bluuebunny/crossref_metadata_2025 huggingface dataset:
Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles
Authors: Alanazi Fayez , Alenezi Mamdouh
Published: July 2023

As the process of urbanization continues to accelerate, the demand for sustainable cities has become more critical than ever before. The incorporation of electric vehicles (EVs) is a key component in creating sustainable cities. However, the development of smart cities for EVs entails more than just the installation of charging stations. Software engineering plays a crucial role in realizing smart cities for electric vehicles. This paper examines the role of software engineering in the creation of smart cities for electric vehicles, the techniques utilized in electric vehicle charging infrastructure, the obstacles faced by software engineers, and the future of software engineering in sustainable cities. Specifically, the paper explores the significance of software engineering in integrating EVs into the transportation system, including the design of smart charging and energy management systems, and the establishment of intelligent transportation systems. Additionally, the paper offers case studies to demonstrate successful software engineering implementations for smart cities. Finally, the paper concludes with a discussion of the challenges that software engineers encounter in implementing intelligent transportation systems for EVs and provides future directions for software engineering in sustainable cities.
GTMesh: A Highly Efficient C++ Template Library for Numerical Schemes on General Topology Meshes
Authors: Jakubec Tomáš , Strachota Pavel
Published: July 2023

This article introduces GTMesh, an open-source C++ library providing data structures and algorithms that facilitate the development of numerical schemes on general polytopal meshes. After discussing the features and limitations of the existing open-source alternatives, we focus on the theoretical description of geometry and the topology of conforming polytopal meshes in an arbitrary-dimensional space, using elements from graph theory. The data structure for mesh representation is explained. The main part of the article focuses on the implementation of data structures and algorithms (computation of measures, centers, normals, cell coloring) by using State-of-the-Art template metaprogramming techniques for maximum performance. The geometrical algorithms are designed to be valid regardless of the dimension of the underlying space. As an integral part of the library, a template implementation of class reflection in C++ has been created, which is sufficiently versatile and suitable for the development of numerical and data I/O algorithms working with generic data types. Finally, the use of GTMesh is demonstrated on a simple example of solving the heat equation by the finite volume method.
Full-Reference Image Quality Assessment Based on Multi-Channel Visual Information Fusion
Authors: Jiang Benchi , Bian Shilei , Shi Chenyang , Wu Lulu
Published: July 2023

This study focuses on improving the objective alignment of image quality assessment (IQA) algorithms with human visual perception. Existing methodologies, predominantly those based on the Laplacian of Gaussian (LoG) filter, often neglect the impact of color channels on human visual perception. Consequently, we propose a full-reference IQA method that integrates multi-channel visual information in color images. The methodology begins with converting red, green, blue (RGB) images into the luminance (L), red–green opponent color channel (M), blue–yellow opponent color channel (N) or LMN color space. Subsequently, the LoG filter is separately applied to the L, M, and N channels. The convoluted components are then fused to generate a contrast similarity map using the root-mean-square method, while the chromaticity similarity map is derived from the color channels. Finally, multi-channel LoG filtering, contrast, and chromaticity image features are connected. The standard deviation method is then used for sum pooling to create a full-reference IQA computational method. To validate the proposed method, distorted images from four widely used image databases were tested. The evaluation, based on four criteria, focused on the method’s prediction accuracy, computational complexity, and generalizability. The Pearson linear correlation coefficient (PLCC) values, recorded from the databases, ranged from 0.8822 (TID2013) to 0.9754 (LIVE). Similarly, the Spearman rank-order correlation coefficient (SROCC) values spanned from 0.8606 (TID2013) to 0.9798 (LIVE). In comparison to existing methods, the proposed IQA method exhibited superior visual correlation prediction accuracy, indicating its promising potential in the field of image quality assessment.
HBTBD: A Heterogeneous Bitcoin Transaction Behavior Dataset for Anti-Money Laundering
Authors: Song Jialin , Gu Yijun
Published: July 2023

In this paper, we predict money laundering in Bitcoin transactions by leveraging a deep learning framework and incorporating more characteristics of Bitcoin transactions. We produced a dataset containing 46,045 Bitcoin transaction entities and 319,311 Bitcoin wallet addresses associated with them. We aggregated this information to form a heterogeneous graph dataset and propose three metapath representations around transaction entities, which enrich the characteristics of Bitcoin transactions. Then, we designed a metapath encoder and integrated it into a heterogeneous graph node embedding method. The experimental results indicate that our proposed framework significantly improves the accuracy of illicit Bitcoin transaction recognition compared with traditional methods. Therefore, our proposed framework is more conducive in detecting money laundering activities in Bitcoin transactions.
Analysis of Dynamic Characteristics of Attached High Rise Risers
Authors: Zhang Linghao , Han Mingjiang , Zhang Qichang , Hao Shuying , Zhen Jianwei
Published: July 2023

The exhaust chimney of third-generation nuclear power units is a typical attached high-rise riser structure. In this paper, the simplified mechanical model and dynamic model of China’s third-generation nuclear power Hualong-1 VNA system, including multiple nonlinear factors, are established for the first time. The DTM (differential transformation method) was first applied to solve the natural vibration characteristics of a multi-point constrained variable cross-section riser structure, and the effects of variable cross-section, variable mass, variable axial force, and different elastic constraint parameters on the natural vibration characteristics of the system were studied. The dynamic behavior of the VNA system under the combined action of internal flow velocity, vortex excitation, and foundation excitation was studied. The results show that the outer diameter function of the VNA system pipeline should be designed as a quadratic function or a near quadratic multi-segment constant value function. The “limiting” effect of constraining large stiffness can force low-order vibration modes with high constraint stiffness to jump to high-order vibration modes with low constraint stiffness. The elastic constraint arrangement scheme with near center symmetry can make the system vibration mode present a half stable and half-curved form. A new optimization design scheme has been proposed regarding the layout and stiffness parameters of the VNA system guide bracket. This can enable the VNA system pipeline to avoid severe oscillations near the response extreme values caused by multiple frequency excitations of seismic loads under design and accident conditions and ensure the service life of the equipment.
Evaluation of Glottal Inverse Filtering Techniques on OPENGLOT Synthetic Male and Female Vowels
Authors: Freixes Marc , Joglar-Ongay Luis , Socoró Joan Claudi , Alías-Pujol Francesc
Published: July 2023

Current articulatory-based three-dimensional source–filter models, which allow the production of vowels and diphtongs, still present very limited expressiveness. Glottal inverse filtering (GIF) techniques can become instrumental to identify specific characteristics of both the glottal source signal and the vocal tract transfer function to resemble expressive speech. Several GIF methods have been proposed in the literature; however, their comparison becomes difficult due to the lack of common and exhaustive experimental settings. In this work, first, a two-phase analysis methodology for the comparison of GIF techniques based on a reference dataset is introduced. Next, state-of-the-art GIF techniques based on iterative adaptive inverse filtering (IAIF) and quasi closed phase (QCP) approaches are thoroughly evaluated on OPENGLOT, an open database specifically designed to evaluate GIF, computing well-established GIF error measures after extending male vowels with their female counterparts. The results show that GIF methods obtain better results on male vowels. The QCP-based techniques significantly outperform IAIF-based methods for almost all error metrics and scenarios and are, at the same time, more stable across sex, phonation type, F0, and vowels. The IAIF variants improve the original technique for most error metrics on male vowels, while QCP with spectral tilt compensation achieves a lower spectral tilt error for male vowels than the original QCP.
Reliability Investigation of Pavement Performance Evaluation Based on Blind-Number Theory: A Confidence Model
Authors: Wei Hui , Liu Yunyao , Li Jue , Liu Lihao , Liu Honglin
Published: July 2023

The evaluation of in-service pavements’ performance is a complex system that encompasses a variety of uncertain factors. These uncertainties include random, fuzzy, gray, and unascertained information, and their interrelationships are intricate, making comprehensive quantification unachievable. Nonetheless, current highway management organizations rely on a comprehensive indicator, namely, the Pavement Quality Index (PQI), to assess the level of pavement performance. This paper introduces a novel approach that employs blind number theory to evaluate the reliability of pavement performance test data. The proposed method aims to enhance the representativeness of PQI and is demonstrated using detection data from highway asphalt pavements in Hunan Province. The method takes into account the probability distribution characteristics of evaluation metrics and incorporates the blind number representation format of PQI. A confidence model for pavement performance evaluation is established to assess the reliability of pavement detection results. The method also integrates expert empowerment and entropy weight to consider both the subjectivity of evaluation and the objectivity of measured data. The method presented in this study has demonstrated superior performance compared to traditional evaluation index systems. This is attributed to the effective utilization of blind information to accurately characterize the discreteness of pavement performance indexes. Consequently, pavement performance can be quantitatively graded based on anticipated issues and data.
3D City Reconstruction: A Novel Method for Semantic Segmentation and Building Monomer Construction Using Oblique Photography
Authors: Xu Wenqiang , Zeng Yongnian , Yin Changlin
Published: July 2023

Existing 3D city reconstruction via oblique photography can only produce surface models, lacking semantic information about the urban environment and the ability to incorporate all individual buildings. Here, we propose a method for the semantic segmentation of 3D model data from oblique photography and for building monomer construction and implementation. Mesh data were converted into and mapped as point sets clustered to form superpoint sets via rough geometric segmentation, facilitating subsequent feature extractions. In the local neighborhood computation of semantic segmentation, a neighborhood search method based on geodesic distances, improved the rationality of the neighborhood. In addition, feature information was retained via the superpoint sets. Considering the practical requirements of large-scale 3D datasets, this study offers a robust and efficient segmentation method that combines traditional random forest and Markov random field models to segment 3D scene semantics. To address the need for modeling individual and unique buildings, our methodology utilized 3D mesh data of buildings as a data source for specific contour extraction. Model monomer construction and building contour extractions were based on mesh model slices and assessments of geometric similarity, which allowed the simultaneous and automatic achievement of these two processes.
A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach
Authors: Bhanbhro Hina , Kwang Hooi Yew , Kusakunniran Worapan , Amur Zaira Hassan
Published: July 2023

