bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization and Validation of a New 3D Printing Ink for Reducing Therapeutic Gap in Pediatrics through Individualized Medicines
Authors: Díaz-Torres Eduardo , Suárez-González Javier , Monzón-Rodríguez Cecilia N. , Santoveña-Estévez Ana , Fariña José B.
Published: June 2023

3D printing technology can be used to develop individualized medicines in hospitals and pharmacies, allowing a high degree of personalization and the possibility to adjust the dose of the API based on the quantity of material extruded. The main goal of incorporating this technology is to have a stock of API-load print cartridges that could be used at different storage times and for different patients. However, it is necessary to study the extrudability, stability, and buildability of these print cartridges during storage time. A paste-like formulation containing hydrochlorothiazide as a model drug was prepared and distributed in five print cartridges, each of which was studied for different storage times (0 h–72 h) and conditions, for repeated use on different days. For each print cartridge, an extrudability analysis was performed, and subsequently, 100 unit forms of 10 mg hydrochlorothiazide were printed. Finally, various dosage units containing different doses were printed, taking into account the optimized printing parameters based on the results of the extrudability analysis carried out previously. An appropriate methodology for the rapid development of appropriate SSE 3DP inks for pediatrics was established and evaluated. The extrudability analysis and several parameters allowed the detection of changes in the mechanical behavior of the printing inks, the pressure interval of the steady flow, and the selection of the volume of ink to be extruded to obtain each of the required doses. The print cartridges were stable for up to 72 h after processing, and orodispersible printlets containing 6 mg to 24 mg of hydrochlorothiazide can be produced using the same print cartridge and during the same printing process with guaranteed content and chemical stability. The proposed workflow for the development of new printing inks containing APIs will allow the optimization of feedstock material and human resources in pharmacy or hospital pharmacy services, thus speeding up their development and reducing costs.
Corneal Permeability and Uptake of Twenty-Five Drugs: Species Comparison and Quantitative Structure–Permeability Relationships
Authors: Santana Cleildo P. , Matter Brock A. , Patil Madhoosudan A. , Silva-Cunha Armando , Kompella Uday B.
Published: June 2023

The purpose of this study was to determine corneal permeability and uptake in rabbit, porcine, and bovine corneas for twenty-five drugs using an N-in-1 (cassette) approach and relate these parameters to drug physicochemical properties and tissue thickness through quantitative structure permeability relationships (QSPRs). A twenty-five-drug cassette containing β-blockers, NSAIDs, and corticosteroids in solution at a micro-dose was exposed to the epithelial side of rabbit, porcine, or bovine corneas mounted in a diffusion chamber, and the corneal drug permeability and tissue uptake were monitored using an LC-MS/MS method. Data obtained were used to construct and evaluate over 46,000 quantitative structure–permeability (QSPR) models using multiple linear regression, and the best-fit models were cross-validated by Y-randomization. Drug permeability was generally higher in rabbit cornea and comparable between bovine and porcine corneas. Permeability differences between species could be explained in part by differences in corneal thickness. Corneal uptake between species correlated with a slope close to 1, indicating generally similar drug uptake per unit weight of tissue. A high correlation was observed between bovine, porcine, and rabbit corneas for permeability and between bovine and porcine corneas for uptake (R2 ≥ 0.94). MLR models indicated that drug characteristics such as lipophilicity (LogD), heteroatom ratio (HR), nitrogen ratio (NR), hydrogen bond acceptors (HBA), rotatable bonds (RB), index of refraction (IR), and tissue thickness (TT) are of great influence on drug permeability and uptake. When data for all species along with thickness as a parameter was used in MLR, the best fit equation for permeability was Log (% transport/cm2·s) = 0.441 LogD − 8.29 IR + 8.357 NR − 0.279 HBA − 3.833 TT + 10.432 (R2 = 0.826), and the best-fit equation for uptake was Log (%/g) = 0.387 LogD + 4.442 HR + 0.105 RB − 0.303 HBA − 2.235 TT + 1.422 (R2 = 0.750). Thus, it is feasible to explain corneal drug delivery in three species using a single equation.
PhCHS5 and PhF3′5′H Genes Over-Expression in Petunia (Petunia hybrida) and Phalaenopsis (Phalaenopsis aphrodite) Regulate Flower Color and Branch Number
Authors: Lou Yuxia , Zhang Qiyu , Xu Qingyu , Yu Xinyu , Wang Wenxin , Gai Ruonan , Ming Feng
Published: June 2023

Flower breeders are continually refining their methods for producing high-quality flowers. Phalaenopsis species are considered the most important commercially grown orchids. Advances in genetic engineering technology have provided researchers with new tools that can be used along with traditional breeding methods to enhance floral traits and quality. However, the application of molecular techniques for the breeding of new Phalaenopsis species has been relatively rare. In this study, we constructed recombinant plasmids carrying flower color-related genes, Phalaenopsis Chalcone synthase (PhCHS5) and/or Flavonoid 3′,5′-hydroxylase (PhF3′5′H). These genes were transformed into both Petunia and Phalaenopsis plants using a gene gun or an Agrobacterium tumefaciens-based method. Compared with WT, 35S::PhCHS5 and 35S::PhF3′5′H both had deeper color and higher anthocyanin content in Petunia plants. Additionally, a phenotypic comparison with wild-type controls indicated the PhCHS5 or PhF3′5′H-transgenic Phalaenopsis produced more branches, petals, and labial petals. Moreover, PhCHS5 or PhF3′5′H-transgenic Phalaenopsis both showed deepened lip color, compared with the control. However, the intensity of the coloration of the Phalaenopsis lips decreased when protocorms were co-transformed with both PhCHS5 and PhF3′5′H. The results of this study confirm that PhCHS5 and PhF3′5′H affect flower color in Phalaenopsis and may be relevant for the breeding of new orchid varieties with desirable flowering traits.
Correction: Savović et al. Power Flow in Multimode Graded-Index Microstructured Polymer Optical Fibers. Polymers 2023, 15, 1474
Authors: Savović Svetislav , Simović Ana , Drljača Branko , Kovačević Milan S. , Kuzmanović Ljubica , Djordjevich Alexandar , Aidinis Konstantinos , Min Rui
Published: June 2023

The authors wish to make three changes to their published paper [...]
Development of New Accelerated Aging Test for Comparison of the Quality of Different Insulating Papers Based on Cellulose
Authors: Mihajlovic Draginja , Vasovic Valentina , Lukic Jelena
Published: June 2023

The aim of this study is to propose a test method for the determination of the quality of transformer paper insulation. For this purpose, the oil/cellulose insulation systems were exposed to various accelerated aging tests. The results of the aging experiments of normal Kraft and thermally upgraded papers, two different types of transformer oil (mineral and natural ester), and copper are shown. Aging was carried out in various experiments at 150 °C, 160 °C, 170 °C, and 180 °C with dry (initial values ≤ 0.5%) and moistened cellulose insulation (initial values 3–3.5%). Following insulating oil and paper, degradation markers were measured: the degree of polymerization, tensile strength, furan derivates, methanol/ethanol, acidity, interfacial tension, and dissipation factor. It was found that the aging of cellulose insulation in cycles was 1.5–1.6 times faster in comparison to continuous aging, due to the more pronounced effect of hydrolytic mechanism in cyclic aging owing to the produced and absorbed water. Furthermore, it was observed that the high initial water content in cellulose increases the aging rate two to three times more than in the dry experimental setup. The proposed aging test in cycles can be used to achieve faster aging and to compare the quality of different insulating papers.
Argon Plasma Jet-Treated Poly (Vinyl Alcohol)/Chitosan and PEG 400 Plus Mangifera indica Leaf Extract for Electrospun Nanofiber Membranes: In Vitro Study
Authors: Sukum Pongphun , Punyodom Winita , Dangtip Somsak , Poramapijitwat Pipath , Daranarong Donraporn , Jenvoraphot Thannaphat , Nisoa Mudtorlep , Kuensaen Chakkrapong , Boonyawan Dheerawan
Published: June 2023

The wound-healing process can be disrupted at any stage due to various internal and external factors. The inflammatory stage of the process plays a vital role in determining the outcome of the wound. Prolonged inflammation due to bacterial infection can lead to tissue damage, slow healing, and complications. Wound dressings made using materials such as poly (vinyl alcohol) (PVA), chitosan (CS), and poly (ethylene glycol) (PEG) with Mangifera extract (ME) added can help reduce infection and inflammation, creating a conducive environment for faster healing. However, creating the electrospun membrane is challenging due to balancing various forces such as rheological behavior, conductivity, and surface tension. To improve the electrospinnability of the polymer solution, an atmospheric pressure plasma jet can induce chemistry in the solution and increase the polarity of the solvent. Thus, this research aims to investigate the effect of plasma treatment on PVA, CS, and PEG polymer solutions and fabricate ME wound dressing via electrospinning. The results indicated that increasing plasma treatment time increased the viscosity of the polymer solution, from 269 mPa∙to 331 mPa∙s after 60 min, and led to an increase in conductivity from 298 mS/cm to 330 mS/cm and an increase in nanofiber diameter from 90 ± 40 nm to 109 ± 49 nm. Incorporating 1% mangiferin extract into an electrospun nanofiber membrane has been found to increase the inhibition rates of Escherichia coli and Staphylococcus aureus by 29.2% and 61.2%, respectively. Additionally, the fiber diameter decreases when compared with the electrospun nanofiber membrane without ME. Our findings demonstrate that electrospun nanofiber membrane with ME has anti-infective properties and can promote faster wound healing.
Thiol-Surface-Engineered Cellulose Nanocrystals in Favor of Copper Ion Uptake
Authors: Dang-Bao Trung , Nguyen Thi-My-Chau , Hoang Gia-Han , Lam Hoa-Hung , Phan Hong-Phuong , Tran Thi-Kieu-Anh
Published: June 2023

Cellulose, the most abundant natural polymer on earth, has recently gained attention for a large spectrum of applications. At a nanoscale, nanocelluloses (mainly involving cellulose nanocrystals or cellulose nanofibrils) possess many predominant features, such as highly thermal and mechanical stability, renewability, biodegradability and non-toxicity. More importantly, the surface modification of such nanocelluloses can be efficiently obtained based on the native surface hydroxyl groups, acting as metal ions chelators. Taking into account this fact, in the present work, the sequential process involving chemical hydrolysis of cellulose and autocatalytic esterification using thioglycolic acid was performed to obtain thiol-functionalized cellulose nanocrystals. The change in chemical compositions was attributed to thiol-functionalized groups and explored via the degree of substitution using a back titration method, X-ray powder diffraction, Fourier-transform infrared spectroscopy and thermogravimetric analysis. Cellulose nanocrystals were spherical in shape and ca. 50 nm in diameter as observed via transmission electron microscopy. The adsorption behavior of such a nanomaterial toward divalent copper ions from an aqueous solution was also assessed via isotherm and kinetic studies, elucidating a chemisorption mechanism (ion exchange, metal chelation and electrostatic force) and processing its operational parameters. In contrast to an inactive configure of unmodified cellulose, the maximum adsorption capacity of thiol-functionalized cellulose nanocrystals toward divalent copper ions from an aqueous solution was 4.244 mg g−1 at a pH of 5 and at room temperature.
Metal and Polymer Based Composites Manufactured Using Additive Manufacturing—A Brief Review
Authors: Rajendran Sundarakannan , Palani Geetha , Kanakaraj Arunprasath , Shanmugam Vigneshwaran , Veerasimman Arumugaprabu , Gądek Szymon , Korniejenko Kinga , Marimuthu Uthayakumar
Published: June 2023

This review examines the mechanical performance of metal- and polymer-based composites fabricated using additive manufacturing (AM) techniques. Composite materials have significantly influenced various industries due to their exceptional reliability and effectiveness. As technology advances, new types of composite reinforcements, such as novel chemical-based and bio-based, and new fabrication techniques are utilized to develop high-performance composite materials. AM, a widely popular concept poised to shape the development of Industry 4.0, is also being utilized in the production of composite materials. Comparing AM-based manufacturing processes to traditional methods reveals significant variations in the performance of the resulting composites. The primary objective of this review is to offer a comprehensive understanding of metal- and polymer-based composites and their applications in diverse fields. Further on this review delves into the intricate details of metal- and polymer-based composites, shedding light on their mechanical performance and exploring the various industries and sectors where they find utility.
Oil Media on Paper: Investigating the Interaction of Cold-Pressed Linseed Oil with Paper Supports with FTIR Analysis
Authors: Banou Penelope , Boyatzis Stamatis , Choulis Konstantinos , Theodorakopoulos Charis , Alexopoulou Athena
Published: June 2023

Previous works of the authors have presented the changes in the optical, mechanical, and chemical properties of the oiled areas of the supports that occur upon ageing due to oil-binder absorption in works of art on paper and printed material. In this framework, transmittance FTIR analysis has indicated that the presence of linseed oil induces the conditions to promote the deterioration of the oil-impregnated areas of the paper supports. However, the analysis of oil-impregnated mock-ups did not provide detailed information about the input of linseed oil formulations and the different types of paper support on the chemical changes that occur upon ageing. This work presents the results of ATR-FTIR and reflectance FTIR, which were used for compensating the previous results, proving indications on the effect of different materials (linseed oil formulations, and cellulosic and lignocellulosic papers) on the development of chemical changes, thus, on the condition of the oiled areas upon ageing. Although linseed oil formulations have a determining effect on the condition of the oiled areas of the support, the paper pulp content appears to have an input to the chemical changes that occur in the system of paper–linseed oil upon ageing. The results presented are more focused on the oil-impregnated mock-ups with cold-pressed linseed oil since results have indicated that this causes more extended changes upon ageing.
Characterization of Synthetic Polymer Coated with Biopolymer Layer with Natural Orange Peel Extract Aimed for Food Packaging
Authors: Gabrić Domagoj , Kurek Mia , Ščetar Mario , Brnčić Mladen , Galić Kata
Published: June 2023

This research was aimed to make biolayer coatings enriched with orange peel essential oil (OPEO) on synthetic laminate, oriented poly(ethylene-terephthalate)/polypropylene (PET-O/PP). Coating materials were taken from biobased and renewable waste sources, and the developed formulation was targeted for food packaging. The developed materials were characterized for their barrier (O2, CO2, and water vapour), optical (colour, opacity), surface (inventory of peaks by FTIR), and antimicrobial activity. Furthermore, the overall migration from a base layer (PET-O/PP) in an acetic acid (3% HAc) and ethanol aqueous solution (20% EtOH) were measured. The antimicrobial activity of chitosan (Chi)-coated films was assessed against Escherichia coli. Permeation of the uncoated samples (base layer, PET-O/PP) increased with the temperature increase (from 20 °C to 40 °C and 60 °C). Films with Chi-coatings were a better barrier to gases than the control (PET-O/PP) measured at 20 °C. The addition of 1% (w/v) OPEO to the Chi-coating layer showed a permeance decrease of 67% for CO2 and 48% for O2. The overall migrations from PET-O/PP in 3% HAc and 20% EtOH were 1.8 and 2.3 mg/dm2, respectively. Analysis of spectral bands did not indicate any surface structural changes after exposure to food simulants. Water vapour transmission rate values were increased for Chi-coated samples compared to the control. The total colour difference showed a slight colour change for all coated samples (ΔE > 2). No significant changes in light transmission at 600 nm for samples containing 1% and 2% OLEO were observed. The addition of 4% (w/v) OPEO was not enough to obtain a bacteriostatic effect, so future research is needed.
Between Tyranny and Anarchy: Islam, COVID-19, and Public Policy
Authors: Mirza Mahan
Published: June 2023

Research on the causes for vaccine resistance among Nigerian Muslims reveals what the philosopher Žižek terms a “heaven in disorder:” lack of trust in public institutions, conspiracy theories, ignorance of basic science, individual apathy, and faith in “Allah as the only protector.” Other social contexts demonstrate far greater compliance. How can governments improve outcomes in vaccine resistant communities amidst such complexity, especially in instances where theology provides a right to dissent? Alongside a right to dissent, “obedience to authority” for the sake of social and political harmony is also an important principle of Islamic thought. It has the ability to enhance widespread compliance to public health guidelines by obligating the setting aside of private convictions in favor of collective cooperation. Religious literacy is an important element for responding effectively to pandemics, and by extension, other global emergencies. While policymakers must tailor their outreach to incommensurable worldviews in society, the human family must also imagine effective political models for cooperation despite divergence in worldviews. Otherwise, societies may need to choose between tyranny and anarchy. This article adds to efforts already underway which aim to demonstrate that engagement with religious norms, rather than their dismissal, represents the most promising path towards tackling vaccine resistance, especially in communities in which religious authority significantly informs social practice.
An Efficient On-Chip Data Storage and Exchange Engine for Spaceborne SAR System
Authors: Lv Hushan , Li Yongrui , Xie Yizhuang , Qiao Tingting
Published: June 2023

Advancements in remote sensing technology and very-large-scale integrated circuit (VLSI) have significantly augmented the real-time processing capabilities of spaceborne synthetic aperture radar (SAR), thereby enhancing terrestrial observational capacities. However, the inefficiency of voluminous data storage and transfer inherent in conventional methods has emerged as a technical hindrance, curtailing real-time processing within SAR imaging systems. To address the constraints of a limited storage bandwidth and inefficient data transfer, this study introduces a three-dimensional cross-mapping approach premised on the equal subdivision of sub-matrices utilizing dual-channel DDR3. This method considerably augments storage access bandwidth and achieves equilibrium in two-dimensional data access. Concurrently, an on-chip data transfer approach predicated on a superscalar pipeline buffer is proposed, mitigating pipeline resource wastage, augmenting spatial parallelism, and enhancing data transfer efficiency. Building upon these concepts, a hardware architecture is designed for the efficient storage and transfer of SAR imaging system data, based on the superscalar pipeline. Ultimately, a data storage and transfer engine featuring register addressing access, configurable granularity, and state monitoring functionalities is realized. A comprehensive imaging processing experiment is conducted via a “CPU + FPGA” heterogeneous SAR imaging system. The empirical results reveal that the storage access bandwidth of the proposed superscalar pipeline-based SAR imaging system’s data efficient storage and transfer engine can attain up to 16.6 GB/s in the range direction and 20.0 GB/s in the azimuth direction. These findings underscore that the storage exchange engine boasts superior storage access bandwidth and heightened data storage transfer efficiency. This considerable enhancement in the processing performance of the entire “CPU + FPGA” heterogeneous SAR imaging system renders it suitable for application within spaceborne SAR real-time processing systems.
Algorithm Fusion for 3D Ground-Penetrating Radar Imaging with Field Examples
Authors: Jeng Yih , Yu Hung-Ming , Chen Chih-Sung
Published: June 2023

