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Aim: To evaluate the predictive value of perinatal factors and neurodevelopmental evaluation in the emotional and behavioural outcomes in preterm‐born children at 7–9 years of age. Methods: We evaluated the Strengths and Difficulties Questionnaire (SDQ) extended score at 8.2 ± 0.2 years, among 70 preterm‐born children (32 early and 38 moderately preterms) with a previous Bayley‐III neurodevelopmental evaluation. Results: Early compared to moderately preterms had a higher total SDQ (12 compared to 8, p = 0.031), and emotional symptoms score (4 compared to 3, p = 0.022); no significant differences were recorded in abnormal/borderline‐scored children between the two groups. The total SDQ and emotional symptoms scores were significantly correlated with gestational age, birth weight, perinatal factors and the cognitive and motor Bayley‐III scores. Early prematurity was associated with the total SDQ score (beta 2.09, 95% CI 1.32, 3.87), and the score of emotional symptoms (beta 1.70, 95% CI 1.38, 2.19), after adjusting for sex, neonatal sepsis and the existence of an older sibling. Conclusion: Prematurity, birth weight, perinatal factors and the cognitive and motor Bayley‐III scores were significantly associated with the total SDQ and the emotional symptoms score, in preterm‐born children. [ABSTRACT FROM AUTHOR]

We present a succinct data structure for permutation graphs, and their superclass of circular permutation graphs, i.e., data structures using optimal space up to lower order terms. Unlike concurrent work on circle graphs (Acan et al. in Theor Comput Sci, https://doi.org/10.1016/j.tcs.2022.06.022, 2022), our data structure also supports distance and shortest-path queries, as well as adjacency and neighborhood queries, all in optimal time. We present in particular the first succinct exact distance oracle for (circular) permutation graphs. A second succinct data structure also supports degree queries in time independent of the neighborhood's size at the expense of an O (log n / log log n) -factor overhead in all running times. Furthermore, we develop a succinct data structure for the class of bipartite permutation graphs. We demonstrate how to run algorithms directly over our succinct representations for several problems on permutation graphs: Clique, Coloring, Independent Set, Hamiltonian Cycle, All-Pair Shortest Paths, and others. Finally, we initiate the study of semi-distributed graph representations; a concept that smoothly interpolates between distributed (labeling schemes) and centralized (standard data structures). We show how to turn some of our data structures into semi-distributed representations by storing only O (n) bits of additional global information, circumventing the lower bound on distance labeling schemes for permutation graphs. [ABSTRACT FROM AUTHOR]

The emergence of the Internet and web technologies has magnified the occurrence of disinformation events and the dissemination of online fake news items. Fake news is a phenomenon where fake news stories are created and propagated online. Such events occur with ever increasing frequency, they reach a wide audience, and they can have serious real-life consequences. As a result, disinformation events are raising critical public interest concerns as in many cases online news stories of fake and disturbing events have been perceived as being truthful. However, even at a conceptual level, there is not a comprehensive approach to what constitutes fake news with regard to the further classification of individual occurrences and the detection/mitigation of actions. This work identifies the emergent properties and entities involved in fake news incidents and constructs a disinformation blueprint (DCAM-DB) based on cybercrime incident architecture. To construct the DCAM-DB in an articulate manner, the authors present an overview of the properties and entities involved in fake news and disinformation events based on the relevant literature and identify the most prevalent challenges. This work aspires to enable system implementations towards the detection, classification, assessment, and mitigation of disinformation events and to provide a foundation for further quantitative and longitudinal research on detection strategies. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of a taxonomy framework for new and emerging technologies and trends in the transport sector. This framework is proposed towards the assessment and monitoring of the acceptance, impact and diffusion of technologies and trends, together with a scoring system and a front–end visualisation of the outcomes. In this context, an overview of the transport technology hype over the last years and the establishment of future transport technologies and trends is provided. Issues arising from different constraints, including technological and technical, are taken into account, also considering the transport sector’s interconnection with other sectors and potentially related bottlenecks and drawbacks. The paper outcome is a methodological framework for the creation of different taxonomies for new and emerging transport technologies and trends, achieved through the quantitative assessment of the attractiveness and competitiveness, in terms of diffusion potential, of emerging transport technologies and trends, by associating explicit indices to the various elements of the taxonomies. The proposed taxonomy, assessment and monitoring framework supports innovation management through the identification and evaluation of new and emerging technologies and trends in the field of transport at various levels, thus providing insights to the sector’s stakeholders, while backing the current transport systems’ transformation through technological advances. [ABSTRACT FROM AUTHOR]

The advancements in computer systems and networks have created a new environment for criminal acts, widely known as cybercrime. Cybercrime incidents are occurrences of particular criminal offences that pose a serious threat to the global economy, safety, and well-being of society. This paper offers a comprehensive understanding of cybercrime incidents and their corresponding offences combining a series of approaches reported in relevant literature. Initially, this paper reviews and identifies the features of cybercrime incidents, their respective elements and proposes a combinatorial incident description schema. The schema provides the opportunity to systematically combine various elements—or cybercrime characteristics. Additionally, a comprehensive list of cybercrime-related offences is put forward. The offences are ordered in a two-level classification system based on specific criteria to assist in better classification and correlation of their respective incidents. This enables a thorough understanding of the repeating and underlying criminal activities. The proposed system can serve as a common reference overtaking obstacles deriving from misconceptions for cybercrimes with cross-border activities. The proposed schema can be extended with a list of recommended actions, corresponding measures and effective policies that match with the offence type and subsequently with a particular incident. This matching will enable better monitoring, handling and moderate cybercrime incident occurrences. The ultimate objective is to incorporate the schema-based description of cybercrime elements to a complete incident management system with standard operating procedures and protocols. [ABSTRACT FROM AUTHOR]

Sentiment lexicons and word embeddings constitute well-established sources of information for sentiment analysis in online social media. Although their effectiveness has been demonstrated in state-of-the-art sentiment analysis and related tasks in the English language, such publicly available resources are much less developed and evaluated for the Greek language. In this paper, we tackle the problems arising when analyzing text in such an under-resourced language. We present and make publicly available a rich set of such resources, ranging from a manually annotated lexicon, to semi-supervised word embedding vectors and annotated datasets for different tasks. Our experiments using different algorithms and parameters on our resources show promising results over standard baselines; on average, we achieve a 24.9% relative improvement in F-score on the cross-domain sentiment analysis task when training the same algorithms with our resources, compared to training them on more traditional feature sources, such as n-grams. Importantly, while our resources were built with the primary focus on the cross-domain sentiment analysis task, they also show promising results in related tasks, such as emotion analysis and sarcasm detection. [ABSTRACT FROM AUTHOR]

Shallow cuttings are one of the most fundamental tools in range searching as many problems in the field admit efficient static data structures due to their application. We present the first efficient deterministic algorithms that, given n three-dimensional points, construct optimal-size (single and multiple) shallow cuttings for orthogonal dominance ranges. Specifically, we show how to construct a single shallow cutting in Onlogn worst-case time, using On space. We also show that the same complexity suffices to construct simultaneously a logarithmic number of shallow cuttings on the input pointset. Our algorithms are optimal in the comparison and algebraic-comparison models, and constitute an important step forwards as the first improvement over previous deterministic polynomial-time guarantees by Matoušek (Comput Geom 2(3):169-186, 1992) and Agarwal et al. (SIAM J Comput 29(3):912-953, 2000) matching the complexity of the optimal deteministic algorithm for the more general 3-d halfspace ranges by Chan and Tsakalidis (Discrete Comput Geom 56(4):866-881, 2016). Our methods yield worst-case efficient preprocessing algorithms for a series of important orthogonal range searching problems in the pointer machine and the word-RAM models, where such shallow cuttings are utilized to support queries efficiently. [ABSTRACT FROM AUTHOR]

Premature infants are a major risk group for bone metabolic disorders. The purpose of this study is to clarify certain aspects of bone metabolism in healthy preterm and fullterm neonates. Forty neonates (20 preterm and 20 fullterm) were the material of the study. For each neonate demographic data (gender, gestational week) and anthropometric data (body weight) were recorded. Blood samples were collected and biochemical markers of bone metabolism (serum ALP, Ca, P, Mg) were immediately estimated. According to the results there is a statistically significant difference in average ALP of preterm neonates compared to full term neonates. Slightly higher values of Ca, P, Mg occurred in premature neonates while there was a statistically significant difference in the weeks of gestation and body weights between the two groups. It is typical in premature neonates the decrease in levels of ALP by the weeks of gestation and the stable levels of Ca. Gestational week seems to positively affect P and Mg levels in preterm neonates. Conclusively from our study's results arises that the week of gestation and not so much the body weight influence the alterations of bone biochemical biomarkers in healthy premature newborns. It seems that very premature neonates have high levels of serum ALP in decompensation of lower levels of Mg and P from all the newborns in this study. Therefore in very premature neonates, it is recommended to estimate serum ALP, Mg and P for assessment of bone turnover. [ABSTRACT FROM AUTHOR]

We present optimal deterministic algorithms for constructing shallow cuttings in an arrangement of lines in two dimensions or planes in three dimensions. Our results improve the deterministic polynomial-time algorithm of Matoušek (Comput Geom 2(3):169-186, 1992) and the optimal but randomized algorithm of Ramos (Proceedings of the Fifteenth Annual Symposium on Computational Geometry, SoCG'99, 1999). This leads to efficient derandomization of previous algorithms for numerous well-studied problems in computational geometry, including halfspace range reporting in 2-d and 3-d, k nearest neighbors search in 2-d, $$({\le }k)$$ -levels in 3-d, order- k Voronoi diagrams in 2-d, linear programming with k violations in 2-d, dynamic convex hulls in 3-d, dynamic nearest neighbor search in 2-d, convex layers (onion peeling) in 3-d, $$\varepsilon $$ -nets for halfspace ranges in 3-d, and more. As a side product we also describe an optimal deterministic algorithm for constructing standard (non-shallow) cuttings in two dimensions, which is arguably simpler than the known optimal algorithms by Matoušek (Discrete Comput Geom 6(1):385-406, 1991) and Chazelle (Discrete Comput Geom 9(1):145-158, 1993). [ABSTRACT FROM AUTHOR]

