Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysing the influence of semantic knowledge in natural language generation

This paper conducts an evaluation of several traditional Language Models for the task of Natural Language Generation, focusing on the surface realisation stage. Specifically, we analyse and compare the n-gram language models and the factored language models through the evaluation of automatically generated sentences. In this manner, factored language models have shown to be better, improving the coherence of the generated sentences compared with the ones generated with n-grams. Furthermore, factored language models were tested with different lexical and semantic knowledge, leading to more suitable generated sentences in the latter case as well as providing a greater expressive richness.
New Quantum Caps in PG(4, 4)

Calderbank, Rains, Shor, and Sloane (see [10]) showed that quantum stabilizer codes correspond to additive quaternary codes in binary projective spaces, which are self‐orthogonal with respect to the symplectic form. A geometric description is given in [8, 19]. In [8] the notion of a quantum cap is introduced. Quantum caps are equivalent to quantum stabilizer codes of minimum distance d=4 when the code is linear over GF(4) . In this paper, we determine the values k such that there exists a quantum k‐cap in PG(4,4) , corresponding to pure linear [[n,n−10,4]] quantum codes, proving, by exhaustive search, that no 11, 37, 39‐quantum caps exist. Moreover we give examples of quantum caps in PG(4,4) not already known in the literature.
Building The Sense-Tagged Multilingual Parallel Corpus

Sense-annotated parallel corpora play a crucial role in natural language processing. This paper introduces our progress in creating such a corpus for Asian languages using English as a pivot, which is the first such corpus for these languages. Two sets of tools have been developed for sequential and targeted tagging, which are also easy to set up for any new language in addition to those we are annotating. This paper also briefly presents the general guidelines for doing this project. The current results of monolingual sense-tagging and multilingual linking are illustrated, which indicate the differences among genres and language pairs. All the tools, guidelines and the manually annotated corpus will be freely available at compling.ntu. edu.sg/ntumc.
Milk and dairy consumption and incidence of cardiovascular diseases and all-cause mortality: dose-response meta-analysis of prospective cohort studies.

BACKGROUND The consumption of dairy products may influence the risk of cardiovascular disease (CVD) and total mortality, but conflicting findings have been reported. OBJECTIVE The objective was to examine the associations of milk, total dairy products, and high- and low-fat dairy intakes with the risk of CVD [including coronary heart disease (CHD) and stroke] and total mortality. DESIGN PubMed, EMBASE, and SCOPUS were searched for articles published up to February 2010. Of > 5000 titles evaluated, 17 met the inclusion criteria, all of which were original prospective cohort studies. Random-effects meta-analyses were performed with summarized dose-response data. Milk as the main dairy product was pooled in these analyses. RESULTS In 17 prospective studies, there were 2283 CVD, 4391 CHD, 15,554 stroke, and 23,949 mortality cases. A modest inverse association was found between milk intake and risk of overall CVD [4 studies; relative risk (RR): 0.94 per 200 mL/d; 95% CI: 0.89, 0.99]. Milk intake was not associated with risk of CHD (6 studies; RR: 1.00; 95% CI: 0.96, 1.04), stroke (6 studies; RR: 0.87; 95% CI: 0.72, 1.05), or total mortality (8 studies; RR per 200 mL/d: 0.99; 95% CI: 0.95, 1.03). Limited studies of the association of total dairy products and of total high-fat and total low-fat dairy products (per 200 g/d) with CHD showed no significant associations. CONCLUSION This dose-response meta-analysis of prospective studies indicates that milk intake is not associated with total mortality but may be inversely associated with overall CVD risk; however, these findings are based on limited numbers.
Nucleotide sequence analysis of the gtfT gene from Streptococcus sobrinus OMZ176

The gtfT gene and its upstream region isolated from the Streptococcus sobrinus OMZ176 chromosomal DNA were sequenced. The gtfT gene was preceded by a potential Shine-Dalgarno sequence. The gtfT gene product, glucosyltransferase (GTF), displays a typical gram-positive bacterial signal peptide sequence and both an active site peptide sequence and carboxy-terminal repeats typical of GTFs. The signal sequence is similar to those of other known GTF proteins. The putative active-site peptide sequence of this enzyme was DGIRVDAVD, which was different by one amino acid from the active-site peptide sequence derived from two different types of the S. sobrinus GTFs reported previously (G. Mooser, S. A. Hefta, R. J. Paxton, J. E. Shively, and T. D. Lee, J. Biol. Chem. 266:8916-8922, 1991). The gtfT gene product has three repeated sequences of 51 to 52 amino acids and a partial repeat of 18 amino acids. Another open reading frame (ORF) was detected in the region immediately upstream of the gtfT gene. The upstream ORF showed substantial DNA homology with the gtfS gene isolated from Streptococcus downei MFe28. The inferred amino acid sequence of the upstream ORF has four repeating units and has extensive homology with the repeated peptides coded by the S. downei gtfS gene. These results suggested that the gtfT gene was a typical gtf gene isolated from the mutans streptococci and that the two gtf genes were located in tandem on the chromosomal DNA of S. sobrinus OMZ176.
Approximating Full Steiner Tree in a Unit Disk Graph

