How to Assess the Impact of Blockchain on Decarbonization in Urban Logistics?

The critical role of blockchain technology has been highlighted in decarbonization and logistics transitions in the literature. Blockchain technology combined with the Smart City paradigm is identified as one of the most important digital technology disruptions and trends of sustainable urban logistics in the future. Unfortunately, none of the current strategic assessment models can evaluate the impact of blockchain technology adoption on the decarbonization pathways in urban logistics. In this study, to assess the impact of blockchain technology adoption on decarbonization goals in urban logistics, we review the literature for the current strategic assessment tools/models, sustainable urban logistics, Smart City paradigm, and blockchain technology application in logistics and decarbonization. We propose a combination of different modelling approaches including the living lab, agent-based models, and specific decision-making algorithms of blockchain technology adoptions in urban logistics and Smart City paradigms to fill the identified gaps in the literature. The main contribution of this study is to identify the research gaps in the analysis of the impact of blockchain on decarbonization in urban logistics.acceptedVersionPeer reviewe

Machine Learning and Computer Vision Techniques in Bee Monitoring Applications

Machine learning and computer vision are dynamically growing fields, which have proven to be able to solve very complex tasks. They could also be used for the monitoring of the honeybee colonies and for the inspection of their health state, which could identify potentially dangerous states before the situation is critical, or to better plan periodic bee colony inspections and therefore save significant costs. In this paper, we present an overview of the state-of-the-art computer vision and machine learning applications used for bee monitoring. We also demonstrate the potential of those methods as an example of an automated bee counter algorithm. The paper is aimed at veterinary and apidology professionals and experts, who might not be familiar with machine learning to introduce to them its possibilities, therefore each family of applications is opened by a brief theoretical introduction and motivation related to its base method. We hope that this paper will inspire other scientists to use the machine learning techniques for other applications in bee monitoring

Tracking Progress Toward EU Biodiversity Strategy Targets : EU Policy Effects in Preserving its Common Farmland Birds

Maximizing the area under biodiversity-related conservation measures is a main target of the European Union (EU) Biodiversity Strategy to 2020. We analyzed whether agrienvironmental schemes (AES) within EU common agricultural policy, special protected areas for birds (SPAs), and Annex I designation within EU Birds Directive had an effect on bird population changes using monitoring data from 39 farmland bird species from 1981 to 2012 at EU scale. Populations of resident and short-distance migrants were larger with increasing SPAs and AES coverage, while Annex I species had higher population growth rates with increasing SPAs, indicating that SPAs may contribute to the protection of mainly target species and species spending most of their life cycle in the EU. Because farmland birds are in decline and the negative relationship of agricultural intensification with their population growth rates was evident during the implementation of AES and SPAs, EU policies seem to generally attenuate the declines of farmland bird populations, but not to reverse them.Peer reviewe

High aboveground carbon stock of African tropical montane forests

Tropical forests store 40-50 per cent of terrestrial vegetation carbon(1). However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests(2). Owing to climatic and soil changes with increasing elevation(3), AGC stocks are lower in tropical montane forests compared with lowland forests(2). Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network(4) and about 70 per cent and 32 per cent higher than averages from plot networks in montane(2,5,6) and lowland(7) forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa(8). We find that the low stem density and high abundance of large trees of African lowland forests(4) is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse(9,10) and carbon-rich ecosystems. The aboveground carbon stock of a montane African forest network is comparable to that of a lowland African forest network and two-thirds higher than default values for these montane forests.Peer reviewe

ARIA 2016:Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA-disseminated and implemented in over 70 countries globally-is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA (Contre les Maladies Chroniques pour un Vieillissement Actif)-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease

ARIA 2016 : Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma and rhinitis and (3) to develop guidelines with all stakeholders that could be used globally for all countries and populations. ARIA-disseminated and implemented in over 70 countries globally-is now focusing on the implementation of emerging technologies for individualized and predictive medicine. MASK [MACVIA (Contre les Maladies Chroniques pour un Vieillissement Actif)-ARIA Sentinel NetworK] uses mobile technology to develop care pathways for the management of rhinitis and asthma by a multi-disciplinary group and by patients themselves. An app (Android and iOS) is available in 20 countries and 15 languages. It uses a visual analogue scale to assess symptom control and work productivity as well as a clinical decision support system. It is associated with an inter-operable tablet for physicians and other health care professionals. The scaling up strategy uses the recommendations of the European Innovation Partnership on Active and Healthy Ageing. The aim of the novel ARIA approach is to provide an active and healthy life to rhinitis sufferers, whatever their age, sex or socio-economic status, in order to reduce health and social inequalities incurred by the disease.Peer reviewe

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Business valuation in times of crisis

Business valuation is very important and complex process, mainly in the current global situation. To determine the company value, we will base our calculations on an analysis of the internal environment of the company, which is affected by macroeconomic and microeconomic influences. The aim of this paper is to determine the value of a selected company using FCFF in an environment of negative and unplanned interventions in the economy. The main source for determining the value of the company is data obtained from the financial statements and annual reports of the limited liability company Pepco, s.r.o. from the period of 2013-2018. The method applied to the selected company is the discounted cash flow method, which is one of the most popular and most frequently used earnings methods. In the first years before the company became known on the Czech market, the value of the FCFF was more often than not in negative numbers. This also affected the value of the business. During next years, with the stable growth of the company, the value of the company also grew. We can expect that due to the global problem of COVID-19, the value of the company will decrease in 2020, but it will not have a very significant effect on its overall value

Creating a Comprehensive Method for the Evaluation of a Company

For investment purposes, the evaluation of a company is not only a matter for a company itself, but also for shareholders and external persons. There are many methods for evaluating a company. This contribution therefore focuses on the creation of a comprehensive method for the evaluation of an industrial enterprise, one that can be used to predict potential future bankruptcies, using a dataset of financial statements of active companies and those in liquidation in the period 2015&ndash;2019. Artificial neural networks were used to process the data, specifically logistic regressions from the data processed in the Statistica and Mathematica software programmes. The results showed that the models created using the Mathematica software are not applicable in practice due to the parameters of the obtained results. In contrast, the artificial neural structures obtained using the neural network model in the Statistica software were prospective due to their performance, which is almost always above 0.8, and the logical economic interpretation of the relevant variables. All the generated and retained networks show excellent performance and few errors. However, one of the artificial structures, network no. 4 (MLP 16-16-2), produces better results than the others. Overall, accuracy is almost 81%. In the case of the classification of companies capable of surviving financial distress, accuracy is almost 90%, with that for the classification of companies at risk of going into bankruptcy at nearly 55%

Egg morphology fails to identify nests parasitized by conspecifics in common pochard: a test based on protein fingerprinting and including female relatedness

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