Structure prediction of nano materials

This thesis is predominantly on the exploration of configurational space of different materials of different dimensions using ab initio techniques. We focus on understanding the predicted geometrical configurations and their electronic properties. For this purpose, we employed MHM to explore the PES as well as identify putative low lying energy structures

Ferromagnetic to spin glass cross over in (La,Tb)_{2/3}Ca_{1/3}MnO_{3}

In the series La_{2/3-x}Tb_{x}Ca_{1/3}MnO_{3}, it is known that the compositions are ferromagnetic for smaller values of x and show spin glass characteristics at larger values of x. Our studies on the magnetic properties of various compositions in the La_{2/3-x}Tb_{x}Ca_{1/3}MnO_{3} series show that the cross over from ferromagnetic to spin glass region takes place above x ~ 1/8. Also, a low temperature anomaly at 30 K, observed in the ac susceptibility curves, disappears for compositions above this critical value of x. A mixed phase region coexists in the narrow compositional range 0.1 <= x <= 0.125, indicating that the ferromagnetic to spin glass cross over is not abrupt.Comment: 5 pages, 5 figure

Financing firms in India

The authors examine the legal and business environments, financing channels, and governance mechanisms of various types of firms in India and compare them to those from other countries. Despite its English commonlaw origin, strong legal protection provided by the law, and a democratic government, corruption within India's legal system and government significantly weakens investor protection in practice. External financing of firms has been dominated by nonmarket sources of financing, while the characteristics of listed firms are similar to those from countries with weak investor protection. The evidence, including results based on a survey of small and medium-scale private firms, shows that alternative financing channels provide the most important source of funds. The authors also find that informal governance mechanisms, such as those based on reputation, trust, and relationships are more important than formal mechanisms (such as courts) in resolving disputes, overcoming corruption, and supporting growth.Banks&Banking Reform,Corporate Law,Financial Intermediation,Governance Indicators,Small Scale Enterprise

Nutritional Status and Menarcheal Age of Rural Adolescent Girls of Salboni Block of Paschim Medinipur, West Bengal, India

Age at menarche is a significant indicator of growth and sexual maturation in girls. During adolescence, anthropometry provides a tool for monitoring and evaluating the hormone-mediated changes in growth and reproductive maturation. Menarche is defined as the first menstrual period. It is considered to be the most obvious sign of puberty in girls. It has been regarded in many cultures as a transitional step to womanhood. This is a cross-sectional study which is done on 1009 school girls who belonged to Salboni block of district Paschim Medinipur of West Bengal, India. To study effect of nutrition on age at menarche, different anthropometric measurements were applied. The study had been done on 10-19 adolescents school girls (1009). For this study, different types of anthropometric measurements were taken like weight and height. Height is measured through anthropometric rod, and weight by a weighing machine. Triceps and biceps Skinfolds are taken by skinfold caliper. Structured questionnaires were followed to know details of socio-economic status. Height was measured to the nearest 0.1 cm and weight to the nearest 0.5 kg. Each subject was weighed with minimum clothing and no footwear. Among studied sample, 896 girls had experienced menarche. Their mean age at menarche was 11.88 years (1.23). To compare anthropometric variable premenarchel and postmenarcheal girls that mean anthropometric measurement of premenarcheal girls more higher than post menarcheal girls in studied girls minimum age at menarche is 9 years and maximum age at menarche was 17 years. Body mass index increased progressively from 13 years to 19 years of age where overall increase was 1.89 kg/m2 from 10 to 19 years which was statistically significant with age (F=17.3, P<0.001), percent body fat was statistically significant with age (F=38.7, P<0.001). Nutritional status was better in postmenarcheal girls than in premenarcheal girls. The study represents typical differential rates of positive change in different body composition measures after the attainment of menarche

Microwave assisted efficient four-wave mixing

We theoretically investigate a N-type 87Rb atomic system for efficient generation and control of a non-degenerate Four wave mixing (FWM) signal in pulsed regime. The susceptibility of the atomic medium is customized as a gain profile by a weak probe field and two strong control fields which allow us to generate the pulsed FWM signal. We study the propagation dynamics of the generated FWM signal inside the nonlinear medium. The FWM signal obtains the exact shape of probe pulse and travels without changing the shape whereas the probe pulse is absorbed inside the nonlinear medium. The conversion efficiency of this scheme without a MW field is 5.8% which can be enhanced further by changing the control field intensity and optical depth. However, a MW field that couples two metastable ground states enhances the conversion efficiency three times (15.55%). The generation and control of such FWM signal in pulsed regime has important applications in signal processing, optical communication and quantum information science

Unsupervised feature extraction using neuro-fuzzy approach

The present article demonstrates a way of formulating a neuro-fuzzy approach for feature extraction under unsupervised training. A fuzzy feature evaluation index for a set of features is newly defined in terms of degree of similarity between two patterns in both the original and transformed feature spaces. A concept of flexible membership function incorporating weighted distance is introduced for computing membership values in the transformed space that is obtained by a set of linear transformation on the original space. A layered network is designed for performing the task of minimization of the evaluation index through unsupervised learning process. This extracts a set of optimum transformed features, by projecting n-dimensional original space directly to n'-dimensional (n'&lt;n) transformed space, along with their relative importance. The extracted features are found to provide better classification performance than the original ones for different real life data with dimensions 3, 4, 9, 18 and 34. The superiority of the method over principal component analysis network, nonlinear discriminant analysis network and Kohonen self-organizing feature map is also established

Fuzzy feature evaluation index and connectionist realization

A new feature evaluation index based on fuzzy set theory and a connectionist model for its evaluation are provided. A concept of flexible membership function incorporating weighting factors, is introduced which makes the modeling of the class structures more appropriate. A neuro-fuzzy algorithm is developed for determining the optimum weighting coefficients representing the feature importance. The overall importance of the features is evaluated both individually and in a group considering their dependence as well as independence. Effectiveness of the algorithms along with comparison is demonstrated on speech and Iris data