Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving the design of the letter contrast sensitivity test.

PURPOSE To develop a small-format letter contrast sensitivity test with improved accuracy, suitable for portable use and near testing, and having a simple and unambiguous scoring system that can be used with reference to existing norms. METHODS A near test, printed on resin-coated paper and mounted on plastic was developed by using Sloan letters, with 0.04 log unit contrast decrements between each letter and a simple scoring procedure. Monte Carlo methods and a Weibull function model of visual performance were used to assess test accuracy. RESULTS The new test has 28% lower score standard deviations than the Pelli-Robson Contrast Sensitivity Chart, over a wide range of low misreporting rates, while maintaining test scores that differ from the Pelli-Robson by 0.01 log unit, permitting use of norms collected with the Pelli-Robson test. CONCLUSIONS While maintaining comparability with Pelli-Robson norms, the new test has improved accuracy in comparison with the Pelli-Robson chart and several other advantages that result from its smaller size.
High performance biosequence database scanning on reconfigurable platforms

Summary form only given. Molecular biologists frequently compare an unknown protein sequence with a set of other known sequences (a database scan) to detect functional similarities. Even though efficient dynamic programming algorithms exist for the problem, the required scanning time is still very high, and because of the rapid database growth finding fast solutions is of highest importance to research in this area. We present a new approach to biosequence database scanning on reconfigurable hardware platforms to gain high performance at low cost. To derive an efficient mapping onto this type of architecture, we have designed fine-grained parallel processing elements (PEs). Since our solution is based on reconfigurable hardware, we can design PEs that are tailored towards the parameters of a query. This results in an implementation with significant runtime savings on a standard off-the-shelf FPGA.
Technical Report - UPC-DAC-RR-CAP-2010-17 Short-Interval Voltage and Frequency Scaling: Characterization and Optimization Opportunities

workload. We have configured an Intel R Core TM 2 processor to operate using 11 different DVFS P-states that cover a range of frequencies from 2.5GHz to 0.8GHz. We have run the SPECcpu2006 benchmark suite and studied the response of every application in front of smooth changes of frequency. The study characterizes every application in terms of the performance, power and energy levels observed. With the output of this study, we explore the space that a short-interval DVFS system offers to design OS policies. We quantify the power and energy savings that can be obtained assuming certain grade of performance degradation in direct relation to the decrements produced in the operating frequency. We have observed that smooth changes in frequency within the lower range of available frequencies have the same effects no matter the characteristics of the target application. On the other side, when the smooth changes occur in the higher levels of the available frequencies, then the memory access ratio exposed by the applications do matter, and the response of the target application is different in terms of performance, power and EDP but equally in terms of energy. The results show that for the studied architecture, it is possible to define OS power policies that reach power savings of 30% while keeping the performance degradation always under a 17% of slowdown. For energy, it is possible to implement OS energy policies that save a 20% of energy, but with a slowdown about 19%. The basis for this level of optimization is a short-interval DVFS system capable of featuring smooth changes in frequency within a wide range of P-states.
The Volcano optimizer generator: extensibility and efficient search

The Volcano project, which provides efficient, extensible tools for query and request processing, particularly for object-oriented and scientific database systems, is reviewed. In particular, one of its tools, the optimizer generator, is discussed. The data model, logical algebra, physical algebra, and optimization rules are translated by the optimizer generator into optimizer source code. It is shown that, compared with the EXODUS optimizer generator prototype, the search engine of the Volcano optimizer generator is more extensible and powerful. It provides effective support for non-trivial cost models and for physical properties such as sorting order. At the same time, it is much more efficient, as it combines dynamic programming with goal-directed searching and branch-and-bound pruning. Compared with other rule-based optimization systems, it provides complete data model independence and more natural extensibility. <<ETX>>
General purpose software package for electromagnetics engineering education

This article presents a general‐purpose educational software applied to electromagnetics engineering education. The program presented allows the students to obtain the RCS, current density, and near field distributions of perfectly electric conducting (PEC) canonical geometries being illuminated by arbitrary incident plane waves. © 2002 Wiley Periodicals, Inc. Comput Appl Eng Educ 10: 33–44, 2002; Published online in Wiley InterScience (www.interscience.wiley.com.); DOI 10.1002/cae.10015
Truthful Linear Regression

We consider the problem of fitting a linear model to data held by individuals who are concerned about their privacy. Incentivizing most players to truthfully report their data to the analyst constrains our design to mechanisms that provide a privacy guarantee to the participants; we use differential privacy to model individuals' privacy losses. This immediately poses a problem, as differentially private computation of a linear model necessarily produces a biased estimation, and existing approaches to design mechanisms to elicit data from privacy-sensitive individuals do not generalize well to biased estimators. We overcome this challenge through an appropriate design of the computation and payment scheme.
Reliable Human Detection and Tracking in Top-View Depth Images

