ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Renewable integration for remote communities: Comparative allowable cost analyses for hydro, solar and wave energy

Many remote communities are reliant on diesel-fueled electricity generation. The extra-ordinary logistical and financial complications in acquiring fuel often result in energy poverty. To alleviate these realities, and simultaneously mitigate noise and emissions, communities are focused on harnessing local renewable resources to achieve aggressive decarbonization and renewable energy penetration. This study quantifies the diesel and emissions mitigation potential of micro-hydro, solar and wave energy; and defines 'allowable-cost' Levelized Cost of Energy (LCOE) targets. Through the application of a bottom-up, time domain energy systems model, Remote Community Optimization Model (RCOM), differing renewable options (including wave, micro-hydro and solar) are compared. The RCOM model formulates the community's energy system operation as a cost minimization optimization problem and generates an hourly dispatch strategy. Comparing hybrid renewables-based systems to the diesel only case, the maximum allowable LCOE values for each renewable energy system to provide economic benefit to the local community are quantified. Additional sensitivities to resource availability, emissions pricing and fuel costs are explored through scenario-based sensitivity analyses. Utilizing RCOM for Hot Springs Cove (remote Canadian community), the diesel system results in LCOE of $0.76/kWh. The development of a small hydro system (225 kW) reduces the community's fuel costs by similar to$5.2 M over the 30-yr. project lifetime. However, these savings are less than the upfront construction capital, and the associated LCOE increases to $1.36/kWh. Based on the novel 'allowable-cost' analysis, wave energy was found to provide economic benefit if the supplied power could be delivered for less than $0.59/kWh; with the added benefit of reducing diesel consumption by 40%, and returning $23,206/kW installed. Comparatively, integrating solar had an allowable-cost LCOE of $0.53/kWh, reduced diesel consumption by only 12%, and gave a return of $6844/kW installed.
Renewable energy consumption and economic growth in OECD countries: A nonlinear panel data analysis

What impact will increasing renewable energy consumption have on economic growth? What is the direction or magnitude of the impact and the determinants behind it? Existing research on the relationship between renewable energy and economic growth focuses on the linear relationship, whereas ignoring the non-linear relationship between them. In this study, the nonlinear relationship between renewable energy and economic growth in OECD countries was investigated by developing panel threshold regression models. Non-renewable energy intensity, urbanization level and per capita income are used as threshold variables to explore the internal mechanism of renewable energy for economic development. Three panel threshold models are developed based on these three threshold variables. The results show that the effect of renewable energy consumption on economic growth is positive, which indicates that increased renewable energy consumpiotn contributes to economic growth. In addition, this positive relationship changes as the threshold value changes, which means that the role of increasing renewable energy consumption to promote economic development is nonlinear. In other words, if the EU countries increase their renewable energy consumption by more than a certain amount (threshold value), the role of renewable energy consumption in promoting economic development is more significant. (C) 2020 Elsevier Ltd. All rights reserved.
Explaining the political nature of environmental impact assessment (EIA): A neo-Gramscian perspective

Environmental Impact Assessment (EIA) is a mandatory decision-support tool in every country of the world, developed 50 years ago to ensure the consideration of the environmental consequences of development decisions prior to approval decisions being made. Specifically, the aim of developing an EIA system was to make decision-making affecting the environment more accountable, through the use of objective scientific evidence. It remains the project decision-support tool of choice despite considerable research efforts failing to provide convincing evidence that it achieves this aim. Here we explain this apparent paradox by arguing that EIA supports neoliberal agendas by facilitating economic development. We present arguments based on a neo-Gramscian perspective that explains how apparent advances in the practice of EIA are sanctioned because they actually maintain the political nature of the EIA system, which continues to undermine attempts to use evidence objectively. We use a narratives of change approach to support this perspective. We conclude that EIA can only make decision-making more accountable if strategies to depoliticise it are employed, including emphasising substantive outcomes. (C) 2019 Elsevier Ltd. All rights reserved.
Measuring environmental sustainability performance of South Asia

Sustainability and low-carbon economy strategies have been widely studied in the past; nevertheless, researchers often ignore the effects of combining energy, economic, and environmental factors when assessing sustainability performance. To fill this gap, we measure the environmental sustainability performance of South Asia using a common weight Data Envelopment Analysis (DEA)-like mathematical model encompassing a comprehensive, up-to-date, and relevant set of indicators. In this paper, we present a measurement of South Asia's environmental sustainability performance for the years 2001-2015. Our results reveal that Bhutan outperforms the rest of the countries in South Asia, with an overall index score of 0.72. Nepal comes second in the region, with a stable score, followed by the Maldives. Afghanistan and Bangladesh are ranked fourth and fifth, respectively, and their overall scores indicate strong potential sustainability performances. India, Sri Lanka and Pakistan follow this list, with poor scores, with Pakistan having the lowest scores during the study period. Based on these findings, we propose a policy to boost the cross-border renewable energy trade for long-term environmental sustainability. (C) 2019 Elsevier Ltd. All rights reserved.
Alcoholic fixation over formalin fixation: A new, safer option for morphologic and molecular analysis of tissues

