Miracle-dz/UniFAR-FTUs huggingface dataset:
EUROPEAN ACADEMIC RESEARCH, VOL

The purpose of this study is the impact of an entrepreneurship training course on the development of entrepreneurial features in sport experts. The semi– experiential method of research utilize and data collect in the form of fieldwork. Sixty physical education students and graduates (30 female and 30 male) divide into three control, nonverbal and verbal group. Data are collected by questionnaire designed by Tojari et al that its permanence was obtained using Cronbach (α=0.811). For analyzing the data, the descriptive and deductive statistics ANOVA is used. Results show that there is a positive and meaningful relationship between entrepreneurship training a variants of risk-taking decisiveness, intelligence, self–confidence and entrepreneurship (p‹0.05). Findings also show that there is no meaningful difference between entrepreneurship training and variants of decisiveness, need for improvement and decision–making (p›0.05). Considering the results of the research, entrepreneurship courses will have deserving effectiveness capabilities in the development of entrepreneurial features on the participants of the course. Behdad Khalili, Farshad Tojari, Mona RezaeiThe Impact of an Entrepreneurship Training Course on the Development of Entrepreneurial Features EUROPEAN ACADEMIC RESEARCH Vol. II, Issue 9 / December 2014 11943
Four agendas for research and policy on emissions mitigation and well-being

Non-technical abstract The climate crisis requires nations to achieve human well-being with low national levels of carbon emissions. Countries vary from one another dramatically in how effectively they convert resources into well-being, and some nations with low levels of emissions have relatively high objective and subjective well-being. We identify urgent research and policy agendas for four groups of countries with either low or high emissions and well-being indicators. Least studied are those with low well-being and high emissions. Understanding social and political barriers to switching from high-carbon to lower-carbon modes of production and consumption, and ways to overcome them, will be fundamental. Technical abstract In order for rapid decarbonization of the world's economies to be consistent with staying within 1.5 (or even 2) °C of warming limits, research is urgently needed on the potential for decoupling human well-being improvements from energy use and greenhouse gas emissions. Improving human well-being is both a higher moral priority, and a more promising candidate for decoupling, than economic growth. Research needs to include the difficult political-economic, judicial and institutional changes needed to support transitions to high well-being and low-carbon pathways. Much of this work will be nation-specific, but it is useful to examine pathways for four groups of nations. We propose an initial set of research questions for each group of nations, on their history and current situation, and on pathways to rapid decarbonization. Existing technology now makes it feasible to achieve low carbon emissions and high human well-being for all nations. But the barriers are substantial, and include addressing existing vested interests of economic sectors, technological lock-in, assumptions embedded in culture, and political structures. Unfortunately, these areas are currently the weakest link in the existing research and policy chain.
Charcoal as an Energy Resource: Global Trade, Production and Socioeconomic Practices Observed in Uganda

Around the world, charcoal has persisted as an energy resource and retained unequivocal dominance in the energy consumption mix of some nations many years on since modern alternatives were invented. Furthermore, it has secured unyielding significance as a commodity on local and international markets and remained an aggressive competitor to electricity and gas for cooking. Here, we analyze the charcoal supply chain and highlight the rudimentary production techniques common within the sub-Saharan region, using Uganda as an example. Top global producers, importers, and exporters are discussed and, based on fieldwork from ten locations in Uganda, we describe common trade practices, economic contributions and the realities of charcoal consumption in areas with concentrated grid and electricity coverage. Indeed, forest degradation and deforestation in the charcoal trade is indiscriminate and the world’s top producers and exporters of charcoal do not necessarily have vast forest resources. Pyrolysis, the process used to produce charcoal from wood, exacerbates risks of wild fires and deteriorates air quality. Our fieldwork indicates that little to no innovation exists to manage waste materials such as ash and polluting gases along the supply chain. Recommendations for the future include better forest conservation practices and more innovation at the cooking level, because effects of localized environmental degradation inevitably lead to negative impacts beyond geographical borders.
CCBE1 promotes tumor lymphangiogenesis and is negatively regulated by TGFβ signaling in colorectal cancer

