Miracle-dz/UniFAR-FTUs huggingface dataset:
China's E-Science Knowledge Grid Environment

The Internet and World Wide Web are milestones in the history of information sharing. Scientists are increasingly relying on them to support their research. Knowledge is the basis of realizing intelligent services. The knowledge grid is a mechanism that can synthesize knowledge from data through mining and reference methods and enable search engines to make references, answer questions, and draw conclusions from masses of data. The knowledge grid infrastructure supports e-science through a set of relevant application services and semantic resources. We have developed a semantic-link-making tool for users to conveniently describe their understandings of provided resources and background knowledge.
Optimal decoding for hard-decision forwarding aided cooperative spatial multiplexing systems

In this letter, the optimal decoding strategy for cooperative spatial multiplexing (CSM) aided systems is derived. In CSM systems, the multiple relay stations (RSs), which compose a virtual antenna array (VAA), independently decode the packets received from the mobile stations (MS) and forward them to the base station (BS). When the BS decodes the signal forwarded from the RSs, the potential decoding errors encountered at the RSs will result in erroneous forwarding, but their effects are mitigated by the proposed solution. Our simulation results show that when the relay link has a significantly higher signal-to-noise ratio than the direct link, the proposed decoding algorithm achieves an approximately 3 dB better performance than conventional CSM, which does not consider the deleterious effects of erroneous forwarding from the RSs.
The Microtubule-Associated Protein Tumor Overexpressed Gene/Cytoskeleton-Associated Protein 5 Is Necessary for Myelin Basic Protein Expression in Oligodendrocytes

Tumor overexpressed gene (TOG) protein, encoded by cytoskeleton-associated protein CKAP5, is a microtubule-associated protein that binds to heterogeneous nuclear ribonucleoprotein (hnRNP) A2. hnRNP A2 is an RNA trafficking factor that associates with myelin basic protein (MBP) mRNA. In oligodendrocytes, TOG, hnRNP A2, and MBP mRNA colocalize in granules that assemble in the perikaryon and are transported to the peripheral network of processes that extends from it. MBP accumulates preferentially in the membrane of the medial and distal portions of these cellular processes. MBP expression was reduced when TOG level was lowered by short-hairpin (sh) RNA. The reduction in TOG did not affect overall cell morphology or the assembly, transport, localization, or number of MBP mRNA-containing granules. Reduced levels of TOG did not affect another oligodendrocyte-specific component, myelin oligodendrocyte glycoprotein, which is expressed at the same time as MBP but translated from mRNA localized in the cell body. Expression in a neural cell line of a green fluorescent protein (GFP)–MBP fusion protein derived from a construct containing GFP and the full-length cDNA for the rat 14 kDa MBP was reduced when TOG level was lowered by shRNA treatment. Expression of GFP, derived from GFP mRNA containing the hnRNP A2 binding element of MBP mRNA, was similarly reduced in cells with low TOG levels. These data indicate that TOG is necessary for efficient translation of MBP mRNA and suggest that this role is mediated by its interaction with hnRNP A2.
Identification of dynamically precipitated phases in hot-working Inconel 718 alloy

Purpose: The main purpose of this paper was to analyze how localized flow/structural inhomogeneties that may develop during hot deformation can affect a precipitated phases and to determine what kind of particles are present in the microstructure of hot-worked Inconel 718 superalloy. Design/methodology/approach: Compression tests were carried out on precipitations hardenable nickel based superalloy of Inconel 718 at constant true strain rates of 10-4 and 4x10-4s-1 at temperature of 720 and 850°C. The dynamic behaviour were explained through observation of the microstructure using standard optical, scanning and transmission electron microscopy. Precipitated phases were identified using EDS technique and based on selected area diffraction pattern. Findings: Microstructural observations of deformed at high temperatures, previously solution treated Inconel superalloy revealed non uniform deformation effects. Distribution of molybdenum- and niobium-rich carbides affected by localized flow was found. Microstructural examination of the alloy also shown shear banding penetrating through the whole grains. Practical implications: The experiments on hot deformation of age hardenable Inconel 718 superalloy and the analysis of dynamic precipitation process have a practical aspect. This interaction could become an important feature of high temperature performance and may also influence the production of specific structures of this material.
Testing sensory evidence against mnemonic templates

