bluuebunny/crossref_metadata_2025 huggingface dataset:
Physical and Chemical Approaches of Photovoltaic Parameters in Dye-Sensitized Solar Cells to ZnO/ZnS:rGO-Based Photoelectrodes
Authors: Pedra Thiago Kurz , Carvalho Ramon Dadalto , Fernandes Cristian Dias , Gularte Luciano Timm , Jauris Carolina Ferreira de Matos , Moreira Eduardo Ceretta , Ferrer Mateus Meneghetti , Raubach Cristiane Wienke , Cava Sérgio da Silva , Jardim Pedro Lovato Gomes , Longo Elson , Moreira Mario Lucio
Published: December 2024

This study proposes an alternative process for obtaining ZnO/ZnS:rGO heterostructures for use in DSSCs and as promising materials for potential applications in other photonic process, such as photocatalysis and photodetection. The compound was obtained through a microwave-assisted hydrothermal method, where the electromagnetic waves and temperature were crucial points for forming ZnO, ZnO/ZnS and reducing graphene oxide (GO). The XRD, Raman, FT-IR, and FESEM results presented the structural, morphological, and chemical structures, which suggest the conversion of ZnO to ZnS for samples with higher concentrations of reduced graphene oxide (rGO). Additionally, the optical properties were analyzed through photoluminescence and UV-Vis measurements. The electrical behavior of the photoelectrodes was investigated through J-V measurements in light and dark conditions. In addition, electrochemical impedance spectroscopy (EIS) was performed and Bode phase plots were created, analyzing the recombination processes and electron lifetime. The J-V results showed that for smaller amounts of rGO, the dye-sensitized solar cells (DSSC) efficiency improved compared to the ZnO/ZnS single structure. However, it was observed that with more significant amounts of rGO, the photocurrent value decreased due to the presence of charge-trapping centers. On the other hand, the best results were obtained for the ZnO/ZnS:1% rGO sample, which showed an increase of 14.2% in the DSSC efficiency compared to the pure ZnO/ZnS photoelectrode.
Neighbor Session Solutions for Integrated Routing Protocols
Authors: Kontsek Martin , Segec Pavel , Moravcik Marek , Smiesko Juraj
Published: December 2024

This paper proposes a novel methodology for the design of dual-stack IP routing protocols focused on neighborships and routing messages transport. The first part describes currently used dual-stack IP routing protocols, their history, and key features. The description of four identified combinations based on a number of neighbor sessions and protocol used for the transport of routing messages is presented afterward. These combinations are introduced as Protocol Integration Solution Classes (PISCs) in this paper. Colored Petri nets (CPNs) are selected as a formal method to create a model of each PISC. The following parts deal with a detailed description and analysis of the created Protocol Integration Solution Class models, which are also verified and compared with each other. Based on the comparison of each PISC model simulation step, the PISC 2 class is selected as the most efficient one. The last part of the paper formulates recommendations for the dual-stack IP routing protocol design based on the results presented in this paper.
Design of Urban Indicators to Optimize the Implementation of Low-Impact Techniques in Semi-Arid Cities
Authors: Volpi-León Valeria , Seck-Tuoh-Mora Juan Carlos , Bigurra-Alzati Carlos Alfredo , Juárez-Sedano Alma Delia , Lizárraga-Mendiola Liliana
Published: December 2024

The study area is a densely populated residential zone located in central Mexico, characterized by a semi-arid climate and diverse land uses, including domestic, commercial, and services. In the study area, water demand is assessed based on land use requirements set by national and local regulations, and an urban configuration pinpoints spaces suitable for rainwater harvesting for self-consumption. This research proposes indicators based on urban, demographic, and hydrological parameters to assess the effectiveness of low-impact development (LID) techniques, such as rooftop rainwater harvesting, aimed at reducing water scarcity in a residential area vulnerable to water shortages in a semi-arid city in the Global South. Additionally, hydrological design conditions are defined to estimate the potential volumes of recoverable water. Indicators for infiltrated water, available water for consumption, runoff water, and sufficient water are established. This framework enables the development of strategies to mitigate water scarcity and improve water management in the area.
Integrating Radar-Based Obstacle Detection with Deep Reinforcement Learning for Robust Autonomous Navigation
Authors: Pico Nabih , Montero Estrella , Vanegas Maykoll , Erazo Ayon Jose Miguel , Auh Eugene , Shin Jiyou , Doh Myeongyun , Park Sang-Hyeon , Moon Hyungpil
Published: December 2024

This study presents an approach to autonomous navigation for wheeled robots, combining radar-based dynamic obstacle detection with a BiGRU-based deep reinforcement learning (DRL) framework. Using filtering and tracking algorithms, the proposed system leverages radar sensors to cluster object points and track dynamic obstacles, enhancing precision by reducing noise and fluctuations. A BiGRU-enabled DRL model is introduced, allowing the robot to process sequential environmental data and make informed decisions in dynamic and unpredictable environments, achieving collision-free paths and reaching the goal. Simulation and experimental results validate the proposed method’s efficiency and adaptability, highlighting its potential for real-world applications in dynamic scenarios.
Analysis and Research on Oil Injection Lubrication of Variable Tooth Thickness Gear Based on CFD Method
Authors: Zhang Huicheng , Liu Yongping , Chen Qi
Published: December 2024

