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Purpose: This study aims to provide data references for deposit cleaning, fuel formulation and lubricant formulation. Design/methodology/approach: The engine disassembly procedure was carried out based on the IO540 operation manual part number 60297-10-1-7 document. Except for the normal disassembly and assembly of the engine and the measurement of parts, the main test contents included break-in run operation, cylinder pressure test, oil consumption run, pretest calibration run, post-test calibration test and the most critical endurance test. The Lycoming IO-540-V4V5 engine and the customized Hartzell CK319 propeller were selected for the test run. Findings: The deposits were mainly composed of C, O, B, Al, Br and Pb, which were mainly sourced from fuel, lubricating oil and body materials. XPS analysis showed that the presence of O determined the richness of the deposit components, giving the deposit structure with organic and inorganic components. Originality/value: This work provides certain data support and reference for subsequent aircraft maintenance, fuel formula and lubricating oil formula. The long-term stability and safety of the aircraft run can be ensured through continuous research, improvement and optimizing the operating of the engine. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-0300/ [ABSTRACT FROM AUTHOR]

This study explores the factors that impact residential energy usage and spending in the United States. Using data from the 2020 Residential Energy Consumption Survey (RECS), we investigate the significance of different energy consumption determinants at various analysis levels. Our analysis covers residential energy usage, electricity, natural gas, propane, and fuel oil consumption. We also examine energy usage for space heating, cooling, and water heating. To leverage the extensive RECS data, which includes over 180 variables, we utilized machine learning (ML) techniques for feature selection and determined their Shapley contribution for different target outcomes. Our results indicate that the CatBoost algorithm outperforms other ML techniques on the 2020 Residential Energy Consumption Survey sample. Our findings demonstrate that it is not appropriate to aggregate consumption and expenditure, as each level has distinct important features. JEL Classification: D12, Q41, R21 [ABSTRACT FROM AUTHOR]

The regional variation of energy structure in China is a significant contributor to the geographic distribution of polycyclic aromatic hydrocarbons (PAHs) in soils, posing a substantial risk to food safety and human health. However, the precise mechanisms and extent to which energy consumption influences the spatial variability of PAHs remain largely unknown. To address this research gap, PAHs data in surface soils across China screened from 155 literatures between 2003 and 2022, coupled with anthropogenic indicators were used to investigate the concentrations, sources, and spatial heterogeneity of the effects of energy consumption on PAHs. Total PAH concentrations exhibited a range of four orders of magnitude from 1.05 to 6,778 μg kg−1, indicating weak to heavy contamination and exhibiting strong spatial variability influenced by human factors. Furthermore, 3–4-ring PAHs were dominant, accounting for an average of 25.07% and 38.55%, respectively, reflecting the significant role of coal in China energy consumption and the associated coal-smoke pollution as a primary factor in ecological environment destruction. The spatial distributions of mean total PAH concentrations descended in the order of Northeast China > North China > Central China > East China > Northwest China > Southwest China > South China, with different PAH composition profiles among regions affected by energy consumption. The geographical weighted regression (GWR) model was used to explore the spatial heterogeneity of energy factors affecting on PAH concentrations. Natural gas, oil, and coal were identified as energy sources with a significant positive correlation to PAH pollution. This indicated that combustion and traffic sources were the primary contributors to PAHs in surface soil in China, with coal, natural gas combustion, and oil consumption identified as the principal energy factors influencing PAH concentrations. The results of this study provide a foundation for future efforts to prevent and control soil pollution. [ABSTRACT FROM AUTHOR]

Accurate prediction of oil and natural gas consumption (ONGC) is crucial for energy security and greenhouse gas emission control. This study uses machine learning to improve forecast accuracy by transforming time series predictions into supervised learning models. A novel stacking learning method, with added cross-validation, enhances model diversity and robustness. The key findings are: (1) The stacking model outperforms base models in predicting China's ONGC. It achieves R2 scores of 94.44% for oil and 98.33% for natural gas, with corresponding RMSE scores of 0.5325 and 0.2919. (2) When comparing the scores of the models in the validation set using cross-validation, it can be observed that the stacking model exhibits the most consistent performance. (3) Through the diversification of models, the stacking approach enhances robustness and achieves better generalization on new datasets. The study provides fresh insights into model stacking for energy consumption prediction. [ABSTRACT FROM AUTHOR]

Non-renewable energy fosters economic growth, whilst simultaneously it serves as the primary source of carbon dioxide (CO2) emissions. Using data from the world's three major carbon emitters over the period 1980–2020, this paper adopts the non-linear autoregressive distributed lag (NARDL) approach to explore the dynamic nexus between energy consumption, economic growth and CO2 emissions. The results reveal that energy consumption matters for economic growth. From a short-term perspective, an increase in oil consumption positively impacts economic growth in the United States and India, whereas a negative shock solely affects China's economic growth. Regarding coal consumption, a positive shock only affects the US's economic growth, while China and India are more likely to be affected by a negative consumption shock. In the long run, the nexus between oil consumption and economic growth exhibits a similar asymmetric pattern in China and the United States. Concerning the effect of coal consumption on economic growth, only negative shocks count for China and positive shocks for the United States. The findings also identify various patterns of energy consumption on CO2 emissions. An increase in oil consumption, whether from a short- or long-run perspective, increases CO2 emissions in all three countries, while a decrease in oil consumption only mitigates CO2 emissions in China and the United States. There are more complicated patterns to the role of coal consumption in CO2 emissions. The results vary significantly from country to country; however, energy consumption has generally promoted economic growth as well as resulted in environmental issues that cannot be disregarded. [ABSTRACT FROM AUTHOR]