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]

Carsharing is often included in packages of measures to encourage a more sustainable mobility. In this paper we determine the key trends and challenges in European carsharing research and innovation. We assess the status and future potential of European carsharing and identify additional research needs. The results show a steady increase in European funding to support urban carsharing projects. This is true for projects studying Information Technology development (i.e. Apps, websites, connected cars, etc). City authorities should conduct an ex-ante analysis before implementing carsharing schemes to ensure it is coordinated with public transport. Monitoring is crucial since carsharing services should contribute to reducing the overall environmental impact of the transport system. City authorities and private providers should collaborate to provide sustainable carsharing schemes that facilitate multimodal travel, lower greenhouse gas emissions, improve urban air quality and provides accessible mobility for all. [ABSTRACT FROM AUTHOR]

Current research in bone mineral metabolism reveals many aspects of osteopenia occurred in premature infants. This review examines not only the pathophysiological and molecular mechanisms of newborn osteopenia but also the risk factors and investigation. Osteopenia of premature infants has increased incidence among other diseases of prematurity. Identification of risk factors is essential for monitoring of osteopenia. Some of the risk factors include low birth weight, prematurity, long term administration of drugs such as corticosteroids, methyloxanthines, furosemide, abnormalities in vitamin D metabolism, poor maternal nutritional and mineral uptake etc. Neonatologists, pediatricians and endocrinologists should investigate premature, low birth weight infants that have high serum alkaline phosphatase and have at least one risk factor. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to present a novel approach for recruiting and ranking job applicants in online recruitment systems, with the objective to automate applicant pre-screening. An integrated, company-oriented, e-recruitment system was implemented based on the proposed scheme and its functionality was showcased and evaluated in a real-world recruitment scenario. Design/methodology/approach – The proposed system implements automated candidate ranking, based on objective criteria that can be extracted from the applicant's LinkedIn profile. What is more, candidate personality traits are automatically extracted from his/her social presence using linguistic analysis. The applicant's rank is derived from individual selection criteria using analytical hierarchy process (AHP), while their relative significance (weight) is controlled by the recruiter. Findings – The proposed e-recruitment system was deployed in a real-world recruitment scenario, and its output was validated by expert recruiters. It was found that with the exception of senior positions that required domain experience and specific qualifications, automated pre-screening performed consistently compared to human recruiters. Research limitations/implications – It was found that companies can increase the efficiency of the recruitment process if they integrate an e-recruitment system in their human resources management infrastructure that automates the candidate pre-screening process. Interviewing and background investigation of applicants can then be limited to the top candidates identified from the system. Originality/value – To the best of the authors' knowledge, this is the first e-recruitment system that supports automated extraction of candidate personality traits using linguistic analysis and ranks candidates with the AHP. [ABSTRACT FROM AUTHOR]

The current paper discusses the most recent advancements in automated vehicle (AV) certification and how existing regulations/best practices from the nuclear field helped make AVs a reality. In particular, three main pillars differentiate the newly devised certification frameworks from previous automotive regulations: the introduction of a safety management system, the adoption of in-service monitoring and reporting data logging systems, and the use of virtual testing to demonstrate the safety of the AV; a set of pillars that are also found in the nuclear practice. The argumentation is informed by relevant literature and shared experiences from the nuclear power plant and transportation fields where there are established safety practices to manage safety-critical cyber-physical systems. Although the nuclear and transportation fields might seem unrelated, strong synergies were found, including risk management approaches and operational data collection procedures, which supported the timely drafting of the new regulation for AVs. Nonetheless, some open challenges remain due to peculiar aspects of AVs that will need to be addressed in the near future. Namely, practical methodologies for the residual-risk calculation for the various Operational Design Domains (ODDs), the design of scalable monitoring techniques, and the definition of detailed procedures for the virtual testing tool qualification. [ABSTRACT FROM AUTHOR]

We examine the neuromotor outcomes of preterm infants with bronchopulmonary dysplasia. Two hundred and nineteen infants (gestational age, ≤32 weeks; birth weight, ≤1500 g) were studied. Neuromotor development was assessed using the Hammersmith Infant Neurological Examination. All potential risk factors associated with neuromotor scores (P < 0.015) were included in the generalized linear model (multiple linear regression) to determine if bronchopulmonary dysplasia had an independent relationship with neuromotor scores. Infants with severe bronchopulmonary dysplasia had lower global scores at ages 6 and 12 months. After adjustment for confounding factors, scores of infants with severe bronchopulmonary dysplasia were reduced by 13.2 units, whereas scores for those with periventricular leukomalacia were reduced by 11.1 units, at age 6 months. At age 12 months, scores for those with periventricular leukomalacia were reduced by 11.9 units. Duration of hospital stay reduced scores by 0.1 for each additional day increase in hospital. Bronchopulmonary dysplasia constitutes a major cause of poor neuromotor outcomes at age 6 months, but improvements in motor outcomes occur over time. [ABSTRACT FROM AUTHOR]

