A Novel Finger-Controlled Passive RFID Tag Design for Human-Machine Interaction.

Radio frequency identification (RFID) has shown its potential in human-machine interaction thanks to its inherent function of identification and relevant physical information of signals, but complex data processing and undesirable input accuracy restrict its application and promotion in practical use. This paper proposes a novel finger-controlled passive RFID tag design for human-machine interaction. The tag antenna is based on a dipole antenna with a separated T-match structure, which is able to adjust the state of the tag by the press of a finger. The state of the proposed tag can be recognized directly by the code received by the RFID reader, and no complex data processing is needed. Since the code is hardly affected by surroundings, the proposed tag is suitable to be used as a wireless switch or control button in multiple scenarios. Moreover, arrays of the proposed tag with rational tag arrangements could contribute to a series of manual control devices, such as a wireless keyboard, a remote controller, and a wireless gamepad, without batteries. A 3 × 4 array of the finger-controlled tag is presented to constitute a simple passive RFID keyboard as an example of the applications of the proposed tag array and it refers to the arrangement of a keypad and can achieve precise, convenient, quick, and practical commands and text input into machines by pressing the tags with fingers. Simulations and measurements of the proposed tag and tag array have been carried out to validate their performances in human-machine interaction.

Fear of disease progression among breast cancer patients in China: a meta-analysis of studies using the fear of progression questionnaire short form.

Background: Fear of disease progression (FoP) is among the most prevalent and major psychological burdens breast cancer patients encounter. Excessive FoP may result in serious adverse effects for patients. FoP in breast cancer patients has gained attention recently; however, its prevalence in China is unknown. Objectives: This meta-analysis and systematic review aimed to assess the overall FoP among Chinese breast cancer patients to make recommendations for treatment and care. Methods: Systematic search databases included PubMed, EMbase, The Cohrane Library, Web of Science, CINAHL, PsycINFO and 4 Chinese databases (Wan Fang Data, CBM, VIP and CNKI). The retrieval time ranged from the database's establishment to March 20, 2023. After two researchers independently evaluated the literature, retrieved information, and assessed the risk of bias for the included literature, Stata 15.1 software was used to conduct a meta-analysis. Results: A total of 37 moderate or high-quality studies involving 9,689 breast cancer patients were included. Meta-analysis showed that the pooled mean score of FoP for Chinese breast cancer patients was 33.84 [95% CI (31.91, 35.77)], prediction interval (21.57 ~ 46.11). The subgroup study found that FoP levels varied among breast cancer patients of different regions, ages, educational levels, marital statuses, residences, illness stages, and disease statuses. Conclusion: Breast cancer patients have higher FoP scores. Healthcare workers should be concerned. We expect that more relevant research will be undertaken and more effective interventions will be developed. Patients can manage their illness and improve their quality of life by reducing their fears. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: PROSPERO CRD42023408914.

The prevalence of diabetes distress in Chinese patients with type 2 diabetes: A systematic review and meta-analysis.

OBJECTIVE: To systematically evaluate the prevalence of Diabetes Distress (DD) in type 2 diabetes mellitus (T2DM) patients in China. METHODS: The PubMed, PsycInfo, Web of Science, The Cochrane Library, EMBASE, China Knowledge Resource in Integrated Database (CNKI), WanFang Database, Weipu Database (VIP), and Chinese Biomedical Database (CBM) electronic databases were searched from inception to August 2022, for cross-sectional studies, that reported prevalence of DD. RESULTS: This study included 55 articles involving 13,160 patients with T2DM. The pooled prevalence of DD was 53.2%. The results of the subgroup analysis showed that among the five regions in China, the highest prevalence of DD was observed in Central China (66%), while the lowest prevalence was recorded in North China (23%). The highest prevalence of DD was 82% in unmarried people. while the lowest prevalence of DD among outpatients was as low as 42%. The results of meta-regression showed that there was no correlation between the prevalence of DD and the year of publication, the average age of the patients, or the duration of the disease. CONCLUSION: More than half of T2DM patients in China may suffer from DD, which is not conducive to the self-management of diabetes patients. The burden on the healthcare system and the burden of disease on individual patients may increase as a result. Medical staff should pay attention to the monitoring and management of the mental health status of patients with T2DM.

The prevalence of alexithymia in psoriasis: A systematic review and meta-analysis.

OBJECTIVES: Alexithymia is characterized by an inability to identify and describe feelings, which may increase the psychological burden of patients with psoriasis. The prevalence of alexithymia in psoriasis has been investigated with variable results. This study aimed to estimate the overall alexithymia prevalence in psoriasis. METHODS: The PubMed, PsycInfo, Web of Science, The Cochrane Library, EMBASE, China Knowledge Resource in Integrated Database (CNKI), WanFang Database, Weipu Database (VIP), and Chinese Biomedical Database (CBM) electronic databases were searched from inception to March 28, 2022, for cross-sectional studies, that reported prevalence of alexithymia. The included studies were evaluated for quality, data synthesis, subgroup analysis, sensitivity analysis, and publication bias. RESULTS: This systematic review and meta-analysis included 16 articles involving 3752 patients with psoriasis from eight countries. The pooled prevalence of alexithymia was 28% (95% CI: 25-32%), with heterogeneity between studies (I2 = 80.03%, p < .001). There was a higher prevalence of alexithymia in women with psoriasis, patients with a Psoriasis Area Severity Index (PASI) score >10, patients with psoriatic arthritis, and patients with psoriasis with visible skin lesions had a higher prevalence of alexithymia. CONCLUSION: More than a quarter of people with psoriasis have alexithymia., But due to the small sample size of the included studies, the results of the subgroup analysis should be interpreted with caution. More research is needed to elucidate the mechanism of alexithymia development in psoriasis. These findings may provide a theoretical basis for the screening and intervention of alexithymia in patients with psoriasis.

Hyperspectral Image Classification via Discriminant Gabor Ensemble Filter.

For a broad range of applications, hyperspectral image (HSI) classification is a hot topic in remote sensing, and convolutional neural network (CNN)-based methods are drawing increasing attention. However, to train millions of parameters in CNN requires a large number of labeled training samples, which are difficult to collect. A conventional Gabor filter can effectively extract spatial information with different scales and orientations without training, but it may be missing some important discriminative information. In this article, we propose the Gabor ensemble filter (GEF), a new convolutional filter to extract deep features for HSI with fewer trainable parameters. GEF filters each input channel by some fixed Gabor filters and learnable filters simultaneously, then reduces the dimensions by some learnable 1×1 filters to generate the output channels. The fixed Gabor filters can extract common features with different scales and orientations, while the learnable filters can learn some complementary features that Gabor filters cannot extract. Based on GEF, we design a network architecture for HSI classification, which extracts deep features and can learn from limited training samples. In order to simultaneously learn more discriminative features and an end-to-end system, we propose to introduce the local discriminant structure for cross-entropy loss by combining the triplet hard loss. Results of experiments on three HSI datasets show that the proposed method has significantly higher classification accuracy than other state-of-the-art methods. Moreover, the proposed method is speedy for both training and testing.

Joint Transformation Learning via the L2,1-Norm Metric for Robust Graph Matching.

Establishing correspondence between two given geometrical graph structures is an important problem in computer vision and pattern recognition. In this paper, we propose a robust graph matching (RGM) model to improve the effectiveness and robustness on the matching graphs with deformations, rotations, outliers, and noise. First, we embed the joint geometric transformation into the graph matching model, which performs unary matching over graph nodes and local structure matching over graph edges simultaneously. Then, the L2,1 -norm is used as the similarity metric in the presented RGM to enhance the robustness. Finally, we derive an objective function which can be solved by an effective optimization algorithm, and theoretically prove the convergence of the proposed algorithm. Extensive experiments on various graph matching tasks, such as outliers, rotations, and deformations show that the proposed RGM model achieves competitive performance compared to the existing methods.

