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Objectives. To investigate what transpires at opioid overdoses where police administer naloxone and to identify the frequency with which concerns about police-administered naloxone are observed. Methods. We reviewed body-worn camera (BWC) footage of all incidents where a Tempe, Arizona police officer administered naloxone or was present when the Tempe Fire Medical Rescue (TFMR) administered it, from February 3, 2020 to May 7, 2021 (n = 168). We devised a detailed coding instrument and employed univariate and bivariate analysis to examine the frequency of concerns regarding police-administered naloxone. Results. Police arrived on scene before the TFMR in 73.7% of cases. In 88.6% of calls the individual was unconscious when police arrived, but 94.6% survived the overdose. The primary concerns about police-administered naloxone were rarely observed. There were no cases of improper naloxone administration or accidental opioid exposure to an officer. Aggression toward police from an overdose survivor rarely occurred (3.6%), and arrests of survivors (3.6%) and others on scene (1.2%) were infrequent. Conclusions. BWC footage provides a unique window into opioid overdoses. In Tempe, the concerns over police-administered naloxone are overstated. If results are similar elsewhere, those concerns are barriers that must be removed. (Am J Public Health. 2022;112(9):1326–1332. https://doi.org/10.2105/AJPH.2022.306918 )

PurposeUnlike protests against police brutality in the past (2014 and earlier), police officers responding to First Amendment-protected demonstrations in summer 2020 likely were wearing body-worn cameras(BWCs). This study seeks to understand police perceptions of the effects of BWCs when used in the George Floyd protests.Design/methodology/approachThe authors use survey data from 100 agencies with federally-funded BWCs to assess the prevalence of BWC deployment to George Floyd protests and perceived benefits and limitations of the technology within this unique context.FindingsAbout three-quarters of agencies encountered some level of demonstration/protest related to the killing of George Floyd, and the majority of those deployed BWCs during these demonstrations. Respondents indicated evidentiary value of footage was a key reason for doing so, and at least three preconditions for a civilizing effect were present.Originality/valueResearch has documented numerous benefits associated with BWCs, from reductions in use of force and citizen complaints to evidentiary value. However, the extent to which BWC benefits extend to public protests is unclear. The George Floyd protests represent an opportunity to understand the prevalence and usefulness of BWCs in policing public protests.

The opioid crisis is the most persistent, long-term public health emergency facing the United States, and available evidence suggests the crisis has worsened during the COVID-19 global pandemic. Naloxone is an effective overdose response that saves lives, but the drug does not address problematic drug use, addiction, or the underlying conditions that lead to overdoses. The opioid crisis is at its core a multidisciplinary, multisystem problem, and an effective response to the crisis requires collaboration across those various systems. This paper describes such a collaborative effort. The Tempe First-Responder Opioid Recovery Project is a multidisciplinary partnership that includes police officers, social workers, substance use peer counselors, public health professionals, police researchers, and drug policy/harm reduction researchers. The project, 10 months underway, trained and equipped Tempe (AZ) police officers to administer Narcan. In addition, a 24/7 in-person "Crisis Outreach Response Team" rapidly responds to any suspected overdose and offers follow-up support, referrals, and services to the individual (and loved ones) for up to 45 days after the overdose. We present preliminary project data including interviews with project managers, counselors, and police officers, descriptions of Narcan administrations in the field, and aggregate data on client service engagement. These data highlight the complexity of the opioid crisis, the collaborative nature of the Tempe project, and the importance of initiating a multidisciplinary, comprehensive response to effectively deal with the opioid problem.

Elastic meta-materials, which we will treat herein as synonymous with elastic micro-architected materials, derive their unique combination of properties from the fine scale geometry of their solid and void regions. Recent advances in additive manufacturing have made the fabrication of such micro-architected materials feasible, and have driven interest in their properties. We consider the class of elastic meta-materials whose micro-architectures are composed of a network of straight struts connected at nodes arranged within a repeating unit cell; the octet truss is one well-known example of such truss lattices. Heretofore, the majority of work characterizing such truss lattices has considered solid struts and has been based on rod theory, a simplification of continuum elasticity which is accurate in the limit of low relative densities. In this paper, we use full continuum theory, solved with finite element analysis on adaptively refined meshes, to characterize the elastic performance of seven truss lattices with cubic geometric symmetry, and whose struts and nodes are hollow; we consider a wide range of strut wall thicknesses and truss relative densities. Varying the wall thickness provides an additional dimension of control, so that stiffness and anisotropy can, to an extent, be decoupled from the relative density of a given truss lattice. We show that a truss’ stiffness can be increased at fixed relative density, with bend-dominated truss lattices showing significantly greater improvement than stretch-dominated designs. Increases in stiffness by a factor of greater than five are observed, and increases by a factor of 100 or more are obtainable. Bend-dominated structures with hollow struts can be found that are stiffer than stretch-dominated ones at nearly all relative densities, contradicting a common rule of thumb. For some trusses, including the octet truss, choosing the wall thickness appropriately allows one to obtain isotropic response over a large range of volume fractions. We use topology optimization to find maximally stiff multiscale structures comprised of micro-architected materials and find that all the trusses we consider perform similarly, with anisotropic trusses resulting in slightly stiffer structures for a given load.

Elastic meta-materials are those whose unique properties come from their micro-architecture, rather than, e.g., from their chemistry. The introduction of such architecture, which is increasingly able to be fabricated due to advances in additive manufacturing, expands the design domain and enables improved design, from the most complex multi-physics design problems to the simple compliance design problem that is our focus. Unfortunately, concurrent design of both the micro-scale and the macroscale is computationally very expensive when the former can vary spatially, particularly in three dimensions. Instead, we provide simple, accurate surrogate models of the homogenized linear elastic response of the isotruss, the octet truss, and the ORC truss based on high-fidelity continuum finite element analyses. These surrogate models are relatively accurate over the full range of relative densities, in contrast to analytical models in the literature, which we show lose accuracy as relative density increases. The surrogate models are also simple to implement, which we demonstrate by modifying Sigmund’s 99-line code to solve a three-dimensional, multiscale compliance design problem with spatially varying relative density. We use this code to generate examples in both two and three dimensions that illustrate the advantage of elastic meta-materials over structures with a single length scale, i.e., those without micro-architectures.

We are concerned with optimization of macroscale elastic structures that are designed utilizing spatially varying microscale metamaterials. The macroscale optimization is accomplished using gradient-based nonlinear topological optimization. But instead of using density as the optimization decision variable, the decision variables are the multiple parameters that define the local microscale metamaterial. This is accomplished using single layer feedforward Gaussian basis function networks as a surrogate models of the elastic response of the microscale metamaterial. The surrogate models are trained using highly resolved continuum finite element simulations of the microscale metamaterials and hence are significantly more accurate than analytical models e.g. classical beam theory . Because the derivative of the surrogate model is important for sensitivity analysis of the macroscale topology optimization , a neural network training procedure based on the Sobolev norm is described. Since the SIMP method is not appropriate for spatially varying lattices , an alternative method is developed to enable creation of void regions. The efficacy of this approach is demonstrated via several examples in which the optimal graded metamaterial outperforms a traditional solid structure.

The present paper focuses on solving partial differential equations in domains exhibiting symmetries and periodic boundary conditions for the purpose of homogenization. We show in a systematic manner how the symmetry can be exploited to significantly reduce the complexity of the problem and the computational burden. This is especially relevant in inverse problems, when one needs to solve the partial differential equation (the primal problem) many times in an optimization algorithm. The main motivation of our study is inverse homogenization used to design architected composite materials with novel properties which are being fabricated at ever increasing rates thanks to recent advances in additive manufacturing. For example, one may optimize the morphology of a two-phase composite unit cell to achieve isotropic homogenized properties with maximal bulk modulus and minimal Poisson ratio. Typically, the isotropy is enforced by applying constraints to the optimization problem. However, in two dimensions, one can alternatively optimize the morphology of an equilateral triangle and then rotate and reflect the triangle to form a space filling D 3 symmetric hexagonal unit cell that necessarily exhibits isotropic homogenized properties. One can further use this D 3 symmetry to reduce the computational expense by performing the “unit strain” periodic boundary condition simulations on the single triangle symmetry sector rather than the six fold larger hexagon. In this paper we use group representation theory to derive the necessary periodic boundary conditions on the symmetry sectors of unit cells. The developments are done in a general setting, and specialized to the two-dimensional dihedral symmetries of the abelian D 2 , i.e. orthotropic, square unit cell and nonabelian D 3 , i.e. trigonal, hexagon unit cell. We then demonstrate how this theory can be applied by evaluating the homogenized properties of a two-phase planar composite over the triangle symmetry sector of a D 3 symmetric hexagonal unit cell.

We validate the predicted performance of new lattice materials that are stiff despite appearing to violate the Maxwell criterion., Materials with a stochastic microstructure, like foams, typically exhibit low mechanical stiffness, whereas lattices with a designed microarchitecture often show notably improved stiffness. These periodic architected materials have previously been designed by rule, using the Maxwell criterion to ensure that their deformation is dominated by the stretching of their struts. Classical designs following this rule tend to be anisotropic, with stiffness depending on the load orientation, but recently, isotropic designs have been reported by superimposing complementary anisotropic lattices. We have designed stiff isotropic lattices de novo with topology optimization, an approach based on continuum finite element analysis. Here, we present results of experiments on these lattices, fabricated by additive manufacturing, that validate predictions of their performance and demonstrate that they are as efficient as those designed by rule, despite appearing to violate the Maxwell criterion. These findings highlight the enhanced potential of topology optimization to design materials with unprecedented properties.

Background Opioid use has emerged as a significant public health crisis in cities across the United States. In Arizona, opioid overdose deaths increased by 65% from 2016 to 2018, leading the Governor of Arizona to declare a State of Emergency. Because police are often the first to arrive at the scene of an overdose, officers are central to an effective response to the opioid crisis in Arizona and elsewhere. However, many police officers do not carry naloxone, which can immediately reverse the life-threatening effects of an opioid overdose. Few studies examine officer perceptions of opioid use or their willingness to carry and administer naloxone. The degree to which officers accept this public health responsibility remains unclear. Methods The authors administered two waves of a survey to patrol officers in the Tempe (AZ) Police Department. The officers completed wave 1 approximately three months before the start of a program that trained and outfitted patrol officers with naloxone. Officers completed wave 2 of the survey several months after the program started. Relying on the Opioid Overdose Knowledge (OOKS), Competence, Concerns, and Attitudes (OOAS) of People who Overdose, and Naloxone-Related Risk Compensation Beliefs (NaRRC-B) scales, the survey captures officer attitudes regarding opioid use, willingness to carry and administer naloxone, and perceptions of their role in responding to the opioid crisis. Results At wave 1, officers conveyed moderate levels of confidence in recognizing an overdose and providing life-saving care. Officers indicated strong support for carrying naloxone and responding to opioid overdoses, and they recognized the value of treatment for users. At wave 2, officers reported significantly greater confidence and competence in responding to overdoses, and their support for carrying naloxone also increased. Both before and after program start, there was little variation in attitudes across gender, race/ethnicity, education, and length of service. Conclusion Officers accept this public health responsibility as part of their mission. Given that officers are frequently first on scene at overdoses and a matter of seconds can determine life or death, police-led naloxone programs will save lives in Tempe and elsewhere.

Electrochemical systems such as fuel cells, flow batteries, and electrochemical reactors are prevalent in industry, but few tools for their numerical design and optimization exist. Controlling fluid flow, active species distribution, and mass transport in the electrode has a dramatic impact on power and efficiency. However, this control is often limited to changing a quasi-two-dimensional flowfield and selecting bulk properties of a monolithic porous material electrode like carbon felt or paper. This can lead to non-uniform reaction rates, underutilized regions of the flow cell, and can limit the ultimate performance of the devices. To address these limitations, we propose using electrodes composed of a micro-architected variable porosity medium. As a specific example, we enable variable porosity by leveraging advances in the additive manufacture of microscale iso-truss lattices. We employ physics-based homogenization of the governing microscopic, continuum transport equations to develop a descriptive model and enable the design of this variable porosity electrode. Our tool is used to generate optimized architectures which are predicted to outperform monolithic electrodes when used in a standard flow-through configuration. We conclude by demonstrating how the optimal porosity distribution changes to retain the performance benefits as the electrode is scaled beyond benchtop-experiments LLNL-ABS- 810799 This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Using three design fields we develop an optimization environment that can simultaneously optimize material, shape and topology. We use the implicit representation of the boundaries with level-set functions that define the shape and topology. Differentiable R-functions allow us to combine these shapes and topology descriptions with Boolean operations. Additionally, we incorporate design dependent-stiffness materials with another design field. Notably, this framework accommodates design dependent loads, has the ability to introduce holes, and ensures the satisfaction of optimality criteria. It builds upon the fictitious domain, ersatz material, material interpolation and level-set methods. It also borrows from parameterized density-based topology optimization methods. Since analytical sensitivities can be computed, we use efficient nonlinear programming algorithms to update the design instead of the Hamilton–Jacobi’s scheme of level-set methods. We illustrate the features of our framework by designing a cantilever beam with octet truss microlattice, a dam with design-dependent loads, and a composite clevis plate.

Advances in additive manufacturing processes have made it possible to build mechanical metamaterials with bulk properties that exceed those of naturally occurring materials. One class of these metamaterials is structural lattices that can achieve high stiffness to weight ratios. Recent work on geometric projection approaches has introduced the possibility of optimizing these architected lattice designs in a drastically reduced parameter space. The reduced number of design variables enables application of a new class of methods for exploring the design space. This work investigates the use of Bayesian optimization, a technique for global optimization of expensive non-convex objective functions through surrogate modeling. We utilize formulations for implementing probabilistic constraints in Bayesian optimization to aid convergence in this highly constrained engineering problem, and demonstrate results with a variety of stiff lightweight lattice designs.

In this short note, we use topology optimization to design multi-phase isotropic three-dimensional composite materials with extremal combinations of isotropic thermal expansion and bulk modulus. In so doing, we provide evidence that the theoretical bounds for this combination of material properties are optimal. This has been shown in two dimensions, but not heretofore in three dimensions. We also show that restricting the design space by enforcing material symmetry by construction does not prevent one from obtaining extremal designs.

There are several classes of operators on graphs to consider in deciding on a collection of building blocks for graph algorithms. One class involves traditional graph operations such as breadth first or depth first search, finding connected components, spanning trees, cliques and other sub graphs, operations for editing graphs and so on. Another class consists of linear algebra operators where the matrices somehow depend on a graph. It is the latter class of operators that this paper addresses. We describe a least squares formulation on graphs that arises naturally in problems of ranking, distributed clock synchronization, social choice, arbitrage detection, and many other applications. The resulting linear systems are analogous to Poisson's equations. We show experimental evidence that some iterative methods that work very well for continuous domains do not perform well on graphs whereas some such methods continue to work well. By studying graph problems that are analogous to discretizations of partial differential equations (PDEs) one can hope to isolate the specific computational obstacles that graph algorithms present due to absence of spatial locality. In contrast, such locality is inherent in PDE problems on continuous domains. There is also evidence that PDE based methods may suggest improvements suitable for implementation on graphs.

Random number sequences are used in a wide range of applications such as simulation, sampling, numerical analysis, cryptography, and recreation. The quality of random number sequences is critical to the correctness of these applications. Many statistical tests have been developed to test various characteristics of random number generators such as randomness, independence, uniformity, etc. Most of them are based on testing on a single sequence. When multiple sequences are employed in an application, their potential correlations are also concerned. In this paper, we explore the techniques of using the Minkowski functionals and their extensions, the Minkowski valuations, to study the mathematical morphology of two dimensional binary image generated by pair-wise random number sequences, and apply this method to describe and compare the properties of several well-known pseudo- and quasi-random number generators.