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Objective To analyze the ability of micro-implant nails placed in different locations in the posterior region to improve the hard and soft tissues of the labiodental region in patients with gummy smiles to provide a reference for clinicians. Methods This study was reviewed and approved by the Ethics Committee, and informed consent was obtained from the patients. Thirty young female patients with anterior tooth protrusions and gummy smiles were included in the retrospective study; 18 patients had micro-implant nails implanted between the premolars (group A), and 12 patients had implant nails placed between the roots of the premolar and the molar and an intraoperatively placed rocking-chair archwire (group B). The preoperative and postoperative distances from the incisal end of the upper mesial incisors to the lower point of the upper lip (U1-Stms), the vertical distance from the incisal end of the upper mesial incisors to the palatal plane (U1-PP), the vertical distance from the point of the alveolar ridge to the palatal plane (Spr-PP), the distance from the incisal end of the upper mesial incisors to the point of the alveolar margin (U1-Spr), and the vertical distance from the point of the proximal middle buccal cusp of the maxillary first molar to the palatal plane of the maxillary first molar (U6-PP) were measured in the cephalometric lateral radiographs of the two groups; additionally, the amount of hard and soft tissues of the upper anterior region exposedduring smiling and the maximum amount of gingiva exposed during smiling were assessed from the smile photograph. Results After correction, the lip-dentition relationship improved significantly in both groups, with an average reduction of 2.6 mm in U1-Stms, 2.4 mm in U1-PP, 1.4 mm in Spr-PP, and 0.9 mm in U1-Spr in Group A. In group B, the U1-Stms was reduced by an average of 2.3 mm, the U1-PPs by an average of 1.6 mm, the Spr-PPs by 1.4 mm, and the U1-Spr by 0.2 mm. The difference between pre- and postoperative U6-PP in both groups was not significant (P>0.05). Group A had greater ∆U1-PP and ∆U1-Spr changes than group B(PP>0.05). The amount of soft and hard tissue exposed and maximum amount of gingiva exposed in the upper anterior region of the smile were reduced in 30 patients postoperatively, with group A having anaverage reduction of 70.19% of the preoperative amount of soft and hard tissue exposed in the upper anterior region and an average reduction of 24.12% of the preoperative maximum amount of gingiva exposed, and group B having an average reduction of 76.12% of the preoperative amount of hard and soft tissue exposed in the upper anterior region and an average reduction of 31.88% of the preoperative maximum gingiva exposed after the operation. The difference in the ratio between the two groups was not statistically significant (P>0.05). Conclusion For patients with proptosis and gummy smiles, placing micro-implant nails between the roots of maxillary premolars can effectively lead to retraction and intrusion of anterior teeth to improve the lip-dentition relationship and improve gummy smile, and placing micro-implant nails between the roots of the maxillary second premolar and the first molar together with the use of rocking chair arches can also achieve a good therapeutic effect.

To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item parameters of new items. Three simulation studies with simulated and real item banks were conducted to investigate the performance of the proposed method and compare it with the joint estimation algorithm (JEA) and the single-item estimation (SIE) methods. The results indicated that the proposed Gini-based online calibration method yielded higher calibration efficiency than those of the SIE method and outperformed the JEA method on item calibration tasks in terms of both accuracy and efficiency under most experimental conditions.

Existing semi-supervised medical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution mismatch. However, current copy-paste methods have three limitations: (1) training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information; (2) low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data; (3) the segmentation performance in low-contrast and local regions is less than optimal. We design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy (SADT), which enhances feature diversity and learns high-quality features to overcome these problems. To be more precise, SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data, which prevents the loss of rare labeled data. We introduce a bi-directional copy-paste mask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in pseudo-supervision. For the mixed images, Deep-Shallow Spatial Contrastive Learning (DSSCL) is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local areas. In this procedure, the features retrieved by the Student Network are subjected to a random feature perturbation technique. On two openly available datasets, extensive trials show that our proposed SADT performs much better than the state-of-the-art semi-supervised medical segmentation techniques. Using only 10% of the labeled data for training, SADT was able to acquire a Dice score of 90.10% on the ACDC (Automatic Cardiac Diagnosis Challenge) dataset. [ABSTRACT FROM AUTHOR]

Purpose: Intrinsic capacity (IC), a crucial indicator for the United Nations Decade of Healthy Ageing 2021– 2030, is defined by WHO as the foundation of functional ability, representing the composite of all physical and mental capacities of an individual. IC spans five function domains: Locomotor, psychological, cognitive, vitality, and sensory (including vision and hearing). Accurate IC assessment is vital for effective interventions, yet comparative analyses of these tools are scarce. Consequently, we evaluated the diagnostic accuracy of three IC assessment tools in individuals aged 80 and above—Integrated care for older people (ICOPE) Step 1, ICOPE Step 2, and the Lopez-Ortiz's IC scoring system. Patients and Methods: This cross-sectional analysis included a total of 475 participants aged ≥ 80 years between July 2023 and January 2024 in 11 nursing homes in Ningbo, Zhejiang Province, China. To assess that included sociodemographic and health-related information alongside the three IC tools. Diagnostic efficacy was gauged using sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), accuracy, Youden index, and the area under the curve (AUC). Results: The detection of IC decline exceeded 85% across all methods. Using ICOPE Step 2 as a benchmark, ICOPE Step 1 showed robust performance across four domains of locomotion, psychological, cognitive, and vitality, whereas the Lopez-Ortiz's IC scoring system was generally ineffective. Conclusion: All three IC assessment methods have limitations. To save resources, ICOPE Step 1 can be considered for direct assessment in non-sensory domains. Conversely, the ICOPE Step 2 and Lopez-Ortiz's IC scoring systems exhibited overly stringent and lenient thresholds, respectively. At this stage, IC assessment tools cannot balance subjectivity and objectivity; thus, it is recommended that the appropriate tool be selected according to actual application scenarios. Continuous improvement of IC assessment tools remains a requirement for future studies. [ABSTRACT FROM AUTHOR]

In order to build a digital platform for power grid, it is necessary to expedite the construction of information collection, processing and the other links, improve holographic perception ability, support multiple intelligent applications, and maximize the data value of the power Internet of Things (IoT). There are problems in massive perception layer terminals, such as different types, diverse communication modes, vertical business deployment, independent platform systems, and information collection barriers. The lack of unified standards and specifications makes it difficult to promote the construction progress of the IoT. It is, therefore, urgent and important to find a unified and universal power IoT adaptation access method to obtain a flexible, standardized, and safe access for all IoT terminals based on maximum utilization of the equipment and protection of the investment.