Who Benefits from Postsecondary Occupational Education? Findings from the1980s and 1990s

Technological changes in the workplace have placed considerable pressure on the U.S. educational system to prepare students for increasingly skillbased occupations. Employers reward new hires for having the skills or credentials needed for their job, underscoring the importance of having either the requisite “tools in your toolbox,” or some basic academic preparation to continue on into postsecondary education. This stress on knowledge acquisition has contributed to a growing wage gap between high school and college graduates. Whether occupational education at the high school level, with its focus on immediate workforce entry after high school, adequately prepares students for college is a public concern. Since students who enroll in these programs are less likely to transfer to a four-year college to obtain a bachelor’s degree, occupational education is criticized for hampering their future earnings. Some of the criticisms of postsecondary occupational education could be allayed if the economic benefits were equal to (or greater than) those of other types of education. This brief investigates the economic benefits of a community college education by analyzing the effects on post-college earnings of a student’s program of study (occupational or academic), the amount of schooling accumulated with and without attaining a degree, and the type of credential earned

Semi-supervised prediction of protein interaction sentences exploiting semantically encoded metrics

Protein-protein interaction (PPI) identification is an integral component of many biomedical research and database curation tools. Automation of this task through classification is one of the key goals of text mining (TM). However, labelled PPI corpora required to train classifiers are generally small. In order to overcome this sparsity in the training data, we propose a novel method of integrating corpora that do not contain relevance judgements. Our approach uses a semantic language model to gather word similarity from a large unlabelled corpus. This additional information is integrated into the sentence classification process using kernel transformations and has a re-weighting effect on the training features that leads to an 8% improvement in F-score over the baseline results. Furthermore, we discover that some words which are generally considered indicative of interactions are actually neutralised by this process

Modulation of en-route charges to redistribute traffic in the European airspace

Peak-load pricing (PLP), a two-tariffs charging scheme commonly used in public transport and utilities, is tested on the European Air Traffic Management (ATM) system as a means for reducing capacity-demand imbalances. In particular, a centralised approach to PLP (CPLP) where a Central Planner (CP) sets en-route charges on the network is presented. CPLP consists of two phases: in the first, congested airspace sectors and their peak and off-peak hours are identified; in the second, CP assesses and sets en-route charges in order to reduce overall shift on the network. Such charges should guarantee that Air Navigation Service Providers (ANSPs) are able to recover their operational costs while inducing the Airspace Users (AUs) to route their flights in a way that respects airspace capacity. The interaction between CP and AUs is modelled as a Stackelberg game and formulated by means of bilevel linear programming. Two heuristic approaches, based on Coordinate-wise Descent and Genetic Algorithms are implemented to solve the CPLP model on a data set obtained from historical data for an entire day of traffic on European airspace. Results show that significant improvements in traffic distribution in terms of shift and sector load can be achieved through this simple en-route charges modulation scheme

A robust, discrete-gradient descent procedure for optimisation with time-dependent PDE and norm constraints

Many physical questions in fluid dynamics can be recast in terms of norm constrained optimisation problems; which in-turn, can be further recast as unconstrained problems on spherical manifolds. Due to the nonlinearities of the governing PDEs, and the computational cost of performing optimal control on such systems, improving the numerical convergence of the optimisation procedure is crucial. Borrowing tools from the optimisation on manifolds community we outline a numerically consistent, discrete formulation of the direct-adjoint looping method accompanied by gradient descent and line-search algorithms with global convergence guarantees. We numerically demonstrate the robustness of this formulation on three example problems of relevance in fluid dynamics and provide an accompanying library SphereManOp

Second best toll and capacity optimisation in network: solution algorithm and policy implications

This paper looks at the first and second-best jointly optimal toll and road capacity investment problems from both policy and technical oriented perspectives. On the technical side, the paper investigates the applicability of the constraint cutting algorithm for solving the second-best problem under elastic demand which is formulated as a bilevel programming problem. The approach is shown to perform well despite several problems encountered by our previous work in Shepherd and Sumalee (2004). The paper then applies the algorithm to a small sized network to investigate the policy implications of the first and second-best cases. This policy analysis demonstrates that the joint first best structure is to invest in the most direct routes while reducing capacities elsewhere. Whilst unrealistic this acts as a useful benchmark. The results also show that certain second best policies can achieve a high proportion of the first best benefits while in general generating a revenue surplus. We also show that unless costs of capacity are known to be low then second best tolls will be affected and so should be analysed in conjunction with investments in the network

Three-body Interactions Improve the Prediction of Rate and Mechanism in Protein Folding Models

Here we study the effects of many-body interactions on rate and mechanism in protein folding, using the results of molecular dynamics simulations on numerous coarse-grained C-alpha-model single-domain proteins. After adding three-body interactions explicitly as a perturbation to a Go-like Hamiltonian with native pair-wise interactions only, we have found 1) a significantly increased correlation with experimental phi-values and folding rates, 2) a stronger correlation of folding rate with contact order, matching the experimental range in rates when the fraction of three-body energy in the native state is ~ 20%, and 3) a considerably larger amount of 3-body energy present in Chymotripsin inhibitor than other proteins studied.Comment: 9 pages, 2 tables and 5 figure

The Return to a Sub-Baccalaureate Education: The Effects of Schooling, Credentials and Program of Study on Economic Outcomes

Over the last 20 years, technological changes in the workplace have placed considerable pressure on the U.S. educational system to adequately prepare students for occupations that increasingly require specific skills. However, certain educators and policy-makers have raised the question of whether vocational education at the high school level, with its focus on immediately entering the workforce after high school, adequately prepares students for college. At the postsecondary level, the debate has centered on whether vocational education restricts access to a four-year college, which may hamper future earnings. This report estimates the returns to a sub-baccalaureate education. The analyses emphasize the effect of a student's program of study, the amount of schooling accumulated with and without attaining a degree, and the type of credential earned. We test whether the earnings of degree attainers are significantly larger than those of similar students with the same amount of postsecondary education but no credential. We also examine whether economic gains from occupational education are realized not only for students who concentrated on vocational education in high school but also for special subpopulations such as older students, racial-ethnic minorities, and academically or economically disadvantaged students

Infinite-Order Percolation and Giant Fluctuations in a Protein Interaction Network

We investigate a model protein interaction network whose links represent interactions between individual proteins. This network evolves by the functional duplication of proteins, supplemented by random link addition to account for mutations. When link addition is dominant, an infinite-order percolation transition arises as a function of the addition rate. In the opposite limit of high duplication rate, the network exhibits giant structural fluctuations in different realizations. For biologically-relevant growth rates, the node degree distribution has an algebraic tail with a peculiar rate dependence for the associated exponent.Comment: 4 pages, 2 figures, 2 column revtex format, to be submitted to PRL 1; reference added and minor rewording of the first paragraph; Title change and major reorganization (but no result changes) in response to referee comments; to be published in PR