bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Based Prediction of Orphan Genes and Analysis of Different Hybrid Features of Monocot and Eudicot Plants
Authors: Gao Qijuan , Zhang Xiaodan , Yan Hanwei , Jin Xiu
Published: March 2023

Orphan genes (OGs) may evolve from noncoding sequences or be derived from older coding material. Some shares of OGs are present in all sequenced genomes, participating in the biochemical and physiological pathways of many species, while many of them may be associated with the response to environmental stresses and species-specific traits or regulatory patterns. However, identifying OGs is a laborious and time-consuming task. This paper presents an automated predictor, XGBoost-A2OGs (identification of OGs for angiosperm based on XGBoost), used to identify OGs for seven angiosperm species based on hybrid features and XGBoost. The precision and accuracy of the proposed model based on fivefold cross-validation and independent testing reached 0.90 and 0.91, respectively, outperforming other classifiers in cross-species validation via other models, namely, Random Forest, AdaBoost, GBDT, and SVM. Furthermore, by analyzing and subdividing the hybrid features into five sets, it was proven that different hybrid feature sets influenced the prediction performance of OGs involving eudicot and monocot groups. Finally, testing of small-scale empirical datasets of each species separately based on optimal hybrid features revealed that the proposed model performed better for eudicot groups than for monocot groups.
A Novel Approach for Adaptive Partial Sliding Mode Controller Design and Tuning in Non-Minimum Phase Switch-Mode Power Supplies
Authors: Salimi Mahdi
Published: March 2023

In this article, a novel systematic approach is proposed for a partial sliding mode controller (SMC) design and tuning in non-minimum phase switch-mode power supplies (SMPS). To achieve a more simplified controller in comparison with the conventional SMCs, the partial SMC (PSMC) is introduced in this article, which just requires a part of the sliding surface for controller formulation. The accuracy of the developed PSMC is proved mathematically within the entire range of operation. Since the control parameters of the PSMC are not selected by trial and error, it can maintain the stability and robustness of the closed-loop system in a broad operational range. In this regard, and to develop a systematic approach for robust control of SMPS, a constant frequency equivalent SMC is designed using the converter nominal parameters. Then, the extracted controller is combined with an adaptive component to ensure asymptotical stability against load and line changes. Considering the Lyapunov stability criteria for nonlinear systems, it is proved that the presented SPMC can be used for output voltage regulation in both discontinuous and continuous operating modes with zero steady state error. To avoid the trial and error method during the controller tuning and parameters selection, the system characteristic equation is extracted using the Jacobian approach. Considering the roots of the characteristic equation and the stable range of the closed-loop system, the controller parameters are tuned. Furthermore, in addition to simulation, the developed approach is evaluated practically using the TMS3220F2810 digital signal processor. It is shown that the dynamic response of the proposed approach is faster than the standard double-loop SMC during load and line changes. Additionally, it is seen that the developed controller is robust against model changes in both continuous and discontinuous operations.
Study on Erosion Model Optimization and Damage Law of Coiled Tubing
Authors: Zhang Binqi , Deng Jingen , Lin Hai , Xu Jie , Wang Guiping , Yan Wei , Wang Kongyang , Li Fuli
Published: March 2023

Coiled tubing (CT) is used as a velocity string to transport high-velocity gas in drainage gas recovery technology. Sand particles flowing at high speed can cause serious erosion of the pipe wall. Long-term erosion wear leads to the degradation of the string strength and can even cause local perforation. In order to study the erosion wear problem of CT, a gas–solid erosion experimental device was established for a full-size pipe with different radii of curvature. A 3D laser confocal technique was used to examine and characterize the microscopic erosion morphology of the inner wall of the CT. The CFD erosion model was selected based on the erosion test data of the inner wall of the CT, and the erosion results of the Finnie model show minimal error and good agreement compared with other models. The average value of the error of the maximum erosion rate at different radii of curvature is 8.3%. The effect of the radius of curvature, gas velocity and solid particle size on the maximum erosion rate of the inner wall of the CT was analyzed based on the Finnie model. The results reveal that erosion wear occurs on the inner wall of the CT’s outer bend. As the radius of curvature is reduced, the maximum erosion rate and area increase, and the position of the maximum erosion rate gradually shifts toward the inlet. The maximum erosion rate is positively correlated with the gas flow rate. However, as the particle size increases, the maximum erosion rate shows a trend of first increasing, then decreasing and finally stabilizing, with a critical particle size of 200 μm. This study can provide theoretical guidance and methods for improving the service life of CT. The erosion rate of the tubing in old wells can be reduced by controlling production and employing appropriate sand control methods, while the erosion rate of tubing in new wells can be reduced by adjusting the wellbore trajectory.
Study on Atomization and Dust Reduction Mechanisms of AEO-9-Charged Solution
Authors: Sun Liying , Ge Shaocheng , Chen Xi , Liu Shuo
Published: March 2023

