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Biogas is a viable alternative for supplying clean and sustainable energy. Despite all manner of policy measures introduced by the Government of India, biogas is not widely used in India. This article tries to identify factors that influence the decision to adopt biogas at household level. We examine a conceptual framework empirically in which a household wants to maximize utility from biogas by using the India Human Development Survey (IHDS) I, which is a nationally representative, multi-topic survey. By applying both maximum likelihood and penalized likelihood methods (Firthlogit) of logistic regression on a sample size of almost 10,384 households, it has been found that wealthy people are more likely to adopt biogas compared to the marginalized section of the society. We recommend more inclusive policy measures for the weaker section of the society to create an enabling environment to make it a self-promoting technology.

This review presents recent advancements in high-voltage rechargeable aqueous batteries employing water-in-salt and modified water-in-salt electrolytes.

Abstract Globally, three-quarter of a billion people live without electricity. Besides, hundreds of million use a solar lantern for less than 4 h a day. Most of the access-deprived are in the Global South, predominantly in Sub-Saharan Africa and South Asia. The United Nations framed the seventh Sustainable Development Goal to improve access. Solar photovoltaic powered mini-grids are increasingly extending better service to deprived regions. However, poor load-factor and expensive storage adversely affect viability. Also, these mini-grids do not support infrequent large loads to avoid further loss of load-factor. Electric cooking is efficient and non-polluting; water treatment facilities can save millions from contaminant and pathogen by providing clean water. Besides, both electric cooking and water treatment are less expensive than alternatives. But mini-grids frequently do not support these. Indeed, the presence of sustained productive loads favourably influences the mini-grid economy. This study investigates the role of critical household loads to deliver similar bearing on the mini-grid economy. Results underscore realisation of desirable impact with household collaboration under a demand-response program. Collaborative consumption can lower initial investment by 62% and reduce the unit energy cost to $0.23. Also, cooperation improves the mini-grid load factor and promotes viability. Additionally, fast deployment needs during and after Covid-19 remains inherently supported while mitigating the pandemic induced financial stress of both consumer and mini-grid operator. This study of 88 nation-states underscores that demand response in a mini-grid can not only improve affordability for all consumers, but it can also bring 186 million people within affordable access.

Abstract Natural resources exist independent of human intervention. Although these interventions can and do affect the balance between ecological and biological diversity conditions these resources support, and their use to promote economic development. Currently, the unsustainable use of these resources threatens this balance, calling for more sustainable patterns of natural resource use and conservation. The primary responsibility for ensuring the proper balance lies with governments, leading to various policies and programs to preserve natural resources. The ultimate goal is to make the masses aware of natural assets’ importance and encourage their sustainable use. To successfully implement, however, these government practices require public communication and participation, and the full consideration of public opinion at various levels of governance. A predictive analytics framework is proposed for understanding public opinion on government policies to improve sustainable water governance. An integrated policy initiative to balance water resources use and conservation launched by the Indian government served as a test case for applying the framework in an attempt to accurately classify the opinion polarity related to the policy. The conventional feature extraction is applied to pre-processed datasets to extract the relevant features. Subsequently, swarm-based feature selection is applied to filter out optimal features. Lastly, opinion mining and textual analysis are performed to determine the most relevant water management factors that need immediate attention. The proposed framework serves as a policy evaluation strategy in the water management domain. The paper closes with a discussion of the general applicability of the proposed framework.

Chronic alcohol consumption induces myocardial damage and a type of non-ischemic cardiomyopathy termed alcoholic cardiomyopathy, where mitochondrial ultrastructural damages and suppressed fusion activity promote cardiomyocyte apoptosis. The aim of the present study is to determine the role of mitochondrial fission proteins and/or other proteins that localise on cardiac mitochondria for apoptosis upon ethanol consumption. In vivo and in vitro chronic alcohol exposure increased mitochondrial Drp1 levels but knockdown of the same did not confer cardioprotection in H9c2 cells. These cells displayed downregulated expression of MFN2 and OPA1 for Bak-mediated cytochrome c release and apoptosis. Dysregulated PTEN/AKT cell survival signal in both ethanol treated and Drp1 knockdown cells augmented oxidative stress by promoting mitochondrial PTEN-L and MFN1 interaction. Inhibiting this interaction with VO-OHpic, a reversible PTEN inhibitor, prevented Bak insertion into the mitochondria and release of cytochrome c to cytoplasm. Thus, our study provides evidence that Drp1-mediated mitochondrial fission is dispensable for ethanol-induced cardiotoxicity and that stress signals induce mitochondrial PTEN-L accumulation for structural and functional dyshomeostasis. Our in vivo results also demonstrates the therapeutic potential of VO-OHpic for habitual alcoholics developing myocardial dysfunction.