Given an edge-weighted graph G = (V;E) and a subset R of V , a Steiner tree of G is a tree which spans all the vertices in R. A full Steiner tree is a Steiner tree which has all the vertices of R as its leaves. The full Steiner tree problem is to nd a full Steiner tree of G with minimum weight. In this paper we present a 20-approximation algorithm for the full Steiner tree problem when G is a unit disk graph.
Direct source-to-drain tunneling and its impact on intrinsic parameter fluctuations in nanometre scale double gate MOSFETs

The conventional MOSFETs are likely to reach scaling limitations at gate lengths between 15 and 10nm. The double-gate MOSFET architecture is a promising candidate for scaling to 10nm and below in line with the requirements of the International Technology Roadmap. However, it is expected that direct source-drain tunnelling would be a major limiting factor in the double-gate device. In this paper we study, using carefully calibrated density gradient simulations, the impact of quantum confinement and tunnelling on the operation of nanometer scale double gate MOSFETs. We show that source-drain tunnelling is unlikely to be a major effect limiting the scaling of the double gate MOSFET design. We also investigate the influence of source-drain tunnelling on the intrinsic parameter fluctuations in these devices.
Substrate Recognition of Nitrogenase-like Dark Operative Protochlorophyllide Oxidoreductase from Prochlorococcus marinus*

Chlorophyll and bacteriochlorophyll biosynthesis requires the two-electron reduction of protochlorophyllide a ringDbya protochlorophyllide oxidoreductase to form chlorophyllide a. A light-dependent (light-dependent Pchlide oxidoreductase (LPOR)) and an unrelated dark operative enzyme (dark operative Pchlide oxidoreductase (DPOR)) are known. DPOR plays an important role in chlorophyll biosynthesis of gymnosperms, mosses, ferns, algae, and photosynthetic bacteria in the absence of light. Although DPOR shares significant amino acid sequence homologies with nitrogenase, only the initial catalytic steps resemble nitrogenase catalysis. Substrate coordination and subsequent [Fe-S] cluster-dependent catalysis were proposed to be unrelated. Here we characterized the first cyanobacterial DPOR consisting of the homodimeric protein complex ChlL2 and a heterotetrameric protein complex (ChlNB)2. The ChlL2 dimer contains one EPR active [4Fe-4S] cluster, whereas the (ChlNB)2 complex exhibited EPR signals for two [4Fe-4S] clusters with differences in their g values and temperature-dependent relaxation behavior. These findings indicate variations in the geometry of the individual [4Fe-4S] clusters found in (ChlNB)2. For the analysis of DPOR substrate recognition, 11 synthetic derivatives with altered substituents on the four pyrrole rings and the isocyclic ring plus eight chlorophyll biosynthetic intermediates were tested as DPOR substrates. Although DPOR tolerated minor modifications of the ring substituents on rings A–C, the catalytic target ring D was apparently found to be coordinated with high specificity. Furthermore, protochlorophyllide a, the corresponding [8-vinyl]-derivative and protochlorophyllide b were equally utilized as substrates. Distinct differences from substrate binding by LPOR were observed. Alternative biosynthetic routes for cyanobacterial chlorophyll biosynthesis with regard to the reduction of the C8-vinyl group and the interconversion of a chlorophyll a/b type C7 methyl/formyl group were deduced.
Back-of-the-Envelope Computation of Throughput Distributions in CSMA Wireless Networks

This work started out with our discovery of a pattern of throughput distributions among links in IEEE 802.11 networks from experimental results. This pattern gives rise to an easy computation method, which we term back-of-the-envelop (BoE) computation. For many network configurations, very accurate results can be obtained by BoE within minutes, if not seconds, by simple hand computation. This allows us to make shortcuts in performance evaluation, bypassing complicated stochastic analysis. To explain BoE, we construct a theory based on the model of an “ideal CSMA network” (ICN). The BoE computation method emerges from ICN when we take the limit c → 0, where c is the ratio of the mean backoff countdown time to the mean transmission time in the CSMA protocol. Importantly, we derive a new mathematical result: the link throughputs of ICN are insensitive to the distributions of the backoff countdown time and transmission time (packet duration) given the ratio of their means c. This insensitivity result explains why BoE works so well for practical 802.11 networks, in which the backoff countdown process is one that has memory, and in which the packet size can be arbitrarily distributed. Our results indicate that BoE is a good approximation technique for modest-size networks such as those typically seen in 802.11 deployments. Beyond explaining BoE, the theoretical framework of ICN is also a foundation for fundamental understanding of very-large-scale CSMA networks. In particular, ICN is similar to the Ising model in statistical physics used to explain phenomena arising out of the interactions of a large number of entities. Many new research directions arise out of the ICN model.
Statistical and kinetic approaches for linear low-density polyethylene melting modeling

