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Advancement in the fields of electrification, automation, and digitalisation and emerging social trends are fuelling the transformation of road transport resulting in the introduction of various innovative mobility solutions. Yet the reaction of people to many of the new solutions is still vastly unknown. This creates an unprecedented quandary for transport planners who are requested to design future transport systems and create the related investment plans without fully validated models to base the assessment upon. As some evidence on citizens' behaviour concerning new mobility solutions starts to be progressively made available, first attempts to update the existing models begin to emerge. Nevertheless, a lot more is needed as some of the transpiring mobility solutions have not yet reached the market, making the corresponding behaviour changes imponderable. In this context, the main purpose of this paper is to provide a review on how travel behaviour changes linked to the deployment of new mobility solutions have been considered in travel demand models. The new mobility solutions studied include carsharing, dynamic ridesharing, micromobility sharing services, and personal and shared autonomous vehicles. An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. The results of the review thus point to the need for holistic demand models that carefully mimic the urban reality with everything it has to offer and account for the importance of individual traits in the decision-making processes. Such models need an in-depth understanding of the microscopic mechanisms leading to the travel behaviour shifts linked to the most innovative mobility solutions. To achieve this level of detail, mobility living labs and their real-life experiments and experience with citizens, which are flourishing in Europe, are suggested to play a crucial role in the years to come. [ABSTRACT FROM AUTHOR]

Brucellosis is a chronic infectious disease caused by brucellae or other bacteria directly invading human body. Brucellosis presents the aggregation characteristics and periodic law of infectious diseases in temporal and spatial distribution. Taking major European countries as an example, this study established the temporal and spatial distribution sequence of brucellosis, analyzed the temporal and spatial distribution characteristics of brucellosis, and quantitatively predicted its epidemic law by using different traditional or machine learning models. This paper indicates that the epidemic of brucellosis in major European countries has statistical periodic characteristics, and in the same cycle, brucellosis has the characteristics of piecewise trend. Through the comparison of the prediction results of the three models, it is found that the prediction effect of long short-term memory and convolutional long short-term memory models is better than autoregressive integrated moving average model. The first mock exam using Conv layer and data vectorizations predicted that the convolutional long short-term memory model outperformed the traditional long short-term memory model. Compared with the monthly scale, the prediction of the trend stage of brucellosis can achieve better results under the single model prediction. These findings will help understand the development trend and liquidity characteristics of brucellosis, provide corresponding scientific basis and decision support for potential risk assessment and brucellosis epidemic prevention and control, and reduce the loss of life and property. [ABSTRACT FROM AUTHOR]

Advancement in the fields of electrification, automation, and digitalisation and emerging social trends are fuelling the transformation of road transport resulting in the introduction of various innovative mobility solutions. Yet the reaction of people to many of the new solutions is still vastly unknown. This creates an unprecedented quandary for transport planners who are requested to design future transport systems and create the related investment plans without fully validated models to base the assessment upon. As some evidence on citizens' behaviour concerning new mobility solutions starts to be progressively made available, first attempts to update the existing models begin to emerge. Nevertheless, a lot more is needed as some of the transpiring mobility solutions have not yet reached the market, making the corresponding behaviour changes imponderable. In this context, the main purpose of this paper is to provide a review on how travel behaviour changes linked to the deployment of new mobility solutions have been considered in travel demand models. The new mobility solutions studied include carsharing, dynamic ridesharing, micromobility sharing services, and personal and shared autonomous vehicles. An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. The results of the review thus point to the need for holistic demand models that carefully mimic the urban reality with everything it has to offer and account for the importance of individual traits in the decision-making processes. Such models need an in-depth understanding of the microscopic mechanisms leading to the travel behaviour shifts linked to the most innovative mobility solutions. To achieve this level of detail, mobility living labs and their real-life experiments and experience with citizens, which are flourishing in Europe, are suggested to play a crucial role in the years to come. [ABSTRACT FROM AUTHOR]

This paper focuses on the design phase of I-BIM tunnelling projects using Sequential Excavation Method (SEM), in Europe, commonly referred to as the New Austrian Tunnelling Method (NATM), and addresses the problem of coupling geotechnical conditions and tunnelling Building Information Model (BIM) for the preparation of the computational model suitable for the finite element analysis method (FEM). The review of the literature led to the conclusion that an automatic merging of the tunnel model and ground model for use in the FEM software is currently not reliable due to the number of differences between various types of models as they serve contrasting needs. Consequently, modelling becomes a manual task, which is very time-consuming and error prone. In this paper, we present the development of a framework for the semiautomatic transformation of the various tunnelling models and respective ground models into the model suitable for further analysis. We conclude that the import and translation of the geometry into the FEM software are most successful and accurate when the initial I- BIM (tunnel) model is prepared at a level of detail appropriate for a computational model. The result is the I-BIM model, fit for use in the FEM software which speeds up the modelling process and reduces errors. We have shown that it is possible to prepare the geometry of a tunnel in the BIM software, transfer it, and use it in the software for geotechnical analysis. This makes the preparation of the tunnel geometry for FEM analysis much easier and faster. Due to the fast preparation of the geometry of the new model, the approach presented in this research is useful in practice. The applicability of the framework and the framework workflow are both presented through a practical case study. [ABSTRACT FROM AUTHOR]

As an alternative trip mode to the private car, carsharing mode first emerged in Europe in the 1940s. Although it possesses many merits such as convenience, affordability, and comfort, its development is far slower than the private car in recent years. Identifying the factors affecting the users' choice between carsharing and private car is becoming very important. This paper proposes an evolution game model to explore the competitive choice process between carsharing and private car under different government policies. First, an evolution game model with incomplete information is developed to analyze the travel choice of carsharing over private car. The influences of government policy are taken into consideration. Then, the evolutionary stable strategy solution of the model is derived from replicator dynamics, and a discussion about the stable condition is presented. Finally, a case study is conducted to validate the proposed model. This study provides a rationale for agencies to improve the current carsharing choice rate between carsharing and private car. [ABSTRACT FROM AUTHOR]

Introduction. eHealth applications have the potential to provide new integrated care services to patients with multimorbidity (MM), also supporting multidisciplinary care. The aim of this paper is to explore how widely eHealth tools have been currently adopted in integrated care programs for (older) people with MM in European countries, including benefits and barriers concerning their adoption, according to some basic health system characteristics. Materials and Methods. In 2014, in the framework of the ICARE4EU project, expert organizations in 24 European countries identified 101 integrated care programs. Managers of the selected programs completed an online questionnaire on several dimensions, including the use of eHealth. We analyzed data from this questionnaire, in addition to qualitative information from six innovative programs which were studied in depth through case study methodology, according to characteristics of national health systems: a national health model (financing system), overall strength of primary care (PC) (structure/service delivery process), and level of (de)centralization of health system (executive powers in a country). Results. 85 programs (out of 101) adopted at least one eHealth tool, and 42 of these targeted explicitly older people. In most cases, Electronic Health Records (EHRs) were used and some benefits emerged like improved care management and integration, although inadequate funding mechanisms represented a major barrier. The analysis by health system characteristics showed a greater adoption of eHealth applications in decentralized countries, in countries with a National Health Service (NHS) model, and in countries with a strong/medium level of PC development. Conclusions. Although in the light of some limitations, findings indicate a relation between implementation of care programs using eHealth tools and basic characteristics of health systems, with decentralization of a health system, NHS model, and strong/medium PC having a key role. However adaptations of European health systems seem necessary, in order to provide a more innovative and integrated care. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) represent a new, growing segment of transportation research. While there have been prior studies and deployments of AVs worldwide, full autonomy in bus transit has gained interest among researchers and practitioners within the last decade, which presents an opportunity to synthesize early trends. Therefore, the objective of this paper is to provide a review of the latest research on fully autonomous buses to summarize findings and identify gaps needing future research. Forty studies were reviewed in detail, and five main themes were identified, which are (1) technology deployment; (2) user acceptance; (3) safety; (4) social and economic aspects; and (5) regulations, policies, and legal issues. The results reveal that most prior studies have focused on technology development, and the area of regulation and policy would benefit from additional study. Noteworthy differences between research in Europe and the United States were also identified. In Europe, large funded projects involving real-world deployments have focused on user acceptance, security and safety, costs, and related legal issues, whereas in the United States, research has primarily concentrated on simulation modelling with limited real-world deployments. The results of this review are important for policy-makers and researchers as AV technology continues to evolve and become more widely available. [ABSTRACT FROM AUTHOR]

Offshore wind energy has become the fastest growing form of renewable energy for the last few years. And the development of offshore wind farms (OWFs) is now characterized by a boom. OWF siting is crucial in the success of wind energy projects. Therefore, this paper aims to introduce intelligent algorithms to improve the siting assessment under conditions of multisource and uncertain information. An optimization macrositing model based on Cloud-Bayesian Network (Cloud-BN) is put forward. We introduce the cloud model and adaptive Gaussian cloud transformation (A-GCT) algorithm to grade indicators and apply BN to achieve nonlinear integration and inference of multi-indicators. Combined with the fuzzy representation of the cloud model and probabilistic reasoning of BN, the proposed model can investigate the most efficient siting areas of OWFs in the North Sea of Europe. The experimental results indicate that the siting accuracy is up to 86.67% with reference to the actual OWF location. [ABSTRACT FROM AUTHOR]

Heat treatment is a method of wood modification with increasing market acceptance in Europe. The major patented European commercial heat treatment processes have trade names ThermoWood, Platowood, Retiwood, Le Bois Perdure, and Oil-Heat-Treated Wood (OHT). To what extent modification of wood affects the resistance of wood to weathering is also an important aspect for wood applications, especially where appearance is important. Unfortunately, heat-treated wood has poor resistance to weathering, and surface treatment with coatings is required for both protection and aesthetic reasons. As a substrate for coating, heat-treated wood has altered characteristics such as lower hygroscopicity and liquid water uptake and changed acidity, wettability, surface free energy, and anatomical microstructure. Various wood species, heat treatment method, treatment intensity, and treatment conditions exhibited a different extent of changes in wood properties. These altered properties could affect coating performance on heat-treated wood. The reported changes in acidity and in surface energy due to heat treatments are inconsistent with one another depending on wood species and temperature of the treatments. This paper gives an overview of the research results with regards to properties of heat-treated wood that can affect coating performance and weathering of uncoated and coated heat-treated wood. [ABSTRACT FROM AUTHOR]

With increasing concerns about urban air quality and carbon emissions, electric vehicles (EVs) have gained popularity in megacities, especially in Europe and Asia. The energy consumption of EVs has subsequently caught researchers’ attention. However, the exploration of energy consumption of EVs has largely focused on people’s revealed driving behavior and rarely touched on their self-perception of driving styles. In this paper, we developed a more human-centric approach, aiming to investigate how the energy efficiency of EVs is shaped by the driving behavior and driving style in the urban scenario from field test data and driving style questionnaires (DSQs). Field tests were carried out on a designated route for a total of 13 drivers in the city of Beijing, where vehicle operation parameters were recorded under both congested and smooth traffic conditions. DSQs were collected from a larger pool of drivers including the field test drivers to be applied to driving style factor analysis. The results of a correlation analysis demonstrate the dynamic interaction between drivers’ revealed behavior and stated driving style under different traffic conditions. We also proposed an energy consumption prediction model with the fusion of collected driving parameters and DSQ data and the result is promising. We hope that this study would draw inspiration for future research on people’s transitioning driving behavior in an electric-mobility era. [ABSTRACT FROM AUTHOR]

Six C-band weather radars located in Europe (Finland, Netherlands, and Switzerland) have been used to monitor the slowly varying solar emission, which is an oscillation with an amplitude of several decibels and a period of approximately 27 days. It is caused by the fact that the number of active regions that enhance the solar radio emission with respect to the quiet component, as seen from Earth, varies because of the Sun’s rotation about its axis. The analysis is based on solar signals contained in the polar volume data produced during the operational weather scan strategy. This paper presents hundreds of daily comparisons between radar estimates and the Sun’s reference signal, during the current active Sun period (year 2014). The Sun’s reference values are accurately measured by the Dominion Radio Astrophysical Observatory (DRAO) at S-band and converted to C-band using a standard DRAO formula. Vertical and horizontal polarization receivers are able to capture the monthly oscillation of the solar microwave signal: the standard deviation of the log-transformed ratio between radars and the DRAO reference ranges from 0.26 to 0.4 dB. A larger coefficient (and a different value for the quiet Sun component) in the standard formula improves the agreement. [ABSTRACT FROM AUTHOR]

The evidence underpinning public health policy is often of low quality, leading to inconsistencies in recommended interventions. One example is the divergence in national policies across Europe for managing contacts of invasive meningococcal disease. Aiming to develop consistent guidance at the European level, a group of experts reviewed the literature and formulated recommendations. The group defined eight priority research questions, searched the literature, and formulated recommendations using GRADE methodology. Five of the research questions are discussed in this paper. After taking into account quality of evidence, benefit, harm, value, preference, burden on patient of the intervention, and resource implications, we made four strong recommendations and five weak recommendations for intervention. Strong recommendations related not only to one question with very low quality of evidence as well as to two questions with moderate to high quality of evidence. The weak recommendations related to two questions with low and very low quality of evidence but also to one question with moderate quality of evidence. GRADE methodology ensures a transparent process and explicit recognition of additional factors that should be considered when making recommendations for policy. This approach can be usefully applied to many areas of public health policy where evidence quality is often low. [ABSTRACT FROM AUTHOR]

The use of substances to enhance human abilities is a constant and cross-cultural feature in the evolution of humanity. Although much has changed over time, the availability on the Internet, often supported by misleading marketing strategies, has made their use even more likely and risky. This paper will explore the case of Mitragyna speciosa Korth. (kratom), a tropical tree used traditionally to combat fatigue and improve work productivity among farm populations in Southeast Asia, which has recently become popular as novel psychoactive substance in Western countries. Specifically, it (i) reviews the state of the art on kratom pharmacology and identification; (ii) provides a comprehensive overview of kratom use cross-culturally; (iii) explores the subjective experiences of users; (iv) identifies potential risks and side-effects related to its consumption. Finally, it concludes that the use of kratom is not negligible, especially for self-medication, and more clinical, pharmacological, and socioanthropological studies as well as a better international collaboration are needed to tackle this marginally explored phenomenon. [ABSTRACT FROM AUTHOR]