bluuebunny/crossref_metadata_2025 huggingface dataset:
Iron Oxide Scale Formation Mechanism and Anti-Corrosion Technology from Induction Remelting of Boiler Coating in Waste Incineration Power Plant
Authors: Qu Zuopeng , Tian Xinli
Published: February 2025

High-frequency induction welding technology represents the development direction of the high-temperature corrosion protection technology for the heating surfaces of the boiler “four tubes”. However, when the high-frequency induction coil heats and remelts the coating on the tube’s outer wall, the tube’s inner wall is also heated, causing an iron oxide scale to form on the tube’s inner wall. When the remelting temperature rises and the temperature of the tube’s inner wall exceeds 580 °C, three layers of oxide films, FeO, Fe3O4, and Fe2O3 are arranged in sequence from the substrate surface of the tube’s inner wall to the outside, with a thickness ratio of approximately 1:10:100. From the XRD spectra of tube iron oxide scale, it can be seen that the oxidation of the tube. The skin is mainly composed of Fe3O4, with a certain amount of Fe2O3 and trace amounts of FeO. The iron in the diffraction peak originates from the metal matrix. However, when the remelting temperature continues to rise and the temperature of the tube’s inner wall exceeds 580 °C, the oxide film begins to thicken significantly, that is, the oxide film begins to transform into an oxide scale. Under the continuous action of high-temperature induction remelting, the reaction between iron and oxygen is accelerated, but because the oxygen ions of water slowly diffuse through two outer layers of oxide films, with a low oxygen concentration. Although the FeO film is thin, it has a loose structure and numerous lattice defects, is unstable and easy to decompose, and easily peels off from the tube’s inner wall. For a pipe wall thickness of 5 mm, if the thinning rate of the inner wall caused by detachment reaches 0.8 mm/year, it is highly likely to cause pipe burst accidents within 4–5 years. The influence of the iron oxide scale on the performance of the tube’s inner wall was evaluated by testing indexes, such as surface hardness and decarburization layer depth. Although the oxide scale reduces the surface hardness of the tube’s inner wall, the surface decarburization layer is very thin, so the effect on the mechanical properties of the tube’s substrate is limited. The technology of inhibiting the formation of the iron oxide scale in induction remelting is briefly introduced. During the high-frequency remelting process of water-cooled walls, as the tube bank moves forward relative to the high-frequency heating coil, nitrogen protection is used to suppress the formation of oxide scale, effectively eliminating the troubles caused by high-frequency induction remelting and achieving the goal of improving the service life of the tube bank. This technology of the nitrogen protection method is used to inhibit the formation of iron oxide scale, not only inhibiting the formation of the iron oxide scale on the tube inner wall and the back of the tube bundle, with remarkable experimental results and broad application prospects.
Plant-Based vs. Animal-Based Diets: Appetitive Traits and Dietary Patterns in Adults Based on Cross-Sectional Surveys
Authors: Wiśniewska Klaudia , Okręglicka Katarzyna Małgorzata , Jaworski Mariusz , Nitsch-Osuch Aneta
Published: February 2025

Background: Dietary patterns play a crucial role in shaping eating behaviours and influencing health outcomes, such as body weight. Understanding how appetitive traits differ between plant-based and animal-based diets can provide insights into dietary strategies for weight management and improved health. Objectives: The aim of this study was to analyse the relationships between appetitive traits, as measured by the Adult Eating Behaviour Questionnaire (AEBQ), and dietary patterns in adults consuming plant-based or animal-based diets. It examined how these dietary patterns influence body mass index (BMI) and explored the differences in appetite-related traits between groups with different levels of plant and animal product consumption. Methods: A cross-sectional survey of 553 Polish adults was conducted using validated questionnaires, including the AEBQ and a food frequency questionnaire (FFQ). The participants were categorised into four dietary groups: high intake of both plant and animal products, low intake of both, plant-based diet, and animal-based diet. The data were analysed using SPSS version 14.0 software. Results: The participants on a plant-based diet had significantly lower BMIs and slower eating rates than those on an animal-based diet. Positive correlations were observed between ’food approach’ traits (e.g., food responsiveness, emotional overeating) and BMI, particularly in individuals with higher animal product consumption. Conversely, ’food avoidance’ traits (e.g., food fussiness, slowness in eating) were more prevalent among those on a plant-based diet. Conclusions: The results suggest that plant-based diets are associated with favourable appetitive traits and a lower BMI. These findings highlight the potential of plant-based diets to support weight control and improve eating behaviours. Further research is warranted to investigate the causal mechanisms underlying these associations.
Nanoparticle-Encapsulated Plant Polyphenols and Flavonoids as an Enhanced Delivery System for Anti-Acne Therapy
Authors: Puspadewi Ririn , Milanda Tiana , Muhaimin Muhaimin , Chaerunisaa Anis Yohana
Published: February 2025

This study conducted a literature review by searching for articles related to the treatment of skin infections/wrinkles using nano-delivery systems containing natural compounds. The search was conducted in various databases for articles published in the last 10 years, with strict inclusion and exclusion criteria. Of the 490 articles found, 40 were considered relevant. Acne vulgaris is a common dermatological disorder characterised by inflammation of the sebaceous glands, often resulting in the development of pimples, cysts, and scarring. Conventional treatments, including antibiotics and topical retinoids, frequently demonstrate limitations such as side effects, resistance, and insufficient skin absorption. Recent advancements in nanotechnology have enabled the creation of innovative drug-delivery systems that enhance the effectiveness and reduce the adverse effects of anti-acne medications. Polyphenols and flavonoids, natural bioactive compounds with notable anti-inflammatory, antioxidant, and antibacterial properties, are recognised for their therapeutic effectiveness in acne treatment. However, their practical application is hindered by insufficient solubility, stability, and bioavailability. The incorporation of these compounds into nanoparticle-based delivery systems has shown promise in resolving these challenges. Various nanoparticle platforms, including lipid-based nanoparticles, polymeric nanoparticles, and solid lipid nanoparticles, are evaluated for their ability to improve the stability, controlled release, and targeted delivery of polyphenols and flavonoids to the skin. The advent of polyphenol and flavonoid-loaded nanoparticles marks a new acne therapy era.
Current Trends in Clinical Trials of Prodrugs
Authors: Boreski Diogo , Schmid Valentine Fabienne , Bosquesi Priscila Longhin , dos Santos Jean Leandro , Scarim Cauê Benito , Reshetnikov Viktor , Chin Chung Man
Published: February 2025

The development of new drugs is a lengthy and complex process regarding its conception and ideation, passing through in silico studies, synthesis, in vivo studies, clinical trials, approval, and commercialization, with an exceptionally low success rate. The lack of efficacy, safety, and suboptimal pharmacokinetic parameters are commonly identified as significant challenges in the discovery of new drugs. To help address these challenges, various approaches have been explored in medicinal chemistry, including the use of prodrug strategies. As a well-established approach, prodrug design remains the best option for improving physicochemical properties, reducing toxicity, and increasing selectivity, all while minimizing costs and saving on biological studies. This review article aims to analyze the current advances using the prodrug approach that has allowed the advance of drug candidates to clinical trials in the last 10 years. The approaches presented here aim to inspire further molecular optimization processes and highlight the potential of this strategy to facilitate the advancement of new compounds to clinical study phases.
Study on Lyophilised Orodispersible Tablets from Plant-Based Drinks as Bulking Agents
Authors: Demeter Adrienn Katalin , Farkas Dóra , Király Márton , Kovács Zoltán , Ludányi Krisztina , Antal István , Kállai-Szabó Nikolett
Published: February 2025

Background/Objectives: Oral administration of active pharmaceutical ingredients (APIs) is the most commonly used route of administration. As dysphagia is a prevalent problem, the size of the swallowed dosage form could negatively influence patient adherence. Orally disintegrating tablets (ODTs) are beneficial dosage forms because they disintegrate within a few seconds in the oral cavity without water. Lactose is one of the most commonly used excipients in the pharmaceutical industry; it served as the central concept of a recent publication on the formulation of milk-based ODTs despite lactose malabsorption being widespread worldwide. Consequently, the plant-based alternative market has grown exponentially and has become a prevailing food trend, with various alternatives to choose from. For this reason, the development of a nonsteroidal anti-inflammatory drug (NSAID)-containing ODT with plant-based drinks (PBDs) was assessed for its innovative potential. Methods: Different PBDs were investigated and compared to traditional and lactose-free milk. The liquids’ viscosity, pH, and particle size were determined, and an electronic tongue was used for the sensory evaluation. The various ODTs were prepared with the freeze-drying method, and then the qualitative characteristics of the dosage form were investigated. Results: Our different measurements show that different plant beverages differ from each other and that these differences have an impact on the technological processing. According to the HPLC-DAD measurements, all values were in the required range. Conclusions: These measurements suggest that the soya drink is the most similar to traditional cow milk and would be the most appropriate choice among the investigated plant-based drinks to be used as a carrier system for an ibuprofen-containing ODT.
Drug Loss at Arterial Bends Can Dominate Off-Target Drug Delivery by Paclitaxel-Coated Balloons
Authors: Tscheuschner Linnea , Stratakos Efstathios , Kostakis Marios , Gravanis Miltiadis , Katsimpoulas Michalis , Pennati Giancarlo , Sigala Fragiska , Tzafriri Abraham R.
Published: February 2025

Background/Objective: Paclitaxel-coated balloons (PCBs) can deliver efficacious drug concentrations to treated arterial segments but are known to exhibit high tracking losses. We aimed to define the governing factors impacting tracking loss and to contrast its drug distribution consequences with those of PCB inflation at the treatment site. Methods: Four naïve and four in-stent restenosis (ISR) porcine superficial femoral arteries (SFA) were treated with PCBs, and plasma samples were collected post-tracking and post-inflation. Animals were sacrificed <1 h post-intervention, and local, upstream, and downstream tissues were collected for paclitaxel quantification. Computationally driven quantitative benchtop-tracking and frictional PCB-sliding experiments modeled paclitaxel loss and delivery to upstream tissue. Results: Paclitaxel concentrations in plasma peaked pre-inflation and declined 30-fold immediately post-inflation. Correspondingly, losses of 30% and 1% of nominal PCB load were measured in vitro during, respectively, tracking over single bend and during device insertion. Mean paclitaxel concentrations were equally high at ISR and naïve SFA treatment sites (56,984 vs. 79,837 ng/g, p > 0.99) and ranged from 9 to 89 ng/g in tissues downstream of these treatment sites. Sampling of non-target upstream iliac artery tissues revealed paclitaxel concentration of 4351 ± 4084 ng/g. Benchtop sliding of PCB samples onto ex vivo porcine artery samples exhibited efficient, pressure independent frictional paclitaxel transfer (124 µg at 0.05 atm vs 126 µg at 0.1 atm, p > 0.99). Conclusions: PCB interactions at porcine vessel bends led to premature tracking loss, resulting in peak plasma concentrations exceeding post-inflation concentrations, and delivery to upstream tissue that is plausibly explained as arising from efficient friction-mediated coating transfer.
Differential Expression of Amaranth AtrDODA Gene Family Members in Betalain Synthesis and Functional Analysis of AtrDODA1-1 Promoter
Authors: Xie Huiying , Zeng Jiajing , Feng Wenli , Gao Wei , Lai Zhongxiong , Liu Shengcai
Published: February 2025

Betalains differ from anthocyanins, and they cannot coexist in the same plant under natural conditions. The L-DOPA 4,5-dioxygenase encoded by the DODA gene is a key step in the pathway of betalain biosynthesis in Caryophyllales plants. Amaranth is an important resource for the study and extraction of betalains. In order to clarify the function of AtrDODA family genes in betalain biosynthesis, we screened out three AtrDODA family gene members associated with betalains based on a genome database and RNA-seq databases of Amaranthus tricolor. Their characterization and expression pattern were further analyzed. The result of subcellular localization showed that all three AtrDODA members were located in the nucleus. Betacyanin and betaxanthin were promoted by paclobutrazol treatment in the leaves and stems of ‘Suxian No.1’ (red), while they were inhibited by gibberellin and darkness, which were consistent with the gene expression pattern of AtrDODAs. After heterologous transformation of the AtrDODA1-1 promoter into tobacco with GUS staining analysis, the promoter activity of AtrDODA1-1 of ‘Suxian No.1’ (red) amaranth was significantly higher than that of ‘Suxian No.2’ (green) amaranth. Furthermore, we analyzed the promoter activity of AtrDODA1-1 by GUS staining and qRT-PCR after sprayed exogenous MeJA and GA3 on the AtrDODA1-1 promoter transformed tobacco plants. The results showed that AtrDODA1-1 responded to plant hormones. This study could lay a foundation for revealing the biological functions of the amaranth DODA gene family, and provide new clues for the molecular mechanism of betalain synthesis.
Labile Carbon Input Mitigates the Negative Legacy Effects of Nitrogen Addition on Arbuscular Mycorrhizal Symbiosis in a Temperate Grassland
Authors: Liu Sitong , Zhang Yuxiao , Yu Xiaoqian , Cui Meng , Jiang Liangchao , Zhang Tao , Gao Yingzhi
Published: February 2025

Nitrogen (N) deposition and carbon (C) addition significantly influence the dynamics of plant–microbe interactions, particularly altering the symbiotic relationship between plants and arbuscular mycorrhizal fungi (AMF). However, the effects and underlying mechanisms of labile C input on the relationship between AMF and various plant species in a nitrogen-enriched environment remain a knowledge gap. A seven-year field experiment was conducted to examine how six levels of N and three levels of labile C addition impact AMF colonization in four key plant species: Leymus chinensis (Trin. ex Bunge) Tzvelev, Stipa baicalensis Roshev., Thermopsis lanceolata R. Br. and Potentilla bifurca Linn. Our results showed that N and C additions exert significantly different effects on the relationship between AMF and various plant species. Labile C addition mitigated historical N negative effects, particularly for S. baicalensis, enhancing AMF infection and promoting nutrient exchange under high-N and low-C conditions. The relationship between AMF and both L. chinensis and T. lanceolata changed to weak mutualism under low-N and high-C conditions, with significant decreases in vesicular and arbuscular abundance. Plant root stoichiometry plays a critical role in modulating AMF symbiosis, particularly under high-N and -C conditions, as reflected in the increased AMF infection observed in T. lanceolata and P. bifurca. Our findings emphasize the species-specific and nutrient-dependent AMF symbiosis, revealing that targeted C input can mitigate the legacy effects of N enrichment. Effective nutrient management is of crucial importance for ecological restoration efforts in temperate grasslands affected by long-term N enrichment.
Geometric Accuracy and Dimensional Precision in 3D Printing-Based Gear Manufacturing: A Study on Interchangeability and Forming Precision
Authors: Wei Xiaofeng , Zhang Siwei , Sun Lingli , Zhao Xinyu , Sun Mengchen , Yu Run , Zhou Xingwen , Li Yuhang
Published: February 2025

This paper investigates the geometric interchangeability and dimensional precision of parts fabricated using Fused Deposition Modeling (FDM), with a focus on gear manufacturing. By employing a substrate and two spur gears as test components, critical process parameters, including layer thickness, extrusion speed, and print temperature, were optimized to achieve enhanced accuracy. Geometric and dimensional tolerances such as straightness, roundness, and surface roughness were systematically evaluated using advanced metrological techniques. The results indicate that larger components demonstrate higher precision, with deviations for large and pinion gears ranging between −0.045 and 0.060 mm, and −0.150 and 0.078 mm, respectively. Analysis reveals that the anisotropic nature of the FDM process and thermal shrinkage significantly impact accuracy, particularly in smaller features. Residual stress analysis reveals that smaller components formed via FDM exhibit higher stress concentrations and dimensional deviations due to voids and uneven thermal contraction, whereas larger components and flat substrates achieve better stress distribution and precision. The findings suggest that reducing material shrinkage coefficients and optimizing process parameters can enhance part quality, achieving dimensional tolerances within ±0.1 mm and geometric consistency suitable for practical applications. This research highlights the potential of FDM for precision manufacturing and provides insights into improving its performance for high-demand industrial applications.
A Social Group Optimization Algorithm Using the Laplace Operator for the Economic Dispatch Problem
Authors: Secui Dinu Calin , Hora Cristina , Dan Florin Ciprian , Secui Monica Liana , Hora Horea Nicolae , Gligor Emil
Published: February 2025

The economic dispatch (ED) problem focuses on the optimal scheduling of thermal generating units in a power system to minimize fuel costs while satisfying operational constraints. This article proposes a modified version of the social group optimization (SGO) algorithm to address the ED problem with various practical characteristics (such as valve-point effects, transmission losses, prohibited operating zones, and multi-fuel sources). SGO is a population-based metaheuristic algorithm with strong exploration capabilities, but for certain types of problems, it may stagnate in a local optimum due to a potential imbalance between exploration and exploitation. The new version, named SGO-L, retains the structure of the SGO but incorporates a Laplace operator derived from the Laplace distribution into all the iterative solution update equations. This adjustment generates more effective search steps in the solution space, improving the exploration–exploitation balance and overall performance in terms of solution stability and quality. SGO-L is validated on four power systems of small (six-unit), medium (10-unit), and large (40-unit and 110-unit) sizes with diverse characteristics. The efficiency of SGO-L is compared with SGO and other metaheuristic algorithms. The experimental results demonstrate that the proposed SGO-L algorithm is more robust than well-known algorithms (such as particle swarm optimization, genetic algorithms, differential evolution, and cuckoo search algorithms) and other competitor algorithms mentioned in the study. Moreover, the non-parametric Wilcoxon statistical test indicates that the new SGO-L version is more promising than the original SGO in terms of solution stability and quality. For example, the standard deviation obtained by SGO-L shows significantly lower values (6.02 × 10−9 USD/h for the six-unit system, 7.56 × 10−5 USD/h for the 10-unit system, 75.89 USD/h for the 40-unit system, and 4.80 × 10−3 USD/h for the 110-unit system) compared to SGO (0.44 USD/h for the six-unit system, 50.80 USD/h for the 10-unit system, 274.91 USD/h for the 40-unit system, and 1.04 USD/h for the 110-unit system).
Data-Driven Soft Sensor Model Based on Multi-Timescale Feature Fusion for Crystal Quality Prediction in Czochralski Process
Authors: Ren Jun-Chao , Wan Yin
Published: February 2025

The accurate real-time prediction of the crystal quality index v/G is an important reference for the real-time monitoring of the growth quality status and the process optimization adjustment of semiconductor silicon single crystals. This paper proposes a data-driven crystal quality indicator v/G soft sensor prediction model based on multi-timescale feature fusion to achieve the effective prediction of the crystal quality indicator v/G. Firstly, the characteristics of the crystal quality index v/G in the growth process of Czochralski silicon single crystal are analyzed. Secondly, the crystal quality index v/G is broken down into several natural components using something called complete ensemble empirical mode decomposition with adaptive noise (CEEMDAD), which provides more stable data. On this basis, each intrinsic mode component is reconstructed according to the sample entropy. Then, the maximum mutual information coefficient (MIC) method is applied to identify the characteristic variables most closely associated with each reconstructed component of the crystal quality index v/G from the process-influencing factors. Then, a long short-term memory network with a self-attention mechanism is used to establish a prediction model of the reconstructed components to extract the multi-timescale feature information from the different components of the crystal quality index v/G. Finally, the prediction results of the crystal quality index v/G are obtained by fusing each subsequent prediction model. According to the actual field data, the comprehensive experimental results validate the efficacy of the proposed soft sensor modeling method for the crystal quality index v/G. Compared with the single model, the proposed prediction model has a smaller MAE, RMSE, and prediction performance index and a higher HR prediction hit rate.
Assessment of Criticality in Water Distribution Networks via Complex Network Theory
Authors: Alaggio Jordana , Barros Daniel , Brentan Bruno , Carpitella Silvia , Herrera Manuel , Izquierdo Joaquín
Published: February 2025

Water distribution networks (WDNs), which are responsible for delivering water of adequate quantity and quality, are vulnerable to threats such as leaks, pipe breaks, and contaminant intrusions. Hence, it is important to identify critical network elements to develop more assertive maintenance strategies for water systems. This paper aims to perform a risk assessment on leaks and pipe breaks to support the identification of critical elements in water supply systems. To this end, complex network theory (CNT) is applied as an alternative to conventional approaches that rely on multiple hydraulic simulations. Metrics such as robustness, redundancy, centrality, and connectivity are used to analyze graphs representing WDNs. Failures are modeled using hydraulic simulations to evaluate their impact on parameters such as pressure and flow. CNT metrics are then applied, including shortest path calculations between water sources and demand vertices to assess pipe importance, and vertex centrality metrics to evaluate node influence on the network. The results of the hydraulic simulations are compared with the outcomes of CNT-based analyses. Multi-criteria analysis is then employed to determine the asset maintenance priority, considering multiple failures and the associated impacts on the system. The results highlight a novel approach that shifts the focus from hydraulic state-based assessments to topology-driven analysis, reducing the influence of uncertainties inherent in water distribution network models.
Biosurfactant Production by Yarrowia lipolytica in Corn Steep Liquor-Based Media for Hydrocarbon Bioremediation
Authors: Lopes Juliana M. , Macedo Bruno P. , Sodré Thuane S. , Cayres Caroline A. , Ferreira Rachel M. , Fraga Jully L. , Coelho Maria Alice Z. , Amaral Priscilla F. F. , Ferreira Tatiana F.
Published: February 2025

Bioremediation using microorganisms offers a sustainable approach to addressing hydrocarbon contamination. This study explores biosurfactant production by Yarrowia lipolytica IMUFRJ 50682 during crude oil and asphaltene-free fraction biodegradation in corn steep liquor (CSL)-based media. By evaluating CSL concentrations (5–30 g/L) and combinations with glucose, molasses, and crude oil, this study demonstrates that CSL is an effective nutrient source for supporting microbial growth and biosurfactant production. The highest emulsification index (EI = 73.3%) was achieved with 20 g/L of CSL after 48 h, while media containing mixed carbon sources (glucose and crude oil) enhanced metabolic efficiency, yielding a maximum cell growth of 8 g/L after 150 h. Despite inhibiting cell growth, the asphaltene-free fraction promoted biosurfactant activity, with the EI reaching 35.8% after 264 h. The results emphasize the importance of pH control, with the optimal emulsification being observed at pH ~6. This work highlights the potential of CSL as a cost-effective and sustainable additive, advancing applications in bioremediation and biosurfactant production and contributing to the development of environmentally compatible hydrocarbon degradation strategies.
Mobile Robots for Environment-Aware Navigation: A Code-Free Approach with Topometric Maps for Non-Expert Users
Authors: Sarno Valeria , Stefanini Elisa , Grioli Giorgio , Pallottino Lucia
Published: February 2025

The growing use of mobile robots in unconventional environments demands new programming approaches to make them accessible to non-expert users. Indeed, traditional programming methods require specialized expertise in robotics and programming, limiting robots’ accessibility to a broader audience. End-user robot programming has emerged to overcome these limitations, aiming to simplify robot programming through intuitive methods. In this work, we propose a code-free approach for programming mobile robots to autonomously execute navigation tasks, i.e., reach a desired goal location from an arbitrary initial position. Our method relies on instructing the robot on new paths through demonstrations while creating and continuously updating a topometric map of the environment. Moreover, by leveraging the information gathered during the instruction phase, the robot can perceive slight environmental changes and autonomously make the best decision in response to unexpected situations (e.g., adjusting its path, stopping, or requesting user intervention). Experiments conducted in both simulated and real-world environments support the validity of our approach, as they show that the robot can successfully reach its assigned goal location in the vast majority of cases.
Radar–Rain Gauge Merging for High-Spatiotemporal-Resolution Rainfall Estimation Using Radial Basis Function Interpolation
Authors: Ryu Soorok , Song Joon Jin , Lee GyuWon
Published: February 2025

This study introduces methods for generating fused precipitation data by applying radial basis function (RBF) interpolation, which integrates radar reflectivity-based data with ground-based precipitation gauge measurements. Rain gauges provide direct point rainfall measurements near the ground, while radars capture the spatial variability of precipitation. However, radar-based estimates, particularly for extreme rainfall events, often lack accuracy due to their indirect derivation from radar reflectivity. The study aims to produce high-resolution gridded ground precipitation data by merging radar rainfall estimates with the precise rain gauge measurements. Rain gauge data were sourced from automated synoptic observing systems (ASOSs) and automatic weather systems (AWSs), while radar data, based on hybrid surface rainfall (HSR) composites, were all provided by the Korea Meteorological Administration (KMA). Although RBF interpolation is a well-established technique, its application to the merging of radar and rain gauge data is unprecedented. To validate the accuracy of the proposed method, it was compared with traditional approaches, including the mean field bias (MFB) adjustment method, and kriging-based methods such as regression kriging (RK) and kriging with external drift (KED). Leave-one-out cross-validation (LOOCV) was performed to assess errors by analyzing overall error statistics, spatial errors, and errors in rainfall intensity data. The results showed that the RBF-based method outperformed the others in terms of accuracy.
Advancements in Surface Acoustic Wave Gyroscope Technology in 2015–2024
Authors: Kukaev Alexander , Shalymov Egor , Shevchenko Sergey , Sorvina Maria , Venediktov Vladimir
Published: February 2025

Although the theoretical basis for surface acoustic wave gyroscopes (SAWGs) was first proposed in 1980, their design concepts are still under development. Nevertheless, these sensors are of a great interest in the potential market owing to their exceptional shock resistance, small size, low power consumption, and simple manufacturing process that ensures low cost. This paper aims to conscientiously investigate the ideas that have been proposed over the past decade in this area and evaluate the potential development required to bring SAWGs to market. It should be of interest for researchers in the field who might have missed some useful solutions that could be a missing piece in their own design, or for young researchers to inspire their creativity and open new research on the topic. Additionally, since some of the reviewed SAWG design concepts are based on a combination of several physical principles (for example, optical measurements), researchers from other fields may find useful solutions for incorporating surface acoustic wave techniques into their device concepts.
Stereo Event-Based Visual–Inertial Odometry
Authors: Wang Kunfeng , Zhao Kaichun , Lu Wenshuai , You Zheng
Published: February 2025

Event-based cameras are a new type of vision sensor in which pixels operate independently and respond asynchronously to changes in brightness with microsecond resolution, instead of providing standard intensity frames. Compared with traditional cameras, event-based cameras have low latency, no motion blur, and high dynamic range (HDR), which provide possibilities for robots to deal with some challenging scenes. We propose a visual–inertial odometry for stereo event-based cameras based on Error-State Kalman Filter (ESKF). The vision module updates the pose by relying on the edge alignment of a semi-dense 3D map to a 2D image, while the IMU module updates the pose using median integration. We evaluate our method on public datasets with general 6-DoF motion (three-axis translation and three-axis rotation) and compare the results against the ground truth. We compared our results with those from other methods, demonstrating the effectiveness of our approach.
Analysis of Structural Design Variations in MEMS Capacitive Microphones
Authors: Peng Tzu-Huan , Hsu Huei-Ju , Huang Jin H.
Published: February 2025

Different microstructures significantly affect the acoustic performance of MEMS capacitive microphones, particularly in key specifications of interest. This paper presents several microstructures, including rib-reinforced backplates, suspended diaphragms, and outer vent holes. Three MEMS microphone designs were implemented to analyze the impact of these microstructures. Equivalent circuit models corresponding to each design were constructed to simulate specifications such as sensitivity, signal-to-noise ratio (SNR), and low corner frequency (LCF), which were validated through experimental measurements. Finite Element Analysis (FEA) was also employed to calculate the acoustic damping of certain microstructures, the mechanical lumped parameters of the diaphragm, and the pre-deformation of the MEMS structure. A compressed air test (CAT) was conducted to evaluate the mechanical reliability of microphone samples. The results of simulations and measurements indicate that rib-reinforced backplates effectively improve microphone reliability, increasing the pass rate in CAT. Compared to fully clamped diaphragms, suspended diaphragms exhibit higher mechanical compliance, which enhances SNR performance but reduces AOP. Outer vent holes can achieve similar functionality to diaphragm vent holes, but their impact on improving AOP requires further design and testing.
Tilting Pad Thrust Bearing Fault Diagnosis Based on Acoustic Emission Signal and Modified Multi-Feature Fusion Convolutional Neural Network
Authors: Mao Meijiao , Jiang Zhiwen , Tan Zhifei , Xiao Wenqiang , Du Guangchao
Published: February 2025

Tilting pad thrust bearings are widely utilized in large rotating machinery such as steam turbines and hydraulic turbines. Defects in their shaft tiles directly impact lubrication characteristics, thereby influencing the overall safety performance of the entire unit. To address this issue, this paper presents a fault diagnosis method for tilting pad thrust bearings using a modified multi-feature fused convolutional neural network (MMFCNN). Initially, an experimental bench for diagnosing faults in tilting pad thrust bearings was developed to collect multi-channel acoustic emission (AE) signals from both normal and faulty pads. Subsequently, the squeeze-and-excitation (SE) module was employed to reallocate the weights of each channel and fuse the features of multi-channel signals. Learning was then conducted on the signal fused with multiple features using the inverse-add module and spanning convolution. Next, a comparative analysis was carried out among the CNN1D, ResNet, and DFCNN models, and the MMFCNN model proposed in this study. The results show that under consistent operating conditions, the MMFCNN model achieves an average fault diagnosis accuracy of 99.58% when utilizing AE signal data from tilting pad thrust bearings in four states as inputs. Furthermore, when different operational conditions are introduced, the MMFCNN model also outperforms other models in terms of accuracy.
Ultra-Sensitive Gas Sensor Based on CDs@ZnO
Authors: Xiao Shuo , Jiao Zheng , Yang Xuechun
Published: February 2025

Ethylene glycol (EG) is a colorless and odorless organic compound, which is an important industrial raw material but harmful to the environment and human health. Thus, it is necessary to develop high-performance sensing materials to monitor EG gas. Herein, sea urchin-shaped ZnO was successfully synthesized by a hydrothermal method. Subsequently, a series of carbon dot (CD)-modified ZnO nanocomposites were successfully prepared using a simple mechanical grinding method. The prepared CDs@ZnO-1 sensor exhibits an excellent response to EG gas, with a response value of 1356.89 to 100 ppm EG at the optimal operating temperature (220 °C). After five cycles of detection, the sensor can still maintain a stable response. The enhanced sensing performance of EG can be attributed to rich oxygen vacancies that are generated on the surface of CDs@ZnO, and the heterojunction formed between p-type CDs and n-type ZnO. This study provides inspiration for the development of high-response semiconductor metal oxide sensors.
Intersections of Big Data and IoT in Academic Publications: A Topic Modeling Approach
Authors: Căuniac Diana-Andreea , Cîrnaru Andreea-Alexandra , Oprea Simona-Vasilica , Bâra Adela
Published: February 2025

As vast amounts of data are generated from various sources such as social media, sensors and online transactions, the analysis of Big Data offers organizations the ability to derive insights and make informed decisions. Simultaneously, IoT connects physical devices, enabling real-time data collection and exchange that transforms interactions within smart homes, cities and industries. The intersection of these fields is essential, leading to innovations such as predictive maintenance, real-time traffic management and personalized solutions. Utilizing a dataset of 8159 publications sourced from the Web of Science database, our research employs Natural Language Processing (NLP) techniques and selective human validation to analyze abstracts, titles, keywords and other useful information, uncovering key themes and trends in both Big Data and IoT research. Six topics are extracted using Latent Dirichlet Allocation. In Topic 1, words like “system” and “energy” are among the most frequent, signaling that Topic 1 revolves around data systems and IoT technologies, likely in the context of smart systems and energy-related applications. Topic 2 focuses on the application of technologies, as indicated by terms such as “technologies”, “industry” and “research”. It deals with how IoT and related technologies are transforming various industries. Topic 3 emphasizes terms like learning and research, indicating a focus on machine learning and IoT applications. It is oriented toward research involving new methods and models in the IoT domain related to learning algorithms. Topic 4 highlights terms such as smart, suggesting a focus on smart technologies and systems. Topic 5 touches upon the role of digital chains and supply systems, suggesting an industrial focus on digital transformation. Topic 6 focuses on technical aspects such as modeling, system performance and prediction algorithms. It delves into the efficiency of IoT networks with terms like “accuracy”, “power” and “performance” standing out.
Cross-Modal Interaction Between Perception and Vision of Grasping a Slanted Handrail to Reproduce the Sensation of Walking on a Slope in Virtual Reality
Authors: Ohashi Yuto , Perusquía-Hernández Monica , Kiyokawa Kiyoshi , Sakata Nobuchika
Published: February 2025

Numerous studies have previously explored the perception of horizontal movements. This includes research on Redirected Walking (RDW). However, the challenge of replicating the sensation of vertical movement has remained a recurring theme. Many conventional methods rely on physically mimicking steps or slopes, which can be hazardous and induce fear. This is especially true when head-mounted displays (HMDs) obstruct the user’s field of vision. Our primary objective was to reproduce the sensation of ascending a slope while traversing a flat surface. This effect is achieved by giving the users the haptic sensation of gripping a tilted handrail similar to those commonly found on ramps or escalators. To achieve this, we developed a walker-type handrail device capable of tilting across a wide range of angles. We induced a cross-modal effect to enhance the perception of walking up a slope. This was achieved by combining haptic feedback from the hardware with an HMD-driven visual simulation of an upward-sloping scene. The results indicated that the condition with tactile presentation significantly alleviated fear and enhanced the sensation of walking uphill compared to the condition without tactile presentation.
Youth Are Not All the Same: On the Appropriateness and Limits of Participatory Methods in Youth Research
Authors: Butti Elena
Published: February 2025

The field of youth studies has traditionally promoted participatory methods, assuming that young people prefer creativity over standard methods like traditional ethnography or one-to-one interviews. However, my experience in Medellín, Colombia, reveals complications. While youth with strong ties to civil society and activism found comfort in participatory methods, youth who were out of school or in conflict with the law felt alienated by formalized processes and institutional spaces. Too often, participatory techniques homogenize youth perspectives, taking the views of socially engaged youth as representative of all youth. Researchers should instead acknowledge diverse youth experiences and employ different methods for different youth groups.
A Conceptual Framework for Sustainable Human Resource Management: Integrating Ecological and Inclusive Perspectives
Authors: Soekotjo Sundari , Sosidah  , Kuswanto Hary , Setyadi Antonius , Pawirosumarto Suharno
Published: February 2025

Purpose: This study proposes a conceptual model integrating ecological and inclusive perspectives within sustainable human resource management (SHRM). It introduces a novel framework that bridges gaps in the literature by integrating ecological sustainability and social inclusivity dimensions to enhance SHRM practices. Design/Methodology/Approach: A systematic literature review synthesizes Green HRM practices and diversity, equity, and inclusion (DEI) principles. The framework is built around three dimensions: ecological sustainability, social inclusivity, and integrated sustainability. Findings: The model demonstrates the synergies between ecological and inclusive practices in SHRM. It shows how Green HRM and DEI enhance employee engagement, organizational resilience, and sustainability performance. The study highlights the uniqueness of integrating ecological and inclusive dimensions in achieving comprehensive sustainability, offering a theoretical advancement in SHRM frameworks. Practical Implications: The framework provides a roadmap for organizations to implement sustainability initiatives, including eco-friendly recruitment, inclusive green training, and equitable work policies. Addressing environmental and social goals simultaneously improves organizational performance and employee well-being. Originality/Value: This research introduces a novel framework that integrates ecological and inclusive dimensions into SHRM. It is the first to emphasize the interplay between Green HRM and DEI as foundational components of sustainable HR practices, providing both theoretical and practical contributions.
Research on the Efficiency and Synergistic Effect of Industrial Green Innovation Development in the Beijing–Tianjin–Hebei Urban Agglomeration
Authors: Wu Hong , Wen Xuewei
Published: February 2025

This research centers on one of northern China’s most crucial economic regions—the Beijing–Tianjin–Hebei urban agglomeration. This paper primarily addresses the present circumstances, developments, and obstacles pertaining to industrial green development and industrial innovation in the region, with a particular focus on its role in fostering integrated economic and environmental growth. This study utilizes a global super-efficiency SBM model and a coupled coordination model, along with a panel data analysis technique, to determine the extent of green development, innovation, and green innovation collaboration in the Beijing–Tianjin–Hebei urban agglomeration cluster between 2018 and 2022. The study revealed that, despite notable advancements in industrial green development in the Beijing–Tianjin–Hebei urban agglomeration in recent years, the disparity in urban development persists, with some cities exhibiting a relatively low input–output ratio for green innovation. There is a pressing need to enhance overall efficiency through policy guidance and technical support. Furthermore, the study underscores the significance of bolstering regional collaboration and facilitating the sharing of resources and technological exchange to attain harmonized regional development.
How Do Start-Ups Develop Circular Business Models? A Systematic Literature Review
Authors: Petri Jaqueline Marchiore , de Francisco Antonio Carlos , Martins de Souza Adriano , de Lima José Donizetti , Trojan Flavio
Published: February 2025

Circular Economy (CE) models have gained attention in the academic community for their ability to promote sustainability and efficiency in resource use. It promotes advances in the traditional linear economy and offers innovative solutions to environmental issues. In this context, start-ups play a key role in implementing Circular Business Models (CBMs), leading the transition to more sustainable practices and positively impacts on the market and the environment. In the current academic literature, there are relevant studies on the implementation of the CE in traditional companies. Still, discussions on how start-ups transition from linear economy to circular business models remain limited. To address this gap, we conducted a systematic literature review on how start-ups design and adapt the linear economy to their circular business models. Our methodology followed the PRISMA 2020 protocol, thoroughly searching the Scopus, Science Direct, and Web of Science databases, resulting in 42 articles. The findings highlight the crucial role of Circular Start-Ups (CSUs) in the transition to a Circular Economy, identifying the challenges and opportunities they face and the internal and external barriers they need to overcome to ensure long-term sustainability. Furthermore, this study highlights the existing gaps in the literature and suggests key areas for future research.
Collaborative Optimization of Stope Cooling and Geothermal Energy Exploitation for Backfill Embedded Heat Exchanger
Authors: Wang Mei , Ni Wanying , Liu Lang , Zan Yutong , Li Jiahui
Published: February 2025

Backfillembedded heat exchanger (BEHE) are used for stope cooling during the mining process and for geothermal energy recovery during the long-term heat extraction stage. This study develops a three-dimensional BEHE model to optimize the pipe arrangement, considering both the immediate requirements of stope cooling and the long-term objectives of geothermal energy exploitation. To evaluate the effects of geothermal energy extraction and stope cooling, heat extraction per meter and average temperature in the stope area are used as criterion parameters. The results indicate that the cooling efficiency is positively correlated with the number of pipe layers and pipe diameter, while it is negatively correlated with pipe spacing, interlayer spacing, and the distance from the bottom of the backfill-embedded heat exchanger (BEHE) to the cold radiation surface. Geothermal energy extraction, on the other hand, is positively correlated with the number of pipe layers, interlayer spacing, and the distance from the bottom of the BEHE to the cold radiation surface. Considering both objectives, the optimal pipe arrangement is determined to be PLS = 1.0 m, S = 500 mm, F = 3, D = 0.05 m, and DN = 50 mm. Additionally, based on a comprehensive analysis of extensive calculation results, an empirical correlation for heat extraction per meter as a function of pipe arrangement parameters was derived.