Laser and optical based methods for detecting and characterising microorganisms

This work investigated novel optical methods of characterizing the activity of microorganisms. Two different systems are studied in detail in this work. The possibility of using line scan speckle systems and imaging systems to understand the microbial behaviour, growth and motility was investigated. Conventionally, the growth and viability of microorganisms are determined by swabbing, plating and incubation, typically at 37degreesC for at least 24 hours. The proposed system allows real-time quantification of morphology and population changes of the microorganisms. An important aspect of the line scan system is the dynamic biospeckle. Dynamic speckle can be obtained from the movement of particles suspended in liquids. The speckle patterns show fluctuations in space and time which may be correlated with the activity of the constituents in the suspension. Initially the speckle parameters were standardized to non-motile and inert specimens such as polystyrene microspheres and suspensions of Staphylococcus aureus. The same optical systems and parameters were later tested on motile, active and live organisms of Escherichia coli. The experimental results that are presented describe the time history of the dynamic speckle pattern. A number of algorithms were used to analyse the intensity data. A 2D-FFT algorithm was used to evaluate the space and time-varying autocorrelation. Analysis of the speckle data in the Fourier domain provided insight into the motility of the organisms in broth. The mathematical analysis also gave further insight into the culture broth evaporation and its particle sedimentation characteristics at 37degreesC. These features correlated with the periodic motions associated with the organism and may therefore provide a signature for the organism and a means of monitoring. These results aided the developemnt of imaging bacterial detection systems which were discussed in the second half of the work. The second experimental system focuses on quantifying the morphology and population dynamics of Euglena gracilis under ambient conditions through image processing. Unlike many other cell systems, Euglena cells change from round to long to round cell shape and these different cell shapes were analyzed over time. In the morphological studies of single Euglena cells, image processing tools and filtering techniques were used and different parameters identified and their efficiency at determining cell shape compared. The best parameter for processing the images and its effectiveness in detecting even the interior motions of constituents within a dead cell was found. The efficiency of the measurement parameters in following sequences of shape changes of the Euglena cell was compared with the visual assessment tests from 12 volunteers and other simple measurement methods including parameters relating to the cells eccentricity, and image processing in the space and frequency domains. One of the major advantages of this system is that living cells can be examined in their natural state without being killed, fixed, and stained. As a result, the dynamics of ongoing biological processes in live cells can be observed and recorded in high contrast and sharp clarity. The population statistics of Euglena gracilis was done in liquid culture. A custom built microscopy system was employed and the laser beam was coupled with a dark field illumination system to enhance the contrast of the images. Different image filters were employed for extracting useful information on the population statistics. Similarly as with the shape study of the Euglena cell, different parameters were identified and the best parameter was selected. The population study of the Euglena cells provided a detection system that indicated the activity of the population

Marterial characterization of asphalt binder using ultrasound testing

The Non-contact ultrasound (NCU) technology was used as an alternative to characterize the physical properties of asphalt binder. The objective of this research is to correlate the physical properties of asphalt binder with non-contact ultrasound measurements. The physical properties of asphalt binder are viscosity and penetration. In this study two types of\u27 AC 30 and AC40 asphalt binders are used. For each type of asphalt binder there are original and aged samples. The non-contact ultrasound measurements are integrated response (IR) and wave velocity (Vm). The IR is the attenuation value of the area underneath the signal wave measured in decibels and can be used to measure the amount of ultrasonic energy transmitted or reflected from a test material. The wave velocity is the velocity of the ultrasound when it passes through the material. The results show that IR can he correlated with physical properties: however wave velocity does not correlate well

A Ring with a Spin : Superfluidity in a toroidal Bose-Einstein condensate

Superfluidity is a remarkable phenomenon. Superfluidity was initially characterized by flow without friction, first seen in liquid helium in 1938, and has been studied extensively since. Superfluidity is believed to be related to, but not identical to Bose-Einstein condensation, a statistical mechanical phenomena predicted by Albert Einstein in 1924 based on the statistics of Satyendra Nath Bose, where bosonic atoms make a phase transition to form a Bose-Einstein condensate (BEC), a gas which has macroscopic occupation of a single quantum state. Developments in laser cooling of neutral atoms and the subsequent realization of Bose-Einstein condensates in ultracold gases have opened a new window into the study of superfluidity and its relation to Bose-Einstein condensation. In our atomic sodium BEC experiment, we studied superfluidity and dissipationless flow in an all-optical toroidal trap, constructed using the combination of a horizontal ``sheet''-like beam and vertical ``ring''-like beam, which, like a circuit loop, allows flow around the ring. On inducing a single quantum of circulation in the condensate, the smoothness and uniformity of the toroidal BEC enabled the sustaining of a persistent current lasting 40 seconds, limited by the lifetime of the BEC due to background gas pressure. This success set the stage for further experiments studying superfluidity. In a first set of experiments, we studied the stability of the persistent current by inserting a barrier in the flow path of the ring. The superflow stopped abruptly at a barrier strength such that the local flow velocity at the barrier exceeded a critical velocity, which supported decay via the creation of a vortex-antivortex pair. Our precise control in inducing and arresting superflow in the BEC is a first step toward studying other aspects of superfluidity, such as the effect of temperature and dimensionality. This thesis discusses these experiments and also details partial-transfer absorption imaging, an imaging technique developed in the course of this work

