bluuebunny/crossref_metadata_2025 huggingface dataset:
A CONSUMER SENTIMENT ANALYSIS METHOD BASED ON EEG SIGNALS AND A RESNEXT MODEL
Authors: SHEN XIAOYING , YUAN CHAO
Published: February 2024

E-commerce is becoming increasingly dependent on technologies such as consumer sentiment research at an ever-increasing rate. Its purpose is to recognize and comprehend the feelings and dispositions of customers by analyzing customer language and behavior as expressed in social media, online reviews, and other forms of digital communication. The proliferation of digital technology has resulted in an increase in the number and variety of channels through which customers can communicate their feelings. Gaining a comprehensive understanding of consumer sentiment may be of great use to businesses, as it enables them to better satisfy customer demands, enhance their products and services, improve their brand reputation, and ultimately increase their level of competitiveness. As a result, consumer sentiment research has evolved into a tool that is essential for the decision-making process in e-commerce as well as the management of customer relationships. Within the scope of this discussion, this study uses deep learning models to improve consumer sentiment research precision. The following is the list of the primary contributions that this paper makes. (1) Advancing the use of EEG signals as a basis for a method for analyzing customer feelings. This technique measures brain activity directly, thus avoiding the restrictions and ambiguities that come with relying on verbal expression. (2) The purpose of this study is to improve the overall performance of the model for analyzing sentiment by incorporating an attention mechanism into the ResNeXt model. This attention mechanism is intended to augment the model’s capacity to extract subtle characteristics. (3) The results of the experiments show that the strategy described in this study is effective in improving EEG-based sentiment analysis performance. When compared to standard text-based sentiment analysis approaches, this sentiment analysis model demonstrates greater objectivity, real-time capabilities, and multidimensionality when applied to consumer sentiment analysis in e-commerce.
AN EPILEPSY DIAGNOSIS METHOD BASED ON A TRANSFERRED ALEXNET MODEL AND EEG SIGNALS
Authors: ZHANG QING , LI CONG , DING YANG
Published: February 2024

Epilepsy is a neurological disorder, and its sudden seizures pose a serious threat to the quality of life of patients. Not only does this condition cause patients to potentially lose control and consciousness during seizures, leading to possible injuries or dangerous situations, but it also has a significant impact on their mental health, triggering issues such as anxiety and depression. An intelligent epilepsy diagnosis process based on electroencephalogram (EEG) signals offers notable advantages. First, it provides noninvasive brainwave signals that accurately monitor and record the patterns and characteristics of epileptic seizures, offering objective diagnostic criteria for doctors. Second, with the use of artificial intelligence and machine learning technologies, large amounts of EEG data can be efficiently analyzed, improving the speed and accuracy of diagnosis and providing timely and effective treatment plans for patients. Additionally, intelligent diagnostic systems can achieve real-time monitoring, promptly alert people to potential epileptic seizures, and provide a safer living environment for patients. In this context, this paper proposes an epilepsy diagnosis method based on a transferred AlexNet model and EEG signals. The main contributions of this paper are as follows. (1) A transfer learning mechanism is incorporated into the AlexNet model through the direct transfer of its neural network structure and the modification of some existing neural network structures, followed by collaborative training with the addition of a domain adaptation layer in the network. This introduced transfer mechanism can address small sample size issues. (2) The traditional AlexNet model suffers from redundant feature extraction, leading to slow training. This paper adds batch normalization (BN) layers after each convolutional layer in the AlexNet model to normalize the features extracted from the convolutional layers. This emphasizes the representation of the important features of EEG signals and enables the lower layers of the network to learn the features needed for EEG signal processing. (3) The transferred AlexNet model proposed in this paper is applied to extract the features of epilepsy EEG signals, and the extracted features are input into a support vector machine (SVM) classifier to obtain epilepsy diagnosis results. Comparative experiments show that the diagnostic method used in this paper yields superior results and shorter training times than those of the competing approaches.
APPLICATION AND EVALUATION OF A MULTI-SCALE ASSESSMENT MODEL FOR ELDERLY DISABILITY
Authors: WANG LI , FENG SHEN , WEI YIN , XU WENTING , HOU RUOHAN , ZHOU JUNHUI , HUANG ZHENLIANG , SHAO ZEGUO
Published: February 2024

As the aging population continues to grow, the increasing number of disabled elderly individuals poses ongoing challenges to society in terms of healthcare and medical burdens. Grading disability is of significant importance for improving medical services and allocating social resources. Traditional grading methods using a single assessment scale tend to be subjective and cannot comprehensively and accurately reflect the real situation. This paper presents the NES (Needs assessment of Elderly care in Shanghai) scale, based on 33 quantified scoring items from basic surveys, to enhance the objectivity and accuracy of disability grading. Correlation analysis of observed items using the C4.5 decision tree algorithm is conducted, followed by an analysis and evaluation of the scale’s performance. The data used in this study are derived from 266 questionnaires collected from eight regions in Shanghai and categorized into three classes: physiological (JKOM/BADL), psychological (BDI/SDS/SAS), and cognitive (CDR). The analysis results show that the NES scale exhibits better robustness in physiological assessment compared to the BADL and JKOM scales. In psychological assessment, the NES scale performs similarly to the SDS and SAS scales. In cognitive assessment, the NES scale’s grading level is slightly higher than that of the CDR scale, demonstrating good comprehensive disability assessment capabilities.
MAC: EPILEPSY EEG SIGNAL RECOGNITION BASED ON THE MLP-SELF-ATTENTION MODEL AND COSINE DISTANCE
Authors: LI PEIJUAN , LIU YITING , CAI WEI , LIU XIN
Published: February 2024

In current epilepsy disease research, accurate identification of epilepsy electroencephalogram (EEG) signals is crucial for improving diagnostic efficiency and developing personalized treatment plans. This study proposes an innovative epilepsy recognition model, MAC, which combines the unique advantages of a multilayer perceptron (MLP), a self-attention mechanism and the cosine distance. This model uses a MLP as the basic model and effectively reduces individual differences among epilepsy patients through its superior linear fitting ability. To more accurately measure the difference between two EEG signals, we introduced the cosine distance as a new feature metric. This metric enhances the performance of epilepsy EEG classification by using the cosine value of the angle in vector space to precisely assess the difference between two individuals. In addition, we introduced a self-attention mechanism into the model to enhance the impact of various factors on the final EEG data. Our experiments employed the EEG database of the Epilepsy Research Center of the University of Bonn. Through comparative experiments, it was proven that the proposed MAC model achieved significant improvement in performance on the epilepsy EEG signal recognition task. This study fills the existing research gap in the field of epilepsy identification and provides a powerful tool for the accurate diagnosis of epilepsy diseases in the future. We believe that the introduction of the MAC model will promote new breakthroughs in epilepsy EEG signal recognition and lay a solid foundation for the development of related fields. This research provides an important theoretical and practical reference for advancing the field of epilepsy identification.
A STUDY ON THE EFFECT OF AEROBIC FITNESS ON THE SYNCHRONICITY OF BRAIN NERVE–LIMB MOVEMENT IN HUMANS
Authors: XU YANLIN , GUAN FUYU , REN JIE
Published: February 2024

In order to analyze the synchronization ability of human brain nerve–limb movement, a research framework based on the gray wolf algorithm was constructed. The response timestamp data of human brain nerves was obtained under command excitation using a near-infrared brain functional imaging testing system as input for the gray wolf algorithm. The body motion response timestamp data was used as the output of the gray wolf algorithm. By using the gray wolf algorithm for swarm intelligence learning and training, the synchronization relationship between brain nerves and limb movements can be obtained. Taking aerobic energy as the key factor, we set up groups with higher aerobic energy and groups with lower aerobic energy, and then conduct the experimental research. The experimental results showed that the synchronization ability of “brain nerve–limb movement” was significantly stronger in the group with higher aerobic fitness than in the group with lower aerobic fitness, and this advantage increased with the increase of testing time interval.
PERCEIVED AND BIOMECHANICAL EFFECTS OF RUNNING SHOE CENTER OF GRAVITY SHIFTING IN AMATEUR MALE RUNNERS
Authors: YANG FAN , HAN TIANYU , GUO TONGTONG , MENG HUANHUAN , YANG MINGHUI , YAN ZHAOQI , CHU ZHAOWEI , FU FENGQIN , WANG YUXI
Published: February 2024

This study examined the influence of running shoe center of gravity relative position shifting forward and backward in sagittal axis on male amateur runners. Twenty-three adult male runners were recruited through social media with paid to participate in this study. The experimental shoe used was the Li Ning Feidian Challenger 3. Forward center of gravity (FCG), defined as the shoe center of gravity located at 10.8[Formula: see text]cm (15% before midpoint) from shoe toe to heel. Intermediate center of gravity (ICG), defined as the shoe center of gravity, is located at 14.8[Formula: see text]cm (midpoint) from shoe toe to heel. Backward center of gravity (BCG), defined as the shoe center of gravity, is located at 23.1[Formula: see text]cm (15% after midpoint) from shoe toe to heel. Questionnaire collection was used to assess the perception of the center of gravity shifting. Ground contact temporal, peak force/pressure of plantar and kinetics indicators data were simultaneously captured by motion capture system and force platform. Three participants (13.04%) correctly perceived the shoe center of gravity shifting forward and backward simultaneously. Shoes ICG peak force underneath Meta 1 increased significantly than BCG by 7.59% ([Formula: see text]). Shoes FCG peak force underneath Meta 2 decreased significantly compared to ICG and BCG by 13.62% and 8.96% ([Formula: see text]). Shoes BCG peak force underneath Meta 5 decreased significantly compared to ICG and FCG by 18.18% and 23.78% ([Formula: see text]). Shoes FCG peak pressure underneath Meta 2 decreased significantly compared to ICG and BCG by 13.02% and 9.19% ([Formula: see text]). Shoes FCG peak pressure underneath Meta 2 decreased significantly compared to ICG and BCG by 11.18% and 9.16% ([Formula: see text]). However, there are no significant differences in kinetic indicators. The findings suggest that a fraction of participants can correct perceived shoe center of gravity shifting. Shoes’ FCG reduces force and pressure in the middle metatarsal regions. Shoes’ BCG reduces force in the lateral and medial metatarsal region. Healthcare professionals can optimize the design of footwear accordingly to improve rehabilitation outcomes and reduce injury risks in runners.
ANALYSIS OF HUMAN LOWER LIMB DYNAMICS AND GAIT RECONSTRUCTION
Authors: LIU TIE
Published: February 2024

In order to achieve gait reconstruction of human posture, a 7-degree-of-freedom model of the human lower limbs is proposed. On the basis of this model, dynamic analysis was conducted and the Lagrange equation of the human lower limb dynamic system was constructed. In the process of solving the kinetic energy–potential energy relationship of the Lagrange equation, the angular solutions of each joint were obtained. Based on actual data, common gait patterns of human lower limbs were presented, and gait reconstruction experiments were conducted. The experimental results show that under the human lower limb model and dynamic analysis method constructed in this paper, the variation curves of the hip joint, knee joint, and ankle joint of the human lower limb have been effectively reconstructed.
INTRAOPERATIVE SURGICAL NAVIGATION BASED ON LASER SCANNER FOR IMAGE-GUIDED ORAL AND MAXILLOFACIAL SURGERY
Authors: LI FANG , HUANG CONGGANG , FENG XIANGMING , WANG LE , ZHANG CHUXI , CHEN XINRONG
Published: February 2024

In oral and maxillofacial surgery, computer-assisted navigation technologies have been widely used to achieve intraoperative positioning. The traditional methods mainly rely on the experience of doctors and the difference between the locations of key points in the surgical area and the preoperative planning, which have certain limitations. In this paper, a new intraoperative surgical navigation framework based on mobile laser scanner is proposed, which ensures that surgery is performed accurately according to the preoperative planning. The framework mainly includes two parts. First, the real-time surface reconstruction of the anatomy should be realized during the operation. Second, the acquired image is matched to the planned image in real time. Although the most common method of surface reconstruction is to render the volume directly from raw data or render the surface from the segmented data using computed tomography/magnetic resonance (CT/MR) data, this method is too complicated for performing the real-time operation during surgery. Furthermore, a new surface registration technique is proposed for image-guided oral and maxillofacial surgery based on the point sets. To improve the registration accuracy and robustness, the point sets are modeled by Mixed Student’s t-Distribution model. In the experiments, the point sets of CT data are from 10 patients with craniomaxillofacial diseases and the surface point set is from the LRS. The TRE of 10 data was less than 1[Formula: see text]mm. Compared with the paired-point registration method and Iterative Closest Point algorithm, the results demonstrated better performance of the proposed method, the surgical situation can be displayed in real time during the surgical process, and any differences from the surgical plan can also be reflected.
KINEMATICS OF LOWER LIMBS DURING SQUATTING FOR CHINESE MALE AND FEMALE YOUTHS
Authors: WEI SHAN , XU CHENGTAO , ZHANG RENGANG , FAIK ASSIA , WANG ZHENGYU , TANG YUEYUE , ZHANG XINXIN , LIU HE
Published: February 2024

This research aimed to measure lower extremity kinematics for male and female youths during daily activities and to identify gender differences from kinematics of lower limbs. A total of 87 healthy participants, comprising 43 Chinese male youths and 44 female youths, were recruited from Anhui Polytechnic University to participate in this research. All participants were instructed to perform squatting activities on a soft mat starting from an upright position. Every participant completed six squatting exercises, and motion capture technology was used to gather 3D kinematic data. SPSS software was used for statistical analysis. The average 3D angles of the hip, knee, and ankle joints of male and female youths were calculated, and then the independent t-test was used for statistical significance. Data analysis showed no significant gender differences in the sagittal movements of the knee and ankle joints for Chinese male and female youths. The mean hip joint angle during squatting was [Formula: see text] for male youths and [Formula: see text] for female youths. The knee joint angle was [Formula: see text] for male youths and [Formula: see text] for female youths. With regard to ankle mobility, the hip and ankle ranges of motion were [Formula: see text] and [Formula: see text] for male youths and [Formula: see text] and [Formula: see text] for female youths. Both sexes showed significant gender differences in the nonsagittal plane. The range of motion (ROM) observed during deep squatting exceeds the ROM after arthroplasty for Chinese male and female youths. These findings contribute to a comprehensive understanding of deep squatting biomechanics for the Chinese population and provide a basis for mitigating hyperflexion exercises and fabricating appropriate joint injury prostheses. By understanding the specific movement patterns of Chinese male and female youths, healthcare professionals can develop individualized interventions and rehabilitation programs to improve functional outcomes, prevent joint injuries, and improve the overall quality of life. The research found significant gender differences for sagittal hip and anterior ankle movements of male youths during squatting. These findings shed light on the kinematics of lower limbs. They have the potential to influence future research and medical practice to improve joint health and functional mobility for Chinese male and female youths.
Quantum confinement effects on the structural and optical properties of nanostructured tin oxide powder
Authors: Besahraoui Fatiha , Chebbah Kheira
Published: February 2024

Nanostructured Tin oxide powders, prepared by chemical precipitation method, exhibit interesting structural and optical properties at nanoscale dimensions. Structural characterization confirmed the formation of pure nanostructured SnO2 powders with average crystalline grain size of 54.4[Formula: see text]nm calculated with relative uncertainty of 1.62%. The optical properties of nanoSnO2 powder performed by using transmittance and photoluminescence measurements reveal high transparency and multi-photon emissions in visible and ultraviolet regions. The different photon emissions are attributed to radiative transitions via oxygen vacancies, Sn interstitials, Sn substitutional and dangling bonds. The lower wavelength value corresponded to the absorption edge peak indicating the good quantum confinement of nanostructured SnO2 powder. The larger optical band gap, calculated through transmittance measurements, confirms the quantum confinement effects. The presence of quantum confinement and native point defects in nanostructured SnO2 powders can contribute to enhancing photon emissions process. This result may offer inherent advantages over conventional materials for photonic quantum information technology. The sustained photon emission at room temperature, indicates that SnO2 nanoparticles could be useful in room temperature quantum computing and can maintain the delicate quantum states required for computation at higher temperatures.
Quantum key distribution based on the quantum eraser
Authors: Elsayed Tarek A.
Published: February 2024

Quantum information and quantum foundations are becoming popular topics for advanced undergraduate courses. Many of the fundamental concepts and applications in these two fields, such as delayed choice experiments and quantum encryption, are comprehensible to undergraduates with basic knowledge of quantum mechanics. In this paper, we show that the quantum eraser, usually used to study the duality between wave and particle properties, can also serve as a generic platform for quantum key distribution. We present a pedagogical example of an algorithm to securely share random keys using the quantum eraser platform and propose its implementation with quantum circuits.
Navigating the Digital Frontier: Emerging Trends in Digital Innovation Management for 2023 and Beyond
Authors: Smolinski Jan
Published: February 2024

Purpose: After the pandemic digital technologies have increasingly become the focus of companies’ innovation management processes. This trend has led to a rapid expansion of the field, with a growing number of research papers on various facets of this topic being published in academic journals. However, the proliferation of literature in the field has complicated the ease with which practitioners and academics can stay up to date with the latest developments and build on recent findings in their respective work. In order to succeed within the field of digital innovation management a strong grasp of the newest trends is required to not fall behind competitors, and to be able to develop cutting edge research. To address this challenge, this paper aims to answer the research question: What are the most common themes in post-pandemic digital innovation management literature? Design/methodology/approach: To answer this question, this study conducted a systematic literature review of 148 academic papers published between 2020 and 2023. The identified trends were subsequently organized into a framework that provides a comprehensive understanding of the field. Findings: The identified trends can be classified as either catalysts or new opportunities. Catalysts are trends that companies can implement to make their digital innovation management more efficient. The four identified catalysts are: the use of artificial intelligence as a vital part of innovating, educating leaders and employees, incorporating digital knowledge management practices, and collaborating with innovation networks. The articles also point to three trends classified as new opportunities that digital innovation management can enable, such as more sustainable initiatives, better foreign aid, and a transition to platformization. Originality: This study summarizes the research direction of digital innovation management and synthesizes important key developments leading up to the year 2023, which researchers and practitioners should be aware of.
Geometric phase for two-mode entangled squeezed-coherent states
Authors: Almas S. Mohammadi , Najarbashi G. , Tavana A.
Published: February 2024

In this paper, we investigate the geometric phase (GP) of two-mode entangled squeezed-coherent states (ESCSs), undergoing unitary cyclic evolution. Results show that increasing the squeezing parameter of either mode of the balanced ESCS compresses the GP elliptically with respect to the coherence parameter of the corresponding mode. While in the case of unbalanced ESCS, the GP is compressed hyperbolically by increasing the squeezing parameters of the either mode. By generalizing the approach to higher constituting-state dimensions, it is found that the GPs of both balanced and unbalanced ESCSs, increase for a specific value of the coherence parameter. By analyzing the states through the Schmidt decomposition method, we find that, locally, the balanced and unbalanced ESCSs are unitarily equivalent. Finally, based on the interferometry technique, we suggest a theoretical scheme for the physical generation of ESCSs.
Modeling the Stimulus-Responsive Behaviors of Fiber-Reinforced Soft Materials
Authors: Dai Lu , Xu Junwei , Xiao Rui
Published: February 2024

