bluuebunny/crossref_metadata_2025 huggingface dataset:
ZnO and AZO Film Potentiometric pH Sensors Based on Flexible Printed Circuit Board
Authors: Yang Po-Hui , Chang Ying-Sheng , Chan Che-Tsung
Published: July 2022

In this study, we deposited zinc oxide (ZnO) and aluminum-doped zinc oxide (AZO) on the electroless nickel immersion gold (ENIG) of a flexible printed circuit board (FPCB) as a potentiometric pH sensor. The sensing films of the pH sensor were fabricated by a radio frequency (RF) sputtering system and analyzed by field emission scanning electron microscope (FE-SEM) and X-ray photoelectron spectroscopy (XPS). In the pH 2 to 10 buffer solutions, it was observed that the characteristics of the pH sensor through the voltage–time (V-T) measurement system include average sensitivity and linearity, drift effect, and repeatability. According to the experimental results, the pH sensors in this study could exhibit good characteristics.
Enhancement of Chiller Performance by Water Distribution on the Adiabatic Cooling Pad’s Mesh Surface
Authors: Borodinecs Anatolijs , Lebedeva Kristina , Sidenko Natalja , Prozuments Aleksejs
Published: July 2022

Evaporative cooling is widely recognized as an energy efficient and environmentally-friendly air conditioning solution, and it has drawn a lot of market interest in recent years. However, this technology is accompanied by several challenges. For instance, insufficient evaporation due to poor and non-homogenous water distribution of the pre-cooling pad significantly reduces the cooling performance. The aim of the study is to develop a technique for numerical simulation of the distribution of a droplet liquid (water) on the mesh surface of an adiabatic cooler to improve the performance of air conditioning equipment. Modern computer-aided design (CAD)/computational fluid dynamics (CFD) programs were used to solve the issue. For the mathematical modelling of the medium motion, non-stationary Navier–Stokes equations were used. Parameters such as heat, mass transfer, and the efficiency of liquid droplet spraying were determined. The current study presents CAD modelling, conducted in SolidWorks platform, of water distribution on the adiabatic cooling pad’s mesh surface for improving air conditioning equipment performance. This study provides the methodology for computer modeling and numerical calculation of the parameters of adiabatic cooling, such as modelling of water atomization process. The results show that the use of additional metal mesh intended as cooling pads increases the mass transfer coefficient by Sh ≈ 15–40%; heat transfer coefficient Nu increases by ≈20–40%; and the atomization efficiency increases by ≈30–40%. The installation of metal pad mesh allows for equalized uniformity of the water distribution. The results imply that there are more opportunities to optimize the parameters of adiabatic cooling, which should be evaluated in further research on the subject.
Deflection Prediction of Rehabilitation Asphalt Pavements through Deep Forest
Authors: Wu Yi , Chen Xueqin , Jiang Dongqi
Published: July 2022

The deep forest is a powerful deep-learning algorithm that has been applied in certain fields. In this study, a deep forest (DF) model was developed to predict the central deflection measured by a falling weight deflectometer (FWD). In total, 11,075 samples containing information related to pavement structure, traffic conditions, and weather conditions were extracted from the LTPP dataset. The performance of the DF model with custom backend settings was compared with that of models random forest (RF), multilayer perceptron (MLP), and DF built on the sklearn backend. All four deep-learning algorithms could identify the complex relationship between central deflection and relevant feature variables with high accuracy and stability. The learning and generalization abilities of DF was stronger than those of MLP and RF. The predictive performance and computation time of DF (custom) were better than those of DF (sklearn), indicating that the custom model was superior to the highly encapsulated model with sklearn as the backend. Feature importance analysis indicated that the drop load of FWD was the key factor influencing deflection. In addition, structural number, annual precipitation, and annual kilo equivalent standard axle load (kESAL) are very important features related with deflection. The feature importance of rehabilitation improvement thickness was less than the drop load, climatic factors, kESAL, structural number, and layer thickness.
Combining Log Files and Monitoring Data to Detect Anomaly Patterns in a Data Center
Authors: Viola Laura , Ronchieri Elisabetta , Cavallaro Claudia
Published: July 2022

Context—Anomaly detection in a data center is a challenging task, having to consider different services on various resources. Current literature shows the application of artificial intelligence and machine learning techniques to either log files or monitoring data: the former created by services at run time, while the latter produced by specific sensors directly on the physical or virtual machine. Objectives—We propose a model that exploits information both in log files and monitoring data to identify patterns and detect anomalies over time both at the service level and at the machine level. Methods—The key idea is to construct a specific dictionary for each log file which helps to extract anomalous n-grams in the feature matrix. Several techniques of Natural Language Processing, such as wordclouds and Topic modeling, have been used to enrich such dictionary. A clustering algorithm was then applied to the feature matrix to identify and group the various types of anomalies. On the other side, time series anomaly detection technique has been applied to sensors data in order to combine problems found in the log files with problems stored in the monitoring data. Several services (i.e., log files) running on the same machine have been grouped together with the monitoring metrics. Results—We have tested our approach on a real data center equipped with log files and monitoring data that can characterize the behaviour of physical and virtual resources in production. The data have been provided by the National Institute for Nuclear Physics in Italy. We have observed a correspondence between anomalies in log files and monitoring data, e.g., a decrease in memory usage or an increase in machine load. The results are extremely promising. Conclusions—Important outcomes have emerged thanks to the integration between these two types of data. Our model requires to integrate site administrators’ expertise in order to consider all critical scenarios in the data center and understand results properly.
Identifying Redox Orbitals and Defects in Lithium-Ion Cathodes with Compton Scattering and Positron Annihilation Spectroscopies: A Review
Authors: Nokelainen Johannes , Barbiellini Bernardo , Kuriplach Jan , Eijt Stephan , Ferragut Rafael , Li Xin , Kothalawala Veenavee , Suzuki Kosuke , Sakurai Hiroshi , Hafiz Hasnain , Pussi Katariina , Keshavarz Fatemeh , Bansil Arun
Published: July 2022

Reduction-oxidation (redox) reactions that transfer conduction electrons from the anode to the cathode are the fundamental processes responsible for generating power in Li-ion batteries. Electronic and microstructural features of the cathode material are controlled by the nature of the redox orbitals and how they respond to Li intercalation. Thus, redox orbitals play a key role in performance of the battery and its degradation with cycling. We unravel spectroscopic descriptors that can be used to gain an atomic-scale handle on the redox mechanisms underlying Li-ion batteries. Our focus is on X-ray Compton Scattering and Positron Annihilation spectroscopies and the related computational approaches for the purpose of identifying orbitals involved in electrochemical transformations in the cathode. This review provides insight into the workings of lithium-ion batteries and opens a pathway for rational design of next-generation battery materials.
Multi-Stream Convolution-Recurrent Neural Networks Based on Attention Mechanism Fusion for Speech Emotion Recognition
Authors: Tao Huawei , Geng Lei , Shan Shuai , Mai Jingchao , Fu Hongliang
Published: July 2022

The quality of feature extraction plays a significant role in the performance of speech emotion recognition. In order to extract discriminative, affect-salient features from speech signals and then improve the performance of speech emotion recognition, in this paper, a multi-stream convolution-recurrent neural network based on attention mechanism (MSCRNN-A) is proposed. Firstly, a multi-stream sub-branches full convolution network (MSFCN) based on AlexNet is presented to limit the loss of emotional information. In MSFCN, sub-branches are added behind each pooling layer to retain the features of different resolutions, different features from which are fused by adding. Secondly, the MSFCN and Bi-LSTM network are combined to form a hybrid network to extract speech emotion features for the purpose of supplying the temporal structure information of emotional features. Finally, a feature fusion model based on a multi-head attention mechanism is developed to achieve the best fusion features. The proposed method uses an attention mechanism to calculate the contribution degree of different network features, and thereafter realizes the adaptive fusion of different network features by weighting different network features. Aiming to restrain the gradient divergence of the network, different network features and fusion features are connected through shortcut connection to obtain fusion features for recognition. The experimental results on three conventional SER corpora, CASIA, EMODB, and SAVEE, show that our proposed method significantly improves the network recognition performance, with a recognition rate superior to most of the existing state-of-the-art methods.
A Calculation Method of Passenger Flow Distribution in Large-Scale Subway Network Based on Passenger–Train Matching Probability
Authors: Su Guanghui , Si Bingfeng , Zhi Kun , Li He
Published: July 2022

The ever-increasing travel demand has brought great challenges to the organization, operation, and management of the subway system. An accurate estimation of passenger flow distribution can help subway operators design corresponding operation plans and strategies scientifically. Although some literature has studied the problem of passenger flow distribution by analyzing the passengers’ path choice behaviors based on AFC (automated fare collection) data, few studies focus on the passenger flow distribution while considering the passenger–train matching probability, which is the key problem of passenger flow distribution. Specifically, the existing methods have not been applied to practical large-scale subway networks due to the computational complexity. To fill this research gap, this paper analyzes the relationship between passenger travel behavior and train operation in the space and time dimension and formulates the passenger–train matching probability by using multi-source data including AFC, train timetables, and network topology. Then, a reverse derivation method, which can reduce the scale of possible train combinations for passengers, is proposed to improve the computational efficiency. Simultaneously, an estimation method of passenger flow distribution is presented based on the passenger–train matching probability. Finally, two sets of experiments, including an accuracy verification experiment based on synthetic data and a comparison experiment based on real data from the Beijing subway, are conducted to verify the effectiveness of the proposed method. The calculation results show that the proposed method has a good accuracy and computational efficiency for a large-scale subway network.
Effect of Planar Interfaces on Nucleation in Melting and Crystallization
Authors: Schmelzer Jürn W. P. , Tipeev Azat O.
Published: July 2022

The effect of planar interfaces on nucleation (namely, on the work of critical cluster formation and their shape) is studied both for crystallization and melting. Advancing an approach formulated about 150 years ago by J. W. Gibbs for liquid phase formation at planar liquid–liquid interfaces, we show that nucleation of liquids in the crystal at crystal–vapor planar interfaces proceeds as a rule with a much higher rate compared to nucleation in the bulk of the crystal. Provided the surface tensions crystal–liquid (σcl), liquid–vapor (σlv), and crystal–vapor (σcv) obey the condition σcv=σcl+σlv, the work of critical cluster formation tends to zero; in the range σcv<σcl+σlv, it is less than one half of the work of critical cluster formation for bulk nucleation. The existence of a liquid–vapor planar interface modifies the work of critical cluster formation in crystal nucleation in liquids to a much less significant degree. The work of critical crystal cluster formation is larger than one half of the bulk value of the work of critical cluster formation, reaching this limit at σcv=σcl+σlv. The shape of the critical clusters can be described in both cases by spherical caps with a radius, R, and a width parameter, h. This parameter, h, is the distance from the cutting plane (coinciding with the crystal–vapor and liquid–vapor planar interface, respectively) to the top of the spherical cap. It varies for nucleation of a liquid in a crystal in the range (h/R)≤1 and for crystal nucleation in a liquid in the range 2≥(h/R)≥1. At σcv=σcl+σlv, the ratio (h/R) of the critical cluster for nucleation in melting tends to zero ((h/R)→0). At the same condition, the critical crystallite has the shape of a sphere located tangentially to the liquid–vapor interface inside the liquid ((h/R)≅2). We present experimental data which confirm the results of the theoretical analysis, and potential further developments of the theoretical approach developed here are anticipated.
Improving Image Super-Resolution Based on Multiscale Generative Adversarial Networks
Authors: Yuan Cao , Deng Kaidi , Li Chen , Zhang Xueting , Li Yaqin
Published: July 2022

Convolutional neural networks have greatly improved the performance of image super-resolution. However, perceptual networks have problems such as blurred line structures and a lack of high-frequency information when reconstructing image textures. To mitigate these issues, a generative adversarial network based on multiscale asynchronous learning is proposed in this paper, whereby a pyramid structure is employed in the network model to integrate high-frequency information at different scales. Our scheme employs a U-net as a discriminator to focus on the consistency of adjacent pixels in the input image and uses the LPIPS loss for perceptual extreme super-resolution with stronger supervision. Experiments on benchmark datasets and independent datasets Set5, Set14, BSD100, and SunHays80 show that our approach is effective in restoring detailed texture information from low-resolution images.
Integrating beyond Content: A Framework for Infusing Elementary STEM-Focused Schools Components into Full-Service Community Schools
Authors: Peters-Burton Erin , Provinzano Kathleen , Koskey Kristin L. K. , May Toni
Published: July 2022

Learning through an integrated STEM framework has been shown to provide elementary students with numerous advantages over learning through isolated content instruction. All students, however, do not have access to high quality STEM instruction for reasons such as living in an under resourced community or their elementary school teachers feeling unprepared in STEM. For the purpose broadening STEM participation, this conceptual paper proposes a thoughtful integration of two interdisciplinary yet separate educational initiatives: STEM-focused elementary schools and full-service community schools (FSCS). In this conceptual manuscript, each educational initiative is first described independently. Then an explanation of how the central tenets of STEM-focused elementary schools and FSCS overlap is presented. Resultantly, a proposed model for integrating the two educational initiatives (FSCSeSTEM) is depicted using a rigorous design-based research methodology. This conceptual piece ultimately demonstrates that it seems prudent to consider integrating not only content in elementary schools, but also well-researched and established educational initiatives for the possibility of expanding STEM opportunities for all. FSCSeSTEM is one such attempt at a conceptual model proposed for future research and practice.
Influence of Substrate and Gate Insulator on the Thermal Characteristics of β-Ga2O3 Field-Effect Transistors: A Simulation Study
Authors: Liu Chaochao , He Hao , Zhou Xinlong , Liu Wenjun
Published: July 2022

β-Ga2O3 suffers from extremely poor thermal conductivity, resulting in a severe self-heating effect. Integrating β-Ga2O3 with high-thermal-conductivity foreign substrates is one of the promising solutions to improve the thermal performance of β-Ga2O3 devices. However, the gate insulator also plays an important role in the device’s thermal characteristics. In this work, we analyze the influence of the thermal conductivity of the substrate and gate insulator and the associated thermal boundary conductance (TBC) on the channel peak temperature (TMAX) investigated by the coupled 3-D thermal simulation. It reveals that AlN and SiC substrate could be sufficient compared to the expensive diamond substrate for substrate integration thermal management scheme. And the reduced TMAX becomes more prominent with the high thermal conductivity gate insulator (e.g., h-BN) than with the conventional Al2O3 gate insulator. Furthermore, the TMAX of the device maintains a very high temperature as the TBC is very low (10 MWm−2K−1), indicating the importance of optimizing TBC. Our results provide useful insights into the thermal management of β-Ga2O3 devices.
Machine Learning in Operating of Low Voltage Future Grid
Authors: Mroczek Bartłomiej , Pijarski Paweł
Published: July 2022

The article is a continuation of the authors’ ongoing research related to power flow and voltage control in LV grids. It outlines how the Distribution System Operator (DSO) can use Machine Learning (ML) technology in a future grid. Based on supervised learning, a Selectively Coherent Model of Converter System Control for an LV grid (SCM_CSC) is proposed. This represents a fresh, new approach to combining off and on-line computing for DSOs, in line with the decarbonisation process. The main kernel of the model is a neural network developed from the initial prediction results generated by regression analysis. For selected PV system operation scenarios, the LV grid of the future dynamically controls the power flow using AC/DC converter circuits for Battery Energy Storage Systems (BESS). The objective function is to maintain the required voltage conditions for high PV generation in an LV grid line area and to minimise power flows to the MV grid. Based on the training and validation data prepared for artificial neural networks (ANN), a Mean Absolute Percentage Error (MAPE) of 0.15% BESS and 0.51–0.55% BESS 1 and BESS 2 were achieved, which represents a prediction error level of 170–300 VA in the specification of the BESS power control. The results are presented for the dynamic control of BESS 1 and BESS 2 using an ANN output and closed-loop PID control including a 2nd order filter. The research work represents a further step in the digital transformation of the energy sector.
A Numerical Study on the Energization of the Field Coils of a Full-Size Wind Turbine with Different Types of Flux Pumps
Authors: Russo Giacomo , Morandi Antonio
Published: July 2022

High temperature superconductivity is emerging as a solution for lightweight, cost-effective and high-power wind generators. Current injection and maintainment/sustainment in the field winding are obtained by metal current leads which, due to persistent heat conduction and joule loss, are responsible for a large part of the total cryogenic heat load. Slip rings, which further reduce the overall performance and reliability of the system, are also required. In this paper we assess the viability of the HTS dynamo and the rectifier flux pumps for energizing the field coils of the EcoSwing 3.6 MW HTS wind generator. Both a “warm” solution, with the rectifier at room temperature, and a “cold” solution, in which the latter is integrated into the cryostat, are investigated with regard to the rectifier flux pump. A comparison with the actual, state-of-the-art, system of the EcoSwing machine is carried out in terms of the total required cooling power and the ability to charge the HTS field winding up to the rated current. It is found that the dynamo flux pump, beside avoiding the need of slip rings, allows the reduction in the required cooling by about 74% with respect to the conventional current-leads-based solution.
The Idea of Sustainable Development and the Possibilities of Its Interpretation and Implementation
Authors: Płonka Aleksandra , Dacko Mariusz , Satoła Łukasz , Dacko Aneta
Published: July 2022

In the publication, the authors put forward a thesis about the low social understanding of the essence of the idea of sustainable development (SD), its assumptions, and difficulties with its implementation. This thesis became the starting point for research on contemporary problems related to the understanding and implementation of the idea of SD in Poland and an inspiration to look at Education for Sustainable Development (ESD). The aim of the study was to get to know the opinions of experts on the statutory definition of SD and social awareness of this idea, and then to relate these opinions to the state of knowledge of students, as well as their opinions and attitudes towards SD. Primary data obtained in the course of surveys among 105 Polish experts (employees of universities, research institutes, government and local government units) and 844 students from several Polish university centres were used. The obtained results indicated gaps in Education for Sustainable Development (ESD) and the related very diverse and often misinterpreted concept of SD, which seems to be one of the key barriers to the implementation of SD in local life.
Geochemical Characteristics and the Sedimentary Environment of Lower Cambrian Argillaceous Rocks on the Kongquehe Slope, Tarim Basin, China
Authors: Shang Kai , Tian Jingchun , Lv Haitao , Zhang Xiang , Li Jian , Zhang Yue
Published: July 2022

The deposition of the Lower Cambrian argillaceous rocks on the Kongquehe slope provides a good opportunity to reconstruct the paleoenvironmental conditions of the Tarim Basin. To explore the paleoredox conditions, paleoclimate, and provenance of this deposit, 21 samples were collected from Well A, and the concentrations of major and trace elements were analyzed. The V/(V + Ni), V/Cr, Ni/Co, U/Th, Uau, and V/Sc ratios indicated that the sediments in the water body from the Lower Cambrian were in a reducing environment, and the degree of reduction weakened from the bottom to the top. The Sr/Cu, Mg/Ca, and Fe/Mn ratios in the sediments revealed that the Lower Cambrian was mainly characterized by a warm and humid paleoclimate, and there may be a paleoclimatic transition toward drought conditions as recorded by the sediments of Xidashan Formation. The chemical alteration index, compositional variation index, plagioclase alteration index values, and Th/U and K/Rb ratios of the Lower Cambrian mudstone all reflected that the parent rock in the study area was mainly subject to low- to medium-degree chemical weathering. Longitudinally, the Lower Cambrian gradually increased and then weakened from Xishanbulake Formation to Xidashan Formation. The ratios of trace elements and rare earth elements as well as Th–Sc–Zr/10, Th–Co–Zr/10, and ∑REE–La/Yb diagrams all showed that the mudstones of Xishanbulake and Xidashan Formations of the Lower Cambrian in the study area have a common parent rock type, mainly sedimentary rocks rich in felsic minerals. Additionally, the structural setting discrimination diagrams of SiO2–K2O/Na2O, Th–Sc–Zr/10, Th–Co–Zr/10, and La–Th–Sc showed that the structural setting of the Lower Cambrian mudstone deposition is mainly a continental island arc environment and has the characteristics of an active continental margin.
Approaches to Carbon Emission Reductions and Technology in China’s Chemical Industry to Achieve Carbon Neutralization
Authors: Ma Lei , Song Mei
Published: July 2022

Based on China’s goal of achieving carbon neutrality by 2060, this study focused on its coal gasification in 2010–2019. Carbon emissions were calculated from industrial data, and an LMDt model was established to analyze the influencing factors of carbon emissions. Through scenario analysis, the paths of carbon emission reductions in the chemical industry were analyzed, and their emission reduction potential was estimated. The results showed that the carbon emissions in the chemical industry increased rapidly in 2010–2019, reaching 196 million tons in 2019. The emission structure was the most important factor in mitigating carbon emissions, and the emission intensity, industrial structure, economic development level, and labor force scale had different degrees of promotion effects, of which emission intensity was the strongest. The chemical industry can reach a carbon peak before 2030 under the three analyzed scenarios, and the emission reduction potential is the largest under the landing policy scenario. The results showed that carbon capture, usage, and storage (CCUS) technology is key for carbon emission reductions and that it is necessary to adjust the industrial structure, reduce emission intensity, and increase forest carbon sink to achieve carbon neutrality in the chemical industry.
The Impact of Opencast Lignite Mining on Rural Development: A Literature Review and Selected Case Studies Using Desk Research, Panel Data and GIS-Based Analysis
Authors: Maciejewska Alina , Kuzak Łukasz , Sobieraj Janusz , Metelski Dominik
Published: July 2022

The future of opencast mining and energy production based on conventional resources is one of the most important issues being discussed in international forums. The whole discussion is becoming increasingly heated and takes on a special significance with the drastic increase in energy commodity prices that has occurred with the outbreak of war in Ukraine. Especially in a country like Poland, these issues are accompanied by heated discussions between miners, the government and citizens. It should be emphasised that Polish lignite mining currently produces about 35% of the cheapest electricity in Poland and also creates many jobs. The aim of this study is to assess the possibility of continuing opencast mining and its impact on rural development—both from an environmental and socio-economic point of view. The study was conducted for two municipalities in Poland where opencast lignite mining plays an important role, namely Kleszczów and Kleczew. As a result, it was found that in the case of the studied municipalities, the presence of opencast mining has contributed to their development, and the application of modern environmental protection technologies and recultivation have reduced the difficulties associated with mining. On the other hand, the decision to start mining should be the result of a comparison between the potential environmental and social benefits and damages. In some cases, mining is beneficial for community development and leads to new opportunities for agriculture and tourism after reclamation. The study is a combination of different methods, i.e., case studies, GIS remote sensing analysis (based on Landsat data) and econometric analysis for selected socio-economic data.
Designing Harvesting and Hauling Cost Models for Energy Cane Production for Biorefineries
Authors: Illukpitiya Prabodh , Yuldashev Firuz , Nasiru Kabirat
Published: July 2022

The harvesting and hauling operations of bioenergy feedstock is an important area in biofuel production. Production costs can be minimized by maintaining optimal machinery units for these operations. The objective of this study is to design an optimal harvesting unit for bioenergy refinery and estimate harvesting and hauling costs of energy cane. A biorefinery with the annual capacity of processing twenty-five million imp. gallons of ethanol were considered. Given the efficiency of harvesting, a two-row soldier system was considered. Considering the year-round supply of energy cane to the refinery, the optimal machinery unit was designed, and the combined operation costs were derived. The average estimated ownership, repair, labor and fuel and lubricant costs of biomass harvest unit were calculated to be $0.50, $0.54, $1.78 and $1.51/mt, respectively. The costs distribution generated showed harvesting and hauling costs could range between $5.47–$9.23/mt of energy cane. The methodology and the research output will provide guidelines for investors in designing harvesting and hauling units and estimating costs for different scales of operation.
Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review
Authors: Jaen-Cuellar Arturo Y. , Elvira-Ortiz David A. , Osornio-Rios Roque A. , Antonino-Daviu Jose A.
Published: July 2022

Renewable energy-based power generation technologies are becoming more and more popular since they represent alternative solutions to the recent economic and environmental problems that modern society is facing. In this sense, the most widely spread applications for renewable energy generation are the solar photovoltaic and wind generation. Once installed, typically outside, the wind generators and photovoltaic panels suffer the environmental effects due to the weather conditions in the geographical location where they are placed. This situation, along with the normal operation of the systems, cause failures in their components, and on some occasions such problems could be difficult to identify and hence to fix. Thus, there are generated energy production stops bringing as consequence economical losses for investors. Therefore, it is important to develop strategies, schemes, and techniques that allow to perform a proper identification of faults in systems that introduce renewable generation, keeping energy production. In this work, an analysis of the most common faults that appear in wind and photovoltaic generation systems is presented. Moreover, the main techniques and strategies developed for the identification of such faults are discussed in order to address the advantages, drawbacks, and trends in the field of detection and classification of specific and combined faults. Due to the role played by wind and photovoltaic generation, this work aims to serve as a guide to properly select a monitoring strategy for a more reliable and efficient power grid. Additionally, this work will propose some prospective with views toward the existing areas of opportunity, e.g., system improvements, lacks in the fault detection, and tendency techniques that could be useful in solving them.
Decision Support Tool to Enable Real-Time Data-Driven Building Energy Retrofitting Design
Authors: Piira Kalevi , Kantorovitch Julia , Kannari Lotta , Piippo Jouko , Vu Hoang Nam
Published: July 2022

The availability of near-real-time data on energy performance is opening new opportunities to optimize buildings’ energy efficiency and flexibility capabilities and to support the decision-making and planning process of building retrofitting infrastructure investment. Existing tools can support retrofitting design and energy performance contracting. However, there are well-recognized shortcomings of these tools related to their usability, complexity, and ability to perform calculations based on the real-time energy performance of buildings. To address this gap, the advanced retrofitting decision support tool is developed and presented in this study. The strengths of our solution rely on easy usability, accuracy, and transparency of results. The automatic collection of real-time building energy consumption data gathered from the building management systems, combined with data analytics techniques, ensures ease of use and quickness of calculation. These results support step-by-step thinking for retrofitting design and hopefully enable a larger utilization rate for deep building retrofits.
Modeling and Stability Analysis of Distributed Secondary Control Scheme for Stand-Alone DC Microgrid Applications
Authors: Aluko Anuoluwapo , Swanson Andrew , Jarvis Leigh , Dorrell David
Published: July 2022

Stand-alone DC microgrids have multiple distributed generation (DG) sources that meet the required demand (load) by using droop control to achieve load (current) sharing between the DGs. The use of droop control leads to a voltage drop at the DC bus. This paper presents a distributed secondary control scheme to simultaneously ensure current sharing between the DGs and regulate the DC bus voltage. The proposed control scheme eliminates the voltage deviation and ensures balanced current sharing by combining the voltage and current errors in the designed secondary control loop. A new flight-based artificial bee colony optimization algorithm is proposed. This selects the parameters of the distributed secondary control scheme to achieve the objectives of the proposed controller. A state–space model of the DC microgrid is developed by using eigenvalue observation to test the impacts of the proposed optimized distributed secondary controller on the stability of the DC microgrid system. A real-time test system is developed in MATLAB/Simulink and used in a Speedgoat real-time simulator to verify the performance of the proposed control scheme for real-world applications. The results show the robustness of the proposed distributed secondary control scheme in achieving balance current sharing and voltage regulation in the DC microgrid with minimal oscillations and fast response time.
Research on Static Stability of Firefighting Adapter
Authors: Matej Jaroslav , Hnilica Richard , Hnilicová Michaela
Published: July 2022

The article is focused on the static stability of a vehicle with a 2000-liter water tank behind the rear axle. The purpose of the research is to evaluate the influence of the tank on stability. The vehicle is composed of a forestry skidder, a water tank, and equipment. To equilibrate the tank a ballast weight of 500 kg in front of the skidder is used. The influence of various combinations of the full water tank, half-filled water tank, and ballast weight is evaluated. The stability is determined as the distances of vectors of a stability triangle and a gravity vector, that is placed in a center of gravity of the whole vehicle. A Python programming language is used to implement the solution. The results are displayed in form of heatmaps. For the analyses, a slope angle of 18∘ is used. The results show that the longitudinal stability is decreased and lateral stability is increased. The tank also makes the vehicle unstable in some positions.
A Farmer’s Perspective on the Relevance of Grassland-Related Innovations in Mediterranean Dehesa Systems
Authors: Fernández-Habas Jesús , Fernández-Rebollo Pilar , Gallardo-Cobos Rosa , Vanwalleghem Tom , Sánchez-Zamora Pedro
Published: July 2022

Grasslands are of key importance for the provision of ecosystem services (ES). Suitable management is essential to guarantee their persistence and functionality. There is a growing interest in innovations such as new technologies aimed at facilitating and improving the management of grasslands while increasing their provision of ES. The uptake of innovations by farmers is a complex process, and relevant socio-economic or technological factors that are crucial to farmers are often overlooked. This information can be useful for increasing the adoption of these innovations through the design of public policies to facilitate them. This paper analyses the relevance of the main innovations that can be applied to the management of the grasslands of Dehesa farms for the farmers and the factors that might affect this relevance. Through questionaries, we gathered information on the relevance that farmers give to the selected innovations and analysed it by cumulative link models. The results show that innovations aimed at increasing the biomass production of grasslands and resilience such as the use of seed mixtures and the use of forage drought-resistant species are considered highly relevant by Dehesa farmers. However, high-tech innovations such as GPS collars were poorly rated which could denote low applicability to the context of Dehesas or the existence of barriers hindering the adoption but also a need for further development and better information on their potential. Characteristics of the farmer and farm such as age, education level, and stocking rate seem to be related to the relevance given to some of the innovations. These results provide insightful information for the implementation and research of relevant grassland-related innovations in the context of Mediterranean Dehesa/Montado systems, as well as for the design of policies supporting them.
Effects of Cellulase, Lactobacillus plantarum, and Sucrose on Fermentation Parameters, Chemical Composition, and Bacterial Community of Hybrid Pennisetum Silage
Authors: Xiong Haoming , Zhu Yanchen , Wen Zhiying , Liu Guangbin , Guo Yongqing , Sun Baoli
Published: July 2022

Hybrid Pennisetum (HP) is a perennial herb with a high yield and high quality, which makes it valuable for research as feed for herbivores. In order to make better use of hybrid Pennisetum as feed, this study studied the effects of cellulase (CE), Lactobacillus plantarum (LP), sucrose (SU), and their mixtures on fermentation parameters, chemical composition, and the bacterial community of hybrid Pennisetum silage. The experiment was divided into 7 treatments, silage treatment, and its abbreviation: CON (control group), CE (100 U/g FM cellulase), LP (1 × 106 cfu/g FM Lactobacillus plantarum), SU (1% FM sucrose), CE+LP (100 U/g FM cellulase + 1 × 106 cfu/g FM Lactobacillus plantarum), CE+SU (100 U/g FM cellulase + 1% FM sucrose), and LP+SU (1 × 106 cfu/g FM Lactobacillus plantarum + 1% FM sucrose). The silage bag was opened on the 60th day of ensilage for subsequent determination. The addition of CE and LP increased lactic acid content (p > 0.05). The pH and acetic acid of CE and LP were lower than CON (p < 0.05), and the crude protein content of CE was higher than CON. Cellulase and Lactobacillus plantarum can improve the quality of hybrid Pennisetum silage. Compared with Lactobacillus plantarum and sucrose, cellulase has better nutrition preservation and the ability to inhibit protein hydrolysis. 16S rRNA analysis showed that the dominant phyla were Fimicutes and Proteobacteria, and the dominant genera were Lactobacillus and Weissella. The changes in fermentation parameters and chemical components of hybrid Pennisetum silage caused by cellulase, Lactobacillus plantarum, sucrose, and their mixture may be the result of bacterial community changes.
Numerical Simulation of Acoustic Resonance in a Duct Containing a Flat Plate
Authors: Geihe Benedict , Wellner Jens , Ashcroft Graham
Published: July 2022

This work is about numerical simulations of vortex induced acoustic resonance in a duct, experimentally investigated by Welsh et al. Vortex shedding of low-speed flow over a flat plate excites an acoustic duct mode, leading to a lock-in of shedding and acoustic resonance frequency over a wide range of flow velocities. This study shows that a state-of-the-art compressible Navier–Stokes flow solver is able to capture the lock-in phenomenon. The focus is on the numerical parameters required to precisely recover the experimental results in terms of lock-in range and acoustic pressure levels. Complete and reliable physical data are thereby obtained, which can aid in developing a systematic understanding of the complex flow interactions. Furthermore, hysteresis behavior is discovered and numerically explored.
Development of a Canadian Food Composition Database of Gluten-Free Products
Authors: Jamieson Jennifer A. , Gill Kelsey , Fisher Samantha , English Marcia
Published: July 2022

Country-specific food composition data are needed for gluten-free (GF) food products to assess nutritional adequacy and diet quality. This research aimed to develop a comprehensive GF food composition database for key GF foods consumed in Canada. Average nutrient data from 167 products were estimated from Nutrition Fact Panel labels and the commercial ingredient list, using an iterative and systematic approach. The database reports mean values for energy and 29 nutrients per 100 g for 33 GF commercial grain-based foods. Nutrient values were evaluated with Health Canada’s nutrient content claims per standard reference serving. On average, GF products were, at minimum, a source of thiamin (73%), riboflavin (70%), niacin (58%), iron (58%), fibre (55%), magnesium (48%), folate (36%), zinc (19%), and calcium (15%). Most GF products were low in saturated fat (85%) and cholesterol (64%) but only 15% were low in total fat and 6% were free of sugar. Micronutrient enrichment and the use of nutrient-dense whole grain flours, legume flours, oil seed husks, and functional fibre ingredients varied within and between categories and brands but appeared to contribute to nutrient content. This database provides a new tool to enhance GF diet assessment in individuals or populations in Canada.
Multiplex PCR Identification of Aspergillus cristatus and Aspergillus chevalieri in Liupao Tea Based on Orphan Genes
Authors: Wang Zhong , Jin Qifang , Li Qin , Ou Xingchang , Li Shi , Liu Zhonghua , Huang Jian’an
Published: July 2022

“Golden flower” fungi in dark tea are beneficial to human health. The rapid identification method of “golden flower” fungi can verify the quality of dark tea products and ensure food safety. In this study, 6 strains were isolated from Liupao tea. They were respectively identified as A. cristatus, A. chevalieri, and A. pseudoglaucus. A. pseudoglaucus was reported as Liupao tea “golden flower” fungus for the first time. It was found that the ITS and BenA sequences of A. cristatus and A. chevalieri were highly conserved. It is difficult to clearly distinguish these closely related species by ITS sequencing. To rapidly identify species, multiplex PCR species-specific primers were designed based on orphan genes screened by comparative genomics analysis. Multiplex PCR results showed that orphan genes were specific and effective for the identification of A. cristatus and A. chevalieri isolated from Liupao tea and Fu brick tea. We confirmed that orphan genes can be used for identification of closely related Aspergillus species. Validation showed that the method is convenient, rapid, robust, sequencing-free, and economical. This promising method will be greatly beneficial to the dark tea processing industry and consumers.
Beneficial Effects of Sodium Nitroprusside on the Aroma, Flavors, and Anthocyanin Accumulation in Blood Orange Fruits
Authors: Zhang Zhong-Wei , Liu Han , Li Hao , Yang Xin-Yue , Fu Yu-Fan , Kang Qi , Wang Chang-Quan , Yuan Ming , Chen Yang-Er , Yuan Shu
Published: July 2022

The quality of Tarocco blood orange (Citrus sinensis (L.) Osbeck), which has been cultivated for many years, has degraded substantially. Decreased sugar content, decreased blood color, and increased sour flavor have developed as a result. To improve fruit quality, we studied the effects of bagging and sodium nitroprusside, as a nitric oxide (NO) donor, on the fruit quality of Tarocco blood orange two months before picking. The results showed that NO treatment effectively improved the content of total soluble solids and limonene in the fruit, as well as the color and hardness of the fruit, but reduced the tannin content. It also increased the contents of soluble sugar, fructose, sucrose, vitamin C, amino acids, and mineral elements. NO treatment inhibited the activities of polygalacturonase and pectin esterase, delayed the degradation of protopectin, and promoted the accumulation of anthocyanins, total flavonoids, and flavonoids synthesis. Thus, NO treatment improved the aroma, flavors, and physical properties of blood orange fruit.
Exploratory Study for Probiotic Enrichment of a Sea Fennel (Crithmum maritimum L.) Preserve in Brine
Authors: Maoloni Antonietta , Cardinali Federica , Milanović Vesna , Osimani Andrea , Verdenelli Maria Cristina , Coman Maria Magdalena , Aquilanti Lucia
Published: July 2022

Considering the increasing consumer demand for vegan and vegetarian health foods, different vegetables have been already exploited to produce non-dairy probiotic foods. In addition to being rich in bioactive compounds, sea fennel (Crithmum maritimum L.), also known as rock samphire, represents a valuable candidate in the production of probiotic-enriched foods, and, to the authors’ knowledge, it has not yet been explored as carrier for probiotics. Hence, the present study was aimed at evaluating the survival of a commercially available probiotic formulation, SYNBIO®, and Lactiplantibacillus plantarum IMC 509 in an artificially acidified, pasteurized sea fennel preserve in brine during a refrigerated storage of 44 days. Despite slight reductions in the microbial loads, at the end of the storage, both the probiotic formulations showed loads higher than 7.0 Log CFU g−1 of sea fennel or mL−1 of brine, above the recommended administration dose to exert beneficial health effects. Thus, acidified sea fennel sprouts in brine represent a potential vehicle for probiotics delivery to humans.
Effect of Swell-Drying on Mango (Mangifera indica) Drying Kinetics
Authors: Casaverde-Pacherrez Luis Alberto , Téllez-Pérez Carmen , Besombes Colette , Marcelo-Aldana Daniel , Allaf Karim , Vásquez-Díaz Edilberto
Published: July 2022

Swell-Drying operation (SD) was applied on mangoes to evaluate its effect on drying kinetics: starting accessibility (δW), apparent drying coefficient (Dapp), and time to obtain a final moisture content of 20% d.b (tf = 20% d.b). Swell-drying consisted of (1) submitting fresh mangoes to a first pre-drying stage under Convective Air Drying (CAD) until a moisture content of 37% d.b; (2) applying Instant Controlled Pressure Drop (DIC) treatments on pre-dried mangoes by following a central composite rotatable design (steam pressure: 0.2–0.6 MPa and treatment time: 5 and 55 s); and (3) apply post-drying of mangoes under CAD. In both cases, CAD was performed at 60 °C and airflow of 1 m/s. Results showed that both the treatment time and the steam pressure impacted the Dapp and the δW. By comparing to the control, SD (0.54 MPa and 48 s) increased the Dapp and δW to 12.2 and 2.7 times, respectively. Moreover, SD triggers a significant reduction in post-drying time (tf = 20% d.b), being this of 2.4 h vs. 30.8 h. These results could be linked to the expansion of the internal pores of mangoes generated by the instant autovaporization of residual water triggered by DIC treatment.
Designing and Implementing the MySusCof App—A Mobile App to Support Food Waste Reduction
Authors: Haas Rainer , Aşan Hakan , Doğan Onur , Michalek Claus Rainer , Karaca Akkan Özlem , Bulut Zeki Atıl
Published: July 2022

Consumers are responsible for almost 50 percent of food waste. Consumer-focused interventions are crucial to achieve many Sustainable Development Goals (SDGs), especially SDG 12.3. There are many factors that cause food waste, and these can be prevented by changing the consumption behavior of adults. Mobile apps are seen as promising tools to change consumer behavior for ensuring more sustainable food consumption. This study describes the development process and examines the perceived quality of MySusCof, an app intended to reduce the food waste of consumers. The uMARS scale was used for collecting data from consumers. Within the scope of the study, two studies were conducted to examine the development process of the application and to determine the user reactions to the mobile application. Results show that gamification elements with hedonic and social components, as well as functional aspects, are important features for user engagement and perceived impact. The qualitative results also supported the user experience in both hedonic and functional value and role of mobile apps to lead behavior change. This study serves as a guideline for future developers of mobile apps intended to lead consumers to a more sustainable food consumption.