bluuebunny/crossref_metadata_2025 huggingface dataset:
A Collection of Molecular Fingerprints of Single Aerosol Particles in Air for Potential Identification and Detection Using Optical Trapping-Raman Spectroscopy
Authors: Alali Haifa , Ai Yukai , Pan Yong-Le , Videen Gorden , Wang Chuji
Published: September 2022

Characterization, identification, and detection of aerosol particles in their native atmospheric states remain a challenge. Recently, optical trapping-Raman spectroscopy (OT-RS) has been developed and demonstrated for characterization of single, airborne particles. Such particles in different chemical groups have been characterized by OT-RS in recent years and many more are being studied. In this work, we collected single-particle Raman spectra measured using the OT-RS technique and began construction of a library of OT-RS fingerprints that may be used as a reference for potential detection and identification of aerosol particles in the atmosphere. We collected OT-RS fingerprints of aerosol particles from eight different categories including carbons, bioaerosols (pollens, fungi, vitamins, spores), dusts, biological warfare agent surrogates, etc. Among the eight categories, spectral fingerprints of six groups of aerosol particles have been published previously and two other groups are new. We also discussed challenges, limitations, and advantages of using single-particle optical trapping-Raman spectroscopy for aerosol-particle characterization, identification, and detection.
The Contribution of Design Thinking to Museum Digital Transformation in Post-Pandemic Times
Authors: Mason Marco
Published: September 2022

With this article, I would like to present a critical examination of my position on the role of design in museums by focusing on the influence of human-centred design practices (also known as design thinking) in the context of digital transformation in museums, a transformation that has been accelerated by two years of the COVID-19 pandemic and its restrictions. The article aims to offer a set of propositions about the contribution of design thinking (DT) to the main challenges museums are facing in a moment of digital transformation. A rigorous evaluation of the value of DT on museums is beyond the scope of this article, however, there is a sufficient body of academic and professional literature to hypothesise the contribution of DT in addressing digital transformation challenges. My argumentation is supported by evidence from the literature review in the museum sector and academia. Firstly, through a critical examination of facts (museum initiatives during the pandemic) and a critical reflection of existing literature, I will identify a set of key museum challenges. Secondly, by critically looking at design literature, I will suggest a set of propositions by discussing the contribution of DT practices in addressing those challenges.
Nanoparticles of Mixed-Valence Oxides MnXCO3-XO4 (0 ≤ X ≤ 1) Obtained with Agar-Agar from Red Algae (Rhodophyta) for Oxygen Evolution Reaction
Authors: Santos Jakeline Raiane D. , Raimundo Rafael A. , Silva Thayse R. , Silva Vinícius D. , Macedo Daniel A. , Loureiro Francisco J. A. , Torres Marco A. M. , Tonelli Domenica , Gomes Uílame U.
Published: September 2022

The development of efficient electrocatalysts for the oxygen evolution reaction (OER) is of paramount importance in sustainable water-splitting technology for hydrogen production. In this context, this work reports mixed-valence oxide samples of the MnXCo3-XO4 type (0 ≤ X ≤ 1) synthesized for the first time by the proteic sol-gel method using Agar-Agar as a polymerizing agent. The powders were calcined at 1173 K, characterized by FESEM, XRD, RAMAN, UV–Vis, FT-IR, VSM, and XPS analyses, and were investigated as electrocatalysts for the oxygen evolution reaction (OER). Through XRD analysis, it was observed that the pure cubic phase was obtained for all samples. The presence of Co3+, Co2+, Mn2+, Mn3+, and Mn4+ was confirmed by X-ray spectroscopy (XPS). Regarding the magnetic measurements, a paramagnetic behavior at 300 K was observed for all samples. As far as OER is concerned, it was investigated in an alkaline medium, where the best overpotential of 299 mV vs. RHE was observed for the sample (MnCo2O4), which is a lower value than those of noble metal electrocatalysts in the literature, together with a Tafel slope of 52 mV dec−1, and excellent electrochemical stability for 15 h. Therefore, the green synthesis method presented in this work showed great potential for obtaining electrocatalysts used in the oxygen evolution reaction for water splitting.
Multi-Junction Solar Cells and Nanoantennas
Authors: De Melo Cunha João P. , Marques Lameirinhas Ricardo A. , N. Torres João Paulo
Published: September 2022

Photovoltaic technology is currently at the heart of the energy transition in our pursuit to lean off fossil-fuel-based energy sources. Understanding the workings and trends of the technology is crucial, given the reality. With most conventional PV cells constrained by the Shockley–Queisser limit, new alternatives have been developed to surpass it. One of such variations are heterojunction cells, which, by combining different semiconductor materials, break free from the previous constraint, leveraging the advantages of both compounds. A subset of these cells are multi-junction cells, in their various configurations. These build upon the heterojunction concept, combining several junctions in a cell—a strategy that has placed them as the champions in terms of conversion efficiency. With the aim of modelling a multi-junction cell, several optic and optoelectronic models were developed using a Finite Element Tool. Following this, a study was conducted on the exciting and promising technology that are nanoantenna arrays, with the final goal of integrating both technologies. This research work aims to study the impact of the nanoantennas’ inclusion in an absorbing layer. It is concluded that, using nanoantennas, it is possible to concentrate electromagnetic radiation near their interfaces. The field’s profiles might be tuned using the nanoantennas’ geometrical parameters, which may lead to an increase in the obtained current.
Modern Synthesis and Sintering Techniques of Calcium Copper Titanium Oxide (CaCu3Ti4O12) Ceramics and Its Current Trend in Prospective Applications: A Mini-Review
Authors: T. Gecil Evangeline , Annamalai A. Raja , Magdaline T. Bonnisa
Published: September 2022

