Miracle-dz/UniFAR-FTUs huggingface dataset:
Ellipsoidal-Set Design of the Decentralized Plug and Play Control for Direct Current Microgrids

Recently the integration of renewable energy resources to direct-current microgrids has become a hot research topic. The voltage stability problem is of paramount importance when the system is subject to external disturbances, parameters uncertainties, and plug-and-play regimes. This paper introduces a novel decentralized voltage tracking for a direct-current islanded microgrid. It consists of numerous Distributed Generation units. The decentralized controller of each distributed generator adjusts the voltage at the point of common coupling to track the desired reference. The proposed control copes with the plug-and-play operation of the microgrid. This means that the possibility of connection/disconnection distributed generators without deteriorating the stability of the overall microgrid is done through the invariant ellipsoid set and the linear matrix inequality optimization. Another merit of the proposed control is that updating the rest of the controllers is not required when a distributed generator is plugged in or out. Moreover, the proposed decentralized controller just uses local states (information) of its distributed generator only. Many simulations and practical studies with different scenarios have been conducted in this paper to verify the performance of the proposed controllers. Comparison with the existing schemes is included.
Convolutional Neural Network-Based Natural Image and MRI Classification Using Gaussian Activated Parametric (GAP) Layer

We propose a novel gaussian activated parametric (GAP) layer for deep neural networks specifically for CNN. This layer normalizes the feature vector using the Gaussian filter-based un-sharpening technique. The goal of the proposed method is to normalize and activate the initial and intermediate feature layers of a deep CNN so that a customized layer can make the feature more distinguish and layers are smoothly tuned for the target-domain classification. Our experiment shows the use of the proposed layer for normalization gives a result almost similar to that of batch normalization and in few cases, the result is slightly better at the cost of higher training time. To demonstrate the result of the proposed layer we are using 4 layers of an encoder-based network as a base architecture for classification in which the first two normalization layers are GAP layers or BN layers whereas the remaining are BN layers. The result of the experiment is better in classification with two GAP layer as normalization layer in a bulkier dataset like ADNI MRI (3D CNN accuracy: 93.58% vs. 91.89%) and CIFAR-10 (2D CNN accuracy: 75.21% vs. 75.11%), whereas the result is better with replacement of first BN layer with GAP in a smaller dataset like 5-animals dataset (2D CNN accuracy: 62.92% vs 58.48%). Therefore, we suggest the use of single GAP layer normalization for smaller datasets and two GAP normalization layers for bigger dataset training. Also, the proposed method produced better results than the cross-channel normalization-based AlexNet network under scratch training.
Efficient Framework for Sentiment Classification Using Apriori Based Feature Reduction

This paper proposes a novel feature selection method for Sentiment Classification. UCI ML Dataset is selected having a textual review from three domains (IMDB Movie, AMAZON Product, and YELP restaurant). Text pre-processing and feature selection technique is applied to the dataset. A Novel Feature Selection approach using Association Rule Mining is presented in which Sentence is converted in binary form and Apriori Algorithm is applied to reduce the dataset. Four Machine Learning algorithms: Naïve Bayes, Support Vector Machine, Random Forest & Logistic Regression to implement experiment. The proposed approach shows an accuracy improvement of 4.2%, 4.9% & 5.9% for IMDB, Amazon & Yelp domain datasets, respectively. Compared with the Genetic Algorithm, Principal Component Analysis, Chi-Square, and Relief based feature selection, the proposed method shows an accuracy improvement of 9.8%, 0.4%, 0.6% & 1.9%, respectively.
Joint tracking and classification of extended targets with complex shapes

This paper addresses the problem of joint tracking and classification (JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model (RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the high-dimensional state space and the severely nonlinear observation model on target state estimation, while the Euclidean distance metric of the normalized Fourier descriptors is applied to obtain the analytical solution of the updated class probability. Consequently, the resulting method is called the “JTC-RHM method. ” Besides, the proposed JTC-RHM is integrated into a Bernoulli filter framework to solve the JTC of a single extended target in the presence of detection uncertainty and clutter, resulting in a JTC-RHM-Ber filter. Specifically, the recursive expressions of this filter are derived. Simulations indicate that: (1) the proposed JTC-RHM method can classify the targets with complex shapes and similar sizes more correctly, compared with the JTC method based on the random matrix model; (2) the proposed method performs better in target state estimation than the star-convex RHM based extended target tracking method; (3) the proposed JTC-RHM-Ber filter has a promising performance in state detection and estimation, and can achieve target classification correctly.
Well-Defined, Nanostructured, Amorphous Metal Phosphate as Electrochemical Pseudocapacitor Materials with High Capacitance

Amorphous micro/nanomaterials are very important members of the noncrystalline materials family and have attracted tremendous interest and exhibited their excellent performance in the application of electrical catalysis and energy storage. The complexity of this research field is limited ultimately by the lack of a facile and practicable strategy to synthesize well-defined ultrathin amorphous nanomaterials. Here, for the first time, we report the random attachment of Co3(PO4)2 amorphous nanoplate building blocks into ultrathin nanosheets with dimensions on the micrometer scale. We found the structure of obtained Co3(PO4)2 amorphous nanosheet can be converted into nanowire by a split process. On the basis of our observations, an assemble-split mechanism for synthesizing ultrathin amorphous nanostructure is proposed. Furthermore, our strategy is general and can be used to prepare other metal phosphate amorphous ultrathin nanostructures. As a demonstration, the synthesized Co3(PO4)2 ultrathin nanowire has be.
Dielectric properties of four softwood species at low-level radio frequencies for optimized heating and drying

ABSTRACT Dielectric heating and drying are important nontraditional technologies for the phytosanitation and quality dehydration of wood products. Unit operation optimization requires, among others, knowledge of the variable dielectric properties of wood so that an optimum dielectric generator matching wood impedance is maintained throughout the process. For this reason, the dielectric properties of four commercially important west coast softwood species were experimentally obtained at various moisture contents, temperatures, and radio frequencies (RF) between 0.1 and 30 MHz. Measurements were carried out on all-sapwood and all-heartwood specimens in both radial and longitudinal directions. Measurements were also done with specimens that were fully saturated with distilled and seawater. All specimens mostly revealed similar qualitative trends in loss factor changes; that is, increases with moisture content and temperature and decreases with increasing frequency. The measurements carried out in the longitudinal direction showed relatively high loss factor values compared to the radial grain direction. Both distilled and seawater saturated loss factors resulted in similar trends and with absolute values hundreds and in some cases thousand times larger than those for specimens in the hygroscopic range.
How Green Trust, Consumer Brand Engagement and Green Word-of-Mouth Mediate Purchasing Intentions

An increasing interest in environmental problems around the world has significantly expanded the demand for green goods, transforming green marketing into an effective tool for businesses to achieve competitive advantage. Yet, as more firms become aware of this strategic advantage, greenwashing activities can also flourish, and customers grow more cautious about green efforts by firms. The present research examines how greenwashing expectations of customers affect their green buying decisions by studying how green trust, consumer brand engagement and green word-of-mouth mediate this relationship. A total of 302 subjects participated in a survey to study greenwashing effects using a high involvement green ad and a low involvement green ad. Results were analyzed using a PLS-SEM approach. The findings show that the greenwashing expectations of customers have no direct effect on green purchase decisions, but that green trust and green word-of-mouth mediate this relationship. Likewise, greenwashing perception significantly affects customer brand engagement indirectly through green trust and there is a full mediation between greenwashing perception and green purchasing intention through green trust, customer brand engagement and green word of mouth. Therefore, the study shows that having a low perception of greenwashing is not enough to increase purchases. For that to occur, companies need to ensure that WOM communicates such efforts and that consumers trust these green initiatives.
Loss of the DYRK1A protein kinase results in reduction of ribosomal protein genes expression, ribosome mass and translation defects

Ribosomal proteins (RPs) are evolutionary conserved proteins that are essential for protein translation. RP expression must be tightly regulated to ensure the appropriate assembly of ribosomes and to respond to the growth demands of cells. The elements regulating the transcription of RP genes (RPGs) have been characterized in yeast and Drosophila, yet how cells regulate the production of RPs in mammals is less well understood. Here, we show that a subset of RPG promoters is characterized by the presence of the palindromic TCTCGCGAGA motif and marked by the recruitment of the protein kinase DYRK1A. The presence of DYRK1A at these promoters is associated with enhanced binding of the TATA-binding protein, TBP, and it is negatively correlated with the binding of the GABP transcription factor, establishing at least two clusters of RPGs that could be coordinately regulated. However, DYRK1A silencing leads to a global reduction of RPGs, mRNA pointing at DYRK1A activities beyond those dependent on its chromatin association. Significantly, cells in which DYRK1A is depleted have reduced RP levels, fewer ribosomes, reduced global protein synthesis and smaller size. We therefore propose a novel role for DYRK1A in coordinating the expression of genes encoding RPs, thereby controlling cell growth in mammals.
Results Of Trenching Investigations Along The New Castle Railroad Survey-1 Seismic Line, New Castle, Delaware

Five trenches were excavated to a depth of 5 to 8 ft along the path of an abandoned railroad grade near the city of New Castle to investigate potential near-surface faults that may be related to earthquake activity in northern Delaware. Seismic reflection profiles along this line suggested the existence of significant faulting in the area, which lies along a postulated fault trend in eastern New Castle County. Subsequent drilling, however, failed to substantiate displacement interpreted for faults in the sedimentary section. Detailed examination of exposures in the trenches also failed to reveal the existence of near surface faults. Together these findings suggest that there has been minimal or no modern near-surface fault activity in this area of New Castle County.
Pyrolysis Behaviors and Thermostability of Polyglycerols and Polyglycerol Fatty Acid Esters

The weight loss behavior of commercial polyglycerols (PG) and PG with various degrees of polymerization, and polyglycerol fatty acid ester (PGFE) with various carbon numbers of acyl group and various degrees of esterification was studied by means of dynamic programmed thermogravimetry (TG). The relationship between the ratio of weight loss at various temperatures and component compositions was also studied by PG. The thermostability of PGFE was evaluated from the temperature of weight loss initiation in dynamic programmed TG, and from the decomposition time-required for a 5% weight loss in isothermal TG. The results are summarized as follows : 1) The temperature of weight loss initiation shifted to the higher temperature side and thermostability was enhanced with increase in the degree of polymerization in the programmed TG of PG. Commercial PG, after removal of water, showed characteristic weight loss pattern depending on the composition of polymerization.2) The ratios of weight loss of PG at room temperature 150°C, 150 250°C, 250 300°C, and 300 350°C were also correlated with the content of water, monoglycerol, the sum of di-and triglycerols, and the sum of tetra-and pentaglycerols in programmed TG, respectively.3) The temperature of weight loss initiation shifted slightly to the higher temperature side with increase in the carbon number of the acyl group in the programmed TG of PGFE. The TG curves from 300 to 400°C showed characteristic weight loss patterns for PGFE with various degrees of esterification, but there was no correlation between the weight loss pattern and degrees of esterification.4) The heat resisting time of PGFE at various temperature was essentially independent of the carbon number of the acyl group as was observed in isothermal TG. However, heat resisting time was reduced and thermostability decreased with increase in the degree of esterification.
PR ] 2 2 D ec 2 00 8 Phase Transition in the 1 d Random Field Ising Model with long range interaction

Abstract We study one–dimensional Ising spin systems with ferromagnetic, long–range interaction decaying as n, α ∈ (12 , ln 3 ln 2 − 1), in the presence of external random fields. We assume that the random fields are given by a collection of symmetric, independent, identically distributed real random variables, gaussian or subgaussian. We show, for temperature and strength of the randomness (variance) small enough, with IP = 1 with respect to the random fields, that there are at least two distinct extremal Gibbs measures.
CHAPTER 1 A New Era of Experimental Political Science ∗

Experimental political science has transformed in the last decade. The use of experiments has dramatically increased throughout the discipline, and technological and sociological changes have altered how political scientists use experiments.We chart the transformation of experiments and discuss new challenges that experimentalists face. We then outline how the contributions to this volume will help scholars and practitioners conduct high-quality experiments. Experimental political science has changed. In two short decades, it evolved from an emergent method to an accepted method to a primary method.We are now entering a new era of experimental political science – what can be called “experimental political science 2.0. ” We do not use the term “era” lightly. The new era reflects, in part, the expanded use of experiments throughout the discipline. But, more fundamentally, it reflects a radical shift in how social scientists design, analyze, and interpret experiments. For most of social science history, the challenges for experimentalists concerned * We thank Nicolette Alayon, Robin Bayes, Jeremy Levy, Jacob Rothschild, and Andrew Thompson for research assistance.We thank LynnVavreck for excellent advice. obtaining data beyond student subject pools and what to do with null results that typically landed in the “file drawer. ” This is no longer true. Data are plentiful, thanks to Internet panels, crowdsourcing platforms, social media, and electronic access to elites; partnerships between researchers and nonacademic entities have also become prolific sources of experimental data. Computing advances have made the implementation and analysis of large-scale studies routine. Moreover, scholars now regularly discuss how to address issues of publication bias, replication, and data-sharing so as to ensure the production of credible experimental research. The challenge now is to ensure that experimentalists design sound studies and
Depolarization of MgH Solar Lines by Collisions with Hydrogen Atoms

Interpretations of the very rich second solar spectrum of the MgH molecule face serious problems owing to the complete lack of any information about rates of collisions between the MgH and hydrogen atoms. This work seeks to begin the process of filling this lacuna by providing, for the first time, quantum excitation, depolarization, and polarization transfer collisional rates of the MgH ground state X 2Σ. To achieve the goals of this work, potential energy surfaces are calculated and then are included in the Schrödinger equation to obtain the probabilities of collisions and, thus, all collisional rates. Our rates are obtained for temperatures ranging from T = 2000 to 15,000 K. Sophisticated genetic programming methods are adopted in order to fit all depolarization rates with useful analytical functions of two variables: the total molecular angular momentum and temperatures. We study the solar implications of our results, and we find that the X 2Σ state of MgH is partially depolarized by isotropic collisions with neutral hydrogen in its ground state 2 S. Our findings show the limits of applicability of the widely used approximation in which the lower-level polarization is neglected.
A New Tool for Covering Risk in Agriculture: The Revenue Insurance Policy

Over the last years, the agricultural sector has faced increasing risks related not only to production activities, but also to climate adversity and a higher frequency of extreme events. These factors, combined with increased price volatility in the markets, have caused greater exposure to risk for farmers. For this reason, risk management in agriculture has taken on an important role within the Common Agricultural Policy. However, in recent years, gradual disaffection of farmers, low penetration of insurance in the arable sector, and a greater need for insurance coverage against market risks have characterised the subsidised risk management system. For all these reasons, starting in 2017, the National Agricultural Insurance Plan has provided new possibilities for covering risks. This paper aims to contribute to the debate on risk management linked to the revenue insurance policy recently adopted in Italy. Using data from the Italian Farm Accountancy Data Network, we simulate the application of the revenue insurance policy with a sample of Italian farms operating in the common and durum wheat sectors. The main findings show that the revenue insurance policy stipulation is, overall, sustainable for both farms and insurance companies.
Quantum Optical Aspects of High-Harmonic Generation

The interaction of electrons with strong laser fields is usually treated with semiclassical theory, where the laser is represented by an external field. There are analytic solutions for the free electron wave functions, which incorporate the interaction with the laser field exactly, but the joint effect of the atomic binding potential presents an obstacle for the analysis. Moreover, the radiation is a dynamical system, the number of photons changes during the interactions. Thus, it is legitimate to ask how can one treat the high order processes nonperturbatively, in such a way that the electron-atom interaction and the quantized nature of radiation be simultaneously taken into account? An analytic method is proposed to answer this question in the framework of nonrelativistic quantum electrodynamics. As an application, a quantum optical generalization of the strong-field Kramers-Heisenberg formula is derived for describing high-harmonic generation. Our formalism is suitable to analyse, among various quantal effects, the possible role of arbitrary photon statistics of the incoming field. The present paper is dedicated to the memory of Prof. Dr. Fritz Ehlotzky, who had significantly contributed to the theory of strong-field phenomena over many decades.
Performance Evaluation of Monolith Based Immobilized Acetylcholinesterase Flow-Through Reactor for Copper(II) Determination with Spectrophotometric Detection

A monolith based immobilized acetylcholinesterase (AChE) flow-through reactor has been developed for the determination of copper(II) using flow injection spectrophotometric system. The bioreactor was prepared inside a microcapillary column by in situ polymerization of butyl methacrylate, ethylene dimethacrylate, and 2,2-dimethoxy-1,2-diphynyletane-1-one in the presence of 1-decanol, followed by vinyl azlactone functionalization and AChE immobilization. The behavior of AChE before and after being immobilized on the monolith was evaluated by kinetic parameters from Lineweaver and Burk equation. The detection was based on measuring inhibition effect on the enzymatic activity of AChE by copper(II) using Ellman’s reaction with spectrophotometric detection at 410 nm. The linear range of the calibration graph was obtained over the range of 0.02–3.00 mg L −1. The detection limit, defined as 10% inhibition ( I10), was found to be 0.04 mg L −1. The repeatability was 3.35 % ( <path id="x1D45B" d="M495 86q-46 -47 -87 -72.5t-63 -25.5q-43 0 -16 107l49 210q7 34 8 50.5t-3 21t-13 4.5q-35 0 -109.5 -72.5t-115.5 -140.5q-21 -75 -38 -159q-50 -10 -76 -21l-6 8l84 340q8 35 -4 35q-17 0 -67 -46l-15 26q44 44 85.5 70.5t64.5 26.5q35 0 10 -103l-24 -98h2 q42 56 97 103.5t96 71.5q46 26 74 26q9 0 16 -2.5t14 -11.5t9.5 -24.5t-1 -44t-13.5 -68.5q-30 -117 -47 -200q-4 -19 -3.5 -25t6.5 -6q21 0 70 48z" /> <path id="x35" d="M153 550l-26 -186q79 31 111 31q90 0 141.5 -51t51.5 -119q0 -93 -89 -166q-85 -69 -173 -71q-32 0 -61.5 11.5t-41.5 23.5q-18 17 -17 34q2 16 22 33q14 9 26 -1q61 -50 124 -50q60 0 93 43.5t33 104.5q0 69 -41.5 110t-121.5 41q-53 0 -102 -20l38 305h286l6 -8 l-26 -65h-233z" /> ) for 1.00 mg L −1 of copper(II). The proposed method was applied to the determination of copper(II) in natural water samples with sampling rate of 4 h −1.