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As NGS (next-generation sequencing) technology develops, metagenomics-based microbial ecology, that is, microbiome research, has recently led to the science of fermented food. Based on the above technology, a study was conducted to understand the characteristics of vinegar made from bokbunja, a local crop in Gochang-gun, Korea. Physicochemical characteristics of vinegar, organic acid analysis, microbial community analysis, and electronic tongue analysis were explored while fermenting the vinegar for 70 days under eight fermentation conditions according to the concentration of bokbunja liquid (100% or 50%), type of fermenter (porcelain jar or stainless container), and fermentation environment (natural outdoor conditions or temperature/oxygen controlled). As a result, distinct microbial community patterns were found in the stage of acetic acid fermentation and, accordingly, this fermentation of Gochang vinegar is classified into three categories. Vinegar prepared by the traditional method of outdoor fermentation using jars showed characteristics of “Acetobacter (42.1%)/Lactobacillus (56.9%) fusion fermentation”. Under conditions where oxygen and temperature were controlled indoors using jars, characteristics of “Komagataeibacter (90.2%) fermentation” were found. “Lactobacillus (92.2%) fermentation” characteristics were discovered under natural outdoor conditions using stainless steel containers. These fermentation pattern differences were related to taxonomic phylogenetic diversity, which was also considered involved in determining organic acid production and taste. These results will be helpful as a scientific basis for understanding the fermentation characteristics of Gochang vinegar and developing high-value-added traditional vinegar products.

There has been a recent increase in research interest in the ways that visual representation is used to facilitate students’ understanding in science classrooms. Yet while many studies have explored individual students’ drawing, few studies have looked into drawing as a collective tool to engage students in thinking and talking together in science classrooms. This study employed a case study approach to understand some of the possibilities for visual representation construction as a collective reasoning tool. By examining two cases of visual representation construction during classroom talk in two elementary science classrooms, this study demonstrates how teachers use visual representation as an instructional strategy, and how visualization engages students’ reasoning, meaning making, and social interactions. We selected two cases that demonstrate the emergence of the teacher’s and students’ drawing activities and analyzed each with a focus on the interactions that occur during the construction of visual representation and how this interaction promotes scientific reasoning and meaning making. For the case analysis, three researchers reviewed the video cases separately several times, and then collectively developed in-depth discussion to bring forth possible themes. The findings include (a) that there were common grounds of visual representation established for collective reasoning, and (b) that visual representations expanded knowledge and reasoning from the individual to social level, thus playing a critical role in students’ reasoning and knowledge building during classroom talk. Pedagogical questions and reflection are discussed for further research on visualization as a cognitive and social tool in classrooms.

This paper presents an energy-optimized electronic performance tracking system (EPTS) device for analyzing the athletic movements of football players. We first develop a tiny battery-operated wearable device that can be attached to the backside of field players. In order to analyze the strategic performance, the proposed wearable EPTS device utilizes the GNSS-based positioning solution, the IMU-based movement sensing system, and the real-time data acquisition protocol. As the life-time of the EPTS device is in general limited due to the energy-hungry GNSS sensing operations, for the energy-efficient solution extending the operating time, in this work, we newly develop the advanced optimization methods that can reduce the number of GNSS accesses without degrading the data quality. The proposed method basically identifies football activities during the match time, and the sampling rate of the GNSS module is dynamically relaxed when the player performs static movements. A novel deep convolution neural network (DCNN) is newly developed to provide the accurate classification of human activities, and various compression techniques are applied to reduce the model size of the DCNN algorithm, allowing the on-device DCNN processing even at the memory-limited EPTS device. Experimental results show that the proposed DCNN-assisted sensing control can reduce the active power by 28%, consequently extending the life-time of the EPTS device more than 1.3 times.

The objective of this study was to evaluate the feasibility of reutilizing phosphorus (P) recovered as struvite from swine wastewater as an alternative to commercial P sources in broiler feed. The recovered struvite was pre-treated as microwave irradiated struvite (MS) and incinerated struvite (IS) to reduce the NH4-N concentration in recovered struvite before application. A preliminary study on the growth performance and blood metabolites of broiler chickens was then performed to assess the effect of MS and IS by comparing with commercial monobasic dicalcium phosphate (MDCP, control). A total of 204 male Ross 308 broiler chickens (mean body weight (BW) of 80 ± 5 g) were randomly allotted to each of 12 pens. The growth performance and blood metabolites analysis of broiler chickens showed no significant difference among the test materials (p > 0.05). However, the apparent total tract digestibility of crude fat was significantly higher in MS and IS treated groups compared to the control (p < 0.05). The digestibility of crude ash in control was significantly lower than that in MS (p < 0.05). The results suggested that P recovered from swine wastewater as struvite can be reutilized as an alternative P source in broiler feed without adverse effects on growth performance and blood metabolites through proper pre-treatment. To our knowledge, this is the first study to evaluate the potential of using struvite in animal feed. This study provides primary evidence for the safety and efficacy of using pre-treated struvite as an alternative source of P in animal feed and will encourage further studies with more rigorous design.

Glaucoma is a leading eye disease, causing vision loss by gradually affecting peripheral vision if left untreated. Current diagnosis of glaucoma is performed by ophthalmologists, human experts who typically need to analyze different types of medical images generated by different types of medical equipment: fundus, Retinal Nerve Fiber Layer (RNFL), Optical Coherence Tomography (OCT) disc, OCT macula, perimetry, and/or perimetry deviation. Capturing and analyzing these medical images is labor intensive and time consuming. In this paper, we present a novel approach for glaucoma diagnosis and localization, only relying on fundus images that are analyzed by making use of state-of-the-art deep learning techniques. Specifically, our approach towards glaucoma diagnosis and localization leverages Convolutional Neural Networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), respectively. We built and evaluated different predictive models using a large set of fundus images, collected and labeled by ophthalmologists at Samsung Medical Center (SMC). Our experimental results demonstrate that our most effective predictive model is able to achieve a high diagnosis accuracy of 96%, as well as a high sensitivity of 96% and a high specificity of 100% for Dataset-Optic Disc (OD), a set of center-cropped fundus images highlighting the optic disc. Furthermore, we present Medinoid, a publicly-available prototype web application for computer-aided diagnosis and localization of glaucoma, integrating our most effective predictive model in its back-end.