bluuebunny/crossref_metadata_2025 huggingface dataset:
The Electrical Conductivity and Mechanical Properties of Monolayer and Multilayer Nanofibre Membranes from Different Fillers: Calculated Based on Parallel Circuit
Authors: Wang Lijian , Li Chuanhe , Zhang Jishu , Wang Chunhong , Zuo Qi , He Wenting , Lin Ligang
Published: November 2022

Advanced research on improving the performance of conductive polymer composites is essential to exploring their potential in various applications. Thus, in this study, the electrical conductivity of multilayer nanofibre membranes composed of polyvinyl alcohol (PVA) with different electroconductive fillers content including zinc oxide (ZnO), multiwalled carbon nanotubes (MWNTs), and Ferro ferric oxide (Fe3O4), were produced via electrospinning. The tensile property and electrical conductivity of monolayer membranes were explored. The results showed that PVA with 2 wt.% MWNTs nanofibre membrane has the best conductivity (1.0 × 10−5 S/cm) and tensile strength (29.36 MPa) compared with other fillers. Meanwhile, the combination of multilayer membrane ZnO/Fe3O4/Fe3O4/MWNTs/ZnO showed the highest conductivity (1.39 × 10−5 S/cm). The parallel circuit and calculation of parallel resistance were attempted to demonstrate the conductive mechanism of multilayer membranes, which can predict the conductivity of other multilayer films. The production of multilayer composites that enhance electrical conductivity and improve conductive predictions was successfully explored.
Recent Advances in the Enzymatic Synthesis of Polyester
Authors: Wang Hong , Li Hongpeng , Lee Chee Keong , Mat Nanyan Noreen Suliani , Tay Guan Seng
Published: November 2022

Polyester is a kind of polymer composed of ester bond-linked polybasic acids and polyol. This type of polymer has a wide range of applications in various industries, such as automotive, furniture, coatings, packaging, and biomedical. The traditional process of synthesizing polyester mainly uses metal catalyst polymerization under high-temperature. This condition may have problems with metal residue and undesired side reactions. As an alternative, enzyme-catalyzed polymerization is evolving rapidly due to the metal-free residue, satisfactory biocompatibility, and mild reaction conditions. This article presented the reaction modes of enzyme-catalyzed ring-opening polymerization and enzyme-catalyzed polycondensation and their combinations, respectively. In addition, the article also summarized how lipase-catalyzed the polymerization of polyester, which includes (i) the distinctive features of lipase, (ii) the lipase-catalyzed polymerization and its mechanism, and (iii) the lipase stability under organic solvent and high-temperature conditions. In addition, this article also focused on the advantages and disadvantages of enzyme-catalyzed polyester synthesis under different solvent systems, including organic solvent systems, solvent-free systems, and green solvent systems. The challenges of enzyme optimization and process equipment innovation for further industrialization of enzyme-catalyzed polyester synthesis were also discussed in this article.
Poly(3-hexylthiophene)-Based Organic Thin-Film Transistors with Virgin Graphene Oxide as an Interfacial Layer
Authors: Tarekegn Eyob N. , Seyedi Mastooreh , Luzinov Igor , Harrell William R.
Published: November 2022

We fabricated and characterized poly(3-hexylthiophene-2, 5-diyl) (P3HT)-based Organic thin-film transistors (OTFTs) containing an interfacial layer made from virgin Graphene Oxide (GO). Previously chemically modified GO and reduced GO (RGO) were used to modify OTFT interfaces. However, to our knowledge, there are no published reports where virgin GO was employed for this purpose. For the sake of comparison, OTFTs without modification were also manufactured. The structure of the devices was based on the Bottom Gate Bottom Contact (BGBC) OTFT. We show that the presence of the GO monolayer on the surface of the OTFT’s SiO2 dielectric and Au electrode surface noticeably improves their performance. Namely, the drain current and the field-effect mobility of OTFTs are considerably increased by modifying the interfaces with the virgin GO deposition. It is suggested that the observed enhancement is connected to a decrease in the contact resistance of GO-covered Au electrodes and the particular structure of the P3HT layer on the dielectric surface. Namely, we found a specific morphology of the organic semiconductor P3HT layer, where larger interconnecting polymer grains are formed on the surface of the GO-modified SiO2. It is proposed that this specific morphology is formed due to the increased mobility of the P3HT segments near the solid boundary, which was confirmed via Differential Scanning Calorimetry measurements.
Study on Debinding and Sintering Processes for Ceramics Fabricated Using Digital Light Processing (DLP) 3D Printing
Authors: Sim Jae-Ho , Koo Bon-Keup , Jung Minhun , Kim Dong-Soo
Published: November 2022

Ceramics have excellent properties such as hardness and thermal and chemical stability. Therefore, researchers have studied the use of 3D printing to produce complex shapes in tools and structural applications. The debinding and sintering processes for ceramic composite materials manufactured using digital light processing (DLP) 3D printing technology were studied. The slurry used for DLP 3D printing requires debinding and sintering, as it contains ceramics and binders. Therefore, the debinding and sintering processes were measured by TG-DSC curves, and the changes in material characteristics were evaluated by setting the debinding holding time (4, 5, and 6 h) and sintering temperature (1100, 1200, and 1300 °C) as parameters. After debinding for 6 h, the density of the ceramic sintered at 1300 °C was 1.36 g/cm2; the linear shrinkage was 22.1%/21.6%/28.5% along the x, y, and z axes, respectively; and the bending strength was 8.58 MPa. As a result of this study, we developed an optimized process for the debinding and sintering of ceramics manufactured through the DLP 3D printing process.
Sortase A Fusion Expression and mIFc2 Co-Expression of Bovine Lactoferricin and Analysis of Its Antibacterial Activity
Authors: Hsu Chao-Yu , Hsieh Chung-Yiu , Yang Cheng-Yao , Chang Yu-Kang , Shih Wen-Ling , Yeh Chuan-Ming , Hu Nien-Jen , Chen Ming-Shan , Nielsen Brent L. , Liu Hung-Jen
Published: November 2022

The coding region for the sortase A (SrtA) of Staphylococcus aureus was fused at the N-terminus of LfcinB. The SrtA-LfcinB fusion protein in E. coli C43(DE3) was expressed with the expected sizes of 21 kDa and 38 kDa by pET21b-SrtA-LfcinB and pET32-1SrtA-LfcinB constructs, respectively. Increased levels of the TrxA-His-SrtA-SrtA-LfcinB fusion protein were detected by the pET32-3SrtA-LfcinB construct having three expression cassettes. LfcinB is released from the expressed SrtA-LfcinB protein by SrtA self-cleavage which is induced in the presence of Ca2+. The antibacterial activity was detected after SrtA-mediated cleavage of LfcinB. Furthermore, to reduce the antimicrobial peptide toxicity to the E. coli host, the human interferon-γ (hIFN-γ) sequences were mutated into a negatively charged mIFc2 protein (7 kDa), which was co-expressed with LfcinB in an insoluble form. The yield of LfcinB was elevated while changing the gene order of LfcinB and mIFc2 (pET21b-fLfcinB-bmIFc2). Furthermore, increased levels of LfcinB were detected using the pET21b-(fLfcinB-bmIFc2)2 construct. To increase the dissolution rate of inclusion bodies, inclusion bodies treated with different temperatures and pH and resuspended in different volumes of 50 mM Tris-HCl were assayed. Our results reveal that heat-treated LfcinB/mIFc2 inclusion bodies at 90 °C, pH 10, and 16X resuspended volumes have the best resolubilization rate. This work suggests that the mIFc2 co-expression system shows higher efficiency for LfcinB production than the SrtA fusion system. The expressed LfcinB from the mIFc2 co-expression system exhibits excellent broad-spectrum antibacterial activities against thirteen Gram-negative and ten Gram-positive bacteria species with a range of minimum inhibitory concentrations (MIC) between 37–150 ug/mL.
Research on Green Reentrant Hybrid Flow Shop Scheduling Problem Based on Improved Moth-Flame Optimization Algorithm
Authors: Xu Feng , Tang Hongtao , Xun Qining , Lan Hongyi , Liu Xia , Xing Wenfang , Zhu Tianyi , Wang Lei , Pang Shibao
Published: November 2022

To address the green reentrant hybrid flow shop-scheduling problem (GRHFSP), we performed lifecycle assessments for evaluating the comprehensive impact of resources and the environment. An optimization model was established to minimize the maximum completion time and reduce the comprehensive impact of resources and the environment, and an improved moth-flame optimization algorithm was developed. A coding scheme based on the number of reentry layers, stations, and machines was designed, and a hybrid population initialization strategy was developed, according to a situation wherein the same types of nonequivalent parallel machines were used. Two different update strategies were designed for updating the coding methods of processes and machines. The population evolution strategy was adopted to improve the local search ability of the proposed algorithm and the quality of the solution. Through simulation experiments based on different datasets, the effectiveness of the proposed algorithm was verified, and comparative evaluations revealed that the proposed algorithm could solve the GRHFSP more effectively than other well-known algorithms.
Healthcare Waste Management in Nigeria: A Review
Authors: Ezeudu Obiora B. , Ezeudu Tochukwu S. , Ugochukwu Uzochukwu C. , Tenebe Imokhai Theophilus , Ajogu Agbaji P. , Nwadi Uchenna V. , Ajaero Charles C.
Published: November 2022

Healthcare waste management has become an important aspect of medical care delivery globally. This is simply because of its hazardous and infectious components that have greater potential for adverse health and environmental impacts. As such, certain guidelines and procedures have been developed by international aid agencies and conventions to guide national governments and local administrations in formulating policies and practices for effective healthcare waste management. In this work, we reviewed the existing literature to appraise the status of healthcare waste management practices in Nigeria. This included generation, segregation, collection, storage, transportation, treatment, and disposal. The current work further reviewed the other essential elements of healthcare waste management, such as policy landscapes, training, awareness, and waste characterization, and discusses challenges and opportunities for effective healthcare waste management in Nigeria. Among the challenges are poor funding, inadequate training, ineffective legislature, and absence of data. However, there are available low-cost technologies that are suitable for the treatment of waste in a developing country like Nigeria. This technology variant offers an opportunity for a circular economy as it can simultaneously achieve energy production, waste management, and other socioeconomic advantages.
Vine Canopy Reconstruction and Assessment with Terrestrial Lidar and Aerial Imaging
Authors: Petrović Igor , Sečnik Matej , Hočevar Marko , Berk Peter
Published: November 2022

