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The understanding of neutron transport by Monte Carlo simulations led to major advancements towards precise interpretation of measurements. URANOS (Ultra Rapid Neutron-Only Simulation) is a free software package which has been developed in the last few years in cooperation with particle physics and environmental sciences, specifically for the purposes of cosmic-ray neutron sensing (CRNS). Its versatile user interface and input/output scheme tailored for CRNS applications offers hydrologists straightforward access to model individual scenarios and to directly perform advanced neutron transport calculations. The geometry can be modeled layer-wise, whereas in each layer a voxel geometry is extruded using a two-dimensional map from pixel images representing predefined materials and allowing for the construction of objects on the basis of pixel graphics without a three-dimensional editor. It furthermore features predefined cosmic-ray neutron spectra and detector configurations and also allows for a replication of important site characteristics of study areas – from a small pond to the catchment scale. The simulation thereby gives precise answers to questions like from which location do neutrons originate? How do they propagate to the sensor? What is the neutron's response to certain environmental changes? In recent years, URANOS has been successfully employed by a number of studies, for example, to calculate the cosmic-ray neutron footprint, signals in complex geometries like mobile applications on roads, urban environments and snow patterns.

Cosmic-ray neutron sensors buried below a snow pack provide a passive and autonomous monitoring technique of snow water equivalent (SWE). The effective neutron flux is attenuated inside the snow volume resulting in an inverse relationship between neutron intensity and the water equivalent of the snow column above the sensor. Neutrons are moderated and absorbed within the snow. Simultaneously, highly energetic cosmic rays produce further neutrons via spallation and evaporation processes. A comprehensive assessment of the neutron flux therefore requires multi-particle simulations which involve all relevant incoming particle species and transient particles from cosmic-ray showers which play a crucial role in neutron production.In our study, we used the Monte Carlo toolkit MCNP6 and validated its high-energy evaporation and spallation models against a measured data set of a neutron intensity profile in water. Based on that we fitted analytical functions to a large variety of simulation setups that describe the neutron intensity as a function of SWE and the moisture content of the soil below the sensor. Moreover, single-particle tracking revealed that the radial footprint of the method does not exceed few meters for detectors below thick snow layers. In the case of shallow snow, however, the diffusive long-range neutron flux in the atmosphere may penetrate through the snow pack to the buried sensor and thereby increases the influence of distant objects. Since the diffusive flux is further sensitive to the atmospheric water content, we developed an air humidity correction tailored to snow-buried neutron detectors.In general, the study aims at a holistic understanding of neutron production and transport processes in snow and the adjacent soil and air volumes in order to improve SWE monitoring by buried cosmic-ray neutron sensors and compares the simulation results to field data.

Accurate soil moisture (SM) measurements are key in hydrological observations and subsequent applications as it can greatly improve our understanding of soil processes. Recently, Cosmic-Ray Neutron Sensors (CRNS) have been recognized as a promising tool in SM monitoring due to its large footprint of several hectares and half a meter in depth. The key characteristic feature of the method is the exceptionally high moderation strength of hydrogen, which makes it nearly independent of the soil chemistry. CRNS has a great potential for irrigation and monitoring applications as to the non-invasive nature of the method and the low-maintenance, independently operating sensors. From the initial focus on hydrological research. CRNS are increasingly used in agriculture, e.g. irrigation management and soil moisture mapping, and have been integrated LoRa or NB-IoT networks for fast data transmission. Two projects are discussed which advance CRNS technologies into monitoring networks. COSMIC-SWAMP aims to provide an open-source water monitoring platform that integrates cosmic ray sensing data with FiWare Smart Application compliant analysis routines. Extending the existing Smart Water Management Platform (swamp-project.org), COSMIC-SWAMP supports dynamic processing of multiple co-located cosmic ray sensor streams to support automated and continuous growth forecasting using Wageningen/WOFOST crop models. ADAPTER involves the development and provision of innovative simulation-based information products. Addressing weather- and climate-resilient agriculture, daily and comprehensive long-term weather and soil information are made available to the agricultural community and all interested parties as easy-to-use analyses, data products, and information interfaces (adapter-projekt.org). The hydrological model ParFlow coupled to its Common Land Model (CLM) module provides a nationwide water balance prediction with 600 m spatial resolution. The data assimilation within the product platform is supported by an independent network of CRNS stations (12 agricultural locations in North Rhine-Westphalia). This contribution provides an overview about the current state of the art in CRNS methodological integration, neutron detection technology and development of IoT interfaces with measurements and forecasts focusing on the water balance, including groundwater.

In a temporal context, sure outcomes may yield higher utility than risky ones as they are available for the execution of plans before the resolution of uncertainty. By observing a disproportionate preference for certainty, empirical research points to a fundamental difference between riskless and risky utility. Chance Theory (CT) accounts for this difference and, in contrast to earlier approaches to separate risky and riskless utility, does not violate basic rationality principles like first-order stochastic dominance or transitivity. CT evaluates the lowest outcome of an act with the riskless utility v and the increments over that outcome, called chances, by subjective expected utility (EU) with a risky utility u. As a consequence of treating sure outcomes differently to risky ones, CT is able to explain the EU-paradoxes of Allais (Econometrica, 21(4): 503–546, 1953) that rely on the certainty effect, and also the critique to EU put forward by Rabin (Econometrica, 68(5): 1281–1292, 2000). Moreover, CT separates risk attitudes in the strong sense, captured entirely by u, from attitude towards wealth reflected solely through the curvature ofv.

Introduction The number of subjects infected with the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout the western hemisphere increased exponentially in the later months of 2020.With this increase in infection, the number of subjects requiring advanced ventilatory support increased concomitantly.We decided to compare the survival rates between coronavirus disease 2019 (COVID-19) subjects versus non-COVID-19 subjects undergoing intubation in the intensive care unit (ICU).We hypothesized that COVID-19 subjects would have lower rates of survival post-intubation. Methods We screened all subjects admitted to the adult critical care unit between January 2020and June 2020 to determine if they met the inclusion criteria.These subjects were required to be spontaneously ventilating upon admission and eventually required intubation.Subjects were selected from our electronic health record (EHR) system EPIC© (Epic Systems, Verona, WI) through a retrospectiveICU admission analysis.We identified and included 267 non-COVID-19 subjects and 56 COVID-19 subjects.Our primary outcome of interest was intubation-related mortality.We defined intubation mortality as unexpected death (within 48 hours of intubation).Our secondary outcomes were the length of stay in the ICU, length of time requiring ventilator support, and proportion of subjects requiring tracheostomy placement. Results Compared to non-coronavirus disease (COVID) subjects, COVID subjects were more likely to be intubated for acute respiratory distress.COVID subjects had longer stays in the ICU and longer ventilator duration than non-COVID subjects.COVID-positive subjects had a decreased hazard ratio for mortality (HR = 0.42, 95% CI: 0.20-0.87, P < 0.05) and increased chances of survival compared to non-COVID subjects. Conclusions We showed therates of intubation survival were no different between the COVID and non-COVID groups.We attribute this finding to intubation preparation, a multidisciplinary team approach, and having the most experienced provider lead the intubation process.

The present paper contributes to the controversy regarding gender differences in risk taking by investigating the impact of social comparison. Drawing on previous results from evolutionary biology, we argue that the social ranking is more important for men than for women, i.e. men (women) should focus more on relative (absolute) income. We develop a corresponding model of decision making under risk which predicts that risk taking is higher (lower) for positively (negatively) correlated risks than for uncorrelated risks and that this effect is stronger for men than for women. These predictions are confirmed by our first experiment. Building upon the first experiment, we show in a second experiment that we can make gender differences to appear or disappear by changing the social context in a systematic way. We conclude that social comparison and the correlation of risks may play an important role for the occurrence of gender differences in risk taking.

