Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Public Investment on Economic Growth in Bangladesh: An Econometric Analysis

This paper explores the role of public investment in the process of economic growth, in the context of Bangladesh economy. Due to lack of recent official statistics, necessary datasets were derived by the author for the period 1973-2011. For the estimation purposes several econometric method are used. The results show that Public Investment has positive effects on GDP in Bangladesh. So increases in public investment should have a positive net impact on economic growth which augments our economic development in future. Findings point out that keeping the high public investment level in Bangladesh together with improvement in institutional surroundings would be beneficial for economic growth. This paper concludes with a number of policy recommendations arising from the research findings. Kewords: Public Investment, Economic Growth, Unit Root Test, Co-integration test, Jarque-Bera test, Multicollinearity test, Heteroskedasticity, Likelihood Ratio Test.
Complexity Theory and Change Management in Sport Organisations

This paper employs complexity theory and the principle of emergence as a construct to explain some forms of change observed during the analysis of research concerning change in Australian sport organizations. Although a consortium of well-established theories proved advantageous in revealing the nature of change attempts within a sample of eight case organizations, some changes remained inexplicable. Upon further investigation, these changes were observed to have properties associated with emergence. Several examples are presented to explicate the emergent behavior. This paper presents evidence to suggest that complexity theory has utility as an alternative perspective explaining certain types of organizational change.
MLAPI: a C++ Framework For Multilevel Preconditioners

We discuss the design of MLAPI, an object oriented framework that enables the development and usage of e‐cient, scalable and portable implementations of multilevel preconditioners for general distributedsparsematrices, inboth serial andparallel environments. The main feature of this framework is the use of several programming paradigms for the difierent implementation layes, with a strong emphasis on object oriented classes and operator overloading for the top layer, and optimized FORTRAN and C code for the layers underneath. In particular, MLAPI takes advantageof ML [21], the algebraic multilevel preconditioning packageofTrilinos[13]. We report several numerical experiments, obtained on serial and parallel computers, to show that theoverloadrequiredbytheobject-orientedlayerisverymodest,thereforeallowingdeveloperstofocus on the new algorithm they are developing and testing, rather than the implementation details, yet obtaining a code whose e‐ciency and scalability is comparable with that of C or FORTRAN layers underneath.
Decomposition of Country-Specific Corporate Bond Spreads

This paper presents a new approach, based on the Merton model, to decomposing corporate bond spreads into the expected loss, bond risk premium and liquidity premium components. The approach focuses on establishing the bond risk premium using the equity risk premium and the hedge ratio, which are estimated using a dividend discount model and a BEKK-GARCH model. The analysis focuses on non-financial European BBB-rated corporate bonds and distinguishes explicitly between German, French, Spanish and Italian firms. The results show that the bond risk premium is the largest component. While the expected loss component made the greatest contribution to the strong widening of the spreads around the turn of 2008/09, the spreads were then heavily dominated by the bond risk premium and investors received relatively low or, at times, no compensation for expected losses. The safe interest rate and the sovereign CDS premiums are key determinants of the expected loss component and the bond risk premium.
Oblique propagation of whistler mode waves in the chorus source region

[1] Whistler mode chorus has been shown to play a role in the process of local acceleration of electrons in the outer Van Allen radiation belt. Most of the quasi-linear and nonlinear theoretical studies assume that the waves propagate parallel to the terrestrial magnetic field. We show a case where this assumption is invalid. We use data from the Cluster spacecraft to characterize propagation and spectral properties of chorus. The recorded high-resolution waveforms show that chorus in the source region can be formed by a succession of discrete wave packets with decreasing frequency that sometimes change into shapeless hiss. These changes occur at the same time in the entire source region. Multicomponent measurements show that waves in both these regimes can be found at large angles to the terrestrial magnetic field. The hiss intervals contain waves propagating less than one tenth of a degree from the resonance cone. In the regime of discrete wave packets the peak of the wave energy density is found at a few degrees from the resonance cone in a broad interval of azimuth angles. The wave intensity increases with the distance from the magnetic field minimum along a given field line, indicating a gradual amplification of chorus in the source region.
Application Research on Testing Efficiency of Main Drainage Pump in Coal Mine Using Thermodynamic Theories