Variable tooth thickness gears have significant effects on the characteristics of the flow field inside the gearbox and the lubrication efficiency under high-speed operating conditions due to their complex parameters, such as tooth profile, cone angle, rotational speed, and oil injection speed. To investigate the impact mechanism of oil injection velocity on the working flow field of high-speed variable tooth thickness gears under varying parameters, this paper establishes an oil injection lubrication model under high rotational speeds of variable tooth thickness gears, based on computational fluid dynamics (CFD) methods and the Volume of Fluid (VOF) model, combined with the dynamic mesh technique. This paper analyzes the lubrication issues at the initial oil injection moment of involute variable tooth thickness gears. By computing the lubricant distribution state at 0.1 s after the oil injection onset based on the stabilized flow field under no-oil-injection condition, discussions are conducted on the single-phase and two-phase flow fields within the gear casing at different cone angles and rotational speeds separately examining the flow states near the oil nozzle and the distribution patterns of lubricant at the meshing portions. The results indicate that, without oil injection, the pressure near the oil nozzle gradually increases with an increase in rotational speed and decreases with an increase in cone angle; at the initial oil injection moment, the lubricant volume fraction at the gear meshing portions gradually increases with an increase in rotational speed and rises with an increase in cone angle.
Temperature Effect on Stability of Tunnel Face Under Unsaturated Seepage Condition
Authors: Xie Yi , Liao Hong , Zhou De
Published: December 2024

As tunnel excavation technology matures and the demand for transportation infrastructure continues to grow, several high-temperature tunnels have successively emerged in high geothermal areas. The construction of tunnels in high-temperature regions is gradually becoming a new challenge encountered in the engineering field. This study aims to conduct a stability analysis of tunnel face excavation under different temperatures. In addition, soil is often considered to be unsaturated. A framework for assessing the stability of tunnel faces in unsaturated soils under fluctuating temperature conditions is proposed, with an analytical approach. The theoretical basis of this framework is established on the influence of temperature on the shear strength of unsaturated soil. The matric suction of unsaturated soil changes with temperature, thereby inducing variations in shear strength. The temperature-induced variation in apparent cohesion is quantified utilizing a temperature-sensitive effective stress model coupled with a soil–water characteristic curve. These models are subsequently incorporated into the stability assessment of tunnel faces in unsaturated soils under steady-state flow conditions. A three-dimensional logarithmic spiral model is utilized to ascertain the unsupported pressure on tunnel faces, with the safety factor (FS) being calculated through an iterative methodology. Subsequently, a comprehensive suite of parametric studies is undertaken to explore the influence of temperature on tunnel face stability under unsaturated seepage conditions, offering valuable insights for practical engineering endeavors.
Sound-Induced Round Window Vibration—Experiment and Numerical Simulations of Energy Transfer Through the Cochlea of the Human Ear
Authors: Zablotni Robert , Tudruj Sylwester , Latalski Jaroslaw , Szymanski Marcin , Kucharski Andrzej , Zając Grzegorz , Rusinek Rafał
Published: December 2024

This study investigates the dynamic properties of the human middle ear and the energy transfer phenomena between the stapes footplate (SF) and the round window membrane (RWM) under sound stimulation. A series of laboratory tests were conducted, and a numerical model of the system was prepared. During the experiments, vibrations in human temporal bones were recorded using a Laser Doppler Vibrometer (LDV), and the frequency response functions (FRFs) of the RWM and SF footplate were computed. Key resonances were identified, with notable differences in vibration amplitude depending on whether the artificial external ear canal was left open or closed. To evaluate the amplification of acoustic waves within the cochlea, the authors proposed a novel index defined as the ratio of the FRF of the RWM and SF, respectively. The performed computations showed that signal amplification is particularly noticeable in the frequency range from 1 to 2 kHz. Subsequently, a simplified computational fluid dynamics (CFD) model of the cochlea was developed to simulate internal pressure distribution within the scala vestibuli (SV) and scala tympani (ST) spaces. The numerical computations of acoustic signal amplification showed good agreement with the experimental data, particularly at the frequencies of 1 and 2 kHz. These findings provide new insights into cochlear acoustics and offer a potential tool for evaluating pathological disorders and designing prosthetic devices.
You Only Attack Once: Single-Step DeepFool Algorithm
Authors: Li Jun , Xu Yanwei , Hu Yaocun , Ma Yongyong , Yin Xin
Published: December 2024

Adversarial attacks expose the latent vulnerabilities within artificial intelligence systems, necessitating a reassessment and enhancement of model robustness to ensure the reliability and security of deep learning models against malicious attacks. We propose a fast method designed to efficiently find sample points close to the decision boundary. By computing the gradient information of each class in the input samples and comparing these gradient differences with the true class, we can identify the target class most sensitive to the decision boundary, thus generating adversarial examples. This technique is referred to as the “You Only Attack Once” (YOAO) algorithm. Compared to the DeepFool algorithm, this method requires only a single iteration to achieve effective attack results. The experimental results demonstrate that the proposed algorithm outperforms the original approach in various scenarios, especially in resource-constrained environments. Under a single iteration, it achieves a 70.6% higher success rate of the attacks compared to the DeepFool algorithm. Our proposed method shows promise for widespread application in both offensive and defensive strategies for diverse deep learning models. We investigated the relationship between classifier accuracy and adversarial attack success rate, comparing the algorithm with others. Our experiments validated that the proposed algorithm exhibits higher attack success rates and efficiency. Furthermore, we performed data visualization on the ImageNet dataset, demonstrating that the proposed algorithm focuses more on attacking important features. Finally, we discussed the existing issues with the algorithm and outlined future research directions. Our code will be made public upon acceptance of the paper.
STGAN: Swin Transformer-Based GAN to Achieve Remote Sensing Image Super-Resolution Reconstruction
Authors: Huo Wei , Zhang Xiaodan , You Shaojie , Zhang Yongkun , Zhang Qiyuan , Hu Naihao
Published: December 2024

Super-resolution (SR) of remote sensing images is essential to compensate for missing information in the original high-resolution (HR) images. Single-image super-resolution (SISR) technique aims to recover high-resolution images from low-resolution (LR) images. However, traditional SISR methods often result in blurred and unclear images due to the loss of high-frequency details in LR images at high magnifications. In this paper, a super-segmental reconstruction model STGAN for remote sensing images is proposed, which fuses the Generative Adversarial Networks (GANs) and self-attention mechanism based on the Reference Super Resolution method (RefSR). The core module of the model consists of multiple CNN-Swin Transformer blocks (MCST), each of which consists of a CNN layer and a specific modified Swin Transformer, constituting the feature extraction channel. In image hypersegmentation reconstruction, the optimized and improved correlation attention block (RAM-V) uses feature maps and gradient maps to improve the robustness of the model under different scenarios (such as land cover change). The experimental results show that the STGAN model proposed in this paper exhibits the best image data perception quality results with the best performance of LPIPS and PI metrics in the test set under RRSSRD public datasets. In the experimental test set, the PSNR reaches 31.4151, the SSIM is 0.8408, and the performance on the RMSE and SAM metrics is excellent, which demonstrate the model’s superior image reconstruction details in super-resolution reconstruction and highlighting the great potential of RefSR’s application to the task of super-scalar processing of remotely sensed images.
Artificial Intelligence Technology for Assessing the Practical Knowledge of Air Traffic Controller Students Based on Their Responses in Multitasking Situations
Authors: Antoško Matej , Polishchuk Volodymyr , Kelemen Martin , Korniienko Anton , Kelemen Miroslav
Published: December 2024

The main goal of the research is to develop an artificial intelligence technology to assess the practical knowledge of air traffic controller (ATCo) students based on their responses in simulated multitasking situations using the proposed neuro-fuzzy model verified in experiments. An informational neuro-fuzzy model was developed and verified on 157,500 real data points. It illustrates an example of inferring the level of practical knowledge in selected ATCo students who were tested using a device measuring the reaction time and relative error rate in multiple-task tasks. The average error in the incorrect response was 7.7% of the experimental data. Data processing was performed using fuzzy set theory and intellectual knowledge analysis. These measurement results are useful for an individual approach to the student’s education to understand and master the correct solutions to achieve the desired educational results. Ensuring a personal approach to the student’s education is key to acquiring the necessary skills, knowledge, and competencies in the profile of the graduate. The developed technology will enable the integration of automated knowledge and skills assessment systems into the real educational process and the identification of problematic topics and tasks in the training of individuals. The result of the conducted research was used for the software design for the practical application in the flight training of ATCo students.
Video Games in Rehabilitation Programs for People with Parkinson’s Disease: A Systematic Review
Authors: Quirosa-Galán Isabel , García-Bravo Sara , Fabara-Rodríguez Anthia Cristina , Rodríguez-Pérez Mª Pilar , Huertas-Hoyas Elisabet , Pérez-Corrales Jorge , Fernández-Gómez Gemma , Donovan Madeleine , García-Bravo Cristina
Published: December 2024

Background: Parkinson’s disease is a neurodegenerative disorder affecting the central and peripheral nervous systems. Its treatment combines pharmacological and rehabilitative approaches, aimed at improving motor symptoms and preventing cognitive decline. Virtual reality emerges as a complementary rehabilitative option, showing efficacy in enhancing motor and cognitive aspects. This study systematically reviews the effectiveness of virtual reality in the rehabilitation of individuals with Parkinson’s disease. Methods: A systematic review was carried out. The Jadad scale was used to assess the methodological quality of the included studies, and the Oxford Center for Evidence-Based Medicine criteria were applied to determine the level of evidence and recommendation. The review followed PRISMA guidelines, with a literature search conducted in databases such as Cochrane and PubMed. Results: The studies indicate improvements in gait, balance, and overall motor function in Parkinson’s patients using virtual reality, though limitations such as small sample sizes and the lack of control groups in some studies are noted. Conclusions: Virtual reality proves to be an effective tool in Parkinson’s rehabilitation, enhancing balance and motor function. However, more studies with adequate methodological quality and larger sample sizes are needed to validate these findings.
The Effects of a Complex Shoulder Exercise Program with Respiratory Training on Muscle Activity and Posture in Individuals Exhibiting Scapular Internal Rotation
Authors: Yan Xin , Zhou Xing-Han , Kim Tae-Ho
Published: December 2024

The purpose of this study was to compare the effects of a complex shoulder exercise program including respiratory training with those of a similar program including thorax-stabilization exercises on muscle activity and posture in individuals exhibiting scapular internal rotation. The subjects of this study were 32 adults with scapular internal rotation. The exercise group performed the complex shoulder exercise program with respiratory training (EG), while the control group performed the complex shoulder exercise program with thorax-stabilization exercises (CG). After 4 weeks of training, the changes in muscle activity and posture were measured. The differences between the two groups were assessed through comparative analysis using an independent t-test. The paired t-test revealed significant disparities in craniovertebral angle (CVA) and sagittal shoulder angle (SSA) posture between the measurements before and after the programs (p < 0.05). Additionally, the paired t-test indicated notable differences in muscle activity of the upper trapezius (UT), middle trapezius (MT), lower trapezius (LT), and serratus anterior (SA) muscles (p < 0.05). According to the findings, both intervention groups presented significant improvements in cervical and shoulder posture and muscle activity. Consequently, combination of the complex shoulder exercise program with either respiratory training or thorax-stabilization exercises had a favorable impact on posture and muscle activity among individuals exhibiting scapular internal rotation.
Development of a Digital Twin of the Harbour Waters and Surrounding Infrastructure Based on Spatial Data Acquired with Multimodal and Multi-Sensor Mapping Systems
Authors: Tomczak Arkadiusz , Stępień Grzegorz , Kogut Tomasz , Jedynak Łukasz , Zaniewicz Grzegorz , Łącka Małgorzata , Bodus-Olkowska Izabela
Published: December 2024

Digital twin is an attractive technology for the representation of objects due to its ability to produce precise measurements and their geovisualisation. Of special interest is the application and fusion of various remote sensing techniques for shallow river and inland water areas, commonly measured using conventional surveying or multimodal photogrammetry. The construction of spatial digital twins of river areas requires the use of multi-platform and multi-sensor measurements to obtain reliable data of the river environment. Due to the high dynamics of river changes, the cost of measurements and the difficult-to-access measurement area, the mapping should be large-scale and simultaneous. To address these challenges, the authors performed an experiment using three measurement platforms (boat, plane, UAV) and multiple sensors to acquire both cloud and image spatial data, which were integrated temporally and spatially. The integration methods improved the accuracy of the resulting digital model by approximately 20 percent.
The Effect of Enriching Tea Infusion with Fruit Additives on Their Antioxidant Properties and the Profile of Bioactive Compounds
Authors: Chilczuk Barbara , Materska Małgorzata , Staszowska-Karkut Monika , Pabich Marzena
Published: December 2024

The aim of the study was to assess the effect of fruit additives on the health-promoting properties of tea infusions. Black and white tea infusions enriched with fruit additives (lemon, quince, strawberry, and sweet pepper) were investigated. To assess the effect of the additives on the properties of the infusions, the content of phenols, antiradical activity, and reducing properties were analysed. The LC-QTOF-MS method facilitated the identification of catechins and the determination of their content. The principal component analysis was used to define the relationship between catechins and the health-promoting properties of the beverages. The research proved that the strawberry and sweet pepper additives improved the quality of the black tea, where the highest antiradical and antioxidant activity was noted. In turn, the additives used for the enrichment of the white tea had a negative effect on its health-promoting properties. The statistical analyses revealed that epicatechin gallate and epicatechin had the greatest impact on the antioxidant properties of the black tea and the white tea, respectively.
Research on Robotic Polishing Process of Marble with Complex Curved Surface Based on Sol–Gel Flexible Tools
Authors: Huang Shengui , Guo Yaobin , Huang Jixiang , Yin Fangchen , Lu Jing
Published: December 2024

Newly developed Sol–gel (SG) flexible tools are used to polish complex marble surfaces with a robot to achieve a high-gloss, low-roughness, and scratch-free surface. The SG tool is composed of semi-solid abrasive and flexible fiber pads, which can realize a dual yielding effect at both the micro and macro levels so that the SG flexible tool can better fit the complex curved surface. Through the simulation analysis of the contact of SG flexible tools, the relationship between different curvature surfaces and polishing forces was obtained. Based on the Preston material removal theory, constant-pressure polishing of surfaces of different curvatures was achieved by simulating the contact force distribution between the SG flexible tool and the marble surface, as well as the constant-pressure material removal profile. By optimizing the space of the polishing trajectory, the uniformity of the material removal depth was improved, and the consistency of surface quality after polishing was enhanced. By establishing a model that correlates the optimum polishing trajectory space with curvature for surfaces of different curvatures, the effective prediction of material removal profiles for robotic polishing of surfaces of different curvatures was achieved. These strategies aim to ensure surface consistency after polishing complex curved surfaces under different conditions, thereby increasing the product’s added value. This research provides initial theoretical guidance for the application of SG flexible tools in the robotic polishing of marble with complex curved surfaces.
Lightweight Photo-Response Non-Uniformity Fingerprint Extraction Algorithm Based on an Invertible Denoising Network
Authors: Yuan Zihang , Xiao Yanhui , Tian Huawei
Published: December 2024

