Making a financial time machine:a multitouch application to enable interactive 3-D visualization of distant savings goals

Financial planning and decision making for the general public continues to vex and perplex in equal measure. Whilst the tools presented by a typical desktop computer should make the task easier, the recent financial crisis confirms the increasing difficulty that people have in calculating the benefits of deferring consumption for future gains (i.e. Saving). We present an interactive concept demonstration for Microsoft SurfaceTM that tackles two of the key barriers to saving decision making. Firstly we show an interface that avoid the laborious writing down or inputting of data and instead embodies the cognitive decision of allocation of resources in a physical gesture based interface, where the scale of the investment or expenditure correlates with the scale of the gesture. Second we show how a fast-forward based animation can demonstrate the impact of small increments in savings to a long term savings goal in a strategy game-based, interactive format. The platform uses custom software (XNATM format) as opposed to the more usual WPFTM format found on Surface applications. This enables dynamic 3-D graphical icons to be used to maximize the interactive appeal of the interface. Demonstration and test trial feedback indicates that this platform can be adapted to suit the narrative of individual purchasing decisions to inform educate diverse user groups about the long term consequences of small financial decisions

U.S. Agricultural Policy Effectiveness: An Analysis of Income and Capital Gain Returns Impacts

This paper examines the effects of agricultural policy upon the first three moments (mean, variance, and skewness) of aggregate farm income distributions. For the income variables examined, the program period distributions were positively skewed relative to the nonprogram period. However, it appears that the significant impact of the programs on risk reduction encourages the asset and product markets to shift the distribution of total returns toward asset appreciation rather than income enhancement

Hydrator Therapies for Chronic Bronchitis. Lessons from Cystic Fibrosis

Patients with the chronic bronchitis form of chronic obstructive pulmonary disease and cystic fibrosis share similar clinical features, including mucus obstruction of airways and the development of chronic/recurrent airways infections that often manifest as disease exacerbations. There is growing evidence that these diseases may have parallels in disease pathogenesis as well, including cystic fibrosis transmembrane conductance regulator dysfunction, mucus dehydration, and defective mucociliary clearance. As progress is made in the development of therapies that target the basic defects that lead to cystic fibrosis lung disease, it is possible that similar approaches could also benefit patients with chronic bronchitis. A deeper understanding of how tobacco smoke and other triggers of chronic bronchitis actually lead to disease, and exploration of the concept that therapies that restore cystic fibrosis transmembrane conductance regulator function, mucus hydration, and/or mucociliary clearance may benefit patients with chronic bronchitis, hold the prospect of significant progress in treating this prevalent disease

From Sensors to Knowledge: The Challenge of Training the Next Generation of Data Analysts

With the advent of commercial-off-the-shelf sensors for use in a variety of applications, integration with analytical software tools, and expansion of available archived datasets, there is a critical need to address the problem of transforming resultant data into comprehensible, actionable information for decision-makers through rigorous analysis. In previous research the participating authors have emphasized that users are often faced with the situation in which they are “drowning in a sea of data” but still “thirsting for knowledge”. The availability of analysis software, tools, and techniques provide opportunities for information collection of ever increasing complexity, but the need for the training of analysts to employ appropriate tools and processes to ensure accurate and applicable results has not been addressed. The purpose of this paper is to discuss the challenges and opportunities facing the training of effective analysts capable of handling a wide-range of data types in this era of dynamic tools and techniques

The Psychogeriatric Assessment Scales: a multidimensional alternative to categorical diagnoses of dementia and depression in the elderly

The Psychogeriatric Assessment Scales (PAS) provide an assessment of the clinical changes seen in dementia and depression. Principal components analysis and latent trait analysis were used to develop a set of scales to summarize these clinical changes. There are three scales derived from an interview with the subject (Cognitive Impairment, Depression, Stroke) and three from an interview with an informant (Cognitive Decline, Behaviour Change, Stroke). Results are reported on the reliability and validity of these scales using data from clinical samples in Sydney and Geneva and a population sample from Canberra. The scales were found to have excellent validity when judged against clinical diagnoses of dementia and depression and could distinguish Alzheimer's from vascular dementia. Cut-off points were developed to indicate correspondence between scale scores and clinical diagnoses. Percentile rank norms were developed from the Canberra population sample. The PAS is easy to administer and score and can be used by lay interviewers after training. It is intended for application both in research and in services for the elderl

Mining Public Domain Data to Develop Selective DYRK1A Inhibitors

Kinases represent one of the most intensively pursued groups of targets in modern-day drug discovery. Often it is desirable to achieve selective inhibition of the kinase of interest over the remaining ∼500 kinases in the human kinome. This is especially true when inhibitors are intended to be used to study the biology of the target of interest. We present a pipeline of open-source software that analyzes public domain data to repurpose compounds that have been used in previous kinase inhibitor development projects. We define the dual-specificity tyrosine-regulated kinase 1A (DYRK1A) as the kinase of interest, and by addition of a single methyl group to the chosen starting point we remove glycogen synthase kinase β (GSK3β) and cyclin-dependent kinase (CDK) inhibition. Thus, in an efficient manner we repurpose a GSK3β/CDK chemotype to deliver 8b, a highly selective DYRK1A inhibitor

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy.

Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization