bluuebunny/crossref_metadata_2025_split huggingface dataset:
Precision Controllable Reversible Watermarking Algorithm for Oblique Photography 3D Models
Authors: Wang Pengbin , Zhang Liming , Zhang Ziyi , Tan Tao 
Published: December 2023

Abstract
The existing reversible watermarking algorithms for the oblique photography 3D model can only restore the original model or not, which fails to meet the diverse needs of different users. Therefore, we propose a reversible watermarking algorithm for the oblique photography 3D model in this paper, aiming to achieve controlled model error recovery. Firstly, according to its global stability, the feature points of the oblique photography 3D model are extracted by utilizing the mean angle between vertex normals. Secondly, a mapping relationship is established based on the ratio of distances between feature points and non-feature points. Then, the vertices are grouped, with each group consisting of one feature point corresponding to several non-feature points. Finally, a spherical coordinate system is constructed with the feature point as the origin of each group. The watermark information is embedded by modifying the radius of the coordinate system. In the process of extracting the watermark, we extracted the watermark from different positions within the radius. This method recovers the model by obtaining different radii so that the method can achieve controlled data error. In addition, the experimental results have demonstrated that this algorithm can achieve controlled recovery of model error and exhibits good robustness against attacks such as translation, rotation, cropping, and simplification.
Alkali etching enhanced polyimide based three-layer composite separator for lithium-ion batteries
Authors: Jiang Wenzhao , Chen Youpeng , Zhang Jiangyun , Zhang Guoqing , Cao Dongqing , Li Xinxi. , Liu Junyuan 
Published: December 2023

Abstract

Separators has directly affected the safety and electrochemical performance of lithium-ion batteries. In this study, an alkali etched enhanced polyimide (PI)/polyacrylonitrile (PAN)@ (Cellulose acetate) CA/PI three-layer composite separator is prepared using electrospinning, non-solvent phase separation, and alkali etching methods. The effects of alkali etching on the mechanical strength, thermal stability, and electrochemical performance of the PI/PAN@CA/PI separator are explored. The obtained separator has two different pore structures, and the surface of the alkali etched separator has abundant polar groups, further enhancing the migration rate of lithium-ions. The mechanical strength and thermal performance decrease with the prolongation of alkali etching time. When the alkali etching time is 3 min, the PI/PAN@CA/PI separator has the best comprehensive performance, with a mechanical strength of 17.8 MPa, ion conductivity of 1.22 mS cm− 1, and interface impedance of 152 Ω. After 100 cycles of charging and discharging at a current density of 1 C, the capacity retention rate is 95.3%. At a current density of 5 C, the specific capacity of charging and discharging can reach 114 mAh g− 1, which is better than the 87.3 mAh g− 1 of the initial PI/PAN@CA/PI separator.
Fish community and its relationships with environmental variables in the channel of Poyang Lake into Yangtze River
Authors: Yin Hong , Wang Sheng , Yang Jing , Chen Shiwei , Hua Qi , Wang Luyao , Yang Qiuju , Hu Maolin 
Published: December 2023

Abstract
The river-lake transitional zone of Poyang Lake is a key water area connecting the Yangtze River and Poyang Lake. It is important to understand the relationship between fish communities, hydrological dynamics, and other water environment factors in these waters. This study examined the status of fish resources in the river-lake transitional zone of Poyang Lake, from 2021 to 2022. We collected 3,880 individual fish, belonging to 5 orders, 10 families, and 54 species. Cypriniformes comprised the largest number of fish species at 64.81% of the total number of species. Overall, the fish ecological types were dominated by carnivorous, demersal, resident and viscous egg fish. According to the relative importance index, there were eight dominant species (including Coilia brachygnathus and Megalobrama mantschuricus). The fish community was more abundant and structure was more complex in downstream areas and in the flood season. This area showed significant regional differences in the fish community structure, whereas seasonal differences were not significant. Analysis showed that the water level and flow correlated significantly with the Margalef richness index and Shannon-Wiener diversity index. Redundancy analysis showed that pH, oxidation-reduction potential, dissolved oxygen and the water level were key environmental factors affecting the fish community structure and species spatio temporal distribution. Thus, high water levels in the flood season and in downstream waters are important to the river-lake transitional zone of Poyang Lake. Collectively, this survey of fish resources in the river-lake transitional zone will support the protection and management of aquatic biological resources in Poyang Lake.
Assessing DNA damage during optical imaging of the preimplantation embryo: a comparison between light sheet and confocal microscopy
Authors: Chow Darren J.X. , Schartner Erik P. , Corsetti Stella , Upadhya Avinash , Morizet Josephine , Gunn-Moore Frank J. , Dunning Kylie R. , Dholakia Kishan 
Published: December 2023

Abstract

Embryo quality assessment by optical imaging is increasing in popularity. Among available optical techniques, light sheet
microscopy has emerged as a superior alternative to confocal microscopy due to its geometry, enabling faster image acquisition
with reduced photodamage to the sample. However, previous assessments of photodamage induced by imaging, may have
failed to measure more subtle impacts. In this study, we employed DNA damage as a sensitive indicator of light induced
damage. We use light sheet microscopy with excitation at a wavelength of 405 nm for imaging embryo autofluorescence and
compare its performance to laser scanning confocal microscopy at the same wavelength. At an equivalent signal-to-noise ratio
for images acquired with both modalities, light sheet microscopy reduces image acquisition time by 10-fold. Further, light sheet
microscopy at this excitation wavelength does not induce DNA damage when compared to non-imaged embryos. In contrast,
imaging with confocal microscopy led to significantly higher levels of DNA damage within embryos. This study confirms that
light sheet microscopy is faster and safer than confocal microscopy for imaging embryos, indicating its potential as a label-free
diagnostic for embryo quality.
Novel hierarchical porous carbon materials derived from bamboo shoot shells for high-performance symmetric supercapacitor
Authors: Zeng Fanen , Zhang Yaning , Lv Qi , Xie Hao , Xu Bing 
Published: December 2023

Abstract
Porous carbon materials were synthesized from bamboo shoot shells through carbonization and static air activation. The physicochemical properties of bamboo shoot shell-based porous carbon (BBC) were observed by scanning electron microscopy, X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, and N2 adsorption desorption analysis. BBC has an optimal hierarchical porous structure that displays a specific surface area of 546.04 m2 g-1 and an average pore diameter of 3.28 nm. The formation mechanism of the BBC, which has a hierarchical porous structure in static air activation, was illustrated systematically. To evaluate the suitability of BBC for practical implementations further, the constructed symmetric supercapacitor achieved an energy density of 11.11 Wh kg-1 at a power density of 252 W kg-1 and an outstanding cyclic retention rate of 100% over 7,000 cycles at a current density of 10 A g-1.
Physically Adjusted Ground Motion Prediction Equations for Induced Seismicity at Preston New Road, UK
Authors: Suroyo Pungky Megasari , Sunny Jaleena , Edwards Benjamin 
Published: December 2023

Abstract

Predicting ground motions due to induced seismicity is a challenging task owing to the scarcity of data and heterogeneity of the uppermost crust. Dealing with this requires a thorough understanding of the underlying physics and consideration of inter-site variability. The most common ground motion model used in practice is the parametric ground motion prediction equation (GMPE), of which hundreds exist in the literature. However, relatively few are developed with a focus on induced seismicity. Developing GMPEs that are specific to an appropriate magnitude-distance range (R < 30 km; 2 < M <6) is important for induced seismicity applications. This paper proposes a framework for the development of physically-based GMPEs to provide more accurate and reliable estimates of the potential induced-seismicity ground motion hazard, allowing for better risk assessment and management strategies.
To demonstrate this approach, a new set of GMPEs for the 2018-2019 induced seismicity sequence at the Preston New Road (PNR) shale gas site near Blackpool, United Kingdom, is presented. The physically-based GMPE was developed based on a pseudo-finite-fault stochastic ground motion simulation, calibrated with parameters derived from the spectral analysis of weak-motion records from induced seismic events. An optimization-based calibration technique using the area metric (AM) was subsequently performed to calibrate optimal parameters for simulating ground motion at the PNR site. Finally, using a suite of forward simulations for events with 1 < M < 6 recorded at distances up to 30 km, combined with empirical data, a location-specific GMPE was derived through adjustment of an existing model.
Metrics Based Dataset Analysis Used For CNN Absolute Pose Estimation
Authors: Kobzili Elhaouari , Allam Ahmed , Grini Abdellah 
Published: December 2023

