Miracle-dz/UniFAR-FTUs huggingface dataset:
Gamma Irradiation Processing on 3D PCL Devices—A Preliminary Biocompatibility Assessment

Additive manufacturing or 3D printing applying polycaprolactone (PCL)-based medical devices represents an important branch of tissue engineering, where the sterilization method is a key process for further safe application in vitro and in vivo. In this study, the authors intend to access the most suitable gamma radiation conditions to sterilize PCL-based scaffolds in a preliminary biocompatibility assessment, envisioning future studies for airway obstruction conditions. Three radiation levels were considered, 25 kGy, 35 kGy and 45 kGy, and evaluated as regards their cyto- and biocompatibility. All three groups presented biocompatible properties, indicating an adequate sterility condition. As for the cytocompatibility analysis, devices sterilized with 35 kGy and 45 kGy showed better results, with the 45 kGy showing overall improved outcomes. This study allowed the selection of the most suitable sterilization condition for PCL-based scaffolds, aiming at immediate future assays, by applying 3D-customized printing techniques to specific airway obstruction lesions of the trachea.
Current Considerations in Surgical Treatment for Adolescents and Young Women with Breast Cancer

Adolescents and young women (AYA) with breast cancer represent a unique patient population, compared to the general population with breast cancer. We performed a literature review to evaluate the factors that influenced the surgical outcomes in this patient population. Fifty-two studies were identified, which evaluated breast surgery type, axillary surgery, contralateral prophylactic mastectomy (CPM), surgical timing, psychological factors, disparities, and imaging use. AYA patients had equivalent oncologic outcomes with breast conserving surgery (BCS) or mastectomy. CPM did not improve survival. There are limited data on axillary management in the AYA population, and while more data would be beneficial, this is currently extrapolated from the general breast cancer population. A shorter time to initiate treatment correlated to better outcomes, and disparities need to be overcome for optimal outcomes. AYA patients appreciated involvement in clinical decisions, and shared decision making should be considered whenever possible. Providers must keep these factors in mind when counseling AYA patients, regarding the surgical management of breast cancer.
Scaling of Miniature Piston Engine Performance Part 2: Energy Losses

Previous work based on measurements of the overall performance of small, (<10 cc displacement) two-stroke piston engines has shown that power and efficiency decrease more rapidly with size in miniature (<10 cc displacement) than in larger-scale engines. The present work seeks explanations for these trends by using energy balance analyses to identify and quantify the principal loss mechanisms in miniature engines. Energy losses in order of decreasing importance are found to be: incomplete combustion, heat transfer, sensible enthalpy in the exhaust, and friction. This ordering is almost opposite to that observed in conventional-scale engines. The results show that the scale-dependence of thermal and mechanical efficiency drive the drop in overall efficiency but that the biggest problem is incomplete combustion that consumes 50–60% of the fuel energy. Power output decreases somewhat less rapidly than efficiency because delivery ratio increases with decreasing scale in the set of engines investigated here.
Wavefront reduction using graphs, neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.
Linear bootstrap methods for vector autoregressive moving-average models

We provide the theoretical justification of bootstrapping stationary invertible echelon vector autoregressive moving-average (VARMA) models using linear methods. The asymptotic validity of the bootstrap is established with strong white noise under parametric and nonparametric assumptions. Our methods are practical and useful for building reliable simulation-based inference and forecasting without implementing nonlinear estimation techniques such as ML which is usually burdensome, time demanding or impractical, particularly in big or highly persistent systems. The relevance of our procedures is more pronounced in the context of dynamic simulation-based techniques such as maximized Monte Carlo (MMC) tests [see Dufour J-M. Monte Carlo tests with nuisance parameters: a general approach to finite-sample inference and nonstandard asymptotics in econometrics. J Econom. 2006;133(2):443–477 and Dufour J-M, Jouini T. Finite-sample simulation-based tests in VAR models with applications to Granger causality testing. J Econom. 2006;135(1–2):229–254 for the VAR case]. Simulation evidence shows that, compared with conventional asymptotics, our bootstrap methods have good finite-sample properties in approximating the actual distribution of the studentized echelon VARMA parameter estimates, and in providing echelon parameter confidence sets with satisfactory coverage.
Photoemission study of the electronic structure of Mo and Mo oxides

The electronic structure of Mo and Mo oxides has been studied using ultraviolet and X-ray photoelectron spectroscopy. The valence band spectrum of Mo(100) is compared with calculations of the density of states (DOS). A fairly good agreement of the characteristic peak positions with the DOS maxima is obtained. The Mo 3d core lines indicate well-defined MoO2 and MoO3 oxidation states with binding energies respectively 0.9 to 5.0 eV higher than that of the Mo metal. By comparing the atomic photoionisation cross sections and electron state occupation numbers with the experimental band intensities the highly ionic character of MoO2 has been estimated. The XPS valence band of MoO2 can be qualitatively described using the molecular orbital model based on a distorted rutile structure. The MoO3 valence band is composed of the O 2p derived band with a characteristic structure around 5 eV reflecting the existence of cationic d interactions. A small peak at about 1 eV below EF is observed in the photoemission of blue substoichiometric MoO3-x (in contrast to transparent MoO3). This is assigned to a small occupied defect band of trapped electrons in oxygen vacancies. Ion bombardment of transparent MoO3 results in a drastic change of the valence band indicating the MoO3 to MoO2 surface modification due to oxygen depletion.
UV-mediated enhancement of antibacterial secondary metabolites in endophytic Lasiodiplodia theobromae

In the science of drug discovery, ultraviolet (UV) irradiation has been applied to induce mutagenesis in fungi to provide possibilities for the stimulation or enhancement of fungal biosynthetic capabilities. This study was carried out to evaluate the effect of UV radiation on the biosynthesis of antibacterial secondary metabolites in an endophytic Lasiodiplodia theobromae. Using standard methods, the fungus was isolated from healthy leaves of Cola acuminata and identified based on PCR amplification and genomic sequencing of the internal transcribed spacer (ITS) region. Cultures of L. theobromae were exposed to UV radiation at different time intervals of 1, 2 and 5 min. The fungus was subjected to solid-state fermentation in rice medium before and after UV treatments. The fungal secondary metabolites were extracted and tested for antibacterial activity using the agar diffusion method. Compounds present in the obtained extracts were identified by HPLC and GC-MS analysis. At a concentration of 1 mg/ml, the extract of the wild type L. theobromae (untreated) was observed to only inhibit Staphylococcus aureus, with an IZD of 12 mm. However, the extract of UV-treated L. theobromae (2 min) inhibited S. aureus, Escherichia coli and Pseudomonas aeruginosa with an IZD of 10 and 4 mm respectively. A wide array of compounds in the phenolics, fatty acids, alkaloids and alkanes classes were identified in the UV-treated and untreated fungal extracts. Overall, UV treatments of L. theobromae stimulated the production of seventeen (17) new compounds that were not detected in the untreated strain. The study confirms UV irradiation as an effective method for stimulating microbial biosynthesis of new bioactive compounds, indicating a promising and potentially abundant source of new drug compounds from microorganisms.
The Distribution and Properties of H II Regions in Early-to- Intermediate Hubble Type Ringed Galaxies

This paper presents a study of the H II regions in 32 ringed and pseudoringed galaxies having Hubble types in the range so+ to Sc. The objective is to illustrate the distributions of H II regions in classic examples of ringed galaxies and to relate the observed properties to resonance theory. The sample is selected from the Catalog of Southern Ringed Galaxies and includes examples covering a range of ring and galaxy morphological properties. We find that the distribution of Hoc luminosity around inner rings is sensitive to the intrinsic shape of the rings. Extremely oval inner rings show a greater concentration of H II regions near the intrinsic ring major axis compared to more circular rings. Nuclear rings are present in several of the sample galaxies and show a range of morphological properties, from a double nuclear ring in NGC 1317 to an irregular feature in NGC 1433. We find also that in galaxies in which an R1 outer ring is prominent in the continuum image, the H II regions follow an R2 morphology. In several cases, the observed distribution of H II regions strongly supports the idea that the rings are linked to specific orbital resonances with the bar. H II region luminosity functions have been derived for all of the sample galaxies. The functions can be represented by power laws whose exponents are very similar to those found for nonringed galaxies. In a few cases, a luminous nuclear ring produces a secondary peak in the luminosity function. One galaxy shows a break in the luminosity function similar to that observed in other galaxies by Kennicutt, Edgar, & Hodge. The most unusual Hoc distribution in the sample was found in the large outer-ringed galaxy NGC 1291. The primary bar, lens, and secondary bar regions of this SO/a galaxy are filled with a wispy pattern of ionized gas filaments very reminiscent of what is seen in the bulge of M31. Subject headings: atlases galaxies: ISM galaxies: spiral galaxies: structure H II regions
Deep Learning Implementation Using Long Short Term Memory Architecture for PM2.5 Concentration Prediction: a Review

PM2.5 is a respirable fine particle with harmful effects. PM2.5 prediction research plays a role to contribute scientific recommendations in actions for controlling air pollution. Nowadays, PM2.5 prediction using deep learning is the most chosen since it is an efficient and cost-effective method for air quality modeling. As a subset of deep learning, LSTM is strong in remembering past experiences and able to identify highly complex relationships of sequential data. LSTM has higher accuracy in time series prediction compared to other deep neural network models. On the other hand hybrid CNN-LSTM, a method that can produce good predictive models since CNN’s ability to extract spatial-temporal features might collaborate with LSTM, it is possible to identify stationary and non-stationary data. Meteorological parameters and other gaseous pollutants affect the concentration of PM2.5 proven by correlation analysis results. Therefore, it is appropriate to use as input for air quality modeling using either LSTM or the hybrid CNN-LSTM method.
Herschel Optimized Tau and Temperature (HOTT) Maps: Uncertainty Analysis and Robust Parameter Extraction

We introduce the HOTT dust optical depth and temperature maps parameterizing thermal dust emission. Such maps have revolutionized studies of the distribution of matter in molecular clouds and processes relevant to star formation, including virial stability. HOTT maps for a suite of fields, including the Herschel Gould Belt Survey, are available online. The standardization of our robust pipeline for modified blackbody fitting of the spectral energy distribution (SED) of high-quality archival submillimeter data from the Herschel Space Observatory is based on a thorough analysis and quantification of the uncertainties of the data. This enables proper weighting in the SED fits. The uncertainties assessed fall into four main categories: instrument noise; the cosmic infrared background anisotropy, a contaminating sky signal; gradient-related noise arising because of dust signal morphology; and calibration uncertainty, scaling with the signal strength. Zero-level adjustments are important too. An analysis of residuals from the SED fits across many fields supports the overall appropriateness of the assumed modified blackbody model and points to where it breaks down. Finding χ 2 distributions close to the theoretical expectation boosts confidence in the pipeline and the optimized quality of the parameter maps and their estimated uncertainties. We compared our HOTT parameter maps to those from earlier studies to understand and quantify the potential for systematic differences.
Nitrous oxide (N 2 O) synthesis by Microcystis aeruginosa

