bluuebunny/crossref_metadata_2025 huggingface dataset:
Iron-Containing Nickel Cobalt Sulfides, Selenides, and Sulfoselenides as Active and Stable Electrocatalysts for the Oxygen Evolution Reaction in an Alkaline Solution
Authors: Abdpour Soheil , Rademacher Lars , Fetzer Marcus N. A. , Beglau Thi Hai Yen , Janiak Christoph
Published: July 2023

Iron-containing nickel sulfides, selenides, and sulfoselenides were synthesized via a simple two-step hydrothermal reaction (temperature ≤ 160 °C) for their application as electrocatalysts in the oxygen evolution reaction (OER) in an alkaline solution (1 mol L−1 KOH). The study demonstrated that iron-containing nickel cobalt sulfides and selenides exhibit superior OER performance with lower overpotentials compared to iron-free nickel cobalt sulfide and selenide, which highlights the significant role of iron in enhancing OER nickel cobalt electrocatalysts: Fe0.1Ni1.4Co2.9(S0.87O0.13)4, η50 = 318 mV; Fe0.2Ni1.5Co2.8(S0.9O0.1)4, η50 = 310 mV; Fe0.3Ni1.2Co2.5(S0.9O0.1)4, η50 = 294 mV; Fe0.6Ni1.2Co2.5(S0.83O0.17)4, η50 = 294 mV; Fe0.4Ni0.7Co1.6(Se0.81O0.19)4, η50 = 306 mV compared to Ni1.0Co2.1(S0.9O0.1)4, η50 = 346 mV; and Ni0.7Co1.4(Se0.85O0.15)4, η50 = 355 mV (all values at current densities η50 of 50 mA cm−2). Furthermore, the iron-containing nickel cobalt sulfoselenide Fe0.5Ni1.0Co2.0(S0.57Se0.25O0.18)4 displayed exceptional OER performance with η50 = 277 mV, surpassing the benchmark RuO2 electrode with η50 = 299 mV. The superior performance of the sulfoselenide was attributed to its low charge transfer resistance (Rct) of 0.8 Ω at 1.5 V vs. the reversible hydrogen electrode (RHE). Moreover, the sulfoselenide demonstrated remarkable stability, with only a minimal increase in overpotential (η50) from 277 mV to 279 mV after a 20 h chronopotentiometry test. These findings suggest that trimetallic iron, nickel and cobalt sulfide, selenide, and especially sulfoselenide materials hold promise as high-performance, cost-effective, and durable electrocatalysts for sustainable OER reactions. This study provides a valuable approach for the development of efficient electrocatalytic materials, contributing to the advancement of renewable energy technologies.
Probing the Pyrolysis Process of Rice Straw over a “Dual-Catalyst Bed” for the Production of Fuel Gases and Value-Added Chemicals
Authors: Uddin Ikram , Sohail Muhammad , Hussain Muhammad Ijaz , Alhokbany Norah , Amaro-Gahete Juan , Estévez Rafael
Published: July 2023

Rice straw is an agricultural byproduct primarily produced in Asian regions. It is crucial to discover an effective method for converting this waste into chemicals that can be utilized to substitute goods derived from fossil fuels. Pyrolysis serves as an interesting procedure to obtain bio-oil from this rice straw. The composition of the bio-oil obtained after the pyrolysis procedure contains a small quantity of value-added chemicals in addition to various gas components in the gas product. Therefore, the development of catalytic systems that improve this pyrolytic reaction is mandatory. Herein, the design of a dual catalyst bed (CEM/ZSM-5) that catalyzes the volatiles that it releases has been developed. The highest output of 42.1 wt.% of bio-oil, 29.9 wt.% of gases and 28.0 wt.% of bio-char was obtained. Nevertheless, the inclusion of single zeolites to biomass yields biofuel outputs of 42.8 wt.%, gas yields of 27.7 wt.%, and a bio-char yielding of 29.5 wt.%. Additionally, the addition of cement to biomass results in a bio-oil yield of 40.4 wt.% and 30.5 wt.% of gas, along with 29.1 wt.% of char. Regarding pyrolysis gas products, the H2 yield in the produced biogas was increased from 35.9 mL/g to 45.7 mL/g, and the CH4 output was increased from 21.1 mL/g to 27.4 mL/g. The bioenergy output was evaluated employing GC-FID and GC-MS (gas and biofuel). The dual catalytic bed had a significant impact on the contents of the generated biofuel, increasing the quantity of hydrocarbons and other value-added compounds.
Physics-Informed Ensemble Machine Learning Framework for Improved Prediction of Tunneling-Induced Short- and Long-Term Ground Settlement
Authors: Liu Linan , Zhou Wendy , Gutierrez Marte
Published: July 2023

Machine learning (ML), one of the AI techniques, has been used in geotechnical engineering for over three decades, resulting in more than 600 peer-reviewed papers. However, AI applications in geotechnical engineering are significantly lagging compared with other fields. One of the reasons for the lagging is that hyperparameters used in many AI techniques need physical meaning in geotechnical applications. This paper focuses on widening the applications of ML in predicting tunneling-induced short- and long-term ground settlement and optimizing ML architectures considering their interpretability and ability to provide physically consistent results. Informed by the underlying physics knowledge, tunneling-induced ground settlement is divided into long-term and short-term settlements since different mechanisms and influencing parameters contribute to these two deformation types. Based on the above considerations, this paper introduces a physics-informed ensemble machine learning (PIML) framework to strengthen the connection between ML techniques and physics theories, followed by identifying/utilizing different sets of parameters for effectively predicting short- and long-term tunneling-induced settlements, respectively. Together with in situ observations and experimental lab results, parameters obtained from physics equations are set as inputs for the ML models. Results show that the proposed PIML framework effectively predicts tunneling-induced ground movements, with a predicting accuracy above 0.8. Additionally, parametric studies of variable significance and comparisons among different ML designs reveal that in situ observed dynamic parameters, for instance tunnel face and monitoring points (DTM), gap parameter, and tunnel depth, are essential in predicting tunneling-induced short-term settlement, while predicting long-term settlements largely depends on features, such as tunnel depth, volume compressibility, and excess pore pressure, derived from physics theories.
The Influence of Cropping Systems on Photosynthesis, Yield, and Grain Quality of Selected Winter Triticale Cultivars
Authors: Jańczak-Pieniążek Marta
Published: July 2023

Soil serves as the fundamental foundation for agricultural production; however, inappropriate utilization of soil in conventional cropping systems (CONV) coupled with agricultural practices focused on maximizing profit through the attainment of high-quality grain yield contributes to its degradation. An alternative to the CONV is the integrated cropping system (INTEG), which is based on sustainable plant cultivation by reducing the use of chemical pesticides and fertilizers. An interesting two-factor field experiment with winter triticale (×Triticosecale Wittm.) was conducted in 2019–2022 in south-eastern Poland. The experimental factors in this study included three winter triticale cultivars, namely Avokado, Medalion, Rotondo, and SU Liborius, and two cropping systems, CONV and INTEG. It was found that the use of the CONV brought out higher grain yield with higher protein and lower fat content. The cultivation of triticale grain under the CONV resulted in a higher thousand-grain weight (TGW), improved grain uniformity, and higher test weight values compared to INTEG. Additionally, the use of the CONV system resulted in improved values of physiological parameters (chlorophyll content and fluorescence and gas exchange), and that was caused by improved photosynthetic efficiency of triticale plants as a result of increased doses of mineral fertilizers, despite being cultivated in the INTEG; cv. SU Liborius achieved better values of yield parameters among the tested triticale cultivars grown in the CONV. Therefore, the selection of a suitable, efficient cultivar allows its growth under lower fertilization conditions and produces high grain yields of good quality. This knowledge can be valuable to farmers, as it would facilitate the selection of a triticale cultivar with the appropriate genetic profile for cultivation under specific agronomic conditions. Eventually, it would allow for the propagation of sustainable agricultural practices and contribute to enhancing soil biodiversity while maintaining the cost-effectiveness of agricultural production.
The Impacts of Land Use Changes on Water Yield and Water Conservation Services in Zhangjiakou, Beijing’s Upstream Watershed, China
Authors: Zhao Lili , Shen Yan-Jun , Liu Mengzhu , Wang Yixuan , Li Yali , Pei Hongwei
Published: July 2023

The Water Conservation Functional Zone and Ecological Environmental Supporting Zone (the Capital Two Zones in China), Zhangjiakou (ZJK) City, situated in China, has played a key role in mitigating water scarcity pressure on Beijing via delivering sustainable and high-quality water yield, as well as water conservation services aimed at maintaining the ecological functions of the Capital Two Zones. However, the changing mechanism for both water yield and water conservation services instigated by the combined impacts of human activities and climate change remains poorly understood. In this study, we used the Integrated Valuation of Ecosystem Services and Trade-offs Tools (InVEST) model to analyze the changes in water yield and water conservation services, revealing the impacts of different land use scenarios. The results showed significant forest and impervious land area increment, while the water surface area decreased sharply from 1990 to 2020, with obvious urbanization expansion in ZJK during the period. Average annual water yield and water conservation from 1990 to 2020 were recorded at 48.98 mm and 2.35 mm, respectively. Precipitation emerged as the primary driver of water yield and conservation service changes, while the south of ZJK generally exhibited higher water yield and conservation service than the north of ZJK. Results also indicate that grassland had the highest water yield, with an average of 56.60 mm, followed by forest (55.66 mm) and shrub (55.07 mm). Further, the forest had the highest water conservation value (3.73 mm), followed by shrub (2.56 mm), and grassland (2.37 mm), respectively. The return of cropland to forest scenario had the most substantial decrease in water yield. Findings suggest that precipitation has a direct impact on water yield and conservation services via the amount of atmospheric water input, while land use alteration contributes to changes in regional-scale water.
Low-Carbon Supply Chain Operation Decisions and Coordination Strategies Considering the Consumers’ Preferences
Authors: Su Limin , Cao Yongchao , Zhang Wenjuan
Published: July 2023

