bluuebunny/crossref_metadata_2025 huggingface dataset:
Wear Analysis of Four Different Single-File Reciprocating Instruments before and after Four Uses in Simulated Root Canals
Authors: Zanza Alessio , Reda Rodolfo , Familiari Giuseppe , Nottola Stefania Annarita , Di Nardo Dario , Testarelli Luca , Donfrancesco Orlando
Published: June 2022

The aim of this study is to assess the surface alterations of four reciprocating instruments before and after the shaping of four resin-simulated root canals. The following four different reciprocating instruments are selected: 10 Reciproc Blue (RB25), 10 WaveOne Gold (WOG), 10 EdgeOne Fire (EOF) and 10 recently introduced instruments OneRECI (OR), for a total of 40 new instruments. Before root canal shaping, each instrument is mounted on a stub in a standardized position and observed using a scanning electron microscope (SEM) to detect any surface alteration, such as microfractures, metal defects, deformations, blunt and disruption of cutting edges, debris, pitting and tip flattening. Micrographs are acquired at the level of the tip, 4 mm, 8 mm and 12 mm from it. After that, each instrument is used in four simulated resin root canals. SEM observation was repeated after the simulated clinical use to assess the wear resistance of the instruments. Surface alterations are registered before and after instrumentation and statistical analysis is performed using a Chi-Square test to verify homogeneity of defects distribution and GLM to evaluate the differences of RMS at baseline and after use for both groups (α level 0.05). Before simulated clinical uses, no alterations are found except for three cases of EOF with metal strips in correspondence to the tip, disruption of the cutting edge of WOG and oily spotting on two different OR. After simulated clinical use, EOF shows a statistically significant difference in terms of spiral distortion and flattening of the cutting edges. The OR shows the highest presence of debris despite the ultrasonic cleaning procedures. No instrument fractures are observed. EOF should be discarded after four clinical uses and carefully inspected after each insertion into root canals. Moreover, tough attention should be paid during disinfection and cleaning procedures after instrumentation considering the copious debris detected in each instrument, particularly in OR.
Joint Communication–Motion Planning in Networked Robotic Systems
Authors: Zhang Zixuan , Zhang Bo , Wu Yunlong
Published: June 2022

In the recent decade, many research efforts in robotic society have considered motion planning for maintaining connectivity in networked robotic system (NRS) by exploiting robotic autonomous mobility. On the other hand, cognitive radio (CR) in the communication society aims at fully exploiting the spectrum in a wireless network, while the motion planning is seldom considered, as a wireless device itself may not decide where to go. In this article, joint communication–motion planning (JCMP) is proposed to boost the capability of NRS by exploiting both the adaptive communications and mobility control of autonomous robots. Specifically, we propose a JCMP framework for NRS, which aims at jointly exploiting the degree-of-freedom in mobility, space, time, frequency and power dimensions from both the motion and communication components. Afterward, we design and evaluate JCMP in a conventional and a CR-relay-assisted robot system, which shows the capability of JCMP in improving the performance of NRS. Finally, we summarize the proposed JCMP-enabled NRS framework and provide a series of future research directions.
A Novel CovidDetNet Deep Learning Model for Effective COVID-19 Infection Detection Using Chest Radiograph Images
Authors: Ullah Naeem , Khan Javed Ali , Almakdi Sultan , Khan Mohammad Sohail , Alshehri Mohammed , Alboaneen Dabiah , Raza Asaf
Published: June 2022

The suspected cases of COVID-19 must be detected quickly and accurately to avoid the transmission of COVID-19 on a large scale. Existing COVID-19 diagnostic tests are slow and take several hours to generate the required results. However, on the other hand, most X-rays or chest radiographs only take less than 15 min to complete. Therefore, we can utilize chest radiographs to create a solution for early and accurate COVID-19 detection and diagnosis to reduce COVID-19 patient treatment problems and save time. For this purpose, CovidDetNet is proposed, which comprises ten learnable layers that are nine convolutional layers and one fully-connected layer. The architecture uses two activation functions: the ReLu activation function and the Leaky Relu activation function and two normalization operations that are batch normalization and cross channel normalization, making it a novel COVID-19 detection model. It is a novel deep learning-based approach that automatically and reliably detects COVID-19 using chest radiograph images. Towards this, a fine-grained COVID-19 classification experiment is conducted to identify and classify chest radiograph images into normal, COVID-19 positive, and pneumonia. In addition, the performance of the proposed novel CovidDetNet deep learning model is evaluated on a standard COVID-19 Radiography Database. Moreover, we compared the performance of our approach with hybrid approaches in which we used deep learning models as feature extractors and support vector machines (SVM) as a classifier. Experimental results on the dataset showed the superiority of the proposed CovidDetNet model over the existing methods. The proposed CovidDetNet outperformed the baseline hybrid deep learning-based models by achieving a high accuracy of 98.40%.
Fuzzy Multi-Mode Time–Cost–Quality Trade-Off Optimization in Construction Management of Hydraulic Structure Projects
Authors: Mendomo Meye Serges , Li Guowei , Shen Zhenzhong , Zhang Jingbin
Published: June 2022