To effectively improve the dust reduction rate of fine dust and prevent the occurrence of secondary dust, surfactant-charged water mist dust reduction technology is proposed. First, the water mist induction-charged atomization mechanism was perfected by an induction-charged spray experiment and the optimal atomization-charged voltage was determined to be 10 kV. Second, by surface tension and spray experiments on AEO-9-charged solutions, the lower the surface tension and viscosity of the solution, the better the atomization effect; the best atomization solution was 10 kV and 0.02% AEO-9. Finally, according to an electrostatic adsorption experiment, it was identified that there was an electrostatic interaction between coal dust and charged droplets. The contact angle experiment showed that the contact angle of the AEO-9 droplets decreased by 68.44% compared with water after 3 s of contact with coal dust. The wetting effect of bituminous coal was significantly improved by adding AEO-9 to water. A molecular simulation was used to study the molecular interaction mechanism among the H2O, AEO-9, and bituminous coal molecules. The simulation results showed that AEO-9 was more active than water, it easily interacted with bituminous coal, and the hydrophilic group covered the surface of the bituminous coal molecules, which increased the electrostatic interaction between the water molecules and bituminous coal surface molecules. After adding AEO-9 to H2O, the intermolecular interaction energy of the H2O/AEO-9/bituminous coal system was enhanced more than that of the H2O/bituminous coal system. This study provides the basis for the application of surfactant-charged water mist dust reduction technology.
Bacterial Foraging Algorithm for a Neural Network Learning Improvement in an Automatic Generation Controller
Authors: Al-Majidi Sadeq D. , Altai Hisham Dawood Salman , Lazim Mohammed H. , Al-Nussairi Mohammed Kh. , Abbod Maysam F. , Al-Raweshidy Hamed S.
Published: March 2023

The frequency diversion in hybrid power systems is a major challenge due to the unpredictable power generation of renewable energies. An automatic generation controller (AGC) system is utilised in a hybrid power system to correct the frequency when the power generation of renewable energies and consumers’ load demand are changing rapidly. While a neural network (NN) model based on a back-propagation (BP) training algorithm is commonly used to design AGCs, it requires a complicated training methodology and a longer processing time. In this paper, a bacterial foraging algorithm (BF) was employed to enhance the learning of the NN model for AGCs based on adequately identifying the initial weights of the model. Hence, the training error of the NN model was addressed quickly when it was compared with the traditional NN model, resulting in an accurate signal prediction. To assess the proposed AGC, a power system with a photovoltaic (PV) generation test model was designed using MATLAB/Simulink. The outcomes of this research demonstrate that the AGC of the BF-NN-based model was effective in correcting the frequency of the hybrid power system and minimising its overshoot under various conditions. The BP-NN was compared to a PID, showing that the former achieved the lowest standard transit time of 5.20 s under the mismatching power conditions of load disturbance and PV power generation fluctuation.
Static Voltage Stability Zoning Analysis Based on a Sensitivity Index Reflecting the Influence Degree of Photovoltaic Power Output on Voltage Stability
Authors: Li Sheng , Lu Yuting , Ge Yulin
Published: March 2023

The large-scale integration of photovoltaic (PV) power can bring a greatly negative influence on the grid-connected system’s voltage stability. To study the static voltage stability (SVS) of PV grid-connected systems, the traditional SVS index, L-index, was re-examined. It was firstly derived and proved that the PV active output Ppv is proportional to the voltage phase angle of the PV station’s POI (Point of Interconnection), based on a simplified two-node system integrated with a PV station operating in PV (active power—voltage) mode or PQ (active power—reactive power) mode with unit power factor. Then a novel voltage stability sensitivity index LPAS-index was proposed that takes the derivative of the L-index with respect to the POI’s voltage phase angle, so as to reflect the influence degree of Ppv on the SVS of each load node. A SVS zoning analysis method for the PV grid-connected system was designed according to the classification results of load nodes based on the proposed LPAS-index, the power grid can be zoned into three kinds of areas that reflect different correlations between the SVS and Ppv: strong correlation, moderate correlation and weak correlation. Since the LPAS-index is less impacted by Ppv, the SVS zoning results are relatively unchanged. On the basis of a classic 14-node system with PV, the practicability of the zoning analysis method was verified. The simulation results show that the PV access point in general falls within the strongly or moderately associated area with Ppv. When most of the load nodes fall within the weakly associated area with Ppv, it is not necessary to consider the impact of Ppv and load power is still the main influencing factor on the SVS. In the multi-PV case, owing to the expansion of areas more affected by Ppv, an excessive Ppv can cause adverse influence on the SVS of the whole power grid; and an effective PV power-shedding measure is proposed to solve this problem. The proposed SVS zoning analysis method can be used for reference by power grid dispatchers.
Simulation Analysis of Novel Integrated LNG Regasification-Organic Rankine Cycle and Anti-Sublimation Process to Generate Clean Energy
Authors: Suri Saadat Ullah Khan , Majeed Muhammad Khaliq , Ahmad Muhammad Shakeel
Published: March 2023

