bluuebunny/crossref_metadata_2025 huggingface dataset:
Punica granatum as Anticandidal and Anti-HIV Agent: An HIV Oral Cavity Potential Drug
Authors: Huerta-Reyes Maira , Gaitán-Cepeda Luis A. , Sánchez-Vargas Luis O.
Published: October 2022

The oral cavity is crucial from diagnosis to adherence to HAART therapy in the HIV/AIDS population; consequently, drugs that can maintain healthy conditions in the oral cavity are necessary for patients with HIV/AIDS. Punica granatum (pomegranate) is a tree that has been employed extensively for centuries in the traditional medicine of ancient cultures for the treatment of a wide range of diseases, including oral and dental diseases. In recent decades, its potent anticandidal properties have been shown, especially on Candida albicans, the cause of the most common clinical manifestation in HIV patients. The present work contributes to the review of the anti-HIV and anticandidal properties of the plant species P. granatum as involved with the oral cavity. The literature reviewed revealed that crude extracts of pomegranate and its main isolated compounds possess inhibitory activity on different HIV targets, including binding viral proteins and the three replicative HIV enzymes. In addition, in the literature reviewed, pomegranate exhibited anticandidal effects on 10 different species. Thus, pomegranate appears to be an excellent candidate to explore and incorporate into the treatment of the oral cavity of HIV/AIDS patients, in that, in addition to its pharmacological effects such as antiviral and anticandidal, pomegranate represents an easily available, inexpensive, and safe natural source.
Genome-Wide Association Study for Agro-Morphological Traits in Eggplant Core Collection
Authors: Ro Nayoung , Haile Mesfin , Kim Bichsaem , Cho Gyu-Taek , Lee Jungro , Lee Yoon-Jung , Hyun Do
Published: October 2022

Eggplant is one of the most economically and nutritionally important vegetables worldwide. The study of the association of phenotypic traits with genetic factors is vital for the rapid and efficient identification and selection of eggplant genetic resources for breeding purposes with desired traits. The eggplant resources (587) collected from different countries, including Korea, were used for establishing the core collection. A total of 288 accessions were selected from 587 Solanum accessions based on 52 single nucleotide polymorphisms (SNPs) markers together with 17 morphological traits. This core collection was further used to analyze the genetic associations of eggplant morphological variations. A large variation was found among the evaluated eggplant accessions for some agro-morphological traits. Stem prickles and leaf prickles showed a significant positive correlation (r = 0.83***), followed by days to flowering and days to maturity (r = 0.64***). A total of 114,981 SNPs were filtered and used for phylogenetic tree analysis, population structure analysis, and genome-wide association study (GWAS). Among the agro-morphological traits, significantly associated SNPs were found for six traits. A total of 377 significantly associated SNPs with six agro-morphological traits were identified. These six traits and the number of SNPs were: days to maturity (51), flower size (121), fruit width (20), harvest fruit color (42), leaf prickles (38), and stem prickles (105). The largest fraction of significant SNPs (11.94%) was obtained on chromosome Ch01, followed by Ch07 and Ch06 with 11.67% and 10.08%, respectively. This study will help to develop markers linked to the most important agro-morphological traits of eggplant genetic resources and support the selection of desirable traits for eggplant breeding programs.
Ground Vegetation in Pinus sylvestris Forests at Different Successional Stages following Clear Cuttings: A Case Study
Authors: Gustienė Dovilė , Varnagirytė-Kabašinskienė Iveta , Stakėnas Vidas
Published: October 2022

The impact of intensive forestry on various components of ecosystems has become the main subject of public and scientific debate in many regions in recent years. Forest ground vegetation is considered one of the most consistent and biodiversity-rich indicators of a certain stage of successional forest development. Therefore, changes in this forest component can potentially show the risks of forest damage due to clear-cutting and recovery trends. This study was carried out to identify the ground vegetation species diversity, including species composition and cover, also ground vegetation species relations with organic layer (forest floor) and upper mineral soil parameters at the different successional stages of the Pinus sylvestris L. stand development, including 1–2-year-old clear-cuts, and 6–130 years old stands. This study identified that the herb and dwarf shrub species were more light-demanding in the 2-year-old clear-cuts, as well as in the 6-year and 10-year old P. sylvestris stands compared to the middle-aged and mature forest stands. The dominant ground vegetation species, characteristic for the Pinetum vaccinio-myrtillosum forest type, were negatively dependent on the forest floor mass; they also had negative correlations with the concentrations of total P, K, Ca, and Mg in the forest floor and upper mineral soil but had positive correlations with the soil pH values and total N. The developed regression models of the percentage cover of mosses, herbs and dwarf shrubs according to the P. sylvestris stand age highlight the stabilization of the increase in the moss cover about 30 years after clear-cutting, with no clear trend for vascular species. The herbs and dwarf shrub species were highly variable during the stand rotation due to the species-specific characteristics and random factors rather than due to the influence of stand age. In this study, relatively short-term changes in ground vegetation species composition and percentage cover were determined after clear-cutting, but an important aspect is that new ground vegetation species appeared in the open areas, creating the potential for increasing species diversity. The clear-cutting system supports different species and numbers of herbs and mosses at different stages of stand development, which potentially increases the overall vegetation species diversity of the ecosystem.
Photosynthetic Apparatus of Hydrocharis morsus-ranae in Different Solar Lighting
Authors: Kordyum Elizabeth , Polishchuk Oleksandr , Akimov Yuri , Brykov Vasyl
Published: October 2022

Hydrocharis morsus-ranae is a free-floating species growing in lakes and slow-flowing rivers near the shore in Europe and Western Asia, and as an invasive plant in the USA and Canada. Light-requiring plants of this species can also grow in the shade, up to about 30% of full sunlight. In this paper we present the data about the photosynthetic apparatus of sunny and shady H. morsus-ranae plants grown in the sun and in the shade in nature. Methods of light and transmission electron microscopy, biochemistry, chlorophyll fluorescence induction as well as the principal component analysis were used. It was found that leaves of plants growing in shade differed from those in the sun with such traits as thickness of a blade, palisade and spongy parenchyma, ultrastructure of chloroplasts, and quantum efficiency of photosynthetic electron transport, the content of chlorophylls and carotenoids, anthocyanins and phenilpropanoids. By these traits, H. morsus-ranae shady plants are similar with shade-bearing plants that indicates their adaptation to light intensity lowering. The ordination plots (PCA) suggested a clear structural and functional shift of plants growing in different lighting showing relationship to light changes in the natural environment. Thus, our results displayed the high phenotypic plasticity of the H. morsus-ranae photosynthetic apparatus, which ensures its acclimation to changing light environment and wide distribution of this species.
Improved Bioherbicidal Efficacy of Bipolaris eleusines through Herbicide Addition on Weed Control in Paddy Rice
Authors: Zhang Jianping , Duan Guifang , Yang Shuang , Yu Liuqing , Lu Yongliang , Tang Wei , Yang Yongjie
Published: October 2022

Bipolaris eleusines was mixed with herbicides to improve the control of barnyardgrass (Echinochloa crus-galli), a noxious weed in rice fields. The compatibility of B. eleusines with herbicides was evaluated for toxic effects on spore germination and mycelium growth in vitro tests, and varied effects were observed with different chemical products. Briefly, 25 g/L penoxsulam OD plus 10% bensulfuron-methyl WP were much more compatible with B. eleusines, and there was no inhibition of spore germination but the promotion of mycelium growth of B. eleusines at all treatment rates. Under greenhouse conditions, the coefficient of the specificity of B. eleusines conidial agent was determined as 3.91, closer to the herbicidal control of 2.89, showing it is highly specific between rice and barnyardgrass. Field experiments in 2011 and 2012 showed that B. eleusines conidial agent displayed good activity on barnyardgrass, monochoria [Monochoria vaginalis (Burm.f.) Presl. Ex Kunth.], and small-flower umbrella sedge (Cyperus difformis L.) and had no negative impact on the rice plant. It also reduced the loss of rice yield when compared with the non-treated control and could make this pathogen a conidial agent for commercial bioherbicidal development in the future.
Pea Breeding for Resistance to Rhizospheric Pathogens
Authors: Wohor Osman Z. , Rispail Nicolas , Ojiewo Chris O. , Rubiales Diego
Published: October 2022

Pea (Pisum sativum L.) is a grain legume widely cultivated in temperate climates. It is important in the race for food security owing to its multipurpose low-input requirement and environmental promoting traits. Pea is key in nitrogen fixation, biodiversity preservation, and nutritional functions as food and feed. Unfortunately, like most crops, pea production is constrained by several pests and diseases, of which rhizosphere disease dwellers are the most critical due to their long-term persistence in the soil and difficulty to manage. Understanding the rhizosphere environment can improve host plant root microbial association to increase yield stability and facilitate improved crop performance through breeding. Thus, the use of various germplasm and genomic resources combined with scientific collaborative efforts has contributed to improving pea resistance/cultivation against rhizospheric diseases. This improvement has been achieved through robust phenotyping, genotyping, agronomic practices, and resistance breeding. Nonetheless, resistance to rhizospheric diseases is still limited, while biological and chemical-based control strategies are unrealistic and unfavourable to the environment, respectively. Hence, there is a need to consistently scout for host plant resistance to resolve these bottlenecks. Herein, in view of these challenges, we reflect on pea breeding for resistance to diseases caused by rhizospheric pathogens, including fusarium wilt, root rots, nematode complex, and parasitic broomrape. Here, we will attempt to appraise and harmonise historical and contemporary knowledge that contributes to pea resistance breeding for soilborne disease management and discuss the way forward.
Correction: Gajurel et al. Production and Secretion of Isowighteone in Hairy Root Cultures of Pigeon Pea (Cajanus cajan) Co-Treated with Multiple Elicitors. Plants 2022, 11, 834
Authors: Gajurel Gaurav , Nopo-Olazabal Luis , Hendrix Emily , Medina-Bolivar Fabricio
Published: October 2022

In the original publication [...]
Classification of Corn Diseases from Leaf Images Using Deep Transfer Learning
Authors: Fraiwan Mohammad , Faouri Esraa , Khasawneh Natheer
Published: October 2022

