Development of calix[4]arene-functionalized microcantilever array sensing system for the rapid, sensitive and simultaneous detection of metal ions in aqueous solutions

The work described in this thesis was conducted with the aim of: 1) investigating the binding capabilities of calix[4]arene-functionalized microcantilevers towards specific metal ions and 2) developing a new16-microcantilever array sensing system for the rapid, and simultaneous detection of metal ions in fresh water. Part I of this thesis reports on the use of three new bimodal calix[4]arenes (methoxy, ethoxy and crown) as potential host/guest sensing layers for detecting selected ions in dilute aqueous solutions using single microcantilever experimental system. In this work it was shown that modifying the upper rim of the calix[4]arenes with a thioacetate end group allow calix[4]arenes to self-assemble on Au(111) forming complete highly ordered monolayers. It was also found that incubating the microcantilevers coated with 5 nm of Inconel and 40 nm of Au for 1 h in a 1.0 M solution of calix[4]arene produced the highest sensitivity. Methoxy-functionalized microcantilevers showed a definite preference for Ca²⁺ ions over other cationic guests and were able to detect trace concentration as low as 10⁻¹² M in aqueous solutions. Microcantilevers modified with ethoxy calix[4]arene displayed their highest sensitivity towards Sr²⁺ and to a lesser extent Ca²⁺ ions. Crown calix[4]arene-modified microcantilevers were however found to bind selectively towards Cs⁺ ions. In addition, the counter anion was also found to contribute to the deflection. For example methoxy calix[4]arene-modified microcantilever was found to be more sensitive to CaCl₂ over other water-soluble calcium salts such as Ca(NO₃)₂ , CaBr₂ and CaI₂. These findings suggest that the response of calix[4]arene-modified microcantilevers should be attributed to the target ionic species as a whole instead of only considering the specific cation and/or anion. Part II presents the development of a 16-microcantilever sensor setup. The implementation of this system involved the creation of data analysis software that incorporates data from the motorized actuator and a two-axis photosensitive detector to obtain the deflection signal originating from each individual microcantilever in the array. The system was shown to be capable of simultaneous measurements of multiple microcantilevers with different coatings. A functionalization unit was also developed that allows four microcantilevers in the array to be coated with an individual sensing layer one at the time. Because of the variability of the spring constants of different cantilevers within the array, results presented were quoted in units of surface stress unit in order to compare values between the microcantilevers in the array.

Tsunami simulation and detection using global navigation satellite system reflectometry

In this thesis, research for tsunami remote sensing using the Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler maps (DDMs) is presented. Firstly, a process for simulating GNSS-R DDMs of a tsunami-dominated sea sur- face is described. In this method, the bistatic scattering Zavorotny-Voronovich (Z-V) model, the sea surface mean square slope model of Cox and Munk, and the tsunami- induced wind perturbation model are employed. The feasibility of the Cox and Munk model under a tsunami scenario is examined by comparing the Cox and Munk model- based scattering coefficient with the Jason-1 measurement. A good consistency be- tween these two results is obtained with a correlation coefficient of 0.93. After con- firming the applicability of the Cox and Munk model for a tsunami-dominated sea, this work provides the simulations of the scattering coefficient distribution and the corresponding DDMs of a fixed region of interest before and during the tsunami. Fur- thermore, by subtracting the simulation results that are free of tsunami from those with presence of tsunami, the tsunami-induced variations in scattering coefficients and DDMs can be clearly observed. Secondly, a scheme to detect tsunamis and estimate tsunami parameters from such tsunami-dominant sea surface DDMs is developed. As a first step, a procedure to de- termine tsunami-induced sea surface height anomalies (SSHAs) from DDMs is demon- strated and a tsunami detection precept is proposed. Subsequently, the tsunami parameters (wave amplitude, direction and speed of propagation, wavelength, and the tsunami source location) are estimated based upon the detected tsunami-induced SSHAs. In application, the sea surface scattering coefficients are unambiguously re- trieved by employing the spatial integration approach (SIA) and the dual-antenna technique. Next, the effective wind speed distribution can be restored from the scat- tering coefficients. Assuming all DDMs are of a tsunami-dominated sea surface, the tsunami-induced SSHAs can be derived with the knowledge of background wind speed distribution. In addition, the SSHA distribution resulting from the tsunami-free DDM (which is supposed to be zero) is considered as an error map introduced during the overall retrieving stage and is utilized to mitigate such errors from influencing sub- sequent SSHA results. In particular, a tsunami detection procedure is conducted to judge the SSHAs to be truly tsunami-induced or not through a fitting process, which makes it possible to decrease the false alarm. After this step, tsunami parameter estimation is proceeded based upon the fitted results in the former tsunami detec- tion procedure. Moreover, an additional method is proposed for estimating tsunami propagation velocity and is believed to be more desirable in real-world scenarios. The above-mentioned tsunami-dominated sea surface DDM simulation, tsunami detection precept and parameter estimation have been tested with simulated data based on the 2004 Sumatra-Andaman tsunami event.

(Table 1) Ratio of hydroxy-GDGT vs. the total core GDGT was calculated based on the detection of hydroxy-GDGT

Hydroxylated glycerol dialkyl glycerol tetraethers (hydroxy-GDGTs) were detected in marine sediments of diverse depositional regimes and ages. Mass spectrometric evidence, complemented by information gleaned from two-dimensional (2D) 1H-13C nuclear magnetic resonance (NMR) spectroscopy on minute quantities of target analyte isolated from marine sediment, allowed us to identify one major compound as a monohydroxy-GDGT with acyclic biphytanyl moieties (OH-GDGT-0). NMR spectroscopic and mass spectrometric data indicate the presence of a tertiary hydroxyl group suggesting the compounds are the tetraether analogues of the widespread hydroxylated archaeol derivatives that have received great attention in geochemical studies of the last two decades. Three other related compounds were assigned as acyclic dihydroxy-GDGT (2OH-GDGT-0) and monohydroxy-GDGT with one (OH-GDGT-1) and two cyclopentane rings (OH-GDGT-2). Based on the identification of hydroxy-GDGT core lipids, a group of previously reported unknown intact polar lipids (IPLs), including the ubiquitously distributed H341-GDGT (Lipp J. S. and Hinrichs K. -U. (2009) Structural diversity and fate of intact polar lipids in marine sediments. Geochim. Cosmochim. Acta 73, 6816-6833), and its analogues were tentatively identified as glycosidic hydroxy-GDGTs. In addition to marine sediments, we also detected hydroxy-GDGTs in a culture of Methanothermococcus thermolithotrophicus. Given the previous finding of the putative polar precursor H341-GDGT in the planktonic marine crenarchaeon Nitrosopumilus maritimus, these compounds are synthesized by representatives of both cren- and euryarchaeota. The ubiquitous distribution and apparent substantial abundance of hydroxy-GDGT core lipids in marine sediments (up to 8% of total isoprenoid core GDGTs) point to their potential as proxies.

Psychometric functions for detection and discrimination with and without flankers.

Recent studies have reported that flanking stimuli broaden the psychometric function and lower detection thresholds. In the present study, we measured psychometric functions for detection and discrimination with and without flankers to investigate whether these effects occur throughout the contrast continuum. Our results confirm that lower detection thresholds with flankers are accompanied by broader psychometric functions. Psychometric functions for discrimination reveal that discrimination thresholds with and without flankers are similar across standard levels, and that the broadening of psychometric functions with flankers disappears as standard contrast increases, to the point that psychometric functions at high standard levels are virtually identical with or without flankers. Threshold-versus-contrast (TvC) curves with flankers only differ from TvC curves without flankers in occasional shallower dippers and lower branches on the left of the dipper, but they run virtually superimposed at high standard levels. We discuss differences between our results and other results in the literature, and how they are likely attributed to the differential vulnerability of alternative psychophysical procedures to the effects of presentation order. We show that different models of flanker facilitation can fit the data equally well, which stresses that succeeding at fitting a model does not validate it in any sense.

The transducer model for contrast detection and discrimination: formal relations, implications, and an empirical test.

The transducer function mu for contrast perception describes the nonlinear mapping of stimulus contrast onto an internal response. Under a signal detection theory approach, the transducer model of contrast perception states that the internal response elicited by a stimulus of contrast c is a random variable with mean mu(c). Using this approach, we derive the formal relations between the transducer function, the threshold-versus-contrast (TvC) function, and the psychometric functions for contrast detection and discrimination in 2AFC tasks. We show that the mathematical form of the TvC function is determined only by mu, and that the psychometric functions for detection and discrimination have a common mathematical form with common parameters emanating from, and only from, the transducer function mu and the form of the distribution of the internal responses. We discuss the theoretical and practical implications of these relations, which have bearings on the tenability of certain mathematical forms for the psychometric function and on the suitability of empirical approaches to model validation. We also present the results of a comprehensive test of these relations using two alternative forms of the transducer model: a three-parameter version that renders logistic psychometric functions and a five-parameter version using Foley's variant of the Naka-Rushton equation as transducer function. Our results support the validity of the formal relations implied by the general transducer model, and the two versions that were contrasted account for our data equally well.

First detection of the Sunyaev Zel'dovich effect increment at λ < 650 μm

The Sunyaev-Zel'dovich (SZ) effect is a spectral distortion of the cosmic microwave background as observed through the hot plasma in galaxy clusters. This distortion is a decrement in the CMB intensity for λ > 1.3 mm, an increment at shorter wavelengths, and small again by λ ~ 250 μm. As part of the Herschel Lensing Survey (HLS) we have mapped 1E0657–56 (the Bullet cluster) with SPIRE with bands centered at 250, 350 and 500 μm and have detected the SZ effect at the two longest wavelengths. The measured SZ effect increment central intensities are ΔI_0 = 0.097 ± 0.019 MJy sr^-1 at 350 μm and ΔI_0 = 0.268 ± 0.031 MJy sr^-1 at 500 μm, consistent with the SZ effect spectrum derived from previous measurements at 2 mm. No other diffuse emission is detected. The presence of the finite temperature SZ effect correction is preferred by the SPIRE data at a significance of 2.1σ, opening the possibility that the relativistic SZ effect correction can be constrained by SPIRE in a sample of clusters. The results presented here have important ramifications for both sub-mm measurements of galaxy clusters and blank field surveys with SPIRE.

Molecular diversity, cultivation, and improved detection by fluorescent in situ hybridization of a dominant group of human gut bacteria related to Roseburia spp. or Eubacterium rectale

Peer reviewed

Molecular diversity, cultivation, and improved detection by fluorescent in situ hybridization of a dominant group of human gut bacteria related to Roseburia spp. or Eubacterium rectale

Peer reviewed

The difference model with guessing explains interval bias in two-alternative forced- chocice detection procedures

The standard difference model of two-alternative forced-choice (2AFC) tasks implies that performance should be the same when the target is presented in the first or the second interval. Empirical data often show “interval bias” in that percentage correct differs significantly when the signal is presented in the first or the second interval. We present an extension of the standard difference model that accounts for interval bias by incorporating an indifference zone around the null value of the decision variable. Analytical predictions are derived which reveal how interval bias may occur when data generated by the guessing model are analyzed as prescribed by the standard difference model. Parameter estimation methods and goodness-of-fit testing approaches for the guessing model are also developed and presented. A simulation study is included whose results show that the parameters of the guessing model can be estimated accurately. Finally, the guessing model is tested empirically in a 2AFC detection procedure in which guesses were explicitly recorded. The results support the guessing model and indicate that interval bias is not observed when guesses are separated out.

Lack of effect of lowering LDL cholesterol on cancer: meta-analysis of individual data from 175,000 people in 27 randomised trials of statin therapy

Background: Statin therapy reduces the risk of occlusive vascular events, but uncertainty remains about potential effects on cancer. We sought to provide a detailed assessment of any effects on cancer of lowering LDL cholesterol (LDL-C) with a statin using individual patient records from 175,000 patients in 27 large-scale statin trials. Methods and Findings: Individual records of 134,537 participants in 22 randomised trials of statin versus control (median duration 4.8 years) and 39,612 participants in 5 trials of more intensive versus less intensive statin therapy (median duration 5.1 years) were obtained. Reducing LDL-C with a statin for about 5 years had no effect on newly diagnosed cancer or on death from such cancers in either the trials of statin versus control (cancer incidence: 3755 [1.4% per year [py]] versus 3738 [1.4% py], RR 1.00 [95% CI 0.96-1.05]; cancer mortality: 1365 [0.5% py] versus 1358 [0.5% py], RR 1.00 [95% CI 0.93-1.08]) or in the trials of more versus less statin (cancer incidence: 1466 [1.6% py] vs 1472 [1.6% py], RR 1.00 [95% CI 0.93-1.07]; cancer mortality: 447 [0.5% py] versus 481 [0.5% py], RR 0.93 [95% CI 0.82-1.06]). Moreover, there was no evidence of any effect of reducing LDL-C with statin therapy on cancer incidence or mortality at any of 23 individual categories of sites, with increasing years of treatment, for any individual statin, or in any given subgroup. In particular, among individuals with low baseline LDL-C (<2 mmol/L), there was no evidence that further LDL-C reduction (from about 1.7 to 1.3 mmol/L) increased cancer risk (381 [1.6% py] versus 408 [1.7% py]; RR 0.92 [99% CI 0.76-1.10]). Conclusions: In 27 randomised trials, a median of five years of statin therapy had no effect on the incidence of, or mortality from, any type of cancer (or the aggregate of all cancer).

Detection and Classification of Whale Acoustic Signals

This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification.

In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information.

In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data.

Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear.

We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale vocalization data set. The word error rate of the DCTNet feature is similar to the MFSC in speech recognition tasks, suggesting that the convolutional network is able to reveal acoustic content of speech signals.

Experimental detection of sudden stiffness change in a structural system employing Laser Doppler Vibrometry

Sudden changes in the stiffness of a structure are often indicators of structural damage. Detection of such sudden stiffness change from the vibrations of structures is important for Structural Health Monitoring (SHM) and damage detection. Non-contact measurement of these vibrations is a quick and efficient way for successful detection of sudden stiffness change of a structure. In this paper, we demonstrate the capability of Laser Doppler Vibrometry to detect sudden stiffness change in a Single Degree Of Freedom (SDOF) oscillator within a laboratory environment. The dynamic response of the SDOF system was measured using a Polytec RSV-150 Remote Sensing Vibrometer. This instrument employs Laser Doppler Vibrometry for measuring dynamic response. Additionally, the vibration response of the SDOF system was measured through a MicroStrain G-Link Wireless Accelerometer mounted on the SDOF system. The stiffness of the SDOF system was experimentally determined through calibrated linear springs. The sudden change of stiffness was simulated by introducing the failure of a spring at a certain instant in time during a given period of forced vibration. The forced vibration on the SDOF system was in the form of a white noise input. The sudden change in stiffness was successfully detected through the measurements using Laser Doppler Vibrometry. This detection from optically obtained data was compared with a detection using data obtained from the wireless accelerometer. The potential of this technique is deemed important for a wide range of applications. The method is observed to be particularly suitable for rapid damage detection and health monitoring of structures under a model-free condition or where information related to the structure is not sufficient.

