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"Rao, Krishna"
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Climate Change and Long-Run Discount Rates
We show that housing markets provide information about the appropriate discount rates for valuing investments in climate change abatement. Real estate is exposed to both consumption and climate risk and its term structure of discount rates is downward sloping, reaching 2.6% for payoffs beyond 100 years. We use a tractable asset pricing model that incorporates features of climate change to show that the term structure of discount rates for climate-hedging investments is thus upward sloping but bounded above by the risk-free rate. At horizons at which risk-free rates are unavailable, the estimated housing discount rates provide an upper bound.
Journal Article
Distinct etiology of chronic inflammation – implications on degenerative diseases and cancer therapy
Acute inflammation is elicited by lipid and protein mediators in defense of the host following sterile or pathogen-driven injury. A common refrain is that chronic inflammation is a result of incomplete resolution of acute inflammation and behind the etiology of all chronic diseases, including cancer. However, mediators that participate in inflammation are also essential in homeostasis and developmental biology but without eliciting the clinical symptoms of inflammation. This non-inflammatory physiological activity of the so called ‘inflammatory’ mediators, apparently under the functional balance with anti-inflammatory mediators, is defined as unalamation ( un-ala-mation ). Inflammation in the absence of injury is a result of perturbance in unalamation due to a decrease in the anti-inflammatory mediators rather than an increase in the inflammatory mediators and leads to chronic inflammation. This concept on the etiology of chronic inflammation suggests that treatment of chronic diseases is better achieved by stimulating the endogenous anti-inflammatory mediators instead of inhibiting the ‘inflammatory’ mediator biosynthesis with Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). Furthermore, both ‘inflammatory’ and anti-inflammatory mediators are present at higher concentrations in the tumor microenvironment compared to normal tissue environments. Since cancer is a proliferative disorder rather than a degenerative disease, it is proposed that heightened unalamation , rather than chronic inflammation, drives tumor growth. This understanding helps explain the inefficacy of NSAIDs as anticancer agents. Finally, inhibition of anti-inflammatory mediator biosynthesis in tumor tissues could imbalance unalamation toward local acute inflammation triggering an immune response to restore homeostasis and away from tumor growth.
Journal Article
R deep learning cookbook : solve complex neural net problems with TensorFlow, H2O and MXNet
This book aims to provide a crash course in building different deep learning models. The application of deep leaning is demonstrated through structures, unstructured, image, and audio case studies. The book also covers transfer learning and how to utilize the power of GPU to enhance the computation efficiency of the deep learning model.
Book
What do we know about community-based health worker programs? A systematic review of existing reviews on community health workers
Objective
To synthesize current understanding of how community-based health worker (CHW) programs can best be designed and operated in health systems.
Methods
We searched 11 databases for review articles published between 1 January 2005 and 15 June 2017. Review articles on CHWs, defined as non-professional paid or volunteer health workers based in communities, with less than 2 years of training, were included. We assessed the methodological quality of the reviews according to AMSTAR criteria, and we report our findings based on PRISMA standards.
Findings
We identified 122 reviews (75 systematic reviews, of which 34 are meta-analyses, and 47 non-systematic reviews). Eighty-three of the included reviews were from low- and middle-income countries, 29 were from high-income countries, and 10 were global. CHW programs included in these reviews are diverse in interventions provided, selection and training of CHWs, supervision, remuneration, and integration into the health system. Features that enable positive CHW program outcomes include community embeddedness (whereby community members have a sense of ownership of the program and positive relationships with the CHW), supportive supervision, continuous education, and adequate logistical support and supplies. Effective integration of CHW programs into health systems can bolster program sustainability and credibility, clarify CHW roles, and foster collaboration between CHWs and higher-level health system actors. We found gaps in the review evidence, including on the rights and needs of CHWs, on effective approaches to training and supervision, on CHWs as community change agents, and on the influence of health system decentralization, social accountability, and governance.
Conclusion
Evidence concerning CHW program effectiveness can help policymakers identify a range of options to consider. However, this evidence needs to be contextualized and adapted in different contexts to inform policy and practice. Advancing the evidence base with context-specific elements will be vital to helping these programs achieve their full potential.
Journal Article
Health equity and COVID-19: global perspectives
The COVID-19 is disproportionally affecting the poor, minorities and a broad range of vulnerable populations, due to its inequitable spread in areas of dense population and limited mitigation capacity due to high prevalence of chronic conditions or poor access to high quality public health and medical care. Moreover, the collateral effects of the pandemic due to the global economic downturn, and social isolation and movement restriction measures, are unequally affecting those in the lowest power strata of societies. To address the challenges to health equity and describe some of the approaches taken by governments and local organizations, we have compiled 13 country case studies from various regions around the world: China, Brazil, Thailand, Sub Saharan Africa, Nicaragua, Armenia, India, Guatemala, United States of America (USA), Israel, Australia, Colombia, and Belgium. This compilation is by no-means representative or all inclusive, and we encourage researchers to continue advancing global knowledge on COVID-19 health equity related issues, through rigorous research and generation of a strong evidence base of new empirical studies in this field.
Journal Article
Macro to micro
Although primarily valued for their suitability for oceanographic applications and soil moisture estimation, microwave remote sensing observations are also sensitive to plant water content (M
w). Since M
w depends on both plant water status and biomass, these observations have the potential to be useful for a range of plant drought response studies. In this paper, we introduce the principles behind microwave remote sensing observations to illustrate how they are sensitive to plant water content and discuss the relationship between landscape-scale M
w and common stand-scale metrics, including plant-scale relative water content, live fuel moisture content and leaf water potential. Lastly, we discuss how various sensor types can be leveraged for specific applications depending on the spatio-temporal resolution needed.
Journal Article
Systematic Review on Impact of Different Irradiance Forecasting Techniques for Solar Energy Prediction
As non-renewable energy sources are in the verge of exhaustion, the entire world turns towards renewable sources to fill its energy demand. In the near future, solar energy will be a major contributor of renewable energy, but the integration of unreliable solar energy sources directly into the grid makes the existing system complex. To reduce the complexity, a microgrid system is a better solution. Solar energy forecasting models improve the reliability of the solar plant in microgrid operations. Uncertainty in solar energy prediction is the challenge in generating reliable energy. Employing, understanding, training, and evaluating several forecasting models with available meteorological data will ensure the selection of an appropriate forecast model for any particular location. New strategies and approaches emerge day by day to increase the model accuracy, with an ultimate objective of minimizing uncertainty in forecasting. Conventional methods include a lot of differential mathematical calculations. Large data availability at solar stations make use of various Artificial Intelligence (AI) techniques for computing, forecasting, and predicting solar radiation energy. The recent evolution of ensemble and hybrid models predicts solar radiation accurately compared to all the models. This paper reviews various models in solar irradiance and power estimation which are tabulated by classification types mentioned.
Journal Article