bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of investment in quality language education on green economic growth: case study of 23 Chinese provinces
Authors: Zhang Ming , Wei XueJiao , Xu Aidi 
Published: July 2023

AbstractThe spread of the threat of climate change has forced countries to try to implement the drivers of green economic growth. In this paper, we seek to explore how green growth is affected by quality language education in 23 Chinese provinces from 2010 to 2021. Employing the ARDL (Autoregressive Distributed Lag) approach and Pooled Mean Group (PMG) estimator, the findings confirmed that a 1% increase in the quality of language education improves sustainable economic growth in Chinese provinces by 0.69% and 0.01% in the short and long term, respectively. Furthermore, the development of sustainable electricity generation is the increasing factor of green prosperity in Chinese provinces. Moreover, any increase in waste generation will harshly impact the sustainable growth of Chinese provinces by 0.57% and 0.15% in the short and long term, respectively. The volume of green investment positively correlates with sustainable growth in Chinese provinces. As the primary policy implication, it is recommended that the Chinese government expand the education for sustainable development (ESD) program, develop social literacy on participation in sustainable power generation, and improve the SMEs' education for green job creation and sustainable investment.
Between piece molds and lost wax: the casting of a diatrete ornamentation in early China rethought
Authors: Peng Peng 
Published: July 2023

AbstractFor a long time, research on the pre-Han (before 202 BCE) Chinese use of the lost-wax process was targeted at demonstrating that it was of no use at all. That position was severely shaken when thezun-panset of Zeng Hou Yi (“Marquis Yi of Zeng,” d. 433 BCE) was unearthed at Hubei Suizhou in 1978, along with subsequently excavated finds or rediscovered artifacts carrying similarly interpenetrating openwork. Since the early 2000s, however, there has been a persistent revival of a research orientation against the use of the lost-wax process in Bronze Age China. After surging first in Chinese academia, the new tide took some time to arrive in the West. A response to Donna Strahan’s prestigious lecture, “Debating the Use of Lost-wax Casting in Ancient China,” this article presents my thinking about lost wax versus piece molds in early Chinese casting practices. Strahan’s studied “diatrete” ornamentation in the Metropolitan Museum of Art, to me, can be securely identified as lost-wax cast thanks to some telltale traces. Through this critical investigation, I invite my fellow art historians, archaeologists, and historians of metal technology to emerge from the “doubting of lost wax” era to tackle new challenges in early Chinese archaeo-metallurgy.
An in-situ integrated material distinction sensor based on density and heat capacity
Authors: Wu Sicheng , Yang Jie , Xing Jian , Yu Jiajie , Zhang Ke 
Published: July 2023

Abstract
Material distinction via artificial intelligence (AI) has been studied extensively and demonstrates strong capacity. However, a high-performance sensor and accurate theoretical model remain necessary to assist AI in precise identification. Here, we developed an in-situ integrated material distinction sensor, which depends on the density (ρ) and heat capacity (C) of measured matter. The device is fabricated using an outer nickel (Ni) thermistor and an inner laser-induced graphene (LIG) heater on a polyimide substrate. When a sample is placed on the surface of the sensor and a certain voltage is applied to the LIG heater, the Ni thermistor will perceive the temperature changing trends, which can reflect the heat absorption and conduction ability of the placed material. Notably, finite element analysis was conducted and the simulation results are perfectly combined with the experimental results, which implied that the ρ and C of the sample together determined the temperature distribution, instead of the thermal conductivity (κ). By establishing a heat absorption model, each kind of material can be identified with a feature value. A novel sensor and corresponding physical model are provided to perceive the material properties, improving the range and accuracy of material identification based on a contact-mode sensing mechanism.
An effective fusion positioning methodology for land vehicles in GPS-denied environments using low-cost sensors
Authors: Zheng Zhiyong , Li Xu , Kong Dong , Hu Jinchao , Hu Yue 
Published: July 2023

