NUTS Classification Research Articles

Анализ на част от нефинансовите предприятия в селските райони на Южен централен район за периода 2010 – 2020 година (в контекста на локализационния индекс – LI)

The presented development attempts to visualize and analyze part of the non-financial enterprises in the rural areas (RA) of the South-Central Region (SCR) of Bulgaria. The aim of the scientific work is to present the localization (concentration) of non-financial enterprises in the rural areas of the South-Central Region and their specialization, relative to the region and the country based on the Localization Index (LI). The development considers the definition of RA as such in the country and the EU. The NUTS classification is applied to group the above-mentioned territories by districts in the region. The methodology includes - Localization index, for analyzing part of the non-financial enterprises (I 55 – Hotel industry, I 56 – Restaurant industry, P – Education and H – Transport, warehousing and posts) in the RA of the SCR according to the CEA – 2008 classification. An empirical, statistical and comparative approach is applied in research, analysis, drawing conclusions and conclusions. The visualization of the developed material is presented in tables and figures, in which the dynamics of numerical values of LI for the period 2010 – 2020 are indicated.

Regional variation in intergenerational social mobility in Britain.

We present the first comprehensive set of estimates of variation in intergenerational social mobility across regions of Great Britain using data from the UK Labour Force Survey. Unlike the Social Mobility Index produced by the Social Mobility Commission, we focus directly on variation in measures of intergenerational social class mobility between the regions in which individuals were brought up. We define regions using the NUTS classification and we consider three levels, from 11 large NUTS1 regions, to 168 NUTS3 regions, across England, Wales, and Scotland. We investigate whether it is possible to form an index of social mobility from these measures and we address a neglected question: how much does the region in which someone was raised matter in comparison with the social class in which they were raised?

Low-Cost Classification of Close and Open Shell Antep Pistachio Nuts based on Image Analysis and Machine Learning

The effectiveness of post-harvest industrial processes is critical to maintaining the economic worth of pistachio nuts, which play an essential role in the agricultural economy. To achieve this level of efficiency, updated applications and technology for pistachio separation and categorization are required. Different pistachio species target different markets, highlighting the need for pistachio species classification. This work aims to develop a classification model that is distinct from existing separation approaches, based on image processing and machine learning, and can provide the required categorization. A computer vision application was done to identify between three types of pistachios. A high-resolution camera was used to capture 385 images of these pistachios. The photos of the pistachio samples were processed using image processing techniques like segmentation and feature extraction. On the given dataset, an advanced classifier based on Decision Tree and Random Forest predictions was constructed, as well as a simple and successful classifier. In the research, an application with feature extraction based on the dimension and pixel measurement is proposed. The proposed approach attained a classification success rate of 100% at 70% train and 30% test, and also, 80% train and 20% test data rate with Random Forest prediction, according to the experimental data. The provided high-performance classification model fills an important demand for the separation of pistachio types while increasing the economic worth of the species.

Romanya’da tarım sektörü ve arazi mülkiyet durumu (1990-2020).

Romanya 13,8 milyon hektar tarım arazisiyle Avrupa Birliği Ülkelerinin toplam tarım alanın % 7,2’sine sahiptir. Ülkede yaşanan siyasi rejim değişikleri ve Avrupa Birliği üyeliği, arazi mülkiyetinde yapısal değişime sebep oldu. 1990 sonrasında büyük çiftlik arazilerinin halka dağıtılması sonucu tarlalar küçük parsellere bölündü. Romanya’nın AB’ye katılım sürecinde ve 2007’de gerçekleşen tam üyelik sonrasında yapılan yasal düzenlemeler, çok uluslu şirketlerin kiralama ve satın almalar yoluyla büyük arazilere sahip olmalarını sağladı. 1990 ile 2020 yılları arasını kapsayan bu çalışmada, Romanya’daki arazi mülkiyetinin devlet, bireysel üretici ve tüzel kişiliğe sahip işletmeler şeklinde yıllara göre değişimi ortaya konulmaktadır. Mısır, buğday ve ayçiçeğinin ekim alanı, üretim miktarı ve verimliliğin yıllara göre değişimi, örnek teşkil etmesi adına tablolar şeklinde gösterilmektedir. AB ülkelerinde kullanılan NUTS sınıflandırması ile Romanya 8 bölgeye ayrılarak incelenmiştir. Kaynak olarak, FAOSTAT ve Romanya Ulusal İstatistik Ajansı esas alınmıştır. Arazi kullanımı verileri CORINE tarafından sağlanmış ve ARCMap ortamında oluşturulmuştur.

