Miracle-dz/UniFAR-FTUs huggingface dataset:
A Generalized and Mode-adaptive Approach to the 2 Power Flow Analysis of the Isolated Hybrid AC / DC 3

Abstract: HybridAC/DC microgrids(HMG) are emerging as an attracting method for integrating 12 the AC/DC distributed energy resources(DERs) with the features of high-performance and low13 cost. In the isolated hybrid AC/DC microgrid (IHMG),the key problem is how to balance the power 14 variation and regulate the voltage and frequency. Various energy storage systems (ESS)and 15 interlinking converter (IC) technologies are viable for this application. The present study proposes a 16 novel unified power flow model to evaluate and compare the abilities of the ESS with different 17 connection topologies and ICs with different control approaches to maintain the voltage and 18 frequency stability of the IHMG. In order to investigate the performance of the proposed scheme, 19 five operation modes of the IHMG are defined and explained. The classification is based on the 20 connection topologies and control modes of the ESS/IC in the IHMG. Then, a set of generic PF 21 equations are derived. Moreover, three binary matrices are applied in the construction of the 22 unified power equations. These matrices are used for describing the running state of the IHMG. 23 Finally, in order to verify the proposed scheme, it is applied to several case studies of the IHMG. 24 The operation characteristics of multi-DC subgrids IHMG in different modes, particularly when an 25 external disturbance occurs, are investigated. 26
On Theorem 6 in “ Relative Entropy and the Multivariable Multidimensional Moment Problem ” [ Mar 2006 1052-1066 ]

Matrix-valued covariance extension and multivariate spectral estimation are formulated as generalized moment problems in the “THREE” approach and its extensions. Under this context, we discuss Theorem 6 in [1] concerning the bijectivity of a moment map defined over a parametric family of spectral densities. In particular, we provide a counterexample in which the moment map under consideration is shown to have a critical point, namely a point at which the Jacobian loses rank. Then with standard techniques in bifurcation theory, we conclude further that the computed critical point is a bifurcation point, which means that the moment map is not injective.
Soil tillage and crop rotation differently affect biodiversity and species assemblage of ground beetles inhabiting winter wheat fields

This paper continues studies on ground beetles (Carabidae) in differently managed winter wheat (Triticum aestivum) fields in Latvia. The main task of those studies was to assess how different soil tillage regimes (ploughing and non-inverse tillage) and different pre-crops (winter wheat and spring rapeseed (Brassica napus) affect assemblage and biodiversity of ground beetles in winter wheat fields. The research was carried out in the Latvia University of Agriculture Research and Study Farm ‘Pēterlauki’ (56°30’39.38’’N; 23°41’30.15’’E) during vegetation season of 2013. The results were compared with the results of similar research carried out at the same place during 2012. Totally 57 ground beetle species were observed in studied fields in 2013. Total species assemblage varied between both consecutive vegetation seasons of the research, however these were minor differences not connected with studied agro-ecological factors. Dominance structure of ground beetle species was significantly different between both vegetation seasons – species which were dominant and subdominant in 2012 became subdominant and dominant one year later, accordingly. Annual effects of soil tillage regime and pre-crop on ground beetle dominance structure also were observed, however some differences were recognized between both vegetation seasons. In case, if weed control was successful, higher ground beetle biodiversity might be observed in ploughed fields pre-cropped with spring rapeseed. Otherwise, significantly higher ground beetle biodiversity may be observed in harrowed soil independently from the pre-crop.
Learning Data Structure Alchemy

We propose a solution based on ﬁrst principles and AI to the decades-old problem of data structure design. Instead of working on individual designs that each can only be helpful in a small set of environments, we propose the construction of an engine, a Data Alchemist, which learns how to blend ﬁne-grained data structure design principles to automatically synthesize brand new data structures
irm size , ownership structure , and systematic liquidity risk : The case f an emerging market

Previous studies support the hypothesis that institutional ownership leads to an enhanced systematic liquidity risk by increasing the commonality in liquidity. By using a proprietary database of all incoming orders and ownership structure in an emerging stock market, we show that institutional ownership leads to an increase in commonality in liquidity for midto-large cap firms; however, only individual ownership can lead to such an increase for small cap firms, revealing a new source of systematic liquidity risk for a specific group of firms. We also reveal that commonality decreases with the increasing number of investors (for both individual and institutional) at any firm size level; suggesting that as the investor base gets larger, views of market participants become more heterogeneous, which provides an alternative way to decrease the systematic liquidity risk. © 2017 Elsevier B.V. All rights reserved.
Characterization of Toll-like Receptor 7 / 8 Agonist Amino Acid for Antigen-Adjuvant Conjugation Co-delivery System

