Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutual Interaction Analysis Between Stock Market Index And Financial Indicators By Granger Causality Method

This study aims to measure the mutual relationship between exchange rates and interest rate and the BIST100 index. For this purpose, the relationship between the variables used in the study was analyzed using the VAR model method. The relationship between the stock market index, dollar/ TL, Euro/TL, and the interest rate was evaluated at the level of 5% and 10% significance with the VAR method. The reaction of the stock market index against a one-unit shock to be applied to exchange rates and interest rate were examined by the effect-reaction analysis. January 2005-March 2019 period based on monthly data, Dollar/TL, Euro/TL, interest rate, and BIST100 index variables were used in the study. According to the results obtained from the analysis, it was determined that the Dollar/TL variable is the cause of the stock market index variable. The study also found that the Dollar/TL variable is the cause of the Euro/TL and interest rate variables.
A Computationally Efficient Sphere Decoding Algorithm with Smart Radius Control

We propose a computationally efficient sphere decoding (SD) algorithm with smart radius control (SRC). As a baseline algorithm for SD, we consider the modified Schnorr-Euchner (SE) algorithm [1] (hereafter, called as the MSE algorithm). In principle, the radius after zero-forcing decision feedback equalization (ZF-DFE) estimation can be reduced further if we select a new lattice vector closer to the received signal vector than the lattice vector corresponding to the ZF-DFE estimate does. In our case, we obtain such a better lattice vector by performing a sequence of alternating one-dimensional searches, starting from the ZF-DFE estimate. We then develop a novel SRC algorithm that adopts adaptively the additional radius reduction process according to the estimated signal-to-noise-power ratio (SNR) after ZF-DFE estimation. In addition, we analyze the effect of detection ordering on the complexity for SD. Column-norm ordering of the channel matrix and optimal ordering [1] are considered here. From our analyses, we see that SRC can reduce greatly the complexity for SD and the degree of complexity reduction gets significant as the SNR decreases, irrespective of detection ordering schemes used.
NUMERICAL SIMULATION OF NEWTONIAN FLUID MIXING INSIDE ASYMETRIC T-SHAPED MICROMIXERS

Achieving eficient mixing of flow streams is one of the important challenges of microfluidics, because of the difficulty to induce flow transition to the turbulent regime. Of the different solutions for devices proposed, T-shaped micromixers stand out, as they have a simple geometry and low production cost and showed promising results when asymmetric inlet conditions are applied. Starting from experimental results obtained when equal flow rates were applied to inlets with different widths, four geometries (one symmetric and three asymmetric) were modelled using CAD 3D software Solidworks. Then, the numerical simulation of twelve flows, corresponding to the Reynolds number based on the outlet channel range of 25 to 295, inside each model was performed. This tool allowed the understanding of how the degree of asymmetry influence mixing quality, and the physical characterization of the five flow regimes previously identified. This allowed to conclude that increasing asymmetry favours mixing quality and also that after transition to engulfment regime, symmetrical micromixers perform better than asymmetrical ones.
Reconstructing 3D Charge Depositions in the MicroBooNE Liquid Argon Time Projection Chamber using Convolutional Neural Networks

We have developed a convolutional neural network (CNN) that reconstructs the three dimensional location of ionization produced by charge particles traversing a wire-readout liquid argon time projection chamber (LArTPC) at MicroBooNE. This method is the ﬁrst CNN application to reconstruct 3D space points directly from two dimensional images of the diﬀerent wire plane views.
Combining ability study for yield and quality traits in cucumber (Cucumis sativus L.)

Seven cucumber (Cucumissativus L.) genotypes (3 lines and 4 testers) were crossed in a line × tester mating design. The resultant 12 hybrids and their parents were evaluated using Randomised Block Design with two replications during Kharif 2018. Sufficient genetic variability was observed for all the characters under study. In this study, the parents L2 (Koradacherry local), T2 (Orathanadu local) and T3 (Aipatti local) exhibited high positive GCA (General Combining Ability) effects for yield related traits and high negative GCA effects for earliness characters. The parent T2 identified in this study may be used in multiple crossing programme to isolate high yielding varieties. Among the hybrid combinations, L2xT3, L1xT2 and L3xT4 expressed the maximum positive significant SCA (Specific Combining Ability) effects for yield and yield associated characters. In the above cross combinations one parent was a good combiner and the other was an average/poor combiner; hence the hybrids can be exploited for transgressive selection.
Arabic Text Classification: An Improved Model using New Relations-Based Features

