Effects of two traits of the ecological state equation on our understanding of species coexistence and ecosystem services

Species coexistence has been a fundamental issue to understand ecosystem functioning since the beginnings of ecology as a science. The search of a reliable and all-encompassing explanation for this issue has become a complex goal with several apparently opposing trends. On the other side, seemingly unconnected with species coexistence, an ecological state equation based on the inverse correlation between an indicator of dispersal that fits gamma distribution and species diversity has been recently developed. This article explores two factors, whose effects are inconspicuous in such an equation at the first sight, that are used to develop an alternative general theoretical background in order to provide a better understanding of species coexistence. Our main outcomes are: (i) the fit of dispersal and diversity values to gamma distribution is an important factor that promotes species coexistence mainly due to the right-skewed character of gamma distribution; (ii) the opposite correlation between species diversity and dispersal implies that any increase of diversity is equivalent to a route of “ecological cooling” whose maximum limit should be constrained by the influence of the third law of thermodynamics; this is in agreement with the well-known asymptotic trend of diversity values in space and time; (iii) there are plausible empirical and theoretical ways to apply physical principles to explain important ecological processes; (iv) the gap between theoretical and empirical ecology in those cases where species diversity is paradoxically high could be narrowed by a wave model of species coexistence based on the concurrency of local equilibrium states. In such a model, competitive exclusion has a limited but indispensable role in harmonious coexistence with functional redundancy. We analyze several literature references as well as ecological and evolutionary examples that support our approach, reinforcing the meaning equivalence between important physical and ecological principles.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

A Cruciform Electron Donor-Acceptor Semiconductor with Solid-State Red Emission: 1D/2D Optical Waveguides and Highly Sensitive/Selective Detection of H2S Gas

In this paper, a new cruciform donor–acceptor molecule 2,2'-((5,5'-(3,7-dicyano-2,6-bis(dihexylamino)benzo[1,2-b:4,5-b']difuran-4,8-diyl)bis(thiophene-5,2-diyl))bis (methanylylidene))dimalononitrile (BDFTM) is reported. The compound exhibits both remarkable solid-state red emission and p-type semiconducting behavior. The dual functions of BDFTM are ascribed to its unique crystal structure, in which there are no intermolecular face-to-face π–π interactions, but the molecules are associated by intermolecular CN…π and H-bonding interactions. Firstly, BDFTM exhibits aggregation-induced emission; that is, in solution, it is almost non-emissive but becomes significantly fluorescent after aggregation. The emission quantum yield and average lifetime are measured to be 0.16 and 2.02 ns, respectively. Crystalline microrods and microplates of BDFTM show typical optical waveguiding behaviors with a rather low optical loss coefficient. Moreover, microplates of BDFTM can function as planar optical microcavities which can confine the emitted photons by the reflection at the crystal edges. Thin films show an air-stable p-type semiconducting property with a hole mobility up to 0.0015 cm2V−1s−1. Notably, an OFET with a thin film of BDFTM is successfully utilized for highly sensitive and selective detection of H2S gas (down to ppb levels).

Azacyclic FTY720 Analogues That Limit Nutrient Transporter Expression but Lack S1P Receptor Activity and Negative Chronotropic Effects Offer a Novel and Effective Strategy to Kill Cancer Cells in Vivo

FTY720 sequesters lymphocytes in secondary lymphoid organs through effects on sphingosine-1-phosphate (S1P) receptors. However, at higher doses than are required for immunosuppression, FTY720 also functions as an anticancer agent in multiple animal models. Our published work indicates that the anticancer effects of FTY720 do not depend on actions at S1P receptors but instead stem from FTY720s ability to restrict access to extracellular nutrients by down-regulating nutrient transporter proteins. This result was significant because S1P receptor activation is responsible for FTY720s dose-limiting toxicity, bradycardia, that prevents its use in cancer patients. Here, we describe diastereomeric and enantiomeric 3- and 4-C-aryl 2-hydroxymethyl pyrrolidines that are more active than the previously known analogues. Of importance is that these compounds fail to activate S1P1 or S1P3 receptors in vivo but retain inhibitory effects on nutrient transporter proteins and anticancer activity in solid tumor xenograft models. Our studies reaffirm that the anticancer activity of FTY720 does not depend upon S1P receptor activation and uphold the promise of using S1P receptor-inactive azacyclic FTY720 analogues in human cancer patients.

