KNOWLEDGE OF HIV/AIDS AMONG MEDICAL STUDENTS IN A TERTIARY CARE TEACHING HOSPITAL IN EASTERN INDIA-A CROSS-SECTIONAL STUDY

Objective- To evaluate the knowledge of HIV/AIDS among medical students in a tertiary care teaching hospital in Eastern India. Materials and Methods- Open level, cross sectional, observational and unicentric clinical trial was done among medical students of College of Medicine & JNM Hospital, Kalyani, Nadia, West Bengal, India. All the students (201) who were attending their scheduled lecture classes were given the questionnaire form, and all queries about the trial/questions were explained thoroughly. The form was filled up by each student separately, references like books, internet etc were not allowed. Forms submission box was placed in the table of lecture theatre. After 15 minutes, and students were asked to submit their forms in that box individually. Filled up forms were collected from the all attending students of all semester batch in the same day. Statiscal analysis was done in Department of Pharmacology.   Result & Analysis-100% students have heard the terms HIV, AIDS, STD. Female students know better than male students about the differences between HIV and AIDS, sign and symptoms of HIV. Although there is no difference about knowledge of mode of transmission of HIV, but female students are more awarded the vertical transmission from mother to child (p-0.006).Female students know better than male students about precaution to protect health worker dealing with an AIDS patient (p-0.0001).   Conclusion- Although, majority of students have the basic knowledge of HIV/AIDS, but periodical academic activities (Seminars, CME etc) are required to upgrade the informations about HIV/AIDS

Machine learning -- based diffractive imaging with subwavelength resolution

Far-field characterization of small objects is severely constrained by the diffraction limit. Existing tools achieving sub-diffraction resolution often utilize point-by-point image reconstruction via scanning or labelling. Here, we present a new imaging technique capable of fast and accurate characterization of two-dimensional structures with at least wavelength/25 resolution, based on a single far-field intensity measurement. Experimentally, we realized this technique resolving the smallest-available to us 180-nm-scale features with 532-nm laser light. A comprehensive analysis of machine learning algorithms was performed to gain insight into the learning process and to understand the flow of subwavelength information through the system. Image parameterization, suitable for diffractive configurations and highly tolerant to random noise was developed. The proposed technique can be applied to new characterization tools with high spatial resolution, fast data acquisition, and artificial intelligence, such as high-speed nanoscale metrology and quality control, and can be further developed to high-resolution spectroscop