A real options approach for valuating intertemporal interdependencies within a value-based IT portfolio management - A risk-return perspective

Value-based IT portfolio management requires the consideration of intertemporal interdependencies that may exist among IT projects. Therefore, several papers suggest adopting the real options approach in order to include intertemporal interdependencies within the valuation of IT projects. However, this paper shows that the standard Black-Scholes model, which is often used for valuating real options, is not appropriate to correctly account for project-specific private risks due to its restrictive assumptions. Since this can have major impacts on the value of IT projects, we develop an approach – based on the Black-Scholes model – to consider private risks properly within project valuation. A comparison of the results of the standard Black-Scholes model used today and our approach finally reveals that the neglect of private risks results in a systematic underestimation of both risk and return of IT projects, which may lead to wrong investment decisions

Nonimmunological alterations of glomerular filtration by s-PAF in the rat kidney

Nonimmunological alterations of glomerular filtration by s-PAF in the rat kidney. Rat kidneys were isolated and perfused with a cell-free perfusion buffer containing 4% albumin. Infusion of platelet activating factor (s-PAF) into the isolated perfused kidney caused a dose-dependent fall in renal vascular resistance (RVR): 12 ± 6% at 10nM s-PAF, 18 ± 3% at 100nM s-PAF and 20 ± 7% at 1 µM. s-PAF. Glomerular filtration rate fell by 32 ± 5% at 10nM, 38 ± 6% at 100nM, and 52 ± 10% at 1 µM. s-PAF (50nM) increased urinary protein excretion after 20 minutes. Because GFR fell to a greater extent than RVR, possible changes in glomerular permeability after s-PAF treatment were assessed morphologically using native ferritin. After s-PAF treatment (100nM), the number of ferritin particles/µm2 increased from 1.2 ± 0.9 (control) to 795 ± 69 in the glomerular basement membrane (GBM) and from 0.2 ± 0.06 (control) to 98 ± 29 in lamina rara externa (LRE). To quantitate changes in fixed anionic charges, polyethylenimine (PEI) was quantitated morphologically in GBM. No significant change between s-PAF treated and untreated kidneys was seen. s-PAF did not alter the sialoglycoprotein pattern in the perfused kidney as assessed by lysozyme staining. These results are in contrast to findings with s-PAF in vivo where in addition to increased glomerular permeability, a reduction of fixed anionic charges is seen. Thus, these results help to differentiate a dual mechanism of s-PAF: 1) a direct action of s-PAF on glomerular epithelial and vascular cells and, 2) an indirect action of s-PAF on glomerular structures via stimulation of release of inflammatory mediators from circulatory cells

Predictive Maintenance – Analysis of Seasonal Dependence of Vehicle Engine Faults

This paper presents methods and results for the analysis of interrelationships between the occurrence of specific engine faults according to seasons. The issue of maintenance is substantial for the automotive industry and improvements are requested due to the enhancement of profitability. Findings of this paper are based on logged-vehicle data from 760.976 vehicles provided by the company Geotab. Utilization of such data gains importance for the automotive service sector with special regard of increasing importance of predictive maintenance. The visualization of the data of three different engine faults was realized with the free graphic and statistics program “Tableau Desktop 2018.1” as well as “IBM SPSS Statistics Subscription Trial for Mac OS”. The result is that the tested interrelations are significant, leading to the conclusion that the engine faults of “vehicle battery has low voltage”, “low priority warning light on” and “general warning light on” are dependent of seasons. This finding can be used to help car manufacturers and car service providers to reduce maintenance costs. Keywords: automotive, big data, predictive maintenance, seasonal engine faults, vehicle error code

Influence of Patient-Specific Covariates on Test Validity of Two Delirium Screening Instruments in Neurocritical Care Patients (DEMON-ICU)

Background: Delirium screening instruments (DSIs) should be used to detect delirium, but they only show moderate sensitivity in patients with neurocritical illness. We explored whether, for these patients, DSI validity is impacted by patient-specific covariates. Methods: Data were prospectively collected in a single-center quality improvement project. Patients were screened for delirium once daily using the Intensive Care Delirium Screening Checklist (ICDSC) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Reference was the daily assessment using criteria from the Diagnostic and Statistical Manual, 4th Edition, Text Revision (DSM-IV-TR). In a two-step receiver operating characteristics regression analysis adjusting for repeated measurements, the impact of acute diagnosis of stroke or transient ischemic attack (TIA), neurosurgical intervention, Richmond Agitation Sedation Scale, and ventilation status on test validity was determined. Results: Of 181 patients screened, 101 went into final analysis. Delirium incidence according to DSM-IV-TR was 29.7%. For the first complete assessment series (CAM-ICU, ICDSC, and DSM-IV-TR), sensitivity for the CAM-ICU and the ICDSC was 73.3% and 66.7%, and specificity was 91.8% and 94.1%, respectively. Consideration of daily repeated measurements increased sensitivity for the CAM-ICU and ICDSC to 75.7% and 73.4%, and specificity to 97.3% and 98.9%, respectively. Receiver operating characteristics regression revealed that lower Richmond Agitation Sedation Scale levels significantly impaired validity of the ICDSC (p = 0.029) and the CAM-ICU in its severity scale version (p = 0.004). Neither acute diagnosis of stroke or TIA nor neurosurgical intervention or mechanical ventilation significantly influenced DSI validity. Conclusions: The CAM-ICU and ICDSC perform well in patients requiring neurocritical care, regardless of the presence of acute stroke, TIA, or neurosurgical interventions. Yet, even very light or moderate sedation can significantly impair DSI performance

