Miracle-dz/UniFAR-FTUs huggingface dataset:
Constrained and Dimensionality-Independent Path Openings

Path openings and closings are morphological operations with flexible line segments as structuring elements. These line segments have the ability to adapt to local image structures, and can be used to detect lines that are not perfectly straight. They also are a convenient and efficient alternative to straight line segments as structuring elements when the exact orientation of lines in the image is not known. These path operations are defined by an adjacency relation, which typically allows for lines that are approximately horizontal, vertical or diagonal. However, because this definition allows zig-zag lines, diagonal paths can be much shorter than the corresponding horizontal or vertical paths. This undoubtedly causes problems when attempting to use path operations for length measurements. This paper 1) introduces a dimensionality-independent implementation of the path opening and closing algorithm by Appleton and Talbot, 2) proposes a constraint on the path operations to improve their ability to perform length measurements, and 3) shows how to use path openings and closings in a granulometry to obtain the length distribution of elongated structures directly from a gray-value image, without a need for binarizing the image and identifying individual objects.
SensingKit: Evaluating the Sensor Power Consumption in iOS Devices

Today's smartphones come equipped with a range of advanced sensors capable of sensing motion, orientation, audio as well as environmental data with high accuracy. With the existence of application distribution channels such as the Apple App Store and the Google Play Store, researchers can distribute applications and collect large scale data in ways that previously were not possible. Motivated by the lack of a universal, multi-platform sensing library, in this work we present the design and implementation of SensingKit, an open-source continuous sensing system that supports both iOS and Android mobile devices. One of the unique features of SensingKit is the support of the latest beacon technologies based on Bluetooth Smart (BLE), such as iBeacon and Eddystone. We evaluate and compare the power consumption of each supported sensor individually, using an iPhone 5S device running on iOS 9. We believe that this platform will be beneficial to all researchers and developers who plan to use mobile sensing technology in large-scale experiments.
Genome wide transcriptional profiling of Herbaspirillum seropedicae SmR1 grown in the presence of naringenin

Herbaspirillum seropedicae is a diazotrophic bacterium which associates endophytically with economically important gramineae. Flavonoids such as naringenin have been shown to have an effect on the interaction between H. seropedicae and its host plants. We used a high-throughput sequencing based method (RNA-Seq) to access the influence of naringenin on the whole transcriptome profile of H. seropedicae. Three hundred and four genes were downregulated and seventy seven were upregulated by naringenin. Data analysis revealed that genes related to bacterial flagella biosynthesis, chemotaxis and biosynthesis of peptidoglycan were repressed by naringenin. Moreover, genes involved in aromatic metabolism and multidrug transport efllux were actived.
KECIR Question Answering System at NTCIR7 CCLQA

At the NTCIR-7 CCLQA (Complex Cross-Language Question Answering) task, we participated in the Chinese-Chinese (C-C) and English-Chinese (E-C) QA (Question Answering) subtasks. In this paper, we describe our QA system, which includes modules for question analysis, document retrieval, information extraction and answer generation. Besides, we used an online MT (Machine Translation) system to deal with question translation in our E-C task. An overall analysis and a detailed module-by-module analysis are presented. Since document retrieval is an essential part of CLQA, we also did experiments and submit QA results using IR4QA results in order to find out which IR technique would help CCLQA.
Student Learning Heterogeneity in School Mathematics

