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Liquid hydrogen is a promising energy carrier in the global hydrogen value chain with the advantages of high volumetric energy density/purity, low operating pressure, and high flexibility in delivery. Safe and high-efficiency storage and transportation are essential in the large-scale utilization of liquid hydrogen. Aiming at the two indicators of the hold time and normal evaporation rate (NER) required in standards, this paper focuses on the thermal behaviors of fluid during the no-vented storage of liquid hydrogen and thermal insulations applied for the liquid hydrogen tanks, respectively. After presenting an overview of experimental/theoretical investigations on thermal behaviors, as well as typical forms/testing methods of performance of thermal insulations for liquid hydrogen tanks, seven perspectives are proposed on the key challenges and recommendations for future work. This work can benefit the design and improvement of high-performance LH2 tanks.

The non-equiatomic FeNiCoAlTaB high-entropy alloy exhibits outstanding quasi-static mechanical properties. Here, we investigate the microstructural evolution and mechanical response of this alloy subjected to dynamic loading, which has not been done before. A novel strategy combining extensive microbanding and martensitic transformation improves the resistance to the plastic instability by deterring the formation of adiabatic shear bands, that only occur beyond a critical shear strain larger than 4. The aged alloy, with grain sizes up to 400 μm, exhibits a dynamic yield stress over 1300 MPa with good deformability in this regime. This investigation sheds light on potential strategies for the enhancement of dynamic mechanical properties of structural materials through the use of a stress-induced martensitic transformation.

Measurement(s) mRNA Expression Technology Type(s) spatial transcriptomics Sample Characteristic - Organism Homo sapiens

Software defect prediction techniques can help software developers find software defects as soon as possible. It can also reduce the cost of software development. This technique usually predicts the target project through the entire source project. However, the data distribution difference between the entire source project and the target project is generally large, so the software defect prediction accuracy is not high. we propose a cross-project software defect prediction technique based on class code similarity CCS-CPDP. Firstly, this technique converts the code set extracted by AST(Abstract Syntax Tree) into a vector set through the DTI (Doc2Bow and TF-IDF) strategy; Secondly, the similarity will be calculated between the vector set of target projects and training projects; Finally, according to the principle of the majority decision subordinate category in KNN, the number of most similar class instances of the training project is determined, the source project is refined by selecting the class instance, and then software defects are predicted and evaluated. We compared CCS-CPDP with softawre defect prediction methods based on four traditional classification models (KNN, Random Forest, Naive Bayes, and Logistic Regression). Experimental results show that CCS-CPDP can improve the effectiveness of CPDP in terms of recall and f1-score.

China has had explosive growth in ischemic stroke (IS) burden with significant ethnic and geographic disparities. The aim of this study was to explore the possible combination effect between gut microbiota and traditional potentially modifiable risk factors for IS among two ethnic minorities (Tujia and Miao) and the Han population. Herein, we first used the 16 S rRNA sequencing to compare the gut microbial compositions of 82 patients with first-ever IS vs. 82 normal controls (NCs) among Han, Tujia, and Miao people between 1 May 2018 and 30 April 2019, from Xiangxi Tujia and Miao Autonomous Prefecture in China. An additive model was used to study the interaction between traditional risk factors and gut microbiota with R software. Linear discriminant analysis (LDA) and LDA effect size (LEfSe) results showed that the identified key gut microbiota's taxonomic composition varied in different ethnicity between the IS patients and NCs. Furthermore, families Lactobacillaceae, Enterococcaceae, Streptococcaceae, and Enterobacteriaceae were found to be positively correlated with high-risk factors and negatively correlated with preventive factors in the IS patients, but families Ruminococcaceae and Lachnospiraceae were just the opposite in the NCs. There were additive interactions between traditional risk factors (systolic blood pressure, diastolic blood pressure, and high-sensitive C-reactive protein) and family Enterococcaceae for first-ever IS with the attributable proportion due to the interaction was 0.74, 0.71, and 0.85, respectively; and the synergy index was 4.45, 3.78, and 7.01, respectively. This preliminary but promising study showed that the gut microbiota disturbances may potentially interact to IS with different ethnic host's traditional risk factors.

