Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Analysis of an Augmented Schumpeterian Endogenous Growth Model

This study conducts an empirical analysis of an augmented Schumpeterian endogenous growth theory using aggregate-level data from 1981 to 2017 for 31 OECD countries. Despite a considerable number of studies analysing endogenous growth, cross-country analyses utilising estimators robust to endogeneity-bias and controlling for the macroeconomic effect of institutions are still rare. In this paper, we employ a relatively consistent estimator to analyse an augmented neoclassical production function that links output per worker to capital accumulation, technological progress, and institutions. Our results from the extended system of generalised method of momentS estimation align with the mainstream consensus that capital accumulation and technological progress or innovation, in the form of R&D activities, determine the level of output per worker in the long run. But in addition, we find that effective institutions underlie the innovation effect. On average, the impact of R&D activities on output per worker is higher in countries with more effective institutions.
Stall Model Identification of a Cessna Citation II from Flight Test Data Using Orthogonal Model Structure Selection

Since 2019, a key element of simulator-based training of airline pilots is stall training. A major and still largely open research question is which level of model fidelity is required for effective training. As part of an effort to answer this question, a model of the quasi-steady stall dynamics of a Cessna Citation II aircraft is identified from flight test data that was specifically collected for this research at an altitude of 5,500 m. To ensure any reductions in elevator and aileron effectiveness during stall were also explicitly measured, the test pilots used additional quasi-random flight test inputs. The considered stall model structure is based on Kirchoff's theory of flow separation. During identification, the nonlinear and linear parameters of the model are estimated in separate, recursively executed, steps. This separation enables the application of a semi-objective model structure selection method using multivariate orthogonal functions for the aerodynamic coefficients included in the model. This approach shows that stall-related effects should be included in the model equations for lift, drag, and pitch moment. Overall, it is found that the model parameters were consistently estimated from the flight test data and that the model accurately describes the aircraft's stall dynamics in the considered flight condition. The developed methodology is concluded to be well-suited for the direct identification of stall models from flight test data.
Is Islamic Bank More Stable Than Conventional Bank? Evidence From Islamic Rural Banks in Indonesia

This study investigates whether Islamic rural banks perform better than conventional rural banks as their competitor in Indonesia. To measure Islamic rural banks' financial performance, we apply financial stability using Z-score and profitability using the return on assets. We use monthly time series data from January 2009 to December 2018. The dynamic regression of the Autoregressive Distributed Lag (ARDL) model is then employed. The results report that the Z-Score of Islamic rural banks is higher than the Z-Score of conventional rural banks. This finding shows that Islamic rural banks are less risky than conventional rural banks. However, the Islamic rural banks' financial stability is very vulnerable to changes in equity, output, and inflation than conventional rural banks. Although the Islamic rural banks' profit rate is lower compared to conventional rural banks, it is considered more stable. The profit of Islamic rural banks is affected by size, equity, domestic output, and inflation.
Co-occurrence frequency in vegetation patches decreases towards the harsh edge along an arid volcanic elevational gradient

Positive plant–plant interactions are thought to drive vegetation patterns in harsh environments, such as semi-arid areas. According to the stress-gradient hypothesis (SGH), the role of positive interactions between species (facilitation) is expected to increase with harshness, predicting associated variation in species composition along environmental gradients. However, the relation between stress and facilitation along environmental gradients is debated. Furthermore, differentiating facilitative interactions from other underlying mechanisms, such as microtopographic heterogeneity, is not trivial. We analysed the spatial co-occurrence relationships of vascular plant species that form patchy vegetation in arid lapilli fields (tephra) from recent volcanic eruptions on La Palma, Canary Islands. Assuming a harshness gradient negatively correlated with elevation because the lower elevations are more arid and water availability is considered the most limiting resource, and that an outcome of facilitation is plants co-occurring in the same patch, from the SGH we expected a greater degree of co-occurrence at lower elevation. We tested this at both the species and the individual plant level. We analysed the species composition of 1277 shrubby vegetation patches at 64 different sampling points, ranging from the coast to around 700 m a.s. l. Patch morphology and microtopographic heterogeneity variables were also measured, to account for their potential effects on the species composition of patches. We used generalized linear models and generalized mixed-effects models to analyse species richness, number of individuals in patches and percentage of patches with positive co-occurrences, and a pairwise co-occurrence analysis combined with a graphical network analysis to reveal positive links between 13 of the species. We found that the percentage of patches with positive co-occurrences increased at higher elevations, in contrast to the predictions of the SGH, but in accordance with a refined stress-gradient hypothesis for arid sites, in which characteristics of the interacting species are incorporated.
Molecular analysis of functional domain and protein motif of endoglucanase gene in marine bacteria isolated from Eucheuma sp. and Sargassum sp.

Marine bacteria which are symbionts with Eucheuma sp. and Sargassum sp. has the ability to convert seloluse into glucose. These processes are important during bioethanol production. Identification using PCR and 16S rRNA primers showed that the symbiotic bacteria in Eucheuma sp. was B. subtilis (97% identical to accession number NR. 027552.1) and symbiotic bacteria in Sargassum sp. was B. thuringiensis (97% identical to access number NR. 043403.1). Cellulotic indexes were identified for B. subtilis (2.477 mm) and B. thuringiensis (6.102 mm). Amplification of the endoglucanase gene were conducted with Bac-EuF and Bac-EuR primers in B. subtilis with size at 1416 bp (95% identical to accession number WP_017696508.1), whereas in B. thuriengeinsis the size was 1251 bp (92% identical to the accession number EEM47662). In silico analysis of the endoglucanase gene, showed that the catalytic and cellulose binding domains of B. subtilis were GH5 (aa residue 1-70) and CBM3 (aa residue 131-212), while in B. thuringiensis only GH8 catalytic domains were identified (aa residue 30 -370). The protein motif of the endoglucanase gene B. subtilis and B. thuringiensis had a high similarity characterized by the asn_glycosylation, camp_phospho_site, ck2_phospho_site, myristyl and pkc_phospho_site motif.
Prediction of COVID-19 Cases using Machine Learning for Effective Public Health Management

COVID-19 is a pandemic that has affected nearly every country in the world At present, sustainable development in the area of public health is considered vital to securing a promising and prosperous future for humans However, widespread diseases, such as COVID-19, create numerous challenges to this goal, and some of those challenges are not yet defined In this study, a Shallow Single-Layer Perceptron Neural Network (SSLPNN) and Gaussian Process Regression (GPR) model were used for the classification and prediction of confirmed COVID-19 cases in five geographically distributed regions of Asia with diverse settings and environmental conditions: namely, China, South Korea, Japan, Saudi Arabia, and Pakistan Significant environmental and non-environmental features were taken as the input dataset, and confirmed COVID-19 cases were taken as the output dataset A correlation analysis was done to identify patterns in the cases related to fluctuations in the associated variables The results of this study established that the population and air quality index of a region had a statistically significant influence on the cases However, age and the human development index had a negative influence on the cases The proposed SSLPNN-based classification model performed well when predicting the classes of confirmed cases During training, the binary classification model was highly accurate, with a Root Mean Square Error (RMSE) of 0 91 Likewise, the results of the regression analysis using the GPR technique with Matern 5/2 were highly accurate (RMSE = 0 95239) when predicting the number of confirmed COVID-19 cases in an area However, dynamic management has occupied a core place in studies on the sustainable development of public health but dynamic management depends on proactive strategies based on statistically verified approaches, like Artificial Intelligence (AI) In this study, an SSLPNN model has been trained to fit public health associated data into an appropriate class, allowing GPR to predict the number of confirmed COVID-19 cases in an area based on the given values of selected parameters Therefore, this tool can help authorities in different ecological settings effectively manage COVID-19
A Latent Space Modeling Approach to Interfirm Relationship Analysis

Interfirm relationships are crucial to our understanding of firms’ collective and interactive behavior. Many information systems-related phenomena, including the diffusion of innovations, standard alliances, technology collaboration, and outsourcing, involve a multitude of relationships between firms. This study proposes a latent space approach to model temporal change in a dual-view interfirm network. We assume that interfirm relationships depend on an underlying latent space; firms that are close to each other in the latent space are more likely to develop a relationship. We construct the latent space by embedding two dynamic networks of firms in an integrated manner, resulting in a more comprehensive view of an interfirm relationship. We validate our approach by introducing three business measures derived from the latent space model to study alliance formation and stock comovement. We illustrate how the trajectories of firms provide insights into alliance activities. We also show that our proposed measures have strong predictive power on stock comovement. We believe the proposed approach enriches the methodology toolbox of IS researchers in studying interfirm relationships.
Calculation of the Absorption of Sound by the Atmosphere

This Standard provides the means to calculate atmospheric absorption losses of sound from any source, moving or stationary, for a wide range of meteorological conditions. The atmosphere is assumed to be still, homogeneous moist air of normal composition. Non-homogeneous atmospheres can be divided into horizontal layers within which homogeneous conditions can be assumed. Attenuation coefficients for puretone sounds are calculated by means of equations (or a table) over ranges of frequency, and the humidity, pressure, and temperature of the atmosphere. For sounds analyzed by fractional-octave-band filters (e.g., one-third-octave-band filters), alternative methods are provided in annexes to calculate the attenuation caused by atmospheric absorption from that specified for pure-tone sounds. This is a preview of "ANSI/ASA S1.26-2014 . ". Click here to purchase the full version from the ANSI store.
Effects of Vermicompost, Compost and Digestate as Commercial Alternative Peat-Based Substrates on Qualitative Parameters of Salvia officinalis

Peat is a common substrate used for the cultivation of potted plants. However, the use of peat in horticulture has recently been questioned from an environmental standpoint, since it is a non-renewable resource and plays a major role in atmospheric CO2 sequestration. The aim of this work was to assess the potentialities of substrates obtained from vermicompost, compost and anaerobic digestion processes to partially substitute peat for sage (Salvia officinalis L.) cultivation. Therefore, we planned an experiment to assess the effect of these substrates on essential oil (EO) yield and composition, as well as on leaf nutrients concentration of sage plants. The three substrates were mixed with commercial peat (Radicom) at a ratio of 40% of alternative substrates and 40% of commercial peat. The chemical properties of the alternative substrates did not affect the leaf content of macro and micronutrients, as well as of heavy metals. Moreover, the EO yield and quality was not affected by the substrates and did not differ among them. Results provided evidence that the three alternative substrates can be used to partially substitute peat in soilless cultivation of sage plants. However, due to the higher values of the electrical conductivity of the substrates obtained from composting and anaerobic digestion processes, such substrates must be used with caution.
Meningkatkan penerapan SAK EMKM dengan persepsi usaha dan kesiapan pelaku UMKM

UMKM (Micro Small Medium Enterprises) plays an important role in developed countries, particularly in Indonesia, which works absorbing many workers to reduce the number of unemployment. This research aims to examine the effect on the application of accounting recording systems, accounting comprehensions, business perceptions, and UMKM preparedness in implementing SAK EMKM. The objects of the research are UMKM in Yogyakarta. The respondents were 120 UMKM owners. This study is using multiple regression analysis to examine the hypothesis. The research method uses purposive sampling under the criteria in UU No. 20 Tahun 2008 tentang Kriteria UMKM. The result indicates that the hypothesis of the accounting recording system and comprehensions does not affect the implementation of SAK EMKM. Meanwhile, the hypothesis of business perceptions and UMKM preparedness has significant positive effect on the implementation of SAK EMKM.
Emotion Recognition Ability as a Predictor of Well-Being During the COVID-19 Pandemic

This study examined emotion recognition ability (ERA) as a predictor of positive and negative affect in two Australian and one German-speaking samples (total N = 469) during the first 2 weeks of major public life restrictions in the COVID-19 pandemic in March/April 2020. Individuals with higher ERA did not report more positive affect, but they felt less burdened and reported less negative affect. This association was fully mediated by lower COVID-19-related media consumption and less negative affect after reading an eyewitness report from an Italian city with a high COVID-19 death toll. However, higher ERA was also related to arguing more with close others. For low-to-medium ERA, an adaptive cognitive emotion regulation style predicted lower media consumption and for medium-to-high ERA, a maladaptive regulation style marginally increased the perceived likelihood of experiencing a similar situation as in Italy, suggesting that regulation style may moderate the ERA–affect relationship.
Sensing Horizontally Oriented Frozen Particles With Polarimetric Radio Occultations Aboard PAZ: Validation Using GMI Coincident Observations and Cloudsat a Priori Information

The sensitivity of PAZ’s Polarimetric Radio Occultation (PRO) observations to horizontally oriented frozen particles is assessed using coincident measurements from the Global Precipitation Measurement (GPM) core satellite’s radiometer GPM Microwave Imager (GMI) and ancillary information from Cloudsat. The difference between the horizontal and vertical polarizations of the GMI observed radiances at 166 GHz, indicative of horizontally oriented particles, is compared with the PAZ differential phase shift observations. A clear positive trend is observed, exhibiting a good correlation between the two observations. The radiometer absolute observations and polarization differences (PD) are then used to build a lookup table of ice water content (IWC) vertical profiles, using coincident observations between GPM and Cloudsat. The vertical profiles of IWC, along with the information of the radiometric PDs and some simple assumptions, are used to simulate the expected PAZ differential phase shift observations. The validation with the PAZ and GPM coincident measurements shows a high correlation between the simulated and observed differential phase shift, therefore proving the sensitivity of polarimetric radio occultations to horizontally oriented frozen particles. These results demonstrate that PRO can not only sense the precipitation near the surface (the original goal of the mission) but also the frozen particles near and well above the freezing level, providing additional detail of the cloud vertical structure.
Foreign Ownership and Corporate Social Responsibility: Evidence from China

