Design and analysis of a novel long-distance double tendon-sheath transmission device for breast intervention robots under MRI field

Cancer represents a major threat to human health. Magnetic resonance imaging (MRI) provides superior performance to other imaging-based examination methods in the detection of tumors and offers distinct advantages in biopsy and seed implantation. However, because of the MRI environment, the material requirements for actuating devices for the medical robots used in MRI are incredibly demanding. This paper describes a novel double tendon-sheath transmission device for use in MRI applications. LeBus grooves are used in the original transmission wheels, thus enabling the system to realize long-distance and large-stroke transmission with improved accuracy. The friction model of the transmission system and the transmission characteristics model of the novel tendon-sheath structure are then established. To address the problem that tension sensors cannot be installed in large-stroke transmission systems, a three-point force measurement method is used to measure and set an appropriate preload in the novel tendon-sheath transmission system. Additionally, experiments are conducted to verify the accuracy of the theoretical model and multiple groups of tests are performed to explore the transmission characteristics. Finally, the novel tendon-sheath transmission system is compensated to improve its accuracy and the experimental results acquired after compensation show that the system satisfies the design requirements

An information diffusion model in social networks with carrier compartment and delay

With the wide applications of the communication networks, the topic of information networks security is getting more and more attention from governments and individuals. This paper is devoted to investigating a malware propagation model with carrier compartment and delay to describe the process of malware propagation in mobile wireless sensor networks. Based on matrix theory for characteristic values, the local stability criterion of equilibrium points is established. Applying the linear approximation method of nonlinear systems, we study the existence of Hopf bifurcation at the equilibrium points. At the same time, we identify some sensitive parameters in the process of malware propagation. Finally, numerical simulations are performed to illustrate the theoretical results

Thoughts and countermeasures of establishing national modern agricultural demonstration zone —— Take Shijiazhuang City, Hebei Province as an example

Modern agricultural demonstration area is of far-reaching significance to promote the development of modern agriculture. According to the current situation of agricultural industry development in Shijiazhuang, this paper analyzes the development conditions of establishing a national modern agricultural demonstration zone, puts forward the basic ideas, development orientation and development countermeasures of building a national modern agricultural demonstration zone, and analyzes the guarantee measures for its development, in order to build Shijiazhuang into a national modern agricultural demonstration zone

Mitigating Shortcuts in Language Models with Soft Label Encoding

Recent research has shown that large language models rely on spurious correlations in the data for natural language understanding (NLU) tasks. In this work, we aim to answer the following research question: Can we reduce spurious correlations by modifying the ground truth labels of the training data? Specifically, we propose a simple yet effective debiasing framework, named Soft Label Encoding (SoftLE). We first train a teacher model with hard labels to determine each sample's degree of relying on shortcuts. We then add one dummy class to encode the shortcut degree, which is used to smooth other dimensions in the ground truth label to generate soft labels. This new ground truth label is used to train a more robust student model. Extensive experiments on two NLU benchmark tasks demonstrate that SoftLE significantly improves out-of-distribution generalization while maintaining satisfactory in-distribution accuracy

Persistent fifth aortic arch: a comprehensive literature review

Persistent fifth aortic arch (PFAA) is an extremely rare congenital cardiovascular anomaly resulting from the failure of the fifth aortic arch to degenerate during embryonic development; it is often associated with various other cardiovascular anomalies. Despite being first reported by Van Praagh in 1969, there have been only a few individual case reports. Owing to its rarity and lack of comprehensive understanding, PFAA is often misdiagnosed or missed diagnosed during clinical. Thus, this review aimed to summarise the embryonic development, pathological classification, imaging diagnosis, and clinical treatment of PFAA to improve its overall understanding, ultimately helping in accurate diagnosis and treatment

Explainability for Large Language Models: A Survey

Large language models (LLMs) have demonstrated impressive capabilities in natural language processing. However, their internal mechanisms are still unclear and this lack of transparency poses unwanted risks for downstream applications. Therefore, understanding and explaining these models is crucial for elucidating their behaviors, limitations, and social impacts. In this paper, we introduce a taxonomy of explainability techniques and provide a structured overview of methods for explaining Transformer-based language models. We categorize techniques based on the training paradigms of LLMs: traditional fine-tuning-based paradigm and prompting-based paradigm. For each paradigm, we summarize the goals and dominant approaches for generating local explanations of individual predictions and global explanations of overall model knowledge. We also discuss metrics for evaluating generated explanations, and discuss how explanations can be leveraged to debug models and improve performance. Lastly, we examine key challenges and emerging opportunities for explanation techniques in the era of LLMs in comparison to conventional machine learning models

Atomistic Conversion Reaction Mechanism of WO3 in Secondary Ion Batteries of Li, Na, and Ca

Intercalation and conversion are two fundamental chemical processes for battery materials in response to ion insertion. The interplay between these two chemical processes has never been directly seen and understood at atomic scale. Here, using in situ HRTEM, we captured the atomistic conversion reaction processes during Li, Na, Ca insertion into a WO3 single crystal model electrode. An intercalation step prior to conversion is explicitly revealed at atomic scale for the first time for Li, Na, Ca. Nanoscale diffraction and ab initio molecular dynamic simulations revealed that after intercalation, the inserted ion–oxygen bond formation destabilizes the transition‐metal framework which gradually shrinks, distorts and finally collapses to an amorphous W and MxO (M=Li, Na, Ca) composite structure. This study provides a full atomistic picture of the transition from intercalation to conversion, which is of essential importance for both secondary ion batteries and electrochromic devices.Das Wechselspiel zwischen Ioneninterkalation und Umwandlung des WO3‐Elektrodenmaterials wurde durch In‐situ‐TEM auf atomarer Ebene untersucht. Die Bildung von Ion‐Sauerstoff‐Bindungen destabilisiert das WO3‐Gerüst: Es schrumpft, wird verzerrt und fällt schließlich zu einer amorphen W‐ und MxO‐Verbundstruktur (M=Li, Na, Ca) zusammen.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134843/1/ange201601542_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134843/2/ange201601542.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134843/3/ange201601542-sup-0001-misc_information.pd