Interaction of cetyltrimethylammonium bromide with drug in aqueous/ electrolyte solution: A combined conductometric and molecular dynamics method study

Interaction between beta-lactum antibiotic drug ciprofloxacin hydrochloride(CFH)and cationic surfactant cetyltrimethylammonium bromide(CTAB)was performed conductometrically in aqueous as well as in the occurrence of different salts(NaCl,KCl as well as NH_4Cl)over the temperature range of 298.15–323.15 K at the regular interval of 5 K.CFH drug has been suggested for the treatment of bacterial infections such as urinary tract infections and acute sinusitis.A clear critical micelle concentration(CMC)was obtained for pure CTAB as well as(CFH+CTAB)mixed systems.The decrease in CMC values of CTAB caused by the addition of CFH reveals the existence of the interaction between the components and therefore it is the indication of micelle formation at lower concentration of CTAB and their CMC values further decrease in attendance of salts.A nonlinear behavior in the CMC versus T plot was observed in all the cases.The ΔG_m~0 values are found to be negative in present study systems demonstrated the stability of the solution.The values of ΔH_m~0 and ΔS_m~0 reveal the existence of hydrophobic and electrostatic interactions between CFH and CTAB.The thermodynamic properties of transfer for the micellization were also evaluated and discussed in detail.Molecular dynamic simulation disclosed that environment of water and salts have impact on the hydrophobic interaction between CFH and CTAB.In water and salts,CTAB adopts spherical micelle in which charged hydrophilic groups are interacted with waters whereas hydrophobic tails form the core of the micelle.This hydrophobic core region is highly conserved and protected.In addition,micelle formation is more favorable in aqueous Na Cl solution than other solutions.     

Preparation and analysis of poly(l-lactic acid) composites with oligo(d-lactic acid)-grafted cellulose

α-Cellulose extracted from jute fiber was grafted with oligo( d -lactic acid) (ODLA) via a graft polycondensation reaction in the presence of para-toluene sulfonic acid and potassium persulfate in toluene at 130 °C for 9 h under 380 mmHg. ODLA was synthesized by the ring-opening polymerization of d -lactides in the presence of stannous octoate (0.03 wt % lactide) and d -lactic acid at 140 °C for 10 h. Composites of poly( l -lactic acid) (PLLA) with the ODLA-grafted α-cellulose were prepared by the solution-mixing and film-casting methods. The grafting of ODLA onto α-cellulose was confirmed by Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). The analysis of the composites was performed with FTIR spectroscopy, SEM, wide-angle X-ray diffraction, and thermogravimetric analysis. The distribution of the grafted α-cellulose in the composites was uniform and showed better compatibility with PLLA through intermolecular hydrogen bonding. Only homocrystalline structures of PLLA were present in the composites, and the thermal stability increased with increasing percentage of grafted α-cellulose. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47424.     

Saponin-loaded SBA-15: release properties and cytotoxicity to Panc-I cancer cells

In this study, first time a nanoformulation, saponin-loaded SBA-15 has been developed for an improved and continuous release. The SBA-15 nanopowder was synthesized by a hydrothermal process. Saponin was introduced into the mesoporous channels of SBA-15 and its concentration in SBA-15 was measured by UV–visible spectrophotometry. The pristine SBA-15 and saponin-loaded SBA-15 were characterized by small-angle XRD, FESEM, HRTEM, TGA, FTIR. N₂ adsorption–desorption isotherms were used to measure the specific surface area and pore channel structure parameters of pristine and loaded SBA-15. Saponin release was studied in phosphate buffered saline (pH 7.4), which revealed that the release rate could be effectively controlled. The controlled drug release is highly desired for cancer treatment. The cytotoxicity of pristine and loaded SBA-15 was analyzed on Panc-I cancer cells. Both the pristine SBA-15 and saponin-loaded SBA-15 nanoparticles showed specific toxicity on the cancer cells. The preliminary results showed that saponin-loaded SBA-15 could be an effective therapeutic agent for Panc-I cancer cells.     

Ontology based E-learning framework: A personalized,adaptive and context aware model

Multimedia Tools and Applications - Enhancing the degree of learner productivity, one of the major challenges in E-Learning systems, may be catered through effective personalization, adaptivity and...     

Sulphur dioxide loadings over megacity Lahore (Pakistan) and adjoining region of Indo-Gangetic Basin

This article presents spatial and temporal variations of planetary boundary layer (PBL) sulphur dioxide (SO₂) over megacity Lahore and adjoining region, a typical representative area in the Indo-Gangetic Basin (IGB) largely influenced by transported volcanic SO₂ from Africa, Middle East, and southern Europe, by using data retrieved from satellite-based Ozone Monitoring Instrument (OMI) during October 2004–September 2015. We find a positive trend of 2.4% per year (slope 0.01 ± 0.005 with y-intercept 0.35 ± 0.03 Dobson Unit (DU), correlation coefficient r = 0.55 and 2-tailed p-value at 0.1) of OMI-SO₂ column with the average value of 0.4 ± 0.05 DU. Strong seasonality of OMI-SO₂ column is observed over the region linked with local meteorology, patterns of anthropogenic emissions, crop residue burning, and vegetation cover. There exists a seasonal high value in winter 0.56 ± 0.24 DU with a peak in December 0.67 ± 0.26 DU. The seasonal lowest value is observed to be 0.29 ± 0.11 DU in wet summer with minimum value in July 0.25 ± 0.06 DU. High growth rates of OMI-SO₂ column over the study region have been observed in January, June, October, and December ranging from 5.7% to 11.6% per year. Satellite data show elevated OMI-SO₂ columns in 2007, 2008, 2011, and 2012 largely contributed by trans-boundary volcanic SO₂. A detailed analysis of volcanic SO₂ transported from Africa and Middle East (Jabal Al-Tair, Dalaffilla, and Nabro volcanoes) over the study area is presented. Air mass trajectories suggest the presence of long-range transported volcanic SO₂ at high altitude levels over Lahore and IGB region during the volcanic episodes. The SO₂ enhancements in PBL during winter season are generally due to significant vertical downdraft of high-altitude volcanic SO₂. For the first time, we present significant influence of volcanic SO₂ from southern Europe (Mt. Etna volcano) reaching over the study area. Daily mean OMI-SO₂ levels up to 21.4, 10.0, 5.6, and 2.4 DU have been noticed due to the eruptions from Dalaffilla, Mt. Etna, Nabro, and Jabal Al-Tair volcanoes, respectively.     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Passive Three Dimensional Face Recognition Using Iso-Geodesic Contours and Procrustes Analysis

We introduce a new model for personal recognition based on the 3-D geometry of the face. The model is designed for application scenarios where the acquisition conditions constrain the facial position. The 3-D structure of a facial surface is compactly represented by sets of contours (facial contours) extracted around automatically pinpointed nose tip and inner eye corners. The metric used to decide whether a point on the face belongs to a facial contour is its geodesic distance from a given landmark. Iso-geodesic contours are inherently robust to head pose variations, including in-depth rotations of the face. Since these contours are extracted from rigid parts of the face, the resulting recognition algorithms are insensitive to changes in facial expressions. The facial contours are encoded using innovative pose invariant features, including Procrustean distances defined on pose-invariant curves. The extracted features are combined in a hierarchical manner to create three parallel face recognizers. Inspired by the effectiveness of region ensembles approaches, the three recognizers constructed around the nose tip and inner corners of the eyes are fused both at the feature-level and the match score-level to create a unified face recognition algorithm with boosted performance. The performances of the proposed algorithms are evaluated and compared with other algorithms from the literature on a large public database appropriate for the assumed constrained application scenario.     

Performance evaluation of semantic registries: OWLJessKB and instanceStore

Service discovery is a critical task in distributed computing architectures for finding a particular service instance. Semantic annotations of services help to enrich the service discovery process. Semantic registries are an important component for the discovery of services and they allow for semantic interoperability through ontology-based query formulation and dynamic mapping of terminologies between system domains. This paper evaluates two semantic registries—OWLJessKB implementation and instanceStore—to determine the suitability of these with regards to the query response time and the overall scalability for use in mathematical services. Mathematical ontologies from the MONET project are used to undertake comparison. The results demonstrate that the performance of registries may be compared across two axes: (1) time to initialize (i.e. time to load an initial ontology into memory); (2) time to query (i.e. time to reason with an ontology loaded into memory).     

Design and analysis of novel micro displacement amplification mechanism actuated by chevron shaped thermal actuators

This paper presents design and analysis of microelectromechanical system (MEMS) based displacement amplification mechanism actuated using thermal actuators with enhanced performance. The proposed model consists of chevron shaped thermal actuators, an amplification mechanism capable of amplifying displacement 20 times and an electrostatic comb drives for sensing displacements. When voltage is applied to thermal chevrons, displacement is produced which is then amplified 20 times. Steady state static thermal electrical analysis is performed under variable resistivity and voltage bias of 2 V. In-plane reaction forces of magnitude 194.2 and 150.91 µN along X and Y-axis, respectively, thus producing displacement of 0.11 and 2.22 µm along X and Y-axis, respectively. Time domain simulations of device are carried with constant electrical resistivity, variable voltage and convective boundary conditions. Modal analysis of the mechanism is carried out to predict the natural frequencies and associated mode shapes of mechanism during free vibrations. The desired mode is at frequency of 286.160 kHz. Dynamic simulations including direct integration-transient, transient modal and steady state modal analysis are performed on the device for time span of 0.0006 s, under application of 25 g and frequency range of 200–300 kHz. Simulation results prove the viability of the mechanism as an amplification device with enhanced voltage–stroke ratio.

     

Fraudulent Firm Classification: A Case Study of an External Audit

This paper is a case study of visiting an external audit company to explore the usefulness of machine learning algorithms for improving the quality of an audit work. Annual data of 777 firms from 14 different sectors are collected. The Particle Swarm Optimization (PSO) algorithm is used as a feature selection method. Ten different state-of-the-art classification models are compared in terms of their accuracy, error rate, sensitivity, specificity, F measures, Mathew’s Correlation Coefficient (MCC), Type-I error, Type-II error, and Area Under the Curve (AUC) using Multi-Criteria Decision-Making methods like Simple Additive Weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The results of Bayes Net and J48 demonstrate an accuracy of 93% for suspicious firm classification. With the appearance of tremendous growth of financial fraud cases, machine learning will play a big part in improving the quality of an audit field work in the future.