bluuebunny/crossref_metadata_2025 huggingface dataset:
A Generator for Recursive Zip Files
Authors: Van Mello Ruben , Audenaert Pieter
Published: October 2024

This paper explores the concept of zip quines, which are zip files that contain themselves upon extraction, extending the idea of computational self-reference. While only two individuals, Russ Cox and Erling Ellingsen, have created such entities, this study focuses on Cox’s method to develop a generator for these files. Overcoming the initial limitations, the generator allows for the inclusion of additional files within the zip quine. Additionally, this research explores the concept of looped zip files, wherein a zip archive contains another archive. This archive then contains the initial zip file. By offering practical methodologies and insights, this study advances the understanding and application of quines in computer science.
Rifampicin-Loaded PLGA/Alginate-Grafted pNVCL-Based Nanoparticles for Wound Healing
Authors: Bibire Tudor , Timofte Daniel Vasile , Dănilă Radu , Panainte Alina-Diana , Yilmaz Cătălina Natalia , Bibire Nela , Agoroaei Luminița , Ghiciuc Cristina Mihaela
Published: October 2024

The topical therapy with rifampicin (RF)-based formulations is beneficial for treating postoperative wound infections and to accelerate healing. Despite recent research highlighting the antibiotic’s significant anti-inflammatory properties, limited topical wound healing products are currently available. The present study aimed to prove that the newly synthesized nanoparticles based on grafted alginate and poly(N-vinylcaprolactam) (pNVCL) and poly-lactic-co-glycolic acid (PLGA) contribute to the healing process of a wound. The methods used were at first the synthesis of the copolymer of alginate and pNVCL via grafting from technique and radical polymerization followed by water-in-oil-in water (W/O/W) emulsification; as oil phase PLGA dissolved in dichloromethane (DCM) was used. The formed nanoparticles were than characterized. The loaded RF was determined to be 160 µg/mL for a 20 mg formulation and within a four-hour time frame approximately 10% of the total loaded amount was released. The inhibitory concentrations (IC50) were 192.1 µg/mL for the nanoparticle, 208.8 µg/mL for pure rifampicin, and 718.1 µg/mL for the rifampicin-loaded nanoparticles. Considering the double role rifampicin was used for, the result was considered satisfactory in the way that these formulations could be used predominantly for postoperative wound irrigation in order to avoid infections and to improve healing.
Height Control System for Wind Turbines Based on Critical Wind Speed Calculation
Authors: Fazylova Alina , Iliev Teodor , Stoyanov Ivaylo , Siemens Eduard
Published: October 2024

The increasing frequency of wind turbine failures due to extreme weather conditions necessitates the implementation of new solutions to enhance their operational reliability. This paper presents an automatic rotor drop system specifically designed for wind turbines equipped with the Onipko rotor. The system aims to protect turbines from damage caused by critical wind speeds, reducing maintenance costs and extending the equipment’s lifespan. The unique design of the Onipko rotor allows it to operate at wind speeds as low as 0.1 m/s. However, its high drag coefficient and lack of aerodynamic optimization make it susceptible to mechanical stress and structural instability under strong gusts, requiring additional protective measures. The paper presents a calculation of the critical wind speed at which protective measures must be initiated. Through mathematical modeling, this study demonstrates the effectiveness of the rotor drop system in ensuring safe operation at wind speeds reaching 23.5 m/s. The optimization of the PI controller parameters provides a rapid response and stability, significantly enhancing the resilience of wind turbines to adverse weather conditions.
Investigation into the Yaw Control of a Twin-Rotor 10 MW Wind Turbine
Authors: Elkodama Amira , Abdellatif A. , Shaaban S. , Rushdi Mostafa A. , Yoshida Shigeo , Ismaiel Amr
Published: October 2024

Multi-rotor system (MRS) wind turbines can provide a competitive alternative to large-scale wind turbines due to their significant advantages in reducing capital, transportation, and operating costs. The main challenges of MRS wind turbines include the complexity of the supporting structure, mathematical modeling of the aerodynamic interaction between the rotors, and the yaw control mechanism. In this work, MATLAB 2018b/Simulink® software was used to model and simulate a twin-rotor wind turbine (TRWT), and an NREL 5 MW wind turbine was used to verify the model outputs. Different random signals of wind velocities and directions were used as inputs to each rotor to generate different thrust loads, inducing twisting moments on the main tower. A yaw controller system was adapted to ensure that the turbine constantly faced the wind to maximize the power output. A DC motor was used as the mechanism’s actuator. The goal was to achieve a compromise between aligning the rotors with the wind direction and reducing the torque induced on the main tower. A comparison between linear and nonlinear controllers was performed to test the yaw system actuator’s response at different wind speeds and directions. Sliding mode control (SMC) was chosen, as it was suitable for the nonlinearity of the system, and its performance showed a faster response compared with the PID controller, with a settling time of 0.17 sec and a very low overshoot. The controller used the transfer function of the motor to generate a sliding surface. The dynamic responses of the controlled angle are shown and discussed. The controller showed promising results, with a suitable response and low chattering signals.
Speciation of the Removed Pollutants in Bioremediation of Hydrocarbon-Contaminated Soil
Authors: Vergnano Andrea , Raffa Carla Maria , Godio Alberto , Chiampo Fulvia
Published: October 2024

