Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Natural Language Semantic Sensing in Dynamic State Spaces

One of the great challenges of robotics is effective humanrobot communication. It is quite challenging for autonomous robots to understand human natural language statements, as these must be mapped from a large highly open space of semantic constructs to precise grounded representations that robots can interpret. Probabilistic models and inference algorithms for natural language processing (NLP) have proved to be especially useful and attractive, due to their high degree of modularity, flexibility, computational efficiency, and ability to naturally tie into probabilistic reasoning algorithms for robotic decision-making [1–8]. While state-of-the-art developments in probabilistic methods have largely focused on natural language command and control, there is also great interest in the ability of humans to quickly and efficiently communicate useful sensory information, i.e. to act as ‘human sensors’ that support probabilistic robotic perception, learning and state estimation tasks [9–15].
Macro to Analyze Data From a Matched or Finely Stratified Case-Control Design

A matched case-control design is a common approach used to assess diseaseexposure relationships, and is often a more efficient method than an unmatched design. However, for the valid analysis of such an approach, a modeling technique that incorporates the matched nature of the data is needed. This prohibits the use of a standard unconditional logistic regression analysis generally available in PROC LOGISTIC. A stratified conditional logistic model has the same flexibility as an unconditional model, yet can still take into account the correlation structure attributable to matching. This paper presents a SAS macro that fits a conditional logistic regression model to matched or finely stratified data using the PHREG procedure. The macro enhances standard PHREG output by producing summary tables and statistics used to describe the matched sets. It also calculates several regression diagnostics, some not available in PHREG, that can be used to assess model fit. This paper is intended for an audience with a working knowledge of statistical modeling.
New Approaches to Efficient Rendering of Complex Reconstructed Environments

The creation of complete reconstructions of populated urban environments are technically difficult tasks primarily due to economic constraints in the modeling phase: complex models need to keep rendering aspects in mind in order to warrant interactive rendering speeds which makes this kind of work a labor-intensive task for highly skilled personel. Specialized modelling tools, which exploit knowledge of the types of object being modelled by working in the application domain, can be used to create appealing virtual reconstructions quickly. At the same time, the structural information from the modeller gives essential hints to the interactive renderer to determine efficient interactive display strategies through the use of level-of-detail and culling techniques. Even more important, only a shift in the modeling paradigm from 'just in case' to 'just in time' can solve the problem applications are faced in real-time rendering. In this paper we discuss the way in which polygonal and multi-resolution surface techniques can complement one another in the effective rendering of complex reconstructed environments. We also draw more general conclusions which apply to other software systems that share the same objectives.
Factors Influencing the Response to High Dose Methotrexate-based Vincristine and Procarbazine Combination Chemotherapy for Primary Central Nervous System Lymphoma

The authors investigated objective response rate to high dose methotrexate (HDMTX)-based combination chemotherapy in primary central nervous system lymphoma (PCNSL), and sought to identify factors that influence response to HDMTX-based combination therapy. Prospective observational analysis was performed on 52 PCNSL patients. All patients received HDMTX (3.5 g/m2) and vincristine (1.4 mg/m2/day) for one day during weeks 1, 3, 5, 7, and 9, and procarbazine (100 mg/m2/day) for one week during weeks 1, 5, and 9. Forty-one patients (78.8%) achieved complete or partial remission. Higher objective response rates were observed for patients with: 1) age < 60 yr; 2) Eastern Cooperative Oncology Group (ECOG) performance score of < 2; 3) low risk status as defined by the International Extranodal Lymphoma Study Group; 4) p53 positivity; 5) XBP-1 negativity; 6) MUM-1 negativity; and 7) homogenous gadolinium enhancement in MR images. Multivariate analysis showed that ECOG performance score of < 2, low risk, negativity for XBP-1, homogenous gadolinium enhancement by MRI, and response to chemotherapy were associated with longer overall survival. In particular, it is interesting to note that patients with a PCNSL that is homogenously enhanced by gadolinium have a higher objective response rate, and a longer progression-free survival and overall survival.
Mobilisations As a Result of Deliberation and Polarising Crisis

To account for the peaceful mobilisations which started in Syria in March 2011, the authors first demonstrate the irrelevance of rational choice and resource mobilisation theories. They build a model of “deliberative mobilisation”, at the core of which is participation in small groups in which individuals transform their values, their calculations and their sociability. Furthermore, to account for the resilience of the regime and the start of the civil war, the authors propose the concept of a “polarising crisis”, characterised by the limited autonomy of social fields, the widening of individual tactical activities, and the strategic use of violence by the state.
A New Method for Partical Discharge Pattern Recognition of Electrical Transformers

Ultrasonic techniques are wildly used in online partial discharge (PD) location and recognition for electrical transformers. This paper focuses on a new ultrasonic feature extraction method. The normalized discharge grey moment features are extracted from ultrasonic signals to perform PD recognition. These features are sent to an improved BP neural network as to perform pattern recognition. Two types of PD patterns, pin-plate discharge and sphere-plate discharge, are tested, the PD pattern recognition method are compared with traditional methods and the recognition rates show that central grey moment has satisfactory ability in characterizing PD types, and the improved back propagation (BP) neural network perfectly met the recognition demands. Central grey moment provides us a novel approach to study partial discharge.
Two-level Data Prefetching

Data prefetching has been shown to be an effective tool in hiding part of the latency associated with cache misses in modern processors. Traditionally, data prefetchers fetch data into a small prefetch buffer near the L1 for low latency, or the L2 cache for greater coverage and less cache pollution. However, with the L1–L2 cache speed gap growing, significant performance gains can be obtained if the data prefetcher can operate as aggressively as an L2-level prefetcher but with the fast hit times of an L1-level prefetcher. In this paper, we propose a prefetching framework where an L1-level prefetcher and an L2level prefetcher work cooperatively to reduce the average access time more than either one alone can. We evaluate several design alternatives suited to perform synergistically under different workloads. From the insight we gather from this analysis, we propose a confidence-based adaptive prefetcher that can improve prefetch efficiency significantly with judicious use of available bus bandwidth. Our results show that for certain prefetcher combinations, twolevel prefetching can achieve the cumulative speedup attained from either prefetcher alone. Furthermore, when compared to other two-level prefetching models, the adaptive design provides similar speedups with appreciably less bus traffic.
Experimental Analysis of Attitudes: The Factorial-Survey Approach

A reading of the studies having been published by important sociological and criminological journals reveals a clear picture: for a variable to be considered dependent in a randomized experimental study (at least for those accepted and published by these journals), it has to be behavioral. The question asked in this article is, may only behavioral measures constitute dependent variables in highly qualified experimental studies? The answer is a distinct “no”, and attitudinal measures are also proposed as possible and legitimate dependent variables in randomized experimental studies. Here the factorial-survey approach, a relatively new survey technique, which combines the benefits of controlled, randomized experimental designs and conventional surveys, is suggested as a characteristic experimental technique in such studies. This article concludes that the factorial-survey approach may be considered an appropriate experimental technique in social science research—it produces findings that less developed methods are not able to examine.
Spatial extensions to bag of visual words

The Bag of Visual Words (BoV) paradigm has successfully been applied to image content analysis tasks such as image classification and object detection. The basic BoV approach overlooks spatial descriptor distribution within images. Here we describe spatial extensions to BoV and experimentally compare them in the VOC2007 benchmark image category detection task. In particular, we compare two ways for tiling images geometrically: soft tiling approach---proposed here---and the traditional hard tiling technique. The experiments also address two methods of fusing information from several tilings of the images: post-classifier fusion and fusion on the level of a SVM kernel. The experiments confirm that the performance of a BoV system can be greatly enhanced by taking the descriptors' spatial distribution into account. The soft tiling technique performs well even with a single tiling mask, whereas multi-mask fusion is necessary for good category detection performance in case of hard tiling. The evaluated fusion mechanisms performed approximately equally well.
Differences in herbivore feeding preferences across a vertical rocky intertidal gradient

Primary producers such as plants and macroalgae can vary in palatability to their her- bivorous grazers; this leads to variation in the intensity of herbivory, which can play an important role in setting the composition and diversity of producer assemblages. However, despite strong gradients in the composition and abundance of herbivores across intertidal gradients, little is known about how macroalgal palatability and associated herbivore defenses vary across strong vertical gradients in marine rocky intertidal zones. Plant defense theory predicts that decreasing intensity of herbivory with increasing tidal elevation should result in higher intertidal species being more palatable and less defended than their lower intertidal counterparts. In this study, we examined the relative palata- bility of 9 pairs of closely related macroalgal species that occupy different elevations across this ver- tical gradient, to 3 of the most common local herbivores. We conducted controlled paired-choice feed- ing assays for every herbivore-algal species combination. Although we found no evidence for a vertical gradient in palatability consistent across all 3 herbivores, there were many significant, spe- cies-specific herbivore preferences driven by morphological and/or chemical properties of the macroalgae. In general, herbivores consumed more of the algae that they did not co-occur with: the lower intertidal herbivores Strongylocentrotus purpuratus and Tegula brunnea preferred higher intertidal algae overall, and the higher intertidal herbivore Tegula funebralis preferred lower inter- tidal algae. Our results suggest that the intensity of herbivory may change with tidal elevation in more complex ways than previously suspected, and that studies of macroalgal palatability and anti- herbivore defenses in these systems will need to examine the relative impacts of a range of herbi- vores on algal community structure.
Thermal and State-Selected Rate Coefficients for the O(3P) + HCl Reaction and New Calculations of the Barrier Height and Width†

