In-vitro Cardiovascular Effects Of Gynura Procumbens (lour.) And Orthosiphon Stamineus (benth.)

Gynura procumbens dan Orthosiphon stamineus digunakan di dalam perubatan tradisional untuk mengubati penyakit darah tinggi. Gynura procumbens and Orthosiphon stamineus have been used as traditional medicine to treat hypertension

Fresh and hardened properties of self-compacting concrete containing of cement kiln dust

There are many wastes form the cement industry among them cement kiln dust (CKD). This residue is obtained after the process of burning the raw materials of cement in the rotary kiln where it is suctioned by fans during the clinker exit of the rotary kiln. Cement dust is a major environmental and economic problem in terms of high quality air pollution ranging from (20-100) microns and the proportions of chlorides, sulphates, alkali and lime living in a way that threatens the general health of human, as well as water pollution if the waste is discharged by rivers and waterways. This investigation’s main objective is to present the potential of using CKD as a cement replacement in self-compacting concrete (SCC). Eight mixes incorporating CKD with partial cement replacement of 0%, 5%, 10%, 20%, 30%, 40%, 50% and 75% in addition to control mix were investigated. The properties of all mixture were determined. Based on the experimental program results, it was found that SCC mixture incorporating 5% to 10% of CKD was almost similar to that of control mixture. The workability of SCC concrete decreased as CKD replacement increased. This established benefits of substituting cement by CKD to make SCC

Improving the Characteristics of Water-Based Drilling Fluids Using Nanoparticles

The capabilities of different types of nanoparticles (NPs) had been exploited to develop a water-based drilling fluid having better characteristics for harsh drilling conditions. More specifically, the objectives of this work are to: 1) investigate the effectiveness of using different oxide NPs: ferric oxide (of sizes< 50 nm), magnetic iron oxide (of average particle size 50 –100 nm), silica NPs (size =12 nm), and zinc oxide NPs (of sizes < 100 nm) on the rheological properties and filter cake characteristics of Ca-bentonite-based drilling fluid at downhole conditions, 2) conduct a sensitivity analysis of the rheological properties of these drilling fluids and investigate the effect of charge potential, 3) determine the optimum concentration of NPs, and 4) evaluate the effect of different drilling fluid additives on the performance of NPs/Ca-bentonite fluids by formulating and testing a complete bentonite-based drilling fluid formula. A reduction of 43% in the fluid loss volume was achieved when using 0.5 wt% of ferric oxide NPs with 7 wt% Ca-bentonite suspension compared to that without NPs. However, using silica or zinc oxide NPs at different concentrations resulted in an increase in the fluid loss volume and filter cake thickness. The inductively coupled plasma (ICP) analysis of the filtrate fluids and the scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) of the filter cakes revealed the replacement of the cations dissociated from the Ca-bentonite by ferric oxide NPs at the investigated conditions, which promoted the formation of rigid clay platelet structure. Furthermore, using 0.5 wt% of NPs provided less agglomeration, as shown by the SEM images, and less filter cake permeability. Moreover, the produced filter cake consisted of two layers, as indicated by the computed-tomography (CT) scan. Increasing the concentration of NPs resulted in an increase in the fluid loss and filter cake thickness. At high NP concentration (2.5 wt%), a new layer of the agglomerated NPs generated in the filter cake close to the surface of formation, which adversely affected the cake characteristics. The ferric oxide and magnetic iron oxide NPs/Ca-bentonite fluids were found to have stable rheological properties at different NP concentrations and temperatures (up to 200°F). Additionally, thermally aging these fluids at 350°F for 16 hours showed minor changes in their rheological properties, which confirmed their applicability in drilling downhole environments. The ferric oxide NPs improved the filter cake and filtration properties of Ca-bentonite-based drilling fluids in the presence of polymer and other additives under both static and dynamic filtration (at 100 rpm). The best filter cake characteristics were obtained when using a NP concentration of 0.3-0.5 wt%. Furthermore, the formulated NPs/Ca-bentonite-based drilling fluids could withstand downhole conditions up to 500 psi and 350°F and produced a filter cake that has 0.151-in. thickness, 6.9 ml filtrate loss volume, and 0.428 µd permeability at this conditions. Moreover, it was noticed that the ultrasonication for at least one hour and bentonite hydration for 16 hours are recommended for better preparation of the formulated ferric oxide NPs/Ca-bentonite-based drilling fluid

