bluuebunny/crossref_metadata_2025 huggingface dataset:
Full-Length Transcriptomes Reconstruction Reveals Intraspecific Diversity in Hairy Vetch (Vicia villosa Roth) and Smooth Vetch (V. villosa Roth var. glabrescens)
Authors: Kong Weiyi , Geng Bohao , Yan Wenhui , Xia Jun , Xu Wenkai , Zhao Na , Guo Zhenfei
Published: November 2024

Hairy vetch (Vicia villosa Roth) and smooth vetch (V. villosa Roth var. glabrescens) are important cover crops and legume forage with great economic and ecological values. Due to the large and highly heterozygous genome, full-length transcriptome reconstruction is a cost-effective route to mining their genetic resources. In this study, a hybrid sequencing approach combining SMRT and NGS technologies was applied. The results showed that 28,747 and 40,600 high-quality non-redundant transcripts with an average length of 1808 bp and 1768 bp were generated from hairy vetch and smooth vetch, including 24,864 and 35,035 open reading frames (ORFs), respectively. More than 96% of transcripts were annotated to the public databases, and around 25% of isoforms underwent alternative splicing (AS) events. In addition, 987 and 1587 high-confidence lncRNAs were identified in two vetches. Interestingly, smooth vetch contains more specific transcripts and orthologous clusters than hairy vetch, revealing intraspecific transcript diversity. The phylogeny revealed that they were clustered together and closely related to the genus Pisum. Furthermore, the estimation of Ka/Ks ratios showed that purifying selection was the predominant force. A putative 3-dehydroquinate dehydratase/shikimate dehydrogenase (DHD/SDH) gene underwent strong positive selection and might regulate phenotypic differences between hairy vetch and smooth vetch. Overall, our study provides a vital characterization of two full-length transcriptomes in Vicia villosa, which will be valuable for their molecular research and breeding.
Green Chemically Synthesized Iron Oxide Nanoparticles–Chitosan Coatings for Enhancing Strawberry Shelf-Life
Authors: Sani Ayesha , Hassan Dilawar , Chanihoon Ghulam Qadir , Melo Máximo Dulce Viridiana , Sánchez-Rodríguez Elvia Patricia
Published: November 2024

To enhance the preservation of strawberries, a novel coating formulation was developed using chitosan (CH) and iron oxide (IO) nanoparticles (NPs) supplemented with ginger and garlic extracts and combined with varying concentrations of 1%, 2%, and 3% Fe3O4 NPs. The results of XRD revealed an average crystalline size of 48.1 nm for Fe3O4 NPs. SEM images identified Fe3O4 NPs as bright spots on the surface of the fruit, while FTIR confirmed their presence by detecting specific functional groups. Additional SEM analysis revealed clear visibility of CH coatings on the strawberries. Both uncoated and coated strawberry samples were stored at room temperature (27 °C), and quality parameters were systematically assessed, including weight loss, firmness, pH, titratable acidity (TA), total soluble solids (TSSs), ascorbic acid content, antioxidant activity, total reducing sugars (TRSs), total phenolic compounds (TPCs), and infection rates. The obtained weight loss was 21.6% and 6% for 1.5% CH and 3% IO with 1.5% CH, whereas the obtained infection percentage was 19.65% and 13.68% for 1.5% CH and 3% IO with 1.5% CH. As strawberries are citric fruit, 3% IO with 1.5% CH contains 55.81 mg/100 g ascorbic acid. The antioxidant activity for 1.5% CH coated was around 73.89%, whereas 3% IO with 1.5% CH showed 82.89%. The studies revealed that coated samples showed better results, whereas CH that incorporates Fe3O4 NP coatings appears very promising for extending the shelf life of strawberries, preserving their quality and nutritional value during storage and transportation.
Polymeric Membranes for Liquid Separation: Innovations in Materials, Fabrication, and Industrial Applications
Authors: Sahu Lalit Ranjan , Yadav Diksha , Borah Debasish , Gogoi Anuranjit , Goswami Subrata , Hazarika Gauri , Karki Sachin , Borpatra Gohain Moucham , Sawake Saurabh V. , Jadhav Sumit V. , Chatterjee Soumya , Ingole Pravin G.
Published: November 2024

Polymeric membranes have emerged as a versatile and efficient liquid separation technology, addressing the growing demand for sustainable, high-performance separation processes in various industrial sectors. This review offers an in-depth analysis of recent developments in polymeric membrane technology, focusing on materials’ advancements, innovative fabrication methods, and strategies for improving performance. We discuss the underlying principles of membrane separation, selecting suitable polymers, and integrating novel materials, such as mixed-matrix and composite membranes, to enhance selectivity, permeability, and antifouling properties. The article also highlights the challenges and limitations associated with polymeric membranes, including stability, fouling, and scalability, and explores potential solutions to overcome these obstacles. This review aims to guide the development of next-generation polymeric membranes for efficient and sustainable liquid separation by offering a detailed analysis of current research and future directions.
Optimization of Metal Injection Molding Processing Conditions for Reducing Black Lines and Meld Lines in Bone Plates
Authors: Lin Chao-Ming , Yen Po-Yu , Tan Chung-Ming
Published: November 2024

The bone plates used in surgery to assist in fracture healing are often manufactured by metal injection molding (MIM) using a feedstock material consisting of metal powder and polymer binder. However, if the local powder concentration is too low or uneven, black lines may be formed, which impair the product appearance. Furthermore, if the melding temperature is too low, it can lead to meld lines and reduced mechanical properties. Accordingly, this study combines mold flow analysis simulations with the single-objective Taguchi robust design method to determine the MIM processing conditions that optimize the powder concentration and melding temperature. Grey relational analysis (GRA) is then used to establish the processing conditions that simultaneously optimize both MIM objectives. It is found that the processing conditions determined through GRA provide a significant improvement over the original design; however, the experimental outcomes are poorer than those achieved through the single-objective Taguchi experiments since the melt temperature effect suppresses that of all the other processing conditions. Consequently, a robust multi-criteria optimization (RMCO) technique is employed to improve the optimization outcome by identifying the dominant factors in the MIM process and fixing them at optimal levels to redesign the Taguchi experiments to optimize the non-primary factors. It is shown that the RMCO method eliminates interference between the multiple factors and hence provides an improved multi-objective optimization outcome. Overall, the integrated framework proposed in this study advances the optimization of the MIM process for bone plates and leads to improved product quality and performance.
Sustainable Transformation of Cellulose-Containing Textile Waste into Multifunctional Panels with Tailored FR-Lignocellulosic Fibres
Authors: Lamoudan Hamid , Abenghal Lahbib , Belosinschi Dan , Brouillette François , Dolez Patricia , Panneton Raymond , Fonrouge Cécile
Published: November 2024

The fashion industry significantly impacts the environment, mainly through the substantial generation of waste textiles fostered by fast fashion business models. This study introduces an innovative approach to textile waste management by recycling waste textiles without the use of chemical or mechanical treatments. Herein, we developed a method adhering to the principles of circular economy to transform these textile wastes into high-quality construction panels using a papermaking process. This method not only provides a sustainable solution to reduce landfill dependency but also enhances resource efficiency in the construction industry. The fabricated panels, composed of a blend of 45% textile waste microfibres and 55% fire-retardant fibres, exhibit several advantageous properties. They feature a low apparent density ranging between 170–180 kg/m3 and a low thermal conductivity coefficient of 0.047 W/m∗K at 50 kPa. It revealed that phosphorylated fibres not only provide flame-retardant properties, but they also significantly improve the mechanical properties of the panels. For example, load at break increases from 12.4 to 81.1 N, stress at break from 0.44 to 3.59 MPa, and E-modulus from 29.2 to 198.8 MPa after the addition of these 55% fibres. Moreover, these panels successfully met the criteria set by international standards for construction products satisfying the fire test, EN ISO 11925-2. These characteristics make the panels superior options for sustainable construction materials, offering enhanced fire resistance and insulation properties, which are critical to meet modern building standards. They mark a pivotal step towards sustainable construction and waste reduction in the fashion industry.
Investigation of the Weldability of 3D-Printed Multi-Material Materials (PLA and PLA Wood) Using Friction Stir Welding
Authors: Şahin Gökhan , Anaç Nergizhan , Koçar Oğuz
Published: November 2024

In the industry sector, it is very common to have different types of dissimilar materials on the same construction rather than products made from a single type of material. Traditional methods (welding, mechanical fastening, and adhesive bonding) and hybrid techniques (friction stir welding, weld bonding, and laser welding) are used in the assembly or joining of these materials. However, while joining similar types of materials is relatively easy, the process becomes more challenging when joining dissimilar materials due to the structure and properties of the materials involved. In recent years, additive manufacturing and 3D printing have revolutionized the manufacturing landscape and have provided great opportunities for the production of polymer-based multi-materials. However, developments in the joining of multi-material parts are limited, and their limits are not yet clear. This study focuses on the joining of 3D-printed products made from PLA-based multiple materials (PLA and PLA Wood) using friction stir welding. Single-material and multi-material parts (with 100% infill ratio and three different combinations of 50% PLA/50% PLA Wood) were welded at a feed rate of 20 mm/min and three different tool rotational speeds (1750, 2000, and 2250 rpm). Tensile and bending tests were conducted on the welded samples, and temperature measurements were taken. The fractured surfaces of the samples were examined to perform a damage analysis. It is determined that the weld strength of multi-materials changes depending on the combination of the material (material design). For multi-materials, a welding efficiency of 74.3% was achieved for tensile strength and 142.68% for bending load.
Regulating Cross-Linking Structure and Dispersion of Core-Shell-Rubber Particles in Polyurethane Composite to Achieve Excellent Mechanical Properties for Structural Adhesive Application
Authors: Jiang Zijin , Li Lingtong , Fu Luoping , Xu Yingte , Zhang Lin , Wu Hong , Guo Shaoyun
Published: November 2024

Structural adhesives are bonding materials that can quickly join structures with components and repair cracks. However, thermosetting polyurethane structural adhesives suffer from disadvantages such as insufficient toughness, poor aging resistance, and long curing time, which greatly limit their practical application. Herein, a polyurethane (PU) composite with excellent mechanical properties was prepared successfully via regulating the cross-linking structure and the dispersion of core-shell-rubber (CSR) particles. Various polyols were selected to improve the cross-linking density of the PU and to enhance the intermolecular forces, which can achieve the high strength and stability of the polyurethane composites. Solvent displacement was used to improve the dispersion of CSR in PU. The cured composite has ultra-high toughness and impact resistance due to the well-dispersed CSR particles. The impact strength was increased from 52.0 to 90.4 kJ/m2, and the elongation at break was increased from 6.1% to 14.9%. Due to the addition of catalyst T120, this composite can be cured quickly at room temperature, reaching high strength after 30 min. In addition, these composites can resist extreme environments, such as high and low temperature changes, UV aging, high humidity and heat environment, and salt spray aging, which has potential and value for practical application. The prepared PU structural adhesive can meet the requirements of structural bonding transit and improve the production efficiency. This work proposed a novel strategy to prepare polyurethane composites with excellent mechanical properties for structural adhesive application.
Advances in Molecular Dynamics-Based Characterization of Water and Ion Adsorption and Transport in C-S-H Gels
Authors: Li Xinjie , Fan Yingfang , Wu Chang , Wang Lei
Published: November 2024

Cementitious material durability is affected by the transport and adsorption of water molecules and ions in the nanopore channels of cement hydration products. Hydrated calcium silicate (C-S-H) accounts for about 70% of the hydration product. It determines the mechanical properties of cementitious materials and their internal transport properties. The molecular dynamics method provides a complementary understanding of experimental and theoretical results. It can further reveal water molecules and ions’ adsorption and transport mechanisms in C-S-H gel pores. This review article provides an overview of the current state of research on the structure of C-S-H gels and the adsorption and transport properties of water molecules and ions within C-S-H gels, as studied through molecular dynamics simulations. This paper summarizes the results of the molecular dynamics-based adsorption transport properties of water molecules and ions in C-S-H gels. The deficiencies in the current study were analyzed, and the fundamental problems to be solved and further research directions were clarified to provide scientific references for revealing the structural properties of C-S-H gels using molecular dynamics.
Rapid Onset of Innate Response, Cytokine Signaling and Humoral Immunity in Inactivated LPAI-H9N2-Vaccinated Broilers
Authors: Raheel Ismail A. , Elbestawy Ahmed R. , Diab Mohamed S. , Abdel-Latif Mervat A. , Tag Nehal , Orabi Ahmed
Published: November 2024

The development of effective and innovative vaccination strategies is urgently needed to better control the spread and transmission of the low-pathogenic avian influenza H9N2 subtype (LPAI-H9N2) in poultry. In addition, the enhancement of innate immunity by some of these innovative inactivated vaccines has not yet been investigated. Here, an experiment was conducted in commercial broiler chickens to compare the immune response to two different inactivated H9N2 vaccines. For this, Group 1 (G1) broilers were vaccinated with vaccine 1 [Nobilis® H9N2-P (pathogen-associated molecular patterns—PAMP) technology], broilers in G2 were vaccinated with vaccine 2 [an inactivated whole H9N2 virus (IWV) autogenous oil emulsion vaccine], while birds in G3 were not vaccinated. The study lasted 34 days. Innate immune parameters (phagocytic activity, nitric oxide, and lysozyme), cytokine signaling (IL-1β, IL-6, IL-8), humoral immunity using the hemagglutination inhibition (HI) test, and the gene expressions of IFN-γ and TLR-21 were assessed. The results showed a significant increase in innate immunity and modulatory cytokines at 24–48 h after the vaccination of G1 broilers, with a continuous increase until the end of the experiment. In addition, a significant increase in geometric mean HI titers was observed in G1 at 11 days post-vaccination (dpv), and a significant (p ˂ 0.05) upregulation of IFN-γ and TLR-21 was observed in the same group, G1, at 31 dpv compared to G2 and G3. Nobilis® H9N2-P may induce faster and stronger innate and active humoral immunity compared to another IWV, which may contribute to the protection of broilers against early H9N2 infections. However, challenge protection studies for several IWV vaccines, including PAMP-H9N2 against LPAI-H9N2, should be further evaluated in both specific pathogen-free (SPF) and commercial broilers.
Simulation and Experiment on Hull Lower Welding Deformation Using Heat Source Shape
Authors: Lee Chung-Woo , Woo Suseong , Kim Jisun
Published: November 2024

