Comparative Evaluation of Apical Sealing Efficacy of Guttaflow Bioseal, Super-Bond Rc Sealer and Adseal Root Canal Sealer.

Objectives: The objectives of this study is to evaluate apical sealing ability of GuttaFlow Bioseal, Super-Bond RC Sealer, and Adseal root canal sealer. Material and Methods: 36 extracted human single rooted permanent teeth, divided into three groups (n = 12) and obturated by lateral condensation technique. Obturation and root canal sealing was done by either Group I: using GuttaFlow Bioseal, Group II: using Super-Bond RC Sealer and Group III: using Adseal sealer, system. Microleakage was assessed by means of dye penetration method. Results: The dye penetration in Group II was more than in Groups I and III in both vertical and horizontal directions, suggesting that GuttaFlow Bioseal and Adseal sealer are effective in reducing the apical leakage compared to Super-Bond RC Sealer. Conclusion: Bioceramic GuttaFlow Bioseal root canal sealers seal are better root canal sealer but they cannot totally eliminate apical leakage.

Multi-obstacle aware smart navigation system for visually impaired people in fog connected IoT-cloud environment.

Design of smart navigation for visually impaired/blind people is a hindering task. Existing researchers analyzed it in either indoor or outdoor environment and also it's failed to focus on optimum route selection, latency minimization and multi-obstacle presence. In order to overcome these challenges and to provide precise assistance to visually impaired people, this paper proposes smart navigation system for visually impaired people based on both image and sensor outputs of the smart wearable. The proposed approach involves the upcoming processes: (i) the input query of the visually impaired people (users) is improved by the query processor in order to achieve accurate assistance. (ii) The safest route from source to destination is provided by implementing Environment aware Bald Eagle Search Optimization algorithm in which multiple routes are identified and classified into three different classes from which the safest route is suggested to the users. (iii) The concept of fog computing is leveraged and the optimal fog node is selected in order to minimize the latency. The fog node selection is executed by using Nearest Grey Absolute Decision Making Algorithm based on multiple parameters. (iv) The retrieval of relevant information is performed by means of computing Euclidean distance between the reference and database information. (v) The multi-obstacle detection is carried out by YOLOv3 Tiny in which both the static and dynamic obstacles are classified into small, medium and large obstacles. (vi) The decision upon navigation is provided by implementing Adaptive Asynchronous Advantage Actor-Critic (A3C) algorithm based on fusion of both image and sensor outputs. (vii) Management of heterogeneous is carried out by predicting and pruning the fault data in the sensor output by minimum distance based extended kalman filter for better accuracy and clustering the similar information by implementing Spatial-Temporal Optics Clustering Algorithm to reduce complexity. The proposed model is implemented in NS 3.26 and the results proved that it outperforms other existing works in terms of obstacle detection and task completion time.

Pharmaceutical research in the Kingdom of Saudi Arabia: A scientometric analysis during 2001-2010.

Studies on the performance of Saudi Arabia in the pharmaceutical science research using quantitative and qualitative measures. They analyze the productivity and global publication share and rank of the top 15 countries. The author studies Saudi Arabia's publications output, growth and citation quality, international collaborative publication share and most important the collaborating partners, contribution and citation impact of its top 15 organizations and authors, productivity patterns of its top publishing journals and characteristics of its highly cited papers.

Knowledge about the availability of the pharmacist in the Nuclear Medicine Department: A questionnaire-based study among health-care professionals.

OBJECTIVE: The objective of this study was to analyze the knowledge about the availability of the pharmacist in the nuclear medicine department among health-care professionals through a prospective cohort study. METHODS: A total of 741 health-care professionals participated in the study by answering 10 simple questions about the role of the pharmacist in the nuclear medicine department and the availability of pharmacist in the nuclear medicine department. An online questionnaire system was used to conduct the study, and participants were invited to participate through personal communications and by promoting the study through social websites including Facebook, LinkedIn and Google (including Gmail and Google+). The study was conducted between April 2013 and March 2014 using the http://www.freeonlinesurveys.com/Webserver. Finally, the data provided by 621 participants was analyzed. Group frequency analysis was performed using Statistical Package for the Social Sciences (SPSS) version 16 (SPSS Inc. USA). RESULTS: The participants were from Malaysia, India, Pakistan, Sri Lanka, Bangladesh, UAE and Nepal. In total, 312 (50.2%) female health-care professionals and 309 (49.8%) male health-care professionals participated in the study. Of the 621 participants, 390 were working in hospitals, and 231 were not working in hospitals. Of the participants who were working in hospitals, 57.6% were pharmacists. The proportion of study participants who were aware of nuclear pharmacists was 55.39%. Awareness about the role of the pharmacist in nuclear medicine was poor. CONCLUSION: The role of the pharmacist in a nuclear medicine unit needs to be highlighted and promoted among health-care professionals and hence that the nuclear medicine team can provide better pharmaceutical care.