The biological removal of a mixture of soil contaminants, namely, hydrocarbons, is not equally efficient for each compound. Some pollutants can be metabolized by the microbial consortium but also generated again as by-products from the removal of others. At the end of the runs, notwithstanding the high integral removal, single compounds can still be present with a relevant concentration. This paper presents the results achieved in a study of the aerobic degradation of diesel oil in three mesocosms carried out for several months with the same operative conditions. They differed in biological management: Natural Attenuation (NA), Biostimulated without inoculation (BS), and Biostimulated with Inoculation (BS + IN). At the end of the runs, the pollution removal was calculated by measuring the residual diesel oil, both as an average in the total amount of soil and only at the bottom of each column. The overall removal was around 2%, 66%, and 72% for NA, BS and BS + IN, reduced to 0%, 48%, and 47%, respectively, if measured only at the bottom. For the biostimulated mesocosms, the speciation of the hydrocarbons was carried out to assess their concentration. The findings evidence the need to delve deeper into this issue and assess the speciation of contaminants.
Design and Stability Analysis of Six-Degree-of-Freedom Hydro-Pneumatic Spring Wheel-Leg
Authors: Wu Zhibo , Jiao Bin , Sun Chuanmeng , Xin Zezhou , Jia Yinzhi , Zhao Heming
Published: October 2024

Traditional hydro-pneumatic spring suspensions are limited to a single vertical degree of freedom, which cannot accommodate the significant technological changes introduced by the new in-wheel motor drive mode. Integrating the motor into the vehicle’s hub creates a direct motor drive mode, replacing the traditional engine–transmission–drive shaft configuration. Together with the dual in-wheel motor wheelset structure, this setup can achieve both drive and differential steering functions. In this study, we designed a six-arm suspension wheel-leg device based on hydro-pneumatic springs, and its structural composition and functional characteristics are presented herein. The external single-chamber hydro-pneumatic springs used in the six-arm structure suspension were analyzed and mathematically modeled, and the nonlinear characteristic curves of the springs were derived. To overcome the instability caused by inconsistent extension lengths of the hydro-pneumatic springs during horizontal steering, the spring correction force, horizontal rotational torque, consistency, and stiffness of the six-degree-of-freedom hydro-pneumatic spring wheel-leg device were analyzed. Finally, with the auxiliary action of tension springs, the rotational torque of the hydro-pneumatic springs and the tension resistance torque of the tension spring counterbalanced each other, keeping the resultant torque on the wheelset at approximately 0 N∙m. The results suggest that the proposed device has excellent self-stabilizing performance and meets the requirements for straight-line driving and differential steering applications. This device provides a new approach for the drive mode and suspension design of the dual in-wheel motor wheelset.
Ship Type Selection and Cost Optimization of Marine Container Ships Based on Genetic Algorithm
Authors: Xiao Ping , Wang Haiyan
Published: October 2024

In the context of the deep-sea transportation supply chain, this paper addresses the complex decision-making problem of vessel allocation and carbon emission optimization for container shipping routes. A bi-level programming model is established, with the upper level aiming to minimize the total operational cost and the lower level focusing on minimizing carbon emissions. Using an example of an operator with five different types of vessels, a genetic algorithm is employed to determine the optimal vessel allocation scheme. The results indicate that the vessel allocation scheme obtained through multiple iterations of the model effectively reduces both carbon emissions and operational costs. Under the condition that the preset labor cost increases year by year, the use of model optimization can significantly reduce the growth of total operating costs. This paper provides theoretical support and practical guidance for shipping companies aiming to optimize decision-making in order to reduce operational costs and carbon emissions.
The Effect of Silver Nanoparticles on Bond Strength of Calcium Silicate-Based Sealer: An In Vitro Study
Authors: Bukhary Sundus , Alkahtany Sarah , AlDabeeb Dalal
Published: October 2024

The aim of this study was to evaluate the bond strength of the calcium silicate-based sealer (CSS) modified with the silver nanoparticles (AgNPs) using the single-cone technique (SC) and the continuous wave condensation (CWC) technique, measured by a universal testing machine. The AgNPs and the modified sealers were characterized by scanning electron microscopy and transmission electron microscopy. One hundred single-rooted extracted human permanent teeth with a single root canal were cleaned and shaped with a Protaper Next system. The teeth were randomly divided into four groups (n = 25) as follows: Group 1, canals were obturated using the SC technique with TotalFill® BC Sealer. Group 2, canals were obturated using the SC technique with TotalFill® BC Sealer mixed with AgNPs. Group 3, canals were obturated using the CWC technique with TotalFill® HiFlow BC Sealer. Group 4, canals were obturated using the CWC technique with TotalFill® HiFlow BC Sealer mixed with AgNPs. After two weeks, 1 mm-thick dentin slices were cut and exposed to a push-out bond strength test using a universal testing machine. Specimens were examined under a digital microscope to determine the mode of failure. Statistical analysis was performed using ANOVA and Tukey multiple comparison tests (p < 0.05). The nanoparticle characterization revealed a spherical morphology with no obvious aggregations. The results showed that group 4 had the highest dislodgement resistance compared to all groups (p < 0.05). Group 4 was significantly higher in push-out bond strength value than group 1 (p < 0.001) and group 3 (p < 0.003), but not significantly higher than group 2. Cohesive failure was the most prevalent failure mode among all groups. It can be concluded that the incorporation of silver nanoparticles into the calcium silicate-based sealer significantly increased the bond strength. The warm obturation approach demonstrated significantly higher resistance to dislodgment as compared to the single-cone technique.
BHI-YOLO: A Lightweight Instance Segmentation Model for Strawberry Diseases
Authors: Hu Haipeng , Chen Mingxia , Huang Luobin , Guo Chi
Published: October 2024

