In search of climate effects on Atlantic Croaker (Micropogonias undulatus) stock off the U.S. Atlantic coast with Bayesian state-space biomass dynamic models

Atlantic Croaker (Micropogonias undulatus) production dynamics along the U.S. Atlantic coast are regulated by fishing and winter water temperature. Stakeholders for this resource have recommended investigating the effects of climate covariates in assessment models. This study used state-space biomass dynamic models without (model 1) and with (model 2) the minimum winter estuarine temperature (MWET) to examine MWET effects on Atlantic Croaker population dynamics during 1972–2008. In model 2, MWET was introduced into the intrinsic rate of population increase (r). For both models, a prior probability distribution (prior) was constructed for r or a scaling parameter (r0); imputs were the fishery removals, and fall biomass indices developed by using data from the Multispecies Bottom Trawl Survey of the Northeast Fisheries Science Center, National Marine Fisheries Service, and the Coastal Trawl Survey of the Southeast Area Monitoring and Assessment Program. Model sensitivity runs incorporated a uniform (0.01,1.5) prior for r or r0 and bycatch data from the shrimp-trawl fishery. All model variants produced similar results and therefore supported the conclusion of low risk of overfishing for the Atlantic Croaker stock in the 2000s. However, the data statistically supported only model 1 and its configuration that included the shrimp-trawl fishery bycatch. The process errors of these models showed slightly positive and significant correlations with MWET, indicating that warmer winters would enhance Atlantic Croaker biomass production. Inconclusive, somewhat conflicting results indicate that biomass dynamic models should not integrate MWET, pending, perhaps, accumulation of longer time series of the variables controlling the production dynamics of Atlantic Croaker, preferably including winter-induced estimates of Atlantic Croaker kills.

Optimal H2 order-one reduction by solving eigenproblems for polynomial equations

A method is given for solving an optimal H2 approximation problem for SISO linear time-invariant stable systems. The method, based on constructive algebra, guarantees that the global optimum is found; it does not involve any gradient-based search, and hence avoids the usual problems of local minima. We examine mostly the case when the model order is reduced by one, and when the original system has distinct poles. This case exhibits special structure which allows us to provide a complete solution. The problem is converted into linear algebra by exhibiting a finite-dimensional basis for a certain space, and can then be solved by eigenvalue calculations, following the methods developed by Stetter and Moeller. The use of Buchberger's algorithm is avoided by writing the first-order optimality conditions in a special form, from which a Groebner basis is immediately available. Compared with our previous work the method presented here has much smaller time and memory requirements, and can therefore be applied to systems of significantly higher McMillan degree. In addition, some hypotheses which were required in the previous work have been removed. Some examples are included.

Case base reduction using solution-space metrics

In this paper we propose a case base reduction technique which uses a metric defined on the solution space. The technique utilises the Generalised Shepard Nearest Neighbour (GSNN) algorithm to estimate nominal or real valued solutions in case bases with solution space metrics. An overview of GSNN and a generalised reduction technique, which subsumes some existing decremental methods, such as the Shrink algorithm, are presented. The reduction technique is given for case bases in terms of a measure of the importance of each case to the predictive power of the case base. A trial test is performed on two case bases of different kinds, with several metrics proposed in the solution space. The tests show that GSNN can out-perform standard nearest neighbour methods on this set. Further test results show that a caseremoval order proposed based on a GSNN error function can produce a sparse case base with good predictive power.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Supersymmetry flows, semi-symmetric space sine-Gordon models and the Pohlmeyer reduction

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Basic ingredients for mathematical modeling of tumor growth in vitro: Cooperative effects and search for space

Based on the literature data from HT-29 cell monolayers, we develop a model for its growth, analogous to an epidemic model, mixing local and global interactions. First, we propose and solve a deterministic equation for the progress of these colonies. Thus, we add a stochastic (local) interaction and simulate the evolution of an Eden-like aggregate by using dynamical Monte Carlo methods. The growth curves of both deterministic and stochastic models are in excellent agreement with the experimental observations. The waiting times distributions, generated via our stochastic model, allowed us to analyze the role of mesoscopic events. We obtain log-normal distributions in the initial stages of the growth and Gaussians at long times. We interpret these outcomes in the light of cellular division events: in the early stages, the phenomena are dependent each other in a multiplicative geometric-based process, and they are independent at long times. We conclude that the main ingredients for a good minimalist model of tumor growth, at mesoscopic level, are intrinsic cooperative mechanisms and competitive search for space. © 2013 Elsevier Ltd.

Air versus saline in the loss of resistance technique for identification of the epidural space

BackgroundThe success of epidural anaesthesia depends on correct identification of the epidural space. For several decades, the decision of whether to use air or physiological saline during the loss of resistance technique for identification of the epidural space has been governed by the personal experience of the anaesthesiologist. Epidural block remains one of the main regional anaesthesia techniques. It is used for surgical anaesthesia, obstetrical analgesia, postoperative analgesia and treatment of chronic pain and as a complement to general anaesthesia. The sensation felt by the anaesthesiologist from the syringe plunger with loss of resistance is different when air is compared with saline (fluid). Frequently fluid allows a rapid change from resistance to non-resistance and increased movement of the plunger. However, the ideal technique for identification of the epidural space remains unclear.ObjectivesTo evaluate the efficacy and safety of both air and saline in the loss of resistance technique for identification of the epidural space.To evaluate complications related to the air or saline injected.Search methodsWe searched the Cochrane Central Register of Controlled Trials (CENTRAL) (2013, Issue 9), MEDLINE, EMBASE and the Latin American and Caribbean Health Science Information Database (LILACS) (from inception to September 2013). We applied no language restrictions. The date of the most recent search was 7 September 2013.Selection criteriaWe included randomized controlled trials (RCTs) and quasi-randomized controlled trials (quasi-RCTs) on air and saline in the loss of resistance technique for identification of the epidural space.Data collection and analysisTwo review authors independently assessed trial quality and extracted data.Main resultsWe included in the review seven studies with a total of 852 participants. The methodological quality of the included studies was generally ranked as showing low risk of bias inmost domains, with the exception of one study, which did not mask participants. We were able to include data from 838 participants in the meta-analysis. We found no statistically significant differences between participants receiving air and those given saline in any of the outcomes evaluated: inability to locate the epidural space (three trials, 619 participants) (risk ratio (RR) 0.88, 95% confidence interval (CI) 0.33 to 2.31, low-quality evidence); accidental intravascular catheter placement (two trials, 223 participants) (RR 0.90, 95% CI 0.33 to 2.45, low-quality evidence); accidental subarachnoid catheter placement (four trials, 682 participants) (RR 2.95, 95% CI 0.12 to 71.90, low-quality evidence); combined spinal epidural failure (two trials, 400 participants) (RR 0.98, 95% CI 0.44 to 2.18, low-quality evidence); unblocked segments (five studies, 423 participants) (RR 1.66, 95% CI 0.72 to 3.85); and pain measured by VAS (two studies, 395 participants) (mean difference (MD) -0.09, 95% CI -0.37 to 0.18). With regard to adverse effects, we found no statistically significant differences between participants receiving air and those given saline in the occurrence of paraesthesias (three trials, 572 participants) (RR 0.89, 95% CI 0.69 to 1.15); difficulty in advancing the catheter (two trials, 227 participants) (RR 0.91, 95% CI 0.32 to 2.56); catheter replacement (two trials, 501 participants) (RR 0.69, 95% CI 0.26 to 1.83); and postdural puncture headache (one trial, 110 participants) (RR 0.83, 95% CI 0.12 to 5.71).Authors' conclusionsLow-quality evidence shows that results do not differ between air and saline in terms of the loss of resistance technique for identification of the epidural space and reduction of complications. Applicability might be compromised, as most of the results described in this review were obtained from parturient patients. This review underlines the need to conduct well-designed trials in this field.

De la cápsula comunitaria al espacio compartido. La búsqueda del post-espacio público en la vivienda de ACM = From community capsules to shared intervals. The search of the post-public space In the housing developments by ACM

Arquitectos y no arquitectos como Rossi, Grassi, Jacobs, Sennett o Lefebvre, denunciaron críticamente durante los 50, 50 y 70 la ruptura entre la calle y el espacio doméstico y el consiguiente declive del dominio público urbano a escala de ciudad y a escala de barrio. La crítica a la "Ville Contemporaine" no solo se escribía, también se dibujaba y a veces, incluso, se construía. La primera generación post-CIAM trabajó intensamente en desmentir con palabras y obras al Oud que ya en los años 20 del pasado siglo, tomando la delantera a Le Corbusier y desde su mejor sentido práctico y estético afirmaba: "Las calles para el negocio, los patios interiores para la vida. Los dos estrictamente separados y con un carácter contradictorio".

Dimensionality Reduction Through Sub-Space Mapping for Nearest Neighbour Algorithms

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