Corrosion behaviour of mechanically polished AA7075-T6 aluminium alloy

In the present study, the effects of mechanical polishing on the microstructure and corrosion behaviour of AA7075 aluminium alloy are investigated. It was found that a nano-grained, near-surface deformed layer, up to 400 nm thickness, is developed due to significant surface shear stress during mechanically polishing. Within the near-surface deformed layer, the alloying elements have been redistributed and the microstructure of the alloy is modified; in particular, the normal MgZn2 particles for T6 are absent. However, segregation bands, approximately 10-nm thick, containing mainly zinc, are found at the grain boundaries within the near-surface deformed layer. The presence of such segregation bands promoted localised corrosion along the grain boundaries within the near-surface deformed layer due to microgalvanic action. During anodic polarisation of mechanically polished alloy in sodium chloride solution, two breakdown potentials were observed at −750 mV and −700 mV, respectively. The first breakdown potential is associated with an increased electrochemical activity of the near-surface deformed layer, and the second breakdown potential is associated with typical pitting of the bulk alloy

Semantic feature-based visual attention model for pedestrian detection

Objective Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism. Method The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model. Result Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video. Conclusion This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians

An Investigation into REIT Performance Persistency

Using a sample of EREIT returns during the period 1993 to 2006 from the CRSP/Ziman REITs database, I construct portfolios of equity REITs based on past raw returns and evaluate their raw returns and risk-adjusted returns during the holding period for persistence. After adjusting for risk with Carhart (1997)’s 4-factor model, I find no evidence of persistence. By implication, a momentum strategy of buying historical winners and short-selling losers does not generate statistically significant abnormal returns. However, I do find strong evidence of performance reversal based on two-year and three-year ranking and holding periods. Consistent with DeBondt and Thaler (1985)’s overreaction theory, investors tend to overreact based on long-term rather than short-term performance records. This would suggest that investors tend to take a much longer period of time to formulate an opinion regarding a REIT’s performance record than previously assumed by earlier researchers. While there is a measurable tendency toward performance reversal, the return spread between the best performing EREITs and worst performing EREITs is marginal. This would indicate that the REIT markets are behaving in a generally efficient fashion. The investigation of the association of EREIT characteristics and performance persistence suggests a property type focus and geographic diversification strategy for EREITs. At the same time, EREITs with high leverage also tend to exhibit good performance persistently

Mechanistic insight into how multidrug resistant Acinetobacter baumannii response regulator AdeR recognizes an intercistronic region

AdeR-AdeS is a two-component regulatory system, which controls expression of the adeABC efflux pump involved in Acinetobacter baumannii multidrug resistance. AdeR is a response regulator consisting of an N-terminal receiver domain and a C-terminal DNA-binding-domain. AdeR binds to a direct-repeat DNA in the intercistronic region between adeR and adeABC. We demonstrate a markedly high affinity binding between unphosphorylated AdeR and DNA with a dissociation constant of 20 nM. In addition, we provide a 2.75 angstrom crystal structure of AdeR DNA-binding-domain complexed with the intercistronic DNA. This structure shows that the alpha 3 and beta hairpin formed by beta 5-beta 6 interacts with the major and minor groove of the DNA, which in turn leads to the introduction of a bend. The AdeR receiver domain structure revealed a dimerization motif mediated by a gearwheel-like structure involving the D108F109-R122 motif through cation pi stack interaction. The structure of AdeR receiver domain bound with magnesium indicated a conserved Glu19Asp20-Asp63 magnesium-binding motif, and revealed that the potential phosphorylation site Asp63(OD1) forms a hydrogen bond with Lys112. We thus dissected the mechanism of how AdeR recognizes the intercistronic DNA, which leads to a diverse mode of response regulation. Unlocking the AdeRS mechanism provides ways to circumvent A. baumannii antibiotic resistance

A Piezoelectric, Strain-Controlled Antiferromagnetic Memory Insensitive to Magnetic Fields

Spintronic devices based on antiferromagnetic (AFM) materials hold the promise of fast switching speeds and robustness against magnetic fields. Different device concepts have been predicted and experimentally demonstrated, such as low-temperature AFM tunnel junctions that operate as spin-valves, or room-temperature AFM memory, for which either thermal heating in combination with magnetic fields, or N\'eel spin-orbit torque is used for the information writing process. On the other hand, piezoelectric materials were employed to control magnetism by electric fields in multiferroic heterostructures, which suppresses Joule heating caused by switching currents and may enable low energy-consuming electronic devices. Here, we combine the two material classes to explore changes of the resistance of the high-N\'eel-temperature antiferromagnet MnPt induced by piezoelectric strain. We find two non-volatile resistance states at room temperature and zero electric field, which are stable in magnetic fields up to 60 T. Furthermore, the strain-induced resistance switching process is insensitive to magnetic fields. Integration in a tunnel junction can further amplify the electroresistance. The tunneling anisotropic magnetoresistance reaches ~11.2% at room temperature. Overall, we demonstrate a piezoelectric, strain-controlled AFM memory which is fully operational in strong magnetic fields and has potential for low-energy and high-density memory applications.Comment: 9 page

Orthogonal machining introduced microstructure modification in AA7150-T651 aluminium alloy

In the present work, orthogonal machining is simulated on AA7150-T651aluminium alloy by cutting using ultramicrotomy. The simulation has successfully reproduced the interaction between the tool and the workpiece during industrial machining process and the associated shear deformation introduced to the workpiece. Within the tertiary shear zone, near-surface deformed layers, characterized by ultrafine grains with diametersless than 100 nm, are generated on the workpiece. The thickness of the deformed layer ranges from approximately 200 nm to 400 nm, depending on the machining parameters. Increased cutting thickness or cutting speed results in the formation of a near-surface deformed layer with increased thickness. Machining with 0 degree clearance angle results in thicker deformed layer compared with that at 45 degrees clearance angle

A novel class of microRNA-recognition elements that function only within open reading frames.

MicroRNAs (miRNAs) are well known to target 3' untranslated regions (3' UTRs) in mRNAs, thereby silencing gene expression at the post-transcriptional level. Multiple reports have also indicated the ability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function through similar mechanisms regardless of the locations of their sites of action. Here, we report a class of miRNA-recognition elements (MREs) that function exclusively in CDS regions. Through functional and mechanistic characterization of these 'unusual' MREs, we demonstrate that CDS-targeted miRNAs require extensive base-pairing at the 3' side rather than the 5' seed; cause gene silencing in an Argonaute-dependent but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences of miRNAs that target CDS versus the 3' UTR and suggest that CDS-targeted miRNAs may use a translational quality-control-related mechanism to regulate translation in mammalian cells