Appl. Sci., Volume 14, Issue 2 (January-2 2024) – 480 articles

Colorectal cancer (CRC) is the third most common cancer diagnosed today and the third leading cause of death among cancer types. CRC is one of the gastrointestinal tumors with obesity as the main extrinsic risk factor, since, according to authors, the meta-inflammation sustained by the excess adipose tissue can provide abundant circulating lipids, as well as hormones and metabolites crucial to tumor development and aggressiveness. The gut microbiota can protect the colon from meta-inflammation and endocrine changes caused by obesity. The present study aimed to investigate the antitumor activity of a commercial probiotic in intestinal tumor cells under two adiposity conditions. Experimental assays were performed on the Caco2 cell line (colon adenocarcinoma) supplemented with differentiated adipocyte’s secretomes of the 3T3-L1 cell line (mouse pre-adipocytes) in two adiposity conditions: (i) differentiation without the use of Pioglitazone (noPGZ) and (ii) differentiation using Pioglitazone (PGZ). The Caco2 cells were first exposed to both secretomes for 24 h and evaluated and subsequently exposed to probiotic extract followed by secretome and evaluated. The effects of these treatments were evaluated using cytotoxicity assays by MTT, cell migration by injury, and antioxidant activity by glutathione assay. The use of secretomes showed a statistically significant increase in cell viability in Caco2 cells, either in noPGZ (p < 0.01) or PGZ (p < 0.05), and the probiotic was not able to reduce this effect. In the injury assay, secretome increased cell migration by more than 199% in both adiposity conditions (p < 0.001 in noPGZ and p < 0.01 in PGZ). In the probiotic treatment, there was a reduction in cell migration compared to the control in adiposity conditions. The antioxidant response of Caco2 cells was increased in both adiposity conditions previously exposed to the probiotic supernatant. This pilot work brings to light some findings that may answer why the modulation of the intestinal microbiota using probiotics is an alternative strategy leading to improvements in the condition and stage of the colon tumor. Additional studies are needed to clarify the role of Pioglitazone in this type of tumor and the metabolites of obesity that are attenuated by the use of probiotics. Full article

The type of soil and its compactness significantly influence its permeability coefficient, which in turn affects the drainage difficulty of soil pore water and the distribution of the infiltration line. However, current tailings dam models typically consider only a single soil layer instead of taking into account the differences in soil types and compactness, resulting in a deviation between simulated results and actual conditions. To address this issue, this study proposes three models with a gradually increasing degree of layering refinement based on soil type and compactness. These models aim to simulate the variations in the infiltration line under three different strategies: constant head, rainfall, and drainage. The simulation results indicate that the average increase in the infiltration line of the three schemes after rainfall is 46.2%, 65.88%, 83.52%, respectively; the fitting percentages for each scheme of infiltration line after 720 days of drainage and the constant head stage are 72.38%, 88.27%, and 93.61%, respectively. It can be seen that the higher the refinement level of the layered model, the more sensitive it is to changes in the infiltration line. Furthermore, as the refinement level of the layered model increases, the simulation effect on the changes in the infiltration line improves, and the simulated results become more consistent with the actual situation. This finding provides a strategy and possibility for the study of the tailings dam’s infiltration lines, safety, and stability. Full article

Background: In this study focusing on colorectal carcinoma (CRC), we address the imperative task of predicting post-surgery treatment needs by identifying crucial tumor features within whole slide images of solid tumors, analogous to locating a needle in a histological haystack. We evaluate two approaches to address this challenge using a small CRC dataset. Methods: First, we explore a conventional tile-level training approach, testing various data augmentation methods to mitigate the memorization effect in a noisy label setting. Second, we examine a multi-instance learning (MIL) approach at the case level, adapting data augmentation techniques to prevent over-fitting in the limited data set context. Results: The tile-level approach proves ineffective due to the limited number of informative image tiles per case. Conversely, the MIL approach demonstrates success for the small dataset when coupled with post-feature vector creation data augmentation techniques. In this setting, the MIL model accurately predicts nodal status corresponding to expert-based budding scores for these cases. Conclusions: This study incorporates data augmentation techniques into a MIL approach, highlighting the effectiveness of the MIL method in detecting predictive factors such as tumor budding, despite the constraints of a limited dataset size. Full article

Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convolutional Neural Networks (CNNs), offers more effective feature recognition in sports videos, but standard CNNs struggle with fast-paced or low-resolution sports videos. Our novel neural network model addresses these challenges. It begins by selecting important frames from sports footage and applying a fuzzy noise reduction algorithm to enhance video quality. The model then uses a bifurcated neural network to extract detailed features, leading to a densely connected neural network with a specific activation function for categorizing videos. We tested our model on a High-Definition Sports Video Dataset covering over 20 sports and a low-resolution dataset. Our model outperformed established classifiers like DenseNet, VggNet, Inception v3, and ResNet-50. It achieved high precision (0.9718), accuracy (0.9804), F-score (0.9761), and recall (0.9723) on the high-resolution dataset, and significantly better precision (0.8725) on the low-resolution dataset. Correspondingly, the highest values on the matrix of four traditional models are: precision (0.9690), accuracy (0.9781), F-score (0.9670), recall (0.9681) on the high-resolution dataset, and precision (0.8627) on the low-resolution dataset. This demonstrates our model’s superior performance in sports video classification under various conditions, including rapid motion and low resolution. It marks a significant step forward in sports data analytics and content categorization. Full article

Underwater autonomous path planning is a critical component of intelligent underwater vehicle system design, especially for maritime conservation and monitoring missions. Effective path planning for these robots necessitates considering various constraints related to robot kinematics, optimization objectives, and other pertinent factors. Sample-based strategies have successfully tackled this problem, particularly the rapidly exploring random tree star (RRT*) algorithm. However, conventional path-searching algorithms may face challenges in the marine environment due to unique terrain undulations, sparse and unpredictable obstacles, and inconsistent results across multiple planning iterations. To address these issues, we propose a new approach specifically tailored to the distinct features of the marine environment for navigation path planning of underwater vehicles, named bidirectional cached rapidly exploring random tree star (BCRRT*). By incorporating bidirectional path planning and caching algorithms on top of the RRT*, the search process can be expedited, and an efficient path connection can be achieved. When encountering new obstacles, ineffective portions of the cached path can be efficiently modified and severed, thus minimizing the computational workload while enhancing the algorithm’s adaptability. A certain number of simulation experiments were conducted, demonstrating that our proposed method outperformed cutting-edge techniques like the RRT* in several critical metrics such as the density of path nodes, planning time, and dynamic adaptability. Full article

This pioneering study presents an in-depth biomechanical examinations of soccer’s diving header, aiming to quantify its impact on ball speed enhancement (BSE) and effective offensive range (EOR). Despite the diving header’s widespread acclaim and historical significance, there remains a dearth of scientific scrutiny into its biomechanical intricacies. Employing an innovative research design featuring a static hanging ball at varied offensive distances and heights, this study replicates diverse header scenarios. The results of 3D motion quantification have shown that a physically excellent player (identified through the maximal standing long jump test) could reach an EOR around 2.64 times his body height. Furthermore, this study unveils that proficient players could attain BSE surpassing 9 m/s, signifying the diving header’s heightened efficacy compared to traditional heading techniques, which could only result in 4.5 m/s. Correlation analyses unveil noteworthy relationships, highlighting the pivotal role of head speed at impact and the influence of minimizing speed drop and temporal disparities for amplified effectiveness. Considerations for optimizing diving header execution are introduced, emphasizing the necessity for targeted training programs. Despite acknowledged limitations inherent to its pilot nature, this exploration furnishes foundational knowledge to guide subsequent research and practical applications, providing valuable insights into soccer training and skill development through a biomechanical lens. Full article

The persistent challenge of adhesion in Fused Filament Fabrication (FFF) technology is deeply rooted in the mechanical and chemical properties of utilized materials, necessitating the exploration of potential resolutions. This involves adjustments targeting the interplay of printing parameters, the mechanical fortification of print beds, and the integration of more adhesive materials, resonating across user levels, from enthusiasts to complex industrial configurations. An in-depth investigation is outlined in this paper, detailing the plan for a systematically designed device. Engineered for FFF device installation, the device facilitates the detachment of printed models, while precisely recording the detachment process, capturing the maximum force, and its progression over time. The primary objective is fabricating a comprehensive measurement apparatus, created for adhesion assessment. The device is adaptable across diverse FFF machines and print bed typologies, conforming to pre-defined conditions, with key features including compactness, facile manipulability, and capacity for recurrent measurements. This pursuit involves evaluating adhesion levels in prints made from diverse materials on varying print bed compositions, aiming to establish a comprehensive database. This repository facilitates judicious material and bed type selection, emphasizing maximal compatibility. Emphasis is placed on operating within a thermally stable context, a pivotal prerequisite for consistent and reproducible results. Full article

