Predicting length of stay in an acute psychiatric hospital

OBJECTIVE: Multivariate statistical methods were used to identify patient-related variables that predicted length of stay in a single psychiatric facility. The study investigated whether these variables remained stable over time and could be used to provide individual physicians with data on length of stay adjusted for differences in clinical caseloads and to detect trends in the physicians' practice patterns. METHODS: Data on all patients discharged over two six-month periods were collected at an acute psychiatric inpatient facility. Stepwise multiple regression analyses were conducted on the two datasets. RESULTS: The results from both analyses revealed that five variables significantly predicted length of stay and were stable over time. They were a primary diagnosis of schizophrenia, the number of previous admissions, a primary diagnosis of a mood disorder, age, and a secondary diagnosis of an alcohol- or other drug-related disorder. For some physicians, the mean length of stay of their patients differed significantly from the length predicted by the regression model--generally, it was shorter. CONCLUSIONS: The results demonstrate that patient-related predictors of length of stay in a single psychiatric hospital can be identified using relatively simple statistical procedures and can be consistent across a large dataset and over time.     

Synthesis and comparative molecular field analysis (CoMFA) of antitumor 3-arylisoquinoline derivatives

In this study a series of 3-arylisoquinoline derivatives were synthesized and cytotoxicity against human melanoma tumor cell evaluated, and a three dimensional quantitative structure-activity relationship was investigated using the comparative molecular field analysis (CoMFA). The results suggested that the electrostatic, steric and hydrophobic factors of 3-arylisoquinolines were strongly correlated with the antitumor activity. Considerable predictive ability (cross-validated r2 as high as 0.721) was obtained through CoMFA.     

Intact recognition of facial emotion in Parkinson's disease.

Although the basal ganglia have been shown to be critical for the expression of emotion in prosody and facial expressions, it is unclear whether they are also critical for recognition of emotions. Selective pathology of parts of the basal ganglia is a hallmark of individuals with Parkinson's disease, and such patients have been examined in several studies of emotion. We examined 18 patients with Parkinson's disease (11 men, 7 women) and 13 age-, education-, gender ratio-, and IQ-matched normal controls on their ability to recognize emotions signaled by facial expressions. Parkinson's patients performed entirely normally on a quantitative task of recognizing emotional facial expressions. The findings do not support the notion that the sectors of basal ganglia that are dysfunctional in Parkinson's disease are essential for recognizing emotion in facial expressions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Isolation of single yeast cells by optical trapping

Individual yeast cells can be successfully isolated and recultured on plates with a new isolation method making use of optical trapping with infrared laser light. The cells can be selected on morphological criteria by high resolution microscopy. The isolation device is constructed from two coverslips separated by spacers, in which selected cells are transferred to a plastic capillary, using the optical trap. To test the procedure, selection experiments were done with a mixture of two Saccharomyces cerevisiae strains, distinguishable both in fluorescence microscopy and on agar plates. These experiments showed that only selected cells were isolated, and close to 100% of the isolated stationary-phase cells formed colonies on agar plates, indicating a high recovery. A lower recovery was obtained with exponential-phase cells, possibly because of a higher sensitivity to laser irradiation. Applications for this method may include the isolation of mutants with altered morphology and the isolation of subpopulations of yeast cultures, for their separate investigation or for the initiation of pure cultures.     

Finding a maximum matching in a permutation graph

We present anO(n log logn) time algorithm for finding a maximum matching in a permutation graph withn vertices, assuming that the input graph is represented by a permutation.     

Adaptive covariate acquisition for minimizing total cost of classification

Machine Learning - In some applications, acquiring covariates comes at a cost which is not negligible. For example in the medical domain, in order to classify whether a patient has diabetes or not,...     

A note on octonionic support vector regression

This note presents an analysis of the octonionic form of the division algebraic support vector regressor (SVR) first introduced by Shilton A detailed derivation of the dual form is given, and three conditions under which it is analogous to the quaternionic case are exhibited. It is shown that, in the general case of an octonionic-valued feature map, the usual "kernel trick" breaks down. The cause of this (and its interpretation) is discussed in some detail, along with potential ways of extending kernel methods to take advantage of the distinct features present in the general case. Finally, the octonionic SVR is applied to an example gait analysis problem, and its performance is compared to that of the least squares SVR, the Clifford SVR, and the multidimensional SVR.     

Leveraging 802.11n frame aggregation to enhance QoS and power consumption in Wi-Fi networks

The Wi-Fi technology, driven by its tremendous success, is expanding into a wide variety of devices and applications. However, many of these new devices, like handheld devices, pose new challenges in terms of QoS and energy efficiency. In order to address these challenges, in this paper we study how the novel MAC aggregation mechanisms developed in the 802.11n standard can be used to enhance the current 802.11 QoS and power saving protocols. Our contribution is twofold. First, we present a simulation study that illustrates the interactions between 802.11n and the current 802.11 QoS and power saving protocols. This study reveals that the 802.11n MAC aggregation mechanisms perform better when combined with the power save mode included in the original 802.11 standard than with the 802.11e U-APSD protocol. Second, we design CA-DFA, an algorithm that, using only information available at layer two, adapts the amount of 802.11n aggregation used by a Wi-Fi station according to the level of congestion in the network. A detailed performance evaluation demonstrates the benefits of CA-DFA in terms of QoS, energy efficiency and network capacity with respect to state of the art alternatives.     

Design optimization of supersonic jet pumps using high fidelity flow analysis

Supersonic jet pumps are simple devices with no moving parts, where a high velocity (primary) flow is used to pump a second fluid. In this paper, Computational Fluid Dynamics (CFD) is combined with an optimization framework in order to develop a tool for the rapid generation of jet pump designs. A key feature of the problem formulation is the transformation of the jet pump design parameters in terms of geometric ratios. This approach dramatically reduces the number of unrealistic designs covered by the Design of Experiments. Optimal Latin Hypercubes for surrogate model building and model validation points are constructed using a permutation genetic algorithm and design points are evaluated using CFD. Surrogate models of primary and entrained flow rates are built using a Moving Least Squares approach. A series of optimizations for various pump sizes are performed using a genetic algorithm and Sequential Quadratic Programming, with responses calculated from the surrogates. This approach results in a set of optimized designs, from which pumps for a wide range of flow rates can be interpolated.