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Abstract While Germany and Japan are going through major energy reforms, natural gas consumption is taking a growing share in their energy supply. This paper adopts a Machine Learning approach to assess the causal link between natural gas consumption and economic growth for both economies. A Causal Direction from Dependency (D2C) algorithm with the interconnection of the sub-class is employed using yearly data from 1970 to 2018. The interconnections of the sub-classes are found for both economies, indicating evidence of causalities operating in both directions. In addition, the propagation over the seven eras is linear and homogeneously continue for Japan, while this effect meets a stabilization phase in the fifth era for Germany. The empirical findings claim strong support for the existence of a bidirectional causality between these variables in Germany and Japan, which is in line with the “feedback hypothesis”. Although the strength of this bidirectional relationship is clear for both economies, its time-propagation is expected to be longer for Japan. Accordingly, this study claims that the gas supply should be further strengthened to progressively replace the most polluting fuels (oil and coal) and ensure a feasible transition towards a renewable path.

We present recent results obtained with a novel spectrometer developed within the EU projectVOLPE (VOLume PhotoEmission from solids with synchrotron radiation), now operational at ESRF (Beamline ID16), where we were able to achieve high energy resolution as well as good statistics photoemission spectra up to 6–8 keV of photoelectron kinetic energy. The spectrometer is a hemispherical deflector analyzer with electrostatic input lens and 2D position sensitive detector. Ag 3d, Au 4f and valence band spectra have been measured from polycrystalline Ag and Au, displaying an overall energy resolution (photons + analyzer) of about 71 meV at 6 keV, as measured at 18K on the Fermi edge. The corresponding resolving power of 8×104 is one of the highest values achieved in photoemission measurements from solid samples.

Abstract A review of the application of porous silicon (PS) in multicrystalline silicon solar cell processes is given. The different PS formation processes, structural and optical properties of PS are discussed from the viewpoint of photovoltaics. Special attention is given to the use of PS as an antireflection coating in simplified processing schemes and for simple selective emitter processes as well as to its light trapping and surface passivating capabilities. The optimization of a PS selective emitter formation results in a 14.1% efficiency mc-Si cell processed without texturization, surface passivation or additional ARC deposition. The implementation of a PS selective emitter into an industrially compatible screenprinted solar cell process is made by both the chemical and electrochemical method of PS formation. Different kinds of multicrystalline silicon materials and solar cell processes are used. An efficiency of 13.2% is achieved on a 25 cm 2 mc-Si solar cell using the electrochemical technique while the efficiencies in between 12% and 13% are reached for very large (100–164 cm 2 ) commercial mc-Si cells with a PS emitter formed by chemical method.

SummaryThe RAG3 gene has been cloned from a Kluyveromyces lactis genomic library by complementation of the rag3 mutation, which shows impaired fermentative growth on glucose in the presence of respiratory inhibitors. From the nucleotide sequence of the cloned DNA, which contained an open reading frame of 765 codons, the predicted protein is 49.5% identical to the Pdc2 protein of Saccharomyces cerevisiae, a regulator of pyruvate decarboxylase in this yeast. Measurement of the pyruvate decarboxylase activity in the original rag3–1 mutant and in the null mutant confirmed that the RAG3 gene is involved in pyruvate decarboxylase synthesis in K. lactis. The effect is exerted at the mRNA level of the pyruvate decarboxylase structural gene KIPDCA. Despite analogies between the RAG3 gene of K. lactis and the PDC2 gene of S. cerevisiae, these genes were unable to reciprocally complement.

The integration of photovoltaic (PV) systems in buildings shows several advantages compared to conventional PV power plants. The main objectives of the present study are the quantitative evaluation of the benefits of building-integrated PV systems over their entire life-cycle and the identification of best solutions to maximize their energy efficiency and CO2 mitigation potential. In order to achieve these objectives, a simplified life-cycle analysis (LCA) has been carried out. Firstly, a number of existing applications have been studied. Secondly, a parametric analysis of possible improvements in the balance-of-system (BOS) has been developed. Finally, the two steps have been combined with the analysis of crystalline silicon technologies. Results are reported in terms of several indicators: energy pay-back time, CO2 yield and specific CO2 emissions. The indicators show that the integration of PV systems in buildings clearly increases the environmental benefits of present PV technology. These benefits will further increase with future PV technologies. Future optimized PV roof-integrated systems are expected to have an energy pay-back time of around 1·5 years (1 year with heat recovery) and to save during their lifetime more than 20 times the amount of CO2 emitted during their manufacturing (34 times with heat recovery). © 1998 John Wiley & Sons, Ltd.

This paper aims to investigate the causal links among export diversification, per capita income, and energy demand for 20 Asia-Pacific Economic Cooperation (APEC) countries. Human capital, industry share, and Foreign Direct Investments (FDI) are included within a multivariate framework. Using data covering the 1995���2018 period, an innovative sequential Artificial Neural Networks experiment is developed. Empirical results highlight that the export diversification index negatively affects the neural target corresponding to energy demand. Conversely, per capita GDP displays a significant influence on the acceleration of the same energy target. Hence, findings suggest that export diversification plays a mitigating role in the demand for energy, which is congruent with the literature. Moreover, economic growth is found to be substantially driven by export diversification, while no evidence of a causal effect is found among export diversification, human capital, and FDI. Such inferences are finally corroborated by a Decision Tree model, conducted as a final robustness check. In line with the Sustainable Development Goals (SDGs), adequate measures are suggested to improve energy savings along the supply chain, without hindering the economic performance of the Asian region. https://www.sciencedirect.com/science/article/pii/S037877882101104X

This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivari...