Miracle-dz/UniFAR-FTUs huggingface dataset:
Uniqueness of quantum states compatible with given measurement results

We discuss the uniqueness of quantum states compatible with given measurement results for a set of observables. For a given pure state, we consider two different types of uniqueness: (1) no other pure state is compatible with the same measurement results and (2) no other state, pure or mixed, is compatible with the same measurement results. For case (1), it was known that for a $d$-dimensional Hilbert space, there exists a set of $4d\ensuremath{-}5$ observables that uniquely determines any pure state. We show that for case (2), $5d\ensuremath{-}7$ observables suffice to uniquely determine any pure state. Thus, there is a gap between the results for (1) and (2), and we give some examples to illustrate this. Unique determination of a pure state by its reduced density matrices (RDMs), a special case of determination by observables, is also discussed. We improve the best-known bound on local dimensions in which almost all pure states are uniquely determined by their RDMs for case (2). We further discuss circumstances where (1) can imply (2). We use convexity of the numerical range of operators to show that when only two observables are measured, (1) always implies (2). More generally, if there is a compact group of symmetries of the state space which has the span of the observables measured as the set of fixed points, then (1) implies (2). We analyze the possible dimensions for the span of such observables. Our results extend naturally to the case of low-rank quantum states.
Finite sample approximation results for principal component analysis: a matrix perturbation approach

Principal component analysis (PCA) is a standard tool for dimensional reduction of a set of $n$ observations (samples), each with $p$ variables. In this paper, using a matrix perturbation approach, we study the nonasymptotic relation between the eigenvalues and eigenvectors of PCA computed on a finite sample of size $n$, and those of the limiting population PCA as $n\to\infty$. As in machine learning, we present a finite sample theorem which holds with high probability for the closeness between the leading eigenvalue and eigenvector of sample PCA and population PCA under a spiked covariance model. In addition, we also consider the relation between finite sample PCA and the asymptotic results in the joint limit $p,n\to\infty$, with $p/n=c$. We present a matrix perturbation view of the "phase transition phenomenon," and a simple linear-algebra based derivation of the eigenvalue and eigenvector overlap in this asymptotic limit. Moreover, our analysis also applies for finite $p,n$ where we show that although there is no sharp phase transition as in the infinite case, either as a function of noise level or as a function of sample size $n$, the eigenvector of sample PCA may exhibit a sharp "loss of tracking," suddenly losing its relation to the (true) eigenvector of the population PCA matrix. This occurs due to a crossover between the eigenvalue due to the signal and the largest eigenvalue due to noise, whose eigenvector points in a random direction.
Spatial relations of dorsal anastomoses and lesion border after middle cerebral artery occlusion.

Occlusion of the middle cerebral artery invariably results in infarction of tissue in stroke-prone spontaneously hypertensive rats (SHRSP). To determine if the lesion border extends beyond the territory of the occluded middle cerebral artery or if the lesion enlarges with time after the occlusion, spatial relations of the lesion and the primary anastomosing collateral branches were investigated. Measurements were made 1 day (n = 8) or 21 days (n = 8) after occlusion in 5-8-week-old SHRSP brains marked by triphenyltetrazolium chloride (TTC) or tissue atrophy. After 1 day of occlusion, the border between TTC-marked and -unmarked tissue was parallel to, and without spatial displacement from, the medial border of infarcted tissue measured 21 days after the occlusion. Thus, the TTC border accurately localizes the medial border of ischemic tissue that progresses to atrophy. The lesion border was 1.16 +/- 0.04 mm downstream from the anastomoses, and the mean distance was not significantly different in frontal, parietal, or rostral occipital regions or between the 2 groups of rats. Thus, a small but significant amount of tissue between the anastomoses and the lesion border was protected against infarction after middle cerebral artery occlusion in SHRSP. After 21 days of occlusion, the dorsal anastomoses were enlarged, bilaterally symmetric in position but not size, and without displacement from the anastomoses in 1-Day rats. Large-diameter anastomoses were further from the lesion than small-diameter anastomoses in both groups of rats, thus indicating that protection is greater near large anastomoses than near small ones. (ABSTRACT TRUNCATED AT 250 WORDS)
Effects of postnatal environmental tobacco smoke on cardio-respiratory control in newborn lambs