Along with the increased use of water resources, some large water conservancy projects began construction to address power supply shortages and control flooding and drainage. As investment grows, construction cycles lengthen, external environmental impacts become bigger, and civil engineering project management becomes more complex. The real aim of the hydraulic-structure engineering project model is to manage ways of delivering the project on time while maintaining reasonable quality standards and building costs, to optimize project value. We note that the trade-off between conflicting objectives in a water conservancy project in an uncertain environment is a difficult task. To simulate the relationship between a project’s construction quality and its time limit, two new piecewise functions—a double exponential function and a quadratic function—were proposed, and then a fuzzy multi-mode discrete time–cost–quality trade-off concept for water-management projects was established. This model finds the best solution to an NP-hard problem using the particle-swarm optimization algorithm (PSO). A comparison of the calculations to previous studies validates the model and its computational approach. The optimized results of a water conservation project are provided as a conceptual framework for project planning and construction timeframes.
An Automatic Foreign Matter Detection and Sorting System for PVC Powder
Authors: Chen Ssu-Han , Jang Jer-Huan , Chang Yu-Ru , Kang Chih-Hsiang , Chen Hung-Yi , Liu Kevin Fong-Rey , Lee Fong-Lin , Hsueh Yang-Shen , Youh Meng-Jey
Published: June 2022

In the present study, an automatic defect detection system has been assembled and introduced for Polyvinyl chloride (PVC) powder. The average diameter for PVC powder is approximately 100 μm. The system hardware includes a powder delivery device, a sieving device, a circular platform, an image capture device, and a recycling device. A defect detection algorithm based on YOLOv4 was developed using CSPDarkNet53 as the backbone for feature extraction, spatial pyramid pooling (SPP) and path aggregation network (PAN) as the neck, and Yoloblock as the head. An auto-annotation algorithm was developed based on a digital image processing algorithm to save time in feature engineering. Several hyper-parameters have been employed to improve the efficiency of detection in the process of training YOLOv4. The Taguchi method was utilized to optimize the performance of detection, in which the mean average precision (mAP) is the response. Results show that our optimized YOLOv4 has a test mAP of 0.9385, compared to 0.8653 and 0.7999 for naïve YOLOv4 and Faster RCNN, respectively. Additionally, with the optimized YOLOv4, there is no false alarm for images without any foreign matter.
Combining High-Resolution Hard X-ray Tomography and Histology for Stem Cell-Mediated Distraction Osteogenesis
Authors: Rodgers Griffin , Sigron Guido R. , Tanner Christine , Hieber Simone E. , Beckmann Felix , Schulz Georg , Scherberich Arnaud , Jaquiéry Claude , Kunz Christoph , Müller Bert
Published: June 2022

Distraction osteogenesis is a clinically established technique for lengthening, molding and shaping bone by new bone formation. The experimental evaluation of this expensive and time-consuming treatment is of high impact for better understanding of tissue engineering but mainly relies on a limited number of histological slices. These tissue slices contain two-dimensional information comprising only about one percent of the volume of interest. In order to analyze the soft and hard tissues of the entire jaw of a single rat in a multimodal assessment, we combined micro computed tomography (µCT) with histology. The µCT data acquired before and after decalcification were registered to determine the impact of decalcification on local tissue shrinkage. Identification of the location of the H&E-stained specimen within the synchrotron radiation-based µCT data collected after decalcification was achieved via non-rigid slice-to-volume registration. The resulting bi- and tri-variate histograms were divided into clusters related to anatomical features from bone and soft tissues, which allowed for a comparison of the approaches and resulted in the hypothesis that the combination of laboratory-based µCT before decalcification, synchrotron radiation-based µCT after decalcification and histology with hematoxylin-and-eosin staining could be used to discriminate between different types of collagen, key components of new bone formation.
UAV Application for Typhoon Damage Assessment in Construction Sites
Authors: Wang Chen , Tang Yutong , Kassem Mukhtar A. , Chen Zhenquan
Published: June 2022

The safety inspection capability of construction sites before typhoons could be improved using a UAV, which has a rapid identification capability. However, the main safety inspection items need construction experience and technical safety specifications. This study aimed to obtain the influencing factors of typhoon and their weight proportion through the knowledge of disaster theory and the analytic hierarchy process (AHP). The effectiveness of this method was verified by collecting and analyzing the field data at the construction site. A set of construction site early warning flows and disaster prevention and mitigation measures for typhoons are proposed. The results show that UAVs can be used as a tool in this scenario, helping to improve disaster prevention and enhancing the capability of construction site management to evaluate typhoon risk. The research provides a much-needed common ground for collecting and analyzing advances in UAVs and immersive technologies, as well as their influence on building projects. Furthermore, this article provides a new horizon for beginner researchers working on digitalized construction research.
Spin Polarization of Electrons in Two-Color XUV + Optical Photoionization of Atoms
Authors: Kabachnik Nikolay M. , Sazhina Irina P.
Published: June 2022