Purified or synthetic antigens including peptides require adjuvant molecules to improve vaccine immunogenicity. Toll-like receptors (TLRs) agonists are powerful vaccine adjuvant candidates. A wide variety of TLR agonists have been studied for the development of antigenadjuvant co-delivery systems. The covalent conjugation between antigen and TLR agonist is one of promising strategies to deliver to target cells. Recently we have reported the development of novel TLR7/8 agonist amino acids. In this paper, we will describe the contribution of antigen–adjuvant conjugation using a TLR7/8 agonist amino acid to antigen-specific immune responses regarding IgG isotype distribution and cytokine production.
Generation Y Employees: The role of Psychological Empowerment on the Relationship between Emotional Intelligence and Interpersonal Citizenship Behaviors

The present study aims to propose and test an integrative model that considers the mediating effects of Generation Y employees’ psychological empowerment (PE) on the relationships between their emotional intelligence (EI) and interpersonal citizenship behaviors (ICB). The model was tested on a sample of 477 Generation Y employees working in IT sector. For the indicators of employees’ EI, Wong and Law’s model, involving ‘self-emotion appraisal’, ‘others’ emotional appraisal’, ‘use of emotion’ and ‘regulation of emotion’, has been applied in the study. Hierarchical regression analyses postulated that EI and ICB were mediated by PE. The relationships between use of emotion and ICB were fully mediated by PE, while the relationships between self-emotion appraisal, others’ emotional appraisal and regulation of emotion and ICB were partially mediated by PE. The findings indicate that organizations should focus more on enhancing PE of Generation Y employees, which is the underlying effect between their EI and ICB.
Energy Market Integration in China : Evidence from Panel Unit Root and Panel Cointegration Tests

The paper tests for energy price co-movement in China over the past decade as part of a strategy to identify the existence of a national energy market. Test results suggest that not all energy commodities are spatially homogenous in prices and the processes of energy price cointegration are different over time and over fuel sources, demonstrating China’s gradual, spatially partial and idiosyncratic energy reform process. Coal and electricity price series have co-moved since 2000, while the national panel cointegration test statistics suggest that gasoline and diesel price series have co-moved since 1997. Regional panel tests also show that there are apparent differences in the emergence of energy price co-movement. This may mean that regional energy markets have emerged in China. One of the important lessons of the research is that an energy market has, to some extent, already emerged in China and, as a consequence, energy prices are much less distorted than previously. If correct, this fact is of major, global, significance both in terms of future environmental effects and future trade and investment negotiations as China is seen internationally as a ‘market driven economy’.
Workflow and Metadata Quality at Springer Nature

Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in online libraries. For this reason, Springer Nature, the world's largest academic book publisher, has traditionally entrusted this task to their most expert editors. These editors manually analyse all new books, possibly including hundreds of chapters, and produce a list of the most relevant topics. Hence, this process has traditionally been very expensive, time-consuming, and confined to a few senior editors. For these reasons, back in 2016 we developed Smart Topic Miner (STM), an ontology-driven application that assists the Springer Nature editorial team in annotating the volumes of all books covering conference proceedings in Computer Science. Since then STM has been regularly used by editors in Germany, China, Brazil, India, and Japan, for a total of about 800 volumes per year. Over the past three years the initial prototype has iteratively evolved in response to feedback from the users and evolving requirements. In this paper we present the most recent version of the tool and describe the evolution of the system over the years, the key lessons learnt, and the impact on the Springer Nature workflow. In particular, our solution has drastically reduced the time needed to annotate proceedings and significantly improved their discoverability, resulting in 9.3 million additional downloads. We also present a user study involving 9 editors, which yielded excellent results in term of usability, and report an evaluation of the new topic classifier used by STM, which outperforms previous versions in recall and F-measure.
Soil carbon sequestration in a pine forest after 9 years of atmospheric CO 2 enrichment

