bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Deployment of MobileNetV3 Model in Edge Computing Devices Using RGB Color Images for Varietal Classification of Chickpea
Authors: Saha Dhritiman , Mangukia Meetkumar Pareshbhai , Manickavasagan Annamalai
Published: July 2023

Chickpeas are one of the most widely consumed pulses globally because of their high protein content. The morphological features of chickpea seeds, such as colour and texture, are observable and play a major role in classifying different chickpea varieties. This process is often carried out by human experts, and is time-consuming, inaccurate, and expensive. The objective of the study was to design an automated chickpea classifier using an RGB-colour-image-based model for considering the morphological features of chickpea seed. As part of the data acquisition process, five hundred and fifty images were collected per variety for four varieties of chickpea (CDC-Alma, CDC-Consul, CDC-Cory, and CDC-Orion) using an industrial RGB camera and a mobile phone camera. Three CNN-based models such as NasNet-A (mobile), MobileNetV3 (small), and EfficientNetB0 were evaluated using a transfer-learning-based approach. The classification accuracy was 97%, 99%, and 98% for NasNet-A (mobile), MobileNetV3 (small), and EfficientNetB0 models, respectively. The MobileNetV3 model was used for further deployment on an Android mobile and Raspberry Pi 4 devices based on its higher accuracy and light-weight architecture. The classification accuracy for the four chickpea varieties was 100% while the MobileNetV3 model was deployed on both Android mobile and Raspberry Pi 4 platforms.
Physics-Informed Neural Networks for Bingham Fluid Flow Simulation Coupled with an Augmented Lagrange Method
Authors: Zhang Jianying
Published: July 2023

As a class of non-Newtonian fluids with yield stresses, Bingham fluids possess both solid and liquid phases separated by implicitly defined non-physical yield surfaces, which makes the standard numerical discretization challenging. The variational reformulation established by Duvaut and Lions, coupled with an augmented Lagrange method (ALM), brings about a finite element approach, whereas the inevitable local mesh refinement and preconditioning of the resulting large-scaled ill-conditioned linear system can be involved. Inspired by the mesh-free feature and architecture flexibility of physics-informed neural networks (PINNs), an ALM-PINN approach to steady-state Bingham fluid flow simulation, with dynamically adaptable weights, is developed and analyzed in this work. The PINN setting enables not only a pointwise ALM formulation but also the learning of families of (physical) parameter-dependent numerical solutions through one training process, and the incorporation of ALM into a PINN induces a more feasible loss function for deep learning. Numerical results obtained via the ALM-PINN training on one- and two-dimensional benchmark models are presented to validate the proposed scheme. The efficacy and limitations of the relevant loss formulation and optimization algorithms are also discussed to motivate some directions for future research.
New Aspects on the Solvability of a Multidimensional Functional Integral Equation with Multivalued Feedback Control
Authors: El-Sayed Ahmed M. A. , Hashem Hind H. G. , Al-Issa Shorouk M.
Published: July 2023

The current study demonstrates the existence of solutions to a multidimensional functional integral equation with multivalued feedback. We seek solutions for the multidimensional functional problem that is defined, continuous, and bounded on the semi-infinite interval. Our proof is based on the technique associated with measures of noncompactness by a given modulus of continuity in the space in BC(R+). Also, some sufficient conditions are investigated to demonstrate the asymptotic stability of the solutions to that multidimensional functional equation. Additionally, we give an example and some particular cases to illustrate our outcomes.
Quantification of Lithium Plating in Lithium-Ion Batteries Based on Impedance Spectrum and Artificial Neural Network
Authors: Bai Miao , Lyu Chao , Yang Dazhi , Hinds Gareth
Published: July 2023

Accurate evaluation of the health status of lithium-ion batteries must be deemed as of great significance, insofar as the utility and safety of batteries are of concern. Lithium plating, in particular, is notoriously known to be a chemical reaction that can cause deterioration in, or even fatal hazards to, the health of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS), which has distinct advantages such as being fast and non-destructive over its competitors, suffices in detecting lithium plating and thus has been attracting increasing attention in the field of battery management, but its ability of assessing quantitatively the degree of lithium plating remains largely unexplored hitherto. On this point, this work seeks to narrow that gap by proposing an EIS-based method that can quantify the degree of lithium plating. The core conception is to eventually circumvent the reliance on state-of-health measurement, and use instead the impedance spectrum to acquire an estimate on battery capacity loss. To do so, the effects of solid electrolyte interphase formation and lithium plating on battery capacity must be first decoupled, so that the mass of lithium plating can be quantified. Then, based on an impedance spectrum measurement, the parameters of the fractional equivalent circuit model (ECM) of the battery can be identified. These fractional ECM parameters are received as inputs by an artificial neural network, which is tasked with establishing a correspondence between the model parameters and the mass of lithium plating. The empirical part of the work revolves around the data collected from an aging experiment, and the validity of the proposed method is truthfully attested by dismantling the batteries, which is otherwise not needed during the actual uptake of the method.
Hip Joint Angles and Moments during Stair Ascent Using Neural Networks and Wearable Sensors
Authors: McCabe Megan V. , Van Citters Douglas W. , Chapman Ryan M.
Published: July 2023

