Implementation and evaluation of online gas-phase chemistry within a regional climate model (RegCM-CHEM4)

Abstract. The RegCM-CHEM4 is a new online climate-chemistry model based on the International Centre for Theoretical Physics (ICTP) regional climate model (RegCM4). Tropospheric gas-phase chemistry is integrated into the climate model using the condensed version of the Carbon Bond Mechanism (CBM-Z; Zaveri and Peters, 1999) with a fast solver based on radical balances. We evaluate the model over continental Europe for two different time scales: (1) an event-based analysis of the ozone episode associated with the heat wave of August 2003 and (2) a climatological analysis of a six-year simulation (2000–2005). For the episode analysis, model simulations show good agreement with European Monitoring and Evaluation Programme (EMEP) observations of hourly ozone over different regions in Europe and capture ozone concentrations during and after the summer 2003 heat wave event. For long-term climate simulations, the model captures the seasonal cycle of ozone concentrations with some over prediction of ozone concentrations in non-heat wave summers. Overall, the ozone and ozone precursor evaluation shows the feasibility of using RegCM-CHEM4 for decadal-length simulations of chemistry-climate interactions

Egyptian EFL Writers’ and Instructors’ Perceptions of Peer Written Feedback

The principal aim of this study is to compare between peer feedback (PF) and teacher feedback (TF) as perceived by adult Egyptian L2 writers. That aim is pursued to seal a gap in the literature, which is the inadequacy of that line of research in Egypt, and particularly targeting adult L2 writers. Earlier researchers have urged other researchers to conduct more research in different countries and in different instructional settings. Consequently, the study is guided by four research questions enquiring about general perceptions of PF versus TF, how PF and TF prioritise feedback on writing features, the perceptions of PF and TF uptake, and differences in gender perception of PF and TF. Adopting a mixed method, the sample included: 81 questionnaire participants, seven interviewees, and 16 writing samples. The data analysis reveals a considerable awareness of the importance of PF, but TF is on the lead slightly. The data shows that peers prioritise almost the same writing features as teachers; however, there is a large gap in the instances of highlighting the errors in those features. Moreover, L2 writers in Egypt perceive the PF and TF uptake in roughly the same way. Finally, the investigation of gender differences yields no significant differences quantitatively, but the interviewed sample indicates that male participants see differences in accepting PF. Results imply that PF practices ought to be encouraged in adult L2 education in Egypt. Teachers need to train learners to provide effective feedback, especially in large classes, to promote more interaction, and create communities of learning among learners

Shape/image registration for medical imaging : novel algorithms and applications.

This dissertation looks at two different categories of the registration approaches: Shape registration, and Image registration. It also considers the applications of these approaches into the medical imaging field. Shape registration is an important problem in computer vision, computer graphics and medical imaging. It has been handled in different manners in many applications like shapebased segmentation, shape recognition, and tracking. Image registration is the process of overlaying two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. Many image processing applications like remote sensing, fusion of medical images, and computer-aided surgery need image registration. This study deals with two different applications in the field of medical image analysis. The first one is related to shape-based segmentation of the human vertebral bodies (VBs). The vertebra consists of the VB, spinous, and other anatomical regions. Spinous pedicles, and ribs should not be included in the bone mineral density (BMD) measurements. The VB segmentation is not an easy task since the ribs have similar gray level information. This dissertation investigates two different segmentation approaches. Both of them are obeying the variational shape-based segmentation frameworks. The first approach deals with two dimensional (2D) case. This segmentation approach starts with obtaining the initial segmentation using the intensity/spatial interaction models. Then, shape model is registered to the image domain. Finally, the optimal segmentation is obtained using the optimization of an energy functional which integrating the shape model with the intensity information. The second one is a 3D simultaneous segmentation and registration approach. The information of the intensity is handled by embedding a Willmore flow into the level set segmentation framework. Then the shape variations are estimated using a new distance probabilistic model. The experimental results show that the segmentation accuracy of the framework are much higher than other alternatives. Applications on BMD measurements of vertebral body are given to illustrate the accuracy of the proposed segmentation approach. The second application is related to the field of computer-aided surgery, specifically on ankle fusion surgery. The long-term goal of this work is to apply this technique to ankle fusion surgery to determine the proper size and orientation of the screws that are used for fusing the bones together. In addition, we try to localize the best bone region to fix these screws. To achieve these goals, the 2D-3D registration is introduced. The role of 2D-3D registration is to enhance the quality of the surgical procedure in terms of time and accuracy, and would greatly reduce the need for repeated surgeries; thus, saving the patients time, expense, and trauma

Minimum Free Energy, Partition Function and Kinetics Simulation Algorithms for a Multistranded Scaffolded DNA Computer

Polynomial time dynamic programming algorithms play a crucial role in the design, analysis and engineering of nucleic acid systems including DNA computers and DNA/RNA nanostructures. However, in complex multistranded or pseudoknotted systems, computing the minimum free energy (MFE), and partition function of nucleic acid systems is NP-hard. Despite this, multistranded and/or pseudoknotted systems represent some of the most utilised and successful systems in the field. This leaves open the tempting possibility that many of the kinds of multistranded and/or pseudoknotted systems we wish to engineer actually fall into restricted classes, that do in fact have polynomial time algorithms, but we\u27ve just not found them yet. Here, we give polynomial time algorithms for MFE and partition function calculation for a restricted kind of multistranded system called the 1D scaffolded DNA computer. This model of computation thermodynamically favours correct outputs over erroneous states, simulates finite state machines in 1D and Boolean circuits in 2D, and is amenable to DNA storage applications. In an effort to begin to ask the question of whether we can naturally compare the expressivity of nucleic acid systems based on the computational complexity of prediction of their preferred energetic states, we show our MFE problem is in logspace (the complexity class L), making it perhaps one of the simplest known, natural, nucleic acid MFE problems. Finally, we provide a stochastic kinetic simulator for the 1D scaffolded DNA computer and evaluate strategies for efficiently speeding up this thermodynamically favourable system in a constant-temperature kinetic regime

COMPARISON OF FT-NIR TRANSMISSION AND HPLC FOR GREEN APPROACH TO DETERMINE PARACETAMOL AND ITS DEGRADATION PRODUCT 4-AMINOPHENOL IN PARACETAMOL TABLETS

Objective: Development and validation of Near infrared (NIR) spectroscopic method for determination of paracetamol and its major degradation product 4-aminophenol in paracetamol tablets and show the agreement between the NIR as a greener technique and the conventional high performance liquid chromatography (HPLC) method, official in British pharmacopeia (BP).Methods: Calibration model for paracetamol and its degradation product 4-aminophenol was built by utilizing chemometric processing which is the most critical step in the development of specific and robust NIR models. It is based mainly on a partial least square regression fit on the transmission mode using paracetamol, 4-aminophenol and excipient materials of the drug products. The results obtained by NIR spectroscopy were compared with the compendial HPLC method in the BP.Results: The chosen models had a root mean square error of the cross validation (RMSECV) values of 1.38, 1.42 and coefficient of correlation (r2) of 99.1, 99.05 for paracetamol and 4-aminophenol respectively, which indicates good fitness and accuracy of the model.Conclusion: The present study showed that NIR could be used with high accuracy for determination of for parent drug and its major degradation product in paracetamol tablets. This proposed technique realizes many of green analytical aspects in developing eco-friendly analytical methods and may replace safely the conventional chromatographic technique without compromising efficacy. Â

DEVELOPMENT AND VALIDATION OF STABILITY INDICATING GREEN HPLC-UV METHOD FOR DETERMINATION OF CEPHALEXIN IN PHARMACEUTICAL DOSAGE FORMS AND HUMAN URINE USING MICELLAR MOBILE PHASE

Objective: Development and validation of simple, stability indicating and green high performance liquid chromatographic (HPLC) method with ultraviolet (UV) detection for determination of cephalexin in pure form, pharmaceutical dosage forms and human urine samples.Methods: The method is based on using of a micellar mobile phase for separation of cephalexin and its degradation products. The analyte was chromatographed on a Kinetex C18 75×4.6 mm, 2.6 μm column. Micellar mobile phase composed of 0.1M sodium dodecyl sulphate (SDS) and 10 % isopropanol (IPA), pH was adjusted to 3±0.05 with phosphoric acid, the flow-rate was 1.0 mL/min, the UV detector was set at 254 nm and the injection volume was 20 µl. Stability indicating properties of the proposed method was proved through exposure of the analyte solutions to 4 different stress conditions of acidic, basic, oxidative and photo-irradiation conditions.Results: Under optimized conditions the average recovery was ranged from 100.4–101.7%. The lower limit of quantification (LOQ) and the lower limit of detection (LOD) were 0.097 and 0.029 μg/ml, respectively. A linear correlation in the range of 1–200 μg/ml with the correlation coefficient (r2) of ≥ 0.999 was obtained. Relatively high inter-and intra-day precisions were achieved, the percentage RSD values were lower than 2. The obtained results were validated according to USP validation parameters.Conclusion: The proposed method was found to be not only a greener method but also faster and more convenient than the USP compendial method. Greener here means that the method is more eco-friendly as it avoids usage of toxic solvent and reagent and switch to more benign chemicals. In addition, allow for injection of urine samples directly into an analytical column without pretreatment due to micellar solubilization of the interfering components of the biological samples.Â

Nurses' Perceptions of Patient Safety Culture in Intensive Care Units: A Cross-Sectional Study

BACKGROUND: Patient safety culture is a relatively new focus where little is known about its current status in Egypt’s teaching hospitals, mainly intensive care units (ICUs). Therefore, the authors of this study attempted to assess the patient safety culture dimensions from the nurses’ perspective. METHODS: An exploratory cross-sectional study was conducted in two ICUs (pediatric ICU and adult ICU) at the University Hospital over 3 months from October till December 2018. Sixty nurses were interviewed using the Hospital Survey on Patient Safety Culture. RESULTS: The current study findings revealed an average positive response to individual items ranging from 6% to 51%. The “Organizational learning†dimension had the highest average percent positive patient safety dimension score (51%) among all respondents, while the “Frequency of events reported†dimension had the lowest one (6%). No statistically significant difference was reported between the pediatric and adult ICUs for all mean scores except for the “Non-punitive response to error†dimension which was reported to be greater in the pediatric intensive care unit (PICU) compared to adult ICU (P < 0.005). The overall patient safety grade was rated acceptable by 47.5% of the interviewed nurses. CONCLUSION: The current study shows that patient safety is fragile in ICUs, and more effort is recommended to increase the awareness of health care providers. Also, hospital managers need to enhance the performance and practices of patient safety within a non-punitive reporting environment

Fingerprint Recognition: A Histogram Analysis Based Fuzzy C-Means Multilevel Structural Approach

In order to fight identity fraud, the use of a reliable personal identifier has become a necessity. Fingerprints are considered one of the best biometric measurements and are used as a universal personal identifier. There are two main phases in the recognition of personal identity using fingerprints: 1) extraction of suitable features of fingerprints, and 2) fingerprint matching making use of the extracted features to find the correspondence and similarity between the fingerprint images. Use of global features in minutia-based fingerprint recognition schemes enhances their recognition capability but at the expense of a substantially increased complexity. The recognition accuracies of most of the fingerprint recognition schemes, which rely on some sort of crisp clustering of the fingerprint features, are adversely affected due to the problems associated with the behavioral and anatomical characteristics of the fingerprints. The objective of this research is to develop efficient and cost-effective techniques for fingerprint recognition, that can meet the challenges arising from using both the local and global features of the fingerprints as well as effectively deal with the problems resulting from the crisp clustering of the fingerprint features. To this end, the structural information of local and global features of fingerprints are used for their decomposition, representation and matching in a multilevel hierarchical framework. The problems associated with the crisp clustering of the fingerprint features are addressed by incorporating the ideas of fuzzy logic in developing the various stages of the proposed fingerprint recognition scheme. In the first part of this thesis, a novel low-complexity multilevel structural scheme for fingerprint recognition (MSFR) is proposed by first decomposing fingerprint images into regions based on crisp partitioning of some global features of the fingerprints. Then, multilevel feature vectors representing the structural information of the fingerprints are formulated by employing both the global and local features, and a fast multilevel matching algorithm using this representation is devised. Inspired by the ability of fuzzy-based clustering techniques in dealing more effectively with the natural patterns, in the second part of the thesis, a new fuzzy based clustering technique that can deal with the partitioning problem of the fingerprint having the behavioral and anatomical characteristics is proposed and then used to develop a fuzzy based multilevel structural fingerprint recognition scheme. First, a histogram analysis fuzzy c-means (HA-FCM) clustering technique is devised for the partitioning of the fingerprints. The parameters of this partitioning technique, i.e., the number of clusters and the set of initial cluster centers, are determined in an automated manner by employing the histogram of the fingerprint orientation field. The development of the HA-FCM partitioning scheme is further pursued to devise an enhanced HA-FCM (EAH-FCM) algorithm. In this algorithm, the smoothness of the fingerprint partitioning is improved through a regularization of the fingerprint orientation field, and the computational complexity is reduced by decreasing the number of operations and by increasing the convergence rate of the underlying iterative process of the HA-FCM technique. Finally, a new fuzzy based fingerprint recognition scheme (FMSFR), based on the EHA-FCM partitioning scheme and the basic ideas used in the development of the MSFR scheme, is proposed. Extensive experiments are conducted throughout this thesis using a number of challenging benchmark databases. These databases are selected from the FVC2002, FVC2004 and FVC2006 competitions containing a wide variety of challenges for fingerprint recognition. Simulation results demonstrate not only the effectiveness of the proposed techniques and schemes but also their superiority over some of the state-of-the-art techniques, in terms of the recognition accuracy and the computational complexity

A Review on the Cerebrovascular Segmentation Methods

© 2018 IEEE. This paper explores various methods that have been proposed for the segmentation of the cerebrovascular structure. All of the methods listed are a combination old, new, automatic and semiautomatic models that produce promising results. Each method will be explained along with its advantages and disadvantages. Each of the methods explained are further explored in this paper with variety algorithms produced by using certain models to target certain areas in the cerebrovascular structure. These algorithms were developed to segment cerebrovascular structures from scans obtained from various image modalities e.g., time of flight magnetic-resonance angiography (TOF-MRA), and computed tomography angiography (CTA)