bluuebunny/crossref_metadata_2025_split huggingface dataset:
Etiopathogenic Correlations in Breast Cancer
Authors: Ionut-Eduard Iordache , Dan Costea , Mirela Grama , Sabina Neacsu , Liliana Steriu , Nicoleta Leopa , Gabriela Baltatescu , Maria Tomulescu , Razvan Popescu 
Published: February 2020

Abstract
The classic treatises, as well as the latest studies regarding the breast neoplasms emphasize the importance of several favorable factors in the genesis of the breast neoplasm.
The physiological personal history (age of the patient, age of first menstruation, late menopause, late-life sex, reduced breastfeeding, etc.), the personal pathological history, the heredocolateral history (breast, uterine neoplasia, other neoplasms) play a significant role, as well as the living and working conditions (stress, smoking, coffee, alcohol consumption), and dietary factors (hyper-lipidemic and hypoproteinemia regimens).
In order to evaluate the impact of these factors in the etiopathogenesis of breast cancer, we fol-lowed their incidence in a prospective study performed on the cases of breast neoplasm hospital-ized and surgically performed in the period between 2012-2018 in the 1st Surgery Clinic.
Det Ambivalente Kvindebillede I Danske Ordsprog
Authors: Archutowski Tomasz 
Published: February 2020

Abstract
The aim of the paper is to identify the image of a woman coded in Danish proverbs. The basis of my research is the assumption that proverbs convey knowledge of how societies perceive the reality and that proverbs are used as interpretative mechanisms. This is mainly achieved thanks to the repetitive nature of proverbs. Simultaneously proverbs force certain perception of the world upon societies and promote certain values.
The image of a woman in the Danish language is composed by two stereotypes, a negative and a positive one. The image is a combination of contradictions. On one hand there is admiration for features such as care, motherhood, life experience and, hard work, but on the other hand women are submitted to discrimination and harsh social pressure. Women are depicted as talkative, dominating, evil, vain, unpredictable, unrestrained. They face pressure to get married, take good care of their looks, or be exemplary housewives. The analysis of Danish proverbs gives a possibility to observe how much women’s social status, character and the perception of women by the society have changed throughout the centuries and how these changes have influenced the language we use and the reality that the language depicts.
Interdependence between international migration and evolution of development gaps
Authors: Băcescu-Cărbunaru Angelica 
Published: February 2020

Abstract
Migration plays an important role in almost all objectives of sustainable development. In the ‘80s and ‘90s, many authors debated the non-deterministic character of the impact of migration on the development of primarily the countries of origin. Migration as a complex process in globalization has amplified relations between states but there have been very rare reductions in development gaps between them that in turn discourage labour migration. In spite of the increase in well-being based on theory, practice has always revealed an asymmetric development that causes an increase in the differences between emigration and immigration countries.
The global strategy for poverty eradication adopted by world leaders in 2000 did not include migration-related targets, probably because the link between migration and development had not yet been properly perceived. Since then, studies, policy analyzes, international forums and migration recommendations have focused on policy-making in practice, including efforts to support migration concerns in the post-2015 development agenda. Various ideas and recommendations were presented during that data on the most appropriate way to use the migration-development link to maximize its positive effects. In 2015 was adopted the 17 Sustainable Development Goals (SDGs) of the 2030 Agenda for Sustainable Development. Starting with these documents, the contribution of migration to sustainable development was officially recognized for the first time.
From the beginning remittances have played an important role in setting migration as the most important development factor. We sustained that this view, on which allmost all national policies are based, distorts the notion of development and hide the main causes of current labor migration. In this context, this study also attempts to analyze the two-way relation between the factors that determine human development (income, education and health) and international migration.
Managing migration is one of the most important issues of global cooperation.
Modelling monthly Gross Domestic Product on the supply side. A case study for Romania
Authors: Bălţăţeanu Alina Mirela 
Published: February 2020

Abstract
This paper aims to estimate monthly Gross Domestic Product (GDP1), which is an important aggregate indicator; It shows the trend of economic activity in the short term. Thus, the macroeconomic and financial risks in the short term with influences on financial markets and investor confidence (economic sentiment) can be identified and correlated. In addition, the monthly GDP series provides a condensed set of information (monthly data) needed to develop potential GDP estimating models correlated with inflation, unemployment and relevant indicators of labor market. Another applicability is quarterly GDP forecast at least two months ahead of the flash estimate published by National Institute of Statistics (NIS2). This article presents a method of estimating the monthly GDP on the supply side. Gross value added has been broken down into five components: industry, construction, trade and transport, other market services, other activities, the first four of which are well interpolated with unifactorial regressions and some monthly explanatory variables. The results show a high correlation between the 4 components of supply and the additional aggregated quarterly series that are also available on a monthly basis. The highest dynamics of monthly GDP was recorded in August 2017 (+9.3%) and the lowest increase in August 2014 (+1.4%) over the period 2014-2018. Starting in January 2018, economic growth slow down, amid a pronounced base effect of the private consumption and weakening external demand.
What is the quality of life in Romania compared to other EU countries?
Authors: Boboc Cristina , Ghită Simona-Ioana , Popescu Adelina , Săseanu Andreea-Simona 
Published: February 2020

