Assessment of the reliability and quality of breast cancer related videos on TikTok and Bilibili: cross-sectional study in China

BackgroundAs the most common malignant tumor in the world, breast cancer also brings a huge disease burden to China. Ordinary people are increasingly inclined to use the Internet, especially video social platforms, as a source of health information. Educating the public to obtain correct information is important to reduce the incidence of breast cancer and improve the prognosis. However, the quality and reliability of breast cancer-related video content have not been fully studied.ObjectiveThis study aims to evaluate the quality of the information of breast cancer-related videos on TikTok and Bilibili video sharing platforms and factors related to video quality.MethodsWe collected the top 100 videos about breast cancer on TikTok and Bilibili, respectively. Categorize videos according to video source and video content. Video quality and reliability were assessed using Global Quality Score (GQS) and modified DISCERN (mDISCERN) tools. We also analyzed the correlation between video quality and video likes, comments, saves, and shares.ResultsAlthough the quality and reliability of Bilibili’s breast cancer videos were higher than TikTok (p = 0.002 and p = 0.001, respectively), the video quality of both video sharing platforms was not satisfactory, with a median GQS scores of 2.00 and 3.00 and mDISCERN scores of 1.00 and 2.00, respectively. In general, the quality and reliability of videos released by medical practitioners were higher than those of non-medical practitioners, and the quality and reliability of videos covering disease-related knowledge were higher than those of news reports (all p < 0.001). Among medical practitioners, the quality of videos uploaded by doctors in breast disease was significantly lower than that of doctors in other areas (p < 0.05). There was a significant positive correlation between video quality and duration (r = 0.240, p < 0.001), a weak negative correlation between video quality and likes (r = 0.191, p < 0.01), video quality and comments (r = 0.256, p < 0.001), video reliability and likes (r = 0.198, p < 0.001), video reliability and comments (r = 0.243, p < 0.01).ConclusionOur study shows that the quality and reliability of breast cancer-related videos on TikTok and Bilibili are poor, and the overall quality is unsatisfactory. But videos uploaded by medical practitioners covering disease knowledge, prevention and treatment are of higher quality. Medical practitioners are encouraged to publish more high-quality videos, while video social platforms should formulate relevant policies to censor and supervise health education videos, so as to enable the public to obtain reliable health information

Research on the relationship between challenging-hindrance stress and employee health based on cross-sectional data by structural equation modeling

Innovations in economic development have highlighted the role of talent, and focusing on employees’ work stress and its impact on employees’ health contributes to the continued development of employees and companies. This article aims to propose the work stress-employee health model and hypotheses under the moderation of perceived organizational support (POS) and self-efficacy. We select appropriate scales; collected 428 responses from questionnaire survey and explored the different effects of challenging/hindrance stress (CS/HS) on the employee’s physical/mental health, and the mechanism of POS and self-efficacy. The results indicated that: (1) CS has a significant positive impact on employees’ mental health; (2) HS has a significant negative impact on employees’ physical and mental health; (3) POS and selfefficacy have moderating effect on the relationship between CS and employees’ mental health, HS and employees’ physical and mental health

Research on the relationship between social network sites use and employee well-being based on cross-sectional data by structural equation modeling

With the rapid rise of social network sites, people’s life and work are influenced to varying degrees. And this paper aims to explore how does social network sites use(SNSU) affect employee well-being(EWB) and the mediating effects of body image disturbance(BID) and self-esteem(SE). Social network sites use, employee well-being, body image disturbance and self-esteem scales were used to obtain data of 435 employees. Results showed that social network sites use positively predicted employee well-being; Self-esteem played a mediating role in the relationship between social network sites use and employee well-being, but the mediation of body image disturbance and the chain mediation of body image disturbance and self-esteem weren’t significant. So social network sites use can lead to body image disturbance to some extent but overall, its impact was positive, which was contributing to employee well-being

Helmet-Wearing Tracking Detection Based on StrongSORT

Object detection based on deep learning is one of the most important and fundamental tasks of computer vision. High-performance detection algorithms have been widely used in many practical fields. For the management of workers wearing helmets in construction scenarios, this paper proposes a framework model based on the YOLOv5 detection algorithm, combined with multi-object tracking algorithms, to monitor and track whether workers wear safety helmets in real-time video. The improved StrongSORT tracking algorithm of DeepSORT is selected to reduce the loss of the tracked object caused by the occlusion, trajectory blur, and motion scale of the object. The safety helmet dataset is trained with YOLOv5s, and the best result of training is used as the weight model in the StrongSORT tracking algorithm. The experimental results show that the [email protected] of all classes in the YOLOv5s model can reach 95.1% in the validation dataset, [email protected]:0.95 is 62.1%, and the precision of wearing helmet is 95.7%. After the box regression loss function was changed from CIOU to Focal-EIOU, the [email protected] increased to 95.4%, [email protected]:0.95 increased to 62.9%, and the precision of wearing helmet increased to 96.5%, which were increased by 0.3%, 0.8% and 0.8%, respectively. StrongSORT can update object trajectories in video frames at a speed of 0.05 s per frame. Based on the improved YOLOv5s combined with the StrongSORT tracking algorithm, the helmet-wearing tracking detection can achieve better performance

Organic Boundary Location Based on Color-Texture of Visual Perception in Wireless Capsule Endoscopy Video

This paper addresses the problem of automatically locating the boundary between the stomach and the small intestine (the pylorus) in wireless capsule endoscopy (WCE) video. For efficient image segmentation, the color-saliency region detection (CSD) method is developed for obtaining the potentially valid region of the frame (VROF). To improve the accuracy of locating the pylorus, we design the Monitor-Judge model. On the one hand, the color-texture fusion feature of visual perception (CTVP) is constructed by grey level cooccurrence matrix (GLCM) feature from the maximum moments of the phase congruency covariance and hue-saturation histogram feature in HSI color space. On the other hand, support vector machine (SVM) classifier with the CTVP feature is utilized to locate the pylorus. The experimental results on 30 real WCE videos demonstrate that the proposed location method outperforms the related valuable techniques

Aligned Chemically Etched Silver Nanowire Monolayer as Surface-Enhanced Raman Scattering Substrates

Abstract Silver nanowires (AgNWs) were chemically etched to significantly increase the surface roughness and then self-assembled on the liquid/gas interfaces via the interfacial assembly method to obtain aligned chemically etched silver nanowire films. The as-fabricated silver nanowire films were used as novel surface-enhanced Raman scattering (SERS) substrates. The morphologies and plasmon characteristics of the substrates were investigated using multiple measurement methods. The performance of as-fabricated substrates was measured using rhodamine B as a probe. The detection limitation can be as low as 10−11 M. The greatly improved plasmonic properties are attributed to the efficient light coupling and larger electromagnetic field enhancement. The novel set of SERS substrates of aligned chemically etched AgNWs is believed to be important for efficient, homogeneous, and ultrasensitive SERS sensing applications

Effects of Different Kinds of Defoamer on Properties of Geopolymer Mortar

As a new type of green inorganic material, geopolymers have excellent mechanical properties, durability, and less environmental pollution. It is considered a new building material that can replace cement, but it also has some disadvantages such as high viscosity, poor fluidity, and more apparent pores after hardening. In this study, the uniaxial compressive strength test of geopolymer mortar was carried out, and the effects of alkali equivalent, alkali activator modulus, bone glue ratio, and silica fume content on the mechanical properties of geopolymer mortar were analyzed. The test results show that when the alkali equivalent is 13%, the alkali activator modulus is 1.4, the bone glue ratio is 2.0, the silicon powder content is 8%, and the metakaolin-based geopolymer mortar has higher uniaxial compressive strength. Through the comparative test of adding different kinds of defoamers and dosage, the effect of defoamers on the compressive strength, fluidity, density, and water-absorption of geopolymer mortar was further studied. The fluidity, density, and water-absorption were improved, and the uniaxial compressive strength was reduced. The formation of cementitious material in the mortar was confirmed by scanning electron microscope (SEM) observation. It was found that the pore structure and pore distribution changed with the content of different defoaming agents, and the microstructure of mortar after defoaming agent material treatment was shown. The proportion and distribution of Na, Al, and Si atoms were analyzed by energy dispersive spectroscopy (EDS). This experimental study shows that the defoamer can be an effective additive for geopolymer mortar