University of California, Santa Barbara
  • Santa Barbara, CA, United States
Recent publications
Here, we report a very sensitive, non-contact, ratio-metric, and robust luminescence-based temperature sensing using a combination of conventional photoluminescence (PL) and negative thermal quenching (NTQ) mechanisms of semiconductor BiFeO 3 (BFO) nanowires. Using this approach, we have demonstrated the absolute thermal sensitivity of ~ 10 mK ⁻¹ over the 300–438 K temperature range and the relative sensitivity of 0.75% K ⁻¹ at 300 K. Further, we have validated thermal sensitivity of BFO nanowires quantitatively using linear regression and analytical hierarchy process (AHP) and found close match with the experimental results. These results indicated that BFO nanowires are excellent candidates for developing high‐performance luminescence-based temperature sensors. Graphical abstract
We introduce three developments within the stochastic many-body perturbation theory: efficient evaluation of off-diagonal self-energy terms, construction of Dyson orbitals, and stochastic constrained random phase approximation. The stochastic approaches readily handle systems with thousands of atoms. We use them to explore the electronic states of twisted bilayer graphene (tBLG) characterized by giant unit cells and correlated electronic states. We document the formation of electron localization under compression; weakly correlated states are merely shifted in energy. We demonstrate how to efficiently downfold the correlated subspace on a model Hamiltonian with a screened frequency-dependent two-body interaction. For the 6° tBLG system, the onsite interactions are between 200 and 300 meV under compression. The Dyson orbitals exhibit spatial distribution similar to the mean-field single-particle states. Under pressure, the electron-electron interactions increase in the localized states; however, the dynamical screening does not fully balance the dominant bare Coulomb interaction.
Coexisting density-wave and superconducting states along with the large anomalous Hall effect in the absence of local magnetism remain intriguing and enigmatic features of the AV 3 Sb 5 kagome metals (A = K, Rb, Cs). Here, we demonstrate via optical spectroscopy and density-functional calculations that low-energy dynamics of KV 3 Sb 5 is characterized by unconventional localized carriers, which are strongly renormalized across the density-wave transition and indicative of electronic correlations. Strong phonon anomalies are prominent not only below the density-wave transition, but also at high temperatures, suggesting an intricate interplay of phonons with the underlying electronic structure. We further propose the star-of-David and tri-hexagon (inverse star-of-David) configurations for the density-wave order in KV 3 Sb 5 . These configurations are strongly reminiscent of p -wave states expected in the Hubbard model on the kagome lattice at the filling level of the van Hove singularity. The proximity to this regime should have intriguing and far-reaching implications for the physics of KV 3 Sb 5 and related materials.
Background HIV epidemic among men who have sex with men (MSM) remains a major public health concern in China. Despite a growing body of research on transgender women worldwide, little is known about Chinese transgender women within MSM. We sought to estimate HIV incidence and distinguish risk factors of HIV acquisition among them from that among cisgener (non-transgender) MSM (cis-MSM). Methods We conducted an open cohort study among Chinese MSM, including those who were identified as transgender in Shanghai and Tianjin. Participants were initially recruited by local community-based organizations from January to June, 2016, and were followed up approximately every 6 months until June 2018. At each visit, a structured questionnaire was used to gather information on demographics, sexual risk behaviors, and HIV status. HIV incidence was calculated as the number of seroconversions divided by total number of person-years of follow-up among HIV-negatives at baseline. Risk factors of HIV acquisition were assessed by univariate and multivariate Cox regression models with time-dependent variables. Results A total of 1056 participants contributed 1260.53 person-years (PYs) of follow-up, 33 HIV seroconversions occurred during the follow-up period, yielding an estimated HIV incidence of 2.62 (95% CI 1.80–3.68) per 100 PYs. HIV incidence among transgender women was 4.42 per 100 PYs, which was significantly higher than that of 1.35 per 100 PYs among cis-MSM, demonstrating a threefold higher odds of HIV infection than cis-MSM. For transgender women, those lived locally ≤ 2 years (adjusted hazard ratio [a HR ] = 1.76, 95% CI 1.13–2.76) and unprotected anal sex last time (a HR = 4.22, 95% CI 1.82–9.79) were more likely to acquire HIV. For cis-MSM, factors associated with HIV acquisition were frequency of anal sex ≥ 3 times in past one month (a HR = 4.19, 95% CI 1.06–16.47) and unprotected anal sex last time (a HR = 5.33, 95% CI 1.52–18.73). Conclusions Compared to cis-MSM, transgender women were at higher risk of HIV acquisition, highlighting an urgent need of tailored prevention. Future HIV program should consider to include them to ensure that this population in China are not left behind. Graphical abstract
This paper develops a Bayesian inference-based probabilistic crack nucleation model for the Ni-based superalloy René 88DT under fatigue loading. A data-driven, machine learning approach is developed, identifying underlying mechanisms driving crack nucleation. An experimental set of fatigue-loaded microstructures is characterized near crack nucleation sites using scanning electron microscopy and electron backscatter diffraction images for correlating the grain morphology and crystallography to the location of crack nucleation sites. A concurrent multiscale model, embedding experimental polycrystalline microstructural representative volume elements (RVEs) in a homogenized material, is developed for fatigue simulations. The RVE domain is modeled by a crystal plasticity finite element model. An anisotropic continuum plasticity model, obtained by homogenization of the crystal plasticity model, is used for the exterior domain. A Bayesian classification method is introduced to optimally select informative state variable predictors of crack nucleation. From this principal set of state variables, a simple scalar crack nucleation indicator is formulated.
Some science education researchers have presented either isolated findings on specific points in time during the pandemic or non-empirical insights or suggestions for how teachers, district leaders, policymakers, and others should take up the learnings from the pandemic to move science education forward. However, there are few studies published to date that provide robust and longitudinal empirical data on what science instruction looked like throughout the pandemic and the magnitude of the impacts of the pandemic on science instruction when compared to pre-pandemic science teaching and learning. We conducted a primarily survey-based study on science instruction and enactment of the Next Generation Science Standards (NGSS) in K-8 classrooms throughout the COVID-19 pandemic. This analysis also incorporates a longitudinal dataset from grade 6–8 teachers across California on their NGSS instruction prior to and throughout the first year of the pandemic, providing insight on instruction over multiple years before and throughout distance learning. Our findings highlight the challenges that teachers and students faced during the pandemic, as well as the significant impacts that distance learning appeared to have on science instruction and teachers’ ability to provide NGSS-aligned instruction. However, we also found that a year after the initial school closures, teachers’ science instruction began to show improvements both in the frequency of science instruction (how often they were able to provide science instruction through distance learning) and the quality of science instruction (how often teachers were able to provide instruction that was aligned with the goals of the NGSS). Implications of this work are far reaching and may impact teachers, students, administrators, policymakers, professional learning providers, and curriculum developers regardless of whether science instruction occurs through distance learning or in-person moving forward.
In the California Current Ecosystem, upwelled water low in dissolved iron (Fe) can limit phytoplankton growth, altering the elemental stoichiometry of the particulate matter and dissolved macronutrients. Iron-limited diatoms can increase biogenic silica (bSi) content >2-fold relative to that of particulate organic carbon (C) and nitrogen (N), which has implications for carbon export efficiency given the ballasted nature of the silica-based diatom cell wall. Understanding the molecular and physiological drivers of this altered cellular stoichiometry would foster a predictive understanding of how low Fe affects diatom carbon export. In an artificial upwelling experiment, water from 96 m depth was incubated shipboard and left untreated or amended with dissolved Fe or the Fe-binding siderophore desferrioxamine-B (+DFB) to induce Fe-limitation. After 120 h, diatoms dominated the communities in all treatments and displayed hallmark signatures of Fe-limitation in the +DFB treatment, including elevated particulate Si:C and Si:N ratios. Single-cell, taxon-resolved measurements revealed no increase in bSi content during Fe-limitation despite higher transcript abundance of silicon transporters and silicanin-1. Based on these findings we posit that the observed increase in bSi relative to C and N was primarily due to reductions in C fixation and N assimilation, driven by lower transcript expression of key Fe-dependent genes.
