Search Results (1,993)

The conventional time-dependent perturbation theory in quantum mechanics is established within the framework of Hermitian Hamiltonians, applicable for describing quantum transitions and associated energy level responses in such systems. However, this theory has fundamental limitations when applied to non-Hermitian systems. Consequently, researchers have systematically extended time-dependent perturbation theory to non-Hermitian systems, establishing a corresponding mature framework. Building on this foundation, this study extends the theory to investigate the transition dynamics induced by non-Hermitian interactions in non-Hermitian Hamiltonian systems. We employ a biorthogonal basis representation for a three-level non-Hermitian system. This work investigates a system comprising an unperturbed static non-Hermitian Hamiltonian and a periodically driven time-dependent perturbation Hamiltonian. Taking the three-level system as a concrete example, we combine analytical methods with numerical simulations to solve and analyze its dynamical evolution equations. These complementary approaches reveal that when system parameters complete a full cycle around an exceptional point, the transitional behavior exhibits specific evolutionary patterns. In this system, quantum transition probabilities exhibit significant asymmetry and non-conservation that depend on the initial and final states, revealing inherent directional characteristics in the dynamical process. Furthermore, for a three-level, periodically driven non-Hermitian system with time-dependent perturbations, this asymmetry is even more pronounced, manifesting as a distinct disparity between forward and reverse transition probabilities. The periodic driving actively amplifies the asymmetry in the transition process. By designing the perturbation spectrum, selective manipulation of specific quantum states can be achieved. Moreover, transition probabilities can be significantly enhanced under resonance conditions, while non-Hermiticity further breaks the system’s inherent symmetry, leading to substantial amplification of transitions in a single direction. By precisely tuning the drive frequency, interactions between specific coupling channels can be selectively enhanced or suppressed. The amplification of channel asymmetry by non-Hermitian properties provides a novel mechanism for directional control of quantum states and opens new pathways for realizing related quantum technologies. Full article

With the rapid proliferation of short-video platforms and live-streaming commerce ecosystems, marketing activities are increasingly manifested through complex multimodal sensing signals. These heterogeneous sensor data streams exhibit strong temporal dependency, high cross-modal coupling, and progressive evolutionary characteristics, making early-stage fraud perception particularly challenging for conventional unimodal or static analytical paradigms. Existing approaches often fail to effectively capture weak anomalous cues emerging across multimodal channels during the initial stages of fraudulent campaigns. To address these limitations, an artificial intelligence-driven multimodal sensor perception framework is proposed for temporal fraud detection in short-video environments. A multimodal temporal alignment module is first designed to synchronize heterogeneous sensor signals with inconsistent sampling granularities. Subsequently, a shared temporal encoding network is constructed to learn evolution-aware representations across multimodal sensor sequences. On this basis, a cross-modal temporal attention fusion mechanism is introduced to dynamically weight sensor contributions at different behavioral stages. Finally, a fraud evolution modeling and early risk prediction module is developed to characterize the progressive intensification of fraudulent activities and to enable risk assessment under incomplete temporal observations. Extensive experiments conducted on real-world datasets collected from multiple mainstream short-video platforms demonstrate the effectiveness of the proposed AI-driven sensing framework. The model achieves an overall accuracy of 0.941, precision of 0.865, recall of 0.812, and F1 score of 0.838, with the AUC further reaching 0.956, significantly outperforming text-based, vision-based, temporal, and conventional multimodal baselines. In early-stage detection scenarios utilizing only the first 30% of video content, the framework maintains stable performance advantages, achieving a precision of 0.812, recall of 0.704, and F1 score of 0.754, validating its capability for proactive fraud warning. Full article

