bluuebunny/crossref_metadata_2025 huggingface dataset:
Feline Toxoplasmosis in Greece: A Countrywide Seroprevalence Study and Associated Risk Factors
Authors: Sioutas Georgios , Symeonidou Isaia , Gelasakis Athanasios I. , Tzirinis Christos , Papadopoulos Elias
Published: December 2022

Toxoplasma gondii is a ubiquitous zoonotic parasite, with felines being the only definitive hosts. Cats shed oocysts with their faeces, and seroprevalence studies can be used to indirectly assess the environmental contamination. The current study aimed to evaluate T. gondii seroprevalence in Greek cats and identify possible risk factors. In total, 1554 blood samples were analyzed from different cats across all nine geographic regions of Greece, and a short questionnaire was completed for each cat. A rapid immunochromatographic test was used to detect anti-T. gondii antibodies, IgG type, and 21.8% of cats were seropositive. Regarding risk factors, when chi-square tests were applied, seropositivity was significantly higher (p < 0.05) in rural cats, cats with outdoor access, and hunting cats. Gender, age, ownership, and raw feeding were not significant risk factors, although female, adult, stray, and raw-feeding cats had a higher seroprevalence than their counterparts. Binary logistic regression models were developed to adjust for the confounding effects of the initially recognized risk factors, and only hunting in urban areas remained a significant risk factor. Greek cats had lower seropositivity than the average European value, and the present research highlights the importance of updated seroprevalence and risk factor studies within the context of One-Health.
The Promotional Effect of GW4869 on C. albicans Invasion and Cellular Damage in a Murine Model of Oral Candidiasis
Authors: Zhang Miaomiao , Li Ruowei , Zhou Yifan , Xie Ruiqi , Ma Jingjing , Liu Hong , Qin Yao , Zhao Maomao , Duan Ning , Ye Pei , Wang Wenmei , Wang Xiang
Published: December 2022

Candida albicans (C. albicans) is one of the most common fungi in the human body; it is an opportunistic pathogen and can cause candidiasis. Extracellular vesicles (EVs) derived from the host cells have a potentially protective effect against pathogens and can be developed as vaccine formulations. GW4869 can inhibit the production and release of EVs. Previous studies have indicated that GW4869 can alter the immune and inflammatory responses of the host. However, the effect of GW4869 on Candida infection and the anti-Candida response of the host has not been investigated. We evaluated the effect of GW4869 on C. albicans invasion, biofilm formation, and cellular damage in a murine model of oral candidiasis. In this study, C. albicans-infected mice were injected with or without GW4869. The results proven by macroscopic, microscopic, and ultramicroscopic methods showed that GW4869 treatment exacerbated the oral candidiasis of mice, promoted C. albicans invasion and biofilm formation, and aggravated oral mucosal inflammation and cellular ultrastructural damage. The results are beneficial in the further exploration of the immune mechanism of C. albicans infection.
Pioglitazone Has a Null Association with Inflammatory Bowel Disease in Patients with Type 2 Diabetes Mellitus
Authors: Tseng Chin-Hsiao
Published: December 2022

Pioglitazone shows potential benefits in inflammatory bowel disease (IBD) in preclinical studies, but its effect in humans has not been researched. We used a nationwide database of Taiwan’s National Health Insurance to investigate whether pioglitazone might affect IBD risk. We enrolled 12,763 ever users and 12,763 never users matched on a propensity score from patients who had a new diagnosis of type 2 diabetes mellitus between 1999 and 2008. The patients were alive on 1 January 2009, and they were followed up for a new diagnosis of IBD until 31 December 2011. Propensity score-weighted hazard ratios were estimated, and the interactions between pioglitazone and major risk factors of IBD (i.e., psoriasis, arthropathies, dorsopathies, chronic obstructive pulmonary disease/tobacco abuse, and any of the above) and metformin were investigated. At the end of the follow-up, 113 ever users and 139 never users were diagnosed with IBD. When compared to never users, the hazard ratio for ever users was 0.809 (95% confidence interval: 0.631–1.037); and none of the hazard ratios for ever users categorized by tertiles of cumulative duration and cumulative dose reached statistical significance. No interactions with major risk factors or metformin were observed. Our findings suggested a null effect of pioglitazone on IBD.
Real-Time Collection of Conidia Released from Living Single Colonies of Podosphaera aphanis on Strawberry Leaves under Natural Conditions with Electrostatic Techniques
Authors: Ayabe Shuka , Kimura Yutaka , Umei Naoki , Takikawa Yoshihiro , Kakutani Koji , Matsuda Yoshinori , Nonomura Teruo
Published: December 2022

