Performance Evaluation of Precast Concrete Using Microwave Heating Form

The purpose of this study is to evaluate the temperature distribution, strength development, porosity, scanning electron microscopy observation, shrinkage, and surface properties of concrete in order to apply microwave heat curing to the precast method and to analyze the CO2 emissions and economic feasibility of microwave heat curing. The heating of a steel form by microwave heating enabled concrete to be efficiently cured at a temperature within a range of _5 _C. After the curing, demolding strength could be cleared through the densification of the concrete by decreasing the porosity of the concrete. Microwave heat curing exhibited excellent performance compared to conventional steam curing in terms of efficient temperature control, occurrence of cracks due to shrinkage, surface condition of concrete after curing, economic efficiency, and CO2 emissions. However, verification and supplementation based on actual data are necessary so that environments applicable to the various sizes and shapes of forms can be prepared

The Relationship Between An Auditing Firm's Characteristics And The Incidence Rate Of Its Clients Subject To AAERs

This paper examines the relationship between an auditors characteristics and the incidence rate of its client subject to the Accounting and Auditing Enforcement Release. Using the sample of AAERs from 2002 to 2006, we find that when a firm is audited from a large accounting firm, there is a significantly less incidence rate subject to AAERs. Also, we find that the audit time of AAERs firms is significantly less than that of non-AAERs firms. Because AAER is related with audit quality, it implies that AAER depends on audit time and audit firm size, and that a firm is affected by the incidence rate of subjects toward AAERs. However, there is no difference between the audit fee of AAERs firms audit fee and that of non-AAERs firms. Although audit time leads to a high audit fee, audit firms are very competitive and therefore, there are some limitations with receiving a high audit fee according to audit time. Therefore, the audit fee is significantly affected by the incidence rate of subjects toward AAERs. Additionally, we also examine the effectiveness of AAERs and the difference of audit efforts depending on the cause of AAERs and the degree of penalties imposed by FSS. Overall, the results suggest that depending on the auditors characteristics, such as the size of accounting firm, audit time, and audit fee, a company is affected by the incidence rate subject to AAERs

Unified Contrastive Fusion Transformer for Multimodal Human Action Recognition

Various types of sensors have been considered to develop human action recognition (HAR) models. Robust HAR performance can be achieved by fusing multimodal data acquired by different sensors. In this paper, we introduce a new multimodal fusion architecture, referred to as Unified Contrastive Fusion Transformer (UCFFormer) designed to integrate data with diverse distributions to enhance HAR performance. Based on the embedding features extracted from each modality, UCFFormer employs the Unified Transformer to capture the inter-dependency among embeddings in both time and modality domains. We present the Factorized Time-Modality Attention to perform self-attention efficiently for the Unified Transformer. UCFFormer also incorporates contrastive learning to reduce the discrepancy in feature distributions across various modalities, thus generating semantically aligned features for information fusion. Performance evaluation conducted on two popular datasets, UTD-MHAD and NTU RGB+D, demonstrates that UCFFormer achieves state-of-the-art performance, outperforming competing methods by considerable margins

Effects of Cytokine Milieu Secreted by BCG-treated Dendritic Cells on Allergen-Specific Th Immune Response

Bacillus Calmette-Guérin (BCG) is reported to suppress Th2 response and asthmatic reaction. Dendritic cells (DCs), the major antigen-presenting cells, infections with BCG are known to result in inducing various cytokines. Thus, DCs are likely to play a role in the effects of BCG on asthma. This study aims at investigating that cytokine milieu secreted by BCG-treated DCs directly enhances allergen-specific Th1 response and/or suppresses Th2 response in allergic asthma. DCs and CD3+ T cells were generated from Dermatophagoides farinae-sensitive asthmatics. DCs were cultured with and without BCG and subjected to flow cytometric analysis. IL-12 and IL-10 were determined from the culture supernatants. Some DCs were cocultured with T cells in the presence of D. farinae extracts after adding the culture supernatants from BCG-treated DCs, and IL-5 and IFN-γ were determined. BCG-treated DCs enhanced significantly the expressions of CD80, CD86, and CD40, and the productions of IL-12 and IL-10. Addition of culture supernatants from BCG-treated DCs up-regulated production of IFN-γ by T cells stimulated by DCs and D. farinae extracts (p<0.05), but did not down-regulate production of IL-5 (p>0.05). The cytokine milieu secreted by BCG-treated DCs directly enhanced allergen-specific Th1 response, although did not suppress Th2 response

Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection

Developing high-performance, real-time architectures for LiDAR-based 3D object detectors is essential for the successful commercialization of autonomous vehicles. Pillar-based methods stand out as a practical choice for onboard deployment due to their computational efficiency. However, despite their efficiency, these methods can sometimes underperform compared to alternative point encoding techniques such as Voxel-encoding or PointNet++. We argue that current pillar-based methods have not sufficiently captured the fine-grained distributions of LiDAR points within each pillar structure. Consequently, there exists considerable room for improvement in pillar feature encoding. In this paper, we introduce a novel pillar encoding architecture referred to as Fine-Grained Pillar Feature Encoding (FG-PFE). FG-PFE utilizes Spatio-Temporal Virtual (STV) grids to capture the distribution of point clouds within each pillar across vertical, temporal, and horizontal dimensions. Through STV grids, points within each pillar are individually encoded using Vertical PFE (V-PFE), Temporal PFE (T-PFE), and Horizontal PFE (H-PFE). These encoded features are then aggregated through an Attentive Pillar Aggregation method. Our experiments conducted on the nuScenes dataset demonstrate that FG-PFE achieves significant performance improvements over baseline models such as PointPillar, CenterPoint-Pillar, and PillarNet, with only a minor increase in computational overhead.Comment: ICRA 202