R2R3-MYB and bHLH transcription factors (TFs) are key regulators of floral secondary metabolism and epidermal development in flowering plants. Orchids exhibit remarkable floral diversity, which is critical for pollination success and ornamental value, yet the evolutionary and functional diversification of these TF families within the genus remains largely unexplored. Here, we conducted a comprehensive pan-genome dissection of R2R3-MYB and bHLH TF families across 18 Dendrobium species, integrating orthologs assignment, phylogenetics, duplication profiling, cis-regulatory annotation, and tissue-specific expression analysis. We identified 3074 R2R3-MYB and 2282 bHLH genes, classified into 69 and 61 orthologous gene groups (OGGs), respectively. Core OGGs accounted for two-thirds of both families, indicating strong evolutionary conservation, whereas variable OGGs reflected lineage-specific diversification. Phylogenetic analyses resolved R2R3-MYBs into 24 canonical subfamilies and revealed conserved heterogeneous expansion patterns in bHLH subfamilies. Promoter architectures of R2R3-MYB genes were enriched in hormone-, stress-, and light-responsive elements, whereas bHLH promoters were dominated by development-related motifs. Tissue-specific expression profiling in Dendrobium ‘Chao Praya Smile’ showed that floral bud-enriched genes were associated with flavonoid/anthocyanin biosynthesis, whereas root-enriched genes were linked to stress and hormone responses. Integration of pan-genomics and transcriptomics highlighted evolutionary trajectory and functional divergence between core and variable gene sets within Dendrobium. Our study establishes a comprehensive, genus-wide framework for understanding the evolutionary and functional characteristics of MYB–bHLH regulatory networks in Dendrobium. These findings provide valuable genetic resources and key candidate targets for functional characterization and molecular breeding, with important implications for genetic improvement of reproductive traits, floral quality, stress resistance, and ornamental and agronomic value in orchids. Full article

Under the framework of the Paris Agreement, carbon trading has emerged as a pivotal market-based instrument for achieving carbon neutrality. Following years of pilot programs, China has taken a critical step toward establishing a unified national carbon market. Consequently, accurate carbon price forecasting is essential for constructing a stable and effective carbon pricing mechanism. However, the 2017 reform of the EU Emissions Trading System (EU ETS) significantly altered the carbon price formation mechanism, exacerbating price volatility and uncertainty. This shift further underscores the urgent need for research into high-precision carbon price forecasting.Existing deep learning models struggle to simultaneously capture short-term high-frequency fluctuations and long-term evolutionary trends within complex carbon market data, a limitation that compromises their prediction accuracy and stability. To address these challenges, this paper proposes a Transformer-based carbon price forecasting model that incorporates an sLSTM structure. By enhancing sequence memory and state update mechanisms, this model effectively improves the capability to model both short-term volatility characteristics and long-term evolutionary patterns of carbon prices. In the data preprocessing phase, Variational Mode Decomposition (VMD) is employed to perform multi-scale decomposition of carbon price sequences, effectively mitigating the issue of overlapping fluctuations across different time scales. Furthermore, the Whale Optimization Algorithm (WOA) is utilized to optimize the number of decomposition modes and the penalty factor, thereby resolving the parameter sensitivity issues inherent in modal decomposition. Experimental results on real-world carbon price datasets demonstrate that the model achieves an average coefficient of determination ($R^2$) of 0.9862 and a Mean Absolute Percentage Error (MAPE) of only 0.5607%. These findings indicate that the proposed method possesses significant advantages in characterizing the complex dynamic features of time series, thereby effectively enhancing prediction accuracy.The proposed model can serve as a supportive tool for carbon-market risk monitoring and policy evaluation by identifying abnormal fluctuations and mitigating market inefficiencies caused by information asymmetry. This enhances the stability and predictability of carbon price signals as incentives for emissions reduction, enabling firms to plan abatement pathways and low-carbon investments, and strengthening the sustainable role of carbon markets in achieving carbon neutrality. Full article

Multi-model ensembles and multi-objective evolutionary algorithms provide a systematic approach to reconciling competing criteria in time-series forecasting. However, most existing methods are tailored to specific tasks and lack essential mathematical details. This study introduces a general multi-objective ensemble framework based on a Multi-Objective Enhanced Crisscross Optimization (MOECSO) algorithm, exemplified through Brent crude oil price forecasting. Initially, ensemble-weight selection is framed as a bi-objective optimization problem, where the two objectives penalize Mean Absolute Error (MAE) and the Sample Standard Deviation of the Validation Residuals (SSDVRs), both assessed on the original United States Dollar (USD) scale under a leakage-free rolling-origin protocol. Subsequently, a Variational Mode Decomposition (VMD) reconstruction operator is defined, which adaptively reconstructs the raw series by integrating intrinsic mode functions with weights derived from their entropy and center-frequency characteristics, while adhering to nonnegativity and normalization constraints. Furthermore, horizontal and vertical crossover operators, along with a hypervolume–ideal-distance archive rule, are introduced, collectively forming a comprehensive MOECSO scheme for bi-objective ensemble weighting. Utilizing a public Brent crude oil dataset, the proposed ensemble demonstrates superior performance compared to robust statistical, machine-learning, and deep-learning benchmarks in terms of MAE, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), while also reducing error dispersion and enhancing robustness during crisis periods. Diebold–Mariano (DM) and superior predictive ability tests with multiple-comparison control validate that these improvements are statistically significant. In summary, this paper presents a mathematically transparent framework for constructing and analyzing multi-objective ensembles in univariate time-series forecasting. Full article

Research on the evolutionary patterns and propagation mechanisms of different drought types is of great significance for regional water resources management and the prevention and control of agricultural drought risks. Taking the arid region in the western Chinese Loess Plateau as the study area, this paper systematically revealed the spatiotemporal variation characteristics, propagation lag time and conditional probability of meteorological and agricultural droughts based on the monthly Standardized Precipitation Evapotranspiration Index (SPEI) and self-calibrating Palmer Drought Severity Index (scPDSI) during 1985–2022 by comprehensively adopting the Mann–Kendall trend test, Sen’s slope estimation, run theory, drought frequency analysis, as well as the Copula function and event-matching method. The results showed that during the study period, meteorological drought (characterized by SPEI) exhibited an insignificant intensification overall, while agricultural drought (characterized by scPDSI) presented a significant mitigation at the monthly scale. The maximum occurrence frequency of agricultural drought reached 70.39%, which was significantly higher than that of meteorological drought (38.82%); in addition, agricultural drought featured a longer average duration and greater severity, with a spatial pattern of higher in the northwest and lower in the southeast in the study area. The average propagation lag time of drought derived from the Copula function was 1.41 months, versus 2.19 months obtained by the event-matching method. When meteorological drought reached the moderate level (SPEI < −1.0), it was likely to trigger agricultural drought of mild or higher severity. The research findings can provide a scientific reference for formulating differentiated drought prevention strategies in the arid region of the western Loess Plateau, China. Full article

Iguanodectes geisleri and I. adujai are freshwater fish from South America. Their taxonomic status and phylogenetic relationships are uncertain due to limited molecular data. High-throughput sequencing was applied to obtain and annotate for the first time the complete mitochondrial genomes of I. geisleri and I. adujai to clarify their phylogenetic positions. Mitochondrial genome sequences of 73 Characoidei species were retrieved from GenBank, with Gyrinocheilus aymonieri and Microphysogobio alticorpus designated as outgroups. Phylogenetic trees were constructed using a mitochondrial protein-coding gene dataset and Maximum Likelihood and Bayesian Inference methods. The complete mitochondrial genome measured 16,774 and 16,802 bp, respectively. Both genomes exhibited highly conserved structures. Despite morphological similarities and a close phylogenetic relationship, differences were detected in genomic structure, base composition, codon usage bias, and the control region between the two species. The two species comprise a strongly supported monophyletic clade and are sister species but represent distinct, independent branches. I. geisleri and I. adujai have been recognized as distinct species based on morphological differences, and this study provides molecular confirmation of their separate taxonomic status. The study provides molecular data for the taxonomic identification of fishes of the genus, Iguanodectes, and foundational mitochondrial genomic data for Characiformes. The study advances research on the genetic evolution of this group and resource conservation. Full article

Background/Objectives: Ziziphus jujuba var. spinosa (sour jujube) is a traditional medicinal plant with remarkable tolerance to abiotic stresses, particularly salinity. However, the regulatory mechanisms underlying its salt stress tolerance remain unclear. NHX genes play a crucial role in plant adaptation to salt stress by mediating Na⁺/K⁺ transport to maintain intracellular ion homeostasis and pH balance. Although the NHX gene family has been characterized in many plant species, its functional characteristics in sour jujube have not yet been systematically investigated. Methods: In this study, using Arabidopsis thaliana as a reference, we identified NHX genes in sour jujube through genome-wide analysis and molecular approaches, and systematically analyzed their phylogenetic relationships, chromosomal locations, conserved motifs, gene structures, cis-regulatory elements in promoter regions, and expression patterns under abiotic stresses, particularly salt stress. Results: The results revealed the presence of eight NHX genes distributed across six chromosomes in sour jujube, which were classified into three subfamilies: Vac-class, Endo-class, and PM-class. Members within the same evolutionary clade exhibited high structural conservation in motif composition and gene architecture. Except for the PM-class, all other clades contained amiloride-binding sites (FF(I/L)(Y/F)LFLLPPI). Analysis of cis-regulatory elements indicated that the promoter regions of these genes were enriched with elements related to defense responses, stress adaptation, and phytohormone signaling, further supporting their role in plant environmental adaptation. Additionally, the qRT-PCR analysis showed that most of the ZjNHX genes in both roots and leaves are up-regulated by salt. Notably, ZjNHX1 expression in roots increased approximately 40-fold within 3 h, whereas ZjNHX2 and ZjNHX3 were strongly induced in leaves under prolonged salt exposure. Conclusions: Taken together, this work gives a detailed overview of the ZjNHX genes and their important roles in response to salt stress in sour jujube. Our findings also provide a foundation for further functional characterization of this gene family. Full article

Porcine circovirus (PCV) is a major viral pathogen associated with multiple systemic diseases in pigs, inflicting significant economic losses to the global swine industry. To investigate the epidemiology and genetic evolution of porcine circovirus in Liaoning Province, China, PCV was detected by qPCR in 1224 clinical samples. Subsequent genetic evolution analysis of the Cap gene was conducted, and an indirect ELISA and monoclonal antibody were established. The results demonstrated PCV2 and PCV3 positivity rates of 14.13% and 21.90%, respectively, with a coinfection rate of 4.08%. All six sequences were identified as belonging to the PCV3b subtype. A representative PCV3 strain was expressed in a prokaryotic expression system and used to immunize 6-week-old female BALB/c mice, resulting in serum antibody titers reaching 1:512,000. The positive hybridoma cell line 3E6 was selected and identified as expressing IgM heavy chains and κ light chains. The prepared monoclonal antibody 3E6 exhibited specific reactivity with the Cap protein. Collectively, this study elucidates the recent epidemiological status and evolutionary characteristics of PCV in pig populations in Liaoning Province, thereby providing an important theoretical basis and reference data for disease prevention, control, diagnosis, and vaccine development. Full article

Plant cysteine oxidase (PCO) catalyzes the oxidation of cysteine residues in the N-degron pathway, thereby regulating the stability and activity of the seventh group of ethylene response factors (ERF-VII), which play a crucial role in reactive oxygen species (ROS)-mediated signal transduction. By regulating the degradation of ERF-VII, the PCO family genes control hormone signaling, which is highly valuable for plant growth and abiotic stress responses. However, systematic studies on PCO genes in Medicago sativa, a key forage legume, remain lacking. Herein, 35 MsPCO genes were identified from the alfalfa (Medicago sativa) genome, and their biological characteristics were comprehensively analyzed via bioinformatics approaches. The results showed that MsPCO genes are asymmetrically distributed across 18 chromosomes and clustered into 5 subgroups phylogenetically. Most MsPCO proteins are hydrophilic and localized in the cytoplasm. A total of 56 duplication events were detected, with most duplicated pairs undergoing purifying selection (Ka/Ks analysis). Collinearity analysis revealed close evolutionary relationships between Medicago sativa and Medicago truncatula, Arabidopsis thaliana or Glycine max. Promoter cis-acting elements in MsPCO genes are involved in light response, stress adaptation, hormone signaling, and growth regulation. Transcriptomic data indicated differential expression of MsPCO genes under abiotic stresses. MsPCO20 is dispersed throughout the cell membrane and nucleus, whereas MsPCO19 is localized to the nucleus, according to subcellular localization experiments. These findings provide candidate genes and a theoretical basis for further functional characterization of PCO genes in alfalfa. Full article

To elucidate the evolutionary patterns and influencing factors affecting the stability of the surrounding rock during tunnel excavation in ductile shear zones, this study takes the tunnel section within the ductile shear zone of the mountain area as a case study. Numerical simulation methods were employed to analyze vertical deformation, plastic zone development, and stress redistribution characteristics of the surrounding rock under a three-step excavation approach. Furthermore, this research investigates how burial depth and surrounding rock grade impact stability. The findings indicate that during the tunnel excavation process, the vertical deformation, plastic zone, and extrusion deformation at the face exhibit significant phased characteristics. Notably, the weak zone of the fractured surrounding rock serves as a concentrated area of deformation. Upon completion of the excavation, the maximum settlement observed at the arch top reached 246.07 mm. The plastic zone primarily experienced shear failure and showed a tendency to stabilize after reaching section Y = 35 m during excavation. The burial depth exerts a significant influence on the stability of the surrounding rock. As the burial depth increases from 400 m to 550 m, there is an observable upward trend in the settlement at the top of the arch, uplift at the bottom of the arch, and maximum principal stress; notably, the rate of increase for maximum principal stress remains stable. The instability mechanism of the surrounding rock, primarily characterized by shear failure, has not altered. The classification grade of the surrounding rock serves as a critical factor influencing stability. The vertical deformation scale, extent of plastic zones, and values for maximum principal stress in Grade IV surrounding rock are considerably smaller than those observed in Grade V. Enhanced mechanical properties and integrity within the rock mass can significantly improve stability conditions for surrounding rocks. These research findings provide a theoretical foundation and engineering reference for optimizing support systems in tunnels traversing ductile shear zones. Full article

Glycogen synthase kinase 3 (GSK3/SHAGGY-like kinase) plays a pivotal role in regulating plant growth, development, and stress responses. To elucidate the characteristics of the GSK family in Glycine max, this study employed whole-genome data combined with bioinformatic and gene expression analyses to investigate the gene structure, chromosomal localization, collinearity, phylogenetic evolution, promoter cis-elements and differential gene expression analysis. Additionally, the expression patterns of GmGSK genes under manganese (Mn) stress and their associated phenotypic alterations were analyzed. A total of 22 GmGSK family members were identified, all harboring the characteristic GSK kinase domain. These members are distributed across 16 chromosomes, encoding proteins ranging from 380 to 802 amino acids (aa) in length. Phylogenetic analysis classified the GmGSK family into four evolutionary clades, consistent with patterns observed in Arabidopsis and Oryza sativa. Members within the same clade share identical exon-intron structures and conserved motifs. Collinearity analysis revealed that segmental duplication events have been crucial in the functional expansion of the GmGSK family through intraspecific collinearity. In recent years, alongside industrial development and fertilizer imbalance, the effective manganese concentration in agricultural soils has risen abnormally in some regions of China, leading to toxic effects on crops. Soybean, an oilseed crop relatively sensitive to manganese, has been adversely impacted. Clarifying the response mechanisms of soybean seedlings to manganese stress is therefore of significant importance for improving both yield and quality. Manganese stress treatment induced significant up-/down-regulation of specific GmGSK members in soybean, concomitant with pronounced inhibition of root elongation and leaf growth. This study provides a theoretical framework for deciphering the molecular regulatory mechanisms by which the GmGSK gene family mediates plant responses to Mn stress, offers insights into soybean Mn tolerance mechanisms, and establishes a foundation for genetic improvement of Mn-tolerant traits in crops. Full article

The early warning of rock mass failure in deep hard-rock mines presents a significant challenge for mine safety management. Microseismic monitoring data offer a novel analytical approach to address this issue. This study investigates the evolutionary patterns of rock mass failure in mining areas through the analysis of spatiotemporal energy data from microseismic events. Initially, key spatiotemporal energy parameters are extracted to identify microseismic events associated with localized damage and their periodic characteristics. Subsequently, a spatiotemporal fractal dimension analysis method is established to achieve fractal interpretation of the data by integrating field cloud maps. Finally, an early warning model centered on temporal energy is constructed, which delineates warning zones through a comprehensive evaluation of fractal dimensions, thereby providing decision-making support for mine safety. Full article

The structural characteristics of the Majiatan fault–fold system in the northwestern Ordos Basin are complex, and the detailed 3D distribution of faults and their evolutionary mechanisms remain insufficiently understood, which restricts effective petroleum exploration in this region. To address this, this study utilizes high-resolution 3D seismic data comprising 20 lines (total length 753.371 km, survey grid 3 × 3 km) and drilling and logging data from 13 wells (including synthetic seismograms) to establish a detailed 3D fault model. We aim to elucidate the fault styles and the formation mechanism of the fault–fold–thrust belt. Results indicate the presence of 47 Mesozoic faults, all of which are thrust faults classified into three types. Structural traps dominate the leading transition zone, whereas lithologic–structural traps are prevalent in the Tian-huan Syncline. Laterally, from south to north, the fault occurrence transitions from west-dipping east-thrust to east-dipping west-thrust, accompanied by a shift in tectonic style from thrusting nappe to late-stage reconstruction. The stress intensity generated during the Late Cretaceous increases northward, causing deformation to shift westward. Typical fault styles observed include “y-shaped”, “flower-shaped”, and “imbricated” structures. The middle-north zones of the Majiatan area and the Hengshanbu Thrust Belt share a unified formation mechanism: initiation in the Late Triassic, main development in the Late Jurassic, initial shaping in the Late Cretaceous, and final modification in the Eocene, driven by the rotation of the Ordos Basin and shear tectonic forces. The most favorable exploration zones are identified at the junctions between the leading zone, the fault–fold zone, and weakly transformed zones. The tectonic evolution model established in this study provides a valuable reference for understanding structural complexities and guiding hydrocarbon exploration in similar fold and thrust belts globally. Full article

Bivalves possess a diverse array of photoreceptive organs that are significant for their evolutionary success and systematic classification. Giant clams are the largest bivalve mollusks, with mantle tissue permanently extended in nature to maintain symbiosis with zooxanthellae and perceive environmental cues. Eyes serve as critical sensory organs for these organisms, yet the structural and functional characteristics of tridacnine eyes remain inadequately understood. This study systematically investigated the ocular traits and visual resolution of three ecologically distinct giant clam species (Tridacna crocea, T. squamosa, T. maxima) using morphometric analysis, hematoxylin-eosin (HE) staining, transmission electron microscopy (TEM), and grating stimulation assays. Significant interspecific differences were observed in eye count, diameter, and pupil-to-eye ratio (PER): T. maxima exhibited the highest mean eye count (221 ± 8), T. squamosa the largest mean eye diameter (0.490 ± 0.082 mm), and T. crocea the highest mean PER (0.363 ± 0.041). Eyes were numerically symmetric on the left and right mantles but positionally asymmetric, showing random distribution patterns along the mantle margin without fixed corresponding locations across species. All three species possessed typical pinhole eyes lacking lenses and retinas, primarily composed of filler cells, receptor cells, and sparse neurons, with symbiotic zooxanthellae distributed in the surrounding mantle tissue. Grating stimulation assays revealed resolvable stripe periods of 5.82–11.64° (T. crocea), 8.62–13.16° (T. squamosa), and 10.15–12.26° (T. maxima), confirming T. crocea as the species with the highest visual resolution. These ocular variations are inferred to reflect adaptive evolution driven by ecological niches and habitat-specific factors (water depth or light intensity), while the simplified pinhole morphology is consistent with their sedentary lifestyle and metabolic dependence on symbiotic zooxanthellae. These ocular variations provide potential morphological markers for the systematic classification of Tridacninae and offer valuable insights for researchers studying the evolutionary plasticity of bivalve visual systems. Full article