bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Seismic Demands on Non-Structural Components Attached to Reinforced Concrete Frames
Authors: Challagulla Surya Prakash , Kontoni Denise-Penelope N. , Suluguru Ashok Kumar , Hossain Ismail , Ramakrishna Uppari , Jameel Mohammed
Published: February 2023

Nonstructural components (NSCs) are the systems that are attached to the floors of a building structure. NSCs have become critical in sustaining post-earthquake functionality while constructing seismic-resilient structures. The seismic behavior of the NSCs primarily depends upon the behavior of the structure to which the NSC is attached. Building structures are subjected to earthquake loads and behave differently when the supporting soil type varies. In light of this, this study investigates the seismic demands on NSC attached to the floors of an elastic-reinforced concrete building frame supported by different soil types. The present study considered a regular building frame and a building frame with mass irregularity on the lower story. A total of 3 sets of 11 horizontal spectral-matched ground motions consistent with each soil type are considered. Floor response spectra (FRS) can be used to measure the seismic load on non-structural components. Primarily, it was found that the ordinates of FRS depend on the floor height, the vibration periods of the building, and the soil type. The presence of mass irregularity at the lower story amplified the floor response at all floor levels. Additionally, the values of floor spectral acceleration increase as soil flexibility increases. The amplification factors are critical for generating the floor response spectra, and their variation along the building height is discussed. The floor acceleration was found to vary non-linearly with the height of the building. Finally, artificial neural networks (ANNs) are employed to develop the prediction models for dynamic amplification factors. The results calculated by the dynamic time history analyses are utilized to validate the proposed prediction models.
Special Issue on Interdisciplinary Researches for Cultural Heritage Conservation
Authors: Saiz-Jimenez Cesareo
Published: February 2023

UNESCO defines cultural heritage as “the legacy of physical artefacts and intangible attributes of a group or society that are inherited from past generations, maintained in the present and bestowed for the benefit of future generations” [...]
Point Cloud Repair Method via Convex Set Theory
Authors: Dong Tianzhen , Zhang Yi , Li Mengying , Bai Yuntao
Published: February 2023

The point cloud is the basis for 3D object surface reconstruction. An incomplete point cloud significantly reduces the accuracy of downstream work such as 3D object reconstruction and recognition. Therefore, point-cloud repair is indispensable work. However, the original shape of the point cloud is difficult to restore due to the uncertainty of the position of the new filling point. Considering the advantages of the convex set in dealing with uncertainty problems, we propose a point-cloud repair method via a convex set that transforms a point-cloud repair problem into a construction problem of the convex set. The core idea of the proposed method is to discretize the hole boundary area into multiple subunits and add new 3D points to the specific subunit according to the construction properties of the convex set. Specific subunits must be located in the hole area. For the selection of the specific subunit, we introduced Markov random fields (MRF) to transform them into the maximal a posteriori (MAP) estimation problem of random field labels. Variational inference was used to approximate MAP and calculate the specific subunit that needed to add new points. Our method iteratively selects specific subunits and adds new filling points. With the increasing number of iterations, the specific subunits gradually move to the center of the hole region until the hole is completely repaired. The quantitative and qualitative results of the experiments demonstrate that our method was superior to the compared method.
Study on Paste Transformation and Parameter Optimization of Cemented Backfilling with Fine Tailings in Deep Gold Deposits
Authors: Wen Xinglin , Ge Zhengchen , Zhao Yuemao , Zhang Zhenghua , Sun Xianteng
Published: February 2023

The key to cementation backfilling in underground stopes of metal mines is quality and efficiency of backfilling. Backfilling quality is inseparable from the cementitious material as well as the tailings properties. To explore the influence of different factors on the strength of the backfilling body, the ratio of backfilling cementitious materials in the preparation process of backfilling slurry was experimentally studied to determine the economical and reasonable proportion of backfilling cementitious materials. Under the multi-factor test, it is concluded that the proportion concentration of 1:6 and 66% in the cemented specimen of medium and fine tailings meets the strength requirements of the surface layer of the backfilling body. Using the numerical simulation software FLAC3D, the movement of rock mass under different backfillings is simulated, and the subsidence of overburden, the stress of the ore body, and the damage range of the plastic zone are analyzed. The results showed that, during the transition from full tailings cemented backfilling to medium-fine tailings paste backfilling, the vertical stress concentration area of the overlying strata shifts from the surrounding ore body to the backfilling body, the plastic zone decreases, and the complexity of failure forms gradually decreases. Finally, the transformation method from full tailings cementation backfilling to medium fine tailings paste backfilling is determined, and the medium fine tailings paste backfilling in a deep gold mine is realized.
Special Issue on Novel Technology and Applications of Micro/Nano Devices and System
Authors: Pinto Vânia , Sousa Paulo , Minas Graça
Published: February 2023

The development of novel technologies and applications for micro/nano devices is an interdisciplinary subject that demands an integration of several research fields, such as material science, biotechnology, medicine, chemistry, informatics, optics, electronics, mechanics, and micro/nanotechnologies [...]
Characteristics of P Adsorption by Profundal Bottom Deposits of Kortowskie Lake (Poland), Restored by the Hypolimnetic Withdrawal Method
Authors: Augustyniak-Tunowska Renata , Karczmarczyk Rafał , Łopata Michał , Grochowska Jolanta , Tunowski Jacek , Tandyrak Renata
Published: February 2023

Phosphorus is a key factor controlling eutrophication processes. Out of all the parts of the lake ecosystem, the biggest pool of this element (more than 90%) is stored in the surficial layers of bottom sediment. Hence, the bottom sediment’s ability to trap and release P is very important in analyzing a lake ecosystem’s function, particularly when the lake is subjected to restoration. Studies were carried out on Lake Kortowskie (87.2 ha in area, maximum depth 17.2 m), restored in 1956 using the hypolimnetic withdrawal method. The sediment cores were taken at two research stations—experimental (max. depth 17.2 m) and control (max. depth 15.7 m). Experiments were made in laboratory conditions. The results showed that phosphorus adsorption in the bottom deposits of Lake Kortowskie was multilayered. The Freundlich, BET, and Freundlich-Langmuir adsorption models best fit the experimental data. Adsorption isotherms were concave, suggesting that P adsorption effectiveness is higher for higher P concentrations in ambient water.
Multifunctional Polymers and Composites
Authors: Jiménez-Suárez Alberto , Prolongo Silvia G.
Published: February 2023

The use of polymer and polymer-based composites has increased over the last decades [...]
New Framework for Complex Assembly Digitalization and Traceability Using Bill of Assembly and Smart Contracts
Authors: Cohen Yuval , Rozenes Shai
Published: February 2023

This paper proposes a framework to automate the generation of traceable and protected documentation of complex assembly processes. The final assembly in aviation, automotive, and appliances industries is a rigorous process that has limited capabilities of full traceability associated with: (1) the parts installed, (2) their fabrication processes, and (3) the assembly work. This is also the case for each of its sub-assemblies. The thousands of parts forming a hierarchy of sub-assemblies that are dynamically accumulated to compose the final assembly make full traceability a challenging feat that is almost unsurmountable. Such full traceability along the entire supply chain requires considerable cost and effort since it must be based on documentation of most assembled parts, assembly tasks, and inspection tasks that compose the full assembled product. In addition, security measures are needed to prevent hostile hacking and unauthorized approach to the assembly documentation throughout the entire supply chain. The related documentation and repeated verifications require considerable effort and have many chances for human errors. So, automating these processes has great value. This article expounds a framework that harnesses blockchain and smart-contract technology to offer automated traceable and protected documentation of the assembly process. For this purpose, we expand the concept of a Bill-Of-Assembly (BOA) to incorporate data from the bill of materials (BOM), the associated assembly activities, the associated activities’ specification parameters and materials, and the associated assembly resources (machines and/or operators). The paper defines the operation of the BOA with blockchain and smart-contract technology, for attaining full traceability, safety, and security, for the entire assembled product. Future research could extend the proposed approach to facilitate the usage of the BOA data structure in constructing a digital twin of the entire simulated system.
Solitary-like Wave Dynamics in Thin Liquid Films over a Vibrated Inclined Plane
Authors: Maksymov Ivan S. , Pototsky Andrey
Published: February 2023

Solitary-like surface waves that originate from the spatio-temporal evolution of falling liquid films have been the subject of theoretical and experimental research due to their unique properties that are not readily observed in other physical systems. Here we investigate, experimentally and theoretically, the dynamics of solitary-like surface waves in a liquid layer on an inclined plane that is subjected to a harmonic low-frequency vibration in a range from 30 to 50 Hz. We employ a standard boundary layer model, which describes large-amplitude deformations of the film surface, assuming that it has a self-similar parabolic longitudinal flow velocity profile, to confirm the experimental results and to explain the interplay between the short-wavelength Faraday instability and long-wavelength gravitational instability. In particular, we demonstrate that the vibration results in a decrease in the average and peak amplitude of the long solitary-like surface waves. However, the speed of these waves remains largely unaffected by the vibration, implying that they may propagate over large distances almost without changing their amplitude, thus rendering them suitable for a number of practical applications, where the immunity of pulses that carry information to external vibrations is required.
Exploration of Applying Pose Estimation Techniques in Table Tennis
Authors: Wu Chih-Hung , Wu Te-Cheng , Lin Wen-Bin
Published: February 2023

The newly developed computer vision pose estimation technique in artificial intelligence (AI) is an emerging technology with potential advantages, such as high efficiency and contactless detection, for improving competitive advantage in the sports industry. The related literature is currently lacking an integrated and comprehensive discussion about the applications and limitations of using the pose estimation technique. The purpose of this study was to apply AI pose estimation techniques, and to discuss the concepts, possible applications, and limitations of these techniques in table tennis. This study implemented the OpenPose pose algorithm in a real-world video of a table tennis game. The research results show that the pose estimation algorithm performs well in estimating table tennis players’ poses from the video in a graphics processing unit (GPU)-accelerated environment. This study proposes an innovative two-stage AI pose estimation method for effectively addressing the current difficulties in applying AI to table tennis players’ pose estimation. Finally, this study provides several recommendations, benefits, and various perspectives (training vs. tactics) of table tennis and pose estimation limitations for the sports industry.
Machine Learning in Manufacturing towards Industry 4.0: From ‘For Now’ to ‘Four-Know’
Authors: Chen Tingting , Sampath Vignesh , May Marvin Carl , Shan Shuo , Jorg Oliver Jonas , Aguilar Martín Juan José , Stamer Florian , Fantoni Gualtiero , Tosello Guido , Calaon Matteo
Published: February 2023

While attracting increasing research attention in science and technology, Machine Learning (ML) is playing a critical role in the digitalization of manufacturing operations towards Industry 4.0. Recently, ML has been applied in several fields of production engineering to solve a variety of tasks with different levels of complexity and performance. However, in spite of the enormous number of ML use cases, there is no guidance or standard for developing ML solutions from ideation to deployment. This paper aims to address this problem by proposing an ML application roadmap for the manufacturing industry based on the state-of-the-art published research on the topic. First, this paper presents two dimensions for formulating ML tasks, namely, ’Four-Know’ (Know-what, Know-why, Know-when, Know-how) and ’Four-Level’ (Product, Process, Machine, System). These are used to analyze ML development trends in manufacturing. Then, the paper provides an implementation pipeline starting from the very early stages of ML solution development and summarizes the available ML methods, including supervised learning methods, semi-supervised methods, unsupervised methods, and reinforcement methods, along with their typical applications. Finally, the paper discusses the current challenges during ML applications and provides an outline of possible directions for future developments.
When Gut Hormones Influence Brain Function in Depression
Authors: Siba Isadora P. , Martynhak Bruno J. , Pereira Marcela
Published: February 2023

The literature on the crosstalk between the brain and the gut has increased considerably in recent years. It is widely accepted now that the microbiome plays a significant role in several brain disorders, neurodevelopment, neurocognitive stages, and physiological functions. However, the mechanisms that influence such crosstalk are still not well elucidated. In this sense, one of the possible mechanisms by which the microbiome could influence brain function is through gut hormones released by enteroendocrine cells: ghrelin, cholecystokinin (CCK), peptide YY (PYY), vasoactive intestinal polypeptide (VIP), glucagon-like peptide (GLP1-2), corticotropin-releasing factor (CRF), glucose-dependent insulinotropic polypeptide (GIP), secretin, serotonin (5-HT), and oxytocin. Especially when one considers that the brain expresses receptors for these hormones in areas important to the neurobiology of brain disorders (e.g., depression), such as the hippocampus, amygdala, hypothalamus, and suprachiasmatic nucleus. To strengthen this hypothesis, gastrointestinal dysfunction (such as altered motility or pain) is relatively common in depressive patients, and changes in diet (low-carbohydrate diets, for example) positively affect mood. Additionally, alterations in the gut microbiome are relatively common in depressive patients and are related to the levels of Akkermansia, Lactobacillus, Bifidobacteria, Faecalibacterium, Roseburia and Clostridium. Finally, concerning the gut-released hormones, the literature reports that ghrelin can be a peripheral marker for the antidepressant treatment success rate and has elevated levels during depression. GLP-1 is tightly correlated with HPA axis activity being decreased by high cortisol levels. CCK seems to be altered in depression due to increased inflammation and activation of Toll-like receptor 4. Such finds allow the postulation that hormones, the microbiome and mood are intertwined and co-dependent. VIP is correlated with circadian rhythms. There is a bidirectional connection of the circadian rhythms between the host and the microbiota. Circadian rhythm disruption is associated with both poor outcomes in mental health and alterations in the microbiota composition. In sum, in the past year, more and more research has been published showing the tight connection between gut and brain health and trying to decipher the feedback in play. Here, we focus on depression.
Volatile Aroma Compounds of Gavina® Watermelon (Citrullus Lanatus L.) Dietary Fibers to Increase Food Sustainability
Authors: D’Eusanio Veronica , Maletti Laura , Marchetti Andrea , Roncaglia Fabrizio , Tassi Lorenzo
Published: February 2023

To deal with climate emergency and reduce environmental impact, agro-industrial wastes are gradually gaining interest and are being used for new products and applications. The large production of watermelons represents an opportunity because of the many byproducts that can be transformed into innovative and valuable foodstuffs. In this study, we examined the lycopene-rich whole dietary fiber (WDF) obtained from the watermelon pomace of a peculiar cultivar, Gavina® (Oristano, Italy) a seedless fruit from Sardinia (Italy). The volatile chemical composition of the WDF was investigated using Solid-Phase Microextraction-Gas Chromatography/Mass Spectrometry (SPME-GC/MS). The aim was to follow the evolution of the Volatile Organic Compounds (VOCs) fraction during storage and verify its stability over time. Since watermelon is an excellent source of carotenoids, their byproducts were the most abundant VOCs of the freshly prepared samples, but their overall abundance decreased significantly during storage. The opposite trend was observed for acids and aldehydes, whose increase over time is related to amino acid degradation. Freshly prepared WDF can be used in the food industry as an antioxidant-rich dietary fiber that imparts a characteristic and pleasant aroma. Over time, its aroma profile and carotenoid content change considerably, reducing its health properties and limiting its potential application as a natural flavor.
On the Countering of Free Vibrations by Forcing: Part II—Damped Oscillations and Decaying Forcing
Authors: Campos Luiz M. B. C. , Silva Manuel J. S.
Published: February 2023

The present two-part paper concerns the active vibration suppression for the simplest damped continuous system, namely the transverse oscillations of an elastic string, with constant tension and mass density per unit length and friction force proportional to the velocity, described by the telegraph or wave-diffusion equation, in two complementary parts. The initial part I considers non-resonant and resonant forcing, by concentrated point forces or continuous force distributions independent of time, with phase shift between the forced and free oscillations, in the absence of damping, in which case the forced telegraph equation reduces to the forced classical wave equation. The present and final part II uses the forced wave-diffusion equation to model the effect of damping, both as amplitude decay and phase shift in time, for non-resonant and resonant forcing by a single point force, with constant magnitude or magnitude decaying exponentially in time at an arbitrary rate. Assuming a finite elastic string fixed at both ends, the free oscillations are (i) sinusoidal modes in space-time with exponential decay in time due to damping. The non-resonant forced oscillations at an applied frequency distinct from a natural frequency are also (ii) sinusoidal in space-time, with constant amplitude and a phase shift such that the work of the applied force balances the dissipation. For resonant forcing at an applied frequency equal to a natural frequency, the sinusoidal oscillations in space-time have (iii) a constant amplitude and a phase shift of π/2. In both cases, the (ii) non-resonant or (iii) resonant forcing dominates the decaying free oscillations after some time. Even by optimizing the forcing to minimize the total energy of oscillation, it remains below the energy of the free oscillation alone, but only for a short time—generally a fraction of the period. A more effective method of countering the damped free oscillations is to use forcing with amplitude decaying exponentially in time; by suitable choice of the forcing decay relative to the free damping, the total energy of oscillation over all time can be reduced to no more than 1/16th of the energy of the free oscillation.
Hydrometeorological Hazards on Crop Production in the State of Veracruz, Mexico
Authors: Valdés-Rodríguez Ofelia Andrea , Salas-Martínez Fernando , Palacios-Wassenaar Olivia Margarita
Published: February 2023

Hydrometeorological hazards are considered the most important phenomena affecting crop production in the Eastern regions of Mexico, where the State of Veracruz is located. However, more information about their consequences on these sites needs to be studied. This research aims to determine the effects of hydrometeorological phenomena on the most important crops cultivated in the State of Veracruz. The methodology involved analyzing the State’s crop production database from 2001 to 2020 and comparing this data with the National Hydrometeorological Disaster Declarations database. Multivariable correlation analysis and geographic information systems were applied to geographically analyze 42 rainfed crops plus the five most valuable ones in the State to determine their production related to climatic phenomena. The results found that the most affected crops are corn, soy, sorghum, beans, and rice, with more than 10,000 lost hectares. Droughts caused total damage to corn, soy, and beans and decreased productivity in corn, orange, lemon, wheat, coffee, and sesame. For the most valuable crops, tropical cyclones caused the highest production decrements in corn, sugar cane, and pineapple, while droughts caused the same effects in lemon and orange. We conclude that tropical cyclones are the most critical phenomena negatively impacting Veracruz, with high implications on the agrifood system.
Automatic Recognition of Constant-Frequency Electromagnetic Disturbances Observed by the Electric Field Detector on Board the CSES
Authors: Han Ying , Yuan Jing , Ouyang Qunbo , Huang Jianping , Li Zhong , Zhang Yanxia , Wang Yali , Shen Xuhui , Zeren Zhima
Published: February 2023

Since the CSES (China Seismo-Electromagnetic Satellite) has been in orbit, it has detected a large number of constant-frequency electromagnetic disturbances (CFEDs), which are horizontal lines on the spectrum. In this paper, we present an algorithm for automatic recognition of CFEDs based on computer vision technology. The relevant results are of great significance for analysis of perturbation events and mining of the transformation laws of global space events. First, a grayscale spectrogram is obtained; then, a horizontal convolution kernel is used to enhance the horizontal edge features of the grayscale graph, and finally, black-and-white binarization is performed to complete data preprocessing. The preprocessed data are then fed into an unsupervised cluster model for training and recognition to realize automatic recognition of CFEDs. Experimental results show that the CFED recognition algorithm proposed in this paper is effective, with a recognition accuracy of more than 98%.
Three Particle Muon-Electron Bound Systems in Quantum Electrodynamics
Authors: Eskin Alexey V. , Korobov Vladimir I. , Martynenko Alexei P. , Martynenko Fedor A.
Published: February 2023

The muonic 2P-2S Lamb shift in muon-electron atoms and ions of helium, lithium, beryllium, and boron with the electron in the ground state was calculated by the perturbation theory using the fine structure constant and the electron-muon mass ratio. The corrections of first- and second-orders of perturbation theory on the Coulomb interaction and nucleus recoil were taken into account. The obtained analytical results were validated numerically using calculations within the variational method.
Iterative Nonlinear Fuzzy Modeling of Lithium-Ion Batteries
Authors: Andújar José M. , Barragán Antonio J. , Vivas Francisco J. , Enrique Juan M. , Segura Francisca
Published: February 2023

Electric vehicles (EVs), in their pure and hybrid variants, have become the main alternative to ensure the decarbonization of the current vehicle fleet. Due to its excellent performance, EV technology is closely linked to lithium-ion battery (LIB) technology. A LIB is a complex dynamic system with extraordinary nonlinear behavior defined by electrical, thermal and electrochemical dynamics. To ensure the proper management of a LIB in such demanding applications as EVs, it is crucial to have an accurate mathematical model that can adequately predict its dynamic behavior. Furthermore, this model must be able to iteratively adapt its parameters to accommodate system disturbances during its operation as well as performance loss in terms of efficiency and nominal capacity during its life cycle. To this end, a methodology that employs the extended Kalman filter to iteratively improve a fuzzy model applied to a real LIB is presented in this paper. This algorithm allows to improve the classical Takagi–Sugeno fuzzy model (TSFM) with each new set of data obtained, adapting the model to the variations of the battery characteristics throughout its operating cycle. Data for modeling and subsequent validation were collected during experimental tests on a real LIB under EVs driving cycle conditions according to the “worldwide harmonised light vehicle test procedure” (WLTP) standard. The TSFM results allow the creation of an accurate nonlinear dynamic model of the LIB, even under fluctuating operating conditions, demonstrating its suitability for modeling and design of model-based control systems for LIBs used in EVs applications.
Improving the Segmentation Accuracy of Ovarian-Tumor Ultrasound Images Using Image Inpainting
Authors: Chen Lijiang , Qiao Changkun , Wu Meijing , Cai Linghan , Yin Cong , Yang Mukun , Sang Xiubo , Bai Wenpei
Published: February 2023

Diagnostic results can be radically influenced by the quality of 2D ovarian-tumor ultrasound images. However, clinically processed 2D ovarian-tumor ultrasound images contain many artificially recognized symbols, such as fingers, crosses, dashed lines, and letters which assist artificial intelligence (AI) in image recognition. These symbols are widely distributed within the lesion’s boundary, which can also affect the useful feature-extraction-utilizing networks and thus decrease the accuracy of lesion classification and segmentation. Image inpainting techniques are used for noise and object elimination from images. To solve this problem, we observed the MMOTU dataset and built a 2D ovarian-tumor ultrasound image inpainting dataset by finely annotating the various symbols in the images. A novel framework called mask-guided generative adversarial network (MGGAN) is presented in this paper for 2D ovarian-tumor ultrasound images to remove various symbols from the images. The MGGAN performs to a high standard in corrupted regions by using an attention mechanism in the generator to pay more attention to valid information and ignore symbol information, making lesion boundaries more realistic. Moreover, fast Fourier convolutions (FFCs) and residual networks are used to increase the global field of perception; thus, our model can be applied to high-resolution ultrasound images. The greatest benefit of this algorithm is that it achieves pixel-level inpainting of distorted regions without clean images. Compared with other models, our model achieveed better results with only one stage in terms of objective and subjective evaluations. Our model obtained the best results for 256 × 256 and 512 × 512 resolutions. At a resolution of 256 × 256, our model achieved 0.9246 for SSIM, 22.66 for FID, and 0.07806 for LPIPS. At a resolution of 512 × 512, our model achieved 0.9208 for SSIM, 25.52 for FID, and 0.08300 for LPIPS. Our method can considerably improve the accuracy of computerized ovarian tumor diagnosis. The segmentation accuracy was improved from 71.51% to 76.06% for the Unet model and from 61.13% to 66.65% for the PSPnet model in clean images.
Advances in Spinal Cord Stimulation
Authors: Lam Christopher M. , Latif Usman , Sack Andrew , Govindan Susheel , Sanderson Miles , Vu Dan T. , Smith Gabriella , Sayed Dawood , Khan Talal
Published: February 2023

Neuromodulation, specifically spinal cord stimulation (SCS), has become a staple of chronic pain management for various conditions including failed back syndrome, chronic regional pain syndrome, refractory radiculopathy, and chronic post operative pain. Since its conceptualization, it has undergone several advances to increase safety and convenience for patients and implanting physicians. Current research and efforts are aimed towards novel programming modalities and modifications of existing hardware. Here we review the recent advances and future directions in spinal cord stimulation including a brief review of the history of SCS, SCS waveforms, new materials for SCS electrodes (including artificial skins, new materials, and injectable electrodes), closed loop systems, and neurorestorative devices.
Continual Learning of a Transformer-Based Deep Learning Classifier Using an Initial Model from Action Observation EEG Data to Online Motor Imagery Classification
Authors: Lee Po-Lei , Chen Sheng-Hao , Chang Tzu-Chien , Lee Wei-Kung , Hsu Hao-Teng , Chang Hsiao-Huang
Published: February 2023

The motor imagery (MI)-based brain computer interface (BCI) is an intuitive interface that enables users to communicate with external environments through their minds. However, current MI-BCI systems ask naïve subjects to perform unfamiliar MI tasks with simple textual instruction or a visual/auditory cue. The unclear instruction for MI execution not only results in large inter-subject variability in the measured EEG patterns but also causes the difficulty of grouping cross-subject data for big-data training. In this study, we designed an BCI training method in a virtual reality (VR) environment. Subjects wore a head-mounted device (HMD) and executed action observation (AO) concurrently with MI (i.e., AO + MI) in VR environments. EEG signals recorded in AO + MI task were used to train an initial model, and the initial model was continually improved by the provision of EEG data in the following BCI training sessions. We recruited five healthy subjects, and each subject was requested to participate in three kinds of tasks, including an AO + MI task, an MI task, and the task of MI with visual feedback (MI-FB) three times. This study adopted a transformer- based spatial-temporal network (TSTN) to decode the user’s MI intentions. In contrast to other convolutional neural network (CNN) or recurrent neural network (RNN) approaches, the TSTN extracts spatial and temporal features, and applies attention mechanisms along spatial and temporal dimensions to perceive the global dependencies. The mean detection accuracies of TSTN were 0.63, 0.68, 0.75, and 0.77 in the MI, first MI-FB, second MI-FB, and third MI-FB sessions, respectively. This study demonstrated the AO + MI gave an easier way for subjects to conform their imagery actions, and the BCI performance was improved with the continual learning of the MI-FB training process.
Evaluation of Vitamin D isolated or Associated with Teriparatide in Peri-Implant Bone Repair in Tibia of Orchiectomized Rats
Authors: Gomes-Ferreira Pedro Henrique Silva , Frigério Paula Buzo , de Moura Juliana , Duarte Nathália Dantas , de Oliveira Danila , Deering Joseph , Grandfield Kathryn , Okamoto Roberta
Published: February 2023

(1) Background: The objective of this study was to evaluate the morphometry of peri-implant bone tissue in orchiectomized rats, treated with vitamin D isolated or associated with teriparatide. (2) Methods: 24 rats were divided into 4 groups: ORQ—orchiectomy, without drug treatment, ORQ+D—orchiectomy, treated with vitamin D, ORQTERI—orchiectomy, treated with teriparatide and ORQTERI+D—orchiectomy, treated with teriparatide + vitamin D. Each animal received an implant in the tibial metaphysis. Euthanasia occurred 60 days after implant surgery. Computed microtomography (micro-CT) was performed to evaluate the parameters of volume and percentage of bone volume (BV, BV/TV), trabecular thickness (Tb.Th), number and separation of trabeculae (Tb.N, Tb.Sp) and percentage of total porosity (Po-tot). Data were subjected to 1-way ANOVA and Tukey post-test, with a significance level of 5%. (3) Results: For the parameters BV, BV/TV, Tb.Th, the ORQTERI+D group showed the highest values in relation to the other groups and for Po-tot, the lowest values were for ORQTERI+D. For Tb.Sp and Tb.N, there was no statistically significant difference when comparing intragroup results (p > 0.05). (4) Conclusions: It was possible to conclude that treatment with vitamin D associated with teriparatide increases bone volume and improves bone quality.
Carboxylated ε-Poly-l-lysine Improves Post-Thaw Quality, Mitochondrial Functions and Antioxidant Defense of Goat Cryopreserved Sperm
Authors: Zhang Weijing , Cui Haixiang , Ding Kexin , Zhou Kaifeng , Li Yajing , Hoque S. A. Masudul , Min Lingjiang , Zhu Zhendong
Published: February 2023

Carboxylated ε-poly-l-lysine (CPLL), a novel cryoprotectant, can protect the sperm membranes by inhibiting ice crystal formation during the cryopreservation process. The present study was conducted to investigate the consequence of CPLL supplementation on the post-thaw quality of cryopreserved goat sperm. For this, different doses (0, 0.5%, 1%, 1.5%, and 2%; v/v) of CPLL were added to the cryopreservation medium, and the motility, membrane and acrosome integrity, mitochondrial membrane potential (MMP), ATP level, ROS production, anti-oxidant defense system, malondialdehyde (MDA) level, and apoptosis in post-thaw sperm were evaluated. It was observed that the addition of 1% CPLL significantly (p < 0.05) increased the total motility, membrane integrity, acrosome integrity, and catalase (CAT) activity of post-thaw sperm compared to those of control and other CPLL doses. The ATP content was observed significantly (p < 0.05) higher in 0.5% and 1% CPLL, however, the SOD activity and progressive motility were significantly (p < 0.05) increased by adding CPLL at 1% and 1.5% level. Moreover, the addition of CPLL at 1% dose not only showed a lower percentage of apoptosis, but also significantly (p < 0.05) increased the MMP while reducing ROS production and MDA levels compared to those of other CPLL doses and/or control. Therefore, it is clear that the supplementation of 1% CPLL can remarkably improve the post-thaw goat sperm motility, membrane and acrosome integrity, antioxidant abundance, mitochondrial potentials, and ATP supply by protecting the sperm from cryodamage and undergoing apoptosis. These findings will provide novel insights into sperm cryobiology.
Parietal Epithelial Cell Behavior and Its Modulation by microRNA-193a
Authors: Bharati Joyita , Chander Praveen N. , Singhal Pravin C.
Published: February 2023

Glomerular parietal epithelial cells (PECs) have been increasingly recognized to have crucial functions. Lineage tracking in animal models showed the expression of a podocyte phenotype by PECs during normal glomerular growth and after acute podocyte injury, suggesting a reparative role of PECs. Conversely, activated PECs are speculated to be pathogenic and comprise extracapillary proliferation in focal segmental glomerulosclerosis (FSGS) and crescentic glomerulonephritis (CrescGN). The reparative and pathogenic roles of PECs seem to represent two sides of PEC behavior directed by the local milieu and mediators. Recent studies suggest microRNA-193a (miR193a) is involved in the pathogenesis of FSGS and CrescGN. In a mouse model of primary FSGS, the induction of miR193a caused the downregulation of Wilms’ tumor protein, leading to the dedifferentiation of podocytes. On the other hand, the inhibition of miR193a resulted in reduced crescent lesions in a mouse model of CrescGN. Interestingly, in vitro studies report that the downregulation of miR193a induces trans-differentiation of PECs into a podocyte phenotype. This narrative review highlights the critical role of PEC behavior in health and during disease and its modulation by miR193a.
Oligodendrocytes Prune Axons Containing α-Synuclein Aggregates In Vivo: Lewy Neurites as Precursors of Glial Cytoplasmic Inclusions in Multiple System Atrophy?
Authors: De Nuccio Francesco , Kashyrina Marianna , Serinelli Francesca , Laferrière Florent , Lofrumento Dario Domenico , De Giorgi Francesca , Ichas François
Published: February 2023