As a result of increasing Arabic text documents' warehouses on local PC storage as well as on the Web, various tools are emerged to process this type of documents. Text classification and categorization are the most important tools to classify documents in order to save, sort and retrieve these documents later. Accordingly in this paper, an improved model to classify Arabic text documents is proposed. In this model, relations between concepts in the Arabic WordNet dictionary are utilized to propose five new features. These new features are compared with the state of the art features using three quantitative metrics, three evaluation datasets, and three classification algorithms. In the results, the new Proposed Relation-based Features (PRF) show their superiority on the state of the art features in most cases.
Theoretical Expression of the Aperture-averaged Irradiance Scintillation Index (ISI) for a Gaussian Beam in Non-Kolmogorov Turbulence with Finite Inner and Outer Scales

This paper investigates the aperture-averaged irradiance scintillation index of a Gaussian beam propagating through a horizontal path in weak anisotropic turbulence. Analytical expressions are deduced based on the generalized exponential atmospheric spectrum for anisotropic turbulence, which includes the spectral power law value of nonKolmogorov turbulence, the finite inner and outer scales of turbulence, the anisotropic factor, and other optical parameters of the Gaussian beam. The numerical results indicate that the aperture-averaged irradiance scintillation index (ISI) is more sensitive to the change of the inner scale than the outer scale, and an increasing aperture diameter or an increasing anisotropic factor can decrease the irradiance scintillation index at the receiver.
Probabilities of Detection and False Alarm in MTM-Based Spectrum Sensing for Cognitive Radio Systems

— The paper presents closed-form expressions for the detection, and false alarm probabilities for spectrum sensing detection based on the Multitaper Spectrum Estimation Method (MTM) using Neyman-Pearson criterion. The MTM spectrum sensing is a powerful technique in Cognitive Radio (CR) systems. It tolerates problems related to bad biasing, and large variance of estimates, that are the main drawbacks in the periodogram (i.e., energy detector). The performance of the MTM spectrum sensing system is controlled by parameters, such as the chosen half time bandwidth product, Discrete Prolate Slepian Sequence (DPSS) (i.e., tapers), DPSS’ eigenvalues, and the number of tapers used. These parameters determine the theoretical probabilities of detection and false alarm, which are used to evaluate the system performance. The paper shows a good match between the theoretical and numerical simulation results.
The nature of ice-nucleating particles affects the radiative properties of tropical convective cloud systems

Abstract. Convective cloud systems in the maritime tropics play a critical role in global climate, but accurately representing aerosol interactions within these clouds persists as a major challenge for weather and climate modelling. We quantify the effect of ice-nucleating particles (INP) on the radiative properties of a complex Tropical Atlantic deep convective cloud field using a regional model with an advanced double-moment microphysics scheme. Our results show that the domain-mean daylight outgoing radiation varies by up to 18 W m−2 depending on the bio- and physico-chemical properties of INP. The key distinction between different INPs is the temperature dependence of ice formation, which alters the vertical distribution of cloud microphysical processes. The controlling effect of the INP temperature dependence is substantial even in the presence of secondary ice production, and the effects of secondary ice formation depend strongly on the nature of the INP. Our results have implications for climate model simulations of tropical clouds and radiation, which currently do not consider a link between INP particle type and ice water content. The results also provide a challenge to the INP measurement community, since we demonstrate that INP concentration measurements are required over the full mixed-phase temperature regime, which covers around 10 orders of magnitude in INP concentration.
Subclinical Left Ventricular Systolic Dysfunction in Patients with Septic Shock Based on Sepsis-3 Definition: A Speckle-Tracking Echocardiography Study

Introduction Left ventricular dysfunction is quite common in septic shock. Speckle-tracking echocardiography (STE) is a novel, highly sensitive method for assessing left ventricular function, capable of detecting subclinical myocardial dysfunction, which is not identified with conventional echocardiography. We sought to evaluate subclinical left ventricular systolic function in patients with septic shock using speckle-tracking echocardiography. Methods From May 2017 to December 2018, patients aged ≥18 years admitted to the intensive care unit with the diagnosis of sepsis and septic shock based on the sepsis-3 definition were included. Patients with other causes of cardiac dysfunction were excluded. Transthoracic echocardiography was performed for all the patients within 24 hours of diagnosis. Left ventricular systolic function was assessed using conventional echocardiography and speckle-tracking echocardiography. Results Patients with septic shock (n = 90) (study group) and 37 matched patients with sepsis but no septic shock (control group) were included. Left ventricular ejection fraction (LVEF) by conventional echocardiography showed no significant difference between two groups (58.2 ± 9.9 vs. 58.6 ± 8.3, p=0.804). The global longitudinal strain (GLS) by STE was significantly reduced in patients with septic shock compared with that in the control (−14.6 ± 3.3 vs. −17.1 ± 3.3, p < 0.001). Based on the cutoff value of GLS ≥ −15% for the definition of subclinical left ventricular systolic dysfunction, this dysfunction was detected in 50 patients with septic shock (55.6%) and in 6 patients in the control group (16.2%) (p < 0.05). Conclusions Speckle-tracking echocardiography can detect early subclinical left ventricular systolic dysfunction via the left ventricular global longitudinal strain compared with conventional echocardiographic parameters in patients with septic shock.
Novel Method for NKS Search in Multidimensional Dataset Using Advance Promish & Ranking Function