Most perceptual decisions require comparisons between current input and an internal template. Classic studies propose that templates are encoded in sustained activity of sensory neurons. However, stimulus encoding is itself dynamic, tracing a complex trajectory through activity space. Which part of this trajectory is pre-activated to reflect the template? Here we recorded magneto- and electroencephalography during a visual target-detection task, and used pattern analyses to decode template, stimulus, and decision-variable representation. Our findings ran counter to the dominant model of sustained pre-activation. Instead, template information emerged transiently around stimulus onset and quickly subsided. Cross-generalization between stimulus and template coding, indicating a shared neural representation, occurred only briefly. Our results are compatible with the proposal that template representation relies on a matched filter, transforming input into task-appropriate output. This proposal was consistent with a signed difference response at the perceptual decision stage, which can be explained by a simple neural model. DOI: http://dx.doi. org/10.7554/eLife.09000. 001
The diagnostic performance of leak-plugging automated segmentation versus manual tracing of breast lesions on ultrasound images

Purpose To assess the diagnostic performance of a leak-plugging segmentation method that we have developed for delineating breast masses on ultrasound images. Materials and methods Fifty-two biopsy-proven breast lesion images were analyzed by three observers using the leak-plugging and manual segmentation methods. From each segmentation method, grayscale and morphological features were extracted and classified as malignant or benign by logistic regression analysis. The performance of leak-plugging and manual segmentations was compared by: size of the lesion, overlap area (Oa) between the margins, and area under the ROC curves (Az). Results The lesion size from leak-plugging segmentation correlated closely with that from manual tracing (R2 of 0.91). Oa was higher for leak plugging, 0.92 ± 0.01 and 0.86 ± 0.06 for benign and malignant masses, respectively, compared to 0.80 ± 0.04 and 0.73 ± 0.02 for manual tracings. Overall Oa between leak-plugging and manual segmentations was 0.79 ± 0.14 for benign and 0.73 ± 0.14 for malignant lesions. Az for leak plugging was consistently higher (0.910 ± 0.003) compared to 0.888 ± 0.012 for manual tracings. The coefficient of variation of Az between three observers was 0.29% for leak plugging compared to 1.3% for manual tracings. Conclusion The diagnostic performance, size measurements, and observer variability for automated leak-plugging segmentations were either comparable to or better than those of manual tracings.
The effects of tissue factor pathway inhibitor and anti-β-2-glycoprotein-I IgG on thrombin generation

The antiphospholipid syndrome (aPS) is a systemic autoimmune disorder characterized by persistent moderate to high titers of antiphospholipid antibodies (aPL), with venous or arterial thrombosis, pregnancy morbidity and thrombocytopenia. It is widely accepted that the pathogenesis of this disorder is due to the contribution of aPL, although the precise mechanisms are unknown. aPL are a family of heterogeneous autoantibodies directed against phospholipid-binding proteins and include lupus anticoagulants (LA) and anticardiolipin antibodies (aCL). The two most common phospholipid-binding proteins targeted are β-2-glycoprotein-I (β2GPI) and prothrombin. They have higher affinities for anionic phospholipids upon binding with certain aPL and therefore may interfere with phospholipid-dependent coagulation reactions and contribute to the prothrombotic state. The major pathway of blood coagulation, the tissue factor (TF) pathway, is triggered by TF in complex with activated coagulation factor VII (FVIIa). Tissue factor pathway inhibitor (TFPI) is a natural anticoagulant that regulates TF: FVIIa proteolytic activity against coagulation factors X (FX) and IX (FIX), by either binding to activated FX (FXa), then to TF: FVIIa, or forming a complex directly with TF: FVIIa: FXa. The resulting quaternary TF: FVIIa: FXa: TFPI complex prevents further TF: FVIIa activity and consequentially decreases thrombin generation and fibrin formation. There is increasing evidence that antibodies with activity against TFPI have a significant role in the development of an increased thrombotic tendency observed in aPS patients. High titers of anti-TFPI autoantibodies have recently been detected with greater frequency among aPS patients compared to patients with aPL only and healthy controls. Furthermore, an inhibitory component to From the Western Australian Biomedical Research Institute, School of Biomedical Sciences, Curtin University of Technology, Perth, WA, Australia (SYL, PE, RO, MA); Department of Haematology, Fremantle Hospital, Perth, WA, Australia (LI, ML); Haematology Department, Royal Perth Hospital, Perth, WA, Australia (JT, RB).
Semi-Supervised Training of Acoustic Models Using Lattice-Free MMI

The lattice-free MMI objective (LF-MMI) has been used in supervised training of state-of-the-art neural network acoustic models for automatic speech recognition (ASR). With large amounts of unsupervised data available, extending this approach to the semi-supervised scenario is of significance. Finite-state transducer (FST) based supervision used with LF-MMI provides a natural way to incorporate uncertainties when dealing with unsupervised data. In this paper, we describe various extensions to standard LF-MMI training to allow the use as supervision of lattices obtained via decoding of unsupervised data. The lattices are rescored with a strong LM. We investigate different methods for splitting the lattices and incorporating frame tolerances into the supervision FST. We report results on different subsets of Fisher English, where we achieve WER recovery of 59-64% using lattice supervision, which is significantly better than using just the best path transcription.
1H NMR and hyperpolarized 13C NMR assays of pyruvate–lactate: a comparative study

Pyruvate–lactate exchange is mediated by the enzyme lactate dehydrogenase (LDH) and is central to the altered energy metabolism in cancer cells. The measurement of exchange kinetics using hyperpolarized 13C NMR has provided a biomarker of response to novel therapeutics. However, the observable signal is restricted to the exchanging hyperpolarized 13C pools and the endogenous pools of 12C‐labelled metabolites are invisible in these measurements. In this study, we investigated an alternative in vitro 1H NMR assay, using [3‐13C]pyruvate, and compared the measured kinetics with a hyperpolarized 13C NMR assay, using [1‐13C]pyruvate, under the same conditions in human colorectal carcinoma SW1222 cells. The apparent forward reaction rate constants (kPL) derived from the two assays showed no significant difference, and both assays had similar reproducibility (kPL = 0.506 ± 0.054 and kPL = 0.441 ± 0.090 nmol/s/106 cells; mean ± standard deviation; n = 3); 1H, 13C assays, respectively). The apparent backward reaction rate constant (kLP) could only be measured with good reproducibility using the 1H NMR assay (kLP = 0.376 ± 0.091 nmol/s/106 cells; mean ± standard deviation; n = 3). The 1H NMR assay has adequate sensitivity to measure real‐time pyruvate–lactate exchange kinetics in vitro, offering a complementary and accessible assay of apparent LDH activity. Copyright © 2013 John Wiley & Sons, Ltd.
Elevated Serum Insulin-Like Growth Factor Binding Protein-2 as a Prognostic Marker in Patients with Ovarian Cancer

Purpose: The purpose of this research was to examine the diagnostic and prognostic significance of elevated serum insulin-like growth factor binding protein (IGFBP)-2 levels in women with ovarian cancer from diagnosis through treatment to relapse or remission. Experimental Design: Serum collected pre- and postoperatively in women newly diagnosed with ovarian cancer, during adjuvant chemotherapy cycles, at 6 months follow-up and at relapse was analyzed for IGFBP-2. Control serum was from women undergoing pelvic or abdominal surgery for benign ovarian disease or nonovarian pathology. Results: IGFBP-2 at diagnosis was significantly elevated (P < 0.0001) in women with ovarian cancer (887 ± 62 ng/ml) compared with benign controls (337 ± 25 ng/ml), and women undergoing nonovarian surgery (439 ± 49 ng/ml) and correlated positively with tumor stage and cellular differentiation but not with CA125. Unexpectedly, IGFBP-2 levels increased additionally 1-week postoperatively in ovarian cancer patients (1581 ± 90 ng/ml; P = 0.0027) as well as controls (977 ± 95 ng/ml; P < 0.0001) and was higher in women who had suboptimal debulking compared with optimal debulking of their tumor. IGFBP-2 levels returned to normal in women without evidence of progressive disease, but remained significantly elevated in women who later relapsed. Patients with IGFBP-2 levels in the highest tertile at diagnosis had a significantly shorter progression-free interval and overall survival. Conclusion: In ovarian cancer IGFBP-2 is elevated at diagnosis, and corresponds to stage and histology with patients in the highest tertile of IGFBP-2 more likely to relapse and have a poorer outlook. Identification of these patients at diagnosis may allow more individualized, aggressive adjuvant treatment and follow-up, and IGFBP-2 may therefore be an important additional prognostic marker in this disease.
Genetic variation at the SLC23A1 locus is associated with circulating concentrations of L-ascorbic acid (vitamin C): evidence from 5 independent studies with >15,000 participants.

BACKGROUND L-ascorbic acid is an essential part of the human diet and has been associated with a wide range of chronic complex diseases, including cardiovascular outcomes. To date, there are no confirmed genetic correlates of circulating concentrations of L-ascorbic acid. OBJECTIVE We aimed to confirm the existence of an association between common variation at the SLC23A1 gene locus and circulating concentrations of L-ascorbic acid. DESIGN We used a 2-stage design, which included a discovery cohort (the British Women's Heart and Health Study), a series of follow-up cohorts, and meta-analysis (totaling 15,087 participants) to assess the relation between variation at SLC23A1 and circulating concentrations of L-ascorbic acid. RESULTS In the discovery cohort, variation at rs33972313 was associated with a reduction in circulating concentrations of L-ascorbic acid (-4.15 micromol/L; 95% CI: -0.49, -7.81 micromol/L; P = 0.03 reduction per minor allele). Pooled analysis of the relation between rs33972313 and circulating L-ascorbic acid across all studies confirmed this and showed that each additional rare allele was associated with a reduction in circulating concentrations of L-ascorbic acid of -5.98 micromol/L (95% CI: -8.23, -3.73 micromol/L; P = 2.0 x 10(-7) per minor allele). CONCLUSIONS A genetic variant (rs33972313) in the SLC23A1 vitamin C active transporter locus was identified that is reliably associated with circulating concentrations of L-ascorbic acid in the general population. This finding has implications more generally for the epidemiologic investigation of relations between circulating L-ascorbic acid and health outcomes.
Towards Deliberative Active Perception using Persistent Memory

—Task coordination for autonomous mobile service robots typically involves a substantial amount of background knowledge and explicit action sequences to acquire the relevant information nowadays. We strive for a system which, given a task, is capable of reasoning about task-relevant knowledge to automatically determine whether that knowledge is sufﬁcient. If missing or uncertain, the robot shall decide autonomously on the actions to gain or improve that knowledge. In this paper we present our baseline system implementing the foundations for these capabilities. The robot has to analyze a tabletop scene and increase its object type conﬁdence. It plans motions to observe the scene from multiple perspectives, combines the acquired data
Distance Perception in Immersive Virtual Environments, Revisited

Numerous previous studies have suggested that distances appear to be compressed in immersive virtual environments presented via head mounted display systems, relative to in the real world. However, the principal factors that are responsible for this phenomenon have remained largely unidentified. In this paper we shed some new light on this intriguing problem by reporting the results of two recent experiments in which we assess egocentric distance perception in a high fidelity, low latency, immersive virtual environment that represents an exact virtual replica of the participant’s concurrently occupied real environment. Under these novel conditions, we make the startling discovery that distance perception appears not to be significantly compressed in the immersive virtual environment, relative to in the real world.
Learning a field of Gaussian mixture model for image classification

Most unsupervised learners such as Kmeans, Gaussian mixture model (GMM) or sparse coding do not use the structure information found from the neighbourhood of an image patch for parameter estimation. A recent image prior technique combine unsupervised learning with Markov Random Field (MRF) by replacing the MRF potential with an unsupervised learner. It uses a neighbourhood of image patches for learning the parameters of the unsupervised learner, thus capturing image structure information. In this work, we apply this image prior technique to GMM parameter estimation so that the learnt model is more expressive than GMM learnt from a single image patch alone. First, we develop a rule for estimating GMM parameter with a fast approximation called the maximization-maximization (MM) algorithm. Then, we allow the same approximation to extend to a neighbourhood of patch or a maximal clique. The effect is similar to taking the product of individual likelihood of each clique or patch within a maximal clique. We tested the performance of the proposed method on an publicly available image categorization dataset and was able to outperform both Kmeans and GMM for different cluster sizes.
Dietary Salt Reduction and Cardiovascular Disease Rates in India: A Mathematical Model

Background Reducing salt intake has been proposed to prevent cardiovascular disease in India. We sought to determine whether salt reductions would be beneficial or feasible, given the worry that unrealistically large reductions would be required, worsening iodine deficiency and benefiting only urban subpopulations. Methods and Results Future myocardial infarctions (MI) and strokes in India were predicted with a Markov model simulating men and women aged 40 to 69 in both urban and rural locations, incorporating the risk reduction from lower salt intake. If salt intake does not change, we expect ∼8.3 million MIs (95% CI: 6.9–9.6 million), 830,000 strokes (690,000–960,000) and 2.0 million associated deaths (1.5–2.4 million) per year among Indian adults aged 40 to 69 over the next three decades. Reducing intake by 3 g/day over 30 years (−0.1 g/year, 25% reduction) would reduce annual MIs by 350,000 (a 4.6% reduction; 95% CI: 320,000–380,000), strokes by 48,000 (−6.5%; 13,000–83,000) and deaths by 81,000 (−4.9%; 59,000–100,000) among this group. The largest decline in MIs would be among younger urban men, but the greatest number of averted strokes would be among rural men, and nearly one-third of averted strokes and one-fifth of averted MIs would be among rural women. Only under a highly pessimistic scenario would iodine deficiency increase (by <0.0001%, ∼1600 persons), since inadequate iodized salt access—not low intake of iodized salt—is the major cause of deficiency and would be unaffected by dietary salt reduction. Conclusions Modest reductions in salt intake could substantially reduce cardiovascular disease throughout India.
Composable Incremental and Iterative Data-Parallel Computation with Naiad

We report on the design and implementation of Naiad, a set of declarative data-parallel language extensions and an associated runtime supporting efficient and composable incremental and iterative computation. This combination is enabled by a new computational model we call differential dataflow, in which incremental computation can be performed using a partial, rather than total, order on time. Naiad extends standard batch data-parallel processing models like MapReduce, Hadoop, and Dryad/DryadLINQ, to support efficient incremental updates to the inputs in the manner of a stream processing system, while at the same time enabling arbitrarily nested fixed-point iteration. In this paper, we evaluate a prototype of Naiad that uses shared memory on a single multi-core computer. We apply Naiad to various computations, including several graph algorithms, and observe good scaling properties and efficient incremental recomputation.
Predictive control of a Linear Motor for tracking of constant references

This paper deals with the application of a model predictive controller (MPC) for tracking to a real system: a linear motor. The MPC formulation used in this paper in a novel approach to track piecewise constant references recently presented by the authors. The main novelties of this controller are: (i) the addition of an artificial steady state and input as decision variables, (ii) the minimization of a modified cost function which penalizes the error with the artificial steady and the distance from the artificial to the desired steady state and (iii) the usage of an extended terminal constraint. The obtained MPC ensures the admissible convergence to any admissible set point for any feasible initial state. The optimization problem associated to this MPC technique results to be a quadratic programming problem parametrized in the current state and the desired steady state. Thus, well-known techniques to compute the control law explicitly based on multiparametric programming can be used, which allows us to apply this control technique to fast systems. We have applied an explicit MPC for tracking to a synchronous linear motor with permanent magnets using a sampling time of 10 ms. This system has been modelled as a linear system with constraints in the input and states. The control objective is to steer the motor at any admissible position in an admissible evolution. The explicit controller has been coded as a search tree for its implementation on a dSPACE Card. The obtained experimental results are satisfactory and show the properties of the predictive controller