Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain Model Acquisition with Missing Information and Noisy Data

In this work, we address the problem of learning planning domain models from example action traces that contain missing and noisy data. In many situations, the action traces that form the input to domain model acquisition systems are sourced from observations or even natural language descriptions of plans. It is often the case that these observations are noisy and incomplete. Therefore, making domain model acquisition systems that are robust to such data is crucial. Previous approaches to this problem have relied upon having access to the underlying state in the input plans. We lift this assumption and provide a system that does not require any state information. We build upon the LOCM family of algorithms, which also lift this assumption in the deterministic version of the domain model acquisition problem, to provide a domain model acquisition system that learns domain models from noisy plans with missing information.
An instrumental variable model of multiple discrete choice

This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. We show that the model delivers set identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which in parametric models require little more calculation than what is involved in a conventional maximum likelihood analysis. The results are illustrated using a model which is essentially the parametric conditional logit model of McFadden (1974) but with potentially endogenous explanatory variables and instrumental variable restrictions. The method employed has wide applicability and for the first time brings instrumental variable methods to bear on structural models in which there are multiple unobservables in a structural equation.
THE POSSIBLE DETECTION OF A BINARY COMPANION TO A TYPE IBN SUPERNOVA PROGENITOR

We present late-time observations of the site of the Type Ibn supernova (SN) 2006jc, acquired with the Hubble Space Telescope Advanced Camera for Surveys. A faint blue source is recovered at the SN position, with brightness , and mag, although there is no detection in a contemporaneous narrow-band image. The spectral energy distribution of the late-time source is well-fit by a stellar-like spectrum ( and ), subject to only a small degree of reddening—consistent with that estimated for SN 2006jc itself at early-times. The lack of further outbursts after the explosion of SN 2006jc suggests that the precursor outburst originated from the progenitor. The possibility of the source being a compact host cluster is ruled out on the basis of the source’s faintness; however, the possibility that the late-time source may be an unresolved light echo originating in a shell or sphere of pre-SN dust (within a radius ) is also discussed. Irrespective of the nature of the late-time source, these observations rule out a luminous blue variable as a companion to the progenitor of SN 2006jc.
Variable verb placement in embedded clauses: comparing English and Norwegian children

This paper reports on two priming studies focusing on embedded word order in English and Norwegian, more specifically on subject-auxiliary inversion (SAI) in embedded questions in English and verb-adverb order (V2) in that-clauses in Norwegian. While the adult languages typically disprefer SAI or V2 in embedded contexts, spontaneous data show that these word orders are produced to a certain extent in specific contexts. Research on child language has shown that children go through a stage where these word orders are relatively frequent. A priming experiment was carried out in both languages, eliciting data from both adults and children. As priming is assumed not to affect ungrammatical structures, we expected there to be priming in the child data, indicating that these word orders are part of the child grammar, but potentially not in the adult data. The results show a clear and reliable priming effect in the English child data, but no priming in the Norwegian experiments.
AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

Abstract. This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.
Photometric variability of the Herbig Ae star HD 37806

Context. The more massive counterparts of T Tauri stars, the Herbig Ae/Be stars, are known to vary in a complex way with no variability mechanism clearly identified. Aims. We attempt to characterize the optical variability of HD 37806 (MWC 120) on time scales ranging between minutes and several years. Methods. A continuous, one-minute resolution, 21 day-long sequence of MOST (Microvariability & Oscillations of STars) satellite observations has been analyzed using wavelet, scalegram and dispersion analysis tools. The MOST data have been augmented by sparse observations over 9 seasons from ASAS (All Sky Automated Survey), by previously non-analyzed ESO (European Southern Observatory) data partly covering 3 seasons and by archival measurements dating back half a century ago. Results. Mutually superimposed flares or accretion instabilities grow in size from about 0.0003 of the mean flux on a time scale of minutes to a peak-to-peak range of <0.05 on a time scale of a few years. The resulting variability has properties of stochastic “red” noise, whose self-similar characteristics are very similar to those observed in cataclysmic binary stars, but with much longer characteristic time scales of hours to days (rather than minutes) and with amplitudes which appear to cease growing in size on time scales of tens of years. In addition to chaotic brightness variations combined with stochastic noise, the MOST data show a weakly defined cyclic signal with a period of about 1.5 days, which may correspond to the rotation of the star.
ASSESSMENT OF ANALYSING BLOCK START PERFORMANCE WITHOUT ARM GROUND REACTION FORCES

The purpose of this study was to assess the analysing reaction time (RT) and normalized power when calculated using two different methods: a method using ground reaction forces (GRFs) of only the legs (legs F-based method) and a method using GRFs of arms and legs (whole F-based method). In total, 127 block start motions from fourteen male sprinters were analysed from all participants. The RT of the legs F-based method was not similar to that of the whole F-based method: the mean difference was 7.4 ms and the 95% CI was –45.1–59.8 ms. In contrast, the normalized power of the legs F-based method was similar to that of the whole F-based method. This information will help reconsider the golden standard methods currently used to analyse RT and encourage the use of analysis methods to analyse the performance in block starts.
Development of swinging part profilometer for optics

A new surface metrology instrument, the ‘Swinging Part Profilometer’ (SPP), has been developed for in-situ measurement of optics undergoing robot-processing in the ground (non-specular) state. In this paper, we present the hardware-design of the SPP, together with software for hardware-control, data-acquisition and surface-reconstruction. First results on a sample part are presented, compared with interferometric metrology, and error-contributions considered. Notably, during each individual scan of a measurement-cycle, the probe remains fixed. This lends itself to automated probe-deployment by the same robot as performs surface-processing, as probe stability is required on only the time-scale for a single scan.
A Congestion-aware Routing Scheme for Autonomous Mobility-on-Demand Systems

We study route-planning for Autonomous Mobility-on-Demand (AMoD) systems that accounts for the impact of road traffic on travel time. Specifically, we develop a congestion-aware routing scheme (CARS) that captures road-utilization-dependent travel times at a mesoscopic level via a piecewise affine approximation of the Bureau of Public Roads (BPR) model. This approximation largely retains the key features of the BPR model, while allowing the design of a real-time, convex quadratic optimization algorithm to determine congestion-aware routes for an AMoD fleet. Through a real-world case study of Manhattan, we compare CARS to existing routing approaches, namely a congestion-unaware and a threshold congestion model. Numerical results show that CARS significantly outperforms the other two approaches, with improvements in terms of travel time and global cost in the order of 20%.
KmsGC: An Unsupervised Color Image Segmentation Algorithm Based on -Means Clustering and Graph Cut

For unsupervised color image segmentation, we propose a two-stage algorithm, KmsGC, that combines -means clustering with graph cut. In the first stage, -means clustering algorithm is applied to make an initial clustering, and the optimal number of clusters is automatically determined by a compactness criterion that is established to find clustering with maximum intercluster distance and minimum intracluster variance. In the second stage, a multiple terminal vertices weighted graph is constructed based on an energy function, and the image is segmented according to a minimum cost multiway cut. A large number of performance evaluations are carried out, and the experimental results indicate the proposed approach is effective compared to other existing image segmentation algorithms on the Berkeley image database.
Diversity of Wild Mushrooms in Nagaland, India

The Indian sub-continent is blessed with favorable agro climatic conditions that are suitable to a varied range of fungal species. Though the occurrence of mushrooms is of diverse nature, they are not well studied and documented. Northeastern region of India is one of the biodiversity hotspots. Nagaland is one of the Northeastern states of India. The people of the state highly covet mushrooms and have been a delicacy since time immemorial. The present study documents the macro fungal diversity in various districts of the state. A total of 87 species of wild mushrooms were collected and identified. They are parasitic, saprophytic and ecto-mycorrhizal in habitat. The highest numbers of mushroom species were collected during May–September from the study areas. Of the collected mushrooms, 37 species were identified as edible, 21 species medicinal, 5 poisonous and 37 inedible/unclassified.
Efficiency vs. Stability in a Mixed Network Formation Model

The purpose of this paper is twofold. First, the incomplete results relative to effciency in a transitional model introduced in a previous paper, distinguishing two types of links, strong or doubly-supported and weak or singly-supported, are completed with a full-characterization. Second, as it turns out, effcient structures are stable only for a small range of values of the parameters within the much wider range where they are effcient. This motivates the study of the impact on stability of allowing players to negotiate bilaterally the shares of the cost of doubly-supported links.
Polyphenols in Monogastric Nutrition – A Review

Abstract The popularity of plant-based feed additives in livestock production has increased significantly in the last decade. Polyphenols are secondary plant metabolites which contain bioactive components and deliver positive effects for humans and animals. They are renowned for their anti-inflammatory, immunomodulatory and anti-mutagenic effects. Polyphenols have antioxidant properties, and they minimize the negative consequences of oxidative stress. Their antioxidant capacity is comparable to that of the major biological antioxidants: vitamins E and C. Despite those advantages, polyphenols are characterized by low bioavailability, and further research is needed to harness their full potential in livestock farming. This article presents a review of findings from recent studies investigating the efficacy of polyphenols in monogastric nutrition, with special emphasis on their antioxidant properties.
Mispricing and lasting arbitrage between parallel markets in the Czech Republic

If co-existing parallel markets are efficient, then arbitrage will maintain a correct pricing relationship. A related question is whether two parallel emerging markets offering more or less the same securities but using different institutional designs, can behave as a single, fully integrated market. In this paper an explicit model of price convergence (with transaction costs) is introduced, in which price differences are studied using levels of arbitrage activity. For the empirical analysis two parallel markets in the Czech Republic are used — the Prague Stock Exchange (PSE) and the RMS (over-the-counter system). In particular, the degree of arbitrage activity is studied for different segments of the PSE and the evolution of arbitrage in the early history of these emerging markets. The empirical results provide evidence of market linkage for actively traded stocks. A significant relationship is found between the segment of the market to which a given firm belongs and the estimated level of arbitrage trading. Moreover, the level of arbitrage activity increases over time for all market segments, and as the markets mature, the differences among the segments gradually disappear.
Response of ericoid mycorrhizal colonization and functioning to global change factors

Summary • Here, we investigated effects of increased atmospheric CO 2 concentration, increased temperatures, and both factors in combination on ericoid mycorrhizal colonization, mycorrhizal functioning and below-ground carbon allocation in a subarctic forest understorey, to evaluate the hypothesis that photosynthesis is a primary driver for mycorrhizal colonization. •T reatment effects on ecosystem processes were investigated using 14 C-pulse labelling and photosynthesis measurements in combination with analysis of ergosterol content in roots. The effects on δ 15 N in leaves were also studied. •E rgosterol content in hair roots was positively correlated with ecosystem photo- synthesis and was higher in heat- and CO 2 -treated plots. Leaves from CO 2 plots tended to be more depleted in 15 N compared with controls both for Vaccinium myrtillus and V. vitis-idaea . • Our results suggest that changes in ecosystem photosynthesis, plant carbon (C) allocation may give rise to changing mycorrhizal colonization under elevated CO 2 and temperature. The role of mycorrhizas in ecosystem N-cycling may change on a long-term basis as inorganic N availability declines with increasing levels of atmospheric CO 2 .
The South African clothing industry: problems experienced with body measurements

Die doel van die navorsing is om die probleme wat die Suid Afrikaanse klere-industrie ondervind, met betrekking tot liggaamsmates wat nodig is vir die vervaardiging van goedpassende klere, te ondersoek en te beskryf. Die voorsiening van klere wat aan ‘n drie-dimensionele liggaam pas, bly ‘n uitdaging, ook vir die Suid-Afrikaanse klere-industrie. Die probleme wat die verbruiker met pas ondervind kan egter nie sonder akkurate liggaamsmates aangespreek word nie.
Protective Effects of Flavonoid Baicalein against Menadione-Induced Damage in SK-N-MC Cells

Oxidative damage and redox metal homeostasis loss are two contributing factors in brain aging and widely distributed neurodegenerative diseases. Oxidative species in company with excessive amounts of intracellular free iron result in Fenton-type reaction with subsequent production of highly reactive hydroxyl radicals which initiate peroxidation of biomolecules and further formation of non-degradable toxic pigments called lipofuscin that amasses in long-lived postmitotic cells such as neurons. Dietary flavonoid baicalein can counteract the detrimental consequences through exertion of a multiplicity of protective actions within the brain including direct ROS scavenging activity and iron chelation. In this study, we evaluated the neuroprotective effects of baicalein in menadione (superoxide radical generator)-treated SK-N-MC neuroblastoma cell line. Our results showed that treatment of cells with menadione led to lipofuscin formation due to elevated intracellular iron contents and accumulation of oxidative products such as MDA and PCO. Also, menadione caused apoptotic cell death in SK-N-MC cells. However, pretreatment with baicalein (40 μM) reversed the harmful effects by chelating free iron and preventing biomolecules peroxidations. Moreover, baicalein prevented cell death through modulation of key molecules in apoptotic pathways including suppression of Bax and caspase-9 activities and induction of bcl2 expression. Key structural features such as presence of hydroxyl groups and iron-binding motifs in baicalein make it the appropriate candidate in antioxidant-based therapy in age-related neurodegenerative diseases.
Alternating optimization of decision trees, with application to learning sparse oblique trees

