A robust method for reliability updating with equality information using sequential adaptive importance sampling

Reliability updating refers to a problem that integrates Bayesian updating technique with structural reliability analysis and cannot be directly solved by structural reliability methods (SRMs) when it involves equality information. The state-of-the-art approaches transform equality information into inequality information by introducing an auxiliary standard normal parameter. These methods, however, encounter the loss of computational efficiency due to the difficulty in finding the maximum of the likelihood function, the large coefficient of variation (COV) associated with the posterior failure probability and the inapplicability to dynamic updating problems where new information is constantly available. To overcome these limitations, this paper proposes an innovative method called RU-SAIS (reliability updating using sequential adaptive importance sampling), which combines elements of sequential importance sampling and K-means clustering to construct a series of important sampling densities (ISDs) using Gaussian mixture. The last ISD of the sequence is further adaptively modified through application of the cross entropy method. The performance of RU-SAIS is demonstrated by three examples. Results show that RU-SAIS achieves a more accurate and robust estimator of the posterior failure probability than the existing methods such as subset simulation.Comment: 38 pages, 6 tables, 9 figure

Hypoxia and cell death in grape berries (Vitis vinifera L.)

Cell death in the mesocarp of berries occurs late in the ripening process, and may influence berry sensory attributes and water retention. There are cultivar-dependent correlations between mesocarp cell death and berry shrivel. Cell death is likely to be associated with yield losses of up to 30% for Shiraz due to berry shrivel, which concentrates sugars and potentially leads to high alcohol content in wine. The main objective of this thesis was to investigate the association between berry internal oxygen concentrations and berry cell death. Experiments were carried out at the Waite vineyards and at the SARDI research vineyard in Nuriootpa. Firstly, in Chapter 2, internal oxygen concentration ([O₂]) across the mesocarp was measured in berries from Chardonnay and Shiraz, both seeded, and Ruby Seedless, from the Waite vineyards, using an oxygen micro-sensor. Change of berry and seed respiration was investigated in Chardonnay. The lenticel density of Chardonnay and Shiraz berry pedicels (stem and receptacle) was assessed. We then tested the long-term effect of blocking pedicel lenticels on berry internal [O₂] profiles and cell death. Air spaces within the Chardonnay berries at different developmental stages were visualized using x-ray micro-CT. Second, in Chapter 3, a factorial trial of two irrigation regimes was applied in season 2014/2015 and a factorial trial of two irrigation regimes and two temperatures was applied in season 2015/2016, in Nuriootpa. Midday stem water potential, stomatal conductance and photosynthetic rate were measured to examine the efficiency of drought and canopy heating treatments. The oxygen micro-sensor was used to measure oxygen concentration in grapes and their respiration rate. Lastly, in Chapter 4, we tested the effects of overhead shading (2014/2015), rootstocks and kaolin application (both in 2016/2017), on Shiraz berry cell death and berry shrivel. In Chardonnay, Shiraz and Ruby Seedless grapes, steep [O₂] gradients were observed across the skin and [O₂] decreased toward the middle of the mesocarp. As ripening progressed, the minimum [O₂] approached zero in the seeded cultivars and correlated to the profile of cell death across the mesocarp. Seed respiration declined during ripening, from a large proportion of total berry respiration early to negligible at latter stages. [O₂] increased towards the central axis corresponding to the presence of air spaces visualised using x-ray micro-CT. These air spaces connect to the pedicel where lenticels are located that are critical for berry O₂ uptake as a function of temperature, and when blocked caused hypoxia in Chardonnay berries, ethanol accumulation and cell death. This work has been published in the Journal of Experimental Botany in February 2018. In Chapter 3, the results of a factorial field experiment comprising two thermal regimes (ambient and heated) and two irrigation regimes (irrigated and non-irrigated) are reported. Non-irrigation, in the first season, increased the rate of cell death relative to control irrigated Shiraz vines. In the second season, non-irrigation advanced the onset of cell death relative to the irrigated treatments independent of temperature. Non-irrigation treatments in the second season also decreased [O₂] within the berry mesocarp relative to the irrigated treatments. An association was established between mesocarp [O₂] and berry cell death. Berry respiration and total berry porosity were also found to decrease during berry ripening. This work has been submitted to the Australian Journal of Grape and Wine Research in February 2018. In Chapter 4, three preliminary trials were undertaken to investigate possible mitigation strategies for berry cell death and dehydration. Trial 1 tested the effect of overhead shading on berry dehydration, cell death and internal oxygen concentrations [O₂]. Trial 2 tested the effect of rootstocks having different drought tolerance on berry dehydration and cell death. Trial 3 tested the effect of kaolin spray, which has been proposed to reduce leaf and cluster temperature and transpiration. Overhead shading reduced the rate of increase in cell death and berry dehydration in Shiraz. This treatment also affected the progression of hypoxia in the berry. Shiraz on the drought tolerant 140 Ruggeri had significantly less cell death and berry dehydration than the less drought tolerant rootstocks (420 A and Schwarzmann). Kaolin spray application reduced berry shrinkage independently of either mesocarp cell death or cluster and leaf temperature. In summary, grape internal [O₂] declined during fruit development and was correlated with the profile of mesocarp cell death. Lenticels on the pedicel provided a pathway for O₂ diffusion into the berry and when covered to restrict O2 diffusion into the berry caused a large reduction in [O₂] in the centre of the berry, an increase in ethanol concentration and cell death. Differences in internal O₂ availability of berries between cultivars could be associated with seed development and differences in lenticel surface area. Higher rates of mesocarp cell death caused by water stress was also associated with hypoxia within grape berries. Rootstocks with different drought resistance properties can affect Shiraz berry dehydration and cell death. Kaolin can effectively reduce Shiraz dehydration after the peak berry mass was reached. The data generated in this study provides the basis for further research into the role of berry gas exchange on berry quality and cultivar selection for adapting viticulture to a warming climate. Understanding the association between berry internal oxygen status and berry shrivel and cell death, as well as the effect of strategies to mitigate cell death and berry shrivel, will provide researchers and growers with new insights in berry ripening and is the basis for future research on berry flavour development and yield optimization.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 201

A Dive into SAM Prior in Image Restoration

The goal of image restoration (IR), a fundamental issue in computer vision, is to restore a high-quality (HQ) image from its degraded low-quality (LQ) observation. Multiple HQ solutions may correspond to an LQ input in this poorly posed problem, creating an ambiguous solution space. This motivates the investigation and incorporation of prior knowledge in order to effectively constrain the solution space and enhance the quality of the restored images. In spite of the pervasive use of hand-crafted and learned priors in IR, limited attention has been paid to the incorporation of knowledge from large-scale foundation models. In this paper, we for the first time leverage the prior knowledge of the state-of-the-art segment anything model (SAM) to boost the performance of existing IR networks in an parameter-efficient tuning manner. In particular, the choice of SAM is based on its robustness to image degradations, such that HQ semantic masks can be extracted from it. In order to leverage semantic priors and enhance restoration quality, we propose a lightweight SAM prior tuning (SPT) unit. This plug-and-play component allows us to effectively integrate semantic priors into existing IR networks, resulting in significant improvements in restoration quality. As the only trainable module in our method, the SPT unit has the potential to improve both efficiency and scalability. We demonstrate the effectiveness of the proposed method in enhancing a variety of methods across multiple tasks, such as image super-resolution and color image denoising.Comment: Technical Repor

Toward Real-World Light Field Super-Resolution

Deep learning has opened up new possibilities for light field super-resolution (SR), but existing methods trained on synthetic datasets with simple degradations (e.g., bicubic downsampling) suffer from poor performance when applied to complex real-world scenarios. To address this problem, we introduce LytroZoom, the first real-world light field SR dataset capturing paired low- and high-resolution light fields of diverse indoor and outdoor scenes using a Lytro ILLUM camera. Additionally, we propose the Omni-Frequency Projection Network (OFPNet), which decomposes the omni-frequency components and iteratively enhances them through frequency projection operations to address spatially variant degradation processes present in all frequency components. Experiments demonstrate that models trained on LytroZoom outperform those trained on synthetic datasets and are generalizable to diverse content and devices. Quantitative and qualitative evaluations verify the superiority of OFPNet. We believe this work will inspire future research in real-world light field SR.Comment: CVPRW 202

Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models

Fine-tuning pre-trained vision-language models (VLMs), e.g., CLIP, for the open-world generalization has gained increasing popularity due to its practical value. However, performance advancements are limited when relying solely on intricate algorithmic designs for a single model, even one exhibiting strong performance, e.g., CLIP-ViT-B/16. This paper, for the first time, explores the collaborative potential of leveraging much weaker VLMs to enhance the generalization of a robust single model. The affirmative findings motivate us to address the generalization problem from a novel perspective, i.e., ensemble of pre-trained VLMs. We introduce three customized ensemble strategies, each tailored to one specific scenario. Firstly, we introduce the zero-shot ensemble, automatically adjusting the logits of different models based on their confidence when only pre-trained VLMs are available. Furthermore, for scenarios with extra few-shot samples, we propose the training-free and tuning ensemble, offering flexibility based on the availability of computing resources. The proposed ensemble strategies are evaluated on zero-shot, base-to-new, and cross-dataset generalization, achieving new state-of-the-art performance. Notably, this work represents an initial stride toward enhancing the generalization performance of VLMs via ensemble. The code is available at https://github.com/zhiheLu/Ensemble_VLM.git.Comment: Technical repor

Hypoxia in grape berries : the role of seed respiration and lenticels on the berry pedicel and the possible link to cell death

Mesocarp cell death (CD) during ripening is common in berries of seeded Vitis vinifera L. wine cultivars. We examined if hypoxia within berries is linked to CD. The internal oxygen concentration ([O 2 ]) across the mesocarp was measured in berries from Chardonnay and Shiraz, both seeded, and Ruby Seedless, using an oxygen micro-sensor. Steep [O 2 ] gradients were observed across the skin and [O 2 ] decreased toward the middle of the mesocarp. As ripening progressed, the minimum [O 2 ] approached zero in the seeded cultivars and correlated to the profile of CD across the mesocarp. Seed respiration declined during ripening, from a large proportion of total berry respiration early to negligible at later stages. [O 2 ] increased towards the central axis corresponding to the presence of air spaces visualized using X-ray micro-computed tomography (CT). These air spaces connect to the pedicel where lenticels are located that are critical for berry O 2 uptake as a function of temperature, and when blocked caused hypoxia in Chardonnay berries, ethanol accumulation, and CD. The implications of hypoxia in grape berries are discussed in terms of its role in CD, ripening, and berry water relations. © The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Experimental Biology

DNA Self-Assembly of Targeted Near-Infrared-Responsive Gold Nanoparticles for Cancer Thermo-Chemotherapy

Targeted Cancer Therapy: Inspired by the ability of DNA hybridization, a targeted near-infrared (NIR) light-responsive delivery system has been developed through simple DNA self-assembly (PEG=polyethylene glycol). This DNA-based platform shows the ability of releasing therapeutics upon near-infrared irradiation, and remarkable targeted thermo- and chemotherapeutic efficacy in vitro and in vivo

ReDas: Supporting Fine-Grained Reshaping and Multiple Dataflows on Systolic Array

Current systolic arrays still suffer from low performance and PE utilization on many real workloads due to the mismatch between the fixed array topology and diverse DNN kernels. We present ReDas, a flexible and lightweight systolic array that can adapt to various DNN models by supporting dynamic fine-grained reshaping and multiple dataflows. The key idea is to construct reconfigurable roundabout data paths using only the short connections between neighbor PEs. The array with 128$\times$128 size supports 129 different logical shapes and 3 dataflows (IS/OS/WS). Experiments on DNN models of MLPerf demonstrate that ReDas can achieve 3.09x speedup on average compared to state-of-the-art work.Comment: 7 pages, 11 figures, conferenc