Stronger instruments via integer programming in an observational study of late preterm birth outcomes

In an optimal nonbipartite match, a single population is divided into matched pairs to minimize a total distance within matched pairs. Nonbipartite matching has been used to strengthen instrumental variables in observational studies of treatment effects, essentially by forming pairs that are similar in terms of covariates but very different in the strength of encouragement to accept the treatment. Optimal nonbipartite matching is typically done using network optimization techniques that can be quick, running in polynomial time, but these techniques limit the tools available for matching. Instead, we use integer programming techniques, thereby obtaining a wealth of new tools not previously available for nonbipartite matching, including fine and near-fine balance for several nominal variables, forced near balance on means and optimal subsetting. We illustrate the methods in our on-going study of outcomes of late-preterm births in California, that is, births of 34 to 36 weeks of gestation. Would lengthening the time in the hospital for such births reduce the frequency of rapid readmissions? A straightforward comparison of babies who stay for a shorter or longer time would be severely biased, because the principal reason for a long stay is some serious health problem. We need an instrument, something inconsequential and haphazard that encourages a shorter or a longer stay in the hospital. It turns out that babies born at certain times of day tend to stay overnight once with a shorter length of stay, whereas babies born at other times of day tend to stay overnight twice with a longer length of stay, and there is nothing particularly special about a baby who is born at 11:00 pm.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS582 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Detecting periodicity in experimental data using linear modeling techniques

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a new method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data, to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive, than traditional spectral techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified styl

Accounting for the effect of heterogeneous plastic deformation on the formability of aluminium and steel sheets

Forming Limit Curves characterise ‘mean’ failure strains of sheet metals. Safety levels from the curves define the deterministic upper limit of the processing and part design window, which can be small for high strength, low formability materials. Effects of heterogeneity of plastic deformation, widely accepted to occur on the microscale, are neglected. Marciniak tests were carried out on aluminium alloys (AA6111-T4, NG5754-O), dual-phase steel (DP600) and mild steel (MS3). Digital image correlation was used to measure the effect of heterogeneity on failure. Heterogeneity, based on strain variance was modelled with the 2-component Gaussian Mixture Model and a framework was proposed to 1) identify the onset of necking and to 2) re-define formability as a probability to failure. The result were ‘forming maps’ in major-minor strain space of contours of constant probability (from probability, P=0 to P=1), which showed how failure risk increased with major strain. The contour bands indicated the unique degree of heterogeneity in each material. NG5754-O had the greatest width (0.07 strain) in plane strain and MS3 the lowest (0.03 strain). This novel characterisation will allow engineers to balance a desired forming window for a component design with the risk to failure of the material

An accretion model for the growth of the central black hole associated with ionization instability in quasars

A possible accretion model associated with the ionization instability of quasar disks is proposed to address the growth of the central black hole harbored in the host galaxy.The mass ratio between black hole and its host galactic bulge is a nature consequence of our model.Comment: submitted to ApJ, 15 page

Improvement of Dynamic Soil Properties Induced by Preloading Verified by a Field Test and Embankment Failure

The results of an elaborate field preloading study on a liquefaction-susceptible site are presented. Preloading was applied by a temporary embankment 9m high. Prior and after preloading, borings with standard penetration tests, cone penetration tests and geophysical studies were performed. During the process of embankment construction and demolition, settlements, excess pore pressures and vertical and horizontal stresses were recorded versus time at different locations. A partial embankment failure occurred during the preloading process. A method predicting failure during the construction of the preload embankment based on excess pore pressure measurements is proposed and verified

Optimal control strategies for tuberculosis treatment: a case study in Angola

We apply optimal control theory to a tuberculosis model given by a system of ordinary differential equations. Optimal control strategies are proposed to minimize the cost of interventions. Numerical simulations are given using data from Angola.Comment: This is a preprint of a paper whose final and definite form will appear in the international journal Numerical Algebra, Control and Optimization (NACO). Paper accepted for publication 15-March-201

Criteria for Inclusion of Newer Bariatric and Metabolic Procedures into the Mainstream: a Survey of 396 Bariatric Surgeons

BACKGROUND: There is currently no consensus on the criteria for inclusion of new bariatric procedures into routine clinical practice. This study canvasses bariatric surgeons in an attempt to define these criteria. METHODS: Bariatric Surgeons from around the world were invited to participate in a questionnaire-based survey on SurveyMonkey ®. RESULTS: 396 bariatric surgeons, 337 International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) members, took the survey. Five clinical studies conducted under the strict monitoring of an Institutional Review Board would satisfy most surgeons (67.7 %, n = 266). When asked regarding the number of patients in these studies, a cumulative number of 500 patients would satisfy 64.5 % (n = 255) of the surgeons. Most respondents regarded endorsement by their national society and IFSO as 'very important' or 'extremely important'. An overwhelming 74.4 % (n = 294) felt that every new procedure should undergo a randomized comparison against one of the established alternatives like Roux-en-Y Gastric Bypass or Sleeve Gastrectomy. CONCLUSION: Evaluation of a new bariatric procedure in at least 5 adequately supervised clinical studies (four of which must be randomized comparisons with one of the existing alternatives) reporting at least 5 years results on a minimum of 500 patients would satisfy majority of bariatric surgeons for the inclusion of a new bariatric procedure into clinical practice. The findings of this survey are simply aimed at starting a discussion on this topic and cannot be used to influence the ground reality until an international consensus can be reached amongst experts.info:eu-repo/semantics/publishedVersio

Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait

Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system