Evaluating cross-organizational ERP requirements engineering practices: a focus group study

This focus group study presents our first validation of practices for engineering the coordination requirements in cross-organizational Enterprise Resource Planning (ERP) projects. The study evaluates 13 practices addressing a variety of coordination aspects crucial to ERP projects. These practices are results in previously published research publications by the first author. The practices are formulated in response to practitioners' needs at ERP adopting organizations. The proposed practices have now reached the stage where we need some independent feedback as to the extent to which they fit the realities of practitioners. We perform this validation by means of a qualitative research approach, namely the focus group method. Current software engineering literature provides few examples of using focus groups in the evaluation of good software development practices. Because of this, providing reflections on our focus-group-based validation experiences will be of value to both the research community and practitioners

Technical Progress and Early Retirement

This paper claims that technical progress induces early retirement of older workers. Technical progress erodes technology specific human capital. Since older workers have shorter career horizons, there is less incentive for them or for their employers to invest in learning how to use the new technologies. Consequently, they are more likely to stop working. We call this effect the erosion effect. Since technical progress also raises wages in the economy as a whole and since technical progress is positively correlated across sectors, this presents an opposite effect of technical progress, which we call the wage effect. Using individual and sector data, we separate the two effects and find support for our theory. JEL Specification: J24, J26, O15, O33Early Retirement, Technical Change, Human Capital, Labor For

The human ARF tumor suppressor senses blastema activity and suppresses epimorphic tissue regeneration.

The control of proliferation and differentiation by tumor suppressor genes suggests that evolution of divergent tumor suppressor repertoires could influence species regenerative capacity. To directly test that premise, we humanized the zebrafish p53 pathway by introducing regulatory and coding sequences of the human tumor suppressor ARF into the zebrafish genome. ARF was dormant during development, in uninjured adult fins, and during wound healing, but was highly expressed in the blastema during epimorphic fin regeneration after amputation. Regenerative, but not developmental signals resulted in binding of zebrafish E2f to the human ARF promoter and activated conserved ARF-dependent Tp53 functions. The context-dependent activation of ARF did not affect growth and development but inhibited regeneration, an unexpected distinct tumor suppressor response to regenerative versus developmental environments. The antagonistic pleiotropic characteristics of ARF as both tumor and regeneration suppressor imply that inducing epimorphic regeneration clinically would require modulation of ARF -p53 axis activation

Meta-analysis of massively parallel reporter assays enables prediction of regulatory function across cell types.

Deciphering the potential of noncoding loci to influence gene regulation has been the subject of intense research, with important implications in understanding genetic underpinnings of human diseases. Massively parallel reporter assays (MPRAs) can measure regulatory activity of thousands of DNA sequences and their variants in a single experiment. With increasing number of publically available MPRA data sets, one can now develop data-driven models which, given a DNA sequence, predict its regulatory activity. Here, we performed a comprehensive meta-analysis of several MPRA data sets in a variety of cellular contexts. We first applied an ensemble of methods to predict MPRA output in each context and observed that the most predictive features are consistent across data sets. We then demonstrate that predictive models trained in one cellular context can be used to predict MPRA output in another, with loss of accuracy attributed to cell-type-specific features. Finally, we show that our approach achieves top performance in the Fifth Critical Assessment of Genome Interpretation "Regulation Saturation" Challenge for predicting effects of single-nucleotide variants. Overall, our analysis provides insights into how MPRA data can be leveraged to highlight functional regulatory regions throughout the genome and can guide effective design of future experiments by better prioritizing regions of interest

Minor Loops in Major Folds: Enhancer-Promoter Looping, Chromatin Restructuring, and Their Association with Transcriptional Regulation and Disease.

The organization and folding of chromatin within the nucleus can determine the outcome of gene expression. Recent technological advancements have enabled us to study chromatin interactions in a genome-wide manner at high resolution. These studies have increased our understanding of the hierarchy and dynamics of chromatin domains that facilitate cognate enhancer-promoter looping, defining the transcriptional program of different cell types. In this review, we focus on vertebrate chromatin long-range interactions as they relate to transcriptional regulation. In addition, we describe how the alteration of boundaries that mark discrete regions in the genome with high interaction frequencies within them, called topological associated domains (TADs), could lead to various phenotypes, including human diseases, which we term as "TADopathies.

