Anti-Solvent-Free Fabrication of Stable FA0.9Cs0.1PbI3 Perovskite Solar Cells with Efficiency Exceeding 24.0% through a Naphthalene-Based Passivator.

The anti-solvent-free fabrication of high-efficiency perovskite solar cells (PSCs) holds immense significance for the transition from laboratory-scale to large-scale commercial applications. However, the device performance is severely hindered by the increased occurrence of surface defects resulting from the lack of control over nucleation and crystallization of perovskite using anti-solvent methods. In this study, 2-(naphthalen-2-yl)ethylamine hydriodide (NEAI) is employed as the surface passivator for perovskite films without using any anti-solvent. Naphthalene demonstrates strong π-π conjugation, which aids in the efficient extraction of charge carriers. Additionally, the naphthalene-ring moieties form a tight attachment to the perovskite surface. After NEAI treatment, FA and I vacancies are selectively occupied by NEA+ and I- in NEAI respectively, thus effectively passivating the surface defects and isolating the surface from moisture. Ultimately, the optimized NEAI-treated device achieves a promising power conversion efficiency (PCE) of 24.19% (with a certified efficiency of 23.94%), featuring a high fill factor of 83.53%. It stands out as one of the reported high PCEs achieved for PSCs using the spin-coating technique without the need for any anti-solvent so far. Furthermore, the NEAI-treated device can maintain ≈87% of its initial PCE after 2000 h in ambient air with a relative humidity of 30% ± 5%.

Pencil-like Hollow Carbon Nanotubes Embedded CoP-V4P3 Heterostructures as a Bifunctional Catalyst for Electrocatalytic Overall Water Splitting.

Electrocatalytic water splitting is one of the most efficient ways of producing green hydrogen energy. The design of stable, active, and efficient electrocatalysts plays a crucial role in water splitting for achieving efficient energy conversion from electrical to hydrogen energy, aimed at solving the lingering energy crisis. In this work, CNT composites modified with CoP-V4P3 composites (CoVO-10-CNT-450P) were formed by carbonising a pencil-like precursor (Co3V2O8-H2O) and growing carbon nanotubes in situ, followed by in situ phosphorylation on the carbon nanotubes. In the HER electrocatalytic process, an overpotential of only 124 mV was exhibited at a current density of 10 mA cm-2. In addition, as an OER catalyst, a low overpotential of 280 mV was attained at a current density of 10 mA cm-2. Moreover, there was no noticeable change in the performance of the catalyst over a 90 h test in a continuous total water splitting experiment. The unique electronic structure and hollow carbon nanotube structure of CoVO-10-CNT-450P effectively increased the catalytic active sites, while also significantly improving the electrocatalytic activity. This work provides theoretical guidance for the design and synthetic route of high-performance non-precious metal electrocatalysts, and actively promotes the commercial application of electrochemical water splitting.

PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples.

Over the last decade, RNA-seq has produced a massive amount of plant transcriptomic sequencing data deposited in public databases. Reanalysis of these public datasets can generate additional novel hypotheses not included in original studies. However, the large data volume and the requirement for specialized computational resources and expertise present a barrier for experimental biologists to explore public repositories. Here, we introduce PlantExp (https://biotec.njau.edu.cn/plantExp), a database platform for exploration of plant gene expression and alternative splicing profiles based on 131 423 uniformly processed publicly available RNA-seq samples from 85 species in 24 plant orders. In addition to two common retrieval accesses to gene expression and alternative splicing profiles by functional terms and sequence similarity, PlantExp is equipped with four online analysis tools, including differential expression analysis, specific expression analysis, co-expression network analysis and cross-species expression conservation analysis. With these online analysis tools, users can flexibly customize sample groups to reanalyze public RNA-seq datasets and obtain new insights. Furthermore, it offers a wide range of visualization tools to help users intuitively understand analysis results. In conclusion, PlantExp provides a valuable data resource and analysis platform for plant biologists to utilize public RNA-seq. datasets.

Equivalent orthotropic model for corrugated plates based on simplified constitutive relation.

The transverse bending stiffness of a corrugated plate determined using an equivalent orthotropic model based on the Dirichlet boundary conditions and representative volume element method is the upper limit of the real solution, albeit often inaccurate in practice. Based on the Kirchhoff hypothesis, the constitutive relations of corrugated plates were reasonably simplified to propose a new corrugated plate equivalent orthotropic model. The resulting equivalent transverse bending stiffness agreed with the results of the most reasonable simplified expression available. Static response results obtained using the proposed model were more accurate than those obtained using the existing model without a simplified constitutive relation. Furthermore, for dynamic response, the proposed model exhibited improved accuracy when predicting low- and high-order natural frequencies. For the arc-and-tangent corrugated plate, two integral parameter expressions were calculated; the proposed equivalent plate model was verified by comparing the results of a full-scale test of the corrugated metal pipe arch culvert.

