Miracle-dz/UniFAR-FTUs huggingface dataset:
New Light Curves and Orbital Period Investigations of the Interacting Binary System
 UV Piscium

UV Psc is a typical RS CVn type system undergoing dynamic chromosphere activity. We performed photometric observations of the system in 2015 and secured new BVR light curves showing well-defined photometric waves. In this paper, we analyzed the light curves using Wilson-Devinney binary code and investigated the orbital period of the system. The combination of our light curve synthesis with the spectroscopic solution developed by previous investigators yielded the absolute parameters as: M1 = 1.104 ± 0.042 Mⵙ, R1 = 1.165 ± 0.025 Rⵙ, and L1 = 1.361 ± 0.041 Lⵙ for the primary star, and M2 = 0.809 ± 0.082 Mⵙ, R2 = 0.858 ± 0.018 Rⵙ, and L2 = 0.339 ± 0.010 Lⵙ for the secondary star. The eclipse timing diagram for accurate CCD and photoelectric timings showed that the orbital period may vary either in a downward parabolic manner or a quasi-sinusoidal pattern. If the latter is adopted as a probable pattern for the period change, a more plausible account for the cyclic variation may be the light time effect caused by a circumbinary object rather than an Applegate-mechanism occurring via variable surface magnetic field strengths.
Modeling study of the onset density for divertor detachment on EAST

The onset density of detachment for L-mode discharges on Experimental Advanced Superconductiong Tokamamak has been studied using the SOLPS code. The effect of divertor closure on the onset density has been assessed by modifying the location of the strike point on a divertor plate. The modeling shows qualitative agreement with experiments in the density threshold. It is found that increasing divertor closure by moving the strike point close to the “V” corner can effectively trap neutrals in a localized region near the plasma strike point and then lower the density threshold of detachment. The influence of plasma current (Ip) on the onset density has also been investigated. The simulation shows that with Ip increased, divertor detachment was achieved at a relatively low normalized density due to the increase in Greenwald density (nG). In addition, the effect of the power across the scrape-off-layer (PSOL) and the radiation fraction on the detachment density threshold has also been studied. The detachment density increases significantly with PSOL as expected, and it can be approximately scaled by PSOL5/7, which is in accordance with the basic two-point model. It is also found that the detachment density can be reduced remarkably through increasing impurity radiative loss.The onset density of detachment for L-mode discharges on Experimental Advanced Superconductiong Tokamamak has been studied using the SOLPS code. The effect of divertor closure on the onset density has been assessed by modifying the location of the strike point on a divertor plate. The modeling shows qualitative agreement with experiments in the density threshold. It is found that increasing divertor closure by moving the strike point close to the “V” corner can effectively trap neutrals in a localized region near the plasma strike point and then lower the density threshold of detachment. The influence of plasma current (Ip) on the onset density has also been investigated. The simulation shows that with Ip increased, divertor detachment was achieved at a relatively low normalized density due to the increase in Greenwald density (nG). In addition, the effect of the power across the scrape-off-layer (PSOL) and the radiation fraction on the detachment density threshold has also been studied. The detachment de.
Reconfigurable metasurface with polarization-independent manipulation for reflection and transmission wavefronts

In this paper, we propose a real-time reconfigurable metasurface unit-cell working at dual-band with polarization-independent manipulation of reflection and transmission wavefronts. The transmission and reflection phases of the designed digital programmable active element can be dynamically adjusted by the states of the PIN diodes. The unit-cell can be designed to respond to different functions in different frequency bands, which makes it more flexible in radiation characteristics. Both the simulation and experiment show that the element can achieve good reconfigurable performances. This work offers a new method for real-time dynamic control of forward and backward electromagnetic wavefronts in the entire space.
PENERAPAN KEMOMETRIK PADA METODE CITRA DIGITAL UNTUK ANALISIS ION MERKURI (II) DENGAN INDIKATOR NANOPARTIKEL PERAK

Digital image method in quantitative analysis usually uses one of the RGB primary color components (Red, Green, Blue), so that not all digital image data can be extracted. Then needed a method that can render the whole RGB values as variables in quantitative analysis are known as chemometric. This research aims to know the influence of the application of chemometric against the sensitivity of the digital image. Chemometry method used is the Principal Component Regression (PCR) and Partial Least Square (PLS) using Unscramber X software from Camo software, USA. This method is applied for the quantitative analysis of Mercury (II) ion with silver nanoparticles (NPP) immobilization on filter paper indicator. The research results showed that chemometric has a good influence against the level of the Limit of Detection (LOD) of the digital image, where the level of LOD with chemometric application of the Principal Component Regression (PCR) is 0.4311 ppb, and Partial Least Square (PLS) is 0.4310 ppb smaller than without the application of chemometric Single Linear Regression (SLR) at 0.837 ppb.
Laparoscopic partial nephrectomy: initial experience

Introduction Partial nephrectomy is considered the gold standard procedure in managing small renal masses less than 4cm. Minimal invasive surgery is a alternative option in those cases. Laparoscopic partial nephrectomy has equivalent oncological results with open partial, offering in the same time all the advantages of minimal invasive surgery. The purpose of our study is to present our initial experience in laparoscopic partial nephrectomy. Material and Methods Between October 2012 and March 2014 , 9 selected patients with enhancing renal masses observed by CT scan, were submitted to laparoscopic partial nephrectomy . Patient demographics, preoperative tumor characteristics and detailed operative , postoperative and pathologic data were collected. Results 6 patients had a right partial nephrectomy and 3 a left one, with no intraoperative complications. In one patient a laparoscopic radical nephrectomy was done because of bleeding. The operation time ranged from 120 to 225 min, estimated blood loss (EBL) ranged from 30 to 300 ml and warm ischemia time (WIT) ranged from 15 to 42 min. One patient didn't require any hilar clamping. Overall, no transfusions were necessary and there were no intraoperative or major postoperative adverse events. One patient occurred with a small subcutaneous haematoma in a port side and another one with a slight transient haematuria which was resolved spontaneously. There was one patient with a microscopic positive surgical margin and all patients are disease free at the 6 month follow up Conclusion Laparoscopic partial nephrectomy is a safe and feasible approach in small renal masses, offering all the advantages of minimal invasive surgery
A general generative adversarial capsule network for hyperspectral image spectral-spatial classification

ABSTRACT A novel generative adversarial capsule network (Caps-GAN) model for hyperspectral image spectral-spatial classification is proposed in this Letter, which can effectively solve the scarce availability problem of annotated samples and improve classification performance. In the proposed method, a series of deconvolutional layers are utilized to generate fake samples as real as training samples with additional label information and 3D capsule network (CapsNet) is designed to discriminate the inputs, which can achieve higher classification performance than convolutional neural networks (CNNs) by considering spatial relationships in images. Furthermore, the generated samples with labels and training samples are put into discriminator for joint training, and the trained discriminator can determine the authenticity of input sample as well as the class label. This auxiliary conditional generative adversarial training strategy can effectively improve the generalization capability of the capsule network when labelled samples are limited. The Pavia University and Indian Pines images are used to evaluate the classification performance, and the overall accuracies of proposed method for these two datasets achieve and , respectively. The comparative experimental results reveal that the proposed model can improve the classification accuracy and provide competitive results compared with state-of-the-art methods, especially when there are few annotated samples.
Boundary Layer Quasi-Equilibrium Limits Convective Intensity Enhancement from the Diurnal Cycle in Surface Heating

A combination of cloud-permitting model (CPM) simulations, satellite, and reanalysis data are used to test whether the diurnal cycle in surface temperature has a significant impact on the intensity of deep convection as measured by high-percentile updraft velocities, lightning, and CAPE. The land–ocean contrast in lightning activity shows that convective intensity varies between land and ocean independently from convective quantity. Thus, a mechanism that explains the land–ocean contrast must be able to do so even after controlling for precipitation variations. Motivated by the land–ocean contrast, we use idealized CPM simulations to test the impact of the diurnal cycle on high-percentile updrafts. In simulations, updrafts are somewhat enhanced due to large-scale precipitation enhancement by the diurnal cycle. To control for large-scale precipitation, we use statistical sampling techniques. After controlling for precipitation enhancement, the diurnal cycle does not affect convective intensities. To explain why sampled updrafts are not enhanced, we note that CAPE is also not increased, likely due to boundary layer quasi equilibrium (BLQE) occurring over our land area. Analysis of BLQE in terms of net positive and negative mass flux finds that boundary layer entrainment, and even more importantly downdrafts, account for most of the moist static energy (MSE) sink that is balancing surface fluxes. Using ERA-Interim data, we also find qualitative evidence for BLQE over land in the real world, as high percentiles of CAPE are not greater over land than over ocean.
Analyzing Approximate Value Iteration Algorithms

In this paper, we consider the stochastic iterative counterpart of the value iteration scheme wherein only noisy and possibly biased approximations of the Bellman operator are available. We call this counterpart the approximate value iteration (AVI) scheme. Neural networks are often used as function approximators, in order to counter Bellman’s curse of dimensionality. In this paper, they are used to approximate the Bellman operator. Because neural networks are typically trained using sample data, errors and biases may be introduced. The design of AVI accounts for implementations with biased approximations of the Bellman operator and sampling errors. We present verifiable sufficient conditions under which AVI is stable (almost surely bounded) and converges to a fixed point of the approximate Bellman operator. To ensure the stability of AVI, we present three different yet related sets of sufficient conditions that are based on the existence of an appropriate Lyapunov function. These Lyapunov function–based conditions are easily verifiable and new to the literature. The verifiability is enhanced by the fact that a recipe for the construction of the necessary Lyapunov function is also provided. We also show that the stability analysis of AVI can be readily extended to the general case of set-valued stochastic approximations. Finally, we show that AVI can also be used in more general circumstances, that is, for finding fixed points of contractive set-valued maps.
Efficient $2\times2$ Printed Circuit Band-Gap Cavity-Backed Slot Antenna

In this article, a novel structure is proposed for the realization of cavity section in the printed gap waveguide (PGW) technology. For the proof of the concept, a multilayer cavity-backed slot antenna element is designed and fabricated so that its performance can be compared to the devices in the literature made by printed circuit board (PCB) technology and also by metal parts using the CNC machine. The proposed structure benefits from the advantages of efficient, low cost, simplified fabrication process, lightweight, and high aperture efficiency compared to common cavity-backed antennas. To manage the available space, the feed is connected to the antenna cavity from the underneath using a coupling aperture. The proposed configuration simplifies the integration of accessory devices in antenna arrays, such as feed networks, phase shifters, and amplifiers. Also, the separation of feed network from the radiation slot section prevents any unwanted radiation. Using the mode analysis, four slots were implemented in the proposed cavity to achieve four equivalent magnetic surface currents with identical phase and magnitude. The antenna operating frequency is 16 GHz, the realized antenna radiation and aperture efficiencies are over 92% and 81.6%, respectively, and its achieved gain is 12 dBi.
Brain Drain - Brain Circulation or ... What Else Happens or Should Happen to the Brains

The article provides a general introductory overview of the (spatial) mobility of highly skilled/qualified persons and discusses the different terms of the mobility of the Highly Skilled, especially those of scientists. It outlines theoretical and empirical aspects of these movements and delineates the drain of European talent to the U.S., especially the outflow of scientists and researchers who contribute considerably to the U.S. innovation system. Further, it takes a closer look at outward mobility in the former socialist countries in Europe, especially in South Eastern Europe, in the period before and after the fall of the Iron Curtain. Finally, the article outlines general policy options in dealing with the mobility of the Highly Qualified.
Global value chain mapping

A key element in conducting industrial organization research is establishing a clear, well-defined and repeatable process to identify and describe the stakeholders and concepts of the analysis across a range of industries and topics. In the global value chain (GVC) research approach, this is divided into two steps: value chain mapping (identifying who and where) and value chain analysis (what and why). This chapter focuses on mapping â€“ the process of identifying the structural elements along the value chain, including firms, products, activities and places. It includes steps and data sources to define the scope of an industry using a combination of international standardized classification systems and insights from existing research and fieldwork. The approach is presented using an industry-neutral value chain visual template along with industry-specific examples of how the process has been applied in existing GVC studies.
Adaptive‐optimal control under time‐varying stochastic uncertainty using past learning

An adaptive‐optimal control architecture is presented for adaptive control of constrained aerospace systems with matched uncertainties that are subject to dynamic stochastic change. The architecture brings together three key elements, ie, model predictive control–based reference command shaping, Gaussian process (GP)–based Bayesian nonparametric model reference adaptive control (MRAC), and online GP clustering over nonstationary GPs. Model predictive control optimizes reference model and its shaped output is passed into GP–based MRAC, which is used to learn the model in presence of significant time‐varying stochastic uncertainty while maintaining stability. Based on a likelihood ratio test, the changepoints are detected and learned. Lastly, the models are created and clustered by non‐Bayesian clustering algorithm. The key salient feature of our architecture is that not only can it detect changes but also it uses online GP clustering to enable the controller to utilize past learning of similar models to significantly reduce learning transients. Furthermore, persistence of excitation conditions are significantly relaxed due to the use of GP‐MRAC. Stability of the architecture is argued theoretically and performance is validated empirically on different scenarios for wing rock dynamics.
Electric Black Holes in a Model of Nonlinear Electrodynamics

The electric counterpart of the magnetic black hole solution found in nonlinear electrodynamics (NED) is presented. The electric field emerges regular and confined whereas the spacetime which satisfies all the energy conditions is singular. Our result is in conformation with a theorem proved before about the existence of regular electric black holes. The thermal properties of the black hole including the first law, Smarr's formula, and the thermal stability are investigated. This provides a chance to compare the electric and magnetic types of black holes in a particular model of NED.
A Personalized Feedback Mechanism Based on Bounded Confidence Learning to Support Consensus Reaching in Group Decision Making

