bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Comparison of Oil Spill and Ship Classification from X-Band Dual- and Single-Polarized SAR Image Using Support Vector Machine, Random Forest, and Deep Neural Network
Authors: Baek Won-Kyung , Jung Hyung-Sup
Published: August 2021

It is well known that the polarization characteristics in X-band synthetic aperture radar (SAR) image analysis can provide us with additional information for marine target classification and detection. Normally, dual-and single-polarized SAR images are acquired by SAR satellites, and then we must determine how accurate the marine mapping performance from dual-polarized (pol) images is versus the marine mapping performance from the single-pol images in a given machine learning model. The purpose of this study is to compare the performance of single- and dual-pol SAR image classification achieved by the support vector machine (SVM), random forest (RF), and deep neural network (DNN) models. The test image is a TerraSAR-X dual-pol image acquired from the 2007 Kerch Strait oil spill event. For this, 824,026 pixels and 1,648,051 pixels were extracted from the image for the training and test, respectively, and sea, ship, oil, and land objects were classified from the image by using the three machine learning methods. The mean f1-scores of the SVM, RF, and DNN models resulting from the single-pol image were approximately 0.822, 0.882, and 0.889, respectively, and those from the dual-pol image were about 0.852, 0.908, and 0.898, respectively. The performance improvement achieved by dual-pol was about 3.6%, 2.9%, and 1% in SVM, RF, and DNN, respectively. The DNN model had the best performance (0.889) in the single-pol test while the RF model was best (0.908) in the dual-pol test. The performance improvement was approximately 2.1% and not noticeable. If the condition that dual-pol images have two-times lower spatial resolution versus single-pol images in the azimuth direction is considered, a small improvement may not be valuable. Therefore, the results show that the performance improvement by X-band dual-pol image may be not remarkable when classifying the sea, ships, oil spills, and sea and land surfaces.
Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements
Authors: Zhang Weihao , Shi Jiancun , Yi Huiwei , Zhu Yan , Xu Bing
Published: August 2021

Determining the geographic location and spatial distribution of underground goaf is of great significance for the prevention of mining subsidence hazards and the detection of illegal mining. However, traditional goaf detection techniques mainly focus on geophysical methods that are labor intensive, have low efficiency, and are expensive. Due to the large range and off-site monitoring capability of interferometric synthetic aperture radar (InSAR) techniques, research on goaf location detection based on InSAR measurements has been increasing. This paper proposes a new method for locating underground goaf based on cross-iteration and InSAR measurements. Firstly, the functional relationship between the geometric parameters of the goaf and the line of sight (LOS) deformation retrieved by InSAR techniques is constructed. Then, the three initial model parameters of the probability integration method (PIM) are determined by mining geological conditions. Finally, the cross-iteration method is used to determine the parameters to characterize the spatial location of underground goaf. The experimental results show that the average relative errors of the simulated experiment and the real experiment are 1.5% and 5.1%, respectively, and the inverted goaf parameters are in good agreement with the real values. Moreover, the proposed method only requires the main lithology of the overlying rock in the goaf and does not depend on the accuracy of PIM model parameters. Therefore, this method has engineering application value for the detection of goaf lacking actual measurement data or that caused by illegal mining.
Information-Based Georeferencing of an Unmanned Aerial Vehicle by Dual State Kalman Filter with Implicit Measurement Equations
Authors: Moftizadeh Rozhin , Vogel Sören , Neumann Ingo , Bureick Johannes , Alkhatib Hamza
Published: August 2021

Georeferencing a kinematic Multi-Sensor-System (MSS) within crowded areas, such as inner-cities, is a challenging task that should be conducted in the most reliable way possible. In such areas, the Global Navigation Satellite System (GNSS) data either contain inevitable errors or are not continuously available. Regardless of the environmental conditions, an Inertial Measurement Unit (IMU) is always subject to drifting, and therefore it cannot be fully trusted over time. Consequently, suitable filtering techniques are required that can compensate for such possible deficits and subsequently improve the georeferencing results. Sometimes it is also possible to improve the filter quality by engaging additional complementary information. This information could be taken from the surrounding environment of the MSS, which usually appears in the form of geometrical constraints. Since it is possible to have a high amount of such information in an environment of interest, their consideration could lead to an inefficient filtering procedure. Hence, suitable methodologies are necessary to be extended to the filtering framework to increase the efficiency while preserving the filter quality. In the current paper, we propose a Dual State Iterated Extended Kalman Filter (DSIEKF) that can efficiently georeference a MSS by taking into account additional geometrical information. The proposed methodology is based on implicit measurement equations and nonlinear geometrical constraints, which are applied to a real case scenario to further evaluate its performance.
Class-Wise Fully Convolutional Network for Semantic Segmentation of Remote Sensing Images
Authors: Tian Tian , Chu Zhengquan , Hu Qian , Ma Li
Published: August 2021

