bluuebunny/crossref_metadata_2025 huggingface dataset:
Optical Trapping, Sensing, and Imaging by Photonic Nanojets
Authors: Li Heng , Song Wanying , Zhao Yanan , Cao Qin , Wen Ahao
Published: October 2021

The optical trapping, sensing, and imaging of nanostructures and biological samples are research hotspots in the fields of biomedicine and nanophotonics. However, because of the diffraction limit of light, traditional optical tweezers and microscopy are difficult to use to trap and observe objects smaller than 200 nm. Near-field scanning probes, metamaterial superlenses, and photonic crystals have been designed to overcome the diffraction limit, and thus are used for nanoscale optical trapping, sensing, and imaging. Additionally, photonic nanojets that are simply generated by dielectric microspheres can break the diffraction limit and enhance optical forces, detection signals, and imaging resolution. In this review, we summarize the current types of microsphere lenses, as well as their principles and applications in nano-optical trapping, signal enhancement, and super-resolution imaging, with particular attention paid to research progress in photonic nanojets for the trapping, sensing, and imaging of biological cells and tissues.
Parametric Study of Proton Acceleration from Laser-Thin Foil Interaction
Authors: Almassarani Mohammed , Meng Sixu , Beleites Burgard , Ronneberger Falk , Paulus Gerhard G. , Gopal Amrutha
Published: October 2021

We experimentally investigated the accelerated proton beam characteristics such as maximum energy and number by varying the incident laser parameters. For this purpose, we varied the laser energy, focal spot size, polarization, and pulse duration. The proton spectra were recorded using a single-shot Thomson parabola spectrometer equipped with a microchannel plate and a high-resolution charge-coupled device with a wide detection range from a few tens of keV to several MeV. The outcome of the experimental findings is discussed in detail and compared to other theoretical works.
Facile Fabrication of Eucommia Rubber Composites with High Shape Memory Performance
Authors: Xia Lin , Meng Jiafeng , Ma Yuan , Zhao Ping
Published: October 2021

We processed a series of shape memory Eucommia rubber (ER) composites with both carbon–carbon and ionic cross-linking networks via a chemical cross-linking method. The influence of the carbon–carbon cross-linking and ion cross-linking degree of ER composites on curing, mechanical, thermal, and shape memory properties were studied by DSC, DMA, and other analytical techniques. Dicumyl peroxide (DCP) and zinc dimethacrylate (ZDMA) played a key role in preparing ER composites with a double cross-linking structure, where DCP initiated polymerization of ZDMA, and grafted ZDMA onto polymer molecular chains and cross-linked rubber molecular chains. Meanwhile, ZDMA combined with rubber macromolecules to build ionic cross-linking bonds in composites under the action of DCP and reinforced the ER composites. The result showed that the coexistence of these two cross-linking networks provide a sufficient restoring force for deformation of shape memory composites. The addition of ZDMA not only improved the mechanical properties of materials, but also significantly enhanced shape memory performance of composites. In particular, Eucommia rubber composites exhibited outstanding mechanical properties and shape memory performance when DCP content was 0.2 phr.
Development and Characterization of Cornstarch-Based Bioplastics Packaging Film Using a Combination of Different Plasticizers
Authors: Abotbina Walid , Sapuan S. M. , Sultan M. T. H. , Alkbir M. F. M. , Ilyas R. A.
Published: October 2021

This work aims to develop cornstarch (CS) based films using fructose (F), glycerol (G), and their combination (FG) as plasticizers with different ratios for food packaging applications. The findings showed that F-plasticized film had the lowest moisture content, highest crystallinity among all films, and exhibited the highest tensile strength and thermostability. In contrast, G-plasticized films showed the lowest density and water absorption with less crystallinity compared to the control and the other plasticized film. In addition, SEM results indicated that FG-plasticized films had a relatively smoother and more coherent surface among the tested films. The findings have also shown that varying the concentration of the plasticizers significantly affected the different properties of the plasticized films. Therefore, the selection of a suitable plasticizer at an appropriate concentration may significantly optimize film properties to promote the utilization of CS films for food packaging applications.
Chitin as a Sorbent Superior to Other Biopolymers: Features and Applications in Environmental Research, Energy Conversion, and Understanding Evolution of Animals
Authors: Blind Felix , Fränzle Stefan
Published: October 2021

Chitin is an effective sorbent which can be used in environmental monitoring, beyond obvious applications in withholding metal-containing pollutants from wastewater- or nuclear fuel reprocessing flows, since background levels in (purified) chitin are very low except for a few metals (Fe, Cu, Al, Ti, and Zn). Since retention of Mx+ and their complexes on chitin depend on an oxidation state, and to a lesser extent the presence of possible ligands or co-ligands, partition between chitin samples exposed to sediment and those exposed to water can be changed by environmental factors such as local biota producing or absorbing/metabolizing effective ligands such as citrate or oxalate and by changes of redox potential. Thermodynamics are studied via log P, using calibration functions log P vs. 1/r or log P vs. Σσ (sum of Hammett parameters of ligand donor groups) for di- and trivalent elements not involved in biochemical activity (not even indirectly) and thus measuring “deviations” from expected values. These “deviations” can be due to input as a pollutant, biochemical use of certain elements, precipitation or (bio-induced reduction of SO42− or CO2) dissolution of solids in sediment. Biochemical processes which occur deep in sediment can be detected due to this effect. Data from grafted chitin (saturation within ≤ 10 min) and from outer surfaces of arthropods caught at the same site do agree well. Log P is more telling than total amounts retrieved. Future applications of these features of chitin are outlined.
Potential Use of Papaya Waste as a Fuel for Bioelectricity Generation
Authors: Rojas-Flores Segundo , Pérez-Delgado Orlando , Nazario-Naveda Renny , Rojales-Alfaro Henry , Benites Santiago M. , De La Cruz-Noriega Magaly , Otiniano Nélida Milly
Published: October 2021

Papaya (Carica papaya) waste cause significant commercial and environmental damage, mainly due to the economic losses and foul odours they emit when decomposing. Therefore, this work provides an innovative way to generate electricity for the benefit of society and companies dedicated to the import and export of this fruit. Microbial fuel cells are a technology that allows electricity generation. These cells were produced with low-cost materials using zinc and copper electrodes; while a 150 mL polymethylmethacrylate tube was used as a substrate collection chamber (papaya waste). Maximum values of 0.736 ± 0.204 V and 5.57 ± 0.45 mA were generated, while pH values increased from 3.848 to 8.227 ± 0.35 and Brix decreased slowly from the first day. The maximum power density value was 878.38 mW/cm2 at a current density of 7.245 A/cm2 at a maximum voltage of 1072.77 mV. The bacteria were identified with an identity percentage of 99.32% for Achromobacter xylosoxidans species, 99.93% for Acinetobacter bereziniae, and 100.00% for Stenotrophomonas maltophilia. This research gives a new way for the use of papaya waste for bioelectricity generation.
Robust Detection of Minute Faults in Uncertain Systems Using Energy Activity
Authors: Singh Manarshhjot , Gehin Anne-Lise , Ould-Boaumama Belkacem
Published: October 2021

Fault detection is one of the key steps in Fault Detection and Isolation (FDI) and, therefore, critical for subsequent prognosis or implementation of Fault Tolerant Control (FTC). It is, therefore, advisable to utilize detection algorithms which are quick and can detect the smallest faults. Model-based detection methods satisfy both these criteria and should be preferred. However, a big limitation for model-based methods is that they require the accurate value of the component parameters, which is difficult to obtain in real situations. This limits the accuracy of model-based methods. This paper proposes a new method for fault detection using Energy Activity (EA) which can detect minute levels of fault in systems with high component uncertainty. Different forms of EA are developed for use as an FDI metric. The proposed forms are simulated using a two-tank system under various types of faults. The results are compared with each other and with the traditional model-based FDI method using Analytical Redundancy Relations (ARRs). The simulations are performed considering model uncertainties to check the inherent performance of the methods. From initial simulations, it is established that the integral form of EA is most suited for fault detection. The integral for if EA is then tested using a real two-tank system considering both the model and measurement uncertainties.
A Small-Scale Study on Removal of Heavy Metals from Contaminated Water Using Water Hyacinth
Authors: Huynh An The , Chen Yi-Ching , Tran Bich Ngoc Thi
Published: October 2021

The aim of this research was to determine whether water hyacinth can be used to remove heavy metals, such as cadmium, arsenic, lead, zinc, and copper, from industrial wastewater. Investigations of the pollution removal or prevention potential of aquatic macrophytes, such as heavy metal bio-indicators in aquatic habitats, can prove to be advanced field studies. Water hyacinth is one of the aquatic plant species that has been effectively utilized for the treatment of wastewater. It is extremely effective in removing stains, suspended solids, BOD, organic matter, and heavy metals. This research focused on the use of water hyacinth to treat wastewater from heavy metals. Water hyacinths can grow in sewage, absorbing and digesting contaminants and transforming sewage effluents into comparatively clean water in the process. As a result, the plants have the potential to be used as natural water purification systems at a fraction of the cost of a standard sewage treatment facility. The experiment was performed using healthy, young, and acclimatized water hyacinths. Containment water with a cadmium concentration of 0.5 mg/L, arsenic concentration of 0.5 mg/L, lead concentration of 2 mg/L, zinc concentration of 5 mg/L, and copper concentration of 5 mg/L was added to five different polyethylene pots with 100 g of water hyacinth in each pot. After 30 days, the removal efficiency for heavy metals (Cd, As, Pb, Zn, and Cu) reached 59–92%, and the results were within the permitted limits according to the National Technical Regulation on Industrial Wastewater in Vietnam. Based on this information, it is possible to deduce that water hyacinth can be utilized to remove cadmium, arsenic, lead, zinc, and copper from industrial wastewater effluents efficiently.
Novel Binding Partners for CCT and PhLP1 Suggest a Common Folding Mechanism for WD40 Proteins with a 7-Bladed Beta-Propeller Structure
Authors: Mak Wai Shun , Tsang Tsz Ming , Chan Tsz Yin , Lukov Georgi L.
Published: October 2021

This study investigates whether selected WD40 proteins with a 7-bladed β-propeller structure, similar to that of the β subunit of the G protein heterotrimer, interact with the cytosolic chaperonin CCT and its known binding partner, PhLP1. Previous studies have shown that CCT is required for the folding of the Gβ subunit and other WD40 proteins. The role of PhLP1 in the folding of Gβ has also been established, but it is unknown if PhLP1 assists in the folding of other Gβ-like proteins. The binding of three Gβ-like proteins, TBL2, MLST8 and CDC20, to CCT and PhLP1, was demonstrated in this study. Co-immunoprecipitation assays identified one novel binding partner for CCT and three new interactors for PhLP1. All three of the studied proteins interact with CCT and PhLP1, suggesting that these proteins may have a folding machinery in common with that of Gβ and that the well-established Gβ folding mechanism may have significantly broader biological implications than previously thought. These findings contribute to continuous efforts to determine common traits and unique differences in the folding mechanism of the WD40 β-propeller protein family, and the role PhLP1 has in this process.
Tutorial on the Use of the regsem Package in R
Authors: Li Xiaobei , Jacobucci Ross , Ammerman Brooke A.
Published: October 2021

Sparse estimation through regularization is gaining popularity in psychological research. Such techniques penalize the complexity of the model and could perform variable/path selection in an automatic way, and thus are particularly useful in models that have small parameter-to-sample-size ratios. This paper gives a detailed tutorial of the R package regsem, which implements regularization for structural equation models. Example R code is also provided to highlight the key arguments of implementing regularized structural equation models in this package. The tutorial ends by discussing remedies of some known drawbacks of a popular type of regularization, computational methods supported by the package that can improve the selection result, and some other practical issues such as dealing with missing data and categorical variables.
An Application of Quantum Logic to Experimental Behavioral Science
Authors: Narens Louis
Published: October 2021

In 1933, Kolmogorov synthesized the basic concepts of probability that were in general use at the time into concepts and deductions from a simple set of axioms that said probability was a σ-additive function from a boolean algebra of events into [0, 1]. In 1932, von Neumann realized that the use of probability in quantum mechanics required a different concept that he formulated as a σ-additive function from the closed subspaces of a Hilbert space onto [0,1]. In 1935, Birkhoff & von Neumann replaced Hilbert space with an algebraic generalization. Today, a slight modification of the Birkhoff-von Neumann generalization is called “quantum logic”. A central problem in the philosophy of probability is the justification of the definition of probability used in a given application. This is usually done by arguing for the rationality of that approach to the situation under consideration. A version of the Dutch book argument given by de Finetti in 1972 is often used to justify the Kolmogorov theory, especially in scientific applications. As von Neumann in 1955 noted, and his criticisms still hold, there is no acceptable foundation for quantum logic. While it is not argued here that a rational approach has been carried out for quantum physics, it is argued that (1) for many important situations found in behavioral science that quantum probability theory is a reasonable choice, and (2) that it has an arguably rational foundation to certain areas of behavioral science, for example, the behavioral paradigm of Between Subjects experiments.
Impacts of Syngas Composition on Anaerobic Fermentation
Authors: Benevenuti Carolina , Amaral Priscilla , Ferreira Tatiana , Seidl Peter
Published: October 2021

Energy consumption places growing demands on modern lifestyles, which have direct impacts on the world’s natural environment. To attain the levels of sustainability required to avoid further consequences of changes in the climate, alternatives for sustainable production not only of energy but also materials and chemicals must be pursued. In this respect, syngas fermentation has recently attracted much attention, particularly from industries responsible for high levels of greenhouse gas emissions. Syngas can be obtained by thermochemical conversion of biomass, animal waste, coal, municipal solid wastes and other carbonaceous materials, and its composition depends on biomass properties and gasification conditions. It is defined as a gaseous mixture of CO and H2 but, depending on those parameters, it can also contain CO2, CH4 and secondary components, such as tar, oxygen and nitrogenous compounds. Even so, raw syngas can be used by anaerobic bacteria to produce biofuels (ethanol, butanol, etc.) and biochemicals (acetic acid, butyric acid, etc.). This review updates recent work on the influence of biomass properties and gasification parameters on syngas composition and details the influence of these secondary components and CO/H2 molar ratio on microbial metabolism and product formation. Moreover, the main challenges, opportunities and current developments in syngas fermentation are highlighted in this review.
Adverse Outcome in Non-Severe COVID-19: Potential Diagnostic Coagulation Tests
Authors: Cacciola Rossella , Gentilini Cacciola Elio , Vecchio Veronica , Cacciola Emma
Published: October 2021

COVID-19-associated coagulopathy (CAC) identifies the coagulation changes in coronavirus disease 2019 (COVID-19) and is responsible for thrombosis. CAC has been studied in critical and severe stage COVID-19 disease through tests including the D-Dimer (DD), prothrombin time (PT), thromboplastin partial time (PTT), platelet count, fibrinogen (Fib), and platelet factor 4 (PF4) tests. However, these tests have some limitations. The aim of this study was to identify more accurate warning tests for early recognition of CAC and to prevent its deterioration to disseminated intravascular coagulation (DIC). First, we measured Interleukin-1α (IL-1α) and IL-8, and tissue factor pathway inhibitor (TFPI) as inflammation and endothelial damage markers, respectively. Second, we measured thrombin antithrombin complex (TAT), β-Thromboglobulin (β-TG), and thromboelastometric parameters including clotting time (CT), clot formation time (CFT), clot firmness (MCF), and clot lysis at 30 min (LY-30), as markers of coagulation and platelet activation. This study included 100 non-severe patients with COVID-19 that developed pulmonary embolism (PE) compared to 80 healthy patients. IL-1α and IL-8, and TFPI were higher as well as TAT and β-TG and thromboelastometric parameters, indicating hypercoagulability. If confirmed in other studies, these results could help in predicting the deterioration of non-severe COVID-19 disease, thereby reducing hospitalizations and health costs.
A Simulation Study of a Planar Cable-Driven Parallel Robot to Transport Supplies for Patients with Contagious Diseases in Health Care Centers
Authors: Carpio Marco , Saltaren Roque , Viola Julio , García Cecilia , Guerra Juan , Cely Juan , Calderón Cristian
Published: October 2021

Currently, a large number of investigations are being carried out in the area of robotics focused on proposing solutions in the field of health, and many of them have directed their efforts on issues related to the health emergency due to COVID-19. Considering that one of the ways to reduce the risk of contagion is by avoiding contact and closeness between people when exchanging supplies such as food, medicine, clothing, etc., this work proposes the use of a planar cable-driven parallel robot for the transport of supplies in hospitals whose room distribution has planar architecture. The robot acts in accordance with a procedure proposed for each task to be carried out, which includes the process of disinfection (based on Ultraviolet-C light) of the supplies transported inside the robot’s end effector. The study presents a design proposal for the geometry of the planar cable-driven parallel robots and its end effector, as well as the software simulations that allow evaluating the robot’s movement trajectories and the responses of the position control system based on Fuzzy-PID controllers.
Wood–Leaf Classification of Tree Point Cloud Based on Intensity and Geometric Information
Authors: Sun Jingqian , Wang Pei , Gao Zhiyong , Liu Zichu , Li Yaxin , Gan Xiaozheng , Liu Zhongnan
Published: October 2021

Terrestrial laser scanning (TLS) can obtain tree point clouds with high precision and high density. The efficient classification of wood points and leaf points is essential for the study of tree structural parameters and ecological characteristics. Using both intensity and geometric information, we present an automated wood–leaf classification with a three-step classification and wood point verification. The tree point cloud was classified into wood points and leaf points using intensity threshold, neighborhood density and voxelization successively, and was then verified. Twenty-four willow trees were scanned using the RIEGL VZ-400 scanner. Our results were compared with the manual classification results. To evaluate the classification accuracy, three indicators were introduced into the experiment: overall accuracy (OA), Kappa coefficient (Kappa), and Matthews correlation coefficient (MCC). The ranges of OA, Kappa, and MCC of our results were from 0.9167 to 0.9872, 0.7276 to 0.9191, and 0.7544 to 0.9211, respectively. The average values of OA, Kappa, and MCC were 0.9550, 0.8547, and 0.8627, respectively. The time costs of our method and another were also recorded to evaluate the efficiency. The average processing time was 1.4 s per million points for our method. The results show that our method represents a potential wood–leaf classification technique with the characteristics of automation, high speed, and good accuracy.
Response of Mangrove Carbon Fluxes to Drought Stress Detected by Photochemical Reflectance Index
Authors: Lu Yaqing , Zhu Xudong
Published: October 2021

The photochemical reflectance index (PRI) has been often used as a physiology-based remote sensing indicator of ecosystem carbon fluxes. However, the assessments of PRI in tracking long-term carbon fluxes with climatic anomalies in mangroves are very limited. In this study, four-year (2017–2020) continuous time series measurements from tower-based eddy covariance and spectral systems in a subtropical mangrove were used to explore the ability of PRI in tracking the response of mangrove carbon fluxes to climate fluctuations and drought stress. The results showed that the temporal dynamics of daily PRI and carbon fluxes shared similar variation patterns over the study period, experiencing simultaneously decreasing trends under drought stress. Compared with the first three years, annual mean values of NEE in 2020 decreased by 10.7% and PRI decreased by 29.0%, correspondingly. PRI and carbon fluxes were significantly correlated across diurnal, seasonal, and annual time scales with better fitness under drought stress. Dark-state PRI (PRI0), the constitutive component of PRI variation due to seasonally changing pigment pool size, showed similar temporal variation as PRI in response to drought stress, while delta PRI (ΔPRI), the facultative component of PRI variation due to diurnal xanthophyll cycle, showed no response to drought stress. This study confirms the ability of PRI to track temporal dynamics of mangrove carbon fluxes on both short-term and long-term scales, with the temporal variation of PRI largely affected by the long-term constitutive pigment pool size. This study highlights the potential of PRI to serve as an early and readily detectable indicator to track the response of the mangrove carbon cycle to climatic anomalies such as drought stress.
An Accurate Doppler Parameters Calculation Method of Geosynchronous SAR Considering Real-Time Zero-Doppler Centroid Control
Authors: Chang Faguang , Yu Chunrui , Li Dexin , Ji Yifei , Dong Zhen
Published: October 2021