Hydrogels can change their size upon swelling. The swelling ratio is the same for all directions in the stress-free state. Dielectric elastomers can reduce their thickness and expand the area upon an electric field. Similarly, the expansion ratio in the plane is also the same for different directions. This isotropic shape change effect limits the function of these soft materials in certain circumstances. To address this issue, recent works have shown that the incorporation of fibers into the polymer matrix can induce an anisotropic response upon external stimulus. In this work, we develop multi-field coupling models for both fiber-reinforced hydrogels and dielectric elastomers. For the former, the change in free energy is caused by the stretching of polymer chains and fibers and the mixing of solvents and polymer networks. The Fickian-type law is adopted for the solvent diffusion. The free energy density for the latter consists of a mechanical part, considering the deformation of both polymer matrix and fibers, and an electric polarization component. Gauss’s law is adopted to obtain the distribution of the electric field. The multi-field models are then implemented for finite element analysis. We consider the stimulus-responsiveness of bilayer strips with an active layer and a passive layer. Without fibers, the strips bend upon the external stimulus. In contrast, the shape changes to helix shapes, which can be further tuned by changing the distribution of fibers. The work provides an efficient design tool for self-folding structures based on stimulus-responsive polymers.
Facile Fabrication of ZnO Nanorods with Extremely Strong Photocatalytic Performance and Antibacterial Activity
Authors: Mohapatra Bandita
Published: February 2024

Development of nanomaterials with strong antibacterial action and highly enhanced photocatalytic activity for water purification is of immense interest. ZnO nanorods, with extremely enhanced solar-driven photocatalytic performance and good antibacterial activity, have been fabricated by facile chemical route. The structural properties of the nanomaterial were thoroughly characterized by SEM, TEM, EDX, HRTEM, STEM-HAADF, elemental profiling, XRD and Raman spectroscopy, while the optical and photocatalytic properties were studied by UV-vis absorption spectroscopy. TEM and FESEM showed nanorods with average width and length as 80[Formula: see text]nm and 178[Formula: see text]nm. XRD showed wurtzite ZnO with 27[Formula: see text]nm crystallite size. PL analysis of ZnO nanorods showed peaks at 415[Formula: see text]nm, 439[Formula: see text]nm, 499[Formula: see text]nm and 561[Formula: see text]nm. The fabricated ZnO nanorods exhibited extremely enhanced photocatalytic performance with very high rate constant of 0.201[Formula: see text]min[Formula: see text] for degradation of organic pollutant MB in water under only 15[Formula: see text]min of solar exposure. ZnO nanorods completely inhibited growth of Bacillus oceanisediminis and Escherichia coli at 500[Formula: see text][Formula: see text]g/mL and 700[Formula: see text][Formula: see text]g/mL, respectively. The origin of antibacterial behavior of ZnO nanorods against B. oceanisediminis and E. coli has been investigated using histidine for scavenging ROS, morphological change by SEM and agarose gel electrophoresis. Our results showed that ROS-induced oxidative stress damages cell wall, evident from SEM, and leads to fragmentation of DNA both of which contribute to the antibacterial action of ZnO nanorods. The tentative mechanism of extremely strong photodegradation performance of ZnO nanorods has also been proposed.
Seismic Resilience Scenario of Algerian Buildings’ Context: Blida City Case Study
Authors: Yousfi Nacim , Belkacem Mounir Ait , Guessoum Nabila , Bensaibi Mahmoud
Published: February 2024

Several studies have been carried out to assess the building’s seismic vulnerability, to mitigate the seismic risk in urban areas, which is one of the most devastating natural hazards causing considerable economic and human losses. These studies must be incorporated to improve the planning of urban areas to have resistant and resilient cities in case of disasters. The seismic feedback has shown that the build-back-better concept has a direct impact on the city’s economic growth. In this paper, the existing buildings’ resilience is assessed, in order to highlight the capacity of these last to keep the functionality when an earthquake occurs. This building’s resilience has been determined for three types of structures: masonry, reinforced concrete and steel, according to the reconstruction time, the reconstruction cost and the damage state. This last has been assessed from empirical fragility curves developed using the log normal distribution for five structures typologies (Unreinforced masonry; reinforced masonry; RC frame; RC shear walls/Mixed RC frame-RC shear walls and steel structures). A seismic resilience scenario was performed using a geographic information system (GIS) and applied for the Blida city (Algeria) classified as a high seismic zone according to Algerian seismic regulations. According to the results found, the old districts of the Blida city, built mainly during the so-called pre-code period, will not be resilient in case of disaster. The other districts built later in the low-code and high-code periods will have, respectively, medium and good functionality.
Generating bright-field images of stained tissue slices from Mueller matrix polarimetric images with CycleGAN using unpaired dataset
Authors: Fan Jiahao , Zeng Nan , He Honghui , He Chao , Liu Shaoxiong , Ma Hui
Published: February 2024

Recently, Mueller matrix (MM) polarimetric imaging-assisted pathology detection methods are showing great potential in clinical diagnosis. However, since our human eyes cannot observe polarized light directly, it raises a notable challenge for interpreting the measurement results by pathologists who have limited familiarity with polarization images. One feasible approach is to combine MM polarimetric imaging with virtual staining techniques to generate standardized stained images, inheriting the advantages of information-abundant MM polarimetric imaging. In this study, we develop a model using unpaired MM polarimetric images and bright-field images for generating standard hematoxylin and eosin (H&E) stained tissue images. Compared with the existing polarization virtual staining techniques primarily based on the model training with paired images, the proposed Cycle-Consistent Generative Adversarial Networks (CycleGAN)-based model simplifies data acquisition and data preprocessing to a great extent. The outcomes demonstrate the feasibility of training CycleGAN with unpaired polarization images and their corresponding bright-field images as a viable approach, which provides an intuitive manner for pathologists for future polarization-assisted digital pathology.
Graphitic carbon nitride as an efficient metal-free photocatalyst for tetracycline removal
Authors: da Silva Afonso Henrique , de Oliveira Carlos Rafael Silva , Francisco Isadora Bertini Martins , de Oliveira Patricia Viera , de Aguiar Catia Rosana Lange , da Silva Adriano
Published: February 2024