Automatic medical X-ray image classification using annotation.

The demand for automatically classification of medical X-ray images is rising faster than ever. In this paper, an approach is presented to gain high accuracy rate for those classes of medical database with high ratio of intraclass variability and interclass similarities. The classification framework was constructed via annotation using the following three techniques: annotation by binary classification, annotation by probabilistic latent semantic analysis, and annotation using top similar images. Next, final annotation was constructed by applying ranking similarity on annotated keywords made by each technique. The final annotation keywords were then divided into three levels according to the body region, specific bone structure in body region as well as imaging direction. Different weights were given to each level of the keywords; they are then used to calculate the weightage for each category of medical images based on their ground truth annotation. The weightage computed from the generated annotation of query image was compared with the weightage of each category of medical images, and then the query image would be assigned to the category with closest weightage to the query image. The average accuracy rate reported is 87.5 %.

Simultaneous determination of moxifloxacin and cefixime by first and ratio first derivative ultraviolet spectrophotometry.

BACKGROUND: The new combination of moxifloxacin HCl and cefixime trihydrate is approved for the treatment of lower respiratory tract infections in adults. At initial formulation development and screening stage a fast and reliable method for the dissolution and release testing of moxifloxacin and cefixime were highly desirable. The zero order overlaid UV spectra of moxifloxacin and cefixime showed >90% overlapping. Hence, simple, accurate precise and validated two derivative spectrophotometric methods have been developed for the determination of moxifloxacin and cefixime. METHODS: In the first derivative spectrophotometric method varying concentration of moxifloxacin and cefixime were prepared and scanned in the range of 200 to 400 nm and first derivative spectra were calculated (n = 1). The zero crossing wavelengths 287 nm and 317.9 nm were selected for determination of moxifloxacin and cefixime, respectively. In the second method the first derivative of ratio spectra was calculated and used for the determination of moxifloxacin and cefixime by measuring the peak intensity at 359.3 nm and 269.6 nm respectively. RESULTS: Calibration graphs were established in the range of 1-16 µg /mL and 1-15 µg /mL for both the drugs by first and ratio first derivative spectroscopic methods respectively with good correlation coefficients. Average accuracy of assay of moxifloxacin and cefixime were found to be 100.68% and 98 93%, respectively. Relative standard deviations of both inter and intraday assays were less than 1.8%. Moreover, recovery of moxifloxacin and cefixime was more than 98.7% and 99.1%, respectively. CONCLUSIONS: The described derivative spectrophotometric methods are simple, rapid, accurate, precise and excellent alternative to sophisticated chromatographic techniques. Hence, the proposed methods can be used for the quality control of the cited drugs and can be extended for routine analysis of the drugs in formulations.

A perspective for clinical pharmacy curriculum development and validation in asian developing nations.

This perspective is a reflection of the Personal teaching experience of the authors. The aim of this perspective is to identify the weaknesses in the pharmacy curriculum development in Asian developing nations and to propose a methodological approach for curriculum validation. It has been seen that improper selection of the course contents were the common limitations found in the pharmacy curriculum in developing nations. Furthermore, lack of facilities and improper student evaluation system were the other flaws that are acting as a main challenge to pharmacy education in developing nations. A systemic way for the curriculum designing and validation can be a solution to manage the observed deficiencies. Keeping in view this motivation a set of task are defined in the form of Pharmacy Curriculum Development and Validation Model (PCDVM) that can be a guideline for the pharmacy educators for the evaluation and validation of the curriculum. Partial or full implementation of this model will enable the pharmacy institutions to deliver quality knowledge to pharmacy students which will further contribute to quality health care system in developing countries.

An automated blood vessel segmentation algorithm using histogram equalization and automatic threshold selection.

This paper focuses on the detection of retinal blood vessels which play a vital role in reducing the proliferative diabetic retinopathy and for preventing the loss of visual capability. The proposed algorithm which takes advantage of the powerful preprocessing techniques such as the contrast enhancement and thresholding offers an automated segmentation procedure for retinal blood vessels. To evaluate the performance of the new algorithm, experiments are conducted on 40 images collected from DRIVE database. The results show that the proposed algorithm performs better than the other known algorithms in terms of accuracy. Furthermore, the proposed algorithm being simple and easy to implement, is best suited for fast processing applications.