bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Analysis of MIMO-mQAM System with Pointing Errors and Beam Spreading in Underwater Málaga Turbulence Channel
Authors: Wang Jianying , Yin Hongxi , Ji Xiuyang , Liang Yanjun
Published: March 2023

Both the long-term beam spreading caused by ocean turbulence and the pointing errors induced by the jitter of transmitters and receivers degrade the performance of underwater wireless optical communication (UWOC) links. To effectively alleviate their effects, an in-depth study was carried out over the Málaga turbulence channel with pointing errors and beam spreading in multiple-input and multiple-output (MIMO) UWOC. First, we analyzed the long-term beam spreading and the received light power for the finite receiving aperture in the presence of pointing error displacements. Based on this, the relationship between beam spreading, pointing errors, and signal power was established. Second, the approximate expressions of the average bit error rate (BER) and the communication outage probability were derived theoretically for this MIMO system using maximal-ratio combining (MRC) diversity. Third, the effects of the pointing errors on the coding and the diversity gains were explored for the MIMO links. Finally, using the observed ocean data from the Global Ocean Argo gridded dataset, we numerically verified the combined effects of ocean turbulence strength, beam spreading, and pointing errors on the average BER and outage probability of this system. These results also proved that adjusting the size of the receiving aperture or the order of the multiple quadrature amplitude modulation (mQAM) could effectively mitigate their effects.
Super-Twisting Sliding Mode Control for the Trajectory Tracking of Underactuated USVs with Disturbances
Authors: Liu Wei , Ye Hui , Yang Xiaofei
Published: March 2023

For an underactuated unmanned surface vehicle (USV), time-varying external disturbances affect the accuracy of trajectory tracking. To ensure trajectory tracking accuracy, in this paper the reduced-order extended state observer (ESO) and the super-twisting second-order sliding mode controller are adopted. The ESO is designed to address the unknown time-varying sideslip angle in the guidance law. Additionally, the super-twisting technology contributes to a reduced chattering effect of the sliding mode. The Lyapunov method is used to analyze the stability of the tracking system and prove that the proposed controllers can ensure the convergence of the tracking errors in finite time. The simulation experiments of the proposed super-twisting sliding mode control (STSMC) and adaptive sliding mode control (ASMC) methods are compared. The results show that the STSMC method enables the USV to complete the task of the reference trajectory tracking. The chattering of the STSMC is also significantly reduced compared to that of the ASMC.
The Future of E-Commerce: Overview and Prospects of Multichannel and Omnichannel Retail
Authors: Iglesias-Pradas Santiago , Acquila-Natale Emiliano
Published: March 2023

Multichannel and omnichannel strategies have become a critical aspect of retailing. In this study, we present an overview of multichannel and omnichannel retail and discuss its applications in the future of retail. To do so, we explore the different areas of interest in multichannel and omnichannel retail highlighted in previous scholarly research, as a preliminary step to propose a comprehensive framework of themes that should be paid attention to for future advancements in the field. A total of 11 studies addressing the main theme of Multichannel Retail and Its Applications in the Future of E-Commerce illustrate this overview and the framework.
Spatial Differentiation and Influencing Mechanisms of Farmland Transfer Rents in Mountainous Areas: Evidence from Chongqing and Its Surrounding Areas
Authors: Du Ting , Li Chao , Wang Zhaolin
Published: March 2023

This study used Chongqing, a municipality in mountainous southwest China, and its surrounding areas as a case study to explore the spatial differentiation of farmland transfer rents in mountainous areas, with the aim of serving as a theoretical and practical reference to realize the value of farmland, ensure regional food security, and promote stable and sound development of the farmland transfer market. In doing so, we applied the GIS spatial analysis method to explore the spatial differentiation and influencing mechanisms of farmland transfer rents in mountainous areas. Our results indicate that farmland transfer rents in mountainous areas have a significant high and low clustering tendency. The high-value areas of farmland transfer rents are mainly located in the downtown area and the west of Chongqing, while the low-value areas are mainly distributed in the Daba Mountains and Wuling Mountains, which are two national contiguous areas of dire poverty. Location and terrain factors are the main driving forces for the spatial differentiation of farmland transfer rents in mountainous areas. Specifically, a 1% increase in farmland mean slope and farmland supply-demand ratio in the study area will lead to a 0.13 and 0.15% decrease in farmland transfer rents, respectively, while a 1% increase in GDP will drive up farmland transfer rents by 0.09%. The policy factor is not significant. The influence of terrain and farmland supply and demand on transfer rents increased from west to east, whereas the influence of traffic location on transfer rents decreased in an outward direction from the southwest of the study area. It is concluded that local governments should objectively view the spatial differentiation of farmland transfer rents in mountainous areas and avoid the blind comparison of transfer rents between regions. Mountainous areas with low transfer rents should focus on increasing the intrinsic value of farmland assets by stimulating effective demand for farmland and improving farming conditions, while mountainous areas with high transfer rents in major grain-producing counties should be wary of their impact on grain production to ensure regional food security.
Effect of Rotational Speed on Tribological Properties of Carbon Fiber-Reinforced Al-Si Alloy Matrix Composites
Authors: Tang Feng , Pan Xiaotao , Deng Yafei , Zhou Zhenquan , Zeng Guoxun , Xiao Sinong
Published: March 2023

Porous carbon fiber-reinforced Al-Si alloy matrix composites and carbon fiber felt-reinforced Al-Si alloy matrix composites with carbon content of 10 wt.% were prepared by die casting. The dry tribological properties of these two composites and Al-Si alloy were studied using a ball-on-disc rotational tribometer in the rotational speed range of 300 r/min to 1000 r/min, and the wear mechanisms were analyzed in combination with the wear morphology. The results show that the friction coefficient and wear rate of these two composites are lower than the Al-Si alloy at different speeds. With the increase in rotational speed, the friction coefficient of the two composites and Al-Si alloy first increases and then decreases, and the wear rate gradually increases. The wear mechanisms of the two composites and Al-Si alloy change from abrasive wear and adhesive wear to delamination wear, but the node speed of the change in the wear mechanism of the composites to delamination wear is higher, and the wear degree is relatively slight. In addition, the comprehensive tribological properties of carbon fiber felt-reinforced Al-Si alloy matrix composites are better than the porous carbon fiber-reinforced Al-Si alloy matrix composites.
Investigating the Efficiency of a Heat Recovery–Storage System Using Heat Pipes and Phase Change Materials
Authors: Vizitiu Robert Stefan , Burlacu Andrei , Abid Chérifa , Balan Marius Costel , Vizitiu Stefanica Eliza , Branoaea Marius , Kaba Nicoleta Elena
Published: March 2023

This study presents an experimental and numerical investigation into the efficiency of a two-stage heat recovery–storage system for reducing the thermal energy losses in the industry. The system is designed to recover and store waste thermal energy from residual fluids using heat pipes for recovery and an environmentally friendly phase change material for heat storage. Experimental investigation was conducted using water as the primary agent and varying the temperature between 60 °C, 65 °C, and 70 °C at a constant flow rate of 24 L/min. The secondary agent, also water, was used at an initial temperature of 10 °C and the flow rate was varied between 1 L/min, 2 L/min, and 3 L/min. The results show that the system had a peak efficiency of 78.1% and was able to recover a significant amount of thermal energy. This study demonstrates the potential of this system to reduce the thermal energy losses in the industry and highlight the importance of further research and development in this field, as the industry is responsible for approximately 14% of the total thermal energy losses and finding efficient ways to recover and store waste thermal energy is crucial to achieving sustainable energy consumption.
Effect of Al Concentration on Structural, Optical and Electrical Properties of (Gd, Al) Co-Doped ZnO and Its n-ZnO/p-Si (1 0 0) Heterojunction Structures Prepared via Co-Sputtering Method
Authors: Raship Nur Amaliyana , Tawil Siti Nooraya Mohd , Nayan Nafarizal , Ismail Khadijah
Published: March 2023

Heterojunction structures of n-ZnO/p-Si were prepared through the growth of undoped ZnO and (Gd, Al) co-doped ZnO films onto p-type Si (1 0 0) substrates, using a co-sputtering method. The structural and optical properties of the Gd-doped ZnO films were studied as a function of different Al doping concentrations. The X-ray diffraction profiles indicated that the films had a nanocrystalline structure of ZnO with a (0 0 2) preferential orientation. An increase in the Al doping concentration deteriorated the (0 0 2) diffraction peak intensity. The transmittance measurements in the UV–Vis wavelength range indicated that the film’s optical gap increased with increase in Al doping concentration. The heterojunction parameters were evaluated using the current–voltage (I-V) characterization carried out of the fabricated n-ZnO/p-Si heterostructure, in dark conditions at room temperature. From these measurements, the n-ZnO-based DMS/p-Si heterojunction diode with the use of (Gd, Al) co-doped ZnO film showed the lowest leakage current of 1.28 × 10−8 A and an ideality factor η of 1.11, close to the ideal diode behavior of η = 1, compared to the n-Gd-doped ZnO/p-Si and n-undoped ZnO/p-Si heterojunction diodes.
DFT Method Used for Prediction of Molecular and Electronic Structures of Mn(VI) Macrocyclic Complexes with Porhyrazine/Phthalocyanine and Two Oxo Ligands
Authors: Chachkov Denis V. , Mikhailov Oleg V.
Published: March 2023

By using the data of the DFT quantum chemical calculation in the OPBE/TZVP and B3PW91/TZVP levels, the possibility of the existence of a manganese(VI) heteroligand complex containing porphyrazine or its tetra[benzo] derivative (phthalocyanine) and two oxygen (O2−) ligands, which is still unknown for this element, is shown. The parameters of the molecular structure, multiplicity of the ground state, NBO analysis data and standard thermodynamic parameters (enthalpy ΔH0f, entropy S0f and Gibbs’s energy ΔG0f of formation) of each of these metal macrocyclic compounds are presented. Additionally, it is noted that, based on the totality of structural data obtained by the above versions of the DFT method, the existence of a similar complex of manganese with di[benzo] derivative of porhyrazine and two oxygen (O2−) ligands seems doubtful.
Corrosion and Mechanical Behavior of the As-Cast and Solid-Solution-Treated AM50 Magnesium Alloy in Different Media
Authors: Yang Miao , Liu Xiaobo , Xing Liyun , Chen Zhaoyu
Published: March 2023

