bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Structural Features of Hydrocinnamic Acid Related to Its Allelopathic Activity against the Parasitic Weed Cuscuta campestris
Authors: Moreno-Robles Antonio , Cala Peralta Antonio , Zorrilla Jesús G. , Soriano Gabriele , Masi Marco , Vilariño-Rodríguez Susana , Cimmino Alessio , Fernández-Aparicio Mónica
Published: October 2022

Cuscuta campestris is a parasitic weed species that inflicts worldwide noxious effects in many broadleaf crops due to its capacity to withdraw nutrients and water directly from the crop vascular system using haustorial connections. Cuscuta campestris control in the majority of crops affected is non-existent, and thus, research for the development of control methods is needed. Hydrocinnamic acid occurs naturally in the rhizosphere, playing regulatory roles in plant–plant and plant–microbe communities. The toxicity of hydrocinnamic acid against C. campestris was recently identified. In the present work, a structure–activity relationship study of 21 hydrocinnamic acid analogues was performed to identify key structural features needed for its allelopathic action against the seedling growth of this parasitic plant. The findings of this study provide the first step for the design of herbicides with enhanced activity for the control of C. campestris infection.
Bioactive Compounds Produced in Leaves of Mulberry (Morus alba L.) Transplants under Modified Environments of Root and Aerial Zones
Authors: Win Aye Nwe , Sankhuan Darunmas , Chintakovid Watcharra , Supaibulwatana Kanyaratt
Published: October 2022

Different shoot/root micro-environments were investigated for growth performances and nutraceutical compounds in leaves of mulberry (Morus alba L.) transplants. Single-node segments were taken from seedling-grown pots of three cultivars: Myanmar large leaf (MLL), Myanmar medium leaf (MML), and C14. Transplant production was compared in soil, vermiculite (V), or the dynamic root floating technique (DRFT). The highest survival percentage of the transplants was obtained from V-system, and MLL showed a higher shoot/root formation over two tested cultivars. The MLL transplants grown in V-system under white LED light (445 and 554 nm) at 200 μmol·m−2·s−1 gave a fresh weight with superior qualified transplants compared to other treatments. The bioactive compounds in leaves of MLL, MML, and C14 were analyzed using GC–MS after incubation with different LED spectra. Ethanol extracts of the leaves revealed that more than 50% of the bioactive compounds were fatty acids and conjugates and varied according to spectra and cultivar. Blue LED light (445 nm) induced the production of total phenolics, whereas white LED light favored the production of total proteins, soluble sugar, and biomass. The modified environments at the root and aerial zones significantly influenced the growth and biochemical parameters of transplants, and this applied technique can elevate useful functional ingredients of mulberry leaves.
Conventional and Omics Approaches for Understanding the Abiotic Stress Response in Cereal Crops—An Updated Overview
Authors: Rakkammal Kasinathan , Priya Arumugam , Pandian Subramani , Maharajan Theivanayagam , Rathinapriya Periyasamy , Satish Lakkakula , Ceasar Stanislaus Antony , Sohn Soo-In , Ramesh Manikandan
Published: October 2022

Cereals have evolved various tolerance mechanisms to cope with abiotic stress. Understanding the abiotic stress response mechanism of cereal crops at the molecular level offers a path to high-yielding and stress-tolerant cultivars to sustain food and nutritional security. In this regard, enormous progress has been made in the omics field in the areas of genomics, transcriptomics, and proteomics. Omics approaches generate a massive amount of data, and adequate advancements in computational tools have been achieved for effective analysis. The combination of integrated omics and bioinformatics approaches has been recognized as vital to generating insights into genome-wide stress-regulation mechanisms. In this review, we have described the self-driven drought, heat, and salt stress-responsive mechanisms that are highlighted by the integration of stress-manipulating components, including transcription factors, co-expressed genes, proteins, etc. This review also provides a comprehensive catalog of available online omics resources for cereal crops and their effective utilization. Thus, the details provided in the review will enable us to choose the appropriate tools and techniques to reduce the negative impacts and limit the failures in the intensive crop improvement study.
Exogenous Spermidine Promotes Germination of Aged Sorghum Seeds by Mediating Sugar Metabolism
Authors: Zhang Min , Li Bang , Wan Zuliang , Chen Xiaofei , Liu Chang , Liu Chunjuan , Zhou Yufei
Published: October 2022

Starch, a substance stored in seeds, is the main source of energy for germination in sorghum seeds. However, as the seeds age, the catabolism of seed starch is affected, thereby seriously damaging germination ability. In this study, we aimed to understand how exogenous spermidine promoted germination in aged sorghum seed. Our phenotypic analysis indicated that exogenous spermidine not only significantly improved the germination rate, germination potential, germination index, and vigor index of aged seeds, but also increased the root and shoot length after germination. Further, physiological analysis showed that exogenous spermidine increased the content of soluble sugar by upregulating the activity of amylase and sucrose invertase. Exogenous spermidine also improved the activities of key enzymes in glycolysis, the tricarboxylic acid cycle, and the pentose phosphate pathway of aged sorghum seeds. Interestingly, exogenous spermidine protected the mitochondrial structure of aged seeds, which was consistent with the increase in the respiration rate and ATP content during seed germination. Moreover, qRT-PCR analysis revealed that exogenous spermidine induced the expression of key genes related to starch and sugar metabolism in aged sorghum seeds. In conclusion, our study demonstrated that exogenous spermidine promoted aged sorghum seed germination by regulating starch and sugar metabolism.
An Integrative Approach to the Flavonoid Profile in Some Plants’ Parts of the Annona Genus
Authors: Ramos Ana Luiza Coeli Cruz , Mazzinghy Ana Carolina do Carmo , Correia Vinícius Tadeu da Veiga , Nunes Bruna Vieira , Ribeiro Lucas Victor , Silva Viviane Dias Medeiros , Weichert Reginaldo Ferreira , Paula Ana Cardoso Clemente Filha Ferreira de , Sousa Isabel Maria Nunes de , Ferreira Ricardo Manuel de Seixas Boavida , Batista-Santos Paula , Araújo Raquel Linhares Bello de , Melo Júlio Onésio Ferreira
Published: October 2022

The Annonaceae family is widely distributed in subtropical and tropical regions. Several species of this family are known for their pharmacological and beneficial properties to human health, mainly attributed to flavonoids. The objective of this work was to carry out an integrative review in order to identify the main flavonoids found in some plant parts belonging to the Annona genus: araticum tree (Annona crassiflora Mart.), graviola tree (Annona muricata), atemoya tree (Annona cherimolia Mill × Annona squamosa L.), pinha tree (Annona squamosa), bananinha tree (Annona leptopetala), and marolinho tree (Annona coriacea). Only articles published between the years 2016 to 2021 that answered the guiding question were considered, in order to obtain recent data. Then, search strategies were designated for each database used: Science Direct, CAPES Periodicals, and Scielo. Most of the studies retrieved from the databases are related to fruits. The results showed that the number of flavonoids identified varies according to the analytical methodology used to identify and quantify the compounds. Quercetin was the most commonly found compound in all fruits of the Annona genus studied, and epicatechin, rutin, and kaempferol were also found to a lesser extent. The presence of these compounds in Annona makes the fruit promising, with potential applicability in the pharmaceutical and food industry.
Hydrogen Production from Methanol–Water Solution and Pure Water Electrolysis Using Nanocomposite Perfluorinated Sulfocationic Membranes Modified by Polyaniline
Authors: Sanchez Carlos , Espinos Francisco J. , Barjola Arturo , Escorihuela Jorge , Compañ Vicente
Published: October 2022

In this work, we report the preparation of Nafion membranes containing two different nanocomposite MF-4SC membranes, modified with polyaniline (PANI) by the casting method through two different polyaniline infiltration procedures. These membranes were evaluated as a polymer electrolyte membrane for water electrolysis. Operating conditions were optimized in terms of current density, stability, and methanol concentration. A study was made on the effects on the cell performance of various parameters, such as methanol concentration, water, and cell voltage. The energy required for pure water electrolysis was analyzed at different temperatures for the different membranes. Our experiments showed that PEM electrolyzers provide hydrogen production of 30 mL/min, working at 160 mA/cm2. Our composite PANI membranes showed an improved behavior over pristine perfluorinated sulfocationic membranes (around 20% reduction in specific energy). Methanol–water electrolysis required considerably less (around 65%) electrical power than water electrolysis. The results provided the main characteristics of aqueous methanol electrolysis, in which the power consumption is 2.34 kW h/kg of hydrogen at current densities higher than 0.5 A/cm2. This value is ~20-fold times lower than the electrical energy required to produce 1 kg of hydrogen by water electrolysis.
Stability of Postcritical Deformation of CFRP under Static ±45° Tension with Vibrations
Authors: Wildemann Valeriy , Staroverov Oleg , Strungar Elena , Lunegova Ekaterina , Mugatarov Artur
Published: October 2022

The paper presents an experimental study on regularities of postcritical deformation of carbon-fiber-reinforced plastic (CFRP) under static ±45° tension. The employed test method is based on ASTM D3518. Displacement and strain fields were identified by a digital image correlation method (DIC) using a VIC-3D contactless optical video system. Acoustic emission signals were obtained using an AMSY-6 system. The surface analysis of samples was carried out using a CarlZeiss SteREO Discovery. V12 optical stereomicroscope and a DinoLite microscope. Three experimental test types were considered: active loading, deformation with unloadings, and tension under additional torsion vibrations with various amplitudes. Loading diagrams were constructed; they showed a number of stages in the damage accumulation process. It was analyzed how heterogeneous strain fields develop; a neck development during softening process was observed. It was noted that the loading system rigidity influences the failure moment. The research considered various shear strain calculation methods using a “virtual extensometer” instrument. Composite mechanical properties were obtained. A shear modulus reduction during a plastic strain increase was revealed. The acoustic emission signals were analyzed; three characteristic frequency bands were observed. Most of the contribution to cumulative energy was made by matrix cracking. A reduction of the number of AE signals associated with the violation of adhesion between the fibers and the matrix during postcritical deformation was observed. The research identified basic surface defects. An appearance of the defects corresponds with their identification by the AE system. It was revealed that the presence of additional torsion vibration leads to an increase in the softening stage length. It was concluded that due regard for the postcritical deformation stage and the loading system rigidity is reasonable during the structure strength analysis.
Nano-Encapsulation of Citrus Essential Oils: Methods and Applications of Interest for the Food Sector
Authors: Oprea Ioana , Fărcaș Anca Corina , Leopold Loredana Florina , Diaconeasa Zoriţa , Coman Cristina , Socaci Sonia Ancuța
Published: October 2022

Citrus essential oils possess many health-promoting benefits and properties of high interest in the food and agri-food sector. However, their large-scale application is limited by their sensitivity to environmental factors. Nanostructures containing citrus essential oils have been developed to overcome the high volatility and instability of essential oils with respect to temperature, pH, UV light, etc. Nanostructures could provide protection for essential oils and enhancement of their bioavailability and biocompatibility, as well as their biological properties. Nano-encapsulation is a promising method. The present review is mainly focused on methods developed so far for the nano-encapsulation of citrus essential oils, with emphasis on lipid-based (including liposomes, solid lipid nanoparticles, nanostructured lipid particles, and nano- and micro-emulsions) and polymer-based nanostructures. The physico-chemical characteristics of the obtained structures, as well as promising properties reported, with relevance for the food sector are also discussed.
TPV Foaming by CO2 Extrusion: Processing and Modelling
Authors: Rainglet Benoit , Besognet Paul , Benoit Cyril , Delage Karim , Bounor-Legaré Véronique , Forest Charlène , Cassagnau Philippe , Chalamet Yvan
Published: October 2022

This work focuses on the extrusion foaming under CO2 of commercial TPV and how the process influences the final morphology of the foam. Moreover, numerical modelling of the cell growth of the extrusion foaming is developed. The results show how a precise control on the saturation pressure, die geometry, temperature and nucleation can provide a homogeneous foam having a low density (<500 kg/m3). This work demonstrates that an optimum of CO2 content must be determined to control the coalescence phenomenon that appears for high levels of CO2. This is explained by longer residence times in the die (time of growth under confinement) and an early nucleation (expansion on the die destabilizes the polymer flow). Finally, this work proposes a model to predict the influence of CO2 on the flow (plasticizing effect) and a global model to simulate the extrusion process and foaming inside and outside the die. For well-chosen nucleation parameters, the model predicts the final mean radius of the cell foam as well as final foam density.
Study on Low-Temperature and Fatigue Performance of High RAP Content Hot Recycled Asphalt Mixture Based on the Degree of Blending (DOB)
Authors: Wu Jianming , Sun Hao , Wan Lixia , Yang Jiangang , Wang Shuyi
Published: October 2022

This paper selected three kinds of AC-20 hot-mix recycled asphalt mixtures with high RAP content (30%, 40%, and 50%). It obtains a mixture of different degrees of miscibility by changing RAP preheating temperatures and mixing temperatures. The calculation formula of the degree of blending (DOB) of RAP asphalt interface recycling is proposed. The DSR test quantitatively characterized the DOB mixture’s low temperature, and fatigue properties were tested by beam bending test and four-point bending fatigue test. The prediction models of the recycled mixture’s low temperature and fatigue properties were proposed. The RAP preheating temperature is the most critical factor that dominates both transfers of RAP asphalt to the surface of new aggregate and the effective blending of old and new asphalt. DOB has a significant great influence on low-temperature performance and fatigue performance. The DOB of recycled asphalt can be improved by adjusting and optimizing the process parameters of plant hot recycled mixture to effectively improve the recycled mixture’s low-temperature crack resistance and fatigue lifetime. The optimal RAP dosage and mixing process of required performance can be obtained based on the prediction models to save experimental time and cost.
Different Radial Modification Profiles Observed on APPJ-Treated Polypropylene Surfaces according to the Distance between Plasma Outlet and Target
Authors: Nascimento Fellype do , Leal Bruno Silva , Quade Antje , Kostov Konstantin Georgiev
Published: October 2022

The plasma jet transfer technique relies on a conductive wire at floating potential, which, upon entering in contact with a primary discharge, is capable of igniting a small plasma plume at the distal end of a long flexible plastic tube. In this work, two different long tube configurations were employed for the surface modification of polypropylene (PP) samples using argon as the working gas. One of the jet configurations has a thin copper (Cu) wire, which was installed inside the long tube. In the other configuration, the floating electrode is a metallic mesh placed between two plastic tubes in a coaxial arrangement. In the first case, the tip of the Cu wire is in direct contact with the working gas at the plasma outlet, whereas, in the second, the inner plastic tube provides an additional dielectric barrier that prevents the conductor from being in contact with the gas. Water contact angle (WCA) measurements on treated PP samples revealed that different surface modification radial profiles are formed when the distance (d) between the plasma outlet and target is changed. Moreover, it was found that the highest WCA reduction does not always occur at the point where the plasma impinges the surface of the material, especially when the d value is small. Through X-ray photoelectron spectroscopy (XPS) analysis, it was confirmed that the WCA values are directly linked to the oxygen-functional groups formed on the PP surfaces after the plasma treatment. An analysis of the WCA measurements along the surface, as well as their temporal evolution, together with the XPS data, suggest that, when the treatment is performed at small d values, the plasma jet removes some functional groups at the point where the plasma hits the surface, thus leading to peculiar WCA profiles.
A Modified Multiparameter Linear Programming Method for Efficient Power System Reliability Assessment
Authors: Zuo Jing , Peng Sui , Yang Yan , Li Zuohong , Zuo Zhengmin , Yu Hao , Lin Yong
Published: October 2022

Power systems face adequacy risks because of the high integration of renewable energy. It is urgent to develop efficient methods for power system operational reliability assessment. Conventional power system reliability assessment methods cannot achieve real-time assessment of system risk because of the high computational complexity and long calculation time. The high computational complexity is mainly caused by a large number of optimal power flow (OPF) calculations. To reduce the computational complexity, this paper transfers the optimal power flow model as a multiparameter linear programming model. Then, the optimal power flow can be obtained by linear calculations. Furthermore, this paper proposes a state reduction method considering the importance index of transmission lines for further improving the calculation efficiency. Case studies are carried out on IEEE standard systems and a provincial power grid in China. Compared with the conventional reliability assessment method, the reliability assessment efficiency of the proposed method increases by 10–40 times, and the assessment error is less than 1%.
The Effects of Graphene Oxide and Reduced Graphene Oxide Conductive Additives on Activated Carbon Supercapacitors
Authors: Strimaitis Jacob , Danquah Samuel Adjepong , Denize Clifford F. , Pradhan Sangram K. , Bahoura Messaoud
Published: October 2022

With their relative ease of production and coupled strong surface functionality and electrical conductivity properties, graphene oxide (GO) and reduced graphene oxide (rGO) are exciting, yet overlooked, graphene-like additive prospects for activated carbon (AC) electrodes in supercapacitors. In this work, we incorporated small amounts of synthesized GO and rGO in AC electrodes via a simple mixing procedure to explore their effects. In addition to materials characterizations, symmetric supercapacitors were made from these electrodes and tested across current densities ranging from 0.1–10 A g−1 and across 10,000 additional charge-discharge cycles at 2 A g−1. Performance measurements indicate that GO and rGO enhance the rate resistance and capacity, respectively, of AC electrodes, but these effects are modest and do not prevent increases in internal resistance over the course of 10,000 cycles. The overall ineffectuality of GO and rGO is reasoned to be due to their isolation and infrequency as a result of the relatively impotent distribution method used.
Investigation on the Injection Pattern of Intermittent Natural Gas Flooding in Ultra-Low Permeability Reservoirs
Authors: Dong Lifei , Li Linxiang , Dong Wenzhuo , Wang Miao , Chen Xiaozhi
Published: October 2022

Natural gas is a viable oil displacement agent in ultra-low-permeability reservoirs due to its good fluidity. It can also cause gas channeling during continuous injection, which limits its oilfield application. In order to relieve gas channeling during natural gas flooding, the injection mode should be changed. The use of intermittent natural gas injection (IGI) after the continuous natural gas injection in an ultra-low-permeability reservoir is proposed, and optimization of the injection parameters is discussed. The results show that IGI can be divided into three stages, the gas injection stage, the well shutting stage and the oil production stage. With the increase in injection time, the oil recovery enhances obviously as a result of IGI because the gas fingering can be controlled at the well shutting stage, and the gas/liquid ratio grows slowly because the gas breakthrough can be reduced at the oil production stage. The oil recovery improves with the increase in cycle time of IGI, while the increase rate reduces evidently after the cycle time reaches 360 min. The oil recovery increment is low if the cycle index exceeds 3 in the ultra-low-permeability reservoir. Thus, the optimal cycle time for each round and the appropriate cycle index of IGI are 360 min and three rounds.
Evaluating the Performance of a Safe Insulin Supply Chain Using the AHP-TOPSIS Approach
Authors: Haji Mona , Kerbache Laoucine , Al-Ansari Tareq
Published: October 2022

People with type 1 diabetes require insulin, a lifesaving and essential medication, to maintain their blood sugar levels below dangerous levels. Unfortunately, the insulin industry faces supply and affordability issues, and patients and their families face an enormous burden. As a result of high prices and lack of availability, individuals are turning to other options for purchasing insulin, such as online pharmacies, which may or may not be legitimate. Despite the necessity of safe insulin for diabetics in the legitimate Pharmaceutical Supply Chain (PSC), few researchers have considered implementing strategies to maximize patient safety for purchasing insulin. Therefore, the current research seeks to bridge this gap and provide cohesive information on overcoming this challenge and maximizing insulin safety. This study employs a Multi-Criteria Decision-Making (MCDM) model that combines Supply Chain Operations Reference (SCOR) metrics, Analytic Hierarchy Process (AHP), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a model that can prioritize and select the best criteria for maximizing insulin safety and achieving the study objective. A comparison of two insulin supply chain scenarios was performed. As a result of this research, adding a traceability technology to the insulin supply chain, specifically blockchain (T42) in scenario 2 provides the best results to the supply chain for maximizing and ensuring the safety of insulin, as compared to scenario 1, where the final score achieved almost 71%. This research provides a useful tool for assessing the safety of other critical goods that customers value in strategic and complex decision-making. Academics, professionals, and decision-makers can benefit from this research using a rigorous scientific decision-support system.
Civic Pride and Political Devotion: The Relics of Thomas Becket in Siena
Authors: Mazzocchio Cecilia
Published: October 2022

Through a survey of archival and primary source material, this article discusses the existence of St. Thomas Becket’s relics in Siena cathedral. The institution’s inventories indicate that, from 1482 until ca. 1529, the relics were housed in an ostensory kept in the sacristy. Today, this object is displayed in the Sala del Tesoro, in the Museum of the Opera del Duomo in Siena. Although the ostensory has been examined in previous scholarship concerned with mapping the cathedral’s heritage, its function as a vessel for the relics of Thomas Becket, and indeed the very presence of these relics in Siena, remain unexplored. Thus, seeking to understand the nature of Becket’s reception in Siena, I examine the whereabouts of his relics within the cathedral, to then widen the investigation to the city at large. The evidence shows that although there were no chapels, altars or churches dedicated to Thomas Becket within the city walls, Siena still engaged with Becket’s sainthood and legacy on multiple levels.
Stratford Caldecott’s Idea of Education
Authors: Lamb Rebekah
Published: October 2022

This essay overviews key aspects of Stratford Caldecott’s idea of liberal arts education, within the Roman Catholic tradition and especially focuses on the centrality of the Eucharist in his thought. It also considers how, according to Caldecott, liberal arts education contains a kind of liturgical affordance or sympathy with the form and nature of worship (within Roman Catholicism). In so doing, this paper offers, to date, the most substantive scholarly introduction to key aspects of Caldecott’s Eucharistic idea of education, within the context of the liberal arts tradition (broadly conceived).
Online Social Behaviors in the Context of Religiosity: A Neural-Networks-Supported Approach to Theists and Atheists
Authors: Jablonska Marta Regina
Published: October 2022

Social media behaviors include those of a religious nature. This paper investigates psychological traits, perceptions, and attitudinal variables concerning manifestations of religiosity on social media of both theists and atheists, as the latter are more overlooked in previous studies. A total of 1358 participants completed a questionnaire. The results suggest associations between the studied variables and religiosity, and differences between theists and atheists. Additionally, this study incorporated artificial neural networks to verify whether religiosity may be grounds for a classification model in the case of online social behaviors. The model correctly predicted 79% of cases. This study examined religiosity from the perspectives of anxiety, coping, social support, discrimination, and social media expectations and behaviors, and showed that religiosity is an important factor to include in online social behavior studies.
Overexpression of ErbB-1 (EGFR) Protein in Eutopic Endometrium of Infertile Women with Severe Ovarian Endometriosis during the ‘Implantation Window’ of Menstrual Cycle
Authors: Poorasamy Jeevitha , Garg Deepali , Bharti Juhi , Nambirajan Aruna , Patil Asmita , Sengupta Jayasree , Ghosh Debabrata
Published: October 2022

The strong association between endometriosis and infertility is of high clinical significance. High proliferative bias in eutopic endometrium during the secretory phase is a hallmark of endometriosis, which may result in high occurrence of implantation failure and resultant infertility in endometriosis. The ErbB family of proteins regulates the proliferation capacity in the endometrium, potentially causing endometrial hostility to the implantation process in endometriosis. However, our knowledge regarding the involvement of the ErbB family in human endometrium during the window of implantation (WOI) in endometriosis-associated infertility is scant. In the present study, the cellular profiles of immunopositive ErbBs-1 to -4 in the endometrium of endometriosis-free, infertile women (Group 1; n = 11) and in eutopic endometrium of infertile women diagnosed with stage IV ovarian endometriosis (Group 2; n = 13) during the mid-secretory phase were compared using standardized guidelines. Computer-aided standardized combinative analysis of immunoprecipitation in different compartments revealed an overexpression of ErbB-1 in the epithelial, stromal and vascular compartments, along with marginally higher ErbB-3 expression (p < 0.06) in the vascular compartment and ErbB-4 expression (p < 0.05) in the glandular epithelium and stroma in the endometrium during the WOI in women with primary infertility associated with stage IV ovarian endometriosis compared with disease-free endometrium of control infertile women. It appears that changes in ErbBs in the eutopic endometrium during WOI induce anomalous proliferative, inflammatory and angiogenic activities in it, which can antagonize endometrial preparation for embryo implantation in endometriosis. This knowledge appears usable in strategizing methods for the treatment of endometriosis-associated infertility, as well as preempting the oncogenic potential of endometriosis.
The Effect of CSR Policy on Earnings Management Behavior: Evidence from Visegrad Publicly Listed Enterprises
Authors: Nagy Marek , Valaskova Katarina , Durana Pavol
Published: October 2022

A corporate socially responsible-focused approach adds value to a firm in the form of financial benefits in addition to improving its corporate image. To meet the demands of various stakeholders, including consumers, employees, and shareholders, and to produce high-quality financial reporting, some managers participate in CSR initiatives. The investigation of the relationship between corporate social responsibility and earnings management in publicly listed Visegrad companies is the main aim of the paper. The purpose is to identify the correlation between the CSR concept (measured by ESG score) and earnings management behavior determined by discretionary accrual levels (using the modified Jones model). To ascertain the association between CSR and earnings/discretionary accrual levels or to describe the major changes in the development of these variables, several statistical techniques were applied (correlation analysis, one-way ANOVA, and one-way ANOVA with repeated measures). As this is a pioneering study in the Visegrad environment (analyzing 35 publicly listed enterprises reporting ESG score), the research findings may have significant policy implications for decision-makers, regulators, auditors, and investors in their efforts to restrict earnings management techniques and enhance the quality of financial reporting.
Ionosphere Monitoring with Remote Sensing
Authors: Giannattasio Fabio
Published: October 2022

Characterising the physical properties of the Earth’s ionosphere is fundamental to shed light on the dynamic processes occurring therein on a wide range of both spatial and temporal scales and to understand several phenomena relevant to Space Weather [...]
An All-Sky Scattering Index Derived from Microwave Sounding Data at Dual Oxygen Absorption Bands
Authors: Kan Wanlin , Hu Hao , Weng Fuzhong
Published: October 2022

Combining the temperature sounding channels near 118 GHz onboard Fengyun-3D (FY-3D) with channels near 50 GHz makes it possible to obtain the spatial and vertical distributions of the clouds through a cloud emission and scattering index (CESI). Previous research has shown its advantages in cloud detection over oceans. In this study, the CESI method is expanded and validated under different surface conditions, and angular corrections are conducted to remove the effect of viewing angles. The landfall process of Typhoon MANGKHUT and a case over special terrain are chosen to investigate its sensitivities to different surface types. It is found that the cloud spatial distribution is well demonstrated in both of the cases. Moreover, the CESI vertical distributions are compared with the Global Precipitation Measurement (GPM) hydrometeor profiles. The results show that CESIs are highly related to the GPM hydrometeor profiles in all of the conditions, and the correlations with the sea surface vary with the weighting functions of the matched channels, while the phenomenon is not obvious for the land surface. In addition, the validation results show that the new threshold combination for different surface types at different heights can be more effective for cloud identification. The probability density distribution for most of the channels of the screened-out clear sky data approximates a Gaussian distribution well, and these radiances can be well assimilated into the numerical weather prediction models.
Numerical Modeling and Parameter Sensitivity Analysis for Understanding Scale-Dependent Topographic Effects Governing Anisotropic Reflectance Correction of Satellite Imagery
Authors: Bishop Michael P. , Young Brennan W. , Colby Jeffrey D.
Published: October 2022

Anisotropic reflectance correction (ARC) of satellite imagery is required to remove multi-scale topographic effects in imagery. Commonly utilized ARC approaches have not effectively accounted for atmosphere-topographic coupling. Furthermore, it is not clear which topographic effects need to be formally accounted for. Consequently, we simulate the direct and diffuse-skylight irradiance components and formally account for multi-scale topographic effects. A sensitivity analysis was used to determine if characterization schemes can account for a collective treatment of effects, using our parameterization scheme as a basis for comparison. We found that commonly used assumptions could not account for topographic modulation in our simulations. We also found that the use of isotropic diffuse irradiance and a topographic shielding parameter also failed to characterize topographic modulation. Our results reveal that topographic effects govern irradiance variations in a synergistic way, and that issues of ARC need to be formally addressed given atmosphere-topography coupling. Collectively, our results suggest that empirical ARC methods cannot be used to effectively address topographic effects, given inadequate parameterization schemes. Characterizing and removing spectral variation from multispectral imagery will most likely require numerical modeling efforts. More research is warranted to develop/evaluate parameterization schemes that better characterize the anisotropic nature of atmosphere-topography coupling.
MECA-Net: A MultiScale Feature Encoding and Long-Range Context-Aware Network for Road Extraction from Remote Sensing Images
Authors: Jie Yongshi , He Hongyan , Xing Kun , Yue Anzhi , Tan Wei , Yue Chunyu , Jiang Cheng , Chen Xuan
Published: October 2022

Road extraction from remote sensing images is significant for urban planning, intelligent transportation, and vehicle navigation. However, it is challenging to automatically extract roads from remote sensing images because the scale difference of roads in remote sensing images varies greatly, and slender roads are difficult to identify. Moreover, the road in the image is often blocked by the shadows of trees and buildings, which results in discontinuous and incomplete extraction results. To solve the above problems, this paper proposes a multiscale feature encoding and long-range context-aware network (MECA-Net) for road extraction. MECA-Net adopts an encoder–decoder structure and contains two core modules. One is the multiscale feature encoding module, which aggregates multiscale road features to improve the recognition ability of slender roads. The other is the long-range context-aware module, which consists of the channel attention module and the strip pooling module, and is used to obtain sufficient long-range context information from the channel dimension and spatial dimension to alleviate road occlusion. Experimental results on the open DeepGlobe road dataset and Massachusetts road dataset indicate that the proposed MECA-Net outperforms the other eight mainstream networks, which verifies the effectiveness of the proposed method.
Advances in Remote Sensing of the Inland and Coastal Water Zones
Authors: Lubczonek Jacek , Terefenko Paweł , Bradtke Katarzyna , Wlodarczyk-Sielicka Marta
Published: October 2022

Coastal zone areas are important parts of the environment, very often subject to constant change [...]
Sparse Channel Pruning and Assistant Distillation for Faster Aerial Object Detection
Authors: Deng Chenwei , Jing Donglin , Ding Zhihan , Han Yuqi
Published: October 2022

In recent years, object detectors based on convolutional neural networks have been widely used on remote sensing images. However, the improvement of their detection performance depends on a deeper convolution layer and a complex convolution structure, resulting in a significant increase in the storage space and computational complexity. Although previous works have designed a variety of new lightweight convolution and compression algorithms, these works often require complex manual design and cause the detector to be greatly modified, which makes it difficult to directly apply the algorithms to different detectors and general hardware. Therefore, this paper proposes an iterative pruning framework based on assistant distillation. Specifically, a structured sparse pruning strategy for detectors is proposed. By taking the channel scaling factor as a representation of the weight importance, the channels of the network are pruned and the detector is greatly slimmed. Then, a teacher assistant distillation model is proposed to recover the network performance after compression. The intermediate models retained in the pruning process are used as assistant models. By way of the teachers distilling the assistants and the assistants distilling the students, the students’ underfitting caused by the difference in capacity between teachers and students is eliminated, thus effectively restoring the network performance. By using this compression framework, we can greatly compress the network without changing the network structure and can obtain the support of any hardware platform and deep learning library. Extensive experiments show that compared with existing detection networks, our method can achieve an effective balance between speed and accuracy on three commonly used remote sensing target datasets (i.e., NWPU VHR-10, RSOD, and DOTA).
Spatio-Temporal Changes, Trade-Offs and Synergies of Major Ecosystem Services in the Three-River Headwaters Region from 2000 to 2019
Authors: Liu Guobo , Shao Quanqin , Fan Jiangwen , Ning Jia , Huang Haibo , Liu Shuchao , Zhang Xiongyi , Niu Linan , Liu Jiyuan
Published: October 2022

The Three-River Headwaters Region (TRHR) is an important part of the ecological barrier of the Qinghai–Tibet Plateau. Understanding the TRHR’s major ecosystem service trade-offs and synergies is important for scientifically integrating and optimizing ecosystem services. We studied the spatial–temporal changes, trade-offs and synergies of the TRHR’s water retention (WR), soil retention (SR), windbreak and sand fixation (WD) and forage supply (FS) services from 2000 to 2019. The results showed that: (1) The TRHR’s WR, SR and FS services gradually decreased from east to west in space, and showed an increasing trend between years; the WD service gradually decreased from west to east in space, and showed a downward trend between years. (2) The synergistic relationship was the dominant relationship between the TRHR’s grassland regulation and provision services. Future research on ecosystem service trade-offs and synergies should consider both the type of ecosystem services and the ecosystem’s multifunctionality. (3) The improvement of the TRHR’s ecosystem services in the future needs to focus on improving the fraction vegetation coverage (FVC) through ecological engineering measures in Maduo, and other areas near the 400 mm precipitation line, and enhancing the synergy of ecosystem services. (4) The restoration of TRHR FVC needs to consider the difference in natural endowments. It is recommended to adopt near-natural restoration in the northwest of the TRHR, and avoid setting too high restoration targets. Planting high-quality pastures in the southeast of the TRHR with good water and heat conditions and rationally allocating grassland ecological and production functions are recommended measures. (5) The TRHR’s grassland should give priority to the development of the ecological functions of natural grasslands, and then give full play to its production functions. Overgrazing is strictly prohibited, so as to avoid the “over-transformation” of ecosystem regulation services to supply services.
Research on Self-Supervised Building Information Extraction with High-Resolution Remote Sensing Images for Photovoltaic Potential Evaluation
Authors: Chen De-Yue , Peng Ling , Zhang Wen-Yue , Wang Yin-Da , Yang Li-Na
Published: October 2022

With the rapid development of the energy industry and the growth of the global energy demand in recent years, the development of the photovoltaic industry has become increasingly significant. However, the development of the PV industry is constrained by high land costs, and land in central cities and industrial areas is often very expensive and unsuitable for the installation of PV equipment in large areas. With this background knowledge, the key to evaluating the PV potential is by counting the rooftop information of buildings, and an ideal solution for extracting building rooftop information is from remote sensing satellite images using the deep learning method; however, the deep learning method often requires large-scale labeled samples, and the labeling of remote sensing images is often time-consuming and expensive. To reduce the burden of data labeling, models trained on large datasets can be used as pre-trained models (e.g., ImageNet) to provide prior knowledge for training. However, most of the existing pre-trained model parameters are not suitable for direct transfer to remote sensing tasks. In this paper, we design a pseudo-label-guided self-supervised learning (PGSSL) semantic segmentation network structure based on high-resolution remote sensing images to extract building information. The pseudo-label-guided learning method allows the feature results extracted by the pretext task to be more applicable to the target task and ultimately improves segmentation accuracy. Our proposed method achieves better results than current contrastive learning methods in most experiments and uses only about 20–50% of the labeled data to achieve comparable performance with random initialization. In addition, a more accurate statistical method for building density distribution is designed based on the semantic segmentation results. This method addresses the last step of the extraction results oriented to the PV potential assessment, and this paper is validated in Beijing, China, to demonstrate the effectiveness of the proposed method.
Accuracy Assessment of Photochemical Reflectance Index (PRI) and Chlorophyll Carotenoid Index (CCI) Derived from GCOM-C/SGLI with In Situ Data
Authors: Sasagawa Taiga , Akitsu Tomoko Kawaguchi , Ide Reiko , Takagi Kentaro , Takanashi Satoru , Nakaji Tatsuro , Nasahara Kenlo Nishida
Published: October 2022

The photochemical reflectance index (PRI) and the chlorophyll carotenoid index (CCI) are carotenoid-sensitive vegetation indices, which can monitor vegetation’s photosynthetic activities. One unique satellite named “Global Change Observation Mission-Climate (GCOM-C)” is equipped with a sensor, “Second Generation Global Imager (SGLI)”, which has the potential to frequently and simultaneously observe PRI and CCI over a wide swath. However, the observation accuracy of PRI and CCI derived from GCOM-C/SGLI remains unclear in forests. Thus, we demonstrated their accuracy assessment by comparing them with in situ data. We collected in situ spectral irradiance data at four forest sites in Japan for three years. We statistically compared satellite PRI with in situ PRI, and satellite CCI with in situ CCI. From the obtained results, the satellite PRI showed poor agreement (the best: r=0.294 (p<0.05)) and the satellite CCI showed good agreement (the best: r=0.911 (p<0.001)). The greater agreement of satellite CCI is possibly because satellite CCI contained fewer outliers and satellite CCI was more resistant to small noise, compared to satellite PRI. Our results suggest that the satellite CCI is more suitable for practical use than the satellite PRI with the latest version (version 3) of GCOM-C/SGLI’s products.
Analysis of the Influence of Deforestation on the Microphysical Parameters of Clouds in the Amazon
Authors: da Silva Helder José Farias , Gonçalves Weber Andrade , Bezerra Bergson Guedes , Santos e Silva Cláudio Moisés , Oliveira Cristiano Prestrelo de , Mutti Pedro Rodrigues
Published: October 2022

Studies have shown that deforestation can cause changes in energy, moisture, and precipitation flows, with implications for local and regional climate. These studies generally focus on understanding how the hydrological cycle is impacted by deforestation, but few studies have investigated these impacts on cloud microphysics in tropical forest regions. The objective of this study was to quantitatively evaluate the impacts of deforestation on the microphysical parameters of clouds, based on data extracted from active and passive orbital sensors from the TRMM satellite. The study area comprised the state of Rondônia, Brazil. The analyses of the microphysical parameters extracted from the Microwave Imager (TMI) and Precipitation Radar (PR) sensors of the 2A-CLIM and 2A25 products were performed considering a period of 14 years. The parameters analyzed were Rain Water Path (RWP), Ice Water Path (IWP), Surface Precipitation (SP), Freezing Level Height (FH), and Rainfall Type (RT). Land cover type data were extracted from the Project to Monitor Deforestation in the Legal Amazon (PMDA). Our results showed that local deforestation significantly altered the microphysical parameters of the study region. In general, the values of the microphysical parameters of the clouds in the transition areas (locations where forest pixels are neighbors to deforested pixels) were about 5–25% higher compared to forested and deforested areas associated with a higher frequency of episodes of convective rainfall possibly driven by mesoscale circulations. Correspondingly, forested areas had higher rainfall rates compared to deforested areas. Meanwhile, deforested areas had higher amounts for IWP, of around 1–16%, and FH, of around 2–8%, in relation to forested areas. Conversely, the RWP showed a decrease of around 2–20%. These results suggest that the microphysical structure of clouds has different characteristics when related to forested and deforested areas in the Amazon. This is useful for evaluation of simulations of cloud microphysical parameters in numerical models of weather and climate.