Abstract
It is still a main challenge to achieve accurate and reliable vehicle positioning in Global Position System (GPS)-denied environments using low-cost sensors. Although existing methods have obtained a certain performance improvement, there is still room for further enhancement in positioning accuracy due to the lack of effective observation information during GPS outages. To address this challenge, this paper proposes an effective fusion positioning methodology based on enhanced observation information. Firstly, a data denoising algorithm based on convolutional denoising autoencoder is developed to effectively filter the noises in inertial sensors, so as to provide more clean data for subsequent modeling. Then, a differential fusion strategy is designed to selectively fuse multiple observation information from monocular camera, low-cost GPS and wheel speed sensor with extended Kalman filter, which can further improve the positioning accuracy. Finally, a long short-term memory-based error prediction model is constructed to learn the mapping relationship between the result of data denoising and differential fusion. In the case of GPS outages, the error model provides accurate corrections to compensate for position errors of inertial navigation system. The performance of the proposed methodology was evaluated on real-world data collected in complex urban environments. Experimental results indicate that the proposed positioning methodology can obtain significant accuracy enhancement.
A reinforcement neural architecture search convolutional neural network for rolling bearing fault diagnosis
Authors: Li Lintao , Jiang Hongkai , Wang Ruixin , Yang Qiao 
Published: July 2023

Abstract
The complexity of machinery makes accurate identification of rolling bearing fault signals difficult. Convolutional neural networks (CNNs) have made some progress, but they rely on the expertise of the network designer and the iterative process of optimizing numerous parameters. Therefore, there is an urgent need to develop a method that reduces the threshold for designing CNNs for a given task. In this article, we propose a reinforcement neural architecture search CNN to address this problem. Firstly, we design a neural architecture search algorithm that can generate different types of sub-networks specifically for fault diagnosis tasks. Secondly, we execute a reinforcement learning-based search strategy to discover promising sub-networks. Furthermore, we enhance the performance of the sub-network by improving the optimizer and training parameters. We conduct extensive experiments using two different types of datasets and verify that the proposed method’s fault classification capability is superior to existing methods.
A 50 pico-g resolution integrated test facility for high-precision inertial sensors
Authors: Mei Bin , Ma Cheng , Bai Yanzheng , Hu Ming , Liu Li , Lv Menghao , Ma Yun , Qu Shaobo , Wu Shuchao , Yu Jianbo , Zhou Zebing 
Published: July 2023

Abstract
High-precision inertial sensors are the key instruments for many applications. However, their performance is difficult to test on the ground due to the effect of seismic noise. To evaluate the complete performance of inertial sensors, the main test items include noise floor test, scale factor calibration, resolution test and so on. The accelerometers used in inertial navigation and precision measurement fields usually require direct resolution test. Depending on the application, the resolution of high-precision accelerometers can reach up to the pico-g (pg) level or even higher. However, the resolution test ability of conventional test systems is limited by the seismic noise and the precision of the input signal, which becomes the main obstacle for the development of sub-nano-g to pg level accelerometers. In this paper, a simultaneous two-dimensional integrated performance test facility is developed using an active vibration isolation bench and precision gravitational input, allowing the performance test of high-precision inertial sensors and direct evaluation of resolution at the 50 pg level.
Nanoflower-like FeVNi3S2–x
as efficient electrocatalyst for alkaline oxygen evolution reaction
Authors: Makabu Cynthia Mulanga , Tian Shengnan , Kalau Marc Kalamb , Gong Zizhen , Niu Weixing , Wu Changcheng , Li Jingde 
Published: July 2023

Abstract
The development of low cost efficient catalysts for oxygen evolution reaction (OER) is still a obstacle to realize the commercialization of electrocatalytic water splitting. Herein, interface engineering and heteroatom doping is adopted to synthesize iron and vanadium doped nickel sulfide on nickel foam via hydrothermal method followed by hydrogen treatment to create sulfur defects. The optimized nanoflower-like FeVNi3S2–x
/NF is an efficient OER electrocatalyst that outperforms many of the reported transition metals catalysts. Benefiting from abundant sulfur defects and the synergistic effect of heteroatom doping, FeVNi3S2–x
/NF exhibits an ultralow overpotential of 230 mV to reach a current density of 100 mA cm−2, a rapid reaction kinetics with a small Tafel slope of 46.6 mV dec−1, and a stable long-term durability in 1 M KOH. Experimental results and characterizations confirm that sulfur vacancies together with the synergistic effect from multiple heteroatom doping can effectively regulate the electronic structure, resulting in increased electrical conductivity and electrochemically active surface area, thus enhancing OER performance. Furthermore, in situ Raman spectroscopy reveals that, the reconstitution amorphous nickel oxyhydroxide (NiOOH) on the catalyst surface is responsible for catalyzing the OER reaction. This work represents a promising methodology to synthesize low-cost and highly active OER electrocatalysts.
Nanowire biosensors with olfactory proteins: towards a genuine electronic nose with single molecule sensitivity and high selectivity
Authors: Noh Sangjun , Tombola Francesco , Burke Peter 
Published: July 2023

Abstract
We describe the concept and roadmap of an engineered electronic nose with specificity towards analytes that differ by as little as one carbon atom, and sensitivity of being able to electrically register a single molecule of analyte. The analyte could be anything that natural noses can detect, e.g. trinitrotoluene (TNT), cocaine, aromatics, volatile organic compounds etc. The strategy envisioned is to genetically engineer a fused olfactory odorant receptor (odorant receptor (OR), a membrane-bound G-protein coupled receptor (GPCR) with high selectivity) to an ion channel protein, which opens in response to binding of the ligand to the OR. The lipid bilayer supporting the fused sensing protein would be intimately attached to a nanowire or nanotube network (either via a covalent tether or a non-covalent physisorption process), which would electrically detect the opening of the ion channel, and hence the binding of a single ligand to a single OR protein domain. Three man-made technological advances: (1) fused GPCR to ion channel protein, (2) nanowire sensing of single ion channel activity, and (3) lipid bilayer to nanotube/nanowire tethering chemistry and on natural technology (sensitivity and selectivity of OR domains to specific analytes) each have been demonstrated and/or studied independently. The combination of these three technological advances and the result of millions of years of evolution of OR proteins would enable the goal of single molecule sensing with specificity towards analytes that differ by as little as one carbon atom. This is both a review of the past and a vision of the future.
A review on advanced band-structure engineering with dynamic control for nonvolatile memory based 2D transistors
Authors: Zhang Chi , Ning Jing , Wang Dong , Zhang Jincheng , Hao Yue 
Published: July 2023

Abstract
With advancements in information technology, an enormous amount of data is being generated that must be quickly accessible. However, conventional Si memory cells are approaching their physical limits and will be unable to meet the requirements of intense applications in the future. Notably, 2D atomically thin materials have demonstrated multiple novel physical and chemical properties that can be used to investigate next-generation electronic devices and breakthrough physical limits to continue Moore’s law. Band structure is an important semiconductor parameter that determines their electrical and optical properties. In particular, 2D materials have highly tunable bandgaps and Fermi levels that can be achieved through band structure engineering methods such as heterostructure, substrate engineering, chemical doping, intercalation, and electrostatic doping. In particular, dynamic control of band structure engineering can be used in recent advancements in 2D devices to realize nonvolatile storage performance. This study examines recent advancements in 2D memory devices that utilize band structure engineering. The operational mechanisms and memory characteristics are described for each band structure engineering method. Band structure engineering provides a platform for developing new structures and realizing superior performance with respect to nonvolatile memory.
Magnetic behavior of Fe3O4@C nanofibers by a facile co-axial electrospinning method
Authors: Sethy Pujashree Priyadarshini , Sundaray Bibekananda 
Published: July 2023

Abstract
Co-axially electrospun, magnetic Fe3O4@carbon (Fe3O4@C) nanofibers comprising Fe3O4 particles in the core and carbon in the shell have been fabricated and their performances as magnetic material have been studied. The electrospun Fe3O4@C nanofibers have been characterized with x-ray diffraction, field emission scanning electron microscopy, high-resolution transmission electron microscope, x-ray photoelectron spectroscope (XPS), and superconducting quantum interference device magnetometer. The structural and microstructural analysis has given a brief idea about the pure Fe3O4 and C phase formation and also the existence of smooth and continuous morphology of Fe3O4@C nanofibers. It has been shown that there exist two different oxidation states of Fe in the XPS spectrum. The magnetization hysteresis loop has been observed at low temperatures (5 K, 100 K) as well as at room temperature (300 K) which gives different magnetic parameters. Temperature dependent magnetic measurements (from 5 to 300 K) suggest the existence of Verwey transition for lower percentage of iron oxide content.
Scalar particle creation in a quantum gravity perspective
Authors: Bilim A B , Aydogdu O , Salti M 
Published: July 2023

Abstract
In gravity’s rainbow perspective (GRP), we intend to analyze the particle production coming from electromagnetic and gravitational fields of the spin-0 (scalar) particles. In accordance with this purpose, a constant external electric field is taken into account together with a rainbow metric with non-isotropic expansion. We obtain the number density of the created Klein–Gordon particles in terms of particle mass, particle charge, external electric field parameter, rainbow functions and particle momentum by using the Bogoliubov transformation method. We display that the number density of the created scalar particles becomes thermal both in the absence of the external constant electric field and in the massless case. We also provide a graphical analysis to scrutinize the particle creation process in the GRP. In this context, it has been observed that rainbow functions drastically alter the number density of the created scalar particles.
Unstable confocal resonator with external flat semi-transparent mirror for additional feedback
Authors: Kislov V I , Ofitserov E N 
Published: July 2023

Abstract
Main characteristics (mode structure of power loss, divergence of resonant radiation) of a three-mirror laser cavity with additional feedback are theoretically studied in the Fresnel approximation on the basis of the Fox-Lee integral equation. The resonator consists of two spherical mirrors, which form an unstable confocal resonator, and a flat semi-transparent mirror, which is installed outside the reference unstable resonator perpendicular to its optical axis. The flat coupling mirror returns part of the radiation back inside the resonator. The level of additional feedback is determined by the reflection coefficient of the flat mirror and the position of the mirror along the optical axis of the resonator. Variation of these parameters makes it possible to control the transparency of the three-mirror resonator over a wide range, up to values close to zero. Results of this paper can be used in the development of high-power lasers with wide aperture (Fresnel numbers of ∼100) on the basis of low-gain active media.
Proposal for the complete high-dimensional Greenberger–Horne–Zeilinger state measurement
Authors: Zeng Zhi 
Published: July 2023

Abstract
A theoretical proposal for the complete analysis of high-dimensional Greenberger–Horne–Zeilinger (GHZ) state is presented in this Letter. We first demonstrate the approach for the complete three-photon GHZ state measurement in three dimensions, and then generalize it to the situation of N-photon system in d dimensions. In our approach, the photonic hyperentanglement and quantum Fourier transform are both utilized. The presented proposal will be useful for the high-dimensional multi-photon quantum computation and quantum communication.
Modified linear regression for predicting ambient particulate pollutants (PM10) during High Particulate Event
Authors: Mohd Jafri I A , Noor N Mohamed , Rahim N A A A , Baidrulhisham S E , Ramli N , Ul-Saufie A Z , Deak G 
Published: July 2023

Abstract
Particulate Matter (PM10) is one of the most significant contributors towards haze or high particulate event (HPE) that occurs in Malaysia. HPE can severely affect human health, environment and economic so it is important to create a reliable prediction model in predicting future PM10 concentration especially during HPE. Therefore, the aim of this study is to investigate the performance of modified linear regression models in predicting the next-day Particulate Matter (PM10+24) concentration at two areas in the peninsular Malaysia namely, Bukit Rambai and Nilai. Hourly air quality dataset during historic HPE in 1997, 2005, 2013 and 2015 were used for analysis. Pearson correlation was used to select the input of the PM10 prediction model where only parameters with moderate (0.6 > r > 0.3) and strong (r > 0.6) correlation with PM10 concentration were selected as independent variables input in creating the multiple linear regression (MLR) model. The performance of modified linear regression model was evaluated by using several performance indicator which is Prediction Accuracy (PA), Index of Agreement (d
2), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results show that the modified MLR (parameter with r > 0.6 included as input) gave the best prediction model for the next-day PM10 concentration in both Bukit Rambai and Nilai.
Analysis of the results from the applied technologies for carbon dioxide sampling in aquatic ecosystems
Authors: Enache N , Laslo L , Matei M , Boboc M , Cătuneanu I , Deák G 
Published: July 2023

Abstract
Globally, streams and rivers contain important stocks of carbon dioxide and release 1.8 ± 0.25 Pg of carbon each year. The literature review demonstrates that wetlands carbon sequestration capacity and effluxes are not homogenous. Considering those differences, it is crucial to comprehend how these effluxes vary depending on the characteristics of open water plots and areas with vegetation along river basins and how different weather conditions affect the variation of CO2 efflux. The purpose of this study was to analyse the various plots along Dambovita river’s watercourse in order to better understand the fluctuation of the CO2 efflux at the water-atmosphere interface and its dependent parameters. Here, we applied two complimentary methods with close chambers: dynamic by respiration chamber and static by injection kit in order to describe CO2 efflux data sets. Additionally, we measured simultaneously the weather parameters (air temperature, precipitation, wind speed), but also the water quality parameters. The CO2 efflux results are a starting point for improving the emission factor for rivers in temperate climate zone, which is 1.46 for default values at the country level. Also, the analysis performed contributes to a better understanding of how spatial and temporal variability of river characteristics impacts CO2 effluxes.
Investigation of Indoor Air Quality by Incorporating Sewage Sludge Waste into Fired Clay Brick
Authors: Salim Nurul Salhana Abdul , Kadir Aeslina Abdul , Noor Norazian Mohamed 
Published: July 2023

Abstract
Generally, the production of sewage sludge waste has increased due to rapid growth of the population. Due to that, the disposal method has become crucial issues nowadays. Therefore, this research focuses on the investigation of indoor air quality of fired clay brick incorporating with sewage sludge. The bricks were incorporated with 0% and 5% of two type of sewage sludge and fired at 1050°C with heating rates 1°C/min. The experiment of Indoor Air Quality was obtained by measuring gases emissions of total volatile organic compound (TVOC), carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), formaldehyde (HCHO) and particulate matter (PM10) and were compared with Industry Code of Practice on Indoor Air Quality requirement standard. From the result shows that by incorporation of 5% of sewage sludge into fired clay brick complied with the standard requirement for building material usage with no negative effect to the environment. As the conclusions, the use of sewage sludge as clay replacement reduces the waste disposal in landfills and produce the low-cost building materials.
Evaluation of the Ecological Risk and the Development of Antimicrobial Resistance due to the Presence of the Macrolide Antibiotics Azithromycin and Clarithromycin in Romanian Aquatic Environment
Authors: Ilie Mihaela , Marinescu Florica , Ghita Gina , Savin Ioana , Tudor Georgeta , Luminaroiu Lucian , Gheorghe Petrache-Ionut , Dumitrescu Georgiana , Noor Norazian Mohamed 
Published: July 2023

Abstract
The presence of antibiotics in the aquatic environment can result in the emergence of antibiotic-resistant pathogens. In this paper, our aim was to identify, quantify and distribute macrolide antibiotics in the aquatic environment in the river basins of Arges-Vedea, Buzau-Ialomita and Dobrogea-Litoral and of the Danube River. In the Arges-Vedea river basin area, clarithromycin was detected most frequently, i.e. 58.62%, in the Buzau-Ialomita river basin area with a frequency of 92.31% azithromycin was detected, and in the Dobrogea - Litoral river basin area clarithromycin was detected with a frequency of 35.48%. The highest concentration of azithromycin, 559 ng/L and of clarithromycin, 502 ng/L was recorded in the Buzau-Ialomita river basin. The ecotoxicological RQecotox risk was also estimated, as well as the risk of developing antibiotic resistance of RQAMR pathogens, by the ratio of Measured Environmental Concentration (MEC) and Predicted No Effect Concentrations (PNEC). The study also aimed to investigate the prevalence of antibiotic resistance in potentially pathogenic bacteria isolated from aquatic environments. Thus, for β-lactam antibiotics, E. coli strains isolated from the Danube River exhibited a very high level of resistance to ampicillin (51%) and high level to azithromycin (43%), cefazolin (38%), amoxicillin+clavulanic acid (36%) and cefoxitin (26%). Low and respectively, low level resistance was noticed for aztreonam (6%) and imipenem (4%).