Collagen and calcium-binding EGF domain-1 (CCBE1) is essential for lymphatic vascular development as it promotes vascular endothelial growth factor C (VEGFC) proteolysis. A recent study reported that CCBE1 was overexpressed in epithelial colorectal cancer (CRC) cells; however, the role of CCBE1 in tumor lymphangiogenesis and the mechanism underlying dysregulated CCBE1 expression in CRC remain undefined. Methods: The role of CCBE1 in tumor lymphangiogenesis and lymphatic metastasis was investigated using human lymphatic endothelial cells (HLECs) model in vitro, and a hindfoot lymphatic metastasis model in vivo. Immunochemistry analysis was performed to assess CCBE1 expression, prognostic value and correlation with clinicopathological characteristics in CRC. The biochemical function and transcriptional regulatory mechanism of CCBE1 were explored by western blot, qPCR, and chromatin immunoprecipitation. Results: Cancer cell-derived CCBE1 enhances VEGFC proteolysis in vitro, facilitates tube formation and migration of HLECs in vitro, and promotes tumor lymphangiogenesis and lymphatic metastasis in vivo. In addition to CRC cells, tumor stroma within CRC tissue shows high CCBE1 expression, which is associated with high lymphatic vessel density, increased lymph node metastasis and poor prognosis. Cancer-associated fibroblasts (CAFs) express and secret CCBE1, thereby contributing to VEGFC maturation and tumor lymphangiogenesis in CRC. Transforming growth factor beta (TGF-β) downregulates the transcription and lymphangiogenic function of CCBE1 in CAFs and CRC cells through direct binding of SMADs to CCBE1 gene locus. Inactivation of the TGF-β pathway correlates with increased CCBE1 expression in CRC. Conclusion: Our results demonstrate the protumorigenic role of CCBE1 in promoting lymphangiogenesis and lymphatic metastasis in CRC, revealing a new mechanism by which loss of TGF-β signaling promotes CRC metastasis.
Optical Trapping, Sizing, and Probing Acoustic Modes of a Small Virus

Prior opto-mechanical techniques to measure vibrational frequencies of viruses work on large ensembles of particles, whereas, in this work, individually trapped viral particles were studied. Double nanohole (DNH) apertures in a gold film were used to achieve optical trapping of one of the smallest virus particles yet reported, PhiX174, which has a diameter of 25 nm. When a laser was focused onto these DNH apertures, it created high local fields due to plasmonic enhancement, which allowed stable trapping of small particles for prolonged periods at low powers. Two techniques were performed to characterize the virus particles. The particles were sized via an established autocorrelation analysis technique, and the acoustic modes were probed using the extraordinary acoustic Raman (EAR) method. The size of the trapped particle was determined to be 25 ± 3.8 nm, which is in good agreement with the established diameter of PhiX174. A peak in the EAR signal was observed at 32 GHz, which fits well with the predicted value from elastic theory.
Isolation and characterization of Group B Streptococci and other pathogens among pregnant women in Ibadan, Southwestern Nigeria

Objective: The detection of Group B streptococci (GBS) in pregnant women allows intrapartum administration of antibiotic prophylaxis to prevent perinatal infection. This study aimed to determine the incidence and antibiotic susceptibility profiles of group B streptococci and other pathogens isolated from pregnant women in Ibadan, Nigeria. Methods and results: One hundred antenatal clinic attendees at Adeoyo Maternity Hospital, Ibadan, were recruited for this study. The age range of the participants was 16 – 41 years, with ages 21– 30 years constituting 63%. Participants were interviewed using a questionnaire to gather demographic data. Two samples of high vaginal swab (HVS) were collected per participant and processed using standard bacteriological methods. The results showed that a total of 120 microbes were isolated and 10 (8.3%) of these isolates were GBS . Other organisms include Staphylococcus aureus [22(18.3%)], Candida albicans [17(14.2%)], Candida species [9(7.5%)], Proteus species [8(6.7%)], Escherichia coli [6(5.0%)], Trichomonas vaginalis [6(5.0%)], Streptococcus pyogenes [5(4.2%)], Enterococcus species [3(2.5%)], and non-pathogens [34(28.3%)]. The pattern of GBS isolated from different age ranges showed that, the incidence was not age-dependent (P=0.05). The antibiotic susceptibility profiles of the bacterial pathogens were studied using disc-diffusion techniques. All the GBS isolates were sensitive to Penincillin G and Erythromycin; with 80% sensitive to Ampicillin, Vancomycin and Augmentin. Conclusion and application of findings: The relatively high incidence (8.3%) of GBS colonization among the pregnant women emphasizes the importance of correct diagnosis and prevention of neonatal infections and of detecting colonization at the end of pregnancy. Therefore, a thorough medical examination and culture of HVS is highly recommended for pregnant women to ensure detection of GBS infection among these immunosuppressed persons. The recovery of antibiotic resistant strains of other bacterial pathogens, especially those recommended in cases of penicillin allergy, also indicates the importance of evaluating microbial susceptibility to antibiotics.
Running head : Effects of diversified farming on arthropods

