On the Rate of Growth of the Population of the United States since 1790 and Its Mathematical Representation

Vaccination Criteria Based on Factors Influencing COVID-19 Diffusion and Mortality

SARS-CoV-2 is highly contagious, rapidly turned into a pandemic, and is causing a relevant number of critical to severe life-threatening COVID-19 patients. However, robust statistical studies of a large cohort of patients, potentially useful to implement a vaccination campaign, are rare. We analyzed public data of about 19,000 patients for the period 28 February to 15 May 2020 by several mathematical methods. Precisely, we describe the COVID-19 evolution of a number of variables that include age, gender, patient’s care location, and comorbidities. It prompts consideration of special preventive and therapeutic measures for subjects more prone to developing life-threatening conditions while affording quantitative parameters for predicting the effects of an outburst of the pandemic on public health structures and facilities adopted in response. We propose a mathematical way to use these results as a powerful tool to face the pandemic and implement a mass vaccination campaign. This is done by means of priority criteria based on the influence of the considered variables on the probability of both death and infection.

COVID-19 cumulative incidence, intensive care, and mortality in Italian regions compared to selected European countries

Background

The high contagiousness and rapid spreading of the coronavirus disease 2019 (COVID-19) has caused a high number of critical to severe life-threatening cases, which required urgent hospital admission and treatment in intensive care units (ICUs). The pandemic has been a tough test for all European national health systems and their capability to provide an adequate reaction.

Methods

The present work aims to reveal correlations between parameters such as COVID-19 incidence, ICU bed occupancy, ICU excess area, and mortality in Italian regions. Public data for the period of March 1 to July 16, 2020, were analyzed using several mathematical and statistical methods.

Results

The analysis defined two separate groups of Italian regions. The examined variables considered within these groups were interlinked and dependent on each other. The regions of the two groups shared the same kind of fitted model (linear) explaining mortality as a function of cumulative incidence, but with higher value of the constant in one group, so characterized by a high intrinsic “strength” of the pandemic, certainly playing a major role in the generation of a large number of severe and life-threatening cases. These results are confirmed at European level. Other factors may condition mortality and be linked to incidence, such as ICU saturation and excess.

Conclusions

These quantitative results could be a very helpful tool to set up preventive measures and optimize biomedical interventions before the pandemic, in its recurrent waves, could overcome the reaction capacity of any public health system.

Hidden Allee effect in photosynthetic organisms

In ecology and population biology, logistic equation is widely applied for simulating the population of organisms. By combining the logistic model with the low-density effect called Allee effect, several variations of mathematical expressions have been proposed. The upper half of the work was dedicated to establish a novel equation for highly flexible density effect model with Allee threshold. Allee effect has been rarely observed in microorganisms with asexual reproduction despite of theoretical studies. According to the exploitation ecosystem hypotheses, plants are believed to be insensitive to Allee effect. Taken together, knowledge on the existence of low-density effect in photosynthetic microorganisms is required for redefining the ecological theories emphasizing the photosynthetic organisms as the basis for food chains. Therefore, in the lower half of the present article, we report on the possible Allee effect in photo-autotrophic organisms, namely, green paramecia, and cyanobacteria. Optically monitored growth of green paramecia was shown to be regulated by Allee-like weak low-density effect under photo-autotrophic and photo-heterotrophic conditions. Insensitiveness of wild type cyanobacteria (Synechocystis sp. Strain PCC6803) to low-density effect was confirmed, as consistent with our empirical knowledge. In contrast, a mutant line of PCC6803 impaired with a photosynthesis-related pxcA gene was shown to be sensitive to typical Allee’s low-density effect (i.e. this line of cells failed to propagate at low cellular density while cells start logarithmic growth at relatively higher inoculating density). This is the first observation that single-gene mutation in an autotrophic organism alters the sensitivity to Allee effect.