End-stage hip joint osteoarthritis treatment, known as total hip arthroplasty (THA), improves satisfaction, life quality, and activities of daily living (ADL) function. Postoperatively, evaluating how patients move (i.e., their kinematics/kinetics) during ADL often requires visits to clinics or specialized biomechanics laboratories. Prior work in our lab and others have leveraged wearables and machine learning approaches such as artificial neural networks (ANNs) to quantify hip angles/moments during simple ADL such as walking. Although level-ground ambulation is necessary for patient satisfaction and post-THA function, other tasks such as stair ascent may be more critical for improvement. This study utilized wearable sensors/ANNs to quantify sagittal/frontal plane angles and moments of the hip joint during stair ascent from 17 healthy subjects. Shin/thigh-mounted inertial measurement units and force insole data were inputted to an ANN (2 hidden layers, 10 total nodes). These results were compared to gold-standard optical motion capture and force-measuring insoles. The wearable-ANN approach performed well, achieving rRMSE = 17.7% and R2 = 0.77 (sagittal angle/moment: rRMSE = 17.7 ± 1.2%/14.1 ± 0.80%, R2 = 0.80 ± 0.02/0.77 ± 0.02; frontal angle/moment: rRMSE = 26.4 ± 1.4%/12.7 ± 1.1%, R2 = 0.59 ± 0.02/0.93 ± 0.01). While we only evaluated healthy subjects herein, this approach is simple and human-centered and could provide portable technology for quantifying patient hip biomechanics in future investigations.
Quantitative Characterization of Gait Patterns in Individuals with Spinocerebellar Ataxia 38
Authors: Pau Massimiliano , Porta Micaela , Pau Chiara , Tacconi Paolo , Sanna Angela
Published: July 2023

Spinocerebellar ataxia 38 (SCA 38) is a rare autosomal neurological disease whose clinical features include, among others, severe gait disturbances that have not yet been fully characterized. In this study, we employed a computerized 3D gait analysis to obtain spatio-temporal parameters of gait and the kinematics in the sagittal plane in the hip, knee, and ankle joints of seven individuals with SCA 38, which were then compared with those of twenty unaffected individuals matched for age, sex, and anthropometric features. The results show that, in comparison with unaffected individuals, those with SCA 38 are characterized by a significantly reduced speed, stride length, and duration of the swing phase, as well as an increased step width and stance and double support phase durations. The point-by-point comparison of the angular trends at the hip, knee, and ankle joints revealed significant alterations during most part of the stance phase for hip joint and at pre-swing/swing phases for knee and ankle joints. For these latter joints, a significantly reduced dynamic range of motion was also found. Such findings provide some new insights into hip and knee kinematics for this specific form of ataxia and may be useful for monitoring the disease’s progression and designing specific, tailored rehabilitative interventions.
Modern Advances in Microendodontics: The State of the Art
Authors: Iandolo Alfredo
Published: July 2023

The concept of “minimally invasive” advances is becoming increasingly popular in the endodontic field [...]
Enhancing Health and Public Health through Machine Learning: Decision Support for Smarter Choices
Authors: Rodrigues Pedro Miguel , Madeiro João Paulo , Marques João Alexandre Lobo
Published: July 2023

In recent years, the integration of Machine Learning (ML) techniques in the field of healthcare and public health has emerged as a powerful tool for improving decision-making processes [...]
Specific Blood Plasma Circulating miRs Are Associated with the Physiological Impact of Total Fish Meal Replacement with Soybean Meal in Diets for Rainbow Trout (Oncorhynchus mykiss)
Authors: Toledo-Solís Francisco Javier , Larrán Ana M. , Ortiz-Delgado Juan B. , Sarasquete Carmen , Dias Jorge , Morais Sofia , Fernández Ignacio
Published: July 2023

High dietary SBM content is known to induce important physiological alterations, hampering its use as a major FM alternative. Rainbow trout (Oncorhynchus mykiss) juveniles were fed two experimental diets during 9 weeks: (i) a FM diet containing 12% FM; and (ii) a vegetable meal (VM) diet totally devoid of FM and based on SBM (26%). Fish fed the VM diet did not show reduced growth performance when compared with fish fed the FM diet. Nevertheless, fish fed the VM diet had an increased viscerosomatic index, lower apparent fat digestibility, higher aminopeptidase enzyme activity and number of villi fusions, and lower α-amylase enzyme activity and brush border integrity. Small RNA-Seq analysis identified six miRs (omy-miR-730a-5p, omy-miR-135c-5p, omy-miR-93a-3p, omy-miR-152-5p, omy-miR-133a-5p, and omy-miR-196a-3p) with higher expression in blood plasma from fish fed the VM diet. Bioinformatic prediction of target mRNAs identified several overrepresented biological processes known to be associated with high dietary SBM content (e.g., lipid metabolism, epithelial integrity disruption, and bile acid status). The present research work increases our understanding of how SBM dietary content has a physiological impact in farmed fish and suggests circulating miRs might be suitable, integrative, and less invasive biomarkers in fish.
Chromosome-Level Analysis of the Pelochelys cantorii Genome Provides Insights to Its Immunity, Growth and Longevity
Authors: Liu Xiaoli , Liu Haiyang , Wang Yakun , Li Mingzhi , Ji Liqin , Wang Kaikuo , Wei Chengqing , Li Wei , Chen Chen , Yu Lingyun , Zhu Xinping , Hong Xiaoyou
Published: July 2023

The Asian giant soft-shelled turtle, Pelochelys cantorii (Trionychidae), is one of the largest aquatic turtles in China and was designated as a First-Grade Protected Animal in China in 1989. Previous investigation based on a combination of Illumina short-read, PacBio long-read and Hi-C scaffolding technologies acquired a high-quality chromosome-level genome of Pc. cantorii. In this study, comparative genomic analysis between Pc. cantorii and 16 other vertebrate genomes indicated that turtles separated from the ancestor of archosaurians approximately 256.6 (95% highest posterior density interval, 263.6–251.9) million years ago (Mya) (Upper Permian to Triassic) and that Pc. cantorii separated from the ancestor of Pd. sinensis and R. swinhoei approximately 59.3 (95% highest posterior density interval, 64.3–54.3) Mya. Moreover, several candidate genes, such as VWA5A, ABCG2, A2M and IGSF1, associated with tumor suppression, growth and age were expanded, implicating their potential roles in the exceptional longevity of turtles. This new chromosome-level assembly has important scientific value in the study of conservation of Pc. cantorii and also enriches the evolutionary investigation of turtle species.
Systemic Photoprotection in Melanoma and Non-Melanoma Skin Cancer
Authors: Hyeraci Mariafrancesca , Papanikolau Elena Sofia , Grimaldi Marta , Ricci Francesco , Pallotta Sabatino , Monetta Rosanna , Minafò Ylenia Aura , Di Lella Giovanni , Galdo Giovanna , Abeni Damiano , Fania Luca , Dellambra Elena
Published: July 2023

Non-melanoma skin cancers (NMSCs), which include basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and actinic keratosis (AK), are the most common cancer diseases in the Caucasian race. If diagnosed late and improperly treated, BCC and SCC can become locally advanced and metastasize. Malignant melanoma (MM) is less frequent but more lethal than NMSC. Given the individual and social burdens of skin cancers, performing an adequate prevention is needed. Ultraviolet (UV) ray exposure is one of the main risk factors for skin cancer. Thus, the first-choice prevention strategy is represented by photoprotection that can be both topical and systemic. The latter consists of the oral administration of molecules which protect human skin against the damaging effects of UV rays, acting through antioxidant, anti-inflammatory, or immunomodulator mechanisms. Although several compounds are commonly used for photoprotection, only a few molecules have demonstrated their effectiveness in clinical trials and have been included in international guidelines for NMSC prevention (i.e., nicotinamide and retinoids). Moreover, none of them have been demonstrated as able to prevent MM. Clinical and preclinical data regarding the most common compounds used for systemic photoprotection are reported in this review, with a focus on the main mechanisms involved in their photoprotective properties.
Special Issue: Principal Challenges in the Adjuvant Treatment of Glioblastoma
Authors: Halatsch Marc-Eric
Published: July 2023

Despite advances in local treatments, such as supramaximal resection (even in eloquent locations [...]
Continuous 3D Printing of Biomimetic Beetle Mandible Structure with Long Bundles of Aramid Fiber Composites
Authors: Li Shuigen , Liu Chang , Zhang Yulong , Zhang Wei , Xu Xuefei , Lin Zhaohua , Liang Yunhong
Published: July 2023

Fiber-reinforced composites are an ideal high-performance composite material made from a combination of high-strength continuous fibers and a polymer matrix. Compared to short cut fibers, continuous long strand fibers can improve the mechanical properties of fiber composites more effectively. Herein, continuous aramid fiber-reinforced PLA filaments with fiber centering were prepared by modifying the outlet design of a desktop-grade thermoplastic single-screw melt extruder. Inspired by the cross-laminated structure of a beetle’s mandible fibers, a biomimetic structure composite was printed, which demonstrates a significant influence on the mechanical properties. The G-code printing program was developed, and the microstructure of the fracture surface of the specimen was analyzed. The uniform and orderly arrangement of aramid fibers within the PLA resin-based 3D-printed specimen was found. Consequentially, the bionic composites exhibits a 12% increase in tensile strength and a 5% increase in impact toughness, confirming the feasibility of utilizing continuous 3D printing to manufacture long bundles of aramid fiber composite filaments for enhanced mechanical performances.
Multifunctionality in Nature: Structure–Function Relationships in Biological Materials
Authors: Zhong Jiaming , Huang Wei , Zhou Huamin
Published: July 2023

Modern material design aims to achieve multifunctionality through integrating structures in a diverse range, resulting in simple materials with embedded functions. Biological materials and organisms are typical examples of this concept, where complex functionalities are achieved through a limited material base. This review highlights the multiscale structural and functional integration of representative natural organisms and materials, as well as biomimetic examples. The impact, wear, and crush resistance properties exhibited by mantis shrimp and ironclad beetle during predation or resistance offer valuable inspiration for the development of structural materials in the aerospace field. Investigating cyanobacteria that thrive in extreme environments can contribute to developing living materials that can serve in places like Mars. The exploration of shape memory and the self-repairing properties of spider silk and mussels, as well as the investigation of sensing–actuating and sensing–camouflage mechanisms in Banksias, chameleons, and moths, holds significant potential for the optimization of soft robot designs. Furthermore, a deeper understanding of mussel and gecko adhesion mechanisms can have a profound impact on medical fields, including tissue engineering and drug delivery. In conclusion, the integration of structure and function is crucial for driving innovations and breakthroughs in modern engineering materials and their applications. The gaps between current biomimetic designs and natural organisms are also discussed.
Self-Healing Silicone Materials: Looking Back and Moving Forward
Authors: Deriabin Konstantin V. , Filippova Sofia S. , Islamova Regina M.
Published: July 2023

This review is dedicated to self-healing silicone materials, which can partially or entirely restore their original characteristics after mechanical or electrical damage is caused to them, such as formed (micro)cracks, scratches, and cuts. The concept of self-healing materials originated from biomaterials (living tissues) capable of self-healing and regeneration of their functions (plants, human skin and bones, etc.). Silicones are ones of the most promising polymer matrixes to create self-healing materials. Self-healing silicones allow an increase of the service life and durability of materials and devices based on them. In this review, we provide a critical analysis of the current existing types of self-healing silicone materials and their functional properties, which can be used in biomedicine, optoelectronics, nanotechnology, additive manufacturing, soft robotics, skin-inspired electronics, protection of surfaces, etc.
Seismic Performance of RC Moment Frame Buildings Considering SSI Effects: A Case Study of the New Venezuelan Seismic Code
Authors: Mata Ramón , Nuñez Eduardo , Hernández Matías , Correa Claudio , Bustamante Guillermo
Published: July 2023

The Soil–Structure Interaction (SSI) effect has been widely evidenced during several earthquakes around the world. In the Venezuelan context, the seismic event in Caracas in 1967 showed the significant consequences of designing buildings without considering the SSI effect. Nevertheless, limited research on the seismic performance of concrete moment frames (commonly used as structural systems in office and residential buildings in Venezuela and Latin America) considering the SSI effects has been developed, although there have been continuous updates to the Venezuelan Seismic Code. In this research, the influence of the SSI on the seismic performance of RC moment frame buildings designed according to the New Venezuelan Seismic Code was studied. An extensive numerical study of 3D buildings using concrete moment frames supported by mat foundations on sandy and clayey soils was performed. The response spectrum method, non-linear static analysis, and non-linear dynamic analysis were used to assess the seismic response of the archetypes studied. The results show that SSI effects can have a significant impact on the seismic response of RC moment frame buildings, increasing the interstory drift ratio and decreasing the shear forces. As is shown in fragility curves, the probability of collapse increases for cases with flexible bases in comparison to the cases of models with fixed bases. Additionally, in the 24-story archetype, the fixed-base model reached a maximum probability of collapse. Finally, a new proposal for the reduction of the strength-reduction factor (R) must be incorporated into the Venezuelan Seismic Code to improve the safety of the structures. Limitations in the use of RC moment frames must be incorporated for high-rise buildings since, as the present work demonstrates, for high-period structures, the normative provisions are not reached.
Role of Ubiquitin Ligases and Conjugases in Targeted Cancer Therapy
Authors: Vriend Jerry
Published: July 2023

The ubiquitin proteasome system regulates the activity of many short-lived proteins in cells [...]
BiVO4 Photoanodes Modified with Synergetic Effects between Heterojunction Functionalized FeCoOx and Plasma Au Nanoparticles
Authors: Chen Huangzhaoxiang , Zhang Qian , Abbas Aumber , Zhang Wenran , Huang Shuzhou , Li Xiangguo , Liu Shenghua , Shuai Jing
Published: July 2023

The design and development of high-performance photoanodes are the key to efficient photoelectrochemical (PEC) water splitting. Based on the carrier transfer characteristics and localized surface plasmon resonance effect of noble metals, gold nanoparticles (AuNPs) have been used to improve the performance of photoanodes. In this study, a novel efficient composite BiVO4/Au/FeCoOx photoanode is constructed, and the quantitative analysis of its performance is systematically conducted. The results reveal that the co-modification of AuNPs and FeCoOx plays a synergetic role in enhancing the absorption of ultraviolet and visible light of BiVO4, which is mainly attributed to the localized surface plasmon resonance effect induced by AuNPs and the extended light absorption edge position induced by the BiVO4/FeCoOx heterojunction. The BiVO4/Au/FeCoOx photoanode exhibits a high photocurrent density of 4.11 mA cm−2 at 1.23 V versus RHE at room temperature under AM 1.5 G illumination, which corresponds to a 299% increase compared to a pristine BiVO4 photoanode. These results provide practical support for the design and preparation of PEC photoanodes decorated with AuNPs and FeCoOx.
The Sonocatalytic Activation of Persulfates on Iron Nanoparticle Decorated Zeolite for the Degradation of 1,4-Dioxane in Aquatic Environments
Authors: Malkapuram Surya Teja , Sonawane Shirish Hari , Rayaroth Manoj P. , Seepana Murali Mohan , Manickam Sivakumar , Karczewski Jakub , Boczkaj Grzegorz
Published: July 2023

In the chemical industry, 1,4-diethylene dioxide, commonly called dioxane, is widely used as a solvent as well as a stabilizing agent for chlorinated solvents. Due to its high miscibility, dioxane is a ubiquitous water contaminant. This study investigates the effectiveness of catalyst- and ultrasound (US)-assisted persulfate (PS) activation with regard to degrading dioxane. As a first step, a composite catalyst was prepared using zeolite. A sonochemical dispersion and reduction method was used to dope zeolite with iron nanoparticles (FeNP/Z). In the subsequent study, the reaction kinetics of dioxane degradation following the single-stage and two-stage addition of PS was examined in the presence of a catalyst. Using GC-MS analysis, intermediate compounds formed from dioxane degradation were identified, and plausible reaction pathways were described. Upon 120 min of sonication in the presence of a catalyst with a two-stage injection of PS, 95% 100 mg/L dioxane was degraded. Finally, the estimated cost of treatment is also reported in this study. Sonolytically activated PS combined with a FeNP/Z catalyst synergizes the remediation of biorefractory micropollutants such as dioxane.
Digitalization and Spatial Documentation of Post-Earthquake Temporary Housing in Central Italy: An Integrated Geomatic Approach Involving UAV and a GIS-Based System
Authors: Tonti Ilaria , Lingua Andrea Maria , Piccinini Fabio , Pierdicca Roberto , Malinverni Eva Savina
Published: July 2023

Geoinformation and aerial data collection are essential during post-earthquake emergency response. This research focuses on the long-lasting spatial impacts of temporary solutions, which have persisted in regions of Central Italy affected by catastrophic seismic events over the past 25 years, significantly and permanently altering their landscapes. The paper analyses the role of geomatic and photogrammetric tools in documenting the emergency process and projects in post-disaster phases. An Atlas of Temporary Architectures is proposed, which defines a common semantic and geometric codification for mapping temporary housing from territorial to urban and building scales. The paper presents an implementation of attribute specification in existing official cartographic data, including geometric entities in a 3D GIS data model platform for documenting and digitalising these provisional contexts. To achieve this platform, UAV point clouds are integrated with non-metric data to ensure a complete description in a multiscalar approach. Accurate topographic modifications can be captured by extracting very high-resolution orthophotos and elevation models (DSM and DTM). The results have been validated in Visso (Macerata), a small historical mountain village in Central Italy which was heavily damaged by the seismic events of 2016/2017. The integrated approach overcomes the existing gaps and emphasizes the importance of managing heterogeneous geospatial emergency data for classification purposes. It also highlights the need to enhance an interoperable knowledge base method for post-disaster temporary responses. By combining geomatic tools with architectural studies, these visualization techniques can support national and local organizations responsible for post-earthquake management through a 3D modelling method to aid future transformations or interventions following other natural disasters.
The Challenges Facing Irish-Medium Primary and Post-Primary Schools When Implementing a Whole-School Approach to Meeting the Additional Education Needs of Their Students
Authors: Nic Aindriú Sinéad , Ó Duibhir Pádraig
Published: July 2023

The literature states the importance of adopting a whole-school approach to inclusion and for meeting the needs of all students. This study investigated the challenges faced by Irish-medium (IM) primary and post-primary schools in relation to providing a whole-school approach to inclusion. This was achieved through a mixed methods study where a stratified sample of teachers from IM schools (N = 56) undertook an anonymous online survey in the first stage. In the second stage, primary and post-primary teachers (N = 31) undertook semi-structured individual interviews to provide in-depth information regarding the data collected in the survey. The findings suggest that like immersion schools internationally, IM schools need more resources through the medium of Irish in relation to assessment, evidence-based interventions, and teaching/learning resources.
Research and Trends in Entrepreneurship Education
Authors: Jardim Jacinto , Sousa Maria José
Published: July 2023

Entrepreneurship education has become increasingly crucial in today’s fast-paced and ever-evolving global economy [...]
Proposal for ‘Video Design Study’ to Train the Next Generation of Visual Creators—An Examination of Video Design Study and Its Influence on a Toyota Special Exhibition
Authors: Sugimori Junko , Arakawa Toshiya
Published: July 2023

Presently, in the video production community, large amounts of content are being created. Accordingly, both Arduino Uno and Raspberry Pi are significantly influencing the progression of media arts. Considering this matter, research on media arts is quite important with regard to the estimation and conception of future trends in video content and artwork. Despite this, all content that is created will eventually be forgotten over time. Therefore, when applying new technology and creating new video content, it is necessary to archive a particular movie creator’s hard work in order to save instructions for later generations on how to “design” video content. This study considers the example of projection mapping and elaborates on the importance of Video Design Study. Notably, “clarification of creating method and process”, which is a very important aspect of Video Design Study, is emphasized in this paper. In addition, a specific example of Video Design Study is introduced via the following special exhibitions: “Dreams of Kiichiro” and “Evolution of Toyota: Dreams of Kiichiro and After That.”
Comparison of Gamma Irradiation Effects on Short Circuit Characteristics of SiC MOSFET Power Devices between Planar and Trench Structures
Authors: Shu Lei , Liao Huai-Lin , Wu Zi-Yuan , Li Yan-Yan , Fang Xing-Yu , Liang Shi-Wei , Li Tong-De , Wang Liang , Wang Jun , Zhao Yuan-Fu
Published: July 2023

