Salvage Hyperthermic Gemcitabine and Docetaxel Combination Chemotherapy After BCG Failure in Non-Muscle Invasive Bladder Cancer Patients

A Thesis submitted to The University of Arizona College of Medicine - Phoenix in partial fulfillment of the requirements for the Degree of Doctor of Medicine.In patients with non-muscle invasive bladder cancer (NMIBC), intravesical BCG has been shown to reduce the rate of disease recurrence and disease progression, as well as improve disease-specific survival. While Bacillus Calmette-Guerin (BCG) has become the gold-standard therapy for NMIBC, there are still patients who fail this therapy or are not good candidates for it. Although a radical cystectomy is recommended when BCG is failed, some patients either desire bladder preservation or are not surgical candidates. Thus, further exploration into salvage chemo therapy treatments should be done to provide these patients with an alternative treatment option. The purpose of this study is to analyze if combination Gemcitabine and Docetaxel chemotherapy (GEM/DOCE) is a successful salvage option in adults who have failed or cannot tolerate BCG therapy for NMIBC, and are poor surgical candidates for a radical cystectomy (RC) or desire bladder preservation. In this retrospective study, 60 patients were included. Overall treatment success was 83% (50/60) at first surveillance, 69% at 1-year, and 55% at 2-years after induction of GEM/DOCE in the entire cohort, and 90%(53/51) at first surveillance, 74% at 1-year, and 56% at 2-years in the BCG-failure patients. These success rates are quite favorable and warrant further investigation in a prospective manner to further optimize this salvage protocol for patients who remain a challenge to treat.This item is part of the College of Medicine - Phoenix Scholarly Projects 2019 collection. For more information, contact the Phoenix Biomedical Campus Library at [email protected]

Combination of Music and Aromatherapy to Improve the Efficiency of Motor Functions and Speech in Patients Paralyzed From Stroke.

With the rapid development of medical technology, millions of dollars are being spent on discovering innovative methods of treating fatal diseases such as stroke that may also result in temporary paralysis. Physiotherapy treatments aimed at restoring brain function in patients paralyzed following a stroke is subjective to the patient and does not guarantee complete rehabilitation. While many practitioners have attempted to employ complementary and alternative methods of treatment such as massage therapy, acupuncture therapy, siddha, and marma therapy, none of them proved to be equally as effective as physiotherapy. However, prior studies support the notion that aromatherapy used in combination with music therapy showed promising results. Aromatherapy, defined as using extracted oils from plants and herbs to naturally treat the body through oral or skin absorption, has been effective in halting the process of apoptosis, or programmed cell death in cells. The inhibition of apoptosis may be principal in delaying the degeneration of brain cells. Music therapy, on the other hand, uses a process known as entrainment to access a paralyzed brain for rhythmic perception. These two processes are connected through transduction, which elaborates the relationship between the olfactory and auditory system that improves the efficiency of memory retention through familiar scents and sounds. Using aromatherapy in combination with music therapy is more effective because it is a self-paced treatment that does not require the administration of a trained professional. This alternative treatment for paralyzed stroke patients will be applicable to the general public if administered in reasonable doses under appropriate conditions.https://scholarscompass.vcu.edu/uresposters/1196/thumbnail.jp

Relationship Building in E-negotiation: Dyadic Effects on Subjective Negotiation Outcomes

E-negotiation is a critical activity that is becoming a new reality (Sokolova et al., 2006), however, the e-negotiation environment lends itself to fewer informative cues than the face-to-face environment. The ability to maintain relationships with parties and negotiate with them in the future increases the negotiator’s bargaining power and could be important beyond economic outcomes (Curhan & Brown, 2011). This study investigates the link between relationship-building and subjective values in negotiation, and how the negotiation medium may change this relationship. Subjective values of rapport, trustworthiness, and interest in future interaction were predicted to both differ by e-negotiation and face-to-face negotiation condition and be influenced by the amount of relationship-building language in the negotiation. Sixty-six same-gender dyads negotiated either by e-negotiation or in person. The impact of dyadic relationship-building was tested using the Actor-Partner Interdependence Model (Kenny et al., 2002). Results found that the amount of relationship-building was not associated with dyadic perceptions of trustworthiness, rapport, or interest in future interaction. There were no significant partner effects for relationship-building and the three subjective value outcomes. Finally, condition did not moderate the link between relationship-building and subjective value outcomes. Possible explanations of the implications and the lack of findings are discussed

Evaluating the Performance of a Large-Scale Facial Image Dataset Using Agglomerated Match Score Statistics

Biometrics systems are experiencing wide-spread usage in identification and access control applications. To estimate the performance of any biometric systems, their characteristics need to be analyzed to make concrete conclusions for real time usage. Performance testing of hardware or software components of either custom or state-of-the-art commercial biometric systems is typically carried out on large datasets. Several public and private datasets are used in current biometric research. West Virginia University has completed several large scale multimodal biometric data collection with an aim to create research datasets that can be used by disciplines concerning secured biometric applications. However, the demographic and image quality properties of these datasets can potentially lead to bias when they are used in performance testing of new systems. To overcome this, the characteristics of datasets used for performance testing must be well understood prior to usage.;This thesis will answer three main questions associated with this issue:;• For a single matcher, do the genuine and impostor match score distributions within specific demographics groups vary from those of the entire dataset? • What are the possible ways to compare the subset of demographic match score distributions against those of the entire dataset? • Based on these comparisons, what conclusions can be made about the characteristics of dataset?;In this work, 13,976 frontal face images from WVU\u27s 2012 Biometric collection project funded by the FBI involving 1200 individuals were used as a \u27test\u27 dataset. The goal was to evaluate performance of this dataset by generating genuine and impostor match scores distributions using a commercial matching software Further, the dataset was categorized demographically, and match score distributions were generated for these subsets in order to explore whether or not this breakdown impacted match score distributions. The match score distributions of the overall dataset were compared against each demographic cohorts.;Using statistical measures, Area under Curve (AUC) and Equal Error Rate (EER) were observed by plotting Receiver Operating Characteristics (ROC) curves to measure the performance of each demographic group with respect to overall data and also within the cohorts of demographic group. Also, Kull-back Leibler Divergence and Jensen Shannon Divergence values were calculated for each demographic cohort (age, gender and ethnicity) within the overall data. These statistical approaches provide a numerical value representing the amount of variation between two match score distributions In addition, FAR and FRR was observed to estimate the error rates. These statistical measures effectively enabled the determination of the impact of different demographic breakdown on match score distributions, and thus, helped in understanding the characteristics of dataset and how they may impact its usage in performance testing biometrics

On predicting stopping time of human sequential decision-making using discounted satisficing heuristic

“Human sequential decision-making involves two essential questions: (i) what to choose next? , and (ii) when to stop? . Assuming that the human agents choose an alternative according to their preference order, our goal is to model and learn how human agents choose their stopping time while making sequential decisions. In contrary to traditional assumptions in the literature regarding how humans exhibit satisficing behavior on instantaneous utilities, we assume that humans employ a discounted satisficing heuristic to compute their stopping time, i.e., the human agent stops working if the total accumulated utility goes beyond a dynamic threshold that gets discounted with time. In this thesis, we model the stopping time in 3 scenarios where the payoff of the human worker is assumed as (i) single-attribute utility, (ii) multi-attribute utility with known weights, and (iii) multi-attribute utility with unknown weights. We propose algorithms to estimate the model parameters followed by predicting the stopping time in all three scenarios and present the simulation results to demonstrate the error performance. Simulation results are presented to demonstrate the convergence of prediction error of stopping time, in spite of the fact that model parameters converge to biased estimates. This observation is later justified using an illustrative example to show that there are multiple discounted satisficing models that explain the same stopping time decision. A novel web application is also developed to emulate a crowd-sourcing platform in our lab to capture multi-attribute information regarding the task in order to perform validations of the proposed algorithms on real data”--Abstract, page iii