This paper compares several approximate methods for calculating rate coefficients for the O(3P) + HCl reaction to presumably more accurate quantum mechanical calculations that are based on applying the J-shifting approximation (QM/JS) to an accurate cumulative reaction probability for J = 0. All calculations for this work employ the recent S4 potential energy surface, which presents a number of challenges for the approximate methods. The O + HCl reaction also poses a significant challenge to computational dynamics because of the heavy−light−heavy mass combination and the broad noncollinear reaction path. The approximate methods for calculating the thermal rate coefficient that are examined in this article are quasiclassical trajectories (QCT), conventional transition state theory (TST), variational transition state theory employing the improved canonical variational theory (ICVT), ICVT with the microcanonical optimized multidimensional tunneling correction (ICVT/μOMT), and reduced dimensionality quantum m.
Dynamic IBVS control of an underactuated UAV

In this paper image based visual servo approach for 3D translational motion and yaw rotation of an under-actuated flying robot is considered. Taking into account the complexity of dynamics of flying robots, main objective of this paper is to consider the dynamics of these robots in designing an image based control strategy. Inertial information of the robot orientation is combined with image information in order to have overall system dynamics in a fashion to apply full dynamic image based controller. Suitable perspective image moments are used in order to have satisfactory trajectories in image space and Cartesian coordinates. A nonlinear controller for the full dynamics of the system is designed. Simulation results are presented to validate the designed controller.
Effects of focus distribution and accentuation on the temporal and melodic organisation of word groups in Dutch

A speaker speaks in order to be heard in order to be understood. The words in an utterance differ in their communicative importance. Some words merely recapitulate predictable referents that were introduced earlier on in the discourse (‘old’ or [–focus] elements); others introduce highly informative, contextually and/or situationally rather unpredictable, referents (‘new’ or [+focus] elements). A speaker, governed by the principle of least effort, will speak as quickly and as sloppily as the hearer will let him get away with. In order to reduce articulatory effort and at the same time maintain the required minimum of perceptual distinctivity, the speaker strikes a compromise: he will pronounce ‘new’ [+focus] elements relatively carefully, slowly and deliberately (hyper-articulated); ‘old’ [–focus] materials, however, will typically be slurred (hypo-articulated). There is a sizable literature to support this specific prediction of Lindblom’s (1990) ‘hyper and hypo’ theory (or H&H theory). Lieberman (1963) showed, for instance, that the word nine in the well-known English expression A stitch in time saves nine is pronounced more sloppily and with less intensity than the same word in the less pregnant context The next number is nine. Moreover, a perceptual experiment indicated that the hyper-articulated word, when excised from its original spoken context, was more intelligible than the hypo-articulated counterpart. These effects were replicated on a larger scale by Hunnicut (1985). Similarly, Fowler & Housum (1987) showed that repeated referents introduced in the preceding sentence (and which were therefore [–focus]), were spoken more quickly than the same words when these were newly introduced into the discourse (and therefore [+focus]). The prosodic head of a [+focus] word or word group (henceforth ‘constituent’) in languages such as Dutch and English is marked by a pitch accent, i.e., has a conspicious change in pitch associated with the stressed syllable. A secondary effect of accentuation is that the word with the pitch change associated to it, is expanded in time by some 10%; moreover, the time-expansion is not limited to just the stressed syllable, but affects unstressed syllables as well (Nooteboom, 1972; Eefting, 1991; Sluijter & van Heuven, 1995, 1996). It is unclear, therefore, whether the temporal expansion of ‘old’ referents in Fowler & Housum’s study is the result of their being [+focus] or of their being pitch accented. The first to tackle this question was Eefting (1991), whose experimental materials were constructed so as to disentangle the effects on temporal expansion due to focus structure on the one hand and of accentedness on the other. Her results show that only the word that carries the pitch accent is temporally expanded; if a [+focus] word remains unaccented (which may
An association based approach to propagate social trust in social networks

