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Background: In urology, ureteral stents are used to treat obstructive diseases. Hematuria (54%), fever, discomfort, and lower urinary system symptoms are the predominant symptoms related to ureteral stent. Aim: This article links stent symptoms to double-j width and length, as well as patient's height, weight, and body mass index (BMI). Ureteric Stent Symptoms Questionnaire (USSQ) was used to measure ureteral stent symptoms at 1st and 4th week of stent in situ as well as the 4th week after pigtail removal. Methods: A 200-patient prospective study, where patients were allocated into four groups following ureteral stent insertion depending on the stent characteristics. Those groups were: 4.8 Fr./26 cm (Group A), 4.8 Fr./28 cm (Group B), 6 Fr/26 cm (Group C), and 6 Fr/28 cm (Group D). Results: Men comprised 53.5% of 200 patients. Participants had an average age of 49 ± 15.5 years, height of 175 ± 8.94 cm, and BMI of 23.8 ± 7.6 cm. The laboratory results were identical between groups. At the first and fourth week, groups had similar urine symptoms, pain severity, health status and occupational activities. The difference in pain location was statistically significant. Group A had 82.4% renal back pain in the first week, whereas Group B had 68.8%, Group C 31.3% and Group D 62.5 (p = 0.04). At the fourth week, 64.7% of Group A patients reported kidney front pain, compared to 100% of Group B, 93.3% of Group C, and 100% of Group D (p = 0.04). There was statistical significance in the sexual activity of the patients. 24.4% of Group C patients stopped sexual activity before stent installation, compared to 10.6%, 8.3%, and 6.4% of the other groups (p = 0.03). A moderate percentage of patients had active sexual activity at week 4 (Group A: 7.8%, Group B: 5.8%, Group C: 8.2%, Group D: 4.1%), p = 0.83. In multivariate analysis, urinary catheter group, age, weight, height, and BMI did not significantly affect urine index score (UIS), pain index score (PIS), general health (GH), quality of work (QW), and quality of sex (QS). Conclusions: Despite various attempts to establish the best ureteral stent, the effect of double-j stent physical features on stent-related symptoms remained unknown. No verdict is conceivable without adequate empirical data. [ABSTRACT FROM AUTHOR]

Since the beginning of the COVID-19 pandemic, few studies have focused on crisis management of multiple services within one hospital over several waves of the pandemic. The purpose of this study was to provide an overview of the COVID-19 crisis response of a Parisian referral hospital which managed the first three COVID cases in France and to analyze its resilience capacities. Between March 2020 and June 2021, we conducted observations, semi-structured interviews, focus groups, and lessons learned workshops. Data analysis was supported by an original framework on health system resilience. Three configurations emerged from the empirical data: 1) reorganization of services and spaces; 2) management of professionals' and patients' contamination risk; and 3) mobilization of human resources and work adaptation. The hospital and its staff mitigated the effects of the pandemic by implementing multiple and varied strategies, which the staff perceived as having positive and/or negative consequences. We observed an unprecedented mobilization of the hospital and its staff to absorb the crisis. Often the mobilization fell on the shoulders of the professionals, adding to their exhaustion. Our study demonstrates the capacity of the hospital and its staff to absorb the COVID-19 shock by putting in place mechanisms for continuous adaptation. More time and insight will be needed to observe whether these strategies and adaptations will be sustainable over the coming months and years and to assess the overall transformative capacities of the hospital. [ABSTRACT FROM AUTHOR]

In general, it is not feasible to collect enough empirical data to capture the entire range of processes that define a complex system, either intrinsically or when viewing the system from a different geographical or temporal perspective. In this context, an alternative approach is to consider model transferability, which is the act of translating a model built for one environment to another less well‐known situation. Model transferability and adaptability may be extremely beneficial—approaches that aid in the reuse and adaption of models, particularly for sites with limited data, would benefit from widespread model uptake. Besides the reduced effort required to develop a model, data collection can be simplified when transferring a model to a different application context. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. Our study adapted a general Dynamic Bayesian Networks (DBN) of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Zostera marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer‐reviewed literature to identify which components needed adjustment including parameterization and quantification of the model and desired outcomes. We adopted both linguistic labels and scenario‐based elicitation to elicit from experts the conditional probabilities used to quantify the DBN. Following the proposed guidelines, the model structure of the general DBN was retained, but the conditional probability tables were adapted for nodes that characterized the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximize model reuse and minimize re‐development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts. [ABSTRACT FROM AUTHOR]

Species interactions drive ecosystem processes and are a major focus of global change research. Among the most consequential interactions expected to shift with climate change are those between insect herbivores and plants, both of which are highly sensitive to temperature. Insect herbivores and their host plants display varying levels of synchrony that could be disrupted or enhanced by climate change, yet empirical data on changes in synchrony are lacking. Using evidence of herbivory on herbarium specimens collected from the northeastern United States and France from 1900 to 2015, we provide evidence that plant species with temperature‐sensitive phenologies experience higher levels of insect damage in warmer years, while less temperature‐sensitive, co‐occurring species do not. While herbivory might be mediated by interactions between warming and phenology through multiple pathways, we suggest that warming might lengthen growing seasons for phenologically sensitive plant species, exposing their leaves to herbivores for longer periods of time in warm years. We propose that elevated herbivory in warm years may represent a previously underappreciated cost to phenological tracking of climate change over longer timescales. [ABSTRACT FROM AUTHOR]

We analytically derived and confirmed by empirical data the following three relations from the quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in the urban population data of France. The first is the relation between the time variation of the power law and the quasi-time-reversal symmetry in the large-scale range of a system that changes quasi-statically. The second is the relation between the time variation of the log-normal distribution and the quasi-time-reversal symmetry in the mid-scale range. The third is the relation among the parameters of log-normal distribution, non-Gibrat's property, and quasi-time-reversal symmetry. [ABSTRACT FROM AUTHOR]