Semantic Map Guided Synthesis of Wireless Capsule Endoscopy Images using Diffusion Models

Wireless capsule endoscopy (WCE) is a non-invasive method for visualizing the gastrointestinal (GI) tract, crucial for diagnosing GI tract diseases. However, interpreting WCE results can be time-consuming and tiring. Existing studies have employed deep neural networks (DNNs) for automatic GI tract lesion detection, but acquiring sufficient training examples, particularly due to privacy concerns, remains a challenge. Public WCE databases lack diversity and quantity. To address this, we propose a novel approach leveraging generative models, specifically the diffusion model (DM), for generating diverse WCE images. Our model incorporates semantic map resulted from visualization scale (VS) engine, enhancing the controllability and diversity of generated images. We evaluate our approach using visual inspection and visual Turing tests, demonstrating its effectiveness in generating realistic and diverse WCE images

Rewarded meta-pruning: Meta Learning with Rewards for Channel Pruning

Convolutional Neural Networks (CNNs) have a large number of parameters and take significantly large hardware resources to compute, so edge devices struggle to run high-level networks. This paper proposes a novel method to reduce the parameters and FLOPs for computational efficiency in deep learning models. We introduce accuracy and efficiency coefficients to control the trade-off between the accuracy of the network and its computing efficiency. The proposed Rewarded meta-pruning algorithm trains a network to generate weights for a pruned model chosen based on the approximate parameters of the final model by controlling the interactions using a reward function. The reward function allows more control over the metrics of the final pruned model. Extensive experiments demonstrate superior performances of the proposed method over the state-of-the-art methods in pruning ResNet-50, MobileNetV1, and MobileNetV2 networks

Co-occurrence matrix analysis-based semi-supervised training for object detection

One of the most important factors in training object recognition networks using convolutional neural networks (CNNs) is the provision of annotated data accompanying human judgment. Particularly, in object detection or semantic segmentation, the annotation process requires considerable human effort. In this paper, we propose a semi-supervised learning (SSL)-based training methodology for object detection, which makes use of automatic labeling of un-annotated data by applying a network previously trained from an annotated dataset. Because an inferred label by the trained network is dependent on the learned parameters, it is often meaningless for re-training the network. To transfer a valuable inferred label to the unlabeled data, we propose a re-alignment method based on co-occurrence matrix analysis that takes into account one-hot-vector encoding of the estimated label and the correlation between the objects in the image. We used an MS-COCO detection dataset to verify the performance of the proposed SSL method and deformable neural networks (D-ConvNets) as an object detector for basic training. The performance of the existing state-of-the-art detectors (DConvNets, YOLO v2, and single shot multi-box detector (SSD)) can be improved by the proposed SSL method without using the additional model parameter or modifying the network architecture.Comment: Submitted to International Conference on Image Processing (ICIP) 201

The expression and cellular localization of phospholipase D isozymes in the developing mouse testis

To examine the involvement of phospholipase D (PLD) isozymes in postnatal testis development, the expression of PLD1 and PLD2 was examined in the mouse testis at postnatal weeks 1, 2, 4, and 8 using Western blot analysis and immunohistochemistry. The expression of both PLD1 and PLD2 increased gradually with development from postnatal week 1 to 8. Immunohistochemically, PLD immunoreactivity was detected in some germ cells in the testis and interstitial Leydig cells at postnatal week 1. PLD was mainly detected in the spermatocytes and residual bodies of spermatids in the testis after 8 weeks after birth. The intense immunostaining of PLD in Leydig cells remained unchanged by postnatal week 8. These findings suggest that PLD isozymes are involved in the spermatogenesis of the mouse testis

Gamma-ray irradiation stimulates the expression of caveolin-1 and GFAP in rat spinal cord: a study of immunoblot and immunohistochemistry

We studied the expression of caveolin-1 in the spinal cords of rats using 60Co γ-ray irradiation (single dose of 8 Gray (Gy)) in order to determine the possible involvement of caveolin-1 in the tissues of the central nervous system after irradiation. Spinal cords sampled at days 1, 4, and 9 post-irradiation (PI) (n = 5 per each time point) were analyzed by Western blot and immunohistochemistry. Western blot analysis showed that the expression of caveolin-1 was significantly increased at day 1 PI (p < 0.05), and returned to the level of normal control rats on days 4 and 9 PI. Immunohistochemistry showed that caveolin-1 immunoreactivity was enhanced in some glial cells, vascular endothelial cells, and neurons in the spinal cords. The increased expression of glial fibrillary acidic protein (GFAP), a marker for an astroglial reaction, was consistent with that of caveolin-1. In addition, caveolin-1 was co-localized in hypertrophied GFAP-positive astrocytes. Taking all these facts into consideration, we postulate that irradiation induces the increased expression of caveolin-1 in cells of the central nervous system, and that its increased expression in astrocytes may contribute to hypertrophy of astrocytes in the spinal cord after irradiation. The precise role of caveolin-1 in the spinal cords should be studied further

Piezoelectric Ceramics with High d33 Constants and Their Application to Film Speakers

A multilayer piezoelectric material was fabricated using piezoelectric materials with low-temperature sintering capabilities and high piezoelectric coefficients to develop a functionally superior piezoelectric speaker with a large-displacement deformation. A soft relaxor was utilized to prepare the component materials, with the optimized composition of the investigated piezoelectric ceramics represented by 0.2Pb((Zn0.8Ni0.2)13Nb23)O3−0.8Pb(Zr0.5Ti0.5)O3. Li2CO3 was added to assist the low-temperature sintering conducted at 875 °C, which yielded a multilayer piezoelectric material with superior properties (d33&nbsp;= 500 pC N−1, kp&nbsp;= 0.63, g33&nbsp;= 44 mV N−1). A multilayer piezoelectric actuator with a single-layer thickness of ~40 µm and dimensions of 12 × 16 mm2 was fabricated by tape casting the prepared green sheets. Finite element analysis revealed that the use of a PEEK film and a smaller silicone–rubber film as a composite in the diaphragm realized optimal frequency-response characteristics; the vibrations generated by the piezoelectric element were amplified. The optimal structure obtained via simulations was applied to fabricate an actual piezoelectric speaker with dimensions of 20 × 24 × 1 mm3. The actual measurements exhibited a sound pressure level of ~75 dB and a total harmonic distortion ≤15% in the audible frequency range (250–20,000 Hz) at an applied voltage of 5&nbsp;Vp

Tri-Doping of Sol–Gel Synthesized Garnet-Type Oxide Solid-State Electrolyte

The rapidly growing Li-ion battery market has generated considerable demand for Li-ion batteries with improved performance and stability. All-solid-state Li-ion batteries offer promising safety and manufacturing enhancements. Herein, we examine the effect of substitutional doping at three cation sites in garnet-type Li7La3Zr2O12 (LLZO) oxide ceramics produced by a sol–gel synthesis technique with the aim of enhancing the properties of solid-state electrolytes for use in all-solid-state Li-ion batteries. Building on the results of mono-doping experiments with different doping elements and sites—Al, Ga, and Ge at the Li+ site; Rb at the La3+ site; and Ta and Nb at the Zr4+ site—we designed co-doped (Ga, Al, or Rb with Nb) and tri-doped (Ga or Al with Rb and Nb) samples by compositional optimization, and achieved a LLZO ceramic with a pure cubic phase, almost no secondary phase, uniform grain structure, and excellent Li-ion conductivity. The findings extend the current literature on the doping of LLZO ceramics and highlight the potential of the sol–gel method for the production of solid-state electrolytes