Tetracycline (TC) is a drug commonly detected in wastewater. Given this, researchers have been working intensely to create efficient methods to eliminate TC from water. Therefore, the work aimed to synthesize a metal-free catalyst, graphitic carbon nitride (g-CN), to remove TC from water through photocatalysis. The one-step methodology via thermal condensation successfully synthesized the catalyst. Also, a Box-Behnken experimental design was used in the TC treatment to optimize variables such as pollutant and catalyst concentration and pH. Under optimized conditions, there was a 79% removal in 2 h. Furthermore, the catalyst was reused in four consecutive cycles, demonstrating remarkable recyclability. Therefore, the catalyst produced proved effective and promising for the aqueous remediation of TC.
Hardware-in-the-loop simulation test platform for UAV flight control system
Authors: Lu Wenjun
Published: February 2024

The flight control system is the integrated command center and core component of the UAV system. Aiming at the problems of poor accuracy and low efficiency in the field measurement of flight control system parameters, combined with the configuration of the flight attitude sensor-vertical gyroscope, hardware-in-the-loop simulation technology, and integrated automatic test methods are adopted. The hardware-in-the-loop simulation test platform for the UAV flight control system composed of a low-cost, high-precision miniaturized UAV attitude calibration platform and a control piston deflection angle test device is designed. The main controller replaces the ground master control station of the UAV and directly sends remote control commands to the aircraft. By changing the attitude of the aircraft, and measuring the voltage of the control signal, the feedback signal, and the rudder angle, the comprehensive performance test of the parameters of the flight control system is realized. The performance test of the platform shows that the platform can meet the test requirements of angular position, system voltage, and control piston deflection angle.
Simulation modeling of PMBLDC motor speed control in electric propulsion of EV system using adaptive nonlinear fuzzy sliding mode controller (ANF-SMC)
Authors: Begam Shaik Ruksana , Loveswara Rao B. , Shobha Rani D.
Published: February 2024

In the current scenario of transportation system, vehicles of conventional are replaced with Electric Vehicles (EVs) with Permanent Magnet Brushless Direct Control Motors (PMBLDCMs) because of the many advantages of the usage of such motors in EVs. Despite the many advantages of the usage of EVs with PMBLDCMs, there were some disadvantages, among them were speed control and dealing with uncertainty problems in the usage of PMBLDCMs in EVs. In rectifying the above-mentioned problems, this work proposed and implemented an ideology of using the nonlinear controller strategy Adaptive Neuro-Fuzzy Sliding Mode Control (ANF-SMC) in the Electric Propulsion Subsystem (EPSS) of EVs with the usage of the proposed nonlinear controller under not loaded and fully loaded vehicles with constant, variable and sudden disturbance in speed conditions. Simulation was carried out using MATLAB version R2020b with Fuzzy Tool Kit (FTK) and simulation performance comparison was done with the existing four (one linear and three nonlinear) controllers. Comparative simulation results infer that the proposed nonlinear controller performs well with zero overshoot and less settling time than that of the existing four (one linear and three nonlinear controllers).
Effective numerical simulation of time fractional KdV equation with weakly singular solutions
Authors: Chen Hu , Lin Xiaotang , Sun Tao , Tang Yifa , Zhang Jingna
Published: February 2024

A second-order time-stepping method for numerically solving the linearized time fractional KdV equation (TFKDVE) whose solution has initial singularity is investigated. Alikhanov’s scheme is used to discretize the Caputo fractional derivative on temporal graded mesh, and the space is approximated by a Petrov–Galerkin spectral method. Detailed stability and error estimate of the full-discrete scheme are given, and the final error bound is [Formula: see text]-robust. Numerical examples are given to illustrate the sharpness of the error analysis.
Edge highlighting of laser-scanned point clouds improves the accuracy of perceived depth in transparent multi-view 3D visualizations
Authors: Aoi Daimon , Hasegawa Kyoko , Li Liang , Sakano Yuichi , Sakamoto Naohisa , Tanaka Satoshi
Published: February 2024