Elinor M. Lichtenberg1,2*, Christina M. Kennedy3, Claire Kremen4, Péter Batáry5, Frank Berendse6, Riccardo Bommarco7, Nilsa A. Bosque-Pérez8, Luísa G. Carvalheiro9,10, William E. Snyder1, Neal M. Williams11, Rachael Winfree12, Björn Klatt5,13,14, Sandra Åström15, Faye Benjamin12, Claire Brittain11, Rebecca Chaplin-Kramer16, Yann Clough13, Heather Connelly17, Bryan Danforth17, Tim Diekötter18, Sanford D. Eigenbrode8, Johan Ekroos13, Elizabeth Elle19, Breno M. Freitas20, Yuki Fukuda21, Hannah R. Gaines-Day22, Claudio Gratton22, Andrea Holzschuh23, Rufus Isaacs24, Marco Isaia25, Shalene Jha26, Dennis Jonason27, Vincent P. Jones28, Alexandra-Maria Klein29, Jochen Krauss23, Deborah K. Letourneau30, Sarina Macfadyen31, Rachel E. Mallinger22, Emily A. Martin23, Eliana Martinez32, Jane Memmott33, Lora Morandin34, Lisa Neame35, Mark Otieno36, Mia G. Park17,37, Lukas Pfiffner38, Michael Pocock39, Carlos Ponce40, Simon G. Potts41, Katja Poveda17, Mariangie Ramos42, Jay A. Rosenheim11, Maj Rundlöf14, Hilary Sardiñas4, Manu E. Saunders43, Nicole L. Schon44, Amber R. Sciligo4, C. Sheena Sidhu45, Ingolf SteffanDewenter23, Teja Tscharntke5, Milan Veselý46, Wolfgang W. Weisser47, Julianna K. Wilson24, David W. Crowder1
Association of MRI-derived radiomic biomarker with disease-free survival in patients with early-stage cervical cancer

Pre-treatment survival prediction plays a key role in many diseases. We aimed to determine the prognostic value of pre-treatment Magnetic Resonance Imaging (MRI) based radiomic score for disease-free survival (DFS) in patients with early-stage (IB-IIA) cervical cancer. Methods: A total of 248 patients with early-stage cervical cancer underwent radical hysterectomy were included from two institutions between January 1, 2011 and December 31, 2017, whose MR imaging data, clinicopathological data and DFS data were collected. Patients data were randomly divided into the training cohort (n = 166) and the validation cohort (n=82). Radiomic features were extracted from the pre-treatment T2-weighted (T2w) and contrast-enhanced T1-weighted (CET1w) MR imagings for each patient. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazard model were applied to construct radiomic score (Rad-score). According to the cutoff of Rad-score, patients were divided into low- and high- risk groups. Pearson's correlation and Kaplan-Meier analysis were used to evaluate the association of Rad-score with DFS. A combined model incorporating Rad-score, lymph node metastasis (LNM) and lymphovascular space invasion (LVI) by multivariate Cox proportional hazard model was constructed to estimate DFS individually. Results: Higher Rad-scores were significantly associated with worse DFS in the training and validation cohorts (P<0.001 and P=0.011, respectively). The Rad-score demonstrated better prognostic performance in estimating DFS (C-index, 0.753; 95% CI: 0.696-0.805) than the clinicopathological features (C-index, 0.632; 95% CI: 0.567-0.700). However, the combined model showed no significant improvement (C-index, 0.714; 95%CI: 0.642-0.784). Conclusion: The results demonstrated that MRI-derived Rad-score can be used as a prognostic biomarker for patients with early-stage (IB-IIA) cervical cancer, which can facilitate clinical decision-making.
Exporting and productivity as part of the growth process: causal evidence from a data-driven structural VAR