The behaviour based trust models generally compute social trust using interactions of a member with other members, referred to as “friends”. These models largely ignore the interactions of friends with their friends, referred to as “friendship effects”. Results from social studies and behavioural science show that friends have a significant influence on the behaviour of the members in the community. Following the famous Spanish proverb on friendship “Tell Me Your Friends and I Will Tell You Who You Are”, we extend our behaviour based trust model by incorporating the “friendship effect”. In this paper, we present a trust propagation model based on associations which combines the behaviour of both individual members and their friends. The propagation of trust in our model depends on three key factors: the density of interactions, the degree of separation and the decay of friendship effect. We evaluate our model using a real dataset and make observations on what happens in a social network with models with and without trust propagation. We report the results in this paper.
Poster: Delay Tolerant Networking for Sensor Networks

Sensor network deployments may be far removed from communications infrastructure such as the Internet. Yet, to be maximally useful, these networks of sensors must ultimately be connected to data storage and analysis facilities. Providing connectivity for such networks may involve exotic and unusual methods of data transfer. In addition, within such networks, problems of intermittent connectivity due to power scheduling, node failure, and packet losses from unpredictable external factors are frequently encountered. As a solution the first problem, we propose the use of the Delay Tolerant Networking (DTN) architecture, which provides reliable data communication across heterogeneous, failure-prone networks. For the second problem, we show elements of the DTN architecture can be employed within a sensor network to mitigate communication interruptions. We suggest an overall architecture, employing the full DTN architecture for access to sensor networks, combined with a subset implementation of its design for use within sensor networks, as a reasonable basis for a complete delay-tolerant sensor network architecture.
The complex X-ray spectrum of the supersoft source MR Vel

We present the X-ray spectrum of MR Vel / RX J0925.7 4758, obtained with the Medium Energy Grating spectrometer of the Chandra X-ray Telescope. The simplest models used by earlier authors, stellar atmo- spheres in combination with a thermal plasma in collisional ionization equilibrium, cannot explain the spectrum. Neither does a photo-ionized plasma. We identify P Cygni proles of Fe XVII and O VIII, from which we conclude that these lines arise in a wind. We conclude that major uncertainty exists about the bolometric luminosity of MR Vel, and perhaps of supersoft sources in general, so that the theoretical prediction that this luminosity derives from steady nuclear burning cannot be veried.
A machine-learning approach to negation and speculation detection in clinical texts

Detecting negative and speculative information is essential in most biomedical text-mining tasks where these language forms are used to express impressions, hypotheses, or explanations of experimental results. Our research is focused on developing a system based on machine-learning techniques that identifies negation and speculation signals and their scope in clinical texts. The proposed system works in two consecutive phases: first, a classifier decides whether each token in a sentence is a negation/speculation signal or not. Then another classifier determines, at sentence level, the tokens which are affected by the signals previously identified. The system was trained and evaluated on the clinical texts of the BioScope corpus, a freely available resource consisting of medical and biological texts: full-length articles, scientific abstracts, and clinical reports. The results obtained by our system were compared with those of two different systems, one based on regular expressions and the other based on machine learning. Our system's results outperformed the results obtained by these two systems. In the signal detection task, the F-score value was 97.3% in negation and 94.9% in speculation. In the scope-finding task, a token was correctly classified if it had been properly identified as being inside or outside the scope of all the negation signals present in the sentence. Our proposal showed an F score of 93.2% in negation and 80.9% in speculation. Additionally, the percentage of correct scopes (those with all their tokens correctly classified) was evaluated obtaining F scores of 90.9% in negation and 71.9% in speculation. © 2012 Wiley Periodicals, Inc.
Consciousness and Control Not Identical Twins

Human cognition and action are intentional and goal-directed, and explaining how they are controlled is one of the most important tasks of the cognitive sciences. After half a century of benign neglect this task is enjoying increased attention. Unfortu- nately, however, current theorizing about control in general, and the role of consciousness for/in control in particular, suffers from major conceptual flaws that lead to confusion regarding the following dis- tinctions: (i) automatic and unintentional processes, (ii) exogenous control and disturbance (in a control-theoretical sense) of endoge- nous control, (iii) conscious control and conscious access to control, and (iv) personal and systems levels of analysis and explanation. Only if these flaws are overcome will a comprehensive understanding of the relationship between consciousness and control emerge. The topic of control is hot in the cognitive sciences, as witnessed by a dramatic increase of hits for the keywords 'executive functions', 'ex- ecutive control', and 'cognitive control' in the Web of Science data- base from zero in 1945-1954 to 3672 for 1995-2004. The feeling is that researchers were occupied for a long time with analysing the cog- nitive machinery but now the time is ripe to find out the way this machinery is used by intelligent agents to realize their intentions (Monsell, 1996). In other words, human will is back on stage. Given that control processes are often considered to be inevitably conscious (e.g., Atkinson & Shiffrin, 1968; Norman & Shallice, 1986; Umilta,