Effect of Invisible Exertions on Computed Tomography Radiologists in Saudi Hospitals

International audienceCurrent radiology practices face extreme pressure on available resources with demands of multi-dimensional requirements. Technicians are at the center of a constant drive for optimal productivity and optimization with the minimal possible resources. This paper evaluates the invisible physical and mental exertions resulting from operating computed tomography (CT) scans by fifty-seven technicians surveyed following current radiology practices. Demographic characteristics were reviewed to evaluate differences across the study variables based on gender, level of education, years of experience, and working sector

Inversion-based Workflow for Oilfield Nested Multi-Casing Evaluation Using Electromagnetic Low Frequency Measurements

Steel casing corrosion analysis is pivotal in well integrity evaluation for ensuring environment-friendly and efficient hydrocarbon production and for well abandonment at the end of the productive life of the well. Due to their sensitivity to metal loss and depth of investigation, low frequency electromagnetics (EM) based corrosion measurements have long been considered as viable non-destructive diagnostic means. For nested multi-casing evaluation, the quantitative data inversion and analysis requires a thorough understanding and modeling of the underlying measurement physics. We propose a model-based parametric inversion methodology for quantitative evaluation of multiple nested casings using multi-spacing and multi-frequency induction measurements, to determine effective thicknesses of individual pipes and take into account variations in casing conductivity and permeabilities. Axi-symmetric finite-element forward modeling is used in the inversion loop to match the tool responses allowing us to include the sensor details in the model. The presence of casing collars and ubiquitous eccentering of individual casings affects the tool responses and reduce the effectiveness of elementary interpretation schemes (often based on remote field eddy current concept and aimed primarily at providing the total metal loss). To quantify the effect of casing and measurement tool eccentering, we performed comprehensive 3- D finite-element modeling. The sensitivity and data resolution analysis is used to evaluate individual measurement importance and optimize the inversion based methodology. The workflow is capable of handling arbitrary number of nested casings and raises a QC flag for eccentered casings based on the reconstruction quality of short spacing measurements. Model covariance matrix from the inversion is used to quantify the inverted parameter uncertainty while the extended data resolution matrix concept is applied to extract information about the measurement channel reconstruction. The proposed methodology has been successfully validated on synthetic data and lab measurements

O(N) Iterative and O(NlogN) Fast Direct Volume

Abstract—Linear complexity iterative and log-linear complex- ity direct solvers are developed for the volume integral equation (VIE) based general large-scale electrodynamic analysis. The dense VIE system matrix is first represented by a new cluster- based multilevel low-rank representation. In this representation, all the admissible blocks associated with a single cluster are grouped together and represented by a single low-rank block, whose rank is minimized based on prescribed accuracy. From such an initial representation, an efficient algorithm is developed to generate a minimal-rank H2-matrix representation. This representation facilitates faster computation, and ensures the same minimal rank’s growth rate with electrical size as evaluated from singular value decomposition. Taking into account the rank’s growth with electrical size, we develop linear-complexity H -matrix-based storage and matrix-vector multiplication, and thereby an O(N ) iterative VIE solver regardless of electrical size. Moreover, we develop an O(NlogN ) matrix inversion, and hence a fast O(NlogN ) direct VIE solver for large-scale electrodynamic analysis. Both theoretical analysis and numerical simulations of large-scale 1-, 2- and 3-D structures on a single- core CPU, resulting in millions of unknowns, have demonstrated ty and superior performance of the proposed VIE electrodynamic solvers

Introducing a Machine Learning Password Metric Based on EFKM Clustering Algorithm

we introduce a password strength metric using Enhanced Fuzzy K-Means clustering algorithm (EFKM henceforth). The EFKM is trained on the OWASP list of 10002 weak passwords. After that, the optimized centroids are maximized to develop a password strength metric. The resulting meter was validated by contrasting with three entropy-based metrics using two datasets: the training dataset (OWASP) and a dataset that we collected from github website that contains 5189451 leaked passwords. Our metric is able to recognize all the passwords from the OWASP as weak passwords only. Regarding the leaked passwords, the metric recognizes almost the entire set as weak passwords. We found that the results of the EFKM-based metric and the entropy-based meters are consistent. Hence the EFKM metric demonstrates its validity as an efficient password strength checker