Liver zonation is fundamental to normal liver function, and numerous studies have investigated the microstructure of normal liver lobules. However, only a few studies have explored the zonation signature in hepatocellular carcinoma (HCC). In this study, we investigated the significance of liver zonation in HCC with the help of single-cell RNA sequencing (scRNA-seq) and multicolor immunofluorescence staining. Liver zonation-related genes were extracted from the literature, and a three-gene model was established for HCC prognosis. The model reliability was validated using bulk RNA and single-cell RNA-level data, and the underlying biological mechanism was revealed by a functional enrichment analysis. The results showed that the signaling pathways of high-risk groups were similar to those of perivenous zones in the normal liver, indicating the possible regulating role of hypoxia in HCC zonation. Furthermore, the co-staining results showed that the low-grade tumors lost their zonation features whereas the high-grade tumors lost the expression of zonation-related genes, which supported the results obtained from the sequencing data.

Liver cancer is the most frequent fatal malignancy. Furthermore, there is a lack of effective therapeutics for this cancer type. To construct a prognostic model for potential beneficiary screens and identify novel treatment targets, we used an adaptive daisy model (ADaM) to identify context-specific fitness genes from the CRISPR-Cas9 screens database, DepMap. Functional analysis and prognostic significance were assessed using data from TCGA and ICGC cohorts, while drug sensitivity analysis was performed using data from the Liver Cancer Model Repository (LIMORE). Finally, a 25-gene prognostic model was established. Patients were then divided into high- and low-risk groups; the high-risk group had a higher stemness index and shorter overall survival time than the low-risk group. The C-index, time-dependent ROC curves, and multivariate Cox regression analysis confirmed the excellent prognostic ability of this model. Functional enrichment analysis revealed the importance of metabolic rearrangements and serine/threonine kinase activity, which could be targeted by trametinib and is the key pathway in regulating liver cancer cell viability. In conclusion, the present study provides a prognostic model for patients with liver cancer and might help in the exploration of novel therapeutic targets to ultimately improve patient outcomes.

Due to the extra evaporation loss caused by the ortho-para hydrogen conversion (OPHC) during the storage and transportation of liquid hydrogen (LH 2), the initial concentration of ortho-hydrogen (o-H 2) plays an important role in the large-scale safe operation and utilization of LH 2. However, there are very limited studies focusing on clarifying the impact of the OPHC on thermal behaviors of LH 2 tanks. In light of this, this paper establishes and develops an extended thermal multi-zone model that couples the OPHC process with the mass and energy conservation equations of the ullage and liquid for an LH 2 tank. With the help of the model, a thermodynamic analysis of the pressurization rate is performed to obtain the dominant parameter that evaluates the effect of the initial o-H 2 concentration on the pressure build-up process. The results indicate that the interfacial mass transfer rate caused by the OPHC is the dominant parameter accounting for more than 90% of the effect of all parameters on the pressurization rate during a 10-day process with an initial liquid fill ratio of 90% and a heat leakage of 40 W. Additionally, the effect of the initial o-H 2 concentration on the optimal liquid fill ratio is discussed in this paper. The results indicate that when the initial o-H 2 concentration changes from 0.2% to 10%, the optimal liquid fill ratio decreases from 82.5% to 74%. The present work provides theoretical support and guidance for controlling the o-H 2 concentration to realize the long-term and high-efficiency storage of LH 2. • Modeling of transient ortho-para hydrogen conversion (OPHC) for LH 2 tanks. • Thermodynamic analysis coupled with OPHC on LH 2 storage is conducted. • Interfacial mass transfer by OPHC determines the pressure rise in LH 2 tanks. • Initial concentration of o-H 2 reduces the optimized liquid fill ratio of tanks. [ABSTRACT FROM AUTHOR]