Multispecies weed competition and their economic threshold on the wheat crop

Two field experiments were conducted to evaluate the effects of multispecies weed competition on wheat grain yield and to determine their economic threshold on the crop. The experiments were conducted in 2002, on two sites in Iran: at the Agricultural Research Station on Ferdowsi University of Mashhad (E1) and on the fields of Shirvan's Agricultural College (E2). A 15 x 50 m area of a 15 ha wheat field in E1 and a 15 x 50 m area of a 28 ha wheat field in E2 were selected as experimental sites. These areas were managed like other parts of the fields, except for the use of herbicides. At the beginning of the shooting stage, 30 points were randomly selected by dropping a 50 x 50 cm square marker on each site. The weeds present in E1 were: Avena ludoviciana, Chenopodium album, Solanum nigrum, Stellaria holostea, Convolvulus spp., Fumaria spp., Sonchus spp., and Polygonum aviculare. In E2 the weeds were A. ludoviciana, Erysimum sp., P. aviculare, Rapistrum rugosum, C. album, Salsola kali, and Sonchus sp. The data obtained within the sampled squares were submitted to regression equations and weeds densities were calculated in terms of TCL (Total Competitive Load). The regression analysis model indicated that only A. ludoviciana, Convolvulus spp. and C. album, in E1; and A. ludoviciana, S. kali, and R. rugosum, in E2 had a significant effect on the wheat yield reduction. Weed economic thresholds were 5.23 TCL in E1 and 6.16 TCL in E2; which were equivalent to 5 plants m-2 of A. ludoviciana or 12 plants m-2 of Convolvulus spp. or 19 plants m-2 of C. album in E1; and 6 plants m-2 A. ludoviciana, 13 plants m-2 S. kali and 27 plants m-2 R. rugosum in E2. Simulations of economic weed thresholds using several wheat grain prices and weed control costs allowed a better comparison of the experiments, suggesting that a more competitive crop at location E1 than at E2 was the cause of a lower weed competitive ability at the first location.

Adaptive value of ryegrass biotypes with low-level resistance and susceptible to the herbicide fluazifop and competitive ability with the wheat culture

Ryegrass is the main weed in wheat crop, causing yield loss due to competition by environmental resources. The objectives of this study were to estimate the fitness cost of ryegrass biotypes with low-level resistance and susceptible to fluazifop and to investigate the relative competitive ability of these biotypes between themselves and against the crop. Thus, fitness cost and competitive ability experiments were conducted under greenhouse conditions. For the fitness cost experiments, the low-level resistant ryegrass biotypes and those susceptible to fluazifop were used. For competitive ability, the treatments were arranged in a replacement series, with five proportions of the wheat cultivar FUNDACEP Horizonte and the low-level resistant and susceptible ryegrass biotypes 100:0, 75:25, 50:50, 25:75 and 0:100. Competitive analysis was carried out through diagrams applied to the replacement experiments and use of relative competitiveness indices. Variables evaluated were plant height, in the fitness cost experiment, and leaf area and shoot dry biomass in both experiments. The ryegrass biotypes show overall similar fitness cost and competitive ability. The wheat cultivar FUNDACEP Horizonte is superior in competitive ability to the ryegrass biotype with low-level resistance and equivalent to the susceptible biotype.

Adaptive control of Hydraulic Drive

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for the Hydraulic Drive. The calculation needed and the modeling were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™ etc. In the work there was applied the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial. The intelligent adaptive to nonlinearities algorithm for solving Lyapunov’s equation was developed. Developed algorithm works properly but considered plant is not met requirement of functioning with. The results showed confirmation that adaptive systems application significantly increases possibilities in use devices and might be used for correction a system’s behavior dynamics.

Tropical inselbergs: habitat types, adaptive strategies and diversity patterns

Inselbergs are isolated rock outcrops that rise abruptly above the surrounding plains. Granitic and gneissic inselbergs are geologically and geomorphologically old and occur throughout a broad spectrum of climatic zones. They form microclimatically and edaphically dry growth sites that support a highly specialized vegetation. Based on physiognomic criteria a number of habitat types can be distinguished that are widespread on inselbergs (e.g. ephemeral flush vegetation, monocotyledonous mats, rock pools). Three hot spots of global inselberg plant diversity can be identified which are both rich in species and endemics: a) southeastern Brazil, b) Madagascar and c) southwestern Australia.

Response threshold to aversive stimuli in stimulated early protein-malnourished rats

Two animal models of pain were used to study the effects of short-term protein malnutrition and environmental stimulation on the response threshold to aversive stimuli. Eighty male Wistar rats were used. Half of the pups were submitted to malnutrition by feeding their mothers a 6% protein diet from 0 to 21 days of age while the mothers of the other half (controls) were well nourished, receiving 16% protein. From 22 to 70 days all rats were fed commercial lab chow. Half of the animals in the malnourished and control groups were maintained under stimulating conditions, including a 3-min daily handling from 0 to 70 days and an enriched living cage after weaning. The other half was reared in a standard living cage. At 70 days, independent groups of rats were exposed to the shock threshold or to the tail-flick test. The results showed lower body and brain weights in malnourished rats when compared with controls at weaning and testing. In the shock threshold test the malnourished animals were more sensitive to electric shock and environmental stimulation increased the shock threshold. No differences due to diet or environmental stimulation were found in the tail-flick procedure. These results demonstrate that protein malnutrition imposed only during the lactation period is efficient in inducing hyperreactivity to electric shock and that environmental stimulation attenuates the differences in shock threshold produced by protein malnutrition

Effects of caffeine on time to exhaustion in exercise performed below and above the anaerobic threshold

Controversy still exists concerning the potential ergogenic benefit of caffeine (CAF) for exercise performance. The purpose of this study was to compare the effects of CAF ingestion on endurance performance during exercise on a bicycle ergometer at two different intensities, i.e., approximately 10% below and 10% above the anaerobic threshold (AT). Eight untrained males, non-regular consumers of CAF, participated in this study. AT, defined as the intensity (watts) corresponding to a lactate concentration of 4 mM, was determined during an incremental exercise test from rest to exhaustion on an electrically braked cycle ergometer. On the basis of these measurements, the subjects were asked to cycle until exhaustion at two different intensities, i.e., approximately 10% below and 10% above AT. Each intensity was performed twice in a double-blind randomized order by ingesting either CAF (5 mg/kg) or a placebo (PLA) 60 min prior to the test. Venous blood was analyzed for free fatty acid, glucose, and lactate, before, during, and immediately after exercise. Rating of perceived exertion and time to exhaustion were also measured during each trial. There were no differences in free fatty acids or lactate levels between CAF and PLA during and immediately after exercise for either intensity. Immediately after exercise glucose increased in the CAF trial at both intensities. Rating of perceived exertion was significantly lower (CAF = 14.1 ± 2.5 vs PLA = 16.6 ± 2.4) and time to exhaustion was significantly higher (CAF = 46.54 ± 8.05 min vs PLA = 32.42 ± 14.81 min) during exercise below AT with CAF. However, there was no effect of CAF treatment on rating of perceived exertion (CAF = 18.0 ± 2.7 vs PLA = 17.6 ± 2.3) and time to exhaustion (CAF = 18.45 ± 7.28 min vs PLA = 19.17 ± 4.37 min) during exercise above AT. We conclude that in untrained subjects caffeine can improve endurance performance during prolonged exercise performed below AT and that the decrease of perceived exertion can be involved in this process

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Determination of anaerobic threshold in rats using the lactate minimum test

The break point of the curve of blood lactate vs exercise load has been called anaerobic threshold (AT) and is considered to be an important indicator of endurance exercise capacity in human subjects. There are few studies of AT determination in animals. We describe a protocol for AT determination by the "lactate minimum test" in rats during swimming exercise. The test is based on the premise that during an incremental exercise test, and after a bout of maximal exercise, blood lactate decreases to a minimum and then increases again. This minimum value indicates the intensity of the AT. Adult male (90 days) Wistar rats adapted to swimming for 2 weeks were used. The initial state of lactic acidosis was obtained by making the animals jump into the water and swim while carrying a load equivalent to 50% of body weight for 6 min (30-s exercise interrupted by a 30-s rest). After a 9-min rest, blood was collected and the incremental swimming test was started. The test consisted of swimming while supporting loads of 4.5, 5.0, 5.5, 6.0 and 7.0% of body weight. Each exercise load lasted 5 min and was followed by a 30-s rest during which blood samples were taken. The blood lactate minimum was determined from a zero-gradient tangent to a spline function fitting the blood lactate vs workload curve. AT was estimated to be 4.95 ± 0.10% of body weight while interpolated blood lactate was 7.17 ± 0.16 mmol/l. These results suggest the application of AT determination in animal studies concerning metabolism during exercise.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.

Contrast sensitivity threshold measured by sweep-visual evoked potential in term and preterm infants at 3 and 10 months of age

Although healthy preterm infants frequently seem to be more attentive to visual stimuli and to fix on them longer than full-term infants, no difference in visual acuity has been reported compared to term infants. We evaluated the contrast sensitivity (CS) function of term (N = 5) and healthy preterm (N = 11) infants at 3 and 10 months of life using sweep-visual evoked potentials. Two spatial frequencies were studied: low (0.2 cycles per degrees, cpd) and medium (4.0 cpd). The mean contrast sensitivity (expressed in percentage of contrast) of the preterm infants at 3 months was 55.4 for the low spatial frequency (0.2 cpd) and 43.4 for the medium spatial frequency (4.0 cpd). At 10 months the low spatial CS was 52.7 and the medium spatial CS was 9.9. The results for the term infants at 3 months were 55.1 for the low spatial frequency and 34.5 for the medium spatial frequency. At 10 months the equivalent values were 54.3 and 14.4, respectively. No difference was found using the Mann-Whitney rank sum T-test between term and preterm infants for the low frequency at 3 or 10 months or for the medium spatial frequency at 3 or 10 months. The development of CS for the medium spatial frequency was equally fast for term and preterm infants. As also observed for visual acuity, CS was equivalent among term and preterm infants, suggesting that visual experience does not modify the development of the primary visual pathway. An earlier development of synapses in higher cortical visual areas of preterm infants could explain the better use of visual information observed behaviorally in these infants.

Effect of the aerobic capacity on the validity of the anaerobic threshold for determination of the maximal lactate steady state in cycling

The maximal lactate steady state (MLSS) is the highest blood lactate concentration that can be identified as maintaining a steady state during a prolonged submaximal constant workload. The objective of the present study was to analyze the influence of the aerobic capacity on the validity of anaerobic threshold (AT) to estimate the exercise intensity at MLSS (MLSS intensity) during cycling. Ten untrained males (UC) and 9 male endurance cyclists (EC) matched for age, weight and height performed one incremental maximal load test to determine AT and two to four 30-min constant submaximal load tests on a mechanically braked cycle ergometer to determine MLSS and MLSS intensity. AT was determined as the intensity corresponding to 3.5 mM blood lactate. MLSS intensity was defined as the highest workload at which blood lactate concentration did not increase by more than 1 mM between minutes 10 and 30 of the constant workload. MLSS intensity (EC = 282.1 ± 23.8 W; UC = 180.2 ± 24.5 W) and AT (EC = 274.8 ± 24.9 W; UC = 187.2 ± 28.0 W) were significantly higher in trained group. However, there was no significant difference in MLSS between EC (5.0 ± 1.2 mM) and UC (4.9 ± 1.7 mM). The MLSS intensity and AT were not different and significantly correlated in both groups (EC: r = 0.77; UC: r = 0.81). We conclude that MLSS and the validity of AT to estimate MLSS intensity during cycling, analyzed in a cross-sectional design (trained x sedentary), do not depend on the aerobic capacity.

Identification of anaerobic threshold using heart rate response during dynamic exercise

The objective of the present study was to characterize the heart rate (HR) patterns of healthy males using the autoregressive integrated moving average (ARIMA) model over a power range assumed to correspond to the anaerobic threshold (AT) during discontinuous dynamic exercise tests (DDET). Nine young (22.3 ± 1.57 years) and 9 middle-aged (MA) volunteers (43.2 ± 3.53 years) performed three DDET on a cycle ergometer. Protocol I: DDET in steps with progressive power increases of 10 W; protocol II: DDET using the same power values as protocol 1, but applied randomly; protocol III: continuous dynamic exercise protocol with ventilatory and metabolic measurements (10 W/min ramp power), for the measurement of ventilatory AT. HR was recorded and stored beat-to-beat during DDET, and analyzed using the ARIMA (protocols I and II). The DDET experiments showed that the median physical exercise workloads at which AT occurred were similar for protocols I and II, i.e., AT occurred between 75 W (116 bpm) and 85 W (116 bpm) for the young group and between 60 W (96 bpm) and 75 W (107 bpm) for group MA in protocols I and II, respectively; in two MA volunteers the ventilatory AT occurred at 90 W (108 bpm) and 95 W (111 bpm). This corresponded to the same power values of the positive trend in HR responses. The change in HR response using ARIMA models at submaximal dynamic exercise powers proved to be a promising approach for detecting AT in normal volunteers.

Comparison of anaerobic threshold determined by visual and mathematical methods in healthy women

Several methods are used to estimate anaerobic threshold (AT) during exercise. The aim of the present study was to compare AT obtained by a graphic visual method for the estimate of ventilatory and metabolic variables (gold standard), to a bi-segmental linear regression mathematical model of Hinkley's algorithm applied to heart rate (HR) and carbon dioxide output (VCO2) data. Thirteen young (24 ± 2.63 years old) and 16 postmenopausal (57 ± 4.79 years old) healthy and sedentary women were submitted to a continuous ergospirometric incremental test on an electromagnetic braking cycloergometer with 10 to 20 W/min increases until physical exhaustion. The ventilatory variables were recorded breath-to-breath and HR was obtained beat-to-beat over real time. Data were analyzed by the nonparametric Friedman test and Spearman correlation test with the level of significance set at 5%. Power output (W), HR (bpm), oxygen uptake (VO2; mL kg-1 min-1), VO2 (mL/min), VCO2 (mL/min), and minute ventilation (VE; L/min) data observed at the AT level were similar for both methods and groups studied (P > 0.05). The VO2 (mL kg-1 min-1) data showed significant correlation (P < 0.05) between the gold standard method and the mathematical model when applied to HR (r s = 0.75) and VCO2 (r s = 0.78) data for the subjects as a whole (N = 29). The proposed mathematical method for the detection of changes in response patterns of VCO2 and HR was adequate and promising for AT detection in young and middle-aged women, representing a semi-automatic, non-invasive and objective AT measurement.

Sodium taste threshold in children and its relationship to blood pressure

Popular science has emphasized the risks of high sodium intake and many studies have confirmed that salt intake is closely related to hypertension. The present mini-review summarizes experiments about salt taste sensitivity and its relationship with blood pressure (BP) and other variables of clinical and familial relevance. Children and adolescents from control parents (N = 72) or with at least one essential hypertensive (EHT) parent (N = 51) were investigated. Maternal questionnaires on eating habits and vomiting episodes were collected. Offspring, anthropometric, BP, and salt taste sensitivity values were recorded and blood samples analyzed. Most mothers declared that they added "little salt" when cooking. Salt taste sensitivity was inversely correlated with systolic BP (SBP) in control youngsters (r = -0.33; P = 0.015). In the EHT group, SBP values were similar to control and a lower salt taste sensitivity threshold. Obese offspring of EHT parents showed higher SBP and C-reactive protein values but no differences in renin-angiotensin-aldosterone system activity. Salt taste sensitivity was correlated with SBP only in the non-obese EHT group (N = 41; r = 0.37; P = 0.02). Salt taste sensitivity was correlated with SBP in healthy, normotensive children and adolescents whose mothers reported significant vomiting during the first trimester (N = 18; r = -0.66; P < 0.005), but not in "non-vomiter offspring" (N = 54; r = -0.18; nonsignificant). There is evidence for a linkage between high blood pressure, salt intake and sensitivity, perinatal environment and obesity, with potential physiopathological implications in humans. This relationship has not been studied comprehensively using homogeneous methods and therefore more research is needed in this field.