Technical note an evaluation of water corrosivity of the river tigris at Baghdad

A series of experiments was carried out on different samples of tap water abstracted from the Baghdad water supply network in order to observe the effect of water on supply pipes, either scale forming or corrosive. This experimental investigation on the corrosive effect of the city of Baghdad tap water showed that the water can be classified as corrosive according to the Ryznar index, while the Langelier index showed that the water has the ability to form scale on the pipes. However, personal field observation indicated that the water is corrosive to the pipes and to the network appurtenance. Other findings are reported herein.     

Spatial analysis of urban stormwater quality: Ramallah district as a case study, Palestine

Urban runoff pollution sources are formidable obstacles to achieving water source goals in numerous municipalities. Ramallah district currently holds one of the highest rates of urbanization in Palestine causing a significant increase in surface runoff. Consequently, this causes increased flooding and a significant decrease in water quality due primarily to the accumulation of pollutants. To date, most research has focused on specifying temporal variations of stormwater quality parameters that include high uncertainties and also increase the risk of pollution control structures' failure. Spatial variations of the runoff quality are the key factor in nonpoint source pollution studies. This research investigates the spatial variability of urban runoff quality parameters in relation to land use of urban catchments. The research estimated pollutant concentration for improved and efficient design of pollution control structures for each land use.     

Political Schemas and Corporate Political Activities During Foreign Market Entry: A Micro-process Perspective

The paper analyses how multinational enterprises (MNEs) manage their interactions with host governments during the market entry process. A qualitative multiple case study collected data through in-depth interviews with multiple participants in six New Zealand MNEs. The analysis identifies two distinct political schemas which represent MNE managers’ assumptions and heuristics regarding how to approach interactions with foreign governments, systematic and episodic, which lead to the enactment of distinct patterns of political activities, each supported by certain political resources and capabilities. We then identify several sources of the variations in these two political schemas at the managerial, firm, industry, and country levels of analysis. Our study deepens understanding of the micro-processes of corporate political activity (CPA) and the processes and activities through which political resources and capabilities are developed, deployed and leveraged by MNE actors in managing their interactions with host governments during the market entry process. In doing so, we highlight the role of international experience in influencing the process of political capability development, and also the role of managerial actions in shaping this evolutionary process.     

Disturbance Evaluation in Power System Based on Machine Learning

The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances. Then, a multi-label classification algorithm based on rating is proposed to understand the relationship between the labels and identify the various power quality disturbances. The two algorithms are combined to construct a multi-label classification model based on a multi-level extreme learning machine, and the optimal network structure of the multi-level extreme learning machine as well as the optimal multi-label classification threshold are developed. The proposed method can be used to classify the single and compound power quality disturbances with improved classification effect, reliability, robustness, and anti-noise performance, according to the experimental results. The hamming loss obtained by the proposed algorithm is about 0.17 whereas ML-RBF, SVM and ML-KNN schemes have 0.28, 0.23 and 0.22 respectively at a noise intensity of 20 dB. The average precision obtained by the proposed algorithm 0.85 whereas the ML-RBF, SVM and ML-KNN schemes indicates 0.7, 0.77 and 0.78 respectively.     

Interactions between color and word processing in a flanker task.

To examine interactions between color and word attributes, participants responded, either manually or vocally, to a central target (color patch or word) flanked by a Stroop stimulus. Color and word attributes of the flanker affected both vocal and manual responding to color patches. Color and word flankers also affected manual responding to word targets, but only word flanker affected vocal responding to word targets. These results are not consistent with models (e.g., translational models) of Stroop tasks, which posit that interactions between colors and words occur only when vocal responding is required. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Observation of Ga droplet formation on (311)A and (511)A GaAs surfaces

Using (100) GaAs substrates as a reference, we present a study of the formation of Ga droplets on (311)A and (511)A GaAs substrates in which the effect of both the substrate temperature and the amount of Ga supplied on the droplet density and height for the three different surfaces have been investigated. Droplets on (100) substrates show a round shape; however, they appear as elongated balls with tails along the [Formula: see text] direction of the (311)A substrate and the [Formula: see text] direction of the (511)A substrate. It has been found that the Ga droplets on (511)A surfaces have lower densities and higher heights than those on (100) substrates. In contrast, Ga droplets on (311)A surfaces have lower heights and much higher densities compared to those for both (100) and (511)A. We observed that the decrease in the droplet density with increasing growth temperature for both (311)A and (511)A is more than twice that for the (100)GaAs surface due to the larger drop in the nucleation rate. Based on these observations, we offer a physical explanation based on the thermodynamics and the anisotropy of the high-index surfaces.     

Putative biomarkers and targets of estrogen receptor negative human breast cancer

Breast cancer is a progressive and potentially fatal disease that affects women of all ages. Like all progressive diseases, early and reliable diagnosis is the key for successful treatment and annihilation. Biomarkers serve as indicators of pathological, physiological, or pharmacological processes. Her2/neu, CA15.3, estrogen receptor (ER), progesterone receptor (PR), and cytokeratins are biomarkers that have been approved by the Food and Drug Administration for disease diagnosis, prognosis, and therapy selection. The structural and functional complexity of protein biomarkers and the heterogeneity of the breast cancer pathology present challenges to the scientific community. Here we review estrogen receptor-related putative breast cancer biomarkers, including those of putative breast cancer stem cells, a minor population of estrogen receptor negative tumor cells that retain the stem cell property of self-renewal. We also review a few promising cytoskeleton targets for ER alpha negative breast cancer.     

Impact of density gradients on the fluid flow inside a vibrating cavity subjected to soret effect

Computational fluid dynamics simulations of thermovibrational flows in a square cavity filled with a water–isopropanol mixture has shown that inaccurate density calculations can predict very different flow behaviours. Specifically, comparison has been made between two density calculation models, viz., a weighted‐average scheme and the Perturbed Chain Statistical Associating Fluid Theory equation of state. While the latter approach predicts a stronger flow in the cavity due to the convective instabilities that are induced by the large spatial gradients in density, the weighted‐average scheme cannot predict this since it does not explicitly depend on the temperature of the mixture. © 2012 Canadian Society for Chemical Engineering