Search Results (73)

This paper proposes a novel Twin Delayed Deep Deterministic Policy Gradient (TDDPG)-based joint optimization algorithm for hybrid reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) systems in Internet of Vehicles (IoV) scenarios. The proposed system model achieves deep integration of sensing and communication by superimposing the communication and sensing signals within the same waveform. To decouple the complex joint design problem, a dual-DDPG architecture is introduced, in which one agent optimizes the transmit beamforming vector and the other adjusts the RIS phase shift matrix. Both agents share a unified reward function that comprehensively considers multi-user interference (MUI), total transmit power, RIS noise power, and sensing accuracy via the CRLB constraint. Simulation results demonstrate that the proposed TDDPG algorithm significantly outperforms conventional DDPG in terms of sum rate and interference suppression. Moreover, the adoption of a hybrid RIS enables an effective trade-off between communication performance and system energy efficiency, highlighting its practical deployment potential in dynamic IoV environments. Full article

The construction of marine ranching is a crucial component of China’s Blue Granary strategy, yet the fragmented knowledge system in marine ranching equipment impedes intelligent management and operational efficiency. This study proposes the first knowledge graph (KG) framework tailored for marine ranching equipment, integrating hybrid ontology design, joint entity–relation extraction, and graph-based knowledge storage: (1) The limitations in existing KG are obtained through targeted questionnaires for diverse users and employees; (2) A domain ontology was constructed through a combination of the top-down and the bottom-up approach, defining seven key concepts and eight semantic relationships; (3) Semi-structured data from enterprises and standards, combined with unstructured data from the literature were systematically collected, cleaned via Scrapy and regular expression, and standardized into JSON format, forming a domain-specific corpus of 1456 annotated sentences; (4) A novel BERT-BiGRU-CRF model was developed, leveraging contextual embeddings from BERT, parameter-efficient sequence modeling via BiGRU (Bidirectional Gated Recurrent Unit), and label dependency optimization using CRF (Conditional Random Field). The TE + SE + R_i + BMESO tagging strategy was introduced to address multi-relation extraction challenges by linking theme entities to secondary entities; (5) The Neo4j-based KG encapsulated 2153 nodes and 3872 edges, enabling scalable visualization and dynamic updates. Experimental results demonstrated superior performance over BiLSTM-CRF and BERT-BiLSTM-CRF, achieving 86.58% precision, 77.82% recall, and 81.97% F1 score. This study not only proposes the first structured KG framework for marine ranching equipment but also offers a transferable methodology for vertical domain knowledge extraction. Full article

Reconfigurable Intelligent Surfaces (RISs) are among the key technologies envisaged for sixth-generation (6G) multiple-input multiple-output (MIMO)–orthogonal frequency division multiplexing (OFDM) wireless systems. However, their passive nature and the frequent absence of a line-of-sight (LoS) path in dense urban environments make uplink channel estimation and localization challenging tasks. Therefore, to achieve channel estimation and localization, this study models the RIS-mobile station (MS) channel as a double-sparse angular structure and proposes a hybrid channel parameter estimation framework for RIS-assisted MIMO-OFDM systems. In the hybrid framework, Simultaneous Orthogonal Matching Pursuit (SOMP) first estimates coarse angular supports. The coarse estimates are refined by a novel refinement stage employing a Variational Bayesian Expectation Maximization (VBEM)-based Off-Grid Sparse Bayesian Learning (OG-SBL) algorithm, which jointly updates azimuth and elevation offsets via Newton-style iterations. An Angle of Arrival (AoA)–Angle of Departure (AoD) matching algorithm is introduced to associate angular components, followed by a 3D localization procedure based on non-LoS (NLoS) multipath geometry. Simulation results show that the proposed framework achieves high angular resolution; high localization accuracy, with 97% of the results within 0.01 m; and a channel estimation error of 0.0046% at 40 dB signal-to-noise ratio (SNR). Full article

The systematics and phylogeny of the most speciose genus (Leopardus) of the felidae have historically been contentious and problematic. These issues have been compounded with the recent advancement of genetic techniques that make it possible to detect events such as incomplete lineage sorting (ILS), punctual historical ancestral introgression (PHAI), and repetitive introgression or recent hybridization (RI-RH). Each of these events have noteworthily affected the Leopardus genus. One Leopardus taxon (Leopardus tigrinus, herein called tigrina) has been especially complex from a phylogenetic point of view. In the last decade, one new species has been reported (L. guttulus) and two other new species likely exist within the tigrinas (L. emiliae and L. pardinoides). However, the most surprising find was the discovery of a new and not previously reported tigrina, the Nariño cat, from the southern Andean region of Colombia (2023). Later that same year, a new paper criticized the discovery. In response to that criticism, herein, we provide new molecular genetics results of the Nariño cat as well as new insights into the molecular phylogeny of the tigrinas inside the Leopardus genus: (1) In this new work, we analyzed the mtND5 gene of Nariño cat samples collected over four years (2001, 2007, 2017, 2023) as well as analyzed mitogenomes of Nariño cat samples collected in three different years (2001, 2017, 2023). The temporal Nariño cat samples (2001, 2007, 2017, 2023) refer to samples taken from a single specimen across different years. Based on these analyses, data from 2001 and 2007 represent the most reliable information. In contrast, samples from 2017 and 2023 may be contaminated with DNA from the Pampas cat and tigrina, respectively. (2) On the other hand, based on sequencing the mtND5 gene of 164 specimens of Leopardus, northern Andean and Central American tigrinas (37 specimens) are divided into at least six different groups (without counting the Nariño cat). Based on our analysis of sequenced mitogenomes of 102 specimens (including 34 northern Andean and Central American tigrinas) of the Leopardus genus, there are at least eight different groups of tigrinas (without counting the Nariño cat). Henceforth, there are strong datasets which support the existence of multiple lineages within the presumed “a priori” northern Andean tigrina and thus much of the genetic diversity of this wild cat has gone unnoticed. There are a series of potential taxa that have gone unnoticed due to a lack of sampling of this polyphyletic Andean feline. Full article

Soil, rhizosphere, and plant-associated microorganisms can enhance plant growth and health. A genomic analysis of these microbes revealed the key characteristics contributing to their beneficial effects. Following a field survey in Panama, four bacterial isolates with plant growth-promoting traits (PGPT) in rice (Oryza sativa L.) were identified. In this study, we sequenced, assembled, and annotated the genomes of Lysinibacillus fusiformis C6 and 24, and Bacillus cereus D23 and 59. The C6 genome was 4,754,472 bp long with 10 contigs, 37.62% guanine-cytosine (GC) content, and 4657 coding sequences (CDS). The 24 genome was 4,683,219 bp with five contigs, 37.65% GC content, and 4550 CDS. The D23 genome was 6,199,908 bp long with 18 contigs, 34.84% GC content, and 6141 CDS. The 59 genome was 6,194,462 bp with 21 contigs, 34.87% GC content, and 6122 CDS. Digital DNA–DNA hybridization (dDDH) and average nucleotide identity (ANI) confirmed that C6 and 24 belong to Lysinibacillus fusiformis, whereas D23 and 59 belong to the Bacillus cereus species. Further results revealed that these bacteria contained genes characteristic of plant growth-promoting bacteria, such as siderophore, phytohormone auxin (IAA) production, and nitrogen-fixing abilities that promote plant growth. Moreover, the antiSMASH database identified gene clusters involved in secondary metabolite production (biosynthetic gene clusters), such as betalactone, NRPS-like, NRP-siderophore, terpene, and RiPP-like clusters. Moreover, diverse and novel biosynthetic clusters (BCGs) have included non-ribosomal peptides (NRPs), polyketides (PKs), bacteriocins, and ribosomally synthesized and post-transcriptionally modified peptides (RiPPs). This work offers new insights into the genomic basis of the studied strains’ plant growth-promoting capabilities. Full article

Alzheimer’s disease (AD) is the most common form of dementia, characterized by β-amyloid (Aβ) plaques and neurofibrillary tangles, leading to neuronal loss and cognitive impairments. Recent studies have reported the dysregulation of RNA splicing in AD pathogenesis. Our previous transcriptomic study demonstrated the neuroprotective effect of the phytocannabinoid cannabinerol (CBNR) against the cell viability loss induced by Aβ in differentiated SH-SY5Y cells. This study also highlighted the deregulation of genes involved in mRNA splicing after Aβ exposure or CBNR pre-treatment. Here, we investigated whether CBNR could restore the splicing defects induced by Aβ in an AD in vitro model. Using the rMATS computational tool for detecting differential alternative splicing events (DASEs) from RNA-Seq data, we obtained 96 DASEs regulated in both conditions and, remarkably, they were all restored by CBNR pre-treatment. The pathway analysis indicated an over-representation of the “Alzheimer’s disease–amyloid secretase pathway”. Additionally, we observed that Aβ exposure increased the frequency of retained introns (RIs) among the shared DASEs, and that this frequency returned to normality by CBNR pre-treatment. Interestingly, most of these RIs contain a premature in-frame stop codon within the RNA sequence. Finally, analyzing the DASE regions for miRNA hybridization, we found 33 potential DASE/miRNA interactions that were relevant in AD pathogenesis. These findings revealed a novel trans-gene regulation by CBNR, potentially explaining part of its neuroprotective role. This is the first study demonstrating the involvement of a cannabinoid in the regulation of mRNA splicing in an AD model. Full article

The Gram-negative genus Aeromonas contains diverse bacterial species that are prevalent in aquatic environments. This present study describes three novel Aeromonas strains: A. ichthyocola sp. nov. A-5^T and A. mytilicola subsp. aquatica subsp. nov. A-8^T isolated from rainbow trout (Oncorhynchus mykiss), and A. mytilicola sp. nov. A-7^T isolated from mussels (Mytilus galloprovincialis), respectively. Genomic analyses revealed that strains A-5^T and A-7^T shared the highest 16S rRNA gene sequence similarity with A. rivipollensis P2G1^T (99.7% and 99.8%, respectively), while strain A-8^T exhibited 99.7% identity with A. media RM^T. Together with morphological, physiological, and biochemical data, genome-based analyses provided additional evidence for species differentiation. Digital DNA–DNA hybridization (dDDH; 56.8−65.9%) and average nucleotide identity (ANI; 94.2–95.7%) values fell below the species delineation thresholds, confirming that these isolates represent distinct taxa. Pathogenicity assays using greater wax moth (Galleria mellonella) larvae demonstrated strain-specific virulence profiles. Further genomic analyses identified biosynthetic gene clusters for nonribosomal peptides (NRPs) and ribosomally synthesized and post-translationally modified peptides (RiPPs), which often have roles in secondary metabolite production. Ecological analyses, based on genomic comparisons and metagenomic database searches, revealed the adaptability of the strains to diverse habitats, including freshwater, wastewater, and activated sludge. Based on the genetic and phenotypic data, the novel taxa Aeromonas ichthyocola sp. nov. A-5ᵀ (LMG 33534ᵀ = DSM 117488ᵀ), Aeromonas mytilicola sp. nov. A-7ᵀ (LMG 33536ᵀ = DSM 117490ᵀ), and Aeromonas mytilicola subsp. aquatica subsp. nov. A-8ᵀ (LMG 33537ᵀ = DSM 117493ᵀ) are proposed. Full article

This paper proposes a novel reconfigurable intelligent surface (RIS)-assisted downlink hybrid free-space optics (FSO)/radio frequency (RF) space–air–ground integrated network (SAGIN) architecture, where the high altitude platform (HAP) converts the optical signal sent by the satellite into an electrical signal through optoelectronic conversion. The drone equipped with RIS dynamically adjusts the signal path to serve ground users, thereby addressing communication challenges caused by RF link blockages from clouds or buildings. To improve the security performance of SAGIN, this paper maximizes the sum secrecy rate (SSR) by optimizing the power allocation, RIS phase shift, and drone trajectory. Then, an alternating iterative framework is proposed for a joint solution using the simulated annealing algorithm, semi-definite programming, and the designed deep deterministic policy gradient (DDPG) algorithm. The simulation results show that the proposed scheme can significantly enhance security performance. Specifically, compared with the NOMA and SDMA schemes, the SSR of the proposed scheme is increased by 39.7% and 286.7%, respectively. Full article

Multi-access edge computing (MEC) has emerged as a cornerstone technology for deploying 6G network services, offering efficient computation and ultra-low-latency communication. The integration of unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) further enhances wireless propagation, capacity, and coverage, presenting a transformative paradigm for next-generation networks. This paper addresses the critical challenge of task offloading and resource allocation in an MEC-based system, where a massive MIMO base station, serving multiple macro-cells, hosts the MEC server with support from a UAV-equipped RIS. We propose an optimization framework to minimize task execution latency for user equipment (UE) by jointly optimizing task offloading and communication resource allocation within this UAV-assisted, RIS-aided network. By modeling this problem as a Markov decision process (MDP) with a discrete-continuous hybrid action space, we develop a deep reinforcement learning (DRL) algorithm leveraging a hybrid space representation to solve it effectively. Extensive simulations validate the superiority of the proposed method, demonstrating significant latency reductions compared to state-of-the-art approaches, thereby advancing the feasibility of MEC in 6G networks. Full article

Bark beetle-associated bacteria from the sub-boreal and boreal forests of northern Canada represent a largely unexplored source of bioactive natural products. This study aims to investigate the chemical potential of bacteria isolated from Dendroctonus ponderosae, Dendroctonus rufipennis, Dendroctonus pseudotsugae, and Ips perturbatus by focusing on nitrogen-containing secondary metabolites. Genomic analyses of the bacterial isolates identified diverse biosynthetic gene clusters (BGCs), including nonribosomal peptides (NRPs), NRPS-PKS hybrids, and ribosomally synthesized and post-translationally modified peptides (RiPPs), many of which exhibit low sequence homology, suggesting potential for novel bioactive compounds. Nitrogen-15 NMR spectroscopy was employed to detect nitrogen-containing functional groups in crude extracts, revealing distinct signals for amides, amines, and nitrogen heterocycles. The combination of BGC predictions and NMR data highlighted the genetic and chemical diversity of these bacteria and underscored the potential for discovering novel nitrogen-rich metabolites. These findings provide a foundation for further exploration of bioactive natural products with pharmaceutical and agrochemical applications and potential to contribute to the understanding of the chemical ecology of bark beetle–microbe interactions in northern ecosystems. Full article

The study of infected biological cells is crucial in modern biomedical research. This work presents a passive sensing approach using optical resonators, designed to detect malignant diseases within a refractive index (RI) range of 1 to 1.5. A comprehensive theoretical analysis is conducted, yielding an expected limit of detection (LoD) ranging from 0.03 nm/RIU to 0.92 nm/RIU. Furthermore, an in-depth investigation of DNA hybridization is performed, incorporating a 1.8 nm linker layer at the analyte boundary. The refractive indices of single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) are 1.456 and 1.529, respectively. The novelty of this work lies in the renaturation process of ssDNA to dsDNA, demonstrated through a labeled sensing modality with a measurable shift in the resonance wavelength spectrum. The proposed surface-functionalized resonators, designed using Silicon-on-Insulator (SOI) technology, include (a) a Rectangular Waveguide-based Ring Resonator (RWRiR), (b) a Rectangular Waveguide-based Racetrack Resonator (RWRaR), (c) a Slot Waveguide-based Ring Resonator (SWRiR), and (d) a Slot Waveguide-based Racetrack Resonator (SWRaR). Among these, the SWRiR exhibits the best performance for DNA sensing, achieving a quality factor (Q-factor) of 2216.714, a sensitivity (S) of 54.282 nm/RIU, and a normalized sensitivity (S’) of 0.0349. Full article

The evolution of reproductive isolation (RI) results in the reduction of interspecific hybridization and the maintenance of species boundaries. Asymmetries in RI, where one species more frequently serves as the maternal or paternal parent in initial F₁ hybrid formation, are commonly observed in plants. Asymmetric introgression, the predominantly unidirectional transfer of genetic material through hybridization and backcrossing, has also been frequently documented in hybridizing plant taxa as well. This study investigates whether asymmetries in total RI measured between species can predict the direction of introgression in naturally hybridizing plant taxa. A meta-analysis was conducted on 19 plant species pairs with published data on both asymmetric total RI, and asymmetric introgression. Species pairs that met these criteria were identified through a comprehensive literature review. A two-tailed binomial test was performed to evaluate whether asymmetric RI was associated with asymmetries in introgression. No significant relationship was found between asymmetries in total RI and the direction of introgression (p = 0.3593). Asymmetric RI largely does not predict the direction of introgression. Rather, introgression patterns may be better understood by examining F₁ and later-generation hybrids in natural settings, focusing on their fitness, mating behaviors, and the ecological and demographic factors that shape hybrid zones. Full article

Battery modelling is essential for optimizing the performance and reliability of Unmanned Aerial Vehicles (UAVs), particularly given the challenges posed by their dynamic power demands and limited onboard computational resources. This study evaluates two widely adopted Equivalent Circuit Models (ECMs), the fixed resistance model and the Thevenin model to determine their suitability for UAV applications. Using the Specific Hybrid Pulse Power Characterization (SHPPC) method, key parameters, including Open Circuit Voltage (OCV), internal resistance (Ri), polarization resistance (R1), and polarization capacitance (C1), were estimated across multiple states of charge (SOC). The models were analyzed under nine parameterization scenarios, ranging from fully average parameters to configurations where selected parameters were tied to SOC. Results indicate that the Thevenin model, with selective SOC-dependent parameters, demonstrated superior predictive accuracy, achieving error reductions of up to 4.26 times compared to the fixed resistance model. Additionally, findings reveal that modelling all parameters as SOC-dependent is unnecessary, as simpler configurations can balance accuracy and computational efficiency, particularly for UAVs with constrained BMS capabilities. Full article

The advent of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, coupled with reconfigurable intelligent surfaces (RISs), presents a significant opportunity for advancing wireless communication technologies. This integration enhances data transmission rates and broadens coverage areas, but challenges in channel estimation (CE) remain due to the limitations of the signal processing capabilities of RIS. To address this, we propose an adaptive channel estimation framework comprising two algorithms: log-sum normalized least mean squares (Log-Sum NLMS) and hybrid normalized least mean squares-normalized least mean fourth (Hybrid NLMS-NLMF). These algorithms leverage the sparse nature of mmWave channels to improve estimation accuracy. The Log-Sum NLMS algorithm incorporates a log-sum penalty in its cost function for faster convergence, while the Hybrid NLMS-NLMF employs a mixed error function for better performance across varying signal-to-noise ratio (SNR) conditions. Our analysis also reveals that both algorithms have lower computational complexity compared to existing methods. Extensive simulations validate our findings, with results illustrating the performance of the proposed algorithms under different parameters, demonstrating significant improvements in channel estimation accuracy and convergence speed over established methods, including NLMS, sparse exponential forgetting window least mean square (SEFWLMS), and sparse hybrid adaptive filtering algorithms (SHAFA). Full article

As the resistance of Plasmodium to the existing antimalarials increases, there is a crucial need to expand the antimalarial drug pipeline. We recently identified potent antimalarial compounds, namely harmiquins, hybrids derived from the β-carboline alkaloid harmine and 4-amino-7-chloroquinoline, a key structural motif of chloroquine (CQ). To further explore the structure−activity relationship, we synthesised 13 novel hybrid compounds at the position N-9 of the β-carboline ring and evaluated their efficacy in vitro against Plasmodium falciparum 3D7 and Dd2 strains (CQ sensitive and multi-drug resistant, respectively). All compounds exhibit persistent antimalarial activity against both strains of P. falciparum. The most interesting derivatives had low nanomolar activity against both strains (IC₅₀ (33) = 4.7 ± 1.3 nM against Pf3D7 and 6.5 ± 2.5 nM against PfDd2; IC₅₀ (37) = 4.6 ± 0.6 nM against 3D7 and 10.5 ± 0.4 nM against Dd2). Resistance indices (RIs) ranged from 0.9 to 5.3 compared to CQ (RI = 14.4), highlighting their superior consistency in activity against both strains. The cytotoxicity screening performed on HepG2 revealed over 3 orders of magnitude higher IC₅₀ for most of the compounds, with SIs from 711.0 to 8081.8. Spectroscopic studies explored the affinities of newly synthesised compounds for DNA, RNA, and HSA. Both tested hybrids, 34 and 39, were intrinsically fluorescent in an aqueous medium, characterised by remarkable Stokes shifts of emission maxima (Δλ = +103 and +93 nm for 34 and 39, respectively). Fluorimetric experiments revealed that compound 34, with its shorter and more flexible linker, exhibited at least an order of magnitude higher affinity toward ds-DNAs versus ds-RNA and two orders of magnitude higher affinity toward GC-DNAs compared to 39. The behaviour of the investigated compounds upon binding to HSA is very similar, showing a strong hypsochromic shift of the emission maximum (almost Δλ = −70 nm) and demonstrating their effectiveness as fluorimetric probes for distinguishing between DNA/RNA and proteins. Full article