bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimation of Nutrient Load for Effective Water Resource Management in Dams: A case study of the Roodeplaat Dam, Southern Africa
Authors: Mnyango Samkele S , Thwala Melusi , Oberholster Paul J , Truter Christoff 
Published: July 2023

Abstract
Poorly treated domestic wastewater and diffuse nutrient loading from agriculture and informal human settlements greatly threaten water resources due to the alteration of ecosystem function and the reduction of the water’s fitness for use. Thus, the aim of the study was to assess nutrient loading in the eutrophic Roodeplaat Dam (RD) to inform water resource management as a foundation for the rehabilitation of the dam. The objectives were to determine Total Phosphorus (TP) and Nitrogen (N) loading capacity into the RD as well as to propose a total mean annual nutrient reduction for the sustainability of the dam. Flow Duration Curves and Load Duration Curves were employed as analytical tools. It was observed from the study N and TP varied significantly among the sites investigated and the actual TP loads were significantly higher than the allowable load throughout the study area. The study further observed that nutrient loading was more prominent during low flows due to the reduced dilution effect. Thus, this study recommended the application of nature-based solutions to control pollution and reduce stormwater and runoff input, as well as employing low-cost green treatment technology options to reduce nutrient loads from domestic wastewater effluent in municipal wastewater treatment pond systems, which requires less energy. Stringent point source pollution control measures were further recommended, and that water quality planning should consider the desired beneficial water use per catchment, considering the impactors.
Ab initio study of structural, mechanical and electronic properties of 3d transitional metal carbide in cubic rocksalt (rs) , zincblende (zb) , and cesium chloride (cc)
Authors: Sabbar Ehsan H. , Al-Zubaidi Hazim A. , Kurdi Aous H. , Ibrahim Isam M. , Ali Iftikhar M. 
Published: July 2023

Abstract

We have studied three structures of 3d transition metal carbides (TMCs) using LDA and GGA approximations. Interestingly, we found that the 3d TMCs (except ScC in rs, zb structures) have higher cohesive energy (Ecoh) than their nitrides indicating carbides are thermodynamically more stable. The computed values of Vickers hardness (Hv) of rs-TiC is about 25.66 GPa and are compatible with the experimental value, rs-TiC and rs-VC are the hardest carbides and even more complicated than their nitrides; this study can reduce the high cost and the time used in experimental discoveries which do not have promising properties. In addition, theoretical calculations can assist the discovery of new super-hard TMCs and grab experimental attention to possible material choices for obtaining desired physical properties; surprisingly, only two carbides in GGA approximation (CrC and MnC) and in addition to this CrC in LDA approximation in cesium chloride (cc) structure are mechanically stable.In contrast, all the 3d TMCs in rocksalt (rs) and seven in zincblende (zb) structures are mechanically stable. The general trend of charge transfer from 3d transitional metal to carbon indicates decreased ionicity and increased covalency along the series. The hybridization of p orbitals of carbon with d orbitals of metal plays a crucial role in determining the mechanical stability and hardness of 3d TMCs. The computation of the total density of states indicates that all the 3d TMCs except zb-TiC and zb-FeC in all phases are metallic. We observed that the elastic constant C44is anti-correlated with the number of electronic states around EF.
Gravitationally magnified high-redshift quasar ULASJ0816+2134 at z=7.46
Authors: Koptelova Ekaterina , Hwang Chorng-Yuan 
Published: July 2023

Abstract
We present data showing that the recently discovered quasar ULASJ081621.49+213442.65 at z=7.461 is a gravitationally lensed quasar, the first strongly lensed quasar at z>7 and only the second lensed quasar known during the epoch of reionization. ULASJ081621.49+213442.65 is multiplied by a faint galaxy at z≥0.5 into four images A1, A2, B, and C with a total magnification factor of ~15. The quasar images were resolved in the deep Y-, J-, H-, and K-band stacks obtained using the 3.8-m UKIRT telescope between 2021 and 2023. The two quasar images, A1 and C, have also been detected by the UKIDSS LAS survey in 2008, when these images increased their brightness due to a high-amplitude quasar flare of ΔmJ~3 mag. The observed positions and relative fluxes of the lensed images are well reproduced by the lens model of a singular isothermal sphere with an external shear component. The intrinsic absolute magnitude of ULASJ081621.49+213442.65 corrected for the lensing magnification factor is M1450 ~ -23 mag, which places this quasar at the faint end of the quasar luminosity function. The magnification-corrected black hole mass and Eddington accretion rate are MBH=(1.72±0.18)×108Msun and Lbol/LEdd=0.22±0.03. During the high-amplitude quasar flare in 2008, the wavelength-dependent time lag between the quasar brightness variations in the Y and J bands was a few times longer than usually measured, suggesting that the increase in the ionizing flux may have also led to the increase in the size of the UV/optical continuum emitting region of ULASJ081621.49+213442.65.
Disentangling the microbial genomic traits associated with aromatic hydrocarbon degradation in a jet fuel-contaminated aquifer
Authors: Hidalgo K. J. , Centurion V. B. , Lemos L. N. , Soriano A. U. , Valoni E. , Baessa M. P. , Richnow H. H. , Vogt C. , Oliveira V.M. 
Published: July 2023

Abstract

Spills of petroleum or its derivatives in the environment lead to an enrichment of microorganisms able to degrade such compounds. The interactions taking place in such microbial communities are complex and poorly understood, since they depend on multiple factors, including diversity and metabolic potential of the microorganisms and a broad range of fluctuating environmental conditions. In our previous study, a complete characterization, based on high-throughput sequencing, was performed in a jet-fuel plume using soil samples and in in-situmicrocosms amended with hydrocarbons and exposed for 120 days. Herein, we propose a metabolic model to describe the monoaromatic hydrocarbon degradation process that takes place in such jet-fuel-contaminated sites, by combining genome-centered analysis, functional predictions and flux balance analysis (FBA). In total, twenty high/medium quality MAGs were recovered; three of them assigned to anaerobic bacteria (Thermincolales, Geobacter and Pelotomaculaceace) and one affiliated to the aerobic bacterium Acinetobacter radioresistens, potentially the main players of hydrocarbon degradation in jet-fuel plumes. Taxonomic assignment of the genes indicated that a putative new species of Geobacteria has the potential for anaerobic degradation pathway, while the Pelotomaculaceae and Thermincolales members probably act via syntrophy oxidizing acetate and hydrogen (fermentation products of oil degradation) via sulfate and/or nitrate reduction.
Tetrahydrofuran Intercalated Layered Vanadium(III) Phosphate Electrode for Aqueous Zinc-ion Battery
Authors: Qiao Yifan , Yuan Jingjing , Lu Yuchen , Ren Yihan , Li Yifan , Zhang Zhihao , Chen Haiqun 
Published: July 2023

Abstract
Layered VOPO4⋅2H2O is considered as a good electrode material structure for the insertion and extraction of energy storage ions, but the lattice water may affect the electrochemical stability. To provide more active site and more stable layered structure, the lattice water was replaced by tetrahydrofuran (THF), and the THF intercalated VOPO4 was obtained. The interlayer spacing has changed from 7.4 Å to 6.3 Å after THF intercalation, and the layered structure of VOPO4-THF is well preserved. It offers enhanced structural stability during charge and discharge processes, minimizing electrode degradation. In addition, increasing the oxidation state of pentavalent vanadium in VOPO4-THF is also beneficial for enhancing the capacitance of electrode materials. Combining the stable layered structure with a high oxidation state, VOPO4-THF electrode material exhibits good capacity and long cycle life. Our work convert traditional VOPO4⋅2H2O electrode into a promising high-performance active electrode for zinc-ion batteries.
Effects of extracts on color, dimensional stability, and decay resistance of thermally modified wood
Authors: Bi Zhenju , Zhou Xiaojian , Chen Jiang , Lei Yafang , Yan Li 
Published: July 2023

Abstract
Thermal modification can enhance the color as well as improve the dimensional stability and decay resistance of wood without the use of chemical modifier, but the impact of extracts from thermally modified wood (TMW) on performance remains unclear. In order to utilize extracts to regulate the properties of the TMW or prepare the imitate TWM without mechanical loss, the effects of TMW acetone extracts on the color, dimensional stability, and decay resistance of TMW were investigated. The 180°C, 200°C and 220°C thermally modified spruce (Picea asperata Mast.) and poplar (Populus tomentosa Carr.)with or without acetone extract were used for CIELab system, anti-swelling efficiency(ASE), and decay resistance test. Fourier infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) were used to characterize extracted and unextracted TMW. The results indicated that the extract showed positive effects on the color, dimensional stability (220°C), and decay resistance of TMW, and this effect weakened with the increase of temperature. The brightness difference (∆L*) and the total color difference (∆E*) of the TMW were reduced due to the removal of the extract, and the wood thermally modified at 180°C was the most significant. The removal of the extract will lead to the improvement of the dimensional stability of the TMW at 180°C and 200°C and the reduction of the TMW at 220°C. The decay resistance of wood thermally modified at 180°C, 200°C, and 220°C decreased after extraction, and was most significant at 180°C. The antifungal activity of the extract was related to the production of vanillin, isovanillic acid, syringic acid and syringaldehyde. Extract from TMW played an important role in the properties of TMW, and can be used to adjust its properties or as a natural wood modifier.
A graph aggregation convolution and attention mechanism based semantic segmentation method for sparse Lidar point cloud data
Authors: Zheng Tong , Chen Jialun , Feng Wenbin , Yu Chongchong 
Published: July 2023

Abstract
In recent years, following the development of sensor and computer techniques, it is favored by many fields, i.e. automatic drive, intelligent home, etc. that the deep learning based semantic segmentation method for point cloud data collected by LiDAR. This type method can automatic extract features of point cloud, helping label semantic categories. However, compared to 2D images, 3D point cloud data is more expensive to acquire. Hence, to save research and production costs, the small-thread LiDAR is a good choice. For one observation scenario, following the decrease of the line, the point cloud will become sparser, which may cause the information loss. To balance the cost and the segmentation effect, we provide a point cloud completion auxiliary semantic segmentation method. The baseline of the proposed method is Bilateral Augmentation and Adaptive Fusion (BAAF) model. The main contribution is a completion module introduction in feature extraction part of BAAF for point cloud data reconstruction. The feature extraction of completion module consists of Graph Aggregation Convolution (GAC) and attention mechanism. Then, we use shuffle transform to upsampling data. In addition, to analyze the effectiveness of the proposed method, we make downsampling to point cloud data in public SemanticKITTI dataset and establish Sparse-SemanticKITTI dataset. Furthermore, it is analyzed that the effect of point cloud with different sparsity degree on classical semantic segmentation, which proves the research significance. Moreover, we compare the segmentation results between classical methods to the proposed one in point cloud data in SemanticKITTI and Sparse-SemanticKITTI dataset, respectively. The effectiveness of the proposed one is verified. Finally, the model complexity is analyzed. In sum, we provide a sparse point cloud semantic segmentation method to balance cost and effect.
Investigation of the thermal deformation behavior exhibited by oxidation products in Fe-Si alloys
Authors: Cao Guangming , Zhao Wencong , Shan Wenchao , Li Silin , Song Wentao , Wang Hao , Liu Zhenyu 
Published: July 2023

