Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting

Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning. Long sequence time-series forecasting (LSTF) demands a high prediction capacity of the model, which is the ability to capture precise long-range dependency coupling between output and input efficiently. Recent studies have shown the potential of Transformer to increase the prediction capacity. However, there are several severe issues with Transformer that prevent it from being directly applicable to LSTF, including quadratic time complexity, high memory usage, and inherent limitation of the encoder-decoder architecture. To address these issues, we design an efficient transformer-based model for LSTF, named Informer, with three distinctive characteristics: (i) a $ProbSparse$ self-attention mechanism, which achieves $O(L \log L)$ in time complexity and memory usage, and has comparable performance on sequences' dependency alignment. (ii) the self-attention distilling highlights dominating attention by halving cascading layer input, and efficiently handles extreme long input sequences. (iii) the generative style decoder, while conceptually simple, predicts the long time-series sequences at one forward operation rather than a step-by-step way, which drastically improves the inference speed of long-sequence predictions. Extensive experiments on four large-scale datasets demonstrate that Informer significantly outperforms existing methods and provides a new solution to the LSTF problem.Comment: 8 pages (main), 5 pages (appendix) and to be appeared in AAAI202

Generation and Bioenergetic Profiles of Cybrids with East Asian mtDNA Haplogroups

Human mitochondrial DNA (mtDNA) variants and haplogroups may contribute to susceptibility to various diseases and pathological conditions, but the underlying mechanisms are not well understood. To address this issue, we established a cytoplasmic hybrid (cybrid) system to investigate the role of mtDNA haplogroups in human disease; specifically, we examined the effects of East Asian mtDNA genetic backgrounds on oxidative phosphorylation (OxPhos). We found that mtDNA single nucleotide polymorphisms such as m.489T>C, m.10398A>G, m.10400C>T, m.C16223T, and m.T16362C affected mitochondrial function at the level of mtDNA, mtRNA, or the OxPhos complex. Macrohaplogroup M exhibited higher respiratory activity than haplogroup N owing to its higher mtDNA content, mtRNA transcript levels, and complex III abundance. Additionally, haplogroup M had higher reactive oxygen species levels and NAD+/NADH ratios than haplogroup N, suggesting difference in mitonuclear interactions. Notably, subhaplogroups G2, B4, and F1 appeared to contribute significantly to the differences between haplogroups M and N. Thus, our cybrid-based system can provide insight into the mechanistic basis for the role of mtDNA haplogroups in human diseases and the effect of mtDNA variants on mitochondrial OxPhos function. In addition, studies of mitonuclear interaction using this system can reveal predisposition to certain diseases conferred by variations in mtDNA

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Searching for the Best FFT Formulas with the SPL Compiler

This paper discuss an approach to implementing and optimizing fast signal transforms based on a domain specific computer language, called SPL. SPL programs, which are essentially mathematical formulas, represent matrix factorizations, which provide fast algorithms for computing many important signal transforms. A special purpose compiler translates SPL programs into e#cient FORTRAN programs. Since there are many formulas for a given transform, a fast implementation can be obtained by generating alternative formulas and searching for the one with the fastest execution time. This paper presents an application of this methodology to the implementation of the FFT