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Wu, Yanan, Shouliang Qi, Yu Sun, Shuyue Xia, Yudong Yao i Wei Qian. "A vision transformer for emphysema classification using CT images". Physics in Medicine & Biology 66, nr 24 (15.12.2021): 245016. http://dx.doi.org/10.1088/1361-6560/ac3dc8.
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Abstract Objective. Emphysema is characterized by the destruction and permanent enlargement of the alveoli in the lung. According to visual CT appearance, emphysema can be divided into three subtypes: centrilobular emphysema (CLE), panlobular emphysema (PLE), and paraseptal emphysema (PSE). Automating emphysema classification can help precisely determine the patterns of lung destruction and provide a quantitative evaluation. Approach. We propose a vision transformer (ViT) model to classify the emphysema subtypes via CT images. First, large patches (61 × 61) are cropped from CT images which contain the area of normal lung parenchyma, CLE, PLE, and PSE. After resizing, the large patch is divided into small patches and these small patches are converted to a sequence of patch embeddings by flattening and linear embedding. A class embedding is concatenated to the patch embedding, and the positional embedding is added to the resulting embeddings described above. Then, the obtained embedding is fed into the transformer encoder blocks to generate the final representation. Finally, the learnable class embedding is fed to a softmax layer to classify the emphysema. Main results. To overcome the lack of massive data, the transformer encoder blocks (pre-trained on ImageNet) are transferred and fine-tuned in our ViT model. The average accuracy of the pre-trained ViT model achieves 95.95% in our lab’s own dataset, which is higher than that of AlexNet, Inception-V3, MobileNet-V2, ResNet34, and ResNet50. Meanwhile, the pre-trained ViT model outperforms the ViT model without the pre-training. The accuracy of our pre-trained ViT model is higher than or comparable to that by available methods for the public dataset. Significance. The results demonstrated that the proposed ViT model can accurately classify the subtypes of emphysema using CT images. The ViT model can help make an effective computer-aided diagnosis of emphysema, and the ViT method can be extended to other medical applications.
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Zang, Qun S., Hesham Sadek, David L. Maass, Bobbie Martinez, Lisha Ma, Jessica A. Kilgore, Noelle S. Williams i in. "Specific inhibition of mitochondrial oxidative stress suppresses inflammation and improves cardiac function in a rat pneumonia-related sepsis model". American Journal of Physiology-Heart and Circulatory Physiology 302, nr 9 (1.05.2012): H1847—H1859. http://dx.doi.org/10.1152/ajpheart.00203.2011.
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Using a mitochondria-targeted vitamin E (Mito-Vit-E) in a rat pneumonia-related sepsis model, we examined the role of mitochondrial reactive oxygen species in sepsis-mediated myocardial inflammation and subsequent cardiac contractile dysfunction. Sepsis was produced in adult male Sprague-Dawley rats via intratracheal injection of S. pneumonia (4 × 106colony formation units per rat). A single dose of Mito-Vit-E, vitamin E, or control vehicle, at 21.5 μmol/kg, was administered 30 min postinoculation. Blood was collected, and heart tissue was harvested at various time points. Mito-Vit-E in vivo distribution was confirmed by mass spectrometry. In cardiac mitochondria, Mito-Vit-E improved total antioxidant capacity and suppressed H2O2generation, whereas vitamin E offered little effect. In cytosol, both antioxidants decreased H2O2levels, but only vitamin E strengthened antioxidant capacity. Mito-Vit-E protected mitochondrial structure and function in the heart during sepsis, demonstrated by reduction in lipid and protein oxidation, preservation of mitochondrial membrane integrity, and recovery of respiratory function. While both Mito-Vit-E and vitamin E suppressed sepsis-induced peripheral and myocardial production of proinflammatory cytokines (tumor necrosis factor-α, interleukin-1β, and interleukin-6), Mito-Vit-E exhibited significantly higher efficacy ( P < 0.05). Stronger anti-inflammatory action of Mito-Vit-E was further shown by its near-complete inhibition of sepsis-induced myeloperoxidase accumulation in myocardium, suggesting its effect on neutrophil infiltration. Echocardiography analysis indicated that Mito-Vit-E ameliorated cardiac contractility of sepsis animals, shown by improved fractional shortening and ejection fraction. Together, our data suggest that targeted scavenging of mitochondrial reactive oxygen species protects mitochondrial function, attenuates tissue-level inflammation, and improves whole organ activities in the heart during sepsis.
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Shin, Hyunji, Soomin Jeon, Youngsoo Seol, Sangjin Kim i Doyoung Kang. "Vision Transformer Approach for Classification of Alzheimer’s Disease Using 18F-Florbetaben Brain Images". Applied Sciences 13, nr 6 (8.03.2023): 3453. http://dx.doi.org/10.3390/app13063453.
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Dementia is a degenerative disease that is increasingly prevalent in an aging society. Alzheimer’s disease (AD), the most common type of dementia, is best mitigated via early detection and management. Deep learning is an artificial intelligence technique that has been used to diagnose and predict diseases by extracting meaningful features from medical images. The convolutional neural network (CNN) is a representative application of deep learning, serving as a powerful tool for the diagnosis of AD. Recently, vision transformers (ViT) have yielded classification performance exceeding that of CNN in some diagnostic image classifications. Because the brain is a very complex network with interrelated regions, ViT, which captures direct relationships between images, may be more effective for brain image analysis than CNN. Therefore, we propose a method for classifying dementia images by applying 18F-Florbetaben positron emission tomography (PET) images to ViT. Data were evaluated via binary (normal control and abnormal) and ternary (healthy control, mild cognitive impairment, and AD) classification. In a performance comparison with the CNN, VGG19 was selected as the comparison model. Consequently, ViT yielded more effective performance than VGG19 in binary classification. However, in ternary classification, the performance of ViT cannot be considered excellent. These results show that it is hard to argue that the ViT model is better at AD classification than the CNN model.
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Li, Haoran, Daiwei Li, Haiqing Zhang, Xincheng Luo, Lang Xu i LuLu Qu. "DXVNet-ViT-Huge (JFT) Multimode Classification Network Based on Vision Transformer". Journal of Economics and Technology Research 4, nr 1 (23.05.2023): p59. http://dx.doi.org/10.22158/jetr.v4n1p59.
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Aiming at the problem that traditional CNN network is not good at extracting global features of images, Based on DXVNet network, Conditional Random Fields (CRF) component and pre-trained ViT-Huge (Vision Transformer) are adopted in this paper Transformer model expands and builds a brand new DXVNet-ViT-Huge (JFT) network. CRF component can help the network learn the constraint conditions of each word corresponding prediction label, improve the D-GRU method based word label prediction errors, and improve the accuracy of sequence annotation. The Transformer architecture of the ViT (Huge) model can extract the global feature information of the image, while CNN is better at extracting the local features of the image. Therefore, the ViT (Huge) Huge pre-training model and CNN pre-training model adopt the multi-modal feature fusion technology. Two complementary image feature information is fused by Bi-GRU to improve the performance of network classification. The experimental results show that the newly constructed Dxvnet-Vit-Huge (JFT) model achieves good performance, and the F1 values in the two real public data sets are 6.03% and 7.11% higher than the original DXVNet model, respectively.
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Szychlinska, Marta Anna, Rosa Imbesi, Paola Castrogiovanni, Claudia Guglielmino, Silvia Ravalli, Michelino Di Rosa i Giuseppe Musumeci. "Assessment of Vitamin D Supplementation on Articular Cartilage Morphology in a Young Healthy Sedentary Rat Model". Nutrients 11, nr 6 (3.06.2019): 1260. http://dx.doi.org/10.3390/nu11061260.
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Deficiency in vitamin D (Vit D) has been widely associated with several musculoskeletal diseases. However, the effects of the exogenous Vit D supplementation are still unclear in the prevention of the latter, especially in the cartilage developmental period. The aim of this study was to compare the effects of Vit D supplementation and restriction on the articular cartilage development in healthy young sedentary rats. To this aim, twelve nine-week-old healthy Sprague–Dawley male rats were subjected to Vit D-based experimental diets: R, with a content in Vit D of 1400 IU/kg; R-DS, with a Vit D supplementation (4000 IU/kg); R-DR, with a Vit D restriction (0 IU/kg) for 10 weeks. The morphology, thickness and expression of cartilage-associated molecules such as collagen type II/X, lubricin and Vit D receptor (VDR), were assessed. Histological, histomorphometric and immunohistochemical evaluations were made on rat tibial cartilage samples. In the present experimental model, restriction of Vit D intake induced: The lower thickness of cartilage compared both to R (p = < 0.0001) and R-DS (p = < 0.0001); reduction of proteoglycans in the extracellular matrix (ECM) compared both to R (p = 0.0359) and R-DS (p = < 0.0001); decreased collagen II (Col II) with respect both to R (p = 0.0076) and R-DS (p = 0.0016); increased collagen X (Col X) immunoexpression when compared both to R (p = < 0.0001) and R-DS (p = < 0.0001), confirming data from the literature. Instead, supplementation of Vit D intake induced: Higher cartilage thickness with respect both to R (p = 0.0071) and R-DR (p = < 0.0001); increase of ECM proteoglycan deposition compared both to R (p = 0.0175) and R-DR (p = < 0.0001); higher immunoexpression of lubricin with respect both to R (p = 0.001) and R-DR (p = 0.0008). These results suggest that Vit D supplementation with diet, already after 10 weeks, has a favorable impact on the articular cartilage thickness development, joint lubrication and ECM fibers deposition in a young healthy rat model.
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De Nuccio, Francesco, Antonia Cianciulli, Chiara Porro, Marianna Kashyrina, Melania Ruggiero, Rosa Calvello, Alessandro Miraglia, Giuseppe Nicolardi, Dario Domenico Lofrumento i Maria Antonietta Panaro. "Inflammatory Response Modulation by Vitamin C in an MPTP Mouse Model of Parkinson’s Disease". Biology 10, nr 11 (9.11.2021): 1155. http://dx.doi.org/10.3390/biology10111155.
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Vitamin C (Vit C) is anutrient present in many foods, particularly citrus fruits, green vegetables, tomatoes, and potatoes. Vit C is studied for its applications in the prevention and management of different pathologies, including neurodegenerative diseases. Neuroinflammation is a defense mechanism activated by a stimulus or an insult that is aimed at the preservation of the brain by promoting tissue repair and removing cellular debris; however, persistent inflammatory responses are detrimental and may lead to the pathogenesis and progression of neurodegenerative diseases like Parkinson’s disease (PD) and Alzheimer’s disease. PD is one of the most common chronic progressive neurodegenerative disorders, and oxidative stress is one of the most important factors involved in its pathogenesis and progression.Due to this, research on antioxidant and anti-inflammatory compounds is an important target for counteracting neurodegenerative diseases, including PD. In the central nervous system, the presence of Vit C in the brain is higher than in other body districts, but why and how this occurs is still unknown. In this research, Vit C, with its anti-inflammatory and anti-oxidative properties, is studied to better understand its contribution to brain protection; in particular, we have investigated the neuroprotective effects of Vit C in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced animal model of PD and its role in the modulation of neuroinflammation. First, we observed that Vit C significantly decreased the MPTP-induced loss of tyrosine hydroxylase (TH)-positive dopaminergic neuronal cells in the substantia nigra, as well as microglial cell activation and astrogliosis. Furthermore, gait and spontaneous locomotor activity, evaluated by an automated treadmill and the Open Field test, respectively, were partially ameliorated by Vit C treatment in MPTP-intoxicated animals. In relation to neuroinflammation, results show that Vit C reduced the protein and mRNA expression of inflammatory cytokines such as IL-6, TLR4, TNF-α, iNOS, and CD40, while anti-inflammatory proteins such as IL-10, CD163, TGF-β, and IL-4 increased. Interestingly, we show for the first time that Vit C reduces neuroinflammation by modulating microglial polarization and astrocyte activation. Moreover, Vit C was able to reduce NLRP3 activation, which is linked to the pathogenesis of many inflammatory diseases, including neuroinflammatory disorders. In conclusion, our study provides evidence that Vit C may represent a new promising dietary supplement for the prevention and alleviation of the inflammatory cascade of PD, thus contributing to neuroprotection.
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Šošić-Jurjević, Branka, Svetlana Trifunović, Jasmina Živanović, Vladimir Ajdžanović, Marko Miler, Nataša Ristić i Branko Filipović. "Vitamin D3 Treatment Alters Thyroid Functional Morphology in Orchidectomized Rat Model of Osteoporosis". International Journal of Molecular Sciences 23, nr 2 (12.01.2022): 791. http://dx.doi.org/10.3390/ijms23020791.
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Vitamin D plays an essential role in prevention and treatment of osteoporosis. Thyroid hormones, in addition to vitamin D, significantly contribute to regulation of bone remodeling cycle and health. There is currently no data about a possible connection between vitamin D treatment and the thyroid in the context of osteoporosis. Middle-aged Wistar rats were divided into: sham operated (SO), orchidectomized (Orx), and cholecalciferol-treated orchidectomized (Orx + Vit. D3; 5 µg/kg b.m./day during three weeks) groups (n = 6/group). Concentration of 25(OH)D in serum of the Orx + Vit. D3 group increased 4 and 3.2 times (p < 0.0001) respectively, compared to Orx and SO group. T4, TSH, and calcitonin in serum remained unaltered. Vit. D3 treatment induced changes in thyroid functional morphology that indicate increased utilization of stored colloid and release of thyroid hormones in comparison with hormone synthesis, to maintain hormonal balance. Increased expression of nuclear VDR (p < 0.05) points to direct, TSH independent action of Vit. D on thyrocytes. Strong CYP24A1 immunostaining in C cells suggests its prominent expression in response to Vit. D in this cell subpopulation in orchidectomized rat model of osteoporosis. The indirect effect of Vit. D on bone, through fine regulation of thyroid function, is small.
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Geng, Shiyong, Zongnan Zhu, Zhida Wang, Yongping Dan i Hengyi Li. "LW-ViT: The Lightweight Vision Transformer Model Applied in Offline Handwritten Chinese Character Recognition". Electronics 12, nr 7 (3.04.2023): 1693. http://dx.doi.org/10.3390/electronics12071693.
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In recent years, the transformer model has been widely used in computer-vision tasks and has achieved impressive results. Unfortunately, these transformer-based models have the common drawback of having many parameters and a large memory footprint, causing them to be difficult to deploy on mobiles as lightweight convolutional neural networks. To address these issues, a Vision Transformer (ViT) model, named the lightweight Vision Transformer (LW-ViT) model, is proposed to reduce the complexity of the transformer-based model. The model is applied to offline handwritten Chinese character recognition. The design of the LW-ViT model is inspired by MobileViT. The lightweight ViT model reduces the number of parameters and FLOPs by reducing the number of transformer blocks and the MV2 layer based on the overall framework of the MobileViT model. The number of parameters and FLOPs for the LW-ViT model was 0.48 million and 0.22 G, respectively, and it ultimately achieved a high recognition accuracy of 95.8% on the dataset. Furthermore, compared to the MobileViT model, the number of parameters was reduced by 53.8%, and the FLOPs were reduced by 18.5%. The experimental results show that the LW-ViT model has a low number of parameters, proving the correctness and feasibility of the proposed model.
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Chang, Youkang, Hong Zhao i Weijie Wang. "ASK-ViT: A Model with Improved ViT Robustness through Incorporating SK Modules Using Adversarial Training". Electronics 11, nr 20 (19.10.2022): 3370. http://dx.doi.org/10.3390/electronics11203370.
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The ViTs model has been widely used since it was proposed, and its performance on large-scale datasets has surpassed that of CNN models. In order to deploy the ViTs model safely in practical application scenarios, its robustness needs to be investigated. There are few studies on the robustness of ViT model, therefore, this study investigates the robustness of the ViT model in the face of adversarial example attacks, and proposes the ASK-ViT model with improving robustness by introducing the SK module. The SK module consists of three steps, Split, Fuse and Select, which adaptively select the size of the perceptual field according to the input of multi-scale information, and extracts the features that help the model to classify examples. In addition, adversarial training is used in the training process. Experimental results show that the accuracy of the proposed defense method against C&W, DI2FGSM, MDI2FGSM, ImageNet-A, and ImageNet-R attacks is 30.104%, 29.146%, 28.885%, 29.573%, and 48.867%, respectively. Compared with other methods, the method in this study shows stronger robustness.
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Mahmoud, Mohamed, Maria Kokozidou, Clemens Gögele, Christian Werner, Alexander Auffarth, Benjamin Kohl, Ingo Mrosewski i Gundula Gesine Schulze-Tanzil. "Does Vitamin K2 Influence the Interplay between Diabetes Mellitus and Intervertebral Disc Degeneration in a Rat Model?" Nutrients 15, nr 13 (25.06.2023): 2872. http://dx.doi.org/10.3390/nu15132872.
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Intervertebral disc (IVD) degeneration is a common cause of low back pain in diabetes mellitus type 2 (T2DM) patients. Its pathogenesis and the vitamin (vit.) K2 influence on this disease remain unclear. Lumbar motion segments of male Zucker Diabetes Fatty (ZDF) rats (non-diabetic [control] and diabetic; fed without or with vit. K2) were used. Femur lengths and vertebral epiphyseal cross-section areas were measured. IVDs were histopathologically examined. Protein synthesis and gene expression of isolated IVD fibrochondrocytes were analyzed. T2DM rats showed histopathological IVD degeneration. Femur lengths and epiphyseal areas were smaller in T2DM rats regardless of vit. K2 feeding. Fibrochondrocytes synthesized interleukin (IL)-24 and IL-10 with no major differences between groups. Alpha smooth muscle actin (αSMA) was strongly expressed, especially in cells of vit. K2-treated animals. Gene expression of aggrecan was low, and that of collagen type 2 was high in IVD cells of diabetic animals, whether treated with vit. K2 or not. Suppressor of cytokine signaling (Socs)3 and heme oxygenase (Hmox)1 gene expression was highest in the cells of diabetic animals treated with vit. K2. Vit. K2 influenced the expression of some stress-associated markers in IVD cells of diabetic rats, but not that of IL-10 and IL-24.
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Feng, Xinglong, Xianwen Gao i Ling Luo. "An improved Vision Transformer-based method for classifying surface defects in hot-rolled strip steel". Journal of Physics: Conference Series 2082, nr 1 (1.11.2021): 012016. http://dx.doi.org/10.1088/1742-6596/2082/1/012016.
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Abstract A new Vision Transformer(ViT) model is proposed for the classification of surface defects in hot rolled strip, optimizing the poor learning ability of the original Vision Transformer model on smaller datasets. Firstly, each module of ViT and its characteristics are analyzed; Secondly, inspired by the deep learning model VGGNet, the multilayer fully connected layer in VGGNet is introduced into the ViT model to increase its learning capability; Finally, by performing on the X-SDD hot-rolled steel strip surface defect dataset. The effect of the improved algorithm is verified by comparison experiments on the X-SDD hot-rolled strip steel surface defect dataset. The test results show that the improved algorithm achieves better results than the original model in terms of accuracy, recall, F1 score, etc. Among them, the accuracy of the improved algorithm on the test set is 5.64% higher than ViT-Base and 2.64% higher than ViT-Huge; the accuracy is 4.68% and 1.36% higher than both of them, respectively.
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Nyffenegger, Naja, Anna Flace, Cédric Doucerain, Franz Dürrenberger i Vania Manolova. "The Oral Ferroportin Inhibitor VIT-2763 Improves Erythropoiesis without Interfering with Iron Chelation Therapy in a Mouse Model of β-Thalassemia". International Journal of Molecular Sciences 22, nr 2 (16.01.2021): 873. http://dx.doi.org/10.3390/ijms22020873.
