bluuebunny/crossref_metadata_2025 huggingface dataset:
High Sensitivity C-Reactive Protein Increases the Risk of Carotid Plaque Instability in Male Dyslipidemic Patients
Authors: Scimeca Manuel , Montanaro Manuela , Cardellini Marina , Bonfiglio Rita , Anemona Lucia , Urbano Nicoletta , Bonanno Elena , Menghini Rossella , Casagrande Viviana , Martelli Eugenio , Servadei Francesca , Giacobbi Erica , Ippoliti Arnaldo , Bei Roberto , Manzari Vittorio , Federici Massimo , Schillaci Orazio , Mauriello Alessandro
Published: November 2021

Background: The aim of this study was to evaluate how the high sensitivity C-reactive protein (hs-CRP) values influence the risk of carotid plaque instability in association with other cardiovascular risk factors. Methods: One hundred and fifty-six carotid plaques from both symptomatic and asymptomatic patients requiring surgical carotid endarterectomy were retrospectively collected. According to the modified American Heart Association, atherosclerosis plaques have been histologically distinguished into unstable and stable. The following anamnestic and hematochemical data were also considered: age, gender, hypertension, diabetes mellitus, smoking habit, therapy, low-density lipoprotein (LDL)-C, kidney failure and hs-CRP. Results: The results of our study clearly show that high levels of hs-CRP significantly increase the carotid plaque instability in dyslipidemic patients. Specifically, a 67% increase of the risk of carotid plaque instability was observed in patients with high LDL-C. Therefore, the highest risk was observed in male dyslipidemic patients 2333 (95% CI 0.73–7.48) and in aged female patients 2713 (95% CI 0.14–53.27). Discussion: These data strongly suggest a biological relationship between the hs-CRP values and the alteration of lipidic metabolism mostly in male patients affected by carotid atherosclerosis. The measurement of hs-CRP might be useful as a potential screening tool in the prevention of atheroscletotic disease.
Automated Quantitative Lung CT Improves Prognostication in Non-ICU COVID-19 Patients beyond Conventional Biomarkers of Disease
Authors: Palumbo Pierpaolo , Palumbo Maria Michela , Bruno Federico , Picchi Giovanna , Iacopino Antonio , Acanfora Chiara , Sgalambro Ferruccio , Arrigoni Francesco , Ciccullo Arturo , Cosimini Benedetta , Splendiani Alessandra , Barile Antonio , Masedu Francesco , Grimaldi Alessandro , Di Cesare Ernesto , Masciocchi Carlo
Published: November 2021

(1) Background: COVID-19 continues to represent a worrying pandemic. Despite the high percentage of non-severe illness, a wide clinical variability is often reported in real-world practice. Accurate predictors of disease aggressiveness, however, are still lacking. The purpose of our study was to evaluate the impact of quantitative analysis of lung computed tomography (CT) on non-intensive care unit (ICU) COVID-19 patients’ prognostication; (2) Methods: Our historical prospective study included fifty-five COVID-19 patients consecutively submitted to unenhanced lung CT. Primary outcomes were recorded during hospitalization, including composite ICU admission for the need of mechanical ventilation and/or death occurrence. CT examinations were retrospectively evaluated to automatically calculate differently aerated lung tissues (i.e., overinflated, well-aerated, poorly aerated, and non-aerated tissue). Scores based on the percentage of lung weight and volume were also calculated; (3) Results: Patients who reported disease progression showed lower total lung volume. Inflammatory indices correlated with indices of respiratory failure and high-density areas. Moreover, non-aerated and poorly aerated lung tissue resulted significantly higher in patients with disease progression. Notably, non-aerated lung tissue was independently associated with disease progression (HR: 1.02; p-value: 0.046). When different predictive models including clinical, laboratoristic, and CT findings were analyzed, the best predictive validity was reached by the model that included non-aerated tissue (C-index: 0.97; p-value: 0.0001); (4) Conclusions: Quantitative lung CT offers wide advantages in COVID-19 disease stratification. Non-aerated lung tissue is more likely to occur with severe inflammation status, turning out to be a strong predictor for disease aggressiveness; therefore, it should be included in the predictive model of COVID-19 patients.
Socio-Organizational Impact of Confocal Laser Endomicroscopy in Neurosurgery and Neuropathology: Results from a Process Analysis and Expert Survey
Authors: Fotteler Marina L. , Liesche-Starnecker Friederike , Brielmaier Maria C. , Schobel Johannes , Gempt Jens , Schlegel Jürgen , Swoboda Walter
Published: November 2021

