Effects of Aging Time and Natural Antioxidants on the Quality of Irradiated Ground Beef

Beef rounds aged for one, two, or three weeks after slaughtering were ground added with 0.05% ascorbic acid + 0.01% α-tocopherol or 0.05% ascorbic acid + 0.01% α- tocopherol + 0.01% sesamol, placed on Styrofoam trays and wrapped with oxygen permeable plastic film, and treated with electron beam irradiation at 0 or 2.5 kGy. The meat samples were displayed under fluorescent light for 7 d at 4° C. Color, lipid oxidation, and volatiles were determined at 0, 3, and 7 d of storage. Irradiation increased lipid oxidation of ground beef regardless of their aging time and storage period. As aging time increased lipid oxidation increased. Adding sesamol increased the effectiveness of ascorbate and tocopherol combination in reducing lipid oxidation especially as aging and storage time increased. The redness of beef were decreased by irradiation and adding ascorbic acid and α-tocopherol before irradiation was effective in maintaining the redness of irradiated ground beef over the storage period. Volatile aldehydes increased only in irradiated control beef. Antioxidant treatments were effective in reducing aldehydes in ground beef during storage

Cross-Modal Learning with 3D Deformable Attention for Action Recognition

An important challenge in vision-based action recognition is the embedding of spatiotemporal features with two or more heterogeneous modalities into a single feature. In this study, we propose a new 3D deformable transformer for action recognition with adaptive spatiotemporal receptive fields and a cross-modal learning scheme. The 3D deformable transformer consists of three attention modules: 3D deformability, local joint stride, and temporal stride attention. The two cross-modal tokens are input into the 3D deformable attention module to create a cross-attention token with a reflected spatiotemporal correlation. Local joint stride attention is applied to spatially combine attention and pose tokens. Temporal stride attention temporally reduces the number of input tokens in the attention module and supports temporal expression learning without the simultaneous use of all tokens. The deformable transformer iterates L times and combines the last cross-modal token for classification. The proposed 3D deformable transformer was tested on the NTU60, NTU120, FineGYM, and Penn Action datasets, and showed results better than or similar to pre-trained state-of-the-art methods even without a pre-training process. In addition, by visualizing important joints and correlations during action recognition through spatial joint and temporal stride attention, the possibility of achieving an explainable potential for action recognition is presented.Comment: 10 pages, 8 figure

Pharmacological utilization of bergamottin, derived from grapefruits, in cancer prevention and therapy

In spite of significant advances in treatment options and the advent of novel targeted therapies, there still remains an unmet need for the identification of novel pharmacological agents for cancer therapy. This has led to several studies evaluating the possible application of natural agents found in vegetables, fruits, or plant-derived products that may be useful for cancer treatment. Bergamottin is a furanocoumarin derived from grapefruits and is also a well-known cytochrome P450 inhibitor. Recent studies have demonstrated potent anti-oxidative, anti-inflammatory, and anti-cancer properties of grapefruit furanocoumarin both in vitro and in vivo. The present review focuses on the potential anti-neoplastic effects of bergamottin in different tumor models and briefly describes the molecular targets affected by this agent

Simultaneous Optimization of Launch Vehicle Stage and Trajectory Considering Operational Safety Constraints

A conceptual design of a launch vehicle involves the optimization of trajectory and stages considering its launch operations. This process encompasses various disciplines, such as structural design, aerodynamics, propulsion systems, flight control, and stage sizing. Traditional approaches used for the conceptual design of a launch vehicle conduct the stage and trajectory designs sequentially, often leading to high computational complexity and suboptimal results. This paper presents an optimization framework that addresses both trajectory optimization and staging in an integrated way. The proposed framework aims to maximize the payload-to-liftoff mass ratio while satisfying the constraints required for safe launch operations (e.g., the impact points of burnt stages and fairing). A case study demonstrates the advantage of the proposed framework compared to the traditional sequential optimization approach.Comment: 25 page

