bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Analysis of Self-Collected Nasal and Oral Swabs for Detection of SARS-CoV-2
Authors: Lim Ho-Jae , Baek Young-Hyun , Park Min-Young , Yang Jae-Hyun , Kim Min-Jin , Sung Nackmoon , Sohn Yong-Hak , Lee Sun-Hwa , Park Jung-Eun , Yang Yong-Jin
Published: September 2022

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third highly pathogenic human coronavirus and is rapidly transmitted by infected individuals regardless of their symptoms. During the COVID-19 pandemic, owing to the dearth of skilled healthcare workers (HCWs) to collect samples for early diagnosis, self-collection emerged as a viable alternative. To evaluate the reliability of self-collection, we compared the virus detection rate using 3990 self-collected swabs and HCW-collected swabs, procured from the same individuals and collected immediately after the self-collection. The results of multiplex reverse-transcription quantitative polymerase chain reaction revealed that the viral load in the HCW-collected swabs was marginally (18.4–28.8 times) higher than that in self-collected swabs. Self-collection showed no significant difference in sensitivity and specificity from HCW-collection (κ = 0.87, McNemar’s test; p = 0.19), indicating a comparable performance. These findings suggest that self-collected swabs are acceptable substitutes for HCW-collected swabs, and that their use improved the specimen screening efficiency and reduced the risk of SARS-CoV-2 infection among HCWs during and after the COVID-19 pandemic.
Effects of Multibracket Orthodontic Treatment versus Clear Aligners on Periodontal Health: An Integrative Review
Authors: Partouche Aaron Jacob David , Castro Filipe , Baptista Ana Sofia , Costa Liliana Gavinha , Fernandes Juliana Campos Hasse , Fernandes Gustavo Vicentis de Oliveira
Published: September 2022

Objective: This integrative review aimed to identify studies comparing the periodontal health in patients wearing multibracket orthodontic appliances and clear aligners. Materials and methods: An integrative literature search was performed through different databases, PubMed/Medline, PMC, and the Cochrane Library. This work was submitted to a search strategy following the PICO method and included the focus question: “Could the chosen orthodontic appliance change significantly the oral hygiene of the patient, impairing the periodontal health?” This work included analytical and controlled studies on humans published between 2005 and 2020, in the English language, establishing a comparison of the periodontal status in patients undergoing orthodontic multibracket and clear aligners therapies. The main periodontal indexes assessed were plaque index (PI), pocket depth (PD), gingival index (GI), and bleeding on probing (BoP). Results: The electronic research displayed 386 articles on PMC, 106 on PubMed, and 40 on the Cochrane Library. After removal, just 25 articles were selected for full-text screening, but just eight studies were eligible for this integrative review. It was enumerated that 204 patients were treated with aligners and 294 with multibracket orthodontic appliances, mainly elastomeric ligated brackets. Only the plaque index displayed a significant difference between the two groups and general data obtained showed a better control for periodontal health in the clear aligners. Limitations such as age, malocclusion severity, therapeutic choice, and different time measure was observed. In addition, the oral hygiene instruction and follow-up by a professional were different, and the role of malocclusion was not present in the studies. Conclusions: Within the limitations of this study, better results for periodontal health were found in the clear aligners. Therefore, more studies are necessary to affirm that aligners are synonymous with better gingival conditions in comparison with multibracket appliances. Other variables such as oral hygiene instructions, motivation, and supportive treatment tend to be more prevalent than the type of appliance itself in the periodontal evaluation.
UAS Hyperspatial LiDAR Data Performance in Delineation and Classification across a Gradient of Wetland Types
Authors: Pricope Narcisa Gabriela , Minei Asami , Halls Joanne Nancie , Chen Cuixian , Wang Yishi
Published: September 2022

Wetlands play a critical role in maintaining stable and productive ecosystems, and they continue to be at heightened risk from anthropogenic and natural degradation, especially along the rapidly developing Atlantic Coastal Plain of North America. As such, strategies to develop up-to-date and high-resolution wetland inventories and classifications remain highly relevant in the context of accelerating sea-level rise and coastal changes. Historically, satellite and airborne remote sensing data along with traditional field-based methods have been used for wetland delineation, yet, more recently, the advent of Uncrewed Aerial Systems (UAS) platforms and sensors is opening new avenues of performing rapid and accurate wetland classifications. To test the relative advantages and limitations of UAS technologies for wetland mapping and classification, we developed wetland classification models using UAS-collected multispectral and UAS-collected light detection and ranging (LiDAR) data relative to airborne-derived LiDAR models of wetland types ranging from palustrine to estuarine. The models were parameterized through a pixel-based random forest algorithm to evaluate model performance systematically and establish variable importance for a suite of variables including topographic, hydrologic, and vegetation-based indices. Based on our experimental results, the average overall classification accuracy and kappa coefficients for the UAS LiDAR-derived models are 75.29% and 0.74, respectively, compared to 79.80% and 0.75 for the airborne LiDAR-derived models, with significant differences in the spatial representation of final wetland classes. The resulting classification maps for the UAS models capture more precise wetland delineations than those of airborne models when trained with ground reference data collected at the same time as the UAS flights. The similar accuracy between the airborne and UAS models suggest that the UAS LiDAR is comparable to the airborne LiDAR. However, given poor revisit time of the airborne surveys and the high spatial resolution and precision of the UAS data, UAS-collected LiDAR provides excellent complementary data to statewide airborne missions or for specific applications that require hyperspatial data. For more structurally complex wetland types (such as the palustrine scrub shrub), UAS hyperspatial LiDAR data performs better and is much more advantageous to use in delineation and classification models. The results of this study contribute towards enhancing wetland delineation and classification models using data collected from multiple UAS platforms.
Divergence-Based Locally Weighted Ensemble Clustering with Dictionary Learning and L2,1-Norm
Authors: Xu Jiaxuan , Wu Jiang , Li Taiyong , Nan Yang
Published: September 2022

