Data Mining In Oil Price Time Series Analysis

This paper sums up the applications of statistic models such as ARCH-family models, cointegration theory and Granger causality etc in oil price time series analysis and introduces the method of data mining combined with statistic knowledge to analysis oil price time series. In addition, the paper also explains advantages, functions, relevant technologies of this method and its potential applications in hedging the oil shock risk

Temporal change in India’s imbalance of carbon emissions embodied in international trade

In India, rapid industrialization and reorganization of the global supply chain are driving economic growth, accompanied by increasing exports and carbon emissions. India is poised to succeed China as the next world manufactory, which will lead to huge emissions in the country. To formulate appropriate emission mitigation measures, it is necessary to further understand the temporal change in India’s emissions at the sectoral level from both the production and consumption perspectives. However, existing studies that have estimated emissions in India have paid less attention to the link among original emitters, final producers and final consumers and to its temporal change. Based on an emission inventory compiled in this study, we trace emission flows from original emitters to final producers and then to final consumers through the international supply chain by using an environmentally extended multi-regional input-output model. This study finds that both production-based and consumption-based emissions in India increased constantly from 2000 to 2014, and production-based emissions had higher growth rates due to the increased coal share. The major receivers of India’s exported emissions were developed countries (e.g., the European Union and the United States), while the main sources of India’s imported emissions were developing countries (e.g., China and Russia). From 2011 to 2014, India’s net exported emissions increased by 29.2% because of the decrease of imported emissions. Moreover, intermediate products (63% and 73.7%) were the major contributors to exported and imported emissions, most of which were embodied in manufacturing products (48.8% and 65.7%, respectively). Therefore, international cooperation to optimize the energy and trade structure and to improve energy efficiency can be effective in mitigating carbon emissions in India

Study on the mechanism of gas migration and breakthrough in saturated bentonite considering the interface effect

IntroductionGas migration in low-permeability buffer materials is a crucial aspect of nuclear waste disposal. This study focuses on Gaomiaozi bentonite to investigate its behavior under various conditions.MethodsWe developed a coupled hydro-mechanical model that incorporates damage mechanisms in bentonite under flexible boundary conditions. Utilizing the elastic theory of porous media, gas pressure was integrated into the soil's constitutive equation. The model accounted for damage effects on the elastic modulus and permeability, with damage variables defined by the Galileo and Coulomb-Mohr criteria. We conducted numerical simulations of the seepage and stress fields using COMSOL and MATLAB. Gas breakthrough tests were also performed on bentonite samples under controlled conditions.ResultsThe permeability obtained from gas breakthrough tests and numerical simulations was within a 10% error margin. The experimentally measured gas breakthrough pressure aligned closely with the predicted values, validating the model's applicability.DiscussionAnalysis revealed that increased dry density under flexible boundaries reduced the damage area and influenced gas breakthrough pressure. Specifically, at dry densities of 1.4 g/cm3, 1.6 g/cm3, and 1.7 g/cm3, the corresponding gas breakthrough pressures were 5.0 MPa, 6.0 MPa, and 6.5 MPa, respectively. At a dry density of 1.8 g/cm3 and an injection pressure of 10.0 MPa, no continuous seepage channels formed, indicating no gas breakthrough. This phenomenon is attributed to the greater tensile and compressive strengths associated with higher dry densities, which render the material less susceptible to damage from external forces

FDTD Modelling of Silver Nanoparticles Embedded in Phase Separation Interface of H-PDLC

We report localized surface plasmon resonance (LSPR) of silver nanoparticles (NPs) embedded in interface of phase separation of holographic polymer-dispersed liquid crystal (H-PDLC) gratings using Finite-Difference Time Domain method. We show that silver NPs exhibit double resonance peak at the interface, and these peaks are influenced by the angle of incident light. We observe a blue shift of the wavelength of resonance peak as the incident angle increases. However, the location of silver NPs at the interface has nearly no effect on the wavelength of resonance peak. Also we show near-field and far-field properties surrounding silver NPs and find that field distribution can be controlled through rotation of incident angle. Therefore, LSPR properties of silver NPs within H-PDLC gratings can be excited by appropriate wavelength and angle of the incident light

A Symmetric Dynamic Learning Framework for Diffeomorphic Medical Image Registration

Diffeomorphic image registration is crucial for various medical imaging applications because it can preserve the topology of the transformation. This study introduces DCCNN-LSTM-Reg, a learning framework that evolves dynamically and learns a symmetrical registration path by satisfying a specified control increment system. This framework aims to obtain symmetric diffeomorphic deformations between moving and fixed images. To achieve this, we combine deep learning networks with diffeomorphic mathematical mechanisms to create a continuous and dynamic registration architecture, which consists of multiple Symmetric Registration (SR) modules cascaded on five different scales. Specifically, our method first uses two U-nets with shared parameters to extract multiscale feature pyramids from the images. We then develop an SR-module comprising a sequential CNN-LSTM architecture to progressively correct the forward and reverse multiscale deformation fields using control increment learning and the homotopy continuation technique. Through extensive experiments on three 3D registration tasks, we demonstrate that our method outperforms existing approaches in both quantitative and qualitative evaluations

Optimization of Inorganic Ceramic Membrane Filtration Process for Tea Enzymes

In order to enhance the clarity of tea enzymes while maximizing the preservation of their functional components during the clarification process, this experiment utilized tea enzymes derived from summer and autumn tea fermentation as the primary material. Through both single-factor and response surface experiments, the effects of inorganic ceramic membrane pore size, transmembrane power, transmembrane pressure, and transmembrane temperature on the content of functional components, membrane flux, transmittance, and soluble solids content of the enzyme solution after membrane filtration were examined. The objective was to determine the optimal conditions for ceramic membrane filtration of tea enzymes. The results showed that, the ideal conditions for ceramic membrane filtration of tea enzymes were as follows: Membrane pore size of 400 nm, transmembrane power of 47 Hz, transmembrane pressure of 0.28±0.02 MPa, and transmembrane temperature of 15±2 ℃. Under these conditions, the retention rates of tea polyphenols, theanine, zinc, selenium, and soluble solids content in tea enzymes were 95.28%, 82.91%, 90.48%, 91.67%, and 84.46% respectively. The transmittance reached 85.10%±0.12% with 2.5-fold improvement compared to before membrane filtration. Additionally, the membrane flux achieved 123.25±2.68 m3/(m2·h). These optimal conditions not only maximized the retention of functional components in tea enzymes, but also ensured their transparency and uniformity. Therefore, employing these conditions for the filtration and clarification of tea enzymes was a viable approach

Experiments and modeling for flexible biogas production by co-digestion of food waste and sewage sludge

This paper explores the feasibility of flexible biogas production by co-digestion of food waste and sewage sludge based on experiments and mathematical modeling. First, laboratory-scale experiments were carried out in variable operating conditions in terms of organic loading rate and feeding frequency to the digester. It is demonstrated that biogas production can achieve rapid responses to arbitrary feedings through co-digestion, and the stability of the anaerobic digestion process is not affected by the overloading of substrates. Compared with the conventional continuous mode, the required biogas storage capacity in flexible feeding mode can be significantly reduced. The optimum employed feeding organic loading rate (OLR) is identified, and how to adjust the feeding scheme for flexible biogas production is also discussed. Finally, a simplified prediction model for flexible biogas production is proposed and verified by experimental data, which could be conveniently used for demand-oriented control. It is expected that this research could give some theoretical basis for the enhancement of biogas utilization efficiency, thus expanding the applications of bio-energy.Sichuan Provincial Key Technology Suppor

Supply chains create global benefits from improved vaccine accessibility

Ensuring a more equitable distribution of vaccines worldwide is an effective strategy to control global pandemics and support economic recovery. We analyze the socioeconomic effects - defined as health gains, lockdown-easing effect, and supply-chain rebuilding benefit - of a set of idealized COVID-19 vaccine distribution scenarios. We find that an equitable vaccine distribution across the world would increase global economic benefits by 11.7% ($950 billion per year), compared to a scenario focusing on vaccinating the entire population within vaccine-producing countries first and then distributing vaccines to non-vaccine-producing countries. With limited doses among low-income countries, prioritizing the elderly who are at high risk of dying, together with the key front-line workforce who are at high risk of exposure is projected to be economically beneficial (e.g., 0.9%~3.4% annual GDP in India). Our results reveal how equitable distributions would cascade more protection of vaccines to people and ways to improve vaccine equity and accessibility globally through international collaboration

Leveraging opportunity of low carbon transition by super-emitter cities in China

Chinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets

Leveraging opportunity of low carbon transition by super-emitter cities in China

Funding Information: The work was supported by the National Natural Science Foundation of China (7224100119), the National Key Research and Development Program of China (2022YFE0208700 and 2022YFE0208500), and the Norwegian Research Council (287690/F20). We appreciate the suggestions from Prof. Edgar Hertwich of Norweign University of Science andTechnology. Publisher Copyright: © 2023 Science China PressChinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets.Peer reviewe