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The use of vegetation in cities is one of the most promising strategies for urban climate change adaptation and mitigation. Tree shade influences heat storage from surfaces reducing long wave radiation emission which directly affects people. People 's heat perception depends more on insolation and the temperature of surrounding objects than on air temperature itself. There is a need for analyzes that include the combined effects of physical and human variables on thermal comfort, as well as location-based studies to address its climatic and social conditions. In order to compare the effect of the trees on microenvironmental temperature and perceived thermal comfort, we measured physical parameters and performed structured interviews on three downtown streets of Montevideo, Uruguay, which had sections with and without trees on four dates during the summer. Generally, people surveyed under both treatments stated they did not feel fully comfortable due to summer heat, but the proportion of people who stated feeling in thermal comfort under tree shade was more than double than the unshaded sections.The seasonal ARIMA analysis supported that the tree shade reduced the microenvironmental temperature by its effect on radiant temperature. By using a statistical decision tree methodology that combines all the variables in the same analysis, we found a greater impact of physical variables than personal variables on people's thermal comfort and thermal preferences. We also identified gender as a significant variable that affects people's thermal preferences, where 46.4 % of females preferred a slightly colder environment.

BackgroundHealthcare coverage has been shown to have implications in the prevalence of coronary artery disease. We explore the impact of lack of healthcare coverage on ischemic heart disease (IHD) mortality in the US.MethodsWe obtained county-level IHD mortality and healthcare coverage data from the CDC databases for a total of 3,119 US counties. The age-adjusted prevalence of current lack of health insurance among individuals aged 18 to 64 years were obtained for the years 2018 and 2019 and were placed into four quartiles. First (Q1) and fourth quartile (Q4) had the least and highest age-adjusted prevalence of adults without health insurance, respectively. IHD mortality rates, adjusted for age through the direct method, were obtained for the same years and compared among quartiles. Ordinary least squares (OLS) regression for each demographic variable was conducted with the quartiles as an ordinal predictor variable and the age-adjusted mortality rate as the outcome variable.ResultsWe identified a total of 172,942 deaths related to ischemic heart disease between 2018 and 2019. Overall AAMR was higher in Q4 (92.79 [95% CI, 92.35-93.23]) compared to Q1 (83.14 [95% CI, 82.74-83.54]), accounting for 9.65 excess deaths per 100,000 person-years (slope = 3.47, p = 0.09). Mortality rates in Q4 for males (126.20 [95% CI, 125.42-126.98] and females (65.57 [95% CI, 65.08-66.05]) were higher compared to Q1 (115.72 [95% CI, 114.99-116.44] and 57.48 [95% CI, 57.04-57.91], respectively), accounting for 10.48 and 8.09 excess deaths per 100,000 person-years for males and females, respectively. Similar trends were seen among Hispanic and non-Hispanic populations. Northeastern, Southern, and Western regions had higher AAMR within Q4 compared to Q1, with higher prevalence of current lack of health insurance accounting for 49.2, 8.15, and 29.04 excess deaths per 100,000 person-years, respectively.ConclusionA higher prevalence of adults without healthcare coverage may be associated with increased IHD mortality rates. Our results serve as a hypothesis-generating platform for future research in this area.

Characterizing fission products in uranium dioxide nuclear fuel is important for predicting its long-term properties. Here, machine learning is used to mine microscopy images of precipitates and nanoscale gas bubbles in high-burn-up fuels, providing detailed structural insight of nanoscale fission products.

Abstract The authors developed an artificial intelligence (AI)-based algorithm for the design and optimization of a nuclear reactor core based on a flexible geometry and demonstrated a 3× improvement in the selected performance metric: temperature peaking factor. The rapid development of advanced, and specifically, additive manufacturing (3-D printing) and its introduction into advanced nuclear core design through the Transformational Challenge Reactor program have presented the opportunity to explore the arbitrary geometry design of nuclear-heated structures. The primary challenge is that the arbitrary geometry design space is vast and requires the computational evaluation of many candidate designs, and the multiphysics simulation of nuclear systems is very time-intensive. Therefore, the authors developed a machine learning-based multiphysics emulator and evaluated thousands of candidate geometries on Summit, Oak Ridge National Laboratory’s leadership class supercomputer. The results presented in this work demonstrate temperature distribution smoothing in a nuclear reactor core through the manipulation of the geometry, which is traditionally achieved in light water reactors through variable assembly loading in the axial direction and fuel shuffling during refueling in the radial direction. The conclusions discuss the future implications for nuclear systems design with arbitrary geometry and the potential for AI-based autonomous design algorithms.