Numerous data processing algorithms are available for ground-penetrating radar (GPR) data processing. However, most of the existing processing algorithms are derived from Fourier theory and assume that the system is linear or that data are stationary, which may oversimplify the case. Some nonlinear algorithms are accessible for improvement but generally are for stationary and deterministic systems. To alleviate the dilemma, this study proposes an algorithm fusion scheme that employs standard linear techniques in conjunction with a newer nonlinear and non-stationary method. The linear techniques include linear filtering, migration, and interpolation. The newer method is mainly for nonlinear filtering and image reconstruction. The results can be demonstrated in a two-dimensional single profile (time–distance section) or a 3D visualization if survey lines fulfill the 3D Nyquist sample intervals requirement. Two controlled experiments were conducted to justify the proposed scheme. Then, a field study including two examples was carried out to demonstrate the feasibility of practical applications. Compared with conventional methods, the proposed algorithm fusion provides better visualization and integrative interpretation for GPR imaging.
Deep-Learning-Based Rice Phenological Stage Recognition
Authors: Qin Jiale , Hu Tianci , Yuan Jianghao , Liu Qingzhi , Wang Wensheng , Liu Jie , Guo Leifeng , Song Guozhu
Published: June 2023

Crop phenology is an important attribute of crops, not only reflecting the growth and development of crops, but also affecting crop yield. By observing the phenological stages, agricultural production losses can be reduced and corresponding systems and plans can be formulated according to their changes, having guiding significance for agricultural production activities. Traditionally, crop phenological stages are determined mainly by manual analysis of remote sensing data collected by UAVs, which is time-consuming, labor-intensive, and may lead to data loss. To cope with this problem, this paper proposes a deep-learning-based method for rice phenological stage recognition. Firstly, we use a weather station equipped with RGB cameras to collect image data of the whole life cycle of rice and build a dataset. Secondly, we use object detection technology to clean the dataset and divide it into six subsets. Finally, we use ResNet-50 as the backbone network to extract spatial feature information from image data and achieve accurate recognition of six rice phenological stages, including seedling, tillering, booting jointing, heading flowering, grain filling, and maturity. Compared with the existing solutions, our method guarantees long-term, continuous, and accurate phenology monitoring. The experimental results show that our method can achieve an accuracy of around 87.33%, providing a new research direction for crop phenological stage recognition.
The Impact of Internal Gravity Waves on the Spectra of Turbulent Fluctuations of Vertical Wind Velocity in the Stable Atmospheric Boundary Layer
Authors: Banakh Viktor A. , Smalikho Igor N.
Published: June 2023

The wave turbulence interactions in the stable boundary layer (SBL) of the atmosphere are studied based on data from lidar measurements of the vertical component of wind velocity during the propagation of internal gravity waves (IGWs). It is shown that as an IGW appears, the amplitude of the spectra of turbulent fluctuations of vertical wind velocity nearby the frequency of quasi-harmonic oscillations induced by an IGW increases significantly, sometimes by several orders of magnitude, compared to the spectra in the absence of an IGW. Since IGW energy is transferred to small-scale turbulence, the amplitude of spectra with the Kolmogorov–Obukhov −5/3 power-law frequency dependence in the inertial frequency range increases. The slope of the spectra in the low-frequency range between the frequency of IGW-induced oscillations and the frequency of the lower boundary of the inertial range exceeds the slope, corresponding to the −5/3 power-law dependence. In this frequency range, the spectra obey the power-law dependence on the frequency with the exponent ranging from −4.2 to −1.9. The average value of the exponent −3 is consistent with a low-frequency slope caused by IGWs in turbulent spectra in the lower SBL.
Three-Dimensional Imaging of Vortex Electromagnetic Wave Radar with Integer and Fractional Order OAM Modes
Authors: Liang Jia , Chen Yijun , Zhang Qun , Luo Ying , Li Xiaohui
Published: June 2023

Vortex electromagnetic (EM) waves, with different orbital angular momentum (OAM) modes, have the ability to distinguish the azimuth of radar targets, and then the two-dimensional reconstruction of the targets can be achieved. However, the vortex EM wave imaging methods in published research have no ability to obtain the elevation of the targets, and thus, the three-dimensional spatial structure and richer feature information of the radar target cannot be obtained. Therefore, a three-dimensional imaging method of vortex EM waves with integer- and fractional-order OAM modes is proposed in this paper, which can realize a three-dimensional reconstruction of a radar target based on a uniform circular array (UCA) with two-step imaging. First, the vortex EM wave with integer- and fractional-order OAM modes is generated, and the echo model with different OAM mode types is established. Thereafter, the echo with integer order is processed to obtain the range-azimuth image by fast Fourier transform (FFT). Then, in order to realize the three-dimensional reconstruction, the echo with fractional order is processed by utilizing the butterfly operation and analyzing the characteristics of the fractional Bessel function. Moreover, the resolution and reconstruction precision of the azimuth and elevation are analyzed. Finally, the effectiveness of the proposed method is verified by simulation experiments.
SCM: A Searched Convolutional Metaformer for SAR Ship Classification
Authors: Zhu Hairui , Guo Shanhong , Sheng Weixing , Xiao Lei
Published: June 2023

