ENHANCEMENT OF DISSOLUTION RATE OF MODAFINIL USING SOLID DISPERSIONS WITH POLYETHYLENEGLYCOLS

Solid  dispersions  (SDs)  of  modafinil  (MDF)  were  prepared using polyethyleneglycols (PEGs), in 1;1, 1;2 and 1;4 proportions by  fusion,  solvent  evaporation  and  physical  mixing  method. Differential  scanning  calorimetry  (DSC)  and  X-ray  powder diffractometry (XRD)  were  used to examine the physical state  of the  drug.  The  data  from  the  XRD  showed  that  the  drug  was converted  to  amorphous  form  as  the  number  and  intensity  of peaks  were  decreased  in  solid  dispersion  as  compared  to  pure drug and physical mixture of drug and carrier. DSC thermograms also  confirmed  the  change  in  physical  state  of  the  drug  as  the peaks were altered or disappeared. With the  highest  ratio of the carriers (1:4), the drug  solubility was enhanced by 38.68, 34.78 and 9.29 folds in solvent evaporation, fusion and physical mixing methods  respectively.  Solid  dispersion  batch  S6  containing drug:PEG6000  in  1:4,  was  selected  to  be  formulated  as  tablet (batch  TS6)  and  evaluated  for in  vitro drug  dissolution  &  six month  stability.  An  increased  dissolution  rate  of  modafinil  was observed  from  SDs  and  PMs,  as  compared  to  pure  crystalline drug.  The  dissolution  rate  of  modafinil  from  its  PMs  or  SDs increased with an increasing amount of polymer.Key  words:  Fusion,  solvent  evaporation,  physical  mixture,  in  vitro dissolution, characterization.

The Prospects for Hybrid Electric Vehicles, 2005-2020: Results of a Delphi Study

The introduction of Toyota's hybrid electric vehicle (HEV), the Prius, in Japan has generated considerable interest in HEV technology among US automotive experts. In a follow-up survey to Argonne National Laboratory's two-stage Delphi Study on electric and hybrid electric vehicles (EVs and HEVs) during 1994-1996, Argonne researchers gathered the latest opinions of automotive experts on the future ''top-selling'' HEV attributes and costs. The experts predicted that HEVs would have a spark-ignition gasoline engine as a power plant in 2005 and a fuel cell power plant by 2020. The projected 2020 fuel shares were about equal for gasoline and hydrogen, with methanol a distant third. In 2020, HEVs are predicted to have series-drive, moderate battery-alone range and cost significantly more than conventional vehicles (CVs). The HEV is projected to cost 66% more than a $20,000 CV initially and 33% more by 2020. Survey respondents view batteries as the component that contributes the most to the HEV cost increment. The mean projection for battery-alone range is 49 km in 2005, 70 km in 2010, and 92 km in 2020. Responding to a question relating to their personal vision of the most desirable HEV and its likely characteristics when introduced in the US market in the next decade, the experts predicted their ''vision'' HEV to have attributes very similar to those of the ''top-selling'' HEV. However, the ''vision'' HEV would cost significantly less. The experts projected attributes of three leading batteries for HEVs and projected acceleration times on battery power alone. The resulting battery packs are evaluated, and their initial and replacement costs are analyzed. These and several other opinions are summarized

Organic Farming In Banana And Guava

India is the second largest producer of fruits in the world. With the increasing population, the cultivable land resource is shrinking day to day. Green Revolution in the post- independence era has shown path to developing countries for self- sufficiency in food but sustaining agricultural production against the finite natural resource base demands has shifted from the “resource degrading” chemical agriculture to a “resource protective” biological or organic farming. The major component of organic farming is: manures, green manures, intercropping, mulching, vermiculture biotechnology, bio fertilizers, biodynamic farming, bio control etc. Application of bio-fertilizer was more effective than organic manures in enhancing fruit growth parameters. When bio-fertilizer was grouped together in Red Fleshed guava and banana cv. grand nine, P-solubilizers were found to have more beneficial influence on fruit physico- chemical characteristics than that of N-fixers

q-Sumudu transforms pertaining to the product of family of q-polynomials and generalized basic hypergeometric functions

The prime objective of commenced article is to determine q-Sumudu transforms of a product of unified family of q-polynomials with basic (or q-) analog of Fox’s H-function and q-analog of I-functions. Specialized cases of the leading outcome are further evaluated as q-Sumudu transform of general class of q-polynomials and q-Sumudu transforms of the basic analogs of Fox’s H-function and I-functions

Micro-Acoustic-Trap (µAT) for microparticle assembly in 3D

Acoustic tweezers facilitate the manipulation of objects using sound waves. With the current state of the technology one can only control mobility for a single or few microparticles. This article presents a state of the art system where an Acoustic Lens was used for developing a Micro-Acoustic Trap for microparticle assembly in 3D. The model particles, 2 µm diameter polystyrene beads in suspension, were driven via acoustic pressure to form a monolayer at wavelength-defined distances above the substrate defined by the focal point of an Acoustic Lens The transducer was driven at 89 MHz, mixed with 100 ms pulses at a repetition rate of 2 Hz. Beyond a threshold drive amplitude sufficient to overcome Brownian motion, this led to 2D assembly of the microparticles into close-packed rafts >80 µm across (∼5 wavelengths of the carrier wave and >40 particles across). This methodology was further extended to manipulation of live Dictyostelium discoideum amoebae. This approach therefore offers maneuverability in controlling or assembling micrometer-scale objects using continuous or pulsed focused acoustic radiation pressure

ESTIMATION OF GUGGULSTERONE-Z IN GOKSHURADI GUGGULU USING REVERSED-PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY

Objective: A study was aimed to estimate guggulsterone-Z (GZ) in Gokshuradi Guggulu (GG).Methods: An analytical method was developed and validated using Waters Alliance high-performance liquid chromatography system (Empower software), equipped with photodiode array detector. Separation was achieved using Phenomenex, C-18 (250 mm×4.6 mm, 5 μ) column. Mobile phase consisted of acetonitrile:water (70:30,v/v). Flow rate was set to 1 ml/min and detection was performed at 251 nm.Results and Discussion: Validation parameters such as linearity, precision, accuracy, limit of detection, limit of quantification, and robustness were performed. Amount of GZ was estimated using linearity equation.Conclusion: GG was found to contain 0.815±0.03 g% w/w GZ. Validated method may be used as one of the parameters to standardize the formulation

QUALITY MANAGEMENT PRACTICES AND COMPETITIVE ADVANTAGE OF SELECTED FOOD AND BEVERAGE MANUFACTURING FIRMS IN LAGOS STATE, NIGERIA

The performance of Food and Beverages manufacturing firms is important to the development of the economy and this has been considered by researchers. In Nigeria, the decline in the performance of this sector in terms of competitive advantage has been noticed which could be as a result of a lack of quality management practices such as leadership behaviour, strategic quality planning, supplier quality management, process management and customer focus. The study investigated the effect of quality management practices on the competitive advantage of selected Food and Beverages manufacturing firms in Lagos State, Nigeria. The survey research design was adopted. The population of the study was 14, 591 top, middle and low-level management employees of the selected Food and Beverages manufacturing firms in Lagos State, Nigeria. A sample size of 491 was determined using the research advisor table. A simple random sampling technique was used. A validated questionnaire was used to collect data. Cronbach’s alpha reliability coefficients for the constructs ranged from 0.866 to 0.954. The response rate was 100%. Data were statistically analysed using descriptive and inferential statistics (multiple and hierarchical regression). Findings revealed that quality management practices had a significant effect on the competitive advantage of Food and Beverages manufacturing firms in Lagos State, (Adj.R2 = 0.117; F (5, 485) = 14.025, p < 0.05). The study concluded that quality management practices affected competitive advantage in Food and Beverages manufacturing firms in Lagos State, Nigeria. The study recommends that Food and Beverages manufacturing firms should encourage the adoption of quality management practices to enhance competitive advantage.  Article visualizations

Estimates of daily oxygen consumption, carbon dioxide and methane emissions, and heat production for beef and dairy cattle using spot gas sampling

A simulation study was conducted to examine accuracy of estimating daily O2 consumption, CO2 and CH4 emissions, and heat production (HP) using a spot sampling technique and to determine optimal spot sampling frequency (FQ). Data were obtained from 3 experiments where daily O2 consumption, emissions of CO2 and CH4, and HP were measured using indirect calorimetry (respiration chamber or headbox system). Experiment 1 used 8 beef heifers (ad libitum feeding; gaseous exchanges measured every 30 min over 3 d in respiration chambers); Experiment 2 used 56 lactating Holstein-Friesian cows (restricted feeding; gaseous exchanges measured every 12 min over 3 d in respiration chambers); Experiment 3 used 12 lactating Jersey cows (ad libitum feeding; gaseous exchanges measured every hour for 1 d using headbox style chambers). Within experiment, averages of all measurements (FQALL) and averages of measurements selected at time points with 12, 8, 6, or 4 spot sampling FQ (i.e., sampling every 2, 3, 4, and 6 h in a 24-h cycle, respectively; FQ12, FQ8, FQ6, and FQ4, respectively) were compared. Within study a mixed model was used to compare gaseous exchanges and HP among FQALL, FQ12, FQ8, FQ6, and FQ4, and an interaction of dietary treatment by FQ was examined. A regression model was used to evaluate accuracy of spot sampling within study [i.e., FQALL (observed) vs. FQ12, FQ8, FQ6, or FQ4 (estimated)]. No interaction of diet by FQ was observed for any variables except for CH4 production in experiment 1. No FQ effect was observed for gaseous exchanges and HP except in experiment 2 where CO2 production was less (5,411 vs. 5,563 L/d) for FQ4 compared with FQALL, FQ12, and FQ8. A regression analysis between FQALL and each FQ within study showed that slopes and intercepts became farther from 1 and 0, respectively, for almost all variables as FQ decreased. Most variables for FQ12 and FQ8 had root mean square prediction error (RMSPE) less than 10% of the mean and concordance correlation coefficient (CCC) greater than 0.80, and RMSPE increased and CCC decreased as FQ decreased. When a regression analysis was conducted with combined data from the 3 experiments (mixed model with study as a random effect), results agreed with those from the analysis for the individual studies. Prediction errors increased and CCC decreased as FQ decreased. Generally, all the estimates from FQ12, FQ8, FQ6, and FQ4 had RMSPE less than 10% of the means and CCC greater than 0.90 except for FQ6 and FQ4 for O2 consumption and CH4 production. In conclusion, the spot sampling simulation with 3 indirect calorimetry experiments indicated that FQ of at least 8 samples (every 3 h in a 24-h cycle) was required to estimate daily O2 consumption, CO2 and CH4 production, and HP and to detect changes in those in response to dietary treatments. This sampling FQ may be considered when using techniques that measure spot gas exchanges such as the GreenFeed and face mask systems

Self-supervised generative adverrsarial network for depth estimation in laparoscopic images

Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo image pair could be solved with convolutional neural networks. However, most recent depth estimation models were trained on datasets with per-pixel ground truth. Such data is especially rare for laparoscopic imaging, making it hard to apply supervised depth estimation to real surgical applications. To overcome this limitation, we propose SADepth, a new self-supervised depth estimation method based on Generative Adversarial Networks. It consists of an encoder-decoder generator and a discriminator to incorporate geometry constraints during training. Multi-scale outputs from the generator help to solve the local minima caused by the photometric reprojection loss, while the adversarial learning improves the framework generation quality. Extensive experiments on two public datasets show that SADepth outperforms recent state-of-the-art unsupervised methods by a large margin, and reduces the gap between supervised and unsupervised depth estimation in laparoscopic images