In-Memory Caching for Enhancing Subgraph Accessibility

Graphs have been utilized in various fields because of the development of social media and mobile devices. Various studies have also been conducted on caching techniques to reduce input and output costs when processing a large amount of graph data. In this paper, we propose a two-level caching scheme that considers the past usage pattern of subgraphs and graph connectivity, which are features of graph topology. The proposed caching is divided into a used cache and a prefetched cache to manage previously used subgraphs and subgraphs that will be used in the future. When the memory is full, a strategy that replaces a subgraph inside the memory with a new subgraph is needed. Subgraphs in the used cache are managed by a time-to-live (TTL) value, and subgraphs with a low TTL value are targeted for replacement. Subgraphs in the prefetched cache are managed by the queue structure. Thus, first-in subgraphs are targeted for replacement as a priority. When a cache hit occurs in the prefetched cache, the subgraphs are migrated and managed in the used cache. As a result of the performance evaluation, the proposed scheme takes into account subgraph usage patterns and graph connectivity, thus improving cache hit rates and data access speeds compared to conventional techniques. The proposed scheme can quickly process and analyze large graph queries in a computing environment with small memory. The proposed scheme can be used to speed up in-memory-based processing in applications where relationships between objects are complex, such as the Internet of Things and social networks

Magnetically-Focusing Biochip Structures for High-speed Active Biosensing with Improved Selectivity

International audienc

“Bio-switch Chip” Based on Nanostructured Conducting Polymer and Entrapped Enzyme

We report a switchable biochip strategy where enzymes were entrapped in conducting polymer layers and the enzymatic reaction of the entrapped enzymes was controlled in real-time via electrical stimuli on the polymer layers. This device is named here as a “bio-switch chip” (BSC). We fabricated BSC structures using polypyrrole (Ppy) with entrapped glucose oxidase (GOx) and demonstrated the switching of glucose oxidation reaction in real-time. We found that the introduction of a negative bias voltage on the BSC structure resulted in the enhanced glucose oxidation reaction by more than 20 times than that without a bias voltage. Moreover, because the BSC structures could be fabricated on specific regions, we could control the enzymatic reaction on specific regions. In view of the fact that enzymes enable very useful and versatile biochemical reactions, the ability to control the enzymatic reactions via conventional electrical signals could open up various applications in the area of biochips and other biochemical industries

Quantitative electrophysiological monitoring of anti–histamine drug effects on live cells via reusable sensor platforms

International audienc

High-Speed Lateral Flow Strategy for a Fast Biosensing with an Improved Selectivity and Binding Affinity

We report a high-speed lateral flow strategy for a fast biosensing with an improved selectivity and binding affinity even under harsh conditions. In this strategy, biosensors were fixed at a location away from the center of a round shape disk, and the disk was rotated to create the lateral flow of a target solution on the biosensors during the sensing measurements. Experimental results using the strategy showed high reaction speeds, high binding affinity, and low nonspecific adsorptions of target molecules to biosensors. Furthermore, binding affinity between target molecules and sensing molecules was enhanced even in harsh conditions such as low pH and low ionic strength conditions. These results show that the strategy can improve the performance of conventional biosensors by generating high-speed lateral flows on a biosensor surface. Therefore, our strategy can be utilized as a simple but powerful tool for versatile bio and medical applications

Fourier Transform Surface Plasmon Resonance of Nanodisks Embedded in Magnetic Nanorods

In this study, we demonstrate the synthesis and application of magnetic plasmonic gyro-nanodisks (GNDs) for Fourier transform surface plasmon resonance based biodetection. Plasmonically active and magnetically responsive gyro-nanodisks were synthesized using electrochemical methods with anodized aluminum templates. Due to the unique properties of GNDs (magnetic responsiveness and surface plasmon bands), periodic extinction signals were generated under an external rotating magnetic field, which is, in turn, converted into frequency domains using Fourier transformation. After the binding of a target on GNDs, an increase in the shear force causes a shift in the frequency domain, which allows us to investigate biodetection for HA1 (the influenza virus). Most importantly, by modulating the number and the location of plasmonic nanodisks (a method for controlling the hydrodynamic forces by rationally designing the nanomaterial architecture), we achieved enhanced biodetection sensitivity. We expect that our results will contribute to improved sensing module performance, as well as a better understanding of dynamic nanoparticle systems, by harnessing the perturbed periodic fluctuation of surface plasmon bands under the modulated magnetic field

Estimating Benzene Exposure Level over Time and by Industry Type through a Review of Literature on Korea

The major purpose of this study is to construct a retrospective exposure assessment for benzene through a review of literature on Korea. Airborne benzene measurements reported in 34 articles were reviewed. A total of 15,729 individual measurements were compiled. Weighted arithmetic means [AM(w)] and their variance calculated across studies were summarized according to 5-year period intervals (prior to the 1970s through the 2010s) and industry type. Industries were classified according to Korea Standard Industrial Classification (KSIC) using information provided in the literature. We estimated quantitative retrospective exposure to benzene for each cell in the matrix through a combination of time and KSIC. Analysis of the AM(w) indicated reductions in exposure levels over time, regardless of industry, with mean levels prior to the 1980–1984 period of 50.4 ppm (n = 2,289), which dropped to 2.8 ppm (n = 305) in the 1990–1994 period, and to 0.1 ppm (n = 294) in the 1995–1999 period. There has been no improvement since the 2000s, when the AM(w) of 4.3 ppm (n = 6,211) for the 2005–2009 period and 4.5 ppm (n = 3,358) for the 2010–2013 period were estimated. A comparison by industry found no consistent patterns in the measurement results. Our estimated benzene measurements can be used to determine not only the possibility of retrospective exposure to benzene, but also to estimate the level of quantitative or semiquantitative retrospective exposure to benzene