Analysis of Building Energy Savings Potential for Metal Panel Curtain Wall Building by Reducing Thermal Bridges at Joints Between Panels

AbstractTo achieve national greenhouse gas reduction in the building sector, heating and cooling energy in buildings should be reduced. The government has strengthened regulations on insulation performance for building energy savings. However, the building envelope has various thermal bridges. In particular, a metal panel curtain wall comprises a number of thermal bridges at joints between the panels and the fixing units, thus degrading the overall thermal performance. To reduce building energy, it is necessary to reduce thermal bridges in building envelopes. This study aims to analyze the energy saving potential achieved by reducing thermal bridges. For this, the insulation performance and building energy needs of the existing and alternative metal panel curtain wall were evaluated. The alternative metal panel curtain wall that uses plastic molds at joints between panels and the thermally-broken brackets was suggested to reduce heat loss through thermal bridges. As results, the effective U-value of the alternative metal panel curtain wall was reduced by 72% compared with the existing metal panel curtain wall. In addition, annual heating energy needs of the alternative metal panel curtain wall building was reduced by 26%, and annual total energy needs was reduced by 6% because annual cooling energy needs of it slightly increased compared with the existing metal panel curtain wall. In conclusion, the alternative metal panel curtain wall considerably influenced the savings in building energy needs by reducing thermal bridges

Experimental Infection of Dogs with Avian-Origin Canine Influenza A Virus (H3N2)

Susceptible dogs were brought into contact with dogs experimentally infected with an avian-origin influenza A virus (H3N2) that had been isolated from a pet dog with severe respiratory syndrome. All the experimentally infected and contact-exposed dogs showed elevated rectal temperatures, virus shedding, seroconversion, and severe necrotizing tracheobronchitis and bronchioalveolitis

BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning

With the surge of large-scale pre-trained models (PTMs), fine-tuning these models to numerous downstream tasks becomes a crucial problem. Consequently, parameter efficient transfer learning (PETL) of large models has grasped huge attention. While recent PETL methods showcase impressive performance, they rely on optimistic assumptions: 1) the entire parameter set of a PTM is available, and 2) a sufficiently large memory capacity for the fine-tuning is equipped. However, in most real-world applications, PTMs are served as a black-box API or proprietary software without explicit parameter accessibility. Besides, it is hard to meet a large memory requirement for modern PTMs. In this work, we propose black-box visual prompting (BlackVIP), which efficiently adapts the PTMs without knowledge about model architectures and parameters. BlackVIP has two components; 1) Coordinator and 2) simultaneous perturbation stochastic approximation with gradient correction (SPSA-GC). The Coordinator designs input-dependent image-shaped visual prompts, which improves few-shot adaptation and robustness on distribution/location shift. SPSA-GC efficiently estimates the gradient of a target model to update Coordinator. Extensive experiments on 16 datasets demonstrate that BlackVIP enables robust adaptation to diverse domains without accessing PTMs' parameters, with minimal memory requirements. Code: \url{https://github.com/changdaeoh/BlackVIP}Comment: Accepted to CVPR 202

In vivo functional photoacoustic tomography of traumatic brain injury in rats

In this study, we demonstrate the potential of photoacoustic tomography for the study of traumatic brain injury (TBI) in rats in vivo. Based on spectroscopic photoacoustic tomography that can detect the absorption rates of oxy- and deoxy-hemoglobins, the blood oxygen saturation and total blood volume in TBI rat brains were visualized. Reproducible cerebral trauma was induced using a fluid percussion TBI device. The time courses of the hemodynamic response following the trauma initiation were imaged with multi-wavelength photoacoustic tomography with bandwidth-limited spatial resolution through the intact skin and skull. In the pilot set of experiments, trauma induced hematomas and blood oxygen saturation level changes were detected, a finding consistent with the known physiological responses to TBI. This new imaging method will be useful for future studies on TBI-related metabolic activities and the effects of therapeutic agents

Moisture dependence of electrical resistivity in under-percolated cement-based composites with multi-walled carbon nanotubes