A web-based database server using 43,710 public RNA-seq samples for the analysis of gene expression and alternative splicing in livestock animals.

BACKGROUND: Livestock animals is of great significance in agricultural production. However, the role of specific gene expression, especially alternative splicing in determining phenotype, is not well understood. The livestock research community needs a gene expression and alternative splicing database contributing to livestock genetic improvement. DESCRIPTION: We report the construction of LivestockExp ( https://bioinfo.njau.edu.cn/livestockExp ), a web-based database server for the exploration of gene expression and alternative splicing using 43,710 uniformly processed RNA-seq samples from livestock animals and several relative species across six orders. The database is equipped with basic querying functions and multiple online analysis modules including differential/specific expression analysis, co-expression network analysis, and cross-species gene expression conservation analysis. In addition to the re-analysis of public datasets, users can upload personal datasets to perform co-analysis with public datasets. The database also offers a wide range of visualization tools and diverse links to external databases enabling users to efficiently explore the results and to gain additional insights. CONCLUSION: LivestockExp covers by far the largest number of livestock animal species and RNA-seq samples and provides a valuable data resource and analysis platform for the convenient utilization of public RNA-seq datasets.

A novel composite anode via immobilizing of Ce-doped PbO2 on CoTiO3 for efficiently electrocatalytic degradation of dye.

The exploitation of efficient electrocatalyst is significantly important for degradation of refractory organic pollutants. Herein, a novel Ti/CoTiO3/Ce-PbO2 composite electrocatalyst (abbreviated as CTO/CP) is successfully constructed via facile consecutive immersion pyrolysis and electro-deposition method and then systematically characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Fourier Transform infrared spectroscopy (FT-IR), energy dispersive spectroscopy (EDS) and near infrared chemical imaging (NIR-CI). Importantly, the electrochemical measurements demonstrate that the CTO/CP possesses numerous prominent properties such as lower charge transfer resistance, larger electroactive area, higher oxygen evolution potential than those of the pristine Ti/CoTiO3 (CTO) and Ti/Ce-PbO2 (CP). Thereby, the CTO/CP exhibits an enhanced electrocatalytic degradation performance with the degradation efficiency as high as 90.0% and COD removal rate of 88.3% at 180 min for the optimal CTO/CP (denoted as 10 layers of CTO and 1 h electrodeposition of CP), in which the ·OH is the major reactive species. Additionally, the optimal CTO/CP also shows a higher ICE/ACE together with lower EEC and desirable stability, universal applicability for many different dyes and reusability. Overall, this work offers a promising approach for enhancing the electrocatalytic properties of CTO via introducing CP.

MetazExp: a database for gene expression and alternative splicing profiles and their analyses based on 53 615 public RNA-seq samples in 72 metazoan species.

RNA-seq has been widely used in experimental studies and produced a massive amount of data deposited in public databases. New biological insights can be obtained by retrospective analyses of previously published data. However, the barrier to efficiently utilize these data remains high, especially for those who lack bioinformatics skills and computational resources. We present MetazExp (https://bioinfo.njau.edu.cn/metazExp), a database for gene expression and alternative splicing profiles based on 53 615 uniformly processed publicly available RNA-seq samples from 72 metazoan species. The gene expression and alternative splicing profiles can be conveniently queried by gene IDs, symbols, functional terms and sequence similarity. Users can flexibly customize experimental groups to perform differential and specific expression and alternative splicing analyses. A suite of data visualization tools and comprehensive links with external databases allow users to efficiently explore the results and gain insights. In conclusion, MetazExp is a valuable resource for the research community to efficiently utilize the vast public RNA-seq datasets.

Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species.

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA's biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

High Performance Tandem Solar Cells with Inorganic Perovskite and Organic Conjugated Molecules to Realize Complementary Absorption.

