bluuebunny/crossref_metadata_2025 huggingface dataset:
Retrieval of Raindrop Size Distribution Using Dual-Polarized Microwave Signals from LEO Satellites: A Feasibility Study through Simulations
Authors: Shen Xi , Huang Defeng David
Published: September 2021

In this paper, a novel approach for raindrop size distribution retrieval using dual-polarized microwave signals from low Earth orbit satellites is proposed. The feasibility of this approach is studied through modelling and simulating the retrieval system which includes multiple ground receivers equipped with signal-to-noise ratio estimators and a low Earth orbit satellite communicating with the receivers using both vertically and horizontally polarized signals. Our analysis suggests that the dual-polarized links offer the opportunity to estimate two independent raindrop size distribution parameters. To achieve that, the vertical and horizontal polarization attenuations need to be measured at low elevation angles where the difference between them is more distinct. Two synthetic rain fields are generated to test the performance of the retrieval. Simulation results suggest that the specific attenuations for both link types can be retrieved through a least-squares algorithm. They also confirm that the specific attenuation ratio of vertically to horizontally polarized signals can be used to retrieve the slope and intercept parameters of raindrop size distribution.
ThermoSteg—Covert Channel for Microbolometer Thermographic Cameras
Authors: Sawicki Krzysztof , Bieszczad Grzegorz , Sosnowski Tomasz
Published: September 2021

The article presents a new concept—steganography in thermography. Steganography is a technique of hiding information in a non-obvious way and belongs to sciences related to information security. The proposed method, called ThermoSteg, uses a modification of one of the parameters of the thermal imaging camera—integration time—to embed the signal containing hidden information. Integration time changing makes the microbolometer array heat up while reading the sensors. The covert information can be extracted from the stream of thermograms recorded by another thermal camera that observes the first one. The covert channel created with the ThermoSteg method allows the transmission of covert data using a thermal sensor as a wireless data transmitter. This article describes a physical phenomenon that is exploited by the ThermoSteg method and two proposed methods of covert data extraction, and presents the results of experiments.
Immunoglobulin E Detection Method Based on Cascade Enzymatic Reaction Utilizing Portable Personal Glucose Meter
Authors: Han Hyogu , Park Junhyun , Ahn Jun
Published: September 2021

We herein describe a cascade enzymatic reaction (CER)-based IgE detection method utilizing a personal glucose meter (PGM), which relies on alkaline phosphatase (ALP) activity that regulates the amount of adenosine triphosphate (ATP). The amount of sandwich assay complex is determined according to the presence or absence of the target IgE. Additionally, the ALP in the sandwich assay catalyzes the dephosphorylation of ATP, a substrate of CER, which results in the changes in glucose level. By employing this principle, IgE was reliably detected at a concentration as low as ca. 29.6 ng/mL with high specificity toward various proteins. Importantly, the limit of detection (LOD) of this portable PGM-based approach was comparable to currently commercialized ELISA kit without expensive and bulky analysis equipment as well as complexed washing step. Finally, the diagnostic capability of this method was also successfully verified by reliably detecting IgE present in a real human serum sample with an excellent recovery ratio within 100 ± 6%.
Adaptive Navigation Algorithm with Deep Learning for Autonomous Underwater Vehicle
Authors: Ma Hui , Mu Xiaokai , He Bo
Published: September 2021

Precise navigation is essential for autonomous underwater vehicles (AUVs). The measurement deviation of the navigation sensors, especially the microelectromechanical systems (MEMS) sensors, is a crucial factor that affects the localization accuracy. Deep learning is a novel method to solve this problem. However, the calculation cycle and robustness of the deep learning method may be insufficient in practical application. This paper proposes an adaptive navigation algorithm with deep learning to address these questions and realize accurate navigation. Firstly, this algorithm uses deep learning to generate low-frequency position information to correct the error accumulation of the navigation system. Secondly, the χ2 rule is selected to judge if the Doppler velocity log (DVL) measurement fails, which could avoid interference from DVL outliers. Thirdly, the adaptive filter, based on the variational Bayesian (VB) method, is employed to estimate the navigation information simultaneous with the measurement covariance, improving navigation accuracy even more. The experimental results, based on AUV field data, show that the proposed algorithm could realize robust navigation performance and significantly improve position accuracy.
Deep Sparse Learning for Automatic Modulation Classification Using Recurrent Neural Networks
Authors: Zang Ke , Wu Wenqi , Luo Wei
Published: September 2021

