PMAA: A Progressive Multi-scale Attention Autoencoder Model for High-Performance Cloud Removal from Multi-temporal Satellite Imagery

Satellite imagery analysis plays a vital role in remote sensing, but the information loss caused by cloud cover seriously hinders its application. This study presents a high-performance cloud removal architecture called Progressive Multi-scale Attention Autoencoder (PMAA), which simultaneously leverages global and local information. It mainly consists of a cloud detection backbone and a cloud removal module. The cloud detection backbone uses cloud masks to reinforce cloudy areas to prompt the cloud removal module. The cloud removal module mainly comprises a novel Multi-scale Attention Module (MAM) and a Local Interaction Module (LIM). PMAA establishes the long-range dependency of multi-scale features using MAM and modulates the reconstruction of the fine-grained details using LIM, allowing for the simultaneous representation of fine- and coarse-grained features at the same level. With the help of diverse and multi-scale feature representation, PMAA outperforms the previous state-of-the-art model CTGAN consistently on the Sen2_MTC_Old and Sen2_MTC_New datasets. Furthermore, PMAA has a considerable efficiency advantage, with only 0.5% and 14.6% of the parameters and computational complexity of CTGAN, respectively. These extensive results highlight the potential of PMAA as a lightweight cloud removal network suitable for deployment on edge devices. We will release the code and trained models to facilitate the study in this direction.Comment: 8 pages, 5 figure

A linear-time algorithm for reconstructing zero-recombinant haplotype configuration on a pedigree

BACKGROUND: When studying genetic diseases in which genetic variations are passed on to offspring, the ability to distinguish between paternal and maternal alleles is essential. Determining haplotypes from genotype data is called haplotype inference. Most existing computational algorithms for haplotype inference have been designed to use genotype data collected from individuals in the form of a pedigree. A haplotype is regarded as a hereditary unit and therefore input pedigrees are preferred that are free of mutational events and have a minimum number of genetic recombinational events. These ideas motivated the zero-recombinant haplotype configuration (ZRHC) problem, which strictly follows the Mendelian law of inheritance, namely that one haplotype of each child is inherited from the father and the other haplotype is inherited from the mother, both without any mutation. So far no linear-time algorithm for ZRHC has been proposed for general pedigrees, even though the number of mating loops in a human pedigree is usually very small and can be regarded as constant. RESULTS: Given a pedigree with n individuals, m marker loci, and k mating loops, we proposed an algorithm that can provide a general solution to the zero-recombinant haplotype configuration problem in O(kmn + k(2)m) time. In addition, this algorithm can be modified to detect inconsistencies within the genotype data without loss of efficiency. The proposed algorithm was subject to 12000 experiments to verify its performance using different (n, m) combinations. The value of k was uniformly distributed between zero and six throughout all experiments. The experimental results show a great linearity in terms of execution time in relation to input size when both n and m are larger than 100. For those experiments where n or m are less than 100, the proposed algorithm runs very fast, in thousandth to hundredth of a second, on a personal desktop computer. CONCLUSIONS: We have developed the first deterministic linear-time algorithm for the zero-recombinant haplotype configuration problem. Our experimental results demonstrated the linearity of its execution time in relation to the input size. The proposed algorithm can be modified to detect inconsistency within the genotype data without loss of efficiency and is expected to be able to handle recombinant and missing data with further extension

High-Fidelity Lake Extraction via Two-Stage Prompt Enhancement: Establishing a Novel Baseline and Benchmark

The extraction of lakes from remote sensing images is a complex challenge due to the varied lake shapes and data noise. Current methods rely on multispectral image datasets, making it challenging to learn lake features accurately from pixel arrangements. This, in turn, affects model learning and the creation of accurate segmentation masks. This paper introduces a unified prompt-based dataset construction approach that provides approximate lake locations using point, box, and mask prompts. We also propose a two-stage prompt enhancement framework, LEPrompter, which involves prompt-based and prompt-free stages during training. The prompt-based stage employs a prompt encoder to extract prior information, integrating prompt tokens and image embeddings through self- and cross-attention in the prompt decoder. Prompts are deactivated once the model is trained to ensure independence during inference, enabling automated lake extraction. Evaluations on Surface Water and Qinghai-Tibet Plateau Lake datasets show consistent performance improvements compared to the previous state-of-the-art method. LEPrompter achieves mIoU scores of 91.48% and 97.43% on the respective datasets without introducing additional parameters or GFLOPs. Supplementary materials provide the source code, pre-trained models, and detailed user studies.Comment: 8 pages, 7 figure

The Arabidopsis Malectin-Like/LRR-RLK IOS1 is Critical for BAK1-Dependent and BAK1-Independent Pattern-Triggered Immunity

