Superparamagnetic polyvinylpyrrolidone/chitosan/Fe3O4 electrospun nanofibers as effective U(VI) adsorbents

Magnetoactive electrospun fibrous membranes consisting of polyvinylpyrrolidone (PVP), chitosan (CS) and pre-fabricated, double-layer oleic acid-coated magnetite nanoparticles (OA.OA.Fe₃O₄) were fabricated and evaluated as new adsorbent materials for the removal and recovery of uranium (U(VI)) from aqueous solutions. The adsorption has been investigated by batch-type experiments and the solid material has been characterized by X-ray diffraction spectroscopy (XRD), Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy/energy dispersive X-ray analysis (TEM/EDX) and vibration sample magnetometry (VSM) measurements prior and after uranium adsorption. The experimental adsorption data were found to be well fitted with the Langmuir isotherm and the pseudo-second order kinetic model. The results indicate that PVP/CS/OA.OA.Fe₃O₄ fibrous adsorbents exhibit good adsorption properties towards U(VI) in aqueous solutions, achieving a q_max value of 0.77 mol kg⁻¹ (183.3 mg g⁻¹) at pH 6.0. The experiments regarding the regeneration and reuse of the magnetoactive adsorbents were carried out using Na₂CO₃, at pH ~11. After four cycles, the percentage relative adsorption remained stable (~100%) whereas the desorption percentage decreased from 31.9% to 21.0%. Generally, the presented results demonstrate that the incorporation of the Fe₃O₄ NPs has a positive effect on the adsorption efficiency of U(VI) from aquatic environments.     

Anti-Idiotype scFv Localizes an Autoepitope in the Globular Domain of C1q

We addressed the issue of C1q autoantigenicity by studying the structural features of the autoepitopes recognized by the polyclonal anti-C1q antibodies present in Lupus Nephritis (LN) sera. We used six fractions of anti-C1q as antigens and selected anti-idiotypic scFv antibodies from the phage library “Griffin.1”. The monoclonal scFv A1 was the most potent inhibitor of the recognition of C1q and its fragments ghA, ghB and ghC, comprising the globular domain gC1q, by the lupus autoantibodies. It was sequenced and in silico folded by molecular dynamics into a 3D structure. The generated 3D model of A1 elucidated CDR similarity to the apical region of gC1q, thus mapping indirectly for the first time a globular autoepitope of C1q. The V_H CDR2 of A1 mimicked the ghA sequence GSEAD suggested as a cross-epitope between anti-DNA and anti-C1q antibodies. Other potential inhibitors of the recognition of C1q by the LN autoantibodies among the selected recombinant antibodies were the monoclonal scFv F6, F9 and A12.     

Analyzing developmental processes on an individual level using nonstationary time series modeling.

Individuals change over time, often in complex ways. Generally, studies of change over time have combined individuals into groups for analysis, which is inappropriate in most, if not all, studies of development. The authors explain how to identify appropriate levels of analysis (individual vs. group) and demonstrate how to estimate changes in developmental processes over time using a multivariate nonstationary time series model. They apply this model to describe the changing relationships between a biological son and father and a stepson and stepfather at the individual level. The authors also explain how to use an extended Kalman filter with iteration and smoothing estimator to capture how dynamics change over time. Finally, they suggest further applications of the multivariate nonstationary time series model and detail the next steps in the development of statistical models used to analyze individual-level data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Empirical Characterization of Session–Based Workload and Reliability for Web Servers

The growing availability of Internet access has led to significant increase in the use of World Wide Web. If we are to design dependable Web–based systems that deal effectively with the increasing number of clients and highly variable workload, it is important to be able to describe the Web workload and errors accurately. In this paper we focus on the detailed empirical analysis of the session–based workload and reliability based on the data extracted from actual Web logs of eleven Web servers. First, we introduce and rigourously analyze several intra–session and inter–session metrics that collectively describe Web workload in terms of user sessions. Then, we analyze Web error characteristics and estimate the request–based and session–based reliability of Web servers. Finally, we identify the invariants of the Web workload and reliability that apply through all data sets considered. The results presented in this paper show that session–based workload and reliability are better indicators of the users perception of the Web quality than the request–based metrics.     

Quasi‐Bayesian Estimation of Time‐Varying Volatility in DSGE Models

We propose a novel quasi‐Bayesian Metropolis‐within‐Gibbs algorithm that can be used to estimate drifts in the shock volatilities of a linearized dynamic stochastic general equilibrium (DSGE) model. The resulting volatility estimates differ from the existing approaches in two ways. First, the time variation enters non‐parametrically, so that our approach ensures consistent estimation in a wide class of processes, thereby eliminating the need to specify the volatility law of motion and alleviating the risk of invalid inference due to mis‐specification. Second, the conditional quasi‐posterior of the drifting volatilities is available in closed form, which makes inference straightforward and simplifies existing algorithms. We apply our estimation procedure to a standard DSGE model and find that the estimated volatility paths are smoother compared to alternative stochastic volatility estimates. Moreover, we demonstrate that our procedure can deliver statistically significant improvements to the density forecasts of the DSGE model compared to alternative methods.     

Interpolymer complexes of poly(acrylamide) and poly(N-isopropylacrylamide) with poly(acrylic acid): a comparative study

The interpolymer complexation, through successive hydrogen bonding, between poly(acrylamide) (PAAm) and poly(N-isopropylacrylamide) (PNiPAAm) with poly(acrylic acid) (PAA) in aqueous solution has been viscometrically and potentiometrically investigated. The stoichiometry of the complexes formed was determined. By comparing the strength of the two complexes the very important contribution of the hydrophobic interaction in their formation has been indicated.     

Comparison of the Flow of Permanent and Condensable Gases through an Asymmetric Porous Membrane

Porous inorganic membranes are usually composed of several layers, which are asymmetric with respect to the flow direction. For permanent gases, investigations about the influence of the flow direction on the mass flux through an asymmetric ceramic membrane were previously performed and can be found in literature. Mass flow differences between the two flow directions were calculated. Here the flow of condensable gases, i.e., of vapors, through the same membrane is analyzed and it is shown that the mass flow might be up to 40 % larger in one direction than in the other direction.     

Challenges and opportunities of multimodal data in human learning: The computer science students' perspective

Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA systems are designed and deployed without learners' involvement. We argue that in order to create MLA interfaces that directly support learning, we need to gain an expanded understanding of how multimodal data can support learners' authentic needs. We present a qualitative study in which 40 computer science students were tracked in an authentic learning activity using wearable and static sensors. Our findings outline learners' curated representations about multimodal data and the non-technical challenges in using these data in their learning practice. The paper discusses 10 dimensions that can serve as guidelines for researchers and designers to create effective and ethically aware student-facing MLA innovations.