bluuebunny/crossref_metadata_2025_split huggingface dataset:
Skillful prediction of UK seasonal energy consumption based on surface climate information
Authors: Li Samuel , Sriver Ryan , Miller Douglas E 
Published: April 2023

Abstract
Climate conditions affect winter heating demand in areas that experience harsh winters. Skillful energy demand prediction provides useful information that may be a helpful component in ensuring a reliable energy supply, protecting vulnerable populations from cold weather, and reducing excess energy waste. Here, we develop a statistical model that predicts winter seasonal energy consumption over the United Kingdom using a multiple linear regression technique based on multiple sources of climate information from the previous fall season. We take the autumn conditions of Arctic sea-ice concentration, stratospheric circulation, and sea-surface temperature as predictors, which all influence North Atlantic oscillation (NAO) variability as reported in a previous study. The model predicts winter seasonal gas and electricity consumption two months in advance with a statistically significant correlation between the predicted and observed time series. To extend the analysis beyond the relatively short time scale of gas and electricity data availability, we also analyze predictability of an energy demand proxy, heating degree days (HDDs), for which the model also demonstrates skill. The predictability of energy consumption can be attributed to the predictability of the NAO and the significant correlation of energy consumption with surface air temperature, dew point depression, and wind speed. We further found skillful prediction of these surface climate variables and HDDs over many areas where the NAO is influential, implying the predictability of energy demand in these regions. The simple statistical model demonstrates the usefulness of fall climate observations for predicting winter season energy demand prediction with a wide range of potential applications across energy-related sectors.
Quantum coherence as asymmetry from complex weak values
Authors: Budiyono Agung , Agusta Mohammad K , Nurhandoko Bagus E B , Dipojono Hermawan K 
Published: April 2023

Abstract
Quantum coherence as an asymmetry relative to a translation group generated by a Hermitian operator, is a necessary resource for the quantum parameter estimation. On the other hand, the sensitivity of the parameter estimation is known to be related to the imaginary part of the weak value of the Hermitian operator generating the unitary imprinting of the parameter being estimated. This naturally suggests a question if one can use the imaginary part of the weak value to characterize the coherence as asymmetry. In this work, we show that the average absolute imaginary part of the weak value of the generator of the translation group, maximized over all possible projective measurement bases, can be used to quantify the coherence as asymmetry relative to the translation group, satisfying certain desirable requirements. We argue that the quantifier of coherence so defined, called translationally-covariant (TC) w-coherence, can be obtained experimentally using a hybrid quantum–classical circuit via the estimation of weak value combined with a classical optimization procedure. We obtain upper bounds of the TC w-coherence in terms of the quantum standard deviation, quantum Fisher information, and the imaginary part of the Kirkwood–Dirac quasiprobability. We further obtain a lower bound and derive a relation between the TC w-coherences relative to two generators of translation group taking a form analogous to the Kennard–Weyl–Robertson uncertainty relation.
Study on PSA method applied to SSC aging sensitive screening and classification in nuclear power plant
Authors: Wang Handing , Li Qiongzhe 
Published: April 2023

Abstract
In order to extend the operation license of nuclear power plant, the nuclear safety during the extended service life must be considered, so as to ensure that the nuclear safety level of nuclear power unit during the extended service life is not lower than that of the original design life. PSA technology can be used to establish an aging PSA model for nuclear power plants during the license extension period, so as to evaluate the impact of SSC aging on the overall safety of nuclear power plants and verify that it can still meet the original design standards. Based on this, the SSC screening analysis method applied to aging PSA of nuclear power plant is put forward. By considering trend analysis, aging failure mode and impact analysis, risk importance analysis, the decision matrix of SSC screening for nuclear power plant is established on the basis of three analysis methods, and a feasible method is established for selecting aging and safety important components. This work also lays a technical foundation for the risk management of nuclear power plants in the license extension stage.
Study on economical efficiency of ocean energy generation in China
Authors: Zhang Cailin , Li Xin , Ma Changlei , Li Meng 
Published: April 2023

Abstract
Ocean energy, as a kind of renewable resource, plays an important role in China’s low-carbon development and meeting its goal of “carbon peaking and carbon neutrality”. The paper aims to calculate the cost of ocean power generation in China and make a medium and long-term forecast. Meanwhile, the offshore wind power development experience and the Levelized Cost of Energy (LCOE) cost pricing model is used for analysis and verification. The results shows that it features a high cost without economical efficiency in the initial stage; With the continuous expansion of installed capacity, the cost will be significantly lowered but the economical efficiency is moderate; the cost will fall significantly when the installed capacity reaches to a 100 MW level, and it has strong economical efficiency. The government should provide policy and financial support for ocean power generation industry; enterprises need to strengthen technological innovation and complete the industrial chain to improve the economical efficiency of scale utilization.
Study on direct parallel charging of lithium-ion battery and supercapacitor
Authors: Dong Ao , Ma Ruifei , Deng Yelin 
Published: April 2023