Deep learning models, especially recurrent neural networks (RNNs), have been successfully applied to automatic modulation classification (AMC) problems recently. However, deep neural networks are usually overparameterized, i.e., most of the connections between neurons are redundant. The large model size hinders the deployment of deep neural networks in applications such as Internet-of-Things (IoT) networks. Therefore, reducing parameters without compromising the network performance via sparse learning is often desirable since it can alleviates the computational and storage burdens of deep learning models. In this paper, we propose a sparse learning algorithm that can directly train a sparsely connected neural network based on the statistics of weight magnitude and gradient momentum. We first used the MNIST and CIFAR10 datasets to demonstrate the effectiveness of this method. Subsequently, we applied it to RNNs with different pruning strategies on recurrent and non-recurrent connections for AMC problems. Experimental results demonstrated that the proposed method can effectively reduce the parameters of the neural networks while maintaining model performance. Moreover, we show that appropriate sparsity can further improve network generalization ability.
Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness
Authors: Chui Kwok Tai , Gupta Brij B. , Liu Ryan Wen , Zhang Xinyu , Vasant Pandian , Thomas J. Joshua
Published: September 2021

Road traffic accidents have been listed in the top 10 global causes of death for many decades. Traditional measures such as education and legislation have contributed to limited improvements in terms of reducing accidents due to people driving in undesirable statuses, such as when suffering from stress or drowsiness. Attention is drawn to predicting drivers’ future status so that precautions can be taken in advance as effective preventative measures. Common prediction algorithms include recurrent neural networks (RNNs), gated recurrent units (GRUs), and long short-term memory (LSTM) networks. To benefit from the advantages of each algorithm, nondominated sorting genetic algorithm-III (NSGA-III) can be applied to merge the three algorithms. This is named NSGA-III-optimized RNN-GRU-LSTM. An analysis can be made to compare the proposed prediction algorithm with the individual RNN, GRU, and LSTM algorithms. Our proposed model improves the overall accuracy by 11.2–13.6% and 10.2–12.2% in driver stress prediction and driver drowsiness prediction, respectively. Likewise, it improves the overall accuracy by 6.9–12.7% and 6.9–8.9%, respectively, compared with boosting learning with multiple RNNs, multiple GRUs, and multiple LSTMs algorithms. Compared with existing works, this proposal offers to enhance performance by taking some key factors into account—namely, using a real-world driving dataset, a greater sample size, hybrid algorithms, and cross-validation. Future research directions have been suggested for further exploration and performance enhancement.
Experiment Control and Monitoring System for LOG-a-TEC Testbed
Authors: Morano Grega , Hrovat Andrej , Vučnik Matevž , Puhan Janez , Gardašević Gordana , Vasiljević Dragan , Javornik Tomaž
Published: September 2021

The LOG-a-TEC testbed is a combined outdoor and indoor heterogeneous wireless testbed for experimentation with sensor networks and machine-type communications, which is included within the Fed4FIRE+ federation. It supports continuous deployment principles; however, it is missing an option to monitor and control the experiment in real-time, which is required for experiment execution under comparable conditions. The paper describes the implementation of the experiment control and monitoring system (EC and MS) as the upgrade of the LOG-a-TEC testbed. EC and MS is implemented within existing infrastructure management and built systems as a new service. The EC and MS is accessible as a new tab in sensor management system portal. It supports several commands, including start, stop and restart application, exit the experiment, flash or reset the target device, and displays the real-time status of the experiment application. When nodes apply Contiki-NG as their operating system, the Contiki-NG shell tool is accessible with the help of the newly developed tool, giving further experiment execution control capabilities to the user. By using the ZeroMQ concurrency framework as a message exchange system, information can be asynchronously sent to one or many devices at the same time, providing a real-time data exchange mechanism. The proposed upgrade does not disrupt any continuous deployment functionality and enables remote control and monitoring of the experiment. To evaluate the EC and MS functionality, two experiments were conducted: the first demonstrated the Bluetooth Low Energy (BLE) localization, while the second analysed interference avoidance in the 6TiSCH (IPv6 over the TSCH mode of IEEE 802.15.4e) wireless technology for the industrial Internet of Things (IIoT).
Real-Time Back Surface Landmark Determination Using a Time-of-Flight Camera
Authors: Ledwoń Daniel , Danch-Wierzchowska Marta , Bugdol Marcin , Bibrowicz Karol , Szurmik Tomasz , Myśliwiec Andrzej , Mitas Andrzej W.
Published: September 2021

Postural disorders, their prevention, and therapies are still growing modern problems. The currently used diagnostic methods are questionable due to the exposure to side effects (radiological methods) as well as being time-consuming and subjective (manual methods). Although the computer-aided diagnosis of posture disorders is well developed, there is still the need to improve existing solutions, search for new measurement methods, and create new algorithms for data processing. Based on point clouds from a Time-of-Flight camera, the presented method allows a non-contact, real-time detection of anatomical landmarks on the subject’s back and, thus, an objective determination of trunk surface metrics. Based on a comparison of the obtained results with the evaluation of three independent experts, the accuracy of the obtained results was confirmed. The average distance between the expert indications and method results for all landmarks was 27.73 mm. A direct comparison showed that the compared differences were statically significantly different; however, the effect was negligible. Compared with other automatic anatomical landmark detection methods, ours has a similar accuracy with the possibility of real-time analysis. The advantages of the presented method are non-invasiveness, non-contact, and the possibility of continuous observation, also during exercise. The proposed solution is another step in the general trend of objectivization in physiotherapeutic diagnostics.
Predictive Management Algorithm for Controlling PV-Battery Off-Grid Energy System
Authors: Alnejaili Tareq , Labdai Sami , Chrifi-Alaoui Larbi
Published: September 2021

