Alejandro Lozano

Red teaming, the practice of adversarially exposing unexpected or undesired model behaviors, is critical towards improving equity and accuracy of large language models, but non-model creator-affiliated red teaming is scant in healthcare. We convened teams of clinicians, medical and engineering students, and technical professionals (80 participants total) to stress-test models with real-world clinical cases and categorize inappropriate responses along axes of safety, privacy, hallucinations/accuracy, and bias. Six medically-trained reviewers re-analyzed prompt-response pairs and added qualitative annotations. Of 376 unique prompts (1504 responses), 20.1% were inappropriate (GPT-3.5: 25.8%; GPT-4.0: 16%; GPT-4.0 with Internet: 17.8%). Subsequently, we show the utility of our benchmark by testing GPT-4o, a model released after our event (20.4% inappropriate). 21.5% of responses appropriate with GPT-3.5 were inappropriate in updated models. We share insights for constructing red teaming prompts, and present our benchmark for iterative model assessments.

The formose reaction (FR) autocatalytically converts simple plausibly prebiotic feedstocks into molecules of biological interest, including ribose. Autocatalysis is a hallmark of life, thus various studies have explored the formose reaction with respect to the origins of life. The FR is robust under appropriate conditions, occurring readily at low temperatures from various substrates, and has been implicated in the generation of meteoritic organic compounds. We explored the FR here using a combination of in silico modeling techniques and high resolution mass spectrometry. The models match experimental results well, and point to the FR being much more complex than previously modeled or measured, and help explain the FR’s potential to generate homochirality and primitive compartments, both of which are also hallmarks of life, before the emergence of the complex directed molecular encoding suggested by the RNA World model. These results suggest the FR requires further study with regard to the origins of life, and its importance may lie in the way it enables and coordinates emergent chemistries, rather than the particular products it generates, such as ribose.

This work proposes a robust sliding mode controller to enforce the tracking trajectory of a cervical orthotic device subjected to asymmetric box constraints. The convergence analysis employs an asymmetric barrier Lyapunov function (ABLF), whose argument is a restricted sliding surface. The stability analysis demonstrates the finite-time convergence of the states towards the sliding surface and, therefore, the exponential stability of the system trajectories. The controller ensures the fulfillment of the restrictions imposed on the sliding surface and consequently over the states. Numerical simulations exhibit the performance of the proposed controller ensuring restricted movements for flexion and extension of a virtual orthotic cervical device. The restricted movements obey asymmetric constraints according to the therapies proposed by medical specialists.

This work deals with the design of a millimetric electrospinning device (MED) controlled with the implemen-tation of a sliding mode controller taking into account states constraints or constraint sliding mode controller (CSM C). The proposed MED is integrated by two cartesian robots with two (injector system) and three (collector system) degrees of freedom, respectively. These two cartesian robots work in a coordinated manner to regulate the deposition processes for the generation of polymeric micro and nanofibers. This strategy addresses one of the most common problems of classic MEDs, guaranteeing that the fibers are deposited in a specific zone (aiming to create 3D polymeric structures). The suggested CSM C successfully restricts the motions of the MED to a predefined working space that led to the production of aligned polymer fibers, ensuring the convergence of the tracking error to the sliding surface in finite-time, while the state constraints are satisfied. Experimental results validate the effectiveness of the proposed CSMC by using the least mean square evaluation of the tracking error and the integral of the control signal. The evaluation is also done following a comparative analysis concerning the performance forced with respect to a state feedback form. The evaluation confirmed the effectiveness of the CDMC strategy compared to the state feedback form.