Abstract: We present a set of time-efficient approaches to index objects moving on the plane to efficiently answer range queries about their future positions. Our algorithms are based on previously described solutions as well as on the employment of efficient access methods. Finally, an experimental evaluation is included that shows the performance, scalability and efficiency of our methods. [Copyright &y& Elsevier]

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]

Immunological abnormalities have been observed in many haemophiliacs receiving clotting factor concentrates. To determine whether similar changes also occur after repeated blood transfusions we estimated T cell subsets and cutaneous delayed hypersensitivity (CDH) in 50 multitransfused children with β-thalassemia major (β-TM). All patients were also tested for anti-HTLV-III/LAV antibodies. A diminished percentage of T lymphocytes (E-rosettes, T3+), and T4+ cells and a low T4/T8 ratio was found in patients as compared to age and sex matched controls (P <0.001). Negative CDH tests to specific antigens (Multi-test) were also found in a significantly larger proportion of β-TM children (P <0.01). Antibodies against HTLV-III/LAV were negative in all patients. Decreased T4/T8 ratio in β-TM children was primarily due to a reduction of T4+ cells and was inversely correlated to the patients" age, number of units of transfused blood (P <0.05) and especially to ferritin serum levels and annual iron balance (P <0.001). These findings indicate that immunological abnormalities in β-TM patients appear to be acquired, transfusion-associated and related to iron load which depends on the appropriate chelation therapy. [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]

Electric vehicles (EVs) have been around for more than a hundred years. Nevertheless, their deployment has not been a sustainable success up until now. Many scientists, engineers and policymakers argue that EVs are a promising, maybe even indispensable option to achieve ambitious decarbonization goals, if powered by electricity from renewable energy sources. At the moment, the EVs market is gaining a lot of momentum and we may be near the point of no return for a sustained mass market deployment of electric vehicles. Many papers exist that describe future prospects of EVs. In our commentary we try to provide a bigger picture view and look at market and societal aspects. We analyze why previous generations of EVs were not successful and how current electric vehicles could become a sustainable success. We perform a semi-quantitative Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis and find that current electric vehicle designs are technologically on par with or better than conventional alternatives. Car buyers go electric when the economics make sense to them. We conclude that incentives are needed for electric vehicles until battery costs lower—as much as to allow EVs to become cheaper—from a total cost of ownership (TCO) perspective, than other alternatives. Other policy measures are needed to overcome remaining barriers, especially in supporting the setup and operation of publicly accessible recharging points to overcome range anxiety. EVs in isolation may not be the next mobility killer app. The real next mobility killer app may emerge as an autonomous shared EV in a world where the border between public and private transport will cease to exist. The findings of our commentary are relevant for scientists, policymakers and industry. [ABSTRACT FROM AUTHOR]

Plug-in electric vehicles (PEV) can be a main lever towards a decarbonised road transport system. The PEV market uptake needs to be nurtured by appropriate support measures for users, for technological advances related to the vehicle and its components, and for all relevant recharging infrastructure deployment. This paper focuses on the role of PEV recharging infrastructure for electric passenger car uptake in Europe. It examines the status of road transport electrification, relevant policies, incentives and national plans. We find that the status and plans of PEV and recharging infrastructure and the corresponding support measures vary significantly between countries. The PEV share in the various analysed countries ranged in 2017 from 0.01% to 5.49% and is estimated to reach values between 0.05% and 12.71% in 2020. The corresponding ratio of PEV per one publicly accessible recharging point ranged between 1 and 60 and is estimated to vary between 3 and 161 in 2020. Diverging plans could lead to market fragmentation in the European Union (EU) and impede the EU-wide circulation of PEVs. The appropriate level of recharging infrastructure should be determined to both support PEV deployment and to prevent sunk investments. Different country experiences vis-à-vis PEV and infrastructure support could be useful to identify best practices. [ABSTRACT FROM AUTHOR]

Business process redesign (BPR) is an organizational initiative for achieving competitive multi-faceted advantages regarding business processes, in terms of cycle time, quality, cost, customer satisfaction and other critical performance metrics. In spite of the fact that BPR tools and methodologies are increasingly being adopted, process innovation efforts have proven ineffective in delivering the expected outcome. This paper investigates the eligibility of BPMN process models towards the application of redesign methods inspired by data-flow communities. In previous work, the transformation of a business process model to a directed acyclic graph (DAG) has yielded notable optimization results for determining average performance of process executions consisting of ad-hoc processes. Still, the utilization encountered drawbacks due to a lack of input specification, complexity assessment and normalization of the BPMN model and application to more generic business process cases. This paper presents an assessment mechanism that measures the eligibility of a BPMN model and its capability to be effectively transformed to a DAG and be further subjected to data-centric workflow optimization methods. The proposed mechanism evaluates the model type, complexity metrics, normalization and optimization capability of candidate process models, while at the same time allowing users to set their desired complexity thresholds. An indicative example is used to demonstrate the assessment phases and to illustrate the usability of the proposed mechanism towards the advancement and facilitation of the optimization phase. Finally, the authors review BPMN models from both an SOA-based business process design (BPD) repository and relevant literature and assess their eligibility. [ABSTRACT FROM AUTHOR]

