Edge removal in random contact networks and the basic reproduction number

Understanding the effect of edge removal on the basic reproduction number ${\mathcal{R}_0}$ for disease spread on contact networks is important for disease management. The formula for the basic reproduction number ${\mathcal{R}_0}$ in random network SIR models of configuration type suggests that for degree distributions with large variance, a reduction of the average degree may actually increase ${\mathcal{R}_0}$ . To understand this phenomenon, we develop a dynamical model for the evolution of the degree distribution under random edge removal, and show that truly random removal always reduces ${\mathcal{R}_0}$ . The discrepancy implies that any increase in ${\mathcal{R}_0}$ must result from edge removal changing the network type, invalidating the use of the basic reproduction number formula for a random contact network. We further develop an epidemic model incorporating a contact network consisting of two groups of nodes with random intra- and inter-group connections, and derive its basic reproduction number. We then prove that random edge removal within either group, and between groups, always decreases the appropriately defined ${\mathcal{R}_0}$ . Our models also allow an estimation of the number of edges that need to be removed in order to curtail an epidemic.     

Epidemic models with uncertainty in the reproduction number

One of the first quantities to be estimated at the start of an epidemic is the basic reproduction number, ${\mathcal{R}_0}$ . The progress of an epidemic is sensitive to the value of ${\mathcal{R}_0}$ , hence we need methods for exploring the consequences of uncertainty in the estimate. We begin with an analysis of the SIR model, with ${\mathcal{R}_0}$ specified by a probability distribution instead of a single value. We derive probability distributions for the prevalence and incidence of infection during the initial exponential phase, the peaks in prevalence and incidence and their timing, and the final size of the epidemic. Then, by expanding the state variables in orthogonal polynomials in uncertainty space, we construct a set of deterministic equations for the distribution of the solution throughout the time-course of the epidemic. The resulting dynamical system need only be solved once to produce a deterministic stochastic solution. The method is illustrated with ${\mathcal{R}_0}$ specified by uniform, beta and normal distributions. We then apply the method to data from the New Zealand epidemic of H1N1 influenza in 2009. We apply the polynomial expansion method to a Kermack–McKendrick model, to simulate a forecasting system that could be used in real time. The results demonstrate the level of uncertainty when making parameter estimates and projections based on a limited amount of data, as would be the case during the initial stages of an epidemic. In solving both problems we demonstrate how the dynamical system is derived automatically via recurrence relationships, then solved numerically.     

Bone refilling in cortical basic multicellular units: insights into tetracycline double labelling from a computational model

Bone remodelling is carried out by ‘bone multicellular units’ ( $\text{ BMU }$ s) in which active osteoclasts and active osteoblasts are spatially and temporally coupled. The refilling of new bone by osteoblasts towards the back of the $\text{ BMU }$ occurs at a rate that depends both on the number of osteoblasts and on their secretory activity. In cortical bone, a linear phenomenological relationship between matrix apposition rate and $\text{ BMU }$ cavity radius is found experimentally. How this relationship emerges from the combination of complex, nonlinear regulations of osteoblast number and secretory activity is unknown. Here, we extend our previous mathematical model of cell development within a single cortical $\text{ BMU }$ to investigate how osteoblast number and osteoblast secretory activity vary along the $\text{ BMU }$ ’s closing cone. The mathematical model is based on biochemical coupling between osteoclasts and osteoblasts of various maturity and includes the differentiation of osteoblasts into osteocytes and bone lining cells, as well as the influence of $\text{ BMU }$ cavity shrinkage on osteoblast development and activity. Matrix apposition rates predicted by the model are compared with data from tetracycline double labelling experiments. We find that the linear phenomenological relationship observed in these experiments between matrix apposition rate and $\text{ BMU }$ cavity radius holds for most of the refilling phase simulated by our model, but not near the start and end of refilling. This suggests that at a particular bone site undergoing remodelling, bone formation starts and ends rapidly, supporting the hypothesis that osteoblasts behave synchronously. Our model also suggests that part of the observed cross-sectional variability in tetracycline data may be due to different bone sites being refilled by $\text{ BMU }$ s at different stages of their lifetime. The different stages of a $\text{ BMU }$ ’s lifetime (such as initiation stage, progression stage, and termination stage) depend on whether the cell populations within the $\text{ BMU }$ are still developing or have reached a quasi-steady state whilst travelling through bone. We find that due to their longer lifespan, active osteoblasts reach a quasi-steady distribution more slowly than active osteoclasts. We suggest that this fact may locally enlarge the Haversian canal diameter (due to a local lack of osteoblasts compared to osteoclasts) near the $\text{ BMU }$ ’s point of origin.     

