Design and implementation of the embedded capacitance layers for decoupling of wireless sensor nodes

In this paper, the embedded capacitance material (ECM) is fabricated between the power and ground layers of the wireless sensor nodes, forming an integrated capacitance to replace the large amount of decoupling capacitors on the board. The ECM material, whose dielectric constant is 16, has the same size of the wireless sensor nodes of 3cm*3cm, with a thickness of only 14μm. Though the capacitance of a single ECM layer being only around 8nF, there are two reasons the ECM layers can still replace the high frequency decoupling capacitors (100nF in our case) on the board. The first reason is: the parasitic inductance of the ECM layer is much lower than the surface mount capacitors'. A smaller capacitance value of the ECM layer could achieve the same resonant frequency of the surface mount decoupling capacitors. Simulation and measurement fit this assumption well. The second reason is: more than one layer of ECM material are utilized during the design step to get a parallel connection of the several ECM capacitance layers, finally leading to a larger value of the capacitance and smaller value of parasitic. Characterization of the ECM is carried out by the LCR meter. To evaluate the behaviors of the ECM layer, time and frequency domain measurements are performed on the power-bus decoupling of the wireless sensor nodes. Comparison with the measurements of bare PCB board and decoupling capacitors solution are provided to show the improvement of the ECM layer. Measurements show that the implementation of the ECM layer can not only save the space of the surface mount decoupling capacitors, but also provide better power-bus decoupling to the nodes.

Resonant power conversion topologies for inductive charging of electrical vehicle batteries

This thesis is concerned with inductive charging of electric vehicle batteries. Rectified power form the 50/60 Hz utility feeds a dc-ac converter which delivers high-frequency ac power to the electric vehicle inductive coupling inlet. The inlet configuration has been defined by the Society of Automotive Engineers in Recommended Practice J-1773. This thesis studies converter topologies related to the series resonant converter. When coupled to the vehicle inlet, the frequency-controlled series-resonant converter results in a capacitively-filtered series-parallel LCLC (SP-LCLC) resonant converter topology with zero voltage switching and many other desirable features. A novel time-domain transformation analysis, termed Modal Analysis, is developed, using a state variable transformation, to analyze and characterize this multi-resonant fourth-orderconverter. Next, Fundamental Mode Approximation (FMA) Analysis, based on a voltage-source model of the load, and its novel extension, Rectifier-Compensated FMA (RCFMA) Analysis, are developed and applied to the SP-LCLC converter. The RCFMA Analysis is a simpler and more intuitive analysis than the Modal Analysis, and provides a relatively accurate closed-form solution for the converter behavior. Phase control of the SP-LCLC converter is investigated as a control option. FMA and RCFMA Analyses are used for detailed characterization. The analyses identify areas of operation, which are also validated experimentally, where it is advantageous to phase control the converter. A novel hybrid control scheme is proposed which integrates frequency and phase control and achieves reduced operating frequency range and improved partial-load efficiency. The phase-controlled SP-LCLC converter can also be configured with a parallel load and is an excellent option for the application. The resulting topology implements soft-switching over the entire load range and has high full-load and partial-load efficiencies. RCFMA Analysis is used to analyze and characterize the new converter topology, and good correlation is shown with experimental results. Finally, a novel single-stage power-factor-corrected ac-dc converter is introduced, which uses the current-source characteristic of the SP-LCLC topology to provide power factor correction over a wide output power range from zero to full load. This converter exhibits all the advantageous characteristics of its dc-dc counterpart, with a reduced parts count and cost. Simulation and experimental results verify the operation of the new converter.

Towards a situation-awareness-driven design of operational business intelligence & analytics systems

With the swamping and timeliness of data in the organizational context, the decision maker’s choice of an appropriate decision alternative in a given situation is defied. In particular, operational actors are facing the challenge to meet business-critical decisions in a short time and at high frequency. The construct of Situation Awareness (SA) has been established in cognitive psychology as a valid basis for understanding the behavior and decision making of human beings in complex and dynamic systems. SA gives decision makers the possibility to make informed, time-critical decisions and thereby improve the performance of the respective business process. This research paper leverages SA as starting point for a design science project for Operational Business Intelligence and Analytics systems and suggests a first version of design principles.

