bluuebunny/crossref_metadata_2025 huggingface dataset:
Composite Coating for the Food Industry Based on Fluoroplast and ZnO-NPs: Physical and Chemical Properties, Antibacterial and Antibiofilm Activity, Cytotoxicity
Authors: Serov Dmitriy , Burmistrov Dmitriy , Simakin Alexander , Astashev Maxim , Uvarov Oleg , Tolordava Eteri , Semenova Anastasia , Lisitsyn Andrey , Gudkov Sergey
Published: November 2022

Bacterial contamination of meat products during its preparation at the enterprise is an important problem for the global food industry. Cutting boards are one of the main sources of infection. In order to solve this problem, the creation of mechanically stable coatings with antibacterial activity is one of the most promising strategies. For such a coating, we developed a composite material based on “liquid” Teflon and zinc oxide nanoparticles (ZnO-NPs). The nanoparticles obtained with laser ablation had a rod-like morphology, an average size of ~60 nm, and a ζ-potential of +30 mV. The polymer composite material was obtained by adding the ZnO-NPs to the polymer matrix at a concentration of 0.001–0.1% using the low-temperature technology developed by the research team. When applying a composite material to a surface with damage, the elimination of defects on a micrometer scale was observed. The effect of the composite material on the generation of reactive oxygen species (H2O2, •OH), 8-oxoguanine in DNA in vitro, and long-lived reactive protein species (LRPS) was evaluated. The composite coating increased the generation of all of the studied compounds by 50–200%. The effect depended on the concentration of added ZnO-NPs. The antibacterial and antibiofilm effects of the Teflon/ZnO NP coating against L. monocytogenes, S. aureus, P. aeruginosa, and S. typhimurium, as well as cytotoxicity against the primary culture of mouse fibroblasts, were studied. The conducted microbiological study showed that the fluoroplast/ZnO-NPs coating has a strong bacteriostatic effect against both Gram-positive and Gram-negative bacteria. In addition, the fluoroplast/ZnO-NPs composite material only showed potential cytotoxicity against primary mammalian cell culture at a concentration of 0.1%. Thus, a composite material has been obtained, the use of which may be promising for the creation of antibacterial coatings in the meat processing industry.
Reactive Oxygen, Nitrogen, and Sulfur Species (RONSS) as a Metabolic Cluster for Signaling and Biostimulation of Plants: An Overview
Authors: Medrano-Macías Julia , Flores-Gallegos Adriana Carolina , Nava-Reyna Erika , Morales Isidro , Tortella Gonzalo , Solís-Gaona Susana , Benavides-Mendoza Adalberto
Published: November 2022

This review highlights the relationship between the metabolism of reactive oxygen species (ROS), reactive nitrogen species (RNS), and H2S-reactive sulfur species (RSS). These three metabolic pathways, collectively termed reactive oxygen, nitrogen, and sulfur species (RONSS), constitute a conglomerate of reactions that function as an energy dissipation mechanism, in addition to allowing environmental signals to be transduced into cellular information. This information, in the form of proteins with posttranslational modifications or signaling metabolites derived from RONSS, serves as an inducer of many processes for redoxtasis and metabolic adjustment to the changing environmental conditions to which plants are subjected. Although it is thought that the role of reactive chemical species was originally energy dissipation, during evolution they seem to form a cluster of RONSS that, in addition to dissipating excess excitation potential or reducing potential, also fulfils essential signaling functions that play a vital role in the stress acclimation of plants. Signaling occurs by synthesizing many biomolecules that modify the activity of transcription factors and through modifications in thiol groups of enzymes. The result is a series of adjustments in plants’ gene expression, biochemistry, and physiology. Therefore, we present an overview of the synthesis and functions of the RONSS, considering the importance and implications in agronomic management, particularly on the biostimulation of crops.
Transcriptome Analysis of Genes Involved in Fatty Acid and Lipid Biosynthesis in Developing Walnut (Juglans regia L.) Seed Kernels from Qinghai Plateau
Authors: Shi Wenjun , Zhang Defang , Ma Zhong
Published: November 2022

Walnut (Juglans regia) is an important woody oil-bearing plant with high nutritional value. For better understanding of the underlying molecular mechanisms of its oil accumulation in the Qinghai Plateau, in this study we monitored walnut fruit development, and 15 cDNA libraries were constructed from walnut seed kernels collected at 72, 79, 93, 118 and 135 days after flowering (DAF). The candidate genes were identified using sequencing and expression analysis. The results showed that the oil content in the kernels increased dramatically in late July and reached the maximum value of 69% in mature seed. More than 90% of the oils were unsaturated fatty acids (UFAs) and linoleic acid (18:2) was the predominant UFA accumulated in mature seed. Differentially expressed genes (DEGs) in 15 KEGG pathways of lipid metabolism were detected. We identified 119 DEGs related to FA de novo biosynthesis (38 DEGs), FA elongation and desaturation (39 DEGs), triacylglycerol (TAG) assembly (24 DEGs), oil bodies (12 DEGs), and transcription factors (TFs, 6 DEGs). The abundantly expressed oleosins, caleosins and steroleosins may be important for timely energy reserve in oil bodies. Weighted gene coexpression network analysis (WGCNA) showed that AP2/ERF and bHLH were the key TFs, and were co-expressed with ACC1, α-CT, BCCP, MAT, KASII, LACS, FATA, and PDCT. Our transcriptome data will enrich public databases and provide new insights into functional genes related to the seed kernel lipid metabolism and oil accumulation in J. regia.
Determination and Quantification of Phytochemicals from the Leaf Extract of Parthenium hysterophorus L. and Their Physio-Biochemical Responses to Several Crop and Weed Species
Authors: Bashar HM Khairul , Juraimi Abdul Shukor , Ahmad-Hamdani Muhammad Saiful , Uddin Md. Kamal , Asib Norhayu , Anwar Md. Parvez , Rahaman Ferdoushi , Karim SM Rezaul , Haque Mohammad Amdadul , Berahim Zulkarami , Nik Mustapha Nik Amelia , Hossain Akbar
Published: November 2022

This current investigation was undertaken both in laboratory and glasshouse for documentation and quantification of phytochemicals from different parts of the parthenium (Parthenium hysterophorus L.) plant through LC-MS and HPLC to study their effect on two crops namely, Bambara groundnut (Vigna subterranean L.) and maize (Zea mays L.), and six different types of weed e.g., Digitaria sanguinalis, Eleusine indica, Ageratum conyzoides, Cyperus iria, Euphorbia hirta, and Cyperus difformis. The parthenium methanolic leaf extracts at 25, 50, 75, and 100 g L−1 were sprayed in the test crops and weeds to assess their physiological and biochemical reactions after 6, 24, 48, and 72 h of spraying these compounds (HAS). The LC-MS analysis confirmed seven types of phytochemicals (caffeic acid, ferulic acid, vanillic acid, parthenin, chlorogenic acid, quinic acid, and p-anisic acid) in the parthenium leaf extract that were responsible for the inhibition of tested crops and weeds. From the HPLC analysis, higher amounts in leaf methanol extracts (40,752.52 ppm) than those of the stem (2664.09 ppm) and flower extracts (30,454.33 ppm) were recorded. Parthenium leaf extract at 100 g L−1 had observed higher phytotoxicity on all weed species except C. difformis. However, all crops were found safe under this dose of extraction. Although both crops were also affected to some extent, they could recover from the stress after a few days. The photosynthetic rate, transpiration rate, stomatal conductance, carotenoid and chlorophyll content were decreased due to the application of parthenium leaf extract. However, when parthenium leaf extract was applied at 100 g L−1 for 72 h, the malondialdehyde (MDA) and proline content were increased in all weeds. Enzymatic antioxidant activity (e.g., superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) contents) were also elevated as a result of the sprayed parthenium leaf extract. The negative impact of physiological and biochemical responses as a consequence of the parthenium leaf extract led the weed species to be stressed and finally killed. The current findings show the feasibility of developing bioherbicide from the methanolic extract of parthenium leaf for controlling weeds, which will be cost-effective, sustainable, and environment friendly for crop production during the future changing climate.
Improvement of Photosynthesis by Biochar and Vermicompost to Enhance Tomato (Solanum lycopersicum L.) Yield under Greenhouse Conditions
Authors: Liu Xinna , Zhang Jie , Wang Qian , Chang Tingting , Shaghaleh Hiba , Hamoud Yousef Alhaj
Published: November 2022

Chlorophyll fluorescence is an important tool in the study of photosynthesis and its effect on the physiological indicators of crop growth is worth exploring. The trial was conducted to investigate the effect of biochar (CK, 0%; BA3, 3%; BA5, 5%; by mass of soil) and vermicompost (VA3, 3%; VA5, 5%) on photosynthesis, chlorophyll fluorescence, and tomato yield under greenhouse condition. Results revealed that photosynthetic parameters and chlorophyll fluorescence traits of BA3, VA3, BA5, and VA5 were significantly higher than those of CK, and the improvement of vermicompost was more effective than biochar at the same application rate. VA3 treatment had the highest net photosynthetic rate (Pn), intercellular CO2 concentration (Ci), variable fluorescence (Fv), maximum fluorescence (Fm), PSII maximum photochemical efficiency (Fv/Fm), PSII potential photochemical activity (Fv/Fo), absorption flux per cross section (CS; ABC/CSm), trapped energy flux per CS (TRo/CSm), and electron transport flux per CS (ETo/CSm), which increased by 49%, 65%, 17%, 12%, 4%, 25%, 10%, 15%, and 30%, respectively, compared with CK. The study also found that BA and VA rates could effectively improve tomato yield and water use efficiency (WUE). The yield under BA3, VA3, BA5, and VA5 treatments was 21%, 33%, 23%, and 25% higher than that under CK, and the WUE increased from 31.2 kg·m−3 under CK to 41.4 kg·m−3 under VA3. Pearson correlation analysis indicated that the increment of photosynthesis showed a highly significant correlation with Fv/Fo, ABC/CSm, TRo/CSm, and ETo/CSm and enhanced the light energy absorbed, trapped, and transported per CS of plant leaves, thereby contributing to the increase in tomato yield. Therefore, for one-season tomato production, the application of 3% vermicompost was considered economical with regard to improving photosynthesis, enhancing WUE, and increasing tomato yield.
The Streptomyces scabiei Pathogenicity Factor Thaxtomin A Induces the Production of Phenolic Compounds in Potato Tubers
Authors: Isayenka Iauhenia , Beaudoin Nathalie
Published: November 2022

