ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
Synthesis of silver and copper oxide nanoparticles using Myristica fragrans fruit extract: Antimicrobial and catalytic applications

The pericarp of Myristica fragrans fruit extract was utilized for a low cost, eco-friendly synthesis of silver (AgNPs) and copper oxide (CuONPs) nanoparticles. The aqueous fruit extract of the plant was used as reducing and stabilizing agents for this preparation. Characterization of the biosynthesized nanoparticles was carried out using UV -Vis spectroscopy, FTIR spectroscopy and X -Ray Diffraction studies. Morphology and size of the particles was observed using Field -Emission Scanning Electron Microscopy (FESEM) and High Resolution Transmission Elec- tron Microscopy (HRTEM). The copper and silver nanoparticles show Surface Plasmon Resonance (SPR) band at 360 and 478 nm respectively in the UV -Vis spectrum. It was observed that size of the synthesized copper oxide and silver nanoparticles are in the range 10 -50 nm. The presence of copper and silver elements was confirmed from their respective EDS spectrum. Involvement of phytochemicals in the stabilization and reduction of the nanoparticles was confirmed by FTIR spectroscopy. CuONPs exhibited catalytic activity in 1,3 -dipolar cyclo- addition reaction between azides and terminal alkynes to form 1,2,3-triazoles. Silver nanoparticle possesses good antibacterial activity against multidrug human pathogens Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus and Bacillus subtilis . The present study focuses on the utilization of the less economic part of Myristica fragrans fruit ?s pericarp for the preparation of copper oxide and silver nanoparticles which have good catalytic and antibacterial activities.
Implementation of property-level flood risk adaptation (PLFRA) measures: Choices and decisions

Hydrometeorological events are highly costly and have strong impacts on the human-environment system. Effective response requires effective risk management concepts and strategies at individual and watershed level to increase community resilience. Focusing on flood risk and the information associated with it, individual risk behavior in the shape of implementing property-level flood risk adaptation (PLFRA) measures is often overlooked. For this research, a comprehensive overview of possible PLFRA measures for homeowners in flood risk areas was made, as well as the possible costs and technical feasibility for new and existing buildings. To complement this, insights into risk mitigation behavior are essential due to the ongoing shift to risk-based and individualized flood risk management, which require a contribution from flood-prone households to risk reduction. Results show that PLFRA measures differentiate in their effectiveness, cost-efficiency and technical feasibility, and full protection can never be guaranteed. Considering risk mitigation behavior, literature generally distinguishes between situational factors (such as communication and economic subsidies) and personal factors (such as personal and psychological components influencing individual behavior).
Revisiting the Environmental Kuznets Curve hypothesis in OECD countries: the role of renewable, non-renewable energy, and oil prices

Environment-economic growth nexus is one of the main concerns of the researchers in the modern era. Although there are several studies in this field, discussions are far from being reached a consensus. The main purpose of this study is to investigate the role of economic growth, renewable and non-renewable energy consumption, oil prices, and trade openness on CO2 emissions in 25 Organization for Economic Co-operation and Development (OECD) countries over the period 1990-2014. We provide a comparative panel data evidence using both the first- and second-generation estimation methods. The Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimations indicate that the Environmental Kuznets Curve (EKC) hypothesis is valid in OECD countries. However, the Augmented Mean Group (AMG) estimator revealed that the EKC hypothesis is invalid. The AMG estimator is a second-generation estimator and provides robust results under cross-sectional dependence compared to the first-generation methods; therefore, the EKC hypothesis is invalid. Our additional findings show that rising renewable energy consumption and oil prices mitigate CO2 emissions while non-renewable energy consumption increases it according to all estimators. No significant relationship is found between trade openness and CO2 emissions.
Ferrets are valuable models for SARS-CoV-2 research

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in an ongoing pandemic with millions of deaths worldwide. Infection of humans can be asymptomatic or result in fever, fatigue, dry cough, dyspnea, and acute respiratory distress syndrome with multiorgan failure in severe cases. The pathogenesis of COVID-19 is not fully understood, and various models employing different species are currently applied. Ferrets can be infected with SARS-CoV-2 and efficiently transmit the virus to contact animals. In contrast to hamsters, ferrets usually show mild disease and viral replication restricted to the upper airways. Most reports have used the intranasal inoculation route, while the intratracheal infection model is not well characterized. Herein, we present clinical, virological, and pathological data from young ferrets intratracheally inoculated with SARS-CoV-2. Infected animals showed no significant clinical signs, and had transient infection with peak viral RNA loads at 4 days postinfection, mild to moderate rhinitis, and pulmonary endothelialitis/vasculitis. Viral antigen was exclusively found in the respiratory epithelium of the nasal cavity, indicating a particular tropism for cells in this location. Viral antigen was associated with epithelial damage and influx of inflammatory cells, including activated neutrophils releasing neutrophil extracellular traps. Scanning electron microscopy of the nasal respiratory mucosa revealed loss of cilia, shedding, and rupture of epithelial cells. The currently established ferret SARS-CoV-2 infection models are comparatively discussed with SARS-CoV-2 pathogenesis in mink, and the advantages and disadvantages of both species as research models for zoonotic betacoronaviruses are highlighted.
Carrier-Free Cross-linked Laccase Crystals for Biocatalytic Degradation of Textile Industrial Effluents

Herein, laccase from Trametes versicolor was used to fabricate carrier-free cross-linked laccase crystals (CLLCs) and deployed as a robust catalyst for waste effluent treatment. The surface morphology and involvement of functional group attributes of CLLCs were scrutinized by scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). As fabricated CLLCs were subjected to kinetic characterization by assessing the effects of pH environment, thermal profile, and substrate (determination of Km and Vmax) on the activity. A fully characterized CLLCs fraction was used to treat synthetic dyes containing waste effluents taken from various industries, i.e., Chenab Textile Industry, M-tax, Sitara, and National Silk & Rayon Mills. Degradation profile revealed 36.8%, 27.6%, 39.9%, and 26.4% degradation of Chenab Textile Industry, M-tax, Sitara, and National Silk & Rayon Mills, respectively, by the free form of laccase, whereas the biocatalytic activity of CCLCs led to 78.6%, 75.6%, 85.5%, and 63.3% degradation of those effluents. The decrease in peak and mass region alongside the presence of new peaks in GC-MS affirms the effective decolorization of contaminated waste effluents. CLLCs retained over 70% and 50% of their degradation activity after 3 and 5 cycles, respectively. In conclusion, CLLCs might represent a robust bioprocess to improve the usability of laccase for various synthetic dyes containing waste effluents to diminish environmental pollution from the dye-based industries.
Multi-objective performance of smart hybrid energy system with Multi-optimal participation of customers in day-ahead energy market

Optimal energy consumption is one of the sustainable development issues in many countries to improve the economic and environmental indices in the energy sector. This paper presents a tri-objective optimal performance of a smart hybrid energy system (SHES) in the presence of customer's participation to optimally reshape the demand profile in the day-ahead energy market. Minimizing the operation costs and the emission pollution as well as maximizing the customer satisfaction level are considered as the objectives of this problem. The three types of demand response (DR) programs consisting of 1) demand curtailment, 2) demand shifting and 3) onsite generation program are considered for optimal scheduling of the electrical and the thermal energy consumption by the customers. The demand curtailment program is considered as the reserve for SHES and the Plug Electric Vehicles (PEVs) are taken into account as the onsite generation program. The uncertainties of energy and reserve prices are modeled using lognormal distribution function. The shuffled frog leaping algorithm (SFLA) is employed to solve the problem from which the non-dominated solutions are generated. Then, the best solution of the non-dominated solutions is selected by the hybrid approach of fuzzy method and the weight sum. To validate the mentioned approach, five case studies are investigated and the results demonstrate optimal scheduling of SHES with acceptable levels of operation costs, emission pollution and customer satisfaction. (C) 2020 Elsevier B.V. All rights reserved.
Performance prediction and techno-economic analysis of solar dish/stirling system for electricity generation

In this study, a new commercial Solar Dish/Stirling (SDS) system with a rated power of 25 kW is experimentally established and thermodynamically modeled. A mathematical model implemented in MATLAB software is developed to simulate the proposed SDS system operation in order to analyze its performance, under conditions of Tianjin, China. An analysis of the daily, monthly, and annual performances of the investigated SDS system is performed. In addition, a techno-economic viability for assessing the electricity cost and life cycle cost of the SDS system is also performed. The results indicated that the proposed SDS system produces 28.748 MWh annually, with a yearly net overall efficiency of 19.55%, and achieves maximum energy of 3.8 MWh with a monthly average efficiency of 22.75% in June. From the energy cost analysis, the levelized energy cost of the SDS system is estimated to be 1.719 CNY/kWh similar to (0.2565 $/kWh). In conclusion, the present study identifies the actual commercial and economic situation of the Dish Stirling technology in China, taking into account the China's feed-in tariff of CSP systems (1.2 CNY/kWh), and it also provides a new theoretical guidance for predicting the annual performance and evaluating the economic situation of the SDS systems.
Sustainability Driven by Agriculture through Digital Transformation

