Segregation by Race in Public Schools Retrospect and Prospect

Solar energy conversion has been intensively studied in past decades and has been shown to be greatly effective for solving the serious environmental pollution and energy shortage problems. Photoelectrocatalysis and photovoltaics have been considered as the two main approaches for solar energy conversion and utilization, which are generally involved with nanostructured materials and/or catalytic processes, greatly affecting the efficiencies for solar energy conversion. Then, it is necessary to understand the relationship between the physical and chemical properties of nanomaterials and their performances for solar energy conversion. It is also important to explore the fundamentals in catalytic processes for solar energy conversion and make breakthrough in design and synthesis of nanomaterials or nanostructures, characterization of material properties, and performance of novel devices and systems. The aim of this special issue is to present some recent progress in the field of advanced catalysis and nanostructure design for solar energy conversion. A brief summary of all accepted papers is provided below

Wheel and Star-critical Ramsey Numbers for Quadrilateral

The star-critical Ramsey number r∗(H1, H2) is the smallest integer k such that every red/blue coloring of the edges of Kn − K1,n−k−1 contains either a red copy of H1 or a blue copy of H2, where n is the graph Ramsey number R(H1, H2). We study the cases of r∗(C4, Cn) and R(C4, Wn). In particular, we prove that r∗(C4, Cn) = 5 for all n \u3e 4, obtain a general characterization of Ramsey-critical (C4, Wn)-graphs, and establish the exact values of R(C4, Wn) for 9 cases of n between 18 and 44

A Correlation Information-based Spatiotemporal Network for Traffic Flow Forecasting

The technology of traffic flow forecasting plays an important role in intelligent transportation systems. Based on graph neural networks and attention mechanisms, most previous works utilize the transformer architecture to discover spatiotemporal dependencies and dynamic relationships. However, they have not considered correlation information among spatiotemporal sequences thoroughly. In this paper, based on the maximal information coefficient, we present two elaborate spatiotemporal representations, spatial correlation information (SCorr) and temporal correlation information (TCorr). Using SCorr, we propose a correlation information-based spatiotemporal network (CorrSTN) that includes a dynamic graph neural network component for integrating correlation information into spatial structure effectively and a multi-head attention component for modeling dynamic temporal dependencies accurately. Utilizing TCorr, we explore the correlation pattern among different periodic data to identify the most relevant data, and then design an efficient data selection scheme to further enhance model performance. The experimental results on the highway traffic flow (PEMS07 and PEMS08) and metro crowd flow (HZME inflow and outflow) datasets demonstrate that CorrSTN outperforms the state-of-the-art methods in terms of predictive performance. In particular, on the HZME (outflow) dataset, our model makes significant improvements compared with the ASTGNN model by 12.7%, 14.4% and 27.4% in the metrics of MAE, RMSE and MAPE, respectively.Comment: 19 pages, 13 figures, 5 table

Isolation and characterization of an Aux/IAA gene (LaIAA2) from Larix

The phytohormone auxin controls many aspects of plant development. Auxin/indole-3-acetic acid (Aux/IAA)  transcriptional factors are key regulators of auxin responses in plants. To investigate the effects of auxin on  gene expression during the rooting process of Larix cuttings, a subtractive cDNA library was constructed and  272 UniEST were obtained by using suppression subtractive hybridization (SSH). Based on a fragment of 272  UniEST, the full-length cDNA of LaIAA2, an Aux /IAA gene from Larix was isolated. Then, the response  expression of LaIAA2 to auxin was determined by treating with different sources and concentration of auxin and cycloheximide and the expression patterns of LaIAA2 were examined in different tissues. The results show  that LaIAA2 appears to be the first response gene of auxin and LaIAA2 gene was involved in the root  development and auxin signaling. The express pattern of LaIAA2 gene indicated that it might play a central role in root development, specially regulated lateral and adventitious root production.Key words: Aux/IAA gene family, auxin, LaIAA2, Lari

Biodiversity and activity of the gut microbiota across the life history of the insect herbivore Spodoptera littoralis

Microbes that live inside insects play critical roles in host nutrition, physiology, and behavior. Although Lepidoptera (butterflies and moths) are one of the most diverse insect taxa, their microbial symbionts are little-studied, particularly during metamorphosis. Here, using ribosomal tag pyrosequencing of DNA and RNA, we investigated biodiversity and activity of gut microbiotas across the holometabolous life cycle of Spodoptera littoralis, a notorious agricultural pest worldwide. Proteobacteria and Firmicutes dominate but undergo a structural “metamorphosis” in tandem with its host. Enterococcus, Pantoea and Citrobacter were abundant and active in early-instar, while Clostridia increased in late-instar. Interestingly, only enterococci persisted through metamorphosis. Female adults harbored high proportions of Enterococcus, Klebsiella and Pantoea, whereas males largely shifted to Klebsiella. Comparative functional analysis with PICRUSt indicated that early-instar larval microbiome was more enriched for genes involved in cell motility and carbohydrate metabolism, whereas in late-instar amino acid, cofactor and vitamin metabolism increased. Genes involved in energy and nucleotide metabolism were abundant in pupae. Female adult microbiome was enriched for genes relevant to energy metabolism, while an increase in the replication and repair pathway was observed in male. Understanding the metabolic activity of these herbivore-associated microbial symbionts may assist the development of novel pest-management strategies

Systematic computational identification of prognostic cytogenetic markers in neuroblastoma

Background: Neuroblastoma (NB) is the most common extracranial solid tumor found in children. The frequent gain/loss of many chromosome bands in tumor cells and absence of mutations found at diagnosis suggests that NB is a copy number-driven cancer. Despite the previous work, a systematic analysis that investigates the relationship between such frequent gain/loss of chromosome bands and patient prognosis has yet to be implemented. Methods: First, we analyzed two NB CNV datasets to select chromosomal bands with a high frequency of gain or loss. Second, we applied a computational approach to infer sample-specific CNVs for each chromosomal band selected in step 1 based on gene expression data. Third, we applied univariate Cox proportional hazards models to examine the association between the resulting inferred copy number values (iCNVs) and patient survival. Finally, we applied multivariate Cox proportional hazards models to select chromosomal bands that remained significantly associated with prognosis after adjusting for critical clinical variables, including age, stage, gender, and MYCN amplification status. Results: Here, we used a computational method to infer the copy number variations (CNVs) of sample-specific chromosome bands from NB patient gene expression profiles. The resulting inferred CNVs (iCNVs) were highly correlated with the experimentally determined CNVs, demonstrating CNVs can be accurately inferred from gene expression profiles. Using this iCNV metric, we identified 58 frequent gain/loss chromosome bands that were significantly associated with patient survival. Furthermore, we found that 7 chromosome bands were still significantly associated with patient survival even when clinical factors, such as MYCN status, were considered. Particularly, we found that the chromosome band chr11p14 has high potential as a novel candidate cytogenetic biomarker for clinical use. Conclusion: Our analysis resulted in a comprehensive list of prognostic chromosome bands supported by strong statistical evidence. In particular, the chr11p14 gain event provided additional prognostic value in addition to well-established clinical factors, including MYCN status, and thereby represents a novel candidate cytogenetic biomarker with high clinical potential. Additionally, this computational framework could be readily extended to other cancer types, such as leukemia