Patterns of entrepreneurial career development: An optimal matching analysis approach

Longitudinal studies of entrepreneurial career development are rare, and current knowledge of self-employment patterns and their relationships with individual difference characteristics is limited. In this study, the authors analyzed employment data from a subsample of 514 participants from the German Socio-Economic Panel study (1984–2008). Results of an optimal matching analysis indicated that a continuous self-employment pattern could be distinguished from four alternative employment patterns (change from employment to self-employment, full-time employees, part-time employees, and farmers). Results of a multinomial logistic regression analysis showed that certain socio-demographic characteristics (i.e., age and gender) and personality characteristics (i.e., conscientiousness and risk-taking propensity) were related to the likelihood of following a continuous self-employment pattern compared to the other employment patterns. Implications for future research on entrepreneurial career development are discussed.

Career patterns: A twenty-year panel study

Using 20 years of employment and job mobility data from a representative German sample (N = 1259), we employ optimal matching analysis (OMA) to identify six career patterns which deviate from the traditional career path of long-term, full-time employment in one organization. Then, in further analyses, we examine which socio-demographic predictors affect whether or not individuals follow that traditional career path. Results indicate that age, gender, marital status, number of children, education, and career starts in the public sector significantly predicted whether or not individuals followed the traditional career path. The article concludes with directions for future theoretical and methodological research on career patterns.

Analysis and Improvements to the Green Falcon Solar Powered UAV

There has recently been a rapidly increasing interest in solar powered UAVs. With the emergence of high power density batteries, long range and low-power micro radio devices, airframes, and powerful micro-processors and motors, small/micro UAVs have become applicable in civilian applications such as remote sensing, mapping, traffic monitoring, search and rescue. The Green Falcon UAV is an innovative project from Queensland University of Technology and has been developed and tested during these past years. It comprises a wide range of subsystems to be analyses and studied such as Solar Panel Cells, Gas sensor, Aerodynamics of the wing and others. Previous test however, resulted in damage to the solar cells and some of the subsystems including motor and ESC. This report describes the repair and verification process followed to improve the efficiency of the Green Falcon UAV. The report shows some of the results obtained in previous static and flight tests as well as some of recommendations.

Income Inequality and Healt: A Multi-Country Analysis

This paper investigates the effect of income inequality on health status. A model of health status was specified in which the main variables were income level, income inequality, the level of savings and the level of education. The model was estimated using a panel data set for 44 countries covering six time periods. The results indicate that income inequality (measured by the Gini coefficient) has a significant effect on health status when we control for the levels of income, savings and education. The relationship is consistent regardless of the specification of health status and income. Thus, the study results provide some empirical support for the income inequality hypothesis.

Thermal sensitivity analysis of spacecraft battery

Transient thermal sensitivity is studied for systems that are subjected to conductive heat transfer within themselves and radiative heat transfer with the surrounding environment, including solar heat radiation, The battery in the Indian national communication satellite is one such system for which the studies are conducted with respect to panel conduction, conductance of insulating blanket, power dissipation within the battery, and absorptance and emittance of various elements, Comparison of sensitivities revealed that battery temperature is sensitive to its power dissipation during the beginning of life of the spacecraft, whereas toward the end of life of the spacecraft mission, the effect of absorptance of optical solar reflector is dominating, The influence of optical property values of the multilayer insulation blanket is almost negligible. Among the parameters studied in this analysis, the battery temperature is found to be mast sensitive to emittance of the optical solar reflector.

