Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross-linguistic annotation of narrativity for English/French verb tense disambiguation

This paper presents manual and automatic annotation experiments for a pragmatic verb tense feature (narrativity) in English/French parallel corpora. The feature is considered to play an important role for translating English Simple Past tense into French, where three different tenses are available. Whether the French Passe Ì Compose Ì, Passe Ì Simple or Imparfait should be used is highly dependent on a longer-range context, in which either narrative events ordered in time or mere non-narrative state of affairs in the past are described. This longer-range context is usually not available to current machine translation (MT) systems, that are trained on parallel corpora. Annotating narrativity prior to translation is therefore likely to help current MT systems. Our experiments show that narrativity can be reliably identified with kappa-values of up to 0.91 in manual annotation and with F1 scores of up to 0.72 in automatic annotation.
A keyphrase based approach to interactive meeting summarization

Rooted in multi-document summarization, maximum marginal relevance (MMR) is a widely used algorithm for meeting summarization (MS). A major problem in extractive MS using MMR is finding a proper query: the centroid based query which is commonly used in the absence of a manually specified query, can not significantly outperform a simple baseline system. We introduce a simple yet robust algorithm to automatically extract keyphrases (KP) from a meeting which can then be used as a query in the MMR algorithm. We show that the KP based system significantly outperforms both baseline and centroid based systems. As human refined KPs show even better summarization performance, we outline how to integrate the KP approach into a graphical user interface allowing interactive summarization to match the user's needs in terms of summary length and topic focus.
The Effects of Hypoproteinemia on Blood‐to‐ Lymph Fluid Transport in Sheep Lung

We studied the effects of reducing the plasma protein concentration on flow and composition of pulmonary lymph in 12 unanesthetized sheep. Whole blood was removed while red cells were returned and lactated Ringers was infused at a rate sufficient to maintain pulmonary vascular pressures at baseline values. A 44–54% reduction in plasma protein concentration resulted in a decrease in the plasma oncotic pressure from 18.6 ± 1.1 to 7.8 ± 0.9 mm Hg. Within an hour after plasmapheresis, lymph flows increased to a maximum of 4 times baseline. Subsequently, lymph flow gradually decreased and were close to baseline at 24 hours. The plasma-to-lymph oncotic gradient was reestablished in 5 hours due to decreased lymph protein. Maintained elevation of lymph flow with hydrostatic and oncotic gradients at baseline values suggest that the blood-to-lymph barrier offers leas resistance to fluid transport. The calculated filtration coefficient increased 2- to 3-fold after plasmapheresis. Protein clearances remained normally coupled to lymph flows. Thus the enhanced fluid transport cannot be attributed to a permeability change In the large pore pathways. Hypoproteinemia may alter the interstitial gel so that there is less resistance to fluid movement. Such changes in fluid conductivity between blood capillaries and lymphatics may augment the lymphatic safety factor against pulmonary edema during hypoproteinemia.
An exploratory clinical trial for combination wound therapy with a novel medical matrix and fibroblast growth factor in patients with chronic skin ulcers: a study protocol.

BACKGROUND Chronic skin ulcers such as diabetic ulcers and venous leg ulcers are increasing and are a costly problem in health care. We have developed a novel artificial dermis, collagen/gelatin sponge (CGS), that is capable of the sustained release of basic fibroblast growth factor (bFGF) for more than 10 days. The objective of this study was to investigate the safety and efficacy of CGS impregnated with bFGF in the treatment of chronic skin ulcers. Methods/ DESIGN Seventeen patients (≥ 20 years of age) with chronic skin ulcers that have not healed by conventional therapy for at least 4 weeks are being recruited. Patients will be applied with CGS impregnated with bFGF of 7 μg/cm(2) or 14 μg/cm(2) after debridement, and the wound bed improvement will be assessed 14 days after application. "Wound bed improvement" is defined as a granulated and epithelialized area on Day 14 in proportion to the baseline wound area after debridement of 50% or higher. Patients will be followed up until 28 days after application to observe the adverse events related to the application of CGS. CONCLUSION This study has been designed to address the safety and efficacy of CGS impregnated with bFGF. If successful, this intervention may be an alternative to bioengineered skin substitutes and lead to substantial and important changes in the management of chronic skin ulcers such as diabetic ulcers and venous ulcers.
Non-data-aided parameter estimation in an additive white gaussian noise channel

