Miracle-dz/UniFAR-FTUs huggingface dataset:
Point matching via affine region expansion

In this work, we present a novel scheme for accurate affine transformation estimation that enables locating large amount of point matches with high geometric precision and low rate of false matches. We show that this is achievable in low computational demand. Point matching is one of the most fundamental tasks in computer vision. It is being extensively used in popular applications like object detection, object tracking, structure from motion and more. Recent publications have shown that considering the affine transformation model of local regions, is extremely beneficial for the purpose of point matching. Although it is not arguable that considering the full affine transformation is extremely beneficial, the use of it in practice is limited as a result of the computational demand. We propose a region expansion method, based on accurate estimation of the affine transformation, which enables prediction of locations beyond the initial local regions. By reducing the amount of false matches considerably, it reduces the need for computationally demanding post processes.
Precoding Design for the MIMO-RoC Downlink

MIMO Radio-over-Copper (MIMO-RoC) is a transport system for indoor coverage that leverages the pre-existing building’s copper cabling infrastructure. In MIMO-RoC, the overall channel from the Base Band Units (BBU) to the end-user is the cascade of a MIMO-radio over a MIMO-cable channel and the analog fronthaul together with a wireless channel enables the transport to the mobile users. The entire system poses two main challenges: i) design low-complexity and flexible allocation strategies between wired and wireless resources; ii) design interference cancellation techniques tailored to the mutually coupled wired-wireless interference. While the former has been extensively investigated, the optimal design of precoding algorithms for the MIMO-RoC downlink is still an open issue and is covered here. In particular, in this paper, the Linear Successive Allocation (LISA) algorithm has been revised and adapted to the MIMO amplify-and-forward (AF) structure of MIMO-RoC. Numerical results validate the proposed method considering a realistic radio environment with 100m copper cable remotization.
Toward Creative 3D Modeling: an Architects' Sketches Study

This paper describes our methodology in providing designers with a new advanced 3D modeling Human-Computer Interaction. The main project - called GINA, a French acronym for Interactive and Natural Geometry - expect to introduce new intuitive and creative 3D modeling tools, relying on 2D perspective drawing reconstruction. We present here the user study we conducted and the implications of this study on the interface of GINA.
Authorship Clustering using Multi-headed Recurrent Neural Networks

A recurrent neural network that has been trained to separately model the language of several documents by unknown authors is used to measure similarity between the documents. It is able to find clues of common authorship even when the documents are very short and about disparate topics. While it is easy to make statistically significant predictions regarding authorship, it is difficult to group documents into definite clusters with high accuracy.
Baryons and domain walls in an N=1 superconformal gauge theory

Coincident D3-branes placed at a conical singularity are related to string theory on AdS{sub 5}{times}X{sub 5}, for a suitable five-dimensional Einstein manifold X{sub 5}. For the example of the conifold, which leads to X{sub 5}=T{sup 1,1}=[SU(2){times}SU(2)]/U(1), the infrared limit of the theory on {ital N} D3-branes was constructed recently. This is an N=1 supersymmetric SU(N){times}SU(N) gauge theory coupled to four bifundamental chiral superfields and supplemented by a quartic superpotential which becomes marginal in the infrared. In this paper we consider D3-branes wrapped over the 3-cycles of T{sup 1,1} and identify them with baryon-like chiral operators built out of products of {ital N} chiral superfields. The supergravity calculation of the dimensions of such operators agrees with field theory. We also study the D5-brane wrapped over a 2-cycle of T{sup 1,1}, which acts as a domain wall in AdS{sub 5}. We argue that upon crossing it the gauge group changes to SU(N){times}SU(N+1). This suggests a construction of supergravity duals of N=1 supersymmetric SU(N{sub 1}){times}SU(N{sub 2}) gauge theories. {copyright} {ital 1998} {ital The American Physical Society}
The Prostate 49 : 30 ^ 37 ( 2001 ) GSTA 1 Expression inNormal , Preneoplastic , and NeoplasticHumanProstateTissue

J. Kellogg Parsons, Chad P. Nelson, Wesley R. Gage, William G. Nelson, Thomas W. Kensler, and Angelo M. De Marzo* TheDepartmentofUrology,The JohnsHopkinsMedical Institutions, Baltimore,Maryland The JohnsHopkins Bloomberg Schoolof PublicHealth,Baltimore,Maryland TheDepartmentofOncology,The JohnsHopkinsMedical Institutions, Baltimore,Maryland TheDepartmentof Pathology,The JohnsHopkinsMedical Institutions,Baltimore,Maryland
A Novel Complex-Modulation Based Space-Time Spreading Scheme with More Than Two Transmit Antennas for MC-DS-CDMA Systems

