bluuebunny/crossref_metadata_2025 huggingface dataset:
Evolution of the Upper Reaches of Fluvial Systems within the Area of the East European Plain Glaciated during MIS 6
Authors: Panin Andrey , Borisova Olga , Belyaev Vladimir , Belyaev Yuri , Eremenko Ekaterina , Fuzeina Yulia , Sheremetskaya Elena , Sidorchuk Aleksey
Published: February 2022

The headwaters of fluvial systems on the East European Plain between the boundaries of the Marine Isotope Stage 2 (MIS 2) and MIS 6 glaciations evolved during the last 150,000 years. At least three main events of high surface runoff caused intensive erosion: at the end of MIS 6, at the end of MIS 2 and in the Middle Holocene. Erosion developed in the territory with variable resistance of geological substrate, from hard-to-erode tills to weak sandy deposits. All erosional features in moraines formed in the pre-Holocene time. Even relatively large forms, such as balkas (small dry valleys), have not yet reached concave longitudinal profiles. A general tendency of their development was deepening. Short episodes of incision occurring during climatic events with increased water flow alternated with long periods of stabilization. Sand-covered areas are most favorable for linear erosion. The gullies formed in the Middle Holocene developed concave longitudinal profiles. The diversity of catchment areas, initial slope inclinations and sediment properties causing their resistance to erosion led to greater differences in the relief features and evolution of the upper reaches of the fluvial systems within the MIS 6 glaciation area compared to the more uniform landscape conditions in the extraglacial regions.
OC4-SO: A New Chlorophyll-a Algorithm for the Western Antarctic Peninsula Using Multi-Sensor Satellite Data
Authors: Ferreira Afonso , Brito Ana C. , Mendes Carlos R. B. , Brotas Vanda , Costa Raul R. , Guerreiro Catarina V. , Sá Carolina , Jackson Thomas
Published: February 2022

Chlorophyll-a (Chl-a) underestimation by global satellite algorithms in the Southern Ocean has long been reported, reducing their accuracy, and limiting the potential for evaluating phytoplankton biomass. As a result, several regional Chl-a algorithms have been proposed. The present work aims at assessing the performance of both global and regional satellite algorithms that are currently available for the Western Antarctic Peninsula (WAP) and investigate which factors are contributing to the underestimation of Chl-a. Our study indicates that a global algorithm, on average, underestimates in-situ Chl-a by ~59%, although underestimation was only observed for waters with Chl-a > 0.5 mg m−3. In high Chl-a waters (>1 mg m−3), Chl-a underestimation rose to nearly 80%. Contrary to previous studies, no clear link was found between Chl-a underestimation and the pigment packaging effect, nor with the phytoplankton community composition and sea ice contamination. Based on multi-sensor satellite data and the most comprehensive in-situ dataset ever collected from the WAP, a new, more accurate satellite Chl-a algorithm is proposed: the OC4-SO. The OC4-SO has great potential to become an important tool not only for the ocean colour community, but also for an effective monitoring of the phytoplankton communities in a climatically sensitive region where in-situ data are scarce.
LiDAR Voxel-Size Optimization for Canopy Gap Estimation
Authors: Ross C. Wade , Loudermilk E. Louise , Skowronski Nicholas , Pokswinski Scott , Hiers J. Kevin , O’Brien Joseph
Published: February 2022

Terrestrial laser scanning of forest structure is used increasingly in place of traditional technologies; however, deriving physical parameters from point clouds remains challenging because LiDAR returns do not have defined areas or volumes. While voxelization methods overcome this challenge, estimation of canopy gaps and other structural attributes are often performed by reducing the point cloud to two-dimensions, thus decreasing the fidelity of the data. Furthermore, relatively few studies have evaluated voxel-size effects on estimation accuracy. Here, we show that voxelized laser-scanning data can be used for canopy-gap estimation without performing dimensionality reduction to the point cloud. Both airborne and terrestrial LiDAR were used to estimate canopy gaps along six vertical transects and four height intervals. Voxel-based estimates were evaluated against hemispherical photography and a sensitivity analysis was performed to identify an optimal voxel size. While the results indicate that our approach can be used with both airborne and terrestrial LiDAR, voxel size has a considerable influence on canopy-gap estimation. Results from our sensitivity analysis indicate that TLS estimation performs best when using 10 cm voxels, yielding canopy gaps ranging from 32–78%. The optimal voxel size for ALS estimation was obtained with 25 cm voxels, yielding estimates ranging from 25–68%.
A Global Assessment of Night Lights as an Indicator for Shipping Activity in Anchorage Areas
Authors: Polinov Semion , Bookman Revital , Levin Noam
Published: February 2022