The lubrication system supplies lubrication and cleans the rotating parts and contacting machinery during the operation of an aero-engine. It is crucial to maintain an adequate amount of lubricant by predicting and analyzing the consumption rate to ensure endurance and maintenance programs are effective. This paper examines the combination of temporal and non-temporal data that impact the characteristic parameters of lubricant consumption rate in aero-engines. Our study focuses on the merging of LSTM (Long Short-Term Memory) + LightGBM (Light Gradient Boosting Machine) + CatBoost, and uses KPCA dimensionality reduction optimization, along with Stacking for the fusion of a multi-feature regression prediction algorithm. On the one hand, this study utilizes integrated learning to fuse feature extractions from LSTM for temporal information and non-temporal information by GDBT (Gradient Boosting Decision Tree). This approach considers the trend and distribution of feature samples to develop a more robust feature extraction method. On the other hand, the integrated learning framework incorporates multi-decision making and feature importance extraction to strengthen the mapping relationship with the predicted output of lubrication oil consumption rate, enabling regression prediction. The algorithm for regression prediction has been executed and the results indicate a final regression prediction MAPE (Mean Absolute Percentage Error) of less than 3%. MSE and RMSE reached 1.28% and 1.33%, the results are in an ideal state. The algorithms used in this paper will be applied in the future to aero-engine lubricant systems and eventually to engines in general. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality and emission reduction goals, energy consumption optimization in the oil and gas industry is crucial for reducing carbon emissions and improving energy efficiency. As a key component in drilling operations, optimizing the energy consumption of drilling pumps has significant potential for energy savings. However, due to the complex and variable geological conditions, diverse operational parameters, and inherent nonlinear relationships in the drilling process, accurately predicting energy consumption presents considerable challenges. This study proposes a novel Long Short-Term Memory Attention model for precise prediction of drilling pump energy consumption. By integrating Long Short-Term Memory (LSTM) networks with the Attention mechanism, the model effectively captures complex nonlinear relationships and long-term dependencies in energy consumption data. Comparative experiments with traditional LSTM and Convolutional Neural Network (CNN) models demonstrate that the LSTM-Attention model outperforms these models across multiple evaluation metrics, significantly reducing prediction errors and enhancing robustness and adaptability. The proposed model achieved Mean Absolute Error (MAE) values ranging from 5.19 to 10.20 and R2 values close to one (0.95 to 0.98) in four test scenarios, demonstrating excellent predictive performance under complex conditions. The high-precision prediction of drilling pump energy consumption based on this method can support energy optimization and provide guidance for field operations. [ABSTRACT FROM AUTHOR]

Russian foreign trade represents the main source of foreign exchange revenue in dealing with European countries, as the total Russian foreign trade with Europe is based on a value of about 232.8 billion dollars as an annual average for the period 2000-2021, of which exports represent about 158.9 billion. dollars, at a rate of 68.3%, and imports at about 73.9 billion dollars, at a rate of 31.7% annually. The volume of savings from trade achieved for the Russian economy amounted to about 85 billion dollars annually during that period, which contributed to achieving an increasing domestic product during that period, an annual average of 1314.4 billion dollars, with a significant annual growth rate of about 73.98 billion dollars, or 5.6% in GDP. Locally, the rate of economic exposure of the Russian economy to the European Union declines during the study period at the end of the study period compared to the beginning of the period, with an average of 19.2%. It is a rate that expresses a good indicator for the Russian economy and that the influence of the European economy is declining on the Russian economy. The study showed that the growth of the Russian domestic product depends mainly on both exports and imports to the European Union and is not affected by any other factors, and that Russian foreign trade was represented in energy and by studying the volume and imports of energy. For the European Union from Russia it turns out that European countries depend mainly on imported energy, at a rate of 74% of consumption in gas, 94% of consumption in oil, and about 38% of the rest of the petroleum products, as an average for that period, and an average of about 57%. By analyzing the production, consumption, and imports of energy in the European Union (oil, gas, coal), it was found that consumption of oil increases. The increase in production during the study period led to an increase in reliance on Russian oil to fill the oil gap, from about 181.2 million tons in 2001 to 214.6 in 2021, with an annual average of about 267.2 million tons. Then, the importance of Russian oil to the European Union in relation to consumption increased from about 31.7% in 2001 to about 52% in 2009, then it decreased to reach about 32.2% in 2021, with an annual average of 40.6% of the volume of European consumption. The volume of Russian oil represents the source to Europe accounted for about 66.6% of Russia’s oil exports to the world during that period. As for gas, the European Union’s amount of imports of Russian gas increased from about 124.7 billion cubic meters during the study period. With an average of 48.2% of the volume of European gas consumption, as for coal, it has been shown that the European Union is trending toward a decrease in the rate of annual consumption of coal, which has led to a relative reduction in dependence on Russian coal. However, the most important countries that still depend on Russian coal to a large extent are Lithuania, with a percentage of 72.2%, Latvia 80.9%, Netherlands 18.7%, Slovakia 23.3%, Spain 32.3%, Norway 12.6%, Belgium 17.6%, Denmark 41.8%, Cyprus 48%, Croatia 35.6%, Finland 37.7%, Britain 18.3%. Looking at the foreign trade between Europe and Russia during the period 2013-2023, it turns out that the volume of energy represents 100 billion dollars annually, out of a total trade amounting to about 222 billion dollars annually, representing 45% of the volume of energy trade between Russia and Europe, of which 99 billion dollars is for imported energy annually, and a percentage of 69.2% of the volume of trade with Russia during that period, while the rest of the trade components were machinery and vehicles, about $34 billion in exports to Russia, $18 billion in other manufactured goods, and $17 billion in chemicals. To clarify the extent of the European economy's dependence, mainly on Russian energy, which represents more than 50% of the energy that Europe uses, to clarify the extent of the European economy's mutual dependence and need on the Russian economy and the Russian economy's need to spend energy to obtain various goods and achieve development. [ABSTRACT FROM AUTHOR]

The accurate prediction of China's energy consumption and CO2 emissions is important for the formulation of energy and environmental policies and achieving carbon neutrality. This paper proposes a new weighted error evaluation criterion that emphasizes the importance of new data, thereby enabling more accurate capture of the variation characteristics of new data and reflecting the principle of new information priority. By optimizing the development coefficient, grey action, and parameters in the time response formula of the traditional GM(1,1), a novel optimized model, OGMW(1,1), is constructed. The accuracy of the new model is verified by three cases from the literature. The future trends of primary energy, oil, and coal consumption and CO2 emissions in China are predicted over the next five years. The conclusions are as follows: First, the new weighted error evaluation criteria are effective and reasonable and can indicate whether a grey model can reliably use the most recent information for modeling. Second, based on the new error evaluation criteria, the development coefficient, ash action, and parameter C in the time response function can be optimized. The results show that the optimization method is reasonable. Third, compared with the traditional models GM, GMO, and ARIMA, the OGMW(1,1) provides better simulation and prediction accuracy, and new information can be prioritized more effectively. Fourth, the forecasting results indicate that China will increase its consumption of primary energy, oil, and coal, as well as its CO2 emissions. Notably, the growth rates of primary energy and oil consumption are high at approximately 22.7% and 25%, coal consumption will increase slightly, and CO2 emissions will increase by approximately 11%. [ABSTRACT FROM AUTHOR]

The article traces the origin of several generalized conformability bounds for split and splitless piston rings used in the automotive industry to troubleshoot and better design piston engines and compressors for lesser emissions and oil consumption by presenting an irregular power cylinder bore shape through individual Fourier waveforms of a different order. The work also elucidates the origin and capabilities of the prematurely forgotten specialized ring-bore contact models of the 1940s for single-order bore deformation (round and oval), according to which a ring-bore seal breach occurs only near the ring ends and emerges with any bore deformation. With the aid of this information, the report explains that the split ring generalized models' theoretically defined conformability bounds are largely conventional categories that become sufficiently compelling engineering tools only by adapting the models to the experimentally observed or analytically asserted ring-bore clearances near the ring ends and considering the ring and bore design and production deviations from the theoretical models. The study further demonstrates that different researchers' semiempirical versions of these bounds were spinoffs from the author's analytical model of 1990. The article's information helps engineers design piston rings and the associated components with better functional and tribological properties. [ABSTRACT FROM AUTHOR]

In this paper, we employ the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of state-level stock returns in the United States (US) based on structurally decomposed four monthly oil shocks associated with oil supply, global economic activity, oil consumption and oil inventory. We find that over the daily period of (February) 1994 to (December) 2022 and various forecast horizons, in 46 out of the 50 states, the GARCH-MIDAS model with at least one oil shock can outperform the benchmark, i.e., the GARCH-MIDAS-Realized Volatility (RV), with 24 states depicting the importance of all the four shocks. In general, oil market-specific shocks, whether supply or demand, tend to matter more than a global economic impact driving the oil market in forecasting volatility of regional stock returns across with better forecasting performances related to states with higher CO2 emissions based on underlying energy consumption data. Our findings have important implications for investors and policymakers, with the observations for the former group depicted by an analysis of economic significance, i.e., utility gains. [ABSTRACT FROM AUTHOR]

The debate over global oil demand growth has become polarized between two trends: the electrification of road transport, which reduces oil consumption, and the rising industrial demand for petrochemicals and plastics, which increases it. Recent forecasts present conflicting views on these trends. While transportation remains the largest oil consuming segment, the impact of growing petrochemical and industrial applications is less well understood due to limited data on intermediate products and refinery processes. Understanding the relationship between consumer goods demand and petrochemical oil use is crucial for accurate corporate planning and energy policy, highlighting the need for improved data and measurement. [ABSTRACT FROM AUTHOR]

ABSTRACT A high circulating total cholesterol (TC) concentration increases the risk for atherosclerosis in the domestic dog. Intake of marine foods is associated with a lowering effect on circulating TC concentration in humans and rodents, but the reported effects of marine ingredients on the TC concentration in domestic dogs has not yet been reviewed. The main aim was to investigate the effects of consuming marine ingredients on the TC concentration in domestic dogs. A systematic literature search was performed using the databases PubMed, Web of Science and Embase, structured around the population (domestic dogs), intervention (source and type of marine ingredients, dose, duration), comparator (control diet) and the primary outcome (circulating TC). Articles were assessed for risk of bias using the SYRCLE's tool. A meta‐analysis was conducted in Review Manager v. 5.4.1 (the Cochrane Collaboration), comprising 12 articles with 243 dogs. Consumption of marine oils resulted in a significantly lower circulating TC concentration relative to comparator groups (mean difference −0.70 mmol/L, 95% CI (−1.21, −0.18), p = 0.008), with high statistical heterogeneity (I2 = 78%). The risk of bias is unclear since few of the entries in the SYRCLE's tool were addressed. We did not identify any studies using marine proteins or marine organisms other that fish. To conclude, intake of marine oils results in a lower TC concentration in dogs, thus reducing an important risk factor for atherosclerosis in canines. This study was registered at www.crd.york.ac.uk/PROSPERO/ as CRD42023396943. [ABSTRACT FROM AUTHOR]

Background: Tropical oils such as palm and coconut oils are renowned for their high saturated fat content and culinary versatility. However, their consumption has sparked debate regarding their health benefits and production concerns. The purpose of this review was to map existing evidence on the health benefits and challenges associated with the consumption of tropical oils. Method: The recommendations for conducting a scoping review by Arksey and O'Malley were followed. PubMed, Dimensions AI, Central, JSTOR Google, Google Scholar, and ProQuest databases were searched for relevant papers. The predetermined keywords used were Consumption" AND "Tropical oil," as well as "Health benefits" OR "Health challenges" AND "Tropical Countries." Peer-reviewed and grey literature published in English were eligible for this review. Result: Tropical oils, such as palm and coconut oils, provide health benefits including essential vitamins (A and E) that enhance ocular health, boost immunity, and support growth. They are also recognised for their role in managing high blood sugar, obesity, and cholesterol levels, while offering antioxidant and anti-inflammatory properties. These oils have wound-healing abilities and are commonly used in infant nutrition and traditional cooking. Nevertheless, prolonged and repeated use of tropical oils to high temperature can degrade vitamin E, whereas excessive intake may result in overdose. Health concerns include oxidative risks, diabetes, cancer, coronary heart disease, high blood pressure, and acrylamide formation due to production challenges excessive consumption. Additional issues include obesity, suboptimal oil production, misconceptions, regulatory obstacles, and preferences for alternative fats. Conclusion: This review suggest that tropical oils provide essential health benefits, including vitamins and antioxidant properties, but pose significant health risks and production challenges, particularly when exposed to high temperatures and through excessive intake. Guidelines on the consumption of tropical oils in the tropical regions are necessary to regulate their consumption. [ABSTRACT FROM AUTHOR]

The G7 countries, which represent a significant portion of global energy consumption and have a major impact on the World economy, consider energy to be of utmost importance. These advanced economies have a significant influence on global oil dynamics. Oil will continue to be a significant component of the global energy system, with an anticipated consumption of 70-80 million barrels per day by 2035. This study aims to investigate the causal relationship between oil consumption and economic growth in G7 countries from 1990 to 2022 using panel data analysis methods. The analysis employed Gengenbach et al.'s (2016) cointegration test and Emirmahmutoğlu and Kose's (2011) causality methods. The results indicate a cointegration relationship and a positive effect of oil consumption on economic growth. However, no causality relationship was detected between the variables, which supports the neutrality hypothesis in the literature. [ABSTRACT FROM AUTHOR]

Copyright of Experimental Technology & Management is the property of Experimental Technology & Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This work focuses on the evolution of lubrication wedge shaping in internal combustion piston engines, taking into account liquid microflows on curved surfaces and coating microgeometries. It introduces a new approach to the analysis of friction losses by simulating the microflow of lubricating oil between the surfaces of piston rings cooperating with the cylinder surface. The models used take into account three types of microgeometry and material expansion. Key results indicate that microirregularities with a stereometry of 0.1–0.2 µm significantly influence the distribution of oil film thickness in the phase of maximum working pressure, which is critical for the functioning of the seal ring. The innovation of the work consists of demonstrating that, despite small changes in the friction force and power in the piston rings, changes in the minimum values of the oil film thickness are significant. The work highlights the failure to take into account microgeometry parameters in friction models, which leads to significant errors in the simulation results, especially in terms of oil film continuity and the contribution of mixed friction. The simulations also indicate that advanced geometric models with high mesh resolution are necessary only for the assessment of changes in oil film thickness during the highest pressure increase in the combustion chamber and taking into account various mixed friction conditions. The results suggest significant progress in engine design and performance, confirming the importance of advanced fluid and mixed friction models in piston engine lubrication research. [ABSTRACT FROM AUTHOR]

Since the measurement of oil quantity in aviation engine lubrication systems is susceptible to multiple parameters, it is difficult to calculate and predict oil consumption rates. We propose an improved method for extracting oil quantity data and predicting oil consumption rates. Engine data are cleansed using density-based clustering algorithms, including density based spatial clustering of applications with noise (DBSCAN), to obtain stable oil quantity data during steady flight conditions. By the least squares method, oil consumption rates are derived with an average fitting goodness of 0.86. Subsequently, a multi-layer perception (MLP) is employed to establish the relationship between oil consumption rates and flight status parameters, resulting in a predicted average absolute percentage error of 1.15%, compared to actual values. The proposed method meets practical engineering requirements, providing a reliable reference for assessing the health status of aviation engine lubrication systems. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive approach to trim optimization as an energy efficiency improvement measure, focusing on reducing fuel consumption for one RO-RO car carrier. Utilizing Computational Fluid Dynamics (CFD) software, the methodology incorporates artificial neural networks (ANNs) to develop a mathematical model for estimating key parameters such as the brake power, daily fuel oil consumption (DFOC) and propeller speed. The complex ANN model is then integrated into a user-friendly software tool for practical engineering applications. The research outlines a seven-phase trim optimization process and discusses its potential extension to other types of ships, aiming to establish a universal methodology for CFD-based engineering analyses. Based on the trim optimization results, the biggest DFOC goes up to 10.5% at 7.5 m draft and up to 8% for higher drafts. Generally, in every considered case, it is recommended to sail with the trim towards the bow, meaning that the ship's longitudinal center of gravity should be adjusted to tilt slightly forward. [ABSTRACT FROM AUTHOR]

Restructuring energy supply and demand is one of the essential measures to realize the carbon emissions reduction target. To explore the impact of the restructuring of energy supply and demand on fossil fuel demand under the carbon emissions reduction target, takes China as an example, obtains a data set, and utilizes the elasticity analysis, incremental contribution method, weighted moving average method and scenario analysis to forecast the structure of energy demand and the consumption of fossil fuels. The study results show that the projected values of China's total energy consumption demand in 2030 and 2035 will be 6300.19-6419.82 million tons of standard coal and 6955.92-7175.29 million tons of traditional coal, respectively. The shares of coal, oil, and natural gas in total energy consumption in 2030 will be 45.68-46.35%, 17.95-18.27%, and 10.71-10.89% respectively; by 2035 the energy structure will be further optimized, and the shares of coal, oil, and natural gas in the total energy consumption will be 39.71-40.53%, 18.07-18.56% and 11.86-12.15%, respectively. Further forecasts of gasoline, kerosene, diesel, and fuel oil consumption in 2030 and 2035 are analyzed in this study. [ABSTRACT FROM AUTHOR]

Copyright of Uluslararasi Ekonomi ve Yenilik Dergisi is the property of Karadeniz Technical University, Depertmant of Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This comprehensive bibliometric analysis investigates energy-saving strategies in petroleum extraction, shedding light on key research areas, trends, and collaborations. The analysis covers 98 research articles spanning from 2003 to 2024, sourced from the Web of Science (WOS) database and analyzed using the Bibliometrics R package v.4.1.3, including descriptive statistics, network analysis, and factorial analysis. Findings reveal significant contributions from China, Canada, Russia, and the USA, with notable collaborations and thematic clusters identified. Top journals, prolific authors, and leading institutions are highlighted, showcasing global efforts in advancing sustainability in the oil industry. Institutions like the University of Calgary and authors such as Gates ID, Ren SR, and Zhang L play significant roles in advancing knowledge in this domain. Keyword analysis underscores prevalent themes such as optimization, simulation, and energy efficiency. Technological innovations, process optimization, and organizational strategies emerge as crucial avenues for reducing electrical energy consumption in oil extraction operations. However, limitations include database constraints and language bias. Overall, this study offers valuable insights for researchers, policymakers, and industry stakeholders, informing future research directions and policy initiatives for enhancing energy efficiency and sustainability in petroleum extraction. [ABSTRACT FROM AUTHOR]

Crude oil is one of the most widely used fossil energy sources at the global level, and it is the main engine of the global economy, including the US economy, which still consumes about 20% of the world's daily oil consumption of 100 million / b / d. Therefore, the cessation of the arrival of crude oil or part of it to The United States is the obsession that preoccupies decision makers in American foreign policy. The United States was and still is, and perhaps will remain in the future, and in the short and medium term, seeking to ensure the flow of crude oil coming from abroad, by all legal and illegal means, and what wars and conflicts the United States fought and more From half a century of time in the areas where crude oil sources and near them, and around the supply routes of international trade only testify to the strategic role of crude oil in the energy policy of the United States. [ABSTRACT FROM AUTHOR]

