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Background Understanding the burden of cervical cancer (CC) in young women aged 15–44 years old are essential for formulating effective preventive strategies. Methods Utilizing the Global Burden of Disease 2019 Study, we estimated incidence, disability-adjusted life-years (DALYs), years of life lost (YLLs) and years lived with disability (YLDs) due to CC among young women from 1990 to 2019. Additionally, we evaluated the temporal trends using estimated annual percentage changes (EAPCs) during this period. We conducted a decomposition analysis to assess the absolute contributions of three components: population growth, population age structure and epidemiologic changes. Results Globally, there were 187 609.22 incident cases of CC worldwide, resulting in 2621 917.39 DALYs in 2019. From1990 to 2019, the age-standardized rates were decline, only the age-standardized YLDs rate (EAPC = 0.02; 95% CI: −0.02 to 0.05) showed a stable trend. The largest increase in age-standardized incidence rate (ASIR) and age-standardized YLDs rate observed in the high-middle social demographic index (SDI) quintiles. Population growth and age structure changes were associated with substantial changes in cases of CC, especially in South Asia and East Asia. Conclusions Globally, the burden of CC in young women continues to increase, as measured by the absolute number. As populations are growing and age structure changes were associated with substantial changes in cases of CC, governments will face increasing demand for treatment, and support services for CC, especially in South Asia and East Asia. [ABSTRACT FROM AUTHOR]

Winter extreme cold events (ECEs) have profound impacts on human health, transportation, energy consumption and the economy, particularly associated with high‐humidity conditions. Recent research has indicated a growing interest in extreme temperature events that account for the presence of water vapour. However, the characteristics of humidity‐related ECEs (HECEs) remain unclear. Given the rise in atmospheric moisture due to global warming, understanding the influence of water vapour on HECEs becomes crucial. This study examined variations in HECEs identified using the wet‐bulb globe temperature (WBGT) in China during 1959–2020 and quantified the impacts of water vapour. The results revealed a decrease in the intensity and frequency of HECEs in China during this period, except for in northern China, where the intensity increased, which contrasts with the trends in traditional ECEs. Furthermore, strong HECEs were found to exhibit greater frequency, duration and intensity in northern China than weak HECEs. Additionally, the specific humidity for all categories of HECEs in China exhibited an upward trend, with a more rapid increase for strong HECEs. The findings indicated that the intensity of HECEs is positively correlated with the increase in water vapour. Defining a water vapour amplification factor revealed amplified intensity and duration at most grid points, particularly across northern China. Therefore, while winter warming reduces traditional ECEs, HECEs persist and even intensify as humidity increases, confirming significant amplification by water vapour. Our results emphasized the importance of increasing water vapour, driven by global warming, which may increase the risk of HECEs in the future. [ABSTRACT FROM AUTHOR]

Co-N-CDs-based MXene nanocomposites (MXene@PDA/Co-N-CDs) were constructed by decorating Co-N-CDs on polydopamine-functionalized MXene nanosheets. Both Co-N-CDs and MXene nanosheets have peroxidase-like activity; when the two materials are combined to form MXene@PDA/Co-N-CDs nanocomposites, the peroxide-like activity can be further enhanced. MXene@PDA/Co-N-CDs could oxidize the substrate 3,3′5,5′-tetramethylbenziline (TMB) to form ox-TMB, as confirmed by detecting the absorption of the blue products. A highly selective colorimetric biosensor was developed for the determination of glutathione (GSH) in the concentration range of 0.3 to 20 µM with a lower detection limit (LOD) of 0.12 µM, which realized the accurate detection of GSH in human serum and urine samples. Moreover, in the tumor microenvironment, MXene@PDA/Co-N-CDs could catalyze hydrogen peroxide to produce hydroxyl free radicals and produce a photothermal effect under the exposure of NIR-I irradiation. The catalytic activity of MXene@PDA/Co-N-CD nanocomposites was fully achieved for the death of cancer cells through photothermal/photodynamic synergistic therapy. The MXene@PDA/Co-N-CDs nanozyme offers multiple applications in GSH detection and tumor therapy. [ABSTRACT FROM AUTHOR]

Cuelure, an effective lure specifically targeting Tephritid fruit flies, has been widely adopted and applied in the monitoring and control of these pests, providing significant support for agricultural pest management. However, its uncontrollable release speed and duration usually lead to a lot of waste, diminishing its effectiveness and increasing the cost of pest control. In order to solve these problems, we focused on Zeugodacus cucurbitae Coquillett and developed a temperature-sensitive nano-controlled release agent for cuelure. The release rate of this agent can be adjusted by adjusting the ambient temperature. The results show that the temperature-sensitive cuelure nano-controlled release agent demonstrates remarkable temperature-responsive controlled release characteristics. It still exhibits exceptional stability even after being subjected to high-temperature treatment at 60 °C for a week, and the trapping efficiency of this attractant remains between 73% and 75%. This study not only holds immense practical value in monitoring, warning, and managing of fruit fly pests, but it also lays a novel theoretical foundation for the development of insect attractants. [ABSTRACT FROM AUTHOR]

Simple Summary: Exposure to short-term high temperatures of 45 °C can enhance the development and reproduction of Zeugodacus cucurbitae (Coquillett). In this study, the function of the ZcVg3 gene in reproduction was studied by interfering with its expression via the injection of siRNA. The silencing of the ZcVg3 gene could affect the expression of other related genes. It also resulted in a significant reduction in egg production, spawning days, ovarian development and lifespan. The results suggest that the ZcVg3 gene plays a crucial role in pest reproduction under short-term high temperatures. Zeugodacus cucurbitae (Coquillett) is a significant pest affecting fruit and vegetables in tropical and subtropical regions, and its development and reproduction are enhanced after exposure to short-term high-temperature stress at 45 °C. Vitellogenin (Vg) is an essential precursor of yolk protein formation in eggs and plays a vital role in the ovarian development of insects. Interfering with the Z. cucurbitae vitellogenin receptor (ZcVgR) gene in short-term high-temperature conditions decreases the fecundity of female adults, while the transcription level of the ZcVg3 gene increases. To elucidate the reproductive function of the ZcVg3 gene and the synergistic relationship among the ZcVgs genes under short-term high temperatures, this study injected siRNA to interfere with the ZcVg3 gene after subjecting Z. cucurbitae to a 1 h treatment at 45 °C and 25 °C. The expression of the ZcVg3 gene was suppressed, leading to the upregulation of the ZcVg1 and ZcVg2 genes, and the expression of the ZcVgR gene was initially decreased and then increased. Silencing the ZcVg3 gene after a 1 h treatment at 45 °C resulted in a reduction of approximately 84.7% and 75.9% in the fecundity and spawning days of female adults compared to the control. The development rate of their ovaries and the ovarian diameter significantly decreased, and their lifespan was reduced by 71%. The ZcVg3 gene plays a crucial role in the reproduction of Z. cucurbitae in short-term high-temperature conditions. The results of this study provide potential targets for the development of RNAi-based techniques for the control of Z. cucurbitae. [ABSTRACT FROM AUTHOR]

The iron and steel industry puts considerable pressure on the regional environment of the Beijing-Tianjin-Hebei (BTH) area, and the PM2.5 pollution has caused serious harm to public health. To explore a detailed and high-resolution emission inventory of the iron and steel industry in the BTH region, a classification technology method with CAMx modelling system was developed and applied for classifying all the iron and steel enterprises in the BTH region. Besides, simulation scenarios were designed particularly for quantitatively assessing the effectiveness of the environmental protection measures. Results show that the pollutant emission of the iron and steel industry significantly contributes to the PM2.5, SO42-, NO3-, and SOA concentrations in the atmospheric environment in sub-areas. Therefore, the enterprises in western and central sub-areas show high classification coefficients. Restricting pollutant emissions using the developed classification technology method is more effective in reducing the PM2.5 concentration of the BTH region compared with the proportional reduction method. Thus, the classification method should be primarily implemented for reducing the air pollutant emissions of the iron and steel industry in the BTH region.

