bluuebunny/crossref_metadata_2025 huggingface dataset:
Wind Speed Forecasts of a Mesoscale Ensemble for Large-Scale Wind Farms in Northern China: Downscaling Effect of Global Model Forecasts
Authors: Shi Jianqiu , Liu Yubao , Li Yang , Liu Yuewei , Roux Gregory , Shi Lan , Fan Xiaowei
Published: January 2022

To facilitate wind power integration for the electric power grid operated by the Inner Mongolia Electric Power Corporation—a major electric power grid in China—a high-resolution (of 2.7 km grid intervals) mesoscale ensemble prediction system was developed that forecasts winds for 130 wind farms in the Inner Mongolia Autonomous Region. The ensemble system contains 39 forecasting members that are divided into 3 groups; each group is composed of the NCAR (National Center for Atmospheric Research) real-time four-dimensional data assimilation and forecasting model (RTFDDA) with 13 physical perturbation members, but driven by the forecasts of the GFS (Global Forecast System), GEM (Global Environmental Multiscale Model), and GEOS (Goddard Earth Observing System), respectively. The hub-height wind predictions of these three sub-ensemble groups at selected wind turbines across the region were verified against the hub-height wind measurements. The forecast performance and variations with lead time, wind regimes, and diurnal and regional changes were analyzed. The results show that the GFS group outperformed the other two groups with respect to correlation coefficient and mean absolute error. The GFS group had the most accurate forecasts in ~59% of sites, while the GEOS and GEM groups only performed the best on 34% and 2% of occasions, respectively. The wind forecasts were most accurate for wind speeds ranging from 3 to 12 m/s, but with an overestimation for low speeds and an underestimation for high speeds. The GEOS-driven members obtained the least bias error among the three groups. All members performed rather accurately in daytime, but evidently overestimated the winds during nighttime. The GFS group possessed the fewest diurnal errors, and the bias of the GEM group grew significantly during nighttime. The wind speed forecast errors of all three ensemble members increased with the forecast lead time, with the average absolute error increasing by ~0.3 m/s per day during the first 72 h of forecasts.
Policy Effect on Clean Coal-Fired Power Development in China
Authors: Zhang Jianyun , Li Xinxin , Pan Lingying
Published: January 2022

The coal power policy has been influencing the development of China’s coal power industry from the aspects of quantity control, technological progress, and market-oriented reform. Meanwhile, the strategic coal power policy of the mid- and long-term future is yet to be well-designed under the carbon peak and neutrality targets. Therefore, it is necessary to have a comprehensive overview of the coal power policy during the past and give targeted prospects for policy-makers. This paper discusses the policy effect on the development and technological progress of the coal power industry by giving an overview of the policy and reform processes of the coal power industry in China in the past 20 years. The results indicate that China’s coal power policy has promoted the progress of coal power generation technology, optimized the coal power structure, accelerated the diversified investment in the power industry, and alleviated the overcapacity problem of coal power generation. After discussion, we conclude that: (1) It is necessary to gradually reduce the average generation hours of coal-fired power units while retaining high-quality coal-fired power units. (2) The renewable energy enterprises that adopt the support services of coal power enterprises should provide reasonable capacity compensation costs to create favorable conditions and achieve sustainable development for China’s coal power industry. (3) To deploy coal power units combined with large-scale renewable energy in the western and northern regions will achieve efficient energy utilization. (4) Different strategies should be adopted for different coal power units, and the peak regulation potential of coal power units with low-capacity parameters should be explored.
Design and Implementation of the Bidirectional DC-DC Converter with Rapid Energy Conversion
Authors: Chen Bing-Zhang , Liao Hsuan , Chen Linda , Chen Jiann-Fuh
Published: January 2022

The bidirectional DC-DC converters are widely used in the energy storage system (ESS) and DC distribution system. The power capacity is limited when the converter is operated with smooth power transfer. In addition, the directions of the inductor current and the capacitor voltage cannot change instantaneously. In this study, a rapid energy conversion technique for smoothing and accelerating the energy transfer under the same specification of the main components in steady state is proposed. Moreover, a bidirectional DC-DC converter with a high conversion ratio is proposed to overcome the commonly low voltage input from renewable energy sources. The operating principles of the proposed converter’s step-down and step-up modes are discussed in this study. Furthermore, to achieve rapid energy conversion, digital control is a crucial component in the converter system. A digital signal processor is used as the control platform, and a control strategy is formulated to achieve rapid energy conversion. The bidirectional DC-DC prototype converter with a 24 V battery, a DC bus of 200 V, and an output power of 500 W is constructed to confirm the feasibility of rapid energy conversion. The proposed converter can be operated in CCM, BCM, and DCM conditions. The transfer period can be completed within one switching cycle when the proposed converter is operated in BCM or DCM. The energy is freewheeled before energy conversion when the proposed converter is operated in CCM condition. In the experiment, the minimum transfer period is 6.29 µs on the DCM stage.
Mucormycosis—Emerging Fungal Threats
Authors: Troiano Gianmarco , Nante Nicola
Published: January 2022

Mucormycosis is an opportunistic fungal infection due to organisms of the Zygomycetes class and the order of Mucorales that can cause various types of infections. In recent years, an increasing phenomenon has been observed—invasive fungal infections especially in the healthcare setting. Among immucompromised patients, an important clinical emergency could be represented by mucormycosis. The epidemiology of mucormycosis has shown an alarming trend and its incidence is rising globally. Four elements are fundamental for a successful treatment: rapid diagnosis, reduction of predisposing factors (if possible), surgical debridement of infected tissues, and appropriate antifungal therapy.
Image-Based Analysis of Dense Particle Mixtures via Mask R-CNN
Authors: Frei Max , Kruis Frank Einar
Published: January 2022

Powders and their mixtures are elemental for many industries (e.g., food, pharmaceutical, mining, agricultural, and chemical). The properties of the manufactured products are often directly linked to the particle properties (e.g., particle size and shape distribution) of the utilized powder mixtures. The most straightforward approach to acquire information concerning these particle properties is image capturing. However, the analysis of the resulting images often requires manual labor and is therefore time-consuming and costly. Therefore, the work at hand evaluates the suitability of Mask R-CNN—one of the best-known deep learning architectures for object detection—for the fully automated image-based analysis of particle mixtures, by comparing it to a conventional, i.e., not machine learning-based, image analysis method, as well as the results of a trifold manual analysis. To avoid the need of a laborious manual annotation, the training data required by Mask R-CNN are produced via image synthesis. As an example for an industrially relevant particle mixture, endoscopic images from a fluid catalytic cracking reactor are used as a test case for the evaluation of the tested methods. According to the results of the evaluation, Mask R-CNN is a well-suited method for the fully automatic image-based analysis of particle mixtures. It allows for the detection and classification of particles with an accuracy of 42.7% for the utilized data, as well as the characterization of the particle shape. Also, it enables the measurement of the mixture component particle size distributions with errors (relative to the manual reference) as low as −2±5 for the geometric mean diameter and −6±5% for the geometric standard deviation of the dark particle class of the utilized data, as well as −8±4% for the geometric mean diameter and −6±2% for the geometric standard deviation of the light particle class of the utilized data. Source code, as well as training, validation, and test data publicly available.
Biochemical Principles in Prion-Based Inheritance
Authors: Dennis Emily M. , Garcia David M.
Published: January 2022

Prions are proteins that can stably fold into alternative structures that frequently alter their activities. They can self-template their alternate structures and are inherited across cell divisions and generations. While they have been studied for more than four decades, their enigmatic nature has limited their discovery. In the last decade, we have learned just how widespread they are in nature, the many beneficial phenotypes that they confer, while also learning more about their structures and modes of inheritance. Here, we provide a brief review of the biochemical principles of prion proteins, including their sequences, characteristics and structures, and what is known about how they self-template, citing examples from multiple organisms. Prion-based inheritance is the most understudied segment of epigenetics. Here, we lay a biochemical foundation and share a framework for how to define these molecules, as new examples are unearthed throughout nature.
Upward Treeline Shifts in Two Regions of Subarctic Russia Are Governed by Summer Thermal and Winter Snow Conditions
Authors: Grigoriev Andrey A. , Shalaumova Yulia V. , Vyukhin Sergey O. , Balakin Dmitriy S. , Kukarskikh Vladimir V. , Vyukhina Arina A. , Camarero Jesús Julio , Moiseev Pavel A.
Published: January 2022

Climate warming impacts on alpine treeline dynamics. However, we still lack robust assessments of the long-term impacts of climate on tree recruitment at the treeline, particularly in remote areas such as the subarctic regions of Russia subjected to different climate influences. We expected that the treelines in two regions may have different features and dynamics patterns. We analyzed climate variables and assessed treeline dynamics by quantifying recruitment using the tree rings of ca. 7000 trees of four species (Betula pubescens Ehrh. ssp. tortuosa, Pinus sylvestris L., Picea abies Ledeb. ssp. obovata, Larix gmelinii Rupr.) along 14 altitudinal transects (series of study plots). We compared the Khibiny Massif (Kola Peninsula) and the western Putorana Plateau, subjected to oceanic and continental influences, respectively. In both regions, summers became warmer, and winters became snowier during the past century. At the low part of the treeline ecotone, tree recruitment has slowly increased since the mid-18th century at the Putorana Plateau and the mid-19th century at the Khibiny but accelerated in the early 20th century at both regions and reached a maximum peak in the second half of the past century. Treeline encroachment intensified in the 1930s at the Khibiny and the 1950s at the Putorana Plateau. Trees encroached in the tundra leading to upward treeline shifts in the late 20th century. The slope exposure affected the rates of treeline shift with higher upward advances on southern-oriented slopes. Tree recruitment and early-winter precipitation were positively correlated. The differences in species composition, treeline altitude and influences of slope orientation on treeline dynamics can be explained primarily by differences in the degree of continentality. The abundance of saplings in both regions allows the future encroachment of trees into tundra and further treeline upward shifts to be forecast.
The Box Tree Moth: An Invasive Species Severely Threatening Buxus Natural Formation in NW Italy
Authors: Ferracini Chiara , Pogolotti Cristina , Mancardi Paolo , Miglio Michela , Bonelli Simona , Barbero Francesca
Published: January 2022

(1) The box tree moth (BTM), Cydalima perspectalis Walker, represents one of the recent examples of exotic insect pests native to Asia accidentally introduced in Europe by the nursery trade. In Europe, BTM develops on Buxus sempervirens L., causing significant damage to ornamental and natural plants. (2) Basic aspects of BTM biology were investigated at three sites in the NW Alps, where B. sempervirens occurs on rocky slopes, forming a protected habitat. In 2019–2021, we evaluated: (i) the seasonal flight activity with sex pheromone traps, (ii) the fecundity and the effects of food on the egg load, (iii) the potential adaptation of BTM on native secondary host plants, and (iv) the recruitment of natural enemies. (3) Our results revealed the presence of two generations per year. The number of mature eggs increased in fed adults and was higher in females of the first generation. No evidence of BTM shift on secondary plants was found in either laboratory or natural conditions, and no significant occurrence of natural enemies was recorded, except for one pupa of the tachinid Pseudoperichaeta nigrolineata. (4) Our findings provide valuable information to address and timely plan management strategies to preserve B. sempervirens as an essential component of rare forest ecosystems.
Revisiting Forest Certification in Sri Lanka: The Forest Management and Export Wood-Based Manufacturing Sector Perspectives
Authors: Perera Priyan , Rupasinghe Rajitha Lakshan , Weerasekera Devin , Vlosky Richard , Bandara Rangika
Published: January 2022

There are discussions and debates surrounding forest certification in developing countries. In this study, we surveyed 50 forest-based companies in Sri Lanka (43 wood-based manufacturers and 7 plantation companies) to ascertain their participation in forest certification, current and future forest certification trends, as well as their satisfaction with the performance of Forest Stewardship Council (FSC) certification in its economic, environmental, and social aspects, using an importance–performance analysis (IPA). Study results indicate that certified companies typically focus on exports and supplying raw materials for value-added exporters. The customer demand/signaling mechanism appears to be the primary driver of FSC certification in Sri Lanka. Forest certification was found to be helpful for companies to access new markets, keep market share, and sell products in existing markets. Results further indicate that price premiums for FSC-certified products exist, though they may not always be significant. However, certification positively influences sales volume and reduces business risks via securing continuous orders from the buyers. The IPA results further indicate that FSC certification has substantially improved company images by positioning certified companies as socially responsible businesses, while helping to create better business stakeholder relationships. FSC certification was found to have weak links in improving on-the-ground environmental performances of certified companies. Study findings have implications for the FSC certification scheme and independent certifiers, enabling them to identify the areas of FSC certification with significant performance gaps.
Identification of Aquaporin Gene Family in Response to Natural Cold Stress in Ligustrum × vicaryi Rehd.
Authors: Dong Jiahui , Niu Shance , Qian Ji , Zhou Juan , Zhao Mengnan , Meng Yu , Di Bao
Published: January 2022

Plants are susceptible to a variety of abiotic stresses during the growing period, among which low temperature is one of the more frequent stress factors. Maintaining water balance under cold stress is a difficult and critical challenge for plants. Studies have shown that aquaporins located on the cytomembrane play an important role in controlling water homeostasis under cold stress, and are involved in the tolerance mechanism of plant cells to cold stress. In addition, the aquaporin gene family is closely related to the cold resistance of plants. As a major greening tree species in urban landscaping, Ligustrum× vicaryi Rehd. is more likely to be harmed by low temperature after a harsh winter and a spring with fluctuating temperatures. Screening the target aquaporin genes of Ligustrum × vicaryi responding to cold resistance under natural cold stress will provide a scientific theoretical basis for cold resistance breeding of Ligustrum × vicaryi. In this study, the genome-wide identification of the aquaporin gene family was performed at four different overwintering periods in September, November, January and April, and finally, 58 candidate Ligustrum × vicaryi aquaporin (LvAQP) genes were identified. The phylogenetic analysis revealed four subfamilies of the LvAQP gene family: 32 PIPs, 11 TIPs, 11 NIPs and 4 SIPs. The number of genes in PIPs subfamily was more than that in other plants. Through the analysis of aquaporin genes related to cold stress in other plants and LvAQP gene expression patterns identified 20 LvAQP genes in response to cold stress, and most of them belonged to the PIPs subfamily. The significantly upregulated LvAQP gene was Cluster-9981.114831, and the significantly downregulated LvAQP genes were Cluster-9981.112839, Cluster-9981.107281, and Cluster-9981.112777. These genes might play a key role in responding to cold tolerance in the natural low-temperature growth stage of Ligustrum × vicaryi.
Differences in Environmental and Hormonal Regulation of Growth Responses in Two Highly Productive Hybrid Populus Genotypes
Authors: Žiauka Jonas , Striganavičiūtė Greta , Szyp-Borowska Iwona , Kuusienė Sigutė , Niemczyk Marzena
Published: January 2022

Phenotypic plasticity, in response to adverse conditions, determines plant productivity and survival. The aim of this study was to test if two highly productive Populus genotypes, characterised by different in vitro etiolation patterns, differ also in their responses to hormones gibberellin (GA) and abscisic acid (ABA), and to a GA biosynthesis inhibitor paclobutrazol (PBZ). The experiments on shoot cultures of ‘Hybrida 275′ (abbr. H275; Populus maximowiczii × P. trichocarpa) and IBL 91/78 (Populus tremula × P. alba) were conducted by either modulating the physical in vitro environment or by adding specific chemicals to the nutrient medium. Our results revealed two main sets of differences between the studied genotypes in environmental and hormonal regulation of growth responses. First, the genotype H275 responded to darkness with PBZ-inhibitable shoot elongation; in contrast, the elongation of IBL 91/78 shoots was not affected either by darkness or PBZ treatment. Secondly, the explants of H275 were unable to recover their growth if it was inhibited with ABA; in contrast, those of IBL 91/78 recovered so well after the temporal inhibition by ABA that, when rooted subsequently, they developed longer shoots and roots than without a previous ABA treatment. Our results indicate that GA catabolism and repressive signalling provide an important pathway to control growth and physiological adaptation in response to immediate or impending adverse conditions. These observations can help breeders define robust criteria for identifying genotypes with high resistance and productivity and highlight where genotypes exhibit susceptibility to stress.
Unlocking the Changes of Phyllosphere Fungal Communities of Fishscale Bamboo (Phyllostachys heteroclada) under Rhombic-Spot Disease Stressed Conditions
Authors: Liu Lijuan , Yang Chunlin , Xu Xiulan , Wang Xue , Liu Ming , Chen Renhua , Tan Feichuan , Liu Yufeng , Lin Tiantian , Liu Yinggao
Published: January 2022

As an important nonwood bioresource, fishscale bamboo (Phyllostachys heteroclada Oliver) is widely distributed in the subtropical region of China. Rhombic-spot disease, caused by Neostagonosporella sichuanensis, is one of the most serious diseases that threatens fishscale bamboo health. However, there is limited knowledge about how rhombic-spot disease influences the diversity and structures of phyllosphere fungal communities. In this study, we investigated the phyllosphere fungal communities from stems, branches, and leaves of fishscale bamboo during a rhombic-spot disease outbreak using 18S rRNA sequencing. We found that only the phyllosphere fungal community from stems was significantly affected by pathogen invasion in terms of community richness, diversity, and structure. FUNGuild analysis revealed that the major classifications of phyllosphere fungi based on trophic modes in stems, branches, and leaves changed from symbiotroph-pathotroph, no obvious dominant trophic mode, and symbiotroph to saprotroph, saprotroph–pathotroph–symbiotroph, and saprotroph–symbiotroph, respectively, after pathogen invasion. The fungal community composition of the three tissues displayed significant differences at the genus level between healthy and diseased plants. The associations among fungal species in diseased samples showed more complex co-occurrence network structures than those of healthy samples. Taken together, our results highlight the importance of plant pathological conditions for the assembly of phyllosphere fungal communities in different tissues.
Case Studies of the Financial Performance of Silvopastoral Systems in Southern Queensland, Australia
Authors: Francis Ben , Venn Tyron , Lewis Tom , Brawner Jeremy
Published: January 2022

There is considerable uncertainty surrounding the future availability of hardwood timber from state-owned native forests in southern Queensland. The timber industry is becoming increasingly reliant on private native forests, where much is on properties primarily managed for beef cattle grazing. Historically, these forests have been periodically high-grade harvested without silvicultural treatment or cleared to increase pasture production where landholders have the right to do so. This study compares these traditional forest management practices at four case study properties against silvopastoral system alternatives. Merchantable timber, pasture and cattle production was estimated for each management scenario with a native forest silvicultural treatment response model. The net present value of each scenario was estimated over a 20-year management period. For all case study properties, the worst-performing forest management scenario was to clear forest for grazing. Investment in silvopastoral systems in southern Queensland was found to be financially attractive, particularly when silvicultural treatments were implemented in year zero to increase timber production. Silvicultural treatments increased the mean annual increment of merchantable timber over 20 years by an average of 1.3 m3/ha/year relative to the scenario where no management was performed in year zero. Forest management scenarios with silvicultural treatments had better financial performance than scenarios without silvicultural treatment. However, long payback periods and sovereign risk are serious impediments to silvopastoral system adoption in southern Queensland. If these concerns can be overcome, private native forests have the potential to be sustainably managed to improve the financial performance of farms, improve regional employment and income generation, supply Queensland’s future hardwood timber needs, and increase carbon sequestration and biodiversity conservation on private land.
Genetic Diversity Revealed by Microsatellites in Genus Carya
Authors: Wang Xinwang , Chatwin Warren , Hilton Angelyn , Kubenka Keith
Published: January 2022

The genus Carya consists of 17 species divided into 3 sections: Carya or the true hickories, Apocarya or the pecan hickories, and Sinocarya or the Asian hickories. Interspecific hybrids exist and have been used in pecan cultivar development. Nuclear and plastid microsatellite or SSR markers have been useful in distinguishing species, sections, and populations. They provide evidence for hybridity between species and can confirm heredity within crosses. As more sophisticated methods of genomic evaluation are cooperatively developed for use in pecan breeding and selection, the use of these methods will be supplemented and informed by the lessons provided by microsatellite markers, as interpreted across broad germplasm collections. In this study, over 400 Carya accessions from diverse diploid and tetraploid taxa and their interspecific hybrids, maintained at the USDA National Collection of Genetic Resources for Carya (NCGR-Carya), were analyzed using 14 nuclear and 3 plastid microsatellite markers. Principal coordinate analysis showed clear taxonomic classifications at multiple taxonomic levels along with patterns of interspecific hybridity. Evidence was also found for genetic differences associated with geographic distribution. The results indicate that this group of markers is useful in examining and characterizing populations and hybrids in the genus Carya and may help delineate the composition of a core collection to help characterize the NCGR-Carya repository collection for use in its pecan breeding program. The SSR fingerprints of the inventories of the USDA NCGR-Carya repository can also be used as a reference for identifying unknown pecan trees for growers.
Sulfane Sulfur Compounds as Source of Reappearance of Reductive Off-Odors in Wine
Authors: Müller Nikolaus , Rauhut Doris , Tarasov Andrii
Published: January 2022

Reactive compounds with one or more sulfane sulfur atoms can be an important source of reductive off-odors in wine. These substances contain labile sulfur, which can participate in microbiological (enzymatic) and chemical transformations (including in the post-bottling period), releasing malodorous hydrogen sulfide (H2S) and its derivatives (MeSH, EtSH, etc.). The following sulfane sulfur compounds were considered in this review as important precursors in the wine chemistry of reductive aromas: elemental sulfur (S8), persulfides (R-S-S-H), polysulfanes (R-Sn-R(′)), polythionates (−O3S-Sn-SO3−), thiosulfate (S2O32−) and derivatives of (poly)sulfane monosulfonic acids (R-Sn-SO3H). This review discusses the formation of these compounds, their reactivity and chemical transformations in wine, including reactions of nucleophilic substitution. In particular, the reactions of thiolysis, thiosulfatolysis and sulfitolysis of sulfane sulfur compounds are described, which lead in the end to reductive aroma compounds. In this way, the review attempts to shed light on some of the mysteries in the field of sulfur chemistry in wine and the reappearance of reductive off-odors after bottling.
Estimation on the Importance of Semantic Web Integration for Art and Culture Related Online Media Outlets
Authors: Giannakoulopoulos Andreas , Pergantis Minas , Konstantinou Nikos , Kouretsis Alexandros , Lamprogeorgos Aristeidis , Varlamis Iraklis
Published: January 2022

Since the dawn of the new millennium and even earlier, a coordinated effort has been underway to expand the World Wide Web into a machine-readable web of data known as the Semantic Web. The field of art and culture has been one of the most eager to integrate with the Semantic Web, since metadata, data structures, linked-data, e.g., the Getty vocabularies project and the Europeana LOD initiative—and other building blocks of this web of data are considered essential in cataloging and disseminating art and culture-related content. However, art is a constantly evolving entity and as such it is the subject of a vast number of online media outlets and journalist blogs and websites. During the course of the present study the researchers collected information about how integrated the media outlets that diffuse art and culture-related content and news are to the Semantic Web. The study uses quantitative metrics to evaluate a website’s adherence to Semantic Web standards and it proceeds to draw conclusions regarding how that integration affects their popularity in the modern competitive landscape of the Web.
An IoT-Based COVID-19 Prevention and Control System for Enclosed Spaces
Authors: Yang Cunwei , Wang Weiqing , Li Fengying , Yang Degang
Published: January 2022

To date, the protracted pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had widespread ramifications for the economy, politics, public health, etc. Based on the current situation, definitively stopping the spread of the virus is infeasible in many countries. This does not mean that populations should ignore the pandemic; instead, normal life needs to be balanced with disease prevention and control. This paper highlights the use of Internet of Things (IoT) for the prevention and control of coronavirus disease (COVID-19) in enclosed spaces. The proposed booking algorithm is able to control the gathering of crowds in specific regions. K-nearest neighbors (KNN) is utilized for the implementation of a navigation system with a congestion control strategy and global path planning capabilities. Furthermore, a risk assessment model is designed based on a “Sliding Window-Timer” algorithm, providing an infection risk assessment for individuals in potential contact with patients.
A Hybrid Robust-Learning Architecture for Medical Image Segmentation with Noisy Labels
Authors: Shi Jialin , Guo Chenyi , Wu Ji
Published: January 2022

Deep-learning models require large amounts of accurately labeled data. However, for medical image segmentation, high-quality labels rely on expert experience, and less-experienced operators provide noisy labels. How one might mitigate the negative effects caused by noisy labels for 3D medical image segmentation has not been fully investigated. In this paper, our purpose is to propose a novel hybrid robust-learning architecture to combat noisy labels for 3D medical image segmentation. Our method consists of three components. First, we focus on the noisy annotations of slices and propose a slice-level label-quality awareness method, which automatically generates label-quality scores for slices in a set. Second, we propose a shape-awareness regularization loss based on distance transform maps to introduce prior shape information and provide extra performance gains. Third, based on a re-weighting strategy, we propose an end-to-end hybrid robust-learning architecture to weaken the negative effects caused by noisy labels. Extensive experiments are performed on two representative datasets (i.e., liver segmentation and multi-organ segmentation). Our hybrid noise-robust architecture has shown competitive performance, compared to other methods. Ablation studies also demonstrate the effectiveness of slice-level label-quality awareness and a shape-awareness regularization loss for combating noisy labels.
Multi-Attribute Decision Making for Energy-Efficient Public Transport Network Selection in Smart Cities
Authors: Munjal Rashmi , Liu William , Li Xuejun , Gutierrez Jairo , Chong Peter Han Joo
Published: January 2022

Smart cities use many smart devices to facilitate the well-being of society by different means. However, these smart devices create great challenges, such as energy consumption and carbon emissions. The proposed research lies in communication technologies to deal with big data-driven applications. Aiming at multiple sources of big data in a smart city, we propose a public transport-assisted data-dissemination system to utilize public transport as another communication medium, along with other networks, with the help of software-defined technology. Our main objective is to minimize energy consumption with the maximum delivery of data. A multi-attribute decision-making strategy is adopted for the selction of the best network among wired, wireless, and public transport networks, based upon users’ requirements and different services. Once public transport is selected as the best network, the Capacitated Vehicle Routing Problem (CVRP) will be implemented to offload data onto buses as per the maximum capacity of buses. For validation, the case of Auckland Transport is used to offload data onto buses for energy-efficient delay-tolerant data transmission. Experimental results show that buses can be utilized efficiently to deliver data as per their demands and consume 33% less energy in comparison to other networks.
Megafires in a Warming World: What Wildfire Risk Factors Led to California’s Largest Recorded Wildfire
Authors: Varga Kevin , Jones Charles , Trugman Anna , Carvalho Leila M. V. , McLoughlin Neal , Seto Daisuke , Thompson Callum , Daum Kristofer
Published: January 2022

Massive wildfires and extreme fire behavior are becoming more frequent across the western United States, creating a need to better understand how megafire behavior will evolve in our warming world. Here, the fire spread model Prometheus is used to simulate the initial explosive growth of the 2020 August Complex, which occurred in northern California (CA) mixed conifer forests. High temperatures, low relative humidity, and daytime southerly winds were all highly correlated with extreme rates of modeled spread. Fine fuels reached very dry levels, which accelerated simulation growth and heightened fire heat release (HR). Model sensitivity tests indicate that fire growth and HR are most sensitive to aridity and fuel moisture content. Despite the impressive early observed growth of the fire, shifting the simulation ignition to a very dry September 2020 heatwave predicted a >50% increase in growth and HR, as well as increased nighttime fire activity. Detailed model analyses of how extreme fire behavior develops can help fire personnel prepare for problematic ignitions.
Two-Phase Gas and Dust Free Expansion: Three-Dimensional Benchmark Problem for CFD Codes
Authors: Stoyanovskaya Olga P. , Grigoryev Vitaliy V. , Suslenkova Anastasiya N. , Davydov Maxim N. , Snytnikov Nikolay V.
Published: January 2022

In the computational mechanics of multiphase dispersed flows, there is an issue of computing the interaction between phases in a mixture of a carrier fluid and dispersed inclusions. The problem is that an accurate dynamics simulation of a mixture of gas and finely dispersed solids with intense interphase interaction requires much more computational power compared to pure gas or a mixture with moderate interaction between phases. To tackle this problem, effective numerical methods are being searched for to ensure adequate computational cost, accuracy, and stability of the results at an arbitrary intensity of momentum and energy exchange between phases. Thus, to assess the approximation, dispersive, dissipative, and asymptotic properties of numerical methods, benchmark solutions of relevant test problems are required. Such solutions are known for one-dimensional problems with linear plane waves. We introduce a novel analytical solution for the nonlinear problem of spherically symmetric expansion of a gas and dust ball into a vacuum. Therein, the dynamics of carrier and dispersed phases are modeled using equations for a compressible inviscid gas. Solid particles do not have intrinsic pressure and are assumed to be monodisperse. The carrier and dispersed phases exchange momentum. In the derived solution, the velocities of gas and dust clouds depend linearly on the radii. The results were reproduced at high, moderate, and low momentum exchange between phases using the SPH-IDIC (Smoothed Particle Hydrodynamics with Implicit Drag in Cell) method implemented based on the open-source OpenFPM library. We reported an example of using the solution as a benchmark for CFD (computational fluid dynamics) models verification and for the evaluation of numerical methods. Our benchmark solution generator developed in the free Scilab environment is publicly available.
Computational Analysis of Actuation Techniques Impact on the Flow Control around the Ahmed Body
Authors: Edwige Stéphie , Gilotte Philippe , Mortazavi Iraj
Published: January 2022

