Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonal stratification of the upper ocean salinity stratification in the Tropics

In comparison to the deep ocean, the upper mixed layer is a region typically characterized by substantial vertical gradients in water properties. Within the Tropics, the rich variability in the vertical shapes and forms that these structures can assume through variation in the atmospheric forcing results in a differential effect in terms of the temperature and salinity stratification. Rather than focusing on the strong halocline above the thermocline, commonly referred to as the salinity barrier layer, the present study takes into account the respective thermal and saline dependencies in the Brunt-V€ais€al€a frequency (N) in order to isolate the specific role of the salinity stratification in the layers above the main pycnocline. We examine daily vertical profiles of temperature and salinity from an ocean reanalysis over the period 2001–2007. We find significant seasonal variations in the Brunt-V€ais€al€a frequency profiles are limited to the upper 300 m depth. Based on this, we determine the ocean salinity stratification (OSS) to be defined as the stabilizing effect (positive values) due to the haline part of N averaged over the upper 300 m. In many regions of the tropics, the OSS contributes 40–50% to N as compared to the thermal stratification and, in some specific regions, exceeds it for a few months of the seasonal cycle. Away from the tropics, for example, near the centers of action of the subtropical gyres, there are regions characterized by the permanent absence of OSS. In other regions previously characterized with salinity barrier layers, the OSS obviously shares some common variations; however, we show that where temperature and salinity are mixed over the same depth, the salinity stratification can be significant. In addition, relationships between the OSS and the sea surface salinity are shown to be well defined and quasilinear in the tropics, providing some indication that in the future, analyses that consider both satellite surface salinity measurements at the surface and vertical profiles at depth will result in a better determination of the role of the salinity stratification in climate prediction systems.
Compact Variable Stiffness Joint with Force Sensing Ability-Application to Classify Contact Surfaces

This paper describes a new compact variable stiffness joint mechanism. This mechanism is so small as to be embedded into the finger joint of a human-sized robotic hand. In the mechanism, a silicone rubber cushion, which is inserted between the motor and the output link is effectively used to adjust the joint stiffness and to sense external forces. The joint stiffness can be controlled by restricting the degree of cushion deformation with a cushion support wall (CS-wall) actuated by a pneumatic system. However, the joint stiffness is adjusted to only the lowest or highest level, because of the difficulties of achieving precise position control of the CS-wall by the pneumatic system. Conversely, the detection of external forces shows good performance. The change in the pressure inside the cushion provides information on the external forces applied to the link. We applied this function to measure the friction force between the robotic finger and the object, and attempted to determine differences in the friction force among twelve types of objects. The experimental results show that the mechanism is able to determine differences in the friction force and its oscillation between the objects. We confirmed that this ability can be used to classify objects. 
Application of Bayesian Co-clustering Methods in Healthcare Fraud Detection

We investigate the utilization of Bayesian co-clustering methods to identify fraud in healthcare insurance systems. Bayesian co-clustering (BCC) algorithm is employed in order to detect the visiting patterns among healthcare users and providers. It involves assignment of each provider-user pair to a co-cluster while allowing mixed membership for any provider and user. Upon completion of this analysis, we have the likelihood of belonging to a given co-cluster for each provider and user. The providers who are found to have a high probability of sharing users with an unusual set of providers are flagged to be investigated for potential fraudulent activity.
The Moderating Effect of the CEO Duality towards the Influence of the Ownership Structure on the Firm Performance among Jordanian Public Shareholders Companies

Previous studies that dealt with corporate governance mechanisms have testified high significant that created some new direction. The current study aims to be engaged in such trends through investigating the relationship between ownership structure as one of the corporate governance mechanisms and performance of the firm with the presence of moderating variable which is CEO duality in developing countries such as Jordan. This study used the panel data method to analyze data for a sample of 180 companies listed on the Amman Stock Exchange (ASE) for the period from 2009 to 2017. Three variables of ownership structure are employed, which are:managerial ownership, government ownership, and family ownership, and moderating variable is CEO duality. The current study used Tobin’s Q to estimate the performance of the firm. The findings show that the ownership structure mechanisms have a significant influence on firm performance measured by (TQ). Where managerial ownership and family ownership shows a significant negative relationship with (TQ). While government ownership shows a significant positive relationship with (TQ). On other hands, moderating effect of CEO duality has a significant positive on the relation between family ownership with (TQ), and has a significant negative on the relationship between managerial ownership and government ownership with (TQ). The findings of this study confirm empirical research continuing to find a new performance measurement to gain a real form of firm performance. Therefore, the evidence of this study provides empirical evidence to stakeholders, managers and interested parties to support them for its decision. Keyword: Corporate Governance, Ownership Structure, CEO Duality, Firm Performance. International Journal of Academic Research in Progressive Education and
Porous polymeric monoliths: design and preparation towards environmental applications

Polymeric monoliths are porous substrates comprised of suitable monomer(s) beside a crosslinking agent and a radical initiator. The polymerization reaction may be thermally or radiation initiated in a mold. They take the shape of continuous rods or columns upon preparation. These materials are porous substrates used to overcome some deficiencies that arose from using the corresponding traditional monoliths such as ceramic and metallic ones. Increasing the efficiency of the monolith can be achieved via grafting the surface. Functional groups on the monolithic surface can be introduced to boost the performance of the monolith. Immobilizing nanoparticles; mainly the metallic ones onto the surface of the polymeric monolith enhances the efficiency of these columns and expands their application fields. Depositing the metal nanoparticles takes place via in-situ reduction of metal nanoparticles from their precursor salts or via ex-situ loading of previously prepared nanoparticles. There are various applications for polymeric monoliths; separation of proteins, small and large molecules can be mentioned. Monoliths are used in chromatographic separation applications beside catalytic implications. These monoliths represent the stationary phase. For expanding the separation application, polymeric monoliths can be applied in electrochromatographic separations. Besides, catalytic reactions can take place inside these monolithic rods.
The Effect of Location on the Structure and Mechanical Properties of Selective Laser Melted 316 L Stainless

Additive Manufacturing (AM) has significantly increased the design freedom available for metal parts and provides flexibility within each build to produce multiple components of varying size and shape. In order to obtain the highest build efficiency, it is ideal to print multiple parts together spanning the entire plate, with as little spacing as possible between the parts. Work has been performed to characterize the variance of materials properties as a function of location within the build volume. This work utilizes mechanical, chemical, and structural analysis techniques to expand on previous work by statistically evaluating the impact of build location on tensile performance in Selective Laser Melting (SLM). Results show that properties span a small range regardless of build design. Specific effects of cover gas convection, location, and build length are observed and evaluated. Finally, sub-grain misorientation values are correlated to material strength through Electron Back Scatter Diffraction (EBSD).
A coupled Discrete Element Method and Finite Volume Method for the simulation of elastic fishnets in interaction with fluid .

Several devices and manmade structures interact dynamically with fluids such as water and air, behaving essentially as flexible elastic systems with large deformations and undergoing complex dynamics. The design and analysis of the configurations that these devices may acquire under different flow conditions can be carried out using numerical modeling tools. This paper presents the implementation of a Discrete Element Method (DEM) coupled with a Finite Volume Method (FVM) to represent the bi-directional dynamic interaction of flexible elastic systems with fluids, and its application to fishnets.
The Story of Logic – CS/Math 4860 Class Notes Fall 2019

These brief notes on the history of logic are meant to be an easily understood basis for stating briefly and informally some of the great ideas in logic. Appreciating how the basic concepts were discovered and why they were needed is an accessible basis for a technical understanding of these concepts. For many students, this historical approach has been a route by which they have come to deeply understand and appreciate logic.
High-sensitivity and Low-cost Optical Transceiver for Passive Optical Network Systems

We have developed a burst-mode optical transceiver for gigabit-per-second-class passive optical network (PON) systems using receiver integrated circuits (ICs) that exhibit high sensitivity with a low-cost PIN-photodiode (positive-intrinsic-negative photodiode (PIN-PD)). This transceiver enables us to construct a low-cost PON system with high quality. High-sensitivity and Low-cost Optical Transceiver for Passive Optical Network Systems † NTT Photonics Laboratories Atsugi-shi, 243-0198 Japan Email: nakamura@aecl.ntt. co.jp Tx module (TOSA) WDM filter BIDI Single-mode optical fiber Output optical signal (λ1) Input optical signal (λ2) Rx module (ROSA) Rx optical signal Tx optical signal Amplifier LD driver Tx data input
Chemical Characteristics of Solfataric-Acidic Pond Waters in the Kirishima Geothermal Area , Kagoshima Prefecture

The biosphere in terrestrial, highly acidic hot springs is composed solely of chemotrophic prokaryotic communities. The major environmental factors affecting these organisms are expected to be temperature and chemical composition. The Kirishima geothermal area surrounding the Kirishima volcano in Japan, in which highly acidic hot springs occur, was selected as the study area. Water samples were collected from 21 ponds and the temperature and pH of these samples were measured. The amount of 21 elements (Li, Na, Mg, Al, Si, P, S, K, Ca, Cr, Mn, Fe, Ni, Cu, Zn, As, Rb, Sr, Cd, Cs, and Pb) was quantified using inductively coupled plasma atomic emission spectroscopy. The temperature, pH, and total concentrations of measured chemical components were 63-94°C, 1.8-4.0, and 3.1-82 mmol L, respectively. Major elements common to all pond waters were S and Si. Calculation of Pearson’s correlation coefficients to clarify the relationships between the environmental factors demonstrated that several chemical components showed significant linear relationships with each other. For example, Fe was strongly correlated with S, Al, P, and Rb, and S was strongly correlated with Al, Mg, P, Rb, and Cs. The total concentration of the measured chemical components was also strongly correlated with six elements (Fe, S, Al, Mg, P, Rb, and Cs). Conversely, pH was strongly correlated with Ca, Na, and As, and temperature was statistically correlated with Mg and Cs. Based on the high factor loadings observed between these elements and temperature, the 21 water samples in the highly acidic hot ponds within the Kirishima geothermal area were chemically classified using principal component analysis. The hot springs could be separated on the basis of differing values of principal component 1 (PC1), which was most strongly influenced by the concentrations of eight elements (Fe, S, Al, Mg, P, As, Rb, and Cs) and principal component 2 (PC2), which was mainly controlled by temperature. The springs were classified into four types : hot springs with relatively high values of both PC1 and PC2 (Type A) ; hot springs with relatively high PC1 and relatively low PC2 (Type B) ; hot springs with relatively low PC1 and relatively high PC2 (Type C) ; and hot springs with relatively low values of both PC1 and PC2 (Type D). The new information obtained in this study on the chemical characteristics of these volcanic, highly acidic hot springs will be helpful for understanding the relationships of the diverse prokaryotic communities that inhabit the solfataric-acidic hot-spring ecosystem.
A Novel Recognition of Indian Bank Cheque Names Using Binary Pattern and Feed Forward Neural Network

Automatic processing of bank cheques is getting more popularity and attracting more researchers. This paper proposes an efficient machine leaning techniques to design and develop an algorithm to read and recognize the nationalized Indian bank cheques using optical character recognition technique, in which binary patterns extracted by applying classification level decision using feed forward artificial Neural network(NN). In the proposed methodology the neural network is trained to classify six standard nationalized Indian bank cheques. The accuracy of the system is analyzed by the invariant features such as different font, size and varieties of characters with noise and the experimental results reveal satisfactory result.
Quantum dynamics of biomolecular systems in noisy environments

We discuss three different aspects of the quantum dynamics of bio-molecular systems and more generally complex networks in the presence of strongly coupled environments. Firstly, we make a case for the systematic study of fundamental structural elements underlying the quantum dynamics of these systems, identify such elements and explore the resulting interplay of quantum dynamics and environmental decoherence. Secondly, we critically examine some existing approaches to the numerical description of system-environment interaction in the non-perturbative regime and present a promising new method that can overcome some limitations of existing methods. Thirdly, we present an approach towards deciding and quantifying the non-classicality of the action of the environment and the observed system-dynamics. We stress the relevance of these tools for strengthening the interplay between theoretical and experimental research in this field.
Trans-Spinal Direct Current Stimulation in Incomplete Spinal Cord Injury Subjects: Analysis of Motor Unit Activity for a New Class of Biomarkers

Electrophysiological changes after trans-spinal direct current stimulation (tsDCS) in incomplete spinal cord injury (SCI) subjects are not well understood. Presumably, cathodal tsDCS facilitates motor function after stimulation is administered in healthy subjects. The aim of this study is to investigate motor unit (MU) features that help describe the effects of tsDCS on incomplete SCI subjects. Based on the data of the double-blind, sham-controlled crossover study of Kuck et al., neural activity of the soleus muscle from one chronic, incomplete SCI subject was analyzed in time and frequency domain. The protocol recorded high density-electromyography (HD-EMG) during plantar flexion sub-maximal contractions before and just after cathodal and sham tsDCS (2.5 mA, 15 min). In frequency domain, several features were obtained from the coherence between two cumulative spike trains (CSTs), which were generated from sets of single motor units (MUs). The coherence peaks and areas of the delta band (0-5 Hz) showed a decrease after cathodal tsDCS and no effect after sham tsDCS. This suggests that cathodal tsDCS decreases the strength of the common drive, which is likely due to an enhanced afferent feedback as secondary common synaptic input. Supporting this hypothesis, it was also found that the number of MUs in the CSTs reaching a plateau in coherence was greater after cathodal tsDCS. In time domain, a decrease in the cross-correlation peaks between smoothed CSTs confirmed the decrease in strength of the common drive found in frequency domain. Moreover, the coefficient of variation of the smoothed CSTs indicated a possible increase in steadiness (decrease in fluctuations) after cathodal tsDCS and no change after sham tsDCS. However, the coefficient of variation of the first common component (FCC, first principal component) as well as the average discharge rate did not reveal any change. The present study provides a novel MU-based analysis of the effects of cathodal tsDCS on lower limb motor impairment due to incomplete SCI. At a later stage, these findings may lead to robust biomarkers for a closed-loop modulation of the corticospinal excitability.
Assessing Patients ’ Understanding , Provider ’ s Participatory Decision-Making , and Communication among Type 2 Diabetic Patients and Their Impact on Diabetes Self-Management in Qatar ’ s Primary Healthcare Centers