The world is stepping forward to a carbon-neutral economic system in response to the rising issues caused by climate change. Fossil fuel combustion is the primary source of increased carbon emissions, energy mix adjustment is critical to climate change mitigation and the carbon neutrality goal. This study investigates the different responses to energy sources' economic growth and environmental sustainability using balanced panel data from 34 Organization for Economic Cooperation and Development (OECD) countries during 1995–2019. This study uses oil, natural gas, and renewable energy to represent traditional, emerging alternative fossil, and green energy sources, respectively. Results show that renewable energy, oil, and natural gas all impose impacts on economic growth, however, renewable energy contributes more than oil and natural gas. Furthermore, there is a significant inverse relationship between the amount of renewable energy produced and carbon dioxide (CO2) emissions. While both natural gas and oil have a positive effect on CO2 emissions, the effect of natural gas is much smaller than that of oil. Furthermore, the causality investigation reveals that renewable energy, oil, and natural gas all show impacts on carbon emissions but do not contribute to economic growth. These findings suggest that increasing investment in renewable energy, with natural gas playing the role of a transitional replacement for oil, will contribute to the "carbon neutrality" process of these countries. [ABSTRACT FROM AUTHOR]

In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield. Statistical analysis has been conducted on nearly 45,000 wells from six fields in China. Critical factors such as lifting method, daily production, pump depth, gas–oil ratio (GOR), and well deviation angle were evaluated individually. Results revealed that higher production could lead to lower normalized consumption for beam pumps, progressive cavity pumps, and electric submersible pump systems, thus enhancing system efficiency. Additionally, a higher GOR might result in lower normalized consumption for the beam pump system, while the deviation angle of the well showed negligible impact on the normalized consumption factor. This manuscript offers a method to assess the impacts of artificial lift methods on production and discusses suggestions for reducing consumption associated with each lifting method in the oilfield. [ABSTRACT FROM AUTHOR]

The energy revolution in Saudi Arabia has accelerated significantly since 2016, driven by the National Vision 2030. Significant changes to energy subsidies took place, and the renewable energy sector has seen rapid growth. The paper presents an empirical analysis of the Saudi energy transition by emphasizing the drivers of fuel consumption in KSA. It primarily attempts to explore the long-run (LR) connection between oil consumption and several economic variables such as economic growth, crude oil prices, investment, and the labor force in Saudi Arabia (KSA) from 1991 up to 2021. The paper implemented the vector error correction model (VECM) and performed different diagnostic tests to provide more evidence about the validity and robustness of the tests. The empirical findings highlighted how important the labor force, savings, GDP, and crude oil price are in determining oil consumption for KSA. The law of demand is significantly present, which negatively affects oil consumption for KSA as an oil exporting country. The results also supported the existence of a long-term direct correlation between the variables and oil consumption. Furthermore, the short-term estimation highlighted that only saving has a negative impact on oil consumption for a single lagged period. Our findings provide governments and regulators with further incentive to slow the expansion in oil consumption, as a larger labor force is demanding more oil to attain the target, faster economic growth, and increased savings are all contributing factors. Our findings are significant because they can assist policymakers, investors, and regulators in generating more efficient oil substitutes and making them affordable for the economy. [ABSTRACT FROM AUTHOR]

Using historical data on energy from (Malanima 2020) and GDP from the Maddison Project Database, this paper investigates the energy-growth nexus in a less-studied region, mainly Australia and New Zealand, since 1870. The long annual series allow meaningful application of recently developed time-varying and quantile Granger causality analysis. Results indicate that there is a bi-directional Granger causal relationship between economic growth and energy, coal, and oil consumption at both ends of the distribution, and during various time periods over the past 150 years. Little evidence is found on the Granger causal relationship from gas consumption to economic growth, but some evidence on the direction from economic growth to gas consumption. The Granger causal relationships between electricity consumption and GDP change over time, but results suggest much closer links between the two in most recent decades, and big (positive and negative) changes in electricity consumption significantly Granger causes economic growth. [ABSTRACT FROM AUTHOR]

Wind propulsion systems (WPS) for commercial ships can be a key ingredient to achieving the IMO green targets. Most WPS installations will operate in conjunction with propellers and marine engines in a hybrid mode, which will affect their performance. The present paper presents the development of a generic, fast, and easy tool to predict the propeller and engine performance variation, along with the cost, as a function of the wind power installed in two operation conditions: fixed ship speed and constant shaft speed. Specific focus is directed toward showing generic trends and trade-offs that inform economic decision-making. To this end, a key feature of the presented work is the ability to assess the cost–benefit of both controllable pitch propellers and fixed pitch propellers (CPPs and FPPs). This provides advice on when, in terms of WPS installation size, it is worthwhile to install which kind of propeller. CPPs are found to be more suitable for newly built wind-powered ships (>70% wind power), while a conventional FPP is satisfactory for wind-assisted ships (<70% wind power) and retrofitted installations. The results for a 91,373 GT bulk carrier showed that a WPS unloads the propeller and the engine, which leads to an increase in the propulsive efficiency and a detrimental rise of the engine specific fuel oil consumption. However, propeller gains are found to be greater than engine losses, which result in extra savings. Thus, not only does a WPS save fuel and corresponding pollutant emissions, but it also increases the entire propulsive efficiency. [ABSTRACT FROM AUTHOR]

The Organization of Petroleum Exporting Countries (OPEC) is the international organization with the function of coordinating and unifying the petroleum policies of its member countries. It centrally controls much of the world's oil supply. While this is generally accepted, it is not well understood how OPEC exercises this broad function, what drives its decision-making. The article closes this gap in the literature through a close study of the published OPEC production policies for the period of 2019–2022. The article finds that internally predicted demand was the primary driver, over external factors that could also have affected production decisions, such as sanctions on OPEC or OPEC+ members, the rise of US shale oil, or climate change mitigation. It follows that consumer states can most effectively influence OPEC petroleum production decision-making by reducing their own oil consumption. The article finally places these findings into a broader context of the law of international organizations, where organizations have a responsibility to exercise their functions within evolving international law. Their decision-making can then be assessed through the three vector-matrix that this article proposes, comprising internal drivers, external factors, and the position of third states. [ABSTRACT FROM AUTHOR]

India, with its rapidly growing economy, has an increasing demand for energy consumption. This study thus adds to the energy-economic growth literature by exploring the effect of renewable (hydro and nuclear) and non-renewable (coal and oil) energy consumption by different sources on the economic growth of India, spanning from 1985 to 2021. The ARDL estimator is used to assess the short- and long-run growth effectiveness of the explanatory variables, while the variance decomposition analysis (VDA) is employed to examine the degree to which one variable can explain the change in variance of another variable. Among the renewable energy sources, hydro-energy consumption is found to be impeding economic growth, while nuclear energy is found to be inducing India's economic growth in the long run. Furthermore, among the non-renewable energy sources, oil consumption is found to be impeding the economic growth, while coal consumption is observed to be augmenting India's economic growth in the long run significantly. The findings reveal that non-renewable energy use plays a crucial role in the economic growth of India; thus, from a policy standpoint, this study recommends the government to invest more in the advancement of the renewable energy sector in order to balance the energy mix and achieve sustainable economic growth. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are becoming very popular nowadays to reduce the consumption of oil and environmental pollution. The use of battery and super-capacitor is increasing as the power-source of EVs. The bi-directional DC-DC converter is essential to integrate the battery and super-capacitor with the motor of the vehicle. However, a conventional second-order bi-directional DC-DC converter cannot give very high/low output voltage due to its efficiency reduction at extreme duty cycles, which is prerequisite for EVs. The problems of achieving high efficiency in wide-input-wide-output (WIWO) voltage range bidirectional operation using a conventional bidirectional converter are summarized in this paper. Additionally, the available converters from the literature for WIWO voltage range operation are discussed in detail. The various wide voltage range DC-DC converters are classified into different categories based on their operating principle. Additionally, the advantage and disadvantages of these various wide voltage range converter topologies are explained for the EV application. Finally, a general conceptual solution to achieve a WIWO converter with high efficiency is proposed. It is essential to change the voltage level of the motor input as per the speed requirement. Hence, this paper presents a clear idea for the WIWO bi-directional converters for EV application. [ABSTRACT FROM AUTHOR]

The article focuses on the prediction of rate cuts in 2024 by Fed Chairman Powell, indicating a potential slowdown in the US economy. Topics discussed include projections of GDP growth, unemployment rates, and interest rate decreases, suggesting cautious consumer spending and potential risks in the commercial real estate market.

India is among the largest and fastest-growing economies in the world. To continue its growth, energy is and will continue to be one of its most important considerations. With a population of over one billion, India is the third largest consumer of petroleum on the globe. To maintain this ranking, India imports a large percentage of its total oil consumption. Given India's current position as a large importer of oil, how does oil price volatility affect the Indian economy? This paper examines the effect of oil price volatility on inflation, economic growth, and the stock market in India. Statistical tests suggest that the overall price level, the real effective exchange rate, and oil prices are negatively related to aggregate output in the long run. Granger causality test results derived from a vector error correction model support bidirectional causality between oil prices and aggregate output, indicating that a change in oil prices also affects aggregate output in the short run. [ABSTRACT FROM AUTHOR]

This article explores the potential for renewable energy sources in Iraq, given the country's current reliance on fossil fuels. It discusses the economic challenges facing Iraq, including the dominance of state-owned firms, strict laws, limited access to finance, a shortage of skilled labor, and poor infrastructure. The article highlights the need for diversification in the economy and decreased dependence on crude oil export revenues. It also discusses the challenges and obstacles to investment in renewable energy projects in Iraq, emphasizing the importance of transitioning to renewable energy sources and the potential benefits they can provide to communities. [Extracted from the article]