Student Learning Heterogeneity in School Mathematics Malcolm Cunningham Doctor of Philosophy Graduate Department of Human Development and Applied Psychology Ontario Institute for Studies in Education University of Toronto 2012 The phrase opportunities to learn (OTL) is most commonly interpreted in institutional, or inter-individual, terms but it can also be viewed as a cognitive, or intra-individual, phenomenon. How student learning heterogeneity (LH) learning differences manifested when children’s understanding is later assessed is understood varies by OTL interpretation. In this study, I argue that the cognitive underpinning of learning disability, learning difficulty, typical achievement, and gifted achievement in mathematics is not well understood in part because of the ambiguity of LH assumptions in previous studies. Data from 104,315 Ontario students who had responded to provincially-mandated mathematics tests in grades 3, 6, and 9 dataset were analyzed using latent trait analysis (LTM) and latent class analysis (LCA). The tests were constructed to distinguish four achievement levels per grade and, either five curriculum strands (grades 3 and 6), three strands (grade 9 applied) or four strands (grade 9 academic). Best-fitting LTM models reflected 3or 4-factors (grade 9 applied and grades 3, 6, 9 academic, respectively). Best-fitting LCA solutions reflected 4or 5-classes (grade 3, 6 and grade 9 applied, academic, respectively). There were differences in relative proportions of students who were distributed across levels and classes. Moreover, grade 9 models were more complex than the reported four achievement levels. To explore intrinsic modeled results further, latent factors were plotted against latent classes. Implications of institutional versus cognitive interpretations are discussed.
Genome-wide linkage scan for loci of musical aptitude in Finnish families: evidence for a major locus at 4q22

Background: Music perception and performance are comprehensive human cognitive functions and thus provide an excellent model system for studying human behaviour and brain function. However, the molecules involved in mediating music perception and performance are so far uncharacterised. Objective: To unravel the biological background of music perception, using molecular and statistical genetic approaches. Methods: 15 Finnish multigenerational families (with a total of 234 family members) were recruited via a nationwide search. The phenotype of all family members was determined using three tests used in defining musical aptitude: a test for auditory structuring ability (Karma Music test; KMT) commonly used in Finland, and the Seashore pitch and time discrimination subtests (SP and ST respectively) used internationally. We calculated heritabilities and performed a genome-wide variance components-based linkage scan using genotype data for 1113 microsatellite markers. Results: The heritability estimates were 42% for KMT, 57% for SP, 21% for ST and 48% for the combined music test scores. Significant evidence of linkage was obtained on chromosome 4q22 (LOD 3.33) and suggestive evidence of linkage at 8q13-21 (LOD 2.29) with the combined music test scores, using variance component linkage analyses. The major contribution of the 4q22 locus was obtained for the KMT (LOD 2.91). Interestingly, a positive LOD score of 1.69 was shown at 18q, a region previously linked to dyslexia (DYX6) using combined music test scores. Conclusion: Our results show that there is a genetic contribution to musical aptitude that is likely to be regulated by several predisposing genes or variants.
The relevance of hedonic price indices: the case of paintings

We argue that for the case of heterogeneous commodities with infrequent tradings, such as paintings, it is relevant to base a price index on hedonic regressions using all sales and not resales only. To support this conclusion we construct a price index for paintings by Impressionists and their followers and compare the various estimators using bootstrapping techniques.
Comparing Personal Project Metrics to Support Process and Product Improvement

Writing high quality software with a minimum of effort is an important thing to learn. Various personal metric collection processes exist, such as PSP and Hackystat. However, using the personal metric collection processes gives only a partial indication of how a programmer stands amongst his peers. Personal metrics vary greatly amongst programmers and it is not always clear what is the “correct” way to develop software. This paper compares personal programming characteristics of students in a class environment. Metrics, such as CK Metrics, have been analyzed and compared against a set of similar students in an attempt to find the correct or accepted value for these metrics. It is our belief that programmers can gain much, if not, more information from comparing their personal metrics against other programmers. Preliminary results show that people with more experience in programming produce different metrics than those with less.
Fixed Point Theorems for Discontinuous Mappings

We prove a generalization of Brouwer's famous xed point theorem to discontinuous maps. The main result shows that for discontinuous functions on a compact convex domain X one can always nd a point x 2 X such that kx ? f(x)k is less than a certain measure of discontinuity. Applications to artiicial neural nets, economic equilibria, and analysis are given.
UZZY M ODEL FOR H UMAN F ACE E XPRESSION R ECOGNITION

