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Introduction Many health providers and communicators who are concerned that patients will not understand numbers instead use verbal probabilities (e.g., terms such as “rare” or “common”) to convey the gist of a health message. Objective To assess patient interpretation of and preferences for verbal probability information in health contexts. Methods We conducted a systematic review of literature published through September 2020. Original studies conducted in English with samples representative of lay populations were included if they assessed health-related information and elicited either (a) numerical estimates of verbal probability terms or (b) preferences for verbal vs. quantitative risk information. Results We identified 33 original studies that referenced 145 verbal probability terms, 45 of which were included in at least two studies and 19 in three or more. Numerical interpretations of each verbal term were extremely variable. For example, average interpretations of the term “rare” ranged from 7 to 21%, and for “common,” the range was 34 to 71%. In a subset of 9 studies, lay estimates of verbal probability terms were far higher than the standard interpretations established by the European Commission for drug labels. In 10 of 12 samples where preferences were elicited, most participants preferred numerical information, alone or in combination with verbal labels. Conclusion Numerical interpretation of verbal probabilities is extremely variable and does not correspond well to the numerical probabilities established by expert panels. Most patients appear to prefer quantitative risk information, alone or in combination with verbal labels. Health professionals should be aware that avoiding numeric information to describe risks may not match patient preferences, and that patients interpret verbal risk terms in a highly variable way.

In recent months the COVID-19 (also known as SARS-CoV-2 and Coronavirus) pandemic has spread throughout the world. In parallel, extensive scholarly research regarding various aspects of the pandemic has been published. In this work, we analyse the changes in biomedical publishing patterns due to the pandemic. We study the changes in the volume of publications in both peer reviewed journals and preprint servers, average time to acceptance of papers submitted to biomedical journals, international (co-)authorship of these papers (expressed by diversity and volume), and the possible association between journal metrics and said changes. We study these possible changes using two approaches: a short-term analysis through which changes during the first six months of the outbreak are examined for both COVID-19 related papers and non-COVID-19 related papers; and a longitudinal approach through which changes are examined in comparison to the previous four years. Our results show that the pandemic has so far had a tremendous effect on all examined accounts of scholarly publications: A sharp increase in publication volume has been witnessed and it can be almost entirely attributed to the pandemic; a significantly faster mean time to acceptance for COVID-19 papers is apparent, and it has (partially) come at the expense of non-COVID-19 papers; and a significant reduction in international collaboration for COVID-19 papers has also been identified. As the pandemic continues to spread, these changes may cause a slow down in research in non-COVID-19 biomedical fields and bring about a lower rate of international collaboration., 26 pages, 9 figures, 11 tables

Positive psychology interventions (PPIs) improve students’ well-being in laboratory settings. Best possible self (BPS) is one of the most widely used PPIs shown in the laboratory to effectively improve participants’ well-being in both the short- and long-term, but limited research has been conducted in real-world contexts. This study applied BPS in an undergraduate classroom to examine its long-term effects. Students enrolled in an undergraduate education course were assigned to treatment and control groups. Three writing activities and four tests were integrated into the course as assignments in both groups. Data were analyzed using a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2\times 3$$\end{document}2×3 (group and time) mixed ANOVA. The results indicate that BPS did not significantly improve the participants’ well-being over time compared with the control group. In fact, the control group performed better than treatment at one month after the intervention. This aligns with recent findings of well-being during COVID-19. Potential implications and areas for future research are discussed.

Whereas much research has largely investigated the safe haven, diversifier and hedge proprieties of cryptocurrency, very few papers have analyzed the hedging issue of cryptocurrency with other assets. As such, this paper attempts to investigate the possibility if Bitcoin can be hedged by selected fiat currencies (EUR, JPY and GBP) as Bitcoin prices have experienced high and persistent volatility. To do so, we compute optimal hedge ratios between Bitcoin and fiat currencies over the period 02/02/2012–30/11/2017 based on the VAR-DCC-GARCH model, VAR-ADCC-GARCH model and VAR-component GARCH-DCC model. A rolling window analysis is employed to establish out-of-sample one-step-ahead forecasts of dynamic conditional correlations between different assets. This leads to establish time-varying hedge ratios and thus dynamic cross-hedging Bitcoin/fiat currency markets. The empirical results clearly show the time-varying correlations between Bitcoin and fiat currencies under different specifications, implying a dynamic behavior of the relationship between such assets. For all the proposed models, such dynamic correlations are rather characterized by trending downward over the period under study. The results also display time-varying hedge ratios which lead to an ongoing regular demand for rebalancing the hedged positions under different specifications. As a matter of fact, using various models which take into account different aspects of volatility and correlation structures allows to better implement dynamic hedging strategies.