Abstract
Quality of life is a broad multidimensional concept that usually includes both objective and subjective evaluations of positive and negative aspects of life.
This paper analyzes the interdependencies between the nine dimensions of quality of life in EU countries, based on objective indicators according to EUROSTAT approach.
The main objective of this paper is to identify some patterns among EU countries and some directions of improvement of quality of life in Romania by using correlation analysis, principal component analysis and cluster methods. There are identified three main dimensions of quality of life: Material dimension, Social dimension and Educational and environmental dimension. Moreover there are identified three clusters among EU countries: one with high levels of all dimensions, one with high levels of Material dimension but low levels of Social dimension and the third one with low levels of Material dimension and Educational and environmental dimension. Romania is included in the third cluster with a high level on Social dimension but a low level in Material dimension and Educational and environmental dimension.
Statistical analysis of living conditions and quality of life in Romania
Authors: Cazacu Mihaela , Țiţan Emilia 
Published: February 2020

Abstract
The way how people define their standards, perceptions and values influence the quality of their lives. The quality of life is a social trend, an important link of the statistical system in any country, and for its measurement all general statistical methods are used: from systematization and data grouping to the calculation of parameters. This article’s aim is to address how the quality of life is perceived in Romania and the relationships between the main indicators that generally define human development.
Classifying non-banking financial institutions based on their financial performance
Authors: Costea Adrian 
Published: February 2020

Abstract
In this paper we evaluate comparatively the performance of non-banking financial institutions in Romania by the means of unsupervised neural networks in terms of Kohonen’ Self-Organizing Maps algorithm. We create a benchmarking model in the form of a two-dimensional map (a self-organizing map) that can be used to assess visually the performance of non-banking financial institutions based on different performance dimensions, such as capital adequacy, assets’ quality and profitability. We use the following indicators: Equity ratio (Leverage) for the capital adequacy dimension, Loans granted to clients (net value) / total assets (net value) for the assets’ quality dimension and Return on assets (ROA) for the profitability dimension. We have excluded from our analysis the other three dimensions used in evaluating the performance of banks, due to lack of data (for the two qualitative dimensions: quality of ownership and management) and irrelevance with the NFIs’ sector (liquidity). The proposed model is based on the Self-Organising Map algorithm which creates a two-dimensional map (e.g. 6x4 = 24 neurons) from p-dimensional input data. The data were collected for eleven non-banking financial institutions for four years 2007-2010, in total 44 observations. Using the visualization capabilities of the Self-Organising Map model and the trajectories we show the movements of the three non-banking financial institutions with the worst performance: the largest underperformer denoted with X, the second largest underperformer denoted with Y and the third largest underperformer denoted with Z between 2007 and 2010.
Possibilities of statistical analysis of hotel activity performance in a competitive environment
Authors: Ghiţă Simona-Ioana , Gogonea Rodica-Manuela , Săseanu Simona-Andreea 
Published: February 2020

Abstract
The hotel industry is an important driver in tourism development of a region, with positive effects on economic growth, concentrating to a large extent the regional tourism services. The quality of services in this sector is decisive for improving the hotel activity performance, especially in terms of a competitive environment increasingly well defined. The service quality is directly proportional to the hotel comfort category. In 2018 Romania had 34 five-star hotels and 359 four-star hotels, representing less than a quarter of all hotels (24.32%). They owned just over 30% of the total number of hotel bed-places. This paper provides a statistical analysis of activity in the hotel industry in Romania, focusing on main elements of its performance, in terms of a competitive environment. As a result of a case-study on the employees of high comfort category hotels in Bucharest, the key elements of a performing activity are revealed, in order to obtain a competitive advantage.
Are Teaching and Research activities mutually exclusive? A Data Mining study on European Universities
Authors: Grădinaru Simona , Aldea Anamaria , Beşir Levida , Albu Crișan 
Published: February 2020