–Space-time spreading (STS) is a promising scheme combining the ubiquitously employed code division multiple access (CDMA) with the emerging space-time block coding (STBC) technique. Almost all research results reported so far mainly focus on the STS schemes based on the full-rate STBC, which use either only two transmit antennas or real-modulations. However, the complex-modulation based STS systems with more than two transmit antennas, despite their much better spectrum efficiency and error performance, hardly receive any attention. To remedy this deficiency, in this paper we propose a complexmodulation based STS scheme with more than two transmit antennas for MC-DS-CDMA systems. We also develop the performance analysis frameworks to evaluate the bit-error-rate (BER) and throughput of the proposed scheme and other representative schemes. The simulation results obtained verify the analytical findings. Both analytical and simulation results show that our proposed scheme can achieve much lower BER and much higher throughput as compared to their counterparts using realmodulation based STS systems. Keyword––Space-Time Spreading (STS), Multicarrier-DirectSequence-CDMA (MC-DS-CDMA), Bit-error-rate (BER), Throughput analysis, Rayleigh fading channel.
Microlocal Techniques for Semiclassical Problems in Geometric Quantization

1. Introduction Recently the microlocal analysis of Toeplitz operators developed by Boutet de Monvel, Sjj ostrand, and Guillemin 10], 9], has been used to obtain various semiclas-sical results for geometrically quantized compact KK ahler manifolds 4], 6], 7]. In this paper we will give an expository account of these methods and results. Part of our approach will be to work out the analogous theory for quantization of C n. The theory of 9] does not apply directly to this case, because of the non-compactness, but the microlocal structure is the same. 1 And the explicitness with which one can write things down in this case makes the structure of the arguments, and in particular the prominence of stationary phase, more transparent. The development of this theory for C n will also yield an improvement of a result of Coburn 11], a theorem connecting the Poisson bracket of two functions two the semiclassical limit of the commutator of the associated operators. The class of functions for which this was proven in 11] constists of trigonometric polynomials plus functions with compact support. We are able to enlarge this to the class of bounded functions with bounded derivatives (see Section 4).
Time delay and direction of arrival estimation of multiple users in slow fading channels

In this paper, the spatial diversity is used to handle the problem of estimating the multipath propagation parameters of multiple users that interfere both in time and frequency. This issue is investigated in the case of slow fading channels. By assuming that the channel is stationary over a set of time slots, we recover each user channel impulse response by use of pilot symbols. A subspace-based algorithm is then separately applied on each user restored channel to sequentially recover the corresponding paths time delays and directions of arrival. For this, one-dimensional spectra optimizations are used. A kind of paths isolation guarantees the pairing between the estimated delays and angles.
A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System

Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical downscaling of global ensemble perturbations. One month consecutive tests are implemented to evaluate the performance of both methods in the operational REPS environment. The perturbation characteristics are analyzed and ensemble forecast verifications are conducted; furthermore, a TC case is investigated. The main conclusions are as follows: the ETKF perturbations contain more power at small scales while the ones derived from downscaling contain more power at large scales, and the relative difference of the two types of perturbations on scales become smaller with forecast lead time. The growth of downscaling perturbations is more remarkable, and the downscaling perturbations have larger magnitude than ETKF perturbations at all forecast lead times. However, the ETKF perturbation variance can represent the forecast error variance better than downscaling. Ensemble forecast verification shows slightly higher skill of downscaling ensemble over ETKF ensemble. A TC case study indicates that the overall performance of the two systems are quite similar despite the slightly smaller error of DOWN ensemble than ETKF ensemble at long range forecast lead times.
Adipose-derived mesenchymal stem cells employed exosomes to attenuate AKI-CKD transition through tubular epithelial cell dependent Sox9 activation

Acute kidney injury (AKI) predisposes patients to an increased risk into progressive chronic kidney disease (CKD), however effective treatments are still elusive. This study aimed to investigate the therapeutic efficacy of human adipose-derived MSCs (hAD-MSCs) in the prevention of AKI-CKD transition, and illuminate the role of Sox9, a vital transcription factor in the development of kidney, in this process. C57BL/6 mice were subjected to unilateral renal ischemia/reperfusion (I/R) with or without hAD-MSC treatment. We found that hAD-MSC treatment upregulated the expression of tubular Sox9, promoted tubular regeneration, attenuated AKI, and mitigated subsequent renal fibrosis. However, these beneficial effects were abolished by a drug inhibiting the release of exosomes from hAD-MSCs. Similarly, Sox9 inhibitors reversed these protective effects. Further, we verified that hAD-MSCs activated tubular Sox9 and prevented TGF-β1-induced transformation of TECs into pro-fibrotic phenotype through exosome shuttling in vitro, but the cells did not inhibit TGF-β1-induced transition of fibroblasts into myofibroblasts. Inhibiting the release of exosomes from hAD-MSCs or the expression of Sox9 in TECs reversed these antifibrotic effects. In conclusion, hAD-MSCs employed exosomes to mitigate AKI-CKD transition through tubular epithelial cell dependent activation of Sox9.
Future Internet in Taiwan: Design and Research Activities over TWAREN Network