Implementing the low-carbon transformation strategy has become an inevitable choice for manufacturing enterprises. However, suppliers often overlook the impact of consumers’ preferences for low-carbon products (LCPs) on their own low-carbon strategies. Based on this idea, this study uses game theory models to analyze how consumer preferences affect suppliers’ decision-making and coordination strategies in low-carbon supply chains (LCSCs). Results show that (1) manufacturers and retailers are more likely to produce and promote LCPs as consumers become more sensitive to carbon emission reduction (CER); (2) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to promotional rates; and (3) manufacturers are less likely to produce LCPs but retailers are more likely to promote them as consumers become more sensitive to retail prices. This study concludes that consumer preferences play a crucial role in determining suppliers’ decisions and coordination strategies in LCSCs.
Optimization of Pressure Management in Water Distribution Systems Based on Pressure-Reducing Valve Control: Evaluation and Case Study
Authors: Tian Yuan , Gao Jingliang , Chen Jianxun , Xie Junshen , Que Qidong , Munthali Rodger Millar , Zhang Tiantian
Published: July 2023

Leakage in water distribution systems (WDS) is a major problem that results in substantial resource wastage. Pressure management, which is based on optimized control strategies using pressure-reducing valve installation, is considered one of the most effective methods for controlling network leakage and can be broadly classified into varied types, depending on the different control strategies. When facing diverse operational conditions in actual engineering, selecting the most suitable optimization strategy for the specific water supply network can greatly control leakage and efficiently utilize water resources. This article employs a greedy algorithm to iteratively determine the control sequence for pressure-reducing valves (PRVs), with the objective of minimizing surplus pressure. Subsequently, it proposed five evaluation indicators, namely, daily flow, daily leakage, pressure imbalance indicator, median daily pressure at nodes, and water age, which are used to evaluate and compare pressure management strategies in two sample networks. Finally, a suitable control strategy was successfully developed and implemented for an actual WDS of Y city in southern China, resulting in significant achievements. In conclusion, this paper embodies our attempt and contemplation in formulating pressure management strategies under diverse operating conditions in WDS, with the objective of providing guidance for practical engineering applications.
A New Hybrid Multi-Population GTO-BWO Approach for Parameter Estimation of Photovoltaic Cells and Modules
Authors: Ali Hossam Hassan , Ebeed Mohamed , Fathy Ahmed , Jurado Francisco , Babu Thanikanti Sudhakar , A. Mahmoud Alaa
Published: July 2023

Modeling the photovoltaic (PV) generating unit is one of the most important and crucial tasks when assessing the accurate performance of the PV system in power systems. The modeling of the PV system refers to the assigning of the optimal parameters of the PV’s equivalent circuit. Identifying these parameters is considered to be a complex optimization problem, especially with the deviation of the solar irradiance and the ambient temperature. In this regard, this paper proposes a novel hybrid multi-population gorilla troops optimizer and beluga whale optimization (HMGTO-BWO) model to evaluate the optimal parameters of the PV cell/panel; it is based on a multi-population strategy to improve its diversity and to avoid the stagnation of the conventional GTO. The BWO explorative and exploitative powers, which are based on synchronized motion and Lévy flight, are used. The suggested HGTO-BWO is implemented to minimize the root mean square error (RMSE) between the simulated and measured data for each cell/panel represented by a double diode model (DDM) and triple diode model (TDM). The proposed HGTO-BWO is investigated according to the standard and CEC-2019 benchmark functions, and the obtained results are compared with seven other optimization techniques in terms of statistical analysis, convergence characteristics, boxplots, and the Wilcoxon rank sum test. The minimum obtained RMSE values of the PVW 752 cell were 2.0886 × 10−4 and 1.527 × 10−4 for the DDM and TDM, respectively. Furthermore, the minimum fetched fitness value for the STM6-40/36 modules was 1.8032 × 10−3. The obtained results proved the effectiveness and preference of the suggested HGTO-BWO in estimating the parameters of the PV modules.
Green Transportation Model in Logistics Considering the Carbon Emissions Costs Based on Improved Grey Wolf Algorithm
Authors: Lu Yiqin , Li Shuang
Published: July 2023

The use of new energy vehicles in transportation can effectively promote the development of green logistics. This study selects heavy–duty diesel trucks as traditional logistics vehicles and heavy–duty electric trucks as new energy logistics vehicles. A green transportation model considering carbon emission costs is established to analyze whether new energy logistics vehicles should be used in long–distance freight delivery and how to arrange the use of two types of logistics vehicles. The model is solved using a grey wolf optimization algorithm, which incorporates good point sets, dynamic adaptive inertia weights, and memory–guided location update equations. The model is then applied to three logistics companies in Zhejiang province, China. In addition, considering the time constraints of the logistics industry, the model is used to simulate the arrangement of logistics transport companies for two types of vehicles in long–distance transportation of goods under realistic situations. Finally, this paper studies the future arrangements for long–distance transportation of goods by logistics companies considering the growing popularity of charging piles and advancements in production technology for new energy vehicles. The results show that the involvement of more new energy logistics vehicles in long–distance transport results in lower transportation costs and reduced pollution generated during transportation.
A Combined Clustering and Trends Analysis Approach for Characterizing Reference Evapotranspiration in Veneto
Authors: Di Nunno Fabio , De Matteo Marco , Izzo Giovanni , Granata Francesco
Published: July 2023