While prenatal environmental tobacco smoke (ETS) exposure has been shown to be a major cause of sudden infant death syndrome, the effects of postnatal ETS exposure have been less studied. The objective of this study is to explore the effects of 15-days postnatal exposure to 20 cigarettes/day on heart rate variability (HRV), respiratory rate variability (RRV) and cardiorespiratory interrelations in newborn lambs. On postnatal day 16, six-hours polysomnographic recording was obtained from six control lambs exposed to room air (group C0) and six lambs exposed to 20 cigarettes/day (group C20) for the first 15 days of life. ECG and respiratory movements (RSP) were continuously monitored. Several analyses were performed on these signals, including heart rate variability analyses (on the RR intervals extracted from the ECG), respiratory rate variability analyses (on different time series extracted from the breathing signal) and cardiorespiratory interrelations analyses (on both the RR interval and the breathing signal). The results suggest that ETS exposure for the first 15 postnatal days leads to slight alterations of cardiorespiratory control, which predominate on respiration.
Curvelet transform-based features extraction for fingerprint identification

The performance of the fingerprint identification process highly depends on its extractor of fingerprint features. So, to reduce the dimensionality of the fingerprint image and improve the identification rate, a fingerprint features extraction method based on Curvelet transform is proposed and presented in this paper. Thus, our paper focuses on presenting of our Curvelet-based fingerprint features extraction method. This method consists of two steps: decompose the fingerprint into set of sub-bands by the Curvelet transform and automatic extraction of the most discriminative statistical features of these sub-bands. An extensive experimental evaluation shows that the proposed method is effective and encouraging.
Mutation of the Melastatin-Related Cation Channel, TRPM3, Underlies Inherited Cataract and Glaucoma

Inherited forms of cataract are a clinically important and genetically heterogeneous cause of visual impairment that usually present at an early age with or without systemic and/or other ocular abnormalities. Here we have identified a new locus for inherited cataract and high-tension glaucoma with variable anterior segment defects, and characterized an underlying mutation in the gene coding for transient receptor potential cation channel, subfamily M, member-3 (TRPM3, melastatin-2). Genome-wide linkage analysis mapped the ocular disease locus to the pericentric region of human chromosome 9. Whole exome and custom-target next-generation sequencing detected a heterozygous A-to-G transition in exon-3 of TRPM3 that co-segregated with disease. As a consequence of alternative splicing this missense mutation was predicted to result in the substitution of isoleucine-to-methionine at codon 65 (c.195A>G; p.I65 M) of TRPM3 transcript variant 9, and at codon 8 (c.24A>G; p.I8 M) of a novel TRPM3 transcript variant expressed in human lens. In both transcript variants the I-to-M substitution was predicted in silico to exert damaging effects on protein function. Furthermore, transient expression studies of a recombinant TRPM3-GFP reporter product predicted that the I-to-M substitution introduced an alternative translation start-site located 89 codons upstream from the native initiator methionine found in eight other TRPM3 transcript variants (1–8). Collectively, these studies have provided the first evidence that TRPM3 is associated with inherited ocular disease in humans, and further provide support for the important role of this cation channel in normal eye development.
Third space openings at a two-way immersion elementary school in North Carolina: Lessons from parent language classes

ABSTRACT Two-way immersion schools are growing in popularity throughout the United States. An emerging issue is to what extent these schools are able to connect with parents from multiple communities. This article describes an effort to connect parents with the school and one another through parent language classes at a Spanish/English two-way immersion elementary school in North Carolina. Evidence of parents building bridges, gaining new knowledge, and imagining a new future were analyzed using the third space theory (Bhabha, 1994; Gutiérrez, 2008), which revealed progress to tap into third spaces while identifying areas for additional development.
Mining hidden communities in social networks using KD-Tree and improved KD-Tree

A Social network structure contains several nodes which are connected based on the relationships. Network community mining methods are used discover all hidden communities in distributed social networks based on some criteria. Several algorithms have been developed to solve the hidden community mining problem. In a given network the links between the nodes are opaque, but few nodes are thin. Finding hidden communities in such a large network is always difficult. The existing algorithms like LM (Community mining based on Local Mixing properties) algorithm gives new methods for characterizing network communities via introducing a stochastic process on networks. And it analyzes the network dynamics based on the large deviation theory concept. Through our literature survey we identified few problems in the existing methods. The actual numbers of communities are identified using the recursive bisection methods. Stopping criterion values are predefined. It does not increase communication performance and network partitioning became complex. To overcome the above mentioned problems proposed two algorithms. First we proposed community bipartition method by using KD-Tree. The stopping criterion is calculated automatically. In that we found few limitations, so we proposed an Improved KD tree algorithm. It improves the effectiveness and scalability. In this paper we analyzed both the algorithms that are LM with KD tree and Improved KD tree.
A Uniform Representation of Hybrid Criteria for Regression Testing