In complex environments, strawberry disease segmentation models face challenges, such as segmentation difficulties, excessive parameters, and high computational loads, making it difficult for these models to run effectively on devices with limited computational resources. To address the need for efficient running on low-power devices while ensuring effective disease segmentation in complex scenarios, this paper proposes BHI-YOLO, a lightweight instance segmentation model based on YOLOv8n-seg. First, the Universal Inverted Bottleneck (UIB) module is integrated into the backbone network and merged with the C2f module to create the C2f_UIB module; this approach reduces the parameter count while expanding the receptive field. Second, the HS-FPN is introduced to further reduce the parameter count and enhance the model’s ability to fuse features across different levels. Finally, by integrating the Inverted Residual Mobile Block (iRMB) with EMA to design the iRMA, the model is capable of efficiently combining global information to enhance local information. The experimental results demonstrate that the enhanced instance segmentation model for strawberry diseases achieved a mean average precision (mAP@50) of 93%. Compared to YOLOv8, which saw a 2.3% increase in mask mAP, the improved model reduced parameters by 47%, GFLOPs by 20%, and model size by 44.1%, achieving a relatively excellent lightweight effect. This study combines lightweight architecture with enhanced feature fusion, making the model more suitable for deployment on mobile devices, and provides a reference guide for strawberry disease segmentation applications in agricultural environments.
A Thermopile-Based Colorimetric Temperature Measurement Method for Arbitrary Bandwidth
Authors: Ji Qing , Ma Youwei , Ding Guoqing , Wang Kundong , Chen Xin
Published: October 2024

Colorimetric temperature measurement is an essential technique in radiometric thermometry. Traditional colorimetric methods determine temperature by comparing the ratio of radiative energies within two narrow bands at specific wavelengths, effectively mitigating the effects of the emissivity of the measured object and ambient conditions. However, these methods typically approximate integration using area calculations when calculating radiative energy. This article eliminates this approximation and calculates the radiative energy with accurate integration. Based on the principle of monotonicity, this article demonstrates for the first time that when two narrow-band infrared radiations are selected, as long as their wavelength ranges do not overlap, the ratio of radiative energies within these bands maintains a monotonic relationship with the measured temperature. This allows the temperature to be inferred from the energy ratio. Furthermore, this conclusion is extended to arbitrary widths of bands as long as their wavelength ranges do not overlap. Building on this foundation, a thermopile-based colorimetric temperature measurement method for arbitrary bandwidth is proposed. Simulation experiments validate this method, showing that the energy ratio maintains a monotonic relationship with the measured temperature as long as the infrared radiation wavelength ranges absorbed by the thermopile do not overlap. The simulation results are consistent with the mathematical proof.
A Self-Calibration Method for Robot End-Effector Using Spherical Constraints
Authors: Wang Xiong , Ren Wenze , Wang Kang , Liu Jun , Lin Jinsong , Feng Jiahui , Zheng Jun , Li Fei
Published: October 2024

A self-calibration method utilizing spherical constraints is proposed for calibration of robot end-effectors. The method establishes a mathematical model to account for both the geometric errors of the robot and the deformation errors of the end-effector. A nonlinear least-squares parameter identification technique based on spherical constraints is employed to achieve autonomous calibration of the end-effector. Contrasted with methodologies relying on point plane or distance constraints, this novel technique delivers superior positioning accuracy, streamlined operational procedures and enhanced efficiency. Both simulation and experimental validation confirm that the self-calibration method using spherical constraints improves the positioning accuracy of the robot end-effector from 3 mm to 0.3 mm, showing the effectiveness of the method.
Random Forest Spatial-Temporal and State Space Models to Assess the Impact of Bushfire-Induced Aerosol Events on Ozone Depletion in Australia
Authors: Hudson Irene , Pedro-Suvorov Phillip , Kocak Servet
Published: October 2024

Serious concerns exist that the increasing frequency of fires may delay the recovery of ozone given increasing temperatures due to climate change. Australian bushfires from September 2019 to February 2020 were catastrophic. A random forest spatial-temporal (RF sp) analysis using satellite data to detect an association between Australian bushfires and stratosphere ozone on the local depletion of ozone in the vicinity of fires in three regions of Australia (Pacific Ocean, Victoria, NSW) has shown a significant reduction in ozone attributable to aerosols from fires. By intervention analysis, increases in aerosols in all three regions were shown to have a significant and ongoing impact 1–5 days later on reducing ozone (p < 0.0001). Intervention analysis also gave similar periods of aerosol exceedance to those found by Hidden Markov models (HMMs). HMMs established a significant and quantifiable decline in ozone due to bushfire-induced aerosols, with significant lags of 10–25 days between times of aerosol exceedance and subsequent ozone level decline in all three regions.
Mediterranean Aquaponics: Fasting and Refeeding in a Polyculture Aquaponic System
Authors: Mitsopoulos Ioannis , Papadopoulou Anastasia , Vlahos Nikolaos , Berillis Panagiotis , Levizou Efi , Mente Eleni
Published: October 2024