Viral dynamics model with CTL immune response incorporating antiretroviral therapy

We present two HIV models that include the CTL immune response, antiretroviral therapy and a full logistic growth term for uninfected $\text{ CD4}^+$ T-cells. The difference between the two models lies in the inclusion or omission of a loss term in the free virus equation. We obtain critical conditions for the existence of one, two or three steady states, and analyze the stability of these steady states. Through numerical simulation we find substantial differences in the reproduction numbers and the behaviour at the infected steady state between the two models, for certain parameter sets. We explore the effect of varying the combination drug efficacy on model behaviour, and the possibility of reconstituting the CTL immune response through antiretroviral therapy. Furthermore, we employ Latin hypercube sampling to investigate the existence of multiple infected equilibria.     

Retention of Dissolved Inorganic Nitrogen by Foliage and Twigs of Four Temperate Tree Species

Nitrogen (N) retention by tree canopies is believed to be an important process for tree nutrient uptake, and its quantification is a key issue in determining the impact of atmospheric N deposition on forest ecosystems. Due to dry deposition and retention by other canopy elements, the actual uptake and assimilation by the tree canopy is often obscured in throughfall studies. In this study, ¹⁵N-labeled solutions ( $ ^{15} {\text{NH}}_{4}^{ + } $ and $ ^{15} {\text{NO}}_{3}^{ - } $ ) were used to assess dissolved inorganic N retention by leaves/needles and twigs of European beech, pedunculate oak, silver birch, and Scots pine saplings. The effects of N form, tree species, leaf phenology, and applied $ {\text{NO}}_{3}^{ - } $ to $ {\text{NH}}_{4}^{ + } $ ratio on the N retention were assessed. Retention patterns were mainly determined by foliar uptake, except for Scots pine. In twigs, a small but significant ¹⁵N enrichment was detected for $ {\text{NH}}_{4}^{ + } $ , which was found to be mainly due to physicochemical adsorption to the woody plant surface. The mean $ {{^{15} {\text{NH}}_{4}^{ + } } \mathord{\left/ {\vphantom {{^{15} {\text{NH}}_{4}^{ + } } {^{15} {\text{NO}}_{3}^{ - } }}} \right. \kern-0em} {^{15} {\text{NO}}_{3}^{ - } }} $ retention ratio varied considerably among species and phenological stadia, which indicates that the use of a fixed ratio in the canopy budget model could lead to an over- or underestimation of the total N retention. In addition, throughfall water under each branch was collected and analyzed for $ ^{15} {\text{NH}}_{4}^{ + } $ , $ ^{15} {\text{NO}}_{3}^{ - } $ , and all major ions. Net throughfall of $ ^{15} {\text{NH}}_{4}^{ + } $ was, on average, 20 times higher than the actual retention of $ ^{15} {\text{NH}}_{4}^{ + } $ by the plant material. This difference in $ ^{15} {\text{NH}}_{4}^{ + } $ retention could not be attributed to pools and fluxes measured in this study. The retention of $ ^{15} {\text{NH}}_{4}^{ + } $ was correlated with the net throughfall of K⁺, Mg²⁺, Ca²⁺, and weak acids during leaf development and the fully leafed period, while no significant relationships were found for $ ^{15} {\text{NO}}_{3}^{ - } $ retention. This suggests that the main driving factors for $ {\text{NH}}_{4}^{ + } $ retention might be ion exchange processes during the start and middle of the growing season and passive diffusion at leaf senescence. Actual assimilation or abiotic uptake of N through leaves and twigs was small in this study, for example, 1–5% of the applied dissolved ¹⁵N, indicating that the impact of canopy N retention from wet deposition on forest productivity and carbon sequestration is likely limited.     

