The Retrieval and Effect of Core Parameters for Near-Field Inter-Body Coupling Communication.

The potential of the Internet of Body (IoB) to support healthcare systems in the future lies in its ability to enable proactive wellness screening through the early detection and prevention of diseases. One promising technology for facilitating IoB applications is near-field inter-body coupling communication (NF-IBCC), which features lower power consumption and higher data security when compared to conventional radio frequency (RF) communication. However, designing efficient transceivers requires a profound understanding of the channel characteristics of NF-IBCC, which remain unclear due to significant differences in the magnitude and passband characteristics of existing research. In response to this problem, this paper clarifies the physical mechanisms of the differences in the magnitude and passband characteristics of NF-IBCC channel characteristics in existing research work through the core parameters that determine the gain of the NF-IBCC system. The core parameters of NF-IBCC are extracted through the combination of transfer functions, finite element simulations, and physical experiments. The core parameters include the inter-body coupling capacitance (CH), the load impedance (ZL), and the capacitance (Cair), coupled by two floating transceiver grounds. The results illustrate that CH, and particularly Cair, primarily determine the gain magnitude. Moreover, ZL mainly determines the passband characteristics of the NF-IBCC system gain. Based on these findings, we propose a simplified equivalent circuit model containing only core parameters, which can accurately capture the gain characteristics of the NF-IBCC system and help to concisely describe the channel characteristics of the system. This work lays a theoretical foundation for developing efficient and reliable NF-IBCC systems that can support IoB for early disease detection and prevention in healthcare applications. The potential benefits of IoB and NF-IBCC technology can, thus, be fully realized by developing optimized transceiver designs based on a comprehensive understanding of the channel characteristics.

A survey on nutritional status among infants at ages of 6 to 24 months / 预防医学

Objective@#To investigate the nutritional status and examine its association with feeding among infants at ages of 6 to 24 months in Xinjiang Uygur Autonomous Region, so as to provide the evidence for improving malnutrition among infants.@*Methods@#Infants at ages of 6 to 24 months participating in physical examinations in Urumqi City and Moyu County from January to December 2021 were enrolled. Participants' gender, age, birth status, place of residence and maternal education level were collected through questionnaire surveys, and infants' feeding was evaluated using Infant and Child Feeding Index (ICFI). Age-specific height and body weight and height-specific body weight were calculated, and nutritional status was evaluated using Z score. The association between ICFI and malnutrition was evaluated using a multivariable logistic regression model.@*Results @#A total of 1 013 infants were surveyed, including 557 boys (54.99%) and 456 girls (45.01%). The participants included 545 infants at ages of 12 to 24 months (53.80%), 969 full-term infants (95.66%), and 617 infants with qualified ICFI scores (60.91%). The prevalence of malnutrition was 8.59% among participants. Multivariable logistic regression analysis showed that infants with qualified ICFI score had a lower risk of malnutrition (OR=0.538, 95%CI: 0.327-0.883) after adjustment for age, birth status, place of residence, maternal education level and monthly household income.@*Conclusion@#The prevalence of malnutrition is low among infants at ages of 6 to 24 months in Xinjiang Uygur Autonomous Region, and infants with qualified feeding have a reduced risk of malnutrition.

Association between dietary patterns during pregnancy and gestational diabetes mellitus / 预防医学

Objective@#To explore the association between dietary patterns during pregnancy and the development of gestational diabetes mellitus (GDM), so as to provide the guidance of diet balance and GDM prevention for pregnant women.@*Methods@#Pregnant women who underwent prenatal examination at the First Affiliated Hospital of Xinjiang Medical University from December 2021 to July 2022 were selected as the subjects. The oral glucose tolerance test (OGTT) was employed at 24 to 28 weeks of gestation to diagnose GDM. The questionnaire of "The Survey on Nutrition and Health of Pregnant Women in China" was used to collect general information, food intake frequency and amount during a month before OGTT. Dietary patterns were determined by factor analysis, and the association between dietary patterns and the development of GDM was identified using a multivariable logistic regression model. @*Results@#Totally 449 pregnant women were included, with a median (interquartile range) age of 31.00 (5.00) years and a median (interquartile range) gestational age of 35.00 (3.00) weeks. There were 7 dietary patterns named potato-cereal pattern, poultry-meat-dessert pattern, milk-egg-aquatic product pattern, mushroom-vegetable-offal pattern, fruit-bean pattern, pickle-wheaten food pattern, and beverage-nut pattern according to the food types with high factor loads. There were 89 cases diagnosed as GDM, with a prevalence rate of 19.82%. Multivariable logistic regression analysis showed that the development of GDM was associated with the poultry-meat-dessert pattern (OR=0.242, 95%CI: 0.086-0.678) and the fruit-bean pattern (OR=0.093, 95%CI: 0.025-0.342), compared with the potato-cereal pattern. @*Conclusion@#Compared to the potato-cereal pattern, the poultry-meat-dessert pattern and the fruit-bean pattern may reduce the risk of GDM. Key words： gestational diabetes mellitus dietary pattern pregnant woman low carbohydrate diet

Exploring attentional bias for real-world, pain-related information in chronic musculoskeletal pain using a novel change detection paradigm.

OBJECTIVES: Attentional biases for pain-related words and images have commonly been reported in individuals with chronic pain. In former studies, however, pain-related stimuli have been presented without context, for example, facial expressions of pain with no accompanying information regarding the location, severity, or cause of pain or injury. The present study investigated attentional biases for pain-related information using complex, real-world scenes in an ecologically valid experimental paradigm. METHODS: Participants with chronic musculoskeletal pain (n=20) and healthy, pain-free controls (n=23) completed a version of the change detection paradigm, the flicker task, which requires participants to detect a single difference between 2 otherwise identical versions of the same scene. These change-scenes were presented in a continuous cycle for approximately 3 minutes, with an unrelated distractor-scene interspersed between. Both pain-related and neutral scenes were used in 4 experimental conditions: change-pain/distractor-pain, change-pain/distractor-neutral, change-neutral/distractor-pain, and change-neutral/distractor-neutral. RESULTS: Individuals with chronic musculoskeletal pain, relative to healthy control participants, took significantly longer to detect changes when the change-scene was pain-related. Within-group analysis showed healthy control participants to take significantly longer to detect changes in neutral change-scenes compared with pain-related change-scenes. DISCUSSION: This study is the first to show individuals with chronic pain possess attentional biases for pain-related information presented as part of complex, real-world scenes. Possible future research includes the use of real-world scenes in visual-search paradigms modifying attentional biases, and exploration into the relations and effects of combined cognitive biases (eg, attention, memory, and interpretation) in chronic pain.