To effectively use aluminum, which is inherently weak under heat, as a material for hull construction, it is crucial to precisely predict the thermal deformation in the weld zone. Most studies employing finite element (FE) methods to predict thermal deformation due to welding typically use estimated heat source conditions based on the results of the weld. However, these estimated values can differ significantly from the actual welding conditions. In this study, we investigated whether using the actual shape of the heat source, rather than an estimated value, can serve as a reliable condition for analysis in predicting thermal deformation. This prediction is essential for minimizing deformation in the fillet welds of an aluminum hull. To compare deformation outcomes, Al 5083, commonly used in hull construction, was selected as the base material. The thermal deformation of aluminum hull fillet welds, welded using the Cold Metal Transfer (CMT) welding method, which reduces heat input, was measured. The simulation results demonstrated similar deformation trends, with discrepancies ranging from a minimum of 0.02 mm to a maximum of 1.4 mm when using actual welding conditions and heat source shapes. The results of this study confirm that the actual heat source shape can be utilized as a reliable condition for predicting thermal deformation in aluminum hull welds. The aim is to contribute to the improvement of aluminum hull manufacturing quality by providing essential data for establishing welding conditions and minimizing deformation.
Numerical Investigation of Complex Hydraulic Fracture Propagation in Shale Formation
Authors: Zheng Heng , Li Fengxia , Wang Di
Published: November 2024

Due to the high flow resistance of shale oil and gas, creating artificial flow channels with high conductivity in shale formation was the main challenge for the development of shale oil and gas resources. To further understand the fracture propagation mechanism in shale formation, this paper proposed a global cohesive element method to simulate the hydraulic fracture propagation behavior in which natural fractures were distributed randomly, and the fracture geometry was quantitatively analyzed. From the simulation, it can be found that the horizontal stress difference was the determining factor affecting the generation of a complex fracture network. The simulation indicated that a low horizontal stress difference was beneficial for improving the stimulated volume. When the stress difference was below 5.0 MPa, numerous branch fractures were created which was the foundation of a complex fracture network. High injection rates with low-viscosity fracturing fluid were helpful for creating a complex fracture network, while high-viscosity fracturing fluid limited the fracture fluid flow into the deep formation.
Design and Parametric Analysis of the Constant Force Characteristics of the Electromagnet for Hydraulic Valves
Authors: Ren Wang , Wu Liujie , Zhang Wei , Jiang Pengfei , Wang Ziyue , Luo Chao , Guo Jichang , Liu Chang , Wei Yaozhong , Chen Zhiliang , He Zongke , Liu Yijie , Yu Ting , Song Yanhe , Yu Bin
Published: November 2024

The electromagnet is the most used driving device for hydraulic valves; especially the proportional electromagnet with constant force characteristics is the basis for the excellent control performance of hydraulic valves. However, the constant force characteristics of the proportional electromagnet are related to many parameters and are difficult to obtain. In view of the above problems, this paper designs a proportional electromagnet for driving hydraulic valves with the goal of constant force characteristics, with the minimum variance of the output electromagnetic force in the working range as the condition. Firstly, this paper introduces the working principle of proportional electromagnets and establishes the model of electromagnetic force. Then, the influences of the basin bottom radius, the guide angle width and the basin mouth depth on the constant force characteristics of the electromagnet were studied by the finite element method (FEM). Their values are found respectively to give the electromagnet constant force characteristics. Finally, the test bench of the electromagnet was built, and its constant force characteristics and output characteristics were continuously tested. The results show that the test results of the output electromagnet force are highly consistent with the simulation results and have constant force characteristics. Related research deepens the understanding of how the key parameters affect the constant force characteristics, and helps designers optimize these parameters to develop new structures, which have certain practical engineering values.
Automatic History Matching Method and Application of Artificial Intelligence for Fractured-Porous Carbonate Reservoirs
Authors: Tong Kaijun , Song Wentong , Chen Han , Guo Sheng , Li Xueyuan , Sun Zhixue
Published: November 2024

Fractured-porous carbonate reservoirs, mainly composed of dolomites and crystalline rocks with various rock types and extremely poor initial porosity and permeability, are dominated by tectonic fractures and exhibit extreme heterogeneity. The fracture system plays a predominant role in hydrocarbon fluid transport. Compared with conventional sandstone reservoirs, fracture geometry and topological structure parameters are key factors for the accuracy and computational efficiency of numerical simulation history matching in fractured reservoirs. To address the matching issue, this paper introduces an artificial intelligence history matching method combining the Monte Carlo experimental planning method with an artificial neural network and a particle swarm optimization algorithm. Taking reservoir geological parameters and phase infiltration properties as the objective function, this method performs reservoir production history matching to correct the geological model. Through case studies, it is verified that this method can accurately correct the geological model of fractured-porous reservoirs and match the observed production data. This research represents a collaborative effort among multiple disciplines, integrating advanced algorithms and geological knowledge with the expertise of computer scientists, geologists, and engineers. Currently the world’s major oilfields history fitting is mainly based on reservoir engineers’ experience to fit; the method is applicable to major oilfields, but the fitting accuracy and fitting efficiency is severely limited, the fitting accuracy is less than 75%, while the artificial intelligence history fitting method shows a stronger applicability; intelligent history fitting is mainly based on the integrity of the field data, and as far as the theory is concerned, the accuracy of the intelligent history fitting can be up to 100%. Therefore, AI history fitting can provide a significant foundation for mine field research. Future research could further explore interdisciplinary collaboration to address other challenges in reservoir characterization and management.
A Study on the Sustainability of Petrochemical Industrial Complexes Through Accident Data Analysis
Authors: Kim Lee Su , Yoon Cheolhee , Lee Daeun , Shin Gwyam , Jung Seungho
Published: November 2024

The increase in energy demand due to industrial development and urbanization has resulted in the development of large-scale energy facilities. Republic of Korea’s petrochemical industrial complexes serve as prime examples of this phenomenon. However, because of complex processes and aging facilities, many of which have been in operation for over a decade, these industrial complexes are prone to process-deviation-related accidents. Chemical accidents in energy facilities involving high-pressure liquids or gases are especially dangerous; therefore, proactive accident prevention is critical. This study is also relevant to corporate environment, social, and governance (ESG) management. Preventing chemical accidents to protect workers from injury is critical for business and preventing damage to surrounding areas from chemical accidents is a key component of ESG safety. In this study, we collected accident data, specifically injury-related incidents, from Republic of Korea’s petrochemical industrial complexes, which are the foundation of the energy industry. We analyzed the causes of accidents in a step-by-step manner. Furthermore, we conducted a risk analysis by categorizing accident data based on the level of risk associated with each analysis result; we identified the main causes of accidents and “high-risk process stages” that posed significant risk. The analysis reveals that the majority of accidents occur during general operations (50%, 167 cases) and process operations (39%, 128 cases). In terms of incident types, fire/explosion incidents accounted for the highest proportion (43%, 144 cases), followed by leakage incidents (24%, 78 cases). Furthermore, we propose a disaster safety artificial intelligence (AI) model to prevent major and fatal accidents during these high-risk process stages. A detailed analysis reveals that human factors such as accumulated worker fatigue, insufficient safety training, and non-compliance with operational procedures can significantly increase the likelihood of accidents in petrochemical facilities. This finding emphasizes the importance of introducing measurement sensors and AI convergence technologies to help humans predict and detect any issues. Therefore, we selected representative accident cases for implementing our disaster safety model.
Settlement and Civility as Pre-Requisite of Evangelization in the Chichimeca Frontier
Authors: Mendez Alonzo Manuel
Published: November 2024

This paper delves into the process of evangelization undertaken by the Spanish in the northern frontier of New Spain during the 16th century, specifically targeting the nomadic Indigenous populations known as Chichimecas. Missionaries encountered unique challenges due to the absence of religious infrastructure, robust political authorities, and the nomadic lifestyle of these groups. To overcome these hurdles, the Spanish implemented a strategy that intertwined evangelization with colonization. The text highlights the significance of constructing physical infrastructure in these frontier territories, such as churches, schools, and dwellings, to facilitate the process of evangelization and colonial control. Moreover, it emphasizes the need to impose a social and political structure on these nomadic communities, transforming them into obedient colonial subjects.
The Crush of Life’s Passion: Interiority in Michel Henry as a Possibility for the Experience of God
Authors: Cunningham Simon
Published: November 2024

The question of whether God can be given in first-hand experience is debated in the secondary literature of Michel Henry. Articulating the history and structure of interiority more deeply provides a more precise conceptualization of his interiority to emerge and thus settle the question, namely that Henry’s thought contains both a dualism and duality. Within his dualism, Henry’s interior appearing is foundational, and has no capacity to reconcile with the world’s appearing that asserts exteriority as a foundation of what is given. Yet an interior/exterior duality emerges within Henry’s foundational interiority. Experiences of things like chairs are exteriorly given in life, while experiences of affectivity like gratitude are interiorly given in life. Since interior experiences are unified with our life and are our life, they lack any phenomenological distance that reduce God to finitude. Thus interiority, when both the foundation and the experience, establishes both a possibility for a first-hand experience of God and a glimpse into God’s experience of Godself. The article closes by showing how Henry suggests a name for God when given in first-hand experience: the Holy Spirit.
“Crocus Flower”: Voriconazole-Induced Hallucinations and Visual Disturbances in a Patient with Recurrent Severe Vulvovaginitis—A Case Report on Irrational Drug Use
Authors: Stoev Svetoslav , Lebanova Hristina
Published: November 2024

Background and Clinical Significance: Voriconazole is a commonly prescribed second-generation azole used for the prevention and treatment of fungal infections. This report seeks to elucidate the relationship between certain intravenous infusion parameters and the causality and severity of potential visual adverse events associated with voriconazole administration, despite existing reports of visual disturbances such as hallucinations and altered visual perception, the underlying causes of which remain inadequately understood. Case Presentation: This case report describes a 32-year-old female patient who experienced sudden hallucinations and visual impairments after receiving an initial dose of intravenous voriconazole for the treatment of recurrent severe vulvovaginitis caused by Candida glabrata. The symptoms quickly disappeared when the dosage and infusion rate were reduced as per the recommendations of the clinical pharmacist. Conclusions: This example emphasizes the possible negative drug responses linked to voriconazole, especially those provoked by its irrational use described as an inappropriate infusion rate, and the crucial role of clinical pharmacists in recognizing and handling these reactions.
Comparison and Analysis of CALIPSO Aerosol Optical Depth and AERONET Aerosol Optical Depth Products in Asia from 2006 to 2023
Authors: Zhao Yinan , Tang Qingxin , Hu Zhenting , Yu Quanzhou , Liang Tianquan
Published: November 2024

Aerosol optical depth (AOD) serves as a significant parameter in aerosol research. With the increasing utilization of satellite data in AOD research, it is crucial to evaluate the satellite AOD data. Using Aerosol Robotic Network (AERONET) in situ measurements, this study investigates the accuracy and applicability of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) AOD data in Asia from June 2006 to June 2023. By matching the CALIPSO AOD data in a 1° × 1° area around the selected AERONET sites, various statistical metrics were used to create a comprehensive evaluation system. The results show that: (1) There is a high correlation between the AODs of CALIPSO and AERONET (R = 0.636), and the AOD values of CALIPSO are only 1.7% higher than those of AERONET on average. The MAE (0.215) and RMSE (0.358) suggest that the error level of CALIPSO AOD is relatively low; (2) In most of the 25 sites throughout Asia CALIPSO AOD have high matching accuracies with the AERONET AOD, and only in three sites has a validation accuracy of ‘Poor’; (3) The accuracy varies across the four seasons, ranked as follows: winter demonstrates the highest accuracy, followed by autumn, spring, and summer; (4) The accuracy varies with surface elevation, with better matching in lowest altitude (<50 m) and high altitude (>500 m) areas, but slightly worse matching in medium altitude (200–500 m) areas and low altitude (50–200 m). The uncertainty in the CALIPSO AOD retrievals varies in seasons, altitudes, and aerosol characteristics.
Trend Analysis of High-Resolution Soil Moisture Data Based on GAN in the Three-River-Source Region During the 21st Century
Authors: Li Zhuoqun , Luo Siqiong , Tan Xiaoqing , Wang Jingyuan
Published: November 2024

Soil moisture (SM) is a crucial factor in land-atmosphere interactions and climate systems, affecting surface energy, water budgets, and weather extremes. In the Three-River-Source Region (TRSR) of China, rapid climate change necessitates precise SM monitoring. This study employs a novel UNet-Gan model to integrate and downscale SM data from 17 CMIP6 models, producing a high-resolution (0.1°) dataset called CMIP6UNet-Gan. This dataset includes SM data for five depth layers (0–10 cm, 10–30 cm, 30–50 cm, 50–80 cm, 80–110 cm), four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5). The UNet-Gan model demonstrates strong performance in data fusion and downscaling, especially in shallow soil layers. Analysis of the CMIP6UNet-Gan dataset reveals an overall increasing trend in SM across all layers, with higher rates under more intense emission scenarios. Spatially, moisture increases vary, with significant trends in the western Yangtze and northeastern Yellow River regions. Deeper soils show a slower response to climate change, and seasonal variations indicate that moisture increases are most pronounced in spring and winter, followed by autumn, with the least increase observed in summer. Future projections suggest higher moisture increase rates in the early and late 21st century compared to the mid-century. By the end of this century (2071–2100), compared to the Historical period (1995–2014), the increase in SM across the five depth layers ranges from: 5.5% to 11.5%, 4.6% to 9.2%, 4.3% to 7.5%, 4.5% to 7.5%, and 3.3% to 6.5%, respectively.
Identification of Intrinsic Friction and Torque Ripple for a Robotic Joint with Integrated Torque Sensors with Application to Wheel-Bearing Characterization
Authors: Turlapati Sri Harsha , Nguyen Van Pho , Gurnani Juhi , Bin Ariffin Mohammad Zaidi , Kana Sreekanth , Yee Wong Alvin Hong , Han Boon Siew , Campolo Domenico
Published: November 2024

Although integrated joint torque sensors in robots dispel the need for external force/torque sensors at the wrist to measure interactions, an inherent challenge is that they also measure the robot’s intrinsic dynamics. This is especially problematic for delicate robot manipulation tasks, where interaction forces may be comparable to the robot intrinsic dynamics. Therefore, the intrinsic dynamics must first be experimentally estimated under no-load conditions, when the measurement only consists of torques due to the transmission of the robot actuator, before external interactions may be measured. In this work, we propose an approach for identifying and predicting the intrinsic dynamics using linear regression with non-linear radial basis functions. Then, we validate this regression on a wheel-bearing turning task, in which its friction is a measure of quality, and thus must be accurately measured. The results showed that the bearing torque measured by the joint 7 torque sensor was within an RMS error of 11% of the torque measured by the external force/torque sensor. This error is much lower than that before our proposed model in compensating the intrinsic dynamics of the robot arm.
Enhanced Fault Diagnosis in Milling Machines Using CWT Image Augmentation and Ant Colony Optimized AlexNet
Authors: Ullah Niamat , Umar Muhammad , Kim Jae-Young , Kim Jong-Myon
Published: November 2024

A method is proposed for fault classification in milling machines using advanced image processing and machine learning. First, raw data are obtained from real-world industries, representing various fault types (tool, bearing, and gear faults) and normal conditions. These data are converted into two-dimensional continuous wavelet transform (CWT) images for superior time-frequency localization. The images are then augmented to increase dataset diversity using techniques such as rotating, scaling, and flipping. A contrast enhancement filter is applied to highlight key features, thereby improving the model’s learning and fault detection capability. The enhanced images are fed into a modified AlexNet model with three residual blocks to efficiently extract both spatial and temporal features from the CWT images. The modified AlexNet architecture is particularly well-suited to identifying complex patterns associated with different fault types. The deep features are optimized using ant colony optimization to reduce dimensionality while preserving relevant information, ensuring effective feature representation. These optimized features are then classified using a support vector machine, effectively distinguishing between fault types and normal conditions with high accuracy. The proposed method provides significant improvements in fault classification while outperforming state-of-the-art methods. It is thus a promising solution for industrial fault diagnosis and has potential for broader applications in predictive maintenance.
Evaluation of Different Commercial Sensors for the Development of Their Automatic Irrigation System
Authors: Millán Sandra , Montesinos Cristina , Campillo Carlos
Published: November 2024

Reliable soil moisture information is essential for accurate irrigation scheduling. A wide range of soil moisture sensors are currently available on the market, but their performance needs to be evaluated as most sensors are calibrated under limited laboratory conditions. The aim of this study was to evaluate the performance of six commercially available moisture sensors (HydraProbe, Teros 10, Teros 11, EnviroPro, CS616 and Drill & Drop) and three tensiometers (Irrometer RSU-C-34, Teros 32 and Teros 21) and to establish calibration equations for a typical sandy soil of the Doñana National Park (Huelva, Spain). The calibration process for soil moisture sensors indicated differences between factory and corrected equations. All tested sensors improved with adjustments made to the factory calibration, except for the HydraProbe sensor which had a more accurate factory equation for a sandy soil. Among the various sensors tested, the Teros 10, Teros 11, and HydraProbe were found to be the easiest to install, typically positioned with an auger to prevent preferential pathways and ensure adequate sensor-soil contact. For tensiometers, the Teros 32 sensor requires specialized labor for its correct installation, as it must be positioned at a specific angle and maintained with distilled water. All tensiometers need a stabilization period after installation.
Retrieval Integrity Verification and Multi-System Data Interoperability Mechanism of a Blockchain Oracle for Smart Healthcare with Internet of Things (IoT) Integration
Authors: Zhou Ziyuan , Chen Long , Zhao Yekang , Yang Xinyi , Han Zhaoyang , He Zheng
Published: November 2024

The proliferation of Internet of Things (IoT) technology has significantly enhanced smart healthcare systems, enabling the collection and processing of vast healthcare datasets such as electronic medical records (EMRs) and remote health monitoring (RHM) data. However, this rapid expansion has also introduced critical challenges related to data security, privacy, and system reliability. To address these challenges, we propose a retrieval integrity verification and multi-system data interoperability mechanism for a Blockchain Oracle in smart healthcare with IoT Integration (RIVMD-BO). The mechanism uses the cuckoo filter technology to effectively reduce the computational complexity and ensures the authenticity and integrity of data transmission and use through data retrieval integrity verification. The experimental results and security analysis show that the proposed method can improve system performance while ensuring security.
A Novel Energy Replenishment Algorithm to Increase the Network Performance of Rechargeable Wireless Sensor Networks
Authors: Tariq  , Eswarakrishnan Vishwanath , Hussain Adil , Wei Zhu , Uzair Muhammad
Published: November 2024

The emerging wireless energy transfer technology enables sensor nodes to maintain perpetual operation. However, maximizing the network performance while preserving short charging delay is a great challenge. In this work, a Wireless Mobile Charger (MC) and a directional charger (DC) were deployed to transmit wireless energy to the sensor node to improve the network’s throughput. To the best of our knowledge, this is the first work to optimize the data sensing rate and charging delay by the joint scheduling of an MC and a DC. We proved we could transmit maximum energy to each sensor node to obtain our optimization objective. In our proposed work, a DC selected a total horizon of 360° and then selected the horizon of each specific 90∘ area based on its antenna orientation. The DC’s orientation was scheduled for each time slot. Furthermore, multiple MCs were used to transmit energy for sensor nodes that could not be covered by the DC. We divided the rechargeable wireless sensor network into several zones via a Voronoi diagram. We deployed a static DC and one MC charging location in each zone to provide wireless charging service jointly. We obtained the optimal charging locations of the MCs in each zone by solving Mix Integral Programming for energy transmission. The optimization objective of our proposed research was to sense maximum data from each sensor node with the help of maximum energy. The lifetime of each sensor network could increase, and the end delay could be maximized, with joint energy transmission. Extensive simulation results demonstrated that our RWSNs were designed to significantly improve network lifetime over the baseline method.
A New Compressed Data Acquisition Method for Power System Based on Chaotic Compressive Measurement
Authors: Yang Shan , Gao Zhirong , Guo Jingbo
Published: November 2024

The digitalization level of the new power system driven by “dual carbon” is increasing, leading to a growth in the amount of data that need to be acquired. This has intensified the contradiction between data volume and acquisition capacity. Therefore, it is urgent to study compressed data acquisition methods for power systems based on data compression. In this regard, a novel compressed data acquisition method based on chaotic compressive measurement with the compressed sensing principle is proposed. Firstly, the advantages of applying compressed sensing are analyzed for data acquisition in power systems, and the key issues that need to be addressed are identified. Subsequently, a chaotic map is sampled based on the basic requirements of the measurement matrix in compressed sensing, and the chaotic compressive measurement matrix is constructed and optimized based on the sampling results. Next, the sparse data difference of the power system is used as the compression target for the optimized chaotic measurement matrix, and an acquisition process is designed to recover the complete power data from a small amount of compressed data. Finally, the proposed method is validated in a case study, and the results demonstrate that the method is correct and effective.
Flat-Knitted Double-Tube Structure Capacitive Pressure Sensors Integrated into Fingertips of Fully Fashioned Glove Intended for Therapeutic Use
Authors: Fischer Susanne , Böhmer Carola , Nasrin Shamima , Sachse Carmen , Cherif Chokri
Published: November 2024

A therapeutic glove, which enables medical non-professionals to perform physiotherapeutic gripping and holding movements on patients, would significantly improve the healthcare situation in physiotherapy. The glove aims to detect the orthogonal pressure load and provide feedback to the user. The use of textile materials for the glove assures comfort and a good fit for the user. This, in turn, implies a textile realization of the sensor system in order to manufacture both the glove and the sensor system in as few process steps as possible, using only one textile manufacturing technique. The flat knitting technology is an obvious choice here. The aim of the study is to develop a textile capacitive pressure sensor that can be integrated into the fingertips of a glove using flat knitting technology and to evaluate its sensor properties with regard to transmission behavior, hysteresis and drift. It was shown that the proposed method of a flat knitting sensor fabrication is suitable for producing both the sensors and the glove in one single process step. In addition, the implementation of an entire glove with integrated pressure sensors, including the necessary electrical connection of the sensor electrodes via knitted conductive paths in three fingers, was successfully demonstrated.
The Design and Application of an Assistive Hip Joint Exoskeleton for Tower Climbing
Authors: Li Ming , Yin Hong , Yang Zhan , Hu Hongwei , Chen Haoyuan , Fu Zhijun , Yang Xiao , Guo Zhao
Published: November 2024

In order to ensure the safety of maintenance personnel during tower climbing and improve the efficiency of power maintenance work, this study designed an assistive hip joint exoskeleton robot and analyzed the kinematic data obtained from tower climbers during the climbing process. A neural-network-based assistive control algorithm for tower climbing was created, and a tower climbing experiment was conducted with volunteers. The surface electromyographic (sEMG) signals of four muscles, namely the biceps femoris (BF), gluteus maximus (GM), semimembranosus (SM), and semitendinosus (ST), were collected to evaluate the performance of the robot. The experimental results show that the exoskeleton robot could reduce the root mean square (RMS) values of the sEMG signals of the main force-generating muscles related to the hip joint. This suggests that the robot can effectively assist personnel in tower climbing operations.
Temperature-Based Long-Term Stabilization of Photoacoustic Gas Sensors Using Machine Learning
Authors: Borozdin Pavel , Erushin Evgenii , Kozmin Artem , Bednyakova Anastasia , Miroshnichenko Ilya , Kostyukova Nadezhda , Boyko Andrey , Redyuk Alexey
Published: November 2024

In this study, we address the challenge of estimating the resonance frequency of a photoacoustic detector (PAD) gas cell under varying temperature conditions, which is crucial for improving the accuracy of gas concentration measurements. We introduce a novel approach that uses a long short-term memory network and a self-attention mechanism to model resonance frequency shifts based on temperature data. To investigate the impact of the gas mixture temperature on the resonance frequency, we modified the PAD to include an internal temperature sensor. Our experiments involved multiple heating and cooling cycles with varying methane concentrations, resulting in a comprehensive dataset of temperature and resonance frequency measurements. The proposed models were trained and validated on this dataset, and the results demonstrate real-time prediction capabilities with a mean absolute error of less than 1 Hz for frequency shifts exceeding 30 Hz over four-hour periods. This approach allows continuous, real-time tracking of the resonance frequency without interrupting the laser operation, significantly enhancing gas concentration measurements and contributing to the long-term stabilization of the sensor. The results suggest that the proposed approach is effective in managing temperature-induced frequency shifts, making it a valuable tool for improving the accuracy and stability of gas sensors in practical applications.
Unidirectional Communications in Secure IoT Systems—A Survey
Authors: Gaina Lucian , Stangaciu Cristina Sorina , Stanescu Daniela , Gusita Bianca , Micea Mihai Victor
Published: November 2024

The security of Internet of Things (IoT) systems has consistently been a challenge, particularly in the context of critical infrastructure. One particular approach not yet employed in this domain is the unidirectional communication paradigm. This survey presents an analysis of the most prevalent unidirectional communication solutions, namely, data diodes, network pumps, unidirectional gateways, and unidirectional protocols. The objective of the survey is to present an analysis of the unidirectional communication methods that meet the requirements of IoT security. These methods are classified according to their implementation and operational mode. The survey analyzes the unidirectional communication solutions based on their performance, the level of security offered, the cost-effectiveness, and their cost of implementation. Additionally, it includes an analysis of the existing off-the-shelf unidirectional communication implementations found in the industry. Furthermore, it identifies some of the most important current issues and development directions.