bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular Characterization of Potato Virus Y (PVY) Using High-Throughput Sequencing: Constraints on Full Genome Reconstructions Imposed by Mixed Infection Involving Recombinant PVY Strains
Authors: Glasa Miroslav , Hančinský Richard , Šoltys Katarína , Predajňa Lukáš , Tomašechová Jana , Hauptvogel Pavol , Mrkvová Michaela , Mihálik Daniel , Candresse Thierry
Published: April 2021

In recent years, high throughput sequencing (HTS) has brought new possibilities to the study of the diversity and complexity of plant viromes. Mixed infection of a single plant with several viruses is frequently observed in such studies. We analyzed the virome of 10 tomato and sweet pepper samples from Slovakia, all showing the presence of potato virus Y (PVY) infection. Most datasets allow the determination of the nearly complete sequence of a single-variant PVY genome, belonging to one of the PVY recombinant strains (N-Wi, NTNa, or NTNb). However, in three to-mato samples (T1, T40, and T62) the presence of N-type and O-type sequences spanning the same genome region was documented, indicative of mixed infections involving different PVY strains variants, hampering the automated assembly of PVY genomes present in the sample. The N- and O-type in silico data were further confirmed by specific RT-PCR assays targeting UTR-P1 and NIa genomic parts. Although full genomes could not be de novo assembled directly in this situation, their deep coverage by relatively long paired reads allowed their manual re-assembly using very stringent mapping parameters. These results highlight the complexity of PVY infection of some host plants and the challenges that can be met when trying to precisely identify the PVY isolates involved in mixed infection.
Polymer Nanocomposites for Photocatalytic Degradation and Photoinduced Utilizations of Azo-Dyes
Authors: Wang Emily Z. , Wang Yigui , Xiao Dequan
Published: April 2021

Specially designed polymer nanocomposites can photo-catalytically degrade azo dyes in wastewater and textile effluents, among which TiO2-based nanocomposites are outstanding and extensively explored. Other nanocomposites based on natural polymers (i.e., chitosan and kaolin) and the oxides of Al, Au, B, Bi, Fe, Li, and Zr are commonly used. These nanocomposites have better photocatalytic efficiency than pure TiO2 through two considerations: (i) reducing the hole/electron recombination rate by stabilizing the excited electron in the conducting band, which can be achieved in TiO2-nanocomposites with graphene, graphene oxide, hexagonal boron nitride (h-BN), metal nanoparticles, or doping; (ii) decreasing the band energy of semiconductors by forming nanocomposites between TiO2 and other oxides or conducting polymers. Increasing the absorbance efficiency by forming special nanocomposites also increases photocatalytic performance. The photo-induced isomerization is exploited in biological systems, such as artificial muscles, and in technical fields such as memory storage and liquid crystal display. Heteroaryl azo dyes show remarkable shifts in photo-induced isomerization, which can be applied in biological and technical fields in place of azo dyes. The self-assembly methods can be employed to synthesize azo-dye polymer nanocomposites via three types of interactions: electrostatic interactions, London forces or dipole/dipole interactions between azo dyes, and photo alignments.
Conductive GelMA–Collagen–AgNW Blended Hydrogel for Smart Actuator
Authors: Ha Jang Ho , Lim Jae Hyun , Kim Ji Woon , Cho Hyeon-Yeol , Jo Seok Geun , Lee Seung Hyun , Eom Jae Young , Lee Jong Min , Chung Bong Geun
Published: April 2021

Blended hydrogels play an important role in enhancing the properties (e.g., mechanical properties and conductivity) of hydrogels. In this study, we generated a conductive blended hydrogel, which was achieved by mixing gelatin methacrylate (GelMA) with collagen, and silver nanowire (AgNW). The ratio of GelMA, collagen and AgNW was optimized and was subsequently gelated by ultraviolet light (UV) and heat. The scanning electron microscope (SEM) image of the conductive blended hydrogels showed that collagen and AgNW were present in the GelMA hydrogel. Additionally, rheological analysis indicated that the mechanical properties of the conductive GelMA–collagen–AgNW blended hydrogels improved. Biocompatibility analysis confirmed that the human umbilical vein endothelial cells (HUVECs) encapsulated within the three-dimensional (3D), conductive blended hydrogels were highly viable. Furthermore, we confirmed that the molecule in the conductive blended hydrogel was released by electrical stimuli-mediated structural deformation. Therefore, this conductive GelMA–collagen–AgNW blended hydrogel could be potentially used as a smart actuator for drug delivery applications.
Comparison of the Thermal Properties of Geopolymer and Modified Gypsum
Authors: Prałat Karol , Ciemnicka Justyna , Koper Artur , Buczkowska Katarzyna Ewa , Łoś Piotr
Published: April 2021

The paper presents the results of research concerning the influence of micromaterials on the heat conductivity coefficient λ, specifically heat Cp and thermal diffusivity a of modified gypsum and geopolymer. Microspheres, hydroxyethyl methylcellulose (HEMC) polymer, and aerogel were used as the gypsum’s modifying materials. The study also investigated an alkali potassium-activated methakaolin-based geopolymer with the addition of aluminium dust. During the measurements of thermal parameters, the nonstationary method was chosen, and an Isomet device—which recorded the required physical quantities—was used. When compared to the reference sample, a decrease in the thermal conductivity and diffusivity of the hardened gypsum— and a simultaneous increase in specific heat—was observed with the addition of micromaterials. The geopolymer sample was characterized by the lowest value of thermal conductivity, equal to 0.1141 W/(m·K). It was over 62% lower than the reference sample containing only gypsum. The experimental values of the thermal conductivity of the gypsum samples with the addition of HEMC, aerogel and microspheres were, respectively, over 23%, 6%, and 8% lower than those of the unmodified gypsum samples. The lowest values of thermal conductivity were observed in the case of the gypsum samples modified with polymer; this resulted from the fact that the polymer caused the greatest change in the structure of the gypsum’s composite, which were expressed by the lowest density and highest porosity.
Optimization of Process Parameters for Fabricating Polylactic Acid Filaments Using Design of Experiments Approach
Authors: Kuo Chil-Chyuan , Chen Jia-You , Chang Yuan-Hao
Published: April 2021

The amount of wasted polylactic acid (PLA) is increasing because 3D printing services are an increasingly popular offering in many fields. The PLA is widely employed in the fused deposition modeling (FDM) since it is an environmentally friendly polymer. However, failed prototypes or physical models can generate substantial waste. In this study, the feasibility of recycling PLA waste plastic and re-extruded it into new PLA filaments was investigated. An automatic PLA filament extruder was first developed for fabricating new PLA filaments. This paper also discusses the process, challenges, and benefits of recycling PLA waste plastic in an effort to fabricate new PLA filaments more sustainable. It was found that it was possible to fabricate PLA filament using recycled PLA waste plastic. The production cost is only 60% of the commercially available PLA filament. The tensile strength of the developed PLA filament is approximately 1.1 times that of the commercially available PLA filament. The design of experiments approach was employed to investigate the optimal process parameters for fabricating PLA filaments. The most important control factor affecting the diameter of PLA filament is the barrel temperature, followed by recycled material addition ratio, extrusion speed, and cooling distance. The optimal process parameters for fabricating PLA filament with a diameter of 1.7 mm include the barrel temperature of 184 °C, extrusion speed of 490 mm/min, cooling distance of 57.5 mm, and recycled material addition ratio of 40%.
Development of a Model Based on Physical Mechanisms for the Explanation of Drug Release: Application to Diclofenac Release from Polyurethane Films
Authors: Abbasnezhad Navideh , Kebdani Mohamed , Shirinbayan Mohammadali , Champmartin Stéphane , Tcharkhtchi Abbas , Kouidri Smaine , Bakir Farid
Published: April 2021

In this study, we present a method for prediction of the drug-release profile based on the physical mechanisms that can intervene in drug release from a drug-carrier. The application presented here incorporates the effects of drug concentration and Reynolds number defining the circulating flow in the testing vein. The experimental data used relate to the release of diclofenac from samples of non-degradable polyurethane subjected to static and continuous flow. This case includes simultaneously three mechanisms: burst-release, diffusion and osmotic pressure, identified beforehand here as being able to contribute to the drug liberation. For this purpose, authors coded the Sequential Quadratic Programming Algorithm to solve the problem of non-linear optimization. The experimental data used to develop the mathematical model obtained from release studies carried out in water solution at 37 °C, for three concentrations of diclofenac and two water flow rates. We discuss the contribution of mechanisms and kinetics by considering two aforementioned parameters and, following that, we obtain the specific-model and compare the calculated results with the experimental results for the reserved cases. The results showed that drug percentage mostly affect the burst release, however flow rate has affected the osmotic release. In addition, release kinetics of all the mechanisms have increased by increasing the values of two considered parameters.
Characterization of the Micelle Formed by a Hydrophobically Modified Pullulan in Aqueous Solution: Size Exclusion Chromatography
Authors: Yang Jia , Sato Takahiro
Published: April 2021

Size exclusion chromatography equipped with a multi-angle, light-scattering online detector (SEC-MALS) measurements were carried out on a hydrophobically modified pullulan (PUL-OSA) with degrees of substitution (DS) of 0.14, 0.2, and 0.3 in 0.01 M aqueous NaCl to obtain the degree of polymerization (N0) dependence of the radius of gyration (⟨S2⟩1/2) for PUL-OSA in the aqueous NaCl. The result was consistent with the loose flower necklace model proposed in a previous study, and the increase in the chain size with introducing OSA groups was explained by the backbone stiffness of the loose flower necklace formed by PUL-OSA. For PUL-OSA samples with DS = 0.2 and 0.3, ⟨S2⟩1/2 obtained by SEC-MALS in a high N0 region deviated downward from ⟨S2⟩1/2 expected by the loose flower necklace model. This deviation came from a tiny amount of the aggregating component of PUL-OSA, taking a branched architecture composed of loose flower necklaces. Although the aggregating component of PUL-OSA was also detected by previous small angle X-ray scattering measurements, its conformation was revealed in this study by SEC-MALS.
How Small Molecules Affect the Thermo-Oxidative Aging Mechanism of Polypropylene: A Reactive Molecular Dynamics Study
Authors: Zhang Fan , Cao Yufei , Liu Xuan , Xu Huan , Lu Diannan , Yang Rui
Published: April 2021