The zero-Doppler centroid control in geosynchronous synthetic aperture radar (GEO SAR) is beneficial to reduce the imaging complexity (reduces range-azimuth coupling in received data), which can be realized by adjusting the radar line of sight (RLS). In order to maintain the zero-Doppler centroid throughout the whole orbit of the GEO SAR satellite, the RLS needs to be adjusted in real-time. Due to the ultra-long synthetic aperture time of GEO SAR, the RLS variation during the synthetic aperture time cannot be neglected. However, in the previous related papers, the real-time variation of RLS during the synthetic aperture time was not taken into account in the calculation of Doppler parameters, which are closely related to the RLS, resulting in inaccurate calculation of Doppler parameters. Considering this issue, an accurate Doppler model (the model of relative motion between satellite and ground target) of GEO SAR is proposed in this paper for the accurate calculation of Doppler parameters (Doppler centroid and Doppler bandwidth and other parameters). Finally, simulation experiments are designed to confirm the effectiveness and necessity of the proposed model. The results indicate that the RLS variation during the synthetic aperture time has a considerable effect on Doppler parameters performance of the GEO SAR, and refers to a more stable azimuth resolution performance (the resolution is kept near a relatively stable value at most positions of the elliptical orbit) compared with the case that does not consider the real-time zero-Doppler centroid control.
Convolutional Neural Network for Pansharpening with Spatial Structure Enhancement Operator
Authors: Huang Weiwei , Zhang Yan , Zhang Jianwei , Zheng Yuhui
Published: October 2021

Pansharpening aims to fuse the abundant spectral information of multispectral (MS) images and the spatial details of panchromatic (PAN) images, yielding a high-spatial-resolution MS (HRMS) image. Traditional methods only focus on the linear model, ignoring the fact that degradation process is a nonlinear inverse problem. Due to convolutional neural networks (CNNs) having an extraordinary effect in overcoming the shortcomings of traditional linear models, they have been adapted for pansharpening in the past few years. However, most existing CNN-based methods cannot take full advantage of the structural information of images. To address this problem, a new pansharpening method combining a spatial structure enhancement operator with a CNN architecture is employed in this study. The proposed method uses the Sobel operator as an edge-detection operator to extract abundant high-frequency information from the input PAN and MS images, hence obtaining the abundant spatial features of the images. Moreover, we utilize the CNN to acquire the spatial feature maps, preserving the information in both the spatial and spectral domains. Simulated experiments and real-data experiments demonstrated that our method had excellent performance in both quantitative and visual evaluation.
The Influence of Frequency Bands and Brain Region on ECoG-Based BMI Learning Performance
Authors: Jung Wongyu , Lim Seokbeen , Kwak Youngjong , Sim Jeongeun , Park Jinsick , Jang Dongpyo
Published: October 2021

Numerous brain–machine interface (BMI) studies have shown that various frequency bands (alpha, beta, and gamma bands) can be utilized in BMI experiments and modulated as neural information for machine control after several BMI learning trial sessions. In addition to frequency range as a neural feature, various areas of the brain, such as the motor cortex or parietal cortex, have been selected as BMI target brain regions. However, although the selection of target frequency and brain region appears to be crucial in obtaining optimal BMI performance, the direct comparison of BMI learning performance as it relates to various brain regions and frequency bands has not been examined in detail. In this study, ECoG-based BMI learning performances were compared using alpha, beta, and gamma bands, respectively, in a single rodent model. Brain area dependence of learning performance was also evaluated in the frontal cortex, the motor cortex, and the parietal cortex. The findings indicated that BMI learning performance was best in the case of the gamma frequency band and worst in the alpha band (one-way ANOVA, F = 4.41, p < 0.05). In brain area dependence experiments, better BMI learning performance appears to be shown in the primary motor cortex (one-way ANOVA, F = 4.36, p < 0.05). In the frontal cortex, two out of four animals failed to learn the feeding tube control even after a maximum of 10 sessions. In conclusion, the findings reported in this study suggest that the selection of target frequency and brain region should be carefully considered when planning BMI protocols and for performing optimized BMI.
Indoor Carrier Phase Positioning Technology Based on OFDM System
Authors: Zhang Zhenyu , Kang Shaoli , Zhang Xiang
Published: October 2021

Carrier phase measurement is a ranging technique that uses the receiver to determine the phase difference between the received signal and the transmitted signal. Carrier phase ranging has a high resolution; thus, it is an important research direction for high precision positioning. It is widely used in global navigation satellite systems (GNSS) systems but is not yet commonly used inwireless orthogonal frequency division multiplex (OFDM) systems. Applying carrier phase technology to OFDM systems can significantly improve positioning accuracy. Like GNSS carrier phase positioning, using the OFDM carrier phase for positioning has the following two problems. First, multipath and non-line-of-sight (NLOS) propagation have severe effects on carrier phase measurements. Secondly, ambiguity resolution is also a primary issue in the carrier phase positioning. This paper presents a ranging scheme based on the carrier phase in a multipath environment. Moreover, an algorithm based on the extended Kalman filter (EKF) is developed for fast integer ambiguity resolution and NLOS error mitigation. The simulation results show that the EKF algorithm proposed in this paper solves the integer ambiguity quickly. Further, the high-resolution carrier phase measurements combined with the accurately estimated integer ambiguity lead to less than 30-centimeter positioning error for 90% of the terminals. In conclusion, the presented methods gain excellent performance, even when NLOS error occur.
Theoretical and Numerical Analysis of Active Switching for Narrow-Band Thermal Emission with Graphene Ribbon Metasurface
Authors: Yada Kyohei , Shimojo Takashi , Okada Hideyuki , Sakurai Atsushi
Published: October 2021

Components smaller than the wavelength of electromagnetic waves are called meta-atoms. Thermal emission can be controlled by an artificial structure in which these meta-atoms are arranged on the surface. This artificial structure is called a metasurface, and its optical properties are determined by the materials and shapes of the meta-atoms. However, optical devices may require active control of thermal emission. In the present study, we theoretically and numerically analyze a wavelength-selective emitter using a graphene ribbon metasurface. The graphene ribbon metasurface consists of a graphene ribbon array, potassium bromide thin film, and silver substrate. The geometric parameters of the graphene metasurface are determined based on an equivalent circuit model that agrees well with the results of the electromagnetic field analysis (rigorous coupled-wave analysis). The proposed emitter causes impedance matching depending on the conductivity of the graphene ribbon in a very narrow wavelength range. The conductivity of graphene can be actively controlled by the gate voltage. Therefore, the proposed emitters may realize near-perfect emission with a high quality factor and active controllable switching for various wavelengths. In addition, the quality factor can be changed by adjusting the electron mobility of graphene. The proposed emitter can be used for optical devices such as thermophotovoltaic systems and biosensing.
In-Network Data Aggregation for Ad Hoc Clustered Cognitive Radio Wireless Sensor Network
Authors: Mortada Mohamad Rida , Nasser Abbass , Mansour Ali , Yao Koffi-Clément
Published: October 2021

In cognitive radio wireless sensor networks (CRSN), the nodes act as secondary users. Therefore, they can access a channel whenever its primary user (PU) is absent. Thus, the nodes are assumed to be equipped with a spectrum sensing (SS) module to monitor the PU activity. In this manuscript, we focus on a clustered CRSN, where the cluster head (CH) performs SS, gathers the data, and sends it toward a central base station by adopting an ad hoc topology with in-network data aggregation (IDA) capability. In such networks, when the number of clusters increases, the consumed energy by the data transmission decreases, while the total consumed energy of SS increases, since more CHs need to perform SS before transmitting. The effect of IDA on CRSN performance is investigated in this manuscript. To select the best number of clusters, a study is derived aiming to extend the network lifespan, taking the SS requirements, the IDA effect, and the energy consumed by both SS and transmission into consideration. Furthermore, the collision rate between primary and secondary transmissions and the network latency are theoretically derived. Numerical results corroborate the efficiency of IDA to extend the network lifespan and minimize both the collision rate and the network latency.
Multi-User Scheduling for 6G V2X Ultra-Massive MIMO System
Authors: He Shibiao , Du Jieru , Liao Yong
Published: October 2021

6G vehicle-to-everything (V2X) communication will be combined with vehicle automatic driving technology and play an important role in automatic driving. However, in 6G V2X systems, vehicle users have the characteristics of high-speed movement. Therefore, how to provide stable and reliable wireless link quality and improve channel gain has become a problem that must be solved. To solve this problem, a new multi-user scheduling algorithm based on block diagonalization (BD) precoding for 6G ultra-massive multiple-input multiple-output (MIMO) systems is proposed in this paper. The algorithm takes advantage of the sensitive nature of BD precoding to channel correlation, uses the Pearson coefficient after matrix vectorization to measure the channel correlation between users, defines the scheduling factor to measure the channel quality according to the user noise enhancement factor, and jointly considers the influence of the correlation between user channels and channel quality, ensuring the selection of high-quality channels while minimizing channel correlation. Simulation results show that compared with the multi-user scheduling algorithm based on subspace correlation, condition number, and geometric angle, the proposed algorithm can obtain higher user channel gain, effectively reduce the system bit error rate, and can be applied to 6G V2X communication.
IDS for Industrial Applications: A Federated Learning Approach with Active Personalization
Authors: Kelli Vasiliki , Argyriou Vasileios , Lagkas Thomas , Fragulis George , Grigoriou Elisavet , Sarigiannidis Panagiotis
Published: October 2021

Internet of Things (IoT) is a concept adopted in nearly every aspect of human life, leading to an explosive utilization of intelligent devices. Notably, such solutions are especially integrated in the industrial sector, to allow the remote monitoring and control of critical infrastructure. Such global integration of IoT solutions has led to an expanded attack surface against IoT-enabled infrastructures. Artificial intelligence and machine learning have demonstrated their ability to resolve issues that would have been impossible or difficult to address otherwise; thus, such solutions are closely associated with securing IoT. Classical collaborative and distributed machine learning approaches are known to compromise sensitive information. In our paper, we demonstrate the creation of a network flow-based Intrusion Detection System (IDS) aiming to protecting critical infrastructures, stemming from the pairing of two machine learning techniques, namely, federated learning and active learning. The former is utilized for privately training models in federation, while the latter is a semi-supervised approach applied for global model adaptation to each of the participant’s traffic. Experimental results indicate that global models perform significantly better for each participant, when locally personalized with just a few active learning queries. Specifically, we demonstrate how the accuracy increase can reach 7.07% in only 10 queries.
Collision Avoidance Strategy for the Autocrane
Authors: Wang Dong , Liu Baochang , Shen Jian , Chen Li , Zhu Lydia
Published: October 2021

The collision between the boom of the autocrane and the obstacle may cause serious equipment damages or casualties. With the development of 6G technology, data between multiple autocranes could be shared in real time, which makes it possible to finely control the autocranes. In order to avoid collision accidents, a collision avoidance strategy is proposed in this paper. This strategy focuses on the evaluation of the collision urgency and different evaluation methods are designed to match the three basic exercise modes of the boom. Based on the collision urgency, the control strategy is then put forward to ensure the boom’s safety in every collision risk level. Additionally, two special cases are also considered to guarantee that all parts of the boom, except for the end, will not hit the obstacle. Lastly, a semi-physical testing platform is established to test the performance of the proposed collision avoidance strategy.
Self-Excited Acoustical Measurement System for Rock Mass Stress Mapping
Authors: Lalik Krzysztof , Dominik Ireneusz , Skrzypkowski Krzysztof , Korzeniowski Waldemar , Zagórski Krzysztof
Published: October 2021

This paper presents the results of a preliminary study of a self-excited acoustical system (SAS) for nondestructive testing (NDT). The SAS system was used for mine excavation stresses examination. The principle of operation of the SAS system based on the elastoacoustical effect is presented. A numerical analysis of the excavation was carried out considering the stress factor. An equivalent model based on a two-degree-of-freedom system with a delay has been developed. This model allowed to determine the relation which relates the frequency of the self-excited system to the stress level in the studied ceiling section. This relationship is defined by the elastoacoustic coefficient. The test details for anchorages in laboratory conditions and Wieliczka Salt Mine were presented. This research details of a method for creating actual stress maps in the ceiling of a mine excavation. The results confirmed the possibility of using the new measurement system to monitor the state of stresses in the rock mass.
Sustainable Public Procurement in Large Infrastructure Projects—Policy Implementation for Carbon Emission Reductions
Authors: Lingegård Sofia , Olsson Johanna Alkan , Kadefors Anna , Uppenberg Stefan
Published: October 2021

The infrastructure construction sector is a significant source of carbon emissions, and more stringent procurement requirements are central to meeting reduction targets in this demand-led and project-based industry. This paper aims to analyze the implementation of international policies for reducing carbon emissions in infrastructure construction, focusing on the interaction between policy ambitions and procurement practices. Based on case studies of large projects and their contexts in five countries worldwide: Australia, the Netherlands, Sweden, the UK, and the US, a cross-country comparison is performed of how policies and practices for carbon reduction develop across multiple implementation levels. Three levels are included in the analysis: policy, industry, and project level. We identify the projects as either drivers of policy goals, frontrunners in industry-level development processes, or translators of national policy. These roles, and the associated pathways for carbon emission reduction, are context-specific and depend on the policy ambitions at the national or regional level, the maturity of the supplier market, and, often, on the strategies of individual champions at the project level. Long-term learning processes, both within and between the various levels, are essential for advancing carbon reduction.
Development of a Cyberinfrastructure for Assessment of the Lower Rio Grande Valley North and Central Watersheds Characteristics
Authors: Navarro Linda , Mahmoud Ahmed , Ernest Andrew , Oubeidillah Abdoul , Johnstone Jessica , Chavez Ivan Rene Santos , Fuller Christopher
Published: October 2021

Lower Laguna Madre (LLM) is designated as an impaired waterway for high concentrations of bacteria and low dissolved oxygen. The main freshwater sources to the LLM flow from the North and Central waterways which are composed of three main waterways: Hidalgo/Willacy Main Drain (HWMD), Raymondville Drain (RVD), and International Boundary & Water Commission North Floodway (IBWCNF) that are not fully characterized. The objective of this study is to perform a watershed characterization to determine the potential pollution sources of each watershed. The watershed characterization was achieved by developing a cyberinfrastructure, and it collects a wide inventory of data to identify which one of the three waterways has a major contribution to the LLM. Cyberinfrastructure development using the Geographic Information System (GIS) database helped to comprehend the major characteristics of each area contributing to the watershed supported by the analysis of the data collected. The watershed characterization process started with delineating the boundaries of each watershed. Then, geospatial and non-geospatial data were added to the cyberinfrastructure from numerous sources including point and nonpoint sources of pollution. Results showed that HWMD and IBWCNF watersheds were found to have a higher contribution to the water impairments to the LLM. HWMD and IBWCNF comprise the potential major sources of water quality impairments such as cultivated crops, urbanized areas, on-site sewage facilities, colonias, and wastewater effluents.
Tourist and Viral Mobilities Intertwined: Clustering COVID-19-Driven Travel Behaviour of Rural Tourists in South Tyrol, Italy
Authors: Scuttari Anna , Ferraretto Valeria , Stawinoga Agnieszka Elzbieta , Walder Maximilian
Published: October 2021

Travel patterns have dramatically changed during the COVID-19 pandemic. Tourism has been both a vector and a victim of the disease. This paper explores the pandemic’s impact on rural tourism, using the theoretical framework of the “mobilities turn” to investigate issues of corporeal and communicative travel found between the first and second waves of the COVID-19 pandemic. A sample of 874 guests visiting the Italian region of South Tyrol, where rural tourism is the norm, identified different patterns of physical travel and approaches to collecting on-site information on COVID-19. Results from a principal component analysis (PCA) and a cluster analysis highlighted at least two different approaches from visitors to the region: the first is more cautious, mostly practiced by domestic tourists, with limited mobility on-site, coupled with a need for information; the second is instead a more adventurous approach, with higher on-site mobility, more use of sustainable forms of transport and less interest in data evidence on COVID-19. Implications for rural tourism and its future are discussed. The hypothesis of an inverse relationship between corporeal and communicative travel needs further exploration in future research.
Pricing and Coordination Strategies of Dual Channels Considering Consumers’ Channel Preferences
Authors: Wang Rufeng , Wang Siqi , Yan Shuli
Published: October 2021

With the rapid development of electronic commerce, consumers can freely buy the same product from a manufacturers’ Internet channel or a resellers’ physical channel. Based on the consumers’ channel preferences, this article classifies consumers into three types and investigates the price decision in a dual-channel supply chain using a Stackelberg game, which assumes that the manufacturer, as the game leader, first sets the wholesale price, then the reseller decides the retail price, according to the wholesale price. Furthermore, some numerical experiments are developed to investigate the impact of consumer acceptance, the degree of customer loyalty, and the proportion of identical shoppers on prices and profits. The results show that whether both the retail price and the wholesale price rise or fall depends on a combination of the cost of the physical channel and the Internet shopper’s acceptance of the Internet channel. The reseller’s profit is always lower than the manufacturer’s profit. The reseller’s profit is lower and the manufacturer’s profit is higher, compared with that of a traditional single channel supply chain. The numerical experiments showed that when an Internet shopper’s acceptance of an Internet channel is lower, the wholesale price and retail price in the dual channels will increase with an increase of the degree of customer loyalty (the proportion of identical shoppers). The reseller’s profit (the manufacturer’s profit) will reduce (rise) with the augmentation of the Internet shopper’s acceptance of an Internet channel. Finally, we design a revenue-sharing contract that can coordinate the supply chain and implement a win–win strategy for all partners. This work makes some contributions to the research area of coordination in dual-channel supply chains.
Design of Combined Auction Model for Emission Rights of International Forestry Carbon Sequestration and Other Pollutants Based on SMRA
Authors: Guo Hongpeng , Lv Zhihao , Hua Junyi , Yuan Hongxu , Yu Qingyu
Published: October 2021

In this paper, the combined transactions for emission rights of international carbon sequestration and other pollutants in forestry have been taken as the research object, and the Simultaneous Multiple Round Auction (SMRA) theory has been used to design a new model for the current auction transactions. In this paper, the feasibility and application of the SMRA model of reach object are studied by the methods of simulation experiment, model analysis, and analogical analysis, and the promotion of this model is discussed. The results show that the new auction model designed in this paper fills in the blank of the combined auction of international forestry carbon sequestration and other pollutant emission rights. It successfully eliminates the winners’ curse and the losses of the sellers. Meanwhile, it provides a new way of resolving ecological deficits problems, achieving the ultimate goal of an overall reduction in carbon and pollution emission. Moreover, it’s beneficial in resolving the structural contradictions between ecological purification and pollutants discharge, hence maximizing the benefits for all the stakeholders. Finally, it is suggested that the SMRA should be adopted in the international trading of emission rights of international carbon sequestration and other pollutants to promote the emission reduction of greenhouse gases and pollutants.