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Motivating older adults to follow up with an outpatient clinician after discharge from emergency departments (ED) is beneficial yet challenging. We aimed to answer whether psychological needs for motivation and discrete emotions observed by care transition coaches would predict this behavioral outcome.Community-dwelling older adults following ED discharge were recruited from three EDs in two U.S. states. We examined home visit notes documented by coaches (N = 725). Retrospective chart reviews of medical records tracked participants' health care utilization for 30 days.Observed knowledge-based competence predicted higher likelihood of outpatient follow-up within 30 days, while observed sadness predicted a lower likelihood of follow-up within seven days following discharge. Moreover, participants who demonstrated happiness were marginally more likely to have an in-person follow-up within seven days, and those who demonstrated knowledge-based competence were more likely to have an electronic follow-up within 30 days.Knowledge-based competence and emotions, as observed and documented in coach notes, can predict older adults' subsequent outpatient follow-up following their ED-discharge.Intervention programs might encourage coaches to check knowledge-based competence and to observe emotions in addition to delivering the content. Coaches could also customize strategies for patients with different recommended timeframes of follow-up.

Purpose Burnout in healthcare can have serious consequences, as it decreases patient care quality. Recent studies have found pharmacy employees have high rates of burnout, but formalized pharmacy well-being programs are not reported in the literature. Methods We developed a departmental pharmacy well-being program and focused residency well-being program in October and July 2020, respectively. The program committees sent anonymous surveys to all pharmacy employees to identify opportunities to improve well-being. The feasibility and impact of ideas were assessed by committee members and presented to pharmacy leadership who endorsed and supported all proposed initiatives prior to implementation. Pharmacist distress scores were measured using the Well-Being Index (WBI). Results The WBI was completed by 49% of invited pharmacists (137 of 278) in November 2020 and 41% (116 of 283) in June 2021. There was a numerical improvement in mean (SD) WBI scores from 2.06 (2.47) in November 2020 to 1.52 (2.49) in June 2021 (P = 0.09). Pharmacy residents had significantly higher distress scores than nonresident pharmacists (P = 0.01). However, pharmacy resident scores improved by almost 50% between the 2 time points, from 4.43 (2.13) to 2.40 (2.42); P = 0.03. Conclusion The development of a system-wide pharmacy well-being program creates a structure to collect ideas from employees, implement well-being initiatives, measure burnout using a validated tool such as the WBI, and continue to build, evaluate, and adapt new interventions. Importantly, the program went beyond addressing individual needs and addressed institutional opportunities that impact well-being. This can serve as a model for other pharmacy departments looking to implement similar programs.

Background: Patient-reported outcome measures (PROMs) can help predict clinical outcomes and improve shared clinical decision-making discussions. There remains a paucity of research assessing how the use of PROMs may drive improved patient experience and patient activation. Methods: New foot and ankle patients completed PROMIS physical function (PF), pain interference (PI), and depression assessments. Patients were then randomized to viewing and discussing their PROMIS scores with their surgeon or not. Following the clinic visit, patients completed a series of Clinician & Group Survey–Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) questions and the Patient Activation Measure (PAM). Responses to the CG-CAHPS questions and PAM were compared between the 2 groups and after clustering on surgeon. Potential interaction effects by social deprivation were also explored. Results: After enrolling patients but removing those lost to follow-up or with missing data, 97 and 116 patients remained in the intervention control cohorts, respectively. No difference was found in CG-CAHPS responses nor PAM scores between the 2 groups ( P > .05). All surgeons were highly rated by all patients. When clustered by surgeon, intervention subjects were less likely to indicate “top box” scores for the understanding domain of the CG-CAHPS question (OR 0.51, P Conclusion: Highly rated foot and ankle surgeons who show and discuss PROM results may not improve patient experience or activation and may, in fact, decrease understanding or patient activation in select populations. Future work is needed to determine when PROM discussions are most beneficial and how best to present PROMs data, as we suspect that how the information was presented—and not the use of PROMs—resulted in our findings. Health literacy tools and/or communication training may better engage different patient groups regarding PROMs. Level of Evidence: Level I, randomized controlled trial.

This article proposes an approach, based on infinite Fourier series, to constructing tractable densities for the bivariate circular analogues of copulas recently coined ‘circulas’. As examples of the general approach, we consider circula densities generated by various patterns of nonzero Fourier coefficients. The shape and sparsity of such arrangements are found to play a key role in determining the properties of the resultant models. The special cases of the circula densities we consider all have simple closed-form expressions involving no computationally demanding normalizing constants and display wide-ranging distributional shapes. A highly successful model identification tool and methods for parameter estimation and goodness-of-fit testing are provided for the circula densities themselves and the bivariate circular densities obtained from them using a marginal specification construction. The modelling capabilities of such bivariate circular densities are compared with those of five existing models in a numerical experiment, and their application illustrated in an analysis of wind directions.

X-ray stereo digital image correlation (DIC) measurements were performed at 10 kHz on the internal surface of a jointed structure in a shock tube at a shock Mach number of 1.42 and compared with optical stereo DIC measurements on the outer, visible surface of the structure. The shock tube environment introduces temperature and density gradients in the gas through which the structure was imaged, resulting in spatial and temporal index of refraction variations. These variations cause bias errors in optical DIC measurements due to beam-steering but have minimal influence on x-ray DIC measurements. These results demonstrate the utility of time-resolved x-ray DIC measurements in complicated environments where optical measurements suffer severe errors and/or are precluded by lack of optical access.

With camera equipment becoming cheaper and computer processing power increasing exponentially, optical test methods are becoming ubiquitous in the mechanics and dynamics communities. However, unlike more traditional methods where the measurement response of interest is obtained directly from the sensor (e.g. an accelerometer directly provides an acceleration), image-based measurement techniques often require a non-trivial amount of post-processing to extract displacements and strains from a series of images. Using experimental images to develop and validate these post-processing algorithms can be a challenge; real images have a finite depth of field, they can have poor contrast, they can be noisy, there can be calibration errors, etc. It is advantageous to create synthetic images with which image processing algorithms can be investigated without the need to deal with all the complexity and cost involved in a real experiment. Synthetic images also provide access to a “true” analytical solution, which is typically not available in an experiment. However, many synthetic image generation tools are either bespoke research codes or built into commercial software, which can limit accessibility. Blender is a free and open-source 3D software package that supports scene modeling and rendering, among other features. It runs an underlying Python scripting engine, so activities such as building and deforming a mesh or rendering a series of images can be automated. For these reasons, Blender has the potential to be used more widely than current synthetic image tools, as well as perform more sophisticated analyses. While Blender was not designed for engineering purposes, this work will demonstrate Blender’s suitability for generating synthetic test images for digital image correlation, and show its accuracy is comparable to commercial synthetic image generation software packages.

The increasing global demand for sustainably-produced crops has led to a renewed interest in exploiting unprocessed rocks as soil amendments and fertilizers. Carbonatite rocks are of particular relevance because of their rapid weathering rates and diverse nutrient contents. However, there are insufficient data to support or refute their efficacy and to understand their mechanism(s) of action. Here, the effects of a carbonatite on two crops were assessed and compared to those of calcitic lime. Wheat and pea were repeatedly grown under a low-nutrient regime under greenhouse conditions and their development, biomass, and shoot nutrient content were measured. The effect of the carbonatite on soil CO2 evolution was also tested for wheat. Wheat grown with carbonatite produced 40% more shoot biomass and 50% more root biomass than plants grown with lime. There was a sharp reduction in specific root length (SRL), consistent with approximately 60% increases in shoot contents of N, P, K, and Mn. These effects were smaller for pea. For wheat, CO2 from the soil was 70% greater with lime than with carbonatite. We conclude that carbonatites can provide benefits to plants beyond serving as liming agents. In addition, root architecture and SRL appear to be useful traits for predicting plant responsiveness to carbonatite addition.

We assessed fidelity of delivery and participant engagement in the implementation of a community paramedic coach-led Care Transitions Intervention (CTI) program adapted for use following emergency department (ED) visits.The adapted CTI for ED-to-home transitions was implemented at three university-affiliated hospitals in two cities from 2016 to 2019. Participants were aged ≥60 years old and discharged from the ED within 24 hours of arrival. In the current analysis, participants had to have received the CTI. Community paramedic coaches collected data on program delivery and participant characteristics at each transition contact via inventories and assessments. Participants provided commentary on the acceptability of the adapted CTI. Using a multimethod approach, the CTI implementation was assessed quantitatively for site- and coach-level differences. Qualitatively, barriers to implementation and participant satisfaction with the CTI were thematically analyzed.Of the 863 patient participants, 726 (84.1%) completed their home visits. Cancellations were usually patient-generated (94.9%). Most planned follow-up visits were successfully completed (94.6%). Content on the planning for red flags and post-discharge goal setting was discussed with high rates of fidelity overall (95% and greater), while content on outpatient follow-up was lower overall (75%). Differences in service delivery between the two sites existed for the in-person visit and the first phone follow-up, but the differences narrowed as the study progressed. Participants showed a 24.6% increase in patient activation (i.e., behavioral adoption) over the 30-day study period (Community paramedic coaches delivered the adapted CTI with high fidelity across geographically distant sites and successfully facilitated participant engagement, highlighting community paramedics as an effective resource for implementing such patient-centered interventions.

This is the second part of a two-part contribution on modeling of the anisotropic elastic-plastic response of aluminum 7079 from an extruded tube. Part I focused on calibrating a suite of yield and hardening functions from tension test data; Part II concentrates on evaluating those calibrations. A rectangular validation specimen with a blind hole was designed to provide heterogeneous strain fields that exercise the material anisotropy, while at the same time avoiding strain concentrations near sample edges where Digital Image Correlation (DIC) measurements are difficult to make. Specimens were extracted from the tube in four different orientations and tested in tension with stereo-DIC measurements on both sides of the specimen. Corresponding Finite Element Analysis (FEA) with calibrated isotropic (von Mises) and anisotropic (Yld2004-18p) yield functions were also conducted, and both global force-extension curves as well as full-field strains were compared between the experiments and simulations. Specifically, quantitative full-field strain error maps were computed using the DIC-leveling approach proposed by Lava et al. The specimens experienced small deviations from ideal boundary conditions in the experiments, which had a first-order effect on the results. Therefore, the actual experimental boundary conditions had to be applied to the FEA in order to make valid comparisons. The predicted global force-extension curves agreed well with the measurements overall, but were sensitive to the boundary conditions in the nonlinear regime and could not differentiate between the two yield functions. Interrogation of the strain fields both qualitatively and quantitatively showed that the Yld2004-18p model was clearly able to better describe the strain fields on the surface of the specimen compared to the von Mises model. These results justify the increased complexity of the calibration process required for the Yld2004-18p model in applications where capturing the strain field evolution accurately is important, but not if only the global force-extension response of the elastic–plastic region is of interest.

In this Review Article, we discuss a range of soft x-ray power diagnostics at inertial confinement fusion (ICF) and pulsed-power fusion facilities. This Review Article describes current hardware and analysis approaches and covers the following methods: x-ray diode arrays, bolometers, transmission grating spectrometers, and associated crystal spectrometers. These systems are fundamental for the diagnosis of ICF experiments, providing a wide range of critical parameters for the evaluation of fusion performance.

Osteoarthritis (OA) is the most common orthopedic condition in dogs, characterized as the chronic, painful end-point of a synovial joint with limited therapeutic options other than palliative pain control or surgical salvage. Since the 1970s, radiography has been the standard-of-care for the imaging diagnosis of OA, despite its known limitations. As newer technologies have been developed, the limits of detection have lowered, allowing for the identification of earlier stages of OA. Identification of OA at a stage where it is potentially reversible still remains elusive, however, yet there is hope that newer technologies may be able to close this gap. In this article, we review the changes in the imaging of canine OA over the past 50 years and give a speculative view on future innovations which may provide for earlier identification, with the ultimate goal of repositioning the limit of detection to cross the threshold of this potentially reversible disease.