Abstract
Universities all around the world operate by following several institutional missions, with a central purpose on teaching and research activities. The importance of each aspect alongside the connection between them provide a disputed topic in the literature, many authors confirming or rejecting the intuitive inverse relationship by using various means, more or less quantitative. This paper aims to examine the teaching and research dimensions of the research-active European universities from a data mining perspective. For each dimension previously considered we employ the K-means Clustering in order to identify the groups of similar higher education institutions and we analyze the insights produced by the results. In addition, we build some target variables considering the teaching and research outputs and we investigate their drivers by employing the Logistic Regression. Furthermore, we explore the controverted relationship between the two institutional missions we considered through the use of Correspondence Analysis. Preliminary results illustrate that the dataset contains two types of universities: a category of very large and prestigious institutions and a second group of small and medium sized institutions, quite different from each other. Interest insights are given by the third part of the study, in which the Correspondence Analysis confirms an inverse relationship between teaching and research activities. Unfortunately, this is very likely a consequence of the time constraint – both activities require the same limited resources and therefore increasing the teaching burden for academics may diminish the time and energy dedicated to research.
A Spatial Econometric Analysis of Health in Romania Augmented with Computer Vision
Authors: Jurchiş Florin-Ionuț 
Published: February 2020

Abstract
The purpose of this study is to analyze the health status in Romania at regional NUTS3 level together with its influential socio-economic factors. Apart from statistical and classical econometrics which are being used in most studies, a spatial analysis has been conducted in order to determine possible similarities and dissimilarities among regions, accounting for the fact that events taking place in a specific area are interrelated with the events in the neighboring regions. The negative distribution of the dependent variable, life expectancy, involves the use of Quantile Spatial Autoregressive Model which also allows to observe the socio-economic and environmental factor influences in different parts of health status proxy distribution. The analysis has led to the conclusion that greater the gaps between rich and poor, or greater the difference between less versus better educated, the greater the differences in health status and life expectancy are. Hence a need for policies designed to reduce territorial health disparities has been identified across Romania’s counties. Moreover, Computer Vision and Deep Learning techniques have been used in order to showcase data collection for urban green spaces variables given that more than half of the globe population is living in urban areas and urban greenery has a high positive influence on health. Using Deep Learning on this particular matter together with the Quantile Spatial Autoregressive Model is an innovative approach that has the main aim of improving the classical econometric modelling.
Characterizing the level of economic development of countries
Authors: Nastu Alexandra , Stancu Stelian , Dumitrache Andreea 
Published: February 2020

Abstract
The main purpose of this paper is to provide an objective analysis of the economic development level of countries. This is done by measuring it through a new index and by classifying the countries in an optimal number of clusters, each group characterizing different levels of economic development. The proposed methodology is based on three steps: creating a composite index (by applying the principal component analysis), establishing the optimal number of development groups (based on the number of principal components and on the hierarchical clustering) and clustering countries into them (with the help of k-means analysis). Therefore, this approach solves the difficulty of classifying the countries, complication that is mentioned in the specialized literature. Also, the paper creates a better understanding on the economic development level of countries, as, usually, the papers examine the economic growth level of countries. The analysis is conducted at the level of 60 countries for year 2015, using 12 indicators from categories that influence economic development (income, inequality, health, education and living conditions). The empirical results revealed that the countries can be grouped in two groups: economical developed countries (approximatively 2/3) and economic developing countries (approximatively 1/3). The countries that are most developed from an economic point of view are: Singapore, Luxemburg and Finland.
Exchangeable models of financial correlations matrices. Bayesian nonparametric models and network derived measures of financial assets
Authors: Opincariu Sorin , Ionescu Stefan 
Published: February 2020

Abstract
De Finetti theorem establishes the conceptual basis of Bayesian inference replacing the independent and identically distributed sampling hypothesis prevalent in frequentist statistics with the much easier to justify in practical settings hypothesis of exchangeability. In this paper we make use of the extension of the concept of exchangeability from sequences to arrays arguing that the invariance to ordering is a much more tenable assumption than independent and identically distributed sampling in the financial modeling problems. Making use of the celebrated Aldous-Hoover representation theorem of exchangeable matrix we construct a Bayesian non-parametric model of the financial returns correlation matrices arguing that a Bayesian approach can mitigate many of the known shortcomings of the usual Pearson correlation coefficient. We posit the correlation matrix to be an exchangeable matrix and construct a Bayesian neural network to estimate the functions from the Aldous-Hoover representation theorem. The correlation matrix model is coupled with a Student-t likelihood (accounting for the heavy tails of financial returns). The model is estimated with a Hamiltonian Monte Carlo sampler. The samples are used to construct an ensemble of networks where each edge is weighted by the size of the correlation between two financial instruments. Various centrality measures are being calculated (betweenness, eigenvector) for each network of the ensemble allowing us to obtain a probabilistic view of each financial instrument’s importance. We also construct a minimum spanning tree associated with the mean correlation matrix allowing us to visualize the most important financial instruments from the universe selected.
Efficiency of SVM classifier with Word2Vec and Doc2Vec models
Authors: Truşcă Maria Mihaela 
Published: February 2020