This paper introduces an energy management strategy for an off-grid hybrid energy system. The hybrid system consists of a photovoltaic (PV) module, a LiFePO4 battery pack coupled with a Battery Management System (BMS), a hybrid solar inverter, and a load management control unit. A Long Short-Term Memory network (LSTM)-based forecasting strategy is implemented to predict the available PV and battery power. The learning data are extracted from an African country with a tropical climate, which is very suitable for PV power applications. Using LSTM as a prediction method significantly increases the efficiency of the forecasting. The main objective of the proposed strategy is to control the different loads according to the forecasted energy availability of the system and the forecasted battery state of charge (SOC). The proposed management algorithm and the system are tested using Matlab/Simulink software. A comparative study demonstrates that the reduction in the energy deficit of the system is approximately 53% compared to the system without load management. In addition to this, the reliability of the system is improved as the loss of power supply probability (LPSP) decreases from 5% to 3%.
Compressed Video Quality Index Based on Saliency-Aware Artifact Detection
Authors: Lin Liqun , Yang Jing , Wang Zheng , Zhou Liping , Chen Weiling , Xu Yiwen
Published: September 2021

Video coding technology makes the required storage and transmission bandwidth of video services decrease by reducing the bitrate of the video stream. However, the compressed video signals may involve perceivable information loss, especially when the video is overcompressed. In such cases, the viewers can observe visually annoying artifacts, namely, Perceivable Encoding Artifacts (PEAs), which degrade their perceived video quality. To monitor and measure these PEAs (including blurring, blocking, ringing and color bleeding), we propose an objective video quality metric named Saliency-Aware Artifact Measurement (SAAM) without any reference information. The SAAM metric first introduces video saliency detection to extract interested regions and further splits these regions into a finite number of image patches. For each image patch, the data-driven model is utilized to evaluate intensities of PEAs. Finally, these intensities are fused into an overall metric using Support Vector Regression (SVR). In experiment section, we compared the SAAM metric with other popular video quality metrics on four publicly available databases: LIVE, CSIQ, IVP and FERIT-RTRK. The results reveal the promising quality prediction performance of the SAAM metric, which is superior to most of the popular compressed video quality evaluation models.
Enhanced Human Activity Recognition Using Wearable Sensors via a Hybrid Feature Selection Method
Authors: Fan Changjun , Gao Fei
Published: September 2021

The study of human activity recognition (HAR) plays an important role in many areas such as healthcare, entertainment, sports, and smart homes. With the development of wearable electronics and wireless communication technologies, activity recognition using inertial sensors from ubiquitous smart mobile devices has drawn wide attention and become a research hotspot. Before recognition, the sensor signals are typically preprocessed and segmented, and then representative features are extracted and selected based on them. Considering the issues of limited resources of wearable devices and the curse of dimensionality, it is vital to generate the best feature combination which maximizes the performance and efficiency of the following mapping from feature subsets to activities. In this paper, we propose to integrate bee swarm optimization (BSO) with a deep Q-network to perform feature selection and present a hybrid feature selection methodology, BAROQUE, on basis of these two schemes. Following the wrapper approach, BAROQUE leverages the appealing properties from BSO and the multi-agent deep Q-network (DQN) to determine feature subsets and adopts a classifier to evaluate these solutions. In BAROQUE, the BSO is employed to strike a balance between exploitation and exploration for the search of feature space, while the DQN takes advantage of the merits of reinforcement learning to make the local search process more adaptive and more efficient. Extensive experiments were conducted on some benchmark datasets collected by smartphones or smartwatches, and the metrics were compared with those of BSO, DQN, and some other previously published methods. The results show that BAROQUE achieves an accuracy of 98.41% for the UCI-HAR dataset and takes less time to converge to a good solution than other methods, such as CFS, SFFS, and Relief-F, yielding quite promising results in terms of accuracy and efficiency.
A Fiber-Integrated CRDS Sensor for In-Situ Measurement of Dissolved Carbon Dioxide in Seawater
Authors: Hu Mai , Chen Bing , Yao Lu , Yang Chenguang , Chen Xiang , Kan Ruifeng
Published: September 2021

