bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Festuca glauca ‘Uchte’ and Festuca amethystina ‘Walberla’ Varieties in a Simulated Extensive Roof Garden Environment
Authors: Hamar-Farkas Dóra , Kisvarga Szilvia , Ördögh Máté , Orlóci László , Honfi Péter , Kohut Ildikó
Published: August 2024

One of the most effective means of increasing urban green areas is the establishment of roof gardens. They have many positive properties and ecological functions, such as filling empty spaces with plants, protecting buildings, dust retention and air cleaning. In the case of extensive constructions, mostly Sedum species are used, planted as carpet-like “grass” sods or by installing modular units as plugs; however, with the use of other plant genera, the efficiency of ecological services could be increased by expanding the diversity. Festuca taxa have good drought resistance, and these plants tolerate temperature alterations well. Their application would increase the biodiversity, quality and decorative value of roof gardens. Experiments were carried out on nursery benches imitating a roof garden, with the use of modular elements intended for Sedum species, which facilitate the establishment of green roofs. In our trial, varieties of two European native species, Festuca glauca Vill. ‘Uchte’ and F. amethystina L. ‘Walberla’, were investigated. In order to find and determine the differences between the cultivars and the effects of the media (leaf mold and rhyolite tuff), we drew inferences after morphological (height, circumference, root weight, fresh and dry weight) and physiological tests (peroxidase and proline enzyme activity). We concluded that F. glauca ‘Uchte’ is recommended for roof garden conditions, planted in modular elements. Although the specimens were smaller in the medium containing fewer organic components than in the version with larger amounts, they were less exposed to the effects of drought stress. This can be a key factor for survival in extreme roof gardens or even urban conditions for all plants.
Effect of Hemp Extraction Procedures on Cannabinoid and Terpenoid Composition
Authors: Chacon Francisco T. , Raup-Konsavage Wesley M. , Vrana Kent E. , Kellogg Joshua J.
Published: August 2024

A variety of techniques have been developed to extract hemp phytochemicals for research and consumption. Some of the most common processes in the industry include supercritical CO2 extraction, hydrodistillation, and solvent-based (ethanol) extractions. Each of these processes has the potential to differentially extract various phytochemicals, which would impact their efficacy, tolerability, and safety. However, despite these differences, there has been no direct comparison of the methods and the resulting phytochemical composition. This work aimed to compare cannabinoid and terpene profiles using the three primary commercial procedures, using hemp inflorescence from a CBD/CBG dominant Cannabis sativa L. cultivar. Extracts were then evaluated for their terpene and cannabinoid content using GC-MS and LC-MS/MS, respectively. Hydrodistilled extracts contained the most variety and abundance of terpenes with β-caryophyllene to be the most concentrated terpene (25–42 mg/g). Supercritical CO2 extracts displayed a minimal variety of terpenes, but the most variety and abundance of cannabinoids with CBD ranging from 12.8–20.6 mg/g. Ethanol extracts contained the most acidic cannabinoids with 3.2–4.1 mg/g of CBDA along with minor terpene levels. The resulting extracts demonstrated substantially different chemical profiles and highlight how the process used to extract hemp can play a large role in product composition and potential biological effects.
The Use of Compost and Arbuscular Mycorrhizal Fungi and Their Combination to Improve Tomato Tolerance to Salt Stress
Authors: Mekkaoui Fadoua , Ait-El-Mokhtar Mohamed , Zaari Jabri Nada , Amghar Ilham , Essadssi Soukaina , Hmyene Abdelaziz
Published: August 2024

Salinity poses a significant challenge to tomato plant development and metabolism. This study explores the use of biostimulants as eco-friendly strategies to enhance tomato plant tolerance to salinity. Conducted in a greenhouse, the research focuses on the Solanum lycopersicum L. behavior under saline conditions. Tomato seeds were treated with arbuscular mycorrhizal fungi (AMF), compost, and their combination under both non-saline and saline conditions (0 and 150 mM NaCl). Plant height, number of flowers and fruits, shoot fresh weight, and root dry weight were negatively impacted by salt stress. The supplementation with compost affected the colonization of AMF, but the application of stress had no effect on this trait. However, the use of compost and AMF separately or in combination showed positive effects on the measured parameters. At the physiological level, compost played a beneficial role in increasing photosynthetic efficiency, whether or not plants were subjected to salinity. In addition, the application of these biostimulants led to an increase in nitrogen content in the plants, irrespective of the stress conditions. AMF and compost, applied alone or in combination, showed positive effects on photosynthetic pigment concentrations and protein content. Under salt stress, characterized by an increase in lipid peroxidation and H2O2 content, the application of these biostimulants succeeded in reducing both these parameters in affected plants through exhibiting an increase in antioxidant enzyme activity. In conclusion, incorporating compost, AMF, or their combined application emerges as a promising approach to alleviate the detrimental impacts of salt stress on both plant performances. These findings indicate optimistic possibilities for advancing sustainable and resilient agricultural practices.
Genome-Wide Identification of B-Box Family Genes and Their Potential Roles in Seed Development under Shading Conditions in Rapeseed
Authors: Chen Si , Qiu Yushan , Lin Yannong , Zou Songling , Wang Hailing , Zhao Huiyan , Shen Shulin , Wang Qinghui , Wang Qiqi , Du Hai , Li Jiana , Qu Cunmin
Published: August 2024

B-box (BBX) proteins, a subfamily of zinc-finger transcription factors, are involved in various environmental signaling pathways. In this study, we conducted a comprehensive analysis of BBX family members in Brassica crops. The 482 BBX proteins were divided into five groups based on gene structure, conserved domains, and phylogenetic analysis. An analysis of nonsynonymous substitutions and (Ka)/synonymous substitutions (Ks) revealed that most BBX genes have undergone purifying selection during evolution. An analysis of transcriptome data from rapeseed (Brassica napus) organs suggested that BnaBBX3d might be involved in the development of floral tissue-specific RNA-seq expression. We identified numerous light-responsive elements in the promoter regions of BnaBBX genes, which were suggestive of participation in light signaling pathways. Transcriptomic analysis under shade treatment revealed 77 BnaBBX genes with significant changes in expression before and after shading treatment. Of these, BnaBBX22e showed distinct expression patterns in yellow- vs. black-seeded materials in response to shading. UPLC-HESI-MS/MS analysis revealed that shading influences the accumulation of 54 metabolites, with light response BnaBBX22f expression correlating with the accumulation of the flavonoid metabolites M46 and M51. Additionally, BnaBBX22e and BnaBBX22f interact with BnaA10.HY5. These results suggest that BnaBBXs might function in light-induced pigment accumulation. Overall, our findings elucidate the characteristics of BBX proteins in six Brassica species and reveal a possible connection between light and seed coat color, laying the foundation for further exploring the roles of BnaBBX genes in seed development.
Recovery of Scots Pine Seedlings from Long-Term Zinc Toxicity
Authors: Ivanov Yury V. , Ivanova Alexandra I. , Kartashov Alexander V. , Kuznetsov Vladimir V.
Published: August 2024

We studied the recovery of the growth and physiological parameters of Scots pine seedlings after long-term zinc toxicity. The removal of excess zinc from the nutrient solution resulted in the rapid recovery of primary root growth but did not promote the initiation and growth of lateral roots. The recovery of root growth was accompanied by the rapid uptake of manganese, magnesium, and copper. Despite the maximum rate of manganese uptake by the roots, the manganese content in the needles of the recovering plants did not reach control values during the 28 days of the experiment, unlike magnesium, iron, and copper. In general, the recovery of ion homeostasis eliminated all of the negative effects on the photosynthetic pigment content in the needles. However, these changes, along with recovery of the water content in the needles, were not accompanied by an increase in the weight gain of the recovering seedlings compared with that of the Zn-stressed seedlings. The increased accumulation of phenolic compounds in the needles persisted for a long period after excess zinc was removed from the nutrient solution. The decreased lignin content in the roots and needles is a characteristic feature of Zn-stressed plants. Moreover, the removal of excess zinc from the nutrient solution did not lead to an increase in the lignin content in the organs.
Genetic Evaluation of Water Use Efficiency and Nutrient Use Efficiency in Populus deltoides Bartr. ex Marsh. Seedlings in China
Authors: Gao Chengcheng , Liu Chenggong , Chen Cun , Liu Ning , Liu Fenfen , Su Xiaohua , Huang Qinjun
Published: August 2024

Populus deltoides Bartr. ex Marsh. represents a valuable genetic resource for fast-growing plantations in temperate regions. It holds significant cultivation and breeding potential in northern China. To establish an efficient breeding population of poplar, we studied the genetic variation of P. deltoides from different provenances. Our focus was on genotypes exhibiting high growth rates and efficient water and nutrient use efficiency (WUE and NUE). We evaluated 256 one-year-old seedlings from six provenances, measuring height, ground diameter, total biomass, and leaf carbon and nitrogen isotope abundance (δ13C and δ15N). Our analytical methods included variance analysis, multiple comparisons, mixed linear models, correlation analysis, and principal component analysis. The results showed that the coefficient of variation was highest for δ15N and lowest for δ13C among all traits. Except for δ15N, the effects of intra- and inter-provenance were highly significant (p < 0.01). The rates of variation for all traits ranged from 78.36% to 99.49% for intra-provenance and from 0.51% to 21.64% for inter-provenance. The heritability of all traits in AQ provenance was over 0.65, and all exhibited the highest level except for seedling height. All traits were significantly positively correlated with each other (p < 0.05), while ground diameter, total biomass, and WUE were highly significantly negatively correlated with latitude (p < 0.01). After a comprehensive evaluation, two provenances and eight genotypes were selected. The genetic gains for seedling height, ground diameter, total biomass, WUE, and NUE were 27.46 cm (178-2-106), 3.85 mm (178-2-141), 16.40 g (178-2-141), 0.852‰ (LA05-N15), and 3.145‰ (174-1-2), respectively. Overall, we revealed that the abundant genetic variation in P. deltoides populations mainly comes from intra-provenance differences and evaluated provenances and genotypes. The results of this study will contribute to optimizing and enhancing the breeding process of Chinese poplar and improving the productivity of fast-growing plantations.
A Hierarchical Model to Predict Time of Flowering of Kiwifruit Using Weather Data and Budbreak Dynamics
Authors: Zhang Jingjing , Alavi Maryam , Guo Lindy , Richardson Annette C. , Kramer-Walter Kris , French Victoria , Jesson Linley
Published: August 2024