Semantic segmentation is a fundamental task in remote sensing image interpretation, which aims to assign a semantic label for every pixel in the given image. Accurate semantic segmentation is still challenging due to the complex distributions of various ground objects. With the development of deep learning, a series of segmentation networks represented by fully convolutional network (FCN) has made remarkable progress on this problem, but the segmentation accuracy is still far from expectations. This paper focuses on the importance of class-specific features of different land cover objects, and presents a novel end-to-end class-wise processing framework for segmentation. The proposed class-wise FCN (C-FCN) is shaped in the form of an encoder-decoder structure with skip-connections, in which the encoder is shared to produce general features for all categories and the decoder is class-wise to process class-specific features. To be detailed, class-wise transition (CT), class-wise up-sampling (CU), class-wise supervision (CS), and class-wise classification (CC) modules are designed to achieve the class-wise transfer, recover the resolution of class-wise feature maps, bridge the encoder and modified decoder, and implement class-wise classifications, respectively. Class-wise and group convolutions are adopted in the architecture with regard to the control of parameter numbers. The method is tested on the public ISPRS 2D semantic labeling benchmark datasets. Experimental results show that the proposed C-FCN significantly improves the segmentation performances compared with many state-of-the-art FCN-based networks, revealing its potentials on accurate segmentation of complex remote sensing images.
Daytime Cloud Detection Algorithm Based on a Multitemporal Dataset for GK-2A Imagery
Authors: Lee Soobong , Choi Jaewan
Published: August 2021

Cloud detection is an essential and important process in remote sensing when surface information is required for various fields. For this reason, we developed a daytime cloud detection algorithm for GEOstationary KOrea Multi-Purpose SATellite 2A (GEO-KOMPSAT-2A, GK-2A) imagery. For each pixel, the filtering technique using angular variance, which denotes the change in top of atmosphere (TOA) reflectance over time, was applied, and filtering technique by using the minimum TOA reflectance was used to remove remaining cloud pixels. Furthermore, near-infrared (NIR) and normalized difference vegetation index (NDVI) images were applied with dynamic thresholds to improve the accuracy of the cloud detection results. The quantitative results showed that the overall accuracy of proposed cloud detection was 0.88 and 0.92 with Visible Infrared Imaging Radiometer Suite (VIIRS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), respectively, and indicated that the proposed algorithm has good performance in detecting clouds.
Quantifying Urban Vegetation Dynamics from a Process Perspective Using Temporally Dense Landsat Imagery
Authors: Yu Wenjuan , Zhou Weiqi , Dawa Zhaxi , Wang Jia , Qian Yuguo , Wang Weimin
Published: August 2021

Urban vegetation can be highly dynamic due to the complexity of different anthropogenic drivers. Quantifying such dynamics is crucially important as it is a prerequisite to understanding its social and ecological consequences. Previous studies have mostly focused on the urban vegetation dynamics through monotonic trends analysis in certain intervals, but not considered the process which provides important insights for urban vegetation management. Here, we developed an approach that integrates trends with dynamic analysis to measure the vegetation dynamics from the process perspective based on the time-series Landsat imagery and applied it in Shenzhen, a coastal megacity in southern China, as an example. Our results indicated that Shenzhen was turning green from 2000–2020, even though a large-scale urban expansion occurred during this period. Approximately half of the city (49.5%) showed consistent trends in greening, most of which were located in the areas within the ecological protection baseline. We also found that 35.3% of the Shenzhen city experienced at least a one-time change in urban greenness that was mostly caused by changes in land cover types (e.g., vegetation to developed land). Interestingly, 61.5% of these lands showed trends in greening in the recent change period and most of them were distributed in build-up areas. Our approach that integrates trends analysis and dynamic process reveals information that cannot be discovered by monotonic trends analysis alone, and such information can provide insights for urban vegetation planning and management.
Cascade and Fusion: A Deep Learning Approach for Camouflaged Object Sensing
Authors: Huang Kaihong , Li Chunshu , Zhang Jiaqi , Wang Beilun
Published: August 2021

The demand for the sensor-based detection of camouflage objects widely exists in biological research, remote sensing, and military applications. However, the performance of traditional object detection algorithms is limited, as they are incapable of extracting informative parts from low signal-to-noise ratio features. To address this problem, we propose Camouflaged Object Detection with Cascade and Feedback Fusion (CODCEF), a deep learning framework based on an RGB optical sensor that leverages a cascaded structure with Feedback Partial Decoders (FPD) instead of a traditional encoder–decoder structure. Through a selective fusion strategy and feedback loop, FPD reduces the loss of information and the interference of noises in the process of feature interweaving. Furthermore, we introduce Pixel Perception Fusion (PPF) loss, which aims to pay more attention to local pixels that might become the edges of an object. Experimental results on an edge device show that CODCEF achieved competitive results compared with 10 state-of-the-art methods.
Temperature Monitoring in Hyperthermia Treatments of Bone Tumors: State-of-the-Art and Future Challenges
Authors: De Tommasi Francesca , Massaroni Carlo , Grasso Rosario Francesco , Carassiti Massimiliano , Schena Emiliano
Published: August 2021

Bone metastases and osteoid osteoma (OO) have a high incidence in patients facing primary lesions in many organs. Radiotherapy has long been the standard choice for these patients, performed as stand-alone or in conjunction with surgery. However, the needs of these patients have never been fully met, especially in the ones with low life expectancy, where treatments devoted to pain reduction are pivotal. New techniques as hyperthermia treatments (HTs) are emerging to reduce the associated pain of bone metastases and OO. Temperature monitoring during HTs may significantly improve the clinical outcomes since the amount of thermal injury depends on the tissue temperature and the exposure time. This is particularly relevant in bone tumors due to the adjacent vulnerable structures (e.g., spinal cord and nerve roots). In this Review, we focus on the potential of temperature monitoring on HT of bone cancer. Preclinical and clinical studies have been proposed and are underway to investigate the use of different thermometric techniques in this scenario. We review these studies, the principle of work of the thermometric techniques used in HTs, their strengths, weaknesses, and pitfalls, as well as the strategies and the potential of improving the HTs outcomes.
In-Line Mach–Zehnder Interferometers Based on a Capillary Hollow-Core Fiber Using Vernier Effect for a Highly Sensitive Temperature Sensor
Authors: Marrujo-García Sigifredo , Hernández-Romano Iván , May-Arrioja Daniel A. , Minkovich Vladimir P. , Torres-Cisneros Miguel
Published: August 2021

In this paper, we propose a highly sensitive temperature sensor based on two cascaded Mach–Zehnder interferometers (MZIs) that work using the Vernier effect. The all-fiber MZIs were assembled by splicing a segment of capillary hollow-core fiber (CHCF) between two sections of multimode fibers (MMFs). This cascaded configuration exhibits a temperature sensitivity of 1.964 nm/°C in a range from 10 to 70 °C, which is ~67.03 times higher than the sensitivity of the single MZI. Moreover, this device exhibits a high-temperature resolution of 0.0153 °C. A numerical analysis was carried out to estimate the devices’ temperature sensitivity and calculate the magnification of the sensitivity produced by the Vernier effect. The numerical results have an excellent agreement with the experimental results and provide a better insight into the working principle of the MZI devices. The sensor’s performance, small size, and easy fabrication make us believe that it is an attractive candidate for temperature measurement in biological applications.
Generator of Slow Denial-of-Service Cyber Attacks
Authors: Sikora Marek , Fujdiak Radek , Kuchar Karel , Holasova Eva , Misurec Jiri
Published: August 2021

In today’s world, the volume of cyber attacks grows every year. These attacks can cause many people or companies high financial losses or loss of private data. One of the most common types of attack on the Internet is a DoS (denial-of-service) attack, which, despite its simplicity, can cause catastrophic consequences. A slow DoS attack attempts to make the Internet service unavailable to users. Due to the small data flows, these attacks are very similar to legitimate users with a slow Internet connection. Accurate detection of these attacks is one of the biggest challenges in cybersecurity. In this paper, we implemented our proposal of eleven major and most dangerous slow DoS attacks and introduced an advanced attack generator for testing vulnerabilities of protocols, servers, and services. The main motivation for this research was the absence of a similarly comprehensive generator for testing slow DoS vulnerabilities in network systems. We built an experimental environment for testing our generator, and then we performed a security analysis of the five most used web servers. Based on the discovered vulnerabilities, we also discuss preventive and detection techniques to mitigate the attacks. In future research, our generator can be used for testing slow DoS security vulnerabilities and increasing the level of cyber security of various network systems.
Because You’re Worth It! The Medicalization and Moralization of Aesthetics in Aging Women
Authors: Pussetti Chiara
Published: August 2021

In this article—based on the fieldwork I conducted in Lisbon (Portugal) between 2018 and 2021, employing in-depth ethnography and self-ethnography—I describe the experience of the medicalization and moralization of beauty in Portuguese women aged 45–65 years. I examine the ways in which practitioners inscribe their expert knowledge on their patients’ bodies, stigmatizing the marks of time and proposing medical treatments and surgeries to “repair” and “correct” them. Beauty and youth are symbolically constructed in medical discourse as visual markers of health, an adequate lifestyle, a strong character and good personal choices (such as not smoking, and a healthy diet and exercise habits). What beauty means within the discourse of anti-aging and therapeutic rejuvenation is increasingly connected to an ideal gender performance of normative, white, middle-class, heterosexual femininity that dismisses structural determinants. The fantasy of eternal youth, linked to a neoliberal ideology of limitless enhancement and individual responsibility, is firmly entrenched in moralizing definitions of aesthetics and gender norms. Finally, my article highlights the ways in which the women I interviewed do not always passively accept the discourse of the devaluation of the ageing body, defining femininity and ageing in their own terms by creating personal variants of the hegemonic normative discourses on beauty and successful ageing.
Social Dimensions in CPS & IoT Based Automated Production Systems
Authors: El-Haouzi Hind Bril , Valette Etienne , Krings Bettina-Johanna , Moniz António Brandão
Published: August 2021

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap between humans and systems in which human was seen as an important source of errors and disruptions. Today, the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised awareness about the central role humans have to play in manufacturing systems, the design of which must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of Things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different human social dimensions associated with CPS and IoT and focuses on their conceptual evolution regarding automated production systems’ sociability, notably by bringing humans back in the loop. Hereby, this paper aims to take stock of current research trends to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. Consequently, different models of sociability as a way to integrate humans in the broad sense and/or the develop future automated production systems have been identified from the literature and analysed.
Facing the Unknown: Healthcare Workers’ Concerns, Experiences, and Burnout during the COVID-19 Pandemic—A Mixed-Methods Study in an Israeli Hospital
Authors: Dopelt Keren , Bashkin Osnat , Davidovitch Nadav , Asna Noam
Published: August 2021

The aim of this study was to describe the experiences of healthcare workers during the first wave of the coronavirus crisis. In a mixed-methods study, data were collected through an online survey completed by 263 hospital staff members, as well as 10 semi-structured, in-depth interviews with physicians, nurses, and medical technologists working on coronavirus wards. Respondents expressed extremely high levels of concern for family members, but they were less apprehensive about their own health and safety. Nurses displayed more apprehension and burnout compared to healthcare workers in other professional roles. The in-depth interviews reinforced and supplemented the survey findings and deepened our understanding of the experience of healthcare workers directly involved in the first wave of coronavirus patient care. The findings of this study illuminate the main concerns of hospital staff during the first wave of the COVID-19 pandemic and deepen our understanding of issues that require systemic attention in order to strengthen mental resilience among hospital staff. The steps required to continue fighting the virus include the development of a mental and emotional support network for healthcare workers to safeguard them and their health, as they care for patients, and to provide ongoing psychosocial support. As later waves of COVID-19 continued, these recommendations are even more pertinent.
Product Design for Automated Remanufacturing—A Case Study of Electric and Electronic Equipment in Sweden
Authors: Shahbazi Sasha , Johansen Kerstin , Sundin Erik
Published: August 2021

Remanufacturing is one of the main practices toward a circular economy and industrial sustainability. Remanufacturing is highly dependent on how circular products are designed and developed. Remanufacturing can also benefit from automation for efficiency, accuracy and flexibility. This paper, via a multiple case study, connects the three areas of remanufacturing, product design and automation and investigates how circular product design can facilitate automation remanufacturing processes. First, circular product design guidelines are discussed with regard to remanufacturing. Second, potential areas for automation at three remanufacturers of electric and electronic equipment are pinpointed. Finally, design guidelines are connected to the identified potential automation areas in each remanufacturing process and discussed together. According to our results, the main incentives for automating remanufacturing processes are mainly related to the work environment, efficiency and quality. In addition, several design guidelines can facilitate automated remanufacturing processes; for instance, the standardization of components, fasteners and remanufacturing tools across different models and brands can also facilitate automated remanufacturing, where products can easily and nondestructively be disassembled by a robot or a machine.
The Other Side of the (Policy) Coin: Analyzing Exnovation Policies for the Urban Mobility Transition in Eight Cities around the Globe
Authors: Graaf Lisa , Werland Stefan , Lah Oliver , Martin Emilie , Mejia Alvin , Muñoz Barriga María Rosa , Nguyen Hien Thi Thu , Teko Edmund , Shrestha Shritu
Published: August 2021

Many cities all over the world highlight the need to transform their urban mobility systems into more sustainable ones, to confront pressing issues such as air and noise pollution, and to deliver on climate change mitigation action. While the support of innovations is high on the agenda of both national and local authorities, consciously phasing-out unsustainable technologies and practices is often neglected. However, this other side of the policy coin, ‘exnovation’, is a crucial element for the mobility transition. We developed a framework to facilitate a more comprehensive assessment of urban mobility transition policies, systematically integrating exnovation policies. It links exnovation functions as identified in transition studies with insights from urban mobility studies and empirical findings from eight city case studies around the world. The findings suggest that most cities use some kinds of exnovation policies to address selective urban mobility issues, e.g., phasing-out diesel buses, restricting the use of polluting motor vehicles in some parts of the city, etc. Still, we found no evidence for a systematic exnovation approach alongside the innovation policies. Our framework specifies exnovation functions for the urban mobility transition by lining out policy levers and concrete measure examples. We hope that the framework inspires future in-depth research, but also political action to advance the urban mobility transition.
A Methodological Framework to Support the Sustainable Innovation Development Process: A Collaborative Approach
Authors: Orellano Martha , Lambey-Checchin Christine , Medini Khaled , Neubert Gilles
Published: August 2021

The notion of sustainable innovation (SI) emerged recently in the academic literature and evokes deep changes in organizations’ products, processes, and practices to favour the creation of social and environmental value in addition to economic returns. The development of SI implies a collaborative process that requires the orchestration of several actors and streams of knowledge to be successful. Indeed, companies adopting the SI path need structured methodologies to guide the collaboration process with internal and external actors and support the decision process. Nevertheless, the literature has focused on the analysis of determinants and drivers of sustainable innovation development, while the process perspective has been discussed less. Through an in-depth case study in a large-sized company in France, this article proposes a methodological framework to guide the collaborative process in the early phases of sustainable innovation development. The framework relies on a combination of qualitative research and a multicriteria decision aiding method (AHP). The contributions of this work address two main aspects: (i) the conceptualization of sustainable innovation (SI) and (ii) the collaborative process between internal and external actors to develop SI. Firstly, our study leads to two additional dimensions to complete the concept of SI, traditionally based on the three pillars of sustainability (economic, environmental, and social), by adding the functional and relational dimensions. Secondly, concerning the collaborative process to develop SI, our framework proposes a structured methodology following five steps: definition of the project scope, setting actors’ motivations, defining satisfaction criteria, proposing SI solutions, and performing a decision-aiding process to define the preference profiles of the key actors.
A Comprehensive Assessment of Exposure and Vulnerabilities in Multi-Hazard Urban Environments: A Key Tool for Risk-Informed Planning Strategies
Authors: Galderisi Adriana , Limongi Giada
Published: August 2021

Although the increase in the frequency and intensity of disasters assigns a key role to disaster risk management in current debate on sustainable development, the efforts of national and local authorities to develop risk-informed planning strategies and increase disaster preparedness are still limited. In multi-hazard urban environments, the main criticality to support risk-informed planning strategies is the persisting lack of effective knowledge bases focused on the vulnerability of exposed assets to different hazards. Hence, this contribution, according to the first priority of the Sendai Framework for Disaster Risk Reduction—understanding disaster risk—and by tidying up methods and indicators developed in both EU research projects and scientific studies devoted to multi-risk and vulnerability assessment, aims at better using available knowledge to guide risk-informed spatial planning. In detail, an indicator-based method to carry out a comprehensive exposure and vulnerability analysis has been outlined and tested on a case study area, the multi-hazard urban area of Campi Flegrei, located in the western part of the metropolitan city of Naples in the South of Italy. The proposed method may contribute to the building up of an effective risk knowledge base, enabling planners to easily access information on exposure and vulnerabilities to different hazards, and to differently combine them into output maps capable of supporting risk- informed planning strategies.
Street Design for Hedonistic Sustainability through AI and Human Co-Operative Evaluation
Authors: Sou Kanyou , Shiokawa Hiroya , Yoh Kento , Doi Kenji
Published: August 2021

Recently, there has been an increasing emphasis on community development centered on the well-being and quality of life of citizens, while pursuing sustainability. This study proposes an AI and human co-operative evaluation (AIHCE) framework that facilitates communication design between designers and stakeholders based on human emotions and values and is an evaluation method for street space. AIHCE is an evaluation method based on image recognition technology that performs deep learning of the facial expressions of both people and the city; namely, it consists of a facial expression recognition model (FERM) and a street image evaluation model (SIEM). The former evaluates the street space based on the emotions and values of the pedestrian’s facial expression, and the latter evaluates the target street space from the prepared street space image. AIHCE is an integrated framework for these two models, enabling continuous and objective evaluation of space with simultaneous subjective emotional evaluation, showing the possibility of reflecting it in the design. It is expected to contribute to fostering people’s awareness that streets are public goods reflecting the basic functions of public spaces and the values and regional characteristics of residents, contributing to the improvement of the sustainability of the entire city.
The CirCo (Circular Coffee) Project: A Case Study on Valorization of Coffee Silverskin in the Context of Circular Economy in Italy
Authors: Overturf Emily , Pezzutto Simon , Boschiero Martina , Ravasio Nicoletta , Monegato Achille
Published: August 2021

Coffee silverskin (CSS) is one of the main byproducts of coffee roasting and poses a potential risk to the environment if disposed of incorrectly. Each year in Italy, over 500,000 tonnes of green coffee are imported for roasting followed by consumption or export. This results in over 7500 tonnes of CSS produced each year which is typically disposed of as solid waste. Silverskin contains lignocellulose and can be used as a substitute for other raw materials to produce paper pulp. Both Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) were performed to compare the impact and cost of CSS paper production to conventional paper production using only virgin pulp. It was shown that the addition of CSS reduces the environmental impact of paper production by 10% and greenhouse gas (GHG) emissions by 13% compared to conventional production with no cost increase (0.01% reduction with addition of CSS) for the producer. The results of this case study show that the utilization of CSS for paper production at the national level in Italy represents a suitable example of circular economy (CE).
An Analysis of Spatial Accessibility Changes According to the Attractiveness Index of Public Libraries Using Social Media Data
Authors: Kim Jiyoung , Lee Jiwon
Published: August 2021

Public libraries provide equitable access to information for all citizens, and they play an important role in preserving and promoting culture, formal education and self-education, and enriching leisure time. Accordingly, there has been an increasing amount of research on the use factors and accessibility of public libraries, but research on the accessibility of public libraries in non-Western cities is insufficient compared to the corresponding research on other public facilities. In particular, in high-density cities such as Seoul, the Republic of Korea, it may be desirable in terms of sustainability to focus on the qualitative, rather than the quantitative, expansion of public libraries. In previous studies, the attractive factors on the supply side were analyzed using questionnaire surveys, but in this study, the attractive factors for users were quantified in the form of the library attraction index by means of user-generated contents such as location-based social media, and the accessibility was analyzed based on this. The results showed that many public libraries have high accessibility, with a high library attraction index. Therefore, these findings indicate that the qualitative expansion of public libraries is important for information equality. It is meaningful that this study analyzed the attractive factors on the supply side by analyzing the contents generated by users.
Brief Literature Review and Classification System of Reliability Methods for Evaluating the Stability of Earth Slopes
Authors: Przewłócki Jarosław
Published: August 2021

The issue of slope stability is one of the most important and yet most difficult geotechnical problems. Assessing slope stability is particularly difficult because of the many uncertainties involved in the process. To take these uncertainties into account, probabilistic methods are used, and the reliability approach is adopted. There are many methods for reliability assessment of earth slope stability. However, there is no system that would organize all of these methods in an unambiguous way. In fact, these methods can be classified in different ways: by assignment to a deterministic classification of methods, by description of uncertainties of soil parameters, by level of reliability according to the theory of reliability, etc. The huge number of articles summarizing the research in this field, but in various “disordered” directions, certainly do not facilitate the understanding or ultimately the practical application of the reliability approach by the engineer. The paper proposes a universal classification system of reliability methods for evaluating the stability of earth slopes. This proposal is preceded by a brief literature review of both historical background and contemporary research on reliability analysis of earth slope stability.
Evaluating the Symmetry in Plantar Pressure Distribution under the Toes during Standing in a Postural Pedobarographic Examination
Authors: Gawronska Karolina , Lorkowski Jacek
Published: August 2021

Pedobarography is a safe, non-invasive diagnostic method that enables estimation of plantar pressure distribution. This article aims to describe the symmetry between right and left toes in the Polish adult population using data obtained during postural pedobarographic examinations. Eighty-two patients, both sexes, with a mean age of 42.12 (range 19–70), without significant pathologies, participated in the study. Plantar pressure was evaluated using a PEL38 pressure plate. The study applies the elements of Cavanagh’s classification to identify the foot sole regions: Hallux, Second Toe and Lateral Toe areas and the entire foot surface. The parameters measured included maximal and average pressures, total support area for each foot, and contact area of the foot with the ground at individual moments of standing. The results showed significantly greater loading under the right Hallux in women. As regards men, higher values in the whole foot pressure distribution were noted on the left side. Plantar pressure distribution does not increase along with the global factors such as age and body mass. The findings suggest that the asymmetry in the morphological structure of the foot does not determine the asymmetry in the plantar pressure distribution. None of the feet studied had full symmetry on the entire surface.
Panorama of the Intracellular Molecular Concert Orchestrated by Actinoporins, Pore-Forming Toxins from Sea Anemones
Authors: Alvarez Carlos , Soto Carmen , Cabezas Sheila , Alvarado-Mesén Javier , Laborde Rady , Pazos Fabiola , Ros Uris , Hernández Ana María , Lanio María Eliana
Published: August 2021

Actinoporins (APs) are soluble pore-forming proteins secreted by sea anemones that experience conformational changes originating in pores in the membranes that can lead to cell death. The processes involved in the binding and pore-formation of members of this protein family have been deeply examined in recent years; however, the intracellular responses to APs are only beginning to be understood. Unlike pore formers of bacterial origin, whose intracellular impact has been studied in more detail, currently, we only have knowledge of a few poorly integrated elements of the APs’ intracellular action. In this review, we present and discuss an updated landscape of the studies aimed at understanding the intracellular pathways triggered in response to APs attack with particular reference to sticholysin II, the most active isoform produced by the Caribbean Sea anemone Stichodactyla helianthus. To achieve this, we first describe the major alterations these cytolysins elicit on simpler cells, such as non-nucleated mammalian erythrocytes, and then onto more complex eukaryotic cells, including tumor cells. This understanding has provided the basis for the development of novel applications of sticholysins such as the construction of immunotoxins directed against undesirable cells, such as tumor cells, and the design of a cancer vaccine platform. These are among the most interesting potential uses for the members of this toxin family that have been carried out in our laboratory.
The Impact of Textile Waste on the Features of High-Density Polyethylene (HDPE) Composites
Authors: Lahtela Ville , Kumar Anil , Kärki Timo
Published: August 2021

An increased amount of textile waste will be available in the future, and its utilization requires attention from various perspectives. The re-utilization of textile waste in a second material cycle is an option for dealing with a global problem that puts stress on the urban environment. In this study, almost 30 kg of clothing were recycled as a raw material in the structure of a composite, whose structural properties were analyzed. The studied materials were made from high-density polyethylene (HDPE), anhydride modified polyethylene, lubricant, and either polyethylene terephthalate (PET) or rayon fibers from recycled clothes. The recycled clothes were identified by a near-infrared (NIR) analyzer, followed by treatment of size reduction and materials compounding by agglomeration and compression molding technologies. The material properties were characterized by thickness swelling, water absorption, impact, and tensile testing. The recycled clothes fibers, acting as a filler component in the structure of the composite, could maintain the properties of the material at the same level as the reference material. PET fibers being used as a component resulted in a significant improvement in impact strength. The study showed that recycled clothes can be re-utilized as a substitute for raw materials, and can be part of a solution for future challenges involving textile waste, following the principles of the circular economy. Textile recycling create opportunities to improve the quality of urban life.
Significance of the Gut Microbiome for Viral Diarrheal and Extra-Intestinal Diseases
Authors: Desselberger Ulrich
Published: August 2021

The composition of the mammalian gut microbiome is very important for the health and disease of the host. Significant correlations of particular gut microbiota with host immune responsiveness and various infectious and noninfectious host conditions, such as chronic enteric infections, type 2 diabetes, obesity, asthma, and neurological diseases, have been uncovered. Recently, research has moved on to exploring the causalities of such relationships. The metabolites of gut microbiota and those of the host are considered in a ‘holobiontic’ way. It turns out that the host’s diet is a major determinant of the composition of the gut microbiome and its metabolites. Animal models of bacterial and viral intestinal infections have been developed to explore the interrelationships of diet, gut microbiome, and health/disease phenotypes of the host. Dietary fibers can act as prebiotics, and certain bacterial species support the host’s wellbeing as probiotics. In cases of Clostridioides difficile-associated antibiotic-resistant chronic diarrhea, transplantation of fecal microbiomes has sometimes cured the disease. Future research will concentrate on the definition of microbial/host/diet interrelationships which will inform rationales for improving host conditions, in particular in relation to optimization of immune responses to childhood vaccines.
Four Simple Biomimetic Mineralization Methods to Improve the Thermostability and Immunogenicity of Virus-like Particles as a Vaccine against Foot-and-Mouth Disease
Authors: Guo Mengnan , Li Jiajun , Teng Zhidong , Ren Mei , Dong Hu , Zhang Yun , Ru Jiaxi , Du Ping , Sun Shiqi , Guo Huichen
Published: August 2021

The need for a cold chain system during storage and transport substantially increases the cost of vaccines. Virus-like particles (VLPs) are among the best countermeasures against foot and mouth disease virus (FMDV). However, VLPs are composed of pure proteins, and thus, are susceptible to heat. To address this problem, four simple biomimetic mineralization methods with the use of calcium phosphate were developed to improve heat tolerance via biomineralization. The results showed that biomineralization can significantly improve the heat resistance of VLPs. The biomineralized VLPs can be stored at low as 25 °C for eight days, and 37 °C for four days. Animal experiments showed that biomineralization had no effect on the immunogenicity of VLPs or the expression of specific antibodies (Abs) and neutralizing Abs. Even after heat treatment at 37 °C for four days, the biomineralized VLPs remained immunogenic and produced highly specific and neutralizing Abs with a high rate of protection. These results suggest that these biomineralization approaches can promote the thermal stability of VLPs against and significantly reduce dependence on cold storage and delivery systems.
Predictors of COVID-19 Vaccine Intention among the Saudi Arabian Population: A Cross-Sectional Survey
Authors: Noushad Mohammed , Nassani Mohammad Zakaria , Koppolu Pradeep , Alsalhani Anas B. , Samran Abdulaziz , Alqerban Ali , Abusalim Ghadah Salim , Barakat Ali , Alshalhoub Mashari Bandar , Rastam Samer
Published: August 2021

