Help: defining the usability requirements of a breast cancer long-term survivorship (LTS) navigator

Indiana University-Purdue University Indianapolis (IUPUI)Long-term survivors (LTSs) of breast cancer are defined as patients who have been in remission for a year or longer. Even after being declared breast-cancer-free, many LTSs have questions that were not answered by clinicians. Although online resources provide some content for LTSs, none, or very little, provide immediate answers to specific questions. Thus, the aim involves proposing specifications for a system, the Health Electronic Learning Platform (HELP), that can assist survivors by becoming an all-inclusive resource for LTSs of breast cancer. To achieve this, relevant information from the literature was used to assess the needs of LTSs. Also, data from a study involving the breast cancer survivor’s forum project that had been filtered to include posts with mentions of features to be added to the website and usability issues encountered. To complete the actual design of the system, a synthesis of the results obtained from these two sources was performed. HELP is simple in terms of its layout and consists of a main search-bar, where LTSs are able to ask questions using their own terms and language. This navigator should not be taken as definitive solution, but instead, should be used as a starting point toward better patient-centered care

New Materials for Photoconductive Terahertz Antennas

In this thesis, we have first introduced a new setup for the reliable characterization of photoconductive antennas to be used in THz time-domain spectroscopy. Using this setup one can benchmark THz antennas with high precision. The intra-day reproducibility error is in the range of 1.9% while the reproducibility within 9 days is 2.6%. This includes not only absolute power stability but also reproducibility of the spectra by eliminating alignment errors that alter the transfer function from sender to receiver. In order to demonstrate the full capabilities of the system, we investigated samples from five LT-GaAs wafers, grown at temperatures between 200°C and 300°C, in a systematic manner. The obtained results are in good agreement with previous studies on the same material system. These results prove that the system allows for quality control of photoconductors with minimum comparison error. We have also investigated the correlation between THz emission strength and the surface properties of the LT-GaAs photoconductive antenna. The THz characteristics were measured with the highly stable setup mentioned above, which allowed exciting a 10-mm long CPS antenna along the gap without changing the alignment of the optical or THz beam path. The surface properties were quantified regarding roughness and grain size. The roughness was extracted from AFM measurements and the grain size from SEM measurements. A comparison of the THz emission strength in form of the peak-to peak THz amplitude and the surface properties showed a strong nonlinear correlation: a smaller grain size and a smoother surface increase the THz amplitude. These results can be used in the future to optimize the performance of THz antennas. Additionally, we have successfully prepared TiN-nanoparticles using ultrasonic and pulsed laser ablation techniques. The two techniques provide with a different distribution of Zeta-potential and particle size. Within our experimental conditions, pulsed laser ablation can give lower particle size and greater Zeta-potential. TiN-nanoparticles prepared by these techniques have a high and flat absorbance in the spectral range 600 -1000 nm. LT-GaAs covered with dispersed TiNnanoparticles has enhanced THz emission when the average particle size is about 62 nm. More investigations are needed on how to develop preparation and deposition techniques in such a way that control the shape, size, distance between the particles. This may lead to a further improvement of the THz power emitted from such devices. Finally, we demonstrated that coating with MnFe2O4 nanoparticles could be used to improve the performance of photoconductive antennas in the THz region. Our experiments demonstrate that coatings with MnFe2O4−particles provided a new approach to increase the photocurrent density on silicon under CW illumination. In order to understand the effect ofMnFe2O4 nanoparticles on photo-excited silicon, a semiconductor model was proposed to describe this phenomenon. We used this model to calculate the transmission amplitudes of THz pulses transmitted through bare silicon substrates and silicon substrates covered by MnFe2O4 nanoparticles under laser irradiation with different powers. Because the effect of MnFe2O4 nanoparticles on silicon significantly provides an enhanced attenuation of terahertz wave, silicon substrates covered by MnFe2O4 nanoparticles have the potential to be used as an optical modulator in the THz region. This may lead to a costefficient component for THz systems operating in transmission mode. Furthermore, MnFe2O4 nanoparticles could be used for the implementation of novel optical devices

Dependability analysis and recovery support for smart grids

The increasing scale and complexity of power grids exacerbate concerns about failure propagation. A single contingency, such as outage of a transmission line due to overload or weather-related damage, can cause cascading failures that manifest as blackouts. One objective of smart grids is to reduce the likelihood of cascading failure through the use of power electronics devices that can prevent, isolate, and mitigate the effects of faults. Given that these devices are themselves prone to failure, we seek to quantify the effects of their use on dependability attributes of smart grid. This thesis articulates analytical methods for analyzing two dependability attributes - reliability and survivability - and proposes a recovery strategy that limits service degradation. Reliability captures the probability of system-level failure; Survivability describes degraded operation in the presence of a fault. System condition and service capacity are selected as measures of degradation. Both reliability and survivability are evaluated using N-1 contingency analysis. Importance analysis is used to determine a recovery strategy that maintains the highest survivability in the course of the recovery process. The proposed methods are illustrated by application to the IEEE 9-bus test system, a simple model system that allows for clear articulation of the process. Simulation is used to capture the effect of faults in both physical components of the power grid and the cyber infrastructure that differentiates it as a smart grid --Abstract, page iii

Predictive analysis of real-time strategy games using graph mining

Machine learning and computational intelligence have facilitated the development of recommendation systems for a broad range of domains. Such recommendations are based on contextual information that is explicitly provided or pervasively collected. Recommendation systems often improve decision-making or increase the efficacy of a task. Real-Time Strategy (RTS) video games are not only a popular entertainment medium, they also are an abstraction of many real-world applications where the aim is to increase your resources and decrease those of your opponent. Using predictive analytics, which examines past examples of success and failure, we can learn how to predict positive outcomes for such scenarios. To do this, one way to represent this type of data in order to model relationships between entities is by using graphs. The vast amount of data has resulting in complex and large graphs that are difficult to process. Hence, researchers frequently employ parallelized or distributed processing. But first, the graph data must be partitioned and assigned to multiple processors in such a way that the workload will be balanced, and inter-processor communication will be minimized. The latter problem may be complicated by the existence of edges between vertices in a graph that have been assigned to different processors. One objective of this research is to develop an accurate predictive recommendation system for multiplayer strategic games to determine recommendations for moves that a player should, and should not, make which can provide a competitive advantage. Another objective is to determine how to partition a single undirected graph in order to optimize multiprocessor load balancing and reduce the number of edges between split subgraphs --Abstract, page iv

Organizational Knowledge Systems Design & Implementation

This research paper aims to explain relationships of   organization learning (OL), knowledge management (KM), talent management (TM) practices and organizational performance (OP) in order to have excellent understanding of the subject by using in-depth analysis of the extant literature. This research offers mechanisms for Organizational Knowledge Systems (OKS) that will help the entity to apply OKS. The research paper has created a complete mechanism of the OKS then tests the proposed model. Keywords: Organization Learning, Knowledge Management, Talent Management and Organization Knowledge Systems

Build Innovation through Organizational Learning Capability

This research paper aims to explain the relationship between Organizational Learning (OL), and Organization Innovation (OI). The Author has used analysis of the related literatures to have deep understanding of the subject. This research offers personal mastery, systems thinking and team learning as organizational Learning Capability that will help the entity to have an innovation

Investigations on how the enteropathogenic Escherichia coli (EPEC) EspF effector inhibits PI-3 kinase-dependent phagocytosis

PhD ThesisEnteropathogenic E. coli inhibits phosphoinositide 3 (PI-3) kinase dependent phagocytosis via a Type Three Secretion System (T3SS) that delivers up to twenty effector proteins into target cells. The T3SS components are encoded on the Locus of Enterocyte Effacement (LEE) pathogenicity island alongside genes for a surface protein, Intimin, and seven effectors (Tir, Map, EspF, EspG, EspZ, EspH and EspB; latter also needed to deliver effectors). Inhibiting phagocytosis is linked to EspB, EspH, EspG and EspF activities with inhibitory mechanisms described for all except EspF. The aim of this study was to determine if EspF alone could inhibit phagocytosis and define the inhibitory mechanism. Initial anti-phagocytosis studies, with J774A.1 macrophages, not only confirmed EspF and T3SS-dependent inhibition but suggested a T3SS-independent contribution. Moreover, studies with effectors-deficient EPEC and non-pathogenic E. coli carrying LEE on a plasmid argued for LEE sufficiency. Surprisingly, delivering EspF into macrophages without most (EPEC multi-mutant) or all (via T3SS of another pathogen, Yersinia) other EPEC effectors argued against EspF sufficiency. Interestingly, the data also argued against EspG driving the anti-phagocytosis process but suggested that EspF’s contribution required Map, EspH, Tir, and/or the Intimin activities. Surprisingly, screening EspF/Map/EspH/Tir/Intimin single, double, triple, quadruple and quintuple mutants failed to confirm the critical roles for EspF or EspH that are linked to phenotypic instability and/or indirect contributions. Preliminary investigations on EspF’s involvement revealed possible features and domains required for its efficient expression, secretion and/or inhibiting phagocytosis. Crucially, the screening data provided many hypotheses including Tir and Intimin being able to drive T3SS-dependent anti-phagocytosis, an idea supported by complementation studies. Collectively, this study provides important new insights on EPEC’s ability to inhibit its uptake by J774A.1 macrophages and reveals unknown levels of complexity.Higher Committee for Education Development in Iraq (HCED

Saliency guided local and global descriptors for effective action recognition

This paper presents a novel framework for human action recognition based on salient object detection and a new combination of local and global descriptors. We first detect salient objects in video frames and only extract features for such objects. We then use a simple strategy to identify and process only those video frames that contain salient objects. Processing salient objects instead of all frames not only makes the algorithm more efficient, but more importantly also suppresses the interference of background pixels. We combine this approach with a new combination of local and global descriptors, namely 3D-SIFT and histograms of oriented optical flow (HOOF), respectively. The resulting saliency guided 3D-SIFT–HOOF (SGSH) feature is used along with a multi-class support vector machine (SVM) classifier for human action recognition. Experiments conducted on the standard KTH and UCF-Sports action benchmarks show that our new method outperforms the competing state-of-the-art spatiotemporal feature-based human action recognition metho

Desdemona and Othello: An Adaptation

Paula Vogel, after 376 years of the publication of Othello, writes her play Desdemona assuming that Othello is right in his accusation to his wife, and Iago’s story about Desdemona’s infidelity is not a false story. After his ear is poisoned with jealousy, Othello asks his wife Desdemona direct questions: “[a]re not you a strumpet? ... What, not a whore?” (4.2. 81, 84). At that moment, most of the readers, if not all, sympathize with Desdemona in a tremendous way. No one can believe or expect for a minute that Othello’s speech is true and that Desdemona is not a faithful wife. Vogel depicts Desdemona as a whore, that Othello imagines her to be, as the new heroine of her play. Vogel characterizes a female figure who is an adventurer, an ordinary woman who is looking for excitement. Vogel rewrites William Shakespeare’s Othello from a female perspective where the focus is not on a man but on a woman. Vogel creates a three-dimensional female character who is problematic and complicated So stated, Vogel adapts a character from the original and develops her to write a play about a different Desdemona