Evaluation of the impact of body mass index on venous thromboembolism risk factors

In this paper, we investigate the interaction impacts of body mass index (BMI) on the other important risk factors for venous thromboembolism (VTE), using deep venous thrombosis (DVT) patient data from the International Warfarin Pharmacogenetics Consortium (IWPC). We apply eight machine learning techniques, including naive Bayes classifier (NB), support vector machine (SVM), elastic net regression (ENET), logistic regression (LR), lasso regression (LAR), multivariate adaptive regression splines (MARS), boosted regression tree (BRT) and random forest model (RF). The RF method is selected as the best model for classification. Out of 33 features considered in this study, we identify 12 variables as relatively important risk factors for VTE. Finally, we examine the interaction impacts of BMI on these important VTE risk factors. We conclude that the impacts of risk factors on VTE incidence are varying across different BMI groups, and the variations are different for different risk factors. Therefore the interaction impacts of BMI on the other risk factors have to be taken into account in order to better understand the incidence of VTE.

Estimation of Tree Heights in an Uneven-Aged, Mixed Forest in Northern Iran Using Artificial Intelligence and Empirical Models

The diameters and heights of trees are two of the most important components in a forest inventory. In some circumstances, the heights of trees need to be estimated due to the time and cost involved in measuring them in the field. Artificial intelligence models have many advantages in modeling nonlinear height–diameter relationships of trees, which sometimes make them more useful than empirical models in estimating the heights of trees. In the present study, the heights of trees in uneven-aged and mixed stands in the high elevation forests of northern Iran were estimated using an artificial neural network (ANN) model, an adaptive neuro-fuzzy inference system (ANFIS) model, and empirical models. A systematic sampling method with a 150 × 200 m network (0.1 ha area) was employed. The diameters and heights of 516 trees were measured to support the modeling effort. Using 10 nonlinear empirical models, the ANN model, and the ANFIS model, the relationship between height as a dependent variable and diameter as an independent variable was analyzed. The results show, according to R2, relative root mean square error (RMSE), and other model evaluation criteria, that there is a greater consistency between predicted height and observed height when using artificial intelligence models (R2 = 0.78; RMSE (%) = 18.49) than when using regression analysis (R2 = 0.68; RMSE (%) = 17.69). Thus, it can be said that these models may be better than empirical models for predicting the heights of common, commercially-important trees in the study area.

Logistic Models for Simulating the Growth of Plants by Defining the Maximum Plant Size as the Limit of Information Flow

Today, the Logistic equations are widely applied to simulate the population growth across a range of fields, chiefly, demography and ecology. Based on an assumption that growth-regulating factors within the Logistic model, namely, the rate of increase (r) and carrying capacity (K), can be considered as the functions reflecting the combination of the organism- and environment-specific parameters, here, we discussed the possible application of modified synthetic Logistic equations to the simulation of the changes in (1) population (density per volume) of photosynthetically growing free-living algae and (2) size (mass per individual) of higher plants, by newly composing r value as a function reflecting the photosynthetic activities. Since higher plants are multi-cellular organisms, a novel concept for the carrying capacity K must also be introduced. We brought the a priori assumption that information sharing amongst cells strongly influences the physiology of multi-cellular structures eventually defining the maximum size of plants, into view. A simplest form of 'synthetic organism' conformed to test this assumption is a linear chain of cells, and the first physiological phenomenon, modeled in this way, is growth. This combination of information flow along a chain, with exponential growth, produces a simple allotropic relationship. This relationship is compared with results for plants and is found to have excellent predictive power. This theory shows that fast-growing organisms, or multicellular structures, remain small, because of their inability to share information sufficiently quickly and, also, predicts determinate growth. The success of this simple model suggests, firstly, that the inclusion of information flows in theoretical physiology models, which have been, to date, dominated by energetic or metabolic assumptions, will be improved by incorporating information flows. Secondly, the application of more complex information theories, such as those of Shannon, to biological systems will offer deep insights into the mechanisms and control of intercellular communication.

Thinning Effects on the Tree Height–Diameter Allometry of Masson Pine (Pinus massoniana Lamb.)

