bluuebunny/crossref_metadata_2025 huggingface dataset:
A Potential-Based Quantization Procedure of the Damped Oscillator
Authors: Márkus Ferenc , Gambár Katalin
Published: September 2022

Today, two of the most prosperous fields of physics are quantum computing and spintronics. In both, the loss of information and dissipation play a crucial role. In the present work, we formulate the quantization of the dissipative oscillator, which aids the understanding of the abovementioned issues, and creates a theoretical frame to overcome these issues in the future. Based on the Lagrangian framework of the damped spring system, the canonically conjugated pairs and the Hamiltonian of the system are obtained; then, the quantization procedure can be started and consistently applied. As a result, the damping quantum wave equation of the dissipative oscillator is deduced, and an exact damping wave solution of this equation is obtained. Consequently, we arrive at an irreversible quantum theory by which the quantum losses can be described.
Physical Differences between Man-Made and Cosmic Microwave Electromagnetic Radiation and Their Exposure Limits, and Radiofrequencies as Generators of Biotoxic Free Radicals
Authors: Georgiou Christos D. , Kalaitzopoulou Electra , Skipitari Marianna , Papadea Polyxeni , Varemmenou Athina , Gavriil Vassilios , Sarantopoulou Evangelia , Kollia Zoe , Cefalas Alkiviadis-Constantinos
Published: September 2022

The critical arguments for radiofrequency radiation exposure limits are currently based on the principle that radio frequencies (RF) and electromagnetic fields (EMFs) are non-ionising, and their exposure limits are even 100-fold lower than those emitted from the Sun in the whole RF-EMF spectrum. Nonetheless, this argument has been challenged by numerous experimental and theoretical studies on the diverse biological effects of RF-EMF at much lower power density (W/m2) levels than today’s exposing limits. On the other hand, less attention has been given to counterarguments based on the differences in the physics concepts underlying man-made versus natural electromagnetic radiation (EMR) and on the fact that man’s biology has been adapted to the natural EMR levels reaching Earth’s surface at single EMF wavelengths, which are the natural limits of man’s exposure to EMFs. The article highlights the main points of interaction of natural and man-made radiation with biomatter and reveals the physical theoretical background that explains the effects of man-made microwave radiation on biological matter. Moreover, the article extends its analysis on experimental quantum effects, establishing the “ionising-like” effects of man-made microwave radiation on biological matter.
Alternate Narratives for the Tamil Yoginis: Reconsidering the ‘Kanchi Yoginis’ Past, Present, and Future
Authors: Stein Emma Natalya , Kasdorf Katherine E.
Published: September 2022

This essay revisits a group of stone goddesses that once shared a temple in southern India, together with the god Shiva and perhaps other deities. Considering the different paths sacred sculptures in India take after becoming separated from their original temple contexts suggests that there were multiple possible histories for these works. The authors reveal a newly discovered goddess from the group and reconsider the significance of the works, including the original temple and the deities it enshrined. Finally, they propose the possibility of bringing these sculptures back together in the context of an exhibition.
Hongzan’s Maitreya Belief in the Context of Late Imperial Chinese Monastic Revival and Chan Decline
Authors: Wang Xing
Published: September 2022

This paper shows that the early Qing Chinese Buddhist monk Zaisan Hongzan’s belief in Maitreya and Tuṣita Heaven pure lands, as reflected in his collection of miracle tales and biographies, should be understood in a broader socio-religious context of Chan decline and monastic revival in late imperial China. It is important to notice that instead of advocating for the combination of Chan and Amitābha’s Pure Land of Bliss practice, Hongzan proposed the most severe criticism of the Chinese Chan tradition since the Song dynasty. Through both his personal doctrinal writings and the narrative strategies applied in his Tuṣita Heaven miracle tales, Hongzan vividly displayed his concerns about literary Chan practice and argued for the pivotal and urgent need for Vinaya among monastic communities. Hongzan’s personal anti-Chan sentiment and his intention to reestablish the study and practice of Buddhist Vinaya disciplines in a time of alleged “crisis” of Chinese Buddhism strongly influenced how he composed and transcribed eminent monks’ biographies related to the cult of Maitreya and Tuṣita Heaven. A “hagiographic” reading of Hongzan’s miracle tale collections is necessary to understand his religious discourse in this special historical stage in China.
Aspects of Medieval Japanese Religion
Authors: Faure Bernard R. , Castiglioni Andrea
Published: September 2022

The focus of this Special Issue is on medieval Japanese religion. Although Kamakura “new” Buddhist schools are usually taken as unquestioned landmarks of the medieval religious landscape, it is necessary to add complexity to this static picture in order to grasp the dynamic and hybrid character of the religious practices and theories that were produced during this historical period. This Special Issue will shed light on the diversity of medieval Japanese religion by adopting a wide range of analytical approaches, encompassing various fields of knowledge such as history, philosophy, materiality, literature, medical studies, and body theories. Its purpose is to expand the interpretative boundaries of medieval Japanese religion beyond Buddhism by emphasizing the importance of mountain asceticism (Shugendō), Yin and Yang (Onmyōdō) rituals, medical and soteriological practices, combinatory paradigms between local gods and Buddhist deities (medieval Shintō), hagiographies, religious cartography, conflations between performative arts and medieval Shintō mythologies, and material culture. This issue will foster scholarly comprehension of medieval Japanese religion as a growing network of heterogeneous religious traditions in permanent dialogue and reciprocal transformation. While there is a moderate amount of works that address some of the aspects described above, there is yet no publication attempting to embrace all these interrelated elements within a single volume. The present issue will attempt to make up for this lack. At the same time, it will provide a crucial contribution to the broad field of premodern Japanese religions, demonstrating the inadequacy of a rigid interpretative approach based on sectarian divisions and doctrinal separation. Our project underlines the hermeneutical importance of developing a polyphonic vision of the multifarious reality that lies at the core of medieval Japanese religion.
When Histological Tumor Type Diagnosed on Core Biopsy Changes Its Face after Surgery: Report of a Deceptive Case of Breast Carcinoma
Authors: d’Amati Antonio , Mariano Marta , Addante Francesca , Giliberti Giovanna , Tomasicchio Giovanni , Mastropasqua Mauro Giuseppe
Published: September 2022

The presence of stromal osteoclast-like giant cells is a distinctive feature of some rare breast tumors, accounting for less than 1% of all breast cancer cases. Although the presence of stromal osteoclast-like giant cells may be encountered in different breast tumors, some authors still describe them as a specific tumor type. Usually, a histological diagnosis of breast carcinoma is made by a pathologist through a biopsy, which is then confirmed through a surgical specimen: it is rare for the two to differ, particularly when there are pathognomonic morphological markers, such as osteoclast-like giant cells. Herein, we report a case of a 45-year-old pre-menopausal woman, who was found to have a single solid mass in her right breast on screening mammogram. She underwent a core biopsy, which showed a malignant epithelial lesion arranged in tubules, glands, and papillae, intermingled with numerous stromal osteoclast-like giant cells. Therefore, a diagnosis of breast cancer with osteoclast-like giant cells was rendered. Curiously, these cells were no longer detectable in the surgical specimen.
Tunable Vibration Absorber Design for a High-Precision Cartesian Robot
Authors: D’Imperio Simone , Berruti Teresa Maria , Gastaldi Chiara , Soccio Pietro
Published: September 2022

In metal sheet processing for automotive application, it is crucial to guarantee high robot dynamics for reduced cycle times and adequate components accuracy to be competitive in the market. Since the two aspects are closely and inversely related, the problem becomes challenging. After the first cutting tests, the Cartesian Robot prototype displayed insufficient dimensional accuracy when undergoing high accelerations. The solution hereby proposed is the design of a Tuned Mass Damper (TMD), working in shear mode, to reduce the robot vibration amplitude. To this end, an initial assessment of the robot frequency response and natural frequencies was performed both by using a Finite Element (FE) model of the machine and experimentally. Further, frequency response analyses were carried out to evaluate the TMD effectiveness and to highlight possible criticalities from the manufacturing point of view. On a numerical level, the proposed design can damp the machine resonant frequencies, also showing a certain grade of tunability before operation and in-plane orientation insensitiveness thanks to the use of cylindrically shaped springs.
Heterogeneity of Increases in Net Primary Production under Intensified Human Activity and Climate Variability on the Loess Plateau of China
Authors: Ni Xiangnan , Guo Wei , Li Xiaoting , Li Shuheng
Published: September 2022

Regrowth of forests is expected to be an important driver in the large uptake of anthropogenic CO2 emissions by the terrestrial biosphere. Yet estimates of carbon sink capacity in mid-high latitude regrowth forests still remain unclear. The Loess Plateau (LP), a key region of the Grain to Green Program (GTGP), leads in the greening of China, while China leads in the greening of the world. For the sake of global ecological sustainability and accurate global carbon sink evaluation, the detection and attribution of vegetation growth on the LP requires further research after 20 years of ecological restoration. In this study, significant continuous rises (increases of 7.45 gC·m−2·a−2, R2 = 0.9328, p < 0.01) in net primary production (NPP) have occurred in the past 20 years. Rapid growth of forest NPP and expansion of forested areas in the southeastern regions has led to vegetation restoration on the LP. Human activities contributed 64.2% to the NPP increases, while climate variations contributed 35.8%. NPP in forests and croplands was dominated by human activities, while grassland NPP was mainly influenced by climate variations on the LP. Meanwhile, a strong El Niño event exacerbated the obstruction of large-scale ecological restoration. These conclusions can provide theoretical support for carbon-cycle assessment and the evaluation of sustainable development.
Surface Subsidence Monitoring Induced by Underground Coal Mining by Combining DInSAR and UAV Photogrammetry
Authors: Zhang Yafei , Lian Xugang , Ge Linlin , Liu Xiaoyu , Du Zheyuan , Yang Wenfu , Wu Yanru , Hu Haifeng , Cai Yinfei
Published: September 2022

Surface subsidence caused by coal mining has become an important factor that affects and restricts the sustainable development of mining districts. It is necessary to use appropriate methods for effective subsidence monitoring. It is hard to monitor large gradient ground deformations with a high accuracy by using differential interferometric synthetic aperture radar (DInSAR) technology. Unmanned aerial vehicle (UAV) photogrammetry is limited in that it monitors the basin edge by subtracting two DEMs (digital elevation models). Therefore, in this paper we propose a combination of DInSAR and UAV photogrammetry to complement the two data advantages and to achieve a high-precision monitoring of mining subsidence areas. The subsidence of coal panel 81,403 in the Yangquan coal mine was obtained using DInSAR and UAV photogrammetry technologies. The appropriate fusion points were selected for the two datasets and the agreement between the fusion data and the leveling data was verified. The results indicated that the combination of DInSAR and UAV technology could monitor the settlement more accurately than the single use of DInSAR or UAV technology.
Adaptive Packet Coding for Reliable Underwater Acoustic Communications
Authors: Jing Lianyou , Tang Yongqi , He Chengbing , Yin Hongxi
Published: September 2022

This work investigates adaptive random linear packet coding (RLPC) for reliable underwater acoustic (UWA) communications. Our goal is to minimize the total transmission time of data blocks by adjusting the packet coding rate. We first consider the application of RLPC with the conventional automatic repeat request (ARQ) scheme. We dynamically adjust the coding rate to fit the time variations of UWA channels by choosing the optimal number of packets in each transmission. The optimal number of packets in each transmission is obtained based on a dynamic programming (DP) algorithm according to the feedback messages, which contain the number of successfully transmitted packets in the last transmission and the channel state information. Furthermore, considering the long propagation delay of UWA communications, we propose a modified juggling-like ARQ (J-ARQ) for the RLPC scheme, for which the duration of each transmission can be adjusted based on the characteristics of RLPC. A two-step DP algorithm is proposed to find out the optimal solutions for this case. Simulation results show that the proposed schemes can improve the throughput efficiency and reduce the outage probability.
Impacts of FY-4A AGRI Radiance Data Assimilation on the Forecast of the Super Typhoon “In-Fa” (2021)
Authors: Zhang Xuewei , Xu Dongmei , Liu Ruixia , Shen Feifei
Published: September 2022

This study assessed the impact of assimilating the Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) observations on the Super Typhoon “In-Fa” event based on the Weather Research and Forecasting Data Assimilation (WRFDA) system of the three-dimensional variational data assimilation (3DVAR) method. It was found that the two water vapor channels 9–10 from the full-disk AGRI datasets yield relatively stable results in terms of the track forecast of In-Fa. A new cloud-detection method using a Particle Filter (PF) was firstly employed to remove the cloud-affected observations by identifying the channel’s weighting function. Compared to the other cloud-detection schemes based on the AGRI “Cloud_Binary_Mask” (CLM) products, the PF method is conducive to reducing the track error of typhoon prediction after improving the utilization of observations under clear-sky conditions. Furthermore, the proposed cycling assimilation scheme has a potential positive effect on the intensity forecast of In-Fa. It seems that assimilating the FY-4A AGRI radiance data improves the predictability of Typhoon In-Fa by adjusting the atmospheric environment.
New Era for Geo-Parsing to Obtain Actual Locations: A Novel Toponym Correction Method Based on Remote Sensing Images
Authors: Wang Shu , Yan Xinrong , Zhu Yunqiang , Song Jia , Sun Kai , Li Weirong , Hu Lei , Qi Yanmin , Xu Huiyao
Published: September 2022

Geo-parsing, one of the key components of geographical information retrieval, is a process to recognize and geo-locate toponyms mentioned in texts. Such a process can obtain locations contained in toponyms successfully with consistent updating of neural network models and multiple contextual features. The significant offset distance between the geo-parsed locations and the actual occurrence locations still remains. This is because the geo-parsed locations sourced from toponyms in texts always point to the centers of cities, counties, or towns, and cannot directly represent the actual occurrence locations such as factories, farms, and activity areas. Consequently, The significant offset distances between the geo-parsed locations and the actual occurrence locations limit text mining applications in micro-scale geographic discoveries. This research aims at decreasing offset distances of geo-parsed locations by proposing a novel Toponym Correction Method based on satellite Remote Sensing Images (TC-RSI). The TC-RSI method uses satellite remote sensing images to provide extra detailed spatial information that can be associated with the sentence toponym by corresponding attributes. The TC-RSI method was validated in a case study of the forest ecological pattern dataset of An’hui province from visual, statistical, and robustness assessments. The correction results show that the TC-RSI method dramatically decreases the offset distances from about 50 km to about 1 km and promotes geographical discoveries on smaller scales. A series of analyses indicated that the TC-RSI is a valid, effective, and promising method to improve the accuracy of geo-parsed locations, which allows text mining to find more accurate geographical discoveries with lower offset distances. Moreover, toponym correction promotes the use of more diverse spatial data sources, such as Lidar, domain gazetteers, Wikimedia, and streetscapes, which are expected to usher in a new era of geo-parsing with toponym corrections.
A Framework Integrating DeeplabV3+, Transfer Learning, Active Learning, and Incremental Learning for Mapping Building Footprints
Authors: Li Zhichao , Dong Jinwei
Published: September 2022