People with diabetes are responsible for most day-to-day decisions related to the management of their disease, making self-directed health care a large part of diabetes management. Historically, the management of diabetes was primarily the responsibility of providers. More recently, however, patient-centered care and comprehensive team approaches have gained attention, with endocrine clinics providing care through a multidisciplinary team that includes a diabetes educator [2]. In fact, many studies, such as the Regimen adherence questionnaire and the Johnson, et al. 24-h recall interview, have revealed that Diabetes Self-Management Education (DSME) is a critical element of care in order to improve patient outcomes [3].
Title Cortical abnormalities in youth at clinical high-risk for psychosis : Findings from the NAPLS 2 cohort

In a recent machine learning study classifying “brain age” based on cross-sectional neuroanatomical data, clinical high-risk (CHR) individuals were observed to show deviation from the normal neuromaturational pattern, which in turn was predictive of greater risk of conversion to psychosis and a pattern of stably poor functional outcome. These effects were unique to cases who were between 12 and 17 years of age when their prodromal and psychotic symptoms began, suggesting that neuroanatomical deviance observable at the point of ascertainment of a CHR syndrome marks risk for an early onset form of psychosis. In the present study, we sought to clarify the pattern of neuroanatomical deviance linked to this “early onset” form of psychosis and whether this deviance is associated with poorer premorbid functioning. T1 MRI scans from 378 CHR individuals and 190 healthy controls (HC) from the North American Prodrome Longitudinal Study (NAPLS2) were analyzed. Widespread smaller cortical volume was observed among CHR individuals compared with HC at baseline evaluation, particularly among the younger group (i.e., those who were 12 to 17 years of age). Moreover, the younger CHR individuals who converted or presented worsened clinical symptoms at follow-up (within 2 years) exhibited smaller surface area in rostral anterior cingulate, lateral and medial prefrontal regions, and parahippocampal gyrus relative to the younger CHR individuals who remitted or presented a stable pattern of prodromal symptoms at follow-up. In turn, poorer premorbid functioning in childhood was associated with smaller surface area in medial orbitofrontal, lateral frontal, rostral anterior cingulate, precuneus, and temporal regions. Together with our prior report, these results are consistent with the view that neuroanatomical deviance manifesting in early adolescence marks vulnerability to a form of psychosis presenting with poor premorbid adjustment, an earlier age of onset (generally prior to the age of 18 years), and poor long-term outcome. https://doi.org/10.1016/j.nicl. 2019.101862 Received 28 December 2018; Received in revised form 1 April 2019; Accepted 19 May 2019 ⁎ Corresponding author at: Department of Psychology, 2 Hillhouse Avenue, New Haven, CT 06511, United States. E-mail address: tyrone.cannon@yale.edu (T.D. Cannon). NeuroImage: Clinical 23 (2019) 101862 Available online 23 May 2019 2213-1582/ © 2019 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). T
A Fourier-Mellin based Equalization Technique for Wideband Linear Time Varying Channels

We wish to suggest a novel equalization technique for wideband linear time varying channels. Motivated from the mammalian auditory system, the central idea behind the equalization strategy is a combination of Mellin and Fourier transforms which is able to compensate the concurrent Doppler and delay spread introduced by the channels. The proposed method does not require large memory usually associated with the buffering process in conventional approach while being computationally attractive simultaneously. Mathematical development of the proposed system is presented along with simulations demonstrating the effectiveness of the same. Keywords—Wideband Channels; Mellin Transform; Channel Equalization; Underwater Acoustic Communication; Bio-Inspired
Tagging child-adult interactions in naturalistic, noisy, daylong school environments using i-vector based diarization system

Assessing child growth in terms of speech and language is a crucial indicator of long term learning ability and life-long progress. Since the preschool classroom provides a potent opportunity for monitoring growth in young children’s interactions, analyzing such data has come into prominence for early childhood researchers. The foremost task of any analysis of such naturalistic recordings would involve parsing and tagging the interactions between adults and young children. An automated tagging system will provide child interaction metrics and would be important for any further processing. This study investigates the language environment of 3-5 year old children using a CRSS based diarization strategy employing an i-vector-based baseline that captures adult-to-child or child-to-child rapid conversational turns in a naturalistic noisy early childhood setting. We provide analysis of various loss functions and learning algorithms using Deep Neural Networks to separate child speech from adult speech. Performance is measured in terms of diarization error rate, Jaccard error rate and shows good results for tagging adult vs children’s speech. Distinction between primary and secondary child would be useful for monitoring a given child and analysis is provided for the same. Our diarization system provides insights into the direction for pre-processing and analyzing challenging naturalistic daylong child speech recordings.