bluuebunny/crossref_metadata_2025 huggingface dataset:
The Cytoplasmic Region of SARAF Reduces Triple-Negative Breast Cancer Metastasis through the Regulation of Store-Operated Calcium Entry
Authors: Saldías María Paz , Cruz Pablo , Silva Ian , Orellana-Serradell Octavio , Lavanderos Boris , Maureira Diego , Pinto Raquel , Cerda Oscar
Published: March 2023

Triple-negative breast cancer has a poor prognosis and is non-responsive to first-line therapies; hence, new therapeutic strategies are needed. Enhanced store-operated Ca2+ entry (SOCE) has been widely described as a contributing factor to tumorigenic behavior in several tumor types, particularly in breast cancer cells. SOCE-associated regulatory factor (SARAF) acts as an inhibitor of the SOCE response and, therefore, can be a potential antitumor factor. Herein, we generated a C-terminal SARAF fragment to evaluate the effect of overexpression of this peptide on the malignancy of triple-negative breast cancer cell lines. Using both in vitro and in vivo approaches, we showed that overexpression of the C-terminal SARAF fragment reduced proliferation, cell migration, and the invasion of murine and human breast cancer cells by decreasing the SOCE response. Our data suggest that regulating the activity of the SOCE response via SARAF activity might constitute the basis for further alternative therapeutic strategies for triple-negative breast cancer.
Muscle Lipid Oxidation Is Not Affected by Obstructive Sleep Apnea in Diabetes and Healthy Subjects
Authors: Lattova Zuzana , Slovakova Lucie , Plihalova Andrea , Gojda Jan , Elkalaf Moustafa , Westlake Katerina , Polak Jan
Published: March 2023

The molecular mechanisms linking obstructive sleep apnea (OSA) with type 2 diabetes mellitus (T2DM) remain unclear. This study investigated the effect of OSA on skeletal muscle lipid oxidation in nondiabetic controls and in type 2 diabetes (T2DM) patients. Forty-four participants matched for age and adiposity were enrolled: nondiabetic controls (control, n = 14), nondiabetic patients with severe OSA (OSA, n = 9), T2DM patients with no OSA (T2DM, n = 10), and T2DM patients with severe OSA (T2DM + OSA, n = 11). A skeletal muscle biopsy was performed; gene and protein expressions were determined and lipid oxidation was analyzed. An intravenous glucose tolerance test was performed to investigate glucose homeostasis. No differences in lipid oxidation (178.2 ± 57.1, 161.7 ± 22.4, 169.3 ± 50.9, and 140.0 ± 24.1 pmol/min/mg for control, OSA, T2DM, and T2DM+OSA, respectively; p > 0.05) or gene and protein expressions were observed between the groups. The disposition index, acute insulin response to glucose, insulin resistance, plasma insulin, glucose, and HBA1C progressively worsened in the following order: control, OSA, T2DM, and T2DM + OSA (p for trend <0.05). No association was observed between the muscle lipid oxidation and the glucose metabolism variables. We conclude that severe OSA is not associated with reduced muscle lipid oxidation and that metabolic derangements in OSA are not mediated through impaired muscle lipid oxidation.
Construction of ceRNA Networks at Different Stages of Somatic Embryogenesis in Garlic
Authors: Bai Yunhe , Liu Min , Zhou Rong , Jiang Fangling , Li Ping , Li Mengqian , Zhang Meng , Wei Hanyu , Wu Zhen
Published: March 2023

LncRNA (long non-coding RNA) and mRNA form a competitive endogenous RNA (ceRNA) network by competitively binding to common miRNAs. This network regulates various processes of plant growth and development at the post-transcriptional level. Somatic embryogenesis is an effective means of plant virus-free rapid propagation, germplasm conservation, and genetic improvement, which is also a typical process to study the ceRNA regulatory network during cell development. Garlic is a typical asexual reproductive vegetable. Somatic cell culture is an effective means of virus-free rapid propagation in garlic. However, the ceRNA regulatory network of somatic embryogenesis remains unclear in garlic. In order to clarify the regulatory role of the ceRNA network in garlic somatic embryogenesis, we constructed lncRNA and miRNA libraries of four important stages (explant stage: EX; callus stage: AC; embryogenic callus stage: EC; globular embryo stage: GE) in the somatic embryogenesis of garlic. It was found that 44 lncRNAs could be used as precursors of 34 miRNAs, 1511 lncRNAs were predicted to be potential targets of 144 miRNAs, and 45 lncRNAs could be used as eTMs of 29 miRNAs. By constructing a ceRNA network with miRNA as the core, 144 miRNAs may bind to 1511 lncRNAs and 12,208 mRNAs. In the DE lncRNA-DE miRNA-DE mRNA network of adjacent stages of somatic embryo development (EX-VS-CA, CA-VS-EC, EC-VS-GE), by KEGG enrichment of adjacent stage DE mRNA, plant hormone signal transduction, butyric acid metabolism, and C5-branched dibasic acid metabolism were significantly enriched during somatic embryogenesis. Since plant hormones play an important role in somatic embryogenesis, further analysis of plant hormone signal transduction pathways revealed that the auxin pathway-related ceRNA network (lncRNAs-miR393s-TIR) may play a role in the whole stage of somatic embryogenesis. Further verification by RT-qPCR revealed that the lncRNA125175-miR393h-TIR2 network plays a major role in the network and may affect the occurrence of somatic embryos by regulating the auxin signaling pathway and changing the sensitivity of cells to auxin. Our results lay the foundation for studying the role of the ceRNA network in the somatic embryogenesis of garlic.
Mechanism Repositioning Based on Integrative Pharmacology: Anti-Inflammatory Effect of Safflower in Myocardial Ischemia–Reperfusion Injury
Authors: Zhao Feng , Jiang Hong , Zhang Tong , Chen Hong , Li Weijie , Li Xin , Wang Ping , Xu Haiyu
Published: March 2023