Economic, environmental and social sustainability is increasingly gaining the attention of academia and commitment in the policies of national economies. Global warming and climate change, weather disasters and disruptions are just some of the challenges that can drastically disrupt stable business models, and thus jeopardize sustainability. Agriculture, as an activity at the center of the value chain, is facing these problems, and, at the same time, contributes to feeding the growing world population and is responsible for conserving resources and ensuring sustainability. Process automation, data analysis and processing, control and management of agricultural operations have transformed the agricultural business and contributed to sustainability, survival and development within supply chains. This article analyzes the literature in the field of sustainability and agriculture led by digital technologies of Industry 4.0. The analysis of the research field showed the high importance of the topic in academic and national circles, given the number of published articles. Secondly, the concepts of sustainable agriculture and sustainability driven agriculture in the context of digital transformation were analyzed and it was shown that transformed agriculture can successfully cope with today's challenges. Finally, guidelines for sustainable development driven by agriculture through the determinants of digital transformation are defined.
The role of environmental entrepreneurship for sustainable development: Evidence from 35 countries in Sub-Saharan Africa

This research seeks to confirm the achievement of sustainable development in Sub-Sahara Africa. In view of this, a panel of 35 Sub-Saharan Africa countries divided into two sub-panels based on their income groupings, namely low-income, and middle-income countries, from 2000 to 2014 with a cross-sectional dependence among the series was used as a prerequisite for the analysis. We used the Pooled Mean Group estimators of the Autoregressive Distributed Lag model to ascertain the long-run mechanism between variables and analyse the Environmental Kuznets Curve hypothesis. The key results are: (1) income per capita significantly increases environmental pollution where environmental entrepreneurship decreases pollution of the environment across all panels of SSA countries; (2) in the low-income SSA economies, trade openness enhance environmental quality but increase environmental pollution in both the aggregated panel and middle-income SSA nations; (3) with the exception of low-income countries, human development palpably decreases environmental pollution in middle-income countries and in the aggregated panel a reduction is observed; (4) from financial development perspective, it produces positive and significant effect in the aggregated panel of SSA countries and middle-income SSA nations; (5) the environmental Kuznets curve conjuncture is supported for the selected panels in SSA region. Consequently, governments and policymakers should reinforce policies for the reduction of environmental pollution, more importantly, green financing policies, encourage aspiring environmental entrepreneurs to set environmentally-driven businesses, promote the use of environmental products to mitigate environmental problems and achieve sustainable development. (C) 2020 Elsevier B.V. All rights reserved.
Cost-benefit analysis of waste photovoltaic module recycling in China

With the rapid development of renewable energy, the impact on environment and resource caused by waste photovoltaic modules has been realized gradually. To solve the problem, recycling becomes an effectual way. Therefore, the aim of this paper was to assess the economic feasibility of the photovoltaic modules recycling project in China by using cost-benefit analysis. It was found that, under the estimated treatment quantity will generate in China in 2020-2034, the recovery cost per kilowatt (kW) of photovoltaic modules will be 25.11 USD, the unit benefit is 25.68 USD/kW, and the unit net benefit is 0.57 USD/kW. The net present value (NPV) and benefit-cost ratio (BCR) are 21.14 million USD and 1.023. The sensitivity analysis indicated that the sale benefits of recycled materials and tax were the most sensitive factors affecting the project's economy. Finally, we proposed ways to improve the economy for the government and related enterprises. (C) 2020 Elsevier Ltd. All rights reserved.
Cytochrome c Expression by Andaliman ( Zanthoxylum acanthopodium) on Cervical Cancer Histology

&lt;b&gt;Background and Objective:&lt;/b&gt; Andaliman is a wild plant in Indonesia and it has been used for centuries as traditional medicine. This study aimed to evaluate the effect of methanol extract of andaliman on apoptosis cancer cells via cytochrome c protein. &lt;b&gt;Materials and Methods:&lt;/b&gt; The rats are divided into 5 groups. K: Control, K&lt;sub&gt;+&lt;/sub&gt;: Cancer model rats, P&lt;sub&gt;1&lt;/sub&gt;: A dose of 100 mg/b.wt./day of andaliman, P&lt;sub&gt;2&lt;/sub&gt;: A dose of 200 mg/b.wt./day and P&lt;sub&gt;3&lt;/sub&gt;: A dose of 400 mg/kg/b.wt./day for 30 days. The rats were dissected, then the cervical tissue was prepared on paraffin blocks, given Immunohistochemistry staining with cytochrome c antibody. &lt;b&gt;Results:&lt;/b&gt; There was a significant difference in body and cervical weight (p<0.01). The histology also showed a significant difference between each treatment (p<0.01) in cytochrome c. The highest cytochrome c expression was at P&lt;sub&gt;2&lt;/sub&gt; and the lowest was at K&lt;sub&gt;-&lt;/sub&gt;. &lt;b&gt;Conclusion:&lt;/b&gt; Andaliman methanol extract can thus be developed into a cervical cancer drug candidate because it can reduce the positive index of cytochrome c in cervical histology.
Prenatal depression exposure alters white matter integrity and neurodevelopment in early childhood

Prenatal exposure to maternal depression increases the risk for onset of emotional and behavioral disorders in children. We investigated the effects of exposure to prenatal depression on white matter microstructural integrity at birth and at 2-3 years, and associated neurodevelopment. Diffusion-weighted images were acquired for children of the Drakenstein Child Health Study at 2-4 weeks postpartum (n=70, 47% boys) and at 2-3 years of age (n=60, 58% boys). Tract-Based Spatial Statistics was used to compare, using an ROI based approach, diffusion tensor metrics across groups defined by presence (>19 on Beck's Depression Inventory and/or >12 on the Edinburgh Postnatal Depression Scale) or absence (below depression thresholds) of depression, and associations with neurodevelopmental measures at age 2-3 years were determined. We did not detect group differences in white matter integrity at neonatal age, but at 2-3 years, children in the exposed group demonstrated higher fractional anisotropy, and lower mean and radial diffusivity in association tracts compared to controls. This was notable in the sagittal stratum (radial diffusivity: p<0.01). Altered white matter integrity metrics were also observed in projection tracts, including the corona radiata, which associated with cognitive and motor outcomes in exposed 2-3-year-olds (p<0.05). Our findings of widespread white matter alterations in 2-3-year-old children with prenatal exposure to depression are consistent with previous findings, as well as with neuroimaging findings in adults with major depression. Further, we identified novel associations of altered white matter integrity with cognitive development in depression-exposed children, suggesting that these neuroimaging findings may have early functional impact.
Multilevel monte carlo for cortical circuit models

Multilevel Monte Carlo (MLMC) methods aim to speed up computation of statistics from dynamical simulations. MLMC is easy to implement and is sometimes very effective, but its efficacy may depend on the underlying dynamics. We apply MLMC to networks of spiking neurons and assess its effectiveness on prototypical models of cortical circuitry under different conditions. We find that MLMC can be very efficient for computing reliable features, i.e., features of network dynamics that are reproducible upon repeated presentation of the same external forcing. In contrast, MLMC is less effective for complex, internally generated activity. Qualitative explanations are given using concepts from random dynamical systems theory.
Study on properties of phase change foam concrete block mixed with paraffin / fumed silica composite phase change material

On-site renewable energy generation systems are installed for buildings to compensate for their energy consumptions due to cooling and heating loads. Fluctuated energy load can significantly affect the decision on the selection of renewable energy systems. This study developed a new phase change foam concrete with low thermal conductivity and suitable phase change temperature to shave the temperature peak in summer and improve the economic feasibility of renewable energy systems. With the adsorption method, this study utilized the fumed silica to absorb paraffin for the composite phase change materials (PCM) formation. Through morphology and liquid leakage tests, this study found that the composite PCM with paraffin content of 45% (wt) had the best adsorption capacity and setting performance. According to the scanning electron microscopy (SEM), metallographic microscopy and X-ray powder diffraction (XRD) tests, the proposed composite PCM and phase change foam concrete blocks have stable morphological structures and physical properties. Also, the differential scanning calorimeter (DSC) showed the proposed composite PCM within the concrete have suitable phase change temperature (about 41 degrees C) and phase change latent heat (the endothermic process is 113.3 J/g and the exothermic process is 112 J/g to avoid building overheating in summer. Finally, the thermal conductivity and heating experiments suggested the proposed phase change foam concrete blocks have low thermal conductivity and strong heat storage capacity. (C) 2019 Elsevier Ltd. All rights reserved.
Improving pesticide fate models for a simple household food processing: considering multiple crop units

To understand the fate of pesticides in crops during household cooking processes and human health risks associated with the ingestion of pesticide-contaminated crops, we propose unit-variability-enhanced models, which are capable of evaluating the removal efficiency of pesticides in multiple crop units by soaking in water. The approach integrates the lognormal production model to reveal the modeling mechanics of internal contamination among two crop units in one soaking bowl. The simulated results for 197 pesticides indicate that pesticides with larger unit-to-unit variability factors (VF) at the residue levels and diffusivity rates in water (DW) are more likely to cause internal contamination. Although internal contamination of pesticide residues between two crop units may occur, we find that the overall removal factor ([Formula: see text]) for two crop units is independent of the ratio of initial residue levels between the two crop units. Based on this discovery, we propose the unit-variability-based (UVB) rule to generalize the [Formula: see text] for an n-crop-unit system, where n crop units soak simultaneously in one container. In addition, we demonstrate that under the same consumable and recycling resources, the soaking of two crop units together in one container can yield a maximum mass removal of pesticides if the two units are randomly sampled. Although other factors, such as temperature and the nature of solutions in the cooking process, should be considered in future studies, our models suggest that this soaking method can be conveniently realized in households to reduce negative health effects.