bluuebunny/crossref_metadata_2025 huggingface dataset:
Nearctic Species in the Palearctic: Trans-Beringian Range, Phylogeny and Phylogeography of Pterostichus (Cryobius) mandibularoides (Coleoptera, Carabidae)
Authors: Zubrii Natalia Andreevna , Filippov Boris Yurevich , Khruleva Olga Arturovna , Kondakov Alexander Vasilevich , Rybalov Leonid Borisovich
Published: May 2022

Subgenus Cryobius is one of the most numerous among the megafauna of tundra soils, but studies on its species distribution, taxonomy, and ecology are lacking. Phylogeny and phylogeography reconstructions of insects with taxonomic complexity have become possible using an integrative approach. Here, we report that specimens of Pterostichus (Cryobius) mandibularoides, described from North America, were detected in Eurasia. Thus, this species has a trans-Beringian range with high distributions in North America, as well as a disjunctive part of the range on the northeastern edge of Asia within Chukotka and Wrangel Island. Eight COI haplotypes with closed relationships (1–2 mutation steps) were detected within the whole range, and one 28S rRNA haplotype was detected for Eurasia. Bayesian phylogeny revealed that P. mandibularoides had the most recent common ancestor with sister species P. brevicornis and P. nivalis. Mean genetic distances of both markers were similar and higher between P. mandibularoides and both P. brevicornis and P. nivalis (>5% ± 1.0%) than between the latter species (<4% ± 1.0%). The obtained results change the previous view about brevicornis group stock differentiation within Cryobius in the Arctic and require a revision of the phylogeny and phylogeography of brevicornis group species and Cryobius altogether.
Spatial Distribution of Cyclograpsus cinereus Dana 1851 on the Rocky Shores of Antofagasta (23°27′ S, Chile)
Authors: Rios-Escalante Patricio , Esse Carlos , Retamal Marco , Zúñiga Oscar , Fajardo Maritza , Ghory Farhana
Published: May 2022

The decapod fauna in the intertidal zone of the rocky shores of Chile is highly diverse, especially along the northern and central mainland coasts, where the influence of the cold Humboldt Current results in high productivity. One of the most abundant species in these ecosystems is the decapod Cyclograpsus cinereus Dana, 1851. The aim of the present study, carried out in the spring and summer seasons between 2018 and 2020, was to determine the spatial distribution patterns of the decapod C. cinereus in different sites along the rocky shores of Antofagasta bay, northern Chile, in order to establish probabilistic models that explain its distribution at each site. Individuals were counted in random quadrants in the intertidal zone. The data thus obtained were processed by application of the variance/mean ratio to determine whether the distribution of individuals was random, aggregated or uniform, associated with Poisson, negative binomial or positive binomial distributions, respectively. The data revealed aggregated (negative binomial) distribution in 15 sampling events, and uniform (positive binomial) distribution in 4 events. The sampling sites were located on rocky shores in four sectors of an urban zone, and two in a protected zone; no significant differences were found between the densities of the sites in the two zones. The results of the interpretative probabilistic models indicated aggregated distribution patterns, agreeing with previously reported interpretative probabilistic models for the distribution of decapods on the rocky shores of central and southern Chile.
Food versus Disturbance: Contradictory Effects of Human Activities on an Opportunistic Seabird Breeding in an Oligotrophic Marine System
Authors: Carlberg Rachael A. , Karris Georgios , Verma Manish , Foufopoulos Johannes
Published: May 2022

The islands of the Aegean Sea are areas of high biodiversity and endemism and harbor globally important seabird communities. Resident seabirds breed on offshore islands, where they often form strong nesting colonies. Breeding seabirds are important determinants of an island’s ecosystem function while also being exposed to a plethora of human activities. Understanding how anthropogenic activities impact such populations is not just essential for seabird conservation but is also critically important for the management of small insular ecosystems and the native species communities they support. We quantify the effect of human activities on the size and locations of Yellow-legged Gull (Larus michahellis) colonies from the Cyclades and Sporades archipelagos. We gathered data on variables suspected to influence seabird colonies, including physical islet characteristics, resource availability, and type and extent of human disturbance. Analyses were conducted on the local (islet) and on the regional (island cluster) levels to identify proximate and ultimate factors shaping the breeding population sizes of resident colonies. On the local level, we identify a clear negative effect of the presence of invasive rats on gull nesting density. Similarly, the presence of feral grazing mammals such as goats and rabbits has negative impacts on gull populations, an effect that appears to be primarily mediated through nest disturbance. Access to landfills and fishing vessels both had positive impacts on gull nesting density. Our results suggest approaches to managing Yellow-legged Gull populations in the Mediterranean Basin by taking into consideration the roles of introduced mammals, fishing activities, and open-air landfills on seabirds in the region.
Genetic Variability within the Murgese Horse Breed Inferred from Genealogical Data and Morphometric Measurements
Authors: Bramante Grazia , Pieragostini Elisa , Ciani Elena
Published: May 2022

The Murgese horse (MH) is a native breed from Apulia (Italy). This study aimed to evaluate the population status with regard to the available pedigree information (6923 animals born between 1900 and 2020), as well as its demographic and morphological evolution. The mean equivalent generations were 5.88. The average relatedness, inbreeding coefficient and increase in inbreeding by equivalent generation (ΔF) were 9.88%, 5.22%, 1.05%, respectively. The effective population size based on ΔF was 47.46. The effective number of founders (fe) was 36, and that of ancestors (fa) was 19. The ratio fe/fa was 1.89 witnessing a bottleneck effect. The ratio fa/fe indicates a 52% reduction of the genetic diversity as expected, given the fact that, for the current population (now recovered to 5000 breeding animals), the fe is 34 and the fa only 17, with 50% of diversity being explained by only six ancestors. Basically, the results reflect a substantial loss of genetic diversity in the MH breed over generations since its official founding, and unbalanced use of sires in the population, highlighting the importance of continuous monitoring and implementation of more effective conservation measures, especially in view of the growing request for boosting genetic improvement for MH morpho-functional traits.
Applied Change Management in Interventional Radiology—Implementation of Percutaneous Thermal Ablation as an Additional Therapeutic Method for Small Renal Masses
Authors: Lomoschitz Friedrich M. , Stummer Harald
Published: May 2022

Interventional radiology (IR) has the potential to offer minimally invasive therapy. With this potential, new and arising IR methods may sometimes be in competition with established therapies. To introduce new methods, transformational processes are necessary. In organizations, structured methods of change management, such as the eight-step process of Kotter—(1) Establishing a sense of urgency, (2) Creating the guiding coalition, (3) Developing a vision and strategy, (4) Communicating the change vision, (5) Empowering employees for broad-based action, (6) Generating short-term wins, (7) Consolidating gains and producing more change, and (8) Anchoring new approaches in the culture—are applied based on considerable evidence. In this article, the application of Kotter’s model in the clinical context is shown through the structured transformational process of the organizational implementation of the percutaneous thermal ablation of small renal masses. This article is intended to familiarize readers in the medical field with the methods of structured transformational processes applicable to the clinical setting.
Digital Droplet PCR in Hematologic Malignancies: A New Useful Molecular Tool
Authors: Galimberti Sara , Balducci Serena , Guerrini Francesca , Del Re Marzia , Cacciola Rossella
Published: May 2022

Digital droplet PCR (ddPCR) is a recent version of quantitative PCR (QT-PCR), useful for measuring gene expression, doing clonality assays and detecting hot spot mutations. In respect of QT-PCR, ddPCR is more sensitive, does not need any reference curve and can quantify one quarter of samples already defined as “positive but not quantifiable”. In the IgH and TCR clonality assessment, ddPCR recapitulates the allele-specific oligonucleotide PCR (ASO-PCR), being not adapt for detecting clonal evolution, that, on the contrary, does not represent a pitfall for the next generation sequencing (NGS) technique. Differently from NGS, ddPCR is not able to sequence the whole gene, but it is useful, cheaper, and less time-consuming when hot spot mutations are the targets, such as occurs with IDH1, IDH2, NPM1 in acute leukemias or T315I mutation in Philadelphia-positive leukemias or JAK2 in chronic myeloproliferative neoplasms. Further versions of ddPCR, that combine different primers/probes fluorescences and concentrations, allow measuring up to four targets in the same PCR reaction, sparing material, time, and money. ddPCR is also useful for quantitating BCR-ABL1 fusion gene, WT1 expression, donor chimerism, and minimal residual disease, so helping physicians to realize that “patient-tailored therapy” that is the aim of the modern hematology.
Radiomics Analysis on Gadoxetate Disodium-Enhanced MRI Predicts Response to Transarterial Embolization in Patients with HCC
Authors: Cannella Roberto , Cammà Carla , Matteini Francesco , Celsa Ciro , Giuffrida Paolo , Enea Marco , Comelli Albert , Stefano Alessandro , Cammà Calogero , Midiri Massimo , Lagalla Roberto , Brancatelli Giuseppe , Vernuccio Federica
Published: May 2022

Objectives: To explore the potential of radiomics on gadoxetate disodium-enhanced MRI for predicting hepatocellular carcinoma (HCC) response after transarterial embolization (TAE). Methods: This retrospective study included cirrhotic patients treated with TAE for unifocal HCC naïve to treatments. Each patient underwent gadoxetate disodium-enhanced MRI. Radiomics analysis was performed by segmenting the lesions on portal venous (PVP), 3-min transitional, and 20-min hepatobiliary (HBP) phases. Clinical data, laboratory variables, and qualitative features based on LI-RADSv2018 were assessed. Reference standard was based on mRECIST response criteria. Two different radiomics models were constructed, a statistical model based on logistic regression with elastic net penalty (model 1) and a computational model based on a hybrid descriptive-inferential feature extraction method (model 2). Areas under the ROC curves (AUC) were calculated. Results: The final population included 51 patients with HCC (median size 20 mm). Complete and objective responses were obtained in 14 (27.4%) and 29 (56.9%) patients, respectively. Model 1 showed the highest performance on PVP for predicting objective response with an AUC of 0.733, sensitivity of 100%, and specificity of 40.0% in the test set. Model 2 demonstrated similar performances on PVP and HBP for predicting objective response, with an AUC of 0.791, sensitivity of 71.3%, specificity of 61.7% on PVP, and AUC of 0.790, sensitivity of 58.8%, and specificity of 90.1% on HBP. Conclusions: Radiomics models based on gadoxetate disodium-enhanced MRI can achieve good performance for predicting response of HCCs treated with TAE.
Efficacy of Contrast-Enhanced Endoscopic Ultrasonography for the Diagnosis of Pancreatic Tumors
Authors: Yokoyama Kensuke , Kanno Atsushi , Miwata Tetsurou , Nagai Hiroki , Ikeda Eriko , Ando Kozue , Kawasaki Yuki , Tamada Kiichi , Lefor Alan Kawarai , Yamamoto Hironori
Published: May 2022

Endoscopic ultrasound can be useful for obtaining detailed diagnostic images for pancreatic disease. Contrast-enhanced harmonic endoscopic ultrasound has allowed to demonstrate not only microvasculature but also real perfusion imaging using second-generation contrast agents. Furthermore, endoscopic ultrasound fine-needle aspiration cytology and histology have become more ubiquitous; however, the risk of dissemination caused by paracentesis has yet to be resolved, and the application of less invasive contrast-enhanced endoscopic ultrasound for the differential diagnosis of pancreatic tumors has been anticipated. Contrast-enhanced harmonic endoscopic ultrasound can contribute to the differential diagnosis of pancreatic tumors.
A ROS Multi-Tier UAV Localization Module Based on GNSS, Inertial and Visual-Depth Data
Authors: Antonopoulos Angelos , Lagoudakis Michail G. , Partsinevelos Panagiotis
Published: May 2022

Uncrewed aerial vehicles (UAVs) are continuously gaining popularity in a wide spectrum of applications, while their positioning and navigation most often relies on Global Navigation Satellite Systems (GNSS). However, numerous conditions and practices require UAV operation in GNSS-denied environments, including confined spaces, urban canyons, vegetated areas and indoor places. For the purposes of this study, an integrated UAV navigation system was designed and implemented which utilizes GNSS, visual, depth and inertial data to provide real-time localization. The implementation is built as a package for the Robotic Operation System (ROS) environment to allow ease of integration in various systems. The system can be autonomously adjusted to the flight environment, providing spatial awareness to the aircraft. This system expands the functionality of UAVs, as it enables navigation even in GNSS-denied environments. This integrated positional system provides the means to support fully autonomous navigation under mixed environments, or malfunctioning conditions. Experiments show the capability of the system to provide adequate results in open, confined and mixed spaces.
Anatomy: An Opportunity for South African Health Science Students to Discuss Their Emotional Responses to Human Remains in the Laboratory
Authors: Hartmann Carol A. , Hutchinson Erin F. , Kramer Beverley
Published: May 2022

Human dissection remains a cornerstone of the anatomy learning experience. However, the emotional response of students to the use of human remains for learning is influenced by a number of factors and is not always positive. Therefore, this study explored the students’ emotional response to and factors affecting their perceptions of the use of human remains for learning anatomy in a South African context. Four hundred and eighty of the 1538 health sciences students enrolled in human anatomy courses at the University of the Witwatersrand, South Africa during 2016 and 2017, completed a voluntary survey. The survey included closed and open-ended questions on students’ emotional responses, coping mechanisms and the factors that affected their perceptions of the use of human remains and dissection. Overall, the students had a positive emotional response. Their perceptions of dissection were affected in positive and negative ways by their religious and cultural beliefs. Feelings of gratitude and respect toward the cadaver were informed by belief systems. However, anxiety was caused by the delay of accepted sociocultural burial practices. Peer discussions were the preferred coping method, which may provide an approach for students to discuss how their beliefs influence their dissection experience.
Intrinsic Characteristics of Forward Simulation Modeling Electric Vehicle for Energy Analysis
Authors: Montaleza Christian , Arévalo Paul , Tostado-Véliz Marcos , Jurado Francisco
Published: May 2022

The forward method for modeling electric vehicles is one of the most suitable for estimating energy consumption in different imposed driving cycles. However, a detailed description of the methodology used for the development of electric vehicle models is necessary and is scarce in the current literature. To fill this gap, this study focuses on highlighting the intrinsic characteristics through a theoretical study with a mathematical model, complemented by demonstrative simulations in Matlab/Simulink. The results show that the forward method can be estimated more accurately based on the energy consumption of the electric vehicle. Moreover, this paper aims to be explicitly descriptive for the development of more complex electric vehicle models to incorporate real driving cycles, being able to size the drivetrain of the vehicle itself or develop ecological routes.
Tuning Bolometric Parameters of Sierpinski Fractal Antenna-Coupled Uncracked/Cracked SWCNT Films by Thermoelectric Characterization at UHF Frequencies
Authors: Vera-Reveles Gustavo , González-Fernández José Vulfrano , Castillo-León Juan Francisco , González Francisco Javier , Díaz de León-Zapata Ramón , de la Rosa-Zapata Ariel Benjamín , Orocio-Castro Norma , Simón Jorge
Published: May 2022

In this work, the bolometric parameters of Sierpinski fractal antenna-coupled SWCNT semi-metallic films are obtained by thermoelectric characterization, this in order to find out the performance as bolometer. The method was based on an experimental setup considering a line-of-sight wireless link between two identical planar fractal antennas, infrared thermography, and electrical resistance measurements. The experimental setup considered the antennas resonant frequencies. Both the transmitting and receiving antenna were third-iteration Sierpinski fractal dipoles designed to work at UHF frequencies. Films made either of cracked or uncracked SWCNT films were each separately coupled to the receiving fractal antenna. Measurements showed that the receiving antenna that was impinged with radiation at UHF frequencies coming from the transmitting antenna, experienced as it was expected an induction of electric current, the induced current flowed through the film producing a temperature change, which in turn caused changes in the radiated heat of the film, as well as changes in the electrical resistance known as Temperature Coefficient of Resistance TCR. The maximum value of TCR for uncracked SWCNT films was −3.6%K−1, higher than the one observed for cracked SWCNT films which exhibited a maximum value of −1.46%K−1. Measurements for conversion of incident radiation to electrical signals known as the Voltage Responsivity ℜv, exhibited values of 9.4 mV/W and 1.4 mV/W for uncracked SWCNT films and cracked SWCNT films, respectively.
Real-Time Classification of Pain Level Using Zygomaticus and Corrugator EMG Features
Authors: Kelati Amleset , Nigussie Ethiopia , Dhaou Imed Ben , Plosila Juha , Tenhunen Hannu
Published: May 2022

The real-time recognition of pain level is required to perform an accurate pain assessment of patients in the intensive care unit, infants, and other subjects who may not be able to communicate verbally or even express the sensation of pain. Facial expression is a key pain-related behavior that may unlock the answer to an objective pain measurement tool. In this work, a machine learning-based pain level classification system using data collected from facial electromyograms (EMG) is presented. The dataset was acquired from part of the BioVid Heat Pain database to evaluate facial expression from an EMG corrugator and EMG zygomaticus and an EMG signal processing and data analysis flow is adapted for continuous pain estimation. The extracted pain-associated facial electromyography (fEMG) features classification is performed by K-nearest neighbor (KNN) by choosing the value of k which depends on the nonlinear models. The presentation of the accuracy estimation is performed, and considerable growth in classification accuracy is noticed when the subject matter from the features is omitted from the analysis. The ML algorithm for the classification of the amount of pain experienced by patients could deliver valuable evidence for health care providers and aid treatment assessment. The proposed classification algorithm has achieved a 99.4% accuracy for classifying the pain tolerance level from the baseline (P0 versus P4) without the influence of a subject bias. Moreover, the result on the classification accuracy clearly shows the relevance of the proposed approach.
Infrared and Visible Image Registration Based on Automatic Robust Algorithm
Authors: Ji Jingyu , Zhang Yuhua , Lin Zhilong , Li Yongke , Wang Changlong , Hu Yongjiang , Yao Jiangyi
Published: May 2022

Image registration is the base of subsequent image processing and has been widely utilized in computer vision. Aiming at the differences in the resolution, spectrum, and viewpoint of infrared and visible images, and in order to accurately register infrared and visible images, an automatic robust infrared and visible image registration algorithm, based on a deep convolutional network, was proposed. In order to precisely search and locate the feature points, a deep convolutional network is introduced, which solves the problem that a large number of feature points can still be extracted when the pixels of the infrared image are not clear. Then, in order to achieve accurate feature point matching, a rough-to-fine matching algorithm is designed. The rough matching is obtained by location orientation scale transform Euclidean distance, and then, the fine matching is performed based on the update global optimization, and finally, the image registration is realized. Experimental results show that the proposed algorithm has better robustness and accuracy than several advanced registration algorithms.
Investigations on the Potential of 5G for the Detection of Wear in Industrial Roller-Burnishing Processes
Authors: Kosel Maximilian , Schippers Tobias , Abdul Aziz , Ishii Kristina , Mainczyk Jacek , Mansel Jürgen , Milnikel Kai , Nurkan Bünyamin , Löschner Ralf , Haefner Konstantin , Zontar Daniel , Brecher Christian
Published: May 2022

Roller burnishing represents an economical alternative to conventional surface-finishing processes, such as fine turning or honing. In contrast to the well-known wear mechanisms of chip-forming processes, the wear behavior in roller-burnishing is strongly based on the experience of the machine operators. The nature of the finishing process makes roller-burnishing very sensitive to surface defects, as it is often not possible to rework the last step in a process chain. In the present work, a prototype for a smart roller-burnishing tool with 5G communication is presented, which serves as an inline-monitoring tool to detect tool wear. A suitable metric to monitor the tool wear of the manufacturing roll is suggested, and the potentials of 5G communication for the described use-case are evaluated. Based on the signal-to-noise ratio of the process-force, a metric is found that distinguishes new rolls from worn rolls with very small defects on the micrometer scale. Using the presented approach, it was possible to distinguish the signal-to-noise ratio of a roll with very small wear marks by 3.8% on average. In the case of stronger wear marks, on the order of 20 µm, the difference increased to up to 15.6%.
Efficient Integration of PV Sources in Distribution Networks to Reduce Annual Investment and Operating Costs Using the Modified Arithmetic Optimization Algorithm
Authors: Montoya Oscar Danilo , Giral-Ramírez Diego Armando , Hernández Jesus C.
Published: May 2022

The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the optimal siting and sizing of photovoltaic resources in medium-voltage levels is addressed from an economical point of view, where the optimization model that represents said problem corresponds to a mixed-integer nonlinear programming model. The maximum allowed size for single photovoltaic units in the distribution network is set at 2400 kW. The investment costs, energy purchase costs and maintenance costs for photovoltaic units, are considered in the objective function. Typical constraints such as power balance, generation capacities, voltage regulation, among others, are considered in the mathematical formulation. The solution of the optimization model is addressed by implementing a modified version of the Arithmetic Optimization Algorithm, which includes a new exploration and exploitation characteristic based on the best current solution in iteration t, i.e., xbestt. This improvement is based on a Gaussian distribution operator that generates new candidate solutions with the center at xbestt, which are uniformly distributed. The main contribution of this research is the proposal of a new hybrid optimization algorithm to solve the exact optimization model, which is based on a combination of the Arithmetic Optimization algorithm with the Vortex Search algorithm and showed excellent numerical results in the IEEE 34-bus grid. The analysis of quantitative results allows us to conclude that the strategy proposed in this work has a greater effectiveness with respect to the General Algebraic Modeling System software solvers, as well as with metaheuristic optimizers such as Genetic Algorithms, the Newton–Metaheuristic Algorithm, and the original Arithmetic Optimization Algorithm. MATLAB was used as a simulation tool.
Predictions Based on Evolutionary Algorithms Using Predefined Control Profiles
Authors: Mînzu Viorel , Georgescu Lucian , Rusu Eugen
Published: May 2022

The general motivation of our work is to meet the main time constraint when implementing a control loop: the Controller’s execution time is less than the sampling period. This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Model Predictive Control or, more generally, Receding Horizon Control structures. The main drawback of the metaheuristic algorithms (including EAs) working in control structures is their great complexity. Usually, the control variables take values between minimum and maximum technological limits. This work’s main idea is to consider the control variables’ domain inside a predefined control profile’s neighbourhood. The Controller takes into account a smaller domain of the control variables without tracking the predefined control profile or a reference trajectory. The convergence of the EA under consideration is not affected; hence, the same best predictions are found. The predefined control profile is already known or can be determined by solving the optimal control problem without time constraints in open-loop and offline. This work also presents a simulation study applying the proposed technique that involves two benchmark control problems. The results prove that the computational complexity decreases significantly.
Synthesis of Donor–Acceptor Copolymers Derived from Diketopyrrolopyrrole and Fluorene via Eco-Friendly Direct Arylation: Nonlinear Optical Properties, Transient Absorption Spectroscopy, and Theoretical Modeling
Authors: Rodríguez-Rea Jonatan , Güizado-Rodríguez Marisol , Maldonado José-Luis , Ramos-Ortiz Gabriel , Reveles José Ulises , Silva Carlos , Barba Victor , Saucedo-Salazar Esmeralda Monserrat , Rodríguez Hernández María Teresa
Published: May 2022

A series of PFDPP copolymers based on fluorene (F) and diketopyrrolopyrrole (DPP) monomers were synthesized via direct arylation polycondensation using Fagnou conditions which involved palladium acetate as catalyst (a gradual catalyst addition of three different percentages were used), potassium carbonate as the base, and neodecanoic acid in N, N-dimethylacetamide. This synthesis provides a low cost compared with traditional methods of transition-metal-catalyzed polymerization. Among the different amounts of catalyst used in the present work, 12% was optimal because it gave the highest reaction yield (81.5%) and one of the highest molecular weights (Mn = 13.8 KDa). Copolymers’ chemical structures, molecular weight distributions, and optical and thermal properties were analyzed. The linear optical properties of PFDPP copolymers resulted very similarly independently to the catalyst amounts used in the synthesis of the PFDPP copolymers: two absorptions bands distinctive of donor–acceptor copolymers, Stokes shifts of 41 nm, a good quantum yield of fluorescence around 47%, and an optical bandgap of 1.7 eV were determined. Electronic nonlinearities were observed in these copolymers with a relatively high two-photon absorption cross-section of 621 GM at 950 nm. The dynamics of excited states and aggregation effects were studied in solutions, nanoparticles, and films of PFDPP. Theoretical calculations modeled the ground-state structures of the (PFDPP)n copolymers with n = 1 to 4 units, determining the charge distribution by the electrostatic potential and modeling the absorption spectra determining the orbital transitions responsible for the experimentally observed leading bands. Experimental and theoretical structure–properties analysis of these donor–acceptor copolymers allowed finding their best synthesis conditions to use them in optoelectronic applications.
A New Relative Permeability Characterization Method Considering High Waterflooding Pore Volume
Authors: Qi Guangfeng , Zhao Jingang , He Hu , Sun Encheng , Yuan Xin , Wang Shuoliang
Published: May 2022

In the process of waterflooding development, high waterflooding PVs will make the fluid percolation in the reservoir more complicated, resulting in lower efficiency of waterflooding. High waterflooding PVs will affect the relative permeability and change the seepage law of oil–water two-phase flow in a high water-cut period. In this study, we performed high waterflooding PVs relative permeability experiments using nine natural cores. The unsteady measurement method is used to test the relative permeability curve. The results show that: (1) the relative permeability is affected by the waterflooding PVs, the recovery efficiency of 2000 waterflooding PVs is 10.72% higher than that of 50 waterflooding PVs on the core scale; (2) it makes water mobility increase sharply, while oil phase flow capacity remains low and decreases at high water cut stage. A new relative permeability characterization method considering high waterflooding PVs is established, which is applied to the numerical simulator. It shows that the remaining oil saturation of the high-permeability belt is higher than the calculation results of the traditional numerical simulator. It means that the injected water does not diffuse much into the low-permeability zone of the formation. The modified simulator is validated with the actual China offshore oilfield model. The numerical saturation of the key section of the passing well is in good agreement with the actual logging interpretation results, and the water cut curve fits better in the whole area. The modified simulator could predict oil production accurately after high waterflooding PVs treatment.
Nano-Iron Oxide-Ethylene Glycol-Water Nanofluid Based Photovoltaic Thermal (PV/T) System with Spiral Flow Absorber: An Energy and Exergy Analysis
Authors: Al Ezzi Amged , Chaichan Miqdam T. , Majdi Hasan S. , Al-Waeli Ali H. A. , Kazem Hussein A. , Sopian Kamaruzzaman , Fayad Mohammed A. , Dhahad Hayder A. , Yusaf Talal
Published: May 2022

Both electrical and thermal efficiencies combine in determining and evaluating the performance of a PV/T collector. In this study, two PV/T systems consisting of poly and monocrystalline PV panels were used, which are connected from the bottom by a heat exchanger consisting of a spiral tube through which a nanofluid circulates. In this study, a base fluid, water, and ethylene glycol were used, and iron oxide nanoparticles (nano-Fe2O3) were used as an additive. The mixing was carried out according to the highest specifications adopted by the researchers, and the thermophysical properties of the fluid were carefully examined. The prepared nanofluid properties showed a limited effect of the nanoparticles on the density and viscosity of the resulting fluid. As for the thermal conductivity, it increased by increasing the mass fraction added to reach 140% for the case of adding 2% of nano-Fe2O3. The results of the zeta voltage test showed that the supplied suspensions had high stability. When a mass fraction of 0.5% nano-Fe2O3 was added the zeta potential was 68 mV, while for the case of 2%, it reached 49 mV. Performance tests showed a significant increase in the efficiencies with increased mass flow rate. It was found when analyzing the performance of the two systems for nanofluid flow rates from 0.08 to 0.17 kg/s that there are slight differences between the monocrystalline, and polycrystalline systems operating in the spiral type of exchanger. As for the case of using monocrystalline PV the electrical, thermal, and total PV/T efficiencies with 2% added Fe2O3 ranged between 10% to 13.3%, 43–59%, and 59 to 72%, respectively, compared to a standalone PV system. In the case of using polycrystalline PV, the electrical, thermal, and total PV/T efficiencies ranged from 11% to 13.75%, 40.3% to 63%, and 55.5% to 77.65%, respectively, compared to the standalone PV system. It was found that the PV/T electrical exergy was between 45, and 64 W with thermal exergy ranged from 40 to 166 W, and total exergy from 85 to 280 W, in the case of using a monocrystalline panel. In the case of using polycrystalline, the PV/T electrical, thermal, and total exergy were between 45 and 66 W, 42–172 W, and 85–238 W, respectively. The results showed that both types of PV panels can be used in the harsh weather conditions of the city of Baghdad with acceptable, and efficient productivity.
Investigation of Shock Wave Oscillation Suppression by Overflow in the Supersonic Inlet
Authors: Cai Feichao , Huang Guanhong , Liu Xiaowei
Published: May 2022

With a focus on the shock oscillation phenomenon of a supersonic inlet at a high Mach number, the influence of isolator overflow on shock oscillation is studied in this paper. The shock wave dynamic model with overflow was established by the theoretical method, and the integrated numerical model of internal flow and external flow in the inlet was established too. The theoretical analysis of rate of overflow and overflow position on the flow field is carried out, and the changes of flow field parameters are studied by numerical simulation under different overflow positions. The results showed that both increasing the rate of overflow and setting the overflow gap close to the shock front were beneficial to reducing the flow parameters’ oscillation. In the viscous flow field, the overflow gap restricted the forward development of the local separation region of the shock train system, thus constraining the shock wave movement process, which could significantly reduce the parameter oscillation. In model C with two groups of overflow gaps, pressure oscillations of sampling point PU8 and PL8 were reduced to 29.81% and 30.56% relative to without overflow, and the corresponding rate of overflow was within 3.6%, which indicated that the appropriate overflow gap setting could effectively suppress the self-excited oscillation in the inlet.
Evidential Extreme Learning Machine Algorithm-Based Day-Ahead Photovoltaic Power Forecasting
Authors: Wang Minli , Wang Peihong , Zhang Tao
Published: May 2022

The gradually increased penetration of photovoltaic (PV) power into electric power systems brings an urgent requirement for accurate and stable PV power forecasting methods. The existing forecasting methods are built to explore the function between weather data and power generation, which ignore the uncertainty of historical PV power. To manage the uncertainty in the forecasting process, a novel ensemble method, named the evidential extreme learning machine (EELM) algorithm, for deterministic and probabilistic PV power forecasting based on the extreme learning machine (ELM) and evidential regression, is proposed in this paper. The proposed EELM algorithm builds ELM models for each neighbor in the k-nearest neighbors initially, and subsequently integrates multiple models through an evidential discounting and combination process. The results can be accessed through forecasting outcomes from corresponding models of nearest neighbors and the mass function determined by the distance between the predicted point and neighbors. The proposed EELM algorithm is verified with the real data series of a rooftop PV plant in Macau. The deterministic forecasting results demonstrate that the proposed EELM algorithm exhibits 15.45% lower nRMSE than ELM. In addition, the forecasting prediction intervals obtain better performance in PICP and CWC than normal distribution.
Distributionally Robust Multi-Energy Dynamic Optimal Power Flow Considering Water Spillage with Wasserstein Metric
Authors: Song Gengli , Wei Hua
Published: May 2022

This paper proposes a distributed robust multi-energy dynamic optimal power flow (DR-DOPF) model to overcome the uncertainty of new energy outputs and to reduce water spillage in hydropower plants. The proposed model uses an ambiguity set based on the Wasserstein metric to address the uncertainty of wind and solar power forecasting errors, rendering the model data-driven. With increasing sample size, the conservativeness of the ambiguity set was found to decrease. By deducing the worst-case expectation in the objective function and the distributed robust chance constraints, the exact equivalent form of the worst-case expectation and approximate equivalent form of the distributed robust chance constraints were obtained. The test results of the IEEE-118 and IEEE-300 node systems indicate that the proposed model could reduce water spillage by more than 85% and comprehensive operation cost by approximately 12%. With an increasing number of samples, the model could reduce conservativeness on the premise of satisfying the reliability of safety constraints.
Technoeconomic Assessment of LNG-Fueled Solid Oxide Fuel Cells in Small Island Systems: The Patmos Island Case Study
Authors: Peloriadi Konstantina , Iliadis Petros , Boutikos Panagiotis , Atsonios Konstantinos , Grammelis Panagiotis , Nikolopoulos Aristeidis
Published: May 2022

Liquefied natural gas (LNG) is regarded as the cleanest among fossil fuels due to its lower environmental impact. In power plants, it emits 50–60% less carbon dioxide into the atmosphere compared to regular oil or coal-fired plants. As the demand for a lower environmental footprint is increasing, fuel cells powered by LNG are starting to appear as a promising technology, especially suitable for off-grid applications, since they can supply both electricity and heating. This article presents a techno-economic assessment for an integrated system consisting of a solid oxide fuel cell (SOFC) stack and a micro gas turbine (MGT) fueled by LNG, that feeds the waste heat to a multi-effect desalination system (MED) on the Greek island of Patmos. The partial or total replacement of the diesel engines on the non-interconnected island of Patmos with SOFC systems is investigated. The optimal system implementation is analyzed through a multi-stage approach that includes dynamic computational analysis, techno-economic evaluation of different scenarios using financial analysis and literature data, and analysis of the environmental and social impact on the island. Specific economic indicators such as payback, net present value, and internal rate of return were used to verify the economic feasibility of this system. Early results indicate that the most sensitive and important design parameter in the system is fuel cell capital cost, which has a significant effect on the balance between investment cost and repayment years. The results of this study also indicate that energy production with an LNG-fueled SOFC system is a promising solution for non-interconnected Greek islands, as an intermediate carrier prior to the long-term target of a CO₂-free economy.
Spiral Groove Parametric Study of Solid Particles Deposition Characteristics in Sealing Lubrication Film
Authors: Chen Huilong , Wei Zepeng , Lu Juncheng , Gui Kai , Chen Yingjian , Cheng Qian , Fu Yanxia , Zhao Binjuan
Published: May 2022

In order to study the effect of groove parameters on solid particles’ deposition in mechanical face seal lubrication film, a multi-phase flow calculation model for the sealing micro-gap lubricating film was established based on the Laminar model, mixture multi-phase flow model, Zwart–Gerber–Belamri cavitation model, and DPM model in Fluent, and a numerical simulation of the effect of groove parameters is presented. The results show that, with the increase of groove depth, the circumferential sedimentary zone in the dam area decreases or even disappears, and the groove area becomes the main sedimentary part; the particle deposition rate decreases first and then increases with the increase of groove depth and spiral angle. The influence of groove depth on the deposition rate at low speed is more significant than that at high speed. The increase of deposition rate caused by a spiral angle that is too large is greater than that caused by a spiral angle that is too small. The optimal groove depth and spiral angle are around 6 µm and 18°, respectively; when the rotating speed is 1000 rpm, the deposition rate increases obviously with the increase of the groove diameter ratio; meanwhile, when the rotating speed increases to more than 2000 rpm, the deposition rate increases first and then decreases with the increase of the groove diameter ratio. When the groove diameter ratio is about 0.5, the deposition rate is the largest. For example, when the rotating speed is 2000 rpm, the deposition rate of the groove diameter ratio, 0.5, is about 200% higher than that of groove diameter ratio, 0.2. The lower the speed, the more sensitive the deposition rate is to the groove diameter ratio. The sensitivity at 1000 rpm is 14 times that at 5000 rpm. The deposition rate increases with the increase of the groove width ratio. The higher the rotating speed, the smaller the rate of deposition rate increase. However, when the rotating speed is 5000 rpm and the groove width ratio is higher than 0.7, the deposition rate increases sharply.
Prediction Method of Beijing Electric-Energy Substitution Potential Based on a Grid-Search Support Vector Machine
Authors: Chi Yuanying , Zhang Yangyi , Li Guozheng , Yuan Yongke
Published: May 2022

Recently, “power cuts” and “coal price surges” have been significant concerns of individuals and societies. The main reasons for a power cut are a recent rapid increase in power consumption, shortage of thermal coal or the large shutdown capacity of thermal power units, resulting in a tight power supply in the power grid. In recent years, the shortage of fossil resources has led to frequent energy crises. In the context of carbon peaks and carbon neutralization, how to better develop electric-energy substitution and eliminate the dependence on fossil energy has become a problem that needs to be solved at present. In this paper, the influencing factors of electric-energy substitution in Beijing are analyzed, and the indexes affecting the electric-energy substitution are outlined. By constructing various machine-learning models, the prediction is performed. The results show that the Gaussian kernel support vector machine model based on a grid search has a good prediction effect on the electric-energy substitution potential in Beijing, which has certain guiding significance for electric-energy substitution potential analysis.
Nonlinear Mixed-Effects Height to Crown Base Model for Moso Bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens) in Eastern China
Authors: Zhou Xiao , Zheng Yaxiong , Guan Fengying , Sharma Ram P. , Zhang Xuan , Zhou Yang
Published: May 2022

Height to crown base (HCB) is an important variable used as a predictor of forest growth and yield. This study developed a nonlinear, mixed-effects HCB model through inclusion of plot-level random effects using data from 29 sample plots distributed across a state-owned Yixing forest farm in Jiangsu province, eastern China. Among several predictor variables evaluated in the analyses, bamboo height, canopy density, and total basal area of bamboo with a diameter larger than that of the subject bamboo individual contributed significantly to the HCB variations. The inclusion of random effects improved the prediction accuracy of the model significantly, indicating that the HCB variations within and across the sample plots were substantial. The model was localized using four sampling strategies, and the study identified that using two medium-sized bamboos by diameter at breast height per sample plot resulted in the smallest prediction error. This strategy, which would balance both measurement cost and potential error, may be applied to estimate the random effects and localization of the nonlinear mixed-effects HCB model for moso bamboo in eastern China.
First Report of Fungal Endophyte Communities and Non-Defensive Phytochemistry of Biocontrol-Inoculated Whitebark Pine Seedlings in a Restoration Planting
Authors: Moler Ehren R. V. , Reinhardt Keith , Sniezko Richard A. , Aho Ken
Published: May 2022

Plant endosymbionts (endophytes) influence host plant health and express genotype-dependent ecological relationships with plant hosts. A fungal species intended to confer host plant resistance to a forest pathogen was used as inoculum to test for effects of inoculation on disease resistance, microbiomes, and phytochemistry of a threatened pine species planted in a restoration setting. Correlations of inoculation presence/absence, phytochemistry, spatial location of seedlings, maternal seed sources, and fungal endophytic communities in the foliage of six-year-old whitebark pine (Pinus albicaulis) seedlings were assessed five years after an experimental inoculation of seedlings with foliar endophytic fungi cultured from whitebark pine trees at Crater Lake National Park, including Paramyrothecium roridum. We hypothesized that P. roridum would modify host microbiomes in a manner that combats white pine blister rust disease. Our assessment of seedlings in the field five years after inoculation allowed us to consider whether inoculation stimulated long-lasting changes in microbiome communities and whether effects varied by seedling genetic family. Tests for effects of endophyte inoculation on disease resistance were inconclusive due to current low levels of rust infection observed at the field site. Foliar fungal endophyte richness and Shannon diversity varied with maternal seed sources. Isotopic stoichiometry and phytochemistry did not vary with seedling spatial proximity, inoculation treatment, or maternal seed family. However, endophyte community composition varied with both seedling spatial proximity and maternal seed sources. Endophytic communities did not vary with the inoculation treatment, and the hypothesized biocontrol was not detected in inoculated seedlings. We draw three conclusions from this work: (1) fungal microbiomes of whitebark pine seedlings across our study site did not vary with host phytochemical signatures of ecophysiological status, (2) the inoculation of P. albicaulis seedlings with a mixture of fungal endophytes did not lead to persistent systemic changes in seedling foliar microbiomes, and (3) in correspondence with other studies, our data suggest that maternal seed source and spatial patterns influence fungal endophyte community composition.