Cooperative Collision Avoidance at Intersections: Algorithms and Experiments

In this paper, we leverage vehicle-to-vehicle (V2V) communication technology to implement computationally efficient decentralized algorithms for two-vehicle cooperative collision avoidance at intersections. Our algorithms employ formal control theoretic methods to guarantee a collision-free (safe) system, whereas overrides are only applied when necessary to prevent a crash. Model uncertainty and communication delays are explicitly accounted for by the model and by the state estimation algorithm. The main contribution of this work is to provide an experimental validation of our method on two instrumented vehicles engaged in an intersection collision avoidance scenario in a test track

Emergence of complexity in hierarchically organized chiral particles

The structural complexity of composite biomaterials and biomineralized particles arises from the hierarchical ordering of inorganic building blocks over multiple scales. Although empirical observations of complex nanoassemblies are abundant, the physicochemical mechanisms leading to their geometrical complexity are still puzzling, especially for nonuniformly sized components. We report the self-assembly of hierarchically organized particles (HOPs) from polydisperse gold thiolate nanoplatelets with cysteine surface ligands. Graph theory methods indicate that these HOPs, which feature twisted spikes and other morphologies, display higher complexity than their biological counterparts. Their intricate organization emerges from competing chirality-dependent assembly restrictions that render assembly pathways primarily dependent on nanoparticle symmetry rather than size. These findings and HOP phase diagrams open a pathway to a large family of colloids with complex architectures and unusual chiroptical and chemical properties

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

The benefits of strength training on musculoskeletal system health: practical applications for interdisciplinary care

Global health organizations have provided recommendations regarding exercise for the general population. Strength training has been included in several position statements due to its multi-systemic benefits. In this narrative review, we examine the available literature, first explaining how specific mechanical loading is converted into positive cellular responses. Secondly, benefits related to specific musculoskeletal tissues are discussed, with practical applications and training programmes clearly outlined for both common musculoskeletal disorders and primary prevention strategies

Multi-scale Functional Nanomaterials for the Spectroscopic Detection of Ionizing Radiation and Characterization of Complex Structural Networks

Materials exhibiting unique properties in the nanoscale have potential to solve challenges that the macroscopic world faces. Translation of nanoscale effects into macroscopic solids is difficult because it requires the ordering of millions of precisely synthesized nanomaterials across multiple lengths scales without losing their spatial confinement. Multi-scale functional nanomaterials seek to combine the advantageous properties of nanoscale subunits with hierarchical organization to target specific applications. One such application that multi-scale functional nanomaterials can provide specific benefit is in the field of ionizing radiation detection. Nanoscale semiconductor materials can achieve high resolution gamma ray detection through efficient rates of multi-exciton generation and the suppression of optical phonons. Solid-state gamma ray detectors require macroscale thickness and pathways of organized semiconductors for charge percolation. This work advances our understanding and capability for nanoscale interactions with gamma rays through investigating new nanosemiconductor materials and approaches for assembling macroscale ordered solids from the nanoparticle subunits. Radiation detector performance was evaluated through the spectroscopic response of each material to a barium-133 gamma ray source, and measuring the peak resolution as the primary quantifiable metric. The first successful material approach utilized a robust aramid nanofiber matrix derived from Kevlar as a scaffold, and nanoparticles of cadmium telluride were grafted onto the polymer backbone to form efficient percolation networks. These aramid nanofiber composites measure tens-to-hundreds of micrometers in thickness, and successfully detect gamma rays with resolution < 1% at 81 keV, comparable to current commercial devices. The cadmium telluride/aramid nanofiber nanocomposites additionally demonstrated mechanical flexibility and resilience, with no degradation of performance up to 1000 bending cycles. Several formulations of aqueously colloidal lead telluride nanoparticles were investigated and developed to replace cadmium telluride in the nanocomposites in order to improve the materials’ stopping power and phonon suppression. The lead telluride/aramid nanofiber nanocomposites demonstrated gamma ray sensitivity, but the higher dielectric constant and limited device thickness constrained their performance with noise due to high capacitance. An alternative nanoparticle system was invented that showed lead telluride nanoparticles spontaneously self-assemble into macroscale transparent hydrogels consisting of a percolating nanoscale network. Graph theory was used as a tool to quantify network structure and develop correlations between electrolyte concentration/composition, the topological descriptor average nodal connectivity, and the rheological and electrical properties of the hydrogels. Functional detectors are prepared by reinforcing the spanning lead telluride networks with crosslinked polymers, which demonstrate scalability to several millimeters without exhibiting any apparent limitation to achieve thicknesses of several centimeters. The lead telluride polymer nanocomposites are shown to preserve the 3D nanoscale network in the macroscale devices and demonstrated resolved detection of the prominent 356 keV gamma ray from barium-133. The findings of this work prove the utility of nanosemiconductors for high-resolution gamma-ray detection, and provide a methodology for producing large-scale functional solids with conserved nanoscale features that retain desirable functionality. The goal of producing percolating networks of semiconducting nanoparticles that span macroscale volumes was demonstrated.PHDChemical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/174407/1/vecdrew_1.pd

Spanning Network Gels from Nanoparticles and Graph Theoretical Analysis of Their Structure and Properties

Gels self-assembled from colloidal nanoparticles (NPs) translate the size-dependent properties of nanostructures to materials with macroscale volumes. Large spanning networks of NP chains provide high interconnectivity within the material necessary for a wide range of properties from conductivity to viscoelasticity. However, a great challenge for nanoscale engineering of such gels lies in being able to accurately and quantitatively describe their complex non-crystalline structure that combines order and disorder. The quantitative relationships between the mesoscale structural and material properties of nanostructured gels are currently unknown. Here, it is shown that lead telluride NPs spontaneously self-assemble into a spanning network hydrogel. By applying graph theory (GT), a method for quantifying the complex structure of the NP gels is established using a topological descriptor of average nodal connectivity that is found to correlate with the gel’s mechanical and charge transport properties. GT descriptions make possible the design of non-crystalline porous materials from a variety of nanoscale components for photonics, catalysis, adsorption, and thermoelectrics.Hydrogels of lead telluride nanoparticles are structurally characterized using graph theory. The morphology of the gels is quantified, identifying the effect of various salt concentrations and compositions on the connectivity of the network structures. Significant influence by divalent cations on gel structure is observed. Relationships between the structural descriptors and viscoelastic and charge transport properties are evaluated.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/172992/1/adma202201313_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/172992/2/adma202201313-sup-0001-SuppMat.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/172992/3/adma202201313.pd

Challenges in the Development of drugs for Systemic Lupus Erythematosus: A Regulatory Perspective

Systemic lupus erythematosus (SLE) is a debilitating disease that affects at least 5 million people worldwide. Currently, there are limited approved treatment options for patients with SLE, and a great need remains for therapies to achieve important treatment goals such as reductions in flares, prevention of organ damage, clinical low disease activity or remission. The purpose of this article is to review the current health authority guidance for the development of drugs to treat SLE and discuss some of the challenges in the development of drugs for SLE from a regulatory perspective. Given the substantial number of failed late-stage clinical trials in this indication despite the inclusion of large numbers of subjects, reviewing the regulatory guidance and complexities surrounding the development of drugs for the treatment of SLE is crucial to understand the complexities of the disease itself and the challenges and limitations to conducting successful trials evaluating the impact of treatment of new agents in SLE. As only one new drug (belimumab, trade name BENLYSTA®) with a novel mechanism of action has been approved over the last six decades, the prescribing information for belimumab will be reviewed in the context of the guidance.https://doi.org/10.21423/jrs-v07delvecchi

Overload effect on the fatigue crack propagation in large-scale tubular joints

10.1111/ffe.12013Fatigue and Fracture of Engineering Materials and Structures365427-438FFES

High temperature nanocomposites with photonic group velocity suppression of thermal emission

Quenching of thermal emission above 0 K is an unusual material property, essential for future energy, transportation, and space technologies. Despite the great effort invested, nearly complete quenching of thermal radiation rather than some reduction of its flux has only been achieved at low temperatures (below 373 K) and in narrow spectral windows using complex techniques suitable only for small scale objects. In this work, we present a light and flexible composite material that can suppress propagating photonic modes and, in this way, quench thermal radiation while preserving heat transfer (by thermal conduction) at a room and higher temperature below 600 K. This has been achieved by altering the local photonic density of states and consequentially the thermal properties of carbon nanotubes forming a percolating nanofiber network with a thermostable polymeric matrix

Hydrogel Containing Nanoparticle-Stabilized Liposomes for Topical Antimicrobial Delivery

Adsorbing small charged nanoparticles onto the outer surfaces of liposomes has become an effective strategy to stabilize liposomes against fusion prior to “seeing” target bacteria, yet allow them to fuse with the bacteria upon arrival at the infection sites. As a result, nanoparticle-stabilized liposomes have become an emerging drug delivery platform for treatment of various bacterial infections. To facilitate the translation of this platform for clinical tests and uses, herein we integrate nanoparticle-stabilized liposomes with hydrogel technology for more effective and sustained topical drug delivery. The hydrogel formulation not only preserves the structural integrity of the nanoparticle-stabilized liposomes, but also allows for controllable viscoeleasticity and tunable liposome release rate. Using Staphylococcus aureus bacteria as a model pathogen, we demonstrate that the hydrogel formulation can effectively release nanoparticle-stabilized liposomes to the bacterial culture, which subsequently fuse with bacterial membrane in a pH-dependent manner. When topically applied onto mouse skin, the hydrogel formulation does not generate any observable skin toxicity within a 7-day treatment. Collectively, the hydrogel containing nanoparticle-stabilized liposomes hold great promise for topical applications against various microbial infections