Learning a decision tree from data is a difficult optimization problem. The most widespread algorithm in practice, dating to the 1980s, is based on a greedy growth of the tree structure by recursively splitting nodes, and possibly pruning back the final tree. The parameters (decision function) of an internal node are approximately estimated by minimizing an impurity measure. We give an algorithm that, given an input tree (its structure and the parameter values at its nodes), produces a new tree with the same or smaller structure but new parameter values that provably lower or leave unchanged the misclassification error. This can be applied to both axis-aligned and oblique trees and our experiments show it consistently outperforms various other algorithms while being highly scalable to large datasets and trees. Further, the same algorithm can handle a sparsity penalty, so it can learn sparse oblique trees, having a structure that is a subset of the original tree and few nonzero parameters. This combines the best of axis-aligned and oblique trees: flexibility to model correlated data, low generalization error, fast inference and interpretable nodes that involve only a few features in their decision.
Statistical modelling of key variables in social survey data analysis

The application of statistical modelling techniques has become a cornerstone of analyses of large-scale social survey data. Bringing this special section on key variables to a close, this final article discusses several important issues relating to the inclusion of key variables in statistical modelling analyses. We outline two, often neglected, issues that are relevant to a great many applications of statistical models based upon social survey data. The first is known as the reference category problem and is related to the interpretation of categorical explanatory variables. The second is the interpretation and comparison of the effects from models for non-linear outcomes. We then briefly discuss other common complexities in using statistical models for social science research; these include the non-linear transformation of variables, and considerations of intersectionality and interaction effects. We conclude by emphasising the importance of two, often overlooked, elements of the social survey data analysis process, sensitivity analysis and documentation for replication. We argue that more attention should routinely be devoted to these issues.
Large Stores and Contracting for Mall Locations

We analyze the contracting problem between a shopping mall and potential anchors (large stores) in a market where consumers with high search costs must choose shopping destinations prior to learning prices. Our model incorporates the interaction between contracting and asymmetric firm sizes into a framework of competing platforms. The mall is but one of three potential destinations in the market, complemented by a stand-alone location for a large store, and a competitive ‘downtown’ centre occupied by small retailers. As in Dudey’s (1990) homogeneousgood framework, consumers choose to visit only one of these locations, based on expected prices at each site. A game of sequential contracting for slots at the mall determines the equilibrium distribution of firms across locations based on their costs and relative bargaining power. We analyze the effects of three policies. First, prohibition of the stand-alone site can increase social welfare, by alleviating excess entry and countering inefficiencies in contracting between the mall owner and potential anchors. Second, subsidies for downtown may push prices at the mall closer to socially efficient levels, but can never increase welfare if the market is initially dominated by a stand-alone big store. A subsidy’s effect on the equilibrium size distribution of mall tenants depends on the concavity of demand. Third, a merger between two big stores can increase social welfare, in part by ameliorating a problem of externalities on non-traders in the contracting with the mall owner. Merged anchor stores that operate at stand-alone sites may retain occupancy of mall space for purely strategic reasons, in order to deter entry.
Transactional distance in a blended learning environment

This paper presents a case study that describes and discusses the problems encountered during the design and implementation of a blended learning course, largely taught online through a web-based learning environment. Based on Moore’s theory of transactional distance, the course was explicitly designed to have dialogue at its heart. However, the reality of systemic behaviours caused by delivering such a course within a group of conventional further and higher educational institutions has led to an entirely unanticipated reversion to structure, with unpleasant consequences for both quality and quantity of dialogue. The paper looks at some of the reasons for this drift, and suggests that some of the disappointing results (in particular in terms of the quality of the students’ experience and associated poor retention) can be attributed to the lack of dialogue, and consequent increase in transactional distance. It concludes with a description and evaluation of steps currently being taken to correct this behaviour. DOI: 10.1080/0968776042000216219