bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing the Thermal Performance of Slender Packed Beds through Internal Heat Fins
Authors: Jurtz Nico , Flaischlen Steffen , Scherf Sören C. , Kraume Matthias , Wehinger Gregor D.
Published: November 2020

Slender packed beds are widely used in the chemical and process industry for heterogeneous catalytic reactions in tube-bundle reactors. Under safety and reaction engineering aspects, good radial heat transfer is of outstanding importance. However, because of local wall effects, the radial heat transport in the vicinity of the reactor wall is hindered. Particle-resolved computational fluid dynamics (CFD) is used to investigate the impact of internal heat fins on the near wall radial heat transport in slender packed beds filled with spherical particles. The simulation results are validated against experimental measurements in terms of particle count and pressure drop. The simulation results show that internal heat fins increase the conductive portion of the radial heat transport close to the reactor wall, leading to an overall increased thermal performance of the system. In a wide flow range (100<Rep<1000), an increase of up to 35% in wall heat transfer coefficient and almost 90% in effective radial thermal conductivity is observed, respectively.
Using Recycled Construction and Demolition Waste Products: A Review of Stakeholders’ Perceptions, Decisions, and Motivations
Authors: Shooshtarian Salman , Caldera Savindi , Maqsood Tayyab , Ryley Tim
Published: November 2020

While the increasing rate of urbanisation is a critical concern for socio-environmental reasons, this also leads to more extraction of natural raw materials and the generation of significant quantities of construction and demolition (C&D) waste. Although the use of recycled C&D waste products is technically feasible and regulated, and positive application examples are evident, it is still unclear how to engage key stakeholders to leverage this opportunity in construction projects. Previous research has shown that there is some level of resistance to the reuse of recycled C&D waste products in construction projects. This highlights a critical need to identify the roles of key stakeholders and the barriers they face when using recycled C&D materials. This paper therefore investigates the type of stakeholders influencing the use of recycled C&D waste products and the main factors affecting stakeholders’ decisions to use recycled C&D waste products through a systematic literature review. The authors present an emergent enablers and barriers for recycled C&D waste products model and provide commentary on how stakeholders’ perceptions, decision and behaviour influence the use of recycled C&D waste products. The authors also contribute to the body of knowledge with insights into the factors that various stakeholders believe influence the market for recycled C&D waste products and provides a reference point for authorities to consider these behavioural insights for policy reform.
A New Model of Consolation
Authors: Jedan Christoph
Published: November 2020

This article presents a new model of consolation that identifies five key themes: (1) an appeal to the inner strength of the consoland; (2) the regulation of emotion; (3) the attempt to preserve, re-write, and perfect the life of the deceased or, more generally, a person undergoing a radical psycho-social transition; (4) a ‘healing’ worldview, in which death has a legitimate place; and (5) reconnection with the community at the different levels of, for instance, family, society and humanity. The study is based on the Western tradition of written consolations. It partially confirms—and also supersedes—earlier studies of consolation based on different methods and smaller ranges of material. The article explores the applicability of the framework beyond the consolatory tradition by analyzing two versions of the Roman Catholic rite of anointing the sick. It argues for the heuristic usefulness of the model in the field of ritual studies, both by demonstrating the limitations of prevalent typologies of ritual and by suggesting a fresh look at ritual efficacy.
Pharyngo-Cervico-Brachial Variant of Guillain-Barré or Miller Fisher Syndromes? When the Overlap Is Misleading
Authors: Tamaoui Leila , Rahmani Mounia , Touati Hajar , Errguig Leila , Benabdeljlil Maria , Aidi Saadia
Published: November 2020

Miller Fisher Syndrome (MFS) is a rare variant of Guillain-Barré Syndrome (GBS). It is largely a clinical diagnosis based on the classical features of ataxia, areflexia, and opthalmoplegia. Its clinical evolution is most often favorable. However, other neurological signs and symptoms may also be present. Supportive laboratory studies (positivity of antibodies, CSF albumin-cytological dissociation and nerve conduction studies) are useful especially in uncommon presentations. We report a case of a 74-year-old patient who exhibited dysphonia and difficulty to swallowing previously to the classic triad of ataxia, areflexia, and opthalmoplegia, characteristic of MFS. CSF analysis demonstrates an albumin-cytological dissociation. Anti-GTa1 antibodies were found but anti-GQ1b antibodies were negative. The patient has spontaneously and completely recovered after 6 weeks.
Technical Aspects of Mining Rate Improvement in Steeply Inclined Coal Seams: A Case Study
Authors: Rak Zbigniew , Stasica Jerzy , Burtan Zbigniew , Chlebowski Dariusz
Published: November 2020

