bluuebunny/crossref_metadata_2025 huggingface dataset:
Changing Patterns of Malaria in Grande Comore after a Drastic Decline: Importance of Fine-Scale Spatial Analysis to Inform Future Control Actions
Authors: Attoumane Artadji , Silai Rahamatou , Bacar Affane , Cardinale Eric , Pennober Gwenaëlle , Herbreteau Vincent
Published: December 2020

Malaria has long been endemic in the Union of Comoros reaching an incidence of 15,045 cases for 100,000 inhabitants in 2010 (103,670 cases). Since then, strengthened control actions based on the distribution of Long-Lasting Insecticidal mosquito Nets and mass treatment have reduced malaria to a low level. However, it persists more specifically in Grande Comore, where 82% of cases were diagnosed between 2010 and 2016. This situation remains a challenge for health authorities seeking to eliminate malaria, by targeting transmission sites more precisely. In this context, this study aimed at mapping malaria at the finest scale, in order to describe its spatial distribution and identify possible environmental indicators. The National Malaria Control Program provided the 2016 data, the only year that could be mapped at the level of localities. This mapping revealed spatial autocorrelation between localities, especially in the east of the island with a major cluster around Itsinkoudi (using the Kulldorff’s spatial scan test). Secondary clusters showed that malaria remains present throughout the island in both rural and urban areas. We also analyzed satellite images (SPOT 5) with remote sensing techniques (Object-Based Image Analysis) to look for environmental indicators. Landscape analysis shows that malaria incidence is correlated across the island with low altitudes, and a larger proportion of grasslands or a fewer proportion of forested areas nearby (at less than 1km around villages). More locally in the east, malaria is linked to larger shrub areas. These relationships could be associated with the fact that lower altitude localities are more interconnected, such facilitating malaria transmission. In 2016, malaria persists in Grande Comore, showing new patterns with more cases in the eastern part of the island and the possibility of high incidences during the dry season. Precise mapping of epidemiological data and landscape analysis allow the identification of clusters and active transmission foci. They are important tools for health surveillance in order to optimize control actions on key transmission locations.
New Contact Sensorization Smart System for IoT e-Health Applications Based on IBC IEEE 802.15.6 Communications
Authors: Hernández David , Ors Rafael , Capella Juan V. , Bonastre Alberto , Campelo José C.
Published: December 2020

This paper proposes and demonstrates the capabilities of a new sensorization system that monitors skin contact between two persons. Based on the intrabody communication standard (802.15.6), the new system allows for interbody communication, through the transmission of messages between different persons through the skin when they are touching. The system not only detects if there has been contact between two persons but, as a novelty, is also able to identify the elements that have been in contact. This sensor will be applied to analyze and monitor good follow-up of hand hygiene practice in health care, following the “World Health Organization Guidelines on Hand Hygiene in Health Care”. This guide proposes specific recommendations to improve hygiene practices and reduce the transmission of pathogenic microorganisms between patients and health-care workers (HCW). The transmission of nosocomial infections due to improper hand hygiene could be reduced with the aid of a monitoring system that would prevent HCWs from violating the protocol. The cutting-edge sensor proposed in this paper is a crucial innovation for the development of this automated hand hygiene monitoring system (AHHMS).
Real-Time Monitoring for Hydraulic States Based on Convolutional Bidirectional LSTM with Attention Mechanism
Authors: Kim Kyutae , Jeong Jongpil
Published: December 2020

By monitoring a hydraulic system using artificial intelligence, we can detect anomalous data in a manufacturing workshop. In addition, by analyzing the anomalous data, we can diagnose faults and prevent failures. However, artificial intelligence, especially deep learning, needs to learn much data, and it is often difficult to get enough data at the real manufacturing site. In this paper, we apply augmentation to increase the amount of data. In addition, we propose real-time monitoring based on a deep-learning model that uses convergence of a convolutional neural network (CNN), a bidirectional long short-term memory network (BiLSTM), and an attention mechanism. CNN extracts features from input data, and BiLSTM learns feature information. The learned information is then fed to the sigmoid classifier to find out if it is normal or abnormal. Experimental results show that the proposed model works better than other deep-learning models, such as CNN or long short-term memory (LSTM).
Automatic Calibration of a Two-Axis Rotary Table for 3D Scanning Purposes
Authors: Bisogni Livio , Mollaiyan Ramtin , Pettinari Matteo , Neri Paolo , Gabiccini Marco
Published: December 2020

Rotary tables are often used to speed up the acquisition time during the 3D scanning of complex geometries. In order to avoid manual registration of the point clouds acquired with different orientations, automatic algorithms to compensate the rotation were developed. Alternatively, a proper calibration of the rotary axis with respect to the camera system is needed. Several methods are available in the literature, but they only consider a single-axis calibration. In this paper, a method for the simultaneous calibration of both axes of the table is proposed. A checkerboard is attached to the table, and several images with different poses are acquired. An optimization algorithm is then setup to determine the orientation and the locations of the two axes. A metric to assess the calibration quality was also defined by computing the average mean reprojection error. This metric is used to investigate the optimal number and distribution of the calibration poses, demonstrating that the optimum calibration results are achieved when a wider dispersion of the calibration poses is adopted.
Human Sentiment and Activity Recognition in Disaster Situations Using Social Media Images Based on Deep Learning
Authors: Sadiq Amin Muhammad , Ahn Huynsik , Choi Young Bok
Published: December 2020

A rapidly increasing growth of social networks and the propensity of users to communicate their physical activities, thoughts, expressions, and viewpoints in text, visual, and audio material have opened up new possibilities and opportunities in sentiment and activity analysis. Although sentiment and activity analysis of text streams has been extensively studied in the literature, it is relatively recent yet challenging to evaluate sentiment and physical activities together from visuals such as photographs and videos. This paper emphasizes human sentiment in a socially crucial field, namely social media disaster/catastrophe analysis, with associated physical activity analysis. We suggest multi-tagging sentiment and associated activity analyzer fused with a a deep human count tracker, a pragmatic technique for multiple object tracking, and count in occluded circumstances with a reduced number of identity switches in disaster-related videos and images. A crowd-sourcing study has been conducted to analyze and annotate human activity and sentiments towards natural disasters and related images in social networks. The crowdsourcing study outcome into a large-scale benchmark dataset with three annotations sets each resolves distinct tasks. The presented analysis and dataset will anchor a baseline for future research in the domain. We believe that the proposed system will contribute to more viable communities by benefiting different stakeholders, such as news broadcasters, emergency relief organizations, and the public in general.
Real-Time Parallel-Serial LiDAR-Based Localization Algorithm with Centimeter Accuracy for GPS-Denied Environments
Authors: Niedzwiedzki Jakub , Niewola Adam , Lipinski Piotr , Swaczyna Piotr , Bobinski Aleksander , Poryzala Pawel , Podsedkowski Leszek
Published: December 2020

In this paper, we introduce a real-time parallel-serial algorithm for autonomous robot positioning for GPS-denied, dark environments, such as caves and mine galleries. To achieve a good complexity-accuracy trade-off, we fuse data from light detection and ranging (LiDAR) and an inertial measurement unit (IMU). The proposed algorithm’s main novelty is that, unlike in most algorithms, we apply an extended Kalman filter (EKF) to each LiDAR scan point and calculate the location relative to a triangular mesh. We also introduce three implementations of the algorithm: serial, parallel, and parallel-serial. The first implementation verifies the correctness of our innovative approach, but is too slow for real-time execution. The second approach implements a well-known parallel data fusion approach, but is still too slow for our application. The third and final implementation of the presented algorithm along with the state-of-the-art GPU data structures achieves real-time performance. According to our experimental findings, our algorithm outperforms the reference Gaussian mixture model (GMM) localization algorithm in terms of accuracy by a factor of two.
Recent Advances in Cell Adhesive Force Microscopy
Authors: Tu Ying , Wang Xuefeng
Published: December 2020

Cell adhesive force, exerting on the local matrix or neighboring cells, plays a critical role in regulating many cell functions and physiological processes. In the past four decades, significant efforts have been dedicated to cell adhesive force detection, visualization and quantification. A recent important methodological advancement in cell adhesive force visualization is to adopt force-to-fluorescence conversion instead of force-to-substrate strain conversion, thus greatly improving the sensitivity and resolution of force imaging. This review summarizes the recent development of force imaging techniques (collectively termed as cell adhesive force microscopy or CAFM here), with a particular focus on the improvement of CAFM’s spatial resolution and the biomaterial choices for constructing the tension sensors used in force visualization. This review also highlights the importance of DNA-based tension sensors in cell adhesive force imaging and the recent breakthrough in the development of super-resolution CAFM.
Recognition System Using Fusion Normalization Based on Morphological Features of Post-Exercise ECG for Intelligent Biometrics
Authors: Choi Gyu Ho , Ko Hoon , Pedrycz Witold , Singh Amit Kumar , Pan Sung Bum
Published: December 2020

Although biometrics systems using an electrocardiogram (ECG) have been actively researched, there is a characteristic that the morphological features of the ECG signal are measured differently depending on the measurement environment. In general, post-exercise ECG is not matched with the morphological features of the pre-exercise ECG because of the temporary tachycardia. This can degrade the user recognition performance. Although normalization studies have been conducted to match the post- and pre-exercise ECG, limitations related to the distortion of the P wave, QRS complexes, and T wave, which are morphological features, often arise. In this paper, we propose a method for matching pre- and post-exercise ECG cycles based on time and frequency fusion normalization in consideration of morphological features and classifying users with high performance by an optimized system. One cycle of post-exercise ECG is expanded by linear interpolation and filtered with an optimized frequency through the fusion normalization method. The fusion normalization method aims to match one post-exercise ECG cycle to one pre-exercise ECG cycle. The experimental results show that the average similarity between the pre- and post-exercise states improves by 25.6% after normalization, for 30 ECG cycles. Additionally, the normalization algorithm improves the maximum user recognition performance from 96.4 to 98%.
A Secure and Lightweight Three-Factor-Based Authentication Scheme for Smart Healthcare Systems
Authors: Ryu Jihyeon , Kang Dongwoo , Lee Hakjun , Kim Hyoungshick , Won Dongho
Published: December 2020

Internet of Things (IoT) technology has recently been integrated with various healthcare devices to monitor patients’ health status and share it with their healthcare practitioners. Since healthcare data often contain personal and sensitive information, healthcare systems must provide a secure user authentication scheme. Recently, Adavoudi-Jolfaei et al. and Sharma and Kalra proposed a lightweight protocol using hash function encryption only for user authentication on wireless sensor systems. In this paper, we found some weaknesses in target schemes. We propose a novel three-factor lightweight user authentication scheme that addresses these weaknesses and verifies the security of the proposed scheme using a formal verification tool called ProVerif. In addition, our proposed scheme outperforms other proposed symmetric encryption-based schemes or elliptic curve-based schemes.
Towards a Simulation Framework for Smart Indoor Spaces
Authors: Golestan Shadan , Nikolaidis Ioanis , Stroulia Eleni
Published: December 2020

The effectiveness of sensor-based applications for smart homes and smart buildings is conditioned upon the deployment configuration of their underlying sensors. Real-world evaluation of alternative possible sensor-deployment configurations is labor-intensive, costly, and time-consuming, which implies the need for a simulation-based methodology. In this work, we report on such a methodology that supports the modeling of indoor spaces, the activities of their occupants, and the behaviors of different types of sensors. We argue that, in order for a simulation to be useful for the purpose of evaluating a sensor deployment configuration, it has to generate realistic event streams of individual sensors over time, as well as realistic compositions of sensor events within a time window. We have evaluated our simulator for smart indoor spaces, SIMsis toolkit, in the context of our Smart-Condo ambient-assisted living platform, supporting the observation and analysis of activities of daily living (ADLs). Our findings indicate that SIMsis produces realistic agent traces and sensor readings, and has the potential to support the process of developing and deploying sensor-based applications.
Wavelet Decomposition in Analysis of Impact of Virtual Reality Head Mounted Display Systems on Postural Stability
Authors: Wodarski Piotr , Jurkojć Jacek , Gzik Marek
Published: December 2020

This study investigated how spatial projection systems influences body balance including postural stability. Analyzing precisely defined frequency bands of movements of the center of pressure makes it possible to determine the effectiveness of the balance system’s response to disruptions and disorders and may be used as an indicator in the diagnosis of motor dysfunction. The study involved 28 participants for whom the center of pressure was assessed in a test with open eyes, closed eyes and with virtual reality projection. Percent distributions of energy during wavelet decomposition were calculated. Changes in body stability were determined for the virtual reality tests and these changes were classified as an intermediate value between the open-eyes test and the closed-eyes test. The results indicate the importance of using safety support systems in therapies involving Virtual Reality. The results also show the necessity of measurements times in stabilographic evaluations in order to conduct a more thorough analysis of very low frequencies of the center of pressure signal.
Wearable Inertial Sensors for Gait Analysis in Adults with Osteoarthritis—A Scoping Review
Authors: Kobsar Dylan , Masood Zaryan , Khan Heba , Khalil Noha , Kiwan Marium Yossri , Ridd Sarah , Tobis Matthew
Published: December 2020

Our objective was to conduct a scoping review which summarizes the growing body of literature using wearable inertial sensors for gait analysis in lower limb osteoarthritis. We searched six databases using predetermined search terms which highlighted the broad areas of inertial sensors, gait, and osteoarthritis. Two authors independently conducted title and abstract reviews, followed by two authors independently completing full-text screenings. Study quality was also assessed by two independent raters and data were extracted by one reviewer in areas such as study design, osteoarthritis sample, protocols, and inertial sensor outcomes. A total of 72 articles were included, which studied the gait of 2159 adults with osteoarthritis (OA) using inertial sensors. The most common location of OA studied was the knee (n = 46), followed by the hip (n = 22), and the ankle (n = 7). The back (n = 41) and the shank (n = 40) were the most common placements for inertial sensors. The three most prevalent biomechanical outcomes studied were: mean spatiotemporal parameters (n = 45), segment or joint angles (n = 33), and linear acceleration magnitudes (n = 22). Our findings demonstrate exceptional growth in this field in the last 5 years. Nevertheless, there remains a need for more longitudinal study designs, patient-specific models, free-living assessments, and a push for “Code Reuse” to maximize the unique capabilities of these devices and ultimately improve how we diagnose and treat this debilitating disease.
Grass-Fed Milk Perception: Profiling Italian Consumer
Authors: Peira Giovanni , Cortese Damiano , Lombardi Giampiero , Bollani Luigi
Published: December 2020

