bluuebunny/crossref_metadata_2025 huggingface dataset:
EuroDRONE, a European Unmanned Traffic Management Testbed for U-Space
Authors: Lappas Vaios , Zoumponos Giorgos , Kostopoulos Vassilis , Lee Hae In , Shin Hyo-Sang , Tsourdos Antonios , Tantardini Marco , Shomko Dennis , Munoz Jose , Amoratis Epameinondas , Maragkakis Aris , Machairas Thomas , Trifas Andra
Published: February 2022

EuroDRONE is an Unmanned Traffic Management (UTM) demonstration project, funded by the EU’s SESAR organization, and its aim is to test and validate key UTM technologies for Europe’s ‘U-Space’ UTM program. The EuroDRONE UTM architecture comprises cloud software (DroNav) and hardware (transponder) to be installed on drones. The proposed EuroDRONE system is a Highly Automated Air Traffic Management System for small UAVs operating at low altitudes. It is a sophisticated, self-learning system based on software and hardware elements, operating in a distributed computing environment, offering multiple levels of redundancy, fail-safe algorithms for conflict prevention/resolution and assets management. EuroDRONE focuses its work on functionalities which involve the use of new communication links, the use of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) technology to communicate information between drones and operators for safe and effective UTM functionality. Practical demonstrations that took place in Patras/Messolonghi in 2019 are presented and show the benefits and shortcomings of near-term UTM implementation in Europe.
Estimating Non-Gaussianity of a Quantum State by Measuring Orthogonal Quadratures
Authors: Park Jiyong
Published: February 2022

We derive the lower bounds for a non-Gaussianity measure based on quantum relative entropy (QRE). Our approach draws on the observation that the QRE-based non-Gaussianity measure of a single-mode quantum state is lower bounded by a function of the negentropies for quadrature distributions with maximum and minimum variances. We demonstrate that the lower bound can outperform the previously proposed bound by the negentropy of a quadrature distribution. Furthermore, we extend our method to establish lower bounds for the QRE-based non-Gaussianity measure of a multimode quantum state that can be measured by homodyne detection, with or without leveraging a Gaussian unitary operation. Finally, we explore how our lower bound finds application in non-Gaussian entanglement detection.
Entropy-Variance Curves of Binary Sequences Generated by Random Substitutions of Constant Length
Authors: Nuño Juan Carlos , Muñoz Francisco J.
Published: February 2022

We study some properties of binary sequences generated by random substitutions of constant length. Specifically, assuming the alphabet {0,1}, we consider the following asymmetric substitution rule of length k: 0→⟨0,0,…,0⟩ and 1→⟨Y1,Y2,…,Yk⟩, where Yi is a Bernoulli random variable with parameter p∈[0,1]. We obtain by recurrence the discrete probability distribution of the stochastic variable that counts the number of ones in the sequence formed after a number i of substitutions (iterations). We derive its first two statistical moments, mean and variance, and the entropy of the generated sequences as a function of the substitution length k for any successive iteration i, and characterize the values of p where the maxima of these measures occur. Finally, we obtain the parametric curves entropy-variance for each iteration and substitution length. We find two regimes of dependence between these two variables that, to our knowledge, have not been previously described. Besides, it allows to compare sequences with the same entropy but different variance and vice versa.
The Random Plots Graph Generation Model for Studying Systems with Unknown Connection Structures
Authors: Ivanko Evgeny , Chernoskutov Mikhail
Published: February 2022

We consider the problem of modeling complex systems where little or nothing is known about the structure of the connections between the elements. In particular, when such systems are to be modeled by graphs, it is unclear what vertex degree distributions these graphs should have. We propose that, instead of attempting to guess the appropriate degree distribution for a poorly understood system, one should model the system via a set of sample graphs whose degree distributions cover a representative range of possibilities and account for a variety of possible connection structures. To construct such a representative set of graphs, we propose a new random graph generator, Random Plots, in which we (1) generate a diversified set of vertex degree distributions and (2) target a graph generator at each of the constructed distributions, one-by-one, to obtain the ensemble of graphs. To assess the diversity of the resulting ensembles, we (1) substantialize the vague notion of diversity in a graph ensemble as the diversity of the numeral characteristics of the graphs within this ensemble and (2) compare such formalized diversity for the proposed model with that of three other common models (Erdos–Rényi–Gilbert (ERG), scale-free, and small-world). Computational experiments show that, in most cases, our approach produces more diverse sets of graphs compared with the three other models, including the entropy-maximizing ERG. The corresponding Python code is available at GitHub.
Characterizing Sustained Use of Cleaner Cooking Fuel in Rural Poor Households of South India
Authors: Kumar Praveen , Du Maritha , Ma Mingyue
Published: February 2022

Approximately 40% of the global population (primarily rural poor) rely on traditional cookstoves, with pernicious social, economic, and health outcomes. The Government of India launched its massive Prime Ministers’ Ujjwala scheme in 2016 to promote liquefied petroleum gas (LPG), a cleaner cooking system, in poor communities. While there has been a surge in adoption, consistent use of LPG has been tepid. We examined the trend of use of LPG for 18 months in 58 poor households of South India. In place of soliciting survey questions on stove usage, we deployed stove use monitoring technologies to accurately measure the use of LPG and traditional stoves. We also analyzed factors characterizing LPG use. None of the households used LPG for more than 55% of their cooking time. LPG refill transportation, perception of faster cooking, and caste were significant predictors of LPG use. The findings highlight that social workers must engage with these communities to improve their awareness and shape their perceptions of cleaner cooking.
Two Modified Questionnaires for the Assessment of Nutrition Impact Symptoms in the Rehabilitation Phase after Burn Injury: A Content Validation Study
Authors: Dimander Josefin , Andersson Agneta , Miclescu Adriana , Huss Fredrik
Published: February 2022

Disease Related Appetite Questionnaire (DRAQ) and Eating Symptom Questionnaire (ESQ) are used to assess nutrition impact symptoms, which are symptoms that can negatively affect the patients’ food intake. However, these questionnaires have not yet been adapted to the needs of patients recovering from burn injuries. Our aim was therefore to develop DRAQ and ESQ for assessments of nutrition impact symptoms after burn injury. A content validation index (I-CVI) for items included in DRAQ and ESQ, regarding their relevance for possible nutrition impact symptoms in a burn-injured patient (Likert scale 1–4), was performed by an expert review group. A clarity validation by expert and non-expert reviewers was carried out. Two of the eleven questions in DRAQ and eight of the fourteen questions in ESQ were not considered relevant and were therefore removed from the questionnaires. Five additional questions were added to DRAQ and two to ESQ. A high degree of consensus on relevance (scale-content validity index average, S-CVI/Ave, 0.86 for DRAQ-burn and 0.83 for ESQ-burn) was reached in the expert group. To conclude, it is suggested that we use developed forms of DRAQ and ESQ (DRAQ-burn and ESQ-burn) for the assessment of nutrition impact symptoms, specifically during the rehabilitation phase of burn-injured patients.
Teachers’ Attitudes toward Autism Spectrum Disorder: A Systematic Review
Authors: Gómez-Marí Irene , Sanz-Cervera Pilar , Tárraga-Mínguez Raúl
Published: February 2022

(1) Teachers’ attitudes toward the inclusion of students with autism spectrum disorder (ASD) in mainstream schools influence daily educational practices. Depending on whether these attitudes are favorable or not, inclusive education could be fully or partially reached. This systematic review aims to analyze teachers’ attitudes toward ASD and to determine the variables that moderate them. (2) We conducted a systematic review in WoS, Scopus, and PsycINFO databases, obtaining an amount of 16 studies included in this review. (3) The results revealed inconclusive levels in teachers’ attitudes: Some of the teachers reported positive attitudes, some neutral, and some negative. (4) Among the variables that probably moderate attitudes, we found knowledge, experience, training, and gender. Future research and implications for pre-service and in-service teachers, school administrators, and policy makers are suggested.
Feature Enhancement-Based Ship Target Detection Method in Optical Remote Sensing Images
Authors: Zhou Liming , Li Yahui , Rao Xiaohan , Wang Yadi , Zuo Xianyu , Qiao Baojun , Yang Yong
Published: February 2022

Ship targets in ORSIs (Optical Remote Sensing Images) have the characteristics of various scales, and most of them are medium and small-scale targets. When the existing target detection algorithms are applied to ship target detection in ORSIs, the detection accuracy is low. There are two main reasons for the above problems, one is the mismatch of the receptive fields, and the other is the lack of feature information. For resolving the problem that multi-scale ship targets are difficult to detect, this paper proposes a ship target detection algorithm based on feature enhancement. Firstly, EIRM (Elastic Inception Residual Module) is proposed for feature enhancement, which can capture feature information of different dimensions and provide receptive fields of different scales for mid- and low-level feature maps. Secondly, the SandGlass-L block is proposed by replacing the ReLu6 activation function of the SandGlass block with the Leaky ReLu activation function. Leaky ReLu solves the problem of 0 output when ReLu6 has negative input, so the SandGlass-L block can retain more feature information. Finally, based on SandGlass-L, SGLPANet (SandGlass-L Path Aggregation Network) is proposed to alleviate the problem of information loss caused by dimension transformation and retain more feature information. The backbone network of the algorithm in this paper is CSPDarknet53, and the SPP module and EIRM act after the backbone network. The neck network is SGLPANet. Experiments on the NWPU VHR-10 dataset show that the algorithm in this paper can well solve the problem of low detection accuracy caused by mismatched receptive fields and missing feature information. It not only improves the accuracy of ship target detection, but also achieves good results when extended to other categories. At the same time, the extended experiments on the LEVIR dataset show that the algorithm also has certain applicability on different datasets.
A Simple Virtual-Vector-Based PWM Formulation for Multilevel Three-Phase Neutral-Point-Clamped DC–AC Converters including the Overmodulation Region
Authors: Busquets-Monge Sergio
Published: February 2022

Neutral-point-clamped (NPC) power conversion topologies are among the most popular multilevel topologies in current industrial products and in industrial and academic research. The proper operation of multilevel three-phase NPC DC–AC converters requires the use of specific pulse-width modulation (PWM) strategies that maintain the DC-link capacitor voltage balance and concurrently optimize various performance factors such as efficiency and harmonic distortion. Although several such PWM strategies have been proposed in the literature, their formulation is often complex and/or covers only particular cases and operating conditions. This manuscript presents a simple formulation of the original virtual-vector-based PWM, which enables capacitor voltage balance in every switching cycle. The formulation is presented, for the general case, in terms of basic phase voltage modulating signals, with no reference to space vectors, involving any number of levels and for any operating conditions, including the overmodulation region. The equivalence of the presented formulation to the original PWM strategy is demonstrated through simulation under different scenarios and operating conditions. Thus, this manuscript offers in a one-stop source a simple, effective, and comprehensive PWM formulation to operate multilevel three-phase NPC DC–AC converters with any number of levels in any operating condition.
Control of a Modified Switched-Capacitor Boost Converter
Authors: Ošlaj Benjamin , Truntič Mitja
Published: February 2022

Switched-capacitor converters and their alternatives have been shown to provide high efficiency with high power densities on smaller volumes, and can thereby be a suitable choice for energy harvesting. This paper proposes a hybrid power architecture based on a switched-capacitor topology and a boost converter that can be used for such purposes. A switching capacitor circuit can achieve any voltage ratio, allowing a boost converter to increase the input voltage to higher voltage levels. The first stage is unregulated with high-efficiency voltage conversion. The boost stage provides a regulated voltage output on such a converter. Rather than cascading two converters, their operation is integrated for the output voltage regulation. One major problem of switched-capacitor converters is output voltage regulation, which is solved by the interconnection of the power stages. The simplicity and robustness of the solution provide the possibility to achieve higher voltage ratios than cascading boost converters and provide higher efficiency. The converter’s size and cost can be improved with the integration of switching capacitors in DC-DC converter structures. A converter prototype has been designed, modelled, and built for the input voltage level of 2 V and power level of 5 W.
Developing IoT Artifacts in a MAS Platform
Authors: Palanca Javier , Rincon Jaime , Julian Vicente , Carrascosa Carlos , Terrasa Andrés
Published: February 2022

The Internet of Things (IoT) is a growing computational paradigm where all kinds of everyday objects are interconnected, forming a vast cyberphysical environment at the edge between the virtual and the real world. Since the emergence of the IoT, Multi-Agent Systems (MAS) technology has been successfully applied in this area, proving itself to be an appropriate paradigm for developing distributed, intelligent systems containing sets of IoT devices. However, this technology still lacks effective mechanisms to integrate the enormous diversity of existing IoT devices systematically. In this context, this paper introduces the concept of the IoT artifact as a new interface abstraction for the development of MAS based on IoT devices. The IoT artifact strictly conforms to the Agents and Artifacts (A&A) meta-model, and it also adopts the programming model of the SPADE multi-agent platform, providing both a consistent theoretical framework and a practical model for real-world applications.
Machine-Learning Methods for Complex Flows
Authors: Vinuesa Ricardo , Le Clainche Soledad
Published: February 2022

We are delighted to introduce this Special Issue focused on novel machine-learning (ML) methods aimed at predicting, modeling, and controlling a variety of complex fluid flow scenarios [...]
Centrally Adapted Optimal Control of Multiple Electric Water Heaters
Authors: Ritchie Michael J. , Engelbrecht Jacobus A. A. , Booysen Marthinus J.
Published: February 2022

Breakthroughs in smart grid technology make it possible to deliver electricity in controlled and intelligent ways to improve energy efficiency between the user and the utility. Demand-side management strategies can reduce overall energy usage and shift consumption to reduce peak loads. Electric water heaters account for 40% of residential energy consumption. Since they are thermal storage devices, advanced control strategies can improve their efficiency. However, existing methods disregard the connection between the user and the grid. We propose a centrally adapted control model that allows for coordinated scheduling to adapt the optimal control schedule of each EWH, spreading the load into off-peak periods to ensure that the grid’s generation capacity is not exceeded. We consider two strategies for the delivery of hot water: temperature matching, and energy matching with Legionella sterilisation, and compare them to a baseline strategy where the thermostat is always switched on. Simulation results for a grid of 77 EWHs showed that an unconstrained peak load of 1.05 kW/EWH can be reduced as low as 0.4 kW/EWH and achieve a median energy saving per EWH of 0.38 kWh/day for the temperature matching strategy and 0.64 kWh/day for the energy matching strategy, without reducing the user’s comfort.
Characteristics and Prediction of the Thermal Diffusivity of Sandy Soil
Authors: Dai Baoming , Zhang Yaxing , Ding Haifeng , Xu Yunlong , Liu Zhiyun
Published: February 2022

Revealing the variation law of thermal diffusivity of sandy soil can provide a theoretical basis for the engineering design and construction in cold and arid regions. Based on experimental data of sandy soil samples, the distribution characteristics and influence of dry density and moisture content on thermal diffusivity are analyzed in this work. Then, the prediction model based on the empirical fitting formula and RBF neural network method for thermal diffusivity of frozen and unfrozen sandy soil is established, and the prediction accuracy of different prediction methods is compared. The results show that (1) thermal diffusivity of sandy soil is positively correlated with the particle size. With the increase of sand size, thermal diffusivity of sandy soil increases significantly. (2) Partial correlation among natural moisture content, dry density, and thermal diffusivity varies with different frozen and unfrozen conditions. (3) For unfrozen sandy soil, the binary RBF neural network prediction model is obviously better than that of the binary empirical fitting formula model. (4) The ternary prediction model has significantly higher prediction accuracy than that of the binary prediction model for frozen sandy soil, and the ternary RBF neural network model has the best prediction effect among the four methods.
The Impact of Detail, Shadowing and Thermal Zoning Levels on Urban Building Energy Modelling (UBEM) on a District Scale
Authors: Faure Xavier , Johansson Tim , Pasichnyi Oleksii
Published: February 2022

New modelling tools are required to accelerate the decarbonisation of the building sector. Urban building energy modelling (UBEM) has recently emerged as an attractive paradigm for analysing building energy performance at district and urban scales. The balance between the fidelity and accuracy of created UBEMs is known to be the cornerstone of the model’s applicability. This study aimed to analyse the impact of traditionally implicit modeller choices that can greatly affect the overall UBEM performance, namely, (1) the level of detail (LoD) of the buildings’ geometry; (2) thermal zoning; and (3) the surrounding shadowing environment. The analysis was conducted for two urban areas in Stockholm (Sweden) using MUBES—the newly developed UBEM. It is a bottom-up physics-based open-source tool based on Python and EnergyPlus, allowing for calibration and co-simulation. At the building scale, significant impact was detected for all three factors. At the district scale, smaller effects (<2%) were observed for the level of detail and thermal zoning. However, up to 10% difference may be due to the surrounding shadowing environment, so it is recommended that this is considered when using UBEMs even for district scale analyses. Hence, assumptions embedded in UBEMs and the scale of analysis make a difference.
Pressure Drop and Energy Recovery with a New Centrifugal Micro-Turbine: Fundamentals and Application in a Real WDN
Authors: Morani Maria Cristina , Simão Mariana , Gazur Ignac , Santos Rui S. , Carravetta Armando , Fecarotta Oreste , Ramos Helena M.
Published: February 2022

Water distribution networks need to improve system efficiency. Hydropower is a clean and renewable energy that has been among the key solutions to environmental issues for many decades. As the turbine is the core of hydropower plants, high attention is paid to creating new design solutions and increasing the performance of turbines in order to enhance energy efficiency of leakage by pressure control. Hence, design and performance analysis of a new turbine is a crucial aspect for addressing the efficiency of its application. In this study, computational fluid dynamics (CFD) modeling is coupled with experimental tests in order to investigate the optimal performance of a new centrifugal turbine. The behavior of the flow through the turbine runner is assessed by means of velocity profiles and pressure contours at all components of the machine under different operating conditions. Finally, the turbine geometry is scaled to a real water distribution network and an optimization procedure is performed with the aim of investigating the optimal location of both the designed new centrifugal micro-turbines (CMT) and pressure reducing valves (PRV) in order to control the excess of pressure and produce energy at the same time.
Latest Expansions in Lipid Enhancement of Microalgae for Biodiesel Production: An Update
Authors: Rawat Jyoti , Gupta Piyush Kumar , Pandit Soumya , Priya Kanu , Agarwal Daksh , Pant Manu , Thakur Vijay Kumar , Pande Veena
Published: February 2022

Research progress on sustainable and renewable biofuel has gained motion over the years, not just due to the rapid reduction of dwindling fossil fuel supplies but also due to environmental and potential energy security issues as well. Intense interest in microalgae (photosynthetic microbes) as a promising feedstock for third-generation biofuels has grown over recent years. Fuels derived from algae are now considered sustainable biofuels that are promising, renewable, and clean. Therefore, selecting the robust species of microalgae with substantial features for quality biodiesel production is the first step in the way of biofuel production. A contemporary investigation is more focused on several strategies and techniques to achieve higher biomass and triglycerides in microalgae. The improvement in lipid enhancement in microalgae species by genetic manipulation approaches, such as metabolic or genetic alteration, and the use of nanotechnology are the most recent ways of improving the production of biomass and lipids. Hence, the current review collects up-to-date approaches for microalgae lipid increase and biodiesel generation. The strategies for high biomass and high lipid yield are discussed. Additionally, various pretreatment procedures that may aid in lipid harvesting efficiency and improve lipid recovery rate are described.
High-Fidelity Steady-State and Transient Simulations of an MTR Research Reactor Using Serpent2/Subchanflow
Authors: Almachi Juan Carlos , Sánchez-Espinoza Víctor Hugo , Imke Uwe
Published: February 2022

In order to join efforts to develop high-fidelity multi-physics tools for research reactor analysis, the KIT is conducting studies to modify the coupled multi-physics codes developed for power reactors. The coupled system uses the Monte Carlo Serpent 2 code for neutron analysis and the Subchanflow code for thermo-hydraulic analysis. Serpent treats temperature dependence using the target motion sampling method and Subchanflow was previously extended and validated with experimental data for plate-type reactor analysis. This work present for the first time the steady-state and transient neutron and thermo-hydraulic analysis of an MTR core defined in the IAEA 10 MW benchmark using Serpent2/Subchanflow. Important global and local parameters for nominal steady-state conditions were obtained, e.g., the lowest and highest core plate/channel power/temperature, the radial and axial core power profile at the plate level, and the core coolant temperature distribution at the subchannel level. The capabilities of Serpent2/Subchanflow to perform transient analysis with on-the-fly motion of the control plates were tested, namely with fast and slow reactivity insertion. Based on the unique results obtained for the first time at the subchannel and plate level, it can be stated that the coupled Serpent2/Subchanflow code is a very promising tool for research reactor safety-related investigations.
Impacts of Separator Thickness on Temperature Distribution and Power Generation Characteristics of a Single PEMFC Operated at Higher Temperature of 363 and 373 K
Authors: Nishimura Akira , Kojima Yuya , Ito Syogo , Hu Eric
Published: February 2022

The aim of this study is to investigate the effects of the separator thickness on not only the heat and mass transfer characteristics, but also the power generation characteristics of a polymer electrolyte membrane fuel cell (PEMFC) with a thin polymer electrolyte membrane (PEM) and thin gas diffusion layer (GDL) operated at higher temperatures of 363 and 373 K. The in-plane temperature distributions on the back of the separator at the anode and cathode, which are the opposite sides to the GDL, are measured using a thermograph at various initial cell temperatures (Tinit), relative humidity (RH) levels, and supply gas flow rates. The total voltage corresponding to the load current is measured in order to evaluate the performance of the PEMFC. As a result, it is revealed that the effect of the RH on the power generation characteristics is more significant when the separator thickness decreases. It is revealed that the power generation performance obtained at high current densities decreases with the increase in Tinit with thinner separator thicknesses. According to the investigation of the in-plane temperature distribution, it is clarified that the temperature decreases at corner positions in the separator with the separator thickness of 2.0 mm, while the temperature gradually increases along with the gas flow with separator thicknesses of 1.5 mm and 1.0 mm.
Lifecycle Assessment and Techno-Economic Analysis of Biochar Pellet Production from Forest Residues and Field Application
Authors: Bergman Richard , Sahoo Kamalakanta , Englund Karl , Mousavi-Avval Seyed Hashem
Published: February 2022

Biochar produced from low-value forest biomass can provide substantial benefits to ecosystems and mitigate climate change-induced risks such as forest fires. Forest residues from restoration activities and timber harvest and biochar itself are bulky and thus incur high logistic costs, so are considered major bottlenecks for the commercialization of the biochar industry. The objectives of this study were to assess the environmental footprints and techno-economic feasibility of converting forest residues in Pacific Northwest United States into biochar pellets using portable systems followed by delivery of the final product to end-users for land application (dispersion). Two portable systems (Biochar Solutions Incorporated (BSI) and Air Curtain Burner (ACB)) were considered for biochar production. A cradle-to-grave lifecycle assessment (LCA) and a discounted cash flow analysis method were used to quantify the environmental impacts and minimum selling price (MSP) of biochar. The global warming (GW) impact of biochar production through BSI and ACB was estimated to be 306–444, and 750–1016 kgCO₂eq/tonne biochar applied to the field, respectively. The MSP of biochar produced through BSI and ACB was 1674–1909 and 528–1051 USD/tonne biochar applied to the field, respectively. Pelletizing of biochar reduced GW impacts during outbound logistics (~8–20%) but increased emissions during pelletizing (~1–9%). Results show the BSI system was a more viable option in terms of GW impact, whereas the ACB system can produce biochar with lower MSP. The results of the study conclude that the production of biochar pellets through the two portable systems and applied to fields can be both an environmentally beneficial and economically viable option.
Bioremediation of Agriculture Soil Contaminated by Organic Pollutants
Authors: Kisić Ivica , Hrenović Jasna , Zgorelec Željka , Durn Goran , Brkić Vladislav , Delač Domina
Published: February 2022

Pipeline spills and pollution of the environment by crude oil pose a threat to natural resources, especially soil and water. One such incident occurred on 25 September 2018 in the area of Budrovac (Croatia; 46°00′14.6″ N 17°04′16.8″ E) on agricultural land as a pipeline spill. Bioremediation of the contaminated soil was carried out with organic pollutants using an environmentally safe absorbent Spill-Sorb (Canadian Sphagnum Peat Moss) and a mineral fertilizer—nitrogen. The experiment was conducted in the greenhouse of the Faculty of Agriculture, Croatia, during a six-month (October 2018–April 2019) study. Samples of agricultural soils contaminated with total petroleum hydrocarbons (TPHs) and polycyclic aromatic hydrocarbons (PAHs) were taken after the rupture of the local gas condensate pipeline. The experiment was conducted in five treatments in triplicate: I-control (clean soil); II-100% contaminated soil + organic absorbent + nitrogen; III-100% contaminated soil + organic absorbent; IV-50% clean soil + 50% contaminated soil + organic absorbent + nitrogen; and V-50% clean soil + 50% contaminated soil + organic absorbent. The soil properties studied were pH, organic matter content, carbon and nitrogen content and ratio, and changes in the concentration of potential organic contaminants—TPHs and individual PAHs. The results demonstrated that the mixture of organic absorbent and nitrogen efficiently removed organic pollutants from the contaminated soil within six months. However, the application of Spill-Sorb alone was more effective for the degradation of hydrocarbons. The effectiveness of the absorbent studied was dependent on the concentration of organic pollutants and nitrogen application.
Genome Wide Association Study Identifies Candidate Genes Related to the Earlywood Tracheid Properties in Picea crassifolia Kom.
Authors: Zhou Chengcheng , Guo Yingtian , Chen Yali , Zhang Hongbin , El-Kassaby Yousry A. , Li Wei
Published: February 2022

Picea crassifolia Kom. is one of the timber and ecological conifers in China and its wood tracheid traits directly affect wood formation and adaptability under harsh environment. Molecular studies on P. crassifolia remain inadequate because relatively few genes have been associated with these traits. To identify markers and candidate genes that can potentially be used for genetic improvement of wood tracheid traits, we examined 106 clones of P. crassifolia, and investigated phenotypic data for 14 wood tracheid traits before specific-locus amplified fragment sequencing (SLAF-seq) was employed to perform a genome wide association study (GWAS). Subsequently, the results were used to screen single nucleotide polymorphism (SNP) loci and candidate genes that exhibited a significant correlation with the studied traits. We developed 4,058,883 SLAF-tags and 12,275,765 SNP loci, and our analyses identified a total of 96 SNP loci that showed significant correlations with three earlywood tracheid traits using a mixed linear model (MLM). Next, candidate genes were screened in the 100 kb zone (50 kb upstream, 50 kb downstream) of each of the SNP loci, whereby 67 candidate genes were obtained in earlywood tracheid traits, including 34 genes of known function and 33 genes of unknown function. We provide the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in wood traits improvement and candidate genes for the development of earlywood tracheid in P. crassifolia.
Investigating Antimicrobial Characteristics/Advantages of Australian Wood Species for Use in Food Packaging—A Feasibility Study
Authors: Shirmohammadi Maryam
Published: February 2022

The antimicrobial characteristics of Australian commercial timber species were studied using a direct screening method and two different microorganisms. The effectiveness of timber samples was compared with plastic and paper samples during an incubation period of 24 h at 37 °C. The initial data with E. coli and S. aureus showed no difference in performance between the plastic and paper samples and the softwood samples tested. Hardwood samples, however, showed an inhibition zone when tested with S. Aureus. The data showed similar trends of inhibition zones developed for sterilised and non-sterilised samples of spotted gum and shining gum species. The observed data showed promising antimicrobial characteristics for both veneer and solid samples of hardwood species. Further studies investigating the type of extractives, their role in antimicrobial characteristics and differences in the type of surface exposed to the microbial contamination from the point of view of timber’s anatomical properties are proposed.
A Tree Ring Proxy Evaluation of Declining Causes in Pinus sylvestris L. and Pinus nigra J.F. Arnold in Northeastern Romania
Authors: Nechita Constantin , Iordache Andreea Maria , Costinel Diana , Botoran Oana Romina , Dănilă Gabriel , Ionete Roxana Elena , Varlam Mihai
Published: February 2022

Drought-induced dieback has been extensively studied in various forests habitats. We used a retrospective tree ring width (TRW), basal area increment (BAI), oxygen isotope ratios in tree ring cellulose (δ18OTR) and carbon isotope ratios in tree ring cellulose (δ13CTR) to assess causes in declining Pinus sylvestris L. and Pinus nigra J.F. Arnold. The climate data analysis indicates a significant increased trend occurred after 1980 in minimum, mean and maximum temperature and a reduced amount of precipitation compared to the 1920–1980-time scale. According to the Palmer Drought Severity Index, we found two extreme drought years (1946 and 2000) and three years with severe drought (1990, 2003 and 2012). One-way ANOVA indicated no significant difference between P. nigra and P sylvestris tree ring width, basal area increment, but a considerable difference between δ13CTR and δ18OTR. Basal area increment evaluated the climate-growth relationship most accurately, comparing to δ18OTR and δ13CTR, which explained the influences of environmental factors in tree rings formation. The δ13CTR was mainly negatively correlated with high temperatures from April-August current growing seasons. The negative correlation between δ13CTR and NDVI indices (June, August) shows a decreased carbon uptake induced by drought from summer to early autumn. The low δ18OTR signal was associated with a complex of factors, including the strong influence of heavy precipitation occurring in the growing season and a weak reaction of declined trees to resources. Species-specific responses to drought in 1990, 2003 and 2012 indicated P. sylvestris as more sensitive to drought whit higher demand for water supply in the optimal compared with P. nigra. Weak and unstable correlations in time with increasing/decreasing values in drought periods were obtained more accurately using δ18OTR compared to δ13CTR. The species-specific resilience response to drought years showed a weak resilience and resistance in P. sylvestris occurred more evident after the 2012 event compared to less sensitive P. nigra trees. Decision-makers can use presented results to reinforce specific management plans capable of protecting and changing local compositions where is the case with species more resistant to drouth.
Variation of Morphological Traits and Quality Indices of Micropropagated Melia volkensii Gürke Clones before Field Planting
Authors: Dushimimana Constantin , Magomere Titus , Mulatya Jackson , Vandenabeele Jan , Olubayo Florence , Smagghe Guy , Werbrouck Stefaan P. O.
Published: February 2022

The quality of acclimatized in vitro cultivated plants is essential to ensure good survival and growth after planting in field conditions. After two months of acclimatization, this study revealed a significant variation in survival rate, shoot characteristics, root traits, and biomass features between 13 clones of Melia volkensii Gürke. A number of quality indices such as the Dickson Quality Index (DQI), shoot dry weight: root dry weight ratio (S:R), and sturdiness quotient (SQ) also showed a large variation. The survival rate was genotype-dependent, with an average of 85%. Extreme genotypes were tall, had long internodes, a lot of leaves, and a large leaf area. At the other side of the spectrum, there were small clones with short internodes and a reduced number of leaves and leaf areas. The high S:R values (>2) of the evaluated clones indicate an imbalance between the shoot and root system, negatively influencing the quality of the in vitro produced M. volkensii plants. The SQ for all clones was below the threshold value of 6, implying a good and expected survival rate. This study illustrates that some clones might systematically score better for SQ, S:R, plant volume, and DQI after acclimatization and that these factors could form the basis for selection.
Productivity-Based Land Suitability and Management Sensitivity Analysis: The Eucalyptus E. urophylla × E. grandis Case
Authors: Shi Miaoying , Xu Jintao , Liu Shilei , Xu Zhenci
Published: February 2022

Eucalyptus plantations are productive and short rotation forests prevalent in tropical areas that experience fast expansion and face controversies in ecological issues. In this study, we perform a systematic analysis of factors influencing eucalyptus growth through plot records from the National Forest Inventories and satellite images. We find primary restricting factors for eucalyptus growth via machine learning algorithms with random forests and accumulated local effects plots, as conventional forest growth models are inadequate to calculate the causal effect with the large number of environmental and socioeconomic factors. As a result, despite common belief that temperature affects eucalyptus growth the most, we find that precipitation is the most evident restricting factor for eucalyptus growth. We then identify and rank key factors that affect timber growth, such as tree density, rotation period, and wood ownership. Finally, we suggest optimal management and planting strategies for local farmers and policymakers to facilitate eucalyptus growth.
A Novel Method for Calculating Stand Structural Diversity Based on the Relationship of Adjacent Trees
Authors: Zhao Zhonghua , Hui Gangying , Liu Wenzhen , Hu Yanbo , Zhang Gongqiao
Published: February 2022

Understanding the diversity and complexity of stand structure is important for managing the biodiversity of forest ecosystem, and stand structural diversity is essential for evaluating forest management activities. Based on the relationship of adjacent trees, a quantitative method of stand structure diversity is proposed to express the heterogeneity of stand structure in tree species, distribution pattern, species separation and size differentiation. In this study, we defined the diversity of structural unit types and derived a new index of forest structural diversity (SD′) employing the additivity principle of the Shannon–Weiner index. The efficiency of the index was verified by applying the new measure to sixteen field survey samples at different locations. The mountain rainforest in Hainan had the highest forest structural diversity, followed by broad-leaved Korean pine forests in Jiaohe (2), Jiaohe (1) and an oak-broadleaved mixed natural forest at Xiaolongshan (2). The SD′ values of plantations and pure natural forest were lower. The simulated data of different thinning methods and the intensity of broad-leaved Korean pine forests show that the new measure can reflect forest management changes on stand structure diversity. The value of SD′ compared with no treatments and the differences were greater as thinning intensity increased. The SD′ index provides minimum and maximum values for different structural unit types in forests to achieve a unified comparative basis for calculating forest structure diversity. It has the characteristics of the general diversity index and can well express the diversity of tree species, distribution pattern and size differentiation simultaneously. The SD′ index can not only calculate the structural diversity of mixed species forests but can also be used to calculate the structural diversity of pure forests. It can also be used to evaluate the change in stand structure diversity after management interventions.
Research on the Temporal and Spatial Distributions of Standing Wood Carbon Storage Based on Remote Sensing Images and Local Models
Authors: Zhang Xiaoyong , Sun Yuman , Jia Weiwei , Wang Fan , Guo Haotian , Ao Ziqi
Published: February 2022

Background and Objectives: It is important to understand the temporal and spatial distributions of standing wood carbon storage in forests to maintain ecological balance and forest dynamics. Such information can provide technical and data support for promoting ecological construction, formulating different afforestation policies, and implementing forest management strategies. Long-term series of Landsat 5 (Thematic Mapper, TM) and Landsat 8 (Operational Land Imager, OLI) remote sensing images and digital elevation models (DEM), as well as multiphase survey data, provide new opportunities for research on the temporal and spatial distributions of standing wood carbon storage in forests. Methods: The extracted remote sensing factors, terrain factors, and forest stand factors were analyzed with stepwise regression in relation to standing wood carbon storage to identify significant influential factors, build a global ordinary least squares (OLS) model and a linear mixed model (LMM), and construct a local geographically weighted regression (GWR), multiscale geographically weighted regression model (MGWR), temporally weighted regression (TWR), and geographically and temporally weighted regression (GTWR). Model evaluation indicators were used to calculate residual Moran’s I values, and the optimal model was selected to explore the spatiotemporal dynamics of standing wood carbon storage in the Liangshui Nature Reserve. Results: Remote sensing factors, topographic factors (Slope), and stand factors (Age and DBH) were significantly correlated with standing wood carbon storage, and the constructed global models exhibited fitting effects inferior to those of the established local models. LMM is also used as a global model to add random effects on the basis of OLS, and R2 is increased to 0.52 compared with OLS. The local models based on geographically weighted regression, namely, GWR, MGWR, TWR, and GTWR, all have good performance. Compared with OLS, the R2 is increased to 0.572, 0.589, 0.643, and 0.734, and the fitting effect of GTWR is the best. GTWR can overcome spatial autocorrelation and temporal autocorrelation problems, with a higher R2 (0.734) and a more ideal model residual than other models. This study develops a model for carbon storage (CS) considering various influential factors in the Liangshui area and provides a possible solution for the estimation of long-term carbon storage distribution.
Beyond Monetary Cost-Benefit Analyses: Combining Economic, Environmental and Social Analyses of Short Rotation Coppice Poplar Production in Slovakia
Authors: Fürtner Daniela , Perdomo Echenique Enrique Alejandro , Hörtenhuber Stefan J. , Schwarzbauer Peter , Hesser Franziska
Published: February 2022

Rising demand for bio-based products exerts a growing pressure on natural resources such as wood. Sustainable solutions are becoming increasingly important to meet the demand. In this study, 20-year poplar Short Rotation Coppice (SRC) plantations located in Western Slovakia are investigated with respect to (socio)-economic, environmental and social sustainability. The cost–benefit methodology is applied to assess the economic profitability of a switch from conventional annual crops (corn maize and winter rye) to perennial SRC. To compare economic profitability of the land management, net present value (NPV), payback time (PBT), internal rate of return (IRR) and benefit–cost ratio (BCR) are calculated. The study was enhanced by adopting the concept of regional value added to indicate the local value creation. The results for the three scenarios yield an NPV equal to 12,156 euros ha−1 for corn maize, 9763 euros ha−1 for winter rye and 2210 euros ha−1 with a PBT of 14.13 years for poplar SRC production. The regional value added for the corn maize scenario was estimated with 10,841 euros ha−1, the winter rye with 7973 euros ha−1 and the poplar SRC with 1802 euros ha−1. To appraise non-monetized social values, semi-structured interviews (N = 4) were conducted among experts familiar with SRC management in Eastern Europe. Non-monetary benefits for the stakeholder groups society, farmers or landowners and the industry were identified in terms of land fragmentation, carbon sequestration and an increase in biodiversity within the plantations, farm diversification and higher independency from wood markets. The relatively poor image of SRC, farmers or landowners having concerns about being tied on long-term contracts and legal restrictions may become obstacles in the establishment of SRC. For estimating the capability of carbon sequestration in SRC plantations the RothC model was utilized, resulting in the potential soil organic carbon (SOC) average increase of 29% during the 20 years. However, a transition in land use patterns must involve thorough considerations of all three pillars of sustainability to ensure long-term viability of the establishment.
Effects of Mulberry Branch and Leaves Silage on Microbial Community, Rumen Fermentation Characteristics, and Milk Yield in Lactating Dairy Cows
Authors: Li Yan , Wang Jiaqi , Mei Jie , Huang Lingxia , Liu Hongyun
Published: February 2022

This study investigated the effects of mulberry branch and leaves (MBL) silage on milk yield, ruminal fermentation, and bacteria composition in dairy cows. Thirty-six mid-lactation cows were selected and randomly allocated into three groups. The control group (C) was fed on a total mixed ratio (TMR) diet, while the experimental groups were fed on TMR supplemented with 5% (L) and 10% (H) MBL silage. The experiment lasted for eight weeks, including two weeks of adaption. The results showed that Group H had an increased milk yield, milk fat content (p < 0.05), and 4% feed conversion ratio (p = 0.10). In addition, rumen propionic acid was significantly increased (p < 0.05), while acetate/propionate was significantly decreased (p < 0.05) in the high MBL silage group. The microbiome analysis showed that Bacteroides, Firmicutes, and Proteobacteria were the predominant phyla. Compared with Group C, the abundance of Bacteroides was significantly decreased (p < 0.01), while the Firmicutes and Proteobacteria were increased but not significantly different in Groups L and H. Prevotella was significantly decreased (p < 0.05) in the MBL silage groups, and Succinivibrionaceae_UCG-001 was increased in Group H. The correlation analysis showed that eight bacterial species belonging to Firmicutes were positively correlated with propionic acid. However, four bacterial species belonging to the Bacteroides group were negatively correlated with propionic acid. In conclusion, feed supplementation with about 5–10% of MBL silage could modulate the rumen microbiota and fermentation, and increase the abundance of fiber-digesting, propionic acid synthesis and milk fat-related microorganisms, thus improving milk yield in dairy cows.