Miracle-dz/UniFAR-FTUs huggingface dataset:
Wide-angle Visual Feature Matching for Outdoor Localization

Wide-angle images exhibit significant distortion for which existing scale-space detectors such as the scale-invariant feature transform (SIFT) are inappropriate. The required scale-space images for feature detection are correctly obtained through the convolution of the image, mapped to the sphere, with the spherical Gaussian. A new visual key-point detector, based on this principle, is developed and several computational approaches to the convolution are investigated in both the spatial and frequency domain. In particular, a close approximation is developed that has comparable computation time to conventional SIFT but with improved matching performance. Results are presented for monocular wide-angle outdoor image sequences obtained using fisheye and equiangular catadioptric cameras. We evaluate the overall matching performance (recall versus 1-precision) of these methods compared to conventional SIFT. We also demonstrate the use of the technique for variable frame-rate visual odometry and its application to place recognition.
Throughput Propagation in Constraint-Based Design Space Exploration for Mixed-Criticality Systems

When designing complex mixed-critical systems on multiprocessor platforms, a huge number of design alternatives has to be evaluated. Therefore, there is a need for tools which systematically find and analyze the ample alternatives and identify solutions that satisfy the design constraints. The recently proposed design space exploration (DSE) tool DeSyDe uses constraint programming (CP) to find implementations with performance guarantees for multiple applications with potentially mixed-critical design constraints on a shared platform. A key component of the DeSyDe tool is its throughput analysis component, called a throughput propagator in the context of CP. The throughput propagator guides the exploration by evaluating each design decision and is therefore executed excessively throughout the exploration. This paper presents two throughput propagators based on different analysis methods for DeSyDe. Their performance is evaluated in a range of experiments with six different application graphs, heterogeneous platform models and mixed-critical design constraints. The results suggest that the MCR throughput propagator is more efficient.
Regional and Temporal Variation in Susceptibility to λ-Cyhalothrin in Onion Thrips, Thrips tabaci (Thysanoptera: Thripidae), in Onion Fields in New York

Abstract Populations of onion thrips, Thrips tabaci Lindeman, from commercial onion fields in New York were evaluated for their susceptibility to the commonly used pyrethroid, λ-cyhalothrin (Warrior T), using a novel system called the Thrips Insecticide Bioassay System (TIBS). To use TIBS, thrips are collected directly from the plant into an insecticide-treated 0.5-ml microcentrifuge tube that has a flexible plastic cap with a small well into which 0.08 ml of a 10% sugar-water solution with food colorant is deposited. The solution is sealed into the well with a small piece of stretched parafilm through which the thrips can feed on the solution. Thrips mortality is assessed after 24 h with the help of a dissecting stereoscope. In 2001, onion thrips populations were collected from 16 different sites and resistance ratios were >1,000 in five populations. Percent mortality at 100 ppm, a recommended field rate, varied from 9 to 100%, indicating high levels of variation in susceptibility. Particular instances of resistance appeared to be the result of practices within an individual field rather than a regional phenomenon. In 2002, we also observed large differences in onion thrips susceptibility, not only between individual fields but also between thrips collected in a single field at mid season and late season, again suggesting that insecticide-use practices within an individual field caused differences in susceptibility. Additional tests indicated no differences in susceptibility between adult and larval onion thrips populations and only relatively minor differences between populations collected from different parts of the same field. Using TIBS, several populations of onion thrips with different susceptibilities to λ-cyhalothrin were identified and then subjected to λ-cyhalothrin-treated onion plants. There was a highly significant positive relationship between percent mortality of thrips from TIBS and percent mortality from the treated onion plants, indicating that results from TIBS could be used to predict spray performance. These data suggest that use of TIBS for evaluating susceptibility to particular insecticides could be instrumental for developing a resistance management strategy for onion thrips.
Economic Impacts of Invasive Species in Forests

Biological invasions by nonnative species are a by‐product of economic activities, with the vast majority of nonnative species introduced by trade and transport of products and people. Although most introduced species are relatively innocuous, a few species ultimately cause irreversible economic and ecological impacts, such as the chestnut blight that functionally eradicated the American chestnut across eastern North America. Assessments of the economic costs and losses induced by nonnative forest pests are required for policy development and need to adequately account for all of the economic impacts induced by rare, highly damaging pests. To date, countrywide economic evaluations of forest‐invasive species have proceeded by multiplying a unit value (price) by a physical quantity (volume of forest products damaged) to arrive at aggregate estimates of economic impacts. This approach is inadequate for policy development because (1) it ignores the dynamic impacts of biological invasions on the evolution of prices, quantities, and market behavior, and (2) it fails to account for the loss in the economic value of nonmarket ecosystem services, such as landscape aesthetics, outdoor recreation, and the knowledge that healthy forest ecosystems exist. A review of the literature leads one to anticipate that the greatest economic impacts of invasive species in forests are due to the loss of nonmarket values. We proposed that new methods for evaluating aggregate economic damages from forest‐invasive species need to be developed that quantify market and nonmarket impacts at microscales that are then extended using spatially explicit models to provide aggregate estimates of impacts. Finally, policies that shift the burden of economic impacts from taxpayers and forest landowners onto parties responsible for introducing or spreading invasives, whether through the imposition of tariffs on products suspected of imposing unacceptable risks on native forest ecosystems or by requiring standards on the processing of trade products before they cross international boundaries, may be most effective at reducing their impacts.
A contour-guided deformable image registration algorithm for adaptive radiotherapy

In adaptive radiotherapy, deformable image registration is often conducted between the planning CT and treatment CT (or cone beam CT) to generate a deformation vector field (DVF) for dose accumulation and contour propagation. The auto-propagated contours on the treatment CT may contain relatively large errors, especially in low-contrast regions. A clinician's inspection and editing of the propagated contours are frequently needed. The edited contours are able to meet the clinical requirement for adaptive therapy; however, the DVF is still inaccurate and inconsistent with the edited contours. The purpose of this work is to develop a contour-guided deformable image registration (CG-DIR) algorithm to improve the accuracy and consistency of the DVF for adaptive radiotherapy. Incorporation of the edited contours into the registration algorithm is realized by regularizing the objective function of the original demons algorithm with a term of intensity matching between the delineated structures set pairs. The CG-DIR algorithm is implemented on computer graphics processing units (GPUs) by following the original GPU-based demons algorithm computation framework (Gu et al 2010 Phys Med Biol. 55 207–219). The performance of CG-DIR is evaluated on five clinical head-and-neck and one pelvic cancer patient data. It is found that compared with the original demons, CG-DIR improves the accuracy and consistency of the DVF, while retaining similar high computational efficiency.
Shape from Silhouette and Neural Network Based Optimization

In this paper, a new approach is proposed to recover the shape for the restricted observation with the limited rotation angle. This is achieved by combining Shape-from-silhouette and the Hopfield neural network based optimization technique. Under the condition that the number of the observed images is restricted with the limited rotation angle, the original Shape-from-silhouette gives poor result, while the HF-NN optimization gives the high performance with the exact shape through the formulation of the partial derivatives of height and gradient. Further, the approach is quite empirical in that no explicit assumptions are used for the specific surface reflectance function. RBF neural network is used to estimate the image irradiance (i.e. reflectance map R) in the optimization process. Then, computer simulation evaluates the accuracy of our method. Moreover, the experiment by the real object is shown and the effectiveness of the proposed method is demonstrated.
CAR: A Compression-Aware Refresh Approach to Improve Memory Performance and Energy Efficiency

DRAM memory is suffering increasingly aggravating refresh penalty, which no longer causes trivial performance degradation and power consumption. As memory capacity increases, refresh penalty has become increasingly worse as more rows have to be refreshed. In this work, we propose a simple, practical, and effective refresh approach called CAR (Compression-Aware Refresh) to efficiently mitigate refresh overheads. We apply data compression technique to store data in compressed format so that data blocks which are originally distributed across all the constituent chips of a rank only need to be stored in a subset of those chips, leaving banks in the remaining chips not fully occupied. As a result, the memory controller can safely skip refreshing memory rows which contain no useful data without compromising data integrity. Such a compression-aware refresh scheme can result in significant refresh savings and thus improve overall memory performance and energy efficiency. Moreover, to further take advantage of data compression, we adopt the rank subsetting technique to enable accesses to only those occupied chips for memory requests accessing compressed data blocks. Evaluations using benchmarks from SPEC CPU 2006 and the PARSEC 3.0 on the recent DDR4 memory systems have shown that CAR can achieve up to 1.66x performance improvement (11.7% on average).
An approximate complex image green's function for a truncated dielectric substrate

In MIC's and printed antennas the dielectric substrates always have finite extent. Rigorous analysis of the truncation effects requires the solution of an integral equation with MoM. This is usually numerically intense especially for 3-D structures. In this paper the truncation effects are incorporated directly in an approximate Green's function. The Characteristic Green's Function (CGF) technique is combined with the complex images method to derive the Green's function. The derived Green's function exhibits excellent agreement with the available rigorous MoM solution of the problem.
Questioning Identity: The Case of One Second‐Language Learner

With the goal of illuminating how identity and cognition are in tension in classroom activity, we examine how one second-language learner answers questions in a mainstream second-grade classroom. To understand this learner's participation, we analyze two conflicting “language games. ” We find the second-language learner often is adept at “passing” as knowing, but that he achieves this identity-preserving expertise at the expense of an understanding of classroom lessons.
Evaluating digital piracy intentions on behaviors

Purpose – The purpose of this paper is to assess how well digital piracy self‐report intentions predict actual digital piracy behaviors in service marketing research.Design/methodology/approach – Study 1 collects 321 surveys to investigate potential measurement issues related to digital piracy intention formation. Study 2 replicates Study 1 based on a separate sample of 267 respondents, and additionally links digital piracy intentions to directly observed digital piracy behaviors across a peer‐to‐peer network.Findings – The results first validate a strong predictive relationship between self‐report intentions and observed digital piracy behaviors (R2=0.36). Second, common method bias and measurement error do not appear to threaten the veracity of reported results. Third, a social psychological model of how digital piracy behaviors emerge is validated based upon the folk theory of the mind. Finally, a two‐dimensional conceptualization of frequency of past behaviors is identified based upon exploratory fact.
Effect of creatine supplementation during resistance training on lean tissue mass and muscular strength in older adults: a meta-analysis

The loss of muscle mass and strength with aging results in significant functional impairment. Creatine supplementation has been used in combination with resistance training as a strategy for increasing lean tissue mass and muscle strength in older adults, but results across studies are equivocal. We conducted a systematic review and meta-analysis of randomized controlled trials of creatine supplementation during resistance training in older adults with lean tissue mass, chest press strength, and leg press strength as outcomes by searching PubMed and SPORTDiscus databases. Twenty-two studies were included in our meta-analysis with 721 participants (both men and women; with a mean age of 57–70 years across studies) randomized to creatine supplementation or placebo during resistance training 2–3 days/week for 7–52 weeks. Creatine supplementation resulted in greater increases in lean tissue mass (mean difference =1.37 kg [95% CI =0.97–1.76]; p<0.00001), chest press strength (standardized mean difference [SMD] =0.35 [0.16–0.53]; p=0.0002), and leg press strength (SMD =0.24 [0.05–0.43]; p=0.01). A number of mechanisms exist by which creatine may increase lean tissue mass and muscular strength. These are included in a narrative review in the discussion section of this article. In summary, creatine supplementation increases lean tissue mass and upper and lower body muscular strength during resistance training of older adults, but potential mechanisms by which creatine exerts these positive effects have yet to be evaluated extensively.
Simple, Fast and Selective Detection of Adenosine Triphosphate at Physiological pH Using Unmodified Gold Nanoparticles as Colorimetric Probes and Metal Ions as Cross-Linkers

We report a simple, fast and selective colorimetric assay of adenosine triphosphate (ATP) using unmodified gold nanoparticles (AuNPs) as probes and metal ions as cross-linkers. ATP can be assembled onto the surface of AuNPs through interaction between the electron-rich nitrogen atoms and the electron-deficient surface of AuNPs. Accordingly, Cu2+ ions induce a change in the color and UV/Vis absorbance of AuNPs by coordinating to the triphosphate groups and a ring nitrogen of ATP. A detection limit of 50 nM was achieved, which is comparable to or lower than that achievable by the currently used electrochemical, spectroscopic or chromatographic methods. The theoretical simplicity and high selectivity reported herein demonstrated that AuNPs-based colorimetric assay could be applied in a wide variety of fields by rationally designing the surface chemistry of AuNPs. In addition, our results indicate that ATP-modified AuNPs are less stable in Cu2+, Cd2+ or Zn2+-containing solutions due to the formation of the corresponding dimeric metal-ATP complexes.
A homogeneous repository for collaborative MDE

The Model Driven Development (MDD) paradigm is gaining acceptance due to its ability to raise the level of abstraction and automation in the construction of software. However, current tools lack of some capabilities that are essential for MDD collaborative work such as version control. Because of this, large-sized projects that need teamwork development are hard to tackle. A software repository is a key component in an infrastructure that supports collaborative work; it provides version control and other advanced features such as distributed development. Several model repository tools are currently available but they are mainly focused in providing model persistence. Several approaches for supporting version control have been proposed but they exhibit some significant limitations as they have been designed to support model management, giving poor or no support for metamodel development. We propose a repository that is capable of uniformly managing metamodels and models through all their development processes. Incremental and collaborative development of (meta)models is supported using a version control system that allows developers to examine the changes applied to the (meta)models. We have devised an architecture to register changes between versions that is an alternative to the traditional delta-based scheme in order to improve performance. Such architecture is explained from the database, driver and version control perspectives.
STAT1‐associated intratumoural TH1 immunity predicts chemotherapy resistance in high‐grade serous ovarian cancer

High‐grade serous ovarian carcinoma (HGSC) accounts for 70% of all epithelial ovarian cancers but clinical management is challenged by a lack of accurate prognostic and predictive biomarkers of chemotherapy response. This study evaluated the role of Signal Transducer and Activator of Transcription 1 (STAT1) as an independent prognostic and predictive biomarker and its correlation with intratumoural CD8+ T cells in a second independent biomarker validation study. Tumour STAT1 expression and intratumoural CD8+ T cell infiltration were assessed by immunohistochemistry as a multicentre validation study conducted on 734 chemotherapy‐naïve HGSCs. NanoString‐based profiling was performed to correlate expression of STAT1 target genes CXCL9, CXCL10 and CXCL11 with CD8A transcript expression in 143 primary tumours. Multiplexed cytokine analysis of pre‐treatment plasma from resistant and sensitive patients was performed to assess systemic levels of STAT1‐induced cytokines. STAT1 was validated as a prognostic and predictive biomarker in both univariate and multivariate models and its expression correlated significantly with intra‐epithelial CD8+ T cell infiltration in HGSC. STAT1 levels increased the prognostic and predictive value of intratumoural CD8+ T cells, confirming their synergistic role as biomarkers in HGSC. In addition, expression of STAT1 target genes (CXCL9, CXCL10 and CXCL11) correlated significantly with levels of, and CD8A transcripts from intratumoural CD8+ T cells within the resistant and sensitive tumours. Our findings provide compelling evidence that high levels of STAT1, STAT1‐induced chemokines and CD8+ T cells correlate with improved chemotherapy response in HGSC. These results identify STAT1 and its target genes as novel biomarkers of chemosensitivity in HGSC. These findings provide new translational opportunities for patient stratification for immunotherapies based on emerging biomarkers of inflammation in HGSC. An improved understanding of the role of interferon‐inducible genes will be foundational for developing immunomodulatory therapies in ovarian cancer.
Cultural And Contextual Effects On Children'S Social Emotional Development And Well Being

The current paper uses structural equation modeling to test the hypotheses that in the context of poverty, responsive parenting is reduced, resulting in lower levels of self-regulation in young children. Furthermore, reduced responsiveness in parents and compromised self-regulatory abilities in children lead to mental health problems in later life. The study utilizes a three-wave, longitudinal design with multiple measures of risk and self-regulation from multiple observers.
Method for Duration and Spectral Shape Transformations of Speech for the Diagnosis of Hearing Problems

In this paper, we present a method for duration and spectral shape transformations of speech based on the combination of pyramidal Discrete Wavelet Transform (DWT) and Synchronized Overlap and Addition (SOLA) technique. The developed scheme is devoted to the diagnosis of hearing problems. The SOLA technique is basically used for duration modifications. The pyramidal DWT gives a semi logarithmic frequency decomposition that represents the frequency scales of human hearing. In addition, it allows a separate manipulation of speech sub-bands. In the proposed scheme, we explore the frame synchronization provided by SOLA technique and the frequency reparation given by the DWT to develop simultaneous time-scale and frequency-magnitude transformations. We have compared the developed method to another scheme that uses the same concept in which the frequency decomposition is based on the Cosine Modulated Pseudo- Quadratic Mirror Filter Bank (CMP-QMF). A software system of speech transformations is implemented. Experimental results show that speech waveforms can be successfully modified to different time-scales and frequency-magnitudes with high quality.
Parallel computation of the minimal elements of a poset

Computing the minimal elements of a partially ordered finite set (poset) is a fundamental problem in combinatorics with numerous applications such as polynomial expression optimization, transversal hypergraph generation and redundant component removal, to name a few. We propose a divide-and-conquer algorithm which is not only cache-oblivious but also can be parallelized free of determinacy races. We have implemented it in Cilk++ targeting multicores. For our test problems of sufficiently large input size our code demonstrates a linear speedup on 32 cores.
Time drives interaction: simulating sessions in diverse searching environments

Real life information retrieval takes place in sessions, where users search by iterating between various cognitive, perceptual and motor subtasks through an interactive interface. The sessions may follow diverse strategies, which, together with the interface characteristics, affect user effort (cost), experience and session effectiveness. In this paper we propose a pragmatic evaluation approach based on scenarios with explicit subtask costs. We study the limits of effectiveness of diverse interactive searching strategies in two searching environments (the scenarios) under overall cost constraints. This is based on a comprehensive simulation of 20 million sessions in each scenario. We analyze the effectiveness of the session strategies over time, and the properties of the most and the least effective sessions in each case. Furthermore, we will also contrast the proposed evaluation approach with the traditional one, rank based evaluation, and show how the latter may hide essential factors that affect users' performance and satisfaction - and gives even counter-intuitive results.
Time-varying noise compensation using multiple Kalman filters

The environmental conditions in which a speech recognition system should be operating are usually nonstationary. We present an approach to compensate for the effects of time-varying noise using a bank of Kalman filters. The presented method is based on the interacting multiple model (IMM) technique well-known in the area of multiple target tracking. Moreover, we propose a way to get fixed-interval smoothed estimates for the environmental parameters. The performances of the proposed approaches are evaluated in the continuous digit recognition experiments where not only the slowly evolving noise but also the rapidly varying noise sources are added to simulate the noisy environments.