bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectral-Based Classification of Genetically Differentiated Groups in Spring Wheat Grown under Contrasting Environments
Authors: Ballesta Paulina , Maldonado Carlos , Mora-Poblete Freddy , Mieres-Castro Daniel , del Pozo Alejandro , Lobos Gustavo A.
Published: January 2023

The global concern about the gap between food production and consumption has intensified the research on the genetics, ecophysiology, and breeding of cereal crops. In this sense, several genetic studies have been conducted to assess the effectiveness and sustainability of collections of germplasm accessions of major crops. In this study, a spectral-based classification approach for the assignment of wheat cultivars to genetically differentiated subpopulations (genetic structure) was carried out using a panel of 316 spring bread cultivars grown in two environments with different water regimes (rainfed and fully irrigated). For that, different machine-learning models were trained with foliar spectral and genetic information to assign the wheat cultivars to subpopulations. The results revealed that, in general, the hyperparameters ReLU (as the activation function), adam (as the optimizer), and a size batch of 10 give neural network models better accuracy. Genetically differentiated groups showed smaller differences in mean wavelengths under rainfed than under full irrigation, which coincided with a reduction in clustering accuracy in neural network models. The comparison of models indicated that the Convolutional Neural Network (CNN) was significantly more accurate in classifying individuals into their respective subpopulations, with 92 and 93% of correct individual assignments in water-limited and fully irrigated environments, respectively, whereas 92% (full irrigation) and 78% (rainfed) of cultivars were correctly assigned to their respective classes by the multilayer perceptron method and partial least squares discriminant analysis, respectively. Notably, CNN did not show significant differences between both environments, which indicates stability in the prediction independent of the different water regimes. It is concluded that foliar spectral variation can be used to accurately infer the belonging of a cultivar to its respective genetically differentiated group, even considering radically different environments, which is highly desirable in the context of crop genetic resources management.
Effect of Duration of LED Lighting on Growth, Photosynthesis and Respiration in Lettuce
Authors: Yudina Lyubov , Sukhova Ekaterina , Gromova Ekaterina , Mudrilov Maxim , Zolin Yuriy , Popova Alyona , Nerush Vladimir , Pecherina Anna , Grishin Andrey A. , Dorokhov Artem A. , Sukhov Vladimir
Published: January 2023

Parameters of illumination including the spectra, intensity, and photoperiod play an important role in the cultivation of plants under greenhouse conditions, especially for vegetables such as lettuce. We previously showed that illumination by a combination of red, blue, and white LEDs with a high red light intensity, was optimal for lettuce cultivation; however, the effect of the photoperiod on lettuce cultivation was not investigated. In the current work, we investigated the influence of photoperiod on production (total biomass and dry weight) and parameters of photosynthesis, respiration rate, and relative chlorophyll content in lettuce plants. A 16 h (light):8 h (dark) illumination regime was used as the control. In this work, we investigated the effect of photoperiod on total biomass and dry weight production in lettuce plants as well as on photosynthesis, respiration rate and chlorophyll content. A lighting regime 16:8 h (light:dark) was used as control. A shorter photoperiod (8 h) decreased total biomass and dry weight in lettuce, and this effect was related to the suppression of the linear electron flow caused by the decreasing content of chlorophylls and, therefore, light absorption. A longer photoperiod (24 h) increased the total biomass and dry weight, nevertheless an increase in photosynthetic processes, light absorption by leaves and chlorophyll content was not recorded, nor were differences in respiration rate, thus indicating that changes in photosynthesis and respiration are not necessary conditions for stimulating plant production. A simple model to predict plant production was also developed to address the question of whether increasing the duration of illumination stimulates plant production without inducing changes in photosynthesis and respiration. Our results indicate that increasing the duration of illumination can stimulate dry weight accumulation and that this effect can also be induced using the equal total light integrals for day (i.e., this stimulation can be also caused by increasing the light period while decreasing light intensity). Increasing the duration of illumination is therefore an effective approach to stimulating lettuce production under artificial lighting.
The Effect of LED Light Spectra on the Growth, Yield and Nutritional Value of Red and Green Lettuce (Lactuca sativa)
Authors: Alrajhi Abdullah A. , Alsahli Abdulaziz S. , Alhelal Ibrahim M. , Rihan Hail Z. , Fuller Michael P. , Alsadon Abdullah A. , Ibrahim Abdullah A.
Published: January 2023

Controlled Environment Agriculture (CEA) is a method of increasing crop productivity per unit area of cultivated land by extending crop production into the vertical dimension and enabling year-round production. Light emitting diodes (LED) are frequently used as the source of light energy in CEA systems and light is commonly the limiting factor for production under CEA conditions. In the current study, the impact of different spectra was compared with the use of white LED light. The various spectra were white; white supplemented with ultraviolet b for a week before harvest; three combinations of red/blue lights (red 660 nm with blue 450 nm at 1:1 ratio; red 660 nm with blue 435 nm 1:1 ratio; red 660 nm with blue at mix of 450 nm and 435 nm 1:1 ratio); and red/blue supplemented with green and far red (B/R/G/FR, ratio: 1:1:0.07:0.64). The growth, yield, physiological and chemical profiles of two varieties of lettuce, Carmoli (red) and Locarno (green), responded differently to the various light treatments. However, white (control) appeared to perform the best overall. The B/R/G/FR promoted the growth and yield parameters in both varieties of lettuce but also increased the level of stem elongation (bolting), which impacted the quality of grown plants. There was no clear relationship between the various physiological parameters measured and final marketable yield in either variety. Various chemical traits, including vitamin C content, total phenol content, soluble sugar and total soluble solid contents responded differently to the light treatments, where each targeted chemical was promoted by a specific light spectrum. This highlights the importance of designing the light spectra in accordance with the intended outcomes. The current study has value in the field of commercial vertical farming of lettuce under CEA conditions.
Systematic Identification of Suitable Reference Genes for Quantitative Real-Time PCR Analysis in Melissa officinalis L
Authors: Bharati Rohit , Sen Madhab Kumar , Kumar Ram , Gupta Aayushi , Žiarovská Jana , Fernández-Cusimamani Eloy , Leuner Olga
Published: January 2023

Melissa officinalis L. is well known for its lemon-scented aroma and various pharmacological properties. Despite these valuable properties, the genes involved in the biosynthetic pathways in M. officinalis are not yet well-explored when compared to other members of the mint family. For that, gene expression studies using quantitative real-time PCR (qRT-PCR) are an excellent tool. Although qRT-PCR can provide accurate results, its accuracy is highly reliant on the expression and stability of the reference gene used for normalization. Hence, selecting a suitable experiment-specific reference gene is very crucial to obtain accurate results. However, to date, there are no reports for experiment-specific reference genes in M. officinalis. Therefore, in the current study, ten commonly used reference genes were assessed for their suitability as optimal reference genes in M. officinalis under various abiotic stress conditions and different plant organs. The candidate genes were ranked based on BestKeeper, comparative ΔCt, geNorm, NormFinder, and RefFinder. Based on the results, we recommend the combination of EF-1α and GAPDH as the best reference genes to normalize gene expression studies in M. officinalis. On the contrary, HLH71 was identified as the least-performing gene. Thereafter, the reliability of the optimal gene combination was assessed by evaluating the relative gene expression of the phenylalanine ammonia lyase (PAL) gene under two elicitor treatments (gibberellic acid and jasmonic acid). PAL is a crucial gene involved directly or indirectly in the production of various economically important secondary metabolites in plants. Suitable reference genes for each experimental condition are also discussed. The findings of the current study form a basis for current and future gene expression studies in M. officinalis and other related species.
Seed Longevity—The Evolution of Knowledge and a Conceptual Framework
Authors: Nadarajan Jayanthi , Walters Christina , Pritchard Hugh W. , Ballesteros Daniel , Colville Louise
Published: January 2023

The lifespan or longevity of a seed is the time period over which it can remain viable. Seed longevity is a complex trait and varies greatly between species and even seed lots of the same species. Our scientific understanding of seed longevity has advanced from anecdotal ‘Thumb Rules,’ to empirically based models, biophysical explanations for why those models sometimes work or fail, and to the profound realisation that seeds are the model of the underexplored realm of biology when water is so limited that the cytoplasm solidifies. The environmental variables of moisture and temperature are essential factors that define survival or death, as well as the timescale to measure lifespan. There is an increasing understanding of how these factors induce cytoplasmic solidification and affect glassy properties. Cytoplasmic solidification slows down, but does not stop, the chemical reactions involved in ageing. Continued degradation of proteins, lipids and nucleic acids damage cell constituents and reduce the seed’s metabolic capacity, eventually impairing the ability to germinate. This review captures the evolution of knowledge on seed longevity over the past five decades in relation to seed ageing mechanisms, technology development, including tools to predict seed storage behaviour and non-invasive techniques for seed longevity assessment. It is concluded that seed storage biology is a complex science covering seed physiology, biophysics, biochemistry and multi-omic technologies, and simultaneous knowledge advancement in these areas is necessary to improve seed storage efficacy for crops and wild species biodiversity conservation.
Metabolomic Profiling, Antibacterial, and Molluscicidal Properties of the Medicinal Plants Calotropis procera and Atriplex halimus: In Silico Molecular Docking Study
Authors: Morad Mostafa Y. , El-Sayed Heba , El-Khadragy Manal F. , Abdelsalam Asmaa , Ahmed Eman Zakaria , Ibrahim Amina M.
Published: January 2023

The potential of plant-based natural compounds in the creation of new molluscicidal and antimicrobial medications has gained attention in recent years. The current study compared the metabolic profiles, antibacterial, and molluscicidal properties of the medicinal plants Calotropis procera (C. procera) and Atriplex halimus (A. halimus). In both plants, 118 metabolites were identified using gas chromatography-mass spectrometry. Palmitic acid, stigmasterol, and campesterol were the most prevalent constituents. C. procera extract showed stronger antibacterial activity than A. halimus against Escherichia coli and Proteus mirabilis. Both extracts exhibited molluscicidal activity against Biomphalaria alexandrina, with LC50 values of C. procera (135 mg/L) and A. halimus (223.8 mg/L). Survival rates of snails exposed to sub-lethal concentrations (LC25) of C. procera and A. halimus extracts were 5% and 20%, respectively. The hatchability of snail eggs exposed to both extracts has been dramatically reduced. Both extracts significantly decreased the levels of alkaline phosphatase, acid phosphatase, total protein, and albumin in snails, as well as causing DNA damage and resulting in numerous hermaphrodite and digestive gland damages and distortions. Molecular docking showed palmitic acid binding with acid, alkaline, and alanine aminotransferases in treated digestive gland snails. In conclusion, C. procera and A. halimus have antibacterial and molluscicidal properties.
Multi-Objective Optimization of Liquid Silica Array Lenses Based on Latin Hypercube Sampling and Constrained Generative Inverse Design Networks
Authors: Chang Hanjui , Lu Shuzhou , Sun Yue , Zhang Guangyi , Rao Longshi
Published: January 2023

Injection molding process parameters have a great impact on plastic production quality, manufacturing cost, and molding efficiency. This study proposes to apply the method of Latin hypercube sampling, and to combine the response surface model and “Constraint Generation Inverse Design Network (CGIDN)” to achieve multi-objective optimization of the injection process, shorten the time to find the optimal process parameters, and improve the production efficiency of plastic parts. Taking the LSR lens array of automotive LED lights as the research object, the residual stress and volume shrinkage were taken as the optimization objectives, and the filling time, melt temperature, maturation time, and maturation pressure were taken as the influencing factors to obtain the optimization target values, and the response surface models between the volume shrinkage rate and the influencing factors were established. Based on the “Constraint-Generated Inverse Design Network”, the optimization was independently sought within the set parameters to obtain the optimal combination of process parameters to meet the injection molding quality of plastic parts. The results showed that the optimal residual stress value and volume shrinkage rate were 11.96 MPa and 4.88%, respectively, in the data set of 20 Latin test samples obtained based on Latin hypercube sampling, and the optimal residual stress value and volume shrinkage rate were 8.47 MPa and 2.83%, respectively, after optimization by the CGIDN method. The optimal process parameters obtained by CGIDN optimization were a melt temperature of 30 °C, filling time of 2.5 s, maturation pressure of 40 MPa, and maturation time of 15 s. The optimization results were obvious and showed the feasibility of the data-driven injection molding process optimization method based on the combination of Latin hypercube sampling and CGIDN.
Bioplastics: Innovation for Green Transition
Authors: Costa Ana , Encarnação Telma , Tavares Rafael , Todo Bom Tiago , Mateus Artur
Published: January 2023

Bioplastics are one of the possible alternative solutions to the polymers of petrochemical origins. Bioplastics have several advantages over traditional plastics in terms of low carbon footprint, energy efficiency, biodegradability and versatility. Although they have numerous benefits and are revolutionizing many application fields, they also have several weaknesses, such as brittleness, high-water absorption, low crystallization ability and low thermal degradation temperature. These drawbacks can be a limiting factor that prevents their use in many applications. Nonetheless, reinforcements and plasticizers can be added to bioplastic production as a way to overcome such limitations. Bioplastics materials are not yet studied in depth, but it is with great optimism that their industrial use and market scenarios are increasing; such growth can be a positive driver for more research in this field. National and international investments in the bioplastics industry can also promote the green transition. International projects, such as EcoPlast and Animpol, aim to study and develop new polymeric materials made from alternative sources. One of their biggest problems is their waste management; there is no separation process yet to recycle the nonbiodegradable bioplastics, and they are considered contaminants when mixed with other polymers. Some materials use additives, and their impact on the microplastics they leave after breaking apart is subject to debate. For this reason, it is important to consider their life cycle analysis and assess their environmental viability. These are materials that can possibly be processed in various ways, including conventional processes used for petrochemical ones. Those include injection moulding and extrusion, as well as digital manufacturing. This and the possibility to use these materials in several applications is one of their greatest strengths. All these aspects will be discussed in this review.
Achieving High Thermal Conductivity and Satisfactory Insulating Properties of Elastomer Composites by Self-Assembling BN@GO Hybrids
Authors: Xie Xing , Yang Dan
Published: January 2023

With increasing heat accumulation in advanced modern electronic devices, dielectric materials with high thermal conductivity (λ) and excellent electrical insulation have attracted extensive attention in recent years. Inspired by mussel, hexagonal boron nitride (hBN) and graphene oxide (GO) are assembled to construct mhBN@GO hybrids with the assistance of poly(catechol-polyamine). Then, mhBN@GO hybrids are dispersed in carboxy nitrile rubber (XNBR) latex via emulsion coprecipitation to form elastomer composites with a high λ and satisfactory insulating properties. Thanks to the uniform dispersion of mhBN@GO hybrids, the continuous heat conduction pathways exert a significant effect on enhancing the λ and decreasing the interface thermal resistance of XNBR composites. In particular, the λ value of 30 vol% mhBN@GO/XNBR composite reaches 0.4348 W/(m·K), which is 2.7 times that of the neat XNBR (0.1623 W/(m·K)). Meanwhile, the insulating hBN platelets hinder the electron transfer between adjacent GO sheets, leading to satisfactory electrical insulation in XNBR composites, whose AC conductivity is as low as 10−10 S/cm below 100 Hz. This strategy opens up new prospects in the assembly of ceramic and carbonaceous fillers to prepare dielectric elastomer composites with high λ and satisfactory electrical insulation, making them promising for modern electrical systems.
A Review on Artificial Intelligence Enabled Design, Synthesis, and Process Optimization of Chemical Products for Industry 4.0
Authors: He Chasheng , Zhang Chengwei , Bian Tengfei , Jiao Kaixuan , Su Weike , Wu Ke-Jun , Su An
Published: January 2023

With the development of Industry 4.0, artificial intelligence (AI) is gaining increasing attention for its performance in solving particularly complex problems in industrial chemistry and chemical engineering. Therefore, this review provides an overview of the application of AI techniques, in particular machine learning, in chemical design, synthesis, and process optimization over the past years. In this review, the focus is on the application of AI for structure-function relationship analysis, synthetic route planning, and automated synthesis. Finally, we discuss the challenges and future of AI in making chemical products.
“There Is No Official Divorce Ritual in the Church”—Challenging a Mantra by Ritual Design
Authors: Lauxmann Bernhard
Published: January 2023

End-of-relationship rituals are not respected within Protestant churches. Therefore, many church websites emphasize that there are no official divorce rituals to this day. This is despite the fact that there are numerous impulses for divorce rituals, some of which are also firmly established in church practice. Practitioners who devote themselves to these rituals often have to be innovative. This article presents three unpublished drafts for separation rituals, which are understood as expressions of ritual design. Experiences from academic teaching show that the field divorce rituals is particularly suitable for initiating learning processes on ritual design, a skill of great importance for future pastors. Although divorce rituals are unpopular now, they are likely to become part of the standard repertoire of churches soon.
An Investigation of All Fiber Free-Running Dual-Comb Spectroscopy
Authors: Yang Fu , Lu Yanyu , Liu Guibin , Huang Shaowei , Chen Dijun , Ying Kang , Qi Weiao , Zhou Jiaqi
Published: January 2023

A dual-comb spectroscopy (DCS) system uses two phase-locked optical frequency combs with a slight difference in the repetition frequency. The spectrum can be sampled in the optical frequency (OF) domain and reproduces the characteristics in the radio frequency (RF) domain through asynchronous optical sampling. Therefore, the DCS system shows great advantages in achieving precision spectral measurement. During application, the question of how to reserve the mutual coherence between the two combs is the key issue affecting the application of the DCS system. This paper focuses on a software algorithm used to realize the mutual coherence of the two combs. Therefore, a pair of free-running large anomalous dispersion fiber combs, with a center wavelength of approximately 1064 nm, was used. After the signal process, the absorption spectra of multiple species were simultaneously obtained (simulated using the reflective spectra of narrow-bandwidth fiber Bragg gratings, abbreviated as FBG). The signal-to-noise ratio (SNR) could reach 13.97 dB (25) during the 100 ms sampling time. In this study, the feasibility of the system was first verified through the simulation system; then, a principal demonstration experiment was successfully executed. The whole system was connected by the optical fiber without additional phase-locking equipment, showing promise as a potential solution for the low-cost and practical application of DCS systems.
Disentangled Dynamic Deviation Transformer Networks for Multivariate Time Series Anomaly Detection
Authors: Wang Chunzhi , Xing Shaowen , Gao Rong , Yan Lingyu , Xiong Naixue , Wang Ruoxi
Published: January 2023

Graph neural networks have been widely used by multivariate time series-based anomaly detection algorithms to model the dependencies of system sensors. Previous studies have focused on learning the fixed dependency patterns between sensors. However, they ignore that the inter-sensor and temporal dependencies of time series are highly nonlinear and dynamic, leading to inevitable false alarms. In this paper, we propose a novel disentangled dynamic deviation transformer network (D3TN) for anomaly detection of multivariate time series, which jointly exploits multiscale dynamic inter-sensor dependencies and long-term temporal dependencies to improve the accuracy of multivariate time series prediction. Specifically, to disentangle the multiscale graph convolution, we design a novel disentangled multiscale aggregation scheme to better represent the hidden dependencies between sensors to learn fixed inter-sensor dependencies based on static topology. To capture dynamic inter-sensor dependencies determined by real-time monitoring situations and unexpected anomalies, we introduce a self-attention mechanism to model dynamic directed interactions in various potential subspaces influenced by various factors. In addition, complex temporal correlations across multiple time steps are simulated by processing the time series in parallel. Experiments on three real datasets show that the proposed D3TN significantly outperforms the state-of-the-art methods.
Superpixel-Based PSO Algorithms for Color Image Quantization
Authors: Frackiewicz Mariusz , Palus Henryk , Prandzioch Daniel
Published: January 2023

Nature-inspired artificial intelligence algorithms have been applied to color image quantization (CIQ) for some time. Among these algorithms, the particle swarm optimization algorithm (PSO-CIQ) and its numerous modifications are important in CIQ. In this article, the usefulness of such a modification, labeled IDE-PSO-CIQ and additionally using the idea of individual difference evolution based on the emotional states of particles, is tested. The superiority of this algorithm over the PSO-CIQ algorithm was demonstrated using a set of quality indices based on pixels, patches, and superpixels. Furthermore, both algorithms studied were applied to superpixel versions of quantized images, creating color palettes in much less time. A heuristic method was proposed to select the number of superpixels, depending on the size of the palette. The effectiveness of the proposed algorithms was experimentally verified on a set of benchmark color images. The results obtained from the computational experiments indicate a multiple reduction in computation time for the superpixel methods while maintaining the high quality of the output quantized images, slightly inferior to that obtained with the pixel methods.
Hierarchical Aggregation for Numerical Data under Local Differential Privacy
Authors: Hao Mingchao , Wu Wanqing , Wan Yuan
Published: January 2023

The proposal of local differential privacy solves the problem that the data collector must be trusted in centralized differential privacy models. The statistical analysis of numerical data under local differential privacy has been widely studied by many scholars. However, in real-world scenarios, numerical data from the same category but in different ranges frequently require different levels of privacy protection. We propose a hierarchical aggregation framework for numerical data under local differential privacy. In this framework, the privacy data in different ranges are assigned different privacy levels and then disturbed hierarchically and locally. After receiving users’ data, the aggregator perturbs the privacy data again to convert the low-level data into high-level data to increase the privacy data at each privacy level so as to improve the accuracy of the statistical analysis. Through theoretical analysis, it was proved that this framework meets the requirements of local differential privacy and that its final mean estimation result is unbiased. The proposed framework is combined with mini-batch stochastic gradient descent to complete the linear regression task. Sufficient experiments both on synthetic datasets and real datasets show that the framework has a higher accuracy than the existing methods in both mean estimation and mini-batch stochastic gradient descent experiments.
Wide-Band Wide-Beam Circularly-Polarized Slot-Coupled Antenna for Wide-Angle Beam Scanning Arrays
Authors: Salucci Marco , Oliveri Giacomo , Hannan Mohammad Abdul , Azaro Renzo , Massa Andrea
Published: January 2023

The design of a wide-band wide-beam circularly-polarized slot-coupled (WWCS) radiating element for wide-angle scanning arrays (WASAs) is addressed. The WWCS radiator exploits a simple geometry composed of a primary (driven) and a secondary (passive) element to generate wide-beam patterns with rotational symmetry and high polarization purity. The synthesis was carried out by means of a customized version of the System-by-Design (SbD) method to derive a WWCS radiator with circular polarization (CP) and wide-band impedance matching. The results of the numerical assessment, along with a tolerance analysis, confirm that the synthesized WWCS radiating element is a competitive solution for the implementation of large WASAs. More specifically, a representative design working at f0=2.45 [GHz] is shown having fractional bandwidth FBW≃15%, half-power beam-width HPBWf0≃180 [deg] in all elevation planes, and high polarization purity with broadside axial ratio ARf0=3.2 [dB] and cross-polar discrimination XPDf0=15 [dB]. Finally, the experimental assessment, carried out on a PCB-manufactured prototype, verifies the wide-band and wide-beam features of the designed WWCS radiator.
Low-Cost UWB Based Real-Time Locating System: Development, Lab Test, Industrial Implementation and Economic Assessment
Authors: Volpi Andrea , Tebaldi Letizia , Matrella Guido , Montanari Roberto , Bottani Eleonora
Published: January 2023

This paper presents the technical development and subsequent testing of a Real-Time Locating System based on Ultra-Wideband signals, with the aim to appraise its potential implementation in a real industrial case. The system relies on a commercial Radio Indoor Positioning System, called Qorvo MDEK1001, which makes use of UWB RF technology to determine the position of RF-tags placed on an item of interest, which in turn is located in an area covered by specific fixed antennas (anchors). Testing sessions were carried out both in an Italian laboratory and in a real industrial environment, to determine the best configurations according to some selected performance indicators. The results support the adoption of the proposed solution in industrial environments to track assets and work in progress. Moreover, most importantly, the solution developed is cheap in nature: indeed, normally tracking solutions involve a huge investment, quite often not affordable above all by small-, medium- and micro-sized enterprises. The proposed low-cost solution instead, as demonstrated by the economic assessment completing the work, justifies the feasibility of the investment. Hence, results of this paper ultimately constitute a guidance for those practitioners who intend to adopt a similar system in their business.
Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury
Authors: Shokouhyan Seyed Mohammadreza , Blandeau Mathias , Wallard Laura , Guerra Thierry Marie , Pudlo Philippe , Gagnon Dany H. , Barbier Franck
Published: January 2023

Neuro mechanical time delay is inevitable in the sensorimotor control of the body due to sensory, transmission, signal processing and muscle activation delays. In essence, time delay reduces stabilization efficiency, leading to system instability (e.g., falls). For this reason, estimation of time delay in patients such as people living with spinal cord injury (SCI) can help therapists and biomechanics to design more appropriate exercise or assistive technologies in the rehabilitation procedure. In this study, we aim to estimate the muscle onset activation in SCI people by four strategies on EMG data. Seven complete SCI individuals participated in this study, and they maintained their stability during seated balance after a mechanical perturbation exerting at the level of the third thoracic vertebra between the scapulas. EMG activity of eight upper limb muscles were recorded during the stability. Two strategies based on the simple filtering (first strategy) approach and TKEO technique (second strategy) in the time domain and two other approaches of cepstral analysis (third strategy) and power spectrum (fourth strategy) in the time–frequency domain were performed in order to estimate the muscle onset. The results demonstrated that the TKEO technique could efficiently remove the electrocardiogram (ECG) and motion artifacts compared with the simple classical filtering approach. However, the first and second strategies failed to find muscle onset in several trials, which shows the weakness of these two strategies. The time–frequency techniques (cepstral analysis and power spectrum) estimated longer activation onset compared with the other two strategies in the time domain, which we associate with lower-frequency movement in the maintaining of sitting stability. In addition, no correlation was found for the muscle activation sequence nor for the estimated delay value, which is most likely caused by motion redundancy and different stabilization strategies in each participant. The estimated time delay can be used in developing a sensory motor control model of the body. It not only can help therapists and biomechanics to understand the underlying mechanisms of body, but also can be useful in developing assistive technologies based on their stability mechanism.
Research on the Relationship between Resistivity and Resistance between Two Points on RCS Test Model
Authors: Wu Yacong , Huang Jun , Song Lei
Published: January 2023

Surface conductivity is one of the key factors in judging whether the RCS (Radar Cross Section) test model is qualified, but the accuracy of traditional detection methods is insufficient. Furthermore, the resistance between two points obtained by traditional methods cannot be directly applied to the electromagnetic simulation analysis of the test model. In this paper, the theoretical model of the relationship between resistivity and resistance between two points on the model surface is proposed. The simulation method for the resistance between two points on the model surface is established. The advantage of the method proposed in this paper compared with the traditional method in detecting the surface resistance of the model is demonstrated intuitively. The experiments are carried out on ITO (Indium Tin Oxide) conductive films with several dimensions and resistivity. Results show that the measured resistance between two points on the model surface is highly consistent with the theoretical and simulated values. Moreover, the comparison of experiments shows that the measurement error of the traditional method is 150% to 200% higher than that of the method proposed in this paper.
An Improved Projector Calibration Method by Phase Mapping Based on Fringe Projection Profilometry
Authors: Liu Yabin , Zhang Bingwei , Yuan Xuewu , Lin Junyi , Jiang Kaiyong
Published: January 2023

Aiming at the problem of the low accuracy of projector calibration in a structured light system, an improved projector calibration method is proposed in this paper. One of the key ideas is to estimate the sub-pixel coordinates in the projector image plane using local random sample consensus (RANSAC). A bundle adjustment (BA) algorithm is adopted to optimize the calibration parameters to further improve the accuracy and robustness of the projector calibration. After system calibration and epipolar rectification, the mapping relationship between the pixel coordinates and the absolute phase in the projector image plane is established by using cubic polynomial fitting, and the disparity is rapidly solved by using the mapping relationship, which not only ensures the measurement accuracy, but also improves the measurement efficiency. The experimental results demonstrated that the average re-projection error after optimization is reduced to 0.03 pixels, and the proposed method is suitable for high-speed 3D reconstruction without the time-consuming homogenous point searching.
Optimal Configuration for Monitoring Stations in a Wireless Localisation Network Based on Received Signal Strength Differences
Authors: Eshagh Mehdi
Published: January 2023

A smart city is a city equipped with many sensors communicating with each other for different purposes. Cybersecurity and signal security are important in such cities, especially for airports and harbours. Any signal interference or attack on the navigation of autonomous vehicles and aircraft may lead to catastrophes and risks in people’s lives. Therefore, it is of tremendous importance to develop wireless security networks for the localisation of any radio frequency interferer in smart cities. Time of arrival, angle of arrival, time-difference of arrivals, received signal strength and received signal strength difference (RSSD) are known observables used for the localisation of a signal interferer. Localisation means to estimate the coordinates of an interferer from some established monitoring stations and sensors receiving such measurements from an interferer. The main goal of this study is to optimise the geometric configuration of the monitoring stations using a desired dilution of precision and/or variance-covariance matrix (VCM) for the transmitter’s location based on the RSSD. The required mathematical models are developed and applied to the Arlanda international airport of Sweden. Our numerical tests show that the same configuration is achieved based on dilution of precision and VCM criteria when the resolution of design is lower than 20 m in the presence of the same constraints. The choice of the pathloss exponent in the mathematical models of the RSSDs is not important for such low resolutions. Finally, optimisation based on the VCM is recommended because of its larger redundancy and flexibility in selecting different desired variances and covariances for the coordinates of the transmitter.
Two-Step Approach for Occupancy Estimation in Intensive Care Units Based on Bayesian Optimization Techniques
Authors: González-Nóvoa José A. , Busto Laura , Campanioni Silvia , Fariña José , Rodríguez-Andina Juan J. , Vila Dolores , Veiga César
Published: January 2023

Due to the high occupational pressure suffered by intensive care units (ICUs), a correct estimation of the patients’ length of stay (LoS) in the ICU is of great interest to predict possible situations of collapse, to help healthcare personnel to select appropriate treatment options and to predict patients’ conditions. There has been a high amount of data collected by biomedical sensors during the continuous monitoring process of patients in the ICU, so the use of artificial intelligence techniques in automatic LoS estimation would improve patients’ care and facilitate the work of healthcare personnel. In this work, a novel methodology to estimate the LoS using data of the first 24 h in the ICU is presented. To achieve this, XGBoost, one of the most popular and efficient state-of-the-art algorithms, is used as an estimator model, and its performance is optimized both from computational and precision viewpoints using Bayesian techniques. For this optimization, a novel two-step approach is presented. The methodology was carefully designed to execute codes on a high-performance computing system based on graphics processing units, which considerably reduces the execution time. The algorithm scalability is analyzed. With the proposed methodology, the best set of XGBoost hyperparameters are identified, estimating LoS with a MAE of 2.529 days, improving the results reported in the current state of the art and probing the validity and utility of the proposed approach.
TriNymAuth: Triple Pseudonym Authentication Scheme for VANETs Based on Cuckoo Filter and Paillier Homomorphic Encryption
Authors: Zhuang Luyuan , Guo Nan , Chen Yufan
Published: January 2023

In VANETs, owing to the openness of wireless communication, it is necessary to change pseudonyms frequently to realize the unlinkability of vehicle identity. Moreover, identity authentication is needed, which is usually completed by digital certificates or a trusted third party. The storage and the communication overhead are high. This paper proposes a triple pseudonym authentication scheme for VANETs based on the Cuckoo Filter and Paillier homomorphic encryption (called TriNymAuth). TriNymAuth applies Paillier homomorphic encryption, a Cuckoo Filter combining filter-level and bucket-level, and a triple pseudonym (homomorphic pseudonym, local pseudonym, and virtual pseudonym) authentication to the vehicle identity authentication scheme. It reduces the dependence on a trusted third party and ensures the privacy and security of vehicle identity while improving authentication efficiency. Experimental results show that the insert overhead of the Cuckoo Filter is about 10 μs, and the query overhead reaches the ns level. Furthermore, TriNymAuth has significant cost advantages, with an OBU enrollment cost of only 0.884 ms. When the data rate in VANETs dr≤ 180 kbps, TriNymAuth has the smallest total transmission delay cost and is suitable for shopping malls and other places with dense traffic.
Reliability of Near-Infrared Spectroscopy with and without Compression Tights during Exercise and Recovery Activities
Authors: Biddulph Brett , Morris John G , Lewis Martin , Hunter Kirsty , Sunderland Caroline
Published: January 2023

Near-infrared spectroscopy (NIRS) is widely used in sports science research, despite the limited reliability of available data. The aim of the present study was to assess the reliability of NIRS with and without compression tights. Thirteen healthy active males, (age 21.5 ± 2.7 years, body mass 82.1 ± 11.2 kg, BMI 24.6 ± 3.2 kg·m−2) completed four trials (two control trials and two trials using compression tights) over a 28-day period. During each trial, participants completed 20 min each of laying supine, sitting, walking (4 km·h−1), jogging, and sitting following the jogging. An NIRS device was attached to the muscle belly of the vastus lateralis and gastrocnemius and recorded tissue saturation index (TSI), muscle oxygenation, and muscle deoxygenation. Systematic bias and 95% limits of agreement (LOA) and coefficient of variation (CV) were used to report reliability measures for each activity type. For TSI, systematic bias (LOA) at the gastrocnemius during the control and tights trial ranged from −0.4 to 1.7% (4.4 to 10.3%) and −1.9 to 3.5% (8.1 to 12.0%), respectively. For the vastus lateralis, the systematic bias (LOA) for the control trial ranged from −2.4 to 1.0% (5.1 to 6.9%) and for the tights trial was −0.8 to 0.6% (7.0 to 9.5%). For TSI, the CV during the control trial ranged from 1.7 to 4.0% for the gastrocnemius and 1.9 to 2.6% for the vastus lateralis. During the tights trials, the CV ranged from 3.0 to 4.5% for the gastrocnemius and 2.6 to 3.5% for the vastus lateralis. The CV for muscle oxygenation during the control and tights trials for the gastrocnemius was 2.7 to 6.2% and 1.0 to 8.8% and for the vastus lateralis was 0.6 to 4.0% and 4.0 to 4.5%, respectively. The relative reliability was poorer in the tights trials, but if the aim was to detect a 5% difference in TSI, NIRS would be sufficiently reliable. However, the reliability of muscle oxygenation and deoxygenation varies considerably with activity type, and this should be considered when determining whether to employ NIRS in research studies.
Unique Structure and Distinctive Properties of the Ancient and Ubiquitous Gamma-Type Envelope Glycoprotein
Authors: Hogan Victoria , Johnson Welkin E.
Published: January 2023

