bluuebunny/crossref_metadata_2025 huggingface dataset:
Band-Averaged Response Sensitivity Study of an Imaging Spectrometer for the CLARREO Pathfinder Mission
Authors: Salehi Fatholah , Thome Kurtis , Wenny Brian N. , Lockwood Ronald , Wang Zhipeng
Published: May 2022

Prelaunch absolute, SI-traceable radiometric calibration of satellite-based sensors is key to ensuring the utility of imaging spectrometer-based data products. The development of detector-based calibration techniques leads to the feasibility of meeting the 0.3% uncertainty level needed to provide climate quality data sets. Detector-based calibration is a method in which a well-understood and stable transfer radiometer is calibrated in a standards laboratory to SI-traceable standards, and transported to a facility calibrating a sensor of interest. The transfer radiometer provides the calibration of the source used in the radiometric calibration. A detector-based calibration approach is part of the prelaunch calibration of the CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) sensor with the Goddard Laser for Absolute Measurement of Radiance (GLAMR) system. The SI-traceability of GLAMR is through the electric watt as part of the absolute radiometric calibration of the detectors at the National Institute of Standards and Technology using the Primary Optical Watt Radiometer. The current work uses GLAMR data collected with a visible and near-infrared imaging spectrometer calibration demonstration system to develop a source/sensor modeled calibration data set as part of a sensitivity study to evaluate uncertainties from the spectral sampling and processing methods that accompany the GLAMR calibration process. The spectral “supersets” include realistic instrumental features as well as effects from the GLAMR source. The methods needed to ensure that spurious sensor and GLAMR data are excluded are described. Results are given from the sensitivity study related to GLAMR spectral sampling and signal-to-noise ratio (SNR) effects, sensor integration time, and frame averaging of the imaging spectrometer data. The study shows that the 6 nm bandwidth sensor simulation requires a 1 nm spectral sampling of the GLAMR source with a radiance level that provides an in-band peak SNR > 200 to ensure that climate quality accuracies can be achieved. The results are also used to refine the test plan for the independent calibration for the CLARREO Pathfinder sensor calibration to optimize test time while meeting the required accuracy levels.
Improvement of VHR Satellite Image Geometry with High Resolution Elevation Models
Authors: Loghin Ana-Maria , Otepka-Schremmer Johannes , Ressl Camillo , Pfeifer Norbert
Published: May 2022

The number of high and very high resolution (VHR) optical satellite sensors, as well as the number of medium resolution satellites is continuously growing. However, not all high-resolution optical satellite imaging cameras have a sufficient and stable calibration in time. Due to their high agility in rotation, a quick change in viewing direction can lead to satellite attitude oscillation, causing image distortions and thus affecting image geometry and geo-positioning accuracy. This paper presents an approach based on re-projection of regularly distributed 3D ground points from object in image space, to detect and estimate the periodic distortions of Pléiades tri-stereo imagery caused by satellite attitude oscillations. For this, a hilly region was selected as a test site. Consequently, we describe a complete processing pipeline for computing the systematic height errors (deformations, waves) of the satellite-based digital elevation model by using a Lidar high resolution terrain model. Ground points with fixed positions, but with two elevations (actual and corrected) are then re-projected to the satellite images with the aid of the Rational Polynomial Coefficients (RPCs) provided with the imagery. Therefore, image corrections (displacements) are determined by computing the differences between the distinct positions of corresponding points in image space. Our experimental results in Allentsteig (Lower Austria) show that the systematic height errors of satellite-based elevation models cannot be compensated with an usual or even high number of Ground Control Points (GCPs) for RPC bias correction, due to insufficiently known image orientations. In comparison to a reference Lidar Digital Terrain Model (DTM), the computed elevation models show undulation effects with a maximum height difference of 0.88 m in along-track direction. With the proposed method, image distortions in-track direction with amplitudes of less than 0.15 pixels were detected. After applying the periodic distortion compensation to all three images, the systematic elevation discrepancies from the derived elevation models were successfully removed and the overall accuracy in open areas improved by 33% in the RMSE. Additionally, we show that a coarser resolution reference elevation model (AW3D30) is not feasible for improving the geometry of the Pléiades tri-stereo satellite imagery.
The Annual Cycle in Mid-Latitude Stratospheric and Mesospheric Ozone Associated with Quasi-Stationary Wave Structure by the MLS Data 2011–2020
Authors: Zhang Chenning , Evtushevsky Oleksandr , Milinevsky Gennadi , Klekociuk Andrew , Andrienko Yulia , Shulga Valery , Han Wei , Shi Yu
Published: May 2022

The purpose of this work is to study quasi-stationary wave structure in the mid-latitude stratosphere and mesosphere (40–50°N) and its role in the formation of the annual ozone cycle. Geopotential height and ozone from Aura MLS data are used and winter climatology for January–February 2011–2020 is considered. The 10-degree longitude segment centered on Longfengshan Brewer station (44.73°N, 127.60°E), China, is examined in detail. The station is located in the region of the Aleutian Low associated with the quasi-stationary zonal maximum of total ozone. Annual and semi-annual oscillations in ozone using units of ozone volume mixing ratio and concentration, as well as changes in ozone peak altitude and in time series of ozone at individual pressure levels between 316 hPa (9 km) and 0.001 hPa (96 km) were compared. The ozone maximum in the vertical profile is higher in volume mixing ratio (VMR) values than in concentration by about 15 km (5 km) in the stratosphere (mesosphere), consistent with some previous studies. We found that the properties of the annual cycle are better resolved in the altitude range of the main ozone maximum: middle–upper stratosphere in VMR and lower stratosphere in concentration. Both approaches reveal annual and semi-annual changes in the ozone peak altitudes in a range of 4–6 km during the year. In the lower-stratospheric ozone of the Longfengshan domain, an earlier development of the annual cycle takes place with a maximum in February and a minimum in August compared to spring and autumn, respectively, in zonal means. This is presumably due to the higher rate of dynamical ozone accumulation in the region of the quasi-stationary zonal ozone maximum. The “no-annual-cycle” transition layers are found in the stratosphere and mesosphere. These layers with undisturbed ozone volume mixing ratio are of interest for more detailed future study.
mmS-TCP: Scalable TCP for Improving Throughput and Fairness in 5G mmWave Networks
Authors: Kim Geon-Hwan , Cho You-Ze
Published: May 2022

The millimeter-wave (mmWave) band, which can provide data rates of multi-gigabits per second, could play a major role in achieving the throughput goals of 5G networks. However, the high-bandwidth mmWave signal is susceptible to blockage by various obstacles, which results in very large and frequent degradation in the quality of the received signals. TCP, the most representative transport layer protocol, suffers from significant performance degradation due to the very dynamic channel conditions of the mmWave signal. Therefore, in this paper, we propose a congestion control algorithm that guarantees sufficient throughput in 5G mmWave networks and that does not significantly worsen TCP fairness. The proposed algorithm, which is a modification of Scalable TCP (S-TCP) that is designed for high-speed networks, provides a more stable performance than the existing TCP congestion control algorithm in mmWave networks through simple modifications. In various simulation experiments that considered the actual mobile user environment, the proposed mmWave Scalable TCP (mmS-TCP) algorithm demonstrated throughput up to 2.4 times higher than CUBIC TCP in single flow evaluation, and the inter-protocol fairness index when competing with CUBIC flow significantly improved from 0.819 of S-TCP to 0.9733. Moreover, the mmS-TCP algorithm reduced the number of duplicated ACKs by 1/4 compared with S-TCP, and it improved the average total throughput and intra-protocol fairness simultaneously.
The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks
Authors: Sepulveda Frank , Thangraj Joseph Soloman , Pulliam Jay
Published: May 2022

Recent technological advances have reduced the complexity and cost of developing sensor networks for remote environmental monitoring. However, the challenges of acquiring, transmitting, storing, and processing remote environmental data remain significant. The transmission of large volumes of sensor data to a centralized location (i.e., the cloud) burdens network resources, introduces latency and jitter, and can ultimately impact user experience. Edge computing has emerged as a paradigm in which substantial storage and computing resources are located at the “edge” of the network. In this paper, we present an edge storage and computing framework leveraging commercially available components organized in a tiered architecture and arranged in a hub-and-spoke topology. The framework includes a popular distributed database to support the acquisition, transmission, storage, and processing of Internet-of-Things-based sensor network data in a field setting. We present details regarding the architecture, distributed database, embedded systems, and topology used to implement an edge-based solution. Lastly, a real-world case study (i.e., seismic) is presented that leverages the edge storage and computing framework to acquire, transmit, store, and process millions of samples of data per hour.
A Micropowered Chemoresistive Sensor Based on a Thin Alumina Nanoporous Membrane and SnxBikMoyOz Nanocomposite
Authors: Gorokh Gennady , Zakhlebayeva Anna , Taratyn Igor , Lozovenko Andrei , Zhylinski Valery , Iji Michael , Fedosenko Vladimir , Taleb Abdelhafed
Published: May 2022

This work presents and discusses the design of an efficient gas sensor, as well as the technological process of its fabrication. The optimal dimensions of the different sensor elements including their deformation were determined considering the geometric modeling and the calculated moduli of the elasticity and thermal conductivity coefficients. Multicomponent SnxBikMoyOz thin films were prepared by ionic layering on an anodic alumina membrane and were used as gas-sensitive layers in the sensor design. The resistance of the SnxBikMoyOz nanostructured film at temperatures up to 150 °C exceeded 106 Ohm but decreased to 104 Ohm at 550 °C in air. The sensitivity of the SnxBikMoyOz composite to concentrations of 5 and 40 ppm H2 at 250 °C (10 mW) was determined to be 0.22 and 0.40, respectively.
Lightweight Internet of Things Botnet Detection Using One-Class Classification
Authors: Malik Kainat , Rehman Faisal , Maqsood Tahir , Mustafa Saad , Khalid Osman , Akhunzada Adnan
Published: May 2022

Like smart phones, the recent years have seen an increased usage of internet of things (IoT) technology. IoT devices, being resource constrained due to smaller size, are vulnerable to various security threats. Recently, many distributed denial of service (DDoS) attacks generated with the help of IoT botnets affected the services of many websites. The destructive botnets need to be detected at the early stage of infection. Machine-learning models can be utilized for early detection of botnets. This paper proposes one-class classifier-based machine-learning solution for the detection of IoT botnets in a heterogeneous environment. The proposed one-class classifier, which is based on one-class KNN, can detect the IoT botnets at the early stage with high accuracy. The proposed machine-learning-based model is a lightweight solution that works by selecting the best features leveraging well-known filter and wrapper methods for feature selection. The proposed strategy is evaluated over different datasets collected from varying network scenarios. The experimental results reveal that the proposed technique shows improved performance, consistent across three different datasets used for evaluation.
Bayesian Semiparametric Regression Analysis of Multivariate Panel Count Data
Authors: Wang Chunling , Lin Xiaoyan
Published: May 2022

Panel count data often occur in a long-term recurrent event study, where the exact occurrence time of the recurrent events is unknown, but only the occurrence count between any two adjacent observation time points is recorded. Most traditional methods only handle panel count data for a single type of event. In this paper, we propose a Bayesian semiparameteric approach to analyze panel count data for multiple types of events. For each type of recurrent event, the proportional mean model is adopted to model the mean count of the event, where its baseline mean function is approximated by monotone I-splines. The correlation between multiple types of events is modeled by common frailty terms and scale parameters. Unlike many frequentist estimating equation methods, our approach is based on the observed likelihood and makes no assumption on the relationship between the recurrent process and the observation process. Under the Poisson counting process assumption, we develop an efficient Gibbs sampler based on novel data augmentation for the Markov chain Monte Carlo sampling. Simulation studies show good estimation performance of the baseline mean functions and the regression coefficients; meanwhile, the importance of including the scale parameter to flexibly accommodate the correlation between events is also demonstrated. Finally, a skin cancer data example is fully analyzed to illustrate the proposed methods.
Expansion of the Invasive Plant Species Reynoutria japonica Houtt in the Upper Bistrița Mountain River Basin with a Calculus on the Productive Potential of a Mountain Meadow
Authors: Negrea Bogdan-Mihai , Stoilov-Linu Valeriu , Pop Cristian-Emilian , Deák György , Crăciun Nicolae , Făgăraș Marius Mirodon
Published: May 2022

Many invasive plant species use interactions with their anthropic environment as a propagation factor and benefit from climate changes, which have become accentuated in the last decade. The way such species interact with climate changes, as well as their high specific ecological plasticity, gives them a consistent advantage over native plant species. This work aims to demonstrate through a simple calculation the quantification of the productive potential of a wet meadow on which populations of an invasive plant species grew. The loss of productive potential induced by Reynoutria japonica Houtt on a mountain meadow in Ciocănești village, Romania, was the main objective. In the case of the productive potential of the meadows, a method for the general calculation of such losses was shown. The degree of anthropization of the studied area was also evaluated, correlating the degree of anthropization with the invasive species’ potential for spreading and affecting the mountain area.
Multi-Session Surface Electromyogram Signal Database for Personal Identification
Authors: Kim Jin-Su , Song Cheol-Ho , Bak EunSang , Pan Sung-Bum
Published: May 2022

Surface electromyogram (sEMG) refers to a biosignal acquired from the skin surface during the contraction of skeletal muscles, and a different signal waveform is generated, depending on the motion performed. Therefore, in contrast to generic personal identification, which uses only a piece of registered information, the sEMG changes the registered information in a personal identification method. The sEMG database (DB) for conventional personal identification has shortcomings, such as a few subjects and the inability to verify sEMG signal variability. In order to solve the problems of DBs, this paper describes a method for constructing a multi-session sEMG DB for many subjects. Data were obtained in two channels when each of the 200 subjects performed 12 motions. There were three sessions, and each motion was repeated 10 times in time intervals of a day or longer between each session. Furthermore, to verify the effectiveness of the constructed sEMG DB, we conducted a personal identification experiment. According to the experimental results, the accuracy for five subjects was 74.19%, demonstrating the applicability of the constructed multi-session sEMG DB.
Exploring the Moral Challenges of Confronting High-Carbon-Emitting Behavior: The Role of Emotions and Media Coverage
Authors: Stoll-Kleemann Susanne , Nicolai Susanne , Franikowski Philipp
Published: May 2022

In this article, we address the climate crisis as a moral issue and discuss the relevant moral and emotional processes and the role of the media underlying the motivations of individuals to behave in a less carbon-emitting manner. We provide theoretical insights from social psychology and emotion research and empirical data based on an online survey from Germany (N = 979). In the theoretical part, we outline the role of emotions in influencing carbon-related behavior, with a particular focus on self-condemning (e.g., guilt or shame), self-praising (e.g., pride), or other-suffering emotions (e.g., empathy). We further summarize the reasons for the low influence of the media on carbon-related behavior compared to the COVID-19 pandemic. The empirical results confirm that participants reported other- suffering and self-condemning emotions in response to news content and rated their likelihood of personal behavior change as high when confronted with news about the climate crisis on a daily basis, as has been widely the case during the COVID-19 pandemic. We argue that the media is responsible for regularly reporting on the victims of the climate crisis in order to generalize self-condemning and other-suffering emotions into affective attitudes. Opinion leaders can function as role models for low-carbon behavior.
How Is Telework Experienced in Academia?
Authors: Widar Linda , Heiden Marina , Boman Eva , Wiitavaara Birgitta
Published: May 2022

An increasing number of academic institutions offer their staff the option to work from other places than the conventional office, i.e., telework. Academic teaching and research staff are recognized as some of the most frequent teleworkers, and this seems to affect their well-being, work performance, and recovery in different ways. This study aimed to investigate academics’ experiences and perceptions of telework within the academic context. For this, we interviewed 26 academics from different Swedish universities. Interviews were analyzed with a phenomenographic approach, which showed that telework was perceived as a natural part of academic work and a necessary resource for coping with, and recovering from, high work demands. Telework was mostly self-regulated but the opportunity could be determined by work tasks, professional culture, and management. Telework could facilitate the individual’s work but could contribute to challenges for the workgroup. Formal regulations of telework were considered a threat to academics’ work autonomy and to their possibility to cope with the high work demands. The findings provide insight into academics’ working conditions during teleworking, which may be important for maintaining a sustainable work environment when academic institutions offer telework options.
Generation of Potential Sites for Sustainable Water Harvesting Techniques in Oum Zessar Watershed, South East Tunisia
Authors: Abdeladhim Mohamed Arbi , Fleskens Luuk , Baartman Jantiene , Sghaier Mongi , Ouessar Mohamed , Ritsema Coen J.
Published: May 2022

Water harvesting techniques (WHTs) are important climate change adaptation measures to better manage rainwater for domestic and agricultural purposes, but which WHT to plan where is subject to sustainability considerations. Moreover, suitability of different WHTs varies from one location to another, depending on physical and socio-economic conditions. This study aimed to identify suitable sites for WHTs taking into account stakeholders’ sustainability criteria. In a participatory assessment framework, Geographic Information Systems and the “Simple Multi-Attribute Rating Technique” were combined to generate suitability maps and to guide sustainable WHTs investments. Steps included the calculation of a sustainability index for a set of traditional and newly introduced WHTs from the perspective of two stakeholder groups, farmers and decision-makers, and its integration with layers of biophysical constraints. An application of the framework in the Oum Zessar watershed, southeast Tunisia, shows that traditional techniques are the most suitable and sustainable for farmers and fall within the highly suitable class in 76.4% of the total area, while decision-makers prefer innovative techniques that are highly suitable in 80.4% of the watershed. The framework offers a scalable transparent process for knowledge integration in support of WHT investment decisions that can be adapted to other dryland areas.
The Adequacy of Accounting Education in the Development of Transversal Skills Needed to Meet Market Demands
Authors: Carvalho Carla , Almeida Ana Carlos
Published: May 2022

With the ongoing digital transformation, accountants will need a more technological profile and greater mastery of transversal skills. In this context, higher education institutions (HEIs) assume a fundamental role, as they must adapt the teaching methodologies of accounting courses to meet new market demands. This study aims to identify the transversal skills most needed by accounting professionals to meet market demands and analyze the suitability of higher education in Portugal for the development of those skills. To this end, semi-structured interviews were carried out with people who directly or indirectly deal with accounting professionals and focus groups that included lecturers, students, and recent graduates. Conclusions indicate that communication is the most valuable transversal skill to respond to the new requirements of the profession, followed by being proactive, showing initiative, successful teamwork, and the ability to adapt to new contexts. Accountants are also required to invest more time in information and communication technologies (ICT) training. Evidence indicates that accounting education in Portugal does not seem to adequately prepare students with these skills, continuing to rely on traditional approaches to teaching and assessment.
Earthquake Vulnerability Reduction by Building a Robust Social-Emotional Preparedness Program
Authors: Daskal Shira , Ben-Eliyahu Adar , Levy Gal , Ben-Haim Yakov , Avny Ronnen
Published: May 2022

Despite the progress made in understanding the characteristics of earthquakes, the predictions of earthquake activity are still inevitably very uncertain, mainly because of the highly complex nature of the earthquake process. The population′s mental strength is of high importance not only to cope with an earthquake, but also to return quickly to functioning. Social-emotional preparedness for extreme adverse events and crises is a critical factor in the population’s quick recovery and return to full functioning. In the present study, we apply a multi-disciplinary lens to extend the scope of earthquake preparedness to include social-emotional programs. The goal of this study is to develop a robust “no-regret” social-emotional preparedness program (SEPP) along with methodological tools for evaluating the SEPP robustness against uncertainty in different earthquake scenarios. The research methodology is twofold. First, we develop the SEPP based on social-emotional proxies-for-robustness, and second, we apply the info-gap decision theory (IGDT) methods to assess the robustness of the SEPP in the face of uncertainty in different earthquake scenarios. The findings indicate gaps between the level of robustness of the SEPP in different scenarios. A key conclusion that emerges from this study is the need for a robust SEPP to make a significant contribution to the population’s ability to return to functioning. Such SEPP should be formulated to maximize the robustness against uncertainty in different scenarios, rather than the traditional planning based on a ‘one size fits all’ approach. Formulating a robust SEPP by analyzing the robustness of the SEPP against uncertainty will enable to make decisions immune to surprises. Ways to create or improve earthquake preparedness are suggested for policy and in-school application.
Can Green Innovation and New Urbanization Be Synergistic Development? Empirical Evidence from Yangtze River Delta City Group in China
Authors: Ma Lindong , Hong Yuanxiao , Chen Xihui , Quan Xiaoyong
Published: May 2022

Green innovation has become the mainstream of the era, and new urbanization is an inevitable choice in China’s urbanization development. Focusing on the topics of green innovation and new urbanization, much work has been done to analyze their influencing factors separately, while the relationship between the two remains to be explored. This paper selects the representative indicators to study the new urbanization and green innovation of the Yangtze River Delta city group from the perspective of the whole and individual cities, in terms of spatiotemporal evolution traits, by using the SBM, entropy method, coupling model, spatial econometric and geographical detector. The results reveal the following: (1) there is a synergistic effect between green innovation and new urbanization development, and the role has been increasing; (2) green innovation and new urbanization present positive spatial autocorrelation and regional agglomeration; (3) in the detection of driving factors, economic development > social conditions > natural resources; most groups (40/66) of factor interactions present nonlinear enhancement, and the digital economy factor accounts for the largest proportion. Finally, according to the findings, we offer a suggestion and a conclusion.
The Principle and Practice of Strong Mine Pressure Control in the Initial Mining and Caving Stages under Multiple Key Strata
Authors: Miao Kaijun , Wang Dapeng , Tu Shihao , Tu Hongsheng , Zhu Defu , Liu Xuewen , Li Wenlong , Tang Long
Published: May 2022

The mechanism of strong mine pressure control in the initial mining and caving stages under multiple key strata (MKS) was studied by theoretical analysis, numerical simulation and field measurement in order to avoid the dynamic pressure accidents caused by the MKS breaking in interactions in the initial mining and caving stage. Panel 13103 (P13103) in the Shan Xi Jinshen Shaping Coal Mine was used sas the study site. The overlying structure and the breaking characteristics of the key strata were analyzed and the overlying structure model of longwall top-coal caving (LTC) under MKS was established. Reasonable initial mining heights and initial caving positions were determined and the spatial and temporal characteristics of ground pressure and roof structure of the working face in the mining process were obtained. The results show that, in the scheme of starting top-coal caving after the working face advanced 20 m, the support damage ratios were all greater than 50% with roof weighting, which is prone to induce prop crash accidents. The dynamic load formed by the second weighting was greater than first weighting under the MKS. The duration of mine pressure tended to be stable with fully developed caving zone heights. With the designed mining scheme, the safe and efficient mining of P13103 is guaranteed.
Agricultural Management Practices and Decision-Making in View of Soil Organic Matter in the Urbanizing Region of Bangalore
Authors: Moran-Rodas Virna Estefania , Preusse Verena , Wachendorf Christine
Published: May 2022

Rapid urbanization and agricultural intensification are currently impacting the soils of many tropical countries. Bangalore is a growing megacity experiencing both issues and their derived ecological and socio-economic effects. This paper seeks to understand how the socio-economic effects of urbanization are affecting soil organic carbon (SOC) in Bangalore’s rural–urban interface. We first compiled information on how management practices affect SOC dynamics and specifically evaluated the effects of fertilization practices on SOC levels in major cropping systems. We then used interview data from farmers’ households across an urbanity gradient in Bangalore to test the association between urbanization as well as related socio-economic drivers and farming practices. We found that fertilization increases SOC concentrations, especially when mineral fertilizer is combined with additional farmyard manure. Single mineral fertilizer and a combination of mineral fertilizer and farmyard manure are commonly applied in Bangalore. Conservation practices, such as reduced tillage and mulching, are applied by 48% and 16% of households, respectively. Farm and household characteristics, including market integration, are the most important determinants of management decisions that affect SOC. Our study shows that improving farm and household conditions and opportunities, independently of the degree of urbanity, is necessary for implementing agricultural practices that can benefit SOC in Bangalore.
Does High Spatial Density Imply High Population Density? Spatial Mechanism of Population Density Distribution Based on Population–Space Imbalance
Authors: Shao Dian , Xiong Weiting
Published: May 2022

Numerous studies have suggested a positive correlation between spatial and population densities. However, few have systematically conducted quantitative analysis and deciphered the detailed correlation in block scale. Here, we construct a population–space correlation algorithm to quantify and compare the correlation between mobile phone signalling data and vector spatial data and identify blocks with uneven population density. We analyse the influences of various urban spatial characteristics on population density and the distribution characteristics of the identified city blocks. Changzhou City, China, was selected as the study case. The results indicate that (1) population density distribution is unbalanced only when spatial density exceeds a critical value, reflecting the level and sphere of influence of blocks with varying spatial densities; (2) low population density distribution is concentrated in the zonal space, along the boundary between primary and secondary urban centres; (3) spatial characteristics affecting population density distribution vary with the type of block, and the green landscape’s attractiveness is reduced. Our study provides a novel perspective on quantifying the link between urban form and population distribution. It can help decision-makers and planners in accurately recommending urban intervention in population density distribution by adjusting the spatial morphology and promoting rational use of urban public resources.
Editorial of Special Issue “Application of Mathematical Modelling and Symmetry in Neuroscience”
Authors: Navarro-Pardo Esperanza
Published: May 2022

The first article is “Spectral Clustering Reveals Different Profiles of Central Sensitization in Women with Carpal Tunnel Syndrome (CTS)” [...]
Electromyographic Activity of Masticatory Muscles in Subjects with Juvenile Idiopathic Arthritis: A Case—Control Study
Authors: Caroccia Francesco , Passanello Ludovica , Pipitone Rossana , Moscagiuri Francesco , Asperio Paolo , Lucchese Alessandra , Breda Luciana , D’Attilio Michele
Published: May 2022

The aim of this study was to evaluate the effect of juvenile idiopathic arthritis (JIA) on the activity of masticatory muscles using surface electromyography (sEMG). Forty-one JIA subjects (ten males, thirty-one females; average age 13 years ± 3) and thirty-two healthy control subjects (twenty-seven females, five males; average age 14 years ± 2) were recruited. sEMG of anterior temporalis (TA), masseter (MM), and sternocleidomastoid (SCM) muscles was performed by using the occlusal contact analyzer software called Teethan (BTS S.p.A., Garbagnate Milanese, Milan, Italy). Comparisons between groups were assessed with unpaired t-tests for non-normally distributed data and with Mann–Whitney U tests for normally distributed parameters. The JIA group showed a significant increased percentage overlapping coefficient of TA (POC TA) (p = 0.01) and impact index (IMP) (p = 0.003). No significant differences were observed for the POC MM, POC SCM, percentage overlapping coefficient between posterior and anterior teeth contact (BAR), the torsion index (TORS), and the asymmetry index (ASIM). Masticatory muscles seemed to be slightly affected by JIA. sEMG could be an effective aid in the early clinical detection of TMJ involvement in JIA. Further research is needed to confirm its validity.
Structural Stability and Electronic Properties of Boron Phosphide Nanotubes: A Density Functional Theory Perspective
Authors: García-Toral Dolores , Mendoza-Báez Raúl , Chigo-Anota Ernesto , Flores-Riveros Antonio , Vázquez-Báez Víctor M. , Cocoletzi Gregorio Hernández , Rivas-Silva Juan Francisco
Published: May 2022

Based on the Density Functional Theory (DFT) calculations, we analyze the structural and electronic properties of boron phosphide nanotubes (BPNTs) as functions of chirality. The DFT calculations are performed using the M06-2X method in conjunction with the 6-31G(d) divided valence basis set. All nanostructures, (n,0) BPNT (n = 5–8, 10, 12, 14) and (n,n) BPNT (n = 3–11), were optimized minimizing the total energy, assuming a non-magnetic nature and a total charge neutrality. Results show that the BPNT diameter size increases linearly with the chiral index “n” for both chiralities. According to the global molecular descriptors, the (3,3) BPNT is the most stable structure provided that it shows the largest global hardness value. The low chirality (5,0) BPNT has a strong electrophilic character, and it is the most conductive system due to the small |HOMO-LUMO| energy gap. The chemical potential and electrophilicity index in the zigzag-type BPNTs show remarkable chirality-dependent behavior. The increase in diameter/chirality causes a gradual decrease in the |HOMO-LUMO| energy gap for the zigzag BPNTs; however, in the armchair-type BPNTs, a phase transition is generated from a semiconductor to a conductor system. Therefore, the nanostructures investigated in this work may be suggested for both electrical and biophysical applications.
Scattering Properties of an Acoustic Anti-Parity-Time-Symmetric System and Related Fabry–Perot Resonance Mode
Authors: Zhang Haixiao , Liu Xiaoli , Bao Yu , Zhang Yiwei , Zhao Jinyu
Published: May 2022