The spin polarization of photoelectrons in two-color XUV + optical multiphoton ionization is theoretically considered using strong field approximation. We assume that both the XUV and the optical radiation are circularly polarized. It is shown that the spin polarization is basically determined by the XUV photoabsorption and that the sidebands are spin polarized as well. Their polarization may be larger or smaller than that of the central photoelectron line depending on the helicity of the dressing field.
Dynamic Behaviors of an Obligate Commensal Symbiosis Model with Crowley–Martin Functional Responses
Authors: Xu Lili , Xue Yalong , Xie Xiangdong , Lin Qifa
Published: June 2022

A two species obligate commensal symbiosis model with Crowley–Martin functional response was proposed and studied in this paper. For an autonomous case, local and global dynamic behaviors of the system were investigated, respectively. The conditions that ensure the existence of the positive equilibrium is coincidentla to the conditions of global stability of a positive equilibrium. For nonautonomous cases, persistent and extinction properties of the system are investigated.
Bio-Assisted Synthesis and Characterization of Zinc Oxide Nanoparticles from Lepidium sativum and Their Potent Antioxidant, Antibacterial and Anticancer Activities
Authors: Meer Bisma , Andleeb Anisa , Iqbal Junaid , Ashraf Hajra , Meer Kushif , Ali Joham Sarfraz , Drouet Samantha , Anjum Sumaira , Mehmood Azra , Khan Taimoor , Ali Mohammad , Hano Christophe , Abbasi Bilal Haider
Published: June 2022

Nanotechnology is an emerging area of research that deals with the production, manipulation, and application of nanoscale materials. Bio-assisted synthesis is of particular interest nowadays, to overcome the limitations associated with the physical and chemical means. The aim of this study was to synthesize ZnO nanoparticles (NPs) for the first time, utilizing the seed extract of Lepidium sativum. The synthesized NPs were confirmed through various spectroscopy and imagining techniques, such as XRD, FTIR, HPLC, and SEM. The characterized NPs were then examined for various in vitro biological assays. Crystalline, hexagonal-structured NPs with an average particle size of 25.6 nm were obtained. Biosynthesized ZnO NPs exhibited potent antioxidant activities, effective α-amylase inhibition, moderate urease inhibition (56%), high lipase-inhibition (71%) activities, moderate cytotoxic potential, and significant antibacterial activity. Gene expression of caspase in HepG2 cells was enhanced along with elevated production of ROS/RNS, while membrane integrity was disturbed upon the exposure of NPs. Overall results indicated that bio-assisted ZnO NPs exhibit excellent biological potential and could be exploited for future biomedical applications. particularly in antimicrobial and cancer therapeutics. Moreover, this is the first comprehensive study on Lepidium sativum-mediated synthesis of ZnO nanoparticles and evaluation of their biological activities.
Clinical and Molecular Spectrum of Sporadic Vascular Malformations: A Single-Center Study
Authors: Diociaiuti Andrea , Rotunno Roberta , Pisaneschi Elisa , Cesario Claudia , Carnevale Claudia , Condorelli Angelo Giuseppe , Rollo Massimo , Di Cecca Stefano , Quintarelli Concetta , Novelli Antonio , Zambruno Giovanna , El Hachem May
Published: June 2022

Sporadic vascular malformations (VMs) are a large group of disorders of the blood and lymphatic vessels caused by somatic mutations in several genes—mainly regulating the RAS/MAPK/ERK and PI3K/AKT/mTOR pathways. We performed a cross-sectional study of 43 patients affected with sporadic VMs, who had received molecular diagnosis by high-depth targeted next-generation sequencing in our center. Clinical and imaging features were correlated with the sequence variants identified in lesional tissues. Six of nine patients with capillary malformation and overgrowth (CMO) carried the recurrent GNAQ somatic mutation p.Arg183Gln, while two had PIK3CA mutations. Unexpectedly, 8 of 11 cases of diffuse CM with overgrowth (DCMO) carried known PIK3CA mutations, and the remaining 3 had pathogenic GNA11 variants. Recurrent PIK3CA mutations were identified in the patients with megalencephaly–CM–polymicrogyria (MCAP), CLOVES, and Klippel–Trenaunay syndrome. Interestingly, PIK3CA somatic mutations were associated with hand/foot anomalies not only in MCAP and CLOVES, but also in CMO and DCMO. Two patients with blue rubber bleb nevus syndrome carried double somatic TEK mutations, two of which were previously undescribed. In addition, a novel sporadic case of Parkes Weber syndrome (PWS) due to an RASA1 mosaic pathogenic variant was described. Finally, a girl with a mild PWS and another diagnosed with CMO carried pathogenic KRAS somatic variants, showing the variability of phenotypic features associated with KRAS mutations. Overall, our findings expand the clinical and molecular spectrum of sporadic VMs, and show the relevance of genetic testing for accurate diagnosis and emerging targeted therapies.
Solid-Phase Synthesis of Red Fluorescent Carbon Dots for the Dual-Mode Detection of Hexavalent Chromium and Cell Imaging
Authors: Hu Jinshuang , Wang Xin , Wei Hua , Zhao Lei , Yao Boxuan , Zhang Caiyun , Zhou Jiarui , Liu Jian , Yang Shenghong
Published: June 2022

The excellent optical properties and biocompatibility of red fluorescence carbon dots (R-CDs) provide a new approach for the effective analysis of hexavalent chromium Cr(VI) in environmental and biological samples. However, the application of R-CDs is still limited by low yield and unfriendly synthesis route. In this study, we developed a new type of R-CDs based on a simple and green solid-phase preparation strategy. The synthesized R-CDs can emit bright red fluorescence with an emission wavelength of 625 nm and also have an obvious visible light absorption capacity. Furthermore, the absorption and fluorescence signals of the R-CDs aqueous solution are sensitive to Cr(VI), which is reflected in color change and fluorescence quenching. Based on that, a scanometric and fluorescent dual-mode analysis system for the rapid and accurate detection of Cr(VI) was established well within the limit of detection at 80 nM and 9.1 nM, respectively. The proposed methods also possess high specificity and were applied for the detection of Cr(VI) in real water samples. More importantly, the synthesized R-CDs with good biocompatibility were further successfully applied for visualizing intracellular Cr(VI) in Hela cells.
High Fundamental Frequency (HFF) Monolithic Quartz Crystal Microbalance with Dissipation Array for the Simultaneous Detection of Pesticides and Antibiotics in Complex Food
Authors: Calero María , Fernández Román , García María , Juan-Borrás Marisol , Escriche Isabel , Arnau Antonio , Montoya Ángel , Jiménez Yolanda
Published: June 2022

As in the case of the food industry in general, there is a global concern about safety and quality in complex food matrices, such as honey, which is driving the demand for fast, sensitive and affordable analytical techniques across the honey-packaging industry. Although excellent techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) are available, these are located in centralized laboratories and are still lacking in speed, simplicity and cost-effectiveness. Here, a new approach is presented where a competitive immunoassay is combined with a novel High Fundamental Frequency Quartz Crystal Microbalance with Dissipation (HFF-QCMD) array biosensor for the simultaneous detection of antibiotics and pesticides in honey. Concretely, thiabendazole and sulfathiazole residues were monitored in spiked honey samples. Results revealed that HFF-QCMD arrays provide a complementary and reliable tool to LC-MS/MS for the analysis of contaminants in these kinds of complex matrices, while avoiding elaborate sample pre-treatment. The good sensitivity achieved (I50 values in the 70–720 µg/kg range) and the short analysis time (60 min for 24 individual assays), together with the ability for multiple analyte detection (24 sensor array) and its cost-effectiveness, pave the way for the implementation of a fast on-line, in situ routine control of potentially hazardous chemical residues in honey.
Optimization of On-Street Parking in the Historical Heritage Part of Lviv (Ukraine) as a Prerequisite for Designing the IoT Smart Parking System
Authors: Zhou Chengjun , Petryshyn Halyna , Liubytskyi Roman , Kochan Orest
Published: June 2022

The city of Lviv faces a scarcity of parking lots, especially in its central zone. A comparison of the results of the in situ studies carried out in 2016 and 2021 in the city center showed the efficiency of the planning activities, due to which the number of on-street parking spaces increased by 72%, whereas the amount of on-street parking spaces in prohibited areas decreased by 32%. The extremely high demand shows that parking spaces in the city center should always be charged. It is reasonable to develop and implement a smart parking system compatible with the concept of the internet of things. In this case, drivers can get a real-time map of available parking spaces. The implementation of such a system should be preceded by a reasonable organization of the on-street parking zones. The high population density of Lviv and the development of urban subcenters require the expansion of the existing parking zones not only in the historic center but also in the remote areas of the city to balance the high demand for parking spaces and to ensure the sustainable development of the whole transport system.
Quality or Quantity? How Structural Parameters Affect Catalytic Activity of Iron Oxides for CO Oxidation
Authors: Schlicher Steffen , Prinz Nils , Bürger Julius , Omlor Andreas , Singer Christian , Zobel Mirijam , Schoch Roland , Lindner Jörg K. N. , Schünemann Volker , Kureti Sven , Bauer Matthias
Published: June 2022

The replacement of noble metal catalysts by abundant iron as an active compound in CO oxidation is of ecologic and economic interest. However, improvement of their catalytic performance to the same level as state-of-the-art noble metal catalysts requires an in depth understanding of their working principle on an atomic level. As a contribution to this aim, a series of iron oxide catalysts with varying Fe loadings from 1 to 20 wt% immobilized on a γ-Al2O3 support is presented here, and a multidimensional structure–activity correlation is established. The CO oxidation activity is correlated to structural details obtained by various spectroscopic, diffraction, and microscopic methods, such as PXRD, PDF analysis, DRUVS, Mössbauer spectroscopy, STEM-EDX, and XAS. Low Fe loadings lead to less agglomerated but high percentual amounts of isolated, tetrahedrally coordinated iron oxide species, while the absolute amount of isolated species reaches its maximum at high Fe loadings. Consequently, the highest CO oxidation activity in terms of turnover frequencies can be correlated to small, finely dispersed iron oxide species with a large amount of tetrahedrally oxygen coordinated iron sites, while the overall amount of isolated iron oxide species correlates with a lower light-off temperature.
Transcriptional Profiling of Insulin-like Growth Factor Signaling Components in Embryonic Lung Development and Idiopathic Pulmonary Fibrosis
Authors: Kheirollahi Vahid , Khadim Ali , Kiliaris Georgios , Korfei Martina , Barroso Margarida Maria , Alexopoulos Ioannis , Vazquez-Armendariz Ana Ivonne , Wygrecka Malgorzata , Ruppert Clemens , Guenther Andreas , Seeger Werner , Herold Susanne , El Agha Elie
Published: June 2022

Insulin-like growth factor (IGF) signaling controls the development and growth of many organs, including the lung. Loss of function of Igf1 or its receptor Igf1r impairs lung development and leads to neonatal respiratory distress in mice. Although many components of the IGF signaling pathway have shown to be dysregulated in idiopathic pulmonary fibrosis (IPF), the expression pattern of such components in different cellular compartments of the developing and/or fibrotic lung has been elusive. In this study, we provide a comprehensive transcriptional profile for such signaling components during embryonic lung development in mice, bleomycin-induced pulmonary fibrosis in mice and in human IPF lung explants. During late gestation, we found that Igf1 is upregulated in parallel to Igf1r downregulation in the lung mesenchyme. Lung tissues derived from bleomycin-treated mice and explanted IPF lungs revealed upregulation of IGF1 in parallel to downregulation of IGF1R, in addition to upregulation of several IGF binding proteins (IGFBPs) in lung fibrosis. Finally, treatment of IPF lung fibroblasts with recombinant IGF1 led to myogenic differentiation. Our data serve as a resource for the transcriptional profile of IGF signaling components and warrant further research on the involvement of this pathway in both lung development and pulmonary disease.
Fundamental and Applied Advances in Stem Cell Therapeutic Research
Authors: Merimi Makram , Rahmani Saida , Afailal Tribak Ahmed , Bouhtit Fatima , Fahmi Hassan , Najar Mehdi
Published: June 2022

We are pleased to present this Special Issue of Cells, entitled ‘Feature Papers in Stem Cells’ [...]
The Good and the Bad: Monocytes’ and Macrophages’ Diverse Functions in Inflammation
Authors: Austermann Judith , Roth Johannes , Barczyk-Kahlert Katarzyna
Published: June 2022

Monocytes and macrophages are central players of the innate immune response and play a pivotal role in the regulation of inflammation. Thereby, they actively participate in all phases of the immune response, from initiating inflammation and triggering the adaptive immune response, through to the clearance of cell debris and resolution of inflammation. In this review, we described the mechanisms of monocyte and macrophage adaptation to rapidly changing microenvironmental conditions and discussed different forms of macrophage polarization depending on the environmental cues or pathophysiological condition. Therefore, special focus was placed on the tight regulation of the pro- and anti-inflammatory immune response, and the diverse functions of S100A8/S100A9 proteins and the scavenger receptor CD163 were highlighted, respectively. We paid special attention to the function of pro- and anti-inflammatory macrophages under pathological conditions.
Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia
Authors: Damtew Addisu , Teferi Ermias , Ongoma Victor , Mumo Richard , Esayas Befikadu
Published: June 2022

The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p < 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.
Poly(2-Methoxyethyl Acrylate) (PMEA)-Coated Anti-Platelet Adhesive Surfaces to Mimic Native Blood Vessels through HUVECs Attachment, Migration, and Monolayer Formation
Authors: Haque Md Azizul , Murakami Daiki , Anada Takahisa , Tanaka Masaru
Published: June 2022

