Understanding Data Augmentation from a Robustness Perspective

In the realm of visual recognition, data augmentation stands out as a pivotal technique to amplify model robustness. Yet, a considerable number of existing methodologies lean heavily on heuristic foundations, rendering their intrinsic mechanisms ambiguous. This manuscript takes both a theoretical and empirical approach to understanding the phenomenon. Theoretically, we frame the discourse around data augmentation within game theory's constructs. Venturing deeper, our empirical evaluations dissect the intricate mechanisms of emblematic data augmentation strategies, illuminating that these techniques primarily stimulate mid- and high-order game interactions. Beyond the foundational exploration, our experiments span multiple datasets and diverse augmentation techniques, underscoring the universal applicability of our findings. Recognizing the vast array of robustness metrics with intricate correlations, we unveil a streamlined proxy. This proxy not only simplifies robustness assessment but also offers invaluable insights, shedding light on the inherent dynamics of model game interactions and their relation to overarching system robustness. These insights provide a novel lens through which we can re-evaluate model safety and robustness in visual recognition tasks.Comment: Not published yet. arXiv admin note: text overlap with arXiv:2212.0405

Effect of non-invasive ventilator in combination with tiotropium bromide on pulmonary function and sleep quality of patients with chronic obstructive pulmonary disease complicated with obstructive sleep apnea-hypopnea syndrome

Purpose: To study the influence of non-invasive ventilator and tiotropium bromide on pulmonary function and sleep quality of patients with chronic obstructive pulmonary disease (COPD) combined with obstructive sleep apnea-hypopnea syndrome (OSAHS).Methods: One hundred and twenty patients with COPD-OSAHS were selected and randomly assigned to control group (CG) and treatment group (TG), with 60 subjects in each group. Non-invasive ventilator therapy was used in both groups, based on conventional therapy, while tiotropium bromide was added in TG. Treatment effectiveness in the two groups was evaluated and compared.Results: Total effectiveness was significantly higher in TG than in CG. Post-therapy arterial oxygen saturation (SaO2) and oxygen partial pressure (PaO2) were increased, while partial pressure of carbon dioxide (PaCO2) and lactic acid (Lac) were decreased in both groups (p < 0.05). Post-treatment values of indices of lung function, viz, forced expiratory volume (FEV1), forced vital capacity (FVC) and FEV1/FVC ratio were higher than the corresponding pre-treatment levels, and also values were significantly higher in TG than in CG (p < 0.05). Average sleep time, apnea and hypopnea index (AHI) and mechanical ventilation time of TG were less than those of CG. There were lower levels of Creactive protein (CRP), procalcitonin (PCT) and interleukin-17 (IL-17) in TG than in CG. During the treatment, no obvious adverse reaction was seen in both groups.Conclusion: Non-invasive ventilator, in combination with tiotropium bromide, is more effective in the treatment of COPD-OSAHS than the use of non-invasive ventilator alone. However, further clinical trials are required before its adoption in clinical practice

EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution

Recently, convolutional networks have achieved remarkable development in remote sensing image Super-Resoltuion (SR) by minimizing the regression objectives, e.g., MSE loss. However, despite achieving impressive performance, these methods often suffer from poor visual quality with over-smooth issues. Generative adversarial networks have the potential to infer intricate details, but they are easy to collapse, resulting in undesirable artifacts. To mitigate these issues, in this paper, we first introduce Diffusion Probabilistic Model (DPM) for efficient remote sensing image SR, dubbed EDiffSR. EDiffSR is easy to train and maintains the merits of DPM in generating perceptual-pleasant images. Specifically, different from previous works using heavy UNet for noise prediction, we develop an Efficient Activation Network (EANet) to achieve favorable noise prediction performance by simplified channel attention and simple gate operation, which dramatically reduces the computational budget. Moreover, to introduce more valuable prior knowledge into the proposed EDiffSR, a practical Conditional Prior Enhancement Module (CPEM) is developed to help extract an enriched condition. Unlike most DPM-based SR models that directly generate conditions by amplifying LR images, the proposed CPEM helps to retain more informative cues for accurate SR. Extensive experiments on four remote sensing datasets demonstrate that EDiffSR can restore visual-pleasant images on simulated and real-world remote sensing images, both quantitatively and qualitatively. The code of EDiffSR will be available at https://github.com/XY-boy/EDiffSRComment: Submitted to IEEE TGR

Local-Global Temporal Difference Learning for Satellite Video Super-Resolution

Optical-flow-based and kernel-based approaches have been widely explored for temporal compensation in satellite video super-resolution (VSR). However, these techniques involve high computational consumption and are prone to fail under complex motions. In this paper, we proposed to exploit the well-defined temporal difference for efficient and robust temporal compensation. To fully utilize the temporal information within frames, we separately modeled the short-term and long-term temporal discrepancy since they provide distinctive complementary properties. Specifically, a short-term temporal difference module is designed to extract local motion representations from residual maps between adjacent frames, which provides more clues for accurate texture representation. Meanwhile, the global dependency in the entire frame sequence is explored via long-term difference learning. The differences between forward and backward segments are incorporated and activated to modulate the temporal feature, resulting in holistic global compensation. Besides, we further proposed a difference compensation unit to enrich the interaction between the spatial distribution of the target frame and compensated results, which helps maintain spatial consistency while refining the features to avoid misalignment. Extensive objective and subjective evaluation of five mainstream satellite videos demonstrates that the proposed method performs favorably for satellite VSR. Code will be available at \url{https://github.com/XY-boy/TDMVSR}Comment: Submitted to IEEE TCSV

Architecture of Heptagonal Metallo-macrocycles via Embedding Metal Nodes Into Its Rigid Backbone

Metal-organic macrocycles have received increasing attention not only due to their versatile applications such as molecular recognition, compounds encapsulation, anti-bacteria and others, but also for their important role in the study of structure-property relationship at nano scale. However, most of the constructions utilize benzene ring as the backbone, which restricts the ligand arm angle in the range of 60, 120 and 180 degrees. Thus, the topologies of most metallo-macrocycles are limited as triangles and hexagons, and explorations of using other backbones with large angles and the construction of metallo-macrocycles with more than six edges are very rare. In this study, we present a novel strategy for self-assembly two giant heptagonal metallo-macrocycles with an inner diameter of 5 nm, by embedding metal nodes into the ligand backbone and regulating the ligand arm angle. By complexing with metal ions, the angle between two arms at the 4,4” position of the central terpyridine (tpy) was extended, resulting in ring expansion of the metallo-macrocycle. This approach enabled the construction of giant and more complex metallo- macrocycles that could not be achieved with traditional benzene ring backbones. The characterization of complex molecules often requires the use of multiple techniques, such as multi-dimensional and multinuclear NMR and multidimensional mass spectrometry analysis. Here, we also utilized transmission electron microscopy (TEM) and ultra-high vacuum (∼E-10 torr) low-temperature (∼77 K) scanning tunneling microscopy (UHV-LT-STM) to characterize complex supramolecules. The resulting metallo-macrocycles formed hierarchical self-assembled nanotube structures at larger densities, which is observed by TEM, while UHV-LT-STM was used for direct visualization of individual complex supramolecules deposited on an Au(111) substrate. Our findings indicate that UHV-LT-STM is an effective methodology for characterizing supramolecules at a single molecule level, providing more details of the molecular structure that is difficult to resolve by the resolution of TEM.https://digitalcommons.odu.edu/gradposters2023_sciences/1005/thumbnail.jp

Methyl Farnesoate Plays a Dual Role in Regulating \u3cem\u3eDrosophila\u3c/em\u3e Metamorphosis

Corpus allatum (CA) ablation results in juvenile hormone (JH) deficiency and pupal lethality in Drosophila. The fly CA produces and releases three sesquiterpenoid hormones: JH III bisepoxide (JHB3), JH III, and methyl farnesoate (MF). In the whole body extracts, MF is the most abundant sesquiterpenoid, followed by JHB3 and JH III. Knockout of JH acid methyl transferase (jhamt) did not result in lethality; it decreased biosynthesis of JHB3, but MF biosynthesis was not affected. RNAi-mediated reduction of 3-hydroxy-3-methylglutaryl CoA reductase (hmgcr) expression in the CA decreased biosynthesis and titers of the three sesquiterpenoids, resulting in partial lethality. Reducing hmgcr expression in the CA of the jhamt mutant further decreased MF titer to a very low level, and caused complete lethality. JH III, JHB3, and MF function through Met and Gce, the two JH receptors, and induce expression of Kr-h1, a JH primary-response gene. As well, a portion of MF is converted to JHB3 in the hemolymph or peripheral tissues. Topical application of JHB3, JH III, or MF precluded lethality in JH-deficient animals, but not in the Met gce double mutant. Taken together, these experiments show that MF is produced by the larval CA and released into the hemolymph, from where it exerts its anti-metamorphic effects indirectly after conversion to JHB3, as well as acting as a hormone itself through the two JH receptors, Met and Gce

Methyl Farnesoate Plays a Dual Role in Regulating \u3cem\u3eDrosophila\u3c/em\u3e Metamorphosis

Corpus allatum (CA) ablation results in juvenile hormone (JH) deficiency and pupal lethality in Drosophila. The fly CA produces and releases three sesquiterpenoid hormones: JH III bisepoxide (JHB3), JH III, and methyl farnesoate (MF). In the whole body extracts, MF is the most abundant sesquiterpenoid, followed by JHB3 and JH III. Knockout of JH acid methyl transferase (jhamt) did not result in lethality; it decreased biosynthesis of JHB3, but MF biosynthesis was not affected. RNAi-mediated reduction of 3-hydroxy-3-methylglutaryl CoA reductase (hmgcr) expression in the CA decreased biosynthesis and titers of the three sesquiterpenoids, resulting in partial lethality. Reducing hmgcr expression in the CA of the jhamt mutant further decreased MF titer to a very low level, and caused complete lethality. JH III, JHB3, and MF function through Met and Gce, the two JH receptors, and induce expression of Kr-h1, a JH primary-response gene. As well, a portion of MF is converted to JHB3 in the hemolymph or peripheral tissues. Topical application of JHB3, JH III, or MF precluded lethality in JH-deficient animals, but not in the Met gce double mutant. Taken together, these experiments show that MF is produced by the larval CA and released into the hemolymph, from where it exerts its anti-metamorphic effects indirectly after conversion to JHB3, as well as acting as a hormone itself through the two JH receptors, Met and Gce