Packaging Determines Color and Odor of Irradiated Ground Beef

Irradiation of ground beef under aerobic conditions oxidized myoglobin and drastically reduced color a*-values. Under vacuum or non-oxygen conditions, however, irradiation did not influence the redness of ground beef. Also, the red color of ground beef was maintained even after the irradiated beef was exposed to aerobic conditions. Vacuum-packaged irradiated ground beef had lower metmyoglobin content and lower oxidation-reduction potential than the aerobically packaged ones. Irradiating ground beef under vacuum-packaging conditions was also advantageous in preventing lipid oxidation and aldehydes production. Vacuum-packaged irradiated beef, however, produced high levels of sulfur volatiles during irradiation and maintained their levels during storage, which resulted in the production of characteristic irradiation off-odor. Double-packaging (V3/A3: vacuum-packaging during irradiation and the first 3 days of storage and then aerobic-packaging for the remaining 3 days) was an effective alternative in maintaining original beef color (red), and minimizing lipid oxidation and irradiation off-odor. The levels of off-odor volatiles in double-packaged irradiated ground beef were comparable to that of aerobically packaged ones, and the degree of lipid oxidation and color changes were close to those of vacuum-packaged ones. Ascorbic acid at 200 ppm level was not effective in preventing color changes and lipid oxidation in irradiated ground beef under aerobic conditions, but was helpful in minimizing quality changes in doublepackaged irradiated ground beef. This suggested that preventing oxygen contact from meat during irradiation and early storage period (V3/A3 double-packaging) and doublepackaging+ascorbic acid combination are excellent strategies to prevent off-odor production and color changes in irradiated ground beef. Developing methods that can prevent quality changes of irradiated beef is important for the implication of irradiation, which will improve the safety of beef

Optical Probing of Electronic Interaction between Graphene and Hexagonal Boron Nitride

Even weak van der Waals (vdW) adhesion between two-dimensional solids may perturb their various materials properties owing to their low dimensionality. Although the electronic structure of graphene has been predicted to be modified by the vdW interaction with other materials, its optical characterization has not been successful. In this report, we demonstrate that Raman spectroscopy can be utilized to detect a few % decrease in the Fermi velocity (vF) of graphene caused by the vdW interaction with underlying hexagonal boron nitride (hBN). Our study also establishes Raman spectroscopic analysis which enables separation of the effects by the vdW interaction from those by mechanical strain or extra charge carriers. The analysis reveals that spectral features of graphene on hBN are mainly affected by change in vF and mechanical strain, but not by charge doping unlike graphene supported on SiO2 substrates. Graphene on hBN was also found to be less susceptible to thermally induced hole doping.Comment: 19 pages, 4 figure

Fine tuning Pre trained Models for Robustness Under Noisy Labels

The presence of noisy labels in a training dataset can significantly impact the performance of machine learning models. To tackle this issue, researchers have explored methods for Learning with Noisy Labels to identify clean samples and reduce the influence of noisy labels. However, constraining the influence of a certain portion of the training dataset can result in a reduction in overall generalization performance. To alleviate this, recent studies have considered the careful utilization of noisy labels by leveraging huge computational resources. Therefore, the increasing training cost necessitates a reevaluation of efficiency. In other areas of research, there has been a focus on developing fine-tuning techniques for large pre-trained models that aim to achieve both high generalization performance and efficiency. However, these methods have mainly concentrated on clean datasets, and there has been limited exploration of the noisy label scenario. In this research, our aim is to find an appropriate way to fine-tune pre-trained models for noisy labeled datasets. To achieve this goal, we investigate the characteristics of pre-trained models when they encounter noisy datasets. Through empirical analysis, we introduce a novel algorithm called TURN, which robustly and efficiently transfers the prior knowledge of pre-trained models. The algorithm consists of two main steps: (1) independently tuning the linear classifier to protect the feature extractor from being distorted by noisy labels, and (2) reducing the noisy label ratio and fine-tuning the entire model based on the noise-reduced dataset to adapt it to the target dataset. The proposed algorithm has been extensively tested and demonstrates efficient yet improved denoising performance on various benchmarks compared to previous methods.Comment: 10 pages (17 pages including supplementary