The stem height–diameter allometric relationship is fundamental in determining forest and ecosystem structures as well as in estimating tree volume, biomass, and carbon stocks. Understanding the effects of silvicultural practices on tree height–diameter allometry is necessary for sustainable forest management, though the impact of measures such as thinning on the allometric relationship remain understudied. In the present study, the effects of thinning on tree height–diameter allometry were evaluated using Masson pine height and diameter growth data from a plantation experiment that included unthinned and thinned treatments with different intensities. To determine whether thinning altered the height–diameter allometry rhythm, the optimal height–diameter model was identified and dummy variable methods were used to investigate the differences among model parameters for different thinning treatments. Periodic (annual) allometric coefficients were calculated based on height and diameter increment data and were modeled using the generalized additive mixed model (GAMM) to further illustrate the response of tree height–diameter allometry to different thinning treatments over time. Significant differences were detected among the parameters of the optimal height–diameter model (power function) for different thinning treatments, which indicated that the pattern of the height–diameter allometry relationship of Masson pine was indeed altered by thinning treatments. Results also indicated a nonlinear trend in the allometric relationship through time which was significantly affected by thinning. The height–diameter allometric coefficient exhibited a unimodal convex bell curve with time in unthinned plots, and thinning significantly interfered with the original trend of the height–diameter allometric coefficient. Thinning caused trees to increase diameter growth at the expense of height growth, resulting in a decrease of the ratio of tree height to diameter, and this trend was more obvious as the thinning intensity increased.

Predicting translational progress in biomedical research

Fundamental scientific advances can take decades to translate into improvements in human health. Shortening this interval would increase the rate at which scientific discoveries lead to successful treatment of human disease. One way to accomplish this would be to identify which advances in knowledge are most likely to translate into clinical research. Toward that end, we built a machine learning system that detects whether a paper is likely to be cited by a future clinical trial or guideline. Despite the noisiness of citation dynamics, as little as 2 years of postpublication data yield accurate predictions about a paper's eventual citation by a clinical article (accuracy = 84%, F1 score = 0.56; compared to 19% accuracy by chance). We found that distinct knowledge flow trajectories are linked to papers that either succeed or fail to influence clinical research. Translational progress in biomedicine can therefore be assessed and predicted in real time based on information conveyed by the scientific community's early reaction to a paper.

Stress response and population dynamics: Is Allee effect hormesis?

Hormesis is a fundamental notion in ecotoxicology while competition between organisms is an essential notion in population ecology and species adaptation and evolution. Both sub-disciplines of ecology deal with the response of organisms to abiotic and biotic stresses. In ecotoxicology, the Linear-non-Threshold (LNT), Threshold and Hormetic models are used to describe the dominant responses of a plethora of endpoints to abiotic stress. In population ecology, the logistic, theta-logistic and the Allee effect models are used to describe the growth of populations under different responses to (biotic) stress induced by population density. The per capita rate of population increase (r) measures species fitness. When it is used as endpoint, the responses to population density seem to perfectly correspond to LNT, Threshold and Hormetic responses to abiotic stress, respectively. Our analysis suggests the Allee effect is a hormetic-like response of r to population density, an ultimate biotic stress. This biphasic dose-response model appears across different systems and situations (from molecules to tumor growth to population dynamics), is highly supported by ecological and evolutionary theory, and has important implications in most sub-disciplines of biology as well as in environmental and earth sciences. Joined multi-disciplinary efforts would facilitate the development and application of advanced research approaches for better understanding potential planetary-scale implications.

Kinetic Modeling and Techno-economic Feasibility of Ethanol Production From Carob Extract Based Medium in Biofilm Reactor

In this study, different carob extract-based media containing Medium A (included all ingredients), Medium B (included yeast extract and salts), Medium C (included (NH4)2SO4 and salts), Medium D (included only salts) and Medium E (included no ingredients) were evaluated for ethanol fermentation by Saccharomyces cerevisiae in a biofilm reactor and their results were used for kinetic modeling. The logistic model for cell growth, Luedeking-Piret model for ethanol production and Modified Luedeking-Piret model for substrate consumption were studied. Kinetic parameters were determined by fitting the observed values of the models. The findings indicated that the predicted data with the suggested kinetic model for each medium fitted very well the experimental data. Estimated kinetics were also in good agreement with experimental kinetics. The techno-economic analysis was performed with the unit costs of the components used in the medium and ethanol. Medium-based process economic feasibility proved carob extract-based Medium E and subsequently Medium D as most economical for ethanol production. The present study verified the potential of carob extract-based medium for increased economical production of ethanol. In conclusion, the ethanol production in a biofilm reactor is growth-associated since α (gP/gX) was greater than β (gP/gX.h) and Media D and E increased the economic production of carob extract-based ethanol.

