Rheokinematics for product development—Formulation screening in rotational rheometers

Product formulations for industrial processes are typically developed at laboratory scale. However, the mixing conditions are not easily mimicked in the laboratory. A rotational device is proposed in this study as a fast laboratory-scale formulation development, which enables mimicking the mixing conditions in the industrial process. The geometrical configurations of the rotational device are from rheometry devices (plate-plate and cone-plate). The main advantages of this method are the small amounts of raw materials and shorter testing times. This methodology is applied to an industrial case study, the reaction injection molding (RIM) process. The mixing length scales evolution in the rotational rheometer were matched to those in RIM machines. The main novelty of this study is the introduction of a protocol that bridges the processing conditions at laboratory using small amounts of raw materials to high throughput continuous flow reactors.     

Nanocomposite powders of hydroxyapatite-graphene oxide for biological applications

The repair of bone fractures is a clinical challenge for patients with impaired healing, such as osteoporosis. Currently, different strategies have been developed to design new biomaterials, enhancing their interactions with biological systems and conducting the cellular behavior in the desired direction to help fracture healing. In the present work, hydroxyapatite-graphene oxide (HA-GO) nanocomposites were produced and the morphological and physicochemical influences of the addition of 0.5 wt%, 1.0 wt% and 1.5 wt% of GO to HA were observed. FEG-SEM and TEM analyses of HA-GO nanocomposites showed HA nanoparticles adhered to the surface of the GO sheets, suggesting an effective method to form nanostructured graphene-based biomaterials. As confirmation, physicochemical analyses by Raman, FTIR and TGA demonstrated a strong affinity between HA and GO, according to the increase of concentration from 0.5 wt% to 1.5 wt% GO in the HA-GO nanocomposites. Also, in order to evaluate the HA-GO nanocomposites behavior under biological microenvironment, in vitro bioactivity and indirect cytotoxicity tests were performed. FEG-SEM analyses confirmed the positive results for the bioactivity properties of HA-GO nanocomposite and indirect cytotoxicity demonstrated that even with a decrease in the hDPSCs viability and proliferation, when increasing to 1.5 wt% of GO concentration, high level of cell viability was exhibited by HA-GO nanocomposites. These biological results suggested the 0.5 wt% HA-GO nanocomposite as a potential bioactive bone graft and a promising biomaterial for bone tissue regeneration, when compared to the pure HA.     

A computational literature review of football performance analysis through probabilistic topic modeling

This research aims to illustrate the potential use of concepts, techniques, and mining process tools to improve the systematic review process. Thus, a review was performed on two online databases (Scopus and ISI Web of Science) from 2012 to 2019. A total of 9649 studies were identified, which were analyzed using probabilistic topic modeling procedures within a machine learning approach. The Latent Dirichlet Allocation method, chosen for modeling, required the following stages: 1) data cleansing, and 2) data modeling into topics for coherence and perplexity analysis. All research was conducted according to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses in a fully computerized way. The computational literature review is an integral part of a broader literature review process. The results presented met three criteria: (1) literature review for a research area, (2) analysis and classification of journals, and (3) analysis and classification of academic and individual research teams. The contribution of the article is to demonstrate how the publication network is formed in this particular field of research, and how the content of abstracts can be automatically analyzed to provide a set of research topics for quick understanding and application in future projects.

     

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

Performance of SSEBop model for estimating wheat actual evapotranspiration in the Brazilian Savannah region

In a scenario where supplying the increasing demand for food depends highly on irrigation, understanding the temporal and spatial variation of actual evapotranspiration (ETa) is essential for water resources management. In the last decades, several models for mapping and monitoring ETa using remote sensing data were developed and studied. In this work, the Simplified Surface Energy Balance for Operational Application (SSEBop) model was applied to estimate actual evapotranspiration of irrigated wheat in the Cerrado (Brazilian Savannahs) region, using ETM+/Landsat 7 and OLI-TIRS/Landsat 8 images. The results were compared with evapotranspiration calculated by the Bowen ratio method. Considering the data referring to satellites overpasses days, SSEBop overestimated ETa by an average of 13.6%, with a coefficient of determination (R²) equal to 0.82 and root mean square error (RMSE) equal to 0.89 mm d^?1. Considering the daily data for the entire period, including the extrapolation for the days between the satellites overpasses, SSEBop overestimated ETa by an average of 5.5%, with R² equal to 0.66 and RMSE equal to 0.95 mm d^?1. The results obtained demonstrated a reliable performance of the SSEBop for estimating actual evapotranspiration of irrigated wheat in the Cerrado, which can contribute to improve the irrigation efficiency and reduce water use conflicts. Considering the simplicity of the modeling concept and operational implementation, it can also be beneficial for water agencies on water resources planning, management and regulation in the region.