For successful dosing of plant protection products, the characteristics of the vine canopies should be known, based on which the spray amount should be dosed. In the field experiment, we compared two optical experimental methods, terrestrial lidar and aerial photogrammetry, with manual defoliation of some selected vines. Like those of other authors, our results show that both terrestrial lidar and aerial photogrammetry were able to represent the canopy well with correlation coefficients around 0.9 between the measured variables and the number of leaves. We found that in the case of aerial photogrammetry, significantly more points were found in the point cloud, but this depended on the choice of the ground sampling distance. Our results show that in the case of aerial UAS photogrammetry, subdividing the vine canopy segments to 5 × 5 cm gives the best representation of the volume of vine canopies.
Assimilation of Water Vapor Retrieved from Radar Reflectivity Data through the Bayesian Method
Authors: Liu Junjian , Fan Shuiyong , Ali Mamtimin , Li Huoqing , Zhang Hailiang , Wang Yu , Aihaiti Ailiyaer
Published: November 2022

This work describes the implementation of an updated radar reflectivity assimilation scheme with the three-dimensional variational (3D-Var) system of Weather Research and Forecast (WRF). The updated scheme, instead of the original scheme assuming the relative humidity to a fixed value where radar reflectivity is higher than a threshold, assimilates pseudo water vapor retrieved by the Bayesian method, which would be consistent with clouds/precipitations provided by the model in theory. To verify the effect of the updated scheme to the improvement of precipitation simulation, a convective case in Wenquan County and the continuous monthly simulation with contrasting experiments in Xinjiang were performed. The test of single reflectivity observation demonstrates that the water vapor retrieved by the Bayesian method is consistent with the meteorological situation around. In the convective case, both the updated and original scheme results show that the assimilation of pseudo water vapor can adjust to the environmental conditions of water vapor and temperature. This can improve the hourly precipitation forecast skill more than the contrasting experiment, which was designed to only assimilate conventional observations and radar radial velocity data. In the continuous monthly experiments, the updated scheme reveals that the analysis of water vapor is more reasonable, and obtains a better precipitation forecast skill for 6 h accumulated precipitation than the contrasting experiments.
Comprehensive Analysis of PERSIANN Products in Studying the Precipitation Variations over Luzon
Authors: Hsu Jie , Huang Wan-Ru , Liu Pin-Yi
Published: November 2022

This study evaluated the capability of satellite precipitation estimates from five products derived from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (including PERSIANN, PERSIANN-CCS, PERSIANN-CDR, PERSIANN-CCS-CDR, and PDIR-Now) to represent precipitation characteristics over Luzon. The analyses focused on monthly and daily timescales from 2003–2015 and adopted surface observations from the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) platform as the evaluation base. Among the five satellite precipitation products (SPPs), PERSIANN-CDR was observed to possess a better ability to qualitatively and quantitatively estimate spatiotemporal variations of precipitation over Luzon for the majority of the examined features with the exception of the extreme precipitation events, for which PERSIANN-CCS-CDR is superior to the other SPPs. These results highlight the usefulness of the addition of the cloud patch approach to PERSIANN-CDR to produce PERSIANN-CCS-CDR to depict the characteristics of extreme precipitation events over Luzon. A similar advantage of adopting the cloud patch approach in producing extreme precipitation estimates was also revealed from the comparison of PERSIANN, PERSIANN-CCS, and PDIR-Now. Our analyses also highlighted that all PERSIANN-series exhibit improved skills in regard to detecting precipitation characteristics over west Luzon compared to that over east Luzon. To overcome this weakness, we suggest that an adjustment in the cloud patch approach (e.g., using different cloud temperature thresholds or different brightness temperature and precipitation rate relationships) over east Luzon may be helpful.
Repeated (4D) Marine Geophysical Surveys as a Tool for Studying the Coastal Environment and Ground-Truthing Remote-Sensing Observations and Modeling
Authors: Stanghellini Giuseppe , Bidini Camilla , Romagnoli Claudia , Archetti Renata , Ponti Massimo , Turicchia Eva , Del Bianco Fabrizio , Mercorella Alessandra , Polonia Alina , Giorgetti Giulia , Gallerani Andrea , Gasperini Luca
Published: November 2022

Sandy beaches and the nearshore environment are dynamic coastal systems characterized by sediment mobilization driven by alternating stormy and mild wave conditions. However, this natural behavior of beaches can be altered by coastal defense structures. Repeated surveys carried out with autonomous surface vehicles (ASVs) may represent an interesting tool for studying nearshore dynamics and testing the effects of mitigation strategies against erosion. We present a one-year experiment involving repeated stratigraphic and morpho-bathymetric surveys of a nearshore environment prone to coastal erosion along the Emilia-Romagna coast (NE Italy), the Lido di Dante beach, carried out between October 2020 and December 2021 using an ASV. Seafloor and subseafloor “snapshots” collected at different time intervals enabled us to delineate the seasonal variability and shed light on key controlling variables, which could be used to integrate and calibrate remote-sensing observations and modeling. The results demonstrated that repeated surveys could be successfully employed for monitoring coastal areas and represent a promising tool for studying coastal dynamics on a medium/short (years/months) timescale.
SATNet: A Spatial Attention Based Network for Hyperspectral Image Classification
Authors: Hong Qingqing , Zhong Xinyi , Chen Weitong , Zhang Zhenghua , Li Bin , Sun Hao , Yang Tianbao , Tan Changwei
Published: November 2022

In order to categorize feature classes by capturing subtle differences, hyperspectral images (HSIs) have been extensively used due to the rich spectral-spatial information. The 3D convolution-based neural networks (3DCNNs) have been widely used in HSI classification because of their powerful feature extraction capability. However, the 3DCNN-based HSI classification approach could only extract local features, and the feature maps it produces include a lot of spatial information redundancy, which lowers the classification accuracy. To solve the above problems, we proposed a spatial attention network (SATNet) by combining 3D OctConv and ViT. Firstly, 3D OctConv divided the feature maps into high-frequency maps and low-frequency maps to reduce spatial information redundancy. Secondly, the ViT model was used to obtain global features and effectively combine local-global features for classification. To verify the effectiveness of the method in the paper, a comparison with various mainstream methods on three publicly available datasets was performed, and the results showed the superiority of the proposed method in terms of classification evaluation performance.
Quality Control of CyGNSS Reflectivity for Robust Spatiotemporal Detection of Tropical Wetlands
Authors: Arai Hironori , Zribi Mehrez , Oyoshi Kei , Dassas Karin , Huc Mireille , Sobue Shinichi , Toan Thuy Le
Published: November 2022

The aim of this study was to develop a robust methodology for evaluating the spatiotemporal dynamics of the inundation status in tropical wetlands with the currently available Global Navigation Satellite System-Reflectometry (GNSS-R) data by proposing a new quality control technique called the “precision index”. The methodology was applied over the Mekong Delta, one of the most important rice-production systems comprising aquaculture areas and natural wetlands (e.g., mangrove forests, peatlands). Cyclone Global Navigation Satellite System (CyGNSS) constellation data (August 2018–December 2021) were used to evaluate the spatiotemporal dynamics of the reflectivity Γ over the delta. First, the reflectivity Γ, shape and size of each specular footprint and the precision index were calibrated at each specular point and reprojected to a 0.0045° resolution (approximately equivalent to 500 m) grid at a daily temporal resolution (Lv. 2 product); then, the results were obtained considering bias-causing factors (e.g., the velocity/effective scattering area/incidence angle). The Lv. 2 product was temporally integrated every 15 days with a Kalman smoother (+/− 14 days temporal localization with Gaussian kernel: 1σ = 5 days). By applying the smoother, the regional-annual dynamics over the delta could be clearly visualized. The behaviors of the GNSS-R reflectivity and the Advanced Land Observing Satellite-2 Phased-Array type L-band Synthetic Aperture Radar-2 quadruple polarimetric scatter signals were compared and found to be nonlinearly correlated due to the influence of the incidence angle and the effective scattering area.
UAV-LiDAR and RGB Imagery Reveal Large Intraspecific Variation in Tree-Level Morphometric Traits across Different Pine Species Evaluated in Common Gardens
Authors: Lombardi Erica , Rodríguez-Puerta Francisco , Santini Filippo , Chambel Maria Regina , Climent José , Resco de Dios Víctor , Voltas Jordi
Published: November 2022

Remote sensing is increasingly used in forest inventories. However, its application to assess genetic variation in forest trees is still rare, particularly in conifers. Here we evaluate the potential of LiDAR and RGB imagery obtained through unmanned aerial vehicles (UAVs) as high-throughput phenotyping tools for the characterization of tree growth and crown structure in two representative Mediterranean pine species. To this end, we investigated the suitability of these tools to evaluate intraspecific differentiation in a wide array of morphometric traits for Pinus nigra (European black pine) and Pinus halepensis (Aleppo pine). Morphometric traits related to crown architecture and volume, primary growth, and biomass were retrieved at the tree level in two genetic trials located in Central Spain and compared with ground-truth data. Both UAV-based methods were then tested for their accuracy to detect genotypic differentiation among black pine and Aleppo pine populations and their subspecies (black pine) or ecotypes (Aleppo pine). The possible relation between intraspecific variation of morphometric traits and life-history strategies of populations was also tested by correlating traits to climate factors at origin of populations. Finally, we investigated which traits distinguished better among black pine subspecies or Aleppo pine ecotypes. Overall, the results demonstrate the usefulness of UAV-based LiDAR and RGB records to disclose tree architectural intraspecific differences in pine species potentially related to adaptive divergence among populations. In particular, three LiDAR-derived traits related to crown volume, crown architecture, and main trunk—or, alternatively, the latter (RGB-derived) two traits—discriminated the most among black pine subspecies. In turn, Aleppo pine ecotypes were partly distinguishable by using two LiDAR-derived traits related to crown architecture and crown volume, or three RGB-derived traits related to tree biomass and main trunk. Remote-sensing-derived-traits related to main trunk, tree biomass, crown architecture, and crown volume were associated with environmental characteristics at the origin of populations of black pine and Aleppo pine, thus hinting at divergent environmental stress-induced local adaptation to drought, wildfire, and snowfall in both species.
Responses of Soil Freeze–Thaw Processes to Climate on the Tibetan Plateau from 1980 to 2016
Authors: Fu Chunwei , Hu Zeyong , Yang Yaoxian , Deng Mingshan , Yu Haipeng , Lu Shan , Wu Di , Fan Weiwei
Published: November 2022

