Two-parameter Hong-Ou-Mandel dip

A modification of the standard Hong-Ou-Mandel interferometer is proposed which allows one to replicate the celebrated coincidence dip in the case of two-independent delay parameters. In the ideal case where such delays are sufficiently stable with respect to the mean wavelength of the pump source, properly symmetrized input bi-photon states allow one to pinpoint their values through the identification of a zero in the coincidence counts, a feature that cannot be simulated by semiclassical inputs having the same spectral properties. Besides, in the presence of fluctuating parameters the zero in the coincidences is washed away: still the bi-photon state permits to recover the values of parameters with a visibility which is higher than the one allowed by semiclassical sources. The detrimental role of loss and dispersion is also analyzed and an application in the context of quantum positioning is presented.Comment: 16 pages,9 figure

Exclusive Hong-Ou-Mandel zero-coincidence point

A generalized multi-parameter Hong-Ou-Mandel interferometer is presented which extends the conventional "Mandel dip" configuration to the case where a symmetric biphoton source is used to monitor the contemporary presence of k independent time-delays. Our construction results in a two-input/two-output setup, obtained by concatenating 50:50 beam splitters with a collection of adjustable achromatic wave-plates. For k=1,2 and k=4 explicit examples can be exhibited that prove the possibility of uniquely linking the zero value of the coincidence counts registered at the output of the interferometer, with the contemporary absence of all the time-delays. Interestingly enough the same result cannot be extended to k=3. Besides, the sensitivity of the interferometer is analyzed when the time-delays are affected by the fluctuations over time-scales that are larger than the inverse of the frequency of the pump used to generate the biphoton state.Comment: 12 pages, 5 figure

Character Segmentation System Based on C# Design and Implementation

AbstractAt present, most of the OCR recognizing through individual character, thus the quality of character segmentation is the key point to affect the quality of OCR recognition system. This paper introduces the formula of projective method in analysis of preliminary segmentation for images. Moreover it applied analysis for connected spatial domain, the correct results shows that writing image well matched. After two analyses and segmentation, characters can be segmented correctly. In order to provide useful solutions to these two problems that characters keying must be performed rapidly and documents digitizing can be conserved for a long time. Therefore, we must place emphasis on the research and development of the character segmentation

Ea-GANs: Edge-Aware Generative Adversarial Networks for Cross-Modality MR Image Synthesis

Magnetic resonance (MR) imaging is a widely used medical imaging protocol that can be configured to provide different contrasts between the tissues in human body. By setting different scanning parameters, each MR imaging modality reflects the unique visual characteristic of scanned body part, benefiting the subsequent analysis from multiple perspectives. To utilize the complementary information from multiple imaging modalities, cross-modality MR image synthesis has aroused increasing research interest recently. However, most existing methods only focus on minimizing pixel/voxel-wise intensity difference but ignore the textural details of image content structure, which affects the quality of synthesized images. In this paper, we propose edge-aware generative adversarial networks (Ea-GANs) for cross-modality MR image synthesis. Specifically, we integrate edge information, which reflects the textural structure of image content and depicts the boundaries of different objects in images, to reduce this gap. Corresponding to different learning strategies, two frameworks are proposed, i.e., a generator-induced Ea-GAN (gEa-GAN) and a discriminator-induced Ea-GAN (dEa-GAN). The gEa-GAN incorporates the edge information via its generator, while the dEa-GAN further does this from both the generator and the discriminator so that the edge similarity is also adversarially learned. In addition, the proposed Ea-GANs are 3D-based and utilize hierarchical features to capture contextual information. The experimental results demonstrate that the proposed Ea-GANs, especially the dEa-GAN, outperform multiple state-of-the-art methods for cross-modality MR image synthesis in both qualitative and quantitative measures. Moreover, the dEa-GAN also shows excellent generality to generic image synthesis tasks on benchmark datasets about facades, maps, and cityscapes

Role of Nrf2 in HLC

Generation of hepatocytes from human adipose-derived mesenchymal stem cells (hADSCs) could be a promising alternative source of human hepatocytes. However, mechanisms to differentiate hepatocytes from hADSCs are not fully elucidated. We have previously demonstrated that our three-step differentiation protocol with glycogen synthase kinase (GSK) 3 inhibitor was effective to improve hepatocyte functions. In this study, we investigated the activation of the nuclear factor erythroid-2 related factor 2 (Nrf2) on hADSCs undergoing differentiation to HLC (hepatocyte-like cells). Our three-step differentiation protocol was applied for 21 days (Step 1 : day 1-6, Step2 : day 6-11, Step3 : day 11-21). Our results show that significant nuclear translocation of Nrf2 occurred from day 11 until the end of HLC differentiation. Nuclear translocation of Nrf2 and CYP3A4 activity in the GSK3 inhibitor-treated group was obviously higher than that in Activin A-treated groups at day 11. The maturation of HLCs was delayed in Nrf2-siRNA group compared to control group. Furthermore, CYP3A4 activity in Nrf2-siRNA group was decreased at the almost same level in Activin A-treated group. Nrf2 translocation might enhance the function of HLC and be a target for developing highly functional HLC

