Miracle-dz/UniFAR-FTUs huggingface dataset:
Power conversion efficiency of 25.26% for silicon heterojunction solar cell with transition metal element doped indium oxide transparent conductive film as front electrode

In this paper, to improve the power conversion efficiency (Eff) of silicon heterojunction (SHJ) solar cells, we developed the indium oxide doped with transition metal elements (IMO) as front transparent conductive oxide (TCO) layer combined with microcrystalline silicon (μ‐Si:H(n+)) for SHJ solar cell. The optical and electrical properties as well as structures of hydrogenated IMO (IMO:H) films were studied and compared to conventional indium tin oxide (ITO) film. Such IMO:H films have high carrier mobility over 70 cm2/V·s, high transmittance, and low free carrier absorption, which leads to a high short circuit current density exceeding 40 mA/cm2. In addition, the low sheet resistance and contact resistivity of the IMO:H films contribute to the high fill factor of the solar cell. The average Eff of solar cells with IMO:H + μ‐Si:H(n+) is improved by 0.4% compared with that of the solar cells with ITO + a‐Si:H(n+). Finally, a certified efficiency up to 25.26% (total area, 274.5 cm2) was achieved.
Direct GaAs Nanowire Growth and Monolithic Light‐Emitting Diode Fabrication on Flexible Plastic Substrates

The growth of self‐catalyzed GaAs nanowires (NWs) and monolithic light‐emitting diode (LED) directly on flexible plastic substrates is reported. Dense GaAs NW forest is attained in self‐catalyzed mode using metalorganic vapor phase epitaxy. The NWs are shown to be crystalline with a zinc‐blende phase. The optical properties of the GaAs NWs are found to be promising in both photoluminescence emission and light‐trapping based on reflectance and transmittance measurements. The LED is fabricated from p‐type NWs by depositing Au as Ohmic contact and TiO2/ITO as an electron‐selective contact. The demonstrated NW growth and LED fabrication represent a significant step toward low‐cost, industrially feasible flexible III–V NW optoelectronic applications, as plastic is inexpensive, and the fabrication steps are compatible with roll‐to‐roll processing.
Margin trading system as stock market stabiliser: evidence based on CSI 300 index

ABSTRACT The daily transaction data of Shanghai and Shenzhen 300 Index are taken as sample data. The GARCH model is used to examine the effect of the margin trading system on the stock market volatility of China. The VAR model is used to further test the separate effects of margin purchase system and short sale system upon the role of stock market stabiliser. Results show that margin trading system can restrain stock market volatility and stabilise the market, but the effect of restraining the stock market volatility is limited and has stage characteristics. In particular, the margin purchase system has a greater short-term restraining effect on stock market volatility than the short sale system, whereas the short sale system can stabilise the market more permanently than the margin purchase system. Through international comparisons, we suggest that the margin trading system should be improved to enhance its role as a stock market stabiliser in China.
Graph-based SLAM using architectural floor plans without loop closure

In simultaneous localization and mapping (SLAM), map distortions appear due to the accumulation of pose estimation errors. Loop closure of graph-based SLAM is known as one of the major solutions to this problem. However, there was still a problem that the errors remain in typical loop closure because it only uses constraints of the relative poses of nodes for error correction. In response, the authors focused on the fact that the environments in architectural floor plans are described accurately. Therefore we propose a method using constraints of the absolute poses based on floor plans. Specifically, the robot pose estimated on the floor plan is used as the absolute pose constraint. By optimizing the pose graph that includes absolute pose constraints, a map can be built more accurately to align with the floor plan. Although SLAM using floor plan has been studied before, we propose a new method to reduce computational cost while maintaining map accuracy without loop closure. In this study, we evaluated the effectiveness of our method by comparison with two other methods, one using loop closure and the other using both loop closure and absolute pose constraints. The results proved that the proposed method can maintain the map accuracy and reduce the computational cost. GRAPHICAL ABSTRACT
Determining the Number of Component Clusters in the Standard Multivariate Normal Mixture Model Using Model-Selection Criteria.

Abstract : The problem of clustering individuals is considered within the context of a multivariate normal mixture using model-selection criteria. Often, the number K of components in the mixture is not known. In practical problems, the question arises as to the appropriate choice of k. The problem is to decide how many components are in the mixture, a difficult multiple decision problem. What the null distribution of the criterion is if the data acutally contain k clusters is not known, and remains largely unresolved still. Two well known model-selection criteria, namely Akike's Information Criterion (AIC) and Schwarz's Criterion are proposed for the first time as two new approaches to the problem of what the appropriate choice of k in the mixture multinormal model should be. The forms of these two model-selection criteria are obtained in the standard multivariate normal mixture model. The results are obtained when data initially partitioned into equal size groups; when data initially reordered; when data initialized by k-means algorithm; when data initialized by special initialization scheme; and when special initialization scheme is used on reordered data.
THE THREE-MM ULTIMATE MOPRA MILKY WAY SURVEY. I. SURVEY OVERVIEW, INITIAL DATA RELEASES, AND FIRST RESULTS

We describe a new mm-wave molecular-line mapping survey of the southern Galactic Plane and its first data releases. The Three-mm Ultimate Mopra Milky Way Survey (ThrUMMS) maps a 60° × 2° sector of our Galaxy’s fourth quadrant, using a combination of fast mapping techniques with the Mopra radio telescope, simultaneously in the J = 1 → 0 ? > lines of 12CO, 13CO, C18O, and CN near 112 GHz at ∼arcminute and ∼0.3 km s−1 resolution, with ∼2 K channel−1 sensitivity for 12CO and ∼1 K channel−1 for the other transitions. The calibrated data cubes from these observations are made available to the community after processing through our pipeline. Here, we describe the motivation for ThrUMMS, the development of new observing techniques for Mopra, and how these techniques were optimized to the objectives of the survey. We showcase some sample data products and describe the first science results on CO-isotopologue line ratios. These vary dramatically across the Galactic Plane, indicating a very wide range of optical depth and excitation conditions, from warm and translucent to cold and opaque. The population of cold clouds in particular have optical depths for 12CO easily exceeding 100. We derive a new, nonlinear conversion law from 12CO integrated intensity to column density, N CO ∝ I CO 1.38 ? > , which suggests that the molecular mass traced by CO in the Galactic disk may have been substantially underestimated. This further suggests that some global relationships in disk galaxies, such as star formation laws, may need to be recalibrated. The large ThrUMMS team is proceeding with several other science investigations.
Automated Generation of Metamorphic Relations for Query-Based Systems

Searching and displaying data based on user queries is a pervasive feature of most software applications such as information systems, web portals, and web APIs. The large volume of data managed by these types of systems, henceforth called query-based systems (QBSs), makes them extremely hard to test due to the difficulty to assess whether the output of a query is correct, the socalled test oracle problem. Metamorphic testing has proved to be a very effective approach to alleviate the oracle problem in QBSs, by exploiting the relations among multiple executions of the QBS under test, socalled metamorphic relations (MRs). However, the identification of MRs mostly remains a manual and creative task, limiting the appli-cability of the approach. In this paper, we propose a method for the automated generation of MRs in QBSs starting from a lightweight specification of the query parameters of the system. Evaluation results show that hundreds of MRs can be automatically identified in real-world systems like IMDb, SkyScanner, or YouTube in just a few seconds.
Design of a High-Efficiency Doherty Power Amplifier for 5G Applications Using Wilkinson Power Divider

In this paper, a novel Doherty Power Amplifier DPA based on a 10 W gallium-nitride high-electron-mobility transistor (GaN-HEMT) technology is designed using Advanced Design System (ADS) software. In the design, two different single Power Amplifiers (PAs) are combined using a Wilkinson power divider which is also used to connect the power to the load. The designed DPA operates in the range of 2.0-3.0 GHz and aims to achieve high efficiency, wide bandwidth and high output power for 5G applications. Simulation results showed a 40% fractional bandwidth and more than 44 dBm of saturated output power. In addition, the Power-Added Efficiency (PAE) and Drain-efficiency (Deff) are about 77% and 84%, respectively. A comparison with the other previous works shows enhancement in the maximum large-signal gain (L_S_Gain) in the average of 2.5 dB and an average PAE of about 10%. This improvement can be attributed to the deployment of the power divider/combiner proposed in the design and also the optimization of the components during the design.
Metamorphic Testing in Bioinformatics Software: A Case Study on Metagenomic Assembly

MetaCompass is a metage nomic assembly tool developed by the Pop Lab at the University of Maryland, College Park [2]. Such tools are vital for studying the DNA of the variety of microorganisms present in mixed environmental samples, but they can be difficult to test due to the infeasibility of assessing the correctness of the output of a given test case. In this paper, we demonstrate a simple metamorphic test that detects inconsistencies in the popular assem-bly tools MEGAHIT [7] and Pilon [11], upon which MetaCompass relies. These inconsistencies were not detected during the development process by standard testing procedures, despite the fact that they may be introducing undesirable noise into MetaCompass's results. Our results suggest that metamorphic testing is a valuable tool for finding otherwise subtle defects in metagenomic assembly software.
Stock Retail Projection: Prediction of Future Stock Market Using LSTM Model

Predicting the stock market is difficult due to its complicated nature in this competitive world. There are many factors like physical behavior, industrial performance, economic factors, etc., which are going to affect the stock price. Due to these factors and a wide range of markets, Predicating Future stock values with high accuracy become tough. As we know that, learning from the past and predicting the future is one of the best things provided by machine learning algorithms for us. Our paper describes how to use machine learning algorithms such as recurrent neural networks (RNN) and, in particular, the Long-Short Term Memory model (LSTM) to forecast stock prices in the future. The central theme of our paper is how we will forecast stock prices and how we will use these algorithms to achieve high precision in forecasting stock prices.
Developing Games with Data-Oriented Design

Data-Oriented Design (DOD) is a software design process used in the commercial game industry for medium to large scale (AAA) games that revolves around data as the central design focus. Since DOD grew organically from industry practices, it has been viewed primarily as a set of tools and design patterns without a cohesive core. After studying data-oriented design, it has become clear that there is one core motivating concept behind DOD and that is that software exists to input, transform, and output data. In order to demonstrate the core concept and tools of DOD, examples are shown. The history and focus of DOD are discussed as well as how DOD is used in current commercial software.
A Vehicular Driving Assistant System Using Spread Spectrum Techniques (Special Section on Spread Spectrum Techniques and Applications)

This paper presents a vehicular driving assistant system that is applicable to a mixed environment. The system uses spread spectrum techniques and consists of several new systems such as PN code assignment system, new vehicle position systems, and a vehicle map update system. Wireless broadcast CDMA is used for inter-vehicle communications. The system is tested by using an autonomous traffic flow simulator including inter-vehicle communications.
Similarity indices I: what do they measure.

A method for estimating the effects of environmental effusions on ecosystems is described. The characteristics of 25 similarity indices used in studies of ecological communities were investigated. The type of data structure, to which these indices are frequently applied, was described as consisting of vectors of measurements on attributes (species) observed in a set of samples. A general similarity index was characterized as the result of a two-step process defined on a pair of vectors. In the first step an attribute similarity score is obtained for each attribute by comparing the attribute values observed in the pair of vectors. The result is a vector of attribute similarity scores. These are combined in the second step to arrive at the similarity index. The operation in the first step was characterized as a function, g, defined on pairs of attribute values. The second operation was characterized as a function, F, defined on the vector of attribute similarity scores from the first step. Usually, F was a simple sum or weighted sum of the attribute similarity scores. It is concluded that similarity indices should not be used as the test statistic to discriminate between two ecological communities.
Edinburgh Research Explorer Changes to serum sample tube and processing methodology does not cause inter-individual variation in automated whole serum N-glycan profiling in health and disease

methods were for three types of (with and were randomised and processed in a fashion. Whole N-glycan release, 2-amino-benzamide labeling and cleanup was automated using a Hamilton Microlab STARlet Liquid Handling robot. Samples were analysed using a hydrophilic interaction liquid chromatogra-phy/ethylene bridged hybrid(BEH) column on an ultra-high performance liquid chromatography instrument. Data were analysed quantitatively by pairwise correlation and hierarchical clustering using the area under each chromatogram peak. Qualitatively, a blinded There was small intra-individual variation in serum N-glycan profiles from samples collected using different sample processing methods. Intra-individual correlation coefficients were between 0.99 and 1. Unsupervised hierarchical clustering and principal coordinate analyses accurately matched samples from the same individual. Qualitative analysis demonstrated good chromatogram overlay and a blinded assessor was able to accurately match individuals based on chromatogram profile, regardless of disease status.
Mitigating Emissions in India: Accounting for the Role of Real Income, Renewable Energy Consumption and Investment in Energy

Accomplishing environmental sustainability has become a global initiative whilst addressing climate change and its effects. Thus, there is a necessity for innovation on part of economies as they seek energy for sustainable development. Thus, we explore the case of India a highly industrialized and heavy emitter of carbon emission. To this end, this study explores the effect of renewable energy, non-renewable, economic growth, and investment in the energy sector on CO 2 emission in the Indian economy. Canonical cointegration regression (CCR), fully modified least squares (FMOLS) and dynamic least squares (DOLS) were used to access the long-run elasticity of the variables as well as Granger causality analysis to detect the direction of causality relationship among the highlighted variables. Empirical regression shows a negative relation between CO 2 emission and renewable energy. Thus, suggesting that renewable energy serves as a panacea for sustainable development in the face of economic growth trajectory. However, there was a positive relationship between CO 2 emission and both non-renewable and real GDP growth. On the Granger analysis, we observe a one-way causality among renewable energy consumption and CO 2 emission, economic development, and energy investment. These outcomes have far-reaching policy direction of environmental sustainability target in Indian economy.
Letter to the Editor: Re: Pinto da Costa, J. & Soares, C. (2005). A weighted rank measure of correlation.

under the null hypothesis of independence between the variables X and Y . Furthermore, they provide numerical evidence suggesting that the limiting null distribution of rW (X, Y ) is normal but mention in Section 5.3 of their paper that “the formal proof is still the subject of ongoing work” and that they plan to extend their investigation to cases where X and Y are dependent. Although they quote a related article of Blest (2000), Pinto da Costa & Soares (2005) are apparently unaware that their coefficient is a symmetrized version of Blest’s coefficient, i.e. rW (X, Y ) = [ν (X, Y ) + ν (Y , X)]/2, where ν(X, Y ) = 2n + 1 n − 1 − 12 n2 − n n ∑
ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF GEMCITABINE: A REVIEW

: Analytical method development and validation is an integral part during the development of drug substance and drug product in the pharmaceutical industry. It plays important role in the discovery, development, manufacture and quality control of pharmaceuticals. Analytical methods are designed to determine the drug content in formulation, presence of impurities, separation of drug and its related impurities and degraded products. Validation of method proves that it can be suitable for its use in research and development and assures the reliability of proposed method. Now days, need of analytical method development is increasing due to the emergence of new drugs and development of new combinations of various drugs as their standard methods are not available in Pharmacopoeias. An effective method development and its validation prove to be very useful in drug discovery and development. This review is focused on literature findings from 2014-2018 of analytical method development and validation of gemcitabine hydrochloride drug in various dosage forms.
Design and Development of the 24 GHz FMCW Radar Sensor for Blind Spot Detection and Lane Change Assistance Systems

— In this paper, we designed and implemented the automotive radar based on Frequency Modulated Continuous Wave method for Lane Change Assist and Blind Spot Detection radar system. We also developed digital signal processing module and a 24 GHz FMCW radar RF module composed of a single transmitter, a single transmitting antenna array of five elements and three receiver s to measure range, velocity and angle for LCA and BSD. In order to verify the developed radar system, we conducted experiments to measure the detection rate and the range accuracy in the anechoic chamber and real road environment. The experimental results show that the developed radar is feasible for use in BSD/LCA systems for automotive.
Structural Analysis of the iZeR Locus of Escherichia coli K12*

The Ile repressor protein negatively controls expres- sion from the ilv and thr promoters of Escherichia coli K12. Its existence was inferred from an analysis of the phenotypes of the ileR mutant avr-16 (Johnson, D. I., and Somerville, R. L. (1983) J. Bacteriol. 155, 49-55). The nucleotide sequence of ileR, the structural gene for Ile repressor, has been determined. A DNA segment of 300 base pairs constitutes the ileR gene. The predicted gene product, a protein of 100 amino acids (molecular weight 11,823) has primary structural features reminiscent of other double-stranded DNA-binding regulatory proteins. approx-
Genetic variations for ‘Nam Hom’ coconut ( Cocos nucifera L.) grown in the western region of Thailand using AFLP markers

Using 10 selected Amplified fragment length polymorphism (AFLP) primers, to investigate the genetic diversity and relationships among ‘Nam Hom’ coconut grown in the western region of Thailand, resulting in amplification of 169 reproducible polymorphic fragment products out of 416 bands scored. The percentages of polymorphic markers for AFLP ranged from 70.00% for E-ACC/M-CAT to 24.14 % for E-ACC/M-CAA primers. The phylogenetic tree dendrogram showed that the 55 coconut accessions grown in western region of Thailand could be classified into four groups at 0.88 of similarity coefficients. This grouping observation is consistent with existing morphological classification of coconut tree. The first group to the third group in this study contains tall coconut group and mutant coconut from dwarf coconut group. While, the forth group contains all coconut which belongs to the dwarf coconut group including ‘Nam Hom’ (‘Kon Chip’ and ‘Kon Klom’ strains) and ‘Nam Wan’ coconut from all production area with 0.895-1.00 of similarity coefficients indicated the narrow genetic diversity. Moreover, the results indicated that the ‘Nam Hom’ coconut samples both ‘Kon Chip’ and ‘Kon Klom’ strains collected in different locations were for the main part genetically similar with cophenetic correlation (r) = 0.9347.
Bird Species Identifier using Convolutional Neural Network

—Due to climate changes, many species of flora and fauna are endangered. In order to protect them, we must first identify the species to which it belongs and the special care which needs to be taken care of for their survival. More than 10,000 species are part of the ecosystem. Identifying the species of the bird from an image is a challenging task as it requires techniques such as image processing and Convolutional Neural Network (CNN). CNN is a very challenging Research Area with lots of issues as a slight variation in the image can be perceived as a completely new image. In our approach, we are using the transfer learning approach for training our neural model.