We Consider multi-dimensional dataset where each data point has set of keyword in feature space allows for the development of new tools to query and explore these multidimensional dataset. In this paper, we study nearest keyword set Queries on text reach multidimensional dataset. We propose a novel method called ProMiSH(Projection and Multiscale Hashing) that uses random projection and hash-based index structure. Our experimental result shows that ProMiSH has Speedup over state-of-art-tree-based techniques. Keyword-based search in text-rich multi-dimensional datasets facilitates many novel applications and tools. In this paper, we consider objects that are tagged with keywords and are embedded in a vector space. For these datasets, we study queries that ask for the tightest groups of points satisfying a given set of keywords.
INDUCTEX PROCESS FLOW A quick overview of the InductEx process flow is required to explain some aspects of full-gate verification. InductEx reads a circuit layout from industry-standard GDS

At present, superconducting integrated circuit layouts are verified through a variety of techniques. A layoutversus-schematic method implemented in Cadence allows extraction of circuit schematics with certain geometry-dependent parameters. Lmeter calculates inductance in a layout network, and with proper setup may also calculate resistance separately. Recently, InductEx was introduced to calculate multi-terminal network inductance in a superconductor structure with support for more complicated three-dimensional geometries. Here we present an improvement to InductEx that allows resistance, inductance and Josephson junction critical current extraction of a full superconducting digital logic gate or cell in a single execution, and in reasonable time. We show how InductEx was designed to operate on tape-out ready layouts, and through example how it is used for full-gate layout verification of contemporary logic cells.
distributions indicate mechanism changes A new perspective on paleopiezometry : Dynamically recrystallized grain size

The dynamically recrystallized grain size is a material parameter associated with dislocation creep of crystalline solids that is especially important as a fl ow stress indicator via piezometer calibrations. Grain sizes have been measured in many studies of deformed rocks as well as metals and ceramics, but global analyses of the frequency distribution of dynamically recrystallized grain sizes are lacking. Here we present the fi rst systematic investigation of the recrystallized grain size distribution, for quartz. The grain diameters, compiled from 555 samples of 31 studies of quartz mylonites deformed over a wide range of conditions, extend from ~3 μm to 3 mm, with distinct maxima at 10–20 μm and 70–80 μm, and minima at 35–40 μm and ~120 μm. The frequency maxima correlate with distinct microstructures and the minima with the transitions between these microstructures, which we interpret to result from the dominance of the recrystallization mechanisms of bulging, subgrain rotation, and grain boundary migration recrystallization. These results demonstrate the necessity of distinct piezometer calibrations for different recrystallization mechanisms and highlight the importance of the recrystallized grain size for theoretical models of dynamic recrystallization.
Nonlinear Subspace Clustering for Face Clustering

We present in this paper a nonlinear subspace clustering (NSC) method for face clustering. Unlike most existing subspace clustering methods which only exploit the linear relationship of samples to learn the a ﬃ ne matrix, our NSC reveals the multi-cluster nonlinear structure of samples via a nonlinear neural network. While kernel-based clustering methods can also address the nonlinear issue of samples, this type of methods su ﬀ ers from the scalability issue. Speciﬁcally, our NSC employs a feed-forward neural network to map samples into a nonlinear space and performs subspace clustering at the top layer of the network, so that the mapping functions and the clustering issues are iteratively learned. Otherwise, our NSC applys a similarity measure based on the grouping e ﬀ ect to capture the local structure of data. Experimental results illustrate that our NSC outperforms the state-of-the-arts.
Assessing Factoid Question-Answer Generation for Portuguese (Short Paper)

We present work on the automatic generation of question-answer pairs in Portuguese, useful, for instance, for populating the knowledge-base of question-answering systems. This includes: (i) a new corpus of close to 600 factoid sentences, manually created from an existing corpus of questions and answers, used as our benchmark; (ii) two approaches for the automatic generation of question-answer pairs, which can be seen as baselines; (iii) results of those approaches in the corpus. 2012 ACM Subject Classiﬁcation Computing methodologies → Natural language processing
Detection and analysis of plasmid-mediated ampC genes from Gram-negative clinical strains

Objective 200 Gram-negative organisms were tested for plasmid-mediated ampC genes by multiplex PCR. Methods Using six sets of primers to amplify DNA templates which were acquired by heating. The amplicons were differentiated by agarose electrophoresis. Results 6 of 200 strains were positive of plasmid-mediated ampC genes. Conclusions Multiplex PCR technique is a easy and quick method and shows high specificity for detecting plasmid-mediated ampC genes within Gram-negative organisms.
Student Proficiency with Transformational Geometry After a College Proof-Based Geometry Class

This report explores pre-service teachers’ proficiency with concepts of transformational geometry at the end of a semester-long advanced geometry course. During the course, the instructor presented transformational geometry content, including congruence proofs, in an attempt to align with the Common Core State Standards for Mathematics. At the end of the course, the students, all pre-service teachers, appeared to mix ideas from the traditional approach involving triangle congruence criteria (SAS, ASA, SSS, AAS) and transformational approaches, and struggled with conceiving of transformation functions as objects. These difficulties appear to compound in their proof-writing attempts such that after citing appropriate transformational geometry ideas, such as the angleor distance-preservation property, they would then supplement with congruence-based approaches in order to finish the proof. This has implications, especially for professional development, as this is the final mathematics class that these preservice teachers will take concerning transformational geometry prior to beginning their classroom instruction.
Adaptive Fuzzy Fast Finite-Time Tracking Control for Nonlinear Systems in Pure-Feedback Form with Unknown Disturbance

In this paper, based on the fast finite-time stability theorem, an adaptive fuzzy control problem is considered for a class of nonlinear systems in pure-feedback form with unknown disturbance. In the controller design process, the mean value theorem is applied to address the nonaffine structure of the pure-feedback plant, the universal approximation capability of the fuzzy logic system (FLS) is utilized to compensate the unknown uncertainties, and the adaptive backstepping technique is used to design the controller model. Combined with the selection of the appropriate Lyapunov function at each step, a fuzzy-based adaptive tracking control scheme is proposed, which ensures that all signals in the closed-loop system are bounded and tracking error converges to a small neighborhood of the origin in fast finite-time. Finally, simulation results illustrate the validity of the proposed approach.
Can the Accuracy of Clusters Determine their Developmental Stage in Children Using the Measure for Cluster Proximity (MCP)?

Children find it difficult to produce consonant clusters during their speech development. Cluster accuracy is widely measured by the proportion of clusters correct (PClC). However, this measure does not quantitatively identify developmental stages in clusters, that is, reduction, vowel epenthesis, or cluster production. The recently proposed measure for cluster proximity (MCP) achieves this by taking into account cluster member accuracy as well. The present study examines whether the aforementioned two measures, PClC and MCP, are correlated for word-final two-member clusters in child English speech. If they are correlated, cluster accuracy can then determine cluster developmental stages. Using thirty-one children’s speech samples, each sample comprising several word-final clusters at different developmental stages, it is found that MCP and PClC are strongly and significantly correlated across the children’s speech samples when classes of clusters or several different clusters are considered cumulatively.
DOMAIN-GENERAL AUDITORY PROCESSING EXPLAINS MULTIPLE DIMENSIONS OF L2 ACQUISITION IN ADULTHOOD

ABSTRACT In this study, we propose a hypothesis that domain-general auditory processing, a perceptual anchor of L1 acquisition, can serve as the foundation of successful post-pubertal L2 learning. This hypothesis was tested with 139 post-pubertal L2 immersion learners by linking individual differences in auditory discrimination across multiple acoustic dimensions to the segmental, prosodic, lexical, and morphosyntactic dimensions of L2 proficiency. Overall, auditory processing was a primary determinant of a range of participants’ proficiency scores, even after biographical factors (experience, age) were controlled for. The link between audition and proficiency was especially clear for L2 learners who had passed beyond the initial phase of immersion (length of residence > 1 year). The findings suggest that greater auditory processing skill benefits post-pubertal L2 learners immersed in naturalistic settings for a sufficient period of time by allowing them to better utilize received input, which results in greater language gains and leads to more advanced L2 proficiency in the long run (similar to L1 acquisition).
Assessment of drought tolerance in Nagina 22 mutants of rice using Poly Ethylene Glycol (PEG)

A laboratory experiment was conducted to screen 500 EMS induced mutants of Nagina22 using low molecular osmotic PEG-6000. The analysis of variance showed that all ten characters showed significant variation at 1% probability level. Nagina22 was screened under six moisture regimes as 0, -2, -4, -6, -8 and -10 bars of PEG-6000 and -6 bars was fixed as optimum concentration for mutant screening. Results of correlation revealed that relative seedling vigour showed positive significant correlation with all characters studied except root length stress index and relative root number. Based on PCA, emergence percentage, promptness index and seedling vigour was considered as selection criteria for selecting drought tolerant mutants under moisture stress. N22-PDT-17 and N22-PDT-64 recorded highest value for all the characters studied except number of roots than Nagina22. Hence, these two mutants were selected as better mutants with altered drought response and could be further validated under natural drought environment.