The phytotoxin thaxtomin A (TA) is the key pathogenicity factor synthesized by the bacteria Streptomyces scabiei, the main causal agent of common scab of potato (Solanum tuberosum L.). TA treatment of potato tuber flesh produces a brown color that was attributed to necrosis. The intensity of TA-induced browning was generally thought to correlate with potato sensitivity to the disease. In this study, we found that TA-induced browning was much more intense in the potato tuber flesh of the common scab moderately resistant variety Russet Burbank (RB) than that observed in tubers of the disease-susceptible variety Yukon Gold (YG). However, there was no significant difference in the level of TA-induced cell death detected in both varieties, suggesting that tubers response to TA does not correlate with the level of sensitivity to common scab. TA-treated potato tuber tissues accumulated significantly higher levels of phenolic compounds than untreated controls, with a higher phenol content detected in RB TA-treated tissues than in those of YG. Browning was associated with a significant induction of the expression of genes of the phenylpropanoid pathway in RB tubers, indicating that TA activated this metabolic pathway. These results suggest that tuber flesh browning induced by TA is due to the accumulation of phenolic compounds. These phenolics may play a role in the protection of potato tubers against S. scabiei.
Investigation on Elastic Constants of Microfibril Reinforced Poly Vinyl Chloride Composites Using Impulsive Excitation of Vibration
Authors: Aravindh Sampath , Venkatachalam Gopalan
Published: November 2022

The creation of tenable green composites is in high demand, due to ecologically available resources paving the way for applications to thrive in the manufacturing, aerospace, structural, and maritime industries. Hence, it is vital to understand the performance characteristics of natural fiber-reinforced polymer composites. The elastic constants of coir fiber powder-reinforced plasticized polyvinyl chloride composite are determined using impulsive excitation vibration in this study. The optimization study on the elastic constants was carried out using Box–Behnken experimental design, based on response surface methodology, having three factors of fiber content (wt.%), fiber size (μm) and chemical treatments. The results were evaluated using analysis of variance and regression analysis. Additionally, experimental and optimized results were compared, leading to error analysis. Young’s modulus of 18.2 MPa and shear modulus of 6.6 MPa were obtained for a combination of fiber content (2 wt%), fiber size (225 μm), and triethoxy (ethyl) silane treatment, which is suitable for various electrical, automotive, etc., applications.
Indicators of Impact Selected Municipal Units on the Air Quality—Case Study from Poland and Romania
Authors: Oana Irimia , Grzegorz Przydatek , Mirela Panainte-Lehadus , Claudia Tomozei , Emilian Mosnegutu , Piotr Gawron
Published: November 2022

A 2020 investigation into air quality in urban areas found that nitrogen oxide and PM10 concentrations were above average. With the exception of summer, three seasons were found to have the highest nitrogen oxide concentrations, with a significant decrease during COVID-19. The significant PM10 relationship showed how communication affects the worsening of air quality, especially in the winter. The highest concentration of nitrogen oxide of 53.99 µg m−3 indicated the possibility of advection of pollutants from outside the agglomeration. The highest level of nitrogen oxide content, 95.95 µg m−3 in the atmospheric air, confirmed the significant presence of pollutants of communication origin. The advancement of electro-mobility and the application of cutting-edge technologies alongside renewable energy sources may contribute to a decrease in the amount of harmful substances released into the atmosphere.
Numerical Study of the Energy Flow Characteristics of Multi-Stage Pump as Turbines
Authors: Ye Sikun , Li Xiaojun , Zhu Zuchao , Li Linmin , Lin Tong
Published: November 2022

Multi-stage pump as turbine (PAT) has a wider range of heads and application intervals compared to single-stage PAT. In our research, we have conducted experimental and numerical simulation studies on this issue. In this paper, based on experimental research, numerical simulation is applied to calculate the multi-stage PAT flow field. The flow characteristics of multi-stage PAT under different working conditions are studied using the entropy production theory. Finally, the Pearson correlation coefficient is used to evaluate the relationship between the hydraulic loss and entropy production of the impellers and guide vanes. The entropy production theory is used to determine the location where the multi-stage PAT energy loss occurs compared with the traditional pressure drop assessment method. The results show that the trend of the numerical simulation results is consistent with the experimental results. The energy loss in the multi-stage PAT is calculated combined with the impeller and guide vane which accounts for 69.1–73% of the total energy loss under all flow conditions. The total entropy production rate of each component under design flow conditions is listed in decreasing order: impeller, guide vane, front and back chamber, a balance disk, and inlet and outlet volute. The first stage component has a larger energy loss compared with the rest of the stages. The magnitude of energy loss is closely related to physical quantities such as flow field velocity and skin friction coefficient. Furthermore, the distribution of streamlines and vortex cores at the impellers reflects that flow domain stability increases from the first stage impeller to the fifth stage impeller. The correlation between entropy production and hydraulic loss was evaluated by the Pearson correlation coefficient. Therefore, using the entropy production theory can effectively identify the characteristics of the flow field and the location of energy losses. It provides a reference for the targeted optimization of multi-stage PAT.
Occurrence of Selected Emerging Contaminants in Southern Europe WWTPs: Comparison of Simulations and Real Data
Authors: Sol Daniel , Menéndez-Manjón Andrea , Arias-García Paula , Laca Amanda , Laca Adriana , Rancaño Amador , Díaz Mario
Published: November 2022