Accurate clustering is a challenging task with unlabeled data. Ensemble clustering aims to combine sets of base clusterings to obtain a better and more stable clustering and has shown its ability to improve clustering accuracy. Dense representation ensemble clustering (DREC) and entropy-based locally weighted ensemble clustering (ELWEC) are two typical methods for ensemble clustering. However, DREC treats each microcluster equally and hence, ignores the differences between each microcluster, while ELWEC conducts clustering on clusters rather than microclusters and ignores the sample–cluster relationship. To address these issues, a divergence-based locally weighted ensemble clustering with dictionary learning (DLWECDL) is proposed in this paper. Specifically, the DLWECDL consists of four phases. First, the clusters from the base clustering are used to generate microclusters. Second, a Kullback–Leibler divergence-based ensemble-driven cluster index is used to measure the weight of each microcluster. With these weights, an ensemble clustering algorithm with dictionary learning and the L2,1-norm is employed in the third phase. Meanwhile, the objective function is resolved by optimizing four subproblems and a similarity matrix is learned. Finally, a normalized cut (Ncut) is used to partition the similarity matrix and the ensemble clustering results are obtained. In this study, the proposed DLWECDL was validated on 20 widely used datasets and compared to some other state-of-the-art ensemble clustering methods. The experimental results demonstrated that the proposed DLWECDL is a very promising method for ensemble clustering.
Application of a Gas-Kinetic BGK Scheme in Thermal Protection System Analysis for Hypersonic Vehicles
Authors: Zhou Di , Du Bingchen , Guo Tongqing , Li Qiaozhong , Lu Zhiliang
Published: September 2022

One major problem in the development of hypersonic vehicles is severe aerodynamic heating; thus, the implementation of a thermal protection system is required. A numerical investigation on the reduction of aerodynamic heating using different thermal protection systems is conducted using a novel gas-kinetic BGK scheme. This method adopts a different solution strategy from the conventional computational fluid dynamics technique, and has shown a lot of benefits in the simulation of hypersonic flows. To be specific, it is established based on solving the Boltzmann equation, and the obtained gas distribution function is used to reconstruct the macroscopic solution of the flow field. Within the finite volume framework, the present BGK scheme is specially designed for the evaluation of numerical fluxes across the cell interface. Two typical thermal protection systems are investigated by using spikes and opposing jets, separately. Both their effectiveness and mechanisms to protect the body surface from heating are analyzed. The predicted distributions of pressure and heat flux, and the unique flow characteristics brought by spikes of different shapes or opposing jets of different total pressure ratios all verify the reliability and accuracy of the BGK scheme in the thermal protection system analysis.
Building Primary Preservice Teachers’ Identity as Engineering Educators
Authors: Lux Nicholas , Hammack Rebekah , Wiehe Blake , Gannon Paul
Published: September 2022

The purpose of this qualitative case study was to investigate how two primary preservice teachers built their engineering education identities during a clinical field experience that emphasized engineering education. More specifically, we explored the development of their engineering education identities while facing unforeseen circumstances and unfamiliar engineering content. We used a nested qualitative case study approach that was bounded by a university practicum field experience that took place at the height of the COVID-19 pandemic. Data sources included preservice teacher interviews and reflective field notes. We found that the preservice teachers faced a series of contextual factors in the clinical experience that both afforded and constrained professional learning opportunities that influenced their identity development. The affordances made professional learning opportunities possible, while the constraints limited professional growth. We also found that it was the negotiation of the factors, where the preservice teachers worked to mitigate the effect of the constraints while maximizing the advantages of the affordances, that had the greatest influence on their engineering pedagogical knowledge and engineering teaching self-efficacy. Findings from this study could provide teacher educators with insight into preparing primary teachers for unexpected challenges when teaching engineering, as well as how to best prepare engineering-efficacious teachers.
Adaptive Knowledge Control in Digital Learning as a Factor in Improving the Quality of Education
Authors: Bystrenina Irina , Nikitin Petr
Published: September 2022

The quality of knowledge is the most important task of the learning system at any level and stage of education. The COVID-19 pandemic has made its own adjustments to the process of organizing education, requiring the transition from traditional to distance learning as soon as possible. In the new conditions, the use of adaptive knowledge control has become relevant, taking into account the individual level of knowledge of the trainees. The study is devoted to the analysis of the features of adaptive testing, the conditions of application and the possibilities of web technologies for its organization. The article presents the results of a study aimed at organizing and conducting adaptive knowledge control as one of the means of implementing an individual learning trajectory. The study presents algorithms for constructing an individual trajectory of adaptive testing for each user. The analysis of web technologies and learning management systems that are currently used in terms of their capabilities for the implementation of the adaptive learning module is carried out. An adaptive testing module has been developed for implementation into the LMS Moodle learning management system, built taking into account the modular organization of the system. The construction of the module is based on a Markov random process with discrete states, continuous and discrete time, which makes it possible to implement a condition for completing testing with the function of viewing detailed statistics of its passage. The problem of developing and implementing an adaptive testing module in an online learning system is considered. The results of experimental work confirming the effectiveness of the implementation of the adaptive testing module are presented. The study of technology by future teachers and its application in practice will contribute to an increasingly widespread implementation in practical activities.
Interactive Mobile Home Tasks vs. Individual Home Tasks in University Foreign Language Education at the Upper-Intermediate Level
Authors: Borzova Elena , Shemanaeva Maria
Published: September 2022

Homework, being an indispensable part of learning, needs special planning and modification in line with the latest educational development. In this view, we assume that mobile devices can provide ample opportunities for students to interact and collaborate with their group-mates to enhance learning outcomes in university foreign language education. Interactive mobile homework assignments combined with individual ones can noticeably improve these outcomes from different perspectives. They engage students in communicative foreign language usage, encouraging both receptive and productive speech acts, student-to-student cooperation in learning through communication, peer-teaching, and pooling resources which promote the amplification of the learning environment through content and language sharing. On the other hand, interactive mobile homework assignments also have certain risks that may decrease the quality of learning, such as possible error exchange, a superficial approach, a switch to use of native language, and chatting, etc. Nevertheless, interactive mobile homework assignments keep students on the task for a longer period of time because they require each student’s pre-task preparation, longer oral exchanges during the “while phase” and post-task individual summary, therefore providing more practice. The study described in the article highlights the characteristics of the interactive mobile homework tasks, suggests a list of homework task types, both individual and interactive, and compares the results of their practical application in university foreign language education. The authors attempt to identify a trend in their contribution to the learning outcomes achieved by the students while completing their homework, either interactively or individually.
Topic Evolution in the Research on Educational Gamification
Authors: Swacha Jakub
Published: September 2022

The research on educational gamification spans many topics of interest. As the total volume of research in this area has greatly increased in the last 10 years, it is interesting to see how the interest in the respective topics has changed over the same period. In this paper, we answer this question by means of keyword analysis performed on 7572 unique keywords extracted from 2203 papers. The obtained results reveal (1) the high popularity of keywords that are non-obviously relevant to gamification, (2) vast disproportions in the volume of research dedicated to different aspects of the same research sub-area, and (3) differing patterns of popularity among the most frequent keywords, as well as (4) keywords introduced and abandoned in recent years. The presented findings bear a number of implications for the future of research on educational gamification.
Extended State Observer Based-Backstepping Control for Virtual Synchronous Generator
Authors: Haroon Shamseldeen Ismail Abdallah , Qian Jing , Zeng Yun , Zou Yidong , Tian Danning
Published: September 2022

The penetration of distributed generators (DGs)-based power electronic devices leads to low inertia and damping properties of the modern power grid. As a result, the system becomes more susceptible to disruption and instability, particularly when the power demand changes during critical loads or the system needs to switch from standalone to a grid-connected operation mode or vice versa. Developing a robust controller to deal with these transient cases is a real challenge. The inverter control method via the virtual synchronous generator (VSG) control method is a better way to supply the system’s inertia and damping features to boost system stability. Therefore, a nonlinear control strategy for VSG with uncertain disturbance is proposed in this paper to enhance the system stability in the islanded, grid-connected, and transition modes. Firstly, the mechanical equations for a VSG’s rotor, which include virtual inertia and damping coefficient, are presented, and the matching mathematical model is produced. Then, the nonlinear backstepping controller (BSC) method combined with the extended state observer (ESO) is constructed to compensate for the uncertainty. The Lyapunov criteria were used to prove the method’s stability. Considering the issue of uncertain items, a second-order ESO is built to estimate uncertainty and external disruption. Finally, the suggested control strategy is validated through three simulation experiments; the findings reveal that the proposed control method has an excellent performance with fast response and tracking under various operating situations.
A New Compact Method Based on a Convolutional Neural Network for Classification and Validation of Tomato Plant Disease
Authors: Wagle Shivali Amit , R Harikrishnan , Varadarajan Vijayakumar , Kotecha Ketan
Published: September 2022

With recent advancements in the classification methods of various domains, deep learning has shown remarkable results over traditional neural networks. A compact convolutional neural network (CNN) model with reduced computational complexity that performs equally well compared to the pretrained ResNet-101 model was developed. This three-layer CNN model was developed for plant leaf classification in this work. The classification of disease in tomato plant leaf images of the healthy and disease classes from the PlantVillage (PV) database is discussed in this work. Further, it supports validating the models with the images taken at “Krishi Vigyan Kendra Narayangaon (KVKN),” Pune, India. The disease categories were chosen based on their prevalence in Indian states. The proposed approach presents a performance improvement concerning other state-of-the-art methods; it achieved classification accuracies of 99.13%, 99.51%, and 99.40% with N1, N2, and N3 models, respectively, on the PV dataset. Experimental results demonstrate the validity of the proposed approach under complex background conditions. For the images captured at KVKN for predicting tomato plant leaf disease, the validation accuracy was 100% for the N1 model, 98.44% for the N2 model, and 96% for the N3 model. The training time for the developed N2 model was reduced by 89% compared to the ResNet-101 model. The models developed are smaller, more efficient, and less time-complex. The performance of the developed model will help us to take a significant step towards managing the infected plants. This will help farmers and contribute to sustainable agriculture.
Density-Dependent Effects on Pulse Compression in GaN Photodetectors Probed by Monte Carlo Studies
Authors: Milestone William J. , Nikishin Sergey A. , Joshi R. P.
Published: September 2022

With increases in the demand for faster electronic switching, requirements for higher operating voltages and currents, and the need to perform under harsh environments while operating at even higher frequencies, the research focus in photoconductive semiconductor switch (PCSS) technology has shifted to wide bandgap semiconductors. Here, we examine the possibility of pulse compression in carbon-doped PCSS devices based on the negative differential mobility concept for faster operation. Monte Carlo simulations are used to build in and model various effects on electron transport including degeneracy, charge polarization, and scattering within a three-valley model fitted to bandstructure calculations. The focus is on exploring the density dependence of pulse compression. Thresholds for the biasing fields naturally emerge. Predictive analysis of the output full-width half-maximum (FWHM) current waveforms, as well as the dynamics of the internal charge cloud behavior, and occupancy of the various valleys within GaN are all obtained. Our results show that an increase in carrier density can increase pulse compression and create pulse-widths that are smaller than the FWHM of the input optical excitation. This bodes well for enhanced repetition rates. Variations produced by moving the laser spot along the GaN PCSS length are also examined. Though data for GaN are not yet available, the trends compare well qualitatively with previous reports for GaAs.
Power-Hardware-in-the-Loop for Stator Windings Asymmetry Fault Analysis in Direct-Drive PMSG-Based Wind Turbines
Authors: Yousefzadeh Meysam , Hedayati Kia Shahin , Hoseintabar Marzebali Mohammad , Arab Khaburi Davood , Razik Hubert
Published: September 2022

This article studies the stator windings asymmetry fault in direct-drive permanent magnet synchronous generator(PMSG)-based wind turbines (WTs), having passive converters at the generator side, through developing a power-hardware-in-the-loop (P-H-i-L) system. It is based on a digital real-time simulation (DRTS) of turbine blades, a wind generator in the abc reference frame, and a three-phase diode rectifier mathematical models. The DC voltage, provided by the model of the three-phase diode rectifier, is linked to a one-level hardware boost converter by using a programmable DC power supply. Furthermore, the maximum power point tracking technique, based on the optimal torque, is evaluated when the one-level boost converter supplies a resistive load. Stator windings asymmetry fault in the PMSG is identified by analyzing the rectifier output voltage, the rotor speed, and the electrical signatures of the boost converter. It shows that this kind of fault clearly gives rise to the amplitudes of both 2·fs and 4·fs frequency components in the mentioned signatures, where fs is the main frequency component of the stator current. DRTSs are compared with digital offline simulations (DoSs), based on a Matlab/Simulink Simscape physical model, to demonstrate the efficacy of the proposed framework.
High-Voltage Power Supply for High Repetitive Rate Marx Generator with Quasi-Resonant Zero-Current Switching Transistor Control Algorithm
Authors: Pachowicz Krzysztof
Published: September 2022

Due to having a number of advantages, Marx generators are still the most widely used devices for generating high-voltage pulses in many fields of science and technology. To ensure their proper operation, especially when the generation of many frequent, highly repetitive pulses is required, a highly efficient high-voltage power supply is needed. The paper describes a specially developed power supply (input voltage 48 V DC, output voltage up to 50 kV) based on the conventional Full Bridge topology with two high-frequency high-voltage transformers and a 6-stage voltage multiplier. In order to avoid many problems caused by low coupling between primary and secondary windings of the transformers and the large parasitic capacitances of the secondary windings, a special quasi-resonant zero-current switching transistor control algorithm with variable switching frequency (dependent on output load) was developed. In the described method, the energy is supplied to the transformer in short pulses, when a pair of diagonal transistors of the full-bridge converter were turned on. Then, the freewheeling state is maintained until all of the energy stored in the leakage inductance of the transformer has been transferred to the secondary side, which means that the current in the primary windings drops to zero. This approach reduces energy losses, electromagnetic disturbances and prevents current distortion in primary winding.
Application of Straw and Biopreparations as a Sustainable Method for Increasing the Organic Carbon Content and Chemical, Physical, and Biological Soil Properties in Spring Barley Culture
Authors: Kanarek Piotr , Breza-Boruta Barbara , Bauza-Kaszewska Justyna , Lamparski Robert
Published: September 2022

Increasing climate change, through its impact on the economy, results in measures to reduce its negative effects. In agriculture, the expected positive effects may come from the implementation of practices with high carbon sequestration potential (e.g., straw incorporation). The idea of using straw as an energy feedstock requires an in-depth analysis of the impact of this practice on the organic carbon content of arable soils. Straw incorporation combined with the use of biopreparations can provide an attractive alternative to conventional fertilization and plant protection systems. This study aimed to assess the effect of straw, effective microorganisms preparation, and biostimulant on the physicochemical and biological soil parameters. The analyses included organic carbon, available P, K, and Mg, total and mineral nitrogen content, pH, bulk density, soil penetration resistance, and the number of soil-culturable heterotrophic bacteria, actinobacteria, and fungi determination. It was found that straw and EM addition resulted in the highest SOC content. Statistically lower values of bulk density and soil penetration resistance were also observed after straw incorporation. The results of our research revealed that, while the addition of straw beneficially affects soil quality, the impact of biopreparations application on soil parameters varies depending on the experimental combination used.
Change of Fossil-Fuel-Related Carbon Productivity Index of the Main Manufacturing Sectors in Poland
Authors: Dominiak Adam , Rusowicz Artur
Published: September 2022

The article presents the global characteristics of the Polish manufacturing industry and the structure of its energy consumption and carbon dioxide emissions related to direct emission as a result of fuel combustion and indirect emission as a result of electricity consumption. The share of individual sectors in energy consumption and emission levels was determined, and the changes in this share over the last 20 years were determined. A method for determining the carbon productivity index for the emissions of individual industries with the use of global macroeconomic indicators was proposed. The index allows for the comparison of the productivity of individual industries, regardless of the nature of production. The change in carbon productivity in Polish industry over time was presented. On this basis, it was assessed which industries are particularly promising in terms of decarbonising the Polish industry.
Smarter Together: Monitoring and Evaluation of Integrated Building Solutions for Low-Energy Districts of Lighthouse Cities Lyon, Munich, and Vienna
Authors: Hainoun Ali , Neumann Hans-Martin , Morishita-Steffen Naomi , Mougeot Baptiste , Vignali Étienne , Mandel Florian , Hörmann Felix , Stortecky Sebastian , Walter Katharina , Kaltenhauser-Barth Martin , Schnabl Bojan , Hartmann Stephan , Valentin Maxime , Gaiddon Bruno , Martin Samuel , Rozel Benoit
Published: September 2022

The Smarter Together project implemented in the three lighthouse cities (LHCs) of Lyon, Munich, and Vienna a set of co-created and integrated smart solutions for a better life in urban districts. The implemented solutions have been monitored using a novel integrated monitoring methodology (IMM) following a co-creation process involving key stakeholders of the LHCs. With focus on holistic building refurbishment and the integration of onsite renewable energy supply (RES), the three LHCs refurbished around 117,497 m2 of floor area and constructed 12,446 m2 of new floor area. They implemented around 833 kWp of PV, 35 kW of solar thermal and 13,122 kW of geothermal heating systems. Altogether, the realized solutions for low-energy districts in the three LHCs will annually save around 4000 MWh/a, generate 1145 MWh/a of RES and reduce around 1496 tCO2/a of CO2 emissions, corresponding to specific values of 37.6 kWh/m2.a and 11.9 kg-CO2/m2.a for final energy saving and CO2 emission reductions, respectively. KPI-based monitoring and evaluation of the implemented solutions provides qualitative and quantitative insight, experience and lessons learned to optimize the process of implementation and deployment of integrated solutions for holistic building refurbishment, and thus contribute to advancing sustainable urban transformation at the district level for both LHCs and FCs.
PHM SURVEY: Implementation of Prognostic Methods for Monitoring Industrial Systems
Authors: Soualhi Abdenour , Lamraoui Mourad , Elyousfi Bilal , Razik Hubert
Published: September 2022

Prognostics and Health Management (commonly called PHM) is a field that focuses on the degradation mechanisms of systems in order to estimate their health status, anticipate their failure and optimize their maintenance. PHM uses methods, tools and algorithms for monitoring, anomaly detection, cause diagnosis, prognosis of the remaining useful life (RUL) and maintenance optimization. It allows for permanently monitoring the health of the system and provides operators and managers with relevant information to decide on actions to be taken to maintain the system in optimal operational conditions. This paper aims to present the emergence of the PHM thematically to describe the subjacent processes, particularly prognosis, how it supplies the different maintenance strategies and to explain the benefits that can be anticipated. More specifically, this paper establishes a state of the art in prognostic methods used today in the PHM strategy. In addition, this paper shows the multitude of possible prognostic approaches and the choice of one among them that will help to provide a framework for industrial companies.
Civic Energy in an Orchard Farm–Prosumer and Energy Cooperative—A New Approach to Electricity Generation
Authors: Łakomiak Aleksandra
Published: September 2022

In Poland, electricity production is based on nonrenewable energy sources. The energy market is dominated by corporations. Rising electricity prices and threats of power shortages have become, among others, prerequisites for the development of distributed sources based on renewable sources, primarily using photovoltaic panels. The development of the renewable energy market is slow due to the lack of legal solutions and insufficient state support. Polish farmers, especially fruit growers, whose electricity consumption costs are a significant item in production costs, may become part of the energy sector by building a local energy system. In 2022, Poland introduced two new legal regulations, which currently provide three options for obtaining electricity using renewable micro-installations. The conducted study aimed at indicating which of the legally permitted option is the most advantageous for fruit farms in Poland. Growers can produce energy by being a prosumer who settles accounts in the net-metering and net-billing system and by participating in an energy cooperative. The direction of changes was ascertained by conducting a pilot study among fruit growers. The study used real quantitative and valuable data on the consumption and costs of electricity in 2012–2022 and the production of photovoltaic panels in a fruit farm in 2021. The study consisted of comparing three models of settling accounts for electricity with two comparative models in two scenarios. The analysis of prosumers’ functioning showed that the situation in Poland is favorable for the development of civic energy. However, participation in an energy cooperative with new legal solutions will not always be the more advantageous solution in terms of economy and energy. In particular, the study showed that the support mechanism needs further changes. The results of the research confirm the existing potential of fruit farms, which can be developed in the area of securing energy needs. The results of this research can be used as the premise for introducing changes to the legal conditions for the establishment and operation of energy cooperatives in Poland.
Deep Reinforcement Learning-Based Approach for Autonomous Power Flow Control Using Only Topology Changes
Authors: Damjanović Ivana , Pavić Ivica , Puljiz Mate , Brcic Mario
Published: September 2022

With the increasing complexity of power system structures and the increasing penetration of renewable energy, driven primarily by the need for decarbonization, power system operation and control become challenging. Changes are resulting in an enormous increase in system complexity, wherein the number of active control points in the grid is too high to be managed manually and provide an opportunity for the application of artificial intelligence technology in the power system. For power flow control, many studies have focused on using generation redispatching, load shedding, or demand side management flexibilities. This paper presents a novel reinforcement learning (RL)-based approach for the secure operation of power system via autonomous topology changes considering various constraints. The proposed agent learns from scratch to master power flow control purely from data. It can make autonomous topology changes according to current system conditions to support grid operators in making effective preventive control actions. The state-of-the-art RL algorithm—namely, dueling double deep Q-network with prioritized replay—is adopted to train effective agent for achieving the desired performance. The IEEE 14-bus system is selected to demonstrate the effectiveness and promising performance of the proposed agent controlling power network for up to a month with only nine actions affecting substation configuration.
Wastewater as a Renewable Energy Source—Utilisation of Microbial Fuel Cell Technology
Authors: Toczyłowska-Mamińska Renata , Mamiński Mariusz Ł.
Published: September 2022

An underappreciated source of renewable energy is wastewater, both municipal and industrial, with global production exceeding 900 km3 a year. Wastewater is currently perceived as a waste that needs to be treated via energy-consuming processes. However, in the current environmental nexus, traditional wastewater treatment uses 1700–5100 TWh of energy on a global scale. The application of modern and innovative treatment techniques, such as microbial fuel cells (MFC), would allow the conversion of wastewater’s chemical energy into electricity without external energy input. It has been demonstrated that the chemically bound energy in globally produced wastewater exceeds 2.5 × 104 TWh, which is sufficient to meet Europe’s annual energy demand. The aim of this paper is to answer the following questions. How much energy is bound in municipal and industrial wastewaters? How much of that energy can be extracted? What benefits will result from alternative techniques of waste treatment? The main finding of this report is that currently achieved energy recovery efficiencies with the use of microbial fuel cells technology can save about 20% of the chemical energy bound in wastewater, which is 5000 TWh on a global scale. The recovery of energy from wastewater via MFC technology can reach as much as 15% of global energy demands.
The Regulation of the Spanish Electricity Sector: A Long Way to Convergence
Authors: Garrués-Irurzun Josean
Published: September 2022

The regulation of the electricity sector, in general and in the particular case of Spain, has been brilliantly analysed by economists and contemporary jurists placing the emphasis, preferably, on economic efficiency and social justice. This article, based on the writings of economic historians in recent years, has as its objective to shed light on the logic to regulatory changes in Spain. Exactly as has been done for other countries, the explanation of factors and of the characteristics of this regulatory change, without doubt, will contribute to the understanding of its special nature within the overall international panorama, as well as a better understanding of the contributions of other previous and future works from different perspectives of analysis. The conclusions on the historical construction of the regulation of the electricity industry until the twentieth century allow us to define four big stages, deeply conditioned by their political regimes and the economic circumstances of the country, as well as by the unequal importance of economic agents in the taking of decisions: powerful energy companies, weak governments, and a complete lack of consumer input.
Terrestrial Water Storage Dynamics: Different Roles of Climate Variability, Vegetation Change, and Human Activities across Climate Zones in China
Authors: Deng Shiyu , Zhang Mingfang , Hou Yiping , Wang Hongyun , Yu Enxu , Xu Yali
Published: September 2022

Understanding terrestrial water storage (TWS) dynamics and associated drivers (e.g., climate variability, vegetation change, and human activities) across climate zones is essential for designing water resources management strategies in a changing environment. This study estimated TWS anomalies (TWSAs) based on the corrected Gravity Recovery and Climate Experiment (GRACE) gravity satellite data and derived driving factors for 214 watersheds across six climate zones in China. We evaluated the long-term trends and stationarities of TWSAs from 2004 to 2014 using the Mann–Kendall trend test and Augmented Dickey-Fuller stationarity test, respectively, and identified the key driving factors for TWSAs using the partial correlation analysis. The results indicated that increased TWSAs were observed in watersheds in tropical and subtropical climate zones, while decreased TWSAs were found in alpine and warm temperate watersheds. For tropical watersheds, increases in TWS were caused by increasing water conservation capacity as a result of large-scale plantations and the implementation of natural forest protection programs. For subtropical watersheds, TWS increments were driven by increasing precipitation and forestation. The decreasing tendency in TWS in warm temperate watersheds was related to intensive human activities. In the cold temperate zone, increased precipitation and soil moisture resulting from accelerated and advanced melting of frozen soils outweigh the above-ground evapotranspiration losses, which consequently led to the upward tendency in TWS in some watersheds (e.g., Xiaoxing’anling mountains). In the alpine climate zone, significant declines in TWS were caused by declined precipitation and soil moisture and increased evapotranspiration and glacier retreats due to global warming, as well as increased agriculture activities. These findings can provide critical scientific evidence and guidance for policymakers to design adaptive strategies and plans for watershed-scale water resources and forest management in different climate zones.
Streptomyces sp. ADR1, Strain Producing β- and γ-Rubromycin Antibiotics, Isolated from Algerian Sahara Desert
Authors: Boumehira Ali Zineddine , Kirby Bronywn , Trindade Marla , Hacène Hocine , Park Enoch Y. , El Enshasy Hesham A.
Published: September 2022

A Gram-positive strain, ADR1, was isolated from soil collected from the Algerian Sahara Desert. The ethyl acetate extract of the fermentation broth showed cytotoxic activity against the PANC-1 cell line (37.1 ± 1.3% viability when applied at a concentration of 100 µg/mL). Fractionation and NMR analysis of two peaks absorbing at 490 nm revealed that they represented β- and γ-rubromycin, anticancer antibiotic compounds. The ADR1 strain contained LL-diaminopimelic acid in the whole-cell hydrolysate, and the partial 16S ribosomal RNA gene sequence (1392 bp, Accession No. KF947515) showed 99% sequence similarity to Streptomyces species. Therefore, the name Streptomyces sp. ADR1 was proposed and deposited in the Wellness Industries Culture Collection (WICC) of the Institute of Bioproduct Development, UTM, Malaysia, under the number (WICC- B86). In a 16 L stirred-tank bioreactor, the stain was adapted to submerged culture conditions and produced rubromycins at a relatively high concentration, with maximums of 24.58 mg/L and 356 mg/L for β- and γ-rubromycins, respectively.
Numerical Study of Mid-IR Ultrashort Pulse Reconstruction Based on Processing of Spectra Converted in Chalcogenide Fibers with High Kerr Nonlinearity
Authors: Sorokin Arseny A. , Andrianov Alexey V. , Anashkina Elena A.
Published: September 2022

Ultrashort optical pulses play an important role in fundamental research and applications. It is important to have reliable information about pulse parameters such as duration, intensity profile, and phase. Numerous methods for characterizing pulses in the near-IR range have been well developed by now. However, there is a challenge with pulse measurement in the mid-IR, which is largely related to the underdeveloped component base in this spectral range. We investigate by means of numerical simulations a simple method of pulse reconstruction applicable in the mid-IR. The method is based on measuring and processing only the initial pulse spectrum and two converted spectra in elements with Kerr nonlinearity for different B-integrals characterizing nonlinear phase accumulation. The hardware implementation of the proposed method is very simple. This method requires only a one-dimensional data set, has no moving parts in the optical scheme, and allows for working with high-energy as well as low-energy pulses. We propose a novel simple, efficient, noise-tolerant algorithm for data processing that assumes spectral phase approximation by a polynomial function. We demonstrate numerically the reconstruction of mid-IR ultrashort pulses, namely 3 μm wavelength pulses, using commercial chalcogenide As2S3-based glass fibers as nonlinear elements.
Water Hardness Alters the Gene Expression Response and Copper Toxicity in Daphnia magna
Authors: Chupani Latifeh , Sjöberg Viktor , Jass Jana , Olsson Per-Erik
Published: September 2022

The influence of water hardness on copper (Cu) toxicity in Daphnia magna was studied using gene expression analysis. Exposing D. magna to Cu in water with increasing levels of hardness decreased the acute toxicity. Hardness did not affect the predicted Cu complexation. After 24 h, D. magna showed an increased level of genes related to metal homeostasis (mt) following exposure to 25 μg Cu/L in hard water. Daphnids in soft and medium water responded to 25 μg Cu/L by upregulation of antioxidant defense and mt genes, revealing oxidative stress as a mechanism of Cu toxicity in D. magna. D. magna exposed to 25 μg Cu/L in soft water did not survive for 96 h. In contrast, those exposed to 25 μg Cu/L in medium and hard water survived for 96 h with significantly higher levels of mt genes. The genes related to oxidative damage (heat shock protein and glutathione S-transferase) in these groups did not deviate from control levels, indicating the protective effect of hardness. Metallothionein genes were upregulated at 17 μg Cu/L at both 24 h and 96 h. The expression of catalase and ferritin increased in this group in soft and hard water at 96 h. The protective effect of hardness (in the tested range) on survival was also observed at a concentration of 25 μg/L. The results suggest metallothionein (A and B), catalase, and ferritin genes, as potential biomarkers for copper exposure in D. magna regardless of hardness.
Risk Assessment of (Herbal) Teas Containing Pyrrolizidine Alkaloids (PAs) Based on Margin of Exposure Approach and Relative Potency (REP) Factors
Authors: Chen Lu , Zhang Qian , Yi Ziwei , Chen Yu , Xiao Weihan , Su Dan , Shi Wenbiao
Published: September 2022

Pyrrolizidine alkaloids (PAs) present distinct toxicity potencies depending on their metabolites and in vivo toxicokinetics. To represent the potency differences of various PAs, the interim relative potency (REP) factors have been derived. However, little is known about the risk assessment for (herbal) teas when taking REP factors into account. In this study, a set of 68 individual 1,2-unsaturated PA in 21 types of (herbal) teas was analyzed using LC-MS/MS. The REP factors for these PAs were applied on the PA levels. The margin of exposure (MOE) approach was employed to assess the risks of the exposure to PAs due to consumption of (herbal) teas. The results show that the total PA levels ranged from 13.4 to 286,682.2 μg/kg d.m., which were decreased by REP correction in most of the teas. The MOE values for tephroseris, borage and lemon balm (melissa) tea based on REP-corrected PA levels were below 10,000, assuming daily consumption of one cup of tea during a lifetime, indicating that consuming these teas may raise a concern. Our study also indicates a priority for risk management for tephroseris tea, as having nephrosis tea for more than 11.2 weeks during a 75-year lifetime would result in an MOE of 10,000.
Three-Dimensional Printing Properties of Polysaccharide Hydrocolloids–Unrinsed Sturgeon Surimi Complex Hydrogels
Authors: Liu Kang , Zhao Nana , Xiang Chenxi , Li Yujin , Jiang Xiaoming , Zeng Mingyong , Xu He , Wang Haiyan , Wu Haohao , Yu Xiaoqing , Zhao Yuanhui
Published: September 2022

Herein, the microstructure and mechanical properties of hydrogels consisting of unrinsed sturgeon surimi (URSS) and plant-derived polysaccharides such as κ-carrageenan (KC), konjac gum (KG), xanthan gum (XG), guar gum (GG) and sodium alginate (SA), were studied by texture analysis, rheological measurement and scanning electron microscopy (SEM). Rheological results showed that the apparent viscosity, storage modulus (G′) and loss modulus (G″) of URSS increased by addition of KC, KG, GG and SA. The gel strength of resultant surimi products fabricated with KG/URSS mixture was significantly higher than that of other groups. KG could significantly improve the hardness (44.14 ± 1.14 N), chewiness (160.34 ± 8.33 mJ) and cohesiveness (0.56 ± 0.02) of the unrinsed surimi gel. Adding SA and KC had no significant effect on the textural characteristics of printed gels. However, an apparent decrease in the relevant mechanical properties of printed hydrogels was observed when XG and GG were added into surimi. SEM indicated that the incorporation of KG and KC could further integrate the gel structure of URSS as compared to hindering the cross-linking of surimi protein by XG and GG, which were in accordance with gel strength and water-holding capacity. These results provided useful information to regulate the 3D printing performance in functionalized surimi-based material.