Abstract
The thermal deformation behavior of oxidation products from Fe-Si alloys with varying Si contents was systematically investigated using a thermal simulation testing machine during compressive deformation at temperatures ranging from 800 to 1100 ℃. The results indicate that FeO exhibits excellent plastic deformation ability and is the primary component undergoing deformation during the thermal process. The plasticity of the oxide product improves with higher deformation temperature, as does the coordination between the oxide product and matrix, and interface straightness. However, an increase in Si content leads to a decrease in FeO content within the oxide product, resulting in reduced overall plastic deformation ability and reduced deformation coordination of oxidation products with the substrate. At the interface, Fe2SiO4 forms a spinel solid solution composed of Fe2SiO4 with FeO and SiO2 that possesses a certain plastic deformation ability due to its FeO content. Moreover, the rise in Si content leads to an increased concentration of point defects in FeO near the interface side of the matrix, thereby facilitating dislocation climbing of FeO and resulting in a steady-state increase in plastic deformation. Thus the increase in the concentration of cationic defects in FeO due to the elevated Si content and the generation of Fe2SiO4 solid solution at the interface between the oxidation products and the substrate are the main reasons for the improvement in the flatness of the interface between the oxidation products and the substrate.
Sustainable Development of Geopolymer Concrete Paver Blocks Blended With Boiler Sand
Authors: V Arulpandian , S Venkatramana , R Jegankumar , G Balaji S 
Published: July 2023

Abstract

The usage of industrial by-product Flyash (FA) and Boiler Sand (BS) in connection with alkali activators in the manufacturing of geopolymer concrete was investigated. Cement is the most important binding component in Concrete and it plays vital role in the Construction Industry. In the current decades, Cement manufacturing units are producing more than 300 million metric ton cement which creates global warming problems because of the release in carbon dioxide (CO2). In the society it is great thread to the environment and human health. This scenario has been changed by preparing new development of cementitious materials instead of cement in the Concrete. Alkali activator based geopolymer act as good binding material in the concrete. The binding capacity of the geopolymer addressed by using Class F FA, Sodium Hydroxide (NaOH) and Sodium Silicate (Na2SiO3) with proper mix ratios. One of the main issues faced by Tyre Industry, in Tirunelveli is the disposal of used boiler sand. Boiler sand used as insulating agent for the boilers in the industries it is obtained around 55 tonnes per week. The idea was proposed the usage of BS in the preparation of geopolymer concrete which leads to reduce the storage problems. The utilaization of BS create economic aspect in the development of concrete. The various trial mix design was made with replacement of Sand by BS of 10%, 20%, and 30% respectively. With this above mentioned various mix proportions Pave blocks are to be manufactured and the various properties are verified with IS 15658:2006 guidelines.
CAQ-Net: A Heart Segmentation Model Based on Q-Net
Authors: Yang Mengzhu , Hu Shunbo , Zhu Dong , Dong Hao , Wang Yongfang 
Published: July 2023

Abstract
The heart is an important organ in the human body, but a variety of heart diseases also seriously threaten human life. To effectively treat and prevent these diseases, the study of precise segmentation of heart parts is particularly important. The heart is divided into four parts: the left and right ventricles and the left and right atria, and the left main trunk is more important, so the left ventricular muscle (LV-MYO), which is located in the middle part, has become the object of many researches. Deep learning medical image segmentation methods have become the main means of image analysis and processing at present, but the deep learning methods based on traditional convolutional neural network (CNN) are not suitable for segmenting organs with few labels and samples like the heart, while the meta-learning method Q-Net, which is used for the segmentation of medical images with small samples, can solve the above problems and achieve better results in the direction of heart segmentation. Since the LV-MYO is wrapped in the left ventricular blood pool (LV-BP), a new model for heart segmentation is proposed in this paper: CAQ-Net. The model redesigns the coding structure of Q-Net and makes improvements in the threshold extraction aspect of Q-Net, which effectively improves the accuracy of segmenting the LV-MYO and the LV-BP parts in the CMR dataset and is validated in another public dataset ABD for validation, and the results are superior to other SOTA methods.
Exploring the Potential of Arginine to Increase Coelenterazine-Renilla Luciferase Affinity and Enzyme Stability: Kinetic and Molecular Dynamics Studies
Authors: Salehiyan Maryam , Emamzadeh Rahman , Nazari Mahboobeh 
Published: July 2023