Assessing the effect of density on population growth when modeling individual encounter data

The relative role of density-dependent and density-independent variation in vital rates and population size remains largely unsolved. Despite its importance to the theory and application of population ecology, and to conservation biology, quantifying the role and strength of density dependence is particularly challenging. We present a hierarchical formulation of the temporal symmetry approach, also known as the Pradel model, that permits estimation of the strength of density dependence from capture-mark-reencounter data. A measure of relative population size is built in the model and serves to detect density dependence directly on population growth rate. The model is also extended to account for temporal random variability in demographic rates, allowing estimation of the temporal variance of population growth rate unexplained by density dependence. We thus present a model-based approach that enable to test and quantify the effect of density-dependent and density-independent factors affecting population fluctuations in a single modeling framework. More generally, we use this modeling framework along with simulated and empirical data to show the value of including density dependence when modeling individual encounter data without the need for auxiliary data.

Organic Acid Content, Antioxidant Capacity, and Fermentation Kinetics of Matured Coconut (Cocos nucifera) Water Fermented by Saccharomyces cerevisiae D254

In this study, the quality of matured coconut water was improved through fermentation with Saccharomyces cerevisiae D254. During fermentation, the kinetic models of yeast growth, alcohol production, and sugar consumption were established based on logistic and Leudeking–Piret equations. Fructose, glucose, sucrose, total phenolic content, and antioxidant capacity (FRAP and ABTS values) were measured consecutively during fermentation. Results showed that R2 for the three models of yeast growth, alcohol production, and sugar consumption were 0.9772, 0.9983, and 0.9887, respectively. Total phenolic and antioxidant assays showed a similar evolution during fermentation, with a rapid increase in exponential phase and an unchanged trend in stationary phase. Moreover, total phenolic and the two antioxidant capacity methods were highly positively correlated. Pyruvic, lactic, citric, and succinic acids were the main organic acids in coconut water after fermentation.

Estimating dose-specific cell division and apoptosis rates from chemo-sensitivity experiments

In-vitro chemo-sensitivity experiments are an essential step in the early stages of cancer therapy development, but existing data analysis methods suffer from problems with fitting, do not permit assessment of uncertainty, and can give misleading estimates of cell growth inhibition. We present an approach (bdChemo) based on a mechanistic model of cell division and death that permits rigorous statistical analyses of chemo-sensitivity experiment data by simultaneous estimation of cell division and apoptosis rates as functions of dose, without making strong assumptions about the shape of the dose-response curve. We demonstrate the utility of this method using a large-scale NCI-DREAM challenge dataset. We developed an R package “bdChemo” implementing this method, available at https://github.com/YiyiLiu1/bdChemo.

Modeling the rheological behavior of thermosonic extracted guava, pomelo, and soursop juice concentrates at different concentration and temperature using a new combination model

This study has modeled the rheological behavior of thermosonic extracted pink-fleshed guava, pink-fleshed pomelo, and soursop juice concentrates at different concentrations and temperatures. The effects of concentration on consistency coefficient (K) and flow behavior index (n) of the fruit juice concentrates was modeled using a master curve which utilized the concentration-temperature shifting to allow a general prediction of rheological behaviors covering a wide concentration. For modeling the effects of temperature on K and n, the integration of two functions from the Arrhenius and logistic sigmoidal growth equations has provided a new model which gave better description of the properties. It also alleviated the problems of negative region when using the Arrhenius model alone. The fitted regression using this new model has improved coefficient of determination, R2 values above 0.9792 as compared to using the Arrhenius and logistic sigmoidal models alone, which presented minimum R2 of 0.6243 and 0.9440, respectively.

Practical applications

In general, juice concentrate is a better form of food for transportation, preservation, and ingredient. Models are necessary to predict the effects of processing factors such as concentration and temperature on the rheological behavior of juice concentrates. The modeling approach allows prediction of behaviors and determination of processing parameters. The master curve model introduced in this study simplifies and generalized rheological behavior of juice concentrates over a wide range of concentration when temperature factor is insignificant. The proposed new mathematical model from the combination of the Arrhenius and logistic sigmoidal growth models has improved and extended description of rheological properties of fruit juice concentrates. It also solved problems of negative values of consistency coefficient and flow behavior index prediction using existing model, the Arrhenius equation. These rheological data modeling provide good information for the juice processing and equipment manufacturing needs.

Microtiter miniature shaken bioreactor system as a scale-down model for process development of production of therapeutic alpha-interferon2b by recombinant Escherichia coli

Background

Demand for high-throughput bioprocessing has dramatically increased especially in the biopharmaceutical industry because the technologies are of vital importance to process optimization and media development. This can be efficiently boosted by using microtiter plate (MTP) cultivation setup embedded into an automated liquid-handling system. The objective of this study was to establish an automated microscale method for upstream and downstream bioprocessing of α-IFN2b production by recombinant Escherichia coli. The extraction performance of α-IFN2b by osmotic shock using two different systems, automated microscale platform and manual extraction in MTP was compared.

Results

The amount of α-IFN2b extracted using automated microscale platform (49.2 μg/L) was comparable to manual osmotic shock method (48.8 μg/L), but the standard deviation was 2 times lower as compared to manual osmotic shock method. Fermentation parameters in MTP involving inoculum size, agitation speed, working volume and induction profiling revealed that the fermentation conditions for the highest production of α-IFN2b (85.5 μg/L) was attained at inoculum size of 8%, working volume of 40% and agitation speed of 1000 rpm with induction at 4 h after the inoculation.

Conclusion

Although the findings at MTP scale did not show perfect scalable results as compared to shake flask culture, but microscale technique development would serve as a convenient and low-cost solution in process optimization for recombinant protein.

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji

Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10-19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak.

Contemporary Developments in Applied Demography within the United States

Changes in technology and methodological developments have significantly changed the field of applied demography in the U.S. over the last decade. These have been accompanied by alterations in perceptions of how the demographic perspective contributes to addressing public and private sector issues. This paper focuses on contemporary developments with the goal of identifying areas of future direction. Following a brief history of applied demography, recent developments are placed into five categories: training, including programs; courses and course materials; institutional structures such as the Population Association of America, the Southern Demographic Association and funding agencies; career opportunities in government, educational institutions and the private sector; technological developments in communication and data storage and retrieval; and methodological developments, such as GIS, that allow researchers to extract additional information from data. These developments provide an overall picture of applied demography in the U.S. early in the twenty-first century and provide ideas about the state of the art in applied demography in the near future.

Development and evaluation of height diameter at breast models for native Chinese Metasequoia

Accurate tree height and diameter at breast height (dbh) are important input variables for growth and yield models. A total of 5503 Chinese Metasequoia trees were used in this study. We studied 53 fitted models, of which 7 were linear models and 46 were non-linear models. These models were divided into two groups of single models and multivariate models according to the number of independent variables. The results show that the allometry equation of tree height which has diameter at breast height as independent variable can better reflect the change of tree height; in addition the prediction accuracy of the multivariate composite models is higher than that of the single variable models. Although tree age is not the most important variable in the study of the relationship between tree height and dbh, the consideration of tree age when choosing models and parameters in model selection can make the prediction of tree height more accurate. The amount of data is also an important parameter what can improve the reliability of models. Other variables such as tree height, main dbh and altitude, etc can also affect models. In this study, the method of developing the recommended models for predicting the tree height of native Metasequoias aged 50–485 years is statistically reliable and can be used for reference in predicting the growth and production of mature native Metasequoia.

Nitrogen Effect on Water-Soluble Polysaccharide Accumulation in Streblonema sp. (Ectocarpales, Phaeophyceae)

The water-soluble polysaccharides of brown algae attract the increasing attention of researchers as an important class of polymeric materials of biotechnological interest. The sole source for production of these polysaccharides has been large brown seaweeds such as members of Laminariales and Fucales. A new source of water-soluble polysaccharides is suggested here: it is a filamentous brown alga Streblonema sp., which can be cultivated under controlled conditions in photobioreactors that allow obtaining algal biomass with reproducible content and quality of polysaccharides. The accumulation of water-soluble polysaccharides can be stimulated by macronutrient limitation. In response to nitrogen deficiency, Streblonema sp. accumulated water-soluble polysaccharides (WSPs) rich in laminaran. WSP accumulation started after 3-4 days following nitrate depletion and reached a plateau at around day 7. Polysaccharide accumulation was related to cellular nitrogen content. The critical internal N level that triggered the onset of polysaccharide accumulation was 2.3% dry weight (DW); at a cellular N concentration less than 1.4% DW, the polysaccharide synthesis stopped. Upon nitrate re-supply, mobilization of WSP occurred after 3 days. These results suggest that a two-stage cultivation process could be used to obtain large algal biomass with high water-soluble polysaccharide production: a first cultivation stage using nitrate-supplemented medium to accumulate algal biomass followed by a second cultivation stage in a nitrate-free medium for 3 to 7 days to enhance polysaccharide content in the alga.

Hill equation and Hatze's muscle activation dynamics complement each other: enhanced pharmacological and physiological interpretability of modelled activity-pCa curves

In pharmacology, particularly receptor theory, the drug dose-effect relation of bio-active substances is frequently described by a sigmoidal function formulated by A.V. Hill. In biomechanics and muscle physiology then again, H. Hatze had elaborated a mathematical model for the stimulation- and length-dependent dynamics of the calcium-induced activation of mammalian skeletal muscle. Here, we prove that muscular activity-pCa curves described by the Hill equation and the equilibrium state predicted by Hatze's activation dynamics are equivalent. Thus, the exponent introduced by Hatze can be directly identified with its counterpart in the Hill equation, by which the former model gains further physiological interpretability. Conversely, the Hill constant can now be interpreted as a function of the fibre length, generally allowing for advanced Hill plots based on model ideas. We derive and examine the complementary relation of both model approaches, highlight the benefits of mutually viewing one approach from the perspective of the other, and address the physiology behind sigmoidal curves.

Carrying capacity in a heterogeneous environment with habitat connectivity

A large body of theory predicts that populations diffusing in heterogeneous environments reach higher total size than if non-diffusing, and, paradoxically, higher size than in a corresponding homogeneous environment. However, this theory and its assumptions have not been rigorously tested. Here, we extended previous theory to include exploitable resources, proving qualitatively novel results, which we tested experimentally using spatially diffusing laboratory populations of yeast. Consistent with previous theory, we predicted and experimentally observed that spatial diffusion increased total equilibrium population abundance in heterogeneous environments, with the effect size depending on the relationship between r and K. Refuting previous theory, however, we discovered that homogeneously distributed resources support higher total carrying capacity than heterogeneously distributed resources, even with species diffusion. Our results provide rigorous experimental tests of new and old theory, demonstrating how the traditional notion of carrying capacity is ambiguous for populations diffusing in spatially heterogeneous environments.

Height-diameter allometry and above ground biomass in tropical montane forests: Insights from the Albertine Rift in Africa

Tropical montane forests provide an important natural laboratory to test ecological theory. While it is well-known that some aspects of forest structure change with altitude, little is known on the effects of altitude on above ground biomass (AGB), particularly with regard to changing height-diameter allometry. To address this we investigate (1) the effects of altitude on height-diameter allometry, (2) how different height-diameter allometric models affect above ground biomass estimates; and (3) how other forest structural, taxonomic and environmental attributes affect above ground biomass using 30 permanent sample plots (1-ha; all trees ≥ 10 cm diameter measured) established between 1250 and 2600 m asl in Kahuzi Biega National Park in eastern Democratic Republic of Congo. Forest structure and species composition differed with increasing altitude, with four forest types identified. Different height-diameter allometric models performed better with the different forest types, as trees got smaller with increasing altitude. Above ground biomass ranged from 168 to 290 Mg ha^-1, but there were no significant differences in AGB between forests types, as tree size decreased but stem density increased with increasing altitude. Forest structure had greater effects on above ground biomass than forest diversity. Soil attributes (K and acidity, pH) also significantly affected above ground biomass. Results show how forest structural, taxonomic and environmental attributes affect above ground biomass in African tropical montane forests. They particularly highlight that the use of regional height-diameter models introduces significant biases in above ground biomass estimates, and that different height-diameter models might be preferred for different forest types, and these should be considered in future studies.

Kinetic interpretation of log-logistic dose-time response curves

A Hill-type time-response curve was derived using a single-step chemical kinetics approximation. The rate expression for the transformation is a differential equation that provides an interpolation formula between the logistic growth curve and second order kinetics. The solution is equivalent to the log-logistic cumulative distribution function with the time constant expressed in terms of a kinetic rate constant. This expression was extended to a full dose-time-response equation by postulating a concentration dependence for the rate constant. This was achieved by invoking a modified form of Haber's law that connects an observed toxic effect with the concentration of the active agent and the elapsed exposure time. Analysis showed that the concept of Concentration Addition corresponds to a special case where the rate constant for the overall transformation rate is proportional to the sum of the rate constants that apply when the agents act individually. Biodiesel "survival" curves were measured and used to test the applicability of the empirical model to describe the effects of inhibitor dosage and binary inhibitor mixtures. Positive results suggest that the proposed dose-response relationship for the toxicity of agents to organisms can be extended to inanimate systems especially in cases where accurate mechanistic models are lacking.

Optimal feed profile for the Rhamnolipid kinetic models by using Tabu search: metabolic view point

Rhamnolipids are bio surfactants which are extra-cellular glycolipids composed of l-rhamnose and 3-hydroxyalkanoics. Rhamnolipids are produced through fermentation process by using Pseudomonas sp. as the species. An alteration to the traditional procedures in order to achieve increase in the production of biosurfactants, a numerous process technologies have been adopted in fed batch mode. Fed batch mode facilitates the high production of product by avoiding the substrate or product inhibition line of attack. To overcome the controlling parameters which reduce the product yield, optimal control profiles are designed. In order to develop viable control methods for fed-batch fermentation of Rhamnolipid production, multiple substrate feeding strategies were employed and their efficiencies were compared with different substrates concentration of glucose, nitrogen and phosphorous. The product formation depends upon the substrate feeding strategy and so, the fed-batch fermentation was carried out by using P. aeruginosa providing substrates at manifold rates. With the obtained experimental data, using the kinetic models (logistic equation and by Luedeking Piret), the kinetic parameters were estimated. These kinetic parameters were implemented in tabu search algorithm and this programme was executed in Dev-C++, optimal control profiles were generated as a result. These obtained optimal control profiles have shown an increase in productivity of rhamnolipid with a decline in computational time. Through this procedure, the optimal control profiles of substrate feeding strategies of glucose, nitrogen and phosphorous were estimated. In comparison with other algorithms like genetic algorithm, Tabu Search algorithm was able to generate an accurate optimal control profiles with a reduction in their intricacy.

Expanded and Practical Use of Logistic Equations in Eco-Toxicity Evaluation: Cases of Lethal Metal Toxicity Curves in Green Paramecia with Minimal-Sized Experiments

In ecological systems, living organisms are surrounded by a number of chemicals, among which certain portion may be toxic to organisms. Therefore, from the environment-centric point of view, importance of accurate eco-toxicological analyses is increasing day-by-day. Eco-toxicity responses in animals and other organisms against chemicals can be scored by several parameters such as median lethal concentration (LC50) and median lethal dose (LD50), for examples. In the present study, we attempted to perform simulations of eco-toxicological nature of given chemicals based on limited data size (showing apparently incomplete curves of toxicity response) through model experiments performed with green paramecia (Paramecium bursaria) exposed to toxic metal ions, by using practically re-arranged logistic equation and Hill-type equations with an aid by graphical elucidation of Gauss-Newton algorithm determining the constants and/or coefficients.

Growth Functions and Culture History: A Perspective on Classic Maya Cultural Development

Using two kinds of asymptotic growth functions, the logistic and the Gompertz curves, the author argues that growth in the absolute numbers of Classic Maya temple centers in the lowlands was probably a process with built-in self-limitations. The logic of the two mathematical functions and the argument from the data provide a growth model embodying a simultaneous acceleration of growth and resistance to growth. After a statistical fitting of Sylvanus G. Morley's site data (drawn from The Ancient Maya, 1946), the model is compared against growth-limiting processes posited by the participants in a recent symposium on the collapse of Classic Maya civilization (Gordon R. Willey and Demitri B. Shimkin, "The Collapse of Classical Maya Civilization in the Southern Lowland: A Sym posium Summary Statement," Southwestern Journal of Anthropology 27: 1-18, 1971).

Determination and toxicity evaluation of the generated products in sulfamethoxazole degradation by UV/CoFe(2)O(4)/TiO(2)

The photodegradation of sulfamethoxazole (SMX) under UV radiation with a recyclable catalyst CoFe2O4/TiO2 was examined. The reaction mechanism during the treatment was determined. The toxicity of the degradation intermediates to aquatic organisms, including the green alga Chlorella vulgaris and the brine shrimp Artemia salina was investigated. SMX was completely removed and about 50% TOC was degraded in 5h. Sixteen intermediates were detected, from which four of them were reported for the first time in this study. Four main decay pathways, i.e., hydroxylation, cleavage of SN bond, nitration of amino group, and isomerization were proposed. About 45% of the total mass sulfur source transformed to sulfate ion, and around 25%, 1%, and 0.25% of the total nitrogen transformed to ammonium, nitrogen, and nitrite ions. The toxicity of the treated solution was significantly reduced compared to that of the parent compound SMX. A variation of the algae growth was observed, which was due to the combination of generation of toxic intermediates (i.e., sulfanilamide) and the release of inorganic substances and carbon source as additional nutrients. The adverse effect on the clearance rate of the brine shrimp was also observed, but it can be eliminated if longer degradation time is used.

Cyclin A2 promotes DNA repair in the brain during both development and aging

Various stem cell niches of the brain have differential requirements for Cyclin A2. Cyclin A2 loss results in marked cerebellar dysmorphia, whereas forebrain growth is retarded during early embryonic development yet achieves normal size at birth. To understand the differential requirements of distinct brain regions for Cyclin A2, we utilized neuroanatomical, transgenic mouse, and mathematical modeling techniques to generate testable hypotheses that provide insight into how Cyclin A2 loss results in compensatory forebrain growth during late embryonic development. Using unbiased measurements of the forebrain stem cell niche, we parameterized a mathematical model whereby logistic growth instructs progenitor cells as to the cell-types of their progeny. Our data was consistent with prior findings that progenitors proliferate along an auto-inhibitory growth curve. The growth retardation inCCNA2-null brains corresponded to cell cycle lengthening, imposing a developmental delay. We hypothesized that Cyclin A2 regulates DNA repair and that CCNA2-null progenitors thus experienced lengthened cell cycle. We demonstrate that CCNA2-null progenitors suffer abnormal DNA repair, and implicate Cyclin A2 in double-strand break repair. Cyclin A2's DNA repair functions are conserved among cell lines, neural progenitors, and hippocampal neurons. We further demonstrate that neuronal CCNA2 ablation results in learning and memory deficits in aged mice.

On the distribution of the time to extinction in the stochastic logistic population model

The aim of this paper is to investigate the distribution of the extinction times, T, of the stochastic logistic process from both the numerical and the theoretical standpoint. The problem is approached first by deriving formulae for the moments of T; it is then shown that in most cases T is, very nearly, a gamma variate. Some simulated results are given and these agree well with the theory. Furthermore, a consideration of the process conditioned on non-extinction is shown to be an effective way of obtaining a large t (time) description of the unconditioned process. Finally, a more general form of the model in which the death-rate as well as the birth-rate is ‘density-dependent' is considered, and by comparison with the usual form of the model the effect on T of this additional factor is assessed.

On the distribution of the time to extinction in the stochastic logistic population model

The aim of this paper is to investigate the distribution of the extinction times,T, of the stochastic logistic process from both the numerical and the theoretical standpoint. The problem is approached first by deriving formulae for the moments ofT; it is then shown that in most casesTis, very nearly, a gamma variate. Some simulated results are given and these agree well with the theory. Furthermore, a consideration of the process conditioned on non-extinction is shown to be an effective way of obtaining a larget(time) description of the unconditioned process. Finally, a more general form of the model in which the death-rate as well as the birth-rate is ‘density-dependent' is considered, and by comparison with the usual form of the model the effect onTof this additional factor is assessed.