Pixel-Level Equalized Matching for Video Object Segmentation

Feature similarity matching, which transfers the information of the reference frame to the query frame, is a key component in semi-supervised video object segmentation. If surjective matching is adopted, background distractors can easily occur and degrade the performance. Bijective matching mechanisms try to prevent this by restricting the amount of information being transferred to the query frame, but have two limitations: 1) surjective matching cannot be fully leveraged as it is transformed to bijective matching at test time; and 2) test-time manual tuning is required for searching the optimal hyper-parameters. To overcome these limitations while ensuring reliable information transfer, we introduce an equalized matching mechanism. To prevent the reference frame information from being overly referenced, the potential contribution to the query frame is equalized by simply applying a softmax operation along with the query. On public benchmark datasets, our proposed approach achieves a comparable performance to state-of-the-art methods

An Active and Soft Hydrogel Actuator to Stimulate Live Cell Clusters by Self-folding

The hydrogels are widely used in various applications, and their successful uses depend on controlling the mechanical properties. In this study, we present an advanced strategy to develop hydrogel actuator designed to stimulate live cell clusters by self-folding. The hydrogel actuator consisting of two layers with different expansion ratios were fabricated to have various curvatures in self-folding. The expansion ratio of the hydrogel tuned with the molecular weight and concentration of gel-forming polymers, and temperature-sensitive molecules in a controlled manner. As a result, the hydrogel actuator could stimulate live cell clusters by compression and tension repeatedly, in response to temperature. The cell clusters were compressed in the 0.7-fold decreases of the radius of curvature with 1.0 mm in room temperature, as compared to that of 1.4 mm in 37 degrees C. Interestingly, the vascular endothelial growth factor (VEGF) and insulin-like growth factor-binding protein-2 (IGFBP-2) in MCF-7 tumor cells exposed by mechanical stimulation was expressed more than in those without stimulation. Overall, this new strategy to prepare the active and soft hydrogel actuator would be actively used in tissue engineering, drug delivery, and micro-scale actuators

3D Cell Printed Tissue Analogues: A New Platform for Theranostics

Stem cell theranostics has received much attention for noninvasively monitoring and tracing transplanted therapeutic stem cells through imaging agents and imaging modalities. Despite the excellent regenerative capability of stem cells, their efficacy has been limited due to low cellular retention, low survival rate, and low engraftment after implantation. Three-dimensional (3D) cell printing provides stem cells with the similar architecture and microenvironment of the native tissue and facilitates the generation of a 3D tissue-like construct that exhibits remarkable regenerative capacity and functionality as well as enhanced cell viability. Thus, 3D cell printing can overcome the current concerns of stem cell therapy by delivering the 3D construct to the damaged site. Despite the advantages of 3D cell printing, the in vivo and in vitro tracking and monitoring of the performance of 3D cell printed tissue in a noninvasive and real-time manner have not been thoroughly studied. In this review, we explore the recent progress in 3D cell technology and its applications. Finally, we investigate their potential limitations and suggest future perspectives on 3D cell printing and stem cell theranostics.116Nsciescopu

Plant Location Selection for Food Production by Considering the Regional and Seasonal Supply Vulnerability of Raw Materials

A production capacity analysis considering market demand and raw materials is very important to design a new plant. However, in the food processing industry, the supply uncertainty of raw materials is very high, depending on the production site and the harvest season, and further, it is not straightforward to analyze too complex food production systems by using an analytical optimization model. For these reasons, this study presents a simulation-based decision support model to select the right location for a new food processing plant. We first define three supply vulnerability factors from the standpoint of regional as well as seasonal instability and present an assessment method for supply vulnerability based on fuzzy quantification. The evaluated vulnerability scores are then converted into raw material supply variations for food production simulation to predict the quarterly production volume of a new food processing plant. The proposed selection procedure is illustrated using a case study of semiprocessed kimchi production. The best plant location is proposed where we can reduce and mitigate risks when supplying raw material, thereby producing a target production volume steadily

Comparative analysis of multiple classification models to improve PM10 prediction performance

With the increasing requirement of high accuracy for particulate matter prediction, various attempts have been made to improve prediction accuracy by applying machine learning algorithms. However, the characteristics of particulate matter and the problem of the occurrence rate by concentration make it difficult to train prediction models, resulting in poor prediction. In order to solve this problem, in this paper, we proposed multiple classification models for predicting particulate matter concentrations required for prediction by dividing them into AQI-based classes. We designed multiple classification models using logistic regression, decision tree, SVM and ensemble among the various machine learning algorithms. The comparison results of the performance of the four classification models through error matrices confirmed the f-score of 0.82 or higher for all the models other than the logistic regression model

Characterization for Binding Complex Formation with Site-Directly Immobilized Antibodies Enhancing Detection Capability of Cardiac Troponin I

The enhanced analytical performances of immunoassays that employed site-directly immobilized antibodies as the capture binders have been functionally characterized in terms of antigen-antibody complex formation on solid surfaces. Three antibody species specific to cardiac troponin I, immunoglobulin G (IgG), Fab, and F(ab′)2 were site-directly biotinylated within the hinge region and then immobilized via a streptavidin-biotin linkage. The new binders were more efficient capture antibodies in the immunoassays compared to randomly bound IgG, particularly, in the low antibody density range. The observed improvements could have resulted from controlled molecular orientation and also from flexibility, offering conditions suitable for binding complex formations