The use of Mediterranean euryhaline fish and halophytes in aquaponics presents a sustainable and alternative approach to food production. The present study investigates the effect of compensatory growth on sea bass (Dicentrarchus labrax) and Baltic prawn (Palaemon adspersus) co-cultivated with the halophytic glasswort (Salicornia europaea). Three autonomous systems were established, each containing forty-five sea bass, nine Baltic prawns, and eight glasswort plants, with different feeding regimes for each treatment: (i) daily feeding (treatment A), (ii) three days of feeding per week followed by four days of fasting (treatment B), and (iii) feeding for seven days followed by seven days of fasting (treatment C). The growth performance of the fish was significantly higher in treatment B. Conversely, the feed conversion ratio (FCR) was notably higher in treatment A. As for the prawns, their final body weight and length were similar across all treatments. The glasswort plants also demonstrated significantly improved growth in treatment B. These results indicate that the incorporation of feeding and fasting cycles can be an effective feed management strategy for polyculture aquaponic systems. Additionally, food deprivation had a positive impact on the growth performance of both glasswort and prawns.
The Impact of a 12-Week Workplace Physical Activity Program on the Quality of Life of Sedentary Workers: A Pilot Study
Authors: Rocha Fernanda Viomar , Matos Rui , Monteiro Diogo , Jacinto Miguel , Antunes Raúl , Amaro Nuno , Santos Tiago , Rodrigues Filipe
Published: October 2024

Office workers frequently display behavioral patterns marked by extended periods of sedentary and seated work. In this context, the implementation of a workplace exercise program has been shown to be effective in mitigating health-related risk factors. This study aimed to evaluate the impact of a 12-week workplace exercise program on the quality of life of employees whose primary occupational duties involve prolonged sitting. The final sample comprised 19 participants (6 females and 13 males), aged between 21 and 48 years (M = 32.26; SD = 9.03). Among these participants, 78.9% reported engaging in a hybrid work arrangement, 15.8% followed an on-site work regimen, and 5.3% worked remotely. Furthermore, 84.2% of participants reported sitting for 6 to 8 h per day, while 15.8% reported sitting for between 9 and 12 h daily. The quality of life of participants was assessed using the Medical Outcomes Study 36-Item Short Form Health Survey. A paired samples t-test was employed to examine differences between dependent variables. The results revealed a statistically significant improvement in general health (p < 0.01), vitality (p < 0.01), social functioning (p < 0.05), and the mental health summary measure (p < 0.04). Promoting physical activity through workplace exercise programs offers substantial benefits for workers’ health and quality of life, contributing to the prevention of occupational diseases.
A Cross-Lingual Media Profiling Model for Detecting Factuality and Political Bias
Authors: Lin Chichen , Wang Yongbin , Li Chenxin , Fan Weijian , Xu Junhui , Wang Qi
Published: October 2024

Media profiling offers valuable insights to enhance the objectivity and reliability of news coverage by providing comprehensive analysis, but the diversity in languages posed significant challenges to our identification of factuality and political bias of non-English sources. The limitation of existing media analysis research is its concentration on a singular high-resource language, and it hardly extends to languages beyond English. To address this, we introduce xMP, a dataset for zero-shot cross-lingual media profiling tasks. xMP’s cross-lingual test set encompasses 34 non-English languages and 18 language families, extending media profiling beyond English resources and allowing us to assess cross-lingual media profiling model performance. Additionally, we propose a method, named R-KAT, to enhance the model’s zero-shot cross-lingual transfer learning capability by building virtual multilingual embedding. Our experiments illustrate that our method improves the transferability of models in cross-lingual media profiling tasks. Additionally, we further discuss the performance of our method for different target languages. Our dataset and code are publicly available.
The Effects of Strata Orientation and Water Presence on the Stability of Engineered Slopes Using DIPS and FLACSlope: A Case Study of Tubatse and Fetakgomo Engineered Road Slopes
Authors: Nkanyane Fumani , Sengani Fhatuwani , Rapholo Maropene Tebello Dinah , Skrzypkowski Krzysztof , Zagórski Krzysztof , Zagórska Anna , Rokita Tomasz
Published: October 2024

