Faculty Publications

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https://hdl.handle.net/1911/75173

This collection includes faculty journal articles deposited per Rice's Open Access Policy and additional faculty work. Items found in this collection can also be found in the authors' departmental faculty publication collections.

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Giedion in America
(gta Verlag, 2024) Geiser, Reto
Sigfried Giedion (1888–1968), one of the main protagonists of the architectural avant-garde in Europe, paradoxically achieved this reputation in America, far from his homeland. Nearly all of Giedion’s books written after his initial stay at Harvard University were published in English long before they became available in his native German. Reto Geiser sheds new light on Giedion’s life and reassesses his work through the lens of cultural transformation and modernization processes. The author questions the unbroken line of developments portrayed in the historiography of modern architecture, and argues that Giedion’s position in between two cultural spheres not only caused ruptures and contradictions in his work but also productively shaped its reception on either side of the Atlantic.
Frontiers in Programming Living Systems: Hybrid Cell-Material Systems for Real-Time Sensing and Actuating
(Rice University, 5/4/2024) Chappell, James; Frow, Emma; Kamat, Neha; Matthews, Kirstin; Montclare, Jin; Silberg, Jonathan; Sonkusale, Sameer; Tran, Lesa; Wilson, Corey
Thickness-Dependent Terahertz Permittivity of Epitaxially Grown PbTe Thin Films
(MDPI, 2023) Kawahala, Nicolas M.; Matos, Daniel A.; Rappl, Paulo H. O.; Abramof, Eduardo; Baydin, Andrey; Kono, Junichiro; Hernandez, Felix G. G.; Smalley-Curl Institute
The exceptional thermoelectric properties of PbTe are believed to be associated with the incipient ferroelectricity of this material, which is caused by strong electron–phonon coupling that connects phononic and electronic dynamics. Here, we have used terahertz time-domain spectroscopy measurements to generate complex permittivity spectra for a set of epitaxially grown PbTe thin films with thicknesses between 100 nm and 500 nm at temperatures from 10 K to 300 K. Using a Drude–Lorentz model, we retrieved the physical parameters of both the phononic and electronic contributions to the THz permittivity. We observed a strong decrease, or softening, of the transverse optical phonon mode frequency with decreasing temperature, determining a thickness-independent negative ferroelectric-transition critical temperature, while we found a thickness-dependent anharmonic phonon decay lifetime. The electronic contribution to the permittivity was larger in thinner films, and both the carrier density and mobility increased with decreasing temperature in all films. Finally, we detected a thickness-dependent longitudinal optical phonon mode frequency, indicating the presence of plasmon–phonon coupling.
Bridging physical intuition and hardware efficiency for correlated electronic states: the local unitary cluster Jastrow ansatz for electronic structure
(Royal Society of Chemistry, 2023) Motta, Mario; Sung, Kevin J.; Whaley, K. Birgitta; Head-Gordon, Martin; Shee, James
A prominent goal in quantum chemistry is to solve the molecular electronic structure problem for ground state energy with high accuracy. While classical quantum chemistry is a relatively mature field, the accurate and scalable prediction of strongly correlated states found, e.g., in bond breaking and polynuclear transition metal compounds remains an open problem. Within the context of a variational quantum eigensolver, we propose a new family of ansatzes which provides a more physically appropriate description of strongly correlated electrons than a unitary coupled cluster with single and double excitations (qUCCSD), with vastly reduced quantum resource requirements. Specifically, we present a set of local approximations to the unitary cluster Jastrow wavefunction motivated by Hubbard physics. As in the case of qUCCSD, exactly computing the energy scales factorially with system size on classical computers but polynomially on quantum devices. The local unitary cluster Jastrow ansatz removes the need for SWAP gates, can be tailored to arbitrary qubit topologies (e.g., square, hex, and heavy-hex), and is well-suited to take advantage of continuous sets of quantum gates recently realized on superconducting devices with tunable couplers. The proposed family of ansatzes demonstrates that hardware efficiency and physical transparency are not mutually exclusive; indeed, chemical and physical intuition regarding electron correlation can illuminate a useful path towards hardware-friendly quantum circuits.