Metal Matrix Micro-encapsulated (M3) fuel consists of TRISO coated fuel particles directly dispersed in a matrix of zirconium metal to form a solid rod. In this integral fuel concept the cladding tube and the failure mechanisms associated with it have been eliminated; therefore, M3 fuel, compared to existing fuel designs, is expected to provide greatly improved operational performance. The main challenge to the deployment of M3 fuels is the low heavy metal load. This needs to be compensated with high density fuel (uranium nitride), larger rods and mainly higher enrichment. This study found that M3 fuel requires about 15.5% enriched UN TRISO particles to match the cycle length of standard fuel when loaded in a PWR. In order to achieve comparable reactivity feedbacks, in particular moderator temperature, the pitch to rod diameter ratio should be reduced to 1.20 compared to the typical 1.326. As M3 fuel provides a better path for heat transfer from the fuel, such smaller pitch is expected to be feasible, but further evaluations especially to examine thermal-hydraulic aspects are required. Analyses of possible load patterns for burnable poisons showed that M3 fuel maintains similar cycle length to that of standard fuel and pin power peaks are also comparable. Nevertheless, further optimization will be required to limit assembly power peaks.

Metal Matrix Micro-encapsulated (M3) fuel consists of TRISO coated fuel particles directly dispersed in a matrix of zirconium metal to form a solid rod. In this integral fuel concept the cladding tube and the failure mechanisms associated with it have been eliminated; therefore, M3 fuel, compared to existing fuel designs, is expected to provide greatly improved operational performance. The main challenge to the deployment of M3 fuels is the low heavy metal load. This needs to be compensated with high density fuel (uranium nitride), larger rods and mainly higher enrichment. This study found that M3 fuel requires about 15.5% enriched UN TRISO particles to match the cycle length of standard fuel when loaded in a PWR. In order to achieve comparable reactivity feedbacks, in particular moderator temperature, the pitch to rod diameter ratio should be reduced to 1.20 compared to the typical 1.326. As M3 fuel provides a better path for heat transfer from the fuel, such smaller pitch is expected to be feasible, but further evaluations especially to examine thermal-hydraulic aspects are required. Analyses of possible load patterns for burnable poisons showed that M3 fuel maintains similar cycle length to that of standard fuel and pin power peaks are also comparable. Nevertheless, further optimization will be required to limit assembly power peaks.

Abstract Background Percutaneous tracheostomy is frequently performed in intensive care units in patients who require prolonged mechanical ventilation. The first crucial step for the physician in these procedures is the precise needle insertion into the trachea. The primary aim of this technical note was to test the new filament and share our experiences in the implementation of the new device. The secondary aim was to show how a physician with basic training in computer-aided design and three-dimensional (3D) printing could independently create useful devices for clinical practice. Methods To simplify this referred clinical procedure and increase its safety, 3D printing and a new medical filament were used to develop a new translaryngeal Tracheostomy Needle Introducer (tTNI) for use in conjunction with the Fantoni’s method of percutaneous tracheostomy. The tTNI is composed of three parts: a support to fit on the rigid endotracheal tube of the Fantoni kit, an external particular shaped arm, and an introducer for the needle. The latest version of the device used a new filament based on a polyester matrix certified for skin contact that was sterilizable in a standard autoclave. Post-printing, minor technical interventions were required to correct small material deformities. Conclusions Our experiences with the thread and the technical features of the material were reported herein in conjunction with some suggestions on how to solve the most frequently encountered problems. The 3D printing technique allows physicians to directly manage the prototyping process of new medical devices, making this process completely independent. The speed of the prototyping process and the testing of each piece allow faster creation of a prototype than with traditional industrial methods. Finally, the new biomedical filaments offer endless possibilities of creation and modelling.

The advance in technology allows for the development of different CT scanners in the field of dual-energy computed tomography (DECT). In particular, a recently developed detector-based technology can collect data from different energy levels, thanks to its layers. The use of this system is suited for material decomposition with perfect spatial and temporal registration. Thanks to post-processing techniques, these scanners can generate conventional, material decomposition (including virtual non-contrast (VNC), iodine maps, Z-effective imaging, and uric acid pair images) and virtual monoenergetic images (VMIs). In recent years, different studies have been published regarding the use of DECT in clinical practice. On these bases, considering that different papers have been published using the DECT technology, a review regarding its clinical application can be useful. We focused on the usefulness of DECT technology in gastrointestinal imaging, where DECT plays an important role.