Study of part of non-agricultural activities in rural areas of South-Central region of Bulgaria for the period 2010 – 2020

Rural areas (RA), according to their geographical determination, are determined by specific characteristics for each of them. The administrative affiliation, on the other hand, fixes the socio-economic profile and in relation to this direction, the aim of the scientific study is to investigate some of the non-agricultural activities - Hotel and restaurant industry (I), Education (P) and Human health and social work (Q) in the rural areas of the South-Central Region (SCR) for the period 2010-2020. The study includes employed persons and enterprises in the specified subsectors. The aim of the current development is to track the movement of employed persons and enterprises in the RA of the country. These subsectors are related to the socio-economic status of these territories. Deductive, comparative method and Localization Index (IL) have been applied. Analysis and conclusions are made based on the Index of localization of the various activities, comparing them to the territories according to the NUTS classification. The conclusion and the findings are based on the results indicated in the study. The Classification of Economic Activities (CEA) of 2008, EU Regulation No 1893/2006 of the European Parliament and of the Council of 20.12.2006 have been applied.

Nuts as a Dietary Enrichment with Selected Minerals—Content Assessment Supported by Chemometric Analysis

Nuts used as a snack and meal accompaniment supply plant protein and fatty acids that are beneficial for human health; however, they can also provide minerals. The aim of this study was to determine the content of selected elements that are often deficient in the diet (calcium, potassium, magnesium, selenium, and zinc) in nuts and determine whether they can be used to supplement deficiencies in the diet. In this study, we analyzed 10 types of nuts (n = 120 samples) that are consumed and available for sale in Poland. The content of calcium, magnesium, selenium, and zinc was determined by the atomic absorption spectrometry method, and flame atomic emission spectrometry was used for determination of potassium contents. The highest median calcium content was found in almonds (2825.8 mg/kg), the highest potassium content in pistachio nuts (15,730.5 mg/kg), the highest magnesium and selenium contents in Brazil nuts (10,509.2 mg/kg and 4348.7 μg/kg, respectively), and the highest zinc content in pine nuts (72.4 mg/kg). All the tested nuts are a source of magnesium, eight types of tested nuts are a source of potassium, six nut types are a source of zinc, and four nut types are a source of selenium; however, among the tested nuts, only almonds can be considered a source of calcium. Moreover, we found that selected chemometric methods can be useful in the classification of nuts. The studied nuts are valuable products that can be used to supplement the diet with selected minerals and can therefore be labelled as functional products crucial for disease prevention.

Applications of machine learning in pine nuts classification

Pine nuts are not only the important agent of pine reproduction and afforestation, but also the commonly consumed nut with high nutritive values. However, it is difficult to distinguish among pine nuts due to the morphological similarity among species. Therefore, it is important to improve the quality of pine nuts and solve the adulteration problem quickly and non-destructively. In this study, seven pine nuts (Pinus bungeana, Pinus yunnanensis, Pinus thunbergii, Pinus armandii, Pinus massoniana, Pinus elliottii and Pinus taiwanensis) were used as study species. 210 near-infrared (NIR) spectra were collected from the seven species of pine nuts, five machine learning methods (Decision Tree (DT), Random Forest (RF), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Naive Bayes (NB)) were used to identify species of pine nuts. 303 images were used to collect morphological data to construct a classification model based on five convolutional neural network (CNN) models (VGG16, VGG19, Xception, InceptionV3 and ResNet50). The experimental results of NIR spectroscopy show the best classification model is MLP and the accuracy is closed to 0.99. Another experimental result of images shows the best classification model is InceptionV3 and the accuracy is closed to 0.964. Four important range of wavebands, 951–957 nm, 1,147–1,154 nm, 1,907–1,927 nm, 2,227–2,254 nm, were found to be highly related to the classification of pine nuts. This study shows that machine learning is effective for the classification of pine nuts, providing solutions and scientific methods for rapid, non-destructive and accurate classification of different species of pine nuts.

