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The global trend of credentialism as well as increased mobility in studies and work bring new requirements regarding the verification of academic qualifications. So far, traditional nostrification processes face challenges related to high process cycle times, elevated fees, and fraud incidents. In the higher education domain, blockchain-based approaches have emerged to revitalize the verification of academic qualifications, but they mostly rely on closed concepts offering their facility to a limited circle of entities. As a result, the verification of degrees is not publicly available to any third party. Moreover, in most cases, a concise process-aware approach describing the intended functionality with appropriate models is missing; this absence raises ambiguity and trust issues in the implemented application. This paper presents the design and early implementation of the VerDe (Verified Degrees) platform; a proposed blockchain-based application for registration and verification of academic qualifications. The novelty of the approach presented in this paper is the implementation of VerDe as a decentralized application utilizing Business Process Model & Notation (BPMN). This work demonstrates that usage of BPMN constructs provides an efficient method in addressing blockchain usability and complexity issues and facilitates the design and implementation of blockchain-based applications. The benefits of deploying VerDe in conjunction with BPMN are an efficient and transparent facility able to handle mobility consequences, detect fraud, and overcome administrative barriers by offering the verification capability to any third-party, and employing a custom-made token that emulates the European Credit Transfer and Accumulation System (ECTS). [ABSTRACT FROM AUTHOR]

The elaborate analysis of a business process (BP) typically informs its potential for business process redesign (BPR), but the latter is usually conducted in a non-systematic way. The purpose of this paper is the introduction of the Business Process Redesign Capacity Assessment (BP-RCA) framework that assesses the redesign capability of BP models, prior to their implementation. This study combines key redesign features introduced by domain experts, to a conceptual framework that takes into consideration an inclusive set of BPR components in three consecutive phases, towards facilitating organizations in the practice of redesign decision making. In this paper, an illustrative case study is used to present the initial phase (selection) of the framework. To assess the usability of the BP-RCA, the authors reviewed twelve established redesign initiatives from literature which proved to implicitly follow similar steps to the proposed framework. The findings indicate that the BP-RCA framework provides a systematic exploration of fundamental redesign aspects and can be used as a reliable measurement of the redesign capacity of candidate BP models. The framework also provides practitioners with the necessary methodology for increasing the BPR effectiveness, the robustness of the varying initiatives and the overall innovativeness of businesses. [ABSTRACT FROM AUTHOR]

• Holistic analysis of electric light commercial vehicles for low emission transport. • Total cost of ownership of some electric vehicle variants is already favourable now. • High penetration scenarios decrease CO 2 and other emissions by 2030 above 3%. • Electric light commercial vehicles can reduce particulate concentrations by ca. 2%. • Besides fiscal support measures, other policies needed to remove market barriers. Transport emissions need to be drastically decreased in order to put Europe on a path towards a long-term climate neutrality. Commercial transport, and especially last mile delivery is expected to grow because of the rise of e-commerce. In this frame, electric light commercial vehicles (eLCVs) can be a promising low-emission solution. Literature holistically analysing the potential of eLCVs as well as related support policies is sparse. This paper attempts to close this research gap. To this aim, the total cost of ownership (TCO) comparisons for eLCVs and benchmark vehicles are performed and support measures that target the improvement of the eLCV TCO are analysed. Various eLCV deployment scenarios until 2030 are explored and their impact on carbon dioxide (CO 2) and other pollutant emissions as well as pollutant concentrations are calculated. It is found that while in several European Union (EU) countries eLCVs are already cost competitive, because of fiscal support, some remaining market barriers need to be overcome to pave the way to mass market deployment of eLCVs. High penetration of eLCVs alone can lead to a reduction of total transport CO 2 emissions by more than 3% by 2030. For pollutant emissions, such as nitrogen oxide (NO x) and particulate matter (PM), the reduction would be equal or even higher. In the case of PM, this can translate to reductions in concentrations by nearly 2% in several urban areas by 2030. Carefully designed support policies could help to ensure that the potential of eLCVs as a low-emission alternative is fully leveraged in the EU. [ABSTRACT FROM AUTHOR]

We present efficient fully persistent B-trees in the I/O model with block size B that support range searches on t reported elements at any accessed version of size n in O (log B ⁡ n + t / B) I/Os and updates at any accessed version in O (log B ⁡ n + log 2 ⁡ B) amortized I/Os, using O (m / B) disk blocks after m updates. This improves both the query and update I/O-efficiency of the previous fully persistent B-trees of Lanka and Mays (ACM SIGMOD ICMD 1991). To achieve the result, we introduce an implementation for ephemeral B-trees that supports searches and updates in O (log B ⁡ n) I/Os, using O (n / B) blocks, where moreover every update makes a worst-case constant number of modifications to the structure. We make these B-trees fully persistent using an I/O-efficient method for full persistence, inspired by the node-splitting method of Driscoll et al. (JCSS 1989). Interesting in its own right, the method is generic enough to be applied to any external memory pointer-based data structure with maximum in-degree d i n and out-degree O (B) , where every node occupies a constant number of blocks on disk. For a user-specified parameter π = Ω (d i n) , we achieve O (π B + log 2 ⁡ π) I/O-overhead per access to a field of an ephemeral block and amortized O (π B + log 2 ⁡ π + d i n π log 2 ⁡ B) I/O-overhead and O (1 / B) block space-overhead per modification to the ephemeral structure. [ABSTRACT FROM AUTHOR]

