Regional estimation of daily to annual regional evapotranspiration with MODIS data in the Yellow River Delta wetland

Evapotranspiration (ET) from the wetland of the Yellow River Delta (YRD) is one of the important components in the water cycle, which represents the water consumption by the plants and evaporation from the water and the non-vegetated surfaces. Reliable estimates of the total evapotranspiration from the wetland is useful information both for understanding the hydrological process and for water management to protect this natural environment. Due to the heterogeneity of the vegetation types and canopy density and of soil water content over the wetland (specifically over the natural reserve areas), it is difficult to estimate the regional evapotranspiration extrapolating measurements or calculations usually done locally for a specific land cover type. Remote sensing can provide observations of land surface conditions with high spatial and temporal resolution and coverage. In this study, a model based on the Energy Balance method was used to calculate daily evapotranspiration (ET) using instantaneous observations of land surface reflectance and temperature from MODIS when the data were available on clouds-free days. A time series analysis algorithm was then applied to generate a time series of daily ET over a year period by filling the gaps in the observation series due to clouds. A detailed vegetation classification map was used to help identifying areas of various wetland vegetation types in the YRD wetland. Such information was also used to improve the parameterizations in the energy balance model to improve the accuracy of ET estimates. This study showed that spatial variation of ET was significant over the same vegetation class at a given time and over different vegetation types in different seasons in the YRD wetlan

Time-optimal variational control of bright matter-wave soliton

Motivated by recent experiments, we present the time-optimal variational control of bright matter-wave soliton trapped in a quasi-one-dimensional harmonic trap by manipulating the atomic attraction through Feshbach resonances. More specially, we first apply a time-dependent variational method to derive the motion equation for capturing the soliton's shape, and secondly combine inverse engineering with optimal control theory to design the atomic interaction for implementing time-optimal decompression. Since the time-optimal solution is of bang-bang type, the smooth regularization is further adopted to smooth the on-off controller out, thus avoiding the heating and atom loss, induced from magnetic field ramp across a Feshbach resonance in practice

A snoRNA modulates mRNA 3' end processing and regulates the expression of a subset of mRNAs.

mRNA 3' end processing is an essential step in gene expression. It is well established that canonical eukaryotic pre-mRNA 3' processing is carried out within a macromolecular machinery consisting of dozens of trans-acting proteins. However, it is unknown whether RNAs play any role in this process. Unexpectedly, we found that a subset of small nucleolar RNAs (snoRNAs) are associated with the mammalian mRNA 3' processing complex. These snoRNAs primarily interact with Fip1, a component of cleavage and polyadenylation specificity factor (CPSF). We have functionally characterized one of these snoRNAs and our results demonstrated that the U/A-rich SNORD50A inhibits mRNA 3' processing by blocking the Fip1-poly(A) site (PAS) interaction. Consistently, SNORD50A depletion altered the Fip1-RNA interaction landscape and changed the alternative polyadenylation (APA) profiles and/or transcript levels of a subset of genes. Taken together, our data revealed a novel function for snoRNAs and provided the first evidence that non-coding RNAs may play an important role in regulating mRNA 3' processing

Latent-Shift: Latent Diffusion with Temporal Shift for Efficient Text-to-Video Generation

We propose Latent-Shift -- an efficient text-to-video generation method based on a pretrained text-to-image generation model that consists of an autoencoder and a U-Net diffusion model. Learning a video diffusion model in the latent space is much more efficient than in the pixel space. The latter is often limited to first generating a low-resolution video followed by a sequence of frame interpolation and super-resolution models, which makes the entire pipeline very complex and computationally expensive. To extend a U-Net from image generation to video generation, prior work proposes to add additional modules like 1D temporal convolution and/or temporal attention layers. In contrast, we propose a parameter-free temporal shift module that can leverage the spatial U-Net as is for video generation. We achieve this by shifting two portions of the feature map channels forward and backward along the temporal dimension. The shifted features of the current frame thus receive the features from the previous and the subsequent frames, enabling motion learning without additional parameters. We show that Latent-Shift achieves comparable or better results while being significantly more efficient. Moreover, Latent-Shift can generate images despite being finetuned for T2V generation.Comment: https://latent-shift.github.i

Deletion of heat shock protein 60 in adult mouse cardiomyocytes perturbs mitochondrial protein homeostasis and causes heart failure.

To maintain healthy mitochondrial enzyme content and function, mitochondria possess a complex protein quality control system, which is composed of different endogenous sets of chaperones and proteases. Heat shock protein 60 (HSP60) is one of these mitochondrial molecular chaperones and has been proposed to play a pivotal role in the regulation of protein folding and the prevention of protein aggregation. However, the physiological function of HSP60 in mammalian tissues is not fully understood. Here we generated an inducible cardiac-specific HSP60 knockout mouse model, and demonstrated that HSP60 deletion in adult mouse hearts altered mitochondrial complex activity, mitochondrial membrane potential, and ROS production, and eventually led to dilated cardiomyopathy, heart failure, and lethality. Proteomic analysis was performed in purified control and mutant mitochondria before mutant hearts developed obvious cardiac abnormalities, and revealed a list of mitochondrial-localized proteins that rely on HSP60 (HSP60-dependent) for correctly folding in mitochondria. We also utilized an in vitro system to assess the effects of HSP60 deletion on mitochondrial protein import and protein stability after import, and found that both HSP60-dependent and HSP60-independent mitochondrial proteins could be normally imported in mutant mitochondria. However, the former underwent degradation in mutant mitochondria after import, suggesting that the protein exhibited low stability in mutant mitochondria. Interestingly, the degradation could be almost fully rescued by a non-specific LONP1 and proteasome inhibitor, MG132, in mutant mitochondria. Therefore, our results demonstrated that HSP60 plays an essential role in maintaining normal cardiac morphology and function by regulating mitochondrial protein homeostasis and mitochondrial function

AgeAnnoMo: A Knowledgebase of Multi-Omics Annotation for Animal Aging

Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks proposed as common and conserved underlying denominators of aging on the molecular, cellular and systemic levels across multiple species. Thus, understanding the function of aging hallmarks and their relationships across species can facilitate the translation of anti-aging drug development from model organisms to humans. Here, we built AgeAnnoMO (https://relab.xidian.edu.cn/AgeAnnoMO/#/), a knowledgebase of multi-omics annotation for animal aging. AgeAnnoMO encompasses an extensive collection of 136 datasets from eight modalities, encompassing 8596 samples from 50 representative species, making it a comprehensive resource for aging and longevity research. AgeAnnoMO characterizes multiple aging regulators across species via multi-omics data, comprehensively annotating aging-related genes, proteins, metabolites, mitochondrial genes, microbiotas and age-specific TCR and BCR sequences tied to aging hallmarks for these species and tissues. AgeAnnoMO not only facilitates a deeper and more generalizable understanding of aging mechanisms, but also provides potential insights of the specificity across tissues and species in aging process, which is important to develop the effective anti-aging interventions for diverse populations. We anticipate that AgeAnnoMO will provide a valuable resource for comprehending and integrating the conserved driving hallmarks in aging biology and identifying the targetable biomarkers for aging research