Purpose: This paper aims to examine the effect of sesame oil (SO) on fatigue and mental health status in women with nonalcoholic fatty liver disease (NAFLD) undergoing a weight-loss diet. Design/methodology/approach: In total, 60 women with NAFLD were randomly assigned to receive 30 g/day of either SO (n = 30) or sunflower oil (n = 30). All the patients received a hypocaloric diet (−500 kcal/day) for 12 weeks in a double-blinded controlled trial. Anthropometric indices, dietary intake, physical activity, fatigue and mental health status were measured at the baseline and the trial cessation. Findings: In total, 53 participants completed the intervention. Significant reductions in anthropometric indices were observed in both groups (p-value = 0.001). Following SO, fatigue (p-value = 0.002), anxiety (p-value = 0.011) and depression (p-value = 0.013) scores were significantly reduced, while no significant changes were observed in stress scores. Originality/value: In summary, the present study was conducted to assess the efficacy of SO consumption on fatigue and mental health status among patients with NAFLD. The results revealed SO consumption significantly reduced fatigue, anxiety and depression scores in comparison with the control group, but not for stress scores. Further clinical trials, different doses, with a longer duration of intervention, in different groups, are necessary to confirm the veracity of the results. [ABSTRACT FROM AUTHOR]

Once a cornerstone of the U.S. economy, crude oil production now experiences a paradigm shift, abundant for domestic consumption and export, signaling a lasting global oil price transformation. Despite a surge in U.S. hydrocarbon production and weakening oil prices, imports from Nigeria dramatically dropped from 1.5 million barrels per day in 2006 to 0.2 million in 2013, ceasing entirely by early 2014. Consequently, Nigeria faced a sudden depletion of trade surpluses and reduced foreign reserves. This study delves into the immediate and long-term challenges confronting Nigeria, particularly examining the impact of recent oil and gas price fluctuations on key macroeconomic factors. Findings highlight the balance of payments' high elasticity to oil price shifts and low elasticity to money supply changes with a coefficient of determination of 78.69%. Additionally, the exchange rate shows low elasticity to oil price changes and moderate elasticity to money supply variations with a coefficient of determination of 82.80%. [ABSTRACT FROM AUTHOR]

In the maritime industry, optimizing vessel fuel oil consumption is crucial for improving energy efficiency and reducing shipping emissions. However, effectively utilizing operational data to advance performance monitoring and optimization remains a challenge. An XGBoost Regressor model was developed using a comprehensive dataset, delivering strong predictive performance (R2 = 0.95, MAE = 10.78 kg/h). This predictive model considers operational (controllable) and environmental (uncontrollable) variables, offering insights into complex FOC factors. To enhance interpretability, SHAP analysis is employed, revealing 'Average Draught (Aft and Fore)' as the key controllable factor and emphasizing 'Relative Wind Speed' as the dominant uncontrollable factor impacting vessel FOC. This research extends to further analysis of the extremely high FOC point, identifying patterns in the Strait of Malacca and the South China Sea. These findings provide region-specific insights, guiding energy efficiency improvement, operational strategy refinement, and sea resistance mitigation. In summary, our study introduces a groundbreaking framework leveraging machine learning and SHAP analysis to advance FOC understanding and enhance maritime decision making, contributing significantly to energy efficiency and operational strategies—a substantial contribution to a responsible shipping performance assessment under tightening regulations. [ABSTRACT FROM AUTHOR]

We examine the impact of the global economic activity, oil supply, oil-specific consumption demand, and oil inventory demand shocks on the expected aggregate skewness of the United States (US) economy, obtained based on a data-rich environment involving 211 macroeconomic and financial variables in the quarterly period of 1975:Q1 to 2022:Q2. We find that positive oil supply and global economic activity shocks increase the expected macroeconomic skewness in a statistically significant way, with the effects being relatively more pronounced in the lower regime of the aggregate skewness factor, i.e., when the US is witnessing downside risks. Interestingly, oil-specific consumption demand and oil inventory demand shocks contain no predictive ability for the overall expected skewness. With skewness being a metric for policymakers to communicate their beliefs about the path of future risks, our results have important implications for policy decisions. [ABSTRACT FROM AUTHOR]

This paper studies the effect of oil price shocks on China's consumer and entrepreneur sentiment using a novel Bayesian inference structural vector autoregression model. Interestingly, we find that oil supply and demand shocks that raise oil prices have significantly positive effects on both consumer and entrepreneur sentiment. These effects are more significant on entrepreneur sentiment than on consumer sentiment. Furthermore, oil price shocks promote consumer sentiment mainly by increasing their satisfaction with current income and their expectation of future employment. Oil price shocks would change consumers' saving and consumption decisions but not their plans to buy cars. Meanwhile, the effect of oil price shocks on entrepreneur sentiment differs across different types of enterprises and industries. [ABSTRACT FROM AUTHOR]