Design and Applications of a Decade-Spanning Terahertz Frequency Comb Spectrometer: Doppler-limited Rotational Spectroscopy of Methanol and Methanol-OD

This thesis details the design and applications of a terahertz (THz) frequency comb spectrometer. The spectrometer employs two offset locked Ti:Sapphire femtosecond oscillators with repetition rates of approximately 80 MHz, offset locked at 100 Hz to continuously sample a time delay of 12.5 ns at a maximum time delay resolution of 15.6 fs. These oscillators emit continuous pulse trains, allowing the generation of a THz pulse train by the master, or pump, oscillator and the sampling of this THz pulse train by the slave, or probe, oscillator via the electro-optic effect. Collecting a train of 16 consecutive THz pulses and taking the Fourier transform of this pulse train produces a decade-spanning frequency comb, from 0.25 to 2.5 THz, with a comb tooth width of 5 MHz and a comb tooth spacing of ~80 MHz. This frequency comb is suitable for Doppler-limited rotational spectroscopy of small molecules. Here, the data from 68 individual scans at slightly different pump oscillator repetition rates were combined, producing an interleaved THz frequency comb spectrum, with a maximum interval between comb teeth of 1.4 MHz, enabling THz frequency comb spectroscopy.

The accuracy of the THz frequency comb spectrometer was tested, achieving a root mean square error of 92 kHz measuring selected absorption center frequencies of water vapor at 10 mTorr, and a root mean square error of 150 kHz in measurements of a K-stack of acetonitrile. This accuracy is sufficient for fitting of measured transitions to a model Hamiltonian to generate a predicted spectrum for molecules of interest in the fields of astronomy and physical chemistry. As such, the rotational spectra of methanol and methanol-OD were acquired by the spectrometer. Absorptions from 1.3 THz to 2.0 THz were compared to JPL catalog data for methanol and the spectrometer achieved an RMS error of 402 kHz, improving to 303 kHz when excluding low signal-to-noise absorptions. This level of accuracy compares favorably with the ~100 kHz accuracy achieved by JPL frequency multiplier submillimeter spectrometers. Additionally, the relative intensity performance of the THz frequency comb spectrometer is linear across the entire decade-spanning bandwidth, making it the preferred instrument for recovering lineshapes and taking absolute intensity measurements in the THz region. The data acquired by the Terahertz Frequency Comb Spectrometer for methanol-OD is of comparable accuracy to the methanol data and may be used to refine the fit parameters for the predicted spectrum of methanol-OD.

Feeding level and frequency for freshwater angelfish

The objective of this study was to determine the optimal feeding level and feeding frequency for the culture of freshwater angelfish (Pterophyllum scalare). A randomized block design in a factorial scheme (3 × 2) with three feeding levels (30, 60 and 90 g/kg of body weight (BW)/day) and two feeding frequencies (1x and 2x/day) was set up in duplicate, representing 24 experimental units. Data were analyzed using two-way ANOVA and the Tukey test for comparison between means. After 84 days, results indicated that both factors influenced fish performance. No interaction between these factors was, however, observed. Increased feeding level and feeding frequency resulted in increased feed intake. The feed conversion ratio was negatively affected by feeding level, but not affected by feeding frequency. Final weights were higher when fish were fed twice daily, at levels of 60 or 90 g/kg BW/day. Specific growth rate was higher when fish received 60 or 90 g/kg BW/day, regardless of the feeding frequency. Survival was not affected by any treatment, with mean survival rates higher than 90%. It is recommended that juveniles be fed at a level of 60 g/kg BW/day with a minimum of two meals per day, to attain optimal survival, growth and feed efficiency.

Analysis of Sampling Data

A Similar Exposure Group (SEG) can be created through the evaluation of workers performing the same or similar task, hazards they are exposed to, frequency and duration of their exposures, engineering controls available during their operations, personal protective equipment used, and exposure data. For this report, the samples of one facility that has collected nearly 40,000 various types of samples will be evaluated to determine if the creation of a SEG can be supported. The data will be reviewed for consistency with collection methods and laboratory detection limits. A subset of the samples may be selected based on the review. Data will also be statistically evaluated in order to determine whether the data is sufficient to terminate the sampling. IHDataAnalyst V1.27 will be used to assess the data. This program uses Bayesian Analysis to assist in making determinations. The 95 percent confidence interval will be calculated and evaluated in making decisions. This evaluation will be used to determine if a SEG can be created for any of the workers and determine the need for future sample collection. The data and evaluation presented in this report have been selected and evaluated specifically for the purposes of this project.

Through Wafer 3D Vertical Micro-Coaxial Probe for High Frequency Material Characterization and Millimeter Wave Packaging Systems

This work presents the development of an in-plane vertical micro-coaxial probe using bulk micromachining technique for high frequency material characterization. The coaxial probe was fabricated in a silicon substrate by standard photolithography and a deep reactive ion etching (DRIE) technique. The through-hole structure in the form of a coaxial probe was etched and metalized with a diluted silver paste. A co-planar waveguide configuration was integrated with the design to characterize the probe. The electrical and RF characteristics of the coaxial probe were determined by simulating the probe design in Ansoft’s High Frequency Structure Simulator (HFSS). The reflection coefficient and transducer gain performance of the probe was measured up to 65 GHz using a vector network analyzer (VNA). The probe demonstrated excellent results over a wide frequency band, indicating its ability to integrate with millimeter wave packaging systems as well as characterize unknown materials at high frequencies. The probe was then placed in contact with 3 materials where their unknown permittivities were determined. To accomplish this, the coaxial probe was placed in contact with the material under test and electromagnetic waves were directed to the surface using the VNA, where its reflection coefficient was then determined over a wide frequency band from dc-to -65GHz. Next, the permittivity of each material was deduced from its measured reflection coefficients using a cross ratio invariance coding technique. The permittivity results obtained when measuring the reflection coefficient data were compared to simulated permittivity results and agreed well. These results validate the use of the micro-coaxial probe to characterize the permittivity of unknown materials at high frequencies up to 65GHz.

Long-term Trends in Magnitude and Frequency of Extreme Rainfall Events in Florida

This study computed trends in extreme precipitation events of Florida for 1950-2010. Hourly aggregated rainfall data from 24 stations of the National Climatic Data Centre were analyzed to derive time-series of extreme rainfalls for 12 durations, ranging from 1 hour to 7 day. Non-parametric Mann-Kendall test and Theil-Sen Approach were applied to detect the significance of trends in annual maximum rainfalls, number of above threshold events and average magnitude of above threshold events for four common analysis periods. Trend Free Pre-Whitening (TFPW) approach was applied to remove the serial correlations and bootstrap resampling approach was used to detect the field significance of trends. The results for annual maximum rainfall revealed dominant increasing trends at the statistical significance level of 0.10, especially for hourly events in longer period and daily events in recent period. The number of above threshold events exhibited strong decreasing trends for hourly durations in all time periods.

Power spectrum model of visual masking: simulations and empirical data

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

Proposal to minimize the difficulty of recording abortion data in sheep

Background: The most frequent viral diseases which can cause abortion in sheep are Blue tongue, Border disease virus, Cache Valley fever and Schmallenberg virus. The diagnosis of abortion, namely virus-induced represents a challenge to field clinicians, since clinical signs presented by the dam are discrete, non-specific and variable (Agerhom et al., 2015). On the other hand, while some foetuses reveal characteristic and visible malformations, others do not reveal any lesions. In face of it, definitive diagnosis requires an appropriate history collection, as well as sending fresh samples, namely abortion material, foetus, placenta and umbilical cord, to a specialty laboratory, to obtain a precise diagnosis. Objectives: The authors suggest a registration method of all mandatory data, in order to further assist the diagnosis of viral diseases at the laboratories, including the most frequent congenital malformations reported in sheep abortions. Methods: Abortion samples of suspected viral origin were collected and all data were registered, in worktables optimized for this purpose. Results: The authors document, using macroscopic figures lesions of malformations in abortions, emphasizing the frequency and the importance of documenting each case, proposing practical and effective worktables to assist the fieldwork. Conclusions: Field clinician’s awareness of the importance of early detection of viral diseases causing abortion outbreaks stimulates a proper data collection for each case of abortion, in order to contribute to a precise diagnosis and posterior consistent epidemiological studies, which may allow diminishing of economic losses.

A NEW DC UPS FOR DC POWER DISTRIBUTION SYSTEM IN DATA CENTER

In recent years, the 380V DC and 48V DC distribution systems have been extensively studied for the latest data centers. It is widely believed that the 380V DC system is a very promising candidate because of its lower cable cost compared to the 48V DC system. However, previous studies have not adequately addressed the low reliability issue with the 380V DC systems due to large amount of series connected batteries. In this thesis, a quantitative comparison for the two systems has been presented in terms of efficiency, reliability and cost. A new multi-port DC UPS with both high voltage output and low voltage output is proposed. When utility ac is available, it delivers power to the load through its high voltage output and charges the battery through its low voltage output. When utility ac is off, it boosts the low battery voltage and delivers power to the load form the battery. Thus, the advantages of both systems are combined and the disadvantages of them are avoided. High efficiency is also achieved as only one converter is working in either situation. Details about the design and analysis of the new UPS are presented. For the main AC-DC part of the new UPS, a novel bridgeless three-level single-stage AC-DC converter is proposed. It eliminates the auxiliary circuit for balancing the capacitor voltages and the two bridge rectifier diodes in previous topology. Zero voltage switching, high power factor, and low component stresses are achieved with this topology. Compared to previous topologies, the proposed converter has a lower cost, higher reliability, and higher efficiency. The steady state operation of the converter is analyzed and a decoupled model is proposed for the converter. For the battery side converter as a part of the new UPS, a ZVS bidirectional DC-DC converter based on self-sustained oscillation control is proposed. Frequency control is used to ensure the ZVS operation of all four switches and phase shift control is employed to regulate the converter output power. Detailed analysis of the steady state operation and design of the converter are presented. Theoretical, simulation, and experimental results are presented to verify the effectiveness of the proposed concepts.

The conjugate gradient partitioned block frequency-domain for multichannel adaptive filtering

The conjugate gradient is the most popular optimization method for solving large systems of linear equations. In a system identification problem, for example, where very large impulse response is involved, it is necessary to apply a particular strategy which diminishes the delay, while improving the convergence time. In this paper we propose a new scheme which combines frequency-domain adaptive filtering with a conjugate gradient technique in order to solve a high order multichannel adaptive filter, while being delayless and guaranteeing a very short convergence time.

Iowa's Barriers to Prenatal Care Project: 2-14 Data Summary, July 2015

The findings in this summary are based on the Iowa Barriers to Prenatal Care project. Ongoing since 1991, the purpose of this project is to obtain brief, accurate information about women delivering babies in Iowa hospitals. Specifically, the project seeks to learn about women’s experiences getting prenatal or delivery care during their current pregnancy. Other information is included which may be pertinent to health planners or those concerned with the systematic development of health care services. This project is a cooperative venture of all of Iowa’s maternity hospitals, the University of Northern Iowa Center for Social and Behavioral Research, and the Iowa Department of Public Health. The Robert Wood Johnson Foundation funded the first three years of this project. The current funding is provided by the Iowa Department of Public Health. The Director is Dr. Mary Losch, University of Northern Iowa Center for Social and Behavioral Research. The Coordinator for the project is Rodney Muilenburg. The questionnaire is distributed to nearly ninety maternity hospitals across the state of Iowa. Nursing staff or those responsible for obtaining birth certificate information in the obstetrics unit are responsible for approaching all birth mothers prior to dismissal and requesting their participation in the study. The questionnaire takes approximately ten minutes to complete. Completed questionnaires are returned to the University of Northern Iowa Center for Social and Behavioral Research for data entry and analysis. Returns are made monthly, weekly, or biweekly depending on the number of births per week in a given hospital. Except in the case of a mother who is too ill to complete the questionnaire, all mothers are eligible to be recruited for participation. The present yearly report includes an analysis of large Iowa cities, African American mothers, and a trend analysis of the last ten years. Also presented in this report is a frequency analysis of all variables included in the 2012 questionnaire. Unless otherwise noted, all entries reflect percentages. Please note that because percentages were rounded, total values may not equal 100%. Data presented are based upon 2012 questionnaires received to date (n = 23,674). All analyses reflect unweighted percentages of those responding.

Interpretable Convolutional Neural Networks for Decoding and Analyzing Neural Time Series Data

Machine learning is widely adopted to decode multi-variate neural time series, including electroencephalographic (EEG) and single-cell recordings. Recent solutions based on deep learning (DL) outperformed traditional decoders by automatically extracting relevant discriminative features from raw or minimally pre-processed signals. Convolutional Neural Networks (CNNs) have been successfully applied to EEG and are the most common DL-based EEG decoders in the state-of-the-art (SOA). However, the current research is affected by some limitations. SOA CNNs for EEG decoding usually exploit deep and heavy structures with the risk of overfitting small datasets, and architectures are often defined empirically. Furthermore, CNNs are mainly validated by designing within-subject decoders. Crucially, the automatically learned features mainly remain unexplored; conversely, interpreting these features may be of great value to use decoders also as analysis tools, highlighting neural signatures underlying the different decoded brain or behavioral states in a data-driven way. Lastly, SOA DL-based algorithms used to decode single-cell recordings rely on more complex, slower to train and less interpretable networks than CNNs, and the use of CNNs with these signals has not been investigated. This PhD research addresses the previous limitations, with reference to P300 and motor decoding from EEG, and motor decoding from single-neuron activity. CNNs were designed light, compact, and interpretable. Moreover, multiple training strategies were adopted, including transfer learning, which could reduce training times promoting the application of CNNs in practice. Furthermore, CNN-based EEG analyses were proposed to study neural features in the spatial, temporal and frequency domains, and proved to better highlight and enhance relevant neural features related to P300 and motor states than canonical EEG analyses. Remarkably, these analyses could be used, in perspective, to design novel EEG biomarkers for neurological or neurodevelopmental disorders. Lastly, CNNs were developed to decode single-neuron activity, providing a better compromise between performance and model complexity.

Radio frequency communication and fault detection for railway signalling

The continuous and swift progression of both wireless and wired communication technologies in today's world owes its success to the foundational systems established earlier. These systems serve as the building blocks that enable the enhancement of services to cater to evolving requirements. Studying the vulnerabilities of previously designed systems and their current usage leads to the development of new communication technologies replacing the old ones such as GSM-R in the railway field. The current industrial research has a specific focus on finding an appropriate telecommunication solution for railway communications that will replace the GSM-R standard which will be switched off in the next years. Various standardization organizations are currently exploring and designing a radiofrequency technology based standard solution to serve railway communications in the form of FRMCS (Future Railway Mobile Communication System) to substitute the current GSM-R. Bearing on this topic, the primary strategic objective of the research is to assess the feasibility to leverage on the current public network technologies such as LTE to cater to mission and safety critical communication for low density lines. The research aims to identify the constraints, define a service level agreement with telecom operators, and establish the necessary implementations to make the system as reliable as possible over an open and public network, while considering safety and cybersecurity aspects. The LTE infrastructure would be utilized to transmit the vital data for the communication of a railway system and to gather and transmit all the field measurements to the control room for maintenance purposes. Given the significance of maintenance activities in the railway sector, the ongoing research includes the implementation of a machine learning algorithm to detect railway equipment faults, reducing time and human analysis errors due to the large volume of measurements from the field.

Data analysis and hydrological modelling of rainfall and discharge extremes along the Tione River: implications for the design of water structures

There are many natural events that can negatively affect the urban ecosystem, but weather-climate variations are certainly among the most significant. The history of settlements has been characterized by extreme events like earthquakes and floods, which repeat themselves at different times, causing extensive damage to the built heritage on a structural and urban scale. Changes in climate also alter various climatic subsystems, changing rainfall regimes and hydrological cycles, increasing the frequency and intensity of extreme precipitation events (heavy rainfall).  From an hydrological risk perspective, it is crucial to understand future events that could occur and their magnitude in order to design safer infrastructures. Unfortunately, it is not easy to understand future scenarios as the complexity of climate is enormous.  For this thesis, precipitation and discharge extremes were primarily used as data sources. It is important to underline that the two data sets are not separated: changes in rainfall regime, due to climate change, could significantly affect overflows into receiving water bodies. It is imperative that we understand and model climate change effects on water structures to support the development of adaptation strategies.   The main purpose of this thesis is to search for suitable water structures for a road located along the Tione River. Therefore, through the analysis of the area from a hydrological point of view, we aim to guarantee the safety of the infrastructure over time.   The observations made have the purpose to underline how models such as a stochastic one can improve the quality of an analysis for design purposes, and influence choices.

Delays In Receiving Obstetric Care And Poor Maternal Outcomes: Results From A National Multicentre Cross-sectional Study.

The vast majority of maternal deaths in low-and middle-income countries are preventable. Delay in obtaining access to appropriate health care is a fairly common problem which can be improved. The objective of this study was to explore the association between delay in providing obstetric health care and severe maternal morbidity/death. This was a multicentre cross-sectional study, involving 27 referral obstetric facilities in all Brazilian regions between 2009 and 2010. All women admitted to the hospital with a pregnancy-related cause were screened, searching for potentially life-threatening conditions (PLTC), maternal death (MD) and maternal near-miss (MNM) cases, according to the WHO criteria. Data on delays were collected by medical chart review and interview with the medical staff. The prevalence of the three different types of delays was estimated according to the level of care and outcome of the complication. For factors associated with any delay, the PR and 95%CI controlled for cluster design were estimated. A total of 82,144 live births were screened, with 9,555 PLTC, MNM or MD cases prospectively identified. Overall, any type of delay was observed in 53.8% of cases; delay related to user factors was observed in 10.2%, 34.6% of delays were related to health service accessibility and 25.7% were related to quality of medical care. The occurrence of any delay was associated with increasing severity of maternal outcome: 52% in PLTC, 68.4% in MNM and 84.1% in MD. Although this was not a population-based study and the results could not be generalized, there was a very clear and significant association between frequency of delay and severity of outcome, suggesting that timely and proper management are related to survival.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.