Safflower (Carthamus tinctorius. L) possesses anti-tumor, anti-thrombotic, anti-oxidative, immunoregulatory, and cardio-cerebral protective effects. It is used clinically for the treatment of cardio-cerebrovascular disease in China. This study aimed to investigate the effects and mechanisms of action of safflower extract on myocardial ischemia–reperfusion (MIR) injury in a left anterior descending (LAD)-ligated model based on integrative pharmacology study and ultra-performance liquid chromatography–quadrupole time-of-flight-tandem mass spectrometer (UPLC-QTOF-MS/MS). Safflower (62.5, 125, 250 mg/kg) was administered immediately before reperfusion. Triphenyl tetrazolium chloride (TTC)/Evans blue, echocardiography, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay, lactate dehydrogenase (LDH) ability, and superoxide dismutase (SOD) levels were determined after 24 h of reperfusion. Chemical components were obtained using UPLC-QTOF-MS/MS. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting were used to analyze mRNA and protein levels, respectively. Safflower dose-dependently reduced myocardial infarct size, improved cardiac function, decreased LDH levels, and increased SOD levels in C57/BL6 mice. A total of 11 key components and 31 hub targets were filtered based on the network analysis. Comprehensive analysis indicated that safflower alleviated inflammatory effects by downregulating the expression of NFκB1, IL-6, IL-1β, IL-18, TNFα, and MCP-1 and upregulating NFκBia, and markedly increased the expression of phosphorylated PI3K, AKT, PKC, and ERK/2, HIF1α, VEGFA, and BCL2, and decreased the level of BAX and phosphorylated p65. Safflower shows a significant cardioprotective effect by activating multiple inflammation-related signaling pathways, including the NFκB, HIF-1α, MAPK, TNF, and PI3K/AKT signaling pathways. These findings provide valuable insights into the clinical applications of safflower.
Dietary Supplementation of Microbial Dextran and Inulin Exerts Hypocholesterolemic Effects and Modulates Gut Microbiota in BALB/c Mice Models
Authors: Jawad Iqra , Bin Tawseen Husam , Irfan Muhammad , Ahmad Waqar , Hassan Mujtaba , Sattar Fazal , Awan Fazli Rabbi , Khaliq Shazia , Akhtar Nasrin , Akhtar Kalsoom , Anwar Munir Ahmad , Munawar Nayla
Published: March 2023

Microbial exopolysaccharides (EPSs), having great structural diversity, have gained tremendous interest for their prebiotic effects. In the present study, mice models were used to investigate if microbial dextran and inulin-type EPSs could also play role in the modulation of microbiomics and metabolomics by improving certain biochemical parameters, such as blood cholesterol and glucose levels and weight gain. Feeding the mice for 21 days on EPS-supplemented feed resulted in only 7.6 ± 0.8% weight gain in the inulin-fed mice group, while the dextran-fed group also showed a low weight gain trend as compared to the control group. Blood glucose levels of the dextran- and inulin-fed groups did not change significantly in comparison with the control where it increased by 22 ± 5%. Moreover, the dextran and inulin exerted pronounced hypocholesterolemic effects by reducing the serum cholesterol levels by 23% and 13%, respectively. The control group was found to be mainly populated with Enterococcus faecalis, Staphylococcus gallinarum, Mammaliicoccus lentus and Klebsiella aerogenes. The colonization of E. faecalis was inhibited by 59–65% while the intestinal release of Escherichia fergusonii was increased by 85–95% in the EPS-supplemented groups, respectively, along with the complete inhibition of growth of other enteropathogens. Additionally, higher populations of lactic acid bacteria were detected in the intestine of EPS-fed mice as compared to controls.
Targeting Peripheral N-Methyl-D-Aspartate Receptor (NMDAR): A Novel Strategy for the Treatment of Migraine
Authors: Kalatharan Veberka , Al-Karagholi Mohammad Al-Mahdi
Published: March 2023

Backgrounds: Several acute and preventive medications were developed for the treatment of migraine. Yet, a significant proportion of patients reports an inadequate response and a lack of tolerability, emphasizing the need for new options. Glutamate is the most important excitatory neurotransmitter in the brain, and glutamate receptors including N-Methyl-D-Aspartate Receptor (NMDAR) are expressed at several levels of the trigeminovascular system, which is the anatomical and physiological substrate of migraine pain. Objective: To review preclinical and clinical studies investigating the role of the NMDAR in migraine pathophysiology. Methods: No protocol was registered for this study. References for the present review were identified from a narrative search of the PubMed database. Search terms such as glutamate, migraine, N-Methyl-D-Aspartate Receptor, and NMDAR were used. No restrictions were made in terms of the language and date of publication. Results: In animal models, administration of monosodium glutamate (MSG) activated and sensitized trigeminovascular neurons. In healthy human participants, consumption of MSG caused headaches, craniofacial sensitivity, and nausea. In in vivo models and through immunolabeling, NMDAR subunits NR1, NR2A, and NR2B were expressed in trigeminal ganglion neurons. In humans, NMDAR antagonists such as ketamine and memantine caused a significant reduction in pain intensity and monthly headache frequency. Conclusions: Accumulative evidence indicates that NMDAR is a promising new target for the treatment of migraine. Selective NMDAR antagonists without central effects are needed to investigate their therapeutic benefit in the treatment of migraine.
Using an Attachment System with PEEK Matrices for Single-Implant Overdentures: In Vitro Retention Force
Authors: Fugariu Ioana , de Souza Raphael Freitas , Rosas Eduardo , Borie Eduardo
Published: March 2023

Single-implant overdentures (SIOs) represent a major biomechanical challenge in terms of prosthetic retention. The Novaloc attachment system has the potential to overcome those challenges when used for SIOs, due to the use of PEEK matrices. This study compared the retentive force of the Novaloc attachment to the traditional Locator system, before and after cyclic insertion–removal cycles. Three Novaloc matrices (white, yellow, and green, corresponding to low, medium, and high retention, respectively) and Locator (medium retention) were tested, totalling four groups. Retentive force was measured using an Imada force gauge before and after 1095 insertion–removal cycles, corresponding to a year of SIO wearing. Retention was tested with the implants angulated at 0, 10, and 20°. Data for the different groups, angles, and cycling periods were tested via linear regression analysis and two-way ANOVA (α = 0.05). Although the Locator system yielded higher retention forces in general, it lost a much higher percentage of retention with cycling. This trend was similar with the three angles, with forces being inversely proportional to the implant angulation. The authors conclude that Novaloc may provide more reliable retention for SIOs due to their higher resistance to insertion–removal cycling.
Emerging Trends in Research on Self-Regulated Learning and Implications for Education: An Introduction to the Special Issue
Authors: Tauber Sarah K. , Ariel Robert
Published: March 2023

Students in higher education face a multitude of challenges when gaining and refining their knowledge [...]
A Critical Review of High-Temperature Tribology and Cutting Performance of Cermet and Ceramic Tool Materials
Authors: Elgazzar Ali , Zhou Sheng-Jian , Ouyang Jia-Hu , Liu Zhan-Guo , Wang Yu-Jin , Wang Ya-Ming
Published: March 2023

Cermet materials exhibit advanced mechanical and tribological properties, and are widely used for tribology, elevated temperature, and machining applications due to their unique amalgamation of hardness, strength, and toughness. This paper presents a comprehensive overview of various cermet systems and recent advances in high-temperature tribology and cutting performance of cermet and ceramic tool materials. It outlines microstructural properties, such as lessening grain sizes, obtaining extended grains, lowering grain boundary phase content, amorphous grain boundary phases crystallizing, inter-granular phase strengthening, and managing crack propagation path. Additionally, surface processing or surface modifications, such as surface texturing, appropriate roughness, or coating technique, can optimize the ceramic and cermet tribological performances. The purpose of this study is to present some guidelines for the design of ceramics and cermets with reduced friction and wear and increased cutting performance. The current research progress concerning tribological properties and surface texturing of cutting tool inserts is critically identified. Lubrication techniques are required in commercial applications to increase the lifetime of cutting tools used in harsh conditions. Liquid lubricants are still commonly utilized in relative motion; however, they have the limitations of not working in extreme settings, such as high-temperature environments. As a result, global research is presently underway to produce new solid lubricants for use in a variety of such conditions. This review also provides a quick outline of current research on this topic.
A Review on Tetrabromobisphenol A: Human Biomonitoring, Toxicity, Detection and Treatment in the Environment
Authors: Miao Baoji , Yakubu Salome , Zhu Qingsong , Issaka Eliasu , Zhang Yonghui , Adams Mabruk
Published: March 2023

Tetrabromobisphenol A (TBBPA) is a known endocrine disruptor employed in a range of consumer products and has been predominantly found in different environments through industrial processes and in human samples. In this review, we aimed to summarize published scientific evidence on human biomonitoring, toxic effects and mode of action of TBBPA in humans. Interestingly, an overview of various pretreatment methods, emerging detection methods, and treatment methods was elucidated. Studies on exposure routes in humans, a combination of detection methods, adsorbent-based treatments and degradation of TBBPA are in the preliminary phase and have several limitations. Therefore, in-depth studies on these subjects should be considered to enhance the accurate body load of non-invasive matrix, external exposure levels, optimal design of combined detection techniques, and degrading technology of TBBPA. Overall, this review will improve the scientific comprehension of TBBPA in humans as well as the environment, and the breakthrough for treating waste products containing TBBPA.
Hydrothermal Synthesis of Nickel Oxide and Its Application in the Additive Manufacturing of Planar Nanostructures
Authors: Dudorova Darya A. , Simonenko Tatiana L. , Simonenko Nikolay P. , Gorobtsov Philipp Yu. , Volkov Ivan A. , Simonenko Elizaveta P. , Kuznetsov Nikolay T.
Published: March 2023