This paper addresses the inspection and evaluation of design reuse in the conceptual schema of CMS-based Web applications in order to improve their design quality. We have utilized WebML as the design platform of our approach and we capture design reuse by detecting all the recurrent design structures within the hypertext schema of an application. We propose a methodology for automatically extracting the hypertext schema of an application which is then submitted to a pattern-based analysis in order to detect all the incorporated recurrent patterns implying design reuse. A pattern is a design structure consisting of a core specification, i.e., an invariant composition of WebML elements that characterizes the pattern and by a number of pattern variants which extend the core specification with all the valid modalities in which the pattern composition can start (starting variants) or terminate (termination variants). Finally, we apply a number of metrics on the identified patterns to evaluate the appropriateness of reuse which results in categorizing them as effective or poor design solutions. By applying the methodology on a web application, developers can inspect all the design structures that occur in its design probably due to design reuse and identify: (i) either effective reusable design solutions for implementing a certain behavior that can also be used as building blocks in future designs and can even form the basis for the discovery of design patterns in CMS domain, or (ii) ineffective recurrent design fragments causing design inconsistencies which imply the need for refactoring in order to improve the application׳s quality. [ABSTRACT FROM AUTHOR]

We present the first static and dynamic external memory data structures for variants of 2-d orthogonal range skyline reporting with worst-case logarithmic query and update I/O-complexity. The results are obtained by using persistent data structures and by extending the attrition priorities queues of Sundar (1989) [26] to also support real-time concatenation, a result of independent interest. We show that the problem is as hard as standard 2-d orthogonal range reporting in the indexability model by a lower bound on the I/O-complexity of 2-d orthogonal anti-dominance skyline reporting queries. [ABSTRACT FROM AUTHOR]

• Continuum thermodynamics provides a frame for modeling oxidative ageing in bitumen. • The examined model accounts for the dependence of oxidative ageing on composition. • Mechanisms at molecular level are linked to the continuum scale by activity models. Diffusion-reaction models derived within the frame of continuum thermodynamics of irreversible processes for reacting mixtures enjoy a number of advantages over purely phenomenological models. This paper explores the potential and challenges of this approach by means of a particular model for spurt oxidation in bitumen. Film ageing experiments are simulated considering different bitumen compositions in terms of SARA fractions. The predicted spurt completion times are contrasted with parameters characterizing the initial composition. The results demonstrate the consistency of the model. Furthermore, the trend regarding spurt completion time predicted by the model is in line with experimental results from the Strategic Highway Research Program (SHRP). In addition, the change in diffusivity due to oxidation is discussed for different compositions. The model consistently predicts a significant decrease in diffusivity due to oxidation in the absence of out-diffusion of reaction products. [ABSTRACT FROM AUTHOR]

Background: Neonatal sepsis has been associated with poor neurodevelopmental outcome, however the evidence regarding the exact mechanism of the inflammation to the developing neonatal brain are inconclusive.Aims: To investigate association between cerebral oxygenation during neonatal sepsis and neurodevelopmental outcome.Study Design: Follow-up assessment of a previously described prospective case-control study.Subjects: A cohort of late preterm (34-37 weeks' gestation) and preterm (<34 weeks' gestation) infants with sepsis and healthy controls, evaluated at 18-24 months of corrected gestational age with Bayley-III Scales for Infant and Toddler Development (BSID-III).Outcome Measures: To evaluate the association between cerebral tissue oxygenation index (cTOI) and fractional tissue oxygen extraction (FTOE), measured with near-infrared spectroscopy, during sepsis and the composite cognitive and motor index scores.Results: Thirty-one infants with blood culture confirmed neonatal sepsis and thirty-five controls were recruited. The cerebral oxygenation was significantly lower in septic neonates, compared to controls (61 ± 7 compared to 72 ± 5; p < 0.001). Infants with sepsis had significantly lower cognitive and motor index scores and higher proportion of suboptimal cognitive (16% compared to 3%, p = 0.045) and motor (16% compared to none, p = 0.008) index score. The low mean cTOI and FTOE noted in septic infants were significantly associated with worse cognitive and motor composite index scores.Conclusions: Infants with lower cerebral oxygenation during neonatal sepsis are at increased risk of worse cognitive and motor scores in the neurodevelopmental assessment. [ABSTRACT FROM AUTHOR]

