bluuebunny/crossref_metadata_2025 huggingface dataset:
A Metro-Based System as Sustainable Alternative for Urban Logistics in the Era of E-Commerce
Authors: Villa Rafael , Monzón Andrés
Published: April 2021

Business to consumer e-commerce (B2C) has increased sharply in recent years driven by a growing online population and changes in consumer behavior. In metropolitan areas, the “Amazon effect” (online retailers’ vast selection, fast shipping, free returns, and low prices) has led to an increased use of light goods vehicles. This is affecting the rational functioning of the transport system, including a high degree of fragmentation, low load optimization, and, among other externalities, higher traffic congestion. This paper investigates the potential of a metro system, in a big city like Madrid, to provide delivery services by leveraging its existing carrying capacity and using the metro stations to collect parcels in lockers. It would be a new mixed distribution model for last-mile deliveries associated with e-commerce. To that end, the paper evaluates the cost and impacts of two alternative scenarios for managing the unused space in rolling stock (shared trains) or specific full train services (dedicated trains) on existing lines. The external costs of the proposed scenarios are compared with current e-commerce delivery scenario (parcel delivery by road). The results show that underground transport of parcels could significantly reduce congestion costs, accidents, noise, GHG emissions, and air pollution.
Assessment of Indoor Environmental Quality in Budget Hotels Using Text-Mining Method: Case Study of Top Five Brands in China
Authors: Shen Zhifeng , Yang Xirui , Liu Chunlu , Li Junjie
Published: April 2021

Guests’ evaluation of indoor environmental quality (IEQ) is important for identifying environment quality problems in hotels and improving service quality. This paper aims to identify IEQ problems in budget hotels in China and improve them. Specifically, 2.06 million online reviews of budget hotels were used to assess IEQ issues in China’s budget hotels in four areas: acoustic environment, luminous environment, indoor air quality (IAQ) and thermal environment. The influences of the season, region and type of customers on the IEQ evaluation were also explored, and the main causes of IEQ problems were also identified. The research results show that the IEQ complaint rates of budget hotels are relatively high. In particular, complaints about the acoustic environment are more common. Differences in seasons and climate zones have significant effects on complaints about the acoustic environment, thermal environment and IAQ. Different types of customers have different concerns about hotel IEQ, among which solo travelers and traveling couples have higher requirements for IEQ. The occurrence of IEQ problems significantly reduces a hotel’s online rating, with IAQ and the thermal environment having the greatest impacts, but the causal factors that trigger IEQ problems are relatively concentrated. The findings of this paper can provide a reference for assessing IEQ problems in hotel buildings and guide hotel managers to adopt targeted IEQ improvement programs to promote sustainable development in the hotel industry.
BIM and IoT Sensors Integration: A Framework for Consumption and Indoor Conditions Data Monitoring of Existing Buildings
Authors: Desogus Giuseppe , Quaquero Emanuela , Rubiu Giulia , Gatto Gianluca , Perra Cristian
Published: April 2021

The low accessibility to the information regarding buildings current performances causes deep difficulties in planning appropriate interventions. Internet of Things (IoT) sensors make available a high quantity of data on energy consumptions and indoor conditions of an existing building that can drive the choice of energy retrofit interventions. Moreover, the current developments in the topic of the digital twin are leading the diffusion of Building Information Modeling (BIM) methods and tools that can provide valid support to manage all data and information for the retrofit process. This paper shows the aim and the findings of research focused on testing the integrated use of BIM methodology and IoT systems. A common data platform for the visualization of building indoor conditions (e.g., temperature, luminance etc.) and of energy consumption parameters was carried out. This platform, tested on a case study located in Italy, is developed with the integration of low-cost IoT sensors and the Revit model. To obtain a dynamic and automated exchange of data between the sensors and the BIM model, the Revit software was integrated with the Dynamo visual programming platform and with a specific Application Programming Interface (API). It is an easy and straightforward tool that can provide building managers with real-time data and information about the energy consumption and the indoor conditions of buildings, but also allows for viewing of the historical sensor data table and creating graphical historical sensor data. Furthermore, the BIM model allows the management of other useful information about the building, such as dimensional data, functions, characteristics of the components of the building, maintenance status etc., which are essential for a much more conscious, effective and accurate management of the building and for defining the most suitable retrofit scenarios.
Regenerating the Historic Urban Landscape through Circular Bottom-Up Actions: The Urban Seeding Process in Rijeka
Authors: Acri Marco , Dobričić Saša , Debevec Maja
Published: April 2021

