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Spray cooling is a promising and effective cooling method, which may be used to solve the heat dissipation problem of high-power electronic components. In this paper, the influences of flow rate, sub-cooling degree, and refrigerant charge on the spray cooling heat transfer performance with R134a as the working fluid were experimentally studied. Results showed that the enhancement effect of the increase of sub-cooling degree on the heat transfer performance is very limited in this experiment. When the sub-cooling degree rises from 5 to 8 K, the heat transfer coefficient increases by 2.6% on average at lower heat flux (45.93–72.55 W/cm2). The increase of refrigerant charge can effectively improve the heat transfer performance, especially at higher heat flux (84.02–105.25 W/cm2). However, the Jacobian number decreases with the increase of the refrigerant charge, which hinders the improvement of heat transfer performance at higher heat flux. Therefore, there is an optimal refrigerant charge of 1.05 kg in this experiment. In addition, based on the experimental data, a Nusselt number dimensionless correlation of R134a solution with higher prediction accuracy was proposed.

In this paper, the outside cabin heat exchanger based on the porous media approach was established. The effects of altitude, viscous resistance coefficient, inertial resistance coefficient, and core thickness on the naturally captured air volume of the heat exchanger were investigated by numerical simulation. Results showed that the naturally captured air volume of the heat exchanger tends to be larger on both sides and smaller in the middle, and there is a quasi-linear increase proportional to the incoming wind velocity. With the increment of altitude, viscous resistance coefficient, and inertial resistance coefficient, the average naturally captured air volume of the heat exchangers shows a downward trend. The trend would be clear with the increment of the incoming wind velocity, nevertheless, the effect of core thickness is weak. In addition, the design values of the viscous resistance coefficient and the inertial resistance coefficient should be restricted in the order of 106 and below 500, respectively. Based on the weak effect of the naturally captured air volume of the heat exchanger, the thickness of the core can be appropriately increased to ensure the heat transfer area of the heat exchanger.

Background Quantitative trait locus (QTL) analysis aims to locate and estimate the effects of the genes influencing quantitative traits and infer the relationship between gene variants and changes in phenotypic characteristics using statistical methods. Some methods have been developed to map QTLs of multiple traits in the case of no genotype error in a given dataset. However, practical genetic data that people use may contain some potential errors because of the limitations of biotechnology. Common genetic data correction methods can only reduce errors, but cannot calculate the degree of error. In this paper, we propose a QTL mapping strategy for multiple traits in the presence of genotype errors. Methods The additive effect, dominant effect, recombination rate, error rate, and other parameters of QTLs can be simultaneously obtained using this new method in the framework of multiple-interval mapping. Results Our simulation results show that the accuracy of parameter estimation can be improved by considering the errors of marker genotypes during the analysis of genetic data. Real data analysis also shows that the new method proposed in this paper can map the QTLs of multiple traits more accurately.

Current genome-wide association analysis has identified a great number of rare and common variants associated with common complex traits, however, more effective approaches for detecting associations between rare and common variants with common diseases are still demanded. Approaches for detecting rare variant association analysis will compromise the power when detecting the effects of rare and common variants simultaneously. In this paper, we extend an existing method of testing for rare variant association based on affected sib pairs (TOW-sib) and propose a variable weight test for rare and common variants association based on affected sib pairs (abbreviated as VW-TOWsib). The VW-TOWsib can be used to achieve the purpose of detecting the association of rare and common variants with complex diseases. Simulation results in various scenarios show that our proposed method is more powerful than existing methods for detecting effects of rare and common variants. At the same time, the VW-TOWsib also performs well as a method for rare variant association analysis.

A cobalt-tripeptide complex (CoGGH) is developed as an electrocatalyst for the selective six-electron, eight-proton reduction of nitrite to ammonium in aqueous buffer near neutral pH. The onset potential for nitrite reduction occurs at -0.65 V vs Ag/AgCl (1 M KCl). Controlled potential electrolysis at -0.90 V generates ammonium with a faradaic efficiency of 90 ± 3% and a turnover number of 3550 ± 420 over 5.5 h. CoGGH also catalyzes the reduction of the proposed intermediates nitric oxide and hydroxylamine to ammonium. These results reveal that a simple metallopeptide is an active functional mimic of the complex enzymes cytochrome c nitrite reductase and siroheme-containing nitrite reductase.

Aiming at the problem of the disconnection between theory and practice in the teaching process of civil aviation Aeronautical Information Service (AIS) course at present, we should start from the actual needs of civil aviation AIS work, and combine with the current theoretical teaching situation of the course. This paper puts forward a practice-oriented teaching mode, designs the course framework, main contents, and the teaching method under the task-driven mode. It provides suggestions and references for the follow-up improvement of the teaching effect of this course.

The detection of gene-environment (GE) interactions is very important for dealing with complex diseases. Although some methods have been proposed to detect the interactions between genes and the environment, however, in the case of rare variants, these methods are limited. In this paper, we extend the existing ADA method and proposed a combined strategy (i-ADA) to identify the gene-environment interaction for rare variants. Firstly, we use Levene test to test the equality of variances under different sites. Secondly, based on the first-sep P-values and combined with the ADA method, we design a novel interaction test. Finally, we use the GAW17 dataset to illustrate the practicality of the proposed method.

miR-101 is an outstanding tumor suppressor in various cancers, while its role in pancreatic cancer (PC) is still unknown. The aim of this study was to investigate the role of miR-101 in epithelial-to-mesenchymal transition (EMT) and its clinical relevance in PC. Our data showed that the miR-101 expression was significantly decreased in human PC tissues, compared to non-tumor counterparts (p

MicroRNAs (miRNAs) have been integrated into tumorigenic programs by regulating genes at post-transcriptional level. Long non-coding RNAs (lncRNAs) are novel targets for miRNAs. Here, we reported that miR-203 down-regulation was closely linked to advanced clinical features and poor overall survival (OS) of patients with hepatocellular carcinoma. We also confirmed that miR-203 and oncogene ADAM9 (a disintegrin and metalloproteinase 9)/oncogenic long non-coding RNA HULC (highly up-regulated in liver cancer) were inversely expressed in hepatocellular carcinoma (HCC) tissues or cell lines. More intriguingly, up-regulation of miR-203 diminished the expression of ADAM9 and HULC in HCC cancer cells. Over-expression of miR-203 could markedly inhibit cell proliferation, invasion and induce cell apoptosis. Furthermore, we identified that miR-203 modulated ADAM9 and HULC in a novel post-transcriptional regulatory mechanism. Over-expression of HULC partly rescued the miR-203-mediated antitumor effects. These results suggested that miR-203 played tumor suppressive roles by downregulating ADAM9 and HULC and indicated its potential application in cancer treatment.

There has been great interest in the development of stable, inexpensive, efficient catalysts capable of reducing aqueous protons to hydrogen (H2), an alternative to fossil fuels. While synthetic H2 evolution catalysts have been in development for decades, recently there has been great progress in engineering biomolecular catalysts and assemblies of synthetic catalysts and biomolecules. In this Forum Article, progress in engineering proteins to catalyze H2 evolution from water is discussed. The artificial enzymes described include assemblies of synthetic catalysts and photosynthetic proteins, proteins with cofactors replaced with synthetic catalysts, and derivatives of electron-transfer proteins. In addition, a new catalyst consisting of a thermophilic cobalt-substituted cytochrome c is reported. As an electrocatalyst, the cobalt cytochrome shows nearly quantitative Faradaic efficiency and excellent longevity with a turnover number of >270000.

With the development of air transport industry in China, the congestion problem in the terminal areas of busy airports has become increasingly serious. In order to alleviate the increasingly frequent air traffic congestion, it is necessary to accurately and objectively predict traffic flow. Traditionally, most predicted methods are based on the number of aircrafts flight in the terminal area to obtain deterministic traffic flow data, without considering the impact of uncertain factors on the prediction results. Based on the uncertainty of demand, this paper uses a probability density prediction method based on quantile regression neural network and kernel density estimation, to analyse the variation of traffic flow at different quantiles according to the obtained continuous conditional quantile function. Predicting the probability density of traffic flow on a certain day, and then comparing the point prediction value corresponding to the peak value, which consider the weather factor and the conditional probability density prediction curve without considering the weather factor, it is concluded that considering the weather factor can make the traffic flow prediction more accurate.

The cobalt complex of an amino-terminal copper and nickel (ATCUN) motif model tripeptide (CoGGH) is shown to act as an electrocatalyst for hydrogen evolution from water near neutral pH with high Faradaic efficiency. The catalyst performance is not significantly impacted by exposure to oxygen. CoGGH represents a new class of hydrogen evolution catalyst that is straightforward to prepare and to modify.

A fluorescent chemodosimeter for cysteine detection was developed based on a tandem conjugate addition and intramolecular cyclization reaction. The method exhibited an excellent selectivity for cysteine over other biothiols such as homocysteine and glutathione.

Biological thiols are essential for maintaining the appropriate redox status of proteins, cells, and organisms.[1] Cysteine (Cys) is an essential amino acid that is involved in protein synthesis, detoxification, and metabolism. Elevated levels of Cys have been associated with neurotoxicity,[2] and Cys deficiency is involved in slowed growth rate, hair depigmentation, edema, lethargy, liver damage, muscle and fat loss, skin lesions, and weakness.[3] Homocysteine (Hcy) has been implicated in various types of vascular and renal diseases. Elevated Hcy in the blood (>12 µm) is a well-known risk factor for cardiovascular[4a] and Alzheimer’s disease,[4b] neutral tube defects, complications during pregnancy, inflammatory bowel disease, and osteoporosis.[4c] Because Cys and Hcy levels are associated with different diseases despite their similar structures, their discrimination is necessary.