This paper presents our experience obtained when mining the thick and steeply-inclined Seam 510 in the Polish Kazimierz-Juliusz coal mine with the use of a unique mechanical face mining system. Seam 510, which is 15–20 m thick and inclined at angles of 40°–45°, was initially treated as uneconomical because effective mining systems were not available. However, to extract high-quality coal resources, a completely mechanized variant of the sublevel caving system was designed based on standard machines and equipment applied in coal mining. Extraction was conducted top-down at the levels of the particular mining sub-level drifts with roof caving. The faces in the extracted coal release areas were protected by a single pair of specially designed mechanized mining system sections. One of the basic problems revealed during extraction of subsequent mining panels, was the observed changeability of the resource mining rates. The extraction losses changed in the available resources from less than 10% to about 50%. This paper presents two typical courses of changes in the extractable resource mining rates. Similar rate changes occurred in both cases with continued mining of a single seam section. Our analysis enabled deposit loss estimations and production output planning under the sublevel caving systems applied in the extraction of seam deposits of similar structure.
Using GIS and Machine Learning to Classify Residential Status of Urban Buildings in Low and Middle Income Settings
Authors: Lloyd Christopher , Sturrock Hugh , Leasure Douglas , Jochem Warren , Lázár Attila , Tatem Andrew
Published: November 2020

Utilising satellite images for planning and development is becoming a common practice as computational power and machine learning capabilities expand. In this paper, we explore the use of satellite image derived building footprint data to classify the residential status of urban buildings in low and middle income countries. A recently developed ensemble machine learning building classification model is applied for the first time to the Democratic Republic of the Congo, and to Nigeria. The model is informed by building footprint and label data of greater completeness and attribute consistency than have previously been available for these countries. A GIS workflow is described that semiautomates the preparation of data for input to the model. The workflow is designed to be particularly useful to those who apply the model to additional countries and use input data from diverse sources. Results show that the ensemble model correctly classifies between 85% and 93% of structures as residential and nonresidential across both countries. The classification outputs are likely to be valuable in the modelling of human population distributions, as well as in a range of related applications such as urban planning, resource allocation, and service delivery.
Robust Data Fusion of UAV Navigation Measurements with Application to the Landing System
Authors: Kolosov Kirill , Miller Alexander , Miller Boris
Published: November 2020

To perform precise approach and landing concerning an aircraft in automatic mode, local airfield-based landing systems are used. For joint processing of measurements of the onboard inertial navigation systems (INS), altimeters and local landing systems, the Kalman filter is usually used. The application of the quadratic criterion in the Kalman filter entails the well-known problem of high sensitivity of the estimate to anomalous measurement errors. During the automatic approach phase, abnormal navigation errors can lead to disaster, so the data fusion algorithm must automatically identify and isolate abnormal measurements. This paper presents a recurrent filtering algorithm that is resistant to anomalous errors in measurements and considers its application in the data fusion problem for landing system measurements with onboard sensor measurements—INS and altimeters. The robustness of the estimate is achieved through the combined use of the least modulus method and the Kalman filter. To detect and isolate failures the chi-square criterion is used. It makes possible the customization of the algorithm in accordance with the requirements for false alarm probability and the alarm missing probability. Testing results of the robust filtering algorithm are given both for synthesized data and for real measurements.
A Numerical Model for Experimental Designs of Vibration-Based Leak Detection and Monitoring of Water Pipes Using Piezoelectric Patches
Authors: Okosun Favour , Celikin Mert , Pakrashi Vikram
Published: November 2020

While the potential use of energy harvesters as structural health monitors show promise, numerical models related to the design, deployment and performance of such monitors often present significant challenges. One such challenge lies in the problem of leak detection in fluid-carrying pipes. Recent advances in experimental studies on energy harvesters for such monitoring has been promising but there is a paucity in existing literature in linking relevant fluid–structure interaction models around such applications. This paper addresses the abovementioned issue by developing a numerical model with Computational Fluid Dynamics (CFD) and Finite Element (FE) tools and carries out extensive analyses to compare it with existing experiments under controlled laboratory conditions. Conventional Polyvinylidene Fluoride (PVDF) films for leak detection and monitoring of water pipes were considered in this regard. The work provides guidelines on parameter selection and modeling for experimental design and repeatability of results for these types of experiments in future, around the demands of leak monitoring. The usefulness of such models is also demonstrated through the ability to estimate the optimum distribution frequency of these sensors that will enable the detection of the smallest leak of consequence under a known or established flow condition.
Radio Wave Propagation and WSN Deployment in Complex Utility Tunnel Environments
Authors: Celaya-Echarri Mikel , Azpilicueta Leyre , Lopez-Iturri Peio , Picallo Imanol , Aguirre Erik , Astrain Jose Javier , Villadangos Jesús , Falcone Francisco
Published: November 2020

