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This study aims to construct a sentiment series generation method for danmu comments based on deep learning, and explore the features of sentiment series after clustering.

This study consisted of two main parts: danmu comment sentiment series generation and clustering. In the first part, the authors proposed a sentiment classification model based on BERT fine-tuning to quantify danmu comment sentiment polarity. To smooth the sentiment series, they used methods, such as comprehensive weights. In the second part, the shaped-based distance (SBD)-K-shape method was used to cluster the actual collected data.

The filtered sentiment series or curves of the microfilms on the Bilibili website could be divided into four major categories. There is an apparently stable time interval for the first three types of sentiment curves, while the fourth type of sentiment curve shows a clear trend of fluctuation in general. In addition, it was found that “disputed points” or “highlights” are likely to appear at the beginning and the climax of films, resulting in significant changes in the sentiment curves. The clustering results show a significant difference in user participation, with the second type prevailing over others.

Their sentiment classification model based on BERT fine-tuning outperformed the traditional sentiment lexicon method, which provides a reference for using deep learning as well as transfer learning for danmu comment sentiment analysis. The BERT fine-tuning–SBD-K-shape algorithm can weaken the effect of non-regular noise and temporal phase shift of danmu text.

The study aims to devise a comprehensive evaluation model (CEM) for evaluating spatial equity in the layout of elderly service facilities (ESFs) to address the inequity in the layout of ESFs within city center communities characterized by limited land resources and a dense elderly population.

The CEM incorporates a suite of analytical tools, including accessibility assessment, Lorenz curve and Gini coefficient evaluations and spatial autocorrelation analysis. Utilizing this model, the study scrutinized the distributional equity of three distinct categories of ESFs in the city center of Xi’an and proposed targeted optimization strategies.

The findings reveal that (1) there are disparities in ESFs’ accessibility among different categories and communities, manifesting a distinct center (high) and periphery (low) distribution pattern; (2) there exists inequality in ESFs distribution, with nearly 50% of older adults accessing only 18% of elderly services, and these inequalities are more pronounced in urban areas with lower accessibility, and (3) approximately 14.7% of communities experience a supply-demand disequilibrium, with demand surpassing supply as a predominant issue in the ongoing development of ESFs.

The CEM formulated in this study offers policymakers, urban planners and service providers a scientific foundation and guidance for decision-making or policy amendment by promptly assessing and pinpointing areas of spatial inequity in ESFs and identifying deficiencies in their development.

The purpose of this study is to provide ideas and theoretical guidance for green, environmentally friendly and efficient “bacteriostasis with bacteria” technology.

In this paper, a beneficial strain of bacteria was extracted and purified from marine mud. Weight-loss test, morphological observation and electrochemical test were used to systematically study the effect of sulfate-reducing bacteria (SRB)-induced corrosion inhibition on X65 steel in simulated offshore oil field production water.

The results showed that a beneficial strain was selected and identified as Vibrio alginolyticus. Under the condition of co-culture of SRB, the average corrosion rate of X65 steel was significantly reduced. In the mixed bacterial system, the surface of X65 steel samples was relatively flat, and the structure of biofilm and corrosion product film was dense. The number of corrosion pits, the average diameter and depth of corrosion pits were significantly reduced. The localized corrosion of X65 steel was significantly inhibited.

The complex and changing marine environment makes the corrosion problem of marine steel increasingly severe, and the microbiologically influenced corrosion (MIC) caused by SRB is particularly serious. The research and development of environmentally friendly corrosion protection technology is a long-term and difficult problem. The use of beneficial microorganisms to control MIC is a green and efficient anticorrosion measure. Compared with terrestrial microorganisms, marine microorganisms can adapt to complex environments, and their metabolites exhibit special biological activities. The use of marine beneficial bacteria can inhibit SRB activity to achieve the corrosion inhibition effect.

Light field images (LFIs) have gained popularity as a technology to increase the field of view (FoV) of plenoptic cameras since they can capture information about light rays with a large FoV. Wide FoV causes light field (LF) data to increase rapidly, which restricts the use of LF imaging in image processing, visual analysis and user interface. Effective LFI coding methods become of paramount importance. This paper aims to eliminate more redundancy by exploring sparsity and correlation in the angular domain of LFIs, as well as mitigate the loss of perceptual quality of LFIs caused by encoding.

