13,029 research outputs found
Classifying False Positive Static Checker Alarms in Continuous Integration Using Convolutional Neural Networks
No full textStatic code analysis in Continuous Integration (CI) environment can significantly improve the quality of a software system because it enables early detection of defects without any test executions or user interactions. However, being a conservative over-approximation of system behaviours, static analysis also produces a large number of false positive alarms, identification of which takes up valuable developer time. We present an automated classifier based on Convolutional Neural Networks (CNNs). We hypothesise that many false positive alarms can be classified by identifying specific lexical patterns in the parts of the code that raised the alarm: human engineers adopt a similar tactic. We train a CNN based classifier to learn and detect these lexical patterns, using a total of about 10K historical static analysis alarms generated by six static analysis checkers for over 27 million LOC, and their labels assigned by actual developers. The results of our empirical evaluation suggest that our classifier can be highly effective for identifying false positive alarms, with the average precision across all six checkers of 79.72%
Crowding and confinement effects on enzyme stability in mesoporous silicas
No full textTo understand the protein functions within a cell, where proteins exist in an extremely crowded and confined state, various modeling and experimental methods have been proposed. Here, we propose a new experimental approach to modulate the macromolecular crowding and/or confinement effects by using mesoporous silicas with two different pore structures. SBA-15 and MSU-F with linear and mesocellular pore structures, respectively, were used to adsorb a model enzyme, glucose oxidase (GOx), in various concentrations ranging from 3 to 430 mg ml(-1). The concentration of adsorbed GOx in the mesopores, representing the degree of crowding, showed a good correlation with thermal enzyme stability. Interestingly, the increase of thermal stability as a function of macromolecular crowding showed different correlations depending on the pore structure of mesoporous silicas. It represents that combination of crowding and confinement effects can promote different microenvironments for enzyme molecules, while mesoporous silicas can impose controlled crowding and confinement effects on enzymes due to their uniform and tunable pore structures. It is anticipated that this new and simple approach can provide a tool to elucidate crowding and confinement effects on the protein functions, including its stability in vivo, because the mesopore environments could mimic the real macromolecular cell system under crowding.
High performance immunoassay using immobilized enzyme in nanoporous carbon
No full textA highly stable immunoassay format was constructed using signal-generating enzyme immobilized in nanoporous carbon. A mesocellular carbon foam, called MSU-F-C, was loaded with horseradish peroxidase (HRP), followed by cross-linking of the enzyme using glutaraldehyde (GA) and modification of the surface with anti-human IgG through EDC/sulfo-NHS chemistry. The resulting MSU-F-C/HRP/anti-human IgG stably retained immobilized enzymes and antibodies, showing higher thermal stability. The MSU-F-C/HRP/anti-human IgG retained about 80% of initial enzyme activity at 40 degrees C after a 5 h incubation, while the HRP/anti-human IgG conjugate resulted in almost 90% loss of initial activity in the same condition. In bead-based immunoassays, the signal amplification using MSU-F-C/HRP/anti-human IgG enabled the sensitive colorimetric detection of a target analyte, human IgG, in a detection limit of similar to 33 pM, with negligible cross-reactivity against rabbit and chicken IgGs.N
Author Correction: Evaluation of skin cancer resection guide using hyper‑realistic in‑vitro phantom fabricated by 3D printing
No full textThe original version of this Article contained an error in the spelling of the author Taehun Kim which was incorrectly given as Teahun Kim. The original Article has been corrected
Polymer-coated spherical mesoporous silica for pH-controlled delivery of insulin
No full textWe report a pH-controlled insulin release system to provide an oral administration route. Mesoporous silica was chosen as a drug carrier, and pH-sensitive polymers were coated onto spherical mesocellular foam with pre-adsorbed insulin. We evaluated the insulin release in both acidic and neutral solutions to compare how this systembehaves under different pH conditions.
Boosting Current Density of Electrocatalytic CO2 Reduction using Metal-Enzyme Hybrid Cathodes
No full textAs a promising solution to global warming, electrocatalytic reduction of carbon dioxide (CO2RR) to liquid fuel has attracted great attention. A primary challenge in industrializing CO2RR technologies for producing liquid fuel is the mass transfer limitation of CO2, which significantly reduces the current density of CO2RR. This study proposes a new enzyme-enhanced electrocatalysis platform for boosting CO2RR current density. This platform integrates an enzyme of bovine carbonic anhydrase (bCA), stabilized on carbon nanotubes (bCA@CNT), into formate/formic acid selective metal catalysts such as tin (Sn) and bismuth (Bi) to prepare Metal-bCA (M-bCA) hybrid cathodes. The incorporation of bCA enhances both the CO2 hydration and the reversible dehydration of bicarbonate to CO2 in the cathode. This dynamic catalysis of bCA facilitates rapid local regeneration of dissolved CO2 from bicarbonate at the catalyst surface, thereby boosting the current density of CO2RR. Consequently, the formate current density of the Sn-bCA cathode was 3.3 times higher than that of the bare Sn cathode in a membrane-electrode assembly (MEA)-type cell. Furthermore, the Bi-bCA cathode achieved an excellent current density of 442 mA cm(-2), 1.5 times higher than the bare Bi cathode, for direct production of highly concentrated (3.4 mol L-1) formic acid in a 3-compartment cell.
Multiplexed immunoassay using the stabilized enzymes in mesoporous silica
No full textMultiplexed immunoassay system was developed using the enzyme-immobilized mesoporous silica in a form of nanoscale enzyme reactors (NERs). which improve the enzyme loading, activity, and stability. Glucose oxidase (GO) and trypsin (TR) were adsorbed into mesoporous silica and further crosslinked for the construction of NERs, and antibody-conjugated NERs were employed for the analysis of target antigens in a sandwich-type magnetic bead-based immunoassay. This approach, called as NER-LISA (NER-linked immunosorbent assay), generated signals out of enzyme reactions that correlated well with the concentration of target antigens. The detection limit of NER-LISA using NER-GO and anti-human IgG was 67 pM human IgG, and the sensitivity was 20 times higher than that of the conventional ELISA using anti-human IgG conjugated GO. Antibody-conjugated NER-GO and NER-TR were successfully employed for the simultaneous detection of two target antigens (human IgG and chicken IgG) in a solution by taking advantage of signals at different wavelengths (absorbances at 570 nm and 410 nm, respectively) from the assays of GO and TR activities, demonstrating the potential of NER-LISA in multiplexed immunoassay. The NER-LISA approach also enabled the successful use of a protease (trypsin), because the NER approach can effectively retain the protease molecules within the mesoporous silica and prevent the digestion of antibodies and enzymes during the whole process of NER-LISA. (C) 2009 Elsevier B.V. All rights reserved.N
DBLP-derived labeled data for author name disambiguation
No full textThis is a DBLP-derived labeled data originally created by Dr. C. Lee Giles at Penn State University and filtered for duplicate removal and error correction by Dr. Jinseok Kim at University of Michigan. For more details, see references below.1. Kim, Jinseok (2018). Evaluating author name disambiguation for digital libraries: a case of DBLP. Scientometrics. doi:10.1007/s11192-018-2824-5 2. Kim, Jinseok & Kim, Jenna (2018). The impact of imbalanced training data on machine learning for author name disambiguation. Scientometrics. doi: 10.1007/s11192-018-2865-9Each row refers to an author name instance with following feature information separated by tab.author name: full name string extracted from DBLPunique author id: labels assigned manually by Dr. C. Lee Giles's teampaper id: assigned by Dr. Jinseok Kimauthor list: names of authors in the byline of the paperyear: publication yearvenue: conference or journal namestitle: stopwords removed and stemmed by the Porter's stemmerIf you want to use this dataset, please consider to cite papers below.For the original dataset: Han, H., Giles, L., Zha, H., Li, C., & Tsioutsiouliklis, K. (2004). Two Supervised Learning Approaches for Name Disambiguation in Author Citations. JCDL 2004: Proceedings of the Fourth ACM/IEEE Joint Conference on Digital Libraries, 296-305. doi:10.1145/996350.996419For the filtered dataset: 1. Kim, Jinseok (2018). Evaluating author name disambiguation for digital libraries: a case of DBLP. Scientometrics. doi:10.1007/s11192-018-2824-5 or2. Kim, Jinseok & Kim, Jenna (2018). The impact of imbalanced training data on machine learning for author name disambiguation. Scientometrics. doi: 10.1007/s11192-018-2865-9</div
Crosslinked chitosan coating on magnetic mesoporous silica with pre-adsorbed carbonic anhydrase for carbon dioxide conversion
No full textCarbonic anhydrase (CA), an enzyme converting CO2 to bicarbonate, was adsorbed into magnetically-separable spherical mesocellular siliceous foam (Mag-S-MCF). Then, chitosan was adsorbed onto the surface of Mag-S-MCF with pre-adsorbed enzymes, and further crosslinked via the glutaraldehyde treatment. The resulting composite materials, the crosslinked chitosan coating on Mag-S-MCF with pre-adsorbed CA (ADS-CA/CS-GA), could effectively prevent leaching of enzymes, showing no decrease of enzyme activity under shaking (200 rpm) for 85 days. ADS-CA/CS-GA also showed no activity decrease under recycled uses via facile magnetic separation, and could be successfully used for the biocatalytic CO2 conversion to bicarbonate, which was further utilized to generate calcium carbonate in the second batch reactor. (C) 2015 Elsevier B.V. All rights reserved.
Effective Antifouling Using Quorum-Quenching Acylase Stabilized in Magnetically-Separable Mesoporous Silica
No full textHighly effective antifouling was achieved by immobilizing and stabilizing an acylase, disrupting bacterial cell-to-cell communication, in the form of cross-linked enzymes in magnetically separable mesoporous silica. This so-called "quorum-quenching" acylase (AC) was adsorbed into spherical mesoporous silica (S-MPS) with magnetic nanoparticles (Mag-S-MPS), and further cross-linked for the preparation of nanoscale enzyme reactors of AC in Mag-S-MPS (NER-AC/Mag-S-MPS). NER-AC effectively stabilized the AC activity under rigorous shaking at 200 rpm for 1 month, while free and adsorbed AC lost more than 90% of their initial activities in the same condition within 1 and 10 days, respectively. When applied to the membrane filtration for advanced water treatment, NER-AC efficiently alleviated the membrane surface, thereby enhancing the filtration performance separable NER-AC, as an effective and sustainable antifouling m for water reclamation. biofilm maturation of Pseudomonas aeruginosa PAO1 on the membrane surface, thereby enhancing the filtration performance by preventing membrane fouling. Highly stable and magnetically separable NER-AC, as an effective and sustainable antifouling material, has a great potential to be used in the membrane filtration for water reclamation.
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