Calcium Copper Titanium Oxide (CaCu3Ti4O12/CCTO) has grasped massive attention for its colossal dielectric constant in high operating frequencies and wide temperature range. However, the synthesis and processing of CCTO directly influence the material’s properties, imparting the overall performance. Researchers have extensively probed into these downsides, but the need for a new and novel approach has been in high demand. Modern synthesis routes and advanced non-conventional sintering techniques have been employed to curb the drawbacks for better properties and performance. This review provides a short overview of the modern synthesis and sintering methods that utilize direct pulse current and electromagnetic waves to improve the material’s electrical, optical, and dielectric properties in the best ways possible. In addition, the current application of CCTO as a photocatalyst under visible light and CuO’s role in the efficient degradation of pollutants in replacement for other metal oxides has been reviewed. This research also provides a brief overview of using CCTO as a photoelectrode in zinc–air batteries (ZAB) to improve the Oxidation-reduction and evolution (ORR/OER) reactions.
Genomic Islands Shape the Genetic Background of Both JP2 and Non-JP2 Aggregatibacter actinomycetemcomitans
Authors: Kittichotirat Weerayuth , Bumgarner Roger E. , Chen Casey
Published: September 2022

Aggregatibacter actinomycetemcomitans is a periodontal pathogen associated with periodontitis. This species exhibits substantial variations in gene content among different isolates and has different virulence potentials. This study examined the distribution of genomic islands and their insert sites among genetically diverse A. actinomycetemcomitans strains by comparative genomic analysis. The results showed that some islands, presumably more ancient, were found across all genetic clades of A. actinomycetemcomitans. In contrast, other islands were specific to individual clades or a subset of clades and may have been acquired more recently. The islands for the biogenesis of serotype-specific antigens comprise distinct genes located in different loci for serotype a and serotype b–f strains. Islands that encode the same cytolethal distending toxins appear to have been acquired via distinct mechanisms in different loci for clade b/c and for clade a/d/e/f strains. The functions of numerous other islands remain to be elucidated. JP2 strains represent a small branch within clade b, one of the five major genetic clades of A. actinomycetemcomitans. In conclusion, the complex process of genomic island acquisition, deletion, and modification is a significant force in the genetic divergence of A. actinomycetemcomitans. Assessing the genetic distinctions between JP2 and non-JP2 strains must consider the landscape of genetic variations shaped by evolution.
Determinants of Virus Variation, Evolution, and Host Adaptation
Authors: LaTourrette Katherine , Garcia-Ruiz Hernan
Published: September 2022

Virus evolution is the change in the genetic structure of a viral population over time and results in the emergence of new viral variants, strains, and species with novel biological properties, including adaptation to new hosts. There are host, vector, environmental, and viral factors that contribute to virus evolution. To achieve or fine tune compatibility and successfully establish infection, viruses adapt to a particular host species or to a group of species. However, some viruses are better able to adapt to diverse hosts, vectors, and environments. Viruses generate genetic diversity through mutation, reassortment, and recombination. Plant viruses are exposed to genetic drift and selection pressures by host and vector factors, and random variants or those with a competitive advantage are fixed in the population and mediate the emergence of new viral strains or species with novel biological properties. This process creates a footprint in the virus genome evident as the preferential accumulation of substitutions, insertions, or deletions in areas of the genome that function as determinants of host adaptation. Here, with respect to plant viruses, we review the current understanding of the sources of variation, the effect of selection, and its role in virus evolution and host adaptation.
Canine Leptospirosis in a Northwestern Region of Colombia: Serological, Molecular and Epidemiological Factors
Authors: Perez-Garcia Janeth , Monroy Fernando P. , Agudelo-Florez Piedad
Published: September 2022

Canine leptospirosis is a zoonosis of epidemiological importance. Dogs are recognized as primary reservoirs of Leptospira interrogans serogroup Canicola and a source of infection to the environment through urine. This study aimed to determine the presence of antibodies against Leptospira in canines from 49 municipalities in the Department of Antioquia, Colombia. We performed a cross-sectional study of dogs included in a neutering control program. We collected 1335 sera samples, assayed by a microagglutination test (MAT), and performed PCR detection in 21 urine samples. We also surveyed 903 dog owners. We found a seroreactivity of 11.2% (150/1335) in Antioquia with titers ≥1:50. Municipalities with the highest number of cases were Belmira (46.1%), Turbo (34.5%), and Concepción (31.0%). L. santarosai was identified by phylogenetic analysis in one urine sample from the municipality of Granada. The most important factor associated with a positive result was the lack of vaccination against leptospirosis (PR 3.3, p ≤ 0.014). Environmental factors such as water presence and bare soil around the household were also associated with Leptospira seroreactivity in the Department of Antioquia. We reviewed a national epidemiological surveillance database for human cases in those municipalities. We found a correlation between the high number of cases in canines and humans, especially in the Uraba. Serological and molecular results showed the circulation of Leptospira. Future public health efforts in the municipalities with the highest numbers of seroreactivity should be directed towards vaccination to prevent animal disease and decrease the probability of transmission of Leptospira. Dogs actively participate in the Leptospira cycle in Antioquia and encourage the implementation of vaccination protocols and coverage.
What Has Happened to Heartworm Disease in Europe in the Last 10 Years?
Authors: Morchón Rodrigo , Montoya-Alonso José Alberto , Rodríguez-Escolar Iván , Carretón Elena
Published: September 2022

Heartworm disease caused by Dirofilaria immitis is a vector-borne disease that affects canids and felids, both domestic and wild, throughout the world. It is a chronic disease which causes vascular damage in pulmonary arteries, and in advanced stages, the presence of pulmonary hypertension and right-sided congestive heart failure can be evidenced. Moreover, pulmonary thromboembolism is caused by the death of the worms, which can be lethal for the infected animal. Furthermore, it is the causative agent of human pulmonary dirofilariosis, being a zoonotic disease. The aim of this review was to update the current epidemiological situation of heartworm in Europe in dogs, cats, wild animals, and vectors insects, and to analyse the factors that may have contributed to the continuous spread of the disease in the last decade (2012–2021). In Europe, the disease has extended to eastern countries, being currently endemic in countries where previously only isolated or imported cases were reported. Furthermore, its prevalence has continued to increase in southern countries, traditionally endemic. This distribution trends and changes are influenced by several factors which are discussed in this review, such as the climate changes, presence of vectors in new areas, the appearance of new competent vector species in the continent, increased movement of pets that travelled to or originated from endemic countries, the urbanisation of rural areas leading to the formation of so-called “heat islands”, or the creation of extensive areas of irrigated crops. The continuous expansion of D. immitis must be monitored, and measures adapted to the situation of each country must be carried out for adequate control.
Designing an Inclusive Learning Training Series for Pharmacy Educators
Authors: McLaughlin Jacqueline E. , Morbitzer Kathryn A. , Volkmar Bethany , Harris Suzanne C. , Williams Charlene R. , Wolcott Michael D. , Jarstfer Michael B. , White Carla Y.
Published: September 2022

This article describes the design, implementation, and evaluation of five faculty development sessions focused on inclusive teaching strategies in pharmacy education. Inclusive strategies ensure that every student can clearly understand and engage in meaningful learning opportunities. Three sessions were implemented in fall 2020 and two in spring 2021. Sessions focused on experiential, didactic, and graduate education. A convergent parallel mixed methods evaluation was conducted using descriptive statistics and thematic analysis. Sessions were highly rated, and participants provided suggestions for curriculum improvement (e.g., creating resources, surveying students, and peer auditing syllabi for aspects of inclusiveness). Given the increasing emphasis on inclusion in pharmacy education, this work is timely for sharing strategies aimed at faculty development and teaching practices.
Evidence of Asexual Overwintering of Melampsora paradoxa and Mapping of Stem Rust Host Resistance in Salix
Authors: Crowell Chase R. , Wilkerson Dustin G. , Smart Lawrence B. , Smart Christine D.
Published: September 2022

Melampsora rust is a devastating disease of shrub willow in North America. Previous work has identified Melampsora paradoxa as one of two identified rust species in New York State that infect Salix purpurea and other important Salix host species, however little is known about the population of this rust species in this region. Genotyping-by-sequencing was used to identify single nucleotide polymorphisms (SNPs) and assess population diversity of M. paradoxa isolates collected from three Salix breeding populations in Geneva, NY between 2015 and 2020. Statistical analyses of SNP revealed that all isolates collected were clonally derived even though they were collected across years. In 2020, isolates were collected from stem infections where uredospore pustules were observed, and these isolates were also identical to M. paradoxa collected in previous seasons. These data suggest that M. paradoxa sampled across multiple years overwintered and reproduced asexually and that stem infection is a possible mechanism for overwintering, both of which are novel findings for this rust species. Additionally, field disease ratings were conducted on a S. purpurea × S. suchowensis F1 breeding population with high disease severity, enabling the discovery of QTL for resistance on chromosomes 1 and 19. Lastly, Colletotrichum salicis was frequently associated with stem rust and may play a role in M. paradoxa stem infection. Together, this work is the first substantial exploration into M. paradoxa population biology, stem infection, and host resistance in Salix.
Advancement in the Breeding, Biotechnological and Genomic Tools towards Development of Durable Genetic Resistance against the Rice Blast Disease
Authors: Sahu Parmeshwar K. , Sao Richa , Choudhary Devendra K. , Thada Antra , Kumar Vinay , Mondal Suvendu , Das Bikram K. , Jankuloski Ljupcho , Sharma Deepak
Published: September 2022