The world is undergoing dynamic changes. For businesses, it brings positives, but also negatives. The positive is the global market for business. The downside of the global market is the increasing competitive pressure. Large enterprises with serial production who are setting production for a longer period ahead are not so noticeable. Small companies are the most vulnerable. There are various tools or overall approaches to business management that allow them to increase work efficiency or production productivity or eliminate waste. In recent years, one can see an increase in the popularity of Lean or Six Sigma. Their contribution to businesses cannot be disputed. Most of the tools and approaches to support business management are oriented or based on the conditions of serial production. Small businesses with piece production are at a disadvantage here. It was this fact that motivated us to focus on piece production and to find space for the implementation of supporting tools that could be helpful. Our research has shown that there are tools that can be applied in the conditions of piece production. The application of the identified tools proved that the results achieved in reducing production times or increasing productivity are unmistakable. Full article

Wire and cable are important industrial products involving the national economy and people’s livelihood, which are hailed as the “blood vessel” and “nerve” of the national economy, providing the basic guarantee for the normal operation of modern economy and society. The data traceability of their production and circulation process is a key factor in ensuring their quality and safety management. We aim to solve the problems of unsafe data transmission, weak quality control, and information islands in the process of wire and cable quality traceability in order to improve the production management efficiency of wire and cable manufacturing enterprises and to reduce the cost of consumer quality traceability of wire and cable products. We analyzed the technical characteristics and advantages of Industrial Internet of Things (IIoT) identity resolution and the blockchain. Key technologies are introduced, a traceability method that integrates the two is proposed, and a quality traceability framework based on the IIoT identity resolution system and blockchain technology is constructed. By analyzing the quality information composition of the wire and cable supply chain, a new quality traceability model based on the wire and cable supply chain is established. Finally, through the verification of the developed quality traceability system, the quality traceability function and quality information of each production link of wire and cable are successfully realized. This paper fills a gap in the field of cable product quality traceability using the combination of IIoT and blockchain technology. According to this model, it also has some potential for the traceability of other industrial products. Full article

Conventional traffic stability studies primarily concentrate on the evolution of disturbances in vehicle motion but seldom consider how collision risk changes spatially and temporally. This study bridges the gap by extending the principles of traffic stability analysis to the field of traffic safety, focusing specifically on the temporal and spatial dynamics of collision risk. Leveraging the concepts of local and string stability, we formulate conditions under which collision risk behaves in a stable manner over time and space through the transfer function approach. A comparative analysis between conventional traffic stability and the newly introduced concept of collision risk stability reveals that while conditions for local stability are largely aligned in both domains, the criteria for string stability differ. These theoretical insights are substantiated through microscopic simulations using a variety of car-following models. The simulations also indicate that the consistency between theoretical and simulation outcomes diminishes as the disturbance magnitude increases, which is attributed to the linearization errors inherent in applying the transfer function in the theoretical derivations. Full article

Multiple markers are generally used in augmented reality (AR) applications that require accurate registration, such as medical and industrial fields. In AR using these markers, there are two inevitable problems: (1) geometric shape discrepancies between a real object and a virtual object, and (2) the relative positions of the markers placed on the virtual object and markers placed on the real object are not consistent. However, studies on applying multiple markers to a large object are still insufficient. Additionally, most studies did not consider these inevitable problems because the markers were subjectively placed (hereafter conventional method). In consideration of these problems, this paper proposes a method for placing multiple markers to provide accurate registration on a large object. The proposed method divides a virtual object evenly and determines the positions of multiple markers automatically using 3D interest points within the divided areas. The proposed method was validated through a performance comparison with the conventional method of subjectively placing markers, and it was confirmed to have more accurate registration. Full article

Pulau Baai Port, located strategically in the Indian Ocean and considered a vital maritime hub in Indonesia, grapples with persistent challenges related to abrasion and sedimentation, which negatively impact its maritime infrastructure. One of the affected components is the exposed gas pipeline installation along the port’s coastline. The sedimentation rate along Pulau Baai’s coastline is alarming, ranging from 600,000 to 800,000 m³/year, resulting in coastal abrasion at a rate of up to 20 m/year. This study focuses on three scenarios using MIKE 21, including a baseline without alternatives, shore protection alternatives, and jetty protection alternatives. A comprehensive dataset, incorporating bathymetric maps, wave patterns, current data, and sediment characteristics, supports the analysis of coastal dynamics, emphasizing the urgency for intervention. The research introduces the novelty of analyzing coastal abrasion through the exposure of underground pipelines, establishing a relationship between impacting factors such as wave height, tides, sedimentation, and coastal abrasion. Mitigation alternatives, particularly alternative model-2 with jetty protection, are recommended based on a thorough evaluation of the model performance and actual measurements. The results show that Pulau Baai’s sediment, primarily sandy, experiences substantial abrasion and coastline changes, notably in alternatives-2 and -3. The study anticipates potential sedimentation in certain sections of the subsea exposed pipelines in the absence of shore protection. The outcomes of this research provide a foundational guide for informed decision making and strategies to ensure the sustainable functionality of maritime infrastructure in Pulau Baai and similar coastal regions. Full article

The aim of this study is to investigate the effects of serum vitamin D levels on the healing of different bone graft materials. Thirty-six male rats were divided into three groups and fed special feeds containing different amounts of vitamin D for 6 weeks before the surgical phase: the high serum vitamin D level group (group H) 10,000 iu/kg vitamin D3; the standard serum vitamin D level group (group C) 1000 iu/kg D3; and the low-level vitamin D group (group L) 100 iu/kg vitamin D3. Under general anesthesia, four defects with a diameter of 5 mm were created in the calvaria of the rats. The defects were augmented with autogenous grafts, allografts, xenografts, or left empty. The serum vitamin D level was measured before the surgery and before sacrifice. At the end of the 6th week, the subjects were sacrificed, and histological and histomorphometric analyses were performed. Study results show that in all graft types, as vitamin D levels increase, the number of new bone formations increases. There was no significant difference between the graft materials in terms of new bone formation criteria in group L. In group H and group C, the highest new bone formation was seen in the allograft group (1.48 ± 0.07, 0.66 ± 0.19, respectively). Prospective randomized clinical studies are required to evaluate the effect of vitamin D dose on the success of augmentation procedures in the clinic. Full article

Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a detection system. Firstly, we have improved YOLOv7 by integrating new convolution operators into the Extended-Efficient Layer Aggregation Network for optimized feature extraction, reducing computations while capturing spatial features effectively. Secondly, to enhance the performance of the feature fusion network, we use Receptive Field Block as the feature pyramid of YOLOv7 and introduce Content-Aware ReAssembly of FEatures as upsampling operators for PRC-Light YOLO. By generating real-time adaptive convolution kernels, this module extends the receptive field, thereby gathering vital information from contexts with richer content. To further optimize the efficiency of model training, we apply the HardSwish activation function. Additionally, the bounding box loss function adopts the Wise-IOU v3, which incorporates a dynamic non-monotonic focusing mechanism that mitigates adverse gradients from low-quality instances. Finally, in order to enhance the PRC-Light YOLO model’s generalization ability, we apply data augmentation techniques to the fabric dataset. In comparison to the YOLOv7 model, multiple experiments indicate that our proposed fabric defect detection model exhibits a decrease of 18.03% in model parameters and 20.53% in computational load. At the same time, it has a notable 7.6% improvement in mAP. Full article

The integration of large-scale wind power into the power grid threatens the stable operation of the power system. Traditional wind power prediction is based on time series without considering the variability between wind turbines in different locations. This paper proposes a wind power probability density prediction method based on a time-variant deep feed-forward neural network (ForecastNet) considering a spatio-temporal distribution. First, the outliers in the wind turbine data are detected based on the isolated forest algorithm and repaired through Lagrange interpolation. Then, based on the graph attention mechanism, the features of the proximity node information of the individual wind turbines in the wind farm are extracted and the input feature matrix is constructed. Finally, the wind power probability density prediction results are obtained using the ForecastNet model based on three different hidden layer variants. The experimental results show that the ForecastNet model with a hidden layer as a dense network based on the attention mechanism (ADFN) predicts better. The average width of the prediction intervals at achieved confidence levels for all interval coverage is reduced by 34.19%, 35.41%, and 35.17%, respectively, when compared to the model with the hidden layer as a multilayer perceptron. For different categories of wind turbines, ADFN also achieves relatively narrow interval average widths of 368.37 kW, 315.87 kW, and 299.13 kW, respectively. Full article

Research and development of the DEMOnstration power plant (DEMO) breeder blanket (BB) has been performed in recent years based on a predefined DEMO tritium breeding ratio (TBR) requirement, which determines a loss of wall surface due to non-breeding in-vessel components (IVCs) which consume plasma-facing wall surface and do not contribute to the breeding of tritium. The integration of different IVCs, such as plasma limiters, neutral beam injectors, electron cyclotron launchers and diagnostic systems, requires cut-outs in the BB, resulting in a loss of the breeder blanket volume, TBR and power generation, respectively. The neutronic analyses presented here have the goal of providing an assessment of the TBR losses associated with each IVC. Previously performed studies on this topic were carried out with simplified, homogenized BB geometry models. To address the effect of the detailed heterogeneous structure of the BBs on the TBR losses due to the inclusion of the IVCs in the tokamak, a series of blanket geometry models were developed for integration in the latest DEMO base model. The assessment was performed for both types of BBs currently developed within the EUROfusion project, the helium-cooled pebble bed (HCPB) and water-cooled lead–lithium (WCLL) concepts, and for the water-cooled lead and ceramic breeder (WLCB) hybrid BB concept. The neutronic simulations were performed using the MCNP6.2 Monte Carlo code with the Joint Evaluated Fission and Fusion File (JEFF) 3.3 data library. For each BB concept, a 22.5° toroidal sector of the DEMO tokamak was developed to assess the TBR and nuclear power generation in the breeder blankets. For the geometry models with the breeder blanket space filled only with blankets without considering IVCs, the results of the TBR calculations were 1.173, 1.150 and 1.140 for the HCPB, WCLL and WLCB BB concepts, respectively. The TBR impact of all IVCs and the losses of the power generation were estimated as a superposition of the individual effects. Full article