IDENTIFICATION OF CAUSE AND EFFECT IN CAUSAL SENTENCES OF GERIATRIC CARE DOMAIN USING CONDITIONAL RANDOM

poster abstractEvent extraction is a key step in many text mining applications. Identified events can be used in various applications such as question-answering systems, information extraction, summarization or building the knowledge base of a clinical decision support system. In this study we used PubMed abstracts of Geriatric care domain that were manually categorized into 42 different subdomains and further divided into causal and non-causal sentences by three domain experts. There are a total of 19,677 sentences in the collected abstracts from PubMed, out of which 2,856 sentences were selected and manually annotated with cause and effect events. We used conditional random fields (CRFs) that are statistical algorithms used to sequentially tag each word in a sentence as a cause or effect event based on some input variables or features. Features used in this study are words, words categories (lowercase, uppercase, mixed of letter and digits, etc.), affixes, part of speech and phrase chunks such as noun or verb phrase. For every word, a window of features before and after each word was also considered. We tested window of size, one to five meaning one to five features before and after each word was included as the input variables. The CRF algorithm was trained and tested on data set with 2,520 sentences in training set, 252 sentences in validation and 84 sentences in test set. Window of four features before and after each word had the best performance with 75.1% accuracy and F-measure of 85% with 84.6% precision and 87% recall

Hash Tables for Embedded and Real-time systems

Common collection objects such as hash tables are included in modern runtime libraries because of their widespread use and efficient implementation. While operating systems and programming languages continue to improve their real-time features, common implementations of hash tables and other collection objects are not necessarily suitable for real-time or embedded-systems. In this paper, we present an algorithm for managing hash tables that is suitable for such systems. The algorithm has been implemented and deployed in place of Java’s Hashtable class. We present evidence of the algorithm’s performance, experimental results documenting our algorithm’s suitability for real-time, and lessons learned from migrating this data structure to real-time and embedded platforms

Hashtables for Real-Time and Embedded Systems

Real-time are beginning to appear in advanced, high-level programming languages such as Java. When complemented by a real-time operating system, the Real-Time Specification for Java (RTSJ) offers strong execution constraints for applications developed in Java. While the RTSJ make the basic services of Java such as storage and thread management ready for many real-time applications, the collection objects, and the rest of the application run-time library, cannot be used by RTSJ applications until their run-time properties are examined and modified as necessary to make them suitable for use by real-time applications. In this work, we examine the Hashtable collection facility of Java and describe how to make it suitable for many real-time applications. Specifically, we reformulate its behavior to provide an execution-time bound on any Hashtable operation, and provide analysis establishing that bound. This analysis quantifies the trade-off between execution-time provisioning for Hashtable operations and the degree of confidence that a given bound will be violated. We present experiments that confirm our analysis and support our claim that Hashtables can be made suitable for many real-time applications

The Role of CIOs and Board’s IT Competence on HIT Investments

Healthcare organizations currently face tough decisions regarding allocating resources to reduce costs and improve patient care. While IT investments have consistently been a priority, it is widely accepted as a given, resulting in research primarily examining IT investment outcomes. Recent studies highlight tensions between the role of CIOs and governing boards in determining IT resource allocations. Recognizing this, the current study investigates the dynamics between healthcare CIO presence and the board in driving targeted HIT investments. Drawing on the upper echelons theory, we theorize and propose several hypotheses to clarify the tensions between the CIO and the influence of boards in the healthcare industry, specifically in the context of HIT investments

Structure based de novo design of IspD inhibitors as anti-tubercular agents

Tuberculosis is one of the leading contagious diseases, caused by Mycobacterium tuberculosis. Despite improvements in anti-tubercular agents, it remains one of the most prevalent infectious diseases worldwide, responsible for a total of 1.6 million deaths annually. The emergence of multidrug resistant strains highlighted the need of discovering novel drug targets for the development of anti-tubercular agents. 2-C-methyl-D-erythritol-4-phosphate cytidyltransferase (IspD) is an enzyme involved in MEP pathway for isoprenoid biosynthesis, which is considered an attractive target for the discovery of novel antibiotics for its essentiality in bacteria and absence in mammals. In the present study, we have employed structure based drug design approach to develop novel and potent inhibitors for IspD receptor. To explore binding affinity and hydrogen bond interaction between the ligand and active site of IspD receptor, docking studies were performed. ADMET and synthetic accessibility filters were used to screen designed molecules. Finally, ten compounds were selected and subsequently submitted for the synthesis and in vitro studies as IspD inhibitors

Identifying Patients' Smoking Status from Electronic Dental Records Data

Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessibility causing obstacles during the time of care and research utility. No studies exist on extracting patient's smoking status automatically from the Electronic Dental Record. This study reports the development and evaluation of an NLP system for this purpose

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records

Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it’s unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. We assessed information congruence by comparing patients’ self-reported dental histories to their original diagnosis assigned by their medical providers in the Electronic Medical Record (EMR). To enable this comparison, we encoded patients CVD information from the free-text data of EDRs into a structured format using natural language processing (NLP). Overall, our NLP approach achieved promising performance extracting patients’ CVD-related information. We observed disagreement between self-reported EDR data and physician-diagnosed EMR data