Mechanical Properties and Dislocation Structure Evolution in Ti6Al7Nb Alloy Processed by High Pressure Torsion

Ultrafine-grained biocompatible Ti-6Al-7Nb alloy was produced by high pressure torsion (HPT). Lattice defects—vacancies and dislocations—investigated by positron annihilation spectroscopy, observations by scanning electron microscopy, and microhardness evaluation are linked to the strain imposed by different numbers of HPT revolutions and to the distance from the specimen center. Positron annihilation spectroscopy showed significant increase of dislocation density and concentration of vacancy clusters after ½ of the HPT revolution. Microhardness increases by 20 pct with increasing strain, but it is heterogenous due to duplex microstructure. The heterogeneity of the microhardness increases with increasing strain, suggesting that a heavily deformed and fragmented α + β lamellar microstructure is more hardened than primary alpha grains. The defect structure is homogenous after ½ HPT revolution, while the microhardness becomes homogenous after 3 HPT revolutions only.     

A computational investigation of airfoil aeroacoustics for structural health monitoring of wind turbine blades

A generalized computational methodology for reduced order acoustic‐structural coupled modeling of the aeroacoustics of a wind turbine blade is presented. This methodology is used to investigate the acoustic pressure distribution in and around airfoils to guide the development of a passive damage detection approach for structural health monitoring of wind turbine blades for the first time. The output of a k ? ε turbulence model computational fluid dynamics simulation is used to calculate simple acoustic sources on the basis of model tuning with published experimental data. The methodology is then applied to a computational case study of a 0.3048‐m chord NACA 0012 airfoil with two internal cavities, each with a microphone placed along the shear web. Five damage locations and four damage sizes are studied and compared with the healthy baseline case for three strategically selected acoustic frequencies: 1, 5, and 10 kHz. In 22 of the 36 cases in which the front cavity is damaged, the front cavity microphone measures an increase in sound pressure level (SPL) above 3 dB, while rear cavity damage only results in six out of 24 cases with a 3‐dB increase in the rear cavity. The 1‐ and 5‐kHz cases show a more consistent increase in SPL than the 10‐kHz case, illustrating the spectral dependency of the model. The case study shows how passive acoustic detection could be used to identify blade damage, while providing a template for application of the methodology to investigate the feasibility of passive detection for any specific turbine blade.     

Effects of feeding rumen-protected methionine pre- and postpartum in multiparous Holstein cows: Lactation performance and plasma amino acid concentrations

Objectives were to evaluate the effect of feeding rumen-protected methionine (RPM) in pre- and postpartum total mix ration (TMR) on lactation performance and plasma AA concentrations in dairy cows. A total of 470 multiparous Holstein cows [235 cows at University of Wisconsin (UW) and 235 cows at Cornell University (CU)] were enrolled approximately 4 wk before parturition, housed in close-up dry cow and replicated lactation pens. Pens were randomly assigned to treatment diets (pre- and postpartum, respectively): UW control (CON) diet = 2.30 and 2.09% of Met as percentage of metabolizable protein (MP) and RPM diet = 2.83 and 2.58% of Met as MP; CU CON = 2.22 and 2.19% of Met as percentage of MP, and CU RPM = 2.85 and 2.65% of Met as percentage of MP. Treatments were evaluated until 112 ± 3 d in milk (DIM). Milk yield was recorded daily. Milk samples were collected at wk 1 and 2 of lactation, and then every other week, and analyzed for milk composition. For lactation pens, dry matter intake (DMI) was recorded daily. Body weight and body condition score were determined from 4 ± 3 DIM and parturition until 39 ± 3 and 49 DIM, respectively. Plasma AA concentrations were evaluated within 3 h after feeding during the periparturient period [d ?7 (±4), 0, 7 (±1), 14 (±1), and 21 (±1); n = 225]. In addition, plasma AA concentrations were evaluated (every 3 h for 24 h) after feeding in cows at 76 ± 8 DIM (n = 16) and within 3 h after feeding in cows at 80 ± 3 DIM (n = 72). The RPM treatment had no effect on DMI (27.9 vs. 28.0 kg/d) or milk yield (48.7 vs. 49.2 kg/d) for RPM and CON, respectively. Cows fed the RPM treatment had increased milk protein concentration (3.07 vs. 2.95%) and yield (1.48 vs. 1.43 kg/d), and milk fat concentration (3.87 vs. 3.77%), although milk fat yield did not differ. Plasma Met concentrations tended to be greater for cows fed RPM at 7 d before parturition (25.9 vs. 22.9 µM), did not differ at parturition (22.0 vs. 20.4 µM), and were increased on d 7 (31.0 vs. 21.2 µM) and remained greater with consistent concentrations until d 21 postpartum (d 14: 30.5 vs. 19.0 µM; d 21: 31.0 vs. 17.8 µM). However, feeding RPM decreased Leu, Val, Asn, and Ser (d 7, 14, and 21) and Tyr (d 14). At a later stage in lactation, plasma Met was increased for RPM cows (34.4 vs. 16.7 µM) consistently throughout the day, with no changes in other AA. Substantial variation was detected for plasma Met concentration (range: RPM = 8.9–63.3 µM; CON = 7.8–28.8 µM) among cows [coefficient of variation (CV) > 28%] and within cow during the day (CV: 10.5–27.1%). In conclusion, feeding RPM increased plasma Met concentration and improved lactation performance via increased milk protein production.     

A Tripodal Peptidic Titanium Phosphonate as a Homochiral Porous Solid Medium for the Heterogeneous Enantioselective Hydration of Epoxides

A porous, homochiral titanium‐phosphonate material based on a tripodal peptide scaffold was used as a heterogeneous reaction medium for the enantioselective hydration (>99%) of styrene oxide. This titanium‐phosphonate material, which was shown to contain confined chiral spaces, was prepared by polymerization of L ‐leucine onto a tris(2‐aminoethyl)amine initiator, followed by capping with phosphonate groups and completed by non‐aqueous condensation with titanium isopropoxide. Circular dichroism confirmed that the peptide tethers yielded a secondary structure. X‐ray powder diffraction and transmission electron microscopy supported by a semi‐empirical model showed the likely formation of a porous, lamellar material that was quantified by nitrogen adsorption.     

Evaluating different fixation protocols for spectral cytopathology, part 1

Spectral cytopathology (SCP) is a novel approach for disease diagnosis that utilizes infrared spectroscopy to interrogate the biochemical components of cellular samples and multivariate statistical methods, such as principal component analysis, to analyze and diagnose spectra. SCP has taken vast strides in its application for disease diagnosis over the past decade; however, fixation-induced changes and sample handling methods are still not systematically understood. Conversely, fixation and staining methods in conventional cytopathology, typically involving protocols to maintain the morphology of cells, have been documented and widely accepted for nearly a century. For SCP, fixation procedures must preserve the biochemical composition of samples so that spectral changes significant to disease diagnosis are not masked. We report efforts to study the effects of fixation protocols commonly used in traditional cytopathology and SCP, including fixed and unfixed methods applied to exfoliated oral (buccal) mucosa cells. Data suggest that the length of time in fixative and duration of sample storage via desiccation contribute to minor spectral changes where spectra are nearly superimposable. These findings illustrate that changes influenced by fixation are negligible in comparison to changes induced by disease.     

A Semi-Procedural Convolutional Material Prior

Lightweight material capture methods require a material prior, defining the subspace of plausible textures within the large space of unconstrained texel grids. Previous work has either used deep neural networks (trained on large synthetic material datasets) or procedural node graphs (constructed by expert artists) as such priors. In this paper, we propose a semi-procedural differentiable material prior that represents materials as a set of (typically procedural) grayscale noises and patterns that are processed by a sequence of lightweight learnable convolutional filter operations. We demonstrate that the restricted structure of this architecture acts as an inductive bias on the space of material appearances, allowing us to optimize the weights of the convolutions per-material, with no need for pre-training on a large dataset. Combined with a differentiable rendering step and a perceptual loss, we enable single-image tileable material capture comparable with state of the art. Our approach does not target the pixel-perfect recovery of the material, but rather uses noises and patterns as input to match the target appearance. To achieve this, it does not require complex procedural graphs, and has a much lower complexity, computational cost and storage cost. We also enable control over the results, through changing the provided patterns and using guide maps to push the material properties towards a user-driven objective.     

A readiness assessment framework for the adoption of 5G based smart-living services

Information Systems and e-Business Management - The subject of this article is to analyze the users’ attitude towards new, 5G-enabled smart living services before their commercial launch. The...     

Temporal response of biochemical and biological sensors with bimodal surface adsorption from a finite sample

Microsystem Technologies - The importance of adsorption-based biochemical/biological sensors in biochemistry and biophysics is paramount. Their temporal response gives information about the...     

Cultivating creative thinking in engineering student teams: Can a computer-mediated virtual laboratory help?

In engineering design, engineers must be able to think creatively, effectively toggling between divergent thinking (developing multiple novel ideas) and convergent thinking (pursuing an appropriate idea using engineering analyses). However, creative thinking is not emphasized in many undergraduate engineering programs. In this empirical study, we analyze the divergent thinking of teams working on a virtual laboratory project. Fifteen student teams' solution paths–as represented by Model Maps–were analyzed to characterize and compare the various elements of divergent thinking: fluency, flexibility, and originality. The solution paths of these teams were compared in two physical laboratory projects and to experts completing the same virtual laboratory project. We found that students demonstrated more divergent thinking in the virtual laboratory project than in the physical laboratory projects; yet, divergent thinking and quality of solution did not correlate. There was little difference between measured elements of divergent thinking between student teams and experts.