Predicting Renewable Energy Investment Using Machine Learning

In order to combat climate change, many countries have promised to bolster Renewable Energy (RE) production following the Paris Agreement with some countries even setting a goal of 100% by 2025. The reasons are twofold: capitalizing on carbon emissions whilst concomitantly benefiting from reduced fossil fuel dependence and the fluctuations associated with imported fuel prices. However, numerous countries have not yet made preparations to increase RE production and integration. In many instances, this reluctance seems to be predominant in energy-rich countries, which typically provide heavy subsidies on electricity prices. With such subsidies, there is no incentive to invest in RE since the time taken to recoup such investments would be significant. We develop a model using a Neural Network (NN) regression algorithm to quantitatively illustrate this conjecture and also use it to predict the reduction in electricity price subsidies required to achieve a specified RE production target. The model was trained using 10 leading metrics from 53 countries. It is envisaged that policymakers and researchers can use this model to plan future RE targets to satisfy the Nationally Determined Contributions (NDC) and determine the required electricity subsidy reductions. The model can easily be modified to predict what changes in other country factors can be made to stimulate growth in RE production. We illustrate this approach with a sample use case

Framework for Building Low-Cost OBD-II Data-Logging Systems for Battery Electric Vehicles

With the electrification of transport (BEVs) and the growing benefits of smart vehicles, there is a need for a simple solution to perform real-time monitoring of the BEV and its battery for diagnostics and coordinated charging. The On-Board Diagnostics (OBD) system, originally designed for internal combustion engine cars (ICE), can be used to extract the necessary BEV data. This paper presents a developed framework for a low-cost solution to online monitoring of BEVs. A Raspberry Pi Zero W, along with other auxiliary components, was installed in two Hyundai Ioniq Battery Electric cars to communicate with the vehicles via the OBD-II port. A python script was developed to periodically request the vehicle data by sending various Parameter IDs to the vehicles and storing the raw response data. A web server was created to process the hexadecimal encoded data and visualize the data on a dashboard. The key parameters, such as the battery state of health (SOH), state of charge (SOC), battery temperature, cell voltages and cumulative energy consumption, were successfully captured and recorded, which can now facilitate trending for battery diagnostics and future integration with smart chargers for coordinated charging

Evaluation of GABAergic neuroactive steroid 3 alpha -hydroxy-5 alpha -pregnane-20-one as a neurobiological substrate for the anti-anxiety effect of ethanol in rats

Rationale: Acute systemic ethanol administration is known to elevate plasma and cerebral levels of neuroactive steroid 3 alpha -hydroxy-5 alpha -pregnane-20-one (3 alpha , 5 alpha -THP; allopregnanolone) to a concentration sufficient to potentiate GABA sub(A) receptors. We have earlier demonstrated that 3 alpha , 5 alpha -THP mediates the antidepressant-like effect of ethanol in Porsolt forced swim test. Objective: The aim of the present study is to explain the relationship between endogenous GABAergic neurosteroids and anxiolytic effect of ethanol in Sprague-Dawley rats. Method: The mediation of 3 alpha , 5 alpha -THP in the anti-anxiety effect of ethanol was assessed by pharmacological interactions of ethanol with various endogenous neurosteroidal modulators and using simulated physiological conditions of altered neurosteroid content in elevated plus maze (EPM) test. Results: Pretreatment of 3 alpha , 5 alpha -THP (0.5-2.5 mu g/rat, i.c.v.) or neurosteroidogenic agents such as 3 alpha , 5 alpha -THP precursor progesterone (5 or 10 mg/kg, i.p.), 11- beta hydroxylase inhibitor metyrapone (50 or 100 mg/kg, i.p.) or the GABA sub(A) receptor agonist muscimol (25 ng/rat, i.c.v.) significantly potentiated the anti-anxiety effect of ethanol (1 g/kg, i.p.). On the other hand, the GABAergic antagonistic neurosteroid dehydroepiandrosterone sulphate (DHEAS) (1 mg/kg, i.p.), the GABA sub(A) receptor blocker bicuculline (1 mg/kg, i.p.), the 5 alpha -reductase inhibitor finasteride (50 x 2 mg/kg, s.c.) or the mitochondrial diazepam binding inhibitory receptor antagonist PK11195 (1 mg/kg, i.p.) reduced ethanol-induced preference of time spent and number of entries into open arms. Anti-anxiety effect of ethanol was abolished in adrenalectomized (ADX) rats as compared to sham-operated control. This ADX-induced blockade was restored by prior systemic injection of progesterone, signifying the contribution of peripheral steroidogenesis in ethanol anxiolysis. Socially isolated animals known to exhibit decreased brain 3 alpha , 5 alpha -THP and GABA sub(A) receptor functions displayed reduced sensitivity to the effects of ethanol and 3 alpha , 5 alpha -THP in EPM test. Conclusions: Our results demonstrated the contributory role of neuroactive steroid 3 alpha , 5 alpha -THP in the anti-anxiety effect of ethanol. It is speculated that ethanol-induced modulation of endogenous GABAergic neurosteroids, especially 3 alpha , 5 alpha -THP, might be crucial pertinent to the etiology of 'trait' anxiety (tension reduction) and ethanol abuse

Coco Monoethanolamide Surfactant as a Sustainable Corrosion Inhibitor for Mild Steel: Theoretical and Experimental Investigations

Recent studies indicate that surfactants are a relatively new and effective class of corrosion inhibitors that almost entirely meet the criteria for a chemical to be used as an aqueous phase corrosion inhibitor. They possess the ideal hydrophilicity to hydrophobicity ratio, which is crucial for effective interfacial interactions. In this study, a coconut-based non-ionic surfactant, namely, coco monoethanolamide (CMEA), was investigated for corrosion inhibition behaviour against mild steel (MS) in 1 M HCl employing the experimental and computational techniques. The surface morphology was studied employing the scanning electron microscope (SEM), atomic force microscope (AFM), and contact measurements. The critical micelle concentration (CMC) was evaluated to be 0.556 mM and the surface tension corresponding to the CMC was 65.28 mN/m. CMEA manifests the best inhibition efficiency (η%) of 99.01% at 0.6163 mM (at 60 °C). CMEA performs as a mixed-type inhibitor and its adsorption at the MS/1 M HCl interface followed the Langmuir isotherm. The theoretical findings from density functional theory (DFT), Monte Carlo (MC), and molecular dynamics (MD) simulations accorded with the experimental findings. The MC simulation’s assessment of CMEA’s high adsorption energy (−185 Kcal/mol) proved that the CMEA efficiently and spontaneously adsorbs at the interface

Chronic progesterone treatment augments while dehydroepiandrosterone sulphate prevents tolerance to ethanol anxiolysis and withdrawal anxiety in rats

We have recently shown that the neurosteroid allopregnanolone modulates anxiolytic effect of ethanol. In the present report, we attempted to examine whether neurosteroids progesterone and dehydroepiandrosterone sulphate (DHEAS), which modulate γ-aminobutyric acid (GABA A) receptor function, affects development of tolerance to ethanol anxiolysis and withdrawal anxiety. Rats on ethanol (6% v/v in nutritionally balanced liquid diet) for prolong period (10 days) were injected twice daily either with vehicle, progesterone (a precursor of allopregnanolone, positive GABA A receptor modulator), finasteride (5α-reductase inhibitor) or DHEAS (negative GABA A receptor modulator). During this period, rats were acutely challenged periodically with ethanol (2 g/kg, i.p., 8% w/v) and subjected to the elevated plus maze test. For withdrawal studies, similar treatment protocols (except ethanol challenge) were employed and on day 11, rats were subjected to the elevated plus maze test at different time intervals post-ethanol withdrawal. While progesterone significantly advanced the development of tolerance to ethanol anxiolysis and enhanced withdrawal anxiety, DHEAS and finasteride prevented such behavioral alterations. These data highlight the important role played by GABAergic neurosteroids progesterone and DHEAS in the development of tolerance to ethanol anxiolysis and withdrawal anxiety in rats. Moreover, it points to the potential usefulness of specific neurosteroids as targets in the treatment of alcoholism

Coco Monoethanolamide Surfactant as a Sustainable Corrosion Inhibitor for Mild Steel: Theoretical and Experimental Investigations

Recent studies indicate that surfactants are a relatively new and effective class of corrosion inhibitors that almost entirely meet the criteria for a chemical to be used as an aqueous phase corrosion inhibitor. They possess the ideal hydrophilicity to hydrophobicity ratio, which is crucial for effective interfacial interactions. In this study, a coconut-based non-ionic surfactant, namely, coco monoethanolamide (CMEA), was investigated for corrosion inhibition behaviour against mild steel (MS) in 1 M HCl employing the experimental and computational techniques. The surface morphology was studied employing the scanning electron microscope (SEM), atomic force microscope (AFM), and contact measurements. The critical micelle concentration (CMC) was evaluated to be 0.556 mM and the surface tension corresponding to the CMC was 65.28 mN/m. CMEA manifests the best inhibition efficiency (η%) of 99.01% at 0.6163 mM (at 60 °C). CMEA performs as a mixed-type inhibitor and its adsorption at the MS/1 M HCl interface followed the Langmuir isotherm. The theoretical findings from density functional theory (DFT), Monte Carlo (MC), and molecular dynamics (MD) simulations accorded with the experimental findings. The MC simulation’s assessment of CMEA’s high adsorption energy (−185 Kcal/mol) proved that the CMEA efficiently and spontaneously adsorbs at the interface

Neurosteroid allopregnanolone mediates anxiolytic effect of etifoxine in rats

Etifoxine (6-chloro-2-ethylamino-4-methyl-4-phenyl-4 H-3,1-benzoxazine hydrochloride), a nonbenzodiazepine anxiolytic drug, potentiates GABA A receptor function perhaps through stimulation of neurosteroid biosynthesis. However, the exact mechanism of etifoxine action is not fully understood. In this study, we have assessed the possible role of GABAergic neurosteroid like allopregnanolone (ALLO) in the anxiolytic-like effect of etifoxine in rats using elevated plus maze test. Selective GABA A receptor agonist, muscimol, ALLO or neurosteroidogenic agents like progesterone, metyrapone or mitochondrial diazepam binding inhibitor receptor (MDR) agonist, FGIN 1–27 significantly heightened the etifoxine-induced anxiolysis. On the other hand, GABA A receptor antagonist, bicuculline or neurosteroid biosynthesis inhibitors like finasteride, indomethacin, trilostane or PBR antagonist, PK11195 significantly blocked the effect of etifoxine. Bilateral adrenalectomy did not influence anti-anxiety effect of etifoxine thereby ruling out contribution of adrenal steroids. Thus, our results provide behavioral evidence for the role of neurosteroids like ALLO in the anti-anxiety effect of etifoxine