Abstract: A battery includes a housing, a core, a first connection piece, and a plate. The core is disposed in the housing. The first connection piece is disposed on one end of the housing. The first connection piece is connected to the core. The plate is disposed on the side of the first connection piece facing away from the core. The side surface of the plate facing away from the first connection piece is provided with at least two concave arc-shaped grooves at intervals. All of the arc-shaped grooves are uniformly disposed annularly along the center of the plate. Groove bottoms of the arc-shaped grooves are welded to the first connection piece.

Abstract: The present disclosure provides a cap assembly, a battery, a battery module, a battery pack, and a vehicle. The cap assembly is used for the battery. The battery includes a cell and a housing for accommodating the cell. The cap assembly includes a busbar plate and a plastic pad. The busbar plate is arranged in the housing, and is attached to the top end of the cell so as to be connected to the cell. The plastic pad is located between the housing and the busbar plate. An edge of the plastic pad extends in a direction close to the busbar plate to form an isolation portion. The plastic pad can cover the busbar plate through the isolation portion, and one side of the isolation portion can be attached to an inner wall of the housing.

Abstract: Disclosed is a computer-implemented method for sequence design, including: obtaining a candidate target sequence set that translates into a source sequence, based on the source sequence; and searching in the candidate target sequence set for a desired target sequence having a sequence structure that minimizes an objective function. The objective function comprises a minimum free energy (MFE) of a candidate target sequence and an additive regularization term.

Abstract: A messenger RNA (mRNA) vaccine has emerged as a promising direction to combat the COVID-19 pandemic. This requires an mRNA sequence that is stable and highly productive in protein expression, features to benefit from greater mRNA secondary structure folding stability and optimal codon usage. Sequence design remains challenging due to the exponentially many synonymous mRNA sequences encoding the same protein. The present disclosure presents embodiments of a linear-time approximation (LinearDesign) reducing the design to an intersection between a Stochastic Context Free Grammar (SCFG) and a Deterministic Finite Automaton (DFA). Embodiments of the LinearDesign may implement an mRNA sequence design using much reduced time with very limited loss. Various methodologies, e.g., finding alternative sequences based on k-best parsing or directly incorporating codon optimality, are presented for incorporating the codon optimality into the design.

Abstract: COVID-19 has become a global pandemic after its inception in late 2019. SARS-CoV-2 genomes are sequenced and shared on public repositories at a fast pace. To keep up with these updates, datasets need to be refreshed and re-cleaned frequently. It may be difficult to analyze SARS-CoV-2 genomes for scientists with limited bioinformatics or programming knowledge. In the present disclosure, system and method embodiments for genome analysis and visualization are developed to address these challenges. A webserver may be used to enable simple and rapid analysis of genomes. Given a new sequence, the system may automatically predict gene boundaries and identify genetic variants, which are presented in an interactive genome visualizer and are downloadable for analysis. A command-line interface may be available for high throughput processing.

Abstract: Presented herein are embodiments of a prefix-to-prefix framework for simultaneous translation that implicitly learns to anticipates in a single translation. Within these frameworks are effective “wait-k” policy model embodiments that may be trained to generate a target sentence concurrently with a source sentence but lag behind by a predefined number of words. Embodiments of the prefix-to-prefix framework achieve low latency and better quality when compared to full-sentence translation in four directions: Chinese?English and German?English. Also presented herein is a novel latency metric that addresses deficiencies of previous latency metrics.

Abstract: Presented herein are embodiments of a prefix-to-prefix framework for simultaneous translation that implicitly learns to anticipates in a single translation. Within these frameworks are effective “wait-k” policy model embodiments that may be trained to generate a target sentence concurrently with a source sentence but lag behind by a predefined number of words. Embodiments of the prefix-to-prefix framework achieve low latency and better quality when compared to full-sentence translation in four directions: Chinese?English and German?English. Also presented herein is a novel latency metric that addresses deficiencies of previous latency metrics.