Confluent monolayers of human umbilical vein endothelial cells (HUVECs) on a poly(2-methoxyethyl acrylate) (PMEA) antithrombogenic surface play a major role in mimicking the inner surface of native blood vessels. In this study, we extensively investigated the behavior of cell–polymer and cell–cell interactions by measuring adhesion strength using single-cell force spectroscopy. In addition, the attachment and migration of HUVECs on PMEA-analogous substrates were detected, and the migration rate was estimated. Moreover, the bilateral migration of HUVECs between two adjacent surfaces was observed. Furthermore, the outer surface of HUVEC was examined using frequency-modulation atomic force microscopy (FM-AFM). Hydration was found to be an indication of a healthy glycocalyx layer. The results were compared with the hydration states of individual PMEA-analogous polymers to understand the adhesion mechanism between the cells and substrates in the interface region. HUVECs could attach and spread on the PMEA surface with stronger adhesion strength than self-adhesion strength, and migration occurred over the surface of analogue polymers. We confirmed that platelets could not adhere to HUVEC monolayers cultured on the PMEA surface. FM-AFM images revealed a hydration layer on the HUVEC surfaces, indicating the presence of components of the glycocalyx layer in the presence of intermediate water. Our findings show that PMEA can mimic original blood vessels through an antithrombogenic HUVEC monolayer and is thus suitable for the construction of artificial small-diameter blood vessels.
Computer Vision-Based Inspection System for Worker Training in Build and Construction Industry
Authors: Ercan M. Fikret , Wang Ricky Ben
Published: June 2022

Recently computer vision has been applied in various fields of engineering successfully ranging from manufacturing to autonomous cars. A key player in this development is the achievements of the latest object detection and classification architectures. In this study, we utilized computer vision and the latest object detection techniques for an automated assessment system. It is developed to reduce the person-hours involved in worker training assessment. In our local building and construction industry, workers are required to be certificated for their technical skills in order to qualify working in this industry. For the qualification, they are required to go through a training and assessment process. During the assessment, trainees implement an assembly such as electrical wiring and wall-trunking by referring to technical drawings provided. Trainees’ work quality and correctness are then examined by a team of experts manually and visually, which is a time-consuming process. The system described in this paper aims to automate the assessment process to reduce the significant person-hours required during the assessment. We employed computer vision techniques to measure the dimensions, orientation, and position of the wall assembly produced hence speeding up the assessment process. A number of key parts and components are analyzed and their discrepancies from the technical drawing are reported as the assessment result. The performance of the developed system depends on the accurate detection of the wall assembly objects and their corner points. Corner points are used as reference points for the measurements, considering the shape of objects, in this particular application. However, conventional corner detection algorithms are founded upon pixel-based operations and they return many redundant or false corner points. In this study, we employed a hybrid approach using deep learning and conventional corner detection algorithms. Deep learning is employed to detect the whereabouts of objects as well as their reference corner points in the image. We then perform a search within these locations for potential corner points returned from the conventional corner detector algorithm. This approach resulted in highly accurate detection of reference points for measurements and evaluation of the assembly.
MCRS1 Expression Regulates Tumor Activity and Affects Survival Probability of Patients with Gastric Cancer
Authors: Wang Liang-Han , Chang Chih-Chun , Cheng Chiao-Yin , Liang Yao-Jen , Pei Dee , Sun Jen-Tang , Chen Yen-Lin
Published: June 2022

Gastric cancer is the fifth most common cancer worldwide and the third most common cause of cancer-related deaths. Surgery remains the first-choice treatment. Chemotherapy is considered in the middle and advanced stages, but has limited success. Microspherule protein 1 (MCRS1, also known as MSP58) is a protein originally identified in the nucleus and cytoplasm that is involved in the cell cycle. High expression of MCRS1 increases tumor growth, invasiveness, and metastasis. The mechanistic relationships between MCSR1 and proliferation, apoptosis, angiogenesis, and epithelial–mesenchymal transition (EMT) remain to be elucidated. We clarified these relationships using immunostaining of tumor tissues and normal tissues from patients with gastric cancer. High MCRS1 expression in gastric cancer positively correlated with Ki-67, Caspase3, CD31, Fibronectin, pAKT, and pAMPK. The hazard ratio of high MCRS1 expression was 2.44 times that of low MCRS1 expression, negatively impacting patient survival.
COVID-19 Underreporting in Brazil among Patients with Severe Acute Respiratory Syndrome during the Pandemic: An Ecological Study
Authors: Lima Tainá Momesso , Palamim Camila Vantini Capasso , Melani Vitória Franchini , Mendes Matheus Ferreira , Pereira Letícia Rojina , Marson Fernando Augusto Lima
Published: June 2022

Underreporting of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is a global problem and might hamper Coronavirus Disease (COVID-19) epidemiological control. Taking this into consideration, we estimated possible SARS-CoV-2 infection underreporting in Brazil among patients with severe acute respiratory syndrome (SARS). An ecological study using a descriptive analysis of the SARS report was carried out based on data supplied by the Influenza Epidemiological Surveillance Information (SIVEP)-Flu (in Brazilian Portuguese, Sistema de Vigilância Epidemiológica da Gripe) in the period between January 2015 and March 2021. The number of SARS cases and related deaths after infection by SARS-CoV-2 or Influenzae was described. The estimation of underreporting was evaluated considering the relative increase in the number of cases with undefined etiological agent comparing 2020 to 2015–2019; and descriptive analysis was carried out including data from January–March/2021. In our data, SARS-CoV-2 infection and the presence of SARS with undefined etiological agent were associated with the higher number of cases and deaths from SARS in 2020/2021. SARS upsurge was six times over that expected in 2020, according to SARS seasonality in previous years (2015–2019). The lowest possible underdiagnosis rate was observed in the age group < 2 y.o. and individuals over 30 y.o., with ~50%; while in the age groups 10–19 and 20–29 y.o., the rates were 200–250% and 100%, respectively. For the remaining age groups (2–5 and 5–9 y.o.) underreporting was over 550%, except for female individuals in the age group 2–5 y.o., in which a ~500% rate was found. Our study described that the SARS-CoV-2 infection underreporting rate in Brazil in SARS patients is alarming and presents different indices, mainly associated with the patients’ age groups. Our results, mainly the underreporting index according to sex and age, should be evaluated with caution.
Reliable Semantic Communication System Enabled by Knowledge Graph
Authors: Jiang Shengteng , Liu Yueling , Zhang Yichi , Luo Peng , Cao Kuo , Xiong Jun , Zhao Haitao , Wei Jibo
Published: June 2022

Semantic communication is a promising technology used to overcome the challenges of large bandwidth and power requirements caused by the data explosion. Semantic representation is an important issue in semantic communication. The knowledge graph, powered by deep learning, can improve the accuracy of semantic representation while removing semantic ambiguity. Therefore, we propose a semantic communication system based on the knowledge graph. Specifically, in our system, the transmitted sentences are converted into triplets by using the knowledge graph. Triplets can be viewed as basic semantic symbols for semantic extraction and restoration and can be sorted based on semantic importance. Moreover, the proposed communication system adaptively adjusts the transmitted contents according to channel quality and allocates more transmission resources to important triplets to enhance communication reliability. Simulation results show that the proposed system significantly enhances the reliability of the communication in the low signal-to-noise regime compared to the traditional schemes.
A Piecewise Linear Mitchell Algorithm-Based Approximate Multiplier
Authors: Liu Hao , Wang Mingjiang , Yao Longxin , Liu Ming
Published: June 2022

In the field of integrated circuits, the computational cost has always been a crucial design metric. In recent years, with the continuous development in the field of computing, the requirements for computation have been growing rapidly. Reducing the computational cost and improving computational efficiency have become the key issues in the field. There are many error-tolerant applications in the multimedia field where approximate computing techniques can be applied to improve computational efficiency and reduce computational costs at the cost of acceptable computational errors. This paper proposed a piecewise linear Mitchell algorithm based on Mitchell logarithmic approximation multiplication algorithm. Additionally, the Pwl-Mit multiplier is designed according to the improved algorithm combined with the data truncation technique. The proposed approximate multiplier has better statistical performance compared with the state-of-the-art multipliers. The design is simulated and synthesized at the TSMC 65 nm process, and its reliability is verified using discrete cosine transform (DCT) transform.
An Effective Deep Learning-Based Architecture for Prediction of N7-Methylguanosine Sites in Health Systems
Authors: Tahir Muhammad , Hayat Maqsood , Khan Rahim , Chong Kil To
Published: June 2022

N7-methylguanosine (m7G) is one of the most important epigenetic modifications found in rRNA, mRNA, and tRNA, and performs a promising role in gene expression regulation. Owing to its significance, well-equipped traditional laboratory-based techniques have been performed for the identification of N7-methylguanosine (m7G). Consequently, these approaches were found to be time-consuming and cost-ineffective. To move on from these traditional approaches to predict N7-methylguanosine sites with high precision, the concept of artificial intelligence has been adopted. In this study, an intelligent computational model called N7-methylguanosine-Long short-term memory (m7G-LSTM) is introduced for the prediction of N7-methylguanosine sites. One-hot encoding and word2vec feature schemes are used to express the biological sequences while the LSTM and CNN algorithms have been employed for classification. The proposed “m7G-LSTM” model obtained an accuracy value of 95.95%, a specificity value of 95.94%, a sensitivity value of 95.97%, and Matthew’s correlation coefficient (MCC) value of 0.919. The proposed predictive m7G-LSTM model has significantly achieved better outcomes than previous models in terms of all evaluation parameters. The proposed m7G-LSTM computational system aims to support the drug industry and help researchers in the fields of bioinformatics to enhance innovation for the prediction of the behavior of N7-methylguanosine sites.
Research on Braking Efficiency of Master-Slave Electro-Hydraulic Hybrid Electric Vehicle
Authors: Wang Junyi , Zhang Tiezhu , Zhang Hongxin , Yang Jian , Zhang Zhen , Meng Zewen
Published: June 2022

To address the problems of short-rangee and poor braking safety of electric vehicles, this paper proposes a master-slave electro-hydraulic hybrid passenger car drive system based on planetary gear. The system couples the electrical energy output from the electric motor with the hydraulic energy output from the electro-hydraulic pump/motor through the planetary gear. The hydraulic system is used as the auxiliary power source of the power system giving full play to the advantages of the hydraulic system and the electric system. After theoretical analysis, this paper establishes a master-slave electro-hydraulic hybrid electric vehicle (MSEHH-EV) model based on planetary gear in AMESim software. A braking energy recovery control strategy is designed with the maximum braking energy recovery efficiency as the target. Braking strength determines the switching of braking modes. Finally, comparing the certified pure electric vehicle (EV) model in AMESim, we are able to substantiate the superiority of the strategy proposed in this paper. The simulation results revealed that the battery consumption rate of the new power vehicle is reduced by 17.766%, 11.358%, and 9.427% under UDDS, NEDC, and WLTC conditions, respectively, which supports the range. At the same time, the braking distance is significantly shortened, and the maximum braking distance is shortened by 15.65 m, 21.97 m, and 21.45 m, respectively, under the three operating conditions, which improves the braking safety.
Antimonotonicity, Hysteresis and Coexisting Attractors in a Shinriki Circuit with a Physical Memristor as a Nonlinear Resistor
Authors: Laskaridis Lazaros , Volos Christos , Stouboulos Ioannis
Published: June 2022

A novel approach to the physical memristor’s behavior of the KNOWM is presented in this work. The KNOWM’s memristor’s intrinsic feature encourages its use as a nonlinear resistor in chaotic circuits. Furthermore, this memristor has been shown to act like a static nonlinear resistor under certain situations. Consequently, for the first time, the KNOWM memristor is used as a static nonlinear resistor in the well-known chaotic Shinriki oscillator. In order to examine the circuit’s dynamical behavior, a host of nonlinear simulation tools, such as phase portraits, bifurcation and continuation diagrams, as well as a maximal Lyapunov exponent diagram, are used. Interesting phenomena related to chaos theory are observed. More specifically, the entrance to chaotic behavior through the antimonotonicity phenomenon is observed. Furthermore, the hysteresis phenomenon, as well as the existence of coexisting attractors in regards to the initial conditions and the parameters of the system, are investigated. Moreover, the period-doubling route to chaos and crisis phenomena are observed too.
Analysis of Impact of Design Solutions of an Electric Machine with Permanent Magnets for Bearing Voltages with Inverter Power Supply
Authors: Berhausen Sebastian , Jarek Tomasz
Published: June 2022

The aim of the article is to present a new idea of limiting the bearing voltage in electric machines with permanent magnets through the use of a shielding winding placed in stator slot wedges. The first part of the article is dedicated to the mechanisms of generating bearing voltages when the machine is supplied from the mains and from a power electronic converter. Additionally, some methods of counteracting these phenomena were described. Next, multivariant simulation tests were carried out based on the two-dimensional field model of a synchronous machine with permanent magnets. The tests were run in order to determine the internal capacitances of the machine, on which the level of bearing voltages depends. Based on these results, the optimal variant of the design solution ensuring the limitation of the bearing voltage to a safe level was selected. Using the model of a two-level converter and based on the equivalent diagram of the internal capacitances of the machine, the influence of the proposed shielding winding on the bearing voltage was estimated.
Modelling Study of Cycle-To-Cycle Variations (CCV) in Spark Ignition (SI)-Controlled Auto-Ignition (CAI) Hybrid Combustion Engine by Using Reynolds-Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES)
Authors: Wang Xinyan , Zhao Hua
Published: June 2022

The spark ignition (SI)-controlled auto-ignition (CAI) hybrid combustion is characterized by early flame propagation combustion and subsequent auto-ignition combustion. The application of combined SI–CAI hybrid combustion can be used to effectively extend the operating range of CAI combustion and achieve smooth transitions between SI and CAI combustion modes. However, SI–CAI hybrid combustion can produce significant cycle-to-cycle variations (CCV). In order to better understand the sources of CCV and minimize its occurrence, the large eddy simulation (LES) and Reynolds-averaged Navier–Stokes (RANS) approaches were employed in this study to model and understand the cyclic phenomenon of SI–CAI hybrid combustion. Both the multi-cycle LES and RANS simulations were analyzed against the experimental measurements in a single cylinder engine at 1500 rpm and a 5.43 bar average indicated the mean effective pressure (IMEP). The detailed analysis of the in-cylinder pressure traces, IMEP, in-cylinder peak pressure (PP), peak pressure rise rate (PPRR) and the crank angles with fuel mass burned fraction at 10%, 50%, 90% and mode transition was performed. The results indicate that overall, the adopted LES simulations could effectively predict the cyclic variations in the hybrid combustion observed in the experiments, while the RANS simulations failed to reproduce the cyclic characteristics at the chosen engine operating conditions. Based on the LES results, the correlation and visualization studies indicate that the cyclic variations in the local velocity around the spark plug lead to the variations in the early flame propagation, which in turn produce temperature fluctuations among the cycles and result in greater variations in the subsequent auto-ignition combustion events.