bluuebunny/crossref_metadata_2025 huggingface dataset:
Acetylsalicylic Acid Suppresses Alcoholism-Induced Cognitive Impairment Associated with Atorvastatin Intake by Targeting Cerebral miRNA155 and NLRP3: In Vivo, and In Silico Study
Authors: Mohamed Doaa I. , Alaa El-Din Aly El-Waseef Dalia , Nabih Enas S. , El-Kharashi Omnyah A. , Abd El-Kareem Hanaa F. , Abo Nahas Hebatallah H. , Abdel-Wahab Basel A. , Helmy Yosra A. , Alshawwa Samar Zuhair , Saied Essa M.
Published: February 2022

Alcoholism is one of the most common diseases that can lead to the development of several chronic diseases including steatosis, and cognitive dysfunction. Statins are lipid-lowering drugs that are commonly prescribed for patients with fatty liver diseases; however, the exact effect of statins on cognitive function is still not fully understood. In the present study, we have investigated the molecular and microscopic basis of cognitive impairment induced by alcohol and/or Atorvastatin (ATOR) administration to male Wistar albino rats and explored the possible protective effect of acetylsalicylic acid (ASA). The biochemical analysis indicated that either alcohol or ATOR or together in combination produced a significant increase in the nucleotide-binding domain–like receptor 3 (NLRP3), interleukin-1β (IL-1β) miRNA155 expression levels in the frontal cortex of the brain tissue. The histological and morphometric analysis showed signs of degeneration in the neurons and the glial cells with aggregations of inflammatory cells and a decrease in the mean thickness of the frontal cortex. Immunohistochemical analysis showed a significant increase in the caspase-8 immunoreaction in the neurons and glial cells of the frontal cortex. Interestingly, administration of ASA reversed the deleterious effect of the alcohol and ATOR intake and improved the cognitive function as indicated by biochemical and histological analysis. ASA significantly decreased the expression levels of miRNA155, NLRP3, and IL1B, and produced a significant decrease in caspase-8 immunoreaction in the neurons and glial cells of the frontal cortex with a reduction in the process of neuroinflammation and neuronal damage. To further investigate these findings, we have performed an extensive molecular docking study to investigate the binding affinity of ASA to the binding pockets of the NLRP3 protein. Our results indicated that ASA has high binding scores toward the active sites of the NLRP3 NACHT domain with the ability to bind to the NLRP3 pockets by a set of hydrophilic and hydrophobic interactions. Taken together, the present study highlights the protective pharmacological effect of ASA to attenuate the deleterious effect of alcohol intake and long term ATOR therapy on the cognitive function via targeting miRNA155 and NLRP3 proteins.
Advances in the Prophylaxis of Respiratory Infections by the Nasal and the Oromucosal Route: Relevance to the Fight with the SARS-CoV-2 Pandemic
Authors: Ivanova Nadezhda , Sotirova Yoana , Gavrailov Georgi , Nikolova Krastena , Andonova Velichka
Published: February 2022

In this time of COVID-19 pandemic, the strategies for prevention of the infection are a primary concern. Looking more globally on the subject and acknowledging the high degree of misuse of protective face masks from the population, we focused this review on alternative pharmaceutical developments eligible for self-defense against respiratory infections. In particular, the attention herein is directed to the nasal and oromucosal formulations intended to boost the local immunity, neutralize or mechanically “trap” the pathogens at the site of entry (nose or mouth). The current work presents a critical review of the contemporary methods of immune- and chemoprophylaxis and their suitability and applicability in topical mucosal dosage forms for SARS-CoV-2 prophylaxis.
Liposomes as Tools to Improve Therapeutic Enzyme Performance
Authors: Cruz Maria Eugénia Meirinhos , Corvo Maria Luísa , Martins Maria Bárbara , Simões Sandra , Gaspar Maria Manuela
Published: February 2022

The drugs concept has changed during the last few decades, meaning the acceptance of not only low molecular weight entities but also macromolecules as bioagent constituents of pharmaceutics. This has opened a new era for a different class of molecules, namely proteins in general and enzymes in particular. The use of enzymes as therapeutics has posed new challenges in terms of delivery and the need for appropriate carrier systems. In this review, we will focus on enzymes with therapeutic properties and their applications, listing some that reached the pharmaceutical market. Problems associated with their clinical use and nanotechnological strategies to solve some of their drawbacks (i.e., immunogenic reactions and low circulation time) will be addressed. Drug delivery systems will be discussed, with special attention being paid to liposomes, the most well-studied and suitable nanosystem for enzyme delivery in vivo. Examples of liposomal enzymatic formulations under development will be described and successful pre-clinical results of two enzymes, L-Asparaginase and Superoxide dismutase, following their association with liposomes will be extensively discussed.
SHE (Sustainability, Health, Ethics)—A Grid for an Embodied Ethic
Authors: Macallan Brian
Published: February 2022

Our current planetary emergency is one in which we are facing significant global warming as a result of human-driven climate change. This is having and will continue to have catastrophic results for the earth’s ecosystems and for life as we know it. The Christian tradition often works actively against the seriousness of these challenges due to its eschatological outlook. Process theology, as one stream within the Christian tradition, embraces a different vision of the future that fosters engagement in current concerns rather than an escapist approach. A process theological proposal is therefore offered that calls for an embodied ethic that embraces the acronym SHE. SHE stands for Sustainability, Health, and Ethics. It provides a dietary grid as a way to embody ethics to bring about societal change in light of environmental challenges. SHE is proposed against a background that argues for Christian engagement in our current global crisis. The idea of “small turnings” as a conceptual idea is adopted to help frame how the SHE grid might be understood.
Comparing Machine Learning and Binary Thresholding Methods for Quantification of Callose Deposits in the Citrus Phloem
Authors: Welker Stacy , Levy Amit
Published: February 2022

Callose is a polysaccharide that can be fluorescently stained to study many developmental and immune functions in plants. High-throughput methods to accurately gather quantitative measurements of callose from confocal images are useful for many applications in plant biology. Previous callose quantification methods relied upon binary local thresholding, which had the disadvantage of not being able to differentiate callose in conditions with low contrast from background material. Here, a measurement approach that utilizes the Ilastik supervised machine learning imagery data collection software is described. The Ilastik software method provided superior efficiency for acquiring counts of callose deposits. We also determined the accuracy of these methods as compared to manual counts. We demonstrate that the automated software methods are both good predictors of manual counts, but that the Ilastik counts are significantly closer. Researchers can use this information to guide their choice of method to quantify callose in their work.
Comparative Antioxidant, Anti-Acetylcholinesterase and Anti-α-Glucosidase Activities of Mediterranean Salvia Species
Authors: Mervić Mateja , Bival Štefan Maja , Kindl Marija , Blažeković Biljana , Marijan Marijan , Vladimir-Knežević Sanda
Published: February 2022

Salvia species have a cosmopolitan distribution and comprise several well-known plants valuable for pharmaceutical and food industries due to their recognized medicinal, food flavouring, and preservative properties. The present study aimed to evaluate and compare the biological activities of seven wild-growing Salvia species from the Mediterranean area (S. fruticosa, S. glutinosa, S. nemorosa, S. officinalis, S. pratensis, S. sclarea, S. verticillata). All studied ethanolic leaf extracts exhibited significant DPPH and NO radical scavenging ability, lipid peroxidation inhibition, and reducing power, as well as moderate iron-chelating properties. Together with S. officinalis and S. fruticosa, S. verticillata showed anti-acetylcholinesterase activity, while S. glutinosa was also found to possess the ability to inhibit α-glucosidase. Total flavonoid (0.37–0.90%), phenolic acid (3.55–12.44%), tannin (1.22–2.60%), and anthocyanin contents (0.03–0.08%) were determined in Salvia leaves. Rosmarinic acid was the predominant hydroxycinnamic acid in all studied sage plants, ranging from 9400 to 38,800 μg/g. The correlation study showed a strong relationship between biological activities and contents of total phenolic acids, total tannins, and rosmarinic acid, indicating their significant contribution to the efficiency of tested Salvia species. Our results highlighted Mediterranean sage plants as rich sources of potent antioxidant, neuroprotective, and hypoglycemic agents which are worthy of further research.
Ethnobotanical Survey of Local Flora Used for Medicinal Purposes among Indigenous People in Five Areas in Lagos State, Nigeria
Authors: Lawal Ibraheem Oduola , Rafiu Basirat Olabisi , Ale Joy Enitan , Majebi Onuyi Emmanuel , Aremu Adeyemi Oladapo
Published: February 2022

Traditional medicine is typically the most accessible primary healthcare for a large proportion of the people in Nigeria. However, its potential remains under-explored, especially with regards to their documentation. This research investigated and documented the use of medicinal plants in the management of various health conditions/diseases among local populations in Lagos State. This study was conducted in five (5) locations of Lagos State i.e., Alimosho, Badagry, Eti-Osa, and Epe (including Ijebu and Imota). Ethnobotanical information from 100 participants was obtained using semi-structured questionnaires. Frequency of citation (FC), relative frequency of citation (RFC), fidelity level (FL), and informant consensus factor (ICF) were used to assess the importance of plants utilised for various health conditions/diseases. We identified 183 plants from 61 plant families with the highest number (24) of plants belonging to Fabaceae. Based on the high FC, the top-five popular plants used for managing health conditions/diseases in the study areas were Mangifera indica (95%), Waltheria indica (93%), Zingiber officinale (87%), Alchornea cordifolia (83%) and Ipomoea involucrata (81%). Furthermore, Rauvolfia vomitoria, Urena lobata and Waltheria indica were recognised as the most adaptable plants, as they were used to treat five different health conditions/diseases. The most commonly used life-forms were herbs (34%) and woody species (shrubs; 30%, and trees; 22%). The most regularly used plant parts were leaves. The calculated RFC values for all medicinal plant species ranged from 0.01 to 0.95, while FL values ranged from 7.14 to 100%. We found 14 health conditions/diseases, with ICF values ranging from 0.88 to 0.95. Insomnia, insanity, convulsion, nervousness, and muscle relaxants had the lowest (ICF = 0.88) agreement, while malaria/fevers, stomach, and respiratory-related diseases had the most (ICF = 0.95) agreement. The documented therapeutic uses of the plants provide basic data for further research aimed at pharmacological and conservation studies of the most important flora existing in the study areas.
Salicylic Acid Improves Antioxidant Defense System and Photosynthetic Performance in Aristotelia chilensis Plants Subjected to Moderate Drought Stress
Authors: González-Villagra Jorge , Reyes-Díaz Marjorie M. , Tighe-Neira Ricardo , Inostroza-Blancheteau Claudio , Escobar Ana Luengo , Bravo León A.
Published: February 2022

