bluuebunny/crossref_metadata_2025 huggingface dataset:
Time-Series Deep Learning Models for Reservoir Scheduling Problems Based on LSTM and Wavelet Transformation
Authors: Tang Jiansong , Yang Ruijia , Yuan Gaoteng , Mao Yingchi
Published: October 2022

In 2022, as a result of the historically exceptional high temperatures that have been observed this summer in several parts of China, particularly in the province of Sichuan, residential demand for energy has increased. Up to 70% of Sichuan’s electricity comes from hydropower, thus creating a sensible and practical reservoir scheduling plan is essential to maximizing reservoir power generating efficiency. However, classical optimization, such as back propagation (BP) neural network, does not take into account the correlation of samples in time while generating reservoir scheduling rules. We proposed a prediction model based on LSTM neural network coupled with wavelet transformation (WT-LSTM) to address the problem. In order to extract the reservoir scheduling rules, this paper first gathers the scheduling operation data from the Xiluodu hydropower station and creates a dataset. Next, it uses the feature of the time-series prediction model with the realization of a complex nonlinear mapping function, time-series learning capability, and high prediction accuracy. The results demonstrate that the time-series deep learning network has high learning capability for reservoir scheduling by comparing evaluation indexes such as root mean square error (RMSE), rank-sum ratio (RSR), and Nash–Sutcliffe efficiency (NSE). The WT-LSTM network model put forward in this research offers better prediction accuracy than conventional recurrent neural networks and serves as a reference base for scheduling decisions by learning previous scheduling data to produce outflow solutions, which has some theoretical and practical benefits.
Comparison of Phase-Locked Loops Used for Frequency Measurements in a Low-Inertia Power Grid with Wind Generation
Authors: Guerrero-Bermúdez Orlando David , Martinez Sergio , Molina Eder , Candelo-Becerra John E.
Published: October 2022

The need for more precise frequency measurements in electric power systems is increasing because of the growing penetration of renewable energy and the subsequent reduction in inertia, which gives rise to more intense frequency fluctuations. Phase-locked loops (PLLs) are now more accurate and present faster dynamic responses, helping to implement primary frequency controllers for renewable generators connected to the grid through power electronics. However, there are differences among PLL implementations that affect their behavior when estimating frequency, depending on factors as location, voltage level, or penetration of renewable energy, among other things. How this affects the ability of PLL-based frequency controllers to adequately estimate the instantaneous mismatch between generation and demand, especially in low-inertia power systems, is still unclear, and constitutes an open research topic. This paper contributes to this research effort by presenting a comparative study of different PLL configurations in order to gain insight into their performance in different scenarios in a low-inertia power system with a high share of wind energy. Constant and variable wind speed scenarios are considered, and PLL behavior is assessed in terms of the absolute mean value and the root-mean-square value of the frequency error, and the absolute value of the frequency derivative error. The results show that the PLL behavior depends on the voltage level and the location, and it was found that the further away the PLL is from the source that controls the frequency, the more noise is produced, which impacts the quality of the frequency measurement.
Evaluating the Efficiency of Connected and Automated Buses Platooning in Mixed Traffic Environment
Authors: Park Suyong , Nam Sanghyeon , Sankar Gokul S. , Han Kyoungseok
Published: October 2022

Due to the battery capacity limitation of battery electric vehicles (BEVs), the importance of minimizing energy consumption has been increasing in recent years. In the mean time, for improving vehicle energy efficiency, platooning has attracted attention of several automakers. Using the connected and automated vehicles (CAVs) technology, platooning can achieve a longer driving range while preserving a closer distance from the preceding vehicle, resulting in the minimization of the aerodynamic force. However, undesired behaviors of human-driven vehicles (HVs) in the platooning group can prohibit the maximization of the energy efficiency. In this paper, we developed a speed planner based on the model predictive control (MPC) to minimize the total platooning energy consumption, and HVs were programmed to maintain a long enough distance from the preceding vehicle to avoid collision. The simulations were performed to determine how HV influences the efficiencies of the platooning group, which is composed of CAVs and HVs together, in several scenarios including the different positions and numbers of the HVs. Test results show that the CAVs planned by our approach reduces energy consumption by about 4% or more than 4% compared to that of the HVs.
Downlink MIMO-NOMA System for 6G Internet of Things
Authors: Xie Weiliang , Ding Xue , Cai Bowen , Li Xiao , Wei Mingshuo
Published: October 2022

This paper proposes a system of 6G Internet of Things (IoT) based on downlink non-orthogonal multiple access (NOMA) technology, where the base station (BS) allows signals of the same frequency to serve users at different distances. In particular, we study a cooperative MIMO-NOMA system based on downlink simultaneous wireless information and power transfer (SWIPT) assistance. To improve the overall performance, we employ machine learning to optimize user-pairing and radio resource allocation. At the end of the paper, the simulation results are obtained, which fully prove that the MIMO-NOMA system constructed in this paper is correct in theory and can be realized in practice.
Design and Implementation of Low Noise Amplifier Operating at 868 MHz for Duty Cycled Wake-Up Receiver Front-End
Authors: Ketata Ilef , Ouerghemmi Sarah , Fakhfakh Ahmed , Derbel Faouzi
Published: October 2022

The integration of wireless communication, e.g., in real- or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, quality of service, and reliability. The improvement of wireless sensor networks (WSN) performance starts by enhancing the capabilities of each sensor node. To minimize latencies without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works since they can be always-on or power-gated with short latencies by a power consumption in the range of some microwatts. Compared to standard receiver technologies, they are usually characterized by drawbacks in terms of sensitivity. To overcome the limitation of the sensitivity of WuRxs, a design of a low noise amplifier (LNA) with several design specifications is required. The challenging task of the LNA design is to provide equitable trade-off performances such as gain, power consumption, the noise figure, stability, linearity, and impedance matching. The design of fast settling LNA for a duty-cycled WuRx front-end operating at a 868 MHz frequency band is investigated in this work. The paper details the trade-offs between design challenges and illustrates practical considerations for the simulation and implementation of a radio frequency (RF) circuit. The implemented LNA competes with many commercialized designs where it reaches single-stage 12 dB gain at a 1.8 V voltage supply and consumes only a 1.6 mA current. The obtained results could be made tunable by working with off-the-shelf components for different wake-up based application exigencies.
An Optimal Control Approach for Enhancing Transients Stability and Resilience in Super Smart Grids
Authors: Alsuwian Turki , Basit Abdul , Amin Arslan Ahmed , Adnan Muhammad , Ali Mansoor
Published: October 2022

Super smart grids (SSGs) are a wide area transmission network that mainly uses renewable energy resources (RERs), contributing to the reduction of greenhouse gas (GHGs) emissions and supporting the power infrastructure of multiple countries. The SSGs comprise two-way communication between the loads and sources of different countries, and these loads can be mostly served with numerous types of RERs tied with the grids. The RERs will play a pivotal role in the development of future grids and the generation of electricity. However, the main challenge to tackle in these RERs is that they are intermittent in nature. Due to intermittency in these RERs, transient stability issues have become one of the critical research challenges in SSGs. These stability issues are escalated and become more difficult to handle if a network is vulnerable to an arising of different kinds of faults. To address these problems, multiple approaches to enhance transient stability already exist in the current literature. After reviewing the literature, flexible alternating current transmission systems (FACTS) devices proved more promising in improving transient stability. Among FACTSdevices, UPFC is a versatile FACTS device, which provides complete stability to power system networks in the form of series and shunt compensations. Considering this scenario, a hypothetical network for SSGs is designed in this research work based on the interconnection between two countries, i.e., Denmark and Norway, to address the transient stability issues in SSGs. The complete probabilistic model of the system is also designed to enhance the stability of the system. The results clearly showed that the insertion of UPFC is an effective technique to enhance the transient stability and resilience of the power system networks as compared to other purposed techniques in the literature. The main contribution of this paper is that extensive simulation studies employing accurate RERs models are used to analyze and investigate various problems arising due to the integration of many clusters of RERs in SSGs.
QCA-Based PIPO and SIPO Shift Registers Using Cost-Optimized and Energy-Efficient D Flip Flop
Authors: Nafees Naira , Ahmed Suhaib , Kakkar Vipan , Bahar Ali Newaz , Wahid Khan A. , Otsuki Akira
Published: October 2022

With the growing use of quantum-dot cellular automata (QCA) nanotechnology, digital circuits designed at the Nanoscale have a number of advantages over CMOS devices, including the lower utilization of power, increased processing speed of the circuit, and higher density. There are several flip flop designs proposed in the literature with their realization in the QCA technology. However, the majority of these designs suffer from large cell counts, large area utilization, and latency, which leads to the high cost of the circuits. To address this, this work performed a literature survey of the D flip flop (DFF) designs and complex sequential circuits that can be designed from it. A new design of D flip flop was proposed in this work and to assess the performance of the proposed QCA design, an in-depth comparison with existing designs was performed. Further, sequential circuits such as parallel-in-parallel-out (PIPO) and serial-in-parallel-out (SIPO) shift registers were designed using the flip flop design that was put forward. A comprehensive evaluation of the energy dissipation of all presented fundamental flip-flop circuits and other sequential circuits was also performed using the QCAPro tool, and their energy dissipation maps were also obtained. The suggested designs showed lower power dissipation and were cost-efficient, making them suitable for designing higher-power circuits.
The Review and Development of Devices with an Increasing Rate of Penetration (ROP) in Deep Formation Drilling Based on Drill String Vibration
Authors: Liu Yongwang , Niu Yixiang , Guan Zhichuan , Lyu Shuquan
Published: October 2022

The oil and gas resources stored in deep strata are an important replacement field of the petroleum industry. Accelerating the exploration and development of deep oil and gas is of great significance to the security of energy strategy. Drilling is the primary link and necessary means of deep oil and gas exploration and development. Slow drilling speed is one of the key problems restricting the exploration and development of deep oil and gas. The research and development of down-hole equipment with an increasing ROP provides a technical means for increasing the ROP. However, the energy of existing down-hole equipment with an increasing ROP comes from the drilling circulation medium, and the ROP increase effect of such equipment is relatively obvious in shallow and middle formations. However, with the increase in well depth, energy in the circulation medium increasingly struggles to reach deeper formations, and the ROP increase effect is not good at the later stage of drilling. In the drilling process, drill string vibration is a frequently encountered complex situation, but it also contains sufficient energy, and the energy of drill string vibration will increase with an increase in the well depth, which can meet the energy demand of increasing the ROP in deep oil and gas exploration. This paper analyzes the characteristics of drill string vibration, and introduces six kinds of devices that take drill string vibration as energy and realize drill string vibration reduction, bottom-hole pressurization, and high-pressure pulse jet, providing a new idea for the development of deep down-hole speed-increasing devices.
Synthesis of Superparamagnetic Fe3O4 Nano-Adsorbent Using an Energy-Saving and Pollution-Reducing Strategy for the Removal of Xylenol Orange Dye in Water
Authors: Xu Yaohui , Wang Qin , Ding Zhao
Published: October 2022

The superparamagnetic Fe3O4 nanoparticles as an absorbent with a size distribution of 4.8–6.4 nm were synthesized using a simple one-pot hydrothermal strategy at 200 °C for 24 h, where iron citrate and distilled were the sum total of raw materials. The as-synthesized Fe3O4 powders showed rapid and efficient adsorption for xylenol orange with a saturated adsorption amount of 42.5 mg/g according to Langmuir linear fitting, and the adsorption reaction between xylenol orange adsorbate and Fe3O4 adsorbent was mostly completed within 10 min. The Fe3O4 nanoparticles not only had superparamagnetism with a saturation magnetization value of 54.9 emu/g at 15 kOe but also possessed strong magnetic response, making them easy to separate easily from aqoeous solution under the attraction of magnet. In this work, the Fe3O4 particles can be totally attracted toward the magnet within 15 s, leaving the suspension a clear solution.
Energy Management Simulation with Multi-Agent Reinforcement Learning: An Approach to Achieve Reliability and Resilience
Authors: Deshpande Kapil , Möhl Philipp , Hämmerle Alexander , Weichhart Georg , Zörrer Helmut , Pichler Andreas
Published: October 2022

The share of energy produced by small-scale renewable energy sources, including photovoltaic panels and wind turbines, will significantly increase in the near future. These systems will be integrated in microgrids to strengthen the independence of energy consumers. This work deals with energy management in microgrids, taking into account the volatile nature of renewable energy sources. In the developed approach, Multi-Agent Reinforcement Learning is applied, where agents represent microgrid components. The individual agents are trained to make good decisions with respect to adapting to the energy load in the grid. Training of agents leverages the historic energy profile data for energy consumption and renewable energy production. The implemented energy management simulation shows good performance and balances the energy flows. The quantitative performance evaluation includes comparisons with the exact solutions from a linear program. The computational results demonstrate good generalisation capabilities of the trained agents and the impact of these capabilities on the reliability and resilience of energy management in microgrids.
Energy-Saving Routing Protocols for Smart Cities
Authors: Medeiros Douglas de Farias , Souza Cleonilson Protasio de , Carvalho Fabricio Braga Soares de , Lopes Waslon Terllizzie Araújo
Published: October 2022

In recent decades, expansion in urban areas has faced issues such as management of public waste, noise, mobility, and air quality, among others. In this scenario, Internet of Things (IoT) and Wireless Sensor Network (WSN) scenarios are being considered for Smart Cities solutions based on the deployment of wireless remote sensor nodes to monitor large urban areas. However, as the number of nodes increases, the amount of data to be routed increases significantly as well, meaning that the choice of the data routing process has great importance in terms of the energy consumption and lifetime of the network. In this work, we describe and evaluate the energy consumption of routing protocols for WSN-based Smart Cities applications in LoRa-based mesh networks, then propose a novel energy-saving radio power adjustment (RPA) routing protocol. The Cupcarbon network simulator was used to evaluate the performance of different routing protocols in terms of their data package delivery rate, average end-to-end delay, average jitter, throughput, and load consumption of battery charge. Additionally, a novel tool for determining the range of nodes based on the Egli propagation model was designed and integrated into Cupcarbon. The routing protocols used in this work are Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Distance Vector Routing (DVR). Our simulation results show that AODV presents the best overall performance, DSR achieves the best results for power consumption, and DVR is the best protocol in terms of latency. Finally, the proposed RPA routing protocol presents power savings of 11.32% compared to the original DSR protocol.
Reframing the Selection of Hydraulic Turbines Integrating Analytical Hierarchy Process (AHP) and Fuzzy VIKOR Multi-Criteria Methods
Authors: Caricimi Rudimar , Dranka Géremi Gilson , Setti Dalmarino , Ferreira Paula
Published: October 2022

Before selecting a proper hydraulic turbine for power generation, conflicting factors frequently emerge from the wide range of available technology alternatives. The preliminary selection of hydraulic turbines (PSHT) has been usually carried out by overlooking and/or overshadowing downstream and upstream processes. The development of a new conceptual framework that allows for including more parameters into the decision-making process at company levels is still required to avoid the danger of engaging in a one-dimensional approach, which would not only result in a reduced and simplistic vision of the choice but would also overlook the trade-offs between individual aspects and the possible unintended side-effects. This paper aims to provide empirical evidence for the PSHT by proposing a well-thought-out framework based on a mixed methodology approach (analytical hierarchy process (AHP) and fuzzy-VIKOR multi-criteria methods) and focused on small hydropower projects. A total of 16 criteria are proposed and divided into 4 main categories—(i) turbine performance, (ii) turbine and generator costs, (iii) other equipment costs, and (iv) civil costs. Findings reported here reveal a specific alignment between investors’ preferences and experts’ judgments with real market practices. The 16 proposed criteria can be further considered to support the decision-making process for PSHT in different head and flow conditions.
Challenges in Energy Communities: State of the Art and Future Perspectives
Authors: Di Lorenzo Gianfranco , Stracqualursi Erika , Micheli Leonardo , Martirano Luigi , Araneo Rodolfo
Published: October 2022

Within the policy framework of the energy union strategy started in 2015, the European Union (EU) finalized the “Clean Energy for all Europeans Package” (CEP) in 2019 [...]
Unified Power Control of Permanent Magnet Synchronous Generator Based Wind Power System with Ancillary Support during Grid Faults
Authors: Ramachandran Vijayapriya , Perumal Angalaeswari Sendraya , Lakshmaiya Natrayan , Paramasivam Prabhu , Dhanasekaran Seshathiri
Published: October 2022

A unified active power control scheme is devised for the grid-integrated permanent magnet synchronous generator-based wind power system (WPS) to follow the Indian electricity grid code requirements. The objective of this paper is to propose control schemes to ensure the continuous integration of WPS into the grid even during a higher percentage of voltage dip. In this context, primarily a constructive reactive power reference is formulated to raise and equalize the point of common coupling (PCC) potential during symmetrical and asymmetrical faults, respectively. A simple active power reference is also proposed to inject a consistent percentage of generated power even during faults without violating system ratings. Eventually, the efficacy of the proposed scheme is demonstrated in terms of PCC voltage enhancement, DC-link potential, grid real, and reactive power oscillation minimization using the PSCAD/ EMTDC software.
How Can Sustainable Public Transport Be Improved? A Traffic Sign Recognition Approach Using Convolutional Neural Network
Authors: Liu Jingjing , Ge Hongwei , Li Jiajie , He Pengcheng , Hao Zhangang , Hitch Michael
Published: October 2022

Sustainable public transport is an important factor to boost urban economic development, and it is also an important part of building a low-carbon environmental society. The application of driverless technology in public transport injects new impetus into its sustainable development. Road traffic sign recognition is the key technology of driverless public transport. It is particularly important to adopt innovative algorithms to optimize the accuracy of traffic sign recognition and build sustainable public transport. Therefore, this paper proposes a convolutional neural network (CNN) based on k-means to optimize the accuracy of traffic sign recognition, and it proposes a sparse maximum CNN to identify difficult traffic signs through hierarchical classification. In the rough classification stage, k-means CNN is used to extract features, and improved support vector machine (SVM) is used for classification. Then, in the fine classification stage, sparse maximum CNN is used for classification. The research results show that the algorithm improves the accuracy of traffic sign recognition more comprehensively and effectively, and it can be effectively applied in unmanned driving technology, which will also bring new breakthroughs for the sustainable development of public transport.
Experimental Characterization of High Tolerance to Beam Irradiation Conditions of Light Beam Power Receiving Module for Optical Wireless Power Transmission Equipped with a Fly-Eye Lens System
Authors: Tai Yuha , Miyamoto Tomoyuki
Published: October 2022

This paper is an experimental characterization of a light-receiving module containing a fly-eye lens system with high tolerance to beam irradiation conditions. The fly-eye lens system, which is tolerant to fluctuations in beam shape, beam size, number of beams, beam incident position, and beam incident direction, was proposed, a light receiver module with a fly-eye lens system was constructed, and its characteristics were evaluated. The effect of the beam size on the fly-eye lens system was evaluated and the tolerance to misalignment of beam incident position was measured. When a GaAs solar cell was irradiated with a laser beam of 450 nm wavelength and 6 W light output through a 90 cm long water tank with tap water, a maximum output of 0.755 W was obtained as underwater OWPT. In addition, a fly-eye lens system with mirrors applied to four surfaces was proposed and fabricated as a light-receiving side module that can receive high incident angles from any direction of up, down, left, and right and its effectiveness was clarified through experiments.
Business Models for Active Buildings
Authors: Elliott Tom , Geske Joachim , Green Richard
Published: October 2022

Active Buildings that allow users to adjust their demands on the grid to the needs of the energy system could greatly assist the transition to net zero, but will not be widely adopted unless the businesses involved can make money from doing so. We describe the construction, flexibility and information supply chains of activities needed to make these buildings work. Drawing on the results of an expert workshop, we set out four possible business models deserving further investigation. Developers may find it profitable to build or upgrade energy-efficient buildings with the monitoring and control equipment needed to adjust demand and energy storage as required, selling them soon after completion. Aggregators monitor the state of the building and communicate with the energy system to adjust the building’s demand while maintaining comfort levels, in return for suitable payments. Energy service companies may sell energy-as-a-service and own the equipment instead of a consumer who wishes to minimize their upfront costs, and the idea of an active, energy-efficient, building may be attractive to the tenants of the new group of all-inclusive rental companies, and hence to those companies. Our discussion shows that each is an evolution of an existing (successful) business model, but that further work will be needed to evaluate their profitability when applied to Active Buildings.
Stakeholder Perspectives on Community Energy Contributing to the Use of Renewable Energy Sources and Improving Energy Security in Nigeria
Authors: Ogunleye Olaoluwa Sunday , Coenen Frans , Hoppe Thomas
Published: October 2022

The need for improved energy security in Nigeria cannot be over-emphasized. Currently, energy security is rather poor, while access to energy is fundamental to socio-economic development and poverty alleviation. Renewable energy could potentially contribute to resolving this because renewable sources such as solar radiation are more available and sustainable, and can be set up in small generation units, meaning that it is suitable for community management and ownership. In theory, a community energy approach could well apply. In this paper, the main research question is: In what ways can community energy initiatives contribute to increasing the use of renewable energy sources and improving energy security in Nigeria according to selected stakeholders and households? A mixed methods research approach was used to answer this question, with stakeholder interviews and survey data from 124 residents in two case studies of selected housing estates in Lagos. The results show that 58% of the households and most of the stakeholders express support for community renewable energy as a viable approach for increasing energy access and greening energy supply. The present study shows that there is a need to raise awareness and support projects for effective and supportive renewable energy policy to encourage local renewable energy community formation.
Special Issue “Genetics in Pediatric Endocrinology”
Authors: Draznin Martin B. , Kanungo Shibani
Published: October 2022

The inception of pediatric endocrinology in the United States began little less than a century ago, but it has grown as a subspecialty field since the 1950s [...]
Historic and Prehistoric Epidemics: An Overview of Sources Available for the Study of Ancient Pathogens
Authors: van der Kuyl Antoinette C.
Published: October 2022

Since life on earth developed, parasitic microbes have thrived. Increases in host numbers, or the conquest of a new species, provide an opportunity for such a pathogen to enjoy, before host defense systems kick in, a similar upsurge in reproduction. Outbreaks, caused by “endemic” pathogens, and epidemics, caused by “novel” pathogens, have thus been creating chaos and destruction since prehistorical times. To study such (pre)historic epidemics, recent advances in the ancient DNA field, applied to both archeological and historical remains, have helped tremendously to elucidate the evolutionary trajectory of pathogens. These studies have offered new and unexpected insights into the evolution of, for instance, smallpox virus, hepatitis B virus, and the plague-causing bacterium Yersinia pestis. Furthermore, burial patterns and historical publications can help in tracking down ancient pathogens. Another source of information is our genome, where selective sweeps in immune-related genes relate to past pathogen attacks, while multiple viruses have left their genomes behind for us to study. This review will discuss the sources available to investigate (pre)historic diseases, as molecular knowledge of historic and prehistoric pathogens may help us understand the past and the present, and prepare us for future epidemics.
Clonal Fidelity and Genetic Diversity of Micropropagated Hancornia speciosa Gomes (Apocynaceae) as Evaluated by Molecular Markers
Authors: Costa Géssica Ferreira da , Cabral Pablo Diego Silva , Silva Fabiano Guimarães , Rubio Neto Aurélio , Mendonça Maria Andréia Corrêa
Published: October 2022

The plant tissue culture procedures for asexual multiplication of Hancornia speciosa represent an important process facilitating the preservation of selected genotypes of this threatened species and large-scale production of plantlets for population reinforcement or other utilization. However, there is no research regarding the somaclonal variation of this threatened species at molecular level. This study aimed to evaluate the role of the multiplication process in the genetic stability of H. speciosa plantlets and calluses using molecular markers. The tissue culture techniques for H. speciosa micropropagation used in this study did not influence the occurrence of somaclonal variation, which can be related to the genotypes of the donor plants and to the low concentrations of growth regulators used in tissue culture procedures adopted. The results observed here provide a reliable methodology for further studies involving micropropagation techniques with the goal of preserving selected or endangered genotypes of H. speciosa without genetic losses and producing seedlings of this species on a large scale. In addition, it was possible to verify that the donor plants used in this study showed a relatively low genetic variability.
Variations in Sap Flux Density of Three Urban Tree Species and Their Main Environmental Influencing Factors in Different Timescales in the Beijing Metropolitan Area
Authors: Chen Yuanyuan , Wang Xiaoke , Zhang Hongxing , Sun Xu
Published: October 2022

Despite the importance of landscape design and water-resources management for urban planning, urban-forest transpiration was seldom estimated in situ. Detailed data on different urban trees’ water resource use and the effect of climatic fluctuations on their transpiration behaviour in different timescales are limited. In this study, we used a thermal dissipation method to measure the sap flux density (Js) of three urban tree species (Pinus tabulaeformis Carrière, Cedrus deodara (Roxb.) G. Don, and Robinia pseudoacacia Linn.) from 1 May 2008 to 30 April 2016 in Beijing Teaching Botanical Garden. The effects of environmental factors on sap flux density (Js) in different timescales were also analyzed. The results showed that there were significant differences in the sap flux density of three trees species in daily, seasonal, and interannual timescales. The hourly, seasonal, and interannual mean sap flux density of Pinus tabulaeformis were higher than that of Cedrus deodara and Robinia pseudoacacia. The seasonal mean Js of Pinus tabulaeformis, Cedrus deodara, and Robinia pseudoacacia in summer were 18.67, 16.19, and 41.62 times that in winter over 2008–2015. The annual mean sap flux density of Pinus tabulaeformis was 1.25–1.72 and 1.26–1.82 times that Cedrus deodara and Robinia pseudoacacia over 2008–2015. The Js responses in three tree species to environmental factors varied differently from daily to interannual timescales. The pattern of day-to-day variation in Js of three urban tree species corresponded closely to air temperature (Ta), soil temperature (Ts), solar radiation (Rs), and vapor pressure deficit (VPD). The Jarvis–Stewart model based on Ta, Rs, and VPD was more suitable for the sap flux density simulation of Pinus tabulaeformis than Cedrus deodara and Robinia pseudoacacia. The main factor affecting the sap flux density of Pinus tabulaeformis and Cedrus deodara was Ta in seasonal timescales. However, the main factor affecting the sap flux density of Robinia pseudoacacia was Ts. The interannual variations in the Js of Pinus tabulaeformis and Robinia pseudoacacia were mainly influenced by wind speed (w) and soil water content (SWC), respectively. The selected environmental factors could not explain the variation in the sap flux density of Cedrus deodara in an interannual timescale. The findings of the present study could provide theoretical support for predicting the water consumption of plant transpiration under the background of climate change in the future.
Population Study Reveals Genetic Variation and Introgression of Four Deciduous Oaks at the Junction between Taihang Mountain and Yanshan Mountain
Authors: Pei Ziqi , Yang Qinsong , Chen Xining , Zong Yu , Li Jinjin , Yang Xiong , Huo Chenrui , Chen Yixin , Luo Na , Kang Jialu , Meng Xiaoqian , Li Yining , Zhou Huirong , Wang Jiaxi , Liu Yong , Li Guolei
Published: October 2022

Oaks (Quercus spp.) are considered model plants for studying plant evolution and natural gene introgression. Beijing area is at the junction between Taihang Mountain and Yanshan Mountain, and it is an overlapping distribution area of several deciduous oaks native to China. Interspecific hybridization often occurs in sympatric sibling species, resulting in blurred interspecific boundaries and hindering the development of breeding. To have better improvement and protection of these oaks, it is urgently necessary to evaluate the genetic diversity and population structure of these oak species. In this study, we collected eleven populations of four oak species (Q. variabilis, Q. mongolica, Q. dentata and Q. aliena) in the Beijing area. By using the polymorphic SSR markers, we analyzed the genetic variation of the collected 400 individuals, investigated the population structure, and found gene introgression events. Q. variabilis had a clearer genetic background as compared to the other three species. Q. mongolica had a more frequent gene introgression with Q. dentata and Q. aliena. Our data reveal the introgression and genetic diversity of the four oak species native to the Beijing area, laying the foundation for conducting an oak germplasm nursery with a clear genetic background for protection and further improvement.
Radionuclides and Metals in the Parks of the City of Belgrade, Serbia: Spatial Distribution and Health Risk Assessment
Authors: Gulan Ljiljana , Stajic Jelena M. , Zeremski Tijana , Durlević Uroš , Valjarević Aleksandar
Published: October 2022

In urban areas, forest patches and parks are usually the places where people spend most of their time outdoors. Because of poor environmental protection policy and insufficient investment in industry and energy, Serbia is often ranked among the European countries with the greatest environmental pollution. In recent years, ecological protests have been organized throughout the country with the aim of raising ecological awareness and resolving environmental issues. The topic has become particularly popular since the plans for opening new mining areas in western Serbia came to the fore. This study was conducted with the aim to investigate radioactivity levels and metals content in soil and foliage of the most popular parks in Belgrade, the capital and largest city of Serbia. Based on a GIS (geographic information system) approach, the spatial distribution maps of radionuclides (226Ra, 232Th, 40K, 7Be, and 137Cs) and metals (As, Cd, Cr, Co, Cu, Na, Ni, Pb, Zn, K, Ca, Mg, and Mn) were made. Ambient dose-equivalent rate in air was also measured. The annual effective doses and excess lifetime cancer risk from radionuclides were calculated. Health effects of exposure to heavy metals in soil were estimated by noncarcinogenic and carcinogenic risk assessment.
Variation Characteristics of Soil Organic Carbon Storage and Fractions with Stand Age in North Subtropical Quercus acutissima Carruth. Forest in China
Authors: Deng Wenbin , Wang Xia , Hu Haibo , Zhu Mengdie , Chen Jianyu , Zhang Shuai , Cheng Can , Zhu Ziyi , Wu Chaoming , Zhu Li
Published: October 2022

Soil labile organic carbon sensitively reflects subtle changes in the soil carbon pool and is an important aspect of forest soil carbon pool research. However, little is known regarding soil labile organic carbon storage and its dynamic changes during the development of Quercus acutissima Carruth. forests. Consequently, we investigated the dynamic changes in soil organic carbon and its labile organic carbon fraction stocks at soil depths of 0–10 cm, 10–20 cm, and 20–40 cm along a 17-year-old, 26-year-old, and 65-year-old chronosequence in Quercus acutissima forests. We found that stand age significantly impacted particulate organic carbon (POC), light fraction organic carbon (LFOC), and soil organic carbon (SOC). The POC, LFOC, and SOC contents at different soil depths exhibited an increasing trend with stand age, which could be described by simple linear regression. However, there was no noteworthy difference in the soil water-soluble organic carbon (WSOC) content between different stand ages. Moreover, the 17-year-old, stand had higher POC, LFOC, and WSOC to SOC ratios. Soil nutrients significantly affected organic carbon and fractions, which revealed that POC, LFOC, WSOC, and SOC were remarkably positively correlated with alkaline hydrolysis nitrogen (AN) and available phosphorus (AP) (p < 0.05). Furthermore, WSOC, POC, LFOC, and SOC were significantly positively correlated with available potassium (AK) (p < 0.05). POC, LFOC, and SOC storage in the 0–40 cm soil layer increased with stand development, while WSOC storage decreased at 65a. In addition, LFOC stocks accounted for the highest proportion of organic carbon stocks. Our results indicated that the development of Quercus acutissima forests was a process of carbon sink; however, the soil organic carbon activity was high, and the soil structure was unstable during the early development stage.
Effects of Forest Conversion on Soil Ecosystem Services in Liuxihe National Forest Park, China
Authors: Zhuang Changwei , Zhang Xiuyu , Han Yu , Dong Mingang , Chen Weijie
Published: October 2022

The transition from natural forest to plantations has increased dramatically in the past decades. Forest conversion will affect soil properties and thus soil ecosystem services. Based on soil indicators, we studied the differences of soil ecosystem services among three forest types in Liuxihe National Forest Park and analyzed the effects of conversion from natural forest to artificial forest on soil ecosystem services. The results showed that the soil carbon sequestration of evergreen broadleaf forest (EBF) was stronger, and the soil organic carbon density (36.43 ± 0.97 kg m−3) was significantly higher than that of moso bamboo forest (MBF) (25.46 ± 1.72 kg m−3) and sugar orange forest (SOF) (19.31 ± 2.68 kg m−3) in the 0–10 cm soil layer. The soil water conservation of MBF was higher, and its soil water content was significantly higher than that of EBF in the three soil layers, which was more than 20% higher than that of EBF. There was no significant difference in soil total nitrogen content among the three forest types, while the soil total phosphorus content of MBF and SOF was more than twice that of EBF. It is important to consider soil ecosystem services in forest protection and restoration in forest parks.
Evaluation of Different Brown Seaweeds as Feed and Feed Additives Regarding Rumen Fermentation and Methane Mitigation
Authors: Ahmed Eslam , Batbekh Belgutei , Fukuma Naoki , Hanada Masaaki , Nishida Takehiro
Published: October 2022

This study investigated the impacts of different brown seaweed species—Ascophyllum nodosum, Sargassum fulvellum, Ecklonia maxima, Lessonia flavicans, Lessonia nigrescens, and Laminaria japonica—on rumen fermentation and methane (CH4) mitigation. The current in vitro batch culture study for 24 h at 39 °C evaluated these species in two experimental designs: as feed additive and as feed. The control group for both experimental designs was composed of 500 mg of basal diet (50% grass hay/50% concentrate). For the feed additives experimental design, each seaweed species was evaluated when it was added at 20% of the basal diet, while as a feed, the inclusion level of each species was 20% to partially replace the concentrate in the basal diet as follows (50% hay/30% concentrate/20% seaweed). Chemical analyses showed that the seaweeds were characterized by a high fiber content and high amounts of minerals such as calcium, potassium, and phosphorus, while the protein content ranged within 7 and 13%. When they were applied as feed additives, they increased the production of volatile fatty acids, with L. japonica being the most effective; however, they failed to suppress CH4 production. In contrast, their inclusion as a feed in the basal diet led to a significant reduction (p < 0.05) in CH4, especially for E. maxima and L. japonica, by up to 18 and 21%, respectively, but this was associated with general inhibition of the rumen fermentation. Therefore, the tested seaweeds could be used as a source of minerals and as a feed additive to improve rumen fermentation, but without anti-methanogenic potential. Meanwhile, their inclusion as feed at 20% could reduce CH4 production with an adverse effect on fermentation. Thus, further trials are needed to identify the appropriate inclusion level to achieve effective CH4 reduction without any detrimental effects on rumen fermentation.
Co-Fermenting Pyrolysis Aqueous Condensate and Pyrolysis Syngas with Anaerobic Microbial Communities Enables L-Malate Production in a Secondary Fermentative Stage
Authors: Robazza Alberto , Welter Claudia , Kubisch Christin , Baleeiro Flávio César Freire , Ochsenreither Katrin , Neumann Anke
Published: October 2022

The pyrolytic conversion of lignocellulosic biomass into fuels and chemicals is a promising option for the valorization of agricultural and forestry residues. However, technological developments are still needed to maximize product recovery and carbon fixation of the pyrolysis process. The pyrolysis aqueous condensate (PAC), a pyrolysis by-product, has a high water content and is highly toxic, hampering its use. The anaerobic digestion of PAC from different biomasses has been proven a viable technology for PAC valorization and detoxification, but its toxicity limits the methanogenic potential. Alternatively, methanation or VFA production from syngas by anaerobic mixed cultures are technologies of scientific interest. This study investigates the potential of a two-stage process to convert the carbon and energy in syngas and PAC into L-malate. PAC and syngas were co-fermented by two mixed cultures at 37 and 55 °C, identifying kinetic inhibitions and the effects of increasing PAC concentrations on the product pool. The media from selected mixed culture fermentations were then inoculated with Aspergillus oryzae for L-malate production. The results show that mixed cultures can perform simultaneous syngas fermentation and PAC detoxification. While PAC concentrations above 2% completely inhibited methanogenesis, CO consumption was inhibited at PAC concentrations above 5%, regardless of the temperature. In fermentations where PAC inhibited methanation, the mixed cultures channelled the carbon and electrons from syngas and PAC to volatile fatty acids or acetate/H2 production, depending on the incubation temperature. Substantial detoxification of PAC was observed under PAC concentrations up to 10% independently of the rates of syngas metabolism. PAC detoxification enabled the further valorization of the acetate produced via syngas and PAC fermentations into L-malate, achieving yields up to 0.17 mM/mM. These results are promising for the development of an integrated process that simultaneously detoxifies and recovers value from gaseous and aqueous waste streams originating from pyrolysis.
Quality Traits of Sourdough Bread Obtained by Novel Digital Technologies and Machine Learning Modelling
Authors: Gonzalez Viejo Claudia , Harris Natalie M. , Fuentes Sigfredo
Published: October 2022

Sourdough bread (SB) has increased popularity due to health benefits and higher interest in artisan breadmaking due to social isolation during the COVID-19 pandemic. However, quality traits and consumer assessment are still limited to complex laboratory analysis and sensory trials. In this research, new and emerging digital technologies were tested to assess quality traits of SB made from six different flour sources. The results showed that machine learning (ML) models developed to classify the type of wheat used for flours (targets) from near-infrared (NIR) spectroscopy data (Model 1) and a low-cost electronic nose (Model 2) as inputs rendered highly accurate and precise models (96.3% and 99.4%, respectively). Furthermore, ML regression models based on the same inputs for NIR (Model 3) and e-nose (Model 4) were developed to automatically assess 16 volatile aromatic compounds (targets) using GC-MS as ground-truth. To reiterate, models with high accuracy and performance were obtained with correlation (R), determination coefficients (R2), and slope (b) of R = 0.97; R2 = 0.94 and b = 0.99 for Model 3 and R = 0.99; R2 = 0.99 and b = 0.99 for Model 4. The development of low-cost instrumentation and sensors could make possible the accessibility of hardware and software to the industry and artisan breadmakers to assess quality traits and consistency of SB.
Malolactic Fermentation—Theoretical Advances and Practical Considerations
Authors: Paramithiotis Spiros , Stasinou Vasiliki , Tzamourani Aikaterini , Kotseridis Yorgos , Dimopoulou Maria
Published: October 2022

There are two main fermentations associated with the vinification process. Alcoholic fermentation (AF), which is conducted by yeasts and malolactic fermentation (MLF), which takes place as a result of the metabolic activity of lactic acid bacteria (LAB) of the genera Oenococcus, former-Lactobacillus, Pediococcus and Leuconostoc. MLF is defined as the biotransformation of L-malic acid to L-lactic acid and carbon dioxide and in addition to deacidification, contributes significantly to microbial stability and often to the improvement of the sensory profile of wines. Therefore, the abiotic and biotic factors that affect MLF, along with its correlation with quality characteristics, has been in the epicenter of intensive research. In addition, practical issues that accompany MLF have also been considered and adequately assessed. The aim of the present review was to explore and critically discuss MLF from both theoretical and practical perspectives.
Effect of Biochar Addition on Mechanism of Heavy Metal Migration and Transformation in Biogas Residue Aerobic Compost
Authors: Yan Wencong , Qu Jingbo , Qu Youpei , Yue Tian , Zhang Quanguo , Yi Weiming , Liu Xiaofeng , Sun Yong
Published: October 2022

In this study, biogas residue fermented by biogas engineering was used as compost raw material, and different quality biochar was added in the composting process to explore the effect of biochar on the transformation of heavy metals in the composting process. The composting process was comprehensively analyzed with the potential ecological risk assessment of heavy metals and redundancy analysis. The addition of 10.0% biochar during composting had a strong passivation effect on exchangeable Cu and Cd, with passivation rates of 11.75 and 63.89%, respectively; the addition of 2.5 and 7.5% biochar had strong passivation ability for exchangeable Zn and Pb, and the passivation rates were 15.26 and 45.02%, respectively. At the end of composting, the potential ecological risk indexes of each treatment were T4 (10.0% biochar) > T3 (7.5% biochar) > T2 (5.0% biochar) > T1 (2.5% biochar) > CK (no biochar added). The risk of heavy metal pollution during the aerobic composting of biogas residue was low, which significantly reduced secondary pollution during the composting process.