Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient and Robust Semantic Hashing Framework for Similar Text Search

Similar text search aims to find texts relevant to a given query from a database, which is fundamental in many information retrieval applications, such as question search and exercise search. Since millions of texts always exist behind practical search engine systems, a well-developed text search system usually consists of recall and ranking stages. Specifically, the recall stage serves as the basis in the system, where the main purpose is to find a small set of relevant candidates accurately and efficiently. Towards this goal, deep semantic hashing, which projects original texts into compact hash codes, can support good search performance. However, learning desired textual hash codes is extremely difficult due to the following problems. First, compact hash codes (with short length) can improve retrieval efficiency, but the demand for learning compact hash codes cannot guarantee accuracy due to severe information loss. Second, existing methods always learn the unevenly distributed codes in the space from a local perspective, leading to unsatisfactory code-balance results. Third, a large fraction of textual data contains various types of noise in real-world applications, which causes the deviation of semantics in hash codes. To this end, in this article, we first propose a general unsupervised encoder-decoder semantic hashing framework, namely MASH (short for Memory-bAsed Semantic Hashing), to learn the balanced and compact hash codes for similar text search. Specifically, with a target of retaining semantic information as much as possible, the encoder introduces a novel relevance constraint among informative high-dimensional representations to guide the compact hash code learning. Then, we design an external memory where the hashing learning can be optimized in the global space to ensure the code balance of the learning results, which can promote search efficiency. Besides, to alleviate the performance degradation problem of the model caused by text noise, we propose an improved SMASH (short for denoiSing Memory-bAsed Semantic Hashing) model by incorporating a noise-aware encoder-decoder framework. This framework considers the noise degree for each text from the semantic deviation aspect, ensuring the robustness of hash codes. Finally, we conduct extensive experiments in three real-world datasets. The experimental results clearly demonstrate the effectiveness and efficiency of MASH and SMASH in generating balanced and compact hash codes, as well as the superior denoising ability of SMASH.
Intercorporeal Biofeedback for Movement Learning

Technology-supported movement learning has received increased attention in HCI. Previous design research has mostly focused on individual experiences, even though the social and situated context is essential to movement learning practices. Based on the experiences from two design projects in the fitness domain featuring open-ended biofeedback artefacts, we propose Intercorporeal Biofeedback as a strong concept to support the design and use of biofeedback in such practices. We ground the concept in situated movement learning theory, phenomenology of social cognition, and HCI work on biofeedback. We articulate four key characteristics of intercorporeal biofeedback: it provides participants with a shared frame of reference, upon which they engage in fluid meaning allocation and use it to guide attention and action, becoming an interactional resource. Intercorporeal biofeedback can serve to guide future design work for situated, social movement practices.
Three-way Preference Completion via Preference Graph

With the personal partial rankings from agents over a subset of alternatives, the goal of preference completion is to infer the agent’s personalized preference over all alternatives including those the agent has not yet handled from uncertain preference of third parties. By combining the partial rankings of the target agent and the partial rankings from third parties to settle some disagreement with three-way preference completion, which includes a general strategy, an optimal strategy, and a pessimistic strategy, it forms the weighted preference graph. Technically, to settle the disagreement and obtain the completed preference of the target agent in the weighted preference graph, maximum likelihood estimation (MLE) under Mallows is proposed and validated theoretically by removing edges with the minimum weight in the weighted preference graph. However, it is not easy to locate the edges with the minimum weight efficiently in a big graph. Hence, an optimal MLE algorithm and three greedy MLE algorithms are proposed to process the MLE. Furthermore, these proposed algorithms are experimentally validated and compared with each other by both the synthetic dataset and the Flixter dataset.
Magnetic force microscopy study of perpendicular media: Signal-to-noise determination and transition noise analysis

Signal-to-noise ratio (SNR) from a limited bit sequence has been extracted from magnetic force microscopy (MFM) images by two different methods and compared. The autocorrelation SNR properties extracted from the MFM image data are in better agreement with spinstand data than “normal” Fourier extracted SNR values. Transition noise data were also extracted and analyzed, “Squeezing” of the noise was measured as the periodicity of the recorded bit pattern became smaller than 250 nm and subsequently a relaxation at ∼200 nm occurred. MFM analysis based SNR data for two media types (CoCrPtTa alloy and CoB/Pd multilayer based) are compared. Ni45Fe55 alloy was used for the soft underlayer material.
Femtosecond laser-induced cone emission in dense cesium vapor

We report the observation of cone emission generated when $\ensuremath{\sim}10\text{\ensuremath{-}}\mathrm{nJ}$, 100-fs laser pulses in the 730\char21{}770 nm wavelength range are transmitted through a dense cesium vapor. The spatial and spectral characteristics of the observed cone emission were studied experimentally. Cone angle dependence on the laser wavelength, laser average power, and Cs atomic and molecular concentrations were investigated. The cone emission (CE) was only observed when the laser beam self-focused after passing through the medium. We identify the self-phase modulation as a dominant mechanism for CE generation in our experiment.
Multi-Feature Fusion Based Object Detecting and Tracking

A new approach is proposed to detect and track the moving object. The affine motion model and the non-parameter distribution model are utilized to represent the object firstly. Then the motion region of the object is detected by background difference while Kalman filter estimating its affine motion in next frame. Center association and mean shift are adopted to obtain the observation values. Finally, the distance variance and scale variance between the estimated and detected regions are used to fuse the observation values to acquire the measurement value. To correct fusion errors, the observable edges are employed. Experimental results show that the new method can successfully track the object under such case as merging, splitting, scale variation and scene noise.
Calibration method with separation patterns of a single-camera

Such as in LAMOST (Large Sky Area Multi-Object Fiber Spectroscopy Telescope), many photometric measurement systems need to reach sub-pixel accuracy with area scan CCD camera. The separation patterns are used to calibrate a single-camera with high precision. Several separation calibration patterns with small size are put on the position of object plane of the camera. Each pattern has some spot array with high precision. The position of each reference point on the image plane of the camera is calculated. The coordinates of the reference points on the calibration patterns are used to calibrate the camera. The curved-surface fitting method is applied to fit the perspective relationship between the object plane and the image plane. The integer pattern with large dimension can be replaced by the several small differential patterns in the situation of large field. The difficulty to manufacture the large pattern is avoided. The experimental results show that the mean value of residual error is less than 0.002mm with the separation calibration method.
Stellar dynamical evidence for dark halos in elliptical galaxies : the case of NGC 4472, IC 4296, and NGC 7144

Extended and accurate major axis kinematical profiles and line strength gradients of the elliptical galaxies NGC 4472, IC 4296, and NGC 7144 have been measured using the ESO NTT in the EMMI long-slit spectroscopic mode. For NGC 7144 the stellar rotation curve and velocity dispersion profile extend to 75″ from the center (where the surface brightness is 24.4 B-mag arcsec −2 , 2.8 mag below the sky), with typical error bars of 10 km s −1 . The flat or slowly increasing velocity dispersion profiles of these galaxies indicate that massive dark halos might dominate their dynamics
Subspace iteration accelrated by using Chebyshev polynomials for eigenvalue problems with symmetric matrices

Bathe's algorithm of subspace iteration for the solution of the eigenvalue problem with symmetric matrices is improved by incorporating an acceleration technique using Chebyshev polynomials. This method of acceleration is particularly effective for this kind of iteration. The rate of convergence of the iteration scheme presented is considerably improved when compared with the original one, and satisfactory rates of convergence can be obtained for a wider range of eigenvalues.
Geometry design of globoidal cams with generalized meshing turret-rollers

