Taking back the power: an analysis of Black women’s communicative resistance

Black women are a structurally oppressed group in a subordinate position in the power hierarchy. Language is an important demonstration of group identity and is used to manage the day-to-day realities of being both Black and women. Scholars have devoted attention to explaining why Black women’s discursive practices are a function of their particular vantage point and can serve as a measure of protection against social and political hostilities. While there is a great deal of research acknowledging Black women’s ability to resist, the work can be extended by analyzing the specific resistance strategies Black women employ in common social environments. This essay uses Black/feminist standpoint and power and discourse frameworks to analyze Black women’s communicative resistance across three communication contexts: (1) education, (2) workplace, and (3) personal relationships.     

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10?000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.     

Privacy protection vs. utility in visual data

Multimedia Tools and Applications - Ubiquitous and networked sensors impose a huge challenge for privacy protection which has become an emerging problem of modern society. Protecting the privacy of...     

Psychological Contract and Turnover Intention in the Information Technology Profession

The recruitment and retention of Information Technology (IT) professionals continue to concern organizations and researchers. We employ psychological contract theory to examine how unmet expectations may influence psychological contract breach and turnover intention. The results of a survey of IT professionals indicate four factors contributing to IT workers’ perceptions of psychological contract breach including perceived supervisor support, emotional dissonance, work exhaustion, and salary. Further, autonomy moderates the relationship between psychological contract breach and turnover intention.     

Identification and Tuning Methods for PI Control Systems Based on Symmetric Send-on-delta Sampling

International Journal of Control, Automation and Systems - Two procedures for the definition of an autotuning algorithm for event-based proportional-integral (PI) control systems are proposed in...     

Evaluation of Carbon Partitioning in New Generation of Quench and Partitioning (Q&P) Steels

Quenching and partitioning (Q&P) and a novel combined process of hot straining (HS) and Q&P (HSQ&P) treatments have been applied to a TRIP-assisted steel in a Gleeble®3S50 thermomechanical simulator. The heat treatments involved intercritical annealing at 800 °C and a two-step Q&P heat treatment with a partitioning time of 100 seconds at 400 °C. The “optimum” quench temperature of 318 °C was selected according to the constrained carbon equilibrium (CCE) criterion. The effects of high-temperature deformation (isothermal and non-isothermal) on the carbon enrichment of austenite, carbide formation, and the strain-induced transformation to ferrite (SIT) mechanism were investigated. Carbon partitioning from supersaturated martensite into austenite and carbide precipitation were confirmed by means of atom probe tomography (APT) and scanning transmission electron microscopy (STEM). Austenite carbon enrichment was clearly observed in all specimens, and in the HSQ&P samples, it was significantly greater than in Q&P, suggesting an additional carbon partitioning to austenite from ferrite formed by the deformation-induced austenite-to-ferrite transformation (DIFT) phenomenon. By APT, the carbon accumulation at austenite/martensite interfaces was observed, with higher values for HSQ&P deformed isothermally (≈ 11 at. pct), when compared with non-isothermal HSQ&P (≈ 9.45 at. pct) and Q&P (≈ 7.6 at. pct). Moreover, a local Mn enrichment was observed in a ferrite/austenite interface, indicating ferrite growth under local equilibrium with negligible partitioning (LENP).

     

Advances in neutron imaging

Imaging techniques based on neutron beams are rapidly developing and have become versatile non-destructive analyzing tools in many research fields. Due to their intrinsic properties, neutrons differ strongly from electrons, protons or X-rays in terms of their interaction with matter: they penetrate deeply into most common metallic materials while they have a high sensitivity to light elements such as hydrogen, hydrogenous substances, or lithium. This makes neutrons perfectly suited probes for research on materials that are used for energy storage and conversion, e.g., batteries, hydrogen storage, fuel cells, etc. Moreover, their wave properties can be exploited to perform diffraction, phase-contrast and dark-field imaging experiments. Their magnetic moment allows for resolving magnetic properties in bulk samples. This review will focus on recent applications of neutron imaging techniques in both materials research and fundamental science illustrated by examples selected from different areas.     

Relationship between solar radiation and surface distribution of vegetation in Fildes Peninsula and Ardley Island,Maritime Antarctica

The aim of this work is to produce a simplified vegetation map of ice-free areas of the Fildes Peninsula (FP) and Ardley Island (AI) thought object-oriented classification using a QuickBird satellite image and to evaluate the influence of the global solar radiation (GSR) over the vegetation distribution. The vegetation data were generated from multiresolution segmentation using the panchromatic and infrared layers, and for the classification we calculated the normalized vegetative difference index (NVDI) and the green NVDI. Two classes were created – Lichen and Moss Cushion SubFormation and Moss Subformation – with 48 vegetation samples collected on surveys during the austral summers of 2008 and 2009. We used a kappa index to evaluate the classification efficiency using 100 sampled points obtained in austral summer of 2013. The GSR was estimated, and in order to evaluate the effect of meteorological phenomena and cloudless, we measured the GSR using a net radiometer model CNR4 installed in FP between 2014 and 2016. The estimate of GSR was done for seasons of 2015, in order to estimate the light compensation point and the saturation point for the plant communities in FP and AI. The kappa index was 0.73 and the global accuracy was 0.78, showing consistency between the classification and ground truth. The area was covered by vegetation in FP was 16.7% and in AI is 59.1%. The vegetation cover is distributed differently at FP and AI, and our results suggest GSR plays an important role in vegetation distribution and these tendencies could be related to greater GSR demand by mosses when compared to lichens.     

Towards the development of technical specifications for the production of lithium–lead alloys for the ITER HCLL TMB

The ITER and DEMO projects are developing new Test Blanket Modules (TBM), where the Pb–Li alloy plays a key role in the new commercial fusion reactors functionality. The Breeding Blanket (BB) has to perform several functions which are essential for the reactor operation. The HCLL TBM is one of the Breeding Blanket concepts to be tested in ITER. It is cooled by He and uses the eutectic liquid metal LLE (Lithium–Lead Eutectic) as breeder material (enriched at 90% in ⁶Li).Pb–Li eutectic alloy has no known uses outside of fusion technology, so the available databases of this material are currently incomplete. It is very important, within the material specifications, to have a complete characterization in order to define their chemical and physical properties, because any variation in the alloy composition has significant consequences in their behaviour, and therefore in their regenerative function inside the blanket.The chemical characterization methodology developed and presented in this paper (useful for both Pb–Li alloys as any Pb alloy) is a key tool that allows performing standard quality control procedures for base material and/or monitoring the alloy during the reactor operation. This report provides a procedure to perform a wide material chemical characterization, assessing the concentrations of major elements, as well as a review of trace level elements that can be found both in the eutectic alloy and in starting materials. In this determination plays an important role the ICP-MS technique because, as a highly sensitive technique, allows very low detection limits.