bluuebunny/crossref_metadata_2025 huggingface dataset:
From the Streets to the Judicial Evidence: Determination of Traditional Illicit Substances in Drug Seizures by a Rapid and Sensitive UHPLC-MS/MS-Based Platform
Authors: Gosetti Fabio , Consonni Viviana , Ballabio Davide , Orlandi Marco Emilio , Amodio Angelo , Valeria Picci Maria , Visentin Marco , Termopoli Veronica
Published: December 2022

According to the 2021 World Drug Report, around 275 million people use drugs of abuse, and 36 million people suffer from addiction, fostering a thriving market for illicit substances. In Italy, 30,083 people were reported to the Judicial Authority for offenses in violation of the Italian Law D.P.R. 309/1990. These offences are sentenced after a qualitative–quantitative analysis of seized materials. Given the large quantity of seized drugs and the need to perform accurate analytical determinations, Italian forensic laboratories struggle to complete analyses in a short time, delaying the entire reporting process needed to achieve sentencing. For this purpose, an UHPLC-MS/MS-based platform was developed at the University of Milano-Bicocca to support law-enforcement authorities. Software was designed to easily manage street seizure acquisition, documentation registration, and sampling. A sensitive UHPLC-MS/MS method was fully validated for the quantification of the traditional illicit substances (cocaine, heroin, 6-MAM, morphine, amphetamine, methamphetamine, MDMA, ketamine, GHB, GBL, LSD, trans-∆9-THC, and THCA) at the ppb level. The final report is relayed to the Prefecture in 3–4 days, even within 24 h for urgent requests. The platform allows for semi-automatic data handling to minimize erroneous results for an accurate report generation by standardized procedures.
Variable Temperature Behaviour of the Hybrid Double Perovskite MA2KBiCl6
Authors: Wei Fengxia , Wu Yue , Sun Shijing , Deng Zeyu , Chew Li , Cheng Baisong , Tan Cheng , White Timothy , Cheetham Anthony
Published: December 2022

Perovskite-related materials show very promising properties in many fields. Pb-free perovskites are particularly interesting, because of the toxicity of Pb. In this study, hybrid double perovskite MA2KBiCl6 (MA = methylammonium cation) was found to have interesting variable temperature behaviours. Both variable temperature single crystal X-ray diffraction, synchrotron powder diffraction, and Raman spectroscopy were conducted to reveal a rhombohedral to cubic phase transition at around 330 K and an order to disorder transition for inorganic cage below 210 K.
Flavonoid Composition and Antibacterial Properties of Crocus sativus L. Petal Extracts
Authors: Naim Nadia , Bouymajane Aziz , Oulad El Majdoub Yassine , Ezrari Said , Lahlali Rachid , Tahiri Abdessalem , Ennahli Said , Laganà Vinci Roberto , Cacciola Francesco , Mondello Luigi , Madani Ilham
Published: December 2022

Saffron petals, which are the main by-products of Crocus sativus L. (Iridaceae family), are produced in large quantities and are known for their many beneficial properties. In this regard, this study aims to investigate the phenolic composition and antibacterial properties of hydroethanolic extracts from Crocus sativus L. petals collected from Serghina (province of Boulmane) in Morocco. The phenolic profiles were characterized using high-performance liquid chromatography coupled to a photodiode array and electrospray ionization mass spectrometry (HPLC-PDA-ESI/MS). The antibacterial potential was evaluated against four bacterial strains potentially causing food-borne disease (Staphylococcus aureus, Salmonella typhimurium, Escherichia coli, and Listeria monocytogenes) using disc diffusion and broth micro-dilution assays. Results showed that a total of 27 phenolic compounds was detected in the Crocus sativus L. petal extracts, which were assigned to flavonoids (kaempferol, quercetin, isorhamnetin, and myricetin derivatives). The most abundant compound was represented by kaempferol-sophoroside isomer (20.82 mg/g ± 0.152), followed by kaempferol-sophoroside-hexoside (2.63 mg/g ± 0.001). The hydroethanolic extracts of Crocus sativus L. petals demonstrated bactericidal effects against Staphylococcus aureus and Listeria monocetogenes and bacteriostatic effects against Escherichia coli and Salmonella typhimurium. Therefore, the by-product Crocus sativus L. petal extracts might be considered as valuable sources of natural antibacterial agents with potential applications in the food and pharmaceutical industries.
Bridges and Vertices in Heteroboranes
Authors: Macgregor Stuart A. , Welch Alan J.
Published: December 2022

A number of (hetero)boranes are known in which a main group atom X ‘bridges’ a B—B connectivity in the open face, and in such species X has previously been described as simply a bridge or, alternatively, as a vertex in a larger cluster. In this study we describe an approach to distinguish between these options based on identifying the best fit of the experimental {Bx} cluster fragment with alternate exemplar {Bx} fragments derived from DFT-optimized [BnHn]2− models. In most of the examples studied atom X is found to be better regarded as a vertex, having ‘a ‘verticity’ of ca. 60–65%. Consideration of our results leads to the suggestion that the radial electron contribution from X to the overall skeletal electron count is more significant than the tangential contribution.
Modern Developments in Bifunctional Chelator Design for Gallium Radiopharmaceuticals
Authors: Davey Patrick R. W. J. , Paterson Brett M.
Published: December 2022

The positron-emitting radionuclide gallium-68 has become increasingly utilised in both preclinical and clinical settings with positron emission tomography (PET). The synthesis of radiochemically pure gallium-68 radiopharmaceuticals relies on careful consideration of the coordination chemistry. The short half-life of 68 min necessitates rapid quantitative radiolabelling (≤10 min). Desirable radiolabelling conditions include near-neutral pH, ambient temperatures, and low chelator concentrations to achieve the desired apparent molar activity. This review presents a broad overview of the requirements of an efficient bifunctional chelator in relation to the aqueous coordination chemistry of gallium. Developments in bifunctional chelator design and application are then presented and grouped according to eight categories of bifunctional chelator: the macrocyclic chelators DOTA and TACN; the acyclic HBED, pyridinecarboxylates, siderophores, tris(hydroxypyridinones), and DTPA; and the mesocyclic diazepines.
Epimeric Mixture Analysis and Absolute Configuration Determination Using an Integrated Spectroscopic and Computational Approach—A Case Study of Two Epimers of 6-Hydroxyhippeastidine
Authors: Le Ngoc-Thao-Hien , Vermeyen Tom , Aerts Roy , Herrebout Wouter A. , Pieters Luc , Tuenter Emmy
Published: December 2022

Structural elucidation has always been challenging, and misassignment remains a stringent issue in the field of natural products. The growing interest in discovering unknown, complex natural structures accompanies the increasing awareness concerning misassignments in the community. The combination of various spectroscopic methods with molecular modeling has gained popularity in recent years. In this work, we demonstrated, for the first time, its power to fully elucidate the 2-dimensional and 3-dimensional structures of two epimers in an epimeric mixture of 6-hydroxyhippeastidine. DFT calculation of chemical shifts was first performed to assist the assignment of planar structures. Furthermore, relative and absolute configurations were established by three different ways of computer-assisted structure elucidation (CASE) coupled with ORD/ECD/VCD spectroscopies. In addition, the significant added value of OR/ORD computations to relative and absolute configuration determination was also revealed. Remarkably, the differentiation of two enantiomeric scaffolds (crinine and haemanthamine) was accomplished via OR/ORD calculations with cross-validation by ECD and VCD.
On the Potential Therapeutic Roles of Taurine in Autism Spectrum Disorder
Authors: Rubio-Casillas Alberto , Redwan Elrashdy M. , Uversky Vladimir N.
Published: December 2022

Contemporary research has found that people with autism spectrum disorder (ASD) exhibit aberrant immunological function, with a shift toward increased cytokine production and unusual cell function. Microglia and astroglia were found to be significantly activated in immuno-cytochemical studies, and cytokine analysis revealed that the macrophage chemoattractant protein-1 (MCP-1), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), and transforming growth factor β-1 (TGFB-1), all generated in the neuroglia, constituted the most predominant cytokines in the brain. Taurine (2-aminoethanesulfonic acid) is a promising therapeutic molecule able to increase the activity of antioxidant enzymes and ATPase, which may be protective against aluminum-induced neurotoxicity. It can also stimulate neurogenesis, synaptogenesis, and reprogramming of proinflammatory M1 macrophage polarization by decreasing mitophagy (mitochondrial autophagy) and raising the expression of the markers of the anti-inflammatory and pro-healing M2 macrophages, such as macrophage mannose receptor (MMR, CD206) and interleukin 10 (IL-10), while lowering the expression of the M1 inflammatory factor genes. Taurine also induces autophagy, which is a mechanism that is impaired in microglia cells and is critically associated with the pathophysiology of ASD. We hypothesize here that taurine could reprogram the metabolism of M1 macrophages that are overstimulated in the nervous system of people suffering from ASD, thereby decreasing the neuroinflammatory process characterized by autophagy impairment (due to excessive microglia activation), neuronal death, and improving cognitive functions. Therefore, we suggest that taurine can serve as an important lead for the development of novel drugs for ASD treatment.
Effect of Substratum Structural Complexity of Coral Seedlings on the Settlement and Post-Settlement Survivorship of Coral Settlers
Authors: Fujiwara Shuichi , Kezuka Daisuke , Hagiwara Kazutaka , Ishimori Hiroo , Tabata Hideo
Published: December 2022

The substratum structure is critical for facilitating settlement and increasing the survivorship of coral settlers. However, knowledge about its structural complexity is largely lacking. In this study, we examined the effect of complexity on the settlement and post-settlement survivorship of coral settlers using four types of structures: groove, using a CSD (Coral Settlement Device, 4.5 cm φ × 2.5 cm H, top-shaped ceramic); flat, using a CP (Ceramic Plate, 29.5 cm L × 3.1 cm W × 0.9 cm H, unglazed ceramic plate); linear, using a CN (Coral Net, mesh size 19 mm, biodegradable plastic net); and wrinkle, using a SS (Scallop Shell, 11.0 cm in shell length). The complexity was obtained from the ratio of the surface area to the vertically projected area of the substratum. The substratum sets were installed in the coral reef around the Ryukyu Islands every May from 2012 to 2014. After about 2 or 6 months of spawning, a certain number of substratum types were sampled, and the number of coral spats that settled on them was counted by taxa classified into Acropora, Pocilloporidae, Millepora, and Others. The larval settlement rate in the first set of samples and the survivorship of coral spats in the second set of samples were estimated. The mean settlement rate was, in order, the CSD; SS; CN; and CP, and the mean survivorship was, in order, the CSD; CP; SS; and CN, over three years. A positive correlation was found between the structural complexity, mean settlement rate, and mean survivorship. Our results show that the structural complexity of coral seedlings affects the settlement of coral larvae and the survivorship of coral spats.
High-Throughput Live and Fixed Cell Imaging Method to Screen Matrigel-Embedded Organoids
Authors: Ramm Susanne , Vary Robert , Gulati Twishi , Luu Jennii , Cowley Karla J. , Janes Michael S. , Radio Nicholas , Simpson Kaylene J.
Published: December 2022

Technical advances in microscopy and automation have enabled image-based phenotypic screening of spheroids and organoids to become increasingly high throughput and high content at the same time. In particular, matrix-embedded 3D structures can recapitulate many aspects of parent (e.g., patient) tissues. Live-cell imaging of growing structures allows tremendous insight into population heterogeneity during drug treatment. However, screening for targeted markers and more detailed morphological analyses typically require fixation of 3D structures, and standard formaldehyde (FA) incubation conditions can dissolve collagen-based extracellular matrices such as Matrigel. The dislocation and clumping of the spheroids make image-based segmentation very difficult and the tracking of structures from the live cell stage to their fixed cell location virtually impossible. In this method, we present a fixation and staining protocol that is gentle enough to maintain 3D structures exactly in their live-cell location and does not alter their morphology. This opens up analytical strategies that connect the spheroid’s growth kinetics and heterogeneity of treatment responses with the more targeted fixed cell stains. Furthermore, we optimized the automated seeding and imaging of spheroids so that screening and phenotypic characterization can be performed in high-throughput at either low or high magnification and yield the same result, independent of the microscope used.
DNN-Based Physical-Layer Network Coding for Visible Light Communications
Authors: Wang Xuesong , Zhang Runxin , Xie Xinyan , Lu Lu
Published: December 2022

The key difference between visible light communication (VLC) and radio frequency (RF) communication is the former’s line-of-sight (LOS) transmission nature, and hence a relay node has to be adopted for VLC to extend its coverage. Physical-layer network coding (PNC) has the advantage of doubling the throughput of a two-way relay network (TWRN), where two end nodes exchange information via the help of a relay, compared with the conventional store-and-forward routing strategy. Although PNC has been studied for VLC in the literature, the state-of-the-art schemes are highly inefficient, requiring tight phase synchronization between the two end nodes, and hence difficult to realize. This paper proposes the application of a deep neural network (DNN) to a PNC VLC system, named DP-VLC, that enables misaligned phases and can deal with the light channel gains and noises in a satisfactory manner without introducing additional computation complexities. We implement DP-VLC using the universal software radio peripheral (USRP) software radio platform and a self-developed VLC optical front-end using commercial off-the-shelf (COTS) light-emitting diodes (LEDs) and photo-diodes (PDs). We find that irregular constellations generated by DP-PNC can be transmitted and recovered in a 1.5 m VLC link effectively. Experimental results show that our DP-PNC prototype performs better than conventional PNC VLC system when the signal-interference-to-noise ratio (SINR) of received optical signals is larger than 13.63 dB and can achieve a throughput of up to 77.38 Mbps in a 20 MHz channel under PNC scheme when the SINR is 22.86 dB. More importantly, we find that DP-VLC performs even better than fixed-constellation PNC system in the saturated SINR regime (e.g., 20–25 dB) where non-linear effects may happen compared with moderate SINR regimes (e.g., 10–20 dB), showing its adaptability to unpredictable impairments in optical links. Our first attempt at realizing DNN-based optical PNC in a TWRN has paved the way for future PNC-enhanced VLC systems.
Demonstration of a Key Distribution Scheme Based on the Masking Effect of Fiber Channel Noise in Power Transmission System
Authors: Wang Xiangqing , Yang Xiaokun , Wang Dongfei , Liu Bin , Zhang Lan , Yang Zufang , Zhu Han , Wu Baohong
Published: December 2022

This paper proposes a novel key distribution method based on the masking effect of fiber channel noise in a power transmission system. The two physical layer signal processing technologies used in this solution are frame synchronization and resampling. The random data sent and received is digitally processed by these two techniques. An experimental platform is built, and the key performance is assessed by analyzing the measured bit error rate (BER) dynamic curve, setting different decision thresholds and the amplitude of the state basis. Experimental results show that the key distribution rate can reach 10 kbit/s with a key consistency rate of 98%. This is of great significance to the development of safe optical communication technology in power transmission systems. In the power communication system, a large number of optical fiber communication devices are used. The key distribution method proposed in this paper can effectively improve the security of optical fiber communication, which is of great significance.
Preparation of Functionalized Magnetic Polystyrene Microspheres and Their Application in Food Safety Detection
Authors: Teng Xin , Ding Xingyu , She Zhuxin , Li Yi , Xiong Xiaohui
Published: December 2022