In numerous electrical power distribution systems and other engineering contexts, single-line diagrams (SLDs) are frequently used. The importance of digitizing these images is growing. This is primarily because better engineering practices are required in areas such as equipment maintenance, asset management, safety, and others. Processing and analyzing these drawings, however, is a difficult job. With enough annotated training data, deep neural networks perform better in many object detection applications. Based on deep-learning techniques, a dataset can be used to assess the overall quality of a visual system. Unfortunately, there are no such datasets for single-line diagrams available to the general research community. To augment real image datasets, generative adversarial networks (GANs) can be used to create a variety of more realistic training images. The goal of this study was to explain how deep-convolutional-GAN- (DCGAN) and least-squares-GAN- (LSGAN) generated images are evaluated for quality. In order to improve the datasets and confirm the effectiveness of synthetic datasets, our work blended synthetic images with actual images. Additionally, we added synthetic images to the original picture collection to prepare an augmented dataset for symbol detection. In this scenario, we employed You Look Only Once (YOLO) V5, one of the versions of YOLO. The recognition performance was improved, reaching an accuracy of 95% with YOLO V5, after combining the actual images with the synthetic images created by the DCGAN and LSGAN. By incorporating synthetic samples into the dataset, the overall quality of the training data was improved, and the learning process for the model became simpler. Furthermore, the proposed method significantly improved symbol detection in SLDs, according to the findings of the experiments.
Design, Modelling, and Analysis of a Capacitive Reservoir Based PWM Digital Circuit of Electro-Hydraulic Proportional Valve
Authors: Liu Xin , Yang Xu , Li Shizhen , Liang Dong
Published: July 2023

The high-speed and high-accuracy current control circuit is a key component for the high-performance electro-hydraulic proportional valve. In this paper, a new capacitive reservoir-based PWM digital circuit (CRPDC) is designed, modeled, and analyzed. The proposed CRPDC employs a capacitive reservoir circuit to acquire electricity from the DC power supply while the PWM control signal is at a high level and the supply current for the proportional valve coil while the PWM control signal is at a low level, which will result in a small ripple and fast response of the coil current. For the proposed CRPDC, the charging and discharging mathematical models are specially established to reveal the response characteristics of the proportional-valve coil current. The coil current control performance of the proposed CRPDC is simulated by the mathematical models and the Multisim models. Simulation results demonstrate that the designed CRPDC can energize the coil current in a high-accuracy and fast-speed manner. In summary, the designed CRPDC has wide application in the current control of the proportional valve coil.
Nonlinear Optical Microscopy of Interface Layers of Epitaxial Garnet Films
Authors: Maydykovskiy Anton , Temiryazeva Marina , Temiryazev Alexey , Murzina Tatiana
Published: July 2023

The structure of magnetic domains is an exciting research object that shows an enormous variety of delightful patterns. Epitaxial garnet is one of the most studied magnetic dielectrics with well-recognized bulk domains, while the magnetic composition at the surface is less investigated. Here we apply the nonlinear optical microscopy technique for the visualization of the interface magnetic domains of 10 μm thick (LuBi)3Fe5O12 film and prove that it is qualitatively similar for both garnet/air and garnet/substrate interfaces. As an efficient extension of the second harmonic generation microscopy, we suggest and demonstrate the possibilities of the third harmonic generation one, which provides higher resolution of the method.
The Teaching Application of the Backward Design Method in Chinese National Undergraduate Engineering Training Integration Ability Competition: Take the Double 8 Carbon-Free Car as an Example
Authors: Ma Xueting , Wang Xufeng , Zhang Hong , Li Hong
Published: July 2023

National Undergraduate Engineering Training Integration Ability Competition is essential in Chinese engineering colleges. Among these items, the carbon-free car competition is popular among college students because of its flexible track, challenging design tasks, and fair judging criteria. In this study, to design a reasonable carbon-free car structure according to the track given by the competition, a reverse analysis method was proposed for the double 8-shaped carbon-free car trajectory based on the space cam mechanism. First, the carbon-free car’s structure was designed, and its stress state was analyzed, with the results indicating that the driving force should be reduced as much as possible under the premise of satisfying the starting requirements to increase the travel distance of the carbon-free car with no slipping. Then, the function between the car track and the front wheel swing angle was established, and the displacement law of the push rod of the cam mechanism was calculated through the swing angle of the front wheel. Finally, the cam profile was got based on the operating law of the push rod. Research has shown that compared with the traditional forward design, this method was more accurate with strong feasibility and operability, which provided good technical support for designing the subsequent carbon-free car competition.
Innovative Attention-Based Explainable Feature-Fusion VGG19 Network for Characterising Myocardial Perfusion Imaging SPECT Polar Maps in Patients with Suspected Coronary Artery Disease
Authors: Apostolopoulos Ioannis D. , Papathanasiou Nikolaοs D. , Papandrianos Nikolaos , Papageorgiou Elpiniki , Apostolopoulos Dimitris J.
Published: July 2023

Greece is among the European Union members topping the list of deaths related to coronary artery disease. Myocardial Perfusion Imaging (MPI) with Single-Photon Emission Computed Tomography (SPECT) is a non-invasive test used to detect abnormalities in CAD screening. The study proposes an explainable deep learning (DL) method for characterising MPI SPECT Polar Map images in patients with suspected CAD. Patient data were recorded at the Department of Nuclear Medicine of the University Hospital of Patras from 16 February 2018 to 28 February 2022. The final study population included 486 patients. An attention-based feature-fusion network (AFF-VGG19) was proposed to perform the diagnosis, and the Grad-CAM++ algorithm was employed to reveal potentially significant regions. AFF-VGG19’s agreement with the medical experts was found to be 89.92%. When training and assessing using the ICA findings as a reference, AFF-VGG19 achieved good diagnostic strength (accuracy of 0.789) similar to that of the human expert (0.784) and with more balanced sensitivity and specificity rates (0.873 and 0.722, respectively) compared to the human expert (0.958 and 0.648, respectively). The visual inspection of the Grad-CAM++ regions showed that the model produced 77 meaningful explanations over the 100 selected samples, resulting in a slight accuracy decrease (0.77). In conclusion, this research introduced a novel and interpretable DL approach for characterising MPI SPECT Polar Map images in patients with suspected CAD. The high agreement with medical experts, robust diagnostic performance, and meaningful interpretability of the model support the notion that attention-based networks hold significant promise in CAD screening and may revolutionise medical decision-making in the near future.
Effect of Alginate Proportion in Glycerol-Reinforced Alginate–Starch Biofilms on Hydrogen Bonds by Raman Spectroscopy
Authors: Kadri Rana , Bresson Serge , Aussenac Thierry
Published: July 2023

Among the most studied natural polymers, alginate, a natural polysaccharide extracted from algae is well known due to its applications related to remarkable properties such as biocompatibility, biodegradability and low toxicity. In order to optimize the physicochemical properties of alginate and starch-based biofilms reinforced by glycerol, we propose of different biofilms by Raman spectroscopy according to the mass proportion of alginate in water: 1%, 2%, 3%, 4% and 5%. The first vibrational study of alginate-based biofilms demonstrated a link between the mass proportion of alginate in water with the contribution of hydrogen bonds through vibrational modes at 1570, 1500 and 1414 cm−1 and with the vibrational contributions of gauche and trans conformational C-C stretching at 1098 and 1068 cm−1, respectively. This link seems to persist in the case of biofilms based on alginate reinforced by glycerol with a lower intensity. For the cases of alginate and starch-based biofilms and glycerol-reinforced alginate–starch biofilms, the impact of the mass proportion of alginate in water on the hydrogen bonds is evaluated by determining an area ratio τ=Area1414/Area1340 between the mode 1414 cm−1 assigned to the hydrogen bonds and 1340 cm−1 assigned to d(O-H) in plane. The vibrational results show interaction between the proportion of alginate and the hydrogen bonds.
Heavy-Duty Use and Charging of Power Tool Battery Packs: A Simulation-Based Study to Improve Cooling Strategies
Authors: Königer Veit , Knoblauch Volker
Published: July 2023

In the fast-growing but also highly competitive market of battery-powered power tools, cell-pack-cooling systems are of high importance, as they guarantee safety and short charging times. A simulation model of an 18 V power tool battery pack was developed to be able to evaluate four different pack-cooling systems (two heat-conductive polymers, one phase change material, and non-convective air as reference) in an application scenario of practical relevance (the intensive use of a power tool followed by cooling down and charging steps). The simulation comprises battery models of 21700 cells that are commercially available as well as heat transfer models. The study highlights the performance of the different cooling materials and their effect on the maximum pack temperature and total charging cycle time. Key material parameters and their influence on the battery pack temperature and temperature homogeneity are discussed. Using phase change materials and heat-conductive polymers, a significantly lower maximum temperature during discharge (up to 26%) and a high shortening potential of the use/charging cycle (up to 32%) were shown. In addition to the cooling material sweep, a parameter sweep was performed, varying the external temperature and air movement. The high importance of the conditions of use on the cooling system’s performance was illustrated.
The Impact of Typhoon “In-Fa” (2021) on Temperature, Salinity, and Chlorophyll-a Concentration in the Upwelling Area of Northwestern East China Sea
Authors: Che Yingliang , Guo Biyun , Mantravadi Venkata Subrahmanyam , Wang Jushang , Ji Zhaokang
Published: July 2023