Ship classification technology using synthetic aperture radar (SAR) has become a research hotspot. Many deep-learning-based methods have been proposed with handcrafted models or using transplanted computer vision networks. However, most of these methods are designed for graphics processing unit (GPU) platforms, leading to limited scope for application. This paper proposes a novel mini-size searched convolutional Metaformer (SCM) for classifying SAR ships. Firstly, a network architecture searching (NAS) algorithm with progressive data augmentation is proposed to find an efficient baseline convolutional network. Then, a transformer classifier is employed to improve the spatial awareness capability. Moreover, a ConvFormer cell is proposed by filling the searched normal convolutional cell into a Metaformer block. This novel cell architecture further improves the feature-extracting capability. Experimental results obtained show that the proposed SCM provides the best accuracy with only 0.46×106 weights, achieving a good trade-off between performance and model size.
RBEF: Ransomware Efficient Public Blockchain Framework for Digital Healthcare Application
Authors: Lakhan Abdullah , Thinnukool Orawit , Groenli Tor Morten , Khuwuthyakorn Pattaraporn
Published: June 2023

These days, the use of digital healthcare has been growing in practice. Getting remote healthcare services without going to the hospital for essential checkups and reports is easy. It is a cost-saving and time-saving process. However, digital healthcare systems are suffering from security and cyberattacks in practice. Blockchain technology is a promising technology that can process valid and secure remote healthcare data among different clinics. However, ransomware attacks are still complex holes in blockchain technology and prevent many healthcare data transactions during the process on the network. The study presents the new ransomware blockchain efficient framework (RBEF) for digital networks, which can identify transaction ransomware attacks. The objective is to minimize transaction delays and processing costs during ransomware attack detection and processing. The RBEF is designed based on Kotlin, Android, Java, and socket programming on the remote process call. RBEF integrated the cuckoo sandbox static and dynamic analysis application programming interface (API) to handle compile-time and runtime ransomware attacks in digital healthcare networks. Therefore, code-, data-, and service-level ransomware attacks are to be detected in blockchain technology (RBEF). The simulation results show that the RBEF minimizes transaction delays between 4 and 10 min and processing costs by 10% for healthcare data compared to existing public and ransomware efficient blockchain technologies healthcare systems.
Linear Segmented Arc-Shaped Piezoelectric Branch Beam Energy Harvester for Ultra-Low Frequency Vibrations
Authors: Piyarathna Iresha Erangani , Thabet Ahmed Mostafa , Ucgul Mustafa , Lemckert Charles , Lim Yee Yan , Tang Zi Sheng
Published: June 2023

Piezoelectric energy harvesting systems have been drawing the attention of the research community over recent years due to their potential for recharging/replacing batteries embedded in low-power-consuming smart electronic devices and wireless sensor networks. However, conventional linear piezoelectric energy harvesters (PEH) are often not a viable solution in such advanced practices, as they suffer from a narrow operating bandwidth, having a single resonance peak present in the frequency spectrum and very low voltage generation, which limits their ability to function as a standalone energy harvester. Generally, the most common PEH is the conventional cantilever beam harvester (CBH) attached with a piezoelectric patch and a proof mass. This study investigated a novel multimode harvester design named the arc-shaped branch beam harvester (ASBBH), which combined the concepts of the curved beam and branch beam to improve the energy-harvesting capability of PEH in ultra-low-frequency applications, in particular, human motion. The key objectives of the study were to broaden the operating bandwidth and enhance the harvester’s effectiveness in terms of voltage and power generation. The ASBBH was first studied using the finite element method (FEM) to understand the operating bandwidth of the harvester. Then, the ASBBH was experimentally assessed using a mechanical shaker and real-life human motion as excitation sources. It was found that ASBBH achieved six natural frequencies within the ultra-low frequency range (<10 Hz), in comparison with only one natural frequency achieved by CBH within the same frequency range. The proposed design significantly broadened the operating bandwidth, favouring ultra-low-frequency-based human motion applications. In addition, the proposed harvester achieved an average output power of 427 μW at its first resonance frequency under 0.5 g acceleration. The overall results of the study demonstrated that the ASBBH design can achieve a broader operating bandwidth and significantly higher effectiveness, in comparison with CBH.
Recurrent Network Solutions for Human Posture Recognition Based on Kinect Skeletal Data
Authors: Guerra Bruna Maria Vittoria , Ramat Stefano , Beltrami Giorgio , Schmid Micaela
Published: June 2023

Ambient Assisted Living (AAL) systems are designed to provide unobtrusive and user-friendly support in daily life and can be used for monitoring frail people based on various types of sensors, including wearables and cameras. Although cameras can be perceived as intrusive in terms of privacy, low-cost RGB-D devices (i.e., Kinect V2) that extract skeletal data can partially overcome these limits. In addition, deep learning-based algorithms, such as Recurrent Neural Networks (RNNs), can be trained on skeletal tracking data to automatically identify different human postures in the AAL domain. In this study, we investigate the performance of two RNN models (2BLSTM and 3BGRU) in identifying daily living postures and potentially dangerous situations in a home monitoring system, based on 3D skeletal data acquired with Kinect V2. We tested the RNN models with two different feature sets: one consisting of eight human-crafted kinematic features selected by a genetic algorithm, and another consisting of 52 ego-centric 3D coordinates of each considered skeleton joint, plus the subject’s distance from the Kinect V2. To improve the generalization ability of the 3BGRU model, we also applied a data augmentation method to balance the training dataset. With this last solution we reached an accuracy of 88%, the best we achieved so far.
Binary-Phase vs. Frequency Modulated Radar Measured Performances for Automotive Applications
Authors: Caffa Mattia , Biletta Francesco , Maggiora Riccardo
Published: June 2023

