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The wide application of communication, automation, computer and other technologies not only provides a new direction for the development of home furnishing, but also makes the concept of “smart home” popular in recent years. The purpose of this study is to design a complex control system for smart healthcare home based on PLC technology. First, the research significance and background of this study are discussed, and the complex system, traditional PID control, and BP neural network algorithm are summarized. Second, the ZigBee wireless sensor network and PLC control system are studied, and the design of a smart health home control complex system based on PLC technology is analyzed. The experimental results show that when the indoor natural gas concentration is more than 1.25%, Y4 and Y3 are powered on, and Y2 is set as 1, that is, the alarm light is on, and the windows and exhaust fans are on. When the indoor flue gas (CO and CO2) concentration exceeds 0.06%, Y4 and Y3 are powered on, Y2 is set as 1, the alarm light is on, and the window exhaust fan is on. When the infrared detection output is 1, Y4 is powered on, Y2 is reset, the window is closed, and the alarm light is on. The human-machine interface of the Android mobile terminal of this system can be directly operated by the user and real-time monitoring data, reflecting the convenience of the design. Therefore, the design of complex home control system is of great significance in the home industry.

Balanced charge injection is key to achieving perovskite light-emitting diodes (PeLEDs) with a low efficiency roll-off at a high brightness. The use of zinc oxide (ZnO) with a high electron mobility as the charge transport layers is desirable; however, photoluminescence (PL) quenching of a perovskite on ZnO always occurs. Here, a quasi-two-dimensional perovskite on ZnO is explored to uncover the PL quenching mechanism, mainly ascribed to the deprotonation of ammonium cations on the ZnO film in association with the decomposition of low-dimensional perovskite phases. Surprisingly, crystal plane-dependent PL quenching results indicate that the deprotonation rate strongly correlates with the crystal orientation of the ZnO surface. We developed a strategy for suppressing perovskite PL quenching by incorporating an atomic layer deposited Al

Colored solar panels, realized by depositing various reflection layers or structures, are emerging as power sources for building with visual aesthetics. However, these panels suffer from reduced photocurrent generation due to the less efficient light harvesting from visible light reflection and degraded power conversion efficiency (PCE). Here, color-patterned silicon heterojunction solar cells are achieved by incorporating luminescent quantum dots (QDs) with high quantum yields as light converters to realize an asthenic appearance with high PCE. It is found that large bandgap (blue) QD layers can convert UV light into visible light, which can notably alleviate the parasitic absorption by the front indium tin oxide and doped amorphous silicon. Additionally, a universal optical path model is proposed to understand the light transmission process, which is suitable for luminescent down-shift devices. In this study, solar cells with a PCE exceeding 23.5% are achieved using the combination of a blue QD layer and a top low refractive index anti-reflection layer. Based on our best knoledge,the obtained PCE is the highest for a color-patterned solar cell. The results suggest an enhanced strategy involving incorporation of luminescent QDs with an optical path design for high-performance photovoltaic panels with visual aesthetics.

Electricity generation triggered by the ubiquitous water evaporation process provides an intriguing way to harvest energy from water. Meanwhile, natural water evaporation is also a fundamental way to obtain fresh water for human beings. Here, a wafer-scale nanostructured silicon-based device that takes advantage of its well-aligned configuration that simultaneously realizes solar steam generation (SSG) for freshwater collection and hydrovoltaic effect generation for electricity output is developed. An ingenious porous, black carbon nanotube fabric (CNF) electrode endows the device with sustainable water self-pumping capability, excellent durable conductivity, and intense solar spectrum harvesting. A combined device based on the CNF electrode integrated with nanostructured silicon nanowire arrays (SiNWs) provided an aligned numerous surface-to-volume water evaporation interface that enables a recorded continuous short-circuit current 8.65 mA and a water evaporation rate of 1.31 kg m

Chronic diseases are gradually becoming the main threat to human health. By designing an efficient hospital management platform to quickly identify the corresponding chronic diseases, it can effectively reduce the labor cost, improve the accuracy of disease identification, and improve treatment efficiency. ADHD is a common behavioral disorder in school-age children, and it is also one of the most common chronic health problems in this period. The internationally recognized prevalence of ADHD is 3%–9%. ADHD often brings adverse effects on children’s life and studying and at the same time increases difficulties for their families. Therefore, this paper designs an intelligent management platform for public hospitals based on a deep learning algorithm, evaluates the current situation and influencing factors of ADHD children through the child adaptive behavior scale and the family function assessment scale, and designs its intelligent platform by using a new technology of fNIRS. According to the nonlinearity and unsteadiness of the fNIRS signal, this paper proposes a motion noise removal method based on EMD algorithm methods: to automatically identify children with ADHD and improve the cognitive function of children with ADHD by intervention technology. The data are from the outpatients of the Department of Child Psychology of the First People’s Hospital of Tianshui City in Gansu Province in 2018. The results showed that there were significant differences in the adaptive behavior scale (CABS) and fad scores between the two groups. In the seven dimensions of family function, there were significant differences between the two groups ( P < 0.01 ). fNIRS management platform can effectively identify ADHD patients with high recognition accuracy. The intelligent management platform can significantly reduce the number of physical examination personnel, prolong the diagnosis and treatment time, reduce a lot of repetitive work, and improve the efficiency of diagnosis and treatment. At the same time, this technology also provides great help for better research and improvement of ADHD patients and provides a reference for the information intelligent construction of modern hospitals.

High-precision orbits are essential for low Earth orbit (LEO) satellite applications. Instead of determinating orbit by the ground monitoring stations, LEO missions are trending to incorporate spaceborne global positioning system receivers for autonomous navigation. Focusing on this issue, we propose a method of real-time orbit determination based on ionosphere combination observation of dual-frequency data using adaptive extended Kalman filter (AEKF). The traditional Kalman filter heavily relies on the initial values of measurement and process noise covariance matrix. However, the environment of the satellite is time-variant, and it is hard to keep the error covariance matrix in the optimal condition all the time. To overcome this disadvantage, the Sage–Husa Kalman filter is introduced. The performance of the proposed algorithm is compared with the conventional EKF, and the results show that the proposed method can guarantee the precision and stability of orbit determination. With the proposed algorithms, we developed a software to solve the orbit suitable for one-day Gravity Recovery and Climate Experiment (GRACE) observations. The obtained results show that the accuracy of orbit determination error is improved with unknown Kalman process noise compared with traditional method. Additionally, the performances of AEKF for different gravity field models are analyzed and compared.

ADHD is a common disease in children, and the pathogenesis is still unclear. Attention deficit is the main manifestation of ADHD, which has a serious impact on children’s learning and growth. The treatment of ADHD is mainly western medicine, supplemented by psychotherapy. More and more studies have shown that ADHD has similar characteristics to psychological diseases, and dopamine beta hydroxylase gene abnormality is the common feature of most mental diseases. In view of the potential relationship between ADHD and dopamine β hydroxylase gene, this paper will study the polymorphism of dopamine β hydroxylase gene in children with ADHD under the nursing intervention mode. This paper is divided into three parts. The first part is theoretical research. In this part, we deeply analyze ADHD. We think that the pathogenesis of ADHD mainly comes from four factors: heredity, environment, nutrition, and behavior. In order to further test the relationship between ADHD and dopamine beta hydroxylase gene, the corresponding experimental model was established in the second part of this paper. All the samples in the experiment are from real cases. The experimental principle and specific operation steps are given in detail. In order to facilitate comparison, the same number of control groups was established in addition to the real disease. The third part is the experimental results and analysis. After a number of comparative experiments, through the analysis of experimental data, we believe that ADHD is closely related to the gene of dopamine beta hydroxylase. Among them, the A2 gene in the patient group was significantly more than that in the normal group, which further verified that ADHD has the characteristics of common psychological diseases.

Low-Density Parity-Check (LDPC) Code has become one of the best coding technologies at present because of its low complexity iterative decoding algorithm and its performance with further close to the Shannon limit. Non-binary LDPC codes designed in high order Galois fields have shown better potential than binary LDPC codes with the same code length and code rate, therefore it was applied for the navigation message encoding in BeiDou satellite navigation system (BDS). The navigation message contains time information, ephemeris parameters, clock correction terms and so forth, which is necessary for navigation solution. As the synchronization head was not encoded, it is hard to deal with data synchronization and navigation data decoding when the navigation receiver works at a low Signal-to-Noise Ratio (SNR). Aiming at this problem, we present a synchronization scheme for BDS B2a signal by utilizing the information from the process of decoding. The synchronizer is based on syndrome checks using the decoding result of the Extended Min-Sum (EMS) algorithm. Ratios of satisfaction of all check restrictions are computed firstly, and then the boundary value is obtained through MonteCarlo method. Simulation results show that the proposed algorithm performs well at relatively low SNR compared with traditional method.

Bi 2 S 3 nanoparticles (NPs) in the form of thin films were deposited on fluorine doped SnO 2 (FTO) coated conducting glass substrates by successive ionic layer adsorption and reaction (SILAR) at room temperature without annealing. The absorption coefficient could reach to the order of 10 6 cm −1 in the visible and NIR region, and the highest one was 5 × 10 6 cm −1 . The highest photocurrent density of the synthesized Bi 2 S 3 thin films (TFs) could maintain 0.8 mA/cm 2 within 700 s under the light intensity kept at 30 mW/cm 2 . The photocurrent density is among the highest reported for any Bi 2 S 3 photoelectrode without annealing to date. The photocurrent display little decrease during 4000 s of testing under illumination. The n-type Bi 2 S 3 thin films display a reasonable photoactivity and photostablity under illumination and are thus promising candidates for photoelectrochemical applications.