Analysis and comparison of resistive, ferroelectric and pyroelectric uncooled bolometers for electronic imaging systems

The performance parameters (responsivity (Rv). detectivity (D*), total noise and response time) of resistive, pyroelectric and ferroelectric bolometer detectors are dependent on a large number of key variables including chopping frequercy, the input impedance and voltage noise of the readout circuitry, the structure dependent parameters (particularly thermal conductance and thermal capacitance), and material properties such as dielectric constant, pyroelectric coefficient, loss tangent and thin film thickness. The interrelationship between the key variables and their influence on performance is often complex and not easily discerned for the three major types of thermal detectors: resistive, pyroelectric and ferroelectric bolometers. In this thesis research, the dependence of Rv, D* and total noise on these key parameters were analyzed and written as equations from which computer calculations could easily be made. The analyzed results were used to compare the pertbrmance of the three types of sensors for present-day structure and material characteristics and also for material characteristics and structures that night be developed in the future

Experimental analysis of gene assembly with TopDown one-step real-time gene synthesis

Herein we present a simple, cost-effective TopDown (TD) gene synthesis method that eliminates the interference between the polymerase chain reactions (PCR) assembly and amplification in one-step gene synthesis. The method involves two key steps: (i) design of outer primers and assembly oligonucleotide set with a melting temperature difference of >10°C and (ii) utilization of annealing temperatures to selectively control the efficiencies of oligonucleotide assembly and full-length template amplification. In addition, we have combined the proposed method with real-time PCR to analyze the step-wise efficiency and the kinetics of the gene synthesis process. Gel electrophoresis results are compared with real-time fluorescence signals to investigate the effects of oligonucleotide concentration, outer primer concentration, stringency of annealing temperature, and number of PCR cycles. Analysis of the experimental results has led to insights into the gene synthesis process. We further discuss the conditions for preventing the formation of spurious DNA products. The TD real-time gene synthesis method provides a simple and efficient method for assembling fairly long DNA sequence, and aids in optimizing gene synthesis conditions. To our knowledge, this is the first report that utilizes real-time PCR for gene synthesis

Identification of Topological Features in Renal Tumor Microenvironment Associated with Patient Survival

Motivation As a highly heterogeneous disease, the progression of tumor is not only achieved by unlimited growth of the tumor cells, but also supported, stimulated, and nurtured by the microenvironment around it. However, traditional qualitative and/or semi-quantitative parameters obtained by pathologist’s visual examination have very limited capability to capture this interaction between tumor and its microenvironment. With the advent of digital pathology, computerized image analysis may provide a better tumor characterization and give new insights into this problem. Results We propose a novel bioimage informatics pipeline for automatically characterizing the topological organization of different cell patterns in the tumor microenvironment. We apply this pipeline to the only publicly available large histopathology image dataset for a cohort of 190 patients with papillary renal cell carcinoma obtained from The Cancer Genome Atlas project. Experimental results show that the proposed topological features can successfully stratify early- and middle-stage patients with distinct survival, and show superior performance to traditional clinical features and cellular morphological and intensity features. The proposed features not only provide new insights into the topological organizations of cancers, but also can be integrated with genomic data in future studies to develop new integrative biomarkers

Response-surface-model-based system sizing for nearly/net zero energy buildings under uncertainty

Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty