Miracle-dz/UniFAR-FTUs huggingface dataset:
Organizational, local, and global innovativeness of family-owned SMEs depending on firm-individual level characteristics: evidence from the Czech Republic

Research background: Comparing to larger businesses, SMEs encounter more problems in their operations. Since innovativeness enables SMEs to be more competitive against their rivals, having more innovative activities might make SMEs overcome these issues. Nevertheless, depending on businesses-founders/owners' characteristics, SMEs' innovativeness in organizational, local, and global extents might differ. Purpose of the article: This research explores differences in family-owned SMEs' innovativeness regarding the age of their founders/entrepreneurs, legal form, and succession of these businesses. Methods: The researchers used a questionnaire survey. Data collection process was completed in 2020. The research sample includes 343 family-owned SMEs that operate in Czechia. The normality test result directs the authors to perform an Independent sample T-test to find differences between selected variables. Findings & value added: According to the obtained results, global innovativeness does not differ depending on firms-owners/entrepreneurs' characteristics. However, limited liability firms perform better in local innovativeness than other firms structured in different legal forms. Moreover, the organizational innovativeness of SMEs with successors is greater than firms without successors. While organizational innovativeness does not differ depending on entrepreneurs/founders' age and legal structure of businesses, local innovativeness does not differ depending on entrepreneurs/founders' age and successors' existence in these businesses. The educational level of entrepreneurs/founders, sector, and SMEs' location might be reasons for similarities and differences between SMEs' innovativeness. From the policy perspective, based on the obtained results, the authors suggest creating industrial zones. Furthermore, policymakers' collaborations with other essential players in the market might stimulate innovative attitudes among businesses. This paper's main contribution to the existing literature is to fill the gap regarding organizational, local, and global innovativeness of family-owned SMEs by providing detailed and empirical results about entrepreneurs' and firms' characteristics. Thus, this paper might draw businesses, policymakers, academicians, and international readers' attention concerning family-owned SMEs' innovativeness.
Dynamic outgassing of deuterium, helium and nitrogen from plasma-facing materials under DEMO relevant conditions

In confined plasma magnetic fusion devices significant amounts of the hydrogen isotopes used for the fusion reaction can be stored in the plasma-facing materials by implantation. The desorption of this retained hydrogen was seen to follow a tα law with α ≈ −0.7 in tokamaks. For a pulsed fusion reactor this outgassing can define the inter-pulse waiting time. This work presents new experimental data on the dynamic outgassing in ITER grade tungsten exposed under the well-defined conditions of PSI-2 to pure and mixed D2 plasmas. A peak ion flux of 1022 D+ m−2 s is applied for up to 6 h at sample temperatures of up to 900 K. Pure D2 and mixed D2 + He, D2 + N2 and D2 + He + N2 plasmas are applied to the sample at 68 V bias. The D2, He, N outgassing at 293 K and 580 k are observed via in-vacuo quadrupole mass spectrometry covering the range of 40 s–200 000 s after exposure. The outgassing decay follows a single power law with exponents α = −0.7 to −1.1 at 293 K, but at 580 K a drop from α = −0.25 to −2.35 is found. For DEMO a pump-down time to 0.5 mPa in the order of 1–5 h can be expected. The outgassing is in all cases dominated by D2.
Introducing a Novel Approach for Oil‐Oil Correlation based on Asphaltene Structure: X‐ray Diffraction

Asphaltenes have always been an attractive subject for researchers. However, the application of this fraction of the geochemical field has only been studied in a limited way. In other words, despite many studies on asphaltene structure, the application of asphaltene structures in organic geochemistry has not so far been assessed. Oil‐oil correlation is a well‐known concept in geochemical studies and plays a vital role in basin modeling and the reconstruction of the burial history of basin sediments, as well as accurate characterization of the relevant petroleum system. This study aims to propose the X‐ray diffraction (XRD) technique as a novel method for oil‐oil correlation and investigate its reliability and accuracy for different crude oils. To this end, 13 crude oil samples from the Iranian sector of the Persian Gulf region, which had previously been correlated by traditional geochemical tools such as biomarker ratios and isotope values, in four distinct genetic groups, were selected and their asphaltene fractions analyzed by two prevalent methods of XRD and Fourier‐transform infrared spectroscopy (FTIR). For oil‐oil correlation assessment, various cross‐plots, as well as principal component analysis (PCA), were conducted, based on the structural parameters of the studied asphaltenes. The results indicate that asphaltene structural parameters can also be used for oil‐oil correlation purposes, their results being completely in accord with the previous classifications. The average values of distance between saturated portions (dr) and the distance between two aromatic layers (dm) of asphaltene molecules belonging to the studied oil samples are 4. 69Å and 3. 54Å, respectively. Furthermore, the average diameter of the aromatic sheets (La), the height of the clusters (Lc), the number of carbons per aromatic unit (Cau), the number of aromatic rings per layer (Ra), the number of sheets in the cluster (Me) and aromaticity (fa) values of these asphaltene samples are 10. 09Å, 34. 04Å, 17. 42Å, 3. 78Å, 10. 61Å and 0. 26Å, respectively. The results of XRD parameters indicate that plots of dr vs. dm, dr vs. Me, dr vs. fa, dm vs. Lc, Lc vs. La, and fa vs. La perform appropriately for distinguishing genetic groups. A comparison between XRD and FTIR results indicated that the XRD method is more accurate for this purpose. In addition, decision tree classification, one of the most efficacious approaches of machine learning, was employed for the geochemical groups of this study for the first time. This tree, which was constructed using XRD data, can distinguish genetic groups accurately and can also determine the characteristics of each geochemical group. In conclusion, the obtaining of structural parameters for asphaltene by the XRD technique is a novel, precise and inexpensive method, which can be deployed as a new approach for oil‐oil correlation goals. The findings of this study can help in the prompt determination of genetic groups as a screening method and can also be useful for assessing oil samples affected by secondary processes.
Mowing machinery and migratory sheep herds are complementary dispersal vectors for grassland species