The significant growth of wireless communications systems in the last years has led to the adoption of a wide range of applications not only for the general public but, also, including utilities and administrative authorities. In this context, the notable expansion of new services for smart cities requires, in some specific cases, the construction of underground tunnels in order to enable the maintenance and operation works of utilities, as well as to reduce the visual impact within the city center. One of the main challenges is that, inherently, underground service tunnels lack coverage from exterior wireless communication systems, which can be potentially dangerous for maintenance personnel working within the tunnels. Accordingly, wireless coverage should be deployed within the underground installation in order to guarantee real-time connectivity for safety maintenance, remote surveillance or monitoring operations. In this work, wireless channel characterization for complex urban tunnel environments was analyzed based on the assessment of LoRaWAN and ZigBee technologies operating at 868 MHz. For that purpose, a real urban utility tunnel was modeled and simulated by means of an in-house three-dimensional ray-launching (3D-RL) code. The utility tunnel scenario is a complex and singular environment in terms of radio wave propagation due to the limited dimensions and metallic elements within it, such as service trays, user pathways or handrails, which were considered in the simulations. The simulated 3D-RL algorithm was calibrated and verified with experimental measurements, after which, the simulation and measurement results showed good agreement. Besides, a complete wireless sensor network (WSN) deployment within the tunnels was presented, providing remote cloud data access applications and services, allowing infrastructure security and safety work conditions. The obtained results provided an adequate radio planning approach for the deployment of wireless systems in complex urban utility scenarios, with optimal coverage and enhanced quality of service.
Internet of Medical Things: An Effective and Fully Automatic IoT Approach Using Deep Learning and Fine-Tuning to Lung CT Segmentation
Authors: Souza Luís Fabrício de Freitas , Silva Iágson Carlos Lima , Marques Adriell Gomes , Silva Francisco Hércules dos S. , Nunes Virgínia Xavier , Hassan Mohammad Mehedi , Albuquerque Victor Hugo C. de , Filho Pedro P. Rebouças
Published: November 2020

Several pathologies have a direct impact on society, causing public health problems. Pulmonary diseases such as Chronic obstructive pulmonary disease (COPD) are already the third leading cause of death in the world, leaving tuberculosis at ninth with 1.7 million deaths and over 10.4 million new occurrences. The detection of lung regions in images is a classic medical challenge. Studies show that computational methods contribute significantly to the medical diagnosis of lung pathologies by Computerized Tomography (CT), as well as through Internet of Things (IoT) methods based in the context on the health of things. The present work proposes a new model based on IoT for classification and segmentation of pulmonary CT images, applying the transfer learning technique in deep learning methods combined with Parzen’s probability density. The proposed model uses an Application Programming Interface (API) based on the Internet of Medical Things to classify lung images. The approach was very effective, with results above 98% accuracy for classification in pulmonary images. Then the model proceeds to the lung segmentation stage using the Mask R-CNN network to create a pulmonary map and use fine-tuning to find the pulmonary borders on the CT image. The experiment was a success, the proposed method performed better than other works in the literature, reaching high segmentation metrics values such as accuracy of 98.34%. Besides reaching 5.43 s in segmentation time and overcoming other transfer learning models, our methodology stands out among the others because it is fully automatic. The proposed approach has simplified the segmentation process using transfer learning. It has introduced a faster and more effective method for better-performing lung segmentation, making our model fully automatic and robust.
PADL: A Modeling and Deployment Language for Advanced Analytical Services
Authors: Díaz-de-Arcaya Josu , Miñón Raúl , Torre-Bastida Ana I. , Del Ser Javier , Almeida Aitor
Published: November 2020

In the smart city context, Big Data analytics plays an important role in processing the data collected through IoT devices. The analysis of the information gathered by sensors favors the generation of specific services and systems that not only improve the quality of life of the citizens, but also optimize the city resources. However, the difficulties of implementing this entire process in real scenarios are manifold, including the huge amount and heterogeneity of the devices, their geographical distribution, and the complexity of the necessary IT infrastructures. For this reason, the main contribution of this paper is the PADL description language, which has been specifically tailored to assist in the definition and operationalization phases of the machine learning life cycle. It provides annotations that serve as an abstraction layer from the underlying infrastructure and technologies, hence facilitating the work of data scientists and engineers. Due to its proficiency in the operationalization of distributed pipelines over edge, fog, and cloud layers, it is particularly useful in the complex and heterogeneous environments of smart cities. For this purpose, PADL contains functionalities for the specification of monitoring, notifications, and actuation capabilities. In addition, we provide tools that facilitate its adoption in production environments. Finally, we showcase the usefulness of the language by showing the definition of PADL-compliant analytical pipelines over two uses cases in a smart city context (flood control and waste management), demonstrating that its adoption is simple and beneficial for the definition of information and process flows in such environments.
Comparing the Use of High- to Low-Cost Black Carbon and Carbon Dioxide Sensors for Characterizing On-Road Diesel Truck Emissions
Authors: Sugrue Rebecca A. , Preble Chelsea V. , Kirchstetter Thomas W.
Published: November 2020

The exhaust plume capture method is a commonly used approach to measure pollutants emitted by in-use heavy-duty diesel trucks. Lower cost sensors, if used in place of traditional research-grade analyzers, could enable wider application of this method, including use as a monitoring tool to identify high-emitting trucks that may warrant inspection and maintenance. However, low-cost sensors have for the most part only been evaluated under ambient conditions as opposed to source-influenced environments with rapidly changing pollutant concentrations. This study compared black carbon (BC) emission factors determined using different BC and carbon dioxide (CO2) sensors that range in cost from $200 to $20,000. Controlled laboratory experiments show that traditional zero and span steady-state calibration checks are not robust indicators of sensor performance when sampling short duration concentration peaks. Fleet BC emission factor distributions measured at two locations at the Port of Oakland in California with 16 BC/CO2 sensor pairs were similar, but unique sensor pairs identified different high-emitting trucks. At one location, the low-cost PP Systems SBA-5 agreed on the classification of 90% of the high emitters identified by the LI-COR LI-7000 when both were paired with the Magee Scientific AE33. Conversely, lower cost BC sensors when paired with the LI-7000 misclassified more than 50% of high emitters when compared to the AE33/LI-7000. Confidence in emission factor quantification and high-emitter identification improves with larger integrated peak areas of CO2 and especially BC. This work highlights that sensor evaluation should be conducted under application-specific conditions, whether that be for ambient air monitoring or source characterization.
Using a Social Robot to Evaluate Facial Expressions in the Wild
Authors: Ramis Silvia , Buades Jose Maria , Perales Francisco J.
Published: November 2020

In this work an affective computing approach is used to study the human-robot interaction using a social robot to validate facial expressions in the wild. Our global goal is to evaluate that a social robot can be used to interact in a convincing manner with human users to recognize their potential emotions through facial expressions, contextual cues and bio-signals. In particular, this work is focused on analyzing facial expression. A social robot is used to validate a pre-trained convolutional neural network (CNN) which recognizes facial expressions. Facial expression recognition plays an important role in recognizing and understanding human emotion by robots. Robots equipped with expression recognition capabilities can also be a useful tool to get feedback from the users. The designed experiment allows evaluating a trained neural network in facial expressions using a social robot in a real environment. In this paper a comparison between the CNN accuracy and human experts is performed, in addition to analyze the interaction, attention and difficulty to perform a particular expression by 29 non-expert users. In the experiment, the robot leads the users to perform different facial expressions in motivating and entertaining way. At the end of the experiment, the users are quizzed about their experience with the robot. Finally, a set of experts and the CNN classify the expressions. The obtained results allow affirming that the use of social robot is an adequate interaction paradigm for the evaluation on facial expression.
Label Noise Cleaning with an Adaptive Ensemble Method Based on Noise Detection Metric
Authors: Feng Wei , Quan Yinghui , Dauphin Gabriel
Published: November 2020

Real-world datasets are often contaminated with label noise; labeling is not a clear-cut process and reliable methods tend to be expensive or time-consuming. Depending on the learning technique used, such label noise is potentially harmful, requiring an increased size of the training set, making the trained model more complex and more prone to overfitting and yielding less accurate prediction. This work proposes a cleaning technique called the ensemble method based on the noise detection metric (ENDM). From the corrupted training set, an ensemble classifier is first learned and used to derive four metrics assessing the likelihood for a sample to be mislabeled. For each metric, three thresholds are set to maximize the classifying performance on a corrupted validation dataset when using three different ensemble classifiers, namely Bagging, AdaBoost and k-nearest neighbor (k-NN). These thresholds are used to identify and then either remove or correct the corrupted samples. The effectiveness of the ENDM is demonstrated in performing the classification of 15 public datasets. A comparative analysis is conducted concerning the homogeneous-ensembles-based majority vote method and consensus vote method, two popular ensemble-based label noise filters.
Is There Sustainable Development after Mining? A Case Study of Three Mining Areas in the Apuseni Region (Romania)
Authors: Botezan Camelia , Constantin Veronica , Meltzer Monika , Radovici Andrei , Pop Alina , Alexandrescu Filip , Stefanescu Lucrina
Published: November 2020

The cessation or downsizing of mining activities induced complex challenges for entire regions in Romania, leading to depopulation, poverty, and pollution. Resource-dependency locked these regions in a mono-industry setting where it was difficult for new development paths to emerge. This paper presents a historical overview of a well-known Romanian mining region and identifies promising recovery opportunities that could shift the trajectory of its mining communities towards new sustainable paths. The research was based on official statistical data for the period 1965/1966–2018, complemented by qualitative data extracted from 39 semi-structured interviews with residents from the study area. The results revealed that the concentration of employment in the mining sector, together with other concurring factors, made it difficult for the communities to find sustainable ways of development while, at the same time, highlighting some possible revitalization and recovery opportunities. The findings contribute to a better understanding of mining communities, which will support the creation of tailored policies and planning strategies aimed towards their sustainable redevelopment.
Perceptions of Bioeconomy and the Desire for Governmental Action: Regional Actors’ Connotations of Wood-Based Bioeconomy in Germany
Authors: Hafner Manuel , Fehr Lukas , Springorum Jan , Petkau Artur , Johler Reinhard
Published: November 2020

The term bioeconomy denotes political strategies that affect all areas of life and economy and require broad social support. Nevertheless, the term has not yet pervaded the everyday lives of many people. It is yet unclear what effects these concepts generate in the form of associations and what conflicts and political demands could be associated with them. Using an ethnographic approach, different actors from the forest and wood field of action were interviewed in two study regions in Germany, who are already, consciously or unconsciously, engaged in bioeconomy at a regional level. Different perceptions and interpretations of bioeconomies can be identified, which are often linked to political demands. These can be clustered into two groups. The first group refers to the forest as a place of primary production and demands an adaptation of forest management. The second group refers to wood as the most important raw material of bioeconomy and demands planning security necessary for change. The paper shows that, from the perspective of the interviewees, government action can contribute to the definition of concepts by sending clear signals and thus overcome the limited reach of strategy papers.
Empowering Sustainable Consumer Behavior in the EU by Consolidating the Roles of Waste Recycling and Energy Productivity
Authors: Dinu Mihai , Pătărlăgeanu Simona Roxana , Petrariu Radu , Constantin Marius , Potcovaru Ana-Mădălina
Published: November 2020

The growth in population and economic activities has direct implications on the deterioration of the natural capital, especially when referring to the increase in greenhouse gas emissions. However, improvement is possible by empowering sustainable consumption and production patterns. Through the 2030 Agenda for Sustainable Development, the United Nations call for a mix of economic development, environmental sustainability, and social inclusion. The agenda also provides the instruments needed to track progress, as each Sustainable Development Goal has a set of indicators meant to assess various dimensions of sustainability. Energy productivity is only one of many, but still special because it reflects sustainable consumption behaviors and production patterns. The 2030 Climate Target Plan elaborated by the European Commission consolidates and brings its contribution to the aims of the 2030 Agenda for Sustainable Development by adding weight to the importance of the greenhouse gas emissions target. The objective of this research was to study the relationship between energy productivity, greenhouse gas emissions, biowaste recycling and nominal GDP in the EU in order to highlight the key of a smooth transition towards sustainable consumption behaviors and production patterns. The results show that recycling, greening the economy and energy productivity are the vectors of this transition.
Full Real-Time Positioning and Attitude System Based on GNSS-RTK Technology
Authors: Olivart i Llop J. M. , Moreno-Salinas D. , Sánchez J.
Published: November 2020

An accurate positioning and attitude computation of vehicles, robots, or even persons is of the utmost importance and critical for the success of many operations in multiple commercial, industrial, and research areas. However, most of these positioning and attitude systems rely on inertial measurement units that must be periodically recalibrated and have a high cost. In the present work, the design of a real-time positioning and attitude system using three positioning sensors based on the GNSS-RTK technology is presented. This kind of system does not need recalibration, and it allows one to define the attitude of a solid by only computing the position of the system in the global reference system and the three angles that the relative positions of the GNSS antennas define with respect to the principal axes of the solid. The position and attitude can be computed in real time for both static and dynamic scenarios. The only limitation of the system is that the antennas need to be in open air to work at full performance and accuracy. All the design phases are covered in the prototype construction: requirement definition, hardware selection, software design, assembly, and validation. The feasibility and performance of the system were tested in both static and dynamic real scenarios.
Academic Achievement and Failure in University Studies: Motivational and Emotional Factors
Authors: Gilar-Corbi Raquel , Pozo-Rico Teresa , Castejón Juan-Luis , Sánchez Tarquino , Sandoval-Palis Ivan , Vidal Jack
Published: November 2020

Universities are committed to offering quality education; however, a high rate of academic failure is often observed in the first year of studies. Considering the impact that motivation and emotional aspects can have on students’ commitment to study and therefore on their academic performance, achievement, and well-being, this study aims to identify the factors associated with academic success or failure in 1071 students entering the National Polytechnic School (Quito, Ecuador). The data were compiled from the existing computer records of the university with the permission of the responsible administrative staff. A predictive model has been used and a binary logistic regression analysis was carried out through the step-forward regression procedure based on the Wald statistic to analyze the predictive capacity of the variables related to emotional intelligence, motivational and self- regulated socio-cognitive skills, goal orientation, and prior academic achievement (measured by university entrance marks and through a knowledge test carried out at the beginning of the university academic year). To determine the cut-off point for the best discriminatory power of each of the variables, a Receiver Operating Characteristics (ROC) curve analysis has been used. The results indicate that the variables that are significant in the prediction of academic success or failure are the two academic performance measures: the emotional attention variable, and the performance-approach goals and the motivational self-efficacy variable. Additionally, the highest predictive power is displayed by the prior academic performance measure obtained through the knowledge test conducted at the beginning of the university course.
Calculation Methods of Emission Factors and Emissions of Fugitive Particulate Matter in South Korean Construction Sites
Authors: Kim Hyunsik , Tae Sungho , Yang Jihwan
Published: November 2020

Recently, efforts to effectively reduce particulate matter by identifying its sources and trends have become necessary due to the sustained damage it has caused in East Asia. In the case of South Korea, damage due to fugitive dust generated at construction sites in densely populated downtown areas is significant, and particulate matter in such fugitive dust directly influences the health of nearby residents and construction workers. Accordingly, the purpose of the present study was to develop a method for calculating emission factors for PM10 and PM2.5 emission amounts in the fugitive dust generated in construction sites and to derive emission amount trends for major variables to predict the amounts of generated particulate matter. To this end, South Korean emission factors for PM10 and PM2.5 for different construction equipment and activities that generate fugitive dust were derived and a method for calculating the amount of particulate matter using the derived emission factors was proposed. In addition, the calculated total emissions using these factors were compared to those calculated using construction site fugitive dust equations developed for the United States, Europe, and South Korea, and the trend analysis of total emissions according to the major emission factor variables was conducted.
The Migration Intentions of Young Egyptians
Authors: Abdelwahed Amr , Goujon Anne , Jiang Leiwen
Published: November 2020

This study examines the migration intentions of young people in Egypt before and after the 2011 revolution, driven by three sets of factors: (1) individual demographic and socioeconomic characteristics, (2) household characteristics, and (3) community characteristics and political and civic participation. Logistic regression models are applied to study the determinants of intentions to live, study, or work abroad among young Egyptians (defined as individuals aged 18 to 29), using data from the Survey of Young People in Egypt (SYPE) conducted in 2009 (N = 8488) and in 2014 (N = 5885). The surveys are nationally representative, covering all governorates in Egypt. The analysis indicates that respondents’ age, gender, marital status, and employment status play a significant role in shaping migration intentions. After the 2011 revolution, the effects are dependent upon economic and institutional conditions. The employment status affects the migration intention of young people in 2009; but the effects become insignificant in 2014. Moreover, respondents who have participated in political and voluntary activities are more likely to express migration intentions. Pollution levels in the community are also positively correlated with the intention to migrate. The results indicate that those who expressed migration intentions are a selective group in terms of demographic and socioeconomic characteristics. Our findings have policy relevance because knowledge and understanding of migration intentions and their determinants can be used to assess and develop scenarios about future migration.
A SWOT Analysis of the UK EV Battery Supply Chain
Authors: Zhang Yun , Rysiecki Louise , Gong Yu , Shi Qi
Published: November 2020

The aim of this research is to identify and explore the UK electric vehicle (EV) battery industry’s supply chain strengths, weaknesses, opportunities and threats (SWOT) by taking a leading UK EV battery company as an exploratory case study. Our research addresses the gap in knowledge surrounding the UK EV battery supply chain, as the current literature is limited whilst demands for EVs are surging. There are significant opportunities awaiting the EV battery industry, though it is crucial that companies are aware of the threats facing them. To address the gap, this research followed an exploratory qualitative research design using semi-structured interviews with experienced interviewees in the industry. By applying the SWOT analysis framework and the theory lens of Resource Based View (RBV), we suggest that the UK EV battery industry should diversify its supply base into multiple regions such as India, Africa, and the US, which would reduce the reliance on sourcing from China whilst maintaining good supplier relationships and continuous innovation.
Volatility in Rainfall and Predictability of Droughts in Northwest Bangladesh
Authors: Uddin Mohammad Ahsan , Kamal ASM Maksud , Shahid Shamsuddin , Chung Eun-Sung
Published: November 2020

This study was conducted to evaluate the variability, trends, volatility, and transition patterns of rainfall in drought-prone northwest Bangladesh. Daily rainfall recorded at five stations for the period 1959–2018 were used for this purpose. Non-parametric tests of variability changes, a modified Mann–Kendall trend test, innovative trend analysis (ITA), a generalized autoregressive conditional heteroscedasticity (GARCH)–jump model, and a Markov chain (MC) were used to assess the variability changes, trends, volatility, and transitions in rainfall to understand the possibility of the persistence of droughts and their predictability. The results showed an overall decrease of variability in annual and seasonal rainfall, but an increase in mean pre-monsoon rainfall and a decrease in mean monsoon rainfall. This caused a decrease in pre-monsoon droughts, but few changes in monsoon droughts. The ITA and rainfall anomaly analysis revealed high temporal variability and, thus, rapid shifts in rainfall regimes, which were also supported by the volatility dynamics and time-varying jumps from the GARCH–jump model and the rapid changes in drought index from the MC analysis. Therefore, the lack of drought in recent years cannot be considered as an indicator of declining droughts in the region.
Design for Sustainable Public Transportation: LCA-Based Tooling for Guiding Early Design Priorities
Authors: Haanstra Willem , Rensink Willem-Jan , Martinetti Alberto , Braaksma Jan , Dongen Leo van
Published: November 2020

Environmental sustainability is an increasingly important subject for public transportation organizations. For passenger train operators, modernization projects provide key opportunities to improve the environmental impact of their rolling stock by making informed design decisions at the midpoint of the life cycle of their trains. Life Cycle Assessment (LCA) is widely adopted as the main instrument for evaluating environmental impact. However, in the past LCA was rarely used in the earlier design stages, where it is most effective, due to constrained access to data, information, and LCA-specific expertise. To this end, a purpose-built streamlined LCA tool for train modernization is developed and demonstrated, following a Design Science Research approach. The developed tool simplifies the application of LCA employing four main design principles: (1) sacrificing the declarative function of LCA, (2) the use of Input–Output-based Life Cycle Inventory, (3) the inclusion of ‘shadow costs’, (4) the limitation of the included environmental impact categories. By streamlining the application of LCA in this way, it becomes possible to introduce LCA-based principles and ways of thinking into a process that would otherwise be inaccessible to performing LCA in: the early design stages of modernization projects.
Fatigue and Thermal Cracking of Hot and Warm Bituminous Mixtures with Different RAP Contents
Authors: Pham Nguyen Hoang , Sauzéat Cédric , Di Benedetto Hervé , González-León Juan A. , Barreto Gilles , Nicolaï Aurélia
Published: November 2020

This paper presents results of laboratory tests on hot and warm bituminous mixtures produced with Reclaimed Asphalt Pavement (RAP). Additives were used to produce warm bituminous mixtures. Fatigue behaviour and thermomechanical behaviour at low temperature were investigated. Fatigue was studied by analysing the tension/compression fatigue test results. Four different failure criteria were used in order to evaluate fatigue life. The low temperature behaviour of the materials was characterized using the Thermal Stress Restrained Specimen Test (TSRST). For each material, three replicates were performed. The experimental device was improved so that radial strains in two directions could be measured during the tests. Tri-dimensional behaviour could thus be investigated. The results of both tests were analysed and the influence of the void content, RAP content, type of additives and manufacturing process was evaluated. The results show that RAP addition and warm bituminous mixtures could be combined to obtain mixtures with performances comparable to classical hot mixtures.
The Path towards Evolutionary—Teal Organizations: A Relationship Trigger on Collaborative Platforms
Authors: Moreno Romero Ana , Uruburu Ángel , Jain Ajay K. , Acevedo Ruiz Manuel , Gómez Muñoz Carlos F.
Published: November 2020

The technological challenges of the so-called fourth industrial revolution, innovative inter-organizational network relations, integration in corporate strategies of sustainability challenges, or unsatisfactory levels of staff commitment stemming from complexity and related uncertainty are some of the main key issues that organizations have to face in the near future. In this context, the appearance of the ‘evolutionary organization’ model marks an important milestone in terms of a renewed identification of fundamental principles for organizations, arguably as an update or revision of systemic thinking. This model allows organizations, functioning as living beings, to be more agile and humanistic and better prepared to establish agile and trustworthy inter-organizational relationships. Collaborative platforms are possible from that ability to add value between organizations while also being closely aligned with the principles and values of evolutionary organizations. The purpose of this paper is to provide insights into how these (teal) organizations work with respect to their common principles of wholeness, evolutionary purpose, and self-management. In the end, the study intends to highlight relevant practical organizational aspects that can better facilitate the management of current and increasing complexity, as well as the transition to more humanistic-oriented organizations.
Field and Modeling Study on Manual and Automatic Irrigation Scheduling under Deficit Irrigation of Greenhouse Cucumber
Authors: R. E. Abdelraouf , Ghanem H. G. , A. Bukhari Najat , El-Zaidy Mohamed
Published: November 2020

The primary goal of all those working in the field of sustainable water management, particularly in the arid and semi-arid zones, is to increase irrigation efficiency, reduce irrigation water losses, and improve water productivity for all crops. This study assessed the automatic irrigation scheduling and irrigation management on the growth, yield, and water productivity of cucumber under greenhouse conditions. A field experiment was conducted using cucumber grown in aplastic greenhouse during the winter of 2017/18 and 2018/19 at the research farm station of the National Research Centre (NRC), El-Noubaria Region, Behaira Governorate, Egypt. In a split-plot experiment, two different methods to control irrigation scheduling (manual control (MC) and automatic control (AC)) were used in the main plots and three deficit irrigation treatments (100% of full irrigation (FI), 80% of FI, and 60% of FI). Through the obtained results, it was found that the use of the automatic control of the irrigation schedule led to an improvement in the productivity and quality characteristics of the cucumber crop. Automatic irrigation control created healthy conditions for the plant roots located under the least water stress. This led to an increase in nitrogen uptake at the ages of 3, 5, 7, and 9 weeks after planting in addition to improving the total leaf area and the chlorophyll content of leaves, which consequently had a greater effect on increasing yield and water productivity of cucumber. Although the highest values of cucumber productivity were obtained with irrigation at 100% of FI, there were no significant differences between 100% FI and 80% of FI, therefore it is preferable to irrigate at 80% of FI, and this means saving 20% of irrigation water that can be used to irrigate other areas. The SALTMED model simulating all of the following evaluation criteria performed well for soil moisture content and N-uptake as well as the leaves area, the yield, and water productivity of cucumber for all treatments for the two growing seasons 2017/18 and 2018/19, with the overall R2 of 0.882, 0.903, 0.975, 0.907, and 0.933, respectively.
Sustainable Soil-Compacted Blocks Containing Blast Furnace Slag (BFS) Activated with Olive Stone BIOMASS Ash (OBA)
Authors: Payá Jordi , Monzó José , Roselló Josefa , Borrachero María Victoria , Font Alba , Soriano Lourdes
Published: November 2020

Soil stabilization using cementing materials is a well-known procedure for earth-based building blocks preparation. For the selected binding materials, innovation usually focuses on low carbon systems, many of which are based on alkaline activation. In the present paper, blast furnace slag (BFS) is used as a mineral precursor, and the innovative alkali activator was olive stone biomass ash (OBA). This means that the most important component in CO2 emissions terms, which is the alkali activator, has been replaced with a greener alternative: OBA. The OBA/BFS mixture was used to prepare compacted dolomitic soil blocks. These specimens were mechanically characterized by compression, and water strength coefficient and water absorption were assessed. The microstructure of blocks and the formation of cementing hydrates were analyzed by field emission scanning electron microscopy and thermogravimetry, respectively. The final compressive strength of the 120-day cured blocks was 27.8 MPa. It was concluded that OBA is a sustainable alkali activator alternative for producing BFS-stabilized soil-compacted blocks: CO2 emissions were 3.3 kgCO2/ton of stabilized soil, which is 96% less than that for ordinary Portland cement (OPC) stabilization.
The EU’s Green Deal: A Third Alternative to Green Growth and Degrowth?
Authors: Ossewaarde Marinus , Ossewaarde-Lowtoo Roshnee
Published: November 2020

In December 2019, the European Union introduced its Green Deal in which the ecological crisis is prioritized. In doing so, the EU seems to be breaking with its traditional green growth discourse. Does it? In this article, we seek to find out whether and to what extent the EC indeed has such a revolutionary cultural, economic and political agenda in mind with its Green Deal. While the green growth discourse presumes a growth-based economy that must become greener, the degrowth discourse questions the growth model and perceives it as ecologically irresponsible. If the European Green Deal represents a third alternative, then it will somehow succeed in prioritizing ecology without welfare loss. To ascertain to what extent the European Green Deal is that third alternative, three preliminary steps need to be undertaken. The first step consists in a brief exposition of the key features of the traditional green growth discourse, as propounded by the EC and its various allies. Thereafter, the overlaps between the green growth discourse and the European Green Deal are noted. In the third section, the latter’s divergences from that previous model are highlighted. In the final section, the main question of the article is answered. It is also suggested that specific interpretations and implementations of the European Green Deal could possibly turn the original communication into an alternative to both green growth and degrowth.
Dynamics of Nonlocal Rod by Means of Fractional Laplacian
Authors: Gusella Vittorio , Autuori Giuseppina , Pucci Patrizia , Cluni Federico
Published: November 2020

The use of fractional models to analyse nonlocal behaviour of solids has acquired great importance in recent years. The aim of this paper is to propose a model that uses the fractional Laplacian in order to obtain the equation ruling the dynamics of nonlocal rods. The solution is found by means of numerical techniques with a discretisation in the space domain. At first, the proposed model is compared to a model that uses Eringen’s classical approach to derive the differential equation ruling the problem, showing how the parameters used in the proposed fractional model can be estimated. Moreover, the physical meaning of the model parameters is assessed. The model is then extended in dynamics by means of a discretisation in the time domain using Newmark’s method, and the responses to different dynamic conditions, such as an external load varying with time and free vibrations due to an initial deformation, are estimated, showing the difference of behaviour between the local response and the nonlocal response. The obtained results show that the proposed model can be used efficiently to estimate the response of the nonlocal rod both to static and dynamic loads.