bluuebunny/crossref_metadata_2025 huggingface dataset:
Aloysia citrodora Extracts Cultivated in Greece as Antioxidants and Potent Regulators of Food Microbiota
Authors: Gkalpinos Vasileios K. , Anagnostou Vasiliki A. , Mitropoulou Gregoria , Kompoura Vasiliki , Karapantzou Ioanna , Fasoulis Christodoulos K. , Vasdekis Efstathios P. , Kourkoutas Yiannis , Tzakos Andreas G.
Published: March 2023

Plant extracts contain valuable sources of biologically active molecules and, lately, have attracted scientific and industrial interest as inhibitors of food-borne pathogens and growth stimulators of beneficial microbes. In this vein, the aim of this study was to explore and exploit the effect of Aloysia citrodora extracts as potent functional regulators of food microbiota by stimulating the growth of probiotic strains and by suppressing the evolution of common food-spoilage and pathogenic bacteria. Aqueous and ethanolic extracts of A. citrodora, rich in polyphenols, were prepared and their phytochemical composition was unveiled by LC-triple quadruple and LC-QToF mass spectrometry. The growth stimulatory activity of a wild-type Lacticaseibacillus rhamnosus strain, along with L. rhamnosus GG, used as a control, was assessed by monitoring cell growth in the presence of sodium chloride, bile salts, thermal stress, and alcohol. We found that the aqueous extract stimulated the growth of probiotic strains at 0.5 mg/mL. At the same concentration, stimulatory activity was observed for the wild-type L. rhamnosus in the presence of bile salts and alcohol and for L. rhamnosus GG in the presence of NaCl and under thermal stress. The ethanolic extract of A. citrodora exhibited prebiotic activity at 0.25 mg/mL, but did not promote the growth of the strains under the stress conditions tested. In addition, minimum inhibitory (MIC) and minimum bactericidal concentrations (MBC) against food-spoilage and pathogenic microbes were determined. The strongest growth inhibitory activity of foodborne pathogens was noted by the A. citrodora ethanolic extract, while the aqueous A. citrodora extract had no effect against Escherichia coli. Importantly, the spoilage and pathogenic microbes tested were more sensitive to the extracts than the probiotic strains, indicating a significant contribution to the functional regulation of food microbiota, provided that they are used at the optimum concentration.
Motion Control Method of Bionic Robot Dog Based on Vision and Navigation Information
Authors: Li Zhaolu , Xu Ning , Zhang Xiaoli , Peng Xiafu , Song Yumin
Published: March 2023

With the progress and development of AI technology and industrial automation technology, AI robot dogs are widely used in engineering practice to replace human beings in high-precision and tedious industrial operations. Bionic robots easily produce control errors due to the influence of spatial disturbance factors in the process of pose determination. It is necessary to calibrate robots accurately to improve the positioning control accuracy of bionic robots. Therefore, a robust control algorithm for bionic robots based on binocular vision navigation is proposed. An optical CCD binocular vision dynamic tracking system is used to measure the end position and pose parameters of a bionic robot, and the kinematics model of the controlled object is established. Taking the degree of freedom parameter of the robot’s rotating joint as the control constraint parameter, a hierarchical subdimensional space motion planning model of the robot is established. The binocular vision tracking method is used to realize the adaptive correction of the position and posture of the bionic robot and achieve robust control. The simulation results show that the fitting error of the robot’s end position and pose parameters is low, and the dynamic tracking performance is good when the method is used for the position positioning of control of the bionic robot.
Trust-Aware Fog-Based IoT Environments: Artificial Reasoning Approach
Authors: Ghaleb Mustafa , Azzedin Farag
Published: March 2023

Establishing service-driven IoT systems that are reliable, efficient, and stable requires building trusted IoT environments to reduce catastrophic and unforeseen damages. Hence, building trusted IoT environments is of great importance. However, we cannot assume that every node in wide-area network is aware of every other node, nor can we assume that all nodes are trustworthy and honest. As a result, prior to any collaboration, we need to develop a trust model that can evolve and establish trust relationships between nodes. Our proposed trust model uses subjective logic as a default artificial reasoning over uncertain propositions to collect recommendations from other nodes in the IoT environment. It also manages and maintains existing trust relationships established during direct communications. Furthermore, it resists dishonest nodes that provide inaccurate ratings for malicious reasons. Unlike existing trust models, our trust model is scalable as it leverages a Fog-based hierarchy architecture which allows IoT nodes to report/request the trust values of other nodes. We conducted extensive performance studies, and confirm the efficiency of our proposed trust model. The results show that at an early stage of the simulation time (i.e., within the first 2% of the number of transactions), our trust model accurately captures and anticipates the behavior of nodes. Results further demonstrate that our proposed trust model isolates untrustworthy behavior within the same FCD and prevents untrustworthy nodes from degrading trustworthy nodes’ reputations.
Multi-Objective Optimization of LCC-S-Compensated IPT System for Improving Misalignment Tolerance
Authors: Yang Junfeng , Liu Rui , Tong Qingbin , Yang Xu , Liu Qiujiang , Yao Aifen
Published: March 2023

Due to their excellent performance, the inductor–capacitor–capacitor-series (LCC-S)-compensated topologies are extensively used in inductive power transfer (IPT) applications. However, perfect alignment of the system’s contactless couplers is difficult, which leads to serious deterioration of the system output characteristics. In this paper, the influence of the coupler misalignment on the performance of the conventional resonant system is studied. To obtain stable output against varying couplings and loads in a certain range, a novel parameter design method based on the multi-objective particle swarm optimization (MOPSO) algorithm is introduced. The multi-objective optimization framework is developed to analyze the Pareto trade-offs between three conflicting performance metrics, namely output current/voltage ripple, reactive power transmission and component stress. Optimization results depict that misalignment tolerances in both constant current output (CCO)-type and constant voltage output (CVO)-type LCC-S-compensated IPT systems are improved, while a wider load range is suitable for a CCO-type system using the method of compensation parameter optimization. Experimental results are highly consistent with the design, achieving a current fluctuation of no more than 10.5% with a load range from 50 Ω to 100 Ω and a voltage fluctuation of less than 10.4% with a narrow load from 90 Ω to 100 Ω over 100% of coupling variations (from 0.25 to 0.5).
Optical Radiation during Sputtering of Lithium into a Noble Gas Using a Nanosecond Electron Beam
Authors: Khasenov Mendykhan , Samarkhanov Kuanysh , Batyrbekov Erlan , Gordienko Yuriy , Kenzhina Inesh E. , Tulubayev Yevgeniy
Published: March 2023

The optical radiation in a gaseous medium upon the irradiation of a lithium layer with a fast electron beam of a 5 ns duration has been studied. The irradiation chamber was filled with argon, krypton, or xenon at a pressure of 10 kPa up to 60 kPa. The lines of lithium atoms appear in the emission spectrum at a lithium layer temperature of 650–680 K, and the intensity of these lines sharply increases with the increasing temperature of the lithium layer. The optical radiation arises from both the transitions of noble gas atoms and the transition of the lithium atom in a time of about 20–30 ns. The duration of the radiation pulses at half maximum at temperatures above 800 K was 60–100 ns at a wavelength of 610.4 nm and 140–220 ns at 670.8 nm in krypton and argon. The various mechanisms for the population of lithium levels during the radiation pulse are discussed.
Multiple Phase Stepping Generation in Alkali Metal Atoms: A Comparative Theoretical Study
Authors: Alhasan Abu Mohamed , Altowyan Abeer S. , Madkhli A. Y. , Abdulrhmann Salah
Published: March 2023

We theoretically demonstrated optical phase switches in light storage-like experiments. Typical light storage (LS) and retrieval experiments consist of the probe field in the probe channel with writing and reading fields across the drive branch, as well as its recovery. The probe and first drive pulses as the standard electromagnetically induced transparency (EIT) effect of storing light are used in the proposed scheme for the atomic excitations. A train of probe pulses is used after a short storage period to induce Raman gain in the drive channel. The proposed scheme was applied to alkali-metal atoms such as 23Na, 87Rb, and 39K vapours. Spatiotemporal phase variations for generated drive pulses were found to shape in the form of discrete phase distributions. The proposed approach in the process of obtaining phase discrete distributions for different irradiation intensities was tested. For weak fields, the discrete distributions were distinct as a result of the differences in the upper hyperfine structure (hf) and the atomic relaxations. However, for moderate fields, the discrete phase distributions are smeared by the atomic relaxations.
Analysis of Airglow Image Classification Based on Feature Map Visualization
Authors: Lin Zhishuang , Wang Qianyu , Lai Chang
Published: March 2023

All-sky airglow imagers (ASAIs) are used in the Meridian Project to observe the airglow in the middle and upper atmosphere to study the atmospheric perturbation. However, the ripples of airglow caused by the perturbation are only visible in the airglow images taken on a clear night. It is a problem to effectively select images suitable for scientific analysis from the enormous amount of airglow images captured under various environments due to the low efficiency and subjectivity of traditional manual classification. We trained a classification model based on convolutional neural network to distinguish between airglow images from clear nights and unclear nights. The data base contains 1688 images selected from the airglow images captured at Xinglong station (40.4° N, 30.5° E). The entire training process was tracked by feature maps which visualized every resulting classification model. The classification models with the clearest feature maps were saved for future use. We cropped the central part of the airglow images to avoid disturbance from the artificial lights at the edge of the vision field according to the feature maps of our first training. The accuracy of the saved model is 99%. The feature maps of five categories also indicate the reliability of the classification model.
Dynamic Responses of Semi-Flexible Pavements Used for the Autonomous Rail Rapid Transit
Authors: Pan Biao , Zhang Hongjian , Liu Song , Gong Minghui , Yang Jun
Published: March 2023

The application of a semi-flexible pavement (SFP) is an effective solution to solve the rutting problems of the autonomous rail rapid transit (ART) system. The service environment of an ART pavement is significantly different from that of the conventional pavement due to the large axle load and high tire pressure of ART vehicles. A test section was constructed in the Zhuzhou ART system and a tire–pavement coupling FE model was built to explore the distribution features of the dynamic responses as well as to optimize the material and structural design. The tire–pavement coupling model was firstly verified by the field test data and then, utilizing the validated model, the parameter study was performed to analyze the influence of the vehicle operating state and pavement conditions. The simulation results show that the transverse tensile strain at the bottom of the SFP layer is dominant for the fatigue cracking of the pavement. Properly reducing the tire pressure can effectively improve the tensile environment at the bottom of the SFP layer. The action of the braking force may cause significant longitudinal tensile strains at the surface of the SFP layer and lead to transverse cracking of the semi-flexible ART pavement. The interlayer bonding between the SFP layer and the asphalt layer has significant influence on the amplitude and distribution of tensile stress at the bottom of the SFP layer. Moreover, to optimize the tensile environment of the semi-flexible ART pavement, the thickness of the SFP layer and the asphalt concrete layer cannot differ too much under the premise of meeting the requirements of rutting resistance performance.
Minimization of the Decoupling Circuit (DC-Link) in Induction Motors
Authors: Carrillo-Santos Luis Mauricio , Ponce-Silva Mario , Hernández-González Leobardo , Calzada-Lara Gabriel , Reyes-Severiano Yesenia , Juarez-Sandoval Oswaldo Ulises
Published: March 2023

There is currently a growing interest in replacing the internal combustion engine with electric motors in transportation applications. However, there are different problems related to electric motors for this application. One of them is the oversizing of the energy decoupling system since to ensure that the decoupling capacitor can store the power fluctuations, the capacitance required by the system is usually oversized. This leads to preference for the use of capacitors with construction technologies that have a lower lifetime than the remaining elements of the propulsion system, directly affecting the reliability of the system. In this article, the energy flow handled by the decoupling capacitor is analyzed considering the critical case of operation of an induction motor to minimize the capacitance required by the propulsion system; emphasizing the conditions that generate a higher energy return, from the motor mode of the electric machine to the decoupling capacitor. From the energy analysis, an equation for the capacitor calculation is obtained, involving proportionality factors that relate to the different operating powers, reducing up to 62.2% of the capacitance value required by the decoupling system, under conditions of maximum energy return in motor mode, compared to existing equations in the literature.
Economic Integrated Structural Framing for BIM-Based Prefabricated Mechanical, Electrical, and Plumbing Racks
Authors: Baek Seungchan , Won Jongsung , Jang Sejun
Published: March 2023

Prefabrication, one of the methods to increase productivity by moving construction activity to factory work, has evolved into multi-trade prefabrication. Although previous studies have introduced the merits and directions of multi-trade prefabrication technology, various design and installation techniques must be developed for the economical application of multi-trade prefabrication. This study aims to provide an economical design for prefabricated mechanical, electrical, and plumbing (MEP) rack (PMR) structural framing. We proposed five types of PMR structural framing techniques and analyzed their required channel material and labor inputs through a pilot test. The efficiency of PMR structural frames was examined by adjusting the supporting interval, moving the duct outside, and removing the upper framing. Economics and productivity analysis revealed that removing the upper framing method was the most effective when the coordination period was secured. Adjusting the supporting intervals is also an economical design option. The findings of this study can help enhance the economic feasibility of prefabrication and modularization of construction and their widespread utilization.
ID Tech: A Virtual Reality Simulator Training for Teenagers with Intellectual Disabilities
Authors: Capallera Marine , Piérart Geneviève , Carrino Francesco , Cherix Robin , Rossier Amélie , Mugellini Elena , Abou Khaled Omar
Published: March 2023

People with intellectual disability (ID) should routinely train themselves to carry out a variety of daily challenging tasks while being supervised by one or more supervisors. Virtual reality (VR) technology enables the simulation of certain learning scenarios that would be risky or difficult to set up or repeatedly replicate in the actual world. This paper introduces a VR simulator created for this aim with the assistance of social educators. The purpose is to use VR to conduct learning exercises with teenagers with ID and assess the extent to which the abilities learned in VR can be transferred to the real world. This project focuses mainly on urban mobility with three types of exercise. A study was conducted with 18 students in five institutions for 7 months. Post-tests were also carried out after 1 month with 11 teenagers. In the end, four teenagers are completely autonomous in their travels: two travel on foot and two travel by public transport. Regarding the impact analysis, the results are stable over time regarding self-reported ease, satisfaction, and fatigability. Finally, the system received valuable feedback from the educators.
Combining the Transformer and Convolution for Effective Brain Tumor Classification Using MRI Images
Authors: Aloraini Mohammed , Khan Asma , Aladhadh Suliman , Habib Shabana , Alsharekh Mohammed F. , Islam Muhammad
Published: March 2023