The short circuit withstand energy (SCWE) variations, and short circuit withstand time (SCWT) variations, of planar and trench silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFET) power devices are studied after exposure to a total ionizing dose (TID). The results for ON bias are explored. The SCWE and SCWT are studied for planar and trench SiC MOSFET power devices tested for TID with gamma irradiation. A higher degradation phenomenon for the SCWE and SCWT are observed for the planar SiC MOSFET. The physical mechanisms for these variations are analyzed and confirmed by technology computer-aided design (TCAD) simulation.
A Deep-Learning-Based Approach to Keystroke-Injection Payload Generation
Authors: Gurčinas Vitalijus , Dautartas Juozas , Janulevičius Justinas , Goranin Nikolaj , Čenys Antanas
Published: July 2023

Investigation and detection of cybercrimes has been in the spotlight of cybersecurity research for as long as the topic has existed. Modern methods are required to keep up with the pace of the technology and toolset used to facilitate these crimes. Keystroke-injection attacks have been an issue due to the limitations of hardware and software up until recently. This paper presents comprehensive research on keystroke-injection payload generation that proposes the use of deep learning to bypass the security of keystroke-based authentication systems focusing on both fixed-text and free-text scenarios. In addition, it specifies the potential risks associated with keystroke-injection attacks. To ensure the legitimacy of the investigation, a model is proposed and implemented within this context. The results of the implemented implant model inside the keyboard indicate that deep learning can significantly improve the accuracy of keystroke dynamics recognition as well as help to generate effective payload from a locally collected dataset. The results demonstrate favorable accuracy rates, with reported performance of 93–96% for fixed-text scenarios and 75–92% for free-text. Accuracy across different text scenarios was achieved using a small dataset collected with the proposed implant model. This dataset enabled the generation of synthetic keystrokes directly within a low-computation-power device. This approach offers efficient and almost real-time keystroke replication. The results obtained show that the proposed model is sufficient not only to bypass the fixed-text keystroke dynamics system, but also to remotely control the victim’s device at the appropriate time. However, such a method poses high security risks when deploying adaptive keystroke injection with impersonated payload in real-world scenarios.
Trajectory Tracking Control of Unmanned Surface Vehicles Based on a Fixed-Time Disturbance Observer
Authors: Li Xiaosong , Li Xiaochen , Ma Dianguang , Kong Xianwei
Published: July 2023

In ocean environments with unknown complex disturbances, the control accuracy for an unmanned surface vehicle (USV) is severely challenged with an increase in task complexity. As the foundation for executing complex tasks, it is particularly important to control a USV to navigate along a safe trajectory that has been set. In order to effectively handle the trajectory tracking problem, an innovative USV tracking control strategy with high accuracy is proposed by combining the integral sliding-mode and disturbance observer technologies, and these are effectively extended to a scenario with the cooperative trajectory tracking of multiple USVs in this study. Specifically, unknown disturbances are treated as lumped uncertainties, and a novel fixed-time stable-convergence disturbance observer (FT-DO) is proposed to effectively observe and approximate the lumped uncertainties. Then, in order to quickly reach and steadily navigate along the desired trajectory, an effective fixed-time stable-convergence fast integral sliding mode is modified, and on this basis, an accurate trajectory tracking controller (FTFISM-TTC) for a single USV and a cooperative trajectory tracking controller for multiple USVs are meaningfully proposed. Finally, the stability of FT-DO and FTFISM-TTC was rigorously proven by using the Lyapunov approach, and a comprehensive simulation of current advanced tracking control methods was conducted by using Matlab, which proved the reliability of the proposed trajectory tracking control strategy and further eliminated the impact of the initial state on the tracking accuracy.
PIDD2 Control of Large Wind Turbines’ Pitch Angle
Authors: Hu Xingqi , Tan Wen , Hou Guolian
Published: July 2023

The pitch control system has a profound impact on the development of wind energy, and yet a delay or non-minimum phase can weaken its performance. Thus, there is a strong incentive to enhance pitch control technology in order to counteract the negative effects of unidentified delays and non-minimum phase characteristics. To reduce the complexity of the parameter-tuning process and improve the performance of the system, in this paper, we propose a novel control method for wind turbine pitch angle with time delays. Specifically, the proposed control method is state-space PIDD2, which is based on internal model control (IMC) and the open-loop system step response. Then, considering the tracking, disturbance rejection and measurement noise, the proposed controller is verified through simulations. The simulation results demonstrate that the state-space PIDD2 (SS-PIDD2) can provide a trade-off between robustness, time domain performance and measurement noise attenuation and effectively improve pitch control performance in contrast to series PID and PI control methods.
Comparison amongst Lagrange, Firefly, and ABC Algorithms for Low-Noise Economic Dispatch and Reactive Power Compensation in Islanded Microgrids
Authors: Singh Shruti , Gao David Wenzhong
Published: July 2023

