bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting the Invasion Risk of the Highly Invasive Acacia mearnsii in Asia under Global Climate Change
Authors: Poudel Anil , Adhikari Pradeep , Adhikari Prabhat , Choi Sue Hyuen , Yun Ji Yeon , Lee Yong Ho , Hong Sun Hee
Published: October 2024

Acacia mearnsii, among the 100 worst invasive weeds worldwide, negatively impacts native biodiversity, agriculture, and natural ecosystems. Global climate change, characterized by rising temperatures and altered precipitation patterns, enhances the risk of A. mearnsii invasion in Asia, making it crucial to identify high-risk areas for effective management. This study performed species distribution modeling using the maximum entropy (MaxEnt) algorithm to predict the potential introduction and spread of A. mearnsii under various climate scenarios based on shared socio-economic pathways (SSP2-4.5 and SSP5-8.5). Currently, only 4.35% of Asia is invaded, with a high invasion risk identified in six countries, including Bhutan, Lebanon, and Taiwan, where more than 75% of their areas are threatened. Under future climate scenarios, 21 countries face invasion risk, among which 14 countries, such as Georgia, Laos, Republic of Korea, and Turkey, are at moderate to very high risk, potentially encompassing up to 87.89% of their territories. Conversely, Northern Asian countries exhibit minimal changes in invasion risk and are considered relatively safe from invasion. These findings underscore that climate change will exacerbate invasion risks across Asia, emphasizing the urgent need for robust management strategies, including stringent quarantine measures and control efforts, to mitigate the threat of A. mearnsii expansion.
CaARP1/CaSGT1 Module Regulates Vegetative Growth and Defense Response of Pepper Plants against Phytophthora capsici
Authors: Li Xia , Weng Yahong , Chen Yufeng , Liu Kaisheng , Liu Yanyan , Zhang Kan , Shi Lanping , He Shuilin , Liu Zhiqin
Published: October 2024

Pepper (Capsicum annuum L.) suffers severe quality and yield loss from oomycete diseases caused by Phytophthora capsici. CaSGT1 was previously determined to positively regulate the immune response of pepper plants against P. capsici, but by which mechanism remains elusive. In the present study, the potential interacting proteins of CaSGT1 were isolated from pepper using a yeast two-hybrid system, among which CaARP1 was determined to interact with CaSGT1 via bimolecular fluorescence complementation (BiFC) and microscale thermophoresis (MST) assays. CaARP1 belongs to the auxin-repressed protein family, which is well-known to function in modulating plant growth. The transcriptional and protein levels of CaARP1 were both significantly induced by infection with P. capsici. Silencing of CaARP1 promotes the vegetative growth of pepper plants and attenuates its disease resistance to P. capsici, as well as compromising the hypersensitive response-like cell death in pepper leaves induced by PcINF1, a well-characterized typical PAMP from P. capsici. Chitin-induced transient expression of CaARP1 in pepper leaves enhanced its disease resistance to P. capsici, which is amplified by CaSGT1 co-expression as a positive regulator. Taken together, our result revealed that CaARP1 plays a dual role in the pepper, negatively regulating the vegetative growth and positively regulating plant immunity against P. capsici in a manner associated with CaSGT1.
Scaling Relationships of the Structural and Rheological Behavior of Tadpole Polymer Chains in Dilute Solution Systems Using Brownian Dynamics Simulations
Authors: Cho Chaehyun , Kim Jun Mo
Published: October 2024

Tadpole polymers, also known as lasso polymers, feature molecular structures that combine a single ring with a single linear side branch, leading to distinct conformational, dynamical, and rheological characteristics compared to their corresponding counterparts, particularly pure linear and pure ring polymers. To elucidate the mechanisms underlying these distinctive behaviors, comprehensive mesoscopic Brownian dynamics (BD) simulations of dilute solution systems of tadpole polymers were conducted using a bead–rod chain model under both equilibrium and flow conditions. Three types of tadpole polymer chains were prepared by varying the ring-to-linear ratio within the tadpole chain and comparing them with the corresponding linear and ring chains. Depending on this ratio, tadpole polymer chains exhibit entirely different structural properties and rotational dynamics, both in equilibrium and under shear flow. As the linear proportion within the tadpole chain increased, the structural, dynamic, and rheological properties of the tadpole polymer chains became more similar to those of pure linear polymers. Conversely, with an increasing ring proportion, these properties began to resemble those of pure ring polymers. Based on these observed tendencies, a simple general scaling expression is proposed for tadpole polymer properties that integrates scaling expressions for both pure linear and pure ring polymers. Our results indicate that the conformational, dynamic, and rheological properties of tadpole polymers, as predicted by these simple scaling expressions, are in good agreement with the simulated values, a result we consider statistically significant.
Hydrogen Bond Integration in Potato Microstructure: Effects of Water Removal, Thermal Treatment, and Cooking Techniques
Authors: Dankar Iman , Haddarah Amira , Pujolà Montserrat , Sepulcre Francesc
Published: October 2024

Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and Scanning electron microscopy (SEM) were used to study the effects of heat treatments and water removal by freeze-drying after different time intervals (6, 12, 24, 48, and 72 h) on the molecular structure of potato tubers. SEM images show structural differences between raw (RP), microwaved (MP), and boiled potato (BP). MP showed a cracked structure. BP was able to re-associate into a granule-like structure after 6 h of freeze-dying, whereas RP had dried granules within a porous matrix after 24 h of freeze-drying. These results are consistent with the moisture content and FTIR results for MP and BP, which demonstrated dried spectra after 6 h of freeze-drying and relatively coincided with RP results after 24 h of freeze-drying. Additionally, three types of hydrogen bonds have been characterized between water and starch, and the prevalence of water very weakly bound to starch has also been detected. The relative crystallinity (RC) was increased by thermal treatment, whereby microwaving recorded the highest value. A comparison of the FTIR and XRD results indicated that freeze-drying treatment overcomes heat effects to generate an integral starch molecule.
Upgrading Sustainable Pipeline Monitoring with Piezoelectric Energy Harvesting
Authors: Mahdi Zainab Kamal , Abbas Riyadh A. , Al-Taleb Manaf K. Hussain , Ali Adnan Hussein , Mohamed Esam M.
Published: October 2024

This study presents the design and implementation of a piezoelectric power harvesting device to capture vibrational energy from pipelines to self-powered IoT devices. The device utilizes key components along with the PPA-1001 piezoelectric sensor, the STM32F103C8T6 microcontroller, and LTC-3588 energy harvesting power supply. Experimental results verified the system’s performance in harvesting power within a specific frequency range of 10 Hz to 50 Hz, with the foremost overall performance at 30 Hz. The device generated the highest voltage of 3.3 V, delivering a power output of 2.18 mW, which is sufficient to power low-power electronic devices. The device maintained solid performance across a temperature range of 40 °C to 50 °C, underscoring its robustness in various environmental situations. The findings highlight the capacity of this form of generation to offer a sustainable power source for remote pipeline tracking, contributing to stronger protection and operational efficiency.
The Assessment of Abrasion Resistance of Casted Non-Ferrous Metals and Alloys with the Use of 3D Scanning
Authors: Strzępek Paweł
Published: October 2024

Three-dimensional scanning techniques are being more frequently used in modern industry, especially for quality control. This study shows the possibility of implementing 3D scanning as a tool for assessing the abrasion resistance of non-ferrous metal and alloy cast rods obtained in the continuous casting process. Samples of the same diameter after preweighing and initial scanning were subjected to abrasion tests in five identical cycles to show the progress of their wear. To conduct this process, the samples were weighed and scanned after each cycle. After the final abrasion test, the pure aluminum weight loss was 7%, with 3.4–4.1 mm abrasion, while the AlSi alloy had a weight loss of only 4.63% and 2.3–2.4 mm abrasion. When it came to pure copper, the loss was 2.76%, with 1.6–1.7 mm abrasion. CuNiSi alloys showed a loss between 2.01% and 2.24% and 1.3–1.5 mm abrasion, while CuMg alloys showed a loss between 1.51% and 1.63% and 1.2–1.4 mm abrasion, depending on the Ni and Mg content, respectively. The obtained results were correlated with the density and hardness of the tested materials and proved that both these factors are relevant when it comes to abrasion resistance; however, hardness is more significant.
A Leakage Safety Discrimination Model and Method for Saline Aquifer CCS Based on Pressure Dynamics
Authors: Ni Jun , Wang Chengjun , Dang Hailong , Jing Hongwei , Zhao Xiaoliang
Published: October 2024

The saline aquifer CCS is a crucial site for carbon storage. Safety monitoring is a key technology for saline aquifer CCS. Current CO2 leakage detection methods include microseismic, electromagnetic, and well-logging techniques. However, these methods face challenges, such as difficulties in determining CO2 migration fronts and predicting potential leakage events; as a result, the formulation of test timing and methods for these safety monitoring techniques are somewhat arbitrary. This study establishes a gas–water two-phase seepage model and solves it using a semi-analytical method to obtain the injection pressure and the derivative curve characteristics of the injection well. The pressure derivative curve can reflect the physical properties of the reservoir through which CO2 flows underground, and it can also be used to determine whether CO2 leakage has occurred, as well as the timing and amount of leakage, based on boundary responses. This study conducted sensitivity analyses on eight parameters to determine the impact of each parameter on the bottom-hole pressure and its derivatives, thereby obtaining the influence of its parameters on different flow stages. The research indicates that, when a steady-state flow characteristic appears at the outer boundary, CO2 leakage will occur. Additionally, the leakage location can be determined by calculating the distance from the injection well. This can guide the placement and measurement of safety monitoring methods for saline aquifer CCS. The method proposed in this paper can effectively monitor the timing, location, and amount of leakage, providing a technical safeguard for promoting CCS technology.
A Review of Linear Compressor Vibration Isolation Methods
Authors: Zeng Xiangkun , Xu Jiansheng , Han Biaojie , Zhu Zhijun , Wang Siyi , Wang Jiangang , Yang Xiaoqing , Cai Renye , Du Canyi , Zeng Jinbin
Published: October 2024

Linear compressors exhibit high compression efficiency and low noise characteristics, showcasing broad application prospects in various fields such as aerospace, medicine, household appliances, and more. However, due to the complexity of their structures and operation, the issue of vibration isolation in linear compressors has long been a research challenge within the industry. Addressing this challenge, this paper provides an overview of vibration isolation optimization methods for linear compressors. It delves into the discussion of different vibration sources in linear compressors and their respective measurement techniques. By integrating both single degree of freedom (SDOF) and multiple degree of freedom (MDOF) vibration isolation models, this paper describes both active and passive vibration isolation methods tailored to linear compressors. Furthermore, a feasible optimization approach is proposed. Finally, the paper offers insights into the developmental potential and feasibility of vibration energy recovery strategies.
Affordable and Reliable RP-HPLC Method for Verapamil Hydrochloride Quantification in Rabbit Plasma for Pharmacokinetics
Authors: Navamanisubramanian Raja , Seetharaman Shanmuganathan , Sugumaran Abimanyu , Alsheikh Mona Y. , Naguib Ibrahim A. , Gamal Mohammed
Published: October 2024

Background: Existing bioanalytical methods for verapamil hydrochloride (VH) are often complex, requiring advanced instrumentation and specialized expertise, which limits their use in resource-constrained laboratories. Aim: The goal of this study is to fill this gap by developing a simplified, robust RP-HPLC-UV approach for the estimation of verapamil hydrochloride in rabbit plasma. Designed to enhance accuracy and precision while minimizing sample preparation challenges, this method addresses existing limitations by providing an affordable and reliable alternative for laboratories lacking sophisticated instrumentation. Methods: The bioanalytical method was implemented on C-18 stationary phase (5 μ, 250 × 4.6 mm) using acetonitrile/0.1% tetrahydrofuran (THF) in water (80:20, in volume) as the liquid system at a 1 mL/min flow speed, employing carvedilol as an internal standard. Results: The reported retention times of verapamil hydrochloride and carvedilol were ~7.64 and 4.69 min, respectively, at sufficiently high system suitability standards. The linearity of the bioanalytical approach can be seen between 0.025 and 5.0 µg/mL (r2 = 0.9991). The findings indicated that there was no matrix influence in terms of accuracy (≥98.96 ± 2.68%), intra- and inter-day precision (≤3.68%), recovery (101.98 ± 2.76%), and procedure efficiency (100.65 ± 1.82%). Benchtop, long-term, and short-term stability investigations all revealed that the verapamil hydrochloride in the bio-samples was stable. The pharmacokinetic parameters (Cmax—3.47 µg/mL; Tmax—1.59 h) were studied from time-dependent plasma concentrations of verapamil hydrochloride estimated after 40 mg oral dosing in New Zealand white rabbits. Conclusions: The developed bioanalytical method provided easier quantitative analysis of verapamil hydrochloride from rabbit plasma and was effectively used in a pharmacokinetic investigation of an oral bolus. The reliable performance of this method under practical conditions positions it as a crucial tool for advancing pharmacokinetic studies across various research environments.
Latent Profiles of Seminary Students’ Perceptions of Sense of Community Amidst the COVID-19 Pandemic
Authors: Jankowski Peter J. , Sandage Steven J. , Wang David C.
Published: October 2024

Existing research on sense of community in educational contexts shows positive associations with well-being and negative associations with mental health symptoms. However, exploration of students’ sense of community within the seminary context is minimal. Drawing on the relational spirituality model, which posits oscillating experiences of dwelling and seeking in a dialectical growth process, we framed sense of community as horizontal dwelling. We used mixture modeling to generate subgroups using items from a measure of sense of community and then explored associations between sense of community and various demographic predictors and personal formation outcomes, including well-being and symptoms, along with virtues and religiousness/spirituality. We did so within the unique context of the COVID-19 pandemic. We used a sample of graduate students from 18 Christian seminaries across North America (N = 867; Mage = 31.95; 48.1% female; 60% White). Factor mixture results supported a 3-class solution, with one class reporting consistently greater ratings of sense of community, labeled the strongly connected, another class reporting consistent mid-level ratings, labeled the moderately connected, and a third class reporting consistently lower ratings, and labeled the disaffected. Results for the disaffected showed a pattern of associations with lower well-being and greater symptoms, and lower religiousness/spirituality, along with greater pandemic stress. The strongly connected showed greater levels of virtuousness, well-being and religiousness/spirituality, and lower symptoms, although they were also more likely to report greater illusory health. The pattern of associations for the moderately connected was a blend of similarities with the other two subgroups. The disaffected also showed a modest risk effect for lower well-being and greater symptoms over time. Findings pointed to providing greater horizontal dwelling among the disaffected and the need for greater seeking among the strongly connected.
Exploring Miracles and Wonders in Pre-Modern Korean Society through the Samguk yusa
Authors: Yun Sung Ha
Published: October 2024

