bluuebunny/crossref_metadata_2025 huggingface dataset:
RIFIS: A Novel Rice Field Sidewalk Detection Dataset for Walk-Behind Hand Tractor
Authors: Crisnapati Padma Nyoman , Maneetham Dechrit
Published: September 2022

Rice field sidewalk (RIFIS) identification plays a crucial role in enhancing the performance of agricultural computer applications, especially for rice farming, by dividing the image into areas of rice fields to be ploughed and the areas outside of rice fields. This division isolates the desired area and reduces computational costs for processing RIFIS detection in the automation of ploughing fields using hand tractors. Testing and evaluating the performance of the RIFIS detection method requires a collection of image data that includes various features of the rice field environment. However, the available agricultural image datasets focus only on rice plants and their diseases; a dataset that explicitly provides RIFIS imagery has not been found. This study presents an RIFIS image dataset that addresses this deficiency by including specific linear characteristics. In Bali, Indonesia, two geographically separated rice fields were selected. The initial data collected were from several videos, which were then converted into image sequences. Manual RIFIS annotations were applied to the image. This research produced a dataset consisting of 970 high-definition RGB images (1920 × 1080 pixels) and corresponding annotations. This dataset has a combination of 19 different features. By utilizing our dataset for detection, it can be applied not only for the time of rice planting but also for the time of rice harvest, and our dataset can be used for a variety of applications throughout the entire year.
Security Analysis of DBTRU Cryptosystem
Authors: Tong Xiaofei , Bi Jingguo , Duan Yufei , Li Lixiang , Wang Licheng
Published: September 2022

DBTRU was proposed by Thang and Binh in 2015. As a variant of NTRU, the integer polynomial ring is replaced by two binary truncated polynomial rings GF(2)[x]/(xn+1). DBTRU has some advantages over NTRU in terms of security and performance. In this paper, we propose a polynomial-time linear algebra attack against the DBTRU cryptosystem, which can break DBTRU for all recommended parameter choices. The paper shows that the plaintext can be achieved in less than 1 s via the linear algebra attack on a single PC.
On the Solvability of the Discrete s(x,·)-Laplacian Problems on Simple, Connected, Undirected, Weighted, and Finite Graphs
Authors: Pietrusiak Filip , Wieteska Renata , Gordinowicz Przemysław
Published: September 2022

We use the finite dimensional monotonicity methods in order to investigate problems connected with the discrete sx,·-Laplacian on simple, connected, undirected, weighted, and finite graphs with nonlinearities given in a non-potential form. Positive solutions are also considered.
Automated Caries Screening Using Ensemble Deep Learning on Panoramic Radiographs
Authors: Bui Toan Huy , Hamamoto Kazuhiko , Paing May Phu
Published: September 2022

Caries prevention is essential for oral hygiene. A fully automated procedure that reduces human labor and human error is needed. This paper presents a fully automated method that segments tooth regions of interest from a panoramic radiograph to diagnose caries. A patient’s panoramic oral radiograph, which can be taken at any dental facility, is first segmented into several segments of individual teeth. Then, informative features are extracted from the teeth using a pre-trained deep learning network such as VGG, Resnet, or Xception. Each extracted feature is learned by a classification model such as random forest, k-nearest neighbor, or support vector machine. The prediction of each classifier model is considered as an individual opinion that contributes to the final diagnosis, which is decided by a majority voting method. The proposed method achieved an accuracy of 93.58%, a sensitivity of 93.91%, and a specificity of 93.33%, making it promising for widespread implementation. The proposed method, which outperforms existing methods in terms of reliability, and can facilitate dental diagnosis and reduce the need for tedious procedures.
Re-Examining the Effects of Official Development Assistance on Foreign Direct Investment Applying the VAR Model
Authors: Ono Saori , Sekiyama Takashi
Published: September 2022

This study re-examined the effect of official development assistance (ODA) of five major donor countries (France, Germany, Japan, the United Kingdom, and the United States) on foreign direct investment (FDI) using panel data from 2003 to 2020. In addition to the system Generalized Method of Moments (GMM) with the gravity model, the Granger causality test and impulse response analysis with the panel VAR model was conducted. It was concluded that ODA did not necessarily have an effect on FDI since the 2000s. It is also suggested that the vanguard effect of Japanese ODA, as indicated by some previous studies, appeared mainly in the 1990s and may not be sustainable. The novelty of this study is to verify the effects of the ODA of major donors on FDI using new data from the 2000s onward, especially to reveal that the vanguard effect of Japanese ODA has not been observed since the 2000s. A limitation of this study is to determine only the presence or absence of a general trend at a statistically significant level. Therefore, further research on individual cases is expected to find how ODA has affected the investment decisions of individual companies.
Fragmented Flying Geese (FFG) and Intra-Regional Agglomeration: Towards a Model Explaining Location Shifting of Japanese Multinational Corporations and the Electric Value Chains of ASEAN Economies
Authors: Bui Minh Tam , Miura Rumi , Saito Masami , Shibata Yusuke , Suenaga Keiichiro
Published: September 2022

In this article, we study corporate behavior and develop a model for trends and factors in Japanese Multinational Corporations (MNCs) in the electrical and electronic industry that have played an important role in the economic development of East and Southeast Asia. We focus on Thailand, where Japanese MNCs are still increasing, and examine the practical applicability of the model. Basically, the model will be developed based on the existing flying geese model and regional agglomeration, but it will also be developed to explain new events such as progress in the division of labor by fragmentation and intra-regional agglomeration in East and Southeast Asia. Japanese MNCs in the electrical and electronic industry have shifted their production bases to developing countries one after another, as a variant of the third type of flying geese model. While the network of the international division of labor is forming with the development of fragmentation, the area around the eastern seaboard from Bangkok is playing an increasingly important role in the network of Japanese companies. In that sense, this study contributes to the body of literature on flying geese models with a modified model embodied with dynamic and systematic features of the ASEAN integrated economies.
Effect of Components and Operating Conditions on the Performance of PEM Electrolyzers: A Review
Authors: Ahmed Khaja Wahab , Jang Myeong Je , Park Moon Gyu , Chen Zhongwei , Fowler Michael
Published: September 2022

Hydrogen is considered to be the fuel of the future and with the advancement of fuel cell technology, there is a renewed interest in hydrogen production by the electrolysis of water. Among low-temperature water electrolysis options, polymer electrolyte membrane (PEM) electrolyzer is the preferred choice due to its compact size, intermittent use, and connectivity with renewable energy. In addition, it is possible to generate compressed hydrogen directly in the PEM electrolyzer, thereby reducing the additional pressurization cost for hydrogen storage. The development of electrocatalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is a major focus of electrolysis research. Other components, such as PEMs, gas diffusion layers (GDL), and bipolar plates (BPs) have also received significant attention to enhance the overall efficiency of PEM electrolyzers. Improvements in each component or process of the PEM electrolyzer have a significant impact on increasing the energy efficiency of the electrolyzer. This work discusses various synthesis techniques to improve the dispersion of OER electrocatalyst and reducing catalyst loading for the PEM electrolyzer. Various techniques are discussed for the development of electrocatalysts, including nanostructured, core shell, and electrodeposition to deposit catalysts on GDL. The design and methodology of new and improved GDL are discussed along with the fabrication of gas diffusion electrodes and passivation techniques to reduce the oxidation of GDL. The passivation technique of BPs using Au and Pt is summarized for its effect on electrolysis efficiency. Finally, the optimization of various operating conditions for PEM electrolyzer are reviewed to improve the efficiency of the electrolyzer.
An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids
Authors: Liu Guodong , Ferrari Maximiliano F. , Ollis Thomas B. , Tomsovic Kevin
Published: September 2022

An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids.
Geochemical Features of Lacustrine Shales in the Upper Cretaceous Qingshankou Formation of Changling Sag, Songliao Basin, Northeast China
Authors: Li Zhongcheng , Bao Zhidong , Wei Zhaosheng , Li Lei , Wang Hailong
Published: September 2022

The organic-rich shale of the Upper Cretaceous Qingshankou Formation is an important hydrocarbon source rock in Northeast China. In this study, taking the lacustrine shale in the Qingshankou Formation as an example, geochemical analysis, including total organic carbon (TOC), Rock-Eval pyrolysis, maceral compositions, X-ray diffraction (XRD), and biomarker analyses, were carried out on twenty-four shale samples to evaluate the geochemistry and environmental features of this shales. The Qingshankou lacustrine shales contains mainly Type I/II1 organic matter and is oil prone, with a good to excellent source rock. Vitrinite reflectance and Rock-Eval pyrolysis parameters show that the Qingshankou lacustrine shales is mainly in the mature stage and within the oil window. Biomarker composition of the shales provide evidence that the Qingshankou lacustrine shales was formed in a reductive sedimentary environment with relatively high salinity water. The organic matter came from a mixture of plankton, bacterial and land plants.
Control of DSTATCOM Using ANN-BP Algorithm for the Grid Connected Wind Energy System
Authors: Irfan Mohammad Mujahid , Malaji Sushama , Patsa Chandrashekhar , Rangarajan Shriram S. , Hussain S. M. Suhail
Published: September 2022

Green energy sources are implemented for the generation of power due to their substantial advantages. Wind generation is the best among renewable options for power generation. Generally, the wind system is directly connected with the power network for supplying power. In direct connection, there is an issue of managing power quality (PQ) concerns such as voltage sag, swells, flickers, harmonics, etc. In order to enhance the PQ in a power network with a wind energy conversion system (WECS), peripheral compensation is needed. In this paper, we highlight a novel control technique to improve the PQ in WECS by adopting an Artificial Neural Network (ANN)-based Distribution Static Compensator (DSTATCOM). In our proposed approach, an online learning-based ANN Back Propagation (BP) model is used to generate the gate pulses of the DSTATCOM, which mitigate the harmonics at the grid side. It is modelled using the MATLAB platform and the total harmonic distortion (THD) of the system is compared with and without DSTATCOM. The harmonics at the source side decreased to less than 5% and are within the IEEE limits. The results obtained reveal that the proposed online learning-based ANN-BP is superior in nature.
Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm
Authors: Shaheen Abdullah , El-Sehiemy Ragab , Kamel Salah , Selim Ali
Published: September 2022

