Miracle-dz/UniFAR-FTUs huggingface dataset:
Consumer purchase intention on Boba drinks in Kuching during Covid-19

Abstract Many businesses were badly impacted as consumer spending habit shifted due to Covid-19 outbreak. The purpose of this study is to investigate consumer purchase intention on Boba drink during Covid-19. By adopting Theory of Planned Behavior, this study explores the influence of perceived behavioral control, subjective norm, and attitude. Importantly, perceived risks is added to the conceptual model to study consumer purchase intention amid Covid-19. Boba drink is a popular beverage in every city in Malaysia, including Kuching, where one could easily spot a Boba drink outlet at almost every corner of the city. A total of 394 complete observations have been obtained from the respondents through a self-administered online survey. The outcome of the analysis uncovered that perceived behavioral control and subjective norm have significant direct relation, while attitude and perceived risks have significant adverse relation with consumer purchase intention during Covid-19. This research offers insights to Boba drink sellers to devise appropriate strategies to market their beverages by targeting consumers’ ability to buy the beverage, health-conscious belief, food safety, and attractive promotion to encourage consumers to buy their products during the pandemic.
Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta

Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. The ability of a molecule to effectively cross the placental barrier and reach the fetus determines the drug’s toxicological effects on the fetus. In this regard, our study aims to predict the permeability of molecules across the placental barrier. Based on publicly available datasets, several machine learning models are comprehensively analysed across different fingerprints and toolkits to find the best suitable models. Several dataset analysis models are utilised to study the data diversity. Further, this study demonstrates the application of neural network-based models to effectively predict the permeability. K-nearest neighbour (KNN), standard vector classifier (SVC) and Multi-layer perceptron (MLP) are found to be the best-performing models with a prediction percentage of 82%, 86.4% and 90.8%, respectively. Different models are compared to predict the chosen set of drugs, drugs like Aliskiren, some insulin secretagogues and glucocorticoids are found to be negative while predicting the permeability.
The Algebra of Systems Biology

In order to understand biochemical networks we need to know not only how their parts work but also how they interact with each other. The goal of systems biology is to look at biological systems as a whole to understand how interactions of the parts can give rise to complex dynamics. In order to do this efficiently, new techniques have to be developed. This work shows how tools from mathematics are suitable to study problems in systems biology such as modeling, dynamics prediction, reverse engineering and many others. The advantage of using mathematical tools is that there is a large number of theory, algorithms and software available. This work focuses on how algebra can contribute to answer questions arising from systems biology. This work received support from: NSF Grant DMS-0511441
Assessment of the Effect of Conflicts on Yam Production Farms in Cross River State, Nigeria

Background: This study was designed to assess the effect of conflicts on yam production in Cross River State. The specific objectives of the study were to; identify the socio-economic characteristics of the respondents, assess the effect of conflicts on yam production in the study area and ascertain the constraints faced by yam farmers in the study area. Methods: The study adopted a multi-stage sampling technique. Three blocks were selected from each of the three Agricultural zones in the state. Three cells were randomly selected from each of the blocks sampled, which gave a total of twenty-seven (27) cells. A total of 450 respondents were selected for the study. Data were collected with the aid of a structured questionnaire. Data obtained were analysed using percentage, mean and standard deviation. Result: The result of the analysis revealed that a good number of the respondents had formal education and were married (53.6%). It was equally observed that conflicts reduced yam availability (X̄=2.50) decreased productivity (X̄=2.78), displaced farmers (X̄=2.68), caused hunger and starvation (X̄=2.62) and reduced arable land (X̄=3.08). The study also noted that the following constraints affected yam production in the study area include insecurity among yam farmers and communities (X̄ = 278), high cost of labour (X̄ = 2.55), lack of funds (X = 2.58) and fear of unexpected conflicts (X̄ = 2.71) among many others. The study recommended that civil defence Corp should be posted to conflicts zones in the state to provide security to the farming communities during farming seasons. The study therefore concludes that government needs to provide compensations to yam farmers who abandoned their farms as a result of conflicts and these would encourage them to return home for their yam business enterprises.
Consistent and Non-Degenerate Model Speci…cation Tests Against Smooth Transition and Neural Network

We develop a regression model speci…cation test that directs maximal power toward smooth transition functional forms, and is consistent against any deviation from the null speci…cation. We provide new details regarding whether consistent parametric tests of functional form are asymptotically degenerate: a test of linear autoregression against STAR alternatives is never degenerate. Moreover, a test of Exponential STAR has power attributes entirely associated with the choice of threshold. In a simulation experiment in which all parameters are randomly selected the proposed test has power nearly identical to a most-powerful test for true STAR, neural network and SETAR processes, and dominates popular tests. We apply the test to U.S. output, money, prices and interest rates.
Unit Root Inference in Generally Trending and Cross-Correlated Fixed-T Panels

This article proposes a new panel unit root test based on the generalized method of moments approach for panels with a possibly small number of time periods, T, and a large number of cross-sectional units, N. In the model that we consider the deterministic trend function is essentially unrestricted and the errors obey a multifactor structure that allows for rich forms of unobserved heterogeneity. In spite of these allowances, the GMM estimator considered is shown to be asymptotically unbiased, -consistent, and asymptotically normal for all values of the autoregressive (AR) coefficient, ρ, including unity, making it a natural candidate for unit root inference. Results from our Monte Carlo study suggest that the asymptotic properties are borne out well in small samples. The implementation is illustrated by using a large sample of US banking institutions to test Gibrat’s Law.
Hearing Impairment and the Log‐Normal Distribution

SUMMARY Data on hearing impairment are studied by using a three-parameter log-normal distribution, all of whose parameters depend on covariates. The fitting algorithm is an extension of generalized linear modelling. Questions for research include the estimation of a base-line distribution of hearing threshold levels for an 'unexposed' population and the development of a model that describes how the distribution changes with age and exposure to noise. The model gives a good description of data from a recent national survey.
Rural South Indian spirometry values show wide variation compared to existing prediction equations

Background and Objective: India, a highly heterogeneous country, has no common reference standards for predicting spirometry values, with very few recent studies from south India. This study aimed to create reference equations for rural south Indian adults, based on a population-based survey in Vellore, south India and compare it with other equations from India. Methods: The data from 583 non-smoking, asymptomatic participants (30 years and older) from a spirometry-based survey for airflow obstruction (rural Vellore, 2018), were used to develop equations for FEV1, FEV1/FVC, and FVC. The dataset was divided for development (70%) and validation (30%), by gender. Differences between observed and predicted values were assessed using the new equations and comparisons made with other equations from India. Results: Predictions with Vellore rural equations were closest to the previous south Indian equations from urban Bangalore. However, the Bangalore equations led to overestimation of FVC values in males, and of both FEV1 and FVC values in females. Using the rural Vellore equations also led to a higher percent of males being classified as having airflow obstruction, compared to the Bangalore equations which underestimated airflow obstruction in this rural population. Comparison with previously derived Indian equations from other parts of the country showed pronounced variations. Conclusions: Our study reiterates the need for representative rural and urban studies of adults from various parts of India, to obtain region specific reference equations, given the wide variations in spirometry values in “normal” individuals, due to social heterogeneities of the Indian population and resulting complexities in defining normal.
THE RELATIONSHIP BETWEEN NORWEGIAN BUSINESS STUDENTS’ ATTITUDES TOWARDS MATHEMATICS AND SUCCESS IN BUSINESS EDUCATION

Although mathematical skills are an important component for business students, many students struggle to understand and meet the demands in different subjects. There is a considerable heterogeneity among the different subjects and the need for good mathematical skills varies from subject to subject. To analyse this, we apply the Attitudes Towards Mathematics Inventory (ATMI) framework. The data are collected by asking students at a business school in Norway. The results are linked to the exam grades in the various subjects. The sample consists of approximately 150 students. As a research method, the standard linear regression model is used. The results show that there is a strong positive correlation between ATMI and success in the various subjects. This applies specifically to the dimension of self-confidence in mathematics. However, there is a considerable variation between the subjects, and in some non-quantitative subjects such as marketing, no correlation was found in this study between ATMI and exam grades. As control variables in the model, gender and Grade Point Average (GPA) from the upper secondary school were included. These variables had a rather small influence on the results for the subjects, but with significant statistical effects on some subjects. This article provides insight into a key factor that can help explain how students are performing in the various business subjects
Star formation properties of Universidad Complutense de Madrid survey galaxies