Индекс на локализация на земеделските стопанство в периода 2008-2016 г. в селските райони на Южен централен район

The rural development policy in Bulgaria is dictated by the accompanying facts, with approximately 45% of the population living in them, covering 85% of the territory. The study and analysis of the socio-economic processes in agriculture of smaller administrative units of the NUTS classification gives an accurate picture of the real situation. The operation of farms ensures the production of different types of agricultural production. Contributing to the formation of Gross Domestic Product and the fulfillment of commitments in relation to the EU Common Agricultural Policy. The application of the localization index for agricultural holdings in the rural areas of the South-Central Region in Bulgaria reveals their real economic status. The study of the specialization factor for agricultural holdings covers an eight-year period 2008-2016. The localization index is the basis for an analysis of the different types of economic processes and phenomena. It is also applicable in smaller administrative areas, namely in the rural municipalities of the South-Central Region.

Innovation ecosystems of Ukraine: a conceptual framework for development in the conditions of glocalization and eurointegration

The paper is devoted to development of theoretical and methodological foundations, conceptual provisions and practical recommendations for the development of innovation ecosystems of Ukraine. The theoretical and methodological foundations of the concept of innovation ecosystem as a result of the development of innovation theory are improved; the interconnection between glocalization of the world economy and the development of innovation processes is revealed. The research revealed the leading role of industry in the development of innovation ecosystems. Scientific and methodical approach for assessment of innovation activities in industry was developed; analysis and assessment of innovation processes in industry was carried out on the basis of proposed approaches in the context of industries and regions. The necessity of neo- industrialization of the economy is substantiated as a condition for the development of the national innovation ecosystem of Ukraine. Obstacles on the way to neo-industrialization and development of national innovation ecosystem are identified and characterized, the proposals for overcoming them have been developed. Systematization of the institutional foundations, the state and problems of European integration of Ukraine in scientific, technical and innovation sphere has been carried out; the directions of strengthening of Ukrainian participation in the European research area were revealed. A conceptual approach to the development of national innovation ecosystem of Ukraine in accordance with the requirements of the European NUTS classification was proposed; a conceptual model of Ukrainian innovation ecosystems was developed. The proposals for the institutional support of the formation of regional innovation ecosystems of Ukraine at the level of economic regions are substantiated. The scientific and methodological approach to the formation of special economic zones as stimulating regulatory regimes aimed at the development of innovation ecosystems was improved.

Смартспеціалізація європейських регіонів – лідерів у сфері інновацій: систематизація підходів

The article is aimed at analyzing and systematizing the approaches to determining the smart priorities of the regions of the European Union, which are leaders in innovative development, to develop recommendations for improving the process of formation of regional strategies for smart specialization in Ukraine. Smart priorities of the top 10 innovatively active regions of the EU according to the Regional Innovation Board were studied using the information provided by the European platform for smart specialization. Certain methodological problems and limitations for the analysis of regional smart specializations related to certain changes in the NUTS classification and different periods of adoption of regional strategies are identified. It is noted that smart priorities in many regions are based on the innovative development of traditional types of economic activity. It is displayed that the processing industry is most involved in the formation of regional smart specializations, also widely involved are the sectors of scientific-technical activities, information and telecommunications, transportation, and education. It is defined that a large proportion of priorities are of complex nature. This is connected with the cross-sectoral cooperation, as well as the use of horizontal-type instruments (digitalization, increasing the value of knowledge, spread of advanced technologies, focusing on the Sustainable Development Goals, social innovations). It is emphasized that the leading regions most often choose digital transformation, sustainable innovations and KETs for the goals of their smart specialization policies. The strategy of smart specialization of the Western Netherlands, which is the result of the collaboration of a number of research institutions, public and private companies and local authorities, is considered. It is concluded that when determining the priorities of Ukrainian regions, it is necessary to focus on the fore-mentioned EU goals and deepen the analysis of scientific-technological specializations of territories, as well as to formalize the role of science and education in regional strategies of smart specialization.

Online Application of a Hyperspectral Imaging System for the Sorting of Adulterated Almonds

Almonds are nutrient-rich nuts. Due to their high level of consumption and relatively high price, their production is targeted for illegal practices, with the intention of earning more profit. The most common adulterants are based on superficial matching, and as an adulterant, the apricot kernel is comparatively inexpensive and almost identical in color, texture, odor, and other physicochemical characteristics to almonds. In this study, a near-infrared hyperspectral imaging (NIR-HSI) system in the wavelength range of 900–1700 nm synchronized with a conveyor belt was used for the online detection of added apricot kernels in almonds. A total of 448 samples from different varieties of almonds and apricot kernels (112 × 4) were scanned while the samples moved on the conveyor belt. The spectral data were extracted from each imaged nut and used to develop a partial least square discrimination analysis (PLS-DA) model coupled with different preprocessing techniques. The PLS-DA model displayed over a 97% accuracy for the validation set. Additionally, the beta coefficient obtained from the developed model was used for pixel-based classification. An image processing algorithm was developed for the chemical mapping of almonds and apricot kernels. Consequently, the obtained model was transferred for the online sorting of seeds. The online classification system feedback had an overall accuracy of 85% for the classification of nuts. However, the model presented a relatively low accuracy when evaluated in real-time for online application, which might be due to the rough distribution of samples on the conveyor belt, high speed, delaying time in suction, and lighting variations. Nevertheless, the developed online prototype (NIR-HSI) system combined with multivariate analysis exhibits strong potential for the classification of adulterated almonds, and the results indicate that the system can be effectively used for the high-throughput screening of adulterated almond nuts in an industrial environment.

SUSTAINABLE REGIONAL DEVELOPMENT AS A FACTOR OF COMPETITIVENESS OF NATIONAL ECONOMY

Regional issues are an indispensable subject of interest of experts from different provinces in each country. The presence of pronounced regional disparities in different domains is generally considered to be the source of various problems in the functioning of the national economy and society as a whole. Over the past two decades, several proposals for regionalization have been put forward in Serbia, given its strategic commitment to EU accession. The paper presents the current regionalization of Serbia in accordance with the NUTS classification, taking into account the specific position of the Kosovo and Metohija region. The basic characteristics of the NUTS 2 level regions are analyzed from the point of view of strengthening the competitiveness of the national economy. In a separate part of the paper, the institutional foundations of the country's regional development and the need to align domestic regional policy with European practices and standards (exogenous vs. endogenous approach, urban-rural, etc.) are discussed. Human capital, entrepreneurship and regional development can be seen as determinants of the mechanism of progress through which national economies grow.

Non-Targeted HPLC-UV Fingerprinting as Chemical Descriptors for the Classification and Authentication of Nuts by Multivariate Chemometric Methods.

Recently, the authenticity of food products has become a great social concern. Considering the complexity of the food chain and that many players are involved between production and consumption; food adulteration practices are rising as it is easy to conduct fraud without being detected. This is the case for nut fruit processed products, such as almond flours, that can be adulterated with cheaper nuts (hazelnuts or peanuts), giving rise to not only economic fraud but also important effects on human health. Non-targeted HPLC-UV chromatographic fingerprints were evaluated as chemical descriptors to achieve nut sample characterization and classification using multivariate chemometric methods. Nut samples were extracted by sonication and centrifugation, and defatted with hexane; extracting procedure and conditions were optimized to maximize the generation of enough discriminant features. The obtained HPLC-UV chromatographic fingerprints were then analyzed by means of principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to carry out the classification of nut samples. The proposed methodology allowed the classification of samples not only according to the type of nut but also based on the nut thermal treatment employed (natural, fried or toasted products).

The rationale and design of the national familial hypercholesterolemia registries in Turkey: A-HIT1 and A-HIT2 studies.

Familial hypercholesterolemia (FH) is a genetic disease characterized by extremely high levels of cholesterol, leading to premature atherosclerosis. Although many countries have already addressed the burden of FH by means of national registries, Turkey has no national FH registry or national screening program to detect FH. Creation of a series of FH registries is planned as part of Turkish FH Initiative endorsed by the Turkish Society of Cardiology to meet this need. This article provides detailed information on the rationale and design of the first 2 FH registries (A-HIT1 and A-HIT2). A-HIT1 is a nationwide survey of adult homozygous FH (HoFH) patients undergoing low-density lipoprotein (LDL) apheresis (LA) in Turkey. A-HIT1 will provide insight into the clinical status of HoFH patients undergoing LA. Primary objective of this cross-sectional study is to identify how HoFH patients on LA are managed. Inclusion criteria are age >12 years, diagnosis of HoFH, and regular LA treatment. All available apheresis centers were electronically invited to participate in the study. The principal physicians of each center will respond to a questionnaire regarding their attitude toward LA. For each patient, another questionnaire will be used to collect data on clinical status, medication use, and disease data. In addition, patients will be asked to complete self-report questionnaires that provide information on quality of life, disease-related anxiety, and depression. A-HIT2 is a registry of adult FH patients presenting at outpatient clinics. At least 1000 FH patients will be recruited from 30 outpatient clinics representing the 12 statistical regions in Turkey based on the EU NUTS classification. Sites specializing in cardiology, internal medicine, and endocrinology were invited to participate. The primary objective of this cross-sectional study is to determine clinical status and management of patients in Turkey diagnosed with FH. Eligibility for screening was defined as having LDL-cholesterol level >160 mg/dL. Inclusion criteria are age >18 years and diagnosis as possible FH (total score of >2 according to Dutch Lipid Clinic Network criteria). In addition to measuring clinical status of patients, a short survey to assess patient level of disease awareness will also be administered. A-HIT1 and A-HIT2 are the first nationwide FH registries in Turkey and will provide important information on the management of Turkish FH patients. In addition, it is planned that they will guide establishment of a national policy for the diagnosis and treatment of FH in Turkey.

Economic Polarization Across European Union Regions in the years 2007–2012 at NUTS 2 Level

Abstract The aim of this paper is to study the economic polarization in countries of the EU at NUTS 2 level in the years 2007–2012. The studies have to decide on positive or negative verification of the hypothesis, which states that the economic crisis of 2008–2013 had an influence on rising economic polarization in EU countries. The method used in this article is an application of some measures of economic polarization and inequality of income distribution. The carried out research did not allow for the positive verification of the hypothesis. Only in a few countries did the economic crisis have an influence on a reduction of the middle class. In most cases the economic collapse did not play any role in the raising of the economic polarization index. The statistical data used in this paper was taken from the following databases: Statistical Yearbook of the Regions – Poland from 2009 to 2013 and Eurostat – Regional statistics by NUTS classification*.

Quality Evaluation of Shelled and Unshelled Macadamia Nuts by Means of Near-Infrared Spectroscopy (NIR).

The quality of shelled and unshelled macadamia nuts was assessed by means of Fourier transformed near-infrared (FT-NIR) spectroscopy. Shelled macadamia nuts were sorted as sound nuts; nuts infected by Ecdytolopha aurantiana and Leucopteara coffeella; and cracked nuts caused by germination. Unshelled nuts were sorted as intact nuts (<10% half nuts, 2014); half nuts (March, 2013; November, 2013); and crushed nuts (2014). Peroxide value (PV) and acidity index (AI) were determined according to AOAC. PCA-LDA shelled macadamia nuts classification resulted in 93.2% accurate classification. PLS PV prediction model resulted in a square error of prediction (SEP) of 3.45 meq/kg, and a prediction coefficient determination value (Rp (2) ) of 0.72. The AI PLS prediction model was better (SEP = 0.14%, Rp (2) = 0.80). Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT-NIR spectroscopy can be successfully used to predict PV and AI in unshelled macadamia nuts, though.

Changing Dynamics of Regional Policyin Turkey: Resistance for Multi-level Governance

This article investigates the relationship between Europeanization and regionalization processes in Turkey. In this respect, it analyses the causes and mechanisms encouraging regionalization process during the EU accession process. Findings suggest that while some of the changes are considered as direct effects of Europeanization (i.e., the adoption of NUTS classification), other developments (i.e. the creation of regional development agencies and their role in regional planning and allocation of national funds) are invoked by indirect mechanisms of Europeanization. The findings also illustrate that although the EU's credibility has declined after 2005 and its regional policy have shifted towards the more centralized model in the post-Lisbon era, developments in these areas in Turkey have gone to opposite directions, more accurately, through the more regionalized model. These changes not only reflect the pre-Lisbon practices of EU regional policy and structural funds underlining a spill-over effect resulting from the dissemination of EU practices and policies, but also contain the spices of Turkish administrative tradition.

Regionalizacija u okviru Evropske unije

The goal of regionalization is multifaceted - political, developmental, economic, historical, cultural, demographic setting. From the standpoint of the European Union, the goal of regionalization is punching the border barrier between the states and the liberation of capital flows, labor, and information. It is evident that the regionalization in this context is seen as a form of better governance and its contents, or as an instrument of control and establishing a balance between regional disparities, and smoother intraallocation of resources. The European Union attaches great importance of joint regional policy of the member states of the integration. The regional policy is one of the fundamental policies of the European Union, which aims to strengthen economic and social cohesion by reducing disparities in levels of development between countries and regions in Europe. Regional Policy of the European Union provides the kind of opportunities and possibilities for regional development of member states. To what extent these policies contribute to the regional development of each country, largely depends on how much the member states and their regions manage the chance to take advantage of the right way. Choice model of regionalization is specificum each country, and in this respect we can say that there is only one, single, universal model that could be applicable in each country. In this paper, at the same time, data classification regions in the European Union (NUTS classification) and gives a brief overview of the region in the approximation Community. At the same time, considering the experience of some European countries in the process of regionalization.

Detection and classification of areca nuts with machine vision

In this study, we present an application of neural networks and image processing techniques for detecting and classifying the quality of areca nuts. Defects with diseases or insects of areca nuts were segmented by a detection line (DL) method. Six geometric features (i.e., the principle axis length, the secondary axis length, axis number, area, perimeter and compactness of the areca nut image), 3 color features (i.e., the mean gray level of an areca nut image on the R, G, and B bands), and defects area were used in the classification procedure. A back-propagation neural network classifier was employed to sort the quality of areca nuts. The methodology presented herein effectively works for classifying areca nuts to an accuracy of 90.9%.

Conceptualising ‘macro-regions’: Viewpoints and tools beyond NUTS classification

Definitions are imposed but properties not. The basic question addressed by this paper is how to ‘detect’ objective socio-economic spatial structures instead of ‘defining’ them arbitrarily. The NUTS classification model is rather arbitrary. Not only have the administrative units been structured through ‘accidental’ historical conditions but the reliability of the measurement of the population in an area is disputable as long as the mobility is strengthened and the ‘usual residence’ becomes more and more vague. Concerning the auxiliary criteria, they are also heterogeneous and are rather perceptions imposed by decision makers than physical entities. The quantitative network analysis (QNA) approach is suggested as a tool to detect macro-structures regarded as socio-economic and natural infrastructure of a ‘macro-region’. This is based on algebraic analysis of a number of variables such as flows of people migration, financial means, information, commodities, bio-diversity elements and parameters of the new relationship between urban and rural areas. In this paper, by using algorithms of QNA, such as Density of flows or Betweenness centrality of places, ‘denser’ networks of flows among places or more ‘central’ places can be differentiated from others, and thus can be used for a more substantial demarcation of ‘macro-regions’.