This paper employs the data of corporate social responsibility rating score of A-share listed companies in China from 2009 to 2018 as a sample to verify the impacts of foreign ownership on corporate social responsibility. Furthermore, this paper explores the moderating role of legal institutional distance and economic institutional distance in the impact of foreign ownership on corporate social responsibility. The empirical results of panel data models show that: Firstly, foreign ownership has a significant positive impact on corporate social responsibility. Secondly, legal institutional distance and economic institutional distance have a positive moderating role in the impacts of foreign ownership on corporate social responsibility. The results of propensity score matching, two-stage least squares and alternative variables methods also give strong backing to the above conclusions. Finally, this paper puts forward that China’s listed companies are supposed to make full use of the supervision power of foreign ownership to promote corporate social responsibility.
Effect of Growth Hormone-releasing Hormone Gene Polymorphism (GHRH/HAEIII) on First Lactation Milk Yield and Milk Composition Traits in Sahiwal Cattle

Background: Growth hormone-releasing hormone (GHRH), also known as somatoliberin is a releasing hormone of growth hormone (GH). GHRH is a peptide hormone found mainly in the hypothalamus. The gene is significantly associated with increase milk yield in cattle. The objective of this study was to identify the polymorphism in the GHRH gene (GHRH/HaeIII) and to evaluate the relationship between the polymorphism with the breeding values for first lactation milk production and composition traits of Sahiwal cattle reared using PCR-RFLP. Methods: A total of 130 animals were included in the study. PCR-RFLP analysis of each 297bp PCR product was carried out using HaeIII restriction enzyme. The single trait animal model was considered for the estimation of breeding values using WOMBAT software. To study the effect of genotype on the individual trait, PROC GLM (SAS 4.3) was used.Result: PCR-RFLP analysis of GHRH gene revealed three genotypes with genotypic frequencies as; 0.05 (AA), 0.42 (AB) and 0.53 (BB). The allelic frequencies for A and B allele were 0.26 and 0.74, respectively. Sahiwal cows with AA genotype have significantly higher (p less than 0.017) fat percentage in milk while the cows with BB genotype; while the BB genotype cows characterized by significantly higher (p less than 0.025) first lactation 305 day milk yield. Among the three genotypes, BB was most abundant while AA genotype was rarest in the screened Sahiwal samples. The identified potential genetic marker could be used for the development of Marker Assisted Selection (MAS) strategy for higher milk yield and milk composition traits in Sahiwal cattle.
Experiences of Front-Line Medical Staffs Fighting Against Coronavirus Disease 2019: A Meta-Synthesis of Qualitative Studies

Background: To explore the experiences of front-line medical staffs fighting against Coronavirus Disease 2019 (COVID-19) by synthesizing evidence from a meta-synthesis of qualitative studies. Methods: We conducted a meta-synthesis to integrate qualitative studies on experiences of front-line medical staffs fighting against COVID-19. Six databases were searched from inception to 1 November 2020, including PubMed, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health (CINAHL), PsycINFO, and Scopus. The Critical Appraisal Skills Programme (CASP) qualitative research appraisal tool was used to appraise the quality of included studies. Thematic synthesis was used to synthesize the data from included studies. Findings: A total of 26 studies were included and six themes were identified: (1) psychological and emotional experience in different stages; (2) social experience; (3) challenges and difficulties; (4) coping styles; (5) demands; (6) growth and transcendence. Interpretation: This meta-synthesis reflects diverse experiences of front-line medical staffs fighting against COVID-19. Appropriate psychological support and social support should be provided to front-line medical staffs. Managers should pay attention to needs of front-line medical staffs for improving professional capability and ensure sufficient supplies to respond to similar crisis. Funding Statement: This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Declaration of Interests: We declare no competing interests.
Electronic Banking Service Quality: Perception of Customers in the Greater Accra Region of Ghana

Abstract The purpose of this study is to examine the impact of electronic banking service quality (SQ) on customer satisfaction (CS) and customer loyalty (CL). It also sought to compare differences between SQ delivery of domestic and foreign origin banks operating in the Greater Accra Region of Ghana. Structural equation modeling (SEM) was employed to investigate the relationships between the dimensions of electronic banking SQ, CS and CL. In addition, the Wilcoxon-Mann-Whitney test was also conducted to establish the differences in electronic banking SQ between local banks and foreign banks. The results show that, all four dimensions of SQ, namely convenience, ease of use, accessibility, and affordability were found to be significant positive drivers of CS. The study also found that CS fully mediates the relationship between all four electronic banking SQ dimensions and CL. Additionally, the study reports that on average foreign origin banks deliver better electronic banking SQ to their customers than domestic banks. Domestic banks should invest more in improving electronic banking SQ to drive CS, CL and ultimately firm performance. The findings of this study reinforce literature on the positive influence of SQ on CS and CL.