Analytical and comparative study of using a CNC machine spindle motor power and infrared technology for the design of a cutting tool condition monitoring system

This paper outlines a comparative study to compare between using the power of the spindle and the infrared images of the cutting tool to design a condition monitoring system. This paper compares the two technologies for the development of a tool condition monitoring for milling processes. Wavelet analysis is used to process the power signal. Image gradient and Wavelet analyses are used to process the infrared images. The results show that the image gradient and wavelet analysis are powerful image processing techniques in detecting tool wear. The power of the motor of the spindle has shown less sensitivity to tool conditions in this case when compared to infrared thermography

Postpartum Mental Health among Young Women

Background: A number of studies have highlighted the physical health problems associated with adolescent pregnancy in Saudi Arabia , However there were few studies dealing with the postpartum psychiatric disorders .The study aims to determine the prevalence of postpartum psychological distress and to evaluate the associated risk factors in a sample of primigravid young women in Al Ahsa region, Saudi Arabia. Methods: We assessed the prevalence of postnatal mental health in 190 young mothers attending the maternity hospital using general health questionnaire. We also assessed the relationship between socio-demographic, psychiatric and obstetric risk factors and the mental health. Results: The percent of women with psychological distress was 35.2%. Significant risk of psychological distress was associated with several socio-demographic, psychiatric and obstetric risk factors. Only four items were found to be significant predictors of postpartum psychological distress; low family income, poor husband support, birth of female baby and gestational diabetes. Conclusions: These results highlighted importance of screening for psychological distress and its associated risk factors in the implementation of proper perinatal care for the pregnant Saudi adolescents

The emerging role of 5-hydroxymethylcytosine in neurodegenerative diseases

Copyright © 2014 Al-Mahdawi, Anjomani Virmouni and Pook. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.This article has been made available through the Brunel Open Access Publishing Fund.DNA methylation primarily occurs within human cells as a 5-methylcytosine (5mC) modification of the cytosine bases in CpG dinucleotides. 5mC has proven to be an important epigenetic mark that is involved in the control of gene transcription for processes such as development and differentiation. However, recent studies have identified an alternative modification, 5-hydroxymethylcytosine (5hmC), which is formed by oxidation of 5mC by ten-eleven translocation (TET) enzymes. The overall levels of 5hmC in the mammalian genome are approximately 10% of 5mC levels, although higher levels have been detected in tissues of the central nervous system (CNS). The functions of 5hmC are not yet fully known, but evidence suggests that 5hmC may be both an intermediate product during the removal of 5mC by passive or active demethylation processes and also an epigenetic modification in its own right, regulating chromatin or transcriptional factors involved in processes such as neurodevelopment or environmental stress response. This review highlights our current understanding of the role that 5hmC plays in neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), fragile X-associated tremor/ataxia syndrome (FXTAS), Friedreich ataxia (FRDA), Huntington's disease (HD), and Parkinson's disease (PD).Sara Anjomani Virmouni was supported by funding to Mark A. Pook from the Friedreich’s Ataxia Research Alliance(FARA)

Robustness of complex networks to node and cluster damage

Copyright @ 2009 Universtiy of WarwickThe goal of this investigation is to assess the robustness of two popular network structures – random networks and scale-free networks – to node and cluster damage. There is no previous work on the latter. For node damage, we remove nodes iteratively and for cluster damage, we first build a network of clusters and then remove the nodes (clusters)

Epigenetics in Friedreich's ataxia: Challenges and opportunities for therapy

Copyright © 2013 Chiranjeevi Sandi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Friedreich's ataxia (FRDA) is an autosomal recessive neurodegenerative disorder caused by homozygous expansion of a GAA·TTC trinucleotide repeat within the first intron of the FXN gene, leading to reduced FXN transcription and decreased levels of frataxin protein. Recent advances in FRDA research have revealed the presence of several epigenetic modifications that are either directly or indirectly involved in this FXN gene silencing. Although epigenetic marks may be inherited from one generation to the next, modifications of DNA and histones can be reversed, indicating that they are suitable targets for epigenetic-based therapy. Unlike other trinucleotide repeat disorders, such as Huntington disease, the large expansions of GAA·TTC repeats in FRDA do not produce a change in the frataxin amino acid sequence, but they produce reduced levels of normal frataxin. Therefore, transcriptional reactivation of the FXN gene provides a good therapeutic option. The present paper will initially focus on the epigenetic changes seen in FRDA patients and their role in the silencing of FXN gene and will be concluded by considering the potential epigenetic therapies.This study is supported by funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant agreement no. 242193/EFACTS; and by funding from theWellcome Trust (089757)

Power optimization for a hydrocarbon industrial plant using a genetic algorithm

In this paper, a genetic algorithm (GA) is considered for optimizing electrical power loss for a real hydrocarbon industrial plant as a single objective problem. The subject plant electrical system consists of 275 buses, two gas turbine generators, two steam turbine generators, large synchronous motors, and other rotational and static loads. The minimization of power losses (J1) objective is used to guide the optimization process, and, consequently, the injected power into the grid (PRInject) is increased. The results obtained demonstrate the potential and effectiveness of the proposed approach to optimize the power consumption. Also, in this paper a cost appraisal for the potential daily, monthly and annual cost saving will be addressed

Impact of limited solvent capacity on metabolic rate, enzyme activities, and metabolite concentrations of S. cerevisiae glycolysis

The cell's cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic rate determined by the solvent capacity constraint is close to that measured in vivo. These results indicate that the limited solvent capacity is a relevant constraint acting on S. cerevisiae at physiological growth conditions, and that a full kinetic model together with the limited solvent capacity constraint can be used to predict both metabolite concentrations and enzyme activities in vivo. © 2008 Vazquez et al

Induced systemic resistance and promotion of wheat and barley plants growth by biotic and non-biotic agents against barley yellow dwarf virus

Barley yellow dwarf virus (BYDV) is an important virus infecting wheat and barley plants and transmitted by several species of aphids in Iraq. Pseudomonas fluorescence and Azospirillum irakense at 108 CFU/ml, Sea force extract and Elsa fungicide at 1 ml/L were used to induce resistance in the plant against BYDV. The four elements were applied before and after virus-plant inoculation. Results show that all elements stimulated plant growth as estimated by plant heights and chlorophyll concentrations, and elicited significant reduction in disease incidence as determine by BYDV-disease scoring symptoms. The applications of these elements twice (before and after virus inoculation) were found to be more efficient in promoting plant growth and reducing virus disease score. The plant heights, chlorophyll concentrations and BYDV-disease scores were 82.25, 85.59, 74.38, 76.26 cm, 54.19, 45.81, 47.98, 47.85 μg/cm2 and 2.0, 3.2, 2.8, 3.3 for P. fluorescence, A. irakense, Sea force extract, and Elsa fungicide treatments, respectively as compared to 62.08 cm, 38.10 μg/cm2 and 1.2 in control treatments for the same parameters. P. fluorescence was more efficient in reducing disease incidence (2.0) as compared to 3.2 with A. irakense, 2.8 with Sea force extract, 3.3 with Elsa, and 5.4 with control. The partially resistant lines, (IBA 99, Arivate and Karonea) were found to be more responsive to treatments than the susceptible ones (Hashmia and Kara).Key words: Sea force extract, barley yellow dwarf virus, Azospirillum irakense, Elsa fungicide

Investigating IoT Middleware Platforms for Smart Application Development

With the growing number of Internet of Things (IoT) devices, the data generated through these devices is also increasing. By 2030, it is been predicted that the number of IoT devices will exceed the number of human beings on earth. This gives rise to the requirement of middleware platform that can manage IoT devices, intelligently store and process gigantic data generated for building smart applications such as Smart Cities, Smart Healthcare, Smart Industry, and others. At present, market is overwhelming with the number of IoT middleware platforms with specific features. This raises one of the most serious and least discussed challenge for application developer to choose suitable platform for their application development. Across the literature, very little attempt is done in classifying or comparing IoT middleware platforms for the applications. This paper categorizes IoT platforms into four categories namely-publicly traded, open source, developer friendly and end-to-end connectivity. Some of the popular middleware platforms in each category are investigated based on general IoT architecture. Comparison of IoT middleware platforms in each category, based on basic, sensing, communication and application development features is presented. This study can be useful for IoT application developers to select the most appropriate platform according to their application requirement