Identification of relevant predictors of loan default using the Elastic Net model

The timely prediction of loan default plays an important role in lending decisions and monitoring loans. However, there has been little development of models for the selection of relevant variables for the prediction of loan default. This study identifies financial and economic indicators for the forward-looking prediction of loan default by the application of a penalised regression approach, namely the Elastic Net model. The study employs a sample of US firms with 162 loan default events in total between 1998 and 2013. The sample is sub-divided to form a Test sample and two holdout samples: one drawn from the same period as the Test sample; and one drawn from a subsequent period. The sample of non-defaulting firms is constructed using prior probabilities based on the bond default rate for each year. The 278 potential variables, including the ten economic indicators and 268 financial ratios or summary indicators, are regularised with the application of the Elastic Net model. This process results in the extraction of the ten predictor variables, thus identified as relevant to distinguishing between defaulting and non-defaulting firms. Only one economic indicator, the interest rate, is identified as relevant to the prediction of loan default. The prediction-usefulness of identified predictor variables are tested using the two most widely used conventional prediction models, multiple discriminant analysis (MDA) and logistic regression (Logit). The resulting MDA and Logit models are compared with Altman’s Z-score model and Ohlson’s O-score model, respectively. Both the Elastic Net prediction models provide more logical explanations of the distinctive characteristics of loan defaulting firms than the Altman’s Z-score and Ohlson’s O-score models. The Elastic Net prediction models outperform the Altman’s Z-score and Ohlson’s O-score models in the accuracy of the Type I, the Type II and the overall classification. When applied to a holdout samples within and outside the same periods, the prediction accuracy of the Elastic Net models is maintained for both defaulting and non-defaulting firms. This thesis contributes to the loan default literature by introducing the Elastic Net model for variable selection which enhances the predictive ability of the loan default prediction model. The findings of this thesis are potentially useful to financial institutions. Identification of financial and economic predictor variables of loan default can also facilitate assessment of the credit risk of loan applicants. The findings of this thesis may also facilitate better loan default prediction for purposes of monitoring loans. Lastly, the identification of relevant predictor variables may be useful for the classification of loans in the application of the expected loss model in the preparation of financial statements.Thesis (Ph.D.) -- University of Adelaide, Business School, 201

Slug-based epithelial-mesenchymal transition gene signature is associated with prolonged time to recurrence in glioblastoma

Background
We previously identified a precise stage-associated gene expression signature of coordinately expressed genes, including the transcription factor Slug (SNAI2) and other epithelial mesenchymal transition (EMT) markers, present in samples from publicly available gene expression datasets in multiple cancer types. The expression levels of the co-expressed genes vary in a continuous and coordinate manner across the samples, ranging from absence of expression to strong co-expression of all genes. These data suggest that tumor cells may pass through an EMT like process of mesenchymal transition to varying degrees. 

Findings
Here we show that this signature in glioblastoma multiforme (GBM) is associated with time to recurrence following initial treatment. By analyzing data from The Cancer Genome Atlas (TCGA), we found that GBM patients who responded to therapy and had long time to recurrence had low levels of the signature in their tumor samples (P = 3x10^-7^). We also found that the signature is strongly correlated in gliomas with the putative stem cell marker CD44, and is highly enriched among the differentially expressed genes in glioblastomas vs. lower grade gliomas. 

Conclusions 
Our results suggest that long delay before tumor recurrence is associated with absence of the mesenchymal transition signature, raising the possibility that inhibiting this transition might improve the durability of therapy in glioma patients

Surveying perception of landslide risk management

Aim of work. Enhanced precipitation due to climate changes leads to increase in both frequency and intensityof landslides in Norway. A proactive approach to risk management is therefore required to significantly reduce the losses associated with landslides. Opinions and perceptions from practitioners on performance of landslide risk management are expected to provide insights on areas for improvement in landslide risk management activities in Norway. They are also useful reference for prioritising future work plans in Klima 2050. How to survey and assess perceptions on landslide risk management? A well-established indicator for performance is the Risk Management Index (RMI) proposed by Cardona et al. (2004). The methodology for calculating this index is based on a survey to technical staff, decision-makers, and stakeholders involved in all stages of risk reduction strategies. The RMI is thus an innovative and useful procedure for measuring perceptions holistically from selected actors. The indicator was first used to measure perceptions of landslide risk management in Norway by Chiu (2015). The present study adopts a similar methodology as Chiu (2015) to obtain more survey results as well as opinions that can also provide insights to the future activities of Klima 2050. Perceptions are surveyed for two time periods: 2015 and 2050 and based on national, county, and municipality levels. Relevant data from Chiu (2015) are also analysed together with the survey data in the present study. Risk Management Index (RMI) The RMI is a composite index that consists of four public policies, which are represented by indices, namely Risk Identification index (RMIRI), Risk Reduction index (RMIRR), Disaster Management index (RMIDM), and Governance and Financial Protection index (RMIFP). The RMI is calculated as the mean of the four public policy indices. Each policy index can take a value from 0 to 100. Therefore, RMI also varies from 0 to 100, where the lowest and highest values correspond to the poorest and best performance of risk management (i.e. RMI and policy indices increase as the performance of risk management improves). Based on the obtained score, the resulting RMI (or its subindices) is subdivided into 5 levels with corresponding verbal description 1: Low, 2: Incipient, 3: Significant, 4: Outstanding and 5: Optimal The survey For the present study, a survey on landslide risk management perceptions in Norway was conducted between mid September and late October, 2015. A total of 28 responses were received. Key observations of the survey results are summarised in the following: 1. RMI at any administrative level in 2015 ranges from 30 to 42, correspondent to performance at level 3: Significant. In 2050, the RMI values increase and ranges from 46 to 66, correspondent to performance level 3: Significant to 4: Outstanding. 2. Policy indices are higher for the national level than sub-national administrative levels. 3. RMIRI at national level is the highest among all policy indices in both years, especially in 2050. 4. Within the RR and DM public policies, indicators associated with upgrading, retrofitting, and reconstruction of assets have the lowest performance levels in both years but a large number of answers of 'not relevant' and 'not able to answer'. 5. RMIFP is the lowest among all policy indices in any year, especially at the municipality and county levels. 6. The indicators considered to be most critical are indicators considered important for the landslide risk management, but within which the performance is considered as low. Technically this would be indicators with relatively low performance levels combined with high relative weights. This combination was identified for the three indicators: RI3. Hazard evaluation and mapping (relatively low rating at municipality level), RR4. Housing improvement and relocation from prone-areas, and DM5. Rehabilitation and reconstruction training. 7. At the end of the survey, the respondents were requested to identify and provide brief explanations on the factors they had predominantly considered when evaluating the change in landslide risk performance from 2015 to 2050. The most frequent considered factors in this connection were factors related to knowledge and technology, climate, risk perception, and anthropogenic activities. Conclusions Based on the survey results and the comments from respondents, it is concluded that several aspects of landslide risk management in Norway can be improved. For example, landslide hazard evaluation and mapping should be prioritised in Norway. Upgrading, retrofitting, and reconstruction of assets may also be included in the landslide risk reduction strategies in Norway. In addition, there should be more focus on inter-institutional organisation as well as allocation and use of financial resources for dealing with landslides at municipality level. Comparing the results for 2015 and 2050, the respondents show an optimistic view of the landslide risk management in the future. In spite that climate change and expanded development are considered to pose greater landslide hazards in the future, landslide risk management in Norway is perceived to improve in the long term. At all the administrative levels, the scores for the majority of indicators showed an improvement from 2015 to 2050. The reason may be related to respondents' belief that better knowledge and technology (e.g. more advanced monitoring and warning systems), increased risk awareness, and appropriate planning and mitigations in the future are powerful enough to adapt to climate change and development. The results can be used in the development of innovations in the landslide risk management in Norway and they are regarded as useful reference for the future work in Klima 2050. However, using the results, extra care should be taken as they are associated with uncertainties related to the limited number of response, subjective nature of perceptions, and limited knowledge of respondents. Further work It is our opinion that the present method can be adapted to and applied in other types of natural hazards in Norway, such as floods, also. However, generally, the questions in the survey should be further simplified or reformulated to make them more understandable. It is suggested to consult practitioners in municipalities about the appropriate terms that should be used in the questions. It is further recommended to expand the present approach of surveying perceptions on landslide risk management to obtain perceptions also from the public, since a more comprehensive evaluation of the effectiveness of landslide risk management can be obtained by comparing between perceptions by experts and the public.publishedVersio

Monitoring live fuel moisture using soil moisture and remote sensing proxies

Live fuel moisture (LFM) is an important fuel property controlling fuel ignition and fire propagation. LFM varies seasonally, and is controlled by precipitation, soil moisture, evapotranspiration, and plant physiology. LFM is typically sampled manually in the field, which leads to sparse measurements in space and time. Use of LFM proxies could reduce the need for field sampling while potentially improving spatial and temporal sampling density. This study compares soil moisture and remote sensing data to field-sampled LFM for Gambel oak (Quercus gambelii Nutt) and big sagebrush (Artemisia tridentata Nutt) in northern Utah. Bivariate linear regression models were constructed between LFM and four independent variables. Soil moisture was more strongly correlated with LFM than remote sensing measurements, and produced the lowest mean absolute error (MAE) in predicted LFM values at most of the sites. When sites were pooled, canopy water content (CWC) had stronger correlations with LFM than normalized difference vegetation index (NDVI) or normalized difference water index (NDWI). MAE values for all proxies were frequently above 20 % LFM at individual sites. Despite this relatively large error, remote sensing and soil moisture data may still be useful for improving understanding of spatial and temporal trends in LFM

Potential commercial application of a bi-layer bone-ligament regeneration scaffold to anterior cruciate ligament replacement

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Materials Science and Engineering, 2006.Includes bibliographical references (p. 71-74).A business model was created in order to explore the commercial application of a bi-layer bone-ligament scaffold to the treatment of torn anterior cruciate ligaments (ACL) requiring replacement. The two main keys in producing the bone scaffold are triple co-precipitation of type-I collagen, chodroitin-6-sulphate, and calcium phosphate minerals and the use of lyophilization to create a network where all the materials are homogeneously dispersed and present in significant amounts. This process allows the creation of a porous network whose physical characteristics, mechanical properties, and material content can all be changed to create a scaffold that closely mimics natural bone. A collagen and chondroitin-6-sulphate scaffold is used for ligament regeneration. The ACL replacement market was chosen because it is one of the most commonly surgically repaired ligaments in the body and because all of the current treatments have drawbacks.(cont.) The exercise of creating a business model made it clear that the commercial potential of starting a company that focused on marketing a direct ACL replacement scaffold would most likely not be successful mainly because surgeons would hesitate to use this product over current methods that are satisfactory and it would be difficult to separate our product from other newer methods which all boast similar advantages over current treatment options. However, the commercial potential of using the technology to create a scaffold for graft site morbidity in certain ACL replacement surgeries is large because there is no competition, and the implantation procedure for the surgeon would be simple.by Jessica C. Li.M.Eng

Human cytomegalovirus pUL79 Is an elongation factor of RNA polymerase II for viral gene transcription

In this study, we have identified a unique mechanism in which human cytomegalovirus (HCMV) protein pUL79 acts as an elongation factor to direct cellular RNA polymerase II for viral transcription during late times of infection. We and others previously reported that pUL79 and its homologues are required for viral transcript accumulation after viral DNA synthesis. We hypothesized that pUL79 represented a unique mechanism to regulate viral transcription at late times during HCMV infection. To test this hypothesis, we analyzed the proteome associated with pUL79 during virus infection by mass spectrometry. We identified both cellular transcriptional factors, including multiple RNA polymerase II (RNAP II) subunits, and novel viral transactivators, including pUL87 and pUL95, as protein binding partners of pUL79. Co-immunoprecipitation (co-IP) followed by immunoblot analysis confirmed the pUL79-RNAP II interaction, and this interaction was independent of any other viral proteins. Using a recombinant HCMV virus where pUL79 protein is conditionally regulated by a protein destabilization domain ddFKBP, we showed that this interaction did not alter the total levels of RNAP II or its recruitment to viral late promoters. Furthermore, pUL79 did not alter the phosphorylation profiles of the RNAP II C-terminal domain, which was critical for transcriptional regulation. Rather, a nuclear run-on assay indicated that, in the absence of pUL79, RNAP II failed to elongate and stalled on the viral DNA. pUL79-dependent RNAP II elongation was required for transcription from all three kinetic classes of viral genes (i.e. immediate-early, early, and late) at late times during virus infection. In contrast, host gene transcription during HCMV infection was independent of pUL79. In summary, we have identified a novel viral mechanism by which pUL79, and potentially other viral factors, regulates the rate of RNAP II transcription machinery on viral transcription during late stages of HCMV infection