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- Hilborn, Erik, et al.
(författare)
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Androgen receptor expression predicts beneficial tamoxifen response in oestrogen receptor-alpha-negative breast cancer
- 2016
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Ingår i: British Journal of Cancer. - : NATURE PUBLISHING GROUP. - 0007-0920 .- 1532-1827. ; 114:3, s. 248-255
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Tidskriftsartikel (refereegranskat)abstract
- Background: Although the androgen receptor (AR) is frequently expressed in breast cancer, its relevance in the disease is not fully understood. In addition, the relevance of AR in determining tamoxifen treatment efficiency requires evaluation. Purpose: To investigate the tamoxifen predictive relevance of the AR protein expression in breast cancer. Methods Patients were randomised to tamoxifen 40 mg daily for 2 or 5 years or to no endocrine treatment. Mean follow-up was 15 years. Hazard ratios were calculated with recurrence-free survival as end point. Results: In patients with oestrogen receptor (ER)-negative tumours, expression of AR predicted decreased recurrence rate with tamoxifen (hazard ratio (HR) = 0.34; 95% confidence interval (CI) = 0.14-0.81; P = 0.015), whereas the opposite was seen in the AR- group (HR = 2.92; 95% CI = 1.16-7.31; P = 0.022). Interaction test was significant P < 0.001. Patients with triple-negative and AR+ tumours benefitted from tamoxifen treatment (HR = 0.12; 95% CI = 0.014-0.95 P = 0.044), whereas patients with AR- tumours had worse outcome when treated with tamoxifen (HR = 3.98; 95% CI = 1.32-12.03; P = 0.014). Interaction test was significant P = 0.003. Patients with ER+ tumours showed benefit from tamoxifen treatment regardless of AR expression. Conclusions: AR can predict tamoxifen treatment benefit in patients with ER- tumours and triple-negative breast cancer.
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| 3. |
- Tram, Tommy, 1987, et al.
(författare)
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Learning Negotiating Behavior Between Cars in Intersections using Deep Q-Learning
- 2018
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Ingår i: IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. ; 2018-November, s. 3169-3174
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Konferensbidrag (refereegranskat)abstract
- This paper concerns automated vehicles negotiating with other vehicles, typically human driven, in crossings with the goal to find a decision algorithm by learning typical behaviors of other vehicles. The vehicle observes distance and speed of vehicles on the intersecting road and use a policy that adapts its speed along its pre-defined trajectory to pass the crossing efficiently. Deep Q-learning is used on simulated traffic with different predefined driver behaviors and intentions. The results show a policy that is able to cross the intersection avoiding collision with other vehicles 98% of the time, while at the same time not being too passive. Moreover, inferring information over time is important to distinguish between different intentions and is shown by comparing the collision rate between a Deep Recurrent Q-Network at 0.85% and a Deep Q-learning at 1.75%.
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| 4. |
- von Fieandt, Linus
(författare)
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Cutting Edge Titanium-based CVD Hard Coatings
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modern tools for metal cutting applications, such as turning or milling, are typically improved with a thin protective coating. Despite being only a few microns thick, the coating can increase the lifetime of the tool by more than 100 times compared to an uncoated tool. Two different types of techniques are normally used to deposit the coatings, i.e. chemical vapor deposition (CVD) or physical vapor deposition (PVD). A CVD coated tool often includes several different layers. TiN-Ti(C,N)-Al2O3-TiN is a common combination. The research in this thesis has focused on deposition, characterization, and optimization of TiN and Ti(C,N) layers. CVD has been used to deposit all coatings studied in this thesis. They were characterized with a variety of techniques such as: X-ray diffraction, electron microscopy and X-ray photoelectron spectroscopy.TiN was deposited on three different substrates, Co, Fe and Ni. It was found that the TiN coating was strongly affected by the substrate. TiN deposited on Fe substrates resulted in a porous interface caused by substrate etching by the reaction gas mixture. CVD of TiN on Ni substrates resulted in an unwanted intermetallic phase (Ni3Ti) in addition to TiN. Etching or corrosion of the Fe substrates could be reduced by lowering the deposition temperature. In addition, the formation of (Ni3Ti) could be significantly reduced by adjusting the partial pressure of the reactant gases. This shows that CVD of TiN on cutting tools with Fe or Ni as a binder phase needs to be optimized with respect to the process parameters.Thermodynamic calculations of the Ti(C,N) CVD process indicates that the major growth species using CH3CN, TiCl4 and H2 as precursors, was HCN and TiCl3. They were formed in the gas phase by homogeneous reactions. Furthermore, it was found that by adjusting the composition of the reaction gas mixture, the preferred orientation, morphology, and micro-structure of the Ti(C,N) coatings could be tailored. As a result, the tribological/mechanical properties of the Ti(C,N) coatings could be significantly improved. A hardness of 40 GPa, i.e. close to super hard could for instance be achieved. The origin of the mechanical improvements was attributed to a more ordered crystallographic orientation in the <111> direction as well as a high defect density close to the coating surface. In addition to the excellent mechanical properties, the Ti(C,N) coatings were also found to have a high corrosion resistance in sea water, thanks to a formation of a passivating surface layer (TiO2).
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