Time-reversal test for stochastic quantum dynamics

The calculation of quantum dynamics is currently a central issue in theoretical physics, with diverse applications ranging from ultracold atomic Bose-Einstein condensates to condensed matter, biology, and even astrophysics. Here we demonstrate a conceptually simple method of determining the regime of validity of stochastic simulations of unitary quantum dynamics by employing a time-reversal test. We apply this test to a simulation of the evolution of a quantum anharmonic oscillator with up to 6.022×1023 (Avogadro's number) of particles. This system is realizable as a Bose-Einstein condensate in an optical lattice, for which the time-reversal procedure could be implemented experimentally.

Identification of residues involved in binding of IL5 to beta(com) using beta(IL3) and beta(com) chimeras

In mice there are two forms of the beta chain used in the IL3 receptor system, beta(com) and beta(IL3). beta(com) is used by the IL3, ILS and GM-CSF receptors whereas Pns is only used in the IL3 receptor. In this work an assay was developed to identify residues of beta(IL3) that restrict IL5 activity. It was found that such residues reside within the 2nd CRM of the molecule. Furthermore, when residues in the beta(IL3) B'-C' loop were replaced with beta(com) sequence a form of beta(IL3) was produced that was able to respond to IL5. This region is also responsible for IL3 binding to beta(IL3) in the absence of alpha chain. It is therefore an important structural motif of beta(com) and beta(IL3) responsible for both ligand interaction and specificity. (C) 1999 Federation of European Biochemical Societies.

Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

Disagreement between correlations of quantum mechanics and stochastic electrodynamics in the damped parametric oscillator

Intracavity and external third order correlations in the damped nondegenerate parametric oscillator are calculated for quantum mechanics and stochastic electrodynamics (SED), a semiclassical theory. The two theories yield greatly different results, with the correlations of quantum mechanics being cubic in the system's nonlinear coupling constant and those of SED being linear in the same constant. In particular, differences between the two theories are present in at least a mesoscopic regime. They also exist when realistic damping is included. Such differences illustrate distinctions between quantum mechanics and a hidden variable theory for continuous variables.

Identification of the coupling between skeletal muscle store-operated Ca2+ entry and the inositol trisphosphate receptor

Examination of store-operated Ca2+ entry (SOC) in single, mechanically skinned skeletal muscle cells by confocal microscopy shows that the inositol 1,4,5-trisphosphate (IP3) receptor acts as a sarcoplasmic reticulum [Ca2+] sensor and mediates SOC by physical coupling without playing a key role in Ca2+ release from internal stores, as is the case with various cell types in which SOC was investigated previously. The results have broad implications for understanding the mechanism of SOC that is essential for cell function in general and muscle function in particular. Moreover, the study ascribes an important role to the IN receptors in skeletal muscle, the role of which with respect to Ca2+ homeostasis was ill defined until now.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion`s biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.

Classification model based on Raman spectra of selected morphological and biochemical tissue constituents for identification of atherosclerosis in human coronary arteries

This study presents the results of Raman spectroscopy applied to the classification of arterial tissue based on a simplified model using basal morphological and biochemical information extracted from the Raman spectra of arteries. The Raman spectrograph uses an 830-nm diode laser, imaging spectrograph, and a CCD camera. A total of 111 Raman spectra from arterial fragments were used to develop the model, and those spectra were compared to the spectra of collagen, fat cells, smooth muscle cells, calcification, and cholesterol in a linear fit model. Non-atherosclerotic (NA), fatty and fibrous-fatty atherosclerotic plaques (A) and calcified (C) arteries exhibited different spectral signatures related to different morphological structures presented in each tissue type. Discriminant analysis based on Mahalanobis distance was employed to classify the tissue type with respect to the relative intensity of each compound. This model was subsequently tested prospectively in a set of 55 spectra. The simplified diagnostic model showed that cholesterol, collagen, and adipocytes were the tissue constituents that gave the best classification capability and that those changes were correlated to histopathology. The simplified model, using spectra obtained from a few tissue morphological and biochemical constituents, showed feasibility by using a small amount of variables, easily extracted from gross samples.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

The universal newborn hearing screening in Brazil: From identification to intervention

Objective: The objective of the study is to investigate the results of the newborn hearing screening program carried out in a Public Hospital in Brazil, in the first 3 years regarding: (1) the prevalence of hearing impairment; (2) the influence of the universal hearing screening program on the age at which the diagnosis of hearing loss is defined; (3) the cost effectiveness of the program; (4) the outcomes, in terms of the age in which the hearing rehabilitation started. Methods: A descriptive study of the first 3 years after starting the universal newborn hearing screening in a Public Hospital of Bauru, Sao Paulo state, Brazil. The screening method consists of a two-stage screening approach with transient otoacoustic emissions (TOAE), conducted by an audiologist. If the outcome in the second-stage screening is REFER, the infant is submitted to diagnostic follow-up testing and intervention at the Audiology and Speech Pathology Clinic at the University of Sao Paulo, campus of Bauru. The evaluation of the costs of the universal newborn hearing screening program per each screened newborn (around 4000/year) was done based on a proposal by the National Center for Hearing Assessment and Management, of the Utah State University, United States of America. Results: 11,466 newborns were submitted to hearing screening, corresponding to 90.52% of the living newborns. The prevalence of sensorineural hearing loss was 0.96:1000. Of the 11 children with sensorineural hearing loss, eight children received hearing aids and five started the therapeutic process before the age of 1. Currently, four children between the ages of 11 months and 2 years old were submitted to cochlear implant surgery. The cost of hearing screening was US$7.00 and the annual cost of the universal newborn hearing screening program was US$26,940.47. Conclusion: The hospital-based universal newborn hearing screening carried out through the Brazilian National Health System is viable, with promising results. However, in a country such as Brazil, which presents large socio-economic differences, the same type of analyses should be performed in several regions, so as to take into account specific aspects, to implement the newborn hearing screening along with the Public System. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Lanczos subspace filter diagonalization: Homogeneous recursive filtering and a low-storage method for the calculation of matrix elements

We develop a new iterative filter diagonalization (FD) scheme based on Lanczos subspaces and demonstrate its application to the calculation of bound-state and resonance eigenvalues. The new scheme combines the Lanczos three-term vector recursion for the generation of a tridiagonal representation of the Hamiltonian with a three-term scalar recursion to generate filtered states within the Lanczos representation. Eigenstates in the energy windows of interest can then be obtained by solving a small generalized eigenvalue problem in the subspace spanned by the filtered states. The scalar filtering recursion is based on the homogeneous eigenvalue equation of the tridiagonal representation of the Hamiltonian, and is simpler and more efficient than our previous quasi-minimum-residual filter diagonalization (QMRFD) scheme (H. G. Yu and S. C. Smith, Chem. Phys. Lett., 1998, 283, 69), which was based on solving for the action of the Green operator via an inhomogeneous equation. A low-storage method for the construction of Hamiltonian and overlap matrix elements in the filtered-basis representation is devised, in which contributions to the matrix elements are computed simultaneously as the recursion proceeds, allowing coefficients of the filtered states to be discarded once their contribution has been evaluated. Application to the HO2 system shows that the new scheme is highly efficient and can generate eigenvalues with the same numerical accuracy as the basic Lanczos algorithm.

Human pigmentation genes: identification, structure and consequences of polymorphic variation

The synthesis of the visible pigment melanin by the melanocyte cell is the basis of the human pigmentary system, those genes directing the formation, transport and distribution of the specialised melanosome organelle in which melanin accumulates can legitimately be called pigmentation genes. The genes involved in this process have been identified through comparative genomic studies of mouse coat colour mutations and by the molecular characterisation of human hypopigmentary genetic diseases such as OCA1 and OCA2. The melanocyte responds to the peptide hormones a-MSH or ACTH through the MC1R G-protein coupled receptor to stimulate melanin production through induced maturation or switching of melanin type. The pheomelanosome, containing the key enzyme of the pathway tyrosinase, produces light red/yellowish melanin, whereas the eumelanosome produces darker melanins via induction of additional TYRP1, TYRP2, SILV enzymes, and the P-protein. Intramelanosomal pH governed by the P-protein may act as a critical determinant of tyrosinase enzyme activity to control the initial step in melanin synthesis or TYRP complex formation to facilitate melanogenesis and melanosomal maturation. The search for genetic variation in these candidate human pigmentation genes in various human populations has revealed high levels of polymorphism in the MC1R locus, with over 30 variant alleles so far identified. Functional correlation of MC1R alleles with skin and hair colour provides evidence that this receptor molecule is a principle component underlying normal human pigment variation. (C) 2001 Elsevier Science B.V. All rights reserved.