The hydrothermal synthesis of nickel oxide in the presence of triethanolamine was studied. Furthermore, the relationship between the synthesis conditions, thermal behavior, crystal structure features, phase composition and microstructure of semi-products, and the target oxide nanopowders was established. The thermal behavior of the semi-products was studied using a simultaneous thermal analysis (in particular, using one that involved thermogravimetric analysis and differential scanning calorimetry, TGA/DSC). An X-ray diffraction (XRD) analysis revealed that varying the triethanolamine and nickel chloride concentration in the reaction system can govern the formation of α- and β-Ni(OH)2-based semi-products that contain Ni(HCO3)2 or Ni2(CO3)(OH)2 as additional components. The set of functional groups in the powders was determined using a Fourier-transform infrared (FTIR) spectroscopy analysis. Using microextrusion printing, a composite NiO—(CeO2)0.80(Sm2O3)0.20 anode film was fabricated. Using XRD, scanning electron microscopy (SEM), and atomic force microscopy (AFM) analyses, it was demonstrated that the crystal structure, dispersity, and microstructure character of the obtained material correspond to the initial nanopowders. Using Kelvin probe force microscopy (KPFM) and scanning capacitance microscopy (SCM), the local electrophysical properties of the printed composite film were examined. The value of its conductivity was evaluated using the four-probe method on a direct current in the temperature range of 300–650 °C. The activation energy for the 500–650 °C region, which is of most interest in the context of intermediate-temperature SOFCs working temperatures, has been estimated.
Two Onnamide Analogs from the Marine Sponge Theonella conica: Evaluation of Geometric Effects in the Polyene Systems on Biological Activity
Authors: Nakamura Fumiaki , Kimura Hiroshi , Fusetani Nobuhiro , Nakao Yoichi
Published: March 2023

Two previously unreported onnamide analogs, 2Z- and 6Z-onnamides A (1 and 2), were isolated from the marine sponge Theonella conica collected at Amami-Oshima Is., Kagoshima Prefecture, Japan. Structures of compounds 1 and 2 were elucidated by spectral analysis. Structure–activity relationships (SARs) for effects on histone modifications and cytotoxicity against HeLa and P388 cells were characterized. The geometry in the polyene systems of onnamides affected the histone modification levels and cytotoxicity.
Evaluation of Biosecurity Measures in Pig Holdings in Slovenia as a Risk Assessment for the Introduction of African Swine Fever Virus
Authors: Plut Jan , Knific Tanja , Golinar Oven Irena , Vengušt Gorazd , Štukelj Marina
Published: March 2023

African Swine Fever (ASF) is persistently spreading and hindering pork production in Europe. Slovenia is one of the last countries in Central Europe without a confirmed ASF case in domestic pigs or in wild boar. The aim of this study was to assess the current biosecurity implementation on different types of pig farms. Internal and external biosecurity status was determined in 17 commercial (CF), 15 non-commercial (NC), and 15 outdoor (O) farms. Data were collected using the Biocheck.UGent questionnaire and assessed in combination with the latest information on the wild boar population in Slovenia. Biosecurity was compared between farm types based on the assessment of 12 subcategories. Statistically significant differences (p < 0.05) were found in six subcategories: (i) purchase of pigs and semen, (ii) visitors and farmworkers, (iii) vermin and bird control, (iv) finishing unit, (v) measures between compartments and use of equipment, and (vi) cleaning and disinfection. The highest total biosecurity score (0–100%) was determined on CF with 64.59 ± 16.47%, followed by NC with 55.73 ± 10.67%, and O with 48.47 ± 8.20%. The density of the wild boar population was estimated from the number of wild boars per km2 per year, with 3 or more hunted wild boars per unit representing the highest density. Geolocation of farms on the wild boar population map showed that two O farms are at high risk and seven farms (1 O, 5 NC, and 1 CF) are at medium risk for disease transmission from wild to domestic pigs. Biosecurity measures must be tightened in some subcategories, especially in areas with a high density of wild boar.
Essential Oil from Glossogyne tenuifolia Inhibits Lipopolysaccharide-Induced Inflammation-Associated Genes in Macro-Phage Cells via Suppression of NF-κB Signaling Pathway
Authors: Lin Wan-Teng , He Yen-Hua , Lo Yun-Hsin , Chiang Yu-Ting , Wang Sheng-Yang , Bezirganoglu Ismail , Kumar K. J. Senthil
Published: March 2023

