NMR studies of poly(2-hydroxy ethyl methacrylate-co-2-vinyl pyridine)

Copolymers of 2-hydroxy ethyl methacrylate-2-vinyl pyridine (H/V) of different composition were synthesized by free radical bulk polymerization using azobisisobutyronitrile (AIBN) as an initiator under nitrogen atmosphere. The copolymer compositions were calculated from ¹H NMR spectra. The reactivity ratios for H/V copolymers obtained from a linear Kelen-Tudos method (KT) and nonlinear error-in-variables method (EVM) are r_H = 0.50 ± 0.10, r_V = 1.04 ± 0.08 and r_H = 0.55, r_V = 1.06 respectively. The complete spectral assignment of methine, methylene, methyl, carbonyl, and aromatic carbon regions in term of compositional and configurational sequences of H/V copolymers were done with the help of ¹³C{¹H} NMR, distortionless enhancement by polarization transfer (DEPT), two-dimensional heteronuclear single quantum coherence (HSQC) along with total correlated spectroscopy (TOCSY). © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

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.     

Two generalized measures of “useful” information

The weighted additivity corresponding to additivity plays a very important role in study of useful information. By using the sum property, the equation satisfied by weighted additivity has been converted to a functional equation, which is further generalized in two ways. The real and continuous solutions of the generalized functional equations have been obtained. In terms of these real and continuous solutions, two new generalized measures of useful information have been characterized and their particular cases have been studied. Some bounds and comparison results have also been obtained.     

The distribution of automobile catalysts-cast platinum, palladium and rhodium in soils adjacent to roads and their uptake by grass

The introduction of automobile catalysts has raised environmental concern, as this pollution control technology is also an emission source for the platinum group elements (PGE). The main aim of this study was to assess the concentrations of Pt, Pd, Rh and Au in soil and grass herbage collected adjacent to 5 roads. Soil and grass samples were collected from 4 fixed distances (0, 1, 2 and 5 m) from the road edge at each site. PGE and Au were determined by ICP-MS in all samples after acid digestion. The maximum soil Pt, Rh and Pd concentrations were measured at the road perimeters. Averaged across the sites, the Pt and Rh concentrations of 15.9+/-7.5 microg Pt kg(-1) and 22.40+/-4.73 microg Rh kg(-1) at 0-m distance decreased to 2.04+/-1.7 microg Pt kg(-1) and 3.51+/-1.96 microg Rh kg(-1), respectively at 5-m away from the roads. Pd concentrations were much higher than Pt or Rh, ranging from 120.8+/-12.0 microg Pd kg(-1) (0-m) to 84.2+/-10.9 microg Pd kg(-1) (5-m), possibly due to differences in its use, emission and/or soil chemistry. Au showed little or no change with distance from the roads. However, the average Au concentration of 18.98+/-0.98 microg Au kg(-1) provides clear evidence of some input possibly due to attrition of automobile electronics. No straightforward influence of traffic flow rates on PGE distribution was found. A combination of dispersal impeding local features and slow moving and stop-and-start traffic conditions or fast moving traffic with flat open spaces may have offset the expected impacts. Rh and Pt soil concentration accounted for 66% and 34% (P<0.01) of the variability observed, respectively in their plant concentrations. Grass Pd and Au concentrations had no relationship with their respective soil concentrations.     

Automated TB classification using ensemble of deep architectures

Multimedia Tools and Applications - Tuberculosis (TB) is an infectious disease that mainly affects the lung region. Its initial screening is mostly performed using chest radiograph, which is also...     

Preparation and photoluminescent analysis of Sm3+ complexes based on unsymmetrical conjugated chromophoric ligand

Journal of Materials Science: Materials in Electronics - The octa-coordinated complexes of Sm(III) with β-diketone and nitrogen-heterocyclic bidentate auxiliary moiety were prepared and...     

Investigation of microstructure of 4‐vinyl pyridine–methacylonitrile copolymers by NMR spectroscopy

4‐Vinyl pyridine–methacrylonitrile (V/M) copolymers of different composition were prepared by bulk polymerization using benzoyl peroxide as an initiator. The copolymer composition was determined from quantitative ¹³C{¹H}‐NMR spectra. The reactivity ratios for V/M copolymer obtained from a linear Kelen‐Tudos method (KT) and nonlinear error‐in‐variables method (EVM) are r_V = 0.79 ± 0.12, r_M = 0.38 ± 0.09 and r_V = 0.79 ± 0.13, r_M = 0.38 ± 0.07, respectively. The complete spectral assignment in term of compositional and configurational sequences of these copolymers were done with the help of distortionless enhancement by polarization transfer (DEPT), two‐dimensional heteronuclear single quantum coherence spectroscopy (HSQC). Total correlated spectroscopy (TOCSY) experiment was used to assign the various three‐bond ¹H‐¹H couplings in the V/M copolymer. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 88: 3232–3238, 2003     

An Efficient Variant of Fully-Convolutional Network for Segmenting Lung Fields from Chest Radiographs

Wireless Personal Communications - Automatic analysis of chest radiographs using computer-aided diagnosis (CAD) systems is pivotal to perform mass screening and detect early signs of various...     

A Novel Ensemble Method for PTB Classification in CXRs

Pulmonary tuberculosis (PTB) is a contagious disease that affects the lung region. PTB is a life-threatening disease if it is detected late or left untreated. To perform the initial screening of PTB, the World Health Organization has recommended chest radiograph. Till now, the screening process requires either the patients to come to secondary health centers from rural areas or the radiologists to go the remote locations. This process is rejuvenated with the introduction of computer-aided diagnosis (CAD) systems. CAD systems reduce the need for expert radiologists in the screening process. However, the development and deployment are still in the early phases as new methods are being developed to improve the performance of CAD systems in terms of accuracy, specificity and sensitivity. In this study, a deep learning-based PTB classification system has been presented that achieves the state-of-the-art performance for TB classification. Firstly, a proposed architecture based on the blocks is presented and then it is used to create an ensemble. In the proposed ensemble, two standard architectures namely AlexNet, and ResNet have also been used in addition to the proposed architecture. All the architectures are trained and evaluated on a combined dataset formed using publicly available standard datasets. The proposed ensemble attains the accuracy of 90.00% and area under the curve equal to 0.96, which is better than the performance of the existing methods.