bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Microwave Pyrolysis Recovery and Reuse Performance of Carbon Fiber Composites
Authors: Li Xuan , Xu Lei , Ren Yiyao , Nan Zheng , Xiao Shijie , Shen Zhigang
Published: May 2024

Carbon fiber-reinforced resin matrix composites find extensive applications across various industries. However, their widespread use also generates significant waste, leading to resource depletion and environmental concerns. Studying the production of composite materials using recovered carbon fiber is imperative to mitigate the environmental impact associated with waste from carbon fiber-reinforced resin matrix composites and optimize resource utilization. In this study, carbon fiber was reclaimed using the microwave pyrolysis–oxidation process. The reclaimed carbon fiber underwent a cutting process to produce shorter carbon fibers tailored to specific requirements, which were then used to fabricate composite plates reinforced with epoxy resin. The mechanical characteristics of the composite were analyzed, along with SEM, XPS, infrared, Raman, and contact angle analyses conducted on the recovered carbon fiber. The test findings suggested minimal variation in the surface morphology of the recovered carbon fiber materials. Post-recovery, an increase in the quantity of oxygen-containing functional groups was observed on the carbon fiber surface. Additionally, the contact angle between the carbon fiber surface and the epoxy adhesive decreased. The mechanical properties of the composite produced from the recovered carbon fiber decreased, including the impact strength, tensile strength, and bending strength, with the impact strength dropping by 24.14%, tensile strength by 15.94%, and bending strength by 8.24%, while maintaining overall reusability, thus paving the way for the comprehensive utilization of carbon fiber resources.
Puzzle of Proteoform Variety—Where Is a Key?
Authors: Naryzhny Stanislav
Published: May 2024

One of the human proteome puzzles is an imbalance between the theoretically calculated and experimentally measured amounts of proteoforms. Considering the possibility of combinations of different post-translational modifications (PTMs), the quantity of possible proteoforms is huge. An estimation gives more than a million different proteoforms in each cell type. But, it seems that there is strict control over the production and maintenance of PTMs. Although the potential complexity of proteoforms due to PTMs is tremendous, available information indicates that only a small part of it is being implemented. As a result, a protein could have many proteoforms according to the number of modification sites, but because of different systems of personal regulation, the profile of PTMs for a given protein in each organism is slightly different.
Geomorphological Evolution in the Tidal Flat of a Macro-Tidal Muddy Estuary, Hangzhou Bay, China, over the Past 30 Years
Authors: Li Li , Shen Fangzhou , Xia Yuezhang , Shi Haijing , Wang Nan , He Zhiguo , Gao Kai
Published: May 2024

Tidal flat plays an important role in coastal development because of its ecological and spatial resources. We take the southern tidal flat in the macro-tidal turbid Hangzhou Bay as an example to study the long-term (1990–2020) evolution of the muddy tidal flat, using remote sensing data and field observational data. The detailed bathymetric elevation of the tidal flat is obtained, using remote sensing images of Landsat and Sentinel-2, combined with the real-time kinematic (RTK) data. The correlation coefficient between the remote sensing data and the RTK data is 0.73. The tidal flat and vegetation areas are affected by reclamation. The total tidal flat area decreased by 467.78 km2. The vegetation area declined from 64.98 km2 in 2000 to 13.41 km2 in 2015 and recovered to 41.62 km2 in 2020. The largest change in tidal flat slope occurs in the eastern and western sides of the tidal flat, compared with the wide middle part. The total length of tidal creeks decreased to 45.95 km in 2005 and then increased to 105.83 km in 2020. The middle- and low-grade tidal creeks accounted for 91.4%, with a curvature slightly larger than 1 in 2020. High-grade tidal creeks occur inside the vegetation areas, with less bending and fewer branch points. Vegetation promotes the development of tidal creeks but limits the lateral swing and bifurcation. These results provide a basis for the management of global tidal flat resources and ecosystems.
Changes in the Water Area of an Inland River Terminal Lake (Taitma Lake) Driven by Climate Change and Human Activities, 2017–2022
Authors: Zi Feng , Wang Yong , Lu Shanlong , Ikhumhen Harrison Odion , Fang Chun , Li Xinru , Wang Nan , Kuang Xinya
Published: May 2024

Constructed from a dataset capturing the seasonal and annual water body distribution of the lower Qarqan River in the Taitma Lake area from 2017 to 2022, and combined with the meteorological and hydraulic engineering data, the spatial and temporal change patterns of the Taitma Lake watershed area were determined. Analyses were conducted using Planetscope (PS) satellite images and a deep learning model. The results revealed the following: ① Deep learning-based water body extraction provides significantly greater accuracy than the conventional water body index approach. With an impressive accuracy of up to 96.0%, UPerNet was found to provide the most effective extraction results among the three convolutional neural networks (U-Net, DeeplabV3+, and UPerNet) used for semantic segmentation; ② Between 2017 and 2022, Taitma Lake’s water area experienced a rapid decrease, with the distribution of water predominantly shifting towards the east–west direction more than the north–south. The shifts between 2017 and 2020 and between 2020 and 2022 were clearly discernible, with the latter stage (2020–2022) being more significant than the former (2017–2020); ③ According to observations, Taitma Lake’s changing water area has been primarily influenced by human activity over the last six years. Based on the research findings of this paper, it was observed that this study provides a valuable scientific basis for water resource allocation aiming to balance the development of water resources in the middle and upper reaches of the Tarim and Qarqan Rivers, as well as for the ecological protection of the downstream Taitma Lake.
Hybrid Machine Learning and Geostatistical Methods for Gap Filling and Predicting Solar-Induced Fluorescence Values
Authors: Tadić Jovan M. , Ilić Velibor , Ilić Slobodan , Pavlović Marko , Tadić Vojin
Published: May 2024