This paper derives the generalized surface equation for cylindrical, conical, and hyperbolic meshing turret-rollers. Based on the generalized equation of meshing turret-rollers, generalized mathematical expressions of surface geometry for globoidal cams with cylindrical, conical, and hyperbolic meshing turret-rollers are derived using theory of conjugate surfaces, differential geometry, and coordinate transformation. A design example is presented for demonstrating procedures of surface generating of the globoidal cam. The result of this work is necessary for the computer-aided design and manufacturing of roller gear cams for industrial applications.
Surface Trap for Cs atoms based on Evanescent-Wave Cooling

We demonstrate a gravito-optical surface trap for Cs atoms which exploits cooling in an evanescent light wave. About 10{sup 5} atoms were cooled down to 3{mu}K and formed a sample with a mean height of {approximately}20 {mu}m above the surface of a dielectric prism. The trap does not use a magnetic field and leads to very small atomic level perturbations. The excited-state population of the stored atoms is {approximately}1.5{times}10{sup {minus}6} and collisional losses are strongly suppressed. {copyright} {ital 1997} {ital The American Physical Society}
Inversion techniques and combinatorial identities: balanced hypergeometric series

Following the earlier works on Inversion Techniques and Combinatorial Identities, the duplicate form of the Gould-Hsu (1973) inversion theorem is constructed. As applications, several terminating balanced hypergeometric formulas are demonstrated, including those due to Andrews (1995), which have been the primary stimulation to the present research. Encouraged by the recent work of Stanton (1998), we establish two higher hypergeometric evaluations with three additional parameters, which specialize further to over two hundreds hypergeometric identities.
Statistical Inference in Instrumental Variables Regression with I(1) Processes

This paper studies the asymptotic properties of instrumental variable (IV) estimates of multivariate cointegrating regressions and allows for deterministic and stochastic regressors as well as quite general deterministic processes in the data-generating mechanism. It is found that IV regressions are consistent even when the instruments are stochastically independent of the regressors. This phenomenon, which contrasts with traditional theory for stationary time series, is a beneficial artifact of spurious regression theory whereby stochastic trends in the instruments ensure their relevance asymptotically. Problems of inference are also addressed and some promising new theoretical results are reported. These involve a class of Wald tests which are modified by semiparametric corrections for serial correlation and for endogeneity. The resulting test statistics which we term fully-modified Wald tests have limiting X2 distributions, thereby removing the obstacles to inference in cointegrated systems that were presented by the nuisance parameter dependencies in earlier work. Some simulation results are reported which seek to explore the sampling behaviour of our suggested procedures. These simulations compare our fully modified (semiparametric) methods with the parametric error-correction methodology that has been extensively used in recent empirical research and with conventional least squares regression. Both the fully-modified and errorcorrection methods work well in finite samples and the sampling performance of each procedure confirms the relevance of asymptotic distribution theory, as distinct from super-consistency results, in discriminating between statistical methods.
Guiding a terahertz quantum cascade laser into a flexible silver-coated waveguide

We report on a promising experimental approach to efficiently couple quantum cascade laser (QCL) sources fabricated in either surface emitting micro-ring resonator or standard edge emitting geometry with terahertz (THz) hollow waveguides. We show that the THz beam of a QCL can be guided into flexible silver-coated polycarbonate waveguides having length in the range 4–12 cm with coupling efficiencies >80%. The dominant optical modes propagating through the waveguides can be selected by varying the polarization of the incoming QCL beam, the coupling geometries, and/or bending the hollow waveguide. Either the lowest loss TE11 or the TE01 mode can be selected and guided through the waveguide with propagation losses in the range 2.1–4.4 dB/m and bending losses lower than 1.2 dB.
Coupling between a dipole antenna and an infinite cable over an ideal ground plane

A formulation is given for the fields radiated by an electric or magnetic dipole of arbitrary orientation in the presence of a cable suspended above a flat and perfectly conducting ground. The cable can be a solid conductor, a leaky coaxial cable, a CATV cable, or a surface-wave transmission line. Illustrative numerical results for both the far-field radiation pattern and excitation of the modal currents on the cable are given for the case of a vertical electric dipole source. Among other things, we find that the resultant radiation or far fields are not markedly influenced by the presence of the cable unless the dipole source is very near the cable. However, there is a significant cross-polarized component produced by the presence of cable that could have important consequences in producing bearing errors in low frequency beacon navigation systems.
Efficiency IV Estimation for Autoregressive Models with Conditional Heterogeneity

