Energy Transformer

Transformers have become the de facto models of choice in machine learning, typically leading to impressive performance on many applications. At the same time, the architectural development in the transformer world is mostly driven by empirical findings, and the theoretical understanding of their architectural building blocks is rather limited. In contrast, Dense Associative Memory models or Modern Hopfield Networks have a well-established theoretical foundation, but have not yet demonstrated truly impressive practical results. We propose a transformer architecture that replaces the sequence of feedforward transformer blocks with a single large Associative Memory model. Our novel architecture, called Energy Transformer (or ET for short), has many of the familiar architectural primitives that are often used in the current generation of transformers. However, it is not identical to the existing architectures. The sequence of transformer layers in ET is purposely designed to minimize a specifically engineered energy function, which is responsible for representing the relationships between the tokens. As a consequence of this computational principle, the attention in ET is different from the conventional attention mechanism. In this work, we introduce the theoretical foundations of ET, explore it's empirical capabilities using the image completion task, and obtain strong quantitative results on the graph anomaly detection task

Trajectory-driven influential billboard placement

In this paper we propose and study the problem of trajectory-driven influential billboard placement: given a set of billboards \ur (each with a location and a cost), a database of trajectories \td and a budget \budget, find a set of billboards within the budget to influence the largest number of trajectories. One core challenge is to identify and reduce the overlap of the influence from different billboards to the same trajectories, while keeping the budget constraint into consideration. We show that this problem is NP-hard and present an enumeration based algorithm with $(1-1/e)$ approximation ratio. However, the enumeration should be very costly when |\ur| is large. By exploiting the locality property of billboards' influence, we propose a partition-based framework \psel. \psel partitions \ur into a set of small clusters, computes the locally influential billboards for each cluster, and merges them to generate the global solution. Since the local solutions can be obtained much more efficient than the global one, \psel should reduce the computation cost greatly; meanwhile it achieves a non-trivial approximation ratio guarantee. Then we propose a \bbsel method to further prune billboards with low marginal influence, while achieving the same approximation ratio as \psel. Experiments on real datasets verify the efficiency and effectiveness of our methods

A \u3cem\u3eLIN28B\u3c/em\u3e Tumor-Specific Transcript in Cancer

The diversity and complexity of the cancer transcriptome may contain transcripts unique to the tumor environment. Here, we report a LIN28B variant, LIN28B-TST, which is specifically expressed in hepatocellular carcinoma (HCC) and many other cancer types. Expression of LIN28B-TST is associated with significantly poor prognosis in HCC patients. LIN28B-TST initiates from a de novo alternative transcription initiation site that harbors a strong promoter regulated by NFYA but not c-Myc. Demethylation of the LIN28B-TST promoter might be a prerequisite for its transcription and transcriptional regulation. LIN28B-TST encodes a protein isoform with additional N-terminal amino acids and is critical for cancer cell proliferation and tumorigenesis. Our findings reveal a mechanism of LIN28B activation in cancer and the potential utility of LIN28B-TST for clinical purposes

Facile Fabrication of Hierarchical MOF–Metal Nanoparticle Tandem Catalysts for the Synthesis of Bioactive Molecules

Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions

Coevolution in Hybrid Genomes: Nuclear-Encoded Rubisco Small Subunits and Their Plastid-Targeting Translocons Accompanying Sequential Allopolyploidy Events in Triticum

The Triticum/Aegilops complex includes hybrid species resulting from homoploid hybrid speciation and allopolyploid speciation. Sequential allotetra- and allohexaploidy events presumably result in two challenges for the hybrids, which involve 1) cytonuclear stoichiometric disruptions caused by combining two diverged nuclear genomes with the maternal inheritance of the cytoplasmic organellar donor; and 2) incompatibility of chimeric protein complexes with diverged subunits from nuclear and cytoplasmic genomes. Here, we describe coevolution of nuclear rbcS genes encoding the small subunits of Rubisco (ribulose 1,5-bisphosphate carboxylase/oxygenase) and nuclear genes encoding plastid translocons, which mediate recognition and translocation of nuclear-encoded proteins into plastids, in allopolyploid wheat species. We demonstrate that intergenomic paternal-to-maternal gene conversion specifically occurred in the genic region of the homoeologous rbcS3 gene from the D-genome progenitor of wheat (abbreviated as rbcS3D) such that it encodes a maternal-like or B-subgenome-like SSU3D transit peptide in allohexaploid wheat but not in allotetraploid wheat. Divergent and limited interaction between SSU3D and the D-subgenomic TOC90D translocon subunit is implicated to underpin SSU3D targeting into the chloroplast of hexaploid wheat. This implicates early selection favoring individuals harboring optimal maternal-like organellar SSU3D targeting in hexaploid wheat. These data represent a novel dimension of cytonuclear evolution mediated by organellar targeting and transportation of nuclear proteins

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data