How do we reach them? Comparing random samples from mobile and landline phones

Quantitative studies of nascent entrepreneurs such as GEM and PSED are required to generate their samples by screening the adult population, usually by phone in developed economies. Phone survey research has recently been challenged by shifting patterns of ownership and response rates of landline versus mobile (cell) phones, particularly for younger respondents. This challenge is acutely intense for entrepreneurship which is a strongly age-dependent phenomenon. Although shifting ownership rates have received some attention, shifting response rates have remained largely unexplored. For the Australian GEM 2010 adult population study we conducted a dual-frame approach that allows comparison between samples of mobile and landline phones. We find a substantial response bias towards younger, male and metropolitan respondents for mobile phones – far greater than explained by ownership rates. We also found these response rate differences significantly biases the estimates of the prevalence of early stage entrepreneurship by both samples, even when each sample is weighted to match the Australian population.

Methodology for extracting quasi-random samples from world wide web domains

The purpose of this paper is to describe a process for sampling specific domain name zones on the World Wide Web. Because of the size of the Web, sampling strategies must be employed in order to effectively model and study the Web business environment.  This paper discusses Various efforts employed to sample the Web, which ranged from random generation of Internet Protocol Addresses and domain names, to the process finally
employed to create descriptive models of the dot-com domain name zones. The paper suggests that sampling the Web Top Level Domains offers a reasonable alternative for business researchers because it requires only familiarity with the use of the simple Web utilities such as File Transfer
Protocols to obtain initial domain name listings.

Sequential fusion of decisions from adaptive and random samples for controlled verification of errors

Fusion techniques have received considerable attention for achieving performance improvement with biometrics. While a multi-sample fusion architecture reduces false rejects, it also increases false accepts. This impact on performance also depends on the nature of subsequent attempts, i.e., random or adaptive. Expressions for error rates are presented and experimentally evaluated in this work by considering the multi-sample fusion architecture for text-dependent speaker verification using HMM based digit dependent speaker models. Analysis incorporating correlation modeling demonstrates that the use of adaptive samples improves overall fusion performance compared to randomly repeated samples. For a text dependent speaker verification system using digit strings, sequential decision fusion of seven instances with three random samples is shown to reduce the overall error of the verification system by 26% which can be further reduced by 6% for adaptive samples. This analysis novel in its treatment of random and adaptive multiple presentations within a sequential fused decision architecture, is also applicable to other biometric modalities such as finger prints and handwriting samples.

Three-dimensional Doppler evaluation of single spherical samples from the placenta: intra- and interobserver reliability

Objective To evaluate the intra- and interobserver reliability of assessment of three-dimensional power Doppler (3D-PD) indices from single spherical samples of the placenta. Methods Women with singleton pregnancies at 2440 weeks' gestation were included. Three scans were independently performed by two observers; Observer 1 performed the first and third scan, intercalated by the scan of Observer 2. The observers independently analyzed the 3D-PD datasets that they had previously acquired using four different methods, each using a spherical sample: random sample extending from basal to chorionic plate; random sample with 2 cm3 of volume; directed sample to the region subjectively determined as containing more color Doppler signals extending from basal to chorionic plate; or directed sample with 2 cm3 of volume. The vascularization index (VI), flow index (FI) and vascularization flow index (VFI) were evaluated in each case. The observers were blinded to their own and each other's results. Additional evaluation was performed according to placental location: anterior, posterior and fundal or lateral. Intra- and interobserver reliability was assessed by intraclass correlation coefficients (ICC). Results Ninety-five pregnancies were included in the analysis. All three placental 3D-PD indices showed only weak to moderate reliability (ICC < 0.66 and ICC < 0.48, intra- and interobserver, respectively). The highest values of ICC were observed when using directed spherical samples from basal to chorionic plate. When analyzed by placental location, we found lower ICCs for lateral and fundal placentae compared to anterior and posterior ones. Conclusion Intra- and interobserver reliability of assessment of placental 3D-PD indices from single spherical samples in pregnant women greater than 24 weeks' gestation is poor to moderate, and clinical usefulness of these indices is likely to be limited. Copyright (c) 2012 ISUOG. Published by John Wiley & Sons, Ltd.

A spectroscopic investigation of pigment and ceramic samples from Copán, Honduras

A combination of micro-Raman spectroscopy, micro-infrared spectroscopy and SEM–EDX was employed to characterize decorative pigments on Classic Maya ceramics from Copán, Honduras. Variation in red paint mixtures was correlated with changing ceramic types and improvements in process and firing techniques. We have confirmed the use of specular hematite on Coner ceramics by the difference in intensities of Raman bands. Different compositions of brown paint were correlated with imported and local wares. The carbon-iron composition of the ceramic type, Surlo Brown, was confirmed. By combining micro-Raman analysis with micro-ATR infrared and SEM–EDX, we have achieved a more comprehensive characterization of the paint mixtures. These spectroscopic techniques can be used non-destructively on raw samples as a rapid confirmation of ceramic type.

Development of an autonomous unmanned aerial system to collect time-stamped samples from the atmosphere and localize potential pathogen sources

This paper presents the hardware development and testing of a new concept for air sampling via the integration of a prototype spore trap onboard an unmanned aerial system (UAS).We propose the integration of a prototype spore trap onboard a UAS to allow multiple capture of spores of pathogens in single remote locations at high or low altitude, otherwise not possible with stationary sampling devices.We also demonstrate the capability of this system for the capture of multiple time-stamped samples during a single mission.Wind tunnel testing was followed by simulation, and flight testing was conducted to measure and quantify the spread during simulated airborne air sampling operations. During autonomous operations, the onboard autopilot commands the servo to rotate the sampling device to a new indexed location once the UAS vehicle reaches the predefined waypoint or set of waypoints (which represents the region of interest). Time-stamped UAS data are continuously logged during the flight to assist with analysis of the particles collected. Testing and validation of the autopilot and spore trap integration, functionality, and performance is described. These tools may enhance the ability to detect new incursions of spores

Taxonomic resolution and quantification of freshwater macroinvertebrate samples from an Australian dryland river : The benefits and costs of using species abundance data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.

Combining HPLC-DAD and ICP-MS data for improved analysis of complex samples: Classification of the root samples from Cortex moutan

A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

Abnormal levels of heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) in tumour tissue and blood samples from patients diagnosed with lung cancer

Lung cancer is the second most common type of cancer in the world and is the most common cause of cancer-related death in both men and women. Research into causes, prevention and treatment of lung cancer is ongoing and much progress has been made recently in these areas, however survival rates have not significantly improved. Therefore, it is essential to develop biomarkers for early diagnosis of lung cancer, prediction of metastasis and evaluation of treatment efficiency, as well as using these molecules to provide some understanding about tumour biology and translate highly promising findings in basic science research to clinical application. In this investigation, two-dimensional difference gel electrophoresis and mass spectrometry were initially used to analyse conditioned media from a panel of lung cancer and normal bronchial epithelial cell lines. Significant proteins were identified with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), pyruvate kinase M2 isoform (PKM2), Hsc-70 interacting protein and lactate dehydrogenase A (LDHA) selected for analysis in serum from healthy individuals and lung cancer patients. hnRNPA2B1, PKM2 and LDHA were found to be statistically significant in all comparisons. Tissue analysis and knockdown of hnRNPA2B1 using siRNA subsequently demonstrated both the overexpression and potential role for this molecule in lung tumorigenesis. The data presented highlights a number of in vitro derived candidate biomarkers subsequently verified in patient samples and also provides some insight into their roles in the complex intracellular mechanisms associated with tumour progression.

Microbial community analysis of Acropora palamata mucus swabs, water and sediment samples from Hawksnest Bay, St. John, U.S. Virgin Islands

Colonies of the scleractinian coral Acropora palmata, listed as threatened under the US Endangered Species Act in 2006, have been monitored in Hawksnest Bay, within Virgin Islands National Park, St. John, from 2004 through 2010 by scientists with the US Geological Survey, National Park Service, and the University of the Virgin Islands. The focus has been on documenting the prevalence of disease, including white band, white pox (also called patchy necrosis and white patches), and unidentified diseases (Rogers et al., 2008; Muller et al., 2008). In an effort to learn more about the pathologies that might be involved with the diseases that were observed, samples were collected from apparently healthy and diseased colonies in July 2009 for analysis. Two different microbial assays were performed on Epicentre Biotechnologies DNA swabs containing A. palmata coral mucus, and on water and sediment samples collected in Hawksnest Bay. Both assays are based on polymerase chain reaction (PCR) amplification of portions of the small rRNA gene (16S). The objectives were to determine 1) if known coral bacterial pathogens Serratia marcescens (Acroporid Serratiosis), Vibrio coralliilyticus (temperature-dependent bleaching, White Syndrome), Vibrio shiloi (bleaching, necrosis), and Aurantimonas coralicida (White Plague Type II) were present in any samples, and 2) if there were any differences in microbial community profiles of each healthy, unaffected or diseased coral mucus swab. In addition to coral mucus, water and sediment samples were included to show ambient microbial populations. In the first test, PCR was used to separately amplify the unique and diagnostic region of the 16S rRNA gene for each of the coral pathogens being screened. Each pathogen test was designed so that an amplified DNA fragment could be seen only if the specific pathogen was present in a sample. A positive result was indicated by bands of DNA of the appropriate size on an agarose gel, which separates DNA fragments based on the size of the molecule. DNA from pure cultures of each of the pathogens was used as a positive control for each assay.

Methylation of tumor associated genes in tissue and plasma samples from liver disease patients

To investigate whether aberrant hypermethylation in plasma DNA could be used as diagnosis makers for hepatocellular carcinoma (HCC), we performed methylation-specific PCR (MSP) to check the methylation status of five tumor associated genes in 36 cases of

The Random Forest Kernel and other kernels for big data from random partitions

We present Random Partition Kernels, a new class of kernels derived by demonstrating a natural connection between random partitions of objects and kernels between those objects. We show how the construction can be used to create kernels from methods that would not normally be viewed as random partitions, such as Random Forest. To demonstrate the potential of this method, we propose two new kernels, the Random Forest Kernel and the Fast Cluster Kernel, and show that these kernels consistently outperform standard kernels on problems involving real-world datasets. Finally, we show how the form of these kernels lend themselves to a natural approximation that is appropriate for certain big data problems, allowing $O(N)$ inference in methods such as Gaussian Processes, Support Vector Machines and Kernel PCA.