Search Results (27,136)

Climate change poses growing threats to Amazonian biodiversity, yet species-specific responses remain poorly understood, particularly in the Colombian Amazon. This study assessed the potential distribution and habitat suitability of eight woody plant species—Euterpe precatoria (Mart.) A.J.Hend., Mauritia flexuosa L.f., Oenocarpus bataua Mart., Minquartia guianensis Aubl., Cedrela odorata L., Virola elongata (Benth.) Warb., Theobroma grandiflorum (Willd. ex Spreng.) Schum. and Thebroma cacao L.—under a baseline period (1970–2000) and future climate projections for mid- (2041–2060) and late-century (2061–2080) periods, using two Shared Socioeconomic Pathways (SSP245 and SSP585). Species distribution models (SDMs) integrated bioclimatic, edaphic, and topographic predictors and were spatially intersected with Special Management Areas. Results revealed contrasting responses among species. M. flexuosa, E. precatoria, O. bataua, V. elongata, M. guianensis and T. cacao retained over 95% of their baseline suitable habitat and even expanded into new regions, reflecting broad climatic resilience under both future scenarios. In contrast, C. odorata experienced moderate contractions, losing 8.7% of their current ranges under SSP585 by 2080. The most vulnerable species was T. grandiflorum, projected to lose up to 27% of its current suitable habitat under the most pessimistic scenario. Overall, losses were mainly concentrated in the natural fractions of Indigenous Reserves and National Natural Parks. These findings underscore the heterogeneous responses of Amazonian species to climate change and highlight the need for adaptive conservation and management strategies. Protecting climate refugia, promoting ecological connectivity, and incorporating climate-resilient species into restoration programs will be critical to maintaining biodiversity, ecosystem services, and local livelihoods in the Colombian Amazon under future climates. Full article

Global navigation satellite system (GNSS) differential code bias (DCB) and topside ionosphere vertical electron content (VEC) can be estimated using onboard data from low-earth-orbit (LEO) satellites. These satellites provide the potential to make up for the lack of ground-based stations in the oceanic and polar regions and establish a high-precision global ionosphere model. In order to study the influences of different LEO-topside VEC processing methods on estimates, we creatively analyzed and compared the results and accuracy of the DCBs and LEO-topside VEC estimates using two topside VEC solutions—the SH-topside VEC (spherical harmonic-topside vertical electron content) and EP-topside VEC (epoch parameter-topside vertical electron content) methods. Some conclusions are drawn as follows. (1) Using GRACE-A data (400 km in 2016), the monthly stabilities (STDs) of GPS satellite DCBs and LEO receiver DCBs using the EP-topside VEC method are better than those using the SH-topside VEC method. For JASON-2 data (1350 km), the STD results of GPS DCBs using the SH-topside VEC method are slightly superior to those using the EP-topside VEC method, and LEO DCBs using the two methods have similar STD results. However, the root mean square (RMS) results for GPS DCBs using the SH-topside VEC model relative to the Center for Orbit Determination in Europe (CODE) products are slightly superior to those using the EP-topside VEC method. (2) The peak ranges of the actual GRACE-A-topside VEC results using the SH-topside VEC and EP-topside VEC methods are within 42 and 35 TECU, respectively, while the peak ranges of the JASON-2-topside VEC results are both within 6 TECU. Additionally, only the SH-topside VEC model results are displayed due to the EP-topside VEC method not modeling VEC. Due to the difference in orbital altitude, the results and distributions of the GRACE-topside VECs differ from those of the JASON-topside VECs, with the former being more consistent with the ground-based results, indicating that there may be different height structures in the LEO-topside VECs. In addition, we applied the IRI-GIM (International Reference Ionosphere model–Global Ionosphere Map) method to compare the LEO-based topside VEC results, which indicate that the accuracy of GRACE-A-topside VEC using the EP-topside VEC method is better than that using the SH-topside VEC method, whereas for JASON-2, the two methods have similar accuracy. Meanwhile, we note that the temporal and spatial resolutions of the SH-topside VEC method are higher than those of the EP-topside VEC method, and the former has a wide range of usability and predictive characteristics. The latter seems to correspond to the single-epoch VEC mean of the former to some extent. Full article

Worldwide, the genus Echium L. (Boraginaceae) is represented by over 60 species of herbaceous plants and shrubs. The species are widely distributed all around the Mediterranean basin, Europe, and the Macaronesian Islands and are known for their analgesic, diuretic, antioxidant, antimicrobial, and antitumor properties. In traditional medicine, they are widely used as a wound-healing and anti-inflammatory agent, for respiratory problems and problems related to mental health, and for general abrasions and fissures of the hands. Four species are naturally distributed in Bulgaria—E. russicum J.F. Gmel., E. vulgare L., E. italicum L., E. plantagineum L., the first three being medicinal. The review aims to summarize the literature describing the content of biologically active substances and the therapeutic effects of Echium spp., with an emphasis on medicinal species distributed in Bulgaria. The content of biologically active substances was monitored, in particular, terpenes, phenolic compounds, flavonoids, naphthoquinones, omega-3 and omega-6 fatty acids, and pyrrolizidine alkaloids. The relationship between bioactive compounds, biological activities, and medicinal uses was researched. After the analysis made in the present review, it can be summarized: Despite extensive research, knowledge of their pharmacological potential is still incomplete. An attempt has therefore been made to outline directions for future research. Full article

Multiparty quantum private comparison (MQPC) aims to determine the equality relationship of inputs from multiple participants while maintaining the confidentiality of these inputs. Current MQPC protocols primarily focus on utilizing d-level quantum states, which limits feasible implementation. To address this issue, we introduce an MQPC protocol that utilizes n-particle Greenberger–Horne–Zeilinger (GHZ) state to enable private comparison while preserving the secrecy of individual inputs. A semi-honest third party (TP), adhering to protocol specifications but potentially curious about private data, generates and distributes GHZ state qubits to all participants. Each party encodes their secret input through rotation operations on their allocated qubits and returns the modified state to the TP, which then performs single-particle quantum measurements to derive the outcomes without accessing the raw inputs. The protocol’s sequence distribution method yields a high qubit efficiency of 1/n, outperforming many existing MQPC protocols. Security analysis confirms resilience against external adversaries employing quantum attack strategies and collusion attempts among participants. Simulations using IBM Qiskit validate the feasibility of the protocol, which relies on GHZ state preparation, single-qubit operations, and single-particle quantum measurements. Full article

Monofractal analysis offers a promising framework for characterizing cardiac dynamics, particularly in the early detection of heart failure. However, most existing approaches rely on long-duration physiological signals and do not explore the classification of disease severity. In this study, we propose a hybrid CNN-ELM model trained exclusively on synthetic monofractal time series of short length (128 to 512 samples), aiming to assess its ability to distinguish between healthy individuals and varying degrees of heart failure defined by the NYHA functional classification. Our results show that Hurst exponent distributions reflect the progressive loss of complexity in cardiac rhythms as heart failure severity increases. The model successfully classified both binary (healthy vs. sick) and multiclass (NYHA I–IV) scenarios by grouping Hurst exponent values ($H_{0.1}$ to $H_{0.9}$) into clinical categories, achieving peak accuracy ranges of 97.3–98.9% for binary classification and 96.2–98.8% for multiclass classification across signal lengths of 128, 256, and 512 samples. Importantly, the CNN-ELM architecture demonstrated fast training times and robust generalization, outperforming previous approaches based solely on support vector machines. These findings highlight the clinical potential of monofractal indices as non-invasive biomarkers of cardiovascular health and support the use of short synthetic signals for scalable, low-cost screening applications. Future work will extend this framework to multifractal and real-world clinical data and explore its integration into intelligent diagnostic systems. Full article

The traditional DC distribution grid is evolving into a meshed structure to create additional energy exchange paths and integrate the rapidly growing renewable energy sources. However, existing converter stations lack sufficient power flow controllability, necessitating the development of multiport power electronic transformers to address potential power flow congestion and high loss issues. This paper proposes a compact multi-terminal modular-multilevel-converter-based power electronic transformer (M³C-PET). This device enables flexible power flow regulation of the connected feeders through adopting two small-capacity power flow control modules (PFCMs). The simple structure and reduced switching count make the proposed PET more competitive and prominent and more cost-effective. Furthermore, this paper elaborates on the operational principle of the proposed device and presents a multilayer power balancing control strategy along with a power flow control scheme. These control strategies are designed based on the internal and external energy distribution mechanism of the proposed PET. The feasibility and effectiveness of the proposed topology and control schemes are rigorously validated through both a MATLAB/Simulink simulation model and a scaled-down experimental prototype. Full article

Recent years have seen a considerable increase in clean, green electricity output from wind energy (WE). It is crucial to obtain the optimum parameters of the two-parameter Weibull distribution (TPWD) for wind speed (WS) to calculate the potential WE. This paper proposes to use the superEGO (SEGO) along with maximum likelihood estimation (MLE) to obtain optimum parameters of the TWPD for WS data. The results showed that SEGO provided better results compared other optimization algorithms used in this context. Moreover, the potential WE for Gdańsk, a city located by the Baltic Sea in northern Poland, was calculated using parameters obtained by using SEGO. It was observed that SEGO performs the best among other optimization algorithms to find optimum parameters for the two-parameter Weibull distribution along with MLE for wind speed. Full article

Alexandrium spp., globally recognized as harmful algal bloom (HAB) species, pose severe threats to marine ecosystems, fisheries, and public health. Based on 469 occurrence records and 24 marine environmental variables, this study employed the Biomod2 ensemble modeling framework to predict the potential distribution of Alexandrium spp. under current and future climate scenarios, and to assess the role of key environmental factors and the spatiotemporal dynamics of habitat centroid shifts. The results revealed that (1) the ensemble model outperformed single models (AUC = 0.998, TSS = 0.977, Kappa = 0.978), providing higher robustness and reliability in prediction; (2) salinity range (bio18, 19.1%) and mean salinity (bio16, 5.8%) were the dominant factors, while minimum temperature (bio23) also showed strong constraints, indicating that salinity determines “whether persistence is possible,” while temperature influences “whether blooms occur”; (3) under present conditions, high-suitability habitats are concentrated in Bohai Bay, the Yangtze River estuary to the Fujian coast, and parts of Guangdong; (4) climate change is predicted to drive a southward shift of suitable habitats, with the most pronounced expansion under the high-emission scenario (RCP8.5), leading to the emergence of new high-risk areas in the South China coast and adjacent South China Sea; (5) centroid analysis further indicated a pronounced southward migration under RCP8.5 by 2100, highlighting a regional reconfiguration of ecological risks. Collectively, salinity and temperature are identified as the core drivers shaping the ecological niche of Alexandrium spp., and future warming is likely to exacerbate HAB risks in southern China. This study delineates key prevention regions and proposes a shift from reactive to proactive management strategies, providing scientific support for HAB monitoring and marine ecological security in China’s coastal waters. Full article

The primary aim of this work is to present, in detail, the recent applications and progress of LIBS in the study of plant samples and related components, highlighting several innovative methods and experimental setups. The latest developments in using LIBS to analyze crop plant leaves, pasture vegetables, grains, seeds, fruits, plant derivatives, and other agricultural products are discussed, with particular emphasis on the analysis of minerals and trace elements in various plant matrices. Trace and metallic minerals are vital for regulating plant growth and development. Understanding how these elements are distributed within plant tissues provides deeper insights into metabolic pathways and processes, as well as potential applications in food technology and agriculture. Advances in quantitative measurements of these elements across different plant sections are examined, with attention given to challenges such as sample preparation, field sampling methods, and calibration techniques. Key features of LIBS, influential parameters, and fundamental instrumentation are also reviewed. Furthermore, this review explores the specific concerns, expectations, and possibilities of using LIBS to assess plant nutritional status and detect toxic elements, while highlighting the distinct advantages and complementary role of LIBS in plant science research. Full article

This study conducted a genome-wide identification and systematic evolutionary analysis of the banana WRKY gene family using bioinformatics, transcriptomics, and molecular biology approaches. A total of 153 WRKY genes were identified in the banana genome, with significant differences in the amino acid count, molecular weight, and other physicochemical properties of their encoded proteins. The subcellular localization of these proteins is primarily in the nucleus. These genes are unevenly distributed across 11 chromosomes, with the highest density on chromosome 7. WRKY gene family members exhibit diverse expression patterns during fruit development and ripening, and some can respond to multiple abiotic and biotic stresses. Systematic evolutionary analysis classified them into three major groups (I, II, and III), with Group II having the highest number of members, which are further divided into five subgroups. Conserved motif analysis revealed that Motif1, Motif2, and Motif4 are key structural elements in the family’s evolution, with some members having a WRKYGKK variant. The gene structure shows a wide range of exon numbers (1–22), and the promoter regions are rich in cis-elements related to light response, hormone signaling, and stress response, indicating their potential for integrating light signals, hormone networks, and multiple stress responses. Collinearity analysis identified 116 segmental duplication events, with Ka/Ks values all less than 1, indicating purifying selection. After ethylene treatment, 51 genes showed significant changes in expression, which can be categorized into four patterns: sustained upregulation, sustained downregulation, initial upregulation followed by downregulation, and delayed upregulation. Among these, MaWRKY10, MaWRKY88, and MaWRKY137 exhibited significant expression changes and may play key roles in fruit ripening. These findings significantly contribute to the theoretical framework regarding the evolution and function of the WRKY family in plants. Moreover, they offer valuable gene resources and regulatory strategies that enhance postharvest banana preservation and molecular breeding efforts. Full article

Background/Objectives: Ultradeformable liposomes represent an established platform for topical delivery of antioxidant compounds, thanks to their structural flexibility and ability to enhance skin permeation, but standardized manufacturing protocols are still lacking. This study presents a microfluidic-based strategy for the scalable production of ultradeformable liposomes encapsulating Stellaria media extract, a polyphenol-rich phytocomplex with strong antioxidant activity. Methods: Liposomes were produced with a GMP-like microfluidic platform enabling fine control of formulation parameters and high reproducibility under conditions directly transferable to continuous manufacturing. Process optimization tested different total flow rates. Characterization included particle size and distribution, encapsulation efficiency, colloidal stability and kinetics of release. Permeation was assessed with Franz diffusion cells using human stratum corneum and epidermidis membranes. Results: Optimal conditions were a flow rate ratio of 3:1 and a total flow rate of 7 mL/min, yielding ultradeformable liposomes with a mean size of 89 ± 1 nm, a polydispersity index < 0.25, and high encapsulation efficiency (72%). The resulting formulation showed long-term colloidal stability and controlled release. Diffusion studies demonstrated a 2-fold increase in permeation rate compared to the free extract. Conclusions: These findings highlight the potential of microfluidics as a robust and scalable technology for the industrial production of ultradeformable liposomes designed to enhance the dermal delivery of bioactive phytocomplex for both pharmaceutical and cosmeceutical applications. Full article

This study presents a green and sustainable approach for synthesizing zinc oxide nanoparticles (ZnO-NPs) using Melia azedarach leaf extract as a reducing and stabilizing agent, with zinc acetate as the precursor. The synthesized nanoparticles were thoroughly characterized to assess their structural, morphological, and physicochemical properties, revealing nanoscale dimensions, enhanced crystallinity, and improved stability compared to commercial ZnO. Controlled release experiments under plant-relevant pH conditions demonstrated a gradual and sustained release of Zn²⁺ ions, accompanied by buffering effects and re-precipitation of Zn(OH)₂, highlighting their potential for long-term nutrient availability in soil systems. Unlike conventional studies that focus mainly on synthesis or characterization, this work emphasizes the functional performance of ZnO-NPs as nanofertilizers, combining eco-friendly production with practical agricultural applications. The plant-mediated synthesis yielded nanoparticles with uniform size distribution, enhanced dispersion, and stability, which are critical for efficient nutrient delivery and persistence in soil. Overall, this study provides a cost-effective, scalable, and environmentally benign strategy for producing ZnO nanoparticles and offers valuable insights into the development of sustainable nanofertilizers aimed at improving crop nutrition, soil fertility, and agricultural productivity. Full article

Transposable elements (TEs) are major components of plant genomes and play crucial roles in adaptive genome evolution and stress tolerance. Under abiotic stress, activated TEs can generate abundant genetic variation and regulate the expression of stress-responsive genes. As a pioneer species in desert and saline–alkali environments, Tamarix chinensis L. has been little studied with respect to the abundance and evolutionary relationships of its LTR retrotransposons, particularly their activation patterns under salt and alkali stresses. This study aimed to investigate the characteristics of the reverse transcriptase (RT) domain of LTR retrotransposons in T. chinensis and to determine their patterns of activation in response to salt and alkali stresses. A total of 629 Ty1-copia and 607 Ty3-gypsy RT nucleotide sequences, which displayed high AT/GC ratios and evidence of stop codon insertions, were identified in T. chinensis by amplicon sequencing. Among these, 211 Ty1-copia and 117 Ty3-gypsy RT sequences with potential transpositional activity each contained distinct domains, suggesting a high degree of conservation. Phylogenetic analysis revealed that the RT sequences of T. chinensis are closely related to those of mangrove, wild potato, and Ipomoea, and may have undergone horizontal transfer. Expression analysis showed that 634 and 181 RT sequences were activated under salt and alkali stresses, respectively, with the majority belonging to salt-induced Ty1-copia families. Compared with the control group, under salt and alkali stresses, the cTy1-copia elements (Ty1-copia with amplificated from cDNA of T. chinensis, the same below) with dominant abundance were mainly concentrated in the Angela subfamily, while the cTy3-gypsy elements induced by alkali stress were primarily distributed in the Tekay and Reina subfamilies. Furthermore, four cTy1-copia and five cTy3-gypsy were identified as candidate key LTR retrotransposons responsive to salt and alkali stresses. Overall, this study provides new insights into the epigenetic mechanisms underlying the adaptation of T. chinensis to saline and alkali stresses and offers a theoretical basis for its potential applications in saline–alkali land reclamation. Full article

The integration of artificial intelligence (AI) and edge computing gives rise to edge intelligence (EI), which offers effective solutions to the limitations of traditional cloud-based AI; however, deploying models across distributed edge platforms raises concerns regarding authenticity, thereby necessitating robust mechanisms for ownership verification. Currently, backdoor-based model watermarking techniques represent a state-of-the-art approach for ownership verification; however, their reliance on model poisoning introduces potential security risks and unintended behaviors. To solve this challenge, we propose BIMW, a blockchain-enabled innocuous model watermarking framework that ensures secure and trustworthy AI model deployment and sharing in distributed edge computing environments. Unlike widely applied backdoor-based watermarking methods, BIMW adopts a novel innocuous model watermarking method called interpretable watermarking (IW), which embeds ownership information without compromising model integrity or functionality. In addition, BIMW integrates a blockchain security fabric to ensure the integrity and auditability of watermarked data during storage and sharing. Extensive experiments were conducted on a Jetson Orin Nano board, which simulates edge computing environments. The numerical results show that our framework outperforms baselines in terms of predicate accuracy, p-value, watermark success rate (WSR), and harmlessness H. Our framework demonstrates resilience against watermarking removal attacks, and it introduces limited latency through the blockchain fabric. Full article

Echo separation has long been a challenging and prominent research focus for Multiple-Input Multiple-Output Synthetic Aperture Radar (MIMO SAR) systems. Digital beamforming (DBF) plays a critical role in achieving effective echo separation, but it often comes at the cost of high system complexity. This paper proposes a novel MIMO SAR scheme based on phase-coded waveforms applied to both inter-pulses and intra-pulses. By introducing phase coding in both dimensions and performing joint azimuth–elevation processing, the proposed method effectively suppresses interference arising during the echo separation process, thereby significantly improving separation performance. Additionally, the approach allows for a significantly simplified array configuration, reducing both hardware requirements and computational burden. The effectiveness and practicality of the proposed scheme are validated through numerical simulations and distributed scene experiments, highlighting its strong potential for application in MIMO SAR systems—particularly in cost-sensitive scenarios and systems with limited elevation channels. Full article