Glossogyne tenuifolia Cassini (Hsiang-Ju in Chinese) is a perennial herb native to Taiwan. It was used in traditional Chinese medicine (TCM) as an antipyretic, anti-inflammatory, and hepatoprotective agent. Recent studies have shown that extracts of G. tenuifolia possess various bioactivities, including anti-oxidant, anti-inflammatory, immunomodulation, and anti-cancer properties. However, the pharmacological activities of G. tenuifolia essential oils have not been studied. In this study, we extracted essential oil from air-dried G. tenuifolia plants, then investigated the anti-inflammatory potential of G. tenuifolia essential oil (GTEO) on lipopolysaccharide (LPS)-induced inflammation in murine macrophage cells (RAW 264.7) in vitro. Treatment with GTEO (25, 50, and 100 μg/mL) significantly as well as dose-dependently inhibited LPS-induced pro-inflammatory molecules, such as nitric oxide (NO) and prostaglandin E2 (PGE2) production, without causing cytotoxicity. Q-PCR and immunoblotting analysis revealed that the inhibition of NO and PGE2 was caused by downregulation of their corresponding mediator genes, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2), respectively. Immunofluorescence and luciferase reporter assays revealed that the inhibition of iNOS and COX-2 genes by GTEO was associated with the suppression of nuclear export and transcriptional activation of the redox-sensitive transcription factor, nuclear factor -κB (NF-κB). In addition, GTEO treatment significantly inhibited phosphorylation and proteosomal degradation of the inhibitor of NF-κB (I-κBα), an endogenous repressor of NF-κB. Moreover, treatment with GTEO significantly blocked the LPS-mediated activation of inhibitory κB kinase α (IKKα), an upstream kinase of the I-κBα. Furthermore, p-cymene, β-myrcene, β-cedrene, cis-β-ocimene, α-pinene, and D-limonene were represented as major components of GTEO. We found that treatment with p-cymene, α-pinene, and D-limonene were significantly inhibiting LPS-induced NO production in RAW 264.7 cells. Taken together, these results strongly suggest that GTEO inhibits inflammation through the downregulation of NF-κB-mediated inflammatory genes and pro-inflammatory molecules in macrophage cells.
MindReader: Unsupervised Classification of Electroencephalographic Data
Authors: Rivas-Carrillo Salvador Daniel , Akkuratov Evgeny E. , Valdez Ruvalcaba Hector , Vargas-Sanchez Angel , Komorowski Jan , San-Juan Daniel , Grabherr Manfred G.
Published: March 2023

Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process. Automatic detection offers the potential to improve the quality of patient care by shortening the time to diagnosis, managing big data and optimizing the allocation of human resources towards precision medicine. Here, we present MindReader, a novel unsupervised machine-learning method comprised of the interplay between an autoencoder network, a hidden Markov model (HMM), and a generative component: after dividing the signal into overlapping frames and performing a fast Fourier transform, MindReader trains an autoencoder neural network for dimensionality reduction and compact representation of different frequency patterns for each frame. Next, we processed the temporal patterns using a HMM, while a third and generative component hypothesized and characterized the different phases that were then fed back to the HMM. MindReader then automatically generates labels that the physician can interpret as pathological and non-pathological phases, thus effectively reducing the search space for trained personnel. We evaluated MindReader’s predictive performance on 686 recordings, encompassing more than 980 h from the publicly available Physionet database. Compared to manual annotations, MindReader identified 197 of 198 epileptic events (99.45%), and is, as such, a highly sensitive method, which is a prerequisite for clinical use.
Application of Multi-Criteria Optimization Methods in the Calibration Process of Digital Measuring Instruments
Authors: Klebba Maciej , Adamczyk Arkadiusz , Wąż Mariusz , Iwen Dominik
Published: March 2023

The article describes the use of multi-criteria optimization methods during the calibration of digital multimeters. Currently, calibration is based on a single measurement of a specific value. The aim of this research was to confirm the possibility of using a series of measurements in order to reduce the measurement uncertainty without significantly extending the calibration time. The automatic measurement loading laboratory stand used during the conducted experiments was essential to obtain results that allowed confirming the thesis. This article presents the applied optimization methods and the results of the calibration of sample digital multimeters obtained thanks to them. As a result of the research, it was found that the use of a series of measurements increased the accuracy of the calibration, reduced the measurement uncertainty, and shortened the calibration time compared to traditional methods.
Rehabilitation Is the Main Topic in Virtual and Augmented Reality and Physical Activity Research: A Bibliometric Analysis
Authors: Denche-Zamorano Angel , Rodriguez-Redondo Yeray , Barrios-Fernandez Sabina , Mendoza-Muñoz María , Castillo-Paredes Antonio , Rojo-Ramos Jorge , Garcia-Gordillo Miguel Angel , Adsuar Jose Carmelo
Published: March 2023

Researchers’ interest in finding practical applications for virtual reality (VR) and augmented reality (AR) technologies has increased as new devices have become cheaper and more accessible, being used in entertainment, healthcare, and rehabilitation fields, among others. This study aims to provide an overview of the current state of scientific literature related to VR, AR, and physical activity (PA). A bibliometric analysis of studies published between 1994 and 2022 was conducted using The Web of Science (WoS), applying the traditional bibliometric laws and using the VOSviewer software for data and metadata processing. The results revealed an exponential increase in scientific production between 2009 and 2021 (R2 = 94%). The United States (USA) was the country/region with the most relevant co-authorship networks (72 papers); the most prolific author was Kerstin Witte, and the most prominent was Richard Kulpa. The most productive journal’s core was composed of high-impact and open access journals. A great thematic diversity was found according to the most used keywords by the co-authors, highlighting concepts such as rehabilitation, cognition, training, and obesity. Then, the research related to this topic is in an exponential development phase, with great interest in the rehabilitation and sports sciences fields.
A Robust Automated Analog Circuits Classification Involving a Graph Neural Network and a Novel Data Augmentation Strategy
Authors: Deeb Ali , Ibrahim Abdalrahman , Salem Mohamed , Pichler Joachim , Tkachov Sergii , Karaj Anjeza , Al Machot Fadi , Kyandoghere Kyamakya
Published: March 2023