The efficiency of a drainage pump should be tested at regular intervals to master the status of the drainage pump in real time and thus achieve the goal of saving energy. The ultrasonic flowmeter method is traditionally used to measure the flow of the pump. But there are some defects in this kind of method of underground coal mine. This paper first introduces the principle of testing the main drainage pump efficiency in coal mine using thermodynamic theories, then analyzes the energy transformation during the process of draining water, and finally derives the calculation formulae of the pump efficiency, which meet the on-site precision of engineering. On the basis of analyzing the theories, the protective sleeve and the base of the temperature sensor are designed to measure the water temperature at inlet and outlet of the pump. The efficiencies of pumps with two specifications are measured, respectively, by using the thermodynamic method and ultrasonic flowmeter method. By contrast, the results show that thermodynamic method can satisfy the precision of the testing requirements accuracy for high-flow and high-lift drainage pump under normal temperatures. Moreover, some measures are summed up to improve the accuracy of testing the pump efficiency, which are of guiding significance for on-site testing of the main drainage pump efficiency in coal mine.
Relativistic orbits and Gravitational waves from gravitomagnetic corrections

Corrections to the relativistic theory of orbits are discussed considering higher order approximations induced by gravitomagnetic effects. Beside the standard periastron effect of General Relativity (GR), a new nutation effect was found due to the c−3 orbital correction. According to the presence of that new nutation effect we studied, via the quadrupole approximation, the gravitational waveforms emitted by a compact object (neutron star (NS) or black hole (BH)) orbiting around a massive black hole (MBH). To obtain the emitted gravitational wave (GW) amplitudes, a numerical solution of the equations is given in different mass ratios and initial conditions. We conclude that the effects we studied could be of interest for the future space laser interferometric GW antenna LISA.
Valuing the non-market production of agriculture Bewertung nicht-marktlicher Agrarproduktion

As a consequence of the negotiations for a new agricultural policy of the EU the multifunctionality of agricultural production has come into new prominence in the public. The philosophy that subsidies for the agricultural sector should be calculated not only by agricultural market production but also according to agricultural noncommodity production like e.g. the conservation of the countryside, makes it necessary to assess the social value of this part of agricultural production. In this paper we scrutinize the welfare theoretical background of the economic valuation of non-market production as well as the existing practical valuation techniques. Further, the applicability of these techniques to the valuation of agricultural noncommodity production is considered.
Endogenous Firm Heterogeneity, ICT and R&D Incentives

Firm heterogeneity explains the productivity driven selection mechanism that determines aggregate productivity growth within industries. This paper empirically demonstrates that ICT has a robust impact on firm heterogeneity only when ICT is used intensively and jointly with specific ICT applications. ICT induced heterogeneity is shown to have a positive impact on the decision to invest in R&D personnel.
The Economics of Land Fragmentation in the North of Vietnam

Land fragmentation, where a single farm has a number of parcels of land, is a common feature of agriculture in many countries, especially in developing countries. In Vietnam, land fragmentation is common, especially in the north. For the whole country, there are about 75 million parcels of land, an average of seven to eight plots per farm household. Such fragmentation can be seen to have negative and positive benefits for farm households and the community generally. Comparative statics analysis and analysis of survey data have led to the conclusion that small-sized farms are likely to be more fragmented, and that fragmentation had a negative impact on crop productivity and increased family labour use and other money expenses. Policies which allow the appropriate opportunity cost of labour to be reflected at the farm level may provide appropriate incentives to trigger farm size change and land consolidation. Policies which tip the benefits in favour of fewer and larger plots, such as strong and effective research and development, an active extension system and strong administrative management, may also lead to land consolidation.
The DR14 APOGEE-TGAS catalogue: Precise chemo-kinematics in the extended solar vicinity

Abstract We describe the DR14 APOGEE-TGAS catalogue, a new SDSS value-added catalogue that provides precise astrophysical parameters, chemical abundances, astro-spectro- photometric distances and extinctions, as well as orbital parameters for ~30, 000 APOGEE-TGAS stars, among them ~5, 000 high-quality giant stars within 1 kpc.
Large deviations for method-of-quantiles estimators of one-dimensional parameters

Abstract We consider method-of-quantiles estimators of unknown one-dimensional parameters, namely the analogue of method-of-moments estimators obtained by matching empirical and theoretical quantiles at some probability level . The aim is to present large deviation results for these estimators as the sample size tends to infinity. We study in detail several examples; for specific models we discuss the choice of the optimal value of λ and we compare the convergence of the method-of-quantiles and method-of-moments estimators.
Application Performance Evaluation using Deep Learning

Developing software for exascale systems will become even more challenging than for today’s systems. Methods for evaluating the performance of applications and identifying potential weaknesses are essential for reaching optimal performance. Though the tools available today are not widely used, and generally require some expert knowledge. In recent years different deep learning techniques have enjoyed great success in various fields, and especially in image recognition. Though it is still to find its way in to the area of application performance evaluation. This work will take the first step towards introducing deep learning to the area of HPC performance evaluation, opening the door for others. Convolutional neural networks will be fed images of timeline views of HPC applications and will identify the intrinsic behavior of the application and return some principal performance metrics. The results show that deep learning techniques indeed can be utilized for evaluating the performance of parallel applications, with the main limitation for its success being the sizes of the data sets available. Furthermore a number of exciting directions for taking the next step utilizing deep learning techniques with performance evaluation are suggested.
Fermi surface of layered compounds and bulk charge density wave systems

A review is given of recent angle-resolved photoemission (ARPES) experiments and analyses on a series of layered charge density wave materials. Important aspects of ARPES are recalled in view of its capability for bulk band, Fermi surface and spectral function mapping despite its surface sensitivity. Discussed are TaS2, TaSe2, NbTe2, TiSe2 and TiTe2 with structures related to the so-called 1T polytype. Many of them undergo charge density wave transitions or exist with a distorted lattice structure. Attempts to explain the mechanism behind the structural reconstruction are given. Depending on the filling of the lowest occupied band a drastically different behaviour is observed. Whereas density functional calculations of the electronic energy and momentum distribution reproduce well the experimental spectral weight distribution at the Fermi energy, the ARPES energy distribution curves reveal that for some of the compounds the Fermi surface is pseudo-gapped. Two different explanations are given, the first based on density functional calculations accounting for the charge-density-wave-induced lattice distortion and the second relying on many-body physics and polaron formation. Qualitatively, both describe the observations well. However, in the future, in order to be selective, quantitative modelling will be necessary, including the photoemission matrix elements.
Data-Driven Activity Scheduler for Multi-Agent Activity-Based Transportation Models

Multi-agent activity-based models solve transportation forecasting problems. Activitybased models model a transportation system with a large number of interacting simple agents. Each agent behaves according to its schedule: sequence of activities. Every activity contains its type, transport mode and spatio-temporal information. There are many implementations of activity-based models that use expert-system approach, but there has been none that is purely data-driven. This work explores the possibility of using a recurrent neural network (RNN) as scheduler. I use an RNN with LSTM blocks (LSTM-RNN) to generate a sequence of activities where each activity feature is probabilistically modeled by selected probability function. The LSTM-RNN is combined with the mixture density network (MDN) approach so it is possible to model features with probability density functions. I compare three di erent probabilistic functions to model temporal features: mass density function, Gaussian mixture and beta mixture. This work presents a loading sequence which loads possible trip destinations for each agent. Finally, the schedules generated by the LSTM-RNN are validated by the Validation Framework for Activity-based Models (VALFRAM).
The Cross-Section of Industry Investment Returns

Firm level characteristics explain the cross section of investment returns of industry portfolios that include listed and unlisted firms. Moreover, common asset pricing models explain the cross-sectional variation of characteristic-based investment returns which include listed and unlisted firms. Assuming that managers of unlisted fi rms are less likely to be affected by investor misvaluation and are less likely to overinvest, our results are consistent with a rational interpretation of the role of characteristics. Given a portfolio characteristic, there are no systematic differences in expected investment returns for listed and unlisted fi rms suggesting their cost of equity are unrelated to whether a rm is listed or unlisted.
The Role of Anatomy in Clinical Practice : A Participant Observation Study of Use of Anatomy in Clinical Practice

Pzlxpose. The study investigated, using the participant observation method, how clinicians use knowledge of anatomy in clinical settings. The aim of the study was to inform clinically oriented anatomy teaching with regard content selection and how to teach anatomy to medical students. Mcffeod. The researcher, a medical doctor and anatomist, was attached to clinical units over a period of 46 weeks (surgery 28 weeks, internal medicine 6 weeks, paediatrics 4 weeks, and obstetrics gynaecology 8 weeks) totaling 2,216 contact hours with clinical practice. The researcher studied clinicians dealings with clinical situations that required knowledge of anatomy by active looking, natural conversation, informal interviewing of various sorts, and checklists. Participation included partaking in the clinical responsibilities of the clinical team. RcswJts. The role of anatomy in clinical practice was classified into two broad themes: practical processes and cognitive processes. With regard practical procedures clinicians use anatomical knowledge as a rationale (basis) for where and how clinical procedures or operations are done; in orientating themselves on the human body; in reading clinical images which involves recognizing anatomical structures; and in recognizing aspects of clinical practice in which anatomy is an outcome determinant. The cognitive aspects involve problem identification; explaining clinical phenomena; understanding Plathogenesis, signs and symptoms, and complications; and problem solving where the knowledge of anatomy is applied to solve a clinical
Specifics of determination of antimotivation for learning activity in prospective teachers from different countries

