Numerical investigation of the thermal stratification in cryogenic tanks subjected to wall heat flux

The flow pattern and thermal stratification of a cryogenic cylindrical tank are numerically studied. The tank sidewall is subjected to either a uniform heat-flux or two discrete levels of uniform heat-flux at the upper and lower halves of the tank wall. The tank bottom is kept at a constant temperature controlled by the heat exchanger of a thermodynamic vent system. The tank pressure is also assumed constant resulting in a constant saturation temperature at the interface which is higher than the tank bottom temperature. The effects of vapor motion and vapor superheat on the mass and heat transfer processes at the interface are assumed negligible such that the calculations of liquid region can be decoupled from the vapor region. Dimensionless steady-state conservation equations are solved by a finite-difference method. The effects of modified Rayleigh number, Prandtl number, tank aspect ratio, wall heat-flux parameter, and wall heat-flux distribution on the liquid velocity and temperature fields are investigated. Also, their effects on the rate of heat transfer through the interface and the tank bottom are examined

Influence Of Environmental Conditions On The Response Of MEMS Resonators

Micro-electro-mechanical-system (MEMS) devices are increasingly employed in physical systems to fill the growing demand for fast, small, cheap sensors. And with MEMS devices rapidly becoming miniaturized to increase accuracy and reduce response time, analysis of their reliability in different environments is increasingly needed. Furthermore, new sensor designs for applications such as temperature, humidity and pressure sensors, that directly utilize the MEMS interactions within their environments, are growing in demand. In this work, a comprehensive study of the response of MEMS cantilever and clamped-clamped resonators under various environmental conditions is performed in both the linear and nonlinear regimes. The study shows a consistent reduction of the natural frequency of cantilever and clamped-clamped MEMS devices due to the increase of humidity under fixed pressure and temperature as a result of decreasing the dynamic viscosity of air. This change is greater at high temperatures and is further increased when thermal stresses build up within the MEMS device or when the device is operated nonlinearly. Moreover, the study presents a possibility to correct for the effects of temperature and humidity due to the linearity around the primary resonance. Finally, this study demonstrates the viability of uncoated sensors for temperature, humidity and pressure sensing. Advisor: Fadi Alsalee

MACHINE LEARNING AUGMENTATION MICRO-SENSORS FOR SMART DEVICE APPLICATIONS

Novel smart technologies such as wearable devices and unconventional robotics have been enabled by advancements in semiconductor technologies, which have miniaturized the sizes of transistors and sensors. These technologies promise great improvements to public health. However, current computational paradigms are ill-suited for use in novel smart technologies as they fail to meet their strict power and size requirements. In this dissertation, we present two bio-inspired colocalized sensing-and-computing schemes performed at the sensor level: continuous-time recurrent neural networks (CTRNNs) and reservoir computers (RCs). These schemes arise from the nonlinear dynamics of micro-electro-mechanical systems (MEMS), which facilitates computing, and the inherent ability of MEMS devices for sensing. Furthermore, this dissertation addresses the high-voltage requirements in electrostatically actuated MEMS devices using a passive amplification scheme. The CTRNN architecture is emulated using a network of bistable MEMS devices. This bistable behavior is shown in the pull-in, the snapthrough, and the feedback regimes, when excited around the electrical resonance frequency. In these regimes, MEMS devices exhibit key behaviors found in biological neuronal populations. When coupled, networks of MEMS are shown to be successful at classification and control tasks. Moreover, MEMS accelerometers are shown to be successful at acceleration waveform classification without the need for external processors. MEMS devices are additionally shown to perform computing by utilizing the RC architecture. Here, a delay-based RC scheme is studied, which uses one MEMS device to simulate the behavior of a large neural network through input modulation. We introduce a modulation scheme that enables colocalized sensing-and-computing by modulating the bias signal. The MEMS RC is tested to successfully perform pure computation and colocalized sensing-and-computing for both classification and regression tasks, even in noisy environments. Finally, we address the high-voltage requirements of electrostatically actuated MEMS devices by proposing a passive amplification scheme utilizing the mechanical and electrical resonances of MEMS devices simultaneously. Using this scheme, an order-of-magnitude of amplification is reported. Moreover, when only electrical resonance is used, we show that the MEMS device exhibits a computationally useful bistable response. Adviser: Dr. Fadi Alsalee

Voltage and Deflection Amplification via Double Resonance Excitation in a Cantilever Microstructure

Cantilever electrostatically-actuated resonators show great promise in sensing and actuating applications. However, the electrostatic actuation suffers from high-voltage actuation requirements and high noise low-amplitude signal-outputs which limit its applications. Here, we introduce a mixed-frequency signal for a cantilever-based resonator that triggers its mechanical and electrical resonances simultaneously, to overcome these limitations. A single linear RLC circuit cannot completely capture the response of the resonator under double resonance excitation. Therefore, we develop a coupled mechanical and electrical mathematical linearized model at different operation frequencies and validate this model experimentally. The double-resonance excitation results in a 21 times amplification of the voltage across the resonator and 31 times amplitude amplification over classical excitation schemes. This intensive experimental study showed a great potential of double resonance excitation providing a high amplitude amplification and maintaining the linearity of the system when the parasitic capacitance is maintained low

USING SYSTEM EXECUTION EXECTION TRACES TO ANALYZE PERFORMANCE PROPERTIES OF SOFTWARE SYSTEMS

poster abstractSystem execution traces (execution logs) are traditionally used to evalu-ate functional properties of a software system. Prior research, however, has shown the usefulness of system execution traces in evaluating software sys-tem performance properties. Due to the complexity and verboseness of a system execution trace, however, higher-level abstractions, e.g., dataflow models are required to support such evaluation. Our current research effort therefore has focused on extending this dataflow model based system per-formance analysis in two folds. In one aspect, we have considered adapting the dataflow model when the system execution trace does not contain prop-erties required to support performance analysis. In the other aspect, we have developed techniques to auto-generate the supporting dataflow model from a system execution trace. The second aspect is critical because it is hard to manually craft a dataflow model for large and complex software sys-tems, especially distributed software systems. The tool and technique we developed for adapting the dataflow model is called System Execution Trace Adaptation Framework (SETAF); whereas, the tool and technique for auto-generating the dataflow model from a system execution trace is called Dataflow Model Auto Constructor (DMAC). Our cur-rent results from applying SETAF to several open-source production software applications show that there are 3 main patterns for adapting system execu-tion traces to support performance analysis if they do not already have the required properties. Likewise, our current results from applying DMAC to the same software applications show that DMAC is able to auto-construct a data-flow model that covers up to 95% of the originating system execution trace. This work was sponsored in part by the Australian Defense Science and Technology Organi-zation (DSTO

Efficient Regeneration System for the Improvement of Kinnow mandarin (Citrus reticulata Blanco)

Kinnow mandarin (Citrus reticulata Blanco.) is a highly adaptable variety among citrus cultivars. An efficient system for in vitro regeneration by organogenesis starting from seed of (C. reticulata Blanco) was developed. Seeds were treated by Murashige and Skoog (MS) media supplemented with 2, 4-Dichlorophenoxyacetic acid (2, 4-D) to initiate callus induction. The best result (96%) were obtained when seeds were treated with MS basal media + 2,4-D (16.0) μM. The regeneration system tested allowed the attainment of highest shoots (90 %) with BA 13.0 μM. An average of 7.8 well-differentiated shoots per explant was obtained. Highest rooting (85%) was achieved in culture medium with 10.0 μM IBA. The well-developed plantlets were transferred to potting mixture. Of the rooted plant, 95% adapted well to soil conditions. Keywords: C. reticulata Blanco, In vitro, Callus induction, Shoot formation, Explant, Rooting. Abbreviations: μM = Micromolar, BA = Benzyl adenine, IBA = Indole-3-butyric acid, TSS = Total soluble solids, NAA

Highly selective and sensitive macrocycle-based dinuclear foldamer for fluorometric and colorimetric sensing of citrate in water.

The selective detection of citrate anions is essential for various biological functions in living systems. A quantitative assessment of citrate is required for the diagnosis of various diseases in the human body; however, it is extremely challenging to develop efficient fluorescence and color-detecting molecular probes for sensing citrate in water. Herein, we report a macrocycle-based dinuclear foldamer (1) assembled with eosin Y (EY) that has been studied for anion binding by fluorescence and colorimetric techniques in water at neutral pH. Results from the fluorescence titrations reveal that the 1·EY ensemble strongly binds citrate anions, showing remarkable selectivity over a wide range of inorganic and carboxylate anions. The addition of citrate anions to the 1·EY adduct led to a large fluorescence enhancement, displaying a detectable color change under both visible and UV light in water up to 2 μmol. The biocompatibility of 1·EY as an intracellular carrier in a biological system was evaluated on primary human foreskin fibroblast (HF) cells, showing an excellent cell viability. The strong binding properties of the ensemble allow it to be used as a highly sensitive, detective probe for biologically relevant citrate anions in various applications

The degree of polymerization and sulfation patterns in heparan sulfate are critical determinants of cytomegalovirus entry into host cells

Several enveloped viruses, including herpesviruses attach to host cells by initially interacting with cell surface heparan sulfate (HS) proteoglycans followed by specific coreceptor engagement which culminates in virus-host membrane fusion and virus entry. Interfering with HS-herpesvirus interactions has long been known to result in significant reduction in virus infectivity indicating that HS play important roles in initiating virus entry. In this study, we provide a series of evidence to prove that specific sulfations as well as the degree of polymerization (dp) of HS govern human cytomegalovirus (CMV) binding and infection. First, purified CMV extracellular virions preferentially bind to sulfated longer chain HS on a glycoarray compared to a variety of unsulfated glycosaminoglycans including unsulfated shorter chain HS. Second, the fraction of glycosaminoglycans (GAG) displaying higher dp and sulfation has a larger impact on CMV titers compared to other fractions. Third, cell lines deficient in specific glucosaminyl sulfotransferases produce significantly reduced CMV titers compared to wild-type cells and virus entry is compromised in these mutant cells. Finally, purified glycoprotein B shows strong binding to heparin, and desulfated heparin analogs compete poorly with heparin for gB binding. Taken together, these results highlight the significance of HS chain length and sulfation patterns in CMV attachment and infectivity

Chemopreventive effect of quince (Cydonia oblonga Mill.) fruit extract on hepatocellular carcinoma induced by diethylnitrosamine in rats

Introduction: Hepatocellular carcinoma (HCC) or primary liver cancer is one of the most prevalent and deadliest cancers, which has been increasing greatly worldwide. Diethylnitrosamine (DEN) is a well-known environmental toxin and potent hepatocarcinogenic dialkylnitrosoamine present in air, water, and in a number of foodstuffs. In the present study, we evaluated preventive effect of aqueous extract of quince (Cydonia oblonga Mill.) fruit (ACO) against DEN-induced hepatocellular carcinoma (HCC) in rats. Methods and Results: The model of hepatocellular carcinoma was induced by a single intraperitoneal injection of DEN (200 mg/kg) as an initiator that after two weeks followed by daily oral administration of 2-acetylaminofluorene (30 mg/kg) as a promoter for two weeks. Quince-treated rats were pretreated with ACO intragastrically at three different doses two weeks prior to DEN injection. The marked reduction of serum biomarkers of liver damage and cancer, including alfa-fetoprotein (AFP), gamma glutamyl transpeptidase (GGT), alanine transaminase (ALT), and aspartate transaminase (AST) were observed in ACO supplemented animals as compared with HCC rats at the end of the experiment. Moreover, the quince extract exhibited in vivo antioxidant activity by elevating glutathione (GSH) contents as well as preventing lipid peroxidation in the liver tissues of DEN-treated rats. The relative weight of liver was also reduced in quince-treaded rats as a prognostic marker in HCC. Conclusions: Our results clearly demonstrated that quince has a chemopreventive effect against HCC in rats and can be proposed as a promising candidate for the prevention of DEN-induced hepatocarcinogenesis. &nbsp

BRAF inhibitors and radiotherapy for melanoma brain metastases: potential advantages and disadvantages of combination therapy

Melanoma is an aggressive malignancy that frequently spreads to the brain, resulting in rapid deterioration in both quality and quantity of life. Historically, treatment options for melanoma brain metastases (MBM) have predominantly consisted of surgery and radiotherapy. While these options can help provide local control, the majority of patients still develop intracranial progression. Indeed, novel therapeutic options, including molecularly targeted agents and immunotherapy, have improved outcomes and are now changing the role of radiotherapy. Up to 50% of melanomas contain an activating BRAF mutation, resulting in hyperactive cellular proliferation and survival. Drugs that target BRAF have been introduced for the treatment of metastatic melanoma and offer hope in improving disease outcomes; however, many of these trials either excluded or had a limited amount of patients with MBM. Recent studies have revealed that melanoma cell lines become more radiosensitive following BRAF inhibition, thus providing a potential synergistic mechanism when combining BRAF inhibitor (BRAFi) and radiotherapy. However, neurotoxicity concerns also exist with this combination. This article reviews the efficacy and limitations of BRAFi therapy for MBM, describes current evidence for combining BRAFis with radiation, discusses the rationale and evidence for combination modalities, and highlights emerging clinical trials specifically investigating this combination in MBM