Regression testing tasks of test case prioritization, test suite reduction/minimization, and regression test selection are typically centered around criteria that are based on code coverage, test execution costs, and code modifications. Researchers have developed and evaluated new individual criteria; others have combined existing criteria in different ways to form what we--and some others--call hybrid criteria. In this paper, we formalize the notion of combining multiple criteria into a hybrid. Our goal is to create a uniform representation of such combinations so that they can be described unambiguously and shared among researchers. We envision that such sharing will allow researchers to implement, study, extend, and evaluate the hybrids using a common set of techniques and tools. We precisely formulate three hybrid combinations, Rank, Merge, and Choice, and demonstrate their usefulness in two ways. First, we recast, in terms of our formulations, others' previously reported work on hybrid criteria. Second, we use our previous results on test case prioritization to create and evaluate new hybrid criteria. Our findings suggest that hybrid criteria of others can be described using our Merge and Rank formulations, and that the hybrid criteria we developed most often outperformed their constituent individual criteria.
An online calibrating method for middle value of current measurement circuit in permanent magnet synchronous motor drives

The measured d/q current signals of vector controlled PMSM in synchronous rotational frame often contain various kinds of noises, which is the main reason for the degradation of a high performance PMSM drive system. In this paper, we investigate a special kind of noise, which has the same frequency with motor's phase current, and come to the conclusion that this noise is induced by the middle value inaccuracy of current measurement circuit. To solve this problem, an online calibrating algorithm based on finite state machine is proposed, which can tightly track the middle value of current measurement circuit, and correct the corresponding parameters used in current sampling and calculating algorithm in time. The calibrating algorithm is calculated incrementally, and therefore it is less time-consuming and suitable for microcontroller. The proposed technique is implemented in a fixed-point DSP based vector controller for PMSM. Experimental results verify the feasibility and effectiveness of the proposed method.
Foveal striate cortex of behaving monkey: single-neuron responses to square-wave gratings during fixation of gaze.

This invention comprises certain analogs of the prostaglandins in which the C-1 carboxylic is replaced by a primary alcohol and the double bond between C-13 and C-14 is replaced by a triple bond. Also provided in this invention, are novel chemical processes useful in the preparation of the above prostaglandin analogs. These prostaglandin analogs exhibit prostaglandin-like activity, and are accordingly useful for the same pharmacological purposes as the prostaglandins. Among these purposes are blood pressure lowering, labor induction at term, reproductive-cycle regulation, gastric antisecretory action, and the like.
A Supervised Method to Chart Multiple Manifolds

The discovery of the manifolds has long been a hot topic in computer vision. In many practical problems, highdimensional data poses a great obstacle to the researchers. But these data points are often sampled from several low-dimensional sub-manifolds. Therefore, charting the sub-manifolds in one coordinate system will help visualize them simultaneously. However, algorithms developed so far all have their own limitations in solving this problem. In this paper, we propose a new supervised method to capture multiple sub-manifolds.
In vivo localization of DNA sequences and visualization of large-scale chromatin organization using lac operator/repressor recognition

We report a new method for in situ localization of DNA sequences that allows excellent preservation of nuclear and chromosomal ultrastructure and direct, in vivo observations. 256 direct repeats of the lac operator were added to vector constructs used for transfection and served as a tag for labeling by lac repressor. This system was first characterized by visualization of chromosome homogeneously staining regions (HSRs) produced by gene amplification using a dihydrofolate reductase (DHFR) expression vector with methotrexate selection. Using electron microscopy, most HSRs showed approximately 100-nm fibers, as described previously for the bulk, large-scale chromatin organization in these cells, and by light microscopy, distinct, large-scale chromatin fibers could be traced in vivo up to 5 microns in length. Subsequent experiments demonstrated the potential for more general applications of this labeling technology. Single and multiple copies of the integrated vector could be detected in living CHO cells before gene amplification, and detection of a single 256 lac operator repeat and its stability during mitosis was demonstrated by its targeted insertion into budding yeast cells by homologous recombination. In both CHO cells and yeast, use of the green fluorescent protein-lac repressor protein allowed extended, in vivo observations of the operator-tagged chromosomal DNA. Future applications of this technology should facilitate structural, functional, and genetic analysis of chromatin organization, chromosome dynamics, and nuclear architecture.
Statistical disclosure attacks: Traffic confirmation in open environments

An improvement over the previously known disclosure attack is presented that allows, using statistical methods, to effectively deanonymize users of a mix system. Furthermore the statistical disclosure attack is computationally efficient, and the conditions for it to be possible and accurate are much better understood. The new attack can be generalized easily to a variety of anonymity systems beyond mix networks. © 2003 by Springer Science+Business Media New York.
Statistical Performance Modeling in Functional Instruction Set Simulators

Despite the recent progress in improving the speed of instruction-accurate simulators cycle-accurate simulation is still prohibitively slow for all but the most basic programs. In this article we present a statistical machine learning approach to performance estimation in fast, instruction accurate simulators and evaluate our methodology comprehensively against three popular embedded RISC processors and about 300 embedded applications. We show that our methodology is capable of providing accurate performance estimations with an average error of less than 3.9% while, on average, operating ≈ 14.5 times faster than cycle-accurate simulation.
Optimal Portfolios with Traditional and Alternative Investments: An Empirical Investigation

This article empirically investigates the diversification effects on a traditional portfolio by introducing alternative investments (hedge funds, managed futures, real estate, private equities, and commodities). The authors analyze two portfolios: the one with the lowest risk (Minimum Risk Portfolio, or MRP) and the one with the highest (modified) Sharpe Ratio (Maximum Relative Performance Portfolio, or MRPP) for the period April 1999 to April 2009. This article is the first attempt to incorporate a variety of risk measures (Volatility, Value at Risk, and Conditional Value at Risk) as the objective function for portfolio optimization and for different estimates for the expected return (historical estimates, robust Bayes-Stein estimates, Capital Asset Pricing Model (CAPM) estimates, and Black-Litterman estimates). Furthermore, the alternative risk measures are additionally modified for the skewness and the kurtosis: modified VaR and modified CVaR. The influences of the higher moments on asset allocation are also examined in connection with different risk measures and various estimators for expected returns.
GIBBS SAMPLING FOR THE UNINITIATED

This document is intended for computer scientists who would like to try out a Markov Chain Monte Carlo (MCMC) technique, particularly in order to do inference with Bayesian models on problems related to text processing. We try to keep theory to the absolute minimum needed, though we work through the details much more explicitly than you usually see even in \introductory" explanations. That means we’ve attempted to be ridiculously explicit in our exposition and notation. After providing the reasons and reasoning behind Gibbs sampling (and at least nodding our heads in the direction of theory), we work through an example application in detail|the derivation of a Gibbs sampler for
Estimating Discrete Choice Models of Demand with Market Level Variation

In this paper we develop and apply a new empirical approach to estimating a widely used class of models of demand for differentiated products. Our approach is applicable to the often encountered situation where the researcher has data on a sample of markets (i.e., the “many markets” setting). Our focus on the “many markets” setting stands in contrast to the “many products” setting that was famously studied by Berry, Levinsohn, and Pakes (1995). We first show that the key identification restriction underlying the Berry, Levinsohn, and Pakes (1995) approach to estimation does not have any identifying power in the many markets setting without further restrictions – the essential problem being the presence of sampling variability in market shares. Furthermore, their inference methods do not apply because of the presence of strategic dependence among products within a market. We show that if choice probabilities are bounded away from zero, the standard consumer model implies enough demand restrictions that we can use to form a system of moment inequalities which hold at the market level. We also construct a profiling approach for parameter inference with moment inequalities, which allows us to study models with a large number of parameters (as typically required in demand applications) by focusing attention on a generalized profile of the parameters, such as the price coefficient. We use our approach to study UPC level demand on scanner data from the Dominick’s Fine Foods database, and find that even for the baseline logit model, demand elasticities nearly double when the “many markets” structure of the data is taken into account.
Wearable Computing Meets Multiagent Systems : A Real-World Interface for the RoboCupRescue Simulation Platform

One big challenge in disaster response is to get an overview over the degree of damage and to provide this information, together with optimized plans for rescue missions, back to teams in the field. Collapsing infrastructure, limited visibility due to smoke and dust, and overloaded communication lines make it nearly impossible for rescue teams to report the total situation consistently. This problem can only be solved by efficiently integrating data of many observers into a single consistent view. A Global Positioning System (GPS) device in conjunction with a communication device, and sensors or simple input methods for reporting observations, offer a realistic chance to solve the data integration problem. We propose preliminary results from a wearable computing device, acquiring disaster relevant data, such as locations of victims and blockades, and show the data integration into the RoboCupRescue Simulation platform, which is a benchmark for MAS within the RoboCup competitions. We show exemplarily how the data can consistently be integrated and how rescue missions can be optimized by solutions developed on the RoboCupRescue simulation platform. The preliminary results indicate that nowadays wearable computing technology combined with MAS technology can serve as a powerful tool for Urban Search and Rescue (USAR).
A classification approach to interpretation of traditional Chinese musical score

Gongchepu, one of the widely-used traditional Chinese musical scores, is hard to read due to the immeasurable rhythmic rule, which only presents a general rhythmic structure while the duration of each note is determined by performer according to the context of the melody. Experience of determining the duration of each note is passed down via oral tradition, and there are few experts who can read such musical score now. However, by capitalizing on classification methods, such as Naïve Bayes and Maximum Entropy Model, rhythms of gongchepu can be labeled and interpreted into staff automatically, making it much easier to read. A precision of 85.63% is achieved in experiments. As an attempt to solve the rhythmic immeasurability problem in the study of musical score with the application of statistical model, this work is conducive to the preservation of Chinese traditional cultural heritage.