Rice production needs to be sustained in the coming decades, as the changeable climatic conditions are becoming more conducive to disease outbreaks. The majority of rice diseases cause enormous economic damage and yield instability. Among them, rice blast caused by Magnaportheoryzae is a serious fungal disease and is considered one of the major threats to world rice production. This pathogen can infect the above-ground tissues of rice plants at any growth stage and causes complete crop failure under favorable conditions. Therefore, management of blast disease is essentially required to sustain global food production. When looking at the drawback of chemical management strategy, the development of durable, resistant varieties is one of the most sustainable, economic, and environment-friendly approaches to counter the outbreaks of rice blasts. Interestingly, several blast-resistant rice cultivars have been developed with the help of breeding and biotechnological methods. In addition, 146 R genes have been identified, and 37 among them have been molecularly characterized to date. Further, more than 500 loci have been identified for blast resistance which enhances the resources for developing blast resistance through marker-assisted selection (MAS), marker-assisted backcross breeding (MABB), and genome editing tools. Apart from these, a better understanding of rice blast pathogens, the infection process of the pathogen, and the genetics of the immune response of the host plant are very important for the effective management of the blast disease. Further, high throughput phenotyping and disease screening protocols have played significant roles in easy comprehension of the mechanism of disease spread. The present review critically emphasizes the pathogenesis, pathogenomics, screening techniques, traditional and molecular breeding approaches, and transgenic and genome editing tools to develop a broad spectrum and durable resistance against blast disease in rice. The updated and comprehensive information presented in this review would be definitely helpful for the researchers, breeders, and students in the planning and execution of a resistance breeding program in rice against this pathogen.
Solvent-Free Production by Extrusion of Bio-Based Poly(glycerol-co-diacids) Sheets for the Development of Biocompatible and Electroconductive Elastomer Composites
Authors: Ji Shengzhi , Stricher Mathilde , Nadaud Frédéric , Guenin Erwann , Egles Christophe , Delbecq Frédéric
Published: September 2022

Faced with growing global demand for new potent, bio-based, biocompatible elastomers, the present study reports the solvent-free production of 13 pure and derived poly(glycerol-co-diacid) composite sheets exclusively using itaconic acid, sebacic acid, and 2,5-furandicarboxylic acid (FDCA) with glycerol. Herein, modified melt polycondensation and Co(II)-catalyzed polytransesterification were employed to produce all exploitable prepolymers, enabling the easy and rapid manufacturing of elastomer sheets by extrusion. Most of our samples were loaded with 4 wt% of various additives such as natural polysaccharides, synthetic polymers, and/or 25 wt% sodium chloride as porogen agents. The removal of unreacted monomers and acidic short oligomers was carried out by means of washing with NaHCO3 aqueous solution, and pH monitoring was conducted until efficient sheet surface neutralization. For each sheet, their surface morphologies were observed by Field-emission microscopy, and DSC was used to confirm their amorphous nature and the impact of the introduction of every additive. The chemical constitution of the materials was monitored by FTIR. Then, cytotoxicity tests were performed for six of our most promising candidates. Finally, we achieved the production of two different types of extrusion-made PGS elastomers loaded with 10 wt% PANI particulates and 4 wt% microcrystalline cellulose for adding potential electroconductivity and stability to the material, respectively. In a preliminary experiment, we showed the effectiveness of these materials as performant, time-dependent electric pH sensors when immersed in a persistent HCl atmosphere.
Research on Discrete Artificial Bee Colony Cache Strategy of UAV Edge Network
Authors: Hong Yang , Zhang Yuexia , Fan Shaoshuai
Published: September 2022

Unmanned aerial vehicle edge networks (UENs) can reduce the cache load of the core network and improve system performance to provide users with efficient content services. However, the time-varying characteristics of content popularity in UENs lead to a low accuracy of popularity prediction, and the capacity limitations of wireless channel conditions lead to a lower cache hit rate than the rates of traditional fiber-optic-based cache strategies. Therefore, this paper proposes the discrete artificial bee colony cache strategy of UENs (DABCCSU). First, the information–dynamics–dissemination model of UENs (IDDMU) is established to deduce the coupling relationship between the channel capacity and the service probability in IDDMU. The influence of the service probability change on the content dissemination process is discussed, and the content popularity in UENs is predicted by the state iteration matrix. Then, the discrete artificial bee colony cache (DABCC) optimization algorithm is proposed. The action function of the artificial bee colony is designed as a random action based on the historical cache strategy. The discrete cache strategy is used as an optimization variable, and the popularity prediction result obtained by IDDMU is used to maximize the cache hit rate. DABCC provides the optimal cache strategy for the UENs, and effectively improves the cache hit rate. The simulation result shows that the accuracy of DABCCSU in content popularity prediction is more than 90%, which achieves a good prediction effect. In terms of cache performance, the average cache hit rate of DABCCSU is 91.62%, which is better than the 51.09% of the Least Recently Used (LRU) strategy, 89.27% of the Greedy Algorithm (GA) and 54.26% of Binary Particle Swarm Optimization (BPSO). In addition, the cache hit rate of DABCCSU under different cache capacities is better than that of LRU, GA, and BPSO, showing a relatively stable performance. It shows that DABCCSU can achieve excellent content popularity prediction, and it can also maximize the cache hit rate under limited communication resources and cache resources to provide UENs with the optimal content cache strategy, and provides users with high-quality content services.
Optimization Strategy of Hybrid Configuration for Volatility Energy Storage System in ADN
Authors: Lei Guoping , Huang Yinhua , Dai Nina , Cai Li , Deng Li , Li Shenghao , He Chao
Published: September 2022

This study aims to address the issues of volatile energy access to the active distribution network (ADN), which are the difficulty of frequency regulation, the increased voltage deviation of the ADN, the decrease in operational security and stability, etc. In this study, a two-stage majorization configuration model is established to identify and understand how volatility energy affects a hybrid energy storage system (HESS). The ADN and HESS with lead-acid batteries and supercapacitors (SC) are examined using day forecast data for wind, solar, and load. In this planning stage, the integrated cost, network loss, and node voltage deviation are considered as optimal objectives in a multi-objective optimization model, while the revised multi-objective optimization particle swarm approach is used to solve the initial value of capacity configuration. In the operation stage, optimizing objectives like wind output power fluctuations, the frequency deviation of HESS is used to solve the modified value of the configuration capabilities of the SC, and the output of different types of units in ADN is further optimized by the quantum particle swarm with the addition of a chaotic mechanism. The simulation study is conducted to determine the best configuration result based on case 33 node examples, and the simulation results demonstrate the model’s viability.
Corporate Social Responsibility in the Telecommunication Industry—Driver of Entrepreneurship
Authors: Raimi Lukman , Panait Mirela , Grigorescu Adriana , Vasile Valentina
Published: September 2022

Beyond the conventional understanding of corporate social responsibility (CSR) as a voluntary obligation for promoting triple-bottom-line CSR, development-oriented CSR is emerging and requires empirical investigation. This organisation-level research fills this gap by exploring development-oriented CSR as a driver of entrepreneurship in Nigeria. Arising from the review of the literature, human capital theory and stakeholder theory provided theoretical groundings for the study. The empirical study provides an enhanced understanding of development-oriented CSR that incorporates entrepreneurship into the extant literature. The target comprised multiple stakeholders in the Nigerian telecommunication industry, from which a sample of 369 responses were analysed using descriptive and inferential statistics. The five tested hypotheses showed mixed results. The stakeholder management and economic dimensions of development-oriented CSR were found to have significant positive effects on entrepreneurship. However, the environmental, national, and social dimensions do not have significant positive effects on entrepreneurship. Overall, it was found that development-oriented CSR is a potential driver of entrepreneurship in the Nigerian telecommunication industry, but the predictability is weak (15%). The study concludes with practical implications and recommendations for further research in this multidisciplinary field.
Dances with Social Robots: A Pilot Study at Long-Term Care
Authors: Li Yizhu , Liang Nan , Effati Meysam , Nejat Goldie
Published: September 2022

Dance therapy can have significant physical, emotional and cognitive benefits for older adults. In particular, social robots can be developed to autonomously facilitate dance sessions to engage these individuals with the aim of improving quality of life. To successfully integrate and promote long-term use of social robots into long-term care homes for such recreational activities, it is important to explore both residents’ and staff’s perceptions of such robots. In this paper, we present the first pilot human–robot interaction study that investigates the overall experiences and attitudes of both residents and staff in a long-term care home for robot-facilitated dance sessions. In general, the questionnaire results from our study showed that both staff and residents had positive attitudes towards the robot-facilitated dance activity. Encouraging trends showed residents had higher ratings for statements on perceived ease of use, safety, and enjoyment than the staff. However, the staff had a statistically significantly higher rating for willingness to use the robots for dance facilitation. Some key statistical differences were also determined with respect to: (1) gender within the resident group (men had higher ratings for the robots being useful in helping facilitate recreational activities), as well as between staff and residents (resident men had higher perceived safety), and (2) prior robot experience (residents with limited prior experience had higher ratings on perceived ease of use and perceived enjoyment than staff with the same level of experience). The robot-facilitated dance activity was positively received by both older adults and staff as an activity of daily living that can enhance wellbeing while also being safe, easy to use and enjoyable.
Low-Light Image Enhancement Using Hybrid Deep-Learning and Mixed-Norm Loss Functions
Authors: Oh JongGeun , Hong Min-Cheol
Published: September 2022

This study introduces a low-light image enhancement method using a hybrid deep-learning network and mixed-norm loss functions, in which the network consists of a decomposition-net, illuminance enhance-net, and chroma-net. To consider the correlation between R, G, and B channels, YCbCr channels converted from the RGB channels are used for training and restoration processes. With the luminance, the decomposition-net aims to decouple the reflectance and illuminance and to train the reflectance, leading to a more accurate feature map with noise reduction. The illumination enhance-net connected to the decomposition-net is used to enhance the illumination such that the illuminance is improved with reduced halo artifacts. In addition, the chroma-net is independently used to reduce color distortion. Moreover, a mixed-norm loss function used in the training process of each network is described to increase the stability and remove blurring in the reconstructed image by reflecting the properties of reflectance, illuminance, and chroma. The experimental results demonstrate that the proposed method leads to promising subjective and objective improvements over state-of-the-art deep-learning methods.
Noise-Adaptive Non-Blind Image Deblurring
Authors: Slutsky Michael
Published: September 2022

This work addresses the problem of non-blind image deblurring for arbitrary input noise. The problem arises in the context of sensors with strong chromatic aberrations, as well as in standard cameras, in low-light and high-speed scenarios. A short description of two common classical approaches to regularized image deconvolution is provided, and common issues arising in this context are described. It is shown how a pre-deconvolved deep neural network (DNN) based image enhancement can be improved by joint optimization of regularization parameters and network weights. Furthermore, a two-step approach to deblurring based on two DNNs is proposed, with the first network estimating deconvolution regularization parameters, and the second one performing image enhancement and residual artifact removal. For the first network, a novel RegParamNet architecture is introduced and its performance is examined for both direct and indirect regularization parameter estimation. The system is shown to operate well for input noise in a three orders of magnitude range (0.01–10.0) and a wide spectrum of 1D or 2D Gaussian blur kernels, well outside the scope of most previously explored image blur and noise degrees. The proposed method is found to significantly outperform several leading state-of-the-art approaches.
A Design of Electromagnetic Velocity Sensor with High Sensitivity Based on Dual-Magnet Structure
Authors: Zhou Xiao , Ruan Yangfan , Mou Xingang , Yuan Yuhao , He Yi
Published: September 2022

The most permanent magnets in current electromagnetic velocity sensors are magnet cylinders that have been axially magnetized, with magnetic boots changing the propagation direction of the magnetic induction lines of the magnet cylinders. However, the magnetic field generated by the magnet cylinders is not fully utilized, which leads to uneven magnetic field intensity of the working air-gap and high magnetic field intensity of the nonworking air-gap. We propose a novel dual-magnet structure (DM) mainly consisting of two magnet loops that are magnetized radially and a magnetic conductive shaft, adopting a concentric nested configuration. The dual-magnet structure can make the magnetic induction lines enter the working air-gap directly from the magnet and increase the effective magnetic field, which is perpendicular to the coils in the working air-gap. This design can further improve the sensitivity of a velocity sensor and enhance its ability to detect weak signals in microtremor exploration. The validity of the dual-magnet structure has been established by numerical simulations and verified by experiments. The results reveal that the magnetic field intensity is increased by 29.18% and the sensitivity is improved by 23.9%, when the total volume and material of the magnet are unchanged. The full utilization of the material is achieved without increasing the complexity of the structure.
Case-Study-Based Overview of Methods and Technical Solutions of Analog and Digital Transmission in Measurement and Control Ship Systems
Authors: Abotaleb Mostafa , Mindykowski Janusz , Dudojc Boleslaw , Masnicki Romuald
Published: September 2022

The purpose of this article is to provide an overview of possible solutions to improve the performance of measurement and control processes in maritime engineering applications. This improvement can be basically provided by adopting techniques to enhance the reliability of measurement/control systems based on the 4–20 mA analogue standard. This aspect will be discussed through a Simscape Simulink model illustrating methods of noise and ground loops elimination for pressure measurement of a 4–20 mA current loop in the tank level measurement system on a bulk carrier commercial ship. Alternatively, improved measurement and control processes can be rendered by utilizing smart transmitters based on wired hybrid analogue–digital (Highway Addressable Remote Transducer (HART)), wired digital (Foundation Fieldbus (FF)) or wireless (wireless HART) communication protocols. A brief theoretical description of these protocols will be presented in this article. As an example of using smart transmitters, a simulation-based case study will analyze the possible options to implement non-intrinsically safe as well as intrinsically safe FF models for the tank level measurement system on a bulk carrier commercial ship. Conclusions obtained through analysis of the simulation results will characterize the behavior of FF segments in safe as well as explosive hazardous areas, highlighting the characteristics of field barriers and segment protectors used in conjunction with the HPTC (High-Power Trunk Concept) intrinsically safe model.
Model Checking Autonomous Components within Electric Power Systems Specified by Interpreted Petri Nets
Authors: Grobelna Iwona , Szcześniak Paweł
Published: September 2022