The paper presents a method for human detection and tracking in depth images captured by a top-view camera system. We introduce a new feature descriptor which outperforms state-of-the-art features like Simplified Local Ternary Patterns in the given scenario. We use this feature descriptor to train a head-shoulder detector using a discriminative class scheme. A separate processing step ensures that only a minimal but sufficient number of head-shoulder candidates is evaluated. This contributes to an excellent runtime performance. A final tracking step reliably propagates detections in time and provides stable tracking results. The quality of the presented method allows us to recognize many challenging situations with humans tailgating and piggybacking.
Towards Compact and Fast Neural Machine Translation Using a Combined Method

Neural Machine Translation (NMT) lays intensive burden on computation and memory cost. It is a challenge to deploy NMT models on the devices with limited computation and memory budgets. This paper presents a four stage pipeline to compress model and speed up the decoding for NMT. Our method first introduces a compact architecture based on convolutional encoder and weight shared embeddings. Then weight pruning is applied to obtain a sparse model. Next, we propose a fast sequence interpolation approach which enables the greedy decoding to achieve performance on par with the beam search. Hence, the time-consuming beam search can be replaced by simple greedy decoding. Finally, vocabulary selection is used to reduce the computation of softmax layer. Our final model achieves 10 times speedup, 17 times parameters reduction, less than 35MB storage size and comparable performance compared to the baseline model.
Comparison of two algorithms for 3D skin reconstruction

In this paper, a study on 3D skin reconstruction based on image pairs is proposed. To recover 3D skin data from images, two different basic models were focused on. The first model was based on dense matching that combined the feature-based and region-based algorithms to propose a two-stage matching algorithm for a dense map. The second model was based on the Markov Random Field (MRF) model that formulated the problem of 3D reconstruction as a Bayes decision task. It was found that one model is more effective for its corresponding skin texture type. Cross-experiments were done to test the two models with the images that the authors' took. The analysis and comparison are summarized in the algorithms for 3D skin reconstruction.
Engineering Egress with Edge Fabric: Steering Oceans of Content to the World

Large content providers build points of presence around the world, each connected to tens or hundreds of networks. Ideally, this connectivity lets providers better serve users, but providers cannot obtain enough capacity on some preferred peering paths to handle peak traffic demands. These capacity constraints, coupled with volatile traffic and performance and the limitations of the 20 year old BGP protocol, make it difficult to best use this connectivity. We present Edge Fabric, an SDN-based system we built and deployed to tackle these challenges for Facebook, which serves over two billion users from dozens of points of presence on six continents. We provide the first public details on the connectivity of a provider of this scale, including opportunities and challenges. We describe how Edge Fabric operates in near real-time to avoid congesting links at the edge of Facebook's network. Our evaluation on production traffic worldwide demonstrates that Edge Fabric efficiently uses interconnections without congesting them and degrading performance. We also present real-time performance measurements of available routes and investigate incorporating them into routing decisions. We relate challenges, solutions, and lessons from four years of operating and evolving Edge Fabric.
Fully covered self-expanding metal stents for refractory pancreatic duct strictures in chronic pancreatitis

Fully covered self-expanding metal stents (FC-SEMSs), which can be removed from the bile duct, have recently been used in the main pancreatic duct (MPD) in chronic pancreatitis. The aim of this study was to investigate the feasibility, safety, and efficacy of FC-SEMSs in painful chronic pancreatitis with refractory pancreatic strictures. The primary endpoints were technical success and procedure-related morbidity. Secondary endpoints were pain relief at the end of follow-up and resolution of the dominant pancreatic stricture at endoscopic retrograde pancreatography. Over 5 months, 10 patients with painful chronic pancreatitis and refractory dominant pancreatic duct strictures were treated with FC-SEMSs. All FC-SEMSs were successfully released and removed, although two stents were embedded in the MPD at their distal end and treated endoscopically without complications. Mild abdominal pain was noted in three patients after stent release. During treatment, pain relief was achieved in nine patients, but one continued to take morphine, because of addiction. Cholestasis developed in two patients and was treated endoscopically; no patient developed acute pancreatitis or pancreatic sepsis. After stent removal, the diameter of the narrowest MPD stricture had increased significantly from 3.5 mm to 5.8 mm. Patients were followed up for a mean of 19.8 months: two patients who continued drinking alcohol presented with mild acute pancreatitis; one patient developed further chronic pancreatic pain; and one had a transient pain episode. At the end of the study, nine patients no longer had chronic pain and no patients had required surgery. Endoscopic treatment of refractory MPD stricture in chronic pancreatitis by placement of an FC-SEMS appears feasible, safe, and potentially effective.
Power Quality Disturbances Recognition Based on a Multiresolution Generalized S-Transform and a PSO-Improved Decision Tree

