Explore the vast range of titles available.

Multistage incremental sheet metal forming (MS-ISF) is used to produce sheet metal parts with a large forming angle. Similar to the forming limit diagram (FLD) in stamping, FLD in MS-ISF is not sufficiently reliable due to the effect of loading path. To solve this problem, a method to calculate the forming limit stress diagram (FLSD) from FLD was proposed. Experiments proved that FLSD is a reliable fracture indicator that is unaffected by the loading path in MS-ISF.

This investigation aims to propose a novel framework for designing and manufacturing cranial prostheses through incremental sheet metal forming (ISF). First, the three-dimensional models of the defective crania and the prosthesis were constructed from the CT data. Then, to verify the formability of the prosthesis model, a method for testing the mesh sheet’s incremental forming limit (IFL) was proposed with a variable angle cone model. The angle between the normal vector of the fracture point and the Z-axis calculated the IFL. The tests showed that the method could realize the testing of the IFL of the mesh sheet with the reduction of processing time and cost. In addition, finite element modeling and experimental trials were used to evaluate the ISF process of the prosthesis, including thickness distribution and geometric accuracy. The results showed that the incremental forming can form prosthesis samples with high precision, while the thickness distribution is relatively uniform without excessive thinning. Finally, the obtained prosthesis sample was practically assembled with the cranial defect model to verify the fitting effect and feasibility of the prosthesis formed by the ISF process.

Multi-stage incremental sheet metal forming (MS-ISF) is a good solution to overcome the maximum forming angle of single-stage incremental sheet metal forming. In order to test the formability of MS-ISF, a novel method to get forming limit diagram (FLD) of MS-ISF was proposed based on changing forming strategies. Aluminum alloy AA1060-O sheet was employed to prove the feasibility of the method. Test results show that the method can provide FLD of MS-ISF which is affected by loading path.

The emergence of models like GPTs, Claude, LLaMA, and Qwen has reshaped AI applications, presenting vast new opportunities across industries. Yet, the integration of tabular data remains notably underdeveloped, despite its foundational role in numerous real-world domains. This gap is critical for three main reasons. First, database or data warehouse data integration is essential for advanced applications; second, the vast and largely untapped resource of tabular data offers immense potential for analysis; and third, the business intelligence domain specifically demands adaptable, precise solutions that many current LLMs may struggle to provide. In response, we introduce TableGPT2, a model rigorously pre-trained and fine-tuned with over 593.8K tables and 2.36M high-quality query-table-output tuples, a scale of table-related data unprecedented in prior research. This extensive training enables TableGPT2 to excel in table-centric tasks while maintaining strong general language and coding abilities. One of TableGPT2's key innovations is its novel table encoder, specifically designed to capture schema-level and cell-level information. This encoder strengthens the model's ability to handle ambiguous queries, missing column names, and irregular tables commonly encountered in real-world applications. Similar to visual language models, this pioneering approach integrates with the decoder to form a robust large multimodal model. We believe the results are compelling: over 23 benchmarking metrics, TableGPT2 achieves an average performance improvement of 35.20% in the 7B model and 49.32% in the 72B model over prior benchmark-neutral LLMs, with robust general-purpose capabilities intact.

Lactic acid was formerly regarded as a byproduct of metabolism. However, extensive investigations into the intricacies of cancer development have revealed its significant contributions to tumor growth, migration, and invasion. Post-translational modifications involving lactate have been widely observed in histone and non-histone proteins, and these modifications play a crucial role in regulating gene expression by covalently attaching lactoyl groups to lysine residues in proteins. This discovery has greatly enhanced our comprehension of lactic acid’s involvement in disease pathogenesis. In this article, we provide a comprehensive review of the intricate relationship between lactate and tumor immunity, the occurrence of lactylation in malignant tumors, and the exploitation of targeted lactate-lactylation in tumor immunotherapy. Additionally, we discuss future research directions, aiming to offer novel insights that could inform the investigation, diagnosis, and treatment of related diseases.

The recently discovered neutron star transient Swift J0243.6+6124 has been monitored by {\\it the Hard X-ray Modulation Telescope} ({\\it Insight-\\rm HXMT). Based on the obtained data, we investigate the broadband spectrum of the source throughout the outburst. We estimate the broadband flux of the source and search for possible cyclotron line in the broadband spectrum. No evidence of line-like features is, however, found up to \\(\\rm 150~keV\\). In the absence of any cyclotron line in its energy spectrum, we estimate the magnetic field of the source based on the observed spin evolution of the neutron star by applying two accretion torque models. In both cases, we get consistent results with \\(B\\rm \\sim 10^{13}~G\\), \\(D\\rm \\sim 6~kpc\\) and peak luminosity of \\(\\rm >10^{39}~erg~s^{-1}\\) which makes the source the first Galactic ultraluminous X-ray source hosting a neutron star.