Nrf2 signaling in sorafenib-resistant HCC

Background and aim As a multiple tyrosine kinase inhibitor, sorafenib is widely used to treat hepatocellular carcinoma (HCC), but patients frequently face resistance problems. Because the mechanism controlling sorafenib-resistance is not well understood, this study focused on the connection between tumor characteristics and the Nrf2 signaling pathway in a sorafenib-resistant HCC cell line. Methods A sorafenib-resistant HCC cell line (Huh7) was developed by increasing the dose of sorafenib in the culture medium until the target concentration was reached. Cell morphology, migration/invasion rates, and expression of stemness-related and ATP-binding cassette (ABC) transporter genes were compared between sorafenib-resistant Huh7 cells and parental Huh7 cells. Next, a small interfering RNA was used to knock down Nrf2 expression in sorafenib-resistant Huh7 cells, after which cell viability, stemness, migration, and ABC transporter gene expression were examined again. Results Proliferation, migration, and invasion rates of sorafenib-resistant Huh7 cells were significantly increased relative to the parental cells with or without sorafenib added to the medium. The expression levels of stemness markers and ABC transporter genes were up-regulated in sorafenib-resistant cells. After Nrf2 was knocked down in sorafenib-resistant cells, cell migration and invasion rates were reduced, and expression levels of stemness markers and ABC transporter genes were reduced. Conclusion Nrf2 signaling promotes cancer stemness, migration, and expression of ABC transporter genes in sorafenib-resistant HCC cells

Make-A-Voice: Unified Voice Synthesis With Discrete Representation

Various applications of voice synthesis have been developed independently despite the fact that they generate "voice" as output in common. In addition, the majority of voice synthesis models currently rely on annotated audio data, but it is crucial to scale them to self-supervised datasets in order to effectively capture the wide range of acoustic variations present in human voice, including speaker identity, emotion, and prosody. In this work, we propose Make-A-Voice, a unified framework for synthesizing and manipulating voice signals from discrete representations. Make-A-Voice leverages a "coarse-to-fine" approach to model the human voice, which involves three stages: 1) semantic stage: model high-level transformation between linguistic content and self-supervised semantic tokens, 2) acoustic stage: introduce varying control signals as acoustic conditions for semantic-to-acoustic modeling, and 3) generation stage: synthesize high-fidelity waveforms from acoustic tokens. Make-A-Voice offers notable benefits as a unified voice synthesis framework: 1) Data scalability: the major backbone (i.e., acoustic and generation stage) does not require any annotations, and thus the training data could be scaled up. 2) Controllability and conditioning flexibility: we investigate different conditioning mechanisms and effectively handle three voice synthesis applications, including text-to-speech (TTS), voice conversion (VC), and singing voice synthesis (SVS) by re-synthesizing the discrete voice representations with prompt guidance. Experimental results demonstrate that Make-A-Voice exhibits superior audio quality and style similarity compared with competitive baseline models. Audio samples are available at https://Make-A-Voice.github.i

BAFF/NFκB経路はソラフェニブ耐性肝癌と癌関連線維芽細胞の相互作用に重要である

The tumor microenvironment affects malignancy in hepatocellular carcinoma (HCC) cells, and cancer-associated fibroblasts (CAFs) play an important role in the microenvironment. As recent studies indicated a difference between CAFs isolated from chemoresistant and non-resistant cancer tissues, therefore we investigated the intracellular mechanism in resistant HCC co-cultured CAFs and interactions between these CAFs with cancer cells. We established a sorafenib-resistant (SR) Huh7 (human HCC) cell line, and characterized it with cytokine assays, then developed CAFs by co-culturing human hepatic stellate cells with resistant or parental Huh7 cells. The 2 types of CAFs were co-cultured with parental Huh7 cells, thereafter the cell viability of these Huh7 cells was checked under sorafenib treatment. The SR Huh7 (Huh7SR) cells expressed increased B-cell activating factor (BAFF), which promoted high expression of CAF-specific markers in Huh7SR-co-cultured CAFs, showed activated BAFF, BAFF-R, and downstream of the NFκB-Nrf2 pathway, and aggravated invasion, migration, and drug resistance in co-cultured Huh7 cells. When we knocked down BAFF expression in Huh7SR cells, the previously increased malignancy and BAFF/NFκB axis in Huh7SR-co-cultured CAFs reversed, and enhanced chemoresistance in co-cultured Huh7 cells returned as well. In conclusion, the BAFF/NFκB pathway was activated in CAFs co-cultured with cell-culture medium from resistant Huh7, which promoted chemoresistance, and increased the malignancy in co-cultured non-resistant Huh7 cells. This suggests that the BAFF/NFκB axis in CAFs might be a potential therapeutic target in chemoresistance of HCC