Research on carbon dioxide (CO2) geological and biogeochemical cycles in the ocean is important to support the geoscience study. Continuous in-situ measurement of dissolved CO2 is critically needed. However, the time and spatial resolution are being restricted due to the challenges of very high submarine pressure and quite low efficiency in water-gas separation, which, therefore, are emerging the main barriers to deep sea investigation. We develop a fiber-integrated sensor based on cavity ring-down spectroscopy for in-situ CO2 measurement. Furthermore, a fast concentration retrieval model using exponential fit is proposed at non-equilibrium condition. The in-situ dissolved CO2 measurement achieves 10 times faster than conventional methods, where an equilibrium condition is needed. As a proof of principle, near-coast in-situ CO2 measurement was implemented in Sanya City, Haina, China, obtaining an effective dissolved CO2 concentration of ~950 ppm. The experimental results prove the feasibly for fast dissolved gas measurement, which would benefit the ocean investigation with more detailed scientific data.
Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma
Authors: Yakno Marlina , Mohamad-Saleh Junita , Ibrahim Mohd Zamri
Published: September 2021

Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique’s impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.
Motor Synergies Measurement Reveals the Relevant Role of Variability in Reward-Based Learning
Authors: Caballero Carla , Moreno Francisco J. , Barbado David
Published: September 2021

Currently, it is not fully understood how motor variability is regulated to ease of motor learning processes during reward-based tasks. This study aimed to assess the potential relationship between different dimensions of motor variability (i.e., the motor variability structure and the motor synergies variability) and the learning rate in a reward-based task developed using a two-axis force sensor in a computer environment. Forty-four participants performed a pretest, a training period, a posttest, and three retests. They had to release a virtual ball to hit a target using a vertical handle attached to a dynamometer in a computer-simulated reward-based task. The participants’ throwing performance, learning ratio, force applied, variability structure (detrended fluctuation analysis, DFA), and motor synergy variability (good and bad variability ratio, GV/BV) were calculated. Participants with higher initial GV/BV displayed greater performance improvements than those with lower GV/BV. DFA did not show any relationship with the learning ratio. These results suggest that exploring a broader range of successful motor synergy combinations to achieve the task goal can facilitate further learning during reward-based tasks. The evolution of the motor variability synergies as an index of the individuals’ learning stages seems to be supported by our study.
Feasibility of Digital Image Correlation for Fatigue Cracks Detection under Dynamic Loading
Authors: Bardakov Vladimir V. , Marchenkov Artem Yu. , Poroykov Anton Yu. , Machikhin Alexander S. , Sharikova Milana O. , Meleshko Natalya V.
Published: September 2021

We address non-contact detection of defects in the railway rails under their dynamic loading and propose to combine digital image correlation (DIC) and finite element modeling (FEM). We show that accurate model of defect-free rail operating at the same loading conditions as the inspected one provides a reliable reference for experimental data. In this study, we tested the rail samples with artificial and fatigue defects under cyclic loading, calculated displacement and stress distributions at different locations of the cracks via DIC and validated the obtained results by FEM. The proposed DIC-FEM approach demonstrates high sensitivity to fatigue cracks and can be effectively used for remote control of rails as well as for non-destructive testing of various other objects operating under dynamic loads.
Usability, User Experience, and Acceptance Evaluation of CAPACITY: A Technological Ecosystem for Remote Follow-Up of Frailty
Authors: Pérez-Rodríguez Rodrigo , Villalba-Mora Elena , Valdés-Aragonés Myriam , Ferre Xavier , Moral Cristian , Mas-Romero Marta , Abizanda-Soler Pedro , Rodríguez-Mañas Leocadio
Published: September 2021

Frailty predisposes older persons to adverse events, and information and communication technologies can play a crucial role to prevent them. CAPACITY provides a means to remotely monitor variables with high predictive power for adverse events, enabling preventative personalized early interventions. This study aims at evaluating the usability, user experience, and acceptance of a novel mobile system to prevent disability. Usability was assessed using the system usability scale (SUS); user experience using the user experience questionnaire (UEQ); and acceptance with the technology acceptance model (TAM) and a customized quantitative questionnaire. Data were collected at baseline (recruitment), and after three and six months of use. Forty-six participants used CAPACITY for six months; nine dropped out, leaving a final sample of 37 subjects. SUS reached a maximum averaged value of 83.68 after six months of use; no statistically significant values have been found to demonstrate that usability improves with use, probably because of a ceiling effect. UEQ, obtained averages scores higher or very close to 2 in all categories. TAM reached a maximum of 51.54 points, showing an improvement trend. Results indicate the success of the participatory methodology, and support user centered design as a key methodology to design technologies for frail older persons. Involving potential end users and giving them voice during the design stage maximizes usability and acceptance.
An Internet of Things and Fuzzy Markup Language Based Approach to Prevent the Risk of Falling Object Accidents in the Execution Phase of Construction Projects
Authors: Martínez-Rojas María , Gacto María José , Vitiello Autilia , Acampora Giovanni , Soto-Hidalgo Jose Manuel
Published: September 2021

The Internet of Things (IoT) paradigm is establishing itself as a technology to improve data acquisition and information management in the construction field. It is consolidating as an emerging technology in all phases of the life cycle of projects and specifically in the execution phase of a construction project. One of the fundamental tasks in this phase is related to Health and Safety Management since the accident rate in this sector is very high compared to other phases or even sectors. For example, one of the most critical risks is falling objects due to the peculiarities of the construction process. Therefore, the integration of both technology and safety expert knowledge in this task is a key issue including ubiquitous computing, real-time decision capacity and expert knowledge management from risks with imprecise data. Starting from this vision, the goal of this paper is to introduce an IoT infrastructure integrated with JFML, an open-source library for Fuzzy Logic Systems according to the IEEE Std 1855-2016, to support imprecise experts’ decision making in facing the risk of falling objects. The system advises the worker of the risk level of accidents in real-time employing a smart wristband. The proposed IoT infrastructure has been tested in three different scenarios involving habitual working situations and characterized by different levels of falling objects risk. As assessed by an expert panel, the proposed system shows suitable results.
Are Traffic Announcements Really Effective? A Systematic Review of Evaluations of Crash-Prevention Communication Campaigns
Authors: Faus Mireia , Alonso Francisco , Fernández Cesáreo , Useche Sergio A.
Published: September 2021

Communication campaigns are commonly used in the traffic and road safety sector to raise public awareness of the importance of avoiding risky road user attitudes and behaviors. Surprisingly few of these communication campaigns evaluate their effectiveness in a formal and comprehensive manner. The core aim of the present systematic review is to identify the type of studies that evaluate the effectiveness of campaigns in this sector, in order to identify and contrast their main findings. This systematic review followed the PRISMA methodology, by means of which the relevant articles based on the search term were identified. A total of 613 indexed articles were filtered, and a final set of 27 articles directly addressing the issue was analyzed. Search strategies were developed and conducted in WOS, Scopus, NCBI, Google Scholar and APA databases. The selected articles point out that, although advertisements alone have a certain positive effect, their effectiveness is substantially increased if they are accompanied by other preventive measures such as legislation or road safety education. In any case, more evaluations of traffic campaigns are needed to identify which techniques are effective and which are not, and which should therefore be replaced by new methods of behavior modification in future communication campaigns.
A Study of Social Integration through Sports Program among Migrant Women in Korea
Authors: Lee Se-Joong , Yeo In-Sung , Ahn Byoung-Wook
Published: September 2021

This study aimed to examine sports programs at multicultural family support centers located throughout the country and present the possibility of social integration through the sports programs. The multicultural sports program showed that it affected the ability of migrant women in international marriages to socially integrate with other women like themselves, their husbands, and the natives, and also affected themselves. In order to clarify the purpose of the research, in-depth interviews were carried out. The collected material was transcribed, encoded, and classified. The results were analyzed from the perspective of sports’ physical, psychological, and social functions. This social integration was shown to be more effective than any other program at the multicultural family support center. Regarding their relationship with their husbands, the program provided opportunities for deepening their mutual understanding. The sports program was also utilized as a place of leisure for the women as well, and it was discovered that sports activities were being used as a means of resolving stress. The migrant women’s life radius and interpersonal relations were small due to their limited linguistic abilities. They provided opportunities to form confidence in their Korean life.
Humble and Kind: Cultural Humility as a Buffer of the Association between Social Dominance Orientation and Prejudice
Authors: Visintin Emilio Paolo , Rullo Marika
Published: September 2021

With the rise of prejudice and discrimination against ethnic and immigrant minorities, strategies to reduce prejudice and discrimination, and to counteract the impact of intolerant, anti-egalitarian ideologies, are needed. Here we focused on cultural humility, i.e., the ability to have a humble and other-oriented approach to others’ cultural backgrounds, resulting from self-examination and critical thinking about structural privileges and inequalities. In this research we proposed that cultural humility might attenuate the effects of intolerant, anti-egalitarian ideologies such as social dominance orientation (SDO) and right-wing authoritarianism (RWA) on negative intergroup attitudes and perceptions. In a correlational study conducted in Italy, we found that cultural humility moderated the associations between SDO and prejudice toward immigrants, as well as between SDO and perceptions of threat posed by immigrants. Specifically, the associations of SDO with prejudice and threat were lower among respondents with high cultural humility compared to respondents with low cultural humility. Conversely, cultural humility did not moderate the effects of RWA on prejudice and threat. Findings are discussed considering the motivations underlying prejudice of high-SDO and high-RWA individuals, and proposing cultural humility training to foster positive intergroup relations.
Male Sex Workers Selling Physical Sex during the COVID-19 Pandemic in Portugal: Motives, Safer Sex Practices, and Social Vulnerabilities
Authors: Pereira Henrique
Published: September 2021

The purpose of this research was to assess the motives, safer sex practices, and vulnerabilities of male sex workers who sold physical sex during the COVID-19 pandemic. This study used a mixed strategy, utilizing purposive sampling techniques to conduct 13 online surveys with male sex workers working in Portugal during the COVID-19 pandemic. Participants were aged between 23 and 47 years old and mostly provided their services to other men. Additionally, half of the participants were immigrants. Participants mentioned paying for essential expenses (rent, food, phone, etc.), having money for day-to-day expenses, wanting to, and enjoying it, as their main motives for engaging in sex work. Regarding sexual practices, 3 to 11 participants did not always or did not consistently use condoms during penetrative sex with their clients. Thematic analysis was used to identify the following repeated patterns of meaning regarding COVID-19-related vulnerabilities, encompassing a loss of clients and income, increased work availability, price reductions and negotiation difficulties, emotional functioning, health care access, safer sex negotiations, age, and immigration status. The findings serve as a basis for recommendations regarding social policies aimed at male sex workers who sell physical sex in Portugal.
Food Itineraries in the Context of Crisis in Catalonia (Spain): Intersections between Precarization, Food Insecurity and Gender
Authors: Gracia-Arnaiz Mabel , Garcia-Oliva Montserrat , Campanera Mireia
Published: September 2021

This work analyzes the relationship between the precarization of everyday life and the increase in food insecurity in Catalonia (Spain). Based on an ethnographic analysis of the food itineraries of a group of people in a situation of precarity, this article examines their lived experiences under the pressure of having to meet daily food needs. The results show that gender differences are significant in terms of the strategies adopted, particularly in the forms of acquisition and preparation, places of consumption and support networks. Given that women are largely responsible for feeding the household, they are the ones most often managing the attendant difficulties. In situations where access to food depends on diverse and irregular sources, they engage in practices that both protect the family group’s basic need to eat and sometimes compromise their own health, eating less than is usual and/or sufficient, skipping meals or even, on occasion, going hungry. The study concludes that providing food involves a crucial set of knowledge and skills for social reproduction that is not incorporated into existing emergency programs, with specific actions to avoid gender inequality likewise being omitted. The article proposes that both issues be discussed and taken into account in health and social policy. This study analyzes a subject that has scarcely been addressed in Spain. The challenge in investigating food insecurity from a gender approach is not only to make visible the crucial roles of women in food security and their contribution to it but also to show how the process of precarization manifests itself unequally across households.
Comparative Nicaraguan Migrant and Non-Migrant Experiences in the Early Twenty-First Century
Authors: Otterstrom Samuel M. , Otterstrom Sarah M. , Engar Amy Kimball , Udall Sarah , Robins Thomas A.
Published: September 2021

This paper examines the circumstances in which Nicaraguan migrants to Costa Rica found themselves and the situations of families in Nicaragua who had household members who had moved to Costa Rica from the late 1990s to 2012. Through surveys and interviews conducted in both Nicaragua and Costa Rica, this paper peers into the immigrant experience of Nicaraguans in Costa Rica and explores such issues as does time in Costa Rica improve the immigrant situation, how competitive were immigrants’ wages compared to those of their home country of Nicaragua, and what percentage of immigrants would send remittances home. The background literature written on the topics of central American migration, chain migration, push and pull factors, and remittances help contextualize the findings of this study. This paper also includes a consideration of how social or trust networks may relate to migrants’ tendency to send remittances. The analysis of the data collected yielded findings such as a small correlation between an immigrant’s salary and the amount of time the immigrant stayed at his or her job, a six times greater wage earned by Nicaraguan immigrants in Costa Rica than the average Nicaraguan wage, and a lower percentage of immigrants sending remittances back to Nicaragua than one might expect, from responses of both Nicaraguan migrants and non-migrants.
The Influence of the Negative Campaign on Facebook: The Role of Political Actors and Citizens in the Use of Criticism and Political Attack in the 2016 Spanish General Elections
Authors: Marcos-García Silvia , Alonso-Muñoz Laura , Casero-Ripollés Andreu
Published: September 2021

Social media has become an essential platform in the field of digital political communication. In the context of accommodating electoral campaigns to digital media and the absence of barriers to freedom of expression existing on these platforms, attacks on political rivals and negative campaigns are increasing on social media. This research analyzes the use of criticism on Facebook by political actors during the electoral campaign and citizens’ reactions to these messages. The sample (n = 601) contains the publications disseminated on Facebook by political parties and leaders during the electoral campaign of the general elections of 26 June 2016 in Spain. The results show that criticism is an emerging resource in the digital communication strategy of political actors, mainly used by the opposition parties and their candidates, who focus their attacks on the party and leader of the Government. Attacks are mainly focused on the professional side of their rivals, although they also give a central role to emotions. Citizens are attracted to these attacks and are prone to interact with posts that include this resource.
Hate Speech, Symbolic Violence, and Racial Discrimination. Antigypsyism: What Responses for the Next Decade?
Authors: Cortés Ismael
Published: September 2021

This paper aims to fulfill a double objective: on the one hand, to explain how hate speech works as a mechanism of racialization towards the Roma, resulting in a concrete form of symbolic violence. On the other hand, to analyze the most relevant institutional responses to fight against antigypsyism, looking at the new EU Roma Framework 2020–2030 with a special attention on the recent developments in Spain. The paper discusses the fact that a focus on symbolic violence and more concretely on hate speech would produce considerably differing approaches to Roma inclusion policies. The paper is divided into three sections: the first section will conceptually address the notions of “antigypsyism”, “racial discrimination”, “symbolic violence”, and “hate speech”. The second section will present and contextualize a series of illustrative cases of antigypsyist hate speech in the context of the COVID-19 pandemic in Spain. The third section will examine the most relevant legislative and policy initiatives adopted to fight against antigypsyism. The paper will wrap up with a discussion and some conclusions on the functioning of hate speech as a symbolic mechanism of racialization; and its capacity to articulate moral hierarchies and social divisions among the Roma and the rest of society.
A Pilot Study of miRNA Expression Profile as a Liquid Biopsy for Full-Marathon Participants
Authors: Kuji Tomoaki , Sugasawa Takehito , Fujita Shin-ichiro , Ono Seiko , Kawakami Yasushi , Takekoshi Kazuhiro
Published: September 2021

Exosomal microRNA (miRNA) in plasma and urine has attracted attention as a novel diagnostic tool for pathological conditions. However, the mechanisms of miRNA dynamics in the exercise physiology field are not well understood in terms of monitoring sports performance. This pilot study aimed to reveal the miRNA dynamics in urine and plasma of full-marathon participants. Plasma and urine samples were collected from 26 marathon participants before, immediately after, 2 h after, and one day after a full marathon. The samples were pooled, and exosomal miRNAs were extracted and analyzed using next-generation sequencing. We determined that the exosomal miRNA expression profile changed under time dependency in full marathon. New uncharacterized exosomal miRNAs such as hsa-miR-582-3p and hsa-miR-199a-3p could be potential biomarkers reflecting physical stress of full marathon in plasma and urine. In addition, some muscle miRNAs in plasma and urine have supported the utility for monitoring physical stress. Furthermore, some inflammation-related exosomal miRNAs were useful only in plasma. These results suggest that these exosomal miRNAs in plasma and/or urine are highly sensitive biomarkers for physical stress in full marathons. Thus, our findings may yield valuable insights into exercise physiology.
Does Urban Agglomeration Promote Urban Land Green Use Efficiency? Take the Yangtze River Economic Zone of China as an Example
Authors: Ge Kun , Zou Shan , Ke Shangan , Chen Danling
Published: September 2021

This paper theoretically constructs the logical framework of urban agglomeration affecting urban land green use efficiency (ULGUE) and employs the super efficiency SBM model with undesired outputs to measure ULGUE based on the research object from 107 prefecture-level cities and above in the Yangtze River Economic Zone. Then, this paper uses the difference-in-differences method to test the impact of urban agglomeration on the ULGUE. The results show that: (1) urban agglomeration has a positive regulatory effect on the ULGUE, and this research conclusion is robust; (2) the promotion effect of urban agglomeration on the ULGUE has regional differences, showing the basic pattern of ordinary prefecture-level cities > regional central cities > provincial capital cities and medium cities > big cities > super large and megacities; (3) small and medium-sized cities should be encouraged to further agglomerate while moderately controlling the excessive agglomeration of super-large cities and megacities. Moreover, it is suggested to improve the level of regional agglomeration from the aspects of flexible use of market mechanisms and policy tools, innovative technology applications to achieve the effective integration of urban agglomeration, and ULGUE promotion.
Chemical Recycling of PET in the Presence of the Bio-Based Polymers, PLA, PHB and PEF: A Review
Authors: Siddiqui Mohammad Nahid , Redhwi Halim Hamid , Al-Arfaj Abdulrahman A. , Achilias Dimitris S.
Published: September 2021

The great increase in the production and consumption of plastics has resulted in large amounts of plastic wastes, creating a serious problem in terms of their environmentally friendly disposal. The need for the production of more environmentally friendly polymers gave birth to the production of biodegradable, and more recently, biobased polymers, used in the production of biodegradable or biobased plastics. Although the percentage of currently produced bioplastics is rather small, almost 1% compared to petrochemical-based plastics, inevitably is going to significantly increase in the near future due to strict legislation recently posed by the European Union and other countries’ Governments. Thus, recycling strategies that have been developed could be disturbed and the economic balance of this sector could be destabilized. In the present review, the recycling of the polymer mainly used in food plastic packaging, i.e., poly(ethylene terephthalate), PET is examined together with its counterparts from the biobased polymers, i.e., poly(lactic acid), PLA (already replacing PET in several applications), poly(3-hydroxybutyrate), PHB and poly(ethylene furanoate), PEF. Methods for the chemical recycling of these materials together with the chemical products obtained are critically reviewed. Specifically, hydrolysis, alcoholysis and glycolysis. Hydrolysis (i.e., the reaction with water) under different environments (alkaline, acidic, neutral), experimental conditions and catalysts results directly in the production of the corresponding monomers, which however, should be separated in order to be re-used for the re-production of the respective polymer. Reaction conditions need to be optimized with a view to depolymerize only a specific polymer, while the others remain intact. Alcoholysis (i.e., the reaction with some alcohol, methanol or ethanol) results in methyl or ethyl esters or diesters that again could be used for the re-production of the specific polymer or as a source for producing other materials. Glycolysis (reaction with some glycol, such as ethylene, or diethylene glycol) is much studied for PET, whereas less studied for the biopolymers and seems to be a very promising technique. Oligomers having two terminal hydroxyl groups are produced that can be further utilized as starting materials for other value-added products, such as unsaturated polyester resins, methacrylated crosslinked resins, biodegradable polyurethanes, etc. These diols derived from both PET and the bio-based polymers can be used simultaneously without the need for an additional separation step, in the synthesis of final products incorporating biodegradable units in their chemical structure.
Investigating the Effect of High-Rise Buildings’ Mass Geometry on Energy Efficiency within the Climatic Variation of Egypt
Authors: El-Agami Mohanad , Hanafy Gehad , Osman Medhat
Published: September 2021

Energy conservation is recently the most important issue all over the world, including in Egypt. Recently, the built environment of Egypt has experienced a dramatic change in its buildings’ typology, with more interest in constructing high-rise buildings. This in turn creates high demand for energy, as high-rise buildings are considered to be one of the most energy-consuming types of buildings. Egypt has a wide variety in its climatic conditions, with seven different inhabited climatic regions, and a further one which is uninhabited. Therefore, integrating the energy efficiency of a building as a major design factor in the early design stages of such a type of buildings is important. This article is concerned with investigating the effect of high-rise buildings’ geometrical shape on the building’s energy consumption within the different climatic regions of Egypt. Four building shapes (square, circular, rectangular, and ellipse) are examined. The long axe of the models is oriented to the north (“the optimum orientation within all regions”), with a window-to-wall ratio (WWR) of 30%. The performance of these models is studied in seven cities representing the inhabited Egyptian climatic regions using simulation software, DesignBuilder, with the EnergyPlus simulation tool. Study findings revealed that adjusting the geometric form of the building significantly affects energy consumption and thermal comfort with climatic variation. The most compact shape, circular, was the most suitable geometrical shape in four regions out of seven. The ellipse shape was found to be the most suitable mass geometry within two other regions, while the square shape was found to be effective in only one region. The results of this research indicate that designers should not use the rectangular shape anywhere across Egypt.
Energy Network Embodied in Trade along the Belt and Road: Spatiotemporal Evolution and Influencing Factors
Authors: Fu Yue , Xue Long , Yan Yixin , Pan Yao , Wu Xiaofang , Shao Ying
Published: September 2021

As an important part of trade in the Belt and Road Initiative (BRI) area, significant research attention has been devoted to direct energy transfer, whereas studies on energy embodied in non-energy products have largely been neglected. To present an overview of energy trade for the BRI members, this study combined multi-regional input-output (MRIO) analysis with complex network analysis to model energy use flows within the BRI’s intermediate and final trade network during 2000–2015. Results showed that intermediate energy trade volume is about 7.29-fold larger than that of final trade. Russia and Mainland China were found to be the main net exporter and net importer in intermediate energy trade, respectively, but in final energy trade their roles are reversed. In intermediate energy trade, resource exploitation and heavy industry are the leading intermediate exporter and importer respectively, whereas household consumption is the largest importer (accounting for about three-fifths of the total) in final energy trade. Based on the complex network analysis, the BRI countries were found to trade widely in the final network while cooperating deeply in the intermediate network, with obvious small-world features. Mainland China and Russia were identified as key economies in both intermediate and final trade networks. In addition, quadratic assignment procedure (QAP) analysis was adopted to explore the determinants of the BRI energy trade from 2000 to 2015. It was found that geographic distance, land adjacency, and culture and language have a consistently significant impact on intermediate trade. Closer geographic distance, being adjacent to land, a higher level of economic development, and a larger size of population can promote final trade. This study aimed to supplement existing studies on direct energy trade and provides implications for understanding the sustainable energy development in the BRI area.