A meaningful video is semantically coherent and changes smoothly. However, most existing fine-grained video representation learning methods learn frame-wise features by aligning frames across videos ...or exploring relevance between multiple views, neglecting the inherent dynamic process of each video. In this paper, we propose to learn video representations by modeling Video as Stochastic Processes (VSP) via a novel process-based contrastive learning framework, which aims to discriminate between video processes and simultaneously capture the temporal dynamics in the processes. Specifically, we enforce the embeddings of the frame sequence of interest to approximate a goal-oriented stochastic process, i.e., Brownian bridge, in the latent space via a process-based contrastive loss. To construct the Brownian bridge, we adapt specialized sampling strategies under different annotations for both self-supervised and weakly-supervised learning. Experimental results on four datasets show that VSP stands as a state-of-the-art method for various video understanding tasks, including phase progression, phase classification, and frame retrieval. Code is available at https://github.com/hengRUC/VSP.
Veterinary antibiotics can enter the environment due to the common practice of land application of manure from treated animals. The environmental fate of tetracyclines in swine manure after ...composting and field application remains largely unknown. This study analyzed the concentrations of tetracyclines in manure, manure-based compost and compost amended soil in selected swine farms from Beijing, Jiaxing and Putian, China to determine the dilution effects of antibiotics when released into the soil environment. The results demonstrate that residues of antibiotics were detected in all samples and chlortetracycline as well as its degradation products should be regarded critically concerning their potential ecotoxicity. Application of manure-based compost to soil could reduce the possible risk posed by antibiotic contamination, but the trigger value of 100 μg/kg was still exceeded in soil samples (776.1 μg/kg dw) from Putian City after application of compost. Field studies such as the present one can help to improve the routine administration of antibiotic-containing composted manure.
Power supply integrity is very important in digital systems. When the frequency on the power loop becomes higher, the impedance on the loop will gradually increase. The change in voltage drop will ...also cause the fluctuation of the output voltage to increase, and eventually causing the overall system becomes unstable and loses efficiency. The coupling capacitance on the loop plays an important role for these phenomenon. In this paper, the output voltage of the switching power supply is supplied to the microcontroller for operation. Simulation software is used to analyze the impedance on the power loop, and the circuit board is used to implement the method of operation and measurement will be discussed in depth on their principles and characteristics.
Multi-Modal Entity Alignment (MMEA) aims to identify equivalent entities across different knowledge graphs by utilizing auxiliary modalities such as images. While MMEA has made significant progress, ...prevailing methods still heavily rely on abundant annotated entity pairs. Active learning seeks to alleviate the labeling burden or enhance model efficiency within fixed labeling capacity through careful sample selection. However, active learning for entity alignment in multimodal scenarios remains unexplored. In our view, it is crucial that data selected from different modalities should complement each other without redundancy or overlap; otherwise, the obtained data may prove a waste of labeling budgets. To achieve this goal, we propose a novel acquisition function leveraging Graph Neural Networks' (GNNs) capability to aggregate information over multiple hops, prioritizing data distant from other modalities' selections. Moreover, existing approaches employ data augmentation by selecting entity pairs whose inter-entity similarities of other modalities exceed a predefined threshold, but this augmentation strategy inadequately capitalizes on the available similarity information among entities. We can further enhance performance by integrating similarity matrices from different modalities. Consequently, our method achieves considerable improvements over existing active learning methods for entity alignment, as demonstrated by the experiments.
The synthesis of chloramphenicol, a kind of amphenicol antibiotic with broad-spectrum antibacterial activity, is challenging due to its stereochemistry. Here, we have designed a four-step ...chemoenzymatic strategy, including a biocatalytic step mediated by
l
-threonine transaldolase from
Pseudomonas
sp. (PsLTTA) to convert 4-nitrobenzaldehyde (
1
) to (2
S
,3
R
)-2-amino-3-hydroxy-3-(4-nitrophenyl)propanoic acid (
2
) followed by a three-step chemical reaction to obtain chloramphenicol. A rational design of PsLTTA was devised by reshaping the substrate binding pocket and substrate access channel, resulting in the best variant PsLTTA-N35A/C57I/F59A/H69F (PsLTTA-Mu9), which achieved a 7.1-fold higher yield of
2
than wild-type PsLTTA. After coupling with ScADH/CbFDH to remove the byproduct acetaldehyde and optimizing the reaction conditions, the whole-cell catalyst BL21(PsLTTA-Mu9/ScADH/CbFDH) could synthesize 200 mM of
2
in four hours with 99% conversion and 97.7% de, delivering the highest time-space yield (11.3 g L
−1
h
−1
) ever reported. Finally, the chemoenzymatic approach was applied for the gram-scale synthesis of
5
with a high overall yield (54%). The success of this strategy demonstrates the great advantage of the chemoenzymatic approach in the asymmetric synthesis of chloramphenicol and may contribute to its industrial synthesis.
Chemo-enzymatic route for chloramphenicol.
The mechanistic target of rapamycin (mTOR) functions as a critical regulator of cellular growth and metabolism by forming multi-component, yet functionally distinct complexes mTORC1 and mTORC2. ...Although mTORC2 has been implicated in mTORC1 activation, little is known about how mTORC2 is regulated. Here we report that phosphorylation of Sin1 at Thr 86 and Thr 398 suppresses mTORC2 kinase activity by dissociating Sin1 from mTORC2. Importantly, Sin1 phosphorylation, triggered by S6K or Akt, in a cellular context-dependent manner, inhibits not only insulin- or IGF-1-mediated, but also PDGF- or EGF-induced Akt phosphorylation by mTORC2, demonstrating a negative regulation of mTORC2 independent of IRS-1 and Grb10. Finally, a cancer-patient-derived Sin1-R81T mutation impairs Sin1 phosphorylation, leading to hyper-activation of mTORC2 by bypassing this negative regulation. Together, our results reveal a Sin1-phosphorylation-dependent mTORC2 regulation, providing a potential molecular mechanism by which mutations in the mTORC1-S6K-Sin1 signalling axis might cause aberrant hyper-activation of the mTORC2-Akt pathway, which facilitates tumorigenesis.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Understanding the driving forces of gene expression variation within human populations will provide important insights into the molecular basis of human phenotypic variation. In the genome, the gene ...expression variability differs among genes, and at present, most research has focused on identifying the genetic variants responsible for the within population gene expression variation. However, little is known about whether microRNAs (miRNAs), which are small noncoding RNAs modulating expression of their target genes, could have impact on the variability of gene expression. Here we demonstrate that miRNAs likely lead to the difference of expression variability among genes. With the use of the genome-wide expression data in 193 human brain samples, we show that the increased variability of gene expression is concomitant with the increased number of the miRNA seeds interacting with the target genes, suggesting a direct influence of miRNA on gene expression variability. Compared with the non-miRNA-target genes, genes targeted by more than two miRNA seeds have increased expression variability, independent of the miRNA types. In addition, single-nucleotide polymorphisms (SNPs) located in the miRNA binding sites could further increase the gene expression variability of the target genes. We propose that miRNAs are one of the driving forces causing expression variability in the human genome.
We study a scheduling environment that finds many real-world manufacturing applications, in which there is a close connection between a hybrid multiprocessor open shop and multiple parallel identical ...flow shops. In this environment, there is an extended two-stage open shop, where in one stage we have a set of parallel identical machines, while in the other we have a two-machine flow shop. Our objective is to minimize the makespan, that is, the latest completion time of all jobs. We pursue approximation algorithms with provable performance, and we achieve a 2-approximation when the number of parallel identical machines is constant or is part of the input; we also design a 5/3-approximation for the special case where there is only one machine in the multiprocessor stage, which remains weakly NP-hard. Our empirical experiments show that both approximation algorithms perform much better in simulated instances; their average ratios over the proposed lower bound are around 1.5 and 1.2, respectively.
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