In this paper, the electricity network automation based on Power Network Reconfiguration (PNR) is implemented to improve the operational reliability of distribution systems using jellyfish search algorithm. For this purpose, system average interruption frequency index (SAIFI), system average interruption unavailability index (SAIUI) and total energy not supplied (TENS) are critical measures. In this paper, a new optimization technique of jellyfish search (JFS) algorithm is employed for distribution network reconfiguration for reliability improvement. It is concerned with the moving patterns of jellyfish. They are divided into three categories. The jellyfish could flow towards the ocean current or between its own swarm. Meanwhile, whenever the food supply is adequate, the jellyfishes are attracted to its location. It is formulated considering the three reliability indices of SAIFI, SAIUI and TENS, simultaneously in a multi-objective model based on the weight factors. The proposed methodology based on the JFS optimizer is implemented on an IEEE 33-node distribution network. According to the numerical results, the SAIFI, SAIUI and TENS is improved by 36.44%, 34.11% and 33.35%, compared to the initial condition. For comparison purposes, tuna swarm optimizer and tunicate swarm algorithm, besides the JFS algorithm, are implemented as well. The simulation results declare the significant outperformance of the JFS algorithm compared to TUNA and TSA in terms of the obtained improvements and the regarding convergence properties.
Design of Power Location Coefficient System for 6G Downlink Cooperative NOMA Network
Authors: Hassan Mohamed , Singh Manwinder , Hamid Khalid , Saeed Rashid , Abdelhaq Maha , Alsaqour Raed
Published: September 2022

Cooperative non-orthogonal multiple access (NOMA) is a technology that addresses many challenges in future wireless generation networks by delivering a large amount of connectivity and huge system capacity. The aim of this paper is to design the varied distances and power location coefficients for far users. In addition, this paper aims to evaluate the outage probability (OP) performance against a signal-to-noise ratio (SNR) for a 6G downlink (DL) NOMA power domain (PD) and DL cooperative NOMA PD networks. We combine a DL cooperative NOMA with a 16 × 16, a 32 × 23, and a 64 × 64 multiple-input multiple-output (MIMO) and a 128 × 128, a 256 × 256, and a 512 × 512 massive MIMO in an innovative method to enhance OP performance rate and mitigate the power location coefficient’s effect for remote users. The results were obtained from Rayleigh fading channels using the MATLAB simulation software program. According to the outcomes, increasing the power location coefficients for the far user from 0.6 to 0.8 reduces the OP rate because increasing the power location coefficient for the far user decreases the power location coefficient for the near user, which results in less interference between them. In terms of the OP performance rate, the DL cooperative NOMA outperforms the NOMA. According to the findings, the DL cooperative NOMA OP rate outperforms the DL NOMA by a rate of 10−0.5. Whereas the 16 × 16 MIMO enhances the OP for the far user by 78.0 × 10−4, the 32 × 32 MIMO increases the OP for the far user by 19.0 × 10−4, and the 64 × 64 MIMO decreases the OP rate for the far user by 5.0 × 10−5. At a SNR of 10 dB, the 128 × 128 massive MIMO improves the OP for the far user by 1.0 × 10−5. The 256 × 256 massive MIMO decreases the OP for the far user by 43.0 × 10−5, and the 512 × 512 massive MIMO enhances the OP for the far user by 8.0 × 10−6. The MIMO techniques improve the OP performance, while the massive MIMO technology enhances the OP performance dramatically.
A Novel Method of Deep Learning for Shear Velocity Prediction in a Tight Sandstone Reservoir
Authors: Jiang Ren , Ji Zhifeng , Mo Wuling , Wang Suhua , Zhang Mingjun , Yin Wei , Wang Zhen , Lin Yaping , Wang Xueke , Ashraf Umar
Published: September 2022

Shear velocity is an important parameter in pre-stack seismic reservoir description. However, in the real study, the high cost of array acoustic logging leads to lacking a shear velocity curve. Thus, it is crucial to use conventional well-logging data to predict shear velocity. The shear velocity prediction methods mainly include empirical formulas and theoretical rock physics models. When using the empirical formula method, calibration should be performed to fit the local data, and its accuracy is low. When using rock physics modeling, many parameters about the pure mineral must be optimized simultaneously. We present a deep learning method to predict shear velocity from several conventional logging curves in tight sandstone of the Sichuan Basin. The XGBoost algorithm has been used to automatically select the feature curves as the model’s input after quality control and cleaning of the input data. Then, we construct a deep-feed neuro network model (DFNN) and decompose the whole model training process into detailed steps. During the training process, parallel training and testing methods were used to control the reliability of the trained model. It was found that the prediction accuracy is higher than the empirical formula and the rock physics modeling method by well validation.
Method to Estimate Thermal Transients in Reactors and Determine Their Parameter Sensitivities without a Forward Simulation
Authors: Holdampf Sydney A. , Osborne Andrew G. , Deinert Mark R.
Published: September 2022

Thermal response time is an important parameter for the control of fast reactors. Modern thermal hydraulic codes allow for the modeling of transient responses and can also be used to understand the dominant factors that affect them. However, simulations can be computationally expensive, particularly for performing parametric analyses of how thermophysical properties affect transient behavior. Here, we present a method for using linear stability analysis to estimate thermal response time and determine the key parameters that affect transient behavior without performing a forward simulation. The approach can also be used to corroborate simulation results and is tested against simulation results produced with a 2D finite difference model. The results show that this approach produces time-dependent temperature profiles that are within 2 × 10−5–0.1% of the numerical results for a single node perturbation. Changes in temperature have the greatest effect on thermal response time, followed by changes to thermal conductivity.
Study on Combustion and Emissions of a Spark Ignition Engine with Gasoline Port Injection Plus Acetone–Butanol–Ethanol (ABE) Direct Injection under Different Speeds and Loads
Authors: Zhang Jufang , Yu Xiumin , Guo Zezhou , Li Yinan , Zhang Jiahua , Liu Dongjie
Published: September 2022

ABE can be used as an alternative fuel for engines. This paper studies the combustion and emission performances of an SI engine with GPI plus ABEDI at different engine speeds and loads. The engine operating conditions included speeds of 1000–2600 rpm at the MAP = 50 kPa and loads of MAP = 30–70 kPa at a speed of 1800 rpm. The ABEDIr contained 0%, 20%, 40%, 60%, 80%, and 100%. At speeds = 1000–1800 or 2200–2600 rpm, the testing results showed the ABEDIr corresponding to the maximum IMEP at 80% or 100%. When the ABEDIr = 60%, HC and NOx emissions were the lowest at speeds of 1000–2600 rpm. Meanwhile, NPN and APN both decreased with the increasing of ABEDIr. As the MAP increased, CA0-90 decreased. At different loads, ABE-added fuels had lower HC and NOx emissions and higher IMEP values than pure gasoline. PN was lower than 4 × 104 n/cm3 when the ABEDIr was over 80%. Overall, 80% ABEDIr is a great choice for engine performance at the test range of loads and speeds, and pure ABE fuel is better if the power performance is the main requirement at high speeds and loads.
Mineral Resource Constraints for China’s Clean Energy Development under Carbon Peaking and Carbon Neutrality Targets: Quantitative Evaluation and Scenario Analysis
Authors: Luo Xinyu , Pan Lingying , Yang Jie
Published: September 2022

With concerns about global warming and energy security, people are reducing fossil fuel use and turning to clean energy technologies. Mineral resources are used as materials for various energy technologies, and with the development of clean energy technologies, the demand for mineral resources will increase. China is a large country with various mineral resources, but its structural supply problem is severe. For China to reach the targets of carbon peaking before 2030 and carbon neutrality before 2060, they have set specific milestones for developing each clean energy industry; thus, the demand for mineral resources in clean energy will increase. We first summarise the mineral resources supply for China’s development of clean energy technologies. We analyse the demand for various mineral resources in specific clean energy technology sectors under the stated policies scenario and sustainable development scenario through scenario setting. Finally, we combine current domestic mineral resource reserves and overseas import channels to analyse China’s mineral resource supply and demand for developing the clean energy industry. Our results show that the surge in clean energy generation and electric vehicle ownership in China between 2020 and 2050 will lead to a significant increase in demand for mineral resources for these technologies and a shortage in the supply of some mineral resources. In particular, the supply of copper, nickel, cobalt, and lithium will be a severe constraint for clean energy development. We also find that secondary recycling of power battery materials in the electric vehicle sector could alleviate China’s resource constraints. The findings of our study provide a better understanding of the kinds of mineral elements that are in short supply on the path of clean energy development in China under carbon peaking and carbon neutrality targets and the future channels that can be used to increase the supply of minerals.
Optimization of Molecular Composition Distribution of Slurry Oil by Supercritical Fluid Extraction to Improve the Structure and Performance of Mesophase Pitch
Authors: Dai Xiaoyu , Ma Yuanen , Zhang Linzhou , Xu Zhiming , Sun Xuewen , Zhao Suoqi
Published: September 2022

The composition distribution of slurry oil has a significant impact on the structure and performance of the mesophase. In this study, supercritical fluid extraction oil (SFEO) and extraction components were extracted from two slurry oils (SLOs) using the supercritical fluid extraction (SFE) technique. The fundamental properties and composition distribution of two SLOs and associated SFEOs were thoroughly investigated. Electron microscopy and spectroscopic techniques were employed to study the morphology and structures of mesophase pitch produced by carbonizing SLOs and their extraction components under the same conditions. The findings revealed that, compared to SLO–LH, SLO–SH has a higher proportion of 4–5 aromatic rings and a narrower hydrocarbon distribution range. In SLO–LH, O1, N1, and N1O1 molecules with long side chains and poor flatness make up the majority of the heterocyclic aromatic hydrocarbons. The distribution of CH compounds can be narrowed by using supercritical fluid extraction to efficiently separate various heteroatom-containing compounds with a higher condensation degree. After supercritical extraction, the mesophase content, texture distribution, and graphitization degree of the mesophase were improved. Polycyclic aromatic hydrocarbons with high planarity help polymer macromolecules stick together and build up in an orderly way. Heterocyclic aromatic hydrocarbons with high condensation and low planarity, on the other hand, play an important role in the formation of mosaic structures.
Secondary Voltage Collaborative Control of Distributed Energy System via Multi-Agent Reinforcement Learning
Authors: Wang Tianhao , Ma Shiqian , Xu Na , Xiang Tianchun , Han Xiaoyun , Mu Chaoxu , Jin Yao
Published: September 2022

In this paper, a new voltage cooperative control strategy for a distributed power generation system is proposed based on the multi-agent advantage actor-critic (MA2C) algorithm, which realizes flexible management and effective control of distributed energy. The attentional actor-critic message processor (AACMP) is extended into the MA2C method to select the important messages from all communication messages adaptively and process important messages efficiently. The cooperative control strategy trained by centralized training and decentralized execution frame will take over the responsibility of the secondary control level for voltage restoration in a distributed manner. The introduction of the attention mechanism reduces the amount of information exchanged and the requirements of the communication network. Finally, a distributed system with six energy nodes is used to verify the effectiveness of the proposed control strategy.
Effects of Radial and Circumferential Flows on Power Density Improvements of Tubular Solid Oxide Fuel Cells
Authors: Essaghouri Abdellah , Zeng Zezhi , Zhao Bingguo , Hao Changkun , Qian Yuping , Zhuge Weilin , Zhang Yangjun
Published: September 2022

Improving the power density of SOFC stacks will accelerate their integration into mobile applications. We developed a 3D Multiphysics model validated by experimental results from early studies to examine the effect of radial and circumferential flows on the power density improvements in a micro-tubular SOFC. The inserts were placed inside the fuel channel to generate flow in different directions. The effects of geometric parameters of these inserts on flow and mass transfer in the fuel channel and porous anode were analyzed. We demonstrate that the radial flow enables the fuel to penetrate directly into the porous anode, increasing the local fuel concentration and enhancing the fuel diffusion to the anode triple-phase boundaries. We found that the circumferential flow has a negligible effect on the diffusion process in the anode and on the increase in power density. The impact of local convective and diffusive mass transfer mechanisms on power density improvement is analyzed using the local Péclet number along the axial direction. Enlarging the radial velocity component perpendicular to the porous anode could effectively increase the power density of the micro-tubular SOFC by 37%. This study helps improve our understanding of mass transfer in fuel channels and helps build a foundation for SOFC channel designs and optimizations.
Three-Phase Grid-Connected Inverter Power Control under Unbalanced Grid Conditions Using a Proportional-Resonant Control Method
Authors: Alathamneh Mohammad , Ghanayem Haneen , Yang Xingyu , Nelms R. M.
Published: September 2022

Proposed in this article is bidirectional real and reactive power control of a three-phase grid-connected inverter under unbalanced grid conditions using a proportional-resonance controller. Different unbalanced grid conditions have been studied, such as unbalanced three-phase load and unbalanced grid impedance. These unbalanced scenarios generate unbalanced grid currents and unbalanced point-of-common-coupling (PCC) voltages, causing large oscillations in both real and reactive power transferred to the grid. The purposes of the suggested technique are to balance the grid currents and point-of-common-coupling voltages as well as control the power injected into the grid. As a result, balanced PCC voltages are guaranteed, the oscillation in real and reactive power is reduced, and power control is achieved. The proposed method’s performance has been verified in MATLAB/SIMULINK simulation software, and different experimental results have been obtained using a real-time interface platform, dSPACE DS1202.
Twelve Years into Genomic Selection in Forest Trees: Climbing the Slope of Enlightenment of Marker Assisted Tree Breeding
Authors: Grattapaglia Dario
Published: September 2022

Twelve years have passed since the early outlooks of applying genomic selection (GS) to forest tree breeding, initially based on deterministic simulations, soon followed by empirical reports. Given its solid projections for causing a paradigm shift in tree breeding practice in the years to come, GS went from a hot, somewhat hyped, topic to a fast-moving area of applied research and operational implementation worldwide. The hype cycle curve of emerging technologies introduced by Gartner Inc. in 1995, models the path a technology takes in terms of expectations of its value through time. Starting with a sudden and excessively positive “peak of inflated expectations” at its introduction, a technology that survives the “valley of disappointment” moves into maturity to climb the “slope of enlightenment”, to eventually reach the “plateau of productivity”. Following the pioneering steps of GS in animal breeding, we have surpassed the initial phases of the Gartner hype cycle and we are now climbing the slope of enlightenment towards a wide application of GS in forest tree breeding. By merging modern high-throughput DNA typing, time-proven quantitative genetics and mixed-model analysis, GS moved the focus away from the questionable concept of dissecting a complex, polygenic trait in its individual components for breeding advancement. Instead of trying to find the needle in a haystack, i.e., the “magic” gene in the complex and fluid genome, GS more efficiently and humbly “buys the whole haystack” of genomic effects to predict complex phenotypes, similarly to an exchange-traded fund that more efficiently “buys the whole market”. Tens of studies have now been published in forest trees showing that GS matches or surpasses the performance of phenotypic selection for growth and wood properties traits, enhancing the rate of genetic gain per unit time by increasing selection intensity, radically reducing generation interval and improving the accuracy of breeding values. Breeder-friendly and cost-effective SNP (single nucleotide polymorphism) genotyping platforms are now available for all mainstream plantation forest trees, but methods based on low-pass whole genome sequencing with imputation might further reduce genotyping costs. In this perspective, I provide answers to why GS will soon become the most efficient and effective way to carry out advanced tree breeding, and outline a simple pilot demonstration project that tree breeders can propose in their organization. While the fundamental properties of GS in tree breeding are now solidly established, strategic, logistics and financial aspects for the optimized adoption of GS are now the focus of attentions towards the plateau of productivity in the cycle, when this new breeding method will become fully established into routine tree improvement.
Effects of Fertilizers and Litter Treatment on Soil Nutrients in Korean Pine Plantation and its Natural Forest of Northeast China
Authors: Hussain Anwaar , Jamil Muhammad Atif , Abid Kulsoom , Duan Wenbiao , Chen Lixin , Li Changzhun
Published: September 2022

Organic and inorganic soil fertilizer addition or removal pose significant effects on soil nutrients. As climate change and other anthropogenic factors are causing deprivation in soil nutrient profiles and altering its proper functioning, complete insight into fertilizer modification and its consequences is required for understanding the sustenance of forest ecosystems. In this regard, an experiment was conducted at Liangshui National Nature Reserve, northeast China, in which two forest soil types (i.e., Korean pine plantation and natural Korean pine forest) were evaluated for their response to external fertilizer applications and litter treatments. The litter treatments were litter application as Ck (undisturbed litter), RL (removed litter) and AL (Alter/double litter i.e., litter removed from RL was added in double litter plots), whereas the synthetic fertilizer treatments were Control (No added N and P), Low (5 g N m−2 a−1 + 5 g P m−2 a−1), Medium (15 g N m−2 a−1 + 10 g P m−2 a−1) and High (30 g N m−2 a−1 + 20 g P m−2 a−1). The outcome showed that soil organic carbon (SOC) was directly proportionate to forest litter amounts. Synthetic fertilizers affected soil total nitrogen (STN) and maximum amounts were recorded in plots with H: 30 g N m−2 a−1 + 20 g P m−2 a−1, as 3.03 ± 0.35 g kg−1 in AL. Similarly, altered litter/double was most effective in enhancing the quantity of soil total phosphorus (STP) (0.75 ± 0.04 g kg−1). Soil sampling carried out during the start and end of the experiment showed decreases in the sixth sampling of: SOC (4–23%), STN (7.5-10.8%) and STP (8.51–13.9%). A positive correlation was observed between SOC and total nitrogen; C:N ratio also increased with SOC. Principal component analysis (PCA) on captured a total of 62.1% variability, on the x-axis (35.1%) and on the y-axis (27%). It was concluded that combined application of N and P at the level of 30 g N m−2 a−1 + 20 g P m−2 a−1 under AL (Alter/double litter) treatment level improved soil total N and P content. The results clearly depicted that forest litter is an important source for building up of soil organic matter, however for attaining maximum sustenance capabilities in soil, the continuity of fertilizer application in either form is a prerequisite.
Estimating Regional Aggregate Economic Value of Forest Recreation Services with Linked Travel Cost Model
Authors: Kaya Güven
Published: September 2022

Multi-site linked travel cost models answer the need for aggregate demand and economic value estimations that consider the attributes of all forest recreation sites in a region and the preferences of visitors at the regional level. This study aimed to predict the aggregate value of forest recreation services in Ankara Province, Turkey, with a discrete choice-count data-linked model in the context of current and changing levels of forest attributes. In the first stage, the site choice model was predicted with the random parameter logit model; in the second stage, the trip demand model was estimated with the negative binomial model. The expected consumer surplus per trip derived from the first model was used as the link variable in the second model. The expected consumer surplus per trip of 14 forest recreation sites was estimated at 137.34 TL, and the annual aggregate consumer surplus per capita was estimated at 156.59 TL—a total of 13.49 million TL in the study area. This study predicts the total benefit will increase by 65% if the development stage of stands at recreation sites increases by two stages, degraded stands are improved, stands have a normal canopy, and the camping facilities are improved.
A Study of Forest Carbon Sink Increment from the Perspective of Efficiency Evaluation Based on an Inverse DEA Model
Authors: He Xiao , Chen Liye , Huang Yan
Published: September 2022

Forest carbon sink efficiency refers to the efficiency of input-output indicators related to carbon sinks. This paper studies carbon sink efficiency from the perspective of resource allocation; guides the optimal allocation of resources; and selects forestry employees, forestry investment amount and afforestation area as input indicators; the forest carbon sink efficiency in China is calculated and analyzed based on a data envelopment analysis model by converting the forest volume into the forest carbon sink through the volume expansion factor method. The grey prediction model is used to estimate the change in the input indicator, and the production possibility set is constructed with the input indicator before and after the change and the current output indicator. The efficiency of the decision units before the change is calculated, and through the comparison of efficiency, the conditions of forest carbon sink increase in 15 provinces are obtained. The optimal allocation of the output indicator is calculated based on the inverse data envelopment analysis model. The largest increase in forestry carbon sink is 169,362 megatons in Guangdong, and the smallest is 619 megatons in Tianjin. Finally, some suggestions for the path of forest carbon sink increment are put forward.
Dissecting the Regulatory Network of Maize Phase Change in ZmEPC1 Mutant by Transcriptome Analysis
Authors: Li Xiaoqi , Li Weiya , Li Na , Tian Runmiao , Qi Feiyan , Meng Juan , Jiang Yajuan , Wang Chenhui , Chen Yongqiang , Guo Zhanyong , Tang Jihua , Zhang Zhanhui
Published: September 2022

The developmental phase changes of maize are closely associated with the life span, environmental adaption, plant height, and disease resistance of the plant and eventually determines the grain yield and quality of maize. A natural mutant, Early Phase Change 1 (ZmEPC1), was selected from the inbred line KN5585. Compared with the wild type plant, the ZmEPC1 mutant exhibits deceased plant stature, accelerated developmental stages, and decreased leaf size. Through the transcriptome sequencing analysis of leaf samples at flowering stage, a total of 4583 differentially expressed genes (DEGs) were screened between the mutant and wild type, including 2914 down-regulated genes and 1669 up-regulated genes. The GO enrichment and KEGG enrichment analysis revealed that the DEGs were mainly involved in hormone response, hormone signal transduction, autophagy, JA response and signal response, photosynthesis, biotic/abiotic stress, and circadian rhythms. The RT-qPCR results revealed that the most tested DEGs display consistent expression alterations between V5 and FT stages. However, several genes showed opposite expression alterations. Strikingly, most of the JA biosynthesis and signaling pathway-related genes displayed diametrically expression alterations between V5 and FT stages. miR156, a key regulator of plant phase transition, exhibited significant down-regulated expression at V5 and FT stages. The expression of two miR156 target genes were both significantly different between mutants and wild type. In conclusion, ZmEPC1 was identified to be mainly involved in the regulation of JA-mediated signaling pathways and hormone response and signaling, which is possible to confer developmental phase change through miR156-SPLs pathway.
A Comparative Cross-Platform Analysis to Identify Potential Biomarker Genes for Evaluation of Teratozoospermia and Azoospermia
Authors: Das Suchismita , Guha Pokhraj , Nath Monika , Das Sandipan , Sen Surojit , Sahu Jagajjit , Kopanska Marta , Dutta Sulagna , Jamal Qazi Mohammad Sajid , Kesari Kavindra Kumar , Sengupta Pallav , Slama Petr , Roychoudhury Shubhadeep
Published: September 2022

Male infertility is a global public health concern. Teratozoospermia is a qualitative anomaly of spermatozoa morphology, contributing significantly to male infertility, whereas azoospermia is the complete absence of spermatozoa in the ejaculate. Thus, there is a serious need for unveiling the common origin and/or connection between both of these diseases, if any. This study aims to identify common potential biomarker genes of these two diseases via an in silico approach using a meta-analysis of microarray data. In this study, a differential expression analysis of genes was performed on four publicly available RNA microarray datasets, two each from teratozoospermia (GSE6872 and GSE6967) and azoospermia (GSE145467 and GSE25518). From the analysis, 118 DEGs were found to be common to teratozoospermia and azoospermia, and, interestingly, sperm autoantigenic protein 17 (SPA17) was found to possess the highest fold change value among all the DEGs (9.471), while coiled-coil domain-containing 90B (CCDC90B) and coiled-coil domain-containing 91 (CCDC91) genes were found to be common among three of analyses, i.e., Network Analyst, ExAtlas, and GEO2R. This observation indicates that SPA17, CCDC90B, and CCDC91 genes might have significant roles to play as potential biomarkers for teratozoospermia and azoospermia. Thus, our study opens a new window of research in this area and can provide an important theoretical basis for the diagnosis and treatment of both these diseases.
Evolutionary Comparison of the Complete Chloroplast Genomes in Convallaria Species and Phylogenetic Study of Asparagaceae
Authors: Lu Qi-Xiang , Chang Xiao , Gao Jing , Wu Xue , Wu Jing , Qi Zhe-Chen , Wang Rui-Hong , Yan Xiao-Ling , Li Pan
Published: September 2022

The genus Convallaria (Asparagaceae) comprises three herbaceous perennial species that are widely distributed in the understory of temperate deciduous forests in the Northern Hemisphere. Although Convallaria species have high medicinal and horticultural values, studies related to the phylogenetic analysis of this genus are few. In the present study, we assembled and reported five complete chloroplast (cp) sequences of three Convallaria species (two of C. keiskei Miq., two of C. majalis L., and one of C. montana Raf.) using Illumina paired-end sequencing data. The cp genomes were highly similar in overall size (161,365–162,972 bp), and all consisted of a pair of inverted repeats (IR) regions (29,140–29,486 bp) separated by a large single-copy (LSC) (85,183–85,521 bp) and a small single-copy (SSC) region (17,877–18,502 bp). Each cp genome contained the same 113 unique genes, including 78 protein-coding genes, 30 transfer RNA genes, and 4 ribosomal RNA genes. Gene content, gene order, AT content and IR/SC boundary structure were nearly identical among all of the Convallaria cp genomes. However, their lengths varied due to contraction/expansion at the IR/LSC borders. Simple sequence repeat (SSR) analyses indicated that the richest SSRs are A/T mononucleotides. Three highly variable regions (petA-psbJ, psbI-trnS and ccsA-ndhD) were identified as valuable molecular markers. Phylogenetic analysis of the family Asparagaceae using 48 cp genome sequences supported the monophyly of Convallaria, which formed a sister clade to the genus Rohdea. Our study provides a robust phylogeny of the Asparagaceae family. The complete cp genome sequences will contribute to further studies in the molecular identification, genetic diversity, and phylogeny of Convallaria.
Genome-Wide Identification and Expression Analysis of the PpYUCCA Gene Family in Weeping Peach Trees (Prunus persica ‘Pendula’)
Authors: Zhang Yuyan , Mao Qinsi , Ma Ruijuan , Xu Jianlan , Yu Mingliang
Published: September 2022

Auxin is an important endogenous plant hormone that is usually present as indole-3-acetic acid (IAA). The flavin monooxygenase YUCCA is the rate-limiting enzyme of IAA biosynthesis and plays an important regulatory role in plant growth and development. To further investigate the function of the YUCCA gene family in weeping peach trees, members of the YUCCA gene family were identified via bioinformatics analysis. The gene structure and conserved domains of the weeping peach YUCCA genes were investigated, and phylogenetic analysis and gene annotation were carried out. Fourteen PpYUCCAs were identified in the weeping peach variety ‘Hongchuizhi’ and were found to be randomly located on five different chromosomes. Moreover, the prediction of subcellular localization showed that most of the YUCCA proteins were localized in the cytoplasm. Based on our transcriptome analysis, only nine PpYUCCAs, including PpYUCCA1, PpYUCCA3/4/5/6, PpYUCCA9, and PpYUCCA12/13/14, were expressed in the weeping peach branches, which could result in the accumulation of auxin. PpYUCCA6/12 may play a critical role in the appearance of the weeping trait, as indicated by the higher expression levels found in the Hongchuizhi variety compared with the Xiahui 6 variety. The results of this study provide a foundation for further research on the biological functions of PpYUCCAs in weeping peach trees.
The Moderating Role of Teamwork Engagement and Teambuilding on the Effect of Teamwork Competence as a Predictor of Innovation Behaviors among University Students
Authors: Martín-Hernández Pilar , Gil-Lacruz Marta , Tesán-Tesán Ana Cristina , Pérez-Nebra Amalia Raquel , Azkue-Beteta Juan Luis , Rodrigo-Estevan María Luz
Published: September 2022

Sustainable innovation is the cornerstone of economic growth and development of regions and nations, as well as of organizational competitiveness and success. Innovation is a complex process that relies on individuals and often implies social activities based on interaction with others. Higher Education (HE) is expected to prepare innovative and teamwork-competent individuals. However, it has been noted that, so far, HE has not really addressed the question of how to train innovative college students capable of working in teams. To face such challenges, incorporating active teaching and learning methodologies, such as game-based learning (GBL), could be of great utility, as well as conducting much more research about the effect of teamwork-related factors on IWB, such as teamwork engagement (TWE) and teambuilding (TB). Under this background, our aim was to test the predictor effect of teamwork competence (TWE) on IWB, exploring the moderating role of TWE and TB in a sample comprising 142 college students of Health Sciences and Social Work. Our obtained results, through a multiple additive moderation analysis, showed that TWC positively predicted IWB. Moreover, this effect was moderated by TWE and TB. Therefore, these findings set light around how to foster IWB in HE.