Oceans play critical roles in the lives, economies, cultures, and nutrition of people globally, yet face increasing pressures from human activities that put those benefits at risk. To anticipate the future of the world's ocean, we review the many human activities that impose pressures on marine species and ecosystems, evaluating their impacts on marine life, the degree of scientific uncertainty in those assessments, and the expected trajectory over the next few decades. We highlight that fundamental research should prioritize areas of high potential impact and greater uncertainty about ecosystem vulnerability, such as emerging fisheries, organic chemical pollution, seabed mining, and the interactions of cumulative pressures, and deprioritize research on areas that demonstrate little impact or are well understood, such as plastic pollution and ship strikes to marine fauna. There remains hope for a productive and sustainable future ocean, but the window of opportunity for action is closing. Expected final online publication date for the Annual Review of Environment and Resources, Volume 47 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
The ocean holds vast quantities of carbon that it continually exchanges with the atmosphere through the air-sea interface. Because of its enormous size and relatively rapid exchange of carbon with the atmosphere, the ocean controls atmospheric CO 2 concentration and thereby Earth's climate on timescales of tens to thousands of years. This review examines the basic functions of the ocean's carbon cycle, demonstrating that the ocean carbon inventory is determined primarily by the mass of the ocean, by the chemical buffering of CO 2 in seawater, and by the action of the solubility and biological pumps that draw carbon into the ocean's deeper layers, where it can be sequestered for decades to millennia. The ocean also plays a critical role in moderating the impacts of climate change by absorbing about 25% of anthropogenic CO 2 emissions over the past several decades. However, this also leads to ocean acidification and reduces the chemical buffering capacity of the ocean and its future ability to take up CO 2 . This review closes with a look at the uncertain future of the ocean carbon cycle and the scientific challenges that this uncertainty brings. Expected final online publication date for the Annual Review of Environment and Resources, Volume 47 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
For a smooth cubic fourfold Y, we study the moduli space M of semistable objects of Mukai vector 2λ1+2λ2 in the Kuznetsov component of Y. We show that with a certain choice of stability conditions, M admits a symplectic resolution M˜, which is a smooth projective hyperkähler manifold, deformation equivalent to the 10-dimensional examples constructed by O'Grady. As applications, we show that a birational model of M˜ provides a hyperkähler compactification of the twisted family of intermediate Jacobians associated to Y. This generalizes the previous result of Voisin [58] in the very general case. We also prove that M˜ is the MRC quotient of the main component of the Hilbert scheme of quintic elliptic curves in Y, confirming a conjecture of Castravet.
Extreme sea conditions are often caused by typhoons that occur obviously in season. How to calculate the design values of marine environmental elements based on statistical characteristic of typhoon in different periods is important. A nested stochastic compound distribution (NSCD) model is proposed based on the stochastic process theory. During a typhoon occurrence, the distributions of the marine environmental elements such as wind velocity (WV) and storm surge (SS) at any moment are described in continuous stochastic processes, and the distribution of typhoon occurrence frequency (TOF) during any period is described by a discrete stochastic process. Based on the measured data in the South China Sea (SCS), the applicability of different marginal distribution functions and Copula functions in the SCS are further discussed, and the specific form of the NSCD model suitable for the SCS is obtained. The Design values of WV and SS for different joint return periods and coincidence return periods are calculated according to the NSCD and the compound extreme value distribution (CEVD). The effects of treating TOF as a stochastic process and a random variable on the design values of the two marine environmental elements are discussed. Results show that the NSCD model contains the traditional CEVD model, which is a form of the NSCD model in a specific time situation. The design values of WV and SS obtained by the NSCD model can reflect the impact of TOF on marine environmental elements. Moreover, the probability of simultaneous occurrence of extreme WV and extreme SS is higher over longer return periods under the influence of typhoons. The NSCD model can therefore be used to make joint probability predictions for a wide range of extreme sea conditions in different time periods according to engineering needs.
