Miracle-dz/UniFAR-FTUs huggingface dataset:
The Determinants of Thailand’s Road Vehicle Exports

Road vehicles, which are a major manufacturing export, can increase employment and income for the Thai population. It has therefore necessitated the effective integration of information and communication technologies to enhance the comparative advantage in international markets. The research aims to investigate the factors affecting Thailand’s road vehicle exports. The four factors ( foreign direct investment, exchange rate, openness, and GDP per capita) were analyzed in the period 1980 to 2018. The findings from the cointegration test shown that all four factors were positively related to road vehicle exports. The impulse response functions present that the real exchange rate was essential for road vehicle exports to grow from the third year onwards. A variance decomposition analysis revealed that GDP per capita and real exchange rate were an important factor of the ten-year forecast for road vehicle exports, followed by trade openness and foreign direct investment. Based on empirical research, the growth rate of GDP per capita can help to expand production capacity and to expedite exports. The depreciation of the Thai baht attracts more foreign investment and demand for Thai products. The growth in trade openness and foreign direct investment is also linked to increased export volume in this sector. Therefore, to promote sustainable growth in vehicle sales, the government needs to expand market destinations and entice foreign investors by offering more incentives.
New Dataset for Forecasting Realized Volatility: Is the Tokyo Stock Exchange Co-Location Dataset Helpful for Expansion of the Heterogeneous Autoregressive Model in the Japanese Stock Market?

This study analyzes the importance of the Tokyo Stock Exchange Co-Location dataset (TSE Co-Location dataset) to forecast the realized volatility (RV) of Tokyo stock price index futures. The heterogeneous autoregressive (HAR) model is a popular linear regression model used to forecast RV. This study expands the HAR model using the TSE Co-Location dataset, stock full-board dataset and market volume dataset based on the random forest method, which is a popular machine learning algorithm and a nonlinear model. The TSE Co-Location dataset is a new dataset. This is the only information that shows the transaction status of high-frequency traders. In contrast, the stock full-board dataset shows the status of buying and selling dominance. The market volume dataset is used as a proxy for liquidity and is recognized as important information in finance. To the best of our knowledge, this study is the first to use the TSE co-location dataset. The experimental results show that our model yields a higher forecast out-of-sample accuracy of RV than the HAR model. Moreover, we find that the TSE Co-Location dataset has become more important in recent years, along with the increasing importance of high-frequency trading.
Robust Smooth Sliding-Mode-Based Controller with Fixed-Time Convergence for Missiles considering Aerodynamic Uncertainty

This paper designed a smooth fixed-time-convergent sliding mode controller for a missile flight system considering aerodynamic uncertainties. Fixed-time convergence theory is incorporated with the sliding mode control technique to ensure that the system tracks desired commands within uniform bounded time under different initial conditions. Unlike previous terminal sliding mode approaches, not only is the bound of settling time independent of initial state, indicating that performance metrics like convergence rate can be predicted beforehand, but the control input is designed to be smooth based on adaptive estimations and some mathematical results without introducing any discontinuous items like the signum function, which avoids the problem of chattering consequently. A cascade control structure is employed with the derived control algorithm, and therein, the control input signal is obtained. Finally, a number of simulations are carried out and demonstrate the effectiveness of the designed controller.
The relationship between savings and economic growth at the disaggregated level

While the literature, both international and in South Africa, is relatively rich in studies on the determinants of foreign direct investment as well as the determinants of savings, none of the work done on South Africa has made use of disaggregated savings data to understand whether there is an observable difference in the marginal propensity to save of the different economic sectors. Thus, this paper attempts to assess the marginal propensity to save by the household, corporate and government sectors in South Africa. The results of the econometric analysis demonstrate that the greatest responsiveness of savings to GDP growth occurs amongst corporates. These findings should inform the South African government on how to regulate sectoral taxation that intends to encourage savings, given the low level of savings in the country.
A Review of the Critical Period Hypothesis in Second Language Acquisition

The issue about the Critical Period Hypothesis in the first and second language acquisition has been on dispute since the notion of the critical period in biology was proposed. In this paper, We make a review of the studies supporting and opposing the existence of a critical period in second language acquisition from the perspectives of psycholinguistics, cognitive linguistics and neurolinguistics in different language aspects. We concluded that no consensus on this controversial issue was found, because of the different research methods, materials, participants in different studies and the discrepant measurement standards and understanding of scholars about the critical period in language acquisition. We also suggested significant implications of the research findings for second language teaching, and made some recommendations for the future research on age effect upon second language acquisition in China.
Modelling two-way relationship between innovation and internationalisation: does learning by export matter?

Abstract This study has picked up an essential question for the Indian pharmaceutical industry, whether innovation and internationalisation follow a two-way relationship during the product patent regime. This study analyzes the role of product, process and variety of innovation on exporting activities of 168 pharmaceutical firms from 2006 to 2013. For this purpose, this study applies two-stage least square probit and tobit model on innovation and export equation separately. The results show the feedback relation between export and innovative performance while there is a differential effect of product and process innovation on exporting. The results strongly support the learning-by-exporting and product-life cycle hypothesis. European origin firms are more likely to be innovative and export-oriented, while U.S. origin firms influence the firms' innovative performance. Business strategy should take account of benefits from the dynamic interaction of innovative and exporting activities and make their strategic decisions carefully.
Performance Modeling and Placement of Transforms for Stateful Mediations

In this paper we propose a new technique for placing large delivey plans for streaming systems on a network of machines to optimize efficiency measures such as latency. In the model we consider, there is a large network of machines and the different fixed end-points of the network act as publishers and subscribers of information. Information demanded by subscribers is a transformed view of the information published by the publishers. The transformed view is the outcome of an acyclic network of simple transformations operating on the publishers’ information or some intermediate transformed view of it. We propose algorithms for the optimal placement of the acyclic transform network on the network of machines. As an example scenario to evaluate the efficacy of our algorithms we consider SQL queries on streaming relational tables. The transform network in this case is the SQL operator tree for the query. We first show how to model the performance of individual operators acting on distributed streams and then develop the optimal placement strategy for different optimization measures. We present our work on a distributed message-oriented middleware and a programming platform for large-scale publish-subscribe applications called SMILE. In our system, we use incremental implementation each of the relational operator for streaming data. We demonstrate that our technique performs significantly better than straightforward approaches like greedy, and random placement.
Title Fundamental Frequency Variation of Neonatal Spontaneous Crying Predicts Language Acquisition in Preterm and Term Infants

Right © 2017 Shinya, Kawai, Niwa, Imafuku and Myowa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Factors affecting the adoption of BYOD in South African small and medium enterprises

The advancement in technological development is now altering the conventional order in the diffusion of Information Technology innovation from a top‐down approach (organization to employees) to a bottom‐up approach (employees to organization). This change is more notable in developed economies and has led to the bring your own device (BYOD) phenomenon, which promises increased productivity for employees and their organizations. There have been several studies on the corporate adoption of BYOD, but few have investigated this phenomenon from a small and medium enterprise (SME) perspective and from developing countries specifically. This study investigated the BYOD phenomenon in South African SMEs. The goal was to identify contextual factors influencing BYOD adoption. A conceptual framework using the Perceived EReadiness Model (PERM) was adopted. The study took an interpretive stance and was qualitative. Data was collected from SMEs using semi‐structured interviews and analyzed using a thematic analysis approach. The findings show that for BYOD to be adopted and institutionalized in an SME, there needs to be organizational and environmental readiness. Organizational readiness in terms of awareness, management support, business resources, human resources, employees' pressure, formal governance, and technological readiness. Environmental readiness in terms of market forces, support from industry, government readiness and the socio‐cultural factor. These readiness factors present both opportunities and challenges that SMEs in developing countries need to concentrate on as they prepare for and use BYOD.
Deep convolutional neural networks for classifying breast cancer using infrared thermography

ABSTRACT Infrared thermography is a technique that can detect anomalies in temperature patterns which can indicate some breast pathologies including breast cancer. One limitation of the method is the absence of standardised thermography interpretation procedures. Deep learning models have been used for pattern recognition and classification of objects and have been adopted as an adjunct methodology in medical imaging diagnosis. In this paper, the use of a deep convolutional neural network (CNN) with transfer learning is proposed to automatically classify thermograms into two classes (normal and abnormal). A population of 311 female subjects was considered analysing two approaches to test the CNN’s performance: one with a balanced class distribution and the second study in a typical screening cohort, with a low prevalence of abnormal thermograms. Results showed that the transfer-learned ResNet-101 model had a sensitivity of 92.3% and a specificity of 53.8%, while with an unbalanced distribution the values were 84.6% and 65.3%, respectively. These results suggest that the model presented in this work can classify abnormal thermograms with high sensitivity which validates the use of infrared thermography as an adjunct method for breast cancer screening.
The Monetary Model of the Exchange Rate under High Inflation -The case of the Turkish Lira/US Dollar

This paper applies the Johansen cointegration technique to examine the validity of the monetary model of exchange-rate determination as an explanation of the Turkish lira/United States dollar relationship over the 1987:1? 2000:12 period. A single cointegrating vector is identified whose coefficients conform in broad terms to the restrictions implied by the monetary model, thus lending support to the interpretation of the model as describing a long-run equilibrium relationship. This support is reinforced by the results derived from the adjustment coefficient, which identify a clear short-run tendency of the exchange rate to revert to the equilibrium value defined by the estimated long-run model. After finding support for the long-run monetary model, we calculate misalignment from the estimated long-run relationship to evaluate whether the lira was overvalued before the eve of the 2001 financial crisis in Turkey. Calculated misalignment shows a substantial overvaluation of the lira before the crisis.
Alternative estimating procedures for multiple membership logit models with mixed effects: indirect inference and data cloning

Multiple-membership logit models with random effects are logit models for clustered binary data, where each statistical unit can belong to more than one group. For these models, the likelihood function is analytically intractable. We propose two different approaches for parameter estimation: data cloning and indirect inference. Data cloning computes maximum likelihood estimates, through the posterior distribution of an adequate Bayesian model fitted on cloned data. We implement a data cloning algorithm specific for the case of multiple-membership models. Indirect inference is a non-likelihood based method which uses an auxiliary model to select sensible estimates. We propose an auxiliary model having the same dimension of parameter space as the target model, which is particularly convenient to reach good estimates very fast. A Monte Carlo experiment compares the two approaches on a set of simulated data. We report also Bayesian posterior mean and INLA hybrid data cloning estimates for comparison. Simulations show a negligible loss of efficiency for the indirect inference estimator, compensated by a relevant computational gain. The approaches are then illustrated with a real example on matched paired data.
A Study on Extent of Adoption of Agri Waste Management Practices by the Farmers of Medak District of Telangana, India

Agricultural waste refers to waste produced from agricultural operations, including waste from farms, poultry houses and slaughterhouses. The present study was focused on, to study the extent of adoption of agri waste management practices and its relationship with the profile of the farmers. The Ex-post facto research design was adopted for the study with a sample of 120, covering Medak district of Telangana state. From the analysis, it was found that majority of the farmers (45.80%) fall under the category of medium adoption, followed by low (27.50%) and high (26.70%) adoption categories with regards to the adoption of agri waste management practices. Correlation analysis between extent of adoption of agri waste management practices and profile characteristics of respondents revealed that, information seeking behavior had positive and significant relationship with adoption at one percent level of significance. The variables education, cropping pattern, infrastructure facilities, innovativeness, achievement motivation, training undergone had positive and farming experience had negative significant relationship with adoption at five per cent level of Original Research Article Ravi et al.; AJAEES, 39(4): 125-133, 2021; Article no.AJAEES. 68238 126 significance. The remaining variables, age, cropping intensity had negatively and farm size, level of aspiration had positively non-significant relationship with extent of adoption of agri waste management practices.
The Credit Channel of Fiscal Policy Transmission.

We propose and test a new channel through which fiscal policy changes can affect the supply of intermediated credit and the real economy. Banks that have greater exposure to firms expected to repatriate a significant amount of foreign income as a result of a 2004-2005 U.S. tax holiday subsequently increase lending to other, purely domestic firms during the period of the tax holiday, leading to higher investment at these firms. Our results complement the existing literature on the credit channel of monetary policy transmission and highlight an important indirect spillover effect of fiscal policy changes on credit-constrained firms.
A time‐variable, phase‐dependent emission line in the X‐ray spectrum of the isolated neutron star RX J0822−4300

RX J0822−4300 is the central compact object associated with the Puppis A supernova remnant. Previous X-ray observations suggested RX J0822−4300 to be a young neutron star with a weak dipole field and a peculiar surface temperature distribution dominated by two antipodal spots with different temperatures and sizes. An emission line at 0.8 keV was also detected. We performed a very deep (130-ks) observation with XMM–Newton, which allowed us to study in detail the phase-resolved properties of RX J0822−4300. Our new data confirm the existence of a narrow spectral feature, best modelled as an emission line, only seen in the ‘soft’-phase interval – when the cooler region is best aligned to the line of sight. Surprisingly, comparison of our recent observations to the older ones yields evidence for a variation in the emission-line component, which can be modelled as a decrease in the central energy from ∼0.80 keV in 2001 to ∼0.73 keV in 2009–10. The line could be generated via cyclotron scattering of thermal photons in an optically-thin layer of gas, or, alternatively, it could originate in low-rate accretion by a debris disc. In any case, a variation in energy, pointing to a variation of the magnetic field in the line-emitting region, cannot be easily accounted for.
Mutation Testing for Physical Computing

Physical computing, which builds interactive systems between the physical world and computers, has been widely used in a wide variety of domains and applications, e.g., the Internet of Things (IoT). Although physical computing has witnessed enormous realisations, testing these physical computing systems still face many challenges, such as potential circuit related bugs which are not part of the software problems, the timing issue which decreasing the testability, etc.; therefore, we proposed a mutation testing approach for physical computing systems to enable engineers to judge the quality of their tests in a more accurate way. The main focus is the communication between the software and peripherals. More particular, we first defined a set of mutation operators based on the common communication errors between the software and peripherals that could happen in the software. We conducted a preliminary experiment on nine physical computing projects based on the Raspberry Pi and Arduino platforms. The results show that our mutation testing method can assess the test suite quality effectively in terms of weakness and inadequacy.
Inside the ‘black box’ of a long-term sport-based youth development boxing academy in New Zealand

Abstract This study examined a well-established, boxing-based positive youth development program for boys in New Zealand. The authors were cognizant of calls for investigation into what occurs within the ‘black box’ of successful programs. The study was interested in identifying and describing what processes and procedures occurred within the Naenae Boxing Academy and the impact that participation in the academy had on the boys in their wider lives. The study used a mixed method approach involving the systematic analysis of boxing sessions, extensive interviewing, surveys of participants, and multiple observations. The program was found to provide a consistent caring and safe environment for the boys. The teaching of positive values to the boys was central to the program, and it was also found that the values learnt impacted on the boys’ behaviors and relationships outside of the academy.
Impact of flood regime on phytoplankton communities in the large African reservoir, Lake Nasser, Egypt

Lake Nasser is a reservoir of freshwater for drinking and irrigation in Egypt and it constitutes an important share in the fisheries sector. This study aims to acquire a better understanding of the status of phytoplankton distribution in Lake Nasser under the current flood regime and before the construction of the Grand Ethiopian Renaissance Dam (GERD). Samples were collected from fifteen sites representing different lake sectors along the main channel of the lake during 2016−2017. Approximately 103 species were recorded, belonging to six different classes, dominated by Cyanobacteria, Bacillariophyceae, Chlorophyceae, whereas Euglenophyceae, Dinophyceae and Chrysophyceae were rare. Based on the abundance of phytoplankton species, the pre-flood and post-flood seasons were very well discriminated. A major blooming of Cyanobacteria in the Tushka sector was detected during the pre-flood season, whereas this phenomenon diminished in the post-flood period when Bacillariophyceae and Chlorophyceae appeared. The results of this study indicated that the most important factors affecting phytoplankton species distribution during pre-flood and post-flood seasons are temperature, nutrients and total dissolved solids. The study confirms that flood regime substantially affects the phytoplankton abundance and distribution in Lake Nasser.
Adolescents challenging discrimination: The benefits of a perspective-taking and action-planning intervention on self-efficacy

Discrimination is widespread and often goes unchallenged. This field experiment with adolescents (N = 639) tested a group discussion designed to increase perceived importance and self-efficacy around challenging discriminatory language. The intervention, which involved perspective-taking and action-planning, led to greater self-efficacy, on delayed measures against active controls, particularly among White British participants.
ASSESSMENT OF MYCOFLORA OF RAW MATERIAL USED IN ASAVA AND ARISHTA PREPARATION IN AYURVEDA

The study was designed to investigate and identify the common fungi present on the surface of the raw material used for asava and arishta preparation. The raw materials were collected from the local vendor in the nearby market. Mycological analysis of the samples was carried out for the detection of fungi on the standard media. Some of these isolates obtained are reported to produce certain secondary metabolites. Five different raw materials viz. nagarmotha (Cyperus rotundus), sugandhbala (Pavonia odorata), dhyatiphool (Woodfordia fructicosa), gudwel (Tinospora cardifolia) and sunthi (Zingiber officinale) were collected. The common fungal isolates obtained belonged to the species Aspergillus, Mucor, Rhizopus, Penicillium and some filamentous yeast were also obtained.
Two stable-by-homogenization models in simple shearing of rate-dependent non-homogeneous materials

In this paper we study two models, the viscoplastic model and the thermoviscous model, of rate-dependent non-homogeneous materials with non-oscillating strain-rate sensitivity submitted to simple quasistatic shearing. We prove that the two models are stable by homogenization, i.e. that the equations in both the heterogeneous problems and the homogenized one have the same form, and we give explicit formulas for the homogenized (effective) coefficients. These formulas depend on the initial conditions, but not on the boundary conditions. Our theoretical results are illustrated by a numerical example.