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise standard deviation, channel reliability constant and bit-error rate are derived and it is shown how these parameters relate to the signal-to-noise ratio (SNR). An alternative derivation of the iterative maximum likelihood (ML) SNR estimator is presented together with a novel, low complexity NDA SNR estimator. The performance of the proposed estimator is compared to previously suggested estimators and the CRLB. The results show that the proposed estimator performs close to the iterative ML estimator at significantly lower computational complexity
Snooker Structure-Based Pharmacophore Model Explains Differences in Agonist and Blocker Binding to Bitter Receptor hTAS2R39

The human bitter taste receptor hTAS2R39 can be activated by many dietary (iso)flavonoids. Furthermore, hTAS2R39 activity can be blocked by 6-methoxyflavanones, 4’-fluoro-6-methoxyflavanone in particular. A structure-based pharmacophore model of the hTAS2R39 binding pocket was built using Snooker software, which has been used successfully before for drug design of GPCRs of the rhodopsin subfamily. For the validation of the model, two sets of compounds, both of which contained actives and inactives, were used: (i) an (iso)flavonoid-dedicated set, and (ii) a more generic, structurally diverse set. Agonists were characterized by their linear binding geometry and the fact that they bound deeply in the hTAS2R39 pocket, mapping the hydrogen donor feature based on T5.45 and N3.36, analogues of which have been proposed to play a key role in activation of GPCRs. Blockers lack hydrogen-bond donors enabling contact to the receptor. Furthermore, they had a crooked geometry, which could sterically hinder movement of the TM domains upon receptor activation. Our results reveal characteristics of hTAS2R39 agonist and bitter blocker binding, which might facilitate the development of blockers suitable to counter the bitterness of dietary hTAS2R39 agonists in food applications.
Evaluation of shipboard wave estimation techniques through model-scale experiments

The paper continues a study on the wave buoy analogy that uses shipboard measurements to estimate sea states. In the present study, the wave buoy analogy is formulated directly in the time domain and relies only partly on wave-vessel response amplitude operators (RAOs), which is in contrast to all previous works that either are formulated in the frequency domain and/or depend entirely on RAOs. Specifically, the paper evaluates a novel concept for wave estimation based on combined techniques using a wave frequency estimator, not dependent on RAOs, to detect wave frequency and, respectively, nonlinear least squares fitting to estimate wave amplitude and phase. The concept has been previously tested with only numerical simulations but in this study the techniques are applied to model-scale experiments. It is shown that the techniques successfully can be used to estimate the wave parameters of a regular wave train.
Morphogenetically Assisted Design Variation

Current engineered systems are often brittle and hard to modify in contrast to living organisms, which adapt to structural changes in a graceful and integrated manner. We refine the concept of functional blueprints, an attempt to capture this adaptability, and present an architecture for adjusting a design through the execution of a network of functional blueprints. We then use our architecture to investigate the efficacy of the functional blueprint approach, presenting a preliminary empirical study of the convergence dynamics of random networks of functional blueprints. Convergence is both rapid and reliable for a wide range of parameters, demonstrating that even simple blueprints can provide effective design adaptation over a wide range of circumstances and pointing the way toward both a deeper theoretical understanding and practical applications. Keywords—morphological computation, spatial computing
Community Answer Summarization for Multi-Sentence Question with Group L1 Regularization

We present a novel answer summarization method for community Question Answering services (cQAs) to address the problem of "incomplete answer", i.e., the "best answer" of a complex multi-sentence question misses valuable information that is contained in other answers. In order to automatically generate a novel and non-redundant community answer summary, we segment the complex original multi-sentence question into several sub questions and then propose a general Conditional Random Field (CRF) based answer summary method with group L1 regularization. Various textual and non-textual QA features are explored. Specifically, we explore four different types of contextual factors, namely, the information novelty and non-redundancy modeling for local and non-local sentence interactions under question segmentation. To further unleash the potential of the abundant cQA features, we introduce the group L1 regularization for feature learning. Experimental results on a Yahoo! Answers dataset show that our proposed method significantly outperforms state-of-the-art methods on cQA summarization task.
Shape Recovery from Stationary Surface Contours by Controlled Observer Motion

The projected deformation of stationary contours and markings on object surfaces is analyzed in this paper. It is shown that given a marked point on a stationary contour, an active observer can move deterministically to the osculating plane for that point by observing and controlling the deformation of the projected contour. Reaching the osculating plane enables the observer to recover the object surface shape along the contour as well as the Frenet frame of the contour. Complete local surface recovery requires either two intersecting surface contours and the knowledge of one principle direction, or more than two intersecting contours. To reach the osculating plane, two strategies involving both pure translation and a combination of translation and rotation are analyzed. Once the Frenet frame for the marked point on the contour is recovered, the same information for all points on the contour can be recovered by staying on osculating planes while moving along the contour. It is also shown that occluding contours and stationary contours deform in a qualitatively different way and the problem of discriminating between these two types of contours can be resolved before the recovery of local surface shape.
Unraveling Dynamic Activities of Autocrine Pathways that Control Drug-Response Transcriptome Networks

Some drugs affect secretion of secreted proteins (e.g. cytokines) released from target cells, but it remains unclear whether these proteins act in an autocrine manner and directly effect the cells on which the drugs act. In this study, we propose a computational method for testing a biological hypothesis: there exist autocrine signaling pathways that are dynamically regulated by drug response transcriptome networks and control them simultaneously. If such pathways are identified, they could be useful for revealing drug mode-of-action and identifying novel drug targets. By the node-set separation method proposed, dynamic structural changes can be embedded in transcriptome networks that enable us to find master-regulator genes or critical paths at each observed time. We then combine the protein-protein interaction network with the estimated dynamic transcriptome network to discover drug-affected autocrine pathways if they exist. The statistical significance (p-values) of the pathways are evaluated by the meta-analysis technique. The dynamics of the interactions between the transcriptome networks and the signaling pathways will be shown in this framework. We illustrate our strategy by an application using anti-hyperlipidemia drug, Fenofibrate. From over one million protein-protein interaction pathways, we extracted significant 23 autocrine-like pathways with the Bonferroni correction, including VEGF-NRP1-GIPC1-PRKCA-PPARalpha, that is one of the most significant ones and contains PPARalpha, a target of Fenofibrate.
Efficient intent-based narrative generation using multiple planning agents

In Interactive Storytelling (IS) the prevailing approach for the automatic generation of plausible narratives that meet global author goals is intentional planning. However, existing approaches suffer from limited expressiveness and poor scalability. We address this by replacing single intentional planners with multiple agents representing the characters of a narrative, which can reason about the relevance of narrative actions given their individual intents. These are then combined using a state-based forward search procedure that results in a significantly smaller search space. Unlike other multiagent approaches, these agents calculate all reasonable plans in a state. This allows a search of a wide range of narrative possibilities prior to execution as in planner-based approaches, rather than agents making early plan commitments in a simulation. We demonstrate that this not only produces the same forms of narrative as single intentional planners but can be extended to generate narratives that are beyond their scope. We also present a search heuristic that exploits the agents' relevant actions to further reduce the size of the explored search space. Experimental results demonstrate system performance that makes it suitable for use in real-time applications such as IS.
The jamming avoidance response in Eigenmannia is controlled by two separate motor pathways

The gymnotiform fish Eigenmannia generates weakly electric signals for electrolocation and communication. The signals are produced by electric organ discharges (EODs) that are driven by a medullary pacemaker nucleus. To avoid jamming by neighboring conspecifics with similar frequencies, a fish raises its own EOD frequency if the neighbor's frequency is lower, and it lowers its EOD frequency if the neighbor's frequency is higher (Watanabe and Takeda, 1963). Both the raising and lowering of EOD frequency of this jamming avoidance response (JAR; Bullock et al., 1972) are thought to be controlled by feature- extracting neurons in the diencephalic prepacemaker nucleus (PPn-G) that discriminate the sign of the frequency difference between the jamming signal and the fish's EOD (Kawasaki et al., 1988a; Rose et al., 1988; for review, see Heiligenberg, 1991). These prepacemaker neurons are excited in response to lower jamming frequencies, thereby raising the frequency, and inhibited by higher jamming frequencies, producing a discharge deceleration. The results of experiments presented here, however, suggest a mechanism for the motor control of the JAR that is different from the one described previously (see, e.g., Heiligenberg, 1991). Two prepacemaker nuclei, one PPn-G and one sublemniscal prepacemaker nucleus (SPPn) (Keller et al., 1991 a,b), which provide the only known inputs to the pacemaker, were lesioned selectively. This article explores the effects of these lesions on the JAR. Pharmacological experiments were used to elucidate the transmitter types involved. The results suggest that the JAR is controlled by two separate motor pathways. One controls frequency rises and originates in the dorsal substructure of the nucleus electrosensorius (Keller, 1988). It sends excitatory connections to the diencephalic prepacemaker and finally to the pacemaker nucleus, where AMPA-type receptors mediate the synaptic transmission. The second pathway controls frequency decreases and originates in the ventral substructure of the nucleus electrosensorius. It provides GABAergic input to the SPPn. The SPPn is tonically active and also controls the EOD frequency even in the absence of jamming signals. Its projection to the pacemaker nucleus is mediated by NMDA-type receptors. The results of this study suggest that there is no single population of final, feature-extracting elements or “recognition units” that controls JAR-related shifts of the pacemaker frequency. Instead, the motor control of the JAR consists of an interaction of two independent pathways according to a “push-pull” principle.
An Entity-centric Approach for Overcoming Knowledge Graph Sparsity

Automatic construction of knowledge graphs (KGs) from unstructured text has received considerable attention in recent research, resulting in the construction of several KGs with millions of entities (nodes) and facts (edges) among them. Unfortunately, such KGs tend to be severely sparse in terms of number of facts known for a given entity, i.e., have low knowledge density. For example, the NELL KG consists of only 1.34 facts per entity. Unfortunately, such low knowledge density makes it challenging to use such KGs in real-world applications. In contrast to best-eort extraction paradigms followed in the construction of such KGs, in this paper we argue in favor of ENTIty Centric Expansion (ENTICE), an entity-centric KG population framework, to alleviate the low knowledge density problem in existing KGs. By using ENTICE, we are able to increase NELL’s knowledge density by a factor of 7.7 at 75.5% accuracy. Additionally, we are also able to extend the ontology discovering new relations and entities.
The Self in social perspective

Contents: Preface. R.B. Felson, The (Somewhat) Social Self: How Others Affect Self-Appraisals. J.D. Brown, Self-Esteem and Self-Evaluation: Feeling Is Believing. H.W. Marsh, Academic Self-Concept: Theory, Meaurement, and Research. D. Dunning, Words to Live By: The Self and Definitions of Social Concepts and Categories. M.R. Leary, The Interplay of Private Self-Processes and Interpersonal Factors in Self-Presentation. B.R. Little, Personal Projects and the Distributed Self: Aspects of a Conative Psychology. D. Oyserman, H.R. Markus, The Sociocultural Self.
Comparison of Several Models for Calculating Ozone Stomatal Fluxes on a Mediterranean Wheat Cultivar (Triticum durum Desf. cv. Camacho)

Ozone stomatal fluxes were modeled for a 3-year period following different approaches for a commercial variety of durum wheat (Triticum durum Desf. cv. Camacho) at the phenological stage of anthesis. All models performed in the same range, although not all of them afforded equally significant results. Nevertheless, all of them suggest that stomatal conductance would account for the main percentage of ozone deposition fluxes. A new modeling approach was tested, based on a 3-D architectural model of the wheat canopy, and fairly accurate results were obtained. Plant species-specific measurements, as well as measurements of stomatal conductance and environmental parameters, were required. The method proposed for calculating ozone stomatal fluxes (FO3_3-D) from experimental gs data and modeling them as a function of certain environmental parameters in conjunction with the use of the YPLANT model seems to be adequate, providing realistic estimates of the canopy FO3_3-D, integrating and not neglecting the contribution of the lower leaves with respect to the flag leaf, although a further development of this model is needed.
Reactive robot system using a haptic interface: an active interaction to transfer skills from the robot to unskilled persons

This paper is concerned with the reactive robot system (RRS) which has been introduced as a novel way of approaching human–robot interactions by exploiting the capabilities of haptic interfaces to transfer skills (from the robot to unskilled persons). The RRS was implemented based on two levels of interaction. The first level, which implements the first two stages of the learning process, represents the conventional control way of interchanging a set of forces in response to a static read of the contact position of some pre-defined dynamic rules (passive interaction). The second level, which implements the last stage of the learning process, represents an enhanced way of interaction between haptic interfaces and humans. This level adds to robotic system a degree of intelligence which enables the robot to dynamically adapt its behavior depending on user wishes (active interaction). In particular, in this paper, the implementation of the second level of the RRS is described in detail. A set of experiments was performed, applied to Japanese handwriting, to verify if second level of the RRS can interact with humans during the autonomous stage of the learning process. The results demonstrated that our system can still provide assistance to users on the autonomous stage while mostly respecting their intentions without significantly affecting their performance.
CRISP-DS: Dual-stream coarse-grained reconfigurable image stream processor for HD digital camcorders and digital still cameras

A 329mW 600M-Pixels/s dual-stream coarsegrained reconfigurable image stream processor is implemented in TSMC 0. 13μm CMOS technology with a core size of 4.84mm2. The reconfigurable pipelined processing element array architecture makes a good balance between computing performance and flexibility with only 10Kb on-chip memory. Moreover, a new dual-stream architecture is proposed to improve the flexibility and hardware efficiency by processing two independent image streams with two-layer context switching, and an isolation technique is also proposed to improve the power consumption. Implementation results show that it achieves 1.52 times power efficiency than previous works and can meet the requirements of high-definition video camcorders and digital still cameras.