Based on the specific binding of sulfonic acid groups to melamine, β-agonists and other compounds, Fe3O4 nano-magnetic beads were coated with polystyrene using an improved micro-suspension emulsion polymerization method, thus forming core–shell magnetic polystyrene microspheres (Fe3O4@PS) with Fe3O4 as the core and polystyrene as the shell. These functionalized microspheres, which can be used as magnetic solid-phase extraction (MSPE) adsorbent, were prepared after further sulfonation. These microspheres were characterized by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), particle size analysis and saturation magnetization measurement. The results showed that these sulfonated magnetic polystyrene microspheres had favorable sphericity. The particle size of these microspheres ranged from 1 μm to 10 μm. Additionally, these microspheres had good dispersion and magnetic responses in both inorganic and organic solvents. Moreover, these functionalized magnetic polystyrene microspheres were tested and evaluated by high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). The results indicated that these sulfonated magnetic polystyrene microspheres (Fe3O4@SPS) could effectively adsorb such illegal additives as β-agonists and melamine in the food matrix.
Blending Recycled High-Density Polyethylene HDPE (rHDPE) with Virgin (vHDPE) as an Effective Approach to Improve the Mechanical Properties
Authors: Zhang Jian , Hirschberg Valerian , Rodrigue Denis
Published: December 2022

The mechanical properties of virgin/recycled high-density polyethylene (HDPE) blends over the complete concentration range was thoroughly investigated in this work. In particular, a focus was made on the long-term properties via mechanical fatigue. Two different mixing methods, namely powder mixing (dry blending) and extrusion mixing (melt blending), were used to determine the effect of processing conditions on the tensile and fatigue behavior of the blends after compression molding. It was found that both tensile (modulus, ultimate strength) and fatigue performances were improved with increasing vHDPE content. Based on the obtained data, a correlation between the blends composition and mechanical properties is reported. Moreover, it was observed that increasing the vHDPE content led to slower crack propagation rate, probably due to less defects (contamination) in the blends. Finally, a negligible difference in mechanical properties (fatigue resistance) between both mixing approaches was observed, but samples produced via powder mixing showed less viscous dissipation (heat generation) as the vHDPE content increased, leading to lower surface temperature rise which can be an advantage for specific applications.
Biological Pretreatment Effects on the Bioconversion of Brewer Spent Grain with Hermetia illucens Larvae
Authors: Sumba-Zhongor Martha , Álava Eduardo , Galarza Luis , Ortiz-Ulloa Johana , Chica Eduardo J. , Ruiz-Barzola Omar , Nieto-Wigby Julia , Jiménez-Feijoo Maria Isabel , Torres-Ulloa Malena
Published: December 2022

Hermetia illucens is an important species for waste management and the circular economy. The aim of this study was to analyze the effects of Trichoderma reesei C2A and Pleurotus sp. as pretreatments of brewer spent grain (BSG). BSG was inoculated with fungal solution or distilled water (control). After seven days, this was used for H. illucens larvae cultivation. At the end of bioconversion process, parameters of substrate reduction and H. illucens larval development were evaluated. Chemical properties of BSG, frass and larvae were also analyzed. With T. reesei C2A pretreatment, highest substrate reduction (46.3 ± 0.9%) was achieved, but larval growth rate was lower (1.0 ± 0.1 mg/d) than that of control (2.8 ± 0.2 mg/d). Larvae of Pleurotus sp. pretreatment had limited development, reflected in their negative growth rate (−0.6 ± 0.2 mg/d). In conclusion, cultivation of H. illucens larvae (six day old) on BSG pretreated with Pleurotus sp. is not recommended. On the other hand, T. reesei C2A pretreatment enhance BSG reduction, and its potential use for lignocellulosic waste management should be more explored.
Correction: Chen et al. A New Triangulation Algorithm for Positioning Space Debris. Remote Sens. 2021, 13, 4878
Authors: Chen Long , Liu Chengzhi , Li Zhenwei , Kang Zhe
Published: December 2022

The authors would like to make the following corrections to this paper [...]
Correlations between the EMG Structure of Movement Patterns and Activity of Postural Muscles in Able-Bodied and Wheelchair Fencers
Authors: Borysiuk Zbigniew , Blaszczyszyn Monika , Piechota Katarzyna , Konieczny Mariusz , Cynarski Wojciech J.
Published: December 2022