The aim of present study was to explore the specifics of determination of negative motivation for learning activity in students of pedagogical universities and pedagogical departments of the universities in different countries – Russia, Kazakhstan and Czech Republic. Participants in the study were 463 students of full-time bachelor and master programs in the universities. In order to reach the study goal, we used the questionnaire of antimotivation for learning activity, created by N.V. Ivanova and E.V. Minaeva, which is aimed at students, who obtain pedagogic education in specialized universities or at pedagogical departments of the university. The study employed factor and correlation analysis of the results, which was conducted in the IBM SPSS Statistics 23 software. We analyzed the significance of environmental factors of antimotivation for learning activity in respondents from different RESUMEN: El objetivo del presente estudio fue explorar los aspectos específicos de la determinación de la motivación negativa para la actividad de aprendizaje en estudiantes de universidades pedagógicas y departamentos pedagógicos de las universidades de diferentes países: Rusia, Kazajstán y República Checa. Los participantes en el estudio fueron 463 estudiantes de programas de licenciatura y maestría de tiempo completo en las universidades. Para alcanzar el objetivo del estudio, se utilizó el cuestionario de antimotivación para la actividad de aprendizaje, creado por N.V. Ivanova y E.V. Minaeva, dirigida a estudiantes que obtienen formación pedagógica en universidades especializadas o en departamentos pedagógicos de la universidad. El estudio empleó el factor y el análisis de correlación de los resultados, que se realizó en el software IBM SPSS Statistics 23. Se analizó la countries and the significance of negative-motivation factors within the groups of negative-motivational determinants of learning activity for students from Russia, Kazakhstan and Czech Republic. We also revealed correlation between the groups of negativemotivational determinants of learning activity in different subject groups. We revealed significant differences in determination of antimotivation for learning activity in prospective teachers from different countries. The results of the study can be used for developing psychological-pedagogical programs for decreasing and overcoming antimotivation for learning activity in students of pedagogical universities and pedagogical departments of the universities in different countries.
AlikE Content Detection in Image and Video

This paper recognizes the problem of detecting alike content from images and video for content based retrieval applications. With the development of digital multimedia data types and available bandwidth there increase a demand of image retrieval systems and the users shift from text based retrieval systems to content based retrieval systems. Selection of extracted features play an important role in content based retrieval systems. These features are used for indexing, selecting and ranking according to the user. Good features selection also reduces the time and space costs of the retrieval process. Content based image retrieval (CBIR) is a technique in which it uses visual contents to search images from the large image or video databases. Alike features can be derived from a set of feature extraction methods like SIFT and MSER. Here the features generated are then combined together to form feature code book. Both mid-level feature description techniques and multi class support vector machine is used as classifiers for detecting purposes. Analysis is done using four different image classes’ viz. cars, flowers, buildings and human faces.
Heuristic numerical and analytical models of the hydrologic controls over vertical solute transport in a domed peat bog, Jura Mountains, Switzerland

We report the results of numerical and analytical simulations to test the hypothesis that downward vertical flow of porewater from the crests of domed alpine and kettle bogs controls vertical porewater distributions of major solutes such as Ca and Mg. The domed Etang de la Gruère bog (EGr), Switzerland, characterized by a vertical downward gradient of 0·04 and stratified layers of peat, is chosen as a field site for the model calibration and evaluation. The middle 4‐m section of the 6·5 m thick bog peat is heavily humified and has a hydraulic conductivity of ∼10−5·6 cm s−1. Above and below, peat is less humified with a hydraulic conductivity of ∼10−3 cm s−1. Heuristic finite difference simulations, using Visual MODFLOW, of the bog hydraulics show that the higher conductivity peat at the bog base is critical to create the observed deep, local flow cells that substantively recharge porewater.
Investigation of the Optical Properties of PbSe/PbX Nanocrystals for Photodetector Applications

Lead selenide and lead selenide/lead sulfide core/shell nanocrystals were investigated for use in near infrared photodetectors. A colloidal synthesis method was used for both the core and core/shell configurations. The lead sulfide shell was examined in order to mitigate oxidation of the nanoparticle surface. Absorbance and photoluminescence spectra were measured at room temperature and 77 K, respectively. Transmission electron microscopy images were also obtained to confirm crystallography and size. Bulk lead selenide was simulated in WIEN2k utilizing the linear-augmented plane wave method of solving density functional theory to better understand the electronic structure of PbSe. The crystal structure, electron density, band structure and density of states are presented and discussed. The calculations correctly predicted a direct band gap at the L point in the Brillouin zone. The band gap calculated was 0.40 eV.