Understanding the aging mechanism of polypropylene (PP) is fundamental for the fabrication and application of PP-based materials. In this paper, we present our study in which we first used reactive molecular dynamics (RMD) simulations to explore the thermo-oxidative aging of PP in the presence of acetic acid or acetone. We studied the effects of temperature and oxygen on the aging process and discussed the formation pathways of typical small molecule products (H2, CO, CO2, CH4, C2H4, and C2H6). The effect of two infection agents, acetic acid and acetone, on the aging reaction was analyzed emphatically. The simulation results showed that acetone has a weak impact on accelerating the aging process, while acetic acid has a significant effect, consistent with previous experimental studies. By tracking the simulation trajectories, both acetic acid and acetone produced small active free radicals to further react with other fragment products, thus accelerating the aging process. The first reaction step of acetic acid is often the shedding of the H atom on the hydroxyl group, while the reaction of acetone is often the shedding of the H atom or the methyl. The latter requires higher energy at lower temperatures. This is why the acceleration effect of acetone for the thermo-oxidative aging of PP was not so significant compared to acetic acid in the experimental temperature (383.15 K).
A Review of Fabrication Methods, Properties and Applications of Superhydrophobic Metals
Authors: Ellinas Kosmas , Dimitrakellis Panagiotis , Sarkiris Panagiotis , Gogolides Evangelos
Published: April 2021

Hydrophobicity and superhydrophobicity with self-cleaning properties are well-known characteristics of several natural surfaces, such as the leaves of the sacred lotus plant (Nelumbo nucifera). To achieve a superhydrophobic state, micro- and nanometer scale topography should be realized on a low surface energy material, or a low surface energy coating should be deposited on top of the micro-nano topography if the material is inherently hydrophilic. Tailoring the surface chemistry and topography to control the wetting properties between extreme wetting states enables a palette of functionalities, such as self-cleaning, antifogging, anti-biofouling etc. A variety of surface topographies have been realized in polymers, ceramics, and metals. Metallic surfaces are particularly important in several engineering applications (e.g., naval, aircrafts, buildings, automobile) and their transformation to superhydrophobic can provide additional functionalities, such as corrosion protection, drag reduction, and anti-icing properties. This review paper focuses on the recent advances on superhydrophobic metals and alloys which can be applicable in real life applications and aims to provide an overview of the most promising methods to achieve sustainable superhydrophobicity.
The Maternité Anglaise: A Lasting Legacy of the Friends’ War Victims’ Relief Committee to the People of France during the First World War (1914–1918)
Authors: Palfreeman Linda
Published: April 2021

After the outbreak of war in Europe in 1914, the British government’s call to arms caused a moral and religious dilemma for members of the Religious Society of Friends (Friends or Quakers), whose fundamental principle was (and is) the rejection of war and violence. Many Friends sought means of reconciling their duty to God with their duty to their country, and the prospect of helping to alleviate the suffering of the civilian victims of the fighting provided them with an acceptable alternative. Together with fellow Friend T. Edmund Harvey MP, Dr Hilda Clark set about rallying the support of Friends and sympathisers willing to go out to France to administer humanitarian aid to non-combatants. The committee adopted the name used by the distinguished organisation that had administered relief in the Franco-Prussian War—the Friends’ War Victims’ Relief Committee (FWVRC). Extensive and multifaceted aid work was carried out in much of northern France by the FWVRC’s general relief team. The following essay, however, examines more closely the medical assistance provided under the leadership of Hilda Clark. In particular, it focuses on the maternity hospital created and run by the FWVRC in Châlons-sur-Marne, which became a lasting legacy of the Friends to the people of the Marne.
God and the Playpen: On the Feasibility of Morally Better Worlds
Authors: Chen Cheryl K.
Published: April 2021

According to the free will defense, God cannot create a world with free creatures, and hence a world with moral goodness, without allowing for the possibility of evil. David Lewis points out that any free will defense must address the “playpen problem”: why didn’t God allow creatures the freedom required for moral goodness, while intervening to ensure that all evil-doing is victimless? More recently, James Sterba has revived the playpen problem by arguing that an omnipotent and benevolent God would have intervened to prevent significant and especially horrendous evil. I argue that it is possible, at least, that such divine intervention would have backfired, and that any attempt to create a world that is morally better than this one would have resulted in a world that is morally worse. I conclude that the atheologian should instead attack the free will defense at its roots: either by denying that the predetermination of our actions is incompatible with our freely per-forming them, or by denying that the actual world—a world with both moral good and evil—is more valuable than a world without any freedom at all.
Deep Learning Based Sea Ice Classification with Gaofen-3 Fully Polarimetric SAR Data
Authors: Zhang Tianyu , Yang Ying , Shokr Mohammed , Mi Chunlei , Li Xiao-Ming , Cheng Xiao , Hui Fengming
Published: April 2021

In this paper, the performance of C-band synthetic aperture radar (SAR) Gaofen-3 (GF-3) quad-polarization Stripmap (QPS) data is assessed for classifying late spring and summer sea ice types. The investigation is based on 18 scenes of GF-3 QPS data acquired in the Arctic Ocean in 2017. In this study, floe ice (FI), brash ice (BI) between floes and open water (OW, ice-free area) were classified based on a mini sea ice residual convolutional network, which we call MSI-ResNet. While investigating the optimal patch size for MSI-ResNet, we found that, as the patch size continues to grow, the classification accuracy first increases and then decreases. A patch size of 31 × 31 was found to achieve the best performance. The performance of classification using different polarization combinations from the QPS data was also assessed. The vertical-vertical (VV) polarization input overestimates the FI category while incorrectly identifying most of the BI as FI. The VH polarization produces a synchronous improvement in FI, BI, and OW discrimination, with a higher overall accuracy and kappa coefficient (91.09% and 0.85, respectively) than the VV polarization (83.37% and 0.70, respectively). The combination of VV and vertical-horizontal (VH) polarizations presents a modest precision improvement for BI and OW together with a slight overestimation for FI. With VV, VH, and horizontal-horizontal (HH) polarization data as the inputs, the user’s accuracy improves to 95.12%, 93.42%, and 95.17% for FI, BI, and OW, respectively. The accuracy was assessed against visual interpretation of the sea ice classes in the images using a stratified sampling method. The application of the MSI-ResNet method to data covering the Beaufort Sea and the north of the Severnaya Zemlya archipelago was found to achieve a high overall accuracy (kappa) of 94.62% (±0.92) and 94.23% (±0.90), respectively. This is similar to the classification accuracy obtained in the Fram Strait. From the results of this study, it is shown that the MSI-ResNet method performs better than the classical support vector machine (SVM) classifier for sea ice discrimination. The GF-3 QPS mode data also show more details in discriminating scattered sea ice floes than the coincident Sentinel-1A Extra Wide (EW) swath mode data.
Multi-Epoch and Multi-Imagery (MEMI) Photogrammetric Workflow for Enhanced Change Detection Using Time-Lapse Cameras
Authors: Blanch Xabier , Eltner Anette , Guinau Marta , Abellan Antonio
Published: April 2021

Photogrammetric models have become a standard tool for the study of surfaces, structures and natural elements. As an alternative to Light Detection and Ranging (LiDAR), photogrammetry allows 3D point clouds to be obtained at a much lower cost. This paper presents an enhanced workflow for image-based 3D reconstruction of high-resolution models designed to work with fixed time-lapse camera systems, based on multi-epoch multi-images (MEMI) to exploit redundancy. This workflow is part of a fully automatic working setup that includes all steps: from capturing the images to obtaining clusters from change detection. The workflow is capable of obtaining photogrammetric models with a higher quality than the classic Structure from Motion (SfM) time-lapse photogrammetry workflow. The MEMI workflow reduced the error up to a factor of 2 when compared to the previous approach, allowing for M3C2 standard deviation of 1.5 cm. In terms of absolute accuracy, using LiDAR data as a reference, our proposed method is 20% more accurate than models obtained with the classic workflow. The automation of the method as well as the improvement of the quality of the 3D reconstructed models enables accurate 4D photogrammetric analysis in near-real time.
Spatio-Temporal Changes of Mass Balance in the Ablation Area of the Muz Taw Glacier, Sawir Mountains, from Multi-Temporal Terrestrial Geodetic Surveys
Authors: Xu Chunhai , Li Zhongqin , Wang Feiteng , Mu Jianxin
Published: April 2021

The glaciers in the Sawir Mountains are an important freshwater resource, and glaciers have been experiencing a continuing retreat over the past few decades. However, studies on detailed glacier mass changes are currently sparse. Here, we present the high-precision evolution of annual surface elevation and geodetic mass changes in the ablation area of the Muz Taw Glacier (Sawir Mountains, China) over the latest three consecutive mass-balance years (2017–2020) based on multi-temporal terrestrial geodetic surveys. Our results revealed clearly surface lowering and negative geodetic mass changes, and the spatial changing patterns were generally similar for the three periods with the most negative surface lowering (approximately −5.0 to −4.0 m a−1) around the glacier terminus. The gradient of altitudinal elevation changes was commonly steep at the low elevations and gentle in the upper-elevation parts, and reduced surface lowering was observed at the glacier terminus. Resulting emergence velocities ranged from 0.11 to 0.86 m a−1 with pronounced spatial variability, which was mainly controlled by surface slope, ice thickness, and the movement of tributary glaciers. Meanwhile, emergence velocities slightly compensated the surface ablation at the ablation area with a proportion of 14.9%, and dynamic thickening had small contributions to glacier surface evolution. Limited annual precipitation and glacier accumulation may result in these weak contributions. Higher-resolution surveys at the seasonal and monthly scales are required to get insight into the mass balance processes and their mechanism.
GSAP: A Global Structure Attention Pooling Method for Graph-Based Visual Place Recognition
Authors: Yang Yukun , Ma Bo , Liu Xiangdong , Zhao Liang , Huang Shoudong
Published: April 2021

The Visual Place Recognition problem aims to use an image to recognize the location that has been visited before. In most of the scenes revisited, the appearance and view are drastically different. Most previous works focus on the 2-D image-based deep learning method. However, the convolutional features are not robust enough to the challenging scenes mentioned above. In this paper, in order to take advantage of the information that helps the Visual Place Recognition task in these challenging scenes, we propose a new graph construction approach to extract the useful information from an RGB image and a depth image and fuse them in graph data. Then, we deal with the Visual Place Recognition problem as a graph classification problem. We propose a new Global Pooling method—Global Structure Attention Pooling (GSAP), which improves the classification accuracy by improving the expression ability of the Global Pooling component. The experiments show that our GSAP method improves the accuracy of graph classification by approximately 2–5%, the graph construction method improves the accuracy of graph classification by approximately 4–6%, and that the whole Visual Place Recognition model is robust to appearance change and view change.
Uncertainty Estimation for Deep Learning-Based Segmentation of Roads in Synthetic Aperture Radar Imagery
Authors: Haas Jarrod , Rabus Bernhard
Published: April 2021

Mission-critical applications that rely on deep learning (DL) for automation suffer because DL models struggle to provide reliable indicators of failure. Reliable failure prediction can greatly improve the efficiency of a system, because it becomes easier to predict when human intervention is required. DL-based systems thus stand to benefit greatly from robust measures of uncertainty over model predictions. Monte Carlo dropout (MCD), a Bayesian method, and deep ensembles (DE) have emerged as two of the most popular and competitive ways to perform uncertainty estimation. Although literature exploring the usefulness of these approaches exists in medical imaging, robotics and autonomous driving domains, it is scarce to non-existent for remote sensing, and in particular, synthetic aperture radar (SAR) applications. To close this gap, we have created a deep learning model for road extraction (hereafter referred to as segmentation) in SAR and use it to compare standard model outputs against the aforementioned most popular methods for uncertainty estimation, MCD and DE. We demonstrate that these methods are not effective as an indicator of segmentation quality when measuring uncertainty (as indicated by model softmax outputs) across an entire image but are effective when uncertainty is measured from the set of road predictions only. Furthermore, we show a marked improvement in the correlation between prediction uncertainty and segmentation quality when we increase the set of road predictions by including predictions with lower softmax scores. We demonstrate the efficacy of our application of MCD and DE methods with an experimental design that measures performance in real-world quality assessment using in-distribution (ID) and out-of-distribution (OOD) data. These results inform the development of mission-critical deep learning systems in remote sensing. Tasks in medical image analysis that have a similar morphology to road structures, such as blood vessel segmentation, can also benefit from our findings.
Sparse Constrained Low Tensor Rank Representation Framework for Hyperspectral Unmixing
Authors: Dong Le , Yuan Yuan
Published: April 2021

Recently, non-negative tensor factorization (NTF) as a very powerful tool has attracted the attention of researchers. It is used in the unmixing of hyperspectral images (HSI) due to its excellent expression ability without any information loss when describing data. However, most of the existing unmixing methods based on NTF fail to fully explore the unique properties of data, for example, low rank, that exists in both the spectral and spatial domains. To explore this low-rank structure, in this paper we learn the different low-rank representations of HSI in the spectral, spatial and non-local similarity modes. Firstly, HSI is divided into many patches, and these patches are clustered multiple groups according to the similarity. Each similarity group can constitute a 4-D tensor, including two spatial modes, a spectral mode and a non-local similarity mode, which has strong low-rank properties. Secondly, a low-rank regularization with logarithmic function is designed and embedded in the NTF framework, which simulates the spatial, spectral and non-local similarity modes of these 4-D tensors. In addition, the sparsity of the abundance tensor is also integrated into the unmixing framework to improve the unmixing performance through the L2,1 norm. Experiments on three real data sets illustrate the stability and effectiveness of our algorithm compared with five state-of-the-art methods.
Multiplexed Affinity Measurements of Extracellular Vesicles Binding Kinetics
Authors: Chiodi Elisa , Daaboul George , Marn Allison , Ünlü M.
Published: April 2021

Extracellular vesicles (EVs) have attracted significant attention as impactful diagnostic biomarkers, since their properties are closely related to specific clinical conditions. However, designing experiments that involve EVs phenotyping is usually highly challenging and time-consuming, due to laborious optimization steps that require very long or even overnight incubation durations. In this work, we demonstrate label-free, real-time detection, and phenotyping of extracellular vesicles binding to a multiplexed surface. With the ability for label-free kinetic binding measurements using the Interferometric Reflectance Imaging Sensor (IRIS) in a microfluidic chamber, we successfully optimize the capture reaction by tuning various assay conditions (incubation time, flow conditions, surface probe density, and specificity). A single (less than 1 h) experiment allows for characterization of binding affinities of the EVs to multiplexed probes. We demonstrate kinetic characterization of 18 different probe conditions, namely three different antibodies, each spotted at six different concentrations, simultaneously. The affinity characterization is then analyzed through a model that considers the complexity of multivalent binding of large structures to a carpet of probes and therefore introduces a combination of fast and slow association and dissociation parameters. Additionally, our results confirm higher affinity of EVs to aCD81 with respect to aCD9 and aCD63. Single-vesicle imaging measurements corroborate our findings, as well as confirming the EVs nature of the captured particles through fluorescence staining of the EVs membrane and cargo.
Drone Swarms as Networked Control Systems by Integration of Networking and Computing
Authors: Asaamoning Godwin , Mendes Paulo , Rosário Denis , Cerqueira Eduardo
Published: April 2021