Integrity-Based Kernel Malware Detection

Kernel-level malware is one of the most dangerous threats to the security of users on the Internet, so there is an urgent need for its detection. The most popular detection approach is misuse-based detection. However, it cannot catch up with today's advanced malware that increasingly apply polymorphism and obfuscation. In this thesis, we present our integrity-based detection for kernel-level malware, which does not rely on the specific features of malware. We have developed an integrity analysis system that can derive and monitor integrity properties for commodity operating systems kernels. In our system, we focus on two classes of integrity properties: data invariants and integrity of Kernel Queue (KQ) requests. We adopt static analysis for data invariant detection and overcome several technical challenges: field-sensitivity, array-sensitivity, and pointer analysis. We identify data invariants that are critical to system runtime integrity from Linux kernel 2.4.32 and Windows Research Kernel (WRK) with very low false positive rate and very low false negative rate. We then develop an Invariant Monitor to guard these data invariants against real-world malware. In our experiment, we are able to use Invariant Monitor to detect ten real-world Linux rootkits and nine real-world Windows malware and one synthetic Windows malware. We leverage static and dynamic analysis of kernel and device drivers to learn the legitimate KQ requests. Based on the learned KQ requests, we build KQguard to protect KQs. At runtime, KQguard rejects all the unknown KQ requests that cannot be validated. We apply KQguard on WRK and Linux kernel, and extensive experimental evaluation shows that KQguard is efficient (up to 5.6% overhead) and effective (capable of achieving zero false positives against representative benign workloads after appropriate training and very low false negatives against 125 real-world malware and nine synthetic attacks). In our system, Invariant Monitor and KQguard cooperate together to protect data invariants and KQs in the target kernel. By monitoring these integrity properties, we can detect malware by its violation of these integrity properties during execution.

GDGT and n-alkane data of sediment core GeoB4901-8

The tight coupling between the atmospheric and oceanic circulation in the equatorial Atlantic region makes this area an important region for paleoclimatic research. Previous studies report the occurrence of large amounts of terrigenous material and soil organic carbon (SOC) within the marine sediments of the eastern Gulf of Guinea. We use the accumulation rates (AR) of branched glycerol dialkyl glycerol tetraethers (GDGTs) to identify variations in SOC delivery to the Niger Fan over the last 35 ka, and compare these records to long-chain n-alkanes as a proxy for higher plant material, to an inorganic proxy for terrigenous input (aluminum AR) and to indicators for the marine productivity (AR of carbonate and crenarchaeol). In addition, sea surface temperatures (SSTs) are calculated based on the TEX86H index and environmental factors affecting the SST-reconstructions are discussed. Our results indicate that Al AR are closely connected to the rate of mean sea level change after 15 ka BP, with an additional influence of the increased monsoonal precipitation and extended vegetation cover corresponding to the African Humid Period (14.8-5.5 ka BP). Branched GDGT AR appears to be determined by shelf erosion in addition to the interplay of monsoonal precipitation and vegetation cover controlling soil erosion. Long-chain n-alkane concentrations clearly show a different trend than the other proxies, which might be due to their predominant eolian transport. Paleo-SSTs show a clear shift from colder temperatures during the last glacial period (20-22 °C) to warmer temperatures during the Holocene (24-26 °C). However, TEX86H-based SSTs are cold-biased compared to recent SSTs and Mg/Ca-based SST reconstructions, which is probably caused by a high seasonality of the Thaumarchaeota, with a maximum productivity of these organisms during the cold summer months. However, a sub-surface production of GDGTs and/or a potential bias of SST reconstruction by terrestrial input could not be completely excluded.

Permanent open water surfaces in central Siberia from ENVISAT ASAR wide swath data 2003/2004, link to shapefile

Permanent water bodies not only store dissolved CO2 but are essential for the maintenance of wetlands in their proximity. From the viewpoint of greenhouse gas (GHG) accounting wetland functions comprise sequestration of carbon under anaerobic conditions and methane release. The investigated area in central Siberia covers boreal and sub-arctic environments. Small inundated basins are abundant on the sub-arctic Taymir lowlands but also in parts of severe boreal climate where permafrost ice content is high and feature important freshwater ecosystems. Satellite radar imagery (ENVISAT ScanSAR), acquired in summer 2003 and 2004, has been used to derive open water surfaces with 150 m resolution, covering an area of approximately 3 Mkm**2. The open water surface maps were derived using a simple threshold-based classification method. The results were assessed with Russian forest inventory data, which includes detailed information about water bodies. The resulting classification has been further used to estimate the extent of tundra wetlands and to determine their importance for methane emissions. Tundra wetlands cover 7% (400,000 km**2) of the study region and methane emissions from hydromorphic soils are estimated to be 45,000 t/d for the Taymir peninsula.