The increasing pressure on urban resilience and the parallel interest in the preservation of the Historic Urban Landscape (HUL) have opened new frontiers of research that find, in the principles of the circular economy, good responses. Cities need to remake themselves from pure consumption to more resilient and circular centers, finding inspiration in their cultural and natural heritage and the history that generated it. The City of Rijeka, Croatia, one of the partners in the CLIC project (an EU-funded Horizon 2020 research project entitled “Circular models Leveraging Investments in Cultural heritage adaptive reuse”), represents an exceptional example of how to manage the change from an industrial port city to a more sustainable and citizen-oriented living space, looking at the potentials of the cultural and historical layers as opportunities for the population. The City of Rijeka, aware of such potentials, applied successfully as a European Capital of Culture 2020 (ECoC 2020), while unlikely facing the negative impacts of the COVID-19 pandemic. In Rijeka, thanks to the CLIC Heritage Innovative Partnership (HIP) program, the efforts to associate the circular economy and historic urban landscape benefit from an exceptional local awareness of the urban cultural and natural heritage, permitting the elaboration of the cultural corridor concept. By using the historical river of the city, the Rječina, as a connecting line of several heritage assets leading toward the Sea waterfront, the cultural corridor represents a space of culture creation based on continuity and proximity, where all citizens can securely reappropriate dismissed parts of the city, similar to the commons’ management practice. The cultural corridor has been imagined as a spatial implementation model that needs actions to be actuated. A set of actions was designed through the urban seeding process, tested in a workshop methodology, meant to address the HUL regeneration through an awareness-raising and cocreation approach by codesigning through situated learning, possible permanent or temporary actions, activities, assets to be replicated in the corridor and, per extension, in the entire city. This article will explain the way the cultural corridor concept and urban seeding were generated in the City of Rijeka, giving evidence of the motivations and the proposals made in parallel with the existing initiatives of the city and its cultural movements.
Integrating Mathematics and Science Teaching in the Context of Education for Sustainable Development: Design and Pilot Implementation of a Teaching-Learning Sequence about Air Quality with Pre-Service Primary Teachers
Authors: Rico Arantza , Agirre-Basurko Elena , Ruiz-González Aritz , Palacios-Agundez Igone , Zuazagoitia Daniel
Published: April 2021

This article presents an interdisciplinary teaching–learning sequence (TLS) about air quality for pre-service primary teachers using an organic learning garden. The design involved a curricular integration of concepts and competences about sustainability, mathematics, and science disciplines following constructivist and active learning strategies, such as problem-based learning and place-based education. In this TLS, both the topic and the learning context act as facilitators of education for sustainable development (ESD). The contents address the overarching STEM and sustainability concepts related to air pollutants, weather, and climate. Our results show that students learned about a STEM topic within a space and context that enables ESD. Several misconceptions related to air quality, weather, and statistics were identified through the evaluation of students’ initial ideas. Furthermore, students’ attitudes towards the topic of study and self-efficacy and perceived relevance of ESD improved after the implementation. These results will guide further improvements of the designed TLS, which connects STEM education and ESD as a transformative educational experience for pre-service teachers. In this sense, we conclude that such initiatives can improve pre-service primary teachers’ self-efficacy as agents of change towards sustainable development goals.
Stabilisation of a Plastic Soil with Alkali Activated Cements Developed from Industrial Wastes
Authors: Cristelo Nuno , Rivera Jhonathan , Miranda Tiago , Fernández-Jiménez Ana
Published: April 2021

The development of alternative materials for the construction industry, based on different types of waste, is gaining significant importance in recent years. This is mostly due to the need to increase sustainability of this heavily polluting activity, thus mitigating the dependence on, for instance, Portland cement. The present paper is related to the development of an alkaline activated cement (AAC) exclusively fabricated from industrial by-products (both precursor and activator). Coal combustion fly ash, a common residue from thermoelectric powerplants, and glass waste, from the manufacture of ophthalmic lenses, were used as precursors. These precursors were activated with a recycled alkaline solution, resulting from the cleaning of aluminium extrusion dies, instead of the more common commercial reagents usually applied for this type of binder. Several pastes were studied, combining the precursor and alkaline solution in different proportions. When the most-performing cements were defined, they were used to stabilise a cohesive soil. The experimental procedure and subsequent analysis were designed based on a Response Surface Methodology model, considering the Activator/Solids and Soil/Precursor ratios as the most relevant variables of the stabilisation process. It was observed that, depending on the type of alkaline cement used, there was an optimum precursor and activator contents to optimise the mechanical properties of the stabilised soil. The reliability of this prediction was especially dependent on the type of precursors and, also, on their respective dissolution process right before the homogenization with the soil, under the working conditions available.
Effect of Natural and Chemical Colorant Supplementation on Performance, Egg-Quality Characteristics, Yolk Fatty-Acid Profile, and Blood Constituents in Laying Hens
Authors: Saleh Ahmed A. , Gawish Esraa , Mahmoud Samy F. , Amber Khairy , Awad Wael , Alzawqari Mohammed H. , Shukry Mustafa , Abdel-Moneim Abdel-Moneim Eid
Published: April 2021

Natural and chemical colorants are attracting a lot of attention as sustainable feed additives due to their effect on food color and because presentation matters to consumers. Color also is a major sensory factor that helps consumers determine food quality and its possible health benefits. For example, highly colored egg yolks can only come from healthy laying hens fed a well-balanced, nutrient-rich diet. Consumers associate an intense yolk color with healthy, nutrient-rich food. There is a growing market request for eggs with rich yolk coloring. The purpose of the current study was to evaluate the impact of natural (paprika) and chemical (carmoisine) colorant supplementation on the performance, egg-quality characteristics, yolk fatty-acid profile, and blood constituents in laying hens. A total of 240 Bovans laying hens were randomly distributed in a completely randomized design in four treatments according to four experimental diets: a control diet (without supplementation of any colorants), a control diet supplemented with 4 kg/ton paprika, a control diet supplemented with 150 g carmoisine/ton, and a control diet supplemented with a combination of 4 kg/ton paprika plus 150 g carmoisine/ton, fed from 42 to 54 weeks of age. Each treatment consisted of 10 replications with six hens. Dietary inclusion of paprika colorant improved (p < 0.05) the feed-conversion ratio and egg-production rate, while final body weight, weight change, feed intake, and egg weight and mass were not affected. The degrees of egg yolk and white were increased (p < 0.05) by the dietary supplements. Yolk color and shell thickness were enhanced (p < 0.05) by adding paprika and/or carmoisine colorants. Supplementation of the paprika colorant alone or in combination with carmoisine increased (p < 0.05) linolenic acid, oleic acid, and vitamin E concentrations in egg yolks. In contrast, egg yolk palmitic acid and liver malondialdehyde contents were decreased (p < 0.05). Paprika and carmoisine colorants and their combination improved (p < 0.05) blood lipid profile in treated hens. We concluded that the dietary supplementation of natural (paprika) colorants has an influential role in improving egg yolk color, production performance, and egg yolk fatty-acid profile in laying hens.
Development of Emergent Knowledge Strategies and New Dynamic Capabilities for Business Education in a Time of Crisis
Authors: Tomé Eduardo , Gromova Elizaveta
Published: April 2021

The current pandemic is, above all, a crisis of knowledge—Humanity had to find a vaccine, and now we are not sure how to behave socially to minimize the pandemic bad effects. For organizations, this situation requires an update in the reflection regarding both the strategy and the actions that should be performed. Therefore, the current crisis requires new ways of applying knowledge strategies and dealing with dynamic capabilities. We first analyze the two questions (knowledge strategies and dynamic capabilities) in abstract and general terms, and then we specifically focus on business education during the COVID-19 crisis. We conclude that COVID-19 creates a need for all knowledge strategies in terms of business education. Data, information, knowledge, and wisdom will be needed; above all, it requires the Unknown-Knowns, which is the basis for Knowledge Sharing, and the Unknown-Unknowns that base Knowledge Exploration because both Knowledge Exploitation and Knowledge Acquisition are strategies business schools use to perform in times of crisis. They are more difficult to implement because both the Known-Knowns and the Known-Unknowns are less valuable to solve a crisis like this one: all this will result in “agile universities”, which will be (and already are) those that will use the right strategies and the right dynamic capabilities and will have better results. The paper is original because we link Knowledge Management and Human Resources Development Concepts to generate a broader and more comprehensive understanding of the organizational behavior about a very specific problem—business education—in a very specific time of the COVID-19 crisis. The limits of the paper relate to the evolution of society itself; we do not know when the crisis will end, and we are not sure how much of the “new normal” will remain in the “post-COVID-19” situation. The topic and analysis are of interest for practitioners because daily, they experience how their reality changed and their need to adapt, yet they do not know how. This topic and analysis are also of interest to scholars because science is based on questions, explaining and providing ways to improve one’s reality. COVID-19 has shown us, dramatically and uniquely, the need for new solutions in times of peace.
Ranking Locations for Hydrogen Production Using Hybrid Wind-Solar: A Case Study
Authors: Almutairi Khalid , Mostafaeipour Ali , Jahanshahi Ehsan , Jooyandeh Erfan , Himri Youcef , Jahangiri Mehdi , Issakhov Alibek , Chowdhury Shahariar , Hosseini Dehshiri Seyyed , Hosseini Dehshiri Seyyed , Techato Kuaanan
Published: April 2021

Observing the growing energy demand of modern societies, many countries have recognized energy security as a looming problem and renewable energies as a solution to this issue. Renewable hydrogen production is an excellent method for the storage and transfer of energy generated by intermittent renewable sources such as wind and solar so that they can be used at a place and time of our choosing. In this study, the suitability of 15 cities in Fars province, Iran, for renewable hydrogen production was investigated and compared by the use of multiple multi-criteria decision-making methods including ARAS, SAW, CODAS, and TOPSIS. The obtained rankings were aggregated by rank averaging, Borda method, and Copeland method. Finally, the partially ordered set ranking technique was used to reach a general consensus about the ranking. The criteria that affect hydrogen production were found to be solar energy potential, wind energy potential, population, air temperature, natural disasters, altitude, relative humidity, land cost, skilled labor, infrastructure, topographic condition, and distance from main roads. These criteria were weighted using the best–worst method (BWM) based on the data collected by a questionnaire. Solar energy potential was estimated using the Angstrom model. Wind energy potential was estimated by using the Weibull distribution function for each month independently. The results of the multi-criteria decision-making methods showed Izadkhast to be the most suitable location for renewable hydrogen production in the studied area.
An NN-Based Double Parallel Longitudinal and Lateral Driving Strategy for Self-Driving Transport Vehicles in Structured Road Scenarios
Authors: Xiong Huiyuan , Liu Huan , Ma Jian , Pan Yuelong , Zhang Ronghui
Published: April 2021

