A Pharmacokinetic Study of Mix-160 by LC-MS/MS: Oral Bioavailability of a Dosage Form of Citroflavonoids Mixture

This study was performed to evaluate and compare the pharmacokinetic parameters between two dosage formulations of hesperidin and naringenin: mixture and tablet. Our objective was to determine that the flavonoid tablet does not significantly modify the pharmacokinetic parameters compared with the mixture. For this study, we administered 161 mg/kg of either mixture (Mix-160) or tablet composed of hesperidin and by intragastric administration. Blood microsamples were collected from tail vein up to 24 h. Serum flavonoid extraction was performed by solid phase extraction and analyzed by LC-MS/MS of triple quadrupole (QqQ). Serum concentration vs. time plot showed that data fitted for a first-order model. The pharmacokinetic parameters were calculated by a noncompartmental model. The results showed that the absorption constant is higher than the elimination constant. The first concentration was found at five minutes, and minimal concentration at 24 h after administration, suggesting a enterohepatic recirculation phenomena and regulation of liver cytochromes’ activity. We did not find meaningful differences between the pharmacokinetic parameters of both samples. We concluded that tablet form did not interfere with the bioavailability of hesperidin and naringenin, and it could be a suitable candidate for developing a drug product.

Application of Capacitance-Resistive Model With Global Optimizer

The need to do a history matching in a deltaic environment with a total of 550 compartmentalized channel reservoirs of Field X brings such heavy challenges in terms of time consumed and uncertainties present. The capacitance-resistive model (CRM) rooted in signal processing between the injection and production rate was chosen to determine connectivity between injectors and producers (f_ij) and flood efficiencies for portions of the field (f_F). These constants become key insights for validating the dynamic synthesis of the reservoirs. CRM relies solely upon production and injection data. Two different control-volumes for CRM, CRMT and CRMP, were solved using a global non-deterministic solver which elevate differential evolution algorithm. The parameters’ solved was then validated with the observed liquid rate of the wells. Several techniques such as using system-wide R2 as the objective function, removal of inactive wells and distance-based weighting were used to improve the validation of the proxy model. The methods were applied to validate analyzed reservoirs with divided regions based on earlier analysis. A first CRM run was presented in this paper to test the algorithm prepared. Then another CRM run were demonstrated in this paper to show how they confirm the compartmentalization within a reservoir when compared to the reservoir’s pressure-over-time plot and earlier manual production-injection data analysis. This paper exemplified the strength of CRM itself which is to describe large-scale system in a way that circumvents geologic modeling and saturation matching with short to moderate computation time, as well as improvements applied to help the optimization process.

A Comparative Study of Fourier Series Models and Seasonal -Autoregressive Integrated Moving Average Model of Rainfall Data in Port Harcourt

This study compares the Seasonal autoregressive integrated moving average (SARIMA) model within Fourier time series model in modelling rainfall data in Port Harcourt Rivers State from 2000-2014. The time plot of the series showed Seasonality but a not obvious trend. The raw data is nonstationary at the level. Time plot of the seasonal differencing of rainfall at lag12 showed a stationary process with seasonality at lag 12 on the PACF and ACF of the series. The periodogram plot reveals that there exist both short and long term cycles within the period. The Fourier series and the seasonal autoregressive moving average models are reduced to 12month of seasonal component.( ) The Akaike Information Criterion (AIC) was used to select better models. The best model is the model that minimises the information criterion. It was observed that SARIMA (1,0,1)(1,1,1)12 models have a minimum AIC value. Hence, SARIMA model performs better in modelling the rainfall data in Port Harcourt then the Fourier series models.

Comparative analysis of hatchability dynamics (CAHD) of eggs in selected hatcheries in Ibadan metropolis

We carried out this study to evaluate the plausibility of the representativeness of time series analysis results using egg hatchability data from 2 selected hatcheries: Bronco and Foresight hatcheries, Oluyole, Ibadan (both at Latitude 7º 23´ N and Longitude 3º 82´ E). The initial summary statistics of egg variables showed that in Bronco hatchery, the quantity of eggs set peaked (14935.53) in the months of November but lowest (11298.91) in the months of March. However, variance of eggs set in the months of September was highest (41018287) but lowest (1613430) in the months of March. The quantity of fertile eggs ranged between 10216.96 (March) and 13527.58 (November). Total number of chicks produced was highest (11966.15) in the months of November and lowest (9265.86) in the months of March. The time plot of egg set for hatching returned an unconditional cyclic variance and similarly with egg transferred. Although, total eggs hatched into chicks had different time plot pattern but it was also an unconditional cyclic variation. The Jarque-Bera (JB) statistics returned for egg set, egg transferred, total chicks hatched and ratio for Bronco hatchery are 1654.92, 1011.46, 38.721 and 57.855, respectively, while that of foresight hatchery are 25.038, 27.006, 235.897 and 365.734, respectively. The acf(x …x ) of the egg variable presented a wider value than that of acf of (x …x ) for foresight hatchery hence, the acf (x …x ) =(x …x ) could not be said to be strictly stationary. However, the acf of the x …x presented a cyclical and reducing acf like the original acf hence, (x …x ) =(x …x ). The acf of the ratio of egg set to total chicks hatched gave cyclical but reducing trend for both Bronco and Foresight hatcheries. These trends were also maintained for the x …x hence xtk+h …x = x …x . TheARIMAmodel of the ratio of the egg hatchability variables has the least corrected akaike information criteria nd Bayesian Information Criteria hence it could be adjudged the most parsimonious.

Modelling the Occurrence of the Novel Pandemic COVID-19 Outbreak– A Box and Jenkins Approach

The corona virus disease 2019 (COVID-19) is a novel pandemic disease that spreads very fast and causes severe respiratory problem to its carrier and thereby results to death in some cases. In this research, we studied the trend, model Nigeria daily COVID-19 cases and forecast for the future occurrences in the country at large. We adopt the Box and Jenkins approach. The time plot showed that the cases of COVID-19 rises rapidly in recent time. KPSS test confirms the non-stationarity of the process (p < 0.05) before differencing. The test also confirmed the stationarity of the process (p > 0.05) after differencing. Various ARIMA (p,d,q) were examined with their respective AICs and Log-likelihood. ARIMA (1, 2, 1) was selected as the best model due to its least AIC (559.74) and highest log likelihood (−276.87). Both Shapiro-Wilk test and Box test performed confirm the fitness of the model (p > 0.05) for the series. Forecast for 30 days was then made for COVID-19 cases in Nigeria. Conclusively, the model obtained in this research can be used to model, monitor and forecast the daily occurrence of COVID-19 cases in Nigeria.

Wireless Sensors System for Stress Detection by Means of ECG and EDA Acquisition

This paper describes the design of a two channels electrodermal activity (EDA) sensor and two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands and transmit them to the ECG sensor with wireless WiFi communication for increased wearability. The sensors system acquires two EDA channels to improve the removal of motion artifacts that take place if EDA is measured on individuals who need to move their hands in their activities. The ECG channels are acquired on the chest and the ECG sensor is responsible for aligning the two ECG traces with the received packets from EDA sensors; the ECG sensor sends via WiFi the aligned packets to a laptop for real time plot and data storage. The metrological characterization showed high-level performances in terms of linearity and jitter; the delays introduced by the wireless transmission from EDA to ECG sensor have been proved to be negligible for the present application.

Phylogeographical spatial diffusion analysis reveals the journey of Geoffroy’s cat through the Quaternary glaciations of South America

Leopardus geoffroyi is a small feline with a widespread distribution in a broad array of habitats. Here we investigate its evolutionary history to characterize the phylogeographical patterns that led to its present distribution using mitochondrial DNA from 72 individuals collected throughout its entire range. All haplotypes conformed to a monophyletic group, including two clades with a central/marginal disposition that is incongruent to the proposed subspecies. Spatial diffusion analysis showed the origin of the species within the oldest and more diverse central clade. A Bayesian Skyline Plot combined with a dispersal through time plot revealed two population increases at 190 000–170 000 and 45 000–35 000 years ago, the latter period accompanied by an increase in the dispersal rate. Species distribution models showed similar patterns between the present and Last Interglacial Period, and a reduction of high-probability areas during the Last Glacial Maximum (LGM). Molecular evidence confirms L. geoffroyi as a monotypic species whose origin is located in Central Argentina. The last glaciation had little effect on the pattern of distribution of the species: the population and range expansion that started before the LGM, although probably being halted, continued after the glaciation and resulted in the presence of this felid in the far south of Patagonia.

ARIMA Modelling of Neonatal Mortality in Abia State of Nigeria

In this study, the incidence neonatal mortality in Abia State of Nigeria was consideredusing data from January 2014 to December 2018. The data was obtained from the FederalMedical Centre, Umuahia in Abia State of Nigeria. The time plot of the data and the ADFtest conducted conrmed the series to be stationary. The plots of the ACF and PACF cuto after lags 4 and 1 respectively which suggested ARIMA (1, 0, 4). However, diagnosticchecks led us to select ARIMA (1, 0, 1) as the best model to t the data and it was used tomake forecast. Our forecasted values indicate there will be a continous decline in the incidenceof neonatal mortality in Abia State of Nigeria. Much should be done to even expedite the decrease.

Impact of Different Mucoadhesive Polymeric Nanoparticles Loaded in Thermosensitive Hydrogels on Transcorneal Administration of 5-Fluorouracil

In a previous paper a thermosensitive hydrogel formulation based on chitosan or its derivatives (TSOH), containing medicated chitosan nanoparticles (Ch NP) for transcorneal administration of 5-fluorouracil (5-FU) was described. The Ch NP-containing TSOH allowed a time-constant 5-FU concentration in the aqueous for 7 h from instillation. The aim of the present work was to study the impact of the surface characteristics of new NP contained in TSOH on ocular 5-FU bioavailability. The Ch derivatives used to prepare NP were quaternary ammonium-Ch conjugate (QA-Ch), S-protected derivative thereof (QA-Ch-S-pro), and a sulphobutyl chitosan derivative (SB-Ch). All NP types had 300–400 nm size, 16–18% encapsulation efficiency, and retained the entrapped drug for at least 15 h. Drug release from TSOH containing NP based on QA-Ch or QA-Ch-S-pro was virtually equal, whereas with TSOH containing NP based on SB-Ch was significantly slower. Instillation, in rabbit eyes, of NP-containing TSOH based on QA-Ch or SB-Ch led to a plateau in the aqueous concentration vs. time plot in the 1–10 h range with significantly enhanced area under curve (AUC). Negative charges on the NP surface slowed down 5-FU release from TSOH while positive charges increased NP contact with the negatively charged ocular surface. Either results in enhanced ocular bioavailability.

Multivariate Time Series Modelling with Seasonal Univariate Components; Evidence from Nigeria GDP

The patterns of GDP variables are graphically examined using time plot presented the time plot for the GDP variables concerning time presented a combined single time plot for all the considered GDP variables. The relationship, as well as the degree of relationship between/among the GDP variables, was further revealed by computing the pairwise correlation. Based on the output, each variable when crossed classified with itself have a strong positive correlation with an output of (1), while pairwise correlation reveals a positive figure with the least estimate being (0.3149), this implies that for all the variables there exist a positive correlation. All the pairwise relationship reveals a strong positive association with all the estimates revealing a value between (0.8-0.9) except ‘trade and industry' that shows a positive relationship but not strong with an estimate of (0.3149). The initial test in fitting a time series model is to examine the series for stationarity. The Augmented Dickey-Fuller test revealed that ‘Agriculture’, ‘Construction’, and Services’” satisfies the requirement of stationarity while the series ‘industry and “Trade” are non-stationary initially but later became stationary after the application of the first difference transformation which was confirmed after the application of the ADF test to the first differenced series. The Johansen co-integration's Trace test was employed to determine the order of co-integration and it was revealed that the series are cointegrated hence presentation of the equation of integration. We presented the lag length estimation criteria which revealed that the lag length of order 5 is appropriate for the VAR model as suggested by Akaike Information Criteria (AIC), Hannan-Quinn (HQ) Information Criteria, Schwarz Information Criteria (SC). The VAR(5) model was fitted for all the considered GDP variables.