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Ferroelectric polymer-based electrocaloric effect may lead to sustainable heat pumps and refrigeration owing to the large electrocaloric-induced entropy changes, flexible, lightweight and zero-global warming potential. Herein, low-k nanodiamonds are served as extrinsic dielectric fillers to fabricate polymeric nanocomposites for electrocaloric refrigeration. As low-k nanofillers are naturally polar-inactive, hence they have been widely applied for consolidate electrical stability in dielectrics. Interestingly, we observe that the nanodiamonds markedly enhances the electrocaloric effect in relaxor ferroelectrics. Compared with their high-k counterparts that have been extensively studied in the field of electrocaloric nanocomposites, the nanodiamonds introduces the highest volumetric electrocaloric enhancement (~23%/vol%). The resulting polymeric nanocomposite exhibits concurrently improved electrocaloric effect (160%), thermal conductivity (175%) and electrical stability (125%), which allow a fluid-solid coupling-based electrocaloric refrigerator to exhibit an improved coefficient of performance from 0.8 to 5.3 (660%) while maintaining high cooling power (over 240 W) at a temperature span of 10 K. Low-k nanodiamonds are discovered to possess the ability to concurrently enhance the electrocaloric effect, thermal conductivity, and electrical stability of polymeric nanocomposites, providing support for electrocaloric refrigeration.

This study explored the latent profiles of self-regulated learning (SRL) strategies (cognitive, metacognitive, and motivational regulation) endorsed by Chinese English-as-a-foreign-language (EFL) readers in a high-stakes testing environment, and also their associations with individual factors (gender, grade, reading proficiency, and motivational beliefs). With a sequential explanatory mixed-methods design, students in grades 11 and 12 (n = 1,113) completed a reading comprehension test and a questionnaire regarding their strategy use and individual factors, and some (n = 16) were randomly selected for follow-up semi-structured interviews. Findings revealed three SRL profiles, characterized by high, medium, and low levels of SRL-strategy use. Self-efficacy and extrinsic motivation most powerfully predicted an individual’s profile membership; all the intrinsic and extrinsic motivation variables were significantly higher for learners from the higher strategy-use profile. Moreover, reading proficiency did not significantly predict profile membership, but more self-regulated students still achieved higher reading scores as a group tendency.

Background The cranial base develops from multipotent mesenchymal cells through endochondral ossification. Genetic ablation of Sonic hedgehog ( Shh ) or Smoothened ( Smo ) leads to early apoptosis of cranial base cells, thus limiting the study of their role in the early development of cranial base. Our previous studies have shown that administration of 150 mg/kg Vismodegib (a Smo -specific small molecule antagonist) in E9.5- or E10.5-mice leads to premature mineralization of the skull base synchondroses. In the current study, we further investigated the molecular mechanisms underlying this model. Results Mice exposed to Vismodegib exhibit premature hypertrophic differentiation and osteogenesis of the cranial base synchondroses after E14.5. However, the expression of Patched1 ( Ptch1 ), Gli1 , parathyroid hormone-related protein ( PTHrP ), and Phh3 was not downregulated in exposure mice. We demonstrate that Shh and Wnt signaling pathways were activated in the cranial base region at E10.5. Administration of Vismodegib at E10.5 transiently inhibited Shh signaling in the cranial base area and caused upregulation of β-catenin expression along with ectopic expression of lymphoid enhancer-binding factor 1 ( Lef1 ) and Runx2 in the ventral mesenchymal cells of the cranial base primordium at E12.5. Diverse degrees of cranial base craniosynostosis induced by various doses of Vismodegib suggest a dose-dependent effect of Shh in early basicranium development. Conclusions The present experiment suggests that early activation of Shh standardizes normal embryonic development of cranial base after initial morphogenesis, which may be mediated through the “antagonistic” effect of Shh signaling on Wnt signaling. Our study provides new insights into the role of signal-crosstalk in early morphogenesis of the cranial base.

