Hydrodynamic and shock heating instabilities of liquid metal strippers for RIA

Stripping of accelerated ions is a key problem for the design of RIA to obtain high efficiency. Thin liquid Lithium film flow is currently considered as stripper for RIA ion beams to obtain higher Z for following acceleration: in extreme case of Uranium from Z=29 to Z=60-70 (first stripper) and from Z=70 till full stripping Z=92 (second stripper). Ionization of ion occurs due to the interaction of the ion with electrons of target material (Lithium) with the loss of parts of the energy due to ionization, Q{sub U}, which is also accompanied with ionization energy losses, Q{sub Li} of the lithium. The resulting heat is so high that can be removed not by heat conduction but mainly by convection, i.e., flowing of liquid metal across beam spot area. The interaction of the beam with the liquid metal generates shock wave propagating along direction perpendicular to the beam as well as excites oscillations along beam direction. We studied the dynamics of these excited waves to determine conditions for film stability at the required velocities for heat removal. It will allow optimizing jet nozzle shapes and flow parameters to prevent film fragmentation and to ensure stable device operation

FACING THE INTELLECTUAL AND CULTURAL CHALLENGES AMONG THE MUSLIM UMMAH IN THE 21ST CENTURY

1. Overview of the Fourth Industrial Revolution 2. Industrial Revolution Implications on people 3. IR4 impact on the Muslim ummah 4. Intellectual and culturalChallenges in the Muslim umma

CLUSTERING ALGORITHMS FOR CATEGORICAL DATA USING CONCEPTS OF SIGNIFICANCE AND DEPENDENCE OF ATTRIBUTES

Clustering categorical data is an essential and integral part of data mining. In this paper, we propose two new algorithms for clustering categorical data, namely, the Standard Deviation of Standard Deviation Significance and Standard Deviation of Standard Deviation Dependence algorithms. The proposed techniques are based mainly on rough set theory, taking into account the significance and dependence of attributes of database concepts. Analysis of the performance of the proposed algorithms compared with others shows their efficiency as well as ability to handle uncertainty together with categorical data

Quantum Modeling of Thermodynamic Properties of Warm Dense Aluminum

Warm dense matter is attracting a lot of attention in the scientific community, due to its formation during intense laser-matter interaction and inertial confinement fusion. However, there is no accurate solution to mapping out the thermodynamic properties of warm dense matter. Experimental data are also incredibly scarce making computational models an incredibly useful tool. This paper provides equation of state (EOS) data for aluminum at specific densities within the warm dense matter regime. The EOS data were calculated using quantum molecular dynamics, which was performed by the computational package QuatumEspresso. EOS were determined by collecting and recording pressure after achieving equilibrium at a constant temperature and density. EOS data are plotted as a phase diagram. We found QuantumEspresso to be an accurate tool for predicting thermodynamic properties of WDM. Future research can be expanded to other materials and elements. The additional data on different materials can help other researchers to find trends and accurate EOS for warm dense matter

Cold Atmospheric Plasma: An Inside Look Through Optical Diagnostics for Biomedical Applications

An emerging technology for medical applications is cold atmospheric plasma (CAP). CAP is generated using various gasses in a “pen” to create room temperature plasma and then carry the effluents and species. Success has been shown when cold atmospheric plasma is applied to oncology treatments, accelerated wound healing, pathogen disinfection, and various material-changing effects. However, the mechanisms behind these effects are still speculative. This study uses multiple diagnostic techniques including fast photography, two wavelength emission spectroscopy and optical emission spectroscopy to characterize the plasma properties and eventually further test the plasma’s interaction with biological samples. The plume dynamics are observed using fast photography methods, allowing determining visible intensity, plume length, and peak intensity, as gas flow rates and mixture are varied. A two wavelength emission spectroscopy approach is used for determination of plume temperature, using narrow band optical filters at 480 nm and 510 nm. Pixel-by-pixel, ratio of intensities is used to predict the temperature with novel image processing code. Optical emission spectroscopy is used to determine the chemical species along the plume length. The temperature of the plume is found to be slightly above room temperature at the core and then cools towards the tip. The temperature varies with intensity and peaks around 6.5lpm with pure argon and varies with gas mixture. Pure argon has the greatest intensity and plume length. The plume seems to be mostly comprised of reactive oxygen and nitrogen agents (RONS). It is likely these RONS that cause the various effects, especially in oncology

Design and analysis of a new brake-by-wire system using machine learning

One of the main aims of the recent research on brake-by-wire systems is to decrease mechanical components. In this paper, we propose replacing the brake pedal with a driving wheel that is fully covered by pressure braking batch sensors. The new mechanism for braking translates pressure exerted through the driver’s hands on the driving wheel to a corresponding electrical signal. A proposed design for the pressure braking batch (PBB) is made out of a mesh of conducting threads separated by a resistive sheet. To the best of our knowledge, this idea has not been raised before in other research papers. Different people have different muscle strengths and so the problem of identifying the intention of the user when pressing the PBB is tackled. For this aim, a new dataset of its kind is created by several volunteers. From each volunteer, age, gender, body mass index (BMI), and maximum pressure exerted on the driving wheel are collected. Using Weka software, the detection accuracy is calculated for a new volunteer to know the intention of his/her pressure on PBB. Among the three algorithms tried, the regression tree gives the best results in predicting the class of the pressure exerted by the volunteers

The Impact of Animation Program on Arabic Learning Vocabulary Recall Among Primary School Pupels: A Case Study at Al-Amin Islamic Primary School, Gombak

In Al Amin Gombak Islamic Primary School, vocabulary recall and acquisition of verbal skills is a major concern in Arabic Language Learning. Classical teaching techniques and learning materials has become ineffective in ensuring the acquisition of those skills. Although each class is equipped with a HD television that can be connected to a laptop via a USB cable, animation programs have yet to be used by the teachers in teaching Arabic Language

INFORMATIVENESS OF UNAUDITED FORWARD-LOOKING FINANCIAL DISCLOSURE: EVIDENCE FROM UK NARRATIVE REPORTING

Forward-looking financial disclosure (FLFD) is potentially uninformative if it does not change from the previous year, especially after a significant change in firm performance. This study uses a sample of UK narrative statements of the annual reports over the period from 2005 to 2011. It employed the automated content analysis technique to measure change in FLFD over years to answer three research questions. First, to what extent does change in firms’ earnings performance drive managers to change FLFD over years? Second, what are the other drivers of the change of FLFD from year to year? Third, do investors use information revealed by the change in FLFD? The study finds a positive association between change in FLFD and change in firm earnings performance. However, it finds weak evidence that firms with larger changes in their earnings performance are likely to change their FLFD more than those with smaller performance changes. In addition, when we distinguish between well-performing and poorly performing firms, it finds that the change in FLFD is more positively associated with poorly performing firms compared to well-performing firms. Furthermore, it finds that change in FLFD is positively (negatively) associated with firm size, (competitive environment), (litigious environment), and (percentage of managerial ownership). In addition, the role of the auditor in overseeing narrative reporting is not appearing for all sample firms or for well-performing firms, however, it is observable only in poorly performing firms. Finally, the study uses firm value three months after the release of the annual report to examine investors’ responses to the changes in FLFD. It finds that the value of a firm decreases as long as it changes its FLFD from the previous year. However, when we distinguish between well and poorly performing firms, it finds that the change in FLFD has no effect on the value of well-performing firms, while, it negatively affects poorly performing firms. The results suggest that FLFD in UK narratives includes some content about firm performance. However, it neither affects the value of well-performing firms nor enhances investors’ valuation of poorly performing firms.Egyptian Ministry of Higher Education - Egyptian Cultural and Educational Bureau in London - Mansoura University in Egyp

STR-830: ENHANCING THE DEFORMATION CAPACITY OF CONCRETE SHEAR WALLS REINFORCED WITH GFRP BARS

An experimental study was recently conducted to address the applicability of concrete shear walls entirely reinforced with glass-fiber-reinforced polymer (GFRP) bars and subjected to quasi-static reversed cyclic lateral loading in attaining reasonable strength and drift requirements specified in different codes. The reported test results clearly show that properly designed and detailed GFRP-reinforced concrete (RC) walls could reach their flexural capacities with no strength degradation. The results also demonstrate that the tested walls were able to achieve recoverable and self-centering behavior up to allowable drift limits before experiencing moderate damage and attain a maximum drift comparable to steel-RC walls. The promising results provide impetus for constructing shear walls with GFRP bars and constitute a step toward using GFRP bars in lateral-resisting systems. Since enhancing concrete confinement at the boundary might be a solution in attempting to increase the deformation capacity of GFRP-RC shear walls without significant loss of strength, a series of shear walls were constructed with different reinforcement confinement configurations at the boundary zone. This paper compares the first tested shear wall to a previously reported shear wall (Mohamed et al 2014a). The results show a significant increase in lateral drift and strength of almost 79% and 27%, respectively, by doubling the confinement reinforcement ratio of the boundary. The seismic behavior of the wall was obviously improved, and the deformability level was significantly enhanced