Soil freeze–thaw processes are remarkable features of the land surface across the Tibetan Plateau (TP). Soil moisture and temperature fluctuate during the freeze–thaw cycle, affecting the soil water and energy exchange between the land and atmosphere. This study investigates variations in the soil temperature, humidity, and freeze–thaw state and their responses to air temperature and precipitation on the TP from 1981 to 2016. Regional simulations of the TP using Community Land Model version 4.5 demonstrate that the climate of the TP has become warmer and wetter over the past 37 years, with increases in both regional average temperature and precipitation. Using empirical orthogonal function analysis and the Mann–Kendall trend test of air temperature, we show that 1980–1998 was relatively cold, and 1999–2016 was relatively warm. Soil temperature and moisture in most areas of the TP were affected by air temperature and precipitation, and both showed an upward trend during the past 37 years. Overall, from 1981 to 2016, the freezing date of the TP has become delayed, the thawing date has been hastened, and the duration of the freeze–thaw state has shortened. The surface soil freezes and thaws first, and these processes pervade deeper soil with the passage of time; freeze–thaw processes have an obvious hysteresis. Precipitation and air temperature had marked effects on the freeze–thaw processes. Higher air temperatures delay the freezing date, hasten the thawing date, and shorten the freeze–thaw period. Areas with the highest precipitation saw late soil freeze, early thaw, and the shortest freeze–thaw duration. Areas with less vegetation froze earlier and thawed later. The freeze–thaw duration increased in the northwest of the plateau and decreased on the rest of the plateau. This article informs research on frozen soil change in the context of global warming.
Micro-Motion Parameter Extraction of Multi-Scattering-Point Target Based on Vortex Electromagnetic Wave Radar
Authors: Bu Lijun , Zhu Yongzhong , Chen Yijun , Song Xiaoou , Yang Yufei , Zang Yadan
Published: November 2022

In addition to traditional linear Doppler shift, the angular Doppler shift in vortex electromagnetic wave (VEMW) radar systems carrying orbital angular momentum (OAM) can provide more accurate target identification micro-motion parameters, especially the detailed features perpendicular to the radar line-of-sight (LOS) direction. In this paper, a micro-motion feature extraction method for a spinning target with multiple scattering points based on VEMW radar is proposed. First, a multi-scattering-point spinning target detection model using vortex radar is established, and the mathematical mechanism of echo signal flash shift in time-frequency (TF) domain is deduced. Then, linear Doppler shift is eliminated by interference processing with opposite dual-mode VEMW. Subsequently, the shift in TF flicker is focused on the reference zero frequency by the iterative phase compensation method, and the number of scattering points is estimated according to the focusing effect. After this, through the constructed compensation phase, the angular Doppler shift is separated, then the angular velocity, rotation radiusand initial phase of the target are estimated. Theoretical and simulation results verify the effectiveness of the proposed method, and more accurate rotation parameters can be obtained in the case of multiple scattering points using the VEMW radar system.
A Novel Method for Detecting and Delineating Coppice Trees in UAV Images to Monitor Tree Decline
Authors: Ghasemi Marziye , Latifi Hooman , Pourhashemi Mehdi
Published: November 2022

Monitoring tree decline in arid and semi-arid zones requires methods that can provide up-to-date and accurate information on the health status of the trees at single-tree and sample plot levels. Unmanned Aerial Vehicles (UAVs) are considered as cost-effective and efficient tools to study tree structure and health at small scale, on which detecting and delineating tree crowns is the first step to extracting varied subsequent information. However, one of the major challenges in broadleaved tree cover is still detecting and delineating tree crowns in images. The frequent dominance of coppice structure in degraded semi-arid vegetation exacerbates this problem. Here, we present a new method based on edge detection for delineating tree crowns based on the features of oak trees in semi-arid coppice structures. The decline severity in individual stands can be analyzed by extracting relevant information such as texture from the crown area. Although the method presented in this study is not fully automated, it returned high performances including an F-score = 0.91. Associating the texture indices calculated in the canopy area with the phenotypic decline index suggested higher correlations of the GLCM texture indices with tree decline at the tree level and hence a high potential to be used for subsequent remote-sensing-assisted tree decline studies.
Feedback Regimes of LFI Sensors: Experimental Investigations
Authors: Bertling Karl , Qi Xiaoqiong , Taimre Thomas , Lim Yah Leng , Rakić Aleksandar D.
Published: November 2022

In this article, we revisit the concept of optical feedback regimes in diode lasers and explore each regime experimentally from a somewhat unconventional point of view by relating the feedback regimes to the laser bias current and its optical feedback level. The results enable setting the operating conditions of the diode laser in different applications requiring operation in different feedback regimes. We experimentally explored and theoretically supported this relationship from the standard Lang and Kobayashi rate equation model for a laser diode under optical feedback. All five regimes were explored for two major types of laser diodes: inplane lasers and vertical-cavity surface emitting lasers. For both lasers, we mapped the self-mixing strength vs. drive current and feedback level, observed the differences in the shape of the self-mixing fringes between the two laser architectures and a general simulation, and monitored other parameters of the lasers with changing optical feedback.
Treatment of Extended Kalman Filter Implementations for the Gyroless Star Tracker
Authors: Critchley-Marrows Joshua J. R. , Wu Xiaofeng , Cairns Iver H.
Published: November 2022