Abstract
Renilla luciferase catalyzes the oxidation of coelenterazine to coelenteramide and results in the emission of a photon of light. Although Renilla luciferase has various applications in biotechnology, its low thermal stability limits the development of its applications. Arginine is a well-known stabilizing amino acid that plays a key role in protein stabilization against inactivation. However, its impact on enzyme properties is unpredictable. This study investigates the impact of arginine on the kinetics and thermal stability of Renilla luciferase. The enzyme's performance was significantly enhanced in the presence of arginine, with catalytic efficiency increasing by 3.31-fold and 3.08-fold when exposed to 0.2 M and 0.3 M arginine, respectively. Additionally, arginine improved the thermal stability of Renilla luciferase. Molecular dynamics simulation showed that the addition of 0.2 M arginine reduced the binding of coelenteramide, the reaction product and an enzyme inhibitor, to the active site of the Renilla luciferase. Therefore, the release of the product was accelerated, and the affinity of Renilla luciferase for coelenterazine increased. Furthermore, Molecular dynamics studies indicated an increased network of water molecules surrounding Renilla luciferase in the presence of 0.2 M arginine. This network potentially enhances the hydrophobic effect on the protein structure, ultimately improving enzyme stability. The findings of this study hold promise for the development of commercial kits incorporating Renilla luciferase.
Global research trends in exosome tumor stem cells and tumor microenvironment: Visualization biology analysis
Authors: Guo Ziwei , Wang Gang , Jin Qian , Xu Luchun , Chen Yue , Lv Wenliang 
Published: July 2023

Abstract
The tumor microenvironment (TME) is an internal environment composed of various cells and an extracellular matrix. Cancer stem cells-derived exosomes (CSC-Exos), as essential messengers involved in various tumor processes, are important carriers for bidirectional communication between the tumor microenvironment and tumor cells and play an important role in the tumor microenvironment. Nevertheless, few bibliometric analyses have been systematically studied in this field. Therefore, we aimed to visualize the research hotspots and trends in this field through bibliometrics to comprehend the future evolution of fundamental and clinical research, as well as to offer insightful information and fresh viewpoints.The Scopus database was used to search the research literature related to exosomes and tumor microenvironments after the establishment of this repository. CiteSpace (version 5.8.R3) and VOSviewer (version 1.6.16) were used for visualization and analysis. In this study, a total of 2077 articles and reviews were included, with the number of articles on exosomes and tumor microenvironments significantly increasing yearly. Recent trends showed that the potential value of exosomes as “tumor diagnostics” and “the application prospect of exosomes as therapeutic agents and drug delivery carriers” will receive more attention in the future. We revealed the current status and hotspots of tumor stem cell-derived exosomes and tumor microenvironments globally through bibliometrics. The prospect of the regulatory role of CSC-Exos in TME, the potential value of diagnosis, and the application of drug delivery vectors will all remain cutting-edge research areas in the field of tumor therapy. Meanwhile, this study provided a functional literature analysis for related researchers.
A product-level digital twin modelling approach for the full lifecycle
Authors: Jiang Linbei , Su Shaohui , Chu Changyong , Chen Chang , Wang Wei 
Published: July 2023

Abstract

The digital twin(DT), as a dynamic intelligence system that organically combines virtual and realistic models and multiple sources of data, fully combines numerical models with real-world data to monitor the operational status of products and predict their lifespan. Therefore, a system modeling approach with high fidelity and timeliness is of great significance for DT models. However, most current DT modeling approaches focus on individual objects and individual aspects of a product, while being deficient in a full lifecycle and multi-object-oriented modeling approach, which is not conducive to the mining and utilization of data on the whole product. Given this challenge, a product-level DT modeling approach based on PLM/PDM theory is proposed in this paper. It combines property model, simulation model, process model, status model, quality model, and feedback model through a digital thread communication framework to collect and utilize product lifecycle data to achieve accurate control of all aspects of the product lifecycle. The product-level DT results are presented by a visualization platform that enables interaction between customers, designers, and fabricators under real-time monitoring of the product manufacturing process throughout the system. Finally, a test case of a wind energy generator was performed to validate the proposed product-level DT modeling approach. The results revealed that the proposed approach is effective and feasible.