Denoising Non-Stationary Signals via Dynamic Multivariate Complex Wavelet Thresholding
(MDPI, 2023) Raath, Kim C.; Ensor, Katherine B.; Crivello, Alena; Scott, David W.
Over the past few years, we have seen an increased need to analyze the dynamically changing behaviors of economic and financial time series. These needs have led to significant demand for methods that denoise non-stationary time series across time and for specific investment horizons (scales) and localized windows (blocks) of time. Wavelets have long been known to decompose non-stationary time series into their different components or scale pieces. Recent methods satisfying this demand first decompose the non-stationary time series using wavelet techniques and then apply a thresholding method to separate and capture the signal and noise components of the series. Traditionally, wavelet thresholding methods rely on the discrete wavelet transform (DWT), which is a static thresholding technique that may not capture the time series of the estimated variance in the additive noise process. We introduce a novel continuous wavelet transform (CWT) dynamically optimized multivariate thresholding method (WaveL2E). Applying this method, we are simultaneously able to separate and capture the signal and noise components while estimating the dynamic noise variance. Our method shows improved results when compared to well-known methods, especially for high-frequency signal-rich time series, typically observed in finance.
Cell behaviors underlying Myxococcus xanthus aggregate dispersal
(American Society for Microbiology, 2023) Murphy, Patrick; Comstock, Jessica; Khan, Trosporsha; Zhang, Jiangguo; Welch, Roy; Igoshin, Oleg A.; Center for Theoretical Physical Biology
The soil bacterium Myxococcus xanthus is a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a second M. xanthus strain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle of M. xanthus.
Stable reconstruction of simple Riemannian manifolds from unknown interior sources
(IOP Publishing Ltd, 2023) Hoop, Maarten V. de; Ilmavirta, Joonas; Lassas, Matti; Saksala, Teemu
Consider the geometric inverse problem: there is a set of delta-sources in spacetime that emit waves travelling at unit speed. If we know all the arrival times at the boundary cylinder of the spacetime, can we reconstruct the space, a Riemannian manifold with boundary? With a finite set of sources we can only hope to get an approximate reconstruction, and we indeed provide a discrete metric approximation to the manifold with explicit data-driven error bounds when the manifold is simple. This is the geometrization of a seismological inverse problem where we measure the arrival times on the surface of waves from an unknown number of unknown interior microseismic events at unknown times. The closeness of two metric spaces with a marked boundary is measured by a labeled Gromov–Hausdorff distance. If measurements are done for infinite time and spatially dense sources, our construction produces the true Riemannian manifold and the finite-time approximations converge to it in the metric sense
The role of stress and fluid saturation on the acoustic response of fractured rock
(Frontiers Media S.A., 2023) Lisabeth, Harrison P.; Ajo-Franklin, Jonathan
Standard rock physics models are formulated to describe the behavior of porous sedimentary reservoirs, with clean sandstones being the archetypal system; however, many situations demand geophysical monitoring of rocks with significantly different structures, such as low porosity, fractured reservoirs. Conventional models also suggest that these “stiff” reservoirs can be challenging to monitor seismically due to small fluid substitution effects, but the presence of fractures leads to stress dependence which may be leveraged for remote monitoring purposes. Using samples from the Duperow Formation (dolostone) obtained from the Danielson test well in Kevin Dome, MT, we conducted ultrasonic and multi-scale structural (profilometry, synchrotron micro-tomography, pressure sensitive film) measurements on naturally fractured core in order to characterize the effects of fluid substitution and effective stress on the acoustic response of fractured reservoir rock with a focus in particular on the textural and seismic characteristics of natural fractures. We find that changes in effective stress can yield changes in velocity of up to 20% and changes in attenuation up to 200%. Measured fluid substitution effects are resolvable, but stress effects dominate. These measurements provide insight into the physical processes controlling acoustic response of fractured rocks in general and can also be used to inform monitoring efforts in fractured reservoirs.