α-Synucleinopathies are spreading neurodegenerative disorders characterized by the intracellular accumulation of insoluble aggregates populated by α-Synuclein (α-Syn) fibrils. In Parkinson’s disease (PD) and dementia with Lewy bodies, intraneuronal α-Syn aggregates are referred to as Lewy bodies in the somata and as Lewy neurites in the neuronal processes. In multiple system atrophy (MSA) α-Syn aggregates are also found within mature oligodendrocytes (OLs) where they form Glial Cytoplasmic Inclusions (GCIs). However, the origin of GCIs remains enigmatic: (i) mature OLs do not express α-Syn, precluding the seeding and the buildup of inclusions and (ii) the artificial overexpression of α-Syn in OLs of transgenic mice results in a burden of soluble phosphorylated α-Syn but fails to form α-Syn fibrils. In contrast, mass spectrometry of α-Syn fibrillar aggregates from MSA patients points to the neuronal origin of the proteins intimately associated with the fibrils within the GCIs. This suggests that GCIs are preassembled in neurons and only secondarily incorporated into OLs. Interestingly, we recently isolated a synthetic human α-Syn fibril strain (1B fibrils) capable of seeding a type of neuronal inclusion observed early and specifically during MSA. Our goal was thus to investigate whether the neuronal α-Syn pathology seeded by 1B fibrils could eventually be transmitted to OLs to form GCIs in vivo. After confirming that mature OLs did not express α-Syn to detectable levels in the adult mouse brain, a series of mice received unilateral intra-striatal injections of 1B fibrils. The resulting α-Syn pathology was visualized using phospho-S129 α-Syn immunoreactivity (pSyn). We found that even though 1B fibrils were injected unilaterally, many pSyn-positive neuronal somas were present in layer V of the contralateral perirhinal cortex after 6 weeks. This suggested a fast retrograde spread of the pathology along the axons of crossing cortico-striatal neurons. We thus scrutinized the posterior limb of the anterior commissure, i.e., the myelinated interhemispheric tract containing the axons of these neurons: we indeed observed numerous pSyn-positive linear Lewy Neurites oriented parallel to the commissural axis, corresponding to axonal segments filled with aggregated α-Syn, with no obvious signs of OL α-Syn pathology at this stage. After 6 months however, the commissural Lewy neurites were no longer parallel but fragmented, curled up, sometimes squeezed in-between two consecutive OLs in interfascicular strands, or even engulfed inside OL perikarya, thus forming GCIs. We conclude that the 1B fibril strain can rapidly induce an α-Syn pathology typical of MSA in mice, in which the appearance of GCIs results from the pruning of diseased axonal segments containing aggregated α-Syn.
The Epigenetic Regulation of RNA N6-Methyladenosine Methylation in Glycolipid Metabolism
Authors: Yang Haiqing , Li Yuting , Huang Linying , Fang Miaochun , Xu Shun
Published: February 2023

The highly conserved and dynamically reversible N6-methyladenine (m6A) modification has emerged as a critical gene expression regulator by affecting RNA splicing, translation efficiency, and stability at the post-transcriptional level, which has been established to be involved in various physiological and pathological processes, including glycolipid metabolism and the development of glycolipid metabolic disease (GLMD). Hence, accumulating studies have focused on the effects and regulatory mechanisms of m6A modification on glucose metabolism, lipid metabolism, and GLMD. This review summarizes the underlying mechanism of how m6A modification regulates glucose and lipid metabolism-related enzymes, transcription factors, and signaling pathways and the advances of m6A regulatory mechanisms in GLMD in order to deepen the understanding of the association of m6A modification with glycolipid metabolism and GLMD.
Special Issue: Resistance to Targeted Therapies in Human Cancer
Authors: Lee Tae-Won , Choi Hee-Joo , Lee Kyung-Min , Lee Jeong-Yeon
Published: February 2023

Cancer is the second leading cause of death worldwide, accounting for approximately 10 million deaths in 2020 [...]
Sodium Tungstate (NaW) Decreases Reactive Oxygen Species (ROS) Production in Cells: New Cellular Antioxidant
Authors: Yañez Alejandro J. , Jaramillo Karen , Blaña Camila , Burgos Rafael A. , Isla Adolfo , Silva Pamela , Aguilar Marcelo
Published: February 2023

Diabetic nephropathy (DN) is the leading cause of end-stage renal failure worldwide. Hyperglycemia generates reactive oxygen species (ROS), contributing to diabetic complications, especially in DN. Sodium Tungstate (NaW) is an effective antidiabetic agent for short and long-term treatments of both type 1 and type 2 diabetes models. In this study, we evaluated the effect of NaW on ROS production in bovine neutrophils incubated with platelet-activating factor (PAF) and in HK-2 cells induced by high glucose or H2O2. In addition, we evaluated the effect on iNOS expression in the type 1 diabetic rat model induced with streptozotocin (STZ). NaW inhibited ROS production in PAF-induced bovine neutrophils, and human tubular cells (HK-2) were incubated in high glucose or H2O2. In addition, NaW inhibited iNOS expression in glomeruli and tubular cells in the type 1 diabetic rat. This study demonstrates a new role for NaW as an active antioxidant and its potential use in treating DN.
Integration of Ultrastructural and Computational Approaches Reveals the Protective Effect of Astaxanthin against BPA-Induced Nephrotoxicity
Authors: A. Eid Refaat , Alaa Edeen Muhammad , Soltan Mohamed A. , Al-Shraim Mubarak , Samir A. Zaki Mohamed , M. Al-Qahtani Saleh , Fayad Eman , T. Salem Eman , K. Abdulsahib Waleed , Emam Hebatallah , M. Hassan Hesham
Published: February 2023

Background: Bisphenol A (BPA) is an environmental contaminant that can induce deleterious organ effects. Human Cytochrome P450 CYP2C9 enzyme belongs to the essential xenobiotic-metabolizing enzymes, producing ROS as a byproduct. Astaxanthin (ATX) is a powerful antioxidant that protects organs and tissues from the damaging effects of oxidative stress caused by various diseases. Aim of the study: This study investigated the possible protective impacts of ATX against BPA-induced nephrotoxicity and its underlying mechanism. Materials and methods: Kidney tissues were isolated and examined microscopically from control, protected, and unprotected groups of rats to examine the potential protective effect of ATX against nephrotoxicity. Moreover, a molecular dynamic (MD) simulation was conducted to predict the performance of ATX upon binding to the active site of P450 CYP2C9 protein receptor as a potential mechanism of ATX protective effect. Results: Implemented computational methods revealed the possible underlying mechanism of ATX protection; the protective impact of ATX is mediated by inhibiting P450 CYP2C9 through binding to its dimeric state where the RMSF value for apo-protein and ATX-complex system were 5.720.57 and 1.040.41, respectively, implicating the ATX-complex system to have lesser variance in its residues, leading to the prevention of ROS excess production, maintaining the oxidant-antioxidant balance and re-establishing the proper mitochondrial functionality. Furthermore, the experimental methods validated in silico outcomes and revealed that ATX therapy effectively restored the typical histological architecture of pathological kidney tissues. Conclusions: ATX prevents BPA-induced nephrotoxicity by controlling oxidative imbalance and reversing mitochondrial dysfunction. These outcomes shed new light on the appropriate use of ATX as a treatment or prophylactic agent for these severe conditions.
Artificial Intelligence in Bladder Cancer Diagnosis: Current Applications and Future Perspectives
Authors: Rossin Giulio , Zorzi Federico , Ongaro Luca , Piasentin Andrea , Vedovo Francesca , Liguori Giovanni , Zucchi Alessandro , Simonato Alchiede , Bartoletti Riccardo , Trombetta Carlo , Pavan Nicola , Claps Francesco
Published: February 2023

Bladder cancer (BCa) is one of the most diagnosed urological malignancies. A timely and accurate diagnosis is crucial at the first assessment as well as at the follow up after curative treatments. Moreover, in the era of precision medicine, proper molecular characterization and pathological evaluation are key drivers of a patient-tailored management. However, currently available diagnostic tools still suffer from significant operator-dependent variability. To fill this gap, physicians have shown a constantly increasing interest towards new resources able to enhance diagnostic performances. In this regard, several reports have highlighted how artificial intelligence (AI) can produce promising results in the BCa field. In this narrative review, we aimed to analyze the most recent literature exploring current experiences and future perspectives on the role of AI in the BCa scenario. We summarized the most recently investigated applications of AI in BCa management, focusing on how this technology could impact physicians’ accuracy in three widespread diagnostic areas: cystoscopy, clinical tumor (cT) staging, and pathological diagnosis. Our results showed the wide potential of AI in BCa, although larger prospective and well-designed trials are pending to draw definitive conclusions allowing AI to be routinely applied to everyday clinical practice.
Towards Automated Meta-Analysis of Clinical Trials: An Overview
Authors: Christopoulou Stella C.
Published: February 2023

Background: Nowadays, much research deals with the application of the automated meta-analysis of clinical trials through appropriate machine learning tools to extract the results that can then be applied in daily clinical practice. Methods: The author performed a systematic search of the literature from 27 September 2022–22 November 2022 in PUBMED, in the first 6 pages of Google Scholar and in the online catalog, the Systematic Review Toolbox. Moreover, a second search of the literature was performed from 7 January 2023–20 January 2023 in the first 10 pages of Google Scholar and in the Semantic Google Scholar. Results: 38 approaches in 39 articles met the criteria and were included in this overview. These articles describe in detail machine learning approaches, methods, and tools that have been or can potentially be applied to the meta-analysis of clinical trials. Nevertheless, while the other tasks of a systematic review have significantly developed, the automation of meta-analyses is still far from being able to significantly support and facilitate the work of researchers, freeing them from manual, difficult and time-consuming work. Conclusions: The evaluation of automated meta-analysis results is presented in some studies. Their approaches show positive and promising results.