Study on the Translation Initiation Mechanism on Picornaviral RNA.

To understand the initiation of translation of picornavirus RNA, cell-free translation of the RNA of encephalomyocarditis virus (EMCV) was examined after hybridization of chemically synthesized cDNA fragments to different sites of the 5\sp\prime untranslated region (5\sp\prime UTR) of the viral RNA and after deletion of specific segments of the 5\sp\prime UTR by RNase H digestion. In addition, translation competition experiments, using RNA fragments derived from different parts of the 5\sp\prime UTR, were performed. The results of these experiments are summarized as follows: (i) Binding of cDNA fragments to sequences between the 5\sp\prime terminus and nucleotide 338 caused no effect on translation of the viral RNA; (ii) binding of cDNA fragments to the sequence between nucleotides 420 and 449 caused a slight inhibition; (iii) binding of fragments to sites between nucleotides 450 and the initiator AUG codon (nucleotide 834) caused strong inhibition; (iv) deletion from the 5\sp\prime terminus to nucleotide 338 caused no effect on translation of the coding region of the RNA, whereas deletion from the 5\sp\prime terminus to nucleotide 450 or beyond totally abolished translation of the coding region; and (v) presence of a 5\sp\prime fragment (from 5\sp\prime terminus to approximate nucleotide 338) caused no effect on translation of EMCV RNA, but presence of either of two other fragments, one from approximately nucleotides 338 to 589, the second from approximately nucleotides 338 to 813, caused inhibition of translation. These results together indicate that the first part of the 5\sp\prime UTR, at least to nucleotide 338, is not required for EMCV RNA translation but the sequence near, and possibly also sequences beyond nucleotide 450 are critical for translation of the viral RNA. For the purpose of future more detailed analysis of the sequence elements that are important for translational initiation, cDNAs corresponding to the 5\sp\prime UTR and a beginning portion of the viral protein coding region of the viral RNA were synthesized and cloned, and two sets of sequential deletion mutants were constructed from the cloned cDNA. Results from an initial in vitro translation study of the synthetic mRNAs from some of these deletion clones are presented

Development of KAISTSAT-4 Expanding the Role of Small Satellite for Scientific Research

The fourth Korean small satellite, KAISTSAT-4, is under development by Satellite Technology Research Center (SaTReC) of the Korea Advanced Institute of Science and Technology (KAIST). The KAISTSAT-4 program was commenced on October 1998 with multiple mission objectives, which include exploring space science, deploying satellite-based data collection system and development of precision star sensor. Despite severe constraints on mass and size, these advanced science and engineering payloads are expected to deliver various useful results and exhibit the unique role of small satellite. We present an overview of the KAISTSAT-4 mission and describe its current status. Finally the prospect of future small satellite programs is briefly introduced

MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark

Multi-target multi-camera tracking is a crucial task that involves identifying and tracking individuals over time using video streams from multiple cameras. This task has practical applications in various fields, such as visual surveillance, crowd behavior analysis, and anomaly detection. However, due to the difficulty and cost of collecting and labeling data, existing datasets for this task are either synthetically generated or artificially constructed within a controlled camera network setting, which limits their ability to model real-world dynamics and generalize to diverse camera configurations. To address this issue, we present MTMMC, a real-world, large-scale dataset that includes long video sequences captured by 16 multi-modal cameras in two different environments - campus and factory - across various time, weather, and season conditions. This dataset provides a challenging test-bed for studying multi-camera tracking under diverse real-world complexities and includes an additional input modality of spatially aligned and temporally synchronized RGB and thermal cameras, which enhances the accuracy of multi-camera tracking. MTMMC is a super-set of existing datasets, benefiting independent fields such as person detection, re-identification, and multiple object tracking. We provide baselines and new learning setups on this dataset and set the reference scores for future studies. The datasets, models, and test server will be made publicly available.Comment: Accepted on CVPR 202