Miracle-dz/UniFAR-FTUs huggingface dataset:
RAPID IN VITRO PROPAGATION OF ARACHIS HYPOGAEA L. VAR. AK 1224: A COMPARATIVE STUDY USING DIFFERENT EXPLANTS

from shoot apices as well as from cotyledonary nodes. De-embryonated cotyledons showed swelling near proximal notch and infrequent shoot multiplication. Shoot multiplication rate in the cotyledonary node explants was higher than shoot apical explants. However, with increasing concentrations of benzylaminopurine in the medium, both cotyledonary nodes and shoot apices exhibited multiple shoot bud formation and these tiny buds could be subsequently developed into leafy shoots by culturing in plant growth regulator free media or in presence of either low level of kinetin (5mg l -1 ) or benzylaminopurine (5mg l -1 ) with or without auxin supplementation (napthalene acetic acid 1mg l -1 ). Shoots of 2-3 cm size could be quickly rooted in presence of either 2, 4 dichlrophenoxy acetic acid or napthalene acetic acid. Well grown rooted plantlets were successfully transferred to soil and after hardening established finally in the field.
Fast Prediction with Sparse Multikernel LS-SVR Using Multiple Relevant Time Series and Its Application in Avionics System

Health trend prediction is critical to ensure the safe operation of highly reliable systems. However, complex systems often present complex dynamic behaviors and uncertainty, which makes it difficult to develop a precise physical prediction model. Therefore, time series is often used for prediction in this case. In this paper, in order to obtain better prediction accuracy in shorter computation time, we propose a new scheme which utilizes multiple relevant time series to enhance the completeness of the information and adopts a prediction model based on least squares support vector regression (LS-SVR) to perform prediction. In the scheme, we apply two innovative ways to overcome the drawbacks of the reported approaches. One is to remove certain support vectors by measuring the linear correlation to increase sparseness of LS-SVR; the other one is to determine the linear combination weights of multiple kernels by calculating the root mean squared error of each basis kernel. The results of prediction experiments indicate preliminarily that the proposed method is an effective approach for its good prediction accuracy and low computation time, and it is a valuable method in applications.
GAINS AND PAYMENTS OF MERGERS AND ACQUISITIONS: FURTHER EVIDENCE FROM THE UK

Using UK data and the standard Event Study methodology framework, the wealth effects of target and acquiring companies involved in merger and acquisition activities over the period from 2000 to 2010 is investigated. Further, we extend our analysis to examine the financing payments of M&A transactions using various test models, namely the size-deciles (SD) control model, Hoare-Govett small companies model, index model (IM), market model (MM) and the capital asset pricing model (CAPM). The results in general indicate that target companies obtain significantly positive and higher abnormal returns than those obtained by the UK acquirers. The results are positively associated with cash offers used in financing the merger and acquisition transactions. Consistent with previous studies we found no clear pattern of abnormal returns around the announcement period for the UK acquirers. Interestingly, the five different test models are generally found to produce similar levels of abnormal returns.
Title An auction-based approach with closed-loop bid adjustment todynamic task allocation in robot teams

Dynamic task allocation is among the most difficult issues in multi-robot coordination, although it is imperative for a multitude of applications. Auction-based approaches are popular methods that allocate tasks to robots by assembling team information at a single location to make practicable decisions. However, a main deficiency of auction-based methods is that robots generally do not have sufficient information to estimate reliable bids to perform tasks, particularly in dynamic environments. While some techniques have been developed to improve bidding, they are mostly open-looped without feed-back adjustments to tune the bid prices for subsequent tasks of the same type. Robots’ bids, if not assessed and adjusted accordingly, may not be trustworthy and would indeed impede team performance. To address this issue, we propose a closed-loop bid adjustment mechanism for auction-based multi-robot task allocation, with an aim to evaluate and improve robots’ bids, and hence enhance the overall team performance. Each robot in a team maintains and uses its own track record as closed-loop feedback information to adjust and improve its bid prices. After a robot has completed a task, it assesses and records its performance to reflect the discrepancy between the bid price and the actual cost of the task. Such performance records, with time-discounting factors, are taken into account to damp out fluctuations of bid prices. Adopting this adjustment mechanism, a task would be more likely allocated to a competent robot that submits a more accurate bid price, and hence improve the overall team performance. Simulation of task allocation of free-range automated guided vehicles serving at a container terminal is presented to demonstrate the effectiveness of the adjustment mechanism.
Managing E-commerce Platform Quality and its Performance Implication: A Multiple-Group Structural Model Comparison

