Proper utilization of antenatal and postnatal care services plays an important role in reducing the maternal mortality ratio and infant mortality rate. This paper assesses the utilization of health care services during pregnancy, delivery and post-delivery among rural women in Uttar Pradesh and examines its determinants. Data from a baseline survey of UP Community Mobilization project was utilized. A cross-sectional sample of currently married women who delivered a baby 15 months prior to the survey was included. Information was collected from (...) 2208 women spread over five districts of UP. Information on socio-demography characteristics, utilization of antenatal care, delivery and postnatal care services was collected. To examine the determinants of utilization of maternal health services, the variables included were three ANC visits, institutional delivery and PNC within 42 days of delivery. Separate multilevel random intercept logistic regressions were used to account for clustering at a block and gram panchayat level after adjusting for covariates. Eighty-three percent of women had any ANC. Of them, 61% reported three or more ANC visits. Although 68% of women delivered in a health facility, 29% stayed for at least 48 h. Any PNC within 42 days after delivery was reported by 26% of women. In the adjusted analysis, women with increasing number of contacts with the health worker during the antenatal period, women exposed to mass-media and non-marginalized women were more likely to have at least three ANC visits during pregnancy. Non-marginalized women and women with at least three ANC visits were more likely than their counterparts to deliver in an institution. Contacts with health worker during pregnancy, marginalization, at least three ANC visits and institutional delivery were the strong determinants for utilization of PNC services. Self-help group membership had no association with the utilization of maternal health services. Utilization of maternal health services was low. Contact with the health worker and marginalization emerged as important factors for utilization of services. Although not associated with the utilization, SHGs can be used for delivering health care messages within and beyond the group. (shrink)

Chromatin structure and dynamics regulate key cellular processes such as DNA replication, transcription, repair, remodeling, and gene expression, wherein different protein factors interact with the nucleosomes. In these events, DNA and RNA polymerases, chromatin remodeling enzymes and transcription factors interact with nucleosomes, either in a DNA‐sequence‐specific manner and/or by recognizing different structural features on the nucleosome. The molecular details of the recognition of a nucleosome by different viral proteins, remodeling enzymes, histone post‐translational modifiers, and RNA polymerase II, have been explored (...) in the recent past. The present review puts forth critical insights into the basic mechanisms of nucleosome recognition by the various protein factors and the role of distinct surface epitopes on a nucleosome. These determinants of the underlying specificity include features such as the acidic patch, arginine anchor, histone post‐translational modifications, core DNA, DNA lesions, and linker DNA. (shrink)

Emotions are multimodal processes that play a crucial role in our everyday lives. Recognizing emotions is becoming more critical in a wide range of application domains such as healthcare, education, human-computer interaction, Virtual Reality, intelligent agents, entertainment, and more. Facial macro-expressions or intense facial expressions are the most common modalities in recognizing emotional states. However, since facial expressions can be voluntarily controlled, they may not accurately represent emotional states. Earlier studies have shown that facial micro-expressions are more reliable than facial (...) macro-expressions for revealing emotions. They are subtle, involuntary movements responding to external stimuli that cannot be controlled. This paper proposes using facial micro-expressions combined with brain and physiological signals to more reliably detect underlying emotions. We describe our models for measuring arousal and valence levels from a combination of facial micro-expressions, Electroencephalography (EEG) signals, galvanic skin responses (GSR), and Photoplethysmography (PPG) signals. We then evaluate our model using the DEAP dataset and our own dataset based on a subject-independent approach. Lastly, we discuss our results, the limitations of our work, and how these limitations could be overcome. We also discuss future directions for using facial micro-expressions and physiological signals in emotion recognition. (shrink)