm in its “blocks-world” environment. Results show that the proposed method generates sample-efficient curious exploration behavior, which exhibits developmental stages, continual learning, and skill acquisition, in an intrinsically-motivated playful agent.
Head shape evolution in Tropidurinae lizards: does locomotion constrain diet?

Different components of complex integrated systems may be specialized for different functions, and thus the selective pressures acting on the system as a whole may be conflicting and can ultimately constrain organismal performance and evolution. The vertebrate cranial system is one of the most striking examples of a complex system with several possible functions, being associated to activities as different as locomotion, prey capture, display and defensive behaviours. Therefore, selective pressures on the cranial system as a whole are possibly complex and may be conflicting. The present study focuses on the influence of potentially conflicting selective pressures (diet vs. locomotion) on the evolution of head shape in Tropidurinae lizards. For example, the expected adaptations leading to flat heads and bodies in species living on vertical structures may conflict with the need for improved bite performance associated with the inclusion of hard or tough prey into the diet, a common phenomenon in Tropidurinae lizards. Body size and six variables describing head shape were quantified in preserved specimens of 23 species, and information on diet and substrate usage was obtained from the literature. No phylogenetic signal was observed in the morphological data at any branch length tested, suggesting adaptive evolution of head shape in Tropidurinae. This pattern was confirmed by both factor analysis and independent contrast analysis, which suggested adaptive co‐variation between the head shape and the inclusion of hard prey into the diet. In contrast to our expectations, habitat use did not constrain or drive head shape evolution in the group.
Molecular Proximal Persistent Na Channels Drive Spike Afterdepolarizations and Associated Bursting in Adult CA 1 Pyramidal Cells

In many principal brain neurons, the fast, all-or-none Na spike initiated at the proximal axon is followed by a slow, graded afterdepolarization (ADP). The spike ADP is critically important in determining the firing mode of many neurons; large ADPs cause neurons to fire bursts of spikes rather than solitary spikes. Nonetheless, not much is known about how and where spike ADPs are initiated. We addressed these questions in adult CA1 pyramidal cells, which manifest conspicuous somatic spike ADPs and an associated propensity for bursting, using sharp and patch microelectrode recordings in acutely isolated hippocampal slices and single neurons. Voltage-clamp commands mimicking spike waveforms evoked transient Na spike currents that declined quickly after the spike but were followed by substantial sustained Na spike aftercurrents. Drugs that blocked the persistent Na current (INaP ), markedly suppressed the sustained Na spike aftercurrents, as well as spike ADPs and associated bursting. Ca 2 spike aftercurrents were much smaller, and reducing them had no noticeable effect on the spike ADPs. Truncating the apical dendrites affected neither spike ADPs nor the firing modes of these neurons. Application of INaP blockers to truncated neurons, or their focal application to the somatic region of intact neurons, suppressed spike ADPs and associated bursting, whereas their focal application to distal dendrites did not. We conclude that the somatic spike ADPs are generated predominantly by persistent Na channels located at or near the soma. Through this action, proximal INaP critically determines the firing mode and spike output of adult CA1 pyramidal cells.
Simulation analysis and study on car-following safety distance model based on braking process of leading vehicle

In order to improve traditional safety distance models based on braking process of the leading vehicle, a new safety distance model of one-lane following condition is established based on traditional safety distance models. The new model considers the relative speed between vehicles and the change process of deceleration value. A simulation using Matlab software verifies that the new model overcomes inaccurate defects in computing safe-distance of the traditional models. Finally, we established an intersection traffic-wave simulation system using Visual C++ 6.0 as the software platform. Simulation results demonstrate that the new model produces better safe-distance prediction between vehicles. Hence, it improves road-use efficiency, reduces vehicle pollution and intersection delays under condition that the safety distance production is ensured. The new model can provide new ideas for control of signalized intersection.
Distributed Control of Networked Dynamical Systems: Static Feedback, Integral Action and Consensus

This paper analyzes distributed control protocols for first- and second-order networked dynamical systems. We propose a class of nonlinear consensus controllers where the input of each agent can be written as a product of a nonlinear gain, and a sum of nonlinear interaction functions. By using integral Lyapunov functions, we prove the stability of the proposed control protocols, and explicitly characterize the equilibrium set. We also propose a distributed proportional-integral (PI) controller for networked dynamical systems. The PI controllers successfully attenuate constant disturbances in the network. We prove that agents with single-integrator dynamics are stable for any integral gain, and give an explicit tight upper bound on the integral gain for when the system is stable for agents with double-integrator dynamics. Throughout the paper we highlight some possible applications of the proposed controllers by realistic simulations of autonomous satellites, power systems and building temperature control.
A unified approach to multi-pose audio-visual ASR

The vast majority of studies in the field of audio-visual automatic speech recognition (AVASR) assumes frontal images of a speaker's face, but this cannot always be guaranteed in practice. Hence our recent research efforts have concentrated on extracting visual speech information from non-frontal faces, in particular the profile view. The introduction of additional views to an AVASR system increases the complexity of the system, as it has to deal with the different visual features associated with the various views. In this paper, we propose the use of linear regression to find a transformation matrix based on synchronous frontal and profile visual speech data, which is used to normalize the visual speech in each viewpoint into a single uniform view. In our experiments for the task of multi-speaker lipreading, we show that this "pose-invariant" technique reduces train/test mismatch between visual speech features of different views, and is of particular benefit when there is more training data for one viewpoint over another (e.g. frontal over profile).
Glare generation based on wave optics

This paper proposes a general method of glare generation based on wave optics. A glare image is regarded as a result of Fraunhofer diffraction, which is equivalent to a 2D Fourier transform of the image of given apertures or obstacles. In conventional methods, the shapes of glare images are categorized according to their source apertures, such as pupils and eyelashes and their basic shapes (e.g. halos, coronas or radial streaks) are manually generated as templates, mainly based on statistical observation. Realistic variations of these basic shapes often depend on the use of random numbers. Our proposed method computes glare images fully automatically from aperture images and can be applied universally to all kinds of apertures, including camera diaphragms. It can handle dynamic changes in the position of the aperture relative to the light source, which enables subtle movement or rotation of glare streaks. Spectra can also be simulated in the glare, since the intensity of diffraction depends on the wavelength of light. The resulting glare image is superimposed onto a given computer-generated image containing high intensity light sources or reflections, aligning the center of the glare image to the high intensity areas. Our method is implemented as a multipass rendering software. By precomputing the dynamic glare image set and putting it into texture memory, the software runs at an interactive rate.
Promoter Hypermethylation of Resected Bronchial Margins

Purpose: Histologically positive bronchial margins after resection for non-small cell lung cancer are associated with shortened patient survival due to local recurrence. We hypothesized that DNA promoter hypermethylation changes at bronchial margins could be detected in patients with no histological evidence of malignancy and that they would reflect epigenetic events in the primary tumor. Experimental Design: Bronchial margins, primary tumor, bronchoalveolar fluid, and paired nonmalignant lung were obtained from 20 non-small cell lung cancer patients who underwent a lobectomy or greater resection. Disease-specific recurrence was the primary end point. The methylation status of p16, MGMT, DAPK, SOCS1, RASSF1A, COX2, and RARβ was examined using methylation-specific polymerase chain reaction. Results: All malignancies had methylation in at least one locus. Concordance of one gene with an identical epigenetic change in the tumor or bronchial margin was observed in 85% of patients. Only one patient had methylation at the bronchial margin for a gene that was not methylated in the corresponding tumor. Median time to recurrence was 37 months (range, 5–71 months). There were two local recurrences and five metastases. There were no significant correlations between DNA methylation in tumor, margins, or bronchoalveolar fluid specimens and either regional recurrence or distant metastases. Conclusions: Histologically negative bronchial margins of resected non-small cell lung cancer exhibit frequent hypermethylation changes in multiple genes. These hyper-methylation abnormalities are also present in the primary tumor and thus may represent a field defect of preneoplastic changes that occurs early in carcinogenesis.
On Gröbner Basis Detection for Zero-dimensional Ideals

The Gr\"obner basis detection (GBD) is defined as follows: Given a set of polynomials, decide whether there exists -and if "yes" find- a term order such that the set of polynomials is a Gr\"obner basis. This problem was shown to be NP-hard by Sturmfels and Wiegelmann. We show that GBD when studied in the context of zero dimensional ideals is also NP-hard. An algorithm to solve GBD for zero dimensional ideals is also proposed which runs in polynomial time if the number of indeterminates is a constant.
USING THE DIRECT SIMULATION MONTE CARLO APPROACH FOR THE BLAST-IMPACT PROBLEM

The viability of using the Direct Simulation Monte Carlo (DSMC) approach to study the blast-impact problem is assessed. An uncoupled analysis of the problem is performed where the solid body is not allowed to move or deform. The numerical simulations are designed to mimic the actual shock-tube experiments. Our code is validated against the shock-tube (Riemann) problem. A novel approach to model the inflow boundary condition is presented which can be used with both particle and continuum methods. A generic implementation of the solid boundary condition for particle methods is described which can easily and efficiently handle arbitrary-shaped bodies. This approach is demonstrated by computing load definition for two model geometries a box and an ‘I’ shaped beam.
Relatively relevant: Assessor shift in document judgements

The evaluation of information retrieval systems relies on relevance judgements – human assessments of whether a document is relevant to a specified search request. In the past, it was demonstrated that test collection assessors disagree with each other to some extent on the relevance of documents and can be inconsistent in themselves. This paper describes a series of investigations on assessor consistency, which demonstrate that the inconsistency of an assessor varies over time. We show that when documents are presented to assessors in a relevance independent order, documents judged as relevant appear to cluster. Examining pairs of documents in a sequence ordered by timeof-judgement, we find that relevance assessors judge highly similar document pairs more consistently when the pairs are seen soon after each other; the consistency reduces when the pairs are judged further apart. We contend that our analysis shows that changes are not due to random error, but instead reflect a relevance shift, whereby the assessor’s conception of what constitutes a relevant document changes over time. Studying types of relevance judgement we find that the shift in judgements is greatest between highly and partially relevant documents. We also examine the impact of this inconsistency on how retrieval runs are ranked relative to each other and find that there appears to be a noticeable effect on such rankings.