Convolutional neural network (CNN)-based remote sensing (RS) image segmentation has become a widely used method for building footprint mapping. Recently, DeeplabV3+, an advanced CNN architecture, has shown satisfactory performance for building extraction in different urban landscapes. However, it faces challenges due to the large amount of labeled data required for model training and the extremely high costs associated with the annotation of unlabelled data. These challenges encouraged us to design a framework for building footprint mapping with fewer labeled data. In this context, the published studies on RS image segmentation are reviewed first, with a particular emphasis on the use of active learning (AL), incremental learning (IL), transfer learning (TL), and their integration for reducing the cost of data annotation. Based on the literature review, we defined three candidate frameworks by integrating AL strategies (i.e., margin sampling, entropy, and vote entropy), IL, TL, and DeeplabV3+. They examine the efficacy of AL, the efficacy of IL in accelerating AL performance, and the efficacy of both IL and TL in accelerating AL performance, respectively. Additionally, these frameworks enable the iterative selection of image tiles to be annotated, training and evaluation of DeeplabV3+, and quantification of the landscape features of selected image tiles. Then, all candidate frameworks were examined using WHU aerial building dataset as it has sufficient (i.e., 8188) labeled image tiles with representative buildings (i.e., various densities, areas, roof colors, and shapes of the building). The results support our theoretical analysis: (1) all three AL strategies reduced the number of image tiles by selecting the most informative image tiles, and no significant differences were observed in their performance; (2) image tiles with more buildings and larger building area were proven to be informative for the three AL strategies, which were prioritized during the data selection process; (3) IL can expedite model training by accumulating knowledge from chosen labeled tiles; (4) TL provides a better initial learner by incorporating knowledge from a pre-trained model; (5) DeeplabV3+ incorporated with IL, TL, and AL has the best performance in reducing the cost of data annotation. It achieved good performance (i.e., mIoU of 0.90) using only 10–15% of the sample dataset; DeeplabV3+ needs 50% of the sample dataset to realize the equivalent performance. The proposed frameworks concerning DeeplabV3+ and the results imply that integrating TL, AL, and IL in human-in-the-loop building extraction could be considered in real-world applications, especially for building footprint mapping.
Topographic Correction of the SELENE MI Images with the LOLA DEM around Shackleton Crater
Authors: Ke Xiaoxue , Wang Chao , Du Jinhuan , Yuan Yuting , Xu Xiong , Feng Yongjiu , Xie Huan , Liu Shijie , Tong Xiaohua
Published: September 2022

Due to the complicated terrain and extreme illumination condition in the lunar south polar region, topography has an impact on the reflectance of the area. This may result in the misinterpretation of the properties of the lunar surface. Therefore, an image obtained across Shackleton Crater by the Multi-band Imager (MI) onboard the first Japanese lunar orbiter SELENE (SELenological and ENgineering Explorer) was utilized to evaluate the topographic effect on the reflectance of the polar region. Three methods—i.e., b correction, C correction, and Minnaert correction—were applied to the MI image to reduce the topographic effect. It was found that the reflectance result of C correction suffers from overcorrection. The topographic effect is enlarged, rather than suppressed, in the reflectance derived with Minnaert correction. Comparatively, b correction is the more appropriate method for the topographic correction of the MI image across the study area. The reflectance of the sunlit slope of the crater wall in the study area decreased by ~60%. The reflectance of the area outside of the crater, with a gentler slope compared to the crater wall, decreased by ~20%. Meanwhile, according to the correlation of the cosine of the local solar incidence angle and the corrected reflectance, the topographic effect was seemingly not completely eliminated in the MI image. However, by analyzing the spectral absorption features of the 1250 nm band, we can attribute this “residual” effect to the different compositions inside and outside of Shackleton Crater, most likely caused by a high concentration of plagioclase. Topographic correction of the MI images over NASA candidate landing regions was also conducted. The results suggest that the topographic effect can contribute significantly to the reflectance of the sunlit slopes, and should not be neglected in the analysis of the reflectance images. This study highlights the topographic impact on the reflectance of the lunar south pole’s surface. In addition, our results also suggest that the compositional differences under various terrains should be considered in the evaluation of the topographic correction of specific regions, such as Shackleton Crater’s inner walls.
Optimizing the Land Use and Land Cover Pattern to Increase Its Contribution to Carbon Neutrality
Authors: Wang Kai , Li Xiaobing , Lyu Xin , Dang Dongliang , Dou Huashun , Li Mengyuan , Liu Siyu , Cao Wanyu
Published: September 2022

Land use and land cover (LULC) contribute to both carbon storage and carbon emissions. Therefore, regulating the LULC is an important means of achieving carbon neutrality under global environmental change. Here, the West Liaohe River Basin, a semiarid watershed, was taken as a case study. Based on the assessment of the carbon storage and emissions induced by LULC from 2000–2020, we set up three different coupled shared socioeconomic pathway (SSP) and representative concentration pathway (RCP) scenarios (SSP119, SSP245, and SSP585), from 2030–2060, to optimize the LULC. Then, the LULC patterns under each scenario were simulated using the patch-generating land use simulation (PLUS) model, and the corresponding changes in carbon storage and emissions were compared and analyzed. It was found that, since 2000, with the expansion of forest, cropland, and construction land, as well as the degradation of grassland, the carbon storage and emissions induced by LULC have significantly increased, but the increase in storage was lower than that of emissions. The scenario simulations revealed that, when we optimize the LULC, mainly including the protection and expansion of ecological land such as forest and grassland in the western and southern edges of the basin, as well as the control and management of cropland land and construction land in the northeast and central parts of the basin, there will be a significant increase in the carbon storage and a significant reduction in carbon emissions from 2030–2060. This indicates that zone-based management measures with rational LULC regulation can contribute to the achievement of carbon neutrality in the study area. Supported by the results of this study, a direct decision-making basis for land use policy regulation to promote regional sustainable development can be undertaken in the basin. This study also provides a reference for low-carbon development in other regions.
Rotating Single-Antenna Spoofing Signal Detection Method Based on IPNN
Authors: Chang Haowei , Pang Chunlei , Zhang Liang , Guo Zehui
Published: September 2022

The traditional carrier-phase differential detection technology mainly relies on the spatial processing method, which uses antenna arrays or moving antennas to detect spoofing signals, but it cannot be applied to static single-antenna receivers. Aiming at this problem, this paper proposes a rotating single-antenna spoofing signal detection method based on the improved probabilistic neural network (IPNN). When the receiver antenna rotates at a constant speed, the carrier-phase double difference of the real signal will change with the incident angle of the satellite. According to this feature, the classification and detection of spoofing signals can be realized. Firstly, the rotating single-antenna receiver collects carrier-phase values and performs double-difference processing. Then, we construct an IPNN model, whose smoothing factor can be adaptively adjusted according to the type of failure mode. Finally, we use the IPNN model to realize the classification and processing of the carrier-phase double-difference observations and obtain the deception detection results. In addition, in order to reflect that the method has a certain practical value, we simulate the spoofing scenario of satellite signals and effectively identify abnormal satellite signals according to the detection results of the inter-satellite differential combination. Actual experiments indicate that the detection accuracy of the proposed method for spoofing signals reaches 98.84%, which is significantly better than the classical probabilistic neural network (PNN) and back-propagation neural network (BPNN), and the method can be implemented in fixed base station receivers for the real-time detection of forwarding spoofing.
Genetic Approach for Joint Transmission Grouping in Next-Generation Cellular Networks
Authors: Kuo Yu-Po , Yu Ya-Ju , Hong Tzung-Pei , Lai Wei-Kuang
Published: September 2022

Coordinated multipoint joint transmission (JT) is one of the critical downlink transmission technologies to improve network throughput. However, multiple cells in a JT group should have the same user data to transmit simultaneously, resulting in a considerable backhaul burden. Even when cells are already equipped with caches in fifth-generation networks, JT groups, without effectively utilizing the caching data, still cause unnecessary backhaul data traffic. In this article, we investigate the JT grouping problem with the consideration of caches at cells. Then, we propose a genetic approach to solve the above problem with the objective of minimizing the amount of backhaul data traffic subject to the data-rate requirement of each user. The simulation results show that our proposed generic algorithm can significantly decrease the backhaul bandwidth consumption compared to the two baselines.
EEG-Based Person Identification during Escalating Cognitive Load
Authors: Kralikova Ivana , Babusiak Branko , Smondrk Maros
Published: September 2022

With the development of human society, there is an increasing importance for reliable person identification and authentication to protect a person’s material and intellectual property. Person identification based on brain signals has captured substantial attention in recent years. These signals are characterized by original patterns for a specific person and are capable of providing security and privacy of an individual in biometric identification. This study presents a biometric identification method based on a novel paradigm with accrual cognitive brain load from relaxing with eyes closed to the end of a serious game, which includes three levels with increasing difficulty. The used database contains EEG data from 21 different subjects. Specific patterns of EEG signals are recognized in the time domain and classified using a 1D Convolutional Neural Network proposed in the MATLAB environment. The ability of person identification based on individual tasks corresponding to a given degree of load and their fusion are examined by 5-fold cross-validation. Final accuracies of more than 99% and 98% were achieved for individual tasks and task fusion, respectively. The reduction of EEG channels is also investigated. The results imply that this approach is suitable to real applications.
A Meta-Analysis on Remote HRI and In-Person HRI: What Is a Socially Assistive Robot to Do?
Authors: Liang Nan , Nejat Goldie
Published: September 2022

Recently, due to the COVID-19 pandemic and the related social distancing measures, in-person activities have been significantly reduced to limit the spread of the virus, especially in healthcare settings. This has led to loneliness and social isolation for our most vulnerable populations. Socially assistive robots can play a crucial role in minimizing these negative affects. Namely, socially assistive robots can provide assistance with activities of daily living, and through cognitive and physical stimulation. The ongoing pandemic has also accelerated the exploration of remote presence ranging from workplaces to home and healthcare environments. Human–robot interaction (HRI) researchers have also explored the use of remote HRI to provide cognitive assistance in healthcare settings. Existing in-person and remote comparison studies have investigated the feasibility of these types of HRI on individual scenarios and tasks. However, no consensus on the specific differences between in-person HRI and remote HRI has been determined. Furthermore, to date, the exact outcomes for in-person HRI versus remote HRI both with a physical socially assistive robot have not been extensively compared and their influence on physical embodiment in remote conditions has not been addressed. In this paper, we investigate and compare in-person HRI versus remote HRI for robots that assist people with activities of daily living and cognitive interventions. We present the first comprehensive investigation and meta-analysis of these two types of robotic presence to determine how they influence HRI outcomes and impact user tasks. In particular, we address research questions regarding experience, perceptions and attitudes, and the efficacy of both humanoid and non-humanoid socially assistive robots with different populations and interaction modes. The use of remote HRI to provide assistance with daily activities and interventions is a promising emerging field for healthcare applications.
An Efficient and Uncertainty-Aware Decision Support System for Disaster Response Using Aerial Imagery
Authors: Bin Junchi , Zhang Ran , Wang Rui , Cao Yue , Zheng Yufeng , Blasch Erik , Liu Zheng
Published: September 2022

Efficient and robust search and rescue actions are always required when natural or technical disasters occur. Empowered by remote sensing techniques, building damage assessment can be achieved by fusing aerial images of pre- and post-disaster environments through computational models. Existing methods pay over-attention to assessment accuracy without considering model efficiency and uncertainty quantification in such a life-critical application. Thus, this article proposes an efficient and uncertain-aware decision support system (EUDSS) that evolves the recent computational models into an efficient decision support system, realizing the uncertainty during building damage assessment (BDA). Specifically, a new efficient and uncertain-aware BDA integrates the recent advances in computational models such as Fourier attention and Monte Carlo Dropout for uncertainty quantification efficiently. Meanwhile, a robust operation (RO) procedure is designed to invite experts for manual reviews if the uncertainty is high due to external factors such as cloud clutter and poor illumination. This procedure can prevent rescue teams from missing damaged houses during operations. The effectiveness of the proposed system is demonstrated on a public dataset from both quantitative and qualitative perspectives. The solution won the first place award in International Overhead Imagery Hackathon.
Measurement-Error Analysis of Fiber Bragg Grating Flexible Sensor for Displacement-Field Monitoring of Geotechnical Engineering
Authors: Tian Changbin , Ma Xiangxue , Peng Bo , Ma Xin , Li Zhiyu
Published: September 2022

Monitoring geotechnical structures and providing real-time early warning is a key measure to mitigate the impacts of disasters (slope slip, subsidence, dam deformation, bridge settlement, etc.). The fiber Bragg grating (FBG) flexible sensor, developed by the combination of flexible material and an FBG sensor, is widely used in geotechnical engineering health monitoring due to its excellent performance. The flexible sensor can perform regional and quasi-distributed measurements of the displacement field of the measured structure, and accurately reflect the operating state of the engineering structure. However, in practical engineering applications, factors such as the strain-transfer rate between the flexible substrate and sensing points, the displacement reconstruction algorithm, and the arrangement interval of the sensing points can cause measurement error, which, in turn, leads to a decrease in the displacement-measurement accuracy. In this paper, the following analysis is performed by means of theoretical derivation and model establishment. The influence of the length, width, and thickness of the cemented layer, the shear modulus of the flexible substrate, and the radius of the groove on the strain-transfer rate were analyzed, and the referential parameters were determined. The displacement reconstruction algorithm is essentially a recursive algorithm, which inevitably introduces cumulative error; the relationship between the layout interval of the sensing points and the measurement error is discussed. Considering the fabrication cost of the sensor and the allowable range of error, a sensing-point-layout interval of 100 mm was chosen. The feasibility and effectiveness of the simulation theory were verified by carrying out deformation-sensing experiments on the developed FBG flexible sensor. The research results can theoretically guide the packaging and fabrication of the FBG flexible sensor, thereby improving the measurement accuracy of the flexible sensor for the measured structure.
LoRaWAN Performance Analysis for a Water Monitoring and Leakage Detection System in a Housing Complex
Authors: Alghamdi Atheer M. , Khairullah Enas F. , Al mojamed Mohammad M.
Published: September 2022

The automation of water leakage detection and monitoring systems has recently been made possible by the Internet of Things (IoT). However, the high cost is an obstacle when applying a network over a large area. The Low-Power Wide-Area Network (LPWAN) was created specifically to address long-range IoT applications. The Long-Range Wide-Area Network (LoRaWAN) is one of the most common LPWANs. In this study, a method for monitoring and detecting water leakage in a housing complex was tested using LoRaWAN. Water leakage was detected using a low-pressure system model comprising a water meter, presser sensor, and smart valve within a LoRa node. This study investigates the use of LoRaWAN for water monitoring and leakage detection by implementing a comprehensive case study to identify LoRaWAN’s feasibility, reliability, and scalability for water monitoring and leakage detection in simulated scenarios. The housing complex varied in size and number of nodes. The LoRaWAN was evaluated by the FloRa simulator package through the Objective Modular Network Testbed (OMNeT++) platform. The results indicated that it was an efficient means of water monitoring and leakage detection in housing complexes.
SPR Sensor Based on a Tapered Optical Fiber with a Low Refractive Index Liquid Crystal Cladding and Bimetallic Ag–Au Layers
Authors: Korec Joanna , Stasiewicz Karol A. , Jaroszewicz Leszek R.
Published: September 2022