This paper analyzes autoregressive time series models where the errors are assumed to be martingale difference sequences that satisfy an additional symmetry condition on their fourth order moments. Under these conditions Quasi Maximum Likelihood estimators of the autoregressive parameters are no longer efficient in the GMM sense. The main result of the paper is the construction of efficient semiparametric instrumental variables estimators for the autoregressive parameters. The optimal instruments are linear functions of the innovation sequence. It is shown that a frequency domain approximation of the optimal instruments leads to an estimator which only depends on the data periodogram and an unknown linear filter. Semiparametric methods to estimate the optimal filter are proposed. The procedure is equivalent to GMM estimators where lagged observations are used as instruments. Due to the additional symmetry assumption on the fourth moments the number of instruments is allowed to grow at the same rate as the sample. No lag truncation parameters are needed to implement the estimator which makes it particularly appealing from an applied point of view.
Lattice thermal conductivity in a silicon nanowire with square cross section

We present a theoretical model of lattice thermal conductivity in a silicon nanowire with square cross section. This model takes into account the modifications of the acoustic phonon dispersion and boundary scattering on the side walls. A good approximation of exact lattice thermal conductivity is obtained by the yielded precise phonon dispersion relations under the xyz algorithm of Nishiguchi et al. [J. Phys.: Condens. Matter 9, 5751 (1997)] and the inclusion of three scattering events on the side walls from the phonon Boltzmann transport equation. Comparison is also made with the thermal conductivity of a cylindrical nanowire.
Development of microchannel plate (MCP) x-ray optics

In the present paper, we describe X-ray images obtained using planar, square pore MCPs in `point-to-point' focusing mode. Angular resolution of 5 arcminutes fwhm has now been measured for full-field illumination of a hydrogen-reduced Galileo MCP (29 mm active diameter; approximately 44,000 active channels). Secondly, we report some preliminary metrology of square-pore microchannel plates using atomic force, scanning electron and optical microscopies. Finally, we extend our study of spherically-slumped, round-pore Philips MCPs operated as X-ray `beam expanders'.
Linear Combinations of Multiple Diagnostic Markers

Abstract The receiver operating characteristic (ROC) curve is a simple and meaningful measure to assess the usefulness of diagnostic markers. To use the information carried by multiple markers, we note that Fisher's linear discriminant function provides a linear combination of markers to maximize the sensitivity over the entire specificity range uniformly under the multivariate normal distribution model with proportional covariance matrices. With no restriction on covariance matrices, we also provide a solution of the best linear combination of markers in the sense that the area under the ROC curve of this combination is maximized among all possible linear combinations. We illustrate both situations discussed in the article with a cancer clinical trial data.
HAPSTR1 localizes HUWE1 to the nucleus to limit stress signaling pathways

HUWE1 is a large, enigmatic HECT domain ubiquitin ligase implicated in the regulation of diverse pathways including DNA repair, apoptosis, and differentiation. How HUWE1 engages its structurally diverse substrates and how HUWE1 activity is regulated are unknown. Using unbiased quantitative proteomics, we identify C16orf72/HAPSTR1 as a dedicated HUWE1 substrate despite HUWE1 targeting substrates in a largely cell type-specific manner. The established physical and genetic interactions between HUWE1 and C16orf72/HAPSTR1 suggest that HAPSTR1 positively regulates HUWE1 function. Here, we show that HAPSTR1 is both a HUWE1 substrate and is required for HUWE1 nuclear localization to facilitate HUWE1 nuclear substrate targeting. HUWE1 or HAPSTR1 loss of function triggers a broad transcriptional stress response. We show that nuclear HUWE1 is both critical for modulating stress signaling pathways, which include p53 and NF-κB-mediated signaling and required for cell proliferation. Combined, our results define a role for HAPSTR1 in gating critical nuclear HUWE1 functions.
Label-Free Mammalian Cell Tracking Enhanced by Precomputed Velocity Fields