Autonomous components within electric power systems can be successfully specified by interpreted Petri nets. Such a formal specification makes it possible to check some basic properties of the models, such as determinism or deadlock freedom. In this paper, it is shown how these models can also be formally verified against some behavioral user-defined properties that relate to the safety or liveness of a designed system. The requirements are written as temporal logic formulas. The rule-based logical model is used to support the verification process. An interpreted Petri net is first written as an abstract logical model, and then automatically transformed into a verifiable model that is supplemented by appropriate properties for checking. Formal verification is then performed with the nuXmv model checker. Thanks to this the initial specification of autonomous components can be formally verified and any design errors can be identified at an early stage of system development. An electric energy storage (EES) is presented as an application system for the provision of a system service for stabilizing the power of renewable energy sources (RES) or highly variable loads. The control algorithm of EES in the form of an interpreted Petri net is then written as a rule-based logical model and transformed into a verifiable model, allowing automatic checking of user-defined requirements.
A Frequency Reconfigurable MIMO Antenna with Bandstop Filter Decoupling Network for Cognitive Communication
Authors: Islam Hashinur , Das Saumya , Ali Tanweer , Bose Tanushree , Prakash Om , Kumar Pradeep
Published: September 2022

A compact reconfigurable MIMO antenna was developed for cognitive radio applications in this research work. A bandstop filter-based decoupling network was employed in this MIMO antenna to keep mutual coupling at a minimum. A single PIN diode was connected in the filter configuration for the purpose of reconfiguration. Controlling the ON/OFF conditions of the PIN diode, it became possible to achieve a MIMO operating frequency of 4.75 GHz in mode 1 and 1.77 GHz in mode 2, respectively. At 4.75 GHz, isolation was 42.68 dB, while at 1.77 GHz, isolation was 26.52 dB. The proposed reconfigurable MIMO antenna achieved a peak gain and radiation efficiency of 6.63 dBi and 92.04 percent in mode 1 and 4.41 dBi and 89.64 percent in mode 2. MIMO characteristics such as an envelope correlation coefficient (ECC) less than 0.253, diversity gain (DG) greater than 9.675 dB, a mean effective gain (MEG) measurement ratio of less than 0.00388 dB, and channel capacity loss (CCL) of less than 0.06528 bits/s/Hz were measured for both operational frequency bands. To make it simple to integrate into small wireless devices, the overall size of the antenna is limited to 48 mm×24 mm 0.28 λ0×0.12 λ0.
Unsupervised Person Re-Identification with Attention-Guided Fine-Grained Features and Symmetric Contrast Learning
Authors: Wu Yongzhi , Yang Wenzhong , Wang Mengting
Published: September 2022

Unsupervised person re-identification has attracted a lot of attention due to its strong potential to adapt to new environments without manual annotation, but learning to recognise features in disjoint camera views without annotation is still challenging. Existing studies tend to ignore the optimisation of feature extractors in the feature-extraction stage of this task, while the use of traditional losses in the unsupervised learning stage severely affects the performance of the model. Additionally the use of a contrast learning framework in the latest methods uses only a single cluster centre or all instance features, without considering the correctness and diversity of the samples in the class, which affects the training of the model. Therefore, in this paper, we design an unsupervised person-re-identification framework called attention-guided fine-grained feature network and symmetric contrast learning (AFF_SCL) to improve the two stages in the unsupervised person-re-identification task. AFF_SCL focuses on learning recognition features through two key modules, namely the Attention-guided Fine-grained Feature network (AFF) and the Symmetric Contrast Learning module (SCL). Specifically, the attention-guided fine-grained feature network enhances the network’s ability to discriminate pedestrians by performing further attention operations on fine-grained features to obtain detailed features of pedestrians. The symmetric contrast learning module replaces the traditional loss function to exploit the information potential given by the multiple samples and maintains the stability and generalisation capability of the model. The performance of the USL and UDA methods is tested on the Market-1501 and DukeMTMC-reID datasets by means of the results, which demonstrate that the method outperforms some existing methods, indicating the superiority of the framework.
Textile-Based Wearable Sensor for Skin Hydration Monitoring
Authors: Jang Minju , Kim Ho-Dong , Koo Hyung-Jun , So Ju-Hee
Published: September 2022

This research describes a wearable skin hydration sensor based on cotton textile to determine the state of hydration within the skin via impedance analysis. The sensor structure comprises a textile substrate, thermoplastic over-layer, conductive patterns, and encapsulant, designed for stable and reliable monitoring of the skin’s impedance change in relation to hydration level. The porcine skin with different hydration levels was prepared as a model system of the skin, and the textile-based sensor carefully investigated the porcine skin samples’ impedance characteristics. The impedance study reveals that (1) the total impedance of skin decreases as its hydration level increases, and (2) the impedance of the stratum corneum and epidermis layers are more dominantly affected by the hydration level of the skin than the dermis layer. Even after repetitive bending cycles, the impedance data of skin measured by the sensor exhibit a reliable dependence on the skin hydration level, which validates the flexibility and durability of the sensor. Finally, it is shown that the textile-based skin hydration sensor can detect various body parts’ different hydration levels of human skin while maintaining a stable conformal contact with the skin. The resulting data are well-matched with the readings from a commercial skin hydration sensor.
Road User Exposure from ITS-5.9 GHz Vehicular Connectivity
Authors: Benini Martina , Parazzini Marta , Bonato Marta , Gallucci Silvia , Chiaramello Emma , Fiocchi Serena , Tognola Gabriella
Published: September 2022

