Designing a training tool for imaging mental models

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network

A comparative Quantitative study on Momordin in the fruit and leave extracts of two different cultivars of Momordicacharantia Linn

Momordica charantia, is widely used as a medicinal plant. Studies have revealed that they contain an array of biologically active proteins like momordin which act as anti-tumor, anti-diabetic, and anti-rheumatic. Since momordin is an active compound, we have made a thorough study on the presence of momordin in the leave and fruit extracts of white and green varieties of the plant. Momordin eluted at 3.84-3.85 min under the standardized HPLC condition. It was found that the momordin was present only in the methanolic extracts of fruit and leave samples and not in the water extracts. The leave samples were found to be contained more quantity of momordin (2878.57 µg/mL) when compared with the fruit extract (72.72 µg/mL). It was also observed that green variety of bitter gourd contained more momordin than white varieties

FLAGCAL:A flagging and calibration package for radio interferometric data

We describe a flagging and calibration pipeline intended for making quick look images from GMRT data. The package identifies and flags corrupted visibilities, computes calibration solutions and interpolates these onto the target source. These flagged calibrated visibilities can be directly imaged using any standard imaging package. The pipeline is written in "C" with the most compute intensive algorithms being parallelized using OpenMP.Comment: 15 Pages, 6 figures, 2 Tables, Accepted for publication in the Experimental Astronomy Journa

The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a cloud system, we still lack insights into how professional software engineers actually use clouds, and how the cloud impacts development practices. This paper reports on the first systematic study on how software developers build applications in the cloud. We conducted a mixed-method study, consisting of qualitative interviews of 25 professional developers and a quantitative survey with 294 responses. Our results show that adopting the cloud has a profound impact throughout the software development process, as well as on how developers utilize tools and data in their daily work. Among other things, we found that (1) developers need better means to anticipate runtime problems and rigorously define metrics for improved fault localization and (2) the cloud offers an abundance of operational data, however, developers still often rely on their experience and intuition rather than utilizing metrics. From our findings, we extracted a set of guidelines for cloud development and identified challenges for researchers and tool vendors

High pressure X-ray preionized TEMA-CO2 laser

The construction of a high-pressure (up to 20 atm) transversely excited CO2 laser using transverse X-ray preionization is described. High pressure operation was found to be greatly improved in comparison to UV-preionized systems. Homogeneous discharges have been achieved in the pressure range 5–20 atm, yielding a specific laser output in the order of 35 J/l

Managing risk in the face of adversity: design and outcomes of rapid glaucoma assessment clinics during a pandemic recovery

Background: The provision of timely care to the high volume of glaucoma patients stratified as “low risk” following pandemic-related appointment deferrals continues to prove challenging for glaucoma specialists. It is unknown whether stratification as “low risk” remains valid over time, raising the potential risk of harm during this period if left unmonitored. This study aimed to evaluate whether Rapid Glaucoma Assessment Clinics (RGACs) are an effective method of assessing “low-risk” patients in order to identify those who may need an escalation of care, therefore reducing the risk of the future incidents of preventable vision loss. / Methods: RGACs were developed which comprised a brief advance telephone history by a clinician and then ophthalmic technician-measured visual acuity and intraocular pressure in clinic. We report outcomes from the first month of operation describing attendance patterns, the proportion of patients from this “low risk” cohort requiring escalation and underlying reasons for treatment escalations. / Results: 639 patients were invited to attend RGACs. 75% attended their booked appointment. Pre-attendance telephone consultations were associated with lower non-attendance rates (13.9% vs 29.3%, p < 0.00001). 15% of patients were no longer deemed to remain at “low risk” with further expedited clinical review scheduled. 10.4% of patients required an escalation in treatment following review. / Conclusions: RGACs are an effective approach to deliver high throughput clinical assessments for large numbers of “low-risk” glaucoma patients with deferred appointments. They enable the rapid identification and treatment of patients who would otherwise face significantly delayed review reducing the risk of future preventable vision loss

CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation of Lungs from CT Scans

Accurate and fast extraction of lung volumes from computed tomography (CT) scans remains in a great demand in the clinical environment because the available methods fail to provide a generic solution due to wide anatomical variations of lungs and existence of pathologies. Manual annotation, current gold standard, is time consuming and often subject to human bias. On the other hand, current state-of-the-art fully automated lung segmentation methods fail to make their way into the clinical practice due to their inability to efficiently incorporate human input for handling misclassifications and praxis. This paper presents a lung annotation tool for CT images that is interactive, efficient, and robust. The proposed annotation tool produces an "as accurate as possible" initial annotation based on the fuzzy-connectedness image segmentation, followed by efficient manual fixation of the initial extraction if deemed necessary by the practitioner. To provide maximum flexibility to the users, our annotation tool is supported in three major operating systems (Windows, Linux, and the Mac OS X). The quantitative results comparing our free software with commercially available lung segmentation tools show higher degree of consistency and precision of our software with a considerable potential to enhance the performance of routine clinical tasks.Comment: 4 pages, 6 figures; to appear in the proceedings of 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014