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Nuclear factor Y (NF-Y) gene family is an important transcription factor composed of three subfamilies of NF-YA , NF-YB and NF-YC , which is involved in plant growth, development and stress response. In this study, 63 tobacco NF-Y genes ( NtNF-Ys ) were identified in Nicotiana tabacum L., including 17 NtNF-YAs , 30 NtNF-YBs and 16 NtNF-YCs . Phylogenetic analysis revealed ten pairs of orthologues from tomato and tobacco and 25 pairs of paralogues from tobacco. The gene structure of NtNF-YAs exhibited similarities, whereas the gene structure of NtNF-YBs and NtNF-YCs displayed significant differences. The NtNF-Ys of the same subfamily exhibited a consistent distribution of motifs and protein 3D structure. The protein interaction network revealed that NtNF-YC12 and NtNF-YC5 exhibited the highest connectivity. Many cis-acting elements related to light, stress and hormone response were found in the promoter of NtNF-Ys . Transcriptome analysis showed that more than half of the NtNF-Y genes were expressed in all tissues, and NtNF-YB9/B14/B15/B16/B17/B29 were specifically expressed in roots. A total of 15, 12, 5, and 6 NtNF-Y genes were found to respond to cold, drought, salt, and alkali stresses, respectively. The results of this study will lay a foundation for further study of NF-Y genes in tobacco and other Solanaceae plants.

Current lake and reservoir water body extraction algorithms are confronted with two critical challenges: (1) design dependency on specific geographical features, leading to constrained cross-regional adaptability (e.g., the JRC Global Water Body Dataset achieves ~90% overall accuracy globally, while the ESA WorldCover 2020 reaches ~92% for water body classification, both showing degraded performance in complex karst terrains); (2) information loss due to cloud occlusion, compromising dynamic monitoring accuracy. To address these limitations, this study presents a multi-feature fusion and multi-level hierarchical extraction algorithm for lake and reservoir water bodies, leveraging the Google Earth Engine (GEE) cloud platform and Sentinel-2 multispectral imagery in the karst landscape of Bijie City. The proposed method integrates the Automated Water Extraction Index (AWEIsh) and Modified Normalized Difference Water Index (MNDWI) for initial water body extraction, followed by a comprehensive fusion of multi-source data—including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Red-Edge Index (NDREI), Sentinel-2 B8/B9 spectral bands, and Digital Elevation Model (DEM). This strategy hierarchically mitigates vegetation shadows, topographic shadows, and artificial feature non-water targets. A temporal flood frequency algorithm is employed to restore cloud-occluded water bodies, complemented by morphological filtering to exclude non-target water features (e.g., rivers and canals). Experimental validation using high-resolution reference data demonstrates that the algorithm achieves an overall extraction accuracy exceeding 96% in Bijie City, effectively suppressing dark object interference (e.g., false positives due to topographic and anthropogenic features) while preserving water body boundary integrity. Compared with single-index methods (e.g., MNDWI), this method reduces false positive rates caused by building shadows and terrain shadows by 15–20%, and improves the IoU (Intersection over Union) by 6–13% in typical karst sub-regions. This research provides a universal technical framework for large-scale dynamic monitoring of lakes and reservoirs, particularly addressing the challenges of regional adaptability and cloud compositing in karst environments.

Broken symmetries play a fundamental role in superconductivity and influence many of its properties in a profound way. Understanding these symmetry breaking states is essential to elucidate the various exotic quantum behaviors in non-trivial superconductors. Here, we report an experimental observation of spontaneous rotational symmetry breaking of superconductivity at the heterointerface of amorphous (a)-YAlO 3 /KTaO 3 (111) with a superconducting transition temperature of 1.86 K. Both the magnetoresistance and superconducting critical field in an in-plane field manifest striking twofold symmetric oscillations deep inside the superconducting state, whereas the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute this behavior to the mixed-parity superconducting state, which is an admixture of s -wave and p -wave pairing components induced by strong spin-orbit coupling inherent to inversion symmetry breaking at the heterointerface of a-YAlO 3 /KTaO 3 . Our work suggests an unconventional nature of the underlying pairing interaction in the KTaO 3 heterointerface superconductors, and brings a new broad of perspective on understanding non-trivial superconducting properties at the artificial heterointerfaces. Superconducting interfaces involving KTaO3 have recently attracted attention due to their relatively high transition temperature. Here, the authors study amorphous-YAlO 3 /KTaO 3 interfaces and find two-fold symmetry in the superconducting regime, possibly due to a mixed-parity superconducting state.

X-ray spectrometers based on superconducting transition edge sensors (TESs) are promising in the spectroscopy research. For several X-ray light source facilities in Shanghai, deployment of TES-based spectrometers is proposed. This paper introduces the work on data processing for a TES-based X-ray spectrometer prototype developed at ShanghaiTech University. A data acquisition software is designed and programmed for multi-pixel data recording. The signal analysis method is optimized to best realize the performance of the prototype. We have achieved 12-channel simultaneous data acquisition and better than 9 eV resolution in the range from 2 to 9 keV for 11 TES pixels.

Tobacco is one of the most important model plants. Plant height is one of the most important agronomic traits in tobacco. To better understand the population genetic structure and the genetic basis of plant height in tobacco, 437 tobacco germplasms were whole genome re-sequencing in this study. A total of 2,263,775 high-quality single nucleotide polymorphisms were identified. The analysis of the population genetic structure showed that tobacco germplasm could be divided into 8 clusters. In addition, gene flow was found between flue-cured tobacco and ustic tobacco, as well as between oriental tobacco and air-cured tobacco. Three genes associated with plant height were identified as candidate genes by genome-wide association study. This study provides valuable genetic resources for population structure analysis and elucidation of the genetic basis of various traits. It helps to improve the efficiency of molecular breeding.

Optical sensors with in-cell logic and memory capabilities offer new horizons in realizing machine vision beyond von Neumann architectures and have been attempted with two-dimensional materials, memristive oxides, phase-changing materials etc. Noting the unparalleled performance of superconductors with both quantum-limited optical sensitivities and ultra-wide spectrum coverage, here we report a superconducting memlogic long-wave infrared sensor based on the bistability in hysteretic superconductor-normal phase transition. Driven cooperatively by electrical and optical pulses, the device offers deterministic in-sensor switching between resistive and superconducting (hence dissipationless) states with persistence > 105 s. This results in a resilient reconfigurable memlogic system applicable for, e.g., encrypted communications. Besides, a high infrared sensitivity at 12.2 μm is achieved through its in-situ metamaterial perfect absorber design. Our work opens the avenue to realize all-in-one superconducting memlogic sensors, surpassing biological retina capabilities in both sensitivity and wavelength, and presents a groundbreaking opportunity to integrate visional perception capabilities into superconductor-based intelligent quantum machines.We demonstrate a novel superconducting LWIR sensor integrating the function of infrared sensitivity, memory and reconfigurable logic computing.

We present a two-step technique for the synthesis of superconducting Cu x Bi 2 Se 3 . Cu 0.15 Bi 2 Se 3 single crystals were synthesized using the melt-growth method. Although these samples are non-superconducting, they can be employed to generate high quality superconducting samples if used as precursors in the following electrochemical synthesis step. Samples made from Cu 0.15 Bi 2 Se 3 reliably exhibit zero-resistance even under the non-optimal quenching condition, while samples made from pristine Bi 2 Se 3 require fine tuning of the quenching conditions to achieve similar performance. Moreover, under the optimal quenching condition, the average superconducting shielding fraction was still lower in the samples made from pristine Bi 2 Se 3 than in the samples made from Cu 0.15 Bi 2 Se 3 . These results suggest that the pre-doped Cu atoms facilitate the formation of a superconducting percolation network. We also discuss the useful clues that we gathered about the locations of Cu dopants that are responsible for superconductivity.

Here, we systematically analyzed the potential fusion and fission events of neighboring genes in Arabidopsis genome and analyzed the influence on the protein targeting.KEY MESSAGEHere, we systematically analyzed the potential fusion and fission events of neighboring genes in Arabidopsis genome and analyzed the influence on the protein targeting.

Stable electric load forecasting plays a significant role in power system operation and grid management. Improving the accuracy of electric load forecasting is not only a hot topic for energy managers and researchers of the power system, but also a fair challenging and difficult task due to its complex nonlinearity characteristics. This paper proposes a new combination model, which uses the least squares support vector machine, extreme learning machine, and generalized regression neural network to predict the electric load in New South Wales, Australia. In addition, the model employs a heuristic algorithm–whale optimization algorithm to optimize the weight coefficient. To verify the usability and generalization ability of the model, this paper also applies the proposed combined model to electricity price forecasting and compares it with the benchmark method. The experimental results demonstrate that the combined model not only can get accurate results for short-term electric load forecasting, but also achieves fine accuracy for the same period of electricity price forecasting.

Background: Modern pharmacological studies have shown that traditional Chinese medicine (TCM) Taraxacum mongolicum possesses anti-cancer activity. Taraxerol (TRX) is a pentacyclic triterpene isolated from T. mongolicum, which is widely used in clinical treatment, and its anti-cancer effects have been extensively studied. However, the effects and molecular mechanism of TRX in gastric cancer (GC) have not been fully explicated. Methods: We used public databases to derive information on potential targets of TRX and proteins related to GC. Also, STRING and R3.6.2 software were used to analyze the protein–protein interaction (PPI). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were done to explain the potential mechanism underlying the regulatory role of TRX in GC. The role of TRX in GC was verified by 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di- phenytetrazoliumromide (MTT) assay, apoptosis analysis, Transwell assay, and wound healing assay, and the key signaling pathways were verified. Results: We identified 135 potential targets for the treatment of GC via network pharmacological analysis. GO and KEGG enrichment analysis showed that steroid hormone receptor activity and the PI3K/AKT signaling pathway were the biological processes and pathways with the highest degree of enrichment. Additionally, cellular experiments revealed that TRX inhibited the proliferation, migration, and invasion of GC cells as well as induced G1 phase arrest and apoptosis in GC cells. Conclusion: Here, we used multi-target and multi-pathway network pharmacological analysis to verify the anti-cancer activity of TRX in GC. Also, in vitro experimental data were used to derive the potential molecular mechanism.