As the growth of society and the continuous upgrading of people's living standards increase, people's requirements for indoor environment are also increasing. To optimize the ventilation methods inside buildings, a numerical simulation method was used to construct numerical simulations of airflow organization and aerosol diffusion, and based on this model, better ventilation methods were determined. To optimize the determined better ventilation method, a multi-constraint optimization model was constructed using infection probability, thermal comfort, energy utilization coefficient, and velocity non-uniformity coefficient. The ventilation method was optimized through multi-objective constraints. To solve the optimization model, an optimized particle swarm algorithm was studied and designed. The results showed that under the "air rain" flow field, the maximum values of aerosol particles at the human body, bed surface, and outlet were 171, 769, and 19,973, respectively, while the minimum values were 4, 169, and 2197, respectively. The "air rain" flow field is a better ventilation method. The maximum and minimum values of the original non-uniformity coefficient were 0.44 and 0.08, respectively. After optimization by the particle swarm optimization algorithm, the maximum and minimum predicted non-uniformity coefficients were 0.457 and 0.08, respectively. The original value and predicted value are very close. The numerical model and algorithm constructed by the research institute are effective. The algorithm designed by the research institute can provide technical support for multi-objective optimization of indoor ventilation methods. [ABSTRACT FROM AUTHOR]

Mechanical metamaterials are often designed with particular properties for specific load‐bearing functions. Alternatively, this study aims to create a class of active lattice metamaterials, dubbed self‐activated solids, that can learn desired stiffness tensors from the elastic deformations they experienced, a crucial feature to improve the performance, efficiency, and functionality of materials. Artificial adaptive matters that combine sensory, control, and actuation elements can offer appealing solutions. However, challenges still remain: The designs will rely on accurate off‐line and global computations, as well as intricate coordination among individual elements. Here, a simple online and local learning strategy is initiated based on contrastive Hebbian learning to gradually guide self‐activated solids to possess sought‐after stiffness tensors autonomously and reversibly. During learning, the bond stiffness of the active lattice varies depending only on its local strain. The numerical tests show that the self‐activated solid can not only achieve the desired bulk, shear, and coupling moduli but also manifest uni‐mode and bi‐mode extremal materials by itself after experiencing the corresponding elastic deformations. Further, the self‐activated solid can also achieve the desired time‐varying moduli when exposed to temporally different loads. The design is applicable to any lattice geometries and is resistant to damage and instabilities. The material design approach and the physical learning strategy suggested can benefit the design of autonomous materials, physical learning machines, and adaptive robots. [ABSTRACT FROM AUTHOR]

As the capital of China and a densely populated major city, the characteristics of Beijing's near-surface wind field change significantly with the increase in the density of underlying urban structures. The high randomness of natural wind makes it extremely difficult to develop a universally applicable wind-resistant load design code based on topographic factors and architectural features. This article takes the wind speeds recorded at 15 different height levels within the urban area by the 325 m meteorological tower in Beijing from 1991 to 2020 as the research subject. It quantifies the wind speed trends at different heights and introduces time-varying functions to establish a non-stationary wind speed model based on the optimal model. Additionally, it compares the basic wind speeds and wind pressure height variation coefficients obtained from measurements with the standards. The results show that, during the past 30 years of urbanization, the near-surface wind speed in the Beijing area has shown a decreasing trend. The model incorporating time-varying functions exhibited the best fit and demonstrated good predictive capabilities, with its calculated basic wind speeds being relatively high. The wind pressure height variation coefficient values in Beijing are between Class C and Class D terrains, being closer to Class C at lower altitudes. The conclusion reveals that urbanization has a significant impact on wind speeds, primarily concentrated at lower height levels, and that the basic wind speeds calculated based on standards underestimate the actual conditions when this impact is not considered. Although the average wind speed's wind profile index across the entire time series is mostly greater than the fixed value of 0.3 given by Class D, this represents an overestimated wind profile index for maximum wind speeds. [ABSTRACT FROM AUTHOR]