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Mobile health technology and integration of patient-reported outcome measures into clinical interventions have the potential to transform patient care. Though patient-reported outcome measure management has been shown to improve outcomes in ambulatory care settings, few studies have examined remote patient-reported outcome measure assessment after major cancer surgery.A multiphased feasibility and usability study was designed. A mobile app-based postoperative symptom intervention tool was developed and evaluated by a focus group of bladder cancer patients and caregivers. Patients were prospectively accrued prior to cystectomy and asked to complete the daily mobile postoperative symptom intervention tool and wear biometric monitoring devices for 30 days post discharge. Retention, postoperative symptom intervention tool completion, and usability were assessed. Exploratory analysis of daily symptoms and patient-generated health information correlated signals with postsurgical complications and hospital readmission.Fifteen patients with a median age of 72 years completed 78% of daily surveys over the 30-day recovery period. Average time to complete the postoperative symptom intervention tool was 152 seconds. All patients agreed that the daily survey was easy to use, and most reported it would be a better way to communicate with the care team about symptoms than calling the clinic. Frequency and severity of patient-reported symptoms appeared to cluster prior to or at the time of complication or unplanned health care encounters on visual-analogue mapping.Using smartphone and wearable technology to capture patient-reported symptoms and biometric data is feasible and rated as highly usable by bladder cancer patients after cystectomy. Symptom scores may signal developing complications and help clinicians identify postsurgical patients who may benefit from intervention.

We agree with Arocha that the common and exclusive focus on aggregate results of psychological studies creates problems. While a paradigm shift toward idiographic approaches or control theory might help, we argue that traditional approaches can accomplish more if measures of variability are taken seriously. We discuss three kinds of studies: within-person treatment studies, questionnaire-based studies, and replication studies. For each of these, we suggest ways to improve psychological meaningfulness by investigating variability surrounding aggregate results, without ending up in an either–or choice between aggregate results and separate, individual results.

To identify subpopulations of dual users of combustible and electronic cigarettes using current smoking and vaping behaviors.Secondary analysis of baseline data from a randomized controlled trial testing a smoking cessation intervention for dual users. Finite mixture modeling of frequency, quantity, and dependence on combustible and electronic cigarettes was used to identify classes. Demographics and additional smoking and vaping variables were used to further characterize the classes.United States.A total of 2896 adults who smoked weekly for the past year and vaped weekly for the past month.Self-report baseline measures assessed demographics and smoking and vaping behaviors and characteristics including days of use per week, frequency of use within a day, time to first use after waking, urges to smoke, smoking cessation motivation, self-efficacy to abstain from smoking, months since vaping initiation, reasons for initiating and maintaining vaping, and future plans to stop vaping.Eight probabilistic classes were identified and well-defined (relative entropy = 0.95, Lo-Mendell-Rubin adjusted likelihood ratio test P 0.0001; class probabilities 0.89-0.97). In general, classes crossed two levels of smoking with four levels of vaping. The largest class (31%) had relatively high levels of smoking (72% daily, 56% 11+ cigarettes per day [CPD], 96% within 30 minutes of waking) and vaping (74% daily, 100% 20+ electronic-CPD, 74% 30 minutes). The next largest class (27%) had relatively high levels of vaping (93% daily, 100% 20+ electronic-CPD, 82% 30 minutes) and very low levels of smoking (28% daily, 12% 11+ CPD, 0% 30 minutes). The six smaller classes (3%-13%) also had distinct smoking and vaping behaviors. All eight classes exhibited distinguishing characteristics beyond current smoking and vaping behaviors.Dual users of combustible and electronic cigarettes are not a homogeneous population, having eight well-defined prospective subpopulations.

In inertial confinement fusion (ICF), deuterium-tritium (DT) fuel is brought to densities and temperatures where fusion ignition occurs. Mix of ablator material into the fuel may prevent ignition by diluting and cooling the fuel. MARBLE experiments at the National Ignition Facility (NIF) provide new insight into how mix affects thermonuclear burn. These experiments use laser-driven capsules containing deuterated plastic foam and tritium gas. Embedded within the foam are voids of known sizes and locations, which control the degree of heterogeneity of the fuel. Initially, the reactants are separated, with tritium concentrated in the voids and deuterium in the foam. During the implosion, mix occurs, leading to DT fusion reactions in the mixed region. Here we show that by measuring ratios of DT and deuterium-deuterium (DD) neutron yields for different macropore sizes and gas compositions, effects of mix heterogeneity on thermonuclear burn may be quantified and understood for the first time.

Objectives Caregivers of allogeneic hematopoietic stem cell transplant (HCT) cancer patients experience high caregiver burden and carry a significant amount of responsibility. Mindfulness has the potential to lessen caregiver burden by aiding in stress management. To date, no studies have examined the efficacy of mindfulness in reducing caregiver burden in this population. Based on our pilot study demonstrating initial feasibility and acceptability of FOCUS (Focusing On mindfulness for Caregivers Under Stress), this 3-arm randomized controlled trial aims to examine the efficacy of a 6-week mindfulness-based stress management program for allogeneic HCT caregivers. Hypotheses include that the FOCUS condition will have lower post-treatment caregiver burden and that patients of these caregivers will have better patient health outcomes compared to other treatment conditions. Method Eligible caregivers will be randomly assigned to one of three treatment conditions: FOCUS, Healthy Living (HL; active control), and Enhanced Care (EC; usual care). Caregivers in FOCUS and HL will participate in 6-week weekly individual treatment sessions and will be sent brief daily momentary interventions/messages. Caregivers in all conditions will complete daily diaries over the course of treatment. Patients of enrolled caregivers will be enrolled for assessments only. Participants will complete assessments at baseline, end of treatment, 2- and 6-months post-treatment. Biomarker data will be collected via hair cortisol concentrations from caregivers at baseline and 6 months post-treatment. Results Recruitment is ongoing. Conclusions The data collected from this study will provide evidence on the efficacy of mindfulness in alleviating HCT caregiver stress and impacting patient health outcomes. Trial registration The current study is registered in clinicaltrials.gov (NCT05078229); see https://clinicaltrials.gov/ct2/show/NCT05078229?term=christine+vinci&draw=2&rank=1.

Sophisticated numerical models that contain fluid interfaces rely upon interface evolution models to approximate the transition to turbulence near interfaces, in the presence of Rayleigh–Taylor (RTI) or Richtmyer–Meshkov (RMI) instability. Semi-analytical models have been developed in recent decades to predict the interface growth from an initial state into the nonlinear regime. Two of these models are considered in this study. They are the Goncharov and the z-models. Both of these interface models have strengths and weaknesses, which are examined here. Both of them have been implemented in the xRAGE compressible flow solver, which models fluid interfaces. The flow solver provides the fluids acceleration as a body force to the interface model. The purpose of such interface model is to evolve the early times of interface position as a subgrid model within a compressible flow simulation in order to then initialize a turbulence model. In this work, the interface models are assessed and compared for their evolution of RTI and RMI. The z-model performed better than the Goncharov model for all cases that were explored.

The Marble campaign on the National Ignition Facility investigates the effect of heterogeneous mix on thermonuclear burn for comparison to a probability distribution function (PDF) burn model. Marble utilizes plastic capsules filled with deuterated plastic foam and a fill gas containing tritium. As the capsules implode, the deuterium in the foam mixes with the tritium gas, and DT neutrons are produced as the shocks compress and heat the mixture. The yield of DT neutrons is dependent on the uniformity of the mix, with more heterogeneous mix producing fewer neutrons. In Marble, the heterogeneity of the mix is controlled by varying the diameter of voids introduced into the foam. The first NIF Marble campaign has been executed in which the Marble capsules were indirectly driven with a single strong shock using NIF hohlraums. The experiments produce a low-convergence, high-ion-temperature implosion. The ratio of DT to DD neutron yield is largely consistent with uniform atomic mix for fine-pore foam, and increases slightly with void diameter, contrary to 1D simulations using the PDF burn model. Recent 3D high-resolution simulations of similar experiments performed on the Omega Laser Facility suggest an explanation.

The engineered macro-pore foam provides a new way to study thermonuclear burn physics by utilizing capsules containing deuterated (D) foam and filling tritium (T) gas in the engineered macro-pores. The implosion of a thermonuclear capsule filled with an engineered macro-pore foam will be complex due to the interaction of a shock wave with the engineered macro-pores. It is our goal to quantify how substantially complex foam structures affect the shape of shock and bulk shock speed. A cylinder-shape shock tube experiment has been designed and performed at the Omega Laser Facility. In order to examine how a foam structure will affect shock propagation, we performed several tests varying (1) engineered macro-pore size, (2) average foam density, and (3) with/without neopentane (C5H12) gas. X-ray radiographic data indicate that shock speed through engineered macro-pore foams depends strongly on average foam density and less on pore size. Experimental shock propagation data helped guide two numerical simulation approaches: (1) a 2D simulation with homogenizing foams rather than explicitly simulating engineered macro-pores and (2) a 2D toroidal-pore approximation adopting a toroidal-tube geometry to model engineered macro-pores.

A two-length scale, second moment turbulence model (Reynolds averaged Navier-Stokes, RANS) is proposed to capture a wide variety of single-phase flows, spanning from incompressible flows with single fluids and mixtures of different density fluids (variable density flows) to flows over shock waves. The two-length scale model was developed to address an inconsistency present in the single-length scale models, e.g. the inability to match both variable density homogeneous Rayleigh-Taylor turbulence and Rayleigh-Taylor induced turbulence, as well as the inability to match both homogeneous shear and free shear flows. The two-length scale model focuses on separating the decay and transport length scales, as the two physical processes are generally different in inhomogeneous turbulence. This allows reasonable comparisons with statistics and spreading rates over such a wide range of turbulent flows using a common set of model coefficients. The specific canonical flows considered for calibrating the model include homogeneous shear, single-phase incompressible shear driven turbulence, variable density homogeneous Rayleigh-Taylor turbulence, Rayleigh-Taylor induced turbulence, and shocked isotropic turbulence. The second moment model shows to compare reasonably well with direct numerical simulations (DNS), experiments, and theory in most cases. The model was then applied to variable density shear layer and shock tube data and shows to be in reasonable agreement with DNS and experiments. The importance of using DNS to calibrate and assess RANS type turbulence models is also highlighted.

OBJECTIVES: To examine the association of acetabular dysplasia and osteoarthritis (OA) of the hip among elderly white women. METHODS: Pelvic radiographs from a sample of 165 white women aged 65 and above with radiographic hip OA and 88 white women aged 65 and above without radiographic changes of hip OA were read for evidence of acetabular dysplasia by a single trained investigator. Acetabular dysplasia was assessed using measurements of the centre edge angle and the acetabular depth, which are both reduced in this condition. Odds ratios for the association between acetabular dysplasia and hip OA were estimated using logistic regression analysis. RESULTS: Fourteen (3.4%) hips had a centre edge angle < 25 degrees, 46 (11.2%) hips had an acetabular depth of < 9 mm, and 54 (13.2%) hips had acetabular dysplasia defined as either of the above. Hips with OA had a small, but not statistically significant, increased prevalence of abnormal centre edge angle (odds ratio: 1.43; 95% confidence intervals: 0.46, 4.46), abnormal acetabular depth (1.47; 0.78, 2.77) and acetabular dysplasia (1.33; 0.74, 2.40). CONCLUSION: These results do not support the hypothesis that mild acetabular dysplasia accounts for a substantial proportion of hip OA in elderly white women. A study with a much larger sample size would be required to rule out a weak association between dysplasia and hip OA of the magnitude actually observed in our study.