Hydrogen embrittlement and the anodic dissolution mechanism are two important aspects of the corrosion behavior of magnesium alloys. Here, to evaluate the effects of these two aspects on the corrosion failure of magnesium alloys under stress, the stress and corrosion behaviors of the AM50 magnesium alloy in air, deionized water, and NaCl solution after solid-solution (T4) treatment were investigated by X-ray diffraction, scanning electron microscopy, slow strain rate tensile testing, and vacuum dehydrogenation. The as-cast AM50 magnesium alloy was mainly composed of the α-Mg and β-Mg17Al12 phases. After T4 treatment, the amount of the β-Mg17Al12 phase was significantly reduced, and only a small amount existed at the grain boundaries. After T4 treatment, the stress corrosion resistance in deionized water improved, but it decreased in an NaCl environment. Dehydrogenation experiments showed that the effect of hydrogen on the corrosion process was weakened owing to the decrease of the β-Mg17Al12 phase after solution treatment. The effects of hydrogen embrittlement and the anodic dissolution mechanism on the corrosion behavior of the AM50 magnesium alloy under stress were different. In deionized water, the hydrogen embrittlement mechanism played the major role, while the anodic dissolution mechanism played the major role in the presence of Cl− ions.
Effect of Nano-Ti Particles on Microstructure and Mechanical Properties of Mg-3Al-1Zn Matrix Composites
Authors: Tian Wei , Gao Pengfei , Han Shengli , Chen Xiaohong , Zhang Fuwei , Zhang Yuhui , Luo Tiegang , Zheng Kaihong
Published: March 2023

In this paper, a new nanoscale metal Ti particle-reinforced Mg-3Al-1Zn matrix composite was successfully designed and prepared, which is mainly characterized by the fact that in addition to the “light” advantages of magnesium matrix composite, it also realizes bidirectional improvement of strength and ductility of the composite, and can be used as an alternative material for military light vehicle armor and individual armor. The SEM test shows that the nano-Ti particles are uniformly distributed at the grain boundary under the extruded state, which nails the grain boundary, inhibits the grain growth, and significantly refines the grain. XRD tests show that the addition of nano-Ti particles increases the crystallinity of the composite, which is consistent with the SEM test results. In addition, the EBSD test shows that the weakening of the texture of Ti/Mg-3Al-1Zn matrix composites and the increase in the starting probability of slip system are the main reasons for the improvement in ductility. Mechanical tests show that the yield strength, tensile strength, and elongation of the 0.5 wt% Ti/Mg-3Al-1Zn matrix composites exceed the peak values of ASTM B107/B107M-13 by 38.6%, 26.7%, and 20%, respectively.
Correlation between Orientation Spread and Ear Forming of As-Annealed AA5151 Aluminum Alloy
Authors: Hsiao Shih-Chieh , Li Chia-Yu , Chang Chih-I , Tseng Tien-Yu , Pan Yeong-Tsuen , Kuo Jui-Chao
Published: March 2023

In the present work, we take the influences of activated slip systems and the orientation spread into account to predict the cup height using analytical earing models and compare the predicted results with experimental results. The effect of boundary conditions of the various stress states and the work hardening exponents are compared and discussed for profile of single crystals. A stress ratio of −0.3 and a hardening exponent of 0.3 are selected for the prediction of earing profiles. The combination of activation of the single slip systems and orientation spread provides the best prediction of deep-drawing profiles. With further consideration of the orientation spread, an increase in the total orientation leads to peak-broadening, i.e., broad and smooth ears. Furthermore, the difference of the height between the maximum and minimum value of cup profiles is reduced because of the orientation spread. The profile for C is found with single ear at 45°, while the other components individually reveal double ears at 35° and 50° for S, at 15° and 45° for B, at 0° and 90° for Cube, at 5° and 90° for r-Cube, and at 15° and 90° for G. Herein, simple analytical earing models are proposed to understand the effects of slip systems and the orientation spread. The deep-drawing profiles are predicted with six major texture components.
A Digital Twin-Based System to Manage the Energy Hub and Enhance the Electrical Grid Resiliency
Authors: Nasiri Gholamreza , Kavousi-Fard Abdollah
Published: March 2023

This article addresses a digital twin-based real-time analysis (DTRA) to meditate the power system vulnerability whenever cascading failures and blackouts occur for any reason, and thus, to improve the resiliency. In addition to this, a water-power package is proposed to enhance the vulnerable percentage of the system by promptly syringing energy to the grid under line/generator outage contingencies. To this end, in the first place, we will develop a digital twin model along with a cloud platform derived from the Amazon Cloud Service (ACS) into the Amazon Web in order to scrutinize the online vulnerability data arising from the equivalent physical twin in real-time. Indeed, such a DTRA model can help us check the real grid’s behavior and determine how to meet the needs of the energy hub system to prevent blackouts. Additionally, a modified bat-based optimization algorithm is matched to settle the energy between the hub system and the electrical grid in furtherance of real-time analysis. To raise awareness, we will first compile how the hub system interactions can be effective in declining the vulnerability indices, and afterward, we will map out the ACS-based digital twin model on the studied case.
A Moth–Flame Optimized Echo State Network and Triplet Feature Extractor for Epilepsy Electro-Encephalography Signals
Authors: Tang Xue-song , Jiang Luchao , Hao Kuangrong , Wang Tong , Liu Xiaoyan
Published: March 2023

The analysis of epilepsy electro-encephalography (EEG) signals is of great significance for the diagnosis of epilepsy, which is one of the common neurological diseases of all age groups. With the developments of machine learning, many data-driven models have achieved great performance in EEG signals classification. However, it is difficult to select appropriate hyperparameters for the models to file a specific task. In this paper, an evolutionary algorithm enhanced model is proposed, which optimizes the fixed weights of the reservoir layer of the echo state network (ESN) according to the specific task. As evaluating a feature extractor relies heavily on the classifiers, a new feature distribution evaluation function (FDEF) using the label information of EEG signals is defined as the fitness function, which is an objective way to evaluate the performance of a feature extractor that not only focuses on the degree of dispersion, but also considers the relation amongst triplets. The performance of the proposed method is verified on the Bonn University dataset with an accuracy of 98.16% and on the CHB-MIT dataset with the highest sensitivity of 96.14%. The proposed method outperforms the previous EEG methods, as it can automatically optimize the hyperparameters of ESN to adjust the structure and initial parameters for a specific classification task. Furthermore, the optimization direction by using FDEF as the fitness of MFO no longer relies on the performance of the classifier but on the relative separability amongst classes.
A Concise Relation Extraction Method Based on the Fusion of Sequential and Structural Features Using ERNIE
Authors: Wang Yu , Wang Yuan , Peng Zhenwan , Zhang Feifan , Yang Fei
Published: March 2023

Relation extraction, a fundamental task in natural language processing, aims to extract entity triples from unstructured data. These triples can then be used to build a knowledge graph. Recently, pre-training models that have learned prior semantic and syntactic knowledge, such as BERT and ERNIE, have enhanced the performance of relation extraction tasks. However, previous research has mainly focused on sequential or structural data alone, such as the shortest dependency path, ignoring the fact that fusing sequential and structural features may improve the classification performance. This study proposes a concise approach using the fused features for the relation extraction task. Firstly, for the sequential data, we verify in detail which of the generated representations can effectively improve the performance. Secondly, inspired by the pre-training task of next-sentence prediction, we propose a concise relation extraction approach based on the fusion of sequential and structural features using the pre-training model ERNIE. The experiments were conducted on the SemEval 2010 Task 8 dataset and the results show that the proposed method can improve the F1 value to 0.902.
Application of Hybrid Model between the Technique for Order of Preference by Similarity to Ideal Solution and Feature Extractions for Bearing Defect Classification
Authors: Lee Chun-Yao , Le Truong-An , Chang Chung-Yao
Published: March 2023

This paper describes a development that offers new opportunities for detecting faulty bearings. Prioritization is based on the technique for order of preference by similarity to the ideal solution (TOPSIS) for the most discriminative features in the faulty bearing dataset. The proposed model is divided into three steps: feature extraction, feature selection, and classification. In feature extraction, variational mode decomposition (VMD) and fast Fourier transform (FFT) are used to extract features from the measured signal of the test motors and use the symmetrical uncertainty (SU) value for calculation, reducing the redundancy of data. In terms of feature selection, the TOPSIS method is used instead of the traditional filtering method, which is applied to analysis and decision making, and important features are selected from seven filtering methods. Finally, in order to validate the classification ability of the proposed model, k-nearest neighbors (KNN), support vector machine (SVM), and artificial neural networks (ANN) are used as independent classifiers. The effectiveness of the proposed model is evaluated by applying two bearing datasets, namely the current dataset of motor vibration signals and the dataset of bearing motors provided by Case Western Reserve University (CWRU). The results show that the comparison of the proposed model with other models shows the feasibility of this study.
Analysis and Projection of Transport Sector Demand for Energy and Carbon Emission: An Application of the Grey Model in Pakistan
Authors: Abbas Shujaat , Yousaf Hazrat , Khan Shabeer , Rehman Mohd Ziaur , Blueschke Dmitri
Published: March 2023

The incredible increase in carbon emissions is a major global concern. Thus, academicians and policymakers at COP26 are continuously urging to devise strategies to reduce carbon and other greenhouse gas emissions. The transportation sector is a major contributor to greenhouse gas emissions in developing countries. Therefore, this study projected an increase in fossil fuel demand for transportation and corresponding carbon dioxide emission in Pakistan from 2018 to 2030 by employing the Grey model and using annual data from 2010 to 2018. Furthermore, the determinant of fossil fuel demand is modeled using an environmental sustainability model such as stochastic regression IPAT that links environmental impact as a product of population, affluence, and technology on annual time series data spanning from 1990 to 2019. The projected values of oil demand and carbon emissions reveal an increasing trend, with average annual growth rates of 12.68% and 11.45%, respectively. The fully modified ordinary least squares (FM-OLS) findings confirmed the environmental Kuznets hypothesis. The increase in population growth emerged as the major driver for oil demand and carbon dioxide emissions, while technological advancement can reduce oil demand and corresponding carbon emissions. This study urges Pakistan to switch from oil to gas and other green energies by encouraging hybrid vehicles, as the number of vehicles on the road positively impacts the transport sector’s oil demand. Moreover, increasing economic growth and controlling the population growth rate by discouraging more children can be a valid policy for reducing oil demand and corresponding carbon emissions.
Application of Fatou’s Lemma for Strong Homogenization of Attractors to Reaction–Diffusion Systems with Rapidly Oscillating Coefficients in Orthotropic Media with Periodic Obstacles
Authors: Bekmaganbetov Kuanysh A. , Chechkin Gregory A. , Chepyzhov Vladimir V.
Published: March 2023

