Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning in Real-Time Search: A Unifying Framework

Real-time search methods are suited for tasks in which the agent is interacting with an initially unknown environment in real time. In such simultaneous planning and learning problems, the agent has to select its actions in a limited amount of time, while sensing only a local part of the environment centered at the agent's current location. Real-time heuristic search agents select actions using a limited lookahead search and evaluating the frontier states with a heuristic function. Over repeated experiences, they refine heuristic values of states to avoid infinite loops and to converge to better solutions. The wide spread of such settings in autonomous software and hardware agents has led to an explosion of real-time search algorithms over the last two decades. Not only is a potential user confronted with a hodgepodge of algorithms, but he also faces the choice of control parameters they use. In this paper we address both problems. The first contribution is an introduction of a simple three-parameter framework (named LRTS) which extracts the core ideas behind many existing algorithms. We then prove that LRTA*, E-LRTA* , SLA*, and γ-Trap algorithms are special cases of our framework. Thus, they are unified and extended with additional features. Second, we prove completeness and convergence of any algorithm covered by the LRTS framework. Third, we prove several upper-bounds relating the control parameters and solution quality. Finally, we analyze the influence of the three control parameters empirically in the realistic scalable domains of real-time navigation on initially unknown maps from a commercial role-playing game as well as routing in ad hoc sensor networks.
A comparative evaluation of smear layer removal by using edta, etidronic acid, and maleic acid as root canal irrigants: An in vitro scanning electron microscopic study

Aim: The purpose of this study is to evaluate and compare the efficacy of 17% EDTA, 18% etidronic acid, and 7% maleic acid in smear layer removal using scanning electron microscopic image analysis. Materials and Methods: Thirty, freshly extracted mandibular premolars were used. The teeth were decoronated to obtain working length of 17mm and instrumentation up to 40 size (K file) with 2.5% NaOCl irrigation between each file. The samples were divided into Groups I (17% ethylenediaminetetraacetic acid (EDTA)), II (18% etidronic acid), and III (7% maleic acid) containing 10 samples each. Longitudinal sectioning of the samples was done. Then the samples were observed under scanning electron microscope (SEM) at apical, middle, and coronal levels. The images were scored according to the criteria: 1. No smear layer, 2. moderate smear layer, and 3 heavy smear layer. Statistical Analysis: Data was analyzed statistically using Kruskal–Wallis analysis of variance (ANOVA) followed by Mann-Whitney U test for individual comparisons. The level for significance was set at 0.05. Results: The present study showed that all the three experimental irrigants removed the smear layer from different tooth levels (coronal, middle, and apical). Final irrigation with 7% maleic acid is more efficient than 17% EDTA and 18% etidronic acid in the removal of smear layer from the apical third of root canal.
Polygonal approximation of digital planar curve using local integral deviation

An algorithm for polygonal approximation based on local integral deviation is presented. The algorithm is tested on various shapes with varying number of dominant points. A comparative study of the proposed procedure with other iterative methods shows that the proposed procedure produces polygon from a digital curve approximating high as well as low curvature regions with almost equal precision.
Emotional Processing of Infants Displays in Eating Disorders

Aim The aim of this study is to examine emotional processing of infant displays in people with Eating Disorders (EDs). Background Social and emotional factors are implicated as causal and maintaining factors in EDs. Difficulties in emotional regulation have been mainly studied in relation to adult interactions, with less interest given to interactions with infants. Method A sample of 138 women were recruited, of which 49 suffered from Anorexia Nervosa (AN), 16 from Bulimia Nervosa (BN), and 73 were healthy controls (HCs). Attentional responses to happy and sad infant faces were tested with the visual probe detection task. Emotional identification of, and reactivity to, infant displays were measured using self-report measures. Facial expressions to video clips depicting sad, happy and frustrated infants were also recorded. Results No significant differences between groups were observed in the attentional response to infant photographs. However, there was a trend for patients to disengage from happy faces. People with EDs also reported lower positive ratings of happy infant displays and greater subjective negative reactions to sad infants. Finally, patients showed a significantly lower production of facial expressions, especially in response to the happy infant video clip. Insecure attachment was negatively correlated with positive facial expressions displayed in response to the happy infant and positively correlated with the intensity of negative emotions experienced in response to the sad infant video clip. Conclusion People with EDs do not have marked abnormalities in their attentional processing of infant emotional faces. However, they do have a reduction in facial affect particularly in response to happy infants. Also, they report greater negative reactions to sadness, and rate positive emotions less intensively than HCs. This pattern of emotional responsivity suggests abnormalities in social reward sensitivity and might indicate new treatment targets.
Improving transparency in physical human-robot interaction using an impedance compensator

In the physical human-robot interaction system, improving transparency performance which allows humans to move as if there is no robot is a challenging topic. In general physical human-robot interaction, the multiaxial force sensor is used to control the robot. However the signal measured from the force sensor involves not only the force applied to the robot by the human motion intention but also the influence of the natural force feedback between the robot and the human hand due to the motion of the robot. Therefore, in order to improve the transparency performance, it is necessary to consider the dynamics of the human hand as well as the dynamics of the robot. In this paper, an novel algorithm to improve transparency performance is proposed. The proposed algorithm uses only the multiaxial force sensor and compensates the natural force feedback by using the human hand impedance and further improves the transparency performance which has a limitation adjusting admittance parameters. The validity of the proposed algorithm is described through the system model analysis and the experiment using the hydraulic upper limb exoskeleton.
Mushu, a free- and open source BCI signal acquisition, written in Python

The following paper describes Mushu, a signal acquisition software for retrieval and online streaming of Electroencephalography (EEG) data. It is written, but not limited, to the needs of Brain Computer Interfacing (BCI). It's main goal is to provide a unified interface to EEG data regardless of the amplifiers used. It runs under all major operating systems, like Windows, Mac OS and Linux, is written in Python and is free- and open source software licensed under the terms of the GNU General Public License.
Evaluation and Use of Registry Data in a GIS Analysis of Diabetes

Objectives to evaluate registry data routinely collected by the Chronic Disease Electronic Management System (CDEMS) in the monitoring of type 2 diabetes mellitus (T2DM) in the Eastern half of the island and use the data to describe the spatial epidemiological patterns of T2DM. Design and Method The starting point was access and retrival of all exsisting data on the diabetes registry. This data was subsequently validated using handwritten medical records. Several clinical indicators were selected to evaluate the registry. The address of each patient was extracted and georeferenced using ArcGIS 10.0 and several maps were created. Results The registry had data for thirteen (13) out of the sixteen (16) health facilities. We found that less than 15 percent of all patients actually had diabetic indicator tests done according to World Health Organization (WHO) standards. The overall prevalence of T2DM was 20.8 per 1000 population. The highest prevalence of diabetes occurred at the northeastern tip of the island. In addition 57.58% of patients with T2DM resided inland and 40.75% of patients residing on the coastal areas. Conclusions In conclusion, we provide evidence that the data collected by the diabetes registry although lacking in many areas was adequate for spatial epidemiological analysis.
Sublanguage Terms: Dictionaries, Usage, and Automatic Classification

The use of terms from natural and social scientific titles and abstracts is studied from the perspective of sublanguages and their specialized dictionaries. Different notions of sublanguage distinctiveness are explored. Objective methods for separating hard and soft sciences are suggested based on measures of sublanguage use, dictionary characteristics, and sublanguage distinctiveness. Abstracts were automatically classified with a high degree of accuracy by using a formula that considers the degree of uniqueness of terms in each sublanguage. This may prove useful for text filtering or information retrieval systems. © 1995 John Wiley & Sons, Inc.
Efficient high-current field emission from arrays of CNT columns

At present carbon nanotubes (CNT) are the most prospective cathode material for triode applications because of their strong field emission (FE) at low electric fields. The FE homogeneity of flat CNT cathodes, however, is still limited by their rather fast and uncontrolled growth which usually leads to strongly varying field enhancement and current carrying capability of the individual emitters. Therefore, patches with multiple emitters might provide a suitable strategy to improve the homogeneity and current stability of CNT cathodes. Accordingly, structured arrays of CNT based columns on flat n-Si substrates were fabricated applying the atmospheric-pressure CVD method with a volatile catalyst source (ferrocene/xylene mixture). Substrates of 6×6 mm2 size and 4 quadrants of 2×2 mm2 with varying patch diameter and two pitch sizes were structured by means of photolithography and selective chemical etching of the thermal 0.3 μm thick SiO2 oxide layer. Preferential growth of CNT in the opened windows of the SiO2 layer was achieved by adjusting the parameters of the synthesis process, i.e. the temperature in the reaction zone, the growth time, the concentration of the catalyst in the feeding solution, the gas-carrier flow rate etc. as described elsewhere [1]. The resulting multiwall CNT for growth times of 30 s and 2 min formed vertically aligned arrays of uniform columns of about 20 μm and 50 μm net height with a pitch to patch ratio of 160/50, 100/50, 100/30 and 100/10 (μm) as ahown in Fig. 1. Obviously, preferential CNT column growth embedded in a floor of shorter CNT is fairly achieved.
Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states.
Digital rights management, copyright, and Napster

Digital Rights Management technologies in the field of copyright protection should meet four objectives: • give consumers new freedom to enjoy music and other forms of content; • give copyright owners and other value chain participants the means to manage and protect their rights in published works; • implement elements of law, such as copyright exceptions, that ensure that rights are managed in accordance with the public interest; • provide users with the means to manage their legitimate personal rights and interests.We sketch how these goals can be achieved with current technology for peer-to-peer Digital Rights Management (DRM). This technology can ensure the neutrality, security, commercial reliability, and trusted interoperability of applications and services used to protect and manage rights in all forms of information, including creative works protected by copyright. The rapidly evolving area of digital commerce in information requires a framework of commercial trust comparable in scope, and at least as reliable, as the systems of trust that underpin commerce in the physical world.
A Mediterranean diet lowers blood pressure and improves endothelial function: results from the MedLey randomized intervention trial.

Background: The consumption of a Mediterranean diet (MedDiet) is associated with a lower risk of cardiovascular disease. However, its impact on blood pressure and endothelial function is not clear.Objective: We sought to determine the effects of adhering to the consumption of a MedDiet for 6 mo on blood pressure and endothelial function in older, healthy Australians.Design: A total of 166 men and women aged >64 y were allocated via minimization to consume either a MedDiet (n = 85) or their habitual diet (HabDiet; control: n = 81) for 6 mo. The MedDiet comprised mainly plant foods, abundant extra-virgin olive oil, and minimal red meat and processed foods. A total of 152 participants commenced the study, and 137 subjects completed the study. Home blood pressure was measured on 5 consecutive days at baseline (n = 149) and at 3 and 6 mo. Endothelial function (n = 82) was assessed by flow-meditated dilatation (FMD) at baseline and 6 mo. Dietary intake was monitored with the use of 3-d weighed food records. Data were analyzed with the use of linear mixed-effects models to determine adjusted between-group differences.Results: The MedDiet adherence score increased significantly in the MedDiet group but not in the HabDiet group (P < 0.001). The MedDiet, compared with the HabDiet, resulted in lower systolic blood pressure (P-diet × time interaction = 0.02) [mean: -1.3 mm Hg (95% CI: -2.2, -0.3 mm Hg; P = 0.008) at 3 mo and -1.1 mm Hg (95% CI: -2.0, -0.1 mm Hg; P = 0.03) at 6 mo]. At 6 mo, the percentage of FMD was higher by 1.3% (95% CI: 0.2%, 2.4%; P = 0.026) in the MedDiet group.Conclusion: Australian men and women who consumed a MedDiet for 6 mo had small but significantly lower systolic blood pressure and improved endothelial function. This trial was registered at www.anzctr. org.au as ACTRN12613000602729.
Speech Enhancement with Applications in Speech Recognition

The objective of this research is to develop feature compensation techniques to make automatic speech recognition (ASR) systems more robust to noise distortions. The research is important as the performance of ASR systems degrades dramatically in adverse environments, and hence greatly limits the speech recognition application deployment. In this report, we aim to build a generic framework for feature compensation to improve speech recognition accuracy by making speech features less affected by noises. The degradation of ASR systems under noisy conditions is due to the mismatch between the clean-trained acoustical models and noisy testing speech features presented to the speech recognition engine. Currently, two general approaches are proposed to reduce this mismatch. The first is to adapt the acoustical model to the noisy testing feature, the other is to compensate the noisy testing feature prior to the recognition. We review existing techniques for noise robust speech recognition and find that these techniques generally ignore inter-frame information of the speech signal. We however believe that inter-frame statistics can contribute to noisy speech features compensation and hence propose a vector autoregressive (VAR) model to model speech feature vectors for speech feature reconstruction by either past or future frames prediction. We propose two feature compensation schemes based on the VAR model and the missing feature theory (MFT). Experiments are carried out using the ground-truth data mask on the AURORA-2 database, and our results show significant improvement to recognition accuracy. Specifically, our experimental results showed a relative error rate reductions of 86.51% and 93.9% with respect to the baseline for the subway noise case of test set A and restaurant noise case of test set B at signal to noise ratio equals to -5dB. The proposed VAR modeling framework is a promising research direction and we will conduct further research to exploit the full potential of this technique.
Influence of Oral Glucose Ingestion on Splanchnic Glucose and Gluconeogenic Substrate Metabolism in Man

To evaluate the role of splanchnic and peripheral tissues in the disposal of an oral glucose load, splanchnic exchange of glucose, lactate, pyruvate, glycerol and amino acids was determined in ten healthy subjects in the basal state and for three hours following the oral ingestion of 100 gm. of glucose. Following glucose ingestion, splanchnic glucose output rose rapidly, reaching values two to three times the basal rate at fifteen minutes and returning to baseline by ninety minutes. A secondary rise in splanchnic glucose output occurred at 150 minutes and coincided with a secondary increment in arterial glucose. Total splanchnic glucose output over three hours was 40 ± 3 gm. , representing a total increase of only 15 ± 3 gm. above basal splanchnic glucose output. The peak rise in blood glucose was directly proportional to the increase in splanchnic glucose output. Arterial concentrations of alanine, lactate and pyruvate rose by 15, 65 and 80 per cent, respectively, following oral glucose. These arterial elevations were preceded by a 75–100 per cent inhibition of splanchnic uptake of alanine and lactate; in the case of pyruvate there was a reversal from a net uptake in the basal state to a significant net splanchnic output after glucose ingestion. Arterial glycerol fell by 50 per cent and was accompanied by a comparable fall in splanchnic uptake. It is concluded that in normal, postabsorptive man, (a) the major portion of a 100 gm. oral glucose load is retained within the splanchnic bed; (b) only 15 per cent of the ingested glucose is available for disposal by peripheral tissues as increased (abovebasal) glucose utilization; (c) the height and shape of the oral glucose tolerance curve are largely determined by the rate and pattern of splanchnic glucose escape; (d) glucose-induced hyperlactatemia, hyperpyruvicemia and hyperalaninemia are due at least in part, to altered splanchnic exchange of these substrates.
Robust Word Sense Translation by EM Learning of Frame Semantics

We propose a robust method of automatically constructing a bilingual word sense dictionary from readily available monolingual ontologies by using estimation-maximization, without any annotated training data or manual tuning. We demonstrate our method on the English FrameNet and Chinese HowNet structures. Owing to the robustness of EM iterations in improving translation likelihoods, our word sense translation accuracies are very high, at 82% on average, for the 11 most ambiguous words in the English FrameNet with 5 senses or more. We also carried out a pilot study on using this automatically generated bilingual word sense dictionary to choose the best translation candidates and show the first significant evidence that frame semantics are useful for translation disambiguation. Translation disambiguation accuracy using frame semantics is 75%, compared to 15% by using dictionary glossing only. These results demonstrate the great potential for future application of bilingual frame semantics to machine translation tasks.
Among-Population Variation in Microbial Community Structure in the Floral Nectar of the Bee-Pollinated Forest Herb Pulmonaria officinalis L

Background Microbial communities in floral nectar have been shown to be characterized by low levels of species diversity, yet little is known about among-plant population variation in microbial community composition. Methodology/Principal Findings We investigated the microbial community structure (yeasts and bacteria) in floral nectar of ten fragmented populations of the bee-pollinated forest herb Pulmonaria officinalis. We also explored possible relationships between plant population size and microbial diversity in nectar, and related microbial community composition to the distance separating plant populations. Culturable bacteria and yeasts occurring in the floral nectar of a total of 100 plant individuals were isolated and identified by partially sequencing the 16S rRNA gene and D1/D2 domains of the 26S rRNA gene, respectively. A total of 9 and 11 yeast and 28 and 39 bacterial OTUs was found, taking into account a 3% (OTU0.03) and 1% sequence dissimilarity cut-off (OTU0.01). OTU richness at the plant population level (i.e. the number of OTUs per population) was low for yeasts (mean: 1.7, range: 0–4 OTUs0.01/0.03 per population), whereas on average 6.9 (range: 2–13) OTUs0.03 and 7.9 (range 2–16) OTUs0.01 per population were found for bacteria. Both for yeasts and bacteria, OTU richness was not significantly related to plant population size. Similarity in community composition among populations was low (average Jaccard index: 0.14), and did not decline with increasing distance between populations. Conclusions/Significance We found low similarity in microbial community structure among populations, suggesting that the assembly of nectar microbiota is to a large extent context-dependent. Although the precise factors that affect variation in microbial community structure in floral nectar require further study, our results indicate that both local and regional processes may contribute to among-population variation in microbial community structure in nectar.