bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation of Spectral Plant Images Using Generative Adversary Network Techniques
Authors: Kumar Sanjay , Kansal Sahil , Alkinani Monagi H. , Elaraby Ahmed , Garg Saksham , Natarajan Shanthi , Sharma Vishnu
Published: August 2022

The spectral image analysis of complex analytic systems is usually performed in analytical chemistry. Signals associated with the key analytics present in an image scene are extracted during spectral image analysis. Accordingly, the first step in spectral image analysis is to segment the image in order to extract the applicable signals for analysis. In contrast, using traditional methods of image segmentation in chronometry makes it difficult to extract the relevant signals. None of the approaches incorporate contextual information present in an image scene; therefore, the classification is limited to thresholds or pixels only. An image translation pixel-to-pixel (p2p) method for segmenting spectral images using a generative adversary network (GAN) is presented in this paper. The p2p GAN forms two neuronal models. During the production and detection processes, the representation learns how to segment ethereal images precisely. For the evaluation of the results, a partial discriminate analysis of the least-squares method was used to classify the images based on thresholds and pixels. From the experimental results, it was determined that the GAN-based p2p segmentation performs the best segmentation with an overall accuracy of 0.98 ± 0.06. This result shows that image processing techniques using deep learning contribute to enhanced spectral image processing. The outcomes of this research demonstrated the effectiveness of image-processing techniques that use deep learning to enhance spectral-image processing.
A Multiscale Fusion Lightweight Image-Splicing Tamper-Detection Model
Authors: Zhao Dan , Tian Xuedong
Published: August 2022

The easy availability and usability of photo-editing tools have increased the number of forgery attacks, primarily splicing attacks, thereby increasing cybercrimes. Because of an existing image-splicing tamper-detection algorithm based on deep learning with high model complexity and weak robustness, a multiscale fusion lightweight model for image-splicing tamper detection is proposed. For the above problems and to improve MobileNetV2, the structural block of the classification part of the original network structure was removed, the stride of the sixth largest structural block of the network was changed to 1, the dilated convolution was used instead of downsampling, and the features extracted from the second and third large structural blocks in the network were downsampled with maximal pooling; then, the constraint on the backbone network was increased by jumping connections. Combined with the pyramid pooling module, the acquired feature layers were divided into regions of different sizes for average pooling; then, all feature layers were fused. The experimental results show that it had a low number of parameters and required a small amount of computation, achieving 91.0% and 96.4% precision on CASIA and COLUMB, respectively, and 83.2% and 88.1% F-measure on CASIA and COLUMB, respectively.
Operation Optimization of Circulating Fluidized Bed Boilers Integration of Variable Renewables
Authors: Deng Boyu , Zhang Yi , Yang Hairui
Published: August 2022

In response to the effects of climate change, China pledged to raise the share of non-fossil fuels in the primary energy consumption to around 25% and bring the total installed capacity of wind and solar power to over 1 [...]
Carbon Intensity and Green Transition in the Chinese Manufacturing Industry
Authors: Peng Cheng , Guo Xiaolin , Long Hai
Published: August 2022

The carbon emissions in China contribute to around one-third of the world total. Therefore, China plays a critical role in global carbon emissions reduction. Over the last few years, the Chinese government has implemented a range of counter-measures to accelerate the green transition. In this research, we empirically investigate the relationship between carbon intensity and the green transition. Based on provincial panel data of Chinese manufacturing industries from 2008 to 2019, we measure the relationship between carbon intensity and green transition capacity in 30 provinces, employing the Generalized Method of Moments (GMM) to examine their influencing mechanism and regional heterogeneity. Furthermore, we use an intermediary model to investigate the influence of financial development on the relationship between carbon intensity and manufacturing green transition. We find that a U-shaped relationship exists, where increasing carbon emissions restrain the green transition initially but improve it later, such that the transition upgrades gradually. Regarding the regional heterogeneity, the GMM results show that carbon intensity has the most significant impact on the green transition in the central provinces, followed by western provinces. Meanwhile, financial performance is an essential contributor to the relationship, as more funds flow into contamination-dominated but profitable projects, thus inhibiting the transition. Urbanization and marketization are also included into threshold models, which suggest the existence of relevant threshold effects in the relationship. These findings have a referenced value suggesting that the local governments follow the U-shaped theory to reform the local carbon reduction policies and green development target according to the regional economic performance and geographical advantages.
Feedback Control Strategy for Transient Stability Application
Authors: Ojetola Samuel T. , Wold Josh , Trudnowski Daniel
Published: August 2022

Power systems are subjected to a wide range of disturbances during daily operations. Severe disturbances, such as a loss of a large generator, a three-phase bolted fault on a generator bus, or a loss of a transmission line, can lead to the loss of synchronism of a generator or group of generators. The ability of a power system to maintain synchronism during the few seconds after being subjected to a severe disturbance is known as transient stability. Most of the modern methods of controlling transient stability involve special protection schemes or remedial action schemes. These special protection schemes sense predetermined system conditions and take corrective actions, such as generator tripping or generation re-dispatch, in real time to maintain transient stability. Another method is the use of a real-time feedback control system to modulate the output of an actuator in response to a signal. This paper provides a fundamental evaluation of the use of feedback control strategies to improve transient stability in a power system. An optimal feedback control strategy that modulates the real power injected and absorbed by distributed energy-storage devices is proposed. Its performance is evaluated on a four-machine power system and on a 34-machine reduced-order model of the Western North American Power System. The result shows that the feedback control strategy can increase the critical fault clearing time by 60%, thereby improving the transient stability of the power system.
Blind Source Separation of Transformer Acoustic Signal Based on Sparse Component Analysis
Authors: Wang Guo , Wang Yibin , Min Yongzhi , Lei Wu
Published: August 2022

In the acoustics-based power transformer fault diagnosis, a transformer acoustic signal collected by an acoustic sensor is generally mixed with a large number of interference signals. In order to separate transformer acoustic signals from mixed acoustic signals obtained by a small number of sensors, a blind source separation (BSS) method of transformer acoustic signal based on sparse component analysis (SCA) is proposed in this paper. Firstly, the mixed acoustic signals are transformed from time domain to time–frequency (TF) domain, and single source points (SSPs) in the TF plane are extracted by identifying the phase angle differences of the TF points. Then, the mixing matrix is estimated by clustering SSPs with a density clustering algorithm. Finally, the transformer acoustic signal is separated from the mixed acoustic signals based on the compressed sensing theory. The results of the simulation and experiment show that the proposed method can separate the transformer acoustic signal from the mixed acoustic signals in the case of underdetermination. Compared with the existing denoising methods of the transformer acoustic signal, the denoising results of the proposed method have less error and distortion. It will provide important data support for the acoustics-based power transformer fault diagnosis.
Recent Advances in Microalgal Biorefineries
Authors: Esteves Ana F. , Salgado Eva M. , Pires José C. M.
Published: August 2022

The increase in the world population leads to the generation of high amounts of wastewater and the requirement for more energy to satisfy the population’s needs [...]
Three-Dimensional CFD Modeling on the Thermal Characteristics of Buried Oil Pipeline Involving the Heat Transfer of Wax Layer
Authors: Xie Hanyu , Li Changjun , Jia Wenlong , Zhang Caigong
Published: August 2022

It is common to have a wax layer on the inner wall of waxy crude oil pipeline. However, the study of the wax layer on the heat transfer of buried pipeline systems is inadequate due to its instability of composition and properties; it may lead to the inaccurate prediction of the pipeline temperature field. Based on the finite element simulation technology, a three-dimensional heat transfer model of buried crude oil pipeline involving wax layer was proposed and solved. The thermal effect of the wax layer on pipeline system was analyzed quantitatively. Numerical results show that the average deviation of soil temperature near the pipeline reach 1.42 K when there is a 4 mm wax layer. Among different thermal conductivity models of heterogeneous materials, the EMT model plays best in predicting the conductivity of a waxy layer. By setting different working conditions, the influence mechanisms of several thermal influencing factors are discussed. The results show that the thermal influence range of heated pipe is positively associated with oil temperature and velocity. The core thermal response zone is about 12 m along the X-axis. Beyond 8 m depth from ground surface, the temperature fluctuation of soil is almost unaffected by the oil pipeline.
Predicting the Optimal Performance of a Concentrated Solar Segmented Variable Leg Thermoelectric Generator Using Neural Networks
Authors: Maduabuchi Chika , Fagehi Hassan , Alatawi Ibrahim , Alkhedher Mohammad
Published: August 2022

The production of high-performing thermoelectrics is limited by the high computational energy and time required by the current finite element method solvers that are used to analyze these devices. This paper introduces a new concentrating solar thermoelectric generator made of segmented materials that have non-uniform leg geometry to provide high efficiency. After this, the optimum performance of the device is obtained using the finite element method conducted using ANSYS software. Finally, to solve the high energy and time requirements of the conventional finite element method, the data generated by finite elements are used to train a regressive artificial neural network with 10 neurons in the hidden layer. Results are that the power and efficiency obtained from the optimized device design are 3× and 2× higher than the original unoptimized device design. Furthermore, the developed neural network has a high accuracy of 99.95% in learning the finite element data. Finally, the neural network predicts the modified device performance about 800× faster than the conventional finite element method. Overall, the paper provides insights into how thermoelectric manufacturing companies can harness the power of artificial intelligence to design very high-performing devices while saving time and cost.
Analysis and Comparison of Two Permanent-Magnet Width-Modulation Arrays for Permanent Magnet Linear Synchronous Motor
Authors: Luo Meizhu , Duan Jian , Yi Zhaoxi
Published: August 2022

Permanent-magnet (PM) width-modulation array is designed to solve the issues resulting from big pole-pitches of PMLSMs in high-speed and high-precision systems. PM width-modulation array provided in this paper is a kind of segmented magnetic-pole structure, featuring low PM eddy currents and low thrust ripples. First, the magnetomotive force (MMF) excited by the PM width-modulation array is analyzed to prove its feasibility, the PM eddy current of the novel array is studied to show its advantage in high-speed applications, and the electromagnetic models of two PM width-modulation arrays are established, which are designed by the equal area method and the triangular modulation method, respectively. Then, the thrust features and the PM usage amounts of the two PM width-modulation arrays are analyzed by the finite element method (FEM) and the performance comparisons are presented. The prototype is manufactured and tested to verify the analytical results. The experimental data agree well with the simulations and analyses.
State Characterization of Lithium-Ion Battery Based on Ultrasonic Guided Wave Scanning
Authors: Li Xiaoyu , Wu Chuxin , Fu Chen , Zheng Shanpu , Tian Jindong
Published: August 2022

Accurate state characterization of batteries is conducive to ensuring the safety, reliability, and efficiency of their work. In recent years, ultrasonic non-destructive testing technology has been gradually applied to battery state estimation. In this paper, research on the state characterization of lithium-ion batteries based on ultrasonic guided wave (UGW) scanning is carried out. The laser Doppler vibrometer (LDV) and the X-Y stage are used to obtain the surface scanning UGW signal and the line scanning UGW signal of lithium-ion batteries under different states of charge and different aging degrees. The propagation law of UGWs in the battery is analyzed by surface scanning signals, then the energy spectrum of the signals is calculated, showing that the aging of the battery attenuates the transmission energy of UGWs. The “point” parameters are extracted from the scanning point signals. On this basis, the “line” parameters composed of line scanning multi-point signals are extracted. By analyzing the changing law of parameters during the charge–discharge process of batteries, several characteristic parameters that can be used to characterize the battery state of charge and state of health are obtained. The method has good consistency in the state characterization of the three batteries and provides a new approach for non-destructive testing and evaluation of battery states.
Linking Indoor Thermal Comfort with Climate, Energy, Housing, and Living Conditions: Portuguese Case in European Context
Authors: Delgado João , Matos Ana Mafalda , Guimarães Ana Sofia
Published: August 2022

Even though the milder climate scenario and constant evolution of thermal building regulation are in light of European initiatives, in Portugal, there are few houses where occupants can remain all the time in perfectly comfortable temperature conditions without resorting to heating or cooling. According to the Long Term Strategy for the Renewal of Buildings (ELPRE), this results from the combination of several factors, namely, low energy use for air conditioning compared to energy needs and aged building stock with poor energy performance. In fact, around 70% of the dwellings currently certified have low energy efficiency (C or less). The purpose of this review article was to analyse and discuss the factors affecting indoor thermal comfort, the inability to keep the home adequately warm in winter and cool in summer, and the risk of poverty or social exclusion in the European context, namely in Portugal. It fills the gap in the literature researching and analysing the motivations for these lower consumptions in Southern Europe, being Portugal a paradigmatic case. The current work integrates the indoor thermal comfort evolution and the current situation in Portugal in the EU context through different thermal comfort indicators and linking with the other statistics data, which may impact the indoor thermal comfort.
Sliding Mode Controller for Parameter-Variable Load Sharing in Islanded AC Microgrid
Authors: Hajihosseini Mojtaba , Lešić Vinko , Shaheen Husam I. , Karimaghaee Paknoosh
Published: August 2022

Controlling voltage, frequency, and current in an islanded microgrid is a challenging problem because the distributed generation sources, stochastic and intermittent in nature, are not connected to the main electricity network to provide stable and clean energy. Therefore, the design of a robust controller to control the output parameters of the islanded microgrid and suppress load variations and disturbances is essential. In this paper, a hysteresis controller is proposed and designed to control the output voltage of an islanded AC microgrid and an improved sliding mode controller (SMC) based on adaptive control principle is designed to control the current of the microgrid. The current controller consists of two parts: An adaptation part, which aims to eliminate disturbances and system uncertainties, and a second part, which aims to deal with the tracking problem of the system under parameter-varying topologies. The adaptation strategy has the advantage of solving the gain tuning problem and chattering reduction. It also requires limited information about disturbance and uncertainties of the system. To validate the proposed control methodology and show its effectiveness, a case study of a simulated islanded microgrid is presented. The results show that the proposed controllers can effectively control the current and voltage underload changes and increase the stability and resilience of the microgrid. The results also reveal that the performance of the proposed controller in terms of total harmonic distortion (THD) and dynamic response overcome the performance of conventional controller by a 4× reduction in THD and 40–200× reduction in settling time.
Innovative Energy Technologies in Road Transport in Selected EU Countries
Authors: Kraciuk Jakub , Kacperska Elżbieta , Łukasiewicz Katarzyna , Pietrzak Piotr
Published: August 2022

The primary aim of this study was to assess and classify selected EU countries to groups differing in terms of the degree of implementation of innovative energy technologies to alleviate adverse externalities in road transport. This aim was realised using three groups of research methods: collection of empirical data, data processing and presentation of study outcomes. When collecting the research material, the authors used the method of critical literature review and the documentation method. The research material was processed using the agglomerative clustering technique, which was one of the hierarchical clustering methods. The distance between objects (here, selected EU countries) was determined based on the Euclidean distance. The outcome of this analysis was a dendrogram, which constitutes a graphical interpretation of obtained results. The study was conducted on 21 EU countries. The analyses covered the years 2013–2019. The sources of materials included literature on the subject and the Eurostat data. The problem of innovative energy technologies in road transport is presently of considerable importance. This results from the current situation related to human activity. As a result of the conducted cluster analysis, groups were distinguished based on differences in the use of innovative energy technologies alleviating negative externalities generated by road transport. The first group comprised Sweden, the Netherlands and Finland. Compared to the other groups, this group was distinguished by the highest values of four indexes, i.e., the share of renewable energy sources used in transport in 2019, the share in the market of electric passenger vehicles in 2019, the share in the market of electric lorries in 2019, as well as the share in the market of hybrid automobiles in 2019. Countries which participated the least in the elimination of negative externalities generated by road transport included Romania, Hungary, Greece, Poland, Latvia and Estonia.
District Heating and Cooling towards Net Zero
Authors: Ravelli Silvia
Published: August 2022

District energy is undergoing a deep transformation towards higher efficiency and greater flexibility through the promotion of renewable energy and waste energy sources [...]
Modeling, Control and Stability Analysis of Power Systems Dominated by Power Electronics
Authors: Chen Xin , Huang Tong , Zhang Donghui
Published: August 2022

With the growth of economic and social demand for electricity, the power system has gradually evolved into a complex network containing a high proportion of renewable generators and large-scale electrical devices [...]
Influence of the Industry’s Output on Electricity Prices: Comparison of the Nord Pool and HUPX Markets
Authors: Rembeza Jerzy , Przekota Grzegorz
Published: August 2022

Electricity markets are characterised by high sensitivity to variations in supply and demand conditions. However, they also exhibit a number of specific characteristics, including large daily, weekly, and seasonal price fluctuations. The aim of this article is to assess the impact of fluctuations in the industry’s output on wholesale electricity prices. Results were compared for the Nord Pool markets, with a high share of renewable energy supply, and the HUPX markets, where fossil fuel and/or nuclear energy supply dominates. The results obtained generally indicate the positive impact of changes in the industry’s output on wholesale electricity prices. This impact was stronger in the HUPX markets and for periods in daily and weekly cycles with higher energy demands. The results indicate that the sensitivity of electricity prices to fluctuations in the industry’s output is lower in markets with a higher share of renewable energy, especially for periods with higher energy demands.
Nuclear and New Energy Technology
Authors: Davydov Roman
Published: August 2022

Due to the growing demand for electrical energy generation worldwide [...]
Torque Superposition Compensation Fault-Tolerant Control for Dual Three-Phase PMSM with an Inverter Single-Leg Open-Circuit Fault
Authors: Zhou Yongyang , Yao Fei , Zhao Shuguang
Published: August 2022

Dual three-phase permanent-magnet synchronous motors (PMSM) have wide applications in electric vehicles due to advantages such as excellent control performance and outstanding fault tolerance capability. However, present fault-tolerant control of inverter single-leg open-circuit faults cannot make full use of each phase winding of the motor, which limits the torque-production capability. This paper proposes a torque superposition compensation (TSC) control which can minimize the stator copper losses while increasing the torque-production capability. The phase winding originally connected to the faulty inverter leg is then linked to the DC-link mid-point. Thus, the winding in the faulty phase can be utilized to generate an additional torque. The symmetric dual three-phase windings torque model and the asymmetric five-phase windings compensation torque model for Ud/2 voltage level are constructed according to the torque superposition, respectively. Then, the three-subplane decomposition transformation matrix for the post-fault dual three-phase PMSM is derived, and the decoupling model in the d-q subplane is constructed, which achieves the optimal enhancement of the torque-production capability. The simulation results verify the effectiveness of the proposed TSC fault-tolerant control.
Raman Spectroscopy of Lignite Gasification Char Morphotypes
Authors: Morga Rafał , Bielowicz Barbara
Published: August 2022

The purpose of this study is to characterize and compare the microstructural features of the main morphotypes occurring in the char obtained at 850–950 °C by fluidized bed gasification of lignite from the “Szczerców” deposit (Central Poland), and to bring new insights into the knowledge on the origin of these morphotypes. Optical microscopy and Raman spectroscopy were used. The char is composed mostly of crassinetwork and inertoid, accompanied by tenuinetwork and small amounts of fusinoid. Tenuinetwork originates mainly from textinite, crassinetwork is formed from attrinite, while inertoid results from transformation of strongly gelified macerals such as densinite and ulminite. Similarities in the microstructure of tenuinetwork and crassinetwork as well as inertoid and fusinoid are observed. Inertoid and fusinoid are composed of larger aromatic systems, with lower amount of alkyl-aryl structures, and their microstructure is better organized compared to tenuinetwork and crassinetwork. Inertoid and fusinoid differ in microscopic appearance and were formed from different starting materials, but their microstructural properties converged during gasification. Different morphological features of the network morphotypes (tenuinetwork, crassinetwork) are not reflected in the differences in their microstructural characteristics.
The Carbon Emission Trading Policy of China: Does It Really Boost the Environmental Upgrading?
Authors: Shahid Rabia , Li Shijie , Gao Jian , Altaf Muhammad Ahsan , Jahanger Atif , Shakoor Awais
Published: August 2022

China’s rapid industrialization has led to massive resource consumption, and the country has recently been highlighted as the World’s top carbon emitter. To pursue a sustainable economy via environmental upgrading, reductions in carbon emission levels are of great concern. The carbon emission reduction policy (CETP) is an environmental regulation aimed at cutting emissions and achieving environmental protection. Based on panel data of pilot and non-pilot regions, this study investigated the policy impact of the CETP on carbon emission reduction through difference-in-differences (DID). The findings, based on pooled OLS (ordinary least squares) and LSDV (least square dummy variable) regressions, revealed that the carbon emissions of the pilot regions (Beijing, Tianjin, Shanghai, Guangdong, Chongqing, and Hubei) had reduced by 12 percent more than the non-pilot regions. Thus, this implies that the CETP causes environmental upgrading. The results were further verified using a number of robustness checks, including parallel trends, placebo test, Granger causality test, and DID regression with a longer sample period. Based on the study findings, it was concluded that to achieve higher upgrade levels related to the environment, the CETP needs to be encouraged and improved for nationwide implementation. Furthermore, sustainable economic development in China also needs strict environmental regulations and policy measures.
Third-Party Damage Model of a Natural Gas Pipeline Based on a Bayesian Network
Authors: Zhu Baikang , Yang Xu , Wang Jun , Shao Chuanhui , Li Fei , Hong Bingyuan , Song Debin , Guo Jian
Published: August 2022

Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently, it is necessary for pipeline operation companies to secure investment on safety, to make sure that the safety equipment (system) works and is in a good condition, to maintain the safety inspection frequency in an organization, to build a management system for residents along the pipeline, and to conduct routine safety performance assessments accordingly.
Improving Transient Stability of a Synchronous Generator Using UIPC with a Unified Control Scheme
Authors: Ghafouri Saeed , Hajiahmadi Mohammad Ali , Firouzi Mehdi , Gharehpetian Gevork B. , Mobayen Saleh , Skruch Paweł
Published: August 2022

In this paper, the Unified Interphase Power Controller (UIPC) is utilized to protect the synchronous generator in case of faults occurring in the transmission system. The UIPC not only maintains the generator’s stability by keeping its load angle within safe operational limits but also prevents high-amplitude currents from flowing through the stator windings. This also allows for more loading on the generator without compromising the system’s stability. Moreover, utilization of the UIPC improves the LVRT capability of the generator by injecting reactive power at the faulted location. Additionally, a novel unified control scheme is proposed for the UIPC that enhances its performance by omitting the necessity of fault detection algorithms. To evaluate the performance of the proposed controller and the efficacy of the UIPC in protecting the synchronous generator under the faults, simulations have been conducted in a MATLAB/Simulink environment. A test grid was developed comprising a synchronous generator, transmission line model, UIPC, and an infinite grid representing the Point of Common Coupling (PCC), and three fault scenarios have been implemented in the transmission system. The comparative analysis of simulation results demonstrates the capability and efficacy of UIPC in isolating the synchronous generator from the faulted location, which in turn not only enhances transient stability of the generator, but also protects generator windings from detrimental faults currents. Moreover, according to the results, UIPC also contributes to recovering the voltage dip of the fault location via injecting reactive power.
Effects of Excess Nitrogen (N) on Fine Root Growth in Tropical Forests of Contrasting N Status
Authors: Zhu Feifei , Gilliam Frank S. , Mulder Jan , Yoh Muneoki , Mo Jiangming , Lu Xiankai
Published: August 2022

Elevated nitrogen (N) deposition may further acidify soils in tropical forests. Yet, we have limited evidence on this prediction and it remained unclear how this would affect fine root growth therein. Here, we report responses of fine root biomass, vitality, and chemistry, as well as related soil parameters to eight years of N additions in three tropical forests different in initial soil N status, with one primary forest being N-saturated, and another two younger forests (one secondary forest and one planted forest) less N-rich. Results showed that in the primary forest, fine root biomass decreased and fine root necromass increased following N addition, resulting in lower live fine root proportion (fine root vitality). Declining fine root vitality was associated with fine root Fe accumulation and soil acidification indicated by regression analysis. These alterations of fine root growth and chemistry co-occurred with soil pH decline, soil exchangeable Fe3+ mobilization, exchangeable Ca2+, and Mg2+ depletion after N treatments in the primary forest. In contrast, N addition only elevated fine root K, Al, and Fe content in the secondary forest. In the planted forest, moderate but significant decreases in soil pH, soil exchangeable K+, and Mg2+ were found after N treatment, with fine root biomass negatively correlated with soil exchangeable Al3+ and Al3+/(Ca2+ + Mg2+) ratio. Our results suggested that long-term N fertilization may negatively affect fine root growth, via severed soil acidification, Fe mobilization, and base cation depletion in highly acidified, N-saturated primary tropical forests. Initial forest N status, influenced by different land-use history, mediates N deposition effects on fine root growth.
Changes in Forest Conditions in a Siberian Larch Forest Induced by an Extreme Wet Event
Authors: Nogovitcyn Aleksandr , Shakhmatov Ruslan , Morozumi Tomoki , Tei Shunsuke , Miyamoto Yumiko , Shin Nagai , Maximov Trofim C. , Sugimoto Atsuko
Published: August 2022

The taiga forest, a semi-arid and nitrogen-limited ecosystem on permafrost, has changed under extreme wet events. This study aims to understand the changes that occurred in a larch forest in Eastern Siberia after the wet event of 2006–2007. In the summer of 2018, studies were conducted at the Spasskaya Pad Experimental Forest Station near Yakutsk, Russia, where a transect (60 m × 510 m) with 34 plots (30 m × 30 m) was set. It included intact sites and affected sites with different levels of forest damage, owing to the extreme wet event. We observed spatial variations in the normalized difference vegetation index (NDVI) calculated from Landsat satellite-observed data, and the foliar δ13C, δ15N, and C/N (carbon/nitrogen) ratio obtained from the needle samples of 105 mature larch trees. Our results reveal that the affected plots had a lower NDVI than the intact plots, resulting from a difference in tree stand density. In addition, the stand density is suggested to be a controlling factor in the spatial variations in the foliar C/N and δ13C values based on their significant relationships with the NDVI in June. We concluded that the larch trees from the regenerating forests in the affected areas have a higher nitrogen level and light availability (relatively low C/N and high δ13C) because of the slight competition for resources, owing to a low-stand density. This may lead to further succession of the larch forests after the extreme wet event.
The Habitat Type and Scale Dependences of Interspecific Associations in a Subtropical Evergreen Broad-Leaved Forest
Authors: Jiang Changchun , Fu Jiaqin , Wang Yunquan , Chai Pengtao , Yang Yidan , Mi Xiangcheng , Yu Mingjian , Ma Keping , Chen Jianhua
Published: August 2022

“Interspecific associations” refers to the interrelationship among different species in a particular spatial distribution, which plays an important role in species distribution, community assembly, and responses to environmental changes. However, the strength and/or direction of interspecific associations may vary with environmental gradients and scales. To understand the effects of habitat types and research scales on interspecific associations in subtropical forests, we modeled the interspecific associations for more than 15,000 individuals representing 74 co-occurring species from three habitat types and three scales by using the variance ratio and the Spearman rank correlation coefficient. We found that overall interspecific associations at a community level exhibited significant positive associations for most habitat types and scales. Moreover, interspecific associations of pairwise species have strong habitat dependence, and the association strengths decreased with the increase in elevation (change in habitat types). However, the scale dependence of pairwise interspecific associations varies with habitat types. The strength of interspecific associations increased with the increasing scales (10 m × 10 m, 20 m × 20 m, and 40 m × 40 m) at low-valleys and mid-hillside habitats, while the scale-dependent effect was not detected at high-ridges. In conclusion, our study highlights the importance of environmental gradients and research scales on interspecific associations in diverse subtropical forests, and environmental gradients and research scales should be considered in future studies.
Fermented Milk Product Enriched with γ-PGA, Peptides and GABA by Novel Co-Fermentation with Bacillus subtilis and Lactiplantibacillus plantarum
Authors: Lee Sam-Pin , Yoon Woong-Kyu , Lee Jinho , Garcia Coralia V.
Published: August 2022

Milk was co-fermented with Bacillus subtilis HA and Lactiplantibacillus plantarum EJ2014 to produce a dairy ingredient enriched with poly-γ-glutamic acid (γ-PGA) and γ-aminobutyric acid (GABA). The first fermentation of milk with B. subtilis HA resulted in a viscous broth with pH 6.56, 0.26% acidity, 1.40 mg/g tyrosine equivalent, and 17.21 U/g protease activity. The viable cell counts of B. subtilis indicated 8.74 log CFU/mL, and the consistency index of the alkaline fermented milk was 1.82 Pa·sn. In addition, 4.65% mucilage was produced with 35.93% γ-PGA content. The milk co-fermented by L. plantarum indicated 1.34% acidity and pH 4.91. The viable bacterial counts of B. subtilis decreased to 4.44 log CFU/mL, whereas those of L. plantarum increased to 9.42 log CFU/mL. Monosodium glutamate (MSG) as a precursor was effectively converted into γ-PGA by B. subtilis, and then residual MSG was completely converted into GABA by L. plantarum with a yield of 26.15 mg/g. Furthermore, the co-fermented milk produced volatiles, including hexanoic acid, 2,3-butanediol, and acetoin, which may be responsible for its aged cheese-like aroma.
Effects of Glucose and Homogenization Treatment on the Quality of Liquid Whole Eggs
Authors: Hu Wei , Wu Yong , Chen Hongbing , Gao Jinyan , Tong Ping
Published: August 2022

To investigate the effect of glucose on the protein structure, physicochemical and processing properties of liquid whole eggs (LWE) under homogenization, different concentrations of glucose (0.01, 0.02, 0.04, 0.08 g/mL) were added into LWE, followed by homogenizing at different pressures (5, 10, 20, 40 MPa), respectively. It was shown that the particle size and turbidity of LWE increased with the increase in glucose concentration while decreasing with the increase in homogenization pressure. The protein unfolding was increased at a low concentration of glucose combined with homogenization, indicating a 40.33 ± 5.57% and 165.72 ± 33.57% increase in the fluorescence intensity and surface hydrophobicity under the condition of 0.02 g/mL glucose at 20 MPa, respectively. Moreover, the remarkable increments in foaming capacity, emulsifying capacity, and gel hardness of 47.57 ± 5.1%, 66.79 ± 9.55%, and 52.11 ± 9.83% were recorded under the condition of 0.02 g/mL glucose at 20 MPa, 0.04 g/mL glucose at 20 MPa, and 0.02 g/mL glucose at 40 MPa, respectively. Reasonably, glucose could improve the processing properties of LWE under homogenization, and 0.02 g/mL–0.04 g/mL and 20–40 MPa were the optimal glucose concentration and homogenization pressure. This study could contribute to the production of high-performance and stable quality of LWE.
Detection of Soluble Solids Content in Different Cultivated Fresh Jujubes Based on Variable Optimization and Model Update
Authors: Sun Haixia , Zhang Shujuan , Ren Rui , Xue Jianxin , Zhao Huamin
Published: August 2022

To solve the failure problem of the visible/near infrared (VIS/NIR) spectroscopy model, soluble solids content (SSC) detection for fresh jujubes cultivated in different modes was carried out based on the method of variable optimization and model update. Iteratively retained informative variables (IRIV) and successive projections algorithm (SPA) algorithms were used to extract characteristic wavelengths, and least square support vector machine (LS-SVM) was used to establish detection models. Compared with IRIV, IRIV-SPA achieved better performance. Combined with the offset properties of the wavelength, repeated wavelengths were removed, and wavelength recombination was carried out to create a new combination of variables. Using these fused wavelengths, the model was recalibrated based on the Euclidean distance between samples. The LS-SVM detection model of SSC was established using the update method of wavelength fusion-Euclidean distance. Good prediction results were achieved using the proposed model. The determination coefficient (R2), root mean square error (RMSE), and residual predictive deviation (RPD) of the test set on SSC of fresh jujubes cultivated in the open field were 0.82, 1.49%, and 2.18, respectively. The R2, RMSE, and RPD of the test set on SSC of fresh jujubes cultivated in the rain shelter were 0.81, 1.44%, and 2.17, respectively. This study realized the SSC detection of fresh jujubes with different cultivation and provided a method for the establishment of a robust VIS/NIR detection model for fruit quality, effectively addressing the industry need for identifying jujubes grown in the open field.
Sargassum thunbergii Extract Attenuates High-Fat Diet-Induced Obesity in Mice by Modulating AMPK Activation and the Gut Microbiota
Authors: Kim Dahee , Yan Jing , Bak Jinwoo , Park Jumin , Lee Heeseob , Kim Hyemee
Published: August 2022

Sargassum thunbergii (Mertens ex Roth) Kuntze (ST) is a brown alga rich in indole-2-carboxaldehyde. This study aimed to investigate the anti-obesity effects of ethanol extract from ST in in vitro and in vivo models. In 3T3-L1 cells, ST extract significantly inhibited lipid accumulation in mature adipocytes while lowering adipogenic genes (C/epba and Pparg) and enhancing metabolic sensors (Ampk, Sirt1), thermogenic genes (Pgc-1a, Ucp1), and proteins (p-AMPK/AMPK and UCP1). During animal investigation, mice were administered a chow diet, a high-fat diet (HF), or an HF diet supplemented with ST extract (at dosages of 150 and 300 mg/kg bw per day) for 8 weeks (n = 10/group). ST extract administration decreased weight gain, white adipose tissue weight, LDL-cholesterol, and serum leptin levels while improving glucose intolerance. In addition, ST extract increased the expression of Ampk and Sirt1 in adipose tissue and in the liver, as well as p-AMPK/AMPK ratio in the liver, compared to HF-fed mice. The abundance of Bacteroides vulgatus and Faecalibacterium prausnitzii in the feces increased in response to ST extract administration, although levels of Romboutsia ilealis decreased compared with those in HF-fed mice. ST extract could prevent obesity in HF-fed mice via the modulation of AMPK activation and gut microbiota composition.
Recent Advances in OMICs Technologies and Application for Ensuring Meat Quality, Safety and Authenticity
Authors: Gagaoua Mohammed
Published: August 2022

Consumers and stakeholders are increasingly demanding that the meat industry guarantees high-quality meat products with stable and acceptable sensory and safety properties [...]
Experiments on the Electron Impact Excitation of Hydrogen Molecules Indicate the Presence of the Second Flavor of Hydrogen Atoms
Authors: Oks Eugene
Published: August 2022

In one of our previous papers, we performed a comparative analysis of the experimental and theoretical cross-sections for the excitation of atomic hydrogen by electrons. We found that the theoretical ratio of the cross-section σ2s of the excitation of the state 2s to the cross-section σ2p of the excitation of the state 2p was systematically higher than the corresponding experimental ratio by about 20% (far beyond the experimental error margins). We showed that this discrepancy can be due to the presence of the Second Flavor of Hydrogen Atoms (SFHA) in the experimental gas and that the share of the SFHA in the mixture, required for removing this discrepancy, was about the same as the share of the usual hydrogen atoms. The theory behind the SFHA was based on the standard quantum mechanics—on the second solution of the Dirac equation for hydrogen atoms—and on the experimental fact that the charge distribution inside the proton has the peak at the center of the proton; the term “flavor” was used by the analogy with flavors of quarks. In the present paper, we used the same guiding principles, as employed in that previous study, for the comparative analysis of the experimental and theoretical cross-sections for the excitation of molecular hydrogen by electrons. We found that presumably the most sophisticated calculations, using the convergent close-coupling method involving 491 states, very significantly underestimate the corresponding experimental cross-sections for the two lowest stable triplet states. We showed that if in some hydrogen molecules one or both atoms would be the SFHA, then the above very significant discrepancy could be eliminated. We estimated that it would take such unusual hydrogen molecules to be represented in the experimental gas by the share of about 0.26. This is just by about 40% smaller than the share 0.45 of the SFHA deduced in our previous analysis of the experiment on the electron impact excitation of hydrogen atoms (rather than hydrogen molecules). It should be emphasized that from the theoretical point of view, the share of the unusual hydrogen molecules in any experimental gas and the share of the unusual hydrogen atoms (SFHA) in any experimental gas should not be expected to coincide (it would be the comparison of “apples to oranges”, rather than “apples to apples”). In addition, given the roughness of the above estimates, we can state that the results of the present paper reinforce the main conclusion of our previous papers of the very significant share of the SFHA in the experimental hydrogen gases. Thus, the experiments on the electron impact excitation of hydrogen molecules are the fourth type of atomic experiments that proved the existence of the SFHA.
Gene–microRNA Network Analysis Identified Seven Hub Genes in Association with Progression and Prognosis in Non-Small Cell Lung Cancer
Authors: Yang Zhiyuan , Wang Hongqi , Zhao Zixin , Jin Yunlong , Zhang Zhengnan , Tan Jiayi , Hu Fuyan
Published: August 2022

Introduction: Lung cancer is the leading cause of cancer deaths in the world and is usually divided into non-small cell lung cancer (NSCLC) and small cell lung cancer. NSCLC is dominant and accounts for 85% of the total cases. Currently, the therapeutic method of NSCLC is not so satisfactory, and thus identification of new biomarkers is critical for new clinical therapy for this disease. Methods: Datasets of miRNA and gene expression were obtained from the NCBI database. The differentially expressed genes (DEGs) and miRNAs (DEMs) were analyzed by GEO2R tools. The DEG-DEM interaction was built via miRNA-targeted genes by miRWalk. Several hub genes were selected via network topological analysis in Cytoscape. Results: A set of 276 genes were found to be significantly differentially expressed in the three datasets. Functional enrichment by the DAVID tool showed that these 276 DEGs were significantly enriched in the term “cancer”, with a statistic p-value of 1.9 × 10−5. The subdivision analysis of the specific cancer types indicated that “lung cancer” occupies the largest category with a p-value of 2 × 10−3. Furthermore, 75 miRNAs were shown to be differentially expressed in three representative datasets. A group of 13 DEGs was selected by analysis of the miRNA–gene interaction of these DEGs and DEMs. The investigation of these 13 genes by GEPIA tools showed that eight of them had consistent results with NSCLC samples in the TCGA database. In addition, we applied the KMplot to conduct the survival analysis of these eight genes and found that seven of them have a significant effect on the prognosis survival of patients. We believe that this study could provide effective research clues for the prevention and treatment of non-small cell lung cancer.