Measures for investigating the contextual modulation of information transmission

The aim of this paper is to show how information theoretic measures can be used to analyse and interpret the results of psychophysical experiments designed to search for conditions under which information from one source modulates the transmission of information from another source. We therefore use measures of mutual and conditional information to analyse systems with two inputs. The information transmitted by such a system can be split into three components depending on whether it is shared between the two inputs or is specific to each. We are concerned here with distinguishing systems that use one input to modulate transmission of information about the other from systems that simply add both inputs, and show how the three components provide evidence for distinguishing between additive and modulatory effects. We also report numerical simulations of the sampling biasses and variances of these measures as a function of the sample size and propose minimum sample sizes that should be used to overcome the bias.     

Double-codified gold nanolabels for enhanced immunoanalysis

A novel double-codified nanolabel (DC-AuNP) based on gold nanoparticle (AuNP) modified with anti-human IgG peroxidase (HRP)-conjugated antibody is reported. It represents a simple assay that allows enhanced spectrophotometric and electrochemical detection of antigen human IgG as a model protein. The method takes advantage of two properties of the DC-AuNP label: first, the HRP label activity toward the OPD chromogen that can be related to the analyte concentration and measured spectrophotometrically; second, the intrinsic electrochemical properties of the gold nanoparticle labels that being proportional to the protein concentration can be directly quantified by stripping voltammetry. Beside these two main direct determinations of human IgG, a secondary indirect detection was also applicable to this system, exploiting the high molar absorptivity of gold colloids, by which, the color intensity of their solution was proportional to the concentration of the antigen used in the assay. Paramagnetic beads were used as supporting material to immobilize the sandwich-type immunocomplexes resulting in incubation and washing times shorter than those typically needed in classical ELISA tests by means of a rapid magnetic separation of the unbound components. A built-in magnet graphite-epoxy-composite electrode allowed a sensibly enhanced adsorption and electrochemical quantification of the specifically captured AuNPs. The used DC-AuNP label showed an excellent specificity/selectivity, as a matter of fact using a different antigen (goat IgG) a minimal nonspecific electrochemical or spectrophotometric signal was measured. The detection limits for this novel double-codified nanoparticle-based assay were 52 and 260 pg of human IgG/mL for the spectrophotometric (HRP-based) and electrochemical (AuNP-based) detections, respectively, much lower than those typically achieved by ELISA tests. The developed label and method is versatile, offers enhanced performances, and can be easily extended to other protein detection schemes as well as in DNA analysis.     

Analyzing the mechanisms of selectivity in biomimetic self-assemblies via IR and NMR spectroscopy of prepolymerization solutions and molecular dynamics simulations

Molecularly imprinted polymers (MIPs) for 2,4-dichlorophenoxyacetic acid were synthesized via a noncovalent approach with 4-vinylpyridine as functional monomer and ethylene glycol dimethacrylate as cross-linker in a methanol/water mixture. Templated polymers synthesized in this self-assembly approach rely on complex formation between the target analyte and functional monomers in porogenic solution prior to radical polymerization. Consequently, the achievable selectivity is governed by the nature and stability of these complexes. The nature of noncovalent interactions responsible for complex formation during imprinting of the template 2,4-dichlorophenoxyacetic acid (2,4-D) with the functional monomer 4-vinylpyridine has been investigated. Fourier transform infrared and 1H NMR spectroscopies provide the fundamental analytical basis for rationalizing the mechanisms of recognition during the imprinting process probing the governing interactions for selective binding site formation at a molecular level. Molecular modeling studies in explicit solvent (chloroform and water) corroborate the importance of hydrogen bonding in aprotic solvents and of hydrophobic interactions in protic media in agreement with the experimental spectroscopic investigations of prepolymerization solutions. Furthermore, chromatographic studies of the synthesized MIPs provided insight on the importance of size, shape, and functionality during selective 2,4-D rebinding processes confirming the results obtained during the prepolymerization studies.     

Structured writing about stressful events: Exploring potential psychological mediators of positive health effects.

In a previous study, the authors found that structured writing about stressful events improved symptomatology in 112 patients with rheumatoid arthritis and asthma relative to patients who did not write (J. Smyth, A. Stone, A. Hurewitz, & A. Kaell, 1999). However, little is currently known about the pathways from the intervention to alterations in outcomes. In addition to measuring symptom outcomes after the intervention in the previous study, the authors monitored perceived stress, quality of sleep, affect, substance use, and medication use on a momentary basis for the 7 days prior to writing, during the 3 intervention days, and for the 14 days following the intervention (N?=?105). These variables were tested in a secondary data analysis to determine whether they mediated the effects observed in the J. Smyth, A. Stone, et al. study. No evidence was found supporting mediation, and the mechanism underlying structured writing about stressful events remains unknown. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Data mining: data analysis on a grand scale?

Modern data mining has evolved largely as a result of efforts by computer scientists to address the needs of 'data owners' in extracting useful information from massive observational data sets. Because of this historical context, data mining to date has largely focused on computational and algorithmic issues rather than the more traditional statistical aspects of data analysis. This paper provides a brief review of the origins of data mining as well as discussing some of the primary themes in current research in data mining, including scalable algorithms for massive data sets, discovering novel patterns in data, and analysis of text, web, and related multimedia data sets.     

Conversational Collaborative Recommendation – An Experimental Analysis

Traditionally, collaborative recommender systems have been based on a single-shot model of recommendation where a single set of recommendations is generated based on a user’s (past) stored preferences. However, content-based recommender system research has begun to look towards more conversational models of recommendation, where the user is actively engaged in directing search at recommendation time. Such interactions can range from high-level dialogues with the user, possibly in natural language, to more simple interactions where the user is, for example, asked to indicate a preference for one of k suggested items. Importantly, the feedback attained from these interactions can help to differentiate between the user’s long-term stored preferences, and her current (short-term) requirements, which may be quite different. We argue that such interactions can also be beneficial to collaborative recommendation and provide experimental evidence to support this claim.     

Long-term validated simulation of a building integrated photovoltaic system

Electrical and thermal simulations of a building integrated photovoltaic system were undertaken with a transient system simulation program using real field input weather data. Predicted results were compared with actual measured data. A site dependent global-diffuse correlation is proposed. The best-tilted surface radiation model for estimating insolation on the inclined surface was selected by statistical tests. To predict the module temperature, a linear correlation equation is developed which relates the temperature difference between module and ambient to insolation. Different combinations of tilted surface radiation model, global-diffuse correlation model and predicted module temperature were used to carry out the simulation and corresponding simulated results compared with the measured data to determine the best combination which gave the least error. Results show that modification of global-diffuse correlation and module temperature prediction improved the overall accuracy of the simulation model. The monthly error between measured and predicted PV output was lied below 16%. Over the period of simulation, the monthly average error between measured and predicted PV output was estimated to be 6.79% whereas, the monthly average error between measured and predicted inverter output was 4.74%.     

Are more senior academics really more research productive than junior academics? Evidence from Australian law schools

This study examines the relationship between academic seniority and research productivity through a study of a sample of academics at Australian law schools. To measure research productivity, we use both publications in top law journals, variously defined, and citation metrics. A feature of the study is that we pay particular attention to addressing the endogeneity of academic rank. To do so, we use a novel identification strategy, proposed by Lewbel (Journal of Business and Economic Statistics 30:67–80, 2012), which utilises a heteroscedastic covariance restriction to construct an internal instrumental variable. Our main finding is that once endogeneity of academic rank is addressed, more senior academics at Australian law schools do not publish more articles in top law journals (irrespective of how top law journals are defined) than their less senior colleagues. However, Professors continue to have greater impact than Lecturers when research productivity is measured in terms of total citations and common citation indices, such as the h-index and g-index.     

A probabilistic approach for the construction of regional earthquake response spectra

Five scenario earthquakes plausible for the Los Angeles metropolitan region, and one numerical approximation of the 1994 Northridge M_w 6.7 event, provide the database of the proposed methodology that is applied for the construction of regional earthquake response spectra. The methodology involves two main stages of data compaction. In the first stage, the Karhunen–Loève (K–L) decomposition of the excitation temporal covariance matrix is performed. In the second stage, the dominant eigenvectors are analytically approximated with Chebyshev polynomials, thus being converted from eigenvectors to eigenfunctions. This compact analytical representation of the nonstationary excitation data provides an exact closed-form solution for the nonstationary response of linear multi-degree-of-freedom systems. Furthermore, statistical inference analysis for the response variables is conducted, which leads to the construction of regional probabilistic response spectra based on the Log-Normal probability model for the response variables.