The aim of this study was to compare different models, either originating from literature or originally proposed in this study, for the interpretation of the melting behavior of polymers. In particular, these models, tested with a linear low-density polyethylene widely used in rotational molding, are suitable for coupling with energy balances in the study of polymer processing. We obtained the experimental data from differential scanning calorimetry (DSC) dynamic scans, assuming that the endothermic flux was related to the rate of melting of the polymer. The studied models were able to predict the broad melting temperature range typically observed during polymer melting with either a statistical or a kinetic approach. The two different approaches were compared with experimental DSC data. The analysis of model performances with complex thermal programs showed that the statistical approach could provide a more realistic representation of polymer melting. These models were particularly suitable in rotational molding, where the lack of any flow and, hence, of any crystalline orientation leads to a degree of melting determined by the actual temperature of the polymer. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 289–295, 2003
Damage evolution in triaxial compression tests of HMA at high temperatures

This paper presents the results of an experiment aimed at capturing and characterizing damage evolution in hot mix asphalt (HMA) at relatively high temperatures. HMA specimens were loaded using a triaxial compression setup to four predefined strain levels at three confining pressures. X-ray computed tomography (CT) was used to capture the microstructure of the HMA specimens before and after loading, and image analysis techniques (IAT) were used to characterize the evolution of air voids and cracks throughout the deformation process. Image analysis techniques were developed to distinguish between air void growth and crack evolution. This is extremely important as the underlying mechanisms for these two phenomena are different. The term "voids" is used throughout this paper to refer to air voids and cracks combined. Damage in HMA was found to initiate following a period of microstructure hardening. In addition, damage was found to be localized in a critical section in a specimen that was mainly responsible for failure. The growth and propagation of cracks in this critical section was significantly larger than that in the rest of the specimen. The study showed that the top part of the specimens exhibited significant cracking, the middle part exhibited significant amount of dilation, and minor microstructural changes occurred in the bottom part. These variations within a specimen are attributed mainly to the heterogeneity of the HMA microstructure. The results of this study are expected to have significant impacts on the current state of knowledge with regard to damage evolution due to permanent deformation at high temperatures. These results are discussed within the framework of a microstructure viscoplastic continuum model for HMA permanent deformation developed by the authors. The results demonstrate that there is a pressing need to prepare homogenous specimens in the laboratory. Otherwise, localization due to microstructure heterogeneity will render the interpretation of laboratory testing results a very difficult task. More importantly the findings of this study will influence the approaches typically followed in the development of permanent deformation models. These models should account for the effect of damage localization on accelerating permanent deformation.
Electromagnetic scattering and induction models for spheroidal geometries

Electromagnetic scattering from a medium containing randomly distributed discrete dielectric spheroidal inclusions is studied. Also, the broadband magnetoquasistatic solution for the induced magnetic field from a conducting and permeable spheroid under time harmonic excitation is demonstrated. Analytical electromagnetic solutions for spheroidal geometries are desirable because of their versatility in modeling manmade and natural shapes including solid and hollow needles, spheres, and disks, while at the same time possessing analytic solutions. Coherent scattering from a collection of small dielectric spheroids populating a dense medium is compared to scattering from a homogeneous sphere. A Method of Moments (MoM) solution is adopted which accounts for spheroid-spheroid interactions directly. Coherent scattering results from these collections are compared to Mie scattering and the effective permittivity of the dense medium is obtained. Results are in good agreement to the classical mixing formula and this lends credibility to both models. In order to reduce memory requirements and computational complexity, the Sparse Matrix/Canonical Grid (SMCG) method is applied to 3-D dense media scattering. By approximating the dyadic Green’s function about a canonical rectilinear grid, weak interaction between spheroid far apart may be quickly approximated. Strong interactions between dielectric spheroid in close proximity are still calculated directly. Weak interactions are quickly evaluated using a novel multilevel block-Toeplitz matrix vector multiply based on the Fast Fourier Transform. Electromagnetic induction (EMI) models of conducting and permeable spheroids under time harmonic excitation are refined to produce the broadband response with high dependability. A hybrid method is constructed consisting of three different approaches: 1) at low frequencies, the formally exact (but truncated) solution is applied, 2) at moderate frequencies, asymptotic expansions of the spheroidal wave functions (SWFs) are employed, 3) and at high, but still magnetoquasistatic, frequencies, a Small Penetration Approximation is borrowed. The combined EMI response is accurate except near a switchover point where there is typically less than a two percent error. Results are compared to data from a set of 17 steel and aluminum machined spheroids taken by the GEM-3 instrument and found to be in excellent agreement. Asymptotic expressions of the SWFs are found to depend on branch points and associated characteristic eigenvalues of the spheroidal wave equation. These branch points are found using polynomial estimation techniques and a quadruple precision Newton-Rhapson
PREDICTION OF LUNG CANCER USING ANFIS CONTROLLER SYSTEM

The most leading cancer among all in human beings is lung cancer. There are more than 17% percent of the total cancer related deaths so the fast and early detection of lung cancer can help in a sharp decrease in the lung cancer death rate.The CT image of lung helps us to find the presence of lung cancer. Doctor analyses the CT image and predicts the presence of cancer nodule. There is a chances of false recognition in the manual identification of cancer.So there is a need of automated approach of lung cancer detection Image processing technique can be used for this purpose. In this paper we propose a Lung cancer identification system that uses a fuzzy inference system to spot the most prominent cancer cells. The approach has four stage to detect the existence of cancer nodule in lung. Pre-processing stage, Segmentation stage, feature extraction stage and fuzzy inference rules to identify lung cells. Pre-processing step includes image enhancement. Enhanced CT image of lung is then passed through segmentation phase. From the segmented output features are extracted to predict the existence of abnormality of lung. On these extracted features ANFIS controllers are applied to identify the possibility of cancer cells.
Representational dynamics of facial viewpoint encoding: Head orientation, viewpoint symmetry, and front-on views.

Faces provide a large variety of information, including the identity of the seen person, their emotional state and social cues, such as the direction of gaze. Crucially, these different aspects of face processing require distinct forms/types of viewpoint encoding. Whereas another person's attentional focus is supported by a view-based code, identification requires the opposite: a fully viewpoint-invariant representation. Different cortical areas have been suggested to provide either function. However, little is known about temporal aspects of viewpoint encoding in the human brain. Here, we combine electroencephalography (EEG) measurements with multivariate decoding techniques to resolve the dynamics of face processing with high temporal resolution. Data were recorded while subjects were presented with faces shown from 37 viewpoints. We then used the resulting patterns of visually evoked potentials to compute representational similarity matrices across time, and performed data- and model-driven analyses to reveal changes in the underlying cortical selectivity, while controlling for effects of low-level stimulus properties and eye-movement artifacts. These analyses revealed a distinct sequence of viewpoint encoding. Head orientations were encoded first, potentially driven by low-level stimulus features. Shortly afterwards, at a latency of about 130ms, these were followed by strong effects of viewpoint symmetry, i.e. the joint selectivity for mirror-symmetric viewing angles, which were previously suggested to support subsequent, viewpoint-invariant identity recognition. At a considerably later stage, about 280ms after visual onset, EEG response patterns demonstrate a large degree of viewpoint invariance across almost all viewpoints tested, with the marked exception of front-on faces, the only viewing angle exhibiting direct eye-contact. Taken together, our results indicate that the encoding of facial viewpoints follows a temporal sequence of coding schemes, including invariance to symmetric viewpoints as a separate stage, supporting distinct task requirements at different stages of face processing. Meeting abstract presented at VSS 2015.
Revealing the Effects of Nanoscale Membrane Curvature on Lipid Mobility

Recent advances in nanoengineering and super-resolution microscopy have enabled new capabilities for creating and observing membrane curvature. However, the effects of curvature on single-lipid diffusion have yet to be revealed. The simulations presented here describe the capabilities of varying experimental methods for revealing the effects of nanoscale curvature on single-molecule mobility. Traditionally, lipid mobility is revealed through fluorescence recovery after photobleaching (FRAP), fluorescence correlation spectroscopy (FCS), and single particle tracking (SPT). However, these techniques vary greatly in their ability to detect the effects of nanoscale curvature on lipid behavior. Traditionally, FRAP and FCS depend on diffraction-limited illumination and detection. A simulation of FRAP shows minimal effects on lipids diffusion due to a 50 nm radius membrane bud. Throughout the stages of the budding process, FRAP detected minimal changes in lipid recovery time due to the curvature versus flat membrane. Simulated FCS demonstrated small effects due to a 50 nm radius membrane bud that was more apparent with curvature-dependent lipid mobility changes. However, SPT achieves a sub-diffraction-limited resolution of membrane budding and lipid mobility through the identification of the single-lipid positions with ≤15 nm spatial and ≤20 ms temporal resolution. By mapping the single-lipid step lengths to locations on the membrane, the effects of membrane topography and curvature could be correlated to the effective membrane viscosity. Single-fluorophore localization techniques, such SPT, can detect membrane curvature and its effects on lipid behavior. These simulations and discussion provide a guideline for optimizing the experimental procedures in revealing the effects of curvature on lipid mobility and effective local membrane viscosity.