Different feedback mechanisms have been reported in consensus reaching models to provide advices for preference adjustment to assist decision makers to improve their consensus levels. However, most feedback mechanisms do not consider the willingness of decision makers to accept these advices. In the opinion dynamics discipline, the bounded confidence model justifies well that in the process of interaction a decision maker only considers the preferences that do not exceed a certain confidence level compared to his own preference. Inspired by this idea, this article proposes a new consensus reaching model with personalized feedback mechanism to help decision makers with bounded confidences in achieving consensus. Specifically, the personalized feedback mechanism produces more acceptable advices in the two cases where bounded confidences are known or unknown, and the unknown ones are estimated by a learning algorithm. Finally, numerical example and simulation analysis are presented to explore the effectiveness of the proposed model in reaching consensus.
Coordinated Control of Underwater Biomimetic Vehicle–Manipulator System for Free Floating Autonomous Manipulation

This article presents a coordinated vehicle–manipulator control method for an underwater biomimetic vehicle–manipulator system (UBVMS) to implement floating autonomous manipulation in practice. An algorithm framework composed of adaptive tracking differentiator (ATD), extended state observer (ESO), improved nonsingular terminal sliding-mode control (I-NTSMC), fuzzy-logic controller (FLC), and estimator of manipulator disturbances, is proposed. The ATD is designed to generate desired motion state and alleviate noise. The ESO is developed to estimate the motion state, systematic uncertainties, and external disturbances. The proposed I-NTSMC method assures the finite-time convergence of the system states and alleviate chattering. The estimation of the manipulator disturbances is incorporated into the control strategy to enhance the station keeping of the vehicle. Finally, underwater autonomous free floating manipulation experiments about opening a door and grasping objects are conducted to validate the theoretical results and confirm the feasibility of the proposed control strategy.
Performance evaluation of some propensity score matching methods by using binary logistic regression model

Abstract The unit selection bias in treatment and control group affects negatively in evaluation of treatment effects. In some studies, the random units selected for the treatment and control group are out of control of the researcher and there may be differences between the units under consideration. This will cause the estimates obtained to be biased. Propensity score matching (PSM) has been used to reduce bias in estimation of treatment effect in observational data. Therefore, nearest neighbor (1:1), caliper, stratification, mahalanobis metric, full and combining propensity score and mahalanobis metric matching, which have been widely used as PSM methods, were compared in terms of the correct classification rates conducting a detailed Monte Carlo simulation study. In addition, standardized and percent reduction bias of covariates were evaluated for each of the PSM methods. It is suggested that stratification and full matching methods should be considered to study with high correct classification rate whereas caliper matching method should be prefered due to the low bias to make statistical inferences.
The Nature of the Triangulum-Andromeda Stellar Structures

Abstract The outer stellar halo is home to a number of substructures that are remnants of former interactions of the Galaxy with its dwarf satellites. Triangulum-Andromeda (TriAnd) is one of these halo substructures, found as a debris cloud by Rocha-Pinto et al., (2004) using 2MASS M giants. Would be these structures related to dwarf galaxies or to the galactic disk? To uncover the nature of these stars we performed a high-resolution spectroscopic study (R = 40,000) along with a kinematic analysis using Gaia data. We determined the atmospheric parameters and chemical abundances of Ca and Mg for the 13 TriAnd candidate stars along with their respective orbits. Our results indicate that the TriAnd stars analyzed have a galactic nature but that these stars are not from the local thin disk.
A Tri-Band Shared-Aperture Antenna for (2.4, 5.2) GHz Wi-Fi Application With MIMO Function and 60 GHz Wi-Gig Application With Beam-Scanning Function

This article presents the design and the realization of a tri-band shared-aperture antenna operating at 2.4, 5.2, and 60 GHz. It puts these three bands of antennas within the same radiating aperture and then realizes the Wi-Fi application with MIMO function and the Wi-Gig application with beam-scanning function simultaneously. It consists of two dual-band printed inverted-F antennas (PIFAs) and two SIW leaky wave antennas. By using the structure-reused technology, PIFA for the Wi-Fi application and the SIW antenna for the Wi-Gig application can share the same radiator without adding an extra aperture area. Thus, the ratio of the radiating aperture utilization can be improved greatly. In addition, MIMO technology is also applied to the Wi-Fi antenna design. The envelope correlation coefficients (ECCs) calculated from the simulated and measured data are all lower than 0.04. The measured radiation efficiencies are 74% to 95% and 76% to 95% within these two bands, respectively. Moreover, due to the optimal layout of the whole design, the Wi-Gig antenna can obtain high gain and wide range of beam coverage at the same time. The measured peak gain is 12.29 dBi, and the beam coverage is ±36° from 57 to 64 GHz.