Estimating Bat and Bird Mortality Occurring at Wind Energy Turbines from Covariates and Carcass Searches Using Mixture Models

Environmental impacts of wind energy facilities increasingly cause concern, a central issue being bats and birds killed by rotor blades. Two approaches have been employed to assess collision rates: carcass searches and surveys of animals prone to collisions. Carcass searches can provide an estimate for the actual number of animals being killed but they offer little information on the relation between collision rates and, for example, weather parameters due to the time of death not being precisely known. In contrast, a density index of animals exposed to collision is sufficient to analyse the parameters influencing the collision rate. However, quantification of the collision rate from animal density indices (e.g. acoustic bat activity or bird migration traffic rates) remains difficult. We combine carcass search data with animal density indices in a mixture model to investigate collision rates. In a simulation study we show that the collision rates estimated by our model were at least as precise as conventional estimates based solely on carcass search data. Furthermore, if certain conditions are met, the model can be used to predict the collision rate from density indices alone, without data from carcass searches. This can reduce the time and effort required to estimate collision rates. We applied the model to bat carcass search data obtained at 30 wind turbines in 15 wind facilities in Germany. We used acoustic bat activity and wind speed as predictors for the collision rate. The model estimates correlated well with conventional estimators. Our model can be used to predict the average collision rate. It enables an analysis of the effect of parameters such as rotor diameter or turbine type on the collision rate. The model can also be used in turbine-specific curtailment algorithms that predict the collision rate and reduce this rate with a minimal loss of energy production.

Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data

Understanding how aquatic species grow is fundamental in fisheries because stock assessment often relies on growth dependent statistical models. Length-frequency-based methods become important when more applicable data for growth model estimation are either not available or very expensive. In this article, we develop a new framework for growth estimation from length-frequency data using a generalized von Bertalanffy growth model (VBGM) framework that allows for time-dependent covariates to be incorporated. A finite mixture of normal distributions is used to model the length-frequency cohorts of each month with the means constrained to follow a VBGM. The variances of the finite mixture components are constrained to be a function of mean length, reducing the number of parameters and allowing for an estimate of the variance at any length. To optimize the likelihood, we use a minorization–maximization (MM) algorithm with a Nelder–Mead sub-step. This work was motivated by the decline in catches of the blue swimmer crab (BSC) (Portunus armatus) off the east coast of Queensland, Australia. We test the method with a simulation study and then apply it to the BSC fishery data.

Segregation predictions for a binary mixture of granular material under flow conditions in a continuum mechanics framework

Abstract not available

Studies on terpenes solubility in water and deep eutectic solvents diagrams for biomedical applications

The main objectives of this work are the measurement of terpenes solubility in water at different temperatures, and the formulation of Deep Eutectic Solvents based on choline chloride and polycarboxylic acids, that can be used as hydrotropes of aqueous solutions in terpenes, replacing conventional organic solvents. In this work a new experimental methodology was implemented, using dialysis membranes, for the measurement of terpenes solubility in water. Concerning the deep eutectic diagrams formulation, the determination of the melting points of the eutectic mixtures was performed using a visual method. The method used for determining solubilities was previously validated using a well-studied model compound, toluene. The experimental results of terpenes solubilities in water resulted in a very satisfactory coefficients of variation, always below 6%. The experimental solubility data were analysed and the temperature dependence is also studied in a thermodynamic perspective. The compound with the largest solubility dependence with the temperature is geraniol, while thymol presents the smallest. The phase diagrams of DES formulated were quite satisfactory, presenting always eutectic points below to 373.15 K. For some compositions, the systems composed by choline chloride and lactic, or malonic, or myristic acid were liquid at room temperature. In the case of monocarboxylic acids, eutectic is formed at 60% mol of the acid, to dicarboxylic acid is formed at 50% mol of the acid and for tricarboxylic acid these point is formed at 30% mol of the acid. In the future, it will be important to study the effect of DES as hydrotropes in aqueous solutions of terpenes. Furthermore, it would be interesting to study more terpenes in order to assess the effect of the size of the alkyl chain and the structures of the compounds.

Validation of neurobehavioral studies for evaluating the perinatal effects of single and mixture exposure to pesticides.

2009

Synthesis of 3,5-Disubstituted Isoxazoles and Isoxazolines in Deep Eutectic Solvents

The synthesis of different 3,5-disubstituted isoxazoles and related isoxazolines using choline chloride:urea as deep eutectic solvent (DES) in a one-pot three step reaction has been accomplished successfully. The use of highly nucleophilic functionalized DES did not affect the process where highly electrophilic reagents or intermediates are involved. The presence of DES showed to be essential since the reaction in absence of this media did not proceed. The DES media could be reused up to five times without a detrimental effect on the yield of the reaction. To exemplify the synthetic potential of this methodology, the reaction was scaled up to the gram scale without any noticeable problem. Finally, different isoxazoles were easily transformed into β-aminoenones.

Application of Mixture Models to Survival Data

Survival models are being widely applied to the engineering field to model time-to-event data once censored data is here a common issue. Using parametric models or not, for the case of heterogeneous data, they may not always represent a good fit. The present study relays on critical pumps survival data where traditional parametric regression might be improved in order to obtain better approaches. Considering censored data and using an empiric method to split the data into two subgroups to give the possibility to fit separated models to our censored data, we’ve mixture two distinct distributions according a mixture-models approach. We have concluded that it is a good method to fit data that does not fit to a usual parametric distribution and achieve reliable parameters. A constant cumulative hazard rate policy was used as well to check optimum inspection times using the obtained model from the mixture-model, which could be a plus when comparing with the actual maintenance policies to check whether changes should be introduced or not.

Humified fraction of organic matter due to plant mixture cultivation.

The aim of this study was to assess the organic matter changes in quantity and quality, particularly of the humic fraction in the surface layer (0?20 cm), of a Typic Plinthustalf soil under different management of plant mixtures used as green manure for mango (Mangifera indica L.) crops. The plant mixtures, which were seeded between rows of mango trees, were formed by two groups of leguminous and non -leguminous plants. Prior to sowing, seeds were combined in different proportions and compositions constituting the following treatments: 100% non-leguminous species (NL); 100% leguminous species (L); 75% L and 25% NL; 50% L and 50% NL; 25% L and 75% NL; and 100% spontaneous vegetation, considered a control. The plant mixtures that grew between rows of mango trees caused changes in the chemical composition of the soil organic matter, especially for the treatments 50% L and 50% NL and 25% L and 75% NL, which increased the content of humic substances in the soil organic matter. However, the treatment 25% L and 75% NL was best at minimising loss of total organic carbon from the soil. The humic acids studied have mostly aliphatic characteristics, showing large amounts of carboxylic and nitrogen groups and indicating that most of the organic carbon was formed by humic substances, with fulvic acid dominating among the alkali soluble fractions.

Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.

CO2 utilization and alternative solvents: effective tools for sustainable applications

The growing concentration of CO2 in the atmosphere and its harmful consequences has led the scientific community to direct its efforts towards sustainable processes. Among the possible approaches, the use of CO2 and alternative solvents are two strategies that are having widespread diffusion. In this work the reuse of CO2 is expressed by using it as a reaction reagent and as trigger to change the physical properties of a catalyst thus facilitating its recovery. As regards the CO2 use as reagent, two catalytic systems have been developed for the conversion of CO2 and epoxides into cyclic carbonates, used in the synthesis of polymers and as aprotic solvents. Homogeneous catalysts made by choline-based eutectic mixtures and heterogeneous catalysts made from biopolymers and waste pyrolysis have been synthesized and tested on this reaction. The carbonate interchange reaction (CIR) of a diol with a linear carbonate (as dimethyl carbonate) is an interesting alternative, for the synthesis of cyclic carbonates; as the second application of CO2 as polarity trigger, it was used for catalyst recovery. In fact DBU, here used as catalyst, is part of the so called “switchable solvents”: they can pass from a less-polar to a more-polar form (and from being soluble to non-soluble in the reaction mixture) when reacting with CO2 in presence of water or alcohols. Also in this case, heterogeneous catalysts made from biopolymers and waste pyrolysis have been synthesized and tested on CIR. As for the use of alternative solvents, this work focuses on the use of Deep Eutectic Solvents (DESs). They are a new generation of solvents composed by a mixture of two or more substances, liquid at room temperature, and non-volatile. New and biobased DESs were here used: i) as reaction media to carry out chemoenzymatic epoxidation; ii) in the extraction of astaxanthin from microalgae culture.

Neutralisation Of The Pharmacological Activities Of Bothrops Alternatus Venom By Anti-pla2 Iggs.

Basic phospholipases A2 (PLA2) are toxic and induce a wide spectrum of pharmacological effects, although the acidic enzyme types are not lethal or cause low lethality. Therefore, it is challenging to elucidate the mechanism of action of acidic phospholipases. This study used the acidic non-toxic Ba SpII RP4 PLA2 from Bothrops alternatus as an antigen to develop anti-PLA2 IgG antibodies in rabbits and used in vivo assays to examine the changes in crude venom when pre-incubated with these antibodies. Using Ouchterlony and western blot analyses on B. alternatus venom, we examined the specificity and sensitivity of phospholipase A2 recognition by the specific antibodies (anti-PLA2 IgG). Neutralisation assays using a non-toxic PLA2 antigen revealed unexpected results. The (indirect) haemolytic activity of whole venom was completely inhibited, and all catalytically active phospholipases A2 were blocked. Myotoxicity and lethality were reduced when the crude venom was pre-incubated with anti-PLA2 immunoglobulins. CK levels in the skeletal muscle were significantly reduced at 6 h, and the muscular damage was more significant at this time-point compared to 3 and 12 h. When four times the LD50 was used (224 μg), half the animals treated with the venom-anti PLA2 IgG mixture survived after 48 h. All assays performed with the specific antibodies revealed that Ba SpII RP4 PLA2 had a synergistic effect on whole-venom toxicity. IgG antibodies against the venom of the Argentinean species B. alternatus represent a valuable tool for elucidation of the roles of acidic PLA2 that appear to have purely digestive roles and for further studies on immunotherapy and snake envenoming in affected areas in Argentina and Brazil.

Inhibitory Effects Of A Cured Antibacterial Bonding System On Viability And Metabolic Activity Of Oral Bacteria.

To evaluate the antimicrobial efficacy of Clearfil SE Protect (CP) and Clearfil SE Bond (CB) after curing and rinsed against five individual oral microorganisms as well as a mixture of bacterial culture prepared from the selected test organisms. Bacterial suspensions were prepared from single species of Streptococcus mutans, Streptococcus sobrinus, Streptococcus gordonii, Actinomyces viscosus and Lactobacillus lactis, as well as mixed bacterial suspensions from these organisms. Dentin bonding system discs (6 mm×2 mm) were prepared, cured, washed and placed on the bacterial suspension of single species or multispecies bacteria for 15, 30 and 60 min. MTT, Live/Dead bacterial viability (antibacterial effect), and XTT (metabolic activity) assays were used to test the two dentin system's antibacterial effect. All assays were done in triplicates and each experiment repeated at least three times. Data were submitted to ANOVA and Scheffe's f-test (5%). Greater than 40% bacteria killing was seen within 15 min, and the killing progressed with increasing time of incubation with CP discs. However, a longer (60 min) period of incubation was required by CP to achieve similar antimicrobial effect against mixed bacterial suspension. CB had no significant effect on the viability or metabolic activity of the test microorganisms when compared to the control bacterial culture. CP was significantly effective in reducing the viability and metabolic activity of the test organisms. The results demonstrated the antimicrobial efficacy of CP both on single and multispecies bacterial culture. CP may be beneficial in reducing bacterial infections in cavity preparations in clinical dentistry.

Direct Visualization Of The Action Of Triton X-100 On Giant Vesicles Of Erythrocyte Membrane Lipids.

The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. In fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. The shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. The Ld domains are then separated from the original vesicle and completely solubilized by TX-100. The insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngomyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.

The Crystal-t Algorithm: A New Approach To Calculate The Sle Of Lipidic Mixtures Presenting Solid Solutions.

Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.