A randomised phase II study of two different schedules of pegylated liposomal doxorubicin in metastatic breast cancer (EORTC-10993).

One hundred and sixteen women with measurable metastatic breast cancer participated in a randomised phase II study of single agent liposomal pegylated doxorubicin (Caelyx) given either as a 60 mg/m2 every 6 weeks (ARM A) or 50 mg/m2 every 4 weeks (ARM B) schedule. Patients were over 65 years of age or, if younger, had refused or been unsuitable for standard anthracyclines. The aims of the study were to evaluate toxicity and dose delivery with the two schedules and obtain further information on the response rate of liposomal pegylated doxorubicin as a single agent in anthracycline nai ve advanced breast cancer. Twenty-six patients had received prior adjuvant chemotherapy (including an anthracycline in 10). Sixteen had received non-anthracycline-based first-line chemotherapy for advanced disease. One hundred and eleven patients were evaluable for toxicity and 106 for response. The delivered dose intensity (DI) was 9.8 mg/m2 (95% CI, 7.2-10.4) with 37 (69%) achieving a DI of >90% on ARM A and 11.9 mg/m2 (95% CI, 7.5-12.8) with 37 (65%) achieving a DI of >90% on ARM B. The adverse event profiles of the two schedules were distinctly different. Mucositis was more common with the every 6 weeks regimen (35% CTC grade 3/4 in ARM A, 14% in ARM B) but palmar plantar erythrodysesthesia (PPE) was more frequent with the every 4 weeks regimen (2% CTC grade 3/4 in ARM A, 16% in ARM B). Confirmed objective partial responses by RECIST criteria were seen with both schedules; 15/51 (29%) on ARM A and 17/56 (31%) on ARM B. Liposomal pegylated doxorubicin showed significant activity in advanced breast cancer with a generally favourable side-effect profile. The high frequency of stomatitis seen with 6 weekly treatment makes this the less preferred of the two schedules tested.

Molecular basis of complete C4 deficiency. A study of three patients.

The highly polymorphic fourth component of human complement (C4) is usually encoded by two genes, C4A and C4B, adjacent to the 21-hydroxylase (21-OH) genes and is also remarkable by the high frequency of the null alleles, C4A*Q0 and C4B*Q0. Complete C4 deficiency is exceptional because this condition appears only in homozygotes for the very rare double-null haplotype C4AQ0,BQ0. This condition in most cases gives rise to systemic lupus erythematosus and an increased susceptibility to infections. The molecular basis for complete C4 deficiency has not yet been established. Therefore we studied the DNA of three previously described C4 deficient patients belonging to unrelated families by restriction fragment length polymorphism analysis using C4 and 21-OH probes. These studies revealed a deletion of the C4B and 21-OHA genes in two patients and no deletion at all in the third patient. Therefore, complete C4 deficiency as a result of homozygosity for the C4AQ0, BQ0 haplotype is not a consequence of a deletion of the C4 genes. The molecular basis of this genetic abnormality is certainly very complex and may vary also from one case to another.

Estimating stochastic volatility diffusion using conditional moments of integrated volatility

We exploit the distributional information contained in high-frequency intraday data in constructing a simple conditional moment estimator for stochastic volatility diffusions. The estimator is based on the analytical solutions of the first two conditional moments for the latent integrated volatility, the realization of which is effectively approximated by the sum of the squared high-frequency increments of the process. Our simulation evidence indicates that the resulting GMM estimator is highly reliable and accurate. Our empirical implementation based on high-frequency five-minute foreign exchange returns suggests the presence of multiple latent stochastic volatility factors and possible jumps. © 2002 Elsevier Science B.V. All rights reserved.

Time-dependent transport through molecular junctions.

We investigate transport properties of molecular junctions under two types of bias--a short time pulse or an ac bias--by combining a solution for Green's functions in the time domain with electronic structure information coming from ab initio density functional calculations. We find that the short time response depends on lead structure, bias voltage, and barrier heights both at the molecule-lead contacts and within molecules. Under a low frequency ac bias, the electron flow either tracks or leads the bias signal (resistive or capacitive response) depending on whether the junction is perfectly conducting or not. For high frequency, the current lags the bias signal due to the kinetic inductance. The transition frequency is an intrinsic property of the junctions.

Modulating unimolecular charge transfer by exciting bridge vibrations.

Ultrafast UV-vibrational spectroscopy was used to investigate how vibrational excitation of the bridge changes photoinduced electron transfer between donor (dimethylaniline) and acceptor (anthracene) moieties bridged by a guanosine-cytidine base pair (GC). The charge-separated (CS) state yield is found to be lowered by high-frequency bridge mode excitation. The effect is linked to a dynamic modulation of the donor-acceptor coupling interaction by weakening of H-bonding and/or by disruption of the bridging base-pair planarity.

Standardizing clinical trials workflow representation in UML for international site comparison.

BACKGROUND: With the globalization of clinical trials, a growing emphasis has been placed on the standardization of the workflow in order to ensure the reproducibility and reliability of the overall trial. Despite the importance of workflow evaluation, to our knowledge no previous studies have attempted to adapt existing modeling languages to standardize the representation of clinical trials. Unified Modeling Language (UML) is a computational language that can be used to model operational workflow, and a UML profile can be developed to standardize UML models within a given domain. This paper's objective is to develop a UML profile to extend the UML Activity Diagram schema into the clinical trials domain, defining a standard representation for clinical trial workflow diagrams in UML. METHODS: Two Brazilian clinical trial sites in rheumatology and oncology were examined to model their workflow and collect time-motion data. UML modeling was conducted in Eclipse, and a UML profile was developed to incorporate information used in discrete event simulation software. RESULTS: Ethnographic observation revealed bottlenecks in workflow: these included tasks requiring full commitment of CRCs, transferring notes from paper to computers, deviations from standard operating procedures, and conflicts between different IT systems. Time-motion analysis revealed that nurses' activities took up the most time in the workflow and contained a high frequency of shorter duration activities. Administrative assistants performed more activities near the beginning and end of the workflow. Overall, clinical trial tasks had a greater frequency than clinic routines or other general activities. CONCLUSIONS: This paper describes a method for modeling clinical trial workflow in UML and standardizing these workflow diagrams through a UML profile. In the increasingly global environment of clinical trials, the standardization of workflow modeling is a necessary precursor to conducting a comparative analysis of international clinical trials workflows.

Use of 16S ribosomal RNA gene analyses to characterize the bacterial signature associated with poor oral health in West Virginia.

BACKGROUND: West Virginia has the worst oral health in the United States, but the reasons for this are unclear. This pilot study explored the etiology of this disparity using culture-independent analyses to identify bacterial species associated with oral disease. METHODS: Bacteria in subgingival plaque samples from twelve participants in two independent West Virginia dental-related studies were characterized using 16S rRNA gene sequencing and Human Oral Microbe Identification Microarray (HOMIM) analysis. Unifrac analysis was used to characterize phylogenetic differences between bacterial communities obtained from plaque of participants with low or high oral disease, which was further evaluated using clustering and Principal Coordinate Analysis. RESULTS: Statistically different bacterial signatures (P<0.001) were identified in subgingival plaque of individuals with low or high oral disease in West Virginia based on 16S rRNA gene sequencing. Low disease contained a high frequency of Veillonella and Streptococcus, with a moderate number of Capnocytophaga. High disease exhibited substantially increased bacterial diversity and included a large proportion of Clostridiales cluster bacteria (Selenomonas, Eubacterium, Dialister). Phylogenetic trees constructed using 16S rRNA gene sequencing revealed that Clostridiales were repeated colonizers in plaque associated with high oral disease, providing evidence that the oral environment is somehow influencing the bacterial signature linked to disease. CONCLUSIONS: Culture-independent analyses identified an atypical bacterial signature associated with high oral disease in West Virginians and provided evidence that the oral environment influenced this signature. Both findings provide insight into the etiology of the oral disparity in West Virginia.