This paper aims at analyzing the consumers’ perception of grass-fed milk so as to understand if a production based on a sustainable business model could represent a response to new and emerging needs in consumption. The sample of the study was constituted by a total of 750 Italian members of the International Association Slow Food. A Principal Component Analysis (PCA) was used to summarize the quantitative variables, which, grouped in “dimensions”, were used as input for multivariate statistics (HCA, MCA) in order to define and explain consumer profiles. Our data confirm an in-progress change in milk consumption: Consumers were more oriented towards quality, local supply chains, traceability, and are characterized by an increasing propensity to a higher expense for grass-fed milk. Further research will enlarge the proposed panorama covering a sample of more general consumers. The study was a preliminary market analysis that could be used as the basis for a production, distribution, and consumption chain grass-fed-based model. Grass-fed milk is a product linking individual and societal needs for more sustainable production and entrepreneurship that creates a higher value product aligned with market needs.
Black Widow Optimization-Based Optimal PI-Controlled Wind Turbine Emulator
Authors: Premkumar K. , Vishnupriya M. , Sudhakar Babu Thanikanti , Manikandan B. V. , Thamizhselvan T. , Nazar Ali A. , Rabiul Islam Md. , Kouzani Abbas Z. , Parvez Mahmud M. A.
Published: December 2020

In this article, the parameters of the proportional-integral (PI) controller of the wind turbine (WT) emulator, i.e., proportional and integral gain of the PI controller, are optimized using a black widow optimization algorithm (BWOA). The proposed system is developed and analyzed using MATLAB/Simulink environment. The performance of the BWOA optimized PI controller is compared with a BAT algorithm, particle swarm optimization, and genetic algorithm optimized PI controller to measure the effectiveness of the proposed control system. The developed system is tested for different operating conditions such as static wind speed settings, static pitch angle conditions, step-change in wind speed settings, and step-change in pitch angle settings. Finally, the proposed system is realized in real-time by hardware experimentations. The results of the experimentation are compared with simulation results as well. The presented simulation and hardware result shows good agreement, which confirms the effectiveness of the proposed method. Thereby, the proposed optimization-based PI-controlled wind emulator can be recommended for emulating the characteristics of any type of WT with a low-cost system.
Is Environmental Sustainability Taking a Backseat in China after COVID-19? The Perspective of Business Managers
Authors: Zhang Dongyong , Hao Mengge , Morse Stephen
Published: December 2020

China’s quick economic recovery from COVID-19 has presented a narrow but vast opportunity to build an economy that is cleaner, fairer, and safer. Will China grab this opportunity? The answer rests with both business managers and the government. Based on a questionnaire survey of 1160 owners and managers of companies headquartered in 32 regions of China and covering 30 industries, this paper explores how COVID-19 has impacted Chinese business, especially with regard to the three dimensions of sustainability (economic, social, and environmental). The results suggest that Chinese companies’ sustainability priorities have been shifted towards the social dimension both during COVID-19 and into the post-pandemic phase, regardless of the type of ownership, company size, or market focus (domestic, overseas, or mixture of the two). However, all types of company prioritize the need for economic sustainability in the post-pandemic phase and in relative terms the importance of the environmental dimension has been diminished. Hence the potential for a post-pandemic environmental rebound effect in China is clear. But it does not have to be the case if Chinese businesses and the government take actions to change its recovery plans to embrace the environmental dimension of sustainability. The paper puts forward some suggestions and recommendations for businesses and the government.
Does Water Pollution Influence Willingness to Accept the Installation of a Mine Near a City? Case Study of an Open-Pit Lithium Mine
Authors: Crespo-Cebada Eva , Díaz-Caro Carlos , Nevado Gil María Teresa , Mirón Sanguino Ángel Sabino
Published: December 2020

Currently, the use of lithium as a resource in the manufacturing of technological components such as mobile phones, computers or even in the automotive sector, is in high demand. In this sense, the prospects for lithium open-pit mines in order to obtain this highly valued resource have improved remarkably. However, the installation of this type of mine causes certain negative environmental consequences such as air pollution, water pollution, and even a reduction in the biodiversity of the environment, which generates welfare losses due to the cost involved. The objective of this work is to analyse the preferences of the citizens of Cáceres (Spain) regarding the possible opening of an open-pit lithium mine in the surroundings of the city. For this, a choice experiment was carried out to identify the willingness to accept certain levels of contamination and/or reduction of biodiversity and to quantify its monetary quantification. Likewise, a mixed-effects model was applied in order to analyse the heterogeneity in preferences and the willingness to accept the installation. The results showed that water pollution is one of the most relevant attributes in the preferences, revealing a very high willingness to accept (€12–38/year) for water pollution compared to other attributes.
A Grid-Based Spatial Analysis for Detecting Supply–Demand Gaps of Public Transports: A Case Study of the Bangkok Metropolitan Region
Authors: Peungnumsai Apantri , Miyazaki Hiroyuki , Witayangkurn Apichon , Kim Sohee Minsun
Published: December 2020

Public transport service has been promoted to reduce the problems of traffic congestion and environmental impacts due to car dependency. Several public transportation modes are available in Bangkok Metropolitan Region (BMR) such as buses, heavy rails, vans, boats, taxis, and trains while in some areas have fewer modes of public transport available. The disparity of public transport service negatively impacts social equity. This study aims to identify the gaps between public transport supply and demand and to demonstrate introduced indicators to assess the public transport performance incorporating transport capacity and equilibrium access aspects. Supply index was used to evaluate the level of service, and the demand index was applied to estimate travel needs. Furthermore, the Lorenz curves and the Gini coefficients were used to measure the equity of public transport. The results highlight that more than half of the BMR population is living in low-supply high-demand areas for public transportation. Moreover, the equitable access analysis has identified that the high-income population has better access to public transport than the low-income population. The results suggest that public transport gaps and equity indicate the inclusiveness of public transportation, as well as to the areas where to improve the public transport service. Thus, the methodology used in this study can be applied to another city or region similar to BMR.
The Relationship between Technological Capabilities and Organizational Impact: Direct and Indirect Routes for Employed and Self-Employed Personal Fitness Trainers
Authors: García-Fernández Jerónimo , Gálvez-Ruiz Pablo , Bohórquez M. Rocío , Grimaldi-Puyana Moisés , Cepeda-Carrión Ignacio
Published: December 2020

The purpose of this study was to investigate the relationships between technological capabilities, individual impact, market agility and organizational impact in employed and self-employed personal trainers hired by fitness centers. The study was performed with 259 personal trainers. Exploratory Factor Analysis, Confirmatory Factor Analysis and a Structural Equation Model were used. The results showed, for the employees, positive relationships between all variables, except for the relationship between individual impact and organizational impact. In contrast, for self-employed personal trainers, only the relationships of technological capabilities with market agility and individual impact, and between the latter and organizational impact, were positive. While the individual variables of the employees show positive relationships with the organizational variables analyzed, this impact could not be determined in the performance of the self-employed. These results are discussed in relation to the previous literature, and possible causes for the differences found between employees and self-employed personal trainers are pointed out. This study’s findings indicate that the promotion and consolidation of personal trainers’ technological capabilities (TCs), whether they are self-employed or employees, will be key for the fitness centers where they work, by directly influencing the individual impact of the trainers on them and in the organizational performance.
Geospatial Simulation Model of Deforestation and Reforestation Using Multicriteria Evaluation
Authors: Monjardin-Armenta Sergio Alberto , Plata-Rocha Wenseslao , Pacheco-Angulo Carlos Eduardo , Franco-Ochoa Cuauhtémoc , Rangel-Peraza Jesus Gabriel
Published: December 2020

Deforestation is an anthropic phenomenon that negatively affects the environment and therefore the climate, the carbon cycle, biodiversity and the sustainability of agriculture and drinking water sources. Deforestation is counteracted by reforestation processes, which is caused by the natural regeneration of forests or by the establishment of plantations. The present research is focused on generating a simulation model to predict the deforestation and reforestation for 2030 and 2050 using geospatial analysis techniques and multicriteria evaluation. The case study is the North Pacific Basin, which is one of the areas with the greatest loss of forest cover in Mexico. The results of the spatial analysis of forest dynamics determined that the forest area in 2030 would be 98,713.52 km2, while in 2050 would be 101,239.8 km2. The mean annual deforestation and reforestation expected in the study area is 115 and 193.84 km2, for the 2014–2030 period, while mean annual deforestation and reforestation values of 95 and 221.31 km2 are expected for the 2030–2050 period. Therefore, considering the forest cover predicted by the deforestation and reforestation model, a carbon capture of 16,209.67 ton/C was estimated for the 2014–2030 period and 587,596.01 ton/C for the 2030–2050.
Meanings and Motives for Consumers’ Sustainable Actions in the Food and Clothing Domains
Authors: Stancu Catalin M. , Grønhøj Alice , Lähteenmäki Liisa
Published: December 2020

The concept of sustainability has been widely discussed in the public arena by public entities and companies; however, consumers express inconsistency and confusion around the meaning of sustainability. This study aims to provide insights into consumers’ associations with the concept of sustainability in general and within two behavioural domains that represent daily necessities (i.e., food and clothing), in addition to exploring the motivational drivers behind sustainable behaviours. A total of 23 semi-structured interviews were conducted with young consumers in Denmark to address this aim. Consumers perceived the concept of sustainability as complex and mainly related it to environmental aspects, whereas social and economic aspects were less emphasised. The interviewees used examples of sustainable behaviours, which cover the whole consumption-cycle, when interpreting sustainability. Consumers had various motivations to engage in sustainable behaviours and these varied by the stage in the consumption-cycle and domain. The interviewees displayed external motivation (e.g., save money, better taste), introjected motivation (e.g., impress others, public self-consciousness), internalised motivation (e.g., reflection of self) and even intrinsic motivation (e.g., pure interest) to engage in different types of sustainable food or clothing behaviours across the consumption-cycle. Different types of motivations drove the same behaviour, suggesting potential synergies or internal conflicts.
The Specificity of Family Firms Providing Accommodation Services—The Experience of a Post-Socialist Country 30 Years after the Economic Transformation
Authors: Górska-Warsewicz Hanna , Dębski Maciej , Rejman Krystyna , Laskowski Wacław
Published: December 2020

This study aimed to analyze the conditions and specificity of family firms (FFs) providing accommodation services in Poland 30 years after the beginning of economic changes. The research was carried out between 2017 and 2018 using the Computer-Assisted Website Interview (CAWI) method. In two stages of research, a total of 1300 questionnaires were sent to FFs providing accommodation services, and we received 83 fully completed questionnaires. This response rate indicates that there is still a lack of trust among FFs as a result of the activities of the socialist economy, which was negative towards private property. The respondents were generally business owners, but several questionnaires were completed by other members of the families running an accommodation service business. All companies participating in the survey provided their services in small towns or rural areas. In the structure of the surveyed FFs by type, guesthouses and lodgings had the largest share, and, in terms of location, FFs from the southern part of the country dominated. We found out that familiarity is an important feature of the Polish FFs providing accommodation services. The majority of FF representatives agreed that focusing on the specifics of family business allows them to compete with companies providing accommodation services. They also pointed out the long-term perspective of business and development and the provision of high-quality services. Such an approach is now possible because the period of a centrally planned economy had to be followed by a change in the way of thinking related to business activity in Poland.
Challenges in Using Earth Observation (EO) Data to Support Environmental Management in Brazil
Authors: Cerbaro Mercio , Morse Stephen , Murphy Richard , Lynch Jim , Griffiths Geoffrey
Published: December 2020

This paper presents the results of research designed to explore the challenges involved in the use of Earth Observation (EO) data to support environmental management Brazil. While much has been written about the technology and applications of EO, the perspective of end-users of EO data and their needs has been under-explored in the literature. A total of 53 key informants in Brasilia and the cities of Rio Branco and Cuiaba were interviewed regarding their current use and experience of EO data and the expressed challenges that they face. The research builds upon a conceptual model which illustrates the main steps and limitations in the flow of EO data and information for use in the management of land use and land cover (LULC) in Brazil. The current paper analyzes and ranks, by relative importance, the factors that users identify as limiting their use of EO. The most important limiting factor for the end-user was the lack of personnel, followed by political and economic context, data management, innovation, infrastructure and IT, technical capacity to use and process EO data, bureaucracy, limitations associated with access to high-resolution data, and access to ready-to-use product. In general, users expect to access a ready-to-use product, transformed from the raw EO data into usable information. Related to this is the question of whether this processing is best done within an organization or sourced from outside. Our results suggest that, despite the potential of EO data for informing environmental management in Brazil, its use remains constrained by its lack of suitably trained personnel and financial resources, as well as the poor communication between institutions.
Trajectory Data Analysis on the Spatial and Temporal Influence of Pedestrian Flow on Path Planning Decision
Authors: Kim Jeongyun , Tak Sehyun , Bierlaire Michel , Yeo Hwasoo
Published: December 2020

The modeling of walking behavior and design of walk-friendly urban pathways have been of interest to many researchers over the past decades. One of the major issues in pedestrian modeling is path planning decision-making in a dynamic walking environment with different pedestrian flows. While previous studies have agreed that pedestrian flow influences path planning, only a few studies have dealt with the empirical data to show the relationship between pedestrian flow and path planning behavior. This study introduces a new methodology for analyzing pedestrian trajectory data to find the dynamic walking conditions that influence the path planning decision. The comparison of the pedestrians’ path shows that the higher proportion of opposite flows are, the greater they influence the path selection decision. In this study, we investigate the relationship between the opposite flow changes and path planning behavior and find the spatial and temporal ranges of the opposite flow that affects the path planning behavior. Lastly, we find the ratio of pedestrians that update their paths with respect to the opposite flow rate.
Characterization of Pseudotachylite and Fault Gouges in Drill Cores from Andong, Korea and Its Implications for Paleo-Earthquakes
Authors: Choo Chang Oh , Jo Su Hyeon , Lee Sang-Youl , Lee Sang-Eun , Jeong Gyo-Cheol
Published: December 2020

Pseudotachylite and fault gouges were observed in core samples of Precambrian granitic gneiss drilled from depths as great as 1000 m in Andong, Korea. Fault gouges were found in the upper parts of the borehole, whereas pseudotachylites developed in the lower parts. Pseudotachylite with widths varying from a few mm to 10 cm sharply contacted or were interlayered with the host rock. The quartz-rich portion of the granitic gneiss remained unaffected, but the mafic portion was melted preferentially. The glassy surface of pseudotachylite is characterized by a smooth, glassy matrix with an amorphous phase and silicate beads with diameters of ~200 nm, together with slickenlines. Slickenlines composed of parallel grooves showed a wavelength of 4–7 μm and an amplitude < 1–2 μm. Residual or surviving grains have rounded corners and edges, indicating that those grains experienced abrasion, possibly from grain rotation or shear stress. Both melting and crushing contribute to the formation of pseudotachylite. Fe was always enriched in the glassy matrix, indicating that the pseudotachylite matrix originated from mafic minerals. The occurrence of pseudotachylite related to paleo-earthquake events showed that crystalline rocks in this area are unsatisfactory candidates for deep-disposal sites for high-level nuclear waste.
Analysis of China’s Iron Trade Flow: Quantity, Value and Regional Pattern
Authors: Chen Xinxi , Mao Jiansu , Tian Hezhong
Published: December 2020

Iron is an important metal material that supports the development of society and national economies. Due to the uneven distribution of resources, there is frequent trade around the world. Therefore, mastering the global flow path and trade pattern provides an essential basis for the sustainable utilization of iron and related products. Based on the artificial flow of iron in international trade, this study used the material flow analysis method to investigate this flow. Based on the data of China’s international iron trade from China Customs and the United Nations trade administration, this study systematically analyzed the structure, type, quantity, and value of iron-containing commodities in 2018. The results were as follows: (1) China was a net importer of iron and formed a trade structure of “import raw materials and export products.” (2) There was a large trade surplus in China’s iron international trade. The quality of iron exported by China was high, and the price is relatively low; therefore, countries around the world have a great dependence on the iron imported from China. (3) Compared with developed countries, China is in urgent need of high-end technologies and can only import high-tech iron products from abroad. Therefore, the value of China’s exports of iron-containing commodities is relatively low, while that of its imports is relatively high.
Local Energy Projects on Islands: Assessing the Creation and Upscaling of Social Niches
Authors: Tsagkari Marula
Published: December 2020

Islands have great potential for renewable energy, and several pilot and experimental projects have been set up on islands globally, aiming to promote clean energy and self-sufficiency. Many of these decentralized energy initiatives oppose the established regimes of centralized electricity generation and introduce new forms of organization and management. Thus, they can be considered social niches. The aim of the present study is to explore the transition potential of renewable energy projects on three islands located in southern Europe. The analysis mobilizes literature on the strategic niche management theory (SNM) with a focus on the role of the various actors and the different management models. Through a systematic analysis of policy documents and the literature, enriched by interviews, the paper identifies different types of renewable energy projects and discusses the potential for scale up. The paper concludes that these projects are currently in the inter-local phase, and decentralization is not only an important innovation for energy production, but also a new form of energy management often dominated by different actors than the established electricity system.
Mechanistic Insights into Plant Chiral Growth
Authors: Nakamura Masayoshi , Hashimoto Takashi
Published: December 2020

The latent left–right asymmetry (chirality) of vascular plants is best witnessed as a helical elongation of cylindrical organs in climbing plants. Interestingly, helical handedness is usually fixed in given species, suggesting genetic control of chirality. Arabidopsis thaliana, a small mustard plant, normally does not twist but can be mutated to exhibit helical growth in elongating organs. Genetic, molecular and cell biological analyses of these twisting mutants are providing mechanistic insights into the left–right handedness as well as how potential organ skewing is suppressed in most plants. Growth direction of elongating plant cells is determined by alignment of cellulose microfibrils in cell walls, which is guided by cortical microtubules localized just beneath the plasma membrane. Mutations in tubulins and regulators of microtubule assembly or organization give rise to helical arrangements of cortical microtubule arrays in Arabidopsis cells and cause helical growth of fixed handedness in axial organs such as roots and stems. Whether tubulins are assembled into a microtubule composed of straight or tilted protofilaments might determine straight or twisting growth. Mechanistic understanding of helical plant growth will provide a paradigm for connecting protein filament structure to cellular organization.
Stability Analysis of Tunnel Face Reinforced with Longitudinal Fiberglass Dowels Together with Steel Pipe Umbrella
Authors: Han Kaihang , Wang Xuetao , Hou Beibei , Cao Cheng-yong , Lin Xing-Tao
Published: December 2020

