bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compensation of environmental parameters for optical detection of chemical oxygen demand
Authors: Yu Jianmin , Wu Jin , Yu Shengnan , Chen Shuyan , Wang Feng , Zhang Xiaojun 
Published: November 2022

Abstract
Chemical oxygen demand (COD) reflects the degree of water damage by organic pollutants, and is an important indicator for water environment protection and marine hydrological monitoring, so it is very important to accurately measure COD. However, changes in ambient temperature and atmospheric noise cause huge deviations in the precise measurement of COD by optical-based water quality detectors. The purpose of this research is to realize the accurate measurement of COD of the optical water quality detector by compensating the environmental parameters of the water quality detector. The compensation model established in this paper is a particle swarm optimization (PSO) back-propagation neural network (BPNN), which can compensate for temperature and filter out atmospheric noise, named back-propagation neural network of particle swarm optimization of filter out atmospheric noise (FAN-PSO-BPNN). FAN-PSO-BPNN reduced the maximum relative error by 92.51%, root mean square error by 91.64%, coefficient of variation by 91.74%, and the distance between the maximum and minimum prediction errors by 92.94% compared with BPNN in filtering out atmospheric noise interference and temperature compensation. The optimization scheme proposed in this paper for BPNN is crucial and effective, and the FAN-PSO-BPNN compensation model improves the anti-interference ability of the water quality detector, guarantees the accurate measurement of COD in seawater, and helps the water quality detector to monitor in seawater for a long time.
A transparent kaolinite-loaded zinc oxide nanocomposite sunscreen with UV shielding rate over 99% based on bidirectional dispersion
Authors: Wang Ling , Cui Xiaomei , Dong Qiuye , Liang Weicong , Jin Hejie 
Published: November 2022

Abstract
Nano-sized TiO2 and ZnO are the most efficient and widely used inorganic sunscreen, but they still have some drawbacks including agglomeration, delamination, clogging pores and high cost. In this study, a kaolinite-loaded zinc oxide nanocomposite sunscreen was prepared and the key technical problems in application of inorganic nano-sized sunscreens was solved. The synthesized kaolinite-loaded zinc oxide nanocomposite was characterized by XRD, SEM, EDS, XRF and UV–vis spectrophotometry. The SEM image of the nanocomposite suggests that agglomeration of nano-ZnO is avoided by bidirectional dispersion of superfine kaolinite powder and nano-ZnO. Nano-effect and UV shielding rate are enhanced and the nanocomposite sunscreen possesses UV shielding efficiency of 1 + 1 > 2. The UV shielding rate of the nanocomposite sunscreen is greater than 99%, only 10% addition of it endows ordinary skin care products with excellent UV protective efficacy. Moreover, the content of nano-ZnO is reduced by half through introduction of kaolinite, the cost of the sunscreen is lowered, delamination and pore clogging are avoided. This work provides a technical approach for producing stronger, safer and more economical popularized anti-UV skincare products.
Graphene delamination from chemical vapor deposited turbostratic multilayer graphene for TEM analysis
Authors: Hayashi Kenjiro , Fushimi Naoki , Kataoka Masako , Kondo Daiyu , Sato Shintaro 
Published: November 2022

Abstract
Turbostratic multilayer graphene (MLG) is of great interest due to its unique electronic properties resulting from a linear band dispersion at the K point, which is similar to that of single-layer graphene. The band structure is derived from the stacking structure of turbostratic MLG where graphene layers have random in-plane rotations with respect to each other. Although wafer-scale growth of turbostratic MLG has been demonstrated, the crystallinity of individual graphene layers is still challenging to investigate. In this study, we present a new approach to reveal the grain structure of turbostratic MLG by transmission electron microscopy (TEM) observation. Mechanical delamination is demonstrated for the chemical vapor deposited MLG to peel off the topmost graphene layers by using a polydimethylsiloxane sheet. Micrometer-scale patterning of the MLG prior to the delamination is found to be effective to obtain graphene films with the designed shape and arrangement. Furthermore, the delaminated graphene films are successfully transferred onto a TEM grid, enabling us to estimate the grain size of the turbostratic MLG. This method is potentially applicable for not only preparing samples but also fabricating vertically stacked heterostructure devices using 2D materials.
Recovery of gold from e-waste via food waste byproducts
Authors: Cecchi Teresa , Gao Zhaojing , Clement Christophe , Camus Anthony , Karim Andrew , Girard Olivier , Santato Clara 
Published: November 2022

