Predicting Delivery Time of Components in a Supply Chain

Generally, the present disclosure is directed to predicting a delivery time of components in a supply chain. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict a delivery time of a component based on enterprise data relating to the component

Fostering efficiency of computational resource allocation - Integrating information services into markets

The application of market mechanisms for the allocation of computing services is a demanding task, which requires bridging economic and associated technical challenges. Even if the market-based approach promises an efficient allocation of computing services, the wide heterogeneity of consumer requirements and the diversity of computational services on provider side are challenging the processes of finding, allocating, and using an appropriate service in an autonomous way. The focus of the most papers is mainly devoted to the optimization embedded in the allocation process itself. However, we think that the optimization process starts much earlier and contains the information gathering until the final market-based resource allocations. In this paper we introduce an integrated framework for market-based allocation of computing services, integrating information retrieval of market information, prediction models, bidding strategies and marked mechanisms. As proof-of-concept, we implemented a first prototype of the framework. Furthermore, we propose a methodology for evaluating strategic behavior in market mechanisms with bidding strategies using market information and statistical prediction techniques. First simulation results show strategic behavior in selected market mechanisms by applying the proposed techniques

Shocks to Product Networks and Post-Earnings Announcement Drift

This paper examines whether shocks to less visible product market peers are an important determinant of industry level post-earnings announcement drift (IPEAD) (Ayers and Freeman 1997; Hui et al. 2016). On the real-side, we find that a focal firm’s earnings are persistently related to the earnings surprises of its peers. On the financial-side, IPEAD arises only when these peers are less visible and when shocks are driven by persistent supply-side shocks to expenses, and not by demand-side shocks to sales. Text-based measures of disclosure opacity show that IPEAD is also stronger when firms provide less informative 10-K disclosures regarding their expenses. Collectively, our results suggest that inattention to less visible peers and a poor informational environment surrounding supply-side shocks are likely channels that generate IPEAD. IPEAD returns are economically large in subsamples motivated by this explanation

On the fit and forecasting performance of New-Keynesian models

The paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR), and then systematically relax the implied cross-equation restrictions. Let ? denote the extent to which the restrictions are being relaxed. We document how the in- and out-of sample fit of the resulting specification (DSGE-VAR) changes as a function of ?. Furthermore, we learn about the precise nature of the misspecification by comparing the DSGE model’s impulse responses to structural shocks with those of the best-fitting DSGE-VAR. We find that the degree of misspecification in large-scale DSGE models is no longer so large to prevent their use in day-to-day policy analysis, yet it is not small enough that it cannot be ignored. JEL Classification: C11, C32, C53Bayesian Analysis, DSGE Models, model evaluation, vector autoregressions

Transcranial direct current stimulation improves the QT variability index and autonomic cardiac control in healthy subjects older than 60 years

Background: Noninvasive brain stimulation technique is an interesting tool to investigate the causal relation between cortical functioning and autonomic nervous system (ANS) responses. Objective: The objective of this report is to evaluate whether anodal transcranial direct current stimulation (tDCS) over the temporal cortex influences short-period temporal ventricular repolarization dispersion and cardiovascular ANS control in elderly subjects. Subjects and methods: In 50 healthy subjects (29 subjects younger than 60 years and 21 subjects older than 60 years) matched for gender, short-period RR and systolic blood pressure spectral variability, QT variability index (QTVI), and noninvasive hemodynamic data were obtained during anodal tDCS or sham stimulation. Results: In the older group, the QTVI, low-frequency (LF) power expressed in normalized units, the ratio between LF and high-frequency (HF) power, and systemic peripheral resistances decreased, whereas HF power expressed in normalized units and α HF power increased during the active compared to the sham condition (P,0.05). Conclusion: In healthy subjects older than 60 years, tDCS elicits cardiovascular and autonomic changes. Particularly, it improves temporal ventricular repolarization dispersion, reduces sinus sympathetic activity and systemic peripheral resistance, and increases vagal sinus activity and baroreflex sensitivity

The effect of the Sarbanes-Oxley Act on industrial innovation – evidence from patenting of stem cell technologies

This paper assesses how financial regulation, in the form of the Sarbanes-Oxley Act (SOX), affects industrial innovation. We describe the decision faced by an investor considering an innovative project before, at the time of, and subsequent to SOX. SOX is shown to create a real option value for investment delay through its short term hike and medium term diminution in uncertainty, and we calculate how implementation parameters impact on delay and subsequent innovation. To test our model’s implications, we examine patenting in stem cell technologies from 2001 to 2009, introducing two methods of endogenously detecting changes in patenting rates. We find a post-SOX dip in patenting consistent with our model, and no long term effect on innovation. We reject US government funding cuts to human embryonic stem cell research as a cause of the observed behaviour, as well as five other sets of explanations

Developmental Trajectories of Alcohol Use and Alcohol Use Disorder

Alcohol use (AU) and alcohol use disorder (AUD) are leading causes of morbidity, premature death, and economic burden. They are also associated with high levels of disability and many other negative outcomes. Twin and family studies have consistently shown that AU and AUD are complex traits influenced by both genetic and environmental factors. Although much has been learned about the genetic and environmental etiology of AU and AUD, significant gaps remain. These include the need for a more comprehensive understanding of the roles of risk and protective factors, and the nature of developmental trajectories underpinning the progression from AU to AUD. The aims of this dissertation are: (1) to examine the roles of resilience and personality disorders in the etiology of AU and AUD; (2) to investigate the nature of longitudinal changes in genetic and environmental risk factors responsible for individual differences in AU; and (3) to determine the moderating roles of key environmental risk factors on the impact of aggregate molecular, or polygenic, risk for AU during adolescence. Using both biometrical behavioral genetic and molecular genetic methodologies, five key findings were observed: (1) Resilience is strongly associated with a reduction in risk for AUD, and this relationship appears to be the result of overlapping genetic and shared environmental influences; (2) Borderline and antisocial personality disorders are the strongest and most stable personality pathology predictors of the phenotypic and genotypic liability to AU and AUD across time; (3) Genetic influences on the development of AUD from early adulthood to mid-adulthood are dynamic, whereby two sets of genetic risk factors contribute to AUD risk; (4) The specific genetic influences on AU follow an unfolding pattern of growth over time, whereas unique environmental risk factors are consistent with an accumulation of environmental impacts and risks across time; and (5) High peer group deviance and low parental monitoring are associated with increased AU, while early parental monitoring moderates the polygenic risk for AU at age 20. The implications of these results with regard to prevention and intervention efforts are discussed