BackgroundAdolescence is a critical period for bone development, and peak bone mass may be reached in late adolescence. Boosting bone accumulation at this time can help preserve adult bone health and avoid osteoporosis later in life. Body mass index (BMI) has been found to have a favorable impact on bone mineral density (BMD) in previous research. However, excessive obesity is harmful to health and may lead to various systemic diseases. Therefore, finding an appropriate BMI to maintain a balance between obesity and BMD is critical for adolescents.MethodsThe datasets from the National Health and Nutrition Examination Survey (NHANES) 2011–2020 were used in a cross-sectional investigation. Multivariate linear regression models were used to examine the linear connection between BMI and BMD. Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship. Subgroup analyses were then conducted based on gender and age.ResultsThis population-based study included a total of 6,143 adolescents aged 8–19 years. In a multivariate linear regression analysis, a good association between BMI and total BMD was shown [0.014 (0.013, 0.014)]. This positive association was maintained in all subgroup analyses grouped by sex and age. Furthermore, the association between BMI and BMD was nonlinear with a saturation point present, as evidenced by smoothed curve fitting. According to the threshold effect study, with an age group of two years, adolescents of different ages had different BMI saturation values with respect to BMD.ConclusionsOur study showed a significant positive and saturated association between BMI and BMD in adolescents aged 8–19 years. Maintaining BMI at saturation values may reduce other adverse effects while achieving optimal BMD.

Abstract-In the centralized heating, ventilating and air-conditioning (HVAC) system, air handling units (AHUs) are traditionally controlled by single-loop proportional-integral-derivative (PID) controllers. The control structure is simple, but the performance is usually not satisfactory. In this paper, we propose a cascade control strategy for temperature control of AHU. Instead of a fixed PID controller in the classical cascade control scheme, a neural network (NN) controller is used in the outer control loop. This approach not only overcomes the tedious tuning procedure for the inner and outer loop PID parameters of a classical cascade control system, but also makes the whole control system be adaptive and robust. The multilayer NN is trained online by a special training algorithm-simultaneous perturbation stochastic approximation (SPSA)-based training algorithm. With the SPSA-based training algorithm, the weight convergence of the NN and stability of the control system is guaranteed. The novel cascade control system has been implemented on an experimental HVAC system. Testing results demonstrate the effectiveness of the proposed algorithm over the classical cascade control system. Index Terms-Air handling units, cascade control, neural networks (NNs), simultaneous perturbation stochastic approximation (SPSA).

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The application of flap surgery is becoming more and more widespread with the development of microsurgical techniques. Currently, postoperative blood flow monitoring of flaps is still mainly assessed by medical staff for traditional clinical parameters, which has the disadvantage of being subjective and unable to monitor in real-time. This study describes a self-contained infrared wireless infrared thermometry device for flap blood supply monitoring and evaluates its effectiveness on eight porcine flap models. A scapular muscle flap model was established using eight small pigs, and the vessels were ligated at irregular intervals using a lumir ligature to simulate arterial crisis and venous crisis. Laser Doppler flowmetry (LDF), the wireless infrared thermometry device, and traditional clinical observation methods were applied to monitor the blood supply of the flap and evaluate the effect. The time to the determination of blood supply disturbance by wireless infrared thermography (IRT) was 28.75 ± 3.30 min and 96.5 ± 27.09 min for the arterial and venous groups, respectively; by LDF was 6.00 ± 1.41 min and 52.75 ± 15.76 min; by clinical observation was 42.00 ± 8.60 min and 156.50 ± 40.91 min, respectively. Paired t-tests were performed between the wireless IRT device and clinical observations, and the statistical results were significantly different in the arterial group and not significantly different in the venous group. Paired t-testing of the wireless infrared thermometry device with the LDF also showed significant differences in the arterial group and non-significant differences in the venous group. This wireless infrared thermometry device outperforms traditional clinical observation methods in monitoring blood supply in a porcine skin flap model. Because of its low cost, real-time monitoring, simple operation, and noninvasive features, it has the potential to be used in clinical practice as a routine means of postoperative blood supply monitoring in flap surgery.

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