A scientific machine learning framework to understand flash graphene synthesis
(Royal Society of Chemistry, 2023) Sattari, Kianoosh; Eddy, Lucas; Beckham, Jacob L.; Wyss, Kevin M.; Byfield, Richard; Qian, Long; Tour, James M.; Lin, Jian; NanoCarbon Center; Welch Institute for Advanced Materials
Flash Joule heating (FJH) is a far-from-equilibrium (FFE) processing method for converting low-value carbon-based materials to flash graphene (FG). Despite its promises in scalability and performance, attempts to explore the reaction mechanism have been limited due to the complexities involved in the FFE process. Data-driven machine learning (ML) models effectively account for the complexities, but the model training requires a considerable amount of experimental data. To tackle this challenge, we constructed a scientific ML (SML) framework trained by using both direct processing variables and indirect, physics-informed variables to predict the FG yield. The indirect variables include current-derived features (final current, maximum current, and charge density) predicted from the proxy ML models and reaction temperatures simulated from multi-physics modeling. With the combined indirect features, the final ML model achieves an average R2 score of 0.81 ± 0.05 and an average RMSE of 12.1% ± 2.0% in predicting the FG yield, which is significantly higher than the model trained without them (R2 of 0.73 ± 0.05 and an RMSE of 14.3% ± 2.0%). Feature importance analysis validates the key roles of these indirect features in determining the reaction outcome. These results illustrate the promise of this SML to elucidate FFE material synthesis outcomes, thus paving a new avenue to processing other datasets from the materials systems involving the same or different FFE processes.
Joint embedding of biological networks for cross-species functional alignment
(Oxford University Press, 2023) Li, Lechuan; Dannenfelser, Ruth; Zhu, Yu; Hejduk, Nathaniel; Segarra, Santiago; Yao, Vicky
Model organisms are widely used to better understand the molecular causes of human disease. While sequence similarity greatly aids this cross-species transfer, sequence similarity does not imply functional similarity, and thus, several current approaches incorporate protein–protein interactions to help map findings between species. Existing transfer methods either formulate the alignment problem as a matching problem which pits network features against known orthology, or more recently, as a joint embedding problem.We propose a novel state-of-the-art joint embedding solution: Embeddings to Network Alignment (ETNA). ETNA generates individual network embeddings based on network topological structure and then uses a Natural Language Processing-inspired cross-training approach to align the two embeddings using sequence-based orthologs. The final embedding preserves both within and between species gene functional relationships, and we demonstrate that it captures both pairwise and group functional relevance. In addition, ETNA’s embeddings can be used to transfer genetic interactions across species and identify phenotypic alignments, laying the groundwork for potential opportunities for drug repurposing and translational studies.https://github.com/ylaboratory/ETNA
Nanobomb optical coherence elastography in multilayered phantoms
(Optica Publishing Group, 2023) Hatami, Maryam; Nevozhay, Dmitry; Singh, Manmohan; Schill, Alexander; Boerner, Paul; Aglyamov, Salavat; Sokolov, Konstantin; Larin, Kirill V.
Many tissues are composed of layered structures, and a better understanding of the changes in the layered tissue biomechanics can enable advanced guidance and monitoring of therapy. The advent of elastography using longitudinally propagating shear waves (LSWs) has created the prospect of a high-resolution assessment of depth-dependent tissue elasticity. Laser activation of liquid-to-gas phase transition of dye-loaded perfluorocarbon (PFC) nanodroplets (a.k.a., nanobombs) can produce highly localized LSWs. This study aims to leverage the potential of photoactivation of nanobombs to incudce LSWs with very high-frequency content in wave-based optical coherence elastography (OCE) to estimate the elasticity gradient with high resolution. In this work, we used multilayered tissue-mimicking phantoms to demonstrate that highly localized nanobomb (NB)-induced LSWs can discriminate depth-wise tissue elasticity gradients. The results show that the NB-induced LSWs rapidly change speed when transitioning between layers with different mechanical properties, resulting in an elasticity resolution of ∼65 µm. These results show promise for characterizing the elasticity of multilayer tissue with a fine resolution.
Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation
(Oxford University Press, 2023) Kille, Bryce; Garrison, Erik; Treangen, Todd J; Phillippy, Adam M
The Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates.To address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications.MashMap3 is available at https://github.com/marbl/MashMap.
What Makes Weak Ties Strong?
(Annual Reviews, 2023) Kim, Minjae; Fernandez, Roberto M.
We raise two challenges concerning the validity of arguments underlying Granovetter's strength of weak ties (SWT) thesis: (a) whether weak ties are actually bridges, i.e., they help reach more socially distant actors than strong ties, and (b) whether weak ties transmit information effectively enough so that weak ties’ alleged structural properties make them more useful than strong ties. In the course of reviewing subsequent research that has made progress in addressing these challenges, we identify both potential limits and possibilities for the SWT thesis. We argue for the importance of identifying how actors’ agency—i.e., the way people use their ties—may affect social networks’ value. We conclude by summarizing some outstanding questions that progress on the SWT thesis has generated.
Supervised convex clustering
(Wiley, 2023) Wang, Minjie; Yao, Tianyi; Allen, Genevera I.
Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters has often been challenging precisely due to their unsupervised nature. Meanwhile, in many real-world scenarios, there are some noisy supervising auxiliary variables, for instance, subjective diagnostic opinions, that are related to the observed heterogeneity of the unlabeled data. By leveraging information from both supervising auxiliary variables and unlabeled data, we seek to uncover more scientifically interpretable group structures that may be hidden by completely unsupervised analyses. In this work, we propose and develop a new statistical pattern discovery method named supervised convex clustering (SCC) that borrows strength from both information sources and guides towards finding more interpretable patterns via a joint convex fusion penalty. We develop several extensions of SCC to integrate different types of supervising auxiliary variables, to adjust for additional covariates, and to find biclusters. We demonstrate the practical advantages of SCC through simulations and a case study on Alzheimer's disease genomics. Specifically, we discover new candidate genes as well as new subtypes of Alzheimer's disease that can potentially lead to better understanding of the underlying genetic mechanisms responsible for the observed heterogeneity of cognitive decline in older adults.
Regulation of Syntaxin3B-Mediated Membrane Fusion by T14, Munc18, and Complexin
(MDPI, 2023) Nishad, Rajkishor; Betancourt-Solis, Miguel; Dey, Himani; Heidelberger, Ruth; McNew, James A.
Retinal neurons that form ribbon-style synapses operate over a wide dynamic range, continuously relaying visual information to their downstream targets. The remarkable signaling abilities of these neurons are supported by specialized presynaptic machinery, one component of which is syntaxin3B. Syntaxin3B is an essential t-SNARE protein of photoreceptors and bipolar cells that is required for neurotransmitter release. It has a light-regulated phosphorylation site in its N-terminal domain at T14 that has been proposed to modulate membrane fusion. However, a direct test of the latter has been lacking. Using a well-controlled in vitro fusion assay, we found that a phosphomimetic T14 syntaxin3B mutation leads to a small but significant enhancement of SNARE-mediated membrane fusion following the formation of the t-SNARE complex. While the addition of Munc18a had only a minimal effect on membrane fusion mediated by SNARE complexes containing wild-type syntaxin3B, a more significant enhancement was observed in the presence of Munc18a when the SNARE complexes contained a syntaxin3B T14 phosphomimetic mutant. Finally, we showed that the retinal-specific complexins (Cpx III and Cpx IV) inhibited membrane fusion mediated by syntaxin3B-containing SNARE complexes in a dose-dependent manner. Collectively, our results establish that membrane fusion mediated by syntaxin3B-containing SNARE complexes is regulated by the T14 residue of syntaxin3B, Munc18a, and Cpxs III and IV.
Real-time, deep-learning aided lensless microscope
(Optica Publishing Group, 2023) Wu, Jimin; Boominathan, Vivek; Veeraraghavan, Ashok; Robinson, Jacob T.
Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to account for the variation of the point spread function (PSF) across the FOV. Here, we present a lensless microscope that achieves real-time image reconstruction by eliminating the use of an iterative reconstruction algorithm. The neural network-based reconstruction method we show here, achieves more than 10000 times increase in reconstruction speed compared to iterative reconstruction. The increased reconstruction speed allows us to visualize the results of our lensless microscope at more than 25 frames per second (fps), while achieving better than 7 µm resolution over a FOV of 10 mm2. This ability to reconstruct and visualize samples in real-time empowers a more user-friendly interaction with lensless microscopes. The users are able to use these microscopes much like they currently do with conventional microscopes.
Consecutive Shifts: A Repeated Measure Study to Evaluate Stress, Biomarkers, Social Support, and Fatigue in Medical/Surgical Nurses
(MDPI, 2023) Cockerham, Mona; Kang, Duck-Hee; Beier, Margaret E.
Nurses report that they are required to work during their scheduled breaks and generally experience extended work times and heavy workloads due to staffing shortages. This study aimed to examine changes in personal, work-related, and overall stress, as well as biological responses and fatigue experienced by nurses during three consecutive 12 h workdays (i.e., the typical “three-twelves” schedule). We also considered the moderating effects of social resources. This prospective study of 81 medical/surgical nurses who completed questionnaires and provided saliva samples at four designated intervals (i.e., pre-shift and post-shift on workdays 1 and 3). Fatigue reported by night shift nurses increased significantly over three consecutive workdays (p = 0.001). Day shift nurses said they encountered more social support than those on the night shift (p = 0.05). Social support moderated the relationship between work-related stress at baseline and reported fatigue on day 3.
Environment and shipping drive environmental DNA beta-diversity among commercial ports
(Wiley, 2023) Andrés, Jose; Czechowski, Paul; Grey, Erin; Saebi, Mandana; Andres, Kara; Brown, Christopher; Chawla, Nitesh; Corbett, James J.; Brys, Rein; Cassey, Phillip; Correa, Nancy; Deveney, Marty R.; Egan, Scott P.; Fisher, Joshua P.; vanden Hooff, Rian; Knapp, Charles R.; Leong, Sandric Chee Yew; Neilson, Brian J.; Paolucci, Esteban M.; Pfrender, Michael E.; Pochardt, Meredith R.; Prowse, Thomas A. A.; Rumrill, Steven S.; Scianni, Chris; Sylvester, Francisco; Tamburri, Mario N.; Therriault, Thomas W.; Yeo, Darren C. J.; Lodge, David M.
The spread of nonindigenous species by shipping is a large and growing global problem that harms coastal ecosystems and economies and may blur coastal biogeographical patterns. This study coupled eukaryotic environmental DNA (eDNA) metabarcoding with dissimilarity regression to test the hypothesis that ship-borne species spread homogenizes port communities. We first collected and metabarcoded water samples from ports in Europe, Asia, Australia and the Americas. We then calculated community dissimilarities between port pairs and tested for effects of environmental dissimilarity, biogeographical region and four alternative measures of ship-borne species transport risk. We predicted that higher shipping between ports would decrease community dissimilarity, that the effect of shipping would be small compared to that of environment dissimilarity and shared biogeography, and that more complex shipping risk metrics (which account for ballast water and stepping-stone spread) would perform better. Consistent with our hypotheses, community dissimilarities increased significantly with environmental dissimilarity and, to a lesser extent, decreased with ship-borne species transport risks, particularly if the ports had similar environments and stepping-stone risks were considered. Unexpectedly, we found no clear effect of shared biogeography, and that risk metrics incorporating estimates of ballast discharge did not offer more explanatory power than simpler traffic-based risks. Overall, we found that shipping homogenizes eukaryotic communities between ports in predictable ways, which could inform improvements in invasive species policy and management. We demonstrated the usefulness of eDNA metabarcoding and dissimilarity regression for disentangling the drivers of large-scale biodiversity patterns. We conclude by outlining logistical considerations and recommendations for future studies using this approach.
Effects of nutrient pulses on exotic species shift from positive to neutral with decreasing water availability
(Wiley, 2024) Otieno, Evans O.; Shen, Changchao; Zhang, Kaoping; Wan, Jinlong; He, Minyan; Tao, Zhibin; Huang, Wei; Siemann, Evan
Temporal fluctuation in nutrient availability generally promotes the growth of exotic plant species and has been recognized as an important driver of exotic plant invasions. However, little is known about how the impact of fluctuating nutrients on exotic species is dependent on the availability of other resources, although most ecosystems are experiencing dramatic variations in a wide variety of resources due to global change and human disturbance. Here, we explored how water availability mediates the effect of nutrient pulses on the growth of six exotic and six native plant species. We subjected individual plants of exotic and native species to well watered or water stressed conditions. For each level of water availability, we added equivalent amounts of nutrients at a constant rate, as a single large pulse, or in multiple small pulses. Under well watered conditions, nutrient pulses promoted exotic plant growth relative to nutrients supplied constantly, while they had no significant effect on natives. In contrast, under water stressed conditions, water deficiency inhibited the growth of all exotic and native species. More importantly, nutrient pulses did not increase plant growth relative to nutrients supplied constantly and these phenomena were observed for both exotic and native species. Taken together, our study shows that the impact of fluctuating nutrient availability on the growth of exotic plant species strongly depends on the variation of other resources, and that the positive effect of nutrient pulses under well watered conditions disappears under water stressed conditions. Our findings suggest that the variation in multiple resources may have complex feedback on exotic plant invasions and, therefore, it is critical to encompass multiple resources for the evaluation of fluctuating resource availability effects on exotic plant species. This will allow us to project the invasive trajectory of exotic plant species more accurately under future global change and human disturbance.
A Magnetically Driven Disk Wind in the Inner Disk of PDS 70*
(IOP Publishing Ltd, 2023) Campbell-White, Justyn; Manara, Carlo F.; Benisty, Myriam; Natta, Antonella; Claes, Rik A. B.; Frasca, Antonio; Bae, Jaehan; Facchini, Stefano; Isella, Andrea; Pérez, Laura; Pinilla, Paola; Sicilia-Aguilar, Aurora; Teague, Richard
PDS 70 is so far the only young disk where multiple planets have been detected by direct imaging. The disk has a large cavity when seen at submillimeter and near-infrared wavelengths, which hosts two massive planets. This makes PDS 70 the ideal target to study the physical conditions in a strongly depleted inner disk shaped by two giant planets, and in particular to test whether disk winds can play a significant role in its evolution. Using X-Shooter and HARPS spectra, we detected for the first time the wind-tracing [O i] 6300 Å line, and confirm the low-moderate value of mass-accretion rate in the literature. The [O i] line luminosity is high with respect to the accretion luminosity when compared to a large sample of disks with cavities in nearby star-forming regions. The FWHM and blueshifted peak of the [O i] line suggest an emission in a region very close to the star, favoring a magnetically driven wind as the origin. We also detect wind emission and high variability in the He i 10830 Å line, which is unusual for low accretors. We discuss that, although the cavity of PDS 70 was clearly carved out by the giant planets, the substantial inner-disk wind could also have had a significant contribution to clearing the inner disk.

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