Abstract
Global materials’ and energy constraints and environmental issues call for a holistic approach to waste upcycling. We propose a chemically rational, cost-effective and environmentally friendly recovery of non-leaching gold from e-waste using aqueous chemistry with hydrogen peroxide, an environmentally benign oxidant, and lactic acid, a food chain byproduct. The oxidation of the base metals enables the release of gold in its metallic state in the form of flakes subsequently separated via filtration. Our main byproduct is a precursor of Cu2O, a relevant metal oxide for solar energy conversion applications. The recovered gold was characterized by scanning electron microscopy, energy dispersive spectroscopy and x-ray photoelectron spectroscopy to gain insight into the morphology of the flakes and their chemical composition. Furthermore, recovered gold was used to successfully fabricate the source and drain electrodes in organic field-effect transistors.
Travelling wave solutions of the cubic nonlocal Fisher-KPP equation: I. General theory and the near local limit
Authors: Billingham J , Needham D J 
Published: November 2022

Abstract
We study non-negative travelling wave solutions, u ≡ U(x − ct) with constant wavespeed c > 0, of the cubic nonlocal Fisher-KPP equation in one spatial dimension, namely,

∂
u

∂
t

=

∂

2

u

∂

x

2

+

u

2

1
−

1

λ

∫

−
∞

∞

ϕ

y
−
x

λ

u

y
,
t

d
y

,

for

(

x
,
t

)

∈
R
×

R

+

, where u(x, t) is the population density. Here ϕ(y) is a prescribed, piecewise continuous, symmetric, nonnegative and nontrivial, integrable kernel, which is nonincreasing for y > 0, has a finite derivative as y → 0+ and is normalised so that

∫

−
∞

∞

ϕ

(

y

)

d
y
=
1

. The parameter λ is the ratio of the lengthscale of the kernel to the diffusion lengthscale. The quadratic version of the equation, with reaction term u(1 − ϕ*u), has a unique travelling wave solution (up to translation) for all c ⩾ c
min = 2. This minimum wavespeed is determined locally in the region where u ≪ 1, (Berestycki et al 2009 Nonlinearity
22 2813–44). For the cubic equation, we find that a minimum wavespeed also exists, but that the numerical value of the minimum wavespeed is determined globally, just as it is for the local version of the equation, (Billingham and Needham 1991 Dynam. Stabil. Syst.
6 33–49). We also consider the asymptotic solution in the limit of a spatially-localised kernel, λ ≪ 1, for which the travelling wave solutions are close to those of the cubic Fisher-KPP equation, u

t
= u

xx
+ u
2(1 − u). We find that when ϕ = o(y
−3) as y → ∞, the minimum wavespeed is

1

2

+
O

(

λ

4

)

, but that when ϕ = O(y
−n
) with 1 < n ⩽ 3, the minimum wavespeed is

1

2

+
O

(

λ

2

(

n
−
1

)

)

. In each case we determine the correction terms. We also compare these asymptotic solutions to numerical solutions and find excellent agreement for some specific choices of kernel.
Multi-modal fusion model for predicting adverse cardiovascular outcome post percutaneous coronary intervention
Authors: Bhattacharya Amartya , Sadasivuni Sudarsan , Chao Chieh-Ju , Agasthi Pradyumna , Ayoub Chadi , Holmes David R , Arsanjani Reza , Sanyal Arindam , Banerjee Imon 
Published: November 2022

Abstract

Background. Clinical medicine relies heavily on the synthesis of information and data from multiple sources. However, often simple feature concatenation is used as a strategy for developing a multimodal machine learning model in the cardiovascular domain, and thus the models are often limited by pre-selected features and moderate accuracy. Method. We proposed a two-branched joint fusion model for fusing the 12-lead electrocardiogram (ECG) signal data with clinical variables from the electronic medical record (EMR) in an end-to-end deep learning architecture. The model follows the joint fusion scheme and learns complementary information from ECG and EMR. Retrospective data from the Mayo Clinic Health Systems across four sites for patients that underwent percutaneous coronary intervention (PCI) were obtained. Model performance was assessed by area under the receiver-operating characteristics (AUROC) and Delong’s test. Results. The final cohort included 17,356 unique patients with a mean age of 67.2 ± 12.6 year (mean ± std) and 9,163 (52.7%) were male. The joint fusion model outperformed the ECG time-domain model with statistical margin. The model with clinical data obtained the highest AUROC for all-cause mortality (0.91 at 6 months) but the joint fusion model outperformed for cardiovascular outcomes - heart failure hospitalization and ischemic stroke with a significant margin (Delong’s p < 0.05). Conclusion. To the best of our knowledge, this is the first study that developed a deep learning model with joint fusion architecture for the prediction of post-PCI prognosis and outperformed machine learning models developed using traditional single-source features (clinical variables or ECG features). Adding ECG data with clinical variables did not improve prediction of all-cause mortality as may be expected, but the improved performance of related cardiac outcomes shows that the fusion of ECG generates additional value.
Superior dark-state cooling via nonreciprocal couplings in trapped atoms
Authors: Wang Chun-Che , Wang Yi-Cheng , Wang Chung-Hsien , Chen Chi-Chih , Jen H H 
Published: November 2022

Abstract
Cooling the trapped atoms toward their motional ground states is key to applications of quantum simulation and quantum computation. By utilizing nonreciprocal couplings between two atoms, we present an intriguing dark-state cooling scheme in Λ-type three-level structure, which is shown superior than the conventional electromagnetically-induced-transparency cooling in a single atom. The effective nonreciprocal couplings can be facilitated either by an atom–waveguide interface or a free-space photonic quantum link. By tailoring system parameters allowed in dark-state cooling, we identify the parameter regions of better cooling performance with an enhanced cooling rate. We further demonstrate a mapping to the dark-state sideband cooling under asymmetric laser driving fields, which shows a distinct heat transfer and promises an outperforming dark-state sideband cooling assisted by collective spin–exchange interactions.
Symmetries and symmetry reductions of the combined KP3 and KP4 equation
Authors: Wang Fa-ren , Lou S Y 
Published: November 2022

Abstract
To find symmetries, symmetry groups and group invariant solutions are fundamental and significant in nonlinear physics. In this paper, the finite point symmetry group of the combined KP3 and KP4 (CKP34) equation is found by means of a direct method. The related point symmetries can be obtained simply by taking the infinitesimal form of the finite point symmetry group. The point symmetries of the CKP34 equation constitute an infinite dimensional Kac-Moody–Virasoro algebra. The point symmetry invariant solutions of the CKP34 equation are obtained via the standard classical Lie point symmetry method.
Constructing unextendible product bases from multiqubit ones
Authors: Zhang Taiyu , Chen Lin 
Published: November 2022

Abstract
The construction of multipartite unextendible product bases (UPBs) is a basic problem in quantum information. We respectively construct two families of 2 × 2 × 4 and 2 × 2 × 2 × 4 UPBs of size eight by using the existing four-qubit and five-qubit UPBs. As an application, we construct novel families of multipartite positive-partial-transpose entangled states, as well as their entanglement properties in terms of the geometric measure of entanglement.
Cross-sections of the 238U (n, γ) 239U reaction in the 3.0–7.0 MeV energy region measured by relative activation method*
Authors: Wen Chun , Han Zheng , Luo Xiao-Bing 
Published: November 2022

Abstract
The reaction cross-sections of 238U (n, γ)239U have been experimentally determined at neutron energies of 6.117 ± 0.119 MeV, 4.626 ± 0.086 MeV, and 3.622 ± 0.348 MeV employing the relative activation approach along with the off-line γ-ray spectroscopy method. The D (d, n)3He reaction was utilized to obtain monoenergetic neutrons of the required energy, and the 197Au (n, γ)198Au reaction cross-sections were adopted as the referential standard to ascertain the neutron capture cross-sections of 238U. Furthermore, the effects of low-energy scattered neutrons, neutron fluence fluctuations, counting of geometric corrections when measuring γ-rays, and neutron and γ-ray self-absorption caused by the sample thickness have been considered and revised in the present work. For a comparison with experimental results, the cross-sections of the 238U (n, γ)239U reaction were calculated theoretically with the original parametric TALYS-1.9 program. The experimental measurements were in contrast to previous experimental results and the evaluation data available for ROSFOND-2010, CENDL-3.2 and ENDF/B-VIII.0.
Rapid Deformation Calculation for Large Reflector Antennas: A Surrogate Model Method
Authors: Zhang Zi-Han , Ye Qian , Fu Li , Wang Jin-Qing , Guo-Xiang Meng , Shen Zhi-Qiang 
Published: November 2022

Abstract
The surface accuracy of the large-aperture reflector antenna has a significant influence on the observation efficiency. Recent researchers have focused on using the finite element (FE) simulation to study the effect of gravity and heat on the deformation distribution of the main reflector. However, the temperature distribution of the antenna is challenging to obtain, and it takes a long time for the FE simulation to carry out FE modeling and post-processing. To address these limitations, this study presents a surrogate model based on Extreme Gradient Boosting (XGBoost) and deep Convolutional Neural Network (CNN) to get the deformation distribution of the main reflector quickly. In the design of the surrogate model, using the XGBoost algorithm and sparse sampling to solve the difficulty of obtaining the entire temperature distribution is first proposed, and then a deep CNN is developed for estimating deformation. Based on the effect of dynamic loads on the antenna structure, a diverse data set is generated to train and test the surrogate model. The results show that the surrogate model reduces the calculating time dramatically and can obtain the indistinguishable deformation compared to the FE simulation. This technique provides a valuable tool for temperature and deformation calculation of large-aperture antennas.
Comparison of helium ion irradiation resistance between nanocrystalline and coarse grained 304 austenitic stainless steel
Authors: Zhang Weiping , Xiong Yi , Wu Jiawei , Cheng Wenrui , Du Congcong , Jin Shuoxue , Sun Baoru , Shen Tongde 
Published: November 2022

Abstract
Improving the radiation resistance of structural materials in the presence of helium is significant for the development of advanced nuclear power systems. Nanostructured materials reduce the grain size and significantly increase the grain boundary density. Hence, it is considered to be an effective method to improve the radiation resistance of materials. In this work, we studied the radiation resistance of nanocrystalline (NC) and coarse grained (CG) 304 austenitic stainless steel (304-SS) by helium ion irradiations. The mean grain sizes of NC and CG 304-SS are ∼45 nm and ∼30 μm, respectively. The results of positron annihilation Doppler broadening spectroscopy and transmission electron microscopy indicate that NC 304-SS not only has better swelling resistance than CG 304-SS, but also has better helium effect resistance. And the swelling of NC 304-SS is reduced by a factor of ∼5.7 compared with CG 304-SS under the irradiation of 170 keV He+ to 2 × 1020 ions m−2 at 723 K. The mechanisms for the excellent swelling resistance of NC 304-SS are discussed.
Evaluation of ‘surgery-friendly’ bone scaffold characteristics: 3D printed ductile BG/PCL scaffold with high inorganic content to repair critical bone defects
Authors: Huang Pengren , Yang Peng , Liu Keming , Tao Wei , Tao Jun , Ai Fanrong 
Published: November 2022

Abstract
The repair of irregular and complex critical bone defects remains a challenge in clinical practice. The application of 3D-printed bioceramics particle/polymer composite scaffolds in bone tissue engineering has been widely studied. At present, the inorganic particle content of the composite scaffolds is generally low, resulting in poor osteogenic activity. However, scaffold with high inorganic content are highly brittle, difficult to operate during surgery, and cannot be in close contact with surrounding bones. Therefore, it is of great significance to design a ‘surgery-friendly’ scaffold with high bioceramic content and good ductility. In this study, we used the solvent method to add high concentration (wt% 70%) bioglass (BG) into polycaprolactone (PCL), and polyethylene glycol was used as plasticizer to prepare 70% BG/PCL composite scaffolds with high ductility using 3D printing technology. In vitro experiments showed that the scaffold had good mechanical properties: easy extension, easy folding and strong compressive resistance. It also showed good performance in biocompatibility and osteogenic activity. It was further observed that compared with pure BG or PCL implantation, the scaffold with higher BG content could have more new bone tissue appeared after 12 weeks. All these results indicate that 3D-printed 70% BG/PCL scaffolds have great potential for personalized repair of bone defects.
Changes in photovoltaic potential over China in a warmer future
Authors: Zhang Jintao , You Qinglong , Ullah Safi 
Published: November 2022

Abstract
Solar photovoltaic (PV) technology offers a promising path for addressing energy demand and mitigating climate change. However, climatic conditions relevant to the productivity of solar power may be changed in a warmer future. Here, we quantify the impact of climate change on PV potential over China based on high-resolution climate projections within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). Our results indicate that the annual mean PV power potential (PV
POT) over China would decrease by several percent relative to the reference period (1986–2005) under a warmer climate, with the most pronounced decrease over the Tibetan Plateau, which is currently the most solar-rich region in China. However, beyond changes in the mean climate state, we demonstrate a substantial increase in events of extreme low PV power outputs (i.e. those falling below the 10th percentile of the probability distribution of the daily PV
POT anomalies). For instance, the frequency of extreme low PV events is projected to reach nearly three times the reference period level over the Tibetan Plateau under the scenario of 3 °C global warming (similar to late-century warming projected based on current mitigation policies). Future changes in PV
POT are dominated by changes in surface solar irradiance, while the warming condition further exacerbates the decrease in PV
POT. Our results highlight that both the mean and extreme conditions of solar inputs should be considered simultaneously when assessing the impacts of climate change on PV power outputs.
Has China’s pilot emission trading system promoted technological progress in industrial subsectors?
Authors: Zhang Haoran , Liu Yu , Choi Yongrok , Yang Lingyu , Li Xinbei 
Published: November 2022

Abstract
Under the ‘dual carbon’ goal, the key to environmental-friendly economic development is to increase total factor productivity (TFP) in a greener way. However, as a key market-based emission reduction mechanism, the exploration related to whether the emission trading system (ETS) promotes green TFP (GTFP) is not deep enough, especially for secondary decomposition of this technical index and for specific industrial subsectors. In this study, combining biennial Malmquist-Luenberger productivity index with multi-period difference in differences model, we assess the technological progress of China’s pilot ETS dynamically. The results show that the pilot ETS promoted GTFP significantly in the industrial subsectors, by 8.5%. The technology change index increased by 17.5%, which is the key action path to increasing GTFP. Furtherly, the mechanism test confirms that the policy works mainly through innovation channel. This study implied that the governance toward carbon-zero economies could be accelerated much more effectively by technological innovation of green.
Marked rebound of agricultural fire emissions in Asia after the outbreak of COVID-19
Authors: Liu Mingxu , Yao Huan , Matsui Hitoshi 
Published: November 2022

Abstract
East and South Asia are major hotspots of crop straw burning worldwide, with profound impacts on air quality and climate change. The Northeast China Plain (NECP) and Punjab, India, are two of the most fertile areas for crop production, which have large-scale agricultural fires during post-harvest seasons. Leveraging established fire-emission databases and satellite-retrieved agricultural fire spots, we show that, while the years 2018 and 2019 recorded low agricultural fire emissions in both the NECP and Punjab, probably due to the implementation of crop straw sustainable management, fire emissions markedly rebounded in 2020, reaching about 190% and 150% of 2019 levels, respectively. The COVID-19 lockdown measures somewhat disrupted eco-friendly crop straw management through restrictions on labor and transportation availability, such that farmers may have had to burn off crop wastes to clear up the land. We further demonstrate that the increased fire emissions in the NECP resulted in serious particulate matter pollution during the fire season in spring 2020, as opposed to considerable decreases in particles from fossil fuel emissions caused by the COVID-19 lockdown. This study suggests the unintended impacts of the COVID-19 pandemic on the agricultural sector and human health.
Semiclassical roots of universality in many-body quantum chaos
Authors: Richter Klaus , Diego Urbina Juan , Tomsovic Steven 
Published: November 2022

Abstract
Quantum chaos of many-body (MB) systems has been swiftly developing into a vibrant research area at the interface between various disciplines, ranging from statistical physics to condensed matter to quantum information and to cosmology. In quantum systems with a classical limit, advanced semiclassical methods provide the crucial link between classically chaotic dynamics and corresponding universal features at the quantum level. Recently, single-particle (SP) techniques dealing with ergodic wave interference in the usual semiclassical limit

ℏ
→
0

have begun to be transformed into the field theoretical domain of N-particle systems in the analogous semiclassical limit

ℏ

e
f
f

=
1

/

N
→
0

, thereby accounting for genuine MB quantum interference. This semiclassical MB theory provides a unified framework for understanding random-matrix correlations of both SP and MB quantum chaotic systems. Certain braided bundles of classical orbits, and of mean field modes, govern interference, respectively, and provide the key to the foundation of universality. Case studies presented include an MB version of Gutzwiller’s trace formula for the spectral density and out-of-time-order correlators along with brief remarks on where further progress may be forthcoming.