Accurate information on port shipping activities is critical for monitoring global and local traffic flows and assessing the state of development of the maritime industry. Such information is necessary for managers and analysts to make strategic decisions and monitor the maritime industry in achieving management goals. In this study, we used monthly night light (NTL) images of the Suomi National Polar-Orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band, between 2012 and 2020, to study the night lights emitted by ships in ports’ anchorage areas, as an indicator for shipping activity in anchorage areas and ports. Using a dataset covering 601 anchorage areas from 97 countries, we found a strong correspondence between NTL data and shipping metrics at the country level (n = 97), such as container port throughput (Rs = 0.84, p < 0.01) and maximum cargo carried by ships (Rs = 0.66, p < 0.01), as well as a strong correlation between the number of anchorage points and the NTL values in anchorage areas across the world (Rs = 0.69, p < 0.01; n = 601). The high correspondence levels of the VIIRS NTL data with various shipping indicators show the potential of using NTL data to analyze the spatio-temporal dynamic changes of the shipping activity in anchorage areas, providing convenient open access and a normalized assessment method for shipping industry parameters that are often lacking.
Smart-Sleeve: A Wearable Textile Pressure Sensor Array for Human Activity Recognition
Authors: Xu Guanghua , Wan Quan , Deng Wenwu , Guo Tao , Cheng Jingyuan
Published: February 2022

Human activity recognition is becoming increasingly important. As contact with oneself and the environment accompanies almost all human activities, a Smart-Sleeve, made of soft and stretchable textile pressure sensor matrix, is proposed to sense human contact with the surroundings and identify performed activities in this work. Additionally, a dataset including 18 activities, performed by 14 subjects in 10 repetitions, is generated. The Smart-Sleeve is evaluated over six classical machine learning classifiers (support vector machine, k-nearest neighbor, logistic regression, random forest, decision tree and naive Bayes) and a convolutional neural network model. For classical machine learning, a new normalization approach is proposed to overcome signal differences caused by different body sizes and statistical, geometric, and symmetry features are used. All classification techniques are compared in terms of classification accuracy, precision, recall, and F-measure. Average accuracies of 82.02% (support vector machine) and 82.30% (convolutional neural network) can be achieved in 10-fold cross-validation, and 72.66% (support vector machine) and 74.84% (convolutional neural network) in leave-one-subject-out validation, which shows that the Smart-Sleeve and the proposed data processing method are suitable for human activity recognition.
Applying Spring Security Framework with KeyCloak-Based OAuth2 to Protect Microservice Architecture APIs: A Case Study
Authors: Chatterjee Ayan , Prinz Andreas
Published: February 2022

In this study, we implemented an integrated security solution with Spring Security and Keycloak open-access platform (SSK) to secure data collection and exchange over microservice architecture application programming interfaces (APIs). The adopted solution implemented the following security features: open authorization, multi-factor authentication, identity brokering, and user management to safeguard microservice APIs. Then, we extended the security solution with a virtual private network (VPN), Blowfish and crypt (Bcrypt) hash, encryption method, API key, network firewall, and secure socket layer (SSL) to build up a digital infrastructure. To accomplish and describe the adopted SSK solution, we utilized a web engineering security method. As a case study, we designed and developed an electronic health coaching (eCoach) prototype system and hosted the system in the expanded digital secure infrastructure to collect and exchange personal health data over microservice APIs. We further described our adopted security solution’s procedural, technical, and practical considerations. We validated our SSK solution implementation by theoretical evaluation and experimental testing. We have compared the test outcomes with related studies qualitatively to determine the efficacy of the hybrid security solution in digital infrastructure. The SSK implementation and configuration in the eCoach prototype system has effectively secured its microservice APIs from an attack in all the considered scenarios with 100% accuracy. The developed digital infrastructure with SSK solution efficiently sustained a load of (≈)300 concurrent users. In addition, we have performed a qualitative comparison among the following security solutions: Spring-based security, Keycloak-based security, and their combination (our utilized hybrid security solution), where SSK showed a promising outcome.
Smart Multi-Sensor System for Remote Air Quality Monitoring Using Unmanned Aerial Vehicle and LoRaWAN
Authors: Camarillo-Escobedo Rosa , Flores Jorge L. , Marin-Montoya Pedro , García-Torales Guillermo , Camarillo-Escobedo Juana M.
Published: February 2022

Deaths caused by respiratory and cardiovascular diseases have increased by 10%. Every year, exposure to high levels of air pollution is the cause of 7 million premature deaths and the loss of healthy years of life. Air pollution is generally caused by the presence of CO, NO2, NH3, SO2, particulate matter PM10 and PM2.5, mainly emitted by economic activities in large metropolitan areas. The problem increases considerably in the absence of national regulations and the design, installation, and maintenance of an expensive air quality monitoring network. A smart multi-sensor system to monitor air quality is proposed in this work. The system uses an unmanned aerial vehicle and LoRa communication as an alternative for remote and in-situ atmospheric measurements. The instrumentation was integrated modularly as a node sensor to measure the concentration of carbon monoxide (CO), nitrogen dioxide (NO2), ammonia (NH3), sulfur dioxide (SO2), and suspended particulate mass PM10 and PM2.5. The optimal design of the multi-sensor system has been developed under the following constraints: A low weight, compact design, and low power consumption. The integration of the multi-sensor device, UAV, and LoRa communications as a single system adds aeeded flexibility to currently fixed monitoring stations.
Area Coverage Maximization under Connectivity Constraint in Wireless Sensor Networks
Authors: Tossa Frantz , Abdou Wahabou , Ansari Keivan , Ezin Eugène C. , Gouton Pierre
Published: February 2022

Wireless sensor networks (WSNs) have several important applications, both in research and domestic use. Generally, their main role is to collect and transmit data from an ROI (region of interest) to a base station for processing and analysis. Therefore, it is vital to ensure maximum coverage of the chosen area and communication between the nodes forming the network. A major problem in network design is the deployment of sensors with the aim to ensure both maximum coverage and connectivity between sensor node. The maximum coverage problem addressed here focuses on calculating the area covered by the deployed sensor nodes. Thus, we seek to cover any type of area (regular or irregular shape) with a predefined number of homogeneous sensors using a genetic algorithm to find the best placement to ensure maximum network coverage under the constraint of connectivity between the sensors. Therefore, this paper tackles the dual problem of maximum coverage and connectivity between sensor nodes. We define the maximum coverage and connectivity problems and then propose a mathematical model and a complex objective function. The results show that the algorithm, called GAFACM (Genetic Algorithm For Area Coverage Maximization), covers all forms of the area for a given number of sensors and finds the best positions to maximize coverage within the area of interest while guaranteeing the connectivity between the sensors.
The Transition from MODIS to VIIRS for Global Volcano Thermal Monitoring
Authors: Campus Adele , Laiolo Marco , Massimetti Francesco , Coppola Diego
Published: February 2022

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the most-used sensors for monitoring volcanoes and has been providing time series of Volcanic Radiative Power (VRP) on a global scale for two decades now. In this work, we analyzed the data provided by the Visible Infrared Imaging Radiometer Suite (VIIRS) by using the Middle Infrared Observation of Volcanic Activity (MIROVA) algorithm, originally developed to analyze MODIS data. The resulting VRP is compared with both the MIROVAMODIS data as well as with the Fire Radiative Power (FRP), distributed by the Fire Information for Resource Management System (FIRMS). The analysis on 9 active volcanoes reveals that VIIRS data analyzed with the MIROVA algorithm allows detecting ~60% more alerts than MODIS, due to a greater number of overpasses (+30%) and improved quality of VIIRS radiance data. Furthermore, the comparison with the nighttime FIRMS database indicates greater effectiveness of the MIROVA algorithm in detecting low-intensity (<10 MW) thermal anomalies (up to 90% more alerts than FIRMS). These results confirm the great potential of VIIRS to complement, replace and improve MODIS capabilities for global volcano thermal monitoring, because of the future end of Terra and Aqua Earth-observing satellite mission of National Aeronautics and Space Administration’s (NASA).
Lessons Learned from a Distributed RF-EMF Sensor Network
Authors: Aerts Sam , Vermeeren Günter , Van den Bossche Matthias , Aminzadeh Reza , Verloock Leen , Thielens Arno , Leroux Philip , Bergs Johan , Braem Bart , Philippron Astrid , Martens Luc , Joseph Wout
Published: February 2022

In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes’ results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km2 was deduced for future networks. Finally, the mobile sensor nodes were used to identify potential RF-EMF exposure hotspots in a previously unattainable area of more than 60 km2. In summary, through the analysis of a small number of RF-EMF sensor nodes (both fixed and mobile) in an urban area, this study offers invaluable insights applicable to future designs and deployments of distributed RF-EMF sensor networks.
Machine Learning-Based Classification of Human Behaviors and Falls in Restroom via Dual Doppler Radar Measurements
Authors: Saho Kenshi , Hayashi Sora , Tsuyama Mutsuki , Meng Lin , Masugi Masao
Published: February 2022

This study presents a radar-based remote measurement system for classification of human behaviors and falls in restrooms without privacy invasion. Our system uses a dual Doppler radar mounted onto a restroom ceiling and wall. Machine learning methods, including the convolutional neural network (CNN), long short-term memory, support vector machine, and random forest methods, are applied to the Doppler radar data to verify the model’s efficiency and features. Experimental results from 21 participants demonstrated the accurate classification of eight realistic behaviors, including falling. Using the Doppler spectrograms (time–velocity distribution) as the inputs, CNN showed the best results with an overall classification accuracy of 95.6% and 100% fall classification accuracy. We confirmed that these accuracies were better than those achieved by conventional restroom monitoring techniques using thermal sensors and radars. Furthermore, the comparison results of various machine learning methods and cases using each radar’s data show that the higher-order derivative parameters of acceleration and jerk, and the motion information in the horizontal direction are the efficient features for behavior classification in a restroom. These findings indicate that daily restroom monitoring using the proposed radar system accurately recognizes human behaviors and allows early detection of fall accidents.
Sex Differences in Anxiety and Depression: What Can (and Cannot) Preclinical Studies Tell Us?
Authors: Mir Franco Rafael , Rivarola María Angélica
Published: February 2022

In recent years, the gender perspective in scientific research and sex differences in biological studies on emotional disorders have become increasingly important. However, sex bias in basic research on anxiety and depression is still far from being covered. This review addresses the study of sex differences in the field of anxiety and depression using animal models that consider this issue so far. What can preclinical studies tell us and what are their main limitations? First, we describe the behavioral tests most frequently used in preclinical research to assess depressive-like and anxiety-like behaviors in rodents. Then, we analyze the main findings, strengths, and weaknesses of rodent models of anxiety and depression, dividing them into three main categories: sex chromosome complement-biased sex differences; gonadal hormone-biased sex differences; environmental-biased sex differences. Regardless of the animal model used, none can reproduce all the characteristics of such complex and multifactorial pathologies as anxiety and depressive disorders; however, each animal model contributes to elucidating the bases that underlie these disorders. The importance is highlighted of considering sex differences in the responses that emerge from each model.
Key Aspects for IT-Services Integration in Urban Transit Service of Medium-Sized Cities: A Qualitative Exploratory Study in Colombia
Authors: Ramirez-Guerrero Tomas , Toro Mauricio , Tabares Marta S. , Salazar-Cabrera Ricardo , Pachón de la Cruz Álvaro
Published: February 2022

In the last ten years, approximately, urban transit systems of Latin American capital cities have evolved significantly. Colombia, specifically, has concentrated this development in its capital cities, consolidated through digital transformation programs in the transportation sector. However, the same phenomenon does not occur in medium-sized cities for different reasons that are important to analyze. This paper presents an exploratory qualitative study involving eight medium-sized cities in the implementation phase of their strategic urban transit systems. Three main aspects that drive this study were identified: technologies and their cost, functional requirements to implement information technology services in transit systems, and economy and administration associated with this type of implementation. Based on this, a semi-structured interview data collection instrument was designed, with the participation of 15 officials distributed in the eight target cities, and one expert from an intelligent transportation system in a capital city. With the information collected, an exploratory analysis was made contrasting the responses given by each interviewee. The most relevant results show that the interviewees prioritize technologies based on open standards to provide information to users; that the northern medium-sized cities of the country do not have strategies that regularize and motivate the use of public transportation; instead, the southern medium-sized cities of the country consider the use of transportation to be necessary. Finally, it was concluded that the information technology services to be included in the provision of transit services should promote these cities’ cultural and economic growth.
Techno-Economic Evaluation of Ozone Application to Reduce Sludge Production in Small Urban WWTPs
Authors: Crutchik Dafne , Franchi Oscar , Jeison David , Vidal Gladys , Pinto Alicia , Pedrouso Alba , Campos José Luis
Published: February 2022

In Chile, small wastewater treatment plants (WWTPs) (treatment capacity of less than 4,800 m3/d) are normally not designed with consideration for the potential valorization of generated sludge. For this reason, they are generally operated at high solids residence times (SRT) (15 d) to promote the decay of biomass, promoting less sludge production and reducing the costs associated with biomass management. Operation at high SRT implies the need for a larger activated sludge system, increasing capital costs. The implementation of a sludge-disintegration unit by ozonation in future WWTPs could enable operation at an SRT of 3 d, with low sludge generation. In this work, we evaluate how the implementation of a sludge-ozonation system in small WWTPs (200–4000 m3/d) would affect treatment costs. Four scenarios were studied: (1) a current WWTP operated at an SRT of 15 d, without a sludge ozonation system; (2) a WWTP operated at an SRT of 15 d, with a sludge-ozonation system that would achieve zero sludge production; (3) a WWTP operated at an SRT of 3 d, with a sludge-ozonation system that would provide the same sludge production as scenario 1; (4) a WWTP operated at an SRT of 15 d, with a sludge-ozonation system that would achieve zero sludge production. Economic analysis shows that the treatment costs for scenarios 1 and 2 are similar, while a reduction in cost of up to 47% is obtained for scenarios 3 and 4.
Characteristics of Soil Macrofauna and Its Coupling Relationship with Environmental Factors in the Loess Area of Northern Shaanxi
Authors: Zhou Yongwei , Liu Changhai , Ai Ning , Tuo Xianghui , Zhang Zhiyong , Gao Rui , Qin Jiafeng , Yuan Caixia
Published: February 2022

Even with the in-depth implementation of forestry ecological projects, such as restoring farmland to forest (grass) in the loess area of northern Shaanxi, the characteristics of soil macrofauna communities and their coupling relationship with environmental factors after vegetation restoration in the study area are yet obscure. However, the soil macrofauna community characteristics are of great significance for evaluating the effectiveness of vegetation restoration in the study area. Therefore, the study aims to reveal the characteristics of the soil macrofauna community and their coupling relationships with the environment in the loess area of northern Shaanxi. In this study, all organisms of the five typical vegetation types in the study area were collected by manual sorting (Armeniaca sibirica and Populus simonii mixed forest (M), Robinia pseudoacacia (P), Populus simonii (S), Populus hopeiensis (H) and Hippophae rhamnoides (R)), and the adjacent abandoned grassland (G) was used as a control group. The group number and the individual number of soil macrofauna of different vegetation types in the study area and their coupling relationships with environmental factors are studied, and the following conclusions were drawn. (1) The study shows that there are certain differences in the environmental factors of different vegetation types in the study area, which include the significant differences in the alkaline nitrogen content of various vegetation types (p < 0.05). (2) The effects of different vegetation on soil macrofauna community were different. There were no significant differences in the soil macrofauna community structure between Armeniaca sibirica and Populus simonii mixed forest, Robinia pseudoacacia, Populus simonii and Populus hopeiensis, but there was a large difference from that of the abandoned grasslands. The community density of soil macrofauna in Armeniaca sibirica and Populus simonii mixed forest and Populus simonii were significantly higher than that in the abandoned grassland (p < 0.05), but the other indexes showed no significant differences. The Shannon–Wiener index of Robinia pseudoacacia and Populus hopeiensis were much lower than that of the abandoned grassland (p < 0.05). (3) The diversity of soil macrofauna communities was mainly affected by pH, alkaline nitrogen, potassium available, vegetation coverage and litter production. (4) Different groups of soil macrofauna were closely related and reacted differently to environmental factors, and vegetation coverage, litter production and alkaline nitrogen content were the key factors affecting the composition of soil macrofauna communities.
An Ethnographic Study of Collaborative Fashion Consumption: The Case of Temporary Clothing Swapping
Authors: Karpova Elena E. , Jestratijevic Iva , Lee JuYoung , Wu Juanjuan
Published: February 2022

This is the first research that has examined temporary swapping, a form of collaborative fashion consumption, that involves clothing exchange between two people that does not require the transfer of product ownership or monetary compensation. In this ethnographic study, we explored benefits, risks, and the meanings constructed by eight women before, during, and after exchanging parts of their wardrobes with a swap partner. Maslow’s hierarchy of needs was used to organize the results of interpretation of participant diaries with photographs of swapped garments and created outfits over a six-month period. While the swapping experience addressed basic physiological needs and secured free resources (more clothing to wear) for all participants, the more advanced psychological (social, self-esteem) and personal growth needs (self-actualization, transcendence) were met for only some of them. Similarly, women perceived different risks (safety and self-esteem risks). Through a holistic interpretation of the results, we discovered two critical factors determining overall temporary swapping satisfaction and success: (1) closeness of the relationship between the swap partners and (2) participant love for clothes. Temporary swapping might play a critical role in the fashion marketplace transition to sustainable consumption practices because it provides a middle ground between product ownership and non-ownership and thus facilitates gradual dematerialization of consumer lifestyle.
Federated Learning Approach to Protect Healthcare Data over Big Data Scenario
Authors: Dhiman Gaurav , Juneja Sapna , Mohafez Hamidreza , El-Bayoumy Ibrahim , Sharma Lokesh Kumar , Hadizadeh Maryam , Islam Mohammad Aminul , Viriyasitavat Wattana , Khandaker Mayeen Uddin
Published: February 2022

The benefits and drawbacks of various technologies, as well as the scope of their application, are thoroughly discussed. The use of anonymity technology and differential privacy in data collection can aid in the prevention of attacks based on background knowledge gleaned from data integration and fusion. The majority of medical big data are stored on a cloud computing platform during the storage stage. To ensure the confidentiality and integrity of the information stored, encryption and auditing procedures are frequently used. Access control mechanisms are mostly used during the data sharing stage to regulate the objects that have access to the data. The privacy protection of medical and health big data is carried out under the supervision of machine learning during the data analysis stage. Finally, acceptable ideas are put forward from the management level as a result of the general privacy protection concerns that exist throughout the life cycle of medical big data throughout the industry.
Customized Investment Decisions for New and Remanufactured Products Supply Chain Based on 3D Printing Technology
Authors: Sun Haoyu , Zheng Huiqi , Sun Xiaoyang , Li Wei
Published: February 2022

Three-dimensional printing and customized products are gradually emerging, and many manufacturers use 3D printing technology to customize products according to the individual needs of consumers. We focus on the differential pricing of new products and remanufactured products after being customized by 3D printing and the profit distribution of supply chain members. Through building the Stackelberg game model led by the manufacturer, we discuss how supply chain members should make investment decisions about customized new and customized remanufactured products with the goal of maximizing the manufacturer’s profit when there are two models of remanufacturing by the OEM and remanufacturing by the retailer. Finally, through the simulation analysis of MATLAB, we explain how the manufacturer and the retailer make decisions under the influence of customization sensitivity coefficient and customization cost. We also analyze the impact of relevant factors on the level of customization effort and whether supply chain members are suitable for custom production. We found that when the level of customization effort is relatively low, both the manufacturer and the retailer should choose the manufacturer to complete the customization process. However, when the level of customization effort is relatively high the manufacturer can transfer the customization process to the retailer, but the retailer should still let the manufacturer lead the customization process for his own profit maximization.
Impact of COVID-19 Pandemic on Hotel Employees in the Greater Accra Region of Ghana
Authors: Hervie Dolores Mensah , Amoako-Atta Ernest , Hossain Md Billal , Illés Csaba Bálint , Dunay Anna
Published: February 2022

This study examines the effect of the COVID-19 pandemic on hotel employees in the Greater Accra Region of Ghana using the conservation of resource and human relations theories to ascertain the level of impact. Data was collected from 511 hotel employees from 58 hotels using questionnaires. The employees were randomly sampled. Stepwise Regression in Statistical Package for Social Sciences version 16 model was used to run the analysis. Nine independent variables were included in a stepwise regression model. Six came out as significant and explained 51.6% of the variation in the percentage of their salary that staff received during the current COVID-19 pandemic. The remaining 48.4% was explained by other factors such as the years of service and whether the facility shut down during the lockdown. It was further identified that about 80% of the respondents had their salaries reduced, and that work schedules and working hours were altered, particularly during the lockdown and closure of the country’s borders. It is recommended that hotels should network, be more customer-oriented, be health- and safety-focused, frequently update their communication channels, and make digitalisation and human resource development a priority as measures to help the industry in its recovery process.
Carbon Footprint at a United Arab Emirates University: GHG Protocol
Authors: Samara Fatin , Ibrahim Sahar , Yousuf Mohammed Ekrima , Armour Rose
Published: February 2022

Background: University campuses can be leaders of change by tracking carbon footprints and establishing strategies for reductions. The American University of Sharjah (AUS) has led this effort in the United Arab Emirates (UAE), establishing an Office of Sustainability to address energy consumption on its campus, resulting in a reduction of 30% by 2015. AUS campus uses the Greenhouse Gas Protocol to annually track carbon footprint. The purpose of this paper is to stablish a framework that institutions can use to calculate the carbon footprint (CF) on their university campuses. Methods: The GHG Protocol, which categorizes emissions into three scopes; 1: direct, 2: indirect, and 3: other indirect emissions, was used as a guideline. This paper covers the following: Scope 1: emissions from university fleet, Scope 2: emissions from electricity and water consumption, Scope 3: emissions from the university commute, limited business air travel and waste. The data for each category are analyzed and recommendations to reduce the carbon footprint are presented. Results: The total CO2 emissions for the AUS campus in 2018–2019 were 94,553.30 tCO2e. Additionally, the percentage contribution of total emissions for Scope 1, 2 and 3 were 0.37%, 61.12% and 38.51%. Conclusions: The two highest contributors of CO2 emissions at the AUS campus are electricity consumption (60.91%) and university commute (36.54%). AUS has hosted numerous educational campaigns and awareness programs to try to reduce carbon emissions, which helped in reducing electricity consumption throughout campus; however, these are still insufficient; hence, the importance of quantifying the CF of the AUS campus. Based on the results obtained, recommendations can be made to reduce overall CO2 emissions for AUS and other higher education institutions in the region and internationally.
Comparing the Learning Approaches of Transfer Students and Direct Entrants in an Asian Higher Education Context
Authors: Cheung Kin , Ho Ceci Sze Wing , Tsang Hilda , Lau Elaine
Published: February 2022

Transfer students (TSs) transitioning from community college (CC) to university have been found to experience adjustment challenges different from those experienced by direct entrants (DEs) admitted straight from high school, which in turn influences their approaches to learning. Learning can enhance the transition towards sustainability, and it is influenced by various factors. However, there have been limited studies examining the factors associated with TSs’ and DEs’ learning approaches. To fill this research gap, this current study used a cross-sectional survey with both TSs (n = 841) and DEs (n = 978) to identify the factors. Our results indicated that the TSs had a higher rate of adoption of surface approaches (SA) to learning than DEs, while TSs and DEs shared some similar predictors of their learning approaches. The results suggest that the commitment of education stakeholders is essential for sustainable learning. They should improve the transfer system by providing adequate support and reduce disparities in the allocation of resources to TSs and DEs, as these affect learning approaches.
Attentional Span Is Determined by Sport Discipline
Authors: Reigal Rafael E. , Enríquez-Molina Rocío , Herrera-Robles Sara , Juárez-Ruiz de Mier Rocío , Pastrana Brincones José Luis , Hernández-Mendo Antonio , Morales-Sánchez Verónica
Published: February 2022

Many studies have highlighted the impact of sport on cognitive functioning. However, more evidence is needed to explain which type of sport is more relevant. The main purpose of this study was to determine the level of attention span based on the type of sport practiced (open vs. closed). In addition, this problem was also analyzed based on gender and training hours. The study sample consisted of 547 participants (27.20% male; 72.80% female), aged between 19 and 35 years old (M = 24.19; SD = 3.74). The “Modrian Images” computerized test, hosted in MenPas Cell software(MenPas 1.0), was used to assess the attention span. The results showed that athletes playing open sports have a better attentional span than others playing closed sports. Moreover, this was also replicated when assessing by gender. Likewise, a greater number of hours in a week participating in sports is related to a better level of attentional span, being less determinant than the type of sport practiced. Data obtained suggest that playing open sports would be more related to the greater development of attention span than playing more closed sports.
Agricultural Sustainability and Its Trends in India: A Macro-Level Index-Based Empirical Evaluation
Authors: Suresh A. , Krishnan P. , Jha Girish K. , Reddy A. Amarender
Published: February 2022

Sustainable development warrants cognizance of the limits of the ecosystem in terms of carrying capacity and technological externalities and, therefore, the limited extent of substitutability of natural capital with physical capital. The notion of sustainability assumes maximization and/or maintenance of current production without increasing the per unit use of inputs. In this paper, we assess the agricultural sustainability of 17 Indian states using an indicator approach for a period of two decades (1991–2011). For the analysis, the paper primarily uses the normalized temporal data for construction of indices for each of the selected indicators grouped under environmental, economic, and social dimensions. Overall, the agricultural sustainability has improved in all the states. Among the sub-components, while the social-sustainability dimension improved in all the states, the environmental and economic dimensions improved in 8 and 14 states, respectively. There was significant variation in sustainability performance among the states. Economic and environmental sustainability indices were negatively correlated. Based on the results, we advocate a strategy that negates this negative correlation. We recommend a comprehensive approach for integrating all the three dimensions for planning actions towards sustainable agricultural growth.
How Strategic Interaction of Innovation Policies between China’s Regional Governments Affects Wind Energy Innovation
Authors: Li Chengming , Shi Han , Zeng Liangen , Dong Xiaomeng
Published: February 2022

Prior research has shown the importance of innovation policies that promote innovation in renewable energy, such as wind power. We study the impact of the strategic interaction of innovation policies between regional governments in terms of wind energy innovation in China. Based on panel data from 2007 to 2018 on a provincial level in China, we construct an innovation strength index of each province in the wind power industry and investigate the inductive effect of the technology-push policy and the demand-pull policy, as well as their spatial spillover effect on wind energy innovation. The results show that the technology-push policy of local governments has an obvious inductive effect on wind energy innovation in the region, while also having a negative spillover effect through R&D factor competitions between regions with geography proximity or with proximity in the ranking of R&D funds input. In terms of the demand-pull policy, only changes at the national level can produce positive spillover effects by promoting expectations of market growth. Yet, competition between regions with proximity in the ranking of wind energy resource reserves produce negative spillover effects. The findings should have a far-reaching impact on the sustainable development of global wind power.
Accuracy of a Method to Monitor Root Position Using a 3D Digital Crown/Root Model during Orthodontic Treatments
Authors: Ogawa Kaho , Ishida Yoshiki , Kuwajima Yukinori , Lee Cliff , Emge Jacob R. , Izumisawa Mitsuru , Satoh Kazuro , Ishikawa-Nagai Shigemi , Da Silva John D. , Chen Chia-Yu
Published: February 2022

This study aimed to assess the accuracy of a method of predicting post-movement root position during orthodontic treatment using a 3D digital crown/root model (3DCRM) created with pre-movement records of both cone-beam computed tomography (CBCT) and dental arch digital scans. Pre- and post-movement CBCT scans and dental arch digital scans of five patients who had completed orthodontic treatments were used in this study. The 3DCRM was superimposed onto the post-movement scanned dental arch to identify the post-movement root position (test method). Post-movement CBCT (referenced as the current method) served as the control to identify the actual post-movement root position. 3D-coordinate analysis revealed no significant differences between the test and current methods along the X and Y axes. However, the discrepancy on the Z axis (especially in cases of intrusion) was greater than that in all other directions for all three tooth types examined (p < 0.05). A strong positive correlation between the degree of discrepancy and the distance of tooth movement was observed on the Z axis (r = 0.71). The 3DCRM method showed promising potential to accurately predict root position during orthodontic treatments without the need for a second CBCT. However, root resorption, which affected the Z axis prediction, needs to be closely monitored using periapical radiographs to complement this method.
Development of Two-Phase Emission Detectors in Russia
Authors: Akimov Dmitry , Bolozdynya Alexander
Published: February 2022