Sun-induced chlorophyll fluorescence (SIF) has proven to be advantageous in estimating gross primary production, despite the lack of a stable relationship. Satellite-based SIF measurements at Level 2 offer comprehensive global coverage and are available in near real time. However, these measurements are often limited by spatial and temporal sparsity, as well as discontinuities. These limitations primarily arise from incomplete satellite trajectories. Additionally, variability in cloud cover and periodic issues specific to the instruments can compromise data quality. Two families of methods have been developed to address data discontinuity: (1) machine learning-based gap-filling techniques and (2) geostatistical techniques (various forms of kriging). The former techniques utilize the relationships between ancillary data and SIF, while the latter usually rely on the available SIF data recordings and their covariance structure to provide estimates at unsampled locations. In this study, we create a synthetic approach for SIF gap filling by hybridizing the two approaches under the umbrella of kriging with external drift. We performed leave-one-out cross-validation of the OCO-2 SIF retrieval aggregates for the entire year of 2019, comparing three methods: ordinary kriging, ML-based estimation using ancillary data, and kriging with external drift. The Mean Absolute Error (MAE) for ML, ordinary kriging, and the hybrid approach was found to be 0.1399, 0.1318, and 0.1183 mW m2 sr−1 nm−1, respectively. We demonstrate that the performance of the hybrid approach exceeds both parent techniques due to the incorporation of information from multiple resources. This use of multiple datasets enriches the hybrid model, making it more robust and accurate in handling the spatio-temporal variability and discontinuity of SIF data. The developed framework is portable and can be applied to SIF retrievals at various resolutions and from various sources (satellites), as well as extended to other satellite-measured variables.
A Gaussian Function Model of Mesoscale Eddy Temperature Anomalies and Research of Spatial Distribution Characteristics
Authors: Duan Yingying , Zhang Hao , Chen Xiao , Zhou Manli
Published: May 2024

Mesoscale eddies are ubiquitous oceanic phenomena and play an important role in ocean circulation, ocean dynamics, and the transport of material energy. Temperature anomalies are a crucial parameter that reflects the state of mesoscale eddies. This study proposes a Gaussian function model to fit the vertical temperature anomaly (TA) profile to facilitate the analysis of variations, and the principle of the model is based on the fact that each TA profile tends to fluctuate around one or more peaks. The model is extracted and validated using Argo profiles within cyclonic and anticyclonic eddies in the Northwest Pacific Ocean spanning over the period from 2002 to 2021. The validation demonstrates that the model can accurately recover the vertical TA profiles with a limited number of parameters. This makes it suitable for analysing the spatial distribution patterns that require a large sample count. The analysis indicates that eddies with different TA profiles have a spatial aggregation effect in geographic distribution. Eddies with lower extreme temperature anomalies, at depths of 200–300 m, are mainly distributed along two bands on the north side of the Kuroshio Extension (KE) and the North Equatorial Current. Eddies with extreme TAs at the deepest depth (500–600 m) are distributed along the KE.
Arctic Sea Ice Albedo Estimation from Fengyun-3C/Visible and Infra-Red Radiometer
Authors: Sun Xiaohui , Guan Lei
Published: May 2024

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases.
A Semantic Spatial Structure-Based Loop Detection Algorithm for Visual Environmental Sensing
Authors: Cheng Xina , Zhang Yichi , Kang Mengte , Wang Jialiang , Jiao Jianbin , Dong Le , Jiao Licheng
Published: May 2024

Loop closure detection is an important component of the Simultaneous Localization and Mapping (SLAM) algorithm, which is utilized in environmental sensing. It helps to reduce drift errors during long-term operation, improving the accuracy and robustness of localization. Such improvements are sorely needed, as conventional visual-based loop detection algorithms are greatly affected by significant changes in viewpoint and lighting conditions. In this paper, we present a semantic spatial structure-based loop detection algorithm. In place of feature points, robust semantic features are used to cope with the variation in the viewpoint. In consideration of the semantic features, which are region-based, we provide a corresponding matching algorithm. Constraints on semantic information and spatial structure are used to determine the existence of loop-back. A multi-stage pipeline framework is proposed to systematically leverage semantic information at different levels, enabling efficient filtering of potential loop closure candidates. To validate the effectiveness of our algorithm, we conducted experiments using the uHumans2 dataset. Our results demonstrate that, even when there are significant changes in viewpoint, the algorithm exhibits superior robustness compared to that of traditional loop detection methods.
Benchmarking Under- and Above-Canopy Laser Scanning Solutions for Deriving Stem Curve and Volume in Easy and Difficult Boreal Forest Conditions
Authors: Muhojoki Jesse , Tavi Daniella , Hyyppä Eric , Lehtomäki Matti , Faitli Tamás , Kaartinen Harri , Kukko Antero , Hakala Teemu , Hyyppä Juha
Published: May 2024

The use of mobile laser scanning for mapping forests has scarcely been studied in difficult forest conditions. In this paper, we compare the accuracy of retrieving tree attributes, particularly diameter at breast height (DBH), stem curve, stem volume, and tree height, using six different laser scanning systems in a managed natural boreal forest. These compared systems operated both under the forest canopy on handheld and unmanned aerial vehicle (UAV) platforms and above the canopy from a helicopter. The complexity of the studied forest sites ranged from easy to difficult, and thus, this is the first study to compare the performance of several laser scanning systems for the direct measurement of stem curve in difficult forest conditions. To automatically detect tree stems and to calculate their attributes, we utilized our previously developed algorithm integrated with a novel bias compensation method to reduce the overestimation of stem diameter arising from finite laser beam divergence. The bias compensation method reduced the absolute value of the diameter bias by 55–99%. The most accurate laser scanning systems were equipped with a Velodyne VLP-16 sensor, which has a relatively low beam divergence, on a handheld or UAV platform. In easy plots, these systems found a root-mean-square error (RMSE) of below 10% for DBH and stem curve estimates and approximately 10% for stem volume. With the handheld system in difficult plots, the DBH and stem curve estimates had an RMSE under 10%, and the stem volume RMSE was below 20%. Even though bias compensation reduced the difference in bias and RMSE between laser scanners with high and low beam divergence, the RMSE remained higher for systems with a high beam divergence. The airborne laser scanner operating above the forest canopy provided tree attribute estimates close to the accuracy of the under-canopy laser scanners, but with a significantly lower completeness rate for stem detection, especially in difficult forest conditions.
Estimation of Land Deformation and Groundwater Storage Dynamics in Shijiazhuang–Baoding–Cangzhou–Hengshui Using Multi-Temporal Interferometric Synthetic Aperture Radar
Authors: Yang Qiuhong , Zhang Xing , Hu Jun , Gui Rong , Yang Liuming
Published: May 2024

Groundwater resources are crucial to socio-economic development and the ecosystem, and over-extraction can cause the groundwater level to drop, deplete reserves, and trigger geological hazards like land subsidence. The North China Plain (NCP) has experienced both subsidence and groundwater depletion due to over-extraction in the past 70 years. In this study, we used MT-InSAR technology and ascending C-band Sentinel-1 SAR data from 2017 to 2023 to study land deformation in the junction area of Shijiazhuang–Baoding–Cangzhou–Hengshui. We identified multiple subsidence funnels with a maximum rate exceeding −150 mm/year and a total deformation surpassing 600 mm. Seasonal decomposition methods accurately separated seasonal signals in the time-series deformation and groundwater level data. An exponential function model applied to long-term deformation showed no significant decrease in subsidence in severely affected areas. By modeling seasonal deformation and seasonal groundwater levels, we determined the elastic skeletal storage coefficients (Ske) to be in the range of 1.02 × 10−3~6.53 × 10−3 in subsidence areas. We obtained the spatiotemporal evolution of the total groundwater storage (TGWS), irreversible ground storage (IGWS), and recoverable ground storage (RGWS). The TGWS and IGWS decreased annually while the RGWS increased, which is attributable to the implementation of the South-to-North Water Diversion Project (SNWDP) and the issuance of groundwater withdrawal policies in the NCP.
Characterization of Magnetoresistive Shunts and Its Sensitivity Temperature Compensation
Authors: Ramírez-Muñoz Diego , García-Gil Rafael , Cardoso Susana , Freitas Paulo
Published: May 2024

The main purpose of the paper is to show how a magnetoresistive (MR) element can work as a current sensor instead of using a Wheatstone bridge composed by four MR elements, defining the concept of a magnetoresistive shunt (MR-shunt). This concept is reached by considering that once the MR element is biased at a constant current, the voltage drop between its terminals offers information, by the MR effect, of the current to be measured, as happens in a conventional shunt resistor. However, an MR-shunt has the advantage of being a non-dissipative shunt since the current of interest does not circulate through the material, preventing its self-heating. Moreover, it provides galvanic isolation. First, we propose an electronic circuitry enabling the utilization of the available MR sensors integrated into a Wheatstone bridge as sensing elements (MR-shunt). This circuitry allows independent characterization of each of the four elements of the bridge. An independently implemented MR element is also analyzed. Secondly, we propose an electronic conditioning circuit for the MR-shunt, which allows both the bridge-integrated element and the single element to function as current sensors in a similar way to the sensing bridge. Third, the thermal variation in the sensitivity of the MR-shunt, and its temperature coefficient, are obtained. An electronic interface is proposed and analyzed for thermal drift compensation of the MR-shunt current sensitivity. With this hardware compensation, temperature coefficients are experimentally reduced from 0.348%/°C without compensation to −0.008%/°C with compensation for an element integrated in a sensor bridge and from 0.474%/°C to −0.0007%/°C for the single element.
Stimulus–Response Plots as a Novel Bowel-Sound-Based Method for Evaluating Motor Response to Drinking in Healthy People
Authors: Haraguchi Takeyuki , Emoto Takahiro
Published: May 2024

Constipation is a common gastrointestinal disorder that impairs quality of life. Evaluating bowel motility via traditional methods, such as MRI and radiography, is expensive and inconvenient. Bowel sound (BS) analysis has been proposed as an alternative, with BS-time-domain acoustic features (BSTDAFs) being effective for evaluating bowel motility via several food and drink consumption tests. However, the effect of BSTDAFs before drink consumption on those after drink consumption is yet to be investigated. This study used BS-based stimulus–response plots (BSSRPs) to investigate this effect on 20 participants who underwent drinking tests. A strong negative correlation was observed between the number of BSs per minute before carbonated water consumption and the ratio of that before and after carbonated water consumption. However, a similar trend was not observed when the participants drank cold water. These findings suggest that when carbonated water is drunk, bowel motility before ingestion affects motor response to ingestion. This study provides a non-invasive BS-based approach for evaluating motor response to food and drink, offering a new research window for investigators in this field.
A Novel Low-Frequency Electromagnetic Active Inertial Sensor for Drug Detection
Authors: Vasilaki Erietta , Markoulakis Emmanouil , Lazari Diamanto , Psaroudaki Antonia , Barbounakis Ioannis , Antonidakis Emmanuel
Published: May 2024

The purpose of this paper is to demonstrate a new discovery regarding the interaction between materials and very low radio frequencies. Specifically, we observed a feedback response on an inertia active sensor when specific frequencies (around 2–4 kHz) are used to irradiate targeted pharmaceutical samples like aspirin or paracetamol drugs. The characteristics of this phenomenon, such as excitation and relaxation time, the relation between deceleration and a material’s quantity, and signal amplitude, are presented and analyzed. Although the underlying physics of this phenomenon is not yet known, we have shown that it has potential applications in remote identification of compounds, detection, and location sensing, as well as identifying substances that exist in plants without the need for any processing. This method is fast, accurate, low-cost, non-destructive, and non-invasive, making it a valuable area for further research that could yield spectacular results in the future.
Seismic Monitoring of a Deep Geothermal Field in Munich (Germany) Using Borehole Distributed Acoustic Sensing
Authors: Azzola Jérôme , Gaucher Emmanuel
Published: May 2024

Geothermal energy exploitation in urban areas necessitates robust real-time seismic monitoring for risk mitigation. While surface-based seismic networks are valuable, they are sensitive to anthropogenic noise. This study investigates the capabilities of borehole Distributed Acoustic Sensing (DAS) for local seismic monitoring of a geothermal field located in Munich, Germany. We leverage the operator’s cloud infrastructure for DAS data management and processing. We introduce a comprehensive workflow for the automated processing of DAS data, including seismic event detection, onset time picking, and event characterization. The latter includes the determination of the event hypocenter, origin time, seismic moment, and stress drop. Waveform-based parameters are obtained after the automatic conversion of the DAS strain-rate to acceleration. We present the results of a 6-month monitoring period that demonstrates the capabilities of the proposed monitoring set-up, from the management of DAS data volumes to the establishment of an event catalog. The comparison of the results with seismometer data shows that the phase and amplitude of DAS data can be reliably used for seismic processing. This emphasizes the potential of improving seismic monitoring capabilities with hybrid networks, combining surface and downhole seismometers with borehole DAS. The inherent high-density array configuration of borehole DAS proves particularly advantageous in urban and operational environments. This study stresses that realistic prior knowledge of the seismic velocity model remains essential to prevent a large number of DAS sensing points from biasing results and interpretation. This study suggests the potential for a gradual extension of the network as geothermal exploitation progresses and new wells are equipped, owing to the scalability of the described monitoring system.
Temperature-Switch-Controlled Second Harmonic Mode Sensor for Brain-Tissue Detection
Authors: Li Xiang , Yang Cheng , Guo Chuming , Li Qijuan , Peng Chuan , Zhang Haifeng
Published: May 2024

Identifying brain-tissue types holds significant research value in the biomedical field of non-contact brain-tissue measurement applications. In this paper, a layered metastructure is proposed, and the second harmonic generation (SHG) in a multilayer metastructure is derived using the transfer matrix method. With the SHG conversion efficiency (CE) as the measurement signal, the refractive index ranges that can be distinguished are 1.23~1.31 refractive index unit (RIU) and 1.38~1.44 RIU, with sensitivities of 0.8597 RIU−1 and 1.2967 RIU−1, respectively. It can distinguish various brain tissues, including gray matter, white matter, and low-grade glioma, achieving the function of a second harmonic mode sensor (SHMS). Furthermore, temperature has a significant impact on the SHG CE, which can be used to define the switch signal indicating whether the SHMS is functioning properly. When the temperature range is 291.4~307.9 Kelvin (K), the temperature switch is in the “open” state, and the optimal SHG CE is higher than 0.298%, indicating that the SHMS is in the working state. For other temperature ranges, the SHG CE will decrease significantly, indicating that the temperature switch is in the “off” state, and the SHMS is not working. By stimulating temperature and using the response of SHG CE, the temperature-switch function is achieved, providing a new approach for temperature-controlled second harmonic detection.
Broken Rotor Bar Detection Based on Steady-State Stray Flux Signals Using Triaxial Sensor with Random Positioning
Authors: Zubčić Marko , Pavić Ivan , Matić Petar , Polak Adam
Published: May 2024

This paper investigates the detection of broken rotor bar in squirrel cage induction motors using a novel approach of randomly positioning a triaxial sensor over the motor surface. This study is conducted on two motors under laboratory conditions, where one motor is kept in a healthy state, and the other is subjected to a broken rotor bar (BRB) fault. The induced electromotive force of the triaxial coils, recorded over ten days with 100 measurements per day, is statistically analyzed. Normality tests and graphical interpretation methods are used to evaluate the data distribution. Parametric and non-parametric approaches are used to analyze the data. Both approaches show that the measurement method is valid and consistent over time and statistically distinguishes healthy motors from those with BRB defects when a reference or threshold value is specified. While the comparison between healthy motors shows a discrepancy, the quantitative analysis shows a smaller estimated difference in mean values between healthy motors than comparing healthy and BRB motors.
Exploring Biosensors’ Scientific Production and Research Patterns: A Bibliometric Analysis
Authors: Valente Bernardo , Pinto Hugo , Pereira Tiago Santos , Campos Rita
Published: May 2024

More sustainable biosensor production is growing in importance, allowing for the development of technological solutions for several industries, such as those in the health, chemical, and food sectors. Tracking the latest advancements in biosensors’ scientific production is fundamental to determining the opportunities for the future of the biosensing field. This article aims to map scientific production in the biosensors field by running a bibliometric analysis of journal articles registered in the Web of Science database under biosensor-related vital concepts. The key concepts were selected by researchers and biosensor technology developers working on the BioAssembler Horizon project. The findings lead to identifying the scientific and technological knowledge base on biosensing devices and tracking the main scientific organisations developing this technology throughout the COVID-19 period (2019–2023). The institutional origin of the publications characterised the global distribution of related knowledge competencies and research partnerships. These results are discussed, shedding light on the scientific, economic, political, and structural factors that contribute to the formation of a scientific knowledge-based focus on the performance and design of these sensors. Moreover, the lack of scientific ties between the three axes of organisations producing expertise in this area (China, USA, and Russia) points towards the need to find synergies through new mechanisms of co-authorship and collaboration.
An Analysis of Blockchain-Based IoT Sensor Network Distributed Denial of Service Attacks
Authors: Arachchige Kithmini Godewatte , Branch Philip , But Jason
Published: May 2024

The Internet of Things (IoT) and blockchain are emerging technologies that have attracted attention in many industries, including healthcare, automotive, and supply chain. IoT networks and devices are typically low-powered and susceptible to cyber intrusions. However, blockchains hold considerable potential for securing low-power IoT networks. Blockchain networks provide security features such as encryption, decentralisation, time stamps, and ledger functions. The integration of blockchain and IoT technologies may address many of the security concerns. However, integrating blockchain with IoT raises several issues, including the security vulnerabilities and anomalies of blockchain-based IoT networks. In this paper, we report on our experiments using our blockchain test bed to demonstrate that blockchains on IoT platforms are vulnerable to DDoS attacks, which can also potentially lead to device hardware failures. We show that a number of anomalies are visible during either a DDoS attack or IoT device failure. In particular, the temperature of IoT hardware devices can exceed 90 °C during a DDoS attack, which could lead to hardware failure and potential fire hazards. We also found that the Block Transaction Rate (BTR) and network block loss percentage can increase due to corrupted hardware, with the BTR dropping to nearly zero blocks/sec and a block loss percentage of over 50 percent for all evaluated blockchains, and as high as 81.3 percent in one case. Our experiments demonstrate that anomalous temperature, latency, bandwidth, BTR, and network block loss percentage can potentially be used to identify DDoS attacks.
Generalized Pulse Width Modulation Switch Model for Converters Based on the Multistate Switching Cell in Discontinuous Conduction Mode
Authors: Tofoli Fernando Lessa
Published: May 2024

This work introduces a generalized version of the pulse width modulation (PWM) switch model applied in the small-signal modeling of converters based on the multistate switching cell (MSSC) operating in discontinuous conduction mode (DCM). It consists of extending the concept formerly introduced by Vorperian for the representation of multiphase converters in DCM, yielding a circuit-based approach that does not rely on matrix manipulations unlike state-space averaging (SSA). The derived dc and ac models are valid for any number of switching states and any operating region defined in terms of the duty cycle, thus allowing for determining the voltage gain and distinct transfer functions. A thorough discussion of results is presented to demonstrate the applicability of the derived models to represent distinct configurations of the MSSC.
Lightweight Hash-Based Authentication Protocol for Smart Grids
Authors: Kook Sangjin , Kim Keunok , Ryu Jihyeon , Lee Youngsook , Won Dongho
Published: May 2024

Smart grids integrate information and communications technology into the processes of electricity production, transportation, and consumption, thereby enabling interactions between power suppliers and consumers to increase the efficiency of the power grid. To achieve this, smart meters (SMs) are installed in households or buildings to measure electricity usage and allow power suppliers or consumers to monitor and manage it in real time. However, SMs require a secure service to address malicious attacks during memory protection and communication processes and a lightweight communication protocol suitable for devices with computational and communication constraints. This paper proposes an authentication protocol based on a one-way hash function to address these issues. This protocol includes message authentication functions to address message tampering and uses a changing encryption key for secure communication during each transmission. The security and performance analysis of this protocol shows that it can address existing attacks and provides 105,281.67% better computational efficiency than previous methods.
Vehicle Detection Algorithms for Autonomous Driving: A Review
Authors: Liang Liang , Ma Haihua , Zhao Le , Xie Xiaopeng , Hua Chengxin , Zhang Miao , Zhang Yonghui
Published: May 2024

Autonomous driving, as a pivotal technology in modern transportation, is progressively transforming the modalities of human mobility. In this domain, vehicle detection is a significant research direction that involves the intersection of multiple disciplines, including sensor technology and computer vision. In recent years, many excellent vehicle detection methods have been reported, but few studies have focused on summarizing and analyzing these algorithms. This work provides a comprehensive review of existing vehicle detection algorithms and discusses their practical applications in the field of autonomous driving. First, we provide a brief description of the tasks, evaluation metrics, and datasets for vehicle detection. Second, more than 200 classical and latest vehicle detection algorithms are summarized in detail, including those based on machine vision, LiDAR, millimeter-wave radar, and sensor fusion. Finally, this article discusses the strengths and limitations of different algorithms and sensors, and proposes future trends.
A Disturbance Compensation Control Strategy for Rotational Speed Standard Device Based on AMB System
Authors: Chen Yulin , Du Lei , Sun Qiao , Bai Jie
Published: May 2024

The rotational speed standard device that can carry loads is the key device for calibrating passive rotational speed sensors. The rotor of the passive rotational speed sensor is connected to the rotor of the standard speed device through a coupling, and the standard reference speed is provided by the standard device. Due to the rotor eccentricity, the unbalanced force of the rotor occurs, and it can not only affect the rotational speed accuracy but can also damage the mechanical bearings of the standard speed device. To solve this issue, a method for suppressing the unbalanced force of the speed standard device based on an active magnetic bearing (AMB) force compensation system is proposed. First, the overall structure of the system is briefly introduced. Then, the force feedback control system model with the AMB as the force actuator is established, and a PI controller is designed to achieve the disturbed force control. Finally, a semi-physical simulation experimental platform is built to verify the effectiveness of the proposed method. The experimental results show that the AMB force compensation system can reduce 84.4%, 81.6%, and 79.8% of the unbalanced vibration force at the frequency of 30 Hz, 90 Hz, and 150 Hz, respectively.
A Retrospective Analysis of Indoor CO2 Measurements Obtained with a Mobile Robot during the COVID-19 Pandemic
Authors: Palacín Jordi , Rubies Elena , Clotet Eduard
Published: May 2024

This work presents a retrospective analysis of indoor CO2 measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions. The robot-based CO2 measurement system was assessed as an alternative to the deployment of a net of sensors in a building in the pandemic period, in which there was a global stock outage of CO2 sensors. The analysis of the obtained measurements confirms that a mobile system can be used to obtain interpretable information on the CO2 levels inside the rooms of a building during a pandemic outbreak.
Breast Cancer Prevention by Dietary Polyphenols: Microemulsion Formulation and In Vitro Studies
Authors: Cristy Ghea Putri , Liana Desy , Chatwichien Jaruwan , Aonbangkhen Chanat , Srisomsap Chantragan , Phanumartwiwath Anuchit
Published: May 2024

Concerns surrounding breast cancer have been increasing, as it leads to the current global cancer incidence and causes a high mortality rate in women. This study investigated the physiological effects of common dietary polyphenols that might prevent breast cancer progression. Quercetin, kaempferol, and rosmarinic acid were selected to explore their potential bioactivities. Each polyphenol was formulated into a microemulsion to improve its bioactivity and bioavailability. In vitro antioxidant and cytotoxicity activities of the selected polyphenols and their microemulsion forms were further investigated. The optimized microemulsion carrier with 1% oleic acid, 3% ethanol, 10% polysorbate 20, and 86% ultrapure water achieved more than 90% polyphenol encapsulation efficiency. The microemulsion was stable for more than 30 days when encapsulating polyphenol in the fluctuating temperature treatment. In vitro studies suggested that rosmarinic acid-loaded microemulsion had the best antioxidant activity compared with other polyphenol-loaded microemulsions (PL-MEs). Blank microemulsion and all PL-MEs significantly inhibited the proliferation of both hormone-dependent (T47D) and hormone-independent (MDA-MB-231) breast cancer cells. More studies are warranted to confirm the contribution of the microemulsion carrier components to the polyphenols’ improved antioxidant activity and high toxicity of PL-MEs on breast cancer cells.
Research and Application of the Simulation Method for Product Development Process Based on System Dynamics
Authors: Yin Fupeng , Gao Qi , Sun Jiakun
Published: May 2024

Product development is a complex process involving intricate components, dynamics and constantly evolving internal and external environments, as well as numerous influencing factors. In order to accurately simulate and predict the effectiveness of the development process, this paper proposes a system dynamics simulation method based on information maturity. Different types of development processes are simulated, and the discussion includes the impact of activity information correlation, information evolution coefficient, start time, and other parameters on the dynamic behavior of the process. This study examines a specific mold development process as a case study to validate the method’s feasibility, accurately predicting the duration and cost of the process. It also investigates dynamic fluctuations resulting from uncertain events such as changes in customer demand and resource shortages. The method provides support for process optimization and resource scheduling.
Bioreactor Expansion Affects Microbial Succession of Mixotrophic Acidophiles and Bioremediation of Cadmium-Contaminated Soils
Authors: Hao Xiaodong , Zhu Ping , Liu Xueduan , Jiang Luhua , Jiang Huidan , Liu Hongwei , Chen Zhiqun
Published: May 2024

Microbial scale-up cultivation is the first step to bioremediating cadmium (Cd)-contaminated soils at the industrial scale. However, the changes in the microbial community as the bioreactor volume expands and their associations with soil Cd removal remain unclear. Herein, a six-stage scale-up cultivation process of mixotrophic acidophiles was conducted, scaling from 0.1 L to 10 m3, to remediate Cd-contaminated soils. The findings showed that bioreactor expansion led to a delay in sulfur and glucose oxidations, resulting in a reduced decline in solution pH and cell density. There were minimal differences observed in bacterial alpha-diversity and community structure as the bioreactor volume increased, except for the 10 m3 scale. However, bioreactor expansion decreased fungal alpha-diversity, changed the community structure, and simplified fungal community compositions. At the family level, Acidithiobacillaceae and Debaryomycetaceae dominated the bacterial and fungal communities throughout the scale-up process, respectively. Correlation analysis indicated that the indirect effect of mixotrophic acidophiles played a significant role in soil Cd removal. Bacterial community shifts, driven by changes in bioreactor volume, decreased the pH value through sulfur oxidation, thereby indirectly enhancing Cd removal efficiency. This study will contribute to the potential industrial application of mixotrophic acidophiles in bioremediating Cd-contaminated soils.
Alternariol Monomethyl-Ether Induces Toxicity via Cell Death and Oxidative Stress in Swine Intestinal Epithelial Cells
Authors: Marin Daniela Eliza , Bulgaru Valeria Cristina , Pertea AnaMaria , Grosu Iulian Alexandru , Pistol Gina Cecilia , Taranu Ionelia
Published: May 2024

Alternariol monomethyl-ether (AME), together with altenuene and alternariol, belongs to the Alternaria mycotoxins group, which can contaminate different substrates, including cereals. The aim of the present study was to obtain a deeper understanding concerning the effects of AME on pig intestinal health using epithelial intestinal cell lines as the data concerning the possible effects of Alternaria toxins on swine are scarce and insufficient for assessing the risk represented by Alternaria toxins for animal health. Our results have shown a dose-related effect on IPEC-1 cell viability, with an IC50 value of 10.5 μM. Exposure to the toxin induced an increase in total apoptotic cells, suggesting that AME induces programmed cell death through apoptosis based on caspase-3/7 activation in IPEC-1 cells. DNA and protein oxidative damage triggered by AME were associated with an alteration of the antioxidant response, as shown by a decrease in the enzymatic activity of catalase and superoxide dismutase. These effects on the oxidative response can be related to an inhibition of the Akt/Nrf2/HO-1 signaling pathway; however, further studies are needed in order to validate these in vitro data using in vivo trials in swine.
Exposure to a Combination of Fusarium Mycotoxins Leads to Lipid Peroxidation and Influences Antioxidant Defenses, Fatty Acid Composition of Phospholipids, and Renal Histology in Laying Hens
Authors: Kulcsár Szabina , Turbók Janka , Kövér György , Balogh Krisztián , Zándoki Erika , Ali Omeralfaroug , Szabó András , Mézes Miklós
Published: May 2024

The effects of combined short-term (3 days) exposure to Fusarium mycotoxins at both the EU recommended limit (T-2/HT-2 toxin: 0.25 mg/kg; DON/3-AcDON/15-AcDON: 5 mg/kg; FB1: 20 mg/kg) and twice the dose (T-2/HT-2 toxin: 0.5 mg/kg, DON/3-AcDON/15-AcDON: 10 mg/kg, and FB1: 40 mg/kg feed) on the kidneys of laying hens were examined. Our study aimed to investigate how these mycotoxins interacted with membrane lipid fatty acid (FA) composition and lipid peroxidation processes. It was observed that the levels of conjugated dienes and trienes were higher than the control in the low-mix group on day 3, and malondialdehyde concentration was higher on days 2 and 3. The proportion of phospholipid (PL) FAs showed that saturated and monounsaturated FAs increased. Still, both n3 and n6 polyunsaturated FAs decreased significantly on day 2 of exposure in the high-mix group. Among the n3 FAs, the level of docosahexaenoic (C22:6 n3) and among n6 FAs, arachidonic (C20:4 n6) acids decreased mainly on day 2 in the high-mix group. The results suggest that the combined exposure to Fusarium mycotoxins induced lipid peroxidation in the kidneys of laying hens, which resulted in marked changes in the PL FA profile. Histological examination revealed time- and dose-dependent increases as consequences of mycotoxin exposure.
Stellar Classification with Vision Transformer and SDSS Photometric Images
Authors: Yang Yi , Li Xin
Published: May 2024

With the development of large-scale sky surveys, an increasing number of stellar photometric images have been obtained. However, most stars lack spectroscopic data, which hinders stellar classification. Vision Transformer (ViT) has shown superior performance in image classification tasks compared to most convolutional neural networks (CNNs). In this study, we propose an stellar classification network based on the Transformer architecture, named stellar-ViT, aiming to efficiently and accurately classify the spectral class for stars when provided with photometric images. By utilizing RGB images synthesized from photometric data provided by the Sloan Digital Sky Survey (SDSS), our model can distinguish the seven main stellar categories: O, B, A, F, G, K, and M. Particularly, our stellar-ViT-gri model, which reaches an accuracy of 0.839, outperforms traditional CNNs and the current state-of-the-art stellar classification network SCNet when processing RGB images synthesized from the gri bands. Furthermore, with the introduction of urz band data, the overall accuracy of the stellar-ViT model reaches 0.863, further demonstrating the importance of additional band information in improving classification performance. Our approach showcases the effectiveness and feasibility of using photometric images and Transformers for stellar classification through simple data augmentation strategies and robustness analysis of training dataset sizes. The stellar-ViT model maintains good performance even in small sample scenarios, and the inclusion of urz band data reduces the likelihood of misclassifying samples as lower-temperature subtypes.
Amphistome Infection and Species Diversity of Freshwater Snails Collected from Selected Wildlife Drinking Water Sources in Matebeleland Region of Zimbabwe
Authors: Sibula Madeline Siyazisiwe , Malatji Mokgadi Pulane , Nyahunda Cosmas , Mukaratirwa Samson
Published: May 2024

This study aimed at determining the identity of freshwater snails collected from selected water habitats frequented by wildlife as source of drinking water in the Matebeleland region of Zimbabwe and further screening the identified snails for natural infections with amphistomes using PCR. A total of 487 freshwater snails were collected from six areas in the Matebeleland region of Zimbabwe for identification and screening of amphistome infection. Eight freshwater snail species were morphologically identified and Biomphalaria pfeifferi, Bul. tropicus, Bul. truncatus, Bul. globosus, and L. (R.) natalensis were confirmed using the COI gene. Bulinus tropicus and Phy. acuta were the most abundant species at 33.9% (165/487) and 31.2% (155/487), respectively. DNA of amphistome was detected in 11.9% (58/487) of the collected snails. The highest infection rate was detected in Bul. globosus (44.4%). West Nicholson recorded the highest infection rate (33.9%), and infection was not detected in L. (R.) natalensis, Phy. acuta, and Bellamya spp. Amphistome DNA from M. tuberculata was successfully sequenced and identified as Calicophoron microbothrium. An additional band was detected in M. tuberculata, Bul. tropicus, and Bul. trancatus, which showed a 96.42% similarity to Paragonimus sp. sequence in the GenBank.
Hardware Implementation of a Resilient Energy Management System for Networked Microgrids
Authors: Hussein Hossam M. , Rafin S M Sajjad Hossain , Abdelrahman Mahmoud S. , Mohammed Osama A.
Published: May 2024

A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each microgrid, including the energy storage systems’ charging and discharging, maintaining the DC bus voltage, and even overseeing the power shared by multiple microgrids, is challenging. Therefore, a microgrid control technique and distributed energy management are used cooperatively in this study to handle the shared power between a system of networked microgrids incorporating photovoltaics and battery energy storage systems. Numerical simulation results from a networked microgrid system verify the accuracy and soundness of the suggested distributed energy management under several operating conditions, including renewable uncertainties and sequential load variations in different zones. The applicability of the suggested technique is confirmed by hardware implementation, and several operational scenarios further evaluate the proposed system on a practical two-microgrid system located in the Florida International University (FIU) testbed.