Emerging contaminants (ECs) include a diverse group of compounds not commonly monitored in wastewaters, which have become a global concern due to their potential harmful effects on aquatic ecosystems and human health. In the present work, six ECs (ibuprofen, diclofenac, erythromycin, triclosan, imidacloprid and 17α-ethinylestradiol) were monitored for nine months in influents and effluents taken from four wastewater treatment plants (WWTPs). Except for the case of ibuprofen, which was in all cases in lower concentrations than those usually found in previous works, results found in this work were within the ranges normally reported. Global removal efficiencies were calculated, in each case being very variable, even when the same EC and facility were considered. In addition, the SimpleTreat model was tested by comparing simulated and real ibuprofen, diclofenac and erythromycin data. The best agreement was obtained for ibuprofen which was the EC with the highest removal efficiencies.
Knowledge Production: Analysing Gender- and Country-Dependent Factors in Research Topics through Term Communities
Authors: Bakshi-Hamm Parminder , Hamm Andreas
Published: November 2022

Scholarly publications are among the most tangible forms of knowledge production. Therefore, it is important to analyse them, amongst other features, for gender or country differences and the incumbent inequalities. While there are many quantitative studies of publication activities and success in terms of publication numbers and citation counts, a more content-related understanding of differences in the choice of research topics is rare. The present paper suggests an innovative method of using term communities in co-occurrence networks for detecting and evaluating the gender- and country-specific distribution of topics in research publications. The method is demonstrated with a pilot study based on approximately a quarter million of publication abstracts in seven diverse research areas. In this example, the method validly reconstructs all obvious topic preferences, for instance, country-dependent language-related preferences. It also produces new insight into country-specific research focuses. It emerges that in all seven subject areas studied, topic preferences are significantly different depending on whether all authors are women, all authors are men, or there are female and male co-authors, with a tendency of male authors towards theoretical core topics, of female authors towards peripheral applied topics, and of mixed-author teams towards modern interdisciplinary topics.
Thermographic Imaging in Cultural Heritage: A Short Review
Authors: Dritsa Vasiliki , Orazi Noemi , Yao Yuan , Paoloni Stefano , Koui Maria , Sfarra Stefano
Published: November 2022

Over the recent period, there has been an increasing interest in the use of pulsed infrared thermography (PT) for the non-destructive evaluation of Cultural Heritage (CH). Unlike other techniques that are commonly employed in the same field, PT enables the depth-resolved detection of different kinds of subsurface features, thus providing helpful information for both scholars and restorers. Due to this reason, several research activities are currently underway to further improve the PT effectiveness. In this manuscript, the specific use of PT for the analysis of three different types of CH, namely documentary materials, panel paintings–marquetery, and mosaics, will be reviewed. In the latter case, i.e., mosaics, passive thermography combined with ground penetrating radar (GPR) and digital microscopy (DM) have also been deepened, considering their suitability in the open field. Such items have been selected because they are characterized by quite distinct physical and structural properties and, therefore, different PT (and, in some cases, verification) approaches have been employed for their investigations.
Optimization of the Trajectory, Transmit Power, and Power Splitting Ratio for Maximizing the Available Energy of a UAV-Aided SWIPT System
Authors: Park Gitae , Lee Kisong
Published: November 2022

In this study, we investigate the maximization of the available energy for an unmanned aerial vehicle (UAV)-aided simultaneous wireless information and power transfer (SWIPT) system, in which the ground terminals (GTs) decode information and collect energy simultaneously from the downlink signal sent by the UAV based on a power splitting (PS) policy. To guarantee that each GT has a fair amount of available energy, our aim is to optimize the trajectory and transmit power of the UAV and the PS ratio of the GTs to maximize the minimum average available energy among all GTs while ensuring the average spectral efficiency requirement. To address the nonconvexity of the formulated optimization problem, we apply a successive convex optimization technique and propose an iterative algorithm to derive the optimal strategies of the UAV and GTs. Through performance evaluations, we show that the proposed scheme outperforms the existing baseline schemes in terms of the max–min available energy by adaptively controlling the optimization variables according to the situation.
In Vivo Penetrating Microelectrodes for Brain Electrophysiology
Authors: Erofeev Alexander , Antifeev Ivan , Bolshakova Anastasia , Bezprozvanny Ilya , Vlasova Olga
Published: November 2022

In recent decades, microelectrodes have been widely used in neuroscience to understand the mechanisms behind brain functions, as well as the relationship between neural activity and behavior, perception and cognition. However, the recording of neuronal activity over a long period of time is limited for various reasons. In this review, we briefly consider the types of penetrating chronic microelectrodes, as well as the conductive and insulating materials for microelectrode manufacturing. Additionally, we consider the effects of penetrating microelectrode implantation on brain tissue. In conclusion, we review recent advances in the field of in vivo microelectrodes.
Optimized Acoustic Phantom Design for Characterizing Body Sound Sensors
Authors: Rennoll Valerie , McLane Ian , Elhilali Mounya , West James E.
Published: November 2022

Many commercial and prototype devices are available for capturing body sounds that provide important information on the health of the lungs and heart; however, a standardized method to characterize and compare these devices is not agreed upon. Acoustic phantoms are commonly used because they generate repeatable sounds that couple to devices using a material layer that mimics the characteristics of skin. While multiple acoustic phantoms have been presented in literature, it is unclear how design elements, such as the driver type and coupling layer, impact the acoustical characteristics of the phantom and, therefore, the device being measured. Here, a design of experiments approach is used to compare the frequency responses of various phantom constructions. An acoustic phantom that uses a loudspeaker to generate sound and excite a gelatin layer supported by a grid is determined to have a flatter and more uniform frequency response than other possible designs with a sound exciter and plate support. When measured on an optimal acoustic phantom, three devices are shown to have more consistent measurements with added weight and differing positions compared to a non-optimal phantom. Overall, the statistical models developed here provide greater insight into acoustic phantom design for improved device characterization.
Super-Resolution Reconstruction Method of Pavement Crack Images Based on an Improved Generative Adversarial Network
Authors: Yuan Bo , Sun Zhaoyun , Pei Lili , Li Wei , Ding Minghang , Hao Xueli
Published: November 2022

A super-resolution reconstruction approach based on an improved generative adversarial network is presented to overcome the huge disparities in image quality due to variable equipment and illumination conditions in the image-collecting stage of intelligent pavement detection. The nonlinear network of the generator is first improved, and the Residual Dense Block (RDB) is created to serve as Batch Normalization (BN). The Attention Module is then formed by combining the RDB, Gated Recurrent Unit (GRU), and Conv Layer. Finally, a loss function based on the L1 norm is utilized to replace the original loss function. The experimental findings demonstrate that the self-built pavement crack dataset’s Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) of the reconstructed images reach 29.21 dB and 0.854, respectively. The results improved compared to the Set5, Set14, and BSD100 datasets. Additionally, by employing Faster-RCNN and a Fully Convolutional Network (FCN), the effects of image reconstruction on detection and segmentation are confirmed. The findings indicate that the segmentation results’ F1 is enhanced by 0.012 to 0.737 and the detection results’ confidence is increased by 0.031 to 0.9102 when compared to state-of-the-art methods. It has a significant engineering application value and can successfully increase pavement crack-detecting accuracy.
Sensor-to-Image Based Neural Networks: A Reliable Reconstruction Method for Diffuse Optical Imaging of High-Scattering Media
Authors: Yuliansyah Diannata Rahman , Pan Min-Chun , Hsu Ya-Fen
Published: November 2022

Imaging tasks today are being increasingly shifted toward deep learning-based solutions. Biomedical imaging problems are no exception toward this tendency. It is appealing to consider deep learning as an alternative to such a complex imaging task. Although research of deep learning-based solutions continues to thrive, challenges still remain that limits the availability of these solutions in clinical practice. Diffuse optical tomography is a particularly challenging field since the problem is both ill-posed and ill-conditioned. To get a reconstructed image, various regularization-based models and procedures have been developed in the last three decades. In this study, a sensor-to-image based neural network for diffuse optical imaging has been developed as an alternative to the existing Tikhonov regularization (TR) method. It also provides a different structure compared to previous neural network approaches. We focus on realizing a complete image reconstruction function approximation (from sensor to image) by combining multiple deep learning architectures known in imaging fields that gives more capability to learn than the fully connected neural networks (FCNN) and/or convolutional neural networks (CNN) architectures. We use the idea of transformation from sensor- to image-domain similarly with AUTOMAP, and use the concept of an encoder, which is to learn a compressed representation of the inputs. Further, a U-net with skip connections to extract features and obtain the contrast image, is proposed and implemented. We designed a branching-like structure of the network that fully supports the ring-scanning measurement system, which means it can deal with various types of experimental data. The output images are obtained by multiplying the contrast images with the background coefficients. Our network is capable of producing attainable performance in both simulation and experiment cases, and is proven to be reliable to reconstruct non-synthesized data. Its apparent superior performance was compared with the results of the TR method and FCNN models. The proposed and implemented model is feasible to localize the inclusions with various conditions. The strategy created in this paper can be a promising alternative solution for clinical breast tumor imaging applications.
Open-Space Vehicle Positioning Algorithm Based on Detection and Tracking in Video Sequences
Authors: Zheng Zhaoyu , Zhang Kai
Published: November 2022

In on-street parking lots, it is very important to obtain the positions and license plate numbers of the vehicles for charging and management. Existing algorithms usually detect vehicles from an input image first, then localize their license plates, and finally recognize the license plate numbers. However, they are of high time and space complexity and cannot work if the vehicles or license plates are obscured. Therefore, this paper proposes an open-space vehicle positioning algorithm based on detection and tracking in video sequences. The work is as follows: (1) To reduce the time and space complexity, parallel detection of vehicles and license plates is carried out. Then, geometric matching is performed to accomplish the correspondences between them. (2) To track vehicles and license plates, this paper improves DeepSORT by combining with integrated voting based on the historical license plate library. (3) To accurately judge the vehicle behavior of entry or exit, a cumulative state detector is designed to increase the fault-tolerance of the proposed algorithm. The experimental results reveal that the proposed algorithm makes improvements in model parameters, inference speed, and tracking accuracy, demonstrating that it can be well applied to open-space vehicle positioning.
Applying Self-Supervised Representation Learning for Emotion Recognition Using Physiological Signals
Authors: Montero Quispe Kevin G. , Utyiama Daniel M. S. , dos Santos Eulanda M. , Oliveira Horácio A. B. F. , Souto Eduardo J. P.
Published: November 2022

The use of machine learning (ML) techniques in affective computing applications focuses on improving the user experience in emotion recognition. The collection of input data (e.g., physiological signals), together with expert annotations are part of the established standard supervised learning methodology used to train human emotion recognition models. However, these models generally require large amounts of labeled data, which is expensive and impractical in the healthcare context, in which data annotation requires even more expert knowledge. To address this problem, this paper explores the use of the self-supervised learning (SSL) paradigm in the development of emotion recognition methods. This approach makes it possible to learn representations directly from unlabeled signals and subsequently use them to classify affective states. This paper presents the key concepts of emotions and how SSL methods can be applied to recognize affective states. We experimentally analyze and compare self-supervised and fully supervised training of a convolutional neural network designed to recognize emotions. The experimental results using three emotion datasets demonstrate that self-supervised representations can learn widely useful features that improve data efficiency, are widely transferable, are competitive when compared to their fully supervised counterparts, and do not require the data to be labeled for learning.
Pavement Quality Evaluation Using Connected Vehicle Data
Authors: Mahlberg Justin A. , Li Howell , Zachrisson Björn , Leslie Dustin K. , Bullock Darcy M.
Published: November 2022

Modern vehicles have extensive instrumentation that can be used to actively assess the condition of infrastructure such as pavement markings, signs, and pavement smoothness. Currently, pavement condition evaluations are performed by state and federal officials typically using the industry standard of the International Roughness Index (IRI) or visual inspections. This paper looks at the use of on-board sensors integrated in Original Equipment Manufacturer (OEM) connected vehicles to obtain crowdsource estimates of ride quality using the International Rough Index (IRI). This paper presents a case study where over 112 km (70 mi) of Interstate-65 in Indiana were assessed, utilizing both an inertial profiler and connected production vehicle data. By comparing the inertial profiler to crowdsourced connected vehicle data, there was a linear correlation with an R2 of 0.79 and a p-value of <0.001. Although there are no published standards for using connected vehicle roughness data to evaluate pavement quality, these results suggest that connected vehicle roughness data is a viable tool for network level monitoring of pavement quality.
A Hybrid State/Disturbance Observer-Based Feedback Control of Robot with Multiple Constraints
Authors: Xu Du , Hu Tete , Ma Ying , Shu Xin
Published: November 2022

Controlling the manipulator is a big challenge due to its hysteresis, deadzone, saturation, and the disturbances of actuators. This study proposes a hybrid state/disturbance observer-based multiple-constraint control mechanism to address this difficulty. It first proposes a hybrid state/disturbance observer to simultaneously estimate the unmeasurable states and external disturbances. Based on this, a barrier Lyapunov function is proposed and implemented to handle output saturation constraints, and a back-stepping control method is developed to provide sufficient control performance under multiple constraints. Furthermore, the stability of the proposed controller is analyzed and proved. Finally, simulations and experiments are carried out on a 2-DOF and 6-DOF robot, respectively. The results show that the proposed control method can effectively achieve the desired control performance. Compared with several commonly used control methods and intelligent control methods, the proposed method shows superiority. Experiments on a 6-DOF robot verify that the proposed method has good tracking performance for all joints and does not violate constraints.
Crystalline Hydrate Dehydration Sensing Based on Integrated Terahertz Whispering Gallery Mode Resonators
Authors: Hou Zhibo , Yuan Shixing , Deng Wentao , Cai Jiahua , Qiu Yaqin , Zhao Yunong , Wang Ziwei , Chen Liao , Liu Huan , Wu Xiaojun , Zhang Xinliang
Published: November 2022

Water molecules play a very important role in the hydration and dehydration process of hydrates, which may lead to distinct physical and chemical properties, affecting their availability in practical applications. However, miniaturized, integrated sensors capable of the rapid, sensitive sensing of water molecules in the hydrate are still lacking, limiting their proliferation. Here, we realize the high-sensitivity sensing of water molecules in copper sulfate pentahydrate (CuSO4·5H2O), based on an on-chip terahertz whispering gallery mode resonator (THz-WGMR) fabricated on silicon material via CMOS-compatible technologies. An integrated THz-WGMR with a high-Q factor of 3305 and a resonance frequency of 410.497 GHz was proposed and fabricated. Then, the sensor was employed to distinguish the CuSO4·xH2O (x = 5, 3, 1). The static characterization from the CuSO4·5H2O to the copper sulfate trihydrate (CuSO4·3H2O) experienced blueshifts of 0.55 GHz/μmol, whereas the dehydration process of CuSO4·3H2O to copper sulfate monohydrate (CuSO4·H2O) exhibited blueshifts of 0.21 GHz/μmol. Finally, the dynamic dehydration processes of CuSO4·5H2O to CuSO4·3H2O at different temperatures were monitored. We believe that our proposed THz-WGMR sensors with highly sensitive substance identification capabilities can provide a versatile and integrated platform for studying the transformation between substances, contributing to hydrated/crystal water-assisted biochemical applications.
Molecular Docking Studies on Methanolic Propolis Extracts Collected from Different Regions in Saudi Arabia as a Potential Inhibitor of Topoisomerase IIβ
Authors: Al-Khalaf Areej A. , Alabdelkareem Ibrahim , Al-Rejaie Salim S. , Mohany Mohamed , Hozzein Wael N.
Published: November 2022

Propolis is a sticky substance made by honeybees from various plant parts that is rich in biologically active substances such as flavonoids, phenolic acids, and phenolics and has a wide range of applications in the food, cosmetics, and pharmaceutical industries. The current study focused on the isolation of honeybee propolis samples from three different locations in Saudi Arabia: Al Hada, Baljurashi, and Rawdat Khuraim, and the evaluation of their anti-cancer effect against human liver cancer cell lines (HeP-G2) and human breast cancer cell lines (MCF-7). Five chemical compounds present in the methanolic extract of propolis honeybee were detected by HPLC. Furthermore, molecular modeling studies were conducted to explain the mechanism of anti-cancer activity exerted by the active compounds. The propolis samples collected from the three isolation sites had anti-cancer activity against MCF-7 and HeP-G2. Samples collected from the Rawdat Khuraim site showed the highest inhibitory activity reaching 81.5% and 83.2% against MCF-7 and HeP-G2, respectively. HPLC detected four main active compounds from propolis samples: pinobanksin, pinocembrin, galangin, and xanthomicrol. The molecular docking technique showed that galangin and pinocembrin had higher anti-cancer activity than xanthomicrol and pinobanksin as the binding affinity of galangin and pinocembrin with the active sites of the topoisomerase IIβ enzyme was much greater.
Characterization of the Toxicological Impact of Heavy Metals on Human Health in Conjunction with Modern Analytical Methods
Authors: Filipoiu Dana Claudia , Bungau Simona Gabriela , Endres Laura , Negru Paul Andrei , Bungau Alexa Florina , Pasca Bianca , Radu Andrei-Flavius , Tarce Alexandra Georgiana , Bogdan Mihaela Alexandra , Behl Tapan , Nechifor Aurelia Cristina , Hassan Syed Shams ul , Tit Delia Mirela
Published: November 2022

Increased environmental pollution, urbanization, and a wide variety of anthropogenic activities have led to the release of toxic pollutants into the environment, including heavy metals (HMs). It has been found that increasing concentrations of HMs lead to toxicity, mineral imbalances, and serious diseases, which are occurring more and more frequently. Therefore, testing has become imperative to detect these deficiencies in a timely manner. The detection of traces of HMs, especially toxic ones, in human tissues, various biological fluids, or hair is a complex, high-precision analysis that enables early diagnosis, addressing people under constant stress or exposed to a toxic environment; the test also targets people who have died in suspicious circumstances. Tissue mineral analysis (TMA) determines the concentration of toxic minerals/metals at the intracellular level and can therefore determine correlations between measured concentrations and imbalances in the body. Framing the already-published information on the topic, this review aimed to explore the toxicity of HMs to human health, the harmful effects of their accumulation, the advantages vs. the disadvantages of choosing different biological fluids/tissues/organs necessary for the quantitative measurement of HM in the human body, as well as the choice of the optimal method, correlated with the purpose of the analysis.
Phytochemical, Antimalarial, and Acute Oral Toxicity Properties of Selected Crude Extracts of Prabchompoothaweep Remedy in Plasmodium berghei-Infected Mice
Authors: Plirat Walaiporn , Chaniad Prapaporn , Phuwajaroanpong Arisara , Septama Abdi Wira , Punsawad Chuchard
Published: November 2022

Malaria remains a life-threatening health problem and encounters with the increasing of antimalarial drug resistance. Medicinal plants play a critical role in synthesizing novel and potent antimalarial agents. This study aimed to investigate the phytochemical constituents, antiplasmodial activity, and evaluate the toxicity of crude ethanolic extracts of Myristica fragrans, Atractylodes lancea, and Prabchompoothaweep remedy in a mouse model. The phytochemical constituents were characterized by liquid chromatography-mass spectrometry (LC-MS). Antimalarial efficacy against Plasmodium berghei was assessed using 4-day suppressive tests at doses of 200, 400, and 600 mg/kg body weight. Acute toxicity was assessed at a dose of 2000 mg/kg body weight of crude extracts. The 4-day suppression test showed that all crude extracts significantly suppressed parasitemia (p < 0.05) compared to the control group. Higher parasitemia suppression was observed both in Prabchompoothaweep remedy at a dose of 600 mg/kg (60.1%), and A. lancea at a dose of 400 mg/kg (60.1%). The acute oral toxicity test indicated that the LD50 values of all extracts were greater than 2000 mg/kg and that these extracts were not toxic in the mouse model. LC-MS analysis revealed several compounds in M. fragrans, A. lancea, and Prabchompoothaweep remedy. For quantitative analysis, 1,2,6,8-tetrahydroxy-3-methylanthraquinone 2-O-b-D-glucoside, chlorogenic acid, and 3-O-(beta-D-glucopyranosyl-(1->6)-beta-D-glucopyranosyl) ethyl 3-hydroxyoctanoate were found in A. lancea, while (7′x,8′x)-4,7′-epoxy-3,8′-bilign-7-ene-3,5′-dimethoxy-4′,9,9′-triol, edulisin III, and tetra-hydrosappanone A trimethyl ether are found in M. fragrans. 6′-O-Formylmarmin was present in the Prabchompoothaweep remedy, followed by pterostilbene glycinate and amlaic acid. This study showed that the ethanolic extracts of A. lancea and Prabchompoothaweep remedy possess antimalarial activity against Plasmodium berghei. None of the extracts had toxic effects on liver and kidney function. Therefore, the ethanolic extract of A. lancea rhizome and Prabchompoothaweep remedy could be used as an alternative source of new antimalarial agents. Further studies are needed to determine the active compounds in both extracts.
Exploring Gauge Theories with Adjoint Matter on the Lattice
Authors: Bergner Georg , Münster Gernot , Piemonte Stefano
Published: November 2022

We review our efforts in investigating gauge theories with fermions in the adjoint representation of the gauge group by means of numerical simulations. These theories have applications in possible extensions of the standard model of particle physics, being a core part of supersymmetric gauge theories. They also play an important role in uncovering fundamental properties of strongly interacting theories due to distinct features, such as a substantially different phase diagram.
The Relationship between Health Literacy and COVID-19 Vaccination Prevalence during a Rapidly Evolving Pandemic and Infodemic
Authors: Feinberg Iris , Scott Jane Yoon , Holland David P. , Lyn Rodney , Scott Lia C. , Maloney Kevin M. , Rothenberg Richard
Published: November 2022

The gap between how health information is communicated and what people understand and can use to make informed health decisions is called health literacy. This gap was exacerbated by the rapidly changing and excessive volume of information, misinformation, and disinformation during the COVID-19 pandemic. People with lower health literacy may not have understood the importance of COVID-19 vaccination for themselves or for their communities. Our aim was to understand health literacy levels within Fulton County, Georgia, and their relationship to vaccine prevalence. Fulton county residents ages 18 and over (n = 425) completed an on-line Health Literacy Questionnaire. Individual, organizational, functional, interactive, and critical health literacy scales were created. Vaccination prevalence data were collected from the Georgia Vaccine Distribution Dashboard. All data were divided into one of three county areas. There were statistically significant variations in vaccine prevalence χ2(3) = 29.325, p < 0.001 among the three county areas. All levels of health literacy predicted overall county vaccination prevalence F (4,420) = 85.941, p < 0.001, There were significant differences in health literacy levels among two of the three county area pairs; the lowest resourced county area had the lowest vaccination prevalence and health literacy rates. This is the first example of relating direct health literacy measures across a major metropolitan US county with vaccine prevalence data.
Study of psycho-emotional reactions of drug-dependent persons in conflict situations
Authors:   Moscow Medical University ", Ionov S. N. ,   Reaviz",   , Moscow, Russia, Romanovskaya N. Yu. ,   Moscow Medical University "Reaviz", Moscow, Russia, Krylova E. V. ,   Moscow Medical University "Reaviz", Moscow, Russia, Vrazovskaya E. A. ,   Moscow Medical University "Reaviz", Moscow, Russia
Published: November 2022

This article is devoted to the examination and analysis of theoretical approaches in the study of drug addiction regarding it as a psychophysiological mechanism. The most characteristic personality traits among people suffering from drug addiction are described in detail. The data of an empirical study of drug addicts’ behavior in conflict situations are presented. The main types of manifestation of reactions in conditions of stress and conflict are considered. The authors analyzed the results regarding the reactions of drug addicts in conflict situations. The most characteristic manifestations of personal qualities in conditions of stress and conflict are described.
Attitude to psychiatr y among medical students worldwide: a review
Authors:   Peoples' Friendship University of Russia, Orlova A. M. , Drozhzhina N. A. ,   Peoples' Friendship University of Russia, Lukyanchikova A. O. ,   Peoples' Friendship University of Russia
Published: November 2022

Mental disorders are currently very common, and it is believed that in Europe, by 2050, the number of patients will more than double. At the same time, there has been a steady decline in students’ interest in choosing psychiatry as their specialty. Therefore, students tend to research and identify factors leading to low interest in psychiatry and compare the impact of internships among medical students around the world, as it is no longer just a local problem, but a global problem
Hemophilia in the practice of a general practitioner and hematologist
Authors:   FSBEI HE Volgograd State Medical University, Skvortsov V. V. , Durnoglazova K. A. ,   FSBEI HE Volgograd State Medical University, Lyoshina O. A. ,   FSBEI HE Volgograd State Medical University
Published: November 2022

Hemophilia is a rare disease whose approved treatment options have remained virtually unchanged for 50 years. However, over the past decade there has been an innovation boom in treatment options that are either under development or have been approved for the treatment of hemophilia, including engineered clotting factors and a vast range of new approaches and techniques. Some of these new techniques, especially gene therapy, show proof of principle in hemophilia, but may have wider applications. These advances, combined with improved diagnostics, are now enabling clinicians to improve standards of care for people with hemophilia. The various mechanisms of action and modifications used in these therapies have implications for their safe and effective use, which must be balanced with their therapeutic utility.