Samguk yusa 三國遺事 (Memorabilia of the Three Kingdoms), compiled by Iryŏn 一然 (1206–1289), a prominent Buddhist monk in Koryŏ, stands as one of Korea’s most valued historical classics. This classic weaves together a collection of captivating and unconventional narratives—marked by their peculiarity, miracles, and wonder—diverging from the usual societal norms. Unlike traditional historical chronicles such as Samguk sagi 三國史記 (Histories of the Three Kingdoms), Samguk yusa presents a diverse mosaic woven with historical anecdotes, legends, and folklore, especially emphasizing connections to Buddhism. The tales of miraculous events hold historical significance, serving as reflective mirrors that not only shaped the beliefs of pre-modern Korean Buddhists but also influenced the wider population of that era in Korea. This paper delves into the cultural significance and societal roles of miracles and wonders within pre-modern Korean society, particularly through a thorough exploration of narratives and accounts within the Samguk yusa. Through these miraculous stories, the Samguk yusa not only validates the spiritual power of Buddhism but also redefines concepts like filial piety and national protection by integrating them into the Buddhist framework. This ensured Buddhism’s enduring significance in Silla society and reinforced the importance of the supernatural as an integral part of a holistic view of history and culture.
Diaphragmatic Palsy Due to a Paraneoplastic Autoimmune Syndrome Revealed by Checkpoint Inhibitors
Authors: Destival Jean-Baptiste , Michot Jean-Marie , Cauquil Cécile , Noël Nicolas , Hacein-Bey-Abina Salima , Chrétien Pascale , Lambotte Olivier
Published: October 2024

Background and Clinical Significance: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment but may underlie diverse and potentially life-threatening immune-related adverse events (irAEs). They may cause various conditions leading to respiratory failure, including myasthenic syndromes and myositis. However, diaphragmatic paralysis (DP) has rarely been reported. To describe patients with diaphragmatic paralysis in a pharmacovigilance registry, we searched the prospective REISAMIC registry at the Gustave Roussy Cancer Center (Villejuif, France) for cases of diaphragmatic palsy (DP) occurring from September 2014 to December 2021. Case Presentation: We identified three patients, in whom DP was confirmed by diaphragmatic ultrasonography, pulmonary function tests, and/or diaphragmatic electroneuromyogram. Diaphragmatic palsy was life-threatening in all patients, as it caused respiratory failure requiring mechanical ventilation. In all cases, a pre-existing subclinical paraneoplastic syndrome was detected. Onconeural antibodies (anti-titin and anti-VGCC) were detected in these patients before and after the initiation of ICI therapy, suggesting a mixed paraneoplastic syndrome with features overlapping those of myasthenic syndrome (myasthenia gravis in one patient and Lambert–Eaton syndrome in another) and myositis. Conclusions: Diaphragmatic palsy is a severe irAE potentially resulting from different mechanisms, including myositis and neuromuscular junction involvement (myasthenia gravis, Lambert–Eaton). Antineuronal antibodies associated with such conditions were already present in our patients prior to immunotherapy initiation, suggesting ICIs could trigger flare-ups of pre-existing silent paraneoplastic autoimmune conditions.
Behavioral Biases in Panic Selling: Exploring the Role of Framing during the COVID-19 Market Crisis
Authors: Kuramoto Yu , Khan Mostafa Saidur Rahim , Kadoya Yoshihiko
Published: October 2024

Panic selling causes long-term losses and hinders investors’ return to the market. It has been explained using prospect theory aspects such as loss and regret aversion. Additionally, overconfidence and overreaction contribute to the disposition effect, leading investors to sell stocks prematurely. However, the framing effect, another disposition effect attribute, has been underexplored in the context of panic selling. This study investigates how the framing effect influences panic selling, particularly during market crises, when investors perceive information differently, depending on its positive or negative framing. Utilizing data from a collaborative survey, we examine Japanese investors’ behavior during the COVID-19 market crisis. Negative framing is negatively associated with complete or partial sale of securities, whereas positive framing has the opposite effect. During market crises, investors presented with negative framing are less likely to panic sell, whereas those presented with positive framing are more prone to it. Other significant factors include gender; men tend to engage more in panic selling. Conversely, higher education, financial literacy, and greater household income and assets are associated with a reduced likelihood of panic selling. These findings underscore the critical role of framing in investor behavior during market crises, providing new insights into the mechanisms underlying panic selling.
The Standardized Spectroscopic Mixture Model
Authors: Small Christopher , Sousa Daniel
Published: October 2024

The standardized spectral mixture model combines the specificity of a physically based representation of a spectrally mixed pixel with the generality and portability of a spectral index. Earlier studies have used spectrally and geographically diverse collections of broadband and spectroscopic imagery to show that the reflectance of the majority of ice-free landscapes on Earth can be represented as linear mixtures of rock and soil substrates (S), photosynthetic vegetation (V) and dark targets (D) composed of shadow and spectrally absorptive/transmissive materials. However, both broadband and spectroscopic studies of the topology of spectral mixing spaces raise questions about the completeness and generality of the Substrate, Vegetation, Dark (SVD) model for imaging spectrometer data. This study uses a spectrally diverse collection of 40 granules from the EMIT imaging spectrometer to verify the generality and stability of the spectroscopic SVD model and characterize the SVD topology and plane of substrates to assess linearity of spectral mixing. New endmembers for soil and non-photosynthetic vegetation (NPV; N) allow the planar SVD model to be extended to a tetrahedral SVDN model to better accommodate the 3D topology of the mixing space. The SVDN model achieves smaller misfit than the SVD, but does so at the expense of implausible fractions beyond [0, 1]. However, a refined spectroscopic SVD model still achieves small (<0.03) RMS misfit, negligible sensitivity to endmember variability and strongly linear scaling over more than an order of magnitude range of spatial resolution.
Study on Static Biomechanical Model of Whole Body Based on Virtual Human
Authors: Cheng Zheng , Luo Bin , Chen Chuan , Guo Huajun , Wu Jiaju , Chen Dongyi
Published: October 2024

Material handling tasks often lead to skeletal injury of workers. The whole-body static biomechanical modeling method based on virtual humans is the theoretical basis for analyzing the human factor index in the lifting process. This paper focuses on the study of humans’ body static biomechanical model for virtual human ergonomics analysis: First, the whole-body static biomechanical model is constructed, which calculates the biomechanical data such as force and moment, average strength, and maximum hand load at human joints. Secondly, the prototype model test system is developed, and the real experiment environment is set up with the inertial motion capture system. Finally, the model reliability verification experiment and application simulation experiment are designed. The comparison results with the industrial ergonomic software show that the model is consistent with the output of the industrial ergonomic software, which proves the reliability of the model. The simulation results show that under the same load, the maximum joint load and the maximum hand load are strongly related to the working posture, and the working posture should be adjusted to adapt to the load. Upright or bent legs have less influence on the maximum load capacity of the hand. Lower hand load capacity is due to forearm extension, and the upper arm extension greatly reduces the load capacity of the hand. Compared with a one-handed load, the two-handed load has a greater load capacity.
Efficient Optimized YOLOv8 Model with Extended Vision
Authors: Zhou Qi , Wang Zhou , Zhong Yiwen , Zhong Fenglin , Wang Lijin
Published: October 2024

In the field of object detection, enhancing algorithm performance in complex scenarios represents a fundamental technological challenge. To address this issue, this paper presents an efficient optimized YOLOv8 model with extended vision (YOLO-EV), which optimizes the performance of the YOLOv8 model through a series of innovative improvement measures and strategies. First, we propose a multi-branch group-enhanced fusion attention (MGEFA) module and integrate it into YOLO-EV, which significantly boosts the model’s feature extraction capabilities. Second, we enhance the existing spatial pyramid pooling fast (SPPF) layer by integrating large scale kernel attention (LSKA), improving the model’s efficiency in processing spatial information. Additionally, we replace the traditional IOU loss function with the Wise-IOU loss function, thereby enhancing localization accuracy across various target sizes. We also introduce a P6 layer to augment the model’s detection capabilities for multi-scale targets. Through network structure optimization, we achieve higher computational efficiency, ensuring that YOLO-EV consumes fewer computational resources than YOLOv8s. In the validation section, preliminary tests on the VOC12 dataset demonstrate YOLO-EV’s effectiveness in standard object detection tasks. Moreover, YOLO-EV has been applied to the CottonWeedDet12 and CropWeed datasets, which are characterized by complex scenes, diverse weed morphologies, significant occlusions, and numerous small targets. Experimental results indicate that YOLO-EV exhibits superior detection accuracy in these complex agricultural environments compared to the original YOLOv8s and other state-of-the-art models, effectively identifying and locating various types of weeds, thus demonstrating its significant practical application potential.
A Novel Ultrasonic Leak Detection System in Nuclear Power Plants Using Rigid Guide Tubes with FCOG and SNR
Authors: Choi You-Rak , Yeo Doyeob , Lee Jae-Cheol , Cho Jai-Wan , Moon Sangook
Published: October 2024

Leak detection in nuclear reactor coolant systems is crucial for maintaining the safety and operational integrity of nuclear power plants. Traditional leak detection methods, such as acoustic emission sensors and spectroscopy, face challenges in sensitivity, response time, and accurate leak localization, particularly in complex piping systems. In this study, we propose a novel leak detection approach that incorporates a rigid guide tube into the insulation layer surrounding reactor coolant pipes and combines this with an advanced detection criterion based on Frequency Center of Gravity shifts and Signal-to-Noise Ratio analysis. This dual-method strategy significantly improves the sensitivity and accuracy of leak detection by providing a stable transmission path for ultrasonic signals and enabling robust signal analysis. The rigid guide tube-based system, along with the integrated criteria, addresses several limitations of existing technologies, including the detection of minor leaks and the complexity of installation and maintenance. By enhancing the early detection of leaks and enabling precise localization, this approach contributes to increased reactor safety, reduced downtime, and lower operational costs. Experimental evaluations demonstrate the system’s effectiveness, focusing on its potential as a valuable addition to the current array of nuclear power plant maintenance technologies. Future research will focus on optimizing key parameters, such as the threshold frequency shift (Δf) and the number of randomly selected frequencies (N), using machine learning techniques to further enhance the system’s accuracy and reliability in various reactor environments.
Correction: Palacín et al. Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant. Sensors 2021, 21, 7216
Authors: Palacín Jordi , Rubies Elena , Clotet Eduard , Martínez David
Published: October 2024

