The identification and characterization of novel antibacterial compounds via target-based and whole cell screening approaches

The emergence of multidrug-resistant bacterial infections in both the clinical setting and the community has created an environment in which the development of novel antibacterial compounds is necessary to keep dangerous infections at bay. While the derivatization of existing antibiotics by pharmaceutical companies has so far been successful at achieving this end, this strategy is short-term, and the discovery of antibacterials with novel scaffolds would be a greater contribution to the fight of multidrug-resistant infections. Described herein is the application of both target-based and whole cell screening strategies to identify novel antibacterial compounds. In a target-based approach, we sought small-molecule disruptors of the MazEF toxin-antitoxin protein complex. A lack of facile, continuous assays for this target required the development of a fluorometric assay for MazF ribonuclease activity. This assay was employed to further characterize the activity of the MazF enzyme and was used in a screening effort to identify disruptors of the MazEF complex. In addition, by employing a whole cell screening approach, we identified two compounds with potent antibacterial activity. Efforts to characterize the in vitro antibacterial activities displayed by these compounds and to identify their modes of action are described.

A path-based framework for analyzing large markov models

Reliability and dependability modeling can be employed during many stages of analysis of a computing system to gain insights into its critical behaviors. To provide useful results, realistic models of systems are often necessarily large and complex. Numerical analysis of these models presents a formidable challenge because the sizes of their state-space descriptions grow exponentially in proportion to the sizes of the models. On the other hand, simulation of the models requires analysis of many trajectories in order to compute statistically correct solutions. This dissertation presents a novel framework for performing both numerical analysis and simulation. The new numerical approach computes bounds on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. This relationship makes it possible for the approach to explore multiple paths at the same time,· thus significantly increasing the number of paths that can be explored in a given amount of time. Furthermore, the use of a structured representation for the state space and the direct computation of the desired reward measure (without ever storing the solution vector) allow it to analyze very large models using a very small amount of storage. Often, path-based techniques must compute many paths to obtain tight bounds. In addition to presenting the basic path-based approach, we also present algorithms for computing more paths and tighter bounds quickly. One resulting approach is based on the concept of path composition whereby precomputed subpaths are composed to compute the whole paths efficiently. Another approach is based on selecting important paths (among a set of many paths) for evaluation. Many path-based techniques suffer from having to evaluate many (unimportant) paths. Evaluating the important ones helps to compute tight bounds efficiently and quickly.

A Component Based Heuristic Search Method with AdaptivePerturbations for Hospital Personnel Scheduling

Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with adaptive perturbations, for a nurse scheduling problem arising at a major UK hospital. The main idea behind this technique is to decompose a schedule into its components (i.e. the allocated shift pattern of each nurse), and then mimic a natural evolutionary process on these components to iteratively deliver better schedules. The worthiness of all components in the schedule has to be continuously demonstrated in order for them to remain there. This demonstration employs a dynamic evaluation function which evaluates how well each component contributes towards the final objective. Two perturbation steps are then applied: the first perturbation eliminates a number of components that are deemed not worthy to stay in the current schedule; the second perturbation may also throw out, with a low level of probability, some worthy components. The eliminated components are replenished with new ones using a set of constructive heuristics using local optimality criteria. Computational results using 52 data instances demonstrate the applicability of the proposed approach in solving real-world problems.

A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.

High Precision Plasma Etch for Pattern Transfer: Towards Fluorocarbon Based Atomic Layer Etching

A basic requirement of a plasma etching process is fidelity of the patterned organic materials. In photolithography, a He plasma pretreatment (PPT) based on high ultraviolet and vacuum ultraviolet (UV/VUV) exposure was shown to be successful for roughness reduction of 193nm photoresist (PR). Typical multilayer masks consist of many other organic masking materials in addition to 193nm PR. These materials vary significantly in UV/VUV sensitivity and show, therefore, a different response to the He PPT. A delamination of the nanometer-thin, ion-induced dense amorphous carbon (DAC) layer was observed. Extensive He PPT exposure produces volatile species through UV/VUV induced scissioning. These species are trapped underneath the DAC layer in a subsequent plasma etch (PE), causing a loss of adhesion. Next to stabilizing organic materials, the major goals of this work included to establish and evaluate a cyclic fluorocarbon (FC) based approach for atomic layer etching (ALE) of SiO2 and Si; to characterize the mechanisms involved; and to evaluate the impact of processing parameters. Periodic, short precursor injections allow precise deposition of thin FC films. These films limit the amount of available chemical etchant during subsequent low energy, plasma-based Ar+ ion bombardment, resulting in strongly time-dependent etch rates. In situ ellipsometry showcased the self-limited etching. X-ray photoelectron spectroscopy (XPS) confirms FC film deposition and mixing with the substrate. The cyclic ALE approach is also able to precisely etch Si substrates. A reduced time-dependent etching is seen for Si, likely based on a lower physical sputtering energy threshold. A fluorinated, oxidized surface layer is present during ALE of Si and greatly influences the etch behavior. A reaction of the precursor with the fluorinated substrate upon precursor injection was observed and characterized. The cyclic ALE approach is transferred to a manufacturing scale reactor at IBM Research. Ensuring the transferability to industrial device patterning is crucial for the application of ALE. In addition to device patterning, the cyclic ALE process is employed for oxide removal from Si and SiGe surfaces with the goal of minimal substrate damage and surface residues. The ALE process developed for SiO2 and Si etching did not remove native oxide at the level required. Optimizing the process enabled strong O removal from the surface. Subsequent 90% H2/Ar plasma allow for removal of C and F residues.

RISK-BASED MULTIOBJECTIVE PATH PLANNING AND DESIGN OPTIMIZATION FOR UNMANNED AERIAL VEHICLES

Safe operation of unmanned aerial vehicles (UAVs) over populated areas requires reducing the risk posed by a UAV if it crashed during its operation. We considered several types of UAV risk-based path planning problems and developed techniques for estimating the risk to third parties on the ground. The path planning problem requires making trade-offs between risk and flight time. Four optimization approaches for solving the problem were tested; a network-based approach that used a greedy algorithm to improve the original solution generated the best solutions with the least computational effort. Additionally, an approach for solving a combined design and path planning problems was developed and tested. This approach was extended to solve robust risk-based path planning problem in which uncertainty about wind conditions would affect the risk posed by a UAV.

Modelling and simulating retail management practices: a first approach

Multi-agent systems offer a new and exciting way of understanding the world of work. We apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between people management practices on the shop-floor and retail performance. Despite the fact we are working within a relatively novel and complex domain, it is clear that using an agent-based approach offers great potential for improving organizational capabilities in the future. Our multi-disciplinary research team has worked closely with one of the UK’s top ten retailers to collect data and build an understanding of shop-floor operations and the key actors in a department (customers, staff, and managers). Based on this case study we have built and tested our first version of a retail branch agent-based simulation model where we have focused on how we can simulate the effects of people management practices on customer satisfaction and sales. In our experiments we have looked at employee development and cashier empowerment as two examples of shop floor management practices. In this paper we describe the underlying conceptual ideas and the features of our simulation model. We present a selection of experiments we have conducted in order to validate our simulation model and to show its potential for answering “what-if” questions in a retail context. We also introduce a novel performance measure which we have created to quantify customers’ satisfaction with service, based on their individual shopping experiences.

CERVIXCHECK: A SPIRITUALLY-BASED SMS TEXT MESSAGING PILOT INTERVENTION TO INCREASE CERVICAL CANCER AWARENESS AND PAP TEST SCREENING INTENTION AMONG AFRICAN AMERICAN WOMEN

African American women account for a disproportionate burden of cervical cancer incidence and mortality rate when compared to non-Hispanic White women. Cervical cancer is one of the most preventable types of cancer, and women can be screened for it with a routine Pap test. Given that religion occupies an essential place in African American lives, framing health messages with important spiritual themes and delivering them through a popular communication delivery channel may allow for a more culturally-relevant and accessible technology-based approach to promoting cervical cancer educational content to African American women. Using community-engaged research as a framework, the purpose of this multiple methods study was to develop, pilot test, and evaluate the feasibility, acceptability, and initial efficacy of a spiritually-based SMS text messaging intervention to increase cervical cancer awareness and Pap test screening intention among African American women. The study recruited church-attending African American women ages 21-65 and was conducted in three phases. Phases 1 and 2 consisted of a series of focus group discussions (n=15), cognitive response interviews (n=8), and initial usability testing that were conducted to inform the intervention development and modifications. Phase 3 utilized a non-experimental one-group pretest-posttest design to pilot test the 16-day text messaging intervention (n=52). Of the individuals enrolled, forty-six completed the posttest (retention rate=88%). Findings provided evidence for the early feasibility, high acceptability, and some initial efficacy of the CervixCheck intervention. There were significant pre-post increases observed for knowledge about cervical cancer and the Pap test (p = .001) and subjective norms (p = .006). Additionally, results post-intervention revealed that 83% of participants reported being either “satisfied” or “very satisfied” with the program and 85% found the text messages either “useful” or “very useful”. 85% of the participants also indicated that they would “likely” or “very likely” share the information they learned from the intervention with the women around them, with 39% indicating that they had already shared some of the information they received with others they knew. A spiritually-based SMS text messaging intervention could be a culturally appropriate and cost-effective method of promoting cervical cancer early detection information to African American women.

A BACKING DEVICE BASED ON AN EMBEDDED STIFFENER AND RETRACTABLE INSERTION TOOL FOR THIN-FILM COCHLEAR ARRAYS

Intracochlear trauma from surgical insertion of bulky electrode arrays and inadequate pitch perception are areas of concern with current hand-assembled commercial cochlear implants. Parylene thin-film arrays with higher electrode densities and lower profiles are a potential solution, but lack rigidity and hence depend on manually fabricated permanently attached polyethylene terephthalate (PET) tubing based bulky backing devices. As a solution, we investigated a new backing device with two sub-systems. The first sub-system is a thin poly(lactic acid) (PLA) stiffener that will be embedded in the parylene array. The second sub-system is an attaching and detaching mechanism, utilizing a poly(N-vinylpyrrolidone)-block-poly(d,l-lactide) (PVP-b-PDLLA) copolymer-based biodegradable and water soluble adhesive, that will help to retract the PET insertion tool after implantation. As a proof-of-concept of sub-system one, a microfabrication process for patterning PLA stiffeners embedded in parylene has been developed. Conventional hotembossing, mechanical micromachining, and standard cleanroom processes were integrated for patterning fully released and discrete stiffeners coated with parylene. The released embedded stiffeners were thermoformed to demonstrate that imparting perimodiolar shapes to stiffener-embedded arrays will be possible. The developed process when integrated with the array fabrication process will allow fabrication of stiffener-embedded arrays in a single process. As a proof-of-concept of sub-system two, the feasibility of the attaching and detaching mechanism was demonstrated by adhering 1x and 1.5x scale PET tube-based insertion tools and PLA stiffeners embedded in parylene using the copolymer adhesive. The attached devices survived qualitative adhesion tests, thermoforming, and flexing. The viability of the detaching mechanism was tested by aging the assemblies in-vitro in phosphate buffer solution. The average detachment times, 2.6 minutes and 10 minutes for 1x and 1.5x scale devices respectively, were found to be clinically relevant with respect to the reported array insertion times during surgical implantation. Eventually, the stiffener-embedded arrays would not need to be permanently attached to current insertion tools which are left behind after implantation and congest the cochlear scala tympani chamber. Finally, a simulation-based approach for accelerated failure analysis of PLA stiffeners and characterization of PVP-b-PDLLA copolymer adhesive has been explored. The residual functional life of embedded PLA stiffeners exposed to body-fluid and thereby subjected to degradation and erosion has been estimated by simulating PLA stiffeners with different parylene coating failure types and different PLA types for a given parylene coating failure type. For characterizing the PVP-b-PDLLA copolymer adhesive, several formulations of the copolymer adhesive were simulated and compared based on the insertion tool detachment times that were predicted from the dissolution, degradation, and erosion behavior of the simulated adhesive formulations. Results indicate that the simulation-based approaches could be used to reduce the total number of time consuming and expensive in-vitro tests that must be conducted.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2016)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2013)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

Iowa Nutrient Reduction Strategy : a science and technology-based framework to assess and reduce nutrients to Iowa waters and the Gulf of Mexico (2012)

On November 19, 2012, Iowa Gov. Terry Branstad, Iowa Secretary of Agriculture Bill Northey, Director Chuck Gipp from the Iowa Department of Natural Resources and Dr. John Lawrence of Iowa State University announced the release of the Iowa Nutrient Reduction Strategy for public comment. A two-month public comment period and several informational meetings allowed the public to provide feedback on the draft strategy. Updates and improvements were made to the draft based on the public comments. The final version of the strategy was released May 29, 2013. The Iowa Nutrient Reduction Strategy is a science and technology-based approach to assess and reduce nutrients delivered to Iowa waterways and the Gulf of Mexico. The strategy outlines voluntary efforts to reduce nutrients in surface water from both point sources, such as wastewater treatment plants and industrial facilities, and nonpoint sources, including farm fields and urban areas, in a scientific, reasonable and cost effective manner. The development of the strategy reflects more than two years of work led by the Iowa Department of Agriculture and Land Stewardship, Iowa Department of Natural Resources and Iowa State University. The scientific assessment to evaluate and model the effects of practices was developed through the efforts of 23 individuals representing five agencies or organizations, including scientists from ISU, IDALS, DNR, USDA Agricultural Research Service and USDA Natural Resources Conservation Service. The strategy was developed in response to the 2008 Gulf Hypoxia Action Plan that calls for the 12 states along the Mississippi River to develop strategies to reduce nutrient loading to the Gulf of Mexico. The Iowa strategy follows the recommended framework provided by EPA in 2011 and is only the second state to complete a statewide nutrient reduction strategy. This strategy is the beginning. Operational plans are being developed and work is underway. This is a dynamic document that will evolve over time, and is a key step towards improving Iowa’s water quality. The impetus for this report comes from the Water Resources Coordination Council (WRCC) which states in its 2014‐15 Annual Report “Efforts are underway to improve understanding of the multiple nutrient monitoring efforts that may be available and can be compared to the nutrient WQ monitoring framework to identify opportunities and potential data gaps to better coordinate and prioritize future nutrient monitoring efforts.” This report is the culmination of those efforts.

A case-based reasoning view of thrombophilia risk

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information.

A Case-base Approach to Workforces’ Satisfaction Assessment

It is well known that human resources play a valuable role in a sustainable organizational development. Indeed, this work will focus on the development of a decision support system to assess workers’ satisfaction based on factors related to human resources management practices. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.