This paper present an approach to recognize human face expression and emotions based on some fuzzy pattern rules. Facial features for this specially eye and lips are extracted an approximated into curves which represents the relationship between the motion of features and change of expression. This paper focuses the concepts like face detections, skin color segmentation, face features extractions and approximation and fuzzy rules formation. Conclusion based on fuzzy patterns never been accurate but still our intension is to put more accurate results.
Measurement of glomerular filtration rate by dynamic contrast‐enhanced magnetic resonance imaging using a subject‐specific two‐compartment model

Measuring glomerular filtration rate (GFR) by dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) as part of standard of care clinical MRI exams (e.g., in pediatric solid tumor patients) has the potential to reduce diagnostic burden. However, enthusiasm for this relatively new GFR test may be curbed by the limited amount of cross‐calibration studies with reference GFR techniques and the vast variety of MR tracer model algorithms causing confusion on the choice of model. To advance MRI‐based GFR quantification via improved GFR modeling and comparison with associated 99mTc‐DTPA‐GFR, 29 long‐term Wilms' tumor survivors (19.0–43.3 years, [median 32.0 ± 6.0 years]) treated with nephrectomy, nonnephrotoxic chemotherapy ± radiotherapy underwent MRI with Gd‐DTPA administration and a 99mTc‐DTPA GFR test. For DCE‐MRI‐based GFR estimation, a subject‐specific two‐compartment (SS‐2C) model was developed that uses individual hematocrit values, automatically defines subject‐specific uptake intervals, and fits tracer‐uptake curves by incorporating these measures. The association between reference 99mTc‐DTPA GFR and MR‐GFRs obtained by SS‐2C, three published 2C uptake, and inflow–outflow models was investigated via linear regression analysis. Uptake intervals varied from 64 sec to 141 sec [96 sec ± 21 sec] and hematocrit values ranged from 30% to 49% [41% ± 4%]; these parameters can therefore not be assumed as constants in 2C modeling. Our MR‐GFR estimates using the SS‐2C model showed accordingly the highest correlation with 99mTc‐DTPA‐GFRs (R2 = 0.76, P < 0.001) compared with other models (R2‐range: 0.36–0.66). In conclusion, SS‐2C modeling of DCE‐MRI data improved the association between GFR obtained by 99mTc‐DTPA and Gd‐DTPA DCE‐MRI to such a degree that this approach could turn into a viable, diagnostic GFR assay without radiation exposure to the patient.
Real Exchange Rate Volatility and the Price of Nontradables in Sudden-Stop-Prone Economies

The dominant view in the empirical literature on exchange rates is that the high variability of real exchange rates is due to movements in exchange-rate-adjusted prices of tradable goods. This paper shows that this dominant view does not hold in Mexican data for the periods in which the country had managed exchange rate regimes. Variance analysis of a 30-year sample of monthly data shows that movements in the price of nontradables relative to tradables account for up to 70 percent of the variability of the real exchange rate during these periods. The paper proposes a model in which this stylized fact, and the Sudden Stops that accompanied the collapse of Mexico's managed exchange rates, could result from an endogenous amplification mechanism operating via nontradables prices in economies with dollarized liabilities and credit constraints. The key feature of this mechanism is Irving Fisher's debt-deflation process. Numerical evaluation suggests that the Fisherian deflation effects on consumption, the current account, and relative prices dwarf those induced by the standard balance sheet effect typical of the Sudden Stops literature.
A . 1 Assessment of Distributed-Cycling Schemes on 45 nm NOR Flash Memory Arrays

The assessment of distributed-cycling activation energy for scaled technologies requires a careful control of experimental tests, preventing spurious effects: in particular, we report on the possibility for long gate-stresses to give rise to parasitic drifts, which add to the threshold-voltage loss during post-cycling bake. When the superposition of the two phenomena is taken into account, the effectiveness of distributed-cycling is fully confirmed at the 45nm NOR node.
Optimal path planning in the workspace for articulated robots using mixed integer programming

