University of California System

The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations. This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual. This report by the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations. Integrative analyses reveal profiles of rare and common variants in different populations. The frequencies of rare variants vary across biological pathways, and hundreds of rare, non-coding variants at conserved sites — such as changes disrupting transcription-factor motifs — can be established for each individual.

Research on fluorescent semiconductor nanocrystals (also known as quantum dots or qdots) has evolved over the past two decades from electronic materials science to biological applications. We review current approaches to the synthesis, solubilization, and functionalization of qdots and their applications to cell and animal biology. Recent examples of their experimental use include the observation of diffusion of individual glycine receptors in living neurons and the identification of lymph nodes in live animals by near-infrared emission during surgery. The new generations of qdots have far-reaching potential for the study of intracellular processes at the single-molecule level, high-resolution cellular imaging, long-term in vivo observation of cell trafficking, tumor targeting, and diagnostics.

This paper contains a new approach toward a theory of robust estimation; it treats in detail the asymptotic theory of estimating a location parameter for contaminated normal distributions, and exhibits estimators--intermediaries between sample mean and sample median--that are asymptotically most robust (in a sense to be specified) among all translation invariant estimators. For the general background, see Tukey (1960) (p. 448 ff.) Let $x_1, \cdots, x_n$ be independent random variables with common distribution function $F(t - \xi)$. The problem is to estimate the location parameter $\xi$, but with the complication that the prototype distribution $F(t)$ is only approximately known. I shall primarily be concerned with the model of indeterminacy $F = (1 - \epsilon)\Phi + \epsilon H$, where $0 \leqq \epsilon < 1$ is a known number, $\Phi(t) = (2\pi)^{-\frac{1}{2}} \int^t_{-\infty} \exp(-\frac{1}{2}s^2) ds$ is the standard normal cumulative and $H$ is an unknown contaminating distribution. This model arises for instance if the observations are assumed to be normal with variance 1, but a fraction $\epsilon$ of them is affected by gross errors. Later on, I shall also consider other models of indeterminacy, e.g., $\sup_t |F(t) - \Phi(t)| \leqq \epsilon$. Some inconvenience is caused by the fact that location and scale parameters are not uniquely determined: in general, for fixed $\epsilon$, there will be several values of $\xi$ and $\sigma$ such that $\sup_t|F(t) - \Phi((t - \xi)/\sigma)| \leqq \epsilon$, and similarly for the contaminated case. Although this inherent and unavoidable indeterminacy is small if $\epsilon$ is small and is rather irrelevant for practical purposes, it poses awkward problems for the theory, especially for optimality questions. To remove this difficulty, one may either (i) restrict attention to symmetric distributions, and estimate the location of the center of symmetry (this works for $\xi$ but not for $\sigma$); or (ii) one may define the parameter to be estimated in terms of the estimator itself, namely by its asymptotic value for sample size $n \rightarrow \infty$; or (iii) one may define the parameters by arbitrarily chosen functionals of the distribution (e.g., by the expectation, or the median of $F$). All three possibilities have unsatisfactory aspects, and I shall usually choose the variant which is mathematically most convenient. It is interesting to look back to the very origin of the theory of estimation, namely to Gauss and his theory of least squares. Gauss was fully aware that his main reason for assuming an underlying normal distribution and a quadratic loss function was mathematical, i.e., computational, convenience. In later times, this was often forgotten, partly because of the central limit theorem. However, if one wants to be honest, the central limit theorem can at most explain why many distributions occurring in practice are approximately normal. The stress is on the word "approximately." This raises a question which could have been asked already by Gauss, but which was, as far as I know, only raised a few years ago (notably by Tukey): What happens if the true distribution deviates slightly from the assumed normal one? As is now well known, the sample mean then may have a catastrophically bad performance: seemingly quite mild deviations may already explode its variance. Tukey and others proposed several more robust substitutes--trimmed means, Winsorized means, etc.--and explored their performance for a few typical violations of normality. A general theory of robust estimation is still lacking; it is hoped that the present paper will furnish the first few steps toward such a theory. At the core of the method of least squares lies the idea to minimize the sum of the squared "errors," that is, to adjust the unknown parameters such that the sum of the squares of the differences between observed and computed values is minimized. In the simplest case, with which we are concerned here, namely the estimation of a location parameter, one has to minimize the expression $\sum_i (x_i - T)^2$; this is of course achieved by the sample mean $T = \sum_i x_i/n$. I should like to emphasize that no loss function is involved here; I am only describing how the least squares estimator is defined, and neither the underlying family of distributions nor the true value of the parameter to be estimated enters so far. It is quite natural to ask whether one can obtain more robustness by minimizing another function of the errors than the sum of their squares. We shall therefore concentrate our attention to estimators that can be defined by a minimum principle of the form (for a location parameter): $T = T_n(x_1, \cdots, x_n) minimizes \sum_i \rho(x_i - T),$ \begin{equation*} \tag{M} where \rho is a non-constant function. \end{equation*} Of course, this definition generalizes at once to more general least squares type problems, where several parameters have to be determined. This class of estimators contains in particular (i) the sample mean $(\rho(t) = t^2)$, (ii) the sample median $(\rho(t) = |t|)$, and more generally, (iii) all maximum likelihood estimators $(\rho(t) = -\log f(t)$, where $f$ is the assumed density of the untranslated distribution). These ($M$)-estimators, as I shall call them for short, have rather pleasant asymptotic properties; sufficient conditions for asymptotic normality and an explicit expression for their asymptotic variance will be given. How should one judge the robustness of an estimator $T_n(x) = T_n(x_1, \cdots, x_n)$? Since ill effects from contamination are mainly felt for large sample sizes, it seems that one should primarily optimize large sample robustness properties. Therefore, a convenient measure of robustness for asymptotically normal estimators seems to be the supremum of the asymptotic variance $(n \rightarrow \infty)$ when $F$ ranges over some suitable set of underlying distributions, in particular over the set of all $F = (1 - \epsilon)\Phi + \epsilon H$ for fixed $\epsilon$ and symmetric $H$. On second thought, it turns out that the asymptotic variance is not only easier to handle, but that even for moderate values of $n$ it is a better measure of performance than the actual variance, because (i) the actual variance of an estimator depends very much on the behavior of the tails of $H$, and the supremum of the actual variance is infinite for any estimator whose value is always contained in the convex hull of the observations. (ii) If an estimator is asymptotically normal, then the important central part of its distribution and confidence intervals for moderate confidence levels can better be approximated in terms of the asymptotic variance than in terms of the actual variance. If we adopt this measure of robustness, and if we restrict attention to ($M$)-estimators, then it will be shown that the most robust estimator is uniquely determined and corresponds to the following $\rho:\rho(t) = \frac{1}{2}t^2$ for $|t| < k, \rho(t) = k|t| - \frac{1}{2}k^2$ for $|t| \geqq k$, with $k$ depending on $\epsilon$. This estimator is most robust even among all translation invariant estimators. Sample mean $(k = \infty)$ and sample median $(k = 0)$ are limiting cases corresponding to $\epsilon = 0$ and $\epsilon = 1$, respectively, and the estimator is closely related and asymptotically equivalent to Winsorizing. I recall the definition of Winsorizing: assume that the observations have been ordered, $x_1 \leqq x_2 \leqq \cdots \leqq x_n$, then the statistic $T = n^{-1}(gx_{g + 1} + x_{g + 1} + x_{g + 2} + \cdots + x_{n - h} + hx_{n - h})$ is called the Winsorized mean, obtained by Winsorizing the $g$ leftmost and the $h$ rightmost observations. The above most robust ($M$)-estimators can be described by the same formula, except that in the first and in the last summand, the factors $x_{g + 1}$ and $x_{n - h}$ have to be replaced by some numbers $u, v$ satisfying $x_g \leqq u \leqq x_{g + 1}$ and $x_{n - h} \leqq v \leqq x_{n - h + 1}$, respectively; $g, h, u$ and $v$ depend on the sample. In fact, this ($M$)-estimator is the maximum likelihood estimator corresponding to a unique least favorable distribution $F_0$ with density $f_0(t) = (1 - \epsilon)(2\pi)^{-\frac{1}{2}}e^{-\rho(t)}$. This $f_0$ behaves like a normal density for small $t$, like an exponential density for large $t$. At least for me, this was rather surprising--I would have expected an $f_0$ with much heavier tails. This result is a particular case of a more general one that can be stated roughly as follows: Assume that $F$ belongs to some convex set $C$ of distribution functions. Then the most robust ($M$)-estimator for the set $C$ coincides with the maximum likelihood estimator for the unique $F_0 \varepsilon C$ which has the smallest Fisher information number $I(F) = \int (f'/f)^2f dt$ among all $F \varepsilon C$. Miscellaneous related problems will also be treated: the case of non-symmetric contaminating distributions; the most robust estimator for the model of indeterminacy $\sup_t|F(t) - \Phi(t)| \leqq \epsilon$; robust estimation of a scale parameter; how to estimate location, if scale and $\epsilon$ are unknown; numerical computation of the estimators; more general estimators, e.g., minimizing $\sum_{i < j} \rho(x_i - T, x_j - T)$, where $\rho$ is a function of two arguments. Questions of small sample size theory will not be touched in this paper.

A bias correction to the Akaike information criterion, AIC, is derived for regression and autoregressive time series models. The correction is of particular use when the sample size is small, or when the number of fitted parameters is a moderate to large fraction of the sample size. The corrected method, called AICC, is asymptotically efficient if the true model is infinite dimensional. Furthermore, when the true model is of finite dimension, AICC is found to provide better model order choices than any other asymptotically efficient method. Applications to nonstationary autoregressive and mixed autoregressive moving average time series models are also discussed.

Simulated gastro-intestinal digestion is widely employed in many fields of food and nutritional sciences, as conducting human trials are often costly, resource intensive, and ethically disputable. As a consequence, in vitro alternatives that determine endpoints such as the bioaccessibility of nutrients and non-nutrients or the digestibility of macronutrients (e.g. lipids, proteins and carbohydrates) are used for screening and building new hypotheses. Various digestion models have been proposed, often impeding the possibility to compare results across research teams. For example, a large variety of enzymes from different sources such as of porcine, rabbit or human origin have been used, differing in their activity and characterization. Differences in pH, mineral type, ionic strength and digestion time, which alter enzyme activity and other phenomena, may also considerably alter results. Other parameters such as the presence of phospholipids, individual enzymes such as gastric lipase and digestive emulsifiers vs. their mixtures (e.g. pancreatin and bile salts), and the ratio of food bolus to digestive fluids, have also been discussed at length. In the present consensus paper, within the COST Infogest network, we propose a general standardised and practical static digestion method based on physiologically relevant conditions that can be applied for various endpoints, which may be amended to accommodate further specific requirements. A frameset of parameters including the oral, gastric and small intestinal digestion are outlined and their relevance discussed in relation to available in vivo data and enzymes. This consensus paper will give a detailed protocol and a line-by-line, guidance, recommendations and justifications but also limitation of the proposed model. This harmonised static, in vitro digestion method for food should aid the production of more comparable data in the future.

These famous lines by Thomas and Stevens are examples of what classical theorists, at least since Aristotle, have referred to as metaphor: instances of novel poetic language in which words like "mother," "go," and "night" are not used in their normal everyday sense. In classical theories of language, metaphor was seen as a matter of language, not thought. Metaphorical expressions were assumed to be mutually exclusive with the realm of ordinary everday language: everyday language had no metaphor, and metaphor used mechanisms outside the realm of everyday conventional language.

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say M 0 implies on a less restricted one M 1 . If T 0 and T 1 denote the goodness-of-fit test statistics associated to M 0 and M 1 , respectively, then typically the difference T d = T 0 − T 1 is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models M 0 and M 1 . As in the case of the goodness-of-fit test, it is of interest to scale the statistic T d in order to improve its chi-square approximation in realistic, that is, nonasymptotic and nonormal, applications. In a recent paper, Satorra (2000) shows that the difference between two SB scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are not available in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models M 0 and M 1 . A Monte Carlo study is provided to illustrate the performance of the competing statistics.

To improve patient care and facilitate clinical research, the International League Against Epilepsy (ILAE) appointed a Task Force to formulate a consensus definition of drug resistant epilepsy. The overall framework of the definition has two "hierarchical" levels: Level 1 provides a general scheme to categorize response to each therapeutic intervention, including a minimum dataset of knowledge about the intervention that would be needed; Level 2 provides a core definition of drug resistant epilepsy using a set of essential criteria based on the categorization of response (from Level 1) to trials of antiepileptic drugs. It is proposed as a testable hypothesis that drug resistant epilepsy is defined as failure of adequate trials of two tolerated, appropriately chosen and used antiepileptic drug schedules (whether as monotherapies or in combination) to achieve sustained seizure freedom. This definition can be further refined when new evidence emerges. The rationale behind the definition and the principles governing its proper use are discussed, and examples to illustrate its application in clinical practice are provided.

It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.These guidelines are intended for use by healthcare professionals who care for patients at risk for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), including specialists in infectious diseases, pulmonary diseases, critical care, and surgeons, anesthesiologists, hospitalists, and any clinicians and healthcare providers caring for hospitalized patients with nosocomial pneumonia. The panel's recommendations for the diagnosis and treatment of HAP and VAP are based upon evidence derived from topic-specific systematic literature reviews.

Interest in mindfulness and its enhancement has burgeoned in recent years. In this article, we discuss in detail the nature of mindfulness and its relation to other, established theories of attention and awareness in day-to-day life. We then examine theory and evidence for the role of mindfulness in curtailing negative functioning and enhancing positive outcomes in several important life domains, including mental health, physical health, behavioral regulation, and interpersonal relationships. The processes through which mindfulness is theorized to have its beneficial effects are then discussed, along with proposed directions for theoretical development and empirical research.

We develop a new edge detection algorithm that addresses two critical issues in this long-standing vision problem: (1) holistic image training, and (2) multi-scale feature learning. Our proposed method, holistically-nested edge detection (HED), turns pixel-wise edge classification into image-to-image prediction by means of a deep learning model that leverages fully convolutional neural networks and deeply-supervised nets. HED automatically learns rich hierarchical representations (guided by deep supervision on side responses) that are crucially important in order to approach the human ability to resolve the challenging ambiguity in edge and object boundary detection. We significantly advance the state-of-the-art on the BSD500 dataset (ODS F-score of 0.782) and the NYU Depth dataset (ODS F-score of 0.746), and do so with an improved speed (0.4 second per image) that is orders of magnitude faster than recent CNN-based edge detection algorithms.

The internationalization of activity theory in the 1980s and 1990s has taken place in the midst of sweeping changes in the political and economic systems of our planet. During a few months, the Berlin Wall came down and Nelson Mandela was freed from prison. Those were only two among the visible symbols of the transformations that continue to amaze the most sophisticated observers.

ABSTRACT There are at least a dozen linguistically significant dimensions of differences between illocutionary acts. Of these, the most important are illocutionary point, direction of fit, and expressed psychological state. These three form the basis of a taxonomy of the fundamental classes of illocutionary acts. The five basic kinds of illocutionary acts are: representatives (or assertives), directives, commissives, expressives, and declarations. Each of these notions is defined. An earlier attempt at constructing a taxonomy by Austin is defective for several reasons, especially in its lack of clear criteria for distinguishing one kind of illocutionary force from another. Paradigm performative verbs in each of the five categories exhibit different syntactical properties. These are explained. (Speech acts, Austin's taxonomy, functions of speech, implications for ethnography and ethnology; English.)

BACKGROUND: Abiraterone acetate, an androgen biosynthesis inhibitor, improves overall survival in patients with metastatic castration-resistant prostate cancer after chemotherapy. We evaluated this agent in patients who had not received previous chemotherapy. METHODS: In this double-blind study, we randomly assigned 1088 patients to receive abiraterone acetate (1000 mg) plus prednisone (5 mg twice daily) or placebo plus prednisone. The coprimary end points were radiographic progression-free survival and overall survival. RESULTS: The study was unblinded after a planned interim analysis that was performed after 43% of the expected deaths had occurred. The median radiographic progression-free survival was 16.5 months with abiraterone-prednisone and 8.3 months with prednisone alone (hazard ratio for abiraterone-prednisone vs. prednisone alone, 0.53; 95% confidence interval [CI], 0.45 to 0.62; P<0.001). Over a median follow-up period of 22.2 months, overall survival was improved with abiraterone-prednisone (median not reached, vs. 27.2 months for prednisone alone; hazard ratio, 0.75; 95% CI, 0.61 to 0.93; P=0.01) but did not cross the efficacy boundary. Abiraterone-prednisone showed superiority over prednisone alone with respect to time to initiation of cytotoxic chemotherapy, opiate use for cancer-related pain, prostate-specific antigen progression, and decline in performance status. Grade 3 or 4 mineralocorticoid-related adverse events and abnormalities on liver-function testing were more common with abiraterone-prednisone. CONCLUSIONS: Abiraterone improved radiographic progression-free survival, showed a trend toward improved overall survival, and significantly delayed clinical decline and initiation of chemotherapy in patients with metastatic castration-resistant prostate cancer. (Funded by Janssen Research and Development, formerly Cougar Biotechnology; ClinicalTrials.gov number, NCT00887198.).

The summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,717 new measurements from 869 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Most of the 120 reviews are updated, including many that are heavily revised. The is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete (both volumes) is published online on the website of the Particle Data Group () and in a journal. Volume 1 is available in print as the . A with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app. The 2024 edition of the Review of Particle Physics should be cited as: S. Navas et al. (Particle Data Group), Phys. Rev. D 110, 030001 (2024) © 2024 2024

The force exerted by unbroken surface waves on a cylindrical object, such asa pile, which extends from the bottom upward above the wave crest, is made upof two components, namely:A drag force proportional to the square of the velocity which may berepresented by a drag coefficient having substantially the same value as forsteady flow, andA virtual mass force proportional to the horizontal component of theaccelerative force exerted on the mass of water displaced by the pile. These relationships follow directly from wave theory and have been confirmedby measurements in the Fluid Mechanics Laboratory of the University ofCalifornia, Berkeley. The maximum force exerted by breakers or incipient breakers is impulsive innature, reaching a value much greater than that produced by unbroken waves butenduring for only a short time interval. This impulsive force represents theultimate development of the accelerative force and is produced by the steepwave front and large horizontal acceleration at the front of a breaker. Thisimpulsive force greatly exceeds the drag force computed from the particlevelocities of the breaker. The reader is cautioned that these preliminary results are applicable only tosingle piles without bracing and are likely to be modified somewhat wheremultiple piles are driven, one within the influence of the other or wheremultiple piles are connected by submerged bracing. This paper is essentially apreliminary report submitted at this time because of the current importance ofwave forces in the design of offshore structures. An extended series ofadditional experiments is planned for the near future. Theoretical Relationships For the sake of simplicity of treatment, the theory will be developed fromthe equations for waves of small amplitude. T.P.2846

Abstract Voluntary acts are preceded by electrophysiological “readiness potentials” (RPs). With spontaneous acts involving no preplanning, the main negative RP shift begins at about—550 ms. Such RPs were used to indicate the minimum onset times for the cerebral activity that precedes a fully endogenous voluntary act. The time of conscious intention to act was obtained from the subject's recall of the spatial clock position of a revolving spot at the time of his initial awareness of intending or wanting to move (W). W occurred at about—200 ms. Control experiments, in which a skin stimulus was timed (S), helped evaluate each subject's error in reporting the clock times for awareness of any perceived event. For spontaneous voluntary acts, RP onset preceded the uncorrected Ws by about 350 ms and the Ws corrected for S by about 400 ms. The direction of this difference was consistent and significant throughout, regardless of which of several measures of RP onset or W were used. It was concluded that cerebral initiation of a spontaneous voluntary act begins unconsciously. However, it was found that the final decision to act could still be consciously controlled during the 150 ms or so remaining after the specific conscious intention appears. Subjects can in fact “veto” motor performance during a 100–200-ms period before a prearranged time to act. The role of conscious will would be not to initiate a specific voluntary act but rather to select and control volitional outcome. It is proposed that conscious will can function in a permissive fashion, either to permit or to prevent the motor implementation of the intention to act that arises unconsciously. Alternatively, there may be the need for a conscious activation or triggering, without which the final motor output would not follow the unconscious cerebral initiating and preparatory processes.

It is increasingly necessary for researchers in all fields to write computer code, and in order to reproduce research results, it is important that this code is published. We present Jupyter notebooks, a document format for publishing code, results and explanations in a form that is both readable and executable. We discuss various tools and use cases for notebook documents.

Abstract The term “access” is frequently used by property and natural resource analysts without adequate definition. In this paper we develop a concept of access and examine a broad set of factors that differentiate access from property. We define access as “the ability to derive benefits from things,” broadening from property's classical definition as “the right to benefit from things.” Access, following this definition, is more akin to “a bundle of powers” than to property's notion of a “bundle of rights.” This formulation includes a wider range of social relationships that constrain or enable benefits from resource use than property relations alone. Using this framing, we suggest a method of access analysis for identifying the constellations of means, relations, and processes that enable various actors to derive benefits from resources. Our intent is to enable scholars, planners, and policy makers to empirically “map” dynamic processes and relationships of access.