On What Counts as a Translation

In this article, instead of taking a particular method as translation, we ask: what does one expect to do with a translation? The answer to this question will reveal, though, that none of the first order methods are capable of fully represent the required transference of ontological commitments. Lastly, we will show that this view on translation enlarge considerably the scope of translatable, and, therefore, ontologically comparable theories

Regulating Air Toxics in Rhode Island: Policy vs. Technical Decisions

Dr. Roqu6 recounts her work as a doctoral candidate at Brown in developing standards for the regulation of airborne carcinogens. Based in part on this experience, she argues that care needs be taken lest those who regulate Risk bury key policy decisions within a mass of often irrelevant technical details

The scattering of charged particles in a weakly unstable plasma

Mean-square deflectron of suprathermal test particles from weakly unstable electron plasm

Does linearity in the dynamics of inflation gap and unemployment rate matter?

This paper tests the hypothesis of linearity against a specific form of nonlinearity in the Data Generating Process (DGP) of the unemployment rate and the difference between the inflation rate (CPI and CPIX1) and the inflation target. The test is performed over each variable using time series models. Under the null hypothesis, the DGP has a linear representation (AR model) and under the alternative, a non linear specification (SETAR model). Unlike traditional ARIMA models, these models allow the endogenous variable to have different regimes across time. The main results are: it is not possible to reject linearity in the deviation of inflation from the inflation target. During the last twenty years, inflation has converged smoothly to the target without any regime switching. Finally, strong evidence is found against linearity in the unemployment rate. On the contrary, it fluctuates with high probability between states or regimes through time.

Influence of Portfolio Management in Decision-Making

Purpose: Today’s manufacturing facilities are challenged by highly customized products and just in time manufacturing and delivery of these products. In this study, a batch scheduling problem has been addressed to enable on-time completion of customer orders in a lean manufacturing environment. The problem is optimizing the partitioning of product components into batches and scheduling of the resulting batches where each customer order is received as a set of products made of various components. Design/methodology/approach: Three different mathematical models for minimization of total earliness and tardiness of customer orders are developed to provide on-time completion of customer orders and also, to avoid excess final product inventory. The first model is a non-linear integer programming model whereas the second is a linearized version of the first. Finally, to solve larger sized instances of the problem, an alternative linear integer model is presented. Findings: Computational study using a suit set of test instances showed that the alternative linear integer model is able to solve all test instances in varying sizes within quite shorter computer times compared to the other two models. It has also been showed that the alternative model is able to solve moderate sized real-world problems. Originality/value: The problem under study differentiates from existing batch scheduling problems in the literature owing to the inclusion of new circumstances that are present in real-world applications. Those are: customer orders consisting of multi-products made of multi-parts, processing of all parts of the same product from different orders in the same batch, and delivering the orders only when all related products are completed. This research also contributes to the literature of batch scheduling problem by presenting new optimization models.Peer Reviewe