ABSTRACT This study develops a comprehensive e-service quality measure of e-commerce platforms as intermediaries, which considers both the functionality of the website itself and the performance assessment of independent sellers. The study further investigates the joint impacts of both the attributes of e-commerce platforms and the performance of independent sellers on users’ online shopping experience: perceived online transaction value and the ensuing satisfaction. Finally, the study examines the effects of e-service quality on the outcome variables across two major e-commerce platforms as intermediaries, eBay and Amazon. The multiple-group structural model analysis provides important insights to understanding differing impacts of different quality components on shopping experiences across various online marketplaces. Theoretical and managerial implications are discussed.
Interleukin-15 and Interleukin-15 Receptor ÃÂ± mRNA-engineered DendriticCells as Promising Candidates for Dendritic Cell-based Vaccination inCancer Immunotherapy

Dendritic cell (DC)-based tumor vaccination holds great potential and is intensively being studied in cancer immunotherapy. Although DC vaccination can result in a survival advantage as shown in various cancer types, there is still room for improvement. Therefore, current DC vaccines urge rigorous optimization in order to increase their immune stimulating capacities for induction of antitumor immunity. In this context, strategies where the interleukin (IL) 15 transpresentation mechanism is incorporated, appear to be of great value due to the activating potential of IL-15 towards IL-15Rβγ expressing cells, such as cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells. In the past 5 years, our research group designed different strategies to generate IL-15-expressing DC with superior T cell and NK cell-activating properties. In this review, we briefly describe the design of our latest DC vaccine, in which DC are genetically engineered to transpresent IL-15 via mRNA electroporation and discuss the capacity of this newly designed DC vaccine to activate NK cells and CTLs. Overall, IL-15 transpresenting DC show the potential to activate antitumor immunity and are promising candidates for DC based cancer immunotherapy.
Teachers' and pre-service teachers' confidence to teach primary school mathematics

Confidence has been variously defined as a dimension attitude, an outcome of beliefs about one's self-efficacy in a particular situation, and as inherent in the process of learning and linked to identity formation. It is often assumed to be associated with ability and crucial to performance. There is evidence that many primary teachers lack confidence in their ability to teach topics in the mathematics curriculum effectively (Beswick, Watson, & Brown, 2006; Watson, Beswick, Caney, & Skalicky, 2006), and that pre-service teachers have reservations about their preparedness to teach mathematics at the level they will be qualified to teach it. Indeed, mathematics anxiety is commonly reported among pre-service primary teachers (e.g., Uusimaki & Nason, 2004). The pre-service (n = 96) and practising (n = 32) teachers in this study worked together in the pre-service teachers' final mathematics curriculum unit in an approach designed to bridge the perceived theory-practice gap. We were interested in the impact of the unit on the pre-service teachers' confidence. Confidence data were collected using a paper based questionnaire that included one section related to confidence. The section comprised 21 items to which participants responded on 5- point Likert scales indicating the extent of their confidence from Low confidence to High confidence. This paper presents data on the confidence of practising primary teachers and pre-service teachers to teach various aspects of the primary school mathematics curriculum. Differences between the confidence of the two groups of teachers at the start and end of the project, and changes in the pre-service teachers' confidence from the beginning to the end of the semester long unit are examined using t-tests. Unsurprisingly the practising teachers were more confident to teach most topics than were their novice colleagues at the start of the semester but this was not the case at the end. In general the pre-service teachers' confidence improved from beginning to end of the semester.
A Stochastic Predator-Prey System with Stage Structure for Predator

The authors introduce stochasticity into a predator-prey system with Beddington-DeAngelis functional response and stage structure for predator. We present the global existence and positivity of the solution and give sufficient conditions for the global stability in probability of the system. Numerical simulations are introduced to support the main theoretical results.
Earnings Management and Stock Performance of Reverse Leveraged Buyouts

Abstract This study provides further evidence of earnings management around security offerings. We find positive and significant discretionary current accruals coincident with offerings of reverse LBOs. Issuers in the most aggressive quartile of earnings management have a one-year aftermarket return that is between 15% and 25% less than the most conservative quartile. We also find a negative and significant relation between abnormal accruals and post-issue abnormal returns within the first year after the offering. The relation remains after controlling for book-to-market ratio, firm size, offering size, and involvement of buyout specialists or management. Although earnings management has been used to explain post-issue long-term underperformance of IPOs and SEOs, our study shows that earnings management can explain post-offering returns of reverse LBOs, even in the absence of post-offering underperformance.
OMI tropospheric NO 2 profiles from cloud slicing: constraints on surface emissions, convective transport and lightning NO x

We derive annual and seasonal global climatologies of tropospheric NO2 profiles from OMI cloudy observations for the year 2006 using the cloud-slicing method on six pressure levels centered at about 280, 380, 500, 620, 720 and 820 hPa. A comparison between OMI and the TM4 model tropospheric NO2 profiles reveals striking overall similarities, which confer great confidence to the cloud-slicing approach to provide details that pertain to annual as well as seasonal means, along with localized discrepancies that seem to probe into particular model processes. Anomalies detected at the lowest levels can be traced to deficiencies in the model surface emission inventory, at mid-tropospheric levels to convective transport and horizontal advective diffusion, and at the upper tropospheric levels to model lightning NOx production and the placement of deeply transported NO2 plumes such as from the Asian summer monsoon. The vertical information contained in the OMI cloud-sliced NO2 profiles provides a global observational constraint that can be used to evaluate chemistry transport models (CTMs) and guide the development of key parameterization schemes.
Design and simulation of a new approach for reconfiguration overhead reduction in RTR systems

The advantage of RTR systems usually comes with some costs. Necessary time for mapping some areas of a program to FPGA is considerable and affects the performance of RTR systems. Configuration compression can reduce the total number of write operations to load a configuration and it has been proved as an efficient technique to deal with the configuration overhead. In this paper, we have developed a new approach for reconfiguration overhead reduction in Xilinx Virtex FPGAs by using compression technique. Since the order of sequence of configuration frames affects the compression rate, we have used genetic algorithm for finding an optimal configuration sequence of frames.
An integration testing method that is proved to find all faults

Although a great deal of research has been done in the area of formal methods and their practical use for the specification and verification of software systems, testing issues are very seldom mentioned by those within the formal methods community. Almost all the methods currently used for testing software are experience based rather than theoretically founded methods. In particular, very few methods allow us to make any statement about the type or number of faults that remain undetected after testing is completed. This paper describes a method for using the existence of a formal specification as the basis for the development of a detailed functional testing strategy. By considering testing from a theoretical point of view we demonstrate that this method can provide a more convincing approach to the problem of detecting all faults. The formal method used, X-machines, is a blend of finite state machines, data structures and processing functions and provides a simple and intuitive way for specifying compute.
MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies

MEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification) was developed as an "intermediate complexity" plankton ecosystem model to study the biogeochemical response, and especially that of the so-called "biological pump", to anthropogenically driven change in the World Ocean (Yool et al., 2011). The base currency in this model was nitrogen from which fluxes of organic carbon, including export to the deep ocean, were calculated by invoking fixed C:N ratios in phytoplankton, zooplankton and detritus. However, due to anthropogenic activity, the atmospheric concentration of carbon dioxide (CO2) has significantly increased above its natural, inter-glacial background. As such, simulating and predicting the carbon cycle in the ocean in its entirety, including ventilation of CO2 with the atmosphere and the resulting impact of ocean acidification on marine ecosystems, requires that both organic and inorganic carbon be afforded a more complete representation in the model specification. Here, we introduce MEDUSA-2.0, an expanded successor model which includes additional state variables for dissolved inorganic carbon, alkalinity, dissolved oxygen and detritus carbon (permitting variable C:N in exported organic matter), as well as a simple benthic formulation and extended parameterizations of phytoplankton growth, calcification and detritus remineralisation. A full description of MEDUSA-2.0, including its additional functionality, is provided and a multi-decadal spin-up simulation (1860–2005) is performed. The biogeochemical performance of the model is evaluated using a diverse range of observational data, and MEDUSA-2.0 is assessed relative to comparable models using output from the Coupled Model Intercomparison Project (CMIP5).
Towards the generation of broadband optical vortices : extending the spectral range of a q-plate by polarization-selective filtering

1Optoelectronics Research Centre, University of Southampton, SO17 1BJ, Southampton, United Kingdom 2Vilnius University Laser Research Center, 10 Sauletekio avenue, LT10223, Vilnius, Lithuania 3State Key Laboratory of Luminescent Materials and Devices, South China, University of Technology, Guangzhou 510640, China 4Altechna R&D Ltd., Mokslininku st. 6A, LT-08412, Vilnius, Lithuania *Corresponding author: aidas.matijosius@ff.vu. lt
Strengthening of Intellectual Capital Dimension

The main objective of this research is to explore capabilities related to trust, self-efficacy, intellectual capital and job satisfaction at head-hunter companies in Indonesia. Development of human resources needs to be done through the strengthening of intellectual capital. Intellectual capital is needed head-hunter in improving company performance. The key to successful head-hunter companies if it has human resources that have added value, especially strong intellectual capital. Research sampling was conducted on 253 candidates who utilize head-hunter services an effort to develop themselves. Quantitative research was developed by utilizing structural equation modeling. Research model developed head-hunter companies that describes intellectual capital as research findings refers to previous model of research. This finding concludes that trust and self-efficacy have significant influence on intellectual capital. Another conclusion stated that intellectual capital has significant effect on job satisfaction. The concept states that intellectual capital can be integrated in global perspective as framework for developing an organization.
FARMERS’ PERCEPTIONS ON MECHANICAL WEEDERS FOR RICE PRODUCTION IN SUB-SAHARAN AFRICA

SUMMARY Competition from weeds is one of the major biophysical constraints to rice (Oryza spp.) production in sub-Saharan Africa. Smallholder rice farmers require efficient, affordable and labour-saving weed management technologies. Mechanical weeders have shown to fit this profile. Several mechanical weeder types exist but little is known about locally specific differences in performance and farmer preference between these types. Three to six different weeder types were evaluated at 10 different sites across seven countries – i.e., Benin, Burkina Faso, Côte d'Ivoire, Ghana, Nigeria, Rwanda and Togo. A total of 310 farmers (173 male, 137 female) tested the weeders, scored them for their preference, and compared them with their own weed management practices. In a follow-up study, 186 farmers from Benin and Nigeria received the ring hoe, which was the most preferred in these two countries, to use it during the entire crop growing season. Farmers were surveyed on their experiences. The probability of the ring hoe having the highest score among the tested weeders was 71%. The probability of farmers’ preference of the ring hoe over their usual practices – i.e., herbicide, traditional hoe and hand weeding – was 52, 95 and 91%, respectively. The preference of this weeder was not related to gender, years of experience with rice cultivation, rice field size, weed infestation level, water status or soil texture. In the follow-up study, 80% of farmers who used the ring hoe indicated that weeding time was reduced by at least 31%. Of the farmers testing the ring hoe in the follow-up study, 35% used it also for other crops such as vegetables, maize, sorghum, cassava and millet. These results suggest that the ring hoe offers a gender-neutral solution for reducing labour for weeding in rice as well as other crops and that it is compatible with a wide range of environments. The implications of our findings and challenges for out-scaling of mechanical weeders are discussed.
UvA-DARE ( Digital Academic Repository ) Inconvenient truths : determinants of strategic ignorance in moral dilemmas

People often have incomplete information about the consequences of their actions for the payoffs of others. In an experimental allocation game I investigate how the choice to learn about such consequences depends on the costs and benefits of altruistic actions. The results show an asymmetric pattern: while the size of others’ potential benefit has little effect, ignorance and selfish behavior go up when information is more ‘inconvenient’, i.e. the fair/efficient alternative is more costly to the decision maker. Thus, in situations of payoff uncertainty, subsidizing fair choices affects prosocial behavior both directly and by increasing the willingness to confront negative consequences of one’s actions. JEL-codes: D83, C72, C91.
Understanding Policy Change Using a Critical Junctures Theory in Comparative Context: The Cases of Ireland and Sweden

Utilizing a new theory for examining critical junctures, we seek to better understand the nature of industrial policy change in Ireland during the 1950s and macroeconomic policy change in Sweden in the 1980s. Did these policy changes constitute critical junctures, or something less, and if so why? The theory consists of three elements—economic crisis, ideational change, and the nature of the policy change—that must be identified for us to be able to declare with some certainty if a policy change constitutes a critical juncture. Herein, we will be examining the roles of a variety of change agents including the media, central banks, and politicians. Our findings will help explain why Irish industrial policy was transformed in the late 1950s, while Swedish macroeconomic policy underwent only minor change in the early 1980s.
AURYN PINK SODERINI OUTDOOR POSITIONING ALGORITHMS BASED ON LTE AND WIFI MEASUREMENTS

AURYN PINK SODERINI Outdoor Positioning Algorithms Based on LTE and WiFi Measurements Tampere University of Technology, 76 pages December 2016 Master’s Degree Programme in Electrical Engineering Major: Wireless Communications Circuits and Systems Examiners: Assoc. Prof. Elena-Simona Lohan and Prof. Robert Piché
Net income prediction of several leading bank in Indonesia using neural approach

The IFRS (International Financial Reporting Standards) defines net income as synonymous with profit and loss. Net income can be used as a consideration for investment decision making for investors who will invest their capital into a company. Net income for the next year cannot be ascertained but can be predicted by using several financial ratios that affect the change in net income. This study tries to predict net income next year by using several financial ratios obtained from four leading banks in Indonesia. The time series data modeling by using Artificial Neural Network (ANN) based Auto-Regressive with Exogenous input (ARX) model. In this study only use one net structure to model time series data in order to improve the efficiency of the model. Back-Propagation (BP) doing backpropagation to fix the weight of each layer of ANN such that to achieve appointed target error.
Allozyme Variation and Population Structure of Carex okamotoi (Cyperaceae), a Korean Endemic Species

The genetic diversity and population structures of fourteen Carex okamotoi (Cyperaceae) populations in Korea were determined using genetic variation at 25 allozyme loci. The Carex okamotoi species is native to Korea. It is endemic to three mountains (Mt. Taeback, Mt. Sobak, and Mt. Noreong) where it is found at 700~1,500 m above sea level. The percentage of polymorphic loci was 40.0%. Genetic diversity at the species level and at the population level was low (H ES =0.106; H EP =0.094), and the extent of the population divergence was relatively low (G ST =0.082). Measurement of deviation from random mating (F IS ) within the 14 populations was 0.238. An indirect estimate of the number of migrants per generation was 2.78 (Nm=2.78). Analysis of fixation indices revealed a substantial heterozygosity deficiency in some populations and at some loci. Mean genetic identity between populations was 0.986.