All-inorganic halide perovskite solar cells (PerSCs) have achieved rapid development in recent years. However, limited by narrow absorption bands, the power conversion efficiency (PCE) of all-inorganic halide PerSCs lag behind the organic-inorganic hybrid ones. In this contribution, to expand their absorption spectra and enhance the PCE, tandem solar cells (TSCs) with inorganic perovskite and organic conjugated molecules are constructed, utilizing CsPbI2Br as an ultraviolet-visible light absorber and a PTB7-Th:IEICO-4F bulk-heterojunction (BHJ) active layer as a near-infrared light absorber. To physically and electronically connect the front and rear subcells, P3HT/MoO3/Ag/PFN-Br is introduced as an interconnecting junction. Finally, the TSCs exhibit a remarkably higher PCE of 17.24% compared to that of the single junction PerSCs (12.09%) and organic solar cells (OSCs) (10.89%). These results indicate that the combination of all-inorganic perovskite and a low bandgap organic active layer for TSCs is a feasible approach to realize broad spectra utilization and efficiency enhancement.

SOMM4mC: a second-order Markov model for DNA N4-methylcytosine site prediction in six species.

MOTIVATION: DNA N4-methylcytosine (4mC) modification is an important epigenetic modification in prokaryotic DNA due to its role in regulating DNA replication and protecting the host DNA against degradation. An efficient algorithm to identify 4mC sites is needed for downstream analyses. RESULTS: In this study, we propose a new prediction method named SOMM4mC based on a second-order Markov model, which makes use of the transition probability between adjacent nucleotides to identify 4mC sites. The results show that the first-order and second-order Markov model are superior to the three existing algorithms in all six species (Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Escherichia coli, Geoalkalibacter subterruneus and Geobacter pickeringii) where benchmark datasets are available. However, the classification performance of SOMM4mC is more outstanding than that of first-order Markov model. Especially, for E.coli and C.elegans, the overall accuracy of SOMM4mC are 91.8% and 87.6%, which are 8.5% and 6.1% higher than those of the latest method 4mcPred-SVM, respectively. This shows that more discriminant sequence information is captured by SOMM4mC through the dependency between adjacent nucleotides. AVAILABILITY AND IMPLEMENTATION: The web server of SOMM4mC is freely accessible at www.insect-genome.com/SOMM4mC. CONTACT: chenyuanyuan@njau.edu.cn or piancong@njau.edu.cn.

Facile synthesis of N, P-doped carbon dots from maize starch via a solvothermal approach for the highly sensitive detection of Fe3.

Nitrogen/phosphorus-doped carbon dots (N, P-CDs) with a quantum yield as high as 76.5% were synthesized by carbonizing maize starch via a facile ethanol solvothermal approach. Transmission electron microscopy (TEM) measurement shows that the as-prepared N, P-CDs displayed a quasi-spherical shape with a mean size of ca. 2.5 nm. Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy disclosed the presence of -OH, -NH2, -COOH, and -CO functional groups over the surface of N, P-CDs. On the basis of excellent fluorescent properties with strong blue fluorescence emission at 445 nm upon excitation at 340 nm, these N, P-CDs were adopted as a fluorescent probe towards the effective detection of Fe3+ ions in water. The limit of detection (LOD) was as low as 0.1 µmol L-1 and showed a better linear relationship in the range of 0.1 ∼ 50 µmol L-1. In conclusion, these synthesized N, P-CDs can be efficiently used as a promising candidate for the detection of Fe3+ ions in some practical samples.

FastD: Fast detection of insecticide target-site mutations and overexpressed detoxification genes in insect populations from RNA-Seq data.

Target-site mutations and detoxification gene overexpression are two major mechanisms conferring insecticide resistance. Molecular assays applied to detect these resistance genetic markers are time-consuming and with high false-positive rates. RNA-Seq data contains information on the variations within expressed genomic regions and expression of detoxification genes. However, there is no corresponding method to detect resistance markers at present. Here, we collected 66 reported resistance mutations of four insecticide targets (AChE, VGSC, RyR, and nAChR) from 82 insect species. Next, we obtained 403 sequences of the four target genes and 12,665 sequences of three kinds of detoxification genes including P450s, GSTs, and CCEs. Then, we developed a Perl program, FastD, to detect target-site mutations and overexpressed detoxification genes from RNA-Seq data and constructed a web server for FastD (http://www.insect-genome.com/fastd). The estimation of FastD on simulated RNA-Seq data showed high sensitivity and specificity. We applied FastD to detect resistant markers in 15 populations of six insects, Plutella xylostella, Aphis gossypii, Anopheles arabiensis, Musca domestica, Leptinotarsa decemlineata and Apis mellifera. Results showed that 11 RyR mutations in P. xylostella, one nAChR mutation in A. gossypii, one VGSC mutation in A. arabiensis and five VGSC mutations in M. domestica were found to be with frequency difference >40% between resistant and susceptible populations including previously confirmed mutations G4946E in RyR, R81T in nAChR and L1014F in VGSC. And 49 detoxification genes were found to be overexpressed in resistant populations compared with susceptible populations including previously confirmed detoxification genes CYP6BG1, CYP6CY22, CYP6CY13, CYP6P3, CYP6M2, CYP6P4 and CYP4G16. The candidate target-site mutations and detoxification genes were worth further validation. Resistance estimates according to confirmed markers were consistent with population phenotypes, confirming the reliability of this program in predicting population resistance at omics-level.

Expanding the Light Harvesting of CsPbI2Br to Near Infrared by Integrating with Organic Bulk Heterojunction for Efficient and Stable Solar Cells.

All-inorganic perovskite (CsPbX3, X = Br or I) solar cells demonstrate superior stability, while the power conversion efficiency (PCE) lags behind the organic-inorganic hybrid counterparts mainly due to the limitation of narrow absorption bands. To broaden their absorption spectrum and improve their PCE, all-inorganic perovskite/organic integrated solar cells utilizing CsPbI2Br as an ultraviolet-visible light absorber and PBDTTT-E-T:IEICO as a near-infrared light absorber are demonstrated in this work. The integrated solar cells exhibit a broadened photoresponse to over 900 nm, attributed to the integration of PBDTTT-E-T:IEICO. The additional absorption enhances the short-circuit current density from 14.78 to 15.98 mA/cm2, resulting in greatly improved PCE of 14.03% for integrated solar cells, much higher than that of the control perovskite solar cells (12.53%) and organic solar cells (7.51%). An in-depth understanding of the charge-transfer dynamic process in the CsPbI2Br/PBDTTT-E-T:IEICO film is comprehensively analyzed by photoinduced transient absorption spectroscopy. Furthermore, the air stability and thermal stability of the integrated solar cells are greatly enhanced. For unencapsulated integrated solar cells, the PCE still preserves 95% of its initial value after aging for 300 h in an ambient environment and retains about 90% of its original value even after aging at 85 °C for 180 h in nitrogen.

Integrated Satellite, Unmanned Aerial Vehicle (UAV) and Ground Inversion of the SPAD of Winter Wheat in the Reviving Stage.

Chlorophyll is the most important component of crop photosynthesis, and the reviving stage is an important period during the rapid growth of winter wheat. Therefore, rapid and precise monitoring of chlorophyll content in winter wheat during the reviving stage is of great significance. The satellite-UAV-ground integrated inversion method is an innovative solution. In this study, the core region of the Yellow River Delta (YRD) is used as a study area. Ground measurements data, UAV multispectral and Sentinel-2A multispectral imagery are used as data sources. First, representative plots in the Hekou District were selected as the core test area, and 140 ground sampling points were selected. Based on the measured SPAD values and UAV multispectral images, UAV-based SPAD inversion models were constructed, and the most accurate model was selected. Second, by comparing satellite and UAV imagery, a reflectance correction for satellite imagery was performed. Finally, based on the UAV-based inversion model and satellite imagery after reflectance correction, the inversion results for SPAD values in multi-scale were obtained. The results showed that green, red, red-edge and near-infrared bands were significantly correlated with SPAD values. The modeling precisions of the best inversion model are R² = 0.926, Root Mean Squared Error (RMSE) = 0.63 and Mean Absolute Error (MAE) = 0.92, and the verification precisions are R² = 0.934, RMSE = 0.78 and MAE = 0.87. The Sentinel-2A imagery after the reflectance correction has a pronounced inversion effect; the SPAD values in the study area were concentrated between 40 and 60, showing an increasing trend from the eastern coast to the southwest and west, with obvious spatial differences. This study synthesizes the advantages of satellite, UAV and ground methods, and the proposed satellite-UAV-ground integrated inversion method has important implications for real-time, rapid and precision SPAD values collected on multiple scales.

FairBase: a comprehensive database of fungal A-to-I RNA editing.

Frequent A-to-I RNA editing has recently been identified in fungi despite the absence of recognizable homologues of metazoan ADARs ("Adenosine Deaminases Acting on RNA"). In particular, there is emerging evidence showing that A-to-I editing is involved in sexual reproduction of filamentous fungi. Here, we report on the creation of FairBase - a fungal A-to-I RNA editing database that provides a platform for deep exploration of fungal RNA editing to relevant academic communities. This database includes a comprehensive collection of A-to-I editing sites in six filamentous fungal species, together with extensive annotations for each editing site. In FairBase, users can conveniently search editing sites and obtain editing levels for each editing site in various RNA-seq samples. In addition, the pathways involving RNA editing are built in FairBase to help users understand the functions of RNA editing. Furthermore, each fungal species has a genome browser (JBrowse) that allows users to explore A-to-I editing in a genomic context. FairBase is the first fungal RNA editing database.