Radars have been widely deployed in cars in recent years, for advanced driving assistance systems. The most popular and studied modulated waveform for automotive radar is the frequency-modulated continuous wave (FMCW), due to FMCW radar technology’s ease of implementation and low power consumption. However, FMCW radars have several limitations, such as low interference resilience, range-Doppler coupling, limited maximum velocity with time-division multiplexing (TDM), and high-range sidelobes that reduce high-contrast resolution (HCR). These issues can be tackled by adopting other modulated waveforms. The most interesting modulated waveform for automotive radar, which has been the focus of research in recent years, is the phase-modulated continuous wave (PMCW): this modulated waveform has a better HCR, allows large maximum velocity, permits interference mitigation, thanks to codes orthogonality, and eases integration of communication and sensing. Despite the growing interest in PMCW technology, and while simulations have been extensively performed to analyze and compare its performance to FMCW, there are still only limited real-world measured data available for automotive applications. In this paper, the realization of a 1 Tx/1 Rx binary PMCW radar, assembled with connectorized modules and an FPGA, is presented. Its captured data were compared to the captured data of an off-the-shelf system-on-chip (SoC) FMCW radar. The radar processing firmware of both radars were fully developed and optimized for the tests. The measured performances in real-world conditions showed that PMCW radars manifest better behavior than FMCW radars, regarding the above-mentioned issues. Our analysis demonstrates that PMCW radars can be successfully adopted by future automotive radars.
User Experience Design for Social Robots: A Case Study in Integrating Embodiment
Authors: Corrales-Paredes Ana , Sanz Diego Ortega , Terrón-López María-José , Egido-García Verónica
Published: June 2023

Social robotics is an emerging field with a high level of innovation. For many years, it was a concept framed in the literature and theoretical approaches. Scientific and technological advances have made it possible for robots to progressively make their way into different areas of our society, and now, they are ready to make the leap out of the industry and extend their presence into our daily lives. In this sense, user experience plays a fundamental role in achieving a smooth and natural interaction between robots and humans. This research focused on the user experience approach in terms of the embodiment of a robot, centring on its movements, gestures, and dialogues. The aim was to investigate how the interaction between robotic platforms and humans takes place and what differential aspects should be considered when designing the robot tasks. To achieve this objective, a qualitative and quantitative study was conducted based on a real interview between several human users and the robotic platform. The data were gathered by recording the session and having each user complete a form. The results showed that participants generally enjoyed interacting with the robot and found it engaging, which led to greater trust and satisfaction. However, delays and errors in the robot’s responses caused frustration and disconnection. The study found that incorporating embodiment into the design of the robot improved the user experience, and the robot’s personality and behaviour were significant factors. It was concluded that robotic platforms and their appearance, movements, and way of communicating have a decisive influence on the user’s opinion and the way they interact.
A Customized Energy Management System for Distributed PV, Energy Storage Units, and Charging Stations on Kinmen Island of Taiwan
Authors: Lee Hsi-Chieh , Liu Hua-Yueh , Lin Tsung-Chieh , Lee Chih-Ying
Published: June 2023

Kinmen, the famous Cold War island also known as Quemoy, is a typical island with isolated power grids. It considers the promotion of renewable energy and electric charging vehicles to be two essential strategies to achieve the goal of a low-carbon island and smart grid. With this motivation in mind, the main objective of this study is to design and deploy an energy management system for hundreds of current PV sites distributed on the island, energy storage systems, and charging stations on the island. In addition, the real-time acquisition of the data for power generation, power storage, and power consumption systems will be used for future demand and response analysis. Moreover, the accumulated dataset will also be utilized for the forecast or prediction of renewable energy generated by the PV systems or power consumed by the battery units or charging stations. The results of this study are promising since a practical, robust, and workable system and database are developed and implemented with a variety of Internet of Things (IoT), data transmission technologies, and the hybrid of on-premises and cloud servers. Users of the proposed system can remotely access the visualized data through the user-friendly web-based and Line bot interfaces seamlessly.
Multimodality Video Acquisition System for the Assessment of Vital Distress in Children
Authors: Boivin Vincent , Shahriari Mana , Faure Gaspar , Mellul Simon , Tiassou Edem Donatien , Jouvet Philippe , Noumeir Rita
Published: June 2023

