Problematika nedoslednega prevajanja kategorij kazalnikov uspešnosti za spremljanje ukrepov SKP v predpisih EK iz angleškega v slovenski jezik

In monitoring and evaluating the performance framework of the CAP, EU Member States are required to establish performance indicators (PI) that will ensure the evaluation of the performance and effectiveness of the main and specific objectives and priorities of each program. Inconsistent translation of EC regulations from English into Slovenian was observed in the context of the types of PI categories and their relations. There was inconsistency between regulations, ambiguity and uncertainty in certain parts of the regulations. This caused a violation of the principle of legal certainty for Slovenia towards the EU and the EC. It was found that legal translators in Slovene translations of some EC regulations use different terms for the same legal matter, which have a different meaning. This disrupts the hierarchical levels of the PI categories, which creates ambiguous obligations for Slovenia in parts of the regulation. The article presents EU and EC regulations, which clearly show the violation of the principle of legal certainty. Through the performed cognitive verbal semantic analysis and with the help of dictionaries, we propose appropriate translations of PI categories. We propose that the regulations and the official documents deriving from them be aligned with the next financial period 2021-2027.Pri spremljanju in vrednotenju okvira uspešnosti SKP so države članice EU dolžne vzpostaviti kazalnike uspešnosti (KU), ki bodo zagotavljali vrednotenje uspešnosti in učinkovitosti glavnih in posebnih ciljev in prednostnih nalog vsakega programa. Opaženo je bilo nedosledno prevajanje predpisov EK iz angleškega v slovenski jezik, v kontekstu vrst kategorij KU in njihovih odnosov. Povzročena je bila neskladnost med predpisi, dvoumnost in nejasnost določenih delov predpisov. S tem je bilo povzročeno kršenje načela pravne varnosti Slovenije do EU in EK. Ugotovljeno je bilo, da pravni prevajalci v slovenskih prevodih nekaterih predpisov EK za isto pravno zadevo uporabljajo drugačne izraze, ki nosijo drugačen pomen. S tem porušijo hierarhične ravni kategorij KU, kar ustvari dvoumne obveznosti Slovenije v delih predpisa. V prispevku predstavimo predpise EU in EK, kjer je jasno prikazano kršenje načela o pravni varnosti. Preko izvedene kognitivne besedne semantične analize in s pomočjo slovarjev predlagamo ustrezne prevode kategorij KU. Predlagamo, da se predpisi in uradni dokumenti, ki iz njih izhajajo, uskladijo z naslednjim finančnim obdobjem 2021-2027

Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative SNPs

Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F-ST) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% +/- 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7.MP was supported by a Basque Government grant (IT1233-19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Designing a proposal of new method for calculating the expected return of agricultural land in the Republic of SloveniaA

Trenutno je Republika Slovenija brez uradno predpisane enotne metodologije za izračun tržne vrednosti kmetijskih zemljišč. Dohodkovni način, ki se ga najpogosteje uporablja pri sodnih cenitvah kmetijskih zemljišč, ima pomanjkljivost v enačbi, saj ne določa jasno opredeljenih pogojev za izračun pričakovanega donosa kmetijskega zemljišča. Na podlagi preučitve enačb in rezultatov vrednotenja kmetijskih zemljišč iz Primorske in Pomurske regije smo z uporabo znane metode prikazali, kaj bi se zgodilo z ocenjenimi vrednostmi, če bi uporabljali natančno izračunan pričakovan donos. Opisali smo nov postopek za izračun pričakovanega donosa, ki temelji na oceni realnega donosa kmetijskih zemljišč v Republiki Sloveniji, pri čemer kmetijska zemljišča pojmujemo kot lastni kapital. Uporabili smo deset letno obrestno mero za državne obveznice, nepovezano beto in izračunano stopnjo kapitalizacije kmetijskih zemljišč. Ugotovili smo, da ima Zahodna regija manjši pričakovani donos kot Vzhodna regija. Ravno tako se je pokazalo, da obstaja neopredeljen vpliv v dohodkovnem načinu, ki se je pokazal šele z uporabo izračunanega pričakovanega donosa. Nov način omogoča izračun realnejše tržne vrednosti kmetijskih zemljišč zaradi upoštevanja cenovnih gibanj. Nov način omogoča izračun poštene tržne vrednosti kmetijskih zemljišč tudi v času ekstremnih ekonomskih položajev države, kot je na primer recesija.Currently, the Republic of Slovenia has not officially prescribed a uniform methodology for calculating the market value of agricultural land. The income method, which is most often used in judicial estimates of agricultural land, has a deficiency in the equation since it does not provide clearly defined conditions for calculating the expected return on agricultural land. Based on the study of the equations and the results of the evaluation of agricultural land from the Primorska region and the Pomurje region, using the known methods, we demonstrated what would happen to the estimated values if we were using the precisely calculated expected yield. We have described a new procedure for calculating the expected return, based on an estimate of the real yield of agricultural land in the Republic of Slovenia, whereby agricultural land is considered as own capital. We used a ten-year interest rate for government bonds, unrelated beta and the calculated rate of capitalization of agricultural land. We have found that the Western region has a lower expected return than the Eastern region. It has also been shown that there is an undetermined influence in the income method, which was shown only using the calculated expected return. The new method allows calculating the realistic market value of agricultural land in order to take into account price movements. The new method makes it possible to calculate the fair market value of agricultural land during the time of the country\u27s extreme economic situation, such as the recession

DESIGNING A PROPOSAL OF NEW METHOD FOR CALCULATING THE EXPECTED RETURN OF AGRICULTURAL LAND IN THE REPUBLIC OF SLOVENIA

Trenutno je Republika Slovenija brez uradno predpisane enotne metodologije za izračun tržne vrednosti kmetijskih zemljišč. Dohodkovni način, ki se ga najpogosteje uporablja pri sodnih cenitvah kmetijskih zemljišč, ima pomanjkljivost v enačbi, saj ne določa jasno opredeljenih pogojev za izračun pričakovanega donosa kmetijskega zemljišča. Na podlagi preučitve enačb in rezultatov vrednotenja kmetijskih zemljišč iz Primorske in Pomurske regije smo z uporabo znane metode prikazali, kaj bi se zgodilo z ocenjenimi vrednostmi, če bi uporabljali natančno izračunan pričakovan donos. Opisali smo nov postopek za izračun pričakovanega donosa, ki temelji na oceni realnega donosa kmetijskih zemljišč v Republiki Sloveniji, pri čemer kmetijska zemljišča pojmujemo kot lastni kapital. Uporabili smo deset letno obrestno mero za državne obveznice, nepovezano beto in izračunano stopnjo kapitalizacije kmetijskih zemljišč. Ugotovili smo, da ima Zahodna regija manjši pričakovani donos kot Vzhodna regija. Ravno tako se je pokazalo, da obstaja neopredeljen vpliv v dohodkovnem načinu, ki se je pokazal šele z uporabo izračunanega pričakovanega donosa. Nov način omogoča izračun realnejše tržne vrednosti kmetijskih zemljišč zaradi upoštevanja cenovnih gibanj. Nov način omogoča izračun poštene tržne vrednosti kmetijskih zemljišč tudi v času ekstremnih ekonomskih položajev države, kot je na primer recesija.Currently, the Republic of Slovenia has not officially prescribed a uniform methodology for calculating the market value of agricultural land. The income method, which is most often used in judicial estimates of agricultural land, has a deficiency in the equation since it does not provide clearly defined conditions for calculating the expected return on agricultural land. Based on the study of the equations and the results of the evaluation of agricultural land from the Primorska region and the Pomurje region, using the known methods, we demonstrated what would happen to the estimated values if we were using the precisely calculated expected yield. We have described a new procedure for calculating the expected return, based on an estimate of the real yield of agricultural land in the Republic of Slovenia, whereby agricultural land is considered as own capital. We used a ten-year interest rate for government bonds, unrelated beta and the calculated rate of capitalization of agricultural land. We have found that the Western region has a lower expected return than the Eastern region. It has also been shown that there is an undetermined influence in the income method, which was shown only using the calculated expected return. The new method allows calculating the realistic market value of agricultural land in order to take into account price movements. The new method makes it possible to calculate the fair market value of agricultural land during the time of the country\u27s extreme economic situation, such as the recession

Testing MCDM model for evaluating the potential of coordinated agri-environmental approaches among farmers on two case studies from Netherlands

&lt;p&gt;In this article a test version of multi-criteria decision-making model for investigating the potential of coordinated agri-environmental measures (AEM) among farmers in EU is presented. Its analysing the parameters included in the test Decision Expert (DEX) model, the sensitivity of the test DEX model and suggesting corrections for the final DEX model. It was showed that the test DEX model lacks in sensitivity of the parameters which can be tackled with a group decision making approach-the Delfi method-for levelling the importance ratio between parameters and an analytical hierarchical process (AHP) pair wise technique weighting.&lt;/p&gt;&lt;p&gt;This publication is part of a project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 818190.&lt;/p&gt

Introducing the SWOT scorecard technique to analyse diversified AE collective schemes with a DEX model

Comparing diversified agri-environmental (AE) collective schemes in their capability to provide AE public goods faces great challenges, mostly because of their diversified nature and relatively new way to approach the provision of AE public goods. The state of the art is that there are not yet any common quantitative indicators or data to build a multi-criteria decision-making (MCDM) model to compare it with other practices and to set the strategic plan for the scheme’s improvement. Nevertheless, some qualitative common data of SWOT analyses are available, but the question remains how to simultaneously compare several SWOT analyses in an MCDM model. This study introduces a new way of transforming the qualitative results of SWOT analyses to fit in the MCDM Decision Expert (DEX) model using a special transformation technique SWOT scorecard. The SWOT scorecard evaluates the importance of qualitative results of several SWOT analyses simultaneously in a quantitative way, describing with points how supportive the environment is to each criterion in the DEX model. The SWOT scorecard keeps track of the original results from SWOT analysis and considers the diversity of AE schemes, which results in an appearance of the convergence points. This gives a key for comparing the AE collective schemes in providing AE public goods. Furthermore, it gives a solution for discussing the synergy between aspects that affect AE public goods provision for every AE scheme investigated. The technique is tested via five AE collective schemes in the DEXi program and gives deeper insight into factors that affect each scheme’s performance