Abstract
Currently, there are few studies on hybrid system charging, and the existing ones rely on many power electronic components to charge lithium-ion battery and supercapacitor, respectively. This paper mainly focuses on the direct parallel charging of lithium-ion battery and supercapacitor, which has simple structure and low cost. However, the capacity of the hybrid system can not be fully utilized due to the unreasonable current distribution during charging. This paper proposes a method that improves the charging effect: constant current charging under fine tuning the resistance distribution of battery branch and supercapacitor branch (CCFTR). The results show that although the charging time is increased slightly with the CCFTR, the charging capacity can increase significantly. Compared with the untreated constant current charging (CC), the charging time is only prolonged by 6.77 minutes with the CCFTR (50mΩ) at 22A (2.75C), but the charging capacity is increased by 48.4%, reaching 95.1% of the rated capacity. And the CCFTR can dramatically prolong the battery life. The effect is better under higher current. Compared to the CC with the same charging current, the CCFTR can extend the battery life by 11.37% at 2.75C and 26.02% at 3.75C.
Application and comparison of multiple machine learning models for the prediction of the laminar burning velocity for CH3OH/H2/air mixtures
Authors: Zheng Kangxue , Wang Xuehui , Wang Jian 
Published: April 2023

Abstract
Recent investigations have indicated that co-firing CH3OH with H2 is a promising approach to develop a carbon-neutral energy system. However, accurate measurements of laminar burning velocities over a wide range of equivalence ratios, H2 mole fractions, pressures and temperatures are complicated and may not available. Hence, this research deeply investigates the application of several machine learning models in predicting the laminar burning velocities of CH3OH/H2 blended fuels. Results denoted that Random Forest Regressor is the most persuasive model based on a thorough comparison, as indicated by the correlation coefficient of 0.99707.
Operation control and optimization of high efficiency hot primary air temperature adjustment device
Authors: Xie Fuyou , Ren Yanhui , Wang Ning , Xue Ligang , Wei Houyu 
Published: April 2023

Abstract
Aiming at the problems existing in the control logic of the current hot primary air temperature adjustment device, such as adjustment lag, poor adjustment quality, deviation of the pulverizing system operation from the normative value and insufficient energy-saving effect in the adjustment process, a standard-based calculation method was proposed. It is a logical optimization scheme that dynamically adapts to the moisture content of raw coal and the coal volume of the pulverized. It has the advantages of faster adjustment speed, high system energy saving effect, and ensures the standard operation of the coal mill.
Research on technical route and economic calculation of solar assisted carbon capture system
Authors: Ma Lin , Zhang Li , Zhang Xinyi 
Published: April 2023

Abstract
This paper takes a 600MW supercritical unit as the research object, and studies the technical route and economic situation of solar photothermal system as the heat source of reboiler of carbon capture system. Taking Monoethanolamine (MEA) as the research object to analyse its desorption energy consumption characteristics, the calculation results show that the carbon capture and regeneration energy consumption of the system is 3.90Gj/t CO2, calculated by the CO2 absorption rate of 85%. Three technical routes of solar assisted carbon capture systems are proposed, and the main thermal economic indexes of the two methods, such as unit coal consumption and thermal efficiency, using the fifth stage extraction steam as an independent heat source and cooperating with the solar photothermal system, are calculated and compared respectively. Based on this, the influence of investment cost and collector area on CO2 emission reduction cost and coal consumption is analysed. The results show that after adding the solar thermal system, the coal consumption of the unit is reduced by 2.5g/(kw) compared with the pure steam extraction heating unit and the thermal efficiency is increased by 0.9%. The CO2 emission reduction cost has a positive correlation trend with the investment cost, and the unit coal consumption has a negative correlation trend with the increase of the collector area.
Blue energy in China: exploring the prospects and development path for marine renewable energy industries
Authors: Wang Ji , Wu Wenjing , Wang Haifeng 
Published: April 2023

Abstract
Marine renewable energy has the characteristics of green and clean, wide distribution, nearby consumption, accurate prediction, and customization on demand. It can provide green energy solutions according to the needs of islands, ocean economic development, and energy consumption of offshore equipment. China has an excellent marine renewable energy resource. Facing great pressure on climate change and energy crisis, the Chinese Government has been showing a strong commitment to marine renewable energy. In this paper, we describe the resources distribution and technology status of marine renewable energy, analyse marine renewable energy strategies in China, and assessment and advices are given for each energy categories. This paper provides an overview of marine renewable energy industries, technology, policy, development trend, structure of industrial chains, challenges, opportunities in China, and provides recommendations for the development of marine renewable energy.
Urban ecological quality and statistical correlation analysis based on satellite remote sensing
Authors: Ma Mingyue , Xu Guochang , Lv Zhiping , Chen Shujun , Li Hanyu , Zhang Guangzong 
Published: April 2023

