CVTrack: Combined Convolutional Neural Network and Vision Transformer Fusion Model for Visual Tracking.

Most single-object trackers currently employ either a convolutional neural network (CNN) or a vision transformer as the backbone for object tracking. In CNNs, convolutional operations excel at extracting local features but struggle to capture global representations. On the other hand, vision transformers utilize cascaded self-attention modules to capture long-range feature dependencies but may overlook local feature details. To address these limitations, we propose a target-tracking algorithm called CVTrack, which leverages a parallel dual-branch backbone network combining CNN and Transformer for feature extraction and fusion. Firstly, CVTrack utilizes a parallel dual-branch feature extraction network with CNN and transformer branches to extract local and global features from the input image. Through bidirectional information interaction channels, the local features from the CNN branch and the global features from the transformer branch are able to interact and fuse information effectively. Secondly, deep cross-correlation operations and transformer-based methods are employed to fuse the template and search region features, enabling comprehensive interaction between them. Subsequently, the fused features are fed into the prediction module to accomplish the object-tracking task. Our tracker achieves state-of-the-art performance on five benchmark datasets while maintaining real-time execution speed. Finally, we conduct ablation studies to demonstrate the efficacy of each module in the parallel dual-branch feature extraction backbone network.

Instance Segmentation and Ensemble Learning for Automatic Temperature Detection in Multiparous Sows.

The core body temperature serves as a pivotal physiological metric indicative of sow health, with rectal thermometry prevailing as a prevalent method for estimating core body temperature within sow farms. Nonetheless, employing contact thermometers for rectal temperature measurement proves to be time-intensive, labor-demanding, and hygienically suboptimal. Addressing the issues of minimal automation and temperature measurement accuracy in sow temperature monitoring, this study introduces an automatic temperature monitoring method for sows, utilizing a segmentation network amalgamating YOLOv5s and DeepLabv3+, complemented by an adaptive genetic algorithm-random forest (AGA-RF) regression algorithm. In developing the sow vulva segmenter, YOLOv5s was synergized with DeepLabv3+, and the CBAM attention mechanism and MobileNetv2 network were incorporated to ensure precise localization and expedited segmentation of the vulva region. Within the temperature prediction module, an optimized regression algorithm derived from the random forest algorithm facilitated the construction of a temperature inversion model, predicated upon environmental parameters and vulva temperature, for the rectal temperature prediction in sows. Testing revealed that vulvar segmentation IoU was 91.50%, while the predicted MSE, MAE, and R2 for rectal temperature were 0.114 °C, 0.191 °C, and 0.845, respectively. The automatic sow temperature monitoring method proposed herein demonstrates substantial reliability and practicality, facilitating an autonomous sow temperature monitoring.

Body Weight Estimation for Pigs Based on 3D Hybrid Filter and Convolutional Neural Network.

The measurement of pig weight holds significant importance for producers as it plays a crucial role in managing pig growth, health, and marketing, thereby facilitating informed decisions regarding scientific feeding practices. On one hand, the conventional manual weighing approach is characterized by inefficiency and time consumption. On the other hand, it has the potential to induce heightened stress levels in pigs. This research introduces a hybrid 3D point cloud denoising approach for precise pig weight estimation. By integrating statistical filtering and DBSCAN clustering techniques, we mitigate weight estimation bias and overcome limitations in feature extraction. The convex hull technique refines the dataset to the pig's back, while voxel down-sampling enhances real-time efficiency. Our model integrates pig back parameters with a convolutional neural network (CNN) for accurate weight estimation. Experimental analysis indicates that the mean absolute error (MAE), mean absolute percent error (MAPE), and root mean square error (RMSE) of the weight estimation model proposed in this research are 12.45 kg, 5.36%, and 12.91 kg, respectively. In contrast to the currently available weight estimation methods based on 2D and 3D techniques, the suggested approach offers the advantages of simplified equipment configuration and reduced data processing complexity. These benefits are achieved without compromising the accuracy of weight estimation. Consequently, the proposed method presents an effective monitoring solution for precise pig feeding management, leading to reduced human resource losses and improved welfare in pig breeding.

CAT-CBAM-Net: An Automatic Scoring Method for Sow Body Condition Based on CNN and Transformer.

Sow body condition scoring has been confirmed as a vital procedure in sow management. A timely and accurate assessment of the body condition of a sow is conducive to determining nutritional supply, and it takes on critical significance in enhancing sow reproductive performance. Manual sow body condition scoring methods have been extensively employed in large-scale sow farms, which are time-consuming and labor-intensive. To address the above-mentioned problem, a dual neural network-based automatic scoring method was developed in this study for sow body condition. The developed method aims to enhance the ability to capture local features and global information in sow images by combining CNN and transformer networks. Moreover, it introduces a CBAM module to help the network pay more attention to crucial feature channels while suppressing attention to irrelevant channels. To tackle the problem of imbalanced categories and mislabeling of body condition data, the original loss function was substituted with the optimized focal loss function. As indicated by the model test, the sow body condition classification achieved an average precision of 91.06%, the average recall rate was 91.58%, and the average F1 score reached 91.31%. The comprehensive comparative experimental results suggested that the proposed method yielded optimal performance on this dataset. The method developed in this study is capable of achieving automatic scoring of sow body condition, and it shows broad and promising applications.

Comparison of flash-free and conventional bonding systems: A systematic review and meta-analysis.

OBJECTIVES: To review the literature systematically to compare the performance of adhesive precoated flash-free bonding systems with conventional adhesive precoated (APC) and operator-coated (OPC) bonding systems. MATERIALS AND METHODS: PubMed, Cochrane Library, Web of Science, and Embase were searched for potential eligible studies. Study selection and data collection were conducted independently. Statistical analysis was performed by Review Manager 5.3. The Cochran Q test was used to test heterogeneity in the included studies. Risk of bias was evaluated using Cochrane RoB 2.0 tool for randomized controlled trials. RESULTS: Six studies were included and the overall risk-of-bias judgment was low risk of bias to some concerns. The results of the meta-analyses showed that flash-free required significantly less bonding time than APC (mean difference [MD]: -1.56; 95% confidence intervals [CIs]: -2.56 to -0.56), and no significant differences were found in bond failure rates (risk ratio [RR]: 1.54; 95% Cis: 0.27 to 8.89) and adhesive remnant index (ARI) (MD: -0.50; 95% CIs: -1.14 to 0.14) between them. Qualitative analysis showed that flash-free might have a positive effect on enamel demineralization compared to APC but the quantity of plaque did not differ between them. CONCLUSIONS: The flash-free bonding system significantly reduced bonding time and it had comparable bond failure rates with APC. So far, there is not enough evidence to support its positive effect on reducing enamel demineralization and the pathogenic bacteria around brackets. In summary, flash-free might be a better choice for clinical bracket bonding.

Design and Optimization for Mounting Primary Mirror with Reduced Sensitivity to Temperature Change in an Aerial Optoelectronic Sensor.

In order to improve the image quality of the aerial optoelectronic sensor over a wide range of temperature changes, high thermal adaptability of the primary mirror as the critical components is considered. Integrated optomechanical analysis and optimization for mounting primary mirrors are carried out. The mirror surface shape error caused by uniform temperature decrease was treated as the objective function, and the fundamental frequency of the mirror assembly and the surface shape error caused by gravity parallel or vertical to the optical axis are taken as the constraints. A detailed size optimization is conducted to optimize its dimension parameters. Sensitivities of the optical system performance with respect to the size parameters are further evaluated. The configuration of the primary mirror and the flexure are obtained. The simulated optimization results show that the size parameters differently affect the optical performance and which factors are the key. The mirror surface shape error under 30 °C uniform temperature decrease effectively decreased from 26.5 nm to 11.6 nm, despite the weight of the primary mirror assembly increases by 0.3 kg. Compared to the initial design, the value of the system's modulation transfer function (0° field angle) is improved from 0.15 to 0.21. Namely, the optical performance of the camera under thermal load has been enhanced and thermal adaptability of the primary mirror has been obviously reinforced after optimization. Based on the optimized results, a prototype of the primary mirror assembly is manufactured and assembled. A ground thermal test was conducted to verify difference in imaging quality at room and low temperature, respectively. The image quality of the camera meets the requirements of the index despite degrading.

Association Between the TaqI (rs731236 T>C) Gene Polymorphism and Dental Caries Risk: A Meta-analysis.

Objective: This study investigated the association of the TaqI (rs731236 T>C) polymorphism in the VDR gene with dental caries. Methods: A comprehensive literature search was performed in PubMed, Web of Science, Embase, SinoMed (the Chinese biomedical literature service system), and the Wiley Online Library. Overall comparisons and subgroup analyses based on ethnicity and the presence of dental caries in dentition were performed. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to assess associations between gene polymorphisms and the risk of dental caries. Results: Seven articles were included in this meta-analysis. The pooled results revealed a significant association of the TaqI (rs731236 T>C) polymorphism with dental caries in the allele contrast model (C vs. T: OR = 1.24, 95% CI = 1.07-1.44, I2 = 42%, p = 0.005) and in the recessive genetic model (CC vs. TT/CT: OR = 1.38, 95% CI = 1.03-1.84, I2 = 0%, p = 0.03). A stratified analysis based on ethnicity revealed a significant association between the TaqI (rs731236 T>C) polymorphism and the risk of dental caries in Asians (C vs. T: OR = 1.28, 95% CI = 1.06-1.54, I2 = 60%, p = 0.009). Subgroup analysis based on the presence of dental caries in dentition found a significant association of the TaqI (rs731236 T>C) polymorphism with permanent tooth caries in the allele contrast model (C vs. T: OR = 1.40, 95% CI = 1.11-1.77, I2 = 76%, p = 0.005) and the recessive genetic model (CC vs. TT/CT: OR = 1.44, 95% CI = 1.03-2.00, I2 = 0%, p = 0.03). Conclusion: The results of this meta-analysis suggest that the C allele and CC genotype of the TaqI (rs731236 T>C) polymorphism in the VDR gene are associated with an increased risk of dental caries.

Astaxanthin inhibits inflammation of human periodontal ligament cells induced by lipopolysaccharide. / è™¾é’ç´ æŠ‘åˆ¶è„‚å¤šç³–è¯±å¯¼äººç‰™å‘¨è†œç»†èƒžç‚Žç—‡ååº”.

OBJECTIVES: Human periodontal ligament cells (hPDLCs) are important source of periodontal tissue reconstruction. Under chronic inflammation, the multi-directional differentiation potential and chemotaxis in hPDLCs are decreased. Therefore, inhibiting inflammatory microenvironment and improving the functional characteristics of stem cells can better promote periodontal tissue reconstruction. This study was to investigate the effect of astaxanthin (AST) on lipopolysaccharide (LPS)-induced inflammation in hPDLCs and the underlying mechanisms. METHODS: hPDLCs were isolated and cultured in vitro, and vimentin and keratin immunocytochemical staining were used to identify hPDLCs. CCK-8 assay was used to measure the effects of AST (1, 5, 10, 20, 50, 100, and 200 µmol/L) on proliferation of hPDLCs. Quantitative RT-PCR (RT-qPCR) and ELISA were used to measure the mRNA and protein expression of inflammatory factors (IL-6, IL-1ß, and TNF-α) in the control (Con) group, the LPS group, and the LPS+AST (5, 10, 20, and 50 µmol/L) group. Western blotting was used to detect the protein expression of IKBα, phosphorylated IKBα (p-IKBα), and p65 in the Con group, the LPS group, the AST (20 µmol/L) group, and the LPS+AST (20 µmol/L) group. After 10 µmol/L PDTC treatment, the mRNA and protein expressions of IL-6, IL-1ß, and TNF-α were detected by RT-qPCR and ELISA. RESULTS: Cell morphology and immunocytochemical staining showed that the cells were in line with the characteristics of hPDLCs. Treatment with AST could promote the proliferation of hPDLCs, which reached the peak at 20 µmol/L. The mRNA and protein expressions of IL-6, IL-1ß, and TNF-α in the LPS group were higher than those in the Con group (all P<0.05). Compared with the LPS group, the mRNA and protein expressions of IL-6, IL-1ß, and TNF-α in the LPS+AST (5, 10, 20, and 50 µmol/L) group were down-regulated (all P<0.05). Compared with the Con group, the levels of IKBα and p65 in cytoplasm of the LPS group were significantly downregulated (both P<0.05), and the levels of p-IKBα in cytoplasm and p65 in nucleus of the LPS group were significantly up-regulated (both P<0.05). Compared with the LPS group, the levels of IKBα and p65 in cytoplasm of the LPS+AST (20 µmol/L) group were significantly upregulated (both P<0.05), and the levels of p-IKBα in cytoplasm and p65 in nucleus of the LPS+AST (20 µmol/L) group were significantly downregulated (both P<0.05). The mRNA and protein expressions of IL-6, IL-1ß, and TNF-α in the LPS+PDTC (10 µmol/L) group were lower than those in the LPS group (all P<0.05). CONCLUSIONS: AST promotes the proliferation of hPDLCs, which is related to suppression of LPS-induced the secretion of inflammatory factors via inhibiting the activation of NF-κB signaling pathway.

Effectiveness of orthodontic temporary anchorage devices in canine retraction and anchorage preservation during the two-step technique: a systematic review and meta-analysis.

BACKGROUND: Temporary anchorage devices have been used for decades in orthodontic practice for many applications. The aim of this systematic review was to assess the effectiveness of orthodontic temporary anchorage devices in canine retraction during the two-step technique. METHODS: A search was systematically performed for articles published prior to June 30, 2019 in five electronic databases (PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, Scopus). The risk of bias was assessed using the Cochrane risk of bias tool for randomized controlled trials (RCTs) and the risk of bias in nonrandomized studies of interventions (ROBINS-I) tool for controlled clinical trials (CCTs). The Grading of Recommendation, Assessment, Development and Evaluation (GRADE) approach was used for the quality assessment. Data concerning the mean difference in mesial molar movement and extent of canine retraction were extracted for statistical analysis. The mean differences and 95% confidence intervals were analyzed for continuous data. A meta-analysis with a random-effects model for comparable outcomes was carried out. RESULTS: Three RCTs and five CCTs were finally included. Meta-analysis showed a significant increase not only in anchorage preservation in the implant anchorage group in both the maxilla (1.56 mm, 95% CI: 1.14 to 1.98, P < 0.00001) and the mandible (1.62 mm, 95% CI: 1.24 to 2.01, P < 0.00001) but also in canine retraction in the implant anchorage group in both the maxilla (0.43 mm, 95% CI: 0.16 to 0.69, P = 0.001) and the mandible (0.26 mm, 95% CI: 0.02 to 0.49, P = 0.03). CONCLUSIONS: There is very low-quality evidence showing that implant anchorage is more efficient than conventional anchorage during canine retraction. Additional high-quality studies are needed.

Application of Two-Photon-Absorption Pulsed Laser for Single-Event-Effects Sensitivity Mapping Technology.

Single-event effects (SEEs) in integrated circuits and devices can be studied by utilizing ultra-fast pulsed laser system through Two Photon Absorption process. This paper presents technical ways to characterize key factors for laser based SEEs mapping testing system: output power from laser source, spot size focused by objective lens, opening window of Pockels cell, and calibration of injected laser energy. The laser based SEEs mapping testing system can work in a stable and controllable status by applying these methods. Furthermore, a sensitivity map of a Static Random Access Memory (SRAM) cell with a 65 nm technique node was created through the established laser system. The sensitivity map of the SRAM cell was compared to a map generated by a commercial simulation tool (TFIT), and the two matched well. In addition, experiments in this paper also provided energy distribution profile along Z axis that is the direction of the pulsed laser injection and threshold energy for different SRAM structures.