Miracle-dz/UniFAR-FTUs huggingface dataset:
Flexibly Instructable Agents

This paper presents an approach to learning from situated, interactive tutorial instruction within an ongoing agent. Tutorial instruction is a flexible (and thus powerful) paradigm for teaching tasks because it allows an instructor to communicate whatever types of knowledge an agent might need in whatever situations might arise. To support this flexibility, however, the agent must be able to learn multiple kinds of knowledge from a broad range of instructional interactions. Our approach, called situated explanation, achieves such learning through a combination of analytic and inductive techniques. It combines a form of explanation-based learning that is situated for each instruction with a full suite of contextually guided responses to incomplete explanations. The approach is implemented in an agent called INSTRUCTO-SOAR that learns hierarchies of new tasks and other domain knowledge from interactive natural language instructions. INSTRUCTO-SOAR meets three key requirements of flexible instructability that distinguish it from previous systems: (1) it can take known or unknown commands at any instruction point; (2) it can handle instructions that apply to either its current situation or to a hypothetical situation specified in language (as in, for instance, conditional instructions); and (3) it can learn, from instructions, each class of knowledge it uses to perform tasks.
Effects of IRF5 Lupus Risk Haplotype on Pathways Predicted to Influence B Cell Functions

Both genetic and environmental interactions affect systemic lupus erythematosus (SLE) development and pathogenesis. One known genetic factor associated with lupus is a haplotype of the interferon regulatory factor 5 (IRF5) gene. Analysis of global gene expression microarray data using gene set enrichment analysis identified multiple interferon- and inflammation-related gene sets significantly overrepresented in cells with the risk haplotype. Pathway analysis using expressed genes from the significant gene sets impacted by the IRF5 risk haplotype confirmed significant correlation with the interferon pathway, Toll-like receptor pathway, and the B-cell receptor pathway. SLE patients with the IRF5 risk haplotype have a heightened interferon signature, even in an unstimulated state (P = 0.011), while patients with the IRF5 protective haplotype have a B cell interferon signature similar to that of controls. These results identify multiple genes in functionally significant pathways which are affected by IRF5 genotype. They also establish the IRF5 risk haplotype as a key determinant of not only the interferon response, but also other B-cell pathways involved in SLE.
Macroeconomic and Labor Market Impact of Russian Immigration in Israel

From the end of 1989 to 1997, over 710 thousand Russian Jews emigrated to Israel, increasing Israel-s working-age population by 15 percent. This paper argues that a canonical one-sector neoclassical growth model explains both the short run and the medium run response of Israel,s economy to this shock. Specifically, we show that average effective wages of native Israelis fell and the return to capital increased during the height of the influx in 1990 and 1991. By 1997 however, both average wages and the return to capital had returned to pre-immigration levels due to an investment boom induced by the initial increase in the return to capital. As predicted by an intertemporal model of the current account, the investment boom was largely financed by external borrowing. Furthermore, despite the high educational levels of the Russian immigrants, the Russian influx did not lower the skill-premia of native Israelis. We show that this result is not explained by Rybczynski-type output composition changes but because the Russian immigrants suffered from substantial occupational downgrading in Israel and thus did not change the relative supply of skilled workers in Israel.
Changing the Story: Implications of Narrative on Teacher Identity

This study takes a qualitative approach to understanding the connections among narrative, professional identity, and reputation management in public education. Through 15 interviews and five focus groups with high-achieving teachers and administrators, researchers explored the narratives these educators share to understand and improve the story of the teaching profession. Central to the findings are societal, organizational, and community-level factors that have led to a reputation crisis for the profession of teaching and thus contribute to the national teacher shortage. Ultimately, this study points to the notion that a shift in the perception of the value of teaching and teachers can be affected when narratives are understood and the principles of reputation management are applied. Communication interventions that provide a path forward are discussed.
Sprouting of active nerve terminals in partially inactive muscles of the rat.

