A Natural Wind Defrosting, Nano-coated Antibacterial Self-cleaning Energy-saving Health Air-cooled Refrigerator

The air-cooled frost-free household refrigerator is popular in the market because of its large size and frost-free size. However, the evaporator defrost process consumes a large amount of electrical energy to limit the wide spread of this refrigerator, at the same time because of its structural problems, resulting in its evaporator, air duct can not be artificially cleaned, leading to the growth of bacteria, pollution of food storage. This research has developed a self-cleaning energy-saving health refrigerator that uses indoor natural wind defrosting, ultra-hydrophilic nano-titanium dioxide coating photocatalytic sterilization and sterilization. After experimental comparison, under the same operating time of the same operating conditions, the refrigeration mode saves 1.5%, the defrost process saves 95%, reduces the amount of frosting by 23%, the temperature changes of the freezer is less than 7 ℃ , and the desterilization rate of nano-coated reaches 80%

The Multivesicular Body and Autophagosome Pathways in Plants

In eukaryotic cells, the endomembrane system consists of multiple membrane-bound organelles, which play essential roles in the precise transportation of various cargo proteins. In plant cells, vacuoles are regarded as the terminus of catabolic pathways whereas the selection and transport of vacuolar cargoes are mainly mediated by two types of organelles, multivesicular bodies (MVBs) also termed prevacuolar compartments (PVCs) and autophagosomes. MVBs are single-membrane bound organelles with intraluminal vesicles and mediate the transport between the trans-Golgi network (TGN) and vacuoles, while autophagosomes are double-membrane bound organelles, which mediate cargo delivery to the vacuole for degradation and recycling during autophagy. Great progress has been achieved recently in identification and characterization of the conserved and plant-unique regulators involved in the MVB and autophagosome pathways. In this review, we present an update on the current knowledge of these key regulators and pay special attention to their conserved protein domains. In addition, we discuss the possible interplay between the MVB and autophagosome pathways in regulating vacuolar degradation in plants

Efficient Conversion of Phenylpyruvic Acid to Phenyllactic Acid by Using Whole Cells of Bacillus coagulans SDM

Background: Phenyllactic acid (PLA), a novel antimicrobial compound with broad and effective antimicrobial activity against both bacteria and fungi, can be produced by many microorganisms, especially lactic acid bacteria. However, the concentration and productivity of PLA have been low in previous studies. The enzymes responsible for conversion of phenylpyruvic acid (PPA) into PLA are equivocal. Methodology/Principal Findings: A novel thermophilic strain, Bacillus coagulans SDM, was isolated for production of PLA. When the solubility and dissolution rate of PPA were enhanced at a high temperature, whole cells of B. coagulans SDM could effectively convert PPA into PLA at a high concentration (37.3 g l 21) and high productivity (2.3 g l 21 h 21) under optimal conditions. Enzyme activity staining and kinetic studies identified NAD-dependent lactate dehydrogenases as the key enzymes that reduced PPA to PLA. Conclusions/Significance: Taking advantage of the thermophilic character of B. coagulans SDM, a high yield and productivity of PLA were obtained. The enzymes involved in PLA production were identified and characterized, which makes possible the rational design and construction of microorganisms suitable for PLA production with metaboli

A Novel Whole-Cell Biocatalyst with NAD+ Regeneration for Production of Chiral Chemicals

Background: The high costs of pyridine nucleotide cofactors have limited the applications of NAD(P)-dependent oxidoreductases on an industrial scale. Although NAD(P)H regeneration systems have been widely studied, NAD(P) + regeneration, which is required in reactions where the oxidized form of the cofactor is used, has been less well explored, particularly in whole-cell biocatalytic processes. Methodology/Principal Findings: Simultaneous overexpression of an NAD + dependent enzyme and an NAD + regenerating enzyme (H2O producing NADH oxidase from Lactobacillus brevis) in a whole-cell biocatalyst was studied for application in the NAD +-dependent oxidation system. The whole-cell biocatalyst with (2R,3R)-2,3-butanediol dehydrogenase as the catalyzing enzyme was used to produce (3R)-acetoin, (3S)-acetoin and (2S,3S)-2,3-butanediol. Conclusions/Significance: A recombinant strain, in which an NAD + regeneration enzyme was coexpressed, displayed significantly higher biocatalytic efficiency in terms of the production of chiral acetoin and (2S,3S)-2,3-butanediol. The application of this coexpression system to the production of other chiral chemicals could be extended by using differen

SurrealDriver: Designing Generative Driver Agent Simulation Framework in Urban Contexts based on Large Language Model

Simulation plays a critical role in the research and development of autonomous driving and intelligent transportation systems. However, the current simulation platforms exhibit limitations in the realism and diversity of agent behaviors, which impede the transfer of simulation outcomes to the real world. In this paper, we propose a generative driver agent simulation framework based on large language models (LLMs), capable of perceiving complex traffic scenarios and providing realistic driving maneuvers. Notably, we conducted interviews with 24 drivers and used their detailed descriptions of driving behavior as chain-of-thought prompts to develop a `coach agent' module, which can evaluate and assist driver agents in accumulating driving experience and developing human-like driving styles. Through practical simulation experiments and user experiments, we validate the feasibility of this framework in generating reliable driver agents and analyze the roles of each module. The results show that the framework with full architect decreased the collision rate by 81.04% and increased the human-likeness by 50%. Our research proposes the first urban context driver agent simulation framework based on LLMs and provides valuable insights into the future of agent simulation for complex tasks.Comment: 12 pages, 8 figure

Deep learning models for predicting RNA degradation via dual crowdsourcing

Medicines based on messenger RNA (mRNA) hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition (‘Stanford OpenVaccine’) on Kaggle, involving single-nucleotide resolution measurements on 6,043 diverse 102–130-nucleotide RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504–1,588 nucleotides) with improved accuracy compared with previously published models. These results indicate that such models can represent in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for dataset creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales

Deep learning models for predicting RNA degradation via dual crowdsourcing

Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition ("Stanford OpenVaccine") on Kaggle, involving single-nucleotide resolution measurements on 6043 102-130-nucleotide diverse RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months, and 41% of nucleotide-level predictions from the winning model were within experimental error of the ground truth measurement. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1588 nucleotides) with improved accuracy compared to previously published models. Top teams integrated natural language processing architectures and data augmentation techniques with predictions from previous dynamic programming models for RNA secondary structure. These results indicate that such models are capable of representing in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for data set creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales

Bilingualism for the Minor or the Major? An Evaluative Analysis of Parallel Conceptions in China

This paper is an analysis of two conceptions of bilingualism that exist in parallel in China. One is traditional bilingualism referring to the use of a native minority language and standard Chinese by minority groups and the other, seen as bilingualism with modern characteristics, is a modern-day phenomenon in which the majority Han group aspire to produce bilinguals with a strong competence in mother tongue Chinese and a foreign language, primarily English, by using Chinese and the foreign language as mediums of instruction in teaching school subjects. The focus of the analysis is on the latter for the simple reason that current literature on the new phenomenon is mostly available only in Chinese. An equally important aim of this paper is to explore the impact of the new phenomenon on minority education and to examine the reason why this impact is largely ignored in bilingualism discussions, despite obvious consequences with respect to ethnic identity, personality development and academic performance of minority students. Thus, the traditional conception is briefly reviewed at the start

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead