Therapeutic potential of statins and the induction of heme oxygenase-1 in preeclampsia

Heme oxygenase (Hmox) is an endogenous system that offers protection against placental cytotoxic damage associated with preeclampsia. The Hmox1/carbon monoxide (CO) pathway inhibits soluble Flt-1 (sFlt-1) and soluble Endoglin (sEng). More importantly, statins induce Hmox1 and suppress the release of sFlt-1 and sEng; thus, statins and Hmox1 activators are potential novel therapeutic agents for treating preeclampsia. The contribution of the Hmox system to the pathogenesis of preeclampsia has been further indicated by the incidence of preeclampsia being reduced by a third in smokers, who had reduced levels of circulating sFlt-1. Interestingly, preeclamptic women exhale less CO compared with women with healthy pregnancies. Hmox1 is reduced prior to the increase in sFlt-1 as Hmox1 mRNA expression in the trophoblast is decreased in the first trimester in women who go on to develop preeclampsia. Induction of Hmox1 or exposure to CO or bilirubin has been shown to inhibit the release of sFlt-1 and sEng in animal models of preeclampsia. The functional benefit of statins and Hmox1 induction in women with preeclampsia is valid not only because they inhibit sFlt-1 release, but also because statins and Hmox1 are associated with anti-apoptotic, anti-inflammatory, and anti-oxidant properties. The StAmP trial is the first randomized control trial (RCT) evaluating the use of pravastatin to ameliorate severe preeclampsia. This proof-of-concept study will pave the way for future global RCT, the success of which will greatly contribute to achieving the United Nations Millennium Development Goals (MDG4 and MDG5) and offering an affordable and easily accessible therapy for preeclampsia. © 2014 The Authors.

Zolotarev's proof of Gauss reciprocity and Jacobi symbols

2000 Mathematics Subject Classification: Primary 11A15.

A Conceptual Foresight Model to Investigate the Adoption of Radio Frequency Identification Technology in the English National Health Service

Radio Frequency Identification Technology (RFID) adoption in healthcare settings has the potential to reduce errors, improve patient safety, streamline operational processes and enable the sharing of information throughout supply chains. RFID adoption in the English NHS is limited to isolated pilot studies. Firstly, this study investigates the drivers and inhibitors to RFID adoption in the English NHS from the perspective of the GS1 Healthcare User Group (HUG) tasked with coordinating adoption across private and public sectors. Secondly a conceptual model has been developed and deployed, combining two of foresight’s most popular methods; scenario planning and technology roadmapping. The model addresses the weaknesses of each foresight technique as well as capitalizing on their individual, inherent strengths. Semi structured interviews, scenario planning workshops and a technology roadmapping exercise were conducted with the members of the HUG over an 18-month period. An action research mode of enquiry was utilized with a thematic analysis approach for the identification and discussion of the drivers and inhibitors of RFID adoption. The results of the conceptual model are analysed in comparison to other similar models. There are implications for managers responsible for RFID adoption in both the NHS and its commercial partners, and for foresight practitioners. Managers can leverage the insights gained from identifying the drivers and inhibitors to RFID adoption by making efforts to influence the removal of inhibitors and supporting the continuation of the drivers. The academic contribution of this aspect of the thesis is in the field of RFID adoption in healthcare settings. Drivers and inhibitors to RFID adoption in the English NHS are compared to those found in other settings. The implication for technology foresight practitioners is a proof of concept of a model combining scenario planning and technology roadmapping using a novel process. The academic contribution to the field of technology foresight is the conceptual development of foresight model that combines two popular techniques and then a deployment of the conceptual foresight model in a healthcare setting exploring the future of RFID technology.