The results of two experiments are reported that included a combined total of approximately 633,000 categorization trials. The experiments investigated the nature of what is automatized after lengthy practice with a rule-guided behavior. The results of both experiments suggest that an abstract rule, if interpreted as a verbal-based strategy, was not automatized during training, but rather the automatization linked a set of stimuli with similar values on one visual dimension to a common motor response. The experiments were designed to test and refine a recent neurocomputational model of how rule-guided behaviors become automatic (Kovacs, Hélie, Tran, & Ashby, 2021). The model assumes that rule-guided behaviors are initially controlled by a distributed neural network centered on rule units in prefrontal cortex, and that in addition to initiating behavior, this network also trains a faster and more direct network that includes projections from visual cortex directly to the rule-sensitive neurons in premotor cortex. The present results support this model and suggest that the projections from visual cortex to prefrontal and premotor cortex are restricted to visual representations of the relevant stimulus dimension only.
The Amazon River basin harbors some of the world's largest wetland complexes, which are of major importance for biodiversity, the water cycle and climate, and human activities. Accurate estimates of inundation extent and its variations across spatial and temporal scales are therefore fundamental to understand and manage the basin's resources. More than fifty inundation estimates have been generated for this region, yet major differences exist among the datasets, and a comprehensive assessment of them is lacking. Here we present an intercomparison of 29 inundation datasets for the Amazon basin, based on remote sensing only, hydrological modeling, or multi-source datasets, with 18 covering the lowland Amazon basin (elevation <500 m, which includes most Amazon wetlands), and 11 covering individual wetland complexes (subregional datasets). Spatial resolutions range from 12.5 m to 25 km, and temporal resolution from static to monthly, spanning up to a few decades. Overall, 31% of the lowland basin is estimated as subject to inundation by at least one dataset. The long-term maximum inundated area across the lowland basin is estimated at 599,700 ± 81,800 km² if considering the three higher quality SAR-based datasets, and 490,300 ± 204,800 km² if considering all 18 datasets. However, even the highest resolution SAR-based dataset underestimates the maximum values for individual wetland complexes, suggesting a basin-scale underestimation of ~10%. The minimum inundation extent shows greater disagreements among datasets than the maximum extent: 139,300 ± 127,800 km² for SAR-based ones and 112,392 ± 79,300 km² for all datasets. Discrepancies arise from differences among sensors, time periods, dates of acquisition, spatial resolution, and data processing algorithms. The median total area subject to inundation in medium to large river floodplains (drainage area > 1000 km²) is 323,700 km². The highest spatial agreement is observed for floodplains dominated by open water such as along the lower Amazon River, whereas intermediate agreement is found along major vegetated floodplains fringing larger rivers (e.g., Amazon mainstem floodplain). Especially large disagreements exist among estimates for interfluvial wetlands (Llanos de Moxos, Pacaya-Samiria, Negro, Roraima), where inundation tends to be shallower and more variable in time. Our data intercomparison helps identify the current major knowledge gaps regarding inundation mapping in the Amazon and their implications for multiple applications. In the context of forthcoming hydrology-oriented satellite missions, we make recommendations for future developments of inundation estimates in the Amazon and present a WebGIS application (https://amazon-inundation.herokuapp.com/) we developed to provide user-friendly visualization and data acquisition of current Amazon inundation datasets.
ZnSnN2 is a non-toxic and earth-abundant photoabsorber material for flexible photovoltaic devices because of its excellent optoelectronic behavior. However, theoretical studies show that the alkaline-earth metallic (Li, Na, K, Rb, Cs, and Fr) dopants in ZnSnN2, particularly lithium (Li), display shallow-acceptor behavior and improve the performance of ZnSnN2 semiconductors. Orthorhombic phase structure with (002) preferred orientation was observed for Li-doped films and the lattice parameters agree well with reported standards. Secondary ion mass spectroscopy (SIMS) analysis revealed the incorporation of Li in Li:ZnSnN2 films. XPS, the density of states, and Born effective charge analysis revealed the chemical bonding states of Li–ZnSnN2. In contrast to the pristine n-type ZnSnN2, Li:ZnSnN2 thin films showed conductivity with p-type hole concentrations varying between 1.14 × 10²⁰–9.47 × 10¹⁹ cm⁻³ and the highest mobility of 20.03 cm²V⁻¹s⁻¹. Therefore, we obtained p-type conductivity by substituting an organolithium reagent (C₄H₉Li) on the Zn site, which highlights that Li:ZnSnN2 can be effectively used as the photoanode layer for next-generation thin-film solar cell devices.
In this study an exploration of insurance risk transfer is undertaken for the cyber insurance industry in the United States of America, based on the leading industry dataset of cyber events provided by Advisen. We seek to address two core unresolved questions. First, what factors are the most significant covariates that may explain the frequency and severity of cyber loss events and are they heterogeneous over cyber risk categories? Second, is cyber risk insurable in regards to the required premiums, risk pool sizes and how would this decision vary with the insured companies industry sector and size? We address these questions through a combination of regression models based on the class of Generalized Additive Models for Location Shape and Scale (GAMLSS) and a class of ordinal regressions. These models will then form the basis for our analysis of frequency and severity of cyber risk loss processes. We investigate the viability of insurance for cyber risk using a utility modeling framework with premiums calculated by classical certainty equivalence analysis utilizing the developed regression models. Our results provide several new key insights into the nature of insurability of cyber risk and rigorously address the two insurance questions posed in a real data driven case study analysis.
As marine spatial planning (MSP) continues to gain global prominence as an approach to ocean governance, planners and other stakeholders are eager to evaluate its social and ecological outcomes and to better understand whether plans are achieving their intended results in an equitable and cost-efficient manner. While a plan’s outcomes for marine environments and coastal communities may be of particular interest, these results cannot be separated from planning processes. The field has yet to fully develop the guidance necessary for this critical consideration of how features of an MSP process and external factors interact with plan performance and outcomes. To fill this gap we used a literature review and expert discussions to identify 19 enabling or disabling conditions of MSP within four major categories: Plan Attributes, Legal Context, Plan Development and Social Context, and Integration. We propose semi-quantitative scoring and the development of narratives to operationalize the framework as part of a comprehensive methodology for MSP outcome evaluation. Applying the framework can add depth to quantitative MSP evaluation, shed light on questions of outcome attribution, and inform plan adaptation. Evaluating MSP outcomes in the explicit context of the enabling or disabling conditions identified here can stimulate discussion around what works in MSP and provide a path forward for assessing the benefits and costs of MSP worldwide. By identifying conditions instrumental to effective MSP, and alternatively, conditions hindering a plan, the framework can be used to guide plan adaptation and promote learning across the wider MSP community.
Pulse rate variability is a physiological parameter that has been extensively studied and correlated with many physical ailments. However, the phase relationship between inter-beat interval, IBI, and breathing has very rarely been studied. Develop a technique by which the phase relationship between IBI and breathing can be accurately and efficiently extracted from photoplethysmography (PPG) data. A program based on Lock-in Amplifier technology was written in Python to implement a novel technique, Dynamic Phase Extraction. It was tested using a breath pacer and a PPG sensor on 6 subjects who followed a breath pacer at varied breathing rates. The data were then analyzed using both traditional methods and the novel technique (Dynamic Phase Extraction) utilizing a breath pacer. Pulse data was extracted using a PPG sensor. Dynamic Phase Extraction (DPE) gave the magnitudes of the variation in IBI associated with breathing (ΔIBI) measured with photoplethysmography during paced breathing (with premature ventricular contractions, abnormal arrhythmias, and other artifacts edited out). ΔIBI correlated well with two standard measures of pulse rate variability: the Standard Deviation of the inter-beat interval (SDNN) (ρ = 0.911) and with the integrated value of the Power Spectral Density between 0.04 and 0.15 Hz (Low Frequency Power or LF Power) (ρ = 0.885). These correlations were comparable to the correlation between the SDNN and the LF Power (ρ = 0.877). In addition to the magnitude ΔIBI, Dynamic Phase Extraction also gave the phase between the breath pacer and the changes in the inter-beat interval (IBI) due to respiratory sinus arrythmia (RSA), and correlated well with the phase extracted using a Fourier transform (ρ = 0.857). Dynamic Phase Extraction can extract both the phase between the breath pacer and the changes in IBI due to the respiratory sinus arrhythmia component of pulse rate variability (ΔIBI), but is limited by needing a breath pacer.