After the onset of the AIDS pandemic, HIV-1 (genus Lentivirus) became the predominant model for studying retrovirus Env glycoproteins and their role in entry. However, HIV Env is an inadequate model for understanding entry of viruses in the Alpharetrovirus, Gammaretrovirus and Deltaretrovirus genera. For example, oncogenic model system viruses such as Rous sarcoma virus (RSV, Alpharetrovirus), murine leukemia virus (MLV, Gammaretrovirus) and human T-cell leukemia viruses (HTLV-I and HTLV-II, Deltaretrovirus) encode Envs that are structurally and functionally distinct from HIV Env. We refer to these as Gamma-type Envs. Gamma-type Envs are probably the most widespread retroviral Envs in nature. They are found in exogenous and endogenous retroviruses representing a broad spectrum of vertebrate hosts including amphibians, birds, reptiles, mammals and fish. In endogenous form, gamma-type Envs have been evolutionarily coopted numerous times, most notably as placental syncytins (e.g., human SYNC1 and SYNC2). Remarkably, gamma-type Envs are also found outside of the Retroviridae. Gp2 proteins of filoviruses (e.g., Ebolavirus) and snake arenaviruses in the genus Reptarenavirus are gamma-type Env homologs, products of ancient recombination events involving viruses of different Baltimore classes. Distinctive hallmarks of gamma-type Envs include a labile disulfide bond linking the surface and transmembrane subunits, a multi-stage attachment and fusion mechanism, a highly conserved (but poorly understood) “immunosuppressive domain”, and activation by the viral protease during virion maturation. Here, we synthesize work from diverse retrovirus model systems to illustrate these distinctive properties and to highlight avenues for further exploration of gamma-type Env structure and function.
COVID-19 Vaccination in Pediatrics: Was It Valuable and Successful?
Authors: Raslan Mohamed Ahmed , Raslan Sara Ahmed , Shehata Eslam Mansour , Mahmoud Amr Saad , Sabri Nagwa A. , Alzahrani Khalid J. , Alzahrani Fuad M. , Alshammeri Saleh , Azevedo Vasco , Lundstrom Kenneth , Barh Debmalya
Published: January 2023

Background: The mass vaccination of children against coronavirus 2019 disease (COVID-19) has been frequently debated. The risk–benefit assessment of COVID-19 vaccination versus infection in children has also been debated. Aim: This systematic review looked for answers to the question “was the vaccination of our children valuable and successful?”. Methods: The search strategy of different articles in the literature was based on medical subject headings. Screening and selection were based on inclusion/exclusion criteria. Results and Discussion: The search results revealed that the majority of the reported adverse events after COVID-19 vaccination in pediatrics were mild to moderate, with few being severe. Injection site discomfort, fever, headache, cough, lethargy, and muscular aches and pains were the most prevalent side effects. Few clinical studies recorded significant side effects, although the majority of these adverse events had nothing to do with vaccination. In terms of efficacy, COVID-19 disease protection was achieved in 90–95% of cases for mRNA vaccines, in 50–80% of cases for inactivated vaccines, and in 58–92% of cases for adenoviral-based vaccines in children and adolescents. Conclusions: Based on available data, COVID-19 immunizations appear to be safe for children and adolescents. Furthermore, multiple studies have proven that different types of vaccines can provide excellent protection against COVID-19 in pediatric populations. The efficacy of vaccines against new SARS-CoV-2 variants and the reduction in vaccine-related long-term adverse events are crucial for risk–benefit and cost-effectiveness assessments; therefore, additional safety studies are required to confirm the long-term safety and effectiveness of vaccinations in children.
Humoral Immune Response to CoronaVac in Turkish Adults
Authors: Cosgun Yasemin , Emanet Nergis , Kamiloglu Ayten Öz , Grage-Griebenow Evelin , Hohensee Susann , Saschenbrecker Sandra , Steinhagen Katja , Korukluoglu Gulay
Published: January 2023

While most approved vaccines are based on the viral spike protein or its immunogenic regions, inactivated whole-virion vaccines (e.g., CoronaVac) contain additional antigens that may enhance protection. This study analyzes short-term humoral responses against the SARS-CoV-2 spike (S1) and nucleocapsid (NCP) protein in 50 Turkish adults without previous SARS-CoV-2 infection after CoronaVac immunization. Samples were collected before vaccination (t0), 28–29 days after the first vaccine dose and prior to the second dose (t1), as well as 14–15 days after the second dose (t2). Anti-S1 IgG and IgA as well as anti-NCP IgG were quantified using ELISA. At t1, seroconversion rates for anti-S1 IgG, anti-S1 IgA and anti-NCP IgG were 30.0%, 28.0% and 4.0%, respectively, increasing significantly to 98.0%, 78.0% and 40.0% at t2. The anti-NCP IgG median (t2) was below the positivity cut-off, while anti-S1 IgG and IgA medians were positive. Anti-S1 IgG levels strongly correlated with anti-S1 IgA (rs = 0.767, p < 0.001) and anti-NCP IgG (rs = 0.683, p < 0.001). In conclusion, two CoronaVac doses induced significant increases in antibodies against S1 and NCP. Despite strong correlations between the antibody concentrations, the median levels and seroconversion rates of S1-specific responses exceed those of NCP-specific responses as early as two weeks after the second vaccine dose.