Augmented semantic segmentation for the digitization of grinding tools based on deep learning

In order to analyze various process characteristics, grinding simulations can be used, which need accurate models of the tool and the individual grains. For this purpose, grinding tools can be digitized. To identify characteristic grains from a large number of measurements, each individual grain has to be analyzed and separated from the bond manually. Therefore, a deep learning-based methodology was developed to achieve a high segmentation accuracy of the grain boundaries efficiently. Additionally, a data augmentation approach was investigated to limit the data necessary for learning. The model transferability was quantified by analyzing different states of tool wear.     

Stochastic modeling of grain wear in geometric physically-based grinding simulations

Grinding processes can be optimized by simulating the influence of individual grains on process forces and surface topographies. However, the process results are significantly influenced by tool wear. Simulating this effect allows, e.g., the prediction of necessary tool changes when manufacturing large forming tools. Therefore, a new point-based approach for modeling arbitrarily shaped grains in different states of tool wear was developed. Based on a small amount of representative wear investigations, a flexible tool model was defined, which can be used for various tool shapes without further experiments. This model can be applied for grinding processes with varying engagement situations.     

MicroRNA-16 Restores Sensitivity to Tyrosine Kinase Inhibitors and Outperforms MEK Inhibitors in KRAS-Mutated Non-Small Cell Lung Cancer

Background: Non-small cell lung cancer (NSCLC) is the leading cause of cancer death worldwide. Chemotherapy, the treatment of choice in non-operable cases, achieves a dismal success rate, raising the need for new therapeutic options. In about 25% of NSCLC, the activating mutations of the KRAS oncogene define a subclass that cannot benefit from tyrosine kinase inhibitors (TKIs). The tumor suppressor miR-16 is downregulated in many human cancers, including NSCLC. The main objectives of this study were to evaluate miR-16 treatment to restore the TKI sensitivity and compare its efficacy to MEK inhibitors in KRAS-mutated NSCLC. Methods: We performed in vitro and in vivo studies to investigate whether miR-16 could be exploited to overcome TKI resistance in KRAS-mutated NSCLC. We had three goals: first, to identify the KRAS downstream effectors targeted by mir-16, second, to study the effects of miR-16 restoration on TKI resistance in KRAS-mutated NSCLC both in vitro and in vivo, and finally, to compare miR-16 and the MEK inhibitor selumetinib in reducing KRAS-mutated NSCLC growth in vitro and in vivo. Results: We demonstrated that miR-16 directly targets the three KRAS downstream effectors MAPK3, MAP2K1, and CRAF in NSCLC, restoring the sensitivity to erlotinib in KRAS-mutated NSCLC both in vitro and in vivo. We also provided evidence that the miR-16–erlotinib regimen is more effective than the selumetinib–erlotinib combination in KRAS-mutated NSCLC. Conclusions: Our findings support the biological preclinical rationale for using miR-16 in combination with erlotinib in the treatment of NSCLC with KRAS-activating mutations.     

Differential Regulation of Interferon Signaling Pathways in CD4+ T Cells of the Low Type-2 Obesity-Associated Asthma Phenotype

In the era of personalized medicine, insights into the molecular mechanisms that differentially contribute to disease phenotypes, such as asthma phenotypes including obesity-associated asthma, are urgently needed. Peripheral blood was drawn from 10 obese, non-atopic asthmatic adults with a high body mass index (BMI; 36.67 ± 6.90); 10 non-obese, non-atopic asthmatic adults with normal BMI (23.88 ± 2.73); and 10 healthy controls with normal BMI (23.62 ± 3.74). All asthmatic patients were considered to represent a low type-2 asthma phenotype according to selective clinical parameters. RNA sequencing (RNA-Seq) was conducted on peripheral blood CD4⁺ T cells. Thousands of differentially expressed genes were identified in both asthma groups compared with heathy controls. The expression of interferon (IFN)-stimulated genes associated with IFN-related signaling pathways was specifically affected in obese asthmatics, while the gap junction and G protein-coupled receptor (GPCR) ligand binding pathways were enriched in both asthma groups. Furthermore, obesity gene markers were also upregulated in CD4⁺ T cells from obese asthmatics compared with the two other groups. Additionally, the enriched genes of the three abovementioned pathways showed a unique correlation pattern with various laboratory and clinical parameters. The specific activation of IFN-related signaling and viral infection pathways might provide a novel view of the molecular mechanisms associated with the development of the low type-2 obesity-associated asthma phenotype, which is a step ahead in the development of new stratified therapeutic approaches.     

In Situ Hydroxyapatite Synthesis Enhances Biocompatibility of PVA/HA Hydrogels

Bone tissue engineering tries to simulate natural behavior of hard tissues. This study aimed to produce scaffolds based on polyvinyl alcohol (PVA) and hyaluronic acid (HA) with hydroxyapatite (HAp) incorporated in two different ways, by in situ synthesis and physical mixing of pre-prepared HAp. In situ synthesis resulted in calcium deficient form of HAp with lower crystallinity. The proliferation of human osteoblast-like cells MG-63 proved to be better in the scaffolds with in situ synthesized HAp compared to those with physically mixed pre-prepared HAp. For scaffolds with PVA/HA/HAp ratio 3:1:2, there was significantly higher initial adhesion (p = 0.0440), as well as the proliferation in the following days (p < 0.001). It seemed to be advantageous improve the properties of the scaffold by in situ synthesizing of HAp directly in the organic matrix.     

Blends of thermoplastic polyurethane and maleic-anhydride grafted polyethylene. I: Morphology and mechanical properties

Thermoplastic polyurethane elastomers (TPU) and polyethylene (PE) form immiscible blends with an extremely low compatibility. In order to improve the dispersion, stability, and properties of these blends, polyethylene was grafted with maleic anhydride (PE-g-MA). Subsequently, it was blended with a commercial polyester - type TPU in a twin-screw extruder. With PE-g-MA as blend component, the particle size was dramatically reduced in comparison with PE. Coalescence was significantly reduced and the increase in particle size with composition was less pronounced than in blends with PE. In addition, the phase adhesion and the mechanical properties were improved by using PE-g-MA as minor component. Grafting of the MA onto the PE leads to a decrease of the molecular weight, the melt viscosity, and the mechanical properties of the pure PE. Hence, the reactive blend system exhibits a lower viscosity ratio. Comparison of these results with those from uncompatibilized blends with different viscosity ratios revealed that the reduction in viscosity ratio has a big influence on the blend morphology and because of that on the mechanical properties. In addition, there is a further effect on morphology and properties caused by the reduction in interfacial tension, which results from the compatibilizer formed at the interface.     

Use of copper shavings to remove mercury from contaminated groundwater or wastewater by amalgamation

The efficacy of copper shavings (Cu(0)) for the removal of Hg2+ from aqueous solution by amalgamation is demonstrated. Two kinds of copper shavings were investigated: (a) chemically processed shavings (Fluka) and (b) recycled shavings from scrap metal. Batch sorption experiments yielded very high retardation coefficients of 28 850-82 830 for the concentration range studied (1-10 000 microg/L Hg2+ dissolved in distilled water or in a 0.01 M CaCl2 matrix solution). Sorption data were well-described bythe Freundlich isotherm equation. Kinetic batch sorption experiments showed that 96-98% of Hg2+ was removed within 2 h. Column experiments were performed with a mercury solution containing 1000 microg/L Hg in a 0.01 M CaCl2 matrix with a flow rate of 0.5 m/d. No mercury breakthrough (c/c(0) = 0.5) could be detected after more than 2300 percolated pore volumes, and the high retardation coefficients determined in the batch studies could be confirmed. Copper was released from the shavings due to the amalgamation process and to copper corrosion by oxygen, resulting in concentrations of mobilized copper of 0.2-0.6 mg/L. Due to their high efficiency in removing Hg2+ from aqueous solution, the use of copper shavings for the removal of mercury from contaminated water is suggested, employing a sequential system of mercury amalgamation followed by the removal of mobilized copper by an ion exchanger such as zeolites. Possible applications could be in environmental technologies such as wastewater treatment or permeable reactive barriers for in situ groundwater remediation.     

Model-based Regional Assessment of Water Use An Example for Semi-arid Northeastern Brazil

Abstract

Water use assessments are a necessary prerequisite for sustainable water resources management and planning in river basins, federal states, or countries. For reasons of transparency, flexibility, ease of update, and the possibility to generate scenarios of future water use, such assessments are best carried out by applying a water use model. To support water resources planning in two federal states of semi-arid Northeastern Brazil, Ceará and Piauí, the regional-scale water use model NoWUM was developed. It computes withdrawal and consumptive water use for each of 332 municipalities, distinguishing five water use sectors: irrigation, livestock, households, industry, and tourism. The model is suited to simulate the impact of global change and of management measures on water demand. Using NoWUM, the present-day water use situation in Ceará and Piauí is assessed. In addition, the impact of inter-annual climate variability and long-term climate change on irrigation requirements is considered. Scarce and uncertain input data lead to a high level of uncertainty in the model results. It is likely that water use in the most important sector, irrigation, is underestimated, while industrial water use is possibly overestimated. With some modifications, NoWUM has the potential to be applied for water use assessments in other data-poor regions of the globe.