bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Biodiversity of a European NATURA 2000 Mediterranean Lagoon through eDNA Metabarcoding
Authors: Specchia Valeria , Saccomanno Benedetta , Zangaro Francesco , Tzafesta Eftychia , Pinna Maurizio
Published: November 2022

Coastal lagoons are considered important habitats both for ecological functions and biodiversity worldwide. Thus, they provide relevant ecosystem services and valuable natural resources. However, coastal lagoons are highly susceptible to anthropogenic pressures that can cause biodiversity losses and require specific biomonitoring programs as well as management measures. In this research, we applied environmental DNA (eDNA) metabarcoding to investigate the biodiversity of a poorly known Mediterranean lagoon included in the European Natura 2000 Network. We used the cytochrome oxidase I (COI) gene marker to capture the entire biodiversity of this highly diversified aquatic coastal environment. With a low sampling effort and rapid laboratory practices, a large amount of valuable biodiversity data was generated and analyzed. Interestingly, this straightforward and broad molecular surveying of biodiversity unveiled a wide variety of taxonomic groups, such as benthic macroinvertebrates, zooplankton, phytoplankton, and macroalgae, which are frequently used as ecological indicators. We were able to detect species that were previously morphologically identified, as well as species never identified before. This research underlines the validity of eDNA metabarcoding in assessing the biodiversity in a poorly known and protected Mediterranean lagoon ecosystem, as well as in identifying the early warnings of environmental stressors. Finally, the research highlights the need to investigate multiple target genes and primers set for a larger analysis of specific species.
BCNet: A Deep Learning Computer-Aided Diagnosis Framework for Human Peripheral Blood Cell Identification
Authors: Chola Channabasava , Muaad Abdullah Y. , Bin Heyat Md Belal , Benifa J. V. Bibal , Naji Wadeea R. , Hemachandran K. , Mahmoud Noha F. , Samee Nagwan Abdel , Al-Antari Mugahed A. , Kadah Yasser M. , Kim Tae-Seong
Published: November 2022

Blood cells carry important information that can be used to represent a person’s current state of health. The identification of different types of blood cells in a timely and precise manner is essential to cutting the infection risks that people face on a daily basis. The BCNet is an artificial intelligence (AI)-based deep learning (DL) framework that was proposed based on the capability of transfer learning with a convolutional neural network to rapidly and automatically identify the blood cells in an eight-class identification scenario: Basophil, Eosinophil, Erythroblast, Immature Granulocytes, Lymphocyte, Monocyte, Neutrophil, and Platelet. For the purpose of establishing the dependability and viability of BCNet, exhaustive experiments consisting of five-fold cross-validation tests are carried out. Using the transfer learning strategy, we conducted in-depth comprehensive experiments on the proposed BCNet’s architecture and test it with three optimizers of ADAM, RMSprop (RMSP), and stochastic gradient descent (SGD). Meanwhile, the performance of the proposed BCNet is directly compared using the same dataset with the state-of-the-art deep learning models of DensNet, ResNet, Inception, and MobileNet. When employing the different optimizers, the BCNet framework demonstrated better classification performance with ADAM and RMSP optimizers. The best evaluation performance was achieved using the RMSP optimizer in terms of 98.51% accuracy and 96.24% F1-score. Compared with the baseline model, the BCNet clearly improved the prediction accuracy performance 1.94%, 3.33%, and 1.65% using the optimizers of ADAM, RMSP, and SGD, respectively. The proposed BCNet model outperformed the AI models of DenseNet, ResNet, Inception, and MobileNet in terms of the testing time of a single blood cell image by 10.98, 4.26, 2.03, and 0.21 msec. In comparison to the most recent deep learning models, the BCNet model could be able to generate encouraging outcomes. It is essential for the advancement of healthcare facilities to have such a recognition rate improving the detection performance of the blood cells.
Over-the-Counter Breast Cancer Classification Using Machine Learning and Patient Registration Records
Authors: Hanis Tengku Muhammad , Ruhaiyem Nur Intan Raihana , Arifin Wan Nor , Haron Juhara , Wan Abdul Rahman Wan Faiziah , Abdullah Rosni , Musa Kamarul Imran
Published: November 2022

This study aims to determine the feasibility of machine learning (ML) and patient registration record to be utilised to develop an over-the-counter (OTC) screening model for breast cancer risk estimation. Data were retrospectively collected from women who came to the Hospital Universiti Sains Malaysia, Malaysia for breast-related problems. Eight ML models were used: k-nearest neighbour (kNN), elastic-net logistic regression, multivariate adaptive regression splines, artificial neural network, partial least square, random forest, support vector machine (SVM), and extreme gradient boosting. Features utilised for the development of the screening models were limited to information in the patient registration form. The final model was evaluated in terms of performance across a mammographic density. Additionally, the feature importance of the final model was assessed using the model agnostic approach. kNN had the highest Youden J index, precision, and PR-AUC, while SVM had the highest F2 score. The kNN model was selected as the final model. The model had a balanced performance in terms of sensitivity, specificity, and PR-AUC across the mammographic density groups. The most important feature was the age at examination. In conclusion, this study showed that ML and patient registration information are feasible to be used as the OTC screening model for breast cancer.
Appendiceal Mucinous Tumor Presenting as Recurrent Bowel Obstruction
Authors: Lin Wei-Tang , Wang Yen-Hsiang , Chen Wei-Yu , Lao Wilson T.
Published: November 2022