This is an open access article under the terms of the Creative Commons AttributionNonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2021 The Authors. Applied Vegetation Science published by John Wiley & Sons Ltd on behalf of International Association for Vegetation Science 1Division of Landscape Ecology and Landscape Planning, Research Centre for Biosystems, Land Use and Nutrition (iFZ), Justus Liebig University Giessen, Giessen, Germany 2Department of Environmental and Life Sciences, Biology, Karlstad University, Karlstad, Sweden
Microstructure, Residual Stresses, and Strain-Rate-Dependent Deformation and Fracture Behavior of AISI 304L Joints Brazed with NiCrSiB Filler Metals

The knowledge of alloy–process–structure–property relationships is of particular interest for several safety-critical brazed components and requires a detailed characterization. Thus, three different nickel-based brazing filler metals were produced with varying chromium and molybdenum content and were used to braze butt joints of the austenitic stainless steel AISI 304L under vacuum. Two holding times were used to evaluate diffusion-related differences, resulting in six specimen variations. Significant microstructural changes due to the formation and location of borides and silicides were demonstrated. Using X-ray diffraction, alloy-dependent residual stress gradients from the brazing seam to the base material were determined and the thermal-induced residual stresses were shown through simulations. For mechanical characterization, impact tests were carried out to determine the impact toughness, as well as tensile tests at low and high strain rates to evaluate the strain-rate-dependent tensile strength of the brazed joints. Further thermal, electrical, and magnetic measurements enabled an understanding of the deformation mechanisms. The negative influence of brittle phases in the seam center could be quantified and showed the most significant effects under impact loading. Fractographic investigations subsequently enabled an enhanced understanding of the fracture mechanisms.
Study of the Yahoo-Yahoo Hash-Tag Tweets Using Sentiment Analysis and Opinion Mining Algorithms

BackgroundSocial media opinion has become a medium to quickly access large, valuable, and rich details of information on any subject matter within a short period. Twitter being a social microblog site, generate over 330 million tweets monthly across different countries. Analyzing trending topics on Twitter presents opportunities to extract meaningful insight into different opinions on various issues.AimThis study aims to gain insights into the trending yahoo-yahoo topic on Twitter using content analysis of selected historical tweets.MethodologyThe widgets and workflow engine in the Orange Data mining toolbox were employed for all the text mining tasks. 5500 tweets were collected from Twitter using the 'yahoo yahoo' hashtag. The corpus was pre-processed using a pre-trained tweet tokenizer, Valence Aware Dictionary for Sentiment Reasoning (VADER) was used for the sentiment and opinion mining, Latent Dirichlet Allocation (LDA) and Latent Semantic Indexing (LSI) was used for topic modeling. In contrast, Multidimensional scaling (MDS) was used to visualize the modeled topics. ResultsResults showed that "yahoo" appeared in the corpus 9555 times, 175 unique tweets were returned after duplicate removal. Contrary to expectation, Spain had the highest number of participants tweeting on the 'yahoo yahoo' topic within the period. The result of Vader sentiment analysis returned 35.85%, 24.53%, 15.09%, and 24.53%, negative, neutral, no-zone, and positive sentiment tweets, respectively. The word yahoo was highly representative of the LDA topics 1, 3, 4, 6, and LSI topic 1.ConclusionIt can be concluded that emojis are even more representative of the sentiments in tweets faster than the textual contents. Also, despite popular belief, a significant number of youths regard cybercrime as a detriment to society.
Fusion of Multispectral Aerial Imagery and Vegetation Indices for Machine Learning-Based Ground Classification

