Miracle-dz/UniFAR-FTUs huggingface dataset:
Foreign direct investment, financial development and economic prosperity in major south Asian economies

PurposeThis paper empirically examines the relationship between foreign direct investment, financial development and other macroeconomic variables like trade openness, domestic investment and labour force and that of GDP per capita in select South Asian countries, i.e. India, Sri Lanka and Pakistan for the period 1990–2018.Design/methodology/approachThe study uses various econometrics tools such as Pedroni, Kao and Johansen–Fisher panel cointegration test, Panel FMOLS and DOLS and Granger causality in order to analyse the long-run and short-run dynamics among the variables under consideration.FindingsThe results of the panel data estimation techniques employed imply that there is a short-run causality running from GDP per capita to FDI and financial development, and results from FMOLS and DOLS indicate that FDI and financial development have positive impacts on GDP per capita in the countries under consideration.Originality/valueIn this paper, we use a dynamic macroeconomic modelling framework to examine the effect of FDI and financial development on per capita income in three major south Asian economies, which are categorized as three Non-Least Developed Contracting States under the South Asian Free Trade Area (SAFTA), 2006, established with an aim to facilitate free trade among them. Considering the diversity of the level of growth experienced by these economies, the study uses appropriate panel regression techniques. Therefore, in addition to proper formulation of policies directed towards scaling up of export and import levels, the respective authorities should also take care that the political stability and institutional quality are maintained.
The Application of ICT and Smart Technologies in Polish Museums—Towards Smart Tourism

The concept of Smart Tourism is rapidly developing alongside Smart Cities, with increasing numbers of ICT solutions being applied for the convenience of travelers as well as for gathering information, which has become a valuable resource. The vast progress in the development of Information Technologies has also impacted the needs and expectations of tourists. However, various branches of tourism are adopting this concept at a different pace, and thus a growing development gap might emerge. Cases from all over the world show that museums are not immune to this, and it is important for their future to meet these expectations. Therefore, the main objective of this study was to investigate the use of modern technologies in Polish museums and assess their readiness for adopting Smart Tourism. For this purpose, a nationwide online survey was conducted with a sample size of 218 museums (from 500 unique entities in total). The results show that the issue of Smart Tourism in Polish museums is ambiguous. The results reveal that, currently, the status of Smart Tourism adoption in museums is quite low, and significant gaps in some areas are shown; at the same time, other areas revealed a high potential for the future application of Smart Tourism.
A Literature Review of Methods in Research on Green Building Cost Analysis

Development greatly influences environmental sustainability and quality. The concept of green building is one solution to minimize environmental damage due to construction. The concept of green building requires greater investment than conventional building. Life Cycle Cost (LCC) impacts the cost of planning, building’s operational and maintenance cost and residual cost. Recently, research of green building on cost analysis is developing rapidly. There are so many studies of green building on cost analysis with different methods. This research addressed several relevant methods and is expected to set clear which methods to use for the future research under green building topics. This journal is meant to find out research method used in determining green building on cost analysis. The method to be carried out is a literature review of 14 relevant reputable journals from 2013-2020. The most widely used method is the Life Cycle Cost Analysis (LCCA).
Metallodielectric opals of layer-by-layer processed coated colloids

Ordered arrays of polystyrene colloids that are layer-by-layer coated with polyelectrolyte or polyelectrolyte/gold nanoparticle multilayers (see Figure and inside front cover) permit control over the peak position of the optical stop band of the assemblies through variation of the coating thickness and composition. The crystalline arrays made of polyelectrolyte multilayer-coated colloids can also be used for infiltration of gold nanoparticles.
Cultivation and Nutritional Value of Prominent Pleurotus spp.: An Overview

Abstract Pleurotus species are commercially essential mushrooms and widely cultivated throughout the world. The production of Pleurotus mushrooms alone accounts for around 25% of that total cultivated mushrooms globally. In America and Europe, Pleurotus species are considered specialty mushrooms, whereas, in Korea, their cultivation is economically profitable, and it is one of the highly consumed species. Pleurotus species are predominantly found in tropical forests and often grow on fallen branches, dead and decaying tree stumps, and wet logs. Biographical studies have shown that the Pleurotus genus is among the more conspicuous fungi that induce wood decay in terrestrial ecosystems worldwide due to its formidable lignin-modifying enzymes, including laccase and versatile peroxidases. Pleurotus species can be grown easily due to their fast colonization nature on diversified agro-substrates and their biological efficiency 100%. Pleurotus mushrooms are rich in proteins, dietary fiber, essential amino acids, carbohydrates, water-soluble vitamins, and minerals. These mushrooms are abundant in functional bioactive molecules, though to influence health. Pleurotus mushrooms are finding unique applications as flavoring, aroma, and excellent preservation quality. Apart from its unique applications, Pleurotus mushrooms have a unique status delicacy with high nutritional and medicinal values. The present review provides an insight into the cultivation of Pleurotus spp. using different agro-waste as growth substances paying attention to their effects on the growth and chemical composition.
Harm reduction as an approach to ethical nursing care of people who use illicit substances: an integrative literature review of micro and meso influences

Abstract People who use illicit substances and experience socioeconomic disadvantage experience poor health as a result of structural vulnerabilities made worse by barriers to health care. In particular, stigma and discrimination often act as a barrier to health care for people who use illicit substances. Lack of respect for persons and judgements based on discrimination are in violation of core ethical principles of nursing practice. Harm reduction, as a guiding philosophy, is proposed as a way to promote respectful and non-judgmental care and minimize the harms associated with illicit substance use in alignment with principles of ethical nursing practice. Utilizing McLeroy’s Ecological Model of Health Promotion as the guiding framework, we conducted an integrated review of relevant literature to identify recommendations for implementing harm reduction in nursing practice at the intrapersonal, interpersonal, and institutional levels. The search yielded 20 primary research articles published from 2008 until 2020 to identify the actions necessary to implement harm reduction in nursing practice. This integrative review summarizes evidence-based actions necessary from the micro- to meso-level to support the implementation of harm reduction as a guiding philosophy to enhance ethical practice in nursing.
An Analysis of the Role of Higher Education Opportunity Expansion in Social Stratification

Article history Received: 29 September 2020 Revised: 6 October 2020 Accepted: 9 October 2020 Published Online: 16 October 2020 With higher education entering the public’s vision, the expansion of higher education opportunities has gradually become a hot topic. The lower class is eager to achieve class mobility through this opportunity, while the upper class firmly grasps the few high-quality places in higher education. What role will the expansion of higher education opportunities plays in the overall social stratification? This paper discusses the impact of the expansion of higher education opportunities on social stratification from the upper class and the lower class.
Galway Point Mutation (FecXG) in the Bone Morphogenetic Protein 15 Gene (BMP15) Is Associated With Prolificacy in the Sudanese Desert Sheep Ecotypes

This study tested the association between FecX G point mutation located in exon 2 of BMP15 gene and the prolificacy of Dubasi, Shugor and Watish sheep ecotypes, under dryland farming, Sudan. Blood samples were randomly collected from unrelated 100 ewes (Dubasi; n= 30, Shugor: n= 30, and Watish: n= 40). Bone Morphogenetic protein ( BMP15 ) gene was amplified using PCR-RFLP. Two genotypes were found in all studied breeds (heterozygous and wild type). The calculated total genotype frequencies of BB, Bb and bb genotypes were 0.31, 0.69 and 0.00, respectively, while allele frequencies were 0.66 for B and 0.34 for b. Litter size was influenced by the genotypes of BMP15 gene, parities and subtypes (p<0.05), highest for Watish and 4 th parity. Alignment of BMP15 samples along with database reference sequence revealed that most sequence regions were identical except for one variable nucleotide at position 111 bp where a guanine (G) was replaced by adenine (A) in Watish and Shugor samples. All amino acids were the same at residue 275. Watish and Shugor breeds are more related. The study concluded that the presence of one copy of FecX G point mutation of BMP15 gene increased the litter size by 0.17 lambs in the studied ecotypes.
Fabric Defect Detection Using Computer Vision Techniques: A Comprehensive Review

There are different applications of computer vision and digital image processing in various applied domains and automated production process. In textile industry, fabric defect detection is considered as a challenging task as the quality and the price of any textile product are dependent on the efficiency and effectiveness of the automatic defect detection. Previously, manual human efforts are applied in textile industry to detect the defects in the fabric production process. Lack of concentration, human fatigue, and time consumption are the main drawbacks associated with the manual fabric defect detection process. Applications based on computer vision and digital image processing can address the abovementioned limitations and drawbacks. Since the last two decades, various computer vision-based applications are proposed in various research articles to address these limitations. In this review article, we aim to present a detailed study about various computer vision-based approaches with application in textile industry to detect fabric defects. The proposed study presents a detailed overview of histogram-based approaches, color-based approaches, image segmentation-based approaches, frequency domain operations, texture-based defect detection, sparse feature-based operation, image morphology operations, and recent trends of deep learning. The performance evaluation criteria for automatic fabric defect detection is also presented and discussed. The drawbacks and limitations associated with the existing published research are discussed in detail, and possible future research directions are also mentioned. This research study provides comprehensive details about computer vision and digital image processing applications to detect different types of fabric defects.
Boosting Sustainable Innovation in Densely Populated Areas: A Milieux Innovateurs Approach

This paper deals with innovation adoption, with the purpose of analyzing the uptake of sustainable innovations among young farms working in urban and periurban contexts. Our hypothesis is that innovative milieus (IM) play a fundamental role in boosting sustainable innovation. In order to analyze the uptake of sustainable innovation, we will make reference to the two logics of the IM approach: the logics of interactions and the logics of learning. The former is focused on the socio-institutional domain, more precisely on relational assets and coordination mechanisms activated by the farms. The latter makes reference to the profile of innovation adopted and on various impacts innovation have under economic, social and environmental points of view. A questionnaire has been submitted to young farms participating to the Oscar Green Coldiretti Awards. In total, three dimensions of innovation are taken into account: economic, social and environmental. Data are processed through statistical tools aiming at describing the diversified set of interaction-learning mechanisms. Results evidence different innovative milieus which pave the way to diversified paths of innovation with different degree of sustainability and impacts.
Effects of processing on the structure of PVC/montmorillonite composites. I. Melt and solution processes

The effects of processing conditions on the structure of poly(vinyl chloride) (PVC)/clay composites were investigated. Dry‐blending conditions were shown to affect composite structure in compression‐molded samples. PVC/(Cloisite Na) nanocomposites could not be prepared by melt compounding. Partially exfoliated and intercalated PVC/(Cloisite 30B) nanocomposites could be prepared by melt compounding. The effects of the grain structure of PVC resin and the PVC fusion mechanism on nanocomposite formation were considered. The particulate structure of the PVC resin was found to restrict the distribution ofclay, which could be improved by increasing the processing temperature. Almost fully exfoliated PVC/(Cloisite 30B) nanocomposites were prepared from solutions in tetrahydrofuran, and the plasticizer migration resistance of these composites was substantially improved. J. VINYL ADDIT. TECHNOL. , 2011. © 2011 Society of Plastics Engineers
A long short-term memory neural network model for knee joint acceleration estimation using mechanomyography signals

