Energy Efficiency Factor Research Articles

Efficacy and Safety of Ultrasound-Guided High-Intensity Focused Ultrasound Ablation in Women With Multiple Uterine Fibroids: An Exploratory Study.

The aim of the work described here was to explore the clinical efficacy and safety of ultrasound-guided high-intensity focused ultrasound (USg-HIFU) treatment in women with multiple fibroids and identify the characteristic parameters predicting USg-HIFU efficacy in multiple fibroids. From February 2021 to August 2022, 138 patients with multiple fibroids (group A comprising 125 patients with two to four fibroids and 13 patients with five or more fibroids) and 149 patients with solitary fibroids (group B) were included. HIFU treatment information, efficacy comparisons and adverse events were recorded. A nomogram model of the characteristic parameters used to predict the efficacy of USg-HIFU in multiple fibroids was established. After USg-HIFU treatment, the statistical comparison of pre-operative versus post-operative symptom scores and fibroid volume in the two groups indicated obvious symptom relief and substantial shrinkage of fibroid volume (all p values <0.001). Nevertheless, group A required more energy and longer treatment and sonication times to achieve a 70% non-perfused volume (NPV) ratio, and had a lower energy efficiency factor than group B (all p values <0.05). No severe complications were observed in either group. The nomogram model included fibroid volume, fibroid location and signal intensity on T2-weighted imaging (T2WI). The area under the receiver operating characteristic curve and the accuracy of the model were 0.698 and 0.686, respectively. USg-HIFU appears to be an effective and safe treatment option for multiple fibroids. Knowledge of the fibroid volume, location and signal intensity on T2WI may help determine the efficacy of USg-HIFU in multiple fibroids.

Assessment of modeling methods for predicting load resulting from hydrogen-air detonation

As hydrogen becomes an increasingly vital component in the transition toward a sustainable energy system, its flammable and detonable properties necessitate a comprehensive understanding of its explosive characteristics. This study evaluated the accuracy and computational efficiency of an innovative numerical approach that integrates CESE compressible CFD solver, chemistry reaction model, and structural FEM solver within LS-DYNA to predict hydrogen detonation loads. Comparisons were made with the commonly used energy equivalent methods, i.e., the TNT equivalent method, and the high-pressure volume method, which utilizes multi-material ALE techniques. Hydrogen detonation test results from open-air space, open-air space with a blast wall, and semi-confined space were compared against numerical simulations. The results revealed that, for scaled distance exceeding 0.79 m/kg1/3, all three methods accurately predicted the peak overpressure. The TNT equivalent method exhibited an unexpectedly high energy efficiency factor exceeding 0.51, significantly surpassing the recommended range of 0.01–0.1 for typical vapor cloud accidents. The CESE-chemistry coupling method exceled in capturing overpressure duration and structural response due to its consideration of chemical kinetics. As the scaled distance reduced to 0.37 m/kg1/3, the CESE-chemistry coupling method maintained its proficiency in modelling pressure waves, while the TNT equivalent method overestimated peak pressure by 494%. Conversely, the high-pressure volume method underestimated the peak pressures within or near the H2-air cloud. Nevertheless, the CESE-chemistry coupling method required significantly higher computational costs, with 15–20 times more computational time compared to the other two methods, and 60–70% of the total computation time was spent solving chemical kinetics. It is concluded from the current study that for scenarios involving close scaled distances (less than 0.37 m/kg1/3) or where the structure locates inside or near the gas cloud, the CESE-chemistry coupling method may be preferred despite its higher computational demands. Conversely, for simulations prioritizing computational efficiency and larger scaled distances, the TNT equivalent method or high-pressure volume method is recommended. These findings offer guidelines for researchers and engineering professionals engaged in assessing and mitigating risks associated with hydrogen explosion accidents in the pursuit of safe and sustainable hydrogen utilization.

