Complete LibTech 2013 Print Program

PDF of the complete print program from the 2013 Library Technology Conferenc

Bridge Deck Runoff: Water Quality Analysis and BMP Effectiveness

INE/AUTC 10.0

Addressing business agility challenges with enterprise systems

It is clear that systems agility (i.e., having a responsive IT infrastructure that can be changed quickly to meet changing business needs) has become a critical component of organizational agility. However, skeptics continue to suggest that, despite the benefits enterprise system packages provide, they are constraining choices for firms faced with agility challenges. The reason for this skepticism is that the tight integration between different parts of the business that enables many enterprise systems\u27 benefits also increases the systems\u27 complexity, and this increased complexity, say the skeptics, increases the difficulty of changing systems when business needs change. These persistent concerns motivated us to conduct a series of interviews with business and IT managers in 15 firms to identify how they addressed, in total, 57 different business agility challenges. Our analysis suggests that when the challenges involved an enterprise system, firms were able to address a high percentage of their challenges with four options that avoid the difficulties associated with changing the complex core system: capabilities already built-in to the package but not previously used, leveraging globally consistent integrated data already available, using add-on systems available on the market that easily interfaced with the existing enterprise system, and vendor provided patches that automatically updated the code. These findings have important implications for organizations with and without enterprise system architectures

Estimating survival in patients with gastrointestinal cancers and brain metastases: An update of the graded prognostic assessment for gastrointestinal cancers (GI-GPA).

BackgroundPatients with gastrointestinal cancers and brain metastases (BM) represent a unique and heterogeneous population. Our group previously published the Diagnosis-Specific Graded Prognostic Assessment (DS-GPA) for patients with GI cancers (GI-GPA) (1985-2007, n = 209). The purpose of this study is to update the GI-GPA based on a larger contemporary database.MethodsAn IRB-approved consortium database analysis was performed using a multi-institutional (18), multi-national (3) cohort of 792 patients with gastrointestinal (GI) cancers, with newly-diagnosed BM diagnosed between 1/1/2006 and 12/31/2017. Survival was measured from date of first treatment for BM. Multiple Cox regression was used to select and weight prognostic factors in proportion to their hazard ratios. These factors were incorporated into the updated GI-GPA.ResultsMedian survival (MS) varied widely by primary site and other prognostic factors. Four significant factors (KPS, age, extracranial metastases and number of BM) were used to formulate the updated GI-GPA. Overall MS for this cohort remains poor; 8 months. MS by GPA was 3, 7, 11 and 17 months for GPA 0-1, 1.5-2, 2.5-3.0 and 3.5-4.0, respectively. >30% present in the worst prognostic group (GI-GPA of ≤1.0).ConclusionsBrain metastases are not uncommon in GI cancer patients and MS varies widely among them. This updated GI-GPA index improves our ability to estimate survival for these patients and will be useful for therapy selection, end-of-life decision-making and stratification for future clinical trials. A user-friendly, free, on-line app to calculate the GPA score and estimate survival for an individual patient is available at brainmetgpa.com

Application of Species Distribution Modeling for Avian Influenza surveillance in the United States considering the North America Migratory Flyways.

Highly Pathogenic Avian Influenza (HPAI) has recently (2014-2015) re-emerged in the United States (US) causing the largest outbreak in US history with 232 outbreaks and an estimated economic impact of $950 million. This study proposes to use suitability maps for Low Pathogenic Avian Influenza (LPAI) to identify areas at high risk for HPAI outbreaks. LPAI suitability maps were based on wild bird demographics, LPAI surveillance, and poultry density in combination with environmental, climatic, and socio-economic risk factors. Species distribution modeling was used to produce high-resolution (cell size: 500m x 500m) maps for Avian Influenza (AI) suitability in each of the four North American migratory flyways (NAMF). Results reveal that AI suitability is heterogeneously distributed throughout the US with higher suitability in specific zones of the Midwest and coastal areas. The resultant suitability maps adequately predicted most of the HPAI outbreak areas during the 2014-2015 epidemic in the US (i.e. 89% of HPAI outbreaks were located in areas identified as highly suitable for LPAI). Results are potentially useful for poultry producers and stakeholders in designing risk-based surveillance, outreach and intervention strategies to better prevent and control future HPAI outbreaks in the US