Cement-based piezoresistive composites have attracted significant attention as smart construction materials for embedding self-sensing capability in concrete infrastructure. Although a number of studies have been conducted using multi-walled carbon nanotubes (MWCNTs) as a functional filler for self-sensing cement-based composites, studies addressing the influence of the internal moisture state on the electrical properties are relatively scant. In this study, we aim to experimentally investigate the effect of internal moisture state on the electrical resistivity of cement-based composites containing MWCNTs as an electrically conductive medium to raise a need for calibration of self-sensing data considering the internal moisture state. To this end, the moisture dependence of electrical resistivity in under-percolated cement-based composites was mainly evaluated, along with other material properties such as strength, shrinkage, and flowability. Results revealed that the electrical resistivity increased almost linearly as the internal relative humidity (IRH) decreased, and the increase was more pronounced below the percolation threshold. In addition, it was found that the strength gained by the microfiller effect of MWCNTs was significantly reduced particularly in under-percolated mixtures, leading to overall strength reductions. Furthermore, this study showed that the more the MWCNT was added, the smaller the flowability was obtained due to the increased viscosity of the mixture. The findings of this study are expected to provide pivotal information for accurate and reliable interpretations of self-sensing data generated by MWCNT-embedded cement-based composites

Effects of a radiation dose reduction strategy for computed tomography in severely injured trauma patients in the emergency department: an observational study

<p>Abstract</p> <p>Background</p> <p>Severely injured trauma patients are exposed to clinically significant radiation doses from computed tomography (CT) imaging in the emergency department. Moreover, this radiation exposure is associated with an increased risk of cancer. The purpose of this study was to determine some effects of a radiation dose reduction strategy for CT in severely injured trauma patients in the emergency department.</p> <p>Methods</p> <p>We implemented the radiation dose reduction strategy in May 2009. A prospective observational study design was used to collect data from patients who met the inclusion criteria during this one year study (intervention group) from May 2009 to April 2010. The prospective data were compared with data collected retrospectively for one year prior to the implementation of the radiation dose reduction strategy (control group). By comparison of the cumulative effective dose and the number of CT examinations in the two groups, we evaluated effects of a radiation dose reduction strategy. All the patients met the institutional adult trauma team activation criteria. The radiation doses calculated by the CT scanner were converted to effective doses by multiplication by a conversion coefficient.</p> <p>Results</p> <p>A total of 118 patients were included in this study. Among them, 33 were admitted before May 2009 (control group), and 85 were admitted after May 2009 (intervention group). There were no significant differences between the two groups regarding baseline characteristics, such as injury severity and mortality. Additionally, there was no difference between the two groups in the mean number of total CT examinations per patient (4.8 vs. 4.5, respectively; p = 0.227). However, the mean effective dose of the total CT examinations per patient significantly decreased from 78.71 mSv to 29.50 mSv (p < 0.001).</p> <p>Conclusions</p> <p>The radiation dose reduction strategy for CT in severely injured trauma patients effectively decreased the cumulative effective dose of the total CT examinations in the emergency department. But not effectively decreased the number of CT examinations.</p

Query-Efficient Black-Box Red Teaming via Bayesian Optimization

The deployment of large-scale generative models is often restricted by their potential risk of causing harm to users in unpredictable ways. We focus on the problem of black-box red teaming, where a red team generates test cases and interacts with the victim model to discover a diverse set of failures with limited query access. Existing red teaming methods construct test cases based on human supervision or language model (LM) and query all test cases in a brute-force manner without incorporating any information from past evaluations, resulting in a prohibitively large number of queries. To this end, we propose Bayesian red teaming (BRT), novel query-efficient black-box red teaming methods based on Bayesian optimization, which iteratively identify diverse positive test cases leading to model failures by utilizing the pre-defined user input pool and the past evaluations. Experimental results on various user input pools demonstrate that our method consistently finds a significantly larger number of diverse positive test cases under the limited query budget than the baseline methods. The source code is available at https://github.com/snu-mllab/Bayesian-Red-Teaming.Comment: ACL 2023 Long Paper - Main Conferenc