Growth of Palm Trees and Woods in the Urban Environment

Trees in the urban environment provide several ecosystem benefits to the population, such as decreasing temperature, increasing humidity, shading, improving air quality, as well as physical and mental well-being. These can be enhanced through the knowledge of the growth of the trees in function of the characteristics of the place where they are inserted. Thus, the objective was to estimate the growth in diameter, height and volume of forest species in the urban environment, in Viçosa, Minas Gerais, Brazil. For this, woody individuals and palm trees present in the urban afforestation of the headquarters campus of the Federal University of Viçosa were selected based on age and had their diameter, breast height and height measured. Allometric equations specific to the study site were used to estimate their volume, and through the relationship with age, the average annual increment was obtained. Woody individuals showed a growth rate in volume of 0,0279 ± 0,0274 m³ year-1 and palm trees, 0,0139 ± 0,0119 m³ year-1. The differences in the average annual increase in volume found between woody individuals and palm trees may be due to morphological differences that affect the secondary growth of individuals. The growth rate of trees in the urban environment is higher when compared to those in forest fragments and experimental plantings. The decrease in growth rates with increasing age was expected due to the relationship between them being of the non-linear type, following a sigmoidal model.

Testing for a Sweet Spot in Randomized Trials

Introduction Randomized trials recruit diverse patients, including some individuals who may be unresponsive to the treatment. Here we follow up on prior conceptual advances and introduce a specific method that does not rely on stratification analysis and that tests whether patients in the intermediate range of disease severity experience more relative benefit than patients at the extremes of disease severity (sweet spot). Methods We contrast linear models to sigmoidal models when describing associations between disease severity and accumulating treatment benefit. The Gompertz curve is highlighted as a specific sigmoidal curve along with the Akaike information criterion (AIC) as a measure of goodness of fit. This approach is then applied to a matched analysis of a published landmark randomized trial evaluating whether implantable defibrillators reduce overall mortality in cardiac patients ( n = 2,521). Results The linear model suggested a significant survival advantage across the spectrum of increasing disease severity (β = 0.0847, P < 0.001, AIC = 2,491). Similarly, the sigmoidal model suggested a significant survival advantage across the spectrum of disease severity (α = 93, β = 4.939, γ = 0.00316, P < 0.001 for all, AIC = 1,660). The discrepancy between the 2 models indicated worse goodness of fit with a linear model compared to a sigmoidal model (AIC: 2,491 v. 1,660, P < 0.001), thereby suggesting a sweet spot in the midrange of disease severity. Model cross-validation using computational statistics also confirmed the superior goodness of fit of the sigmoidal curve with a concentration of survival benefits for patients in the midrange of disease severity. Conclusion Systematic methods are available beyond simple stratification for identifying a sweet spot according to disease severity. The approach can assess whether some patients experience more relative benefit than other patients in a randomized trial. [Box: see text]

Mild Pretreatments to Increase Fructose Consumption in Saccharomyces cerevisiae Wine Yeast Strains

The present research investigates the effect of different pretreatments on glucose and fructose consumption and ethanol production by four Saccharomyces cerevisiae wine strains, three isolated and identified from different wine regions in Turkey and one reference strain. A mild stress temperature (45 °C, 1 h) and the presence of ethanol (14% v/v) were selected as pretreatments applied to cell cultures prior to the fermentation step in synthetic must. The goodness fit of the mathematical models was estimated: linear, exponential decay function and sigmoidal model were evaluated with the model parameters R2 (regression coefficient), RMSE (root mean square error), MBE (mean bias error) and χ2 (reduced Chi-square). Sigmoidal function was determined as the most suitable model with the highest R2 and lower RMSE values. Temperature pretreatment allowed for an increase in fructose consumption rate by two strains, evidenced by a t90 value 10% lower than the control. One of the indigenous strains showed particular promise for mild temperature treatment (45 °C, 1 h) prior to the fermentation step to reduce residual glucose and fructose in wine. The described procedure may be effective for indigenous yeasts in preventing undesirable sweetness in wines.

The Master-Curve Band considering Measurement and Modeling Uncertainty for Bituminous Materials

This paper proposes using the master-curve band (MCB) to incorporate the unavoidable measurement errors and modeling uncertainty into the bitumen master-curve construction. In general, the rheological property of bitumen within the linear viscoelastic region is characterized by the master curve of modulus and/or phase angle, provided that the bitumen complies with the time-temperature superposition principle (TTSP). However, the master-curve construction is essentially a mathematical fitting process regardless of whether or not the original data is perfect enough to fit. For this reason, the MCB was introduced to consider the uncertainty information instead of a single master curve. Rheological data of four kinds of bitumen including unaged and aged bitumen were used to construct the MCBs. The results indicated that the generalized sigmoidal model showed the widest master-curve band, followed by Christensen-Anderson-Marasteanu (CAM) and CAM ( G g ) models. The width of MCB was a useful tool to identify the sensitivity of bitumen to rheological models. The sensitivity of bitumen to rheological models is associated with the number of active parameters in rheological models and model parameters’ confidence intervals. The construction of an MCB was beneficial to select the rheological models. Accordingly, the CAM ( G g ) model is proved to be the best to analyze the aging effects.

Study of patterned GaAsSbN nanowires using sigmoidal model

This study presents the first report on patterned nanowires (NWs) of dilute nitride GaAsSbN on p-Si (111) substrates by self-catalyzed plasma-assisted molecular beam epitaxy. Patterned NW array with GaAsSbN of Sb composition of 3% as a stem provided the best yield of vertical NWs. Large bandgap tuning of ~ 75 meV, as ascertained from 4 K photoluminescence (PL), over a pitch length variation of 200–1200 nm has been demonstrated. Pitch-dependent axial and radial growth rates show a logistic sigmoidal growth trend different from those commonly observed in other patterned non-nitride III–V NWs. The sigmoidal fitting provides further insight into the PL spectral shift arising from differences in Sb and N incorporation from pitch induced variation in secondary fluxes. Results indicate that sigmoidal fitting can be a potent tool for designing patterned NW arrays of optimal pitch length for dilute nitrides and other highly mismatched alloys and heterostructures.

Modelos cinéticos sigmoidales aplicados al crecimiento de Saccharomyces boulardii

Predictive microbiology is an interesting tool that allows evaluating the behavior of biomass and metabolites in different culture media, providing multiple benefits, whether scientific or industrial, for these and other reasons the objective of this research was to evaluate applied sigmoidal kinetic models to the growth of Saccharomyces boulardii in milk. For this purpose, flasks were prepared with 200 mL of fresh cow's milk, previously sterilized at 121 ° C x 15 min, then the strains were inoculated at a temperature of 37 ° C and incubated at the same temperature under constant shaking of 20 revolutions per minute (rpm) in a water bath with shaking, for 7 h; To construct the curves and obtain the growth constants, colony-forming units were counted per milliliter (cfu / ml) at one-hour intervals, with a monocular microscope and Neubauer chamber. Also, the pH and titratable acidity expressed in lactic acid were measured. The data obtained were converted to a logarithmic scale to apply the sigmoidal equations of Gompertz, Logistic, Modified Logistic and Weibull. The results of the kinetic modeling gave us that the modified Logistics and Logistics models presented a better fit compared to the rest. Likewise, the Weibull model presented the lowest value of adjustment, on the other hand, in the analysis of the statistical criteria, all models except Weibull present similarity. Finally, each sigmoidal model allowed to evaluate the growth of Saccharomyces boulardii with each of its kinetic constants.

Predict the Phase Angle Master Curve and Study the Viscoelastic Properties of Warm Mix Crumb Rubber-Modified Asphalt Mixture

To identify the most accurate approach for constructing of the dynamic modulus master curves for warm mix crumb rubber modified asphalt mixtures and assess the feasibility of predicting the phase angle master curves from the dynamic modulus ones. The SM (Sigmoidal model) and GSM (generalized sigmoidal model) were utilized to construct the dynamic modulus master curve, respectively. Subsequently, the master curve of phase angle could be predicted from the master curve of dynamic modulus in term of the K-K (Kramers–Kronig) relations. The results show that both SM and GSM can predict the dynamic modulus very well, except that the GSM shows a slightly higher correlation coefficient than SM. Therefore, it is recommended to construct the dynamic modulus master curve using GSM and obtain the corresponding phase angle master curve in term of the K-K relations. The Black space diagram and Wicket diagram were utilized to verify the predictions were consistent with the LVE (linear viscoelastic) theory. Then the master curve of storage modulus and loss modulus were also obtained. Finally, the creep compliance and relaxation modulus can be used to represent the creep and relaxation properties of warm-mix crumb rubber-modified asphalt mixtures.

Mathematical evaluation of responses to surgical stimuli under general anesthesia

Surgical invasion activates nociception, while anesthesia suppresses it. Under general anesthesia, stimulation, which is the balance between nociception and anti-nociception, induces responses, including activation of the autonomic nervous system. To evaluate the associations between stimulation (S) and the resultant responses (R), we examined R values, which were calculated using mathematical models of Stevens’ power law, Gompertz function and logistic function. The previously developed Nociceptive Response (NR) formula was applied as a modified logistic model. S values were calculated using a linear function in the NR formula. In a retrospective study, we developed an exponential model of Stevens’ power law and a sigmoidal model of Gompertz function using differential equations, by adjusting R values to correspond to NR values, in consecutive patients undergoing surgery under general anesthesia (n = 4,395). In a subsequent prospective study, we validated the superiority of R values of Gompertz function and the NR formula in an exponential model in adult patients undergoing tympanoplasty (n = 141) and laparoscopic cholecystectomy (n = 86). In conclusion, both modified logistic function and Gompertz function are likely appropriate mathematical models for representing responses to stimulation resulting from the balance between nociception/anti-nociception during surgical procedures under general anesthesia.

Predictive Framework for Modeling Changes in Asphalt Mixture Moduli with Oxidative Aging

This paper presents a predictive framework for asphalt mixture moduli as a function of aging time with two levels of sophistication. This work is built on the method currently implemented in Pavement mechanistic-empirical (ME) that uses an effective time/frequency concept based on time-aging superposition to model the effect of aging on a mixture’s modulus. Time-aging superposition implies that an asphalt mixture’s modulus mastercurves, corresponding to different aging levels, coincide when they are shifted horizontally on the log-frequency axis. This study improves the accuracy of the existing model by decoupling the time-temperature and time-aging shifts. The new framework also uses the binder dynamic shear modulus | G*| as an aging index instead of the viscosity, which is used in Pavement ME. The | G*| aging index is used to calculate an effective frequency at short-term aging (STA), which is then used in the asphalt mixture sigmoidal model to calculate the corresponding asphalt mixture modulus with aging. The pavement aging model introduced by NCHRP 09-54 predicts log | G*| at 64°C and 10 rad/s for a specific field-aged condition and pavement depth. The proposed framework can use the predicted log | G*| to predict the mixture’s corresponding dynamic modulus (| E*|) at that aging level and pavement depth. Level 1 of this framework requires characterizing the | G*| at STA and calibrating the NCHRP 09-54 pavement aging model as well as measuring the mixture | E*| at STA. Level 2 does not require any binder testing, providing relatively less accurate predictions but relieving some testing requirements.

Establishment of Complex Modulus Master Curves Based on Generalized Sigmoidal Model for Freeze–Thaw Resistance Evaluation of Basalt Fiber-Modified Asphalt Mixtures

This study aims to study the freeze–thaw (F–T) resistance of asphalt mixture incorporating styrene–butadiene–styrene (SBS) polymer and basalt fiber by using the established complex master curves of the generalized Sigmoidal model. Asphalt mixture samples incorporating styrene–butadiene–styrene (SBS) polymer and basalt fiber were manufactured following the Superpave gyratory compaction (SGC) method and coring as well as sawing. After 0–21 F–T cycles processing, a complex modulus test asphalt mixture specimen was performed to evaluate the influence of the F–T cycle. Besides, according to the time–temperature superposition principle, the master curves of a complex modulus were constructed to reflect the dynamic mechanical response in an extended range of reduced frequency at an arbitrary temperature. The results indicated that the elastic and viscous portions of asphalt mixture incorporating SBS and basalt fiber have decreased overall. It could be observed from the dynamic modulus ratio that the dynamic modulus ratios of specimens were more affected by the F–T cycle at low frequency or high temperature. Thus, in the process of asphalt pavement design and maintenance, attention should be paid to seasonal frozen asphalt pavement under low frequency and high temperature.