Powdery mildew fungi produce progeny conidia on conidiophores, and promote the spread of powdery mildew diseases by dispersal of the conidia from conidiophores in the natural environment. To gain insights and devise strategies for preventing the spread of powdery mildew infection, it is important to clarify the ecological mechanism of conidial dispersal from conidiophores. In this study, all of the progeny conidia released from single colonies of strawberry powdery mildew fungus (Podosphaera aphanis (Wallroth) U. Braun and S. Takamatsu var. aphanis KSP-7N) on true leaves of living strawberry plants (Fragaria × ananassa Duchesne ex Rozier cv. Sagahonoka) were consecutively collected over the lifetime of the colony with an electrostatic rotational spore collector (insulator drum) under greenhouse conditions, and counted under a high-fidelity digital microscope. The insulator drum consisted of a round plastic container, copper film, thin and transparent collector film, electrostatic voltage generator, and timer mechanism. When negative charge was supplied from the voltage generator to the copper film, the collector film created an attractive force to trap conidia. The electrostatically activated collector film successfully attracted progeny conidia released from the colony. Experiment was carried out at just one colony on one leaf for each month (in February, May, July, October, November, and December in 2021), respectively. Each collector film was exchanged for a new collector film at 24 h intervals until KSP-7N ceased to release progeny conidia from single colonies. Collection experiments were carried out to estimate the total number of conidia released from a single KSP-7N colony over a 35–45-day period after inoculation. During the fungal lifetime, KSP-7N released an average of 6.7 × 104 conidia from each of the single colonies at approximately 816 h. In addition, conidial release from KSP-7N colonies was largely affected by the light intensity and day length throughout a year; the number of conidia released from single KSP-7N colonies in night-time was clearly smaller than that in daytime, and the time of conidial release from single KSP-7N colonies was shorter by approximately 2 to 4 h in autumn and winter than in spring and summer. The ecological characteristics related to conidial releases from KSP-7N colonies will be helpful information for us to successfully suppress the spread of strawberry powdery mildews onto host plants under greenhouse conditions.
Combined Transcriptomic and Metabolomic Analysis Reveals Insights into Resistance of Arabidopsis bam3 Mutant against the Phytopathogenic Fungus Fusarium oxysporum
Authors: Kalogeropoulou Eleni , Aliferis Konstantinos A. , Tjamos Sotirios E. , Vloutoglou Irene , Paplomatas Epaminondas J.
Published: December 2022

The wilt-inducing strains of Fusarium oxysporum are responsible for severe damage to many economically important plant species. The most cost-effective and environmentally safe method for the management of Fusarium wilt is the use of resistant cultivars when they are available. In the present study, the Arabidopsis genotype with disruptions in the β-amylase 3 (BAM3) gene, which encodes the major hydrolytic enzyme that degrades starch to maltose, had significantly lower susceptibility to Fusarium oxysporum f. sp. raphani (For) compared to wild-type (wt) plants. It showed the lowest disease severity and contained reduced quantities of fungal DNA in the plant vascular tissues when analyzed with real-time PCR. Through metabolomic analysis using gas chromatography (GC)–mass spectrometry (MS) and gene-expression analysis by reverse-transcription quantitative PCR (RT-qPCR), we observed that defense responses of Arabidopsis bam3 mutants are associated with starch-degradation enzymes, the corresponding modification of the carbohydrate balance, and alterations in sugar (glucose, sucrose, trehalose, and myo-inositol) and auxin metabolism.
A Morphometric Analysis of the Santolina chamaecyparissus Complex (Asteraceae)
Authors: Giacò Antonio , De Giorgi Paola , Astuti Giovanni , Caputo Paolo , Serrano Miguel , Carballal Rodrigo , Sáez Llorenç , Bacchetta Gianluigi , Peruzzi Lorenzo
Published: December 2022

The genus Santolina (Asteraceae, Anthemideae) includes 26 species of aromatic evergreen shrubs endemic to the western Mediterranean Basin. Santolina is widely used as ornamental plant, in xerigardening, and in ethnobotany. The Santolina chamaecyparissus complex, including about half of the known species diversity, has been properly investigated on systematic and taxonomic grounds only recently, and a complete morphometric study is still missing. Here we provide a morphometric characterization and comparison of all the 14 species of this complex, using both univariate and multivariate analyses. Our results suggest that species of this complex can be distinguished using combinations of quantitative and qualitative character-states, mostly related to the leaf morphology. The analysis of S. villosa, a tetraploid/hexaploid Spanish endemic, showed that the two cytotypes cannot be safely identified based on morphology. Coupling this evidence with available phylogenetic information, we conclude that there is no reason to split the two cytotypes of S. villosa in two distinct taxa. An identification key for all the species of the complex is presented.
Nephroprotective Activity of Papaloquelite (Porophyllum ruderale) in Thioacetamide-Induced Injury Model
Authors: Vázquez-Atanacio María José , Bautista Mirandeli , González-Cortazar Manasés , Romero-Estrada Antonio , De la O-Arciniega Minarda , Castañeda-Ovando Araceli , Sosa-Gutiérrez Carolina G. , Ojeda-Ramírez Deyanira
Published: December 2022

Acute kidney injury and impaired kidney function is associated with reduced survival and increased morbidity. Porophyllum ruderale is an edible plant endemic to Mexico used in Mexican traditional medicine. The aim of this study was to evaluate the nephroprotective effect of a hydroalcoholic extract (MeOH:water 70:30, v/v) from the aerial parts of P. ruderale (HEPr). Firstly, in vitro the antioxidant and anti-inflammatory activity of HEPr was determined; after the in vivo nephroprotective activity of HEPr was evaluated using a thioacetamide-induced injury model in rats. HEPr showed a slight effect on LPS-NO production in macrophages (15% INO at 40 µg/mL) and high antioxidant activity in the ferric reducing antioxidant power (FRAP) test, followed by the activity on DPPH and ABTS radicals test (69.04, 63.06 and 32.96% of inhibition, respectively). In addition, values of kidney injury biomarkers in urine (urobilinogen, hemoglobin, bilirubin, ketones, glucose, protein, pH, nitrites, leukocytes, specific gravity, and the microalbumin/creatinine) and serum (creatinine, urea, and urea nitrogen) of rats treated with HEPr were maintained in normal ranges. Finally, 5-O-caffeoylquinic, 4-O-caffeoylquinic and ferulic acids; as well as 3-O-quercetin glucoside and 3-O-kaempferol glucoside were identified by HPLC as major components of HEPr. In conclusion, Porophyllum ruderale constitutes a source of compounds for the treatment of acute kidney injury.
Strawberry Biostimulation: From Mechanisms of Action to Plant Growth and Fruit Quality
Authors: Garza-Alonso Carlos Alberto , Olivares-Sáenz Emilio , González-Morales Susana , Cabrera-De la Fuente Marcelino , Juárez-Maldonado Antonio , González-Fuentes José Antonio , Tortella Gonzalo , Valdés-Caballero Marin Virgilio , Benavides-Mendoza Adalberto
Published: December 2022

The objective of this review is to present a compilation of the application of various biostimulants in strawberry plants. Strawberry cultivation is of great importance worldwide, and, there is currently no review on this topic in the literature. Plant biostimulation consists of using or applying physical, chemical, or biological stimuli that trigger a response—called induction or elicitation—with a positive effect on crop growth, development, and quality. Biostimulation provides tolerance to biotic and abiotic stress, and more absorption and accumulation of nutrients, favoring the metabolism of the plants. The strawberry is a highly appreciated fruit for its high organoleptic and nutraceutical qualities since it is rich in phenolic compounds, vitamins, and minerals, in addition to being a product with high commercial value. This review aims to present an overview of the information on using different biostimulation techniques in strawberries. The information obtained from publications from 2000–2022 is organized according to the biostimulant’s physical, chemical, or biological nature. The biochemical or physiological impact on plant productivity, yield, fruit quality, and postharvest life is described for each class of biostimulant. Information gaps are also pointed out, highlighting the topics in which more significant research effort is necessary.
Spatio-Temporal Water Hyacinth Monitoring in the Lower Mondego (Portugal) Using Remote Sensing Data
Authors: Pádua Luís , Duarte Lia , Antão-Geraldes Ana M. , Sousa Joaquim J. , Castro João Paulo
Published: December 2022

Monitoring invasive plant species is a crucial task to assess their presence in affected ecosystems. However, it is a laborious and complex task as it requires vast surface areas, with difficult access, to be surveyed. Remotely sensed data can be a great contribution to such operations, especially for clearly visible and predominant species. In the scope of this study, water hyacinth (Eichhornia crassipes) was monitored in the Lower Mondego region (Portugal). For this purpose, Sentinel-2 satellite data were explored enabling us to follow spatial patterns in three water channels from 2018 to 2021. By applying a straightforward and effective methodology, it was possible to estimate areas that could contain water hyacinth and to obtain the total surface area occupied by this invasive species. The normalized difference vegetation index (NDVI) was used for this purpose. It was verified that the occupation of this invasive species over the study area exponentially increases from May to October. However, this increase was not verified in 2021, which could be a consequence of the adopted mitigation measures. To provide the results of this study, the methodology was applied through a semi-automatic geographic information system (GIS) application. This tool enables researchers and ecologists to apply the same approach in monitoring water hyacinth or any other invasive plant species in similar or different contexts. This methodology proved to be more effective than machine learning approaches when applied to multispectral data acquired with an unmanned aerial vehicle. In fact, a global accuracy greater than 97% was achieved using the NDVI-based approach, versus 93% when using the machine learning approach (above 93%).
Exogenous Application of Glycine Betaine on Sweet Cherry Tree (Prunus avium L.): Effects on Tree Physiology and Leaf Properties
Authors: Serapicos Marta , Afonso Sílvia , Gonçalves Berta , Silva Ana Paula
Published: December 2022

Biostimulants, such as glycine betaine (GB), are a sustainable way to boost productivity and quality in fruit crops, even in adverse environment conditions. Sweet cherry (Prunus avium L.) is an important crop, which is very sensitive to abiotic stress. Known primarily for its fruits, its leaves are also rich in bioactive substances, which, however, still have no commercial value. There are no studies about the effects of GB exogenous application on biochemical parameters of sweet cherry leaves and few studies about effects in sweet cherry tree physiology. This study was conducted in a Portuguese sweet cherry commercial orchard. Lapins sweet cherry trees were treated with a commercial product based on GB, at two different concentrations (0.25% and 0.40%). The applications were performed at three different phenological stages, according to the BBCH (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) scale: 77, 81 and 86 BBCH. Both GB treatments improved leaf water status, photosynthetic pigments, soluble solids content, total phenolic contents, and antioxidant activity, resulting in better leaf water status regulation, greater photosynthetic capacity, and higher antioxidant activity. These results shows that GB can benefit sweet cherry tree physiology and provide new opportunities for sweet cherry leaves valorisation.
Large-Scale Preparation of Uniform Millet Bread-like Durable Benzoxazine-Phthalonitrile Foam with Outstanding Mechanical and Thermal Properties
Authors: Lei Wenwu , Wang Dengyu , Liu Qi , Li Kui , Li Ying , Zhong Fei , Liu Qiancheng , Wang Pan , Feng Wei , Yang Xulin
Published: December 2022

It is essentially important to develop durable polymer foams for services in high-temperature conditions. The current study reported the preparations and properties of a high-performance benzoxazine-phthalonitrile (BZPN) foam by utilizing azodicarbonamide and tween-80 as the blowing agent and stabilizer, respectively. Rheological and curing studies indicated that the appropriate foaming temperature for BZPN foam is below 180 °C, and its foaming viscosity window is below 20 Pa·s. Guided by these results, uniform millet bread-like BZPN foams with decimeter leveling size were successfully realized, suggesting the high prospect of large-scale production. The structural, mechanical, and thermal properties of BZPN foams were then investigated in detail. BZPN foam involves a hierarchical fracture mechanism during the compressive test, and it shows a high compression strength of over 6 MPa. During a burning test over 380 °C, no visible smoke, softening, or droplet phenomena appeared and the macroscopic structure of BZPN foam was well maintained. Mechanically robust, flame-retardant, and uniform large-size BZPN foam are promising light durable materials with high service temperatures, i.e., as filling materials even in a very narrow pipette.
Electropolymerized 4-Aminobenzoic Acid Based Voltammetric Sensor for the Simultaneous Determination of Food Azo Dyes
Authors: Ziyatdinova Guzel , Titova Maria , Davletshin Rustam
Published: December 2022

Electrochemical sensors with polymeric films as a sensitive layer are of high interest in current electroanalysis. A voltammetric sensor based on multi-walled carbon nanotubes (MWCNTs) and electropolymerized 4-aminobenzoic acid (4-ABA) has been developed for the simultaneous determination of synthetic food azo dyes (sunset yellow FCF and tartrazine). Based on the voltammetric response of the dyes’ mixture, the optimal conditions of electropolymerization have been found to be 30-fold potential scanning between −0.3 and 1.5 V, at 100 mV s−1 in the 100 µmol L−1 monomer solution in phosphate buffer pH 7.0. The poly (4-ABA)-based electrode shows a 10.5-fold increase in its effective surface area and a 17.2-fold lower electron transfer resistance compared to the glassy carbon electrode (GCE). The sensor gives a sensitive and selective response to sunset yellow FCF and tartrazine, with the peak potential separation of 232 mV in phosphate buffer pH 4.8. The electrooxidation parameters of dyes have been calculated. Simultaneous quantification is possible in the dynamic ranges of 0.010–0.75 and 0.75–5.0 µmol L−1 for both dyes, with detection limits of 2.3 and 3.0 nmol L−1 for sunset yellow FCF and tartrazine, respectively. The sensor has been tested on orange-flavored drinks and validated with chromatography.
Geometrical and Electronic Analysis of Polyepoxysuccinic Acid (PESA) for Iron Sulfide Scale Inhibition in Oil Wells
Authors: Magadia Patricia , Abdulla Samah , Elbashier Elkhansa , Hussein Ibnelwaleed A. , Khaled Mazen , Saad Mohammed
Published: December 2022

Scale formation causes major losses in oil wells, related to production and equipment damages. Thus, it is important to develop effective materials to prevent scale formation and inhibit any additional formation. One known environmentally friendly material with promising performance for scale inhibition is polyepoxysuccinic acid (PESA). However, the performance and further development of any scale treatment chemical is highly affected by its electronic structure and behavior. Thus, this paper aims to obtain insights into the kinetics and thermodynamics of the chemical reactions during scale inhibition by investigating the geometrical and electronic structure of PESA. Density Functional Theory (B3LYP/6–31 g (d)-lanl2dz) was used to study the structure of PESA, considering different forms of PESA and their corresponding binding affinities and chemical behaviors. The scale is represented as FeII ions, and PESA is modeled as (n = 1, and 2). Three conditions of PESA were considered: the standard form, the form with a modified electron donating group (R- = CH3-), and ammonium salt of PESA (M+ = NH4+). The results showed that PESA has a high binding affinity to FeII, comparable to known chelating agents, with the highest binding affinity for ammonium salt of PESA with the CH3- donating group (−1530 kJ/mol). The molecular orbitals (MO), electron affinity (EA), and charge analysis further explained the findings. The HOMO-LUMO gap and EA results revealed the high reactivity and thermodynamic stability of all forms of PESA. In addition, the ammonium salt form of PESA with the electron donating group performs better, as it has a greater overall negative charge in the compounds. Furthermore, the NH4+ cationic group tends to lower the value of the HOMO orbital, which increases the inhibition performance of PESA.
Association Measure and Compact Prediction for Chemical Process Data from an Information-Theoretic Perspective
Authors: Luo Lei , He Ge , Zhang Yuequn , Ji Xu , Zhou Li , Dai Yiyang , Dang Yagu
Published: December 2022

Mutual information (MI) has been widely used for association mining in complex chemical processes, but how to precisely estimate MI between variables of different numerical types, discriminate their association relationships with targets and finally achieve compact and interpretable prediction has not been discussed in detail, which may limit MI in more complicated industrial applications. Therefore, this paper first reviews the existing information-based association measures and proposes a general framework, GIEF, to consistently detect associations and independence between different types of variables. Then, the study defines four mutually exclusive association relations of variables from an information-theoretic perspective to guide feature selection and compact prediction in high-dimensional processes. Based on GIEF and conditional mutual information maximization (CMIM), a new algorithm, CMIM-GIEF, is proposed and tested on a fluidized catalytic cracking (FCC) process with 217 variables, one which achieves significantly improved accuracies with fewer variables in predicting the yields of four crucial products. The compact variables identified are also consistent with the results of Shapley Additive exPlanations (SHAP) and industrial experience, proving good adaptivity of the method for chemical process data.
A Robust Hammerstein-Wiener Model Identification Method for Highly Nonlinear Systems
Authors: Sun Lijie , Hou Jie , Xing Chuanjun , Fang Zhewei
Published: December 2022

The existing results show the applicability of the Over-Parameterized Model based Hammerstein-Wiener model identification methods. However, it requires to estimate extra parameters and performer a low rank approximation step. Therefore, it may give rise to unnecessarily high variance in parameter estimates for highly nonlinear systems, especially using a small and noisy data set. To overcome this corruptive phenomenon. To overcome this corruptive phenomenon, in this paper, a robust Hammerstein-Wiener model identification method is developed for highly nonlinear systems when using a small and noisy data set, where two parsimonious parametrization models with fewer parameters are used, and an iteration method is then used to retrieve the true system parameters from the parametrization models. Such modification can improve the parameter estimation performance in terms of accuracy and variance compared with the over-parametrization model based identification methods. All the above-mentioned developments are analyzed with variance analysis, along with a simulation example to confirm the effectiveness.
Technological Assessment on Steam Reforming Process of Crude Glycerol to Produce Hydrogen in an Integrated Waste Cooking-Oil-Based Biodiesel Production Scenario
Authors: Naranje Vishal , Swarnalatha R. , Batra Ojas , Salunkhe Sachin
Published: December 2022

The current scenario of society is to produce fuel from renewable energy resources. The purpose of this research work is to develop an integrated approach for glycerol valorization and biodiesel production. Employing a range of methodologies widely used in the industry, technical analysis and assessments of the process’s applicability in real-world situations are also made. The integrated process plant is simulated using Aspen Plus®. Several different sensitivity analyses are carried out to describe the process that improves efficiency and are designed to maximize hydrogen recovery from the reforming section. The integrated process results are compared with several existing standalone biodiesel production processes. Additionally, the results are verified with the theoretical studies on glycerol valorization. The outcomes of the process plant simulation reveal coherent results with the current industrial standards for the two processes. The results show that the amount of glycerol produced (stream 7) is 60.72 kmol/h in mass flow rate, this translates to 7272.74 kg/h. The hydrogen produced is 488.76 kmol/h and, in mass flow rate, this translates to 985.3 kg/h. The total yield of hydrogen produced is around 13%. The biodiesel yield is at 92.5%. It shows a realistic recovery that would be attained if the process is implemented, contrary to theoretical studies.
Late Medieval Mysticism and the Analogy of Grace and Nature
Authors: Wojtulewicz Christopher M.
Published: December 2022

Erich Przywara’s insightful and Christological interpretation of Aquinas’ maxim regarding grace and nature suggests that nature and reason ought to pass through a redemptive ‘death’ with respect to grace and faith. This highlights the inadmissibility of proportioning finality to nature and reason. But more can be said regarding this particular reclamation of a high scholastic view. The late medieval mystical tradition shows a relationship between grace and nature, faith and reason, which sheds further light on this project, and in particular offers a way of valorising a Christological understanding of the relationship within each pair. I propose that this occurs specifically within the mystical context when any and all finality ascribed to apophasis ‘dies’, resulting in an oscillation between both ontic and noetic expressions of transcendence and immanence. This includes the question of mystical claims to spiritually outgrow ecclesial contexts and specificities. I highlight this with particular reference to Meister Eckhart and Jan van Ruusbroec.
Global Wheat Production and Threats to Supply Chains in a Volatile Climate Change and Energy Crisis
Authors: Halecki Wiktor , Bedla Dawid
Published: December 2022

As climate change and energy crises increase, NPK (nitrogen, phosphorus and potassium) fertilizer supply chains become more volatile. Globally, the Russian attack on Ukraine has caused the cost of gas to rise and fertilizer supplies to decline. This aggression may worsen the energy and wheat resource crisis in global supply chains. As a result of the escalation of hostilities, natural gas, oil, and coal prices have rapidly increased. In the years preceding the conflict, the agricultural sector had already begun to suffer, caused by unprecedented increases in the prices of natural gas and raw materials for the production of fertilizers stemming from Russian manipulation, especially in the gas market. Prior to the growing season, farmers were still unable to afford fertilizer prices. This situation will be exacerbated by the war. We can conclude from our results that European countries and the United States have high wheat production potential. Developed countries have significant nitrogen, phosphorus, and potassium fertilizer resources. Ukraine has a large yield gap, ranging between 4.5 and 7 Mg/ha. Wheat supply crises can be caused by tense geopolitical affairs, including military aggression and economic embargoes. Based on this, we recommend that decision-makers focus on crop quality to increase the country’s own production.
Mutli-Robot Cooperative Object Transportation with Guaranteed Safety and Convergence in Planar Obstacle Cluttered Workspaces via Configuration Space Decomposition
Authors: Vlantis Panagiotis , Bechlioulis Charalampos P. , Kyriakopoulos Kostas J.
Published: December 2022

In this work, we consider the autonomous object transportation problem employing a team of mobile manipulators within a compact planar workspace with obstacles. As the object is allowed to translate and rotate and each robot is equipped with a manipulator consisting of one or more moving links, the overall system (object and mobile manipulators) should adapt its shape in a flexible way so that it fulfills the transportation task with safety. To this end, we built a sequence of configuration space cells, each of which defines an allowable set of configurations of the object, as well as explicit intervals for each manipulator’s states. Furthermore, appropriately designed under- and over-approximations of the free configuration space are used in an innovative way to guide the configuration space’s exploration without loss of completeness. In addition, we coupled methodologies based on Reference Governors and Prescribed Performance Control with harmonic maps, in order to design a distributed control law for implementing the transitions specified by the high-level planner, which possesses guaranteed invariance and global convergence properties, thus avoiding the requirement for synchronized motion as inherently dictated by the majority of the related works. Furthermore, the proposed low-level control law does not require continuous information exchange between the robots, which rely only on measurements of the object’s configuration and their own states. Finally, a transportation scenario within a complex warehouse workspace demonstrates the proposed approach and verifies its efficiency.
FlowerPhenoNet: Automated Flower Detection from Multi-View Image Sequences Using Deep Neural Networks for Temporal Plant Phenotyping Analysis
Authors: Das Choudhury Sruti , Guha Samarpan , Das Aankit , Das Amit Kumar , Samal Ashok , Awada Tala
Published: December 2022

A phenotype is the composite of an observable expression of a genome for traits in a given environment. The trajectories of phenotypes computed from an image sequence and timing of important events in a plant’s life cycle can be viewed as temporal phenotypes and indicative of the plant’s growth pattern and vigor. In this paper, we introduce a novel method called FlowerPhenoNet, which uses deep neural networks for detecting flowers from multiview image sequences for high-throughput temporal plant phenotyping analysis. Following flower detection, a set of novel flower-based phenotypes are computed, e.g., the day of emergence of the first flower in a plant’s life cycle, the total number of flowers present in the plant at a given time, the highest number of flowers bloomed in the plant, growth trajectory of a flower, and the blooming trajectory of a plant. To develop a new algorithm and facilitate performance evaluation based on experimental analysis, a benchmark dataset is indispensable. Thus, we introduce a benchmark dataset called FlowerPheno, which comprises image sequences of three flowering plant species, e.g., sunflower, coleus, and canna, captured by a visible light camera in a high-throughput plant phenotyping platform from multiple view angles. The experimental analyses on the FlowerPheno dataset demonstrate the efficacy of the FlowerPhenoNet.
An Examination of the SMAP Operational Soil Moisture Products Accuracy at the Tibetan Plateau
Authors: Deng Khidir Abdalla Kwal , Petropoulos George P. , Bao Yansong , Pavlides Andrew , Saidou Chaibou Abdoul Aziz , Habtemicheal Birhanu Asmerom
Published: December 2022

Surface soil moisture (SSM) plays an essential role in the Earth’s water cycle and land surface processes as well as in vegetative growth, ecological health, and ecosystem properties. Particularly, information on this parameter’s spatiotemporal variability at the Tibetan Plateau is of key importance to the study of climate and the impact of climate change due to it is distinctive characteristics in this area. The present study assesses the operational SSM products provided by the SMAP (Soil Moisture Active and Passive) satellite at the Tibetan Plateau, Naqu observational station, China. In particular, the globally distributed Level 3 operational products, SPL3SMP_36km and the Enhanced Passive SSM Product SPL3SMP_9km, are evaluated in two-phases. SSM and the surface temperature estimates by SPL3SMP_36km and SPL3SMP_9km are compared against corresponding ground data available at the Naqu observation network. All in all, the examined products captured the SSM dynamics in the studied area. The results showed that precipitation is the key driving source of SSM variability. SSM fluctuated significantly and was dependent on precipitation in the studied region. Statistical metrics, such as the root mean square error (RMSE), varied for SPL3SMP_36km and SPL3SMP_9km in the ranges of 0.036–0.083 m3/m3 and 0.074–0.097 m3/m3, respectively. The unbiased RMSE (ubRMSE) was higher than the SMAP uncertainty limit (0.04 m3/m3) in most cases. This study establishes some of the causes for the different performances of SMAP products, mainly, the ancillary input dataset parameterizations, and, specifically, the surface temperature parameterization schemes of SMAP retrieval algorithm is analyzed and discussed. Our research findings highlight, among others, the usefulness of those SSM products from SMAP, particularly in mesoscale studies, providing additional useful insights into the use of those products in practice in China and globally.
Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network
Authors: Kanerva Heini , Honkavaara Eija , Näsi Roope , Hakala Teemu , Junttila Samuli , Karila Kirsi , Koivumäki Niko , Alves Oliveira Raquel , Pelto-Arvo Mikko , Pölönen Ilkka , Tuviala Johanna , Östersund Madeleine , Lyytikäinen-Saarenmaa Päivi
Published: December 2022

Various biotic and abiotic stresses are causing decline in forest health globally. Presently, one of the major biotic stress agents in Europe is the European spruce bark beetle (Ips typographus L.) which is increasingly causing widespread tree mortality in northern latitudes as a consequence of the warming climate. Remote sensing using unoccupied aerial systems (UAS) together with evolving machine learning techniques provide a powerful tool for fast-response monitoring of forest health. The aim of this study was to investigate the performance of a deep one-stage object detection neural network in the detection of damage by I. typographus in Norway spruce trees using UAS RGB images. A Scaled-YOLOv4 (You Only Look Once) network was implemented and trained for tree health analysis. Datasets for model training were collected during 2013–2020 from three different areas, using four different RGB cameras, and under varying weather conditions. Different model training options were evaluated, including two different symptom rules, different partitions of the dataset, fine-tuning, and hyperparameter optimization. Our study showed that the network was able to detect and classify spruce trees that had visually separable crown symptoms, but it failed to separate spruce trees with stem symptoms and a green crown from healthy spruce trees. For the best model, the overall F-score was 89%, and the F-scores for the healthy, infested, and dead trees were 90%, 79%, and 98%, respectively. The method adapted well to the diverse dataset, and the processing results with different options were consistent. The results indicated that the proposed method could enable implementation of low-cost tools for management of I. typographus outbreaks.
Influence of GEDI Acquisition and Processing Parameters on Canopy Height Estimates over Tropical Forests
Authors: Lahssini Kamel , Baghdadi Nicolas , le Maire Guerric , Fayad Ibrahim
Published: December 2022

LiDAR technology has been widely used to characterize structural parameters of forest ecosystems, which in turn are valuable information for forest monitoring. GEDI is a spaceborne LiDAR system specifically designed to measure vegetation’s vertical structure, and it has been acquiring waveforms on a global scale since April 2019. In particular, canopy height is an important descriptor of forest ecosystems, as it allows for quantifying biomass and other inventory information. This paper analyzes the accuracy of canopy height estimates from GEDI data over tropical forests in French Guiana and Gabon. The influence of various signal acquisition and processing parameters is assessed to highlight how they impact the estimation of canopy heights. Canopy height models derived from airborne LiDAR data are used as reference heights. Several linear and non-linear approaches are tested given the richness of the available GEDI information. The results show that the use of regression models built on multiple GEDI metrics allows for reaching improved accuracies compared to a direct estimation from a single GEDI height metric. In a notable way, random forest improves the canopy height estimation accuracy by almost 80% (in terms of RMSE) compared to the use of rh_95 as a direct proxy of canopy height. Additionally, convolutional neural networks calibrated on GEDI waveforms exhibit similar results to the ones of other regression models. Beam type as well as beam sensitivity, which are related to laser penetration, appear as parameters of major influence on the data derived from GEDI waveforms and used as input for canopy height estimation. Therefore, we recommend the use of only power and high-sensitivity beams when sufficient data are available. Finally, we note that regression models trained on reference data can be transferred across study sites that share identical environmental conditions.
Gale Wind Speed Retrieval Algorithm Using Ku-Band Radar Data Onboard GPM Satellite
Authors: Panfilova Maria , Karaev Vladimir
Published: December 2022

An algorithm to retrieve the wind speed within a wide swath from the normalized radar cross section (NRCS) is developed for the data of Ku-band radar operating in scanning mode installed onboard the Global Precipitation Measurement (GPM) satellite. NRCS at the nadir is calculated within a wide swath and is used to obtain the wind speed. The scatterometer data are used to obtain the dependence between NRCS at the nadir and the wind speed for gale winds. The algorithm was validated also using the Advanced Scatterometer (ASCAT) data and revealed good accuracy.
Linear and Nonlinear Characteristics of Long-Term NDVI Using Trend Analysis: A Case Study of Lancang-Mekong River Basin
Authors: Zhong Xuzhen , Li Jie , Wang Jinliang , Zhang Jianpeng , Liu Lanfang , Ma Jun
Published: December 2022

Vegetation is the main body of the terrestrial ecosystem and is a significant indicator of environmental changes in the regional ecosystem. As an essential link connecting South Asia and Southeast Asia, the Lancang-Mekong River Basin(LMRB) can provide essential data support and a decision-making basis for the assessment of terrestrial ecosystem environmental changes and the research and management of hydrology and water resources in the basin by monitoring changes in its vegetation cover. This study takes the Lancang-Mekong River Basin as the study area, and employs the Sen slope estimation, Mann–Kendall test, and Hurst exponent based on the MODIS NDVI data from 2000 to 2021 to study the spatial and temporal evolution trend and future sustainability of its NDVI. Besides, the nonlinear characteristics such as mutation type and mutation year are detected and analyzed using the BFAST01 method. Results demonstrated that: (1) In the past 22 years, the NDVI of the Lancang-Mekong River Basin generally exhibited a fluctuating upward trend, and the NDVI value in 2021 was the largest, which was 0.825, showing an increase of 4.29% compared with 2000. However, the increase rate was different: China has the most considerable NDVI growth rate of 7.25%, followed by Thailand with an increase of 7.21%, Myanmar and Laos as the third, while Cambodia and Vietnam have relatively stable vegetation changes. The overall performance of NDVI is high in the south and low in the north, and is dominated by high and relatively high vegetation coverage, of which the area with vegetation coverage exceeding 0.8 accounts for 62%. (2) The Sen-MK trend showed that from 2000 to 2021, the area where the vegetation coverage in the basin showed a trend of increase and decrease accounted for 66.59% and 18.88%, respectively. The Hurst exponent indicated that the areas where NDVI will continue to increase, decrease, and remain unchanged in the future account for 60.14%, 25.29%, and 14.53%, respectively, and the future development trend of NDVI is uncertain, accounting for 0.04%. Thus, more attention should be paid to areas with a descending future development trend. (3) BFAST01 detected eight NDVI mutation types in the Lancang-Mekong River Basin over the past 22 years. The mutations mainly occurred in 2002–2018, while 2002–2004 and 2014–2018 were the most frequent periods of breakpoints. The mutation type of “interruption: increase with negative break” was changed the most during this period, which accounts for 36.54%, and the smallest was “monotonic decrease (with negative break)”, which only accounts for 0.65%. This research demonstrates that combining the conventional trend analysis method with the BFAST mutation test can more accurately analyze the spatiotemporal variation and nonlinear mutation of NDVI, thus providing a scientific reference to develop ecological environment-related work.
Wuhan MST Radar Observations of a Tropopause Descent Event during Heavy Rain on 1–2 June 2015
Authors: Qi Hao , Chen Gang , Lin Yiming , Gong Wanlin , Chen Feilong , Li Yaxian , Zhou Xiaoming
Published: December 2022

During heavy rain on 1–2 June 2015 in central China, the Wuhan mesosphere–stratosphere–troposphere (MST) radar was applied to record the atmospheric responses to the rain with a 30 min period. According to the vertical gradient of the echo power above 500 hPa, the tropopause height could be determined by MST radar detection. The tropopause descent was clearly observed by the Wuhan MST radar a few hours before the rain, and then the tropopause recovered to usual heights during the rain. The observation of the radiosonde in Wuhan was in line with that of the radar. Both the potential vorticity and the ozone mass mixing ratio variations at 100 hPa level implied the fall of the tropopause. During the tropopause decent, enhanced radar echoes appeared in the upper troposphere, the echo spectral widths became broader, and the large vertical wind velocities were recorded and indicated the occurrence of strong convective activities. The relative humidity was also found to increase at all tropospheric heights, including the region close to the tropopause. The convective flow may have transported water vapor to the tropopause heights, and a temperature decrease in this region was also recorded. It is very likely that water vapor cooling induced the tropopause descent.
High-Dimensional Seismic Data Reconstruction Based on Linear Radon Transform–Constrained Tensor CANDECOM/PARAFAC Decomposition
Authors: Ouyang Zhiyuan , Zhang Liqi , Wang Huazhong , Yang Kai
Published: December 2022

Random noise and missing seismic traces are common in field seismic data, which seriously affects the subsequent seismic processing flow. The complete noise-free high-dimensional seismic dataset in the frequency–space (f-x) domain under the local linear assumption are regarded as a low-rank tensor, and each high dimensional seismic dataset containing only one linear event is a rank-1 tensor. The tensor CANDECOM/PARAFAC decomposition (CPD) method estimates complete noise-free seismic signals by characterizing high-dimensional seismic signals as the sum of several rank-1 tensors. In order to improve the stability and effect of the tensor CPD algorithm, this paper proposes a linear Radon transform–constrained tensor CPD method (RCPD) by using the sparsity of factor matrix in the Radon domain after high-dimensional seismic signal tensor CPD and uses alternating direction multiplier method (ADMM) to solve the established optimization problem. This proposed method is an essential realization of the high-dimensional linear Radon transform, and the results of synthetic and field data reconstruction prove the effectiveness of the proposed method.
Inversion and Monitoring of the TP Concentration in Taihu Lake Using the Landsat-8 and Sentinel-2 Images
Authors: Liang Yongchun , Yin Fang , Xie Danni , Liu Lei , Zhang Yang , Ashraf Tariq
Published: December 2022

Eutrophication is a significant factor that damages the water ecosystem’s species balance. The total phosphorus (TP) concentration is a vital water quality indicator in assessing surface water eutrophication. This paper predicts the spatial distribution of TP concentration using remote sensing, measured data, and the partial least squares regression (PLSR) method. Based on the correlation analysis, the models were built and tested using the TP concentration and Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 Operational Land Imager (OLI) image spectra. The results demonstrated that the best technique based on band combinations of the Sentinel-2 and Landsat-8 images achieved good precision. The coefficient of determination (R2), root mean square error of prediction (RMSEP), and residual prediction deviation (RPD) were 0.771, 0.023 mg/L, and 2.086 for Sentinel-2 images and 0.630, 0.032 mg/L, and 1.644 for Landsat-8 images, respectively. The TP concentration maps were interpolated using the inverse distance weighting method, and the inversion results obtained from the images were in good agreement. The western and northwestern regions of Taihu Lake, where significant cyanobacterial blooms occurred, had TP concentrations greater than 0.20 mg/L; nevertheless, the central and eastern regions had amounts ranging from 0.05 to 0.20 mg/L. In order to prove the extensibility of the model, the optimal algorithm was applied to the Sentinel-2 and Landsat-8 images in 2017. The optimal algorithm based on Landsat-8 images has a better verification effect (RMSEP = 0.027 mg/L, and R = 0.879 for one Landsat-8 image), and the optimal algorithm based on Sentinel-2 images has moderate verification effect (RMSEP = 0.054 mg/L and 0.045 mg/L, and R = 0.771 and 0.787 for two Sentinel-2 images). The interpolation and inversion maps are in good agreement, indicating that the model is suitable for the Landsat-8 and Sentinel-2 images, which can be complementary for higher temporal resolutions. Monitoring water quality using multiple remote sensing images can provide the scientific basis for water quality dynamic monitoring and prevention in China.