The photo-response non-uniformity (PRNU) noise of imaging sensors significantly aids digital forensics and judicial identification, as it can be used as the fingerprint for uniquely identifying individual imaging devices. During the PRNU fingerprint extraction, it is very important for source camera identification to estimate the natural noise from real-world images. Most existing deep learning-based neural networks have a large number of model parameters, and they may not be practical in realistic scenarios such as deploying the model on small devices like smartphones and remote forensics equipment. In this paper, we present a lightweight PRNU fingerprint extraction algorithm based on an invertible denoising network (InvDN) for source camera identification. Specifically, to reduce the number of parameters, the deep network uses a constant amount of memory to compute the gradient and employs the same parameters for both forward and backward propagation. In addition, by introducing an information-loss-less reversible network, more complete PRNU fingerprint information can be extracted. Experimental results show that this algorithm exhibits superior PRNU fingerprint extraction performance and generalization ability compared to the state-of-the-art PRNU fingerprint extraction algorithms.
Low Tensor Rank Constrained Image Inpainting Using a Novel Arrangement Scheme
Authors: Ma Shuli , Fan Youchen , Fang Shengliang , Yang Weichao , Li Li
Published: December 2024

Employing low tensor rank decomposition in image inpainting has attracted increasing attention. This study exploited novel tensor arrangement schemes to transform an image (a low-order tensor) to a higher-order tensor without changing the total number of pixels. The developed arrangement schemes enhanced the low rankness of images under three tensor decomposition methods: matrix SVD, tensor train (TT) decomposition, and tensor singular value decomposition (t-SVD). By exploiting the schemes, we solved the image inpainting problem with three low-rank constrained models that use the matrix rank, TT rank, and tubal rank as constrained priors. The tensor tubal rank and tensor train multi-rank were developed from t-SVD and TT decomposition, respectively. Then, ADMM algorithms were efficiently exploited for solving the three models. Experimental results demonstrate that our methods are effective for image inpainting and superior to numerous close methods.
Influence of Aging Processes on the Characteristics of Power LEDs Soldered Using Composite Solder Pastes
Authors: Górecki Krzysztof , Ptak Przemysław , Skwarek Agata
Published: December 2024

In this paper, the issue of an aging process’s influence on power LEDs’ properties is considered. Some measured DC characteristics of these devices and their thermal and optical parameters obtained are presented after considering different values of the aging process’ duration. Components soldered using different metal–ceramic composite pastes, e.g., with TiO2, were tested. The tested devices and the used measurement setup are described. The measurement procedure is described in detail. The obtained measurement results are discussed. It is shown that after the aging process at elevated temperatures, worse properties were observed for the power LEDs soldered using classical SACX0307 alloy. Most of the samples soldered with reference alloy (not composite) were damaged during the test. The best properties were obtained for the samples soldered with solder paste with the addition of titanium oxide.
Study on the Effects and Mechanisms of Action of Biological Enzymes on the Quality of Summer Rock Tea Extract
Authors: Wang Zixuan , Yang Bo , Zhou Peng , Yang Guang , Zhao Zhijun
Published: December 2024

The gallated catechin content in Wuyi Rock Tea is higher in the summer, leading to a more bitter and less desirable taste. Here, tannase, tyrosinase, and laccase were used to treat summer Rougui Wuyi Rock Tea extracts. The effects of single and combined enzymes on the taste of the tea extracts and their mechanisms of action were analyzed. Compared with the no-enzyme-treated sample, the sensory score results showed that tannase was the most effective, increasing the bitterness and astringency scores by 113.9% and 255.3%, respectively. Among the combined enzyme treatments, the samples treated with tannase and tyrosinase yielded the best sensory scores, with bitterness and astringency scores increasing by 141.2% and 289.0%, respectively. Data obtained using an electronic tongue confirmed the role of these enzymes, showing that, in addition to bitterness and astringency, enzyme treatment also influenced the bitterness aftertaste and astringency aftertaste, as well as its sourness and sweetness. Further product analysis revealed that tannase hydrolyzes the ester bonds on the gallacyl groups in gallated catechins, converting them to non-gallated catechins, while tyrosinase and laccase oxidize the phenolic hydroxyl groups on catechins to form o-quinone, leading to the production of theaflavins and improved tea quality. This study presents an effective approach to improving the quality of summer tea using biological enzymes.
Software-Defined Radio-Based Internet of Things Communication Systems: An Application for the DASH7 Alliance Protocol
Authors: Joosens Dennis , BniLam Noori , Berkvens Rafael , Weyn Maarten
Published: December 2024

