Communication-Efficient Split Learning via Adaptive Feature-Wise Compression

This paper proposes a novel communication-efficient split learning (SL) framework, named SplitFC, which reduces the communication overhead required for transmitting intermediate feature and gradient vectors during the SL training process. The key idea of SplitFC is to leverage different dispersion degrees exhibited in the columns of the matrices. SplitFC incorporates two compression strategies: (i) adaptive feature-wise dropout and (ii) adaptive feature-wise quantization. In the first strategy, the intermediate feature vectors are dropped with adaptive dropout probabilities determined based on the standard deviation of these vectors. Then, by the chain rule, the intermediate gradient vectors associated with the dropped feature vectors are also dropped. In the second strategy, the non-dropped intermediate feature and gradient vectors are quantized using adaptive quantization levels determined based on the ranges of the vectors. To minimize the quantization error, the optimal quantization levels of this strategy are derived in a closed-form expression. Simulation results on the MNIST, CIFAR-10, and CelebA datasets demonstrate that SplitFC provides more than a 5.6% increase in classification accuracy compared to state-of-the-art SL frameworks, while they require 320 times less communication overhead compared to the vanilla SL framework without compression

Unbiased Estimator for Distorted Conics in Camera Calibration

In the literature, points and conics have been major features for camera geometric calibration. Although conics are more informative features than points, the loss of the conic property under distortion has critically limited the utility of conic features in camera calibration. Many existing approaches addressed conic-based calibration by ignoring distortion or introducing 3D spherical targets to circumvent this limitation. In this paper, we present a novel formulation for conic-based calibration using moments. Our derivation is based on the mathematical finding that the first moment can be estimated without bias even under distortion. This allows us to track moment changes during projection and distortion, ensuring the preservation of the first moment of the distorted conic. With an unbiased estimator, the circular patterns can be accurately detected at the sub-pixel level and can now be fully exploited for an entire calibration pipeline, resulting in significantly improved calibration. The entire code is readily available from https://github.com/ChaehyeonSong/discocal

TRansPose: Large-Scale Multispectral Dataset for Transparent Object

Transparent objects are encountered frequently in our daily lives, yet recognizing them poses challenges for conventional vision sensors due to their unique material properties, not being well perceived from RGB or depth cameras. Overcoming this limitation, thermal infrared cameras have emerged as a solution, offering improved visibility and shape information for transparent objects. In this paper, we present TRansPose, the first large-scale multispectral dataset that combines stereo RGB-D, thermal infrared (TIR) images, and object poses to promote transparent object research. The dataset includes 99 transparent objects, encompassing 43 household items, 27 recyclable trashes, 29 chemical laboratory equivalents, and 12 non-transparent objects. It comprises a vast collection of 333,819 images and 4,000,056 annotations, providing instance-level segmentation masks, ground-truth poses, and completed depth information. The data was acquired using a FLIR A65 thermal infrared (TIR) camera, two Intel RealSense L515 RGB-D cameras, and a Franka Emika Panda robot manipulator. Spanning 87 sequences, TRansPose covers various challenging real-life scenarios, including objects filled with water, diverse lighting conditions, heavy clutter, non-transparent or translucent containers, objects in plastic bags, and multi-stacked objects. TRansPose dataset can be accessed from the following link: https://sites.google.com/view/transpose-datasetComment: Under revie

Iterative Soft Decoding Algorithm for DNA Storage Using Quality Score and Redecoding

Ever since deoxyribonucleic acid (DNA) was considered as a next-generation data-storage medium, lots of research efforts have been made to correct errors occurred during the synthesis, storage, and sequencing processes using error correcting codes (ECCs). Previous works on recovering the data from the sequenced DNA pool with errors have utilized hard decoding algorithms based on a majority decision rule. To improve the correction capability of ECCs and robustness of the DNA storage system, we propose a new iterative soft decoding algorithm, where soft information is obtained from FASTQ files and channel statistics. In particular, we propose a new formula for log-likelihood ratio (LLR) calculation using quality scores (Q-scores) and a redecoding method which may be suitable for the error correction and detection in the DNA sequencing area. Based on the widely adopted encoding scheme of the fountain code structure proposed by Erlich et al., we use three different sets of sequenced data to show consistency for the performance evaluation. The proposed soft decoding algorithm gives 2.3% ~ 7.0% improvement of the reading number reduction compared to the state-of-the-art decoding method and it is shown that it can deal with erroneous sequenced oligo reads with insertion and deletion errors

Narrowband THz Emission from a Plasma Oscillator Imbedded in a Plasma Density Gradient

A novel method is presented for generating radiation using the beat wave associated with a bi-frequency laser pulse, to excite plasma oscillations in a plasma slab with a density gradient. By resonantly exciting a plasma wave, it can be localised and transformed into a plasma oscillator that produces a beam of radially polarised terahertz radiation. Particle-in-cell simulations and analytic theory are used to demonstrate its main characteristics, which includes narrow bandwidth. The radiator should have useful applications such as terahertz-band particle accelerators and pump-probe experiments

