Miracle-dz/UniFAR-FTUs huggingface dataset:
Which is in front of Chinese people: Past or Future? A study on Chinese people's space-time mapping

Recent research shows that Chinese, when they gesture about time, tend to put the past “ahead” and the future “behind”. Do they think of time in the way as suggested by their gestures? In this study we investigate whether Chinese people explicitly have such past-in-front mappings. In experiment 1 we show that when time conceptions are constructed with neutral wording (without spatial metaphors), Chinese people are more likely to have a pastin-front-mapping than Spaniards. This could be due to cultural differences in temporal focus of attention, in that Chinese people are more past-oriented than Europeans. However, additional experiments (2 & 3) show that, independent of culture, Chinese people’s past-in-front mapping is sensitive to the wording of sagittal spatial metaphors. In comparison to a neutral condition, they have more past-in-front mappings when time conceptions are constructed with past-in-front spatial metaphors (“front day”, means the day before yesterday), whereas fewer pastin-front mappings are constructed with future-in-front metaphors. There thus appear to be both long-term effects of cultural attitudes on the spatialization of time, and also immediate effects of the space-time metaphors used to probe people’s mental representations.
AUGMENTED VIRTUAL REALITY APPLICATIONS IN MANUFACTURING

Augmented Reality (AR) is a growing area in virtual reality research. The world environment around us provides a wealth of information that is difficult to duplicate in a computer. This is evidenced by the worlds used in virtual environments. Either these worlds are very simplistic such as the environments created for immersive entertainment and games, or the system that can create a more realistic environment has a million dollar price tag such as flight simulators. An augmented reality system generates a composite view for the user. It is a combination of the real scene viewed by the user and a virtual scene generated by the computer that augments the scene with additional information.
Multi-channel EEG compression based on 3D decompositions

Various compression algorithms for multi-channel electroencephalograms (EEG) are proposed and compared. The multi-channel EEG is represented as a three-way tensor (or 3D volume) to exploit both spatial and temporal correlations efficiently. A general two-stage coding framework is developed for multi-channel EEG compression. In the first stage, we consider (i) wavelet-based volumetric coding; (ii) energy-based lossless compression of wavelet subbands; (iii) tensor decomposition based coding. In the second stage, the residual is quantized and coded. Through such two-stage approach, one can control the maximum error (worst-case distortion). Numerical results for a standard EEG data set show that tensor-based coding achieves lower worst-case error and comparable average error than the wavelet- and energy-based schemes.
Differential decoding for SFBC OFDM systems in underwater MIMO channels

We investigate the use of differential space frequency block codes (SFBCs) with orthogonal frequency division multiplexing (OFDM) over underwater acoustic channels. While SFBC efficiently exploits spatial transmit diversity, differentially coherent detection eliminates the need for extensive signal processing required for channel tracking. System performance is demonstrated using real data transmitted in the 12-26 kHz acoustic band from a vehicle moving at 0.5-2 m/s and received over a 100 m shallow water channel, using 4-QAM and a varying number of carriers ranging from 128 to 2048. Performance results demonstrate the advantage of the differentially coherent SFBC detection over the conventional, coherent SFBC detection which suffers from imperfect channel estimation.
Smoothed particle hydrodynamics simulations of the core-degenerate scenario for Type Ia supernovae

The core-degenerate scenario for Type Ia supernovae involves the merger of the hot core of an asymptotic giant branch star and a white dwarf, and might contribute a non-negligible fraction of all thermonuclear supernovae. Despite its potential interest, very few studies, and based on only crude simplifications, have been devoted to investigate this possible scenario, compared with the large efforts invested to study some other scenarios. Here we perform the first three-dimensional simulations of the merger phase, and find that this process can lead to the formation of a massive white dwarf, as required by this scenario. We consider two situations, according to the mass of the circumbinary disc formed around the system during the final stages of the common envelope phase. If the disc is massive enough, the stars merge on a highly eccentric orbit. Otherwise, the merger occurs after the circumbinary disc has been ejected and gravitational wave radiation has brought the stars close enough for the secondary to overflow its Roche lobe radius. Not surprisingly, the overall characteristics of the merger remnants are similar to those found for the double-degenerate scenario, independently of the very different core temperature and of the orbits of the merging stars. They consist of a central massive white dwarf, surrounded by a hot, rapidly rotating corona and a thick debris region.
Budget-Dependent Convergence Rate of Stochastic Approximation

Convergence rate results are derived for a stochastic optimization problem where a performance measure is minimized with respect to a vector parameter t. Assuming that a gradient estimator is available and that both the bias and the variance of the estimator are (known) functions of the budget devoted to its computation, the gradient estimator is employed in conjunction with a stochastic approximation (SA) algorithm. Our interest is to figure out how to allocate the total available computational budget to the successive SA iterations. The effort is devoted to solving the asymptotic version of this problem by finding the convergence rate of SA toward the optimizer, first as a function of the number of iterations and then as a function of the total computational effort. As a result the optimal rate of increase of the computational budget per iteration can be found. Explicit expressions for the case where the computational budget devoted to an iteration is a polynomial in the iteration number, and where the bias and variance of the gradient estimator are polynomials of the computational budget, are derived. Applications include the optimization of steady-state simulation models with likelihood ratio, perturbation analysis, or finite-difference gradient estimators; optimization of infinite-horizon models with discounting; optimization of functions of several expectations; and so on. Several examples are discussed. Our results readily generalize to general root-finding problems.
On the Relative Strength of Pebbling and Resolution

The last decade has seen a revival of interest in pebble games in the context of proof complexity. Pebbling has proven to be a useful tool for studying resolution-based proof systems when comparing the strength of different subsystems, showing bounds on proof space, and establishing size-space trade-offs. The typical approach has been to encode the pebble game played on a graph as a CNF formula and then argue that proofs of this formula must inherit (various aspects of) the pebbling properties of the underlying graph. Unfortunately, the reductions used here are not tight. To simulate resolution proofs by pebblings, the full strength of nondeterministic black-white pebbling is needed, whereas resolution is only known to be able to simulate deterministic black pebbling. To obtain strong results, one therefore needs to find specific graph families which either have essentially the same properties for black and black-white pebbling (not at all true in general) or which admit simulations of black-white pebblings in resolution. This paper contributes to both these approaches. First, we design a restricted form of black-white pebbling that can be simulated in resolution and show that there are graph families for which such restricted pebblings can be asymptotically better than black pebblings. This proves that, perhaps somewhat unexpectedly, resolution can strictly beat black-only pebbling, and in particular that the space lower bounds on pebbling formulas in [Ben-Sasson and Nordstrom 2008] are tight. Second, we present a versatile parametrized graph family with essentially the same properties for black and black-white pebbling, which gives sharp simultaneous trade-offs for black and black-white pebbling for various parameter settings. Both of our contributions have been instrumental in obtaining the time-space trade-off results for resolution-based proof systems in [Ben-Sasson and Nordstrom 2009].
Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

We present a trajectory optimization framework for legged locomotion on rough terrain. We jointly optimize the center of mass motion and the foothold locations, while considering terrain conditions. We use a terrain costmap to quantify the desirability of a foothold location. We increase the gait's adaptability to the terrain by optimizing the step phase duration and modulating the trunk attitude, resulting in motions with guaranteed stability. We show that the combination of parametric models, stochastic-based exploration and receding horizon planning allows us to handle the many local minima associated with different terrain conditions and walking patterns. This combination delivers robust motion plans without the need for warm-starting. Moreover, we use soft-constraints to allow for increased flexibility when searching in the cost landscape of our problem. We showcase the performance of our trajectory optimization framework on multiple terrain conditions and validate our method in realistic simulation scenarios and experimental trials on a hydraulic, torque controlled quadruped robot.
Differential evolution based advised SVM for histopathalogical image analysis for skin cancer detection

Automated detection of cancerous tissue in histopathological images is a big challenge. This work proposed a new pattern recognition method for histopathological image analysis for identification of cancerous tissues. It comprised of feature extraction using a combination of wavelet and intensity based statistical features and autoregressive parameters. Moreover, differential evolution based feature selection is used for dimensionality reduction and an efficient self-advised version of support vector machine is used for evaluation of selected features and for the classification of images. The proposed system is trained and tested using a dataset of 150 histopathological images and showed promising comparative results with an average diagnostic accuracy of 89.1%.
Measurement of inflammatory cytokines by multicytokine assay in tears of patients with glaucoma topically treated with chronic drugs

Aim: To investigate the ocular surface inflammatory response to chronic topical treatments in patients with glaucoma by measuring the cytokine level in tears using multiplex bead analysis. Methods: Tear samples were collected from 21 patients with glaucoma and 12 healthy volunteers. Tears were analysed for the presence of 17 cytokines: interleukin (IL)1β, IL2, IL4, IL5, IL6, IL7, IL8, IL10, IL12, IL13, IL17, granulocyte-colony stimulating factor, granulocyte-macrophage stimulating factor, interferon (INF)γ, monocyte chemotactic protein (MCP)1, macrophage inflammatory protein 1β and tumour necrosis factor (TNF)α. The cytokines in each sample of tears were measured using multiplex bead analysis with microspheres as solid support for immunoassays. Results: In the tears of treated patients, proinflammatory cytokines (IL1β, IL6, IL12, TNFα) were significantly increased compared with controls. T helper (Th)1 (INFγ, IL2) and Th2 (IL5, IL10, IL4) type cytokines were also significantly higher (p<0.05); however, the most marked increase was observed with Th1 cytokines. The expression of chemokine IL8 and MCP1 was also increased in the treated group. Conclusion: This study shows that pro-inflammatory cytokine secretion by conjunctival cells is increased in response to topical treatments for glaucoma. The characterisation of cytokines in tears was previously limited by the small volume attainable, a limitation that has been overcome by multiplex analysis.
The edge-fault tolerant hamiltonian of the balanced hypercube

Huang and Wu proposed a new network which is called balanced hypercube, the balanced hypercube is a variant of the hypercube network. As a crucial factor to evaluate the performance of the interconnection networks, fault tolerance of the interconnection networks has been widely studied in recent years. Hence, it is nature to consider the fault tolerance of the balanced hypercubes. Wu and Huang have proved that the balanced hypercube is bipartite graph. Hao has proved that there exists a fault-free Hamiltonian path between any two adjacent vertices in BHn with (2n-2) faulty edges. This paper has proved one Hamiltonian property in BHn with (n - 1) faulty edges.
Calculated RF electric field and temperature distributions in RF thermal ablation: Comparison with gel experiments and liver imaging

The present paper is a study of theoretic modeling and experimental tests of that modeling for the local heating due to radiofrequency thermal ablation. A model is developed for the current and the associated electric field produced by a radiofrequency ablation probe. The temperature distributions resulting from the induced ohmic currents in the surrounding material are considered. A comparison is made between the theoretic temperature profiles and the shapes of thermal ablation ‘lesions’ produced in a controlled gelatin sample experiment. Comparison with the contours of human thermally induced liver lesions found in MRI studies also provides a validation of the success of the modeling. Successful modeling should lead to methods for optimization of the ablation procedure, especially as it is used in interventional MRI.
Vector Approximation File: Cluster Bounding in High-Dimension Data Set

 Abstract— In many modern application ranges high-dimensional feature vectors are used to model complex data sets. We have proposed an overview about efficient indexing method for high-dimensional database using an filtering approach known as vector approximation approach which supports the nearest neighbor search efficiently And A cluster distance bound based on separating hyper planes, that complements our index in electively retrieving clusters that contain data entries closest to the query. The Creation of approximation for Vectors for use in similarity (also known the retrieval of k-nearest neighbor) is examined.
Molecular Systems Biology Peer Review Process File Tt-seq Captures Enhancer Landscapes Immediately after T-cell Stimulation Editor: Maria Polychronidou Transaction Report

(Note: With the exception of the correction of typographical or spelling errors that could be a source of ambiguity, letters and reports are not edited. The original formatting of letters and referee reports may not be reflected in this compilation.) Thank you again for submitting your work to Molecular Systems Biology. We have now heard back from the two referees who agreed to evaluate your study. As you will see below, the reviewers raise some concerns, which we would ask you to address in a revision. The reviewers' recommendations are quite clear so I think that there is no need to repeat the points listed below. Please let me know in case you would like to further discuss any of the issues raised. This manuscript reports the application of TT-seq, a powerful method recently developed by the authors, to study rapid transcriptional responses of enhancers and promoters. It is demonstrated here that 4sU labeling pulses as short as 5 minutes can be applied to detect rapid up-and down-regulation of transcriptional activity genome-wide after application of particular stimuli to cells. Because TT-seq appears to be a relatively simple method (compared to some other run-on transcription mapping methods) these results are important to a broad readership and worthy of publication in MSB. The manuscript is clear and the data look solid.
A Modular Formalization of Reversibility for Concurrent Models and Languages

Causal-consistent reversibility is the reference notion of reversibility for concurrency. We introduce a modular framework for defining causal-consistent reversible extensions of concurrent models and languages. We show how our framework can be used to define reversible extensions of formalisms as different as CCS and concurrent X-machines. The generality of the approach allows for the reuse of theories and techniques in different settings.
Ethanol and Reactive Species Increase Basal Sequence Heterogeneity of Hepatitis C Virus and Produce Variants with Reduced Susceptibility to Antivirals

Hepatitis C virus (HCV) exhibits a high level of genetic variability, and variants with reduced susceptibility to antivirals can occur even before treatment begins. In addition, alcohol decreases efficacy of antiviral therapy and increases sequence heterogeneity of HCV RNA but how ethanol affects HCV sequence is unknown. Ethanol metabolism and HCV infection increase the level of reactive species that can alter cell metabolism, modify signaling, and potentially act as mutagen to the viral RNA. Therefore, we investigated whether ethanol and reactive species affected the basal sequence variability of HCV RNA in hepatocytes. Human hepatoma cells supporting a continuous replication of genotype 1b HCV RNA (Con1, AJ242652) were exposed to ethanol, acetaldehyde, hydrogen peroxide, or L-buthionine-S,R-sulfoximine (BSO) that decreases intracellular glutathione as seen in patients. Then, NS5A region was sequenced and compared with genotype 1b HCV sequences in the database. Ethanol and BSO elevated nucleotide and amino acid substitution rates of HCV RNA by 4–18 folds within 48 hrs which were accompanied by oxidative RNA damage. Iron chelator and glutathione ester decreased both RNA damage and mutation rates. Furthermore, infectious HCV and HCV core gene were sufficient to induce oxidative RNA damage even in the absence of ethanol or BSO. Interestingly, the dn/ds ratio and percentage of sites undergoing positive selection increased with ethanol and BSO, resulting in an increased detection of NS5A variants with reduced susceptibility to interferon alpha, cyclosporine, and ribavirin and others implicated in immune tolerance and modulation of viral replication. Therefore, alcohol is likely to synergize with virus-induced oxidative/nitrosative stress to modulate the basal mutation rate of HCV. Positive selection induced by alcohol and reactive species may contribute to antiviral resistance.
Breaking Path Symmetries on 4-Connected Grid Maps

Pathfinding systems that operate on regular grids are common in the AI literature and often used in real-time video games. Typical speed-up enhancements include reducing the size of the search space using abstraction, and building more informed heuristics. Though effective each of these strategies has shortcomings. For example, pathfinding with abstraction usually involves trading away optimality for speed. Meanwhile, improving on the accuracy of the well known Manhattan heuristic usually requires significant extra memorWe present a different kind of speedup technique based on the idea of identifying and eliminating symmetric path segments in 4-connected grid maps (which allow straight but not diagonal movement). Our method identifies rectangular rooms with no obstacles and prunes all interior nodes, leaving only a boundary perimeter. This process eliminates many symmetric path segments and results in grid maps which are often much smaller and consequently much faster to search than the original. We evaluate our technique on a range of different grid maps including a well known set from the popular video game Baldur's Gate II. On our test data, A* can run up to 3.5 times faster on average. We achieve this without using any significant extra memory or sacrificing solution optimality.
chy1, an Arabidopsis Mutant with Impaired β-Oxidation, Is Defective in a Peroxisomal β-Hydroxyisobutyryl-CoA Hydrolase*

The Arabidopsis chy1 mutant is resistant to indole-3-butyric acid, a naturally occurring form of the plant hormone auxin. Because the mutant also has defects in peroxisomal β-oxidation, this resistance presumably results from a reduced conversion of indole-3-butyric acid to indole-3-acetic acid. We have cloned CHY1, which appears to encode a peroxisomal protein 43% identical to a mammalian valine catabolic enzyme that hydrolyzes β-hydroxyisobutyryl-CoA. We demonstrated that a human β-hydroxyisobutyryl-CoA hydrolase functionally complementschy1 when redirected from the mitochondria to the peroxisomes. We expressed CHY1 as a glutathioneS-transferase (GST) fusion protein and demonstrated that purified GST-CHY1 hydrolyzes β-hydroxyisobutyryl-CoA. Mutagenesis studies showed that a glutamate that is catalytically essential in homologous enoyl-CoA hydratases was also essential in CHY1. Mutating a residue that is differentially conserved between hydrolases and hydratases established that this position is relevant to the catalytic distinction between the enzyme classes. It is likely that CHY1 acts in peroxisomal valine catabolism and that accumulation of a toxic intermediate, methacrylyl-CoA, causes the altered β-oxidation phenotypes of the chy1 mutant. Our results support the hypothesis that the energy-intensive sequence unique to valine catabolism, where an intermediate CoA ester is hydrolyzed and a new CoA ester is formed two steps later, avoids methacrylyl-CoA accumulation.
Dynamic trajectory of multiple single-unit activity during working memory task in rats

Working memory plays an important role in complex cognitive tasks. A popular theoretical view is that transient properties of neuronal dynamics underlie cognitive processing. The question raised here as to how the transient dynamics evolve in working memory. To address this issue, we investigated the multiple single-unit activity dynamics in rat medial prefrontal cortex (mPFC) during a Y-maze working memory task. The approach worked by reconstructing state space from delays of the original single-unit firing rate variables, which were further analyzed using kernel principal component analysis (KPCA). Then the neural trajectories were obtained to visualize the multiple single-unit activity. Furthermore, the maximal Lyapunov exponent (MLE) was calculated to quantitatively evaluate the neural trajectories during the working memory task. The results showed that the neuronal activity produced stable and reproducible neural trajectories in the correct trials while showed irregular trajectories in the incorrect trials, which may establish a link between the neurocognitive process and behavioral performance in working memory. The MLEs significantly increased during working memory in the correctly performed trials, indicating an increased divergence of the neural trajectories. In the incorrect trials, the MLEs were nearly zero and remained unchanged during the task. Taken together, the trial-specific neural trajectory provides an effective way to track the instantaneous state of the neuronal population during the working memory task and offers valuable insights into working memory function. The MLE describes the changes of neural dynamics in working memory and may reflect different neuronal population states in working memory.
A Predicted Interactome for Arabidopsis 1(C)(W)(OA)

, Nicholas J. Provart,A. Harvey Millar, and Matt Geisler*Department of Plant Biology, Southern Illinois University, Carbondale, Illinois 62901 (J.G.-L., M.G.);Australian Research Council Centre of Excellence in Plant Energy Biology, University of Western Australia,Crawley, Western Australia 6009, Australia (N.O., A.H.M.); and Department of Cell and Systems Biology,University of Toronto, Toronto, Ontario, Canada M5S 3B2 (R.A., N.J.P.)