Climate change is having an increasing effect on the water cycle, hindering the proper management of water resources for different purposes. Veneto, Northern Italy, is a region characterized by various climatic conditions, ranging from the coastal area to the inland, which exhibits significant agricultural productivity with high irrigation demand, up to the mountainous area to the north. This study assesses a key aspect of climate change in Veneto by focusing on a crucial hydrological parameter, the reference evapotranspiration (ETo), which is calculated using the Penman–Monteith equation. The K-means algorithm was employed to divide Veneto into nine homogeneous regions, each characterized by specific evapotranspiration and climatic features. Furthermore, the seasonal Mann–Kendall (MK) test and the innovative trends analysis (ITA) method were used to investigate the trends related to monthly precipitation, ETo, and climate variables. The seasonal MK test revealed negative trends in precipitation for all clusters. In contrast, ETo trends appear to be decreasing for some clusters, both on the coast and inland, and increasing for others. The ITA method indicated more pronounced trends for higher values of ETo and precipitation, highlighting significant variations that primarily impact extreme values. Overall, this study’s approach, which incorporates clustering and trends analysis methods, provides a detailed depiction of ETo in Veneto, enabling the identification of distinct homogeneous areas and the assessment of evolutionary trends concerning evapotranspiration and precipitation, from the coastal to the mountainous regions.
An Overview of Sandbox Experiment on Ground Heat Exchangers
Authors: Zhou Sihan , Zhu Lijie , Wan Runan , Zhang Tao , Zhang Yongzheng , Zhan Yi , Wang Fang , Zhang Linfeng , You Tian
Published: July 2023

As an energy-efficient and low-carbon technology, ground-source heat pumps are promising to contribute to carbon neutrality in the building sector. A crucial component of these systems is the ground heat exchanger, which has been extensively studied through sandbox experiments. These experiments play a vital role in understanding heat transfer characteristics and validating simulation results. In order to facilitate the improvement of ground heat exchangers and the development of ground-source heat-pump systems, this article provides a comprehensive summary of existing sandbox experiments. The borehole sandbox experiments are classified into the single borehole experiment, borehole group experiment, seepage experiment, and multi-layer soil experiment. It was observed that the heat transfer efficiency of a single spiral tube is only 80% compared to that of a double spiral tube. Moving on to energy-pile sandbox experiments, they are further divided into mechanical performance, thermal performance, and thermal-mechanical coupled performance tests. It was revealed that the heat transfer distance of a single U-shaped energy pile in the radial direction is three times greater than in the vertical direction. For the mentioned sandbox experiments, the sandbox design, experiment conduction, testing conditions, and result analyses are summarized. To improve the sandbox experiments, there are still some difficulties in building a similarity experiment, testing the temperatures in a small error, controlling the boundary conditions accurately, and testing the thermophysical properties of soil accurately. Furthermore, the perspectives of sandbox experiments of ground heat exchangers are also proposed. The sandbox experiments under complex environment conditions or with novel composite energy geo-structures or ground heat exchangers with new materials and new technologies would be further investigated. By addressing these aspects, this review aims to provide guidelines for the design, construction, operation, and optimization of sandbox experiments for different ground heat exchangers, ultimately promoting the wider adoption of ground-source heat pumps in achieving carbon neutrality.
Nondestructive Measurement of the Water Content in Building Materials by Single-Sided NMR-MOUSE
Authors: Zhaxi Quzhen , Zhou Hua , Long Zhenyu , Guo Juwen , Zhou Yanping , Zhang Zhongjian
Published: July 2023

Water has a significant impact on the properties of building materials. A nuclear magnetic resonance (NMR) spectrometer can be used to detect water in materials and measure its distribution nondestructively, rapidly, and accurately. In this paper, a novel method is introduced for using single-sided NMR to measure the water content (WC) of building materials, including brick, sandstone, mortar, and concrete. The NMR signal intensity and water content of these building materials were measured using a single-sided NMR-MOUSE PM25 and a high-precision electronic scale, respectively. A total of 80 groups of NMR signal intensity and water content data were obtained in two different measurement environments. The NMR signal intensity and water content data for each of the four building materials were fitted by the least squares method. The similarity of the coefficients of the determined correlations demonstrated that these relations are universal for building materials and independent of the NMR signal intensity and water content measurement environments.
Integration with Visual Perception—Research on the Usability of a Data Visualization Interface Layout in Zero-Carbon Parks Based on Eye-Tracking Technology
Authors: Li Guangxu , Wang Lingyu , Hu Jie
Published: July 2023

With the continued application of data visualization technology in sustainable development, the construction of carbon emission monitoring platforms is becoming increasingly popular in industrial parks. However, there are many kinds of such interfaces, the usability of which remains unclear. Therefore, in order to explore the usability of current carbon emission visualization interfaces in parks and put forward humanized optimization strategies for their subsequent design, this study used eye-tracking technology to analyze the data readability of six types of layouts from three aspects of visual perception features: integrity, understandability, and selectivity. Quantitative data from eye movement experiments and visual perception characteristics were evaluated using a Likert scale in an analysis of different layouts, and the correlation data between three visual perception characteristics and the readability of different layout data were obtained using an SPSS tool. The results show that, compared with a layout containing 3D graphics, the pure data type of interface has a shorter task completion time and higher readability; however, it provides fewer choices for users and is less interesting. In addition, there is a significant negative correlation between integrity and task completion time; the more complete the interface layout, the shorter the task completion time. In summary, a certain correlation was found between visual perception characteristics and the readability of interface layout using this method. At the same time, the advantages and disadvantages of different interface layouts were also analyzed, and more humanized optimization directions and strategies were devised. This is vital for aiding subsequent research on the influence of specific layout elements to optimize visualization interfaces that display carbon emission data.
Using Highly Flexible SbSn@NC Nanofibers as Binderless Anodes for Sodium-Ion Batteries
Authors: Liang Jiaojiao , Fang Gengkun , Niu Xinmiao , Zhang Zhihao , Wang Yufei , Liao Lingyuan , Zheng Xiaoming , Huang Di , Wei Yuehua
Published: July 2023

Flexible and binderless electrodes have become a promising candidate for the next generation of flexible power storage devices. However, developing high-performance electrode materials with high energy density and a long cycle life remains a serious challenge for sodium-ion batteries (SIBs). The main issue is the large volume change in electrode materials during the cycling processes, leading to rapid capacity decay for SIBs. In this study, flexible electrodes for a SnSb alloy–carbon nanofiber (SnSb@NC) membrane were successfully synthesized with the aid of hydrothermal, electrospinning and annealing processes. The as-prepared binderless SnSb@NC flexible anodes were investigated for the storage properties of SIBs at 500 °C, 600 °C and 700 °C (SnSb@NC-500, SnSb@NC-600 and SnSb@NC-700), respectively. And the flexible SnSb@NC-700 electrode displayed the preferable SIB performances, achieving 240 mAh/g after 100 cycles at 0.1 A g−1. In degree-dependent I-V curve measurements, the SnSb@NC-700 membrane exhibited almost the same current at different bending degrees of 0°, 45°, 90°, 120° and 175°, indicating the outstanding mechanical properties of the flexible binderless electrodes.
A Study on the Surface Vibration Effect of CO2 Phase Transition Cracking Based on the Time-Domain Recursive Analysis Method
Authors: Abi Erdi , Liu Lu , Zhang Jie , Zeng Qifu , Wu Fayou , Li Haotian
Published: July 2023

Supercritical CO2 phase change fracturing technology has been widely used in rock engineering. However, the surface vibration characteristics induced by phase change rock breaking have not been sufficiently studied. In this paper, a model for calculating the surface vibration velocity induced by supercritical CO2 phase change was established based on the time-domain recursive method, and the reliability of the model was verified using LS-DYNA nonlinear finite element software; based on the model for calculating the blasting energy of a compressed gas and water vapor container, the surface vibration velocity and decay law induced by CO2 phase change fracturing and equivalent explosive blasting were compared and analyzed. The results show that the ground vibration velocity calculation model based on the time-domain recurrence method can better evaluate the ground vibration characteristics induced by supercritical CO2 phase change fracturing, and the vibration velocity decays exponentially with the fracture distance; the peak pressure of supercritical CO2 phase change is only 1/3.36 of that of explosive blasting, but the action time is 100 times longer than that of explosive blasting, and the peak vibration velocity is 1/74~1/78 of that of equivalent explosive blasting.
Wigner–Ville Distribution Associated with Clifford Geometric Algebra Cln,0, n=3(mod 4) Based on Clifford–Fourier Transform
Authors: Bhat Mohammad Younus , Rafiq Shahbaz , Zayed Mohra
Published: July 2023

In this study, the Wigner–Ville distribution is associated with the one sided Clifford–Fourier transform over Rn, n = 3(mod 4). Accordingly, several fundamental properties of the WVD-CFT have been established, including non-linearity, the shift property, dilation, the vector differential, the vector derivative, and the powers of τ∈Rn. Moreover, powerful results on the WVD-CFT have been derived such as Parseval’s theorem, convolution theorem, Moyal’s formula, and reconstruction formula. Eventually, we deduce a directional uncertainty principle associated with WVD-CFT. These types of results, as well as methodologies for solving them, have applications in a wide range of fields where symmetry is crucial.
Symmetry in Ordinary and Partial Differential Equations and Applications
Authors: Vetro Calogero
Published: July 2023

This Special Issue of the journal Symmetry is dedicated to recent progress in the field of nonlinear differential problems [...]
Orientation-Dependent High-Order Harmonic Generation from Monolayer ZnO
Authors: Hu Zijian , Xie Xiance , Yang Zhihong , Wang Yunhui , Jiang Shicheng
Published: July 2023

Solid-state high-order harmonic generation (HHG) now is a strong tool for detecting target properties, like band structure, Berry curvature and transition dipole moments (TDMs). However, the physical mechanism of high-order harmonic generation (HHG) in solids has not been fully elucidated. According to previously published works, in addition to the inter-band polarization, intra-band currents, and anomalous currents due to Berry curvature, there is another term which will be called the mixture term (MT). Taking monolayer ZnO as a sample, it is found that the intensity of the mixture term, which has been ignored for a long time in previous works, actually is comparable with other terms. Additionally, we compare the orientation-dependent HHG spectra that originated from different mechanisms. It is found that the inter-band and mixture HHG show similar orientation features. Meanwhile, Berry curvature only produces perpendicularly polarized even harmonics, and intra-band perpendicularly polarized even harmonics show special orientation features which can be explained by the orientation-dependent group velocity. This work will help people understand the mechanisms of solid-HHG better.
Efficient Application of the Factorized form of the Unitary Coupled-Cluster Ansatz for the Variational Quantum Eigensolver Algorithm by Using Linear Combination of Unitaries
Authors: Xu Luogen , Freericks James K.
Published: July 2023

The variational quantum eigensolver is one of the most promising algorithms for near-term quantum computers. It has the potential to solve quantum chemistry problems involving strongly correlated electrons with relatively low-depth circuits, which are otherwise difficult to solve on classical computers. The variational eigenstate is constructed from a number of factorized unitary coupled-cluster terms applied onto an initial (single-reference) state. Current algorithms for applying one of these operators to a quantum state require a number of operations that scale exponentially with the rank of the operator. We exploit a hidden SU(2) symmetry to allow us to employ the linear combination of unitaries approach, Our Prepare subroutine uses n+2 ancilla qubits for a rank-n operator. Our Select(U^) scheme uses O(n)Cnot gates. This results in a full algorithm that scales like the cube of the rank of the operator n3, a significant reduction in complexity for rank five or higher operators. This approach, when combined with other algorithms for lower-rank operators (when compared to the standard implementation), will make the factorized form of the unitary coupled-cluster approach much more efficient to implement on all types of quantum computers.
Multi-Strategy Enhanced Dung Beetle Optimizer and Its Application in Three-Dimensional UAV Path Planning
Authors: Shen Qianwen , Zhang Damin , Xie Mingshan , He Qing
Published: July 2023

Path planning is a challenging, computationally complex optimization task in high-dimensional scenarios. The metaheuristic algorithm provides an excellent solution to this problem. The dung beetle optimizer (DBO) is a recently developed metaheuristic algorithm inspired by the biological behavior of dung beetles. However, it still has the drawbacks of poor global search ability and being prone to falling into local optima. This paper presents a multi-strategy enhanced dung beetle optimizer (MDBO) for the three-dimensional path planning of an unmanned aerial vehicle (UAV). First, we used the Beta distribution to dynamically generate reflection solutions to explore more search space and allow particles to jump out of the local optima. Second, the Levy distribution was introduced to handle out-of-bounds particles. Third, two different cross operators were used to improve the updating stage of thief beetles. This strategy accelerates convergence and balances exploration and development capabilities. Furthermore, the MDBO was proven to be effective by comparing seven state-of-the-art algorithms on 12 benchmark functions, the Wilcoxon rank sum test, and the CEC 2021 test suite. In addition, the time complexity of the algorithm was also analyzed. Finally, the performance of the MDBO in path planning was verified in the three-dimensional path planning of UAVs in oil and gas plants. In the most challenging task scenario, the MDBO successfully searched for feasible paths with the mean and standard deviation of the objective function as low as 97.3 and 32.8, which were reduced by 39.7 and 14, respectively, compared to the original DBO. The results demonstrate that the proposed MDBO had improved optimization accuracy and stability and could better find a safe and optimal path in most scenarios than the other metaheuristics.
Comparative Analysis of Image Classification Models for Norwegian Sign Language Recognition
Authors: Svendsen Benjamin , Kadry Seifedine
Published: July 2023

Communication is integral to every human’s life, allowing individuals to express themselves and understand each other. This process can be challenging for the hearing-impaired population, who rely on sign language for communication due to the limited number of individuals proficient in sign language. Image classification models can be used to create assistive systems to address this communication barrier. This paper conducts a comprehensive literature review and experiments to find the state of the art in sign language recognition. It identifies a lack of research in Norwegian Sign Language (NSL). To address this gap, we created a dataset from scratch containing 24,300 images of 27 NSL alphabet signs and performed a comparative analysis of various machine learning models, including the Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Convolutional Neural Network (CNN) on the dataset. The evaluation of these models was based on accuracy and computational efficiency. Based on these metrics, our findings indicate that SVM and CNN were the most effective models, achieving accuracies of 99.9% with high computational efficiency. Consequently, the research conducted in this report aims to contribute to the field of NSL recognition and serve as a foundation for future studies in this area.
Effect of Aging on Physicochemical Properties and Size Distribution of PET Microplastic: Influence on Adsorption of Diclofenac and Toxicity Assessment
Authors: Papac Zjačić Josipa , Tonković Stefani , Pulitika Anamarija , Katančić Zvonimir , Kovačić Marin , Kušić Hrvoje , Hrnjak Murgić Zlata , Lončarić Božić Ana
Published: July 2023

Microplastics (MPs) are detected in the water, sediments, as well as biota, mainly as a consequence of the degradation of plastic products/waste under environmental conditions. Due to their potentially harmful effects on ecosystems and organisms, MPs are regarded as emerging pollutants. The highly problematic aspect of MPs is their interaction with organic and inorganic pollutants; MPs can act as vectors for their further transport in the environment. The objective of this study was to investigate the effects of ageing on the changes in physicochemical properties and size distribution of polyethylene terephthalate (PET), as well as to investigate the adsorption capacity of pristine and aged PET MPs, using pharmaceutical diclofenac (DCF) as a model organic pollutant. An ecotoxicity assessment of such samples was performed. Characterization of the PET samples (bottles and films) was carried out to detect the thermooxidative aging effects. The influence of the temperature and MP dosage on the extent of adsorption of DCF was elucidated by employing an empirical modeling approach using the response surface methodology (RSM). Aquatic toxicity was investigated by examining the green microalgae Pseudokirchneriella subcapitata. It was found that the thermooxidative ageing process resulted in mild surface changes in PET MPs, which were reflected in changes in hydrophobicity, the amount of amorphous phase, and the particle size distribution. The fractions of the particle size distribution in the range 100–500 μm for aged PET are higher due to the increase in amorphous phase. The proposed mechanisms of interactions between DCF and PET MPs are hydrophobic and π–π interactions as well as hydrogen bonding. RSM revealed that the adsorption favors low temperatures and low dosages of MP. The combination of MPs and DCF exhibited higher toxicity than the individual components.
A Mother’s Dilemma: The 5-P Model for Vaccine Decision-Making in Pregnancy
Authors: Cox Elizabeth , Sanchez Magali , Taylor Katherine , Baxter Carly , Crary Isabelle , Every Emma , Futa Brianne , Adams Waldorf Kristina M.
Published: July 2023

Pregnant women are a highly vaccine-resistant population and face unique circumstances that complicate vaccine decision-making. Pregnant women are also at increased risk of adverse maternal and neonatal outcomes to many vaccine-preventable diseases. Several models have been proposed to describe factors informing vaccine hesitancy and acceptance. However, none of these existing models are applicable to the complex decision-making involved with vaccine acceptance during pregnancy. We propose a model for vaccine decision-making in pregnancy that incorporates the following key factors: (1) perceived information sufficiency regarding vaccination risks during pregnancy, (2) harm avoidance to protect the fetus, (3) relationship with a healthcare provider, (4) perceived benefits of vaccination, and (5) perceived disease susceptibility and severity during pregnancy. In addition to these factors, the availability of research on vaccine safety during pregnancy, social determinants of health, structural barriers to vaccine access, prior vaccine acceptance, and trust in the healthcare system play roles in decision-making. As a final step, the pregnant individual must balance the risks and benefits of vaccination for themselves and their fetus, which adds greater complexity to the decision. Our model represents a first step in synthesizing factors informing vaccine decision-making by pregnant women, who represent a highly vaccine-resistant population and who are also at high risk for adverse outcomes for many infectious diseases.
Optimal Exploitation of Urban Water Supply Networks Based on Pressure Management with the Nondominated Sorting Differential Evolution (NSDE) Algorithm
Authors: Cemiloglu Ahmed , Licai Zhu , Ugurenver Abbas , Nanehkaran Yaser A.
Published: July 2023

Urban water distribution networks are crucial infrastructures for providing essential services to society, but their exorbitant costs and limited water resources make their optimization a critical research area. Optimal management and design of these networks can help to reduce costs and enhance their efficiency while meeting technical, economic, and quality standards. In particular, the management of network pressure is critical for reducing leakage in water distribution systems. Thus, this study aimed to investigate two objective functions for optimizing the water distribution network: (i) minimizing costs while considering the number of pressure-relief valves, and (ii) minimizing network pressure by observing the optimal pressure range. To achieve this, the Nondominated Sorting Differential Evolution (NSDE) multi-objective metaheuristic algorithm was employed as the optimization tool, and a computer program was written in MATLAB software for solving the optimization models. EPANET software was also used for hydraulic simulation of the water distribution network. The efficiency and capabilities of these models were tested on the case study of the third district of Mashhad in Iran. The results indicated that the installation and adjustment of pressure-relief valves in accordance with the positions and optimal settings of the output of the proposed models significantly improved the desired goals, particularly the average pressure of the network. As an example of optimization, the study achieved a 56.12% reduction in pressure compared to the case without a plan, considering five pressure-relief valves.
Photogrammetric Technique-Based Quantitative Measuring of Gravity Erosion on Steep Slopes in Laboratory: Accuracy and Application
Authors: Xia Jinwen , Zhang Lichao , Huang Xuhua , Lu Xianghui , Ge Peilin , Wei Yujie , Cai Chongfa
Published: July 2023

Quantitative measuring of gravity erosion contributes to a better understanding of soil-mass failure occurrence and prediction. However, the measurement of gravity erosion requires the continuous monitoring of the objective terrain, due to its occurrence, usually within seconds, and combination with hydraulic erosion. The photogrammetric technique can quickly obtain terrain data and provide a new method for measuring gravity erosion. Based on a continuous high-overlapping image-acquisition equipment, a Structure-from-Motion-Multi-View-Stereo (SfM-MVS)-integrated workflow, and volume calculation, a new working methodology was established for measuring gravity erosion on steep granitic slopes in the laboratory. The results showed a good match between the digital point clouds derived from SfM-MVS-integrated workflow and terrestrial laser scanning (TLS), achieving millimeter-scale accuracy. The mean distance between the point clouds derived from TLS and SfM-MVS was 1.13 mm, with a standard deviation of 0.93 mm. The relative errors among the volumes calculated by SfM-MVS and TLS or the conventional oven-drying method were all within 10%, with a maximum error of 9.3% and a minimum error of 0.2%. A total of 213 gravitational erosion events were measured in the laboratory by using the SfM-MVS method, further confirming its feasibility.
Study on Purification Efficiency of Novel Aquatic Plant Combinations and Characteristics of Microbial Community Disturbance in Eutrophic Water Bodies
Authors: Jia Jianna , Xiao Huan , Peng Shitao , Zhang Kailei
Published: July 2023

Aquatic plant restoration is an important technique for the treatment of eutrophic water bodies. There are significant differences in pollutant removal efficiency among different combinations of aquatic plant species in eutrophic water bodies. Therefore, further research on the selection of suitable combinations of aquatic plant species is of great significance for the restoration of eutrophic water bodies. This study investigated the pollutant removal efficiency and bacterial community structure of three novel combinations of aquatic plants, including Lythraceae, Nymphaea, and Myriophyllum (LNM group), Lythraceae, Nymphaea, and Hydrilla verticillata (LNH group), and Lythraceae, Nymphaea, and Vallisneria (LNV group), as well as a control group (CK group). The components of the CK group were only sediment and culture water without any plants. The results show that on one hand, the LNH group had the highest removal rate of COD (90.29%); the LNV group exhibited the highest removal rates for NH4+-N and TN, with removal rates of 61.20% and 82.94%, respectively; and there was no significant difference in the removal rate of TP among the experimental groups, except for the LNH group, which showed higher initial removal efficiency for TP. On the other hand, plant combinations had different impacts on the top 13 dominant microflora at the phylum level. Proteobacteria and Actinobacteria showed the highest removal efficiency for COD in the LNH group, while Verrucomicrobi, Chloroflex, and Acidobacteria showed higher removal efficiency for NH4+-N and TN in the LNV and LNH groups. In summary, the three different combinations of aquatic plants exhibited distinct pollutant removal characteristics, significantly altered the structure of the microbial community, and provided a theoretical basis for their practical application in the restoration of eutrophic water bodies.
Research on the Hydraulic Characteristics of Island Fishways by Experimental and Numerical Methods
Authors: Zeng Guorui , Xu Maosen , Mou Jiegang , Wang Keke , Ren Yun
Published: July 2023

With the development of hydraulic structures, rivers are becoming fragmented, and their connectivity is greatly affected. Important migratory routes through which fish complete their life processes are hindered. In severe cases, it may lead to the extinction of fish species. As facilities commonly used to assist fish upstreaming, fishways are significant for environmental remediation and have received attention from different scholars. This article proposed a new type of fishway, inspired by Tesla valves with obstructing reverse flow characteristics and classic fishway structures. Due to its characteristic of introducing a water-blocking island structure, it was denominated as an island-style fishway. This work studied an island fishway through a combination of physical models and numerical simulations. The results show that this fishway could achieve various flow patterns suitable for fish migration, and the flow rate control was stable. This study also explored the impact of island spacing arrangement on the turbulent structure of the pool chamber. It was found that when the island distance is set at 1.5d, indicators such as flow velocity and turbulent kinetic energy could achieve significant control effects. However, inappropriate d values might cause adverse effects. This research could provide reference ideas for the design of new fishways.
State of Health Assessment for Lithium-Ion Batteries Using Incremental Energy Analysis and Bidirectional Long Short-Term Memory
Authors: Li Yanmei , Luo Laijin , Zhang Chaolong , Liu Huihan
Published: July 2023

The state of health (SOH) of a lithium ion battery is critical to the safe operation of such batteries in electric vehicles (EVs). However, the regeneration phenomenon of battery capacity has a significant impact on the accuracy of SOH estimation. To overcome this difficulty, in this paper we propose a method for estimating battery SOH based on incremental energy analysis (IEA) and bidirectional long short-term memory (BiLSTM). First, the IE curve that effectively describes the complex chemical characteristics of the battery is obtained according to the energy data calculated from the constant current (CC) charging phase. Then, the relationship between the IE curve and battery SOH degradation characteristics is analyzed and the peak height of the IE curve is extracted as the aging characteristic of the battery. Further, Pearson correlation analysis is utilized to determine the linear correlation between the proposed aging characteristics and the battery SOH. Finally, BiLSTM is employed to capture the underlying mapping relationship between peak characteristics and SOH, and a battery SOH estimation model is developed. The results demonstrate that the proposed method is able to estimate battery SOH under two different charging conditions with a root mean square error less than 0.5% and coefficient of determination above 98%. Additionally, the method is combined with Pearson correlation analysis to select an aging characteristic with high correlation, reducing the required data input and computational burden.