Similarity measures in heterogeneous information networks (HINs) have become increasingly important in recent years. Most measures in such networks are based on the meta path, a relation sequence connecting object types. However, in real-world scenarios, there exist many complex semantic relationships, which cannot be captured by the meta path. Therefore, a meta structure is proposed, which is a directed acyclic graph of object and relation types. In this paper, we explore the complex semantic meanings in HINs and propose a meta-structure-based similarity measure called StructSim. StructSim models the probability of subgraph expansion with bias from source node to target node. Different from existing methods, StructSim claims that the subgraph expansion is biased, i.e., the probability may be different when expanding from the same node to different nodes with the same type based on the meta structure. Moreover, StructSim defines the expansion bias by considering two types of node information, including out-neighbors of current expanded nodes and in-neighbors of next hop nodes to be expanded. To facilitate the implementation of StructSim, we further designed the node composition operator and expansion probability matrix with bias. Extensive experiments on DBLP and YAGO datasets demonstrate that StructSim is more effective than the state-of-the-art approaches. Full article

Dual-polarization division multiplexing (DPDM) is considered to be a potential method to boost the secure key rate (SKR) of the continuous-variable quantum key distribution (CV-QKD) system. In this article, we propose a pilot alternately assisted local local oscillator (LLO) CV-QKD scheme based on multi-dimensional multiplexing, where time division multiplexing and frequency division multiplexing are combined with dual-polarization multiplexing techniques to dramatically isolate the quantum signal from the pilot tone. We establish a general excess noise model for the LLO CV-QKD system to analyze the influence mechanism of various disturbances (e.g., time-domain diffusion, frequency-domain modulation residual, and polarization perturbation) on the key parameters, such as the channel transmittance and excess noise. Specifically, the photon leakage noise from the reference path to the quantum path and that between quantum signals with two different polarization paths are simultaneously analyzed in the dual-polarization LLO CV-QKD scheme for the first time. Furthermore, a series of simulations are established to verify the performance of the proposed scheme. The results show that the maximal isolation degree achieves 84.0 dB~90.4 dB, and the crosstalk between pilot tones and quantum signals can be suppressed to a very small range. By optimizing the system parameters (e.g., modulation variance and repetition frequency), the SKR with 12.801 Mbps@25 km is achieved under the infinite polarization extinction ratio (PER) and 30 dB residual ratio of the frequency modulation in the nanosecond-level pulse width. Moreover, the performance of the proposed DPDM CV-QKD scheme under relatively harsh conditions is simulated; the results show that the SKR with 1.02 Mbps@25 km is achieved under a relatively low PER of 17 dB with the nanosecond-level pulse width and 20 dB residual ratio of the frequency modulation. Our work lays an important theoretical foundation for the practical DPDM LLO CV-QKD system. Full article

Urban landscape parks play a crucial role in providing recreational opportunities for citizens. Different types of landscapes offer varying levels of comfort experiences. However, the assessment of landscape comfort primarily relies on subjective evaluations and basic physiological measurements, which lack sufficient quantification of relevant data. This study employed electroencephalography (EEG) technology and subjective questionnaire evaluation methods. Participants observed two sets of landscape demonstration videos using virtual reality (VR) devices, and EEG alpha values and subjective evaluation scores were collected to assess the comfort levels of free-form landscape and regular-form landscape. Additionally, this study explored the correlation between landscape characteristics and physiological comfort. The analysis of the results showed that: 1. The average amplitude of EEG alpha waves recorded from 11 electrodes in the left temporal lobe and right parietal lobe of the participants was higher after they watched the free-form landscape demonstration. The increased alpha values suggest that free-form landscapes are more likely to induce physiological comfort in these specific brain regions. In contrast, regular-form landscape was found to induce higher alpha values at seven specific electrodes located in the occipital cortex, right temporal lobe, and central regions of the participants. In general, free-form landscape provided physiological comfort to a greater number of brain regions. 2. The two groups of landscapes exhibit distinct subjective cognitive differences in terms of their landscape characteristics. These differences, ranked in order of magnitude, include rhythmicity, sense of order, sense of security, and sense of dependence. 3. This study examined the α-waves of specific brain regions, including the right and left temporal lobe and occipital lobe, as well as subjective scoring. It discovered that the rhythmicity, degree of variation, degree of color, and sense of nature of a landscape impact the α-wave value of electrodes in different brain regions. Moreover, there exists a certain linear relationship between the four landscape features and the α-wave values in different regions of the brain. The results of this study provide some reference for the creation of a comfortable landscape design. Full article