Appendiceal mucinous tumors are rare, with variable malignant potential, and they are usually found incidentally. Clinical symptoms are nonspecific. Rarely, appendiceal mucinous neoplasm causes bowel obstruction and makes diagnosis more difficult. We present a case of an 84-year-old female who came to our emergency department having had abdominal fullness and constipation for 5 days. Ileus, due to an affected adhesion band, was diagnosed initially, and symptoms improved gradually under conservative treatment. However, 3 months later she presented to the emergency department again with abdominal pain and distension; small bowel obstruction due to adhesion was again diagnosed. Recurrent bowel obstruction prompted emergent surgery. Operative findings showed a whitish appendiceal tumor adhering to and directly invading the adjacent ileum, with a segment of herniated small bowel wedged in between, causing the obstruction. Upon reviewing the initial computed tomography scan, the dilated tubular structure of appendiceal tumor was misrecognized as small bowel loop; there was no surrounding inflammatory sign, leading to diagnosis difficulty. Instead of a common cause of bowel obstruction, such as adhesion band, this case revealed bowel obstruction can be caused by the direct invasion of an appendiceal tumor. Awareness of this condition with careful image evaluation of small bowel obstruction is essential for diagnosis.
Epicardial Adipose Tissue Thickness Is Related to Plaque Composition in Coronary Artery Disease
Authors: Park Soon Sang , Jung Jisung , Mintz Gary S. , Jin Uram , Park Jin-Sun , Park Bumhee , Shin Han-Bit , Seo Kyoung-Woo , Yang Hyoung-Mo , Lim Hong-Seok , Choi Byoung-Joo , Yoon Myeong-Ho , Shin Joon-Han , Tahk Seung-Jea , Choi So-Yeon
Published: November 2022

(1) Background: Currently, limited data are available regarding the relationship between epicardial fat and plaque composition. The aim of this study was to assess the relationship between visceral fat surrounding the heart and the lipid core burden in patients with coronary artery diseases; (2) Methods: Overall, 331 patients undergoing coronary angiography with combined near-infrared spectroscopy and intravascular ultrasound imaging were evaluated for epicardial adipose tissue (EAT) thickness using transthoracic echocardiography. Patients were divided into thick EAT and thin EAT groups according to the median value; (3) Results: There was a positive correlation between EAT thickness and maxLCBI4mm, and maxLCBI4mm was significantly higher in the thick EAT group compared to the thin EAT group (437 vs. 293, p < 0.001). EAT thickness was an independent predictor of maxLCBI4mm ≥ 400 along with age, low-density lipoprotein-cholesterol level, acute coronary syndrome presentation, and plaque burden in a multiple linear regression model. Receiver operating characteristic curve analysis showed that EAT thickness was a predictor for maxLCBI4mm ≥ 400; (4) Conclusions: In the present study, EAT thickness is related to the lipid core burden assessed by NIRS-IVUS in patients with CAD which suggests that EAT may affect the stability of the plaques in coronary arteries.
Functional Gastrointestinal Diseases and Dietary Practices among Pakistani Children—A Schools Based Cross-Sectional Study
Authors: Malik Zoha Imtiaz , Umer Muhammad Farooq , Ali Khizar Nabeel , Kawish Ayesha Babar , Arshed Muhammad , Zofeen Shumaila , Farid Awais
Published: November 2022

Background: Functional gastrointestinal diseases (FGIDs) are an important yet highly under explored area among public health issues. FGIDs’ complex etiology makes them of interest along with their prevalence in children steadily increasing, especially in the developing world. We aimed to determine the burden FGIDs pose on school-going children, and to determine its association with the dietary intake patterns in Pakistani children. Methodology: The study included 385 school-children from public and private schools in Pakistan through multistage random sampling, from March to August 2022. We used the Food Frequency Questionnaire (FFQ) and Rome IV Criteria for a comprehensive exploration of the issue. Associations between the FGIDs and dietary factors were analyzed using chi-square and Fischer’s exact tests in SPSS version 26.0. Results: Females constituted 77.4% (n = 298) of all respondents, while 44.9% (n = 173) of the total reported a family history of gastrointestinal diseases. FFQ analysis showed varying consumption frequencies for different food groups. Functional abdominal pain and irritable bowel syndrome (IBS) were the highest reported FGIDs with a prevalence of 38.7% (n = 149) and 24.9% (n = 96), respectively. Statistical associations were found between different FGIDs and gender, age, household income, family members, and dietary variables such as fruit, vegetable, beverage and pulse consumption. Conclusion: FGIDs were found to be associated with a number of socio-demographic and dietary factors which calls for small scale and large scale attention to the issue. Results from the current study and further studies may help develop guidelines to manage these disorders in Pakistan.
Complexity Science in Human Change: Research, Models, Clinical Applications
Authors: Orsucci Franco , Tschacher Wolfgang
Published: November 2022

Complexity and entropy prevail in human behavior and social interaction because the systems underlying behavior and interaction are, without a doubt, highly complex [...]
A New Exergy Disaggregation Approach for Complexity Reduction and Dissipative Equipment Isolation in Thermoeconomics
Authors: dos Santos Rodrigo Guedes , Lourenço Atilio Barbosa , de Faria Pedro Rosseto , Barone Marcelo Aiolfi , Santos José Joaquim Conceição Soares
Published: November 2022

Thermoeconomics connects thermodynamic and economic concepts in order to provide information not available in conventional energy and economic analysis. Most thermoeconomicists agree that exergy is the most appropriate thermodynamic magnitude to associate with cost. In some applications, exergy disaggregation is required. Despite the improvement in result accuracy, the modeling complexity increases. In recent years, different exergy disaggregation approaches have been proposed, mostly to deal with dissipative components and residues, despite all of them also increasing the complexity of thermoeconomics. This study aims to present a new thermoeconomic approach based on exergy disaggregation, which is able to isolate dissipative components with less modeling complexity. This approach, called the A&F Model, splits the physical exergy into two terms, namely, Helmholtz energy and flow work. These terms were evaluated from a thermoeconomic point of view, through a cost allocation in an ideal Carnot cycle, and they were also applied and compared with the UFS Model, through a cost allocation analysis, in a case study with an organic Rankine cycle-powered vapor compression refrigeration system. The complexity and computational effort reduction in the A&F are significantly less than in the UFS Model. This alternative approach yields consistent results.
Flexible Temperature Control Solution for Integrated Circuits Testing—Silicon Creations Thermal Elephant
Authors: Laczewski Andrzej , Kasiński Krzysztof
Published: November 2022

Both scientific and industrial applications require temperature stabilization and enforcement for testing purposes. In this study, we present a solution capable of handling socket-based IC test systems enabling packages from QFN up to FCBGA, or even COB solutions. The temperature range covers the full-range industrial temperature range (−40 °C to +125 °C). The extended temperature range of −55 °C to +150 °C is conditionally possible. Solution supports dry-air installation, safety mechanisms and flexible thermal head assemblies. We present the key features and architecture of the solution named “Thermal Elephant” that found applications in the industrial (characterization of the IP hard macros) and scientific applications (radiation imaging ICs).
Identification of the Strategy of the Energy and Utilities Sector from the G7 Group Countries, from the Perspective of a Dominant Strategy Approach
Authors: Niemczyk Jerzy , Borowski Kamil , Trzaska Rafał , Trzaska Mateusz , Sus Aleksandra , Matuszewski Maciej
Published: November 2022

The aim of the research, the effect of which is this article, is to identify the hierarchy of selected approaches to building a strategy in companies from the sector of Energy and Utilities included in seven stock market indexes of the G7 countries The obtained results are related to the isolation of cognitive knowledge about the preferred approaches to the strategy in energy companies currently undergoing intensive changes and that are listed in the stock indexes of the G7 countries. The Authors proved that the strategy implementation in companies representing Energy and Utilities sectors is mainly based on the resource approach. Moreover, such an approach is supported by the classic tools of the positional school, resulting in shaping the competitive position in the sector of differentiating the Chamberlin’s rent.
Development of Future Compact and Eco-Friendly HVDC Gas Insulated Systems: Test Verification of Shape-Optimized DC Spacer Models
Authors: Li Haoluan , Zebouchi Nabila , Haddad Manu , Reid Alistair , Ekkel Egbert
Published: November 2022

Spacers for the HVDC GIS/GIL play an important role in mechanically supporting conductors and separating compartments. At the same time, their insulation performance affects the stability and safety of system operation. Design rules and knowledge specific to AC spacers do not apply to those of DC spacers. Considering the shape influence on the surface electric field intensity of the spacer under HVDC applied voltage, as determined in our previous work, an optimized shape of a spacer model based on finite element electric field calculations and using standard HVAC alumina filled epoxy material and two novel types of materials were studied. The simulation’s results show that the DC shape optimization of the spacers can effectively reduce the electric field magnitudes along the spacer under different temperature gradients. To verify practically these findings, this paper presents the reduced scale gas insulated prototype that was constructed, the optimized DC spacers that were fabricated and the DC testing results using SF6-free surrounding gas: C4-Perfluoronitrile (C4-PFN, 3MTM NovecTM 4710)/CO2 and Trifluoroiodomethane (CF3I)/CO2. The results show that the shape-optimized spacer models made of conventional HVAC filled epoxy material have successfully passed the tests up to the maximum applicable ±123 kV DC exceeding thus ±119 kV DC that corresponds to the nominal voltage ±500 kV DC of the full scale.
Forecasting Short-Term Electricity Load Using Validated Ensemble Learning
Authors: Sankalpa Chatum , Kittipiyakul Somsak , Laitrakun Seksan
Published: November 2022

As short-term load forecasting is essential for the day-to-day operation planning of power systems, we built an ensemble learning model to perform such forecasting for Thai data. The proposed model uses voting regression (VR), producing forecasts with weighted averages of forecasts from five individual models: three parametric multiple linear regressors and two non-parametric machine-learning models. The regressors are linear regression models with gradient-descent (LR), ordinary least-squares (OLS) estimators, and generalized least-squares auto-regression (GLSAR) models. In contrast, the machine-learning models are decision trees (DT) and random forests (RF). To select the best model variables and hyper-parameters, we used cross-validation (CV) performance instead of the test data performance, which yielded overly good test performance. We compared various validation schemes and found that the Blocked-CV scheme gives the validation error closest to the test error. Using Blocked-CV, the test results show that the VR model outperforms all its individual predictors.
Thermal Energy Storage in Concentrating Solar Power Plants: A Review of European and North American R&D Projects
Authors: Pascual Sara , Lisbona Pilar , Romeo Luis M.
Published: November 2022

Thermal energy storage (TES) is the most suitable solution found to improve the concentrating solar power (CSP) plant’s dispatchability. Molten salts used as sensible heat storage (SHS) are the most widespread TES medium. However, novel and promising TES materials can be implemented into CSP plants within different configurations, minimizing the TES costs and increasing the working temperature to improve the thermal performance of the associated power block. The first objective of this review is to provide an overview of the most widespread CSP technologies, TES technologies and TES-CSP configurations within the currently operational facilities. Once this information has been compiled, the second aim is to collect and present the existing European and North American TES-CSP Research and Development (R&D) projects within the last decade (2011–2021). Data related to these projects such as TES-CSP configuration path, TES and CSP technologies applied, storage capacity, power block associated and the levelized cost of electricity (LCOE) of the commercial up-scaling project are presented. In addition, project information such as location, research period, project leader and budget granted are also extracted. A timeline of the R&D projects launched from 2011 is built, showing the technology readiness level (TRL) achieved by the end of the project.
Surveying Dewatered Areas in the Fish Spawning Sites during Short-Term Drawdown Operations: Case Study of a Large Hydropower Plant Reservoir in the Lowland Area, Lithuania
Authors: Jurevičius Linas , Punys Petras , Kasiulis Egidijus , Šilinis Linas
Published: November 2022

This paper presents research on the dewatering areas during drawdown operations in the Kaunas Hydropower Plant (HPP) reservoir situated in the lowland area of Lithuania. It is a multipurpose reservoir primarily used for power generation by two large hydropower plants. Because of the HPP peaking operation and the reservoir morphology—a shallow, gently sloping littoral zone—significant dewatered areas can occur (during drawdown operations). This is especially dangerous during the fish spawning period. Therefore, reservoir operation rules are in force that limit operation of the HPPs and secure other reservoir stakeholder needs. There is a lack of knowledge about the fish spawning locations, how they are changing, and what areas are dewatered at different stages of HPP operation. This knowledge is crucial for decision making and efficient water resources management in order to increase power generation and protect the environment at the same time. A detailed survey of an area containing several potential spawning grounds (about 5 ha) was conducted to track changes in the dewatering areas. The aim of the study is to investigate different surveying methods, gather knowledge about potential fish spawning sites, and investigate the dewatered areas that occur during water level (WL) fluctuations. The methodology and insights of this study can be used in similar lowland countries to assist in improving the usage of water resources while increasing power generation.
Numerical Investigation and Performance Enhancement by Means of Geometric Sensitivity Analysis and Parametric Tuning of a Radial-Outflow High-Pressure Oil–Gas Turbine
Authors: Song Peng , Wang Shengyuan , Sun Jinju
Published: November 2022

The pressure at the natural gas wellhead typically ranges from tens to hundreds of atmospheres. Traditionally, the wellhead pressure must be throttled into a low level to satisfy the requirement of gathering pipelines, in which a large amount of pressure energy is wasted. The high-pressure oil–gas turbine is a promising approach to convert the wellhead pressure energy into shaft power or electricity. In this paper, a numerical investigation is conducted on a radial-outflow high-pressure oil–gas turbine utilized in a wellhead pressure power generation system. Using the self-defined real oil–gas physical properties and Computational Fluid Dynamics (CFD), the internal flow and performance of the high-pressure oil–gas turbine under complex operating conditions are investigated. To improve the turbine flow and performance, a Latin Hypercube Sampling-based parametric tuning is performed on the stator and rotor blade geometries. The application of such an approach effectively adjusts the flow matching and eliminates the flow separation, by which the turbine performance is significantly enhanced.
A Virtual Inertia Method for Stability Control of DC Distribution Systems with Parallel Converters
Authors: Gao Qun , Jiang Yan , Peng Ke , Liu Lei
Published: November 2022

DC distribution systems are a typical power electronic system with low inertia, low-rotational kinetic energy, and poor antidisturbance capability when loads fluctuate or parameters change. In this paper, a virtual inertia control with an additional first-order filtering link is proposed on the basis of P-Udc droop control. The results of the simulations and experiments verify that the additional inertia control reduces the voltage change rate and improves the system inertia by adjusting the virtual capacitance value on the DC side of the converter, which can achieve a smoother and more accurate voltage control and suppress the continuous voltage oscillation.
Hydrodynamic Response and Tension Leg Failure Performance Analysis of Floating Offshore Wind Turbine with Inclined Tension Legs
Authors: Jia Zhaolin , Wu Han , Chen Hao , Li Wei , Li Xinyi , Lian Jijian , He Shuaiqi , Zhang Xiaoxu , Zhao Qixiang
Published: November 2022

The tension legs are the essential parts of the tension legs platform-type (TLP-type) floating offshore wind turbine (FOWT) against the extra buoyancy of FOWT. Therefore, the TLP-type FOWT will face the risk of tension leg failure. However, there are seldom analyses on the hydrodynamic response and tension leg failure performance of FOWT with inclined tension legs. In this paper, a hydrodynamic model was established using three-dimensional hydrodynamic theory and applied in the motion response and tension analyses of FOWT with conventional and new tension leg arrangements on Moses. The influence of draft and tension leg arrangement on the performance of FOWT with inclined tension legs were studied. The optimum draft was the height of the column and lower tensions were obtained for the new tension leg arrangement. Moreover, the tension leg failure performance of FOWT with inclined tension legs was evaluated under different failure conditions. The results illustrated that the FOWT with the new tension leg arrangement can still operate safely after one tension leg fails.
Condition Forecasting of a Power Transformer Based on an Online Monitor with EL-CSO-ANN
Authors: Fan Jingmin , Shao Huidong , Cao Yunfei , Feng Lutao , Chen Jianpei , Meng Anbo , Yin Hao
Published: November 2022

Power transformers are vital to the power grid and discovering the latent faults in advance is helpful for avoiding serious problems. This study addressed the problem of forecasting and diagnosing the faults of power transformers with small dissolved gas analysis (DGA) data samples that arise from faults in transformers with low occurrence rates. First, an online monitor that was developed in our previous work was applied to obtain the DGA data. Second, the ensemble learning (EL) of a bagging algorithm with bootstrap resampling was used to deal with small training samples. Finally, a criss-cross-optimized neural network (i.e., CSO-NN) was applied to the short-term prediction of the DGA data, based on which the transformer status could be forecasted. The case studies showed that the proposed EL-CSO-NN algorithm integrated into the monitor was capable of achieving satisfactory classification and prediction accuracy for transformer fault forecasting.
Ensemble-Based Flow Field Estimation Using the Dynamic Wind Farm Model FLORIDyn
Authors: Becker Marcus , Allaerts Dries , van Wingerden Jan-Willem
Published: November 2022

Wind farm control methods allow for a more flexible use of wind power plants over the baseline operation. They can be used to increase the power generated, to track a reference power signal or to reduce structural loads on a farm-wide level. Model-based control strategies have the advantage that prior knowledge can be included, for instance by simulating the current flow field state into the near future to take adequate control actions. This state needs to describe the real system as accurately as possible. This paper discusses what state estimation methods are suitable for wind farm flow field estimation and how they can be applied to the dynamic engineering model FLORIDyn. In particular, we derive an Ensemble Kalman Filter framework which can identify heterogeneous and changing wind speeds and wind directions across a wind farm. It does so based on the power generated by the turbines and wind direction measurements at the turbine locations. Next to the states, this framework quantifies uncertainty for the resulting state estimates. We also highlight challenges that arise when ensemble methods are applied to particle-based flow field simulations. The development of a flow field estimation framework for dynamic low-fidelity wind farm models is an essential step toward real-time dynamic model-based closed-loop wind farm control.
Impact of Climate Change and Technological Innovation on the Energy Performance and Built form of Future Cities
Authors: Ahmadian Ehsan , Bingham Chris , Elnokaly Amira , Sodagar Behzad , Verhaert Ivan
Published: November 2022

The building and transportation sectors are responsible for the greatest proportion of energy consumption in cities. While they are intrinsically interlinked with urban built form and density, climate change and technological innovation are having an effect on their relative contributions. This paper aims to develop an optimisation framework to facilitate the identification of the most energy-efficient urban built forms and urban geometry for the future built environment that can be adapted to the changing climate and ongoing technological development. It examines future scenarios for the city of London as a temperate climate zone (as a case study), in 2050, and contrasts it with the present situation. Specifically, the impact of climate change along with the penetration of electric vehicles into the transportation system that can be charged via rooftop photovoltaics is investigated. This study initially develops the geometrical models of four selected urban built forms and, secondly, analyzes their energy performance using an urban energy simulation software. The results, showing the impact of future scenarios on building energy performance, urban built form and density, demonstrate that court and tunnel-court built forms show better energy performance for future development. It is therefore recommended that for future urban developments in London, deep plan court and tunnel-court buildings with a lower number of storeys and a large cut-off angle are more advantageous in terms of building energy to accommodate the expected climate change. Finally, results of simulation trials indicate that the total building energy demand in 2050 is considerably higher than in the present climate as a result of additional cooling load and electric vehicle charging load.
Design and Simulation of a Highly Reliable Modular High-Power Current Source
Authors: Zhou Qing , Xu Yuelei , Qi Xin , Zhang Zhaoxiang
Published: November 2022

Currently, modularization, low complexity, and high performance are the three directions that high-power power supplies are gradually moving toward. Under the premise of determining the objective conditions such as operating environment and material technology, a significant task in power supply reliability design is to optimize the power supply’s structure, topology, and mode of operation. In this paper, we analyze the reliability design of parallel module redundancy in detail and design the overall structure of the power supply. To further improve the reliability of the power supply, methods for power reliability design at the leg level and component level are proposed. This paper verifies the correctness of the design through simulation and develops a N + 1 modular redundant power supply according to the design scheme. The simulation experiment verifies the consistency of the design scheme and parameters.
Uses of Superconducting Magnetic Energy Storage Systems in Microgrids under Unbalanced Inductive Loads and Partial Shading Conditions
Authors: Alkhafaji Ahmed Samawi , Trabelsi Hafedh
Published: November 2022

Superconducting magnetic energy storage (SMES) systems are characterized by their high-power density; they are integrated into high-energy density storage systems, such as batteries, to produce hybrid energy storage systems (HESSs), resulting in the increased performance of renewable energy sources (RESs). Incorporating RESs and HESS into a DC bus to obtain a DC microgrid concept is considered a more attractive option for solving system reliability and stability issues. In this paper, we focus on employing SMES systems based on their characteristics of a fast response and high efficiency, which contribute to increased battery lifespan, and reducing the mismatch between the energy supplied by the renewable energy source and the load demand by compensating for the effects of partial shading on the PV system on the DC bus side and the imbalance in loads on the other side of the AC bus. The incremental conductance algorithm (INC) is used for maximum power point tracking (MPPT) in the PV system. Fuzzy logic control (FLC) is proposed for the generation of control signals for the DC–DC chopper used to charge/discharge the SMES coil. Simulations using MATLAB/Simulink were then carried out to assess the proposed models of the (standalone and grid) connection systems.
On the Factors of Impact Pressure in Supercritical CO2 Phase-Transition Blasting—A Numerical Study
Authors: Pu Chao , Liu Zhenjian , Pu Ge
Published: November 2022

Carbon dioxide phase transition blasting (CO2-PB) technology is an effective and economical technology used for breaking rocks. The use of CO2-PB can significantly reduce the vibration damage to surrounding rocks. There is little research on the shockwave generated by the CO2-PB, and simulation can better show the flow field characteristics. In order to clarify the mechanism of its blasting load process, a theoretical analysis and a numerical model were developed to study the flow-field characteristics and the impact pressure of CO2-PB. Our results show that the CO2 absorbs heat from the surrounding environment, producing a significant low-temperature area. The overpressure is significantly lower than the driving gas pressure to the ambient pressure, limiting the maximum over-pressure that can be obtained. When the pressure in CO2-PB reaches 100 MPa, the shockwave is about 4.25 MPa. As the distance increases, the peak value of the shockwave decays rapidly. As the dimensionless distance increases from 1 to 5, the dimensionless overpressure decreases from 1 to 0.23. Under the same blasting pressure, increasing the filling pressure and increasing the filling volume slightly reduce the initial pressure of the shockwave. In the shock stage, strong compression is formed on the surface of the shockwave, resulting in a higher peak pressure value. Meanwhile, the stable pressure is influenced by the target distance, blasting pressure, and CO2-PB length.
Surrogate Model for Design Uncertainty Estimation of Nonlinear Electromagnetic Vibration Energy Harvester
Authors: Kulik Marcin , Gabor Rafał , Jagieła Mariusz
Published: November 2022

The paper proposes a solution to the problem of estimating the uncertainty of the output power with respect to the design parameters for an electromagnetic vibration energy harvesting converter. Due to costly utilisation of time-domain mathematical models involved in the procedure of determination of the average output power of the system, an algorithm for developing the surrogate model that enables rapid estimation of this quantity within the prescribed frequency band limits is proposed. As a result, the metamodel sensitive to the most impactful design parameters is developed using Kriging with successive refinement of the design grid for gaining the accuracy. Under operational conditions with a constant magnitude of the acceleration signal and the prescribed frequency band limits, the surrogate model enables evaluation of the average output power of the system at 105 design points in less than 2 s of computer execution time. The consistency and accuracy of the results obtained from the surrogate model is confirmed by comparison of selected results of computations with measurements carried out on the manufactured prototype. Based on the latter and the surrogate model, the confidence intervals for the design procedure were determined and the most important spread quantities were estimated, providing quantitative information on the accuracy of the design procedure developed for the considered system.
Wind Tunnel Study on the Tip Speed Ratio’s Impact on a Wind Turbine Wake Development
Authors: Neunaber Ingrid , Hölling Michael , Obligado Martin
Published: November 2022

We propose an experimental study on the influence of the tip speed ratio on the spatial development of a wind turbine wake. To accomplish this, a scaled wind turbine is tested in a wind tunnel, and its turbulent wake measured for streamwise distances between 1 and 30 diameters. Two different tip speed ratios (5.3 and 4.5) are tested by varying the pitch angle of the rotor blades between the optimal setting and one with an offset of +6∘. In addition, we test two Reynolds numbers for the optimal tip speed ratio, ReD=1.9×105 and ReD=2.9×105 (based on the turbine diameter and the freestream velocity). For all cases, the mean streamwise velocity deficit at the centerline evolves close to a power law in the far wake, and we check the validity of the Jensen and Bastankhah-Porté-Agel engineering wind turbine wake models and the Townsend-George wake model for free shear flows for this region. Lastly, we present radial profiles of the mean streamwise velocity and test different radial models. Our results show that the lateral profile of the wake is properly fitted by a super-Gaussian curve close to the rotor, while Gaussian-like profiles adapt better in the far wake.
Comparative Reliability Assessment of Hybrid Si/SiC and Conventional Si Power Module Based PV Inverter Considering Mission Profile of India and Denmark Locations
Authors: Kshatri Sainadh Singh , Dhillon Javed , Mishra Sachin , Haghighi Ali Torabi , Hunt Julian David , Patro Epari Ritesh
Published: November 2022

Energy harnessing from renewable energy sources has become more flexible with power electronic technologies. Recent advancements in power electronic technologies achieve converter efficiency higher than 98%. Today, reliable power electronic devices are needed to design a PV-based energy converter (inverter) to reduce the risk of failure and maintenance costs during operation. Wide-bandgap SiC devices are becoming more common in power electronic converters. These devices are designed to reduce switching loss and improve the efficiency of the system. Nevertheless, the cost of SiC devices is a major concern. Hence, to improve the reliability of the PV inverter while considering the economic aspects, this paper develops a highly reliable PV inverter with a hybrid Si/SiC power module that consists of a Si-IGBT with a SiC anti-parallel diode. A test case of a 3 kW PV inverter is considered for reliability analysis. The loading of the PV inverter is done under uncertain environmental conditions by considering the yearly Mission Profile (MP) data related to Ambient Temperature (AT) and Solar Irradiance (SI) at the India and Denmark locations. The effectiveness of the proposed hybrid Si/SiC power module is tested by comparing it with a conventional IGBT power module. The results showcase the marked improvement in PV inverter reliability with the proposed hybrid power module.
Application of Mobile Operators’ Data in Modern Geographical Research
Authors: Babkin Roman , Badina Svetlana , Bereznyatsky Alexander
Published: November 2022

Mobile operators’ data are one type of Big Data. These are any data about events related to the use of a mobile phone. These data include subscriber identifiers and associated time and location attributes. Big Data in general usually includes datasets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. Big Data can be described by the following key characteristics: volume, variety, velocity, veracity, value, variability etc. Mobile operators’ data are supplied by the Mobile Network Operators. The main distinguishing features of the operator are, firstly, the possession of a state license to use the radio frequency spectrum, and, secondly, the possession or control over the elements of the network infrastructure necessary to provide services to subscribers in the authorized radio frequency spectrum. The smallest structural territorial element for cellular communication systems is a cell; its dimensions can be different (250 by 250 m, 500 by 500 m, etc.).
How to Predict Premature Multiphase Steel Cracks during Edge Flangeability
Authors: Peres Lucas Salomao , Souza João Henrique C. , Batalha Gilmar Ferreira
Published: November 2022

The present paper makes a critical review based on the literature and presents examples of experiments developed by the authors, showing how the hole expansion ratio test (HERT) could be useful to understand and avoid premature cracks caused by flanging operations in sheet metal parts made of advanced high-strength steels. An approach based on damage theory was evaluated along with the mechanical tests necessary to understand the phenomenon, the influence of the trimming process, and the correlation between experimental mechanical testing and simulations. The procedures presented in this work allow for the prediction of edge cracks, often verified after flanging steps during the stamping process, allowing for reductions in tooling costs and setup loops.
Balsam Fir (Abies balsamea (L.) Mill.) Wood Quality after Defoliation by Spruce Budworm (Choristoneura fumiferana Clem.) in the Boreal Forest of Quebec, Canada
Authors: Lemay Audrey , Barrette Julie , Krause Cornelia
Published: November 2022

Eastern spruce budworm (Choristoneura fumiferana Clem.) is considered the most important disturbing insect in coniferous stands in eastern North America. During an outbreak, spruce budworm can cause severe defoliation in balsam fir (Abies balsamea (L.) Mill.), which can affect wood properties such as moisture content and mechanical properties. This project aimed to assess the influence of the duration of spruce budworm defoliation on the wood quality of mature balsam fir trees. To do this, we studied sapwood proportion, decay, moisture content, mechanical properties and tracheid dimensions in stands that had suffered three, four or five years of defoliation. We also compared living and dead balsam firs and evaluated the change in wood properties with time. Our results showed that dead balsam firs suffered from a loss of wood quality rapidly after their death, particularly in terms of moisture content and decay in the sapwood. Sapwood proportion was similar between living and dead trees, but the sapwood of dead trees contained more decay and had a lower moisture content than living trees. Mechanical properties and tracheid dimensions were 10% and 4% lower in dead trees than in living trees. We did not observe any major differences in wood properties between the three durations of defoliation, suggesting that wood degradation occurs before that. The study did not make it possible to determine the optimal duration of defoliation to harvest the stands.
The Influence of Urban Green Space Soundscape on the Changes of Citizens’ Emotion: A Case Study of Beijing Urban Parks
Authors: Zhou Yihui , Dai Ping , Zhao Zheng , Hao Chunxu , Wen Yali
Published: November 2022

Coronavirus disease 2019 has significantly impacted mental health. Urban green spaces’ ecological function can improve citizens’ well-being and mental health; thus, this study explored the value realisation mechanism of ecological products in green space by examining the impact of urban green space soundscape on citizens’ emotions. Additionally, we investigated citizens’ subjective perceptions and emotional changes in soundscape through questionnaires. An A-weighted sound pressure level meter was used to measure the sound pressure levels at three points in a day to obtain the sound pressure level changes during different day periods in a park. Subsequently, the universal conclusion through a comparative analysis of the sound pressure level change in urban parks during the day was roughly ‘M’ shape. Further, a structural equation model analysed the influence of different soundscape on public sentiment and used a multigroup analysis to examine the difference in the impact of natural sounds in summer and winter on the change in public opinion. The results show that natural and living sounds positively affect citizens’ emotions, whereas mechanical sounds negatively affect citizens’ emotions. Furthermore, natural sounds in summer positively affect citizens’ moods significantly. Conversely, natural sounds in winter negatively affect citizens’ attitudes, but this is not obvious. Finally, this study proposed some suggestions for managing and improving urban green space soundscape.
Management of Forest Residues as a Raw Material for the Production of Particleboards
Authors: Pędzik Marta , Tomczak Karol , Janiszewska-Latterini Dominika , Tomczak Arkadiusz , Rogoziński Tomasz
Published: November 2022

Expanding the base of raw materials for use in the production of wood-based materials, researchers and panel manufacturers around the world are increasingly trying to produce panel prototypes from raw materials available in a given area and climate, or by managing waste from wood industry processing. The aim of the study was therefore to test the hypothesis that forest residues de-rived from Scots pine roundwood harvesting have the same suitability for the production of three-layer particleboard as the wood of the most valuable part of the Scots pine stem, by comparing selected properties of raw wood material and final product—particleboard. Characterization of both the raw material and the physical-mechanical and hygienic properties of the produced panels was carried out. For these panels from the tree trunk, MOR was 14.6 N/mm2, MOE 1960 N/mm2 and IB 0.46 N/mm2. The MOR and IB values turned out to be higher for the panel from the branch and are 16.5 and 0.72 N/mm2, respectively. Excessive swelling of the panels resulted in all manufactured particleboards meeting the standardized performance requirements of EN 312 for interior furnishing panels (including furniture) for use in dry conditions (type P2).
Effects of Lactic Acid Bacteria Fermentation on Physicochemical Properties, Functional Compounds and Antioxidant Activity of Edible Grass
Authors: Li Xianxiu , He Tao , Mao Jianwei , Sha Ruyi
Published: November 2022

Fermented foods are known worldwide for their functional health properties. In order to promote the relative product development of edible grass, Lactobacillus plantarum (Lp) and Lactobacillus rhamnosus (Lr) were used to ferment edible grass in this study. Effects of fermentation using Lp and Lr in monoculture and binary mixture on physicochemical properties, the contents of functional compounds and the antioxidant activity of edible grass at different fermentation times were investigated by colorimetric method and high-performance liquid chromatography (HPLC). Results show that the pH value and total sugar content of the three fermented edible grasses at the 4th day were lower than those of unfermented water extract (defined as the control sample) and kept almost unchanged at the 7th day. The total polyphenol content and total flavonoid content of the three fermented edible grasses were lower than those of the control sample by the oxidation of phenolic compounds caused by polyphenol oxidases. The highest soluble protein content and superoxide dismutase (SOD) activity were found in the binary mixture of Lp and Lr fermentation at the 7th day, which were respectively 11 and 1.78 times higher than those of control sample. The oxalic acid content of all fermented edible grasses shows a significant decrease with increasing fermentation time, especially for the binary mixture at the 7th day, reaching only 24% of the control sample. However, the contents of lactic acid and succinic acid of the three fermented edible grasses were higher than those of the control sample because of the metabolism of the microorganism. Functional compounds including soluble protein, SOD, lactic acid and succinic acid played the main positive roles in antioxidation, while oxalic acid had a negative correlation with antioxidation. Therefore, the antioxidant activity of edible grass was dramatically enhanced by Lactobacillus strain fermentation.