Software-Defined Radio (SDR) technology has been a very popular and powerful prototyping device for decades. It finds applications in both fundamental research or application-oriented tasks. Additionally, the continuing rise of the Internet of Things (IoT) necessitates the validation, processing, and decoding of a large number of received signals. This is where SDRs can be a valuable instrument. In this work, we present an open-source software system using GNU Radio and SDRs, which improves the comprehension of the physical layer aspects of Internet of Things communication systems. Our implementation is generic and application-agnostic. Therefore, it can serve as a learning and investigation instrument for any IoT communication system. Within this work, we implement the open-source DASH7 Alliance Protocol (D7AP). The developed software tool can simulate synthetic DASH7 signals, process recorded data sets, and decode the received DASH7 packets in real time using an SDR front-end. The software is accompanied by three data sets collected in controlled, indoor, and suburban environments. The experimental results revealed that the total packet losses of the data sets were 0%, 2.33%, and 16.67%, respectively. Simultaneously, the three data sets were received by a dedicated DASH7 gateway with total packet losses of 0%, 3.83%, and 7.92%, respectively.
Wireless May Benefit Blockchain
Authors: Kim Seungmo , Choi Junsung
Published: December 2024

Wireless technologies now take every part of one’s everyday life. As such, it will be no longer a surprise if a blockchain system is composed of wirelessly connected nodes. However, wireless communication is known for its inherent unreliability caused by noise, interference, limited bandwidth, etc. Motivated by this fundamental problem, this paper investigates the impact of wireless communications on the performance of three representative consensus mechanisms, viz., proof of work (PoW), proof of stake (PoS), and proof of coverage (PoC). It features a comprehensive analytical framework that mathematically derives metrics quantifying the scalability and the level of decentralization of the three consensus mechanisms, constituting a key contribution of this work. The paper then proceeds to present extensive simulation results as a means to confirm the underpinning theoretical findings. Overall, we emphasize that the framework’s holisticity will allow it to be applied to diverse consensus mechanisms.
A Novel Procedure in Scrutinizing a Cantilever Beam with Tip Mass: Analytic and Bifurcation
Authors: Alanazy Asma , Moatimid Galal M. , Amer T. S. , Mohamed Mona A. A. , Abohamer M. K.
Published: December 2024

An examination was previously derived to conclude the understanding of the response of a cantilever beam with a tip mass (CBTM) that is stimulated by a parameter to undergo small changes in flexibility (stiffness) and tip mass. The study of this problem is essential in structural and mechanical engineering, particularly for evaluating dynamic performance and maintaining stability in engineering systems. The existing work aims to study the same problem but in different situations. He’s frequency formula (HFF) is utilized with the non-perturbative approach (NPA) to transform the nonlinear governing ordinary differential equation (ODE) into a linear form. Mathematica Software 12.0.0.0 (MS) is employed to confirm the high accuracy between the nonlinear and the linear ODE. Actually, the NPA is completely distinct from any traditional perturbation technique. It simply inspects the stability criteria in both the theoretical and numerical calculations. Temporal histories of the obtained results, in addition to the corresponding phase plane curves, are graphed to explore the influence of various parameters on the examined system’s behavior. It is found that the NPA is simple, attractive, promising, and powerful; it can be adopted for the highly nonlinear ODEs in different classes in dynamical systems in addition to fluid mechanics. Bifurcation diagrams, phase portraits, and Poincaré maps are used to study the chaotic behavior of the model, revealing various types of motion, including periodic and chaotic behavior.
The Singularity of the K4 Homeomorphic Graph
Authors: Ma Haicheng
Published: December 2024

Let G be a finite simple graph and let A(G) be its adjacency matrix. Then, G is singular if A(G) is singular. The singularity of graphs is of certain interest in graph theory and algebraic combinatorics. For positive integers ai≥2, i=1,2,…,6. Insert a1−2, a2−2, a3−2, a4−2, a5−2 and a6−2 vertices in the six edges of the complete graph K4, respectively, then the resulting graph is called the K4 homeomorphic graph, denoted by K(a1,a2,a3,a4,a5,a6). In this paper, we give the necessary and sufficient condition for the singularity of K(a1,a2,a3,a4,a5,a6), and we also show that the probability of a K4 homeomorphic graph K(a1,a2,a3,a4,a5,a6) being a singular graph is equal to 193512.
Handling Multicollinearity and Outliers in Logistic Regression Using the Robust Kibria–Lukman Estimator
Authors: Lukman Adewale F. , Mohammed Suleiman , Olaluwoye Olalekan , Farghali Rasha A.
Published: December 2024

Logistic regression models encounter challenges with correlated predictors and influential outliers. This study integrates robust estimators, including the Bianco–Yohai estimator (BY) and conditionally unbiased bounded influence estimator (CE), with the logistic Liu (LL), logistic ridge (LR), and logistic KL (KL) estimators. The resulting estimators (LL-BY, LL-CE, LR-BY, LR-CE, KL-BY, and KL-CE) are evaluated through simulations and real-life examples. KL-BY emerges as the preferred choice, displaying superior performance by reducing mean squared error (MSE) values and exhibiting robustness against multicollinearity and outliers. Adopting KL-BY can lead to stable and accurate predictions in logistic regression analysis.
A Comparative Study and Numerical Solutions for the Fractional Modified Lorenz–Stenflo System Using Two Methods
Authors: Elbadri Mohamed , Abdoon Mohamed A. , Alzahrani Abdulrahman B. M. , Saadeh Rania , Berir Mohammed
Published: December 2024

