Communicative Agents for Software Development

Software engineering is a domain characterized by intricate decision-making processes, often relying on nuanced intuition and consultation. Recent advancements in deep learning have started to revolutionize software engineering practices through elaborate designs implemented at various stages of software development. In this paper, we present an innovative paradigm that leverages large language models (LLMs) throughout the entire software development process, streamlining and unifying key processes through natural language communication, thereby eliminating the need for specialized models at each phase. At the core of this paradigm lies ChatDev, a virtual chat-powered software development company that mirrors the established waterfall model, meticulously dividing the development process into four distinct chronological stages: designing, coding, testing, and documenting. Each stage engages a team of agents, such as programmers, code reviewers, and test engineers, fostering collaborative dialogue and facilitating a seamless workflow. The chat chain acts as a facilitator, breaking down each stage into atomic subtasks. This enables dual roles, allowing for proposing and validating solutions through context-aware communication, leading to efficient resolution of specific subtasks. The instrumental analysis of ChatDev highlights its remarkable efficacy in software generation, enabling the completion of the entire software development process in under seven minutes at a cost of less than one dollar. It not only identifies and alleviates potential vulnerabilities but also rectifies potential hallucinations while maintaining commendable efficiency and cost-effectiveness. The potential of ChatDev unveils fresh possibilities for integrating LLMs into the realm of software development.Comment: 25 pages, 9 figures, 2 table

Genome-Wide DNA Methylation Maps in Follicular Lymphoma Cells Determined by Methylation-Enriched Bisulfite Sequencing

BACKGROUND: Follicular lymphoma (FL) is a form of non-Hodgkin's lymphoma (NHL) that arises from germinal center (GC) B-cells. Despite the significant advances in immunotherapy, FL is still not curable. Beyond transcriptional profiling and genomics datasets, there currently is no epigenome-scale dataset or integrative biology approach that can adequately model this disease and therefore identify novel mechanisms and targets for successful prevention and treatment of FL. METHODOLOGY/PRINCIPAL FINDINGS: We performed methylation-enriched genome-wide bisulfite sequencing of FL cells and normal CD19(+) B-cells using 454 sequencing technology. The methylated DNA fragments were enriched with methyl-binding proteins, treated with bisulfite, and sequenced using the Roche-454 GS FLX sequencer. The total number of bases covered in the human genome was 18.2 and 49.3 million including 726,003 and 1.3 million CpGs in FL and CD19(+) B-cells, respectively. 11,971 and 7,882 methylated regions of interest (MRIs) were identified respectively. The genome-wide distribution of these MRIs displayed significant differences between FL and normal B-cells. A reverse trend in the distribution of MRIs between the promoter and the gene body was observed in FL and CD19(+) B-cells. The MRIs identified in FL cells also correlated well with transcriptomic data and ChIP-on-Chip analyses of genome-wide histone modifications such as tri-methyl-H3K27, and tri-methyl-H3K4, indicating a concerted epigenetic alteration in FL cells. CONCLUSIONS/SIGNIFICANCE: This study is the first to provide a large scale and comprehensive analysis of the DNA methylation sequence composition and distribution in the FL epigenome. These integrated approaches have led to the discovery of novel and frequent targets of aberrant epigenetic alterations. The genome-wide bisulfite sequencing approach developed here can be a useful tool for profiling DNA methylation in clinical samples

Resonant scattering of green light enabled by Ag@TiO2 and its application in a green light projection screen

The ability to selectively scatter green light is essential for an RGB transparent projection display, and this can be achieved by a silver-core, titania-shell nanostructure (Ag@TiO2), based on the metallic nanoparticle's localized surface plasmon resonance. The ability to selectively scatter green light is shown in a theoretical design, in which structural optimization is included, and is then experimentally verified by characterization of a transparent film produced by dispersing such nanoparticles in a polymer matrix. A visual assessesment indicates that a high-quality green image can be clearly displayed on the transparent film. For completeness, a theoretical design for selective scattering of red light based on Ag@TiO2 is also shown.NRF (Natl Research Foundation, S’pore)Accepted versio

A novel vertical dual-loop reactor for rapid start-up of simultaneous partial nitrification and anammox process in treating landfill leachate: Performances and mechanisms

A novel vertical dual-loop reactor (VDLR) was developed to start and conduct a single-stage partial nitritation (PN) and anammox (PN/A) process for treating landfill leachate. Results showed that the total nitrogen (TN) removal reached 1.54 kg N/m3 center dot d in the VDLR. It exhibited excellent mixing uniformity and buffer performance, which can increase the nitrogen removal performance up to 42.1 % via the improvement of anammox granular sludge activity (a particle size of 0.5-1 mm). Mass balance and microbial analysis indicated that the VDLR achieved efficient TN removal via anammox (99.24 %) and AOB (Nitrosomonas and Ellin6067) and anAOB (Candidatus kuenenia) played a vital role in this process

A novel vertical dual-loop reactor for rapid start-up of simultaneous partial nitrification and anammox process in treating landfill leachate: Performances and mechanisms

A novel vertical dual-loop reactor (VDLR) was developed to start and conduct a single-stage partial nitritation (PN) and anammox (PN/A) process for treating landfill leachate. Results showed that the total nitrogen (TN) removal reached 1.54 kg N/m3 center dot d in the VDLR. It exhibited excellent mixing uniformity and buffer performance, which can increase the nitrogen removal performance up to 42.1 % via the improvement of anammox granular sludge activity (a particle size of 0.5-1 mm). Mass balance and microbial analysis indicated that the VDLR achieved efficient TN removal via anammox (99.24 %) and AOB (Nitrosomonas and Ellin6067) and anAOB (Candidatus kuenenia) played a vital role in this process