bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation and Evaluation of Inhalable Microparticles with Improved Aerodynamic Performance and Dispersibility Using L-Leucine and Hot-Melt Extrusion
Authors: Jeong Jin-Hyuk , Kim Ji-Su , Choi Yu-Rim , Shin Dae Hwan , Kang Ji-Hyun , Kim Dong-Wook , Park Yun-Sang , Park Chun-Woong
Published: June 2024

Dry-powder inhalers (DPIs) are valued for their stability but formulating them is challenging due to powder aggregation and limited flowability, which affects drug delivery and uniformity. In this study, the incorporation of L-leucine (LEU) into hot-melt extrusion (HME) was proposed to enhance dispersibility while simultaneously maintaining the high aerodynamic performance of inhalable microparticles. This study explored using LEU in HME to improve dispersibility and maintain the high aerodynamic performance of inhalable microparticles. Formulations with crystalline itraconazole (ITZ) and LEU were made via co-jet milling and HME followed by jet milling. The LEU ratio varied, comparing solubility, homogenization, and aerodynamic performance enhancements. In HME, ITZ solubility increased, and crystallinity decreased. Higher LEU ratios in HME formulations reduced the contact angle, enhancing mass median aerodynamic diameter (MMAD) size and aerodynamic performance synergistically. Achieving a maximum extra fine particle fraction of 33.68 ± 1.31% enabled stable deep lung delivery. This study shows that HME combined with LEU effectively produces inhalable particles, which is promising for improved drug dispersion and delivery.
Construction of an Infectious DNA Clone of Grapevine Geminivirus A Isolate GN and Its Biological Activity in Plants Analyzed Using an Efficient and Simple Inoculation Method
Authors: Liu Can , Yu Shangzhen , Wang Jinying , Xie Yinshuai , Li Hanwei , Zhang Xueqing , Feng Chenlu , Zhang Wenhao , Cheng Yuqin
Published: June 2024

The pathogenicity of grapevine geminivirus A (GGVA), a recently identified DNA virus, to grapevine plants remains largely unclear. Here, we report a new GGVA isolate (named GGVAQN) obtained from grapevine ‘Queen Nina’ plants with severe disease symptoms. The infectious clone of GGVAQN (pXT-GGVAQN) was constructed to investigate its pathogenicity. Nicotiana benthamiana plants inoculated with GGVAQN by agroinfiltration displayed upward leaf curling and chlorotic mottling symptoms. A simple, quick, and efficient method for delivering DNA clones of GGVAQN into grapevine plants was developed, by which Agrobacterium tumefaciens cells carrying pXT-GGVAQN were introduced into the roots of in vitro-grown ‘Red Globe’ grape plantlets with a syringe. By this method, all ‘Red Globe’ grape plants were systemically infected with GGVAQN, and the plants exhibited chlorotic mottling symptoms on their upper leaves and downward curling, interveinal yellowing, and leaf-margin necrosis symptoms on their lower leaves. Our results provide insights into the pathogenicity of GGVA and a simple and efficient inoculation method to deliver infectious viral clones to woody perennial plants.
Morphological and Molecular Identification of Phytophthora capsici Isolates with Differential Pathogenicity in Sechium edule
Authors: Soto-Contreras Anell , Caamal-Chan María G. , Ramírez-Mosqueda Marco A. , Murguía-González Joaquín , Núñez-Pastrana Rosalía
Published: June 2024

Chayote (Sechium edule) is a crop of great economic and pharmaceutical importance in Mexico. Chayote is affected by Phytophthora capsici, which causes plant wilt and fruit rot. Three isolates of P. capsici (A1-C, A2-H, and A3-O) were obtained from three producing areas in Veracruz, Mexico. Morphometric characteristics of sporangia and the colony pattern on three different media were described. They were molecularly identified by amplification of the internal transcribed spacer region (ITS) and the partial sequence of cytochrome c oxidase subunit 1 (COI), sequences that were phylogenetically analyzed. The mating type, pathogenicity in S. edule fruits, and sensitivity to metalaxyl were determined. Isolate A1-C presented the largest sporangium; all sporangia were papillated, with different morphologies and pedicel lengths. All isolates showed different colony patterns: chrysanthemum (A1-C), stellate (A2-H), and petaloid (A3-O). The topology of the phylogenetic tree was similar for the ITS region and COI gene, the sequences of the three isolates clustered with sequences of the genus Phytophthora classified in group 2b, corroborating their identity as P. capsici. The mating type of isolates A1-C and A3-O was A2 and of isolate A2-H was A1. The pathogenicity test indicated that isolate A1-C was the most virulent and with intermediate sensitivity to metalaxyl. This work suggests that P. capsici isolates from various production areas in Mexico may exhibit morphological and virulence variability.
Albumin-Based Hydrogel Films Covalently Cross-Linked with Oxidized Gellan with Encapsulated Curcumin for Biomedical Applications
Authors: Tincu (Iurciuc) Camelia Elena , Daraba Oana Maria , Jérôme Christine , Popa Marcel , Ochiuz Lăcrămioara
Published: June 2024

Bovine serum albumin (BSA) hydrogels are non-immunogenic, low-cost, biocompatible, and biodegradable. In order to avoid toxic cross-linking agents, gellan was oxidized with NaIO4 to obtain new functional groups like dialdehydes for protein-based hydrogel cross-linking. The formed dialdehyde groups were highlighted with FT-IR and NMR spectroscopy. This paper aims to investigate hydrogel films for biomedical applications obtained by cross-linking BSA with oxidized gellan (OxG) containing immobilized β-cyclodextrin–curcumin inclusion complex (β-CD–Curc) The β-CD–Curc improved the bioavailability and solubility of Curc and was prepared at a molar ratio of 2:1. The film’s structure and morphology were evaluated using FT-IR spectroscopy and SEM. The swelling degree (Q%) values of hydrogel films depend on hydrophilicity and pH, with higher values at pH = 7.4. Additionally, the conversion index of -NH2 groups into Schiff bases increases with an increase in OxG amount. The polymeric matrix provides protection for Curc, is non-cytotoxic, and enhances antioxidant activity. At pH = 5.5, the skin permeability and release efficiency of encapsulated curcumin were higher than at pH = 7.4 because of the interaction of free aldehyde and carboxylic groups from hydrogels with amine groups from proteins present in the skin membrane, resulting in a better film adhesion and more efficient curcumin release.
Interfacial Interaction between Functionalization of Polysulfone Membrane Materials and Protein Adsorption
Authors: Yan Sheng , Qiu Yunren
Published: June 2024

This study that modified polysulfone membranes with different end-group chemical functionalities were prepared using chemical synthesis methods and experimentally characterized. The molecular dynamics (MD) method were used to discuss the adsorption mechanism of proteins on functionalized modified polysulfone membrane materials from a molecular perspective, revealing the interactions between different functionalized membrane surfaces and protein adsorption. Theoretical analysis combined with basic experiments and MD simulations were used to explore the orientation and spatial conformational changes of protein adsorption at the molecular level. The results show that BSA exhibits different variability and adsorption characteristics on membranes with different functional group modifications. On hydrophobic membrane surfaces, BSA shows the least stable configuration stability, making it prone to nonspecific structural changes. In addition, surface charge effects lead to electrostatic repulsion for BSA and reduce the protein adsorption sites. These MD simulation results are consistent with experimental findings, providing new design ideas and support for modifying blood-compatible membrane materials.
Investigation of Viscoelastic Guided Wave Properties in Anisotropic Laminated Composites Using a Legendre Orthogonal Polynomials Expansion–Assisted Viscoelastodynamic Model
Authors: Liu Hongye , Huang Ziqi , Yin Zhuang , Sun Maoxun , Bo Luyu , Li Teng , Tian Zhenhua
Published: June 2024

This study investigates viscoelastic guided wave properties (e.g., complex–wavenumber–, phase–velocity–, and attenuation–frequency relations) for multiple modes, including different orders of antisymmetric, symmetric, and shear horizontal modes in viscoelastic anisotropic laminated composites. To obtain those frequency–dependent relations, a guided wave characteristic equation is formulated based on a Legendre orthogonal polynomials expansion (LOPE)–assisted viscoelastodynamic model, which fuses the hysteretic viscoelastic model–based wave dynamics and the LOPE–based mode shape approximation. Then, the complex–wavenumber–frequency solutions are obtained by solving the characteristic equation using an improved root–finding algorithm, which leverages coefficient matrix determinant ratios and our proposed local tracking windows. To trace the solutions on the dispersion curves of different wave modes and avoid curve–tracing misalignment in regions with phase–velocity curve crossing, we presented a curve–tracing strategy considering wave attenuation. With the LOPE–assisted viscoelastodynamic model, the effects of material viscosity and fiber orientation on different guided wave modes are investigated for unidirectional carbon–fiber–reinforced composites. The results show that the viscosity in the hysteresis model mainly affects the frequency–dependent attenuation of viscoelastic guided waves, while the fiber orientation influences both the phase–velocity and attenuation curves. We expect the theoretical work in this study to facilitate the development of guided wave–based techniques for the NDT and SHM of viscoelastic anisotropic laminated composites.
Research on the Ghost Cell Immersed Boundary Method for Compressible Flow
Authors: Yang Bo , Song Moru , Zhu Guoming
Published: June 2024

In this paper, a kind of immersed boundary method, the discretized force with ghost cell method, is introduced to study compressible flow. Meanwhile, an adaptive mesh refinement scheme and a wall treatment for turbulent flow are proposed. With the help of in-house code, the accuracy of the method is verified based on several classic tests.
Effect of the Volume Concentration of Binary Mixed Particles on the Flow and Wear Characteristics of Centrifugal Pumps
Authors: Wang Yanping , Zu Yehang , He Tielin , Deng Xiaofeng , Li Yi
Published: June 2024

Solid–liquid two-phase centrifugal pumps are important fluid transport components in production and life. Most of the studies about the influence of solid-phase parameters on fluid transport mostly focus on single-component solid particles. In this work, two kinds of glass beads with particle sizes of 2 mm and 0.4 mm were used to study the effect of the binary mixed particle volume concentration on the internal flow and wear characteristics of a centrifugal pump. The flow distribution of the binary mixed particles in a centrifugal pump and the interactions between the particles and flow components at different volume concentrations (Cv = 5%, Cv = 7.5%, Cv = 10%, Cv = 12.5%, Cv = 15%) were studied using a Computational Fluid Dynamics-Discrete Element Method (CFD-DEM). The research results show that with the increase in particle volume concentration, the head and efficiency of the pump decrease. Additionally, the distributions of the particles with different concentrations in the impeller flow passage were obtained. Moreover, the coupling force of the flow field acting on the particles decreases with the increase in particle concentration and the time it takes to convey small particles decreases with the increase in concentration, while that of large particles decreases first and then increases. Furthermore, the contact force between the particles and the blade changes periodically with time, and the wear of the centrifugal pump is mainly concentrated on the pressure surface of the blade and the wall of the volute outlet side; the wear rate increases as the particle concentration increases.
Research on the Law of Crack Propagation in Oil Well Fracturing Process
Authors: Zhao Liang , Li Qi , Luo Xiangrong
Published: June 2024

In the field of oilfield fracturing development, a profound understanding of the evolution and propagation of damage during the fracturing process is crucial for preventing well water coning and channeling. This study aimed to unravel the complexity of damage evolution during fracturing and elucidate the causes of well water flooding phenomena. To accurately describe the damage propagation laws, a damage constitutive model considering compaction and post-peak correction parameters was established in this research. The model, through parameter adjustment, enhances the precision of stress calculation during the rock compaction phase and accounts for the stress degradation pattern subsequent to damage. This model was applied to simulate the damage evolution under various conditions in oil layer profiles and wellbore cross-sections, including the impact of different perforation angles, natural fracture patterns, and the ratio of longitudinal to transverse boundary pressures. The research concludes that well water channeling and flooding are primarily caused by damage propagation and the connectivity with adjacent water-bearing formations. The proposed rock damage constitutive model demonstrated an accuracy improvement of more than 3% compared to previous studies. Additionally, the study discovered that when the angle between the perforation section and the formation exceeds 30°, the risk of fracture propagation into adjacent layers increases, leading to an elevated risk of post-fracturing water flooding. The presence of natural fractures in the oil layer provides a conduit for damage propagation, accelerating the process of damage in the oil layer. Furthermore, the perforation angle and the ratio of boundary pressure loads during the fracturing process were identified as the main factors influencing the direction change of fracture propagation. The conclusions drawn from this study provide a scientific basis for preventing post-fracturing water channeling and flooding issues and offer new perspectives for the development of well fracturing technology, aiding in the resolution of water flooding problems associated with well fracturing.
MFPANet: Multi-Scale Feature Perception and Aggregation Network for High-Resolution Snow Depth Estimation
Authors: Zhao Liling , Chen Junyu , Shahzad Muhammad , Xia Min , Lin Haifeng
Published: June 2024

Accurate snow depth estimation is of significant importance, particularly for preventing avalanche disasters and predicting flood seasons. The predominant approaches for such snow depth estimation, based on deep learning methods, typically rely on passive microwave remote sensing data. However, due to the low resolution of passive microwave remote sensing data, it often results in low-accuracy outcomes, posing considerable limitations in application. To further improve the accuracy of snow depth estimation, in this paper, we used active microwave remote sensing data. We fused multi-spectral optical satellite images, synthetic aperture radar (SAR) images and land cover distribution images to generate a snow remote sensing dataset (SRSD). It is a first-of-its-kind dataset that includes active microwave remote sensing images in high-latitude regions of Asia. Using these novel data, we proposed a multi-scale feature perception and aggregation neural network (MFPANet) that focuses on improving feature extraction from multi-source images. Our systematic analysis reveals that the proposed approach is not only robust but also achieves high accuracy in snow depth estimation compared to existing state-of-the-art methods, with RMSE of 0.360 and with MAE of 0.128. Finally, we selected several representative areas in our study region and applied our method to map snow depth distribution, demonstrating its broad application prospects.
Lossy Compression of Single-channel Noisy Images by Modern Coders
Authors: Kryvenko Sergii , Lukin Vladimir , Vozel Benoit
Published: June 2024

Lossy compression of remote-sensing images is a typical stage in their processing chain. In design or selection of methods for lossy compression, it is commonly assumed that images are noise-free. Meanwhile, there are many practical situations where an image or a set of its components are noisy. This fact needs to be taken into account since noise presence leads to specific effects in lossy compressed data. The main effect is the possible existence of the optimal operation point (OOP) shown for JPEG, JPEG2000, some coders based on the discrete cosine transform (DCT), and the better portable graphics (BPG) encoder. However, the performance of such modern coders as AVIF and HEIF with application to noisy images has not been studied yet. In this paper, analysis is carried out for the case of additive white Gaussian noise. We demonstrate that OOP can exist for AVIF and HEIF and the performance characteristics in it are quite similar to those for the BPG encoder. OOP exists with a higher probability for images of simpler structure and/or high-intensity noise, and this takes place according to different metrics including visual quality ones. The problems of providing lossy compression by AVIF or HEIF are shown and an initial solution is proposed. Examples for test and real-life remote-sensing images are presented.
50 GHz Four-Port Coupling-Reduced Probe Card Utilizing Pogo Pins Housed in Custom Metallic Socket
Authors: Lee K. M. , Kim J. S. , Ahn S. , Park E. , Myeong J. , Kim M.
Published: June 2024

A design for a pogo-pin probe card featuring a metallic socket is proposed to eliminate signal leakage and coupling loss in a multi-port environment. The proposed metallic pogo-pin socket includes a metal wall structure between adjacent pogo pins, ensuring complete isolation. This metal wall offers an advantage in removing coupling issues between pogo pins that can occur with typical dielectric pogo-pin sockets. The designed probe card is fabricated as a prototype and verified for its performance. Measurement results using a test through line show that coupled power is minimized, providing a low-loss transmission performance of −2.14 dB to an RF chip at 50 GHz, all within a compact size. Although the dielectric spacer used to secure the pogo pins allows for some leakage, it can maintain a low coupling performance of under −15 dB in the millimeter-wave band. The prototype probe card can deliver an RF signal to a 5G circuit with a low loss of −0.7 dB at 28 GHz and −1.9 dB at 39 GHz frequency. The designed probe card is capable of transmitting multiple RF signals to the RF system without signal distortion in a multi-port environment.
Lifetime Prediction of Permanent Magnet Synchronous Motor in Selective Compliance Assembly Robot Arm Considering Insulation Thermal Aging
Authors: Chen Mingxu , Zhang Bingye , Li Haibo , Gao Xiang , Wang Jiajin , Zhang Jian
Published: June 2024

The direct-drive selective compliance assembly robot arm (SCARA) is widely used in high-end manufacturing fields, as it omits the mechanical transmission structures and has the advantages of high positioning accuracy and fast movement speed. However, due to the intensifying dynamic coupling problem of structures in the direct-drive SCARA, the permanent magnet synchronous motors (PMSMs) located at the joints will take on nonstationary loads, which causes excessive internal temperature and reduces the lifetime of PMSMs. To address these issues, the lifetime prediction of PMSMs is studied. The kinematic and dynamic models of the SCARA are established to calculate the torque curve required by the PMSM in specific typical motion tasks. Additionally, considering thermal stress as the main factor affecting lifetime, accelerated degradation tests are conducted on insulation material. Then, the reliability function of the PMSM is formulated based on the accelerated degradation model. Based on the parameters and working conditions of the PMSM, the temperature field distribution is obtained through simulation. The maximum temperature is used as the reference temperature to conduct reliability evaluation and lifetime prediction of the PMSM. The research results show that for a typical point-to-point task, the PMSM can run for 102,623 h while achieving the reliability requirement of 0.99.
Efficient Guided Wave Modelling for Tomographic Corrosion Mapping via One-Way Wavefield Extrapolation
Authors: Hassefras Emiel , Volker Arno , Verweij Martin
Published: June 2024

Mapping corrosion depths along pipeline sections using guided-wave-based tomographic methods is a challenging task. Accurate defect sizing depends heavily on the precision of the forward model in guided wave tomography. This model is fitted to measured data using inversion techniques. This study evaluates the effectiveness of a recursive extrapolation scheme for tomography applications and full waveform inversion. It employs a table-driven approach, with precomputed extrapolation operators stored across a spectrum of wavenumbers. This enables fast modelling for extensive pipe sections, approaching the speed of ray tracing while accurately handling complex velocity models within the full frequency band. This ensures an accurate representation of diffraction phenomena. The study examines the assumptions underlying the extrapolation approach, namely, the negligible reflection and conversion of modes at defects. In our tomography approach, we intend to use multiple wave modes—A0, S0, and SH1—and helical paths. The acoustic extrapolation method is validated through numerical studies for different wave modes, solving the 3D elastodynamic wave equation. Comparison with an experimentally measured single-mode wavefield from an aluminium plate with an artificial defect reveals good agreement.
A Multi-Scale Natural Scene Text Detection Method Based on Attention Feature Extraction and Cascade Feature Fusion
Authors: Li Nianfeng , Wang Zhenyan , Huang Yongyuan , Tian Jia , Li Xinyuan , Xiao Zhiguo
Published: June 2024

Scene text detection is an important research field in computer vision, playing a crucial role in various application scenarios. However, existing scene text detection methods often fail to achieve satisfactory results when faced with text instances of different sizes, shapes, and complex backgrounds. To address the challenge of detecting diverse texts in natural scenes, this paper proposes a multi-scale natural scene text detection method based on attention feature extraction and cascaded feature fusion. This method combines global and local attention through an improved attention feature fusion module (DSAF) to capture text features of different scales, enhancing the network’s perception of text regions and improving its feature extraction capabilities. Simultaneously, an improved cascaded feature fusion module (PFFM) is used to fully integrate the extracted feature maps, expanding the receptive field of features and enriching the expressive ability of the feature maps. Finally, to address the cascaded feature maps, a lightweight subspace attention module (SAM) is introduced to partition the concatenated feature maps into several sub-space feature maps, facilitating spatial information interaction among features of different scales. In this paper, comparative experiments are conducted on the ICDAR2015, Total-Text, and MSRA-TD500 datasets, and comparisons are made with some existing scene text detection methods. The results show that the proposed method achieves good performance in terms of accuracy, recall, and F-score, thus verifying its effectiveness and practicality.
Adaptive Low-Rank Tensor Estimation Model Based Multichannel Weak Fault Detection for Bearings
Authors: Jiang Huiming , Wu Yue , Yuan Jing , Zhao Qian , Chen Jin
Published: June 2024

Multichannel signals contain an abundance of fault characteristic information on equipment and show greater potential for weak fault characteristics extraction and early fault detection. However, how to effectively utilize the advantages of multichannel signals with their information richness while eliminating interference components caused by strong background noise and information redundancy to achieve accurate extraction of fault characteristics is still challenging for mechanical fault diagnosis based on multichannel signals. To address this issue, an effective weak fault detection framework for multichannel signals is proposed in this paper. Firstly, the advantages of a tensor on characterizing fault information were displayed, and the low-rank property of multichannel fault signals in a tensor domain is revealed through tensor singular value decomposition. Secondly, to tackle weak fault characteristics extraction from multichannel signals under strong background noise, an adaptive threshold function is introduced, and an adaptive low-rank tensor estimation model is constructed. Thirdly, to further improve the accurate estimation of weak fault characteristics from multichannel signals, a new sparsity metric-oriented parameter optimization strategy is provided for the adaptive low-rank tensor estimation model. Finally, an effective multichannel weak fault detection framework is formed for rolling bearings. Multichannel data from the repeatable simulation, the publicly available XJTU-SY whole lifetime datasets and an accelerated fatigue test of rolling bearings are used to validate the effectiveness and practicality of the proposed method. Excellent results are obtained in multichannel weak fault detection with strong background noise, especially for early fault detection.
A Guide to Measuring Heart and Respiratory Rates Based on Off-the-Shelf Photoplethysmographic Hardware and Open-Source Software
Authors: Stevens Guylian , Hantson Luc , Larmuseau Michiel , Heerman Jan R. , Siau Vincent , Verdonck Pascal
Published: June 2024

The remote monitoring of vital signs via wearable devices holds significant potential for alleviating the strain on hospital resources and elder-care facilities. Among the various techniques available, photoplethysmography stands out as particularly promising for assessing vital signs such as heart rate, respiratory rate, oxygen saturation, and blood pressure. Despite the efficacy of this method, many commercially available wearables, bearing Conformité Européenne marks and the approval of the Food and Drug Administration, are often integrated within proprietary, closed data ecosystems and are very expensive. In an effort to democratize access to affordable wearable devices, our research endeavored to develop an open-source photoplethysmographic sensor utilizing off-the-shelf hardware and open-source software components. The primary aim of this investigation was to ascertain whether the combination of off-the-shelf hardware components and open-source software yielded vital-sign measurements (specifically heart rate and respiratory rate) comparable to those obtained from more expensive, commercially endorsed medical devices. Conducted as a prospective, single-center study, the research involved the assessment of fifteen participants for three minutes in four distinct positions, supine, seated, standing, and walking in place. The sensor consisted of four PulseSensors measuring photoplethysmographic signals with green light in reflection mode. Subsequent signal processing utilized various open-source Python packages. The heart rate assessment involved the comparison of three distinct methodologies, while the respiratory rate analysis entailed the evaluation of fifteen different algorithmic combinations. For one-minute average heart rates’ determination, the Neurokit process pipeline achieved the best results in a seated position with a Spearman’s coefficient of 0.9 and a mean difference of 0.59 BPM. For the respiratory rate, the combined utilization of Neurokit and Charlton algorithms yielded the most favorable outcomes with a Spearman’s coefficient of 0.82 and a mean difference of 1.90 BrPM. This research found that off-the-shelf components are able to produce comparable results for heart and respiratory rates to those of commercial and approved medical wearables.
Elastic Self-Recovering Hybrid Nanogenerator for Water Wave Energy Harvesting and Marine Environmental Monitoring
Authors: Wang Qiuxiang , Yu Gao , Lou Ying , Li Mengfan , Hu Jiaxi , Li Jiaodi , Cui Weiqi , Yu Aifang , Zhai Junyi
Published: June 2024

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.
An Aeromagnetic Compensation Strategy for Large UAVs
Authors: Ye Liwei , Yu Zhentao , Zhang Yaxun , Chi Cheng , Cheng Pu , Chen Jie
Published: June 2024

Aeromagnetic surveys are widely used in geological exploration, mineral resource assessment, environmental monitoring, military reconnaissance, and other areas. It is necessary to perform magnetic compensation for interference in these fields. In recent years, large unmanned aerial vehicles (UAVs) have been more suitable for magnetic detection missions because of the greater loads they can carry. This article proposes some methods for the magnetic compensation of large multiload UAVs. Because of the interference of the large platform and instrument noise, the standard deviations (stds) of the compensation data used in this paper are larger. At the beginning of this article, using the traditional T-L model, we avoid the shortcomings of the anti-magnetic interference ability of triaxial magnetic gate magnetometers. The direction cosine information is obtained by using an inertial navigation system, the global positioning system, and a triaxial magnetic gate magnetometer. Then, we increase the amplitude of the maneuvers in the compensation process; this reduces the multicollinearity problems in the compensation matrix to a certain extent, but it also results in greater magnetic field interference. Lastly, we employ the method of Lasso regularization Newton iteration (LRNM). Compared to the traditional methods of least squares (LS) and singular value decomposition (SVD), LRNM provides improvements of 34% and 27%, respectively. In summary, this series of schemes can be used to perform effective compensation for large multi-load UAVs and improve the actual use of large UAVs, making them more accurate in the measurement of aeromagnetic survey data.
Time Use, Health, and Well-Being across the Life Cycle: A Gender Analysis
Authors: Matud M. Pilar , Bethencourt Juan Manuel , del Pino Mᵃ José , Hernández-Lorenzo D. Estefanía , Fortes Demelsa , Ibáñez Ignacio
Published: June 2024

Although time use is one of people’s most important resources, there are social forces and inequalities that shape how time is used. The aim of this research is to examine gender differences in time use from adolescence to old age and to analyze the association of such use with sociodemographic characteristics and with women’s and men’s health and well-being. A cross-sectional study was conducted with a sample of 5700 women (54.2%) and men (45.8%) from the Spanish general population, aged 14 to 85 years. Participants were assessed using five self-reported measures of time use, health, mental symptoms, psychological well-being, life satisfaction, social support, and masculine/instrumental and feminine/expressive traits. The results showed that although there were important differences in life cycle stage and occupation, women spent more time than men on housework, childcare, and caring for sick relatives, while men spent more time than women on enjoying activities and exercise. More time spent on housework was associated with worse health and well-being for women and more exercise with better health and well-being for both genders. It is concluded that gender is relevant to time use and the impact of different uses of time on health and well-being.
Can Green Finance Be a Regulator of “Water–Energy–Food” Synergy? Evidence from the Yangtze River Delta
Authors: Wang Yuchao
Published: June 2024

The synergistic relationship between water, energy, and food faces increasing challenges. Green finance as a policy tool promotes high-quality and efficient development of water, energy, and food subsystems. However, whether it can improve the synergistic relationship of “water–energy–food” (WEF) still needs to be studied. Using the panel data of 38 prefecture-level cities in the Yangtze River Delta (YRD) from 2013 to 2021, and network DEA and panel regression models, we study the impact of green finance on the level of synergy of “water–energy–food”. The results of the study show that green finance can promote the synergy level of “water–energy–food” in the Yangtze River Delta city cluster, which was first inhibited and then promoted from 2013 to 2021. The impacts of green finance on the efficiency of the three subsystems are also characterized by a “U” shape. However, linear impacts show differences, with green finance improving the efficiency of the water subsystem but not the energy and food subsystems. The implementation of China’s national strategies empowers green finance. The digital strategy, the “dual carbon” strategy, and the new urbanization strategy have increased the effectiveness of green finance in contributing to the level of water–energy–food synergy. Regional heterogeneity analysis shows that the promotion effect of green finance mainly exists in non-resource-based cities, non-main grain-producing areas, and non-cities along the South-to-North water diversion route and large cities. Finally, this paper puts forward relevant policy recommendations.
Considerations for Eco-LeanSat Satellite Manufacturing and Recycling
Authors: Buitrago-Leiva Jeimmy Nataly , Camps Adriano , Moncada Niño Alvaro
Published: June 2024

This research aims to contribute to the development of the Eco-LeanSat concept by focusing on a sustainable approach to satellite manufacturing and the repurposing of remaining satellite capabilities after failure. Despite satellites no longer being suitable for their original purposes, these remaining capabilities can find new applications. The study begins by identifying relevant innovative eco-design applications. Subsequently, it examines sustainability within the satellite lifecycle supply chain, categorizing it into four methods: (1) active debris removal, (2) transport logistics, (3) mission extension, and (4) repair and construction. Aligned with emerging trends in space activities, the study also considers future developments to maximize satellites’ potential to provide new services. Additionally, the research includes a description of a potential lean manufacturing process that encompasses logistic chains to support the development of a more sustainable space economy. Finally, the study concludes with a technological survey tracing the evolution of the development of the SmallSat and CubeSat platforms that identifies relevant innovative designs for a sustainable space environment.
Trend Changes and the Driving Forces of Environmental Indicators in Countries Worldwide: A Structural Change Analysis of Variations in CO2 Emissions and Eco-Efficiency
Authors: Ito Yasunori , Fujii Hidemichi
Published: June 2024

Many authors state that climate change is driven by increasing CO2 emissions worldwide. An understanding of the major driving forces affecting emissions over time in both developed and developing countries is important. Thus, in this study, structural break analysis is used to identify when the trends of environmental indicators—CO2 emissions and environmental efficiency (EE)—across countries worldwide change. Our findings revealed notable structural breaks occurring in countries in 1994, coinciding with ballooning fossil energy prices. Regarding CO2, 55 of 143 countries experienced a structural break. Furthermore, another wave of structural breaks emerged in 2014, corresponding to the implementation of CO2 emission reduction plans by certain nations. For CO2, 64 of 143 countries experienced a structural break. Upon detecting breakpoints and their trends, we utilized LMDI factor decomposition analysis to discern their driving factors, thereby elucidating the underlying dynamics. In Latin America and the Caribbean, most breakpoints were undesirable shifts, but recently, desirable shifts have increased in North America, Oceania, and Europe, which include many countries with high economic levels, improving energy-related factors. Sub-Saharan Africa can also be said to have undergone an undesirable shift regarding energy-related factors. This study clarifies the precise influences on the trend of CO2 emissions at the global level by identifying the point in time when there is a significant statistical, rather than a subjective, breakpoint.
Sustainable Value Chain for Sustainable Lending of State-Owned Banks in Indonesia
Authors: Manurung Kepas Antoni Adrianus , Siregar Hermanto , Fahmi Idqan , Hakim Dedi Budiman
Published: June 2024

Banks have enormous potential to support the achievement of sustainable development goals (SDGs) in accordance with their function as financial intermediaries through sustainable lending. However, the average national financing growth for the sustainable business activity category over the past four years is still 12%. The aim of this research is to identify the conditions of sustainable lending at state-owned conventional banks and analyze the influence of the value chain, economic performance, and ESG performance on sustainable lending. The research was conducted at state-owned commercial banks in Indonesia. The research utilized structural equation modeling (SEM). The SEM results of this study describe value chain, ESG performance (environmental, social, and governance), and economic performance and have direct and positive influences on sustainable lending, of which ESG performance has the biggest influence. As per each individual aspect, social orientation makes the biggest contribution toward sustainable lending.
Study on the Spatial Layout and Influencing Factors of Campsites in the Yellow River Basin
Authors: Fang Xiaofei , Tai Pengfei , Jiang Fugao
Published: June 2024

Based on the camping sites in the Yellow River Basin published by Amap, this study examines the spatial distribution pattern of camping sites using various indices, including the average nearest neighbor index, geographical concentration index, disequilibrium index, and kernel density estimation. The research findings are as follows: (1) Camping sites exhibit a highly significant agglomeration distribution, and the spatial scale presents a non-equilibrium characteristic of “east dense west sparse”. The distribution density of camping sites shows clear hot and cold spots, forming a general pattern of “one belt, one mass, two points”. The locations of these camping sites commonly follow the rule of “backing mountains, along roads, and accompanied by scenery”. (2) The spatial distribution of camping sites is influenced by both natural factors, such as elevation and air quality, and social factors, such as highway mileage and the number of high-level scenic spots. The impact of social factors is found to be more substantial than that of natural environmental factors.
Determining the Interaction of Social Sustainability with the Physical Environment: A Case Study of Adana, Turkey
Authors: Acik Etike Buse , Erdonmez Dincer Muyesser Ebru
Published: June 2024

Social sustainability has emerged as a critical factor in evaluating societal welfare and well-being. Consequently, researchers have initiated the development of a theoretical framework to delineate the components of social sustainability, achieving notable progress in this endeavor. However, the interplay between the social dimension and the environmental and economic dimensions remains insufficiently explored in user experiences, posing challenges in integrating social sustainability into preliminary design parameters in the built environment and resulting in socially inefficient spaces. This study seeks to elucidate the relationship between social sustainability and the environment while devising a measurement methodology that encompasses the physical environment. Concentrating on public spaces, pivotal in daily experiences and reflective of individual interactions, the research was conducted across five distinct public spaces in the Seyhan district of Adana. Methodologically, the study employed field research, preliminary examination, and statistical analysis. Data collection techniques, including surveys, observations, and measurements, were utilized to unveil statistically significant correlations between social sustainability and the physical environment of public spaces. Consequently, this study delineates the dimensions of these relationships and translates them into actionable design data.
Research on Path Optimization for Collaborative UAVs and Mothership Monitoring of Air Pollution from Port Vessels
Authors: Shen Lixin , Sun Jie , Yang Dong
Published: June 2024

The seriousness of vessel air pollution has forced the International Maritime Organization (IMO) to introduce a series of relevant laws and regulations. This paper proposes a monitoring scheme based on the synergistic operation of motherships and UAVs. This scheme innovatively adopts a harbor sea patrol vessel or the other official vessel (mothership) as the mobile power supply base for UAVs and realizes efficient and accurate monitoring of vessel air pollution in the pre-monitored area at sea by carrying multiple UAVs. The focus of this paper is on the path optimization problem for multi-UAV collaboration with mothership (MUCWM) monitoring, where the objective is to minimize the total monitoring time for MUCWM. The following three main aspects are studied in this paper: (1) multi-UAV monitoring path optimization; (2) the collaboration mechanism between the mothership and multiple UAVs; and (3) mothership traveling path optimization. In order to effectively solve the above problems, this thesis constructs a path optimization model for multi-UAV collaborative mothership monitoring of air pollution from vessels in port waters; solves the model using the improved adaptive differential evolution (IADE) algorithm; and verifies the effectiveness of the model and the algorithm by using the position data in the Automatic Identification System (AIS) of vessels in Ningbo Zhoushan Port. Through the performance comparison and sensitivity analysis of the algorithm, it is confirmed that the algorithm can effectively solve the path planning problem of the collaborative operation between the mothership and multiple UAVs. The research results in this paper not only help to reduce the air pollution level of harbor vessels and improve the efficiency of sea cruising but also play an important supporting role in the enforcement of relevant emission regulations.
Harnessing Local Dynamics for Upgrading Informal Settlements: The Ezbit Hegazi Experience with the ALEXU-CoE-SUG
Authors: Al-Hagla Khalid
Published: June 2024

Informal settlements pose multifaceted challenges to urban development, necessitating a reconsideration of traditional upgrading approaches. This study examines the integration of the street-led approach within the Ezbit Hegazi informal settlement, leveraging the Alexandria University Centre of Excellence for Smart Urban Governance’s (ALEXU-CoE-SUG’s) innovative framework. It highlights the centrality of ‘Demand for Good Governance’ (DFGG) practices in bridging the gap between governmental (supply-side) and community (demand-side) objectives, fostering a collaborative urban upgrading process. Through an in-depth case study analysis, this paper reveals the potential of aligning governmental agendas with local aspirations, emphasizing the importance of local dynamics in sustainable urban development. The findings indicate that integrating bottom-up community engagement with top-down institutional support can lead to more effective and sustainable urban regeneration. The study concludes that a combined approach, leveraging both grassroots initiatives and formal governance structures, is crucial for the successful upgrading of informal settlements. The findings contribute to the urban studies literature by providing insights into the synergies between supply and demand perspectives in the context of informal settlement upgrading, offering implications for policy and practice in similar urban settings globally.
Clustering Mixed-Type Data via Dirichlet Process Mixture Model with Cluster-Specific Covariance Matrices
Authors: Burhanuddin Nurul Afiqah , Ibrahim Kamarulzaman , Zulkafli Hani Syahida , Mustapha Norwati
Published: June 2024

Many studies have shown successful applications of the Dirichlet process mixture model (DPMM) for clustering continuous data. Beyond continuous data, in practice, one can expect to see different data types, including ordinal and nominal data. Existing DPMMs for clustering mixed-type data assume a strict covariance matrix structure, resulting in an overfit model. This article explores a DPMM for mixed-type data that allows the covariance matrix to differ from one cluster to another. We assume an underlying latent variable framework for ordinal and nominal data, which is then modeled jointly with the continuous data. The identifiability issue on the covariance matrix poses computational challenges, thus requiring a nonstandard inferential algorithm. The applicability and flexibility of the proposed model are illustrated through simulation examples and real data applications.
Analysis from the Functional Viewpoint of a Single-Cylinder Horizontal Steam Engine with a Crosshead Trunk Guide through Engineering Graphics
Authors: Rojas-Sola José Ignacio , Barranco-Molina Juan Carlos
Published: June 2024

This paper explores a historical innovation created by Henry Muncaster: a stationary steam engine featuring a single-cylinder horizontal design with a crosshead trunk guide. Through the application of engineering graphics techniques, we have elucidated the functioning of this invention by developing a 3D CAD model based on the original drawings published in Model Engineer magazine in 1957. However, the geometric modeling process faced challenges due to missing and erroneous dimensions for several components. Consequently, dimensional, geometric, and movement constraints were applied to ensure the coherence and functionality of the 3D CAD model, alongside conducting an interference analysis. Ultimately, the proper alignment of the cylinder and crosshead was ascertained, which is crucial for maintaining uniform forces and motions within the steam engine. This alignment is pivotal for achieving balanced operation, minimizing vibrations, and enhancing the overall efficiency of the invention.