TripleNet: A Low Computing Power Platform of Low-Parameter Network

With the excellent performance of deep learning technology in the field of computer vision, convolutional neural network (CNN) architecture has become the main backbone of computer vision task technology. With the widespread use of mobile devices, neural network models based on platforms with low computing power are gradually being paid attention. This paper proposes a lightweight convolutional neural network model, TripleNet, an improved convolutional neural network based on HarDNet and ThreshNet, inheriting the advantages of small memory usage and low power consumption of the mentioned two models. TripleNet uses three different convolutional layers combined into a new model architecture, which has less number of parameters than that of HarDNet and ThreshNet. CIFAR-10 and SVHN datasets were used for image classification by employing HarDNet, ThreshNet, and our proposed TripleNet for verification. Experimental results show that, compared with HarDNet, TripleNet's parameters are reduced by 66% and its accuracy rate is increased by 18%; compared with ThreshNet, TripleNet's parameters are reduced by 37% and its accuracy rate is increased by 5%.Comment: 4 pages, 2 figure

Three-stage binarization of color document images based on discrete wavelet transform and generative adversarial networks

The efficient segmentation of foreground text information from the background in degraded color document images is a hot research topic. Due to the imperfect preservation of ancient documents over a long period of time, various types of degradation, including staining, yellowing, and ink seepage, have seriously affected the results of image binarization. In this paper, a three-stage method is proposed for image enhancement and binarization of degraded color document images by using discrete wavelet transform (DWT) and generative adversarial network (GAN). In Stage-1, we use DWT and retain the LL subband images to achieve the image enhancement. In Stage-2, the original input image is split into four (Red, Green, Blue and Gray) single-channel images, each of which trains the independent adversarial networks. The trained adversarial network models are used to extract the color foreground information from the images. In Stage-3, in order to combine global and local features, the output image from Stage-2 and the original input image are used to train the independent adversarial networks for document binarization. The experimental results demonstrate that our proposed method outperforms many classical and state-of-the-art (SOTA) methods on the Document Image Binarization Contest (DIBCO) dataset. We release our implementation code at https://github.com/abcpp12383/ThreeStageBinarization

CCDWT-GAN: Generative Adversarial Networks Based on Color Channel Using Discrete Wavelet Transform for Document Image Binarization

To efficiently extract the textual information from color degraded document images is an important research topic. Long-term imperfect preservation of ancient documents has led to various types of degradation such as page staining, paper yellowing, and ink bleeding; these degradations badly impact the image processing for information extraction. In this paper, we present CCDWT-GAN, a generative adversarial network (GAN) that utilizes the discrete wavelet transform (DWT) on RGB (red, green, blue) channel splited images. The proposed method comprises three stages: image preprocessing, image enhancement, and image binarization. This work conducts comparative experiments in the image preprocessing stage to determine the optimal selection of DWT with normalization. Additionally, we perform an ablation study on the results of the image enhancement stage and the image binarization stage to validate their positive effect on the model performance. This work compares the performance of the proposed method with other state-of-the-art (SOTA) methods on DIBCO and H-DIBCO ((Handwritten) Document Image Binarization Competition) datasets. The experimental results demonstrate that CCDWT-GAN achieves a top two performance on multiple benchmark datasets, and outperforms other SOTA methods

Inductorless CMOS Receiver Front-End Circuits for 10-Gb/s Optical Communications

[[abstract]]In this paper, a 10-Gb/s inductorless CMOS receiver front end is presented, including a transimpedance amplifier and a limiting amplifier. The transimpedance amplifier incorporates Regulated Cascode (RGC), active-inductor peaking, and intersecting active feedback circuits to achieve a transimpedance gain of 56 dB and a bandwidth of 8.27 GHz with a power dissipation of 35 mW. The limiting amplifier employs interleaving active feedback to achieve a differential voltage gain of 44.5 dB and a bandwidth of 10.3 GHz while consuming 226 mW. Both circuits are realized in 0.18- m CMOS technology with a 1.8-V supply.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙

Exposure to Secondhand Smoke and Risk of Tuberculosis: Prospective Cohort Study

Background: Prospective evidence on the association between secondhand-smoke exposure and tuberculosis is limited. Methods: We included 23,827 never smokers from two rounds (2001 and 2005) of Taiwan National Health Interview Survey. Information on exposure to secondhand smoke at home as well as other sociodemographic and behavioral factors was collected through in-person interview. The participants were prospectively followed for incidence of tuberculosis through cross-matching the survey database to the national tuberculosis registry of Taiwan. Results: A total of 85 cases of active tuberculosis were identified after a median follow-up of 7.0 years. The prevalence of exposure to secondhand smoke at home was 41.8% in the study population. In the multivariable Cox proportional hazards analysis, secondhand smoke was not associated with active tuberculosis (adjusted hazard ratio [HR], 1.03; 95% CI, 0.64 to 1.64). In the subgroup analysis, the association between secondhand smoke and tuberculosis decreased with increasing age; the adjusted HR for those = 18 and = 40 and = 60 years old was 8.48 (0.77 to 93.56), 2.29 (0.75 to 7.01), 1.33 (0.58 to 3.01), and 0.66 (0.35 to 1.23) respectively. Results from extensive sensitivity analyses suggested that potential misclassification of secondhand-smoke exposure would not substantially affect the observed associations. Conclusions: The results from this prospective cohort study did not support an overall association between secondhand smoke and tuberculosis. However, the finding that adolescents might be particularly susceptible to secondhand smoke's effect warrants further investigation

Designing primers and evaluation of the efficiency of propidium monoazide – Quantitative polymerase chain reaction for counting the viable cells of Lactobacillus gasseri and Lactobacillus salivarius

AbstractThe purpose of this study is to evaluate the efficiency of using propidium monoazide (PMA) real-time quantitative polymerase chain reaction (qPCR) to count the viable cells of Lactobacillus gasseri and Lactobacillus salivarius in probiotic products. Based on the internal transcription spacer and 23S rRNA genes, two primer sets specific for these two Lactobacillus species were designed. For a probiotic product, the total deMan Rogosa Sharpe plate count was 8.65±0.69 log CFU/g, while for qPCR, the cell counts of L. gasseri and L. salivarius were 8.39±0.14 log CFU/g and 8.57±0.24 log CFU/g, respectively. Under the same conditions, for its heat-killed product, qPCR counts for L. gasseri and L. salivarius were 6.70±0.16 log cells/g and 7.67±0.20 log cells/g, while PMA-qPCR counts were 5.33±0.18 log cells/g and 5.05±0.23 log cells/g, respectively. For cell dilutions with a viable cell count of 8.5 log CFU/mL for L. gasseri and L. salivarius, after heat killing, the PMA-qPCR count for both Lactobacillus species was near 5.5 log cells/mL. When the PMA-qPCR counts of these cell dilutions were compared before and after heat killing, although some DNA might be lost during the heat killing, significant qPCR signals from dead cells, i.e., about 4–5 log cells/mL, could not be reduced by PMA treatment. Increasing PMA concentrations from 100 μM to 200 μM or light exposure time from 5 minutes to 15 minutes had no or, if any, only minor effect on the reduction of qPCR signals from their dead cells. Thus, to differentiate viable lactic acid bacterial cells from dead cells using the PMA-qPCR method, the efficiency of PMA to reduce the qPCR signals from dead cells should be notable

MCRS2 represses the transactivation activities of Nrf1

<p>Abstract</p> <p>Background</p> <p>Nrf1 [p45 nuclear factor-erythroid 2 (p45 NF-E2)-related factor 1], a member of the CNC-bZIP (CNC basic region leucine zipper) family, is known to be a transcriptional activator by dimerization with distinct partners, such as Maf, FosB, c-Jun, JunD, etc. The transcriptional roles of CNC-bZIP family are demonstrated to be involved in globin gene expression as well as the antioxidant response. For example, CNC-bZIP factors can regulate the expression of detoxification proteins through AREs, such as expression of human gamma-glutamylcysteine synthetases (GCS), glutathione S-transferases (GST), UDP-glucuronosyl transferase (UDP-GT), NADP (H) quinone oxidoreductase (NQOs), etc. To further explore other factor(s) in cells related to the function of Nrf1, we performed a yeast two-hybrid screening assay to identify any Nrf1-interacting proteins. In this study, we isolated a cDNA encoding residues 126–475 of MCRS2 from the HeLa cell cDNA library. Some functions of MCRS1 and its splice variant-MSP58 and MCRS2 have been previously identified, such as transforming, nucleolar sequestration, ribosomal gene regulation, telomerase inhibition activities, etc. Here, we demonstrated MCRS2 can function as a repressor on the Nrf1-mediated transactivation using both in vitro and in vivo systems.</p> <p>Results</p> <p>To find other proteins interacting with the CNC bZIP domain of Nrf1, the CNC-bZIP region of Nrf1 was used as a bait in a yeast two-hybrid screening assay. MCRS2, a splicing variant of p78/MCRS1, was isolated as the Nrf1-interacting partner from the screenings. The interaction between Nrf1 and MCRS2 was confirmed <it>in vitro </it>by GST pull-down assays and <it>in vivo </it>by co-immunoprecipitation. Further, the Nrf1-MCRS2 interaction domains were mapped to the residues 354–447 of Nrf1 as well as the residues 314–475 of MCRS2 respectively, by yeast two-hybrid and GST pull-down assays. By immunofluorescence, MCRS2-FLAG was shown to colocalize with HA-Nrf1 in the nucleus and didn't result in the redistribution of Nrf1. This suggested the existence of Nrf1-MCRS2 complex in vivo. To further confirm the biological function, a reporter driven by CNC-bZIP protein binding sites was also shown to be repressed by MCRS2 in a transient transfection assay. An artificial reporter gene activated by LexA-Nrf1 was also specifically repressed by MCRS2.</p> <p>Conclusion</p> <p>From the results, we showed MCRS2, a new Nrf1-interacting protein, has a repression effect on Nrf1-mediated transcriptional activation. This was the first ever identified repressor protein related to Nrf1 transactivation.</p

VoiceBank-2023: A Multi-Speaker Mandarin Speech Corpus for Constructing Personalized TTS Systems for the Speech Impaired

Services of personalized TTS systems for the Mandarin-speaking speech impaired are rarely mentioned. Taiwan started the VoiceBanking project in 2020, aiming to build a complete set of services to deliver personalized Mandarin TTS systems to amyotrophic lateral sclerosis patients. This paper reports the corpus design, corpus recording, data purging and correction for the corpus, and evaluations of the developed personalized TTS systems, for the VoiceBanking project. The developed corpus is named after the VoiceBank-2023 speech corpus because of its release year. The corpus contains 29.78 hours of utterances with prompts of short paragraphs and common phrases spoken by 111 native Mandarin speakers. The corpus is labeled with information about gender, degree of speech impairment, types of users, transcription, SNRs, and speaking rates. The VoiceBank-2023 is available by request for non-commercial use and welcomes all parties to join the VoiceBanking project to improve the services for the speech impaired.Comment: submitted to 26th International Conference of the ORIENTAL-COCOSD