Label-free cell imaging, where the cell is not “labeled” or modified by fluorescent chemicals, is an important research area in the field of biology. It avoids altering the cell’s properties which typically happens in the process of chemical labeling. However, without the contrast enhancement from the label, the analysis of label-free imaging is more challenging than label-based imaging. In addition, it provides few human interpretable features, and thus needs machine learning approaches to help with the identification and tracking of specific cells. We are interested in label-free phase contrast imaging to track cells flowing in a cell sorting device where images are acquired at 500 frames/s. Existing Multiple Object Tracking (MOT) methods face four major challenges when used for tracking cells in a microfluidic sorting device: (i) most of the cells have large displacements between frames without any overlap; (ii) it is difficult to distinguish between cells as they are visually similar to each other; (iii) the velocities of cells vary with the location in the device; (iv) the appearance of cells may change as they move in and out of the focal plane of the imaging sensor that observes the isolation process. In this paper, we introduce a method for tracking cells in a predefined flow in the sorting device via phase contrast microscopy. Our proposed method is based on DeepSORT and YOLOv4 and exploits prior knowledge of a cell’s velocity to assist tracking. We modify the Kalman filter in DeepSORT to accommodate a non-constant velocity motion model and integrate a representative velocity field obtained from fluid dynamics into the Kalman filter. The experimental results show that our proposed method outperforms several MOT methods for tracking cells in the sorting device.
Staphylococcus aureus prophages are gatekeepers of lipid utilization to control membrane plasticity, bacterial fitness, and antibiotic adaptation

Lipids are essential components of bacterial membranes and phages are quasi-ubiquitous in bacteria. In the human pathogen Staphylococcus aureus, two common prophages ϕ13 and ϕ11. 1 are preferentially integrated in lipase genes, and act as regulatory switches of respectively Geh, a triglyceride lipase, and Hlb, a sphingomyelinase. The factors driving selection for this prophage conservation in lipase genes and the impact on S. aureus fitness are not well understood. We report that prophage status of both ϕ13 and ϕ11. 1 affect membrane phospholipid composition and bacterial growth in serum. They vary the extent to which toxic C18:2, released from Geh activity on triglycerides, are incorporated in bacterial membranes. Hlb and Geh lipases lead respectively to palmitic acid C16 and linoleic acid C18:2, which compete for binding to fatty acid kinase subunit FakB1. When both lipases are active, interference from C16 decreases C18:2 incorporation via FakB1 and reduces fatty acid synthesis (FASII)-mediated elongation. In the presence of FASII inhibitor AFN-1252, S. aureus relies on exogenous fatty acids, and adapts faster when Hlb is intact (ϕ13 absent), but slower when Hlb is inhibited. Faster adaptation correlates with less incorporation of C18:2. These findings contribute to explaining the selective advantage of Hlb-conversion by ϕ13 as a means of increasing membrane plasticity and S. aureus adaptation to environmental lipids. They also reveal an effect of ϕ13 status on anti-FASII adaptation. Prophage status and host-specific lipid environments may be important for accurate prediction of S. aureus infection risk and efficacy of new therapeutics. Importance Staphylococcus aureus is a major cause of untreatable human bacterial infections and its lipases are crucial for virulence and immune response escape. Prophages inserted in these lipase-encoding genes able to reversibly switch their activities are common in S. aureus, but the selective benefits of their maintenance is little understood. We demonstrate that two prophages, inserted in triglyceride and sphingomyelin lipase genes, interactively modulate fatty acid incorporation into bacterial membranes. The presence or absence of these prophages determine how S. aureus adapts to lipid environments, by affecting membrane plasticity, bacterial fitness, and adaptation to an antibiotic inhibiting fatty acid synthesis. Our findings highlight the importance of assessing S. aureus prophages and host lipid environments when evaluating infection risk and therapy efficacy.