Soft mode dynamics of ferroelectric relaxors

International audienceHyper-Raman scattering is a non-linear inelastic spectroscopy sensitive to polar excitations of solids whatever the crystalline symmetry. This selection rule is very attractive in particular for centrosymmetric structures for which polar modes are inactive in Raman. HRS has been performed in the cubic relaxors PbMg1/3Nb2/3O3 (PMN) and PbMg1/3Ta2/3O3 (PMT), with particular attention to the low frequency region, down to about 2 cm-1. Spectra have been recorded over a wide temperature range (900K-30K in PMN) and the results compared to existing infrared and neutron scattering data. This complete set of vibrational information provides the framework for a detailed analysis of the polarization dynamics in these systems. In particular, in both materials, the soft mode response exhibits a doublet structure up to the highest temperature investigated [1,2] emphasizing therefore a common property of cubic relaxors. The lowest frequency component is assigned to the primary soft mode of symmetry F1u, while the second likely originates from a local disorder persisting until very high temperatures, and which lifts the cubic selection rules. On cooling, the soft F1u-mode of PMN becomes overdamped at the onset of the Burns temperature but very interestingly, it splits between 600K and 400K into two components which harden on decreasing further the temperature. This behavior likely highlights the onset of a local anisotropy of the polarization and provides therefore new insight about the relaxor nature

Comprehensive study: machine learning approaches for COVID-19 diagnosis

Coronavirus disease 2019 (COVID-19) is caused a large number of death since has declared as an international pandemic in December 2019, and it is spreading all over the world (more than 200 countries). This situation puts the health organizations in an aberrant demand for urgent needs to develop significant early detection and monitoring smart solutions. Therefore, that new system or solution might be capable to identify COVID-19 quickly and accurately. Nowadays, the science of artificial intelligence (AI), and internet of things (IoT) techniques have an extensive range of applications, it can be initiated a possible solution for early detection and accurate decisions. We believe, combine both of the IoT revolution and machine learning (ML) methods are expected to reshape healthcare treatment strategies to provide smart (diagnosis, treatments, monitoring, and hospitals). This work aims to overview the recent solutions that have been used for early detection, and to provide the researchers a comprehensive summary that contribute to the pandemic control such AI, IoT, cloud, fog, algorithms, and all the dataset and their sources that recently published. In addition, all models, frameworks, monitoring systems, devices, and ideas (in four sections) have been sufficiently presented with all clarifications and justifications. Also, we propose a new vision for early detection based on IoT sensors data entry using 1 million patients-data to verify three proposed methods

Improving saddle stitching line using affordable embedded system

In most printing factories, the stitching machine is considered as a significant tool in accomplishing the printing process cycle, such as in the Printing House of the University of Kufa (PHUK), complete their jobs using a cheap manual machine, and thus this leads to an increase in the number of employees and work hours. That is because the automated stitching machine of production is very costly. A decent printing house design maximizes production with a minimum investment in new equipment parts. However, a decent PHUK layout alone cannot reach the intended aims unless firmly linked with a developed production line of an automated stitching machine for the purpose of reducing cost, time, and efforts. This article focused on designing and developing automatic saddle stitching machines for folded paper sheet products such as newspapers, magazines, catalogs, exam sheets, etc. using accommodate devices such as Arduino and infrared sensors. Furthermore, the proposed design is applied in PHUK successfully and it showed that the cost of the stitching machine and the manpower is reduced by 60 percent, also the time is reduced by 70 percent. Finally, one of the significant implications of this work is using IT in management of resources

An insight into internet sector in Iraq

The internet is considered to be the most advanced technology today and a gateway to modern communication and the sharing of information, products, services, and technology. Nowadays, users want to be able to access anywhere and anytime several services and applications, which is increasing data traffic and triggering a mobile data explosion. Iraq has major problems in increasing the growth and use of the internet and changing the standard method of communication. This is a big challenge, however, since there are several variables that characterize this phase of transformation. In this paper, the problems, vision, and solutions are presented in details. This study aims to clarify the factors of internet use in Iraq by the use of an acceptable approach and by suggesting new solutions for all the presented problems. This work also, clarify the expected traffic and the mechanism to transform the traffic between local ISP’s networks (AS) internet exchange points

The role of endogenous free radical signalling in human endometrium

Differentiation of human endometrial stromal cells (HESCs) into specialized decidual cells is critical for embryo implantation and maintenance of a successful pregnancy. Initiation of this differentiation process, termed decidualization, is strictly dependent on elevated cAMP levels, whereas its maintenance requires continuous progesterone signalling. Here I show that NADPH oxidase-dependent reactive oxygen species (ROS) play a critical role in initiating and maintaining the decidual process. I first show that cAMP-dependent induction of decidual marker genes can be attenuated or enhanced upon inhibition or activation of the NADPH oxidase complex, respectively. Time-course analysis demonstrated that cAMP enhances endogenous ROS production, apparent after 12 hours of stimulation, which coincides with a marked induction of differentiation markers. By a process of elimination, I identified NOX4 as the main catalytic subunit involved in decidualization. Silencing of NOX4, or its cofactor p22PHOX, impaired the decidual process. I then show that the NOX4/p22PHOX complex regulates the transcriptional activity of CCAAT/enhancer binding protein β, a key regulator of HESC differentiation. Furthermore, microarray analysis revealed that the NOX4/p22PHOX complex functions downstream FOXO1, a multifaceted transcription factor involved in antioxidant defences, DNA repair and cell cycle regulation. In agreement, knockdown of NOX4/p22PHOX complex disrupted endogenous ROS production and resulted in a paradoxical prooxidant stress response further characterized by activation of the DNA repair pathway in the absence of primary DNA damage or cell death. Finally, I provide preliminary data that p22PHOX is downregulated at the transcript and protein level in the eutopic endometrium of patients with endometriosis. In summary, endogenous ROS signalling is critical for the differentiation and redox homeostasis of HESCs. Furthermore, deregulation of endometrial NADPH oxidase-dependent ROS production and signalling may be a hallmark of endometriosis, a prevalent and debilitating reproductive disorder

Sentiment analysis of comments in social media

Social media platforms are witnessing a significant growth in both size and purpose. One specific aspect of social media platforms is sentiment analysis, by which insights into the emotions and feelings of a person can be inferred from their posted text. Research related to sentiment analysis is acquiring substantial interest as it is a promising filed that can improve user experience and provide countless personalized services. Twitter is one of the most popular social media platforms, it has users from different regions with a variety of cultures and languages. It can thus provide valuable information for a diverse and large amount of data to be used to improve decision making. In this paper, the sentiment orientation of the textual features and emoji-based components is studied targeting “Tweets” and comments posted in Arabic on Twitter, during the 2018 world cup event. This study also measures the significance of analyzing texts including or excluding emojis. The data is obtained from thousands of extracted tweets, to find the results of sentiment analysis for texts and emojis separately. Results show that emojis support the sentiment orientation of the texts and that texts or emojis cannot separately provide reliable information as they complement each other to give the intended meaning

Development an Anomaly Network Intrusion Detection System Using Neural Network

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypted HTTP subset traffic of DARPA 1999 data set, from 55.234% in the PAYL system alone to 99.94% in the proposed system; due to the existence of the neural network self-organizing map (SOM). In addition SOM decreases the ratio of false positive from 44.676% in the PAYL system alone to 5.176% in the proposed system. The proposed system provides 80% detection ability of smart worms that are meant to invade the PAYL detector in the PAYL system alone, due to the existence of the randomization stage in the proposed system

Oral manifestations in young adults infected with COVID-19 and impact of smoking:a multi-country cross-sectional study

Background: Oral manifestations and lesions could adversely impact the quality of people's lives. COVID-19 infection may interact with smoking and the impact on oral manifestations is yet to be discovered. Objectives: The aim of this study was to assess the self-reported presence of oral lesions by COVID-19-infected young adults and the differences in the association between oral lesions and COVID-19 infection in smokers and non-smokers. Methods: This cross-sectional multi-country study recruited 18-to-23-year-old adults. A validated questionnaire was used to collect data on COVID-19-infection status, smoking and the presence of oral lesions (dry mouth, change in taste, and others) using an online platform. Multi-level logistic regression was used to assess the associations between the oral lesions and COVID-19 infection; the modifying effect of smoking on the associations. Results: Data was available from 5,342 respondents from 43 countries. Of these, 8.1% reported COVID-19-infection, 42.7% had oral manifestations and 12.3% were smokers. A significantly greater percentage of participants with COVID-19-infection reported dry mouth and change in taste than non-infected participants. Dry mouth (AOR=, 9=xxx) and changed taste (AOR=, 9=xxx) were associated with COVID-19-infection. The association between COVID-19-infection and dry mouth was stronger among smokers than non-smokers (AOR = 1.26 and 1.03, p = 0.09) while the association with change in taste was stronger among non-smokers (AOR = 1.22 and 1.13, p = 0.86). Conclusion: Dry mouth and changed taste may be used as an indicator for COVID-19 infection in low COVID-19-testing environments. Smoking may modify the association between some oral lesions and COVID-19-infection

Medical genetics in developing countries in the Asia-Pacific region: challenges and opportunities

Advances in genetic and genomic technology changed health-care services rapidly in low and middle income countries (LMICs) in the Asia-Pacific region. While genetic services were initially focused on population-based disease prevention strategies, they have evolved into clinic-based and therapeutics-oriented service. Many LMICs struggled with these noncommunicable diseases and were unprepared for the needs of a clinical genetic service. The emergence of a middle class population, the lack of regulatory oversight, and weak capacity-building in medical genetics expertise and genetic counseling services led to a range of genetic services of variable quality with minimal ethical oversight. Some of the current shortcomings faced include the lack of awareness of cultural values in genetic health care, the variable stages of socioeconomic development and educational background that led to increased demand and abuse of genetics, the role of women in society and the crisis of gender selection, the lack of preventive and care services for genetic and birth defects, the issues of gene ethics in medicine, and the lack of understanding of some religious controversies. These challenges provide opportunities for both developing and developed nations to work together to reduce the inequalities and to ensure a caring, inclusive, ethical, and cost-effective genetic service in the region