The study involved Paralympic wheelchair fencers (N = 7) in two disability categories, and able-bodied female epee fencers (N = 7), members of the polish paralympic fencing teams. The performance of postural muscles and sword arm muscles in both groups of fencers, and of the front and rear leg muscles in the able-bodied fencers, was examined using surface electromyography with an accelerometer and the OptiTrack motion analysis system, as well as ground force reaction platforms. The activation sequence of individual muscles was determined and the structure of movement patterns in able-bodied and wheelchair fencers was formulated. A statistically significant correlation was found between the complex motor reaction time and latissimus dorsi muscle activation (p = 0.039, Z = −2.062) in wheelchair fencers. High correlations between the vertical force and EMG signal values of the gastrocnemius caput laterale muscle (0.85 for p = 0.022) were found in able-bodied fencers. A heuristic analysis indicated the significance of postural muscles in the movement patterns of wheelchair and able-bodied fencers. These muscles play a crucial role in the anticipatory postural adjustment of the trunk during technical fencing actions, including attacks on the opponent’s body.
Impedance Coupled Voltage Boosting Circuit for Polyvinylidene Fluoride Based Energy Harvester
Authors: Lee Kibae , Jeong Yoonsang , Lee Chong Hyun , Lee Jongkil , Seo Hee-Seon , Cho Yohan
Published: December 2022

Polyvinylidene fluoride (PVDF) is an emerging method for energy harvesting by fluid motion with superior flexibility. However, the PVDF energy harvester, which has a high internal impedance and generates a low voltage, has a large power transmission loss. To overcome this problem, we propose an impedance-coupled voltage-boosting circuit (IC-VBC) that reduces the impedance of the PVDF energy harvester and boosts the voltage. SPICE simulation results show that IC-VBC reduces the impedance of the PVDF energy harvester from 4.3 MΩ to 320 kΩ and increases the output voltage by 2.52 times. We successfully charged lithium-ion batteries using the PVDF energy harvester and IC-VBC with low-speed wind power generation.
Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning
Authors: Silva Luis Augusto , Sales Mendes André , Sánchez San Blas Héctor , Caetano Bastos Lia , Leopoldo Gonçalves Alexandre , Fabiano de Moraes André
Published: December 2022

Due to the increasing urban development, it has become important for municipalities to permanently understand land use and ecological processes, and make cities smart and sustainable by implementing technological tools for land monitoring. An important problem is the absence of technologies that certify the quality of information for the creation of strategies. In this context, expressive volumes of data are used, requiring great effort to understand their structures, and then access information with the desired quality. This study are designed to provide an initial response to the need for mapping zones in the city of Itajaí (SC), Brazil. The solution proposes to aid object recognition employing object-based classifiers OneR, NaiveBayes, J48, IBk, and Hoeffding Tree algorithms used together with GeoDMA, and a first approach in the use of Region-based Convolutional Neural Network (R-CNN) and the YOLO algorithm. All this is to characterize vegetation zones, exposed soil zones, asphalt, and buildings within an urban and rural area. Through the implemented model for active identification of geospatial objects with similarity levels, it was possible to apply the data crossover after detecting the best classifier with accuracy (85%) and the kappa agreement coefficient (76%). The case study presents the dynamics of urban and rural expansion, where expressive volumes of data are obtained and submitted to different methods of cataloging and preparation to subsidize rapid control actions. Finally, the research describes a practical and systematic approach, evaluating the extraction of information to the recommendation of knowledge with greater scientific relevance. Allowing the methods presented to apply the calibration of values for each object, to achieve results with greater accuracy, which is proposed to help improve conservation and management decisions related to the zones within the city, leaving as a legacy the construction of a minimum technological infrastructure to support the decision.
Monitoring Single-Phase LV Charging of Electric Vehicles
Authors: Kuwałek Piotr , Wiczyński Grzegorz
Published: December 2022

The paper presents the results of the monitoring process of the charging of an electric vehicle battery pack. Battery pack charging with a capacity of 58kWh was monitored in a single-phase 230V/50Hz circuit. The slow charging system used was configured to obtain a current of 10A. During monitoring, the focus was on the recognition of the charging, considering the impact of this process on power quality and, consequently, on the reliability of electrical machines. Research results show that the monitored charges are one-, two-, or three-stage processes. The variations in the currents, power, and higher harmonic contents were observed. The effects of such variations depend on the properties of the power grid at the point of connection of the charging system. Knowledge of the variation of the voltages, currents, and active and reactive power allows for the determination of the requirements of the measuring equipment used for charging the monitoring, including the selection of discrimination/averaging time of monitored quantities. The research results also indicate the need for continuous monitoring of the power quality in the power supply circuit of electrical loads, e.g., electrical machines. Continuous monitoring supports the diagnostics of electrical machines and allows the appropriate measures to increase their reliability.
In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns
Authors: Syed Toqeer Ali , Siddiqui Muhammad Shoaib , Abdullah Hurria Binte , Jan Salman , Namoun Abdallah , Alzahrani Ali , Nadeem Adnan , Alkhodre Ahmad B.
Published: December 2022