The study of multi-agent systems such as drone swarms has been intensified due to their cooperative behavior. Nonetheless, automating the control of a swarm is challenging as each drone operates under fluctuating wireless, networking and environment constraints. To tackle these challenges, we consider drone swarms as Networked Control Systems (NCS), where the control of the overall system is done enclosed within a wireless communication network. This is based on a tight interconnection between the networking and computational systems, aiming to efficiently support the basic control functionality, namely data collection and exchanging, decision-making, and the distribution of actuation commands. Based on a literature analysis, we do not find revision papers about design of drone swarms as NCS. In this review, we introduce an overview of how to develop self-organized drone swarms as NCS via the integration of a networking system and a computational system. In this sense, we describe the properties of the proposed components of a drone swarm as an NCS in terms of networking and computational systems. We also analyze their integration to increase the performance of a drone swarm. Finally, we identify a potential design choice, and a set of open research challenges for the integration of network and computing in a drone swarm as an NCS.
An Architecture for Reliable Transportation of Delicate Goods
Authors: Matos Paulo , Rufino José , Lopes Rui
Published: April 2021

Adequate conditions are critical to avoiding damage or degradation of products during transportation, especially in the case of delicate goods like food products, live animals, precision machinery or art items, among others. The damages are not always readily identified: sometimes they are only detected several days or weeks after the merchandise has been delivered. Moreover, it may be hard to assess if the problems resulted from the transport conditions, and it may be even harder to prove it, making it difficult to determine and assign responsibilities. Also, transport is a global business, typically involving different companies and means (truck, train, plane, ship, …). Usually, customers hire the service to a single commercial entity, but the service is performed by several companies, like transporters, stockists and dispatchers. To know whether the transport requirements are fulfilled or not is thus essential to assessing responsibilities and encouraging compliance by all the players in the process. In this paper, the authors propose an architecture that allows certifying, in an exempt manner, the conditions under which the transport of sensitive goods are carried out. In case of compliance, it protects the entities of the transport chain and ensures the customer that the merchandise has not been subject to conditions that may have affected its integrity or quality. If problems are detected, it allows to identify the non-compliant players and to assign responsibilities. The solution is based on ultra-low-power, low-cost devices (equipped with several sensors, a real-time clock, and Bluetooth Low Energy services), a mobile application and several cloud services (including a Coordinated Universal Time service).
One-Stage Anchor-Free 3D Vehicle Detection from LiDAR Sensors
Authors: Li Hao , Zhao Sanyuan , Zhao Wenjun , Zhang Libin , Shen Jianbing
Published: April 2021

Recent one-stage 3D detection methods generate anchor boxes with various sizes and orientations in the ground plane, then determine whether these anchor boxes contain any region of interest and adjust the edges of them for accurate object bounding boxes. The anchor-based algorithm calculates the classification and regression label for each anchor box during the training process, which is inefficient and complicated. We propose a one-stage, anchor-free 3D vehicle detection algorithm based on LiDAR point clouds. The object position is encoded as a set of keypoints in the bird’s-eye view (BEV) of point clouds. We apply the voxel/pillar feature extractor and convolutional blocks to map an unstructured point cloud to a single-channel 2D heatmap. The vehicle’s Z-axis position, dimension, and orientation angle are regressed as additional attributes of the keypoints. Our method combines SmoothL1 loss and IoU (Intersection over Union) loss, and we apply (cosθ,sinθ) as angle regression labels, which achieve high average orientation similarity (AOS) without any direction classification tricks. During the target assignment and bounding box decoding process, our framework completely avoids any calculations related to anchor boxes. Our framework is end-to-end training and stands at the same performance level as the other one-stage anchor-based detectors.
Metal-Modified Montmorillonite as Plasmonic Microstructure for Direct Protein Detection
Authors: Giovannini Giorgia , Garoli Denis , Rupper Patrick , Neels Antonia , Rossi René M. , Boesel Luciano F.
Published: April 2021

Thanks to its negative surface charge and high swelling behavior, montmorillonite (MMT) has been widely used to design hybrid materials for applications in metal ion adsorption, drug delivery, or antibacterial substrates. The changes in photophysical and photochemical properties observed when fluorophores interact with MMT make these hybrid materials attractive for designing novel optical sensors. Sensor technology is making huge strides forward, achieving high sensitivity and selectivity, but the fabrication of the sensing platform is often time-consuming and requires expensive chemicals and facilities. Here, we synthesized metal-modified MMT particles suitable for the bio-sensing of self-fluorescent biomolecules. The fluorescent enhancement achieved by combining clay minerals and plasmonic effect was exploited to improve the sensitivity of the fluorescence-based detection mechanism. As proof of concept, we showed that the signal of fluorescein isothiocyanate can be harvested by a factor of 60 using silver-modified MMT, while bovine serum albumin was successfully detected at 1.9 µg/mL. Furthermore, we demonstrated the versatility of the proposed hybrid materials by exploiting their plasmonic properties to develop liquid label-free detection systems. Our results on the signal enhancement achieved using metal-modified MMT will allow the development of highly sensitive, easily fabricated, and cost-efficient fluorescent- and plasmonic-based detection methods for biomolecules.
Self-Powered Point-of-Care Device for Galvanic Cell-Based Sample Concentration Measurement
Authors: Álvarez-Carulla Albert , Montes-Cebrián Yaiza , Colomer-Farrarons Jordi , Miribel-Català Pere Lluís
Published: April 2021