Formalin is a widely used fixative but there is potential public health risks to exposure. Besides, alcoholic fixation is advantageous over formalin fixation because of faster fixation, optimal preservation and safer workplace environment. Following fixation by EMA and 10% neutral buffered formalin (NBF), we analyzed the tissue morphology, antigenic stability, DNA and RNA quantity with quality (OD value). The findings of EMA fixing on both the tissue morphology and molecular characterization, were satisfactory. Specially, EMA was faster in penetration of tissues than NBF, fixed ideally as early as 8 h of fixation whereas improper fixation was evident for NBF. In Hematoxylin and Eosin (H & E) staining, better cellular details with stronger affinity for staining were observed. In immunohistochemistry, better antigenic stability was reported for EMA-fixed tissues. The nucleic acid analysis revealed that total genomic DNA and RNA yield from EMA fixed tissues were significantly higher (P < 0.05) with superior quality than NBF fixed tissues. Our results suggest that EMA could be a potential alternative to NBF for fixation and preservation of tissues. These data provide new insights into an option for a safer working environment to support study and research.
Histomorphological and Biochemical Analysis of Rat Model of Menopausal Skin Aging

The study examined the skin histomorphology and biochemistry in mature ovariectomized rats treated and not treated with estrogen. Biochemical parameters (superoxide dismutase, malondialdehyde, and hydroxyproline content) were measured in dorsal skin samples collected in 50 days after surgery. The morphology of dorsal skin was analyzed under a microscope. In ovariectomized rats, the skin levels of superoxide dismutase and hydroxyproline were significantly lower, while the superoxide dismutase content was significantly higher than in shamoperated animals (p<0.05). Estrogen therapy significantly increased the levels of superoxide dismutase and hydroxyproline and reduced superoxide dismutase level in ovariectomized rats in comparison with the corresponding parameters in untreated ovariectomized animals (p<0.05). Histomorphological analysis of the skin from non-treated ovariectomized rats revealed reduced vascularization and lower density of papillary capillaries in comparison with these parameters in sham-operated controls; estrogen treatment prevented these changes. We concluded that ovariectomized rats can be employed as a model of aging skin in menopause.
Significant impacts of COVID-19 lockdown on urban air pollution in Kolkata (India) and amelioration of environmental health

The fatal novel coronavirus (COVID-19) pandemic disease smashes the normal tempo of global socio-economic and cultural livelihood. Most of the countries impose a lockdown system with social distancing measures to arrest the rapid transmission of this virus into the human body. The objective of this study is to examine the status of air quality during and pre-COVID-19 lockdown and to recommend some long-term sustainable environmental management plan. The pollution data like PM10, PM2.5, O-3, SO2, NO(2)and CO have been obtained from State Pollution Control Board under Govt. of West Bengal. Similarly, various land surface temperature (LST) maps have been prepared using LANDSAT-8 OLI and LANDSAT-7 ETM + images of USGS. The maps of NO(2)and aerosol concentration over Indian subcontinent have been taken from ESA and NASA. The digital thematic maps and diagrams have been depicted by Grapher 13 and Arc GIS 10.3 platforms. The result shows that the pollutants like CO, NO(2)and SO(2)are significantly decreased, while the average level of O(3)has been slightly increased in 2020 during the lockdown due to close-down of all industrial and transport activities. Meanwhile, around 17.5% was the mean reduction of PM(10)and PM(2.5)during lockdown compared with previous years owing to complete stop of vehicles movement, burning of biomass and dust particles from the construction works. This study recommends some air pollution-tolerant plant species (in urban vacant spaces and roof tops) for long-term cohabitation among environment, society and development.
Evaluation of geothermal energy extraction in Enhanced Geothermal System (EGS) with multiple fracturing horizontal wells (MFHW)