Abstract
Jiangsu Province is an area with active economic and social development. With the advancement of urbanization, ecological issues have become a hot spot in the region. Objectively and quantitatively assessing spatial-temporal environmental quality changes is crucial for environmental protection and policymaking. Remote sensing is a very effective ground-based information acquisition tool for long-term ecological analysis. Thus, this study uses remote sensing to evaluate the quality of the ecological environment in Jiangsu Province. The Remote Sensing Ecological Index (RSEI) from 1990 to 2020 is calculated on the Google Earth Engine platform. The spatial-temporal changes and spatial auto-correlation of the ecological environment quality are evaluated. The results show that from 1990 to 2020, the ecological status shows a downward-rising-flat trend. The RSEI has decreased from 0.4677(1990) to 0.4524(2005) and then increased from 0.4524(2005) to 0.4562(2020). The spatial auto-correlation analysis show that the spatial distribution of ecological quality is positively correlated. The clustering map of RSEI spatially correlated local indicators show that the hot points are mainly located in the north and middle parts of the study area. The cold points are mainly distributed in the southern Yangtze River coastal urban cluster. Such a technique is not limited by time and space, so it can be widely used in monitoring and protecting the ecological environment.
Effects of land use change on the ecosystem service value – A case study of Jiulongjiangkou, Fujian, China, from 2013 to 2021
Authors: Liu Zhong , Zhou Jinlan , Zhu Lirong , Lin Chih-Wei 
Published: April 2023

Abstract
In this study, we utilized the dynamic changes in land use and ecosystem service value to provide ecological security protection and realize the coordinated development of ecosystem service functions for the Jiulongjiangkou Wetland Reserve. We counted the land use changes and calculated the ecological service value of the Jiulongjiangkou by using eCognition 9.0, ArcMap 10.2, Fragstats 4.2, and other software based on the remote sensing image from 2013 to 2021 with five phases, which were captured by Landsat-8 satellite. The results showed that the land use type of Jiulongjiangkou City changed significantly and was affected by human activities, in which the wetland area decreased by 8.61 km2, a decrease of 8.5%. In the past ten years, the value of ecosystem service has not increased, which decreased by 1.3*108 RMB in 2021 compared with 2013. In the future, we should continue to increase the protection of forest lands and waters, maintain the stability of the ecosystem of protected areas, rationally plan the land for construction, actively develop green agriculture, and steadily enhance the value of ecosystem service.
Enhanced removal of triclosan from contaminated water by indigenous isolate Burkholderia sp. L303
Authors: Qiu Lan , Guo Xiaoyuan , Shim Hojae 
Published: April 2023

AbstractTriclosan (TCS), one of the most widely used antimicrobial agents, is frequently detected at wastewater treatment plants and environmental matrices including soil, water, sediment, and biota samples. In this study, a TCS-degrading bacterium was isolated from local activated sludge and identified asBurkholderiasp. L303. Strain L303 could degrade TCS (0.5-8 mg/L) as sole carbon source. The optimal condition was 35°C and pH 7. Thein-vitroassay with the glucose-enriched cells showed the ability of TCS degradation in real water samples, indicating the functional enzyme expressed in the absence of TCS. The bioaugmentation of strain L303 in non-sterile wastewater showed better degradation rate than that in the control groups. The community profiles showed the potential cooperative interactions between strain L303 and indigenous bacteria, thereby enhancing the TCS degradation in the real polluted water. The finding of this study could facilitate in developing appropriate bioaugmentation strategy by using live bacteria or active enzyme and in designing beneficial community interactions within native and external species for treating TCS-laden waters.
Analysis and research on the characteristics of pollutants discharged from the separate storm pump station
Authors: Yuan Wenqi 
Published: April 2023

Abstract
The separate storm pump station can reduce the overflow pollution in rainy days and reduce the impact on the water environment. However, before or after rainfall, the impact of the discharge of diversion rainwater pump station on the water environment is still prominent, which has become one of the important reasons restricting the improvement of water environment pollution. This paper investigates the diversion rainwater pump stations in Shanghai, analyzes the discharge flow and pollution law of the diversion rainwater pump stations according to the operation data, and studies the characteristics, causes and effects of discharge pollution. Therefore, to provide support for the pollutant discharge control of the diversion rainwater pump station.
Study on the adsorption characteristics of lead in soil by biochar from co-pyrolysis of rice straw and sludge
Authors: Wang Hui , Ge Shifu , Ye Lei , Zhou Cailin 
Published: April 2023

