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User-generated content sharing networks (UGCSNets), in which members are content contributors as well as users, have had a significant impact on the sharing economy and on society via the sharing and reuse of contents. In a UGCSNet, managing for growth requires a quantitative grasp of how individual members' participation and sharing affect and are affected by the membership and content volume; these interactions form a dynamic loop. In this paper, a quantitative modeling approach for the loop dynamics of UGCSNet growth is developed by exploiting limited empirical data. A teaching material sharing network serves as a baseline case study, and Wikipedia serves as a validation case for the modeling approach design. The novel modeling approach consists of 1) set of generalized bass diffusion model-embedded stochastic difference equations (GBDSDEs) of the loop dynamics and 2) a quasi-bootstrap-based nonlinear least square method to extract from the limited empirical data and periodically update the model parameters as the UGCSNet evolves. In GBDSDEs, two difference equations describe the number of members and content volume evolution. The stochastic drives consist of measures of individual participation and content uploading. The drive models are an innovative generalization of the bass diffusion model as probabilistic models of known qualitative descriptions regarding how the individual willingness to participate and share is affected by the total membership and content volume. Analyses of the coefficients of determination show good fits between model predictions and actual outcomes for both Smart Creative Teachers Net and Wikipedia growths. Applications of the modeling approach to what-if analyses demonstrate its value to predict and assess the effects of specific managerial strategies-such as the initial content volume and the number of founding altruistic members-on the growth of a UGCSNet.

In-line anomaly detection (AD) not only identifies the needs for semiconductor equipment maintenance but also indicates potential line yield problems. Prompt AD based on available equipment sensory data (ESD) facilitates proactive yield and operations management. However, ESD items are highly diversified and drastically scale up along with the increased use of sensors. Even veteran engineers lack knowledge about ESD items for automated AD. This paper presents a novel Spectral and Time Autoencoder Learning for Anomaly Detection (STALAD) framework. The design consists of four innovations: (1) identification of cycle series and spectral transformation (CSST) from ESD, (2) unsupervised learning from CSST of ESD by exploiting Stacked AutoEncoders, (3) hypothesis test for AD based on the difference between the learned normal data and the tested sample data, (4) dynamic procedure control enabling periodic and parallel learning and testing. Applications to ESD of an HDP-CVD tool demonstrate that STALAD learns normality without engineers’ prior knowledge, is tolerant to some abnormal data in training input, performs correct AD, and is efficient and adaptive for fab applications. Complementary to the current practice of using control wafer monitoring for AD, STALAD may facilitate early detection of equipment anomaly and assessment of impacts to process quality.

Abstract Background Polyethylene glycol (PEG) is widely used in industry and medicine. Anti-PEG antibodies have been developed for characterizing PEGylated drugs and other applications. However, the underlying mechanism for specific PEG binding has not been elucidated. Methods The Fab of two cognate anti-PEG antibodies 3.3 and 2B5 were each crystallized in complex with PEG, and their structures were determined by X-ray diffraction. The PEG-Fab interactions in these two crystals were analyzed and compared with those in a PEG-containing crystal of an unrelated anti-hemagglutinin 32D6-Fab. The PEG-binding stoichiometry was examined by using analytical ultracentrifuge (AUC). Results A common PEG-binding mode to 3.3 and 2B5 is seen with an S-shaped core PEG fragment bound to two dyad-related Fab molecules. A nearby satellite binding site may accommodate parts of a longer PEG molecule. The core PEG fragment mainly interacts with the heavy-chain residues D31, W33, L102, Y103 and Y104, making extensive contacts with the aromatic side chains. At the center of each half-circle of the S-shaped PEG, a water molecule makes alternating hydrogen bonds to the ether oxygen atoms, in a similar configuration to that of a crown ether-bound lysine. Each satellite fragment is clamped between two arginine residues, R52 from the heavy chain and R29 from the light chain, and also interacts with several aromatic side chains. In contrast, the non-specifically bound PEG fragments in the 32D6-Fab crystal are located in the elbow region or at lattice contacts. The AUC data suggest that 3.3-Fab exists as a monomer in PEG-free solution but forms a dimer in the presence of PEG-550-MME, which is about the size of the S-shaped core PEG fragment. Conclusions The differing amino acids in 3.3 and 2B5 are not involved in PEG binding but engaged in dimer formation. In particular, the light-chain residue K53 of 2B5-Fab makes significant contacts with the other Fab in a dimer, whereas the corresponding N53 of 3.3-Fab does not. This difference in the protein-protein interaction between two Fab molecules in a dimer may explain the temperature dependence of 2B5 in PEG binding, as well as its inhibition by crown ether.

Background: Development of an efficacious egg-free mock-up H5N1 vaccine is key to our preparedness against pandemic avian flu. Methods: This is a single-center, randomized, observer-blinded phase I clinical trial evaluating the safety and immunogenicity of an alum-adjuvanted Madin–Darby canine kidney (MDCK)-derived inactivated whole-virion H5N1 influenza vaccine in healthy adults. Hemagglutination inhibition (HAI) and neutralizing antibody titers were measured using horse and turkey red blood cells (RBCs). Results: Thirty-six adult subjects were randomized to receive two doses of 0.5 mL of the MDCK-derived H5N1 alum-adjuvanted vaccine containing 7.5, 15, or 30 μg of hemagglutinin (HA) 21 days apart. The candidate vaccine was well tolerated and safe across the three dosing groups. The most frequent adverse event was injection site pain (46.5%). Both HAI and neutralizing antibody titers increased after each vaccination in all three dosing groups. The best HAI responses, namely a seroconversion rate of 91.7% and a geometric mean ratio of 9.51 were achieved with the HA dose of 30 μg assayed using horse RBCs at day 42. HAI titers against H5N1 avian influenza virus was significantly higher when measured using horse RBCs compared with turkey RBCs. Conclusions: This Phase I trial showed the MDCK-derived H5N1 candidate vaccine is safe and immunogenic. The source of RBCs has a significant impact on the measurement of HAI titers (ClinicalTrials.gov number: NCT01675284.). Keywords: Influenza A, Avian influenza, H5N1, Vaccination, Immune response

In recent years, microgrids have developed as important parts of power systems and have provided affordable, reliable, and sustainable supplies of electricity. Each microgrid is managed as a single controllable entity with respect to the existing power system but demands for joint operation and sharing the benefits between a microgrid and its hosting utility. This paper is focused on the joint operation of a microgrid and its hosting utility, which cooperatively minimize daily generation costs through energy exchange, and presents a payment calculation scheme for power transactions based on a fair allocation of reduced generation costs. To fairly compensate for energy exchange between the micro- and utility grids, we adopt the cooperative game theoretic solution concept of Shapley value. We design a case study for a fictitious interconnection model between the Mueller microgrid in Austin, Texas and the utility grid in Taiwan. Our case study shows that when compared to standalone generations, both the micro- and utility grids are better off when they collaborate in power exchange regardless of their individual contributions to the power exchange coalition.