The miR-15b-Smurf2-HSP27 axis promotes pulmonary fibrosis

Background Heat shock protein 27 (HSP27) is overexpressed during pulmonary fibrosis (PF) and exacerbates PF; however, the upregulation of HSP27 during PF and the therapeutic strategy of HSP27 inhibition is not well elucidated. Methods We have developed a mouse model simulating clinical stereotactic body radiotherapy (SBRT) with focal irradiation and validated the induction of RIPF. HSP25 (murine form of HSP27) transgenic (TG) and LLC1-derived orthotropic lung tumor models were also used. Lung tissues of patients with RIPF and idiopathic pulmonary fibrosis, and lung tissues from various fibrotic mouse models, as well as appropriated cell line systems were used. Public available gene expression datasets were used for therapeutic response rate analysis. A synthetic small molecule HSP27 inhibitor, J2 was also used. Results HSP27 expression with its phosphorylated form (pHSP27) increased during PF. Decreased mRNA expression of SMAD-specific E3 ubiquitin-protein ligase 2 (Smurf2), which is involved in ubiquitin degradation of HSP27, was responsible for the increased expression of pHSP27. In addition, increased expression of miRNA15b was identified with decreased expression of Smurf2 mRNA in PF models. Inverse correlation between pHSP27 and Smurf2 was observed in the lung tissues of PF animals, an irradiated orthotropic lung cancer models, and PF tissues from patients. Moreover, a HSP27 inhibitor cross-linked with HSP27 protein to ameliorate PF, which was more effective when targeting the epithelial to mesenchymal transition (EMT) stage of PF. Conclusions Our findings identify upregulation mechanisms of HSP27 during PF and provide a therapeutic strategy for HSP27 inhibition for overcoming PF.This work was supported by grants from the National Research Foundation of Korea, (NRF-2018R1A5A2025286, NRF-2020R1A2C3013255, NRF-2020M2D9A2093974, NRF-2020R1I1A1A01070841, NRF-2020M2D9A2093976 and NRF-2022R1A2C3011611), funded by the Korean government (Ministry of Science and ICT)

Comparative genome analyses of four rice-infecting Rhizoctonia solani isolates reveal extensive enrichment of homogalacturonan modification genes

Background Plant pathogenic isolates of Rhizoctonia solani anastomosis group 1-intraspecific group IA (AG1-IA) infect a wide range of crops causing diseases such as rice sheath blight (ShB). ShB has become a serious disease in rice production worldwide. Additional genome sequences of the rice-infecting R. solani isolates from different geographical regions will facilitate the identification of important pathogenicity-related genes in the fungus. Results Rice-infecting R. solani isolates B2 (USA), ADB (India), WGL (India), and YN-7 (China) were selected for whole-genome sequencing. Single-Molecule Real-Time (SMRT) and Illumina sequencing were used for de novo sequencing of the B2 genome. The genomes of the other three isolates were then sequenced with Illumina technology and assembled using the B2 genome as a reference. The four genomes ranged from 38.9 to 45.0 Mbp in size, contained 9715 to 11,505 protein-coding genes, and shared 5812 conserved orthogroups. The proportion of transposable elements (TEs) and average length of TE sequences in the B2 genome was nearly 3 times and 2 times greater, respectively, than those of ADB, WGL and YN-7. Although 818 to 888 putative secreted proteins were identified in the four isolates, only 30% of them were predicted to be small secreted proteins, which is a smaller proportion than what is usually found in the genomes of cereal necrotrophic fungi. Despite a lack of putative secondary metabolite biosynthesis gene clusters, the rice-infecting R. solani genomes were predicted to contain the most carbohydrate-active enzyme (CAZyme) genes among all 27 fungal genomes used in the comparative analysis. Specifically, extensive enrichment of pectin/homogalacturonan modification genes were found in all four rice-infecting R. solani genomes. Conclusion Four R. solani genomes were sequenced, annotated, and compared to other fungal genomes to identify distinctive genomic features that may contribute to the pathogenicity of rice-infecting R. solani. Our analyses provided evidence that genomic conservation of R. solani genomes among neighboring AGs was more diversified than among AG1-IA isolates and the presence of numerous predicted pectin modification genes in the rice-infecting R. solani genomes that may contribute to the wide host range and virulence of this necrotrophic fungal pathogen.This research was supported by a Ph. D fellowship awarded to D.-Y. Lee by the Monsanto Beachell-Borlaug International Scholarship Program (MBBISP) as well as grants from the National Research Foundation of Korea to YHL (NRF-2020R1A2B5B03096402, NRF-2015M3A9B8028679, and NRF2018R1A5A1023599), the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry through Agricultural Microbiome Program to YHL (918017–04) and the USDA Hatch Project to GLW. KTK and JK is grateful for a graduate fellowship through the Brain Korea 21 Plus Program

Cytosolic calcium regulates cytoplasmic accumulation of TDP-43 through Calpain-A and Importin alpha 3

Cytoplasmic accumulation of TDP-43 in motor neurons is the most prominent pathological feature in amyotrophic lateral sclerosis (ALS). A feedback cycle between nucleocytoplasmic transport (NCT) defect and TDP-43 aggregation was shown to contribute to accumulation of TDP-43 in the cytoplasm. However, little is known about cellular factors that can control the activity of NCT, thereby affecting TDP-43 accumulation in the cytoplasm. Here, we identified via FRAP and optogenetics cytosolic calcium as a key cellular factor controlling NCT of TDP-43. Dynamic and reversible changes in TDP-43 localization were observed in Drosophila sensory neurons during development. Genetic and immunohistochemical analyses identified the cytosolic calcium-Calpain-A-Importin α3 pathway as a regulatory mechanism underlying NCT of TDP-43. In C9orf72 ALS fly models, upregulation of the pathway activity by increasing cytosolic calcium reduced cytoplasmic accumulation of TDP-43 and mitigated behavioral defects. Together, these results suggest the calcium-Calpain-A-Importin α3 pathway as a potential therapeutic target of ALS. © Park et al.1