Abstract
The adsorption kinetics and short-term soil adsorption experiments were carried out for the biochar (mixed charcoal) prepared by co-pyrolysis of rice straw and sludge. The results showed that the specific surface area and total pore volume of co-pyrolysed biochar were significantly increased compared with sludge pyrolysis biochar. In the lead solution adsorption experiment, the removal rate of lead ions in the solution reached 99.34% using mixed-burning biochar produced at 600 °C for 24h, and the unit mass adsorption capacity was 64.57 mg/g. In the soil adsorption experiment, 12 g/kg of mixed charcoal was added to lead-contaminated soil, and the leaching toxicity and bioavailability of lead-contaminated soil after stabilization for 30 days decreased by 45.3% and 37.0%, respectively. The soil pH value with 12 g/kg of mixed charcoal added within 30 days fluctuated between 7.03 and 7.12, and no acid or alkaline pollution was generated. Co-pyrolysed biochar can effectively reduce the leaching toxicity and bioavailability of lead in soil. For soil with a lead pollution concentration of less than 1600 mg/kg, adding 12 to 16 g/kg of co-pyrolysed biochar produced at 600 °C can achieve a satisfactory repair effect.
Propagation of surface magnetoplasmon polaritons in a symmetric waveguide with two-dimensional electron gas
Authors: GAO Mingxiang , WANG Baojun , GUO Bin 
Published: April 2023

Abstract
The properties of surface magnetoplasmon polaritons (SMPPs) in a symmetric structure, composed of two semi-infinite regions of high-density two-dimensional electron gas (2DEG) separated by a thin film in Voigt configuration, are investigated. The normal and absorption dispersion relations for the transverse magnetic polarization are derived by correlating Maxwell’s equation and the boundary conditions. It is demonstrated that the features of SMPPs are greatly influenced by the external magnetic field, collision frequency of 2DEG, the dielectric constant, and the thickness of the thin film, suggesting that the locations and propagation lengths of SMPPs can be governed accordingly. It is shown that the symmetry of the physical geometry preserves the symmetry of the dispersion relations of SMPPs. Furthermore, it is discovered that as the external magnetic field increases, the penetration depth of SMPPs decreases, while their energy loss reduces, implying that plasmons can propagate for longer distances. Additionally, it is observed that SMPPs in the symmetric configuration have a longer lifetime than those in the asymmetric configuration.
Spectrally adapted physics-informed neural networks for solving unbounded domain problems
Authors: Xia Mingtao , Böttcher Lucas , Chou Tom 
Published: April 2023

Abstract
Solving analytically intractable partial differential equations (PDEs) that involve at least one variable defined on an unbounded domain arises in numerous physical applications. Accurately solving unbounded domain PDEs requires efficient numerical methods that can resolve the dependence of the PDE on the unbounded variable over at least several orders of magnitude. We propose a solution to such problems by combining two classes of numerical methods: (i) adaptive spectral methods and (ii) physics-informed neural networks (PINNs). The numerical approach that we develop takes advantage of the ability of PINNs to easily implement high-order numerical schemes to efficiently solve PDEs and extrapolate numerical solutions at any point in space and time. We then show how recently introduced adaptive techniques for spectral methods can be integrated into PINN-based PDE solvers to obtain numerical solutions of unbounded domain problems that cannot be efficiently approximated by standard PINNs. Through a number of examples, we demonstrate the advantages of the proposed spectrally adapted PINNs in solving PDEs and estimating model parameters from noisy observations in unbounded domains.
DeepMicroGen: a generative adversarial network-based method for longitudinal microbiome data imputation
Authors: Choi Joung Min , Ji Ming , Watson Layne T , Zhang Liqing 
Published: April 2023

Abstract

Motivation
The human microbiome, which is linked to various diseases by growing evidence, has a profound impact on human health. Since changes in the composition of the microbiome across time are associated with disease and clinical outcomes, microbiome analysis should be performed in a longitudinal study. However, due to limited sample sizes and differing numbers of timepoints for different subjects, a significant amount of data cannot be utilized, directly affecting the quality of analysis results. Deep generative models have been proposed to address this lack of data issue. Specifically, a generative adversarial network (GAN) has been successfully utilized for data augmentation to improve prediction tasks. Recent studies have also shown improved performance of GAN-based models for missing value imputation in a multivariate time series dataset compared with traditional imputation methods.

Results
This work proposes DeepMicroGen, a bidirectional recurrent neural network-based GAN model, trained on the temporal relationship between the observations, to impute the missing microbiome samples in longitudinal studies. DeepMicroGen outperforms standard baseline imputation methods, showing the lowest mean absolute error for both simulated and real datasets. Finally, the proposed model improved the predicted clinical outcome for allergies, by providing imputation for an incomplete longitudinal dataset used to train the classifier.

Availability and implementation
DeepMicroGen is publicly available at https://github.com/joungmin-choi/DeepMicroGen.