bluuebunny/crossref_metadata_2025 huggingface dataset:
A Systematic Review of Conceptualizations, Early Indicators, and Educational Provisions for Intellectual Precocity
Authors: Conejeros-Solar María Leonor , Catalán Sandra , Gómez-Arizaga María Paz , López-Jiménez Tatiana , Contador Natalie , Sandoval-Rodríguez Katia , Bustamante Cristóbal , Quijanes Josefa
Published: August 2024

Intellectual precocity in children poses unique challenges and opportunities for educational systems. This systematic review aims to comprehensively analyze intellectual precocity in children until 6 years old, including its definition, manifestations, and various educational programs for intellectually precocious learners. Following PRISMA guidelines, a comprehensive search of electronic databases was conducted. The study included 26 articles published between 2013 and 2023 that provided a conceptualization of precocity or giftedness, and/or focused on characteristics of precocity, and/or investigated educational programs for intellectually precocious children. The authors’ conceptualizations of precocity varied, with some providing clear definitions based on a developmental view of precocity, while others merely mentioned the concept. Early indicators of superior traits have been observed in areas such as reading, math, problem-solving, and even in fields that have been traditionally disregarded, such as visual arts. Educational provisions varied widely, including approaches based on enrichment and project-based learning; however, interventions based on socioemotional elements are also highlighted. The findings emphasize the importance of early identification and targeted educational strategies to support the unique needs of intellectually precocious individuals. Future research should focus on longitudinal studies and the development of evidence-based interventions.
Spatial Structure and Vulnerability of Container Shipping Networks: A Case Study in the Beibu Gulf Sea Area
Authors: Xia Mengyu , Chen Jinhai , Zhang Pengfei , Peng Peng , Claramunt Christophe
Published: August 2024

Ports play an important role in maintaining the effectiveness of maritime logistics. When ports encounter congestion, strikes, or natural disasters, the maritime container transportation network might be significantly affected. The Beibu Gulf sea area is a key channel to supporting China’s participation in international economic cooperation in the western region. It is highly susceptible to the influence of the political and economic instability. This study introduces a dual-component framework to analyze the inherent structure and potential vulnerabilities of the container transportation network in the Beibu Gulf Sea areas. The findings show that the core layer of the network exhibited circular solidification characteristics. The entire network heavily relies on some core ports, such as Haiphong Port, Ho Chi Minh Port, and Qinzhou Port, and it highlights the potential increases in vulnerability. The finding shows that deliberate attacks have a greater impact than random attacks on the normal operations of maritime networks. If ports with high intermediary centrality are attacked, the connectivity and transportation efficiency of the Beibu Gulf maritime network will be significantly affected. However, under such circumstances, redistributing cargo transportation through route adjustments can deal with the transmission of cascading failures and maintain the network’s resilience. Based on the existing knowledge and the data collected in a case study, this research stands out as the first to provide a critical examination of the spatial structure and vulnerability of container shipping networks in the Beibu Gulf sea.
Calculation Method for Sortie Mission Reliability of Shipborne Unmanned Vehicle Group
Authors: Shi Han , Wang Nengjian , Liu Qinhui
Published: August 2024

To ensure unmanned vehicles can perform a sortie mission quickly, efficiently, safely and reliably after receiving the command, it is necessary to calculate the sortie mission reliability of the shipborne unmanned vehicle group before loading. Aimed at the layout and sortie characteristics of an unmanned vehicle group, a sortie mission network model and a calculation method for sortie mission reliability are designed in this paper. Firstly, this paper uses space partition to parallel search for equal-length minimal paths based on the two-terminal network reliability. Secondly, this paper adopts the sum of disjoint products to process the equal-length minimal path set, innovatively proposing a calculation method for the sortie mission reliability of the shipborne unmanned vehicle group. Finally, the sortie mission reliability for three typical cases was calculated and compared with the Monte Carlo method. The comparative analysis indicates that the proposed method is both accurate and efficient, thereby corroborating its scientific validity and practical effectiveness. This study fills the gap in the field of sortie mission reliability and lays a theoretical foundation for subsequent research. Meanwhile, the method proposed in this paper can also be extended to the reliability calculation of a multiple-vehicle sortie mission in similar enclosed spaces.
Theoretical Investigation of a Novel Two-Dimensional Non-MXene Mo3C2 as a Prospective Anode Material for Li- and Na-Ion Batteries
Authors: Xue Bo , Zeng Qingfeng , Yu Shuyin , Su Kehe
Published: August 2024

A new two-dimensional (2D) non-MXene transition metal carbide, Mo3C2, was found using the USPEX code. Comprehensive first-principles calculations show that the Mo3C2 monolayer exhibits thermal, dynamic, and mechanical stability, which can ensure excellent durability in practical applications. The optimized structures of Lix@(3×3)-Mo3C2 (x = 1–36) and Nax@(3×3)-Mo3C2 (x = 1–32) were identified as prospective anode materials. The metallic Mo3C2 sheet exhibits low diffusion barriers of 0.190 eV for Li and 0.118 eV for Na and low average open circuit voltages of 0.31–0.55 V for Li and 0.18–0.48 V for Na. When adsorbing two layers of adatoms, the theoretical energy capacities are 344 and 306 mA h g−1 for Li and Na, respectively, which are comparable to that of commercial graphite. Moreover, the Mo3C2 substrate can maintain structural integrity during the lithiation or sodiation process at high temperature. Considering these features, our proposed Mo3C2 slab is a potential candidate as an anode material for future Li- and Na-ion batteries.
Integrated Use of Furnace Bottom Ash as Fine Aggregate and Cement Replacement for Sustainable Mortar Production
Authors: Tang Waiching , Onaizi Ali M. , Onaizi Sagheer A. , Sajjad Umer , Liu Yanju
Published: August 2024

Recycling fly ash (FA) and furnace bottom ash (FBA) help with reducing greenhouse gas emissions, conserving natural resources, and minimizing waste accumulation. However, research on recycling FBA is progressing more slowly compared to FA. This research aims to investigate the combined use of FBA as a replacement for both fine aggregate and cement and its influence on the performance of mortar. The findings indicated that incorporating 25% FBA as a fine aggregate replacement and 10% or 20% ground FBA (GFBA) as a cement replacement significantly enhanced compressive strength after 28 and 56 days. Flexural strength was comparable to control mortar at 28 days and superior at 56 days. However, increasing the FBA content beyond 25% as a fine aggregate replacement reduced workability and increased porosity, which negatively affected mechanical performance and water absorption. Microstructural analyses revealed denser and more compact structures in the mortar with combined FBA replacement for both fine aggregate and cement, specifically 25% as a fine aggregate replacement and 10% and 20% as cement replacements. Optimal performance was noted in mixtures with Ca/Si and Ca/Al ratios within the ranges of 1.8–1.5 and 0.24–0.19, respectively. Trace element leaching analysis has not shown significant differences between GFBA, FA, and OPC. Regarding environmental impact assessment, using FBA as a fine aggregate replacement did not show a significant reduction in CO2 emissions, but replacing cement with FBA reduced emissions remarkably. Generally, using FBA as a replacement for both fine aggregate and cement in mortar enhances compressive and flexural strengths at optimal levels, promotes sustainability by reducing landfill waste and CO2 emissions, and supports cleaner production practices despite some workability challenges.
Analysis of Polymer-Ceramic Composites Performance on Electrical and Mechanical Properties through Finite Element and Empirical Models
Authors: Keshyagol Kiran , Hiremath Shivashankarayya , H. M. Vishwanatha , Rao P. Krishnananda , Hiremath Pavan , Naik Nithesh
Published: August 2024

Polymer and ceramic-based composites offer a unique blend of desirable traits for improving dielectric permittivity. This study employs an empirical approach to estimate the dielectric permittivity of composite materials and uses a finite element model to understand the effects of permittivity and filler concentration on mechanical and electrical properties. The empirical model combines the Maxwell-Wagner-Sillars (MWS) and Bruggeman models to estimate the effective permittivity using Barium Titanate (BT) and Calcium Copper Titanate Oxide (CCTO) as ceramic fillers dispersed in a Polydimethylsiloxane (PDMS) polymer matrix. Results indicate that the permittivity of the composite improves with increased filler content, with CCTO/PDMS emerging as the superior combination for capacitive applications. Capacitance and energy storage in the CCTO/PDMS composite material reached 900 nF and 450 nJ, respectively, with increased filler content. Additionally, increased pressure on the capacitive model with varied filler content showed promising effects on mechanical properties. The interaction between BT filler and the polymer matrix significantly altered the electrical properties of the model, primarily depending on the composite’s permittivity. This study provides comprehensive insights into the effects of varied filler concentrations on estimating mechanical and electrical properties, aiding in the development of real-world pressure-based capacitive models.
A Study of the Effects of Moisture on Composite−to−Metal Double−Lap Shear Joints
Authors: Li Weidong , Zeng Rui , Zhang Qian , Duan Ziqi , Shen Pengfei , Zhong Xiangyu , Jiang Shicai , Bao Jianwen
Published: August 2024

This work investigated the effects of moisture absorption treatment on composite−to−metal double−lap shear joints (DLSJs) bonded with epoxy adhesive film through experiments and simulations. The composite−to−metal DLSJ can be divided into five parts (the interface between the composite and adhesive, the interface between the adhesive and metal, the composite adherend, the metal adherend, and the adhesive layer). First, the wet−dependent properties of the adhesive and interfaces were obtained through adhesive tensile tests and GC tests, which showed that the properties of the adhesive and interfaces were significantly affected by the moist environment. Then, tensile tests of the composite−to−metal double−lap shear joints were carried out in dry and wet environments. Finally, based on the experimental investigations, a finite element (FE) model that considered cohesive damage was established for simulating damage evolution and predicting the failure loads and failure modes of the DLSJs. The results of both the experimental and numerical tests show that the DLSJ failure load decreases significantly after immersion in 95 °C water, and the major failure mode transfers from adhesive failure to interface failure. The research results provide a theoretical basis or basic data for the structural design of adhesively bonded composite−to−metal.
An Inertial Relaxed CQ Algorithm with Two Adaptive Step Sizes and Its Application for Signal Recovery
Authors: Suebcharoen Teeranush , Suparatulatorn Raweerote , Chaobankoh Tanadon , Kunwai Khwanchai , Mouktonglang Thanasak
Published: August 2024

This article presents a novel inertial relaxed CQ algorithm for solving split feasibility problems. Note that the algorithm incorporates two adaptive step sizes here. A strong convergence theorem is established for the problem under some standard conditions. Additionally, we explore the utility of the algorithm in solving signal recovery problems. Its performance is evaluated against existing techniques from the literature.
General Fractional Economic Dynamics with Memory
Authors: Tarasov Vasily E.
Published: August 2024

For the first time, a self-consistent mathematical approach to describe economic processes with a general form of a memory function is proposed. In this approach, power-type memory is a special case of such general memory. The memory is described by pairs of memory functions that satisfy the Sonin and Luchko conditions. We propose using general fractional calculus (GFC) as a mathematical language that allows us to describe a general form of memory in economic processes. The existence of memory (non-locality in time) means that the process depends on the history of changes to this process in the past. Using GFC, exactly solvable economic models of natural growth with a general form of memory are proposed. Equations of natural growth with general memory are equations with general fractional derivatives and general fractional integrals for which the fundamental theorems of GFC are satisfied. Exact solutions for these equations of models of natural growth with general memory are derived. The properties of dynamic maps with a general form of memory are described in the general form and do not depend on the choice of specific types of memory functions. Examples of these solutions for various types of memory functions are suggested.
Evaluation of Resistance Induction Promoted by Bioactive Compounds of Pseudomonas aeruginosa LV Strain against Asian Soybean Rust
Authors: Barazetti André Riedi , Dealis Mickely Liuti , Basso Kawany Roque , Silva Maria Clara Davis , Alves Leonardo da Cruz , Parra Maria Eugênia Alcântara , Simionato Ane Stéfano , Cely Martha Viviana Torres , Macedo Arthur Ladeira , Silva Denise Brentan , Andrade Galdino
Published: August 2024

Pseudomonas are known as higher producers of secondary metabolites with antimicrobial properties and plant growth promoters, including resistance induction. These mechanisms should be an alternative to pesticide use in crop production. Phakopsora pachyrhizi causes Asian soybean rust, representing a high loss of yield around the world. The objective of this paper was to evaluate the application of secondary metabolites produced by Pseudomonas aeruginosa LV strain from the semi-purified fraction F4A in soybean plants to induce plant resistance against P. pachyrhizi in field conditions. The experimental design was performed in randomized blocks with three replicates using two F4A doses (1 and 10 μg mL−1) combined or not with fungicides (Unizeb Gold® or Sphere Max®). The control treatment, with Uni + Sph, saponins, flavonoids, and sphingolipids, showed higher intensities in the plants. In contrast, plants treated with the F4A fraction mainly exhibited fatty acid derivatives and some non-identified compounds with nitrogen. Plants treated with Sphere Max®, with or without F4A10, showed higher intensities of glycosylated flavonoids, such as kaempferol, luteolin, narigenin, and apigenin. Plants treated with F4A showed higher intensities of genistein and fatty acid derivatives. These increases in flavonoid compound biosynthesis and antioxidant properties probably contribute to the protection against reactive oxygen species (ROS).
Response Surface Methodology-Based Optimization of the Chitinolytic Activity of Burkholderia contaminans Strain 614 Exerting Biological Control against Phytopathogenic Fungi
Authors: Ben Slimene Debez Imen , Houmani Hayet , Mahmoudi Henda , Mkadmini Khaoula , Garcia-Caparros Pedro , Debez Ahmed , Tabbene Olfa , Djébali Naceur , Urdaci Maria-Camino
Published: August 2024

As part of the development of alternative and environmentally friendly control against phytopathogenic fungi, Burkholderia cepacia could be a useful species notably via the generation of hydrolytic enzymes like chitinases, which can act as a biological control agent. Here, a Burkholderia contaminans S614 strain exhibiting chitinase activity was isolated from a soil in southern Tunisia. Then, response surface methodology (RSM) with a central composite design (CCD) was used to assess the impact of five factors (colloidal chitin, magnesium sulfate, dipotassium phosphate, yeast extract, and ammonium sulfate) on chitinase activity. B. contaminans strain 614 growing in the optimized medium showed up to a 3-fold higher chitinase activity. This enzyme was identified as beta-N-acetylhexosaminidase (90.1 kDa) based on its peptide sequences, which showed high similarity to those of Burkholderia lata strain 383. Furthermore, this chitinase significantly inhibited the growth of two phytopathogenic fungi: Botrytis cinerea M5 and Phoma medicaginis Ph8. Interestingly, a crude enzyme from strain S614 was effective in reducing P. medicaginis damage on detached leaves of Medicago truncatula. Overall, our data provide strong arguments for the agricultural and biotechnological potential of strain S614 in the context of developing biocontrol approaches.
Pre- to Postbiotics: The Beneficial Roles of Pediatric Dysbiosis Associated with Inflammatory Bowel Diseases
Authors: Ottria Roberta , Xynomilakis Ornella , Casati Silvana , Ciuffreda Pierangela
Published: August 2024

Probiotics are “live microorganisms which, when administered in adequate amount, confer health benefits on the host”. They can be found in certain foods like yogurt and kefir and in dietary supplements. The introduction of bacterial derivatives has not only contributed to disease control but has also exhibited promising outcomes, such as improved survival rates, immune enhancement, and growth promotion effects. It is interesting to note that the efficacy of probiotics goes beyond the viability of the bacteria, giving rise to concepts like paraprobiotics, non-viable forms of probiotics, and postbiotics. Paraprobiotics offer various health benefits in children with intestinal dysbiosis, contributing to improved digestive health, immune function, and overall well-being. In this review, the potential of these therapeutic applications as alternatives to pharmacological agents for treating pediatric intestinal dysbiosis will be thoroughly evaluated. This includes an analysis of their efficacy, safety, long-term benefits, and their ability to restore gut microbiota balance, improve digestive health, enhance immune function, and reduce inflammation. The aim is to determine if these non-pharmacological interventions can effectively and safely manage intestinal dysbiosis in children, reducing the need for conventional medications and their side effects.
Trophoblast Organoids: Capturing the Complexity of Early Placental Development In Vitro
Authors: Wessel Brady M. , Castro Jenna N. , Roberts Victoria H. J.
Published: August 2024

First trimester placental development comprises some of the most critical yet understudied events that impact fetal development. Improper placentation leads to a host of health issues that not only impact the fetal period but also influence offspring throughout their lives. Thus, a paradigm to study early placental development is necessary, and this has spurred on the pursuit of new in vitro model systems that recapitulate specific aspects of placentation. One of the most complex and translationally valid models to arise are organoids, three-dimensional structures comprising multiple differentiated cell types that originate from a common progenitor population. Trophoblasts are the progenitor cells of the placenta, serving as the proliferative base for placental development. Recent advances have enabled the derivation of organoids from primary tissue, yet access to first trimester human samples is ethically constrained; derivation from established trophoblast stem cell lines is an alternative source. Organoids have already proven useful in generating insights into molecular events that underlie trophoblast differentiation, with the identification of new cell subtypes that are primed to differentiate down different paths. In this review, (1) we recap early pregnancy development events, (2) provide an overview of the cellular complexity of the placenta, (3) discuss the generation of organoids from tissue versus cellular sources, (4) highlight the value of translational animal models, and (5) focus on the complexities of the molecular regulation of trophoblast organoid development, differentiation, and function.
Fault Detection and Isolation in Transient Conditions on a Heated Two-Tank System: A Multiway Principal Component Analysis Approach
Authors: Dippenaar Marchel C. , van Schoor George , Uren Kenneth R. , van Niekerk Willem M. K.
Published: August 2024

This paper presents a methodology for fault detection and isolation (FDI) in transient conditions using a multiway principal component analysis (MPCA) approach where practical data have been augmented with simulated data to conduct FDI when there are insufficient practical data. The motivation for using a heated two-tank system is due to the fact that it resembles a basic process in terms of controllable variables, noise, disturbances, and changes in operating points. Normal and faulty condition data of the practical heated two-tank system as well as a Simulink® model of the heated two-tank system were used. The MPCA technique has enhanced ability to detect and isolate faults in transient conditions compared to classic principal component analysis (PCA). MPCA, however, requires a vast amount of normal process transient conditions data to train the model to then enable meaningful fault detection and isolation. In this study, the practical normal transient conditions data are augmented with simulated normal transient conditions data to meet the requirement of a large amount of data. Utilising different datasets for the training of the MPCA model, the fault detection and isolation performance was evaluated with various metrics. This paper presents positive results towards the implementation of MPCA for fault detection in transient conditions.
Evaluation and Simulation Study of Rock Drillability Grades in the Tazhong-Tabei Block
Authors: Cheng Tianhui , Li Guolun , Wang Yarong , Qin Hailong , Fu Qiang , Cheng Wei , Zhu Liang
Published: August 2024

In response to the unclear rock properties of the formations in the Tazhong-Tabei block of the Tarim Basin and the difficulties in selecting drill bits, indoor rock drillability tests were conducted under high temperature and high-pressure conditions. The tests analyzed the changes in the drillability grade values of roller cone bits and PDC bits under the coupling effects of confining pressure and temperature. The research indicates that the drillability grade values of the rocks in this formation range between 4 and 6. Additionally, the drillability grade values of PDC bits are lower than those of roller cone bits. As confining pressure increases, the drillability grade values of the rocks also increase significantly when the confining pressure exceeds 30 MPa. Conversely, as the temperature rises, the drillability grade values of the rocks decrease substantially when the temperature exceeds 140 °C. A drillability analysis model for roller cone bits and PDC bits was established using finite element simulation software. The simulated drillability grade values of the rocks showed a discrepancy of less than 10% compared to the indoor test data, proving the accuracy and reliability of the indoor test data. Based on the rock drillability test results, the use of PDC bits is recommended for this formation. The optimized PDC bits successfully drilled through the target formation. These research findings are of guiding significance for accurately understanding the physical and mechanical properties of the formation rocks in the Tazhong-Tabei block and for the optimal selection of drill bits for this area.
Effect of Ba Addition on the Catalytic Performance of NiO/CeO2 Catalysts for Methane Combustion
Authors: Huang Xiuhui , Yang Wenkai , Li Junfeng
Published: August 2024

Methane catalytic combustion, a method for efficient methane utilization, features high energy efficiency and low emissions. The key to this process is the development of highly active and stable catalysts. This study involved the synthesis of a range of catalysts, including NiO/CeO2, NiO–M/CeO2, and NiO-Ba/CeO2. In order to modify the NiO/CeO2 catalysts to improve their catalytic activity, various alkaline earth metal ions were introduced, and the catalysts were characterized to evaluate the impact of different alkaline earth metal ion doping. It was found that the introduction of Ba as a dopant yielded the highest catalytic activity among the dopants tested. Based on this, the influence of the impregnation sequence, the Ba loading amount, and other factors on the catalytic activity of the NiO/CeO2 catalysts doped with Ba were investigated, and comprehensive characterization was conducted using a variety of analytical techniques, including N2 adsorption/desorption, X-ray diffraction, Fourier transform infrared, hydrogen temperature-programmed reduction, methane temperature-programmed surface reaction, and oxygen temperature-programmed oxidation. The H2–TPR characterization results suggest that Ba introduction partially enhances the reducing property of NiO/CeO2 catalysts, and improves the surface oxygen activity in the catalysts. Meanwhile, the CH4–TPSR and O2–TPO results indicate that Ba introduction also boosts the bulk-phase oxygen liquidity in the catalysts, renders the migration of bulk-phase oxygen to surface oxygen, and increases the surface oxygen number in the catalysts. These results provide evidence of the effectiveness of this catalyst in methane catalytic combustion.
Application of Salvinia biloba Raddi. in the Phytoextraction of the Emerging Pollutant Octocrylene in an Aquatic Environment
Authors: Moura Matheus A. S. , Nascimento Gabrielle C. S. G. , Valarini Osvaldo , Peron Ana P. , Souza Débora C.
Published: August 2024

The phytotreatment technique, which has never been used to treat emerging compounds, is used in this work to measure the phytoextraction of octocrylene (OC) in three concentrations (200, 400, and 600 μg/L of OC) by Salvinia biloba Raddi. The species proved to be a phytoextractor by accumulating OC in floating leaves at concentrations of 1,500,000 μg/kg in treatment 200 and 1,050,000 in 600 μg/L of OC. Chlorophyll synthesis was affected at all OC concentrations, especially 400 μg/L, with a chlorophyll a/b ratio of less than 1. Enzymatic activity responded to the contaminant: CAT and APX are inhibited in the submerged portions after 48 h, staying below 2.0E−6 μmol/min/μg of protein. GPOX was totally inhibited during the experiment, and SOD remains active at 200 and 600 μg/L. The cytogenotoxic effects of OC to confirm phytoextraction were evaluated by globally regulated tests with Allium cepa bulbs and germinal bulbs in Lactuca sativa and Avena fatua every 48 h. These tests showed that after 72 h of phytoextraction, the medium was no longer cytogenotoxic and the seeds germinated above 30%, confirming the phytoextractor capacity of S. biloba. Thus, we can affirm that S. biloba can be used in the phytotreatment of aquatic environments contaminated with OC.
Plasma CXCL4–DNA/RNA Complexes and Anti-CXCL4 Antibodies Modulation in an SSc Cohort under Iloprost Treatment
Authors: Mennella Anna , Stefanantoni Katia , Palazzo Raffaella , Ocone Giuseppe , Pietraforte Immacolata , Truglia Simona , Bisconti Ilaria , Pisacreta Alba , Riccieri Valeria , Lande Roberto , Frasca Loredana
Published: August 2024

Background: Systemic sclerosis (SSc) is an autoimmune disease characterized by vascular and immunity alterations and skin/internal organ fibrosis. Aberrant levels of plasma CXCL4, CXCL4–RNA/DNA complexes, type I IFN (IFN-I) and anti-CXCL4 antibodies characterize SSc. These parameters influence each other: CXCL4–self-DNA/RNA complexes are triggers of IFN-I in plasmacytoid dendritic cells (pDCs), and anti-CXCL4 autoantibodies amplify this effect. Here, we assess the modulation over time of plasma CXCL4 and the related parameters of CXCL4–DNA/RNA complexes, anti-CXCL4 antibodies, IFN-α and TNF-α in an SSc cohort under the synthetic analogue of prostacyclin PGI2 (iloprost) treatment to address contribution of these parameters to pathogenesis and their role as biomarkers. Methods: We analyzed immunological parameters at baseline (T0) and after 3 (T3) and 6 (T6) months in 30 SSc patients. Responders were the patients that lowered their disease activity parameters after six months of treatment. Results: Anti-CXCL4 autoantibodies correlated with both IFN-α and TNF-α levels in SSc plasma. Responders significantly down-regulated serum IFN-α. In seven patients with a shorter disease duration, improvement coincides with a decrease in plasma IFN-α, CXCL4 and TNF-α. Iloprost efficiently blocks pDCs IFN-α production induced by CXCL4–DNA/RNA complexes in vitro. Conclusions: The data suggest a possible role of iloprost as a disease-modifying drug, mainly accompanied by down-regulation of plasma IFN-I levels. Since CXCL4, IFN-I and TNF-α down-modulation was evident and significant in improving SSc patients with a shorter disease duration, these results warrant future investigations on the early use of iloprost to slow SSc progression.
Research on Positioning and Navigation System of Greenhouse Mobile Robot Based on Multi-Sensor Fusion
Authors: Cheng Bo , He Xueying , Li Xiaoyue , Zhang Ning , Song Weitang , Wu Huarui
Published: August 2024

The labor shortage and rising costs in the greenhouse industry have driven the development of automation, with the core of autonomous operations being positioning and navigation technology. However, precise positioning in complex greenhouse environments and narrow aisles poses challenges to localization technologies. This study proposes a multi-sensor fusion positioning and navigation robot based on ultra-wideband (UWB), an inertial measurement unit (IMU), odometry (ODOM), and a laser rangefinder (RF). The system introduces a confidence optimization algorithm based on weakening non-line-of-sight (NLOS) for UWB positioning, obtaining calibrated UWB positioning results, which are then used as a baseline to correct the positioning errors generated by the IMU and ODOM. The extended Kalman filter (EKF) algorithm is employed to fuse multi-sensor data. To validate the feasibility of the system, experiments were conducted in a Chinese solar greenhouse. The results show that the proposed NLOS confidence optimization algorithm significantly improves UWB positioning accuracy by 60.05%. At a speed of 0.1 m/s, the root mean square error (RMSE) for lateral deviation is 0.038 m and for course deviation is 4.030°. This study provides a new approach for greenhouse positioning and navigation technology, achieving precise positioning and navigation in complex commercial greenhouse environments and narrow aisles, thereby laying a foundation for the intelligent development of greenhouses.
Automatic Weight Redistribution Ensemble Model Based on Transfer Learning to Use in Leak Detection for the Power Industry
Authors: Kwon Sungsoo , Jeon Seoyoung , Park Tae-Jin , Bae Ji-Hoon
Published: August 2024

Creating an effective deep learning technique for accurately diagnosing leak signals across diverse environments is crucial for integrating artificial intelligence (AI) into the power plant industry. We propose an automatic weight redistribution ensemble model based on transfer learning (TL) for detecting leaks in diverse power plant environments, overcoming the challenges of site-specific AI methods. This innovative model processes time series acoustic data collected from multiple homogeneous sensors located at different positions into three-dimensional root-mean-square (RMS) and frequency volume features, enabling accurate leak detection. Utilizing a TL-driven, two-stage learning process, we first train residual-network-based models for each domain using these preprocessed features. Subsequently, these models are retrained in an ensemble for comprehensive leak detection across domains, with control weight ratios finely adjusted through a softmax score-based approach. The experiment results demonstrate that the proposed method effectively distinguishes low-level leaks and noise compared to existing techniques, even when the data available for model training are very limited.
Solar Heat Flux Suppression on Optical Antenna of Geosynchronous Earth Orbit Satellite-Borne Lasercom Sensor
Authors: Liu Ming , Zhao Hongwei , Zhu Chengwei , Wen Guanyu
Published: August 2024

The objective of this article is to examine potential techniques for suppressing solar heat flow on the optical antenna of a laser communication sensor. Firstly, the characteristics of the geosynchronous Earth orbit’s (GEO) space radiation environment are analysed, and a combined passive and active thermal control solution is proposed. Secondly, the temperature distribution of the lasercom sensor under extreme operating conditions is simulated utilising IDEAS-TMG (6.8 NX Series) software, which employs Monte Carlo and radiative heat transfer numerical calculation methods. Finally, a strategy for avoiding direct sunlight around midnight is proposed. The simulation results demonstrated that the thermal control solution and solar avoidance strategy proposed in this paper achieved long-term fine-stable control of the temperature field of the optical antenna, which met the thermal permissible communication hours per daily orbit cycle in excess of 14 h per day.
Attribute Feature Perturbation-Based Augmentation of SAR Target Data
Authors: Jin Rubo , Cheng Jianda , Wang Wei , Zhang Huiqiang , Zhang Jun
Published: August 2024

Large-scale, diverse, and high-quality data are the basis and key to achieving a good generalization of target detection and recognition algorithms based on deep learning. However, the existing methods for the intelligent augmentation of synthetic aperture radar (SAR) images are confronted with several issues, including training instability, inferior image quality, lack of physical interpretability, etc. To solve the above problems, this paper proposes a feature-level SAR target-data augmentation method. First, an enhanced capsule neural network (CapsNet) is proposed and employed for feature extraction, decoupling the attribute information of input data. Moreover, an attention mechanism-based attribute decoupling framework is used, which is beneficial for achieving a more effective representation of features. After that, the decoupled attribute feature, including amplitude, elevation angle, azimuth angle, and shape, can be perturbed to increase the diversity of features. On this basis, the augmentation of SAR target images is realized by reconstructing the perturbed features. In contrast to the augmentation methods using random noise as input, the proposed method realizes the mapping from the input of known distribution to the change in unknown distribution. This mapping method reduces the correlation distance between the input signal and the augmented data, therefore diminishing the demand for training data. In addition, we combine pixel loss and perceptual loss in the reconstruction process, which improves the quality of the augmented SAR data. The evaluation of the real and augmented images is conducted using four assessment metrics. The images generated by this method achieve a peak signal-to-noise ratio (PSNR) of 21.6845, radiometric resolution (RL) of 3.7114, and dynamic range (DR) of 24.0654. The experimental results demonstrate the superior performance of the proposed method.
The Parameter Calibration of Social Force Model for Pedestrian Flow Simulation Based on YOLOv5
Authors: Li Tianle , Xu Bingbing , Lu Weike , Chen Zidan , Zhang Sizheng , Xia Fanjun
Published: August 2024

With the increasing importance of subways in urban public transportation systems, pedestrian flow simulation for supporting station management and risk analysis becomes more necessary. There is a need to calibrate the simulation model parameters with real-world pedestrian flow data to achieve a simulation closer to the real situation. This study presents a calibration approach based on YOLOv5 for calibrating the simulation model parameters in the social force model inserted in Anylogic. This study compared the simulation results after model calibration with real data. The results show that (1) the parameters calibrated in this paper can reproduce the characteristics of pedestrian flow in the station; (2) the calibration model not only decreases global errors but also overcomes the common phenomenon of large differences between simulation and reality.
Cyber–Physical Distributed Intelligent Motor Fault Detection
Authors: Al-Anbuky Adnan , Altaf Saud , Gheitasi Alireza
Published: August 2024

This research paper explores the realm of fault detection in distributed motors through the vision of the Internet of electrical drives. This paper aims at employing artificial neural networks supported by the data collected by the Internet of distributed devices. Cross-verification of results offers reliable diagnosis of industrial motor faults. The proposed methodology involves the development of a cyber–physical system architecture and mathematical modeling framework for efficient fault detection. The mathematical model is designed to capture the intricate relationships within the cyber–physical system, incorporating the dynamic interactions between distributed motors and their edge controllers. Fast Fourier transform is employed for signal processing, enabling the extraction of meaningful frequency features that serve as indicators of potential faults. The artificial neural network based fault detection system is integrated with the solution, utilizing its ability to learn complex patterns and adapt to varying motor conditions. The effectiveness of the proposed framework and model is demonstrated through experimental results. The experimental setup involves diverse fault scenarios, and the system’s performance is evaluated in terms of accuracy, sensitivity, and false positive rates.
Between-Session Reliability of Field-Based Assessments of Isometric Neck Strength
Authors: Oxford Samuel W. , Clarke Neil D. , Tallis Jason
Published: August 2024

The reliability of the fixed-frame dynamometer for measuring isometric neck strength is established, but with limited field-based applications. This study aimed to establish the inter- and intra-session reliability of the peak force for neck flexors, extensors, and side flexors using the VALD ForceFrame and DynaMo and the force–time characteristics in the quadruped position (ForceFrame). Twenty-seven recreationally active males performed three repetitions of isometric neck flexion, extension, and side flexion over two sessions in random order using the VALD ForceFrame and DynaMo. Both devices demonstrated acceptable reliability, with the Forceframe ICC > 0.8 and CV% < 13.8% and the DynaMo ICC > 0.76 and CV% < 13.8%. No systematic or proportional differences were found using the Passing–Bablock procedure, and Bland–Altman analysis confirmed agreement across measures. Reliability was shown for right-side (ICC > 0.76) and left-side (ICC > 0.79) flexion and flexion (ICC > 0.75) across 50, 100, 150, and 200 ms. Statistical parametric mapping indicated no differences in ForceFrame-generated isometric force–time curves between sessions, though the CV was highest in the force development phase. The findings suggest that both tools can reliably assess neck strength, supporting their use in sports and clinical settings. However, assessment methods are not interchangeable, emphasising the need for standardised neck strength assessment approaches.
Score Images as a Modality: Enhancing Symbolic Music Understanding through Large-Scale Multimodal Pre-Training
Authors: Qin Yang , Xie Huiming , Ding Shuxue , Li Yujie , Tan Benying , Ye Mingchuan
Published: August 2024

Symbolic music understanding is a critical challenge in artificial intelligence. While traditional symbolic music representations like MIDI capture essential musical elements, they often lack the nuanced expression in music scores. Leveraging the advancements in multimodal pre-training, particularly in visual-language pre-training, we propose a groundbreaking approach: the Score Images as a Modality (SIM) model. This model integrates music score images alongside MIDI data for enhanced symbolic music understanding. We also introduce novel pre-training tasks, including masked bar-attribute modeling and score-MIDI matching. These tasks enable the SIM model to capture music structures and align visual and symbolic representations effectively. Additionally, we present a meticulously curated dataset of matched score images and MIDI representations optimized for training the SIM model. Through experimental validation, we demonstrate the efficacy of our approach in advancing symbolic music understanding.
Advancing Urban Resilience Amid Rapid Urbanization: An Integrated Interdisciplinary Approach for Tomorrow’s Climate-Adaptive Smart Cities—A Case Study of Wuhan, China
Authors: Makvandi Mehdi , Li Wenjing , Li Yu , Wu Hao , Khodabakhshi Zeinab , Xu Xinhui , Yuan Philip
Published: August 2024

This research addresses the urgent challenges posed by rapid urbanization and climate change through an integrated interdisciplinary approach combining advanced technologies with rigorous scientific exploration. The comprehensive analysis focused on Wuhan, China, spanning decades of meteorological and land-use data to trace extreme urbanization trajectories and reveal intricate temporal and spatial patterns. Employing the innovative 360° radial Fibonacci geometric growth framework, the study facilitated a meticulous dissection of urban morphology at granular scales, establishing a model that combined fixed and mobile observational techniques to uncover climatic shifts and spatial transformations. Geographic information systems and computational fluid dynamics were pivotal tools used to explore the intricate interplay between urban structures and their environments. These analyses elucidated the nuanced impact of diverse morphosectors on local conditions. Furthermore, genetic algorithms were harnessed to distill meaningful relationships from the extensive data collected, optimizing spatial arrangements to enhance urban resilience and sustainability. This pioneering interdisciplinary approach not only illuminates the complex dynamics of urban ecosystems but also offers transformative insights for designing smarter, more adaptable cities. The findings underscore the critical role of green spaces in mitigating urban heat island effects. This highlights the imperative for sustainable urban planning to address the multifaceted challenges of the 21st century, promoting long-term environmental sustainability and urban health, particularly in the context of tomorrow’s climate-adaptive smart cities.
Synthesis and Crystal Structure of Ilmenite-Type Silicate with Pyrope Composition
Authors: Ishii Takayuki , Sinmyo Ryosuke , Katsura Tomoo
Published: August 2024

Akimotoite, ilmenite-type MgSiO3 high-pressure polymorph can be stable in the lower-mantle transition zone along average mantle and subducting slab geotherms. Significant amounts of Al2O3 can be incorporated into the structure, having the pyrope (Mg3Al2Si3O12) composition. Previous studies have investigated the effect of Al2O3 on its crystal structure at nearly endmember compositions. In this study, we synthesized high-quality ilmenite-type Mg3Al2Si3O12 phase at 27 GPa and 1073 K by means of a Kawai-type multi-anvil press and refined the crystal structure at ambient conditions using a synchrotron X-ray diffraction data via the Rietveld method to examine the effect of Al2O3. The unit-cell lattice parameters were determined to be a = 4.7553(7) Å, c = 13.310(2) Å, and V = 260.66(6) Å3, with Z = 6 (hexagonal, R3¯). The volume of the present phase was placed on the akimotoite-corundum endmember join. However, the refined structure showed a strong nonlinear behavior of the a- and c-axes, which can be explained by Al incorporation into the MgO6 and SiO6 octahedral sites, which are distinctly different each other. Ilmenite-type Mg3Al2Si3O12 phase may be found in shocked meteorites and can be a good indicator for shock conditions at relatively low temperatures of 1027–1127 K.
The Impact of Spoofing Attacks in Connected Autonomous Vehicles under Traffic Congestion Conditions
Authors: Tzoannos Zisis-Rafail , Kosmanos Dimitrios , Xenakis Apostolos , Chaikalis Costas
Published: August 2024

In recent years, the Internet of Things (IoT) and the Internet of Vehicles (IoV) represent rapidly developing technologies. The majority of car manufacturing companies invest large amounts of money in the field of connected autonomous vehicles. Applications of connected and autonomous vehicles (CAVs) relate to smart transport services and offer benefits to both society and the environment. However, the development of autonomous vehicles may create vulnerabilities in security systems, through which attacks could harm both vehicles and their drivers. To this end, CAV development in vehicular ad hoc networks (VANETs) requires secure wireless communication. However, this kind of communication is vulnerable to a variety of cyber-attacks, such as spoofing. In essence, this paper presents an in-depth analysis of spoofing attack impacts under realistic road conditions, which may cause some traffic congestion. The novelty of this work has to do with simulation scenarios that take into consideration a set of cross-layer parameters, such as packet delivery ratio (PDR), acceleration, and speed. These parameters can determine the integrity of the exchanged wave short messages (WSMs) and are aggregated in a central trusted authority (CTA) for further analysis. Finally, a statistical metric, coefficient of variation (CoV), which measures the consequences of a cyber-attack in a future crash, is estimated, showing a significant increase (12.1%) in a spoofing attack scenario.
Advancing Dual-Active-Bridge DC–DC Converters with a New Control Strategy Based on a Double Integral Super Twisting Sliding Mode Control
Authors: Sami Irfan , Alhosaini Waleed , Khan Danish , Ahmed Emad M.
Published: August 2024

Dual-Active-Bridge (DAB) DC–DC converters are becoming increasingly favored for their efficiency in transferring electrical power across varying voltage levels. They are crucial in enhancing safety and reliability in various fields, such as renewable energy systems, electric vehicles, and the power supplies of electronic devices. This paper introduces a new control strategy for bidirectional isolated DAB DC–DC converters, implementing a Double Integral Super Twisting Sliding Mode Control (DI-STSMC) to accurately regulate the output voltage and current. The approach starts with a state-space representation to mathematically model the DAB converter. In light of model uncertainties and external disturbances, a robust DI-STSMC controller has been formulated to optimize the DAB converter’s output performance. This method achieves zero steady-state error without chattering and provides a quick response to fluctuations in load and reference changes. The validity of the proposed technique is demonstrated through simulation results and a control hardware-in-the-loop (CHIL) experimental setup, using Typhoon HIL 606 and Imperix B-Box RCP 3.0 on a 230 W DAB converter. Furthermore, the paper offers a comparative analysis of the DI-STSMC with other control strategies, such as the proportional-integral (PI) controller, standard sliding mode control (SMC), and integral sliding mode control (ISMC).