This paper presents a study of the influence of bimetallic layer covers of a tapered optical fiber surrounded by a low refractive index liquid crystal on the properties of light propagation in the taper structure. This research follows previous works on the effect of monometallic thin films (Au and Ag). In this case, the total thicknesses of the bimetallic layers were h = 10 nm, and the participation of gold and silver was equal. The films were deposited on one side of the tapered waist area. The liquid crystal cells were controlled with a voltage U from 0 to 200 V, with and without amplitude modulation at a frequency of fmod = 5 Hz. For the purposes of this research, spectral characteristics were obtained for a wavelength λ ranging from 550 to 1200 nm. Measurements were carried out at room temperature for three types of rubbed layers orientation—orthogonal, parallel, and twist in relation to the fiber axis. Obtained resonant peaks were compared with the previous results regarding the resonant wavelength, peak width, SNR, and maximum absorption. In the presented paper, the novelty is mainly focused on the materials used and their time stability, as well as corresponding changes in the technological parameters used.
Parameter-Adaptive TVF-EMD Feature Extraction Method Based on Improved GOA
Authors: Zhou Chengjiang , Xiong Zenghui , Bai Haicheng , Xing Ling , Jia Yunhua , Yuan Xuyi
Published: September 2022

In order to separate the sub-signals and extract the feature frequency in the signal accurately, we proposed a parameter-adaptive time-varying filtering empirical mode decomposition (TVF-EMD) feature extraction method based on the improved grasshopper optimization algorithm (IGOA). The method not only improved the local optimal problem of GOA, but could also determine the bandwidth threshold and B-spline order of TVF-EMD adaptively. Firstly, a nonlinear decreasing strategy was introduced in this paper to adjust the decreasing coefficient of GOA dynamically. Then, energy entropy mutual information (EEMI) was introduced to comprehensively consider the energy distribution of the modes and the dependence between the modes and the original signal, and the EEMI was used as the objective function. In addition, TVF-EMD was optimized by IGOA and the optimal parameters matching the input signal were obtained. Finally, the feature frequency of the signal was extracted by analyzing the sensitive mode with larger kurtosis. The optimization experiments of 23 sets of benchmark functions showed that IGOA not only enhanced the balance between exploration and development, but also improved the global and local search ability and stability of the algorithm. The analysis of the simulation signal and bearing signal shows that the parameter-adaptive TVF-EMD method can separate the modes with specific physical meanings accurately. Compared with ensemble empirical mode decomposition (EEMD), variational mode decomposition (VMD), TVF-EMD with fixed parameters and GOA-TVF-EMD, the decomposition performance of the proposed method is better. The proposed method not only improved the under-decomposition, over-decomposition and modal aliasing problems of TVF-EMD, but could also accurately separate the frequency components of the signal and extract the included feature information, so it has practical significance in mechanical fault diagnosis.
A Wirelessly Powered 4-Channel Neurostimulator for Reconstructing Walking Trajectory
Authors: Takeuchi Masaru , Tokutake Katsuhiro , Watanabe Keita , Ito Naoyuki , Aoyama Tadayoshi , Saeki Sota , Kurimoto Shigeru , Hirata Hitoshi , Hasegawa Yasuhisa
Published: September 2022

A wirelessly powered four-channel neurostimulator was developed for applying selective Functional Electrical Stimulation (FES) to four peripheral nerves to control the ankle and knee joints of a rat. The power of the neurostimulator was wirelessly supplied from a transmitter device, and the four nerves were connected to the receiver device, which controlled the ankle and knee joints in the rat. The receiver device had functions to detect the frequency of the transmitter signal from the transmitter coil. The stimulation site of the nerves was selected according to the frequency of the transmitter signal. The rat toe position was controlled by changing the angles of the ankle and knee joints. The joint angles were controlled by the stimulation current applied to each nerve independently. The stimulation currents were adjusted by the Proportional Integral Differential (PID) and feed-forward control method through a visual feedback control system, and the walking trajectory of a rat’s hind leg was reconstructed. This study contributes to controlling the multiple joints of a leg and reconstructing functional motions such as walking using the robotic control technology.
Simplified Attachable EEG Revealed Child Development Dependent Neurofeedback Brain Acute Activities in Comparison with Visual Numerical Discrimination Task and Resting
Authors: Oda Kazuyuki , Colman Ricki , Koshiba Mamiko
Published: September 2022

The development of an easy-to-attach electroencephalograph (EEG) would enable its frequent use for the assessment of neurodevelopment and clinical monitoring. In this study, we designed a two-channel EEG headband measurement device that could be used safely and was easily attachable and removable without the need for restraint or electrode paste or gel. Next, we explored the use of this device for neurofeedback applications relevant to education or neurocognitive development. We developed a prototype visual neurofeedback game in which the size of a familiar local mascot changes in the PC display depending on the user’s brain wave activity. We tested this application at a local children’s play event. Children at the event were invited to experience the game and, upon agreement, were provided with an explanation of the game and support in attaching the EEG device. The game began with a consecutive number visual discrimination task which was followed by an open-eye resting condition and then a neurofeedback task. Preliminary linear regression analyses by the least-squares method of the acquired EEG and age data in 30 participants from 5 to 20 years old suggested an age-dependent left brain lateralization of beta waves at the neurofeedback stage (p = 0.052) and of alpha waves at the open-eye resting stage (p = 0.044) with potential involvement of other wave bands. These results require further validation.
The Acceptance and Use Behavior of Shared Mobility Services in a Rural Municipality
Authors: Schaefer Cindy , Stelter Aida , Holl-Supra Sonja , Weber Stephan , Niehaves Björn
Published: September 2022

In rural regions, needs-based mobility services play an important role in the provision of public services. Shared Mobility Services can optimally complement local public transportation such as buses and trains, even in rural regions, and support the transformation of transportation. There is already research on Shared Mobility Services in the literature, but there is no comparison between all of Germany-wide and a specific municipality. We were interested in learning to what extent there is acceptance among citizens and what their usage behavior is towards such new alternatives. We also aimed to find out whether there are differences between large cities and rural regions and to what extent they differ from each other. In this case study, interplay was demonstrated using the example of a funded Smart City mobility project in a German rural municipality. The objective was to show whether the potential exists to initiate traffic turnaround with the help of Shared Mobility Services. In a quantitative survey of 418 German citizens, 114 of them from the rural municipality, the acceptance and usage behavior of Shared Mobility Services (in the form of car, bike and e-scooter sharing) was investigated. The results show that participants are very interested in Shared Mobility Services and have already gained initial experience with such services. However, there is still a lack of comprehensive services; for instance, the demand for car sharing is still too low, as many citizens still own a private vehicle. Our results show that citizens are too little informed about Shared Mobility Services and that these services need to be advertised much more strongly and clearly, both in analog and digitally. Our study shows that traffic turnaround can be achieved and that many citizens can imagine greater use of Shared Mobility Services in their everyday lives in the future. However, for this to happen, the necessary infrastructure must be in place in rural regions, and local authorities must motivate citizens with sufficient educational work about what is on offer and how to use it.
Trans Territorialization: Building Empowerment beyond Identity Politics
Authors: Yeros Stathis G. , Chiesi Leonardo
Published: September 2022

Transgender/gender non-conforming (TGNC) people and especially people of color face homelessness and housing precarity in the United States at much higher rates than other LGBTQ+ people. In response, during the past decade, TGNC-centered organizations have spearheaded new forms of housing activism, such as cooperatives and Community Land Trusts, building spaces with distinct spatial and aesthetic characteristics. This paper situates those spaces within histories of LGBTQ+ placemaking. It advances the notion of trans territorialization through the analysis of a case study, My Sistah’s House, an organization led by TGNC people of color in Memphis, Tennessee. We analyze trans territorialization as an activist form of spatial appropriation distinct from the better-studied gayborhood model. We assess its generalizable characteristics at three distinct but interrelated scales: dwelling units, community, and cultural embodiment.
Biochemical and Physical Performance Responses to a Soccer Match after a 72-Hour Recovery Period
Authors: Marqués-Jiménez Diego , Calleja-González Julio , Arratibel-Imaz Iñaki , Terrados Nicolás
Published: September 2022

The physiological and neuromuscular responses at 72 h post-match are not widely researched, despite evidence showing substantial changes in recovery markers at 72 h post-match. Consequently, the aim of this study was to determine the biochemical and physical performance responses to a soccer match after a 72-h recovery period. Male soccer players of a semiprofessional team participated in this study. Before playing a friendly match, blood values of testosterone, cortisol, the testosterone-to-cortisol ratio and urea were collected and the squat jump and the Bangsbo Repeated Sprint Ability test were performed. These measurements were considered as baseline (pre match) and were obtained again after a 72-h recovery period. Results indicate that physical performance at 72 h post-match was similar to baseline (squat jump: p = 0.974; total Repeated Sprint Ability time: p = 0.381; Repeated Sprint Ability fatigue index: p = 0.864). However, perturbations in the biochemical milieu derived from the soccer match metabolic and physiological stress were still evident at this time point. While no significant differences compared to pre match were obtained in testosterone and urea concentrations after the recovery period, cortisol and testosterone-to-cortisol ratio values were significantly higher (14.74 ± 3.68 µg/dL vs. 17.83 ± 2.65 µg/dL; p = 0.045; ES 0.92 [0.00; 1.84], very likely) and lower (39.08 ± 13.26 vs. 28.29 ± 7.45; p = 0.038; ES −0.96 [−1.89; −0.04], very likely), respectively. In conclusion, soccer players have similar physical performance to the pre match after a 72-h recovery period, even with signs of biochemical and physiological stress.