Stability of a Stochastic Model of an SIR Epidemic with Vaccination

We prove almost sure exponential stability for the disease-free equilibrium of a stochastic differential equations model of an SIR epidemic with vaccination. The model allows for vertical transmission. The stochastic perturbation is associated with the force of infection and is such that the total population size remains constant in time. We prove almost sure positivity of solutions. The main result concerns especially the smaller values of the diffusion parameter, and describes the stability in terms of an analogue \(\mathcal{R}_\sigma\) of the basic reproduction number \(\mathcal{R}_0\) of the underlying deterministic model, with \(\mathcal{R}_\sigma \le \mathcal{R}_0\). We prove that the disease-free equilibrium is almost sure exponentially stable if \(\mathcal{R}_\sigma <1\).     

Transmission dynamics for vector-borne diseases in a patchy environment

In this paper, a mathematical model is derived to describe the transmission and spread of vector-borne diseases over a patchy environment. The model incorporates into the classic Ross–MacDonald model two factors: disease latencies in both hosts and vectors, and dispersal of hosts between patches. The basic reproduction number \(\mathcal{R }_0\) is identified by the theory of the next generation operator for structured disease models. The dynamics of the model is investigated in terms of \(\mathcal{R }_0\) . It is shown that the disease free equilibrium is asymptotically stable if \(\mathcal{R }_0<1\) , and it is unstable if \(\mathcal{R }_0>1\) ; in the latter case, the disease is endemic in the sense that the variables for the infected compartments are uniformly persistent. For the case of two patches, more explicit formulas for \(\mathcal{R }_0\) are derived by which, impacts of the dispersal rates on disease dynamics are also explored. Some numerical computations for \(\mathcal{R }_0\) in terms of dispersal rates are performed which show visually that the impacts could be very complicated: in certain range of the parameters, \(\mathcal{R }_0\) is increasing with respect to a dispersal rate while in some other range, it can be decreasing with respect to the same dispersal rate. The results can be useful to health organizations at various levels for setting guidelines or making policies for travels, as far as malaria epidemics is concerned.     

Head impact accelerations for brain strain-related responses in contact sports: a model-based investigation

Both linear \((\mathbf{a}_{\mathrm{lin}})\) and rotational \((\mathbf{a}_{\mathrm{rot}} )\) accelerations contribute to head impacts on the field in contact sports; however, they are often isolated in injury studies. It is critical to evaluate the feasibility of estimating brain responses using isolated instead of full degrees-of-freedom (DOFs) accelerations. In this study, we investigated the sensitivities of regional brain strain-related responses to resultant \(\mathbf{a}_{\mathrm{lin}}\) and \(\mathbf{a}_{\mathrm{rot}}\) as well as the relative contributions of these acceleration components to the responses via random sampling and linear regression using parameterized, triangulated head impacts with kinematic variable values based on on-field measurements. Two independently established and validated finite element models of the human head were employed to evaluate model-consistency and dependency in results: the Dartmouth Head Injury Model and Simulated Injury Monitor. For the majority of the brain, volume-weighted regional peak strain, strain rate, and von Mises stress accumulated from the simulation significantly correlated with the product of the magnitude and duration of \(\mathbf{a}_{\mathrm{rot}}\) , or effectively, the rotational velocity, but not to \(\mathbf{a}_{\mathrm{lin}}\) . Responses from \(\mathbf{a}_{\mathrm{rot}}\) -only were comparable to the full-DOF counterparts especially when normalized by injury-causing thresholds (e.g., volume fractions of large differences virtually diminished (i.e., \(<\) 1 %) at typical difference percentage levels of 1–4 % on average). These model-consistent results support the inclusion of both rotational acceleration magnitude and duration into kinematics-based injury metrics and demonstrate the feasibility of estimating strain-related responses from isolated \(\mathbf{a}_{\mathrm{rot}}\) for analyses of strain-induced injury relevant to contact sports without significant loss of accuracy, especially for the cerebrum.     

The average local ionization energy as a tool for identifying reactive sites on defect-containing model graphene systems

In a continuing effort to further explore the use of the average local ionization energy $ \overline{\mathrm{I}}\left( \mathbf{r} \right) $ as a computational tool, we have investigated how well $ \overline{\mathrm{I}}\left( \mathbf{r} \right) $ computed on molecular surfaces serves as a predictive tool for identifying the sites of the more reactive electrons in several nonplanar defect-containing model graphene systems, each containing one or more pentagons. They include corannulene (C₂₀H₁₀), two inverse Stone-Thrower-Wales defect-containing structures C₂₆H₁₂ and C₄₂H₁₆, and a nanotube cap model C₂₂H₆, whose end is formed by three fused pentagons. Coronene (C₂₄H₁₂) has been included as a reference planar defect-free graphene model. We have optimized the structures of these systems as well as several monohydrogenated derivatives at the B3PW91/6-31G* level, and have computed their $ \overline{\mathrm{I}}\left( \mathbf{r} \right) $ on molecular surfaces corresponding to the 0.001 au, 0.003 au and 0.005 au contours of the electronic density. We find that (1) the convex sides of the interior carbons of the nonplanar models are more reactive than the concave sides, and (2) the magnitudes of the lowest $ \overline{\mathrm{I}}\left( \mathbf{r} \right) $ surface minima (the $ {{\overline{\mathrm{I}}}_{{\mathrm{S}\text{,}\min }}} $ ) correlate well with the interaction energies for hydrogenation at these sites. These $ {{\overline{\mathrm{I}}}_{{\mathrm{S}\text{,}\min }}} $ values decrease in magnitude as the nonplanarity of the site increases, consistent with earlier studies. A practical benefit of the use of $ \overline{\mathrm{I}}\left( \mathbf{r} \right) $ is that a single calculation suffices to characterize the numerous sites on a large molecular system, such as graphene and defect-containing graphene models.

Long-term analysis of Hubbard Brook stable oxygen isotope ratios of streamwater and precipitation sulfate

In response to decreasing atmospheric emissions of sulfur (S) since the 1970s there has been a concomitant decrease in S deposition to watersheds in the Northeastern U.S. Previous study at the Hubbard Brook Experimental Forest, NH (USA) using chemical and isotopic analyzes ( $ \delta^{34} {\text{S}}_{{{\text{SO}}_{4} }} $ ) combined with modeling has suggested that there is an internal source of S within these watersheds that results in a net loss of S via sulfate in drainage waters. The current study expands these previous investigations by the utilization of δ¹⁸O analyzes of precipitation sulfate and streamwater sulfate. Archived stream and bulk precipitation samples at the Hubbard Brook Experimental Forest from 1968–2004 were analyzed for stable oxygen isotope ratios of sulfate ( $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ ). Overall decreasing temporal trends and seasonally low winter values of $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ in bulk precipitation are most likely attributed to similar trends in precipitation $ \delta^{18} {\text{O}}_{{{\text{H}}_{2} {\text{O}}}} $ values. Regional climate trends and changes in temperature control precipitation $ \delta^{18} {\text{O}}_{{{\text{H}}_{2} {\text{O}}}} $ values that are reflected in the $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ values of precipitation. The significant relationship between ambient temperature and the $ \delta^{18} {\text{O}}_{{{\text{H}}_{2} {\text{O}}}} $ values of precipitation is shown from a nearby site in Ottawa, Ontario (Canada). Although streamwater $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ values did not reveal temporal trends, a large difference between precipitation and streamwater $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ values suggest the importance of internal cycling of S especially through the large organic S pool and the concomitant effect on the $ \delta^{18} {\text{O}}_{{{\text{SO}}_{4} }} $ values in drainage waters.     