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In β-thalassemia, ineffective erythropoiesis leads to anemia and systemic iron overload. The management of iron overload by chelation therapy is a standard of care. However, iron chelation does not improve the ineffective erythropoiesis. We recently showed that the oral ferroportin inhibitor VIT-2763 ameliorates anemia and erythropoiesis in the Hbbth3/+ mouse model of β-thalassemia. In this study, we investigated whether concurrent use of the iron chelator deferasirox (DFX) and the ferroportin inhibitor VIT-2763 causes any pharmacodynamic interactions in the Hbbth3/+ mouse model of β-thalassemia. Mice were treated with VIT-2763 or DFX alone or with the combination of both drugs once daily for three weeks. VIT-2763 alone or in combination with DFX improved anemia and erythropoiesis. VIT-2763 alone decreased serum iron and transferrin saturation (TSAT) but was not able to reduce the liver iron concentration. While DFX alone had no effect on TSAT and erythropoiesis, it significantly reduced the liver iron concentration alone and in the presence of VIT-2763. Our results clearly show that VIT-2763 does not interfere with the iron chelation efficacy of DFX. Furthermore, VIT-2763 retains its beneficial effects on improving ineffective erythropoiesis when combined with DFX in the Hbbth3/+ mouse model. In conclusion, co-administration of the oral ferroportin inhibitor VIT-2763 and the iron chelator DFX is feasible and might offer an opportunity to improve both ineffective erythropoiesis and iron overload in β-thalassemia.
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Xu, Zengbing, Xinyu Tang i Zhigang Wang. "A Multi-Information Fusion ViT Model and Its Application to the Fault Diagnosis of Bearing with Small Data Samples". Machines 11, nr 2 (12.02.2023): 277. http://dx.doi.org/10.3390/machines11020277.
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To solve the fault diagnosis difficulty of bearings with small data samples, a novel multi-information fusion vision transformer (ViT) model based on time–frequency representation (TFR) maps is proposed in this paper. The original vibration signal is decomposed into different scale sub-signals by the discrete wavelet transforms (DWTs), and the continuous wavelet transforms (CWTs) are used to transform these different scale sub-signals into time–frequency representation (TFR) maps, which are concatenated to input to the ViT model to diagnose the bearing fault. Through the multifaceted experiment analysis on the fault diagnosis of bearings with small data samples, the diagnosis results demonstrate that the proposed multi-information fusion ViT model can diagnose the fault of bearings with small data samples, with strong generalization and robustness; its average diagnosis accuracy achieved 99.85%, and it was superior to the other fault diagnosis methods, such as the multi-information fusion CNN, ViT model based on one-dimensional vibration signal, and ViT model based on the TFR of the original vibration signal.
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Bao, Zheng, Xue Wang, Yuhong Li i Fumin Feng. "Vitamin D Alleviates Cognitive Dysfunction by Activating the VDR/ERK1/2 Signaling Pathway in an Alzheimer’s Disease Mouse Model". Neuroimmunomodulation 27, nr 4 (2020): 178–85. http://dx.doi.org/10.1159/000510400.
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<b><i>Objective:</i></b> Vitamin D (Vit D), a steroid hormone, has been linked to cognitive impairment and dementia, such as Alzheimer’s disease (AD). 1, 25(OH)<sub>2</sub>D<sub>3</sub> is the biologically active form of Vit D, which has been shown to have neuroprotective effects. This compound is being evaluated as an emerging therapeutic treatment in models of AD. <b><i>Material and Methods:</i></b> The present study was designed to investigate whether Vit D could alleviate cognitive impairment in an AD rat model by regulating the VDR/ERK1/2 signaling pathway. Adult male APPswe/PS1ΔE9 rats (<i>n</i> = 40) were randomly divided into 2 groups: the AD group and the Vit D + AD group (20 mice per group), and 40 C57BL/6J age-matched mice were separated into the control (CON) group and the Vit D + CON group (20 mice per group). The Morris water maze and object recognition tests were used to evaluate learning and memory functions of the mice. Hematoxylin and eosin staining was used to evaluate morphological changes in hippocampal neurons. Western blotting was used to evaluate the proteins responsible for these changes. <b><i>Results:</i></b> We found that Vit D improved learning and memory abilities and morphological defects in hippocampal neurons. Vit D decreased the gene expression of caspase-3 and Bax and increased the expression of Bcl-2. Vit D also increased the protein expression of VDR and p-ERK1 protein in AD mice. <b><i>Conclusion:</i></b> This study provides new clues about the mechanism by which Vit D exerts neuroprotective effects in an AD mouse model.
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Tang, Xinyu, Zengbing Xu i Zhigang Wang. "A Novel Fault Diagnosis Method of Rolling Bearing Based on Integrated Vision Transformer Model". Sensors 22, nr 10 (20.05.2022): 3878. http://dx.doi.org/10.3390/s22103878.
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In order to improve the diagnosis accuracy and generalization of bearing faults, an integrated vision transformer (ViT) model based on wavelet transform and the soft voting method is proposed in this paper. Firstly, the discrete wavelet transform (DWT) was utilized to decompose the vibration signal into the subsignals in the different frequency bands, and then these different subsignals were transformed into a time–frequency representation (TFR) map by the continuous wavelet transform (CWT) method. Secondly, the TFR maps were input with respective to the multiple individual ViT models for preliminary diagnosis analysis. Finally, the final diagnosis decision was obtained by using the soft voting method to fuse all the preliminary diagnosis results. Through multifaceted diagnosis tests of rolling bearings on different datasets, the diagnosis results demonstrate that the proposed integrated ViT model based on the soft voting method can diagnose the different fault categories and fault severities of bearings accurately, and has a higher diagnostic accuracy and generalization ability by comparison analysis with integrated CNN and individual ViT.
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Wang, Boyuan. "Automatic Mushroom Species Classification Model for Foodborne Disease Prevention Based on Vision Transformer". Journal of Food Quality 2022 (17.08.2022): 1–11. http://dx.doi.org/10.1155/2022/1173102.
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Mushrooms are the fleshy, spore-bearing structure of certain fungi, produced by a group of mycelia and buried in a substratum. Mushrooms are classified as edible, medicinal, and poisonous. However, many poisoning incidents occur yearly by consuming wild mushrooms. Thousands of poisoning incidents are reported each year globally, and 80% of these are from unidentified species of mushrooms. Mushroom poisoning is one of the most serious food safety issues worldwide. Motivated by this problem, this study uses an open-source mushroom dataset and employs several data augmentation approaches to decrease the probability of model overfitting. We propose a novel deep learning pipeline (ViT-Mushroom) for mushroom classification using the Vision Transformer large network (ViT-L/32). We compared the performance of our method against that of a convolutional neural network (CNN). We visualized the high-dimensional outputs of the ViT-L/32 model to achieve the interpretability of ViT-L/32 using the t-distributed stochastic neighbor embedding (t-SNE) method. The results show that ViT-L/32 is the best on the testing dataset, with an accuracy score of 95.97%. These results surpass previous approaches in reducing intraclass variability and generating well-separated feature embeddings. The proposed method is a promising deep learning model capable of automatically classifying mushroom species, helping wild mushroom consumers avoid eating toxic mushrooms, safeguarding food safety, and preventing public health incidents of food poisoning. The results will offer valuable resources for food scientists, nutritionists, and the public health sector regarding the safety and quality of mushrooms.
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Li, Xuan, Mengyuan Yu, Dihong Xu, Shuhong Zhao, Hequn Tan i Xiaolei Liu. "Non-Contact Measurement of Pregnant Sows’ Backfat Thickness Based on a Hybrid CNN-ViT Model". Agriculture 13, nr 7 (14.07.2023): 1395. http://dx.doi.org/10.3390/agriculture13071395.
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Backfat thickness (BF) is closely related to the service life and reproductive performance of sows. The dynamic monitoring of sows’ BF is a critical part of the production process in large-scale pig farms. This study proposed the application of a hybrid CNN-ViT (Vision Transformer, ViT) model for measuring sows’ BF to address the problems of high measurement intensity caused by the traditional contact measurement of sows’ BF and the low efficiency of existing non-contact models for measuring sows’ BF. The CNN-ViT introduced depth-separable convolution and lightweight self-attention, mainly consisting of a Pre-local Unit (PLU), a Lightweight ViT (LViT) and an Inverted Residual Unit (IRU). This model could extract local and global features of images, making it more suitable for small datasets. The model was tested on 106 pregnant sows with seven randomly divided datasets. The results showed that the CNN-ViT had a Mean Absolute Error (MAE) of 0.83 mm, a Root Mean Square Error (RMSE) of 1.05 mm, a Mean Absolute Percentage Error (MAPE) of 4.87% and a coefficient of determination (R-Square, R2) of 0.74. Compared to LviT-IRU, PLU-IRU and PLU-LviT, the CNN-ViT’s MAE decreased by more than 12%, RMSE decreased by more than 15%, MAPE decreased by more than 15% and R² improved by more than 17%. Compared to the Resnet50 and ViT, the CNN-ViT’s MAE decreased by more than 7%, RMSE decreased by more than 13%, MAPE decreased by more than 7% and R2 improved by more than 15%. The method could better meet the demand for the non-contact automatic measurement of pregnant sows’ BF in actual production and provide technical support for the intelligent management of pregnant sows.
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Mandell, Erica, Gregory Seedorf, Jason Gien i Steven H. Abman. "Vitamin D treatment improves survival and infant lung structure after intra-amniotic endotoxin exposure in rats: potential role for the prevention of bronchopulmonary dysplasia". American Journal of Physiology-Lung Cellular and Molecular Physiology 306, nr 5 (1.03.2014): L420—L428. http://dx.doi.org/10.1152/ajplung.00344.2013.
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Vitamin D (vit D) has anti-inflammatory properties and modulates lung growth, but whether vit D can prevent lung injury after exposure to antenatal inflammation is unknown. We hypothesized that early and sustained vit D treatment could improve survival and preserve lung growth in an experimental model of bronchopulmonary dysplasia induced by antenatal exposure to endotoxin (ETX). Fetal rats (E20) were exposed to ETX (10 μg), ETX + Vit D (1 ng/ml), or saline (control) via intra-amniotic (IA) injections and delivered 2 days later. Newborn pups exposed to IA ETX received daily intraperitoneal injections of vit D (1 ng/g) or saline for 14 days. Vit D treatment improved oxygen saturations (78 vs. 87%; P < 0.001) and postnatal survival (84% vs. 57%; P < 0.001) after exposure to IA ETX compared with IA ETX alone. Postnatal vit D treatment improved alveolar and vascular growth at 14 days by 45% and 25%, respectively ( P < 0.05). Vit D increased fetal sheep pulmonary artery endothelial cell (PAEC) growth and tube formation by 64% and 44%, respectively ( P < 0.001), and prevented ETX-induced reductions of PAEC growth and tube formation. Vit D directly increased fetal alveolar type II cell (ATIIC) growth by 26% ( P < 0.001) and enhanced ATIIC growth in the presence of ETX-induced growth suppression by 73% ( P < 0.001). We conclude that antenatal vit D therapy improved oxygenation and survival in newborn rat pups and enhanced late lung structure after exposure to IA ETX in vivo, which may partly be due to direct effects on vascular and alveolar growth.
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Wang, Zhaojun, Zhongqun Wang, Jie Zhu, Xinguang Long i Jinchuan Yan. "Vitamin K2 can suppress the expression of Toll-like receptor 2 (TLR2) and TLR4, and inhibit calcification of aortic intima in ApoE-/- mice as well as smooth muscle cells". Vascular 26, nr 1 (6.06.2017): 18–26. http://dx.doi.org/10.1177/1708538117713395.
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Background and objectives Vascular calcification is a common complication in atherosclerosis. Accumulating evidence showed that Toll-like receptors (TLRs) mediate pro-inflammatory and atherosclerosis. Recent studies demonstrated that vascular calcification is one of the detrimental effects of vitamin K (Vit K) antagonists. However, the effects of Vit K on the expression of TLR2 and 4 and intimal calcification in artery remained unidentified. Methods and results Eighteen ApoE-/- mice were randomly divided into model group, Vit K-treated group, and control group. The mice of model and Vit K-treated group were fed with high-fat diet, while control group mice were fed with normal diet. Mice of Vit K-treated group were administered orally with vitamin K2 (40 mg.kg−1.day−1) for 12 weeks. Twelve weeks later the aortic sections of mice were acquired and stained with hematoxylin and eosin and von Kossa, respectively. Calcium content and activity of alkaline phosphatase (ALP) at aortic tissues were measured. The expression levels of TLR2 and TLR4 in aorta sections were detected by immunohistochemisty and RT-PCR, respectively. The effects of Vit K on cellular calcification were further studied in A7r5 SMCs. Results demonstrated that high-fat diet induced typical atherosclerosis with intimal calcification in ApoE-/- mice, while in Vit K-treated group atherosclerosis and calcium deposits were not serious; Vit K2 also inhibited cellular calcification in A7r5 SMCs. Quantitative analysis showed that calcium and ALP activity at aortic tissues in the Vit K-treated mice were significantly lower than that of the model group ( P < 0.01); Compared to the control group, the expression levels of TLR2 and TLR4 in the model group were significantly higher ( P < 0.05), while in Vit K-treated group the levels of TLR2 and 4 were significantly lower than that in the model group. Furthermore, the content of calcium was positively related to the expression levels of TLR2 and TLR4 mRNA at aortic tissues ( r = 0.77 and r = 0.79, respectively, both P < 0.001). Conclusion VitK2 can inhibit intimal calcification of aortic artery induced by high-fat diet in ApoE-/- mice and A7r5 SMCs calcification induced by β-sodium glycerophosphate, and meanwhile can reduce the expression of TLR2 and TLR4. These results suggested that the effects of VitK2 on vascular calcification may be associated with the expression of TLR2 and TLR4.
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Chang, YouKang, Hong Zhao i Weijie Wang. "Enhancing the robustness of vision transformer defense against adversarial attacks based on squeeze-and-excitation module". PeerJ Computer Science 9 (13.01.2023): e1197. http://dx.doi.org/10.7717/peerj-cs.1197.
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Vision Transformer (ViT) models have achieved good results in computer vision tasks, their performance has been shown to exceed that of convolutional neural networks (CNNs). However, the robustness of the ViT model has been less studied recently. To address this problem, we investigate the robustness of the ViT model in the face of adversarial attacks, and enhance the robustness of the model by introducing the ResNet- SE module, which acts on the Attention module of the ViT model. The Attention module not only learns edge and line information, but also can extract increasingly complex feature information; ResNet-SE module highlights the important information of each feature map and suppresses the minor information, which helps the model to perform the extraction of key features. The experimental results show that the accuracy of the proposed defense method is 19.812%, 17.083%, 18.802%, 21.490%, and 18.010% against Basic Iterative Method (BIM), C&W, DeepFool, DI2FGSM, and MDI2FGSM attacks, respectively. The defense method in this paper shows strong robustness compared with several other models.
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Feng, Hao, Bo Yang, Jingwen Wang, Mingzhe Liu, Lirong Yin, Wenfeng Zheng, Zhengtong Yin i Chao Liu. "Identifying Malignant Breast Ultrasound Images Using ViT-Patch". Applied Sciences 13, nr 6 (9.03.2023): 3489. http://dx.doi.org/10.3390/app13063489.
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Recently, the Vision Transformer (ViT) model has been used for various computer vision tasks, due to its advantages to extracting long-range features. To better integrate the long-range features useful for classification, the standard ViT adds a class token, in addition to patch tokens. Despite state-of-the-art results on some traditional vision tasks, the ViT model typically requires large datasets for supervised training, and thus, it still face challenges in areas where it is difficult to build large datasets, such as medical image analysis. In the ViT model, only the output corresponding to the class token is fed to a Multi-Layer Perceptron (MLP) head for classification, and the outputs corresponding to the patch tokens are exposed. In this paper, we propose an improved ViT architecture (called ViT-Patch), which adds a shared MLP head to the output of each patch token to balance the feature learning on the class and patch tokens. In addition to the primary task, which uses the output of the class token to discriminate whether the image is malignant, a secondary task is introduced, which uses the output of each patch token to determine whether the patch overlaps with the tumor area. More interestingly, due to the correlation between the primary and secondary tasks, the supervisory information added to the patch tokens help with improving the performance of the primary task on the class token. The introduction of secondary supervision information also improves the attention interaction among the class and patch tokens. And by this way, ViT reduces the demand on dataset size. The proposed ViT-Patch is validated on a publicly available dataset, and the experimental results show its effectiveness for both malignant identification and tumor localization.
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Jun, Kyungkoo. "Is Vehicle Plate Corner Prediction by Vision Transformer Better than CNNs?" Scientific Programming 2023 (27.01.2023): 1–10. http://dx.doi.org/10.1155/2023/4301632.
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The license plate recognition performance can be improved by converting the license plate photographed from the side to the front view. To perform this transformation, four vertex corner positions of the license plate are required. Existing deep learning methods to find these corner positions use a convolutional neural network (CNN). In this study, we propose a model using a vision transformer (ViT), a nonconvolutional method that has recently been attracting attention, as a backbone, and compare its performance with existing CNN models. The ablation study is conducted by diversifying the ViT structure. Through these results, it was found that ViT has strengths in model size reduction but is similar in performance or inferior to CNN and that ViT training is more difficult than CNN.
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Bao, Shuai, Jiping Liu, Liang Wang i Xizhi Zhao. "Application of Transformer Models to Landslide Susceptibility Mapping". Sensors 22, nr 23 (23.11.2022): 9104. http://dx.doi.org/10.3390/s22239104.
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Landslide susceptibility mapping (LSM) is of great significance for the identification and prevention of geological hazards. LSM is based on convolutional neural networks (CNNs); CNNs use fixed convolutional kernels, focus more on local information and do not retain spatial information. This is a property of the CNN itself, resulting in low accuracy of LSM. Based on the above problems, we use Vision Transformer (ViT) and its derivative model Swin Transformer (Swin) to conduct LSM for the selected study area. Machine learning and a CNN model are used for comparison. Fourier transform amplitude, feature similarity and other indicators were used to compare and analyze the difference in the results. The results show that the Swin model has the best accuracy, F1-score and AUC. The results of LSM are combined with landslide points, faults and other data analysis; the ViT model results are the most consistent with the actual situation, showing the strongest generalization ability. In this paper, we believe that the advantages of ViT and its derived models in global feature extraction ensure that ViT is more accurate than CNN and machine learning in predicting landslide probability in the study area.
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R Ebrahim, Amal, Mohamed El-Mesery, Amro El-Karef i Laila A. Eissa. "Vitamin D potentiates anti-tumor activity of 5-fluorouracil via modulating caspase-3 and TGF-β1 expression in hepatocellular carcinoma-induced in rats". Canadian Journal of Physiology and Pharmacology 96, nr 12 (grudzień 2018): 1218–25. http://dx.doi.org/10.1139/cjpp-2018-0445.
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We investigated the role of vitamin D (Vit D) alone and in combination with 5-fluorouracil (5-FU) in thioacetamide (TAA)-induced hepatocellular carcinoma (HCC) in rats. Fifty male Sprague–Dawley rats were randomized into a control group and 4 groups that received TAA (200 mg/kg, i.p.) twice per week for 16 weeks. These 4 groups were further divided as follows: HCC group; 5-FU group (75 mg/kg, i.p., once weekly for 3 weeks starting from the 12th week); Vit D group (200 IU/kg daily by oral tube for 16 weeks); and 5-FU + Vit D group (received the previously mentioned dosage regimens of 5-FU and Vit D). HCC was detected by histopathological changes in liver sections and the elevation of serum α-fetoprotein (AFP). Treatment with 5-FU + Vit D significantly decreased gene expression of nuclear factor erythroid 2-related factor 2 (NrF2) and transforming growth factor β1 (TGF-β1) at both the gene and protein level and serum AFP concentrations in comparison with their corresponding monotherapy. Moreover, 5-FU + Vit D treatment enhanced apoptosis by increasing caspase-3 gene and protein expression. Conclusively, Vit D enhances antitumor activity of 5-FU in an HCC-induced model and improves liver function of treated animals. Combination therapy in a TAA-induced HCC rat model was more effective than 5-FU or Vit D through the modulation of TGF-β1, caspase-3, and NrF2 expressions.
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Mabalirajan, Ulaganathan, Jyotirmoi Aich, Geeta Devi Leishangthem, Surendra Kumar Sharma, Amit Kumar Dinda i Balaram Ghosh. "Effects of vitamin E on mitochondrial dysfunction and asthma features in an experimental allergic murine model". Journal of Applied Physiology 107, nr 4 (październik 2009): 1285–92. http://dx.doi.org/10.1152/japplphysiol.00459.2009.
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We showed recently that IL-4 causes mitochondrial dysfunction in allergic asthma. IL-4 is also known to induce 12/15-lipoxygenase (12/15-LOX), a potent candidate molecule in asthma. Because vitamin E (Vit-E) reduces IL-4 and inhibits 12/15-LOX in vitro, here we tested the hypothesis that Vit-E may be effective in restoring key mitochondrial dysfunctions, thus alleviating asthma features in an experimental allergic murine model. Ovalbumin (OVA)-sensitized and challenged male BALB/c mice showed the characteristic features of asthma such as airway hyperresponsiveness (AHR), airway inflammation, and airway remodeling. In addition, these mice showed increase in the expression and metabolites of 12/15-LOX, reduction in the activity and expression of the third subunit of mitochondrial cytochrome- c oxidase, and increased cytochrome c in lung cytosol, which indicate that OVA sensitization and challenge causes mitochondrial dysfunction. Vit-E was administered orally to these mice, and 12/15-LOX expression, key mitochondrial functions, ultrastructural changes of mitochondria in bronchial epithelia, and asthmatic parameters were determined. Vit-E treatment reduced AHR, Th2 response including IL-4, IL-5, IL-13, and OVA-specific IgE, eotaxin, transforming growth factor-β1, airway inflammation, expression and metabolites of 12/15-LOX in lung cytosol, lipid peroxidation, and nitric oxide metabolites in the lung, restored the activity and expression of the third subunit of cytochrome- c oxidase in lung mitochondria and bronchial epithelia, respectively, reduced the appearance of cytochrome c in lung cytosol, and also restored mitochondrial ultrastructural changes of bronchial epithelia. In summary, these findings show that Vit-E reduces key mitochondrial dysfunctions and alleviates asthmatic features.
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Tosan Peter Omayone i Grace Iyabo Adebayo- Gege. "Vitamin E ameliorates oxidative stress in the stomach of l-arginine induced acute pancreatitis rat model". Magna Scientia Advanced Research and Reviews 8, nr 1 (30.05.2023): 046–52. http://dx.doi.org/10.30574/msarr.2023.8.1.0058.
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Gut dysfunction is a major outcome during acute pancreatitis (AP). Some studies have reported a positive association between acute pancreatitis and peptic ulcer. The major cause of peptic ulcer is due to ischaemia reperfusion leading to oxidative stress. This study assessed the oxidative status of the stomach during AP and the role of vitamin (Vit.) E administration. Twenty male Wistar rats were divided randomly into 4 groups; Control, Vit. E (500 mg/kg) only, AP and Vit. E + AP. Acute pancreatitis was induced by administering four doses of l-arginine (100 mg/100 g) intraperitoneally at 1-hour interval. The rats were sacrificed 72 hours later and stomach obtained for mucin content and biochemical assays (MDA, MPO, NO, CAT, GST, and GSH). Mucin content was depleted following AP induction while, vit. E significantly increase mucin content. AP resulted in significant reduction of antioxidant enzymes (GSH and GST) and increase in oxidative stress markers (MDA, MPO and NO). Vitamin E reverse these changes. In conclusion, the oxidative status of the stomach was greatly altered following AP induction with an increase in oxidative stress markers and decrease in antioxidants. Vitamin E was able to protect the stomach from the damaging effect of acute pancreatitis.
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Wang, Guanqun, He Chen, Liang Chen, Yin Zhuang, Shanghang Zhang, Tong Zhang, Hao Dong i Peng Gao. "P2FEViT: Plug-and-Play CNN Feature Embedded Hybrid Vision Transformer for Remote Sensing Image Classification". Remote Sensing 15, nr 7 (26.03.2023): 1773. http://dx.doi.org/10.3390/rs15071773.
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Remote sensing image classification (RSIC) is a classical and fundamental task in the intelligent interpretation of remote sensing imagery, which can provide unique labeling information for each acquired remote sensing image. Thanks to the potent global context information extraction ability of the multi-head self-attention (MSA) mechanism, visual transformer (ViT)-based architectures have shown excellent capability in natural scene image classification. However, in order to achieve powerful RSIC performance, it is insufficient to capture global spatial information alone. Specifically, for fine-grained target recognition tasks with high inter-class similarity, discriminative and effective local feature representations are key to correct classification. In addition, due to the lack of inductive biases, the powerful global spatial context representation capability of ViT requires lengthy training procedures and large-scale pre-training data volume. To solve the above problems, a hybrid architecture of convolution neural network (CNN) and ViT is proposed to improve the RSIC ability, called P2FEViT, which integrates plug-and-play CNN features with ViT. In this paper, the feature representation capabilities of CNN and ViT applying for RSIC are first analyzed. Second, aiming to integrate the advantages of CNN and ViT, a novel approach embedding CNN features into the ViT architecture is proposed, which can make the model synchronously capture and fuse global context and local multimodal information to further improve the classification capability of ViT. Third, based on the hybrid structure, only a simple cross-entropy loss is employed for model training. The model can also have rapid and comfortable convergence with relatively less training data than the original ViT. Finally, extensive experiments are conducted on the public and challenging remote sensing scene classification dataset of NWPU-RESISC45 (NWPU-R45) and the self-built fine-grained target classification dataset called BIT-AFGR50. The experimental results demonstrate that the proposed P2FEViT can effectively improve the feature description capability and obtain outstanding image classification performance, while significantly reducing the high dependence of ViT on large-scale pre-training data volume and accelerating the convergence speed. The code and self-built dataset will be released at our webpages.
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Lu, Jiaqi. "Convolutional neural network and vision transformer for image classification". Applied and Computational Engineering 5, nr 1 (14.06.2023): 104–8. http://dx.doi.org/10.54254/2755-2721/5/20230542.
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Visual Transformer (ViT) has been a hot topic for research for the past few years after it first emerged in the field. On image recognitions, due to the amount of information ViT could retrieve from the source image, in cases it can rival the traditionally prevailing Convolutional Neural Network (CNN). Then there emerged different models based on ViT, all being built having a specific field or a flaw not addressed by original ViT in mind. In this paper these models are being tested on the same dataset along with a standard CNN to see how they perform compare to each other, and the best performing ViT model was then changed to see how there would be some possible improvements.
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Chen, Mengzhao, Mingbao Lin, Ke Li, Yunhang Shen, Yongjian Wu, Fei Chao i Rongrong Ji. "CF-ViT: A General Coarse-to-Fine Method for Vision Transformer". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 6 (26.06.2023): 7042–52. http://dx.doi.org/10.1609/aaai.v37i6.25860.
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Vision Transformers (ViT) have made many breakthroughs in computer vision tasks. However, considerable redundancy arises in the spatial dimension of an input image, leading to massive computational costs. Therefore, We propose a coarse-to-fine vision transformer (CF-ViT) to relieve computational burden while retaining performance in this paper. Our proposed CF-ViT is motivated by two important observations in modern ViT models: (1) The coarse-grained patch splitting can locate informative regions of an input image. (2) Most images can be well recognized by a ViT model in a small-length token sequence. Therefore, our CF-ViT implements network inference in a two-stage manner. At coarse inference stage, an input image is split into a small-length patch sequence for a computationally economical classification. If not well recognized, the informative patches are identified and further re-split in a fine-grained granularity. Extensive experiments demonstrate the efficacy of our CF-ViT. For example, without any compromise on performance, CF-ViT reduces 53% FLOPs of LV-ViT, and also achieves 2.01x throughput. Code of this project is at https://github.com/ChenMnZ/CF-V
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Zabihi, Mohsen, Fatemeh Askarian, Seyedhossein Hekmatimoghaddam, Mohammadreza Rashidi Nooshabadi, Mohammad Sajjad Zabihi i Seyed Ruhollah Mousavinasab. "Ascorbic Acid Significantly Decreases Creatine Kinase Plasma Levels in an Animal Model of Statin/Fibrate-Induced Myopathy". Advances in Pharmacological and Pharmaceutical Sciences 2021 (29.12.2021): 1–7. http://dx.doi.org/10.1155/2021/5539595.
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Background. Myopathy is one of the side effects of lipid-lowering drugs, especially statins and particularly when combined with a fibrate. To diagnose myopathy and determine its severity, the plasma levels of three enzymes, creatine kinase (CK), aldolase, and lactate dehydrogenase (LDH), are routinely measured. Physical exercise can aggravate the statin-associated muscular disease. The question is whether antioxidants like ascorbic acid (Vit. C) can prevent such myopathy. Methods. In this experiment, a combination of atorvastatin (ATV, 80 mg/kg/day) and gemfibrozil (GMF, 1000 mg/kg/day) orally for 10 days as well as exercise as forced swimming on days 8, 9, and 10 were used to induce myopathy. Ascorbic acid (50 mg/kg/day, orally) was added to ATV/GMF plus exercise regimen throughout the 10 days in the treatment group. Mean blood levels of CK, aldolase, and LDH were measured in addition to swimming tolerance times. Results. There was a significantly higher swimming tolerance time P < 0.05 and lower CK levels P < 0.01 in rats receiving ATV/GMF/Vit. C plus exercise compared with rats not taking Vit. C. LDH and aldolase did not decrease significantly. Conclusion. The results of this study showed that Vit. C can be effective in preventing myopathy caused by fat-lowering drugs.
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Zhang, Bo, Lu Liu, Shiwen Zhao, Xu Wang, Liyang Liu i Shao Li. "Vitexicarpin Acts as a Novel Angiogenesis Inhibitor and Its Target Network". Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/278405.
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Vitexicarpin (VIT) isolated from the fruits ofVitex rotundifoliahas shown antitumor, anti-inflammatory, and immunoregulatory properties. This work is designed to evaluate the antiangiogenic effects of VIT and address the underlying action mechanism of VIT by a network pharmacology approach. The results validated that VIT can act as a novel angiogenesis inhibitor. Firstly, VIT can exert good antiangiogenic effects by inhibiting vascular-endothelial-growth-factor- (VEGF-) induced endothelial cell proliferation, migration, and capillary-like tube formation on matrigel in a dose-dependent manner. Secondly, VIT was also shown to have an antiangiogenic mechanism through inhibition of cell cycle progression and induction of apoptosis. Thirdly, VIT inhibited chorioallantoic membrane angiogenesis as well as tumor angiogenesis in an allograft mouse tumor model. We further addressed VIT’s molecular mechanism of antiangiogenic actions using one of our network pharmacology methods named drugCIPHER. Then, we tested some key molecules in the VEGF pathway targeted by VIT and verified the inhibition effects of VIT on AKT and SRC phosphorylation. Taken together, this work not only identifies VIT as a novel potent angiogenesis inhibitor, but also demonstrates that network pharmacology methods can be an effective and promising approach to make discovery and understand the action mechanism of herbal ingredients.
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Jiang, Zhencun, Zhengxin Dong, Lingyang Wang i Wenping Jiang. "Method for Diagnosis of Acute Lymphoblastic Leukemia Based on ViT-CNN Ensemble Model". Computational Intelligence and Neuroscience 2021 (21.08.2021): 1–12. http://dx.doi.org/10.1155/2021/7529893.
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Acute lymphocytic leukemia (ALL) is a deadly cancer that not only affects adults but also accounts for about 25% of childhood cancers. Timely and accurate diagnosis of the cancer is an important premise for effective treatment to improve survival rate. Since the image of leukemic B-lymphoblast cells (cancer cells) under the microscope is very similar in morphology to that of normal B-lymphoid precursors (normal cells), it is difficult to distinguish between cancer cells and normal cells. Therefore, we propose the ViT-CNN ensemble model to classify cancer cells images and normal cells images to assist in the diagnosis of acute lymphoblastic leukemia. The ViT-CNN ensemble model is an ensemble model that combines the vision transformer model and convolutional neural network (CNN) model. The vision transformer model is an image classification model based entirely on the transformer structure, which has completely different feature extraction method from the CNN model. The ViT-CNN ensemble model can extract the features of cells images in two completely different ways to achieve better classification results. In addition, the data set used in this article is an unbalanced data set and has a certain amount of noise, and we propose a difference enhancement-random sampling (DERS) data enhancement method, create a new balanced data set, and use the symmetric cross-entropy loss function to reduce the impact of noise in the data set. The classification accuracy of the ViT-CNN ensemble model on the test set has reached 99.03%, and it is proved through experimental comparison that the effect is better than other models. The proposed method can accurately distinguish between cancer cells and normal cells and can be used as an effective method for computer-aided diagnosis of acute lymphoblastic leukemia.
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Hamza, Reham, Rasha Al-Eisa i Nahla El-Shenawy. "Efficacy of Mesenchymal Stem Cell and Vitamin D in the Treatment of Diabetes Mellitus Induced in a Rat Model: Pancreatic Tissues". Coatings 11, nr 3 (10.03.2021): 317. http://dx.doi.org/10.3390/coatings11030317.
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Treatment with mesenchyme stem cells (MSCs) plays a significant role in the therapies of many diseases such as diabetics. Vitamin D plays a significant role in the development of insulin and can increase the insulin action sensitivity of peripheral tissues. Moreover, there is limited research concerning the mechanism of the therapeutic action of MSCs with the combination of vitamin D (vit. D). Therefore, we evaluated the effect of MSC intervention in a diabetic animal model. Diabetes was induced by streptozotocin (STZ) injection at a dose of 50 mg/kg in adult male rats The diabetic rats were injected with MSCs derived from bone marrow (2 × 106 per rat), either alone or in combination with vit. D through the tail vein for four weeks. Serum insulin, glucose, C-peptide, glycosylated hemoglobin, and lipid profile levels were determined. Pancreatic oxidative stress, histology, and electron microscopy were evaluated, and the gene expression of cytokines was assessed by real-time polymerase chain reaction PCR. MSC treatment suppressed pancreatic inflammatory cytokine secretion and oxidative stress in diabetic rats, resulting in improved pancreatic histology and cellular structure, and the complication of hyperglycemia was observed. Engrafted MSCs were found inside degraded pancreatic regions and regulated inflammatory cytokines. Our results demonstrated that treatment with MSCs and vit. D in combination prevented pancreatic injury via antioxidant and immune regulation in diabetic rats, contributing to the prevention of pancreatic dysfunction, improvement of lipid metabolism, and regulation of cytokine gene expression compared with each one separately. All these mechanisms also improved the histological structure of the pancreas based on transmission electron microscopy. The combination of MSCs and vit. D appears to have contributed to a greater improvement in the diabetic pancreatic complication of rats than was observed by each one separately. Therefore, this association can be used as antidiabetic therapy.
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Николаев, Ю. Л., П. Н. Шкатов, Э. Ф. Ахметшина i А. А. Саморуков. "Математическое описание и анализ сигнала виброиндукционного преобразователя при воздействии нормальной составляющей магнитных потоков рассеяния над дефектным участком". Дефектоскопия 7 (lipiec 2021): 19–27. http://dx.doi.org/10.31857/s0130308221070034.
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Theoretical and experimental researches of vibration-induction transducer (VIT) outlet signal formed during exposure to normal leakage magnetic field intensity component Hn over the defective area were carried out. Theoretical research is based on an assumption that VIT signal is a trigonometric series that is limited by first five harmonics. As initial data for mathematical model creation, well-known conformities for Hn distribution over the defective area were used. Based on acquired mathematical model conformities of VIT signal harmonical composition permutation during its movement over the defective area with varying amplitudes and vibration frequency were found. Theoretical research results were proven experimentally. Moreover, additional possibilities of this way of magnetic testing are shown in comparison with conventional ones.
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Min, Hyemin, Esther Youn i Yhong-Hee Shim. "Maternal Caffeine Intake Disrupts Eggshell Integrity and Retards Larval Development by Reducing Yolk Production in a Caenorhabditis elegans Model". Nutrients 12, nr 5 (7.05.2020): 1334. http://dx.doi.org/10.3390/nu12051334.
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During pregnancy, most women are exposed to caffeine, which is a widely consumed psychoactive substance. However, the consequences of maternal caffeine intake on the child remain largely unknown. Here, we investigated the intergenerational effects of maternal caffeine intake on offspring in a Caenorhabditis elegans model. We treated a young mother (P0) with 10 mM of caffeine equivalent to 2–5 cans of commercial energy drinks and examined its reproduction and growth rate from P0 to F2 generation. The fertility decreased and embryonic lethality increased by defective oocytes and eggshell integrity in caffeine-ingested mothers, and F1 larval development severely retarded. These results were due to decreased production of vitellogenin protein (yolk) in caffeine-ingested mothers. Furthermore, effects of RNA interference of vitellogenin (vit) genes, vit-1 to vit-6, in P0 mothers can mimic those by caffeine-ingested mothers. In addition, RNA interference (RNAi) depletion of unc-62 (human Meis homeobox), a transcriptional activator for vit genes, also showed similar effects induced by caffeine intake. Taken together, maternal caffeine intake reduced yolk production mediated by the UNC-62 transcription factor, thereby disrupting oocyte and eggshell integrity and retarding larval development. Our study suggests the clinical significance of caffeine intake for prospective mothers.
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Mattioli, Simona, Corrado Dimauro, Alberto Cesarani, Alessandro Dal Bosco, Desiree Bartolini, Francesco Galli, Anna Migni i in. "A Dynamic Model for Estimating the Interaction of ROS–PUFA–Antioxidants in Rabbit". Antioxidants 11, nr 3 (10.03.2022): 531. http://dx.doi.org/10.3390/antiox11030531.
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Defining optimal nutrition in animals and humans remains a main scientific challenge. The objective of the work was to develop a dynamic model of reactive oxygen species (ROS)–polyunsaturated fatty acid (PUFA)–antioxidant homeostasis using the rabbit as a model. The problem entity was to evaluate the main metabolites generated from interactions between traits included in the conceptual model and identified by three main sub–models: (i) ROS generation, (ii) PUFA oxidation and (iii) antioxidant defence. A mathematical model (VENSIM software) that consisted of molecular stocks (INPUTs, OUTPUTs), exchange flows (intermediate OUTPUTs) and process rates was developed. The calibration was performed by using standard experimental data (Experiment 1), whereas the validation was carried out in Experiments 2 and 3 by using supra–nutritional dietary inputs (VIT E+ and PUFA+). The accuracy of the models was measured using 95% confidence intervals. Analytical OUTPUTs (ROS, PUFA, Vit E, Ascorbic acid, Iso–/NeuroProstanes, Aldehydes) were well described by the standard model. There was also good accuracy for the VIT E+ scenario, whereas some compensatory rates (Kc1–Kc4) were added to assess body compensation when high levels of dietary PUFA were administered (Experiment 3). In conclusion, the model can be very useful for predicting the effects of dietary treatments on the redox homeostasis of rabbits.
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Fischer, Cecilie, Franz Jakob, Matthias Kohl, Stephanie Kast, Simon Von Stengel, Katharina Kerschan-Schindl, Uwe Lange i in. "Additive Effects of Exercise and Vitamin D Supplementation (with and without Calcium) on Bone Mineral Density in Older Adults: A Systematic Review and Meta-Analysis". Journal of Osteoporosis 2023 (8.08.2023): 1–13. http://dx.doi.org/10.1155/2023/5570030.
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Exercise is a recognized component in the prevention and therapy of osteoporosis. The present systematic review and meta-analysis aimed to determine the effect of Vitamin D (Vit-D) added to exercise versus exercise alone on bone mineral density (BMD) at the lumbar spine (LS) or hip in older adults. A systematic review based on six literature databases according to PRISMA included (a) exercise trials, with an exercise (EX) and a combined exercise + Vit-D group (EX + Vit-D), (b) intervention ≥ 6 months, and (c) BMD assessments at LS or hip. Effects sizes (MD) and 95%-confidence intervals (95%-CI) were calculated using a random-effect model that includes the inverse heterogeneity model (IVhet). Five studies with 281 participants in the EX and 279 participants in the EX + Vit-D were included. No significant differences between EX versus EX + Vit-D were observed for BMD-LS (MD: 0.002, 95%-CI: −0.033 to 0.036) or BMD-hip (MD: 0.003, 95%-CI: −0.035 to 0.042). Heterogeneity between the trial results was moderate-substantial for LS (I2 = 0%) and moderate for hip-BMD (I2 = 35%). The funnel plot analysis suggests evidence for a publication/small study bias for BMD-LS and hip results. In summary, this present systematic review and meta-analysis were unable to determine significant positive interaction of exercise and Vit-D on LS- or hip-BMD. We predominately attribute this finding to (1) the less bone-specific exercise protocols of at least two of the five studies and (2) the inclusion criteria of the studies that did not consequently focus on Vit-D deficiency. This issue should be addressed in more detail by adequately powered exercise trials with promising exercise protocols and participants with Vit-D deficiency. This trial is registered with the International Prospective Register of Systematic Reviews (PROSPERO) ID: CRD42022309813.
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Liu, Chunyang, Yuxuan Ban, Hongyu Li, Nan Guo, Xiqiang Ma, Fang Yang, Xin Sui i Yan Huang. "Accurate Recognition Method for Rolling Bearing Failure of Mine Hoist in Strong Noise Environment". Machines 11, nr 6 (6.06.2023): 632. http://dx.doi.org/10.3390/machines11060632.
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The operating environment of rolling bearings in mine hoists is complicated, and detecting their faults is hindered by a weak and unstable initial vibration signal. This directly affects the ability to extract pertinent fault features. This paper puts forward an adaptive fault diagnosis method for rolling bearings that combines the Variational Modal Decomposition (VMD) model and Vision Transformer (ViT) deep learning network model. The objective was to address the difficulty of extracting relevant fault features from bearing vibration signals in environments with strong noise levels. First, an improved VMD+ViT model was used to remove the strong noise from the original bearing signal and adaptively classify the fault types; then, the impacts of modal components and encoder numbers on the accuracy of fault diagnosis were explored. Finally, the proposed methodology was validated by applying it to actual rolling bearing fault data, including both open-source and fault test datasets. The research findings indicated that employing a VMD+ViT integrated model consisting of one modal component with the highest Pearson correlation coefficient and eight encoders resulted in high accuracy in diagnosing faults, even in the presence of high levels of noise in the bearing’s vibration signal. The proposed diagnostic method achieved a diagnostic accuracy of over 92.70% on the open-source bearing dataset with strong interference noise and over 98.62% on the fault test dataset. The proposed method exhibited high accuracy and strong robustness, making it suitable for effectively diagnosing and accurately identifying different categories of rolling bearing faults in mine hoists, even in environments with high levels of noise.
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Ho, Myoung Jin, Dong Woo Park i Myung Joo Kang. "Design of Novel Tricaprylin-Incorporated Multi-Layered Liposomal System for Skin Delivery of Ascorbic Acid with Improved Chemical Stability". Pharmaceuticals 16, nr 1 (13.01.2023): 121. http://dx.doi.org/10.3390/ph16010121.
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L-ascorbic acid (Vit C) possesses a variety of dermatological functions in maintaining skin health and anti-aging properties. However, its topical application is challenging owing to its liability to light, oxygen, or heat. Therefore, in this study, a novel liposomal system, including a lipophilic neutral oil named a lipo-oil-some (LOS), was designed to improve the chemical stability and aid the skin absorption of Vit C. The vesicular systems were prepared using the ethanol injection method, employing phosphatidylcholine, cholesterol, dipalmitoyl-sn-glycerol-3-phosphoglycerol, and tricaprylin as neutral oil. The optimized LOS was characterized as follows: shape, multi-layered sphere; size, 981 nm; zeta potential, −58 mV; and Vit C encapsulation efficiency, 35%. The encapsulation of the labile compound into the novel system markedly enhanced photostability, providing over 10% higher Vit C remaining compared to Vit C solution or Vit C-loaded conventional liposome under a light intensity of 20,000 lx. On the other hand, the ex vivo skin permeation and accumulation of Vit C with the LOS system were comparable to those of smaller conventional liposomes (198 nm) in a Franz diffusion cell model mounted with porcine skin. Based on these findings, we concluded that the novel liposomal system could be utilized for skin delivery of Vit C with enhanced chemical stability.
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Zhang, Jiahong, Honglie Guo, Jin Guo i Jing Zhang. "An Information Entropy Masked Vision Transformer (IEM-ViT) Model for Recognition of Tea Diseases". Agronomy 13, nr 4 (19.04.2023): 1156. http://dx.doi.org/10.3390/agronomy13041156.
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Tea is one of the most popular drinks in the world. The rapid and accurate recognition of tea diseases is of great significance for taking targeted preventive measures. In this paper, an information entropy masked vision transformation (IEM-ViT) model was proposed for the rapid and accurate recognition of tea diseases. The information entropy weighting (IEW) method was used to calculate the IE of each segment of the image, so that the model could learn the maximum amount of knowledge and information more quickly and accurately. An asymmetric encoder–decoder architecture was used in the masked autoencoder (MAE), where the encoder operated on only a subset of visible patches and the decoder recovered the labeled masked patches, reconstructing the missing pixels for parameter sharing and data augmentation. The experimental results showed that the proposed IEM-ViT had an accuracy of 93.78% for recognizing the seven types of tea diseases. In comparison to the currently common image recognition algorithms including the ResNet18, VGG16, and VGG19, the recognition accuracy was improved by nearly 20%. Additionally, in comparison to the other six published tea disease recognition methods, the proposed IEM-ViT model could recognize more types of tea diseases and the accuracy was improved simultaneously.
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Wang, Jing, Peitong Li, Rongfeng Zhao, Ruyan Zhou i Yanling Han. "CNN Attention Enhanced ViT Network for Occluded Person Re-Identification". Applied Sciences 13, nr 6 (14.03.2023): 3707. http://dx.doi.org/10.3390/app13063707.
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Person re-identification (ReID) is often affected by occlusion, which makes most of the features extracted by ReID models contain a lot of identity-independent noise. Recently, the use of Vision Transformer (ViT) has enabled significant progress in various visual artificial intelligence tasks. However, ViT suffers from insufficient local information extraction capability, which should be of concern to researchers in the field of occluded ReID. This paper conducts a study to exploit the potential of attention mechanisms to enhance ViT in ReID tasks. In this study, an Attention Enhanced ViT Network (AET-Net) is proposed for occluded ReID. We use ViT as the backbone network to extract image features. Even so, occlusion and outlier problems still exist in ReID. Then, we combine the spatial attention mechanism into the ViT architecture, by which we enhance the attention of ViT patch embedding vectors to important regions. In addition, we design a MultiFeature Training Module to optimize the network by the construction of multiple classification features and calculation of the multi-feature loss to enhance the performance of the model. Finally, the effectiveness and superiority of the proposed method are demonstrated by broad experiments on both occluded and non-occluded datasets.
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Tian, Jialin, Xing Xu, Fumin Shen, Yang Yang i Heng Tao Shen. "TVT: Three-Way Vision Transformer through Multi-Modal Hypersphere Learning for Zero-Shot Sketch-Based Image Retrieval". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 2 (28.06.2022): 2370–78. http://dx.doi.org/10.1609/aaai.v36i2.20136.
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In this paper, we study the zero-shot sketch-based image retrieval (ZS-SBIR) task, which retrieves natural images related to sketch queries from unseen categories. In the literature, convolutional neural networks (CNNs) have become the de-facto standard and they are either trained end-to-end or used to extract pre-trained features for images and sketches. However, CNNs are limited in modeling the global structural information of objects due to the intrinsic locality of convolution operations. To this end, we propose a Transformer-based approach called Three-Way Vision Transformer (TVT) to leverage the ability of Vision Transformer (ViT) to model global contexts due to the global self-attention mechanism. Going beyond simply applying ViT to this task, we propose a token-based strategy of adding fusion and distillation tokens and making them complementary to each other. Specifically, we integrate three ViTs, which are pre-trained on data of each modality, into a three-way pipeline through the processes of distillation and multi-modal hypersphere learning. The distillation process is proposed to supervise fusion ViT (ViT with an extra fusion token) with soft targets from modality-specific ViTs, which prevents fusion ViT from catastrophic forgetting. Furthermore, our method learns a multi-modal hypersphere by performing inter- and intra-modal alignment without loss of uniformity, which aims to bridge the modal gap between modalities of sketch and image and avoid the collapse in dimensions. Extensive experiments on three benchmark datasets, i.e., Sketchy, TU-Berlin, and QuickDraw, demonstrate the superiority of our TVT method over the state-of-the-art ZS-SBIR methods.
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Gonzales Chaves, Macarena M. S., Clarisa Marote, Gretel G. Pellegrini, Andrés Pighin, Maria C. de Landeta, Fima Lifshitz, Silvia M. Friedman, Patricia Mandalunis i Susana N. Zeni. "BONE MASS RECOVERY OF OSTEOPENIC VITAMIN D INSUFFICIENT RATS FROM STRONTIUM RANELATE TREATMENT: DOES THE RESPONSE DEPEND ON VITAMIN D NUTRITIONAL STATUS OR ON SOURCE OF VITAMIN D (D2 VERSUS D3)?" Journal of Musculoskeletal Research 13, nr 03 (wrzesień 2010): 95–108. http://dx.doi.org/10.1142/s0218957710002582.
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It was investigated if Vitamin D (Vit D) status or source (Vitamin D2 vs. Vitamin D3) interferes with bone mass recovery from strontium ranelate (SrRa) treatment of rats with Vit D insufficiency and established osteopenia. Osteopenic and Vit D insufficient rats were divided in groups to complete a 105-day period. First experiment: The rats were fed with diets that only varied in Vit D (100 vs. 0 IU%) and/or SrRa (0 vs. 900 mg/kg/day) content. A SHAM group received Vit D throughout the experience. Second experiment: Rats were divided into groups and received Vit D2 or Vit D3 through diet and SrRa by gavages in a fasting state. Two SHAM groups received Vit D2 or Vit D3 throughout the study. Results: Levels of 25-hydroxyvitamin 25OHD were reduced in groups lacking dietary Vit D (p < 0.001). Independently of Vit D status or source, SrRa did not affect body weight gain or bone alkaline phosphatase levels; osteocalcin and C-terminal telopeptide of type I collagen levels were reduced (p < 0.05) and bone Sr content was increased (p < 0.0001). Although no improvement in biomechanical parameters was observed, total skeletal bone mineral content and proximal tibial bone mineral density were increased (p < 0.05). There was a reduction in the trabecular number and an increase in the trabecular surface and bone volume without reaching SHAM levels. Conclusion: This is the first study that examined SrRa effects in an osteopenic vitamin D–insufficient experimental model. Under our experimental conditions, SrRa increased bone Sr content independently of Vit D status or source; however, no evidence of an anabolic or antifracture effect was found, and only a slight decrease in some bone resorption parameters was observed.
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Yin, Miao, Burak Uzkent, Yilin Shen, Hongxia Jin i Bo Yuan. "GOHSP: A Unified Framework of Graph and Optimization-Based Heterogeneous Structured Pruning for Vision Transformer". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 9 (26.06.2023): 10954–62. http://dx.doi.org/10.1609/aaai.v37i9.26298.
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The recently proposed Vision transformers (ViTs) have shown very impressive empirical performance in various computer vision tasks, and they are viewed as an important type of foundation model. However, ViTs are typically constructed with large-scale sizes, which then severely hinder their potential deployment in many practical resources constrained applications. To mitigate this challenging problem, structured pruning is a promising solution to compress model size and enable practical efficiency. However, unlike its current popularity for CNNs and RNNs, structured pruning for ViT models is little explored. In this paper, we propose GOHSP, a unified framework of Graph and Optimization-based Structured Pruning for ViT models. We first develop a graph-based ranking for measuring the importance of attention heads, and the extracted importance information is further integrated to an optimization-based procedure to impose the heterogeneous structured sparsity patterns on the ViT models. Experimental results show that our proposed GOHSP demonstrates excellent compression performance. On CIFAR-10 dataset, our approach can bring 40% parameters reduction with no accuracy loss for ViT-Small model. On ImageNet dataset, with 30% and 35% sparsity ratio for DeiT-Tiny and DeiT-Small models, our approach achieves 1.65% and 0.76% accuracy increase over the existing structured pruning methods, respectively.
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Majtan, Juraj, Martin Sojka, Helena Palenikova, Marcela Bucekova i Viktor Majtan. "Vitamin C Enhances the Antibacterial Activity of Honey against Planktonic and Biofilm-Embedded Bacteria". Molecules 25, nr 4 (23.02.2020): 992. http://dx.doi.org/10.3390/molecules25040992.
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Multifactorial antibacterial action is an important feature of honey; however, its bactericidal efficacy against biofilm-embedded bacteria is limited. The aim of this study was to investigate the impact of vitamin C (Vit C) on the antibacterial activity of natural honeys against planktonic as well as biofilm-embedded bacterial pathogens. The antibacterial activity of four honey samples supplemented with Vit C was expressed as the minimum inhibitory concentration (MIC). At sub-MICs, Vit C significantly increased the antibacterial activity of the tested honeys against Pseudomonas aeruginosa in planktonic cultures. However, after supplementation, honeydew honey, the most active honey, was ineffective against Staphylococcus aureus. On the other hand, when 100% honeydew honey was supplemented with Vit C (100 mg/g of honey) in a multispecies wound biofilm model, complete eradication of almost all bacterial isolates, including S. aureus, was observed. Furthermore, a mixture of honey and Vit C was partially effective against Enterococcus faecalis, whereas honey alone exhibited no antibacterial activity against this bacterium. Vit C counteracted hydrogen peroxide in honey solution and, thus, eliminated the major antibacterial compound present in honey. It is likely that a combination of honey with Vit C may trigger the intracellular production of reactive oxygen species in bacterial cells, but the exact cellular mechanisms warrant further investigations.
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Bao, Shuai, Jiping Liu, Liang Wang, Milan Konečný, Xianghong Che, Shenghua Xu i Pengpeng Li. "Landslide Susceptibility Mapping by Fusing Convolutional Neural Networks and Vision Transformer". Sensors 23, nr 1 (22.12.2022): 88. http://dx.doi.org/10.3390/s23010088.
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Landslide susceptibility mapping (LSM) is an important decision basis for regional landslide hazard risk management, territorial spatial planning and landslide decision making. The current convolutional neural network (CNN)-based landslide susceptibility mapping models do not adequately take into account the spatial nature of texture features, and vision transformer (ViT)-based LSM models have high requirements for the amount of training data. In this study, we overcome the shortcomings of CNN and ViT by fusing these two deep learning models (bottleneck transformer network (BoTNet) and convolutional vision transformer network (ConViT)), and the fused model was used to predict the probability of landslide occurrence. First, we integrated historical landslide data and landslide evaluation factors and analysed whether there was covariance in the landslide evaluation factors. Then, the testing accuracy and generalisation ability of the CNN, ViT, BoTNet and ConViT models were compared and analysed. Finally, four landslide susceptibility mapping models were used to predict the probability of landslide occurrence in Pingwu County, Sichuan Province, China. Among them, BoTNet and ConViT had the highest accuracy, both at 87.78%, an improvement of 1.11% compared to a single model, while ConViT had the highest F1-socre at 87.64%, an improvement of 1.28% compared to a single model. The results indicate that the fusion model of CNN and ViT has better LSM performance than the single model. Meanwhile, the evaluation results of this study can be used as one of the basic tools for landslide hazard risk quantification and disaster prevention in Pingwu County.
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Hur, Ender, Alev Garip, Asuman Camyar, Sibel Ilgun, Melih Ozisik, Sena Tuna, Murat Olukman i in. "The Effects of Vitamin D on Gentamicin-Induced Acute Kidney Injury in Experimental Rat Model". International Journal of Endocrinology 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/313528.
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Introduction. Acute kidney injury (AKI) pathogenesis is complex. Findings of gentamicin nephrotoxicity are seen in 30% of the AKI patients. Vitamin D has proven to be effective on renin expression, inflammatory response, oxidative stress, apoptosis, and atherosclerosis. We aimed to investigate the effect of vitamin D in an experimental rat model of gentamicin-induced AKI.Methods. Thirty nonuremic Wistar albino rats were divided into 3 groups: Control group, 1 mL saline intramuscular (im) daily; Genta group, gentamicin 100 mg/kg/day (im); Genta + vitamin D, gentamicin 100 mg/kg/day (im) in addition to 1α, 25 (OH)2D30.4 mcg/kg/day subcutaneously for 8 days. Blood pressures and 24-hour urine were measured. Blood urea and creatinine levels and urine tubular injury markers were measured. Renal histology was semiquantitatively assessed.Results. Urea, creatinine and urine neutrophil gelatinase-associated lipocalin, and kidney injury molecule-1 were all increased in Genta group indicating AKI model. Systolic blood pressure decreased, but urine volume and glutathione increased in Genta + Vit D group compared to Control group. Histological scores indicating tubular injury increased in Genta and Genta + Vit D groups.Conclusions. Vitamin D does not seem to be effective on histological findings although it has some beneficial effects via RAS system and a promising effect on antioxidant system.
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Richter, Jan, Gerhard Metzner i Ulrich Behn. "Mathematical Modelling of Venom Immunotherapy". Journal of Theoretical Medicine 4, nr 2 (2002): 119–32. http://dx.doi.org/10.1080/10273660290022172.
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Allergic hypersensitivity of type I for hymenoptera venoms is the most frequent reason for acute IgE-mediated anaphylactic reactions. The subcutaneous injection of increasing doses of purified allergen followed by long-term administration of an adequate maintenance dose over a period of 3–5 years called venom immunotherapy (VIT) has been proven to be a very effective treatment achieving protection in about 96% of allergic patients. Even though the principle of hyposensitisation has been introduced already 90 years ago, the underlying immunoregulatory mechanisms of VIT remain poorly understood. Recent studies suggest a shift in cytokine production from a Th2 to a Th1 cytokine profile during therapy. In this paper, a mathematical model for T-cell regulation and a model for mast cell/basophil desensitisation are presented and analysed to explain the mechanism of conventional rush and ultra-rush VIT.
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Chen, Shuwen, Siyuan Lu, Shuihua Wang, Yiyang Ni i Yudong Zhang. "Shifted Window Vision Transformer for Blood Cell Classification". Electronics 12, nr 11 (28.05.2023): 2442. http://dx.doi.org/10.3390/electronics12112442.
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Blood cells play an important role in the metabolism of the human body, and the status of blood cells can be used for clinical diagnoses, such as the ratio of different blood cells. Therefore, blood cell classification is a primary task, which requires much time for manual analysis. The recent advances in computer vision can be beneficial to free doctors from tedious tasks. In this paper, a novel automated blood cell classification model based on the shifted window vision transformer (SW-ViT) is proposed. The SW-ViT architecture is firstly pre-trained on the ImageNet dataset and fine-tuned on the blood cell images for classification. Two transfer strategies are employed to generate better classification results. One is to fine-tune the entire SW-ViT, and the other is to only fine-tune the linear output layer of the SW-ViT while all the other parameters are frozen. A public dataset named BCCD_Dataset (Blood Cell Count and Detection) is utilized in the experiments. The results show that the SW-ViT outperforms several state-of-the-art methods in terms of classification accuracy. The proposed SW-ViT can be applied in daily clinical diagnosis.
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Wang, Aili, Shuang Xing, Yan Zhao, Haibin Wu i Yuji Iwahori. "A Hyperspectral Image Classification Method Based on Adaptive Spectral Spatial Kernel Combined with Improved Vision Transformer". Remote Sensing 14, nr 15 (2.08.2022): 3705. http://dx.doi.org/10.3390/rs14153705.
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In recent years, methods based on deep convolutional neural networks (CNNs) have dominated the classification task of hyperspectral images. Although CNN-based HSI classification methods have the advantages of spatial feature extraction, HSI images are characterized by approximately continuous spectral information, usually containing hundreds of spectral bands. CNN cannot mine and represent the sequence properties of spectral features well, and the transformer model of attention mechanism proves its advantages in processing sequence data. This study proposes a new spectral spatial kernel combined with the improved Vision Transformer (ViT) to jointly extract spatial spectral features to complete classification task. First, the hyperspectral data are dimensionally reduced by PCA; then, the shallow features are extracted with an spectral spatial kernel, and the extracted features are input into the improved ViT model. The improved ViT introduces a re-attention mechanism and a local mechanism based on the original ViT. The re-attention mechanism can increase the diversity of attention maps at different levels. The local mechanism is introduced into ViT to make full use of the local and global information of the data to improve the classification accuracy. Finally, a multi-layer perceptron is used to obtain the classification result. Among them, the Focal Loss function is used to increase the loss weight of small-class samples and difficult-to-classify samples in HSI data samples and reduce the loss weight of easy-to-classify samples, so that the network can learn more useful hyperspectral image information. In addition, using the Apollo optimizer to train the HSI classification model to better update and compute network parameters that affect model training and model output, thereby minimizing the loss function. We evaluated the classification performance of the proposed method on four different datasets, and achieved good classification results on urban land object classification, crop classification and mineral classification, respectively. Compared with the state-of-the-art backbone network, the method achieves a significant improvement and achieves very good classification accuracy.