Miracle-dz/UniFAR-FTUs huggingface dataset:
Reactive sampling-based temporal logic path planning

We develop a sampling-based motion planning algorithm that combines long-term temporal logic goals with short-term reactive requirements. The mission specification has two parts: (1) a global specification given as a Linear Temporal Logic (LTL) formula over a set of static service requests that occur at the regions of a known environment, and (2) a local specification that requires servicing a set of dynamic requests that can be sensed locally during the execution. Our method consists of two main ingredients: (a) an off-line sampling-based algorithm for the construction of a global transition system that contains a path satisfying the LTL formula, and (b) an on-line sampling-based algorithm to generate paths that service the local requests, while making sure that the satisfaction of the global specification is not affected. Building on our previous work [1], the focus of this paper is on the on-line part of the overall method.
Inference Under the Influence: The Impact of Alcohol and Inhibition Conflict on Women's Sexual Decision Making

Integrating Zajonc's affective primacy framework with Steele and Southwick's Inhibitory Conflict Model, we hypothesized that alcohol would have its strongest impact when one's initial affective reaction was in direct conflict with more cognitively based inhibitory cues. In an alcohol by expectancy balanced placebo design, women viewed potential partners from a fictitious video dating service who varied in attractiveness and sexual risk. Only under high inhibitory conflict (i. e., an attractive, sexually risky partner) did alcohol enhance perceived relationship potential. Interestingly, women who consumed alcohol were not less likely to notice risk cues than their sober counter-parts. Alcohol expectancy resulted in both lower estimates of risk and elevated estimates of relationship potential for the high inhibitory conflict target. Thus, in situations involving high but not low inhibitory conflict, alcohol and alcohol expectancy may suppress the impact of inhibitory cues, enabling women to more readily pursue their initial affective reactions.
Quantifying Turfgrass Color Using Digital Image Analysis

Color is a major component of the aesthetic quality of turf and often evaluated in field studies. Digital image analysis may be an improved, objective method to quantify turf color. Studies were conducted to determine if digital image analysis with SigmaScan software (SPSS, Chicago, IL) was capable of: (i) accurately determining the hue, saturation, and brightness (HSB) levels of Munsell Plant Tissue color chips, (ii) quantifying visual color differences among zoysiagrass (Zoysia japonica Steud.) and creeping bentgrass (Agrostis palustris Huds. { = A. stolonifera var. palustris (Hods.) Farw. }} plots receiving various N treatments, and (iii) quantifying genetic color differences among bermudagrass (Cynodon spp.) cultivars. Digital images of turf plots were analyzed with SigmaScan software to determine average HSB levels for each image. A dark green color index (DGCI) was created from HSB values for direct comparison with visual ratings. Digital image analysis accurately quantified the HSB levels (r 2 = 0.99, 0.96, and 0.97, respectively) of Munsell color chips corresponding to turf colors. Significant HSB differences were present among N treatments in creeping bentgrass, while only significant hue differences existed in zoysiagrass. Significant hue and saturation differences were present among bermudagrass cultivars. There was strong agreement between DGCI values and visual ratings. The relative variances of the HSB and DGCI were significantly less than the variance associated with multiple raters. This evaluation technique may facilitate objective comparisons of turf color across researchers, locations, and years when images are collected under equal lighting conditions (i.e., the use of an artificial light source at night or in an enclosed system).
Nanoshell-Enabled Photonics-Based Imaging and Therapy of Cancer

Metal nanoshells are a novel type of composite spherical nanoparticle consisting of a dielectric core covered by a thin metallic shell which is typically gold. Nanoshells possess highly favorable optical and chemical properties for biomedical imaging and therapeutic applications. By varying the relative the dimensions of the core and the shell, the optical resonance of these nanoparticles can be precisely and systematically varied over a broad region ranging from the near-UV to the mid-infrared. This range includes the near-infrared (NIR) wavelength region where tissue transmissivity peaks. In addition to spectral tunability, nanoshells offer other advantages over conventional organic dyes including improved optical properties and reduced susceptibility to chemical/thermal denaturation. Furthermore, the same conjugation protocols used to bind biomolecules to gold colloid are easily modified for nanoshells. In this article, we first review the synthesis of gold nanoshells and illustrate how the core/shell ratio and overall size of a nanoshell influences its scattering and absorption properties. We then describe several examples of nanoshell-based diagnostic and therapeutic approaches including the development of nanoshell bioconjugates for molecular imaging, the use of scattering nanoshells as contrast agents for optical coherence tomography (OCT), and the use of absorbing nanoshells in NIR thermal therapy of tumors.
Distributed Workload Dissemination for Makespan Minimization in Disruption Tolerant Networks

Mobile devices are undergoing explosive proliferation today. Although they are gaining more and more capabilities, they still fall short to execute complex applications. One possible solution to alleviate this limitation is offloading tasks to remote clouds. However, it may require persistent connectivity to the Internet and thus is not always available or affordable. An alternative solution is taking advantage of pervasive mobile devices and their pairwise encounters. In this paradigm, complex tasks from mobile devices are processed in a distributed and collaborative fashion on all mobile devices that are loosely-connected. Working towards this vision, this paper studies the following problem: given a task that originates at some node in a Disruption Tolerant Network (DTN), how are we to disseminate the task's workload during the pairwise contacts among mobile devices to achieve makespan minimization? We first imagine access to an oracle that has global and future knowledge of node mobility, and we design a provably-optimal centralized polynomial-time solution as the benchmark for comparison. With the insights obtained from the centralized solution, we then develop a distributed dissemination algorithm, D2, which maintains certain neighborhood information at individual nodes. D2 makes dissemination decisions based on the estimations of the potential computational capacities and the future workloads of mobile nodes. Extensive trace-driven simulations confirm the effectiveness of D2.
Nuclei Accumbens Phase Synchrony Predicts Decision-Making Reversals Following Negative Feedback

The nucleus accumbens plays a key role in reinforcement-guided behaviors. Here, we report that electrophysiological oscillatory phase synchrony between the two nuclei accumbens may play a crucial role in using negative feedback to guide decision making. We recorded local field potentials from the human nucleus accumbens and the medial frontal cortex (via surface EEG) from patients who had deep brain stimulation electrodes implanted. Patients performed a reversal learning task in which they decided whether to alter their decision strategy following monetary losses. Strategy switches following losses were preceded by enhanced theta (4–8 Hz) phase synchrony between the nuclei accumbens, and a break-down of gamma (20–80 Hz)–α (8–12 Hz) coupling. Furthermore, the strength of the intersite phase synchrony predicted response time adjustments in the subsequent trial. These findings suggest that a neural network including the nucleus accumbens bilaterally becomes functionally connected via theta phase synchrony to signal the need to adjust behavior.
The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding

A tight integration of Mitchell's version space algorithm with Agrawal et al.'s Apriori algorithm is presented. The algorithm can be used to generate patterns that satisfy a variety of constraints on data. Constraints that can be imposed on patterns include the generality relation among patterns and imposing a minimum or a maximum frequency on data sets of interest. The theoretical framework is applied to an important application in chemo-informatics, i.e. that of finding fragments of interest within a given set of compounds. Fragments are linearly connected substructures of compounds. An implementation as well as preliminary experiments within the application are presented.
Teaching Higher and Lower in Mastery Goal Structure: The Perspective of Students

Taking a student’s perspective, this study aims to characterize students’ descriptions of teaching higher and lower in mastery goal emphasis, in elementary, middle, traditional, and democratic schools. Data were collected by student surveys and interviews from fifth- through eighth-grade Israeli students. Nineteen interviews, describing 5 science teachers perceived by their students as higher or lower in mastery goal emphasis, were chosen for further analyses, which employed the TARGETS framework. Results provided concrete illustrations of higher and lower mastery-emphasizing teaching, in different types of schools. Task, time, and autonomy emerged as salient dimensions differentiating between higher and lower perceived mastery goal structure as well as preparation for tests, recognition equality, and teachers’ attentiveness.
Promoting self-regulation and mathematics achievement: the role of a hypermedia application

The present study aimed to evaluate the efficacy of a hypermedia application in improving students’ use of self-regulated learning strategies, self-efficacy in mathematics, and mathematics achievement. A total of 2862 students and their 62 teachers participated in the study. The study followed a pre-post design, with classes randomly assigned to three treatment conditions. In the first group, the students learned the contents of a curricular unit (i.e. Pythagorean Theorem) using a hypermedia application designed for the purposes of this research; in the second group, students were made aware of the hypermedia application, did not use it to learn the content, but were encouraged to use technology in class; and in the third group, the students did not know about the existence of the application and classes were taught without using technology. Pre-test results did not show differences among the participating groups in prior knowledge, self-regulated learning, and self-efficacy. After the intervention, the results showed the effectiveness of the hypermedia application to improve mathematics achievement and self-regulated learning processes. The first group achieved a significant increase in the dependent variables when compared to the other groups, and the second group obtained better scores in the dependent variables relative to the third.
Model Checking Object Petri Nets in Prolog ( Application Paper )

Object Petri nets (OPNs) provide a natural and modular method for the modelling of many real-world systems. We give a structure-preserving translation of OPNs to Prolog, avoiding the need for an unfolding to a flat Petri net. The translation provides support for reference and value semantics, and even allows different objects to be treated as copyable or non-copyable, respectively. The method is developed for OPNs with arbitrary nesting. We then apply logic programming tools to animate, compile and model check OPNs. In particular, we use the partial evaluation system logen to produce an OPN compiler, and we use the model checker xtl to verify CTL formulas. We also use logen to produce special purpose model checkers. We present two case studies, along with experimental results. A comparison to OPN translations to Maude specifications and model checking is given, showing that our approach is roughly twice as fast for larger systems. We also tackle infinite state model checking using the ecce system.
Cyclostationary Signatures for Rendezvous in OFDM-Based Dynamic Spectrum Access Networks

Distributed coordination of operating frequencies and bandwidths is one of the key challenges in the development of dynamic spectrum access (DSA) technology. The spectrum efficiency of DSA networks is achieved through the use of spectrum white spaces, frequency bands which are unoccupied at a given time and place. The issue of frequency rendezvous arises as the availability of these white spaces may change dynamically in frequency, time and space. We propose a novel solution to the problem of distributed rendezvous in dynamic spectrum access networks using cyclostationary signatures. By embedding a cyclostationary signature or watermark in a transmitted signal, the received signal can be uniquely detected, classified, and used for frequency acquisition by distributed dynamic spectrum access-enabled nodes in a network. This paper therefore makes three key contributions. First, a solution to the problem of distributed rendezvous in DSA networks using the novel concept of cyclostationary signatures is presented. Second, a low-complexity technique for generating these cyclostationary signatures in OFDM (orthogonal frequency division multiplexing) waveforms is described. Finally, an initial performance analysis of an implemented test platform is discussed.
Sequential Monte Carlo Tracking of the Natural Rate of Interest

Have interest rates been held "too low" in relation to the natural rate of interest over recent years? Using a dynamic optimizing business cycle model satisfying the natural rate hypothesis and generalized to allow for nonstationarity in the underlying stochastic processes, this paper attempts a real-time evaluation of the US monetary policy stance, while ensuring consistency between the speci…cation of price adjustments and the evolution of the economy under ‡exible prices. To do this, the model’s likelihood function is evaluated using a Sequential Monte Carlo algorithm, providing joint estimates of the structural parameters and the unobservable, time-varying, nonstationary state variables. As a result, a detailed tracking of the whole distribution of the natural rate can be obtained, enabling a thorough assessment of half century of US monetary policy.
Relating Architectural Decay and Sustainability of Software Systems

Ensuring the longevity of a software system is an important concern for developers and maintainers. However, when a system's architecture decays during evolution and its quality degrades as a result, the system's long-term sustainability is highly affected. In this light, providing mediums to estimate and track the sustainability of a software system is necessary to help engineers stay aware of system health. Most existing techniques and tools estimate the level of sustainability in code, paying significantly less attention to the analysis and understanding of architectural decay. This position paper provides a taxonomy of architectural smells, metrics, and their impacted quality properties. We relate these smells to maintenance and evolution areas as a first step toward our ultimate goal of estimating the sustainability of systems. We finally report some initial results drawn from a set of subject systems as promising future work using our taxonomy.
Attachment in psychological therapy : an exploratory study into patient and therapist attachment patterns and their relationship with early engagement and therapeutic alliance

word count = 225 Attachment in psychological therapy 87 Practitioner Points: • High levels of anxious and avoidant attachment styles associated with greater psychological distress within patient population • Avoidant attachment styles predictive of early engagement difficulties • Anxious and avoidant patient attachments can interfere with the quality of the therapeutic alliance • Therapists reported greater attachment security, although their attachment patterns were not significantly associated with the early therapeutic process Attachment in psychological therapy
Corecursive Featherweight Java

Despite cyclic data structures occur often in many application domains, object-oriented programming languages provide poor abstraction mechanisms for dealing with cyclic objects. Such a deficiency is reflected also in the research on theoretical foundation of object-oriented languages; for instance, Featherweigh Java (FJ), which is one of the most widespread object-oriented calculi, does not allow creation and manipulation of cyclic objects. We propose an extension to Featherweight Java, called COFJ, where it is possible to define cyclic objects, abstractly corresponding to regular terms, and where an abstraction mechanism, called regular corecursion, is provided for supporting implementation of coinductive operations on cyclic objects. We formally define the operational semantics of COFJ, and provide a handful of examples showing the expressive power of regular corecursion; such a mechanism promotes a novel programming style particularly well-suited for implementing cyclic data structures, and for supporting coinductive reasoning.
Immigrants and natives: Investigating differences between staff and students' use of technology

The corollary of the ‘Digital Native’ ‐ young, technologically avid and literate ‐ is the ‘Digital Immigrant’ ‐ older, less familiar and comfortable with technology. The accompanying rhetoric posits that in the higher education sector, staff and students are ensconced firmly on either side of a ‘digital divide’, with critical implications and consequences for teaching and learning. This proposition was tested by surveying 108 staff and 2588 first-year undergraduate students across three Australian Universities about their use of a large selection of common and emerging technologies. These technologies were grouped into eight coherent categories using factor analysis. A MANOVA was then used to analyse different uses of these technologies according to participants’ role (staff or student), gender and age. Significant main effects were reported for each of these independent variables and differences were seen particularly for technologies related to mobile phone use and gaming. However, the absolute magnitudes of most differences between groups were small and, critically, there were no role, gender or age effects for technology-based activities associated with Web 2.0 technologies, and the overall use of these technologies was low. These findings support a growing evidence base that, while some differences exist, the ‘digital divide’ between students and staff is not nearly as large as some commentators would have us believe.
A SARS Method for Reliable Spectrum Sensing in Multiband Communication Systems

This paper introduces a novel method of spectrum sensing in communication systems that utilizes nonuniform sampling in conjunction with a suitable spectral analysis tool. It is referred to here as spectral analysis for randomized sampling (SARS). Owing to the deployment of nonuniform sampling, the proposed technique can accomplish the sensing task by using sampling rates well below the ones demanded by uniform-sampling-based digital signal processing (DSP). The effect of the cyclostationary nature of the incoming digital communication signal on the adequacy of the adopted periodogram-type estimator for the spectrum sensing operation is addressed. The statistical characteristics of the estimator are presented. General reliability conditions on the length of the required signal observation window, i.e., sensing time, for a chosen sampling rate or vice versa are provided amid a sought system performance. The impact of the presence of noise and processing transmissions with various power levels on the derived dependability recommendations is given. The analytical results are illustrated by numerical examples. This paper establishes a new framework for efficient spectrum sensing where considerable savings on the sampling rate and number of processed samples can be attained.
Parallel execution of multi-set constraint rewrite rules

Multi-set constraint rewriting allows for a highly parallel computational model and has been used in a multitude of application domains such as constraint solving, agent specification etc. Rewriting steps can be applied simultaneously as long as they do not interfere with each other.We wish that the underlying constraint rewrite implementation executes rewrite steps in parallel on increasingly popular becoming multi-core architectures. We design and implement efficient algorithms which allow for the parallel execution of multi-set constraint rewrite rules. Our experiments show that we obtain some significant speed-ups on multi-core architectures
Empirical Corrections for Basin Effects in Stochastic Ground-Motion Prediction

Amplification corrections are presented for the finite-fault stochastic ground-motion simulation model; these corrections represent the total effect of the Los Angeles basin on the ground-motion spectra. Spectral amplification ratios were calculated by dividing the observed spectra for the 1994 Northridge and 1987 Whittier Narrows earthquakes, including shear- and basin-generated waves, by the simulated spectra created assuming an average rock-site condition. Smoothed amplification data were plotted above 3D images of the basin revealing a general correlation between the estimated basin depth and total basin amplification for both earthquakes over three frequency ranges: low (0.2-2 Hz), intermediate (2-8 Hz), and high (8-12.5 Hz). The depth-dependent corrections are derived from the regression of the combined data from both earthquakes in order to reduce an uncertainty caused by the azimuth of incoming waves. Ground-motion duration is defined as the time for 95% of the acceleration spectral energy to pass after the S -wave arrival. Due to ambiguity in defining a basin parameter controlling duration, it was impossible to develop a generic equation that would relate the duration ratio (observed/synthetic) to some characteristic of the basin. Users are cautioned, though, that the durations within the basin may be as much as four times longer than the simulated ones. The procedure is outlined for potential users who wish to use the results of this study in synthesizing more accurate earthquake ground motions, taking into account complicated basin-geometry and near-surface effects. The results are directly applicable to engineering simulation of strong ground motions in a sedimentary-basin environment. Manuscript received 21 May 2002.
First Report of Outbreaks of the Fall Armyworm Spodoptera frugiperda (J E Smith) (Lepidoptera, Noctuidae), a New Alien Invasive Pest in West and Central Africa

The fall armyworm Spodoptera frugiperda is a prime noctuid pest of maize on the American continents where it has remained confined despite occasional interceptions by European quarantine services in recent years. The pest has currently become a new invasive species in West and Central Africa where outbreaks were recorded for the first time in early 2016. The presence of at least two distinct haplotypes within samples collected on maize in Nigeria and São Tomé suggests multiple introductions into the African continent. Implications of this new threat to the maize crop in tropical Africa are briefly discussed.