This paper combines empirical observations, kinematic analysis, and numerical simulation to investigate slope failure susceptibility, with practical implications for regional infrastructure projects. Six slopes along the R37 road were analyzed to assess the impact of strata orientation and water presence on slope stability. The results indicate that various factors interact to destabilize the mechanical integrity of both rock and soil materials. Dry slopes were found to be less vulnerable to failure, although geological conditions remained influential. Numerical modeling using FLACSlope (version 8.1) revealed that the factor of safety (FoS) decreases as the water presence increases, highlighting the critical need for effective drainage solutions. Kinematic analysis, incorporating DIPS modeling and toppling charts, identified toppling as the most likely failure mode, with a 90% susceptibility rate, followed by planar and wedge failures at 6% and less than 5%, respectively. These findings are validated by the observed slope conditions and empirical data. Planar failures were often remnants of both sliding and toppling failures. Given the significant risk posed to road infrastructure, particularly where FoS hovers just above the stability threshold, this study emphasizes the importance of proactive, long-term slope monitoring and early mitigation strategies to prevent catastrophic failures. The results can guide infrastructure design and maintenance, ensuring safer and more resilient roadways in regions prone to slope instability. Nonetheless, the use of sophisticated slope stability modeling techniques is recommended for a thorough understanding of the mechanical dynamics of the slope material, and for catering to the shortfalls of the techniques applied in this paper.
Configurational Design of a Hybrid System Based on an Air–Water Heat Pump and Biomass Boiler for a Rural Dwelling
Authors: Uche Javier , Tajik Jamalabad Milad , Martínez Amaya
Published: October 2024

Hybrid energy systems combine multiple energy sources and storage technologies to enhance performance and meet diverse energy needs. Hybrid heat pump systems are particularly suitable for heating and cooling buildings in rural areas. Air-source heat pumps have two well-known disadvantages during the coldest period of the year, when the building’s heating load is at its peak: the heat pump’s capacity is reduced and it needs to perform defrost cycles. A potential solution is to size the heat pump to cover only a portion of the peak load and to use a second heat generator in a hybrid heat pump system. There is a gap in the literature regarding the configurational analysis of hybrid heat pump (HHP) systems, particularly in terms of combining heat pumps and biomass boilers, and evaluating their efficiency, economic aspects, and environmental impact. Thus, in this research, a dynamic model of a HHP system, consisting of an air-to-water heat pump paired with a biomass boiler as a backup, is presented. Various configurations of the HHP system have been developed to evaluate key performance indicators, such as efficiency, emissions, operational costs, and other relevant factors. The findings of this paper indicate that the energy performance of HHP systems is significantly affected by the system layout, heat pump size, cut-off temperature, and the control algorithm used to activate the heat generators. Moreover, series operation of HHP systems is not only more efficient than parallel operation but also results in lower emissions and reduced operation costs. As expected, the energy loss associated with defrost cycles significantly impacts the overall performance of a hybrid system based on an air-source heat pump. Finally, the impact of the cut-off temperature on the key parameters in the configuration analysis was examined, and the optimal performance of the HHP system, in terms of minimizing operational costs and emissions, was depicted using a heat map diagram.
Reconstructing High Dynamic Range Image from a Single Low Dynamic Range Image Using Histogram Learning
Authors: Lin Huei-Yung , Lin Yi-Rung , Lin Wen-Chieh , Chang Chin-Chen
Published: October 2024

High dynamic range imaging is an important field in computer vision. Compared with general low dynamic range (LDR) images, high dynamic range (HDR) images represent a larger luminance range, making the images closer to the real scene. In this paper, we propose an approach for HDR image reconstruction from a single LDR image based on histogram learning. First, the dynamic range of an LDR image is expanded to an extended dynamic range (EDR) image. Then, histogram learning is established to predict the intensity distribution of an HDR image of the EDR image. Next, we use histogram matching to reallocate pixel intensities. The final HDR image is generated through regional adjustment using reinforcement learning. By decomposing low-frequency and high-frequency information, the proposed network can predict the lost high-frequency details while expanding the intensity ranges. We conduct the experiments based on HDR-Real and HDR-EYE datasets. The quantitative and qualitative evaluations have demonstrated the effectiveness of the proposed approach compared to the previous methods.
Enhancing IoT Security Using GA-HDLAD: A Hybrid Deep Learning Approach for Anomaly Detection
Authors: Mutambik Ibrahim
Published: October 2024

The adoption and use of the Internet of Things (IoT) have increased rapidly over recent years, and cyber threats in IoT devices have also become more common. Thus, the development of a system that can effectively identify malicious attacks and reduce security threats in IoT devices has become a topic of great importance. One of the most serious threats comes from botnets, which commonly attack IoT devices by interrupting the networks required for the devices to run. There are a number of methods that can be used to improve security by identifying unknown patterns in IoT networks, including deep learning and machine learning approaches. In this study, an algorithm named the genetic algorithm with hybrid deep learning-based anomaly detection (GA-HDLAD) is developed, with the aim of improving security by identifying botnets within the IoT environment. The GA-HDLAD technique addresses the problem of high dimensionality by using a genetic algorithm during feature selection. Hybrid deep learning is used to detect botnets; the approach is a combination of recurrent neural networks (RNNs), feature extraction techniques (FETs), and attention concepts. Botnet attacks commonly involve complex patterns that the hybrid deep learning (HDL) method can detect. Moreover, the use of FETs in the model ensures that features can be effectively extracted from spatial data, while temporal dependencies are captured by RNNs. Simulated annealing (SA) is utilized to select the hyperparameters necessary for the HDL approach. In this study, the GA-HDLAD system is experimentally assessed using a benchmark botnet dataset, and the findings reveal that the system provides superior results in comparison to existing detection methods.
Impedance Spectroscopy of Lanthanum-Doped (Pb0.75Ba0.25)(Zr0.70Ti0.30)O3 Ceramics
Authors: Adamczyk-Habrajska Małgorzata , Makowska Jolanta , Pikula Tomasz , Wodecka-Duś Beata , Bartkowska Joanna A. , Panek Rafał , Osińska Katarzyna
Published: October 2024