This study addressed an important but not yet thoroughly investigated topic regarding human exposure to radio-frequency electromagnetic fields (RF-EMF) generated by vehicular connectivity. In particular, the study assessed, by means of computational dosimetry, the RF-EMF exposure in road users near a car equipped with vehicle-to-vehicle (V2V) communication antennas. The exposure scenario consisted of a 3D numerical model of a car with two V2V antennas, each fed with 1 W, operating at 5.9 GHz and an adult human model to simulate the road user near the car. The RF-EMF dose absorbed by the human model was calculated as the specific absorption rate (SAR), that is, the RF-EMF power absorbed per unit of mass. The highest SAR was observed in the skin of the head (34.7 mW/kg) and in the eyes (15 mW/kg); the SAR at the torso (including the genitals) and limbs was negligible or much lower than in the head and eyes. The SAR over the whole body was 0.19 mW/kg. The SAR was always well below the limits of human exposure in the 100 kHz–6 GHz band established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The proposed approach can be generalized to assess RF-EMF exposure in different conditions by varying the montage/number of V2V antennas and considering human models of different ages.
Kernel Function-Based Ambiguity Function and Its Application on DOA Estimation in Impulsive Noise
Authors: Dou Yuzi , Li Sen
Published: September 2022

To solve the problem that the traditional ambiguity function cannot well reflect the time-frequency distribution characteristics of linear frequency modulated (LFM) signals due to the presence of impulsive noise, two robust ambiguity functions: correntropy-based ambiguity function (CRAF) and fractional lower order correntropy-based ambiguity function (FLOCRAF) are defined based on the feature that correntropy kernel function can effectively suppress impulsive noise. Then these two robust ambiguity functions are used to estimate the direction of arrival (DOA) of narrowband LFM signal under an impulsive noise environment. Instead of the covariance matrix used in the ESPRIT algorithm by the spatial CRAF matrix and FLOCRAF matrix, the CRAF-ESPRIT and FLOCRAF-ESPRIT algorithms are proposed. Computer simulation results show that compared with the algorithms only using ambiguity function and the algorithms only using the correntropy kernel function-based correlation, the proposed algorithms using ambiguity function based on correntropy kernel function have good performance in terms of probability of resolution and estimation accuracy under various circumstances. Especially, the performance of the FLOCRAF-ESPRIT algorithm is better than the CRAF-ESPRIT algorithm in the environment of low generalized signal-to-noise ratio and strong impulsive noise.
Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network
Authors: Macdonald Fraser L. A. , Lepora Nathan F. , Conradt Jörg , Ward-Cherrier Benjamin
Published: September 2022

Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detection. The sensor incorporates an event-based vision system (mini-eDVS) into a low-form factor artificial fingertip (the NeuroTac). The processing of tactile information is performed through a Spiking Neural Network with unsupervised Spike-Timing-Dependent Plasticity (STDP) learning, and the resultant output is classified with a 3-nearest neighbours classifier. Edge orientations were classified in 10-degree increments while tapping vertically downward and sliding horizontally across the edge. In both cases, we demonstrate that the sensor is able to reliably detect edge orientation, and could lead to accurate, bio-inspired, tactile processing in robotics and prosthetics applications.
Discriminative Method for Crack Detection Signals in Balanced-Field Electromagnetic Technique Based on Amplitude-Phase Composite Figure
Authors: Li Jiayin , Yang Lijian , Zheng Wenxue , Liu Bin
Published: September 2022

The balanced-field electromagnetic technique is an effective in-line inspection method for pipeline cracks. To address the problem that the interference signal generated by the tilt jitter of the sensor during the detection process affects the judgment of cracks, this paper proposes a method to differentiate the crack detection signal from the sensor jitter signal by using an amplitude-phase composite figure. The generation principle of the detection signal was analyzed by using the mutual inductance model, and the amplitude-phase composite figure was constructed by using the components of the detection signal after quadrature demodulation. The feasibility of using the phase as a signal discrimination feature was illustrated by finite element simulations, and the characteristics of the amplitude-phase composite figure were determined. The validity of the proposed method was verified experimentally. The results show that the crack detection signal and the signal generated by the sensor jitter are of the same frequency with similar waveforms and significantly different phases. The phase base value of the crack detection signal ranges from 35° to 55°, and the phase base value of the jitter signal is −4°. In terms of the characteristics of the amplitude-phase composite figure, the crack detection signal distribution is symmetrical about the origin in the first and third quadrants, and the axial crack is closer to the Y-axis than the circumferential crack; the jitter signal is distributed in the second and fourth quadrants and has a very small angle to the X-axis. In addition, the proposed method effectively weakens the observation of the phase noise region in the detection signal of the balanced-field electromagnetic technique.