Microwave assistant synthesis of trans-4-nitrostilbene derivatives in solvent free condition

A general method for the synthesis of trans-4-nitrostilbenes has been developed. The trans-4-nitrostilbene could be synthesized in good yields under microwave irradiation within 10 min through Perkin reaction by using 4-nitrophenylacetic acid, benzaldehydes and pyrrolidine

Light induced non-volatile switching of superconductivity in single layer FeSe on SrTiO3 substrate

The capability of controlling superconductivity by light is highly desirable for active quantum device applications. Since superconductors rarely exhibit strong photoresponses, and optically sensitive materials are often not superconducting, efficient coupling between these two characters can be very challenging in a single material. Here we show that, in FeSe/SrTiO3 heterostructures, the superconducting transition temperature in FeSe monolayer can be effectively raised by the interband photoexcitations in the SrTiO3substrate. Attributed to a light induced metastable polar distortion uniquely enabled by the FeSe/SrTiO3 interface, this effect only requires a less than 50 µW cm−2 continuous-wave light field. The fast optical generation of superconducting zero resistance state is non-volatile but can be rapidly reversed by applying voltage pulses to the back of SrTiO3substrate. The capability of switching FeSe repeatedly and reliably between normal and superconducting states demonstrate the great potential of making energy-efficient quantum optoelectronics at designed correlated interfaces

Study of the features of coronary artery atheromatous plaque using intravascular ultrasound in patients with impaired glucose tolerance

AbstractObjectiveWe used intravascular ultrasound (IVUS) to analyze the features of coronary artery atheromatous plaque in patients with impaired glucose tolerance and mild-to-moderate angiographic coronary stenosis. The aim was to determine the clinical significance of plaque characteristics as well as the relationship between hemoglobin A1c (HbA1c) levels and coronary artery lesions.MethodsHbA1c levels were evaluated in 85 patients (96 lesions), of whom 46 had impaired glucose tolerance (IGT Group) and 39 had normal blood glucose (NBG Group). IVUS was used to analyze the lesion vessel of both groups qualitatively and quantitatively. The external elastic membrane area (EEMA), minimal lumen area (MLA), plaque area (PA), and plaque burden (PB) were measured for both the target lesion and the reference segments (reference external elastic membrane area (REEMA), reference minimal lumen area (RMLA), reference plaque area (RPA), and reference plaque burden (RPB), respectively).ResultsHbA1c levels were significantly higher in the IGT Group than in the NBG Group (P < 0.05). In the IGT Group there was more soft plaque, eccentric plaque, and positive remodeling, and less calcification, while in the NBG Group there was much harder plaque and calcification, no reconstruction, and negative remodeling (P < 0.05). MLA was smaller in the IGT Group than in the NBG Group, while EEMA, PA, and PB were clearly greater (P < 0.05). In the meantime, RMLA was clearly smaller in the IGT Group than in the NBG Group, while RPA and RPB were greater (P < 0.05). HbA1c levels were positively correlated with PA and PB, and negatively correlated with MLA.ConclusionIVUS is very valuable for the evaluation of mild-to-moderate coronary lesions. The coronary artery lesions in patients with IGT are more serious and widespread than those in patients with NBG. HbA1c levels might be of some value in assessing the severity of coronary artery lesions

You Can Backdoor Personalized Federated Learning

Existing research primarily focuses on backdoor attacks and defenses within the generic federated learning scenario, where all clients collaborate to train a single global model. A recent study conducted by Qin et al. (2023) marks the initial exploration of backdoor attacks within the personalized federated learning (pFL) scenario, where each client constructs a personalized model based on its local data. Notably, the study demonstrates that pFL methods with \textit{parameter decoupling} can significantly enhance robustness against backdoor attacks. However, in this paper, we whistleblow that pFL methods with parameter decoupling are still vulnerable to backdoor attacks. The resistance of pFL methods with parameter decoupling is attributed to the heterogeneous classifiers between malicious clients and benign counterparts. We analyze two direct causes of the heterogeneous classifiers: (1) data heterogeneity inherently exists among clients and (2) poisoning by malicious clients further exacerbates the data heterogeneity. To address these issues, we propose a two-pronged attack method, BapFL, which comprises two simple yet effective strategies: (1) poisoning only the feature encoder while keeping the classifier fixed and (2) diversifying the classifier through noise introduction to simulate that of the benign clients. Extensive experiments on three benchmark datasets under varying conditions demonstrate the effectiveness of our proposed attack. Additionally, we evaluate the effectiveness of six widely used defense methods and find that BapFL still poses a significant threat even in the presence of the best defense, Multi-Krum. We hope to inspire further research on attack and defense strategies in pFL scenarios. The code is available at: https://github.com/BapFL/code.Comment: Submitted to TKD

Several Treatments on Nonconforming Element Failed in the Strict Patch Test

For nonconforming finite elements, it has been proved that the models whose convergence is controlled only by the weak form of patch tests will exhibit much better performance in complicated stress states than those which can pass the strict patch tests. However, just because the former cannot provide the exact solutions for the patch tests of constant stress states with a very coarse mesh (strict patch test), their usability is doubted by many researchers. In this paper, the non-conforming plane 4-node membrane element AGQ6-I, which was formulated by the quadrilateral area coordinate method and cannot pass the strict patch tests, was modified by three different techniques, including the special numerical integration scheme, the constant stress multiplier method, and the orthogonal condition of energy. Three resulting new elements, denoted by AGQ6M-I, AGQ6M-II, and AGQ6M, can pass the strict patch test. And among them, element AGQ6M is the best one. The original model AGQ6-I and the new model AGQ6M can be treated as the replacements of the well-known models Q6 and QM6, respectively

Protective effect of Acorus tatarinowii extract against alzheimer in 3xTg-AD mice

Purpose: To investigate the protective effect of Acorus tatarinowii extract (ATE) against Alzheimer's disease in 3xTg-AD mice. Method: The cognitive function of 3xTg-AD mice was assessed using Morris water maze test. The levels of the amyloid beta deposits and NeuN in the hippocampus were evaluated by immunohistochemical assay while brain neurotrophic derived factor (BDNF) and tyrosine kinase B (TrkB) expressions were determined by western blot analysis. Results: ATE treatment significantly ameliorated learning and memory deficits in AD mice, as shown by increased time spent in the target zone during probe tests. The escape latency in animals treated with 600 mg/kg ATE (24.8 ± 1.3 s) was significantly increased relative to ontreated 3xTg-AD mice (8.5 ± 1.0 s, p &lt; 0.01). In addition, ATE significantly decreased Aβ deposits, increased NeuN-positive cells, and upregulated the expression of BDNF (1.9 ± 0.4, p &lt; 0.05) and TrkB (1.9 ± 0.2, p &lt; 0.05) in 3xTg AD mice. Conclusion: These results suggest that ATE treatment may be a useful strategy for managing memory impairment induced by several neurodegenerative diseases

TransPrompt v2: A Transferable Prompting Framework for Cross-task Text Classification

Text classification is one of the most imperative tasks in natural language processing (NLP). Recent advances with pre-trained language models (PLMs) have shown remarkable success on this task. However, the satisfying results obtained by PLMs heavily depend on the large amounts of task-specific labeled data, which may not be feasible in many application scenarios due to data access and privacy constraints. The recently-proposed prompt-based fine-tuning paradigm improves the performance of PLMs for few-shot text classification with task-specific templates. Yet, it is unclear how the prompting knowledge can be transferred across tasks, for the purpose of mutual reinforcement. We propose TransPrompt v2, a novel transferable prompting framework for few-shot learning across similar or distant text classification tasks. For learning across similar tasks, we employ a multi-task meta-knowledge acquisition (MMA) procedure to train a meta-learner that captures the cross-task transferable knowledge. For learning across distant tasks, we further inject the task type descriptions into the prompt, and capture the intra-type and inter-type prompt embeddings among multiple distant tasks. Additionally, two de-biasing techniques are further designed to make the trained meta-learner more task-agnostic and unbiased towards any tasks. After that, the meta-learner can be adapted to each specific task with better parameters initialization. Extensive experiments show that TransPrompt v2 outperforms single-task and cross-task strong baselines over multiple NLP tasks and datasets. We further show that the meta-learner can effectively improve the performance of PLMs on previously unseen tasks. In addition, TransPrompt v2 also outperforms strong fine-tuning baselines when learning with full training sets

Shape-Free Finite Element Method: Another Way between Mesh and Mesh-Free Methods

Performances of the conventional finite elements are closely related to the mesh quality. Once distorted elements are used, the accuracy of the numerical results may be very poor, or even the calculations have to stop due to various numerical problems. Recently, the author and his colleagues developed two kinds of finite element methods, named hybrid stress-function (HSF) and improved unsymmetric methods, respectively. The resulting plane element models possess excellent precision in both regular and severely distorted meshes and even perform very well under the situations in which other elements cannot work. So, they are called shape-free finite elements since their performances are independent to element shapes. These methods may open new ways for developing novel high-performance finite elements. Here, the thoughts, theories, and formulae of above shape-free finite element methods were introduced, and the possibilities and difficulties for further developments were also discussed