The long-term solution to managing the current COVID-19 pandemic is through mass immunization of the population. However, uncertainty or unwillingness to receive the vaccine could be a barrier in attaining sufficient vaccine coverage. Therefore, understanding the psychology of the population towards the vaccines against COVID-19 is of paramount importance. Our study was aimed at determining the predictors of COVID-19 vaccine intention in the Saudi Arabian population. A structured questionnaire guided by the ‘Report of the SAGE working group on vaccine hesitancy’ was administered during a span of two months among the general population from all administrative regions of Saudi Arabia, proceeding the launch of the vaccination campaign. In total, 879 out of 1600 subjects responded and completed the survey (response rate 54.9%). About 56 percent of the participants intended to be vaccinated. The predictors of a higher intention to vaccinate included those 50 years of age or older, male subjects, people suffering from systemic disease/s, subjects who were not previously infected with COVID-19, those who follow the updates about COVID-19 vaccines, and adults with a higher level of anxiety about contracting coronavirus (p < 0.05). Results from our study and other similar studies can aid policy makers and stakeholders in planning effective strategies based on the changing behavior of the population.
Domestic Saudi Arabian Travellers’ Understanding about COVID-19 and Its Vaccination
Authors: Alshahrani Najim , Alshahrani Sultan , Farag Shehata , Rashid Harunor
Published: August 2021

Background: There is a lack of data on Saudi domestic air travellers’ understanding regarding COVID-19 and their attitude towards the COVID-19 vaccination. Objectives: This study aimed to assess Saudi domestic air travellers’ understanding regarding COVID-19 and attitude towards mandating the COVID-19 vaccination for travellers. Methods: A survey using a self-administered, structured, and closed-ended questionnaire was conducted among domestic air travellers in Saudi Arabia. Participants’ socio-demographic information, travel history, health status, and attitudes and willingness to accept the COVID-19 vaccination were collected and analysed. Results: Of the 2236 respondents who participated in the survey, 542 (24.25%) had a history of COVID-19, 803 (35.9%) were exposed to a COVID-19 case, 1425 (63.7%) were concerned about catching COVID-19 during air travel, 796 (35.6%) thought the COVID-19 vaccination should be obligatory for travellers, 1105 (49.4%) thought it should be optional, and 335 (15.0%) thought the vaccination was unnecessary. Being of the male gender (adjusted odds ratio [aOR] 1.41, 95% confidence interval [95% CI] 1.14–1.69), being concerned about contracting COVID-19 (aOR 1.34, 95% CI 1.12–2.10) and frequent travelling (aOR 1.40, 95% CI 1.10–3.40) were predictors of vaccination uptake. Conclusion: This study demonstrates that although domestic Saudi travellers were concerned about COVID-19 infection, vaccine hesitancy was prevalent among them.
Efficacy of Two Chlamydia abortus Subcellular Vaccines in a Pregnant Ewe Challenge Model for Ovine Enzootic Abortion
Authors: Livingstone Morag , Wattegedera Sean Ranjan , Palarea-Albaladejo Javier , Aitchison Kevin , Corbett Cecilia , Sait Michelle , Wilson Kim , Chianini Francesca , Rocchi Mara Silvia , Wheelhouse Nicholas , Entrican Gary , Longbottom David
Published: August 2021

Chlamydia abortus, the aetiological agent of enzootic abortion of ewes, is a major cause of reproductive loss in small ruminants worldwide, accounting for significant economic losses to the farming industry. Disease can be managed through the use of commercial inactivated or live whole organism-based vaccines, although both have limitations particularly in terms of efficacy, safety and disease-associated outbreaks. Here we report a comparison of two experimental vaccines (chlamydial outer membrane complex (COMC) and octyl glucoside (OG)-COMC) based on detergent extracted outer membrane preparations of C. abortus and delivered as prime-boost immunisations, with the commercial live vaccine Cevac® Chlamydia in a pregnant sheep challenge model. No abortions occurred in either experimental vaccine group, while a single abortion occurred in the commercial vaccine group. Bacterial shedding, as a measure of potential risk of transmission of infection to naïve animals, was lowest in the COMC vaccinated group, with reductions of 87.5%, 86.4% and 74% observed for the COMC, OG-COMC and live commercial vaccine groups, respectively, compared to the unvaccinated challenge control group. The results show that the COMC vaccine performed the best and is a safer efficacious alternative to the commercial vaccines. However, to improve commercial viability, future studies should optimise the antigen dose and number of inoculations required.
A Priority-Based Autonomous Intersection Management (AIM) Scheme for Connected Automated Vehicles (CAVs)
Authors: Zhang Hui , Zhang Rongqing , Chen Chen , Duan Dongliang , Cheng Xiang , Yang Liuqing
Published: August 2021

In this paper, we investigate the intersection traffic management for connected automated vehicles (CAVs). In particular, a decentralized autonomous intersection management scheme that takes into account both the traffic efficiency and scheduling flexibility is proposed, which adopts a novel intersection–vehicle model to check conflicts among CAVs in the entire intersection area. In addition, a priority-based collision-avoidance rule is set to improve the performance of traffic efficiency and shorten the delays of emergency CAVs. Moreover, a multi-objective function is designed to obtain the optimal trajectories of CAVs, which considers ride comfort, velocities of CAVs, fuel consumption, and the constraints of safety, velocity, and acceleration. Simulation results demonstrate that our proposed scheme can achieve good performance in terms of traffic efficiency and shortening the delays of emergency CAVs.