A high‐order fully explicit flux‐form semi‐Lagrangian shallow‐water model

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106984/1/fld3887.pd

Objective tropical cyclone extratropical transition detection in high‐resolution reanalysis and climate model data

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high‐resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable‐resolution Community Atmosphere Model (CAM) at two different resolutions (ΔX∼55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, ΔX∼38 km), and the ERA‐Interim Reanalysis (ERA‐I, ΔX∼80 km). The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA‐I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High‐resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold‐core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.Key PointsAn objective detection technique for tracking tropical cyclone extratropical transition in gridded climate data is describedObjectively calculated extratropical transition climatology in high‐resolution reanalyses closely match observational studiesTropical cyclones in CAM take too long to undergo extratropical transition highlighting model biases requiring further investigationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/1/jame20355_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/2/jame20355.pd

Genomic Expansion of Magnetotactic Bacteria Reveals an Early Common Origin of Magnetotaxis with Lineage-specific Evolution

The origin and evolution of magnetoreception, which in diverse prokaryotes and protozoa is known as magnetotaxis and enables these microorganisms to detect Earth’s magnetic field for orientation and navigation, is not well understood in evolutionary biology. The only known prokaryotes capable of sensing the geomagnetic field are magnetotactic bacteria (MTB), motile microorganisms that biomineralize intracellular, membrane-bounded magnetic single-domain crystals of either magnetite (Fe3O4) or greigite (Fe3S4) called magnetosomes. Magnetosomes are responsible for magnetotaxis in MTB. Here we report the first large-scale metagenomic survey of MTB from both northern and southern hemispheres combined with 28 genomes from uncultivated MTB. These genomes expand greatly the coverage of MTB in the Proteobacteria, Nitrospirae, and Omnitrophica phyla, and provide the first genomic evidence of MTB belonging to the Zetaproteobacteria and “Candidatus Lambdaproteobacteria” classes. The gene content and organization of magnetosome gene clusters, which are physically grouped genes that encode proteins for magnetosome biosynthesis and organization, are more conserved within phylogenetically similar groups than between different taxonomic lineages. Moreover, the phylogenies of core magnetosome proteins form monophyletic clades. Together, these results suggest a common ancient origin of iron-based (Fe3O4 and Fe3S4) magnetotaxis in the domain Bacteria that underwent lineage-specific evolution, shedding new light on the origin and evolution of biomineralization and magnetotaxis, and expanding significantly the phylogenomic representation of MTB

Molecular Dissection of Mesenchymal–Epithelial Interactions in the Hair Follicle

De novo hair follicle formation in embryonic skin and new hair growth in adult skin are initiated when specialized mesenchymal dermal papilla (DP) cells send cues to multipotent epithelial stem cells. Subsequently, DP cells are enveloped by epithelial stem cell progeny and other cell types to form a niche orchestrating hair growth. Understanding the general biological principles that govern the mesenchymal–epithelial interactions within the DP niche, however, has been hampered so far by the lack of systematic approaches to dissect the complete molecular make-up of this complex tissue. Here, we take a novel multicolor labeling approach, using cell type–specific transgenic expression of red and green fluorescent proteins in combination with immunolabeling of specific antigens, to isolate pure populations of DP and four of its surrounding cell types: dermal fibroblasts, melanocytes, and two different populations of epithelial progenitors (matrix and outer root sheath cells). By defining their transcriptional profiles, we develop molecular signatures characteristic for the DP and its niche. Validating the functional importance of these signatures is a group of genes linked to hair disorders that have been largely unexplored. Additionally, the DP signature reveals novel signaling and transcription regulators that distinguish them from other cell types. The mesenchymal–epithelial signatures include key factors previously implicated in ectodermal-neural fate determination, as well as a myriad of regulators of bone morphogenetic protein signaling. These findings establish a foundation for future functional analyses of the roles of these genes in hair development. Overall, our strategy illustrates how knowledge of the genes uniquely expressed by each cell type residing in a complex niche can reveal important new insights into the biology of the tissue and its associated disease states

Lung diffusing capacity for nitric oxide and carbon monoxide in relation to morphological changes as assessed by computed tomography in patients with cystic fibrosis

Background Due to large-scale destruction, changes in membrane diffusion (Dm) may occur in cystic fibrosis (CF), in correspondence to alterations observed by computed tomography (CT). Dm can be easily quantified via the diffusing capacity for nitric oxide (DLNO), as opposed to the conventional diffusing capacity for carbon monoxide (DLCO). We thus studied the relationship between DLNO as well as DLCO and a CF-specific CT score in patients with stable CF. Methods Simultaneous single-breath determinations of DLNO and DLCO were performed in 21 CF patients (mean ± SD age 35 ± 9 y, FEV1 66 ± 28%pred). Patients also underwent spirometry and bodyplethysmography. CT scans were evaluated via the Brody score and rank correlations (rS) with z-scores of functional measures were computed. Results CT scores correlated best with DLNO (rS = -0.83; p < 0.001). Scores were also related to the volume-specific NO transfer coefficient (KNO; rS = -0.63; p < 0.01) and to DLCO (rS = -0.79; p < 0.001) but not KCO. Z-scores for DLNO were significantly lower than for DLCO (p < 0.001). Correlations with spirometric (e.g., FEV1, IVC) or bodyplethysmographic (e.g., SRaw, RV/TLC) indices were weaker than for DLNO or DLCO but most of them were also significant (p < 0.05 each). Conclusion In this cross sectional study in patients with CF, DLNO and DLCO reflected CT-morphological alterations of the lung better than other measures. Thus the combined diffusing capacity for NO and CO may play a future role for the non-invasive, functional assessment of structural alterations of the lung in CF