Background: Structural response measurements are challenging in aerodynamic testing environments due to high-speed requirements, facility vibrations, and the desire for non-intrusive measurements. Objective: This study uses stereo digital image correlation (DIC) to investigate the response of a jointed beam under aerodynamic loading in a shock tube. Methods: The incident shock subjects the beam to an impulsive frontal load followed by periodic transverse loading from vortex shedding. Several considerations necessary to realize high-precision are addressed: first, a hybrid stereo camera calibration accounted for tangential distortions when imaging through thick windows. Second, a measurement bias from Xenon flash-lamp light sources was identified and removed using laser illumination. Third, facility motion was mitigated by vibration isolation and appropriate signal filtering. Finally, aero-optical distortions from turbulence were removed using a low-order reconstruction. Results: The resulting displacement data has a noise floor of approximately ± 1 μm at 20 kHz sampling rate. The reduction of primary noise sources allows a transient structural response on the order of 10–40 μm to be quantified. The highest vibrations occurred when the vortex shedding frequency matched the beam’s natural frequency. Conclusion: the noise reduction techniques described allow for structural measurements requiring high-precision, non-intrusive displacement data to be performed in aerodynamic environments.

We introduce a general, flexible, parametric survival modelling framework which encompasses key shapes of hazard function (constant, increasing, decreasing, up-then-down, down-then-up), various common survival distributions (log-logistic, Burr type XII, Weibull, Gompertz), and includes defective distributions (i.e., cure models). This generality is achieved using four basic distributional parameters: two scale-type parameters and two shape parameters. Generalising to covariate dependence, the scale-type regression components correspond to accelerated failure time (AFT) and proportional hazards (PH) models. Therefore, this general formulation unifies the most popular survival models which allows us to consider the practical value of possible modelling choices for survival data. Furthermore, in line with our proposed flexible baseline distribution, we advocate the use of multi-parameter regression in which more than one distributional parameter depends on covariates - rather than the usual convention of having a single covariate-dependent (scale) parameter. While many choices are available, we suggest introducing covariates through just one or other of the two scale parameters, which covers AFT and PH models, in combination with a `power' shape parameter, which allows for more complex non-AFT/non-PH effects, while the other shape parameter remains covariate-independent, and handles automatic selection of the baseline distribution. We explore inferential issues in simulations, both with and without a covariate, with particular focus on evidence concerning the need, or otherwise, to include both AFT and PH parameters. We illustrate the efficacy of our modelling framework by investigating differences between treatment groups using data from a lung cancer study and a melanoma study. Censoring is accommodated throughout.

We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we have extolled the virtues of the "power generalized Weibull" (PGW) distribution as an attractive vehicle for univariate parametric survival analysis: it is a tractable, parsimonious, model which interpretably allows for a wide variety of hazard shapes and, when adapted (to give an adapted PGW, or APGW, distribution), covers a wide variety of important special/limiting cases. Here, we additionally observe a frailty relationship between a PGW distribution with one value of the parameter which controls distributional choice within the family and a PGW distribution with a smaller value of the same parameter. We exploit this frailty relationship to propose a bivariate shared frailty model with PGW marginal distributions: these marginals turn out to be linked by the so-called BB9 or "power variance function" copula. This particular choice of copula is, therefore, a natural one in the current context. We then adapt the bivariate PGW distribution, in turn, to accommodate APGW marginals. We provide a number of theoretical properties of the bivariate PGW and APGW models and show the potential of the latter for practical work via an illustrative example involving a well-known retinopathy dataset, for which the analysis proves to be straightforward to implement and informative in its outcomes. The novelty in this article is in the appropriate combination of specific ingredients into a coherent and successful whole.

Neutron time-of-flight (nTOF) detectors have been used on Sandia National Laboratories’ Z-Machine for inertial confinement fusion and magnetized liner fusion experiments to infer physics parameters including the apparent fuel-ion temperature, neutron yield, the magnetic-radius product (BR), and the liner rho-r. Single-paddle, dual-paddle, and co-axial scintillation nTOF detectors are used in axial lines-of-sight (LOS) and LOS that are 12° from the midplane. Detector fabrication, characterization, and calibration are discussed.

Ceramic phosphors have been used for non-contact, 2-dimensional temperature sensing in high strain and high temperature environments. The Novel Aerosol Deposition Technique was used to fabricate coatings of Dysprosium doped Yttrium Aluminum Garnet and Mg4F2GeO4:Mn phosphors. Preliminary microstructural/optical characterization has been conducted. Dysprosium doped Yttrium Aluminum Garnet coatings were found to contain both garnet and perovskite phases and had an as-sprayed crystallite size of 25-30 nm. The fast response time and thermal/environmental stability of the doped ceramic phosphors make them excellent materials for temperature measurements on surfaces such as rapidly rotating turbine components. The high density, robust, room temperature deposition of phosphors through the Aerosol Deposition process greatly improves the current state-of-the-art of non-contact temperature sensing

Our main, novel, result is that a certain non-central chi-squared mixture of non-central chi-squared distributions is itself a scaled non-central chi-squared distribution. From this and a link to a known result on a mixture representation for a scaled central chi-squared distribution, numerous further mixture results, both old and new, ensue. These include mixture results for central F, non-central F and Libby-Novick distributions. The main result involves distributions all with the same degrees of freedom; it is also extended to the case where the mixing non-central chi-squared distribution has degrees of freedom an even number larger than that of the conditional non-central chi-squared distribution, with further consequences pursued.

We consider a novel family of cumulative hazard functions (CHFs) controlled by a single shape parameter, which corresponds to proportionality on a certain scale, in such a way that the family is closed under inversion of the CHF and under frailty mixing using an appropriate mixing distribution. The latter leads to natural shared frailty models in the bivariate case. We also suggest how best to incorporate a second, complementary, shape parameter in order to obtain especially useful parametric models for survival and reliability analysis.

Digital Image Correlation (DIC) is a well-established, non-contact diagnostic technique used to measure shape, displacement and strain of a solid specimen subjected to loading or deformation. However, measurements using standard DIC can have significant errors or be completely infeasible in challenging experiments, such as explosive, combustion, or fluid-structure interaction applications, where beam-steering due to index of refraction variation biases measurements or where the sample is engulfed in flames or soot. To address these challenges, we propose using X-ray imaging instead of visible light imaging for stereo-DIC, since refraction of X-rays is negligible in many situations, and X-rays can penetrate occluding material. Two methods of creating an appropriate pattern for X-ray DIC are presented, both based on adding a dense material in a random speckle pattern on top of a less-dense specimen. A standard dot-calibration target is adapted for X-ray imaging, allowing the common bundle-adjustment calibration process in commercial stereo-DIC software to be used. High-quality X-ray images with sufficient signal-to-noise ratios for DIC are obtained for aluminum specimens with thickness up to 22.2 mm, with a speckle pattern thickness of only 80 μm of tantalum. The accuracy and precision of X-ray DIC measurements are verified through simultaneous optical and X-ray stereo-DIC measurements during rigid in-plane and out-of-plane translations, where errors in the X-ray DIC displacements were approximately 2–10 μm for applied displacements up to 20 mm. Finally, a vast reduction in measurement error—5–20 times reduction of displacement error and 2–3 times reduction of strain error—is demonstrated, by comparing X-ray and optical DIC when a hot plate induced a heterogeneous index of refraction field in the air between the specimen and the imaging systems. Collectively, these results show the feasibility of using X-ray-based stereo-DIC for non-contact measurements in exacting experimental conditions, where optical DIC cannot be used.

The idea of transforming one random variate to another with a more convenient density has been developed in the first half of the 20th century. In his thesis, Norman L. Johnson (1917–2004) develope...

Carbonatites are unusual alkaline rocks with diverse compositions. Although previous work has characterized the effects these rocks have on soils and plants, little is known about their impacts on local ecosystems. Using a deposit within the Great Lakes–St. Lawrence forest in northern Ontario, Canada, we investigated the effect of a carbonatite on soil chemistry and on the structure of plant and soil microbial communities. This was done using a vegetation survey conducted above and around the deposit, with corresponding soil samples collected for determining soil nutrient composition and for assessing microbial community structure using 16S/ITS Illumina Mi-Seq sequencing. In some soils above the deposit a soil chemical signature of the carbonatite was found, with the most important effect being an increase in soil pH compared with the non-deposit soils. Both plants and microorganisms responded to the altered soil chemistry: the plant communities present in carbonatite-impacted soils were dominated by ruderal species, and although differences in microbial communities across the surveyed areas were not obvious, the abundances of specific bacteria and fungi were reduced in response to the carbonatite. Overall, the deposit seems to have created microenvironments of relatively basic soil in an otherwise acidic forest soil. This study demonstrates for the first time how carbonatites can alter ecosystems in situ.

The Cauchy–Schlomilch transformation states that for a function f and a, b>0, the integral of f(x2) and af((ax−bx−1)2) over the interval [0,∞) are the same. This elementary result is used to evalua...

Integral membrane transporters play essential roles in the movement of substrates across biological membranes. One approach to produce transporters suitable for structural studies is to introduce mutations that reduce conformational flexibility and increase stability. However, it can be difficult to predict which mutations will result in a more stable protein. Previously, we stabilised the uric acid‐xanthine transporter, UapA, a member of the SLC23 family, through introduction of a single‐point mutation, G411V, trapping the protein in the inward‐facing conformation. Here, we attempted to stabilise the structurally related BOR1 transporter from Arabidopsis thaliana, a member of the SLC4 family, by introducing the equivalent substitution. We identified possible residues, P362 and M363, in AtBOR1, likely to be equivalent to the G411 of UapA, and generated four mutants, P362V or L and M363F or Y. Stability analysis using heated Fluorescent Size Exclusion Chromatography indicated that the M363F/Y mutants were more stable than the WT AtBOR1 and P362V/L mutants. Furthermore, functional complementation analysis revealed that the M363F/Y mutants exhibited reduced transport activity compared to the P362V/L and WT proteins. Purification and crystallisation of the M363F/Y proteins yielded crystals that diffracted better than WT (5.5 vs 7 Å). We hypothesise that the increased bulk of the F and Y substitutions limits the ability of the protein to undergo the conformational rearrangements associated with transport. These proteins represent a basis for future studies on AtBOR1., We transferred a stabilising substitution (G411V) in the membrane transporter UapA from Aspergillus nidulans to the structurally related BOR1 transporter from the model plant, Arabidopsis thaliana. Amino acid substitutions M363F and M363Y result in increased stability of AtBOR1 associated with reduced transport activity and thus reduced conformational flexibility. AtBOR1 M363 is likely equivalent to UapA G411. ​

Background Endometriosis (where endometrial-like tissue is found outside the uterus) affects ~ 176 million women worldwide and can lead to debilitating pelvic pain. There is an unmet need for new medical treatment options for endometriosis. Pelvic peritoneal mesothelial cells of women with endometriosis exhibit detrimental metabolic reprogramming that creates an environment favouring the formation and survival of endometriosis lesions. We have generated powerful preclinical proof-of-concept data to show that it is possible to correct this metabolic phenotype using dichloroacetate (DCA), a non-hormonal compound previously used to treat rare metabolic disorders in children. We plan a single-arm, open-label, single site exploratory clinical trial to inform the design of a future randomised controlled trial (RCT) to determine the efficacy of DCA for the treatment of endometriosis-associated pain. Methods We will recruit 30 women with endometriosis-associated pain over a 6-month period. All participants will receive approximately 6.25 mg/kg oral DCA capsules twice daily for 6 weeks, with a dose increase to approximately 12.5 mg/kg twice daily for a further 6 weeks if their pain has not been adequately controlled on this dose regime and side-effects are acceptable. If pain is adequately controlled with minimal side-effects, the lower dose will be continued for a further 6 weeks. The primary objective is to determine whether it is possible to achieve acceptable recruitment and retention rates within the defined exclusion and inclusion criteria. Secondary objectives are to determine the acceptability of the trial to participants, including the proposed methods of recruitment, treatment, follow-up frequency and number of questionnaires. The recruitment rate will be determined by the proportion of patients recruited from the pool of eligible women. The retention rate will be determined by the proportion of participants who attended the final trial visit. Discussion This is a feasibility study to explore effectiveness and acceptability of the proposed field methodology (recruitment, retention, study processes and compliance with treatment). The results will be used to inform the design of a future RCT. Trial registration ClinicalTrials.gov, NCT04046081 Registered 6 August 2019

Chemotherapy-induced peripheral neuropathy (CIPN) is widely recognized as a potentially severe toxicity that often leads to dose reduction or discontinuation of cancer treatment. Symptoms may persist despite discontinuation of chemotherapy and quality of life can be severely compromised. The clinical symptoms of CIPN, and the cellular and molecular targets involved in CIPN, are just as diverse as the wide variety of anticancer agents that cause peripheral neurotoxicity. There is an urgent need for extensive molecular and functional investigations aimed at understanding the mechanisms of CIPN. Furthermore, a reliable human cell culture system that recapitulates the diversity of neuronal modalities found in vivo and the pathophysiological changes that underlie CIPN would serve to advance the understanding of the pathogenesis of CIPN. The demonstration of experimental reproducibility in a human peripheral neuronal cell system will increase confidence that such an in vitro model is clinically useful, ultimately resulting in deeper exploration for the prevention and treatment of CIPN. Herein, we review current in vitro models with a focus on key characteristics and attributes desirable for an ideal human cell culture model relevant for CIPN investigations.

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. In this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level' the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental' DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errors were computed, even though there was no model form error, because the filtering effect of the DIC engine was neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental' DIC data were purposefully misaligned slightly from the FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In summary, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled' to the DIC data can meaningful, quantitative error maps be computed.

A line VISAR (Velocity Interferometer System for Any Reflector) has been designed and commissioned at the Sandia National Laboratory’s Z-machine. The instrument consists of an F/2 collection system, beam transport, and an interferometer table that contains two Mach–Zehnder type interferometers and an eight channel Gated Optical Imaging (GOI) system. The VISAR probe laser operates at the 532 nm wavelength, and the GOI bandpass is 540–600 nm. The output of each interferometer is passed to an optical streak camera with four selectable sweep speeds. The system is designed with three interchangeable optics modules to select a full field of view of 1 mm, 2 mm, or 4 mm. The optical beam transport system connects the target image plane to the interferometers and the gated optical imagers. The target is integrated into a sacrificial final optics assembly that is integral to the transport beamline.

The density power divergence, indexed by a single tuning parameter α, has proved to be a very useful tool in minimum distance inference. The family of density power divergences provides a generalized estimation scheme which includes likelihood-based procedures (represented by choice α=0 for the tuning parameter) as a special case. However, under data contamination, this scheme provides several more stable choices for model fitting and analysis (provided by positive values for the tuning parameter α). As larger values of α necessarily lead to a drop in model efficiency, determining the optimal value of α to provide the best compromise between model-efficiency and stability against data contamination in any real situation is a major challenge. In this paper, we provide a refinement of an existing technique with the aim of eliminating the dependence of the procedure on an initial pilot estimator. Numerical evidence is provided to demonstrate the very good performance of the method. Our technique has a general flavour, and we expect that similar tuning parameter selection algorithms will work well for other M-estimators, or any robust procedure that depends on the choice of a tuning parameter.

Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Finally, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.