Theoretical and empirical findings suggest that individuals are sensitive to the observability of their actions and the downstream consequences of this observability. We connect three streams of literature (social preferences, behavior change, and social norms) to investigate the conditions for which these claims are valid. Across multiple high-powered studies, we examine the mechanisms through which observability of one’s actions affects pro-sociality, when and why it sometimes fails, and how to utilize social and economic incentives to enact behavior change. Our three main results are: (i) observability alone has very little positive effect and can even backfire; (ii) inequality aversion drives the observed backfiring of observability; (iii) increasing the salience of norms can mitigate unintended consequences and successfully increase pro-sociality. From a policy perspective, our results highlight the potential pitfalls of simple behavioral interventions.

BACKGROUND: The primary objective of this study was to employ a national database to evaluate the association of hospital urbanicity, urban versus rural, on mortality and length of hospital stay in patients hospitalized with acute respiratory failure. METHODS: We used the 2014 National Inpatient Sample database to evaluate the association of hospital urbanicity with (1) mortality and (2) prolonged hospital stay, defined as ≥ 75th percentile of the study population. We conducted a mixed-effects logistic regression analysis adjusting for sociodemographic variables and medical comorbidities. The random effect was hospital identification number (a unique value assigned in the NIS database for a specific institution). The odds ratio (OR), 95% CI, and P values were reported for each independent variable. RESULTS: The odds of inpatient mortality were significantly higher among urban teaching (OR 1.39, 95% CI 1.39–1.66, P CONCLUSIONS: This study supports the current body of literature that there are significant differences in patient populations among hospital type. Differences in health outcomes among different types of hospitals should be considered when designing policies to address health equity as these are unique populations with specific needs.

Understanding the neural correlates of risk-sensitive skin conductance responses can provide insights into their connection to emotional and cognitive processes. To provide insights into this connection, we studied the cortical correlates of risk-sensitive skin conductance peaks using electroencephalography. Fluctuations in skin conductance responses were elicited while participants played a threat-of-shock card game. Precise temporal information about skin conductance peaks was obtained by applying continuous decomposition analysis on raw electrodermal signals. Shortly preceding skin conductance peaks, we observed a decrease in oscillatory power in the frequency range between 3 and 17 Hz in occipitotemporal cortical areas. Atlas-based analysis indicated the left lingual gyrus as the source of the power decrease. The oscillatory power averaged across 3-17 Hz showed a significant negative relationship with the skin conductance peak amplitude. Our findings indicate a possible interaction between attention and threat perception.

Background. Intubations, especially in emergent settings, carry a high risk of hemodynamic instability with potentially catastrophic outcomes. Weight-based dosing of induction drugs can be inappropriately high for elective or emergent intubations and lead to hemodynamic instability. We hypothesized that monitoring the patient state index of SEDLine monitors (Masimo, Irvine, CA) would decrease the dose of induction drugs in the operating room during elective intubations. Methods. In this randomized study, SEDLine monitoring was provided to the intervention group but not to the control group during the induction of anesthesia in the operating room. Anesthesia providers in the intervention group were advised to titrate induction drugs to a Patient State Index of Results. We found no significant difference in propofol equivalents between groups ( P = .41). Using a SEDLine decreased the odds that a patient would require vasopressors during induction (odds ratio of .39 [95% confidence interval, .15–.98]). Conclusion. SEDLine monitoring during induction did not decrease dosing of the induction drugs etomidate and propofol but decreased the odds of receiving vasopressors. Further studies are warranted to assess the utility of processed electroencephalography in emergent intubations outside of the operating room.

Economic theory suggests that the deterrence of deviant behavior is driven by a combination of severity and certainty of punishment. This paper presents the first controlled experiment to study a third important factor that has been mainly overlooked: the swiftness of formal sanctions. We consider two dimensions: the timing at which the uncertainty about whether one will be punished is dissolved and the timing at which the punishment is actually imposed, as well as the combination thereof. By varying these dimensions of delay systematically, we find a surprising non-monotonic relation with deterrence: either no delay (immediate resolution and immediate punishment) or maximum delay (both resolution and punishment as much as possible delayed) emerge as most effective at deterring deviant behavior and recidivism. Our results yield implications for the design of institutional policies aimed at mitigating misconduct and reducing recidivism. Supplementary Information The online version contains supplementary material available at doi:10.1007/s11166-021-09352-x.

Purpose Sepsis remains amongst the most common causes of death worldwide. It has been described as a disease of the elderly, but contemporary data on risk factors and mortality is lacking. Materials and methods Multi-center longitudinal cohort study using non-public, state of California data from January 1, 2008 to September 31, 2015. Patients with sepsis, severe sepsis, and septic shock were identified using ICD-9-CM diagnosis and procedure codes with age subgroups of 18–44, 45–64, 65–74, 75–84, and >85 years old. Descriptive statistics and a single direct logistic regression model were used to present data on incidence and mortality and to identify independent factors associated with mortality. Results Of 30,282,159 total inpatient encounters, 20,358,569 met inclusion criteria and 1,566,306 met sepsis criteria. Conditions associated with mortality included metastatic cancer, age, liver disease, residing in a care facility, and a gastrointestinal source of infection as well as fungal infection. Mortality in the >85-year-old subgroup with septic shock was 45.7%, lower than previously reported. Conclusion Age remains an important sepsis risk factor, but other conditions correlated more closely with sepsis-associated death. Patients over 85 years of age suffering from septic shock may have a better chance of survival than previously thought.

The Surgical Care Improvement Project (SCIP) added the SCIP-Inf-10 measure to mandate that all surgical patients have perioperative temperature management to reduce surgical site infection. While the basis of this measure originated in colorectal surgery, we hypothesized that this would also apply to thoracic surgery patients.This was a retrospective single-center pilot study reviewing two years of thoracic surgery cases for the incidence and duration of hypothermia during the operation and surgical site infection occurring within 30 days. Hypothermia was defined as a core temperature of36° C. Results: A total of 317 patients were included in the study. Sixty-two percent of patients were identified as hypothermic. The average intraoperative temperature was 35.4°C ± 0.8°C in the hypothermic group and 36.4°C ± 0.3°C in the normothermic group. There were four surgical site infections in the study with three cases from the36°C group (p = 1). There was no difference in average post-anesthesia care unit length of stay between the groups. The average hospital length of stay was 5.5 ± 5.2 days for the hypothermic group and 8.6 ± 12.8 days for the normothermic group (p=0.0024).Perioperative hypothermia was common in thoracic surgery and did not have a negative impact on surgical site infection.

Background: Sepsis continues to be the leading cause of death in intensive care units and surgical patients comprise almost one third of all sepsis patients. Anemia is a modifiable risk factor for worse postoperative outcomes in sepsis patients. Here we aim to evaluate the association of preoperative anemia and postoperative mortality in sepsis patients undergoing exploratory laparotomy. Methods: The National Surgical Quality Improvement Program registry was used to query for preoperative sepsis patients undergoing exploratory laparotomy between 2014 and 2016. Preoperative hematocrit was stratified into 4 categories: ≥30% to polycythemia, Results: The unadjusted 30-day death rate was the highest for patients with preoperative hematocrit Conclusion: Preoperative anemia in sepsis patients undergoing surgery can lead to increased mortality, postoperative complications, and length of hospital stay. Diagnosing sepsis early in the hospital course can allow physicians more time to titrate anticoagulation medications and treat preoperative anemia.

Background: Predicting the mortality from post-operative sepsis remains a continuing problem. We built a statistical model using national data to predict mortality in patients who developed post-operative sepsis. Methods: This is a retrospective study using the American College of Surgeons National Quality Surgical Improvement Program database, in which we gathered data from adult patients between 2011 and 2016 who experienced postoperative sepsis. We designed a predictive model using multivariable logistic regression on a training set and validated the model on a separate test set. Results: There were 128,325 patients included in the final dataset, in which 18,499 (14.4%) died within 30-days of surgery. The model consisted of 10 covariates: American Society of Anesthesiologists Physical Status classification score, preoperative sepsis, age, chronic obstructive pulmonary disease, postoperative myocardial infarction, postoperative stroke, postoperative acute renal failure, transfusion requirement, and infection type. A point-based risk calculator was developed, which had an area under the receiver operating characteristics curve of 0.819 (95% confidence interval 0.814-0.823). Conclusion: Although further work is needed to confirm and validate our model on external datasets, our scoring system provides a novel way to measure mortality in septic post-operative patients.

BACKGROUND: A retrospective study was performed to evaluate factors associated with 30-d re-intubation following surgical aortic valve repair. We hypothesized a significant increase in the odds of re-intubation among patients with preoperative comorbidities. METHODS: The American College of Surgery National Surgical Quality Improvement Program database from 2007 to 2016 was used to evaluate demographic and clinical factors associated with 30-d re-intubation following surgical aortic valve repair. Multivariable logistic regression was used to report factors associated with 30-d re-intubation while controlling for various patient characteristics. RESULTS: The study population consisted of 5,766 adult subjects who underwent surgical aortic valve repair, of whom 258 (4.47%) were re-intubated within 30 d of surgery. The mean ± SD age was 69 ± 12.98 y, and 3,668 (63.6%) were male. The prevalence of diabetes mellitus, shortness of breath, poor functional status, COPD, congestive heart failure, hypertension, and bleeding disorder was higher among subjects who were re-intubated compared to those who were not (P < .05). Age, severe COPD, congestive heart failure, and bleeding disorder were associated with this outcome. CONCLUSIONS: Age, COPD, congestive heart failure, and bleeding disorder were associated with 30-d re-intubation in this surgical cohort. If surgical aortic valve repair is deemed non-emergent, patients should be optimized preoperatively and receive careful postoperative planning to reduce the risk of postoperative complications.

Purpose This performance improvement project was undertaken to reduce costly delays in first-case, operating room (OR) start times. Design Two Plan, Do, Study, Act (PDSA) cycles. Methods In PDSA 1, student nurses observed 30 patients' paths of travel from hospital entrance to OR and documented time spent at key stopping points. Directional signs were placed after PDSA 1. PDSA 2 consisted of an electronic medical record (EMR) review of pre- and postsignage cases (n = 492 and n = 538 respectively). Findings In the initial PDSA cycle (n = 30), one reason for delay was the time patients spent finding the preoperative area (POA). Signage was placed at strategic points noted to confuse patients. PDSA cycle 2 found median presignage POA arrival times (34 minutes) were significantly higher than postsignage POA arrival times (20 minutes) (U = 51,618.0, z = −16.934, P Conclusions Delayed wayfinding contributed to delayed OR starts but improved with appropriate signage.

State-ownership of commercial companies exists around the world, and it is important to understand its effect on financing and investment decisions. Empirically, firms that are partially state-owned (SOE) usually profit from easier access to capital. We propose a novel explanation for this: investors’ social preferences can affect capital allocation if SOEs are perceived as socially beneficial. In support of this we found that people attribute social benefits more to SOEs than to private firms, and their propensity to invest depends on this attitude. Further, in an incentivized modified stochastic public goods game, participants invested in risky options with positive externalities even when the aggregate of private return and externality was lower than the return of an investment option with only private returns. For the case of the EU, we discuss alternative explanations such as state guarantees and political lending in the light of regulations of state aid. We conclude that even if these regulations prohibit direct or indirect state aid for SOEs, state-ownership can affect capital allocation through investors’ social preferences.