Thermal conductivity measurement of liquids in a microfluidic device

A new microfluidic-based approach to measuring liquid thermal conductivity is developed to address the requirement in many practical applications for measurements using small (microlitre) sample size and integration into a compact device. The approach also gives the possibility of high-throughput testing. A resistance heater and temperature sensor are incorporated into a glass microfluidic chip to allow transmission and detection of a planar thermal wave crossing a thin layer of the sample. The device is designed so that heat transfer is locally one-dimensional during a short initial time period. This allows the detected temperature transient to be separated into two distinct components: a short-time, purely one-dimensional part from which sample thermal conductivity can be determined and a remaining long-time part containing the effects of three-dimensionality and of the finite size of surrounding thermal reservoirs. Identification of the one-dimensional component yields a steady temperature difference from which sample thermal conductivity can be determined. Calibration is required to give correct representation of changing heater resistance, system layer thicknesses and solid material thermal conductivities with temperature. In this preliminary study, methanol/water mixtures are measured at atmospheric pressure over the temperature range 30–50°C. The results show that the device has produced a measurement accuracy of within 2.5% over the range of thermal conductivity and temperature of the tests. A relation between measurement uncertainty and the geometric and thermal properties of the system is derived and this is used to identify ways that error could be further reduced

Combination schemes for turning point prediction

We propose new forecast combination schemes for predicting turning points of business cycles. The combination schemes deal with the forecasting performance of a given set of models and possibly providing better turning point predictions. We consider turning point predictions generated by autoregressive (AR) and Markov-Switching AR models, which are commonly used for business cycle analysis. In order to account for parameter uncertainty we consider a Bayesian approach to both estimation and prediction and compare, in terms of statistical accuracy, the individual models and the combined turning point predictions for the United States and Euro area business cycles

Use of Data-Biased Random Walks on Graphs for the Retrieval of Context-Specific Networks from Genomic Data

Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data

Anti-inflammatory effects of nicotine in obesity and ulcerative colitis

Cigarette smoke is a major risk factor for a number of diseases including lung cancer and respiratory infections. Paradoxically, it also contains nicotine, an anti-inflammatory alkaloid. There is increasing evidence that smokers have a lower incidence of some inflammatory diseases, including ulcerative colitis, and the protective effect involves the activation of a cholinergic anti-inflammatory pathway that requires the α7 nicotinic acetylcholine receptor (α7nAChR) on immune cells. Obesity is characterized by chronic low-grade inflammation, which contributes to insulin resistance. Nicotine significantly improves glucose homeostasis and insulin sensitivity in genetically obese and diet-induced obese mice, which is associated with suppressed adipose tissue inflammation. Inflammation that results in disruption of the epithelial barrier is a hallmark of inflammatory bowel disease, and nicotine is protective in ulcerative colitis. This article summarizes current evidence for the anti-inflammatory effects of nicotine in obesity and ulcerative colitis. Selective agonists for the α7nAChR could represent a promising pharmacological strategy for the treatment of inflammation in obesity and ulcerative colitis. Nevertheless, we should keep in mind that the anti-inflammatory effects of nicotine could be mediated via the expression of several nAChRs on a particular target cell

Optimal central-place foraging by beavers: Tree-size selection in relation to defensive chemicals of quaking aspen

At a newly occupied pond, beavers preferentially felled aspen smaller than 7.5 cm in diameter and selected against larger size classes. After one year of cutting, 10% of the aspen had been cut and 14% of the living aspen exhibited the juvenile growth form. A phenolic compound which may act as a deterrent to beavers was found in low concentrations in aspen bark, and there was no significant regression of relative concentration of this compound on tree diameter. At a pond which had been intermittently occupied by beavers for over 20 years, beavers selected against aspen smaller than 4.5 cm in diameter, and selected in favor of aspen larger than 19.5 cm in diameter. After more than 28 years of cutting at this site, 51% of the aspen had been cut and 49% of the living aspen were juvenileform. The phenolic compound was found in significantly higher concentrations in aspen bark than at the newly occupied site, and there was a significant negative regression of relative concentration on tree diameter. The results of this study show that responses to browsing by trees place constraints on the predictive value of standard energy-based optimal foraging models, and limitations on the use of such models. Future models should attempt to account for inducible responses of plants to damage and increases in concentrations of secondary metabolites through time.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47775/1/442_2004_Article_BF00379963.pd

The objective method: Probabilistic combinatorial optimization and local weak convergence

This survey describes a general approach to a class of problems that arise in combinatorial probability and combinatorial optimization. Formally, the method is part of weak convergence theory, but in concrete problems the method has a flavor of its own. A characteristic element of the method i

Two large British kindreds with familial Parkinson's disease: A clinico-pathological and genetic study

We present the findings of a study of two large unrelated kindreds with autosomal dominant Parkinson's disease. The affected members were assessed clinically and with [18F]6-fluorodopa-PET and were indistinguishable from patients with the sporadic form of Parkinson's disease. In one kindred, an affected member was examined subsequently at autopsy and Lewy bodies were present in a distribution typical of sporadic Parkinson's disease. These kindreds are distinct from other Parkinsonian kindreds with identified genetic loci (PARK1-4) and provide further evidence for genetic heterogeneity in familial Parkinson's disease.link_to_OA_fulltex