This study examines the effects of La3+ doping on (Pb0.75Ba0.25)(Zr0.70Ti0.30)O3(PBZT) ceramics, which were synthesized using the conventional solid-state reaction method. X-ray diffraction analysis confirmed that the PBZT structure, including PBZT doped with La3+ at concentrations x = 1 at.% and x = 2 at.%, exhibited a rhombohedral (R3c) space group, while higher doping levels of x = 3 at.% and x = 4 at.% led to a dominant cubic (Pm-3m) phase with approximately 30% of a remnant rhombohedral component. Scanning electron microscopy (SEM, JEOL JSM-7100F TTL LV, Jeol Ltd., Tokyo, Japan) and energy dispersive X-ray spectroscopy (EDS) were utilized to investigate the structure and morphology of these ceramics. The findings indicated that the chemical composition of the ceramic samples closely corresponded to the initial stoichiometry of the ceramic powder. An increase in the amount of lanthanum results in a decrease in the average grain size of the ceramics. The electrical properties were further evaluated using complex impedance spectroscopy (IS) over a range of temperatures and frequencies, as well as temperature dependence of DC conductivity. The similarity in the changes in activation energy for DC conductivity and grain boundary conductivity, caused by lanthanum ion modification, allows for the conclusion that grain boundaries are the primary microstructural element responsible for conductivity in these materials.
A Thermogravimetric Analysis of Biomass Conversion to Biochar: Experimental and Kinetic Modeling
Authors: Călin Cătălina , Sîrbu Elena-Emilia , Tănase Maria , Győrgy Romuald , Popovici Daniela Roxana , Banu Ionuț
Published: October 2024

This study investigates the pyrolytic decomposition of apple and potato peel waste using thermogravimetric analysis (TGA). In addition, using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS), the influence of pyrolysis temperature on the physicochemical characteristics and structural properties of biochar was studied. The degradation of biomass samples was studied between 25 °C and 800 °C. Although apple and potato peel decomposition present similar thermogravimetric profiles, there are some differences that can be evidenced from DTG curves. Potato peel showed one degradation peak in the range 205–375 °C with 50% weight loss; meanwhile, the apple peel exhibited two stages: one with a maximum at around 220 °C and about 38% weight loss caused by degradation of simple carbohydrates and a second peak between 280 °C and 380 °C with a maximum at 330 °C, having a weight loss of approximately 24%, attributed to cellulose degradation. To gain more insight into the phenomena involved in biomass conversion, the kinetics of the reaction were analyzed using thermal data collected in non-isothermal conditions with a constant heating rate of 5, 10, 20, or 30 °C /min. The kinetic analysis for each decomposed biomass (apple and potato) was carried out based on single-step and multi-step type techniques by combining the Arrhenius form of the decomposition rate constant with the mass action law. The multi-step approaches provided further insight into the degradation mechanisms for the whole range of the decomposition temperatures. The effect of temperature on biomass waste structure showed that the surface morphologies and surface functional groups of both samples are influenced by the pyrolysis temperature. A higher pyrolysis temperature of 800 °C results in the disappearance of the bands characteristic of the hydroxyl, aliphatic, ether, and ester functional groups, characteristic of a porous surface with increased adsorption capacity. Therefore, this study concludes that biomass waste samples (apple and potato) can produce high yields of biochar and are a potential ecological basis for a sustainable approach. The preliminary adsorption tests show a reasonably good nitrate removal capacity for our biochar samples.
Analysis of Enterprise Internet of Things Maturity Models: A Review
Authors: Solis Pino Andrés Felipe , Ruiz Pablo H. , Mon Alicia , Collazos Cesar Alberto , Moreira Fernando
Published: October 2024

Maturity models are valuable tools when assessing the readiness and progress of technology incorporation in organizations, providing information for decision-making, resource allocation, and competitive advantage. The Internet of Things is a technology paradigm of global importance, especially for organizations, as it supports productivity improvements, real-time analysis, and customer satisfaction. Therefore, adopting and implementing this technology in enterprises brings several challenges, such as technological, organizational, security, and maturity issues. However, secondary studies that systematically compile the existing literature on these specific mechanisms for the enterprise domain are still being determined. This article aims to address this knowledge gap by conducting a review to deepen and synthesize the existing knowledge. This research followed established methodologies and protocols to synthesize and analyze the state of the art in the area; 489 documents were retrieved from seven bibliographic databases, and, applying inclusion and exclusion criteria, 36 primary studies were selected. The results indicate that the typical structures of maturity models incorporate technological, organizational, human, performance, and security dimensions through graded levels that denote the sophistication of the Internet of Things. Measurement techniques and metrics vary from model to model. There are few empirical validations or standardized improvement frameworks. The main conclusion is that there is a diversity of models, dimensions, indicators, and methods and a need for more comprehensive, adaptable, and user-friendly tools to help companies assess their Internet of Things maturity and inform future development strategies.
Traffic Congestion Scheduling for Underground Mine Ramps Based on an Improved Genetic Scheduling Algorithm
Authors: Miao Wenkang , Zhao Xingdong
Published: October 2024

The dispatching of trackless transportation on the ramp of underground metal mines is closely related to the transportation efficiency of daily production equipment, personnel, and construction materials in the mine. The current dispatching of trackless transportation on the ramp of underground metal mines is discontinuous and imprecise, with unscientific vehicle arrangement leading to low efficiency and transportation congestion. This paper presents this study, which puts forward a kind of trackless transportation optimization method that can fully make use of the ramp in the roadway, and the slow slope fork point can be used for the trackless transportation vehicle passing section to improve the efficiency of trackless transportation on the ramp. This study adopts the principles of fuzzy logic and uses interval-based positioning instead of real-time positioning to effectively reduce the spatial complexity inherent in the algorithm. At the same time, this research presents a modified genetic algorithm that incorporates a time-loss fitness calculation. This innovation makes it possible to differentiate traffic priorities between different types of vehicles, thus bringing the scheduling scheme more in line with the economic objectives of the mining operations. Various parameters were determined and several sets of simulation experiments were carried out on the response speed and scheduling effect of the scheduling system, resulting in a 10 to 20 percent improvement for different vehicles in the efficiency of underground mining transport operations.
Comparison Between InterCriteria and Correlation Analyses over sEMG Data from Arm Movements in the Horizontal Plane
Authors: Angelova Maria , Raikova Rositsa , Angelova Silvija
Published: October 2024

InterCriteria analysis (ICrA) and two kinds of correlation analyses, Pearson (PCA) and Spearman (SCA), were applied to surface electromyography (sEMG) signals obtained from human arm movements in the horizontal plane. Ten healthy participants performed ten movements, eight of which were cyclic. Each cyclic movement (CM) consisted of flexion and extension phases with equal duration (10 s, 6 s, 2 s, and 1 s) and two 5 s rest poses between them. The CMs were performed with and without an added load of 0.5 kg on the wrists of the participants. The sEMG signals from six different muscles or separate muscle heads (m. deltoideus pars clavicularis, m. deltoideus pars spinata, m. brachialis, m. anconeus, m. biceps brachii, and m. triceps brachii long head) were recorded and used to compare the results of the ICrA, PCA, and SCA. All three methods found identical consonance pairs for the flexion and extension CM phases. Additionally, PCA detected two more consonance pairs in the extension phases. In this investigation, ICrA, PCA, and SCA were proven to be reliable tools when applied separately or in combination for sEMG data. These three methods are appropriate for researching arm movements in the horizontal plane and experimental protocol revision.
Short-Term Effect of Attributional Versus Non-Attributional Negative Normative Feedback on Motor Tasks: A Double-Blind Study
Authors: Fernández-Ozcorta Eduardo José , Arbinaga Félix , Checa Irene , Romero-Pérez Nehemías , Cano-Manzano Pablo , Godoy-Izquierdo Débora
Published: October 2024

Augmented feedback can alter motor performance. We examined if presenting attributional versus non-attributional negative normative feedback differently impacted short-term motor performance. With a double-blind experimental design, 49 students (36.7% female, Mage = 17.14 and SD = ±0.35) were assigned to the following two groups: G1: Attributional Negative Normative Feedback group (n = 24) and G2: Non-Attributional Negative Normative Feedback group (n = 25), with the dependent variable being the score obtained on a dart-throwing test. The results showed that those participants who received negative social comparative feedback presented in an attributional way (internal, controllable, and unstable) obtained higher scores in the dart throwing task than those who received negative social comparative feedback presented in a non-attributional way. Furthermore, these differences were maintained in the retention and transfer tests conducted 24 h after the practice phase. These findings have practical implications in motor behavior learning and performance.
Risk and Complexity Assessment of Autonomous Vehicle Testing Scenarios
Authors: Wei Zhiyuan , Zhou Hanchu , Zhou Rui
Published: October 2024

Autonomous vehicles (AVs) must fulfill adequate safety requirements before formal application, and performing an effective functional evaluation to verify vehicle safety requires extensive testing in different scenarios. However, it is crucial to rationalize the application of different scenarios to support different testing needs; thus, one of the current challenges limiting the development of AVs is the critical evaluation of scenarios, i.e., the lack of quantitative criteria for scenario design. This study introduces a method using the Spherical Fuzzy-Analytical Network Process (SF-ANP) to evaluate these scenarios, addressing their inherent risks and complexities. The method involves constructing a five-layer model to decompose scenario elements and using SF-ANP to calculate weights based on element interactions. The study evaluates 700 scenarios from the China In-depth Traffic Safety Study–Traffic Accident (CIMSS-TA) database, incorporating fuzzy factors and element weights. Virtual simulation of vehicles in the scenarios was performed using Baidu Apollo, and the performance of the scenarios was assessed by collecting the vehicle test results. The correlation between the obtained alternative safety indicators and the quantitative values confirms the validity and scientific validity of this approach. This will provide valuable guidance for categorizing audiovisual test scenarios and selecting corresponding scenarios to challenge different levels of vehicle functionality. At the same time, it can be used as a design basis to generate a large number of effective scenarios to accelerate the construction of scenario libraries and promote commercialization of AVs.
Preliminary Study of Air Pollution and Adverse Pregnancy Outcomes: A Mendelian Randomization Study
Authors: Shan Chunhan , Chen Liwen , Mo Huayan , Chen Xin , Han Chen , Tao Fangbiao , Gao Hui
Published: October 2024

The chief aim of this research is to investigate the causality of air pollutants and adverse pregnancy outcomes. Two-sample Mendelian randomization was conducted, employing genetic variants connected with air pollution as instrumental variables. Sixteen adverse pregnancy outcomes were extracted as the main outcome measures from the genome-wide association study (GWAS). The inverse-variance weighted (IVW) method was conducted as the primary analysis method. This study found that there were causal association between NO2 and pre-eclampsia (weighted median: OR = 1.30, 95% CI = [1.03–1.64], p = 0.029) and between PM2.5 and placental abruption (IVW: OR = 10.94, 95% CI = [1.28–93.45], p = 0.029). There were potential causal relationships between NO2 and gestational hypertension (IVW: OR = 1.14, 95% CI = [0.99–1.30], p = 0.060); NO2 and placental abruption (IVW: OR = 1.97, 95% CI = [0.90–4.28], p = 0.089); NOx and fetal growth restriction (IVW: OR = 0.06, 95% CI = [0.99–1.12], p = 0.089); PM2.5 and slow fetal growth and fetal malnutrition (MR–Egger: OR = 54,240.95, 95% CI = [2.08–1,411,757,729.46], p = 0.059); PM10 and hyperemesis gravidarum (MR–Egger: OR = 0.12, 95% CI = [0.02–0.97], p = 0.086); PM10 and preterm birth (weighted median: OR = 1.60, 95% CI = [0.95–2.70], p = 0.075); and PM10 and spontaneous abortion (weighted median: OR = 1.60, 95% CI = [0.95–2.70], p = 0.075). There was no pleiotropy, but there was some heterogeneity. In conclusion, air pollution has a causal effect on several adverse pregnancy outcomes.
Spatiotemporal Distribution of Mercury in Tree Rings and Soils Within Forests Surrounding Coal-Fired Power Plants
Authors: Ha Eugene , Kim Ikhyun , Chae Heemun , Lee Sangsin , Ahn Youngsang , Choi Byoungkoo
Published: October 2024

The release of mercury (Hg) from coal-fired power plants (CPPs) into local ecosystems poses substantial environmental and health hazards. This study was conducted in Chungcheong-nam-do, South Korea, a region featuring over half of the country’s coal power facilities, to estimate the impacts of CPPs on Hg distribution in forest ecosystems. By analyzing Hg concentrations in pine tree rings and soil at 21 locations around CPPs and comparing them to control sites and industrial zones, we present a nuanced understanding of the effects of CPPs on Hg concentration. The analysis of Hg concentrations in tree rings showed a significant decrease in Hg levels as the distance from the power plants increased, suggesting that CPPs primarily influence Hg distribution in trees within a 25 km radius. In contrast, soil Hg concentrations did not exhibit a clear trend. This may reflect the limitations of this study in accounting for the physicochemical properties of the soil at each sampling site. Nevertheless, the Potential Ecological Risk Index for soil Hg contamination indicated a higher risk rating within a 1 km radius of the CPPs compared to other locations. Hg concentrations in tree rings have shown a steady decline since the 1970s, suggesting the positive effects of air pollution regulations. This also highlights the value of tree core samples as effective tools for monitoring historical Hg pollution. Furthermore, the higher historical concentrations of Hg in tree rings imply that trees may have acted as sinks for atmospheric Hg in the past.
Temperature and Ozone Response to Different Forcing in the Lower Troposphere and Stratosphere
Authors: Usacheva Margarita , Rozanov Eugene , Zubov Vladimir , Smyshlyaev Sergei
Published: October 2024

To evaluate the contributions of different forcings to the temperature and atmospheric composition changes between 1980 and 2020, we exploited the chemistry-climate model (CCM) SOCOLv3. The study examined ozone content and atmospheric temperature response to (1) ozone-depleting substances; (2) greenhouse gas concentrations, ocean surface temperature, and sea ice coverage; (3) solar irradiance; and (4) stratospheric aerosol loading and, separately, (5) greenhouse gas concentrations, (6) ocean surface temperature and sea ice coverage, and (7) NOx surface emissions. To evaluate the impacts of specific factors, we performed model runs driven by each factor (1–7) variability as well as a reference experiment that accounted for the influence of all factors simultaneously. We identified the relative contribution of different factors to the evolution of the temperature and ozone content of the lower troposphere and stratosphere from 1980 to 2020. The model results were in good agreement with the reanalyses (MERRA2 and ERA5). We showed that stratospheric ozone depletion before the Montreal Protocol introduction and partial recovery after that were chiefly driven by ODS. Stratospheric aerosol from major volcanic eruptions caused only short-term (up to 5 years) ozone decline. Increased greenhouse gas emissions dominate the ongoing long-term stratospheric cooling as well as tropospheric and surface warming. Solar irradiance contributed to short-term fluctuations but had a minimal long-term impact. Furthermore, our analysis of the solar signal in the tropical stratosphere underscores the complex interplay of solar radiation with volcanic, oceanic, and atmospheric factors, revealing significant altitudinal distributions of temperature and ozone responses to solar activity. Our findings advocate further innovative methodologies to take into account the nonlinearity of the atmospheric processes.