Analog mixed-signal (AMS) verification is one of the essential tasks in the development process of modern systems-on-chip (SoC). Most parts of the AMS verification flow are already automated, except for stimuli generation, which has been performed manually. It is thus challenging and time-consuming. Hence, automation is a necessity. To generate stimuli, subcircuits or subblocks of a given analog circuit module should be identified/classified. However, there currently needs to be a reliable industrial tool that can automatically identify/classify analog sub-circuits (eventually in the frame of a circuit design process) or automatically classify a given analog circuit at hand. Besides verification, several other processes would profit enormously from the availability of a robust and reliable automated classification model for analog circuit modules (which may belong to different levels). This paper presents how to use a Graph Convolutional Network (GCN) model and proposes a novel data augmentation strategy to automatically classify analog circuits of a given level. Eventually, it can be upscaled or integrated within a more complex functional module (for a structure recognition of complex analog circuits), targeting the identification of subcircuits within a more complex analog circuit module. An integrated novel data augmentation technique is particularly crucial due to the harsh reality of the availability of generally only a relatively limited dataset of analog circuits’ schematics (i.e., sample architectures) in practical settings. Through a comprehensive ontology, we first introduce a graph representation framework of the circuits’ schematics, which consists of converting the circuit’s related netlists into graphs. Then, we use a robust classifier consisting of a GCN processor to determine the label corresponding to the given input analog circuit’s schematics. Furthermore, the classification performance is improved and robust by involving a novel data augmentation technique. The classification accuracy was enhanced from 48.2% to 76.6% using feature matrix augmentation, and from 72% to 92% using Dataset Augmentation by Flipping. A 100% accuracy was achieved after applying either multi-Stage augmentation or Hyperphysical Augmentation. Overall, extensive tests of the concept were developed to demonstrate high accuracy for the analog circuit’s classification endeavor. This is solid support for a future up-scaling towards an automated analog circuits’ structure detection, which is one of the prerequisites not only for the stimuli generation in the frame of analog mixed-signal verification but also for other critical endeavors related to the engineering of AMS circuits.
Enzymatic Glucose Fiber Sensor for Glucose Concentration Measurement with a Heterodyne Interferometry
Authors: Hsu Cheng-Chih , Chung Wan-Yu , Chang Chun-Yi , Wu Chyan-Chyi , Lee Cheng-Ling
Published: March 2023

In this study, we developed a glucose fiber sensor incorporating heterodyne interferometry to measure the phase difference produced by the chemical reaction between glucose and glucose oxidase (GOx). Both theoretical and experimental results showed that the amount of phase variation is inversely proportional to glucose concentration. The proposed method provided a linear measurement range of the glucose concentration from 10 mg/dL to 550 mg/dL. The experimental results indicated that the sensitivity is proportional to the length of the enzymatic glucose sensor, and the optimum resolution can be obtained at a sensor length of 3 cm. The optimum resolution of the proposed method is better than 0.6 mg/dL. Moreover, the proposed sensor demonstrates good repeatability and reliability. The average relative standard deviation (RSD) is better than 10% and satisfied the minimum requirement for point-of-care devices.
Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare
Authors: Lu Tian , Ji Shourui , Jin Weiqiu , Yang Qisheng , Luo Qingquan , Ren Tian-Ling
Published: March 2023

Sensors enable the detection of physiological indicators and pathological markers to assist in the diagnosis, treatment, and long-term monitoring of diseases, in addition to playing an essential role in the observation and evaluation of physiological activities. The development of modern medical activities cannot be separated from the precise detection, reliable acquisition, and intelligent analysis of human body information. Therefore, sensors have become the core of new-generation health technologies along with the Internet of Things (IoTs) and artificial intelligence (AI). Previous research on the sensing of human information has conferred many superior properties on sensors, of which biocompatibility is one of the most important. Recently, biocompatible biosensors have developed rapidly to provide the possibility for the long-term and in-situ monitoring of physiological information. In this review, we summarize the ideal features and engineering realization strategies of three different types of biocompatible biosensors, including wearable, ingestible, and implantable sensors from the level of sensor designing and application. Additionally, the detection targets of the biosensors are further divided into vital life parameters (e.g., body temperature, heart rate, blood pressure, and respiratory rate), biochemical indicators, as well as physical and physiological parameters based on the clinical needs. In this review, starting from the emerging concept of next-generation diagnostics and healthcare technologies, we discuss how biocompatible sensors revolutionize the state-of-art healthcare system unprecedentedly, as well as the challenges and opportunities faced in the future development of biocompatible health sensors.
Control and Measurement Systems Supporting the Production of Haylage in Baler-Wrapper Machines
Authors: Zawada Michał , Nijak Mateusz , Mac Jarosław , Szczepaniak Jan , Legutko Stanisław , Gościańska-Łowińska Julia , Szymczyk Sebastian , Kaźmierczak Michał , Zwierzyński Mikołaj , Wojciechowski Jacek , Szulc Tomasz , Rogacki Roman
Published: March 2023