A company should measure an intangible asset at its fair value at the time of acquisition. The costs of internally developing, maintaining, or restoring intangible assets generally should be expensed as incurred (with some exceptions). Intangible assets other than goodwill may or may not be amortized depending on their useful lives to the entity: Assets with finite lives are amortized; assets with indefinite lives are not. Goodwill is not amortized.

In-situ observations from radiosondes, surface land and marine stations, and aircraft play an important role in data assimilation for global numerical weather prediction, even in the current era when observations from satellites provide approximately 90% of the observations assimilated. In addition, these observations are widely used in verification for both model forecasts and satellite datasets, and radiosonde data serve as critical anchor observations in variational bias correction schemes used primarily for satellite radiances. This chapter examines the characteristics of these three types of in-situ observations (along with related subtypes such as dropsondes and Mode-S aircraft observations) in terms of measurement systems, errors and biases, data formats and their impact on precision, as well as how these data are processed for use in data assimilation including quality control considerations. The underappreciated need for accurate metadata, including platform characteristics and station location, is also presented. Recent changes in in-situ observations are discussed, with the decrease in aircraft observations associated with COVID-19 demonstrating how these data complement each other and compensate for temporary or even longer term deficiencies.

This chapter introduces the role of intertemporal expectations into our analysis. Effects of current and expected inflation on long-term interest rates will be the focus of the first half of this chapter. This will be followed by a discussion of the ultimate macroeconomic meltdown—hyperinflation.

Data assimilation schemes blend observational data, with limited coverage, with a short term forecast to produce an analysis, which is meant to be the best estimate of the current state of the atmosphere. Appropriately specifying observation error statistics is necessary to obtain an optimal analysis. Observation error can originate from instrument error as well as the error of representation. While representation error is most commonly associated with unresolved scales and processes, this term is often considered to include contributions from pre-processing or quality control and errors associated with the observation operator. With a focus on practical operational implementation, this chapter aims to define the components of observation error, discusses their sources and characteristics, and provides an overview of current methods for estimating observation error statistics. We highlight the implicit assumptions of these methods, as well as their shortcomings. We will detail current operational practice for diagnosing observation error and accounting for correlated observation error. Finally, we provide a practical methodology for using these diagnostics, as well as the associated innovation-based observation impact, to optimize the assimilation of meteor radar observations in the upper atmosphere.

The mobile communications’ standard that succeeded the UMTS system became known as Long-Term Evolution (LTE). The Long-Term Evolution–Advanced, or LTE-Advanced (LTE-A) version, was developed by the Third-Generation Partnership Project (3GPP). The LTE-A exceeds the International Telecommunication Union (ITU) requirements for the fourth-generation radiocommunication (4G) standard, known as IMT-Advanced.

We contribute to the assessment of the employment implications of the COVID crisis by classifying economic sectors according to the confinement decrees of three European countries (Germany, Spain and Italy). The analysis of these decrees can be used to make a first assessment of the implications of the COVID crisis on labour markets, and also to speculate on mid and long-term developments, since the most and least affected sectors are probably going to continue to operate differently until a vaccine or other long-term solution is found. Using an ad-hoc extraction of EU-LFS data, we apply this classification to the analysis of employment in Germany, Italy and Spain but also UK, Poland and Sweden, in order to cover the whole spectrum of institutional labour market settings within Europe. Our results, in line with recent literature, show that the employment impact is asymmetric within and between countries. In particular, the countries that are being hardest hit by the pandemic itself (Spain and Italy, and also the UK) are the countries more likely to suffer the worst employment implications of the confinement, because of their productive specialisation and labour market institutions. Indeed, these were also the labour markets that were more vulnerable before the crisis: characterised by high unemployment and precarious work (especially temporary contracts).