WaspBase: a genomic resource for the interactions among parasitic wasps, insect hosts and plants.

Insect pests reduce yield and cause economic losses, which are major problems in agriculture. Parasitic wasps are the natural enemies of many agricultural pests and thus have been widely used as biological control agents. Plants, phytophagous insects and parasitic wasps form a tritrophic food chain. Understanding the interactions in this tritrophic system should be helpful for developing parasitic wasps for pest control and deciphering the mechanisms of parasitism. However, the genomic resources for this tritrophic system are not well organized. Here, we describe the WaspBase, a new database that contains 573 transcriptomes of 35 parasitic wasps and the genomes of 12 parasitic wasps, 5 insect hosts and 8 plants. In addition, we identified long non-coding RNA, untranslated regions and 25 widely studied gene families from the genome and transcriptome data of these species. WaspBase provides conventional web services such as Basic Local Alignment Search Tool, search and download, together with several widely used tools such as profile hidden Markov model, Multiple Alignment using Fast Fourier Transform, automated alignment trimming and JBrowse. We also present a collection of active researchers in the field of parasitic wasps, which should be useful for constructing scientific networks in this field.

The genomic features of parasitism, Polyembryony and immune evasion in the endoparasitic wasp Macrocentrus cingulum.

BACKGROUND: Parasitoid wasps are well-known natural enemies of major agricultural pests and arthropod borne diseases. The parasitoid wasp Macrocentrus cingulum (Hymenoptera: Braconidae) has been widely used to control the notorious insect pests Ostrinia furnacalis (Asian Corn Borer) and O. nubilalis (European corn borer). One striking phenomenon exhibited by M. cingulum is polyembryony, the formation of multiple genetically identical offspring from a single zygote. Moreover, M. cingulum employs a passive parasitic strategy by preventing the host's immune system from recognizing the embryo as a foreign body. Thus, the embryos evade the host's immune system and are not encapsulated by host hemocytes. Unfortunately, the mechanism of both polyembryony and immune evasion remains largely unknown. RESULTS: We report the genome of the parasitoid wasp M. cingulum. Comparative genomics analysis of M. cingulum and other 11 insects were conducted, finding some gene families with apparent expansion or contraction which might be linked to the parasitic behaviors or polyembryony of M. cingulum. Moreover, we present the evidence that the microRNA miR-14b regulates the polyembryonic development of M. cingulum by targeting the c-Myc Promoter-binding Protein 1 (MBP-1), histone-lysine N-methyltransferase 2E (KMT2E) and segmentation protein Runt. In addition, Hemomucin, an O-glycosylated transmembrane protein, protects the endoparasitoid wasp larvae from being encapsulated by host hemocytes. Motif and domain analysis showed that only the hemomucin in two endoparasitoids, M. cingulum and Venturia canescens, possessing the ability of passive immune evasion has intact mucin domain and similar O-glycosylation patterns, indicating that the hemomucin is a key factor modulating the immune evasion. CONCLUSIONS: The microRNA miR-14b participates in the regulation of polyembryonic development, and the O-glycosylation of the mucin domain in the hemomucin confers the passive immune evasion in this wasp. These key findings provide new insights into the polyembryony and immune evasion.

Linking potential heat source and sink to urban heat island: Heterogeneous effects of landscape pattern on land surface temperature.

Rapid urbanization has significantly contributed to the development of urban heat island (UHI). Regulating landscape composition and configuration would help mitigate the UHI in megacities. Taking Shenzhen, China, as a case study area, we defined heat source and heat sink and identified strong and weak sources as well as strong and weak sinks according to the natural and socioeconomic factors influencing land surface temperature (LST). Thus, the potential thermal contributions of heat source and heat sink patches were differentiated. Then, the heterogeneous effects of landscape pattern on LST were examined by using semiparametric geographically weighted regression (SGWR) models. The results showed that landscape composition has more significant effects on thermal environment than configuration. For a strong source, the percentage of patches has a positive impact on LST. Additionally, when mosaicked with some heat sink, even a small improvement in the degree of dispersion of a strong source helps to alleviate UHI. For a weak source, the percentage and density of patches have positive impacts on LST. For a strong sink, the percentage, density, and degree of aggregation of patches have negative impacts on LST. The effects of edge density and patch shape complexity vary spatially with the fragmentation of a strong sink. Similarly, the impacts of a weak sink are mainly exerted via the characteristics of percent, density, and shape complexity of patches.

Improved Neural Networks with Random Weights for Short-Term Load Forecasting.

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting.