Browse Articles
Discover research articles across all indexed journals
Riemannian manifold dynamic attention fusion network for motor imagery EEG decoding
A novel Upward-Extended Five-Zone model for overburden failure in deep coal seams with ultra-thick Cretaceous strata
Comparative genomics and cefepime synergy of a lytic Vectrevirus phage Eco-MTCMU-01, targeting extended spectrum β-lactamase-producing Escherichia coli
Finite element analysis of high-rise prefabricated shear walls with discontinuous rebars
Towards higher order oscillatory Ising machines
Abstract Ising machines as hardware solvers of combinatorial optimization problems (COPs) can efficiently explore large solution spaces due to their inherent parallelism and physics-based dynamics. Many important COPs such as satisfiability (SAT) assume arbitrary interactions between problem variables, while most Ising machines only support pairwise (second-order) interactions. This necessitates translation of higher-order interactions to pairwise, which typically results in extra variables not corresponding to problem variables, and a larger problem for the Ising machine to solve than the original problem. This in turn can significantly increase time-to-solution and/or degrade solution accuracy. In this paper, considering a representative CMOS-compatible class of Ising machines, we propose a practical design to enable direct hardware support for higher order interactions. By minimizing the overhead of problem translation and mapping, our design can result in up to 4 $$\times$$ lower time-to-solution without compromising solution accuracy.
Omics-based study of salt stress mechanisms in mountain peach (Prunus davidiana Carr.) in Northwest China
Abstract Long-term field evidence shows that peach trees grafted onto mountain peach ( Prunus davidiana Carr.) rootstocks exhibit superior salt tolerance in Northwest China’s saline-alkali soils compared to those on hairy peach ( Prunus persica L.) rootstocks, yet the mechanism is unclear. This study compared physiological and transcriptomic analysis, providing a theoretical basis for understanding breeding responses of ‘Longmi 9’ peach to salt stress. Mountain peach effectively restricted leaf Na⁺ accumulation (up to 36.36% reduction) and Cl⁻ influx, maintained a higher K⁺/Na⁺ ratio, and showed only half the reduction in stomatal aperture under high stress, thereby preserving photosynthesis. In contrast, hairy peach exhibited sensitive ion accumulation. Transcriptomics revealed a more targeted response in mountain peach, with 256 differentially expressed genes (DEGs) across three stress levels versus 1196 in hairy peach. Both varieties activated phenylpropanoid and α-linolenic acid metabolism pathways. Notably, mountain peach uniquely coordinated glutathione, nitrogen, and pyruvate metabolism into a synergistic network, whereas hairy peach relied more on flavonoid biosynthesis. Quantitative real-time PCR (qRT-PCR) validation of ten co-enriched DEGs, such as PRX44 , OPR2 and CCR2 , confirmed expression trends consistent with the transcriptome data, thereby verifying its reliability. This work elucidates the multilevel, coordinated regulatory mechanism conferring salt tolerance in mountain peach, providing robust theoretical foundations for the development of salt-tolerant peach cultivars.
Adaptive Blockchain-Oriented Trust Management in IoV using Proximal Policy Optimization
Integrative network pharmacology and in vitro/in vivo validation reveal the protective effects of sotetsuflavone against osteoarthritis associated with PI3K/Akt/NF-κB signaling
A hybrid underwater crack image enhancement method
Induction of mucosal immune responses against SARS-CoV-2: a heterologous intramuscular mRNA-LNP prime/pulmonary recombinant subunit pull vaccination strategy
Analysis of sparse vector data using tessellation based on root volume–optimal cycles
Abstract This study proposes a novel approach to investigate sparse vector datasets. The key feature of our method is the tessellation of space using volume–optimal cycles, a useful tool in persistent homology. Using this tessellation, we divide the space into polygons with short edges, which enables the evaluation of the vorticity or circulation of the vector field. The proposed method is applied to both artificial and real datasets, and the results show that our approach effectively visualizes and quantifies the rotational component of a vector field.
Intensity-based criterion for determining exceptional point in parity-time (PT) symmetric coupled array of optical waveguidesk
Multi-scale and context-aware enhanced YOLOv8 for breast tumor detection in ultrasound images
Climatic determinants of rheumatic and autoimmune musculoskeletal pain: a fourteen-year primary care time-series study
Regular substance use relates to cost sensitivity during cost-benefit decision-making in stable and volatile learning contexts
Abstract Research on substance use and decision-making relates reward sensitivity, cost insensitivity, and inconsistent use of cost information to greater substance use severity. However, little work tests how people compare rewards to costs within the same choice. Further, no work examines how the comparison of rewards to costs varies across different contexts. We administered a new cost-benefit variant of a probabilistic learning task to a diverse community sample with elevated rates of substance use ( N = 130). Individuals with more years of regular substance use tended not to repeat safe choices particularly in contexts where doing so was advantageous, and repeated risky choices after they incurred losses regardless of context. Individuals with more years of regular substance use also showed reduced discrimination between loss magnitudes, selecting the risky choice even as loss magnitudes increased. Computational modeling parameters indicated that these individuals under-weighted losses, though this relationship weakened when accounting for age. Altogether, these results suggest that decreased sensitivity to cost information may characterize continued substance use despite incurring negative consequences.
Whole-genome sequencing of samples from a Streptococcus parasuis infection
Illusion of competence: vision–language models provide confident but inaccurate explanations in cytological diagnostics
Abstract Large vision-language models (LVLMs) have shown impressive image-understanding capabilities across domains. However, their suitability for cytomorphological diagnostics remains unclear. Here, we systematically evaluated four state-of-the-art generalist LVLMs, GPT-4o, Gemini-2.0, Llama-3.2, and DeepSeek-VL2, and three biomedical LVLMs, LLaVA-Med, CONCH, and BiomedCLIP, across key cytomorphology benchmarks, including peripheral blood cell classification, morphology assessment, bone marrow cell classification, and cervical smear malignancy detection. Performance was assessed under zero-shot, few-shot, and fine-tuned settings. In zero-shot and few-shot evaluations, LVLMs performed poorly, often approaching random performance. In peripheral blood cell classification, GPT-4o achieved a zero-shot F1 score of only 0.22 ± 0.02 and a few-shot F1 score of 0.36 ± 0.03. Even after fine-tuning, GPT-4o was outperformed by a lightweight, dedicated hematology model. Beyond classification accuracy, we assessed interpretability and trustworthiness. Although LVLMs generated textual justifications, these often reflected textbook knowledge rather than the actual morphological features present in the cell images. Expert evaluation showed that 30% of explanations for misclassified cells were rated as poor or misleading. While LVLMs could segment cellular structures such as nuclei and granules, they failed to reliably identify the image regions relevant to their classification decisions. Our findings underscore three major limitations of current LVLMs in cytomorphology: (1) low diagnostic accuracy, (2) poor generalizability across domains, and (3) unreliable explainability. These results suggest that LVLMs require substantial improvement before they can be used for cell-type classification and morphology characterization in diagnostic settings. Purpose-built models remain the more effective and trustworthy choice.
A blockchain-enabled multi-objective reinforcement learning framework for secure energy- and time-efficient smart path planning in cloud environments
Genetic diversity and mobile genetic element associated multidrug resistance in Salmonella enterica from broiler chickens in Egypt
Abstract Salmonella enterica remains a leading foodborne zoonotic pathogen worldwide, with poultry serving as a major reservoir and vehicle for antimicrobial resistance dissemination to humans. This study investigated the genotypic basis and distribution of multidrug resistance (MDR) among 29 S. enterica isolates from broiler farms in Egypt, emphasizing the role of mobile genetic elements as integrons and the assessment of genetic relatedness using ERIC-PCR. Molecular screening revealed high prevalence of resistance determinants, including flo R (93.1%), tet A (86.2%), aph A1 (82.8%), cml A (75.9%), ere A (75.9%), sul I (62.1%), aad A1 (51.7%), dfr A1 (48.3%), aac (3)-IV (44.8%), tet B (41.4%), sul II (31.0%), aac (6′)-Ib-cr (24.1%), cat A1 (20.7%), fos A3 (20.7%), and qnr A (10.3%). High-risk serovars, including S. Jerusalem, S. Colorado, and S. Kentucky, harbored multiple resistance genes and exhibited pronounced XDR profiles. Notably, this study reports the detection of aph A1 and fos A3 in Salmonella isolates derived from broiler chickens, which may represent an early or uncommon finding in Egypt. Many resistance genes were associated with horizontally transferable class 1 integron, underscoring its key role in the dissemination of multidrug resistance (MDR) within poultry systems and along the food chain. ERIC-PCR genotyping segregated isolates into two major genetic groups with seven sub-clusters, reflecting clustering patterns and genetic diversity among the isolates, alongside notable heterogeneity in resistance, virulence, and biofilm-associated genes.Overall, poultry in Egypt represents a significant reservoir of genetically diverse and potentially transmissible MDR S. enterica , highlighting the need for enhanced antimicrobial stewardship and genomic surveillance to mitigate public health risks.