This paper provides a solution to the new fractional-order Lorenz–Stenflo model using the adaptive predictor–corrector approach and the ρ-Laplace New Iterative Method (LρNIM), representing an extensive comparison between both techniques with RK4 related to accuracy and error analysis. The results show that the suggested approaches allow one to be more accurate in analyzing the dynamics of the system. These techniques also produce results that are comparable to the results of other approximate techniques. The techniques can, thus, be used on a wider class of systems in order to provide more accurate results. These techniques also appropriately identify chaotic attractors in the system. These techniques can be applied to solve various numerical problems arising in science and engineering in the future.
On the Construction of a Two-Step Sixth-Order Scheme to Find the Drazin Generalized Inverse
Authors: Zhang Keyang , Soleymani Fazlollah , Shateyi Stanford
Published: December 2024

This study introduces a numerically efficient iterative solver for computing the Drazin generalized inverse, addressing a critical need for high-performance methods in matrix computations. The proposed two-step scheme achieves sixth-order convergence, distinguishing it as a higher-order method that outperforms several existing approaches. A rigorous convergence analysis is provided, highlighting the importance of selecting an appropriate initial value to ensure robustness. Extensive numerical experiments validate the analytical findings, showcasing the method’s superior speed and efficiency, making it an advancement in iterative solvers for generalized inverses.
On Trees with a Given Number of Vertices of Fixed Degree and Their Two Bond Incident Degree Indices
Authors: Albalahi Abeer M. , Rizwan Muhammad , Bhatti Akhlaq A. , Gutman Ivan , Ali Akbar , Alraqad Tariq , Saber Hicham
Published: December 2024

This paper is mainly concerned with the study of two bond incident degree (BID) indices, namely the variable sum exdeg index SEIa and the general zeroth-order Randić index Rα0. The minimum values of SEIa and Rα0 in the class of all trees of fixed order containing no vertex of even degree are obtained for a>1 and α∈[0,1]; also, the maximum value of Rα0 in the mentioned class is determined for 0<α<1. Moreover, in the family of all trees of fixed order and with a given number of vertices of even degrees, the extremum values of SEIa and Rα0 are found for every real number α∉{0,1} and a>1. Furthermore, in the class of all trees of fixed order and with a given number of vertices of maximum degree, the minimum values of SEIa and Rα0 are determined when a>1 and α does not belong to the closed interval [0,1]; in the same class, the maximum values of Rα0 are also found for 0<α<1. The graphs that achieve the obtained extremal values are also determined.
External Validation of Deep Learning Models for Classifying Etiology of Retinal Hemorrhage Using Diverse Fundus Photography Datasets
Authors: Khosravi Pooya , Huck Nolan A. , Shahraki Kourosh , Ghafari Elina , Azimi Reza , Kim So Young , Crouch Eric , Xie Xiaohui , Suh Donny W.
Published: December 2024

Retinal hemorrhage (RH) is a significant clinical finding with various etiologies, necessitating accurate classification for effective management. This study aims to externally validate deep learning (DL) models, specifically FastVit_SA12 and ResNet18, for distinguishing between traumatic and medical causes of RH using diverse fundus photography datasets. A comprehensive dataset was compiled, including private collections from South Korea and Virginia, alongside publicly available datasets such as RFMiD, BRSET, and DeepEyeNet. The models were evaluated on a total of 2661 images, achieving high performance metrics. FastVit_SA12 demonstrated an overall accuracy of 96.99%, with a precision of 0.9935 and recall of 0.9723 for medical cases, while ResNet18 achieved a 94.66% accuracy with a precision of 0.9893. A Grad-CAM analysis revealed that ResNet18 emphasized global vascular patterns, such as arcuate vessels, while FastVit_SA12 focused on clinically relevant areas, including the optic disk and hemorrhagic regions. Medical cases showed localized activations, whereas trauma-related images displayed diffuse patterns across the fundus. Both models exhibited strong sensitivity and specificity, indicating their potential utility in clinical settings for accurate RH diagnosis. This study underscores the importance of external validation in enhancing the reliability and applicability of AI models in ophthalmology, paving the way for improved patient care and outcomes.
Artificial Intelligence Transforming Post-Translational Modification Research
Authors: Kim Doo Nam , Yin Tianzhixi , Zhang Tong , Im Alexandria K. , Cort John R. , Rozum Jordan C. , Pollock David , Qian Wei-Jun , Feng Song
Published: December 2024

Post-Translational Modifications (PTMs) are covalent changes to amino acids that occur after protein synthesis, including covalent modifications on side chains and peptide backbones. Many PTMs profoundly impact cellular and molecular functions and structures, and their significance extends to evolutionary studies as well. In light of these implications, we have explored how artificial intelligence (AI) can be utilized in researching PTMs. Initially, rationales for adopting AI and its advantages in understanding the functions of PTMs are discussed. Then, various deep learning architectures and programs, including recent applications of language models, for predicting PTM sites on proteins and the regulatory functions of these PTMs are compared. Finally, our high-throughput PTM-data-generation pipeline, which formats data suitably for AI training and predictions is described. We hope this review illuminates areas where future AI models on PTMs can be improved, thereby contributing to the field of PTM bioengineering.
Optimal Vase Solution for Gerbera hybrida Cut Flower Keeping Fresh by Activating SA and Cytokinin Signaling and Scavenging Reactive Oxygen Species
Authors: Xia Chaoshui , Cao Yiyang , Gan Weixin , Lin Huifeng , Li Huayang , Lin Fazhuang , Lu Zhenhong , Chen Weiting
Published: December 2024