This paper considers the task of path planning for articulated robots such that the end effector is driven optimally between two points in the workspace while collision with dynamic obstacles is avoided. Compared to path planning in the configuration space, approaches in the workspace save the computationally expensive step of mapping obstacles from the workspace into the configuration space. The method presented here builds on a problem formulation as a mixed-integer program considering time-varying constraints resulting from moving obstacles, as well as state and input constraints depending on the region of the work space. The method is applied to a two-link robot with static and moving obstacles and is evaluated for different situations.
Proposal Automatic image annotation based on learning visual cues

Labeling the semantic content of images is a problem known as image annotation. Automatic image annotation is the process by which a computer system automatically assigns metadata, in the form of captions or keywords, to a digital image. Automatic image annotation often uses computer vision techniques to extract meaningful cues from the image content. It can be applied in image retrieval systems to organize and locate images of interest from a database. Most of the image database systems employ manual annotation, that is users enter some descriptive keywords when the images are loaded,registered or browsed. Although manual annotation of image content is considered a “best case” in terms of accuracy (meaningful keywords are selected by the human) it is a time consuming and intensive process. In addition, human annotation is subjective: human observers tend to disregard background elements favoring subjects related on their life like humans or animals. Automatic image annotation can be regarded as multi-class image classification problem with a very large number of classes. Typically, image analysis in the form of extracted feature vectors and the training annotation words, are used by machine learning to automatically apply annotations to new images. The objective of this thesis is the development of an architecture of classifiers for automatic image annotation. The proposed framework is based on the idea that regionlevel analysis can improve image scene analysis and content description. The approach based on regions should provide a more robust classification since it is a good compromise between local and global approaches. The building blocks of my thesis will be: 1. Representing the image content by first segmenting the image and then computing meaningful descriptions for each region. 2. Studying data-driven feature selection for reducing the description dimension, devising unsupervised or partially supervised learning strategies to organize the data in homogeneous clusters 3. Designing an architecture of classifiers able to automatically assign a set of tags to a given image.
Circulating KCNH2 Current-Activating Factor in Patients with Heart Failure and Ventricular Tachyarrhythmia

Background It is estimated that approximately half of the deaths in patients with HF are sudden and that the most likely causes of sudden death are lethal ventricular tachyarrhythmias such as ventricular tachycardia (VT) or fibrillation (VF). However, the precise mechanism of ventricular tachyarrhythmias remains unknown. The KCNH2 channel conducting the delayed rectifier K+ current (IKr) is recognized as the most susceptible channel in acquired long QT syndrome. Recent findings have revealed that not only suppression but also enhancement of IKr increase vulnerability to major arrhythmic events, as seen in short QT syndrome. Therefore, we investigated the existence of a circulating KCNH2 current-modifying factor in patients with HF. Methodology/Principal Findings We examined the effects of serum of HF patients on recombinant IKr recorded from HEK 293 cells stably expressing KCNH2 by using the whole-cell patch-clamp technique. Study subjects were 14 patients with non-ischemic HF and 6 normal controls. Seven patients had a history of documented ventricular tachyarrhythmias (VT: 7 and VF: 1). Overnight treatment with 2% serum obtained from HF patients with ventricular arrhythmia resulted in a significant enhancement in the peaks of IKr tail currents compared to the serum from normal controls and HF patients without ventricular arrhythmia. Conclusions/Significance Here we provide the first evidence for the presence of a circulating KCNH2 channel activator in patients with HF and ventricular tachyarrhythmias. This factor may be responsible for arhythmogenesis in patients with HF.
Modeling Neighbor Discovery in Bluetooth Low Energy Networks

In this letter, an analytical model is proposed for 3-channel-based neighbor discovery in Bluetooth Low Energy (BLE) networks. The model can be used to determine some important performance metrics, such as average latency or average energy consumption during the course of discovering neighbors. Since intermittent connections are frequently encountered in practical scenarios of BLE, the modeling results can provide a beneficial guidance to customize advertising or scanning behavior towards user desired performance.
A randomized controlled trial of green tea catechins in protection against ultraviolet radiation–induced cutaneous inflammation