Augmented reality (AR) has gained enormous popularity and acceptance in the past few years. AR is indeed a combination of different immersive experiences and solutions that serve as integrated components to assemble and accelerate the augmented reality phenomena as a workable and marvelous adaptive solution for many realms. These solutions of AR include tracking as a means for keeping track of the point of reference to make virtual objects visible in a real scene. Similarly, display technologies combine the virtual and real world with the user’s eye. Authoring tools provide platforms to develop AR applications by providing access to low-level libraries. The libraries can thereafter interact with the hardware of tracking sensors, cameras, and other technologies. In addition to this, advances in distributed computing and collaborative augmented reality also need stable solutions. The various participants can collaborate in an AR setting. The authors of this research have explored many solutions in this regard and present a comprehensive review to aid in doing research and improving different business transformations. However, during the course of this study, we identified that there is a lack of security solutions in various areas of collaborative AR (CAR), specifically in the area of distributed trust management in CAR. This research study also proposed a trusted CAR architecture with a use-case of tourism that can be used as a model for researchers with an interest in making secure AR-based remote communication sessions.
Decoupling of Dual-Polarized Antenna Arrays Using Non-Resonant Metasurface
Authors: Luo Shengyuan , Mei Peng , Zhang Yiming , Pedersen Gert Frølund , Zhang Shuai
Published: December 2022

A non-resonant metasurface (NRMS) concept is reported in this paper to improve the isolation of dual-polarized and wideband large-scale antenna arrays. By properly designing the NRMS, it can perform stable negative permeability and positive permittivity along the tangential direction of the NRMS within a wide band, which can be fully employed to suppress the mutual couplings of large-scale antenna arrays. At the same time, the proposed NRMS can also result in positive permittivity and permeability along the normal direction of the NRMS, which guarantees the free propagation of electromagnetic waves from antenna arrays along the normal direction. For demonstration, a 4×4 dual-polarized antenna array loading with the proposed NRMS is designed to improve the isolations of the antenna array. The simulations demonstrate that the isolations among all ports are over 24 dB from 4.36 to 4.94 GHz, which are experimentally verified by the measured results. Moreover, the radiation patterns of antenna elements are still maintained after leveraging the proposed NRMS. Due to the simple structure of the proposed NRMS, it is very promising to be widely employed for massive MIMO antenna arrays.
Robust Data Augmentation Generative Adversarial Network for Object Detection
Authors: Lee Hyungtak , Kang Seongju , Chung Kwangsue
Published: December 2022

Generative adversarial network (GAN)-based data augmentation is used to enhance the performance of object detection models. It comprises two stages: training the GAN generator to learn the distribution of a small target dataset, and sampling data from the trained generator to enhance model performance. In this paper, we propose a pipelined model, called robust data augmentation GAN (RDAGAN), that aims to augment small datasets used for object detection. First, clean images and a small datasets containing images from various domains are input into the RDAGAN, which then generates images that are similar to those in the input dataset. Thereafter, it divides the image generation task into two networks: an object generation network and image translation network. The object generation network generates images of the objects located within the bounding boxes of the input dataset and the image translation network merges these images with clean images. A quantitative experiment confirmed that the generated images improve the YOLOv5 model’s fire detection performance. A comparative evaluation showed that RDAGAN can maintain the background information of input images and localize the object generation location. Moreover, ablation studies demonstrated that all components and objects included in the RDAGAN play pivotal roles.
Industrial Shared Wireless Communication Systems—Use Case of Autonomous Guided Vehicles with Collaborative Robot
Authors: Stój Jacek , Kampen Anne-Lena , Cupek Rafał , Smołka Ireneusz , Drewniak Marek
Published: December 2022

Dedicated fieldbuses were developed to provide temporal determinisms for industrial distributed real-time systems. In the early stages, communication systems were dedicated to a single protocol and generally supported a single service. Industrial Ethernet, which is used today, supports many concurrent services, but usually only one real-time protocol at a time. However, shop-floor communication must support a range of different traffic from messages with strict real-time requirements such as time-driven messages with process data and event-driven security messages to diagnostic messages that have more relaxed temporal requirements. Thus, it is necessary to combine different real-time protocols into one communication network. This raises many challenges, especially when the goal is to use wireless communication. There is no research work on that area and this paper attempts to fill in that gap. It is a result of some experiments that were conducted while connecting a Collaborative Robot CoBotAGV with a production station for which two real-time protocols, Profinet and OPC UA, had to be combined into one wireless network interface. The first protocol was for the exchange of processing data, while the latter integrated the vehicle with Manufacturing Execution System (MES) and Transport Management System (TMS). The paper presents the real-time capabilities of such a combination—an achievable communication cycle and jitter.
Microwave-Based Subsurface Characterization through a Combined Finite Element and Variable Exponent Spaces Technique
Authors: Schenone Valentina , Estatico Claudio , Gragnani Gian Luigi , Pastorino Matteo , Randazzo Andrea , Fedeli Alessandro
Published: December 2022

A microwave characterization technique to inspect subsurface scenarios is proposed and numerically assessed in this paper. The approach is based on a combination of finite element electromagnetic modeling and an inversion procedure in Lebesgue spaces with variable exponents. The former allows for description of the measurement system and subsurface scenario with high accuracy, while the latter exploits the adaptive definition of exponent function to achieve improved results in the regularized solution of the inverse scattering problem. The method has been assessed with numerical simulations regarding two-layered environments with both planar and non-planar air–soil interfaces. The results show the capabilities of the method of detecting buried objects in different operative conditions.
Quantitative Evaluation of In Vivo Corneal Biomechanical Properties after SMILE and FLEx Surgery by Acoustic Radiation Force Optical Coherence Elastography
Authors: Zhao Yanzhi , Zhu Yirui , Wang Yongbo , Yang Hongwei , He Xingdao , Alvarez-Arenas Tomas Gomez , Li Yingjie , Huang Guofu
Published: December 2022

The purpose of this study is to quantitatively evaluate the differences in corneal biomechanics after SMILE and FLEx surgery using an acoustic radiation force optical coherence elastography system (ARF-OCE) and to analyze the effect of the corneal cap on the integrity of corneal biomechanical properties. A custom ring array ultrasound transducer is used to excite corneal tissue to produce Lamb waves. Depth-resolved elastic modulus images of the in vivo cornea after refractive surgery were obtained based on the phase velocity of the Lamb wave. After refractive surgery, the average elastic modulus of the corneal flap decreased (71.7 ± 24.6 kPa), while the elastic modulus of the corneal cap increased (219.5 ± 54.9 kPa). The average elastic modulus of residual stromal bed (RSB) was increased after surgery, and the value after FLEx (305.8 ± 48.5 kPa) was significantly higher than that of SMILE (221.3 ± 43.2 kPa). Compared with FLEx, SMILE preserved most of the anterior stroma with less change in corneal biomechanics, which indicated that SMILE has an advantage in preserving the integrity of the corneal biomechanical properties. Therefore, the biomechanical properties of the cornea obtained by the ARF-OCE system may be one of the essential indicators for evaluating the safety of refractive surgery.
On the Use of Haloalkane/Acrylate-Based Holographic Gratings as Compression and Rotation Sensors
Authors: Castagna Riccardo , Riminesi Cristiano , Di Donato Andrea , Francescangeli Oriano , Lucchetta Daniele Eugenio
Published: December 2022

In this work, we test the effectiveness of using highly transparent holographic phase reflection and transmission volume gratings based on multifunctional acrylates as linear compression and rotation sensors. The gratings are recorded in a holographic mixture based on multi-reticulated acrylate and haloalkanes. To activate the photo-polymerization process, we used a mixture of 6-oxocamphore and rhodamine 6G. The mixture is a simplified version of the mixture used in previous works and shows some interesting features mainly in connection with the different roles played by the rhodamine 6G dye at different writing wavelengths λ = 532 nm and λ = 460 nm. Regarding reflection gratings, the maximum achieved diffraction efficiency is ≈50% and their use as linear compression sensors produces a shift in the reflection peak of 2 nm. Following the removal of compression, the grating slowly returns to the initial state. Regarding transmission gratings, the maximum achieved diffraction efficiency is ≈45% and they demonstrate very high sensitivity to even small rotations in a free-standing configuration.
Data Valuation Algorithm for Inertial Measurement Unit-Based Human Activity Recognition
Authors: Kim Yeon-Wook , Lee Sangmin
Published: December 2022

This paper proposes a data valuation algorithm for inertial measurement unit-based human activity recognition (IMU-based HAR) data based on meta reinforcement learning. Unlike previous studies that received feature-level input, the algorithm in this study added a feature extraction structure to the data valuation algorithm, and it can receive raw-level inputs and achieve excellent performance. As IMU-based HAR data are multivariate time-series data, the proposed algorithm incorporates an architecture capable of extracting both local and global features by inserting a transformer encoder after the one-dimensional convolutional neural network (1D-CNN) backbone in the data value estimator. In addition, the 1D-CNN-based stacking ensemble structure, which exhibits excellent efficiency and performance on IMU-based HAR data, is used as a predictor to supervise model training. The Berg balance scale (BBS) IMU-based HAR dataset and the public datasets, UCI-HAR, WISDM, and PAMAP2, are used for performance evaluation in this study. The valuation performance of the proposed algorithm is observed to be excellent on IMU-based HAR data. The rate of discovering corrupted data is higher than 96% on all datasets. In addition, classification performance is confirmed to be improved by the suppression of discovery of low-value data.
Hourly Water Level Forecasting in an Hydroelectric Basin Using Spatial Interpolation and Artificial Intelligence
Authors: Tucci Mauro
Published: December 2022

In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were used to learn the model: a number of weather stations, satellite observations, the reanalysis dataset, and basin data. With the goal of predicting the water level of the basin, the model was composed by three cascade modules. Firstly, different spatial interpolation methods, such as Kriging, Radial Basis Function, and Natural Neighbours, were compared and applied to interpolate the weather stations data nearby the basin area to infer the main environmental variables (air temperature, air humidity, precipitation, and wind speed) in the basin area. Then, using these variables as inputs, a neural network was trained to predict the mean soil moisture concentration over the area, also to improve the low availability due to satellite orbits. Finally, a non-linear auto regressive exogenous input (NARX) model was trained to simulate the basin level with different prediction horizons, using the data from the previous modules and past basin data (water level, discharge flow rate, and turbine flow rate). Accurate predictions of the basin water level were achieved within 1 to 6 h ahead, with mean absolute errors (MAE) between 2 cm and 10 cm, respectively.
Shared-Weight-Based Multi-Dimensional Feature Alignment Network for Oriented Object Detection in Remote Sensing Imagery
Authors: Hu Xinxin , Zhu Changming
Published: December 2022

