PHOTOCATALYTIC OXIDATION OF ALDEHYDES/PCE USING POROUS ANATASE TITANIA AND VISIBLE-LIGHT-RESPONSIVE BROOKITE TITANIA

We have synthesized an annealed porous aerogel titania (LUAG2), which demonstrates a very high photocatalytic activity for aldehydes and perchloroethylene (PCE) photocatalytic oxidation (PCO) in gas phase under blacklight and fluorescent light irradiation. LUAG2 has a BET surface area of 237 m²/g and a porosity of 0.31 (volume fraction). X-ray diffraction (XRD) analysis shows LUAG2 is nearly pure anatase. It has improved the destruction of PCE and aldehydes as a group by 10-34% with black light compared to Degussa P-25. The optimum water vapor to butyraldehyde molar ratio is around 1/3. LUAG2 also shows better mineralization to CO₂ than Degussa P-25 TiO₂ does. Under irradiation of a 4 W fluorescent lamp LUAG2 gives a consistently higher conversion than that of Degussa P-25. The highly active photocatalyst indicates potential applications in indoor and outdoor environmental pollution control. A visible-light-responsive TiO₂, NTB 200, is also investigated for comparison purposes.     

A stochastic Kaczmarz algorithm for network tomography

We develop a stochastic approximation version of the classical Kaczmarz algorithm that is incremental in nature and takes as input noisy real time data. Our analysis shows that with probability one it mimics the behavior of the original scheme: starting from the same initial point, our algorithm and the corresponding deterministic Kaczmarz algorithm converge to precisely the same point. The motivation for this work comes from network tomography where network parameters are to be estimated based upon end-to-end measurements. Numerical examples via Matlab based simulations demonstrate the efficacy of the algorithm.     

Viscosity of Porous Glasses

Viscosity of porous glasses has been derived from the elastic stress analysis, using the viscous analogy. Viscosity as a function of porosity has been estimated for spherical as well as for arbitrary pore geometry. Since the pore geometry changes during sintering, a shape factor that varies with pore geometry has been considered to predict the viscosity–porosity relationship. Viscosity as a function of porosity was measured on cordierite-type glass by isothermal sinter-forging experiments and data showed good agreement with the analysis. Experimental data from literature on viscosity as a function of porosity on two other glasses also show good agreement with the analysis.     

A STUDY OF EXPERIMENTAL DESIGN OPTIMALITY FOR WIENER SYSTEMS

In the context of nonlinear dynamic system identification for Hammerstein systems, Rollins et al. (2003a) studied the information efficiency of the following two competing experimental design approaches: statistical design of experiments (SDOE) and pseudo-random sequences design (PRSD). The focus of this study is the Wiener system and evaluates SDOE against PRS under D-optimal efficiency. Three cases are evaluated and the results strongly support SDOE as the better approach.     

Extension-dominated improved dispersive mixing in single-screw extrusion. Part 2: Comparative analysis with twin-screw extruder

In Part 1 of this work, the possibility of improving single-screw extruders (SSE) better dispersive mixer was explored by harnessing extensional flows provided by the hyperbolic contracting–diverging channels of extensional mixing elements (EME). Addition of the EME to the pin screw generated enhanced breakup for polymer blends and nanocomposite systems without significant penalty in flow rate. In Part 2, experiments are performed on immiscible polymer blends (low-viscosity ratio and high-viscosity ratio) and nanocomposites on both SSE and twin-screw extruder (TSE) with the same rotation speed and throughput. Morphological results show tremendous improvement in dispersive mixing capability of SSE when equipped with EME that are mainly comparable to conventional TSE that is, with kneading blocks as mixing sections, although not as good as TSEs equipped with EMEs. Mechanical results also show enhanced modulus when EME is used in SSE operations.     

Free-living inferential modeling of blood glucose level using only noninvasive inputs

The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements.     

Fault-Tolerant Convergence Routing

This paper presents fault-tolerant protocols for fast packet switch networks withconvergence routing. The objective is to provide fast reconfiguration and continuous host-to-host communication after a link or a node (switch) failure,Convergence routingcan be viewed as a variant ofdeflection routing,which combines, in a dynamic fashion, the on-line routing decision with the traffic load inside the network. Unlike other deflection techniques, convergence routing operates withglobal sense of directionand guarantees that packets will reach or converge to their destinations. Global sense of direction is achieved by embedding of virtual rings to obtain a linear ordering of the nodes. We consider virtual ring embeddings over (i) a single spanning tree, and (ii) over two edge-disjoint spanning trees. Thus, the fault-tolerant solution is based on spanning trees and designed for a switch-based (i.e., arbitrary topology) architecture called MetaNet. In this work, the original MetaNet's convergence routing scheme has been modified in order to facilitate the property that the packet header need not be recomputed after a failure and/or a reconfiguration. This is achieved by having, at the network interface, a translator that maps the unique destination address to a virtual address. It is argued that virtual rings embedded over two-edge disjoint spanning trees increase the fault tolerance for both node and link faults and provides continuous host-to-host communication.     

An Adaptive Role for DNA Double-Strand Breaks in Hippocampus-Dependent Learning and Memory

DNA double-strand breaks (DSBs), classified as the most harmful type of DNA damage based on the complexity of repair, lead to apoptosis or tumorigenesis. In aging, DNA damage increases and DNA repair decreases. This is exacerbated in disease, as post-mortem tissue from patients diagnosed with mild cognitive impairment (MCI) or Alzheimer’s disease (AD) show increased DSBs. A novel role for DSBs in immediate early gene (IEG) expression, learning, and memory has been suggested. Inducing neuronal activity leads to increases in DSBs and upregulation of IEGs, while increasing DSBs and inhibiting DSB repair impairs long-term memory and alters IEG expression. Consistent with this pattern, mice carrying dominant AD mutations have increased baseline DSBs, and impaired DSB repair is observed. These data suggest an adaptive role for DSBs in the central nervous system and dysregulation of DSBs and/or repair might drive age-related cognitive decline (ACD), MCI, and AD. In this review, we discuss the adaptive role of DSBs in hippocampus-dependent learning, memory, and IEG expression. We summarize IEGs, the history of DSBs, and DSBs in synaptic plasticity, aging, and AD. DSBs likely have adaptive functions in the brain, and even subtle alterations in their formation and repair could alter IEGs, learning, and memory.