Background: Safe systemic protection from the health hazards of ultraviolet radiation (UVR) in sunlight is desirable. Green tea is consumed globally and is reported to have anti-inflammatory properties, which may be mediated through the impact on cyclooxygenase and lipoxygenase pathways. Recent data suggest that green tea catechins (GTCs) reduce acute UVR effects, but human trials examining their photoprotective potential are scarce. Objective: We performed a double-blind, randomized, placebo-controlled trial to examine whether GTCs protect against clinical, histologic, and biochemical indicators of UVR-induced inflammation. Design: Healthy adults (aged 18–65 y, phototypes I–II) were randomly allocated to 1350 mg encapsulated green tea extract (540 mg GTC) with 50 mg vitamin C or placebo twice daily for 3 mo. Impact on skin erythema, dermal leukocytic infiltration, and concentrations of proinflammatory eicosanoids was assessed after solar-simulated UVR challenge, and subject compliance was determined through assay of urinary GTC metabolite epigallocatechin glucuronide. Results: Volunteers were assigned to the active (n = 25) or the placebo (n = 25) group. After supplementation, median (IQR) sunburn threshold (minimal erythema dose) was 28 (20–28) and 20 (20–28) mJ/cm2 in the active and placebo groups, respectively (nonsignificant), with no difference in AUC analysis for measured erythema index after a geometric series of 10 UVR doses. Skin immunohistochemistry showed increased neutrophil and CD3+ T-lymphocyte numbers post-UVR in both groups (P < 0.01) with no statistically significant differences between groups after supplementation. Cyclooxygenase and lipoxygenase metabolites prostaglandin E2 (vasodilator) and 12-hydroxyeicosatetraenoicacid (chemoattractant), respectively, increased after UVR (P < 0.05), with no differences between supplementation groups. Conclusion: Oral GTC (1080 mg/d) with vitamin C over 3 mo did not significantly reduce skin erythema, leukocyte infiltration, or eicosanoid response to UVR inflammatory challenge. This trial was registered at clinicaltrials.gov as NCT01032031.
Fast and Tight Polynomial Bounds Based on Bernstein Expansion

Semi-deteministic optimization methods We consider with : J Ω → Ω ⊂. We make the following assump tions: 1 (,) J C ∈ Ω and is coercive. The infimum of J is denoted by J m (when J m is unknown, we set J m to a low value). Many deterministic minimization algorithms can be seen as discrete dynamical systems coming from the discretization of first or second order Cauchy problems. On the other hand, global optimization can be considered as an over-determined Boundary Value Problem (BVP) for these problems. For instance, the steepest descent method leads to the following BVP: The over-determination can be removed by considering the initial conditions υ as new variables to be found by the minimization of h(υ) = J(x υ (T υ))-J m , where x υ is the solution of the dynamical system starting from υ. This is solved with an original Semi-Deterministic Algorithm (SDA) which minimizes h(υ) using a multi-dimensional shooting method. Application to credit portfolio optimization Various version of this SDA have been validated on several industrial problems involving local minima such as: credit portfolio management, optical fiber synthesis, shape optimization of fast-microfluidic-mixer devices, temperature and pollution control in a bunsen flame, shape optimization of coastal structures … During this presentation, we will focus on the application of our method to the improvement under constraints of various portfolio performances, in particular non-convex risk measures and profitability. We discuss the global optimization of the higher order moments of a portfolio of financial assets. The proposed model is an extension of the celebrated mean variance model of Markowitz. Since asset returns typically exhibit excess kurtosis and are often skewed, and investors would prefer positive skewness and try to reduce kurtosis of their portfolio returns, the mean variance model (assuming either normally distributed returns or quadratic utility functions) might be too simplifying. The inclusion of higher order moments has therefore been proposed as a possible augmentation of the classical model in order to make it more widely applicable. The resulting problem is non-convex, large scale, and highly relevant in financial optimization. We discuss the solution of the model using two stochastic algorithms. The first is a simulated annealing (SA) approach where a solution is iteratively updated. SA has two main ingredients: first, white noise is added to the current solution in order to generate a new solution within the neighborhood within the current one. …