COVID-19 incidence disparities have been documented in the literature, but the different driving factors among age groups have yet to be explicitly explained. This study proposes a community-based ...COVID-19 spatial disparity model, considering different levels of geographic units (individual and community), various contextual variables, multiple COVID-19 outcomes, and different geographic contextual elements. The model assumes the existence of age nonstationarity effects on health determinants, suggesting that health effects of contextual variables vary among place and age groups. Based on this conceptual model and theory, the study selected 62 county-level variables for 1,748 U.S. counties during the pandemic, and created an Adjustable COVID-19 Potential Exposure Index (ACOVIDPEI) using principal component analysis (PCA). The validation was done with 71,521,009 COVID-19 patients in the U.S. from January 2020 through June 2022, with high incidence rates shifting from the Midwest, South Carolina, North Carolina, Arizona, and Tennessee to the West and East coasts. This study corroborates the age nonstationarity effect of health determinants on COVID-19 exposures. These results empirically identify the geographic disparities of COVID-19 incidence rates among age groups and provide the evidentiary guide for targeting pandemic recovery, mitigation, and preparedness in communities.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Under topological guidance, the self‐assembly process based on a tetratopic porphyrin synthon results in a hydrogen‐bonded organic framework (HOF) with the predicted square layers topology (sql) but ...unsatisfied stability. Strikingly, simply introducing a transition metal in the porphyrin center does not change the network topology but drastically causes noticeable change on noncovalent interaction, orbital overlap, and molecular geometry, therefore ultimately giving rise to a series of metalloporphyrinic HOFs with high surface area, and excellent stability (intact after being soaked in boiling water, concentrated HCl, and heated to 270 °C). On integrating both photosensitizers and catalytic sites into robust backbones, this series of HOFs can effectively catalyze the photoreduction of CO2 to CO, and their catalytic performances greatly depend on the chelated metal species in the porphyrin centers. This work enriches the library of stable functional HOFs and expands their applications in photocatalytic CO2 reduction.
Crystallographic and computational studies on a series of porphyrinic hydrogen‐bonded organic frameworks (HOFs) reveal that metallization of porphyrin centers greatly alters the orbital overlap of the adjacent porphyrin, the geometry of the molecule/layer, and the strength of noncovalent interactions. Therefore, metalloporphyrin HOFs exhibit much higher stability, surface area, and catalytic activity than metal‐free porphyrinic HOFs.
This review aimed at investigating the related studies on English as a foreign language (EFL) teachers' self-assessment and its role in their self-efficacy and self-regulation. Earlier investigations ...have proved that teacher self-assessment was significantly correlated with self-regulation. Moreover, studies showed that self-assessment and self-regulation enabled teachers to consider their teaching effectiveness, and they were important components of formative assessment. Earlier studies showed that self-assessment raised learner awareness and increased self-efficacy significantly through the improvement of mastery experiences. Furthermore, the study presented the implications and future directions of this line of research for different people, such as EFL teachers, teacher educators, and foreign language scholars. The ideas can improve their awareness of teacher self-assessment, self-regulation, and self-efficacy in educational contexts.
With the rapid development of artificial intelligence (AI) theory, particularly deep learning neural networks, robot vacuums equipped with AI power can automatically clean indoor floors by using ...intelligent programming and vacuuming services. To date, several deep AI models have been proposed to distinguish indoor objects between cleanable litter and noncleanable hazardous obstacles. Unfortunately, these existing deep AI models focus entirely on the accuracy enhancement of object classification, and little effort has been made to minimize the memory size and implementation cost of AI models. As a result, these existing deep AI models require far more memory space than a typical robot vacuum can provide. To address this shortcoming, this paper aims to study and find an efficient deep AI model that can achieve a good balance between classification accuracy and memory usage (i.e., implementation cost). In this work, we propose a weight-quantized SqueezeNet model for robot vacuums. This model can classify indoor cleanable litters from noncleanable hazardous obstacles based on the image or video captures from robot vacuums. Furthermore, we collect videos or pictures captured by built-in cameras of robot vacuums and use them to construct a diverse dataset. The dataset contains 20,000 images with a ground-view perspective of dining rooms, kitchens and living rooms for various houses under different lighting conditions. Experimental results show that the proposed deep AI model can achieve comparable object classification accuracy of around 93% while reducing memory usage by at least 22.5 times. More importantly, the memory footprint required by our AI model is only 0.8 MB, indicating that this model can run smoothly on resource-constrained robot vacuums, where low-end processors or microcontrollers are dedicated to running AI algorithms.
