Miracle-dz/UniFAR-FTUs huggingface dataset:
Noun Compound Interpretation

Noun compounds (or noun sequences) are a productive, continuous sequence of more than one nouns. Most of the noun compounds appear only once in a large corpus. These characteristics of noun compounds make them a special case, and demand special treatment. Here, the problem is to find noun compounds from text, parse them if required, and extract semantic relation between components of the noun compound. A task of extracting an abstract relation between components of the noun compound (e.g., apple pie: Made Of), or paraphrasing noun compound using verb and prepositions (apple pie : “a pie made of apple” or “a pie with apple flavor”), is known as interpretation of noun compound (or noun compound interpretation). For our work, we use a set of predefined abstract labels as semantic relations. Following are major bottlenecks in current system, and our approaches to solve the same: 1. There is no acceptable inventory of semantic relations. We have analzed a inventory of semantic relations[1], and we trying to refine the inventory. We are also planning to use a data driven approach which will help in refining the current inventories. 2. Inspite of millions of noun compounds in large corpora, there is no sufficiently large annotated dataset for supervised training. We are planning to use semisupervised approach to tackle this. 3. Context influences semantic relations. But, the present datasets have annotation for each noun compound without context. We are planning to study how context can be used for the task. We are planning to use web-extracted information to bring the context in play.
Dissolution controlled grain growth in Nickel Alloy UDIMET 720Li

The present paper examines the mechanisms for simultaneous manipulation of grain size and γ′ dissolution leading to the microstructure that balance creep and fatigue properties in UDIMET 720Li. For sub (near) solvus heat treatments, grain growth and γ′ dissolution occur simultaneously. Grain size following heat treatment is determined largely by the primary γ′ particle dispersion, via Zener-Smith pinning. Remarkably, grain growth occurs only as a result of precipitate dissolution. The resulting grain size is dictated by a combination of initial particle dispersion in the as-received material and heat treatment temperature. It is likely to hold so long as the initial grain size is close to the Zener-Smith limit and where the kinetics of grain growth and dissolution share similar rates.
Condition for Precise Measurement of Soil Surface Roughness

Whereas it is well known that electromagnetic scattering by a randomly rough surface is strongly influenced by the surface-height correlation function, it is not clear as to how long a surface-height profile is needed and at what interval it should be sampled to experimentally quantify the correlation function of a real surface. This paper presents the results of a Monte Carlo simulation conducted to answer these questions. It was determined that, in order to measure the rms height and the correlation length with a precision of %, the surface segment should be at least long and long, respectively, where is the mean (or true) value of the surface correlation length. Shorter segment lengths can be used if multiple segments are measured and then the estimated values are averaged. The second part of the study focused on the relationship between sampling interval and measurement precision. It was found that, in order to estimate the surface roughness parameters with a precision of %, it is necessary that the surface be sampled at a spacing no longer than 0.2 of the correlation length.
Analysis of atrial fibrillation after CABG using wavelets

In the present study, Wavelet analysis of P wave for the prediction of Atrial Fibrillation after CABG is evaluated. Continuous Wavelet Transform is applied to ECG and Mean/Max parameters are calculated within the P window for different frequency bands. Thus, 24 parameters are available, which, along with the 4 window lengths (corresponding to P wave length of X, Y, Z, V signals), make a pool of available parameters to be used for classification. Linear regression is used for the classification of the two groups and bootstrapping is applied in order to enhance statistical robustness. The features to be used in the regression model are selected from the pool of available parameters by use of an iterative procedure. The outcome of the feature selection procedure shows that X and Z-axis features as well as vector-magnitude features are the most important ones for the prediction of Atrial Fibrillation after CABG.
Hapstick: A Soft Flexible Joystick for Stiffness Rendering via Fiber Jamming

Continuum robots are well-suited for applications in delicate and constrained environments, such as minimally invasive surgery, due to their inherent compliance and ability to conform to highly curved paths. Yet the kinematic dissimilarity between continuum robots and conventional, off-the-shelf input devices, along with the general lack of haptic feedback available with such devices, can lead to non-intuitive control. In this work, we present Hapstick — a soft, flexible haptic joystick that uses fiber jamming to modulate its stiffness and provide feedback to users during teleoperation tasks. We characterize the performance of Hapstick, showing that the bending stiffness increases linearly with the increase in applied vacuum load. A psychophysical study is also conducted to obtain the just noticeable difference in stiffness that users can perceive using Hapstick. Lastly, we perform a study in which participants use Hapstick to teleoperate a physical tendon-driven continuum robot in a simulated colorectal cancer screening task. Users correctly identify the position and development stages of cancerous tissues in 25 out of 27 trials, illustrating the potential of jamming-based mechanisms as bidirectional interfaces capable of providing effective haptic feedback.
Distributed H∞ control of multi-agent systems with directed networks

This paper studies the distributed H∞ control problem of identical linear time invariant multi-agent systems subject to external disturbances. A directed graph containing a spanning tree is used to model the communication topology. Based on the relative states of the neighbor agents and a subset of absolute states of the agents, distributed static H∞ controllers are proposed. The concept of an H∞ performance region is extended to the directed graph situation. Then the results are used to solve the leader–follower H∞ consensus problem. Sufficient conditions are proposed based on bounded real lemma and algebraic graph theory. The effectiveness of the theoretical results is illustrated via numerical simulations.
0033 Genome-wide association analysis of composite sleep scores in 413,904 individuals

Recent genome-wide association studies (GWAS) of individual sleep traits have identified hundreds of genetic loci, often implicating genes and biological pathways that are shared across sleep phenotypes. Modeling multiple dimensions of sleep may allow identification of common underlying genetic mechanisms and complement analyses of individual traits. Moreover, construction of novel sleep health scores, accounting for correlations between traits, has the potential to enhance specificity and power for genetic analyses. We performed GWAS of composite sleep scores derived from five sleep questions characterizing 413,904 individuals of European ancestry from the UK Biobank. We constructed an additive sleep score (SS-add) as a sum of up to five favorable self-reported sleep behaviors (sleep duration of 7-8 hours, early chronotype, few insomnia symptoms, no snoring, and no excessive daytime sleepiness) as well as five principal component scores (SS-PC1 – SS-PC5) using the underlying sleep traits. SNP-level association studies of the sleep scores were complemented with multiple follow-up analyses, including investigation of pathway, tissue, and cell-type enrichments, as well as comprehensive genetic correlation (381 representative phenotypes) and bi-directional Mendelian randomization (MR) analyses (40 selected phenotypes). Sleep scores SS-PC1 (interpretable as longer duration sleep without insomnia symptoms) and SS-PC2 (healthy sleep without snoring or sleepiness) showed higher heritability (respectively 11.7% and 9.3%) compared with their primary underlying traits. SS-PC3 (loading strongly on chronotype) showed highest overall heritability (15.3%). Accounting for the six GWAS, we identified 28 significant novel loci (p< 8.3e-9), 31 additional novel loci (p< 5e-8), and 341 loci previously reported (p< 5e-8) by GWAS of individual sleep traits. Associated loci mapped to genes enriched in expression in brain tissues, and in metabolic and neuronal pathways. Numerous neurological, cardiometabolic and other traits were genetically correlated with sleep health (104 with|rho_g|>0.3, p< 2e-5). MR associations (p< 2e-4) pointed to causes (BMI [SS-PC2/PC4], smoking [SS-add/PC1], lower socio-economic status [SS-add/PC5]) and consequences (coronary heart disease [SS-add/PC1], pain [SS-PC1/5]) of poor sleep. Composite sleep health scores revealed novel genetic mechanisms of related sleep behaviors, helped clarify relationships with neurological and cardiometabolic traits, and deserve further investigation. R01HL153814 (to H.W.), NHLBI R35HL135818 (to S.R.), 1R01HL146751 (to R.S.), UKB Application 6818.
On the Algebraic Problem Concerning the Normal Forms of Linear Dynamical Systems

Introduction. Let m be the number of degrees of freedom of a linear conservative dynamical systenm and let the point (q1, q2,9 * , q'Mn Pl p2, . . . p'mt) of the phase space be denoted by x = (xl, x2, , x.2M). A system of 2m ordinary differential equations of the first order, which are homogeneous, linear and do not contain t explicitly, is a canonical system if, and only if, there exists a symmetric matrix A, such that the differential equations may be written in the form (i) Bdx/dt =Ax,
Noncooperative optimizations of controls for time-periodic Navier-Stokes systems with multiple solutions

Time-periodic systems governed by differential equations are somewhat difficult to consider in the numerical setting because they may possess many solutions. The number of solutions of such systems may be finite or infinite. Further, some trajectories which are exactly time-periodic over a given period might only approximately solve the governing equation, whereas nearby trajectories which exactly solve the governing equation might only be approximately time-periodic over the given period. The difficulty of the time-periodic setting is compounded in the case of systems governed by the Navier-Stokes equation, as the solutions of such systems in the timeevolving setting may be chaotic and multiscale. When considering the optimization of controls for such systems in the time-periodic setting, the situation is thus particularly delicate, as one doesn’t know a priori which time-periodic solution (or approximate solution) one should design the controls for. In the present work, the idea of noncooperative optimization is applied in an attempt to develop a tractable framework to solve the problem of optimization of controls for time-periodic Navier-Stokes systems. The noncooperative aspect of the optimization, however, is somewhat nonstandard: the best controls are found for the worst (of the many) time-periodic solutions of the governing equation. As the number of solutions may be finite, we have employed a technique developed by Barbu (1998) of first looking at a suitable approximation of the timeperiodic system of interest with an infinite number of solutions, finding the solution to this approximate system with a gradient-based algorithm leveraging an adjoint analysis, then refining the level of approximation until we have solved (with a sufficient level of accuracy) the optimization problem we are actually interested in. The present brief note motivates this work, presents the structure of our analysis, and outlines the resulting numerical algorithm. A future paper (under preparation) will describe our mathematical proofs of the associated thoerems in detail and present some preliminary numerical results.
Modified Particle Swarm Optimization for 0-1 Knapsack Problems

The algorithm and the search strategies of particle swarm optimization are introduced, on base of which concepts such as equivalent transformation, the difference value transformation and the transform serial sequence are defined according to characteristics of 0-1 knapsack problem, then a kind of special particle swarm optimization that is applicable to solve 0-1 knapsack problem is designed. The experimental results show the possibility and the efficiency of the modified particle swarm optimization on solving 0-1 knapsack problem.
FIBROMYALGIA FROM THE GENDER PERSPECTIVE: TRIGGERING, CLINICAL PRESENTATION AND COPING

ABSTRACT Objective: to identify the gender-based differences regarding triggering, clinical presentation and coping of fibromyalgia. Method: an integrative literature review of the narrative type and conducted in five stages, about how research studies discuss the gender-based differences regarding fibromyalgia. It was carried out in November 2022 with the fibromyalgia/fibromialgia and gender/gênero descriptors in the LILACS, MEDLINE, BDENF and IBECS databases via BVS and PubMed. The studies included were those published in the last 10 years, available in full and of free access, in English, Portuguese and Spanish. Results: a total of 16 research studies conducted in United States, Spain, Mexico, Portugal, Egypt, Israel, Italy and Colombia were analyzed. No studies were found in Brazil, an only one of them includes a nurse as author. There is a prevalence of fibromyalgia in females and it is agreed that belonging to this gender can be a risk factor for the disease, due to the lower pain threshold and greater sensitivity to pressure and temperature. Men and women have different pain perceptions and experiences, which can generate underdiagnosis among the former. There are few male participants in the research studies. Only one survey addressed the transgender population. Conclusion: there are divergent conclusions, with controversial data and hypotheses to explain the diagnostic disparity between the genders, and the low number of diagnosed men impacts on research studies. There is a broad field to be explored in Brazil about this topic and there is an evident need for research studies with transgender people. Analyses that correlate all genders may help reorganize fibromyalgia management to promote the patients' well-being and quality of life.
Pitch, roll, and yaw moment generator for insect-like tailless flapping-wing MAV

In this work, we proposed a control moment generator, which is called Trailing Edge Change (TEC) mechanism, for attitudes change in hovering insect-like tailless flapping-wing MAV. The control moment generator was installed to the flapping-wing mechanism to manipulate the wing kinematics by adjusting the wing roots location symmetrically or asymmetrically. As a result, the mean aerodynamic force center of each wing is relocated and control moments are generated. The three-dimensional wing kinematics captured by three synchronized high-speed cameras showed that the flapping-wing MAV can properly modify the wing kinematics. In addition, a series of experiments were performed using a multi-axis load cell to evaluate the forces and moments generation. The measurement demonstrated that the TEC mechanism produced reasonable amounts of pitch, roll and yaw moments by shifting position of the trailing edges at the wing roots of the flapping-wing MAV.
Muon Reconstruction and the Search for Leptoquarks at LHC

This diploma thesis focuses on the reconstruction of high-energetic muons. This simulation study was performed within the ATLAS experiment at the Large Hadron Collider (LHC) which is a pp-collider with a centre-of-mass energy √ s = 14 TeV. The purpose of this study was to identify muons with strongly overestimated transverse momentum using Monte Carlo simulated data which has been generated using Pythia and run through a full detector simulation. These muons can lead to a faked leptoquark signal, as leptoquark-decays can include high-energetic muons. If leptoquarks exist, only a small number of such events is expected which makes the safe momentum measurement a crucial point. To achieve an optimal reconstruction, selection criteria have been developed which compare the track’s χ, the particle’s η-direction and the reconstructed pT s from the different reconstruction algorithms, namely the inner detector standalone reconstruction, the muon spectrometer standalone reconstruction and a combination of both. The selection criteria are used to decide which reconstruction is chosen for a given muon. By using this selection method – contrarily to applying a cut – no events are thrown away. As a result the selection reduces the number of misreconstructed muon pT s which leads to a lower background and hence to a higher probability of identifying real leptoquark events.
Low Risk Anomaly and Coskewness: Evidence from Europe

Empirical findings that less risky stocks consistently outperform the riskier ones have motivated a great number of studies on the low risk anomaly. This paper aims to explain it away by controlling for coskewness of stock returns with the market return on the European stock market represented by constituents of the S&P 350 Index. Stocks are double sorted on coskewness and beta volatility into 2x5 quintile portfolios, and their excess returns are subsequently regressed on the Fama-French three and five factor models separately for both coskewness categories. In the low coskewness category, a persistent, highly significant low risk anomaly is identified. As the coskewness increases, the low risk anomaly dramatically decreases and loses statistical significance. As a result, in the high coskewness category, less risky portfolios no longer consistently outperform the riskier ones. Results demonstrate that accounting for coskewness in the model remarkably decreases the profitability of low risk and betting-against-beta strategies in European data.
Estimation of Response Probability in Correlated Binary Data: A New Approach

We consider analysis of binary observations from multiple sites of each subject. In this case, observations from the same subject tend to be correlated. In estimating the common response probability in correlated binary data, two weighting systems have been most popular: equal weights to sites, and equal weights to subjects. When the number of sites varies subject by subject, performance of these two weighting systems depends on the extent of correlation among sites within each subject. In this paper, we describe a new weighting method that minimizes the variance of the estimator. We apply these methods to data from a study involving an enzymatic diagnostic test to illustrate the estimation of the sensitivity and the specificity of periodontal diagnostic tests. Simulation studies were conducted to compare the performance of the new estimator with that of other estimators.
Atrial Fibrillation Detection Using Electrocardiogram Signal Input to LMD and Ensemble Classifier

Atrial fibrillation (AFib) is a type of heart arrhythmia, marked by an erratic and rapid contraction of the atria. Computer-aided diagnosis of AFib using electrocardiogram (ECG) sensor data may become a valuable tool in the detection and management of this common cardiac arrhythmia. In this letter, we present a new hybrid approach for the automatic classification of ECG signals using the local mean decomposition (LMD) and ensemble boosted trees classifier (EBTC). The LMD algorithm is employed to adaptively decompose the recorded ECG data into product functions (PFs). In total, four entropy-based features, namely, log energy, sure, Shannon, and threshold entropy, are computed from each PF. The Kruskal–Wallis algorithm is employed to check the statistical significance of the obtained features and an EBTC is used for the screening of AFib episodes. The proposed technique achieved the highest classification accuracy of 92.33%, 90.33%, and 90.00% by classifying immediate terminating and nonterminating, terminates after one minute and nonterminating, immediate terminating and terminates after one minute AFib episodes, respectively. The presented method outperforms the existing machine learning-based approaches for detecting AFib using ECG data acquired from the publicly accessible AF Termination Challenge Database.
Comparing Two Methods of Leaf Area Index Estimation for Rice (Oryza sativa L.) Using In-Field Spectroradiometric Measurements and Multispectral Satellite Images

This work presents a remote sensing application to estimate the leaf area index (LAI) in two rice (Oryza sativa L.) varieties (IDIAP 52-05 and IDIAP FL 137-11), as a proxy for crop performance. In-field, homogeneous spectroradiometric measurements (350–1050 nm) were carried in two campaigns (June–November 2017 and January–March 2018), on a private farm, TESKO, located in Juan Hombrón, Coclé Province, Panama. The spectral fingerprint of IDIAP 52-05 plants was collected in four dates (47, 67, 82 and 116 days after sowing), according to known phenological stages of rice plant growth. Moreover, true LAI or green leaf area was measured from representative plants and compared to LAI calculated from normalized PlanetScope multi-spectral satellite images (selected according to dates close to the in-field collection). Two distinct estimation models were used to establish the relationships of measured LAI and two vegetational spectral indices (NDVI and MTVI2). The results show that the MTVI2 based model has a slightly higher predictive ability of true LAI (R2 = 0.92, RMSE = 2.20), than the NDVI model. Furthermore, the satellite images collected were corrected and satellite LAI was contrasted with true LAI, achieving in average 18% for Model 2 for MTVI2, with the NDVI (Model 1) corrected model having a smaller error around 13%. This work provides an important advance in precision agriculture, specifically in the monitoring of total crop growth via LAI for rice crops in the Republic of Panama.
Rotation Matrix Estimation Between Non-Corresponding 3-D Point Sets

A method to solve a pose estimation problem, that is, the estimation of a rigid body transformation (in particular, a rotation matrix) that gives the best match between the registration of non-corresponding 3-D point sets is proposed. First, it is shown that the rotation matrix can be estimated by left singular vector matrices derived by the singular value decomposition of the given 3-D point sets. Next, it is shown that the rotation matrix between non-corresponding 3-D point sets whose number of elements is different can be found immediately using the proposed method by numerical simulations.