The literature since Apollo contains exhaustive material on attitude filtering, usually treating the problem of two sensors, a combination of state measuring and inertial devices. More recently, it has become popular for a sole attitude determination device to be considered. This is especially the case for a star tracker given its unbiased stellar measurement and recent improvements in optical sensor performance. The state device indirectly estimates the attitude rate using a known dynamic model. In estimation theory, two main attitude filtering approaches are classified, the additive and the multiplicative. Each refers to the nature of the quaternion update in the filter. In this article, these two techniques are implemented for the case of a sole star tracker, using simulated and real night sky image data. Both sets of results are presented and compared with each other, with a baseline established through a basic linear least square estimate. The state approach is more accurate and precise for measuring angular velocity than using the error-based filter. However, no discernible difference is observed between each technique for determining pointing. These results are important not only for sole device attitude determination systems, but also for space situational awareness object localisation, where attitude and rate estimate accuracy are highly important.
Acoustic and Thermal Characterization of Therapeutic Ultrasonic Langevin Transducers under Continuous- and Pulsed Wave Excitations
Authors: Kim Jinhyuk , Lee Jungwoo
Published: November 2022

We previously conducted an empirical study on Langevin type transducers in medical use by examining the heat effect on porcine tissue. For maximum acoustic output, the transducer was activated by a continuous sinusoidal wave. In this work, pulsed waves with various duty factors were applied to our transducer model in order to examine their effect on functionality. Acoustic power, electro-acoustic conversion efficiency, acoustic pressure, thermal effect on porcine tissue and bovine muscle, and heat generation in the transducer were investigated under various input conditions. For example, the results of applying a continuous wave of 200 VPP and a pulse wave of 70% duty factor with the same amplitude to the transducer were compared. It was found that continuous waves generated 9.79 W of acoustic power, 6.40% energy efficiency, and 24.84 kPa acoustic pressure. In pulsed excitation, the corresponding values were 9.04 W, 8.44%, and 24.7 kPa, respectively. The maximum temperature increases in bovine muscle are reported to be 83.0 °C and 89.5 °C for each waveform, whereas these values were 102.5 °C and 84.5 °C in fatty porcine tissue. Moreover, the heat generation around the transducer was monitored under continuous and pulsed modes and was found to be 51.3 °C and 50.4 °C. This shows that pulsed excitation gives rise to less thermal influence on the transducer. As a result, it is demonstrated that a transducer triggered by pulsed waves improves the energy efficiency and provides sufficient thermal impact on biological tissues by selecting proper electrical excitation types.
Sensor Location Matters When Estimating Player Workload for Baseball Pitching
Authors: Agresta Cristine , Freehill Michael T. , Zendler Jessica , Giblin Georgia , Cain Stephen
Published: November 2022

Estimating external workload in baseball pitchers is important for training and rehabilitation. Since current methods of estimating workload through pitch counts and rest days have only been marginally successful, clubs are looking for more sophisticated methods to quantify the mechanical loads experienced by pitchers. Among these are the use of wearable systems. While wearables offer a promising solution, there remains a lack of standards or guidelines for how best to employ these devices. As a result, sensor location and workload calculation methods vary from system to system. This can influence workload estimates and blur their interpretation and utility when making decisions about training or returning to sport. The primary purpose of this study was to determine the extent to which sensor location influences workload estimate. A secondary purpose was to compare estimates using different workload calculations. Acceleration data from three sensor locations—trunk, throwing upper arm, and throwing forearm—were collected from ten collegiate pitchers as they threw a series of pitches during a single bullpen session. The effect of sensor location and pitch type was assessed in relation to four different workload estimates. Sensor location significantly influenced workload estimates. Workload estimates calculated from the forearm sensor were significantly different across pitch types. Whole-body workload measured from a trunk-mounted sensor may not adequately reflect the mechanical loads experienced at throwing arm segments. A sensor on the forearm was the most sensitive to differences in workloads across pitch types, regardless of the calculation method.
Fabrication and Characterization of Novel Silk Fiber-Optic SERS Sensor with Uniform Assembly of Gold Nanoparticles
Authors: Kang Taeyoung , Cho Yongjun , Yuk Kyeong Min , Yu Chan Yeong , Choi Seung Ho , Byun Kyung Min
Published: November 2022

Biocompatible optical fibers and waveguides are gaining attention as promising platforms for implantable biophotonic devices. Recently, the distinct properties of silk fibroin were extensively explored because of its unique advantages, including flexibility, process compatibility, long-term biosafety, and controllable biodegradability for in vitro and in vivo biomedical applications. In this study, we developed a novel silk fiber for a sensitive optical sensor based on surface-enhanced Raman spectroscopy (SERS). In contrast to conventional plasmonic nanostructures, which employ expensive and time-consuming fabrication processes, gold nanoparticles were uniformly patterned on the top surface of the fiber employing a simple and cost-effective convective self-assembly technique. The fabricated silk fiber-optic SERS probe presented a good performance in terms of detection limit, sensitivity, and linearity. In particular, the uniform pattern of gold nanoparticles contributed to a highly linear sensing feature compared to the commercial multi-mode fiber sample with an irregular and aggregated distribution of gold nanoparticles. Through further optimization, silk-based fiber-optic probes can function as useful tools for highly sensitive, cost-effective, and easily tailored biophotonic platforms, thereby offering new capabilities for future implantable SERS devices.
Demonstration of Spatial Modulation Using a Novel Active Transmitter Detection Scheme with Signal Space Diversity in Optical Wireless Communications
Authors: Song Tingting , Nirmalathas Ampalavanapillai , Lim Christina
Published: November 2022

Line-of-sight (LOS) indoor optical wireless communications (OWC) enable a high data rate transmission while potentially suffering from optical channel obstructions. Additional LOS links using diversity techniques can tackle the received signal performance degradation, where channel gains often differ in multiple LOS channels. In this paper, a novel active transmitter detection scheme in spatial modulation (SM) is proposed to be incorporated with signal space diversity (SSD) technique to enable an increased OWC system throughput with an improved bit-error-rate (BER). This transmitter detection scheme is composed of a signal pre-distortion technique at the transmitter and a power-based statistical detection method at the receiver, which can address the problem of power-based transmitter detection in SM using carrierless amplitude and phase modulation waveforms with numerous signal levels. Experimental results show that, with the proposed transmitter detection scheme, SSD can be effectively provided with ~0.61 dB signal-to-noise-ratio (SNR) improvement. Additionally, an improved data rate ~7.5 Gbit/s is expected due to effective transmitter detection in SM. The SSD performances at different constellation rotation angles and under different channel gain distributions are also investigated, respectively. The proposed scheme provides a practical solution to implement power-based SM and thus aids the SSD realization for improving system performance.
Flat Multi-Wavelength Brillouin Erbium-Doped Fiber Laser Based on a Sagnac Loop for High-Sensitivity Sensor
Authors: Chen Liang , He Jian , Liu Yi
Published: November 2022

We have demonstrated the use of a flat multi-wavelength Brillouin erbium-doped fiber laser (MWBEFL) based on a Sagnac loop with an unpumped erbium-doped fiber (Un-EDF) as a high-sensitivity sensor. A Sagnac loop with a Un-EDF was used as power equalizer to achieve multi-wavelength power flatness by adjusting the birefringence beat length properly. In the experiments, the best result obtained in terms of Brillouin Stokes lines and output power flatness was ±0.315 dB and the optical signal-to-noise ratio (OSNR) was 18.97 dB within a 33 nm bandwidth range from 1532.0 nm to 1565.0 nm. The flatness of the 33 nm bandwidth range varied from ±0.315 dB to ±1.38 dB and the average OSNR was about 17.51 dB. The peak power values of Brillouin Stokes lines observed under different wavelengths were extremely close and their range of fluctuation was about ±0.37 dB. These experimental results were close to our previous experimental values obtained using a passive Sagnac loop with a Un-EDF. The flat range covering almost the entire C-band has broad application prospects in high-sensitivity distributed optical fiber sensing and wavelength-division multiplexing.
Vehicular Environment Identification Based on Channel State Information and Deep Learning
Authors: Ribouh Soheyb , Sadli Rahmad , Elhillali Yassin , Rivenq Atika , Hadid Abdenour
Published: November 2022

This paper presents a novel vehicular environment identification approach based on deep learning. It consists of exploiting the vehicular wireless channel characteristics in the form of Channel State Information (CSI) in the receiver side of a connected vehicle in order to identify the environment type in which the vehicle is driving, without any need to implement specific sensors such as cameras or radars. We consider environment identification as a classification problem, and propose a new convolutional neural network (CNN) architecture to deal with it. The estimated CSI is used as the input feature to train the model. To perform the identification process, the model is targeted for implementation in an autonomous vehicle connected to a vehicular network (VN). The proposed model is extensively evaluated, showing that it can reliably recognize the surrounding environment with high accuracy (96.48%). Our model is compared to related approaches and state-of-the-art classification architectures. The experiments show that our proposed model yields favorable performance compared to all other considered methods.
A Privacy-Preserving, Two-Party, Secure Computation Mechanism for Consensus-Based Peer-to-Peer Energy Trading in the Smart Grid
Authors: Li Zhihu , Xu Haiqing , Zhai Feng , Zhao Bing , Xu Meng , Guo Zhenwei
Published: November 2022

Consumers in electricity markets are becoming more proactive because of the rapid development of demand–response management and distributed energy resources, which boost the transformation of peer-to-peer (P2P) energy-trading mechanisms. However, in the P2P negotiation process, it is a challenging task to prevent private information from being attacked by malicious agents. In this paper, we propose a privacy-preserving, two-party, secure computation mechanism for consensus-based P2P energy trading. First, a novel P2P negotiation mechanism for energy trading is proposed based on the consensus + innovation (C + I) method and the power transfer distribution factor (PTDF), and this mechanism can simultaneously maximize social welfare and maintain physical network constraints. In addition, the C + I method only requires a minimum set of information to be exchanged. Then, we analyze the strategy of malicious neighboring agents colluding to attack in order to steal private information. To defend against this attack, we propose a two-party, secure computation mechanism in order to realize safe negotiation between each pair of prosumers based on Paillier homomorphic encryption (HE), a smart contract (SC), and zero-knowledge proof (ZKP). The energy price is updated in a safe way without leaking any private information. Finally, we simulate the functionality of the privacy-preserving mechanism in terms of convergence performance, computational efficiency, scalability, and SC operations.
SGGformer: Shifted Graph Convolutional Graph-Transformer for Traffic Prediction
Authors: Pu Shilin , Chu Liang , Hu Jincheng , Li Shibo , Li Jihao , Sun Wen
Published: November 2022

Accurate traffic prediction is significant in intelligent cities’ safe and stable development. However, due to the complex spatiotemporal correlation of traffic flow data, establishing an accurate traffic prediction model is still challenging. Aiming to meet the challenge, this paper proposes SGGformer, an advanced traffic grade prediction model which combines a shifted window operation, a multi-channel graph convolution network, and a graph Transformer network. Firstly, the shifted window operation is used for coarsening the time series data, thus, the computational complexity can be reduced. Then, a multi-channel graph convolutional network is adopted to capture and aggregate the spatial correlations of the roads in multiple dimensions. Finally, the improved graph Transformer based on the advanced Transformer model is proposed to extract the long-term temporal correlation of traffic data effectively. The prediction performance is evaluated by using actual traffic datasets, and the test results show that the SGGformer proposed exceeds the state-of-the-art baseline.
Test-Retest Reliability of Acoustic Emission Sensing of the Knee during Physical Tasks
Authors: Khokhlova Liudmila , Komaris Dimitrios-Sokratis , Tedesco Salvatore , O’Flynn Brendan
Published: November 2022

Acoustic emission (AE) sensing is an increasingly researched topic in the context of orthopedics and has a potentially high diagnostic value in the non-invasive assessment of joint disorders, such as osteoarthritis and implant loosening. However, a high level of reliability associated with the technology is necessary to make it appropriate for use as a clinical tool. This paper presents a test-retest and intrasession reliability evaluation of AE measurements of the knee during physical tasks: cycling, knee lifts and single-leg squats. Three sessions, each involving eight healthy volunteers were conducted. For the cycling activity, ICCs ranged from 0.538 to 0.901, while the knee lifts and single-leg squats showed poor reliability (ICC < 0.5). Intrasession ICCs ranged from 0.903 to 0.984 for cycling and from 0.600 to 0.901 for the other tasks. The results of this study show that movement consistency across multiple recordings and minimizing the influence of motion artifacts are essential for higher test reliability. It was shown that motion artifact resistant sensor mounting and the use of baseline movements to assess sensor attachment can improve the sensing reliability of AE techniques. Moreover, constrained movements, specifically cycling, show better inter- and intrasession reliability than unconstrained exercises.
Flat Photonic Crystal Fiber Plasmonic Sensor for Simultaneous Measurement of Temperature and Refractive Index with High Sensitivity
Authors: An Wei , Li Chao , Wang Dong , Chen Wenya , Guo Shijing , Gao Song , Zhang Chunwei
Published: November 2022

A compact temperature-refractive index (RI) flat photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR) is presented in this paper. Sensing of temperature and RI takes place in the x- and y- polarization, respectively, to avoid the sensing crossover, eliminating the need for matrix calculation. Simultaneous detection of dual parameters can be implemented by monitoring the loss spectrum of core modes in two polarizations. Compared with the reported multi-function sensors, the designed PCF sensor provides higher sensitivities for both RI and temperature detection. A maximum wavelength sensitivity of −5 nm/°C is achieved in the temperature range of −30–40 °C. An excellent optimal wavelength sensitivity of 17,000 nm/RIU is accomplished in the RI range of 1.32–1.41. The best amplitude sensitivity of RI is up to 354.39 RIU−1. The resolution of RI and temperature sensing is 5.88 × 10−6 RIU and 0.02 °C, respectively. The highest value of the figure of merit (FOM) is 216.74 RIU−1. In addition, the flat polishing area of the gold layer reduces the manufacturing difficulty. The proposed sensor has the characteristics of high sensitivity, simple structure, good fabrication repeatability, and flexible operation. It has potential in medical diagnosis, chemical inspection, and many other fields.
An Algorithm with Iteration Uncertainty Eliminate Based on Geomagnetic Fingerprint under Mobile Edge Computing for Indoor Localization
Authors: Li Jie , Sun Liming , Liu Dongpeng , Yu Ruiyun , Wang Xingwei
Published: November 2022

Indoor localization problems are difficult due to that the information, such as WLAN and GPS, cannot achieve enough precision for indoor issues. This paper presents a novel indoor localization algorithm, GeoLoc, with uncertainty eliminate based on fusion of acceleration, angular rate, and magnetic field sensor data. The algorithm can be deployed in edge devices to overcome the problems of insufficient computing resources and long delay caused by high complexity of location calculation. Firstly, the magnetic map is built and magnetic values are matched. Secondly, orientation updating and position selection are iteratively executed using the fusion data, which gradually reduce uncertainty of orientation. Then, we filter the trajectory from a path set. By gradually reducing uncertainty, GeoLoc can bring a high positioning precision and a smooth trajectory. In addition, this method has an advantage in that it does not rely on any infrastructure such as base stations and beacons. It solves the common problems regarding the non-uniqueness of the geomagnetic fingerprint and the deviation of the sensor measurement. The experimental results show that our algorithm achieves an accuracy of less than 2.5 m in indoor environment, and the positioning results are relatively stable. It meets the basic requirements of indoor location-based services (LBSs).