Silica coating of gold nanoparticles

“Gold colloids have been homogenously coated with silica using silane coupling agents as a primer to make the gold surface vitreophilic. After adding active silica, the particles are transferred in ethanol for uniform silica coating by using the Stober method. Gold nanoparticles used for this study ranged from 5 nm up to 40 nm with mixed results. Silica condensation can be controlled to produce different silica thicknesses on gold. The main problem while coating smaller particles (5 nm and 10 nm) was the final coagulation or necking of silica after coating the gold surface. The possible causes for this effect are also examined. These composite nanoparticles are then characterized by studying their optical properties particularly absorbance using a fiber optic spectrometer. Such complex but functional particles and structures should have potential applications in optics and other areas”--Abstract, page iii

Fabrication and characterization of Polymer Light Emitting Diodes (PLEDs) for display application

The performance of polymer light emitting diode (PLED) strongly depends on materials, fabrication and the structure of the device. Polymer light-emitting diodes typically consists of emitting layer(s) sandwiched between a cathode and an anode. In our study indium tin oxide (ITO) is used as anode, the polymer blend as emitting layer and metals such as aluminum, silver as cathodes. Investigation in this area is focused to fully understand and develop the method of fabrication of PLEDs using the available resources and to understand the effect of variation of blend ratios of polyfluorene polymers (TFB: 9, 9\u27-dioctylfluorene-co-N-(4-butylphenyl) diphenylamine and F8BT: poly (9, 9\u27dioctylfluorene- co-benzothiadiazole)), different cathodes, addition of buffer layer (calcium acetylacetonate [Ca (acac)z]) on the built devices

TRADITIONAL USED PLANTS AGAINST COGNITIVE DECLINE

The medicinal plants in classical literature of Ayurved and traditional folk care health practices provide clues to new area of pharmaceutical research. The numbers of plants had been mentioned in Ayurveda for curing various pathophysiological stages of ailment and these are being practiced in various traditional streams in different parts of India. The present study aims to focus selected herbs that can be beneficial over psychological factors like cognition. Cognitive behavioral performance can be commonly noticed with gradually increasing forgetfulness generally due to old age or some neuropathological factors. It may troublesome or embarrassing to observe such suffering individual with mild behavior problems. But consistent or increasing concern about your mental performance may suggest Cognitive Decline. Ayurveda consider three Gunas i.e., Satva, Raja and Tama along with Tridoshas and their disequilibrium leads to abnormal functioning and behavior pattern of mental health. The significance of mental health is equally empathized under the definition of health by WHO along with physical health. Todays upcoming lifestyle in term of diet and regimen leads to number of Psychological factors. Cognitive Decline is one of them. The selected herbal drugs possess Sadnyastapan property and helpful in cognitive enhancement. Ayurveda mentioned list of plants that are used and practiced for the treatment neurological disorders in traditional indigenous medicine. The medicinal plants possess positive effects on various cognitive functions by means of its multifold action. The selected mentioned drugs in the study can be useful for treatment of neuropsychiatric disorders and capable of enhancing cognitive performance. These herbs can prove better medicaments in case of Cognitive Decline

EVALUATION OF ANTI-ANXIETY EFFECT OF NIFEDIPINE COMPARED TO DIAZEPAM IN SWISS ALBINO MICE USING BEHAVIOURAL MODELS

Objective: The present study was undertaken to evaluate the acute and chronic anxiolytic effects of nifedipine in comparison to diazepam using in Swiss Albino mice using two behavioral models. Methods: 30 Swiss albino mice were divided into 5 groups with 6 mice in each group. The study was conducted in two phases to evaluate acute and chronic effects. The groups consisted of diazepam (1 mg/kg), 3 doses of nifedipine (2.6 mg/kg, 5.2 mg/kg and 10.4 mg/kg) and vehicle control. The Elevated Plus Maze (EPM) and Light and Dark box were used to evaluate the anti-anxiety effects. The number of entries and time spent in the open arm of the elevated plus-maze and in the light area of light and dark box model were noted and compared among the 5 groups. Observations were analyzed using ANOVA and post hoc Tukey's test. Results: Nifedipine (5.2 mg/kg and 10.4 mg/kg) significantly increased the number of entries and time spent in the open arm compared to vehicle control in the EPM test (p<0.001). Similarly, in the light and dark box test, nifedipine (5.2 mg/kg and 10.4 mg/kg) increased the number of entries and time spent in the light area compared to vehicle control (p<0.05). However, the low dose of nifedipine (2.6 mg/kg) did not exhibit significant findings. Conclusion: Two doses of nifedipine (5.2 mg/kg and 10.4 mg/kg) possess anti-anxiety effects both on acute and chronic administration in both elevated plus maze and light and dark box model

Example-based Explanations for Random Forests using Machine Unlearning

Tree-based machine learning models, such as decision trees and random forests, have been hugely successful in classification tasks primarily because of their predictive power in supervised learning tasks and ease of interpretation. Despite their popularity and power, these models have been found to produce unexpected or discriminatory outcomes. Given their overwhelming success for most tasks, it is of interest to identify sources of their unexpected and discriminatory behavior. However, there has not been much work on understanding and debugging tree-based classifiers in the context of fairness. We introduce FairDebugger, a system that utilizes recent advances in machine unlearning research to identify training data subsets responsible for instances of fairness violations in the outcomes of a random forest classifier. FairDebugger generates top-$k$ explanations (in the form of coherent training data subsets) for model unfairness. Toward this goal, FairDebugger first utilizes machine unlearning to estimate the change in the tree structures of the random forest when parts of the underlying training data are removed, and then leverages the Apriori algorithm from frequent itemset mining to reduce the subset search space. We empirically evaluate our approach on three real-world datasets, and demonstrate that the explanations generated by FairDebugger are consistent with insights from prior studies on these datasets

Ayurvedic approach of hypertension and prevention through Ayurveda

Modernization in medical field has changed the understanding of illness. Many a diseases has been vanished and newer emerged with the time. Hypertension is one among them, a newer condition which has been creating burden on health expenditure of mankind and being the risk factor for many diseases. Hypertension is not curable condition, so the prevention is major factor to avoid the condition. Hypertension is not directly mentioned in ayurvedic literature but knowledge prevailing to the condition is scattered under different headings in Ayurveda classics. This article is an attempt to conceptualize and to search preventive measures in Ayurveda

Automatic Partial Code Generation using Class and Sequence Diagrams

The main objective is to provide overview of one of the Model Driven Engineering Tool i.e. Transformation tool. Model Driven engineering tool is used to develop, interpret, compare, align, measure, verify, transform, etc. models or Meta models. Model is interpreted as “UML Model”. UML based approach provides abstraction to deal with the complex embedded applications and when combined with Model-driven Engineering can also provide automation through automatic code generation. This paper presents an approach to generate structural and behavioral code from UML class and sequence implementation of a code generator

E-Resources are boon for the teaching and research work of an academic institute: A survey on usage and awareness of e-resources by the NMIMS (Deemed University) engineering faculties, Mumbai

Information is a nervous system for the teacher and researcher, without the information they cannot teach and generate new information in an academic institute. The information and communication technology tools have changed the mode of communication and availability of information in a digital environment. In this study, efforts have been made to study the use and awareness of e-resources by the engineering faculties of NMIMS (Deemed to be University), Mumbai. The result shows that majority of the faculty members i.e. 85.71 % access e-resources for the research and learning purpose, it is also found that busy schedule in the institute prevents the effective and efficient use of the e-resources i.e. 552.38 % respondents