When tunnels are constructed under difficult geotechnical conditions in urban areas, tunnel face stability is one of the main issues to be addressed. To ensure tunnel face stability and reduce the impact of tunneling on adjacent structures, a few alternative procedures of ground reinforcement should be adopted, which includes reinforcing the soil ahead of the face using longitudinal fiberglass dowels alone or together with a steel pipe umbrella. It is of great academic value and engineering signification to reasonably determine the limit reinforcement density of these ground reinforcements. In this paper, an analytical prediction model is proposed by using the limit analysis method to analyze the tunnel face stability, and the favorable effects of longitudinal fiberglass dowels and steel pipe umbrella on tunnel face stability are investigated quantitatively. The analytical prediction model consists of a wedge ahead of the tunnel face, distributed force acting on the wedge exerted by overlying ground, and the support forces stem from the longitudinal fiberglass dowels. Moreover, sensitivity analysis is conducted to study the effect of the depth of cover, the tunnel shape, the reinforcement installation interval and the reduction factor on the required limit reinforcement density.
Computational Costs of Multi-Frontal Direct Solvers with Analysis-Suitable T-Splines
Authors: Paszyńska Anna , Paszyński Maciej
Published: December 2020

In this paper, we consider the computational cost of a multi-frontal direct solver used for the factorization of matrices resulting from a discretization of isogeometric analysis with T-splines, and analysis-suitable T-splines. We start from model projection or model heat transfer problems discretized over two-dimensional meshes, either uniformly refined or refined towards a point or an edge. These grids preserve several symmetries and they are the building blocks of more complicated grids constructed during adaptive isotropic refinement procedures. A large class of computational problems construct meshes refined towards point or edge singularities. We propose an ordering that permutes the matrix in a way that the computational cost of a multi-frontal solver executed on adaptive grids is linear. We show that analysis-suitable T-splines with our ordering, besides having other well-known advantages, also significantly reduce the computational cost of factorization with the multi-frontal direct solver. Namely, the factorization with N T-splines of order p over meshes refined to a point has a linear O(Np4) cost, and the factorization with T-splines on meshes refined to an edge has O(N2pp2) cost. We compare the execution time of the multi-frontal solver with our ordering to the Approximate Minimum Degree (AMD) and Cuthill–McKee orderings available in Octave.
Evolutionary Detection Accuracy of Secret Data in Audio Steganography for Securing 5G-Enabled Internet of Things
Authors: Alhaddad Mohammed J. , Alkinani Monagi H. , Atoum Mohammed Salem , Alarood Alaa Abdulsalm
Published: December 2020

With the unprecedented growing demand for communication between Internet of Things (IoT) devices, the upcoming 5G and 6G technologies will pave the path to a widespread use of ultra-reliable low-latency applications in such networks. However, with most of the sensitive data being transmitted over wireless links, security, privacy and trust management are emerging as big challenges to handle. IoT applications vary, from self-driving vehicles, drone deliveries, online shopping, IoT smart cities, e-healthcare and robotic assisted surgery, with many applications focused on Voice over IP (VoIP) and require securing data from potential eavesdroppers and attackers. One well-known technique is a hidden exchange of secret data between the devices for which security can be achieved with audio steganography. Audio steganography is an efficient, reliable and low-latency mechanism used for securely communicating sensitive data over wireless links. MPEG-1 Audio Layer 3’s (MP3’s) bit rate falls within the acceptable sound quality required for audio. Its low level of noise distortion does not affect its sound quality, which makes it a good carrier medium for steganography and watermarking. The strength of any embedding technique lies with its undetectability measure. Although there are many detection techniques available for both steganography and watermarking, the detection accuracy of secret data has been proven erroneous. It has yet to be confirmed whether different bit rates or a constant sampling rate for embedding eases detection. The accuracy of detecting hidden information in MP3 files drops with the influence of the compression rate or increases. This drop or increase is caused by either the increase in file track size, the sampling rate or the bit rate. This paper presents an experimental study that evaluates the detection accuracy of the secret data embedded in MP3. Training data were used for the embedding and detection of text messages in MP3 files. Several iterations were evaluated. The experimental results show that the used approach was effective in detecting the embedded data in MP3 files. An accuracy rate of 97.92% was recorded when detecting secret data in MP3 files under 128-kbps compression. This result outperformed the previous research work.
Street Name Data as a Reflection of Migration and Settlement History
Authors: Berkemer Sarah J. , Stadler Peter F.
Published: December 2020

Street names (odonyms) play an important role not only as descriptors of geographic locations but also due to their sociological and political connotations and commemorative character. Here we analyse street names in Europe and North America extracted from OpenStreetMap, asking in particular to what extent odonyms reflect early European settlements in the New World, i.e., the immigration of German, Austrian and Scandinavian minorities. We observe that old street names of European origin can predominantly be found in rural areas. North American street names indeed recapitulate local and regional settlement histories. The aim of this study is to demonstrate that easily accessible data sets from freely available map data such as street names convey usable information concerning migration patterns and the history of settlements in the case of European immigrants in North America as well as colonial history. We provide a freely available pipeline to analyse this kind of data.