Inversions of interseismic geodetic surface velocities often cannot uniquely resolve the three-dimensional slip-rate distribution along closely spaced faults. Microseismic focal mechanisms reveal stress information at depth and may provide additional constraints for inversions that estimate slip rates. Here, we present a new inverse approach that utilizes both surface velocities and subsurface stressing-rate tensors to constrain interseismic slip rates and activity of closely spaced faults. We assess the ability of the inverse approach to recover slip rate distributions from stressing-rate tensors and surface velocities generated by two forward models: 1) a single strike-slip fault model and 2) a complex southern San Andreas fault system (SAFS) model. The single fault model inversions reveal that a sparse array of regularly spaced stressing-rate tensors can recover the forward model slip distribution better than surface velocity inversions alone. Because focal mechanism inversions currently provide normalized deviatoric stress tensors, we perform inversions for slip rate using full, deviatoric or normalized deviatoric forward-model-generated stressing-rate tensors to assess the impact of removing stress magnitude from the constraining data. All the inversions, except for those that use normalized deviatoric stressing-rate tensors, recover the forward model slip-rate distribution well, even for the SAFS model. Jointly inverting stressing rate and velocity data best recovers the forward model slip-rate distribution and may improve estimates of interseismic deep slip rates in regions of complex faulting, such as the southern SAFS; however, successful inversions of crustal data will require methods to estimate stressing-rate magnitudes.

Whether your scientific presentation is in-person or remote, everyone will understand more of your presentation if it has captions. Like subtitles of a movie, open captioning makes verbal material accessible for many people. A study of BBC television watchers reports that 80% of 15 caption users are not deaf nor hard of hearing (1). During English-spoken scientific presentations, people who are deaf or hard of hearing, people who have auditory processing disorder and not yet fluent non-native English speakers develop listening fatigue that can prohibit their understanding and limit their participation in discussions. Increasing the accessibility of our presentations and improving inclusivity of discussions provides a path 20 towards increasing diversity within sciences. Studies show that subtitles/captioning improve both English language skills (e.g., 2, 3) and accessibility of science for deaf and hard of hearing participants (e.g., 3, 4). Furthermore, not everyone may be in a space where they can access audio, for example, if they are sharing space with other workers. A myriad of tools and platforms can provide captioning for live presentations. Why then don’t 25 we regularly caption presentations? Our resistance may be due to factors such as not knowing or believing that captioning is needed, not knowing how to use these tools, and believing that the resulting captioning will be inadequate. In response to the first reason, folks should not be forced to disclose their disability in order for presentations to be accessible to them. In response to the last two reasons, this article outlines different strategies for providing captions and presents 30 results of our performance assessment of Artificial Intelligence (AI) based auto-caption of jargon rich geologic passages. Because most scientific presentations are delivered using either Microsoft PowerPoint or Google Slides presentation software, we focus our performance assessment on the auto-captioning provided by these platforms. While a variety of tools can add captions to recorded lectures that can be edited to improve accuracy, offering a transcript after a 35 live presentation is not a suitable solution to improve participation. Here we provide evidence-based best-practices for providing captioning that will increase the accessibility of live scientific presentations In-Person Presentations For in-person presentations, trained human captionists or AI-based auto caption/transcription 40 software can provide live captioning (Fig. 1). Captionists use stenography tools to provide

While about 17% of the adult population have significant hearing loss, we remain under-represented within academia outside of the field of Deaf Studies. One primary contributor to the leaky pipeline is lack of mentorship due to the difficulty of deaf and hard of hearing academics in recognizing one another. Hearing loss among non-signers is seldom obvious. Consequently, non-signing deaf and hard of hearing academics at predominantly hearing institutions often remain isolated without guidance on how to manage the myriad of communication challenges facing academics, such as teaching, leading group meetings, addressing questions at conferences, participating in discussions at professional meetings, and serving on grant proposal panels. Adequate solutions are often not available from our hearing health care providers nor from disability services offices, which are mandated and designed to serve undergraduate students. However, the success of all academics depends on mastering these different communication challenges. To fill the mentoring gap, we have started a blog by and for academics at all career stages with some degree of hearing loss called, “The Mind Hears”. This title derives from the Victor Hugo quote “What matters deafness of the ear when the mind hears, the one true deafness, the incurability deafness is that of the mind.” The goals of the blog are: To provide a forum for crowd-sourcing ways to minimize our challenges and share strategies for thriving in academia with hearing loss. To foster a network of deaf and hard of hearing academics who promote hearing inclusive strategies at universities. Through this blog we hope to reach deaf and hard of hearing academics all around the world, and thus reduce isolation in our community and build a community toolbox of resources and ideas. Hearing loss is variable and can affect us in many and different ways – but through this shared blog we hope to provide something of value to all of those who visit and contribute to our discussions.

Crustal deformation occurs both as localized slip along faults and distributed deformation off faults; however, we have few robust estimates of off-fault deformation. Scaled physical experiments simulate crustal strike-slip faulting and allow direct measurement of fault slip to regional deformation, quantified as Kinematic Efficiency (KE). We offer an approach for KE prediction using a 2D Convolutional Neural Network (CNN) trained directly on images of fault maps produced by physical experiments. A suite of experiments with different loading rate and basal boundary conditions, contribute over 13,000 fault maps throughout strike-slip fault evolution. Strain maps allow us to directly calculate KE and its uncertainty, utilized in the loss function and performance metric. The trained CNN achieves 91% accuracy in KE prediction of an unseen dataset. The application of the CNN trained on scaled experiments to crustal fault maps provides estimates of off-fault deformation that overlap available geologic estimates.