The recent 'outburst' of COVID-19 spurred efforts to model and forecast its diffusion patterns, either in terms of infections, people in need of medical assistance (ICU occupation) or casualties. Forecasting patterns and their implied end states remains cumbersome when few (stochastic) data points are available during the early stage of diffusion processes. Extrapolations based on compounded growth rates do not account for inflection points nor end-states. In order to remedy this situation, we advance a set of heuristics which combine forecasting and scenario thinking. Inspired by scenario thinking we allow for a broad range of end states (and their implied growth dynamics, parameters) which are consecutively being assessed in terms of how well they coincide with actual observations. When applying this approach to the diffusion of COVID-19, it becomes clear that combining potential end states with unfolding trajectories provides a better-informed decision space as short term predictions are accurate, while a portfolio of different end states informs the long view. The creation of such a decision space requires temporal distance. Only to the extent that one refrains from incorporating more recent data, more plausible end states become visible. Such dynamic approach also allows one to assess the potential effects of mitigating measures. As such, our contribution implies a plea for dynamically blending forecasting algorithms and scenario-oriented thinking, rather than conceiving them as substitutes or complements. ispartof: SCIENTOMETRICS vol:124 issue:3 pages:2703-2715 ispartof: location:Switzerland status: published

The chapter examines the links between long-term changes in social-ecological systems and the development of property rights by studying self-governance, common-pool resources (CPRs), and property rights in a Sami context. The main conclusion is that Sami by and large created their own rules for how natural resources should be harvested and consumed, as well as for how resources should be monitored and rules should be enforced. Well-defined property rights were a prerequisite for people to engage in, and gain profits from, land-use regimes. We conclude that user’s access to natural resources, and rights to use them, determined the households’ economic performance and development. Features of two frameworks are introduced. They give a background to our theoretical thinking and provide a means of organizing the inquiry.

The Swiss government, through its Energy Strategy 2050, is engaged on a path to transition Switzerland to become a carbon-neutral country by the year 2050. In this chapter, we look at the impact that the electorate can have on this transition and on the Swiss electricity market. This is done using hybrid agent-based modelling. We model the Swiss electricity market and we add to this a model of the policy-making process. This allows us to study which policy instruments are more likely to be implemented depending on the Swiss electricity market progression and on the policy actors’ interests. The results have shown that the electorate has a limited impact on the policy chosen and on the electricity market. Overall, an environmentally conscious electorate leads policy actors to select the carbon tax as a policy more often. This, however, has the adverse effect to increase the electricity price and increase import dependency in winter. In high demand growth scenarios, the carbon tax policy is not sufficient to stem the construction of gas turbine power plants. We also show that because the electricity model does not consider an extended demand response option or technology advancement, the knowledge gained from this model is limited. This drives the behaviour of the model into scenarios which are unlikely to happen, such as a large increase of the gas turbine power plants. Overall, we conclude that, in their current form, even with an environmentally conscious electorate, the electricity market conditions do not allow Switzerland to reach its emissions targets.

The purpose of this concise and brief paper, which is deliberately slim in size and bibliography, is contained. First of all, it aims to show the existence of several forms of compliance characterized by different geneses and purposes and, therefore, to highlight the ambiguity of a term that is not always used in a univocal sense, due also to its links with other issues that are currently highly debated. Moreover, it argues that despite the different forms and meanings that compliance can assume, it is possible to identify a common unifying thread. On the basis of a positive assessment of the development of compliance, especially in relation to the ever-increasing importance of legal and reputational risks associated with economic activity, the paper ends with a brief overview of the legal instruments available to support this trend or, more properly, to ensure that the proclaimed importance of compliance is accompanied by effective implementation suitable to positively affect business management.

In this volume, the concept of climate-smart forestry (CSF) has been introduced as adaptive forest management and governance to address climate change, fostering resilience and sustainable ecosystem service provision. Adaptive forest management and governance are seen as vital ways to mitigate the present and future impact of climate change on forest. Following this trajectory, we determine the ecosystem services approach as a potential adaptive tool to contribute to CSF. Ecosystem services as public or common goods face the traditional social dilemma of individual versus collective interests, which often generate conflicts, overuse, and resource depletion. This chapter focuses on the ecosystem servicegovernance approach, especially on incentive tools for behavioral change to CSF in the long term, which is a basic precondition for the sustainability of ecosystem integrity and functions, as well as ensuring the continuous delivery of ecosystem goods and services, as per the CSF definition. Payments for ecosystem services (PES) are seen as innovative economic instruments when adding a social dimension by involving local communities and their values to ensure the long-term resilience and adaptation of forest ecosystems to climate change. We argue that tackling climate changeadaptation requires the behavioral change of ecosystem service providers to a collaborative and integrated PES approach, as also emphasized by the Sustainable Development Goals (SDGs) of the Agenda 2030.

The article explores the latest legal acts in the field of legal relations regulation using digital innovations. The concept of the term “digital innovation” is analyzed, it is emphasized that its scope is practically unlimited. Attention is drawn to the objective need and statutory possibility of introducing a pilot legal regime and applying special regulation for a certain group of persons and in a certain territory for a particular period of time, due to the absence of general binding rules, requirements and standards. The author relates the concept and basic rules of establishing an experimental legal regime and a legal experiment, and identifies different goals, grounds and procedure for establishing.

The purpose of this work is to theoretically substantiate and empirically prove the need to introduce a digital educational environment into the educational process. The theoretical and methodological basis of the study is given, on the basis of which the research sample is built. Taking into account all the interrelated main blocks of activity the general methodology is considered for a higher educational institution. To obtain the empirical base of the study, we introduce samples of respondents who are offered a research methodology in the form of selected questionnaires, the validity of which is empirically proven. Taking into account the purpose of the study all questionnaires are selected to identify the usefulness and necessity of introducing a digital educational environment into the educational process. Using the methods of mathematical statistics, empirical results are processed and a new term “the phenomenon of problematic Internet use” is introduced. Correlation analysis allows you to identify differences between samples and formulate patterns of their dependencies. Based on the conducted research and subsequent analysis, the authors prove the need for a more in-depth study of the introduced phenomenon by developing a multi-factor questionnaire in order to create a complex of psychological and pedagogical support designed to increase the level of efficiency of the educational process in higher education.

The purpose of this paper is to analyze the macroeconomic factors influencing M&A activity in the Vietnamese market, analyzing both short run and long term. The theoretical foundation is analyzed and synthesized from previous studies. Quantitative research methods and vector error correction model were employed to analyze time-series data. The results of the study indicate that, in the long run, M&A activity is affected by money supply, political risk, and economic growth. In the short term, the impact on M&A is the tax burden, and institutional and regulatory factors.

“Indoctrination” is a term which refers to the intent to impose ideas or beliefs upon people in areas that ultimately call for individual reflection, decision-making, and choice. It is a distasteful activity because it is aimed at limiting the individual’s ability to think and choose. Religious or moral education are not necessarily indoctrination and it is possible to create a Jewish education that is not indoctrination.

With the term dynamometry (from the Greek dynamis “strength” and metron “measure”), we mean the method by which muscle strength can be measured. The muscle strength can be expressed as (Barbat-Artigas et al. 2012)

The rehabilitation of rigid (concrete) pavements with the placement of an asphalt overlay is a common maintenance technique which results in a structure known as a flexible composite pavement. The most common form of distress in this type of pavement is reflection cracking which can be due to traffic and/or climatic loading and it is considered as a very complex deterioration mechanism. A simplified mechanics-based approach identified from the literature has been developed to model the progression of reflective cracking. To demonstrate the model, results have been compared with data from the Long-Term Pavement Performance (LTPP) database, which contains performance and traffic data from monitored in-service road sections in North America. Results reveal the development of reflective cracking at different periods after the placement of the asphalt overlay and with different rates of cracking depending on the structure and material properties of a section as well as the specific traffic axle loading of each pavement section. The results help in identifying those factors which have a greater influence on the progression of reflection cracking in flexible composite pavements.

This chapter is about the scope of workflow automation in the printing industry. In many cases, the term workflow refers only to the work steps within production, i.e. in prepress, press and postpress. In this chapter, however, the term is defined more broadly, which is why areas such as the print buyer’s purchase order, materials management, or shipping the finished products to the customer are included.

Being able to estimate future velocity on a road network has applications from vehicle navigation systems to emergency vehicle dispatching systems. The existence of traffic congestion can severely impact travelers’ travel time and in this paper we explore methods to take it into account in velocity forecasting models. Using a data approach, different traffic observations can be classified into classes with and without congestion. Our research shows that using congestion as an attribute can reduce the prediction error when implementing machine learning models, such as random forest or multi-layer perceptron. Furthermore, training separate models for each class performs better than using congestion as an extra attribute. A methodology for the congestion pattern identification is proposed, based only in the velocity and volume values.

