Bamboo Joints Review on the Millennium Bridge in Green School Bali

The Millennium Bridge in Green School Bali is a bamboo bridge building which is a unique building. This structure has local cultural value and has sustainable material. Bamboo, as its material, has been used in traditional way, but become popular lately according with sustainable issue nowadays. In general, this descriptive analytical research will evaluate the bamboo design of The Millennium bridge in The Green School Bali, especially focusing on the joints as constructional material, whether it has already conformed to the literature or not and seek the innovation of the architect for this matter. The analysis will be carried out after surveying the existing state in the form of the photos and making computer model of the researched object, then analyzing the form of the bridge. Keywords: The Millennium bridge, Bamboo bridge, Bamboo, Sustainable material, Green School Bali. DOI: 10.7176/ADS/91-04 Publication date:March 31st 202

Optimizing Filter Size in Convolutional Neural Networks for Facial Action Unit Recognition

Recognizing facial action units (AUs) during spontaneous facial displays is a challenging problem. Most recently, Convolutional Neural Networks (CNNs) have shown promise for facial AU recognition, where predefined and fixed convolution filter sizes are employed. In order to achieve the best performance, the optimal filter size is often empirically found by conducting extensive experimental validation. Such a training process suffers from expensive training cost, especially as the network becomes deeper. This paper proposes a novel Optimized Filter Size CNN (OFS-CNN), where the filter sizes and weights of all convolutional layers are learned simultaneously from the training data along with learning convolution filters. Specifically, the filter size is defined as a continuous variable, which is optimized by minimizing the training loss. Experimental results on two AU-coded spontaneous databases have shown that the proposed OFS-CNN is capable of estimating optimal filter size for varying image resolution and outperforms traditional CNNs with the best filter size obtained by exhaustive search. The OFS-CNN also beats the CNN using multiple filter sizes and more importantly, is much more efficient during testing with the proposed forward-backward propagation algorithm

High-density Vero cell perfusion culture in BioBLU 5p Single-Use Vessels

Vero cells are anchorage-dependent cells that are widely used as a platform for viral vaccine production. In stirred-tank bioreactors, they are ordinarily grown on microcarriers. Fibra-Cel® disks are a promising alternative attachment matrix with a high surface-to-volume ratio. They provide a three-dimensional environment that protects cells from damaging shear forces, helping to achieve high cell densities. In this study, we cultivated Vero cells in Eppendorf BioBLU 5p Single-Use Vessels pre-packed with Fibra-Cel. The process was controlled with a BioFlo® 320 bioprocess control station. We cultivated the cells in perfusion mode, which ensures a consistent supply of nutrients and the removal of toxic byproducts. We achieved the very high Vero cell density of approximately 43 million cells per mL, demonstrating great potential for Vero-cell-based vaccine production using Fibra-Cel packed-bed vessels

Cell culture scale-up in BioBLU® c rigid-wall, single-use bioreactors

For cultivation of mammalian cells in biopharmaceutical research and manufacturing, single-use technology possesses several advantages to autoclavable material. Bioreactor scalability is critical to streamlining the adaptation of culture volumes during process development and manufacturing. We analyzed BioBLU Single-Use Vessels of different sizes (maximum working volumes of 0.25 L, 3.75 L, and 40 L) that are of geometrically similar stirred-tank design. We identified a scalable tip speed zone and an overlapping range of kLa values, which cover most mammalian cell culture needs. Using computational fluid dynamics simulations we determined the power numbers of the BioBLU bioreactors. Based on these data we scaled up a mAb production process in CHO cells from 250 mL to 3.75 L to 40 L by keeping constant P/V values (impeller power consumption per liquid volume) among the differently sized vessels. Similar cell growth curves and mAb production profiles were achieved at all three scales. In summary, this study demonstrates the excellent scalability of the single-use bioreactors tested

Dynamic Acoustic Compensation and Adaptive Focal Training for Personalized Speech Enhancement

Recently, more and more personalized speech enhancement systems (PSE) with excellent performance have been proposed. However, two critical issues still limit the performance and generalization ability of the model: 1) Acoustic environment mismatch between the test noisy speech and target speaker enrollment speech; 2) Hard sample mining and learning. In this paper, dynamic acoustic compensation (DAC) is proposed to alleviate the environment mismatch, by intercepting the noise or environmental acoustic segments from noisy speech and mixing it with the clean enrollment speech. To well exploit the hard samples in training data, we propose an adaptive focal training (AFT) strategy by assigning adaptive loss weights to hard and non-hard samples during training. A time-frequency multi-loss training is further introduced to improve and generalize our previous work sDPCCN for PSE. The effectiveness of proposed methods are examined on the DNS4 Challenge dataset. Results show that, the DAC brings large improvements in terms of multiple evaluation metrics, and AFT reduces the hard sample rate significantly and produces obvious MOS score improvement