During brain tumor resection surgery, it is essential to determine the tumor borders as the extent of resection is important for post-operative patient survival. The current process of removing a tissue sample for frozen section analysis has several shortcomings that might be overcome by confocal laser endomicroscopy (CLE). CLE is a promising new technology enabling the digital in vivo visualization of tissue structures in near real-time. Research on the socio-organizational impact of introducing this new methodology to routine care in neurosurgery and neuropathology is scarce. We analyzed a potential clinical workflow employing CLE by comparing it to the current process. Additionally, a small expert survey was conducted to collect data on the opinion of clinical staff working with CLE. While CLE can contribute to a workload reduction for neuropathologists and enable a shorter process and a more efficient use of resources, the effort for neurosurgeons and surgery assistants might increase. Experts agree that CLE offers huge potential for better diagnosis and therapy but also see challenges, especially due to the current state of experimental use, including a risk for misinterpretations and the need for special training. Future studies will show whether CLE can become part of routine care.
The Importance of Using Physical Tridimensional Models for the Management and Planning of Extended Osseous Odontogenic Lesions
Authors: Guerra Domenico , Severino Marco , Caruso Sara , Rastelli Sofia , Gatto Roberto
Published: November 2021

(1) Surgical intervention becomes crucial in situations in which lack of action would cause a decrease in quality of life for the patient. As healthcare professionals, our next objective is to reduce patient fear perception. This work’s aim is to illustrate how physical tridimensional models can serve not only as confidence boosters for the patient, but also as a valid tool to aid both the clinician and the fostering of a patient–doctor relationship. (2) An example case managed using a stereolithographic model in the pre-surgical planning stage is presented in which surgical planning was carried out by analysis of radiographic investigations combined with a tridimensional resin model derived from the patient’s x-ray exam. (3) Successful enucleation, surgical debridement, and stable follow-up shows the effectiveness of the applied surgical protocol, confirming that planification using a physical representation of the tridimensional exam aids in the correct surgical management of said lesions. (4) The effectiveness o101f the surgical act itself as well as the follow-up showing ossification of the bony lesion and absence of relapse of a highly recurrent lesion confirms the effectiveness of the tools used for this surgical intervention.
A Quantum Blind Multi-Signature Method for the Industrial Blockchain
Authors: Cai Zhengying , Liu Shi , Han Zhangyi , Wang Rui , Huang Yuehua
Published: November 2021

Traditional anti-quantum methods and multi-signature technologies to secure the blockchain against quantum attacks will quickly reduce the efficiency and scalability of the industrial blockchain, where the computational resources will experience a polynomial rise with the increasing number of traders. Here, a quantum blind multi-signature method is proposed for the multi-party transaction to provide anti-quantum security. First, the proposed multi-party transaction frame and quantum key distribution in the industrial blockchain are introduced. It integrates a novel quantum blind multi-signature algorithm that is based on the quantum entanglement mechanism, and it is absolutely secure in theory. Second, the anti-quantum multi-signature algorithm is illustrated, where there are four phases, i.e., initialization, signing, verification, and implementation. Third, the security and complexity of the proposed framework are analyzed and compared with related methods in references, and our proposed method is verified to be able to offer good computational performance and blockchain scalability for multi-party transaction. Last, the paper is summarized and future research directions are proposed.
Customer-Based Brand Equity for a Tourism Destination: The Case of Croatia
Authors: Cervova Lenka , Vavrova Jitka
Published: November 2021

Tourism has been negatively impacted by the global COVID-19 pandemic, making it even more important for tourist destinations to focus on their brand equity from the perspective of their customers—visitors. The aim of this paper is therefore to verify and modify the model of customer-based brand equity for a tourism destination (CBBETD) and its attributes for the destination of Croatia from the perspective of Czech tourists, among whom primary research was conducted using the CAWI method (n = 451). The main CBBE dimensions were extracted using factor analysis and a model with four dimensions (awareness, image, quality and loyalty) was created. The identified attributes explain between 55% and 82% of the variability of a given dimension. Although the study’s results follow the published models of CBBETD, the attributes in each dimension and the subdimension in the image dimension reflect the specificities of the destination of Croatia. Thus, the results of this paper extend the economic theory with another model and are also applicable in the field of destination management.
The Dramatic Arc in the Development of Argumentation Skills of Upper Secondary School Students in Geography Education
Authors: Härmä Kimmo , Kärkkäinen Sirpa , Jeronen Eila
Published: November 2021

Geography education can facilitate learners’ critical thinking and argumentation skills to make well-reasoned decisions on social and environmental issues. This study reports on a geography course consisting of 18 lessons, each of them 75 min, designed to afford intensive practice in argumentation to upper secondary school students (n = 21) and following the dramatic arc. The study produces examples of different developmental pathways of upper secondary school students’ argumentation during the geography course. In this qualitative case study, the data were collected from learning diaries and analyzed using content analysis following ARRA-analysis (Analysis of Reasoning, Rhetorics and Argumentation), which is based on Toulmin’s argumentation model. The results indicated that most of the students developed justified arguments and composed clear claims and relevant rhetorical modes such as qualifications, rhetorical questions and rebuttals. Justification categories that were mainly used were backings, grounds and warrants. However, some students had difficulties in recognizing the main claim and arguments. The students developed their argumentation skills following the dramatic arc. They possessed the prerequisites for argumentative reasoning and writing but needed further practice in analytical and critical writing.
Beyond Content: The Role of STEM Disciplines, Real-World Problems, 21st Century Skills, and STEM Careers within Science Teachers’ Conceptions of Integrated STEM Education
Authors: Dare Emily Anna , Keratithamkul Khomson , Hiwatig Benny Mart , Li Feng
Published: November 2021