Multiple functions of gingival and mucoperiosteal fibroblasts in oral wound healing and repair

Fibroblasts are cells of mesenchymal origin. They are responsible for the production of most extracellular matrix in connective tissues and are essential for wound healing and repair. In recent years, it has become clear that fibroblasts from different tissues have various distinct traits. Moreover, wounds in the oral cavity heal under very special environmental conditions compared with skin wounds. Here, we reviewed the current literature on the various interconnected functions of gingival and mucoperiosteal fibroblasts during the repair of oral wounds. The MEDLINE database was searched with the following terms: (gingival OR mucoperiosteal) AND fibroblast AND (wound healing OR repair). The data gathered were used to compare oral fibroblasts with fibroblasts from other tissues in terms of their regulation and function during wound healing. Specifically, we sought answers to the following questions: (i) what is the role of oral fibroblasts in the inflammatory response in acute wounds; (ii) how do growth factors control the function of oral fibroblasts during wound healing; (iii) how do oral fibroblasts produce, remodel and interact with extracellular matrix in healing wounds; (iv) how do oral fibroblasts respond to mechanical stress; and (v) how does aging affect the fetal-like responses and functions of oral fibroblasts? The current state of research indicates that oral fibroblasts possess unique characteristics and tightly controlled specific functions in wound healing and repair. This information is essential for developing new strategies to control the intraoral wound-healing processes of the individual patient.

Compact Singlet S Helium Wave functions(corrected)

This is a corrected version of the Phys. Rev. A 74,14501 (2006) article. The result is improved slightly from that in the original paper.

NONLINEAR TIME SERIES/SYSTEM ANALYSIS (STATE-SPACE, DYNAMICS, INTERVENTION, RESILIENCE, KALMAN)

A discussion of nonlinear dynamics, demonstrated by the familiar automobile, is followed by the development of a systematic method of analysis of a possibly nonlinear time series using difference equations in the general state-space format. This format allows recursive state-dependent parameter estimation after each observation thereby revealing the dynamics inherent in the system in combination with random external perturbations.^ The one-step ahead prediction errors at each time period, transformed to have constant variance, and the estimated parametric sequences provide the information to (1) formally test whether time series observations y(,t) are some linear function of random errors (ELEM)(,s), for some t and s, or whether the series would more appropriately be described by a nonlinear model such as bilinear, exponential, threshold, etc., (2) formally test whether a statistically significant change has occurred in structure/level either historically or as it occurs, (3) forecast nonlinear system with a new and innovative (but very old numerical) technique utilizing rational functions to extrapolate individual parameters as smooth functions of time which are then combined to obtain the forecast of y and (4) suggest a measure of resilience, i.e. how much perturbation a structure/level can tolerate, whether internal or external to the system, and remain statistically unchanged. Although similar to one-step control, this provides a less rigid way to think about changes affecting social systems.^ Applications consisting of the analysis of some familiar and some simulated series demonstrate the procedure. Empirical results suggest that this state-space or modified augmented Kalman filter may provide interesting ways to identify particular kinds of nonlinearities as they occur in structural change via the state trajectory.^ A computational flow-chart detailing computations and software input and output is provided in the body of the text. IBM Advanced BASIC program listings to accomplish most of the analysis are provided in the appendix. ^

Asymptotically Optimum Estimation of a Probability in Inverse Binomial Sampling under General Loss Functions

The optimum quality that can be asymptotically achieved in the estimation of a probability p using inverse binomial sampling is addressed. A general definition of quality is used in terms of the risk associated with a loss function that satisfies certain assumptions. It is shown that the limit superior of the risk for p asymptotically small has a minimum over all (possibly randomized) estimators. This minimum is achieved by certain non-randomized estimators. The model includes commonly used quality criteria as particular cases. Applications to the non-asymptotic regime are discussed considering specific loss functions, for which minimax estimators are derived.

Equation of state for hot dense matter using a relativistic screened hydrogenic model

The study of matter under conditions of high density, pressure, and temperature is a valuable subject for inertial confinement fusion (ICF), astrophysical phenomena, high-power laser interaction with matter, etc. In all these cases, matter is heated and compressed by strong shocks to high pressures and temperatures, becomes partially or completely ionized via thermal or pressure ionization, and is in the form of dense plasma. The thermodynamics and the hydrodynamics of hot dense plasmas cannot be predicted without the knowledge of the equation of state (EOS) that describes how a material reacts to pressure and how much energy is involved. Therefore, the equation of state often takes the form of pressure and energy as functions of density and temperature. Furthermore, EOS data must be obtained in a timely manner in order to be useful as input in hydrodynamic codes. By this reason, the use of fast, robust and reasonably accurate atomic models, is necessary for computing the EOS of a material.

SMA-Based Muscle-Like Actuation in Biologically Inspired Robots: A State of the Art Review

New actuation technology in functional or "smart" materials has opened new horizons in robotics actuation systems. Materials such as piezo-electric fiber composites, electro-active polymers and shape memory alloys (SMA) are being investigated as promising alternatives to standard servomotor technology [52]. This paper focuses on the use of SMAs for building muscle-like actuators. SMAs are extremely cheap, easily available commercially and have the advantage of working at low voltages. The use of SMA provides a very interesting alternative to the mechanisms used by conventional actuators. SMAs allow to drastically reduce the size, weight and complexity of robotic systems. In fact, their large force-weight ratio, large life cycles, negligible volume, sensing capability and noise-free operation make possible the use of this technology for building a new class of actuation devices. Nonetheless, high power consumption and low bandwidth limit this technology for certain kind of applications. This presents a challenge that must be addressed from both materials and control perspectives in order to overcome these drawbacks. Here, the latter is tackled. It has been demonstrated that suitable control strategies and proper mechanical arrangements can dramatically improve on SMA performance, mostly in terms of actuation speed and limit cycles.

Changes in resting-state functionally connected parieto-frontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Vector spaces of entire functions of unbounded type

Let E be an infinite dimensional complex Banach space. We prove the existence of an infinitely generated algebra, an infinite dimensional closed subspace and a dense subspace of entire functions on E whose non-zero elements are functions of unbounded type. We also show that the τδ topology on the space of all holomorphic functions cannot be obtained as a countable inductive limit of Fr´echet spaces. RESUMEN. Sea E un espacio de Banach complejo de dimensión infinita y sea H(E) el espacio de funciones holomorfas definidas en E. En el artículo se demuestra la existencia de un álgebra infinitamente generada en H(E), un subespacio vectorial en H(E) cerrado de dimensión infinita y un subespacio denso en H(E) cuyos elementos no nulos son funciones de tipo no acotado. También se demuestra que el espacio de funciones holomorfas con la topología ? no es un límite inductivo numberable de espacios de Fréchet.

A unified framework for linear function approximation of value functions in stochastic control

This paper contributes with a unified formulation that merges previ- ous analysis on the prediction of the performance ( value function ) of certain sequence of actions ( policy ) when an agent operates a Markov decision process with large state-space. When the states are represented by features and the value function is linearly approxi- mated, our analysis reveals a new relationship between two common cost functions used to obtain the optimal approximation. In addition, this analysis allows us to propose an efficient adaptive algorithm that provides an unbiased linear estimate. The performance of the pro- posed algorithm is illustrated by simulation, showing competitive results when compared with the state-of-the-art solutions.

Monte Carlo limit cycle characterization

The fixed point implementation of IIR digital filters usually leads to the appearance of zero-input limit cycles, which degrade the performance of the system. In this paper, we develop an efficient Monte Carlo algorithm to detect and characterize limit cycles in fixed-point IIR digital filters. The proposed approach considers filters formulated in the state space and is valid for any fixed point representation and quantization function. Numerical simulations on several high-order filters, where an exhaustive search is unfeasible, show the effectiveness of the proposed approach.