1. Certain muscles in the hind foot of rats were partially paralysed by applying tetrodotoxin to part of their motor innervation. In these muscles motor nerve sprouting occurred from the terminals of the unblocked axons. The extent of sprouting was compared with that seen in totally paralysed and in partially denervated muscles. 2. Action potentials were blocked in the medial and lateral plantar nerves of adult rats for 5‐13 days by continuous superfusion with a solution containing tetrodotoxin. The drug was delivered through a tube and nerve cuff from an osmotic pump placed intraperitoneally. Control experiments showed that nerve block was complete and that signs of nerve damage were absent in the animals included in the study. 3. Two muscles (the second lumbrical and flexor digitorum brevis), which received innervation only from the medial plantar nerve, were totally paralysed by the nerve block. Two different muscles (the fourth lumbrical and flexor digitorum quinti brevis) were only partially paralysed, since they received their innervation from the lateral plantar nerve and, in addition, from the sural nerve which was not blocked. One day before the final experiment, the lateral plantar nerve was cut, and its terminals degenerated. Thus in the partially paralysed muscles only the unblocked terminals from the sural nerve remained. These terminals were observed after staining with zinc iodide and osmium tetroxide. Similarly, terminals from the medial plantar nerve were examined in the totally blocked muscles from the same animal. 4. In other experiments, muscles were partially denervated by cutting the lateral plantar nerve in order to compare effects of nerve block and nerve section. 5. Sprouting occurred under all three conditions. Active terminals in the muscles partially paralysed for 5‐7 days sprouted to the same extent as terminals in muscles totally blocked during the same period: about 35% of the terminals had sprouts, and their average length was about 13 micron. Sprouting was more pronounced in partially denervated muscles: about 65% of the terminals had sprouts and they averaged 24 micron in length. Collateral (preterminal) sprouts were seen only after partial denervation. 6. Physiological and histological observations suggested that sprouts in paralysed muscles, unlike those in partially denervated muscles, seldom if ever made new synapses on neighbouring muscle fibres, even after 12‐13 days of nerve block. 7. The results show that inactive muscle fibres cause active nerve terminals on neighbouring fibres to sprout, perhaps by releasing a diffusible, sprout‐promoting factor, which is part of the stimulus for motor nerve sprouting in partially denervated muscles.
Magnetic moments of the octet baryons in the colour-dielectric model

Baryon magnetic moments are calculated in the colour-dielectric model with pion and kaon loops. The only free parameter of the model is determined from the nucleon isoscalar radius, and all SU(3) symmetry breaking, including that in the quark sector, is determined by mesonic masses and decay constants. Good agreement with experiment is obtained for the ratios of the magnetic moments, but the inclusion of kaons does not improve the results. The results obtained in this approach are significantly better than any that have been obtained in hedgehog-based models.
Estimating Extracellular Spike Waveforms from CA1 Pyramidal Cells with Multichannel Electrodes

Extracellular (EC) recordings of action potentials from the intact brain are embedded in background voltage fluctuations known as the “local field potential” (LFP). In order to use EC spike recordings for studying biophysical properties of neurons, the spike waveforms must be separated from the LFP. Linear low-pass and high-pass filters are usually insufficient to separate spike waveforms from LFP, because they have overlapping frequency bands. Broad-band recordings of LFP and spikes were obtained with a 16-channel laminar electrode array (silicone probe). We developed an algorithm whereby local LFP signals from spike-containing channel were modeled using locally weighted polynomial regression analysis of adjoining channels without spikes. The modeled LFP signal was subtracted from the recording to estimate the embedded spike waveforms. We tested the method both on defined spike waveforms added to LFP recordings, and on in vivo-recorded extracellular spikes from hippocampal CA1 pyramidal cells in anaesthetized mice. We show that the algorithm can correctly extract the spike waveforms embedded in the LFP. In contrast, traditional high-pass filters failed to recover correct spike shapes, albeit produceing smaller standard errors. We found that high-pass RC or 2-pole Butterworth filters with cut-off frequencies below 12.5 Hz, are required to retrieve waveforms comparable to our method. The method was also compared to spike-triggered averages of the broad-band signal, and yielded waveforms with smaller standard errors and less distortion before and after the spike.
A Minimal Model of a Central Pattern Generator and Motoneurons for Insect Locomotion

We adapt the generic three-dimensional bursting neuron model derived in the companion paper [SIAM J. Appl. Dyn. Syst. , 3 (2004), pp. 636--670] to model central pattern generator interneurons and slow and fast motoneurons in insect locomotory systems. Focusing on cockroach data, we construct a coupled network that retains sufficient detail to allow investigation and prediction of biophysical parameter changes. We show that the model can encompass stepping frequency, duty cycle, and motoneuron output variations observed in cockroaches, and we reduce it to an analytically tractable symmetric network of coupled phase oscillators from which general principles can be extracted. The model's modular form allows dynamical analyses of individual components and the addition of other components, so we expect it to be more generally useful.
Research on ship slanting rudder anti-pitching intelligent adaptive Generalized Predictive Control

This article presents a method to build a T-S fuzzy model based on Generalized Dynamic Fuzzy Neural Network (GD-FNN) of Elliptical Basis Function in order to solve the problem of ship motion model's uncertainty and nonlinearity. The proposed method needs neither prior fuzzy neural networks structure knowledge nor prior training phase, it can be used to build the nonlinear and uncertain part through online adaptive learning algorithm. The fuzzy rules could be generated and pruned on-line by learning. The ship vertical (heave and pitch) dynamic linear adaptive CARMA model can be got by local dynamic linearization at each sampling point. Then Generalized Predictive Control (GPC) law is deduced by combining adaptive linear model with generalized predictive control. Simulation experiment shows that this algorithm is effective and efficient, its anti-pitching effect reaches 82.2%.
Pulsed-field gradient nuclear magnetic resonance as a tool for studying translational diffusion, part 1: basic theory

Translational diffusion is the most fundamental form of transport in chemical and biochemical systems. Pulsed-field gradient nuclear magnetic resonance provides a convenient and noninvasive means for measuring translational motion. In this method the attenuation of the echo signal from a Hahn spin-echo pulse sequence containing a magnetic field gradient pulse in each τ period is used to measure the displacement of the observed spins. In the present article, the physical basis of this method is considered in detail. Starting from the Bloch equations containing diffusion terms, the (analytical) equation linking the echo attenuation to the diffusion of the spin for the case of unrestricted isotropic diffusion is derived. When the motion of the spin occurs within a confined geometry or is anisotropic, such as in in vivo systems, the echo attenuation also yields information on the surrounding structure, but as the analytical approach becomes mathematically intractable, approximate or numerical means must be used to extract the motional information. In this work, two common approximations are considered and their limitations are examined. Measurements in anisotropic systems are also considered in some detail. ©1997 John Wiley & Sons, Inc. Concepts Magn Reson 9: 299–336, 1997
An Algorithm for Verication and Change Detection Between 3D Geospatial Databases and Aerial Images

: An algorithm for building detection in aerial images is presented. The algorithm is based on a combination of unsupervised segmentation and selection of a training set based on existing building registrations. The classiﬁcation/detection step is based on individual comparison of the segments, represented by their covariance matrices, which are compared using a suitable metric.
An efficient implementation and evaluation of Reid's multiple hypothesis tracking algorithm for visual tracking

An efficient implementation of Reid's multiple hypothesis tracking (MHT) algorithm is presented in which the the k-best hypotheses are determined in polynomial time using an algorithm due to Murty (1968). The MHT algorithm is then applied to several motion sequences. The MHT capabilities of track initiation, termination and continuation are demonstrated. Continuation allows the MHT to function despite temporary occlusion of tracks. Between 50 and 150 corner features are simultaneously tracked in the image plane over a sequence of up to 60 frames. Each corner is tracked using a simple linear Kalman filter and any data association uncertainty is resolved by the MHT. Kalman filter parameter estimation is discussed and experimental results show that the algorithm is robust to errors in the motion model.
An Object-Based Classification of Mangroves Using a Hybrid Decision Tree - Support Vector Machine Approach

Mangroves provide valuable ecosystem goods and services such as carbon sequestration, habitat for terrestrial and marine fauna, and coastal hazard mitigation. The use of satellite remote sensing to map mangroves has become widespread as it can provide accurate, efficient, and repeatable assessments. Traditional remote sensing approaches have failed to accurately map fringe mangroves and true mangrove species due to relatively coarse spatial resolution and/or spectral confusion with landward vegetation. This study demonstrates the use of the new Worldview-2 sensor, Object-based image analysis (OBIA), and support vector machine (SVM) classification to overcome both of these limitations. An exploratory spectral separability showed that individual mangrove species could not be spectrally separated, but a distinction between true and associate mangrove species could be made. An OBIA classification was used that combined a decision-tree classification with the machine-learning SVM classification. Results showed an overall accuracy greater than 94% (kappa = 0.863) for classifying true mangroves species and other dense coastal vegetation at the object level. There remain serious challenges to accurately mapping fringe mangroves using remote sensing data due to spectral similarity of mangrove and associate species, lack of clear zonation between species, and mixed pixel effects, especially when vegetation is sparse or degraded.
A Supervised Learning Approach Towards Profiling the Preservation of Authorial Style in Literary Translations

Recently there has been growing interest in the application of approaches from the text classification literature to fine-grained problems of textual stylometry. This paper seeks to answer a question which has concerned the translation studies community: how does a literary translator’s style vary across their translations of different authors? This study focuses on the works of Constance Garnett, one of the most prolific English-language translators of Russian literature, and uses supervised learning approaches to analyse her translations of three well-known Russian authors, Ivan Turgenev, Fyodor Dosteyevsky and Anton Chekhov. This analysis seeks to identify common linguistic patterns which hold for all of the translations from the same author. Based on the experimental results, it is ascertained that both document-level metrics and n-gram features prove useful for distinguishing between authorial contributions in our translation corpus and their individual efficacy increases further when these two feature types are combined, resulting in classification accuracy of greater than 90 % on the task of predicting the original author of a textual segment using a Support Vector Machine classifier. The ratio of nouns and pronouns to total tokens are identified as distinguishing features in the document metrics space, along with occurrences of common adverbs and reporting verbs from the collection of n-gram features.
A Duplex PCR-Based Assay for Measuring the Amount of Bacterial Contamination in a Nucleic Acid Extract from a Culture of Free-Living Protists

Background Cultures of heterotrophic protists often require co-culturing with bacteria to act as a source of nutrition. Such cultures will contain varying levels of intrinsic bacterial contamination that can interfere with molecular research and cause problems with the collection of sufficient material for sequencing. Measuring the levels of bacterial contamination for the purposes of molecular biology research is non-trivial, and can be complicated by the presence of a diverse bacterial flora, or by differences in the relative nucleic acid yield per bacterial or eukaryotic cell. Principal Findings Here we describe a duplex PCR-based assay that can be used to measure the levels of contamination from marine bacteria in a culture of loricate choanoflagellates. By comparison to a standard culture of known target sequence content, the assay can be used to quantify the relative proportions of bacterial and choanoflagellate material in DNA or RNA samples extracted from a culture. We apply the assay to compare methods of purifying choanoflagellate cultures prior to DNA extraction, to determine their effectiveness in reducing bacterial contamination. Together with measurements of the total nucleic acid concentration, the assay can then be used as the basis for determining the absolute amounts of choanoflagellate DNA or RNA present in a sample. Conclusions The assay protocol we describe here is a simple and relatively inexpensive method of measuring contamination levels in nucleic acid samples. This provides a new way to establish quantification and purification protocols for molecular biology and genomics in novel heterotrophic protist species. Guidelines are provided to develop a similar protocol for use with any protistan culture. This assay method is recommended where qPCR equipment is unavailable, where qPCR is not viable because of the nature of the bacterial contamination or starting material, or where prior sequence information is insufficient to develop qPCR protocols.
Adults in Training: An International Comparison of Continuing Education and Training.

Data from the International Adult Literacy Survey (IALS) were analyzed to compare the incidence and volume of continuing education (CE) and training among adults in the following countries: Australia, Belgium, Canada, Ireland, the Netherlands, New Zealand, Poland, Switzerland, the United Kingdom, and the United States. The following were among the key findings of the analysis: (1) in all 10 countries, employed adults are more likely than unemployed adults to participate in CE or training; (2) participation in job-related training is substantially higher than participation in education and training undertaken for personal or other reasons; (3) participation rates do not differ substantially by gender; (4) participation rates are higher among adults who already possess higher-level educational qualifications; (5) younger adults are more likely than their older counterparts to participate in CE or training; (6) individuals working in large firms and organizations are more likely to participate in CE; and (7) in all countries studied, employers were by far the most common financial sponsors of all training and job-related training in particular. (Appended are a table detailing enrollments in education and training courses by selected populations and a table detailing responses to the IALS by target populations in the 10 study countries.) (MN) Reproductions supplied by EDRS are the best that can be made from the original document. Unclassified CERVVVD(99)1 OECD Organisation de Cooperation et de Developpement Economiques OLIS : 07-Apr-1999 OMOrganisation for Economic Co-operation and Development Dist. : 09-Apr-1999 OCDE
A Latent Variable Model for Discourse-aware Concept and Entity Disambiguation

This paper takes a discourse-oriented perspective for disambiguating common and proper noun mentions with respect to Wikipedia. Our novel approach models the relationship between disambiguation and aspects of cohesion using Markov Logic Networks with latent variables. Considering cohesive aspects consistently improves the disambiguation results on various commonly used data sets.
Eyeball and blink controlled firing system for military tank using LabVIEW

Presently, most of the modern military tanks require 4 members to operate. In this paper, we try to reduce the number of persons to operate the tank by one and increase the ease of targeting enemies. This is achieved by controlling the firing systems of the tank with the help of eyeball movement and blink. Image of the eye is captured using a camera, which is placed in front of the eye, and centroid of the iris is found to track the eye. The turret's vertical as well as horizontal position is controlled using the eyeball movement and the gun can be fired with the help of blink. It is possible to switch between the main gun and the machine gun with ease. The machine gun is also controlled in a similar manner. Thus, our system allows the driver to control the tank as well as the firing system thereby reducing number of people to control the tank.
Trace driven dynamic deadlock detection and reproduction

Dynamic analysis techniques have been proposed to detect potential deadlocks. Analyzing and comprehending each potential deadlock to determine whether the deadlock is feasible in a real execution requires significant programmer effort. Moreover, empirical evidence shows that existing analyses are quite imprecise. This imprecision of the analyses further void the manual effort invested in reasoning about non-existent defects. In this paper, we address the problems of imprecision of existing analyses and the subsequent manual effort necessary to reason about deadlocks. We propose a novel approach for deadlock detection by designing a dynamic analysis that intelligently leverages execution traces. To reduce the manual effort, we replay the program by making the execution follow a schedule derived based on the observed trace. For a real deadlock, its feasibility is automatically verified if the replay causes the execution to deadlock. We have implemented our approach as part of WOLF and have analyzed many large (upto 160KLoC) Java programs. Our experimental results show that we are able to identify 74% of the reported defects as true (or false) positives automatically leaving very few defects for manual analysis. The overhead of our approach is negligible making it a compelling tool for practical adoption.