The development of highly active and durable electrocatalysts toward the N2 reduction reaction (NRR) holds a key to ambient electrocatalytic NH3 synthesis. Herein, fluorine (F)-doped SnO2 mesoporous ...nanosheets on carbon cloth (F-SnO2/CC) were developed as an efficient NRR electrocatalyst. Benefiting from the combined structural advantages of mesoporous nanosheet structure and F-doping, the F-SnO2/CC exhibited high NRR activity with an NH3 yield of 19.3 μg h–1 mg–1 and a Faradaic efficiency of 8.6% at −0.45 V (vs RHE) in 0.1 M Na2SO4, comparable or even superior to those of most reported NRR electrocatalysts. Density functional theory calculations revealed that the F-doping could readily tailor the electronic structure of SnO2 to render it with improved conductivity and increased positive charge on active Sn sites, leading to the lowered reaction energy barriers and boosted NRR activity.
Electrospinning is an advanced technology for the preparation of drug-carrying nanofibers that has demonstrated great advantages in the biomedical field. Electrospun nanofiber membranes are widely ...used in the field of drug administration due to their advantages such as their large specific surface area and similarity to the extracellular matrix. Different electrospinning technologies can be used to prepare nanofibers of different structures, such as those with a monolithic structure, a core-shell structure, a Janus structure, or a porous structure. It is also possible to prepare nanofibers with different controlled-release functions, such as sustained release, delayed release, biphasic release, and targeted release. This paper elaborates on the preparation of drug-loaded nanofibers using various electrospinning technologies and concludes the mechanisms behind the controlled release of drugs.
Depression is a major mental health issue worldwide, and university students with heavy burdens of study are at a high risk for depression. While a number of studies have been conducted regarding ...depression among university students in China, there is a lack of information regarding the national prevalence of depression among Chinese university students. Therefore, we performed a meta-analysis to statistically pool the prevalence of depression among Chinese university students.
A systematic search of scientific databases was conducted, including Chinese Web of Knowledge, Embase, PubMed, Wanfang (a Chinese database) and Weipu (a Chinese database) to find relevant publications published between 1995 and December 2015. This was supplemented by a secondary review of the reference lists of all retrieved papers to find additional relevant citations. Studies published in either English or Chinese that provided prevalence estimates of depression in Chinese university students were considered. Prevalence estimates of each eligible study were extracted and pooled in our meta-analysis using a random-effects model.
A total of 39 studies conducted between 1997 and 2015 including 32,694 university students were analyzed. Our results indicate that the overall prevalence of depression among Chinese university students is 23.8% (95% CI: 19.9%-28.5%). Substantial heterogeneity in prevalence estimates was noted. Subgroup analysis revealed that the prevalence of depression among medical students is higher than among other students.
Overall, the prevalence of depression among Chinese university students is exceedingly high. This suggests that it is imperative that more attention be given to the development of appropriate mental healthcare strategies for university students in China.
The sirtuin family in health and disease Wu, Qi-Jun; Zhang, Tie-Ning; Chen, Huan-Huan ...
Signal transduction and targeted therapy,
12/2022, Letnik:
7, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Sirtuins (SIRTs) are nicotine adenine dinucleotide(+)-dependent histone deacetylases regulating critical signaling pathways in prokaryotes and eukaryotes, and are involved in numerous biological ...processes. Currently, seven mammalian homologs of yeast Sir2 named SIRT1 to SIRT7 have been identified. Increasing evidence has suggested the vital roles of seven members of the SIRT family in health and disease conditions. Notably, this protein family plays a variety of important roles in cellular biology such as inflammation, metabolism, oxidative stress, and apoptosis, etc., thus, it is considered a potential therapeutic target for different kinds of pathologies including cancer, cardiovascular disease, respiratory disease, and other conditions. Moreover, identification of SIRT modulators and exploring the functions of these different modulators have prompted increased efforts to discover new small molecules, which can modify SIRT activity. Furthermore, several randomized controlled trials have indicated that different interventions might affect the expression of SIRT protein in human samples, and supplementation of SIRT modulators might have diverse impact on physiological function in different participants. In this review, we introduce the history and structure of the SIRT protein family, discuss the molecular mechanisms and biological functions of seven members of the SIRT protein family, elaborate on the regulatory roles of SIRTs in human disease, summarize SIRT inhibitors and activators, and review related clinical studies.
To support multiple on-demand services over fixed communication networks, network operators must allow flexible customization and fast provision of their network resources. One effective approach to ...this end is network virtualization, whereby each service is mapped to a virtual subnetwork providing dedicated on-demand support to network users. In practice, each service consists of a prespecified sequence of functions, called a service function chain (SFC), while each service function in a SFC can only be provided by some given network nodes. Thus, to support a given service, we must select network function nodes according to the SFC and determine the routing strategy through the function nodes in a specified order. A crucial network slicing problem that needs to be addressed is how to optimally localize the service functions in a physical network as specified by the SFCs, subject to link and node capacity constraints. In this paper, we formulate the network slicing problem as a mixed binary linear program and establish its strong NP-hardness. Furthermore, we propose efficient penalty successive upper bound minimization (PSUM) and PSUM-R(ounding) algorithms, and two heuristic algorithms to solve the problem. Simulation results are shown to demonstrate the effectiveness of the proposed algorithms.
Electroreduction of N2 represents a promising technique for ambient NH3 synthesis, but exploring efficient electrocatalysts for nitrogen reduction reaction (NRR) remains a key challenge. Herein, we ...reported our experimental and theoretical findings that FeMoO4 could be a new candidate for effective and durable NRR in neutral solution. The developed FeMoO4 nanorods exhibited a fascinating NRR activity with an NH3 yield of 45.8 μg h–1 mg–1 (−0.5 V) and a Faradaic efficiency of 13.2% (−0.3 V). Mechanistic studies disclosed that Fe and Mo synergistically promoted the N2 adsorption and accelerated the electron transfer on FeMoO4, whereas the unsaturated 3-fold coordinated Mo (Mo3c) sites served as the main active centers for stabilizing the key *N2H intermediate and reducing the reaction energy barrier.
Understanding the drivers of low-carbon practices in green supply chain management in the construction industry is essential because it largely addresses the major problem of global warming due to ...carbon dioxide emissions. The purpose of this study is to investigate key drivers of low-carbon practices in green supply chain management in construction industry. Based on institutional theory, relational view theory, and self-determination theory, three drivers for low-carbon practices were identified, namely, environmental regulation, supply chain relationship, and organizational culture. Then a questionnaire was administered and data were collected from the owners, contractors, designers, and other relevant parties of the construction project. Partial least squares structural equation modeling was used to analyze data. The results show that supply chain relationship and organizational culture are positively and directly correlated with the low-carbon practices level of green supply chain management. In addition, this study also found that organizational culture partially mediates the relationship between supply chain relationship and low-carbon practices. Contrary to expectations, environmental regulation has no direct effect on practices, while supply chain relationship and organizational culture fully mediate the relationship between environmental regulation and practices. As limited research has been conducted to examine the drivers for green supply chain management low-carbon practices in the construction industry, this study bridges the knowledge gap and contributes to the current knowledge system of green supply chain management. Additionally, the findings of this study can provide authorities and practitioners with a deeper understanding of low-carbon practices in green supply chain management, and helping to propose more feasible measures to reduce carbon dioxide emissions and improve environmental performance.
•Clear definition and specific classification for atomically precise HPTCs are provided.•Typical examples are illustrated from synthesis-structures-properties perspective.•Bright future for HPTCs in ...bottom-up assembly for materials with tunable performances.
To exploit the use of solar energy in photocatalysis, metal ion doping is one of the most effective ways. At present, atomically precise heterometallic polyoxotitanium clusters (HPTCs) are of great interest as well-defined models for the way in which metal ions are doped into bulk titanium dioxide. Recently, researchers have contributed great efforts in HPTCs where majority metal ions throughout the periodic table have successfully incorporated. The incorporation of particular characteristics of metal dopants provides the opportunity to modify the microscopic electronic structure, then optical response, and ultimate macroscopical performances. In this review, we aim to summarize the recent progress on such a rapidly evolving topic of HPTCs and provide potential theoretical models for the rational design of photocatalysts and solar energy capture. Firstly, a brief summary of the synthetic strategies and bonding models between the metals and PTCs is provided. Then clear definition and classification of the HPTCs reported up to date is given. Moreover, representative examples are illustrated from experimental, theoretical and photophysical/photochemical perspectives, particularly in light absorption, fluorescence, photocatalysis, and gas sorption etc. Finally, the main challenges and opportunities are proposed with the goal of expanding the sunlight harvesting application range of HPTCs.
Recent reports show that at least 95% of the world's population is breathing polluted air. However, the impact of air quality on air pollution‐related medical expenditure and utilization is sparse. ...This study estimates the short‐term health care cost impacts of air pollution using a meteorological phenomenon—thermal inversion—as an instrumental variable for air quality. Using information on outpatient care for respiratory diseases from universal health insurance claim data in Taiwan during 2006–2012, our estimates suggest that a one‐unit reduction in the air quality index (AQI) leads to NT$2.3 billion (nearly US$74 million) of savings in respiratory‐related outpatient expenditure per year. Given that the average AQI is equal to 32 during our study period, completely removing air pollution would reduce the national health expenditure by approximately 8% annually. Our results provide the important implication that the cost of controlling air pollutant emissions can be offset by curtailing health care expenditure.
With the rapid development of mobile Internet, the demand for multicast is growing rapidly, such as content pushing and video streaming. The multicast service is usually offered to users without ...interrupting their on-going unicast transmission, and thus the multicast and unicast beamformers needs to be jointly designed, which generally requires perfect channel state information (CSI). However, perfect CSI is usually unavailable due to the channel estimation error. In this paper, we propose a learning based approach to jointly design the multicast and unicast beamformers with imperfect CSI. To learn the beamforming strategy, a new graph neural network (GNN) based architecture named unicast-multicast GNN (UMGNN) is proposed, which only requires the estimated channel. UMGNN can guarantee the permutation invariance/equivalence and model the special property in the multicast transmission, i.e., the multicast rate is determined by the worst user. Moreover, by sharing the parameters across different users, UMGNN exhibits a pretty good scalability to different number of users. Numerical results show that UMGNN outperforms a fully connected neural network and a widely used sampling-based algorithm. To highlight its performance in the multicast transmission, we also show that UMGNN can find the correct worst user that determines the multicast rate.
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