Unmanned Aerial Vehicles (UAVs) are emerging and promising platforms for carrying different types of cameras for remote sensing. The application of multispectral vegetation indices for ground cover classification has been widely adopted and has proved its reliability. However, the fusion of spectral bands and vegetation indices for machine learning-based land surface investigation has hardly been studied. In this paper, we studied the fusion of spectral bands information from UAV multispectral images and derived vegetation indices for almond plantation classification using several machine learning methods. We acquired multispectral images over an almond plantation using a UAV. First, a multispectral orthoimage was generated from the acquired multispectral images using SfM (Structure from Motion) photogrammetry methods. Eleven types of vegetation indexes were proposed based on the multispectral orthoimage. Then, 593 data points that contained multispectral bands and vegetation indexes were randomly collected and prepared for this study. After comparing six machine learning algorithms (Support Vector Machine, K-Nearest Neighbor, Linear Discrimination Analysis, Decision Tree, Random Forest, and Gradient Boosting), we selected three (SVM, KNN, and LDA) to study the fusion of multi-spectral bands information and derived vegetation index for classification. With the vegetation indexes increased, the model classification accuracy of all three selected machine learning methods gradually increased, then dropped. Our results revealed that that: (1) spectral information from multispectral images can be used for machine learning-based ground classification, and among all methods, SVM had the best performance; (2) combination of multispectral bands and vegetation indexes can improve the classification accuracy comparing to only spectral bands among all three selected methods; (3) among all VIs, NDEGE, NDVIG, and NDVGE had consistent performance in improving classification accuracies, and others may reduce the accuracy. Machine learning methods (SVM, KNN, and LDA) can be used for classifying almond plantation using multispectral orthoimages, and fusion of multispectral bands with vegetation indexes can improve machine learning-based classification accuracy if the vegetation indexes are properly selected.
Entrepreneurial Motivation, Psychological Capital, and Business Success of Young Entrepreneurs in the DRC

The proponents of the entrepreneurial motivation dichotomy have argued that opportunity-driven entrepreneurs are more likely to succeed and sustain in entrepreneurship, unlike people who start-up businesses out of necessity. However, disagreement still exists on why and under which conditions the former might outperform the latter. This research contributes to this debate by examining the mediation role of psychological capital in the relationship between entrepreneurial motivation and business success among youths. This study relied on a random sample of 295 young entrepreneurs surveyed from Bukavu in the Democratic Republic of the Congo (DRC). We applied partial least squares to analyze the hypothesized relationships. Evidence for the positive effect of opportunity-led motivation on psychological capital was found, but the findings did not support any direct effect of entrepreneurial motivation on business success. Instead, psychological capital positively and significantly mediated the relationship between entrepreneurial motivation and business success. This paper makes a distinctive new contribution to the understanding of the intriguing and controversial entrepreneurial motivation dichotomy—a business success relationship. To this end, we have found out that opportunity entrepreneurs have 3% more chance of succeeding in businesses compared to necessity entrepreneurs, because the former outperform the latter by 4% in the dimensions of psychological capital. This paper has new policy implications, as it reveals the great importance of psychological capital in promoting business success, thus reducing unemployment among youths, and offers tips from which psychological capital can be built or improved.
Ownership Variation in Violated Regulations and National Care Standards: Evidence From Social Care Providers

Social care services are increasingly provisioned in quasi-markets in which for-profit, public, and third sector providers compete for contracts. Existing research has investigated the implications of this development by analyzing ownership variation in latent outcomes such as quality, but little is known about whether ownership predicts variation in more concrete outcomes, such as violation types. To address this research gap, we coded publicly available inspection reports of social care providers regulated by the Care Inspectorate in Scotland and created a novel data set enabling analysis of ownership variation in violations of (a) regulations, and (b) national care standards over an entire inspection year (n = 4,178). Using negative binomial and logistic regression models, we find that for-profit providers are more likely to violate non-enforceable outcomes (national care standards) relative to other ownership types. We did not identify a statistically significant difference between for-profit and third sector providers with regard to enforceable outcomes (regulations).
Ecological and geological processes impacting speciation modes drive the formation of wide‐range disjunctions within tribe Putorieae (Rubiaceae)

Wide‐range geographically discontinuous distributions have long intrigued scientists. We explore the role of ecology, geology, and dispersal in the formation of these large‐scale disjunctions, using the angiosperm tribe Putorieae (Rubiaceae) as a case study. From DNA sequences of nuclear ITS and six plastid markers, we inferred a phylogeny with 65% of all known Putorieae species. Divergence times, ancestral ranges, and diversification rate shifts were then estimated using Bayesian inference. We further explored species climatic tolerances and performed ancestral niche reconstruction to discriminate among alternative speciation modes, including geographical and ecological vicariance, and ecogeographical, ecological, and dispersal‐mediated speciation. As a result, we identified seven major clades in Putorieae, some of which exhibit striking geographical disjunctions, matching the Rand Flora pattern, with sister species in the Canary Islands and eastern and southern Africa. Initial diversification within the tribe occurred in the early Miocene, coincident with a period of climate warming; however, most clades diverged within the last 10 Myr. Aridification and high extinction rates, coupled with ecological vicariance, explain the oldest disjunctions. Adaptation to new environmental conditions, after allopatry, is observed in several clades. Dispersal, either long‐distance or via corridors made available by mountain uplift, is behind the most recent disjunctions. Some of these events were followed by ecological speciation and rapid diversification, with species becoming adapted to xeric or increasingly colder continental climates. We show that an integrative approach may help discriminate among speciation modes invoked to explain disjunctions at macroevolutionary time scales, even when extinction has erased the signature of past events.
A study of wild medicinal plants used in Nargu Wildlife Sanctuary of district Mandi in Himachal Pradesh, India

Radha1*, Pallavi Chauhan1, Sunil Puri1, Mamta Thakur1, Sonia Rathour1, Abhishek Kumar Sharma2, Ashok Pundir3 1School of Biological and Environmental Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, India. 2School of Pharmaceutical Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, India. 3School of Mechanical and Civil Engineering, Shoolini University of Biotechnology and Management Sciences, Solan, India.
CFD Analysis and Design of Detailed Target Configurations for an Accelerator-Driven Subcritical System

Abstract High-fidelity analysis has been utilized in the design of beam target options for an accelerator-driven subcritical system. Designs featuring stacks of plates with square cross section have been investigated for both tungsten and uranium target materials. The presented work includes the first thermal-hydraulic simulations of the full, detailed target geometry. The innovative target cooling manifold design features many regions with complex flow features, including 90° bends and merging jets, which necessitate three-dimensional fluid simulations. These were performed using the commercial computational fluid dynamics code STAR-CCM+. Conjugate heat transfer was modeled between the plates, cladding, manifold structure, and fluid. Steady-state simulations were performed but lacked good residual convergence. Unsteady simulations were then performed, which converged well and demonstrated that flow instability existed in the lower portion of the manifold. It was established that the flow instability had little effect on the peak plate temperatures, which were well below the melting point. The estimated plate surface temperatures and target region pressure were shown to provide sufficient margin to subcooled boiling for standard operating conditions. This demonstrated the safety of both potential target configurations during normal operation.
Effects of Intervention Schemes on Sulphadoxine-Pyrimethamine Compliance Among Pregnant Women in a Health Facility in Port Harcourt, Rivers State, Nigeria

Background: Malaria causes diverse adverse effects in the fetus due to the invasion of the placenta by Plasmodium. The use of intermittent preventive treatment (Sulphadoxinepyrimethamine- IPTp-SP) as a control measure for malaria in pregnancy has been recommended and shown to reduce unwanted birth outcomes. Objectives: This work aimed to evaluate the effects of intervention schemes on sulphadoxine-pyrimethamine (SP) compliance and utilization among pregnant women in a health facility in Port Harcourt, Nigeria. Methods: A hospital-based survey was carried out among pregnant women admitted to the Labor ward of Obio-Cottage hospital. The information of mothers was collected using a well-structured and pre-tested questionnaire and from their antenatal care (ANC) records. Results: Time of ANC registration indicated that 87%, 11.33%, and 1.66% of mothers were registered during their first, second, and third trimesters, respectively. Sulphadoxinepyrimethamine was the drug of choice for 93.66% of the women while 6.33% took other drugs. The survey revealed that 97.15% and 2.85% of the women started SP usage in their second and third trimesters, respectively. It was observed that the majority of the women (69.39%) took SP thrice while 24.19% and 6.40% consumed it twice and once, respectively. Regarding knowledge about SP, 89% of the women viewed SP as a preventive drug for malaria while 11% acknowledged it as a therapeutic drug. The birth outcomes of the neonates whose mothers took SP indicated that 1.42% had low birth weight (LBW) while 98.57% had acceptable birth weight. Meanwhile, 10.53% of the babies born to the mothers who did not use SP had LBW, and 89.47% of them had acceptable birth weights. Overall, 98.93% of the neonates of SP-compliant women and 89.48% of the babies of non-compliant women were alive. Non- compliant women had higher prevalence of preterm birth (5.76%) and fetal death (5.26%) than SP-compliant women (0.7% and 0.35%, respectively). Conclusions: Adequate knowledge and compliance with SP usage were high in the studied population, which was associated with favorable birth outcomes.