Enhanced accuracy of kinetic information from CT-CPMG experiments by transverse rotating-frame spectroscopy

Micro-to-millisecond motions of proteins transmit pivotal signals for protein function. A powerful technique for the measurement of these motions is nuclear magnetic resonance spectroscopy. One of the most widely used methodologies for this purpose is the constant-time Carr–Purcell–Meiboom–Gill (CT-CPMG) relaxation dispersion experiment where kinetic and structural information can be obtained at atomic resolution. Extraction of accurate kinetics determined from CT-CPMG data requires refocusing frequencies that are much larger than the nuclei’s exchange rate between states. We investigated the effect when fast processes are probed by CT-CPMG experiments via simulation and show that if the intrinsic relaxation rate $ \left( {R_{2,0}^{CT - CPMG} } \right) $ ( R 2 , 0 CT ? CPMG ) is not known a priori the extraction of accurate kinetics is hindered. Errors on the order of 50 % in the exchange rate are attained when processes become fast, but are minimized to 5 % with a priori $ R_{2,0}^{CT - CPMG} $ R 2 , 0 CT ? CPMG information. To alleviate this shortcoming, we developed an experimental scheme probing $ R_{2,0}^{CT - CPMG} $ R 2 , 0 CT ? CPMG with large amplitude spin-lock fields, which specifically contains the intrinsic proton longitudinal Eigenrelaxation rate. Our approach was validated with ubiquitin and the Oscillatoria agardhii agglutinin (OAA). For OAA, an underestimation of 66 % in the kinetic rates was observed if $ R_{2,0}^{CT - CPMG}\, $ R 2 , 0 CT ? CPMG is not included during the analysis of CT-CPMG data and result in incorrect kinetics and imprecise amplitude information. This was overcome by combining CT-CPMG with $ R_{2,0}^{CT - CPMG} $ R 2 , 0 CT ? CPMG measured with a high power R_1ρ experiment. In addition, the measurement of $ R_{2,0}^{CT - CPMG} $ R 2 , 0 CT ? CPMG removes the ambiguities in choosing between different models that describe CT-CPMG data.     

Forecasting the 2001 Foot-and-Mouth Disease Epidemic in the UK

Near real-time epidemic forecasting approaches are needed to respond to the increasing number of infectious disease outbreaks. In this paper, we retrospectively assess the performance of simple phenomenological models that incorporate early sub-exponential growth dynamics to generate short-term forecasts of the 2001 foot-and-mouth disease epidemic in the UK. For this purpose, we employed the generalized-growth model (GGM) for pre-peak predictions and the generalized-Richards model (GRM) for post-peak predictions. The epidemic exhibits a growth-decelerating pattern as the relative growth rate declines inversely with time. The uncertainty of the parameter estimates \( (r{\text{ and }}p) \) narrows down and becomes more precise using an increasing amount of data of the epidemic growth phase. Indeed, using only the first 10–15 days of the epidemic, the scaling of growth parameter (p) displays wide uncertainty with the confidence interval for p ranging from values ~ 0.5 to 1.0, indicating that less than 15 epidemic days of data are not sufficient to discriminate between sub-exponential (i.e., p < 1) and exponential growth dynamics (i.e., p = 1). By contrast, using 20, 25, or 30 days of epidemic data, it is possible to recover estimates of p around 0.6 and the confidence interval is substantially below the exponential growth regime. Local and national bans on the movement of livestock and a nationwide cull of infected and contiguous premises likely contributed to the decelerating trajectory of the epidemic. The GGM and GRM provided useful 10-day forecasts of the epidemic before and after the peak of the epidemic, respectively. Short-term forecasts improved as the model was calibrated with an increasing length of the epidemic growth phase. Phenomenological models incorporating generalized-growth dynamics are useful tools to generate short-term forecasts of epidemic growth in near real time, particularly in the context of limited epidemiological data as well as information about transmission mechanisms and the effects of control interventions.     

Longitudinal distribution of nitrate δ15N and δ18O in two contrasting tropical rivers: implications for instream nitrogen cycling

The longitudinal variations in the nitrogen (δ¹⁵N) and oxygen (δ¹⁸O) isotopic compositions of nitrate (NO₃ ^?), the carbon isotopic composition (δ¹³C) of dissolved inorganic carbon (DIC) and the δ¹³C and δ¹⁵N of particulate organic matter were determined in two Southeast Asian rivers contrasting in the watershed geology and land use to understand internal nitrogen cycling processes. The $ \delta^{15} {\text{N}}_{{{\text{NO}}_{3} }} $ became higher longitudinally in the freshwater reach of both rivers. The $ \delta^{18} {\text{O}}_{{{\text{NO}}_{3} }} $ also increased longitudinally in the river with a relatively steeper longitudinal gradient and a less cultivated watershed, while the $ \delta^{18} {\text{O}}_{{{\text{NO}}_{3} }} $ gradually decreased in the other river. A simple model for the $ \delta^{15} {\text{N}}_{{{\text{NO}}_{3} }} $ and the $ \delta^{18} {\text{O}}_{{{\text{NO}}_{3} }} $ that accounts for simultaneous input and removal of NO₃ ^? suggested that the dynamics of NO₃ ^? in the former river were controlled by the internal production by nitrification and the removal by denitrification, whereas that in the latter river was significantly affected by the anthropogenic NO₃ ^? loading in addition to the denitrification and/or assimilation. In the freshwater-brackish transition zone, heterotrophic activities in the river water were apparently elevated as indicated by minimal dissolved oxygen, minimal δ¹³C_DIC and maximal pCO₂. The δ¹⁵N of suspended particulate nitrogen (PN) varied in parallel to the $ \delta^{15} {\text{N}}_{{{\text{NO}}_{3} }} $ there, suggesting that the biochemical recycling processes (remineralization of PN coupled to nitrification, and assimilation of NO₃ ^?-N back to PN) played dominant roles in the instream nitrogen transformation. In the brackish zone of both rivers, the $ \delta^{15} {\text{N}}_{{{\text{NO}}_{3} }} $ displayed a declining trend while the $ \delta^{18} {\text{O}}_{{{\text{NO}}_{3} }} $ increased sharply. The redox cycling of NO₃ ^?/NO₂ ^? and/or deposition of atmospheric nitrogen oxides may have been the major controlling factor for the estuarine $ \delta^{15} {\text{N}}_{{{\text{NO}}_{3} }} $ and $ \delta^{18} {\text{O}}_{{{\text{NO}}_{3} }} $ , however, the exact mechanism behind the observed trends is currently unresolved.     

Convergence to genetically uniform state in stepping stone models of population genetics

We investigate continuous time stepping stone models. Extending the models treated in population genetics, we consider the system described by the following infinite dimensional stochastic differential equation, $$dx_k (t) = a_k (x_k )dB_k + \left\{ {\sum\limits_{j \in S} {q_{k,jXj} } } \right\}dt, k \in S$$ which contains the effects of random sampling drift and a kind of stochastic fluctuation in selection. We obtain a necessary and sufficient condition for the system to converge to a genetically uniform state.     

Assessing the condition of the Missouri, Ohio, and Upper Mississippi rivers (USA) using diatom-based indicators

Diatom-based indicators were developed to assess environmental conditions in the Missouri, Ohio, and Upper Mississippi rivers. Disturbance gradients, comprising the first two principal components derived from a suite of stressor variables, included a trophic gradient (Trophic) and a gradient reflecting agriculture and other development activities (Ag/Dev). Diatom-based indicators were developed by creating models using weighted average calibration and regression-based transfer functions to relate planktonic and periphytic diatom species assemblages to each disturbance gradient. The most predictive disturbance models combined phytoplankton and periphyton assemblages into a single bioindicator model (observed versus inferred: Trophic $ r_{\text{boot}}^{2} = 0. 5 6 $ ; Ag/Dev $ r_{\text{boot}}^{2} = 0. 7 0 $ ). The geographic applicability of bioindicators was assessed by limiting sample geographical range during model calibrations. Geographic scale was limited by creating bioindicators using samples from: (a) each river, and (b) combined Mississippi/Missouri samples excluding Ohio River sites which were chemically unique. Indicator performance decreased with geographically restrictive models, therefore river basin-wide models, developed across all three rivers, is recommended. The most effective diatom-based disturbance bioindicators for this great river ecosystem could be applied using phytoplankton, periphyton, or combined assemblages to infer both trophic and agriculture/development disturbances.     

Investigation of the possibility of exceeding the Greenwald density limit during ECRH in T-10

In T-10 experiments, attempts were made to significantly exceed the Greenwald limit $\bar n_{Gr} $ during high-power (P _ab=750 kW) electron-cyclotron resonance heating (ECRH) and gas puffing. Formally, the density limit $(\bar n_e )_{\lim } $ exceeding the Greenwald limit $({{(\bar n_e )_{\lim } } \mathord{\left/ {\vphantom {{(\bar n_e )_{\lim } } {\bar n_{Gr} }}} \right. \kern-0em} {\bar n_{Gr} }} = 1.8)$ was achieved for q _L=8.2. However, as q _L decreased, the ratio ${{(\bar n_e )_{\lim } } \mathord{\left/ {\vphantom {{(\bar n_e )_{\lim } } {\bar n_{Gr} }}} \right. \kern-0em} {\bar n_{Gr} }}$ also decreased, approaching unity at q _L≈3. It was suggested that the “current radius” (i.e., the radius of the magnetic surface enclosing the bulk of the plasma current I _p), rather than the limiter radius, was the parameter governing the value of $(\bar n_e )_{\lim } $ . In the ECRH experiments, no substantial degradation of plasma confinement was observed up to $\bar n_e \sim 0.9(\bar n_e )_{\lim } $ regardless of the ratio ${{(\bar n_e )_{\lim } } \mathord{\left/ {\vphantom {{(\bar n_e )_{\lim } } {\bar n_{Gr} }}} \right. \kern-0em} {\bar n_{Gr} }}$ . In different scenarios of the density growth up to $(\bar n_e )_{\lim } $ , two types of disruptions related to the density limit were observed.     

A New Generalized Logistic Sigmoid Growth Equation Compared with the Richards Growth Equation

A new sigmoid growth equation is presented for curve-fitting,analysis and simulation of growth curves. Like the logisticgrowth equation, it increases monotonically, with both upperand lower asymptotes. Like the Richards growth equation, itcan have its maximum slope at any value between its minimumand maximum. The new sigmoid equation is unique because it alwaystends towards exponential growth at small sizes or low densities,unlike the Richards equation, which only has this characteristicin part of its range. The new sigmoid equation is thereforeuniquely suitable for circumstances in which growth at smallsizes or low densities is expected to be approximately exponential,and the maximum slope of the growth curve can be at any value.Eleven widely different sigmoid curves were constructed withan exponential form at low values, using an independent algorithm.Sets of 100 variations of sequences of 20 points along eachcurve were created by adding random errors. In general, thenew sigmoid equation fitted the sequences of points as closelyas the original curves that they were generated from. The newsigmoid equation always gave closer fits and more accurate estimatesof the characteristics of the 11 original sigmoid curves thanthe Richards equation. The Richards equation could not estimatethe maximum intrinsic rate of increase (relative growth rate)of several of the curves. Both equations tended to estimatethat points of inflexion were closer to half the maximum sizethan was actually the case; the Richards equation underestimatedasymmetry by more than the new sigmoid equation. When the twoequations were compared by fitting to the example dataset thatwas used in the original presentation of the Richards growthequation, both equations gave good fits. The Richards equationis sometimes suitable for growth processes that may or may notbe close to exponential during initial growth. The new sigmoidis more suitable when initial growth is believed to be generallyclose to exponential, when estimates of maximum relative growthrate are required, or for generic growth simulations.Copyright1999 Annals of Botany Company Asymptote,Cucumis melo,curve-fitting, exponential growth, intrinsic rate of increase, logistic equation, maximum growth rate, model, non-linear least-squares regression, numerical algorithm, point of inflexion, relative growth rate, Richards growth equation, sigmoid growth curve.     

Provenance variation and genetic parameters of Eucalyptus viminalis in Argentina

Genetic parameters for growth, stem straightness, pilodyn penetration, relative bark thickness and survival were estimated in a base-population of five open-pollinated provenance/progeny trials of Eucalyptus viminalis. The trials, located in northern, central and southern Buenos Aires Province, Argentina, comprised 148 open-pollinated families from 13 Australian native provenances and eight local Argentinean seedlots. The Australian native provenances come from a limited range of the natural distribution. Overall survival, based on the latest assessment of each trial, was 62.4%. Single-site analyses showed that statistically significant provenances differences (p?<?0.05) for at least one of the studied traits in three out of the five trials analyzed. The local land race performed inconsistently in this study. The average narrow-sense individual-tree heritability estimate $ \left( {{{\hat{h}}^2}} \right) $ was 0.27 for diameter and 0.17 for total height. Values of $ {\hat{h}^2} $ also increased with age. Pilodyn penetration, assessed at only one site, was more heritable $ \left( {{{\hat{h}}^2} = 0.32} \right) $ than the average of growth traits. Estimated individual-tree heritabilities were moderate to low for stem straightness (average of 0.20) and relative bark thickness (0.16). The estimated additive genetic correlations $ \left( {{{{r}}_{{A}}}} \right) $ between diameter and height were consistently high and positive ( $ {{r}_{^A}} $ average of 0.90). High additive genetic correlations were observed between growth variables and pilodyn penetration ( $ {{r}_{^A}} $ average of 0.58). Relative bark thickness showed a negative correlation with diameter $ \left( {{{{r}}_{^A}} = - 0.39} \right) $ and height $ \left( {{{{r}}_{^A}} = - 0.51} \right) $ . The average estimated additive genetic correlation between sites was high for diameter (0.67). The implications of all these parameter estimates for genetic improvement of E. viminalis in Argentina are discussed.     

Towards a conceptualization of ETL and physical storage of semantic data warehouses as a service

The data warehouse technology has become the incontestable tool for businesses and organizations to make strategic decisions to ensure their competitively. The construction of a data warehouse ( $\mathcal{D}\mathcal{W}$ ) passes by selecting relevant information sources, extracting relevant data and loading them into the $\mathcal{D}\mathcal{W}$ . These processes require a precise expertise from designers related to logical and physical implementations of information sources, which is not usually an easy task. The diversity and heterogeneity of information sources makes the construction process of the $\mathcal{D}\mathcal{W}$ complex and time consuming. Domain ontologies have been proposed to reduce heterogeneity between sources, platforms, services, etc. They resolve syntax and semantic conflicts. The phenomenon of adopting domain ontologies by organizations creates a new type of databases, called semantic databases ( $\mathcal{S}\mathcal{D}\mathcal{B}$ ). As a consequence, they become a candidate for building the semantic $\mathcal{D}\mathcal{W}$ ( $\mathcal{S}\mathcal{D}\mathcal{W}$ ). To handle the diversity of information sources and hide the implementations aspects of sources, proposing a generic framework for constructing $\mathcal{D}\mathcal{W}$ becomes a necessity. In this paper, we first proposed an ontology-based approach for designing $\mathcal{S}\mathcal {D}\mathcal{B}$ . Secondly, ETL phases are defined at ontological level to hide the implementation details. Thirdly, a storage service for ontologies and its associated data is given. Finally, our proposal is validated through a case study and a tool.     

Topological classification and enumeration of RNA structures by genus

To an RNA pseudoknot structure is naturally associated a topological surface, which has its associated genus, and structures can thus be classified by the genus. Based on earlier work of Harer–Zagier, we compute the generating function $\mathbf{D}_{g,\sigma }(z)=\sum _{n}\mathbf{d}_{g,\sigma }(n)z^n$ for the number $\mathbf{d}_{g,\sigma }(n)$ of those structures of fixed genus $g$ and minimum stack size $\sigma $ with $n$ nucleotides so that no two consecutive nucleotides are basepaired and show that $\mathbf{D}_{g,\sigma }(z)$ is algebraic. In particular, we prove that $\mathbf{d}_{g,2}(n)\sim k_g\,n^{3(g-\frac{1}{2})} \gamma _2^n$ , where $\gamma _2\approx 1.9685$ . Thus, for stack size at least two, the genus only enters through the sub-exponential factor, and the slow growth rate compared to the number of RNA molecules implies the existence of neutral networks of distinct molecules with the same structure of any genus. Certain RNA structures called shapes are shown to be in natural one-to-one correspondence with the cells in the Penner–Strebel decomposition of Riemann’s moduli space of a surface of genus $g$ with one boundary component, thus providing a link between RNA enumerative problems and the geometry of Riemann’s moduli space.