Safety of Sonazoid in Assisting High-Intensity Focused Ultrasound Ablation Therapy for Advanced Liver Malignant Lesions: A Single-Arm Clinical Study

The aim of the study described here was to evaluate the safety of Sonazoid-assisted high-intensity focused ultrasound (HIFU) in the treatment of advanced malignant liver lesions. A single-arm study was designed to enroll participants who were diagnosed with advanced primary liver cancer or liver metastases and proposed to receive Sonazoid assistance during HIFU treatment. Serological examination was conducted within 1 wk, and side effects in each patient were monitored for 1 mo. To evaluate therapeutic efficacy, the contrast-enhanced magnetic resonance imaging was performed 1 mo after treatment, and short-term follow-up was conducted a year later. A total of 17 participants (12 male, 5 female) with an average age of 58 y (range: 46-73 y) were enrolled, including 11 patients with hepatocellularcarcinoma, 2 patients with hepaticmetastasis and 4 patients with cholangiocarcinoma. The total volume of tumor mass was 111.82 (11.01-272.30) cm3. The average total ablation time for a patient was 2021 ± 1030 s, and the energy efficiency factor was 5979.7 (3108.0, 45634.5) J/cm3. Immediately after HIFU treatment, 1 patient (5.9%) achieved complete response (CR), 4 patients (23.5%) had a moderate response, 8 patients (47.1%) had partial reperfusion and 4 patients (23.5%) had stable disease (SD). The average ablation rate for all the tumors was 51.5 ± 26.7%. The level of glutamic-pyruvic transaminase (ALT) was mildly increased in 71.6% (12/17) of patients after HIFU therapy. Mean ALT values before and after treatment were 22 (14, 35) U/L and 36 (25, 41) U/L, respectively (Z=1.947, p=0.051). Mild or obvious edema in skin and subcutaneous soft tissues were observed in 76.5% of patients, but no serious side effects were found. Twelve months after treatment, the follow-up results revealed that 1 patient (5.8%) achieved a CR, 8 patients (47.1%) had SD and 8 patients (47.1%) had progressive disease. The estimated median time to progression was 11 mo after treatment, with a 95% confidence interval of 6, 11 for all involved patients. Use of Sonazoid is safe and feasible for improving HIFU ablation efficiency during the treatment of advanced malignant liver lesions. The therapeutic efficacy of Sonazoid-assisted HIFU needs to be explored in additional controlled clinical investigations.

Research on the low carbon development path of China's coal industry under carbon peaking & carbon neutral target: Based on the RCPs-SSPs framework

Coal industry is one of the important engines of China's economic development and one of the key units in advancing the goal of CO2 peaking and CO2 neutrality. This study systematically measured the CO2 emissions of coal resources at the stages of mining and washing, transportation, processing and conversion, and consumption and utilization from a whole life cycle perspective, analyzed the drivers of CO2 emissions using the Kaya-LMDI model, and set up scenarios based on the RCPs-SSPs framework to explore the CO2 peaking paths. The specific findings were as follows. (1) The CO2 emissions of this industry increased from 2224.62 Mt to 7676.63 Mt from 2000 to 2020, an annual increase 6.39%. Among them, the processing and conversion stage is the main contributor to the CO2 emission, and its CO2 emission increases from 1296.23 Mt to 5003.65 Mt, an annual increase 6.99%. (2) Industrial structure, energy efficiency, and energy structure factors showed negative inhibitory effects on CO2 emissions in this industry. Further, from the trend of the driving effects of each factor, the inhibitory effects of industrial structure and energy structure on CO2 emissions showed an increasing trend, and the inhibitory effects of energy efficiency on CO2 emissions showed an increasing trend followed by a decreasing trend. (3) The results of the scenario analysis showed that the sustainability-oriented scenario is the low-carbon development state that this industry can achieve through more comprehensive and active initiatives in achieving the expected socio-economic development goals, and it is also a relatively reasonable path to achieve CO2 peak and CO2 neutrality. Under this scenario, the total CO2 emission of China's coal industry in 2030 reaches 10.044 billion tons, which is 1.083 billion tons less than that of the status quo continuation scenario in 2030, and the CO2 reduction effect is obvious. These findings can provide a reference for the improvement of low-carbon development policies in the coal industry.

Total-Factor Energy Efficiency and Its Driving Factors in China’s Agricultural Sector: An Empirical Analysis of the Regional Differences

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc.

An energy survey to optimize the technological parameters during the milling of AISI 304L steel using the RSM, ANN and genetic algorithm

ABSTRACT The world’s population growth has led to increased demand for products, which requires enormous energy consumption. Therefore, energy savings are becoming a primary objective for industrial sectors. This study uses artificial intelligence, specifically response surface methodology (RSM), artificial neural networks (ANN) and genetic algorithms (GA), to optimise machining parameters in the mechanical manufacturing sector. The findings demonstrate that the use of artificial intelligence can reduce the amount of energy used in machining operations, increasing both productivity and cost. According to the analysis of variance, the depth of cut a p and the feed rate V f are the most influential factors on total specific energy consumed (TSEC). Meanwhile, spindle speed is the most influential factor for energy efficiency (EE). EE increases when there is an increase in the rate of material removal as opposed to decreasing total specific energy. The study also shows that the multi-objective optimisation with the genetic algorithm can reduce TSEC by 44.13% and increase EE by 14.63%. The optimal cutting parameters given by the genetic algorithm are the spindle speed, feed, depth of cut and number of teeth.

An energy-CP-combined model for predicting the fatigue life of polycrystalline materials under high cycle and very high cycle fatigue

A fatigue life prediction model in the high to very high cycle fatigue (VHCF) regime of as-received 7075-T6 Al alloy material is proposed. The relative parameters in the life prediction model are obtained by crystal plasticity finite element (CPFE) framework. The modified Ohno-Wang constitutive model is embedded into the CPFE model considering the evolution of back stress during the cyclic loading. In the life prediction model, the range of energy efficiency factors is validated by verifying the plastic strain energy density (PSED) with fatigue experimental data. The fatigue experiments are performed using an ultrasonic fatigue system to validate the fatigue life prediction model. The predicted life is estimated using the maximum and minimum energy efficiency factors, it is found that the life prediction model can accurately predict the VHCF life. It is found that 72.8%–81.3% of the experimental fatigue life can be captured using the proposed model. Moreover, the localized deformation in the grain scale can be well-captured considering the heterogeneity of mechanical properties.

Life cycle assessment of a micro-region Hungarian municipal solid waste: Evaluation of six waste-to-energy scenarios

Waste-to-energy technologies are key to a sustainable future. The non-recyclable share is often converted to refuse-derived fuel (RDF) for energy utilization to landfill only about 10% of the initial volume. The composition of such fuels may significantly vary; therefore, the currently investigated samples were compared to several others available in the literature and found to be internationally representative. Then six different waste-to-energy scenarios were evaluated, suitable for a Hungarian micro-region: steam turbine, external combustion gas turbine, Organic Rankine Cycle with both direct and indirect fuel use, gas turbine, and internal combustion engine. The first three incinerated RDF, while the last three utilized pyrolysis gas of RDF. The thermal cycle of all six scenarios was evaluated first, followed by their assessment of the energy efficiency factor of the recovery, R1, mandated by the European Parliament and of the Council in Annex II of Directive 2008/98/EC on waste. It was concluded that the R1 threshold of 0.65 was only fulfilled by the gas turbine and the internal combustion engine. Finally, the environmental impact of the systems is addressed via life cycle assessment. The results were normalized and weighted to end up with a single score to facilitate decision-making, which is a novel approach in the field of WtE system assessment. The steam turbine, the gas turbine, and the internal combustion engine were all relatively efficient thermal cycles, resulting in a very similar positive impact with a mean of 321 person equivalent. This measure of the two Organic Rankine Cycle scenarios and the external combustion gas turbine was 639 person equivalent.

Measurement and driving factors of carbon productivity in China's provinces: From the perspective of embodied carbon emissions.

Carbon productivity incorporates economic development and carbon emissions within a unified framework for measuring the economic value per unit carbon emissions. In the context of climate change, improving carbon productivity is of great value for promoting low-carbon development in a country or region. From the perspective of embodied carbon emissions, this study constructs an embodied carbon productivity (ECP) index and uses the Logarithmic Mean Divisia Index decomposition method to study the evolution trends and driving factors of ECP in China's provinces based on China Interregional Input-Output Tables for 2002, 2007, 2012, and 2017. The following results were obtained: First, China's overall ECP showed a continuously increasing trend during the entire period, with the energy efficiency factor playing the largest role among all driving factors. Second, the ECP in 19 of the 30 Chinese provinces continued to increase and the contributions of energy emission ratio, ECP per capita, and population size factors to the increase in ECP presented evident disparities among different provinces. Third, the ECP in three major regions ranged from high to low in the order of East, Central, and West, with the largest growth in the Central, followed by the West, with the smallest in the East. Based on the analysis of research results, we proposed relevant policy recommendations to further improve China's ECP and achieve low-carbon economy.

Measurements and spatio-temporal evolution of regional energy efficiency convergence in China

Balancing the ecological and economic benefits of energy consumption is an essential requirement and a key part of achieving the task of high-quality economic development and the goal of carbon neutrality. This paper analyses the energy efficiency and spatial and temporal evolution characteristics of thirty Chinese provinces and cities from 2006 to 2019 based on the DSBM model. The results show that, firstly, environmental factors have a significant impact on the evaluation of energy efficiency, with the national energy efficiency showing phase fluctuations and a decreasing trend from the east to the center and then to the west during the sample period. Secondly, the country and the three major regions did not show a σ convergence. Thirdly, there is significant absolute and conditional convergence in overall energy efficiency after considering spatial spillover effects, and with a turning point. Fourthly, energy efficiency in the three major regions also shows a clubbing phenomenon, with different regions tending to their own steady state of energy efficiency. Finally, we put forward suggestions for improving energy efficiency. The results of the study help to understand the changing trends and influencing factors of inter-regional energy efficiency in China, which can provide a reference for achieving the transformation of energy structure and has important practical significance.

Energy and air? The impact of energy efficiency improvement on air quality in China.

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality.

How the energy technology influences the total factor of energy efficiency?: evidence from China.

Technological progress is of great importance to total-factor energy efficiency (TFEE). However, previous research has not narrowed technological progress into the energy field, generating rough and ambiguous empirical evidence for policymakers. In addition, technological progress is often discussed from a conventional perspective as a whole, ignoring its heterogeneity and spillover effect between regions. This study applies the stock of energy patents to reflect the effect of technological progress in the energy field on TFEE at first. The dynamic models are then employed to investigate if and how technological progress influences TFEE from the conventional and spatial perspectives for China's over the period of 2000-2016. The conventional analysis shows that energy technology is of great importance to TFEE. However, the creation-type of technology coming from businesses specifically is shown to have more success in enhancing TFEE than other types of energy technology. Further evidence coming from the spatial econometrics demonstrates that technology spillovers across regions are rather common and have significant effects on TFEE.

Perspectives on the Applications of Radiative Cooling in Buildings and Electric Cars

Cooling energy consumption is a major contributor to various sectors in hot climates with a significant number of warm days throughout the year. Buildings account for 40% of total energy consumption, with approximately ∼30–40% of that used for cooling in geographical areas such as Iran. Energy demand for cooling is an important factor in the overall energy efficiency of electric mobility. Electric vehicles (EVs) consume ∼30–50% of energy for the air conditioning (AC) system. Therefore, the efficient management of the cooling demand is essential in implementing energy-saving strategies. Passive radiative cooling is capable of providing subambient cooling without consuming any energy. This article reviews potential applications of passive radiative cooling in reducing cooling energy for buildings. It also provides a rough estimate of the amount of energy saved when applying a radiative cool roof to a model building. It is shown that by using radiative cool materials on roofs, the share of electricity usage for cooling can be reduced to 10%, leading to a reduction in cooling load by 90%. Additionally, the potential use of radiative cool coats of various types for different EV components, such as shell/body, windows, and fabrics, is introduced. Although the prospects of the design and engineering of radiative cooling products appear promising for both buildings and EVs, further investigations are necessary to evaluate scalability, durability, and performance based on factors such as geography and meteorology.

A Study of Factors Affecting National Energy Efficiency

National energy efficiency is a key driver for the sustainable development of society. However, the conditions for increasing energy efficiency vary widely around the world and depend on numerous controllable and uncontrollable factors. Existing indicators for assessing energy efficiency typically focus on individual factors, neglecting the complex interplay of socioeconomic, environmental, technological, and other factors that influence energy efficiency. This limitation hampers the quality of assessments. The goal of this study is to develop and apply a comprehensive methodological approach for assessing the influence of key factors on energy efficiency across different countries. The approach utilizes factor analysis methods to identify correlations between indicators and energy-efficiency factors. The study’s findings offer a model for assessing energy efficiency that enables a more profound and comprehensive analysis of the multifactorial impact experienced by national economies in various energy-efficiency domains and areas.

How government green investment affects the carbon emission reduction process: empirical evidence from prefecture-level cities in China

Government green investment (GGI) is one of the effective tools for reducing carbon emissions (CEs). This is of great significance for the realization of “carbon peaking and carbon neutrality.” This study innovatively considers the multidimensional CE reduction (CER) process indexes to explore the impact mechanism of GGI on China’s CER process. At the same time, CER is particularly critical in resource-dependent regions. This study incorporates this perspective to explore the CER effect of GGI in these regions. This paper developed a multidimensional evaluation system for China’s CER process, using panel data of 269 prefecture-level cities from 2008 to 2019 to explore the impact of GGI on China’s CER process. The results indicated that 1) GGI promotes CER in China as a whole and effectively inhibits CEs,per capitaCEs, and CE intensity; 2) GGI promotes CER to some extent by enhancing the energy efficiency and total factor productivity; 3) it plays a larger role in CER in regions with a high energy endowment; and 4) the impact of GGI on CER is heterogeneous in geographical regions, city sizes, and economic development levels. This study makes policy recommendations for reducing CEs, including intensifying GGI and playing its investment-pulling role, thereby increasing the investment related to improving energy efficiency and total factor productivity and promoting government intervention in areas with high energy endowments.

A comprehensive review of energy efficient routing protocols for query driven wireless sensor networks

In this current era of communications and networking, The Internet of things plays the main role in the making of smart communication and networking. In this article, we have focused on the literature survey on wireless sensor networks which are energy efficient. Various standard protocols are reviewed along with some enhanced protocols which makes the network energy efficient. The comparison of the standard and enhanced protocols with respect to various applications in wireless sensor networks is thoroughly done in this article. The outcomes of the enhanced protocols are also briefly discussed. For easier analysis to future researchers, a comparative table which lists the enhanced protocols which are compared with standard counterparts along with the factors for energy efficiency of the protocols. This article also comments on the issues and challenges of the protocols which can be further analyzed for making the wireless sensor network more energy efficient.

Spatiotemporal influencing factors of energy efficiency in 43 european countries: A spatial econometric analysis

The increase in consumption and the increase in the use of resources linked to increasing human activity puts both energy security and sustainability at risk, which has led to a global restructuring of the policy agenda to ensure and integrate environmental well-being through channels such as energy efficiency (EE). Bearing this in mind, the objective of this research is to analyze the relationship between energy efficiency, renewable energy and financial development? For this reason, an analysis is conducted, which includes energy intensity measured by the Gross Domestic Product (GDP) per unit of energy use as a measure of efficiency for 43 European countries (period 1990–2019). The objective is to observewhether the use of renewable energy and the investments being made are driving economies towards higher EE and sustainable economic growth. The present study leverages on spatial econometrics models, which allow for the analysis of spillovers between economies. The results obtained allow us to observe the existence of spatial autocorrelation of EE between countries in Europe. Secondly, it is observed that the use of renewable energies promotes EE in neighbouring economies, as well as in the return effect. On the other hand, financial development shows that only the institutional component favours EE by generating a return effect on the economy itself, while the stock market component deteriorates the EE of neighbouring economies and on the same economy. Therefore, the analyzed data shows that the use of renewable energies promotes the improvement of EE and that being close to countries that replace the use of traditional energies with alternative sources has a positive effect on national EE. These mechanisms would allow policy makers to develop mechanisms for greener and more sustainable development, while encouraging efficient energy use.

Research on the dynamic evolution and influence factors of industrial energy efficiency in China Yangtze River Economic Belt

Improving the Yangtze River Economic Belt's industrial energy efficiency is not only an important measure to alleviate China's energy shortages but also a drive to promote green economic development. The Super-EBM model, Malmquist productivity index, exploratory spatial data analysis, and Spatial Dubin model are used in this article to investigate the spatial-temporal dynamic development characteristics and influencing factors of industrial energy efficiency in 108 cities of the Yangtze River Economic Belt from 2011 to 2020. The findings demonstrate that the industrial energy efficiency of the Yangtze River Economic Belt and its three urban agglomerations went through three stages, including the “oscillation period,” “stability period,” and “enhancement period,” and decreases from east to west in the spatial dimension. The Yangtze River Delta urban agglomeration has the highest industrial energy efficiency, followed by the Middle-reach Yangtze River urban agglomeration, and the Chengdu-Chongqing urban agglomeration is the lowest. Further, this article identifies seven influencing factors including government intervention, industrial structure, degree of openness, R&amp;D investment, urbanization, economic development, and environmental regulation. This article provides suggestions for industrial energy efficiency improvement.

Factors influencing USgHIFU ablation for adenomyosis with NPVR ≥ 50%

Objective To investigate the influencing factors of ultrasound-guided HIFU (USgHIFU) ablation for adenomyosis with a non-perfused volume ratio (NPVR)≥50%. Methods A total of 299 patients with adenomyosis who underwent USgHIFU ablation were enrolled. Quantitative signal intensity (SI) analysis was performed on T2WI and dynamic enhancement type. The energy efficiency factor (EEF) was defined as the ultrasound energy delivered for ablating 1 mm3 of tissue. NPVR ≥ 50% was used as the criterion for technical success. Adverse effects and complications were recorded. Logistic regression analyses of variables were conducted to identify the factors affecting NPVR ≥ 50%. Results The median NPVR was 53.5% (34.7%). There were 159 cases in the NPVR ≥ 50% group and 140 cases in the NPVR < 50% group. The EEF in NPVR < 50.0% group was significantly higher than that in NPVR ≥ 50% group (p < 0.05). The incidence of intraoperative adverse effects and postoperative adverse events in the NPVR < 50% group were higher than those in the NPVR ≥ 50% group (p < 0.05 for both). Logistic regression analysis showed that abdominal wall thickness, SI difference on T2WI between adenomyosis and rectus abdominis, and enhancement type on T1WI were protective factors for NPVR ≥ 50% (p < 0.05), while the history of childbirth was an independent risk factor (p < 0.001). Conclusions Compared with NPVR < 50%, NPVR ≥ 50% did not increase the intraprocedural and postprocedural adverse reactions. The possibility of NPVR ≥ 50% was higher in patients with thinner abdominal walls, showed slight enhancement of adenomyosis on T1WI, with a history of childbirth, or in whom the SI difference on T2WI between adenomyosis and rectus abdominis was more minor.

The drivers and barriers of energy efficiency

Energy efficiency is “the first fuel” due to its abundant availability and low cost in terms of supply, based on the IEA. The primary energy intensity was often employed to measure energy efficiency. Among 46 countries, the improvement of energy efficiency from 2000 to 2020 ranged between 61.54% and −3.16%, suggesting the situation and influence factors of energy efficiency may be different across countries. To systematically find the drivers and barriers of energy efficiency, panel regression models were built. The variation of energy efficiency can be explained by not only the traditional GDP and structure effects in the decomposition methods, but also the weather, trade, and infrastructure effects. For the heterogeneous countries, the average performer, instead of the best one in the data envelopment analysis, was compared. Estimated results indicated that key drivers of energy efficiency were the growth of GDP, increases of renewable energy, and electrification. The global warming decreased heating degree days and increased cooling degree days, causing the climate factors partially offset each other. Other factors of the energy efficiency improvement included the industrial transformation, trade openness, and increasing population. These influences were different across countries; thus, the country-specific routes of energy efficiency improvement were found.