A novel self-powered point-of-care low-power electronics approach for galvanic cell-based sample concentration measurement is presented. The electronic system harvests and senses at the same time from the single cell. The system implements a solution that is suitable in those scenarios where extreme low power is generated from the fuel cell. The proposed approach implements a capacitive-based method to perform a non-linear sweep voltammetry to the cell, but without the need to implement a potentiostat amplifier for that purpose. It provides a digital-user readable result without the need for external non-self-powered devices or instruments compared with other solutions. The system conception was validated for a particular case. The scenario consisted of the measurement of a NaCl solution as the electrolyte, which was related to the conductivity of the sample. The electronic reader continuously measured the current with a transfer function gain of 1.012 V mA−1. The overall system exhibited a maximum coefficient of variation of 6.1%, which was an improvement compared with the state-of-the-art. The proof of concept of this electronics system was validated with a maximum power consumption of 5.8 μW using commercial-off-the-self parts.
Load Resistance Optimization of a Magnetically Coupled Two-Degree-of-Freedom Bistable Energy Harvester Considering Third-Harmonic Distortion in Forced Oscillation
Authors: Noh Jinhong , Kim Pilkee , Yoon Yong-Jin
Published: April 2021

In this study, the external load resistance of a magnetically coupled two-degree-of-freedom bistable energy harvester (2-DOF MCBEH) was optimized to maximize the harvested power output, considering the third-harmonic distortion in forced response. First, the nonlinear dynamic analysis was performed to investigate the characteristics of the large-amplitude interwell motions of the 2-DOF MCBEH. From the analysis results, it was found that the third-harmonic distortion occurs in the interwell motion of the 2-DOF MCBEH system due to the nonlinear magnetic coupling between the beams. Thus, in this study, the third-harmonic distortion was considered in the optimization process of the external load resistance of the 2-DOF MCBEH, which is different from the process of conventional impedance matching techniques suitable for linear systems. The optimal load resistances were estimated for harmonic and swept-sine excitations by using the proposed method, and all the results of the power outputs were in excellent agreements with the numerically optimized results. Furthermore, the associated power outputs were compared with the power outputs obtained by using the conventional impedance matching technique. The results of the power outputs are discussed in terms of the improvement in energy harvesting performance.
Comparison of Self-Reported and Device-Based Measured Physical Activity Using Measures of Stability, Reliability, and Validity in Adults and Children
Authors: Fiedler Janis , Eckert Tobias , Burchartz Alexander , Woll Alexander , Wunsch Kathrin
Published: April 2021

Quantification of physical activity (PA) depends on the type of measurement and analysis method making it difficult to compare adherence to PA guidelines. Therefore, test-retest reliability, validity, and stability for self-reported (i.e., questionnaire and diary) and device-based measured (i.e., accelerometry with 10/60 s epochs) PA was compared in 32 adults and 32 children from the SMARTFAMILY study to examine if differences in these measurement tools are systematic. PA was collected during two separate measurement weeks and the relationship for each quality criteria was analyzed using Spearman correlation. Results showed the highest PA values for questionnaires followed by 10-s and 60-s epochs measured by accelerometers. Levels of PA were lowest when measured by diary. Only accelerometry demonstrated reliable, valid, and stable results for the two measurement weeks, the questionnaire yielded mixed results and the diary showed only a few significant correlations. Overall, higher correlations for the quality criteria were found for moderate than for vigorous PA and the results differed between children and adults. Since the differences were not found to be systematic, the choice of measurement tools should be carefully considered by anyone working with PA outcomes, especially if vigorous PA is the parameter of interest.
Liquid Level Detection in Standard Capacity Measures with Machine Vision
Authors: Bobovnik Gregor , Mušič Tim , Kutin Jože
Published: April 2021

Capacity measures are commonly used volume standards for testing measuring systems for liquids other than water. Manual readings from the measuring scale can often be difficult due to the location of the capacity measure or to the nature of the measured liquid. This article focuses on the automation of this procedure by using a single camera machine vision system. A camera positioned perpendicular to the transparent neck captures the image of the liquid meniscus and the measuring scale. The volume reading is determined with the user-defined software in the LabVIEW programming environment, which carries out the image preprocessing, detection of the scale marks and the liquid level, correction of lens distortion and parallax effects and final unit conversions. The realized measuring system for liquid level detection in standard capacity measures is tested and validated by comparing the automated measurement results with those taken by the operators. The results confirm the appropriateness of the presented measuring system for the field of legal metrology.
Design of a Wideband Tonpilz Transducer Comprising Non-Uniform Piezoceramic Stacks with Equivalent Circuits
Authors: Pyo Seonghun , Afzal Muhammad Shakeel , Lim Youngsub , Lee Seungjin , Roh Yongrae
Published: April 2021

