Background The spider Trichonephila antipodiana (Araneidae), commonly known as the batik golden web spider, preys on arthropods with body sizes ranging from ∼2 mm in length to insects larger than itself (>20‒50 mm), indicating its polyphagy and strong dietary detoxification abilities. Although it has been reported that an ancient whole-genome duplication event occurred in spiders, lack of a high-quality genome has limited characterization of this event. Results We present a chromosome-level T. antipodiana genome constructed on the basis of PacBio and Hi-C sequencing. The assembled genome is 2.29 Gb in size with a scaffold N50 of 172.89 Mb. Hi-C scaffolding assigned 98.5% of the bases to 13 pseudo-chromosomes, and BUSCO completeness analysis revealed that the assembly included 94.8% of the complete arthropod universal single-copy orthologs (n = 1,066). Repetitive elements account for 59.21% of the genome. We predicted 19,001 protein-coding genes, of which 96.78% were supported by transcriptome-based evidence and 96.32% matched protein records in the UniProt database. The genome also shows substantial expansions in several detoxification-associated gene families, including cytochrome P450 mono-oxygenases, carboxyl/cholinesterases, glutathione-S-transferases, and ATP-binding cassette transporters, reflecting the possible genomic basis of polyphagy. Further analysis of the T. antipodiana genome architecture reveals an ancient whole-genome duplication event, based on 2 lines of evidence: (i) large-scale duplications from inter-chromosome synteny analysis and (ii) duplicated clusters of Hox genes. Conclusions The high-quality T. antipodiana genome represents a valuable resource for spider research and provides insights into this species’ adaptation to the environment.

Thin film CdS/CdTe heterojunction device is a leading technology for the solar cells of the next generation. We report on two novel device configurations for these cells where the traditional CdS window layer is replaced by nanowires (NW) of CdS, embedded in an aluminum oxide matrix or free-standing. An estimated 26.8% improvement in power conversion efficiency over the traditional device structure is expected, primarily because of the enhanced spectral transmission of sunlight through the NW-CdS layer and a reduction in the junction area/optical area ratio. In initial experiments, nanostructured devices of the two designs were fabricated and a power conversion efficiency value of 6.5% was achieved.

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Nanoporous anodic aluminum oxide (AAO) has been used widely as a template for device fabrication. In many nanostructured electro-optical device designs, AAO grown on an ITO substrate is the desired configuration. However, a residual thin aluminum oxide barrier layer between ITO and the AAO pores remains and process non-uniformities during the template fabrication can cause serious problems in the quality of nanowires deposited later in these pores. It was observed that in many templates, even the pores closest to each other could have their barrier layer thicknesses differ by as much as 10-20 nm. In this paper, causes and remedies for this non-uniformity are investigated, including the effects of a thin Ti interlayer inserted between the ITO and AAO. Templates with different Ti layer thickness and annealing conditions were compared. Mechanisms for the formation of voids beneath the barrier layer were analyzed and studied experimentally. Reactive ion etch (RIE) was found to be the preferred method to mitigate process non-uniformities. Using the above methods, barrier-free AAO templates on ITO substrates were obtained; their thicknesses ranged from 200 to 1000 nm. The characteristics of CdS nanowires electrodeposited into the initial templates with non-uniform barrier layer thicknesses and into the processed, barrier-free templates were compared.

Soil heavy metals affect human life and the environment, and thus, it is very necessary to monitor their contents. Substantial research has been conducted to estimate and map soil heavy metals in large areas using hyperspectral data and machine learning methods (such as neural network), however, lower estimation accuracy is often obtained. In order to improve the estimation accuracy, in this study, a back propagation neural network (BPNN) was combined with the particle swarm optimization (PSO), which led to an integrated PSO-BPNN method used to estimate the contents of soil heavy metals: Cd, Hg, and As. This study was conducted in Guangdong, China, based on the soil heavy metal contents and hyperspectral data collected from 90 soil samples. The prediction accuracies from BPNN and PSO-BPNN were compared using field observations. The results showed that, 1) the sample averages of Cd, Hg, and As were 0.174 mg/kg, 0.132 mg/kg, and 9.761 mg/kg, respectively, with the corresponding maximum values of 0.570 mg/kg, 0.310 mg/kg, and 68.600 mg/kg being higher than the environment baseline values; 2) the transformed and combined spectral variables had higher correlations with the contents of the soil heavy metals than the original spectral data; 3) PSO-BPNN significantly improved the estimation accuracy of the soil heavy metal contents, with the decrease in the mean relative error (MRE) and relative root mean square error (RRMSE) by 68% to 71%, and 64% to 67%, respectively. This indicated that the PSO-BPNN provided great potential to estimate the soil heavy metal contents; and 4) with the PSO-BPNN, the Cd content could also be mapped using HuanJing-1A Hyperspectral Imager (HSI) data with a RRMSE value of 36%, implying that the PSO-BPNN method could be utilized to map the heavy metal content in soil, using both field spectral data and hyperspectral imagery for the large area.