Arbitrarily Oriented Object Detection in aerial images is a highly challenging task in computer vision. The mainstream methods are based on the feature pyramid, while for remote-sensing targets, the misalignment of multi-scale features is always a thorny problem. In this article, we address the feature misalignment problem of oriented object detection from three dimensions: spatial, axial, and semantic. First, for the spatial misalignment problem, we design an intra-level alignment network based on leading features that can synchronize the location information of different pyramid features by sparse sampling. For multi-oriented aerial targets, we propose an axially aware convolution to solve the mismatch between the traditional sampling method and the orientation of instances. With the proposed collaborative optimization strategy based on shared weights, the above two modules can achieve coarse-to-fine feature alignment in spatial and axial dimensions. Last but not least, we propose a hierarchical-wise semantic alignment network to address the semantic gap between pyramid features that can cope with remote-sensing targets at varying scales by endowing the feature map with global semantic perception across pyramid levels. Extensive experiments on several challenging aerial benchmarks show state-of-the-art accuracy and appreciable inference speed. Specifically, we achieve a mean Average Precision (mAP) of 78.11% on DOTA, 90.10% on HRSC2016, and 90.29% on UCAS-AOD.
Temperature Field Reconstruction Method for Acoustic Tomography Based on Multi-Dictionary Learning
Authors: Wei Yuankun , Yan Hua , Zhou Yinggang
Published: December 2022

A reconstruction algorithm is proposed, based on multi-dictionary learning (MDL), to improve the reconstruction quality of acoustic tomography for complex temperature fields. Its aim is to improve the under-determination of the inverse problem by the sparse representation of the sound slowness signal (i.e., reciprocal of sound velocity). In the MDL algorithm, the K-SVD dictionary learning algorithm is used to construct corresponding sparse dictionaries for sound slowness signals of different types of temperature fields; the KNN peak-type classifier is employed for the joint use of multiple dictionaries; the orthogonal matching pursuit (OMP) algorithm is used to obtain the sparse representation of sound slowness signal in the sparse domain; then, the temperature distribution is obtained by using the relationship between sound slowness and temperature. Simulation and actual temperature distribution reconstruction experiments show that the MDL algorithm has smaller reconstruction errors and provides more accurate information about the temperature field, compared with the compressed sensing and improved orthogonal matching pursuit (CS-IMOMP) algorithm, which is an algorithm based on compressed sensing and improved orthogonal matching pursuit (in the CS-IMOMP, DFT dictionary is used), the least square algorithm (LSA) and the simultaneous iterative reconstruction technique (SIRT).
Wireless Capacitive Liquid-Level Detection Sensor Based on Zero-Power RFID-Sensing Architecture
Authors: Ahmad Shaheen , Khosravi Ramin , Iyer Ashwin K. , Mirzavand Rashid
Published: December 2022

In this paper, a new method for the wireless detection of liquid level is proposed by integrating a capacitive IDC-sensing element with a passive three-port RFID-sensing architecture. The sensing element transduces changes in the liquid level to corresponding fringe-capacitance variations, which alters the phase of the RFID backscattered signal. Variation in capacitance also changes the resonance magnitude of the sensing element, which is associated with a high phase transition. This change in the reactive phase is used as a sensing parameter by the RFID architecture for liquid-level detection. Practical measurements were conducted in a real-world scenario by placing the sensor at a distance of approximately 2 m (with a maximum range of about 7 m) from the RFID reader. The results show that the sensor node offers a high sensitivity of 2.15°/mm to the liquid-level variation. Additionally, the sensor can be used within or outside the container for the accurate measurement of conductive- or non-conductive-type liquids due to the use of polyethylene coating on the sensitive element. The proposed sensor increases the reliability of the current level sensors by eliminating the internal power source as well as complex signal-processing circuits, and it offers real-time response, linearity, high sensitivity, and excellent repeatability, which are suitable for widespread deployment of sensor node applications.
Calibration of a Stereoscopic Vision System in the Presence of Errors in Pitch Angle
Authors: Felipe Jonatán , Sigut Marta , Acosta Leopoldo
Published: December 2022

This paper proposes a novel method for the calibration of a stereo camera system used to reconstruct 3D scenes. An error in the pitch angle of the cameras causes the reconstructed scene to exhibit some distortion with respect to the real scene. To do the calibration procedure, whose purpose is to eliminate or at least minimize said distortion, machine learning techniques have been used, and more specifically, regression algorithms. These algorithms are trained with a large number of vectors of input features with their respective outputs, since, in view of the application of the procedure proposed, it is important that the training set be sufficiently representative of the variety that can occur in a real scene, which includes the different orientations that the pitch angle can take, the error in said angle and the effect that all this has on the reconstruction process. The most efficient regression algorithms for estimating the error in the pitch angle are derived from decision trees and certain neural network configurations. Once estimated, the error can be corrected, thus making the reconstructed scene appear more like the real one. Although the authors base their method on U-V disparity and employ this same technique to completely reconstruct the 3D scene, one of the most interesting features of the method proposed is that it can be applied regardless of the technique used to carry out said reconstruction.