Active flow control with jet devices is a promising approach for vehicle aerodynamics control. In this work an extended computational study is performed comparing three different actuation strategies for active flow control around the square back Ahmed body at Reynolds number 500,000 (based on the vehicle height). Numerical simulations are run using a Large Eddy Simulation (LES) approach, well adapted to calculate the unsteady high Reynolds number flow control using periodic jet devices. computations are validated comparing to in-house experiments for uncontrolled and some controlled cases. The novelty of this investigation is mainly related to the in-depth study of the base flow and actuation approaches by an accurate LES method and their comparison to experiments. Here, several simulations are performed to estimate the effect of active controls on the flow topology and the drag reduction. Beside the continuous blowing jet, three periodic actuation techniques including periodic blowing and suction as well as the zero flux synthetic jet devices are explored. The slots are implemented discontinuously in order to achieve a better control efficiency linked to vortex generation. In this framework, spectral analyses on global aerodynamical quantities, rear pressure/drag coefficient behavior examination as well as wake structure investigations are performed in order to compare these jet actuations. As a result, shear layer variations are observed during the blowing phase, but the main flow topology change occurs with suction and synthetic jets. Rear back pressure is therefore substantially increased.
Experimental Investigation on Heat Transfer Enhancement with Passive Inserts in Flat Tubes in due Consideration of an Efficiency Assessment
Authors: Bertsche Dirk , Knipper Paul , Meinicke Sebastian , Dubil Konrad , Wetzel Thomas
Published: January 2022

This paper presents results of an experimental investigation on pressure drop and heat transfer for a wide range of Reynolds and Prandtl numbers ranging from 8 < Pr < 60 and 40 < Re < 3500, for flat tubes without and with passive inserts. For three different kinds of passive insert designs, the impact on heat and momentum transfer due to coaction of the total set of passive inserts with different shape and amount was investigated. Experimental results were analyzed regarding two main aspects: Heat transfer mechanisms and pressure drop induced by friction and form drag forces due to the presence of different shapes. After heat and momentum transfer mechanisms for each passive insert design were analyzed, heat transfer and pressure drop enhancement were compared to each other, leading to an efficiency discussion. Different concepts for efficiency evaluation, which are cited in literature, were applied to the presented experimental data. Pros and cons of the different concepts are discussed. Finally, we propose an equation for evaluation of total performance, which fully respects the energetic and exergetic aspects of heat transfer and pressure drop enhancement.
A Direct-Forcing Immersed Boundary Method for Incompressible Flows Based on Physics-Informed Neural Network
Authors: Huang Yi , Zhang Zhiyu , Zhang Xing
Published: January 2022

The application of physics-informed neural networks (PINNs) to computational fluid dynamics simulations has recently attracted tremendous attention. In the simulations of PINNs, the collocation points are required to conform to the fluid–solid interface on which no-slip boundary condition is enforced. Here, a novel PINN that incorporates the direct-forcing immersed boundary (IB) method is developed. In the proposed IB-PINN, the boundary conforming requirement in arranging the collocation points is eliminated. Instead, velocity penalties at some marker points are added to the loss function to enforce no-slip condition at the fluid–solid interface. In addition, force penalties at some collocation points are also added to the loss function to ensure compact distribution of the volume force. The effectiveness of IB-PINN in solving incompressible Navier–Stokes equations is demonstrated through the simulation of laminar flow past a circular cylinder that is placed in a channel. The solution obtained using the IB-PINN is compared with two reference solutions obtained using a conventional mesh-based IB method and an ordinary body-fitted grid method. The comparison indicates that the three solutions are in excellent agreement with each other. The influences of some parameters, such as weights for different loss components, numbers of collocation and marker points, hyperparameters in the neural network, etc., on the performance of IB-PINN are also studied. In addition, a transfer learning experiment is conducted on solving Navier–Stokes equations with different Reynolds numbers.
Derivative-Free Kurchatov-Type Accelerating Iterative Method for Solving Nonlinear Systems: Dynamics and Applications
Authors: Wang Xiaofeng , Chen Xiaohe
Published: January 2022

Two novel Kurchatov-type first-order divided difference operators were designed, which were used for constructing the variable parameter of three derivative-free iterative methods. The convergence orders of the new derivative-free methods are 3, (5+17)/2≈4.56 and 5. The new derivative-free iterative methods with memory were applied to solve nonlinear ordinary differential equations (ODEs) and partial differential equations (PDEs) in numerical experiments. The dynamical behavior of our new methods with memory was studied by using dynamical plane. The dynamical planes showed that our methods had good stability.
Robust Stability of Fractional Order Memristive BAM Neural Networks with Mixed and Additive Time Varying Delays
Authors: Han Xiuping , Hymavathi M. , Sanober Sumaya , Dhupia Bhawna , Syed Ali M.
Published: January 2022

This paper is concerned with the problem of the robust stability of fractional-order memristive bidirectional associative memory (BAM) neural networks. Based on Lyapunov theory, fractional-order differential inequalities and linear matrix inequalities (LMI) are applied to obtain a robust asymptotical stability. Finally, numerical examples are presented.
Generalized p-Convex Fuzzy-Interval-Valued Functions and Inequalities Based upon the Fuzzy-Order Relation
Authors: Khan Muhammad , Treanțǎ Savin , Budak Hüseyin
Published: January 2022

Convexity is crucial in obtaining many forms of inequalities. As a result, there is a significant link between convexity and integral inequality. Due to the significance of these concepts, the purpose of this study is to introduce a new class of generalized convex interval-valued functions called (p,s)-convex fuzzy interval-valued functions ((p,s)-convex F-I-V-Fs) in the second sense and to establish Hermite–Hadamard (H–H) type inequalities for (p,s)-convex F-I-V-Fs using fuzzy order relation. In addition, we demonstrate that our results include a large class of new and known inequalities for (p,s)-convex F-I-V-Fs and their variant forms as special instances. Furthermore, we give useful examples that demonstrate usefulness of the theory produced in this study. These findings and diverse approaches may pave the way for future research in fuzzy optimization, modeling, and interval-valued functions.
Cardiovascular Circulatory System and Left Carotid Model: A Fractional Approach to Disease Modeling
Authors: Traver José Emilio , Nuevo-Gallardo Cristina , Tejado Inés , Fernández-Portales Javier , Ortega-Morán Juan Francisco , Pagador J. Blas , Vinagre Blas M.
Published: January 2022

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, according to recent reports from the World Health Organization (WHO). This fact encourages research into the cardiovascular system (CVS) from multiple and different points of view than those given by the medical perspective, highlighting among them the computational and mathematical models that involve experiments much simpler and less expensive to be performed in comparison with in vivo or in vitro heart experiments. However, the CVS is a complex system that needs multidisciplinary knowledge to describe its dynamic models, which help to predict cardiovascular events in patients with heart failure, myocardial or valvular heart disease, so it remains an active area of research. Firstly, this paper presents a novel electrical model of the CVS that extends the classic Windkessel models to the left common carotid artery motivated by the need to have a more complete model from a medical point of view for validation purposes, as well as to describe other cardiovascular phenomena in this area, such as atherosclerosis, one of the main risk factors for CVDs. The model is validated by clinical indices and experimental data obtained from clinical trials performed on a pig. Secondly, as a first step, the goodness of a fractional-order behavior of this model is discussed to characterize different heart diseases through pressure–volume (PV) loops. Unlike other models, it allows us to modify not only the topology, parameters or number of model elements, but also the dynamic by tuning a single parameter, the characteristic differentiation order; consequently, it is expected to provide a valuable insight into this complex system and to support the development of clinical decision systems for CVDs.
Development and Evaluation of Liquid Plaster Loaded with Chromolaena odorata Leaf Extract Endowed with Several Beneficial Properties to Wound Healing
Authors: Sangnim Tanikan , Meeboon Parinya , Phongsewalak Parinda , Prasongdee Parichat , Sriamornsak Pornsak , Singh Inderbir , Manmuan Suwisit , Huanbutta Kampanart
Published: January 2022

Liquid plaster (LP) is a recently developed wound dressing product that can be used to cover wounds in various parts of the body, especially small injuries or wounds in body parts involved in movement. Given the benefits and applications of LP, this study aimed to develop and evaluate Chromolaena odorata extract-loaded LP with antimicrobial and hemostasis effects. The study was first conducted through the extraction of Choromolaena odorata leaf by using an ethanol maceration technique and identification of the compounds with high-performance liquid chromatography. The LP loaded with Chromolaena odorata extract demonstrates an ability to inhibit S. aureus and S. epidermidis at a MIC of 0.25 mg/mL and MBC of 0.5 mg/mL. The antioxidant activity test was performed by ABTS and DPPH methods demonstrating the free-radical scavenging activity of the extract. The blood clotting activity was established by varying the concentration of Choromolaena odorata leaf extract from 0.0625 mg/mL to 1 mg/mL. The formulation of the film-forming system was developed by varying the solvent, polymer, and plasticizer proportions. The optimum formulation displayed fast film-forming with high elasticity of the film. Moreover, the 20 mg/mL herbal extract-loaded LP provided an antibacterial effect with admissible water vapor transmission and low skin irritation. As a result, the study demonstrates the possibility of introducing the Chromolaena odorata extract-loaded LP to increase the effectiveness of wound healing and the antibacterial effect on the skin.