In the world, brain tumor (BT) is considered the major cause of death related to cancer, which requires early and accurate detection for patient survival. In the early detection of BT, computer-aided diagnosis (CAD) plays a significant role, the medical experts receive a second opinion through CAD during image examination. Several researchers proposed different methods based on traditional machine learning (TML) and deep learning (DL). The TML requires hand-crafted features engineering, which is a time-consuming process to select an optimal features extractor and requires domain experts to have enough knowledge of optimal features selection. The DL methods outperform the TML due to the end-to-end automatic, high-level, and robust feature extraction mechanism. In BT classification, the deep learning methods have a great potential to capture local features by convolution operation, but the ability of global features extraction to keep Long-range dependencies is relatively weak. A self-attention mechanism in Vision Transformer (ViT) has the ability to model long-range dependencies which is very important for precise BT classification. Therefore, we employ a hybrid transformer-enhanced convolutional neural network (TECNN)-based model for BT classification, where the CNN is used for local feature extraction and the transformer employs an attention mechanism to extract global features. Experiments are performed on two public datasets that are BraTS 2018 and Figshare. The experimental results of our model using BraTS 2018 and Figshare datasets achieves an average accuracy of 96.75% and 99.10%, respectively. In the experiments, the proposed model outperforms several state-of-the-art methods using BraTS 2018 and Figshare datasets by achieving 3.06% and 1.06% accuracy, respectively.
Closed Form Constraint Equations Used to Express Frictionless Slip of Multibody Systems Attached to Finite Elements—Application to a Contact between a Double Pendulum and a Beam
Authors: Lipinski Krzysztof
Published: March 2023

This paper focuses on the numerical modeling of the dynamics of mechanical systems. Robots that can inspect high-voltage lines inspired this research. Their control systems must anticipate potential grab positions appropriately. We intend to formulate equations dedicated to the numerical description of the robot/cable contact. The investigated problem is not straightforward, since parts of the modeled systems are numerically inhomogeneous. They consist of multibody and finite element components. These components interact with each other only through frictionless point contact. We limit the present investigation to the mathematical modeling of these frictionless point connections. According to the model-adopted assumption, the location of the contact point is invariant in the multibody structure, but it is variable in the finite elements part. Unlike the classically used models (i.e., spring/damper models of elastic contacts), we focus on constraint equations. We present and discuss their details in this paper. Following the presence of the constraint equations, their associated Lagrange multipliers appear in the dynamics equations of the two sub-models. The main feature/result of the presently proposed method is the closed form of the coordinate-portioning formulae, proposed in this paper, employed to eliminate the dependent coordinates and the constraint-associated Lagrange multipliers. To verify the applicability of the proposed elimination methodology, we test its use in a dedicated numerical example. During the test, we limit the investigation to a frictionless connection between a double pendulum and a beam. The results confirm that the proposed methodology allows us to model the investigated frictionless contact. We shall underline a vital property, that the proposed elimination method is universal, and thus one can easily extend/modify the above methodology to operate with other multibody/finite element contacts.
Payload Camera Breadboard for Space Surveillance—Part I: Breadboard Design and Implementation
Authors: Filho Joel , Gordo Paulo , Peixinho Nuno , Melicio Rui , Gafeira Ricardo
Published: March 2023

The rapid increase of space debris poses a risk to space activities, so it is vital to develop countermeasures in terms of space surveillance to prevent possible threats. The current Space Surveillance Network is majorly composed of radar and optical telescopes that regularly observe and track space objects. However, these measures are limited by size, being able to detect only a tiny amount of debris. Hence, alternative solutions are essential for securing the future of space activities. Therefore, this paper proposes the design of a payload camera breadboard for space surveillance to increase the information on debris, particularly for the under-catalogued ones. The device was designed with similar characteristics to star trackers of small satellites and CubeSats. Star trackers are attitude devices usually used in satellites for attitude determination and, therefore, have a wide potential role as a major tool for space debris detection. The breadboard was built with commercial off-the-shelf components, representing the current space-camera resolution and field of view. The image sensor was characterized to compute the sensitivity of the camera and evaluate the detectability performance in several simulated positions. Furthermore, the payload camera concept was tested by taking images of the night sky using satellites as proxies of space debris, and a photometric analysis was performed to validate the simulated detectability performance.
A Novel Small Target Detection Strategy: Location Feature Extraction in the Case of Self-Knowledge Distillation
Authors: Liu Gaohua , Li Junhuan , Yan Shuxia , Liu Rui
Published: March 2023

Small target detection has always been a hot and difficult point in the field of target detection. The existing detection network has a good effect on conventional targets but a poor effect on small target detection. The main challenge is that small targets have few pixels and are widely distributed in the image, so it is difficult to extract effective features, especially in the deeper neural network. A novel plug-in to extract location features of the small target in the deep network was proposed. Because the deep network has a larger receptive field and richer global information, it is easier to establish global spatial context mapping. The plug-in named location feature extraction establishes the spatial context mapping in the deep network to obtain the global information of scattered small targets in the deep feature map. Additionally, the attention mechanism can be used to strengthen attention to the spatial information. The comprehensive effect of the above two can be utilized to realize location feature extraction in the deep network. In order to improve the generalization of the network, a new self-distillation algorithm was designed for pre-training that could work under self-supervision. The experiment was conducted on the public datasets (Pascal VOC and Printed Circuit Board Defect dataset) and the self-made dedicated small target detection dataset, respectively. According to the diagnosis of the false-positive error distribution, the location error was significantly reduced, which proved the effectiveness of the plug-in proposed for location feature extraction. The mAP results can prove that the detection effect of the network applying the location feature extraction strategy is much better than the original network.
The Effect of Local Doping of the Polymer–Polymer Interface Using Cu2O Particles
Authors: Lachinov Alexey N. , Karamov Danfis D. , Galiev Azat F. , Lachinov Alexey A. , Yusupov Azat R. , Shaposhnikova Vera V. , Salazkin Sergey N. , Chebotareva Alla B.
Published: March 2023

Electrically conductive polymer materials are increasingly being used as electronic materials, for example, in thin-film transistors. However, the low mobility of charge carriers limits their use. One of the ways to increase the mobility of charge carriers can be the use of interface conductivity along the regions separating the two polymer films. It is important that it could be realized with non-conjugated polymers. There is no direct experimental evidence that the transport of charge carriers occurs along such an interface. It is impossible to deny the possibility of transport on the surfaces of polymer films. The purpose of this work is to study the current flow path in a multilayer sample by marking the polymer–polymer interface with a doping nanolayer of a Cu2O island film. Spectral methods in the field of electronic absorption of copper oxide were used to control the island film. The electronic parameters of the polymer–polymer interface were studied using injection methods and volt-ampere characteristics. Atomic force microscopy was used to control the thickness and uniformity of the samples. It was found that the doping of the polymer–polymer interface using Cu2O particles strongly affects the transport of charge carriers; in particular, the conductivity of the structure increases. It is established that this is due to an increase in the mobility of the charge carriers and a decrease in the height of the potential barrier at the 3D metal–2D interface area. Thus, it is established that the transport of charge carriers occurs along the polymer–polymer interface at the structure parameters specified in this work.
Evaluation of the Effectiveness of Overheated Dry-Saturated Steam Disinfection in the Control of the Dental Chair Contamination by Bioluminescence Analysis: A Pilot In Vitro Study
Authors: Luppieri Valentina , Giangreco Manuela , Chermetz Maddalena , Ronfani Luca , Cadenaro Milena
Published: March 2023

This study aimed to evaluate, through Adenosine triphosphate (ATP) bioluminescence analysis, the effectiveness of an overheated dry-saturated steam device (Polti Sani System) in decreasing the superficial microbial contamination on dental chairs’ surfaces after 30 s steam disinfection (T1) in comparison to baseline (T0), i.e., at the end of an aerosol-generating procedure (AGDP), and to investigate any differences in the tested surfaces’ contamination at T0 in relation to the surface’s type. Three dental chair surfaces (scialytic lamp, control button panel, spit bowl), sized 10 × 10 cm each, were swabbed and analyzed before and after steam application. The procedure was repeated 20 times for a total of 60 before–after evaluations. Non-parametric tests were used to analyze Relative Light Unit (RLU) values and categorical data on the ATP molecules’ amount detected on the tested surfaces. Statistically significant differences were found for both RLU and categorical data for all surfaces, and each type of surface evaluated at T0 and T1 (p < 0.05). Differences in RLU among the tested surfaces at T0 were not significant. By reducing the microbial contamination on the evaluated surfaces, the overheated dry-saturated steam system was an effective measure for the disinfection of the dental chair’s surfaces after AGDPs, potentially reducing the risk of cross-infections.
An Identification Method for the “Effective Coupling Loss Factor” Based on the Hybrid FE-SEA Model
Authors: Su Jintao , Zheng Ling
Published: March 2023

Due to the limitation of the SEA method, the hybrid FE-SEA method has become a powerful tool to solve the medium-frequency “acoustic-vibration problem”. However, in most cases, the solution process of the hybrid FE-SEA model is often accompanied by ill-posed matrix problems, such as the inverse solution of the matrix, and the calculation accuracy is not high, which affects the overall calculation accuracy of the hybrid FE-SEA model. In this paper, the calculation method for the effective coupling matrix of the hybrid FE-SEA model is further improved. Based on the basic parameter solving method of the hybrid FE-SEA model, the hybrid FE-SEA model for three-coupled systems is established. In this paper, the deterministic subsystem and the random subsystem response solving problem in three-coupled systems is studied. The method is extended to the multi-coupled system, and an improved calculation method for the coupling matrix of the hybrid FE-SEA model is proposed. On the basis of the weighted iterative method of the principal element, intermediate variables and error transfer are introduced. The parameter identification problem of the effective coupling loss factor of the hybrid FE-SEA model is solved, which provides a solution for parameter identification of the hybrid FE-SEA model.
The Mixture of Gastrodia elata and Glycyrrhiza uralensis Attenuates Scopolamine-Induced Cognitive Disorder
Authors: Lee Ji-Hyun , Kim Sung-Wook , Lee Seong-Hoon , Cho Jae-Yeon , Hwang Su-Ha , Lee Won-Woo , Lee Jang-Won , Kim Dae-Ki , Jeon Yong-Deok
Published: March 2023

Background: Cognitive disorders are symptoms of degenerative neuronal diseases such as Alzheimer’s disease (AD). This study evaluated the effects of a mixture of Gastrodiae elata (GE) and Glycyrrhizae uralensis (GU) (GGW) on scopolamine-treated cognitive function disorders in vivo. Methods: To induce memory impairment and cognitive disorder, C57BL/6 mice were intraperitoneally administered scopolamine. In the experimental period, the Y-maze, passive avoidance, and water maze tests were carried out to measure the ameliorative effect of GGW on cognitive function disorder. The expression of amyloid-β (Aβ), brain-derived neurotrophic factor (BDNF), and acetylcholinesterase (AChE) in the hippocampal tissues were measured. In addition, to assess the effect of GGW on brain tissue, tissues were stained using hematoxylin and eosin (H&E). Results: GGW treatment improved latencies in the Y-maze, water maze, and passive avoidance tests compared with scopolamine treatment alone. GGW administration downregulated Aβ and AChE expression. In addition, BDNF expression was upregulated by GGW administration. Conclusion: These results suggest that GGW ameliorates impaired cognitive function in a scopolamine-induced mouse model. In addition, GGW could control the pathway of scopolamine-induced cognitive disorders by regulating Aβ, AChE, and BDNF. These results suggest that GGW could be used as a treatment agent for cognitive dysfunction.
Recent Advances in Artificial Intelligence-Assisted Ultrasound Scanning
Authors: Tenajas Rebeca , Miraut David , Illana Carlos I. , Alonso-Gonzalez Rodrigo , Arias-Valcayo Fernando , Herraiz Joaquin L.
Published: March 2023

Ultrasound (US) is a flexible imaging modality used globally as a first-line medical exam procedure in many different clinical cases. It benefits from the continued evolution of ultrasonic technologies and a well-established US-based digital health system. Nevertheless, its diagnostic performance still presents challenges due to the inherent characteristics of US imaging, such as manual operation and significant operator dependence. Artificial intelligence (AI) has proven to recognize complicated scan patterns and provide quantitative assessments for imaging data. Therefore, AI technology has the potential to help physicians get more accurate and repeatable outcomes in the US. In this article, we review the recent advances in AI-assisted US scanning. We have identified the main areas where AI is being used to facilitate US scanning, such as standard plane recognition and organ identification, the extraction of standard clinical planes from 3D US volumes, and the scanning guidance of US acquisitions performed by humans or robots. In general, the lack of standardization and reference datasets in this field makes it difficult to perform comparative studies among the different proposed methods. More open-access repositories of large US datasets with detailed information about the acquisition are needed to facilitate the development of this very active research field, which is expected to have a very positive impact on US imaging.
A Study on the Occurrence Characteristics of Harmful Blue-Green Algae in Stagnant Rivers Using Machine Learning
Authors: Jung Woo Suk , Jo Bu Geon , Kim Young Do
Published: March 2023

Several changes have occurred in the river environment of Nakdong river due to the construction of multifunctional weirs as part of the Four Major Rivers Project. This river currently exhibits characteristics that are similar to those of a stagnant water area in which the river depth increases and the flow velocity decreases. Consequently, blue-green algae are frequently observed. Toxic substances secreted by blue-green algae are harmful to aquatic ecosystems and the human body; therefore, ensuring the stability of the water quality of Nakdong river is of utmost importance. Various factors are associated with the occurrence of blue-green algae. Therefore, the causal relationship between these causative factors must be identified. In this study, we investigated factors influencing algal growth, such as water quality, hydraulics, and weather, and algal occurrence patterns by site were analyzed. Recent studies have used data mining and machine-learning techniques in algal management to quantitatively identify the characteristics of blue-green algae. In machine learning, the prediction results differ depending on the selection of parameters, which are an important aspect in the management of blue-green algae with complex causes. In this study, we quantitatively analyzed the conditions for the occurrence of cyanobacteria according to the influencing factors using decision trees and random forests, which are machine-learning techniques, along with an analysis of the major complex factors influencing the occurrence of blue-green algae in the Nakdong river weirs. Considering the water quality and hydraulic factors, we analyzed the characteristics of algal generation in each weir at different hydraulic volume times. In addition, we investigated the possibility of improving the accuracy of cyanobacterial prediction according to the learning factors. Through these analyses, we attempted to study the characteristics of blue-green algae in stagnant rivers.
Self-Betrayal or Self-Deception? The Case of Jackson Pollock
Authors: Langhorne Elizabeth L.
Published: March 2023

Clement Greenberg interpreted the rise of authentic modern art as a rejection of kitsch and “half-baked” religiosity and celebrated Jackson Pollock as representing what he called for. However, his presentation of Pollock as a leading modernist fails to do justice to his lifelong spiritual quest and to his desire to reach a broad public, which led him to open his art and person to the popular media of photography and film. Following Greenberg, Donald Kuspit would have us understand Pollock’s embrace of and by the public as a self-betrayal, transforming his great abstractions into decorative kitsch. Kuspit’s understanding of Pollock’s “true self”, however, cannot convince. His embrace of the public did lead Pollock to doubt his artistic enterprise: his dream of art as alchemy. But, the great abstractions testify to the power of that dream to create great art, challenging us to reconsider the relationship between authentic art and mass culture, of modernism, spirituality, and the public.
Assessing the Risk of Spreading COVID-19 in the Room Utilizing Low-Cost Monitoring System
Authors: Bujňák Marek , Pirník Rastislav , Kuchár Pavol , Rástočný Karol
Published: March 2023

High hygiene standards were established during the COVID-19 epidemic, and their adherence was closely monitored. They included the need to regularly wash one’s hands and the requirement to cover person’s upper airways or keep at least a two-meter space between individuals. The ITS (Information Technology Systems) community made a big contribution to this by developing methods and applications for the ongoing observation of people and the environment. Our major objective was to create a low-cost, straightforward system for tracking and assessing the danger of spreading COVID-19 in a space.The proposed system collects data from various low-cost environmental sensors such as temperature, humidity, CO2, the number of people, the dynamics of speech, and the cleanliness of the environment with a significant connection to elements of wearable electronics and then evaluate the level of contamination and possible risks and, in the event of a high level of risk, alerts the person to take actions that can reduce or eliminate favourable conditions for the spread of the virus. The system was created at the Laboratory of industrial control systems of the University of Žilina, Slovakia. The experiment demonstrates the ability and feasibility to control the number of people in a space depending on particular symptoms like fever, coughing, and hand hygiene. On the other hand, the laboratory’s temperature, humidity, and air quality should be controlled to reduce the spread of illness.
Towards Space Deployment of the NDSA Concept for Tropospheric Water Vapour Measurements
Authors: Facheris Luca , Antonini Andrea , Argenti Fabrizio , Barbara Flavio , Cortesi Ugo , Cuccoli Fabrizio , Del Bianco Samuele , Dogo Federico , Feta Arjan , Gai Marco , Gregorio Anna , Macelloni Giovanni , Mazzinghi Agnese , Melani Samantha , Montomoli Francesco , Ortolani Alberto , Rovai Luca , Severin Luca , Scopa Tiziana
Published: March 2023

A novel measurement concept specifically tuned to monitoring tropospheric water vapour’s vertical distribution has been demonstrated on a theoretical basis and is currently under development for space deployment. The NDSA (Normalised Differential Spectral Attenuation) technique derives the integrated water vapour (IWV) along the radio link between a transmitter and a receiver carried by two LEO satellites, using the linear correlation between the IWV and a parameter called spectral sensitivity. This is the normalised incremental ratio of the spectral attenuation at two frequencies in the Ku and K bands, with the slope of the water vapour absorption line at 22.235 GHz. Vertical profiles of WV can be retrieved by inverting a set of IWV measurements acquired in limb geometry at different tangent altitudes. This paper provides a comprehensive insight into the NDSA approach for sounding lower tropospheric WV, from the theoretical investigations in previous ESA studies, to the first experimental developments and testing, and to the latest advancements achieved with the SATCROSS project of the Italian Space Agency. The focus is on the new results from SATCROSS activities; primarily, on the upgrading of the instrument prototype, with improved performance in terms of its power stability and the time resolution of the measurements. Special emphasis is also placed on discussing tomographic inversion methods capable of retrieving tropospheric WV content from IWV measurements, i.e., the least squares and the external reconstruction approaches, showing results with different spatial features when applied to a given atmospheric scenario. The ultimate goal of deploying the NDSA measurement technique from space is thoroughly examined and conclusions are drawn after presenting the results of an Observing System Simulation Experiment conducted to assess the impact of NDSA data assimilation on environmental model simulations.
Consumer Preferences for Craft Beer by Means of Artificial Intelligence: Are Italian Producers Doing Well?
Authors: Pilone Vittoria , Di Pasquale Alessandro , Stasi Antonio
Published: March 2023

To identify the key drivers of consumption, we analyzed consumer preferences and estimated the willingness to pay for craft beer compared with industrial products in Italy. For this purpose, we conducted an ad hoc survey of 469 craft beer drinkers and set up an econometric strategy using a machine learning estimation technique. The main results show that young consumers, the ability to perceive and evaluate quality, and the frequency of consumption are the main profile elements that, more than others, orient preferences. In the meantime, sustaining local beer producers, sharing good time with friends, and the perception of beer as healthier compared with other drinks are also important. The most preferable product attributes are can packaging and the search for unique taste.
Accelerated Diffusion-Weighted MRI of Rectal Cancer Using a Residual Convolutional Network
Authors: Mohammadi Mohaddese , Kaye Elena A. , Alus Or , Kee Youngwook , Golia Pernicka Jennifer S. , El Homsi Maria , Petkovska Iva , Otazo Ricardo
Published: March 2023

