bluuebunny/crossref_metadata_2025 huggingface dataset:
A 10-Year-Old Girl’s Dysfunctional ‘Self-Help’ in ADHD: Suppression of Hyperkinetic Symptoms via Self-Induced Weight Loss in the Context of Anorexia Nervosa—A Case Report
Authors: Mestermann Stefan , Stonawski Valeska , Böhm Lea , Kratz Oliver , Moll Gunther H. , Horndasch Stefanie
Published: September 2023

Anorexia Nervosa (AN) and Attention Deficit Hyperactivity Disorder (ADHD) are frequent mental disorders in child and adolescent psychiatry. Comorbidity of these disorders is, however, rare among minors. Thus, little is known about their mutual impact on illness development as well as diagnostic and therapeutic influencing factors. We report the case of a 10-year old girl with AN and massive underweight. At the age of 5, ADHD had been diagnosed. Application of ADHD-specific medication had been refused by her caregiver. As of 3rd grade, hyperkinetic symptoms were significantly reduced, which was later linked to beginning AN-induced weight loss. At inpatient admission, no clinically relevant ADHD-related symptoms were present. Accompanying weight gain, rather ‘sudden’ appearance of attention difficulties, motoric hyperactivity and impulsivity were reported, widely impairing our patient’s schoolwork and further daily life. Methylphenidate medication showed good clinical response and tolerability. We hypothesize that the former massive underweight had suppressed ADHD-specific behaviour. AN with significant weight loss could possibly mask hyperkinetic symptoms in children. Thus, sufficient clinical diagnostics and intense monitoring during ED treatment are required. Physicians and therapists should be sensitized for interactions in the joint occurrence of these mental disorders among minors.
Reactive Sputter Deposition of Ga2O3 Thin Films Using Liquid Ga Target
Authors: Gajdics Marcell , Serényi Miklós , Kolonits Tamás , Sulyok Attila , Horváth Zsolt Endre , Pécz Béla
Published: September 2023

Ga2O3 is a promising material in the optoelectronics and semiconductor industry. In this work, gallium oxide thin films were deposited via radio frequency (RF) sputtering, using a liquid Ga target. The reactive sputtering was carried out using different oxygen flow rates and DC target potentials induced via the RF power. The thickness of the samples varied between 160 nm and 460 nm, depending on the preparation conditions. The composition and the refractive index of the layers were investigated via energy-dispersive spectroscopy, X-ray photoelectron spectroscopy, and spectroscopic ellipsometry, respectively. It was found that, through the use of a lower DC target potential, a better film quality and higher oxygen content can be achieved. The reactive sputtering was modeled based on the Berg model, with the aim of determining the sputtering yields and the sticking coefficient. It was shown that an increase in DC target potential leads to the preferential sputtering of gallium.
The Use of IoT for Determination of Time and Frequency Vibration Characteristics of Industrial Equipment for Condition-Based Maintenance
Authors: Turkin Ihor , Leznovskyi Viacheslav , Zelenkov Andrii , Nabizade Agil , Volobuieva Lina , Turkina Viktoriia
Published: September 2023

The subject of study in this article is a method for industrial equipment vibration diagnostics that uses discrete Fourier transform and Allan variance to increase precision and accuracy of industrial equipment vibration diagnostics processes. We propose IoT-oriented solutions based on smart sensors. The primary objectives include validating the practicality of employing platform-oriented technologies for vibro-diagnostics of industrial equipment, creating software and hardware solutions for the IoT platform, and assessing measurement accuracy and precision through the analysis of measurement results in both time and frequency domains. The IoT system architecture for industrial equipment vibration diagnostics consists of three levels. At the autonomous sensor level, vibration acceleration indicators are obtained and transmitted via a BLE digital wireless data transmission channel to the second level, the hub, which is based on a BeagleBone single-board microcomputer. The computing power of BeagleBone is sufficient to work with artificial intelligence algorithms. At the third level of the server platform, the tasks of diagnosing and predicting the state of the equipment are solved, for which the Dictionary Learning algorithm implemented in the Python programming language is used. The verification of the accuracy and precision of the vibration diagnostics system was carried out on the developed stand. A comparison of the expected and measured results in the frequency and time domains confirms the correct operation of the entire system.
Distribution and Conservation Status of European Pond Turtles Emys orbicularis (L., 1758) in Algeria
Authors: Gherbi Nourhane , Tiar-Saadi Manel , Boucheker Abdennour , Široký Pavel , Mezghiche Chahinez , Draidi Khalil , Bouslama Zihad , Tiar Ghoulem
Published: September 2023

The Maghreb population of Emys orbicularis extends over a narrow strip of northern Morocco, Algeria, and Tunisia. Our understanding of the presence of this turtle in Algeria, in contrast to Morocco and Tunisia, is quite limited and frequently rests on a few small-scale studies or even reports from a century ago. The present study provides the first complete data on the distribution and level of threat of this species in Algeria. A field survey was carried out based on the data obtained from scattered local reports and available studies that suggested the presence of the species in Algerian wetlands. Data on climatic and habitat preferences, the geographic elevation of inhabited localities, and their conservation status were collected. A total of 45 wetlands were inhabited by E. orbicularis, of which 40 were part of a well-interconnected eastern metapopulation, joined by an extensive hydrographic network. In some places, the species has persisted for over 130 years in the same wetland complex. However, the five remaining populations living in central North Algeria are fragmented, highly isolated, and therefore more threatened. With a few exceptions, turtles inhabit lowlands below 100 m above sea level. Detected sub-populations inhabit mostly stagnant waters (60%), sometimes dams and lakes (24%), and sporadically also slow-moving water bodies (16%). Altogether, the Algerian distribution of E. orbicularis extends to a total area of 2900 km2, a 40 km wide strip with a length of 490 km west of the Tunisian border. Although restricted to this narrow strip, the persistence of numerous populations in Algeria, especially in Numidia, testifies to their relatively better conservation status. In order to ensure the sustainability of these efforts, follow-up and monitoring activities should be suggested, with special attention paid to highly isolated populations to maintain their long-term viability.
Current Obstacles (With Solutions) in Type 2 Diabetes Management, Alongside Future Directions
Authors: Belančić Andrej , Klobučar Sanja , Rahelić Dario
Published: September 2023

Dear Reader, [...]
Measuring Surface Deformation of Asphalt Pavement via Airborne LiDAR: A Pilot Study
Authors: Zhu Junqing , Gao Yingda , Huang Siqi , Bu Tianxiang , Jiang Shun
Published: September 2023

Measuring the surface deformation of asphalt pavement and acquiring the rutting condition is of great importance to transportation agencies. This paper proposes a rutting measuring method based on an unmanned aerial vehicle (UAV) mounted with Light Detection and Ranging (LiDAR). Firstly, an airborne LiDAR system is assembled and the data acquisition method is presented. Then, the method for point cloud processing and rut depth computation is presented and the results of field testing are discussed. Thirdly, to investigate error factors, the laser footprint positioning model is established and sensitivity analysis is conducted. Factors including flight height, LiDAR instantaneous angel, and ground inclination angle are discussed. The model was then implemented to obtain the virtual rut depth and to verify the accuracy of the field test results. The main conclusions include that the measurement error increases with the flight height, instantaneous angle, and angular resolution of the LiDAR. The inclination angle of the pavement surface has adverse impact on the measuring accuracy. The field test results show that the assembled airborne LiDAR system is more accurate when the rut depth is significant. The findings of this study pave the way for future exploration of rutting measurement with airborne LiDAR.
Quantum Information Entropy for Another Class of New Proposed Hyperbolic Potentials
Authors: Santana-Carrillo R. , de J. León-Montiel Roberto , Sun Guo-Hua , Dong Shi-Hai
Published: September 2023

In this work, we investigate the Shannon entropy of four recently proposed hyperbolic potentials through studying position and momentum entropies. Our analysis reveals that the wave functions of the single-well potentials U0,3 exhibit greater localization compared to the double-well potentials U1,2. This difference in localization arises from the depths of the single- and double-well potentials. Specifically, we observe that the position entropy density shows higher localization for the single-well potentials, while their momentum probability density becomes more delocalized. Conversely, the double-well potentials demonstrate the opposite behavior, with position entropy density being less localized and momentum probability density showing increased localization. Notably, our study also involves examining the Bialynicki–Birula and Mycielski (BBM) inequality, where we find that the Shannon entropies still satisfy this inequality for varying depths u¯. An intriguing observation is that the sum of position and momentum entropies increases with the variable u¯ for potentials U1,2,3, while for U0, the sum decreases with u¯. Additionally, the sum of the cases U0 and U3 almost remains constant within the relative value 0.01 as u¯ increases. Our study provides valuable insights into the Shannon entropy behavior for these hyperbolic potentials, shedding light on their localization characteristics and their relation to the potential depths. Finally, we extend our analysis to the Fisher entropy F¯x and find that it increases with the depth u¯ of the potential wells but F¯p decreases with the depth.
Topology Optimization of Turbulent Flow Cooling Structures Based on the k-ε Model
Authors: Sun Yiwei , Hao Menglong , Wang Zexu
Published: September 2023

Topology optimization (TO) is an effective approach to designing novel and efficient heat transfer devices. However, the TO of conjugate heat transfer has been essentially limited to laminar flow conditions only. The present study proposes a framework for TO involving turbulent conjugate heat transfer based on the variable density method. Different from the commonly used and oversimplified Darcy model, this approach is based on the more accurate and widely accepted k-ε model to optimize turbulent flow channels. We add penalty terms to the Navier–Stokes equation, turbulent kinetic energy equation, and turbulent energy dissipation equation, and use interpolation models for the thermal properties of materials. A multi-objective optimization function, aiming to minimize the pressure drop and the average temperature, is set up to balance the thermal and hydraulic performance. A case study is conducted to compare various optimization methods in the turbulent regime, and the results show that the present method has substantially higher optimization effectiveness while remaining computationally inexpensive.
Stability Analysis of Switched Linear Singular Systems with Unstable and Stable Modes
Authors: Xiong Jiandong , Wang Yidian , Huo Yanfang , Zhao Hongpeng
Published: September 2023

In this paper, stability is studied for a class of switched singular systems containing both stable and unstable modes. By introducing a time-varying piecewise Lyapunov function (TVPLF) and a mode-dependent average dwell time (ADT) switching rule, the computable sufficient conditions for system stability are derived. The time-varying piecewise Lyapunov functions are piecewise continuously differentiable on every mode (but may not be differentiable at the interpolating points of the dwell time). This Lyapunov function method is particularly advantageous in overcoming the limitations of traditional multiple Lyapunov function (MLF) methods, which may not have a feasible solution when dealing with switched systems containing only unstable modes. As such, the TVPLF offers greater flexibility in application. Compared with the conventional ADT switching rule, the mode-dependent ADT switching rule not only enables each mode to have its own ADT but also allows for its own switching strategy. Specifically, the stable mode adopts a slow switching strategy while the unstable mode adopts a fast one, thereby reducing the conservatism of the ADT switching rule. Furthermore, based on the stability analysis, the time-varying controllers are proposed to stabilize the switched singular system, which can be expressed as the sequential linear combination of a series of linear state feedback on each mode. The proposed controllers are continuous for each mode, which are different from the controllers designed through the traditional MLF and MDLF methods, where the controllers designed by traditional MLF are the time-invariant linear state feedback in each mode while the controllers designed by the MDLF are piecewise continuous for each mode.
Improving the System of Indicators for Assessing the Effectiveness of Modern Regional Innovation Systems
Authors: Strielkowski Wadim , Kalyugina Svetlana , Fursov Victor , Mukhoryanova Oxana
Published: September 2023

In the post-pandemic social and economic conditions, the proper assessment of the effectiveness of regional innovation systems (RISs) becomes a key endeavor. In our paper, we highlight the necessity to enhance the set of indicators used to evaluate the performance of regional innovation systems in countries with varying innovation capabilities. Specifically, we concentrate on examining case studies from the United States, Japan, China, and the Czech Republic, comparing their experiences with the current situation to innovations and innovation systems in Russia and drawing lessons for this country. Utilizing the Global Innovation Index (GII) rankings, we conduct an analysis of the characteristics of innovative progress and propose specific groups of indicators that can enhance the effectiveness of evaluating the innovative advancement of different regions. Moreover, we determine the need for uniqueness, flexibility, and adaptability of these based on the state’s strategic guidelines in the field of innovation and the innovative potential of the territory as well as the factors of external and internal influence. In addition, we conduct and present the results of the bibliometric network analysis of the research publications retrieved from the Web of Science (WoS) database using VOSViewer software and covering the role of regional innovation systems (RISs) in shaping up the national innovation systems (NISs) both in general terms and specifically applied to the case of Russia. Our results might be relevant for the stakeholders and policymakers who are engaged in promoting innovation, regional development, and sustainable economic growth, as well as for the academics working on the topics of innovation and economic development.
MegaDetectNet: A Fast Object Detection Framework for Ultra-High-Resolution Images
Authors: Wang Jian , Zhang Yuesong , Zhang Fei , Li Yazhou , Nie Lingcong , Zhao Jiale
Published: September 2023

Addressing the challenge of efficiently detecting objects in ultra-high-resolution images during object detection tasks, this paper proposes a novel method called MegaDetectNet, which leverages foreground image for large-scale resolution image object detection. MegaDetectNet utilizes a foreground extraction network to generate a foreground image that highlights target regions, thus avoiding the computationally intensive process of dividing the image into multiple sub-images for detection, and significantly improving the efficiency of object detection. The foreground extraction network in MegaDetectNet is built upon the YOLOv5 model with modifications: the large object detection head and classifier are removed, and the PConv convolution is introduced to reconstruct the C3 module, thereby accelerating the convolution process and enhancing foreground extraction efficiency. Furthermore, a Res2Rep convolutional structure is developed to enlarge the receptive field and improve the accuracy of foreground extraction. Finally, a foreground image construction method is proposed, fusing and stitching foreground target regions into a unified foreground image. This approach replaces multiple divided sub-images with a single foreground image for detection, reducing overhead time. The proposed MegaDetectNet method’s effectiveness for detecting objects in ultra-high-resolution images is validated using the publicly available DOTA dataset. Experimental results demonstrate that MegaDetectNet achieves an average time reduction of 83.8% compared to the sub-image division method among various commonly used object detectors, with only a marginal 8.7% decrease in mAP (mean Average Precision). This validates the practicality and efficacy of the MegaDetectNet method for object detection in ultra-high-resolution images.
A Bi-Directional Two-Dimensional Deep Subspace Learning Network with Sparse Representation for Object Recognition
Authors: Li Xiaoxue , Feng Weijia , Wang Xiaofeng , Guo Jia , Chen Yuanxu , Yang Yumeng , Wang Chao , Zuo Xinyu , Xu Manlu
Published: September 2023

A principal component analysis network (PCANet), as one of the representative deep subspace learning networks, utilizes principal component analysis (PCA) to learn filters that represent the dominant structural features of objects. However, the filters used in PCANet are linear combinations of all the original variables and contain complex and redundant principal components, which hinders the interpretability of the results. To address this problem, we introduce sparse constraints into a subspace learning network and propose three sparse bi-directional two-dimensional PCANet algorithms, including sparse row 2D2PCANet (SR2D2PCANet), sparse column 2D2PCANet (SC2D2PCANet), and sparse row–column 2D2PCANet (SRC2D2PCANet). These algorithms perform sparse operations on the projection matrices in the row, column, and row–column direction, respectively. Sparsity is achieved by utilizing the elastic net to shrink the loads of the non-primary elements in the principal components to zero and to reduce the redundancy in the projection matrices, thus improving the learning efficiency of the networks. Finally, a variety of experimental results on ORL, COIL-100, NEC, and AR datasets demonstrate that the proposed algorithms learn filters with more discriminative information and outperform other subspace learning networks and traditional deep learning networks in terms of classification and run-time performance, especially for less sample learning.
Investigation of the Feasibility of the Dynamic Equivalent Model of Large Photovoltaic Power Plants in a Harmonic Resonance Study
Authors: Xie Yuzhe , He Yanhua , Zhou Xuntian , Zhang Zhigang
Published: September 2023

In recent years, there have been several harmonic resonance accidents around the world that involve renewable energy power plants. The frequency scanning method is the most widely used technique in engineering practice to evaluate the severity of resonance due to its simple operation and clear physical meaning. However, when establishing electromagnetic transient simulation models and conducting frequency scans, a single generation unit or a few renewable generation units are usually used to represent the original power plant for the purpose of reducing model complexity and improving the simulation efficiency. Such a practice has been found to be effective in dynamic studies around the fundamental frequency. However, its feasibility in harmonic resonance studies has not yet been fully investigated. Because of this research gap, a feasibility study is conducted in this paper by using a real-life photovoltaic power plant. The detailed harmonic model of the plant is first established using the harmonic linearization method, and the equivalent harmonic model is then developed using the power loss conservation method. The feasibility of the equivalent model was investigated in detail, and the impact of the different impedance models on the resonance analysis was analyzed. The results indicate that the conventional dynamic equivalent model can effectively reflect the harmonic resonance characteristics of photovoltaic power plants. Furthermore, a more simplified model that ignores the inductance of the collector line is recommended in this paper to further reduce the modeling complexity.
Sparse Adversarial Attacks against DL-Based Automatic Modulation Classification
Authors: Jiang Zenghui , Zeng Weijun , Zhou Xingyu , Feng Peilun , Chen Pu , Yin Shenqian , Han Changzhi , Li Lin
Published: September 2023

Automatic modulation recognition (AMR) serves as a crucial component in domains such as cognitive radio and electromagnetic countermeasures, acting as a significant prerequisite for the efficient signal processing of receivers. Deep neural networks (DNNs), despite their effectiveness, are known to be vulnerable to adversarial attacks. This vulnerability has inspired the introduction of subtle interference to wireless communication signals—interference so minuscule that it is difficult for the human eye to discern. Such interference can mislead eavesdroppers into erroneous modulation pattern recognition when using DNNs, thereby camouflaging communication signal modulation patterns. Nonetheless, the majority of current camouflage methods used for electromagnetic signal modulation recognition rely on a global perturbation of the signal. They fail to consider the local agility of signal disturbance and the concealment requirements for bait signals that are intercepted by the interceptor. This paper presents a generator framework designed to produce perturbations with sparse properties. Furthermore, we introduce a method to reduce spectral loss, which minimizes the spectral difference between adversarial perturbation and the original signal. This method makes perturbation more challenging to monitor, thereby deceiving enemy electromagnetic signal modulation recognition systems. The experimental results validated that the proposed method significantly outperformed existing methods in terms of generation time. Moreover, it can generate adversarial signals characterized by high deceivability and transferability even under extremely sparse conditions.
Evaluation of the Performances of Foam System as an Agent of Enhancing Oil Recovery
Authors: Liu Renjing , Wang Jing , Liu Huiqing
Published: September 2023

Foam has been used in petroleum engineering to enhance oil recovery for many years. It is a very complicated dispersion system, and the performances are affected by many factors. In order to understand the influence rules and mechanisms of such factors, the performances and mechanisms of foam systems are investigated by static and core flooding experiments with Sodium Dodecyl Sulfate. It is found that a polymer may reduce the foaming ability, but significantly enhance the foam stability in both oil-free and oil-bearing environments, while the optimal concentration is around 1500 mg/L in this case. NaCl may reduce the stability, but the capability of enhancing the foaming ability and oil tolerance gradually increases and stabilizes when the concentration reaches to 7000 mg/L. Oil can reduce the foam stability, and the stability decreases as the oil saturation increases to 0.15. Moreover, the foam stability is worse in light oil conditions than in heavy oil conditions. In the sand-pack tests, the resistance factors of foam are much higher than that of a polymer solution. The maximum resistance factor of the foam tested reaches about 230. The residual resistance factor of polymer-enhanced foam (PEF) is generally larger than that of pure foam and salt enhanced foam (SEF) in an oil-free environment. The maximum value of resistance factor of PEF and SEF is only about 60, and that of pure foam is less than 40 in an oil-bearing environment. In the parallel sand-pack tests, both ultimate oil recovery and incremental oil recovery are the best when using PEF, with SEF the second, and pure foam the worst.
Transitioning to Clean Energy: A Comprehensive Analysis of Renewable Electricity Generation in the EU-27
Authors: Dolge Kristiana , Blumberga Dagnija
Published: September 2023

The EU power sector is under increasing pressure due to rising electricity demand and the need to meet decarbonisation targets. Member states have been active in investing in renewables and building capacity to increase their share of renewables in electricity generation. However, it is important to examine what progress each member state has made in the deployment of renewable energy for electricity generation and what factors influence gross electricity generation from renewable energy. In this study, logarithmic mean Divisia index (LMDI) analysis was used to examine the changes in EU-27 countries’ gross electricity generation from renewable energy sources (RES), wind, and solar PV from 2012 to 2021. The results show that the RES deployment per capita effect and the RES share effect were the main positive factors for the total gross electricity generation from RES in the EU. In contrast, the RES capacity productivity effect and the energy intensity effect had negative contributions. Population growth had a positive influence but was less significant than the other factors. The deployment of RES per capita effect was the main factor in the overall growth of gross electricity generation from RES in Northern Europe, Central Western Europe, and Central Eastern Europe, according to comparisons between the regional groups. RES share effect was the main driver in Southern Europe. The decrease in RES capacity productivity was the second most important factor influencing the variation in the amount of energy generated by RES in Northern Europe and Central Western Europe. The results could be used to develop more effective and tailored renewable energy policies that take into account the existing main drivers of RES, wind, and solar energy in each of the EU-27 member states.
Numerical Investigation on the Yield Pillar Bearing Capacity under the Two-End-Type Cable Reinforcement
Authors: Shan Changhao , Cao Shenggen , Zhang Zeyu , Lin Kewen , Sun Jialong
Published: September 2023

For underground coal mining techniques such as gob-side entry retaining (GER) or gob-side entry driving (GED), the stability of yield pillars is paramount. A well-designed yield pillar aims to withstand mining-induced stresses. This study delves into the impact of bi-terminal cable support on the stability of such pillars. Utilizing 30 distinct numerical models, each with varying pillar width/height (w/h) ratios and diverse cable support methodologies, our findings suggest an upward trend in both peak and residual strength in response to heightened support strength. Notably, pillars with a wider configuration exhibited a more pronounced increase in peak strength compared to their narrower counterparts, while the latter showcased a more pronounced residual strength enhancement. Additionally, the residual/peak strength ratio was smaller in narrower pillars and increased with the increase in the cable support strength. In view of the surrounding rock mass’s support stress distribution, numerical modelling was adopted to analyze the underlying support mechanism. The results showed the support stress zones extended farther on both sides of pillars with the decrease in the row spacing, which made the radial stresses rise effectively and ameliorated the coal pillar’s stress state. Finally, with the 8311 operation advancing towards the station, the deformation amplitude of the coal pillar was only 2.28%, and the stability of the coal pillar was effectively maintained.
Design and Implementation of Digital Twin Diesel Generator Systems
Authors: Dong Xiaotong , Huang Jing , Luo Ningzhao , Hu Wenshan , Lei Zhongcheng
Published: September 2023

In stationary power generation units such as distributed remote site power systems and ship power systems, diesel engine generator systems are essential for supplying electricity. This paper proposes a digital twin diesel generator system for teaching and research purposes. A five-layer resilient architecture, including a web interface layer, server cluster layer, real-time data layer, controller layer, and equipment layer, is proposed in this paper. Based on the resilient architecture, users are able to build, implement and monitor the digital twin through web interfaces. Apart from MATLAB/Simulink, a modeling tool called M2PLink is developed to allow users to create mathematical models using a block diagram editor similar to Simulink. Various basic blocks for control systems are provided for users to form sophisticated models. These models are converted into executable codes which are downloaded to the simulator in the controller layer, where the real-time simulations are implemented. A web-based real-time monitoring interface with many widgets such as charts, oscilloscopes, and three-dimensional (3D) animation is also provided for users to customize their monitoring interface. All the signals can be traced and all the parameters can be tuned in the monitoring interface. The users are able to interact with the digital twin just like they do with the real system. The proposed system can not only be used for research such as digital twin-assisted real-time online monitoring but also for educational purposes, which is not only cost-effective but can also ensure the safety of the user as well as the equipment.
Optimal Configuration of Power/Thermal Energy Storage for a Park-Integrated Energy System Considering Flexible Load
Authors: Zhu Zhi , Wang Miaomiao , Xing Zuoxia , Liu Yang , Chen Shihong
Published: September 2023

The park-integrated energy system can achieve the optimal allocation, dispatch, and management of energy by integrating various energy resources and intelligent control and monitoring. Flexible load participation in scheduling can reduce peak and valley load, optimize load curves, further improve energy utilization efficiency, and reduce system costs. Based on this, firstly, a flexible power-load model is established considering the translatable load, transferable load, and reducible load; and a thermal flexible load model is established based on the fuzziness of user perception of temperature in this study; then, the mixed integer linear programming method is adopted, and the sum of the carbon transaction cost, operation and maintenance cost, compensation cost, power purchase cost, gas purchase cost, wind and light abandonment penalty cost and investment cost of the system is minimized as the objective function, and the configuration of the integrated energy system is optimized, and the optimal capacity of each equipment and the output of each period are obtained. Finally, taking an industrial park in Liaoning Province of China as an example, the analysis is carried out. The example results show that by scheduling the flexible electrical load and flexibly adjusting the indoor temperature, renewable energy consumption can be promoted, and electricity load and heat-load curves can be optimized to increase the installed capacity of wind turbines, reduce the capacity of gas turbines, batteries, and heat-storage tanks, improve system economy, and improve the penetration rate of renewable energy.
Multi-Angle Reliability Evaluation of Grid-Connected Wind Farms with Energy Storage Based on Latin Hypercube Important Sampling
Authors: Yang Weixin , Zhang Yangfan , Wang Yu , Liang Kai , Zhao Hongshan , Yang Ao
Published: September 2023

Aiming to combat the problems of slow speed and poor accuracy of reliability evaluation of the power system in wind farms with energy storage, this paper proposes a method of reliability evaluation based on Latin hypercube important sampling (LHIS). Firstly, we aimed to establish the Latin hypercube important sampling evaluation model by combining the Latin hypercube sampling method with the important sampling method. Secondly, we aimed to optimize the sample probability distribution of the components and conduct hierarchical sampling of the system. Then, the comprehensive risk indicator (CRI) was proposed to evaluate the operational risk and the wind storage generation interrupted energy benefit (WSGIEB) was proposed to evaluate the contribution of the reliability. Finally, simulation experiments were carried out through various power system operation scenarios. The simulation results show that the proposed method is 47% higher than the improving importance sampling method (IM-IS) in evaluation speed and 33% higher than the improving importance sampling method in calculation accuracy.
Structural and Functional Characteristics of Soil Fungal Communities near Decomposing Moso Bamboo Stumps
Authors: Liang Fengna , Yu Le , Jin Cheng , Huang Xiao , Huang Yonglai , Tang Luhong , Tang Longxing , Ma Xiangqing , Cai Liping
Published: September 2023

Background and Objectives: Fungi degrade lignin and other fibers, thus playing an essential role in the decomposition of Phyllostachys edulis (Carrière) J.Houz. (Moso bamboo) stumps. Herein, we characterized key soil fungal communities near different levels of decomposing Moso bamboo stumps (mildly, moderately, and heavily decayed). Materials and Methods: High-throughput sequencing technology was used to analyze the soil fungal communities inside and outside of mild, moderate, and heavy decomposing Moso bamboo stumps. Results: We found nine phyla, 30 classes, 77 orders, 149 families, and 247 genera of soil fungi near the bamboo stumps. Soil fungi OTUs and diversity and richness indices were lower outside than inside the stumps, and decreased with increasing degrees of decay. Inside the bamboo stumps, Soil fungi OTUs and diversity and richness indices were the highest and lowest in moderate and heavy decay bamboo stumps, respectively. Ascomycota dominated inside (from 81% to 46%) and outside (from 69% to 49%) the stumps, and their relative abundance gradually decreased with decomposition, whereas that of Basidiomycota increased outside the stumps (from 17% to 49%). Two-way ANOVA showed that the interaction between the two factors of occurring inside and outside the bamboo stumps and the degree of decay, significantly affected Chytridiomycota and Penicillium (p < 0.001) and significantly affected Mucoromycota (p < 0.05). The abundance of different genera was significantly correlated with saprotrophic functional groups. Conclusion: Changes in the structure and functional groups of soil fungal communities may play an important role during different levels of decomposition of Moso bamboo stumps. This study provides a scientific basis for screening functional fungal strains that promote the decomposition of Moso bamboo stumps.
Structural Equation Modeling of Phosphorus Transformations in Soils of Larix principis-rupprechtii Mayr. Plantations
Authors: Tian Huixia , Li Zuzheng , Song Zhaopeng , Han Hairong , Cheng Xiaoqin
Published: September 2023

Understanding the soil phosphorus (P) cycle is a prerequisite for the sustainable management of land resources. The sequential-extraction method was used to determine P fractions in 513 soils of Larix principis-rupprechtii Mayr. plantations. With these data, this study applied structural equation modeling to evaluate the interaction between various soil P fractions. Quantitative analysis was conducted on the importance of different soil P pools and P transformation pathways on soil P availability in a larch plantation. Our study showed that soluble inorganic P (Pi) was directly positively affected by labile Pi, labile organic P (Po), secondary mineral P, and primary mineral P, and was directly negatively affected by moderately labile Po. Soluble Pi was not directly affected by occluded P. The primary mineral P (β = 0.40) had the greatest total impact on soluble Pi, followed by secondary mineral P (β = 0.32) and labile P (labile Pi and Po, β = 0.31), and then occluded P (β = 0.11), with the total impact of moderately labile Po being relatively small (β = −0.06). In summary, this study reveals the important roles of soluble Pi in P transformations and in determining overall P availability in soils, as well as the extensive effects of weathering on soil P dynamics in L. principis-rupprechtii plantations.
FL-YOLOv7: A Lightweight Small Object Detection Algorithm in Forest Fire Detection
Authors: Xiao Zhuo , Wan Fang , Lei Guangbo , Xiong Ying , Xu Li , Ye Zhiwei , Liu Wei , Zhou Wen , Xu Chengzhi
Published: September 2023

Given the limited computing capabilities of UAV terminal equipment, there is a challenge in balancing the accuracy and computational cost when deploying the target detection model for forest fire detection on the UAV. Additionally, the fire targets photographed by the UAV are small and prone to misdetection and omission during detection. This paper proposes a lightweight, small target detection model, FL-YOLOv7, based on YOLOv7. First, we designed a light module, C3GhostV2, to replace the feature extraction module in YOLOv7. Simultaneously, we used the Ghost module to replace some of the standard convolution layers in the backbone network, accelerating inference speed and reducing model parameters. Secondly, we introduced the Parameter-Free Attention (SimAm) attention mechanism to highlight the features of smoke and fire targets and suppress background interference, improving the model’s representation and generalization performance without increasing network parameters. Finally, we incorporated the Adaptive Spatial Feature Fusion (ASFF) module to address the model’s weak small target detection capability and use the loss function with dynamically adjustable sample weights (WIoU) to weaken the impact of low-quality or complex samples and improve the model’s overall performance. Experimental results show that FL-YOLOv7 reduces the parameter count by 27% compared to the YOLOv7 model while improving 2.9% mAP50small and 24.4 frames per second in FPS, demonstrating the effectiveness and superiority of our model in small target detection, as well as its real-time and reliability in forest fire scenarios.
Drought and Vulnerability in Mexico’s Forest Ecosystems
Authors: Agustín-Canales Noé San , Cruz-Sánchez Yadihra , Borja-de la Rosa Ma. Amparo , González-Tepale Ma. Rosa , Monterroso-Rivas Alejandro Ismael
Published: September 2023

In Mexico, some regions have frequent droughts, while others are beginning to experience their presence and impacts. Therefore, this work aimed to characterize drought in the last twenty-one years and evaluate the vulnerability of forests to this phenomenon. The method consisted of applying the standard precipitation index (SPI-12), calculating the drought vulnerability index (DVI), and applying it to the country’s forest areas. The results confirm that forests are vulnerable to drought for five main reasons. First, geographically, the country has large arid and semiarid areas with little natural precipitation. Second, droughts frequently occur and are present in the national territory, covering from 25% to 75% of the surface in recent years. Third, the socioeconomic characteristics of the population living in municipalities and forest territories increase the vulnerability of these areas to drought. Fourth, drought can trigger other catastrophes, such as fires or forest pests. Fifth, the combination of two or more of the above in the same territory magnifies exposure to drought for both forests and people. Temperate forest ecosystems, in particular, have been subject to the prevalence of drought in recent years and, thus, should receive more attention. Finally, technical and cartographic elements, such as those presented herein, are essential for supporting the formulation of proactive forest response plans to address drought events.
Flavonoid Metabolome-Based Active Ingredient Mining and Callus Induction in Catalpa bungei C. A. Mey
Authors: Zeng Xiaofeng , Wang Xiao , Zeng Yanling , Hou Jinbo , Liu Zhiming
Published: September 2023

Catalpa bungei C. A. Mey is a unique and precious multi-purpose tree species that possesses great timber-related, ornamental and medicinal values. In this study, MS, N6 and DKW were used as basic media, and different concentrations of 6-BA and NAA were added for callus induction. The induction rate and total flavonoid content of callus tissue showed that the best callus induction medium was DKW + 2.0 mg·L−1 6-BA + 0.5–1.0 mg·L−1 NAA. The leaves of different bark phenotypes of C. bungei C. A. Mey and the callus tissue extracted from young leaves of C. bungei C. A. Mey were used as experimental materials to construct metabolomic profiles of widely targeted flavonoids. Based on the metabolomic databases, the predominant flavonoids were screened from the callus tissues. Eight flavonoid metabolites increased in callus, and diosmetin-7-O-rutinoside (diosmin) was the flavonoid constituent with the shortest retention time, most efficient detection and best medicinal functions among these 8. The optimal medium for callus induction was supplemented with different concentrations of elicitors (salicylic acid SA and yeast extract YE). The optimal elicitor and the amount to be added were determined by analyzing the induction rate of callus, as well as the total contents of flavonoids and diosmin. The addition of SA and YE in appropriate amounts increased the total flavonoid content in the callus, but only the addition of YE promoted the formation of diosmin in the callus. The optimal medium formulation to promote the formation of callus was DKW + 2.0 mg·L−1 6-BA + 1.0 mg·L−1 NAA + 30 g·L−1 sucrose + 6.8 g·L−1 agar + 10 μmol·L−1 SA. The medium formulation to optimally increase the content of geraniol glucoside was DKW + 2.0 mg·L−1 6-BA + 1.0 mg·L−1 NAA + 30 g·L−1 sucrose + 6.8 g·L−1 agar + 200 mg·L−1 YE. The results of the present study will provide a scientific basis for the subsequent increase in the content of the active components of the suspension cells via the addition of elicitors, and for the production of diosmin in factory settings.
Trade-Off between Hydraulic Safety and Efficiency in Plant Xylem and Its Influencing Factors
Authors: Li Shan , Wang Jing , Lu Sen , Salmon Yann , Liu Peng , Guo Junkang
Published: September 2023

Forests are vital ecosystems that are increasingly threatened by environmental stress; exploring the possible trade-off between hydraulic safety and efficiency in plant xylem is crucial to understanding their environmental adaptation strategies. However, to date, there is no consensus whether such trade-offs exist among and within species. To better comprehend the mechanism of xylem water transport, in this review, we summarized previously published work on xylem hydraulic safety and efficiency trade-off from the inter-species, intra-species, and intra-tree perspectives and its influencing factors. We gathered data on xylem hydraulic safety and efficiency and their related anatomical traits, i.e., conduit diameter and inter-conduit pit membrane thickness, from a total of 653 plant species analyzed in 80 published papers. At the inter-species level, we confirmed that there is a weak hydraulic safety and efficiency trade-off. For gymnosperms and herbaceous species, the observed trade-off is stronger. At the intra-species level, the hydraulic safety and efficiency trade-off was found in individuals of the same species investigated in the literature. At the intra-tree level, there is a trade-off between hydraulic safety and efficiency for leaves, stems, and roots, and we confirmed the vessel widening hypothesis, i.e., vessel diameter in the outer wood increases from the top to the bottom of the tree. Additionally, pit membrane thickness increases as the tree height decreases, thus increasing the xylem hydraulic efficiency and affecting the trade-off. Finally, we discussed the environmental factors affecting the trade-off between hydraulic safety and efficiency in the xylem, such as plant habitats, temperature, rainfall, altitude, and soil. Further investigations of the bordered pit membrane from the three-dimensional perspective would be useful to understand the hydraulic safety and efficiency trade-off at the nanoscale.
Summer Compound Drought-Heat Extremes Amplify Fire-Weather Risk and Burned Area beyond Historical Thresholds in Chongqing Region, Subtropical China
Authors: Gutiérrez Rodríguez Lucas , He Yingpeng , Sun Mengqi , Yao Yinan , de Dios Víctor Resco
Published: September 2023

Global warming is associated with an increase in compound drought-heat events (CDHEs), leading to larger and more extreme fire-weather risk in mesic forests. Wildfire activity in subtropical China, under the influence of monsoonal rainfall, was historically limited to dry winters and rare in rainy summers. Here, we seek to test whether this area is on the brink of a major change in its fire regime characterized by larger fire seasons, extending into the summer, leading to increases in fire activity (burned area). We analyze fire activity in Chongqing Municipality (46,890 km2), an important area of subtropical China hosting the Three Gorges Reservoir Area. We observed significant increases in summer forest fires under anomalous dry-hot summer conditions, where the total burned area was 3–6 times the historical annual mean (previously confined to the winter season). Vapor pressure deficit (VPD), an indicator of hot and dry weather conditions (i.e., fire-weather risk), was a strong predictor of fire activity, with larger wildfires occurring on days where VPD was higher than 3.5 kPa. Results indicate that a major wildfire activity expansion may occur in the area due to climate change and the widening time window of fire-weather risk, unless strong fire prevention and local adaptation policies are implemented.
Targeted Removal of Galloylated Flavanols to Adjust Wine Astringency by Using Molecular Imprinting Technology
Authors: Du Guorong , Wang Xiaoyu , Zhao Qinghao
Published: September 2023

Excessive galloylated flavanols not only cause instability in the wine but also lead to unbalanced astringency. Although clarification agents are always used to precipitate unstable tannins in wine, the non-specific adsorption of tannins results in the failure to precisely regulate the tannin composition of the wine. In this work, molecularly imprinted polymers (MIPs) with template molecules of galloylated flavanols were designed to specifically adsorb gallotannins to reduce wine astringency. The results showed that the “pores” on the surface of the MIPs are the structural basis for the specific adsorption of the target substances, and the adsorption process is a chemically driven single-molecule layer adsorption. Moreover, in the mono/oligomeric gallotannin-rich model solution, the adsorption of gallotannins by I-MIPs prepared as single template molecules reached 71.0%, and the adsorption capacity of MIPs for monomeric gallotannins was about 6.0 times higher than polymeric gallotannins. Given the lack of technology for the targeted adsorption of tannins from wine, this work explored the targeted modulation of wine astringency by using molecular imprinting techniques.
Special Issue “Genetics and Epigenetics in Endocrine Disorders”
Authors: Trebušak Podkrajšek Katarina , Kotnik Primož
Published: September 2023

In the last decade, the development of high-throughput sequencing methodologies has significantly improved the gathering of genomic information and consequent under-standing of the genetic and epigenetic background of complex and monogenetic endocrine disorders [...]