Abstract
Support Vector Machine model is one of the most intensive used text data classifiers ever since the moment of its development. However, its performance depends not only on its features but also on data preprocessing and model tuning. The main purpose of this paper is to compare the efficiency of more Support Vector Machine models using both TF-IDF approach and Word2Vec and Doc2Vec neural networks for text data representation. Besides the data vectorization process, I try to enhance the models’ efficiency by identifying which kind of kernel fits better the data or if it is just better to opt for the linear case. My results prove that for the “Reuters 21578” dataset, nonlinear Support Vector Machine is more efficient when the conversion of text data into numerical attributes is realized using Word2Vec models instead of TF-IDF and Doc2Vec representations. When it is considered that data meet linear separability requirements, TF-IDF representation outperforms all other options. Surprisingly, Doc2Vec models have the lowest performance and only in terms of computational cost they provide satisfactory results. This paper proves that while Word2Vec models are truly efficient for text data representation, Doc2Vec neural networks are unable to exceed even TF-IDF index representation. This evidence contradicts the common idea according to which Doc2Vec models should provide a better insight into the training data domain than Word2Vec models and certainly than the TF-IDF index.
When a Stroke is not Just a Stroke: Escherichia coli Meningitis with Ventriculitis and Vasculitis: A Case Report
Authors: Ribeiro Barbara , Bishop Peter , Jalili Sima 
Published: February 2020

Abstract

Introduction
Community-acquired Escherichia coli ventriculitis is considered a rare condition. Central nervous system (CNS) infection due to gram-negative bacilli is usually associated with previous neurosurgical interventions. The recent publication of cases of Escherichia coli meningitis and ventriculitis suggests its prevalence may be underestimated by the literature.

Case presentation
A case of community-acquired Escherichia coli CNS infection on a 58 year old patient presenting with altered consciousness but without neck stiffness, nor significant past medical history is reported. Imaging and lumbar puncture findings suggested a complex case of meningitis with associated ventriculitis and vasculitis. Escherichia coli was later identified in cultures. Subsequent multi-organ support in Intensive Care was required. The patient was treated with a prolonged course of intravenous antimicrobials guided by microbiology, resulting in some neurological recovery. The main challenges encountered in the management of the patient were the lack of clear recommendations on the duration of treatment and the potential development of multi-resistant organisms.

Conclusion
Bacterial central nervous system infections can have an atypical presentation, and an increasing number of cases of community-acquired ventriculitis have been reported. Early consideration should be given to use magnetic resonance imaging to help guide treatment. A long course of antibiotics is often required for these patients; however, the optimal duration for antimicrobial treatment is not well defined.
The Effect of Early Childhood Education and Care Services in Latvia
Authors: Kūkoja Katrīne 
Published: February 2020

Abstract
The growing number of studies stresses the importance of social investment at an early age by showing that social investment at this period has the highest returns in human capital. The main instrument of social investment at an early age is high quality early childhood education and care services. The aim of the research was to identify whether the first signs of social investment return could be observed in Latvia, since statistic data showed that there was an expansion of early childhood education and care services over the last decades, especially for children until obligatory pre-school age. Research results showed that positive connection could be observed between pre-school attendance rate and fertility rate, female and overall employment rate, average earning, etc. However, no connection could be observed when it came to education outcomes in the short term. The author recommends conducting more research regarding service quality and investment return in the future.
Quality, Equity, Inclusion and Lifelong Learning in Pre-service Teacher Education
Authors: Sunthonkanokpong Wisuit , Murphy Elizabeth 
Published: February 2020

Abstract
Sustainable Development Goal 4 (SDG 4) focuses on ensuring inclusive and equitable, quality education and lifelong learning opportunities for all. One of the three means of implementation of SDG 4 targets is SDG 4c which calls on countries and donors to significantly increase the supply of qualified teachers in developing and underdeveloped countries. This emphasis on the supply of teachers is in recognition of the fact that the quality of education ultimately depends on teachers. In general, there is widespread agreement that teacher education has an important role to play in the achievement of the SDG 4 targets. However, there has been limited attention in the literature to SDG 4 in a context of teacher education. This paper aims to contribute to the literature on SDG 4 and teacher education. The paper first presents a conceptual framework pertaining to quality, equity, inclusion, and lifelong learning. Next, the framework is applied to the case of Thailand to identify examples of progress the country is making in support of realization of SDG 4 in teacher education. The framework with the four concepts can be applied by researchers to identify examples of progress on SDG 4 in teacher education in other countries and contexts.