Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management

Maintaining traceability links among software artifacts is particularly important for many software engineering tasks. Even though automatic traceability link recovery tools are successful in identifying the semantic connections among software artifacts produced during software development, no existing traceability link management approach can effectively and automatically deal with software evolution. We propose a technique to automatically manage traceability link evolution and update the links in evolving software. Our novel technique, called incremental Latent Semantic Indexing (iLSI), allows for the fast and low-cost LSI computation for the update of traceability links by analyzing the changes to software artifacts and by reusing the result from the previous LSI computation before the changes. We present our iLSI technique, and describe a complete automatic traceability link evolution management tool, TLEM, that is capable of interactively and quickly updating traceability links in the presence of evolving software artifacts. We report on our empirical evaluation with various experimental studies to assess the performance and usefulness of our approach.This is a manuscript of a proceeding published as H. -Y. Jiang, T. N. Nguyen, I. -X. Chen, H. Jaygarl and C. K. Chang, "Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management," 2008 23rd IEEE/ACM International Conference on Automated Software Engineering, 2008, pp. 59-68, doi: 10.1109/ASE.2008.16. Posted with permission. © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management

Maintaining traceability links among software artifacts is particularly important for many software engineering tasks. Even though automatic traceability link recovery tools are successful in identifying the semantic connections among software artifacts produced during software development, no existing traceability link management approach can effectively and automatically deal with software evolution. We propose a technique to automatically manage traceability link evolution and update the links in evolving software. Our novel technique, called incremental Latent Semantic Indexing (iLSI), allows for the fast and low-cost LSI computation for the update of traceability links by analyzing the changes to software artifacts and by reusing the result from the previous LSI computation before the changes. We present our iLSI technique, and describe a complete automatic traceability link evolution management tool, TLEM, that is capable of interactively and quickly updating traceability links in the presence of evolving software artifacts. We report on our empirical evaluation with various experimental studies to assess the performance and usefulness of our approach.This is a manuscript of a proceeding published as H. -Y. Jiang, T. N. Nguyen, I. -X. Chen, H. Jaygarl and C. K. Chang, "Incremental Latent Semantic Indexing for Automatic Traceability Link Evolution Management," 2008 23rd IEEE/ACM International Conference on Automated Software Engineering, 2008, pp. 59-68, doi: 10.1109/ASE.2008.16. Posted with permission. © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Design and Vehicle Implementation of Autonomous Lane Change Algorithm based on Probabilistic Prediction

This paper describes design, vehicle implementation and validation of a motion planning and control algorithm of autonomous driving vehicle for lane change. Autonomous lane change is necessary for high-level autonomous driving. A vehicle equipped with diverse devices like sensors and computer is introduced for implementation and validation of autonomous driving. The autonomous driving system consists of three parts: perception, motion planning and control. In a perception part, surrounding vehicles' states and lane information are estimated. In motion planning part, using these information and chassis information, probabilistic prediction is conducted for ego vehicle and surrounding vehicle separately. And then, driving mode are decided among three modes: lane keeping, lane change and traffic pressure. Driving mode is determined based on a safety distance by predicting states of surrounding vehicles and ego vehicle. If the ego vehicle cannot perform lane change when the lane change is required, the most proper space is selected considering the probabilistic prediction information and the safety distance. Target states are defined based on driving mode and information of surrounding vehicles behaviors. In control part, the distributed control architecture for real time implementation to the vehicle. A linear quadratic regulator (LQR) optimal control and a model predictive control (MPC) are used to obtain the longitudinal acceleration and the desired steering angle. The proposed automated driving algorithm has been evaluated via vehicle test, which has used one autonomous vehicle and two normal vehicles.N

Comparative Assessment of the Anti-<i>Helicobacter pylori</i> Activity and Gastroprotective Effects of Three Herbal Formulas for Functional Dyspepsia In Vitro

Helicobacter pylori has been implicated in various gastrointestinal disorders, including functional dyspepsia. This study aimed to compare the anti-H. pylori activity and gastroprotective effects of three typical herbal formulas used for gastrointestinal disorders in Korea: Shihosogan-tang (ST), Yijung-tang (YT), and Pyeongwi-san (PS). Firstly, we assessed the total phenolic and flavonoid contents, as well as the antioxidative capacity. Additionally, we evaluated the antibacterial effect on H. pylori using an ammonia assay, minimum inhibitory concentration (MIC) test, and the disk agar diffusion method. Furthermore, we examined alterations in the gene expression of tight junction proteins, pro-inflammatory cytokines, and cellular vacuolation using an AGS cell model infected with H. pylori. While ST exhibited a higher total phenolic content, superior free radical scavenging, and inhibition of H. pylori compared to YT and PS, YT more evidently inhibited gastric cellular morphological changes such as vacuolation. All formulations significantly ameliorated changes in inflammatory and gastric inflammation-related genes and cellular morphological alterations induced by H. pylori infection. Overall, the present in vitro study suggests that all three herbal formulas possess potential for ameliorating gastrointestinal disorders, with ST relatively excelling in inhibiting H. pylori infection and inflammation, while YT potentially shows greater efficacy in directly protecting the gastric mucosa

Ginseng extracts improve circadian clock gene expression and reduce inflammation directly and indirectly through gut microbiota and PI3K signaling pathway

Abstract Despite the potential benefits of herbal medicines for therapeutic application in preventing and treating various metabolic disorders, the mechanisms of action were understood incompletely. Ginseng (Panax ginseng), a commonly employed plant as a dietary supplement, has been reported to play its hot property in increasing body temperature and improving gut health. However, a comprehensive understanding of the mechanisms by which ginseng regulates body temperature and gut health is still incomplete. This paper illustrates that intermittent supplementation with ginseng extracts improved body temperature rhythm and suppressed inflammatory responses in peripheral metabolic organs of propylthiouracil (PTU)-induced hypothermic rats. These effects were associated with changes in gut hormone secretion and the microbiota profile. The in-vitro studies in ICE-6 cells indicate that ginseng extracts can not only act directly on the cell to regulate the genes related to circadian clock and inflammation, but also may function through the gut microbiota and their byproducts such as lipopolysaccharide. Furthermore, administration of PI3K inhibitor blocked ginseng or microbiota-induced gene expression related with circadian clock and inflammation in vitro. These findings demonstrate that the hot property of ginseng may be mediated by improving circadian clock and suppressing inflammation directly or indirectly through the gut microbiota and PI3K-AKT signaling pathways

Understanding the correlation between energy‐state mismatching and open‐circuit voltage loss in bulk heterojunction solar cells

Abstract Photoinduced intermolecular charge transfer (PICT) determines the voltage loss in bulk heterojunction (BHJ) organic photovoltaics (OPVs), and this voltage loss can be minimized by inducing efficient PICT, which requires energy‐state matching between the donor and acceptor at the BHJ interfaces. Thus, both geometrically and energetically accessible delocalized state matching at the hot energy level is crucial for achieving efficient PICT. In this study, an effective method for quantifying the hot state matching of OPVs was developed. The degree of energy‐state matching between the electron donor and acceptor at BHJ interfaces was quantified using a mismatching factor (MF) calculated from the modified optical density of the BHJ. Furthermore, the correlation between the open‐circuit voltage (Voc) of the OPV device and energy‐state matching at the BHJ interface was investigated using the calculated MF. The OPVs with small absolute MF values exhibited high Voc values. This result clearly indicates that the energy‐state matching between the donor and acceptor is crucial for achieving a high Voc in OPVs. Because the MF indicates the degree of energy‐state matching, which is a critical factor for suppressing energy loss, it can be used to estimate the Voc loss in OPVs