Gerbera (Gerbera hybrida) is a popular cut flower on the market, so extending its vase life (VL) is an important goal in the horticultural industry. The aim of this study was to improve the freshness of gerbera cut flowers through the optimal solution (OS) and to analyze its preservation mechanism. We used chitosan (COS), calcium chloride (CaCl2), and citric acid (CA) as the main ingredients of the vase solution and determined the OS ratio of 104 mg/L of COS, 92 mg/L of CA, and 93 mg/L of CaCl2 using the Box–Behnken design-response surface method (BBD-RSM). Gerbera preservation results showed that the VL of the OS was 14.5 days, which was significantly longer than that of flowers maintained in the Basic Vase Solution (BVS) and the Commercial Formulation (CF) and was highly consistent with the theoretical VL of 14.57 d. Transcriptome analysis indicated that the OS might extend VL by regulating phytohormone signaling pathways, such as cytokinin and salicylic acid signaling. The qRT-PCR analysis of key candidate genes supported these findings, with significant upregulation observed in genes related to cytokinin synthesis (e.g., GhIPT1 and GhIPT9), salicylic acid signaling related to pathogen defense (e.g., GhTGA1, GhTGA4, GhNPR1, and GhRBOHA), and plant wax synthesis and stress response (e.g., GhKCS5, GhCUT1, and GhKCS6). Further, transcriptome GO-enrichment and physiological analysis showed that the OS might extend VL of Gerbera cut flowers by scavenging reactive oxygen species, including by activating the expression of genes related to oxidoreductase activity and the activities of antioxidant-system-related enzymes catalase (CAT), peroxidase (POD), ascorbate peroxidase (APX), and superoxide dismutase (SOD), while decreasing the malondialdehyde (MDA) content. These results provide valuable insights into the mechanisms underlying the extended VL of gerbera cut flowers and offer a foundation for developing more effective preservation techniques.
Do Endangered Glacial Relicts Have a Chance for Effective Conservation in the Age of Global Warming? A Case Study: Salix lapponum in Eastern Poland
Authors: Arciszewski Michał , Pogorzelec Magdalena , Parzymies Marzena , Bronowicka-Mielniczuk Urszula , Mieczan Tomasz
Published: December 2024

The abiotic stresses to which plants are exposed, especially in times of climate change, can result in the disruption of natural plant physiological processes. Sudden atmospheric phenomena may increase the risk of failure in protecting rare and extinction-threatened plant species by translocation. This study aimed to determine the effect of extreme ambient temperatures on the condition and physiological response of Salix lapponum plantlets used for their reintroduction into the natural habitat. Salix lapponum plants obtained by micropropagation methods at different stages of growth under laboratory conditions were subjected to a biological experiment. Plants were exposed for 12 h to temperature extremes (0 °C and 30 °C), after which the values of selected markers of the biochemical response were determined, such as photosynthetic pigments and anthocyanin content, guaiacol peroxidase and catalase activity, the presence of ROS and the RWC value. The study showed that plants at early growth stages were sensitive to low-temperature stress. In contrast, older ones showed a stronger response to high temperature, marked by an increased anthocyanin content and guaiacol peroxidase activity. It was also found that a short exposure to temperature extremes did not change the photosynthetic pigment content or catalase activity. The results of the study may be an important indication for the optimization of plant acclimatization methods in the process of their active protection by species translocation.
The Liver X Receptor Promotes Immune Homeostasis via Controlled Activation of the Innate Immune System in the Liver
Authors: Nakashima Hiroyuki , Kearney Bradley M. , Kinoshita Manabu
Published: December 2024

The liver is an indispensable metabolic organ, responsible for accumulating and transporting various nutritional compounds in hepatocytes. However, the transport of these materials from the liver is an energetically intensive task because they contain a considerable number of hydrophobic components, including free cholesterol, and require specialized transfer proteins to shuttle these substances through an aqueous phase. Liver X receptors (LXRs) induce the expression of cholesterol transporters in macrophages to transport free cholesterol derived from apoptotic cells into extracellular space via high-density lipoproteins. Additionally, LXRs control innate immune cells through two major mechanisms: upregulating the phagocytic activity of macrophages and suppressing inflammatory reactions to prevent aggressive activation of immune cells. Therefore, the primary role of LXRs is to accelerate efferocytosis without provoking inflammation and facilitate the transfer of free cholesterol from the intracellular space. This mechanism makes the innate immune system a substantial contributor to systemic metabolic control. Concomitantly, LXRs are important factors in regulating systemic defense mechanisms through the efficient regulation of immune cells. LXR activation, therefore, has great potential for clinical applications in the treatment of metabolic, infectious, and autoimmune diseases. In this review, we discuss the current understanding of the link between LXRs and innate immune cells in the liver, along with prospects for clinical applications of LXR agonists.