Pure cultures of Microcystis aeruginosa synthesized nitrous oxide (N 2 O) when supplied with nitrite (NO 2- ) in darkness (198.9 nmol·g-DW -1 ·h -1 after 24 hours) and illumination (163.1 nmol∙g-DW -1 ∙h -1 after 24 hours) whereas N 2 O production was negligible in abiotic controls supplied with NO 2- and in cultures deprived of exogenous nitrogen. N 2 O production was also positively correlated to the initial NO 2- and M. aeruginosa concentrations, but low to negligible when nitrate (NO 3- ) and ammonium (NH 4+ ) were supplied as the sole exogenous N source instead of NO 2- . A protein database search 10 revealed M. aeruginosa possesses protein homologues to eukaryotic microalgae enzymes known to catalyse the successive reduction of NO 2- into nitric oxide (NO) and N 2 O. Our laboratory study is the first demonstration that M. aeruginosa possesses the ability to synthesize N 2 O. As M. aeruginosa is a bloom-forming cyanobacterium found globally, further research (including field monitoring) is now needed to establish the significance of N 2 O synthesis by M. aeruginosa under relevant conditions (especially in terms of N supply). Further work is also needed to confirm the biochemical pathway and potential function of 15 this synthesis. Graphical
Optimal Ownership of Public Goods Reconsidered

Consider a non-governmental organization (NGO) that can invest in a public good. Should the government or the NGO own the public project? In an incomplete contracting framework with split-the-di⁄erence bargaining, Besley and Ghatak (2001) argue that the party who values the public good most should be the owner. We demonstrate the robustness of their insight when the split-the-di⁄erence rule is replaced by the deal-me-out solution. Our (cid:133)nding is in contrast to the private good results of Chiu (1998) and De Meza and Lockwood (1998), who show that the optimal ownership structure crucially depends on whether the split-the-di⁄erence rule or the deal-me-out solution is used.
Climate change projections of wet and dry extreme events in the Upper Jhelum Basin using a multivariate drought index: Evaluation of bias correction

Bias correction (BC) is often a necessity to improve the applicability of global and regional climate model (GCM and RCM, respectively) outputs to impact assessment studies, which usually depend on multiple potentially dependent variables. To date, various BC methods have been developed which adjust climate variables separately (univariate BC) or jointly (multivariate BC) prior to their application in impact studies (i.e., the component-wise 15 approach). Another possible approach is to first calculate the multivariate hazard index from the original, biased simulations, and bias-correct the impact model output or index itself using univariate methods (direct approach). This has the advantage of circumventing the difficulties associated with correcting the inter-variable dependence of climate variables which is not considered by univariate BC methods. Using a multivariate drought index (i.e., SPEI) as an example, the present study compares different state-of- 20 the-art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) applied to climate model simulations stemming from different experiments at different spatial resolutions (namely CORDEX, CORDEX-CORE and CMIP6). The BC methods are calibrated and evaluated over the same historical period (1986-2005). The proposed framework is demonstrated as a case study over a transboundary watershed, i.e. the Upper Jhelum Basin (UJB) in the Western Himalaya. 25 Results show that (1) there is some added value of multivariate BC methods over the univariate methods in adjusting the inter-variable relationship, however, comparable performance is found for SPEI indices. (2) The best performing BC methods exhibits a comparable performance under both approaches with a slightly better performance for the direct approach. (3) The added value of the high-resolution experiments (CORDEX-CORE) compared to their coarser resolution counterparts (CORDEX) are not apparent in this study.
Can Everyone Tap into the Housing Piggy Bank? Racial Disparities in Access to Home Equity

Disclosure Act lender file. They are also grateful to Neil Bhutta, Julie Cheney, Hajime Hadeishi, Bob Hunt, Tesia Lemelle, Dubravka Ritter, Amanda Roberts, and Anna Tranfaglia for providing helpful comments and suggestions. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. Any remaining errors are the authors’ responsibility.
Data fusion uncertainty-enabled methods to map street-scale hourly NO2 in Barcelona: a case study with CALIOPE-Urban v1.0

Abstract. Comprehensive monitoring of NO2 exceedances is imperative for protecting human health, especially in urban areas with traffic. However, an accurate spatial characterization of the exceedances is challenging due to the typically low density of air quality monitoring stations and the inherent uncertainties in urban air quality models. We study how observational data from different sources and timescales can be combined with a dispersion air quality model to obtain bias-corrected NO2 hourly maps at the street scale. We present a kriging-based data fusion workflow that merges dispersion model output with continuous hourly observations and uses a machine-learning-based land use regression (LUR) model constrained with past short intensive passive dosimeter campaign measurements. While the hourly observations allow the bias adjustment of the temporal variability in the dispersion model, the microscale LUR model adds information on the NO2 spatial patterns. Our method includes an uncertainty calculation based on the estimated error variance of the universal kriging technique, which is subsequently used to produce urban maps of probability of exceeding the 200 µg m−3 hourly and the 40 µg m−3 annual NO2 average limits. We assess the statistical performance of this approach in the city of Barcelona for the year 2019. Our results show that simply merging the monitoring stations with the model output already significantly increases the correlation coefficient (r) by +29 % and decreases the root mean square error (RMSE) by −32 %. When adding the time-invariant microscale LUR model in the data fusion workflow, the improvement is even more remarkable, with +46 % and −48 % for the r and RMSE, respectively. Our work highlights the usefulness of high-resolution spatial information in data fusion methods to better estimate exceedances at the street scale.
Numerical simulation of flow past a rotating and rotary oscillating circular cylinder on unstructured meshes

The unsteady flow past a circular cylinder which starts rotating or rotary oscillating impulsively from rest in a viscous fluid is investigated for Reynolds numbers Re = 200 and 1000, rectilinear speed ratios α between 0.5 and 5.0, and forced oscillating frequencies fs between 0.1 and 2.0. Numerical solutions of the Navier-Stokes equations are obtained by using a finite volume method on an unstructured colocated grid. The objective of the study is to examine the effect of the rotating and rotary oscillating circular cylinder on the flow patterns and dynamics loads. The numerical results reveal that the Karman vortex street vanishes entirely behind the rotating cylinder when the ratio α exceeds the critical value, and the vortex shedding behind the rotary oscillating cylinder undergoes mainly three modes named 'synchronization', 'competition' and 'natural shedding' with the increase of fs. Based on the amplitude spectra analysis of the lift coefficients, the regions of the classification of flow structure modes are presented, which provide important references for the flow control in the ocean engineering.
Hydroclimate and bedrock permeability determine young water fractions in streamflow across the tropical Andes mountains and Amazon floodplain

The role of topography on water transit times and pathways through catchments is unclear, especially in mountainous environments — yet these environments play central roles in global water, sediment, and 30 biogeochemical fluxes. Moreover, the vast majority of intensively monitored catchments are located in northern latitudes. As a result, the interplay between water transit, topography and other landscape characteristics is particularly underexplored in tropical environments. Here we present the results of a multi-year hydrologic sampling campaign (twice-monthly and storm sampling) to quantify water transit in seven small catchments (< 3 km 2 ) across the transition from the Andes mountains to Amazon floodplain in 35 southern Peru. We use the stable isotope composition of water (δ 18 O H2O ) to calculate the fraction of streamflow comprised of recent precipitation (“young water fraction”) for each of the seven small catchments. Mean unweighted young water fractions (F yw ) are 3 − 10 % in the Andes, 15 − 23 % at mid-elevation and 3 − 4 % in the foreland floodplain. Weighting the F yw calculation by volume of streamflow and precipitation yield F yw of 7 − 47 %. Across these catchments, topography does not exert a clear control on 40 water transit; instead stream F yw is controlled by a combination of hydroclimate and bedrock permeability. Mid-elevation sites are posited to have the highest F yw due to less permeable bedrock, poorly developed soils and more frequent and intense rainfall. The data presented here allow us to explore relationships between topography, bedrock permeability, hydroclimate and stream baseflow F yw — particularly highlighting the role of bedrock permeability and hydroclimate in determining water transit times in a 45 tropical mountain setting.