This work proposes a new efficient LF coding framework. On the coding side, a new sampling scheme and a hierarchical prediction structure are used to eliminate redundancy in the LFI's angular and spatial domains. At the decoding side, high-quality dense LF is reconstructed using a view synthesis method based on the residual channel attention network (RCAN).

In three different LF datasets, our proposed coding framework not only reduces the transmitted bit rate but also maintains a higher view quality than the current more advanced methods.

(1) A new sampling scheme is designed to synthesize high-quality LFIs while better ensuring LF angular domain sparsity. (2) To further eliminate redundancy in the spatial domain, new ranking schemes and hierarchical prediction structures are designed. (3) A synthetic network based on RCAN and a novel loss function is designed to mitigate the perceptual quality loss due to the coding process.

This study aims to investigate a chromium-free sealing treatment process to replace the chromate sealing process in response to the environmental hazards caused by chromate in the Phosphate chemical conversion (PCC) coating post-treatment sealing process.

In this paper, chromium-free sealing technology was used to post-treat PCC coatings. Scanning electron microscopy was used to investigate the structure of the surface of the PCC coatings after the sealing treatment, and the corrosion resistance, hydrophobicity and bonding were tested using an electrochemical workstation, a copper sulfate spot-drop test, a lacquer bonding test, a contact angle meter and a neutral salt spray test.

Chromium-free closure makes the grain distribution on the surface of the PCC coating more uniform and dense, and forms an organic film on the surface of the coating, which significantly improves the corrosion resistance and hydrophobicity of the PCC coating, does not affect the coating film bonding force and has similar performance with potassium dichromate solution.

The results show that the corrosion resistance of PCC coatings after chromium-free sealing treatment is improved, and chromium-free sealing has the potential to replace chromium sealing.

The main focus is to provide a non-similar solution for the magnetohydrodynamic (MHD) flow of Casson fluid over a curved stretching surface through the novel technique of the artificial intelligence (AI)-based Lavenberg–Marquardt scheme of an artificial neural network (ANN). The effects of joule heating, viscous dissipation and non-linear thermal radiation are discussed in relation to the thermal behavior of Casson fluid.

The non-linear coupled boundary layer equations are transformed into a non-linear dimensionless Partial Differential Equation (PDE) by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ordinary differential equations (ODEs). The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

The results indicate that the non-linear radiation parameter increases the fluid temperature. The Casson parameter reduces the fluid velocity as well as the temperature. The mean squared error (MSE), regression plot, error histogram, error analysis of skin friction, and local Nusselt number are presented. Furthermore, the regression values of skin friction and local Nusselt number are obtained as 0.99993 and 0.99997, respectively. The ANN predicted values of skin friction and the local Nusselt number show stability and convergence with high accuracy.

AI-based ANNs have not been applied to non-similar solutions of curved stretching surfaces with Casson fluid model, with viscous dissipation. Moreover, the authors of this study employed Levenberg–Marquardt supervised learning to investigate the non-similar solution of the MHD Casson fluid model over a curved stretching surface with non-linear thermal radiation and joule heating. The governing boundary layer equations are transformed into a non-linear, dimensionless PDE by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ODEs. The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.

First, the ability to provide barrier protection, galvanic protection, and corrosion product protection provided by hot-dip galvanized coating is introduced. Then, according to the varying Fe content, the growth process of each sublayer within the hot-dip galvanized coating, as well as their respective microstructures and physical properties, is presented. Finally, the electrochemical corrosion behaviors of the different sublayers are analyzed.

The hot-dip galvanized coating is composed of η-Zn sublayer, ζ-FeZn13 sublayer, δ-FeZn10 sublayer, and Γ-Fe3Zn10 sublayer. Among these sublayers, with the increase in Fe content, the corrosion potential moves in a noble direction.

There is a lack of research on the corrosion behavior of each sublayer of hot-dip galvanized coating in different electrolytes.

It provides theoretical guidance for the microstructure control and performance improvement of hot-dip galvanized coatings.

The formation mechanism, coating properties, and corrosion behavior of different sublayers in hot-dip galvanized coating are expounded, which offers novel insights and directions for future research.