The rapid development of 3D scanning has allowed us to digitally capture cultural heritage objects as large-scale point clouds, recording their complex internal and external structures. We have developed a 3D multi-view transparent visualization using edge highlighting as visual guide, improving accuracy of perceived depth for reliable visual analyses of the 3D scanned point clouds. When transparently visualizing a 3D object on a 3D multi-view display, the depth information tends to become less distinct. Therefore, we aimed to explore whether emphasizing the statistically extracted 3D edges of the scanned object can enhance the perceived depth of transparently visualized 3D objects. We conducted psychophysical experiments where participants were asked to report their perceived magnitudes of depth for multiple types of 3D structures of cultural heritage presented on a multi-view 3D display. The results indicated that our edge highlighting reduced the underestimation of depth from 46.8% to 34.0% on average. This improvement persisted even when the 3D structures produced an atypical linear perspective, normally caused by reverse depths, where the front and back are reversed. These findings suggest that edge highlighting brings us an effective visual guide to improve the accuracy of perceived depths on a 3D multi-view display.
Recent Advances on Scaffolds: A Comprehensive Review of Materials, Fabrication Techniques, and Applications
Authors: Varpe Aishwarya , Shinde Shubham , Champaty Biswajeet , Dash Aiswarya , Kumar Uttam , Khade Shankar
Published: February 2024

Scaffolds offer a three-dimensional framework supporting cell growth, proliferation, and differentiation of cells which are used to repair and regenerate tissues. Recent advancements in scaffold technology have significantly exploited the field of tissue engineering and regenerative medicine. This comprehensive review provides in-depth exploration of scaffold materials, fabrication techniques, and their recent progress in applications. Composite scaffolds have promising applications in bone and dental tissue regeneration due to their greater mechanical properties and ability to promote cell growth. The inherent crosslinking present in hydrogels allows them to maintain their integrity and three-dimensional structure without dissolving. However, there is a growing interest in smart hydrogels which can respond to changes in their external surroundings like pH, ionic strength, temperature, or specific molecules. dECM scaffold is an alternative potential technique for reconstructing the functional organs/tissues by excluding the cell-associated antigens while maintaining the native ECM compositions like growth factors, basement membrane structural proteins, and GAG’s. The degree of porosity in scaffolds can be increased by various fabrication techniques such as TIPS, SCPL, gas foaming, and freeze drying. GelMA hydrogels have shown promising potential in cell proliferation and tissue regeneration. In addition, graphene and its derivatives have been instrumental in the fabrication of bioactive scaffolds for cartilage regeneration. The introduction of additive manufacturing technologies, specifically 3D bioprinting, has significantly improved the precision and control of scaffold fabrication.
Strategic One-Pot Synthesis of 1,2,3-Triazole-Based Dihydropyrimidinone Hybrids Using Magnetic CuFe2O4 NPS as Heterogeneous Catalyst and Their DFT, Molecular Docking Studies
Authors: Bendi Anjaneyulu , Mittal Chinmay , Chauhan Vishaka , Dharma Rao G. B.
Published: February 2024

A rapid and enormously professional new-flanged 3,5-disubstituted triazole derivatives were synthesized by the one-pot five-component condensation reaction in the course of transesterification followed by the Biginelli/Click reaction in aqueous medium using magnetic CuFe2O4 NPs as heterogeneous catalyst beneath ultrasonic acceleration in aqueous medium. The synthesized 3,5-disubstituted triazole derivatives were finely characterized and the characterized desired target molecules were employed for the quantum chemical calculations for each reactant and product have been well thought-out using density functional theory. Furthermore, the molecular docking and ADMET revision of all the derivatives have been achieved as digestive enzyme and Cathepsin-B inhibitors and their connections with BSA to treat different diseases.
Indoor 2D Autonomous Exploration with an Omnidirectional Robot: A Strategy Based on Rapidly-Exploring Random Trees
Authors: Sumer Ecem , Imamoglu Mehmed Rafi , Temeltas Hakan
Published: February 2024

An essential characteristic of a fully autonomous robot is the capability to examine an unfamiliar environment and construct a representation of it. The challenge of autonomous exploration involves overcoming various sub-problems, including Simultaneous Localization and Mapping (SLAM), motion planning, target identification, and informed decision-making for target selection. This paper presents a frontier-based methodology to identify potential navigation targets for the autonomous exploration of unknown environments by an omnidirectional robot. Permanent and temporary Rapidly-exploring Random Tree (RRT)-based structures are used to search the map and detect frontier points. A novel temporary RRT-based structure, Frontier Temporary Tree, is introduced in this study. It is noteworthy that RRT is solely used to search the explorable space for frontier points and does not contribute to motion planning. A cost-benefit analysis, taking into account path cost, heading cost, and information gain, is used to evaluate the frontier points and determine the best target among them. The proposed method is subjected to rigorous testing through both simulation and experimental studies with an omnidirectional robot under real-world scenarios. Comparative results from simulation studies show that our method consistently outperforms, demonstrating its robustness and efficacy.
Synthesis of sodium silicate and its application of dielectric relaxation spectroscopy — A report
Authors: Chakraborty Sudhangshu , Sheikh Md Ayub
Published: February 2024

This study aims to explain the dielectric relaxation in sodium silicate (Na2SiO3) and its direct dependence on temperature across various frequencies. The study examines and elucidates the involvement of various types of polarization in the thermo-active dielectric relaxation process. Both low-frequency dielectric dispersion and complex impedance play pivotal roles in controlling the thermo-active dielectric relaxation process. Utilizing complex data plots, the study actively, and prominently illustrates the relaxation process.
Exploring the Emergency Planning Requirements: A Qualitative Research Study at the Kingdom of Saudi Arabia
Authors: Alrehaili Naif R
Published: February 2024

This study aimed to explore emergency planning requirements for managing disasters in the Kingdom of Saudi Arabia (KSA). The study adopted interpretivism; an inductive approach; a descriptive survey; and qualitative methods to address its aim. The techniques used included a literature review and semi-structured interviews. The study sample consisted of 13 experts from the KSA General Directorate of Civil Defence (GDCD). The data were analyzed by using content analysis. The study findings revealed that the emergency planning requirements are administrative requirements, including regulations and legislation; technical requirements, which include equipment; human resources, including staff and responders; identifying, analyzing, and evaluating risks; determining the tasks and responsibilities of the relevant agencies and stakeholders; qualified leadership; determining the chain of command at national and local levels; coordination and cooperation among stakeholders; knowledge gained from local or international experiences; updated database; the availability of sufficient financial resources; completed infrastructure; and improved training and practice. The study also found that although emergency planning requirements are more or less in place, there is a need for further improvement and development; specifically, there is a need for better understanding, knowledge, and awareness. Consequently, it strongly recommends that all emergency planning requirements developed from this study should be implemented simultaneously and as an integrated whole. By doing so, it could help decision makers and emergency planners at government emergency agencies to improve, develop, and reinforce emergency planning, specifically in reducing disaster risks.
Improving Monocular 3D Object Detection by Synthetic Images with Virtual Depth
Authors: He Chenhang , Zhang Lei
Published: February 2024

Exploiting geometric features is a common approach to enhance monocular 3D object detection. However, their performance is limited due to the absence of depth information. To address this limitation, an external depth estimator can be employed to predict depth, but this approach significantly reduces the efficiency and flexibility of the model. Instead of relying on a costly depth estimator, we propose a depth-aware monocular 3D object detector that is trained using augmented training data. Specifically, we utilize reference images and their corresponding depth maps to train an efficient rendering module, which synthesizes a variety of photo-realistic images with different virtual depths. By learning from these images, the detector adapts its features to depth variations. Furthermore, we introduce an auxiliary module that guides the network to learn more informative representations from the depth images. Both modules are removed after training, resulting in no additional computational overhead during the final deployment.
An Expert System for Indian Sign Language Recognition Using Spatial Attention–based Feature and Temporal Feature
Authors: Das Soumen , Biswas Saroj Kr. , Purkayastha Biswajit
Published: February 2024

Sign Language (SL) is the only means of communication for the hearing-impaired people. Normal people have difficulty understanding SL, resulting in a communication barrier between hearing impaired people and hearing community. However, the Sign Language Recognition System (SLRS) has helped to bridge the communication gap. Many SLRs are proposed for recognizing SL; however, a limited number of works are reported for Indian Sign Language (ISL). Most of the existing SLRS focus on global features other than the Region of Interest (ROI). Focusing more on the hand region and extracting local features from the ROI improves system accuracy. The attention mechanism is a widely used technique for emphasizing the ROI. However, only a few SLRS used the attention method. They employed the Convolution Block Attention Module and temporal attention but Spatial Attention (SA) is not utilized in previous SLRS. Therefore, a novel SA based SLRS named Spatial Attention-based Sign Language Recognition Module (SASLRM) is proposed to recognize ISL words for emergency situations. SASLRM recognizes ISL words by combining convolution features from a pretrained VGG-19 model and attention features from a SA module. The proposed model accomplished an average accuracy of 95.627% on the ISL dataset. The proposed SASLRM is further validated on LSA64, WLASL, and Cambridge Hand Gesture Recognition datasets where, the proposed model reached an accuracy of 97.84%, 98.86%, and 98.22%, respectively. The results indicate the effectiveness of the proposed SLRS in comparison with the existing SLRS.
A Product-form Network for Systems with Job Stealing Policies
Authors: Olliaro Diletta , Casale Giuliano , Marin Andrea , Rossi Sabina
Published: February 2024

In queueing networks, product-form solutions are of fundamental importance to efficiently compute performance metrics in complex models of computer systems. The product-form property entails that the steady-state probabilities of the joint stochastic process underlying the network can be expressed as the normalized product of functions that only depend on the local state of the components. In many relevant cases, product-forms are the only way to perform exact quantitative analyses of large systems.

In this work, we introduce a novel class of product-form queueing networks where servers are always busy. Applications include model of systems where successive refinements on jobs improve the processes quality but are not strictly required to obtain a result. To this aim, we define a job movement policy that admits instantaneous migrations of jobs from non-empty waiting buffers to empty ones. Thus, the resulting routing scheme is state-dependent. This class of networks maximizes the system throughput.

This model can be implemented with arbitrary topology, including feedback, and both in an open and closed setting. As far as closed systems are concerned, we give a convolution algorithm and the corresponding mean value analysis to compute expected performance indices for closed models.