Recently, the depletion of fossil fuel reserves and the harmful environmental effects caused by burning fossil fuels have signified the supreme importance of utilizing sustainable energy reserves such as geothermal and solar energies. The advancement of the Organic Rankine Cycle as a clean energy generation path by researchers has gained momentous demand for its commercialization. The sole Organic Rankine Cycle can produce a large amount of energy in contrast to other power production cycles. To make this clean energy recovery sustainable, liquefied natural gas cold energy can be utilized through regasification to integrate the Organic Rankine Cycle with the anti-sublimation carbon dioxide capture process, merging the biogas setup. Liquefied natural gas cold energy recovery has paramount importance with aspects of energy economy and environment preservation. Liquefied natural gas regasification in shell and tube heat exchangers poses a minimal freezing risk and is high duty. Anti-sublimation of biogas is an energy-intensive process. It can be materialized from liquefied natural gas cold energy implementation through the Organic Rankine Cycle by maintaining cryogenic temperatures there. In this situation, greenhouse gas emissions can be minimized. The simulation analysis is performed based on thermodynamic and techno-economic assessments of the poly-generation energy systems. It is proved to be useful in conducting by regulating different working fluids. The optimum electric power generated is 2492 MW. While the optimum net present value, energy efficiency, and exergy efficiency of this proposed energy system are 19.5, 57.13%, and 76.20%, respectively. The governmental authorities and environmental protection can benefit from this scientific research work to create an environmentally friendly atmosphere and energy for contemporary society.
Chemical and Microbiological Techniques for Recovery and/or Removal of Elements from Incinerated Sewage Sludge Ash—A Review of Basic Methods
Authors: Kasina Monika , Jarosz Kinga
Published: March 2023

In the face of material shortages, growing environmental awareness, and technical advancement, incinerated waste materials are being considered secondary resources. Especially incinerated sewage sludge ash is of interest due to its massive and increasing production and relatively stable composition with a satisfying concentration of elements of value. This paper revises the basic methods for recovery of valuable components from incineration sewage sludge and simultaneous removal or stabilization of elements that may negatively influence the environment with further ash usage or storage. The presented work focuses on collating and analysing the efficiency of currently used approaches as well as their limitations and perspectives for future development. Chemical methods analysed include acidic and alkaline leaching, chelating, and sequential leaching. Due to scarce examples from literature, the exploration of a microbiological approach focuses on the mechanisms and potential for application of different microorganisms for element extraction. The methods described are relatively efficient and affordable, yet still need further development. Specifically, microbiological approaches are rarely used for incineration sewage sludge treatment regardless of their potential advantages over other approaches. Constant mineral and chemical composition within one incineration plant can vary among plants due to many factors, so a well-established range of techniques and an individual approach are important.
A Novel Computation of Delay Margin Based on Grey Wolf Optimisation for a Load Frequency Control of Two-Area-Network Power Systems
Authors: Ibrahim Mohammad Haziq , Peng Ang Swee , Dani Muhammad Norfauzi , Khalil Ashraf , Law Kah Haw , Yunus Sharina , Rahman Mohammad Ishlah , Au Thien Wan
Published: March 2023

In classical power systems, frequency measurements are transferred via a specialised communication channel, resulting in time delay. The time delay plays a major role in a power system, which can reduce the dynamic performance of the load–frequency control (LFC) system and can destabilise the system. The research to date has tended to focus on developing a new algorithm to determine the delay margin (DM) rather than looking into a hybrid algorithm which includes a nature-inspired metaheuristic optimisation technique. This paper introduces a novel method for computing the DM based on grey wolf optimisation (GWO), specifically for the constant time delay. In the proposed method, GWO is employed to optimise the minimum error of the spectral radius and to determine the best design variable of the crossing frequency. With the help of the proposed method, the sweeping range is no longer required, which improves the accuracy of the result. To evaluate the proposed method, a two-area network power system is considered as a case study. Furthermore, the effect of the PI controller gains on the DM is taken into account. The proposed method efficacy is demonstrated by comparing it with the most recently published methods. The results demonstrate that the proposed method is remarkably better than the existing methods found in the literature, where the smallest percentage inaccuracy using the simulation-based DM based on GWO is found to be 0.000%.
A CFD Study on the Effects of Injection Timing and Spray Inclusion Angle on Performance and Emission Characteristics of a DI Diesel Engine Operating in Diffusion-Controlled and PCCI Modes of Combustion
Authors: Cengiz Cengizhan , Unverdi Salih Ozen
Published: March 2023

In three-dimensional (3D) computational fluid dynamics (CFD) simulations, the effects of injection timing and spray inclusion angle (SIA) on performance and emissions of diffusion-controlled and Premixed Charge Compression Ignition (PCCI) combustion in part load for a heavy-duty direct injection (HDDI) diesel engine are studied. The start of injection (SOI) of a 146° SIA injector is varied between −70 and −10 °crank angle (°CA) after top dead center (ATDC). For −50 °CA ATDC SOI with various SIAs between 80° and 146°, PCCI combustion reduces mono-nitrogen oxide (NOx) emissions significantly compared to conventional diesel combustion (CDC). Due to incomplete combustion in rich zones formed by droplet–cylinder wall interaction, early wide SIA injection deteriorates combustion efficiency (CE) and Indicated Mean Effective Pressure (IMEP) and increases soot and carbon monoxide (CO) emissions. Narrow-angle sprays interacting with the piston bowl elevate CE and IMEP and decrease soot and CO emissions but increases NOx emissions. Optimal combustion is achieved by avoiding fuel droplet–cylinder wall interaction. By spray-targeting at the stepped lip of the piston bowl, 100° SIA and −50 °CA ATDC SOI yield, respectively, the highest CE and IMEP: 97.8% and 3.37 bar and the lowest soot and CO emissions: 33.5 and 2.2 ppm, with acceptable NOx emissions.
Partial Discharge Localization Techniques: A Review of Recent Progress
Authors: Chan Jun Qiang , Raymond Wong Jee Keen , Illias Hazlee Azil , Othman Mohamadariff
Published: March 2023

Monitoring the partial discharge (PD) activity of power equipment insulation is crucial to ensure uninterrupted power system operation. PD occurrence is highly correlated to weakened insulation strength. If PD occurrences are left unchecked, unexpected insulation breakdowns may occur. The comprehensive PD diagnostic process includes the detection, localization, and classification of PD. Accurate PD source localization is necessary to locate the weakened insulation segment. As a result, rapid and precise PD localization has become the primary focus of PD diagnosis for power equipment insulation. This paper presents a review of different approaches to PD localization, including conventional, machine learning (ML), and deep learning (DL) as a subset of ML approaches. The review focuses on the ML and DL approaches developed in the past five years, which have shown promising results over conventional approaches. Additionally, PD detection using conventional, unconventional, and a PCB antenna designed based on UHF techniques is presented and discussed. Important benchmarks, such as the sensors used, algorithms employed, algorithms compared, and performances, are summarized in detail. Finally, the suitability of different localization techniques for different power equipment applications is discussed based on their strengths and limitations.
A Systematic Review of Carbon Capture, Utilization and Storage: Status, Progress and Challenges
Authors: Liu Enbin , Lu Xudong , Wang Daocheng
Published: March 2023

The problem of global warming and climate change has attracted global attention, and reducing the concentration of CO2 in the atmosphere is an important step towards solving the problem. This paper mainly introduces the current development status, research hotspots, challenges and some emerging technologies of carbon capture, utilization and storage (CCUS). Among CO2 capture technologies, solvent absorption technology is currently the most mature and widely used technology, among which ionic liquid technology has great application prospects because its molecular structure can be designed and different functional groups can be connected. The surface functionalization of metal–organic frameworks in the adsorption method endows them with excellent CO2 adsorption capacity. In CO2 transportation, temperature and pressure must be considered in pipeline transportation, because they will affect the phase state of CO2 transportation. The impact of impurities on CO2 pipeline transportation is a challenge that affects pipeline design and transportation safety. In CO2 utilization, the key to enhanced oil recovery, gas recovery and displacement of coalbed methane is to increase the recovery rate and increase the storage capacity at the same time. Only by strengthening the research on the adsorption behavior between CO2 and CH4 and revealing the relevant mechanism can innovative technologies be developed. The chemical utilization of CO2 has formed many routes, but they all lack certain advantages. Most scholars are working on catalysts for CO2 conversion, especially copper-based catalysts that can convert CO2 into methanol. The conversion rate of CO2 can be effectively increased through doping or process improvement. The coupling of electrocatalytic technology and renewable energy is an important development direction in the future. In CO2 storage, geological storage is currently the most important method, especially in saline aquifers. There are currently critical issues concerning reservoir integrity and leakage potential that should be further investigated. CO2 leakage will cause serious environmental problems, and the common monitoring methods are reviewed and discussed in this paper. Finally, the research status, hotspots and cooperation networks of CCUS are summarized by using CiteSpace software in order to help the development of CCUS technology. In addition, through the review and analysis, it is found that CCUS is faced with challenges such as low capture efficiency, difficulties in transformation and utilization, high operating costs, lack of strong support policies, and lack of international cooperation, which restrict the further development of CCUS.
Gas Hydrates: Applications and Advantages
Authors: Gaidukova Olga , Misyura Sergey , Morozov Vladimir , Strizhak Pavel
Published: March 2023

Gas hydrates are promising components for a wide range of industries and the national economy. This paper outlines the gas hydrate application areas with the greatest potential. Gas hydrates of methane, ethane, propane, carbon dioxide and freon were investigated. Double gas hydrates were found to be coming into use. Natural and artificial hydrates are now being exploited. The main properties and component composition of hydrates, as well as their extraction methods are described. The key aspects of using hydrates in the energy industry, gas chemistry and petrochemistry, heat exchange systems and fire safety management are highlighted. These specific aspects were identified by analyzing the known experimental findings, results of mathematical modeling, bench and field tests, as well as trial runs of industrial systems. The recent advances in science and technology in this field were analyzed. The range of tasks that need to be tackled to improve the efficiency of using gas hydrates are defined.
Optimization of Fracturing Parameters by Modified Genetic Algorithm in Shale Gas Reservoir
Authors: Zhou Xin , Ran Qiquan
Published: March 2023

Shale gas reservoirs have extremely low porosity and permeability, making them challenging to exploit. The best method for increasing recovery in shale gas reservoirs is horizontal well fracturing technology. Hence, fracturing parameter optimization is necessary to enhance shale gas horizontal fracturing well production. Traditional optimization methods, however, cannot meet the requirements for overall optimization of fracturing parameters. As for intelligent optimization algorithms, most have excellent global search capability but incur high computation costs, which limits their usefulness in real-world engineering applications. Thus, a modified genetic algorithm combined based on the Spearman correlation coefficient (SGA) is proposed to achieve the rapid optimization of fracturing parameters. SGA determines the crossover and mutation rates by calculating the Spearman correlation coefficient instead of randomly determining the rates like GA does, so that it could quickly converge to the optimal solution. Within a particular optimization time, SGA could perform better than GA. In this study, a production prediction model is established by the XGBoost algorithm based on the dataset obtained by simulating the shale gas multistage fracturing horizontal well development. The result shows that the XGBoost model performs well in predicting shale gas fracturing horizontal well production. Based on the trained XGBoost model, GA, SGA, and SGD were used to optimize the fracturing parameters with the 30-day cumulative production as the optimization objective. This process has conducted nine fracturing parameter optimization tests under different porosity and permeability conditions. The results show that, compared with GA and SGD, SGA has faster speed and higher accuracy. This study’s findings can help optimize the fracturing parameters faster, resulting in improving the production of shale gas fracturing horizontal wells.
Charter Schools: An Alternative Option in American Schooling
Authors: Tong Tong , Smith Shelby Leigh , Fienberg Michael , Kho Adam
Published: March 2023

Charter schools are educational institutions in the United States funded through taxation but operated privately under a charter or contract with a public entity, providing alternative public education options to families. Charter schools are subject to fewer rules and regulations and have greater autonomy than traditional public schools over operations, curriculum, and instruction, although have greater stakes in school accountability.
A SWOT Analysis of AWH Project Implementation in the Brazilian Amazon as Perceived by Affordable Housing Stakeholders
Authors: Lima Maria de Fátima de Brito , Souza Álvaro Nogueira de , Teixeira Divino Eterno , Souza Hallefy Junio de , Matricardi Eraldo Aparecido Trondoli , Miguel Éder Pereira , Borges Luís Antônio Coimbra , Silva Márcio Lopes da
Published: March 2023

In Brazil, affordable housing programs aimed at low-income populations reach a limited number of people. In the northern region, conventional bricklaying is the preferred method of building affordable single-family houses, which are essentially sets of tiny houses on the outskirts of cities. Conventional bricklaying can damage the environment. This study, started in July 2019, aimed to understand the perception of using timber to build affordable houses by housing program stakeholders and determine why the beneficiaries of housing programs prefer brick houses to wooden houses in locations with building permits. We applied a SWOT analysis to a group of 60 individuals comprising government agents and wooden and brick house residents of cities located in the northern region of Brazil. Subsequently, we devised relevant strategies, validated by stakeholders involved in public policy, for the provision of wooden housing for low-income populations. We used R software to analyze the data, and the results showed that the beneficiaries of affordable housing programs were unaware of wooden architectural projects and their durability, despite the regional abundance of wood and its environmental benefits. We suggest using strategies based on the SWOT analysis and validated by a group of experts to include the Affordable Wooden Housing (AWH) Project in the National Rural Housing Program (PNHR) and Harvest Plan.
Impacts of Exotic Pests on Forest Ecosystems: An Update
Authors: Guo Qinfeng , Potter Kevin M. , Ren Hai , Zhang Peixia
Published: March 2023

Pests (e.g., insects, pathogens) affect forest communities through complex interactions with plants, other animals, and the environment. While the effects of exotic (non-native) pests on trees received broad attention and were extensively studied, fewer studies addressed the ecosystem-level consequences of these effects. Related studies so far mostly only targeted a very few dominant pests (e.g., hemlock woolly adelgid—HWA, beech bark disease—BBD, and spongy moth—SM) and were limited to aspects of the complex situation such as (1) pests’ direct physical disturbance to forest ecosystems, (2) altered geochemical elements of soils, water, and air (e.g., excretion), and (3) feedback effects from the alteration of ecosystems on plants, native insects, and present and future pest invasions. New studies also show that, in general, planted forests appear to be more prone to exotic pest invasions and thus suffer greater impacts than natural forests. Integrated studies are critically needed in the future to address (1) direct/indirect interactions of pests with ecosystem elements, (2) both short- and long-term effects, and (3) feedback effects. We discuss the implications of the new findings and corresponding management strategies.
Growth Characteristics of Seven Willow Species Distributed in Eastern Japan in Response to Compost Application
Authors: Kayama Masazumi , Kikuchi Satoshi , Uemura Akira , Takahashi Masayoshi
Published: March 2023

To establish a short rotation coppice (SRC) system in the temperate region of East Asia, planting was conducted for cuttings from seven species, including Salix eriocarpa, S. gilgiana, S. gracilistyla, S. integra, S. sachalinensis, S. serissaefolia, and S. subfragilis, with wide distribution in eastern Japan. During cultivation, cheap compost derived from swine manure and containing high concentrations of various nutrients was added. Three treatment groups, including control, low manure (5 Mg ha−1), and high manure (10 Mg ha−1) treatments, were established, and seven willows were grown for two complete growing seasons to obtain the clone density of 10,000 cuttings ha−1. The manure treatments accelerated the growth of all the willow species after two growing seasons. The averages of annual biomass production of seven willows grown under the control, low manure, and high manure treatments were 0.2 Mg ha−1yr−1, 5.3 Mg ha−1yr−1, and 8.5 Mg ha−1yr−1, respectively. By comparing with the biomasses of seven willows, the largest annual biomass production rates of 14.1 and 13.7 Mg ha−1yr−1 were observed in the high manure treatments of S. sachalinensis and S. subfragilis, respectively. For two species under the high manure treatment, S. sachalinensis had the thickest shoots, and S. subfragilis had the tallest shoots. These growth characteristics of S. sachalinensis and S. subfragilis originate from their high biomass production. Overall, these results suggest that S. sachalinensis and S. subfragilis are potentially feasible candidates for the SRC system in temperate regions of East Asia.
Quantifying the Potential Vegetation Distribution under Climate Change: The Case of Cryptomeria fortunei in Dongting Lake Watershed, China
Authors: Huang Lintong , Luo Mingke , Jiang Xia , Zhang Peng , Wang Hongxiang , Hong Fengtian , He Ning , Guo Wenxian , Niu Yong
Published: March 2023

Potential vegetation distribution is an important study in environmental sciences. We utilized the Mixed Least Squares–Total Least Squares (MLS-TLS) method and the Signal Mode Decomposition method and the Ecological Niche model to identify the inter-correlations of internal climate change factors and constructed an environmental factor response regression model. We identified the resonance periods and trend relationships among climate factors (temperature, precipitation, and evapotranspiration) and found that the evapotranspiration of the watershed interferes with the correlation between temperature and precipitation on a five-year scale. The specific change degree of extreme climate indicators in the region was quantified by the Range of Variability Approach, among which the precipitation indicators were all below 33% (low change). There were significant differences between the key bioclimatic variables and Aspect of the development of suitable vegetation habitats. The difference between the Aspect and average daily air temperature is the main contributor to the spatial distribution of vegetation, and the mutual contribution is 76.19%. Our regression model can effectively simulate the potential distribution of vegetation (r = 0.854). Compared to the MaxEnt model, our regression model can quantitatively and intuitively provide suitable habitat values for Cryptomeria fortunei at any given location in the basin. Under future scenarios (2021–2040), suitable habitat for Cryptomeria fortunei in the eastern and western regions of the basin is projected to deteriorate further. The research results can provide some help for policymakers to eliminate the potential adverse effects of future climate change on regional ecology.
MS-FRCNN: A Multi-Scale Faster RCNN Model for Small Target Forest Fire Detection
Authors: Zhang Lin , Wang Mingyang , Ding Yunhong , Bu Xiangfeng
Published: March 2023

Unmanned aerial vehicles (UAVs) are widely used for small target detection of forest fires due to its low-risk rate, low cost and high ground coverage. However, the detection accuracy of small target forest fires is still not ideal due to its irregular shape, different scale and how easy it can be blocked by obstacles. This paper proposes a multi-scale feature extraction model (MS-FRCNN) for small target forest fire detection by improving the classic Faster RCNN target detection model. In the MS-FRCNN model, ResNet50 is used to replace VGG-16 as the backbone network of Faster RCNN to alleviate the gradient explosion or gradient dispersion phenomenon of VGG-16 when extracting the features. Then, the feature map output by ResNet50 is input into the Feature Pyramid Network (FPN). The advantage of multi-scale feature extraction for FPN will help to improve the ability of the MS-FRCNN to obtain detailed feature information. At the same time, the MS-FRCNN uses a new attention module PAM in the Regional Proposal Network (RPN), which can help reduce the influence of complex backgrounds in the images through the parallel operation of channel attention and space attention, so that the RPN can pay more attention to the semantic and location information of small target forest fires. In addition, the MS-FRCNN model uses a soft-NMS algorithm instead of an NMS algorithm to reduce the error deletion of the detected frames. The experimental results show that, compared to the baseline model, the proposed MS-FRCNN in this paper achieved a better detection performance of small target forest fires, and its detection accuracy was 5.7% higher than that of the baseline models. It shows that the strategy of multi-scale image feature extraction and the parallel attention mechanism to suppress the interference information adopted in the MS-FRCNN model can really improve the performance of small target forest fire detection.
Genome-Wide Identification and Expression Analysis of CesA Gene Family in Corymbia citriodora
Authors: Wang Chubiao , Huang Anying , He Wenliang , Ou Yuduan , Lu Wanhong , Lin Yan , Wang Peng , Luo Jianzhong
Published: March 2023