Understanding teachers’ conceptions surrounding integrated STEM education is vital to the successful implementation of integrated STEM curricula in K-12 classrooms. Of particular interest is understanding how teachers conceptualize the role of the STEM disciplines within their integrated STEM teaching. Further, despite knowing that content-agnostic characteristics of integrated STEM education are important, little is known about how teachers conceptualize the real-world problems, 21st century skills, and the promotion of STEM careers in their integrated STEM instruction. This study used an exploratory case study design to investigate conceptions of 19 K-12 science teachers after participating in an integrated STEM-focused professional development and implementing integrated STEM lessons into their classrooms. Our findings show that all teacher participants viewed STEM education from an integrative perspective that fosters the development of 21st century skills, using real-world problems to motivate students. Our findings also reveal that teachers have varying ideas related to the STEM disciplines within integrated STEM instruction, which could assist teacher educators in preparing high-quality professional development experiences. Findings related to real-world problems, 21st century skills, and STEM careers provide a window into how to best support teachers to include these characteristics into their teaching more explicitly.
Microwave Interferometric System for GPR Positioning
Authors: Miccinesi Lapo , Pieraccini Massimiliano , Lepri Chiara
Published: November 2021

Ground penetrating radar (GPR) systems are sensors that are able to acquire underground images by scanning the surface of the soil/pavement under investigation. Usually, a GPR system records its own position along the scan line, using a mechanical odometer, i.e., a rolling wheel in contact with the ground. This simple and cheap solution can be ineffective on uneven terrains. In this paper, a positioning system based on an interferometric radar is presented. This kind of radar is able to detect small displacements of the targets in its field of view. Such a capability was used to track the GPR position along a line. The system was validated with simulations and tested in a realistic experimental scenario.
Enhancement of Radar Detection Accuracy Using H-Beam Wave Polarization in Random Media
Authors: El-Ocla Hosam
Published: November 2021

This work addresses the range in which the accuracy of object identification is enhanced regardless of radar parameters. We compute the radar cross-section (RCS) of conducting objects in free space and random media. We use beam wave incidence and postulate its coherency with a finite width around an object located in the far field. Accordingly, we examine the impact of radar parameters on the RCS, where these parameters include the incident angle, target size and complexity, medium fluctuation intensity and the beam size of the incident waves. H-wave polarization is assumed for the waves’ incidence.
Broadband and Integratable 2 × 2 TWT Amplifier Unit for Millimeter Wave Phased Array Radar
Authors: Guo Guo , Yan Zhenlin , Sun Zhenzhen , Liu Jianwei , Yang Ruichao , Gong Yubin , Wei Yanyu
Published: November 2021

A novel power amplifier unit for a phased array radar with 2 × 2 output ports for a vacuum electron device is proposed. Double parallel connecting microstrip meander-lines are employed as the slow-wave circuits of a large power traveling wave tube operate in a Ka-band. The high frequency characteristics, the transmission characteristics, and the beam–wave interaction processes for this amplifier are simulated and optimized. For each output port of one channel, the simulation results reveal that the output power, saturated gain, and 3-dB bandwidth can reach 566 W, 27.5 dB, and 7 GHz, respectively. Additionally, the amplified signals of four output ports have favorable phase congruency. After fabrication and assembly, transmission tests for the 80-period model are performed preliminarily. The tested “cold” S-parameters match well with the simulated values. This type of integratable amplifier combined with a vacuum device has broad application prospects in the field of high power and broad bandwidth on a millimeter wave phased array radar.
Segmentation of Overlapping Grape Clusters Based on the Depth Region Growing Method
Authors: Peng Yun , Zhao Shengyi , Liu Jizhan
Published: November 2021

Accurately extracting the grape cluster at the front of overlapping grape clusters is the primary problem of the grape-harvesting robot. To solve the difficult problem of identifying and segmenting the overlapping grape clusters in the cultivation environment of a trellis, a simple method based on the deep learning network and the idea of region growing is proposed. Firstly, the region of grape in an RGB image was obtained by the finely trained DeepLabV3+ model. The idea of transfer learning was adopted when training the network with a limited number of training sets. Then, the corresponding region of the grape in the depth image captured by RealSense D435 was processed by the proposed depth region growing algorithm (DRG) to extract the front cluster. The depth region growing method uses the depth value instead of gray value to achieve clustering. Finally, it fils the holes in the clustered region of interest, extracts the contours, and maps the obtained contours to the RGB image. The images captured by RealSense D435 in a natural trellis environment were adopted to evaluate the performance of the proposed method. The experimental results showed that the recall and precision of the proposed method were 89.2% and 87.5%, respectively. The demonstrated performance indicated that the proposed method could satisfy the requirements of practical application for robotic grape harvesting.
Predictive Maintenance Neural Control Algorithm for Defect Detection of the Power Plants Rotating Machines Using Augmented Reality Goggles
Authors: Lalik Krzysztof , Wątorek Filip
Published: November 2021

The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user. The presented platform allows for the utilization of artificial intelligence to analyze vibrations generated by the rotary drive system to determine the technical condition of a wind turbine model monitored by an image processing system that measures frequencies generated by the machine.
Verification and Validation of Large Eddy Simulation for Tip Clearance Vortex Cavitating Flow in a Waterjet Pump
Authors: Han Chengzao , Long Yun , Xu Mohan , Ji Bin
Published: November 2021

In this paper, large eddy simulation (LES) was adopted to simulate the cavitating flow in a waterjet pump with emphasis on the tip clearance flow. The numerical results agree well with the experimental observations, which indicates that the LES method can make good predictions of the unsteady cavitating flows around a rotor blade. The LES verification and validation (LES V&V) analysis was used to reveal the influence of cavitation on the flow structures. It can be found that the LES errors in cavitating region are larger than those in the non-cavitating area, which is mainly caused by more complicated cavitating and tip clearance flow structures. Further analysis of the interaction between the cavitating and vortex flow by the relative vorticity transport equation shows that the stretching, dilatation and baroclinic torque terms have major effects on the generation and transport of vortex structure. Meanwhile the Coriolis force term and viscosity term also exacerbate the vorticity transport in the cavitating region. In addition, the flow loss characteristics of this pump are also revealed by the entropy production theory. It is indicated that the tip clearance flow and trailing edge wake flow cause the viscous dissipation and turbulent dissipation, and the cavitation can further enhance the instability of the flow field in the tip clearance.
Modeling Hydraulic Fracturing Using Natural Gas Foam as Fracturing Fluids
Authors: Zheng Shuang , Sharma Mukul M.
Published: November 2021

Stranded gas emission from the field production because of the limitations in the pipeline infrastructure has become one of the major contributors to the greenhouse effects. How to handle the stranded gas is a troublesome problem under the background of global “net-zero” emission efforts. On the other hand, the cost of water for hydraulic fracturing is high and water is not accessible in some areas. The idea of using stranded gas in replace of the water-based fracturing fluid can reduce the gas emission and the cost. This paper presents some novel numerical studies on the feasibility of using stranded natural gas as fracturing fluids. Differences in the fracture creating, proppant placement, and oil/gas/water flowback are compared between natural gas fracturing fluids and water-based fracturing fluids. A fully integrated equation of state compositional hydraulic fracturing and reservoir simulator is used in this paper. Public datasets for the Permian Basin rock and fluid properties and natural gas foam properties are collected to set up simulation cases. The reservoir hydrocarbon fluid and natural gas fracturing fluids phase behavior is modeled using the Peng-Robinson equation of state. The evolving of created fracture geometry, conductivity and flowback performance during the lifecycle of the well (injection, shut-in, and production) are analyzed for the gas and water fracturing fluids. Simulation results show that natural gas and foam fracturing fluids are better than water-based fracturing fluids in terms of lower breakdown pressure, lower water leakoff into the reservoir, and higher cluster efficiency. NG foams tend to create better propped fractures with shorter length and larger width, because of their high viscosity. NG foam is also found to create better stimulated rock volume (SRV) permeability, better fracturing fluid flowback with a large water usage reduction, and high natural gas consumption. The simulation results presented in this paper are helpful to the operators in reducing natural gas emission while reducing the cost of hydraulic fracturing operation.
Inspection Robotic UGV Platform and the Procedure for an Acoustic Signal-Based Fault Detection in Belt Conveyor Idler
Authors: Shiri Hamid , Wodecki Jacek , Ziętek Bartłomiej , Zimroz Radosław
Published: November 2021

Belt conveyors are commonly used for the transportation of bulk materials. The most characteristic design feature is the fact that thousands of idlers are supporting the moving belt. One of the critical elements of the idler is the rolling element bearing, which requires monitoring and diagnostics to prevent potential failure. Due to the number of idlers to be monitored, the size of the conveyor, and the risk of accident when dealing with rotating elements and moving belts, monitoring of all idlers (i.e., using vibration sensors) is impractical regarding scale and connectivity. Hence, an inspection robot is proposed to capture acoustic signals instead of vibrations commonly used in condition monitoring. Then, signal processing techniques are used for signal pre-processing and analysis to check the condition of the idler. It has been found that even if the damage signature is identifiable in the captured signal, it is hard to automatically detect the fault in some cases due to sound disturbances caused by contact of the belt joint and idler coating. Classical techniques based on impulsiveness may fail in such a case, moreover, they indicate damage even if idlers are in good condition. The application of the inspection robot can “replace” the classical measurement done by maintenance staff, which can improve the safety during the inspection. In this paper, the authors show that damage detection in bearings installed in belt conveyor idlers using acoustic signals is possible, even in the presence of a significant amount of background noise. Influence of the sound disturbance due to the belt joint can be minimized by appropriate signal processing methods.
Optimization-Based Network Identification for Thermal Transient Measurements
Authors: Ziegeler Nils J. , Nolte Peter W. , Schweizer Stefan
Published: November 2021

Network identification by deconvolution is a proven method for determining the thermal structure function of a given device. The method allows to derive the thermal capacitances as well as the resistances of a one-dimensional thermal path from the thermal step response of the device. However, the results of this method are significantly affected by noise in the measured data, which is unavoidable to a certain extent. In this paper, a post-processing procedure for network identification from thermal transient measurements is presented. This so-called optimization-based network identification provides a much more accurate and robust result compared to approaches using Fourier or Bayesian deconvolution in combination with Foster-to-Cauer transformation. The thermal structure function obtained from network identification by deconvolution is improved by repeatedly solving the inverse problem in a multi-dimensional optimization process. The result is a non-diverging thermal structure function, which agrees well with the measured thermal impedance. In addition, the associated time constant spectrum can be calculated very accurately. This work shows the potential of inverse optimization approaches for network identification.
An Assessment of Heating Load Reduction by a Solar Air Heater in a Residential Passive Ventilation System
Authors: Matsunaga Junichiro , Kikuta Koki , Hirakawa Hideki , Mizuno Keita , Tajima Masaki , Hayashi Motoya , Fukushima Akira
Published: November 2021

In this paper, the authors examined the technology to maximize the use of renewable energy. Passive ventilation systems are expected to reduce the energy consumption of the fan and the maintenance burden. In addition, the wall-mounted solar air heater can supply thermal energy without using any energy at all. Therefore, this paper presents a “passive ventilation system with a solar air heater” that combines a passive ventilation system with the solar air heater to preheat the air. This system can reduce the ventilation load. To evaluate the solar air heater performance in a real environment, we developed a simulation for calculating the heat collection capacity of the solar air heater, and then the system was implemented in a real building for verification. The simulation performs hourly unsteady calculations, allowing for accurate evaluation of the annual simulation. Based on the measurement results, the effects of heating load reduction and prediction methods are presented. The solar air heater reduced the monthly ventilation load by up to 50% or more, and by at least 15%. It was also confirmed that there was a high correlation between the actual measurements and the simulation results.
Application of Smart Technologies in Metropolis GZM to Reduce Harmful Emissions in District Heating Systems
Authors: Kinelski Grzegorz , Stęchły Jakub , Sienicki Adrian , Czornik Kai , Borkowski Piotr
Published: November 2021

Harmful emissions from heating installations have recently received public attention in Poland. Polish municipalities mainly take their heat from local district heating networks with large-scale coal-fired heat sources. Today, transition to nonemissive sources on this scale would be impractical. The easiest way to reduce carbon emissions is to limit heat consumption, but at the same time, to preserve thermal comfort, the application of smart technologies is necessary. Veolia operates on 71 district heating systems in Poland, including Warsaw, Lodz, and Poznan. Since heat consumption in Warsaw and Metropolis GZM is at a similar level, this is a case study of Hubgrade automation system application within the Warsaw district heating network. This paper also presents results of simulation of harmful emission reduction potential in Metropolis GZM. Simulation results show that there is a potential for saving approximately 275 kt of CO2 for the whole Metropolis GZM.
A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations
Authors: Betta Giovanni , Capriglione Domenico , Ferrigno Luigi , Laracca Marco , Miele Gianfranco , Polese Nello , Sangiovanni Silvia
Published: November 2021

The reliability of systems and components is a fundamental need for the efficient development of a smart distribution grid. In fact, the presence of a fault in one component of the grid could potentially lead to a service interruption and loss of profit. Since faults cannot be avoided, the introduction of a diagnostic scheme could predict the fault of a component in order to carry out predictive maintenance. In this framework, this paper proposes a novel Fault Detection and Isolation (FDI) scheme for AC/DC converters in MV/LV substations. In order to improve the reliability of the FDI procedure, the system architecture includes also an Instrument Fault Detection and Isolation section for identifying faults that could occur on the instruments and sensors involved in the monitoring process of the AC/DC converter. The proposed architecture is scalable, easily upgradable, and uses cost-effective sensors. Tests, carried out on a real test site, have demonstrated the efficacy of the proposal showing very good IFDI diagnostic performance for the 12 types of faults tested. Furthermore, as the FDI diagnostic performance regards, it shows a detection rate close to 100%.
Series Architecture on Hybrid Electric Vehicles: A Review
Authors: Benevieri Alessandro , Carbone Lorenzo , Cosso Simone , Kumar Krishneel , Marchesoni Mario , Passalacqua Massimiliano , Vaccaro Luis
Published: November 2021

The use of series architecture nowadays is mainly on hybrid buses. In comparison with series-parallel and parallel architectures, which are usually exploited on medium-size cars, the series architecture allows achieving internal combustion engine higher efficiency. The downside of this architecture, due to a double energy conversion (i.e., mechanical energy converted in electrical energy and electrical energy converted again in mechanical energy), is that additional losses are introduced. For this reason, the parallel and the series/parallel architectures were considered more suitable for hybrid medium-size cars. Nevertheless, the use of new technologies can change this scenario. Regarding storage systems, supercapacitors achieved a significant energy density, and they guarantee much higher efficiency than battery storage. Moreover, the use of wide-bandgap components for power electronic converters, such as silicon carbide devices, assure lower losses. In this scenario, the series architecture can become competitive on medium-size cars. This paper shows a review of various studies performed on this topic.
Statistical Feature Extraction Combined with Generalized Discriminant Component Analysis Driven SVM for Fault Diagnosis of HVDC GIS
Authors: Zhou Ruixu , Gao Wensheng , Liu Weidong , Ding Dengwei , Zhang Bowen
Published: November 2021

Accurately identifying the types of insulation defects inside a gas-insulated switchgear (GIS) is of great significance for guiding maintenance work as well as ensuring the safe and stable operation of GIS. By building a set of 220 kV high-voltage direct current (HVDC) GIS experiment platforms and manufacturing four different types of insulation defects (including multiple sizes and positions), 180,828 pulse current signals under multiple voltage levels are successfully measured. Then, the apparent discharge quantity and the discharge time, two inherent physical quantities unaffected by the experimental platform and measurement system, are obtained after the pulse current signal is denoised, according to which 70 statistical features are extracted. In this paper, a pattern recognition method based on generalized discriminant component analysis driven support vector machine (SVM) is detailed and the corresponding selection criterion of involved parameters is established. The results show that the newly proposed pattern recognition method greatly improves the recognition accuracy of fault diagnosis in comparison with 36 kinds of state-of-the-art dimensionality reduction algorithms and 44 kinds of state-of-the-art classifiers. This newly proposed method not only solves the difficulty that phase-resolved partial discharge (PRPD) cannot be applied under DC condition but also immensely facilitates the fault diagnosis of HVDC GIS.
James I of Aragon (1213–1276)
Authors: Serrano-Coll Marta
Published: November 2021

James I, King of Aragon (1213–1276). He was the third king of the Crown of Aragon, which had come into existence through the union between Queen Petronila of Aragon (1157–1164) and the Count of Barcelona Ramon Berenguer IV (1137–1162). James I represents a milestone in the iconography of the Kings of Aragon, although this is due more to his successors’ promotion of him rather than to his own efforts. In order to organise and unify his dominions after the conquests of Mallorca and Valencia, he immersed himself in legal work that consolidated his legislative power whilst still allowing his territories to retain a certain degree of autonomy. He carried out an essential monetary reorganisation in which his coinage retained its obverse but altered its reverse according to the place of issue. He never succeeded in being crowned, although he featured the crown prominently in his stamps and seals and, on some coins, he added the term rex gratia Dei. In addition, he revived the sword as a royal insignia, having proclaimed the right of conquest as the basis of his sovereignty.
Greenhouse Gas Emission Offsets of Forest Residues for Bioenergy in Queensland, Australia
Authors: Garvie Leanda C. , Roxburgh Stephen H. , Ximenes Fabiano A.
Published: November 2021

Harnessing sustainably sourced forest biomass for renewable energy is well-established in some parts of the developed world. Forest-based bioenergy has the potential to offset carbon dioxide emissions from fossil fuels, thereby playing a role in climate change mitigation. Despite having an established commercial forestry industry, with large quantities of residue generated each year, there is limited use for forest biomass for renewable energy in Queensland, and Australia more broadly. The objective of this study was to identify the carbon dioxide mitigation potential of replacing fossil fuels with bioenergy generated from forest harvest residues harnessed from commercial plantations of Pinus species in southeast Queensland. An empirical-based full carbon accounting model (FullCAM) was used to simulate the accumulation of carbon in harvest residues. The results from the FullCAM modelling were further analysed to identify the energy substitution and greenhouse gas (GHG) emissions offsets of three bioenergy scenarios. The results of the analysis suggest that the greatest opportunity to avoid or offset emissions is achieved when combined heat and power using residue feedstocks replaces coal-fired electricity. The results of this study suggest that forest residue bioenergy is a viable alternative to traditional energy sources, offering substantive emission reductions, with the potential to contribute towards renewable energy and emission reduction targets in Queensland. The approach used in this case study will be valuable to other regions exploring bioenergy generation from forest or other biomass residues.
Selection of Water-Saving Plants and Annual Water Consumption Estimation for Garden Green Spaces in Beijing
Authors: Yin Qun , Shi Xiaodeng , Xiong Shuangjiang , Qu Yi , Zhou Yang , Liu Jinglan , Jia Zhongkui , Ma Luyi
Published: November 2021

Currently, the number of urban garden green spaces (GGSs) being constructed in Beijing is increasing, and their high water resource demands contradict the severe water shortage situation in Beijing that is restricting urban construction and economic development. This has created an urgent need to build water-saving GGSs. This study analyzed and compared the daily/annual water consumption of 79 common plants in Beijing, and low-water-consumption (LWC) trees, shrubs and herbs were selected; additionally, the total annual water consumption (TAWC) of all plants in the built-up areas of all 16 districts in Beijing was calculated according to the result of the eighth general survey of landscaping resources in Beijing. The results are as follows: (1) fifteen LWC tree species were selected from among 25 species, and the average daily water consumption (DWC) was <1.09 kg·m−2; (2) nineteen LWC shrubs were selected from among 35 shrubs, and the average DWC was <1.17 kg·m−2; (3) eleven LWC herbs were selected from among 19 herbs, and the AWC was <460.3 kg·m−2; (4) the TAWC of all trees, shrubs and herb plants in the Beijing GGSs was 1.104 × 109, 0.139 × 109, and 0.16 × 109 m3, respectively. Based on the above results, it was estimated that the TAWC of all plants in the built-up areas of all 16 districts in Beijing is approximately 1.403 × 109 m3. These findings provide a better understanding of the water consumption of GGS plants in cities in semiarid and semihumid climates and can be used to help select LWC greening plants that can reduce water consumption when expanding green areas in cities.
Characterization of a Novel Emaravirus Affecting Ash Species (Fraxinus spp.) in Europe
Authors: Gaskin Thomas R. , Tischendorf Max , Günther Ines , Rehanek Marius , Büttner Carmen , von Bargen Susanne
Published: November 2021

We identified a novel virus in diseased European ash (Fraxinus excelsior) and manna ash (F. ornus) trees exhibiting chlorotic ringspots, mottle and leaf deformation such as curling and shoestring symptoms. High-throughput sequencing (HTS, Illumina RNASeq) of total RNA isolated from diseased leaf material in combination with RT-PCR-based amplification techniques and Sanger sequencing determined five complete genome segments, each encoding a single open reading frame. Sequence analyses of RNA1–RNA5 revealed a genome organization typical for emaraviruses, i.e., (i) conserved and complementary terminal 5′ and 3′ termini of each genome segment (ii) proteins showing significant homologies to the RNA-dependent RNA polymerase (RdRP) encoded by RNA1, the glycoprotein precursor (GPP) encoded by RNA2, the viral nucleocapsid protein (N, RNA3), the movement protein (MP, RNA4), and a protein of 26 kDA (P26, RNA5) highly similar to proteins of unknown function encoded by other emaraviruses. Furthermore, we identified spherical particles (double-membrane bodies, DMB) of different sizes (70–80 nm in diameter) which are typical for emaraviruses exclusively in virus-infected leaf tissue exhibiting mottle and leaf deformation. Sequence comparison and phylogenetic analyses confirmed the identified novel virus as a new member of the genus Emaravirus. We established a species-specific RT-PCR detection protocol and could associate the observed disease symptoms with the infection of the novel emaravirus in F. excelsior and F. ornus. Therefore, we propose the name ash shoestring-associated emaravirus (ASaV). Investigation of ASaV-infected sample trees originating from different locations in Switzerland, Germany, Italy and Sweden provided a wide geographical distribution of the virus in affected ash species. To our knowledge, this is the first confirmation of an emaravirus affecting ash tree species with shoestring symptoms of leaves in Europe.
Characterization of Soybean Protein Isolate-Food Polyphenol Interaction via Virtual Screening and Experimental Studies
Authors: Ao Le , Liu Panhang , Wu Annan , Zhao Jing , Hu Xiaosong
Published: November 2021

(1) Background: Protein–polyphenol interactions have been widely studied regarding their influence on the properties of both protein and the ligands. As an important protein material in the food industry, soybean protein isolate (SPI) experiences interesting changes through polyphenols binding. (2) Methods: In this study, a molecular docking and virtual screening method was established to evaluate the SPI–polyphenol interaction. A compound library composed of 33 commonly found food source polyphenols was used in virtual screening. The binding capacity of top-ranking polyphenols (rutin, procyanidin, cyanidin chloride, quercetin) was validated and compared by fluorescence assays. (3) Results: Four out of five top-ranking polyphenols in virtual screening were flavonoids, while phenolic acids exhibit low binding capacity. Hydrogen bonding and hydrophobic interactions were found to be dominant interactions involved in soybean protein–polyphenol binding. Cyanidin chloride exhibited the highest apparent binding constant (Ka), which was followed by quercetin, procyanidin, and rutin. Unlike others, procyanidin addition perturbed a red shift of SPI fluorescence, indicating a slight conformational change of SPI. (4) Conclusions: These results suggest that the pattern of SPI–polyphenol interaction is highly dependent on the detailed structure of polyphenols, which have important implications in uncovering the binding mechanism of SPI–polyphenol interaction.
Simultaneous Determination of Purines and Uric Acid in Chinese Chicken Broth Using TFA/FA Hydrolysis Coupled with HPLC-VWD
Authors: Wu Manli , Zhang Wangang , Shen Xixi , Wang Wei
Published: November 2021

Chinese chicken broth is well known for its outstanding nutritional value and flavor, widely consumed in China. This study was designed to develop a sensitive and accurate high-performance liquid chromatography-variable wavelength detector (HPLC-VWD) method to simultaneously determine purines and uric acid in Chinese chicken broth for gout and hyperuricemia dietary management. Chromatographic separation was performed on an Agilent TC-C18 (2) column (4.6 mm × 250 mm, 5.0 µm), using 0.02 M KH2PO4 (pH 4.0) as a mobile phase. Sample pretreatment was optimized to enable the extraction of all analytes from Chinese chicken broth. The optimal pretreatment conditions were chicken broth-60% trifluoroacetic acid (TFA)/20% formic acid (FA) (1:1, v/v) in a volume ratio of 1:3 and hydrolysis for 40 min at 85 °C in a water bath. The limits of detection (LODs) and limits of quantification (LOQs) of the purines and uric acid were 0.58–1.71 µg/L and 1.92–5.70 µg/L, respectively. The recoveries were 91–101%, with the relative standard deviations (RSDs) lower than 3%. The complete method has been successfully applied to determine purines and uric acid in various Chinese chicken soups obtained from different provinces in China.
Predicted Shelf-Life, Thermodynamic Study and Antioxidant Capacity of Breadsticks Fortified with Grape Pomace Powders
Authors: Bianchi Federico , Lomuscio Elisabetta , Rizzi Corrado , Simonato Barbara
Published: November 2021

Grape pomace (GP), is the main winemaking by-product and could represent a valuable functional food ingredient being a source of bioactive compounds, like polyphenols. Polyphenols prevent many non-communicable diseases and could contrast the oxidation reaction in foods. However, the high content in polyunsaturated fatty acid, the described pro-oxidant potential action of some polyphenols and the complex interactions with other components of matrices during food processing must be considered. Indeed, all these factors could promote oxidative reactions and require focused and specific assay. The aims of this study were to evaluate the effects of GP powder (GPP) addition (at 0%, 5% and 10% concentrations) in breadsticks formulations both on the antioxidant activity at room temperature during storage and on the shelf-life by the OXITEST predictive approach. GPP fortification increased the total polyphenols content and the antioxidant activities of breadsticks. FRAP reduced during the first two days of storage at room temperature, TPC increased during the 75 days, while ABTS showed a slight progressive decrease. However, GP negatively influenced OXITEST estimated shelf-life of breadsticks, incrementing the oxidation rate. In conclusion, even if GP fortification of breadsticks could improve the nutritional value of the products, the increased commercial perishability represents a drawback that must be considered.
Carcass Traits, Meat Quality, and Volatile Compounds of Lamb Meat from Different Restricted Grazing Time and Indoor Supplementary Feeding Systems
Authors: Wang Bo , Wang Zhenzhen , Chen Yong , Liu Xueliang , Liu Kun , Zhang Yingjun , Luo Hailing
Published: November 2021

This study was conducted to investigate the carcass traits, meat quality, and volatile compounds of growing lambs under different restricted grazing time and indoor supplementary feeding systems. Fifty 3-month-old male Tan lambs (with similar body weight) were divided into five groups randomly according to grazing time 12 h/d (G12), 8 h/d(G8), 4 h/d(G4), 2 h/d (G2), and 0 h (G0, indoor supplementary feeding). Animals were slaughtered at the end of the experiment, and the longissimus thoracis (LT) samples were collected for further analysis. The results indicated that indoor supplementary feeding improved the percentages of carcass fat and non-carcass fat of pre-slaughter weight (PSW) and decreased the cooking loss of lamb meat. Grazing for 8 h/d or 2 h/d enhanced PSW, carcass, and meat percentages of PSW. Lambs grazing for 2 h/d with supplement and indoor supplementary feeding lambs had a higher level of intramuscular fat and lightness (L*) value and lower cooking loss in the LT muscle, but higher yellowness (b*) and fat content were found in indoor supplementary feeding lambs. More categories of volatile compounds were identified in meat from grazing lambs than from indoor supplementary feeding lambs, but lower content of aldehydes and total volatile flavor compounds was detected in grazing lambs. Overall, the results demonstrated that the feeding system is a main factor that affects lamb meat quality, and proper grazing time can improve the quantity and quality of lamb meat and provide meat with different flavors to the consumers.
A Comparison of β-Carotene, Phytoene and Amino Acids Production in Dunaliella salina DF 15 (CCAP 19/41) and Dunaliella salina CCAP 19/30 Using Different Light Wavelengths
Authors: Sui Yixing , Mazzucchi Laura , Acharya Parag , Xu Yanan , Morgan Geraint , Harvey Patricia J.
Published: November 2021

Strains of Dunaliella salina microalgae are of considerable research and industrial interest because they hyper-accumulate β-carotene as well as produce high-quality protein. To explore the co-production of valuable compounds in D. salina, this study compared the production of β-carotene, phytoene and amino acids in two strains cultivated under white, red or blue light until no further nitrogen was available. D. salina DF15 (CCAP 19/41 (PLY DF15)) produced more than 12% β-carotene (ash-free dry weight (AFDW) basis), and red light triggered the production of 9-cis β-carotene at a 9-cis/all-trans β-carotene ratio of 1.5. Phytoene production was also evident in D. salina DF15 under all conditions, particularly under blue light. However, the profile of essential amino acids (EAAs) and calculation of the essential amino acid index (EAAI) was less than ideal in terms of protein quality, for both strains. Umami compounds, quantified as monosodium glutamate (MSG) equivalents, indicated a higher equivalent umami concentration (EUC) in D. salina DF15 under red light (3.2 g MSG/100 g AFDW) than in D. salina CCAP19/30. Overall, D. salina DF15 demonstrates valuable traits for further exploration and product optimisation.
Pulmonary Arterial Hypertension: A Deeper Evaluation of Genetic Risk in the -Omics Era
Authors: Machado Rajiv D. , Southgate Laura
Published: November 2021

Pulmonary arterial hypertension (PAH) is a highly heterogeneous disorder with a complex, multifactorial aetiology [...]