In a microgrid, the distributed generators (DG) can power the user loads directly. As a result, power quality (PQ) events are more likely to affect the users. This paper proposes a Multiresolution Generalized S-transform (MGST) approach to improve the ability of analyzing and monitoring the power quality in a microgrid. Firstly, the time-frequency distribution characteristics of different types of disturbances are analyzed. Based on the characteristics, the frequency domain is segmented into three frequency areas. After that, the width factor of the window function in the S-transform is set in different frequency areas. MGST has different time-frequency resolution in each frequency area to satisfy the recognition requirements of different disturbances in each frequency area. Then, a rule-based decision tree classifier is designed. In addition, particle swarm optimization (PSO) is applied to extract the applicable features. Finally, the proposed method is compared with some others. The simulation experiments show that the new approach has better accuracy and noise immunity.
The Diffusion Mechanism of Water Transport in Amine-Cured Epoxy Networks

In the present work, time-resolved attenuated total reflection Fourier transform infrared spectroscopy (ATR-IR), near-infrared (NIR) spectroscopy, and generalized two-dimensional (2D) correlation analysis were used to investigate water diffusion processes and the state of water molecules in six different epoxy resins. Positron annihilation lifetime spectroscopy (PALS) experimental results and IR results suggested that water diffusion is controlled by local chain reorientation and bond dissociation of water molecules from epoxy networks. Dynamic mechanical analysis (DMA) results of glass transition temperatures of epoxy resins after immersion in hot water correlated well with the PALS and IR results. In addition, four types of water molecules, termed nonbonded (S0), single bonded (S1), loosely double hydrogen bonded (S2L), and tightly double bonded (S2T), were detected. It was likewise found, as verified by rough estimation, that water molecules with double hydrogen bonds mostly accomplished diffusion.
Parallel Distributed Genetic Programming

This chapter describes Parallel Distributed Genetic Programming (PDGP), a form of Genetic Programming (GP) which is suitable for the development of programs with a high degree of paral-lelism and an eecient and eeective reuse of partial results. Programs are represented in PDGP as graphs with nodes representing functions and terminals, and links representing the ow of control and results. In the simplest form of PDGP links are directed and unlabelled, in which case PDGP can be considered a generalisation of standard GP. However, more complex representations can be used, which allow the exploration of a large space of possible programs including standard tree-like programs, logic networks, neural networks, recurrent transition networks, nite state automata, etc. In PDGP, programs are manipulated by special crossover and mutation operators which guarantee the syntactic correctness of the oospring. For this reason PDGP search is very eecient. PDGP programs can be executed in diierent ways, depending on whether nodes with side eeects are used or not. The chapter describes the representations, the operators and the interpreters used in PDGP, and illustrates its behaviour on a number of problems.
The Relation Between Optical Extinction and Hydrogen Column Density in the Galaxy

A linear relation between the hydrogen column density ( N H ) and optical extinction ( A V ) in the Galaxy has long been observed. A number of studies found differing results in the slope of this relation. Here, we utilize the data on 22 supernova remnants that have been observed with the latest generation X-ray observatories and for which optical extinction and/or reddening measurements have been performed and ﬁnd N H (cm − 2 ) = (2.21 ± 0.09) × 10 21 A V (mag). We compare our result with the previous studies and assess any systematic uncertainties that may affect these results.
Alignment-based Modules for Encapsulating Ontologies

Ontology engineering on the web requires a well-defined ontology module system that allows sharing knowledge. This involves declaring modules that expose their content through an interface which hides the way concepts are modeled. We provide a straightforward syntax for such modules which is mainly based on ontology alignments. We show how to adapt a generic semantics of alignments so that it accounts for the hiding of non-exported elements, but honor the semantics of the encapsulated ontologies. The generality of this framework allows modules to be reused within different contexts built upon various logical formalisms.
The evolution of antiherbivore defenses and their contribution to species coexistence in the tropical tree genus Inga

