Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Based on data on the shear wave speed and physical properties of the shallow sediment samples collected in the northwest South China Sea, the hyperparameter selection and contribution of the characteristic factors of the machine learning model for predicting the shear wave speed of seafloor sediments were studied using the eXtreme Gradient Boosting (XGBoost) algorithm. An XGBoost model for predicting the shear wave speed of seafloor sediments was established based on four physical parameters of the sediments: porosity (n), water content (w), density (ρ), and average grain size (MZ). The result reveals that: (1) The shear wave speed has a good correlation with n, w, ρ, and MZ, and their Pearson correlation coefficients are all above 0.75, indicating that they can be used as the suitable characteristic parameters for predicting the shear wave speed based on the XGBoost model; (2) When the number of weak learners (n_estimators) is 115 and the maximum depth of the tree (max_depth) is 6, the XGBoost model has a very high goodness of fit (R2) of the validation data of 0.914, the very low mean absolute error (MAE) and mean absolute percentage error (MAPE) of the predicted shear wave speed are 3.366 m/s and 9.90%, respectively; (3) Compared with grain-shearing (GS) model and single- and dual-parameter regression equation prediction models, the XGBoost model for the shear wave speed of seafloor sediments has higher fitting goodness and lower prediction error

Effects of Fluorination on Fused Ring Electron Acceptor for Active Layer Morphology, Exciton Dissociation, and Charge Recombination in Organic Solar Cells

Fluorination is one of the effective approaches to alter the organic semiconductor properties that impact the performance of the organic solar cells (OSCs). Positive effects of fluorination are also revealed in the application of fused ring electron acceptors (FREAs). However, in comparison with the efforts allocated to the material designs and power conversion efficiency enhancement, understanding on the excitons and charge carriers' behaviors in high-performing OSCs containing FREAs is limited. Herein, the impact of fluorine substituents on the active layer morphology, and therefore exciton dissociation, charge separation, and charge carriers' recombination processes are examined by fabricating OSCs with PTO2 as the donor and two FREAs, O-IDTT-IC and its fluorinated analogue O-IDTT-4FIC, as the acceptors. With the presence of O-IDTT-4FIC in the devices, it is found that the excitons dissociate more efficiently, and the activation energy required to split the excitons to free charge carriers is much lower; the charge carriers live longer and suffer less extent of trap-assisted recombination; the trap density is 1 order of magnitude lower than that of the nonfluorinated counterpart. Overall, these findings provide information about the complex impacts of FREA fluorination on efficiently performed OSCs

A Random Forest Model for Daily PM2.5 Personal Exposure Assessment for a Chinese Cohort

Errors in air pollution exposure assessment are often considered as a major limitation in epidemiological studies. However, it is difficult to obtain accurate personal level exposure on cohort populations due to the often prohibitive expense. Personal exposure estimation models are used in lieu of direct personal exposure measures but still suffer from issues of availability and accuracy. We aim to establish a personal PM2.5 exposure assessment model for a cohort population and assess its performance by applying our model on cohort subjects. We analyzed data from representative sites selected from the subclinical outcomes of polluted air in China (SCOPA-China) cohort study and established a random forest model for estimating daily PM2.5 personal exposure. We also applied the model among subjects recruited in the project mentioned above within the same area and study period to estimate the reliability of the model. The established model showed a good fit with an R2 of 0.81. The model application results showed similar patterns with empirically measured data. Our pilot study provided a validated and feasible modeling approach for assessing daily personal PM2.5 exposure for large cohort populations. The promising model framework can improve PM2.5 exposure assessment accuracy for future environmental health studies of large populations

Dual Encapsulation of Electron Transporting Materials To Simplify High-Efficiency Blue Thermally Activated Delayed Fluorescence Devices

The charge flux balance and interfacial optimization are two core concerns when simplifying blue thermally activated delayed fluorescence (TADF) diodes, which reflects the more stringent demand on carrier transporting materials (CTM) as the embodiment of the contradiction between charge transportation and quenching suppression with the opposite requirement on intermolecular interactions. Herein, phenylbenzimidazole (<b>PBI</b>) was used as the core substituted with two diphenylphosphine oxide (DPPO) groups to form six dual-encapsulated charge–exciton separation (CES)-type electron transporting materials (ETM) with the collective name of <b><i>xy</i>PBIDPO</b>. Through tuning the substitution positions of DPPO group, its two functions of resonance and steric effects were integrated and optimized to enhance charged moiety encapsulation without cost of reducing electroactivity. As the result, among <b><i>xy</i>PBIDPO</b>, <b><i>mm</i>PBIDPO</b> successfully realizes the balance of favorable electrical performance and interfacial interaction suppressions in virtue of its doubled <i>mesa</i>-substitution structure and roughly symmetrical configuration, rendering the good electron affinity of 2.8 eV, the high electron mobility by the level of 10^–6 cm² V^–1 s^–1 and effective <b>PBI</b>-core encapsulation. Consequently, <i><b>mm</b></i><b>PBIDPO</b> was used to extremely simplify the blue TADF devices with the state-of-the-art performance from trilayer and quadruple-layer configurations, such as the maximum external quantum efficiency (EQE) beyond 20% and improved efficiency stability. This work not only established a solid example of CES-type ETM for high-performance simple structured blue TADF devices but also provided the direction of developing this kind of materials in the future

Transcriptome sequencing of the naked mole rat (Heterocephalus glaber) and identification of hypoxia tolerance genes

The naked mole rat (NMR; Heterocephalus glaber) is a small rodent species found in regions of Kenya, Ethiopia and Somalia. It has a high tolerance for hypoxia and is thus considered one of the most important natural models for studying hypoxia tolerance mechanisms. The various mechanisms underlying the NMR's hypoxia tolerance are beginning to be understood at different levels of organization, and next-generation sequencing methods promise to expand this understanding to the level of gene expression. In this study, we examined the sequence and transcript abundance data of the muscle transcriptome of NMRs exposed to hypoxia using the Illumina HiSeq 2500 system to clarify the possible genomic adaptive responses to the hypoxic underground surroundings. The RNA-seq raw FastQ data were mapped against the NMR genome. We identified 2337 differentially expressed genes (DEGs) by comparison of the hypoxic and control groups. Functional annotation of the DEGs by gene ontology (GO) analysis revealed enrichment of hypoxia stress-related GO categories, including ‘biological regulation’, ‘cellular process’, ‘ion transport’ and ‘cell-cell signaling’. Enrichment of DEGs in signaling pathways was analyzed against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to identify possible interactions between DEGs. The results revealed significant enrichment of DEGs in focal adhesion, the mitogen-activated protein kinase (MAPK) signaling pathway and the glycine, serine and threonine metabolism pathway. Furthermore, inhibition of DEGs (STMN1, MAPK8IP1 and MAPK10) expression induced apoptosis and arrested cell growth in NMR fibroblasts following hypoxia. Thus, this global transcriptome analysis of NMRs can provide an important genetic resource for the study of hypoxia tolerance in mammals. Furthermore, the identified DEGs may provide important molecular targets for biomedical research into therapeutic strategies for stroke and cardiovascular diseases