Abstract
Convolutional neural networks (CNNs) have recently been used for a variety of computer vision tasks,including pose regression and image classification. Estimating the absolute localisation of a monocular camera in six degrees of freedom (6-DOF) is a new CNN application. The accuracy of the data set utilized will directly affect how well this strategy performs. In this research, utilizing a CNN architecture built on six dimensions of pose regression, we present new metrics to assess dataset quality and achieve adequate performances of Camera absolute posture estimate from a single image. The Structural SIMilarity (SSIM) and Correlation similarity rates are the suggested metrics. These two metrics are based on the analysis of visual similarity across all of the CNN training images. By leveraging the camera poses in our work, we present a different type of metric. As a result, using the position and orientation of the camera, all training camera views are combined to create a three-dimensional map of a probable coverage volume. The camera covering rate metric is used to define the latter.The proposed metrics are intended to give a first understanding of a dataset’s limitations when utilized for absolute pose regression using CNN architecture. By assuring an acceptable Camera coverage volume and minimizing ambiguity by managing similarity carefully, our metrics may also direct us effectively in dataset elaboration to cope with the expected performances. Our metrics are evaluated using the well-known PoseNet framework, which is applied to a well-known dataset (7-scenes).The obtained results are encouraging and deal with our expectations in terms of prediction errors.
MSC Classification: 68T07 , 68T01 , 68T20 , 68T45
Phenotypic comparison and the potential antitumor function of immortalized bone marrow-derived macrophages (iBMDMs)
Authors: Xie Dong-kun , Yao Jin , Li Peng-hui , Zhu Yan-wen , Chen Jia-nuo , Cao Xiu-li , Cheng Shi-lin , Chen Ya-miao , Wang Liang , Wang Zan-han , Qiao Rong , Ge Jia-mei , Yue Huan , Wei Li , Liu Zhong-yuan , Han Hua , Qin Hong-yan , Zhao Jun-long 
Published: December 2023

Abstract
Macrophages are an important component of innate immunity and involved in the immune regulation of multiple diseases. The functional diversity and plasticity make macrophages to exhibit different polarization phenotypes after different stimuli. During tumor progression, the M2-like polarized tumor-associated macrophages (TAMs) promote tumor progression by assisting immune escape, facilitating tumor cell metastasis, and switching tumor angiogenesis. Our previous studies demonstrated that functional remodeling of TAMs through engineered-modifying or gene-editing provides the potential immunotherapy for tumor. However, lack of proliferation capacity and maintained immune memory of infused macrophages restricts the application of macrophage-based therapeutic strategies in the repressive tumor immune microenvironment (TIME). Although J2 retrovirus infection enabled immortalization of bone marrow-derived macrophages (iBMDMs) and facilitated the mechanisms exploration and application, little is known about the phenotypic and functional differences among multi kinds of macrophages. In this study, we demonstrated iBMDMs exhibited the features of rapid proliferation and long-term survival. We also compared iBMDMs with RAW264.7 cell line and mouse primary BMDMs with in vitro and in vivo experiments, indicating that the iBMDMs could undergo the same polarization response as normal macrophages with no obvious cellular morphology changes after polarization. What’s more, iBMDMs owned stronger phagocytosis and pro-apoptosis functions on tumor cells. In addition, M1-polarized iBMDMs could maintain the anti-tumor phenotypes and domesticated the recruited macrophages of receptor mice, which further improved the TIME and repressed tumor growth. In summary, iBMDMs can serve as a good object for the function and mechanism study of macrophages and the optional source of macrophage immunotherapy.
Fe3O4@SiO2@CS.HCl.VO3 as A Novel Recyclable Heterogeneous Catalyst with Core-Shell Structure for Oxidation of Sulfides
Authors: Ismaile Ula Zuhaire , Bahrami Kiumars , Khodamorady Minoo 
Published: December 2023