With continued development of urban rail transit networks, the quantity of overlapping metro tunnels is increasing. Long-term service performance of the tunnel structure can be threatened a lot by complicated dynamic response of tunnel–ground system under train load, especially in the overlapping cases. Based on a case of four overlapping tunnels in soft clay region, dynamic response of the tunnel–ground system and long-term settlement of the tunnels are investigated with finite element method (FEM) and empirical method. It is shown that, maximum acceleration and dynamic principal stress of the lining in overlapping zone are 48.2% and 19.8%, respectively, larger than that in non-overlapping zone. The ten-year accumulation settlement of the tunnel in overlapping zone is 173.7% larger than that in non-overlapping zone. Uneven settlement occurs in the overlapping zone, and the radius of curvature of the tunnel (12,461 m) exceeds the requirements of the specification (15,000 m). Grouted reinforcement can control the uneven settlement well. Radius of curvature of the tunnel can be refined to 33,967 m, which meets the requirements of the specification.

With slope movements man does not encounter every day, but it should be noted that this happens, and it happens more often. These movements are influenced only by two factors, namely nature and humans themselves. Slope deformations are one of the most widespread and to some extent one of the most dangerous country geohazards and represent significant geobarriers to urbanization planning. With gradually expanding populations comes extensive and demanding technical works built in increasingly complex and less favorable geological conditions. In complex geological conditions, it is mainly about understanding the overall geological environment with the development and effectively designing geotechnical structures to ensure long-term stability. The term effective design encompasses a set of geotechnical construction, which complement each other, so that their final effect has the desired influence. In this paper, we have attempted to describe ways of determining global stability, which is directly conditional on the building progress of stabilizing construction. This procedure creates and directs geotechnical engineers. Any change in construction has an impact on the global calculation, which should be adapted and subsequently verified. This calculation also influences new geological and geomechanical conditions that are specified by the construction process. Contractors may skip these essential steps, due to time and cost skips and thus embarks on the risky work, often with fatal consequences.

Due to the impact of modern information technology, the construction of transportation infrastructure has entered the “Intelligent Era.” The conventional construction technology is also undergoing a paradigm shift. In this paper, the term “intelligent construction” is defined, and the status quo of global transportation infrastructure construction with emerging intelligent construction technologies is summarized. The framework of intelligent construction is presented on all aspects of the integration of modern information technology and the conventional highway technologies. The essential elements of intelligent construction include sensing, analysis, decision-making, and execution. Big data, machine learning, and expert system are applied to provide practical technical solutions for intelligent construction. This paper also elaborates on the process of intelligent decision-making and auto-feedback machine controls. Finally, the future development of intelligent construction is laid out. The globally coordinated efforts by the International Society for Intelligent Construction (ISIC) will help the leading development and implementation of intelligent construction into the future.

The major highway network in the UK was developed from the 1960s, and the earthworks are generally well engineered. However, as many of the earthworks get older, slope failures are becoming more common, with some posing a threat to the safety of transport operations. Field measurements of soil water content and pore water pressure changes within the surface zone of a highway cut slope in London Clay at Newbury, Berkshire, UK, have been carried out continuously since 2003. This paper describes and gives examples of the long-term field measurements from the site at Newbury and details a number of significant findings from the observations from the site. The paper explains how these have been used to calibrate appropriate models of seasonal cycles of pore water pressure and slope deterioration.

Volumetric water content (VWC) and matric suction vary temporally in the foundation layers of pavements and railways due to various influencing environmental factors. The resilient and permanent deformation behaviors of railway foundation materials are strongly linked to the suction within the soil, reinforcing the need for the measurement thereof. This paper reports on the installation of VWC sensors, tensiometers and fixed-matrix soil-water suction sensors in different configurations within the foundation layers of a new 26 tonne/axle railway line near Ermelo in South Africa. Local weather data was recorded using a weather station at the site. The VWC sensors and the fixed-matrix soil-water suction sensors also monitored soil layer temperature. The measurement techniques used are critically compared with regard to their ability to respond to weather events. Practical aspects pertaining to the installation procedures and maintenance required for the different techniques are also reported. It was found that tensiometers require careful consideration to ensure pore-water continuity when installed in the field. Nonetheless, tensiometers were the most reliable and accurate form of measurement in this study. The use of VWC sensors to infer suction in silica flour is a novel idea. However, this method showed limited success in this study. Fixed-matrix soil–water suction sensors provided the best long-term stability and ease of installation. However, the accuracy of these sensors requires further investigation.

High-speed railways (HSR) set strict limits on subgrade settlement. Excessive settlement, especially the differential settlement at the transition part between viaduct lines and embankment lines, could lead to discomfort on HSR trains and even accidents like derailments. Thus, proper ground treatment measures are inevitably needed. Screw-shaft pile reinforced subgrade was adopted in the transition section of Yancheng–Nantong HSR. However, limited research has been done to investigate the performance of screw-shaft pile reinforced subgrade. In this paper, numerical models were established to analyze the performance, especially the long-term settlement, of the reinforced subgrade. It was found that shaft-screw pile reinforced subgrade could control the long-term settlement better than the traditional shaft pile subgrade. The advantage becomes greater when the train speed increases. Moreover, the application of shaft-screw pile reinforced subgrade could reduce the material usage by about 10%. Briefly, shaft-screw reinforced subgrade could satisfy the settlement control requirements and achieve greater cost efficiency in sandy subgrades.

In the pavilion laboratory there are three different windows evaluated since 2011. These windows are suitable for low-energy or passive houses. Two different plastic based windows were modelled and the temperatures were compared to the real measurement with different outdoor temperatures. One of the windows, with the theoretically worst properties was recently removed and another one was mounted into the laboratory. Than the window was tested in the climate chamber. Result is the comparison of temperature courses with simulation of the same winter day as recorded with the weather station. Similar results were obtained and the degradation of thermal properties of the window were confirmed.

This paper presents the first results of the development of a holistic care platform. A user-centered approach is taken to align the platform as closely as possible to the needs of potential users and to create real added value with the platform in contrast to existing solutions. In the context of this study, the term user is understood to mean both people with assistance needs and their relatives or caregivers, but also potential providers who offer their products or services via the platform. Within the framework of the user-centered approach, potential competitors were first analyzed. Besides, a qualitative analysis was conducted to identify unmet needs and implementation ideas of the users that could be covered by a care platform.

Fibre reinforced concrete (FRC) has quickly become an attractive solution for increasing both the mechanical performance and sustainability of concrete structures. In particular, polymeric fibres are increasingly recognized as offering significant benefits for FRC structural applications, especially in areas such as durability. Nonetheless, the behaviour of such FRC remains to be fully understood, especially from the perspective of long-term effects such as shrinkage and creep. Therefore, in this study, a comprehensive experimental programme is carried out for short- and long-term characterization of polypropylene FRC (PPFRC). The experimental program consisted of producing concretes C40/50 with 0, 3 and 9 kg/m3 of polypropylene fibres. Besides specimens for testing mechanical properties, shrinkage and creep in compression and under bending were tested. Finally, full-scale 3–m span beams with minimum steel reinforcement (0.18%) were tested until failure and under sustained loads. The results are analysed and the contribution of polypropylene fibres to reducing deflections and crack widths is assessed, with no evidence of local flexural failures due to tertiary creep phenomena. The results of this study can provide a contribution towards a fuller understanding of PPFRC structural behaviour and its future incorporation into design codes. The authors want also express their gratitude to the Spanish Ministry of Science and Innovation for the financial support received under the scope of the project CREEF (Creep and Fatigue of fibre reinforced concrete elements) (PID2019-108978RB-C32). This study has also received funding from MBCC Group. This support is gratefully acknowledged. Any opinions, findings, conclusions, and/or recommendations in the paper are those of the authors and do not necessarily represent the views of the individuals or organizations acknowledged.