Ultrasonic Guided Wave Characterization and Damage Detection in Foam-core Sandwich Panel using PWAS and LDV

Lamb wave type guided wave propagation in foam core sandwich structures and detectability of damages using spectral analysis method are reported in this paper. An experimental study supported by theoretical evaluation of the guided wave characteristics is presented here that shows the applicability of Lamb wave type guided ultrasonic wave for detection of damage in foam core sandwich structures. Sandwich beam specimens were fabricated with 10 mm thick foam core and 0.3 mm thick aluminum face sheets. Thin piezoelectric patch actuators and sensors are used to excite and sense guided wave. Group velocity dispersion curves and frequency response of sensed signal are obtained experimentally. The nature of damping present in the sandwich panel is monitored by measuring the sensor signal amplitude at various different distances measured from the center of the linear phased array. Delaminations of increasing width are created and detected experimentally by pitch-catch interrogation with guided waves and wavelet transform of the sensed signal. Signal amplitudes are analyzed for various different sizes of damages to differentiate the damage size/severity. A sandwich panel is also fabricated with a planer dimension of 600 mm x 400 mm. Release film delamination is introduced during fabrication. Non-contact Laser Doppler Vibrometer (LDV) is used to scan the panel while exciting with a surface bonded piezoelectric actuator. Presence of damage is confirmed by the reflected wave fringe pattern obtained from the LDV scan. With this approach it is possible to locate and monitor the damages by tracking the wave packets scattered from the damages.

Influence of dust deposition on photovoltaic panel performance

Solar photovoltaic power plants are ideally located in regions with high insolation levels. Photovoltaic performance is affected by high cell temperatures, soiling, mismatch and other balance-of-systems related losses. It is crucial to understand the significance of each of these losses on system performance. Soiling, highly dependent on installation conditions, is a complex performance issue to accurately quantify. The settlement of dust on panel surfaces may or may not be uniform depending on local terrain and environmental factors such as ambient temperature, wind and rainfall. It is essential to investigate the influence of dust settlement on the operating characteristics of photovoltaic systems to better understand losses in performance attributable to soiling. The current voltage (I-V) characteristics of photovoltaic panels reveal extensive information to support degradation analysis of the panels. This paper attempts to understand performance losses due to dust through a dynamic study into the I-V characteristics of panels under varying soiling conditions in an outdoor experimental test-bed. Further, the results of an indoor study simulating the performance of photovoltaic panels under different dust deposition regimes are discussed in this paper. (C) 2014 Monto Mani. Published by Elsevier Ltd. This is all open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Inequality for Wage Earners and Self-Employed: Evidence from Panel Data

Published as an article in: Oxford Bulletin of Economics and Statistics, 2009, vol. 71, issue 4, pages 491-518.

The effect of flexibility in working hours on fertility: A comparative analysis of selected european countries

The main aim of this paper is to measure the extent to which part-time work enhances fertility for married or cohabiting women of fertile age. The study covers eleven European countries. The data used are a pool sample of five waves of the European Community Household Panel. Given that we believe that the decisions concerning fertility and labor market status are taken jointly, we carry out a simultaneous estimation approach. Results suggest that policy makers wishing to implement adequate part-time schedules so as to enhance fertility should look at the part-time schedules available in Belgium, Ireland and The Netherlands, which enhance fertility for women who take advantage of this flexibility measure so as to reconcile family and work.

Identification of a biomarker panel for colorectal cancer diagnosis

Background: Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60- mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality–lost values imputation, probes quality, data smoothing and intraclass variability filtering–the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

Technology for Single Cell Protein Analysis in Immunology and Cancer Prognostics

The first chapter of this thesis deals with automating data gathering for single cell microfluidic tests. The programs developed saved significant amounts of time with no loss in accuracy. The technology from this chapter was applied to experiments in both Chapters 4 and 5.

The second chapter describes the use of statistical learning to prognose if an anti-angiogenic drug (Bevacizumab) would successfully treat a glioblastoma multiforme tumor. This was conducted by first measuring protein levels from 92 blood samples using the DNA-encoded antibody library platform. This allowed the measure of 35 different proteins per sample, with comparable sensitivity to ELISA. Two statistical learning models were developed in order to predict whether the treatment would succeed. The first, logistic regression, predicted with 85% accuracy and an AUC of 0.901 using a five protein panel. These five proteins were statistically significant predictors and gave insight into the mechanism behind anti-angiogenic success/failure. The second model, an ensemble model of logistic regression, kNN, and random forest, predicted with a slightly higher accuracy of 87%.

The third chapter details the development of a photocleavable conjugate that multiplexed cell surface detection in microfluidic devices. The method successfully detected streptavidin on coated beads with 92% positive predictive rate. Furthermore, chambers with 0, 1, 2, and 3+ beads were statistically distinguishable. The method was then used to detect CD3 on Jurkat T cells, yielding a positive predictive rate of 49% and false positive rate of 0%.

The fourth chapter talks about the use of measuring T cell polyfunctionality in order to predict whether a patient will succeed an adoptive T cells transfer therapy. In 15 patients, we measured 10 proteins from individual T cells (~300 cells per patient). The polyfunctional strength index was calculated, which was then correlated with the patient's progress free survival (PFS) time. 52 other parameters measured in the single cell test were correlated with the PFS. No statistical correlator has been determined, however, and more data is necessary to reach a conclusion.

Finally, the fifth chapter talks about the interactions between T cells and how that affects their protein secretion. It was observed that T cells in direct contact selectively enhance their protein secretion, in some cases by over 5 fold. This occurred for Granzyme B, Perforin, CCL4, TNFa, and IFNg. IL- 10 was shown to decrease slightly upon contact. This phenomenon held true for T cells from all patients tested (n=8). Using single cell data, the theoretical protein secretion frequency was calculated for two cells and then compared to the observed rate of secretion for both two cells not in contact, and two cells in contact. In over 90% of cases, the theoretical protein secretion rate matched that of two cells not in contact.

Moderate energy impact analysis combining phenomenological contact law with localised damage and integral equation method

A computational impact analysis methodology has been developed, based on modal analysis and a local contact force-deflection model. The contact law is based on Hertz contact theory while contact stresses are elastic, defines a modified contact theory to take account of local permanent indentation, and considers elastic recovery during unloading. The model was validated experimentally through impact testing of glass-carbon hybrid braided composite panels. Specimens were mounted in a support frame and the contact force was inferred from the deceleration of the impactor, measured by high-speed photography. A Finite Element analysis of the panel and support frame assembly was performed to compute the modal responses. The new contact model performed well in predicting the peak forces and impact durations for moderate energy impacts (15 J), where contact stresses locally exceed the linear elastic limit and damage may be deemed to have occurred. C-scan measurements revealed substantial damage for impact energies in the range of 30-50 J. For this regime the new model predictions might be improved by characterisation of the contact law hysteresis during the unloading phase, and a modification of the elastic vibration response in line with damage levels acquired during the impact. © 2011 Elsevier Ltd. All rights reserved.

Grand Challenges for Data Sensing and Analysis

A diverse group of experts proposed the 9 grand challenges outlined in this booklet. This expert task force was assembled by the ASCE TCCIT Data Sensing and Analysis (DSA) Committee and endorsed by the TRB AFH10(1) Construction IT joint subcommittee at the request of their membership. The task force did not rank the challenges selected, nor did it endorse particular approaches to meeting them. Rather than attempt to include every important goal for data sensing and analysis, the panel chose opportunities that were both achievable and sustainable to help people and the planet thrive. The panel’s conclusions were reviewed by several subject-matter experts. The DSA is offering an opportunity to comment on the challenges by contacting the task force chair via email at becerik@usc.edu.

Design Study of a Heavily Loaded Ice Class Propeller Using an Advance Panel Method

A design and optimization procedure developed and used for a propeller installed on a twin-semitunnel-hull ship navigating in very shallow and icy water under heavy load conditions is presented. The base propeller for this vessel was first determined using classic design routines under open-water condition with existing model test data. In the optimization process, a panel method code (PROPELLA) was used to vary the pitch values and distributions and take into account the inflow wake distribution, tunnel gap, and cavitation effects. The optimized propeller was able to improve a ship speed of 0.02 knots higher than the desired speed and 0.06 knots higher than the classic B-series propeller. The analysis of the effect of inflow wake, hull tunnel, cavitation, and blade rake angle on propulsive performance is the focus of this paper.