Rational synthesis of hydrogen‐bonded organic frameworks (HOFs) with predicted structure has been a long‐term challenge. Herein, by using the efficient, simple, low‐cost, and scalable ...mechanosynthesis, we demonstrate that reticular chemistry is applicable to HOF assemblies based on building blocks with different geometry, connectivity, and functionality. The obtained crystalline HOFs show uniform nano‐sized morphology, which is challenging or unachievable for conventional solution‐based methods. Furthermore, the one‐pot mechanosynthesis generated a series of Pd@HOF composites with noticeably different CO oxidation activities. In situ DRIFTS studies indicate that the most efficient composite, counterintuitively, shows the weakest CO affinity to Pd sites while the strongest CO affinity to HOF matrix, revealing the vital role of porous matrix to the catalytic performance. This work paves a new avenue for rational synthesis of HOF and HOF‐based composites for broad application potential.
Efficient and green mechanochemistry was performed to realize the reticular synthesis of hydrogen‐bonded organic frameworks with predictable structures. Moreover, a series of Pd@HOF composites were generated by the one‐pot mechanosynthesis, which showed different catalytic activities for CO oxidation. The synergetic effect between Pd and HOF was revealed by in situ DRIFTS, proving the application potential of functionalized HOF‐composites.
It is preserved that one of the noteworthy influential subjects of success and achievement is emotions, and enhancing emotions is dominant in promoting the language learning of students in the ...classroom. Although emotions are an integral part of the practices of both educators and students, their function has been sidelined due to the emphasis on intellectual instead of emotional scopes of foreign language learning. Therefore, the present theoretical review tries to refocus on the role of emotions of teachers and learners and their effects on language success and achievement. Successively, the effectiveness of verdicts for educators, students, syllabus designers, and future researchers are deliberated.
Robot vacuum cleaners have gained widespread popularity as household appliances. One significant challenge in enhancing their functionality is to identify and classify small indoor objects suitable ...for safe suctioning and recycling during cleaning operations. However, the current state of research faces several difficulties, including the lack of a comprehensive dataset, size variation, limited visual features, occlusion and clutter, varying lighting conditions, the need for real-time processing, and edge computing. In this paper, I address these challenges by investigating a lightweight AI model specifically tailored for robot vacuum cleaners. First, I assembled a diverse dataset containing 23,042 ground-view perspective images captured by robot vacuum cleaners. Then, I examined state-of-the-art AI models from the existing literature and carefully selected three high-performance models (Xception, DenseNet121, and MobileNet) as potential model candidates. Subsequently, I simplified these three selected models to reduce their computational complexity and overall size. To further compress the model size, I employed post-training weight quantization on these simplified models. In this way, our proposed lightweight AI model strikes a balance between object classification accuracy and computational complexity, enabling real-time processing on resource-constrained robot vacuum cleaner platforms. I thoroughly evaluated the performance of the proposed AI model on a diverse dataset, demonstrating its feasibility and practical applicability. The experimental results show that, with a small memory size budget of 0.7 MB, the best AI model is L-w Xception 1, with a width factor of 0.25, whose resultant object classification accuracy is 84.37%. When compared with the most accurate state-of-the-art model in the literature, this proposed model accomplished a remarkable memory size reduction of 350 times, while incurring only a slight decrease in classification accuracy, i.e., approximately 4.54%.
Embedding plasmonic metals in metal–organic frameworks (MOFs) can build an advanced visible‐light photocatalyst architecture utilizing the localized surface plasmon resonance (LSPR) effect, while the ...practical performances have been restricted by the sluggish charge transfer at metal–MOF interface and through the secondary building units (SBUs) of the adopted carboxylate MOFs currently. Herein, a pyrazolate Ni‐MOF (PFC‐9) featured with an 1D SBU chain is selected to be the host catalyst to immobilize Au nanoparticles as a novel and optimized construction for LSPR photocatalysis. Compared with the common 3D‐connected SBUs of carboxyl‐ZrOx and pyrazole‐NiOx configurations in the reference MOFs, the 1D (−Ni−NPz−NPz−)∞ chain in PFC‐9 creates abundant Au/MOF contacts, a short and low‐resistant pathway for Au‐to‐Ni2+ transport of hot electrons, and enables fluent electron utilization at the continuous active Ni sites. Consequently, the Au/PFC‐9 photocatalyst achieves the optimum activity for visible‐light‐driven H2 production. This work shows an example to promote the LSPR‐sensitized photocatalysis taking the advantage of MOFs’ structural tunability, providing significant guidance for the rational design of highly efficient photocatalysts.
A novel Au/MOF photocatalyst is constructed by taking the advantage of the pyrazole groups and catalytically active Ni2+ nodes in the 1D coordination chain of PFC‐9. The short‐range and low‐resistant hot‐electron transfer, from Au to Ni and throughout the continuous Ni sites, results in optimum activity for Au‐sensitized photocatalytic H2 production superior to cases without 1D pyrazolate secondary building units.
The phenomenon of nationalist digital vigilantism targeting Chinese intellectual women is rising in China. To illustrate how national identities and social exclusion are discursively constructed, as ...well as the potential vulnerabilities experienced by Chinese female intellectuals, four high-profile cases that took place between 2017 and 2021 are chosen. Critical discourse analysis is conducted on collected Sina Weibo comments, WeChat public account articles, and news articles published by state-run media. The research identifies three main discourses: the ungrateful traitor, the corrupt elite, and the ugly slut. These discursive interactions demonstrate the fluidity of both discursive and operational conditions in nationalist digital vigilantism, which amplifies the targets’ vulnerability. This research contributes to the study of misogynist populist nationalism by providing an empirical analysis in an under-studied social context—China, and to the study of Chinese populist nationalism by foregrounding an under-studied perspective—misogyny.
To investigate the role of adsorption by biochar and biodegradation by bacteria in the wastewater treatment system of microorganisms immobilized on biochar, Nonylphenol (NP) removal ...(adsorption + degradation) rates and degradation rates from water by NP degrading bacteria immobilized on bamboo charcoal (BC) and wood charcoal (WC) were examined in a short-term and long-term. Results showed that cells immobilized on different biochar had different NP removal effects, and cells immobilized on bamboo charcoal (I-BC) was better. After eight rounds of long-term reuse, the cumulative removal rate and the degradation rate of NP in water by I-BC were 93.95% and 41.86%, respectively, significantly higher than those of cells immobilized on wood charcoal (69.60%, 22.78%) and free cells (64.79%, 19.49%) (P < 0.01). The rise in the ratio of the degradation rate to the removal rate indicated that the long-term NP removal effect is more dependent on biodegradation. The amount of residual NP in I-BC still accounted for about 50%, indicating that the secondary pollution in the disposal of carrier could not be ignored. In addition, promotion effect of biochar on microorganisms were observed by SEM, quantitative PCR and 16S rRNA. Pseudomonas, Achromobacter, Ochrobactrum and Stenotrophomonas were predominant bacteria for NP degradation. The addition of biochar (especially bamboo charcoal) also effectively delayed the transformation of their community structure.
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•Cells immobilized on bamboo charcoal showed higher removal and degradation rate.•Nonylphenol removal was more dependent on degradation in microbe-biochar system.•Biochar could protect microorganism and delay the transform of community structure.•The amount of pollutants remaining in biochar could not be ignored.
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