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Author Correction: The oldest known lepidosaur and origins of lepidosaur feeding adaptations

Role of ionization potential depression for generation of strongly coupled plasmas in high-pressure supercritical fluids

Resolving passage ambiguity in machine reading comprehension using lightweight transformer architectures

Identification of anomalous geological structures for iron mines using a multi-geophysical prospecting method: a case study of Songhu iron mine

Uncovering the role of RNA binding proteins in colorectal cancer through single-cell transcriptomic analysis

Wound healing improvement by a multicomponent wound dressing of keratinocyte-imprinted polydimethylsiloxane substrate in a rabbit model

Spatiotemporal analysis of consumer scanning behavior using integrated QR code and POI data

Publisher Correction: Radiation-induced amphiregulin drives tumour metastasis

Examining Japanese laypeople’s nationality preferences for physicians: a nationwide study

Abstract This study aimed to investigate physician nationality preferences of Japanese laypeople and the reasons behind the preferences. We performed a nationwide study in May 2025. The participants were monitors of an internet survey company who responded to closed questions regarding nationality preferences across different physician qualities and clinical scenarios, along with open-ended questions regarding their expectations and concerns about care by foreign national physicians. We analyzed responses to the closed questions by descriptive statistics. We compared responses between individuals with prior experience of seeing a foreign national physician and those without such experiences by chi-square test. For free-text responses, we performed inductive content analysis. Among 2004 respondents, approximately half to two-thirds preferred Japanese physicians. Participants with prior experience of seeing a foreign national physician were significantly less likely to indicate a nationality-concordant preference. In free-text responses, 337 participants provided expectations (360 codes) and 938 provided concerns (982 codes). Among concerns, 723 codes were labelled as a language barrier. Participants expressed expectations of the possible strengths of foreign national physicians. This study clarified the nationality preferences of Japanese laypeople in physician selection. The findings have significant implications, including the necessity of reconsidering medical education strategies, public education, and inclusive policy frameworks.

Heat reduction during bone drilling using a two-stage drilling strategy

Evaluating the role of microplastics and wastewater in shaping Vibrio spp. and antibiotic resistance gene abundance in urban freshwaters

Tri branch attention enhanced 3DUNet for remote sensing based hyperspectral image classification

Effects of combined group reminiscence and exercise therapy on psychological wellbeing and functional fitness among older adults with dementia

Eltrombopag olamine induces apoptosis in human breast adenocarcinoma and hepatocellular carcinoma cells through modulation of multiple apoptotic pathways

Establishing a national pediatric stem cell transplantation registry in Iran addressing implementation and data quality challenges

Integrated genomic-transcriptomic analysis of clavulanic acid production in differentially productive Streptomyces clavuligerus strains

Large language models are biased — local initiatives are fighting for change

Pharmacovigilance analysis of vision disorders relating to brimonidine treatment and mechanism study using network toxicology and molecular docking

EnCTN: an enhanced AI-enabled deep learning framework for security enhancement in blockchain transactions

Abstract The deep learning technique has emerged as an exemplary model for managing the Artificial Intelligence-based Blockchain framework with technological enhancements to guarantee reliable data through the consensus procedure. The deep learning-enabled blockchain transaction model has involved the development of security to solve the problems of confidentiality and data anonymity. The Hybrid techniques of the Blockchain with the Deep Learning technique are proposed to generate enhanced data durability and its propagation through the enhanced convolutional temporal network (EnCTN) for transaction analysis in a blockchain-enabled Auto Encoder technique. The sliding window extraction technique is used to extract information from a particular window size to evaluate the needed input values from the temporal series. The dilated Convolution is used to capture the long-range dependencies. The proposed technique is implemented in the Ethereum environment using Python, and experimental results show that it has produced an improved performance than the relevant technique in several performance parameters. The anomaly classification accuracy is improved than the relevant technique and it is evaluated using the NSL-KDD dataset. The proposed framework delivers an efficient solution for the real-world anomaly detection application while accurate discovery of temporal anomalies and computational efficiency is enhanced.

Temperature driven density gradients of two congeneric felids reveal contrasting responses to climate change at a range margin