With the growth of the number of elderly and disabled with motor dysfunction, the demand for assisted exercise is increasing. Wearable power assistance robots are developed to provide athletic ability of limbs for the elderly or the disabled who have weakened limbs to better self-care ability. Existing wearable power-assisted robots generally use surface electromyography (sEMG) to obtain effective human motion intentions. Due to the characteristics of sEMG signals, it is limited in many applications. To solve the above problems, we design a long short-term memory (LSTM) neural network model based on human mechanomyography (MMG) signals to estimate the motion acceleration of knee joint. The acceleration can be further calculated by the torque required for movement control of the wearable power assistance robots for the lower limb. We detect MMG signals on the clothed thigh, extract features of the MMG signals, and then, use principal component analysis to reduce the features’ dimensions. Finally, the dimension-reduced features are inputted into the LSTM neural network model in time series for estimating the acceleration. The experimental results show that the average correlation coefficient (R) is 94.48 ± 1.91% for the estimation of acceleration in the process of continuously performing under approximately π/4 rad/s. This approach can be applied in the practical applications of wearable field.
In vitro study of selected essential oils against Colletotrichum sp. and Lasiodiplodia sp. causing postharvest diseases in papaya

Anthracnose caused by Colletotrichum sp. and stem-end rot (SER) caused predominantly by Lasiodiplodia sp. are common postharvest diseases affecting papaya in Sri Lanka and are currently managed by synthetic chemicals which are hazardous. Use of essential oils (EOs) is considered a non-hazardous alternative. This in vitro study investigated the antifungal potential of selected EOs against anthracnose and SER pathogens isolated from papaya var. ‘Red Lady’. A poisoned food bioassay was carried out to evaluate the antifungal effect of EOs (Cardamom, citronella, orange, mustard and lemon). Colony diameter was taken as a measure of growth. Bioassays consisted of EOs at 500, 750, 1000 μl l-1 with untreated control, three replicates and three separate trials. Cardamom (1000 μl l-1) and citronella (750 μll-1) significantly (P<0.05) inhbited Colletotrichum sp. and Lasiodiplodia sp. from papaya. According to GC-MS, higher percentages of antifungal geraniol, geranyl acetate are present in citronella while a-terpinyl acetate, 1, 8-cineole are present in cardamom oil.
On the mechanism for plasma hydrogenation of graphene

We report that hydrogenation of mono-, bi-, and trilayer graphene samples via exposure to H2 plasma occurs as a result of electron irradiation of H2O adsorbates on the samples, rather than H species in the plasma as reported by [Elias et al., Science 323, 610 (2009)]. We propose that the hydrogenation mechanism is electron-impact fragmentation of H2O adsorbates into H+ ions. At incident electron energies >60 eV, we observe hydrogenation that is significantly more stable at temperatures >200 °C than previously reported.
Deep learning for survival and competing risk modelling

Abstract The article examines novel machine learning techniques for survival analysis in a credit risk modelling context. Using a large dataset of US mortgages, we evaluate the adequacy of DeepHit, a deep learning-based competing risk model, and random survival forests. The observed results provide strong evidence that both models predict default and prepayment risk more accurately than statistical benchmarks in the form of the Cox proportional hazard model and the Fine and Gray model. The superiority of the machine learning models is robust across different periods including stressed periods. We also find machine learning models do not require larger amounts of training data than the statistical benchmarks. Finally, we extend methods for estimating feature importance scores to deep neural networks for survival analysis and clarify which covariates determine the estimated survival functions of DeepHit. An online companion with additional results is available in Supplementary Information.
Explaining Variability in Response Style Traits: A Covariate-Adjusted IRTree

Contamination of responses due to extreme and midpoint response style can confound the interpretation of scores, threatening the validity of inferences made from survey responses. This study incorporated person-level covariates in the multidimensional item response tree model to explain heterogeneity in response style. We include an empirical example and two simulation studies to support the use and interpretation of the model: parameter recovery using Markov chain Monte Carlo (MCMC) estimation and performance of the model under conditions with and without response styles present. Item intercepts mean bias and root mean square error were small at all sample sizes. Item discrimination mean bias and root mean square error were also small but tended to be smaller when covariates were unrelated to, or had a weak relationship with, the latent traits. Item and regression parameters are estimated with sufficient accuracy when sample sizes are greater than approximately 1,000 and MCMC estimation with the Gibbs sampler is used. The empirical example uses the National Longitudinal Study of Adolescent to Adult Health’s sexual knowledge scale. Meaningful predictors associated with high levels of extreme response latent trait included being non-White, being male, and having high levels of parental support and relationships. Meaningful predictors associated with high levels of the midpoint response latent trait included having low levels of parental support and relationships. Item-level covariates indicate the response style pseudo-items were less easy to endorse for self-oriented items, whereas the trait of interest pseudo-items were easier to endorse for self-oriented items.
Logical Structure for User Friendly dynamic Web Page Visualization for Small Screen Terminals Promoting E-Business

Now-a-days when everything is going digitalized, internet and web plays a vital role in everyone’s life. When one has to ask something or has any online task to perform, one has to use internet to access relevant web-pages throughout. These web-pages are mainly designed for large screen terminals. But due to mobility, handy and economic reasons most of the persons are using small screen terminals (SST) like mobile phone, palmtop, pagers, tablet computers and many more. Reading a web page which is actually designed for large screen terminal on a small screen is time consuming and cumbersome task because there are many irrelevant content parts which are to be scrolled or there are advertisements, etc. Here main concern is e-business users. To overcome such issues the source code of a web page is organized in tree data-structure. In this paper we are arranging each and every main heading as a root node and all the content of this heading as a child node of the logical structure. Using this structure, we regenerate a web-page automatically according to SST size. DOM and VIPS algorithms are the main background techniques which are supporting the current research. To restructure a web page in a more user friendly and content presenting format. Method Backtracking: web page heading queue generation. Concept of logical structure supports every SST.
Actualizando los abordajes socioculturales de la obesidad: propuestas a partir de Hacking, Bourdieu y Foucault

Resumen El aumento de las tasas de obesidad y sus consecuencias negativas, tanto individuales como colectivas, reclama la necesidad de nuevos enfoques cientificos, que permitan un abordaje multidisciplinar que integre los factores biologicos y socioculturales, explorando en profundidad tanto los aspectos objetivos como subjetivos de este problema. En este sentido, en el presente trabajo proponemos un conjunto de reflexiones teoricas, que puedan servir como marco critico de actualizacion de las aportaciones de corte sociocultural en los debates cientificos sobre la obesidad y el sobrepeso. Para ello, primero revisaremos las principales caracteristicas de los enfoques biologico y sociocultural sobre el tema. Y despues pasaremos a proponer dicho conjunto de reflexiones, realizando un analisis de los conceptos de tres teoricos sociales de corte critico, vistos como modelos potencialmente fertiles pero poco usados en este tipo de tema por distintos motivos.
Evaluating the effect of differentiated inquiry-based science lesson modules on gifted students' scientific process skills

The concept of “Global citizenship”, which has become more and more important, based on the students' multi-focused individual development, has brought to the fore based on 21st century skills and has required appropriate educational environments for gifted students. In this context, the development of differentiated inquiry-based science lesson modules for gifted students will fill the current gap as it is important for the literature. The aim of this study is to examine the impact of differentiated inquiry-based science lesson modules for gifted students on the students' scientific process skills (SPS). As a method, the nature of the study was directed us to mixed nested patterns and developed three modules that applied to 16 gifted students in Science and Art Centers. In the evaluation process, we used “Diet Cola SPS test” as quantitative data source for pre and posttests. Also, we used observations in the implementation process and SPS activity reports filled out by students as qualitative data sources. As a result of data analysis, we found that SPS improved significantly (t (14) = -5.06, p <. 05). Accordingly, we have seen that this development in students is in basic and causal SPS, there is less development in experimental processes. We concluded that the gifted students needed more in depth and challenging activities in longer periods using modules like given in this study.