In the last decades, fibre reinforced concretes became widely adopted in structural applications. Nevertheless, some elements of their mechanical behaviour are not fully understood. For instance, the effect of environmental conditions on the short and long-term behaviour of these materials has been studied to a limited extent only. In this perspective, the present paper presents the results of a large experimental campaign involving flexural tests on Macro Synthetic Fibre Reinforced Concrete (MSFRC) specimens under short- and long-term loads. Two different polypropylene Fibres were used, with dosages of 8kg/m3 and 10kg/m3. The effect of temperature on the short-term behaviour of these materials was investigated by performing three-point bending tests at 20 °C and 40 °C in cracked and uncracked conditions. The effect of temperature variations on long-term deformations was studied by means of four-point bending tests on pre-cracked notched beams at increasing temperatures, from 20 °C to 40°C. The paper presents the test results as well as analyses the effective number of fibres crossing the cracks.

Visual programming has become a term that stands for intuitive software development. It dispenses largely with textual notation and instead uses graphical program modules. The use of visual techniques is connected with the hope, among other things, to be able to create and understand programs more easily and better than before, which would open up access to software development for non-programmers. This could lead to a reduction of the enormous application backlog in many places. In this research, we design and build a web-based Visual Query builder tool to query the Waves blockchain database, using a flow-based programming language as well as an empirical evaluation of the tool that, on the one hand, measures the semantic understandability of a visual representation of a query, and compare it to its textual representation in SQL. On the other hand, we evaluate the user acceptance of the tool.

In this paper, we will evaluate the performance of five machine learning algorithms on large cap ten NIFTY50 companies. Author has implied a 10 year historical dataset that is utilized from yahoo finance and implemented using tensor flow application in google collaborator. Meanwhile, it is very uncertain to refrain from the findings of the concurrent studies to the real–world investing strategies due to lack of predictable results. This paper elaborates the attempt to measure the performance of neural fuzzy inference systems along with five different machine learning algorithms for a 10 year dataset. Several models developed on machine learning concepts were evaluated on a short term dataset that imparted very limited value of prediction accuracy. According to latest research advancement, most researchers focused on in-depth involvement of Machine learning algorithms to elaborate about future stock decisions. The experimental results show that Decision trees algorithm has highest prediction accuracy as compared to other Machine learning Algorithms [8] Neural Fuzzy Inference System.

The Covid-19 pandemic has brought too many concerns in businesses whether they will survive or fail. This is what makes forecasting crucial since it guides businesses in order to make appropriate decisions. In a pandemic environment, forecasting is critical because there is little historical data available. Taking this into consideration, in this study, fuzzy time series (FTS) and grey model (GM), which do not require long past time series data are implemented for short term forecasting of a product sold on a dedicated social media account. After adopting monthly sales data of the related product, accuracy of fuzzy time series and grey model are improved with parameter optimization. According to the results of absolute percentage error (APE), both methods demonstrate superior forecasting accuracies when the product shows an increasing sales trend. This study can also be a reference for businesses that are positively affected by the pandemic due to increased sales and willing to act on the opportunities it has already emerged. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The novel hybrid learning model based on neural networks and grammatical inference is proposed in the paper. The model is used within the multi-derivational parsing of vague language methodology. The foundations of the methodology and the learning algorithms are presented. The model has been used for the implementation of the short term electrical load forecasting system.

In this chapter, to attenuate the chattering phenomenon, the discontinuous term of the controllers in Chap. 5 is replaced by single-input single-output (SISO) radial basis function neural networks (RBFNNs), which are non-linear and continuous functions, thus resulting in adaptive neural sliding mode control (ANSMC). And, to relax the demands of knowing the bounds of the uncertainties and disturbances suffered by the system, the output layer weights of the RBFNNs are updated online to compensate for these uncertainties and disturbances as well as to guarantee the stability of the system without any prior knowledge of them and its bounds.

Support is the term used in the geostatistical literature to describe the volume or size of the data. For instance, the average grade of a mined pushback refers to a volume/support much larger than a sample that represents the average grade along one meter of a diamond drill hole. This difference in support must be considered if these two sources of information are used to build grade models.

This paper investigates the urban transportation planning framework related to long term refugee camps and their integration with the surrounding areas. The research considers the case of Naher El Bared Camp (NBC) in North Lebanon. First, the transport study for NBC before 2007 is analyzed via implementing the four steps model and performing a micro analysis using Emme regional transportation model linked with ArcGIS and Synchro software for signalized intersection traffic analysis. Then, a new transport model for the year 2030 is developed subject to several to social, economic, land use, and political constraints. This paper is the first documented study that investigates urban transportation planning for long term refugee camps in the Middle East region countries.