This paper introduces a little known category of estimators - Linear Non-Gaussian vector autoregression models that are acyclic or cyclic - imported from the machine learning literature, to revisit a well-known debate. Does exporting increase firm productivity? Or is it only more productive firms that remain in the export market? We focus on a relatively well-studied country (Chile) and on already-exporting firms (i.e. the intensive margin of exporting). We explicitly look at the co-evolution of productivity and growth, and attempt to ascertain both contemporaneous and lagged causal relationships. Our findings suggest that exporting does not have any causal influence on the other variables. Instead, export seems to be determined by other dimensions of firm growth. With respect to learning by exporting (LBE), we find no evidence that export growth causes productivity growth within the period and very little evidence that exporting growth has a causal effect on subsequent TFP growth.
Estimation of Poverty Based on Remote Sensing Image and Convolutional Neural Network

Poverty has always been one of the topics concerned by governments and researchers all over the world, especially in developing countries. Remote sensing image is widely used in poverty estimation because of its large area observation, timeliness and periodicity. In this study, we explore the applicability of convolution neural network (CNN) combined with remote sensing image in regional poverty estimation. In the 2016 economic indicators estimation of Guizhou Province, China, the Pearson coefficient of per capita GDP (PCGDP) reached 0.76, which means that the image features extracted by CNN can explain the change of PCGDP of county level economic indicators up to 76%. Compared with other methods, our method still has high precision. Based on these results, we found that convolutional neural network combined with remote sensing image can be used in regional poverty estimation.
Efficacy of Low Dose Doxorubicin Therapy in Patients with Non-APL Acute Myeloblastic Leukemia

Background: Doxorubicin is a chemotherapeutic drug that acts by blocking topoisomerase 2 enzyme. It is used for treatment of many solid and hematological cancers; unfortunately it has serious side effects. The usual Doxorubicin dose for patients with acute myeloblastic leukemia (AML) is 40-60 mg/m2. This is the first study that assessed the efficacy of low dose Doxorubicin in patients with non acute promyelocytic leukemia (APL) AML. Methods: A retrospective study was done at Assiut University, where data were collected from hospital records of 103 patients with AML, after fulfilling certain inclusion criteria. Patients were treated with the conventional 3/7 induction regimen, however doxorubicin was prescribed in a lower dose compared with other studies. Results: The median age of our patients was 38 years, and 86.4% were with primary AML. Complete remission (CR) was achieved in 60.2% of the study patients. Primary AML type and M2 FAB subtype, were found to be good prognostic factors (P=0.000 and 0.067, respectively). Survival analysis showed that the longest overall survival (OS) and disease free survival (DFS) for the study patients were 60 and 55 months respectively. There was no significant difference regarding OS and DFS between male and female patients (P=0.903, 0.848, respectively). Conclusion: In conclusion this study provided a novel therapeutic strategy that encourages the use of low dose Doxorubicin for treatment of young age adults with non- APL AML. This will reduce treatment expenses, minimize cardiotoxicity, and allow addition of adjunctive therapy which in its turn minimizes resistance.
Facing Islamist Terrorism

International crises like dramatic terror attacks leave their mark on society in various ways. According to the existing literature, some of these consequences include two seemingly conflicting responses: increasing as well as decreasing support for the incumbent government. To make sense of this seeming contradiction, this study combines these observations in one empirical framework. We investigate the effects of Islamist terrorism on citizens' evaluation of the national government by logistic regression analyses using data from the European Social Survey (ESS) for Germany from 2014 to 2017. Our analyses demonstrate that support for the government significantly increases in the aftermath of Islamist terror attacks. However, the intensity of such support decreases with repeated exposure to terror attacks, and these effects even reverse when a certain level of terror is reached. Further, we find that radical right parties benefit from the issues accentuated by terrorism. JEL-Codes: H12, H56, D72, D74
TUAL INFORMATION MAXIMIZATION

This paper studies learning the representations of whole graphs in both unsupervised and semi-supervised scenarios. Graph-level representations are critical in a variety of real-world applications such as predicting the properties of molecules and community analysis in social networks. Traditional graph kernel based methods are simple, yet effective for obtaining fixed-length representations for graphs but they suffer from poor generalization due to hand-crafted designs. There are also some recent methods based on language models (e.g. graph2vec) but they tend to only consider certain substructures (e.g. subtrees) as graph representatives. Inspired by recent progress of unsupervised representation learning, in this paper we proposed a novel method called InfoGraph for learning graph-level representations. We maximize the mutual information between the graph-level representation and the representations of substructures of different scales (e.g., nodes, edges, triangles). By doing so, the graph-level representations encode aspects of the data that are shared across different scales of substructures. Furthermore, we further propose InfoGraph*, an extension of InfoGraph for semi-supervised scenarios. InfoGraph* maximizes the mutual information between unsupervised graph representations learned by InfoGraph and the representations learned by existing supervised methods. As a result, the supervised encoder learns from unlabeled data while preserving the latent semantic space favored by the current supervised task. Experimental results on the tasks of graph classification and molecular property prediction show that InfoGraph is superior to state-of-the-art baselines and InfoGraph* can achieve performance competitive with state-of-the-art semi-supervised models.
THE CHILD QUANTITY-QUALITY TRADE-OFF: EVIDENCE FROM THE POPULATION HISTORY OF ENGLAND MARC P. B. KLEMP AND JACOB L. WEISDORF

We investigate the linkage from sibship size to individual literacy with the Cambridge Group’s demographic (church book) data for historical England. We use exogenous variation in sibship size from parental fecundity and parish-level neonatal mortality to identify the causal mechanism. Our analysis shows that each additional sibling reduces the probability of being literate among all siblings by roughly 10 percentage points. This existence of a historical child quantity-quality trade-off lends strong support to Unified Growth Theory and squares nicely with empirical findings from historical
Volatility Regimes and Cross-market Correlation Dynamics in the Determination of the Optimal International Equity Portfolio

A Markov-switching technique is used to examine co-movement dynamics between domestic and global stock markets and to develop a state-varying approach to the design of an international portfolio. A bivariate Markov switching ARCH (SWARCH) model is designed to evaluate four possible combinations of the volatility states which can characterize both the domestic and world markets, thus allowing the generation of state-varying portfolio loadings on the basis of 4-state correlations. The following conclusions are drawn. First, the domestic and global markets are more strongly correlated when both simultaneously find themselves in the same state of volatility. Conversely, this correlation is weaker when a different volatility state characterizes each market. Furthermore, the circumstances in which both the domestic and global stock markets simultaneously experience high levels of volatility prove strongest cross-market correlations, and result in least effective at reducing the risk stemming from international portfolio diversification. Next, this study determines state-varying portfolio loadings which prove effective at the task of asset allocation, particularly under conditions of market volatility. Finally, filtering structural changes out from the variance-switching process leads to a considerable decrease of the time variation involved in generating state-varying portfolio loadings, which, in turn, leads to lower transaction costs when compared to the performance of the conventional GARCH model. JEL classification: G11, G15
DEFORMABILITY OF THE NEAR-SURFACE LAYER INCLUDING COATINGS

The increased plasticity of the near-surface layer compared to the substrate, even in case of brittle materials and coatings, can often be observed by microscopy on the friction surfaces. Ratcheting or the tribological transformation of the structure (TTS), as a response of the first body to the friction load, can only be explained by this phenomenon. Authors have already published theoretical and experimental studies about the effect of the local changes of the state factors on the deformability of the near-surface layer [1]. According to Johnson [2], authors have expressed their opinion, that the compressive stress state, especially its hydrostatic pressure component, has primary importance from point of view of the increasing of plasticity [3].