Internet has played an important part in the success of information technologies. With growing and changing demands, there are many limitations faced by current Internet. A number of network test beds are created for solving a set of specific problems in Internet. Traditionally, these test beds are lacking of large scale network and flexibility. Therefore, it is necessary to design and implement a test bed which can support wide range of experiments and has an ability of programmable network. Besides, there has been a big change enabled by cloud computing in recent years. Everything is virtualized, including networking. We focus on integrating management functions in virtual network. In this paper, we design and create a Future Internet test bed in Taiwan over TWAREN Research Network. This test bed evolves into an environment for programmable network and cloud computing. This paper also presents several finished and ongoing experiments on the test bed for multiple aspects including topology discovery, multimedia streaming, and virtual network integration. We will continue to extend our test bed and propose innovative applications for the next generation Internet.
Temporal expression patterns of 39 Brachyury‐downstream genes associated with notochord formation in the Ciona intestinalis embryo

Expression of the Brachyury (Ci‐Bra) gene of the ascidian Ciona intestinalis is initiated at the 64‐cell stage. Gene expression is restricted to notochord precursor cells, and Ci‐Bra plays a key role in notochord differentiation. In a previous study, nearly 50 cDNA clones for potential Ci‐Bra‐downstream genes that are expressed in notochord cells were isolated. The present determination, by whole‐mount in situ hybridization, of the temporal expression patterns of 19 notochord‐specific and 20 notochord‐predominant genes demonstrated that the timings of initiation of the expression of various genes was not identical. The expression of several genes was initiated as early as the gastrula stage. However, the expression of most of the notochord‐specific genes commenced at the neural plate stage. Partial nucleotide sequence data of these clones suggest that genes expressed earlier encode potential transcriptional factors and/or nuclear proteins, while those expressed later encode proteins implicated in cell adhesion, signal transduction, regulation of the cytoskeleton, and components of the extracellular matrix. These gene activities may be associated with changes in cell shape and adhesion during the intercalation and extension of the notochord cells.
A Method of Measuring Term Representativeness - Baseline Method Using Co-occurrence Distribution

This paper introduces a scheme, which we call the baseline method, to define a measure of term representativeness and measures defined by using the scheme. The representativeness of a term is measured by a normalized characteristic value defined for a set of all documents that contain the term. Normalization is done by comparing the original characteristic value with the characteristic value defined for a randomly chosen document set of the same size. The latter value is estimated by a baseline function obtained by random sampling and logarithmic linear approximation. We found that the distance between the word distribution in a document set and the word distribution in a whole corpus is an effective characteristic value to use for the baseline method. Measures defined by the baseline method have several advantages including that they can be used to compare the representativeness of two terms with very different frequencies, and that they have well-defined threshold values of being representative. In addition, the baseline function for a corpus is robust against differences in corpora; that is, it can be used for normalization in a different corpus that has a different size or is in a different domain.
Analysis–adjustment–synthesis networks

This paper presents a novel neural network architecture, analysis–adjustment–synthesis network (AASN), and tests its efficiency and accuracy in modelling non-linear function and classification. The AASN is a composite of three sub-networks: analysis sub-network; adjustment sub-network; and synthesis sub-network. The analysis sub-network is a one-layered network that spreads the input values into a layer of ‘spread input neurons’. This synthesis sub-network is a one-layered network that spreads the output values back into a layer of ‘spread output neurons’. The adjustment sub-network, between the analysis sub-network and the synthesis sub-network, is a standard multi-layered network that operates as the learning mechanism. After training the adjustment sub-network in recalling phase, the synthesis sub-network receives the output values of spread output neurons and synthesizes them into output values with a weighted-average computation. The weights in the weighted-average computation are deduced from the method of Lagrange multipliers. The approach is tested using four function mapping problems and one classification problem. The results show that combining the analysis sub-network and the synthesis sub-network with a multi-layered network can significantly improve a network's efficiency and accuracy.
Scene Text Detection via Edge Cue and Multi-features

Inspired by the fact that edge is an important cue to distinguish texts from background, we propose a novel scene text detection method via edge cue and multiple features, which has two main parts, i.e. candidate character region (CCR) extraction and region classification. For CCR extraction, the edges are first extracted from the input image, which are then broken and merged based on color features to form the final edge image. For each edge connected component, a number of image patches are extracted by translating and scaling its boundary rectangle to generate the CCRs. For region classification, the character regions are extracted from the CCRs by using a region classification technique, which extracts both the hand-designed low-level features and deep convolution neural network based high-level features of the regions for classification. And then the character regions are merged to form the candidate text regions, based on which the final text region are detected by using the region classification technique. The proposed method is evaluated on two latest ICDAR benchmark datasets and the experimental results demonstrate that the proposed method outperforms the state-of-the-art approaches of scene text detection.
Region-based brain selection and classification on pet images for Alzheimer's disease computer aided diagnosis

Positron Emission Tomography (PET) is a 3-D functional imaging modality which help physicians to diagnose neurodegenerative diseases like Alzheimer's Disease (AD). Computer-aided detection and diagnosis, based on medical imaging techniques is of importance for a quantitative evaluation. A novel method of ranking the effectiveness of brain regions to separate AD from healthy brains images is presented. Brain images are first mapped into 116 anatomical regions of interest. The first four moments and the entropy of the histograms of these regions are computed. Receiver Operating Characteristics curves are then used to rank the ability of regions to separate PET brain images. Twenty one selected regions are input to both Support Vector Machine and Random Forest classifiers and evaluation is done on 142 brain PET images. Classification results are better than those obtained when using the whole 116 initial regions or when inputting the whole brain voxels. In addition, an important computational time reduction was obtained.
Evaluation of the Biostar Chlamydia OIA Assay with Specimens from Women Attending a Sexually Transmitted Disease Clinic

ABSTRACT Chlamydia trachomatis infections are the most prevalent sexually transmitted diseases (STDs) in the United States. In acute-care settings such as clinics and emergency rooms, a desirable chlamydia screening assay should exhibit good sensitivity and good specificity and should provide test results while the patient is still present. The Biostar Chlamydia OIA (Biostar, Inc., Boulder, Colo.) is an optical immunoassay (OIA) that provides test results in less than 30 min and that uses a test format that allows office-based testing. This assay is performed entirely at room temperature without the need for rotators or other specialized equipment. The goal of this study was to compare the performance of the Biostar Chlamydia OIA for the detection of C. trachomatis with the performance of cell culture, direct fluorescent-antibody (DFA) assay (Syva MicroTrak; Syva Co., Palo Alto, Calif.), and PCR (Roche Amplicor Chlamydia trachomatis; Roche, Branchburg, N.J.) for the detection ofC. trachomatis infections in women attending an urban STD clinic. For calculations of relative test performance (sensitivity, specificity, and positive and negative predictive values), patient specimens that yielded positive results by two or more of the four assays (cell culture, DFA assay, PCR, and OIA) were classified as “true infections. ” By these criteria, 42 of 306 total specimens were classified as positive for C. trachomatis (positive prevalence, 13.7%), 11 (3.6%; 10 by PCR and 1 by DFA assay) were positive by a single assay, and 253 (82.7%) were negative by all four tests. All culture-positive specimens were also positive by at least one other assay. Among the culture-negative specimens, 14 (5%) specimens were positive by two of the three non-culture-based assays used. By using the criterion that positivity by at least two of the tests indicated a true infection, the relative sensitivities were as follows: culture and PCR, 92.9% each; Biostar Chlamydia OIA, 73.8%; and DFA assay, 59.5%.
Mobility Classifier Using Radio Beacons: A Robust Approach to Different GSM and Wi-Fi Densities

We propose a pervasive mobility classification method using radio beacons such as Global System for Mobile communications (GSM) and Wi-Fi traces. The model adopts different classifiers depending on the densities of radio beacons in different environments. We demonstrate how coarser-grained mobility states such as being stationary, walking, or driving can be satisfactorily inferred from our method using a data set of i) five hours gathered from one user in five differently-characterized areas and ii) sixteen hours gathered from sixteen individuals. Our model works across environments having different radio densities by employing the GSM-based classifier when Wi-Fi densities are too sparse with 81.54%. We also present that our model trained with the small data set gathered from one user is effectively applied to sixteen other individuals with 78% accuracy, which suggests the scalability of our model to new users.
Role of Multibody Dynamics Based Simulation in Human , Robotic and Hybrid Locomotion Benchmarking *

— Multibody dynamics has provided methods for simulating vehicles and machines since the seventies, thus helping in the design of such systems as their behavior can be anticipated before having a physical prototype. Those methods can also be applied today to the study of locomotion, but different challenges arise depending on whether the system is human, robotic or hybrid. This work attempts to point out the challenges that must be faced in each case to carry out a simulation, and the advantages that can be obtained by exchanging results for the three types of systems.