The development of an optimized system of narcotic and explosive contraband mimics for calibration and training of biological detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

System-on-a-Chip (SOC) based environmental monitoring platform for the detection of hazardous materials

The purpose of this research is design considerations for environmental monitoring platforms for the detection of hazardous materials using System-on-a-Chip (SoC) design. Design considerations focus on improving key areas such as: (1) sampling methodology; (2) context awareness; and (3) sensor placement. These design considerations for environmental monitoring platforms using wireless sensor networks (WSN) is applied to the detection of methylmercury (MeHg) and environmental parameters affecting its formation (methylation) and deformation (demethylation). ^ The sampling methodology investigates a proof-of-concept for the monitoring of MeHg using three primary components: (1) chemical derivatization; (2) preconcentration using the purge-and-trap (P&T) method; and (3) sensing using Quartz Crystal Microbalance (QCM) sensors. This study focuses on the measurement of inorganic mercury (Hg) (e.g., Hg2+) and applies lessons learned to organic Hg (e.g., MeHg) detection. ^ Context awareness of a WSN and sampling strategies is enhanced by using spatial analysis techniques, namely geostatistical analysis (i.e., classical variography and ordinary point kriging), to help predict the phenomena of interest in unmonitored locations (i.e., locations without sensors). This aids in making more informed decisions on control of the WSN (e.g., communications strategy, power management, resource allocation, sampling rate and strategy, etc.). This methodology improves the precision of controllability by adding potentially significant information of unmonitored locations.^ There are two types of sensors that are investigated in this study for near-optimal placement in a WSN: (1) environmental (e.g., humidity, moisture, temperature, etc.) and (2) visual (e.g., camera) sensors. The near-optimal placement of environmental sensors is found utilizing a strategy which minimizes the variance of spatial analysis based on randomly chosen points representing the sensor locations. Spatial analysis is employed using geostatistical analysis and optimization occurs with Monte Carlo analysis. Visual sensor placement is accomplished for omnidirectional cameras operating in a WSN using an optimal placement metric (OPM) which is calculated for each grid point based on line-of-site (LOS) in a defined number of directions where known obstacles are taken into consideration. Optimal areas of camera placement are determined based on areas generating the largest OPMs. Statistical analysis is examined by using Monte Carlo analysis with varying number of obstacles and cameras in a defined space. ^

Evaluation of TerraSAR-X Observations for Wetland InSAR Application

This paper assesses the potential of using spaceborne X-band synthetic aperture radar (SAR) data for monitoring water-level changes over wetlands. Our analysis is based on three sets of TerraSAR-X (TSX) observations acquired over South Florida's Everglades wetlands during an eight-month period in 2008. The first set was acquired in single HH polarization stripmap mode over our northern study area, consisting of managed wetlands and urban environments. The second set was acquired in dual-polarization stripmap mode over the western half of the same area, consisting mostly of managed wetlands. The third set was also acquired with dual-polarization stripmap mode over our southern study area, consisting of natural flow freshand salt-water wetlands in the southern Everglades. The first data set was used for a proof-of-concept study to verify that X-band data can generate coherent interferograms in wetland areas. Interferometric processing of this data set shows a high level of coherence (> 0.35) over both wetland and urban regions, maintaining interferometric phase in all three interferograms spanning 11 days. Surprisingly, phase is maintained over some of the wetlands even for interferograms spanning 33 days. The other two data sets were used to evaluate interferometric coherence of all four polarization modes and to determine dominant scattering mechanism in each wetland environment. Our results show high coherence values (> 0.4) in all polarization modes, with highest values in HH, then VV, and lowest in HV or VH. Interferograms calculated from multipolarization data show very similar fringe patterns regardless of the polarization type, suggesting that the phase information in all polarization data reflects water-level changes in wetlands and that volume scattering may be less important than commonly believed. We also used the two multipolarization data sets to conduct the Pauli decomposition, finding a strong dependence of scattering mechanism on vegetation t- - ype. The high interferometric coherence level of all polarization data suggests that a significant part of the X-band scattered signal interacts with lower sections of the vegetation (trunks and branches), because scattering from wind-affected canopies cannot support such a high coherence level. The high spatial resolution of TSX, combined with its 11-day repeat orbit, makes this X-band sensor surprisingly suitable for wetland interferometric SAR applications.

The Development of an Optimized System of Narcotic and Explosive Contraband Mimics for Calibration and Training of Biological Detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

Multi-objective optimization of the molecular structure of refrigerants

The aim of this work was to develop a new methodology, which can be used to design new refrigerants that are better than the currently used refrigerants. The methodology draws some parallels with the general approach of computer aided molecular design. However, the mathematical way of representing the molecular structure of an organic compound and the use of meta models during the optimization process make it different. In essence, this approach aimed to generate molecules that conform to various property requirements that are known and specified a priori. A modified way of mathematically representing the molecular structure of an organic compound having up to four carbon atoms, along with atoms of other elements such as hydrogen, oxygen, fluorine, chlorine and bromine, was developed. The normal boiling temperature, enthalpy of vaporization, vapor pressure, tropospheric lifetime and biodegradability of 295 different organic compounds, were collected from open literature and data bases or estimated. Surrogate models linking the previously mentioned quantities with the molecular structure were developed. Constraints ensuring the generation of structurally feasible molecules were formulated and used in commercially available optimization algorithms to generate molecular structures of promising new refrigerants. This study was intended to serve as a proof-of-concept of designing refrigerants using the newly developed methodology.

Design, development and control of a new generation high performance linear actuator for parallel robots and other applications

The main focus of this research is to design and develop a high performance linear actuator based on a four bar mechanism. The present work includes the detailed analysis (kinematics and dynamics), design, implementation and experimental validation of the newly designed actuator. High performance is characterized by the acceleration of the actuator end effector. The principle of the newly designed actuator is to network the four bar rhombus configuration (where some bars are extended to form an X shape) to attain high acceleration. Firstly, a detailed kinematic analysis of the actuator is presented and kinematic performance is evaluated through MATLAB simulations. A dynamic equation of the actuator is achieved by using the Lagrangian dynamic formulation. A SIMULINK control model of the actuator is developed using the dynamic equation. In addition, Bond Graph methodology is presented for the dynamic simulation. The Bond Graph model comprises individual component modeling of the actuator along with control. Required torque was simulated using the Bond Graph model. Results indicate that, high acceleration (around 20g) can be achieved with modest (3 N-m or less) torque input. A practical prototype of the actuator is designed using SOLIDWORKS and then produced to verify the proof of concept. The design goal was to achieve the peak acceleration of more than 10g at the middle point of the travel length, when the end effector travels the stroke length (around 1 m). The actuator is primarily designed to operate in standalone condition and later to use it in the 3RPR parallel robot. A DC motor is used to operate the actuator. A quadrature encoder is attached with the DC motor to control the end effector. The associated control scheme of the actuator is analyzed and integrated with the physical prototype. From standalone experimentation of the actuator, around 17g acceleration was achieved by the end effector (stroke length was 0.2m to 0.78m). Results indicate that the developed dynamic model results are in good agreement. Finally, a Design of Experiment (DOE) based statistical approach is also introduced to identify the parametric combination that yields the greatest performance. Data are collected by using the Bond Graph model. This approach is helpful in designing the actuator without much complexity.

High spatial and temporal resolution interrogation of fully distributed chirped fiber Bragg grating sensors

A novel interrogation technique for fully distributed linearly chirped fiber Bragg grating (LCFBG) strain sensors with simultaneous high temporal and spatial resolution based on optical time-stretch frequency-domain reflectometry (OTS-FDR) is proposed and experimentally demonstrated. LCFBGs is a promising candidate for fully distributed sensors thanks to its longer grating length and broader reflection bandwidth compared to normal uniform FBGs. In the proposed system, two identical LCFBGs are employed in a Michelson interferometer setup with one grating serving as the reference grating whereas the other serving as the sensing element. Broadband spectral interferogram is formed and the strain information is encoded into the wavelength-dependent free spectral range (FSR). Ultrafast interrogation is achieved based on dispersion-induced time stretch such that the target spectral interferogram is mapped to a temporal interference waveform that can be captured in real-Time using a single-pixel photodector. The distributed strain along the sensing grating can be reconstructed from the instantaneous RF frequency of the captured waveform. High-spatial resolution is also obtained due to high-speed data acquisition. In a proof-of-concept experiment, ultrafast real-Time interrogation of fully-distributed grating sensors with various strain distributions is experimentally demonstrated. An ultrarapid measurement speed of 50 MHz with a high spatial resolution of 31.5 μm over a gauge length of 25 mm and a strain resolution of 9.1 μϵ have been achieved.

Biologically Inspired Design of Protein-Silica Hybrid Nanoparticles for Drug Delivery Applications

The design and application of effective drug carriers is a fundamental concern in the delivery of therapeutics for the treatment of cancer and other vexing health problems. Traditionally utilized chemotherapeutics are limited in efficacy due to poor bioavailability as a result of their size and solubility as well as significant deleterious effects to healthy tissue through their inability to preferentially target pathological cells and tissues, especially in treatment of cancer. Thus, a major effort in the development of nanoscopic drug delivery vehicles for cancer treatment has focused on exploiting the inherent differences in tumor physiology and limiting the exposure of drugs to non-tumorous tissue, which is commonly achieved by encapsulation of chemotherapeutics within macromolecular or supramolecular carriers that incorporate targeting ligands and that enable controlled release. The overall aim of this work is to engineer a hybrid nanomaterial system comprised of protein and silica and to characterize its potential as an encapsulating drug carrier. The synthesis of silica, an attractive nanomaterial component because it is both biocompatible as well as structurally and chemically stable, within this system is catalyzed by self-assembled elastin-like polypeptide (ELP) micelles that incorporate of a class of biologically-inspired, silica-promoting peptides, silaffins. Furthermore, this methodology produces near-monodisperse, hybrid inorganic/micellar materials under mild reaction conditions such as temperature, pH and solvent. This work studies this material system along three avenues: 1) proof-of-concept silicification (i.e. the formation and deposition of silica upon organic materials) of ELP micellar templates, 2) encapsulation and pH-triggered release of small, hydrophobic chemotherapeutics, and 3) selective silicification of templates to potentiate retention of peptide targeting ability.

(Table 1) Isotopic composition of organic compinents of DSDP Hole 24-231

Plant leaf wax hydrogen isotope (dDwax) reconstructions are increasingly being used to reconstruct hydrological change. This approach is based upon the assumption that variations in hydroclimatic variables, and in particular, the isotopic composition of precipitation (dDP), dominate dDwax. However modern calibration studies suggest that offsets between plant types may bias the dDwax hydrological proxy at times of vegetation change. In this study, I pair leaf wax analyses with published pollen data to quantify this effect and construct the first vegetation-corrected hydrogen isotopic evidence for precipitation (dDcorrP). In marine sediments from Deep Sea Drilling Program Site 231 in the Gulf of Aden spanning 11.4-3.8 Ma (late Miocene and earliest Pliocene), I find 77 per mil swings in dDwax that correspond to pollen evidence for substantial vegetation change. Similarities between dDP and dDcorrP imply that the hydrological tracer is qualitatively robust to vegetation change. However, computed vegetation corrections can be as large as 31 per mil indicating substantial quantitative uncertainty in the raw hydrological proxy. The resulting dDcorrP values quantify hydrological change and allow us to identify times considerably wetter than modern at 11.09, 7.26, 5.71 and 3.89 Ma. More generally, this novel interpretative framework builds the foundations of improved quantitative paleohydrological reconstructions with the dDwax proxy, in contexts where vegetation change may bias the plant-based proxy. The vegetation corrected paleoprecipitation reconstruction dDcorrP, represents the best available estimate as proof-of-concept, for an approach that I hope will be refined and more broadly applied.

The application of PCA as a movement pattern recognition technique: A proof of principle

Quantitative methods can help us understand how underlying attributes contribute to movement patterns. Applying principal components analysis (PCA) to whole-body motion data may provide an objective data-driven method to identify unique and statistically important movement patterns. Therefore, the primary purpose of this study was to determine if athletes’ movement patterns can be differentiated based on skill level or sport played using PCA. Motion capture data from 542 athletes performing three sport-screening movements (i.e. bird-dog, drop jump, T-balance) were analyzed. A PCA-based pattern recognition technique was used to analyze the data. Prior to analyzing the effects of skill level or sport on movement patterns, methodological considerations related to motion analysis reference coordinate system were assessed. All analyses were addressed as case-studies. For the first case study, referencing motion data to a global (lab-based) coordinate system compared to a local (segment-based) coordinate system affected the ability to interpret important movement features. Furthermore, for the second case study, where the interpretability of PCs was assessed when data were referenced to a stationary versus a moving segment-based coordinate system, PCs were more interpretable when data were referenced to a stationary coordinate system for both the bird-dog and T-balance task. As a result of the findings from case study 1 and 2, only stationary segment-based coordinate systems were used in cases 3 and 4. During the bird-dog task, elite athletes had significantly lower scores compared to recreational athletes for principal component (PC) 1. For the T-balance movement, elite athletes had significantly lower scores compared to recreational athletes for PC 2. In both analyses the lower scores in elite athletes represented a greater range of motion. Finally, case study 4 reported differences in athletes’ movement patterns who competed in different sports, and significant differences in technique were detected during the bird-dog task. Through these case studies, this thesis highlights the feasibility of applying PCA as a movement pattern recognition technique in athletes. Future research can build on this proof-of-principle work to develop robust quantitative methods to help us better understand how underlying attributes (e.g. height, sex, ability, injury history, training type) contribute to performance.

Supply Chain Resilience? Definition of concept and its formative elements.

The objective of this paper is to conceptualize Supply Chain Resilience (SCRes) and identify which supply chain capabilities can support the containment of disruptions and how these capabilities affect SCRes. Through a systematic and structured review of literature, this paper provides insights into the conceptualization and research methodological background of the SCM field. A total of one hundred and thirty four carefully selected refereed journal articles were systematically analyzed leading to the introduction of a novel definition for SCRes, which the authors view as the as “the ability to proactively plan and design the Supply Chain network for anticipating unexpected disruptive (negative) events, respond adaptively to disruptions while maintaining control over structure and function and transcending to a post-event robust state of operations, if possible, more favorable than the one prior to the event, thus gaining competitive advantage”. Finally, a critical examination of existing conceptual frameworks for understanding the relationships between the SCRes concept and its identified formative elements, is taking place.

The potential contributions of concept maps for learning website to assessment for learning practices

The purpose of this paper is to examine the promising contributions of the Concept Maps for Learning (CMfL) website to assessment for learning practices. The CMfL website generates concept maps from relatedness degree of concepts pairs through the Pathfinder Scaling Algorithm. This website also confirms the established principles of effective assessment for learning, for it is capable of automatically assessing students' higher order knowledge, simultaneously identifying strengths and weaknesses, immediately providing useful feedback and being user-friendly. According to the default assessment plan, students first create concept maps on a particular subject and then they are given individualized visual feedback followed by associated instructional material (e.g., videos, website links, examples, problems, etc.) based on a comparison of their concept map and a subject matter expert's map. After studying the feedback and instructional material, teachers can monitor their students' progress by having them create revised concept maps. Therefore, we claim that the CMfL website may reduce the workload of teachers as well as provide immediate and delayed feedback on the weaknesses of students in different forms such as graphical and multimedia. For the following study, we will examine whether these promising contributions to assessment for learning are valid in a variety of subjects.