Tonpilz transducers are desirable for their superior performance in underwater target detection and communication applications. Several design schemes to widen their bandwidth have been reported, but these schemes often involve a complex structure or arrangement of additional components. In this study, a simple design is proposed to improve the bandwidth of a multimode Tonpilz transducer by using a non-uniform drive section that consists of piezoelectric stacks of various thicknesses. The efficacy of the design is illustrated with a multimode Tonpilz transducer having three lead zirconate titanate (PZT) stacks of different thicknesses. A new equivalent circuit was developed to analyze the frequency response of the transducer incorporating the non-uniform drive section and was used for rigorous analysis of the effects of varying the position and thickness of the non-uniform stacks on the transmitting characteristics of the transducer. The validity of the design was verified through the fabrication and characterization of a prototype multimode Tonpilz transducer. The developed structure can be readily extended to an arbitrary number of stacks in the Tonpilz transducer with any number of PZT disks in each stack.
Robust Principal Component Thermography for Defect Detection in Composites
Authors: Ebrahimi Samira , Fleuret Julien , Klein Matthieu , Théroux Louis-Daniel , Georges Marc , Ibarra-Castanedo Clemente , Maldague Xavier
Published: April 2021

Pulsed Thermography (PT) data are usually affected by noise and as such most of the research effort in the last few years has been directed towards the development of advanced signal processing methods to improve defect detection. Among the numerous techniques that have been proposed, principal component thermography (PCT)—based on principal component analysis (PCA)—is one of the most effective in terms of defect contrast enhancement and data compression. However, it is well-known that PCA can be significantly affected in the presence of corrupted data (e.g., noise and outliers). Robust PCA (RPCA) has been recently proposed as an alternative statistical method that handles noisy data more properly by decomposing the input data into a low-rank matrix and a sparse matrix. We propose to process PT data by RPCA instead of PCA in order to improve defect detectability. The performance of the resulting approach, Robust Principal Component Thermography (RPCT)—based on RPCA, was evaluated with respect to PCT—based on PCA, using a CFRP sample containing artificially produced defects. We compared results quantitatively based on two metrics, Contrast-to-Noise Ratio (CNR), for defect detection capabilities, and the Jaccard similarity coefficient, for defect segmentation potential. CNR results were on average 40% higher for RPCT than for PCT, and the Jaccard index was slightly higher for RPCT (0.7395) than for PCT (0.7010). In terms of computational time, however, PCT was 11.5 times faster than RPCT. Further investigations are needed to assess RPCT performance on a wider range of materials and to optimize computational time.
TTAS: Trusted Token Authentication Service of Securing SCADA Network in Energy Management System for Industrial Internet of Things
Authors: Yang Yu-Sheng , Lee Shih-Hsiung , Chen Wei-Che , Yang Chu-Sing , Huang Yuen-Min , Hou Ting-Wei
Published: April 2021

The vigorous development of the Industrial Internet of Things brings the advanced connection function of the new generation of industrial automation and control systems. The Supervisory Control and Data Acquisition (SCADA) network is converted into an open and highly interconnected network, where the equipment connections between industrial electronic devices are integrated with a SCADA system through a Modbus protocol. As SCADA and Modbus are easily used for control and monitoring, the interconnection and operational efficiency between systems are highly improved; however, such connectivity inevitably exposes the system to the open network environment. There are many network security threats and vulnerabilities in a SCADA network system. Especially in the era of the Industrial Internet of Things, any security vulnerability of an industrial system may cause serious property losses. Therefore, this paper proposes an encryption and verification mechanism based on the trusted token authentication service and Transport Layer Security (TLS) protocol to prevent attackers from physical attacks. Experimentally, this paper deployed and verified the system in an actual field of energy management system. According to the experimental results, the security defense architecture proposed in this paper can effectively improve security and is compatible with the actual field system.
CPW Fed Compact UWB 4-Element MIMO Antenna with High Isolation
Authors: Yin Wenfei , Chen Shaoxiang , Chang Junjie , Li Chunhua , Khamas Salam K.
Published: April 2021

In the paper, an extremely compact multiple-input-multiple-output (MIMO) antenna is proposed for portable wireless ultrawideband (UWB) applications. The proposed prototype consists of four monopole antenna elements, which are placed perpendicularly to achieve polarization diversity. In addition, the mutual coupling between antenna elements is suppressed by designing the gap between the radiation element and the ground plane. Moreover, a matching stub has been connected to the feedline to ensure impedance matching in high frequency. Both simulated and measured results indicate that the proposed antenna has a bandwidth of 3–20 GHz, with a high isolation better than 17 dB. In addition, the designed MIMO antenna offers excellent radiation characteristics and stable gain over the whole working band. The envelope correlation coefficient (ECC) is less than 0.1, which shows that the antenna can meet the polarization diversity characteristics well.