This work presents a deep-learning-based denoising technique to accelerate the acquisition of high b-value diffusion-weighted MRI for rectal cancer. A denoising convolutional neural network (DCNN) with a combined L1–L2 loss function was developed to denoise high b-value diffusion-weighted MRI data acquired with fewer repetitions (NEX: number of excitations) using the low b-value image as an anatomical guide. DCNN was trained using 85 datasets acquired on patients with rectal cancer and tested on 20 different datasets with NEX = 1, 2, and 4, corresponding to acceleration factors of 16, 8, and 4, respectively. Image quality was assessed qualitatively by expert body radiologists. Reader 1 scored similar overall image quality between denoised images with NEX = 1 and NEX = 2, which were slightly lower than the reference. Reader 2 scored similar quality between NEX = 1 and the reference, while better quality for NEX = 2. Denoised images with fourfold acceleration (NEX = 4) received even higher scores than the reference, which is due in part to the effect of gas-related motion in the rectum, which affects longer acquisitions. The proposed deep learning denoising technique can enable eightfold acceleration with similar image quality (average image quality = 2.8 ± 0.5) and fourfold acceleration with higher image quality (3.0 ± 0.6) than the clinical standard (2.5 ± 0.8) for improved diagnosis of rectal cancer.
Hair Follicle Transcriptome Analysis Reveals Differentially Expressed Genes That Regulate Wool Fiber Diameter in Angora Rabbits
Authors: Huang Dongwei , Ding Haisheng , Wang Yuanlang , Cheng Guanglong , Wang Xiaofei , Leng Taishan , Zhao Huiling
Published: March 2023

Wool fiber diameter (WFD) is an important index of wool traits and the main determinant of wool quality and value. However, the genetic determinants of fiber diameter have not yet been fully elucidated. Here, coarse and fine wool of Wan strain Angora rabbits and their hair follicle traits were characterized. The results indicated significant differences in the diameters of wool fibers and their hair follicles. The RNA sequencing (RNA-Seq) technique was used to identify differences in gene expression in hair follicles between coarse and fine wool. In total, 2574 differentially expressed genes (DEGs) were found between the two hair follicle groups. Transcription factors, keratin-associated protein (KAP) and keratin (KRT) families, and ECM-related genes may control the structure of fine fibers in rabbits. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that skin development, epidermal cell and keratinocyte differentiation, epithelium development, and Notch and ribosome signaling pathways were significantly enriched, respectively. GSEA further filtered six important pathways and related core genes. PPI analysis also mined functional DEGs associated with hair structure, including LEF1, FZD3, SMAD3, ITGB6, and BMP4. Our findings provide valuable information for researching the molecular mechanisms regulating wool fiber and could facilitate enhanced selection of super-fine wool rabbits through gene-assisted selection in the future.
Molecular Influence of the ATM Protein in the Treatment of Human Cells with Different Radioprotective Drugs: Comparisons between Antioxidative and Pro-Episkevic Strategies
Authors: Restier-Verlet Juliette , Drouet Michel , Pras Pauline , Ferlazzo Mélanie L. , Granzotto Adeline , Sonzogni Laurène , Al-Choboq Joëlle , El Nachef Laura , François Sabine , Bourguignon Michel , Foray Nicolas
Published: March 2023

The radiation protection strategy with chemical agents has long been based on an antioxidative approach consisting in reducing the number of radical oxygen and nitrogen species responsible for the formation of the radiation-induced (RI) DNA damage, notably the DNA double-strand breaks (DSB), whose subset participates in the RI lethal effect as unrepairable damage. Conversely, a DSB repair-stimulating strategy that may be called the “pro-episkevic” approach (from the ancient Greek episkeve, meaning repair) can be proposed. The pro-episkevic approach directly derives from a mechanistic model based on the RI nucleoshuttling of the ATM protein (RIANS) and contributes to increase the number of DSB managed by NHEJ, the most predominant DSB repair and signaling pathway in mammalians. Here, three radioresistant and three radiosensitive human fibroblast cell lines were pretreated with antioxidative agents (N-acetylcysteine or amifostine) or to two pro-episkevic agents (zoledronate or pravastatin or both (ZOPRA)) before X-ray irradiation. The fate of the RI DSB was analyzed by using γH2AX and pATM immunofluorescence. While amifostine pretreatment appeared to be the most efficient antioxidative process, ZOPRA shows the most powerful radiation protection, suggesting that the pro-episkevic strategy may be an alternative to the antioxidative one. Additional investigations are needed to develop some new drugs that may elicit both antioxidative and pro-episkevic properties and to quantify the radiation protection action of both types of drugs applied concomitantly.