Modified Kuijk Bandgap Reference with VGO Extraction

This creative component presents an innovative CMOS Bandgap Reference Generator topology targeting sub-ppm temperature coefficient over a wide temperature range. The proposed circuit consists of extracting VGO from the temperature characteristics of VBE. VGO is the bandgap voltage of the silicon that is extrapolated at 0K and is temperature independent over a wide range of temperature (-40°C to 125°C). Analytical constraints are carefully investigated which lead to the output voltage that is proportional to VGO when certain mismatches and opamp offsets are accurately trimmed using two temperatures trimming. The modified circuit, less number of operational amplifiers and resistors which make the circuit less complex, reduces area and power requirements. Transistor level simulations are implemented in GlobalFoundries 130nm process and achieve temperature coefficient about 3.5ppm/°C across the industrial temperature range (-40 °C to 80 °C)

High Performance GNRFET Devices for High-Speed Low-Power Analog and Digital Applications

Indiana University-Purdue University Indianapolis (IUPUI)Recent ULSI (ultra large scale integration) technology emphasizes small size devices, featuring low power and high switching speed. Moore's law has been followed successfully in scaling down the silicon device in order to enhance the level of integration with high performances until conventional devices failed to cop up with further scaling due to limitations with ballistic effects, and challenges with accommodating dopant fluctuation, mobility degradation, among other device parameters. Recently, Graphene based devices o ered alternative approach, featuring small size and high performances. This includes high carrier mobility, high carrier density, high robustness, and high thermal conductivity. These unique characteristics made the Graphene devices attractive for high speed electronic architectures. In this research, Graphene devices were integrated into applications with analog, digital, and mixed signals based systems. Graphene devices were briefly explored in electronics applications since its first model developed by the University of Illinois, Champaign in 2013. This study emphasizes the validation of the model in various applications with analog, digital, and mixed signals. At the analog level, the model was used for voltage and power amplifiers; classes A, B, and AB. At the digital level, the device model was validated within the universal gates, adders, multipliers, subtractors, multiplexers, demultiplexers, encoders, and comparators. The study was also extended to include Graphene devices for serializers, the digital systems incorporated into the data structure storage. At the mixed signal level, the device model was validated for the DACs/ADCs. In all components, the features of the new devices were emphasized as compared with the existing silicon technology. The system functionality and dynamic performances were also elaborated. The study also covered the linearity characteristics of the devices within full input range operation. GNRFETs with a minimum channel length of 10nm and an input voltage 0.7V were considered in the study. An electronic design platform ADS (Advanced Design Systems) was used in the simulations. The power amplifiers showed noise figure as low as 0.064dbs for class A, and 0.32 dbs for class B, and 0.69 dbs for class AB power amplifiers. The design was stable and as high as 5.12 for class A, 1.02 for class B, and 1.014 for class AB. The stability factor was estimated at 2GHz operation. The harmonics were as low as -100 dbs for class A, -60 dbs for class B, and -50dbs for class AB, all simulated at 1GHz. The device was incorporated into ADC system, and as low as 24.5 micro Watt power consumption and 40 nsec rise time were observed. Likewise, the DAC showed low power consumption as of 4.51 micro Watt. The serializer showed as minimum power consumption of the order of 0.4mW. These results showed that these nanoscale devices have potential future for high-speed communication systems, medical devices, computer architecture and dynamic Nano electromechanical (NEMS) which provides ultra-level of integration, incorporating embedded and IoT devices supporting this technology. Results of analog and digital components showed superiority over other silicon transistor technologies in their ultra-low power consumption and high switching speed

Bharati Mukherjee’s Jasmine: Decolonizing Text or Postcolonial Jane Eyre?

A strong belief in the diversity of the immigration narrative is found time and time again in Mukherjee\u27s novel Jasmine, a postcolonial text that looks at the shifting identity politics through the immigration journey of Jyoti, a young girl from India. Mukherjee establishes an overarching decolonizing narrative of an immigrant through Jyoti’s transition in identities throughout the course of her story, using the liminality of Jyoti’s identity as a means of deconstructing the immigrant myth

Industrial Pollution: Contamination of Surface Water & Human Health in Veerapura, Bangalore

Articlehttp://deepblue.lib.umich.edu/bitstream/2027.42/96998/1/UMURJ-Issue07_2010-MVallurupalli.pd