Explore the vast range of titles available.

Two new species of the genus Dorylaimopsis Ditlevsen, 1918 from the subtidal zone of the Yellow Sea are described and illustrated. Dorylaimopsis sinica sp. nov . is characterised by the lateral differentiation in the form of longitudinal rows of larger dots which consisting of three rows of dots in about the anterior 20% and posterior 20% of the total body length and two rows of dots in the rest portion of the body, by the multispiral amphidial fovea having three turns; slender, equal, arcuated spicules; cephalated proximal end with a short median cuticularised lamina; length 1.9–2.2 times the cloacal body diameter; gubernaculum with two geniculate curved apophyses and 14–17 papilliform precloacal supplements; and excretory pore posterior to nerve ring. Dorylaimopsis zhangi sp. nov . is characterised by having cephalic setae 6–7 μm long, amphidial fovea with three turns, lateral differentiation consisting of four longitudinal rows of larger dots in the pharyngeal and tail regions, three longitudinal rows of larger dots in the middle region of body, spicules slender and slightly curved, length 2.0–2.5 times the cloacal body diameter, and 18 small, pit-like precloacal supplements. An updated dichotomous key is provided for the 29 valid species of Dorylaimopsis .

Autoimmune hepatitis (AIH) is a complex immune-mediated liver disorder characterized by dysregulated immune responses. This study aimed to decode the distinct immune landscape and regulatory mechanisms of AIH using integrated single-cell and bulk RNA sequencing. The data of single-cell RNA-seq (scRNA-seq) and bulk RNA-seq were downloaded from GEO database. The cell clustering, differential gene expression, trajectory analysis, functional enrichment, and cell-cell communication were performed were analyzed using R software. Five major immune cell types were identified, with CD8 + T cells and NK cells significantly expanded in AIH. Functional enrichment showed upregulation of immune activation, inflammation, and metabolic pathways in these cells. The cell-cell communication analysis revealed robust interactions between CD8 + T and NK cells, primarily driven by the CCL5-CCR signaling axis. Integrative analysis of scRNA-seq and bulk RNA-seq identified four common DEIRGs (ITK, IL7R, CXCR4 and SORT1) and one transcription factor PRDM1. This study identified dysregulated immune cell clusters, signaling pathways, and potential therapeutic targets in AIH.

Background Insulin resistance (IR) is associated with coronary artery disease (CAD) severity. However, its underlying mechanisms are not fully understood. Therefore, our study aimed to explore the relationship between IR and coronary inflammation and investigate the synergistic and mediating effects of coronary inflammation on the association between IR and CAD severity. Methods Consecutive patients with CAD who underwent coronary angiography and coronary computed tomography angiography between April 2018 and March 2023 were enrolled. The triglyceride–glucose index (TyG index) and peri-coronary adipose tissue (PCAT) attenuation around the proximal right coronary artery (RCA) were used to evaluate IR and coronary inflammation, respectively. The correlation between the TyG index and PCAT attenuation was analyzed using linear regression models. Logistic regression models were further used for investigating the correlation of the TyG index and PCAT attenuation with CAD severity. A mediation analysis assessed the correlation between IR and CAD severity mediated by coronary inflammation. Results A total of 569 participants (mean age, 62 ± 11 years; 67.8% men) were included in the study. PCAT attenuation was positively associated with the TyG index ( r  = 0.166; P  < 0.001). After adjusting for potential confounders, the per standard deviation increment in the TyG index was associated with a 1.791 Hounsfield unit (HU) increase (95% confidence interval [CI], 0.920–2.662 HU; P  < 0.001) in the PCAT attenuation. In total, 382 (67.1%) patients had multivessel CAD. The patients in the high-TyG index/high PCAT attenuation group had approximately 3.2 times the odds of multivessel CAD compared with those in the low-TyG index/low PCAT attenuation group (odds ratio, 3.199; 95%CI, 1.826–5.607; P  < 0.001). Mediation analysis indicated that PCAT attenuation mediated 31.66% of the correlation between the TyG index and multivessel CAD. Conclusions The TyG index positively correlated with PCAT attenuation in patients with CAD. The TyG index and PCAT attenuation showed a synergistic correlation with multivessel CAD. Furthermore, PCAT attenuation partially mediated the relationship between the TyG index and CAD severity. Controlling inflammation in patients with high IR and coronary inflammation may provide additional benefits.

Pain management is currently important in neonatal intensive care unit (NICU). The superiority in pain relief of the combined oral sucrose (OS) and nonnutritive sucking (NNS) to other single intervention has not been well established. The administration of sucrose has been considered to potentially induce adverse events, which has been controversial. This study aims to investigate the combined effects and safety in comparison with other single intervention methods, including NNS, OS alone, breast milk and oral glucose. We searched databases including Medline (via Pubmed), Embase (via Ovid), web of science, and Cochrane Library for randomized controlled trials from Jan 1, 2000 to Mar 31, 2021. The data were analyzed in the meta-analysis using Review manager Version 5.3. Pain score was the primary outcome in this meta-analysis. The adverse events were assessed qualitatively. A total of 16 studies were eligible in the meta-analysis. The results demonstrated a significant reduction in pain score in the NNS+OS group compared with NNS alone (SMD = -1.69, 95%CI, -1.69,-0.65) or sucrose alone (SMD = -1.39, 95% CI, -2.21,-0.57) during the painful procedures. When compared NNS+OS with breast milk, no significant difference was detected (SMD = -0.19, 95% CI: -0.5, 0.11). The combined effects of NNS and OS might be superior to other single intervention method. However, the effects might be mild for moderate-to-severe pain.

Physical unclonable functions (PUFs) are of immense potential in authentication scenarios for Internet of Things (IoT) devices. For creditable and lightweight PUF applications, key attributes, including low power, high reconfigurability and large challenge-response pair (CRP) space, are desirable. Here, we report a ferroelectric field-effect transistor (FeFET)-based strong PUF with high reconfigurability and low power, which leverages the FeFET cycle-to-cycle variation throughout the workflow and introduces charge-domain in-memory computing. The proposed PUF cells are fabricated at 28 nm node, and the experimental measurements reveal high uniformity, uniqueness and repeatability. Remarkably, our PUF achieves near-ideal reconfigurability and ultra-low 1.89fJ per bit readout energy, significantly outperforming the state-of-the-art PUFs. Furthermore, we show that the PUF is robust against parameter variations and resilient to machine learning (ML) attacks. These performances highlight the great promise of the FeFET-based strong PUF as a feasible IoT security solution. Physical unclonable functions (PUFs) are important in authentication applications for Internet of Things devices. This work reports a ferroelectric field-effect transistor-based strong PUF utilizing the transistor cycle-to-cycle variation and verifies its feasibility using 28 nm HKMG technology.

Misinformation is a pervasive problem in the social media era, undermining social trust, while the emergence of AI-generated misinformation further exacerbates this issue and threatens social order. This study employs the third-person effect as a theoretical framework and collected 726 questionnaire responses to examine individuals’ perceptions of AI-generated misinformation. When exploring the relationships among misinformation exposure, social undesirability, perceived realism, and AI literacy with respect to perceived effects on oneself and on others, individuals recognize that they themselves are also easily influenced by AI-generated misinformation. Furthermore, perceived effects on oneself and others are positively correlated with corrective actions, while no significant relationship is observed with restrictive actions, thus providing suggestions for individual involvement in combating AI-generated misinformation.

In this paper, the multi-objective optimization of the 12-pole radial active magnetic bearing (RAMB) is investigated. In the optimization of the RAMB, the decision-maker is more interested in the Pareto-optimal solutions in a certain region. This paper proposes a decomposition-based and preference-based multi-objective evolutionary algorithm (MOEA/D-Pref). The proposed MOEA/D-Pref not only allows the number of Pareto-optimal solutions to be more concentrated in the region of interest but also preserves solutions in other regions. These preserved solutions enable decision-makers to observe a more complete Pareto front, thus gaining more comprehensive insights. In this paper, a mathematical model of the 12-pole RAMB is established, and, with the help of this model and the proposed algorithm, the optimal design of the 12-pole RAMB is completed. The difference between the current stiffness coefficients of the optimized RAMB, calculated by the proposed algorithm and by the finite element method, is 2.3%. The difference between the displacement stiffness coefficient of the optimized RAMB as calculated by the proposed algorithm and by the finite element method is 3.9%. These differences, being less than 4%, are relatively low and verify the reliability of the mathematical model established.

Currently, it is still a challenge to detect single-trial P300 from electroencephalography (EEG) signals. In this paper, to address the typical problems faced by existing single-trial P300 classification, such as complex, time-consuming and low accuracy processes, a single-trial P300 classification algorithm based on multiplayer data fusion convolutional neural network (CNN) is proposed to construct a centralized collaborative brain-computer interfaces (cBCI) for fast and highly accurate classification of P300 EEG signals. In this paper, two multi-person data fusion methods (parallel data fusion and serial data fusion) are used in the data pre-processing stage to fuse multi-person EEG information stimulated by the same task instructions, and then the fused data is fed as input to the CNN for classification. In building the CNN network for single-trial P300 classification, the Conv layer was first used to extract the features of single-trial P300, and then the Maxpooling layer was used to connect the Flatten layer for secondary feature extraction and dimensionality reduction, thereby simplifying the computation. Finally batch normalisation is used to train small batches of data in order to better generalize the network and speed up single-trial P300 signal classification. In this paper, the above new algorithms were tested on the Kaggle dataset and the Brain-Computer Interface (BCI) Competition III dataset, and by analyzing the P300 waveform features and EEG topography and the four standard evaluation metrics, namely Accuracy, Precision, Recall and F1-score,it was demonstrated that the single-trial P300 classification algorithm after two multi-person data fusion CNNs significantly outperformed other classification algorithms. The results show that the single-trial P300 classification algorithm after two multi-person data fusion CNNs significantly outperformed the single-person model, and that the single-trial P300 classification algorithm with two multi-person data fusion CNNs involves smaller models, fewer training parameters, higher classification accuracy and improves the overall P300-cBCI classification rate and actual performance more effectively with a small amount of sample information compared to other algorithms.

Non-volatile content addressable memories (NV-CAMs) accelerate memory augmented neural networks (MANNs) for brain-like efficient learning from a few examples or even one example. However, most existing NV-CAMs operate in current domain, posing challenges in reliable, low-power, and sensing-friendly Hamming distance (HD) computation. To address these challenges, this work proposes transferring the computation to charge domain using ferroelectric capacitive memory (FCM). For the first time, a charge-domain 2FCM CAM based on the inversion-type FCM is reported. By storing data as device capacitance, this CAM structure directly outputs HD as linear multi-level voltages, enabling simplified sensing processes and reduced peripheral costs. Its differential nature further exhibits immunity to device variation, ensuring accuracy in the computation of long data vectors. Parallel 16-bit HD computation using a fabricated 16 × 16 2FCM CAM array is experimentally demonstrated with record performance at array level, evidencing the superiority of charge-domain computation and showcasing tremendous potential for in-memory-search applications. Non-volatile content addressable memories are widely applied to accelerate memory-augmented neural networks, yet the existing current-domain data search operation faces challenges. Zhou et al. show charge-domain operation utilizing ferroelectric capacitive memory to lower peripheral sensing overhead.

Background Thyroid nodules have attracted much attention due to their high incidence and potential for malignant transformation. Compared with the clinical assessment and diagnosis of thyroid nodules, there are relatively few studies on the epidemiological risk factors for thyroid nodules. The aim of this study was to investigate the prevalence of thyroid nodule among adults in Zhejiang province and to explore their relationship with physiological and psychosocial factors. Methods The data used in this study were obtained from the baseline survey of the Zhejiang Provincial Cohort Study on Environment and Health. From June 2022 to December 2023, a total of 21,712 participants from five representative cities in Zhejiang were recruited for the baseline survey. Based on the inclusion and exclusion criteria, 15,595 adults were included in the analysis. The data were collected via self-report questionnaires and physical examinations. Multivariate logistic regression analysis was subsequently performed. Results The detection rate of thyroid nodules was 50.98% among adults in Zhejiang province. Age, gender, education level, BMI, tea and alcohol consumption all had a statistically significant association with thyroid nodules ( p  < 0.05). After adjusting for sociodemographic factors, results of logistic regression analysis showed that good life satisfaction (OR = 0.854, 95% CI: 0.780–0.934) had a lower risk of thyroid nodules, however, poor life satisfaction (OR = 1.406, 95% CI: 1.014–1.951), social isolation (OR = 1.294, 95% CI: 1.089–1.538) and a family history of thyroid nodules (OR = 1.334, 95% CI: 1.064–1.672) had a greater risk of thyroid nodules. Conclusion The detection rate of thyroid nodules in adults of Zhejiang province was an increasing trend compared with that in previous years. In addition to the sensitive thyroid nodule screening technology, influencing factors mentioned in this study might also represent credible candidates for this increase. As variable influence factors, weight management, good interpersonal relationships and life satisfaction should be the focus of health interventions.