Providing dental and oral health care to all children in Kerala remains a thorny challenge. Lack of community water fluoridation, dental workforce shortages and geographical barriers all aggravate oral health and access problems. Children from low-income and minority families and children with special needs are at particular risk. Family centered disease prevention strategies are needed to reduce oral health disparities in children. Oral health promotion can take place in a primary care practitioner's office, but medical providers often lack relevant training. Present study was conducted to evaluate knowledge and attitude of graduating medical students towards infant oral health qualitative methods were used to evaluate the program.
Crystallization is an important physicochemical process which has relevance in material science, biology, and the environment. Decades of experimental and theoretical efforts have been made to understand this fundamental symmetry-breaking transition. While experiments provide equilibrium structures and shapes of crystals, they are limited to unraveling how molecules aggregate to form crystal nuclei that subsequently transform into bulk crystals. Computer simulations, mainly molecular dynamics (MD), can provide such microscopic details during the early stage of a crystallization event. Crystallization is a rare event that takes place in time scales much longer than a typical equilibrium MD simulation can sample. This inadequate sampling of the MD method can be easily circumvented by the use of enhanced sampling (ES) simulations. In most of the ES methods, the fluctuations of a system's slow degrees of freedom, called collective variables (CVs), are enhanced by applying a bias potential. This transforms the system from one state to the other within a short time scale. The most crucial part of such CV-based ES methods is to find suitable CVs, which often needs intuition and several trialand-error optimization steps. Over the years, a plethora of CVs has been developed and applied in the study of crystallization. In this review, we provide a brief overview of CVs that have been developed and used in ES simulations to study crystallization from melt or solution. These CVs can be categorized mainly into four types: (i) spherical particle-based, (ii) molecular template-based, (iii) physical property-based, and (iv) CVs obtained from dimensionality reduction techniques. We present the context-based evolution of CVs, discuss the current challenges, and propose future directions to further develop effective CVs for the study of crystallization of complex systems.
The main purpose of the study is to compare the digital library job requirements and the curriculum offered in Indian LIS departments. Data were obtained from two sources: 180 job advertisements obtained through online job sites and course outlines obtained from the websites of 21 universities. The content analysis method was followed in the research for data analysis. The findings indicate that employers demand good communication skills and ability of working on digital library software, handling library management software, knowledge of basic computer skills, programming and markup languages. Job ads also indicate that a bachelors’ and masters’ degree programme in library and information science are the minimum essential requirements for employing digital library professionals. The study also found that there is no separate digital library programme offered whereas digital library course contents are integrated into BLIS & MLIS programmes. The digital library topics such as training students in using library management software, digital library software and content management systems; creating databases using MySql; website designing are offered at both bachelor’s and master’s degree levels. This paper compares what is demanded in the job market and what is offered by LIS departments and found that the curriculum does not fully address the needs of the job market, as certain topics such as troubleshooting and problem solving skills were seen missing from the Indian LIS curricula.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.