Mapping the semantic structure of cognitive neuroscience.

Cognitive neuroscience, as a discipline, links the biological systems studied by neuroscience to the processing constructs studied by psychology. By mapping these relations throughout the literature of cognitive neuroscience, we visualize the semantic structure of the discipline and point to directions for future research that will advance its integrative goal. For this purpose, network text analyses were applied to an exhaustive corpus of abstracts collected from five major journals over a 30-month period, including every study that used fMRI to investigate psychological processes. From this, we generate network maps that illustrate the relationships among psychological and anatomical terms, along with centrality statistics that guide inferences about network structure. Three terms--prefrontal cortex, amygdala, and anterior cingulate cortex--dominate the network structure with their high frequency in the literature and the density of their connections with other neuroanatomical terms. From network statistics, we identify terms that are understudied compared with their importance in the network (e.g., insula and thalamus), are underspecified in the language of the discipline (e.g., terms associated with executive function), or are imperfectly integrated with other concepts (e.g., subdisciplines like decision neuroscience that are disconnected from the main network). Taking these results as the basis for prescriptive recommendations, we conclude that semantic analyses provide useful guidance for cognitive neuroscience as a discipline, both by illustrating systematic biases in the conduct and presentation of research and by identifying directions that may be most productive for future research.

Dramatic variability of the carbonate system at a temperate coastal ocean site (Beaufort, North Carolina, USA) is regulated by physical and biogeochemical processes on multiple timescales.

Increasing atmospheric carbon dioxide (CO2) from anthropogenic sources is acidifying marine environments resulting in potentially dramatic consequences for the physical, chemical and biological functioning of these ecosystems. If current trends continue, mean ocean pH is expected to decrease by ~0.2 units over the next ~50 years. Yet, there is also substantial temporal variability in pH and other carbon system parameters in the ocean resulting in regions that already experience change that exceeds long-term projected trends in pH. This points to short-term dynamics as an important layer of complexity on top of long-term trends. Thus, in order to predict future climate change impacts, there is a critical need to characterize the natural range and dynamics of the marine carbonate system and the mechanisms responsible for observed variability. Here, we present pH and dissolved inorganic carbon (DIC) at time intervals spanning 1 hour to >1 year from a dynamic, coastal, temperate marine system (Beaufort Inlet, Beaufort NC USA) to characterize the carbonate system at multiple time scales. Daily and seasonal variation of the carbonate system is largely driven by temperature, alkalinity and the balance between primary production and respiration, but high frequency change (hours to days) is further influenced by water mass movement (e.g. tides) and stochastic events (e.g. storms). Both annual (~0.3 units) and diurnal (~0.1 units) variability in coastal ocean acidity are similar in magnitude to 50 year projections of ocean acidity associated with increasing atmospheric CO2. The environmental variables driving these changes highlight the importance of characterizing the complete carbonate system rather than just pH. Short-term dynamics of ocean carbon parameters may already exert significant pressure on some coastal marine ecosystems with implications for ecology, biogeochemistry and evolution and this shorter term variability layers additive effects and complexity, including extreme values, on top of long-term trends in ocean acidification.

The island-scale internal wave climate of Moorea, French Polynesia

Analysis of five-year records of temperatures and currents collected at Moorea reveal strong internal wave activity at predominantly semi-diurnal frequencies impacting reef slopes at depths 30m around the entire island. Temperature changes of 1.5C to 3C are accompanied by surges of upward and onshore flow and vertical shear in onshore currents. Superimposed on annual temperature changes of approximately 3C, internal wave activity is high from Oct-May and markedly lower from Jun-Sep. The offshore pycnocline is broadly distributed with continuous stratification to at least 500m depth, and a subsurface fluorescence maximum above the strong nutricline at approximately 200m. Minimum buoyancy periods range from 4.8 to 6min, with the maximum density gradient occurring at 50 to 60m depth in summer and deepening to approximately 150 to 200m in winter. The bottom slope angle around all of Moorea is super-critical relative to the vertical stratification angle suggesting that energy propagating into shallow water is only a portion of total incident internal wave energy. Vertical gradient Richardson numbers indicate dominance by density stability relative to current shear with relatively limited diapycnal mixing. Coherence and lagged cross-correlation of semi-diurnal temperature variation indicate complex patterns of inter-site arrival of internal waves and no clear coherence or lagged correlation relationships among island sides. Semi-diurnal and high frequency internal wave packets likely arrive on Moorea from a combination of local and distant sources and may have important impacts for nutrient and particle fluxes in deep reef environments. © 2012 American Geophysical Union. All Rights Reserved.

Droplet generation with modulated AC electromagnetic field at nozzle exit

A method of droplet generation based on applying a modulated AC high frequency magnetic field in the localized region of capillary breakup is considered as ans alternative to traditional methods for high temperature liquid melt droplet serial production by pressure variation. The method is based on a pseudo-spectral approximation with a coordinate transformation adaptin to the developing free surface. The electromagnetic field is recomputed continuously with the domain shape change. Practical application cases for liquid silicon droplets of 0.5 - 2 mm diameter are considered in detail.

Identifying the damage mechanisms in paper using the acoustic emission monitoring technique

This paper investigates the use of the acoustic emission (AE) monitoring technique for use in identifying the damage mechanisms present in paper associated with its production process. The microscopic structure of paper consists of a random mesh of paper fibres connected by hydrogen bonds. This implies the existence of two damage mechanisms, the failure of a fibre-fibre bond and the failure of a fibre. This paper describes a hybrid mathematical model which couples the mechanics of the mass-spring model to the acoustic wave propagation model for use in generating the acoustic signal emitted by complex structures of paper fibres under strain. The derivation of the mass-spring model can be found in [1,2], with details of the acoustic wave equation found in [3,4]. The numerical implementation of the vibro-acoustic model is discussed in detail with particular emphasis on the damping present in the numerical model. The hybrid model uses an implicit solver which intrinsically introduces artificial damping to the solution. The artificial damping is shown to affect the frequency response of the mass-spring model, therefore certain restrictions on the simulation time step must be enforced so that the model produces physically accurate results. The hybrid mathematical model is used to simulate small fibre networks to provide information on the acoustic response of each damage mechanism. The simulated AEs are then analysed using a continuous wavelet transform (CWT), described in [5], which provides a two dimensional time-frequency representation of the signal. The AEs from the two damage mechanisms show different characteristics in the CWT so that it is possible to define a fibre-fibre bond failure by the criteria listed below. The dominant frequency components of the AE must be at approximately 250 kHz or 750 kHz. The strongest frequency component may be at either approximately 250 kHz or 750 kHz. The duration of the frequency component at approximately 250 kHz is longer than that of the frequency component at approximately 750 kHz. Similarly, the criteria for identifying a fibre failure are given below. The dominant frequency component of the AE must be greater than 800 kHz. The duration of the dominant frequency component must be less than 5.00E-06 seconds. The dominant frequency component must be present at the front of the AE. Essentially, the failure of a fibre-fibre bond produces a low frequency wave and the failure of a fibre produces a high frequency pulse. Using this theoretical criteria, it is now possible to train an intelligent classifier such as the Self-Organising Map (SOM) [6] using the experimental data. First certain features must be extracted from the CWTs of the AEs for use in training the SOM. For this work, each CWT is divided into 200 windows of 5E-06s in duration covering a 100 kHz frequency range. The power ratio for each windows is then calculated and used as a feature. Having extracted the features from the AEs, the SOM can now be trained, but care is required so that the both damage mechanisms are adequately represented in the training set. This is an issue with paper as the failure of the fibre-fibre bonds is the prevalent damage mechanism. Once a suitable training set is found, the SOM can be trained and its performance analysed. For the SOM described in this work, there is a good chance that it will correctly classify the experimental AEs.