After publication of the research paper [...]
An Acoustic Sensor System to Measure Aeolian Ripple Morphology and Migration Rates
Authors: Zhang Pei , Bae Jinsu , Parteli Eric J. R. , Sherman Diane , Sherman Douglas J.
Published: October 2024

Acoustic distance sensors have a long history of use to detect subaqueous bedforms. There have been few comparable applications for aeolian bedforms such as ripples. To address this, we developed a simple and reliable apparatus comprising a pair of distance sensors, a bracket upon which they are mounted, and a base upon which the bracket can slide. Our system relies on two Senix Corporation (Hinesburg, VT, USA), ToughSonic® model 14-TSPC-30S1-232 acoustic distance sensors: one to measure surface elevation changes (in this case, ripple morphology) and a second to measure horizontal location. The ToughSonic® vertical resolution was 0.22 mm and the horizontal scan distance was about 0.60 m with a locational accuracy of 0.22 mm. The measurement rate was 20 Hz, but we over-sampled at 1 KHz. Signal processing involves converting volts to meters, detrending the data, and removing noise. Analysis produces ripple morphologies and migration rates that conform with independent measurements. The advantages of this system relative to terrestrial laser scanning or structure from motion are described.
A Monitoring Device and Grade Prediction System for Grain Mildew
Authors: Xu Lei , Li Yane , Weng Xiang , Shi Jiankai , Feng Hailin , Liu Xingquan , Zhou Guoxin
Published: October 2024

Mildew infestation is a significant cause of loss during grain storage. The growth and metabolism of mildew leads to changes in gas composition and temperature within granaries. Recent advances in sensor technology and machine learning enable the prediction of grain mildew during storage. Current research primarily focuses on predicting mildew occurrence or grading using simple machine learning methods, without in-depth exploration of the time series characteristics of mildew process data. A monitoring device was designed and developed to capture high-quality microenvironment parameters and image data during a simulated mildew process experiment. Using the “Yongyou 15” rice varieties from Zhejiang Province, five simulation experiments were conducted under varying temperature and humidity conditions between January and May 2023. Mildew grades were defined through manual analysis to construct a multimodal dataset for the rice mildew process. This study proposes a combined model (CNN–LSTM–A) that integrates convolutional neural networks (CNN), long short-term memory (LSTM) networks, and attention mechanisms to predict the mildew grade of stored rice. The proposed model was compared with LSTM, CNN–LSTM, and LSTM–Attention models. The results indicate that the proposed model outperforms the others, achieving a prediction accuracy of 98%. The model demonstrates superior accuracy and more stable performance. The generalization performance of the prediction model was evaluated using four experimental datasets with varying storage temperature and humidity conditions. The results show that the model achieves optimal prediction stability when the training set contains similar storage temperatures, with prediction accuracy exceeding 99.8%. This indicates that the model can effectively predict the mildew grades in rice under varying environmental conditions, demonstrating significant potential for grain mildew prediction and early warning systems.
Analysis of Ecological Environment in the Shanxi Section of the Yellow River Basin and Coal Mining Area Based on Improved Remote Sensing Ecological Index
Authors: Chai Huabin , Zhao Yuqiao , Xu Hui , Xu Mingtao , Li Wanyin , Chen Lulu , Wang Zhan
Published: October 2024

As a major coal-producing area, the Shanxi section of the Yellow River Basin has been significantly affected by coal mining activities in the local ecological environment. Therefore, an in-depth study of the ecological evolution in this region holds great scientific significance and practical value. In this study, the Shanxi section of the Yellow River Basin, including its planned coal mining area, was selected as the research subject. An improved remotely sensed ecological index model (NRSEI) integrating the remotely sensed ecological index (RSEI) and net primary productivity (NPP) of vegetation was constructed utilizing the Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, and the Sen + Mann–Kendall analysis method was employed to comprehensively assess the ecological environment quality and its evolutionary trends in the study area. The findings in this paper indicate the following data: (1) The contribution of the first principal component of the NRSEI model is more than 70%, and the average correlation coefficient is higher than 0.79. The model effectively integrates the information of multiple ecological indicators and enhances the applicability of regional ecological environment evaluation. (2) Between 2003 and 2022, the ecological environment quality in the Shanxi section of the Yellow River Basin showed an overall upward trend, with the average NRSEI value experiencing phases of fluctuation, increase, decline, and stabilization. The NRSEI values in non-coal mining areas consistently remained higher than those in coal mining areas. (3) Over 60% of the areas have improved ecological conditions, especially in coal mining areas. (4) The impact of coal mining on the ecological environment is significant within a 6 km radius, while the effects gradually diminish in the 6 to 10 km range. This study not only offers a reliable methodology for evaluating ecological environment quality on a large scale and over a long time series but also holds significant guiding value for the ecological restoration and sustainable development of the Shanxi section of the Yellow River Basin and its coal mining area.
Seed Priming Technology: Current Perspectives
Authors: Hernández José Antonio , Barba-Espín Gregorio , Díaz-Vivancos Pedro
Published: October 2024

Seeds are vital components in the life cycle of plants, as they are responsible for the propagation of new plant generations [...]
Emerging and Conventional Water Desalination Technologies Powered by Renewable Energy and Energy Storage Systems toward Zero Liquid Discharge
Authors: Elewa Mahmoud M.
Published: October 2024

The depletion of fossil fuels has become a significant global issue, prompting scientists to explore and refine methods for harnessing alternative energy sources. This study provides a comprehensive review of advancements and emerging technologies in the desalination industry, focusing on technological improvements and economic considerations. The analysis highlights the potential synergies of integrating multiple renewable energy systems to enhance desalination efficiency and minimise environmental consequences. The main areas of focus include aligning developing technologies like membrane distillation, pervaporation and forward osmosis with renewable energy and implementing hybrid renewable energy systems to improve the scalability and economic viability of desalination enterprises. The study also analyses obstacles related to desalination driven by renewable energy, including energy storage, fluctuations in energy supply, and deployment costs. By resolving these obstacles and investigating novel methodologies, the study enhances the understanding of how renewable energy can be used to construct more efficient, sustainable, and economical desalination systems. Thermal desalination technologies require more energy than membrane-based systems due to the significant energy requirements associated with water vaporisation. The photovoltaic-powered reverse osmosis (RO) system had the most economically favourable production cost, while MED powered via a concentrated solar power (CSP) system had the highest production cost. The study aims to guide future research and development efforts, ultimately promoting the worldwide use of renewable energy-powered desalination systems.
On the Periphery of the European Social Sciences—A Scientometric Analysis of Publication Performance, Excellence, and Internal Bias in Social Sciences in the Visegrad Countries
Authors: Sasvári Péter , Lendvai Gergely Ferenc
Published: October 2024

This study examines the publication performance of the Czech Republic, Poland, Hungary, and Slovakia across 24 social science disciplines indexed by Scopus from 2019 to 2023. Using data from Scopus, SciVal, and Scimago, we analyzed regional journal statuses, disciplinary backlogs, journal biases, and publication excellence. Our results show that Poland and the Czech Republic lead in journal and publication counts, whereas Hungary and Slovakia lag behind significantly. Four disciplines—e-learning, human factors and ergonomics, life-span and life-course studies, and social work—had minimal or no publications, highlighting their marginalization. We found a high internal bias in publication practices, notably in Poland and Hungary, which raises concerns considering the Norwegian list standards. While Poland and the Czech Republic show a higher proportion of excellent publications, the overall number of high-quality articles remains low, and publications by the Big Five publishers are exceedingly limited. This analysis underscores the need for strategic policy interventions to enhance research quality and international collaboration to improve the scientific standing of the Visegrad countries.
In Vivo Validation of a Computer-Assisted Bowel Length Measurement System
Authors: Mayer Benjamin F. B. , Bodenstedt Sebastian , Mietkowski Patrick , Rempel Rudolf , Schulte Lena M. , Speidel Stefanie , Kenngott Hannes G. , Kowalewski Karl F.
Published: October 2024

(1) Background: The aim of this study was to investigate potential translational factors for optical 3D reconstruction in an in vivo setting using a newly developed computerized bowel length measurement system (BMS) as a real-time application. (2) Methods: The BMS was evaluated in an in vivo porcine experiment for the influence of light source power (Watt), laparoscope-to-bowel distance (cm), bowel rotation, image background, and surgical objects in the image. Endpoints were robustness, calculated as success rate (SR) in percent, and accuracy, defined as relative error (RE) in percent of BMS measurement result to ground truth. (3) Results: A total of 1992 bowel measurements were performed on n = 7 pigs using the BMS. Bowel measurements were robust and accurate regardless of light source power, at a laparoscope-to-bowel distance of 5 cm (SR 100%, RE 18 ± 38.5%), when the small bowel was aligned horizontally (SR 100%, RE 7.3 ± 36.2%) or in the image background (SR 100%, RE 15.2 ± 23.4%), and when no additional instruments were in the image. (4) Conclusions: Applications based on optical 3D reconstruction are feasible for intraoperative use and could enable quantitative laparoscopy.
Vegetation Growth and Physiological Adaptation of Pioneer Plants on Mobile Sand Dunes
Authors: Cao Yingfei , Xu Hong , Li Yonggeng , Su Hua
Published: October 2024

The Hunshandake Sandy Land is one of the largest sandy areas in China and the closest source of sand dust to the Beijing and Tianjing areas. Sand fixation by vegetation is considered the most efficient strategy for sand control and sustainable development, so clarifying the vegetation coverage and plant adaptation characteristics in the Hunshandake Sandy Land is helpful in guiding restoration and improving local sustainability. Here, we investigated the vegetation growth on the mobile sand dunes in the Hunshandake Sandy Land and specified the photosynthesis and stomatal characteristics of the pioneer plants for sand fixation. The vegetation survey showed that the windward slopes of the mobile sand dunes had far lower plant coverage (6.3%) and plant biodiversity (two species m−2) than the leeward ones (41.0% and eight species m−2, respectively). Elymus sibiricus L. and Agriophyllum squarrosum (L.) Moq. were the only two sand-fixing pioneer plants that grew on both the windward and leeward slopes of the mobile sand dunes and had higher plant heights, greater abundance, and more biomass than other plants. Physiological measurements revealed that Elymus sibiricus L. and Agriophyllum squarrosum (L.) Moq. also had higher photosynthetic rates, transpiration rates, and water use efficiency. In addition, the stomata density (151–197 number mm−2), length (18–29 μm), and area index (13–19%) of these two pioneer species were smaller than those of the common grassland species in Inner Mongolia, suggesting that they were better adapted to the dry habitat of the mobile sand dunes. These findings not only help in understanding the adaptive strategies of pioneer plants on mobile sand dunes, but also provide practical guidance for sand dune restoration and the sustainable development of local areas. Pioneer sand-fixing plant species that are well adapted to sand dunes can be used for sowing or aerial seeding in sand fixation during ecosystem restoration.
Assessment of Wind Energy Potential and Optimal Site Selection for Wind Energy Plant Installations in Igdir/Turkey
Authors: Şahin Gökhan , Koç Ahmet , Doğan Sülem Şenyiğit , van Sark Wilfried
Published: October 2024

Wind energy is an eco-friendly, renewable, domestic, and infinite resource. These factors render the construction of wind turbines appealing to nations, prompting numerous governments to implement incentives to augment their installed capacity of wind turbines. Alongside augmenting the installed capacity of wind turbines, identifying suitable locations for their installation is crucial for optimizing turbine performance. This study aims to evaluate potential sites for wind power plant installation via a GIS, a mapping technique. The Analytic Hierarchy Process (AHP) was employed to assess the locations, including both quantitative and qualitative aspects that significantly impact the wind farm suitability map. Utilizing the GIS methodology, all datasets were examined through height and raster transformations of land surface temperature, plant density index, air pressure, humidity, wind speed, air temperature, land cover, solar radiation, aspect, slope, and topographical characteristics, resulting in the creation of a wind farm map. The correlation between the five-year meteorological data and environmental parameters (wind direction, daily wind speed, daily maximum and minimum air temperatures, daily relative humidity, daily average air temperature, solar radiation duration, daily cloud cover, air humidity, and air pressure) influencing the wind power plant in Iğdır province, including Iğdır Airport, Karakoyunlu, Aralık, and Tuzluca districts, was analyzed. If wind energy towers are installed at 1 km intervals across an area of roughly 858,180 hectares in Igdir province, an estimated 858,180 GWh of wind energy can be generated. The GIS-derived wind power plant map indicates that the installation sites for wind power plants are located in regions susceptible to wind erosion.
The State of the Art on Phase Change Material-Modified Asphalt Pavement
Authors: Guo Meng , Cheng Xiaojun , Wei Sishuang , Xiu Hanbo , Song Shanglin
Published: October 2024

During the construction and maintenance of asphalt pavement, a lot of non-renewable resources are consumed, which discharge a variety of waste gasses and smoke, causing a serious impact on the environment. Reducing society’s reliance on non-renewable resources is therefore key to improving sustainability. It is found that phase change materials (PCMs), as environmentally friendly materials, can spontaneously store and release heat energy by changing the phase state, thus reducing the adverse effect of temperature on asphalt pavement, reducing the occurrence of high-temperature stress, minimizing the cost of road construction and maintenance, and saving resources. In order to promote the application of PCMs in asphalt pavement, to promote self-controlling temperature technology for asphalt pavement, and to improve the sustainable development of asphalt pavement, this paper reviews the research status of PCMs in asphalt pavement, both domestically and abroad. The results show that the thermal conductivity of the modified asphalt binder can reach 0.29–0.39 W/mK, and the thermal diffusivity can reach 0.2–0.3 mm2/s, but the influence on the viscosity of the asphalt is limited, and both are less than 2000CP. The durability and thermal stability of the modified asphalt mixture are improved, and the maximum temperature can be lowered by 9 °C, which effectively reduces the occurrence of hightemperature stress. This review will help to better understand the function of PCMs and promote the sustainable development of green and environmentally friendly asphalt pavement.