Plasma membrane-localized pattern recognition receptors (PRRs) such as FLAGELLIN SENSING2 (FLS2), EF-TU RECEPTOR (EFR) and CHITIN ELICITOR RECEPTOR KINASE 1 (CERK1) recognize microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). A reverse genetics approach on genes responsive to the priming agent beta-aminobutyric acid (BABA) revealed IMPAIRED OOMYCETE SUSCEPTIBILITY1 (IOS1) as a critical PTI player. Arabidopsis thaliana ios1 mutants were hyper-susceptible to Pseudomonas syringae bacteria. Accordingly, ios1 mutants showed defective PTI responses, notably delayed up-regulation of the PTI-marker gene FLG22-INDUCED RECEPTOR-LIKE KINASE1 (FRK1), reduced callose deposition and mitogen-activated protein kinase activation upon MAMP treatment. Moreover, Arabidopsis lines over-expressing IOS1 were more resistant to bacteria and showed a primed PTI response. In vitro pull-down, bimolecular fluorescence complementation, co-immunoprecipitation, and mass spectrometry analyses supported the existence of complexes between the membrane-localized IOS1 and BRASSINOSTEROID INSENSITIVE1-ASSOCIATED KINASE1 (BAK1)-dependent PRRs FLS2 and EFR, as well as with the BAK1-independent PRR CERK1. IOS1 also associated with BAK1 in a ligand-independent manner, and positively regulated FLS2-BAK1 complex formation upon MAMP treatment. In addition, IOS1 was critical for chitin-mediated PTI. Finally, ios1 mutants were defective in BABA-induced resistance and priming. This work reveals IOS1 as a novel regulatory protein of FLS2-, EFR- and CERK1-mediated signaling pathways that primes PTI activation

Evolution of Hepatitis B Virus in a Chronic HBV-Infected Patient over 2 Years

Mutations in full-length HBV isolates obtained from a chronic HBV-infected patient were evaluated at three time points: 1 day, 6 months, and 31 months. While 5 nucleotides variation, and an 18 bp deletion of preS1 have been kept in during at least the first two years, C339T mutation occurring in the hydrophilic region of HBsAg and T770C that caused polymerase V560A substitution were the new point mutations found existing in sequenced clones of the 3rd time point. Internal deletion of coding region obviously appeared in the 3rd time point. The splicers included two new 5′-splice donors and three new 3′-splice acceptors besides the reported donors and acceptors and may have produced presumptive HBV-spliced proteins or truncated preS proteins. ALT, HBeAg and viral DNA load varied during the follow-up years. These data demonstrated the diversity of genomes in HBV-infected patient during evolution. Combined with clinical data, the HBV variants discovered in this patient may contribute to viral persistence of infection or liver pathogenesis

Mining the Virgin Land of Neurotoxicology: A Novel Paradigm of Neurotoxic Peptides Action on Glycosylated Voltage-Gated Sodium Channels

Voltage-gated sodium channels (VGSCs) are important membrane protein carrying on the molecular basis for action potentials (AP) in neuronal firings. Even though the structure-function studies were the most pursued spots, the posttranslation modification processes, such as glycosylation, phosphorylation, and alternative splicing associating with channel functions captured less eyesights. The accumulative research suggested an interaction between the sialic acids chains and ion-permeable pores, giving rise to subtle but significant impacts on channel gating. Sodium channel-specific neurotoxic toxins, a family of long-chain polypeptides originated from venomous animals, are found to potentially share the binding sites adjacent to glycosylated region on VGSCs. Thus, an interaction between toxin and glycosylated VGSC might hopefully join the campaign to approach the role of glycosylation in modulating VGSCs-involved neuronal network activity. This paper will cover the state-of-the-art advances of researches on glycosylation-mediated VGSCs function and the possible underlying mechanisms of interactions between toxin and glycosylated VGSCs, which may therefore, fulfill the knowledge in identifying the pharmacological targets and therapeutic values of VGSCs

Rainfall Variation under Different Climate Change Scenarios Based on Cmip3 and Cmip5 Projections: a Case Study in Taiwan

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Phase behavior and hydrocarbons distribution in shale oil during EOR with nano-confinement effect

The pore structure of shale reservoirs leads to the complex phase behavior of shale reservoir fluids, which is aggravated due to changes in fluid composition during reservoir development. Effective prediction of changes in the phase behavior of fluids in shale reservoirs is important. This paper proposes a pore-size-dependent Peng-Robinson equation of state (PR-EOS) to describe phase behavior in nanopores. The approach considers the shift of critical parameters and the gas-liquid capillary pressure and compiles by MATLAB. The verification of the model is satisfying by matching the result with Tnavigator PVTi using the published date. The results show that fluids in nanoscale pores are more likely to exhibit near-critical or condensate states. We also compare the changes in phase behavior when fluids dissolve CO2 and CH4 and observe the phase transition (from gaseous to liquid phase) of the lighter crude oil sample that dissolved more gas during the differential liberation experiment (DL). Finally, we use CO2 pre-pad energized fracturing of a shale oil reservoir in northern China as an example to explain abnormal production performances, such as a majority of light hydrocarbons in the produced fluid of the well during the flow back stage, single gas phase production in the early production stage, and stable gas/oil ratio (GOR) in the process of development. Our novel methodology and phase behavior change mechanism can enhance our understanding of the phase behavior of fluids in shale oil reservoirs during enhanced oil recovery