The CesA proteins are key players in cellulose synthesis. Eucalyptus is well-known for cellulose synthesis, although the mechanism of cellulose synthesis is largely unknown. In this study, 11 CcCesA genes were identified by comprehensive bioinformatics analysis in Corymbia citriodora, a eucalypt species. CcCesA genes were generally conserved in each subfamily. Among them, four genes lacked a transmembrane domain in the N-terminal. We showed that genes of CesA2, 4, 5, and 8 may regulate the synthesis of secondary cell walls (SCWs) through phylogenetic trees analysis. Two pairs of segmental duplication and one pair of tandem duplication were detected in CcCesAs. Analysis of Ka/Ks ratios revealed that the duplicated genes were under negative or purifying selection. Numerous cis-acting elements related to plant hormones and light reactions were identified in the promoters of CcCesAs. Expression analysis confirmed that genes of CesA2, 4, and 8 regulate the synthesis of SCWs, and CesA8, in particular, had the highest expression compared with other genes. The results will help us understand the complexity of the CcCesAs in different diameters at breast height and provide valuable information for future functional characterization of specific genes in C. citriodora.
TSBA-YOLO: An Improved Tea Diseases Detection Model Based on Attention Mechanisms and Feature Fusion
Authors: Lin Ji , Bai Di , Xu Renjie , Lin Haifeng
Published: March 2023

Tea diseases have a significant impact on the yield and quality of tea during the growth of tea trees. The shape and scale of tea diseases are variable, and the tea disease targets are usually small, with the intelligent detection processes of tea diseases also easily disturbed by the complex background of the growing region. In addition, some tea diseases are concentrated in the entire area of the leaves, needing to be inferred from global information. Common target detection models are difficult to solve these problems. Therefore, we proposed an improved tea disease detection model called TSBA-YOLO. We use the dataset of tea diseases collected at the Maoshan Tea Factory in China. The self-attention mechanism was used to enhance the ability of the model to obtain global information on tea diseases. The BiFPN feature fusion network and adaptively spatial feature fusion (ASFF) technology were used to improve the multiscale feature fusion of tea diseases and enhance the ability of the model to resist complex background interference. We integrated the Shuffle Attention mechanism to solve the problem of difficult identifications of small-target tea diseases. In addition, we used data-enhancement methods and transfer learning to expand the dataset and relocate the parameters learned from other plant disease datasets to enhance tea diseases detection. Finally, SIoU was used to further improve the accuracy of the regression. The experimental results show that the proposed model is good at solving a series of problems encountered in the intelligent recognition of tea diseases. The detection accuracy is ahead of the mainstream target detection models, and the detection speed reaches the real-time level.
Research on the Combustion Characteristics of Coal Piles and the Fire Risks of Closed Coal Bunkers
Authors: Zhao Lihong , Fang Ping , Wang Zhenhua , Zhao Jinlong , Xiao Niqi
Published: March 2023

Closed coal bunkers emerged as a novel form of coal storage for coal-fired power stations. Nevertheless, heat builds continually in the storage process because of the constant oxidation of coal and combined with the impact of a confined coal bunker environment, it is difficult for heat to dissipate, resulting in frequent coal bunker fires. Consequently, research on coal pile combustion characteristics is crucial to the design of coal bunker safety. The experimental platform was set up in this study to conduct combustion tests of various specifications, and the burning rate, flame height, flame temperature, and heat radiation flux were analyzed to identify the critical parameters impacting coal bunker safety. First, the maximum burning rate of coal heaps during steady burning was calculated, improving coal pile combustion theory and providing guidance for coal bunker design. Second, the maximum flame height was determined, which can provide an important design guide for coal bunker height designs. In addition, it was discovered that high temperatures in flames, smoke, and smoldering coal might cause coal bunker buildings to collapse, so future designs should strengthen coal bunker fire resistance and keep the coal pile away from the load-bearing structures to prevent collapse from excessive temperatures. Moreover, the diameter of coal piles has an influence on the heat flow. For this reason, a coal bunker’s design must consider the coal pile’s fire separation distance from the coal bunker and avoid large coal piles. Consequently, the study gives recommendations and support for planning coal bunker safety and enriches experimental data for coal pile fires.
Cross-Correlation Multifractal Analysis of Technological Innovation, Financial Market and Real Economy Indices
Authors: Ke Jinchuan , Duan Yu , Xu Chao , Zhang Yue
Published: March 2023

Technological innovation, the financial market, and the real economy are mutually promoting and restricting. Considering the interference of market-noise information, this paper applies the wavelet-denoising method of the soft- and hard-threshold compromise functions to process the original information so as to eliminate the noise information, and combines multifractal detrended cross-correlation analysis with the sliding-window approach, focusing on the change in the Hurst index and the parameter change in the multifractal spectrum to explore the interaction in between. The research results show that there is a certain cross-correlation among technological-innovation, financial-market, and real-economy indices. Firstly, the cross-correlation among them has significant multifractal characteristics rather than single-fractal characteristics. Secondly, the fractal characteristics reveal the long memory of the interaction among the three indices. Thirdly, there are also obvious differences in the degree of local chaos and volatility of the interaction. Fourthly, the cross-correlation among technological-innovation, financial-market, and real-economy indices has significant multifractal characteristics rather than single-fractal characteristics. In comparison, the cross-correlation multifractal characteristics among technological innovation, the financial market, and the real economy are time-varying, and the cross-correlation multifractal characteristics between the technological-innovation index and the real-economy index are the most obvious.
Efficient Decentralized Leadership under Hybrid Work and Attachment to Regions
Authors: Aoyama Naoto , Silva Emilson Caputo Delfino
Published: March 2023

Under the ‘new normal’ in the labor market, individuals can work remotely or in person, a hybrid work mode that became ubiquitous during the pandemic. This paper studies the efficiency of decentralized leadership in federations in which hybrid work is the modus operandi. Self-interested regional governments and a benevolent central government interact strategically in dynamic games in which there are provisions of federal and regional public goods and interregional income and fiscal transfers, the population is attached to regions and hybrid work creates a common labor market in the federation. In this setting, we first show that decentralized leadership is inefficient if the center controls income transfers only. This result provides an efficiency enhancing motivation for the center to additionally control earmarked transfers: we demonstrate that decentralized leadership is efficient whenever the center controls both income and earmarked transfers. However, this is not the only federal regime in which decentralized leadership is efficient. It is efficient in the absence of earmarked transfers if it is appropriately selective: when the regional governments commit to the provision of the federal public only and the center redistributes income across regions.
Risk-Stratified Breast Cancer Screening Incorporating a Polygenic Risk Score: A Survey of UK General Practitioners’ Knowledge and Attitudes
Authors: Ayoub Aya , Lapointe Julie , Nabi Hermann , Pashayan Nora
Published: March 2023

A polygenic risk score (PRS) quantifies the aggregated effects of common genetic variants in an individual. A ‘personalised breast cancer risk assessment’ combines PRS with other genetic and nongenetic risk factors to offer risk-stratified screening and interventions. Large-scale studies are evaluating the clinical utility and feasibility of implementing risk-stratified screening; however, General Practitioners’ (GPs) views remain largely unknown. This study aimed to explore GPs’: (i) knowledge of risk-stratified screening; (ii) attitudes towards risk-stratified screening; and (iii) preferences for continuing professional development. A cross-sectional online survey of UK GPs was conducted between July–August 2022. The survey was distributed by the Royal College of General Practitioners and via other mailing lists and social media. In total, 109 GPs completed the survey; 49% were not familiar with the concept of PRS. Regarding risk-stratified screening pathways, 75% agreed with earlier and more frequent screening for women at high risk, 43% neither agreed nor disagreed with later and less screening for women at lower-than-average risk, and 55% disagreed with completely removing screening for women at much lower risk. In total, 81% felt positive about the potential impact of risk-stratified screening towards patients and 62% felt positive about the potential impact on their practice. GPs selected training of healthcare professionals as the priority for future risk-stratified screening implementation, preferring online formats for learning. The results suggest limited knowledge of PRS and risk-stratified screening amongst GPs. Training—preferably using online learning formats—was identified as the top priority for future implementation. GPs felt positive about the potential impact of risk-stratified screening; however, there was hesitance and disagreement towards a low-risk screening pathway.
Terrain Ruggedness and Canopy Height Predict Short-Range Dispersal in the Critically Endangered Black-and-White Ruffed Lemur
Authors: Mancini Amanda N. , Chandrashekar Aparna , Lahitsara Jean Pierre , Ogbeta Daisy Gold , Rajaonarivelo Jeanne Arline , Ranaivorazo Ndimbintsoa Rojoarinjaka , Rasoazanakolona Joseane , Safwat Mayar , Solo Justin , Razafindraibe Jean Guy , Razafindrakoto Georges , Baden Andrea L.
Published: March 2023

Dispersal is a fundamental aspect of primates’ lives and influences both population and community structuring, as well as species evolution. Primates disperse within an environmental context, where both local and intervening environmental factors affect all phases of dispersal. To date, research has primarily focused on how the intervening landscape influences primate dispersal, with few assessing the effects of local habitat characteristics. Here, we use a landscape genetics approach to examine between- and within-site environmental drivers of short-range black-and-white ruffed lemur (Varecia variegata) dispersal in the Ranomafana region of southeastern Madagascar. We identified the most influential drivers of short-range ruffed lemur dispersal as being between-site terrain ruggedness and canopy height, more so than any within-site habitat characteristic evaluated. Our results suggest that ruffed lemurs disperse through the least rugged terrain that enables them to remain within their preferred tall-canopied forest habitat. Furthermore, we noted a scale-dependent environmental effect when comparing our results to earlier landscape characteristics identified as driving long-range ruffed lemur dispersal. We found that forest structure drives short-range dispersal events, whereas forest presence facilitates long-range dispersal and multigenerational gene flow. Together, our findings highlight the importance of retaining high-quality forests and forest continuity to facilitate dispersal and maintain functional connectivity in ruffed lemurs.