The Value of Knowing that You Do Not Know

The value of knowing about data availability and system accessibility is analyzed through theoretical models of Information Economics. When a user places an inquiry for information, it is important for the user to learn whether the system is not accessible or the data is not available, rather than not have any response. In reality, various outcomes can be provided by the system: nothing will be displayed to the user (e.g., a traffic light that does not operate, a browser that keeps browsing, a telephone that does not answer); a random noise will be displayed (e.g., a traffic light that displays random signals, a browser that provides disorderly results, an automatic voice message that does not clarify the situation); a special signal indicating that the system is not operating (e.g., a blinking amber indicating that the traffic light is down, a browser responding that the site is unavailable, a voice message regretting to tell that the service is not available). This article develops a model to assess the value of the information for the user in such situations by employing the information structure model prevailing in Information Economics. Examples related to data accessibility in centralized and in distributed systems are provided for illustration

Are There Returns to the Wages of Young Men from Working While in School?

This paper examines the impacts of work experience acquired while youth were in high school (and college) on young men's wage rates during the 1980s and 1990s. Previous studies have found evidence of sizeable and persistent rates of return to working while enrolled in school, especially high school, on subsequent wage growth. Such findings may represent causal effects of having acquired work experience while still enrolled in school, but they may also be the result of failure to fully account for individual differences in young adults' capacities to acquire such skills and be productive in the work force later in life. We re-examine the robustness of previous attempts to control for unobserved heterogeneity and selectivity. We explore more general methods for dealing with dynamic forms of selection by explicitly modeling the educational and work choices of young men from age 13 through their late twenties. Using data on young men from the 1979 National Longitudinal Survey of Youth (NLSY79), we find that the estimated returns to working while in high school or college are dramatically diminished in magnitude and statistical significance when one uses these dynamic selection methods. As such, our results indicate a decided lack of robustness to the inference about the effects of working while in school that has been drawn from previous work.

Technical Progress and Early Retirement

This paper claims that technical progress induces early retirement of older workers. It presents a model where human capital is technology specific, so that technical progress erodes some existing human capital. This affects mostly older workers, who have a smaller incentive to learn the new technology, since their career horizon is shorter. Hence, they tend to work less. We find support to this erosion effect in HRS data, which shows that retirement and unemployment of older workers are positively related to technical progress in their sectors. Unlike the effect across sectors, the model is ambiguous about the aggregate effect of technical progress on labor supply of older workers. While in sectors with many innovations it falls due to the erosion effect, in other sectors it increases due to higher wages. To examine which effect dominates we run a time series test using US data and find that the rate of average technical progress reduces aggregate labor force participation by the old. Namely, the erosion effect dominates.This paper claims that technical progress induces early retirement of older workers. It presents a model where human capital is technology specific, so that technical progress erodes some existing human capital. This affects mostly older workers, who have a smaller incentive to learn the new technology, since their career horizon is shorter. Hence, they tend to work less. We find support to this erosion effect in HRS data, which shows that retirement and unemployment of older workers are positively related to technical progress in their sectors. Unlike the effect across sectors, the model is ambiguous about the aggregate effect of technical progress on labor supply of older workers. While in sectors with many innovations it falls due to the erosion effect, in other sectors it increases due to higher wages. To examine which effect dominates we run a time series test using US data and find that the rate of average technical progress reduces aggregate labor force participation by the old. Namely, the erosion effect dominates.Non-Refereed Working Papers / of national relevance onl

How do marital status, wage rates, and work commitment interact?

How marriage interacts with men's earnings is an important public policy issue, given debates over programs to directly encourage healthy marriages. This paper generates new findings about the earnings-marriage relationship by estimating the linkages between marriage, work commitment, and wage rates. Unlike other studies of the marital wage premium for men, we examine how marital status and marital transitions affect hours worked as well as wage rates, take account of the feedback effect on wage rates and earnings associated with marriage effects on hours worked, estimate marriage effects on black and low skill men, control for several dimensions of selection, and follow men from age 17-40. We find that marriage increases men's earnings by about 20 percent and also find a rise in wage rates and hours worked increases marriage. These findings suggest that both marriage-enhancing and earnings-enhancing policies can set off a virtuous circle, in which marriage and earnings reinforce each other over time. Unmarried men who appear unable to support a family because of low current earnings are likely to become more adequate breadwinners once they marry. Thus, if proposed programs are able to increase the utility from and appreciation of marriage, they are likely to generate earnings gains for men as an important side effect

MPRAnalyze: statistical framework for massively parallel reporter assays.

Massively parallel reporter assays (MPRAs) can measure the regulatory function of thousands of DNA sequences in a single experiment. Despite growing popularity, MPRA studies are limited by a lack of a unified framework for analyzing the resulting data. Here we present MPRAnalyze: a statistical framework for analyzing MPRA count data. Our model leverages the unique structure of MPRA data to quantify the function of regulatory sequences, compare sequences' activity across different conditions, and provide necessary flexibility in an evolving field. We demonstrate the accuracy and applicability of MPRAnalyze on simulated and published data and compare it with existing methods