This paper reviews the history of the development of two-phase emission detector technology that was invented 50 years ago at the Moscow Engineering Physics Institute and is currently being used to search for dark matter, novel neutrino physics and double beta-decay in several internationally running experiments.
Developing an Effective Peptide-Based Vaccine for COVID-19: Preliminary Studies in Mice Models
Authors: Yang Haiqiang , Cao Jessica , Lin Xiaoyang , Yue Jingwen , Zieneldien Tarek , Kim Janice , Wang Lianchun , Fang Jianmin , Huang Ruo-Pan , Bai Yun , Sneed Kevin , Cao Chuanhai
Published: February 2022

Coronavirus disease 2019 (COVID-19) has caused massive health and economic disasters worldwide. Although several vaccines have effectively slowed the spread of the virus, their long-term protection and effectiveness against viral variants are still uncertain. To address these potential shortcomings, this study proposes a peptide-based vaccine to prevent COVID-19. A total of 15 B cell epitopes of the wild-type severe acute respiratory coronavirus 2 (SARS-CoV-2) spike (S) protein were selected, and their HLA affinities predicted in silico. Peptides were divided into two groups and tested in C57BL/6 mice with either QS21 or Al(OH)3 as the adjuvant. Our results demonstrated that the peptide-based vaccine stimulated high and durable antibody responses in mice, with the T and B cell responses differing based on the type of adjuvant employed. Using epitope mapping, we showed that our peptide-based vaccine produced antibody patterns similar to those in COVID-19 convalescent individuals. Moreover, plasma from vaccinated mice and recovered COVID-19 humans had the same neutralizing activity when tested with a pseudo particle assay. Our data indicate that this adjuvant peptide-based vaccine can generate sustainable and effective B and T cell responses. Thus, we believe that our peptide-based vaccine can be a safe and effective vaccine against COVID-19, particularly because of the flexibility of including new peptides to prevent emerging SARS-CoV-2 variants and avoiding unwanted autoimmune responses.
Increased Heparanase Levels in Urine during Acute Puumala Orthohantavirus Infection Are Associated with Disease Severity
Authors: Cabrera Luz E. , Schmotz Constanze , Saleem Moin A. , Lehtonen Sanna , Vapalahti Olli , Vaheri Antti , Mäkelä Satu , Mustonen Jukka , Strandin Tomas
Published: February 2022

Old–world orthohantaviruses cause hemorrhagic fever with renal syndrome (HFRS), characterized by acute kidney injury (AKI) with transient proteinuria. It seems plausible that proteinuria during acute HFRS is mediated by the disruption of the glomerular filtration barrier (GFB) due to vascular leakage, a hallmark of orthohantavirus–caused diseases. However, direct infection of endothelial cells by orthohantaviruses does not result in increased endothelial permeability, and alternative explanations for vascular leakage and diminished GFB function are necessary. Vascular integrity is partly dependent on an intact endothelial glycocalyx, which is susceptible to cleavage by heparanase (HPSE). To understand the role of glycocalyx degradation in HFRS–associated proteinuria, we investigated the levels of HPSE in urine and plasma during acute, convalescent and recovery stages of HFRS caused by Puumala orthohantavirus. HPSE levels in urine during acute HFRS were significantly increased and strongly associated with the severity of AKI and other markers of disease severity. Furthermore, increased expression of HPSE was detected in vitro in orthohantavirus–infected podocytes, which line the outer surfaces of glomerular capillaries. Taken together, these findings suggest the local activation of HPSE in the kidneys of orthohantavirus–infected patients with the potential to disrupt the endothelial glycocalyx, leading to increased protein leakage through the GFB, resulting in high amounts of proteinuria.
Physics-Based Simulation and Automation of a Load-Haul-Dump Operation for an Articulated Dump Truck
Authors: Hejase Bilal , Ozguner Umit
Published: February 2022

Many trucks are used for a class of activities involving a sequence of basic load-haul-dump operations. The repetitiveness of this operation has been an enabler for autonomous vehicle technology in efforts to increase safety and efficiency. In this paper, we present a framework for the automation of the load-haul-dump operation in a mine setting using an articulated dump truck. A simulation environment for the testing of autonomous driving algorithms is developed and a custom mining environment is generated to adapt to our simulation settings. We also present an operational decomposition of the sequence of tasks and develop a finite state machine for high-level decision making based on this decomposition. A path tracking module that considers both bodies of the articulated truck is also developed. The resulting architecture was implemented to achieve autonomy for a load-haul-dump operation in the simulated environment within a fixed path. Experiments show that the proposed FSM-path tracking system can automate the load-haul-dump operation; and that the simulation environment can support the testing and development of autonomous driving algorithms for configurations such as an articulated truck.
Correction: Piscitelli et al. Adaptive Agricultural Strategies for Facing Water Deficit in Sweet Maize Production: A Case Study of a Semi-Arid Mediterranean Region. Water 2021, 13, 3285
Authors: Piscitelli Lea , Colovic Milica , Aly Adel , Hamze Mohamad , Todorovic Mladen , Cantore Vito , Albrizio Rossella
Published: February 2022

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