The purpose of this study is therefore to detail an additive manufacturing process for printing TiD parts for implant applications. Titanium–diamond (TiD) is a new composite that provides biocompatible three-dimensional multimaterial structures. Thus, the authors report a powder-deposition and print optimization strategy to overcome the dual-functionality gap by printing bulk TiD parts. However, despite favorable customization outcomes, relatively few additive manufacturing (AM) feedstock powders offer the biocompatibility required for medical implant and device technologies.

AM offers a platform to fabricate customized patient-specific parts. Developing feedstock that can be 3D printed into specific 3D structures while providing a favorable interface with the human tissue remains a challenge. Using laser metal deposition, feedstock powder comprising diamond and titanium was co-printed into TiD parts for mechanical testing to determine optimal manufacturing parameters.

TiD parts were fabricated comprising 30% and 50% diamond. The composite powder had a Hausner ratio of 1.13 and 1.21 for 30% and 50% TiD, respectively. The flow analysis (Carney flow) for TiD 30% and 50% was 7.53 and 5.15 g/s. The authors report that the printing-specific conditions significantly affect the integrity of the printed part and thus provide the optimal manufacturing parameters for structural integrity as determined by micro-computed tomography, nanoindentation and biocompatibility of TiD parts. The hardness, ultimate tensile strength and yield strength for TiD are 4–6 GPa (depending on build position), 426 MPa and 375 MPa, respectively. Furthermore, the authors show that increasing diamond composition to 30% results in higher osteoblast viability and lower bacteria count than titanium.

In this study, the authors provide a clear strategy to manufacture TiD parts with high integrity, performance and biocompatibility, expanding the material feedstock library and paving the way to customized diamond implants. Diamond is showing strong potential as a biomedical material; however, upscale is limited by conventional techniques. By optimizing AM as the avenue to make complex shapes, the authors open up the possibility of patient-specific diamond implant solutions.

The effect of spinning has been studied and analysed for different projectile shapes such as ogive, blunt, cylindrical and conical by using numerical simulations.

Projectile shape is one of the important parameters in the penetration mechanism. The present study deals with the failure mechanisms and ballistic evaluation for different nose-shaped projectiles undergoing normal impact with spinning. Materials characterization has been made by Johnson–Cook strength and failure models, and LS-DYNA simulations are used to analyse the impact of steel projectiles on an Al 7075-T651 target at different impact velocities under normal impact conditions. The experimental results from the literature are used to validate the model. Based on the residual velocity values, the Recht-Ipson model has been curve-fitted and approximate ballistic limit velocity has been evaluated. The approximated ballistic limit velocity is found to be 3.4% higher than the experimental results and compared well with the experimental results. Subsequently, the validated model conditions are used to study and analyse the effect of spinning for different nose-shaped projectiles undergoing normal impact conditions.

The ductile hole failure is observed for the ogive nose projectile, petals are formed and fragmented for the conical projectile, and plugging is observed for cylindrical projectiles. A Recht-Ipson curve is presented for each spinning condition for each projectile shape and the ballistic limit has been evaluated for each condition.

The proposed research outputs are original and innovative and, have a lot of importance in defence applications, particularly in arms and ammunition.

We use the extended finite element method (XFEM) to model the whole process of initiation and propagation of cracks in the inner dense pyrolytic carbon (IPyC) layer of tri-structural isotropic (TRISO) particle induced by the microdefect in an irradiation-induced thermomechanical coupling environment and study the effect of microdefect sizes on the propagation path.

The irradiation-induced thermal–mechanical coupling analysis is first conducted for the representative volume element (RVE) of the TRISO particle by using the conventional finite element method (CFEM) so that the stress distribution is obtained. The stress results are then restored for the enriched elements, and the simulation of crack initiation and propagation is eventually carried out by using the XFEM.

1. As a crack initiates in the IPyC layer, it will terminate at the free edge of the RVE TRISO particle in the end. 2. The size of the microdefect has a significant impact on the propagation path.

The ceramic dispersion microencapsulated (CDM) fuel is a good accident-resistant fuel whose safe operation is crucial to the safety and reliability of the whole nuclear reactor. It is of great scientific significance and practical value to study the irradiation-induced thermomechanical coupling stress distribution and cracking behavior in the IPyC layer of TRISO particles for the CDM fuel. Crack initiation and propagation analysis is challengeable for this complex multi-layer structure. This can help understand the failure mechanism of TRISO particles and evaluate the operation safety of the reactor.