bluuebunny/crossref_metadata_2025 huggingface dataset:
Multivariate Interaction Analysis of Zea mays L. Genotypes Growth Productivity in Different Environmental Conditions
Authors: Ljubičić Nataša , Popović Vera , Kostić Marko , Pajić Miloš , Buđen Maša , Gligorević Kosta , Dražić Milan , Bižić Milica , Crnojević Vladimir
Published: May 2023

Evaluating maize genotypes under different conditions is important for identifying which genotypes combine stability with high yield potential. The aim of this study was to assess stability and the effect of the genotype–environment interaction (GEI) on the grain yield traits of four maize genotypes grown in field trials; one control trial without nitrogen, and three applying different levels of nitrogen (0, 70, 140, and 210 kg ha−1, respectively). Across two growing seasons, both the phenotypic variability and GEI for yield traits over four maize genotypes (P0725, P9889, P9757 and P9074) grown in four different fertilization treatments were studied. The additive main effects and multiplicative interaction (AMMI) models were used to estimate the GEI. The results revealed that genotype and environmental effects, such as the GEI effect, significantly influenced yield, as well as revealing that maize genotypes responded differently to different conditions and fertilization measures. An analysis of the GEI using the IPCA (interaction principal components) analysis method showed the statistical significance of the first source of variation, IPCA1. As the main component, IPCA1 explained 74.6% of GEI variation in maize yield. Genotype G3, with a mean grain yield of 10.6 t ha−1, was found to be the most stable and adaptable to all environments in both seasons, while genotype G1 was found to be unstable, following its specific adaptation to the environments.
Identification and Expression Analysis of the Isopentenyl Transferase (IPT) Gene Family under Lack of Nitrogen Stress in Oilseed (Brassica napus L.)
Authors: Chen Jingdong , Wan Heping , Zhu Wenhui , Dai Xigang , Yu Yi , Zeng Changli
Published: May 2023

BnIPT gene family members in Brassica napus and analyzing their expression under different exogenous hormones and abiotic stress treatments to provide a theoretical basis for clarifying their functions and molecular genetic mechanisms in nitrogen deficiency stress tolerance of B. napus. Using the Arabidopsis IPT protein as the seed sequence, combined with the IPT protein domain PF01715, 26 members of the BnIPT gene family were identified from the whole genome of the rape variety ZS11. Additionally, the physicochemical properties and structures, phylogenetic relationships, synteny relationships, protein–protein interaction network, and gene ontology enrichment were analyzed. Based on transcriptome data, the expression patterns of the BnIPT gene under different exogenous hormone and abiotic stress treatments were analyzed. We used the qPCR method to identify the relative expression level of BnIPT genes that may be related to the stress resistance of rapeseed in transcriptome analysis under normal nitrogen (N: 6 mmol·L−1) and nitrogen deficiency (N: 0) conditions and analyzed its effect on rapeseed under nitrogen deficiency stress role in tolerance. In response to nitrogen deficiency signals, the BnIPT gene showed a trend of up-regulation in shoots and down-regulation in roots, indicating that it may affect the process of nitrogen transport and redistribution to enhance the stress resistance of rapeseed to respond to the nitrogen deficiency stress. This study provides a theoretical basis for clarifying the function and molecular genetic mechanism of the BnIPT gene family in nitrogen deficiency stress tolerance in rape.
Plant Tolerance to Drought Stress with Emphasis on Wheat
Authors: Adel Sarah , Carels Nicolas
Published: May 2023

Environmental stresses, such as drought, have negative effects on crop yield. Drought is a stress whose impact tends to increase in some critical regions. However, the worldwide population is continuously increasing and climate change may affect its food supply in the upcoming years. Therefore, there is an ongoing effort to understand the molecular processes that may contribute to improving drought tolerance of strategic crops. These investigations should contribute to delivering drought-tolerant cultivars by selective breeding. For this reason, it is worthwhile to review regularly the literature concerning the molecular mechanisms and technologies that could facilitate gene pyramiding for drought tolerance. This review summarizes achievements obtained using QTL mapping, genomics, synteny, epigenetics, and transgenics for the selective breeding of drought-tolerant wheat cultivars. Synthetic apomixis combined with the msh1 mutation opens the way to induce and stabilize epigenomes in crops, which offers the potential of accelerating selective breeding for drought tolerance in arid and semi-arid regions.
Effects of Nigella sativa Oil Fractions on Reactive Oxygen Species and Chemokine Expression in Airway Smooth Muscle Cells
Authors: Mosbah Asma , Khither Hanane , Mosbah Camélia , Slimani Abdelkader , Mahrouk Abdelkader , Akkal Salah , Nieto Gema
Published: May 2023

Background: many previous studies have demonstrated the therapeutic potential of N. sativa total oil fractions, neutral lipids (NLs), glycolipids (GLs), phospholipids (PLs), and unsaponifiable (IS) in asthma patients. We therefore tested its effect on airway smooth muscle (ASM) cells by observing its ability to regulate the production of glucocorticoid (GC)-insensitive chemokines in cells treated with TNF-α/IFN-γ, and its antioxidative and reactive oxygen species (ROS) scavenging properties. Materials and methods: the cytotoxicity of N. sativa oil fractions was assessed using an MTT assay. ASM cells were treated with TNF-α/IFN-γ for 24 h in the presence of different concentrations of N. sativa oil fractions. An ELISA assay was used to determine the effect of N. sativa oil fractions on chemokine production (CCL5, CXCL-10, and CXCL-8). The scavenging effect of N. sativa oil fractions was evaluated on three reactive oxygen species (ROS), O2•−, OH•, and H2O2. Results: our results show that different N. sativa oil fractions used at 25 and 50 µg/mL did not affect cell viability. All fractions of N. sativa oil inhibited chemokines in a concentration-dependent manner. Interestingly, the total oil fraction showed the most significant effect of chemokine inhibition, and had the highest percentage of ROS scavenging effect. Conclusion: these results suggest that N. sativa oil modulates the proinflammatory actions of human ASM cells by inhibiting the production of GC-insensitive chemokines.
The Metabolic Profile of Young, Watered Chickpea Plants Can Be Used as a Biomarker to Predict Seed Number under Terminal Drought
Authors: Purdy Sarah J. , Fuentes David , Ramamoorthy Purushothaman , Nunn Christopher , Kaiser Brent N. , Merchant Andrew
Published: May 2023

Chickpea is the second-most-cultivated legume globally, with India and Australia being the two largest producers. In both of these locations, the crop is sown on residual summer soil moisture and left to grow on progressively depleting water content, finally maturing under terminal drought conditions. The metabolic profile of plants is commonly, correlatively associated with performance or stress responses, e.g., the accumulation of osmoprotective metabolites during cold stress. In animals and humans, metabolites are also prognostically used to predict the likelihood of an event (usually a disease) before it occurs, e.g., blood cholesterol and heart disease. We sought to discover metabolic biomarkers in chickpea that could be used to predict grain yield traits under terminal drought, from the leaf tissue of young, watered, healthy plants. The metabolic profile (GC-MS and enzyme assays) of field-grown chickpea leaves was analysed over two growing seasons, and then predictive modelling was applied to associate the most strongly correlated metabolites with the final seed number plant−1. Pinitol (negatively), sucrose (negatively) and GABA (positively) were significantly correlated with seed number in both years of study. The feature selection algorithm of the model selected a larger range of metabolites including carbohydrates, sugar alcohols and GABA. The correlation between the predicted seed number and actual seed number was R2 adj = 0.62, demonstrating that the metabolic profile could be used to predict a complex trait with a high degree of accuracy. A previously unknown association between D-pinitol and hundred-kernel weight was also discovered and may provide a single metabolic marker with which to predict large seeded chickpea varieties from new crosses. The use of metabolic biomarkers could be used by breeders to identify superior-performing genotypes before maturity is reached.
Improving Flavonoid Accumulation of Bioreactor-Cultured Adventitious Roots in Oplopanax elatus Using Yeast Extract
Authors: Jin Mei-Yu , Wang Miao , Wu Xiao-Han , Fan Ming-Zhi , Li Han-Xi , Guo Yu-Qing , Jiang Jun , Yin Cheng-Ri , Lian Mei-Lan
Published: May 2023

Oplopanax elatus is an endangered medicinal plant, and adventitious root (AR) culture is an effective way to obtain its raw materials. Yeast extract (YE) is a lower-price elicitor and can efficiently promote metabolite synthesis. In this study, the bioreactor-cultured O. elatus ARs were treated with YE in a suspension culture system to investigate the elicitation effect of YE on flavonoid accumulation, serving for further industrial production. Among YE concentrations (25-250 mg/L), 100 mg/L YE was the most suitable for increasing the flavonoid accumulation. The ARs with various ages (35-, 40-, and 45-day-old) responded differently to YE stimulation, where the highest flavonoid accumulation was found when 35-day-old ARs were treated with 100 mg/L YE. After YE treatment, the flavonoid content increased, peaked at 4 days, and then decreased. By comparison, the flavonoid content and antioxidant activities in the YE group were obviously higher than those in the control. Subsequently, the flavonoids of ARs were extracted by flash extraction, where the optimized extraction process was: 63% ethanol, 69 s of extraction time, and a 57 mL/g liquid–material ratio. The findings provide a reference for the further industrial production of flavonoid-enriched O. elatus ARs, and the cultured ARs have potential application for the future production of products.
Phytochemical Characterization of Saudi Mint and Its Mediating Effect on the Production of Silver Nanoparticles and Its Antimicrobial and Antioxidant Activities
Authors: Qanash Husam , Bazaid Abdulrahman S. , Binsaleh Naif K. , Alharbi Bandar , Alshammari Nawaf , Qahl Safa H. , Alhuthali Hayaa M. , Bagher Abdullatiff A.
Published: May 2023

The green synthesis of nanoparticles (NPs) is attracting enormous attention as a new area of study that encompasses the development and discovery of new agents for their utilization in different fields, such as pharmaceuticals and food. Nowadays, the use of plants, particularly medicinal plants, for the creation of NPs has emerged as a safe, ecofriendly, rapid, and simple approach. Therefore, the present study aimed to use the Saudi mint plant as a medicinal plant for the synthesis of silver nanoparticles (AgNPs) and to evaluate the antimicrobial and antioxidant activities of AgNPs compared to mint extract (ME). A phenolic and flavonoid analysis that was conducted by using HPLC indicated the presence of numerous compounds in the ME. Through an HPLC analysis, chlorogenic acid at a concentration of 7144.66 µg/mL was the main detected component in the ME, while catechin, gallic acid, naringenin, ellagic acid, rutin, daidzein, cinnamic acid, and hesperetin were identified in varying concentrations. AgNPs were synthesized by using ME and were confirmed via UV–visible spectroscopy at 412 nm of the maximum absorption. The mean diameter of the synthesized AgNPs was measured by TEM to be 17.77 nm. Spectra obtained by using energy-dispersive X-ray spectroscopy indicated that silver was the main element formation in the created AgNPs. The presence of various functional groups, analyzed by using Fourier transform infrared spectroscopy (FTIR), indicated that the mint extract was responsible for reducing Ag+ to Ag0. The spherical structure of the synthesized AgNPs was confirmed by X-ray diffraction (XRD). Furthermore, the ME showed reduced antimicrobial activity (a zone of inhibition of 30, 24, 27, 29, and 22 mm) compared with the synthesized AgNPs (a zone of inhibition of 33, 25, 30, 32, 32, and 27 mm) against B. subtilis, E. faecalis, E. coli, P. vulgaris, and C. albicans, respectively. The minimum inhibitory concentration of the AgNPs was lower than that of the ME for all of the tested micro-organisms, except for P. vulgaris. The MBC/MIC index suggested that the AgNPs revealed a higher bactericidal effect compared to the ME. The synthesized AgNPs exhibited antioxidant activity with a reduced IC50 (IC50 of 8.73 µg/mL) compared to that of the ME (IC50 of 13.42 µg/mL). These findings demonstrate that ME could be applied as a mediator for AgNPs synthesis and natural antimicrobial and antioxidant agents.
Nanofluids of Amphiphilic Kaolinite-Based Janus Nanosheets for Enhanced Oil Recovery: The Importance of Stable Emulsion
Authors: Mao Yixuan , Lanzon Alain Luigi , Zheng Botuo , Xu Zhengxiao , Jiang Jiatong , Harbottle David , Yu Kai , Chen Mingfeng , Sheng Yu , Zhang Huagui
Published: May 2023

To meet the increasing global demand for energy, better recovery of crude oil from reservoirs must be achieved using methods that are economical and environmentally benign. Here, we have developed a nanofluid of amphiphilic clay-based Janus nanosheets via a facile and scalable method that provides potential to enhance oil recovery. With the aid of dimethyl sulfoxide (DMSO) intercalation and ultrasonication, kaolinite was exfoliated into nanosheets (KaolNS) before being grafted with 3-methacryloxypropyl-triemethoxysilane (KH570) on the Alumina Octahedral Sheet at 40 and 70 °C to form amphiphilic Janus nanosheets (i.e., KaolKH@40 and KaolKH@70). The amphiphilicity and Janus nature of the KaolKH nanosheets have been well demonstrated, with distinct wettability obtained on two sides of the nanosheets, and the KaolKH@70 was more amphiphilic than the KaolKH@40. Upon preparing Pickering emulsion in a hydrophilic glass tube, the KaolKH@40 preferentially stabilized emulsions, while the KaolNS and KaolKH@70 tended to form an observable and high-strength elastic planar interfacial film at the oil–water interface as well as films climbing along the tube’s surface, which were supposed to be the result of emulsion instability and the strong adherence of Janus nanosheets towards tube’s surface. Subsequently, the KaolKH was grafted with poly(N-Isopropylacrylamide) (PNIPAAm), and the prepared thermo-responsive Janus nanosheets demonstrated a reversible transformation between stable emulsion and the observable interfacial films. Finally, when the samples were subjected to core flooding tests, the nanofluid containing 0.01 wt% KaolKH@40 that formed stable emulsions showed an enhanced oil recovery (EOR) rate of 22.37%, outperforming the other nanofluids that formed observable films (an EOR rate ~13%), showcasing the superiority of Pickering emulsions from interfacial films. This work demonstrates that KH-570-modified amphiphilic clay-based Janus nanosheets have the potential to be used to improve oil recovery, especially when it is able to form stable Pickering emulsions.
Supervenience and the Public Health Standard for Psychoactive Substances
Authors: Chaiton Michael
Published: May 2023

This paper uses Geoffrey Rose’s theory of population health change to identify that part of lack of resolution of the harm reduction debates emerges from the philosophical question of the possibility of group-level causation. Group-level causation, otherwise known as the supervenience of higher levels onto lower levels, has been a core matter of philosophical and ethical debate. This paper argues that there, the public health standard depends crucially on the contextual environment rather than the individual product’s intrinsic properties. Interpretation of the benefits or the harms of e-cigarettes or other harm reduction products depends on the often unstated assumptions of the potential policy and cultural environments in which e-cigarettes exist, as well as the separate debate over the absolute or relative level of harm of e-cigarettes. Unfortunately, most of the research conducted will not contribute to our understanding of the potential impact of e-cigarettes until we focus on the potential changes to the social and political environment.
The Conversation around Islam on Twitter: Topic Modeling and Sentiment Analysis of Tweets about the Muslim Community in Spain since 2015
Authors: González-Baquero William , Amores Javier J. , Arcila-Calderón Carlos
Published: May 2023

Social media, especially Twitter, has become a platform where hate, toxic, intolerant, and discriminatory speech is increasingly spread. These messages are aimed at different vulnerable social groups, due to some of their differentiating characteristics with respect to the dominant one, whether they are phenotypic, religious, cultural, gender, sexual, etc. Of all these minorities, one of the most affected is the Muslim community, especially since the beginning of the Mediterranean refugee crisis, during which migration from the Middle East and North Africa increased considerably. Spain does not escape this reality as, given its proximity to Morocco, it is one of the main destinations for migrants from North Africa. In this context, there are already several studies focused on specifically investigating Islamophobic speech disseminated on social platforms, normally focused on specific cases. However, there are still no studies focused on analyzing the entire conversation around Islam and the Muslim community that takes place on Twitter and in a southern European country such as Spain, aiming to identify the latent sentiments and the main underlying topics and their characteristics, which would help to relativize and dimension the relevance of Islamophobic messages, as well as to analyze them from a more solid base. The main objective of the present study is to identify the most frequent words, the main underlying topics, and the latent sentiments that predominate in the general conversation about Islam and the Muslim community on Twitter in Spain and in Spanish during the last 8 years. To do this, 190,320 messages that included keywords related to Muslim culture and religion were collected and analyzed using computational techniques. The findings show that the most frequent words in these messages were mostly descriptive and not derogatory, and the predominant latent topics were mostly neutral and informative, although two of them could be considered reliable indicators of Islamophobic rejection. Similarly, while the overall average sentiment in this conversation trended negatively, neutral and positive messages were more prevalent. However, in the negative messages, the sentiment was considerably more pronounced.
Methodology for Mapping the Ecological Security Pattern and Ecological Network in the Arid Region of Xinjiang, China
Authors: Wang Yishan , Zhang Fei , Li Xingyou , Johnson Verner Carl , Tan Mou Leong , Kung Hsiang-Te , Shi Jingchao , Bahtebay Jupar , He Xin
Published: May 2023

Xinjiang is an important arid region in the northwest of China and plays an important role in the field of ecological security protection in China. Because of its aridity, the identification of critical areas for ecological protection and the optimization of ecological space structure in Xinjiang are of great significance for promoting the harmonious development of the oasis economy, enhancing the ecological environment, and improving human well-being. This study applied an ecological security evaluation from the three dimensions of habitat quality, ecosystem service value, and soil-water conservation to identify the basic situation of the ecological security pattern. The core “source” area of ecological protection was extracted using the morphological spatial pattern analysis (MSPA) method, while the ecological corridor and important ecological nodes were identified using the minimum cumulative resistance model (MCR). The “point-line-plane” three-dimensional ecological network structure was then constructed, providing a case for the development of the ecological security and construction in the oasis. The results showed that in the arid regions of Xinjiang, the ecological land is extremely fragmented and is mainly distributed in the mountains and waters distant from human activities. Overall, there is a substantial geographical disparity with a low level of ecological security, particularly in the ecological marginal areas. The ecological network framework of Xinjiang is characterized by an uneven distribution of “sources”, broken corridor structure, and a low degree of networking. Therefore, this study proposed an ecological space layout system consisting of “7 ecological subsystems, 51 source areas, 87 ecological corridors, and 33 ecological nodes” by combining the regional physical and geographical characteristics with the overall development plan.
Warm Core and Deep Convection in Medicanes: A Passive Microwave-Based Investigation
Authors: Panegrossi Giulia , D’Adderio Leo Pio , Dafis Stavros , Rysman Jean-François , Casella Daniele , Dietrich Stefano , Sanò Paolo
Published: May 2023

Mediterranean hurricanes (Medicanes) are characterized by the presence of a quasi-cloud-free calm eye, spiral-like cloud bands, and strong winds around the vortex center. Typically, they reach a tropical-like cyclone (TLC) phase characterized by an axisymmetric warm core without frontal structures. Yet, some of them are not fully symmetrical, have a shallow warm-core structure, and a weak frontal activity. Finding a clear definition and potential classification of Medicanes based on their initiation and intensification processes, understanding the role of convection, and identifying the evolution to a TLC phase are all current research topics. In this study, passive microwave (PMW) measurements and products are used to characterize warm core (WC) and deep convection (DC) for six Medicanes that occurred between 2014 and 2021. A well-established methodology for tropical cyclones, based on PMW temperature sounding channels, is used to identify the WC while PMW diagnostic tools and products (e.g., cloud-top height (CTH) and ice water path (IWP)), combined with lightning data, are used for DC detection and characterization. The application of this methodology to Medicanes highlights the possibility to describe their WC depth, intensity, and symmetry and to identify the cyclone center. We also analyze to what extent the occurrence and characteristics of the WC are related to the Medicane’s intensity and DC development. The results show that Medicanes reaching full TLC phase are associated with deep and symmetric WCs, and that asymmetric DC features in the proximity of the center, and in higher CTH and IWP values, with scarce lighting activity. Medicanes that never develop to a fully TLC structure are associated with a shallower WC, weaker and more sparse DC activity, and lower CTHs and IWP values. Ultimately, this study illustrates the potential of PMW radiometry in providing insights into dynamic and thermodynamic processes associated with Medicanes’ WC characteristics and evolution to TLCs, thus contributing to the ongoing discussion about Medicanes’ definition.
Preliminary Results of the Three-Dimensional Plasma Drift Velocity at East Asian Low-Latitudes Observed by the Sanya Incoherent Scattering Radar (SYISR)
Authors: Jin Yuyan , Zhao Biqiang , Hao Honglian , Yue Xinan , Ding Feng , Ning Baiqi , Zeng Lingqi , Li Zishen
Published: May 2023

As the first advanced modular phase array incoherent scatter radar (ISR) established in the Eastern Hemisphere at low latitudes, Sanya ISR (SYISR) can measure the line-of-sight (LOS) velocity of ion drift in multiple directions, potentially yielding the spatial distribution of ionospheric plasma drift. Three beam-scanning modes are designed for plasma drift detection: meridian, zonal and cross-shaped (both meridian and zonal) plane, which will provide the distribution of plasma drift in latitude/longitude as well as altitude. The altitude profile of plasma drift and the first presented distribution of low latitude plasma drift in the meridian plane for March to May 2021 are inversed through LOS velocity using cross-shaped and meridian beam-scanning modes, respectively. A statistical correlation coefficient between the vpn and crest-to-trough ratio (CTR) of equatorial ionization anomaly (EIA) TEC and a case study of magnetic storm response in plasma drift show that the inversed plasma drift can be a good indicator in response to the changes in atmospheric tide and solar wind at different time scales and explain the corresponding ionospheric electron density variations at low and equatorial latitudes. This study proves that the SYISR-measured plasma drift is reliable and will play an important role in the atmosphere-ionosphere-magnetospheric coupling study in the East Asian region.
Large-Scale Land Subsidence Monitoring and Prediction Based on SBAS-InSAR Technology with Time-Series Sentinel-1A Satellite Data
Authors: Guo Hengliang , Yuan Yonghao , Wang Jinyang , Cui Jian , Zhang Dujuan , Zhang Rongrong , Cao Qiaozhuoran , Li Jin , Dai Wenhao , Bao Haoming , Qiao Baojin , Zhao Shan
Published: May 2023

Rapid urban development in China has aggravated land subsidence, which poses a potential threat to sustainable urban development. It is imperative to monitor and predict land subsidence over large areas. To address these issues, we chose Henan Province as the study area and applied small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) technology to obtain land deformation information for monitoring land subsidence from November 2019 to February 2022 with 364 multitrack Sentinel-1A satellite images. The current traditional time-series deep learning models suffer from the problems of (1) poor results in extracting a sequence of information that is too long and (2) the inability to extract the feature information between the influence factor and the land subsidence well. Therefore, a long short-term memory-temporal convolutional network (LSTM-TCN) deep learning model was proposed in order to predict land subsidence and explore the influence of environmental factors, such as the volumetric soil water layer and monthly precipitation, on land subsidence in this study. We used leveling data to verify the effectiveness of SBAS-InSAR in land subsidence monitoring. The results of SBAS-InSAR showed that the land subsidence in Henan Province was obvious and uneven in spatial distribution. The maximum subsidence velocity was −94.54 mm/a, and the uplift velocity was 41.23 mm/a during the monitoring period. Simultaneously, the land subsidence in the study area presented seasonal changes. The rate of land subsidence in spring and summer was greater than that in autumn and winter. The prediction accuracy of the LSTM-TCN model was significantly better than that of the individual LSTM and TCN models because it fully combined their advantages. In addition, the prediction accuracies, with the addition of environmental factors, were improved compared with those using only time-series subsidence information.
Towards a Digital Twin Prototype of Alpine Glaciers: Proposal for a Possible Theoretical Framework
Authors: Fissore Vanina , Bovio Lorenza , Perotti Luigi , Boccardo Piero , Borgogno-Mondino Enrico
Published: May 2023

The Destination Earth (DestinE) European initiative has recently brought into the scientific community the concept of the Digital Twin (DT) applied to Earth Sciences. Within 2030, a very high precision digital model of the Earth, continuously fed and powered by Earth Observation (EO) data, will provide as many digital replicas (DTs) as the different domains of the earth sciences are. Considering that a DT is driven by use cases, depending on the selected application, the provided information has to change. It follows that, to achieve a reliable representation of the selected use case, a reasonable and complete a priori definition of the needed elements that DT must contain is mandatory. In this work, we define a possible theoretical framework for a future DT of the Italian Alpine glaciers, trying to define and describe all those information (both EO and in situ data) and relationships that necessarily have to enter the process as building blocks of the DT itself. Two main aspects of glaciers were considered and investigated: (i) the “metric quantification” of their spatial dynamics (achieved through measures) and (ii) the “qualitative (semantic) description” of their health status as definable through observations from domain experts. After the first identification of the building blocks, the work proceeds focusing on existing EO data sources providing their essential elements, with specific focus on open access high-resolution (HR) and very-high-resolution (VHR) images. This last issue considered two scales of analysis: local (single glacier) and regional (Italian Alps). Some considerations were furtherly reported about the expected glaciers-related applications enabled by the availability of a DT at regional level. Applications involving both metric and semantic information were considered and grouped in three main clusters: Glaciers Evolution Modelling (GEM), 4D Multi Reality, and Virtual Reality. Limitations were additionally explored, mainly related to the technical characteristics of available EO VHR open data and some conclusions provided.
Micromotion Feature Extraction with VEMW Radar Based on Rotational Doppler Effect
Authors: Lv Kun , Ma Hui , Jiang Xinrui , Bai Jian , Liu Hongwei
Published: May 2023

Micro-Doppler (m-D) analysis is the most effective mechanism for detecting rotating targets or components; however, it fails when the target rotation plane is perpendicular to the radar line of sight (LOS). The vortex electromagnetic wave (VEMW) provides a unconventional structure of wavefront phase modulation on the cross-plane of the radar LOS, on which the radial m-D vanishes while the rotational Doppler (RD) appears. In the absence of the position of rotation center, this paper focuses on the micromotion parameters estimation based on RD effect for rotating target, and then proposes an estimation procedure, referred to as the two-step method. The micromotion parameters of the rotating target include the rotation attitude, the rotation radius and the position of the rotation center while the latter is coupled to the former two. Firstly, the micromotion parameters are roughly estimated based on the RD curve parameters obtained from the time-frequency (TF) spectrum of the received signal. Secondly, the maximum likelihood estimation (MLE) is used to accurately estimate the micromotion parameters. In addition, the Cramér–Rao bound (CRB) of parameter estimation is derived. The simulation studies the influencing factors of estimation performance and verifies that the proposed estimation method can provide excellent estimation accuracy of the micromotion parameters.
Snowpack Dynamics Influence Tree Growth and Signals in Tree Rings of Tianshan Mountain, Central Asia
Authors: Fan Yuting , Li Qian , Shang Huaming , Jiang Shengxia , Zhang Tongwen , Zhang Ruibo , Qin Li , Yu Shulong , Zhang Heli
Published: May 2023

Snow is an important source of freshwater in the Tianshan Mountains of Central Asia. This study established 18 tree ring width chronologies and compound chronologies and analyzed the effects of snow depth, measured both by remote sensing and at meteorological stations, on the radial growth of spruce trees. The results showed that the established standard chronology of tree ring width is suitable for the analysis of tree ring climatology. The correlation coefficient of the ring width index (RWI) and the remote sensing snow depth was greater than that of the meteorological station snow depth. For the remote sensing snow depth, the correlation coefficients were greater in the winter and spring months compare to other periods, while the correlation coefficients of the meteorological stations were greater only in the winter. The nonlinear method (BRNN) showed good fitting in the reconstruction of the historical snow depth. The reconstructed snow depth exhibited a decreasing trend in the Bharakonu Mountains (BM), Narathi Mountains (NM), and Halke mountains (KM) sub-regions in the overall reconstructed period; however, the trends were inconsistent in both the historical and the observed periods, indicating the importance of reconstructing snow depth in the Tianshan Mountains.
Radar Observation of the Lava Tubes on the Moon and Mars
Authors: Qiu Xiaohang , Ding Chunyu
Published: May 2023

The detection of lava tubes beneath the surfaces of the Moon and Mars has been a popular research topic and challenge in planetary radar observation. In recent years, the Moon–based ground penetrating radar (GPR) carried by the Chinese Chang’e–3/–4 mission, the RIMFAX radar carried by the Mars mission Perseverance, and the RoSPR radar and MOSIR radar carried by China’s Tianwen–1 orbiter have extensively promoted the exploration of the underground space of extraterrestrial bodies, which is crucial for the future utilization and development of these spaces. This paper expounds on the principles, methods, and detection results of using GPR to detect lava tubes on the Moon and Mars. First, lava tubes’ formation mechanism and morphological characteristics are outlined, followed by an introduction to GPR’s working principles and classification. The advantages, disadvantages, and prospects of different types of radar in detecting the lava tubes are analyzed. Finally, the distribution of lava tubes on the Moon and Mars is briefly summarized, and the potential utilization of lava tubes is discussed. We believe that the GPR technique is an effective geophysical method for exploring the underground structures of the Moon and Mars, and the lava tubes beneath the surface of extraterrestrial bodies can provide important references for selecting future Moon and Mars bases.
A Review of Hyperspectral Image Super-Resolution Based on Deep Learning
Authors: Chen Chi , Wang Yongcheng , Zhang Ning , Zhang Yuxi , Zhao Zhikang
Published: May 2023

Hyperspectral image (HSI) super-resolution (SR) is a classical computer vision task that aims to accomplish the conversion of images from lower to higher resolutions. With the booming development of deep learning (DL) technology, more and more researchers are dedicated to the research of image SR techniques based on DL and have made remarkable progress. However, no scholar has provided a comprehensive review of the field. As a response, in this paper we aim to supply a comprehensive summary of the DL-based SR techniques for HSI, including upsampling frameworks, upsampling methods, network design, loss functions, representative works with different strategies, and future directions, in which we design several sets of comparative experiments for the advantages and limitations of two-dimensional convolution and three-dimensional convolution in the field of HSI SR and analyze the experimental results in depth. In addition, the paper also briefly discusses the secondary foci such as common datasets, evaluation metrics, and traditional SR algorithms. To the best of our knowledge, this paper is the first review on DL-based HSI SR.
The Application of a Convolutional Neural Network for the Detection of Contrails in Satellite Imagery
Authors: Hoffman Jay P. , Rahmes Timothy F. , Wimmers Anthony J. , Feltz Wayne F.
Published: May 2023

This study presents a novel approach for the detection of contrails in satellite imagery using a convolutional neural network (CNN). Contrails are important to monitor because their contribution to climate change is uncertain and complex. Contrails are found to have a net warming effect because the clouds prevent terrestrial (longwave) radiation from escaping the atmosphere. Globally, this warming effect is greater than the cooling effect the clouds have in the reduction of solar (shortwave) radiation reaching the surface during the daytime. The detection of contrails in satellite imagery is challenging due to their similarity to natural clouds. In this study, a certain type of CNN, U-Net, is used to perform image segmentation in satellite imagery to detect contrails. U-Net can accurately detect contrails with an overall probability of detection of 0.51, a false alarm ratio of 0.46 and a F1 score of 0.52. These results demonstrate the effectiveness of using a U-Net for the detection of contrails in satellite imagery and could be applied to large-scale monitoring of contrail formation to measure their impact on climate change.
Understanding Social Media Dependency, and Uses and Gratifications as a Communication System in the Migration Era: Syrian Refugees in Host Countries as a Case Study
Authors: Aldamen Yasmin
Published: May 2023

Through the theoretical frameworks of the media system dependency model and uses and gratifications theory, this study examined the uses of social media by Syrian refugees in Jordan and Turkey. A mixed-methods approach was used to increase the credibility and validity of the study’s findings by combining a qualitative method with quantitative data. The findings show that there were some factors that affected the Syrian refugees’ use of social media before seeking refuge in Jordan and Turkey, which were mainly its ban due to the regime’s censorship and a bad Internet connection due to the bad infrastructure. The absence of these two factors led to an increase in their social media dependency after seeking refuge. There are variances in which social media sites Syrian refugees use the most and why. The majority relied on Facebook for various reasons, and this dependency had varying repercussions on individuals. Furthermore, many immigrants were acquainted with new platforms, implying that refugees became social-media-literate and participated in the updates of the new platforms, even if such sites were not well known to the general public. The Syrian refugees’ dependency on social media varies from person to person due to differences in personal goals, social status, locations, living characteristics, and easy access to the Internet. Furthermore, this dependency on social media has different effects on them according to the media system dependency model. The refugees become increasingly dependent on social media to satisfy their needs and, because of that, social media dependency will become more important in their lives and will increase its influence and effects on them. Furthermore, the study found that the Syrian refugees depended on social media for various gratifications, such as educational, work, and business; information access; cultural and social aspects; connecting with networks and families; establishing friendships; learning new skills; self-expression; making business; and finding work, in addition to reaching routes and contacting smugglers to help them leave the country.
Economic and Technological Efficiency of Renewable Energy Technologies Implementation
Authors: Wang Wei , Melnyk Leonid , Kubatko Oleksandra , Kovalov Bohdan , Hens Luc
Published: May 2023

Recent trends prove that energy production is shifting from traditional fossil fuel combustion technologies to renewable energy-based technologies. To estimate the economic efficiency of renewable energy technology implementation, the data for the EU-27 member states during the 2012–2021 period were collected; additionally, technological efficiency was analyzed based on a critical literature review. Breusch and Pagan Lagrangian multiplier tests were employed to select the most suitable econometric model. The results suggest that an increase in the share of renewable energy sources by one percentage point (1) decreased CO2 emissions by 0.137 metric tons per capita (technological efficiency) and (2) decreased greenhouse gases by 13 g per EUR, in terms of GDP (economic efficiency). Regarding the Kyoto Protocol implementation, it was found for EU-27 that an increase in the share of renewable energy sources by one percentage point was related to a decrease of one percentage point in the greenhouse gases index. GDP per capita appeared to be an insignificant driver for reductions in per capita CO2 emissions, while it proved to be important for economic efficiency models. Thus, increasing GDP per capita by 1000 USD reduces greenhouse gases by 7.1 g per EUR of GDP in EU-27. This paper also confirmed that a unit of electricity (1 kWh) generated by traditional energy plants is seven to nineteen times more environmentally costly than renewable energy generation. This paper thus concludes that digital transformations and additive manufacturing brought about the significant dematerialization of industrial production and the promotion of renewable energy on industrial and household levels.
Simulation-Based Engineering of Heterogeneous Collaborative Systems—A Novel Conceptual Framework
Authors: Perišić Ana , Perišić Ines , Perišić Branko
Published: May 2023

We discuss the collaboration support of loosely coupled Smart Systems through configurable hyper-frameworks. Based on the system-of-systems (SoS) paradigm, in this article, we propose the model of a novel extendible conceptual framework with domain-specific moderation support for model-based simulations and the engineering of complex heterogeneous systems. The domain knowledge meta-model and corresponding management enterprise architecture enable the creation of template-based specializations. The proposed SoS conceptual framework meta-model represents an initial framework prototype that supports modeling, simulation, analysis, and utilization of dynamic architecting of heterogeneous SoS configurations. A Smart-Habitat concept encapsulating Smart-Area, Smart-City, Smart-Lot, Smart-Building, and Smart-Unit abstractions illustrate the frameworks’ applicability. The proposed SoS conceptual framework represents the initial conceptual support for modeling, simulation, analysis, and dynamic architecting of heterogeneous SoS configurations. We plan to refine the component architecture meta-model, specify a language workbench with Domain-Specific Orchestration Language support, and verify the configuration-based simulation manifest creation. These actions lead to the framework’s next stage, an operational framework (OF) instance, as a transitional artifact to the aimed software framework (SwF) counterpart.
Features of Nautical Tourism in Portugal—Projected Destination Image with a Sustainability Marketing Approach
Authors: Cardoso Lucília , Lopes Eunice , Almeida Giovana Goretti Feijó de , Lima Santos Luís , Sousa Bruno , Simões Jorge , Perna Fernando
Published: May 2023

Nautical tourism stands out for its potential to achieve social-economic development in coastal and island destinations and as a lever for sustainable tourism. However, the lack of a clear definition of nautical tourism at the international level makes it difficult to characterize it, and the case of Portugal is no exception. In fact, despite the enormous potential of Portuguese nautical tourism, there is a lack of studies that characterize this type of tourism in the Portuguese tourism destination. This paper intends to make a first attempt to fill this gap by assessing the projected destination image of Portuguese nautical tourism with a sustainable marketing approach. In the design of the research, the content analysis methodology was applied. The data were collected from the official websites of the Portuguese legislation and the Portuguese nautical tourism players and analyzed through a theoretical model of sustainable marketing deriving from the literature review. The results provide the sustainable projected destination image of Portuguese nautical tourism and identify the main trends in the legislative framework, tourism activities, networks of players, and support infrastructures for Portuguese nautical tourism. The findings provide practical and useful insights for Portuguese nautical tourism stakeholders aiming to improve a sustainable projected destination image, as well as for researchers identifying research gaps in the nautical tourism topics. This study also provides a new methodological contribution, proposing a theoretical model of the projected destination image of nautical tourism with an approach to sustainable marketing, which can be applied to other nautical tourism destinations.
A CNNA-Based Lightweight Multi-Scale Tomato Pest and Disease Classification Method
Authors: Xu Yanlei , Gao Zhiyuan , Zhai Yuting , Wang Qi , Gao Zongmei , Xu Zhao , Zhou Yang
Published: May 2023

Tomato is generally cultivated by transplanting seedlings in ridges and furrows. During growth, there are various types of tomato pests and diseases, making it challenging to identify them simultaneously. To address this issue, conventional convolutional neural networks have been investigated, but they have a large number of parameters and are time-consuming. In this paper, we proposed a lightweight multi-scale tomato pest and disease classification network, called CNNA. Firstly, we constructed a dataset of tomato diseases and pests consisting of 27,193 images with 18 categories. Then, we compressed and optimized the ConvNeXt-Tiny network structure to maintain accuracy while significantly reducing the number of parameters. In addition, we proposed a multi-scale feature fusion module to improve the feature extraction ability of the model for different spot sizes and pests, and we proposed a global channel attention mechanism to enhance the sensitivity of the network model to spot and pest features. Finally, the model was trained and deployed to the Jetson TX2 NX for inference of tomato pests and diseases in video stream data. The experimental results showed that the proposed CNNA model outperformed the pre-trained lightweight models such as MobileNetV3, MobileVit, and ShuffleNetV2 in terms of accuracy and all parameters, with a recognition accuracy of 98.96%. Meanwhile, the error rate, inference time for a single image, network parameters, FLOPs, and model size were only 1%, 47.35 ms, 0.37 M, 237.61 M, and 1.47 MB, respectively.