bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecological Restoration Process of El Hito Saline Lagoon: Potential Biodiversity Gain in an Agro-Natural Environment
Authors: Nuévalos-Tello Carlos , Hernández-Torres Daniel , Sardinero-Roscales Santiago , Pajares-Guerra Miriam , Chilton Anna , Jiménez-Ballesta Raimundo
Published: November 2024

In the global context of biodiversity and ecosystem services loss, the integration of agriculture with ecological restoration is crucial. This study presents the biodiversity value (Bv) index for the first time as a tool for decision-making and securing funding for future restoration projects. The Bv index was used to assess biodiversity values in both restored natural habitats and agricultural areas in the saline lagoon of El Hito, a natural reserve located within an agricultural landscape in central Spain. Additionally, we estimated biodiversity gains from habitat transitions and explored the relationship between biodiversity, soil pH, and salinity. Sustainable agricultural practices, combined with ecological restoration methods, can lead to synergistic actions that reduce the potential detrimental effects of agriculture. Our results show that transitioning from agricultural to natural habitats consistently increases biodiversity. Among agricultural practices, multiannual vegetated fallows had the highest Bv values. Restoration led to a continuous biodiversity improvement, with the exception of the final transition from permanent pastures to Elymus 1410, which showed a slight decline in biodiversity. We also found that higher soil salinity and pH were associated with greater biodiversity values, likely due to historical agricultural practices that favored areas with lower salinity and pH for higher productivity. Salinity and pH act as limiting factors for biodiversity; therefore, agricultural plots with lower salinity and pH, particularly those adjacent to natural habitats, are expected to yield greater biodiversity gains if restored.
A Comprehensive Framework for Monitoring and Providing Early Warning of Resource and Environmental Carrying Capacity Within the Yangtze River Economic Belt Based on Big Data
Authors: Tong Cheng , Jin Yanhua , Liang Bangli , Ye Yang , Bao Haijun
Published: November 2024

The Yangtze River Economic Belt (YREB), spanning 11 provinces and municipalities across China, is of paramount importance due to its high economic development and strategic role in national distribution. However, the YREB, which has experienced rapid economic growth, faces challenges resulting from its previously expansive development model, including regional resource and environmental issues. Consequently, a systematic analysis encompassing socio-economic, ecological, and resource-environmental aspects is vital for a comprehensive and quantitative understanding of the YREB’s overall condition. This study explores resource and environmental carrying capacity (RECC) by constructing an integrated framework that includes remote sensing data, geographic information data and social statistical data, which allows for a precise analysis of RECC dynamics from 2010 to 2020. The findings demonstrate an upward trend in the overall quality of RECC from 2010 to 2020, achieving higher grades over time. However, there is significant spatial heterogeneity, with a notable decrease in RECC levels moving from the eastern to the western regions within the YREB. Moreover, low-level RECC areas situated in the northwest of the YREB, show a trend of moving toward regions of higher altitude from 2010 to 2020 based on analysis using the standard deviation ellipse (SDE) method. When considering to the three major urban agglomerations within the YREB, overall RECC in middle and lower agglomerations is generally stable and on an upward trend while cities in upper reaches exhibit significant variation and fluctuations, highlighting them as areas requiring future focus. Therefore, specific indicators were applied to monitor RECC risk for each of these three agglomerations, respectively, after which optimized strategies could be proposed based on different early warning levels. Ultimately this study allows local authorities to implement timely and effective interventions to mitigate risks and promote sustainable development.
Effect of Continuous Intake of Lactobacillus salivarius WB21 on Tissues Surrounding Implants: A Double-Blind Randomized Clinical Trial
Authors: Taniguchi Yusuke , Suzuki Nao , Kakura Kae , Tanabe Kazunari , Ito Ryutaro , Kashiwamura Tadahiro , Fujimoto Akie , Naito Marie , Yoneda Masahiro , Hanioka Takashi , Kido Hirofumi
Published: November 2024

Objective: This study aimed to improve the health of peri-implant tissues through continuous intake of Lactobacillus salivarius WB21 (LSWB21) tablets. Methods: A double-blind, randomized controlled trial was conducted with 23 maintenance patients who had generally healthy oral peri-implant tissues. Participants were divided into a test group (n = 12) receiving LSWB21 tablets and a control group (n = 11) receiving placebos. All patients took one tablet three times daily for 2 months. Evaluation measures included modified Gingival Index (mGI), modified Plaque Index (mPI), modified Bleeding Index (mBI), salivary secretory IgA, and oral symptoms assessed at baseline, 1 month, and 2 months. Results: After 2 months, significant improvements in the mGI, mPI, and mBI were observed in the test group; significant improvement in the mPI was observed in the control group. Changes in the mGI over 2 months significantly differed between the groups (p = 0.038), and multiple regression analysis confirmed the effectiveness of LSWB21 in reducing the mGI (p = 0.034). Subjective symptoms such as bad breath in the test group and tongue symptoms in the control group also significantly improved. Conclusion: Continuous intake of LSWB21 may be beneficial for stabilizing peri-implant tissue. Trial registration: UMIN000039392 (UMIN-CTR).
Interactions of Laser-Induced Thermal Plume with Liquid–Air Interfaces in Straight-Chain Alcohols
Authors: Anderson Reese W. , Anderson Allison I. , Gealy Mark W. , Ulness Darin J.
Published: November 2024

This study investigates the dynamics of thermal plumes interacting with the liquid–air interface in straight-chain alcohols and their mixtures using a photothermal imaging technique based on thermal lensing. This method enables the indirect measurement of temperature gradients via changes in refractive index caused by localized laser heating. Employing a collimated laser beam, the results show the formation and evolution of cylindrical heated zones and their interactions with the liquid–air interface. The study reveals that, while some alcohols exhibit stable surface behaviors, others demonstrate complex dynamical behaviors, including strong stable steady-state oscillations. The findings contribute to understanding fluid dynamics in molecular liquids near their liquid–air interfaces.
Research on the Sealing Performance of Segmented Annular Seals Based on Fluid–Solid–Thermal Coupling Model
Authors: He Zhenpeng , Jia Lanhao , Si Jiaxin , Li Ning , Wang Hongyu , Li Baichun , Guo Yuhang , Zhao Shijun , Luo Wendong
Published: November 2024

High-speed segmented annular seals are often subjected to friction and wear, and the groove design on the sealing surface can effectively suppress this loss. For the purpose of improving the sealing performance, the segmented annular seal models of three structures are established, and the accuracy of the calculation model is verified by comparing with the previous results. Through fluid–solid–thermal coupled analysis, the flow field characteristics, opening characteristics, and leakage characteristics of the segmented annular seal under high working condition parameters were studied. The results show that the setting of the shallow groove forms the hydrodynamic effect by squeezing and hindering the flow of fluid in the clearance. The increase in rotational speed and pressure difference can promote the increase in the opening force, while the temperature has no significant effect on the opening of the seal. Seals with ladder-like grooves have the best opening performance, and seals without shallow grooves are already difficult to open under conditions of high pressure difference and large spring forces. Temperature and pressure difference are the main factors affecting the leakage of the seal, while the influence of the rotation speed is small. When the sealed pressure increases from 0.15 MPa to 0.4 MPa, the maximum increase in the leakage of the seal with specific groove design is 4.657 times the original. As the temperature rises from 420 K to 620 K, the maximum decrease in the three structures is up to 22.9%. Among the seals of the three structures, seals with ladder-like grooves have medium leakage. This research will contribute to the improvement of research methods for the sealing performance of segmented annular rings, especially for the evaluation of groove design and opening characteristics.
Residual Stress Distribution in Dievar Tool Steel Bars Produced by Conventional Additive Manufacturing and Rotary Swaging Processes
Authors: Izák Josef , Strunz Pavel , Levytska Olena , Németh Gergely , Šaroun Jan , Kocich Radim , Pagáč Marek , Tuharin Kostyantyn
Published: November 2024

The impact of manufacturing strategies on the development of residual stresses in Dievar steel is presented. Two fabrication methods were investigated: conventional ingot casting and selective laser melting as an additive manufacturing process. Subsequently, plastic deformation in the form of hot rotary swaging at 900 °C was applied. Residual stresses were measured using neutron diffraction. Microstructural and phase analysis, precipitate characterization, and hardness measurement—carried out to complement the investigation—showed the microstructure improvement by rotary swaging. The study reveals that the manufacturing method has a significant effect on the distribution of residual stresses in the bars. The results showed that conventional ingot casting resulted in low levels of residual stresses (up to ±200 MPa), with an increase in hardness after rotary swaging from 172 HV1 to 613 HV1. SLM-manufactured bars developed tensile hoop and axial residual stresses in the vicinity of the surface and large compressive axial stresses (−600 MPa) in the core due to rapid cooling. The subsequent thermomechanical treatment via rotary swaging effectively reduced both the surface tensile (to approximately +200 MPa) and the core compressive residual stresses (to −300 MPa). Moreover, it resulted in a predominantly hydrostatic stress character and a reduction in von Mises stresses, offering relatively favorable residual stress characteristics and, therefore, a reduction in the risk of material failure. In addition to the significantly improved stress profile, rotary swaging contributed to a fine grain (3–5 µm instead of 10–15 µm for the conventional sample) and increased the hardness of the SLM samples from 560 HV1 to 606 HV1. These insights confirm the utility of rotary swaging as a post-processing technique that not only reduces residual stresses but also improves the microstructural and mechanical properties of additively manufactured components.
Constitutive Modelling Analysis and Hot Deformation Process of AISI 8822H Steel
Authors: Elanany Khaled , Borek Wojciech , Ebied Saad
Published: November 2024

This study used the Gleeble 3800 thermomechanical simulator to examine the hot deformation characteristics of AISI 8822H steel. The main goal was to understand the alloy’s behaviour under various thermomechanical settings, emphasising temperature ranges between 1173 K and 1323 K and strain rates from 0.01 s−1 to 10 s−1. This study aimed to enhance the alloy’s manufacturing process by offering a thorough understanding of the material’s response to these conditions. Four various constitutive models—Arrhenius-type, Johnson–Cook, modified Johnson–Cook, and Trimble—were used in a comprehensive technique to forecast flow stress values in order to meet the study’s goals. The accuracy of each model in forecasting the behaviour of the material under the given circumstances was assessed. A thorough comparison investigation revealed that the Trimble model was the most accurate model allowing prediction of material behaviour, with the maximum correlation factor (R = 0.99) and at least average absolute relative error (1.7%). On the other hand, the Johnson–Cook model had the least correlation factor (R = 0.92) and the maximum average absolute relative error (32.2%), indicating that it was the least accurate because it could not account for all softening effects.
Effect of Hydrophobic Fumed Silica on Bending Strength of Sodium Silicate-Bonded Sand Cores
Authors: Li Yunbo , Zhang Huarui , Chen Jiulong , Xiang Ting , Cheng Ying , Zhang Hu
Published: November 2024

Inorganic sand cores involving sodium silicate binder and microsilica have environmental advantages during the casting process of aluminum alloy. Nevertheless, the bending strength of sodium silicate-bonded sand (SSBS) needs to be further improved. In this research, the effect of hydrophobic fumed silica on the bending strength of sand cores was studied. The experimental results revealed that hydrophobic fumed silica with the addition of 0.050 wt.% can be adopted as an optimal modifier to enhance the bending strength of SSBS. According to scanning electron microscope and spectroscopy techniques, dense bonding bridges and a complex Si–O–Si network containing specific silicon molecules with a silicon atom bonded to three other silicon atoms contribute to the excellent bending strength, with a 53.1% increase in cold strength (24 h) compared to a commercial sample of a modified sand core. Meanwhile, the newly formed Si–O–Al chemical bond plays a crucial role in increasing the bending strength of sand cores.
A Review on Properties of Electrodeposited Nickel Composite Coatings: Ni-Al2O3, Ni-SiC, Ni-ZrO2, Ni-TiO2 and Ni-WC
Authors: Zellele Daniel M. , Yar-Mukhamedova Gulmira Sh. , Rutkowska-Gorczyca Malgorzata
Published: November 2024

Nickel electrodeposition is a widely utilized method for creating thin films on various substrates with various desirable attributes. Recently, there has been a growing interest in developing nickel composite coatings that incorporate additional elements or particles into the nickel matrix to enhance their properties. These composite coatings offer superior corrosion resistance, hardness, tribological, and other functional benefits compared with pure nickel coatings. Some of the recent advancements in electrodeposited nickel composite coatings include improved wear resistance, enhanced mechanical properties, and better corrosion resistance. Researchers have discovered that reinforcing the nickel matrix with Al2O3, SiC, ZrO2, WC, and TiO2 particles to obtain nickel composite coatings can significantly enhance all these important functional properties of various substrates. The uniform distribution of these particles within the nickel matrix acts as a barrier to wear and tear. Studies have also shown that nickel composite coatings with those particles exhibit superior mechanical properties, including increased hardness. These particles help to refine the grain size of the nickel matrix and deter movements that may cause defects, leading to greater mechanical strength. Moreover, nickel composite coatings offer improved protection against corrosion compared with pure nickel coatings. This review provides a detailed discussion of nickel composite coatings with regard to their comparative advantages compared with pure nickel coatings on different substrates.
Multiscale Wettability of Microtextured Irregular Surfaces
Authors: Peta Katarzyna
Published: November 2024

Surface microgeometry created by the energy of electric discharges is related to surface wetting behavior. These relationships change depending on the scale of observation. In this work, contact angles correlated with the surface complexity of AA 6060 after electro-discharge machining were analyzed at different observation scales. This research focuses on the methodology of selecting the best scales for observing wetting phenomena on irregular surfaces, as well as indicating the topographic characterization parameters of the surface in relation to the scales. Additionally, the geometric features of the surface that determine the contact angle were identified. In this study, the surfaces of an aluminum alloy are rendered using focus variation 3D microscopy and described by standardized ISO, area-scale, and length-scale parameters. The research also confirms that it is possible to design surface wettability, including its hydrophilicity and hydrophobicity, using electrical discharge machining parameters. The static and dynamic behavior of liquids on surfaces relevant to contact mechanics was also determined.
Hooked-End Steel Fibers Affecting Damping Ratio of Modified Self-Compacting Concrete with Rubber and Marble/Granite Additions
Authors: Gomes Amauri Ernesto , Gachet Luisa A. , Lintz Rosa Cristina C. , de L. N. M. Melo Mirian , Osório Wislei R.
Published: November 2024

The aim of this investigation is to determine the effects of hooked-end steel fibers on both the fresh and hardened properties of modified self-compacting concretes (SCC). For this purpose, the steel fibers are associated with other residue contents (i.e., marble, granite, and rubber). These concatenated material contents constitute a novelty since no investigations are reported. It is found that with the increase in rubber content, a better ability to absorb energy is observed. This indicates that a good alternative to structural material is provided. Fresh properties are evaluated by using flow, T500 time, V-funnel, and J-ring methods. The mechanical behavior is evaluated in terms of compressive strength, tensile strength, static and dynamic modulus of elasticity, and damping ratio. Experimental results of the water absorption, porosity, and density are also attained. It is also found that an SCC mixture containing steel fiber, marble/granite residue, and rubber content is a potential mixture to be considered when designing in SCC associated with an improved damping ratio. Although the rubber content decreases the mechanical behavior and slump flow, the concatenated utilization of marble/granite residues and steel fiber contents provides a slight improvement in the damping result. An environmental benefit can also be associated since cement consumption is decreased with marble additions.
Form-Stable Phase-Change Materials Using Chemical Vapor Deposition-Derived Porous Supports: Carbon Nanotube/Diatomite Hybrid Powder and Carbon Nanotube Sponges
Authors: Lamastra Francesca Romana , Bragaglia Mario , Paleari Lorenzo , Nanni Francesca , Fabborcino Francesco , Scarselli Manuela
Published: November 2024

In this work, two types of chemical vapor deposition (CVD)-derived porous supporting materials consisting of CNTs–decorated diatomite (CNT/DE) and CNT sponges (CNS) were developed to prepare novel form-stable phase-change material (PCM) composites by impregnation, using polyethylene glycol (PEG) as the PCM. The CNT/DE support matrix showed highly entangled nanotubes (the weight ratio of CNTs to DE was 0.16) over and inside the porous structure of diatomite, giving the hybrid matrix an electrical response. The CNS that resulted was mainly composed of bent and interconnected CNTs forming a three-dimensional highly porous structure. XPS and FTIR results revealed that CNTs in both the supporting materials have a moderate amount of oxygen-containing functional groups. Both hosts allow for high PEG loading (about 75 wt%) without showing any PCM leakage during melting. Both form-stable PCM composites showed high thermal reliability upon a hundred melting–solidification DSC cycles (PEG/CNT/DE latent heat is 86 ± 4 J/g and PEG/CNS latent heat is 100 ± 2 J/g; melting temperature 34 °C). An analytical model was used to evaluate the passive cooling performance of the systems, simulating the thermal behaviour of a building wall containing the confined PCM in the hosts, resulting in a reduction in required cooling power of about 10%. The overall results suggest that the developed form-stable PCM composites could be considered promising additive materials for the production of building envelopes with thermal energy storage capability.
Analysis and Validation of Lightweight Carriage Structures Using Basalt Fiber Composites
Authors: Wang Xianglin , Yuan Shaoqing , Sun Wei , Hao Wenfeng , Zhang Xufeng , Yang Zhongjia
Published: November 2024

With the growth in road transport volume and increasingly stringent environmental regulations, the use of lightweight dump trucks not only reduces fuel consumption but also enhances transport efficiency, aligning with the principles of green development. It has now become a key focus in the field of heavy-duty vehicle research. The carriage is located at the rear of the dump truck, connected to the chassis, and serves as the box for carrying cargo, making its strength and durability crucial. As one of the important components of heavy-duty vehicles, the carriage accounts for 15% to 25% of the total vehicle weight, and its weight reduction efficiency is significantly higher than that of other vehicle systems. This paper presents a prefabricated carriage structure based on basalt fiber composite panels combined with a metal frame, achieving the lightweight design of the carriage while meeting the stringent requirements for high load-bearing capacity and strength in heavy-duty vehicles, and significantly improving assembly and production efficiency. Given the complex working environment and diverse loading demands of heavy vehicles, this study incorporates real operating conditions of dump trucks, utilizing theoretical calculations and design analyses to construct finite element models for various scenarios, followed by detailed numerical simulations in ABAQUS (2023). Additionally, a bending–shear test of the side panel was designed and conducted to validate the accuracy of the finite element model, with comparative analysis performed between simulation results and experimental data, effectively assessing the safety and reliability of this lightweight composite carriage structure. The results indicate that the designed carriage not only meets the strength, stiffness, and impact resistance requirements of current heavy-duty carriages but also significantly reduces the carriage weight. This research provides scientific reference and engineering value for the application of composite materials in the lightweight design and structural optimization of dump trucks.
Polyacrylonitrile Composites Blended with Asphalt as a Low-Cost Material for Producing Synthetic Fibers: Rheology and Thermal Stability
Authors: Pripakhaylo Artem V. , Tsypakin Alexei A. , Klam Anton A. , Andreichev Andrei L. , Timerbaev Andrei R. , Shapovalova Oksana V. , Magomedov Rustam N.
Published: November 2024

The results of rheological studies and thermal analysis of polymer compositions based on polyacrylonitrile copolymers (PAN) of different molecular weights and asphalt isolated by n-pentane solvent deasphalting are presented. It was found that the asphalt content in mixtures with PAN at the level of 10–30 wt.% improves the rheological properties of the polymer composite melt. In particular, the temperatures of extrusion and molding of fibers tend to reduce, and the time during which the melt retains its rheological characteristics necessary for extrusion is notably increased, from 43 to 92 min. Thermal analysis by DSC revealed no effect of asphalt additive in an amount of up to 30 wt.% on radical PAN cyclization and the subsequent stage of fiber stabilization. Our study proved the possibility of preparing polymer composites based on PAN and asphalt suitable for extrusion and eventual molding of continuous filaments of synthetic fibers with reduced cost of production.
Influence of Ag-18Cu-10Zn Filler Material on Microstructure and Properties of Laser-Welded Al/Cu Dissimilar Butt Joints
Authors: He Ziquan , Liu Fei , Gao Ping , Pang Lihui , Su Yong
Published: November 2024

Dissimilar welding between aluminum and copper poses significant challenges, primarily due to differences in their thermal and mechanical properties, resulting in brittle intermetallic compounds, limited joint strength, and high electrical resistivity. This study aims to overcome these issues by employing Ag-18Cu-10Zn filler material and optimizing laser power with a focus on improving joint strength and electrical conductivity. The results indicate that the incorporation of silver and zinc enhances the phase composition and microstructure of the weld. By forming solid solution phases such as Ag2Al and Cu5Zn8, the brittle Al2Cu phase commonly found in traditional Al/Cu welding is replaced. This not only promotes the heterogeneous nucleation of fine silver-rich grains but also restricts the excessive growth of silver-poor grains, resulting in a uniform distribution of fine grains throughout the weld. These modifications contribute to both fine-grain strengthening and dispersion strengthening. At an optimal laser power of 750 W, joint strength reaches 109 MPa, while joint resistivity decreases to 3.19 μΩ·cm, 12.6% lower than that of the aluminum alloy base material. This study proposes a process for achieving highly conductive, reliable Al/Cu dissimilar metal joints, potentially impacting the aluminum–copper connections in battery modules for new energy vehicles.
Prediction of Concrete Compressive Strength Based on ISSA-BPNN-AdaBoost
Authors: Li Ping , Zhang Zichen , Gu Jiming
Published: November 2024

Strength testing of concrete mainly relies on physical experiments, which are not only time-consuming but also costly. To solve this problem, machine learning has proven to be a promising technological tool in concrete strength prediction. In order to improve the accuracy of the model in predicting the compressive strength of concrete, this paper chooses to optimize the base learner of the ensemble learning model. The position update formula in the search phase of the sparrow search algorithm (SSA) is improved, and piecewise chaotic mapping and adaptive t-distribution variation are added, which enhances the diversity of the population and improves the algorithm’s global search and convergence abilities. Subsequently, the effectiveness of the improvement strategy was demonstrated by comparing improved sparrow search algorithm (ISSA) with some commonly used intelligent optimization algorithms on 10 test functions. A back propagation neural network (BPNN) optimized with ISSA was used as the base learner, and the adaptive boosting (AdaBoost) algorithm was used to train and integrate multiple base learners, thus establishing an adaptive boosting algorithm based on back propagation neural network improved by the improved sparrow search algorithm (ISSA-BPNN-AdaBoost) concrete compressive strength prediction model. Then comparison experiments were conducted with other ensemble models and single models on two strength prediction datasets. The experimental results show that the ISSA-BPNN-AdaBoost model exhibits excellent results on both datasets and can accurately perform the prediction of concrete compressive strength, demonstrating the superiority of ensemble learning in predicting concrete compressive strength.
Design and Simulation of Portable Paving Vehicle for Straw Checkerboard Barriers
Authors: Peng Zuntao , Jia Mingrun , Fang Jingrong , Jiang Feng
Published: November 2024

Paving straw checkerboard barriers in the desert is an efficient measure of wind break and sand fixation. Generally, straw checkerboard barriers are paved manually. Focusing on the low automation level of straw checkerboard barrier paving, a portable paving vehicle for straw checkerboard barriers was designed in this paper. First, the portable paving vehicle for straw checkerboard barriers was designed using SolidWorks, and the design contents include a grass insertion mechanism, an intermittent transmission mechanism, a metamorphic mechanism, and motor and power supply. Then, the load test of the grass insertion mechanism was carried out to determine the maximum force load of 25 N during the grass insertion process, and the strength of the rocker and the horizontal slide rod were checked. Among them, the safety factor of the rocker rod and the horizontal slide rod were 1 and 1.5, respectively, and the allowable stress of the rocker rod and the horizontal slide rod was 27.3 MPa and 205 MPa. The maximum stresses of 0.92 MPa and 67 MPa were less than the allowable stresses, which meet the strength requirements. In order to verify the design principle and the results of the strength check, the grass insertion mechanism, rocker, and horizontal slide rod were analyzed by using ABAQUS. The results show that the grass insertion mechanism has an obvious rapid return characteristic, which is in agreement with the design principle. At the same time, the maximum stress of the rocker rod and the horizontal slide rod was 1 MPa and 36 MPa, respectively, which meets the strength requirements. Finally, the physical prototype was manufactured and its running state was verified. The results show that the physical prototype can pave the straw checkerboard sand barrier on the sand normally, and the portable paving vehicle for straw checkerboard barriers can be a reference for other sand-control vehicles and provide an effective way of paving straw checkerboard barriers to control desertification.
Design and Rapid Prototyping of Deformable Rotors for Amphibious Navigation in Water and Air
Authors: Du Chengrong , Zhao Dongbiao
Published: November 2024

This paper aims to report the design of a mechanism to drive a propeller to deform between an aerial and one aquatic shape. This mechanism can realize the deformation of blade angle, radius, blade twist angle distribution and blade section thickness. Inspired by the Kresling origami structure and utilizing its rotation-folding motion characteristics, a propeller hub structure with variable blade angle is designed. A blade deformation unit (S-unit) with extensional-torsional kinematic characteristics is designed through the motion analysis of a spherical four-bar mechanism. A rib support structure fixed to the linkages of the s-unit is designed to achieve the change in blade section thickness. Based on motion analysis, the coordinate transformation method has been used to establish the relationship between propeller shape and deformation mechanism. The deformation of blade extension, blade twist distribution, and blade section thickness are analyzed. The deformation ability of the proposed structure can be verified then by kinematic simulation and rapid prototyping based on 3-D printing. It is proved that the proposed mechanism is applicable to deformable propeller design. The rapid prototype testing validates the stable motion of the mechanism. However, due to the relatively large self-weight of the structure, the blade has a slight deformation. In the subsequent work, the structural strength issue needs to be emphasized.
Prior Knowledge-Informed Graph Neural Network with Multi-Source Data-Weighted Fusion for Intelligent Bogie Fault Diagnosis
Authors: Huang Yuanxing , Cui Bofeng , Mao Xianqun , Yang Jinsong
Published: November 2024

The current multi-source fusion fault diagnosis algorithm rarely considers the information correlation of multi-sensor networks and the important difference between multi-sensors. Aiming at this challenge, we propose an intelligent fault identification method for high-speed railway bogie based on the graph neural network embedded with prior knowledge, which brings the spatial information of the sensor network into the diagnosis algorithm and re-weights each sensor according to the diagnosis results. Firstly, the time–domain correlation of vibration signals between bogie sensor networks is calculated as the prior knowledge. Then, based on the spatial topological relationship of the sensors, the graph correlation matrix of the network is established. Further, the importance of each sensor is dynamically analyzed and updated together with the training process. The proposed method is tested on a high-precision bogie test bed, and the experimental results demonstrate the effectiveness and superiority of the proposed method.
Overview of IoT Security Challenges and Sensors Specifications in PMSM for Elevator Applications
Authors: Vlachou Eftychios I. , Vlachou Vasileios I. , Efstathiou Dimitrios E. , Karakatsanis Theoklitos S.
Published: November 2024

The applications of the permanent magnet synchronous motor (PMSM) are the most seen in the elevator industry due to their high efficiency, low losses and the potential for high energy savings. The Internet of Things (IoT) is a modern technology which is being incorporated in various industrial applications, especially in electrical machines as a means of control, monitoring and preventive maintenance. This paper is focused on reviewing the use PMSM in lift systems, the application of various condition monitoring techniques and real-time data collection techniques using IoT technology. In addition, we focus on different categories of industrial sensors, their connectivity and the standards they should meet for PMSMs used in elevator applications. Finally, we analyze various secure ways of transmitting data on different platforms so that the transmission of information takes into account possible unwanted instructions from exogenous factors.
Node-Centric Pruning: A Novel Graph Reduction Approach
Authors: Shokouhinejad Hossein , Razavi-Far Roozbeh , Higgins Griffin , Ghorbani Ali A.
Published: November 2024

In the era of rapidly expanding graph-based applications, efficiently managing large-scale graphs has become a critical challenge. This paper introduces an innovative graph reduction technique, Node-Centric Pruning (NCP), designed to simplify complex graphs while preserving their essential structural properties, thereby enhancing the scalability and maintaining performance of downstream Graph Neural Networks (GNNs). Our proposed approach strategically prunes less significant nodes and refines the graph structure, ensuring that critical topological properties are maintained. By carefully evaluating node significance based on advanced connectivity metrics, our method preserves the topology and ensures high performance in downstream machine learning tasks. Extensive experimentation demonstrates that our proposed method not only maintains the integrity and functionality of the original graph but also significantly improves the computational efficiency and preserves the classification performance of GNNs. These enhancements in computational efficiency and resource management make our technique particularly valuable for deploying GNNs in real-world applications, where handling large, complex datasets effectively is crucial. This advancement represents a significant step toward making GNNs more practical and effective for a wide range of applications in both industry and academia.
Cyclic Structure, Vertex Degree and Number of Linear Vertices in Minimal Strong Digraphs
Authors: Arcos-Argudo Miguel , Lacalle Jesús , Pozo-Coronado Luis M.
Published: November 2024

Minimal Strong Digraphs (MSDs) can be regarded as a generalization of the concept of tree to directed graphs. Their cyclic structure and some spectral properties have been studied in several articles. In this work, we further study some properties of MSDs that have to do with bounding the length of the longest cycle (regarding the number of linear vertices, or the maximal in- or outdegree of vertices); studying whatever consequences from the spectral point of view; and giving some insight about the circumstances in which an efficient algorithm to find the longest cycle contained in an MSD can be formulated. Among other properties, we show that the number of linear vertices contained in an MSD is greater than or equal to the maximal (respectively minimal) in- or outdegree of any vertex of the MSD and that the maximal length of a cycle contained in an MSD is lesser than or equal to 2n−m where n,m are the order and the size of the MSD, respectively; we find a bound for the coefficients of the characteristic polynomial of an MSD, and finally, we prove that computing the longest cycle contained in an MSD is an NP-hard problem.
On Unicyclic Graphs with a Given Number of Pendent Vertices or Matching Number and Their Graphical Edge-Weight-Function Indices
Authors: Ali Akbar , Alanazi Abdulaziz M. , Hassan Taher S. , Shang Yilun
Published: November 2024

Consider a unicyclic graph G with edge set E(G). Let f be a real-valued symmetric function defined on the Cartesian square of the set of all distinct elements of G’s degree sequence. A graphical edge-weight-function index of G is defined as If(G)=∑xy∈E(G)f(dG(x),dG(y)), where dG(x) denotes the degree a vertex x in G. This paper determines optimal bounds for If(G) in terms of the order of G and a parameter z, where z is either the number of pendent vertices of G or the matching number of G. The paper also fully characterizes all unicyclic graphs that achieve these bounds. The function f must satisfy specific requirements, which are met by several popular indices, including the Sombor index (and its reduced version), arithmetic–geometric index, sigma index, and symmetric division degree index. Consequently, the general results obtained provide bounds for several well-known indices.
An Efficient Simulated Annealing Algorithm for the Vehicle Routing Problem in Omnichannel Distribution
Authors: Yu Vincent F. , Lin Ching-Hsuan , Maglasang Renan S. , Lin Shih-Wei , Chen Kuan-Fu
Published: November 2024

A variant of the vehicle routing problem (VRP) known as the Vehicle Routing Problem in Omnichannel Retailing Distribution Systems (VRPO) has recently been introduced in the literature, driven by the increasing adoption of omnichannel logistics in practice. The VRPO scenario involves a large retailer managing several stores, a depot, and a homogenous fleet of vehicles to meet the demands of both stores and online customers. This variant falls within the class of VRPs that consider precedence constraints. Although the vehicle routing problem in omnichannel retailing distribution (VRPO) has been addressed using a few heuristic and metaheuristic approaches, the use of Simulated Annealing (SA) remains largely unexplored in the pickup and delivery problem (PDP) literature, both before and after the rise of omnichannel logistics. This article introduces the Efficient Simulated Annealing (ESA) algorithm, demonstrating its suitability in generating new benchmark solutions for the VRPO. In experiments with sixty large instances, ESA significantly outperformed two previous algorithms, discovering new best-known solutions (BKSs) in fifty-nine out of sixty cases. Additionally, ESA demonstrated superior efficiency in 68.3% of the test cases in terms of reduced computational times, showcasing its higher effectiveness in handling complex VRPO instances.
Statistical Modeling to Improve Time Series Forecasting Using Machine Learning, Time Series, and Hybrid Models: A Case Study of Bitcoin Price Forecasting
Authors: Qureshi Moiz , Iftikhar Hasnain , Rodrigues Paulo Canas , Rehman Mohd Ziaur , Salar S. A. Atif
Published: November 2024

Bitcoin (BTC-USD) is a virtual currency that has grown in popularity after its inception in 2008. BTC-USD is an internet communication network that makes using digital money, including digital payments, easy. It offers decentralized clearing of transactions and money supply. This study attempts to accurately anticipate the BTC-USD prices (Close) using data from September 2023 to September 2024, comprising 390 observations. Four machine learning models—Multi-layer Perceptron, Extreme Learning Machine, Neural Network AutoRegression, and Extreme-Gradient Boost—as well as four time series models—Auto-Regressive Integrated Moving Average, Auto-Regressive, Non-Parametric Auto-Regressive, and Simple Exponential Smoothing models—are used to achieve this end. Various hybrid models are then proposed utilizing these models, which are based on simple averaging of these models. The data-splitting technique, commonly used in comparative analysis, splits the data into training and testing data sets. Through comparison testing with training data sets consisting of 30%, 20%, and 10%, the present work demonstrated that the suggested hybrid model outperforms the individual approaches in terms of error metrics, such as the MAE, RMSE, MAPE, SMAPE, and direction accuracy, such as correlation and the MDA of BTC. Furthermore, the DM test is utilized in this study to measure the differences in model performance, and a graphical evaluation of the models is also provided. The practical implication of this study is that financial analysts have a tool (the proposed model) that can yield insightful information about potential investments.
Semiparametric Analysis of Additive–Multiplicative Hazards Model with Interval-Censored Data and Panel Count Data
Authors: Wang Tong , Li Yang , Sun Jianguo , Wang Shuying
Published: November 2024

In survival analysis, interval-censored data and panel count data represent two prevalent types of incomplete data. Given that, within certain research contexts, the events of interest may simultaneously involve both data types, it is imperative to perform a joint analysis of these data to fully comprehend the occurrence process of the events being studied. In this paper, a novel semiparametric joint regression analysis framework is proposed for the analysis of interval-censored data and panel count data. It is hypothesized that the failure time follows an additive–multiplicative hazards model, while the recurrent events follow a nonhomogeneous Poisson process. Additionally, a gamma-distributed frailty is introduced to describe the correlation between the failure time and the count process of recurrent events. To estimate the model parameters, a sieve maximum likelihood estimation method based on Bernstein polynomials is proposed. The performance of this estimation method under finite sample conditions is evaluated through a series of simulation studies, and an empirical study is illustrated.
Maximizing Collagen Yield from Underutilized Lumpfish (Cyclopterus lumpus) Skins by Optimizing Pre-Cleaning and Extraction Methods
Authors: Scheja Judith Maria , Sigurðarson Jens Jakob , Ólafsson Halldór Gunnar , Einarsson Hjörleifur
Published: November 2024

Female lumpfish (Cyclopterus lumpus) are a primary target of commercial fishery for their roe, a substitute for caviar. The remaining carcasses are underutilized rest raw material. The pre-treatment and acid extraction conditions of collagen from lumpfish skins were optimized. Full factorial design was used to optimize the alkali pre-treatment conditions with NaOH. The optimal conditions were X1 = 0.1 M (NaOH concentration), X2 = 6 h (NaOH treatment time), X3 = 4 °C (treatment temperature) and X4 = 1:5 (w/v, solid to liquid ratio). Optimized conditions for collagen extraction with acetic acid were investigated using a Box–Behnken design. The result suggested a concentration of 0.9 M acetic acid, treatment temperature of 21 °C, a treatment time of 36 h in a total of 2 volumes of acid. Combined optimized effects resulted in a collagen yield of 45% (DW/DW) with high purity (>90%) and a high hydroxyproline content (7.9%). A scale-up experiment (starting with 45 kg) showed that the yield was somewhat lower (18–25%). Enzyme hydrolysis of skin after acetic acid extraction added another 23% (DW/DW) to the yield and enzyme hydrolysis of precleaned skins resulted in 60% (DW/DW).
Marine Lectins and Lectin-like Proteins as Promising Molecules Targeting Aberrant Glycosylation Signatures in Human Brain Tumors
Authors: Buriak Ivan , Kumeiko Vadim
Published: November 2024

Glycosylation is a ubiquitous and the most structurally diverse post-translational modification of proteins. High levels of phenotypic heterogeneity in brain tumors affect the biosynthetic pathway of glycosylation machinery, resulting in aberrant glycosylation patterns. Traditionally, unique glycocode readers, carbohydrate-binding proteins, have been used to identify differentially expressed carbohydrate determinants associated with the tumor cell surface. However, identifying novel distinctive glycosylation signatures in brain tumors requires the timely development of molecular tools capable of targeting them. We classified marine-derived lectins and lectin-like molecules according to their ability to cover aberrant glycosylation patterns in brain tumors to encourage exploration of the potential of these molecules for precision diagnostics and personalized therapy.
Paternal Contributions to Recurrent Pregnancy Loss: Mechanisms, Biomarkers, and Therapeutic Approaches
Authors: Kaltsas Aris , Zikopoulos Athanasios , Kojovic Vladimir , Dimitriadis Fotios , Sofikitis Nikolaos , Chrisofos Michael , Zachariou Athanasios
Published: November 2024

Background and Objectives: Recurrent pregnancy loss (RPL) affects numerous couples worldwide and has traditionally been attributed mainly to maternal factors. However, recent evidence highlights significant paternal influences on pregnancy viability and outcomes. This review aims to comprehensively examine male contributions to pregnancy loss, focusing on underlying mechanisms, novel biomarkers, and integrated strategies for improved reproductive success. Materials and Methods: A comprehensive narrative review was conducted by searching databases including PubMed and Embase for the literature published from January 2004 to October 2024. Studies focusing on paternal influences in RPL—encompassing oxidative stress, genetic and epigenetic mechanisms, health conditions, lifestyle factors, environmental exposures, and advancements in sperm proteomics—were included. Inclusion criteria were peer-reviewed articles in English that directly addressed paternal factors in RPL; studies not meeting these criteria were excluded. Results: The review identified that paternal factors such as advanced age, metabolic and cardiovascular health issues, chronic diseases, lifestyle habits (e.g., smoking, alcohol consumption, poor diet), and environmental exposures significantly affect sperm integrity through mechanisms like oxidative stress, DNA fragmentation, and epigenetic alterations. Advanced paternal age and poor health conditions are associated with increased risks of miscarriage and adverse pregnancy outcomes. Novel sperm proteomic biomarkers have been identified, offering potential for enhanced diagnostics and personalized interventions. Integrated approaches involving multidisciplinary assessments, preventive strategies, and genetic counseling are essential for effectively addressing RPL. Conclusions: Integrating paternal factors into clinical evaluations is crucial for effectively addressing recurrent pregnancy loss. Recognizing and modifying paternal risk factors through lifestyle changes, medical interventions, and environmental management can improve pregnancy outcomes. The findings underscore the need for incorporating paternal assessments into standard care and highlight the importance of future research focusing on standardizing diagnostic protocols, expanding studies on paternal contributions, and integrating proteomic biomarkers into clinical practice to facilitate personalized treatment strategies.