RESUMEN
A simple and stable cataluminescence (CTL) sensing platform based on a single sensing material for effective and rapid detection of aldehydes is an urgent need due to growing concerns for the environment, security, and health. Here, an effective and user-friendly identification method is successfully proposed to determine six common aldehydes of homologous compounds via a heterothermic CTL sensor system. Using Gd2O3 with excellent catalytic activity as a sensing material, thermodynamic and kinetic insights into the interactions between Gd2O3 and aldehydes at different temperatures were extracted and integrated to generate a unique constellation profile for each tested aldehyde, whereby achieving their effective and prompt determination. Moreover, the sensor system allowed the quantitative analysis of aldehydes with detection limits of 0.001, 0.009, 0.011, 0.011, 0.007, and 0.003 µg mL-1. Significantly, the sensor system had an excellent stability of up to 30 days. The CTL sensing platform was constructed based on a thermal regulation strategy that can provide a new approach to chemical agent identification.
RESUMEN
Hybrid nanogenerators (HNGs) represent a promising avenue for water energy harvesting, yet their commercial viability faces hurdles such as limited power output, poor coupling, and constrained operational lifespans. Here, a highly coupled triboelectric-electromagnetic magnetic-levitation hybrid nanogenerator (ML-HNG) is introduced that shows great potential for water energy harvesting. The ML-HNG fulfills the challenges of high power output, strong coupling, and long operational lifespans. During the contact-separation process of the triboelectric nanogenerator (TENG), the changing magnetic flux in the electromagnetic generator's coils generates a potential difference between the coils and Cu electrodes. The unique design of the ML-HNG employs a shared coil electrode configuration, which enhances the coupling without adding extra volume. This integration allows the ML-HNG to achieve multi-frequency vibrations and multiple output cycles per external longitudinal movement, a phenomenon known as the frequency multiplication effect. With an average power density of 1.69 W m-3 in water, the ML-HNG provides continuous power for a thermo-hygrometer and can quickly drive a wireless water level alarm system within a minute. This groundbreaking hybrid nanogenerator design holds significant promise for the efficient and consistent harvesting of low-frequency ocean wave energy, marking a substantial advancement in blue energy technology.
RESUMEN
To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.
RESUMEN
The state-of-the-art triboelectric nanogenerator (TENG) technology has numerous advantages and creates new prospects for the rapid development of the Internet of Things (IoT) in marine environments. Here, to accelerate the application process of TENG, an elaborately designed multilayered sleeve-structured hybrid nanogenerator (M-HNG) is developed to efficiently and persistently harvest marine energy. The M-HNG integrates an electromagnetic nanogenerator (EMG) with four coils and a multilayered sleeve-structured TENG (MS-TENG) with three freestanding layer units to increase spatial utilization efficiency. Moreover, rabbit fur strips are introduced to enhance the output performance and strengthen the durability of TENG. Therefore, the MS-TENG has high durability due to its soft-contact structure, maintaining its performance even after 240,000 cycles. When a 1000 µF capacitor is charged by M-HNG utilizing a power management circuit (PMC), the stored energy is increased from 2.62 mJ to 140.11 mJ, representing a significant improvement of 52-fold. The M-HNG triggered by water waves has successfully powered various small electronic devices, including 1200 LED lights, nine thermo-hygrometers, a water quality testing pen, and water level alarms. The proposed M-HNG effectively harvests low-frequency water wave energy, introducing an innovative concept for constructing a hybrid TENG with enhanced density and durability.
RESUMEN
BACKGROUND: Physical education is pivotal in our country's education reform. Urban schools have notably enhanced the intensity of physical education in recent years. However, the effects of physical education on students' anxiety, depression, and self-esteem levels, as well as their interrelations, remain unexplored. AIM: To analyze the influence of physical education on students' anxiety, depression, and self-esteem. METHODS: This study employed a cross-sectional design. A stratified cluster sampling method was used to select 478 first-year university students. Self-administered questionnaires were used to investigate the physical education status and basic information of college students. We used the Physical Activity Rank Scale-3 (PARS-3), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), and Self-Esteem Scale (SES) to assess the level of exercise, anxiety, depression, and self-esteem. Multiple Logistic regression was used to analyze the factors influencing anxiety, depression, and low self-esteem. The receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the predictive ability of PARS-3 scores for anxiety, depression, and low self-esteem. Spearman's correlation was used to analyze the correlations among the PARS-3, SAS, SDS, and SES. RESULTS: Compared with the domestic norms, SAS and SDS scores were higher, and SES scores were lower (P < 0.05). Among the participants, 210 (43.93%) had PARS-3 scores below 20, 94 (19.67%) had scores of 20-42, and 174 (36.40%) had scores above 42. After adjusting for daily sleep time, gender, being an only child, major, father's educational background, mother's educational background, and family residence, PARS-3 scores were independent influencing factors for anxiety, depression, and low self-esteem (P < 0.05). The AUC of PARS-3 scores predicting anxiety, depression, and low self-esteem were 0.805 (0.760-0.849), 0.799 (0.755-0.843), and 0.831 (0.788-0.874), respectively. The sensitivities were 0.799, 0.801, and 0.748, and the specificities were 0.743, 0.716, and 0.814, respectively. PARS-3 was negatively correlated with SAS and SDS scores (r = -0.566, -0.621, both P < 0.001) and positively correlated with SES scores (r = -0.621, P < 0.001). SES scores were negatively correlated with SAS and SDS scores (r = -0.508, r = -0.518, both P < 0.001). CONCLUSION: The amount of physical activity is negatively correlated with anxiety and depression degree and positively correlated with self-esteem degree.