For the microgrids to operate securely, distributed generators must be able to interact with one another without experiencing any communication delays or noise. To develop a more effective economic dispatch strategy, this research focuses on noise’s effect on the performance of an islanded microgrid. Three different strategies, Lagrange, firefly, and artificial bee colony algorithms, are compared for optimal solutions of economic dispatch. Their performance is compared based on stability during noise interference and faster response time with and without the virtual synchronous generator-STATCOM strategy. The virtual synchronous generator is used as a voltage source to regulate active power and reactive power with the grid. A STATCOM controller is introduced in the system for reactive power compensation. Reactive power compensation is the process of controlling reactive power to enhance the efficiency of alternating current power systems. By boosting the active power, reactive power compensation in the transmission system will increase the stability of microgrids. The voltage, output power, power factor, and phase angle of the microgrid benefit from the stability provided by the controller. As a result, the performance and resilience of the microgrid is improved.
Applying Neural Networks in Wineinformatics with the New Computational Wine Wheel
Authors: Le Long , Hurtado Pedro Navarrete , Lawrence Ian , Tian Qiuyun , Chen Bernard
Published: July 2023

Wineinformatics involves the application of data science techniques to wine-related datasets generated during the grape growing, wine production, and wine evaluation processes. Its aim is to extract valuable insights that can benefit wine producers, distributors, and consumers. This study highlights the potential of neural networks as the most effective black-box classification algorithm in wineinformatics for analyzing wine reviews processed by the Computational Wine Wheel (CWW). Additionally, the paper provides a detailed overview of the enhancements made to the CWW and presents a thorough comparison between the latest version and its predecessors. In comparison to the highest accuracy results obtained in the latest research work utilizing an elite Bordeaux dataset, which achieved approximately 75% accuracy for Robert Parker’s reviews and 78% accuracy for the Wine Spectator’s reviews, the combination of neural networks and CWW3.0 consistently yields improved performance. Specifically, this combination achieves an accuracy of 82% for Robert Parker’s reviews and 86% for the Wine Spectator’s reviews on the elite Bordeaux dataset as well as a newly created dataset that contains more than 10,000 wines. The adoption of machine learning algorithms for wine reviews helps researchers understand more about quality wines by analyzing the end product and deconstructing the sensory attributes of the wine; this process is similar to reverse engineering in the context of wine to study and improve the winemaking techniques employed.
Meta-Narrative Review of Artificial Intelligence Applications in Fire Engineering with Special Focus on Heat Transfer through Building Elements
Authors: Bakas Iasonas , Kontoleon Karolos J.
Published: July 2023

Artificial intelligence (AI), as a research and analysis method, has recently been gaining ground in the ever-evolving scientific field of fire engineering in buildings. Despite the initial delay in utilising machine learning and neural networks due to the shortfall of available computational power, a review of cutting-edge scientific research demonstrates that scientists are now exploring and routinely incorporating such systems in their research processes. As such, a considerable volume of new research is being produced comprising applications of AI in fire engineering. These findings and research questions ought to be summarised, organised, and made accessible for further investigation and refinement. The present study aims to identify recent scientific publications relating to artificial intelligence applications in fire engineering, with particular focus on those tackling the issue of heat transfer through building elements. The method of the meta-narrative review, as implemented in the field of medical advancement research, is discussed, adapted, and finally utilised to weave a narrative that enables the reader to follow the most recent, influential, and impactful works. Efforts are made to uncover trends in the search for heat transfer models and properties under fire loading using AI. The review concludes with our thoughts on how future research can enrich the current findings on heat transfer in buildings exposed to fire actions and elevated temperatures.
Kombucha and Water Kefir Grains Microbiomes’ Symbiotic Contribution to Postbiotics Enhancement
Authors: Pihurov Marina , Păcularu-Burada Bogdan , Cotârleț Mihaela , Grigore-Gurgu Leontina , Borda Daniela , Stănciuc Nicoleta , Kluz Maciej , Bahrim Gabriela Elena
Published: July 2023

Wild artisanal cultures, such as a symbiotic culture of bacteria and yeasts (SCOBY) and water kefir grains (WKG), represent a complex microorganism consortia that is composed of yeasts and lactic and acetic acid bacteria, with large strains of diversity and abundance. The fermented products (FPs) obtained by the microbiome’s contribution can be included in functional products due to their meta-biotics (pre-, pro-, post-, and paraprobiotics) as a result of complex and synergistic associations as well as due to the metabolic functionality. In this study, consortia of both SCOBY and WKG were involved in the co-fermentation of a newly formulated substrate that was further analysed, aiming at increasing the postbiotic composition of the FPs. Plackett–Burman (PBD) and Response Surface Methodology (RSM) techniques were employed for the experimental designs to select and optimise several parameters that have an influence on the lyophilised starter cultures of SCOBY and WKG activity as a multiple inoculum. Tea concentration (1–3%), sugar concentration (5–10%), raisins concentration (3–6%), SCOBY lyophilised culture concentration (0.2–0.5%), WKG lyophilised culture concentration (0.2–0.5%), and fermentation time (5–7 days) were considered the independent variables for mathematical analysis and fermentation conditions’ optimisation. Antimicrobial activity against Bacillus subtilis MIUG B1, Staphylococcus aureus ATCC 25923, Escherichia coli ATCC 25922, and Aspergillus niger MIUG M5, antioxidant capacity (DPPH), pH and the total acidity (TA) were evaluated as responses. The rich postbiotic bioactive composition of the FP obtained in optimised biotechnological conditions highlighted the usefulness of the artisanal co-cultures, through their symbiotic metabolic interactions for the improvement of bioactive potential.
The Potential of Wine Lees as a Fat Substitute for Muffin Formulations
Authors: Bianchi Federico , Cervini Mariasole , Giuberti Gianluca , Simonato Barbara
Published: July 2023

The current study evaluates the prospect of wine lees (WL), a costless by-product from Amarone winemaking, as a fat replacer in muffin formulation. WL have elsewhere replaced sunflower oil, allowing the creation of 0, 25, 50, 75, and 100% fat-substituted muffins named ML0, ML25, ML50, ML75, and ML100, respectively. Batter rheology, in addition to the textural and colorimetric characteristics, the pore dimension, and the sensory aspect of the different formulations were evaluated. The batter consistency (K) of fat-replaced muffins was lower than that of the control, while the hardness and chewiness of the end products were higher. ML25 and ML50 samples reached the highest volume, while the baking loss decreased due to WL’s fiber components. ML25, ML50, ML75, and ML100 accounted for caloric reductions of 9, 18, 22, and 26%, respectively, compared to full-fat muffins. Muffins with WL showed a darker crust and crumb as lightness (L*) decreased. Moreover, a* parameter increased with the increment of WL in the formulation, leading to a redder and less yellow-hued fat-replaced muffin. In conclusion, WL could effectively replace fat in the 25–50% range in muffins, achieving a final product with reduced calories, a higher dietary fiber content, higher volume, and promising sensory aspects.
On a System of Equations with General Fractional Derivatives Arising in Diffusion Theory
Authors: Miskovic-Stankovic Vesna , Atanackovic Teodor M.
Published: July 2023

A novel two-compartment model for drug release was formulated. The general fractional derivatives of a specific type and distributed order were used in the formulation. Earlier used models in pharmacokinetics with fractional derivatives follow as special cases of the model proposed here. As a first application, we used this model to study the release of gentamicin from poly(vinyl alcohol)/chitosan/gentamicin (PVA/CHI/Gent) hydrogel aimed at wound dressing in the medical treatment of deep chronic wounds. As a second application, we studied the release of gentamicin from antibacterial biodynamic hydroxyapatite/poly(vinyl alcohol) /chitosan/gentamicin (HAP/PVA/CS/Gent) coating on a titanium substrate for bone tissue implants, which enables drug delivery directly to the infection site. In both cases. a good agreement is obtained between the measured data and the data calculated from the model proposed here. The form of the general fractional derivatives used here results in an additional parameter in the compartmental model used here. This, as a consequence, leads to a better approximation of the experimental data with only a slightly more complicated numerical procedure in obtaining the solution.
The Impact of COVID-19 on BRICS and MSCI Emerging Markets Efficiency: Evidence from MF-DFA
Authors: Ameer Saba , Nor Safwan Mohd , Ali Sajid , Zawawi Nur Haiza Muhammad
Published: July 2023

This study examines the response of the BRICS and MSCI emerging stock market indices to the COVID-19 outbreak. For this purpose, this study uses a multifractal detrended fluctuation analysis (MF-DFA) to investigate the market efficiency dynamics of these indices and then ranks them based on their market efficiency. Overall, our results indicate that the returns from all the stock indices exhibit long-range correlations, implying that these markets are not weak-form efficient. Specifically, China showed the highest level of multifractality (i.e., inefficiency), which can be attributed to its highly volatile market structure. Using a subsample analysis, we further explore the impact of COVID-19 on these markets’ efficiency by dividing the dataset into pre- and post-COVID periods. The findings indicate that COVID-19 adversely affected the efficiency of all the indices. Surprisingly, improvement in the Chinese market’s inefficiency was witnessed, which can be attributed to the prompt and effective measures (i.e., timely imposition of health-related measures such as lockdowns and resident quarantines to contain COVID-19 and financial packages designed to curtail the economic meltdown) introduced by the Chinese government. The findings of this study may help investors, policymakers and regulators in refining their financial and policy decisions according to the new efficiency levels of these markets.
Rheological Properties of Gel Foam Co-Stabilized with Nanoparticles, Xanthan Gum, and Multiple Surfactants
Authors: Sheng Youjie , Zhang Hanling , Ma Li , Wang Zhenping , Hu Die , Zhang Shanwen
Published: July 2023

Gel foam has the advantages of gel and foam and shows good prospects for applications in the fields of fire prevention and extinguishing. Rheology has a significant impact on the application of gel foam, but there is little related research. In the present study, hydrophilic silica nanoparticles (NPs) and water-soluble polymer xanthan gum (XG) were combined with fluorocarbon surfactant (FS-50) and hydrocarbon surfactant (APG0810) to create gel foam. The foaming ability and foam drainage were evaluated. The gel foam’s rheology, including its flow behavior and viscoelasticity, was systematically investigated. The results show that the foaming of the FS-50/APG0810 mixture decreases but the foam drainage increases in the presence of NPs and/or XG. All of the foams belong to the category of non-Newtonian fluids with shear thinning behavior. The flow curves of the foams are consistent with the Cross model. The presence of XG/NPs enhanced the foam viscoelasticity of the FS-50/APG0810 mixture. The silica NPs showed a better ability to enhance foam viscoelasticity but a worse ability to stabilize the foam compared to XG. This research can offer theoretical support for the industrial usage of gel foam.