Titlebook: Himalaya on the Threshold of Change; Vishwambhar Prasad Sati Book 2020 Springer Nature Switzerland AG 2020 Climate Change in the Himalaya.

Morsel

Population, Social and Economic Changes. Besides, a group of people belong to Scheduled Tribes. Caste system prevailed during the past whereas, in due course of time, it has diluted. Occupational structure of all the segments of society has been changing from practicing agriculture to working in the service sector.

slow-wave-sleep

Sustainable Development Under Changing Environmentvelopment of abundance natural resources. In this chapter, the major sectors of development and several policy measures such as sectoral approach, social inclusion and development of infrastructural facilities have been described broadly.

APNEA

Migration and Agrarian Changen of traditional cereals has decreased while, wheat and paddy is largely growing in the river valleys and the mid-altitudes. This chapter describes about migration and agrarian changes in the Uttarakhand Himalaya.

保留

policy makers have to deal with raising socioeconomic disparities and need for environmental interventions to reduce pollution and improve wellbeing. The PULSE project, funded by the EU commission under the H2020 program, aims at providing an instrument that assesses health and wellbeing in cities t

climax

ding to patient’s specific characteristics. A critical step towards this goal is the interpretation of genomic variants, whose presence can be revealed by next generation sequencing. In particular, cancer variant interpretation defines whether the patient harbors genomic alterations that could be ta

Anthology

CUB

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Vishwambhar Prasad Satiphysicians to annotate condition severity are time-consuming and costly. Previously, a passive learning algorithm called CAESAR was developed to capture severity in EHRs. This approach required physicians to label conditions manually, an exhaustive process. We developed a framework that uses two Act

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NICE

Vishwambhar Prasad Satiphysicians to annotate condition severity are time-consuming and costly. Previously, a passive learning algorithm called CAESAR was developed to capture severity in EHRs. This approach required physicians to label conditions manually, an exhaustive process. We developed a framework that uses two Act