Corn is a mass-produced agricultural product that plays a major role in the food chain and many agricultural products in addition to biofuels. Furthermore, households in poor countries may depend on small-scale corn cultivation for their basic needs. However, corn crops are vulnerable to diseases, which greatly affects farming yields. Moreover, extreme weather conditions and unseasonable temperatures can accelerate the spread of diseases. The pervasiveness and ubiquity of technology have allowed for the deployment of technological innovations in many areas. Particularly, applications powered by artificial intelligence algorithms have established themselves in many disciplines relating to image, signal, and sound recognition. In this work, we target the application of deep transfer learning in the classification of three corn diseases (i.e., Cercospora leaf spot, common rust, and northern leaf blight) in addition to the healthy plants. Using corn leaf image as input and convolutional neural networks models, no preprocessing or explicit feature extraction was required. Transfer learning using well-established and well-designed deep learning models was performed and extensively evaluated using multiple scenarios for splitting the data. In addition, the experiments were repeated 10 times to account for variability in picking random choices. The four classes were discerned with a mean accuracy of 98.6%. This and the other performance metrics exhibit values that make it feasible to build and deploy applications that can aid farmers and plant pathologists to promptly and accurately perform disease identification and apply the correct remedies.
Effects of an Isobutylene–Maleic Anhydride Copolymer on the Rheological Behavior and Early Hydration of Natural Hydraulic Lime
Authors: Wei Xiaohong , Li Yunfeng , Hui Jing , Wang Wenwen , Zhang Biao , Chang Liangliang , Jiao Yuhong , Sang Zhen , Luo Hongjie , Wang Xiufeng
Published: October 2022

Natural hydraulic lime (NHL) is a cementitious material widely used in the restoration of stone cultural relics and maintenance of historic buildings, the practical use of which is mainly hindered by its poor fluidity. Due to the multilayer (double-layer) adsorption that isobutylene–maleic anhydride (IBMA) has on the surface of NHL, the effects that IBMA copolymer have on the fluidity and hydration of NHL were thus investigated. Moreover, the yield stress and plastic viscosity of NHL pastes were found to be reduced significantly by the incorporation of IBMA. Combined with the effects of electrostatic repulsion and steric hindrance, the flocculated structures in NHL pastes were gradually dismantled, releasing the trapped water and leading to a significant enhancement in the fluidity of NHL. IBMA was found to postpone the early hydration of NHL. In particular, it showed that adding specific content of IBMA can significantly improve the early strength of NHL.
High-Transparency and Colorless Polyimide Film Prepared by Inhibiting the Formation of Chromophores
Authors: Su Chuanxiang , Liu Pengjia , Yue Jingyu , Huan Hengjian , Yang Zhenghui , Yang Kai , Guo Haiquan , Zhao Jianying
Published: October 2022

Colorless polyimides (CPIs) with outstanding mechanical properties are essential materials in the production of flexible display panels, foldable windows, and even spacecraft cockpits. This paper specifically elaborates that the Morkit unit, and azo and nitro chromophores are important factors contributing to yellow PI, together with the well-known charge transfer complex (CTC) theory. Three diamine monomers, two anhydrides monomers, and three blockers were used to inhibit chromophores formation and, thus, obtain CPI films. The cut-off wavelength was blue-shifts to 334 nm and the transmittance is improved to 98.9% in the UV–vis range. Mechanical and thermal properties of the CPI films are not reduced through coupling effects of the blockers. Therefore, the inhibition method of the Morkit units and chromophore groups is a promising process for preparing CPIs to be used as flexible display materials.
Recent Advances in the Removal of Organic Dyes from Aqueous Media with Conducting Polymers, Polyaniline and Polypyrrole, and Their Composites
Authors: Stejskal Jaroslav
Published: October 2022

Water pollution by organic dyes, and its remediation, is an important environmental issue associated with ever-increasing scientific interest. Conducting polymers have recently come to the forefront as advanced agents for removing dye. The present review reports on the progress represented by the literature published in 2020–2022 on the application of conducting polymers and their composites in the removal of dyes from aqueous media. Two composites, incorporating the most important polymers, polyaniline, and polypyrrole, have been used as efficient dye adsorbents or photocatalysts of dye decomposition. The recent application trends are outlined, and future uses also exploiting the electrical and electrochemical properties of conducting polymers are offered.
Durability against Wetting-Drying Cycles of Sustainable Biopolymer-Treated Soil
Authors: Soldo Antonio , Miletic Marta
Published: October 2022

The world today is more oriented towards sustainable and environmental-friendly solutions in every field of science, technology, and engineering. Therefore, novel sustainable and eco-friendly approaches for soil improvement have also emerged. One of the effective, promising, and green solutions is the utilization of biopolymers. However, even though the biopolymers proved to be effective in enhancing the soil-mechanical properties, it is still unknown how they behave under real environmental conditions, such as fluctuating temperatures, moisture, plants, microorganisms, to name a few. The main research aim is to investigate the durability of biopolymer-improved soil on the cyclic processes of wetting and drying. Two types of biopolymers (Xanthan Gum and Guar Gum), and two types of soils (clean sand and silty sand) were investigated in this study. The results indicated that some biopolymer-amended specimens kept more than 70% of their original mass during wetting-drying cycles. During the compressive strength analysis, some biopolymer-treated specimens kept up to 45% of their initial strength during seven wetting-drying cycles. Furthermore, this study showed that certain damaged soil-biopolymer bonds could be restored with proper treatment. Repeating the process of wetting and drying can reactivate the bonding properties of biopolymers, which amends the broken bonds in soil. The regenerative property of biopolymers is an important feature that should not be neglected. It gives a clearer picture of the biopolymer utilization and makes it a good option for rapid temporary construction or long-standing construction in the areas with an arid climate.
Improving Deproteinization in Colombian Latex from Hevea brasiliensis: A Bibliometric Approximation
Authors: Hernandez-Tenorio Fabian , Arroyave-Miranda Héctor , Miranda Alejandra M. , González Sandra M. , Rodríguez Carlos A. , Sáez Alex A.
Published: October 2022

Natural Rubber Field Latex (NRFL) allergens restrict its use in some markets due to health-threatening allergic reactions. These molecules are proteins that are related to asymptomatic sensitization and hypersensitivity mediated by immunoglobulin E (IgE). Although NRFL allergens have been investigated since the 1980s, there are still gaps in knowledge regarding the development of deproteinized natural rubber (DPNR). Therefore, in this study, the deproteinization of NRFL from the lower basin of the Cauca River, Antioquia-Colombia was evaluated using eight systems. The highest removal value was 84.4% and was obtained from the treatment containing SDS (Sodium dodecyl sulfate), Urea, and Ethanol. It was also possible to determine that at high concentrations of SDS, removal percentages higher than 70% are reached. On the other hand, all deproteinizing systems decreased NRFL Zeta potentials without self-coagulation, suggesting enhanced colloidal stability in DPNR latex. On the other hand, the bibliometric analysis presented technological advances in DPRN through different parameters and bibliometric networks. The analysis presented makes an important contribution from the bibliometric approach that could be positive for the development of research on DPNR.
Toward Thermochromic VO2 Nanoparticles Polymer Films Based Smart Windows Designed for Tropical Climates
Authors: Murillo-Quirós Natalia , Vega-Garita Victor , Carmona-Calvo Antony , Rojas-González Edgar A. , Starbird-Perez Ricardo , Avendaño-Soto Esteban
Published: October 2022

Thermochromic smart windows have been extensively investigated due to two main benefits: first, the comfort for people in a room through avoiding high temperatures resulting from solar heating while taking advantage of the visible light, and second, the energy efficiency saving offered by using those systems. Vanadium dioxide (VO2) is one of the most used materials in the development of thermochromic devices. The countries located in the tropics show little use of these technologies, although studies indicate that due to their characteristics of solar illumination and temperature, they could benefit greatly. To optimize and achieve maximum benefit, it is necessary to design a window that adjusts to tropical conditions and at the same time remains affordable for extensive implementation. VO2 nanoparticles embedded in polymeric matrices are an option, but improvements are required by means of studying different particle sizes, dopants and polymeric matrices. The purpose of this review is to analyze what has been regarding toward the fabrication of smart windows based on VO2 embedded in polymeric matrices for tropical areas and provide a proposal for what this device must comply with to contribute to these specific climatic needs.
Influence of Ulluco Starch Modified by Annealing on the Physicochemical Properties of Biodegradable Films
Authors: Daza Luis Daniel , Parra Daniela O. , Rosselló Carmen , Arango Walter Murillo , Eim Valeria Soledad , Váquiro Henry Alexander
Published: October 2022

This work aimed to evaluate the use of annealing (ANN) ulluco starch in the preparation of biodegradable films and its impact on the physicochemical properties of the materials. Three film samples (FS1, FS2, and FS3) were prepared at a fixed starch concentration (2.6% w/v) using glycerol as a plasticizer and then compared to a control sample (FSC) prepared with native ulluco starch. The physical, mechanical, and thermal properties of the films were evaluated. The use of ANN starch decreased the solubility (from 21.8% to 19.5%) and the swelling power (from 299% to 153%) of the film samples. In addition, an increase in opacity and relative crystallinity (from 7.54% to 10.5%) were observed. Regarding the thermal properties, all the samples presented high stability to degradation, with degradation temperatures above 200 °C. However, the samples showed deficiencies in their morphology, which affected the barrier properties. The use of ANN starch has some advantages over native starch in preparing films. However, more analysis is needed to improve the barrier properties of the materials. This work reveals the potential of the ANN ulluco starch for biodegradable film preparation. In addition, the use of modified ulluco starch is an alternative to add value to the crop, as well as to replace non-biodegradable materials used in the preparation of packaging.
The Influence of Personality Traits on Specific Coping Styles and the Development of Posttraumatic Stress Symptoms following Acute Coronary Syndrome: A Cluster Analytic Approach
Authors: Princip Mary , von Känel Roland , Zuccarella-Hackl Claudia , Meister-Langraf Rebecca E. , Znoj Hansjörg , Schmid Jean-Paul , Barth Jürgen , Schnyder Ulrich , Jimenez-Gonzalo Lucia , Ledermann Katharina
Published: October 2022

Objective: A growing body of literature suggests a relationship between personality traits and posttraumatic stress disorder (PTSD) symptoms after acute coronary events (ACS). However, specific personality profiles have not been examined in patients after ACS. Thus, the aim of the present study was to examine personality profiles created from response patterns on the resilience, alexithymia and type D personality (TDP) scales and to examine associations with PTSD symptoms, symptom clusters and coping styles among a sample of ACS patients. Methods: A cluster analytic approach was utilized to identify risk profiles based on personality variables and a series of ANOVAs in 154 patients. Post hoc analyses were conducted to examine the relationship between each profile, and interviewer-rated PTSD symptoms and different coping styles. Results: The analyses indicated a three-cluster solution, including low- (high resilience, low alexithymia and non-TDP), medium- (average resilience, average alexithymia and non-TDP) and high-risk (low resilience, high alexithymia and TDP) profiles. Clusters differed significantly in all three coping subscales. At 3-month follow up, clusters differed significantly in all three PTSD subscales (re-experiencing, avoidance and hyperarousal). At 12-month follow up, the differences remained significant for the hyperarousal subscale only. Conclusions: The personality profiles identified and the respective associations to PTSD symptoms and coping strategies highlight the potential impact for the psychological adjustment following ACS.
The Apocalypse as a Cosmotheandric Communion: A Hindu-Christian Dialogue
Authors: Dixit Shruti
Published: October 2022

Theologians have been engaged in the reflections of the eschatological in the social and moral conditions of the world for some years now, but the emphasis on the indisputable need for an interfaith dialogue at such a moment is evidently absent. Arguably, the apocalyptic times of pandemic, induced communal hatred, bilateral hostility, and racial discriminations, on a global level, which are also accompanied with many instances by increased charitable behavior and a heightened sense of human responsibility. This paper focuses on apocalyptic theologies in the context of Hindu and Christian settings in India and how they interact, creating the possibility for an interfaith dialogue. Based on Raimon Panikkar’s neologism ‘cosmotheandric vision,’ the paper establishes a relation between intercultural theologies and interfaith dialogue. The apocalypse can be studied as being a constant reminder of the cosmotheandric nature of the universe, for Hindus and Christians alike, fostering a dialogue between the two religions, entirely cognizant of their hermeneutical differences. The moment of apocalypse can be analyzed as a point of cosmotheandric union and absolute togetherness, wherein cultural and religious differences disappear with the consciousness of the whole, the One.
Valorizations of Marigold Waste for High-Value Products and Their Industrial Importance: A Comprehensive Review
Authors: Chauhan Ajeet Singh , Chen Chiu-Wen , Singhania Reeta Rani , Tiwari Mansi , Sartale Rijuta Ganesh , Dong Cheng-Di , Patel Anil Kumar
Published: October 2022

The municipal authorities in developing nations face serious challenges in marigold flower garbage management. The primary issue is that they never are reused after prayers. Flower waste of Tagetes erecta, T. patula, and Calendula officinalis L. are commonly used for carotenoid and flavonoid extractions and, subsequently, used for incense stick and biogas production. Marigold plants are also used for phytoremediation during their growth stage. The lutein industry is booming due to its increasing market demand, expected to reach ~2121.2 billion tons by 2022, where marigolds are a major contributor globally. The process of isolating lutein from saponified marigold oleoresin yields a product with 70–85% purity. Lutein is a major xanthophyll (70–88%) of marigold petals, and a maximum of 21.23 mg/g of lutein was extracted. This review discusses the properties of selective marigold species, their compositions, and the extraction of different flavonoids and carotenoids, especially lutein. Moreover, different extraction methods of marigold lutein, the collection of marigold waste, and their subsequent utilization to derive several value-added products are discussed. Among physical treatments, ultrasonic-assisted extraction and enzymatic treatment with 5% solids loading were the maximum-yielding methods.
Criteria for Selecting Areas to Identify Ecosystem Services Provided by Geodiversity: A Study on the Coast of São Paulo, Brazil
Authors: Queiroz Debora Silva , Garcia Maria da Glória Motta , Pereira Paulo
Published: October 2022

Ecosystem services are essential for life. Despite traditionally focusing on biodiversity, several studies have presented the ecosystem services provided by geodiversity. However, the choice of the study area is still a step that raises doubts for the researcher. Several elements of geodiversity must occur in the area so that different ecosystem services can be identified. Thus, the selection of the study area is a crucial step of the research. This work aims to determine the criteria for the selection of potential areas for the identification of ecosystem services by geodiversity in Baixada Santista, central coast of São Paulo, Brazil. The criteria established were (i) characterization of the physical environment based on the geodiversity index map and the watershed map and (ii) description of land use based on the characterization of land use and analysis of territorial planning instruments. As a result, the watershed with high levels of geodiversity and diversity of land uses was selected. The criterion was important, as it is an area already used in soil management and different land uses can provide a variety of ecosystem services. Thus, these criteria proved to be effective in the selection of areas for the evaluation of ecosystem services by geodiversity.
Flood Vulnerability Assessment and Mapping: A Case Study for Australia’s Hawkesbury-Nepean Catchment
Authors: Schwarz Imogen , Kuleshov Yuriy
Published: October 2022

Floods are one of the most destructive natural hazards to which Australia is exposed. The frequency of extreme rainfall events and consequential floods are projected to increase into the future as a result of anthropogenic climate change. This highlights the need for more holistic risk assessments of flood affected regions. Flood risk assessments (FRAs) are used to inform decision makers and stakeholders when creating mitigation and adaptation strategies for at-risk communities. When assessing flood risk, previous FRAs from Australia’s most flood prone regions were generally focused on the flood hazard itself, and rarely considering flood vulnerability (FV). This study assessed FV in one of Australia’s most flood prone regions—the Hawkesbury-Nepean catchment, and investigated indicator-based approaches as a proxy method for Australian FV assessment instead of hydrological modelling. Four indicators were selected with the intention of representing environmental and socio-economic characteristics: elevation, degree of slope, index of relative socio-economic disadvantage (IRSD), and hydrologic soil groups (HSGs). It was found that combination of low elevation, low degree of slope, low IRSD score, and very-low infiltration soils resulted in very high levels of vulnerability. FV was shown to be at its highest in the Hawkesbury-Nepean valley flood plain region on the outskirts of Greater Western Sydney, particularly in Blacktown, Penrith, and Liverpool. This actionable risk data which resulted from the final FV index supported the practicality and serviceability of the proxy indicator-based approach. The developed methodology for FV assessment is replicable and has the potential to help inform decision makers of flood-prone communities in Australia, particularly in data scarce areas.
DSNUNet: An Improved Forest Change Detection Network by Combining Sentinel-1 and Sentinel-2 Images
Authors: Jiang Jiawei , Xing Yuanjun , Wei Wei , Yan Enping , Xiang Jun , Mo Dengkui
Published: October 2022

The use of remote sensing images to detect forest changes is of great significance for forest resource management. With the development and implementation of deep learning algorithms in change detection, a large number of models have been designed to detect changes in multi-phase remote sensing images. Although synthetic aperture radar (SAR) data have strong potential for application in forest change detection tasks, most existing deep learning-based models have been designed for optical imagery. Therefore, to effectively combine optical and SAR data in forest change detection, this paper proposes a double Siamese branch-based change detection network called DSNUNet. DSNUNet uses two sets of feature branches to extract features from dual-phase optical and SAR images and employs shared weights to combine features into groups. In the proposed DSNUNet, different feature extraction branch widths were used to compensate for a difference in the amount of information between optical and SAR images. The proposed DSNUNet was validated by experiments on the manually annotated forest change detection dataset. According to the obtained results, the proposed method outperformed other change detection methods, achieving an F1-score of 76.40%. In addition, different combinations of width between feature extraction branches were analyzed in this study. The results revealed an optimal performance of the model at initial channel numbers of the optical imaging branch and SAR image branch of 32 and 8, respectively. The prediction results demonstrated the effectiveness of the proposed method in accurately predicting forest changes and suppressing cloud interferences to some extent.
An Application of Hyperspectral Image Clustering Based on Texture-Aware Superpixel Technique in Deep Sea
Authors: Ye Panjian , Han Chenhua , Zhang Qizhong , Gao Farong , Yang Zhangyi , Wu Guanghai
Published: October 2022

This paper aims to study the application of hyperspectral technology in the classification of deep-sea manganese nodules. Considering the spectral spatial variation of hyperspectral images, the difficulty of label acquisition, and the inability to guarantee stable illumination in deep-sea environments. This paper proposes a local binary pattern manifold superpixel-based fuzzy clustering method (LMSLIC-FCM). Firstly, we introduce a uniform local binary pattern (ULBP) to design a superpixel algorithm (LMSLIC) that is insensitive to illumination and has texture perception. Secondly, the weighted feature and the mean feature are fused as the representative features of superpixels. Finally, it is fused with fuzzy clustering method (FCM) to obtain a superpixel-based clustering algorithm LMSLIC-FCM. To verify the feasibility of LMSLIC-FCM on deep-sea manganese nodule data, the experiments were conducted on three different types of manganese nodule data. The average identification rate of LMSLIC-FCM reached 83.8%, and the average true positive rate reached 93.3%, which was preferable to the previous algorithms. Therefore, LMSLIC-FCM is effective in the classification of manganese nodules.
A Field-Data-Aided Comparison of Three 10 m Land Cover Products in Southeast Asia
Authors: Ding Yaxin , Yang Xiaomei , Wang Zhihua , Fu Dongjie , Li He , Meng Dan , Zeng Xiaowei , Zhang Junyao
Published: October 2022

To study global and regional environment protection and sustainable development and also to optimize mapping methods, it is of great significance to compare three existing 10 m resolution global land cover products in terms of accuracy: FROM-GLC10, the ESRI 2020 land cover product (ESRI2020), and the European Space Agency world cover 2020 product (ESA2020). However, most previous validations lack field collection points in large regions, especially in Southeast Asia, which has a cloudy and rainy climate, creating many difficulties in land cover mapping. In 2018 and 2019, we conducted a 56-day field investigation in Southeast Asia and collected 3326 points from different places. By combining these points and 14,808 other manual densification points in a stratified random sampling, we assessed the accuracy of the three land cover products in Southeast Asia. We also compared the impacts of the different classification standards, the different sample methods, and the different spatial distributions of the sample points. The results show that in Southeast Asia, (1) the mean overall accuracies of the FROM-GLC10, ESRI2020, and ESA2020 products are 75.43%, 79.99%, and 81.11%, respectively; (2) all three products perform well in croplands, forests, and built-up areas; ESRI2020 and ESA2020 perform well in water, but only ESA2020 performs well in grasslands; and (3) all three products perform badly in shrublands, wetlands, or bare land, as both the PA and the UA are lower than 50%. We recommend ESA2020 as the first choice for Southeast Asia’s land cover because of its high overall accuracy. FROM-GLC10 also has an advantage over the other two in some classes, such as croplands and water in the UA aspect and the built-up area in the PA aspect. Extracting the individual classes from the three products according to the research goals would be the best practice.
Target Detection Method of UAV Aerial Imagery Based on Improved YOLOv5
Authors: Luo Xudong , Wu Yiquan , Wang Feiyue
Published: October 2022

Due to the advantages of small size, lightweight, and simple operation, the unmanned aerial vehicle (UAV) has been widely used, and it is also becoming increasingly convenient to capture high-resolution aerial images in a variety of environments. Existing target-detection methods for UAV aerial images lack outstanding performance in the face of challenges such as small targets, dense arrangement, sparse distribution, and a complex background. In response to the above problems, some improvements on the basis of YOLOv5l have been made by us. Specifically, three feature-extraction modules are proposed, using asymmetric convolutions. They are named the Asymmetric ResNet (ASResNet) module, Asymmetric Enhanced Feature Extraction (AEFE) module, and Asymmetric Res2Net (ASRes2Net) module, respectively. According to the respective characteristics of the above three modules, the residual blocks in different positions in the backbone of YOLOv5 were replaced accordingly. An Improved Efficient Channel Attention (IECA) module was added after Focus, and Group Spatial Pyramid Pooling (GSPP) was used to replace the Spatial Pyramid Pooling (SPP) module. In addition, the K-Means++ algorithm was used to obtain more accurate anchor boxes, and the new EIOU-NMS method was used to improve the postprocessing ability of the model. Finally, ablation experiments, comparative experiments, and visualization of results were performed on five datasets, namely CIFAR-10, PASCAL VOC, VEDAI, VisDrone 2019, and Forklift. The effectiveness of the improved strategies and the superiority of the proposed method (YOLO-UAV) were verified. Compared with YOLOv5l, the backbone of the proposed method increased the top-one accuracy of the classification task by 7.20% on the CIFAR-10 dataset. The mean average precision (mAP) of the proposed method on the four object-detection datasets was improved by 5.39%, 5.79%, 4.46%, and 8.90%, respectively.
Comparison and Analysis of Stellar Occultation Simulation Results and SABER-Satellite-Measured Data in Near Space
Authors: Sun Mingchen , Dong Xiang , Zhu Qinglin , Cheng Xuan , Wang Hongguang , Wu Jiaji
Published: October 2022

In this study, we analyze the accuracy of the stellar occultation technique to detect the oxygen number density and temperature in near space. Based on the validation of the algorithm related to stellar occultation using a single wavelength of 762 nm, the simulation and inversion are performed using the oxygen absorption A-band, and the results are compared with SABER observations to calculate the deviation. Then, the distribution of the detection accuracy with wavelength, latitude, and altitude is analyzed. The results show that the radiant transmittance of the basic observation varies significantly with wavelength and altitude, and it is not sensitive to a change of latitude. The inversion results of each wavelength at different latitudes can be combined, and it can be seen that the 754–769 nm band is preferred for oxygen and temperature detection. Therefore, analyzing the accuracy results of the specific wavelength 757.84 nm at different latitudes, the temperature accuracy can reach 0.1 K in the stratosphere at both low and high latitudes and 0.6–34 K at middle latitudes. The temperature detection accuracy in the mesosphere at each latitude reaches about a dozen K. The deviation of the inversion results at middle latitudes is larger in the thermosphere, and at the other two latitudes, it is about a few dozen K. From the analysis of relative deviation, excluding the deviation of 95–100 km, the deviation of other altitudes is within the ideal range, and the minimum can reach 0. The accuracy of the oxygen number density increases with latitude, and the relative deviation of the middle and high latitudes is around 10–20%. Based on the above results, it is concluded that the technique of starlight occultation exhibits high accuracy for detecting atmospheric parameters in the near space region, and the results lay the technical foundation for the independent development of stellar occultation.
MSCNet: A Multilevel Stacked Context Network for Oriented Object Detection in Optical Remote Sensing Images
Authors: Zhang Rui , Zhang Xinxin , Zheng Yuchao , Wang Dahan , Hua Lizhong
Published: October 2022

Oriented object detection has recently become a hot research topic in remote sensing because it provides a better spatial expression of oriented target objects. Although research has made considerable progress in this field, the feature of multiscale and arbitrary directions still poses great challenges for oriented object detection tasks. In this paper, a multilevel stacked context network (MSCNet) is proposed to enhance target detection accuracy by aggregating the semantic relationships between different objects and contexts in remote sensing images. Additionally, to alleviate the impact of the defects of the traditional oriented bounding box representation, the feasibility of using a Gaussian distribution instead of the traditional representation is discussed in this paper. Finally, we verified the performance of our work on two common remote sensing datasets, and the results show that our proposed network improved on the baseline.
LiDAR-Based Hatch Localization
Authors: Jiang Zeyi , Liu Xuqing , Ma Mike , Wu Guanlin , Farrell Jay A.
Published: October 2022

This paper considers the problem of determining the time-varying location of a nearly full hatch during cyclic transloading operations. Hatch location determination is a necessary step for automation of transloading, so that the crane can safely operate on the cargo in the hatch without colliding with the hatch edges. A novel approach is presented and evaluated by using data from a light detection and ranging (LiDAR) mounted on a pan-tilt unit (PT). Within each cycle, the hatch area is scanned, the data is processed, and the hatch corner locations are extracted. Computations complete less than 5 ms after the LiDAR scan completes, which is well within the time constraints imposed by the crane transloading cycle. Although the approach is designed to solve the challenging problem of a full hatch scenario, it also works when the hatch is not full, because in that case the hatch edges can be more easily distinguished from the cargo data. Therefore, the approach can be applied during the whole duration of either loading or unloading. Experimental results for hundreds of cycles are present to demonstrate the ability to track the hatch location as it moves and to assess the accuracy (standard deviation less than 0.30 m) and reliability (worst case error less than 0.35 m).
Energy Saving Planner Model via Differential Evolutionary Algorithm for Bionic Palletizing Robot
Authors: Deng Yi , Zhou Tao , Zhao Guojin , Zhu Kuihu , Xu Zhaixin , Liu Hai
Published: October 2022

Energy saving in palletizing robot is a fundamental problem in the field of industrial robots. However, the palletizing robot often suffers from the problems of high energy consumption and lacking flexibility. In this work, we introduce a novel differential evolution algorithm to address the adverse effects caused by the instability of the initial trajectory parameters while reducing the energy. Specially, a simplified analytical model of the palletizing robot is firstly developed. Then, the simplified analytical model and the differential evolutionary algorithm are combined to form a planner with the goal of reducing energy consumption. The energy saving planner optimizes the initial parameters of the trajectories collected by the bionic demonstration system, which in turn enables a reduction in the operating power consumption of the palletizing robot. The major novelty of this article is the use of a differential evolutionary algorithm that can save the energy consumption as well as boosting its flexibility. Comparing with the traditional algorithms, the proposed method can achieve the state-of-the-art performance. Simulated and actual experimental results illustrate that the optimized trajectory parameters can effectively reduce the energy consumption of palletizing robot by 16%.
Current Ratio and Stability Issues of Electronically Enhanced Current Transformer Stimulated by Stray Inter-Winding Capacitance and Secondary-Side Disturbance Voltage
Authors: Zajec Peter
Published: October 2022

Electronically enhanced current transformers (EECT) have gained much interest in power quality assessment. Their magnitude and phase angle error, which mainly relates to the properties of the ferromagnetic materials used, the impedance of the secondary load, and the inter-turns capacitance, are thoroughly analyzed. In contrast, the capacitance between the windings, i.e., inter-winding capacitances and their limiting effects on EECT operation, are rarely analyzed in detail—in particular, no details on the control design of the assisting electronic unit, its tuning recommendations, or both are provided. In this paper, the capacitive coupling between indication and compensating winding of EECT with simplified feedthrough construction is analyzed thoroughly in terms of current ratio error and stability of the implemented configuration of the trans-conductance amplifier. The preliminary assumption about the adverse effect of the inter-winding capacitance shunting both ends of the original amplifier, composed of two series-connected inverting amplifier stages, was confirmed and resolved within a modified amplifier with the help of a simplified simulation model and was experimentally proven with measurements on a custom-built EECT prototype. Furthermore, the analyzed phenomena were linked to trans-conductance amplifier parameters, explicitly with its compensating networks, and summarized in their design guidelines. Throughout the paper, the EECT features obtained with original and modified amplifier designs are compared with the plain composite current transformer to demonstrate the benefits of the modified amplifier, especially its robustness against inter-winding capacitance variations.
An Improved Adaptive Median Filtering Algorithm for Radar Image Co-Channel Interference Suppression
Authors: Li Nuozhou , Liu Tong , Li Hangqi
Published: October 2022

In order to increase the accuracy of ocean monitoring, this paper proposes an improved adaptive median filtering algorithm based on the tangential interference ratio to better suppress marine radar co-channel interference. To solve the problem that co-channel interference reduces the accuracy of radar images’ parameter extraction, this paper constructs a tangential interference ratio model based on the improved Laplace operator, which is used to describe the ratio of co-channel interference along the antenna rotation direction in the original radar image. Based on the idea of between-class variance, the tangential interference ratio threshold is selected to divide co-channel interference into high-ratio regions and low ones. Moreover, an improved adaptive median filter is used to process regions of high ratio based on the median of sub-windows, while that of low-ratio regions is processed by the adaptive median filter based on the median of current windows. Radar-measured data from Bohai Bay, China are used for algorithm validation and experimental results show that the proposed filtering algorithm performs better than the adaptive median filtering algorithm.