Accurate prediction of flowering times is essential for efficient orchard management for kiwifruit, facilitating timely pest and disease control and pollination interventions. In this study, we developed a predictive model for flowering time using weather data and observations of budbreak dynamics for the ‘Hayward’ and ‘Zesy002’ kiwifruit. We used historic data of untreated plants collected from 32 previous studies conducted between 2007 and 2022 and analyzed budbreak and flowering timing alongside cumulative heat sum (growing degree days, GDDs), chilling unit (CU) accumulation, and other environmental variables using weather data from the weather stations nearest to the study orchards. We trained/parameterized the model with data from 2007 to 2019, and then evaluated the model’s efficacy using testing data from 2020 to 2022. Regression models identified a hierarchical structure with the accumulation of GDDs at the start of budbreak, one of the key predictors of flowering time. The findings suggest that integrating climatic data with phenological events such as budbreak can enhance the predictability of flowering in kiwifruit vines, offering a valuable tool for kiwifruit orchard management.
UV-B Stress-Triggered Amino Acid Reprogramming and ABA-Mediated Hormonal Crosstalk in Rhododendron chrysanthum Pall.
Authors: Yu Wang , Zhou Xiangru , Xu Hongwei , Zhou Xiaofu
Published: August 2024

Increased UV-B radiation due to ozone depletion adversely affects plants. This study focused on the metabolite dynamics of Rhododendron chrysanthum Pall. (R. chrysanthum) and the role of ABA in mitigating UV-B stress. Chlorophyll fluorescence metrics indicated that both JA and ABA increased UV-B resistance; however, the effect of JA was not as strong as that of ABA. Metabolomic analysis using UPLC−MS/MS (ultra-performance liquid chromatography and tandem mass spectrometry) revealed significant fluctuations in metabolites under UV-B and ABA application. UV-B decreased amino acids and increased phenolics, suggesting antioxidant defense activation. ABA treatment upregulated lipids and phenolic acids, highlighting its protective role. Multivariate analysis showed distinct metabolic clusters and pathways responding to UV-B and ABA, which impacted amino acid metabolism and hormone signal transduction. Exogenous ABA negatively regulated the JA signaling pathway in UV-B-exposed R. chrysanthum, as shown by KEGG enrichment. This study deepens understanding of plant stress-tolerance mechanisms and has implications for enhancing plant stress tolerance through metabolic and hormonal interventions.
Comparative Physiological and Transcriptomic Analyses of Oat (Avena sativa) Seedlings under Salt Stress Reveal Salt Tolerance Mechanisms
Authors: Zhou Xiangrui , Wang Miaomiao , Yang Li , Wang Wenping , Zhang Yuehua , Liu Linbo , Chai Jikuan , Liu Huan , Zhao Guiqin
Published: August 2024

Soil salinity is a major abiotic stress limiting crop production globally. Oat (Avena sativa) is an annual cereal with a strong salt tolerance, a high yield, and nutritional quality, although the mechanisms underlying its salt stress response remain largely unknown. We examined the physiological and transcriptomic responses of A. sativa seedlings to salt stress in tolerant cultivar Qingyongjiu 195 and sensitive cultivar 709. Under salt stress, Qingyongjiu 195 maintained a higher photosynthetic efficiency, antioxidant enzymes activity, and leaf K+ accumulation but a lower Na+ uptake than 709. RNA-seq revealed 6616 differentially expressed genes (DEGs), including 4265 up- and 2351 downregulated. These were enriched in pathways like plant–pathogen interaction, phenylpropanoid biosynthesis, and MAPK signaling. We specifically highlight DEGs involved in photosynthesis (chlG, CP47 psbB, COX2, LHCB) and antioxidants (trxA, GroES). Qingyongjiu 195 also appeared to enhance K+ uptake via KAT1 and AKT2 and sequester Na+ in vacuoles via NHX2. Additionally, HKT restricted Na+ while promoting K+ transport to shoots, maintaining K+/Na+. The expression levels of CAX, ACA, CML, CaM, and CDPK in Qingyongjiu 195 were higher than those in 709. Oats regulated Ca2+ concentration through CAX and ACA after salt stress, decoded Ca2+ signals through CML, and then transferred Ca2+ signals to downstream receptors through the Ca2+ sensors CaM and CDPK, thereby activating K+/Na+ transporters, such as SOS1 and NHX, etc. Our results shed light on plant salt stress response mechanisms and provide transcriptomic resources for molecular breeding in improving salt tolerance in oats.
Unique Jurassic Ovaries Shed a New Light on the Nature of Carpels
Authors: Fu Qiang , Sun Jie , Zheng Shaolin , Wang Xin
Published: August 2024

Enclosed ovules are a reproductive feature restricted to angiosperms. Although this feature can be used as a criterion for identifying fossil angiosperms, how ovules are enclosed and the nature of the placenta are still foci of debates. A reason underlying these controversies is the lack of reproductive organ fossils shedding light on these issues. These controversies hinder a clear understanding of angiosperm evolution and systematics. Here, we report a new fossil ovary, Xenofructus dabuensis gen. et sp. nov, from the Middle Jurassic of Liaoning, China. Our fossil clearly demonstrates the existence of ovules in Xenofructus that has a free central placentation. This new feature implies that a placenta in angiosperm gynoecia is homologous to an ovule/seed-bearing axis, and free central placentation is one of the early developed placentations. This discovery is apparently at odds with the current understanding of placentation and its evolution. Apparently, the understanding of angiosperms and their gynoecia should be updated with newly available palaeobotanical data.
Enhancing Flame Retardancy and Smoke Suppression in EPDM Rubber Using Sepiolite-Based Systems
Authors: Zheng Jiawang , Zhang Xu , Liu Dawei , Zhang Liwei , Guo Yuxia , Liu Wei , Zhao Shuai , Li Lin
Published: August 2024

The burning of Ethylene–Propylene–Diene Monomer (EPDM) rubber generates substantial smoke, posing a severe threat to the environment and personal safety. Considering the growing emphasis on safety and environmental protection, conventional non-smoke-suppressing flame retardants no longer satisfy the present application requirements. Consequently, there is an urgent need to develop a novel flame retardant capable of suppressing smoke formation while providing flame retardancy. Sepiolite (SEP), a porous silicate clay mineral abundant in silica and magnesium, exhibits notable advantages in the realm of flame retardancy and smoke suppression. This research focuses on the synthesis of two highly efficient flame-retardant smoke suppression systems, namely AEGS and PEGS, using Enteromorpha (EN), graphene (GE), sepiolite (SEP), ammonium polyphosphate (APP), and/or piperazine pyrophosphate (PPAP). The studied flame-retardant systems were then applied to EPDM rubber and the flame-retardant and smoke suppression abilities of EPDM/AEGS and EPDM/PEGS composites were compared. The findings indicate that the porous structure of sepiolite plays a significant role in reducing smoke emissions for EPDM composites during combustion.
Hydrothermal Carbonization of Residual Biomass from Agricultural and Agro-Industrial Sector
Authors: De Francesco Carmine , Gasperini Thomas , Duca Daniele , Toscano Giuseppe , Ilari Alessio
Published: August 2024

Hydrothermal carbonization (HTC) is a promising method for the conversion of agricultural and agro-industrial residues into valuable products. HTC processes biomass through chemical reactions that produce hydrochar, a carbon-rich solid similar to lignite. Unlike other thermochemical processes, HTC can handle high-moisture biomass without pre-drying. This article evaluates the efficiency of HTC on wood chips, wheat straw, and grape pomace, examining their chemical and structural characteristics and critical operational parameters such as the temperature, pressure, biomass/water ratio, and reaction time. The obtained results highlight that the two key process parameters are the temperature and the ratio between the solid biomass and liquid phase. Increasing the first parameter increases the energy content by 20% and increases the carbon concentration by up to 50%, while reducing the oxygen content by 30% in the hydrochar. Varying the second parameter leads to the alternating reduction of the ash content but simultaneously reduces the energy content. The reaction time seems to have a limited influence on the quality parameters of the biochar produced. Lastly, HTC appears to successfully enhance the overall quality of widely available agricultural wastes, such as grape pomace.
Effect of Far-Infrared Drying on Broccoli Rhizomes: Drying Kinetics and Quality Evaluation
Authors: Zhang Gen , Yu Yun , Yao Chunyu , Zhou Lang , Zhu Guangyao , Lai Yushu , Niu Po
Published: August 2024

To clarify the effects of far-infrared drying technology on the drying kinetics and quality of broccoli rhizomes, broccoli rhizomes were dehydrated at 60, 65, 70, 75 and 80 °C, respectively. Eight thin-layer drying mathematical models were used to explore the drying kinetic characteristics and comprehensively evaluate their quality. The results showed that the higher the drying temperature, the shorter the time required to dry the broccoli rhizomes to the endpoint, and the higher the drying rate. The drying temperature was 80 °C, the shortest drying time was 360 min, and the average drying rate was 4.72 g·g−1·min−1. The longest drying time at 60 °C was 660 min, and the minimum average drying rate was 1.99 g·g−1·min−1. The effective diffusion coefficients of moisture at different drying temperatures were 1.22 × 10−6, 1.25 × 10−6, 1.34 × 10−6, 1.46 × 10−6 and 1.55 × 10−6 m2/min, respectively. The activation energy was calculated to be 12.26 kJ/mol by the linear relationship between the effective moisture diffusion coefficient and time. From the thermodynamic parameters, the drying of broccoli rhizomes is a non-spontaneous process, and it is necessary to absorb heat from the medium to achieve dehydration. With an increase in the drying temperature, the drying effect is better. The fitting results of eight mathematical models showed that Modified Page, Page, and Wang and Singh were the best mathematical models for the far-infrared drying kinetics of the broccoli rhizomes. The membership function method comprehensively evaluated the quality of the broccoli rhizome dry products. The comprehensive order was 60 °C > 65 °C > 75 °C > 70 °C > 80 °C. When the temperature was 60 °C, the physicochemical properties and nutritional quality of broccoli rhizome were well preserved, and the quality was the best. Therefore, 60 °C is the best temperature for broccoli rhizome drying. The results provide a theoretical reference for further improving the far-infrared drying quality of broccoli rhizomes.
Numerical Study on the Heat Dissipation Performance of Diamond Microchannels under High Heat Flux Density
Authors: Zhao Jiwen , Zhao Kunlong , Hao Xiaobin , Li Yicun , Zhang Sen , Liu Benjian , Dai Bing , Cao Wenxin , Zhu Jiaqi
Published: August 2024

Heat dissipation significantly limits semiconductor component performance improvement. Thermal management devices are pivotal for electronic chip heat dissipation, with the enhanced thermal conductivity of materials being crucial for their effectiveness. This study focuses on single-crystal diamond, renowned for its exceptional natural thermal conductivity, investigating diamond microchannels using finite element simulations. Initially, a validated mathematical model for microchannel flow heat transfer was established. Subsequently, the heat dissipation performance of typical microchannel materials was analyzed, highlighting the diamond’s impact. This study also explores diamond microchannel topologies under high-power conditions, revealing unmatched advantages in ultra-high heat flux density dissipation. At 800 W/cm2 and inlet flow rates of 0.4–1 m/s, diamond microchannels exhibit lower maximum temperatures compared to pure copper microchannels by 7.0, 7.2, 7.4, and 7.5 °C, respectively. Rectangular cross-section microchannels demonstrate superior heat dissipation, considering diamond processing costs. The exploration of angular structures with varying parameters shows significant temperature reductions with increasing complexity, such as a 2.4 °C drop at i = 4. The analysis of shape parameter ki indicates optimal heat dissipation performance at ki = 1.1. This research offers crucial insights for developing and optimizing diamond microchannel devices under ultra-high-heat-flux-density conditions, guiding future advancements in thermal management technology.
Mathematical Model of the Migration of the CO2-Multicomponent Gases in the Inorganic Nanopores of Shale
Authors: Dou Xiangji , Li Hong , Hong Sujin , Peng Mingguo , He Yanfeng , Qian Kun , Guo Luyao , Ma Borui
Published: August 2024

Nanopores in shale reservoirs refer to extremely small pores within the shale rock, categorised into inorganic and organic nanopores. Due to the differences in the hydrophilicity of the pore walls, the gas migration mechanisms vary significantly between inorganic and organic nanopores. By considering the impact of irreducible water and the variations in effective migration pathways caused by pore pressure and by superimposing the weights of different migration mechanisms, a mathematical model for the migration of CO2-multicomponent gases in inorganic nanopores of shale reservoirs has been established. The aim is to accurately clarify the migration laws of multi-component gases in shale inorganic nanopores. Additionally, this paper analyses the contributions of different migration mechanisms and studies the effects of various factors, such as pore pressure, pore size, component ratios, stress deformation, and water film thickness, on the apparent permeability of the multi-component gases in shale inorganic nanopores. The research results show that at high pressure and large pore size (pore pressure greater than 10 MPa, pore size greater than 4 nm), slippage flow dominates, while at low pressure and small pore size (pore pressure less than 10 MPa, pore size less than 4 nm), Knudsen diffusion dominates. With the increase of the stress deformation coefficient, the apparent permeability of gas gradually decreases. When the stress deformation coefficient is less than 0.05 MPa−1, the component ratio significantly impacts bulk apparent permeability. However, when the coefficient exceeds 0.05 MPa−1, this influence becomes negligible. The research results provide a theoretical basis and technical support for accurately predicting shale gas productivity, enhancing shale gas recovery, and improving CO2 storage efficiency.
The Recent Advancement of Graphene-Based Cathode Material for Rechargeable Zinc–Air Batteries
Authors: Belete Abrham Sendek , Worku Ababay Ketema , Ayele Delele Worku , Assegie Addisu Alemayehu , Teshager Minbale Admas
Published: August 2024

Graphene-based materials (GBMs) are a prospective material of choice for rechargeable battery electrodes because of their unique set of qualities, which include tunable interlayer channels, high specific surface area, and strong electrical conductivity characteristics. The market for commercial rechargeable batteries is now dominated by lithium-ion batteries (LIBs). One of the primary factors impeding the development of new energy vehicles and large-scale energy storage applications is the safety of LIBs. Zinc-based rechargeable batteries have emerged as a viable substitute for rechargeable batteries due to their affordability, safety, and improved performance. This review article explores recent developments in the synthesis and advancement of GBMs for rechargeable zinc–air batteries (ZABs) and common graphene-based electrocatalyst types. An outlook on the difficulties and probable future paths of this extremely promising field of study is provided at the end.
Precious and Base Metal Minerals in Black Sands of the Egyptian Mediterranean Coast: Mineralogical and Geochemical Attributes
Authors: Abdel-Karim Abdel-Aal M. , Gad Ahmed
Published: August 2024

This paper investigates the mineralogical and geochemical characteristics, as well as the possible sources, of gold, silver, platinum group elements (PGE), copper, and lead found in the beach sands along Egypt’s Mediterranean coast. Using scanning electron microscopy and electron probe micro-analysis, this study determines the morphology and micro-chemistry of separated grains to assess their economic potential and how various minerals respond to different transport distances. The analysis reveals that gold grains are of high purity (94.11 to 98.55 wt.%; average 96 wt.% Au) and are alloyed with Ag (1.28–2.32 wt.%) and Cu (0.16–3.15 wt.%). Two types of gold grains were identified, indicating differences in transport distances. Variations in morphology, surface features, inclusion types, rims, and chemistry of the native metals, including gold grains, suggest differences in composition, weathering degree, transport distance, deposit types, and host rocks. The average Ag concentration in gold grains (1.86 wt.%) suggests a link to mesothermal or supergene deposits. Most silver, copper, and lead grains are spherical, with some variations in shape. Silver grains have 71.66–95.34 wt.% Ag (avg. 82.67 wt.%). Copper grains have 92.54–98.42 wt.% Cu (avg. 94.22 wt.%). Lead grains contain 74.22–84.45 wt.% Pb (avg. 79.26 wt.%). The identified platinum group minerals (PGM) belong to the Pt–Fe alloys and sperrylite, both of which are PPGE-bearing minerals. These metals likely originate from the weathering of upstream Nile tributaries surrounded by igneous and metamorphic rocks from Ethiopian and Central African regions, with a minor contribution from the Egyptian Eastern Desert Mountains.
Hybrid Sensor Fusion Mixed with Reinforcement Learning in Autonomous Dual-Arm Lifting Tasks Performed by Humanoid Robots
Authors: Hernandez-Vicen Juan , Łukawski Bartek , Martinez Santiago , Tsagarakis Nikos , Balaguer Carlos
Published: August 2024

Humanoid robots often struggle with tasks such as lifting objects due to the complexity involved in identifying contact points, applying the correct force, and tracking task progress. We propose an integrated solution that leverages the dual-arm capability of humanoids and utilizes sensor fusion from vision and force sensors. Our system employs a computer vision algorithm to detect and characterize object properties (shape, size, position, orientation) and differentiate between parallel and non-parallel bi-manipulation tasks. The controller then identifies optimal contact points for the end effectors, generating trajectories fed into a closed-loop controller using force feedback. For parallel bi-manipulation, momentum cancellation is achieved through sensor fusion. For non-parallel surfaces, a reinforcement learning algorithm determines the appropriate lifting force to prevent slippage using only two contact points. Experimental validation on a real humanoid platform demonstrates the effectiveness of our approach in autonomously lifting objects, regardless of contact surface configuration. This advancement significantly enhances the reliability and versatility of humanoid robots in performing complex manipulation tasks, contributing to their practical deployment in human-oriented environments.
Dextractor:Deformation Extractor Framework for Monitoring-Based Ground Radar
Authors: Helmy Islam , Campbell Lachie , Ahmadi Reza , Awrangjeb Mohammad , Paliwal Kuldip
Published: August 2024

The radio frequency (RF) data generated from a single-chip millimeter-wave (mmWave) ground-based multi-input multi-output (GB-MIMO) radar can provide a highly robust, precise measurement for deformation in harsh environments, overcoming challenges such as different lighting and weather conditions. Monitoring deformation is significant for safety factors in different applications, such as detecting and monitoring the ground stability of underground mines. However, radar images can experience different types of clutter and artifacts besides the spreading effects caused by the side lobes, resulting in the foremost challenge of suppressing clutter and monitoring deformation.In the state of the art, the introduced frameworks usually include many filters proposed for different types of noise, with commercial systems typically using an amplitude threshold. This paper proposes a framework for monitoring the deformation, where the essential process is to apply a data-driven threshold to the amplitude heatmap, detect the deformation, and eliminate noise. The proposed threshold is an iterative approach based on radar imagery statistics, and it performs well for the collected dataset. The principal advantage of our proposed framework is simplicity, reducing the burden of using different filters. We can consider the dynamic threshold based on data statistics as a data-driven machine learning tool. The results show promising performance for our method in monitoring the deformation and removing clutter compared to the benchmark method.
Exploring the Green Tide Transport Mechanisms and Evaluating Leeway Coefficient Estimation via Moderate-Resolution Geostationary Images
Authors: Ji Menghao , Dou Xin , Zhao Chengyi , Zhu Jianting
Published: August 2024

The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity.
The 2024 Mw 7.1 Wushi Earthquake: A Thrust and Strike-Slip Event Unveiling the Seismic Mechanisms of the South Tian Shan’s Thick-Skin Tectonics
Authors: Qiu Jiangtao , Sun Jianbao , Ji Lingyun
Published: August 2024

The southern margin of the South Tian Shan has drawn attention due to the intense compressional deformation and seismic activity associated with its thrust structures. However, the deformation and seismic activity in the thick-skinned thrust sheets of the root zones are minimal. The Mw 7.1 Wushi earthquake on 23 January 2024 serves as a window to reveal these unknown aspects of the seismic mechanisms in this structural setting. Using the Leveraging Interferometric Synthetic Aperture Radar (InSAR) technique, we unlock critical insights into the coseismic deformation fields. The seismogenic fault is an unmapped segment within the Maidan Fault system, exhibiting a strike ranging from 241° to 222°. It is characterized by a shallow dip angle of 62° and a deeper dip angle of 56°. Remarkably, the seismic rupture did not propagate to the Earth’s surface. The majority of slip distribution is concentrated within a range of 4 to 26 km along the strike, indicating that this earthquake was a thrust event on a blind fault within the thick-skinned tectonics of the South Tian Shan. Coulomb stress changes indicate that aftershocks primarily occur in the stress-loading region. Interestingly, some aftershocks are very shallow, causing clear surface deformation. Inversion results show that the fault planes of two aftershocks are located above the main shock fault plane at extremely shallow depths (<6 km). Combining geophysical profile data, we infer that ruptures in the deep-seated thick-skinned structures during the main shock triggered ruptures in the shallow thrust structures. This triggering relationship highlights the potential for combined ruptures of the main shocks and aftershocks in the deep-seated thick-skinned structures beneath the South Tian Shan to result in larger disasters than typical seismic events.
Efficient Path Planning Algorithm Based on Laser SLAM and an Optimized Visibility Graph for Robots
Authors: Hu Yunjie , Xie Fei , Yang Jiquan , Zhao Jing , Mao Qi , Zhao Fei , Liu Xixiang
Published: August 2024

Mobile robots’ efficient path planning has long been a challenging task due to the complexity and dynamism of environments. If an occupancy grid map is used in path planning, the number of grids is determined by grid resolution and the size of the actual environment. Excessively high resolution increases the number of traversed grid nodes and thus prolongs path planning time. To address this challenge, this paper proposes an efficient path planning algorithm based on laser SLAM and an optimized visibility graph for mobile robots, which achieves faster computation of the shortest path using the optimized visibility graph. Firstly, the laser SLAM algorithm is used to acquire the undistorted LiDAR point cloud data, which are converted into a visibility graph. Secondly, a bidirectional A* path search algorithm is combined with the Minimal Construct algorithm, enabling the robot to only compute heuristic paths to the target node during path planning in order to reduce search time. Thirdly, a filtering method based on edge length and the number of vertices of obstacles is proposed to reduce redundant vertices and edges in the visibility graph. Additionally, the bidirectional A* search method is implemented for pathfinding in the efficient path planning algorithm proposed in this paper to reduce unnecessary space searches. Finally, simulation and field tests are conducted to validate the algorithm and compare its performance with classic algorithms. The test results indicate that the method proposed in this paper exhibits superior performance in terms of path search time, navigation time, and distance compared to D* Lite, FAR, and FPS algorithms.
Inversion Uncertainty of OH Airglow Rotational Temperature Based on Fine Spectral Measurement
Authors: Jiang Baichuan , Gao Haiyang , Niu Shuqi , Ren Ke , Sun Shaoyang
Published: August 2024

The inversion of temperature by detecting the ratio of the intensity of airglow vibrational and rotational spectral lines is a traditional method for obtaining mesopause temperature. However, previous studies have shown that there is significant uncertainty in the temperature inversion using this technology. A spectrograph instrument called the Mesosphere Airglow Fine Spectrometer (MAFS) was previously developed by our research team. Based on the MAFS, this work systematically evaluated the impact of the spectral line extraction methods and residual background noise elimination methods on temperature inversion results of the OH (6-2) Q-branch as the target. The fitting of residual background noise using different numbers of sampling points can cause the inverted temperature to vary by 5 K to 10 K without changing the overall trend. The temperature inversion results obtained using the three-region single-fit method were generally 3 K to 5 K higher than those obtained using the two-region double-fit method. Moreover, the temperature obtained using the Gaussian fitting area varied by approximately 15 K, with changes in the residual background noise fitting method; however, when using a spectrum peak instead of the Gaussian fitting area, this variation decreased to approximately 10 K. When the temperature is higher, both the residual background noise fitting and the spectral line intensity extraction methods have a more significant impact on the uncertainty of temperature inversion.
Pyramid Cascaded Convolutional Neural Network with Graph Convolution for Hyperspectral Image Classification
Authors: Pan Haizhu , Yan Hui , Ge Haimiao , Wang Liguo , Shi Cuiping
Published: August 2024

Convolutional neural networks (CNNs) and graph convolutional networks (GCNs) have made considerable advances in hyperspectral image (HSI) classification. However, most CNN-based methods learn features at a single-scale in HSI data, which may be insufficient for multi-scale feature extraction in complex data scenes. To learn the relations among samples in non-grid data, GCNs are employed and combined with CNNs to process HSIs. Nevertheless, most methods based on CNN-GCN may overlook the integration of pixel-wise spectral signatures. In this paper, we propose a pyramid cascaded convolutional neural network with graph convolution (PCCGC) for hyperspectral image classification. It mainly comprises CNN-based and GCN-based subnetworks. Specifically, in the CNN-based subnetwork, a pyramid residual cascaded module and a pyramid convolution cascaded module are employed to extract multiscale spectral and spatial features separately, which can enhance the robustness of the proposed model. Furthermore, an adaptive feature-weighted fusion strategy is utilized to adaptively fuse multiscale spectral and spatial features. In the GCN-based subnetwork, a band selection network (BSNet) is used to learn the spectral signatures in the HSI using nonlinear inter-band dependencies. Then, the spectral-enhanced GCN module is utilized to extract and enhance the important features in the spectral matrix. Subsequently, a mutual-cooperative attention mechanism is constructed to align the spectral signatures between BSNet-based matrix with the spectral-enhanced GCN-based matrix for spectral signature integration. Abundant experiments performed on four widely used real HSI datasets show that our model achieves higher classification accuracy than the fourteen other comparative methods, which shows the superior classification performance of PCCGC over the state-of-the-art methods.
An Effective and Lightweight Full-Scale Target Detection Network for UAV Images Based on Deformable Convolutions and Multi-Scale Contextual Feature Optimization
Authors: Yu Wanwan , Zhang Junping , Liu Dongyang , Xi Yunqiao , Wu Yinhu
Published: August 2024

Currently, target detection on unmanned aerial vehicle (UAV) images is a research hotspot. Due to the significant scale variability of targets and the interference of complex backgrounds, current target detection models face challenges when applied to UAV images. To address these issues, we designed an effective and lightweight full-scale target detection network, FSTD-Net. The design of FSTD-Net is based on three principal aspects. Firstly, to optimize the extracted target features at different scales while minimizing background noise and sparse feature representations, a multi-scale contextual information extraction module (MSCIEM) is developed. The multi-scale information extraction module (MSIEM) in MSCIEM can better capture multi-scale features, and the contextual information extraction module (CIEM) in MSCIEM is designed to capture long-range contextual information. Secondly, to better adapt to various target shapes at different scales in UAV images, we propose the feature extraction module fitting different shapes (FEMFDS), based on deformable convolutions. Finally, considering low-level features contain rich details, a low-level feature enhancement branch (LLFEB) is designed. The experiments demonstrate that, compared to the second-best model, the proposed FSTD-Net achieves improvements of 3.8%, 2.4%, and 2.0% in AP50, AP, and AP75 on the VisDrone2019, respectively. Additionally, FSTD-Net achieves enhancements of 3.4%, 1.7%, and 1% on the UAVDT dataset. Our proposed FSTD-Net has better detection performance compared to state-of-the-art detection models. The experimental results indicate the effectiveness of the FSTD-Net for target detection in UAV images.
Cascaded-Filter-Based Reverberation Suppression Method of Short-Pulse Continuous Wave for Active Sonar
Authors: Cui Yonglin , Liao Shuhan , Gao Juncheng , Zhu Haidong , Zhao Nengtong , Luo An
Published: August 2024

Reverberation is the main background interference in active sonar and seriously interferes with the extraction of the target echo. Active sonar systems can use short-pulse continuous wave (CW) signals to reduce the reverberation intensity. However, as the pulse width of the CW signals decreases, the reverberation envelope exhibits a high-frequency oscillating phenomenon. Active sonar often uses the cell average constant false alarm ratio (CA-CFAR) method to process the reverberation, which steadily decays with transmission distance. However, the high-frequency oscillation of the reverberation envelope deteriorates the performance of CA-CFAR, which causes a higher false alarm rate. To tackle this problem, the formation mechanism of the high-frequency oscillation characteristics of the reverberation envelope of the short-pulse-width CW signals is modeled and analyzed, and on this basis, an α filter is designed to suppress the high-frequency oscillation of the reverberation envelope before applying CA-CFAR. The simulation and lake trial results indicate that this method can effectively suppress high-frequency oscillations of the reverberation envelope, as well as exhibit robustness and resistance to reverberation interference.
Perturbation Transmit Beamformer Based Fast Constant Modulus MIMO Radar Waveform Design
Authors: Zheng Hao , Wu Hao , Zhang Yinghui , Yan Junkun , Xu Jian , Sun Yantao
Published: August 2024

In this paper, a fast method to generate a constant-modulus (CM) waveform for a multiple-input, multiple-output, (MIMO) radar is proposed. To simplify the optimization process, the design of the transmit waveform is decoupled from the design of transmit beamformers (TBs) and subpulses. To further improve the computational efficiency, the TBs’ optimization is conducted in parallel, and a linear programming model is proposed to match the desired beampattern. Additionally, we incorporate the perturbation vectors into the TBs’ optimization so that the TBs can be adjusted to satisfy the CM constraint. To quickly generate the CM subpulses with the desired range-compression (RC) performance, the classical linear frequency modulation (LFM) signal and non-LFM (NLFM) are adopted as subpulses. Meanwhile, to guarantee the RC performance of the final angular waveform, the selection of LFM signal parameters is analyzed to achieve a low cross-correlation between subpulses. Numerical simulations verify the transmit beampattern performance, RC performance, and computational efficiency of the proposed method.