Project description:We run an experimental study using sender-receiver games to evaluate how senders' willingness to lie to others compares to their willingness to tell hard truths, i.e., promote an outcome that the sender knows is unfair to the receiver without explicitly lying. Unlike in previous work on lying when it has consequences, we do not find that antisocial behavior is less frequent when it involves lying than when it does not. In fact, we find the opposite result in the setting where there is social contact between senders and receivers, and receivers have enough information to judge whether they have been treated unfairly. In this setting, we find that senders prefer to hide behind a lie and implement the antisocial outcome by being dishonest rather than by telling the truth. These results are consistent with social image costs depending on the social proximity between senders and receivers, especially when receivers can judge the kindness of the senders' actions.
Project description:Using electron spectroscopy, we have investigated nanoplasma formation from noble gas clusters exposed to high-intensity hard-x-ray pulses at ~5 keV. Our experiment was carried out at the SPring-8 Angstrom Compact free electron LAser (SACLA) facility in Japan. Dedicated theoretical simulations were performed with the molecular dynamics tool XMDYN. We found that in this unprecedented wavelength regime nanoplasma formation is a highly indirect process. In the argon clusters investigated, nanoplasma is mainly formed through secondary electron cascading initiated by slow Auger electrons. Energy is distributed within the sample entirely through Auger processes and secondary electron cascading following photoabsorption, as in the hard x-ray regime there is no direct energy transfer from the field to the plasma. This plasma formation mechanism is specific to the hard-x-ray regime and may, thus, also be important for XFEL-based molecular imaging studies. In xenon clusters, photo- and Auger electrons contribute more significantly to the nanoplasma formation. Good agreement between experiment and simulations validates our modelling approach. This has wide-ranging implications for our ability to quantitatively predict the behavior of complex molecular systems irradiated by high-intensity hard x-rays.
Project description:Time-resolved and ultrafast hard X-ray imaging, scattering and spectroscopy are powerful tools for elucidating the temporal and spatial evolution of complexity in materials. However, their temporal resolution has been limited by the storage-ring timing patterns and X-ray pulse width at synchrotron sources. Here we demonstrate that dynamic X-ray optics based on micro-electro-mechanical-system resonators can manipulate hard X-ray pulses on time scales down to 300 ps, comparable to the X-ray pulse width from typical synchrotron sources. This is achieved by timing the resonators with the storage ring to diffract X-ray pulses through the narrow Bragg peak of the single-crystalline material. Angular velocities exceeding 107 degrees s-1 are reached while maintaining the maximum linear velocity well below the sonic speed and material breakdown limit. As the time scale of the devices shortens, the devices promise to spatially disperse the temporal width of X-rays, thus generating a temporal resolution below the pulse-width limit.
Project description:Nowadays powerful X-ray sources like synchrotrons and free-electron lasers are considered as ultimate tools for probing microscopic properties in materials. However, the correct interpretation of such experiments requires a good understanding on how the beam affects the properties of the sample, knowledge that is currently lacking for intense X-rays. Here we use X-ray photon correlation spectroscopy to probe static and dynamic properties of oxide and metallic glasses. We find that although the structure does not depend on the flux, strong fluxes do induce a non-trivial microscopic motion in oxide glasses, whereas no such dependence is found for metallic glasses. These results show that high fluxes can alter dynamical properties in hard materials, an effect that needs to be considered in the analysis of X-ray data but which also gives novel possibilities to study materials properties since the beam can not only be used to probe the dynamics but also to pump it.
Project description:An accurate description of the interaction of intense hard X-ray pulses with heavy atoms, which is crucial for many applications of free-electron lasers, represents a hitherto unresolved challenge for theory because of the enormous number of electronic configurations and relativistic effects, which need to be taken into account. Here we report results on multiple ionization of xenon atoms by ultra-intense (about 1019 W/cm2) femtosecond X-ray pulses at photon energies from 5.5 to 8.3 keV and present a theoretical model capable of reproducing the experimental data in the entire energy range. Our analysis shows that the interplay of resonant and relativistic effects results in strongly structured charge state distributions, which reflect resonant positions of relativistically shifted electronic levels of highly charged ions created during the X-ray pulse. The theoretical approach described here provides a basis for accurate modeling of radiation damage in hard X-ray imaging experiments on targets with high-Z constituents.
Project description:Lacking disease-modifying osteoarthritis drugs (DMOADs) for knee osteoarthritis (KOA), Total Knee Arthroplasty (TKA) is often considered an important clinical outcome. Thus, it is important to determine the most relevant factors that are associated with the risk of TKA. The present study aims to develop a model based on a combination of X-ray trabecular bone texture (TBT) analysis, and clinical and radiological information to predict TKA risk in patients with or at risk of developing KOA. This study involved 4382 radiographs, obtained from the OsteoArthritis Initiative (OAI) cohort. Cases were defined as patients with TKA on at least one knee prior to the 108-month follow-up time point and controls were defined as patients who had never undergone TKA. The proposed TKA-risk prediction model, combining TBT parameters and Kellgren-Lawrence (KL) grades, was performed using logistic regression. The proposed model achieved an AUC of 0.92 (95% Confidence Interval [CI] 0.90, 0.93), while the KL model achieved an AUC of 0.86 (95% CI 0.84, 0.86; p < 0.001). This study presents a new TKA prediction model with a good performance permitting the identification of at risk patient with a good sensitivy and specificity, with a 60% increase in TKA case prediction as reflected by the recall values.
Project description:ObjectiveTo determine whether changes in preoperative osteoarthritis (OA) symptoms are associated with improvement after total knee replacement (TKR) and to identify predictors of clinically significant improvement.MethodsData on Osteoarthritis Initiative participants who were annually assessed and underwent TKR were included. T0 was the assessment prior to TKR while T-1 was the assessment prior to that. T+2 was the second assessment after TKR. We compiled data on the Western Ontario and McMaster Universities OA Index (WOMAC), OA-related symptoms, and radiographic severity. We defined clinically significant improvement as improvement in WOMAC total score ≥ to the minimal important difference (MID) (0.5 SD of mean change) between T0 and T+2 and also considered other definitions of improvement. Logistic regression models were performed to evaluate the relationship between improvement and preoperative measures.ResultsImproved (n = 211) compared to unimproved (n = 58) patients had greater worsening of their WOMAC pain (p = 0.002) and disability (p < 0.001) from T-1 to T0. Preoperative measures as predictors of improvement included higher WOMAC disability (OR = 1.08, p < 0.001), presence of chronic OA symptoms in the surgical knee (OR = 5.77, p = 0.033), absence of OA-related symptoms in the contralateral knee (OR = 9.25, p < 0.001), exposure to frequent knee bending (OR = 3.46, p = 0.040), and having a Kellgren-Lawrence x-ray grade of ≥2 in the contralateral knee (OR = 4.71, p = 0.010).ConclusionsMore than 75% of participants had improvement after TKR. Improved patients were more likely to have escalation of OA pain and disability prior to surgery than unimproved patients. Other preoperative measures predicted improvement after TKR.
Project description:This meta-analysis evaluated preoperative aspiration culture for diagnosing prosthetic joint infection (PJI) in total hip arthroplasty (THA) and total knee arthroplasty (TKA). The pooled sensitivity and specificity were 0.72 (95% confidence interval, 0.65 to 0.78) and 0.95 (0.93 to 0.97), respectively. Subgroup analyses revealed nonsignificant worse diagnostic performance for THA than for TKA (sensitivity, 0.70 versus 0.78; specificity, 0.94 versus 0.96). Preoperative aspiration culture has moderate to high sensitivity and very high specificity for diagnosing PJI.
Project description:Single particle diffractive imaging data from Rice Dwarf Virus (RDV) were recorded using the Coherent X-ray Imaging (CXI) instrument at the Linac Coherent Light Source (LCLS). RDV was chosen as it is a well-characterized model system, useful for proof-of-principle experiments, system optimization and algorithm development. RDV, an icosahedral virus of about 70 nm in diameter, was aerosolized and injected into the approximately 0.1 μm diameter focused hard X-ray beam at the CXI instrument of LCLS. Diffraction patterns from RDV with signal to 5.9 Ångström were recorded. The diffraction data are available through the Coherent X-ray Imaging Data Bank (CXIDB) as a resource for algorithm development, the contents of which are described here.
Project description:BackgroundIn January 2020, The Centers for Medicare and Medicaid Services approved total knee arthroplasty (TKA) to be performed in ambulatory surgery centers (ASCs). This study aims to develop a predictive model for targeting appropriate patients for ASC-based TKA.MethodsA retrospective review of 2266 patients (205 same-day discharge [SDD; 9.0%] and 2061 one-day length of stay [91.0%]) undergoing TKA at a regional medical center between July 2016 and September 2020 was conducted. Multiple logistic regression was used to evaluate predictors of SDD, as these patients represent those most likely to safely undergo TKA in an ASC.ResultsControlling for other demographics and comorbidities, patients with the following characteristics were at reduced odds of SDD: increased age (odds ratio [OR] = 0.935, P < .001), body mass index ≥35 (OR = 0.491, P = .002), female (OR = 0.535, P < .001), nonwhite race (OR = 0.456, P = .003), primary hypertension (OR = 0.710, P = .032), ≥3 comorbidities (OR = 0.507, P = .002), American Society of Anesthesiologists score ≥3 (OR = 0.378, P < .001). The model was deemed to be of adequate fit using the Hosmer and Lemeshow test (χ2 = 12.437, P = .112), and the area under the curve was found to be 0.773 indicating acceptable discrimination.ConclusionFor patients undergoing primary TKA, increased age, body mass index ≥35, female gender, nonwhite race, primary hypertension, ≥3 comorbidities, and American Society of Anesthesiologists score ≥3 decrease the likelihood of SDD. A predictive model based on readily available patient presentation and comorbidity characteristics may aid surgeons in identifying patients that are candidates for SDD or ASC-based TKA.