bluuebunny/crossref_metadata_2025 huggingface dataset:
A Stable Sound Field Control Method for a Personal Audio System
Authors: Wang Song , Zhang Cong
Published: November 2023

A personal audio system has a wide application prospect in people’s lives, which can be implemented by sound field control technology. However, the current sound field control technology is mainly based on sound pressure or its improvement, ignoring another physical property of sound: particle velocity, which is not conducive to the stability of the entire reconstruction system. To address the problem, a sound field method is constructed in this paper, which minimizes the reconstruction error in the bright zone, minimizes the loudspeaker array effort in the reconstruction system, and at the same time controls the particle velocity and sound pressure of the dark zone. Five unevenly placed loudspeakers were used as the initial setup for the computer simulation experiment. Simulation results suggest that the proposed method is better than the PM (pressure matching) and EDPM (eigen decomposition pseudoinverse method) methods in the bright zone in an acoustic contrast index, the ACC (acoustic contrast control) method in a reconstruction error index, and the ACC, PM, and EDPM methods in the bright zone in a loudspeaker array effort index. The average array effort of the proposed method is the smallest, which is about 9.4790, 8.0712, and 4.8176 dB less than that of the ACC method, the PM method in the bright zone, and the EDPM method in the bright zone, respectively, so the proposed method can produce the most stable reconstruction system when the loudspeaker system is not evenly placed. The results of computer experiments demonstrate the performance of the proposed method, and suggest that compared with traditional methods, the proposed method can achieve more balanced results in the three indexes of acoustic contrast, reconstruction error, and loudspeaker array effort on the whole.
Assessing Change of Direction Ability in Young Male Athletes: A Comparative Analysis of Change of Direction Deficit and Change of Direction Total Time
Authors: Ye Jiachi , Wang Yi , Gao Binghong
Published: November 2023

This study aimed to explore the relationship between change of direction deficit (CODD), change of direction total time (CODTT), and linear sprint time and to compare the differences between CODD and CODTT in assessing an athlete’s change of direction (COD) ability. Forty-four highly trained male young athletes underwent Y-shaped pre-planned agility, Pro-agility, and 30 m linear sprint tests. The results showed a moderate to highly significant correlation between CODTT and linear speed time at 0–5 m, 0–10 m, and 0–30 m (r = 0.5–0.8), while there was no statistically significant relationship between CODD and linear speed time at 0–5 m and 0–10 m (r = 0.0–0.3). CODD and CODTT were moderate to highly correlated (r = 0.4–0.8), with CODD for 180° COD showing a higher predictive value for CODTT compared to 45° COD (14–35% vs. 49–63%). Additionally, 13–22% of the participants showed opposing results for COD ability when comparing the standardized Z-score of Pro-agility 0–10 m CODTT and CODD. Pro-agility 0–10 m CODD also resulted in a higher asymmetry ratio (2% vs. 7%) and COD ability imbalances (0% vs. 38%) than Pro-agility 0–10 m CODTT. In conclusion, CODD may provide a more accurate assessment of an athlete’s COD ability than CODTT.
Particle Formation Mechanism of TiCl4 Hydrolysis to Prepare Nano TiO2
Authors: Le Qianjun , Yu Shengfei , Luo Wusheng
Published: November 2023

This study utilizes Aspen Plus chemical process simulation software (V11), applies uniform nucleation theory and growth kinetics equations, and explores the particle formation mechanism of TiCl4 hydrolysis to prepare nano TiO2. In the water/ethanol system, the effects of the reaction time, reaction temperature, water addition, pH value, and ethanol amount on the crystal nucleation rate and TiO2 particle distribution (PSD) were studied in detail by adding triethanolamine dropwise and using the Aspen Plus chemical process software simulation calculation method. The calculation results indicate that at room temperature, the formation of TiO2 crystal nuclei mainly occurs in the first 300 s and then enters the growth stage. The reaction was carried out under neutral conditions at room temperature for 4 h in 1 mL TiCl4, 6 mL C6H15NO3, 15 mL H2O, and 30 mL C2H5OH. The maximum number of particles reached 195 mesh per cubic micrometer, and the particle size after crystal nucleus growth was smaller, with a D50 of 6.15 nm. The distribution curve shows a normal distribution, which is basically consistent with the experimental results. When studying various factors, it was found that controlling the reaction time within 60 min and maintaining the reaction temperature at room temperature can reduce the particle size D50 to 2.44 nm. Continuing to adjust the amount of water added, it was found that at 1 mL, D50 decreased again to 0.19 nm. Adjusting the pH value found that maintaining the neutrality did not change the particle size. Continuing to adjust ethanol, it was found that adding an appropriate amount of ethanol promoted nucleation and growth. At 4 mL, the maximum number of particles reached 199 mesh per cubic micrometer, but D50 slightly increased to 0.24 nm.
AI-Powered Intelligent Seaport Mobility: Enhancing Container Drayage Efficiency through Computer Vision and Deep Learning
Authors: Lee Hoon , Chatterjee Indranath , Cho Gyusung
Published: November 2023

The rapid urbanization phenomenon has introduced multifaceted challenges across various domains, including housing, transportation, education, health, and the economy. This necessitates a significant transformation of seaport operations in order to optimize smart mobility and facilitate the evolution of intelligent cities. This conceptual paper presents a novel mathematical framework rooted in deep learning techniques. Our innovative model accurately identifies parking spaces and lanes in seaport environments based on crane positions, utilizing live Closed-Circuit Television (CCTV) camera data for real-time monitoring and efficient parking space allocation. Through a comprehensive literature review, we explore the advantages of merging artificial intelligence (AI) and computer vision (CV) technologies in parking facility management. Our framework focuses on enhancing container drayage efficiency within seaports, emphasizing improved traffic management, optimizing parking space allocation, and streamlining container movement. The insights from our study provide a foundation that could have potential implications for real-world applications. By integrating cutting-edge technologies, our proposed framework not only enhances the efficiency of seaport operations, but also lays the foundation for sustainable and intelligent seaport systems. It signifies a significant leap toward the realization of intelligent seaport operations, contributing profoundly to the advancement of urban logistics and transportation networks. Future research endeavors will concentrate on the practical implementation and validation of this pioneering mathematical framework in real-world seaport environments. Additionally, our work emphasizes the crucial need to explore further applications of AI and CV technologies in seaport logistics, adapting the framework to address the evolving urbanization and transportation challenges. These efforts will foster continuous advancements in the field, shaping the future of intelligent seaport operations.
Learning to Segment Blob-like Objects by Image-Level Counting
Authors: Wüstefeld Konstantin , Ebbinghaus Robin , Weichert Frank
Published: November 2023

There is a high demand for manually annotated data in many of the segmentation tasks based on neural networks. Selecting objects pixel by pixel not only takes much time, but it can also lead to inattentiveness and to inconsistencies due to changing annotators for different datasets and monotonous work. This is especially, but not exclusively, the case with sensor data such as microscopy imaging, where many blob-like objects need to be annotated. In addressing these problems, we present a weakly supervised training method that uses object counts at the image level to learn a segmentation implicitly instead of relying on a pixelwise annotation. Our method uses a given segmentation network and extends it with a counting head to enable training by counting. As part of the method, we introduce two specialized losses, contrast loss and morphological loss, which allow for a blob-like output with high contrast to be extracted from the last convolutional layer of the network before the actual counting. We show that similar high F1-scores can be achieved with weakly supervised learning methods as with strongly supervised training; in addition, we address the limitations of the presented method.
Multi-Pedestrian Tracking Based on KC-YOLO Detection and Identity Validity Discrimination Module
Authors: Li Jingwen , Wu Wei , Zhang Dan , Fan Dayong , Jiang Jianwu , Lu Yanling , Gao Ertao , Yue Tao
Published: November 2023

Multiple-object tracking (MOT) is a fundamental task in computer vision and is widely applied across various domains. However, its algorithms remain somewhat immature in practical applications. To address the challenges presented by complex scenarios featuring instances of missed detections, false alarms, and frequent target switching leading to tracking failures, we propose an approach to multi-object tracking utilizing KC-YOLO detection and an identity validity discrimination module. We have constructed the KC-YOLO detection model as the detector for the tracking task, optimized the selection of detection frames, and implemented adaptive feature refinement to effectively address issues such as incomplete pedestrian features caused by occlusion. Furthermore, we have introduced an identity validity discrimination module in the data association component of the tracker. This module leverages the occlusion ratio coefficient, denoted by “k”, to assess the validity of pedestrian identities in low-scoring detection frames following cascade matching. This approach not only enhances pedestrian tracking accuracy but also ensures the integrity of pedestrian identities. In experiments on the MOT16, MOT17, and MOT20 datasets, MOTA reached 75.9%, 78.5%, and 70.1%, and IDF1 reached 74.8%, 77.8%, and 72.4%. The experimental results demonstrate the superiority of the methodology. This research outcome has potential applications in security monitoring, including public safety and fire prevention, for tracking critical targets.
Correlation between Biogenic Amines and Their Precursors in Stored Chicken Meat
Authors: Wójcik Wojciech , Damaziak Krzysztof , Łukasiewicz-Mierzejewska Monika , Świder Olga , Niemiec Jan , Wójcicki Michał , Roszko Marek , Gozdowski Dariusz , Riedel Julia , Marzec Agata
Published: November 2023

Biogenic amines (BAs) are biologically active substances found in the cells of microorganisms, plants, and animals. These BAs serve many vital functions in the body. However, an excessive amount can be toxic, especially for individuals taking monoamine oxidase (MAO) and diamine oxidase (DAO) inhibitors. They primarily form in products rich in amino acids, the primary substrates for BA formation. The aim of this study was to determine the formation of BAs and their precursor amino acids in chicken breast and leg muscles stored under chilling conditions. Analyses of BA and AA determinations were conducted on days 1, 3, 5, 7, and 10 of muscle storage. There was a noted increase in BAs with the storage of both muscle types (p < 0.05). Distinct levels of BAs were detected (p < 0.05) in the muscles, except for putrescine (p > 0.05). Interactions emerged between the two factors for various Bas, including histamine (p = 0.001), tyramine (p < 0.001), BAI index (p < 0.001), tryptamine (p < 0.001), agmatine (p = 0.001), spermidine (p < 0.001), TOTAL BA-1 (p < 0.001), and TOTAL BA-2 (p = 0.016). There was no evident interaction between the type of meat and storage time concerning amino acid content (p > 0.05). Correlations in breast muscles were observed for biogenic amine–amino acid pairs such as putrescine–ornithine (r = −0.57) (p < 0.05), spermidine–ornithine (r = −0.73) (p < 0.05), and phenylethylamine–phenylethylalanine (r = −0.50) (p < 0.05). In leg muscles, significant correlations were found for histamine–histidine (r = −0.87) (p < 0.05), putrescine–ornithine (r = −0.96) (p < 0.05), and phenylethylamine–phenylethylalanine (r = −0.65) (p < 0.05). The results obtained can be used in the future to estimate the levels of BAs with knowledge of the levels of individual amino acids and inversely.
HSDT: Table-Overflow Attack Defender with Historical Statistics Based Dynamic Timeout in Software Defined Networks
Authors: Noh Sichul Kevin , Park Minho
Published: November 2023

A Software Defined Network (SDN) provides efficient network management by decoupling two planes: the control plane and the data plane. However, although SDN provides efficient network management, it also causes several critical vulnerabilities. In particular, the lack of memory for a flow table in the data plane can be exploited to conduct a flow table overflow attack. This paper proposes a history-based dynamic timeout scheme to mitigate the flow table overflow attack. The proposed scheme dynamically sets up both hard timeout and idle timeout based on statistical history for each flow, which can quickly remove attack flows from a flow table. Consequently, it can keep the occupancy of the flow table low and secure the robustness against the flow table overflow attack. The experiment results show that the proposed HSDT can mitigate the overflow attack with reasonable overhead by effectively evicting attack flow rules from the flow table while it has a minimal impact on the other normal flow rules and bandwidth.
Cytoprotective–Antioxidant Effect of Brunfelsia grandiflora Extract on Neuron-like Cells
Authors: Rodríguez José-Luis , Mateos Raquel , Palomino Olga , Fernández-Alfonso Maria S. , Ramos-Cevallos Norma , Inostroza-Ruiz Luis , Panduro-Tenazoa Nadia , Bada-Laura Wendy , Ramírez-Flores Noé , Goya Luis
Published: November 2023

Brunfelsia grandiflora is a South American solanaceae widely used since long ago for its recognized medicinal properties. We have recently reported its chemical composition, showing a relevant number of bioactive compounds with antioxidant capacity, and proved the cytoprotective and antioxidative stress potential of B. grandiflora in cultured endothelial cells. Since B. grandiflora extracts have shown effects on the central nervous system, the present study was designed to show the potential cytoprotective capacity and the antioxidative stress potential of phenolic extracts from the plant on cultured neuron-like cells, as a model to reduce the presentation or effects of chronic diseases of the nervous system. To this end, we studied its reactive oxygen species (ROS)-reducing capacity, its antioxidant defense mechanisms, and some molecular markers involved in redox balance and apoptosis. The results show that cell survival and most changes in biomarkers related to oxidative status, ROS, reduced glutathione, glutathione peroxidase and reductase, malondialdehyde, and caspase 3/7 activity, and molecular expression of cell death-related genes (BAX, BNIP3, and APAF1), NFκB, SOD, and NRF2 (genes from oxidative stress—antioxidants) induced by oxidative stress were prevented by either co- or pretreatment of neuron-like cells with B. grandiflora extracts (25–200 µg/mL). The results demonstrate the chemoprotective potential of the plant and support its medicinal use.
A Review of Research on Diagnosability of Control Systems Based on Structural Analysis
Authors: Gu Xuping , Shi Xianjun
Published: November 2023

Structural analysis, a model-based fault diagnosis approach, has been extensively highlighted since it does not depend on an exact analytical system model. The structural analysis approach focuses on obtaining the required information for fault detection and fault-tolerant control from the structural model of the control system. Diagnosability is a design attribute that indicates the fault diagnosis capabilities. Diagnosability design not only guarantees that the structure of the control system gives adequate fault information but also that the control system achieves the fault diagnosis with the least cost and the most excellent efficiency. In this paper, in combination with the research progress of structural analysis, the study first designs the structural diagnosability model of the control system based on structural analysis; secondly, the essential techniques of diagnosability evaluation and diagnosability design based on structural analysis are analyzed and summarized, and the diagnosability index system based on structural analysis is designed based on the structural detectability and structural isolation; this lays the foundation for the development of the diagnosability; lastly, the study summarizes the problems of diagnosability research based on structural analysis and the future development direction.
A Novel Multi-Task Performance Prediction Model for Spark
Authors: Shen Chao , Chen Chen , Rao Guozheng
Published: November 2023

Performance prediction of Spark plays a vital role in cluster resource management and system efficiency improvement. The performance of Spark is affected by several variables, such as the size of the input data, the computational power of the system, and the complexity of the algorithm. At the same time, less research has focused on multi-task performance prediction models for Spark. To address these challenges, we propose a multi-task Spark performance prediction model. The model integrates a multi-head attention mechanism and a convolutional neural network. It implements the prediction of execution times for single or multiple Spark applications. Firstly, the data are dimensionally reduced by a dimensionality reduction algorithm and fed into the model. Secondly, the model integrates a multi-head attention mechanism and a convolutional neural network. It captures complex relationships between data features and uses these features for Spark performance prediction. Finally, we use residual connections to prevent overfitting. To validate the performance of the model, we conducted experiments on four Spark benchmark applications. Compared to the benchmark prediction model, our model obtains better performance metrics. In addition, our model predicts multiple Spark benchmark applications simultaneously and maintains deviations within permissible limits. It provides a novel way for the assessment and optimization of Spark.
Brake Squeal Investigations Based on Acoustic Measurements Performed on the FIVE@ECL Experimental Test Bench
Authors: Besset Sebastien , Lenoir David , Sinou Jean-Jacques
Published: November 2023

Radiated noise is a major topic of interest regarding the brake squeal phenomenon as it is directly linked to the noise generated which can be potentially detrimental to user comfort and perception. However, very few studies offer in-depth and comprehensive insight into the analysis and understanding of acoustic noise during squeal events. This study is intended to provide an original contribution to this issue by investigating acoustic phenomena occurring during the squeal phenomenon via a digital antenna composed of 117 microphones. Experiments are performed on the Friction-Induced Vibration and noisE test bench at Ecole Centrale de Lyon (FIVE@ECL). The first main aim is to investigate the characteristics of the acoustic radiated field during brake squeal and more particularly to describe the evolution of the radiated field patterns per revolution of the disc system. The second major aim is to illustrate the possibility of reconstructing the radiated acoustic field everywhere in the space surrounding the brake system, leading to the construction of a robust representation of 3D acoustic patterns, providing acoustic squeal events in the physical space around the brake system. Results show that the vibratory signature remains identical during squeal event braking test. The acoustic signature of squeal noise consists mainly of a fundamental frequency and its harmonic components, with secondary lower contributions from other fundamental frequencies. The associated radiated acoustic field during squeal events are characterized by different directivities and intensities of the acoustic radiated field for each squeal frequency, with potential changes in these directivities and intensities over short times corresponding to the rotation period of the disc.
Effect of Wood Densification and GFRP Reinforcement on the Embedment Strength of Poplar CLT
Authors: Rostampour-Haftkhani Akbar , Abdoli Farshid , Arabi Mohammad , Nasir Vahid , Rashidi Maria
Published: November 2023

Embedment strength is an important factor in the design and performance of connections in timber structures. This study assesses the embedment strength of lag screws in three-ply cross-laminated timber (CLT) composed of densified poplar wood with densification ratios of 25% and 50%, under both longitudinal (L) and transverse (T) loading conditions. The embedment strength was thereafter compared with that of CLT reinforced with glass-fiber-reinforced polymer (GFRP). The experimental data was compared with results obtained using different models for calculating embedment strength. The findings indicated that the embedment strength of CLT specimens made of densified wood and GFRP was significantly greater than that of control specimens. CLT samples loaded in the L direction showed higher embedment strength compared to those in the T direction. In addition, 50% densification had the best performance, followed by 25% densification and GFRP reinforcement. Modelling using the NDS formula yielded the highest accuracy (mean absolute percentage error = 10.31%), followed by the Ubel and Blub (MAPE = 21%), Kennedy (MAPE = 28.86%), CSA (MAPE = 32.68%), and Dong (MAPE = 40.07%) equations. Overall, densification can be considered as an alternative to GFRP reinforcement in order to increase the embedment strength in CLT.
SSCL-TransMD: Semi-Supervised Continual Learning Transformer for Malicious Software Detection
Authors: Kou Liang , Zhao Donghui , Han Hui , Xu Xiong , Gong Shuaige , Wang Liandong
Published: November 2023

Machine learning-based malware (malicious software) detection methods have a wide range of real-world applications. However, these types of approaches suffer from the fatal problem of “model aging”, in which the validity of the model decreases rapidly as the malware continues to evolve and variants emerge continuously. The model aging problem is usually solved by model retraining, which relies on lots of labeled samples obtained at great expense. To address this challenge, this paper proposes a semi-supervised continuous learning malware detection model based on Transformer. Firstly, this model improves the lifelong semi-supervised mixture algorithm to dynamically adjust the weighted combination of new sample sequences and historical ones to solve the imbalance problem. Secondly, the Learning with Local and Global Consistency algorithm is used to iteratively compute similarity scores for the unlabeled samples in the mixed samples to obtain pseudo-labels. Lastly, the Multilayer Perceptron is applied for malware classification. To validate the effectiveness of the model, this paper conducts experiments on the CICMalDroid2020 dataset. The experimental results show that the proposed model performs better than existing deep learning detection models. The F1 score has an average improvement of 1.27% compared to other models when conducting binary classification. And, after inputting hybrid samples, including historical data and new data, four times, the F1 score is still 1.96% higher than other models.
Research on the Accuracy of Clothing Simulation Development: The Influence of Human Body Part Characteristics on Virtual Indicators
Authors: Cheng Zhe , Wu Xinzhou , Kuzmichev Victor
Published: November 2023

Currently, many virtual simulation design studies of compression pants do not consider pressure distribution and human body characteristics. Therefore, this study aimed to optimize the simulation design accuracy of compression pants by investigating female body characteristics to improve the pressure distribution and enhance comfort. Firstly, we divided the body part features into flexible and rigid parts, performed compression relationship analysis between the material and the body, and collected qualitative and quantitative data related to the potential influencing factors. Subsequently, by conducting correlation analysis of the data, a pressure prediction model was established to address the pressure value errors in the simulation data. The research results showed that there was a significant difference between the real and virtual pressures in the flexible parts of the female body, and that the real pressure was closely related to the elasticity and thickness properties of the material. By optimizing virtual pressure values, the consistency between the virtual pressure and real test results can be significantly improved. The accurate prediction and optimization of pressure values can lead to the reduction of material waste and energy consumption during the manufacturing process.
Decision-Making in Fallback Scenarios for Autonomous Vehicles: Deep Reinforcement Learning Approach
Authors: Lee Cheonghwa , An Dawn
Published: November 2023

This paper proposes a decision-making algorithm based on deep reinforcement learning to support fallback techniques in autonomous vehicles. The fallback technique attempts to mitigate or escape risky driving conditions by responding to appropriate avoidance maneuvers essential for achieving a Level 4+ autonomous driving system. However, developing a fallback technique is difficult because of the innumerable fallback situations to address and eligible optimal decision-making among multiple maneuvers. We employed a decision-making algorithm utilizing a scenario-based learning approach to address these issues. First, we crafted a specific fallback scenario encompassing the challenges to be addressed and matched the anticipated optimal maneuvers as determined by heuristic methods. In this scenario, the ego vehicle learns through trial and error to determine the most effective maneuver. We conducted 100 independent training sessions to evaluate the proposed algorithm and compared the results with those of heuristic-derived maneuvers. The results were promising; 38% of the training sessions resulted in the vehicle learning lane-change maneuvers, whereas 9% mastered slow following. Thus, the proposed algorithm successfully learned human-equivalent fallback capabilities from scratch within the provided scenario.
Evaluating the Ileal and Cecal Microbiota Composition of a 1940 Heritage Genetic Line and a 2016 Commercial Line of white Leghorns Fed Representative Diets from 1940 to 2016
Authors: Wall Dannica C. , Dittoe Dana , Malherios Ramon D. , Anderson Kenneth E. , Anthony Nick
Published: November 2023

This study identified and evaluated differences between microbiome compositions of the ileum and ceca of 1940 and 2016 white leghorn genetic strains fed representative contemporary diets from those times. Ileal and cecal samples were collected at 69 weeks of age. Alpha and beta diversity metrics were generated, and the Analysis of Composition of Microbiomes (ANCOM) was utilized to determine significantly different taxa. Ileum and ceca alpha diversity were significantly different (p = 0.001; Q = 0.001); however, no differences between genetic lineage were observed (p > 0.05; Q > 0.05). Beta diversity between the ileum and ceca and the genetic lines was significantly different (p = 0.001; Q = 0.001). The ANCOM of the ileum showed significant differences between Proteobacteria and Actinobacteriota phyla (p ˂ 0.05) and significant differences between Pseudomonas, Rhizobiaceae, Leuconostoc, and Aeriscardovia genera (p ˂ 0.05). For ceca ANCOM, Proteobacteria, Firmicutes, Actinobacteriota, and Euryarchaeota phyla were significantly different (p ˂ 0.05), with Firmicutes having the highest relative abundance across all groups, and there were significant differences in genera Pseudomonas, Leuconostoc, Alloprevotella, and Aeri scardovia, with Alloprevotella having the highest relative abundance. The results suggest that genetic makeup in conjunction with the nutritional composition influences the cecal and ileal microbiota of corresponding hens.
Characterization of Freeze-Thaw Cycle Damage to Mudstone in Open Pit in Cold Regions—Based on Nuclear Magnetic Resonance Method
Authors: Lu Xiang , Qi Xiang , Tian Ya , Li Rui , Wang Zhile , Tu Lixiao , Zhang Zhiyuan
Published: November 2023

Damage deterioration of rocks in cold regions under seasonal changes and daily cycles of freezing and thawing generate a series of engineering geological problems. These problems will seriously affect the safe and efficient production of open-pit mines. In this paper, a freeze–thaw cycle test and uniaxial compression test considering the natural conditions of the slope were carried out. Mechanical properties and damage mechanisms of open-pit mine mudstone under freeze–thaw conditions were investigated based on nuclear magnetic resonance (NMR) technology. The test results show that the microscopic internal pore structure of mudstone was changed under the superimposed effect of freeze–thaw damage and hydration damage. The internal pore size of mudstone increased with the number of freeze–thaw cycles, while the average pore size of the natural mudstone test increased more. Macroscopically, the compressive strength and modulus of elasticity of mudstone varied linearly with the number of freezing cycles, and the compressive strength and modulus of elasticity showed a decreasing trend. The strain-softening characteristics of mudstone samples were significant for more freeze–thaw cycles. The study explains the microscopic causes of mudstone deterioration in open-pit mines in cold regions and offers guidance for solving engineering disasters caused by mudstone deterioration.
Prediction of Cyanobacteria Using Decision Tree Algorithm and Sensor Monitoring Data
Authors: Jo Bu-Geon , Jung Woo-Suk , Nam Su-Han , Kim Young-Do
Published: November 2023

A multifunctional weir was built on the Nakdong River. As a result, changes in the river environment occurred, such as an increase in river residence time. This causes changes in water quality, including green algae. The occurrence of green algae in the Nakdong River, which is used as a water source, also affects the purified water supply system. In particular, the mass spread of harmful algae is becoming a major problem as the frequency and intensity of occurrences increase. There are various causes of blue-green algae. We would like to examine the relationships between causal factors through a decision tree-based algorithm. Additionally, we would like to predict the occurrence of green algae based on the combination of these factors. For prediction, we studied categorical prediction based on the blue-green algae warning system used in Korea. RF, Catboost and XGBoost algorithms were used. Optimal hyperparameters were applied. We compared the prediction performance of each algorithm. In addition, the predictability of using sensor-based data was reviewed for a preemptive response to the occurrence of blue-green algae. By applying sensor-based data, the accuracy was over 80%. Prediction accuracy by category was also over 75%. It is believed that real-time prediction is possible through sensor-based factors. The optimal forecast period was analyzed to determine whether a preemptive response was possible and the possibility of improvement was examined through the segmentation of prediction categories. When there were three categories, 79% of predictions were possible by the 21st day. In seven categories, 75% prediction was possible up to 14 days. In this study, sensor-based categorical predictability was derived. In addition, real-time response and proactive response were determined. Such sensor-based algae prediction research is considered important for future blue-green algae management and river management.
Nonlinear Controller for an Inverted Pendulum Using the Trigonometric Function
Authors: Lower Michal
Published: November 2023

In this paper, a nonlinear controller (TR) for an inverted pendulum using the trigonometric function is presented. The TR controller is a new proposal, which is represented by a simple mathematical formula. TR operation does not require complex calculations, so it can be applied even to the simplest microcontrollers. Tuning the TR controller is very simple, and the range of stable operation is very wide. Simulation tests of the TR controller showed that the controller is effective even for deviations exceeding 50∘. The TR controller tests were compared to the results of a PID controller. The TR controller is designed to stabilise an inverted pendulum in the equilibrium point, a state in which the pendulum is in a upright position. Stabilisation for other deflection-angle set points was not taken into account. During the research, steps were taken to simulate phenomena characteristic of real solutions. An inertial block and a disturbance were introduced into the test system. Despite the introduced difficulties, the TR controller effectively stabilised the pendulum without the need to retune the controller settings. Consequently, the TR controller is an attractive alternative to previously applied solutions for the stabilisation of an inverted pendulum.
Studies on the Energy Consumption of Material Cutting in the Onion Peeling Process
Authors: Zastempowski Marcin , Bochat Andrzej , Wachowicz Marcin , Tanaś Wojciech
Published: November 2023

This paper describes experimental studies of cutting the outer layer of onions in a machine processing process. For this purpose, an original, globally innovative machine design with a modular structure was used, which was constructed in a real scale. For the purposes of carrying out the experimental studies, a test stand was constructed, a plan and programme for the studies were adopted, and a research methodology was developed. The results gained and the data obtained from the equations of the regression function for the developed machine design were used to construct systems of independent variables for which the dependent variable reaches extreme values. The unit energy consumption of the onion peeling process increases together with an increase in the number of air nozzles and the air pressure supplying the unit for removing the skins, while an increase in the material feeding speed and in the distance of the air nozzles results in a decrease in the energy consumption of the process.
The State of Precipitation Measurements at Mid-to-High Latitudes
Authors: Milani Lisa , Kidd Christopher
Published: November 2023

The measurement of global precipitation is important for quantifying and understanding the Earth’s systems. While gauges form the basis of conventional measurements, global measurements are only truly possible using satellite observations. Over the last 50–60 years, satellite systems have evolved to provide a comprehensive suite of observing systems, including many sensors that are capable of precipitation retrievals. While much progress has been made in developing and implementing precipitation retrieval schemes, many techniques have concentrated upon retrievals over regions with well-defined precipitation systems, such as the tropics. At higher latitudes, such retrieval schemes are less successful in providing accurate and consistent precipitation estimates, especially due to the large diversity of precipitation regimes. Furthermore, the increasing dominance of snowfall at higher latitudes imposes a number of challenges that require further, urgent work. This paper reviews the state of the current observations and retrieval schemes, highlighting the key factors that need to be addressed to improve the estimation and measurement of precipitation at mid-to-high latitudes.
Homotopes of Quasi-Jordan Algebras
Authors: Alhefthi Reem K. , Siddiqui Akhlaq A. , Jamjoom Fatmah B.
Published: November 2023

The notion of quasi-Jordan algebras was originally proposed by R. Velasquez and R. Fellipe. Later, M. R. Bremner provided a modification called K-B quasi-Jordan algebras; these include all Jordan algebras and all dialgebras, and hence all associative algebras. Any quasi-Jordan algebra is special if it is isomorphic to a quasi-Jordan subalgebra of some dialgebras. Keeping in view the pivotal role of homotopes in the theory of Jordan algebras, we begin a study of the homotopes of quasi-Jordan algebras; among other related results, we show that the homotopes of any special quasi-Jordan algebra are special quasi-Jordan algebras and that the homotopes of a K-B quasi-Jordan algebra is a quasi-Jordan algebra. In the sequel, we also give some open problems.
Investigating the Link between Eating Attitudes, Taste and Odour Preferences and the Chemical Senses
Authors: St Clair Layla , Grady Alyssa , Mahmut Mehmet K.
Published: November 2023

Objectives: To examine if higher degrees of pathological eating attitudes in a non-clinical sample are associated with odour and taste perception and preferences based on psychophysical ratings. Participants and Methods: A total of 80 female university students completed the eating attitudes test (EAT-26), followed by four chemosensory measures including olfactory and gustatory perception plus perceptual ratings and preferences for food odours and tastes. Results: There were no significant correlations between EAT-26 scores and measures of olfactory and gustatory perception. However, a significant interaction effect indicated higher degrees of pathological eating attitudes may be associated with differential sensitivity to sweet and fatty food odours compared to those with lower levels of pathological eating attitudes. Conclusions: This was the first study to examine pathological eating attitudes using food stimuli with a non-clinical sample. The results remain preliminary until replication. However, the findings highlight the need for development of measures of disordered eating attitudes and behaviours that go beyond caloric restriction.
Dynamics of Methane-Consuming Biomes from Wieliczka Formation: Environmental and Enrichment Studies
Authors: Goraj Weronika , Pytlak Anna , Grządziel Jarosław , Gałązka Anna , Stępniewska Zofia , Szafranek-Nakonieczna Anna
Published: November 2023

The rocks surrounding Wieliczka salt deposits are an extreme, deep subsurface ecosystem that as we studied previously harbors many microorganisms, including methanotrophs. In the presented research bacterial community structure of the Wieliczka Salt Mine was determined as well as the methanotrophic activity of the natural microbiome. Finally, an enrichment culture of methane-consuming methanotrophs was obtained. The research material used in this study consisted of rocks surrounding salt deposits in the Wieliczka Salt Mine. DNA was extracted directly from the pristine rock material, as well as from rocks incubated in an atmosphere containing methane and mineral medium, and from a methanotrophic enrichment culture from this ecosystem. As a result, the study describes the composition of the microbiome in the rocks surrounding the salt deposits, while also explaining how biodiversity changes during the enrichment culture of the methanotrophic bacterial community. The contribution of methanotrophic bacteria ranged from 2.614% in the environmental sample to 64.696% in the bacterial culture. The methanotrophic enrichment culture was predominantly composed of methanotrophs from the genera Methylomonas (48.848%) and Methylomicrobium (15.636%) with methane oxidation rates from 3.353 ± 0.105 to 4.200 ± 0.505 µmol CH4 mL−1 day−1.
Microplastics in Different Tissues of a Commonly Consumed Fish, Scomberomorus guttatus, from a Large Subtropical Estuary: Accumulation, Characterization, and Contamination Assessment
Authors: Hossain Mohammad Belal , Pingki Farjana Haque , Azad Md. Abdus Samad , Nur As-Ad Ujjaman , Banik Partho , Paray Bilal Ahamad , Arai Takaomi , Yu Jimmy
Published: November 2023

Microplastics (MPs) ingestion by fish signifies a worldwide threat to human health but limited research has examined their existence within the consumable portions (muscle) of fish. Thus, this study was undertaken to unveil the prevalence, characterization, and contamination extent of MPs across various body tissues, including the muscle of the king mackerel (S. guttatus) from the lower Meghna estuary in Bangladesh—a pioneering investigation in this region. In our analysis, we identified a total of 487 MPs, with an average abundance of 48.7 ± 20.3 MPs/individual. These MPs were distributed across different tissues, with respective concentrations of 0.84 ± 0.45 items/g in the digestive tract, 2.56 ± 0.73 items/g in the gills, and 0.3 ± 1.72 items/g in the muscle tissue. The observed variations among these tissue types were statistically significant (p < 0.05). Moreover, a significant positive correlation indicated that fish with higher weight had higher MPs in their gills and DT (digestive tract). The majority were <0.5 mm in size (97.74%) and exhibited a fiber-like shape (97.74%), with a notable prevalence of transparent (25.87%) and a pink coloration (27.92%). Remarkably, the majority of MPs were discovered within the size range of <0.5–1 mm (100%), particularly in the muscle tissue, signifying a substantial transfer of MPs into the human diet. Besides, we discovered only three polymer types of microplastics which could be attributed to the extensive use of food packaging, plastic containers, wrapping plastics, residential garbage, and plastic pipes that end up in the aquatic environment via river discharges. The contamination factor (CF) values of fish muscle (5.75) and the digestive tract (5.50) indicated that these fish organs were considerably contaminated (3 < CF < 6) with MPs. The pollution index of MPs (PLI > 1) indicated a high contamination level for MPs pollution of S. guttatus in the lower Meghna River estuary.
Genetic Diversity and Signatures of Selection in the Roughskin Sculpin (Trachidermus fasciatus) Revealed by Whole Genome Sequencing
Authors: San Lize , He Zhongwei , Liu Yufeng , Zhang Yitong , Cao Wei , Ren Jiangong , Han Tian , Li Bingbu , Wang Guixing , Wang Yufen , Hou Jilun
Published: November 2023

The roughskin sculpin (Trachidermus fasciatus) is an endangered fish species in China. In recent years, artificial breeding technology has made significant progress, and the population of roughskin sculpin has recovered in the natural environment through enhancement programs and the release of juveniles. However, the effects of released roughskin sculpin on the genetic structure and diversity of wild populations remain unclear. Studies on genetic diversity analysis based on different types and numbers of molecular markers have yielded inconsistent results. In this study, we obtained 2,610,157 high-quality SNPs and 494,698 InDels through whole-genome resequencing of two farmed populations and one wild population. Both farmed populations showed consistent levels of genomic polymorphism and a slight increase in linkage compared with wild populations. The population structure of the two farmed populations was distinct from that of the wild population, but the degree of genetic differentiation was low (overall average Fst = 0.015). Selective sweep analysis showed that 523,529 genes were selected in the two farmed populations, and KEGG enrichment analysis showed that the selected genes were related to amino acid metabolism, which might be caused by artificial feeding. The findings of this study provide valuable additions to the existing genomic resources to help conserve roughskin sculpin populations.
Dynamics of Docosahexaenoic Acid Utilization by Mouse Peritoneal Macrophages
Authors: Monge Patricia , Astudillo Alma M. , Pereira Laura , Balboa María A. , Balsinde Jesús
Published: November 2023

In this work, the incorporation of docosahexaenoic acid (DHA) in mouse resident peritoneal macrophages and its redistribution within the various phospholipid classes were investigated. Choline glycerophospholipids (PC) behaved as the major initial acceptors of DHA. Prolonged incubation with the fatty acid resulted in the transfer of DHA from PC to ethanolamine glycerophospholipids (PE), reflecting phospholipid remodeling. This process resulted in the cells containing similar amounts of DHA in PC and PE in the resting state. Mass spectrometry-based lipidomic analyses of phospholipid molecular species indicated a marked abundance of DHA in ether phospholipids. Stimulation of the macrophages with yeast-derived zymosan resulted in significant decreases in the levels of all DHA-containing PC and PI species; however, no PE or PS molecular species were found to decrease. In contrast, the levels of an unusual DHA-containing species, namely PI(20:4/22:6), which was barely present in resting cells, were found to markedly increase under zymosan stimulation. The levels of this phospholipid also significantly increased when the calcium-ionophore A23187 or platelet-activating factor were used instead of zymosan to stimulate the macrophages. The study of the route involved in the synthesis of PI(20:4/22:6) suggested that this species is produced through deacylation/reacylation reactions. These results define the increases in PI(20:4/22:6) as a novel lipid metabolic marker of mouse macrophage activation, and provide novel information to understand the regulation of phospholipid fatty acid turnover in activated macrophages.