The impact of anthropogenic CO2 emissions on climate change may be mitigated in part by C sequestration in terrestrial ecosystems as rising atmospheric CO2 concentrations stimulate primary productivity and ecosystem C storage. Carbon will be sequestered in forest soils if organic matter inputs to soil profiles increase without a matching increase in decomposition or leaching losses from the soil profile, or if the rate of decomposition decreases because of increased production of resistant humic substances or greater physical protection of organic matter in soil aggregates. To examine the response of a forest ecosystem to elevated atmospheric CO2 concentrations, the Duke Forest Free-Air CO2 Enrichment (FACE) experiment in North Carolina, USA, has maintained atmospheric CO2 concentrations 200 lL L 1 above ambient in an aggrading loblolly pine (Pinus taeda) plantation over a 9-year period (1996–2005). During the first 6 years of the experiment, forest-floor C and N pools increased linearly under both elevated and ambient CO2 conditions, with significantly greater accumulations under the elevated CO2 treatment. Between the sixth and ninth year, forest-floor organic matter accumulation stabilized and C and N pools appeared to reach their respective steady states. An additional C sink of 30 g C m 2 yr 1 was sequestered in the forest floor of the elevated CO2 treatment plots relative to the control plots maintained at ambient CO2 owing to increased litterfall and root turnover during the first 9 years of the study. Because we did not detect any significant elevated CO2 effects on the rate of decomposition or on the chemical composition of forest-floor organic matter, this additional C sink was likely related to enhanced litterfall C inputs. We also failed to detect any statistically significant treatment effects on the C and N pools of surface and deep mineral soil horizons. However, a significant widening of the C : N ratio of soil organic matter (SOM) in the upper mineral soil under both elevated and ambient CO2 suggests that N is being transferred from soil to plants in this aggrading forest. A significant treatment time interaction indicates that N is being transferred at a higher rate under elevated CO2 (P 5 0.037), suggesting that enhanced rates of SOM decomposition are increasing mineralization and uptake to provide the extra N required to support the observed increase in primary productivity under elevated CO2.
Mindfulness for Optimal Performance for Musicians

Mindfulness Abstract This paper is a presentation of my creative thesis for the pursuit of my Mindfulness Studies master’s degree from Lesley University. To enhance focus, boost compassion, and support optimal performance states, this work focuses on the potential benefits of teaching concentration, relaxation, and compassion meditations--and other mindfulness techniques--to professional adult musicians who often suffer from stress, performance anxiety, and self-criticism. Included in this thesis is a literature review on that topic, an explanation of gaps noted in this field of research, a discussion explaining the rationale for how the literature review has informed the creation of an eight-week mindfulness course for professional adult musicians, concluding thoughts, and a list of works cited. The findings of the literature review suggest that mindfulness practices could be valuable for enhancing optimal performance states in professional adult musicians by reducing stress and self-criticism, and enhancing concentration, relaxation, and self-compassion. Therefore, it is concluded that this topic should be studied further; the creation of the Student’s Manual and Teacher’s Guide for a Mindfulness for Optimal Performance for Musicians course nudges this finding towards a deliverable program.
Vision Calibration for Industrial Robots An Approach using Cognex VisionPro

Most manufacturing processes rely upon the use of industrial robot arms for different applications, such as inline robotics, system assembly robotics and machine tending robotics. In the pursuit of the highest industrial quality standards, accuracy, precision, flexibility and a larger potential to increase the competitiveness in the market, some industrial robot cells make use of vision sensors. These vision sensors and cameras are used to guide the robot cells in pick and place, perform measurements and other applications. In order to successfully execute these tasks, there is the need to relate the cameras’ 2D projections with 3D positions of the robot’s coordinate system, which can only be done after a calibration process. This master thesis project’s main focus is to develop a standard application capable of automatically calibrating the cameras in the robot’s workspace, by estimating their exact position and orientation with respect to the robot, while also compensating for the non-linear distortion of its lenses. At the same time, 3D tools are proposed and introduced. The developed calibration procedures not only show an improvement in typical applications up to 11 times, when comparing a calibrated and uncalibrated camera, but are also responsible for significantly decreasing human effort in the process of teaching the tools’ positions to the robot. In conclusion, the mentioned procedures were also implemented with success at the company at which this project has been developed.
Investigation of the effect of Metamaterial on the Dual band Antenna performance for resonating between GSM 900 & Wi-Fi

In the proposed work, a dual band antenna has been designed and fabricated on a Rogers (RT/Duroid 5880tm) substrate of permittivity 2.2 and thickness 1.6mm for resonating between GSM 900 & Wi-Fi. The novelty of the proposed work lies in loading Split Ring Resonator in the Ground plane of the Antenna for improving the Return loss in the higher band and the radiation pattern. Various antenna performance parameters such as Gain, Bandwidth, Return loss and radiation pattern were investigated with and without meta material loading.
P o S ( T e x a s 2 0 1 0 ) 0 4 0 3 D Collapse and Accretion in Slowly Rotating

Several tests have been made using the code GADGET-2, to model the collapse and accretion of a Polytropic envelope onto a BH of 1M . Based on previous results, a minimal resolution (NSPH = 50000) is chosen and simulations are carried out with different initial angular momentum distributions. These will provide information about the formation of accretion disks at different distances from the BH. By observing the accretion of a non rotating, low internal energy Uint polytropic envelope, we tested the Paczynski-Wiita potential used to account for some relativistic effects on the gas due to the BH. These series of tests will help develop the necessary modifications to GADGET-2 in the context of the collapsar model for GRBs.
Hybrid 14 nm FinFET-Silicon Photonics Technology for Low-Power Tb / s / mm 2 Optical I /

Abstract We demonstrate a microbump flip-chip integrated 14nmFinFET CMOS-Silicon Photonics (SiPh) technology platform enabling ultra-low power Optical I/O transceivers with 1.6Tb/s/mm bandwidth density. The transmitter combines a differential FinFET driver with a Si ring modulator, enabling 40Gb/s NRZ optical modulation at 154fJ/bit dynamic power consumption in a 0.015mm footprint. The receiver combines a FinFET trans-impedance amplifier (TIA) with a Ge photodiode, enabling 40Gb/s NRZ photodetection with -10.3dBm sensitivity at 75fJ/bit power consumption, in a 0.01mm footprint. High-quality data transmission and reception is demonstrated in a loop-back experiment at 1330nm wavelength over standard single mode fiber (SMF) with 2dB link margin. Finally, a 4x40Gb/s, 0.1mm wavelength-division multiplexing (WDM) transmitter with integrated thermal control is demonstrated, enabling Optical I/O scaling substantially beyond 100Gb/s per fiber.
Testing of Mobile Applications : Challenges and Future Research Directions

While mobile applications are becoming so extraordinarily adopted, it is still unclear if they deserve any specific testing approach for their verification and validation. This paper wants to investigate new research directions on mobile applications testing automation, by answering three research questions: (RQ1) are mobile applications (so) different from traditional ones, so to require different and specialized new testing techniques? , (RQ2) what are the new challenges and research directions on testing mobile applications? , and (RQ3) which is the role automation may play in testing mobile applications? We answer those questions by analyzing the current state of the art in mobile applications development and testing, and by proposing our view on the topic.
Bayesian Network-based Classifiers for Face Detection

Face detection is a prerequisite of face recognition in many artificial intelligence systems. Because faces appear in different scales, illuminations, colors, orientations and different head poses in an image, fast and accurate detection remains a challenging task for profile faces or faces with perturbations such as shadows, glasses and beard. Therefore, our research concentrates on faces that are hard to detect with current algorithms [1]. Currently, major methods of face detection are based on maximum likelihood learning method, which is computationally efficient but might converge to suboptimal due to mismatch between its optimization criteria (parameter likelihood) and its actual goal of classification (label prediction accuracy) [2]. In contrast, Bayesian Network (BN) can reflect both the conditional independencies and dependencies among features of human face and therefore is more efficient and accurate [3]. There are several algorithms to learn BN from data in an acceptable time and space complexity. Moreover, BN is robust to error or missing data. Therefore, we choose BN as our classification method.
Development on the High Dynamic GPS Signal Simulator Signal Model

According to receiver's dynamic environment,high dynamic GPS signal simulator can precisely generate GPS signal that the receiver get.After a thorough analysis of the signal received by the GPS receiver,it is found that in the GPS signal simulator the frequency of the code and carrier and the time delay of the signal spreding are computed at a certain interval according to the receiver time.Since there is a acceleration between the receiver and GPS satellites,the interval of the signal transmit time is not equal to the interval of the signal sampled time.The computation method for the GPS signal in the high dynamic condition is presented.Based on the error analyse of the model,the method with the increasing the sampling rate for minimizing the errors caused by the simulation of the high acceleration signal is proposed.
Extraction of brain tissues by non-parametric region growing method

It is desirable to process the brain images by computers in order to extract brain region from MRI. When these method are applied to MRI, it has been necessary to experimentally decide parameters in order to get best performances. In this paper, we propose a novel algorithm for the automatic extraction of brain tissues from MRI. This algorithm is called the non-parametric region growing (NPRG) method which does not need the parameter. By NPRG, we can get the same extracted brain regions as the conventional method that has to experimentally decide the parameters.
Do Bioreactor Designs with More Efficient Oxygen Supply to Ovarian Cortical Tissue Fragments Enhance Follicle Viability and Growth In Vitro?

Background: Autotransplantation of cryopreserved ovarian tissue is currently the main option to preserve fertility for cancer patients. To avoid cancer cell reintroduction at transplantation, a multi-step culture system has been proposed to obtain fully competent oocytes for in vitro fertilization. Current in vitro systems are limited by the low number and health of secondary follicles produced during the first step culture of ovarian tissue fragments. To overcome such limitations, bioreactor designs have been proposed to enhance oxygen supply to the tissue, with inconsistent results. This retrospective study investigates, on theoretical grounds, whether the lack of a rational design of the proposed bioreactors prevented the full exploitation of follicle growth potential. Methods: Models describing oxygen transport in bioreactors and tissue were developed and used to predict oxygen availability inside ovarian tissue in the pertinent literature. Results: The proposed theoretical analysis suggests that a successful outcome is associated with enhanced oxygen availability in the cultured tissue in the considered bioreactor designs. This suggests that a rational approach to bioreactor design for ovarian tissue culture in vitro may help exploit tissue potential to support follicle growth.