When adults without university education search the Internet for health information: The roles of Internet-specific epistemic beliefs and a source evaluation intervention

In the present research, N = 48 adults without university education were tasked to conduct two web searches on unfamiliar health-related issues. Three research objectives were examined: the predictive value of individuals’ Internet-specific epistemic beliefs for their navigation behavior and post-search decisions in Web Search Task 1; the effects of a short source evaluation intervention on individuals’ navigation behavior and post-search decisions in Web Search Task 2; and the effects of the source evaluation intervention on individuals’ Internet-specific epistemic beliefs. Results showed that beliefs concerning the justification by multiple sources were positively related to the time spent on reliable objective web pages and to the likelihood to make a post-search decision that was in accordance with the objective pages. Beliefs that the Internet is a reliable knowledge resource were also positively related to the time spent on objective pages as well as to greater certainty in the post-search decision. Second, in Web Search Task 2, the intervention group spent more time on objective web pages, was more likely to make a decision that was in accordance with these pages, and was more certain of their decision than the control group. Third, one week after the intervention, individuals possessed stronger beliefs concerning the justification by multiple sources than before. In conclusion, the present research indicates that both adaptive Internet-specific beliefs and a short source evaluation intervention have positive effects on non-university educated adults’ online health information seeking and that their Internet-specific epistemic beliefs can be fostered through such an intervention.     

Categorizing health-related cues to action: using Yelp reviews of restaurants in Hawaii

Yelp, a social media site, undeniably has an influence on consumers' food choice in spite of its ability to reflect consumers' real voice being criticized. Since unhealthy food choices contribute to health problems, such as obesity and malnourishment, we attempted to examine these problems by better understanding consumers through health-related cues to action—a construct from the Health Belief Model (HBM)— on Yelp Honolulu's restaurant reviews. Our research revealed 13 main categories: Ingredient, Type of food, Taste, Lifestyle, Cooking, Option, Price, Portion, Well-being, Nutrition, Hygiene, Emotional attachment and indulgence, and Feeling. We argue that these categories may ultimately lead consumers to make healthier food choices. In search of the most appealing way to communicate with the target group, underlying concepts that derived from these categories can be tested. Marketers in food industry (or public health policy-makers) can craft their strategies for healthy food brands/products (or healthy eating scheme) based on the concept test research. Moreover, Yelp can apply these insights in the development of their algorithm and filter system in order to help consumers find healthy food if they wish to do so. Restaurants can also improve their strategy, menu, and communication execution to meet the growing demands of health conscious consumers.     

基于有线无线异构网络融合的桥梁健康监测系统

对于大跨度桥梁的健康检测,较为先进并已广泛使用的有线健康监测技术逐渐取代了传统的手工操作,但在实际应用中产生了安装电缆和更新系统带来的麻烦。相比之下,新开发的无线桥梁结构健康监测传感器技术更容易部署和更新,它克服有线系统存在的这些缺陷。然而,在某些情况下,无线网络的通信质量不能保证,导致系统的效率和可靠性受到影响。提出一种新的异构健康监测系统,它拥有有线和无线健康监测技术的优点。     

公共卫生信息平台软件工程化开发探讨

本文讲述了在公共卫生信息平台项目的开发过程中采用软件工程化方法和技术进行平台的开发。分析了软件工程化开发现状及需求,探讨了软件工程化目标和软件工程化技术路线,并给出了软件工程化开发步骤。     

A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications

For the elderly and chronic patients with cardiovascular disease who live alone, it is necessary to constantly monitor their physiological parameters, especially the electrocardiogram (ECG), to effectively prevent and control their health condition and even to provide urgent treatment or care while an emergency such as the abnormal variation of heart rate (HR) occurs. In this paper, a wireless in-home physiological monitoring system, based on multi-hop relay communications, which can ubiquitously and continuously monitor the patient's ECG at any time or any place at home without space limit and the “dead spot” due to the extended communication coverage by multi-hop wireless connectivity, is proposed. The system consists of a mobile-care device, which is responsible for capturing and wirelessly sending the patient's ECG data, a wireless multi-hop relay network (WMHRN) that is in charge of relaying the data sent by the former, and a residential gateway (RG), which is responsible for gathering and uploading the received ECG data to the remote care server through the Internet to carry out the patient's health condition monitoring and the management of pathological data. However, in order to assure that the ECG data can be effectively and timely forwarded, from the mobile-care device to the RG through the WMHRN, to meet the healthcare quality of service (H-QoS) demand for reliable and real-time end-to-end ECG transmission, the analysis of WMHRN latency in data-forwarding stage and the deployment consideration of wireless relay nodes are investigated in detail in this work. Moreover, an emergency alert service using short message service (SMS), based on the detection of abnormal variation of HR, is also used in the RG to further enhance the healthcare service quality. A prototype of this system has been developed and implemented. Finally, the experimental results are presented to verify the feasibility of the proposed system.     

Effectiveness of participatory ergonomic interventions on health outcomes: a systematic review

The objective of this study was to conduct a systematic review of the literature on the effectiveness of participatory ergonomic (PE) interventions for improving workers' health. The search strategy targeted six electronic databases and identified 442 potential articles. Each article was examined by pairs of reviewers for relevance (assessed a participative ergonomic workplace intervention, with at least one health outcome, published in English in peer reviewed literature). Twenty-three articles met relevance criteria and were then appraised for methodological strength. Using a best evidence synthesis approach, 12 studies that were rated as 'medium' or higher provided partial to moderate evidence that PE interventions have a positive impact on: musculoskeletal symptoms, reducing injuries and workers' compensation claims, and a reduction in lost days from work or sickness absence. However, the magnitude of the effect requires more precise definition.     

基于嵌入式系统的智能超声波清洁器

以Philips的89LPC936单片机作为智能化软硬件平台,综合超声波清洗,臭氧消毒,负离子保健等手段进行面部美容的新方法.实际运用表明,该方法能深入一般方法难以涉及的皮肤深层.加快新陈代谢,用于面部美容,起到了很好的作用.     

Health-guided recipe recommendation over knowledge graphs

While the availability of large-scale online recipe collections presents opportunities for health consumers to access a wide variety of recipes, it can be challenging for them to discover relevant recipes. Whereas most recommender systems are designed to offer selections consistent with users’ past behavior, it remains an open problem to offer selections that can help users’ transition from one type of behavior to another, intentionally. In this paper, we introduce health-guided recipe recommendation as a way to incrementally shift users towards healthier recipe options while respecting the preferences reflected in their past choices. Introducing a knowledge graph (KG) into recommender systems as side information has attracted great interest, but its use in recipe recommendation has not been studied. To fill this gap, we consider the task of recipe recommendation over knowledge graphs. In particular, we jointly learn recipe representations via graph neural networks over two graphs extracted from a large-scale Food KG, which capture different semantic relationships, namely, user preferences and recipe healthiness, respectively. To integrate the nutritional aspects into recipe representations and the recommendation task, instead of simple fusion, we utilize a knowledge transfer scheme to enable the transfer of useful semantic information across the preferences and healthiness aspects. Experimental results on two large real-world recipe datasets showcase our model’s ability to recommend tasty as well as healthy recipes to users.     

A Multi-scale Attention-based Facial Emotion Recognition Method Based on Deep Learning

Recently, people have been paying more and more attention to mental health, such as depression, autism, and other common mental diseases. In order to achieve a mental disease diagnosis, intelligent methods have been actively studied. However, the existing models suffer the accuracy degradation caused by the clarity and oc-clusion of human faces in practical applications. This paper, thus, proposes a multi-scale feature fusion network that obtains feature information at three scales by locating the sentiment region in the image, and integrates global feature information and local feature information. In addition, a focal cross-entropy loss function is designed to improve the network''s focus on difficult samples during training, enhance the training effect, and increase the model recognition accuracy. Experimental results on the challenging RAF_DB dataset show that the proposed model exhibits better facial expression recognition accuracy than existing techniques.     

Health information technologies for patients with diabetes

Patients with chronic illnesses, such as diabetes, need daily care and follow-up beyond occasional visits to healthcare providers. Research has shown that overcoming a multifaceted illness, such as diabetes, requires patients to be engaged in the monitoring and management of their own health. Health information technology (HIT) has been shown to empower chronically-ill patients to take charge of their healthcare, and alleviate their daily frustrations while they strive to lead a normal life. In this paper, we surveyed 31 patients with diabetes to identify the major frustrations they experience daily, examine the role of HIT in their current treatment, and identify gaps in their current care and education that, if addressed, could improve their quality of life. Themes identified in our survey results include a lack of interaction with healthcare providers, difficulties in scheduling appointments, a lack of timely communication with healthcare providers, and challenges in managing the complex care of diabetes. The contributions of this paper include a detailed set of recommendations on how HIT can be utilized to help chronically-ill patients live a better life despite their illnesses, with a particular emphasis on diabetes care and management.