Abstract
Iron nanoparticles, with low toxicity and many active sites, are among the materials that not only reduce waste along with green chemistry, but also increase the separation power and recover the catalyst from the reaction environment. In this study, first, the surface of iron nanoparticles was silanized, and in the next step, the complex of chitosan HCl.VO3.was placed on the surface of MNPs (Fe3O4@SiO2@Cs.HCl.VO3). This nanocatalyst is a novel, recoverable and potent nanocatalyst with high selectivity for the oxidation of sulfides to sulfoxides. Various physicochemical techniques such as IR, XRD, TGA, SEM, EDX, mapping, TEM and VSM were used to affirm the well synthesis of the catalyst. Oxidation of sulfides in the presence of hydrogen peroxide as green oxidant and in ethanol was catalyzed by the Fe3O4@SiO2@Cs.HCl.VO3. All sulfoxides were achieved with high efficiency and in a short time. The notable privileges of this method include facile and economic catalyst synthesis, proper catalyst durability, great performance, simple catalyst isolation, good recovery capability at least up to 5 times without an index drop in catalytic power.
100 % Natural Biomass Thermoplastic Materials Comprising Wood, Stone, and Natural Deep Eutectic Solvent Prepared by an Industrial Twin-Screw Extruder
Authors: Mori Ryohei 
Published: December 2023

Abstract
Biomass-based renewable and biodegradable materials are attractive candidates for replacing non-biodegradable petrochemical-derived plastics. Herein, a wood-based thermoplastic material comprising wood, stone, and a natural deep eutectic solvent (NADES) was prepared by a facile method using an industrial twin-screw extruder. In addition, molding products were also obtained by simple injection molding. All of the components were derived from 100% biomass (assuming talc as biomass), with no materials originating from petroleum or fossil fuels. A deep eutectic solvent was used to dissolve a part of the wood to afford a 100% biomass-based thermoplastic material by using a simple twin-screw extrusion process. The results revealed that the introduction of rosin or poly(3-hydroxybutyrate-co-3-hydroxyvalerate) led to the improvement in the mechanical strength and water resistance. IR and NMR spectral analyses revealed that cellulose, hemicellulose, and lignin were still present after treatment with NADES. As wood and stones are abundant and cost-effective materials, the as-prepared materials demonstrate novelty as new 100% bio-based thermoplastic materials.
Large eddy simulation of emulsified canola oil combustion in swirl-promoted combustion chamber
Authors: Li Qibo , Alvarado Jorge , Kannaiyan Kumaran , Sadr Reza 
Published: December 2023

Abstract

Recent studies have revealed that large eddy simulation (LES) as CFD technique is capable of capturing the unstable features of two-phase swirling flows during the combustion of straight vegetable oil (SVO) emulsions. In this study, blends of canola oil and methanol have been selected as emulsified SVO fuels for simulation purposes. To fully understand the effects of swirl number and equivalence ratio on combustion characteristics of emulsified canola oil, a numerical approach based on the discrete phase model (DPM), stochastic model and Taylor Analogy Breakup (TAB) model have been adopted to simulate SVO blend droplets in a swirl-promoted environment. Moreover, simulation results of fuel droplets distribution are compared directly with experimental results. Furthermore, a two-step chemical reaction mechanism and the Eddy-Dissipation model have been used to understand the effects of swirl number and equivalence ratio on the combustion characteristics of SVO. A robust and stable numerical algorithm has been selected and validated, which is capable of simulating turbulent combustion of emulsified canola oil using LES by considering two swirl numbers and equivalence ratios. Results reveal that turbulent flow and combustion characteristics are affected by the swirl number significantly. The simulation emission data show the same trends as the experimental results even though the simulations depict higher combustion temperatures in absence of heat losses. Nevertheless, the comprehensive numerical approach has been validated using experimental LDA droplet size distribution data. In summary, the numerical approach can be applied as a first order approximation to determine the effects of biofuel blend and swirl number on emission levels.
Evaluating predictive hybrid neural network models in spatiotemporal context: An application on Influenza outbreak predictions
Authors: Furkan Hamed Bin , Ayman Nabila , Uddin Md. Jamal 
Published: December 2023

Abstract

In the rigorous and varied field of infectious disease outbreak modeling, there remains a notable gap in addressing the spatiotemporal challenges present in established models. This study aimed to fill this gap by evaluating four already established hybrid neural network models designed to predict influenza outbreaks, given that influenza is a major infectious disease. These models were analyzed by employing time series data from eight different countries which is a deviation from the original articles to challenge the models with imposed spatial difficulties, in a month-on-month structure to assess their abilities to handle spatiotemporal dependencies. The models' predictions were compared using MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Squared Error) metrics, as well as graphical representations of the original values and predicted values generated by employed models. The GA-LSTM model yielded the lowest MAPE score of 62.38% followed by GA-ConvLSTM-CNN model with a MAPE score of 66.23% among all the models, and the SARIMA-LSTM model excelled in achieving the lowest average RMSE score of 66.93 as well as reporting the lowest RMSE score for three out of eight countries studied. In this case also, GA-ConvLSTM-CNN model comes in second place with an average RMSE score of 68.46. Considering these results and the ability to follow the seasonal trends of the actual values, this study suggests the SARIMA-LSTM model to be more robust to spatiotemporal challenges compared with the other models under examination.
Association of induced abortion with bipolar disorder and major depression from the UK Biobank: A Propensity Score Matching and Weighting Analysis
Authors: Sun Hao , Huang Jie , Liu Huan , Chen Yanjie , Dong Yongfei , Chu Ziyan , Sun Hongpeng , Tang Zaixiang , Liu Jingfang 
Published: December 2023

Abstract
Background:Female induced abortion is associated with anxiety and depression, However, fewer studies have focused on the association between induced abortion and bipolar disorder and major depression (BDMD).
Objectives: This study aimed to investigate the association between IA and BDMD, and the possible dose-response relationship between them.
Methods: We conducted a cross-sectional study of 13,200 female UK
Biobank participants. Self-reported number of IAs was categorized into two groups: Non-IA and IA, Moreover, we also explored the number of IA episodes. Covariates adjustment, propensity scores matching (PSM), and inverse probability of treatment weighting (IPTW) were conducted to correct and minimize bias.
Results: The IPTW-multivariate logistic regression revealed the OR was 1.25(95%CI:1.19-1.32) and the PSM-multivariate logistic regression revealed the OR was 1.25(95%CI:1.10-1.41) in the IA group, The different number of IAs were also correlated with BDMD,p for trend was <0.05. There was a nonlinear relationship between the number of IAs and the risk of BDMD according to the three-knots restricted cubic spline regression model. Similar conclusions were obtained from the sensitivity analysis.
Conclusion:IA was an independent factor for BDMD, Care for mental health care for women after spontaneous abortion is crucial.
Sp3-rich Porous Carbon for Doublet Layer Supercapacitors
Authors: Bhattacharyya Tamoghna 
Published: December 2023

Abstract
Efficient utilization of alternative energies hinges on the performance and cost of energy storage systems. In the foreseeable future, supercapacitors remain the most promising option for many energy storage applications. But their widespread use is limited by their low energy storage density and relatively high effective series resistance. To date, however, the highest energy density of a carbon-based solid-state supercapacitor is limited up to 139 Wh kg− 1. Here, we report our findings in the synthesis of a sp3 -rich carbon through a simple, one-step process and direct insertion of pyridinic and graphitic nitrogen in an NH3 atmosphere at -780C. Further, the hetero atom doped sp3 -rich carbon materials-based doublet layer supercapacitors with ordered architecture and shorter diffusion path & lower resistance, demonstrated excellent energy density (218.4 Wh kg− 1) with excellent cycling stability. This simple approach to low-cost carbonaceous materials with unique architecture and functionality could be a promising alternative to fabrication of hetero atom doped carbon structures for making next generation high capacitive batteries and hence, high energy storage device.
DFT study on the electronic, structure, magnetic and optical properties of TiO2 anatase
Authors: Sadek Otmane , Touhtouh Samira , Hajjaji Abdelowahed 
Published: December 2023

Abstract

In this work, the electronic structure, magnetic and optical properties of the anatase phase of titanium dioxide (TiO2) were etudiée by the Density Functional Theory (DFT) method, using the GGA+U method. As a result, the magnetic electronic properties show that anatase is a non-magnetic semiconductor with an indirect gap of 3.202. Optical properties such as dielectric function, refractive index, extinction coefficient, reflectivity, absorption coefficient and conductivity were found to be 8.21, 2.91, 1.98, 0.532, 517000 cm-1 and 8.9 fs-1 respectively. These results are in agreement with the available experimental results.