bluuebunny/crossref_metadata_2025 huggingface dataset:
What Do Younger and Well-Educated Adults Think about Self-Medication? Results of a Survey during a Public Science Event at Leipzig University
Authors: Gebert Ines , Hundertmark Sabine , Bertsche Thilo
Published: August 2024

Background: Consecutive visitors to a public science event at Leipzig University were asked about their opinions/attitudes regarding their personal use of self-medication. Methods: A written questionnaire survey addressed (i) participants’ characteristics, (ii) frequency of self-medication use in the last 12 months, (iii) symptoms/complaints most frequently considered applicable, (iv) preconditions, (v) limitations, (vi) risks, (vii) fears, (viii) medication information sources, (ix) influencing factors, and (x) reasons for decision making. Results: (i) A total of 189 visitors (median age: 29.0 years; Q25/Q75: 22.0/44.0) participated, of whom 64.0% were female, 38.6% had a university degree, 20.1% were in training, and 14.8% were licensed in a healthcare profession. (ii) A total of 59.3% of participants stated that they had used self-medication regularly in the last 12 months. The most common answers in the respective questions were (iii) headache, 86.2%; (iv) mild complaints/symptoms, 94.7%; (v) duration, 91.6%; (vi) “self-medication may cause adverse drug reactions”, 94.2%; (vii) “developing a habituation effect”, 58.7%; (viii) pharmacists, 93.7%; (ix) “physician’s recommendation”, 89.3%; (x) “intensity of complaints”, 92.6%; and (vi) 61.3% believed that they could choose an appropriate self-medication. Conclusion: Younger and well-educated adults report using self-medication frequently and rate their expertise as high. Healthcare professionals are the preferred source of information.
Metabolome and Mycobiome of Aegilops tauschii Subspecies Differing in Susceptibility to Brown Rust and Powdery Mildew Are Diverse
Authors: Pishchik Veronika N. , Chizhevskaya Elena P. , Kichko Arina A. , Aksenova Tatiana S. , Andronov Evgeny E. , Chebotar Vladimir K. , Filippova Polina S. , Shelenga Tatiana V. , Belousova Maria H. , Chikida Nadezhda N.
Published: August 2024

The present study demonstrated the differences in the seed metabolome and mycobiome of two Aegilops tauschii Coss accessions with different resistance to brown rust and powdery mildew. We hypothesized that the seeds of resistant accession k-1958 Ae. tauschii ssp. strangulata can contain a larger number of metabolites with antifungal activity compared with the seeds of susceptible Ae. tauschii ssp meyeri k-340, which will determine differences in the seed fungal community. Our study emphasizes the differences in the seed metabolome of the studied Ae. tauschii accessions. The resistant accession k-1958 had a higher content of glucose and organic acids, including pyruvic, salicylic and azelaic acid, as well as pipecolic acids, galactinol, glycerol and sitosterol. The seeds of Ae. tauschii-resistant accession k-1958 were found to contain more active substances with antifungal activity. The genera Cladosporium and Alternaria were dominant in the seed mycobiome of the resistant accession. The genera Alternaria, Blumeria and Cladosporium dominated in seed mycobiome of susceptible accession k-340. In the seed mycobiome of the resistant k-1958, a higher occurrence of saprotrophic micromycetes was found, and many of the micromycetes were biocontrol agents. It was concluded that differences in the seed metabolome of Ae. tauschii contributed to the determination of the differences in mycobiomes.
Characteristics of Rhizosphere Microbiome, Soil Chemical Properties, and Plant Biomass and Nutrients in Citrus reticulata cv. Shatangju Exposed to Increasing Soil Cu Levels
Authors: Mo Xiaorong , Huang Qichun , Chen Chuanwu , Xia Hao , Riaz Muhammad , Liang Xiaomin , Li Jinye , Chen Yilin , Tan Qiling , Wu Songwei , Hu Chengxiao
Published: August 2024

The prolonged utilization of copper (Cu)-containing fungicides results in Cu accumulation and affects soil ecological health. Thus, a pot experiment was conducted using Citrus reticulata cv. Shatangju with five Cu levels (38, 108, 178, 318, and 388 mg kg−1) to evaluate the impacts of the soil microbial processes, chemistry properties, and citrus growth. These results revealed that, with the soil Cu levels increased, the soil total Cu (TCu), available Cu (ACu), organic matter (SOM), available potassium (AK), and pH increased while the soil available phosphorus (AP) and alkali-hydrolyzable nitrogen (AN) decreased. Moreover, the soil extracellular enzyme activities related to C and P metabolism decreased while the enzymes related to N metabolism increased, and the expression of soil genes involved in C, N, and P cycling was regulated. Moreover, it was observed that tolerant microorganisms (e.g., p_Proteobacteria, p_Actinobacteria, g_Lysobacter, g_Sphingobium, f_Aspergillaceae, and g_Penicillium) were enriched but sensitive taxa (p_Myxococcota) were suppressed in the citrus rhizosphere. The citrus biomass was mainly positively correlated with soil AN and AP; plant N and P were mainly positively correlated with soil AP, AN, and acid phosphatase (ACP); and plant K was mainly negatively related with soil β−glucosidase (βG) and positively related with the soil fungal Shannon index. The dominant bacterial taxa p_Actinobacteriota presented positively correlated with the plant biomass and plant N, P, and K and was negatively correlated with plant Cu. The dominant fungal taxa p_Ascomycota was positively related to plant Cu but negatively with the plant biomass and plant N, P, and K. Notably, arbuscular mycorrhizal fungi (p_Glomeromycota) were positively related with plant P below soil Cu 108 mg kg−1, and pathogenic fungi (p_Mortierellomycota) was negatively correlated with plant K above soil Cu 178 mg kg−1. These findings provided a new perspective on soil microbes and chemistry properties and the healthy development of the citrus industry at increasing soil Cu levels.
Genome-Wide Identification and Expression Analyses of the Thaumatin-Like Protein Gene Family in Tetragonia tetragonoides (Pall.) Kuntze Reveal Their Functions in Abiotic Stress Responses
Authors: Huang Zengwang , Ding Qianqian , Wang Zhengfeng , Jian Shuguang , Zhang Mei
Published: August 2024

Thaumatin-like proteins (TLPs), including osmotins, are multifunctional proteins related to plant biotic and abiotic stress responses. TLPs are often present as large multigene families. Tetragonia tetragonoides (Pall.) Kuntze (Aizoaceae, 2n = 2x = 32), a vegetable used in both food and medicine, is a halophyte that is widely distributed in the coastal areas of the tropics and subtropics. Saline–alkaline soils and drought are two major abiotic stress factors significantly affecting the distribution of tropical coastal plants. The expression of stress resistance genes would help to alleviate the cellular damage caused by abiotic stress factors such as high temperature, salinity–alkalinity, and drought. This study aimed to better understand the functions of TLPs in the natural ecological adaptability of T. tetragonoides to harsh habitats. In the present study, we used bioinformatics approaches to identify 37 TtTLP genes as gene family members in the T. tetragonoides genome, with the purpose of understanding their roles in different developmental processes and the adaptation to harsh growth conditions in tropical coral regions. All of the TtTLPs were irregularly distributed across 32 chromosomes, and these gene family members were examined for conserved motifs of their coding proteins and gene structure. Expression analysis based on RNA sequencing and subsequent qRT-PCR showed that the transcripts of some TtTLPs were decreased or accumulated with tissue specificity, and under environmental stress challenges, multiple TtTLPs exhibited changeable expression patterns at short (2 h), long (48 h), or both stages. The expression pattern changes in TtTLPs provided a more comprehensive overview of this gene family being involved in multiple abiotic stress responses. Furthermore, several TtTLP genes were cloned and functionally identified using the yeast expression system. These findings not only increase our understanding of the role that TLPs play in mediating halophyte adaptation to extreme environments but also improve our knowledge of plant TLP evolution. This study also provides a basis and reference for future research on the roles of plant TLPs in stress tolerance and ecological environment suitability.
Organic Waste from the Management of the Invasive Oxalis pes-caprae as a Source of Nutrients for Small Horticultural Crops
Authors: Lorenzo Paula , Galhano Cristina , Dias Maria Celeste
Published: August 2024

The management of invasive plants is a challenge when using traditional control methods, which are ineffective for large areas, leading to the abandonment of invaded areas and the subsequent worsening of the situation. Finding potential uses for waste resulting from invaders’ management could motivate their control in the long-term, concurrently providing new bio-based resources with different applications. Oxalis pes-caprae is an invasive plant, widely distributed worldwide, which spreads aggressively through bulbils, creating a dense ground cover. This study was designed to assess the potential of Oxalis aboveground waste for use as fertilizer and in ameliorating deficit irrigation effects in growing crops. Diplotaxis tenuifolia (wild rocket) seedlings were planted in pots with soil mixed with Oxalis waste at 0, 2.2 and 4.3 kg m−2 or with commercial fertilizer, left to grow for 27 days and then irrigated at 100% or 50% field capacity for 14 days. The incorporation of the Oxalis waste improved the biomass, photosynthesis, sugars, total phenols and total antioxidant capacity in the crop, achieving commercial fertilization values, as well as increasing the phosphorus in soils. However, Oxalis waste seems not to directly affect plants’ relative water contents. Our results support the use of Oxalis waste as fertilizer, which can encourage the long-term control of this invasive species.
Research Progress on Lignin Depolymerization Strategies: A Review
Authors: Pei Zhengfei , Liu Xiaofang , Chen Jiasheng , Wang Huan , Li Hu
Published: August 2024

As the only natural source of aromatic biopolymers, lignin can be converted into value-added chemicals and biofuels, showing great potential in realizing the development of green chemistry. At present, lignin is predominantly used for combustion to generate energy, and the real value of lignin is difficult to maximize. Accordingly, the depolymerization of lignin is of great significance for its high-value utilization. This review discusses the latest progress in the field of lignin depolymerization, including catalytic conversion systems using various thermochemical, chemocatalytic, photocatalytic, electrocatalytic, and biological depolymerization methods, as well as the involved reaction mechanisms and obtained products of various protocols, focusing on green and efficient lignin depolymerization strategies. In addition, the challenges faced by lignin depolymerization are also expounded, putting forward possible directions of developing lignin depolymerization strategies in the future.
Development of a Cure Model for Unsaturated Polyester Resin Systems Based on Processing Conditions
Authors: Barakat Abdallah , Al Ghazal Marc , Fono Tamo Romeo Sephyrin , Phadatare Akash , Unser John , Hagan Joshua , Vaidya Uday
Published: August 2024

Unsaturated polyester resin (UPR) systems are extensively used in composite materials for applications in the transportation, marine, and infrastructure sectors. There are continually evolving formulations of UPRs that need to be evaluated and optimized for processing. Differential Scanning Calorimetry (DSC) provides valuable insight into the non-isothermal and isothermal behavior of UPRs within a prescribed temperature range. In the present work, non-isothermal DSC tests were carried out between temperatures of 0.0 °C and 250 °C, through different heating and cooling ramp rates. The isothermal DSC tests were carried out between 0.0 and 170 °C. The instantaneous rate of cure of the tested temperatures were measured. The application of an autocatalytic model in a calculator was used to simulate curing behaviors under different processing conditions. As the temperature increased from 10 °C up to 170 °C, the rate of cure reduced, and the heat of reaction increased. The simulated cure behavior from the DSC data showed that the degree of cure (α) maximum value of 71.25% was achieved at the highest heating temperature of 85 °C. For the low heating temperature, i.e., 5 °C, the maximum degree of cure (α) did not exceed 12% because there was not enough heat to activate the catalyst to crosslink further.
The Effect of Hydrophobic Modified Block Copolymers on Water–Oil Interfacial Properties and the Demulsification of Crude Oil Emulsions
Authors: Zhang Juan , Liu Ping , Gao Yuan , Yu Qingping
Published: August 2024

The demulsification effect of three types of block copolymers, BP123, BPF123, and H123, with the same PEO and PPO segments but different hydrophobic modification groups on crude oil emulsions and the properties of oil–water interfaces were investigated using demulsification experiments, an interfacial tensiometer, and surface viscoelastic and zeta potential instruments in this paper. The results showed that the hydrophobic modification group of the block copolymers had great effects on the demulsification performance. The H123 block copolymers with the strongest hydrophobicity had the best demulsification effect on the crude oil emulsions. The properties of the oil–water interfaces indicated that the modified block copolymers achieved the demulsification of crude oil emulsions by reducing the strength of the oil–water interfacial film and the interfacial tension.
Development of Edible Films Based on Nostoc and Modified Native Potato Starch and Their Physical, Mechanical, Thermal, and Microscopic Characterization
Authors: Mojo-Quisani Antonieta , Ccallo-Silva Daniel A. , Choque-Quispe David , Calla-Florez Miriam , Ligarda-Samanez Carlos A. , Comettant-Rabanal Raúl , Mamani-Condori Raul , Huamaní-Meléndez Víctor J.
Published: August 2024

Considering the potential of biopolymers from underutilized Andean sources in Peru to improve the characteristics of edible films, this work aimed to evaluate the formation of a polymeric matrix composed of Nostoc and modified potato starch for the formulation of edible films for food coating. The effects of polymer matrix ratio and drying temperature on films obtained by thermoforming were studied, determining the water vapor permeability and mechanical properties using a multifactorial design. Additionally, thermal properties were characterized by TGA and DSC, and structural properties by FT-IR and scanning electron microscopy. The results showed that the films exhibited lower solubility, lighter hues, better water vapor resistance, higher tensile strength, and improved thermal stability with increasing modified starch content. The formulation with higher Nostoc content exhibited a more homogeneous surface according to microscopy images, and no new chemical bonds were formed by adding modified starch and Nostoc to the polymer matrix, according to FT-IR spectra. These findings are promising and suggest using Nostoc for elaborating edible films composed of native and modified starch from native Andean potatoes as bio-based materials with potential application in the food industry.
Numerical Study of Melt-Spinning Dynamic Parameters and Microstructure Development with Ongoing Crystallization
Authors: Liu Xiangqian , Feng Pei , Yang Chongchang , Hu Zexu
Published: August 2024

In response to an investigation on the paths of changes in the crystallization and radial differences during the forming process of nascent fibers, in this study, we conducted numerical simulation and analyzed the changes in crystallization mechanical parameters and tensile properties through a fluid dynamics two-phase model. The model was based on the melt-spinning method focusing on melt spinning, the environment of POLYFLOW, and the method of joint simulation, coupled with Nakamura crystallization kinetics, including the development of process collaborative parameters, stretch-induced crystallization, viscoelasticity, filament cooling, gravity term, inertia, and air resistance. Finally, for nylon 6 BHS and CN9987 resin spinning, the model successfully predicted the distribution changes in temperature, velocity, strain rate tensor, birefringence, and stress tensor along the axial and radial fibers and obtained the variation pattern of fibers’ crystallinity along the entire spinning process under different stretching rates. Furthermore, we also explored the effects of spinning conditions, including inlet flow rate, winding speeds, and the extrusion temperature, on the fibers’ crystallization process and obtained the influence rules of different spinning conditions on fiber crystallization. Knowing the paths of changes in mechanical performance can provide important guidance and optimization strategies for the future industrial preparation of high-performance fibers.
Research on Energy Dissipation of Hydrofoil Cavitation Flow Field with FBDCM Model
Authors: Huang Rui , Wang Yulong , Xu Haitao , Qiu Chaohui , Ma Wei
Published: August 2024

In order to obtain a more detailed and comprehensive relationship between the cavitation phenomenon and energy loss, this paper takes an NACA66 hydrofoil as an example to analyze the specific relationship between the cavitation flow field and energy dissipation by using entropy production theory, a ZGB cavitation model, and k-ε turbulence model which were modified by a Filter-Based Density Correction model (FBDCM). The results show that the modified k-ε model can effectively capture the morphology of cavity evolution in the cavitation flow field. The vortex dilatation term contributes the most to the vorticity transport in cavitation flow. The energy loss of the cavitation flow field is primarily composed of turbulent dissipation, which is primarily distributed in the area below the lifted attached cavity and inside the vortex induced by the cloud cavity. The direct dissipation entropy production is predominantly distributed in the area near the stagnation point of the hydrofoil’s leading edge and inside the cavity. The wall entropy production is chiefly distributed in the area where the cavity is not covered. The cavitation entropy production mainly occurs on the vapor–liquid interface, and the value is negative, indicating that the vapor–liquid conversion in the cavitation process needs to absorb energy from the flow field.
Strategy for Renewable Energy Consumption Based on Scenario Reduction and Flexible Resource Utilization
Authors: Cao Xiaoqing , Yang Xuan , Li He , Chen Di , Zhang Zhengyu , Yang Qingrui , Zou Hongbo
Published: August 2024

With the growing global emphasis on renewable energy, the issue of renewable energy consumption has emerged as a hot topic of current research. In response to the volatility and uncertainty in the process of renewable energy consumption, this study proposes a renewable energy consumption strategy based on scenario reduction and flexible resource utilization. This strategy aims to achieve the efficient utilization of renewable energy sources through optimized resource allocation while ensuring the stable operation of the power system. Firstly, this study employs scenario analysis methods to model the volatility and uncertainty of renewable energy generation. By applying scenario reduction techniques, typical scenarios are selected to reduce the complexity of the problem, providing a foundation for the construction of the optimization model. At the same time, by fully considering the widely available small-capacity energy storage units within the system, a flexible cloud energy storage scheduling model is constructed to assist in renewable energy consumption. Finally, the validity and feasibility of the proposed method are demonstrated through case studies. Through analysis, the proposed scenario generation method achieved a maximum value of 26.28 for the indicator IDBI and a minimum value of 1.59 for the indicator ICHI. Based on this foundation, the cloud energy storage model can fully absorb renewable energy, reducing the net load peak-to-trough difference to 1759 kW, a decrease of 809 kW compared with the traditional model.
Adaptive Finite-Time Constrained Attitude Stabilization for an Unmanned Helicopter System under Input Delay and Saturation
Authors: Li Yang , Yang Ting
Published: August 2024

This study focuses on addressing the constrained attitude stabilization problem for an unmanned helicopter (UH) system subject to disturbances, input delay and actuator saturation. A constrained memory sliding mode is first presented to constrain the flight attitude while handling the input delay. On this basis, an adaptive finite-time nonlinear observer is proposed to estimate the lumped disturbance with unknown upper bound. Moreover, based on the hyperbolic tangent function, a saturated attitude controller is designed to tackle the input saturation problem via the adaptive laws. The finite-time stability of the closed-loop constrained attitude system is proved by Lyapunov synthesis. Finally, the developed scheme can accomplish attitude stabilization and overcome the influence of disturbances, attitude constraint, input delay and actuator saturation in an easy way. Numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.
Prediction of Liquid Accumulation Height in Gas Well Tubing Using Integration of Crayfish Optimization Algorithm and XGBoost
Authors: Xia Wenlong , Liu Botao , Xiang Hua
Published: August 2024

The prediction of the liquid build-up height in gas wells is a crucial aspect of reservoir development and is essential for the efficient execution of drainage and gas extraction operations. Excessive liquid accumulation can lead to well flooding and operational shutdowns, resulting in significant economic losses. To prevent such occurrences, accurate estimation of the liquid height in gas well tubing is necessary. However, existing petroleum engineering models face numerous challenges in predicting liquid height, including complex theoretical solution steps and reliance on fundamental well parameters and extensive empirical data. The paper proposes an innovative blend of the Crayfish Optimization Algorithm (COA) with the eXtreme Gradient Boosting (XGBoost) methodology to forecast the liquid loading heights in gas wells. The COA is employed to optimize eight hyperparameters of the XGBoost, including the number of trees, maximum depth, minimum child weight, learning rate, minimum loss reduction, subsample, L1 regularization, and L2 regularization. After fine-tuning the hyperparameters, the XGBoost undergoes a retraining process, followed by an evaluation. Through comparative analysis with actual measurements from 32 wells in a gas field as well as support vector regression (SVR), XGBoost, random forest (RF), and PLATA (which predict liquid volume in the tubing and annulus), the proposed COA–XGBoost demonstrates a high degree of alignment with the measured values. It provides the most accurate predictions, with a mean relative error of only 2.25%. Compared with the traditional XGBoost, the COA–XGBoost reduced the mean relative error in predicting gas well tubing liquid loading height by 32.63%. Compared with the previous PLATA, the proposed model achieved a 3.52% decrease in mean relative error, enabling more accurate assessment of the severity of liquid loading in gas wells.
Computational Analysis of Upscaled Fibrotic Liver Multi-Lobule Flows and Metabolism
Authors: Coombe Dennis , Wallace Cooper , Rezania Vahid , Tuszynski Jack A.
Published: August 2024

The modeling of fibrotic effects on fluid flow and metabolism in the liver can be computationally challenging. This paper combines innovative concepts based on fundamental physics to address such issues at the level of the liver functional unit, the lobule, and upscales and extends this to a multi-lobule tissue scale analysis. Fibrosis effects on fluid flow and metabolism are introduced using percolation theory and its consequences are explored for single lobule and multi-lobule patterns, without and with distortion.
Acid-Etched Fracture Conductivity with In Situ-Generated Acid in Ultra-Deep, High-Temperature Carbonate Reservoirs
Authors: Jia Haizheng , Pu Hongyuan , Li Jianmin , Wang Junchao , Chen Xi , Mou Jianye , Gao Budong
Published: August 2024

In situ-generated acid is commonly employed in ultra-deep, high-temperature carbonate reservoirs during acid fracturing to increase the effective acid penetration distance. However, the variation pattern of acid-etched fracture conductivity with in situ-generated acid has not been systematically studied. This paper investigates the evolution of the conductivity of primary and secondary fractures through a series of experiments involving in situ acid displacement and acid-etched fracture conductivity measurement. Based on the experimental results, a calculation model for the conductivity of acid-etched fractures with in situ-generated acid was established. The study indicates that after acid etching, rough particulate points and grooved dissolution patterns form on the surfaces of primary and secondary fractures, respectively. The dissolution volume in primary fractures is greater than that in secondary fractures, with both showing a linear increase over time. Due to the presence of dissolution grooves on the surfaces of secondary fractures, their conductivity is higher than that of primary fractures under the same acid–rock contact time. The conductivity of both primary and secondary fractures increases with the acid–rock contact time. However, beyond approximately 70 min of contact time, the conductivity of primary fractures shows no significant increase. The conductivity of primary and secondary fractures with in situ-generated acid is slightly lower than that with gelled acid under the same contact time, but significantly higher than that with crosslinked acid. This study provides guidance for the design and parameter optimization of acid fracturing in ultra-deep, high-temperature carbonate reservoirs.
Study on Short-Term Electricity Load Forecasting Based on the Modified Simplex Approach Sparrow Search Algorithm Mixed with a Bidirectional Long- and Short-Term Memory Network
Authors: Zhang Chenjun , Zhang Fuqian , Gou Fuyang , Cao Wensi
Published: August 2024

In order to balance power supply and demand, which is crucial for the safe and effective functioning of power systems, short-term power load forecasting is a crucial component of power system planning and operation. This paper aims to address the issue of low prediction accuracy resulting from power load volatility and nonlinearity. It suggests optimizing the number of hidden layer nodes, number of iterations, and learning rate of bi-directional long- and short-term memory networks using the improved sparrow search algorithm, and predicting the actual load data using the load prediction model. Using actual power load data from Wuxi, Jiangsu Province, China, as a dataset, the model makes predictions. The results indicate that the model is effective because the enhanced sparrow algorithm optimizes the bi-directional long- and short-term memory network model for predicting the power load data with a relative error of only 2%, which is higher than the prediction accuracy of the other models proposed in the paper.
Practical Mysticism in Islam and Christianity: A Comparative Study of Rabia al-Adawiyya and Catherine of Genoa
Authors: Idoko Patricia Enedudu
Published: August 2024

The mystical experiences in various forms are fundamental to major religious traditions. The idea of “mysticism” brings up the concept of the ineffable mysterium, which is seen as the central theme around which religions are based. The comparative studies of Rabia al-Adawiyya and Catherine of Genoa do not intend, as with phenomenological and essentialist approaches to the study of religion, to only focus on the similarities of the mystics in order to find universal structures and essential meanings. Nor does it seek to concentrate solely on the differences between the mystics as done by constructivist scholars. Instead, the comparative methodology used in this article highlights the similarities and differences between the respective mystics, Rabia and Catherine, and uses these comparisons to draw attention to an example of interreligious spirituality that cuts across religious traditions. To illustrate this point, it helps to compare two mystics: Rabia from the Islamic tradition and Catherine from the Christian tradition. This study is structured in four parts: an introduction to the concept of mystical experiences, a brief overview of the lives of Rabia and Catherine, a comparative analysis of their mystical characteristics, and a discussion of how their experiences can serve as a model for interreligious spirituality and friendship.
What Is the “Similarity” of Humankind? A Difference between Confucian and Mohist Religious Ethics
Authors: Yao Yurui
Published: August 2024

Both pre-Qin Confucianism and Mohism aimed to find a universalist consensus of belief in order to deal with social chaos and disunity, but they diverged at a basic level on what is the fundamental universality of humankind and how to achieve it. In the debate between Mencius and Mohists, Mohists believed that the fundamental “similarity” of humankind lies in the field of “self-interest”, so they emphasized the acquisition of Heaven’s favor through external achievements and sacrificial offerings. On the contrary, Mencius took the fundamental similarity of humans to the level of the inner heart-mind and believed that the fundamental “sameness” of humans lies in their “heart-mind” rather than in being “self-interested”, so he advocated the connection with the heavenly part within us when we follow the guidance of the heart-mind. Their differing interpretations of the fundamental question of “the similarity of humankind” ultimately resulted in the divergences and discrepancies between two religious ethical forms and their outcomes in early China.
Underwater Acoustic Scattering from Multiple Ice Balls at the Ice–Water Interface
Authors: Hu Siwei , Chen Wenjian , Sun Hui , Zhou Shunbo , Yin Jingwei
Published: August 2024

We investigate the underwater acoustic scattering from various distributed “ice balls” floating on the water, aiming to understand acoustic scattering in the marginal ice zone (MIZ). The MIZ, including a wide range of heterogeneous ice cover, significantly impacts acoustic propagation. We use acoustic modelling, simulation, and laboratory experiments to understand the acoustic scattering from various distributed ice balls. The acoustic scattering fields from a single sound source (90 kHz) in water are analyzed based on selected principal scattering waves between the surfaces of ice and water. The target strengths are calculated using the plate element method and physical acoustic methods, which are validated with water tank experimental data. The methodology is then extended to multiple ice ball cases, specifically considering a single ice ball, equally spaced ice balls of the same size, and randomly distributed ice balls of various sizes. Additionally, experimental measurements under similar conditions are conducted in a laboratory water tank. The scattering intensities at different receiving positions are simulated and compared with lab experiments. The results show good agreement between experimental and numerical results, with an absolute error of less than 3 dB. Scattering intensity is positively correlated with water surface reflection when the receiving angle is close to the mirror reflection angle of the incident wave. Our approach sets the groundwork for further research to address more complex ice–water interfaces with various ice covers in the MIZ.
MFO-Fusion: A Multi-Frame Residual-Based Factor Graph Optimization for GNSS/INS/LiDAR Fusion in Challenging GNSS Environments
Authors: Zou Zixuan , Wang Guoshuai , Li Zhenshuo , Zhai Rui , Li Yonghua
Published: August 2024

In various practical applications, such as autonomous vehicle and unmanned aerial vehicle navigation, Global Navigation Satellite Systems (GNSSs) are commonly used for positioning. However, traditional GNSS positioning methods are often affected by disturbances due to external observational conditions. For instance, in areas with dense buildings, tree cover, or tunnels, GNSS signals may be obstructed, resulting in positioning failures or decreased accuracy. Therefore, improving the accuracy and stability of GNSS positioning in these complex environments is a critical concern. In this paper, we propose a novel multi-sensor fusion framework based on multi-frame residual optimization for GNSS/INS/LiDAR to address the challenges posed by complex satellite environments. Our system employs a novel residual detection and optimization method for continuous-time GNSS within keyframes. Specifically, we use rough pose measurements from LiDAR to extract keyframes for the global system. Within these keyframes, the multi-frame residuals of GNSS and IMU are estimated using the Median Absolute Deviation (MAD) and subsequently employed for the degradation detection and sliding window optimization of the GNSS. Building on this, we employ a two-stage factor graph optimization strategy, significantly improving positioning accuracy, especially in environments with limited GNSS signals. To validate the effectiveness of our approach, we assess the system’s performance on the publicly available UrbanLoco dataset and conduct experiments in real-world environments. The results demonstrate that our system can achieve continuous decimeter-level positioning accuracy in these complex environments, outperforming other related frameworks.
Real-Time Detection and Correction of Abnormal Errors in GNSS Observations on Smartphones
Authors: Mu Hongbo , Yu Xianwen , Aragon-Angel Angela , Wang Jiafu , Wu Yanze
Published: August 2024

Smartphones, due to the integration of low-cost GNSS chips and linearly polarized antennas, frequently experience abnormal errors in their observations, particularly during positioning on water surfaces. In response to this issue, this paper proposes a method for detecting and correcting abnormal errors in GNSS observations on smartphones. Firstly, the state and observation equations of the Kalman filter are formulated based on the continuous and smooth characteristics of pseudorange and carrier observations. Secondly, real-time detection of abnormal error occurrence in observations is performed by assessing whether the difference between the predicted and observed values computed by the Kalman filter exceeds a specified threshold. Finally, depending on abnormal errors within the epoch, different strategies are applied for real-time reparation of observations containing anomalies. Two smartphones have been used for static tests on land and kinematic tests on water. Results show that under various environmental conditions, the proposed method effectively enhances the quality of observations on smartphones. Specifically, the method achieved a maximum improvement of 86.03% in pseudorange quality and 84.31% in carrier phase quality. The method proposed in this paper outperformed the State-Based method by approximately 10% on land and by 10–35% on water. It also shows high stability and reliability, particularly in complex environments such as navigation on water.
Decentralized System Synchronization among Collaborative Robots via 5G Technology
Authors: Celik Ali Ekber , Rodriguez Ignacio , Ayestaran Rafael Gonzalez , Yavuz Sirma Cekirdek
Published: August 2024

In this article, we propose a distributed synchronization solution to achieve decentralized coordination in a system of collaborative robots. This is done by leveraging cloud-based computing and 5G technology to exchange causal ordering messages between the robots, eliminating the need for centralized control entities or programmable logic controllers in the system. The proposed solution is described, mathematically formulated, implemented in software, and validated over realistic network conditions. Further, the performance of the decentralized solution via 5G technology is compared to that achieved with traditional coordinated/uncoordinated cabled control systems. The results indicate that the proposed decentralized solution leveraging cloud-based 5G wireless is scalable to systems of up to 10 collaborative robots with comparable efficiency to that from standard cabled systems. The proposed solution has direct application in the control of producer–consumer and automated assembly line robotic applications.
Design and Characterization of a Wearable Inertial Measurement Unit
Authors: Tirado Diego Valdés , Carro Gonzalo García , Alvarez Juan C. , López Antonio M. , Álvarez Diego
Published: August 2024

The utilization of inertial measurement units as wearable sensors is proliferating across various domains, such as health care, sports, and rehabilitation. This expansion has produced a market of devices tailored to accommodate very specific ranges of operational demands. Simultaneously, this growth is creating opportunities for the development of a new class of devices more oriented towards general-purpose use and capable of capturing both high-frequency signals for short-term, event-driven motion analysis and low-frequency signals for extended monitoring. For such a design, which combines flexibility and low cost, a rigorous evaluation of the device in terms of deviation, noise levels, and precision is essential. This evaluation is crucial for identifying potential improvements and refining the design accordingly, yet it is rarely addressed in the literature. This paper presents the development process of such a device. The results of the design process demonstrate acceptable performance in optimizing energy consumption and storage capacity while highlighting the most critical optimizations needed to advance the device towards the goal of a smart, general-purpose unit for human motion monitoring.
Detection Method of Stator Coating Quality of Flat Wire Motor Based on Improved YOLOv8s
Authors: Wang Hongping , Chen Gong , Rong Xin , Zhang Yiwen , Song Linsen , Shang Xiao
Published: August 2024

The stator of a flat wire motor is the core component of new energy vehicles. However, detecting quality defects in the coating process in real-time is a challenge. Moreover, the number of defects is large, and the pixels of a single defect are very few, which make it difficult to distinguish the defect features and make accurate detection more difficult. To solve this problem, this article proposes the YOLOv8s-DFJA network. The network is based on YOLOv8s, which uses DSFI-HEAD to replace the original detection head, realizing task alignment. It enhances joint features between the classification task and localization task and improves the ability of network detection. The LEFG module replaces the C2f module in the backbone of the YOLOv8s network that reduces the redundant parameters brought by the traditional BottleNeck structure. It also enhances the feature extraction and gradient flow ability to achieve the lightweight of the network. For this research, we produced our own dataset of stator coating quality regarding flat wire motors. Data augmentation technology (Gaussian noise, adjusting brightness, etc.) enriches the dataset, to a certain extent, which improves the robustness and generalization ability of YOLOv8s-DFJA. The experimental results show that in the performance of YOLOv8s-DFJA compared with YOLOv8s, the mAP@.5 index increased by 6.4%, the precision index increased by 1.1%, the recall index increased by 8.1%, the FPS index increased by 9.8FPS/s, and the parameters decreased by 3 Mb. Therefore, YOLOv8s-DFJA can be better realize the fast and accurate detection of the stator coating quality of flat wire motors.
Early Bolt Loosening Detection Method Based on Digital Image Correlation
Authors: Li Yinyin , Wu Yusen , Gao Kang , Yang Huiyuan
Published: August 2024

Bolt loosening can significantly impact the accuracy, stability, and safety of equipment. The detection of bolt loosening in a timely manner is crucial for ensuring the safety, reliability, performance, and service life of equipment, structures, and systems. Various methods exist for detecting bolt loosening, such as strain gauges and ultrasonic waves. However, these technologies have some limitations that impede their widespread application. In this paper, for the high-pressure pipe manifolds that may experience leakage accidents due to the loosening of bolts, an early bolt loosening detection method based on digital image correlation is proposed. Initially, a model is established through tensile tests to relate the average strain on the side of the bolt head to the axial force. Subsequently, an industrial camera captures images of bolts with random speckles under operational conditions. Using digital image correlation technology, the average strain in a specific region on the side of the bolt head is calculated. By integrating the average strain into the established relationship model between the average strain and axial force, the axial force of the bolt under operational conditions can be predicted, enabling the early assessment of bolt loosening. The findings show that the average strain on the side of the bolt head increases proportionally with the axial force, indicating a strong linear relationship. This method enables accurate prediction of the bolt’s axial force, offering a new approach for identifying the early loosening of bolts in high-pressure manifolds and monitoring structural health.
Enhanced Detection and Recognition of Road Objects in Infrared Imaging Using Multi-Scale Self-Attention
Authors: Liu Poyi , Zhang Yunkang , Guo Guanlun , Ding Jiale
Published: August 2024

In infrared detection scenarios, detecting and recognizing low-contrast and small-sized targets has always been a challenge in the field of computer vision, particularly in complex road traffic environments. Traditional target detection methods usually perform poorly when processing infrared small targets, mainly due to their inability to effectively extract key features and the significant feature loss that occurs during feature transmission. To address these issues, this paper proposes a fast detection and recognition model based on a multi-scale self-attention mechanism, specifically for small road targets in infrared detection scenarios. We first introduce and improve the DyHead structure based on the YOLOv8 algorithm, which employs a multi-head self-attention mechanism to capture target features at various scales and enhance the model’s perception of small targets. Additionally, to prevent information loss during the feature transmission process via the FPN structure in traditional YOLO algorithms, this paper introduces and enhances the Gather-and-Distribute Mechanism. By computing dependencies between features using self-attention, it reallocates attention weights in the feature maps to highlight important features and suppress irrelevant information. These improvements significantly enhance the model’s capability to detect small targets. Moreover, to further increase detection speed, we pruned the network architecture to reduce computational complexity and parameter count, making the model suitable for real-time processing scenarios. Experiments on our self built infrared road traffic dataset (mainly including two types of targets: vehicles and people) show that compared with the baseline, our method achieves a 3.1% improvement in AP and a 2.5% increase in mAP on the VisDrone2019 dataset, showing significant enhancements in both detection accuracy and processing speed for small targets, with improved robustness and adaptability.
Bearing Dynamics Modeling Based on the Virtual State-Space and Hammerstein–Wiener Model
Authors: Jiang Genghong , Zhou Kai , Li Zhaorong , Yan Jianping
Published: August 2024

This study investigates a novel approach for assessing the health status of rotating machinery transmission systems by analyzing the dynamic degradation of bearings. The proposed method generates multi-dimensional data by creating virtual states and constructs a multi-dimensional model using virtual state-space in conjunction with mechanism model analysis. Innovatively, the Hammerstein–Wiener (HW) modeling technique from control theory is applied to identify these dynamic multi-dimensional models. The modeling experiments are performed, focusing on the model’s input and output types, the selection of nonlinear module estimators, the configuration of linear module transfer functions, and condition transfer. Dynamic degradation response signals are generated, and the method is validated using four widely recognized databases consisting of accurate measurement signals collected by vibration sensors. Experimental results demonstrated that the model achieved a modeling accuracy of 99% for multiple bearings under various conditions. The effectiveness of this dynamic modeling method is further confirmed through comparative experimental data and signal images. This approach offers a novel reference for evaluating the health status of transmission systems.
Improved Fast-Response Consensus Algorithm Based on HotStuff
Authors: Wang Rong , Yuan Minfu , Wang Zhenyu , Li Yin
Published: August 2024

Recent Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) protocols increasingly focus on scalability and security to meet the growing demand for Distributed Ledger Technology (DLT) applications across various domains. Current BFT consensus algorithms typically require a single leader node to receive and validate votes from the majority process and broadcast the results, a design challenging to scale in large systems. We propose a fast-response consensus algorithm based on improvements to HotStuff, aimed at enhancing transaction ordering speed and overall performance of distributed systems, even in the presence of faulty copies. The algorithm introduces an optimistic response assumption, employs a message aggregation tree to collect and validate votes, and uses a dynamically adjusted threshold mechanism to reduce communication delay and improve message delivery reliability. Additionally, a dynamic channel mechanism and an asynchronous leader multi-round mechanism are introduced to address multiple points of failure in the message aggregation tree structure, minimizing dependence on a single leader. This adaptation can be flexibly applied to real-world system conditions to improve performance and responsiveness. We conduct experimental evaluations to verify the algorithm’s effectiveness and superiority. Compared to the traditional HotStuff algorithm, the improved algorithm demonstrates higher efficiency and faster response times in handling faulty copies and transaction ordering.