To address the challenge of forecasting power output from large-scale photovoltaic (PV) bases in desert regions during sand and dust storms, this paper proposes a hybrid data-physics driven prediction method. This approach utilizes satellite remote sensing to obtain regional irradiance data, transforming the traditional one-dimensional time-series forecasting into a two-dimensional spatiotemporal sequence prediction, thereby tracking the dynamic evolution of irradiance intensity under the influence of sand and dust. Firstly, a forecasting model based on a conditional variational autoencoder (CVAE) optimized with a recurrent state-space model (RSSM) is constructed to effectively capture both the deterministic trends and stochastic fluctuations in irradiance variation, providing a reliable input basis for power calculation. Secondly, at the physical modeling level, the model comprehensively considers the isotropic scattering characteristics and changes in sky clarity induced by sand and dust weather, establishing a physical mapping relationship from irradiance to PV output. This mitigates the constraint of scarce historical operational data in desert and sandy regions. This research provides a novel solution for regional-level PV power forecasting under extreme sand and dust weather, contributing to enhanced dispatchability and transmission stability of renewable energy bases during abrupt meteorological changes.

In this study, we developed a reflective localized surface plasmon resonance (LSPR) optical fiber sensor, based on silver nanoparticles (Ag NPs). To enhance the sensitivity of the LSPR optical sensor, two key parameters were optimized, the length of the sensing area and the coating time of the Ag NPs. A sensing length of 1.5 cm and a 1-h coating time proved to be suitable conditions to produce highly sensitive sensors for biosensing. The optimized sensor has a high refractive index sensitivity of 387 nm/RIU, which is much higher than that of other reported individual silver nanoparticles in solutions. Moreover, the sensor was further modified with antigen to act as a biosensor. Distinctive wavelength shifts were found after each surface modification step. In addition, the reflective LSPR optical fiber sensor has high reproducibility and stability.

Objective: We analyzed the COVID-19 Open Research Dataset (CORD-19) to understand leading research institutions, collaborations among institutions, major publication venues, key research concepts, and topics covered by pandemic-related research.Methods: We conducted a descriptive analysis of authors’ institutions and relationships, automatic content extraction of key words and phrases from titles and abstracts, and topic modeling and evolution. Data visualization techniques were applied to present the results of the analysis.Results: We found that leading research institutions on COVID-19 included the Chinese Academy of Sciences, the US National Institutes of Health, and the University of California. Research studies mostly involved collaboration among different institutions at national and international levels. In addition to bioRxiv, major publication venues included journals such as The BMJ, PLOS One, Journal of Virology, and The Lancet. Key research concepts included the coronavirus, acute respiratory impairments, health care, and social distancing. The ten most popular topics were identified through topic modeling and included human metapneumovirus and livestock, clinical outcomes of severe patients, and risk factors for higher mortality rate.Conclusion: Data analytics is a powerful approach for quickly processing and understanding large-scale datasets like CORD-19. This approach could help medical librarians, researchers, and the public understand important characteristics of COVID-19 research and could be applied to the analysis of other large datasets.

CO2 (GWP = 1) is considered as a promising natural alternative refrigerant to HFC-134a in mobile air conditioning (MAC) applications. The objective of this study is to investigate the cooling performance characteristics of a CO2 MAC system. A prototype CO2 MAC system, consisting of a CO2 electrical compressor, CO2 parallel flow microchannel heat exchangers, and an electrical expansion valve, was developed and tested. Factor analysis experiments were conducted to reveal the effect of outdoor temperature on the cooling performance of this CO2 MAC system. Compared with a conventional R134a MAC system, the prototype CO2 MAC system achieved comparable cooling capacity, but had COP reductions of 26% and 10% at 27 °C and 45 °C outdoor conditions, respectively. In addition, based on refrigerant properties, theoretical cycle analysis was done to reveal the impact of evaporator, gas cooler and compressor, on the system cooling performance. It is concluded that the increase of overall compressor efficiency or the decrease of gas cooler approaching temperature could greatly improve the COP of this CO2 MAC system.

Background China is experiencing an increasingly serious aging population. Cognitive function is an important factor and guarantee for the quality of life of older people. Therefore, to achieve healthy aging, this study aimed to examine the sequential multiple mediating effects of indoor ventilation frequency and cognitive function on anxiety and self-rated health in the Chinese older people population. Methods Using the 2018 China Longitudinal Health and Longevity Survey (CLHLS) dataset, we finally selected 10,372 Chinese seniors over the age of 65. First, we describe the basic socio-demographic information of the sample population. Second, Spearman correlation analysis was used to determine whether there was a correlation between indoor ventilation frequency, anxiety, self-rated health, and cognitive function among Chinese older people. Finally, the SPSS macro process program was used to complete the sequence multiple mediation analysis. Results Indoor ventilation frequency, anxiety, self-rated health and cognitive function were significantly correlated ( p  < 0.01). Indoor ventilation frequency not only has a direct positive impact on the cognitive function of older people (effect = 0.1427; Standard error = 0.0201; 95%CI: LL = 0.1034, UL = 0.1821), but also indirectly affected cognitive function through three pathways: independent mediation of anxiety (effect = 0.0078; Standard error = 0.0021; 95%CI: LL = 0.0041, UL = 0.0121), independent mediating effect of self-rated health (effect = 0.0154; Standard error = 0.0030; 95%CI: LL = 0.0098, UL = 0.0215), and the chain mediating effect between anxiety and self-rated health (effect = 0.0046; Standard error = 0.0009; 95%CI: LL = 0.0029, UL = 0.0065). Limitations All projects are self-reported and some results may be biased. In the future, it may be more inspiring to explore more detailed and specific effects of indoor air quality on cognitive function in older people. Conclusions Studies have shown that indoor ventilation frequency can improve cognitive function by reducing anxiety and improving self-rated health in older people Chinese. Encouraging older adults to increase the frequency of indoor ventilation will benefit their mental health and cognitive function. Highlights This study provides empirical evidence for the association between indoor ventilation frequency and cognitive function in older people Chinese adults. We used nationally representative data to investigate the relationship between indoor ventilation frequency and cognitive function and further explored the mediating role of anxiety and self-rated health in Chinese older adults. Indoor ventilation frequency can not only directly affect cognitive function in older people, but also indirectly affect cognitive function through anxiety and self-rated health. Anxiety and self-rated health have a series of mediating effects between indoor ventilation frequency and cognitive function.

Background To investigate the association between indoor ventilation frequency and symptoms of depression and anxiety in older persons. Methods A binary logistic regression model was used to analyze the effects of indoor ventilation frequency on depression and anxiety by using data from the 2018 Chinese longitudinal healthy longevity survey (CLHLS). Results A total of 9,690 older persons with an average age of (83.20 ± 11.27) years were included, including 4,458 males (46.0%) and 5,232 females (54.0%). The average score of indoor ventilation frequency was (6.06 ± 1.98) points, including 770 people (7.9%) with low frequency, 3,066 people (31.6%) with medium frequency, and 5,854 people (60.4%) with high frequency. 842 (8.7%) had symptoms of depression and 204 (2.1%) had symptoms of anxiety. Compared with the older persons with low indoor ventilation frequency, the older persons with higher ventilation frequency had a lower incidence of depression (OR(95%CI) = 1.92 (1.50 ∼ 2.46), 1.51 (1.27 ∼ 1.79); P  < 0.001). However indoor ventilation frequency was not associated with anxiety symptoms. Conclusion Indoor ventilation frequency is related to depressive symptoms in older persons. Communities and families should pay more attention to indoor ventilation and intervene in time to promote and improve the mental health of older persons.

The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM 2.5 in Hubei Province, China, to determine the specific role (i.e., overflow, limited overflow, bilateral, inflow, and limited inflow) of each city on regional pollution formation. Furthermore, a dynamic Apriori algorithm considering time-lag effects was used to mine the spatio-temporal associations of extreme PM 2.5 pollution events among different cities. Results suggest that the northern and central cities with high-level PM 2.5 concentration in Hubei have a significant spillover effect, whereas the eastern and southern cities generally play a role as the sink of pollutants. Based on the association rules of extreme PM 2.5 pollution, four main pollutant transport channels were excavated and well matched with the trajectories extracted by the atmospheric model. This paper provides new insights for exploring the interaction of intercity particulate pollution, which is a supplement and cross-validation of the model results.