Economic Value Added and Small Businesses

Economic Value Added (EVA), a tool for creating wealth, is a leading idea in corporate finance today. Highly regarded companies like Coca-Cola and CSX have seen their market value soar since adopting EVA. The concept is straightforward; value is created when earnings exceed the cost of invested capital. Thus, EVA is rapidly gaining acceptance among large, publicly-traded corporations. However, EVA can be applied effectively to create value in small, privately-held firms, too. This article illustrates EVA's application in small, privately-held firms, examines EVA "s strengths and weaknesses, discusses ways to overcome those weaknesses, and describes specific operating, investing and financing actions small business managers can take to create wealth

Performance of PCA3 and TMPRSS2:ERG urinary biomarkers in prediction of biopsy outcome in the Canary Prostate Active Surveillance Study (PASS).

BackgroundFor men on active surveillance for prostate cancer, biomarkers may improve prediction of reclassification to higher grade or volume cancer. This study examined the association of urinary PCA3 and TMPRSS2:ERG (T2:ERG) with biopsy-based reclassification.MethodsUrine was collected at baseline, 6, 12, and 24 months in the multi-institutional Canary Prostate Active Surveillance Study (PASS), and PCA3 and T2:ERG levels were quantitated. Reclassification was an increase in Gleason score or ratio of biopsy cores with cancer to ≥34%. The association of biomarker scores, adjusted for common clinical variables, with short- and long-term reclassification was evaluated. Discriminatory capacity of models with clinical variables alone or with biomarkers was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSeven hundred and eighty-two men contributed 2069 urine specimens. After adjusting for PSA, prostate size, and ratio of biopsy cores with cancer, PCA3 but not T2:ERG was associated with short-term reclassification at the first surveillance biopsy (OR = 1.3; 95% CI 1.0-1.7, p = 0.02). The addition of PCA3 to a model with clinical variables improved area under the curve from 0.743 to 0.753 and increased net benefit minimally. After adjusting for clinical variables, neither marker nor marker kinetics was associated with time to reclassification in subsequent biopsies.ConclusionsPCA3 but not T2:ERG was associated with cancer reclassification in the first surveillance biopsy but has negligible improvement over clinical variables alone in ROC or DCA analyses. Neither marker was associated with reclassification in subsequent biopsies

Assessing the Health of Richibucto Estuary with the Latent Health Factor Index

The ability to quantitatively assess the health of an ecosystem is often of great interest to those tasked with monitoring and conserving ecosystems. For decades, research in this area has relied upon multimetric indices of various forms. Although indices may be numbers, many are constructed based on procedures that are highly qualitative in nature, thus limiting the quantitative rigour of the practical interpretations made from these indices. The statistical modelling approach to construct the latent health factor index (LHFI) was recently developed to express ecological data, collected to construct conventional multimetric health indices, in a rigorous quantitative model that integrates qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modelling approach allows (a) statistical inference of health for observed sites and (b) prediction of health for unobserved sites, all accompanied by formal uncertainty statements. Thus far, the LHFI approach has been demonstrated and validated on freshwater ecosystems. The goal of this paper is to adapt this approach to modelling estuarine ecosystem health, particularly that of the previously unassessed system in Richibucto in New Brunswick, Canada. Field data correspond to biotic health metrics that constitute the AZTI marine biotic index (AMBI) and abiotic predictors preconceived to influence biota. We also briefly discuss related LHFI research involving additional metrics that form the infaunal trophic index (ITI). Our paper is the first to construct a scientifically sensible model to rigorously identify the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content --- all regarded a priori as qualitatively important abiotic drivers --- towards site health in the Richibucto ecosystem.Comment: On 2013-05-01, a revised version of this article was accepted for publication in PLoS One. See Journal reference and DOI belo

H0LiCOW X: Spectroscopic/imaging survey and galaxy-group identification around the strong gravitational lens system WFI2033-4723

Galaxies and galaxy groups located along the line of sight towards gravitationally lensed quasars produce high-order perturbations of the gravitational potential at the lens position. When these perturbation are too large, they can induce a systematic error on $H_0$ of a few-percent if the lens system is used for cosmological inference and the perturbers are not explicitly accounted for in the lens model. In this work, we present a detailed characterization of the environment of the lens system WFI2033-4723 ($z_{\rm src} = 1.662$, $z_{\rm lens}$ = 0.6575), one of the core targets of the H0LICOW project for which we present cosmological inferences in a companion paper (Rusu et al. 2019). We use the Gemini and ESO-Very Large telescopes to measure the spectroscopic redshifts of the brightest galaxies towards the lens, and use the ESO-MUSE integral field spectrograph to measure the velocity-dispersion of the lens ($\sigma_{\rm {los}}= 250^{+15}_{-21}$ km/s) and of several nearby galaxies. In addition, we measure photometric redshifts and stellar masses of all galaxies down to $i < 23$ mag, mainly based on Dark Energy Survey imaging (DR1). Our new catalog, complemented with literature data, more than doubles the number of known galaxy spectroscopic redshifts in the direct vicinity of the lens, expanding to 116 (64) the number of spectroscopic redshifts for galaxies separated by less than 3 arcmin (2 arcmin) from the lens. Using the flexion-shift as a measure of the amplitude of the gravitational perturbation, we identify 2 galaxy groups and 3 galaxies that require specific attention in the lens models. The ESO MUSE data enable us to measure the velocity-dispersions of three of these galaxies. These results are essential for the cosmological inference analysis presented in Rusu et al. (2019).Comment: Matches the version accepted for publication by MNRAS. Note that this paper previously appeared as H0LICOW X

COSMOGRAIL XVI: Time delays for the quadruply imaged quasar DES J0408-5354 with high-cadence photometric monitoring

We present time-delay measurements for the new quadruply imaged quasar DES J0408-5354, the first quadruply imaged quasar found in the Dark Energy Survey (DES). Our result is made possible by implementing a new observational strategy using almost daily observations with the MPIA 2.2m telescope at La Silla observatory and deep exposures reaching a signal-to-noise ratio of about 1000 per quasar image. This data quality allows us to catch small photometric variations (a few mmag rms) of the quasar, acting on temporal scales much shorter than microlensing, hence making the time delay measurement very robust against microlensing. In only 7 months we measure very accurately one of the time delays in DES J0408-5354: Dt(AB) = -112.1 +- 2.1 days (1.8%) using only the MPIA 2.2m data. In combination with data taken with the 1.2m Euler Swiss telescope, we also measure two delays involving the D component of the system Dt(AD) = -155.5 +- 12.8 days (8.2%) and Dt(BD) = -42.4 +- 17.6 days (41%), where all the error bars include systematics. Turning these time delays into cosmological constraints will require deep HST imaging or ground-based Adaptive Optics (AO), and information on the velocity field of the lensing galaxy.Comment: 9 pages, 5 figures, accepted for publication in Astronomy & Astrophysic

Hidden clusters: the articulation of agglomeration in City Regions

For many years, local economic development has been driven by the desire to maintain, attract and nurture clusters of economic activity in targeted industrial sectors. However, where clusters are not conventionally sector-based, public policy needs to develop alternative approaches to leverage the economic benefits and realise competitive advantage. Drawing on a study of the Sheffield City Region (SCR), the paper explores the challenge of leveraging ‘hidden’ cross-sectoral clusters, which do not fit dominant discourses of agglomeration-led growth. We posit that it is the cross-sectoral connections and networks in the SCR which represent its key strength, yet these are only partially reflected by current place marketing and policy considerations, and, in many ways, are overlooked and thus remain ‘hidden’. The paper argues that the competitive advantage of the SCR is undermined when it characterises clusters in terms of industrial sectors, and instead needs to articulate its strengths as a strategically important industrial centre. The paper concludes by drawing out a number of implications for academic theory and policy development

Astrometric calibration and performance of the Dark Energy Camera

We characterize the ability of the Dark Energy Camera (DECam) to perform relative astrometry across its 500~Mpix, 3 deg^2 science field of view, and across 4 years of operation. This is done using internal comparisons of ~4x10^7 measurements of high-S/N stellar images obtained in repeat visits to fields of moderate stellar density, with the telescope dithered to move the sources around the array. An empirical astrometric model includes terms for: optical distortions; stray electric fields in the CCD detectors; chromatic terms in the instrumental and atmospheric optics; shifts in CCD relative positions of up to ~10 um when the DECam temperature cycles; and low-order distortions to each exposure from changes in atmospheric refraction and telescope alignment. Errors in this astrometric model are dominated by stochastic variations with typical amplitudes of 10-30 mas (in a 30 s exposure) and 5-10 arcmin coherence length, plausibly attributed to Kolmogorov-spectrum atmospheric turbulence. The size of these atmospheric distortions is not closely related to the seeing. Given an astrometric reference catalog at density ~0.7 arcmin^{-2}, e.g. from Gaia, the typical atmospheric distortions can be interpolated to 7 mas RMS accuracy (for 30 s exposures) with 1 arcmin coherence length for residual errors. Remaining detectable error contributors are 2-4 mas RMS from unmodelled stray electric fields in the devices, and another 2-4 mas RMS from focal plane shifts between camera thermal cycles. Thus the astrometric solution for a single DECam exposure is accurate to 3-6 mas (0.02 pixels, or 300 nm) on the focal plane, plus the stochastic atmospheric distortion.Comment: Submitted to PAS