It is vastly acknowledged that analyzing social networks is a very challenging research area. Take as a striking example the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. This comprises a fundamental aspect, which concerns the detection of user communities. In certain fields such as sociology and computer science where interactions and associations are often represented in the form of graphs, detecting communities is of vital importance. This paper addresses the need for an efficient and innovative methodology for community detection that will also leverage users’ behavior on emotional level. Ekman emotional scale is the key point with which the methodology analyzes user’s tweets in order to determine their emotional behavior. Consequently, the derived communities are estimated with the use of three different metrics, while the weighted version of a modularity community detection algorithm is utilized. There is substantial evidence indicating that our proposed methodology creates influential enough communities. [ABSTRACT FROM AUTHOR]

Integrated photovoltaics are an emerging technology which can extend the range of electric vehicles. However, up to now there is a lack of a consensus method that would provide consumers with an estimate of the fraction of annual driving which could be covered by solar power generated onboard in different usage scenarios and locations. To address this, we assess the energy implications of vehicle integrated photovoltaics for a commuter car and light delivery van for six climatic regions and for typical daily usage profiles over a ten-year period. The analysis captures the energy needs for driving and cabin temperature control to an unprecedented level of detail. Our results reveal that the grid power needed to drive such vehicles on identical routes can vary by more than 44% between climate regions. In the best case the solar power generated can cover up to 35% of the driving range per year. This contribution can vary by a factor of 2.5 between different climates, from 1800 to 5100 km annually, considerably mitigating the effect of ambient conditions on electric range. We propose developing consumer labels for solar electric vehicles that would consider this variation according to climatic conditions. The method described in this paper could help to frame initial discussions for such labels. We identify further requirements for research and development, standardisation, and policy needs. • Above 5000 km solar range possible for commuter car and van with integrated PV. • Ten year simulation reveals solar range differences by factor 2.5 across climates. • Over 44% difference in grid electricity needs across six climates globally. • At the moment vehicle integrated PV not financially viable. • Consumer labels for PVEV may be needed to inform about performance variations. [ABSTRACT FROM AUTHOR]

Integrated photovoltaics are an emerging technology which can extend the range of electric vehicles. However, up to now there is a lack of a consensus method that would provide consumers with an estimate of the fraction of annual driving which could be covered by solar power generated onboard in different usage scenarios and locations. To address this, we assess the energy implications of vehicle integrated photovoltaics for a commuter car and light delivery van for six climatic regions and for typical daily usage profiles over a ten-year period. The analysis captures the energy needs for driving and cabin temperature control to an unprecedented level of detail. Our results reveal that the grid power needed to drive such vehicles on identical routes can vary by more than 44% between climate regions. In the best case the solar power generated can cover up to 35% of the driving range per year. This contribution can vary by a factor of 2.5 between different climates, from 1800 to 5100 km annually, considerably mitigating the effect of ambient conditions on electric range. We propose developing consumer labels for solar electric vehicles that would consider this variation according to climatic conditions. The method described in this paper could help to frame initial discussions for such labels. We identify further requirements for research and development, standardisation, and policy needs. • Above 5000 km solar range possible for commuter car and van with integrated PV. • Ten year simulation reveals solar range differences by factor 2.5 across climates. • Over 44% difference in grid electricity needs across six climates globally. • At the moment vehicle integrated PV not financially viable. • Consumer labels for PVEV may be needed to inform about performance variations. [ABSTRACT FROM AUTHOR]

Background: Adequate nutrition is essential for optimal neurodevelopment to preterm infants. Our aim was to evaluate the impact of caloric deprivation on Bayley-III scales performance at 18-24 months of corrected age, in a cohort of preterm infants.Methods: We prospectively enrolled infants with gestational age <30 weeks and birth weight <1500 g. Apart from a whole cohort analysis, we performed a subgroup analysis between infants received inadequate calories (<85 Kcal/kg/day) during the first two weeks of age, compared to a standard nutrition group. All infants underwent a Bayley-III assessment at 18-24 months of corrected age.Results: From the 63 preterm infants analysed, 25% had caloric deprivation compared to 75% with adequate nutrition. Caloric deprived infants were of lower gestational age and birth weight, and received a lower amount of enteral feeding during the first 14 days of age. There were no differences between the two groups regarding the common neonatal co-morbidities. Caloric deprived infants had significantly lower composite index scores at 18-24 months of corrected age. Caloric deprivation, late onset sepsis, necrotizing enterocolitis, and bronchopulmonary dysplasia were significant risk factors of neurodevelopmental impairment.Conclusions: Several neonatal factors affect the neurodevelopmental outcome of preterm infants, and nutrition may pose an important role. [ABSTRACT FROM AUTHOR]