Baler-wrappers are machines designed to produce high-quality forage, in accordance with the requirements of sustainable agriculture. Their complicated structure, and significant loads occurring during operation, prompted the creation of systems for controlling the machines’ processes and measuring the most important work parameters, in this work. The compaction control system is based on a signal from the force sensors. It allows for detection differences in the compression of the bale and additionally protects against overload. The method of measuring the swath size, with the use of a 3D camera, was presented. Scanning the surface and travelled distance allows for estimating the volume of the collected material—making it possible to create yield maps (precision farming). It is also used to vary the dosage of ensilage agents, that control the fodder formation process, in relation to the moisture and temperature of the material. The paper also deals with the issue of measuring the weight of the bales—securing the machine against overload and collecting data for planning the bales’ transport. The machine, equipped with the above-mentioned systems, allows for safer and more efficient work, and provides information about the state of the crop in relation to a geographical position, which allows for further inferences.
Electrocardiogram Heartbeat Classification for Arrhythmias and Myocardial Infarction
Authors: Pham Bach-Tung , Le Phuong Thi , Tai Tzu-Chiang , Hsu Yi-Chiung , Li Yung-Hui , Wang Jia-Ching
Published: March 2023

An electrocardiogram (ECG) is a basic and quick test for evaluating cardiac disorders and is crucial for remote patient monitoring equipment. An accurate ECG signal classification is critical for real-time measurement, analysis, archiving, and transmission of clinical data. Numerous studies have focused on accurate heartbeat classification, and deep neural networks have been suggested for better accuracy and simplicity. We investigated a new model for ECG heartbeat classification and found that it surpasses state-of-the-art models, achieving remarkable accuracy scores of 98.5% on the Physionet MIT-BIH dataset and 98.28% on the PTB database. Furthermore, our model achieves an impressive F1-score of approximately 86.71%, outperforming other models, such as MINA, CRNN, and EXpertRF on the PhysioNet Challenge 2017 dataset.
UAV-Aided Dual-User Wireless Power Transfer: 3D Trajectory Design and Energy Optimization
Authors: Gou Xiaogang , Sun Zhaojie , Huang Kaiyuan
Published: March 2023

Unmanned aerial vehicles (UAVs) have been widely considered to enhance the communication coverage, as well as the wireless power transfer (WPT) of energy-constrained communication networks to prolong their lifetime. However, the trajectory design of a UAV in such a system remains a key problem, especially considering the three-dimensional (3D) feature of the UAV. To address this issue, a UAV-assisted dual-user WPT system was investigated in this paper, where a UAV-mounted energy transmitter (ET) flies in the air to broadcast wireless energy to charge the energy receivers (ERs) on the ground. By optimizing the UAV’s 3D trajectory toward a balanced tradeoff between energy consumption and WPT performance, the energy harvested by all ERs during a given mission period was maximized. The above goal was achieved through the following detailed designs. On the one hand, on the basis of previous research results, there is a one-to-one correspondence between the UAV’s abscissa and height, so only the relationship between the height and time was focused on in this work to obtain the UAV’s optimal 3D trajectory. On the other hand, the idea of calculus was employed to calculate the total harvested energy, leading to the proposed high-efficiency trajectory design. Finally, the simulation results demonstrated that this contribution is capable of enhancing the energy supply by carefully designing the 3D trajectory of the UAV, compared to its conventional counterpart. In general, the above-mentioned contribution could be a promising way for UAV-aided WPT in the future Internet of Things (IoT) and wireless sensor networks (WSNs).
Applying Reinforcement Learning for Enhanced Cybersecurity against Adversarial Simulation
Authors: Oh Sang Ho , Jeong Min Ki , Kim Hyung Chan , Park Jongyoul
Published: March 2023

Cybersecurity is a growing concern in today’s interconnected world. Traditional cybersecurity approaches, such as signature-based detection and rule-based firewalls, are often limited in their ability to effectively respond to evolving and sophisticated cyber threats. Reinforcement learning (RL) has shown great potential in solving complex decision-making problems in various domains, including cybersecurity. However, there are significant challenges to overcome, such as the lack of sufficient training data and the difficulty of modeling complex and dynamic attack scenarios hindering researchers’ ability to address real-world challenges and advance the state of the art in RL cyber applications. In this work, we applied a deep RL (DRL) framework in adversarial cyber-attack simulation to enhance cybersecurity. Our framework uses an agent-based model to continuously learn from and adapt to the dynamic and uncertain environment of network security. The agent decides on the optimal attack actions to take based on the state of the network and the rewards it receives for its decisions. Our experiments on synthetic network security show that the DRL approach outperforms existing methods in terms of learning optimal attack actions. Our framework represents a promising step towards the development of more effective and dynamic cybersecurity solutions.
Reduced Order Modeling of Nonlinear Vibrating Multiphysics Microstructures with Deep Learning-Based Approaches
Authors: Gobat Giorgio , Fresca Stefania , Manzoni Andrea , Frangi Attilio
Published: March 2023

Micro-electro-mechanical-systems are complex structures, often involving nonlinearites of geometric and multiphysics nature, that are used as sensors and actuators in countless applications. Starting from full-order representations, we apply deep learning techniques to generate accurate, efficient, and real-time reduced order models to be used for the simulation and optimization of higher-level complex systems. We extensively test the reliability of the proposed procedures on micromirrors, arches, and gyroscopes, as well as displaying intricate dynamical evolutions such as internal resonances. In particular, we discuss the accuracy of the deep learning technique and its ability to replicate and converge to the invariant manifolds predicted using the recently developed direct parametrization approach that allows the extraction of the nonlinear normal modes of large finite element models. Finally, by addressing an electromechanical gyroscope, we show that the non-intrusive deep learning approach generalizes easily to complex multiphysics problems.
Developing Edge AI Computer Vision for Smart Poultry Farms Using Deep Learning and HPC
Authors: Cakic Stevan , Popovic Tomo , Krco Srdjan , Nedic Daliborka , Babic Dejan , Jovovic Ivan
Published: March 2023

This research describes the use of high-performance computing (HPC) and deep learning to create prediction models that could be deployed on edge AI devices equipped with camera and installed in poultry farms. The main idea is to leverage an existing IoT farming platform and use HPC offline to run deep learning to train the models for object detection and object segmentation, where the objects are chickens in images taken on farm. The models can be ported from HPC to edge AI devices to create a new type of computer vision kit to enhance the existing digital poultry farm platform. Such new sensors enable implementing functions such as counting chickens, detection of dead chickens, and even assessing their weight or detecting uneven growth. These functions combined with the monitoring of environmental parameters, could enable early disease detection and improve the decision-making process. The experiment focused on Faster R-CNN architectures and AutoML was used to identify the most suitable architecture for chicken detection and segmentation for the given dataset. For the selected architectures, further hyperparameter optimization was carried out and we achieved the accuracy of AP = 85%, AP50 = 98%, and AP75 = 96% for object detection and AP = 90%, AP50 = 98%, and AP75 = 96% for instance segmentation. These models were installed on edge AI devices and evaluated in the online mode on actual poultry farms. Initial results are promising, but further development of the dataset and improvements in prediction models is needed.
Adaptive Control for Gravitational Wave Detection Formation Considering Time-Varying Communication Delays
Authors: Zhang Yu , Liu Yuan , Zhang Juzheng , Lu Zhenkun , Yang Jikun
Published: March 2023

A distributed six-degree-of-freedom (6-DOF) cooperative control for multiple spacecraft formation is investigated considering parametric uncertainties, external disturbances, and time-varying communication delays. Unit dual quaternions are used to describe the kinematics and dynamics models of the 6-DOF relative motion of the spacecraft. A distributed coordinated controller based on dual quaternions with time-varying communication delays is proposed. The unknown mass and inertia, as well as unknown disturbances, are then taken into account. An adaptive coordinated control law is developed by combining the coordinated control algorithm with an adaptive algorithm to compensate for parametric uncertainties and external disturbances. The Lyapunov method is used to prove that the tracking errors converge globally asymptotically. Numerical simulations show that the proposed method can realize cooperative control of attitude and orbit for the multi-spacecraft formation.
Miniaturized On-Ground 2.4 GHz IoT LTCC Chip Antenna and Its Positioning on a Ground Plane
Authors: Molins-Benlliure Jaime , Cabedo-Fabrés Marta , Antonino-Daviu Eva , Ferrando-Bataller Miguel
Published: March 2023

This paper presents a very low-profile on-ground chip antenna with a total volume of 0.075λ0× 0.056λ0× 0.019λ0 (at f0 = 2.4 GHz). The proposed design is a corrugated (accordion-like) planar inverted F antenna (PIFA) embedded in low-loss glass ceramic material (DuPont GreenTape 9k7 with ϵr = 7.1 and tanδ = 0.0009) fabricated with LTCC technology. The antenna does not require a clearance area on the ground plane where the antenna is located, and it is proposed for 2.4 GHz IoT applications for extreme size-limited devices. It shows a 25 MHz impedance bandwidth (for S11 < −6 dB), which means a relative bandwidth of 1%). A study in terms of matching and total efficiency is performed for several size ground planes with the antenna installed at different positions. The use of characteristic modes analysis (CMA) and the correlation between modal and total radiated fields is performed to demonstrate the optimum position of the antenna. Results show high-frequency stability and a total efficiency difference of up to 5.3 dB if the antenna is not placed at the optimum position.
An Extended AI-Experience: Industry 5.0 in Creative Product Innovation
Authors: Grech Amy , Mehnen Jörn , Wodehouse Andrew
Published: March 2023

Creativity plays a significant role in competitive product ideation. With the increasing emergence of Virtual Reality (VR) and Artificial Intelligence (AI) technologies, the link between such technologies and product ideation is explored in this research to assist and augment creative scenarios in the engineering field. A bibliographic analysis is performed to review relevant fields and their relationships. This is followed by a review of current challenges in group ideation and state-of-the-art technologies with the aim of addressing them in this study. This knowledge is applied to the transformation of current ideation scenarios into a virtual environment using AI. The aim is to augment designers’ creative experiences, a core value of Industry 5.0 that focuses on human-centricity, social and ecological benefits. For the first time, this research reclaims brainstorming as a challenging and inspiring activity where participants are fully engaged through a combination of AI and VR technologies. This activity is enhanced through three key areas: facilitation, stimulation, and immersion. These areas are integrated through intelligent team moderation, enhanced communication techniques, and access to multi-sensory stimuli during the collaborative creative process, therefore providing a platform for future research into Industry 5.0 and smart product development.