Salicylic acid (SA) has been shown to ameliorate drought stress. However, physiological and biochemical mechanisms involved in drought stress tolerance induced by SA in plants have not been well understood. Thus, this study aimed to study the role of SA application on enzymatic and non-enzymatic antioxidants, photosynthetic performance, and plant growth in A. chilensis plants subjected to moderate drought stress. One-year-old A. chilensis plants were subjected to 100% and 60% of field capacity. When plants reached moderate drought stress (average of stem water potential of −1.0 MPa, considered as moderate drought stress), a single SA application was performed on plants. Then, physiological and biochemical features were determined at different times during 14 days. Our study showed that SA application increased 13.5% plant growth and recovered 41.9% AN and 40.7% gs in drought-stressed plants on day 3 compared to drought-stressed plants without SA application. Interestingly, SOD and APX activities were increased 85% and 60%, respectively, in drought-stressed SA-treated plants on day 3. Likewise, SA improved 30% total phenolic content and 60% antioxidant capacity in drought-stressed A. chilensis plants. Our study provides insight into the SA mechanism to tolerate moderate drought stress in A. chilensis plants.
Anti-Inflammatory Functions of Methanol Extract from Malus baccata (L.) Borkh. Leaves and Shoots by Targeting the NF-κB Pathway
Authors: Song Chaoran , Chen Hongxi , Kim Soo Ah , Lee Jong Sub , Choung Eui Su , Zhang Zhiyun , Kim Soo-Yong , Kim Jong-Hoon , Cho Jae Youl
Published: February 2022

Malus baccata (L.) Borkh. is a widely used medical plant in Asia. Since the anti-inflammatory mechanism of this plant is not fully understood, the aim of this study was to explore the anti-inflammatory function and mechanism of Malus baccata (L.) Borkh. methanol extract (Mb-ME). For in vitro experiments, nitric oxide production assay, PCR, overexpression strategy, immunoblotting, luciferase reporter assay, and immunoprecipitation were employed to explore the molecular mechanism and the target proteins of Mb-ME. For in vivo experiments, an HCl/EtOH-induced gastritis mouse model was used to confirm the anti-inflammatory function. Mb-ME showed a strong ability to inhibit the production of nitric oxide and the expression of inflammatory genes. Mb-ME decreased NF-κB luciferase activity mediated by MyD88 and TRIF. Moreover, Mb-ME blocked the activation of Src, Syk, p85, Akt, p50, p60, IKKα/β, and IκBα in LPS-induced RAW264.7 cells. Overexpression and immunoprecipitation analyses suggested Syk and Src as the target enzymes of Mb-ME. In vitro results showed that Mb-ME could alleviate gastritis and relieve the protein expression of p-Src, p-Syk, and COX-2, as well as the gene expression of COX-2 and TNF-α. In summary, this study implied that Mb-ME performs an anti-inflammatory role by suppressing Syk and Src in the NF-κB signaling pathway, both in vivo and in vitro.
Variations in Structure among Androecia and Floral Nectaries in the Inverted Repeat-Lacking Clade (Leguminosae: Papilionoideae)
Authors: Sinjushin Andrey , Ploshinskaya Maria , Maassoumi Ali Asghar , Mahmoodi Mohammad , Bagheri Ali
Published: February 2022

The vast majority of highly valuable species of the Leguminosae in temperate latitudes belong to the Inverted Repeat-Lacking Clade (IRLC). Despite having a generally conserved monosymmetric floral morphology, members of this group are remarkable with a pronounced diversity of floral sizes, modes of staminal fusion, and pollination strategies. This paper examined androecia and floral nectaries (FNs) in selected genera of the IRLC. External morphology was investigated using stereomicroscopy and scanning electron microscopy. In some cases, the pattern of staminal fusion was additionally examined in transverse sections using light microscopy. Androecia of all selected genera fell into one of four types, viz., monadelphous, pseudomonadelphous, diadelphous or diadelphous reduced (with inner stamens converted into sterile staminodes). However, there was significant variation in the stamens’ mode of contact, as well as the shape and size of the fenestrae providing access to FNs. Some types seemed to arise independently in different genera, thus providing a high level of homoplasy. FNs were more conserved and comprised areas of secretory stomata in the abaxial part of the receptacle and/or hypanthium. Nectariferous stomata could be found in very miniaturized flowers (Medicago lupulina) and could even accompany monadelphy (Galega). This indicates that preferential self-pollination may nevertheless require visitation by insects.
Influence of the Integration of Geopolymer Wastes on the Characteristics of Binding Matrices Subjected to the Action of Temperature and Acid Environments
Authors: Hattaf Rabii , Aboulayt Abdelilah , Lahlou Nouha , Touhami Mohamed Ouazzani , Gomina Moussa , Samdi Azzeddine , Moussa Redouane
Published: February 2022

Recycling geopolymer waste, by reusing it as a raw material for manufacturing new geopolymer binding matrices, is an interesting asset that can add to the many technical, technological and environmental advantages of this family of materials in the construction field. This can promote them as promising alternatives to traditional materials, such as Portland cements, which are not so environmentally friendly. Recent studies have shown that the partial replacement of reactive aluminosilicates (metakaolin and fly ash) up to a mass rate of 50% by geopolymer waste does not significantly affect the compressive strength of the new product. In line with these findings, this paper investigates the effects of aggressive environments, i.e., high temperatures (up to 1000 °C) and acid attacks (pH = 2), on the characteristics of these new matrices. Different techniques were used to understand these evolutions: mineralogical analysis by X-ray diffraction (XRD), thermogravimetry-differential thermal analysis (TGA-DTA), mechanical characterization and scanning electron Microscopy (SEM) observations. The results are very satisfactory: in the exposure temperature range explored, the new matrices containing geopolymer waste suffered losses in compressive strength similar to those of the matrices without waste (considered as materials reference). On the other hand, the new matrices exhibited good chemical stability in acid media. These results confirm that the reuse of geopolymer waste is a promising recycling solution in the construction sector.
The Effect of Superabsorbent Polymer on the Resilient and Plastic Strain Behavior of Cemented Soil under Traffic Load
Authors: Dai Di , Peng Jie , Bai Lanlan , Li Gang , Lin Hongmin
Published: February 2022

In road construction, a large number of excavated soils need to be treated with stabilizers. The addition of superabsorbent polymer (SAP) can improve the road performance of these stabilized soils. In order to predict roadbed deformation, dynamic triaxial tests were carried out on cemented soil containing SAP to investigate its resilient and plastic strain behavior. The effects of SAP content, cyclic stress ratio, and loading frequency on cement-stabilized soils with SAP were analyzed combined with the number of cycles. This study demonstrates how these influencing factors effect the resilient strain, dynamic elastic modulus, and accumulated plastic strain, which are crucial to better understanding the strain behavior of cement-stabilized soil with SAP. The results show that SAP can significantly improve the brittle failure characteristics and dynamic strength of cement-stabilized soil. Soil with higher SAP content possesses smaller accumulated plastic strain; with the increase in the cyclic stress ratio, the dynamic elastic modulus decreases significantly, whereas the accumulated plastic strain has the opposite trend. In addition, the lower frequency produces larger cumulative axial strain.
pH-Responsive Nanocarriers in Cancer Therapy
Authors: AlSawaftah Nour M. , Awad Nahid S. , Pitt William G. , Husseini Ghaleb A.
Published: February 2022

A number of promising nano-sized particles (nanoparticles) have been developed to conquer the limitations of conventional chemotherapy. One of the most promising methods is stimuli-responsive nanoparticles because they enable the safe delivery of the drugs while controlling their release at the tumor sites. Different intrinsic and extrinsic stimuli can be used to trigger drug release such as temperature, redox, ultrasound, magnetic field, and pH. The intracellular pH of solid tumors is maintained below the extracellular pH. Thus, pH-sensitive nanoparticles are highly efficient in delivering drugs to tumors compared to conventional nanoparticles. This review provides a survey of the different strategies used to develop pH-sensitive nanoparticles used in cancer therapy.
Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton
Authors: Amor Nesrine , Noman Muhammad Tayyab , Ismail Adla , Petru Michal , Sebastian Neethu
Published: February 2022

In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values.
Design and Study of a Photo-Switchable Polymeric System in the Presence of ZnS Nanoparticles under the Influence of UV Light Irradiation
Authors: Pizarro Guadalupe , Alavia Wilson , González Karen , Díaz Héctor , Marambio Oscar , Martin-Trasanco Rudy , Sánchez Julio , Oyarzún Diego , Neira-Carrillo Andrónico
Published: February 2022

Recent progress in the field of photosensitive materials has prompted a need to develop efficient methods to synthesize materials with basic intermolecular architectural designs and novel properties. Accordingly, in this work we design and study a photoactive polymer as a photo-switchable polymeric system in the presence and absence of ZnS nanoparticles (average size < 10 nm) at 5 wt.%. The influence of UV light irradiation on its properties were also studied. The photoactive block copolymer was obtained from styrene (S) and methyl methacrylate (MMA) as monomers and 1-(2-hydroxyethyl)-3,3-dimethylindoline-6-nitrobenzopyran (SP) was grafted to the block copolymer backbone as a photochromic agent. Furthermore, the incorporation of ZnS (NPs) as photo-optical switch component into the system enhances the purple colored photo-emission, with the open form of the spiropyran derivative (merocyanine, MC). The ZnS stabilize the isomeric equilibrium in the MC interconversion of the photochromic agent. The photo-switchable properties of the PS-b-PMMA-SP in the presence of ZnS (NPs) were examined using UV-VIS spectroscopy, Photoluminescence (PL) spectroscopy, optical fluorescence and scanning electronic microscopy (SEM-EDX.). The observed changes in the absorbance, fluorescence and morphology of the system were associated to the reversible interconversion of the two states of the photochromic agent which regulates the radiative deactivation of the luminescent ZnS NPs component. After UV irradiation the photoactive polymer becomes purple in color. Therefore, these basic studies can lead to the development of innovative functional and nanostructured materials with photosensitive character as photosensitive molecular switches.
Novel Antiviral and Antibacterial Durable Polyester Fabrics Printed with Selenium Nanoparticles (SeNPs)
Authors: Abou Elmaaty Tarek , Sayed-Ahmed Khaled , Elsisi Hanan , Ramadan Shaimaa M. , Sorour Heba , Magdi Mai , Abdeldayem Shereen A.
Published: February 2022

The COVID-19 pandemic has clearly shown the importance of developing advanced protective equipment, and new antiviral fabrics for the protection and prevention of life-threatening viral diseases are needed. In this study, selenium nanoparticles (SeNPs) were combined with polyester fabrics using printing technique to obtain multifunctional properties, including combined antiviral and antibacterial activities as well as coloring. The properties of the printed polyester fabrics with SeNPs were estimated, including tensile strength and color fastness. Characterization of the SeNPs was carried out using TEM and SEM. The results of the analysis showed good uniformity and stability of the particles with sizes range from 40–60 nm and 40–80 nm for SeNPs 25 mM and 50 mM, respectively, as well as uniform coating of the SeNPs on the fabric. In addition, the SeNPs—printed polyester fabric exhibited high disinfection activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with an inhibition percentage of 87.5%. Moreover, a toxicity test of the resulting printed fabric revealed low cytotoxicity against the HFB4 cell line. In contrast, the treated fabric under study showed excellent killing potentiality against Gram-positive bacteria (Bacillus cereus) and Gram-negative bacteria (Pseudomonas aeruginosa, Salmonella typhi, and Escherichia coli). This multifunctional fabric has high potential for use in protective clothing applications by providing passive and active protection pathways.
Static Permittivity and Electro-Optical Properties of Bi-Component Orthoconic Antiferroelectric Liquid Crystalline Mixtures Targeted for Polymer Stabilized Sensing Systems
Authors: Nepal Shantiram , Das Banani , Das Malay Kumar , Sarkar Madhumita Das , Urbańska Magdalena , Czerwiński Michał
Published: February 2022

The behavior of two newly formulated bi-component orthoconic antiferroelectric liquid crystalline (OAFLC) systems, i.e., the Compound A + Compound B mixture system and Compound C + Compound B mixture system has been discussed in light of temperature and concentration dependencies of helical pitch length, spontaneous polarization, relaxation time, bulk viscosity, and the anchoring energy strength coefficient, together with static dielectric permittivity (ε) and dielectric anisotropy. Compound A + Compound B mixtures possess spontaneous polarization between 190–340 nC.cm−2 and fast relaxation times between 190–320 µs in the smectic antiferroelectric SmCA* phase at room temperature. Compound C + Compound B mixtures also have a spontaneous polarization in the range of 190–280 nC.cm−2 and relaxation times in the range of 190–230 µs at room temperature. Most of the mixtures have a helical pitch below one micrometer in the SmCA* phase. These advanced mixtures show a broad temperature range of the antiferroelectric SmCA* phase, fast switching of molecules under an applied electric field, negative dielectric anisotropy and a short helical pitch, confirming the advantage of designing new polymer-stabilized OAFLC that is targeted for novel application in sensing devices, utilizing the fast responsive electro-optical modulation elements.
Geotouristic Route Proposal for Touristic Development in a Mining Area—Case Study
Authors: Carrión-Mero Paúl , Turner-Carrión Magner , Herrera-Franco Gricelda , Bravo-Murillo Gianella , Aguilar-Aguilar Maribel , Paz-Salas Nataly , Berrezueta Edgar
Published: February 2022

In recent decades, geotourism has been presented as an alternative for the sustainable socioeconomic development of the community. In addition, it shows significant growth. Portovelo canton, located in the south of Ecuador, is characterised by a significant geological importance complemented by the mining culture and history interest, turning into the first mining centre. Mining is the main economic activity in the area. However, the development of illegal mining without technical considerations affects the canton and its surroundings. Faced with this problem, the need arises for alternatives to improve the inhabitants’ quality of life and protect their geological heritage. This work aims to propose a geotouristic route (GR) in the course of the Amarillo River through the characterisation and quantitative assessment of 10 interest sites (four geosites and six touristic sites), which enhance the geotourism development of the canton, including geoconservation strategies. The methodological process includes (i) characterisation of sites and GR proposal, (ii) sites and GR assessment using the Geotouristic Route Assessment Matrix method (GtRAM, acronym in Spanish) and Brilha method for geosites, and (iii) proposal of geotourism development and geoconservation strategies in a sustainability framework through the analysis of strengths, opportunities, weaknesses, and threats (SWOT). The results obtained from the proposed GR reflect that 60% of the proposed sites have a tourist interest classified as high, of which the Museo Mineralógico Magner Turner was the best-rated geoheritage element. Similarly, the high scientific, educational, and tourist values of the proposed geoheritage sites are highlighted. Strategies have been established to enhance the GR value: (i) Promoting geotourism through different activities and (ii) proposals for geoconservation and conditioning of geoheritage sites and tourist interest sites considering the geological and environmental impact. The methodology used in the study made it possible to establish geo-guidelines focused on local development, which are coupled with the knowledge of two main groups: Geo-experts and the community.
Numerical Prediction of Duality Principle with Bloch-Floquet Periodic Boundary Condition in Fully Anisotropic FDTD
Authors: Feng Naixing , Zhang Yuxian , Huang Zhixiang , Yang Lixia , Wu Xianliang
Published: February 2022

In this paper, in accordance with fully anisotropic electromagnetic materials, the duality principle is successfully validated by the fully anisotropic finite-difference time-domain (FDTD) with Bloch-Floquet periodic boundary condition (BPBC), which in theory is first effectively applied to the verification of time-domain electromagnetic computation. Starting from the conventional duality principle of isotropy, those conditions can be given without any loss term. Without loss of generality, the electromagnetic duality rules involving dielectric and magnetic lossy tensors could be obtained by combining complex extension from original real parameters. In our further research, we introduce the duality principle into the BPBC cases, then execute and validate three different fully anisotropic models by means of the FDTD method under either TE or TM modes. From highly accurate numerical point of view, we apply ourselves to a more effective verification which can forecast the reflection and transmission coefficients and detect the subsurface echoes through the duality principle.
Kernel Ridge Regression Hybrid Method for Wheat Yield Prediction with Satellite-Derived Predictors
Authors: Ahmed A. A. Masrur , Sharma Ekta , Jui S. Janifer Jabin , Deo Ravinesh C. , Nguyen-Huy Thong , Ali Mumtaz
Published: February 2022

Wheat dominates the Australian grain production market and accounts for 10–15% of the world’s 100 million tonnes annual global wheat trade. Accurate wheat yield prediction is critical to satisfying local consumption and increasing exports regionally and globally to meet human food security. This paper incorporates remote satellite-based information in a wheat-growing region in South Australia to estimate the yield by integrating the kernel ridge regression (KRR) method coupled with complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the grey wolf optimisation (GWO). The hybrid model, ‘GWO-CEEMDAN-KRR,’ employing an initial pool of 23 different satellite-based predictors, is seen to outperform all the benchmark models and all the feature selection (ant colony, atom search, and particle swarm optimisation) methods that are implemented using a set of carefully screened satellite variables and a feature decomposition or CEEMDAN approach. A suite of statistical metrics and infographics comparing the predicted and measured yield shows a model prediction error that can be reduced by ~20% by employing the proposed GWO-CEEMDAN-KRR model. With the metrics verifying the accuracy of simulations, we also show that it is possible to optimise the wheat yield to achieve agricultural profits by quantifying and including the effects of satellite variables on potential yield. With further improvements in the proposed methodology, the GWO-CEEMDAN-KRR model can be adopted in agricultural yield simulation that requires remote sensing data to establish the relationships between crop health, yield, and other productivity features to support precision agriculture.
Polarization Estimation with a Single Vector Sensor for Radar Detection
Authors: He Yaomin , Yang Jian
Published: February 2022

Target detection using radar has important applications in military and civilian fields. Aimed at targets containing interference, radar polarimetry can facilitate discrimination between the target and interference. Since existing methods require the utilization of interference signals without targets in advance, they have a poor effect on interference with variable polarization. To solve this problem, this paper proposes a novel synchronous method to estimate the parameters of interference. First, we introduce a definition of the pulse compression signal-to-noise ratio, and prove that it is the polarization invariant in the virtual polarization adaptation. Then, for signals containing a target, interference, and noise, we propose a novel synchronous estimation method. Subsequently, we propose the two-dimensional golden selected method to further optimize the method with minimum calculation, and prove that the method presented in this paper is convergent and globally optimal. Finally, we analyze the presented method from three aspects: robustness, complexity, and applicability; the results of which demonstrate the efficacy of the method presented in this paper.
Three-Dimensional Geometry Reconstruction Method for Slowly Rotating Space Targets Utilizing ISAR Image Sequence
Authors: Zhou Zuobang , Liu Lei , Du Rongzhen , Zhou Feng
Published: February 2022

For a slowly rotating space target (SRST) with a fixed axis, traditional 3D geometry reconstruction methods become invalid as the projection vectors cannot be formed without accurate target rotational parameters. To tackle this problem, we present a new technique for 3D geometry reconstruction by using inverse synthetic aperture radar (ISAR) image sequence energy accumulation (ISEA). Firstly, by constituting the motion model of SRST, an explicit expression is derived to describe the relative geometric relationship between the 3D geometry and ISAR image sequence. Then accurate rotational parameters and the 3D geometry of SRST can be estimated by combining the idea of the ISEA method and quantum-behaved particle swarm optimization (QPSO). Compared with the ISEA method, which can be only applied to triaxial stabilized space targets, the proposed method can achieve 3D geometry reconstruction of SRST. Experimental results based on the simulated point model and simulated electromagnetic computer aided design (CAD) model validate the effectiveness and robustness of the proposed method.
Correlating Extremes in Wind Divergence with Extremes in Rain over the Tropical Atlantic
Authors: King Gregory P. , Portabella Marcos , Lin Wenming , Stoffelen Ad
Published: February 2022

Air–sea fluxes are greatly enhanced by the winds and vertical exchanges generated by mesoscale convective systems (MCSs). In contrast to global numerical weather prediction models, space-borne scatterometers are able to resolve the small-scale wind variability in and near MCSs at the ocean surface. Downbursts of heavy rain in MCSs produce strong gusts and large divergence and vorticity in surface winds. In this paper, 12.5 km wind fields from the ASCAT-A and ASCAT-B tandem mission, collocated with short time series of Meteosat Second Generation 3 km rain fields, are used to quantify correlations between wind divergence and rain in the Inter-Tropical Convergence Zone (ITCZ) of the Atlantic Ocean. We show that when there is extreme rain, there is extreme convergence/divergence in the vicinity. Probability distributions for wind divergence and rain rates were found to be heavy-tailed: exponential tails for wind divergence (P∼e−αδ with slopes that flatten with increasing rain rate), and power-law tails for rain rates (P∼(R*)−β with a slower and approximately equal decay for the extremes of convergence and divergence). Co-occurring points are tabulated in two-by-two contingency tables from which cross-correlations are calculated in terms of the odds and odds ratio for each time lag in the collocation. The odds ratio for extreme convergence and extreme divergence both have a well-defined peak. The divergence time lag is close to zero, while it is 30 min for the convergence peak, implying that extreme rain generally appears after (lags) extreme convergence. The temporal scale of moist convection is thus determined by the slower updraft process, as expected. A structural analysis was carried out that demonstrates consistency with the known structure of MCSs. This work demonstrates that (tandem) ASCAT winds are well suited for air–sea exchange studies in moist convection.
Application of TLS Method in Digitization of Bridge Infrastructures: A Path to BrIM Development
Authors: Mohammadi Masoud , Rashidi Maria , Mousavi Vahid , Yu Yang , Samali Bijan
Published: February 2022

Over the past years, bridge inspection practices and condition assessments were predicated upon long-established manual and paper-based data collection methods which were generally unsafe, time-consuming, imprecise, and labor-intensive, influenced by the experience of the trained inspectors involved. In recent years, the ability to turn an actual civil infrastructure asset into a detailed and precise digital model using state-of-the-art emerging technologies such as laser scanners has become in demand among structural engineers and managers, especially bridge asset managers. Although advanced remote technologies such as Terrestrial Laser Scanning (TLS) are recently established to overcome these challenges, the research on this subject is still lacking a comprehensive methodology for a reliable TLS-based bridge inspection and a well-detailed Bridge Information Model (BrIM) development. In this regard, the application of BrIM as a shared platform including a geometrical 3D CAD model connected to non-geometrical data can benefit asset managers, and significantly improve bridge management systems. Therefore, this research aims not only to provide a practical methodology for TLS-derived BrIM but also to serve a novel sliced-based approach for bridge geometric Computer-Aided Design (CAD) model extraction. This methodology was further verified and demonstrated via a case study on a cable-stayed bridge called Werrington Bridge, located in New South Wales (NSW), Australia. In this case, the process of extracting a precise 3D CAD model from TLS data using the sliced-based method and a workflow to connect non-geometrical information and develop a BrIM are elaborated. The findings of this research confirm the reliability of using TLS and the sliced-based method, as approaches with millimeter-level geometric accuracy, for bridge inspection subjected to precise 3D model extraction, as well as bridge asset management and BrIM development.
Multi-Scale Ship Detection Algorithm Based on a Lightweight Neural Network for Spaceborne SAR Images
Authors: Liu Shanwei , Kong Weimin , Chen Xingfeng , Xu Mingming , Yasir Muhammad , Zhao Limin , Li Jiaguo
Published: February 2022

The current limited spaceborne hardware resources and the diversity of ship target scales in SAR images have led to the requirement of on-orbit real-time detection of ship targets in spaceborne synthetic aperture radar (SAR) images. In this paper, we propose a lightweight ship detection network based on the YOLOv4-LITE model. In order to facilitate the network migration to the satellite, the method uses MobileNetv2 as the backbone feature extraction network of the model. To solve the problem of ship target scale diversity in SAR images, an improved receptive field block (RFB) structure is introduced, enhancing the feature extraction ability of the network, and improving the accuracy of multi-scale ship target detection. A sliding window block method is designed to detect the whole SAR image, which can solve the problem of image input. Experiments on the SAR ship dataset SSDD show that the detection speed of the improved lightweight network could reach up to 47.16 FPS, with the mean average precision (mAP) of 95.03%, and the model size is only 49.34 M, which demonstrates that the proposed network can accurately and quickly detect ship targets. The proposed network model can provide a reference for constructing a spaceborne real-time lightweight ship detection network, which can balance the detection accuracy and speed of the network.
Development of a Multi-Index Method Based on Landsat Reflectance Data to Map Open Water in a Complex Environment
Authors: Ticehurst Catherine , Teng Jin , Sengupta Ashmita
Published: February 2022

Mapping surface water extent is important for managing water supply for agriculture and the environment. Remote sensing technologies, such as Landsat, provide an affordable means of capturing surface water extent with reasonable spatial and temporal coverage suited to this purpose. Many methods are available for mapping surface water including the modified Normalised Difference Water Index (mNDWI), Fisher’s water index (FWI), Water Observations from Space (WOfS), and the Tasseled Cap Wetness index (TCW). While these methods can discriminate water, they have their strengths and weaknesses, and perform at their best in different environments, and with different threshold values. This study combines the strengths of these indices by developing rules that applies an index to the environment where they perform best. It compares these indices across the Murray-Darling Basin (MDB) in southeast Australia, to assess performance and compile a heuristic rule set for accurate application across the MDB. The results found that all single indices perform well with the Kappa statistic showing strong agreement, ranging from 0.78 for WOfS to 0.84 for TCW (with threshold −0.035), with improvement in the overall output when the index best suited for an environment was selected. mNDWI (using a threshold of −0.3) works well within river channels, while TCW (with threshold −0.035) is best for wetlands and flooded vegetation. FWI and mNDWI (with threshold 0.63 and 0, respectively) work well for remaining areas. Selecting the appropriate index for an environment increases the overall Kappa statistic to 0.88 with a water pixel accuracy of 90.5% and a dry pixel accuracy of 94.8%. An independent assessment illustrates the benefit of using the multi-index approach, making it suitable for regional-scale multi-temporal analysis.
Prediction of Landslide Displacement Based on the Combined VMD-Stacked LSTM-TAR Model
Authors: Gao Yaping , Chen Xi , Tu Rui , Chen Guo , Luo Tong , Xue Dongdong
Published: February 2022

The volatility of the cumulative displacement of landslides is related to the influence of external factors. To improve the prediction of nonlinear changes in landslide displacement caused by external influences, a new combined forecasting model of landslide displacement has been proposed. Variational modal decomposition (VMD) was used to obtain the trend and fluctuation sequences of the original sequence of landslide displacement. First, we established a stacked long short time memory (LSTM) network model and introduced rainfall and reservoir water levels as influencing factors to predict the fluctuation sequence; next, we used a threshold autoregressive (TAR) model to predict the trend sequence, following which the trend and fluctuation prediction sequence were superimposed to obtain the cumulative predicted displacement of the landslide. Finally, the VMD-stacked LSTM-TAR combination model based on the variational modal decomposition, stacked long short time memory network, and a threshold autoregressive model was built. Taking the landslide of Baishuihe in the Three Gorges Reservoir area as an example, through comparison with the prediction results of the VMD-recurrent neural network-TAR, VMD-back propagation neural network-TAR, and VMD-LSTM-TAR, the proposed combined prediction model was noted to have high accuracy, and it provided a novel approach for the prediction of volatile landslide displacement.
Detailed Mapping of Lava and Ash Deposits at Indonesian Volcanoes by Means of VHR PlanetScope Change Detection
Authors: Rösch Moritz , Plank Simon
Published: February 2022

Mapping of lava flows in unvegetated areas of active volcanoes using optical satellite data is challenging due to spectral similarities of volcanic deposits and the surrounding background. Using very high-resolution PlanetScope data, this study introduces a novel object-oriented classification approach for mapping lava flows in both vegetated and unvegetated areas during several eruptive phases of three Indonesian volcanoes (Karangetang 2018/2019, Agung 2017, Krakatau 2018/2019). For this, change detection analysis based on PlanetScope imagery for mapping loss of vegetation due to volcanic activity (e.g., lava flows) is combined with the analysis of changes in texture and brightness, with hydrological runoff modelling and with analysis of thermal anomalies derived from Sentinel-2 or Landsat-8. Qualitative comparison of the mapped lava flows showed good agreement with multispectral false color time series (Sentinel-2 and Landsat-8). Reports of the Global Volcanism Program support the findings, indicating the developed lava mapping approach produces valuable results for monitoring volcanic hazards. Despite the lack of bands in infrared wavelengths, PlanetScope proves beneficial for the assessment of risk and near-real-time monitoring of active volcanoes due to its high spatial (3 m) and temporal resolution (mapping of all subaerial volcanoes on a daily basis).