Severe typhoon “In-Fa” passed through the northwestern region of East China Sea (ECS) in July 2021, affecting oceanic variables such as seawater temperature, salinity, and chlorophyll-a (Chl-a) concentration over the upwelling area. In this study, we analyzed the influence of the passage of typhoon “In-Fa” on the marine environment over the Upwelling Area off the Yangtze River Estuary (UAYRE) and the Upwelling Area of Zhoushan (UAZS). The results showed a significant decrease in sea surface temperature (SST) during the “In-Fa” typhoon, with maximum SST reductions of 2.98 °C in the UAYRE and 1.46 °C in the UAZS, which showed a “right bias” (indicating a greater cooling effect on the right side of the typhoon path compared to the left side). “In-Fa” influenced the temperature and salinity structure of the study areas and deepened the mixed layer depth (MLD). The MLD varied from the shallowest values of 2.02 m (18 July) to the deepest values of 19.4 m (26 July) in the UAYRE and from 2.43 m (18 July) to 16.79 m (25 July) in the UAZS. Furthermore, “In-Fa” led to an increase in sea surface Chl-a concentration, with a maximum Chl-a concentration enhancement of 285.58% (from 20 July to 28 July) in the UAYRE and 233.33% (from 20 July to 27 July) in the UAZS. The Ekman suction effect of “In-Fa” strengthened the upwelling, facilitating the transport of deep-sea nutrients to the upper ocean and providing favorable conditions for the growth of phytoplankton, thus benefiting the reproduction and survival of zooplankton, fish, and shrimp. This study contributes to understanding the mechanisms by which typhoons impact the ocean environment in upwelling area and provides valuable insights for the sustainable development of marine fisheries resources.
Critical Review on Radiative Forcing and Climate Models for Global Climate Change since 1970
Authors: Lu Qing-Bin
Published: July 2023

This review identifies a critical problem in the fundamental physics of current climate models. The large greenhouse effect of rising CO2 assumed in climate models is assessed by six key observations from ground- and satellite-based measurements. This assessment is enhanced by statistical analyses and model calculations of global or regional mean surface temperature changes by conventional climate models and by a conceptual quantum physical model of global warming due to halogen-containing greenhouse gases (halo-GHGs). The postulated large radiative forcing of CO2 in conventional climate models does not agree with satellite observations. Satellite-observed warming pattern resembles closely the atmospheric distribution of chlorofluorocarbons (CFCs). This review helps understand recent remarkable observations of reversals from cooling to warming in the lower stratosphere over most continents and in the upper stratosphere at high latitudes, surface warming cessations in the Antarctic, North America, UK, and Northern-Hemisphere (NH) extratropics, and the stabilization in NH or North America snow cover, since the turn of the century. The complementary observation of surface temperature changes in 3 representative regions (Central England, the Antarctic, and the Arctic) sheds new light on the primary mechanism of global warming. These observations agree well with not CO2-based climate models but the CFC-warming quantum physical model. The latter offers parameter-free analytical calculations of surface temperature changes, exhibiting remarkable agreement with observations. These observations overwhelmingly support an emerging picture that halo-GHGs made the dominant contribution to global warming in the late 20th century and that a gradual reversal in warming has occurred since ~2005 due to the phasing out of halo-GHGs. Advances and insights from this review may help humans make rational policies to reverse the past warming and maintain a healthy economy and ecosystem.
Characterization of Non-Linear Bi-Skew Jordan n-Derivations on Prime ∗-Algebras
Authors: Ali Asma , Alali Amal S. , Tasleem Mohd
Published: July 2023

Let A be a prime *-algebra. A product defined as U•V=UV∗+VU∗ for any U,V∈A, is called a bi-skew Jordan product. A map ξ:A→A, defined as ξpnU1,U2,⋯,Un=∑k=1npnU1,U2,...,Uk−1,ξ(Uk),Uk+1,⋯,Un for all U1,U2,...,Un∈A, is called a non-linear bi-skew Jordan n-derivation. In this article, it is shown that ξ is an additive ∗-derivation.
Analysis of Comfort during Transfer by a Dual-Arm Care Robot Based on Human Body Pressure and Surface Electromyographic Signals
Authors: Guan Qifei , Yang Zhiqiang , Lu Hao , Guo Shijie
Published: July 2023

In-home elderly care faces a crucial challenge regarding mobility among essential assistive devices, for which dual-arm care robots present a viable solution. However, ensuring human comfort in human–robot interactions necessitate quantifiable standards. Currently, the field lacks accurate biomechanical model solutions and objective comfort evaluation. In response to this need, this study proposes a method for solving human–robot statics models based on real-time pressure and position information. Employing the Optitrack motion capture system and Tekscan pressure sensors, we collect real-time positional and pressure data. This information is then incorporated into our human–robot statics model, facilitating the instantaneous calculation of forces and moments within the human body’s sagittal plane. Building on this, comprehensive research literature review and meticulous questionnaire surveys are conducted to establish a comprehensive comfort evaluation function. To validate this function, experiments are performed to enable real-time assessment of comfort levels experienced during the process of transferring the human body. Additionally, the Noraxon surface electromyography (sEMG) sensors are utilized to capture real-time sEMG signals from the erector spinae, adductor muscles and quadratus lumborum, thereby providing objective validation for the comfort evaluation function. The experimental findings demonstrate that the proposed methodology for evaluating comfort achieves an accuracy rate of 85.1%.
Determination of a Measurement Procedure for the Study of Cells’ Dielectric Properties through Descriptive Statistic
Authors: D’Alvia Livio , Peruzzi Barbara , Apa Ludovica , Del Prete Zaccaria , Rizzuto Emanuele
Published: July 2023

This paper presents a measurement procedure for analyzing the dielectric properties of cells using descriptive statistics. The study focuses on four cancer cell lines (MDA-MB-231 and MCF-7 breast cancer, SaOS-2, and 143B osteosarcoma) and DMEM culture medium, utilizing the Lorentzian fit model of the return-loss function. The measurements are performed using a circular patch resonator with a 40 mm diameter, powered by a miniVNA operating in the frequency range of 1 MHz to 3 GHz. Eight specimens are prepared for each group to ensure reliability, and the return loss is recorded ten times for each specimen. Various statistical parameters are calculated and evaluated, including the average value, standard deviation, coefficient of variation, and relative error between the average and the first values. The results demonstrate that one single acquisition highly represents the entire set of ten data points, especially for the resonant frequency, with an accuracy error lower than 0.05%. These findings have significant implications for the methodological approach to detecting cells’ dielectric properties, as they substantially reduce time and preserve the specimens without compromising the accuracy of the experimental results.
Three-Dimensional Bioprinting in Cardiovascular Disease: Current Status and Future Directions
Authors: Sun Zhonghua , Zhao Jack , Leung Emily , Flandes-Iparraguirre Maria , Vernon Michael , Silberstein Jenna , De-Juan-Pardo Elena M. , Jansen Shirley
Published: July 2023

Three-dimensional (3D) printing plays an important role in cardiovascular disease through the use of personalised models that replicate the normal anatomy and its pathology with high accuracy and reliability. While 3D printed heart and vascular models have been shown to improve medical education, preoperative planning and simulation of cardiac procedures, as well as to enhance communication with patients, 3D bioprinting represents a potential advancement of 3D printing technology by allowing the printing of cellular or biological components, functional tissues and organs that can be used in a variety of applications in cardiovascular disease. Recent advances in bioprinting technology have shown the ability to support vascularisation of large-scale constructs with enhanced biocompatibility and structural stability, thus creating opportunities to replace damaged tissues or organs. In this review, we provide an overview of the use of 3D bioprinting in cardiovascular disease with a focus on technologies and applications in cardiac tissues, vascular constructs and grafts, heart valves and myocardium. Limitations and future research directions are highlighted.
Immunolocalization of the AT-1R Ang II Receptor in Human Kidney Cancer
Authors: Muscella Antonella , Resta Leonardo , Cossa Luca , Marsigliante Santo
Published: July 2023

This study aimed to evaluate AT1-R expression in normal and cancerous human kidneys, how these expressions are modified, and AT1-R functionality. AT-1R mRNA expression, determined by real-time PCR, was detected in all samples. AT-1R mRNA increased in well-differentiated cancer (G1, p < 0.01) and decreased 2.9-fold in undifferentiated cancer (G4, p < 0.001) compared with normal kidney tissues. Immunocytochemistry analysis showed that the AT-1R was expressed in the normal tubular epithelium. The glomerulus was also immunoreactive, and as expected, the smooth muscle cells of the vessel walls also expressed the receptor. A total of 35 out of 42 tumors were AT-1R positive, with the cell tumors showing varying numbers of immunoreactive cells, which were stained in a diffuse cytoplasmic and membranous pattern. Computer-assisted counting of the stained tumor cells showed that the number of AT-1R-positive cells increased in the well-differentiated cancers. The functionality of AT-1R was assessed in primary cultures of kidney epithelial cells obtained from three G3 kidney cancer tissues and corresponding histologically proven non-malignant tissue adjacent to the tumor. Indeed, Ang II stimulated, in a dose-dependent manner, the 24 h proliferation of normal kidney cells and cancer cells in the primary culture and phosphorylated extracellular regulated kinases 1 and 2. In conclusion, Ang II may be involved in the growth or function of neoplastic kidney tissue.
MicroRNA-7: A New Intervention Target for Inflammation and Related Diseases
Authors: Chen Chao , Guo Mengmeng , Zhao Xu , Zhao Juanjuan , Chen Longqing , He Zhixu , Xu Lin , Zha Yan
Published: July 2023

MicroRNAs (miRNAs) are a class of small noncoding RNA that can regulate physiological and pathological processes through post-transcriptional regulatory gene expression. As an important member of the miRNAs family, microRNA-7 (miR-7) was first discovered in 2001 to play an important regulatory role in tissue and organ development. Studies have shown that miR-7 participates in various tissue and organ development processes, tumorigenesis, aging, and other processes by regulating different target molecules. Notably, a series of recent studies have determined that miR-7 plays a key regulatory role in the occurrence of inflammation and related diseases. In particular, miR-7 can affect the immune response of the body by influencing T cell activation, macrophage function, dendritic cell (DC) maturation, inflammatory body activation, and other mechanisms, which has important potential application value in the intervention of related diseases. This article reviews the current regulatory role of miR-7 in inflammation and related diseases, including viral infection, autoimmune hepatitis, inflammatory bowel disease, and encephalitis. It expounds on the molecular mechanism by which miR-7 regulates the occurrence of inflammatory diseases. Finally, the existing problems and future development directions of miR-7-based intervention on inflammation and related diseases are discussed to provide new references and help strengthen the understanding of the pathogenesis of inflammation and related diseases, as well as the development of new strategies for clinical intervention.
Increasing Awareness for Peripheral Artery Disease through the Identification of Novel Biomarkers
Authors: Li Ben , Syed Muzammil H. , Qadura Mohammad
Published: July 2023

Peripheral artery disease (PAD) is a chronic atherosclerotic disorder that involves the lower extremity arteries, manifesting in claudication, rest pain, and tissue loss [...]
Nociceptor–Macrophage Interactions in Apical Periodontitis: How Biomolecules Link Inflammation with Pain
Authors: Menon Nandita , Kishen Anil
Published: July 2023

Periradicular tissues have a rich supply of peripheral afferent neurons, also known as nociceptive neurons, originating from the trigeminal nerve. While their primary function is to relay pain signals to the brain, these are known to be involved in modulating innate and adaptive immunity by initiating neurogenic inflammation (NI). Studies have investigated neuroanatomy and measured the levels of biomolecules such as cytokines and neuropeptides in human saliva, gingival crevicular fluid, or blood/serum samples in apical periodontitis (AP) to validate the possible role of trigeminal nociceptors in inflammation and tissue regeneration. However, the contributions of nociceptors and the mechanisms involved in the neuro-immune interactions in AP are not fully understood. This narrative review addresses the complex biomolecular interactions of trigeminal nociceptors with macrophages, the effector cells of the innate immune system, in the clinical manifestations of AP.
Weight Is a Predictor of Delayed Operation Time in Primary Isolated Anterior Cruciate Ligament Reconstruction
Authors: Lim Sungtae , Lee Sung-Sahn , Oh Juyong , Lee Dae-Hee
Published: July 2023

Background: Few studies have evaluated the impact of obesity on operation time in patients with ACL reconstruction. The purpose of this study was to understand the effect of obesity on operation time in patients with arthroscopic anterior cruciate ligament (ACL) reconstruction. Methods: A total of 103 patients were included. The mean pure operation time was 45.9 ± 13.4 min. Considering that 15 min incremental increases in operation time are an independent risk factor for complications, all patients were classified into two groups according to operation time: more or less than 61 min. Demographic data were compared between both groups. Pure operation time was defined as operative time without suture time (pure operation time = suture start time − operation start time). Correlation analysis between demographic data and pure operation time was performed, and multiple linear regression analysis was used to identify the predictors of pure operation time. Results: The pure operation time ≥61 min group (n = 34) had a 14.7 kg higher weight and 4.5 kg/m2 higher body mass index (BMI) than those with pure operation time < 61 min (n = 69). Weight (r = 0.635, p < 0.001) and BMI (r = 0.584, p < 0.001) were positively correlated with operation time. Multiple linear regression analysis showed that weight (β = 0.635, p < 0.001) was the only predictor of operation time. A weight of 74.25 kg was a cut-off value for a pure operation time of >61 min. Conclusions: The weight and BMI of the group with pure operation time of ≥61 min were 14.7 kg and 4.5 kg/m2 higher, respectively. The weight of patients with ACL tears was a factor affecting delay in the operation time. Patients weighing over 74.25 kg were more likely to delay ACL reconstruction.
Cancer Predisposition Syndromes and Thyroid Cancer: Keys for a Short Two-Way Street
Authors: Balinisteanu Ioana , Panzaru Monica-Cristina , Caba Lavinia , Ungureanu Maria-Christina , Florea Andreea , Grigore Ana Maria , Gorduza Eusebiu Vlad
Published: July 2023

Cancer predisposition syndromes are entities determined especially by germinal pathogenic variants, with most of them autosomal dominantly inherited. The risk of a form of cancer is variable throughout life and affects various organs, including the thyroid. Knowing the heterogeneous clinical picture and the existing genotype–phenotype correlations in some forms of thyroid cancer associated with these syndromes is important for adequate and early management of patients and families. This review synthesizes the current knowledge on genes and proteins involved in cancer predisposition syndromes with thyroid cancer and the phenomena of heterogeneity (locus, allelic, mutational, and clinical).
Demographic and Clinical Predictors of Drug Response in Epileptic Children in Jeddah
Authors: Magadmi Rania , Alyoubi Reem
Published: July 2023

Epilepsy is a chronic neurological disease of the brain. Over 20 antiseizure medications are available on the market, but a third of patients still have drug-resistant epilepsy. This study was designed to assess the impact of the demographic and clinical characteristics of epileptic children on their likelihood of developing drug resistance. This study was a multicenter, hospital-based, cross-sectional, case–control study of pediatric patients diagnosed with epilepsy in Jeddah, Saudi Arabia. The study included 101 children with epilepsy. Fifty-six patients showed good response to antiseizure medications (ASMs), and forty-five patients had a poor response. A statistically significant good response to ASMs was reported among younger patients, those who did not report parental consanguinity, those who did not have a family history of epilepsy, and those diagnosed with partial seizures, with no reported adverse effects. The levetiracetam regimen was statistically significant regarding the responsiveness to ASMs. Patients on a monotherapy regimen elicited a significantly better response to levetiracetam than patients on polytherapy (p < 0.001). No significant association was found between the response to ASMs and the sex, nationality, body mass index, complete blood count, or vitamin B12 level. In conclusion, the ASM response in epileptic patients can be predicted by knowing the patient’s demographic and epileptic history. However, the complete blood count and vitamin B12 level failed to predict patients’ response to ASMs.
Grasping Performance Analysis and Comparison of Multi-Chamber Ring-Shaped Soft Grippers
Authors: Wang Dan , Wu Xiaojun
Published: July 2023

Biologically inspired pneumatic ring-shaped soft grippers have been extensively studied in the field of soft robotics. However, the effect of the number of air chambers on the grasping performance (grasping range and load capacity) of ring-shaped soft grippers has not been studied. In this article, we propose three ring-shaped soft grippers with the same area of inner walls of air chambers and different numbers of air chambers (two-chamber, three-chamber, and four-chamber) for analyzing and comparing their grasping performance. Finite element method (FEM) models and experimental measurements are conducted to compare the deformation of the inner walls of the three ring-shaped soft grippers, the results indicate that the grasping range of the three-chamber ring-shaped soft gripper is larger than that of the two-chamber ring-shaped soft gripper and the four-chamber ring-shaped soft gripper. Then we choose the three-chamber ring-shaped soft gripper to study the relationship between contact force and air pressure by FEM models and experimental measurements. Several groups of experiments are constructed to compare the load capacity of the three ring-shaped soft grippers, the results indicate that the load capacity of the three-chamber ring-shaped soft gripper is higher than that of the two-chamber ring-shaped soft gripper and the four-chamber ring-shaped soft gripper. The above results reveal that the grasping performance of the three-chamber ring-shaped soft gripper is better than that of other two ring-shaped soft grippers. Furthermore, the application experiments indicate that the three ring-shaped soft grippers can grasp various objects with different weights, material properties, and shapes. This study provides a new idea for investigating ring-shaped soft grippers.
A CRISPR-Cas12a-Based Diagnostic Method for Japanese Encephalitis Virus Genotypes I, III, and V
Authors: Kwak Namki , Park Bum Ju , Song Yoon-Jae
Published: July 2023

The Japanese encephalitis virus (JEV) is prevalent in Asian countries, including Korea, Japan, China, Vietnam, and India. JEV is transmitted to humans by Culex mosquitoes. Despite extensive research efforts, no approved antiviral agents are currently available, although JE can be prevented by vaccination. DNA endonuclease-targeted CRISPR trans reporter (DETECTR) is a newly emerging CRISPR-Cas12a-based molecular diagnostic method combined with isothermal nucleic acid amplification. In this study, DETECTR with reverse transcription–recombinase polymerase amplification (RT-RPA) was effectively utilized for JEV diagnosis and detected down to 10 RNA copies for JEV genotype I (GI) and 1 × 102 copies for both GIII and GV, achieving similar sensitivity to RT-PCR while displaying no cross-reaction with other viruses. A one-tube, one-temperature format of DETECTR was further developed, and its efficiency compared with that of conventional DETECTR.
Glucose Oxidase/Egg White Protein Microparticles with a Redox Mediator for Glucose Biosensors on a Screen-Printed Electrode and a Decomposable Electrode
Authors: Rasitanon Natcha , Rattanapan Parinthorn , Kaewpradub Kanyawee , Buranachai Chittanon , Jeerapan Itthipon
Published: July 2023

Glucose oxidase (GOx) is a typical model enzyme used to create biosensors. Exploring a strategy to prepare ready-to-use functional enzymatic microparticles combining GOx and food-based proteins offers compelling advantages. However, no reports exist on the integration of egg white materials to synthesize functional biorecognition particles with glucose oxidation catalytic functions for electrochemical biosensors. Here, we demonstrate functional microparticles combining egg white proteins, GOx, and 9,10-phenanthrenequinone (PQ). The egg white proteins crosslink to form three-dimensional scaffolds to accommodate GOx and redox molecules. The PQ mediator enhances electron transfer between the electrode surface and the GOx enzyme’s flavin adenine dinucleotides. The functional microparticles are directly applied to the printed electrode. The performance of these microparticles is evaluated using a screen-printed carbon nanotube (CNT)-modified electrode coated with GOx/PQ/egg white protein microparticles. The analytical performance of the system exhibits a linear range of 0.125−40 mM, with a maximum current (Imax) and a Michaelis–Menten constant (Km) being 0.2 µA and 4.6 mM, respectively. Additionally, a decomposable electrode composed of CNTs and edible oil conjugated with functional enzyme microparticles is shown to undergo degradation under gastric conditions. Utilizing food-based proteins to accommodate enzymes and to create redox-active microparticles for catalyzing glucose oxidation offers advantages in developing affordable and degradable bioelectrodes. This concept holds promise for advancing biocompatible electrodes in biosensor and bioelectronics applications.