Comparison of tooth movement and biological response resulting from different force magnitudes combined with osteoperforation in rabbits.

OBJECTIVE: To compare tooth movement rate and histological responses with three different force magnitude designs under osteoperforation in rabbit models. METHODOLOGY: 48 rabbits were divided into three groups: Group A, Group B, and Group C, with traction force of 50 g, 100 g, 150 g, respectively. Osteoperforation was performed at the mesial of the right mandibular first premolar, the left side was not affected. One mini-screw was inserted into bones between two central incisors. Coil springs were fixed to the first premolars and the mini-screw. Tooth movement distance was calculated, and immunohistochemical staining of PCNA, OCN, VEGF, and TGF-ß1 was analyzed. RESULTS: The tooth movement distance on the surgical side was larger than the control side in all groups (P<0.01). No significant intergroup difference was observed for the surgical side in tooth movement distance among the three groups (P>0.05). For the control side, tooth movement distance in Group A was significantly smaller than Groups B and C (P<0.001); no significant difference in tooth movement distance between Group B and Group C was observed (P>0.05). On the tension area of the moving premolar, labeling of PCNA, OCN, VEGF and TGF-ß1 were confirmed in alveolar bone and periodontal ligament in all groups. PCNA, OCN, VEGF and TGF-ß1 on the surgical side was larger than the control side in all groups (P<0.001). CONCLUSION: Osteoperforation could accelerate orthodontic tooth movement rate in rabbits. Fast osteoperforation-assisted tooth movement in rabbits was achieve with light 50 g traction.

Kernel Embedding Multiorientation Local Pattern for Image Representation.

Local feature descriptor plays a key role in different image classification applications. Some of these methods such as local binary pattern and image gradient orientations have been proven effective to some extent. However, such traditional descriptors which only utilize single-type features, are deficient to capture the edges and orientations information and intrinsic structure information of images. In this paper, we propose a kernel embedding multiorientation local pattern (MOLP) to address this problem. For a given image, it is first transformed by gradient operators in local regions, which generate multiorientation gradient images containing edges and orientations information of different directions. Then the histogram feature which takes into account the sign component and magnitude component, is extracted to form the refined feature from each orientation gradient image. The refined feature captures more information of the intrinsic structure, and is effective for image representation and classification. Finally, the multiorientation refined features are automatically fused in the kernel embedding discriminant subspace learning model. The extensive experiments on various image classification tasks, such as face recognition, texture classification, object categorization, and palmprint recognition show that MOLP could achieve competitive performance with those state-of-the art methods.

Comparison of tooth movement and biological response resulting from different force magnitudes combined with osteoperforation in rabbits

Abstract Objective To compare tooth movement rate and histological responses with three different force magnitude designs under osteoperforation in rabbit models. Methodology 48 rabbits were divided into three groups: Group A, Group B, and Group C, with traction force of 50 g, 100 g, 150 g, respectively. Osteoperforation was performed at the mesial of the right mandibular first premolar, the left side was not affected. One mini-screw was inserted into bones between two central incisors. Coil springs were fixed to the first premolars and the mini-screw. Tooth movement distance was calculated, and immunohistochemical staining of PCNA, OCN, VEGF, and TGF-β1 was analyzed. Results The tooth movement distance on the surgical side was larger than the control side in all groups (P<0.01). No significant intergroup difference was observed for the surgical side in tooth movement distance among the three groups (P>0.05). For the control side, tooth movement distance in Group A was significantly smaller than Groups B and C (P<0.001); no significant difference in tooth movement distance between Group B and Group C was observed (P>0.05). On the tension area of the moving premolar, labeling of PCNA, OCN, VEGF and TGF-β1 were confirmed in alveolar bone and periodontal ligament in all groups. PCNA, OCN, VEGF and TGF-β1 on the surgical side was larger than the control side in all groups (P<0.001). Conclusion Osteoperforation could accelerate orthodontic tooth movement rate in rabbits. Fast osteoperforation-assisted tooth movement in rabbits was achieve with light 50 g traction.