We study reaction–diffusion systems with rapidly oscillating terms in the coefficients of equations and in the boundary conditions, in media with periodic obstacles. The non-linear terms of the equations only satisfy general dissipation conditions. We construct trajectory attractors for such systems in the strong topology of the corresponding trajectory dynamical systems. By means of generalized Fatou’s lemma we prove the strong convergence of the trajectory attractors of considered systems to the trajectory attractors of the corresponding homogenized reaction–diffusion systems which contain an additional potential.
Quarantine and Vaccination in Hierarchical Epidemic Model
Authors: Gubar Elena , Taynitskiy Vladislav , Fedyanin Denis , Petrov Ilya
Published: March 2023

The analysis of global epidemics, such as SARS, MERS, and COVID-19, suggests a hierarchical structure of the epidemic process. The pandemic wave starts locally and accelerates through human-to-human interactions, eventually spreading globally after achieving an efficient and sustained transmission. In this paper, we propose a hierarchical model for the virus spread that divides the spreading process into three levels: a city, a region, and a country. We define the virus spread at each level using a modified susceptible–exposed–infected–recovery–dead (SEIRD) model, which assumes migration between levels. Our proposed controlled hierarchical epidemic model incorporates quarantine and vaccination as complementary optimal control strategies. We analyze the balance between the cost of the active virus spread and the implementation of appropriate quarantine measures. Furthermore, we differentiate the levels of the hierarchy by their contribution to the cost of controlling the epidemic. Finally, we present a series of numerical experiments to support the theoretical results obtained.
OFPI: Optical Flow Pose Image for Action Recognition
Authors: Chen Dong , Zhang Tao , Zhou Peng , Yan Chenyang , Li Chuanqi
Published: March 2023

Most approaches to action recognition based on pseudo-images involve encoding skeletal data into RGB-like image representations. This approach cannot fully exploit the kinematic features and structural information of human poses, and convolutional neural network (CNN) models that process pseudo-images lack a global field of view and cannot completely extract action features from pseudo-images. In this paper, we propose a novel pose-based action representation method called Optical Flow Pose Image (OFPI) in order to fully capitalize on the spatial and temporal information of skeletal data. Specifically, in the proposed method, an advanced pose estimator collects skeletal data before locating the target person and then extracts skeletal data utilizing a human tracking algorithm. The OFPI representation is obtained by aggregating these skeletal data over time. To test the superiority of OFPI and investigate the significance of the model having a global field of view, we trained a simple CNN model and a transformer-based model, respectively. Both models achieved superior outcomes. Because of the global field of view, especially in the transformer-based model, the OFPI-based representation achieved 98.3% and 94.2% accuracy on the KTH and JHMDB datasets, respectively. Compared with other advanced pose representation methods and multi-stream methods, OFPI achieved state-of-the-art performance on the JHMDB dataset, indicating the utility and potential of this algorithm for skeleton-based action recognition research.
Event-Triggered Control for Intra/Inter-Layer Synchronization and Quasi-Synchronization in Two-Layer Coupled Networks
Authors: Zhang Cheng , Zhang Chuan , Meng Fanwei , Liang Yi
Published: March 2023

This paper studies the intra/inter-layer synchronization and quasi-synchronization in two-layer coupled networks via event-triggered control, in which different layers have mutually independent topologies. First, based on Lyapunov stability theory and event-triggered thoughts, hybrid controllers are designed, respectively, for intra-layer synchronization (ALS) and inter-layer synchronization (RLS). Second, a novel event-triggered rule is proposed, under which intra-layer quasi-synchronization (ALQS) and inter-layer quasi-synchronization (RLQS) can be respectively realized, and the event-triggered frequency can be greatly reduced. Moreover, the upper bound of the synchronization error can be flexibly adjusted by changing the parameters in event-triggered conditions, and the Zeno phenomenon about event-triggered control is also discussed in this paper. Finally, numerical examples are provided to confirm the correctness and validity of the proposed scheme.
Novel Insights into the Mechanism Underlying High Polysaccharide Yield in Submerged Culture of Ganoderma lucidum Revealed by Transcriptome and Proteome Analyses
Authors: Wang Qiong , Xu Mengmeng , Zhao Liting , Chen Lei , Ding Zhongyang
Published: March 2023

Polysaccharides are crucial dietary supplements and traditional pharmacological components of Ganoderma lucidum; however, the mechanisms responsible for high polysaccharide yields in G. lucidum remain unclear. Therefore, we investigated the mechanisms underlying the high yield of polysaccharides in submerged cultures of G. lucidum using transcriptomic and proteomic analyses. Several glycoside hydrolase (GH) genes and proteins, which are associated with the degradation of fungal cell walls, were significantly upregulated under high polysaccharide yield conditions. They mainly belonged to the GH3, GH5, GH16, GH17, GH18, GH55, GH79, GH128, GH152, and GH154 families. Additionally, the results suggested that the cell wall polysaccharide could be degraded by GHs, which is beneficial for extracting more intracellular polysaccharides from cultured mycelia. Furthermore, some of the degraded polysaccharides were released into the culture broth, which is beneficial for obtaining more extracellular polysaccharides. Our findings provide new insights into the mechanisms underlying the roles that GH family genes play to regulate high polysaccharide yields in G. lucidum.
Adaptation Strategies to High Hydrostatic Pressures in Pseudothermotoga species Revealed by Transcriptional Analyses
Authors: Fenouil Romain , Pradel Nathalie , Belahbib Hassiba , Roumagnac Marie , Bartoli Manon , Ben Hania Wajdi , Denis Yann , Garel Marc , Tamburini Christian , Ollivier Bernard , Summers Zarath , Armougom Fabrice , Dolla Alain
Published: March 2023

Pseudothermotoga elfii strain DSM9442 and P. elfii subsp. lettingae strain DSM14385 are hyperthermophilic bacteria. P. elfii DSM9442 is a piezophile and was isolated from a depth of over 1600 m in an oil-producing well in Africa. P. elfii subsp. lettingae is piezotolerant and was isolated from a thermophilic bioreactor fed with methanol as the sole carbon and energy source. In this study, we analyzed both strains at the genomic and transcriptomic levels, paying particular attention to changes in response to pressure increases. Transcriptomic analyses revealed common traits of adaptation to increasing hydrostatic pressure in both strains, namely, variations in transport membrane or carbohydrate metabolism, as well as species-specific adaptations such as variations in amino acid metabolism and transport for the deep P. elfii DSM9442 strain. Notably, this work highlights the central role played by the amino acid aspartate as a key intermediate of the pressure adaptation mechanisms in the deep strain P. elfii DSM9442. Our comparative genomic and transcriptomic analysis revealed a gene cluster involved in lipid metabolism that is specific to the deep strain and that was differentially expressed at high hydrostatic pressures and might, thus, be a good candidate for a piezophilic gene marker in Pseudothermotogales.
Artificial Cultivation Changes Foliar Endophytic Fungal Community of the Ornamental Plant Lirianthe delavayi
Authors: Wu Nan-Nan , Zeng Zhao-Ying , Xu Qin-Bin , Zhang Han-Bo , Xu Tao
Published: March 2023

Many wild ornamental plant species have been introduced to improve the landscape of cities; however, until now, no study has been performed to explore the composition and function of foliar endophytes associated with cultivated rare plants in cities after their introduction. In this study, we collected the leaves of the healthy ornamental plant Lirianthe delavayi from wild and artificially cultivated habitats in Yunnan and compared their diversity, species composition, and functional predictions of their foliar endophytic fungal community based on high-throughput sequencing technology. In total, 3125 ASVs of fungi were obtained. The alpha diversity indices of wild L. delavayi populations are similar to those of cultivated samples; however, the species compositions of endophytic fungal ASVs were significantly varied in the two habitats. The dominant phylum is Ascomycota, accounting for more than 90% of foliar endophytes in both populations; relatively, artificial cultivation trends to increase the frequency of common phytopathogens of L. delavayi, such as Alternaria, Erysiphe. The relative abundance of 55 functional predictions is different between wild and cultivated L. delavayi leaves (p < 0.05); in particular, chromosome, purine metabolism, and peptidases are significantly increased in wild samples, while flagellar assembly, bacterial chemotaxis, and fatty acid metabolism are significantly enhanced in cultivated samples. Our results indicated that artificial cultivation can greatly change the foliar endophytic fungal community of L. delavayi, which is valuable for understanding the influence of the domestication process on the foliar fungal community associated with rare ornamental plants in urban environments.
Colonization Ability of Bacillus subtilis NCD-2 in Different Crops and Its Effect on Rhizosphere Microorganisms
Authors: Zhao Weisong , Ban Yiyun , Su Zhenhe , Li Shezeng , Liu Xiaomeng , Guo Qinggang , Ma Ping
Published: March 2023

Bacillus subtilis strain NCD-2 is a promising biocontrol agent for soil-borne plant diseases and shows potential for promoting the growth of some crops. The purposes of this study were to analyze the colonization ability of strain NCD-2 in different crops and reveal the plant growth promotion mechanism of strain NCD-2 by rhizosphere microbiome analysis. qRT-PCR was used to determine the populations of strain NCD-2, and microbial communities’ structures were analyzed through amplicon sequencing after application of strain NCD-2. Results demonstrated that strain NCD-2 had a good growth promotion effect on tomato, eggplant and pepper, and it was the most abundant in eggplant rhizosphere soil. There were significantly differences in the types of beneficial microorganisms recruited for different crops after application of strain NCD-2. PICRUSt analysis showed that the relative abundances of functional genes for amino acid transport and metabolism, coenzyme transport and metabolism, lipid transport and metabolism, inorganic ion transport and metabolism, and defense mechanisms were enriched in the rhizospheres of pepper and eggplant more than in the rhizospheres of cotton, tomato and maize after application of strain NCD-2. In summary, the colonization ability of strain NCD-2 for five plants was different. There were differences in microbial communities’ structure in rhizosphere of different plants after application of strain NCD-2. Based on the results obtained in this study, it was concluded that the growth promoting ability of strain NCD-2 were correlated with its colonization quantity and the microbial species it recruited.
TNFR1 Mediated Apoptosis Is Protective against Mycobacterium avium in Mice
Authors: Shundo Yuki , On Rintaro , Matsumoto Takemasa , Ouchi Hiroshi , Fujita Masaki
Published: March 2023

Mycobacterium avium is an intracellular proliferating pathogen that causes chronic refractory respiratory infection. Although apoptosis induced by M. avium has been reported in vitro, the role of apoptosis against M. avium infection in vivo remains unclear. Here, we investigated the role of apoptosis in mouse models of M. avium infection. Tumor necrosis factor receptor-1 knockout mice (TNFR1-KO) andTNFR2-KO micewere used. M. avium (1 × 107 cfu/body) was administered intratracheally to mice. Apoptosis in lungs was detected by terminal deoxynucleotidyl transferase mediated dUTP nick end labeling and lung histology as well as cell death detection kits using BAL fluids. TNFR1-KO mice were susceptible to M. avium infection compared with TNFR2-KO and wild type mice based on the bacterial number and lung histology. Higher numbers of apoptotic cells were detected in the lungs of TNFR2-KO and wild-type mice were compared with TNFR1-KO mice. The inhalation of Z-VAD-FMK deteriorated M. avium infection compared with vehicle-inhaled controls. Overexpression of Iκ-B alpha by adenovirus vector attenuated M. avium infection. Our study showed apoptosis had an important role in innate immunity against M. avium in mice. The induction of apoptosis in M. avium-infected cells might be a new strategy to control M. avium infection.
From the Mountain to the Valley: Drivers of Groundwater Prokaryotic Communities along an Alpine River Corridor
Authors: Retter Alice , Haas Johannes Christoph , Birk Steffen , Stumpp Christine , Hausmann Bela , Griebler Christian , Karwautz Clemens
Published: March 2023

Rivers are the “tip of the iceberg”, with the underlying groundwater being the unseen freshwater majority. Microbial community composition and the dynamics of shallow groundwater ecosystems are thus crucial, due to their potential impact on ecosystem processes and functioning. In early summer and late autumn, samples of river water from 14 stations and groundwater from 45 wells were analyzed along a 300 km transect of the Mur River valley, from the Austrian alps to the flats at the Slovenian border. The active and total prokaryotic communities were characterized using high-throughput gene amplicon sequencing. Key physico-chemical parameters and stress indicators were recorded. The dataset was used to challenge ecological concepts and assembly processes in shallow aquifers. The groundwater microbiome is analyzed regarding its composition, change with land use, and difference to the river. Community composition and species turnover differed significantly. At high altitudes, dispersal limitation was the main driver of groundwater community assembly, whereas in the lowland, homogeneous selection explained the larger share. Land use was a key determinant of the groundwater microbiome composition. The alpine region was more diverse and richer in prokaryotic taxa, with some early diverging archaeal lineages being highly abundant. This dataset shows a longitudinal change in prokaryotic communities that is dependent on regional differences affected by geomorphology and land use.
Coal Mine Goaf Interpretation: Survey, Passive Electromagnetic Methods and Case Study
Authors: Wang Nan , Wang Zijian , Sun Qianhui , Hui Jian
Published: March 2023

Coal mine goaf detection remains confronted with the lack of fast, effective and low-cost exploration means, especially for the accurate prediction of mining threats primarily caused by hydraulic infiltration. The rapid popularization of passive electromagnetic methods has contributed greatly to improving the interpretation effects of different types of goafs. This paper, firstly, summarizes the pros and cons of various exploration methods in goaf detection. Then, the feasibility of goaf detection using novel passive electromagnetic methods (e.g., the super low frequency alternating magnetic component method (SLF) and audio frequency magnetotelluric method (AMT)) is proposed and further discussed. With well-designed geo-electrical goaf models, the theoretical results demonstrate that the semi-quantitative interpretation of SLF responses can be directly used for the delineation of the target layer in the estimated depth range. In contrast, 3D inversion provides more information about conductive targets with the appropriate initial model selection. Then, shallow, low-resistive targets can be more accurately allocated in the inversion maps. Moreover, the real data interpretation results from study areas demonstrate that the SLF method can utilize the magnetic component responses to effectively identify the fault structures, and indirectly contributes to judge the goaf collapse locations in favor of describing the potential distribution of fracture water infiltration. Combined with the three-dimensional (3D) resistivity inversion of AMT data, the low-resistive water-rich areas within the depth of 400 m were revealed. The inverted depth distributions are basically consistent with those of the water-filled goafs and surrounding layers, which were also confirmed by known logging data. The detailed delineations of water-control fracture zones can be inferred to relate to aquifers in some mining areas; this can reveal potential collapses that require successive mining planning. In specific working faces, goaf risks have been handled in advance by strengthening the continuous monitoring of the water level and water inflow. The above verification has laid a theoretical and practical foundation for passive electromagnetic interpretation methods for effectively predicting collapse-type risks or hydraulic threats in coal mine goafs.
A New Approach to the Grinding Kinetics of Magnetite Ore Based on the Population Balance Model
Authors: Yuan Chengfang , Wu Caibin , Fang Xin , Liao Ningning , Tong Jiaqi , Li Yuqing
Published: March 2023

A new approach to batch grinding kinetics was established based on the conventional population balance model, with magnetite as the experimental object. The distribution function commonly used in the population balance model is a sum of two power functions, i.e., Bi1=φ(xi−1x1+1−φ(xi−1x1)β. Based on the new finding that the cumulative mass fraction coarser than the size class of the discharge is consistent with the first-order grinding kinetic, the gi function of the new approach is only a single power function, i.e., =+k1xia, which will greatly reduce the parameter error and make the fit more accurate. The maximum error between simulation calculations and the actual experiment using the two methods did not exceed 1%, indicating that both models can accurately predict the fracture characteristics of magnetite. Because the new approach has fewer derived parameters, it addresses the conventional population balance model’s problems of large computational effort and poor fitting accuracy, making it more applicable to the study of the impact of parameters on the grinding status, with a simpler process and higher accuracy. In addition, this new method is applicable to minerals other than magnetite. Further research is required to verify its applicability to wide size ranges and continuous grinding.
Potential Future Alternative Resources for Rare Earth Elements: Opportunities and Challenges
Authors: Balaram Vysetti
Published: March 2023

Currently, there is an increasing industrial demand for rare earth elements (REE) as these elements are now integral to the manufacture of many carbon-neutral technologies. The depleting REE ores and increasing mining costs are prompting us to consider alternative sources for these valuable metals, particularly from waste streams. Although REE concentrations in most of the alternative resources are lower than current REE ores, some sources including marine sediments, coal ash, and industrial wastes, such as red mud, are emerging as promising with significant concentrations of REE. This review focuses on the alternative resources for REE, such as ocean bottom sediments, continental shelf sediments, river sediments, stream sediments, lake sediments, phosphorite deposits, industrial waste products, such as red mud and phosphogypsum, coal, coal fly ash and related materials, waste rock sources from old and closed mines, acid mine drainage, and recycling of e-waste. Possible future Moon exploration and mining for REE and other valuable minerals are also discussed. It is evident that REE extractions from both primary and secondary ores alone are not adequate to meet the current demand, and sustainable REE recovery from the alternative resources described here is also necessary to meet the growing REE demand. An attempt is made to identify the potential of these alternative resources and sustainability challenges, benefits, and possible environmental hazards to meet the growing challenges of reaching the future REE requirements.
Boosting the Catalytic Performance of AuAg Alloyed Nanoparticles Grafted on MoS2 Nanoflowers through NIR-Induced Light-to-Thermal Energy Conversion
Authors: Rodríguez-da-Silva Sara , El-Hachimi Abdel Ghafour , López-de-Luzuriaga José M. , Rodríguez-Castillo María , Monge Miguel
Published: March 2023

MoS2 nanoflowers (NFs) obtained through a hydrothermal approach were used as the substrate for the deposition of tiny spherical bimetallic AuAg or monometallic Au nanoparticles (NPs), leading to novel photothermal-assisted catalysts with different hybrid nanostructures and showing improved catalytic performance under NIR laser irradiation. The catalytic reduction of pollutant 4-nitrophenol (4-NF) to the valuable product 4-aminophenol (4-AF) was evaluated. The hydrothermal synthesis of MoS2 NFs provides a material with a broad absorption in the Vis-NIR region of the electromagnetic spectrum. The in situ grafting of alloyed AuAg and Au NPs of very small size (2.0–2.5 nm) was possible through the decomposition of organometallic complexes [Au2Ag2(C6F5)4(OEt2)2]n and [Au(C6F5)(tht)] (tht = tetrahydrothiophene) using triisopropilsilane as reducing agent, leading to nanohybrids 1–4. The new nanohybrid materials display photothermal properties arising from NIR light absorption of the MoS2 NFs component. The AuAg-MoS2 nanohybrid 2 showed excellent photothermal-assisted catalytic activity for the reduction of 4-NF, which is better than that of the monometallic Au-MoS2 nanohybrid 4. The obtained nanohybrids were characterised by transmission electron microscopy (TEM), High Angle Annular Dark Field—Scanning Transmission Electron Microscopy—Energy Dispersive X-ray Spectroscopy (HAADF-STEM-EDS), X-ray photoelectron spectroscopy and UV-Vis-NIR spectroscopy.
Sodium Ion Pre-Intercalation of δ-MnO2 Nanosheets for High Energy Density Aqueous Zinc-Ion Batteries
Authors: Ding Yuanhao , Xue Weiwei , Chen Kaihao , Yang Chenghua , Feng Qi , Zheng Dezhou , Xu Wei , Wang Fuxin , Lu Xihong
Published: March 2023

With the merits of low cost, environmental friendliness and rich resources, manganese dioxide is considered to be a promising cathode material for aqueous zinc-ion batteries (AZIBs). However, its low ion diffusion and structural instability greatly limit its practical application. Hence, we developed an ion pre-intercalation strategy based on a simple water bath method to grow in situ δ-MnO2 nanosheets on flexible carbon cloth substrate (MnO2), while pre-intercalated Na+ in the interlayer of δ-MnO2 nanosheets (Na-MnO2), which effectively enlarges the layer spacing and enhances the conductivity of Na-MnO2. The prepared Na-MnO2//Zn battery obtained a fairly high capacity of 251 mAh g−1 at a current density of 2 A g−1, a satisfactory cycle life (62.5% of its initial capacity after 500 cycles) and favorable rate capability (96 mAh g−1 at 8 A g−1). Furthermore, this study revealed that the pre-intercalation engineering of alkaline cations is an effective method to boost the properties of δ-MnO2 zinc storage and provides new insights into the construction of high energy density flexible electrodes.