In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient’s numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management.
Exploring Research on the Construction and Application of Knowledge Graphs for Aircraft Fault Diagnosis
Authors: Tang Xilang , Chi Guo , Cui Lijie , Ip Andrew W. H. , Yung Kai Leung , Xie Xiaoyue
Published: June 2023

Fault diagnosis is crucial for repairing aircraft and ensuring their proper functioning. However, with the higher complexity of aircraft, some traditional diagnosis methods that rely on experience are becoming less effective. Therefore, this paper explores the construction and application of an aircraft fault knowledge graph to improve the efficiency of fault diagnosis for maintenance engineers. Firstly, this paper analyzes the knowledge elements required for aircraft fault diagnosis, and defines a schema layer of a fault knowledge graph. Secondly, with deep learning as the main method and heuristic rules as the auxiliary method, fault knowledge is extracted from structured and unstructured fault data, and a fault knowledge graph for a certain type of craft is constructed. Finally, a fault question-answering system based on a fault knowledge graph was developed, which can accurately answer questions from maintenance engineers. The practical implementation of our proposed methodology highlights how knowledge graphs provide an effective means of managing aircraft fault knowledge, ultimately assisting engineers in identifying fault roots accurately and quickly.
Attention Recurrent Neural Network-Based Severity Estimation Method for Early-Stage Fault Diagnosis in Robot Harness Cable
Authors: Kim Heonkook , Lee Hojin , Kim Seongyun , Kim Sang Woo
Published: June 2023

Cable is crucial to the control and instrumentation of machines and facilities. Therefore, early diagnosis of cable faults is the most effective approach to prevent system downtime and maximize productivity. We focused on a “soft fault state”, which is a transient state that eventually becomes a permanent fault —open-circuit and short-circuit. However, the issue of soft fault diagnosis has not been considered enough in previous research, which could not provide crucial information, such as fault severity, to support maintenance. In this study, we focused on solving soft fault problem by estimating fault severity to diagnose early-stage faults. The proposed diagnosis method comprised a novelty detection and severity estimation network. The novelty detection part is specially designed to deal with varying operating conditions of industrial applications. First, an autoencoder calculates anomaly scores to detect faults using three-phase currents. If a fault is detected, a fault severity estimation network, wherein long short-term memory and attention mechanisms are integrated, estimates the fault severity based on the time-dependent information of the input. Accordingly, no additional equipment, such as voltage sensors and signal generators, is required. The conducted experiments demonstrated that the proposed method successfully distinguishes seven different soft fault degrees.
Green Infrastructure as an Effective Tool for Urban Adaptation—Solutions from a Big City in a Postindustrial Region
Authors: Janiszek Monika , Krzysztofik Robert
Published: June 2023

Adaptation to climate change is becoming one of the main paradigms for how cities function and develop. The significant role of green infrastructure (GI) as a tool for cities to adapt to climate change is increasingly emphasized among practitioners of spatial planning and in the research literature. Thus, despite the local impact, green infrastructure planning necessitates the creation of a holistic and integrated city management system. The aim of the article is to identify the effects generated by projects implemented in the field of green infrastructure in big cities of post-industrial regions and to formulate determinants and barriers limiting the strengthening of cities’ adaptive capacity to climate change. In the methodological dimension, the article is based on the desk-research method (analysis of project documentation and specialist literature), logical reasoning and the case study method, enriched with a series of interviews and observation of the study area to present the selected projects implemented as part of green infrastructure. Solutions based on nature, green infrastructure and the adaptation of ecosystems are of strategic importance for the challenges of reducing the negative effects of urban heat islands and the risk of flooding, rational space management, regeneration of degraded urban spaces, the coexistence of urban and green space and, consequently, increasing housing, as well as cultural and recreation areas. This is especially true of post-industrial regions, such as the Katowice Conurbation in Poland, to which the examples presented here refer.
Two-Stage Grid-Connected Frequency Regulation Control Strategy Based on Photovoltaic Power Prediction
Authors: Wang Shuzheng , Zhu Haiming , Zhang Shaowen
Published: June 2023

The large number of photovoltaics connected to the distribution network via power electronic converters squeezes the functional space of traditional synchronous generators in the power system and reduces the inertia of the network itself. However, due to the random and fluctuating nature of PV power generation, different types of meteorological conditions can also affect the inertia support capability of PV output power. Therefore, this paper proposes a frequency regulation control strategy based on the dynamic characteristics of the grid-side DC capacitor. Firstly, the control strategy of the grid-side inverter is improved and the mechanism of the frequency dynamic response model under PV penetration is analysed. Secondly, data from different weather types are correlated and analysed to predict PV power, and wireless sensor technology is used to introduce the data signals into the control link. Finally, a simulation model of a two-stage PV power generation system is developed and the fast-response capability of the system under different control parameters when the load is increased or decreased is analysed. The results show that under the proposed frequency regulation strategy, the larger the regulation coefficient and virtual inertia time constant, the greater the virtual inertia provided by the PV power generation, which improves the stability of the distribution network.