The deep geothermal energy produced from Enhanced Geothermal System (EGS) has a great development prospect because of enormous potential and environmental friendliness. EGS process involves a complex thermal-hydraulic process, and fractures in EGS are main channels for fluid flow and heat transfer, the understanding of which is crucial to the sustainable utilization of geothermal reservoirs. In this paper, a 3D thermal-hydraulic coupled numerical model is proposed to describe the interaction of fluid flow and heat transfer. Besides, the EGS with multiple fracturing horizontal wells (MFHW) is adopted to evaluate the effect of multiple hydraulic fractures on geothermal energy extraction performance. The MFHW with multiple stimulated fractures could increase fluid flow path and heat exchange area significantly, thereby enhance the heat recovery ability. Firstly, we analyzed the evolution of temperature and flow fields in EGS and compared the MFHW EGS with conventional vertical EGS. Secondly, the effects of fracturing parameters, including the fracture number, fracture length, and fracture conductivity, on heat extraction performance were investigated. Finally, the cost for drilling and hydraulic fracturing in MFHW EGS was calculated. The results indicate that MFHW EGS has a higher cumulative thermal production and a better heat extraction performance than that of conventional vertical EGS. For the optimization of hydraulic fracture parameters, the cumulative thermal production firstly increases and then decreases as the fracture number increases, the cumulative thermal production curve exists an inflection point of fracture number. Longer fracture length and higher fracture conductivity could enhance the cumulative thermal production, but the output growth slows down gradually. Considering economic cost, the best fracture parameters for MFHW EGS in this paper are the fracture number of 7, the fracture length of 300 m, and the fracture conductivity of 350 mu m(2).cm, respectively. The research provides a better study for multiple fracturing horizontal wells (MFHW) EGS and helps to optimize fracture parameters and geothermal reservoir management, which is conductive to improve the geothermal energy efficiency. (C) 2019 Elsevier Ltd. All rights reserved.
Disaggregated renewable energy consumption and environmental pollution nexus in G-7 countries

Although it is widely accepted that renewable energy consumption is vital for environmental sustainability, the environmental effectiveness of individual renewable energy types is often overlooked. Therefore, this paper examined the multivariate relationship between disaggregated renewable energy (hydroelectricity, wind, solar and biomass) consumption, economic growth and environmental pollution for the period from 1991 to 2014 in G-7 (The Group of Seven) countries. The study used both augmented mean group estimator and panel bootstrap causality method to consider the cross-sectional dependence and country specific heterogeneity across G-7 countries. Empirical findings indicate that increasing biomass energy consumption was efficient to reduce carbon emission in France, Germany, Japan and the United States; increasing hydroelectricity usage was efficient to reduce carbon emission in Italy and the United Kingdom; wind energy consumption reduced emission in Canada and solar energy usage was efficient on reducing emission in France and Italy for observed period. Moreover, in case of panel, it is found that increasing hydroelectricity, biomass and wind energy consumption reduced carbon emissions while the impact of solar energy consumption is statistically insignificant in G-7 countries. In addition, the hydroelectricity consumption was found the most efficient renewable energy source to reduce environmental pollution for the panel of G-7 countries. (C) 2019 Elsevier Ltd. All rights reserved.
A hybrid framework to predict ski jumping forces by combining data-driven pose estimation and model-based force calculation

The aim of this paper is to propose a hybrid framework that combines a data-driven pose estimation with model-based force calculation in order to predict the ski jumping force from a recorded motion video. A skeletal model consisting of five joints (ear, hip, knee, ankle, and toe) and four rigid segments (head/arm/trunk or HAT, thigh, shank, and foot) connecting each joint is developed. The joint forces are calculated from the dynamic equilibrium equations, which requires the time history of joint coordinates. They are estimated from a recorded motion video using a deep neural network for pose estimation trained with human motion data. Joint coordinates can be obtained by the proposed deep neural network directly from images of jumping motion without using any markers. The validity and usefulness of the proposed method are confirmed in lab experiments. Further, our method is practically applicable to the study in a real competition environment because it is not required to attach any sensor or marker to athletes.Highlights A method to predict the ski jumping force from a recorded motion video is proposed.It combines a data-driven pose estimation with a model-based force calculation.The proposed method does not require any markers and sensors to be attached to athletes.In a laboratory environment, the relative error in the maximum jumping force is less than 7%.The method can be easily applied to a field study in a real competition environment.
Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand

Disasters such as fires, earthquakes, and floods cause severe casualties and enormous economic losses. One effective method to reduce these losses is to construct a disaster relief network to deliver disaster supplies as quickly as possible. This method requires solutions to the following problems. 1) Given the established distribution centers, which center(s) should be open after a disaster? 2) Given a set of vehicles, how should these vehicles be assigned to each open distribution center? 3) How can the vehicles be routed from the open distribution center(s) to demand points as efficiently as possible? 4) How many supplies can be delivered to each demand point on the condition that the relief allocation plan is made a priority before the actual demands are realized? This study proposes a model for risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand that solves the four problems simultaneously. The novel contribution of this study is its presentation of a new model that includes conditional value at risk with regret (CVaR-R)-defined as the expected regret of worst-case scenarios-as a risk measure that considers both the reliability and unreliability aspects of demand variability in the disaster relief facility location and vehicle routing problem. Two objectives are proposed: the CVaR-R of the waiting time and the CVaR-R of the system cost. Due to the nonlinear capacity constraints for vehicles and distribution centers, the proposed problem is formulated as a bi-objective mixed-integer nonlinear programming model and is solved with a hybrid genetic algorithm that integrates a genetic algorithm to determine the satisfactory solution for each demand scenario and a non-dominated sorting genetic algorithm II (NSGA-II) to obtain the non-dominated Pareto solution that considers all demand scenarios. Moreover, the Nash bargaining solution is introduced to capture the decision-maker's interests of the two objectives. Numerical examples demonstrate the trade-off between the waiting time and system cost and the effects of various parameters, including the confidence level and distance parameter, on the solution. It is found that the Pareto solutions are distributed unevenly on the Pareto frontier due to the difference in the number of the distribution centers opened. The Pareto frontier and Nash bargaining solution change along with the confidence level and distance parameter, respectively.
Renewable energy for sustainable rural development: Synergies and mismatches

Energy transition is increasingly regarded as a promising opportunity for the economic development of rural areas. This possibility is associated with the siting and (co-)ownership of decentralized (small-scale) renewable energy facilities. The underlying productive link, however, has been taken for granted, rather than conceptually and practically cultivated. Thus, while renewable energy-based rural development has been stated as a desired by-product of energy transitions, its potential has remained largely unfulfilled. This review aims to illuminate the ambiguous interplay between renewable energy and rural development in the context of the current trajectories of the energy transition. In doing so, we first examine different ways renewable energy may contribute to rural development and explore how the synergetic conflation of renewable energy and rural development has played out in Denmark and Scotland, as two countries that have forged ahead with renewable energy in rural areas. Second, we draw on the different experiences in the two countries to critically discuss policy-related mismatches that hamper a more efficient contribution of renewable energy to rural development, and sketch out some thoughts about the need to bring rural matters and rural communities into the discussion if the synergies between energy transition and rural development are to be taken seriously.
Revisiting the environmental Kuznets curve for city-level CO2 emissions: based on corrected NPP-VIIRS nighttime light data in China

With the increasing trend of global warming, the Chinese government faces tremendous pressure to reduce CO2 emissions. The purpose of this study is to accurately measure CO2 emissions at the city scale in China and examine the environmental Kuznets curve, thereby providing a reference for decision-making. Corrected NPP-VIIRS nighttime light data were used to accurately estimate carbon dioxide emissions at the provincial and city scales in China. Then, based on the STRIPAT model, 291 cities in China were used to verify the environmental Kuznets curve. Our results show that on the provincial scale, the R-2 between the estimated value and the statistical value of carbon dioxide reaches 0.85. Western cities in China emit more CO2, as do economically developed cities and industry- and mining-dominated cities. There are two CO2 emission hot spots in the north and one cold spot in the south. It was found that the environmental Kuznets curve on the city scale exists. This study has practical value in utilizing NPP-VIIRS data for the estimation of city CO2 emissions. The results also have academic value for determining factors that contribute to carbon dioxide emissions and can provide a reference for relevant decision makers. This study could be considered the first to simulate CO2 emissions at the provincial and city levels in China based on a NPP-VIIRS nighttime light model to explore the associated geographical distribution characteristics and potential influencing factors. (C) 2020 Elsevier Ltd. All rights reserved.
Los posibles mecanismos de pardeamiento del tejido adiposo blanco: una diana novedosa para el tratamiento de la obesidad

The increase of the obesity pandemic worldwide over the last several decades has generated a constant need for the scientific world to develop new possibilities to combat obesity. Since the discovery that brown adipose tissue (BAT) exists in adult humans, and BAT activation contributes to a negative energy balance, much more attention has been focused on the understanding of the molecular switches and their different regulatory mechanisms turning on energy expenditure. Recent insights have revealed that a range of stimuli including cold exposure, physical activity and diet, and critical transcription molecules such as PPARγ, PRDM16, PGC-1α and UCP1, aiming at the induction of BAT activation, could cause the browning of white adipose tissue, thereby dissipating energy and increasing heat production. An increasing number of studies that point to the white adipose tissue (WAT) browning strategies aiming at diet-induced and/or genetically determined obesity have been tested in mouse models as well as in human studies. The aim of this review is to summarize the transcriptional regulators as well as the various mediators that have been regarded as potential therapeutic targets in the process of WAT browning.