On the Divergence of Lagrange Interpolation to |x|

AbstractIt is a classical result of Bernstein that the sequence of Lagrange interpolation polynomials to |x| at equally spaced nodes in [−1, 1] diverges everywhere, except at zero and the end-points. In the present paper we show that the case of equally spaced nodes is not an exceptional one in this sense. Namely, we prove that the divergence everywhere in 0 < |x| < 1 of the Lagrange interpolation to |x| takes place for a broad family of nodes, including in particular the Newman nodes, which are known to be very efficient for rational interpolation

Adapting Traffic Simulation for Traffic Management: A Neural Network Approach

Static models and simulations are commonly used in urban traffic management but none feature a dynamic element for near real-time traffic control. This work presents an artificial neural network forecaster methodology applied to traffic flow condition prediction. The spatially distributed architecture uses life-long learning with a novel adaptive Artificial Neural Network based filter to detect and remove outliers from training data. The system has been designed to support traffic engineers in their decision making to react to traffic conditions before they get out of control. We performed experiments using feed-forward backpropagation, cascade-forward back-propagation, radial basis, and generalized regression Artificial Neural Networks for this purpose. Test results on actual data collected from the city of Leicester, UK, confirm our approach to deliver suitable forecasts

Neighbouring Link Travel Time Inference Method Using Artificial Neural Network

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper presents a method for modelling relationship between road segments using feed forward back-propagation neural networks. Unlike most previous papers that focus on travel time estimation of a road based on its traffic information, we proposed the Neighbouring Link Inference Method (NLIM) that can infer travel time of a road segment (link) from travel time its neighbouring segments. It is valuable for links which do not have recent traffic information. The proposed method learns the relationship between travel time of a link and traffic parameters of its nearby links based on sparse historical travel time data. A travel time data outlier detection based on Gaussian mixture model is also proposed in order to reduce the noise of data before they are applied to build NLIM. Results show that the proposed method is capable of estimating the travel time on all traffic link categories. 75% of models can produce travel time data with mean absolute percentage error less than 22%. The proposed method performs better on major than minor links. Performance of the proposed method always dominates performance of traditional methods such as statistic-based and linear least square estimate methods

Estimation of Travel Times for Minor Roads in Urban Areas Using Sparse Travel Time Data

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link

Chamber material effects on actinometric measurements in rf glow discharges

The relative concentration of atomic fluroine was measured in a CF4 rf glow discharge using the actinometric technique. The dependence of fluorine concentration on power, pressure and flow are presented and shown to be dependent upon reactor wall material and electrode material.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70093/2/JAPIAU-69-5-2885-1.pd

Computational Intelligence to Improve Air Quality and Traffic Management

Computational Intelligence (CI) techniques are strong and efficient and capable of enhancing current traffic and air quality management systems

Planktonic Aggregates as Hotspots for Heterotrophic Diazotrophy: The Plot Thickens

Biological dinitrogen (N-2) fixation is performed solely by specialized bacteria and archaea termed diazotrophs, introducing new reactive nitrogen into aquatic environments. Conventionally, phototrophic cyanobacteria are considered the major diazotrophs in aquatic environments. However, accumulating evidence indicates that diverse non-cyanobacterial diazotrophs (NCDs) inhabit a wide range of aquatic ecosystems, including temperate and polar latitudes, coastal environments and the deep ocean. NCDs are thus suspected to impact global nitrogen cycling decisively, yet their ecological and quantitative importance remain unknown. Here we review recent molecular and biogeochemical evidence demonstrating that pelagic NCDs inhabit and thrive especially on aggregates in diverse aquatic ecosystems. Aggregates are characterized by reduced-oxygen microzones, high C:N ratio (above Redfield) and high availability of labile carbon as compared to the ambient water. We argue that planktonic aggregates are important loci for energetically-expensive N-2 fixation by NCDs and propose a conceptual framework for aggregate-associated N-2 fixation. Future studies on aggregate-associated diazotrophy, using novel methodological approaches, are encouraged to address the ecological relevance of NCDs for nitrogen cycling in aquatic environments

Tissue microarrays: one size does not fit all

<p>Abstract</p> <p>Background</p> <p>Although tissue microarrays (TMAs) are commonly employed in clinical and basic-science research, there are no guidelines for evaluating the appropriateness of a TMA for a given biomarker and tumor type. Furthermore, TMA performance across multiple biomarkers has not been systematically explored.</p> <p>Methods</p> <p>A simulated TMA with between 1 and 10 cores was designed to study tumor expression of 6 biomarkers with varied expression patterns (B7-H1, B7-H3, survivin, Ki-67, CAIX, and IMP3) using 100 patients with clear cell renal cell carcinoma (RCC). We evaluated agreement between whole tissue section and TMA immunohistochemical biomarker quantification to assess how many TMA cores are necessary to adequately represent RCC whole tissue section expression. Additionally, we evaluated associations of whole tissue section and TMA expression with RCC-specific death.</p> <p>Results</p> <p>The number of simulated TMA cores necessary to adequately represent whole tissue section quantification is biomarker specific. Although 2-3 cores appeared adequate for B7-H3, Ki-67, CAIX, and IMP3, even as many as 10 cores resulted in poor agreement for B7-H1 and survivin compared to RCC whole tissue sections. While whole tissue section B7-H1 was significantly associated with RCC-specific death, no significant associations were detected using as many as 10 TMA cores, suggesting that TMAs can result in false-negative findings if the TMA is not optimally designed.</p> <p>Conclusions</p> <p>Prior to TMA analysis, the number of TMA cores necessary to accurately represent biomarker expression on whole tissue sections should be established as there is not a one-size-fits-all TMA. We illustrate the use of a simulated TMA as a cost-effective tool for this purpose.</p

Relative fluorine concentrations in radio frequency/electron cyclotron resonance hybrid glow discharges

The relative concentration of atomic fluorine was measured in a radio frequency (rf) glow discharge and a modified electron cyclotron resonance microwave/rf hybrid discharge in CF4 using an actinometric technique. The dependence of fluorine concentration on rf and microwave power, pressure, flow, and excitation source are presented. Anomalous behavior with rf power at constant microwave power was observed when using the Ar 750‐nm line as the actinometric species.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70900/2/APPLAB-60-7-818-1.pd

Protocols for the assurance of microarray data quality and process control

Microarrays represent a powerful technology that provides the ability to simultaneously measure the expression of thousands of genes. However, it is a multi-step process with numerous potential sources of variation that can compromise data analysis and interpretation if left uncontrolled, necessitating the development of quality control protocols to ensure assay consistency and high-quality data. In response to emerging standards, such as the minimum information about a microarray experiment standard, tools are required to ascertain the quality and reproducibility of results within and across studies. To this end, an intralaboratory quality control protocol for two color, spotted microarrays was developed using cDNA microarrays from in vivo and in vitro dose-response and time-course studies. The protocol combines: (i) diagnostic plots monitoring the degree of feature saturation, global feature and background intensities, and feature misalignments with (ii) plots monitoring the intensity distributions within arrays with (iii) a support vector machine (SVM) model. The protocol is applicable to any laboratory with sufficient datasets to establish historical high- and low-quality data