Rapid and Sensitive Detection of Escherichia coli O157:H7 Using a QCM Sensor based on Aptamers Selected by Whole-Bacterium SELEX and a Multivalent Aptamer System

Escherichia coli O157:H7 is one of the top five pathogens contributing to foodborne diseases, causing an estimated 2,138 cases of hospitalization in the US each year. The extremely low infectious dose demands for more rapid and sensitive methods to detect E. coli O157:H7. The objective of this study is to select aptamers specifically binding to E. coli O157:H7 using whole-bacterium SELEX (Systematic Evolution of Ligands by Exponential Enrichment) and to create a multivalent aptamer system by rolling circle amplification (RCA) with the selected aptamer sequence for sensitive detection of E. coli O157:H7 using a quartz crystal microbalance (QCM) sensor. Briefly, A total of 19 rounds of selection against live E. coli O157:H7 and 6 rounds of counter selection were performed for SELEX. One sequence S1 that appeared 16 (out of 20) times was characterized and a dissociation constant (Kd) of 10.30 nM was obtained. Using phi29 DNA polymerase, RCA reaction was performed, which produced a long ssDNA strand composed of thousands of repetitive aptamer sequences, termed as a multivalent aptamer system, on the electrode. The QCM sensor based on a multivalent aptamer system was able to quantitatively detect E. coli O157:H7. The limit of detection (LOD) of the QCM sensor was determined to be 34 CFU/ml, respectively, with the whole detection procedure in less than 40 min. The QCM sensor also showed high specificity for E. coli O157:H7 when it was cross-tested with five non-target bacteria. The QCM aptasensor in this study provided a common platform for detection of different foodborne pathogens

State and market integration in China: A spatial econometrics approach to 'local protectionism'

In the past two decades, controversial evidence has been produced supporting the case for local protectionism in China. This paper overviews the most important contributions and presents a new approach which applies spatial econometrics on prefectural-level data. The main advantage of this method is to rely on a theoretically less biased and internal benchmark for assessing the impact of provincial borders on spatial interdependences, as we compare within province and across province growth spillovers for neighbouring prefectures. We show that provincial borders exert a strong impact on spillovers. Further, we also analyze spillovers of local public expenditures, which could be interpreted as proxies for government interventions. Again, provincial borders matter. Yet, we are cautious in interpreting this as evidence for local protectionism, and propose the notion of 'cellularity' as an alternative explanation. Cellularity results from a confluence of different factors, such as administrative structure, institutional changes and regional culture. --Domestic market integration in China: local protectionism,spatial econometrics,growth spillovers,expenditure spillovers,cellularity

Activated Dissociation of H2 on Cu(001): The Role of Quantum Tunneling

The activation and dissociation of H2 molecules on Cu(001) surface is studied theoretically. The activation barrier for the dissociation of H2 on Cu(001) is determined by first-principles calculations to be ~ 0.59 eV in height. Electron transfer from the substrate Cu to H2 plays a key role in the activation, breaking of the H-H bond and the formation of the Cu-H bonds. At around the critical height of bond breaking, two stationary states are identified, which correspond respectively to the molecular and dissociative state. Using the transfer matrix method, we are able to study the role of quantum tunneling in the dissociation process along the minimum energy pathway (MEP), which is found to be significant at room temperature and below. At given temperatures, the tunneling contributions from the translational and vibrational motions of H2 are quantified for the dissociation process. Within a wide range of temperatures, the effects of quantum tunneling on the effective barriers of dissociation and the rate constants are revealed. The deduced energetic parameters associated with thermal equilibrium and non-equilibrium (molecular beam) conditions are comparable with experimental data. In the low-temperature region, crossover from classical to quantum regime is identified.Comment: 33 pages, 11 figure

A solution processed flexible nanocomposite electrode with efficient light extraction for organic light emitting diodes.

Highly efficient organic light emitting diodes (OLEDs) based on multiple layers of vapor evaporated small molecules, indium tin oxide transparent electrode, and glass substrate have been extensively investigated and are being commercialized. The light extraction from the exciton radiative decay is limited to less than 30% due to plasmonic quenching on the metallic cathode and the waveguide in the multi-layer sandwich structure. Here we report a flexible nanocomposite electrode comprising single-walled carbon nanotubes and silver nanowires stacked and embedded in the surface of a polymer substrate. Nanoparticles of barium strontium titanate are dispersed within the substrate to enhance light extraction efficiency. Green polymer OLED (PLEDs) fabricated on the nanocomposite electrode exhibit a maximum current efficiency of 118 cd/A at 10,000 cd/m(2) with the calculated external quantum efficiency being 38.9%. The efficiencies of white PLEDs are 46.7 cd/A and 30.5%, respectively. The devices can be bent to 3 mm radius repeatedly without significant loss of electroluminescent performance. The nanocomposite electrode could pave the way to high-efficiency flexible OLEDs with simplified device structure and low fabrication cost

SCALE: Online Self-Supervised Lifelong Learning without Prior Knowledge

Unsupervised lifelong learning refers to the ability to learn over time while memorizing previous patterns without supervision. Previous works assumed strong prior knowledge about the incoming data (e.g., knowing the class boundaries) which can be impossible to obtain in complex and unpredictable environments. In this paper, motivated by real-world scenarios, we formally define the online unsupervised lifelong learning problem with class-incremental streaming data, which is non-iid and single-pass. The problem is more challenging than existing lifelong learning problems due to the absence of labels and prior knowledge. To address the issue, we propose Self-Supervised ContrAstive Lifelong LEarning (SCALE) which extracts and memorizes knowledge on-the-fly. SCALE is designed around three major components: a pseudo-supervised contrastive loss, a self-supervised forgetting loss, and an online memory update for uniform subset selection. All three components are designed to work collaboratively to maximize learning performance. Our loss functions leverage pairwise similarity thus remove the dependency on supervision or prior knowledge. We perform comprehensive experiments of SCALE under iid and four non-iid data streams. SCALE outperforms the best state-of-the-art algorithm on all settings with improvements of up to 3.83%, 2.77% and 5.86% kNN accuracy on CIFAR-10, CIFAR-100 and SubImageNet datasets.Comment: Submitted for revie