Comparative Study of In-situ Test and Laboratory Test on Material Reflectivity

AbstractThis paper gives the theory algorithm of material reflectivity, and works out the in-situ material reflectivity combined with in-situ conditions, researches the influence rules of material's reflectivity under practical solar radiation intensity, and the feasibility of this simple in-situ test method is researched by the comparison of in-situ test result and laboratory test result

Efficient and durable uranium extraction from uranium mine tailings seepage water via a photoelectrochemical method

Current photocatalytic uranium (U) extraction methods have intrinsic obstacles, such as the recombination of charge carriers, and the deactivation of catalysts by extracted U. Here we show that, by applying a bias potential on the photocatalyst, the photoelectrochemical (PEC) method can address these limitations. We demonstrate that, owing to efficient spatial charge-carriers separation driven by the applied bias, the PEC method enables efficient and durable U extraction. The effects of multiple operation conditions are investigated. The U extraction proceeds via single-step one-electron reduction, resulting in the formation of pentavalent U, which can facilitate future studies on this often-overlooked U species. In real seepage water the PEC method achieves an extraction capacity of 0.67 gU m(-3).h(-1) without deactivation for 156 h continuous operation, which is 17 times faster than the photocatalytic method. This work provides an alternative tool for U resource recovery and facilitates future studies on U(V) chemistry

Anxiety, depression, and insomnia among nurses during the full liberalization of COVID-19: a multicenter cross-sectional analysis of the high-income region in China

IntroductionFrontline nurses fighting against the epidemic were under great psychological stress. However, there is a lack of studies assessing the prevalence rates of anxiety, depression, and insomnia among frontline nurses after the full liberalization of COVID-19 in China. This study demonstrates the impact of the full liberalization of COVID-19 on the psychological issues and the prevalence rate and associated factors of depressive symptoms, anxiety, and insomnia among frontline nurses.MethodsA total of 1766 frontline nurses completed a self-reported online questionnaire by convenience sampling. The survey included six main sections: the 9-item Patient Health Questionnaire (PHQ-9), the 7-item Generalized Anxiety Disorder (GAD-7), the 7-item Insomnia Severity Index (ISI), the 10-item Perceived Stress Scale (PSS-10), sociodemographic information, and work information. Multiple logistic regression analyses were applied to identify the potential significantly associated factors for psychological issues. The study methods were compliant with the STROBE checklist.Results90.83% of frontline nurses were infected with COVID-19, and 33.64% had to work while infected COVID-19. The overall prevalence of depressive symptoms, anxiety and insomnia among frontline nurses was 69.20%, 62.51%, and 76.78%, respectively. Multiple logistic analyses revealed that job satisfaction, attitude toward the current pandemic management, and perceived stress were associated with depressive symptoms, anxiety, and insomnia.ConclusionsThis study highlighted that frontline nurses were suffering from varying degrees of depressive symptoms, anxiety, and insomnia during full liberalization of COVID-19. Early detection of mental health issues and preventive and promotive interventions should be implemented according to the associated factors to prevent a more serious psychological impact on frontline nurses

Adiponectin-Mediated Promotion of CD44 Suppresses Diabetic Vascular Inflammatory Effects

While adiponectin (APN) was known to significantly abolish the diabetic endothelial inflammatory response, the specific mechanisms have yet to be elucidated. Aortic vascular tissues from mice fed normal and high-fat diets (HFD) were analyzed by transcriptome analysis. GO functional annotation showed that APN inhibited vascular endothelial inflammation in an APPL1-dependent manner. We confirmed that activation of the Wnt/β-catenin signaling plays a key role in APN-mediated anti-inflammation. Mechanistically, APN promoted APPL1/reptin complex formation and β-catenin nuclear translocation. Simultaneously, we identified APN promoted the expression of CD44 by activating TCF/LEF in an APPL1-mediated manner. Clinically, the serum levels of APN and CD44 were decreased in diabetes; the levels of these two proteins were positively correlated. Functionally, treatment with CD44 C-terminal polypeptides protected diabetes-induced vascular endothelial inflammation in vivo. Collectively, we provided a roadmap for APN-inhibited vascular inflammatory effects and CD44 might represent potential targets against the diabetic endothelial inflammatory effect

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A Representation Model of Geometrical Tolerances Based on First Order Logic

Part 7: Knowledge RepresentationInternational audienceTolerance representation models are used to specify tolerance types and explain semantics of tolerances for nominal geometry parts. To well explain semantics of geometrical tolerances, a representation model of geometrical tolerances based on First Order Logic (FOL) is presented in this paper. We first investigate the classifications of feature variations and give the FOL representations of them based on these classifications. Next, based on the above representations, we present a FOL representation model of geometrical tolerances. Furthermore, we demonstrate the effectiveness of the representation model by specifying geometrical tolerance types in an example

A numerical study of the effects of injection rate shape on combustion and emission of diesel engines

The spray characteristics including spray droplet sizes, droplet distribution, spray tip penetration length and spray diffusion angle directly affects the mixture process of fuel and oxygen and then plays an important role for the improvement of combustion and emission performance of diesel engines. Different injection rate shapes may induce different spray characteristics and then further affect the subsequent combustion and emission performance of diesel engines. In this paper, the spray and combustion processes based on four different injection rate shapes with constant injection duration and injected fuel mass were simulated in the software of AVL FIRE. The numerical models were validated through comparing the results from the simulation with those from experiment. It was found that the dynamic of diesel engines with the new proposed hump shape of injection rate and the original saddle shape is better than that with the injection rate of rectangle and triangle shape, but the emission of NOX is higher. And the soot emission is lowest during the late injection period for the new hump-shape injection rate because of a higher oxidation rate with a better mixture between fuel and air under the high injection pressure