DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDN

The optimal multicast tree problem in the Software-Defined Networking (SDN) multicast routing is an NP-hard combinatorial optimization problem. Although existing SDN intelligent solution methods, which are based on deep reinforcement learning, can dynamically adapt to complex network link state changes, these methods are plagued by problems such as redundant branches, large action space, and slow agent convergence. In this paper, an SDN intelligent multicast routing algorithm based on deep hierarchical reinforcement learning is proposed to circumvent the aforementioned problems. First, the multicast tree construction problem is decomposed into two sub-problems: the fork node selection problem and the construction of the optimal path from the fork node to the destination node. Second, based on the information characteristics of SDN global network perception, the multicast tree state matrix, link bandwidth matrix, link delay matrix, link packet loss rate matrix, and sub-goal matrix are designed as the state space of intrinsic and meta controllers. Then, in order to mitigate the excessive action space, our approach constructs different action spaces at the upper and lower levels. The meta-controller generates an action space using network nodes to select the fork node, and the intrinsic controller uses the adjacent edges of the current node as its action space, thus implementing four different action selection strategies in the construction of the multicast tree. To facilitate the intelligent agent in constructing the optimal multicast tree with greater speed, we developed alternative reward strategies that distinguish between single-step node actions and multi-step actions towards multiple destination nodes

SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks

We introduce SwiftSage, a novel agent framework inspired by the dual-process theory of human cognition, designed to excel in action planning for complex interactive reasoning tasks. SwiftSage integrates the strengths of behavior cloning and prompting large language models (LLMs) to enhance task completion performance. The framework comprises two primary modules: the Swift module, representing fast and intuitive thinking, and the Sage module, emulating deliberate thought processes. The Swift module is a small encoder-decoder LM fine-tuned on the oracle agent's action trajectories, while the Sage module employs LLMs such as GPT-4 for subgoal planning and grounding. We develop a heuristic method to harmoniously integrate the two modules, resulting in a more efficient and robust problem-solving process. In 30 tasks from the ScienceWorld benchmark, SwiftSage significantly outperforms other methods such as SayCan, ReAct, and Reflexion, demonstrating its effectiveness in solving complex real-world tasks.Comment: Project website: https://yuchenlin.xyz/swiftsage

Soybean-VCF2Genomes: a database to identify the closest accession in soybean germplasm collection

Background The development of next generation sequencer (NGS) and the analytical methods allowed the researchers to profile their samples more precisely and easier than before. Especially for agriculture, the certification of the genomic background of their plant materials would be important for the reliability of seed market and stable yield as well as for quarantine procedure. However, the analysis of NGS data is still difficult for non-computational researchers or breeders to verify their samples because majority of current softwares for NGS analysis require users to access unfamiliar Linux environment. Main body Here, we developed a web-application, Soybean-VCF2Genomes, http://pgl.gnu.ac.kr/soy_vcf2genome/ to map single sample variant call format (VCF) file against known soybean germplasm collection for identification of the closest soybean accession. Based on principal component analysis (PCA), we simplified genotype matrix for lowering computational burden while maintaining accurate clustering. With our web-application, users can simply upload single sample VCF file created by more than 10x resequencing strategy to find the closest samples along with linkage dendrogram of the reference genotype matrix. Conclusion The information of the closest soybean cultivar will allow breeders to estimate relative germplasmic position of their query sample to determine soybean breeding strategies. Moreover, our VCF2Genomes scheme can be extended to other plant species where the whole genome sequences of core collection are publicly available.Publication of this article has been funded by Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ01333901) Rural Development Administration, Republic of Korea and the fund of research promotion program, Gyeongsang National University, 2017

The Draft Genome of an Octocoral, Dendronephthya gigantea

Coral reefs composed of stony corals are threatened by global marine environmental changes. However, soft coral communities of octocorallian species, appear more resilient. The genomes of several cnidarians species have been published, including from stony corals, sea anemones, and hydra. To fill the phylogenetic gap for octocoral species of cnidarians, we sequenced the octocoral, Dendronephthya gigantea, a nonsymbiotic soft coral, commonly known as the carnation coral. The D. gigantea genome size is similar to 276 Mb. A high-quality genome assembly was constructed from PacBio long reads (29.85 Gb with 108x coverage) and Illumina short paired-end reads (35.54 Gb with 128x coverage) resulting in the highest N50 value (1.4 Mb) reported thus far among cnidarian genomes. About 12% of the genome is repetitive elements and contained 28,879 predicted protein-coding genes. This gene set is composed of 94% complete BUSCO ortholog benchmark genes, which is the second highest value among the cnidarians, indicating high quality. Based on molecular phylogenetic analysis, octocoral and hexacoral divergence times were estimated at 544 MYA. There is a clear difference in Hox gene composition between these species: unlike hexacorals, the Antp superclass Evx gene was absent in D. gigantea. Here, we present the first genome assembly of a nonsymbiotic octocoral, D. gigantea to aid in the comparative genomic analysis of cnidarians, including stony and soft corals, both symbiotic and nonsymbiotic. The D. gigantea genome may also provide clues to mechanisms of differential coping between the soft and stony corals in response to scenarios of global warming

Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild-type primary glioblastoma

Background Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fishers exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a highly heterogeneous TMZ-response pattern within each GBM patient usingin vitro TMZ screening and genomic characterization of multisector GSCs. Lastly, the prediction model that evaluates the TMZ efficacy for primary IDH-wt GBMs was developed into a webserver for public usage (http://www.wang-lab-hkust.com:3838/TMZEP) Conclusions We identified molecular characteristics associated to TMZ sensitivity, and illustrate the potential clinical value of a ML model trained from pharmacogenomic profiling of patient-derived GSC against IDH-wt GBMs

Strategies of developing Transition Metal-Based Heterogeneous electrocatalyst for efficient energy conversion reactions

School of Energy and Chemical Engineering (Energy Engineering)clos

SoyDBean: a database for SNPs reconciliation by multiple versions of soybean reference genomes

Abstract Due to the development of sequence technology and decreased cost, many whole genome sequences have been obtained. As a result, extensive genetic variations have been discovered from many populations and germplasms to understand the genetic diversity of soybean (Glycine max [L.] Merr.). However, assessing the quality of variation is essential because the published variants were collected using different bioinformatic methods and parameters. Furthermore, despite the enhanced genome contiguity and more efficient filling of “N” stretches in the new reference genome, there remains a dearth of endeavors to verify the caliber of variations present in it. The primary goal of this research was to discern a dependable set of SNPs that can withstand reconciliation across multiple reference genomes. Additionally, the investigation aimed to reconfirm the variations through the utilization of numerous whole genome sequencing data obtained from publicly available databases. Based on the result, we created datasets that comprised the thoroughly verified SNP coordinates between the reference assemblies. The resulting “SoyDBean” database is now publicly accessible through the following URL: http://soydbean.plantprofile.net/