Dementia affects cognitive functions of adults, including memory, language, and behaviour. Standard diagnostic biomarkers such as MRI are costly, whilst neuropsychological tests suffer from sensitivity issues in detecting dementia onset. The analysis of speech and language has emerged as a promising and non-intrusive technology to diagnose and monitor dementia. Currently, most work in this direction ignores the multi-modal nature of human communication and interactive aspects of everyday conversational interaction. Moreover, most studies ignore changes in cognitive status over time due to the lack of consistent longitudinal data. Here we introduce a novel fine-grained longitudinal multi-modal corpus collected in a natural setting from healthy controls and people with dementia over two phases, each spanning 28 sessions. The corpus consists of spoken conversations, a subset of which are transcribed, as well as typed and written thoughts and associated extra-linguistic information such as pen strokes and keystrokes. We present the data collection process and describe the corpus in detail. Furthermore, we establish baselines for capturing longitudinal changes in language across different modalities for two cohorts, healthy controls and people with dementia, outlining future research directions enabled by the corpus. [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 report describes a newborn girl presenting with some of the common features of DiGeorge syndrome/velocardiofacial syndrome (DGS/VCFS), including hypocalcemia, atrial septal defect, and aortic stenosis. Several genetic tests were carried out to determine the origin of the clinical phenotype. MLPA was initially performed followed by aCGH, cytogenetic analysis, and FISH. Cytogenetic analysis of the proband's parents was also done. MLPA revealed a deletion in 22q11.1q11.2 spanning from the cat eye syndrome region to the most commonly deleted region in DGS/VCFS patients. The size of the deletion as defined by aCGH was 3.2 Mb. The karyotype of the proband was 45,XX,der(1)t(1;22)(p36.3;q11.2)dn,-22, the karyotypes of the parents were normal. FISH analysis showed that the 22q11 deletion occurred in the der(1). No loss or gain of chromosomal material was evident for chromosome 1, as confirmed by MLPA, aCGH, and FISH. Unbalanced translocations resulting in DGS are relatively rare, with limited reports in the literature. To our knowledge, this is the second case involving chromosome 1 and the first one with breakpoints in 1p36 and 22q11.2. This case also emphasizes the importance of combining diagnostic methods to better understand a given genetic abnormality. [ABSTRACT FROM AUTHOR]

A letter to the editor and a reply are presented in response to the article "Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery," by Roberto Romero and colleagues in the 2010 issue.

Edge-fuzzy graphs constitute an essential modeling paradigm across a broad spectrum of domains ranging from artificial intelligence to computational neuroscience and social network analysis. Under this model, fundamental graph properties such as edge length and graph diameter become stochastic and as such they are consequently expressed in probabilistic terms. Thus, algorithms for fuzzy graph analysis must rely on non-deterministic design principles. One such principle is Random Walker, which is based on a virtual entity and selects either edges or, like in this case, vertices of a fuzzy graph to visit. This allows the estimation of global graph properties through a long sequence of local decisions, making it a viable strategy candidate for graph processing software relying on native graph databases such as Neo4j. As a concrete example, Chebyshev Walktrap, a heuristic fuzzy community discovery algorithm relying on second order statistics and on the teleportation of the Random Walker, is proposed and its performance, expressed in terms of community coherence and number of vertex visits, is compared to the previously proposed algorithms of Markov Walktrap, Fuzzy Walktrap, and Fuzzy Newman-Girvan. In order to facilitate this comparison, a metric based on the asymmetric metrics of Tversky index and Kullback-Leibler divergence is used. [ABSTRACT FROM AUTHOR]

Objective Chorioamnionitis and fetal inflammatory response syndrome (FIRS) are significant risk factors for early onset sepsis (EOS). Recently, the use “Intrauterine Inflammation or Infection or both” or triple I has been proposed, classifying cases into an isolated maternal fever, suspected triple I, or confirmed chorioamnionitis. Evidence suggests that the association between suspected chorioamnionitis and confirmed histological chorioamnionitis (HCA) is not consistent, as well as the impact of HCA on the development of EOS. We aimed to evaluate the association between suspected chorioamnionitis and HCA, the impact of HCA on EOS, and the effect of antepartum antibiotic prophylaxis on EOS. Methods We retrospectively reviewed the medical records of all infants admitted to our institution, between 2017 and 2018, with a diagnosis of chorioamnionitis. We recorded the clinical evidence of chorioamnionitis, the histologic report of the placenta, the maternal and neonatal data, the neonatal inflammatory markers including C-reactive protein (CRP), and the incidence of EOS. The impact of antepartum antibiotic prophylaxis on the infants’ CRP and EOS was calculated, and the logistic regression model was performed to estimate the association of confirmed HCA with EOS, while controlling for FIRS stage, gestation age, birth weight, maternal fever, foul-smelling amniotic fluid, and prolonged rupture of membranes. Results During the study period, a total of 266 infants were identified; 81 (30%) infants had a confirmed HCA (HCA-present cases), and 185 (70%) infants were diagnosed with suspected triple I (HCA-absent cases). Antepartum antibiotics had been commenced in a significantly higher proportion in HCA-present cases (46%) in comparison to 14% of HCA-absent cases (p < .001). HCA-present infants were of significantly lower gestation (31.6 ± 4weeks versus 33.3 ± 4weeks, p = .004), and birth weight (1826 ± 840 g versus 2092 ± 849 g, p = .019), they had a significantly higher rate of clinical symptoms (31% versus 6%, p < .001), and a higher CRP at birth and 24 h (1.4 ± 1.5 mg/dL versus 0.3 ± 0.2 mg/dL, p < .001, and 2.1 ± 2.3 mg/dL versus 0.4 ± 0.6 mg/dL, p < .001, respectively). All HCA-present cases had evidence of FIRS; 43% were stage I, 25% stage II, and 32% were FIRS stage III. A significantly higher proportion of HCA-present infants were diagnosed with EOS (46% as compared to 6%, p < .001). The antepartum antibiotic administration was related to a significantly lower CRP at birth and 24 h only in HCA-present cases, albeit not with any reduction ιn EOS incidence. HCA was significantly associated with EOS (RR 3.18, 95% CI 2.81–5.18, p < .001). After adjusting for perinatal factors, the presence of HCA (OR 7.89, 95% CI 1.19-23.34, p = .032) and an advanced FIRS stage (OR 10.35, 95% CI 4.23–25.32, p < .001) were significantly associated with EOS. Conclusions Amongst infants with suspected chorioamnionitis, the diagnosis is partially supported by histological confirmation, and that is more prominent in pregnancies of a lower gestation. The presence of HCA and an advanced FIRS stage predispose to an increased risk of EOS after adjusting for other perinatal and neonatal factors. The antepartum prophylaxis against intra-amniotic infection was related to a significantly lower CRP in HCA-present cases. [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]

To evaluate the consistency of the Hammersmith Infant Neurological Examination scores of very-low-birth-weight infants at 6 and 12 months of age and its correlation to cranial ultrasonography findings, we designed a prospective study between January 2005 and January 2008, in the tertiary Neonatal Unit of Aristotle University of Thessaloniki, Greece. All infants enrolled had a cranial ultrasonography performed at term. Preterm infants born at <32 weeks gestation with a birth weight <1500 g were eligible for the study. One hundred seventy-four infants were finally enrolled; out of those, 46 (26%) had an optimal score at 6 and 76 (44%) at 12 months of age. Mean global scores were 61 and 69 at 6 and 12 months, respectively. The Hammersmith Infant Neurological Examination score significantly increased between 6 and 12 months, equally in all ultrasonography groups. The presence of cystic periventricular leukomalacia was associated to lower scores and neurologic impairment. [ABSTRACT FROM PUBLISHER]

Background: Stressful events during infancy may predispose to the development of functional gastrointestinal disorders (FGIDs) in childhood. Aims: To evaluate the association of necrotizing enterocolitis (NEC) with childhood FGIDs. Methods: We conducted a study, comparing 29 children of eight to ten years with a history of NEC with 58 children with no history of NEC. Subjects were assessed for FGIDs, based on Rome‐III criteria. Results: Among 29 subjects with NEC, 17 had surgical and 12 conservative NEC. Subjects with surgically, or conservatively managed NEC developed FGIDs at a significantly higher proportion, as compared to children with no history of NEC, later in childhood (41%, 33%, and 13% respectively, p = 0.033). Functional constipation was the most frequently identified disorder (35%, 33%, and 7% respectively). A significant association was detected between FGIDs and the history of perinatal stress (p = 0.049), NEC (p = 0.011), and the surgical management of NEC (p = 0.015). Conclusions: Our study suggests that there is a potential association between NEC and FGIDs later in childhood with functional constipation being the most frequently identified disorder. [ABSTRACT FROM AUTHOR]

Summary: DEsubs is a network-based systems biology R package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customized framework with a broad range of operation modes at all stages of the subpathway analysis, enabling so a case-specific approach. The operation modes include pathway network construction and processing, subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render DEsubs a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level drug targets and biomarkers for complex diseases. [ABSTRACT FROM AUTHOR]

Development of vehicles that are powered by photovoltaics (PV) is desirable, and is crucial for reduction in CO2 emissions from the transport sector to realize a decarbonized society. Our investigations show that the majority of the passenger cars that cruise only with solar energy can be realized by installing a high-efficiency PV module. Although the Toyota Prius demonstration car, which is equipped with a 860 W rated-output power PV module, has shown a 36.6 km dâˆ'1 PV-powered driving range at solar irradiance of 6.2 kWh mâˆ'2 dâˆ'1, practical driving ranges of PV-powered vehicles are shown to be shorter than the estimated values due to some losses of solar cell modules, such as temperature rise under sunny conditions. In this paper, we conduct a systematic analysis of the effects of these losses on the PV-powered driving range in order to obtain guidelines for the development of highly efficient solar cell modules for vehicle integrated applications. The analytical results show that the IIIâ€"V compound solar cell modules have more suitable properties compared to other cells because of their higher potential conversion efficiencies of 37% with a smaller temperature coefficient of âˆ'0.19% °Câˆ'1 compared to âˆ'0.29% °Câˆ'1 for Si back contact solar cell modules and âˆ'0.26% °Câˆ'1 for Si heterojunction solar cell modules. Our theoretical calculations that take these losses into account suggest that installing the IIIâ€"V-based triple-junction solar cell modules provides a potential PV-powered driving range of 30 km dâˆ'1 on average, and more than 50 km dâˆ'1 on a sunny day under the irradiation conditions in Japan. [ABSTRACT FROM AUTHOR]

Abstract: In this paper a technique for a quantum computer architecture is demonstrated using the discrete energy levels of an impurity doped semiconductor to represent the quantum computational basis. External signals are used to perform quantum logical gates and recombination mechanisms are suitably modelled in order to demonstrate quantum information processing. The physical mechanism which performs the logical equivalent of the Controlled-NOT (CNOT) gate is presented along with a mechanism obtaining an output with a similar statistical behavior with the Hadamard Gate. The computational basis was checked for errors when used for solving a quantum algorithm. Hence, using suitable simulation on a silicon structure, the computational errors that degrade the quantum information processing are considered and computed. These error results are found to be fairly small. [Copyright &y& Elsevier]

The broad acceptance of mobile technology has undoubtedly created new opportunities in communication. The proposed environment attempts to enhance the information flow among the members of a department and, furthermore, to provide a test-bed mobile Web application for students undertaking Internet technologies courses. The key ideas are to support the educational process to provide auxiliary access to educational information sources, such as announcements, course schedules, grades, and user directory details. As a second system integration step, additional mobile Web services were introduced, such as application forms of the department's administration office, project assignment, and discussion groups. Technological evaluation and students' feedback indicate that the proposed solution is both efficient in communication perspective and effective for student involvement in the mobile Web initiative. Future steps include multimedia messages (MMS) integration and third-generation (3G)-based information delivery. [ABSTRACT FROM AUTHOR]

Computational methods on molecular sequence data are at the heart of computational molecular biology. Identification of known or unknown DNA and RNA motifs or regions involved in various biological processes such as initiation of transcription, gene expression and translation, or the discovery of various types of repeats are some of the applications of major concern. An accurate identification and localization of such elements will allow biologists to perform deeper studies of the structure, function and evolution of genomes. This requires the development of faster and more complex mathematical models and computer algorithms. In this work we discuss current techniques to cope with string problems in molecular sequence data. We focus on Weighted Sequences and Sequences with "don't care characters", explaining the open problems and their relevance to biological applications. [ABSTRACT FROM AUTHOR]

Abstract: The classic two-stepped approach of the Apriori algorithm and its descendants, which consisted of finding all large itemsets and then using these itemsets to generate all association rules has worked well for certain categories of data. Nevertheless for many other data types this approach shows highly degraded performance and proves rather inefficient. We argue that we need to search all the search space of candidate itemsets but rather let the database unveil its secrets as the customers use it. We propose a system that does not merely scan all possible combinations of the itemsets, but rather acts like a search engine specifically implemented for making recommendations to the customers using techniques borrowed from Information Retrieval. [Copyright &y& Elsevier]

Web-based learning environments give e-learning new potential by enabling personalized, interactive, just-in-time, current, and user-centric learning tools. In this work, we present the architecture, design, and implementation of a Web-based learning environment that can be used to build and support online learning communities. New material can be uploaded and positioned through a simple Web interface that also allows for account management, definition of topic associations (that lead to the production of recommendations for further reading), and a set of additional explicit and implicit adaptations produced dynamically for personalizing the overall learning experience. Online learning communities may greatly benefit from incorporating adaptive features that take advantage of the knowledge and experiences of community members and use it to better serve each individual depending on personal preferences, goals, and needs, as well as the history of community activity. [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]

Maternal diet before and during pregnancy plays an important role for the developing fetus. Any eating disorder in this period can cause transient or/and permanent negative effects on the mother and her offspring. [ABSTRACT FROM AUTHOR]