We present new near-infrared J and K imaging data for 67 galaxies from the Universidad Complutense de Madrid (UCM) survey used in the determination of the SFR density of the local Universe by Gallego et al. This is a sample of local star-forming galaxies with redshift lower than 0.045, and they constitute a representative subsample of the galaxies in the complete UCM survey. From the new data, complemented with our own Gunn−r images and long-slit optical spectroscopy, we have measured integrated K-band luminosities, r−J and J−K colours, and Hα luminosities and equivalent widths. Using a maximum likelihood estimator and a complete set of evolutionary synthesis models, these observations allow us to estimate the strength of the current (or most recent) burst of star formation, its age, the star formation rate and the total stellar mass of the galaxies. An average galaxy in the sample has a stellar mass of 5×10^10 M_⊙ and is undergoing (or has recently completed) a burst of star formation involving about 2 per cent of its total stellar mass. We identify two separate classes of star-forming galaxies in the UCM sample: low-luminosity, high-excitation galaxies (HII-like) and relatively luminous spiral galaxies (starburst disk−like). The former show higher specific star formation rates (SFRs per unit mass) and burst strengths, and lower stellar masses than the latter. With regard to their specific star formation rates, the UCM galaxies are intermediate objects between normal quiescent spirals and the most extreme H II galaxies.
Identification of ABF/AREB gene family in tomato (Solanum lycopersicum L.) and functional analysis of ABF/AREB in response to ABA and abiotic stresses

Abscisic acid (ABA) is a plant hormone that plays an important regulatory role in plant growth and stress response. The AREB (ABA-responsive element binding protein)/ABF (ABRE-binding factor) are important ABA-signaling components that participate in abiotic stress response. However, genome-scale analysis of ABF/AREB has not been systemically investigated in tomato. This study was conducted to identify tomato ABF/AREB family members and analyze their response to ABA and abiotic stresses. The results show that a total of 10 ABF/AREB members were identified in tomato, which are randomly distributed on five chromosomes. Domain analysis showed that these members exhibit high protein similarity, especially in the basic leucine zipper (bZIP) domain region. Subcellular localization analysis indicated that all 10 ABF/AREB members are localized in the nucleus. Phylogenetic tree analysis showed that tomato ABF/AREB genes are divided into two groups, and they are similar with the orthologs of other plants. The analysis of cis-acting elements showed that most tomato ABF/AREB genes contain a variety of hormones and stress-related elements. Expression profiles of different tissues indicated that SlABF2 and SlABF10 play an important role in fruit ripening. Finally, qRT-PCR analysis revealed that 10 tomato ABF/AREB genes respond to ABA, with SlABF3 being the most sensitive. SlABF3, SlABF5 and SlABF10 positively respond to salt and cold stresses. SlABF1, SlABF3 and SlABF10 are significantly induced under UV radiation treatment. SlABF3 and SlABF5 are significantly induced in osmotic stress. Overall, this study may provide insight into the role of tomato ABF/AREB homologues in plant response to abiotic stresses, which laid a foundation for future functional study of ABF/AREB in tomato.
Integral combinations of Heavisides

A sufficiently smooth function of d variables that decays fast enough at infinity can be represented pointwise by an integral combination of Heaviside plane waves (i.e., characteristic functions of closed half‐spaces). The weight function in such a representation depends on the derivatives of the represented function. The represen‐tation is proved here by elementary techniques with separate arguments for even and odd d, and unifies and extends various results in the literature (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Intracranial Metastasis of Extracranial Chondrosarcoma: Systematic Review With Illustrative Case

Background Cerebral chondrosarcoma metastases are rare and aggressive neoplasms. The rarity of presentation has precluded rigorous analysis of diagnosis, risk factors, treatment, and survival. We analyzed every reported case through exhaustive literature review. We further present the first case with Maffucci syndrome. Methods Three databases, PubMed, Embase, and Google Scholar, and crossed references were queried for cerebral chondrosarcoma metastases. Extracted variables included demographics, risk factors, tumor characteristics, interventions, and outcomes. Univariate and multivariate analyses were performed. Results Fifty-six patients were included from 1,489 literature results. The average age at brain metastasis was 46.6±17.6 years and occurred at a median of 24±2.8 months from primary diagnosis. Primary tumor histology (dedifferentiated 5.0±1.5 months, mesenchymal 24±3.0 months, conventional 41±7.4 months, p<0.05) and grade (low grade 54±16.7 months vs. high-grade 10±6.4 months, p<0.001) correlated with time interval until brain metastasis. A multiple enchondromatosis syndrome occurred in 13.2% of cases. At time of brain metastases diagnosis, extracranial metastases were identified in 76.2% of cases. Median survival after the development of brain metastasis was 2.0±0.78 months with a 1-year survival of 10.0%. On regression analysis, surgery reduced brain metastasis mortality risk and radiation trended towards reduced mortality risk (surgery: hazard ratio [HR] 0.22, 95% confidence interval [CI] 0.064–0.763, p=0.017; radiation: HR 0.31, 95% CI 0.091–1.072, p=0.064). Conclusion We present a systematic review of cerebral chondrosarcoma metastases. Primary tumor histology and grade correlate with time until cerebral metastasis. Following cerebral metastasis, these tumors have poor prognosis and modestly benefit from surgery.
Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street

Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent work has produced modest increases only in the confidence of the uncertainty estimate itself. This review summarizes the contributions toward reducing the uncertainty in the aerosol forcing of climate made by satellite observations, measurements taken within the atmosphere, as well as modeling and data assimilation. We adopt a more measurement‐oriented perspective than most reviews of the subject in assessing the strengths and limitations of each; gaps and possible ways to fill them are considered. Currently planned programs supporting advanced, global‐scale satellite and surface‐based aerosol, cloud, and precursor gas observations, climate modeling, and intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved, are all essential. But in addition, new efforts are needed: (a) to obtain systematic aircraft in situ measurements capturing the multi‐variate probability distribution functions of particle optical, microphysical, and chemical properties (and associated uncertainty estimates), as well as co‐variability with meteorology, for the major aerosol airmass types; (b) to conceive, develop, and implement a suborbital (aircraft plus surface‐based) program aimed at systematically quantifying the cloud‐scale microphysics, cloud optical properties, and cloud‐related vertical velocities associated with aerosol‐cloud interactions; and (c) to focus much more research on integrating the unique contributions of satellite observations, suborbital measurements, and modeling, to reduce the persistent uncertainty in aerosol climate forcing.
Sustainable marketing activities, event image, perceived value and tourists’ behavioral intentions in the sports tourism

PurposeThis study constructs the influence mechanism model of sustainable marketing activities (SMAs), event image, commemorative product perceived value and tourists’ behavioral intentions (TBIs) in the sports tourism context of the Beijing Winter Olympic Games. Additionally, the article discusses the role of event image and product perceived value in enhancing the SMAs’ effect on TBIs.Design/methodology/approachThe research analyzed 315 valid questionnaires from tourists in the Chinese market by structural equation modeling.FindingsThe results indicate that SMAs positively impact sports tourism event image, tourists’ perceived commemorative product value and TBIs. Meanwhile, event image and product perceived value mediate the SMAs and TBIs relationship.Research limitations/implicationsConsidering SMAs as essential for sustainable development, this paper contributes to the strategic management discipline. Additionally, the research expands the analysis of event image and product perceived value in the brand theory and customer behavior research.Practical implicationsThe article outlines the principal value of SMAs implementation in enhancing behavioral intentions. It also reveals that a favorable event image and good perceived value can enhance SMAs’ effectiveness toward positively influencing TBIs, especially purchase intentions. It provides a new vision for nonprofit organizations to prioritize SMAs’ implementation in marketing strategies.Originality/valueIt is pioneering work with a complex research framework for SMAs implementation in the sports tourism context.
Study of thermal performance of double pipe heat exchanger using W-cut twisted tape

ABSTRACT An experimental analysis was carried out to estimate Nusselt number and friction factor behavior in a double pipe heat exchanger for W-cut twisted tape, in which Reynolds numbers ranging from 5500 to 16,000 are used, and the depth of W-cut to width of twisted tape ratio are 0.2, 0.4, and 0.6 in twisted tape of 10 mm width and 1 mm thickness. Effects of twist ratio are also analyzed by varying twist ratio 5, 10 and 15. It has been found that using twisted tape inserts causes turbulence and flow separation, resulting in better fluid mixing. Due to augmentation in turbulence, an enhancement in heat transfer and TPF was observed. Validation of test section done with predefined correlation and experimental results. It has been found that peak enhancement in Nusselt number and friction factor observed at Reynolds number 5500 for depth of W-cut 6 mm and twist ratio of 5 is\\are 105.47% and 301% respectively. Maximum TPF and friction factor were seen under the same circumstances. For the current analysis, the maximum TPF observed is 1.35.
A Review of Subjective Assessments in Virtual Reality for Lighting Research

Immersive virtual reality allows showing people virtual environments with high levels of presence, realism, and “feeling of being”, as if they were in the real world. With this aim, virtual environments must provide proper light distributions and elicit sensations similar to those seen in the real world. So far, experiments with human subjects are the most effective way to evaluate the accuracy of virtual reality in reproducing real spaces. This paper investigates the role of subjective assessments in lighting research using virtual reality. According to the review results, the investigations aimed at using immersive virtual reality for lighting can mainly be divided into three groups: (i) comparison between virtual and physical environments, (ii) analysis of different lighting scenarios, and (iii) investigation of users’ interaction with the virtual model. On the one hand, the results show that immersive virtual reality is a useful tool for research and design in lighting. On the other hand, they highlight the limitations that still need to be overcome. Finally, the main findings and gaps concerning the subjective assessment were listed.