The pursuit of artificial structures exhibiting unusual acoustic properties is a major scientific endeavor, in which anti-parity-time (PT) symmetry has been coming into view recent years. At the same time, with the emergence of new acoustic metamaterials, the classical Fabry–Perot resonance mode also exhibits fascinating scattering features similar to those of the anti-PT-symmetric system. We derive the generalized relation for the scattering parameters of an acoustic anti-PT-symmetric system with a transfer matrix, including conjugate bidirectional reflection coefficients and pure real feature of transmission coefficient. In the absence of the real or the imaginary (representing gain/loss) part of the refractive index, the anti-PT-symmetric system degrades into a pair of complementary media, resulting in the bidirectional total transmission. Moreover, a Fabry–Perot resonance mode exhibiting conjugate bidirectional reflection coefficients and a pure imaginary transmission coefficient has been demonstrated. Our results are meaningful for guiding the experimental test of an acoustic anti-PT-symmetric system and the design of associated bidirectional response prototype devices.
Recent Progress of Squaraine-Based Fluorescent Materials and Their Biomedical Applications
Authors: Qiao Weiguo , Li Zhong’an
Published: May 2022

Squaraines (SQs) are unusual cyanine dyes with a unique resonance-stabilized zwitterionic structure. These dyes have attracted significant attention in the fields of organic electronics and organic photonics, due to their facile synthesis, intense and narrow visible and near-infrared absorption/emission, high photostability, low biotoxicity, etc. In this review, we summarize the recent progress of SQ-based fluorescent materials and their biomedical applications. After a brief introduction to SQs, general synthetic routes and design principles of SQ-based fluorescent materials, as well as their aggregation-induced luminescence behaviors, are discussed. Subsequently, their biomedical applications for cell imaging and as fluorescent sensors and therapeutic agents are introduced. Finally, a summary and perspective are given for promoting the development of SQs-based fluorescent materials.
An Improved Multi-Objective Harris Hawk Optimization with Blank Angle Region Enhanced Search
Authors: Yan Zhicheng , Jin Qibing , Zhang Yang , Wang Zeyu , Li Ziming
Published: May 2022

Aiming at the problems of low precision, low search efficiency, and being easy to fall into local optimization of the multi-objective harris hawk optimization algorithm (MOHHO) based on grid method, a MOHHO based on blank angle region enhanced search (BARESMOHHO) is proposed. The main changes of the algorithm are as follows: firstly, chaotic mapping is used to initialize the population, which is beneficial to speed up the search. Then, in order to find low-density regions faster, the algorithm adjusts the classification level according to the number of individuals in the external archive. In order to make the distribution of individuals in the target space more uniform, inspired by the idea of symmetrical segmentation, the number of archives at different levels are symmetrically distributed. Finally, it strengthens the search for the non-individual region (blank angle region) in the process of division. The effectiveness of the proposed algorithm is verified by comparing it with some known classical functions on test functions.
A New Dynamic Fault Tree Analysis Method of Electromagnetic Brakes Based on Bayesian Network Accompanying Wiener Process
Authors: Pang Jihong , Dai Jinkun , Zhang Chaohui , Zhou Hongyong , Li Yong
Published: May 2022

Product fault diagnosis has always been the focus of quality and reliability research. However, a failure–rate curve of some products is a symmetrical function, the fault analysis result is not true because the failure period of the products cannot be judged accurately. In order to solve the problem of fault diagnosis, this paper proposes a new Takagi-Sugeno (T-S) dynamic fault tree analysis method based on a Bayesian network accompanying the Wiener process. Firstly, the top event, middle event, and bottom event of the product failure mode are determined, and the T-S dynamic fault tree is constructed. Secondly, in order to form the Bayesian network diagram of the T-S dynamic fault tree, the events in the fault tree are transformed into nodes, and the T-S dynamic gate is also transformed into directed edges. Then, the Wiener process is used to model the performance degradation process of the stationary independent increment of the symmetric function distribution, and the maximum likelihood estimation method is applied to estimate the unknown parameters of the degradation model. Next, the product residual life prediction model is established based on the concept of first arrival time, and a symmetric function of failure–rate curve is obtained by using the product failure probability density function. According to the fault density function derived from the Wiener process, the reverse reasoning algorithm of the Bayesian network is established. Combined with the prior probability of the bottom event, the posterior probability of the root node is calculated and sorted as well. Finally, taking the insufficient braking force of electromagnetic brakes as an example, the practicability and objectivity of the new method are proved.
Geometry of Developable Surfaces of Frenet Type Framed Base Curves from the Singularity Theory Viewpoint
Authors: Zhao Qiming , Yang Lin , Wang Yongqiao
Published: May 2022

In this paper, we consider Frenet type framed base curves that may have singular points and define one-parameter developable surfaces associated with such curves. By using the singularity theory, we classify the generic singularities of the developable surfaces, which are cuspidal edges and swallowtails. In order to characterize these singularities, two geometric invariants are discovered. At last, an example is given to demonstrate the main results.
Global Quantum Information-Theoretic Measures in the Presence of Magnetic and Aharanov-Bohm (AB) Fields
Authors: Edet Collins Okon , Ettah Emmanuel Benjamin , Aljunid Syed Alwee , Endut Rosdisham , Ali Norshamsuri , Ikot Akpan Ndem , Asjad Muhammad
Published: May 2022

The global quantum information-theoretical analysis of the class of Yukawa potential (CYP) in the presence of magnetic and Aharonov–Bohm (AB) fields has been examined both analytically and numerically in this research piece. The energy equation and wave function for the CYP are obtained by solving the Schrodinger equation in the presence of external magnetic and AB fields using the functional analysis technique. The probability density is used to calculate the Tsallis, Rényi, and Onicescu information energy entropies numerically. The influence of the screening parameter (β), magnetic (B→), and AB (ξ) fields on the global information-theoretical measurements for the CYP is explored. Atomic and molecular physics, quantum chemistry, and physics are specific areas where these research findings will find application.
Optimization of 5G/6G Telecommunication Infrastructure through an NFV-Based Element Management System
Authors: Arulappan Arunkumar , Raja Gunasekaran , Passi Kalpdrum , Mahanti Aniket
Published: May 2022

Network Function Virtualization (NFV) is an enabling technology that brings together automated network service management and corresponding virtualized network functions that use an NFV Infrastructure (NFVI) framework. The Virtual Network Function Manager (VNFM) placement in a large-scale distributed NFV deployment is therefore a challenging task due to the potential negative impact on performance and operating expense cost. The VNFM assigns Virtual Network Functions (VNFs) and operates efficiently based on network demands with resilient performance through efficient placement techniques. The degradation in performance and a tremendous increase in capital expenditure and operating expenses indicated this chaotic problem. This article proposed a method for VNFM placement using information on the resources of each nodes’ Element Manager (EM), which is an efficient method to assign VNFs to each node of element management systems. In addition, this paper proposed an Optimized Element Manager (OEM) method for looking at appropriate EMs for the placement of VNF through periodic information on available resources. It also overcomes challenges such as delays and variations in VNFs workload for edge computing and distributed cloud regions. The performance is measured based on computations performed on various optimization algorithms such as linear programming and tabu search algorithms. The advent of the new service provisioning model of BGP-EVPN for VXLAN is materialized by integrating VTS with OpenStack. The numerical analysis shows that the proposed OEM algorithm gives an optimal solution with an average gap of 8%.
Cytotoxicity of Venoms and Cytotoxins from Asiatic Cobras (Naja kaouthia, Naja sumatrana, Naja atra) and Neutralization by Antivenoms from Thailand, Vietnam, and Taiwan
Authors: Chong Ho Phin , Tan Kae Yi , Liu Bing-Sin , Sung Wang-Chou , Tan Choo Hock
Published: May 2022

Envenoming by cobras (Naja spp.) often results in extensive local tissue necrosis when optimal treatment with antivenom is not available. This study investigated the cytotoxicity of venoms and purified cytotoxins from the Monocled Cobra (Naja kaouthia), Taiwan Cobra (Naja atra), and Equatorial Spitting Cobra (Naja sumatrana) in a mouse fibroblast cell line, followed by neutralization of the cytotoxicity by three regional antivenoms: the Thai Naja kaouthia monovalent antivenom (NkMAV), Vietnamese snake antivenom (SAV) and Taiwanese Neuro bivalent antivenom (NBAV). The cytotoxins of N. atra (NA-CTX) and N. sumatrana (NS-CTX) were identified as P-type cytotoxins, whereas that of N. kaouthia (NK-CTX) is S-type. All venoms and purified cytotoxins demonstrated varying concentration-dependent cytotoxicity in the following trend: highest for N. atra, followed by N. sumatrana and N. kaouthia. The antivenoms moderately neutralized the cytotoxicity of N. kaouthia venom but were weak against N. atra and N. sumatrana venom cytotoxicity. The neutralization potencies of the antivenoms against the cytotoxins were varied and generally low across NA-CTX, NS-CTX, and NK-CTX, possibly attributed to limited antigenicity of CTXs and/or different formulation of antivenom products. The study underscores the need for antivenom improvement and/or new therapies in treating local tissue toxicity caused by cobra envenomings.
On the Non-Abelian U-Duality of 11D Backgrounds
Authors: Musaev Edvard T.
Published: May 2022

In this work, we generalise the procedure of the non-abelian T-duality based on a B-shift and a sequence of formal abelian T-dualities in non-isometric directions to 11-dimensional backgrounds. This consists of a C-shift followed by either a formal (abelian) U-duality transformation or taking an IIB section. By construction, this is a solution generating transformation. We investigate the restrictions and applicability of the procedure and find that it can provide supergravity solutions for the SL(5) exceptional Drinfeld algebra only when the isometry algebra of the sigma-model target space decomposes into a direct sum. This is consistent with examples known in the literature.
Goldstone States as Non-Local Hidden Variables
Authors: Fabbri Luca
Published: May 2022

We consider the theory of spinor fields in polar form, where the spinorial true degrees of freedom are isolated from their Goldstone states, and we show that these carry information about the frames which is not related to gravitation, so that their propagation is not restricted to be either causal or local: we use them to build a model of entangled spins where a singlet possesses a uniform rotation that can be made to collapse for both states simultaneously regardless their spatial distance. Models of entangled polarizations with similar properties are also sketched. An analogy with the double-slit experiment is also presented. General comments on features of Goldstone states are given.