This work is a follow-up to previous research by our team and is devoted to studying a dual-sinusoidal placement of distributed fiber-optic sensors (FOSs) that are embedded inside an adhesive joint between two composite laminates. The constructed smart continuous fiber-reinforced polymer composite structure is well suited to the structural health monitoring (SHM) system for offshore wind turbine blades. Three main drawbacks of SHM through embedded distributed FOSs, however, have been identified in this article, so their impact must be analyzed. Despite existing research, the influence of the dual-sinusoidal placement under various loading conditions on structural mechanical behavior and sensing functionality has not been considered yet since its introduction. Thus, this study aims to identify the resulting strain patterns and sensing capabilities from an optimized dual-sinusoidal placement of FOSs in various loading cases through finite element modeling. Ultimately, this work illustrates the strain-measuring advantages of dual-sinusoidal FOSs, explains the correspondence between the strains measured by FOSs and that of host structures, and discusses the balance among mechanical influences, sensing functions, and monitoring coverage. It is worth noting that the current work is a still introductory concept that aims at refining key parameters that have been emphasized in previous research, before starting an applied study that will consider both numerical and validation steps on real large smart composite structures. Full article

In order to solve the problems of low efficiency and complex cutting tools in conventional face gear machining, this paper presents a machining method of ruled surface face gears with conical cutters and proposes a new pinion to correct deviation and its machining method. Firstly, the mathematical models of ruled surface face gears and conical cutters are established, the motion rules of the conical cutter are derived, and the influence of basic parameters on the tooth surface deviation between ruled surface and conventional surface is analyzed. Secondly, for the sake of correction of tooth surface deviation, reverse conjugation is applied to the ruled surface to obtain a corrected pinion. On the basis of hobbing cylindrical gears, the purpose of machining corrected pinions is achieved by increasing CNC motions. Finally, the manufacturing process is simulated by VERICUT software, the results demonstrate that the machining error of ruled surface and pinion do not exceed 10 μm, and through LTCA, the meshing performance of the ruled surface face gear pair is basically the same as that of conventional face gear pair, proving the feasibility of replacing the latter with the former. This study provides a new manufacturing method for face gears. Full article

This paper develops a material-structure integrated design and optimization method based on a multiscale approach for the lightweight design of CFRP car doors. Initially, parametric modeling of RVE is implemented, and their elastic performance parameters are predicted using the homogenization theory based on thermal stress, exploring the impact of RVE parameters on composite material performance. Subsequently, a finite element model of the CFRP car door is constructed based on the principle of equal stiffness, and a parameter transfer across microscale, mesoscale, and macroscale levels is achieved through Python programming. Finally, the particle generation and updating strategies in the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm are improved, enabling the algorithm to directly solve multi-constraint and multi-objective optimization problems that include various composite material layup process constraints. Case study results demonstrate that under layup process constraints and car door stiffness requirements, plain weave, twill weave, and satin weave composite car doors achieve weight reductions of 15.85%, 14.54%, and 15.35%, respectively, compared to traditional metal doors, fulfilling the requirements for a lightweight design. This also provides guidance for the lightweight design of other vehicle body components. Full article

Traditional villages, rich in historical and cultural value, hold a high level of preservation value. In the process of urbanization, traditional villages face the crisis of decline, making it difficult to perpetuate the carried cultural heritage. The Ganjiang River Basin hosts numerous traditional villages with rich research value, making the study of their preservation and development in this region a significant topic. This paper, from the perspective of landscape ecology, employs geographic detectors to analyze the driving factors behind the emergence of traditional villages in the Ganjiang River Basin, summarizing the spatial distribution characteristics of traditional villages. A classification method based on village landscape features is adopted to categorize traditional villages in the Ganjiang River Basin, providing a reference for planning the preservation and development of traditional villages. The research results show that plain areas are more suitable for the continuation of traditional villages; a single suitable environmental element cannot provide an environment conducive to the development of traditional villages, which is the result of the combined effect of multiple suitable elements; the study has divided traditional village landscapes into nine types, with clear distribution differences among different types of villages; for different regions and types of traditional villages, it is necessary to balance development and protection tendencies and plan differently according to environmental characteristics. Full article

Aiming at the current complex problem of the mechanized high-quality picking of tender tea buds, this paper designs a tender tea bud-picking manipulator. In the picking process, the quality of the petiole and leaf blade of the tender tea bud is crucial, as the traditional cutting picking method destroys the cell structure of the tender tea buds, resulting in rapid oxidation of the cuts, thus losing the bright green appearance and pure taste. For this reason, this paper draws on the quality requirements of tender tea buds and traditional manual picking technology, simulating the process of the manual picking action, putting forward a ‘rotary pull-up’ clamping and ripping picking method, and designing the corresponding actuating structure. Using PVDF material piezoelectric thin-film sensors to detect the clamping force of the tender tea bud picking, the corresponding sensor hardware circuit is designed. In addition, the finite element analysis method is also used to carry out stress analysis on the mechanical fingers to verify the rationality of the automatic mechanism to ensure the high-quality picking of tender tea buds. In terms of the control of the manipulator, an SMC-PID control method is designed by using MATLAB/Simulink 2021 and Adam 2020 software for joint simulation. The way to control the closed-loop system angle and angular velocity error feedback is by adjusting the PID parameters, which quickly converts the sliding mode control to the sliding mode surface. The simulation results show that the SMC-PID control method proposed in this paper can meet the demand in tender tea bud picking and simultaneously has high control accuracy, response speed, and stability. Full article

Oxidative stress, a physiological process that can damage cells, is known to affect various aspects of oral health. Oxidative stress can influence dental implant longevity and health. Assessing biomarkers of oxidative stress in saliva is beneficial for diagnosing and tracking the progression of oral diseases. A study is made of salivary oxidative stress in patients with dental implants with or without periodontitis. The study consisted of the following groups: Group1 (healthy without dental implants); Group 2 (subjects undergoing periodontal maintenance without dental implants); Group 3 (healthy patients with implants older than six months); and Group 4 (patients undergoing periodontal maintenance with implants older than six months). A complete examination of the oral cavity was made in each patient and a questionnaire was used to assess habits of hygiene, quality of life, and information about the implants. The following parameters were recorded in unstimulated whole saliva: ferric reducing antioxidant power (FRAP), Trolox equivalent antioxidant capacity (TEAC), cupric reducing antioxidant capacity (CUPRAC), advanced oxidation protein products (AOPP), and total proteins (TP). A total of 160 patients were studied, with 40 patients per group. The mean oxidative stress biomarker values obtained in the patients without implants and with implants were FRAP 0.590 ± 0.514 and 0.588 ± 0.334 mmol/L (p = 0.974); TEAC 0.320 ± 0.223 and 0.315 ± 0.172 mmol/L (p = 0.879); CUPRAC 0.286 ± 0.216 and 0.288 ± 0.151 mmol/L (p = 0.956); AOPP 456.04 ± 789.75 and 430.65 ± 752.05 µmol/L (p = 0.838); and TP 73.90 ± 50.83 and 70.36 ± 56.93 mg/dL (p = 0.684), respectively. No substantial variations were noted in the salivary oxidative stress biomarker levels between patients with controlled periodontal disease and/or dental implants compared to healthy individuals. Full article

Aim: The aim was to assess the effect of antimicrobial photodynamic therapy (a-PDT) on the oral health-related quality of life (OHRQoL) of denture stomatitis patients. Methods: Forty patients were randomly selected to participate. Candidal proliferation was confirmed by using a CHROMagar culture and Gram staining. The denture surface and palatal mucosa were sprayed with a methylene blue photosensitizer prior to the photobiomodulation application. Laser therapy was applied two times a week at 72 h intervals for a period of 8 weeks. The OHIP-EDENT questionnaire was used to analyze the improvement in the OHRQoL. A Wilcoxon test was used to perform the candidal colony-forming unit’s count and comparison. A t-test was applied to evaluate the OHRQoL responses. Results: The overall CFU/mL values were higher in the dentures of the patients compared to a palatal mucosa swab. For instance, the CFU count was reduced from 5.56 ± 2.15 (baseline) to 3.17 ± 2.77 CFU/mL on day 60 on the palates. Similarly, the a-PDT application on the intaglio surface of the denture showed a reduction from 38.83 ± 14.71 to 29.05 ± 15.52 CFU/mL. A significant difference (p < 0.05) was found in function improvement as well as a reduction in physical pain, psychological discomfort, physical disability, and social interaction among the participants after photobiomodulation treatment. Conclusions: The OHRQoL was significantly improved in the DS patients. The Candida albicans abundance was radically reduced after the a-PDT application. Full article

The Sanshandao Gold Mine is currently in the deep mining stage. The ground pressure on the surrounding rocks is gradually becoming more considerable, and at the same time, threatened by the overlying seawater, the possibility of mine water inrush accidents is increasing. In this study, the MTS815 rock triaxial seepage test system was employed for the triaxial compression testing and stress–seepage coupled testing of granite under different confining pressures. The results show that granite’s pre-peak mechanical evolution under different confining pressures is divided into four stages (the crack closure stage, linear elasticity stage, stable crack expansion stage, and unstable crack expansion stage). With the increase in the confining pressure, the crack initiation threshold, crack damage threshold, and peak threshold gradually increased, but the closure threshold had no corresponding change. Moreover, in the loading process, the permeability curve first decreased and then increased, and the confining pressure suppressed the peak permeability of granite. Finally, based on the test results, stress sensitivity analysis was carried out, and it was found that polynomials fit the relationship between permeability and effective stress better. Granite’s permeability showed strong stress sensitivity at medium confining pressures. The stress sensitivity of the permeability of granite decreased with increasing effective stress at medium and high confining pressures, while it tended to increase at low confining pressures. Full article

Objective: The objective was to compare the shear bond strength (SBS) and the adhesive remnant index (ARI) amongst six orthodontic bracket groups. Materials and Methods: Three-dimensional printed polycrystalline alumina brackets (3DBs), ceramic brackets (CBs), and metal brackets (MBs), divided into six groups, were bonded to bovine incisors using different bonding procedures. The SBSs were obtained using a universal testing machine, and the ARIs were assessed with a stereomicroscope. The statistical analyses included one-way analysis of variance (ANOVA) for SBS differences and Fisher’s exact test to show ARI differences amongst the groups (p < 0.05). Results: No significant differences (p > 0.05) were measured amongst the SBSs of the 3DB groups (12.3 MPa, 12.6 MPa, 12.3 MPa, 11.0 MPa, respectively). The latter four groups generally had significantly lower SBSs (p < 0.001) than the conventional bracket groups, CB and MB (16.9 MPa and 19.3 MPa, respectively). Also, there was no significant difference in SBSs for the CB and MB groups (p > 0.05). A high ARI for CBs and MBs (2) indicated that more than 50% of the adhesive remained on the enamel surface. The four 3DB groups had no residual adhesive or less than 50% adhesive on the enamel surface after debonding (ARI scores 0 and 1). A significant difference in ARI levels existed across the types of brackets (p < 0.05). Conclusion: Three-dimensional printed polycrystalline alumina brackets exhibited adequate SBS values for successful bonding. However, the values were lower compared to those for conventional ceramic and metal brackets. The majority of the adhesive remnant for the 3D-printed brackets was mainly located on the bracket base. Full article

Accurate medical image segmentation is paramount for precise diagnosis and treatment in modern healthcare. This research presents a comprehensive study of the efficacy of particle swarm optimization (PSO) combined with histogram equalization (HE) preprocessing for medical image segmentation, focusing on lung CT scan and chest X-ray datasets. Best-cost values reveal the PSO algorithm’s performance, with HE preprocessing demonstrating significant stabilization and enhanced convergence, particularly for complex lung CT scan images. Evaluation metrics, including accuracy, precision, recall, F1-score/Dice, specificity, and Jaccard, show substantial improvements with HE preprocessing, emphasizing its impact on segmentation accuracy. Comparative analyses against alternative methods, such as Otsu, Watershed, and K-means, confirm the competitiveness of the PSO-HE approach, especially for chest X-ray images. The study also underscores the positive influence of preprocessing on image clarity and precision. These findings highlight the promise of the PSO-HE approach for advancing the accuracy and reliability of medical image segmentation and pave the way for further research and method integration to enhance this critical healthcare application. Full article

A general and precise protocol that follows the standards of an inverse problem in engineering is proposed to estimate groundwater velocity from experimental lectures of temperature vertical profiles in a 2D aquifer. Several values of error in the temperature measurements are assumed. Since a large quantity of parameters and initial conditions influence the solution of this process, the protocol is very complex and needs to be tested to ensure its reliability. The studied scenario takes into account the input temperature of the water as well as the isothermal conditions at the surface and bottom of the aquifer. The existence of an input region, in which profiles develop to become linear, allows us to eliminate experimental measurements beyond such a region. Once the protocol is developed and tested, it is successfully applied to estimate the regional (lateral) groundwater velocity of the real aquifer and the result compared with estimations coming from the piezometric map. Full article