bluuebunny/crossref_metadata_2025 huggingface dataset:
Linking Acrosome Size and Genetic Divergence in an Inter-Oceanic Mussel from the Pacific and Atlantic Coasts: A Case of Incipient Speciation?
Authors: Briones Carolina , Nuñez José J. , Pérez Montse , Garrido Orlando , Campos Bernardita , Godoy Karina , Hartley Ricardo , Oyarzún Pablo A. , Guiñez Ricardo
Published: February 2024

In recent years, advances in analyses of the sperm morphology and genetics of Perumytilus purpuratus have allowed to two evolutionary scenarios for this mussel to be suggested: (1) the scenario of cryptic species and (2) the scenario of incipient or in progress speciation. For a better understanding of the evolutionary history of P. purpuratus, we performed extensive sampling along a latitudinal gradient of ca. 7180 km of coastline—from the Southern Pacific Ocean to the Atlantic Ocean—and we delved deeper into the sperm morphology of P. purpuratus, exploring its association with the phylogeny and population genetics to determine whether the variability in sperm traits between the northern and southern regions was a signal of cryptic or incipient species. Overall, our results showed that sperm sizes were strongly correlated with the genetic structure in males of P. purpuratus. We identified at 37° S on the Pacific coast a coincident break of both sperm size and genetic disruption that can be explained by historical events and postglacial recolonization as causal phenomena for the observed divergences. Furthermore, evidence of genetic admixture between lineages was found at 38° S, suggesting the presence of an introgressive hybridization zone and incomplete reproductive isolation in an in fraganti or incipient speciation process.
An In-Depth Look at Fonni’s Dog Behavior under Different Outdoor Conditions
Authors: Cocco Raffaella , Sechi Sara , Giannetto Claudia , Rizzo Maria , Piccione Giuseppe , Arfuso Francesca
Published: February 2024

This study aimed to investigate the common social and communicative behaviors of the Fonni’s Dog under different outdoor conditions. For this study, 70 adult dogs (3–7 years; 32 intact males, 38 intact females) belonging to the Fonni’s breed were used. A total of 35 dogs were kept in kennels and 35 were free-ranging dogs in their sheep/goat livestock units. A behavioral repertoire was adapted from the literature and an ethogram was filled in for each dog. All dogs were evaluated in the presence of the owner. Fisher’s exact test, following Bonferroni’s correction, was used to test possible differences in the categorical variables (presence or absence of the behavior) between free-ranging dogs and dogs kept in kennels. The study revealed that several categories of the dogs’ body language were associated with the management condition. However, the breed motivations (guarding and defense of the territory) were satisfied both in kennel and in the animals who were free in the property. The current study suggests a good behavioral balance of the Fonni’s Dogs which could be attributed to correct communication between dogs and owners.
Comparative Assessment of the Antibacterial and Antibiofilm Actions of Benzalkonium Chloride, Erythromycin, and L(+)-Lactic Acid against Raw Chicken Meat Campylobacter spp. Isolates
Authors: Kostoglou Dimitra , Vass Athina , Giaouris Efstathios
Published: February 2024

Campylobacter spp. are significant zoonotic agents, which cause annually millions of human cases of foodborne gastroenteritis worldwide. Their inclusion in biofilms on abiotic surfaces seems to play a pivotal role in their survival outside of the host, growth, and spread. To successfully mitigate the risks that arise with these bacteria, it is crucial to decrease their prevalence within the food production chain (from farm to the table), alongside the successful treatment of the resulting illness, known as campylobacteriosis. For this, the use of various antimicrobial agents remains actively in the foreground. A general-purpose biocide and cationic surfactant (benzalkonium chloride; BAC), a widely used macrolide antibiotic (erythromycin; ERY), and a naturally occurring organic acid (L(+)-lactic acid; LA) were comparatively evaluated in this work for their potential to inhibit both the planktonic and biofilm growth of 12 selected Campylobacter spp. (of which, seven were C. jejuni and five were C. coli) raw chicken meat isolates, all grown in vitro as monocultures. The inhibitory action of LA was also studied against four mixed-culture Campylobacter biofilms (each composed of three different isolates). The results showed that the individual effectiveness of the agents varied significantly depending on the isolate, growth mode (planktonic, biofilm), intercellular interactions (monocultures, mixed cultures), and the growth medium used (with special focus on blood presence). Thus, BAC exhibited minimum inhibitory concentrations (MICs), minimum bactericidal concentrations (MBCs), and minimum biofilm inhibitory concentrations (MBICs) that ranged from 0.5 to 16 μg/mL. Interestingly enough, these values varied widely from 0.25 to 1024 μg/mL for ERY. Concerning LA, the MICs, MBCs, and MBICs varied from 1024 to 4096 μg/mL, with mixed-culture biofilm formation always being more difficult to suppress when compared to biofilm monocultures. In addition, it was evident that intercellular interactions encountered within mixed-culture Campylobacter biofilms significantly influenced both the population dynamics and the tolerance of each consortium member to acid exposure. Overall, the findings of this study provide useful information on the comparative effectiveness of three well-known antimicrobial agents for the control of Campylobacter spp. under various growth modes (i.e., planktonic, biofilm, monocultures, mixed cultures) that could potentially be encountered in food production and clinical settings.
Comparative Evaluation of the Microleakage of Glass Ionomers as Restorative Materials: A Systematic Review of In Vitro Studies
Authors: Alsari Abtihal , Ghilotti James , Sanz José Luis , Llena Carmen , Folguera Sofía , Melo María
Published: February 2024

This study aimed to perform a qualitative synthesis of the available in vitro evidence on the microleakage of commercially available conventional glass ionomer cements (GICs), resin-modified glass ionomer cements (RMGICs), and modified glass ionomer cements with nano-fillers, zirconia, or bioactive glasses. A systematic review was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Review and Meta-Analysis) statement standards. The literature search was performed in Medline (via PubMed), Embase, Web of Science, and Scopus to identify relevant articles. Laboratory studies that evaluated microleakage of GICs, RMGICs, and modified glass ionomer cements with nano-fillers, zirconia, or bioactive glasses were eligible for inclusion. The QUIN risk of bias tool for the assessment of in vitro studies conducted in dentistry was used. After the study selection process, which included duplicate removal, title and abstract screening, and full-text assessment, 15 studies were included. A qualitative synthesis of the evidence is presented, including author data, year of publication, glass ionomer materials used, sample characteristics, microleakage technique and values, and main outcome measures for primary and permanent teeth. Although no statistically significant differences were found in numerous studies, most results showed that RMGICs exhibited less leakage than conventional GICs. All studies agreed that leakage was significantly higher at dentin margins. It was also higher at the gingival margin than at the occlusal margin. Nano-filled RMGICs Ketac N100, Equia Forte, and Zirconomer appear to have less microleakage than conventional GICs and RMGICs. Further investigations using a standardized procedure are needed to confirm the results.
Effect of a Crystalline Admixture on the Permeability Properties of Concrete and the Resistance to Corrosion of Embedded Steel
Authors: Antón Carlos , Gurdián Hebé , de Vera Guillem , Climent Miguel-Ángel
Published: February 2024

Reinforced concrete structure durability hinges on concrete permeability, which relies on the characteristics of the inner porous network. Harmful ions and gases can accelerate steel corrosion. Permeability-reducing admixtures (PRA), including crystalline admixtures (CA), are commonly used to mitigate this. This study examines a commercial CA’s impact on durability-related aspects in concrete specimens. Two concrete mixtures with matching proportions were prepared: a reference mix and another mix with a commercial crystalline admixture. Several properties were studied, such as compressive strength, density, porosity, electrical resistivity, water absorption capacity, chloride diffusion, air permeability, and corrosion resistance. The studied admixture in concrete yields several positive outcomes such as a slight reduction in mixing water, a potential 6% increase in concrete’s compressive strength and the development of a denser and less permeable structure with 3% lower porosity and water absorption than the reference mix. Electrical resistivity improves by 10%. Unidirectional chloride diffusion tests show no differences. Air permeability decreases by from 36% to 55%, and the water absorption rate diminishes by 23%. The admixture potentially reduces the scatter in corrosion initiation periods for steel reinforcements, delaying corrosion onset by around 60 days, although more extensive experiments are needed for definitive conclusions.
Protective Effects on Neuronal SH-SY5Y Cells and Antioxidant Activity of Enzymatic Hydrolyzate from Silkworms Fed the Leaves of Cudrania tricuspidata
Authors: An Gyu-Mi , Jung Tae-Hwan , Han Kyoung-Sik
Published: February 2024

We investigated the antioxidant activity and neuroprotective effects of an enzymatic hydrolyzate from silkworms fed the leaves of Cudrania tricuspidata (ESLC) produced by enzymatic treatment. The proteins in silkworms fed the leaves of Cudrania tricuspidata (SLC) were effectively hydrolyzed using enzymatic treatment. The total polyphenols of ESLC were significantly higher, and the superoxide dismutase-like activity and 2,2′-azino-bis (3-thylbenzothiazoline-6-sulfonicacid) diammonium salt radical scavenging capacity of ESLC were significantly increased compared to the SLC group. We evaluated the properties of ESLC to protect SH-SY5Y cells from H2O2-induced oxidative stress. The viability rate of SH-SY5Y neuroblastoma cells was significantly restored when treated with ESLC at a concentration of 100 μg/mL or 250 μg/mL. Furthermore, the mitogen-activated protein kinase (MAPK) pathway was investigated, and ESLC significantly inhibited the phosphorylation of c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), and p38. Therefore, ESLC can potentially be used as an antioxidant. The polyphenol content increases owing to hydrolysis through enzymatic treatment, which increases the antioxidant effect and inhibits the phosphorylation of JNK, ERK, and p38 by activating the MAPK pathway, which inhibits cell death from oxidative stress and exerts cytoprotective effects.
Optimizing Logistics and Transportation Locations in the China–Pakistan Economic Corridor: A Strategic Risk Assessment
Authors: Ilyas Muhammad , Jin Zhihong , Ullah Irfan
Published: February 2024

Logistics centers (LCs) have become a critical component of supply chain networks, playing an essential role in the development and implementation of logistics and supply chain management strategies. Recognizing the importance of LCs, Pakistan and China have initiated an extensive plan to establish and expand an LC system as part of the China–Pakistan Economic Corridor (CPEC) initiative. However, the implementation of this plan has faced challenges due to the inadequate prioritization of factors used to identify LCs. This research proposes a structured framework for selecting LC locations, employing a combination of fuzzy logic and the technique for order of preference by similarity to the ideal solution (TOPSIS). These widely used methods address various challenges encountered in location selection. The findings highlight crucial logistics hubs in China and Pakistan, emphasizing factors such as port accessibility, freight demand, and transportation costs. The prioritization of criteria for LC selection is determined through the evaluation of variables and alternatives. The proposed framework enhances decision-making based on multiple criteria by addressing uncertainty and subjective assessments.
Boosting Noise Reduction Effect via Unsupervised Fine-Tuning Strategy
Authors: Jiang Xinyi , Xu Shaoping , Wu Junyun , Zhou Changfei , Ji Shuichen
Published: February 2024

Over the last decade, supervised denoising models, trained on extensive datasets, have exhibited remarkable performance in image denoising, owing to their superior denoising effects. However, these models exhibit limited flexibility and manifest varying degrees of degradation in noise reduction capability when applied in practical scenarios, particularly when the noise distribution of a given noisy image deviates from that of the training images. To tackle this problem, we put forward a two-stage denoising model that is actualized by attaching an unsupervised fine-tuning phase after a supervised denoising model processes the input noisy image and secures a denoised image (regarded as a preprocessed image). More specifically, in the first stage we replace the convolution block adopted by the U-shaped network framework (utilized in the deep image prior method) with the Transformer module, and the resultant model is referred to as a U-Transformer. The U-Transformer model is trained to preprocess the input noisy images using noisy images and their labels. As for the second stage, we condense the supervised U-Transformer model into a simplified version, incorporating only one Transformer module with fewer parameters. Additionally, we shift its training mode to unsupervised training, following a similar approach as employed in the deep image prior method. This stage aims to further eliminate minor residual noise and artifacts present in the preprocessed image, resulting in clearer and more realistic output images. Experimental results illustrate that the proposed method achieves significant noise reduction in both synthetic and real images, surpassing state-of-the-art methods. This superiority stems from the supervised model’s ability to rapidly process given noisy images, while the unsupervised model leverages its flexibility to generate a fine-tuned network, enhancing noise reduction capability. Moreover, with support from the supervised model providing higher-quality preprocessed images, the proposed unsupervised fine-tuning model requires fewer parameters, facilitating rapid training and convergence, resulting in overall high execution efficiency.
Blockchain and Access Control Encryption-Empowered IoT Knowledge Sharing for Cloud-Edge Orchestrated Personalized Privacy-Preserving Federated Learning
Authors: Wang Jing , Li Jianhua
Published: February 2024

Federated learning (FL) is emerging as a powerful paradigm for distributed data mining in the context of Internet of Things (IoT) big data. It addresses privacy concerns associated with data outsourcing by enabling local data training and knowledge (i.e., model) sharing. However, simplistic local knowledge sharing can inadvertently expose user privacy to advanced attacks, such as model inversion or gradient leakage. Furthermore, achieving fine-grained and personalized privacy protection for IoT users remains a challenge. In this paper, we propose a novel solution called hierarchical blockchain-empowered cloud-edge orchestrated federated learning (HBCE-FL) to address these challenges. HBCE-FL is designed to provide secure, intelligent, and distributed data analysis for IoT users. To tackle FL’s privacy issues, we develop a multi-level access control encryption and blockchain-based approach for sharing IoT knowledge within the HBCE-FL framework. Our approach classifies IoT users into different levels based on their individual privacy requirements, enabling fine-grained privacy protection. The blockchain is employed for identity authentication, key management, and message sanitization. For scenarios involving IoT users with non-IID data, we integrate federated multi-task learning into HBCE-FL to ensure fairness, robustness, and privacy. Finally, we conduct experiments using classic MNIST and CIFAR10 datasets to validate our approach. The experimental results illustrate that HBCE-FL effectively achieves personalized privacy-preserving FL without losing IoT data availability. Regardless of whether IoT data are homogeneous or heterogeneous, our approach enhances model accuracy and convergence rates by enabling secure IoT knowledge access and sharing for IoT users.
Adsorption Kinetics and Mechanism of Pb(II) and Cd(II) Adsorption in Water through Oxidized Multiwalled Carbon Nanotubes
Authors: Li Xin , Cui Yating , Du Wanting , Cui Weiheng , Huo Lijuan , Liu Hongfang
Published: February 2024

Toxic heavy metals are ubiquitous in the aquatic environment and show a significant danger to human health. Carbon nanotubes have been extensively used in treating the contamination of groundwater due to their porous multi-layer nature. Batch tests revealed that oxidized multiwalled carbon nanotubes (O-MWCNTS) offer better removal of Pb(II). The removal rate of Pb(II) was 90.15% at pH 6 within 24 h, which was ~58% more than that of Cd(II). The removal rate decreased to 55.59% for Pb(II) and to 16.68% for Cd(II) when the initial concentration of Pb(II)/Cd(II) ranged from 5 to 15 mg·g−1. The removal rate in the competitive tests was about 60.46% for Pb(II) and 9.70% for Cd(II). The Langmuir model offered better description of the adsorptive data for both ions. And the Qm of Pb(II) was 5.73 mg·g−1, which was 2.39 mg·g−1 more than that of Cd(II) in a single-icon system, while Qm was 7.11 mg·g−1 with Pb(II) and 0.78 mg·g−1 with Cd(II) in competitive water. And thermodynamic tests further indicated that the activating energy of Pb(II) and Cd(II) was 83.68 and 172.88 kJ·mol−1, respectively. Lead and cadmium adsorbed on the surface of O-MWCNTS are antagonistic in the competitive system. Based on XPS analyses, it was concluded that the absorbed lead/cadmium species on O-MWCNTS were (-COO)2Pb, (-COO)Pb(-O)/(-COO)2Cd, and (-COO)Cd(-O). Additionally, they offered theoretical evidence supporting the practicality of using nanocomposite membranes as a means to remove cadmium and lead.
Risk-Quantification Method for Car-Following Behavior Considering Driving-Style Propensity
Authors: Wang Kedong , Qu Dayi , Yang Yufeng , Dai Shouchen , Wang Tao
Published: February 2024

To systematically study the influence of a propensity for a particular driving style on car-following risk, a safety potential field risk-quantification method that considers driving style is proposed. First, we classify driving behaviors and construct a field-based safety potential car-following model via analogy with intermolecular interactions; second, we establish a risk-quantification model by considering driving style, risk exposure, and risk severity and classify the consequent risk into four levels, high risk, medium risk, low risk, and safe, using the fuzzy C-means algorithm. Finally, we predict the car-following risk using the LightGBM algorithm in real time. The experimental results show that the LightGBM algorithm can recognize up to 86% of medium–high risk levels compared to the Decision Tree and Random Forest Algorithms. It can achieve effective prediction of car-following risk, which provides sufficient warning information to drivers and helps improve the overall safety of vehicle operation.
The Bearing Surface Defect Detection Method Combining Magnetic Particle Testing and Deep Learning
Authors: Li Long , Liu Zhiyuan , Zhao Hengyi , Xue Lin , Wu Jianbo
Published: February 2024

As a critical foundational component, bearings find widespread application in various mechanical equipment. In order to achieve automated defect detection in the bearing-manufacturing process, a defect detection algorithm combining magnetic particle inspection with deep learning is proposed. Dynamic thresholding and generative adversarial network (GAN) methods are employed to extract defect samples from bearing images and augment the dataset, thereby enhancing data diversity. To mitigate the impact of irrelevant displays in bearing images, a coordinated attention (CA) mechanism is introduced into the backbone network of the deep learning model to focus on key information. Additionally, an adaptive spatial feature fusion module (ASFF) is incorporated during the multiscale fusion stage to maintain consistency in features across different hierarchical levels. The weighted intersection over union (WIoU) bounding box loss function is utilized to replace the original generalized intersection over union (GIoU) in the network, directing the model’s attention towards common-quality anchor boxes to reduce the adverse effects of inconsistent annotations. The experimental results demonstrate that the improved network achieves a mean average precision (mAP) of 98.4% on the bearing dataset, representing a 4.2% improvement over the original network.
Application of a Variable Weight Time Function Combined Model in Surface Subsidence Prediction in Goaf Area: A Case Study in China
Authors: Chai Huabin , Xu Hui , Hu Jibiao , Geng Sijia , Guan Pengju , Ding Yahui , Zhao Yuqiao , Xu Mingtao , Chen Lulu
Published: February 2024

To attain precise forecasts of surface displacements and deformations in goaf areas (a void or cavity that remains underground after the extraction of mineral resources) following coal extraction, this study based on the limitations of individual time function models, conducted a thorough analysis of how the parameters of the model impact subsidence curves. Parameter estimation was conducted using the trust-region reflective algorithm (TRF), and the time function models were identified. Then we utilized a combined model approach and introduced the sliding window mechanism to assign variable weights to the model. Based on this, the combined model was used for prediction, followed by the application of this composite prediction to engineering scenarios for the dynamic forecasting of surface movements and deformations. The results indicated that, in comparison with DE, GA, PSO algorithms, the TRF exhibited superior stability and convergence. The parameter models obtained using this method demonstrated a higher level of predictive accuracy. Moreover, the predictive precision of the variable-weight time function combined model surpassed that of corresponding individual time function models. When employing six different variable-weight combination prediction models for point C22, the Weibull-MMF model demonstrated the most favorable fitting performance, featuring a root mean square error (RMSE) of 32.98 mm, a mean absolute error (MAE) of 25.66 mm, a mean absolute percentage error (MAPE) of 7.67%; the correlation coefficient R2 reached 0.99937. These metrics consistently outperformed their respective individual time function models. Additionally, in the validation process of the combined model at point C16, the residuals were notably smaller than those of individual models. This reaffirmed the accuracy and reliability of the proposed variable-weight combined model. Given that the variable-weight combination model was an evolution from individual time function models, its applicability extends to a broader range, offering valuable guidance for the dynamic prediction of surface movement and deformation in mining areas.
Intrinsic Mode-Based Network Approach to Examining Multiscale Characteristics of Sea Surface Temperature Variability
Authors: Lim Gyuchang , Park Jong-Jin
Published: February 2024

Variability of sea surface temperature (SST), characterized by various spatiotemporal scales, is a proxy of climate change. A network analysis combined with empirical mode decomposition is newly presented for examining scale-dependent spatial patterns of SST variability. Our approach is applied to SST anomaly variability in the East/Japan Sea (EJS), consisting of satellite-derived daily datasets of 0.25° × 0.25° resolution from 1981 to 2023. Through the spatial distribution of instantaneous energy in intrinsic modes and features of intrinsic-mode networks, scale-dependent spatiotemporal features are found. The season-specific spatial pattern of energy density is observed only for weekly to semiannual modes, while a persistent high-energy distribution in the tongue-shaped region from East Korea Bay (EKB) to the Sub-Polar Front (SPF) is observed only for annual-to-decadal modes. The seasonality is apparent in the time evolution of energy only for weekly-to-annual modes, with a peak in summer and an increasing trend since the 2010s. Hubs of intrinsic-mode networks are observed in the whole southern area (some northern part) of EJS during the summer (winter), only for monthly to semiannual modes. Regional communities are observed only for weekly to seasonal modes, while there is an inter-basin community with annual-to-biennial modes, incorporating two pathways of East Sea Intermediate Water (ESIW).
Improved Temporal Fuzzy Reasoning Spiking Neural P Systems for Power System Fault Diagnosis
Authors: Shao Ning , Chen Qing , Xie Dan , Sun Ye , Yu Chengao
Published: February 2024

Fuzzy and temporal reasoning can effectively improve the accuracy of fault diagnosis methods. However, there are challenges in practical applications, such as missing alarm messages, temporal reasoning with complex calculations, and complex modeling processes. Therefore, this study proposes an improved temporal fuzzy reasoning spiking neural P (ITFRSNP) system for power system fault diagnosis. First, the ITFRSNP system and its reasoning method are proposed to perform association reasoning between confidence degrees and temporal constraints. Second, a general fault diagnosis model and process are developed based on the ITFRSNP system to diagnose various faulty components and simplify the modeling process. In addition, a search method is provided for identifying suspected faulty components, considering the missing alarm message of the circuit breaker. Simulation results of fault cases demonstrate that the proposed method exhibits high accuracy and fault tolerance. It can precisely identify faulty components despite incorrect operations or inaccurate alarm messages of protective relays and circuit breakers. Moreover, the search method effectively narrows down the diagnostic scope without missing suspected faulty components in scenarios where alarms from boundary circuit breakers are missing, thereby enhancing the fault diagnosis efficiency. The fault diagnosis model features a straightforward structure and reasoning process with minimal computational complexity, making it suitable for real-time diagnosis of complex faults within power systems.
Involvement of Vasoactive Intestinal Peptide Family Members in Diabetic Keratopathy
Authors: Maugeri Grazia , D’Amico Agata Grazia , Magrì Benedetta , D’Agata Velia
Published: February 2024

Diabetic keratopathy (DK) is a common ocular complication of diabetes, characterized by alteration of the normal wound-healing mechanism, reduction of epithelial hemidesmosomes, disruption of the basement membrane, impaired barrier function, reduced corneal sensitivity, corneal ulcers, and corneal edema. The limited number of clinical studies do not allow a full characterization of the pathophysiology of DK and, until now, effective therapeutic approaches have not been available. However, in recent years, neuropeptides gained great attention for their biochemical characteristics and therapeutic potential. This review focuses on the role of neuropeptides vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP) in the eye and, in particular, in the cornea, in physiological conditions, or during DK, by providing an overview of this diabetes mellitus complication.
Stability Analysis of Buck Converter Based on Passivity-Based Stability Criterion
Authors: Zhang Yajing , Si Jinyao , Wang Xiu-Teng , Li Jianguo , Zhao Hongyan
Published: February 2024

Recently, the stability of DC microgrids has attracted increasing attention. The traditional stability analysis method cannot not meet the requirements for the complexity and bidirectional energy flow of the system. In this paper, a passivity-based stability criterion (PBSC) is proposed to analyze the stability of the cascade system. In order to realize the passivity of the system, an improved feedback control method based on the traditional double-loop control strategy is proposed, which will improve the stability region and guarantee the passivity of the system. Moreover, a Buck-CPL simulation model is established based on MATLAB/Simulink R2008, and the correctness of the theoretical analysis is verified by experiments.
Performance Analysis and Optimization Design of a Dual-Mode Reconfigurable Ankle Joint Parallel Rehabilitation Mechanism
Authors: Zhang Lei , Li Ruiqin , Ning Fengping , Chai Chao , Jia Zengyu
Published: February 2024

In this study, a dual-mode reconfigurable parallel ankle joint rehabilitation mechanism is proposed to meet the needs of patients in different ankle rehabilitation stages. This mechanism can switch between the 1T2R (where R represents rotation and T represents translation) and 2T1R motion modes. The screw theory and the modified G-K formula were used to analyze and verify the degree of freedom of the mechanism. The non-parasitic motion characteristics were analyzed by examining the topological structure of the mechanism. An inverse kinematics model was established using the closed-loop vector method, and the mechanism’s singularity was analyzed based on the Jacobian matrix. The Jacobian matrix and the numerical method were used to compare and analyze the workspace index, the rotational dexterity index and the load capacity performance index before and after the introduction of branched chains with actuation redundancy. A particle swarm optimization algorithm was used to optimize the geometric dimensional parameters of the mechanism. The results show that the mechanism exhibits the characteristics of a parallel mechanism without parasitic motion in the two motion modes. Using branched chains with actuation redundancy can significantly improve the rotational dexterity and load capacity performance index, without affecting the workspace index. Compared to the original mechanism, the kinematic performance of the optimized mechanism is significantly improved. It is concluded that the proposed mechanism can meet the needs of ankle joint activity training in the 1T2R motion mode and the needs of ankle joint proprioception training in the 2T1R motion mode, which can better meet the needs of patients in different rehabilitation stages.
Noise Differentiation and Atom Number Measurement in Optical Lattice Clocks by Analyzing Clock Stabilities with Various Parameters
Authors: Zhao Guodong , Guo Feng , Lu Xiaotong , Chang Hong
Published: February 2024

We propose a method that enables the precise determination of the number of atoms in a Dick-noise-free optical lattice clock, by effectively addressing quantum projection noise. Our approach relies on conducting stability measurements at three distinct parameter sets, allowing us to differentiate between quantum projection noise, photon shot noise, and technical noise. Importantly, it enables accurate extraction of the atom number, even in the presence of photon shot noise and technical noise. We utilize numerical simulations to validate our approach, optimize the modulation parameters for minimal uncertainty, and investigate the impact of atom number fluctuations on the determinacy of our results. The numerical results show the validity of our method and demonstrate an estimated uncertainty in the atom number that is below 4% with 6.7 h measurement, provided that the standard deviation of atom number fluctuation is kept below 0.14 times the average atom number.
Structurally Invariant Higher-Order Ince-Gaussian Beams and Their Expansions into Hermite-Gaussian or Laguerre-Gaussian Beams
Authors: Abramochkin Eugeny G. , Kotlyar Victor V. , Kovalev Alexey A.
Published: February 2024

Paraxial beam modes, which propagate in space and focus without changing their transverse intensity pattern, are of great value for multiplexing transmitted data in optical communications, both in waveguides and in free space. The best-known paraxial modes are the Hermite-Gaussian and Laguerre-Gaussian beams. Here, we derive explicit analytical expressions for Ince-Gaussian (IG) beams for several first values of the indices p = 3, 4, 5, and 6. In total, we obtain expressions for the amplitudes of 24 IG beams. These formulae are written as superpositions of the Laguerre-Gaussian (LG) or Hermite-Gaussian (HG) beams, with the superposition coefficients explicitly depending on the ellipticity parameter. Due to simultaneous representation of the IG modes via the LG and HG modes, it is easy to obtain the IG modes in the limiting cases wherein the ellipticity parameter is zero or approaches infinity. The explicit dependence of the obtained expressions for the IG modes on the ellipticity parameter makes it possible to change the intensity pattern at the beam cross-section by continuously varying the parameter values. For the first time, the intensity distributions of the IG beams are obtained for negative values of the ellipticity parameter. The obtained expressions could facilitate a theoretical analysis of properties of the IG modes and could find practical applications in the numerical simulation or generation of such beams with a liquid-crystal spatial light modulator.
Noise Separation Technique for Enhancing Substation Noise Assessment Using the Phase Conjugation Method
Authors: Fan Shengping , Liu Jiang , Li Linyong , Li Sheng
Published: February 2024

The intrinsic noise of different transformers in the same substation belongs to the same type of noise, which is strongly coherent and difficult to separate, greatly increasing the cost of substation noise assessment and treatment. To solve the problem, the present paper proposes a noise separation technique using the phase conjugation method to separate the intrinsic noise signals of different transformers: firstly, the reconstruction of sound source information is realized by the phase conjugation method based on the measurement and emission of a line array; secondly, the intrinsic noise signals of the sound source are obtained by the equivalent point source method. The error of the separation technique is analyzed by point source simulation, and the optimal arrangement form of the microphone line array is studied. A validation experiment in a semi-anechoic chamber is also carried out, and the results prove that the error of separation technique is less than 2dBA, which is the error tolerance of engineering applications. Finally, a noise separation test of three transformers is performed in a substation using the proposed technique. The results show that the proposed technique is able to realize the intrinsic noise separation of each transformer in the substation, which is of positive significance for substation noise assessment and management.
Simulation of Gas Fracturing in Reservoirs Based on a Coupled Thermo-Hydro-Mechanical-Damage Model
Authors: Qi Enze , Xiong Fei , Cao Zhengzheng , Zhang Yun , Xue Yi , Zhang Zhizhen , Ji Ming
Published: February 2024

Gas fracturing technology for enhancing rock permeability is an area with considerable potential for development. However, the complexity and variability of underground conditions mean that a variety of rock physical parameters can affect the outcome of gas fracturing, with temperature being a critical factor that cannot be overlooked. The presence of a temperature field adds further complexity to the process of gas-induced rock fracturing. To explore the effects of temperature fields on gas fracturing technology, this paper employs numerical simulation software to model the extraction of shale gas under different temperature conditions using gas fracturing techniques. The computer simulations monitor variations in the mechanical characteristics of rocks during the process of gas fracturing. This analysis is performed both prior to and following the implementation of a temperature field. The results demonstrate that gas fracturing technology significantly improves rock permeability; temperature has an impact on the effectiveness of gas fracturing, with appropriately high temperatures capable of enhancing the fracturing effect. The temperature distribution plays a crucial role in influencing the results of gas fracturing. When the temperature is low, the fracturing effect is diminished, resulting in a lower efficiency of shale gas extraction. Conversely, when the temperature is high, the fracturing effect is more pronounced, leading to a higher shale gas production efficiency. Optimal temperatures can enhance the efficacy of gas fracturing and consequently boost the efficiency of shale gas extraction. Changes in the parameters of the rock have a substantial impact on the efficiency of gas extraction, and selecting suitable rock parameters can enhance the recovery rate of shale gas. This paper, through numerical simulation, investigates the influence of temperature on gas fracturing technology, with the aim of contributing to its improved application in engineering practices.
Operation Optimization of a Bucket Conveyor Transporting Wastes in the Processing Plant of a Hard Coal Mine
Authors: Jendrysik Sebastian , Rogala-Rojek Joanna , Kowol Daniel , Wieczorek Andrzej N.
Published: February 2024

This study presents the structure and principles of operation of the control system for a bucket conveyor operating in a jig preparation plant. The idea of controlling the conveyor speed is to maintain constant, nominal filling of the buckets, and thus achieve a constant mass of material on the conveyor. As part of the completed task, a new control algorithm was developed and implemented to increase transport efficiency. Simulation and industrial test results were analyzed, in which the traditional PID controller was replaced with a fuzzy controller, which enabled control error reduction, thus achieving better control quality.
Tin (Sn) Geochemical Mapping Based on a Fixed-Value Method: A Case Illustration in Gejiu Area, Southwest China
Authors: Xu Shengchao , Li Jie , Zhang Xiaobing , Huang Zhao , Huang Yuanyou , Long Yujiang , Xu Yongqiang , Song Xufeng , Chen Zheng , Li Yuanbin , Hou Zhaolei , Gong Qingjie
Published: February 2024

Geochemical maps play an important role in mineral resource exploration. There are three traditional methods for creating geochemical maps: the cumulative frequency method, the logarithmic interval method, and the Avg±k∗Std (where Avg and Std are the abbreviations of average and standard deviation, and k is a multiple of Std) method. However, with the increasing scope of the study area and cumulative data, the limitations of traditional methods, which depend on the amount of data, are exposed. A fixed-value method for Sn geological mapping is proposed to overcome the limitations of traditional methods. In the fixed-value method, Sn concentrations are divided into 19 levels on 18 fixed values ranging from 1 μg/g (corresponding to the detection limit) to 1000 μg/g (corresponding to the cut-off grade of Sn in hard rocks). The 19 levels are mapped in six color tones. The first to fifth levels are the lowest background areas in blue tones, which correspond to Sn concentrations ranging from the minimum to 3.4 μg/g. The sixth to ninth levels are high background areas in yellow tones corresponding to concentrations less than 10 μg/g, the 10th to 12th are low anomaly areas in pink tones less than 28 μg/g, the 13th to 15th are high anomaly areas in red tones less than 200 μg/g (corresponding to the placer cut-off grade), the 16th to 18th in gray tones less than 1000 μg/g, and the 19th level is in black corresponding to Sn ores with Sn concentration not less than 1000 μg/g. The fixed-value method along with three traditional methods was used to contour the Sn geochemical maps in the Gejiu area in Southwest China. The illustration results of the presented fixed-value method and three traditional methods for geochemical mapping of Sn are all feasible for Sn deposit exploration in the Gejiu area, Southwest China. Compared to traditional methods, the presented fixed-value method overcomes the flaws of traditional methods and is also more meaningful in geochemistry.
Testing of Indoor Obstacle-Detection Prototypes Designed for Visually Impaired Persons
Authors: Păpară Radu , Grec Loredana , Potarniche Ioana-Adriana , Voichița Ramona Gălătuș
Published: February 2024

Outdoor solutions aiding the navigation of visually impaired individuals can seamlessly transition to indoor environments. Take, for instance, the adaptation of special lanes and configurations on the floor. However, these existing solutions fall short when it comes to addressing obstacles above ground level, such as open windows, as highlighted in a previous article on the use of ultrasonic glove for visually impaired users. In response, the present proposal is a user-friendly, cost-effective solution that is capable of detecting elevated obstacles. Importantly, this solution aligns with a user’s language preferences, eliminating the need for learning new languages or possessing IT skills. Users simply specify their desired language for the prototype to communicate in, ensuring a personalized experience. The system alerts users to the presence of obstacles through varying levels of warning, calculated based on the distance between the obstacle and the user’s current position. This approach not only enhances safety but also prioritizes accessibility and ease of use.
Exploring HDV Driver–CAV Interaction in Mixed Traffic: A Two-Step Method Integrating Latent Profile Analysis and Multinomial Logit Model
Authors: Kong Dewen , Wang Miao , Zhang Kanyu , Sun Lishan , Wang Qingqing , Zhang Xi
Published: February 2024

Human-driven vehicles (HDVs) will share the road with connected autonomous vehicles (CAVs) in the near future. Accordingly, the investigation of the interactive behavior of HDV drivers toward CAVs is becoming critical. In this study, a questionnaire survey was first conducted. The heterogenous clusters of HDV drivers were revealed through the latent profile analysis based on the collected dataset, with the focus on their trust and familiarity with CAVs, their attitudes towards sharing the road with CAVs, and their risk perception and perceived behavior control when they faced the CAVs. Subsequently, the correlation between the respective latent cluster and several socio-demographic factors was understood based on the multinomial logistic regression model, and the choice behavior of each cluster in different interactive driving scenarios was revealed. Three vital findings were reported. (1) Three profile clusters of HDV drivers (i.e., negative individuals, neutral individuals, and positive individuals) were revealed. (2) The drivers of a low/middle income and with a long driving experience were more likely to be negative individuals, whereas the CAV experience can make drivers feel positive towards CAVs. (3) Negative individuals might give up on changing lanes when a CAV platoon driving was noticed in the target lanes; in addition, they might raise more rigorous requirements for vehicle spacing in the lane-changing process when finding CAVs driving in the target lanes. To be specific, negative and neutral individuals preferred driving in front of the CAV platoons. The findings can provide references for developing effective management measures or CAV control strategies for transportation systems.
An Exploration of Artistic Expressions of Everyday Peri-Urban Landscapes as a Method of Socio-Spatial Analysis in Spatial Planning
Authors: Staessen Annelies , Salvador Antonio José , Lyngstad Ingfrid
Published: February 2024

Everyday landscapes, including peri-urban areas, play a pivotal role in shaping our physical and mental environments. Nevertheless, spatial planning often falls short of integrating contemporary everyday life and lived space. This paper advocates for an expanded approach beyond traditional planning methods, exploring the potential of artistic representations like drawings, photographs, and films to capture the nuances of peri-urban landscapes. Based on a selection of contemporary artistic works in the fields of drawing, photography, and cinema, this paper explores, through an analysis of specific projects and interviews with the artists, the potentials and constraints of these types of representations. This analysis of selected works reveals that these mediums embody a rich and complex collective journey, showcasing the profound connection between the artist and the environment. Structured around the key stages of analysis, documentation, and communication, the discussion elucidates the interrelated nature of these phases within a broader creative process. It underscores the significance of recognizing these artistic representations as integral components in planning processes, emphasizing their potential to provide unique insights into the complexities of peri-urban landscapes. In conclusion, this article proposes a set of recommendations for the incorporation of these artistic mediums within planning processes and urban studies.
The Behavior and Removal of Condensable Particulate Matter in Flue Gas in a Multi-Field Force: A Modeling and Experimental Study
Authors: Liu Wenting , Zhang Xinde , Zhou Zhiyong , Lu Jianyi
Published: February 2024

Condensable particulate matter (CPM) is different from filterable particulate matter (FPM), which could escape from air pollution control devices (APCDs) and pose a great threat to the environment and human health. Thus, modeling and experimental studies were conducted on CPM particle behavior and removal, in a cold electrode electrostatic precipitator (CE−ESP) coupled with a electric field, temperature field and concentration field. A multi−field force coupling model was then established that was based on the mechanical behavior of particles inside the CE−ESP. The results showed that temperature field was beneficial to depositing small size particles and that, the greater the temperature gradient, the higher CPM’s removal efficiency. While the electric field tended to gather larger size particles, the greater the voltage provided, the higher the removal efficiency for CPM and FPM. In the multi−field, the augmented coagulation and the removal efficiencies of both CPM and FPM increased significantly, reaching 89% and 98%, respectively. Subsequently, experiments were conducted by a self−made CE−ESP device, which showed the removal efficiencies of CE−ESP of a CPM in a multi−field were 91% and 81% for a coal−fired power plant and a waste incineration plant, respectively. This research could make a great contribution to CPM condensation, aggregation and removal.
Influence of Saharan Dust on the Composition of Urban Aerosols in Palermo City (Italy)
Authors: Varrica Daniela , Alaimo Maria Grazia
Published: February 2024

The Mediterranean Basin is involved in a recurring phenomenon wherein air masses laden with dust from North Africa impact the southern regions of the European continent. Saharan dust has been associated with increased mortality and respiratory symptoms. Palermo is a large coastal city, and in addition to the impact of desert dust particles, it has a mixture of anthropogenic sources of pollutants. In this study, we collected Saharan dust samples during August 2022 and October 2023, following a high-intensity Saharan dust event, and measured concentrations of 33 major and trace elements as well as Rare Earth Elements (REE). The mineralogical characterization of the deposition dust collected during Saharan events revealed calcite, dolomite, quartz, and clay minerals. The presence of palygorskite is indicative of Saharan events. Seven elements (Ca, Mg, Al, Ti, Fe, K, and Na) account for 98% of the total analyzed inorganic burden. Elemental ratios are valuable tools in atmospheric sciences for estimating sources of air masses. The results highlight that the city of Palermo is mainly affected by dust from the north-western Sahara.