Fatty liver diseases are the most common and major health concern arises from the modern lifestyle and alcohol (ethanol) abuse. The prevalence of non-alcoholic fatty liver diseases (NAFLD) has been observed prominently in obese and diabetic individuals, while alcoholic liver disease is common in alcoholic persons. Fatty liver disease, such as steatohepatitis, leads to fibrosis, cirrhosis and eventually hepatocellular carcinoma. The present study was designed to investigate the effect of 7,8-Dihydroxyflavone (7,8-DHF) against high-fat diet (HFD) and ethanol (EtOH)-induced hepatotoxicity in rats.Male Wistar rats (150-200 g) were fed HFD (58% calories from fat) and EtOH (3-15% in drinking water) for 12 weeks. 7,8-DHF was administered intraperitoneally at the dose of 5 mg/kg/day for the last four weeks. After 12 weeks, biochemical, ELISA, RT-PCR, and histological studies have been carried out.Biochemical analyses revealed the involvement of oxidative stress and inflammation in the liver of HFD and EtOH-fed rats. 7,8-DHF treatment significantly reduced HFD and EtOH-induced oxidative stress as evidenced by the reduction of lipid peroxidation and augmentation of reduced glutathione level. Moreover, IL-1β level was found significantly reduced in 7,8-DHF treated EtOH, HFD and EtOH+HFD groups. The semi-quantitative RT-PCR results indicated down-regulation of Nrf-2 and HO-1 and up-regulation of NF-κB and iNOS mRNA expression level in the liver of HFD and EtOH-fed rats, which was ameliorated by 7,8-DHF treatment.The present study suggested that 7,8-DHF could be an effective pharmacological intervention in combating HFD and EtOH-induced hepatotoxicity.

Residential buildings constitute roughly one-fourth of the total energy use across the globe. Numerous studies have shown that providing an energy breakdown increases residents' awareness of energy use and can help save up to 15% energy. A significant amount of prior work has looked into source-separation techniques collectively called non-intrusive load monitoring (NILM), and most prior NILM research has leveraged high-frequency household aggregate data for energy breakdown. However, in practice most smart meters only sample hourly or once every 15 minutes, and existing NILM techniques show poor performance at such a low sampling rate. In this paper, we propose a TreeCNN model for energy breakdown on low frequency data. There are three key insights behind the design of our model: i) households consume energy with regular temporal patterns, which can be well captured by filters learned in CNNs; ii) tree structure isolates the pattern learning of each appliance that helps avoid magnitude variance problem, while preserves relationship among appliances; iii) tree structure enables the separation of known appliance from unknown ones, which de-noises the input time series for better appliance-level reconstruction. Our TreeCNN model outperformed seven existing baselines on a public benchmark dataset with lower estimation error and higher accuracy on detecting the active states of appliances.

Light‐emitting solar cells (LESCs) have tremendous potential in the next‐generation optoelectronics industry due to their excellent photophysical properties and general configurational advantages. The important feature of these LESC devices is that it can reversibly transduce optical energy to electrical energy and vice versa in a single platform. Consequently, they have significant potential in the development of solar light‐emitting diode (LED) street lights in rural, semiurban, and urban areas. However, their commercial development has been limited so far due to the complex device geometry, unfavorable alignment of energy levels, poor quality of transport layers, incomplete coverage of the solar spectrum, and more notably, intrinsic instability of perovskites. Herein, the recent developments in the field are discussed, followed by a critical analysis of major challenges and possible solutions to overcome these challenges. Finally, a roadmap for the successful development of efficient and stable dual‐functioning perovskite‐based LESCs is provided, which can be useful for the energy industry.

Abstract Energy demand for space cooling in residential buildings is projected to witness rapid growth, primarily fueled by increasing household incomes in developing countries. To manage this ever-increasing cooling demand, integration of phase change materials (PCMs) in building walls is a potential solution that can reduce the buildings’ cooling energy consumption and peak cooling loads. However, to attain the proposed benefits from PCM integration, it is crucial to appropriately select PCM parameters such as its phase-change temperature and positioning in the wall. Thus, this investigation studied the energy performance of PCM integrated brick masonry walls for cooling load management in residential buildings under periodic steady-state conditions to identify the parameters that govern its performance and develop simple design guidelines. The research found that regardless of the amount of latent heat stored by the PCM, the daily heat gains and cooling loads were equal for wall configurations having equal thermal resistances under identical boundary conditions. Furthermore, even with the application of night ventilation, adding a PCM layer to a well-insulated wall did not reduce its cooling load; thus, PCM integration was ineffective in reducing the cooling load. However, the latent heat stored by the PCM reduced the fluctuations in the hourly heat gains and cooling loads; thus, PCM integration was found suitable for peak load management. For the PCM's proper utilization, its recommended position is on the inner side of the wall with sufficient insulation shielding it from outdoor conditions, and its melting temperature should be close to the indoor set-point temperature.