The molecular genetics of polycystic ovary syndrome.

Imperial Users onl

Visual-Inertial Sensor Fusion Models and Algorithms for Context-Aware Indoor Navigation

Positioning in navigation systems is predominantly performed by Global Navigation Satellite Systems (GNSSs). However, while GNSS-enabled devices have become commonplace for outdoor navigation, their use for indoor navigation is hindered due to GNSS signal degradation or blockage. For this, development of alternative positioning approaches and techniques for navigation systems is an ongoing research topic. In this dissertation, I present a new approach and address three major navigational problems: indoor positioning, obstacle detection, and keyframe detection. The proposed approach utilizes inertial and visual sensors available on smartphones and are focused on developing: a framework for monocular visual internal odometry (VIO) to position human/object using sensor fusion and deep learning in tandem; an unsupervised algorithm to detect obstacles using sequence of visual data; and a supervised context-aware keyframe detection. The underlying technique for monocular VIO is a recurrent convolutional neural network for computing six-degree-of-freedom (6DoF) in an end-to-end fashion and an extended Kalman filter module for fine-tuning the scale parameter based on inertial observations and managing errors. I compare the results of my featureless technique with the results of conventional feature-based VIO techniques and manually-scaled results. The comparison results show that while the framework is more effective compared to featureless method and that the accuracy is improved, the accuracy of feature-based method still outperforms the proposed approach. The approach for obstacle detection is based on processing two consecutive images to detect obstacles. Conducting experiments and comparing the results of my approach with the results of two other widely used algorithms show that my algorithm performs better; 82% precision compared with 69%. In order to determine the decent frame-rate extraction from video stream, I analyzed movement patterns of camera and inferred the context of the user to generate a model associating movement anomaly with proper frames-rate extraction. The output of this model was utilized for determining the rate of keyframe extraction in visual odometry (VO). I defined and computed the effective frames for VO and experimented with and used this approach for context-aware keyframe detection. The results show that the number of frames, using inertial data to infer the decent frames, is decreased

High prevalence of extended-spectrum β-lactamase (blaCTX-M-15) and New Delhi metallo-β-lactamase-1 (NDM-1) genes among high-level carbapenem resistance Klebsiella pneumonia: an alarm for our health system

Background: The extended-spectrum β-lactamase (ESBL) carbapenems-resistant Klebsiella isolates are considered one of the most significant challenging in the treatment of patients in hospitals. The aim of this study was to determine the prevalence of important carbapenem resistance genes ESBL subtypes and between K. pneumoniae from patients at hospital in Tehran, Iran.Methods: Fifty-four isolates of K. pneumoniae were isolated from Shariatee Hospital in Tehran from February 2013 to July 2016. Antibiotic testing was done by using the standard disk diffusion method and E-test MIC. The confirmation of carbapenemase activity was performed using an MHT and a new method called the carbapenem inactivation method test (CIM). Finally, a polymerase chain reaction (PCR) and sequencing of related genes was performed.Results: Our PCR data demonstrate that blaCTX-M group’s 40 (81.4%) genes were the most prevalent in our hospital followed by group genes blaCTX-M-3 (18.51%) and blaCTX-M-2 (20.38%). The distribution of the CTX-M group revealed that blaCTX-M-15 23 (42.6%) was the dominant subtype. The coexistence of multiple genes included blaTEM, CTX-M and blaSHV, and CTX-M The presence of blaNDM1, blaOXA-48, and blaKPC were identified in the carbapenem-resistant isolates, 22 (40.7%), 10 (18.5%), and 7 (12.9%) respectively.Conclusion: Our research showed that a CIM test for the first time in Iran is possible and has a high facility for the fast identification of carbapenem-resistant Klebsiella (CRK). We are encountered with the emergence of CTX-M, OXA-48, KPC, and NDM1 harboring CRK strains in our hospitals. Therefore, the treatment of patients infected with these isolates will be an important future concern in our clinical settings.Running Head: Resistance genes among carbapenem-resistant Klebsiella pneumoniaKeywords: New Delhi metallo-beta-lactamase-1, Klebsiella pneumoniae, Carbapenem, Extended-spectrum ß-lactamas

An Artificial Neural Network for Movement Pattern Analysis to Estimate Blood Alcohol Content Level

Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of “just-in-time” injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC) level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN), we performed regression analysis to define a model determining association between gait features and BACs. Part (70%) of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN) was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption

A Comparative Study of the Curriculum of Undergraduate Nursing Education in Iran and Selected Renowned Universities in the World

Background & Objective: In order to achieve more success in the Bachelor of Science in the discipline of nursing education in Iran and identify its weaknesses and strengths, comparative studies and utilization of successful universities’ strategies and experiences are necessary. The present research compares the curricula of undergraduate nursing education in Iran and 8 selected universities from America, Europe, Australia, and Asia. The universities were compared in terms of student selection methods, mission and objective, general structure, program length, educational content, teaching and learning methods, educational strategies, role of graduates, and evaluation methodologies. Methods: This was a descriptive-comparative study. In the present study, 8 renowned and innovative nursing schools were selected through purposeful sampling method. The important components and indices of nursing curricula of the 8 nursing schools in America, Europe, Australia, and Asia were analyzed. Then, each studied item was compared between the selected nursing schools and nursing schools of Iran. Practical suggestions were made to improve the quality of the nursing curriculum in Iran in terms of improvement of each studied item. The research model used in this study was the Beredy model that identified the 4 stages of description, interpretation, proximity, and comparison in comparative studies. Results: The general objectives and educational contents in all curricula of the examined nursing schools were to some extent similar. However, the establishment and development of the contents and the method, extent, and type of addressing them were different. These differences created different contents. Moreover, despite the many similarities in training and evaluation techniques, many differences depending on the level and purpose of the program were observed. Conclusion: It seems that although the nursing curriculum in Iran does not hold a dissatisfactory position in comparison with the other studied curricula, in order to resolve the flaws, items like goals selection, student selection methods, research, teaching and evaluation (theory and performance) methodologies need to be reviewed and revised. Key Words: Comparative study, Curriculum component, Nursing Bachelor of Science, Beredy mod

Association between CYP19 gene SNP rs2414096 Polymorphism and polycystic ovary syndrome in Chinese women

<p>Abstract</p> <p>Background</p> <p>Several studies have reported the association of the SNP rs2414096 in the CYP19 gene with hyperandrogenism, which is one of the clinical manifestations of polycystic ovary syndrome (PCOS). These studies suggest that SNP rs2414096 may be involved in the etiopathogenisis of PCOS. To investigate whetherthe CYP19 gene SNP rs2414096 polymorphism is associated with the susceptibility to PCOS, we designed a case-controlled association study including 684 individuals.</p> <p>Methods</p> <p>A case-controlled association study including 684 individuals (386 PCOS patients and 298 controls) was performed to assess the association of SNP rs2414096 with PCOS. Genotyping of SNP rs2414096 was conducted by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method that was performed on genomic DNA isolated from blood leucocytes. Results were analyzed in respect to clinical test results.</p> <p>Results</p> <p>The genotypic distributions of rs2414096 (GG, AG, AA) in the CYP19 gene (GG, AG, AA) in women with PCOS (0.363, 0.474, 0.163, respectively) were significantly different from that in controls (0.242, 0.500, 0.258, respectively) (<it>P </it>= 0.001). E2/T was different between the AA and GG genotypes. Age at menarche (AAM) and FSH were also significantly different among the GG, AG, and AA genotypes in women with PCOS (P = 0.0391 and 0.0118, respectively). No differences were observed in body mass index (BMI) and other serum hormone concentrations among the three genotypes, either in the PCOS patients or controls.</p> <p>Conclusions</p> <p>Our data suggest that SNP rs2414096 in the CYP19 gene is associated with susceptibility to PCOS.</p