Plants and their herbivores constitute more than half of the organisms in tropical forests. Therefore, a better understanding of the evolution of plant defenses against their herbivores may be central for our understanding of tropical biodiversity. Here, we address the evolution of antiherbivore defenses and their possible contribution to coexistence in the Neotropical tree genus Inga (Fabaceae). Inga has >300 species, has radiated recently, and is frequently one of the most diverse and abundant genera at a given site. For 37 species from Panama and Peru we characterized developmental, ant, and chemical defenses against herbivores. We found extensive variation in defenses, but little evidence of phylogenetic signal. Furthermore, in a multivariate analysis, developmental, ant, and chemical defenses varied independently (were orthogonal) and appear to have evolved independently of each other. Our results are consistent with strong selection for divergent defensive traits, presumably mediated by herbivores. In an analysis of community assembly, we found that Inga species co-occurring as neighbors are more different in antiherbivore defenses than random, suggesting that possessing a rare defense phenotype increases fitness. These results imply that interactions with herbivores may be an important axis of niche differentiation that permits the coexistence of many species of Inga within a single site. Interactions between plants and their herbivores likely play a key role in the generation and maintenance of the conspicuously high plant diversity in the tropics.
Accurate American Option Pricing by Grid Stretching and High Order Finite Differences

In this paper, we present an accurate discretization for the numerical solution of the Black-Scholes equation for pricing European options and for the linear complementarity problem related to pricing American options. The aim is to find accurate option prices and hedge parameters with a small number of grid points. Fourth order finite differences are employed, as well as a grid stretching in space by means of an analytic coordinate transformation. This transformation is made time-dependent for pricing American options following the optimal exercise boundary. Numerical pricing experiments including discrete dividend payment confirm the accuracy of the methods proposed.
Nucleic Acids Research

A human placental lambda gtll cDNA library was screened with an antisera directed against a peptide of the first intracellular loop of the C-pro- tein linked photoreceptor bovine rhodopsin (1). A clone, pHPS1-2 was iden- tified and a 1788 bp EcoR I restriction fragment sequenced. The putative open reading frame encodes a protein that is similar to other membrane receptor proteins by a variety of criteria (Table I). Immunoblot analysis of a lambda lysogen of pHPS1-2 indicates that the determinant of antibody recognition does not lie in the predicted open reading frame. This determinant arose as a fusion product of beta-galactosidase and the extreme 5' region of pHPS1-2. The nature of this putative protein is undetermined.
Model-based hand tracking using a hierarchical Bayesian filter

This paper sets out a tracking framework, which is applied to the recovery of three-dimensional hand motion from an image sequence. The method handles the issues of initialization, tracking, and recovery in a unified way. In a single input image with no prior information of the hand pose, the algorithm is equivalent to a hierarchical detection scheme, where unlikely pose candidates are rapidly discarded. In image sequences, a dynamic model is used to guide the search and approximate the optimal filtering equations. A dynamic model is given by transition probabilities between regions in parameter space and is learned from training data obtained by capturing articulated motion. The algorithm is evaluated on a number of image sequences, which include hand motion with self-occlusion in front of a cluttered background
Temporel and spectral analysis of time interleaved high pass sigma delta converter

Delta sigma modulators are widely used for low to moderate rate analog-to-digital conversion. But they are not adapted to high rate conversion because of time oversampling requirement. Parallel architecture is a potential solution to increase the frequency range of /spl Delta//spl Sigma/ ADC, especially the time-interleaved high-pass /spl Delta//spl Sigma/ converter. In this paper, we analyze the immunity from low-frequency offered by the high-pass /spl Delta//spl Sigma/ modulators in time-interleaved /spl Delta//spl Sigma/ ADC. The high-pass /spl Delta//spl Sigma/ modulators not only retains the performance of the converter and eliminates low frequency noise, but also allows simple adaptive channel gain equalization scheme to minimize channel gain mismatch effects by using LMS algorithm.
A new semantically annotated corpus with syntactic-semantic and cross-lingual senses

In this article, we describe a new sense-tagged corpus for Word Sense Disambiguation. The corpus is constituted of instances of 20 French polysemous verbs. Each verb instance is annotated with three sense labels: (1) the actual translation of the verb in the english version of this instance in a parallel corpus, (2) an entry of the verb in a computational dictionary of French (the Lexicon-Grammar tables) and (3) a fine-grained sense label resulting from the concatenation of the translation and the Lexicon-Grammar entry.
A Framework for De ning LogicsRobert Harper

The Edinburgh Logical Framework (LF) provides a means to deene (or present) logics. It is based on a general treatment of syntax, rules, and proofs by means of a typed-calculus with dependent types. Syntax is treated in a style similar to, but more general than, Martin-LL of's system of arities. The treatment of rules and proofs focuses on his notion of a judgement. Logics are represented in LF via a new principle, the judgements as types principle, whereby each judgement is identiied with the type of its proofs. This allows for a smooth treatment of discharge and variable occurrence conditions and leads to a uniform treatment of rules and proofs whereby rules are viewed as proofs of higher-order judgements and proof checking is reduced to type checking. The practical beneet of our treatment of formal systems is that logic-independent tools such as proof editors and proof checkers can be constructed.