Traditional markets form a critical part of rural-urban food systems in sub-Saharan Africa (SSA). Aside from providing more affordable and physically accessible food to low-income consumers, traditional markets serve as wholesalers to street vendors, create market entry points for smallholder farmers, and provide essential employment opportunities for sellers. However, many traditional markets face ongoing challenges such as infrastructure deficits, poor waste management, and internal conflict that undermine their effectiveness. Markets that perform effectively can provide requisite services to vendors and manage relationships between actors within and outside the market. We propose that the degree to which traditional markets are able to play an effective role in rural-urban food systems depends on the governance structures in place in individual markets. We aim to take initial steps toward developing an institutional analysis methodology that can be used to identify the set of institutional arrangements that are appropriate for successfully governing traditional markets. Using data from a 2021 phone call survey of 81 urban and rural markets in Zambia, and drawing inspiration from Ostrom's design principles for enduring common pool resources, we identify some of the institutional arrangements that tend to lead to effective market performance in Zambia, including market formality, the role of market committees, government engagement in markets, and conflict resolution protocols. Our study alone does not definitively identify the set of institutions that are appropriate for successfully governing traditional markets, particularly beyond the Zambian context. However, we highlight the types of data that need to be collected to achieve this objective by contributing a survey instrument and an empirical dataset of traditional markets across the rural-urban food system.
Icelandic basalts have low oxygen isotope (δ18O) values compared to other ocean island localities. While this observation is often ascribed to the assimilation of low-δ18O crust, a low-δ18O mantle beneath Iceland has also been suggested. To discern crustal from mantle-derived signals, high-quality in-situ and bulk crystal δ18O measurements have been obtained from olivine crystals covering 16 Ma of activity at the Iceland hotspot. The results are combined with olivine (ol) major, minor and trace element chemistry. Relationships between δ18Ool and indicators of melt evolution do not support a singular process responsible for lowering of δ18O values. However, correlations are observed between δ18Ool values and indicators of crustal processes. Such patterns are used to filter out data that are likely to reflect effects from crustal assimilation to highlight δ18Ool values indicative of source-derived variability only. Although filtered, the dataset reveals, that δ18Ool values, significantly lower than the canonical depleted upper mantle value, are derived from the Iceland mantle. Coupled δ18Ool and ³He/⁴Heol measurements done on olivine crystals from the same samples demonstrate that low-δ18O components (down to δ18Oolivine = 4.2‰) are a trait of the modern Iceland plume and that low-δ18O and low-³He/⁴He components have become more apparent in the hotspot products since 60 Ma. Olivine chemistry characteristics suggest that this low-δ18O component is best sampled in melts that reflect contributions from pyroxenitic mantle lithologies, likely related to the recycling of oceanic lithosphere within the plume. An increase in plume flux, as traced by increasing plume temperatures and plume buoyancy after 35 Ma, led to enhanced entrainment of lower mantle material carrying recycled low-δ18O oceanic lithosphere. Such material has become more apparent with time as is reflected in source-derived low-δ18O and high ³He/⁴He values in olivine from the modern Iceland plume. Moreover, the coincidence of the Iceland plume-head and the North Atlantic Rift at from ∼25 Ma likely assisted and further promoted enhanced plume-melting. Thus, the combination of changes in mantle upwelling and tectonic reorganisation of the North Atlantic led to the introduction of recycled oceanic lithosphere into the Iceland plume and the formation of the Iceland Plateau ∼25 Ma.
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10,269 members
Kai Ewert
  • Materials Research Laboratory
Samuel P Burke
  • Department of Physics
Werner Kuhn
  • Department of Geography
Alan Fridlund
  • Department of Psychological and Brain Sciences
Bruce Edward Kendall
  • Bren School of Environmental Science and Management
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