Studies on self-driving transport vehicles have focused on longitudinal and lateral driving strategies in automated structured road scenarios. In this study, a double parallel network (DP-Net) combined with longitudinal and lateral strategy networks is constructed for self-driving transport vehicles in structured road scenarios, which is based on a convolutional neural network (CNN) and a long short-term memory network (LSTM). First, in feature extraction and perception, a preprocessing module is introduced that can ensure the effective extraction of visual information under complex illumination. Then, a parallel CNN sub-network is designed that is based on multifeature fusion to ensure better autonomous driving strategies. Meanwhile, a parallel LSTM sub-network is designed, which uses vehicle kinematic features as physical constraints to improve the prediction accuracy for steering angle and speed. The Udacity Challenge II dataset is used as the training set with the proposed DP-Net input requirements. Finally, for the proposed DP-Net, the root mean square error (RMSE) is used as the loss function, the mean absolute error (MAE) is used as the metric, and Adam is used as the optimization method. Compared with competing models such as PilotNet, CgNet, and E2E multimodal multitask network, the proposed DP-Net is more robust in handling complex illumination. The RMSE and MAE values for predicting the steering angle of the E2E multimodal multitask network are 0.0584 and 0.0163 rad, respectively; for the proposed DP-Net, those values are 0.0107 and 0.0054 rad, i.e., 81.7% and 66.9% lower, respectively. In addition, the proposed DP-Net also has higher accuracy in speed prediction. Upon testing the collected SYSU Campus dataset, good predictions are also obtained. These results should provide significant guidance for using a DP-Net to deploy multi-axle transport vehicles.
From Goods to Services and from Linear to Circular: The Role of Servitization’s Challenges and Drivers in the Shifting Process
Authors: Hidalgo-Carvajal David , Carrasco-Gallego Ruth , Morales-Alonso Gustavo
Published: April 2021

To move closer to achieving the United Nations’ Sustainable Development Goals (SDGs), a change from the traditional paradigm of the linear economy towards the circular economy is of paramount importance. One of the key promoters of this shift is servitization, which involves a shift from a purely transactional product-selling model to customer satisfaction through providing the service inherent to the product. Although servitization is a promising field for academics and practitioners, its adoption faces different challenges and drivers that need to be understood and addressed. A latent issue is the lack of common language around the topic. In the present study, a systematic literature review has been conducted to allow the identification and classification of the main challenges and drivers. Based on the findings, we propose a classification framework that identifies, classifies, and groups common challenges and drivers to different areas of knowledge on servitization through intensity heat maps. From a managerial point of view, our results highlight the importance of embracing servitization as a collective effort from the different departments within a company.
Regional-Scale Landslide Susceptibility Mapping Using Limited LiDAR-Based Landslide Inventories for Sisak-Moslavina County, Croatia
Authors: Bostjančić Iris , Filipović Marina , Gulam Vlatko , Pollak Davor
Published: April 2021

In this paper, for the first time, a regional-scale 1:100,000 landslide-susceptibility map (LSM) is presented for Sisak-Moslavina County in Croatia. The spatial relationship between landslide occurrence and landslide predictive factors (engineering geological units, relief, roughness, and distance to streams) is assessed using the integration of a statistically based frequency ratio (FR) into the analytical hierarchy process (AHP). Due to the lack of landslide inventory for the county, LiDAR-based inventories are completed for an area of 132 km2. From 1238 landslides, 549 are chosen to calculate the LSM and 689 for its verification. Additionally, landslides digitized from available geological maps and reported via the web portal “Report a landslide” are used for verification. The county is classified into four susceptibility classes, covering 36% with very-high and high and 64% with moderate and low susceptibility zones. The presented approach, using limited LiDAR data and the extrapolation of the correlation results to the entire county, is encouraging for primary regional-level studies, justifying the cost-benefit ratio. Still, the positioning of LiDAR polygons prerequires a basic statistical analysis of predictive factors.
On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model
Authors: Salamone Sara , Lenzo Basilio , Lutzemberger Giovanni , Bucchi Francesco , Sani Luca
Published: April 2021

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.
Particulate Matter Short-Term Exposition, Mobility Trips and COVID-19 Diffusion: A Correlation Analyses for the Italian Case Study at Urban Scale
Authors: Cartenì Armando , Cascetta Furio , Di Francesco Luigi , Palermo Felisia
Published: April 2021

The conjecture discussed in this paper was that the daily number of certified cases of COVID-19 is direct correlated to the average particular matter (PM) concentrations observed several days before when the contagions occurred (short-term effect), and this correlation is higher for areas with a higher average seasonal PM concentration, as a measure of prolonged exposure to a polluted environment (long-term effect). Furthermore, the correlations between the daily COVID-19 new cases and the mobility trips and those between the daily PM concentrations and mobility trips were also investigated. Correlation analyses were performed for the application case study consisting in 13 of the main Italian cities, through the national air quality and mobility monitoring systems. Data analyses showed that the mobility restrictions performed during the lockdown produced a significant improvement in air quality with an average PM concentrations reduction of about 15%, with maximum variations ranging between 25% and 42%. Estimation results showed a positive correlation (stronger for the more highly polluted cities) between the daily COVID-19 cases and both the daily PM concentrations and mobility trips measured about three weeks before, when probably the contagion occurred. The obtained results are original, and if confirmed in other studies, it would lay the groundwork for the definition of the main context variables which influenced the COVID-19 spread. The findings highlighted in this research also supported by the evidence in the literature and allow concluding that PM concentrations and mobility habits could be considered as potential early indicators of COVID-19 circulation in outdoor environments. However, the obtained results pose significant ethical questions about the proper urban and transportation planning; the most polluted cities have not only worst welfare for their citizens but, as highlighted in this research, could lead to a likely greater spread of current and future respiratory and/or pulmonary health emergencies. The lesson to be learned by this global pandemic will help planners to better preserve the air quality of our cities in the post-COVID-19 era.
How the SP System May Promote Sustainability in Energy Consumption in IT Systems
Authors: Wolff J. Gerard
Published: April 2021

The SP System (SPS), referring to the SP Theory of Intelligence and its realisation as the SP Computer Model, has the potential to reduce demands for energy from IT, especially in AI applications and in the processing of big data, in addition to reductions in CO2 emissions when the energy comes from the burning of fossil fuels. The biological foundations of the SPS suggest that with further development, the SPS may approach the extraordinarily low (20 W)energy demands of the human brain. Some of these savings may arise in the SPS because, like people, the SPS may learn usable knowledge from a single exposure or experience. As a comparison, deep neural networks (DNNs) need many repetitions, with much consumption of energy, for the learning of one concept. Another potential saving with the SPS is that like people, it can incorporate old learning in new. This contrasts with DNNs where new learning wipes out old learning (‘catastrophic forgetting’). Other ways in which the mature SPS is likely to prove relatively parsimonious in its demands for energy arise from the central role of information compression (IC) in the organisation and workings of the system: by making data smaller, there is less to process; because the efficiency of searching for matches between patterns can be improved by exploiting probabilities that arise from the intimate connection between IC and probabilities; and because, with SPS-derived ’Model-Based Codings’ of data, there can be substantial reductions in the demand for energy in transmitting data from one place to another.
Information Transmission Mechanism of Inequality of Opportunity and Effort on Settlement Intention
Authors: Gao Junjie , Feng Lyubing , Yao Xianguo
Published: April 2021

China is promoting sustainable economic development through urbanisation, but migrants’ low settlement intention has become an obstacle to the urbanisation process. The key leading to this problem is that the current economic system lacks an index with high information transparency to convey the characteristics of the destination city, so that migrants’ choice of settling city is a kind of act of chance. By referring to Roemer’s equality of opportunity theory, this paper takes the indexes of inequality of opportunity (IO) and inequality of effort (IE) of the destination as market signals representing the characteristics information of destination, innovatively proposes an information transmission mechanism to improve migrants’ settlement intention. According to the IO and IE of the destination, migrants can effectively identify the economic incentive modes and social characteristics of the destination city before migration, and then make an accurate judgment on the possibility of realizing income growth and social integration in the destination. The feasibility of this mechanism was verified by the data of China Labor-force Dynamics Survey (CLDS). The result indicates that IO and IE can indeed convey information about economic incentives of the destination and attract migrants to settle down there. In addition, IE can convey positive messages on two social characteristics of the destination, namely, promotion fairness and social network, while IO sends negative messages on both aspects. Cities that plan to expand their population scale can leverage this mechanism to optimise their IO and IE indexes, so as to attract migrants to settle down in the city.
Machine-Learning Based Memory Prediction Model for Data Parallel Workloads in Apache Spark
Authors: Myung Rohyoung , Choi Sukyong
Published: April 2021

A lack of memory can lead to job failures or increase processing times for garbage collection. However, if too much memory is provided, the processing time is only marginally reduced, and most of the memory is wasted. Many big data processing tasks are executed in cloud environments. When renting virtual resources in a cloud environment, it is necessary to pay the cost according to the specifications of resources (i.e., the number of virtual cores and the size of memory), as well as rental time. In this paper, given the type of workload and volume of the input data, we analyze the memory usage pattern and derive the efficient memory size of data-parallel workloads in Apache Spark. Then, we propose a machine-learning-based prediction model that determines the efficient memory for a given workload and data. To determine the validity of the proposed model, we applied it to data-parallel workloads which include a deep learning model. The predicted memory values were in close agreement with the actual amount of required memory. Additionally, the whole building time for the proposed model requires a maximum of 44% of the total execution time of a data-parallel workload. The proposed model can improve memory efficiency up to 1.89 times compared with the vanilla Spark setting.
A Statistical Analysis of Observational Hubble Parameter Data to Discuss the Cosmology of Holographic Chaplygin Gas
Authors: Sarkar Amrita , Chattopadhyay Surajit , Güdekli Ertan
Published: April 2021

A scheme for the generalized Chaplygin gas equation of state is shown by using the holographic Ricci dark energy. Regression analysis and a chi-square test were performed. A second order polynomial regression has been established as the relation between the Hubble Parameter and redshift. It has established a set of parameters that can predict the Equation of State (EoS) parameter.
Multi-Objective Caching Optimization for Wireless Backhauled Fog Radio Access Network
Authors: Bani-Bakr Alaa , Hindia MHD Nour , Dimyati Kaharudin , Hanafi Effariza , Tengku Mohmed Noor Izam Tengku Faiz
Published: April 2021

Proactive content caching in a fog radio access network (F-RAN) is an efficient technique used to alleviate delivery delay and traffic congestion. However, the symmetric caching of the content is impractical due to the dissimilarity among the contents popularity. Therefore, in this paper, a multi-objective random caching scheme to balance the successful transmission probability (STP) and delay in wireless backhauled F-RAN is proposed. First, stochastic geometry tools are utilized to derive expressions of the association probability, STP, and average delivery delay. Next, the complexity is reduced by considering the asymptotic STP and delay in the high signal-to-noise ratio (SNR) regime. Then, aiming at maximizing the STP or minimizing the delay, the multi-objective cache placement optimization problem is formulated. A novel projected multi-objective cuckoo search algorithm (PMOCSA) is proposed to obtain the Pareto front of the optimal cache placement. The numerical results show that PMOCSA outperforms the original multi-objective cuckoo search algorithm (MOCSA) in terms of convergence to a feasible Pareto front and its rate. It also shows that the proposed multi-objective caching scheme significantly outperforms the well-known benchmark caching schemes by up to 40% higher STP and 85% lower average delay.
Sensitivity Analysis of Key Formulations of Topology Optimization on an Example of Cantilever Bending Beam
Authors: Sotola Martin , Marsalek Pavel , Rybansky David , Fusek Martin , Gabriel Dusan
Published: April 2021

Topology optimization is a modern method for optimizing the material distribution in a given space, automatically searching for the ideal design of the product. The method aims to maximize the design performance of the system regarding given conditions. In engineering practice, a given space is first described using the finite element method and, subsequently, density-based method with solid isotropic material with penalty. Then, the final shape is found using a gradient-based method, such as the optimality criteria algorithm. However, obtaining the ideal shape is highly dependent on the correct setting of numerical parameters. This paper focuses on the sensitivity analysis of key formulations of topology optimization using the implementation of mathematical programming techniques in MATLAB software. For the purposes of the study, sensitivity analysis of a simple spatial task—cantilever bending—is performed. This paper aims to present the formulations of the optimization problem—in this case, minimization of compliance. It should be noted that this paper does not present any new mathematical formulas but rather provides an introduction into the mathematical theory (including filtering methods and calculating large-size problems using the symmetry of matrices) as well as a step-by step guideline for the minimization of compliance within the density-based topology optimization and search for an optimal shape. The results can be used for complex commercial applications produced by traditional manufacturing processes or by additive manufacturing methods.
Fixed Points Theorems for Unsaturated and Saturated Classes of Contractive Mappings in Banach Spaces
Authors: Berinde Vasile , Păcurar Mădălina
Published: April 2021

Based on the technique of enriching contractive type mappings, a technique that has been used successfully in some recent papers, we introduce the concept of a saturated class of contractive mappings. We show that, from this perspective, the contractive type mappings in the metric fixed point theory can be separated into two distinct classes, unsaturated and saturated, and that, for any unsaturated class of mappings, the technique of enriching contractive type mappings provides genuine new fixed-point results. We illustrate the concept by surveying some significant fixed-point results obtained recently for five remarkable unsaturated classes of contractive mappings. In the second part of the paper, we also identify two important classes of saturated contractive mappings, whose main feature is that they cannot be enlarged by enriching the contractive mappings.
Multiscale Thermodynamics: Energy, Entropy, and Symmetry from Atoms to Bulk Behavior
Authors: Chamberlin Ralph , Clark Michael , Mujica Vladimiro , Wolf George
Published: April 2021

Here, we investigate how the local properties of particles in a thermal bath may influence the thermodynamics of the bath, and consequently alter the statistical mechanics of subsystems that comprise the bath. We are guided by the theory of small-system thermodynamics, which is based on two primary postulates: that small systems can be treated self-consistently by coupling them to an ensemble of similarly small systems, and that a large ensemble of small systems forms its own thermodynamic bath. We adapt this “nanothermodynamics” to investigate how a large system may subdivide into an ensemble of smaller subsystems, causing internal heterogeneity across multiple size scales. For the semi-classical ideal gas, maximum entropy favors subdividing a large system of “atoms” into an ensemble of “regions” of variable size. The mechanism of region formation could come from quantum exchange symmetry that makes atoms in each region indistinguishable, while decoherence between regions allows atoms in separate regions to be distinguishable by their distinct locations. Combining regions reduces the total entropy, as expected when distinguishable particles become indistinguishable, and as required by a theorem in quantum mechanics for sub-additive entropy. Combining large volumes of small regions gives the usual entropy of mixing for a semi-classical ideal gas, resolving Gibbs paradox without invoking quantum symmetry for particles that may be meters apart. Other models presented here are based on Ising-like spins, which are solved analytically in one dimension. Focusing on the bonds between the spins, we find similarity in the equilibrium properties of a two-state model in the nanocanonical ensemble and a three-state model in the canonical ensemble. Thus, emergent phenomena may alter the thermal behavior of microscopic models, and the correct ensemble is necessary for fully-accurate predictions. Another result using Ising-like spins involves simulations that include a nonlinear correction to Boltzmann’s factor, which mimics the statistics of indistinguishable states by imitating the dynamics of spin exchange on intermediate lengths. These simulations exhibit 1/f-like noise at low frequencies (f), and white noise at higher f, similar to the equilibrium thermal fluctuations found in many materials.
Trace Level Determination of Saccharides in Pristine Marine Aerosols by Gas Chromatography—Tandem Mass Spectrometry
Authors: Choi Na-Rae , Yoon Yong-Jun , Park Ki-Tae , Kim Ki-Ae , Kim Yong-Pyo , Ahn Yun-Gyong , Lee Ji-Yi
Published: April 2021

The quantification and identification of saccharides in pristine marine aerosols can provide useful information for determining the contributions of anthropogenic and natural sources of the aerosol. However, individual saccharide compounds in pristine marine aerosols that exist in trace amounts are difficult to analyze due to their low concentrations. Thus, in this study, we applied gas chromatography–tandem mass spectrometry (GC-MS/MS) in multiple reaction monitoring (MRM) mode to analyze the particulate matter with an aerodynamic diameter equal or less than 2.5 μm (PM2.5) samples, and the results were compared with those of conventional GC-MS. To investigate the chemical properties of pristine marine aerosols, 12 PM2.5 samples were collected while aboard Araon, an ice-breaking research vessel (IBRV), as it sailed from Incheon, South Korea to Antarctica. The method detection limits of GC-MS/MS for 10 saccharides were 2–22-fold lower than those of GC-MS. Consequently, the advantages of GC-MS/MS include (1) more distinct peak separations, enabling the accurate identification of the target saccharides and (2) the quantification of all individual saccharide compounds with concentrations outside the quantifiable range of GC-MS. Accordingly, the time resolution for sampling saccharides in pristine marine aerosols can be improved with GC-MS/MS.
Occurrence and Human Health Risk Assessment of Pharmaceuticals and Hormones in Drinking Water Sources in the Metropolitan Area of Turin in Italy
Authors: Papagiannaki Dimitra , Morgillo Stefania , Bocina Gianluca , Calza Paola , Binetti Rita
Published: April 2021

Pharmaceuticals and hormones (PhACs) enter the aquatic environment in multiple ways, posing potential adverse effects on non-target organisms. They have been widely detected in drinking water sources, challenging water companies to reassure good quality drinking water. The aim of this study was to evaluate the concentration of sixteen PhACs in both raw and treated drinking water sources in the Metropolitan Area of Turin—where Società Metropolitana Acque Torino (SMAT) is the company in charge of the water cycle management—and evaluate the potential human health risks associated to these compounds. Multivariate spatial statistical analysis techniques were used in order to characterize the areas at higher risk of pollution, taking into account the already existing SMAT sampling points’ network. Health risks were assessed considering average detected concentrations and provisional guideline values for individual compounds as well as their combined mixture. As reported in the just-issued Drinking Water Directive 2020/2184/UE, in order to establish priority substances, a risk assessment of contaminants present in raw drinking water sources is required for monitoring, identifying potential health risks and, if necessary, managing their removal. The results showed negligibly low human health risks in both raw water sources and treated water.
Adaptive Evolution of New Variants of Dengue Virus Serotype 1 Genotype V Circulating in the Brazilian Amazon
Authors: Ribeiro Geovani de Oliveira , Gill Danielle Elise , Ribeiro Edcelha Soares D’Athaide , Monteiro Fred Julio Costa , Morais Vanessa S. , Marcatti Roberta , Rego Marlisson Octavio da S. , Araújo Emerson Luiz Lima , Witkin Steven S. , Villanova Fabiola , Deng Xutao , Sabino Ester Cerdeira , Delwart Eric , Leal Élcio , da Costa Antonio Charlys
Published: April 2021

Dengue virus (DENV) is a mosquito-borne viral pathogen that plagues many tropical-climate nations around the world, including Brazil. Molecular epidemiology is a growing and increasingly invaluable tool for understanding the dispersal, persistence, and diversity of this impactful virus. In this study, plasma samples (n = 824) from individuals with symptoms consistent with an arboviral febrile illness were analyzed to identity the molecular epidemiological dynamics of DENV circulating in the Brazilian state of Amapá. Twelve DENV type 1 (DENV-1) genomes were identified, which were phylogenetically related to the BR4 lineage of genotype V. Phylodynamics analysis suggested that DENV-1 BR-4 was introduced into Amapá around early 2010, possibly from other states in northern Brazil. We also found unique amino acids substitutions in the DENV-1 envelope and NS5 protein sequences in the Amapá isolates. Characterization of the DENV-1 BR-4 sequences highlights the potential of this new lineage to drive outbreaks of dengue in the Amazon region.
Development of an RT-LAMP Assay for the Rapid Detection of SFTS Virus
Authors: Sano Shiori , Fukushi Shuetsu , Yamada Souichi , Harada Shizuko , Kinoshita Hitomi , Sugimoto Satoko , Yoshikawa Tomoki , Kurosu Takeshi , Takamatsu Yuki , Shimojima Masayuki , Toda Shoichi , Hamada Yuka , Fujisawa Naoki , Sugimoto Takayuki , Saijo Masayuki
Published: April 2021

Detection of severe fever with thrombocytopenia syndrome (SFTS) virus (SFTSV) during the early phase of the disease is important for appropriate treatment, infection control, and prevention of further transmission. The reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a nucleic acid amplification method that amplifies the target sequence under isothermal conditions. Here, we developed an RT-LAMP with a novel primer/probe set targeting a conserved region of the SFTSV L segment after extraction of viral RNA (standard RT-LAMP). Both the Chinese and Japanese SFTSV strains, including various genotypes, were detected by the standard RT-LAMP. We also performed RT-LAMP using the same primer/probe set but without the viral RNA extraction step (called simplified RT-LAMP) and evaluated the diagnostic efficacy. The sensitivity and specificity of the simplified RT-LAMP were 84.9% (45/53) and 89.5% (2/19), respectively. The simplified RT-LAMP can detect SFTSV in human sera containing >103.5 copies/mL viral RNA. The two RT-LAMP positive but quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) negative samples were positive in the conventional RT-PCR, suggesting that there was no false positive reaction in the RT-LAMP. Both the standard and simplified RT-LAMP are useful for detecting the SFTSV genome in patients during the early phase of the disease.
Characteristics of Anti-SARS-CoV-2 Antibodies in Recovered COVID-19 Subjects
Authors: Huynh Angela , Arnold Donald M. , Smith James W. , Moore Jane C. , Zhang Ali , Chagla Zain , Harvey Bart J. , Stacey Hannah D. , Ang Jann C. , Clare Rumi , Ivetic Nikola , Chetty Vasudhevan T. , Bowdish Dawn M. E. , Miller Matthew S. , Kelton John G. , Nazy Ishac
Published: April 2021

Coronavirus Disease 2019 (COVID-19) is a global pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While detection of SARS-CoV-2 by polymerase chain reaction with reverse transcription (RT-PCR) is currently used to diagnose acute COVID-19 infection, serological assays are needed to study the humoral immune response to SARS-CoV-2. Anti-SARS-CoV-2 immunoglobulin (Ig)G/A/M antibodies against spike (S) protein and its receptor-binding domain (RBD) were characterized in recovered subjects who were RT-PCR-positive (n = 153) and RT-PCR-negative (n = 55) using an enzyme-linked immunosorbent assay (ELISA). These antibodies were also further assessed for their ability to neutralize live SARS-CoV-2 virus. Anti-SARS-CoV-2 antibodies were detected in 90.9% of resolved subjects up to 180 days post-symptom onset. Anti-S protein and anti-RBD IgG titers correlated (r = 0.5157 and r = 0.6010, respectively) with viral neutralization. Of the RT-PCR-positive subjects, 22 (14.3%) did not have anti-SARS-CoV-2 antibodies; and of those, 17 had RT-PCR cycle threshold (Ct) values > 27. These high Ct values raise the possibility that these indeterminate results are from individuals who were not infected or had mild infection that failed to elicit an antibody response. This study highlights the importance of serological surveys to determine population-level immunity based on infection numbers as determined by RT-PCR.