Objective: To examine cerebral oxygenation and perfusion in small for gestational age (SGA) compared with appropriate for gestational age (AGA) neonates during the first postnatal week, and to investigate any association with neurodevelopmental outcomes at 24–36 months of age. Methods: A prospective matched case-control study was conducted evaluating cerebral oxygenation and perfusion, using near-infrared spectroscopy (NIRS), between SGA and AGA neonates, during the first postnatal week. A neurodevelopmental assessment with Bayley-III was performed at 24–36 months of age. Results: Forty-eight SGA and 48 AGA neonates of similar gestation (32.8 ± 2.1 vs. 32.5 ± 1.9) were enrolled. On the first postnatal day, the cerebral oxygenation was equal between SGA and AGA neonates (71 ± 7% vs. 72 ± 8%); however, in the subgroup analysis, males had higher oxygenation compared to female SGA neonates (73 ± 7% vs. 69 ± 7%, P = 0.04). Cerebral perfusion was significantly higher in SGA neonates on the first postnatal day (1.4 ± 0.6 vs. 1.1 ± 0.5, P = 0.04), but this difference was diminished on subsequent measurements. There were no significant differences between the SGA and AGA infants regarding the composite cognitive, communication and motor index scores. The length of mechanical ventilation and late-onset sepsis were significant risk factors affecting the cognitive and communication composite index scores, respectively. Conclusion: Cerebral oxygenation was equal between SGA and AGA neonates, while cerebral perfusion was transiently increased in SGA neonates during the first postnatal day. There was no significant association of cerebral oxygenation and perfusion with neurodevelopmental outcomes. [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]

This study is an attempt to describe a conventional breeding program on Greek oregano (Origanum vulgare ssp. hirtum). First of all, a descriptor list including the most significant morphological traits was developed for the starting genetic material. The program aimed to select the elite selfplants obtained from the initial population originated from Samothraki Island, in purpose to generate the ideotype of a new cultivar, characterized by desirable agronomical traits and qualitative properties. Therefore, a pedigree intraselection method, based on widely spaced single-plant performance through honeycomb arrangement, was applied. The existing genetic/phenotypic variability of plants and families produced after selection was evaluated for plant’s growth and biomass density, type of stems and inflorescences and their components of yield potential. In addition, the effect of the mode of pollination on plants’ performance from two types of families obtained from self (SP) and open pollination (OP) was assessed. The evaluation for the components of yield potential, the composition of essential oil and carvacrol content, was detected in selected self plants, revealing genotypes with high yield potential. The target of this breeding program was the selection for high essential oil and carvacrol content and stabilization of valuable herbage components. The main selection criteria; high carvacrol and essential oil content, dry weight of leaves and flowers, ratio of leaves and flowers per stem, were subjected to statistical analysis using analytic hierarchy process, and plants were ranking according to their performance. The end-scope of this research was to recombine or even improve the starting population of local population of Greek oregano, according to mean essential oil content and carvacrol, biomass production and uniformity in desirable yield components using efficient breeding and statistical tools of selection. [ABSTRACT FROM AUTHOR]

Objective Neonates with sepsis have increased risk of cerebral injury. Our aim was to evaluate cerebral oxygenation in septic neonates using near-infrared spectroscopy. Study Design A prospective study was designed enrolling neonates with sepsis, as defined by the International Consensus Conference of Pediatric Sepsis criteria and matched controls. Three cerebral half-hourly measurements were performed during the first, third, and seventh day of the episode and the values of tissue oxygenation index (TOI) and fractional tissue oxygen extraction (FTOE) were compared between the two groups. Result The study population consisted of 50 septic and 44 control neonates with similar characteristics. No differences on TOI and FTOE were recorded in the first and third day. However, on the seventh day, septic neonates had significantly decreased oxygenation (62.7 ± 7 vs. 71.4 ± 4.4%, p < 0.001) and increased oxygen extraction (0.35 ± 0.07 vs. 0.27 ± 0.05, p < 0.001), irrespectively of the severity of the infection. Conclusion Although septic neonates have normal cerebral oxygenation in the first and third day of the sepsis, they present decreased cerebral oxygenation in the seventh day independently of the infection severity. [ABSTRACT FROM AUTHOR]

Sentiment Analysis on Twitter Data is indeed a challenging problem due to the nature, diversity and volume of the data. People tend to express their feelings freely, which makes Twitter an ideal source for accumulating a vast amount of opinions towards a wide spectrum of topics. This amount of information offers huge potential and can be harnessed to receive the sentiment tendency towards these topics. However, since no one can invest an infinite amount of time to read through these tweets, an automated decision making approach is necessary. Nevertheless, most existing solutions are limited in centralized environments only. Thus, they can only process at most a few thousand tweets. Such a sample is not representative in order to define the sentiment polarity towards a topic due to the massive number of tweets published daily. In this work, we develop two systems: the first in the MapReduce and the second in the Apache Spark framework for programming with Big Data. The algorithm exploits all hashtags and emoticons inside a tweet, as sentiment labels, and proceeds to a classification method of diverse sentiment types in a parallel and distributed manner. Moreover, the sentiment analysis tool is based on Machine Learning methodologies alongside Natural Language Processing techniques and utilizes Apache Spark's Machine learning library, MLlib. In order to address the nature of Big Data, we introduce some pre-processing steps for achieving better results in Sentiment Analysis as well as Bloom filters to compact the storage size of intermediate data and boost the performance of our algorithm. Finally, the proposed system was trained and validated with real data crawled by Twitter, and, through an extensive experimental evaluation, we prove that our solution is efficient, robust and scalable while confirming the quality of our sentiment identification. [ABSTRACT FROM AUTHOR]