Detection of anthropogenic climate change using a fingerprint method

A fingerprint method for detecting anthropogenic climate change is applied to new simulations with a coupled ocean-atmosphere general circulation model (CGCM) forced by increasing concentrations of greenhouse gases and aerosols covering the years 1880 to 2050. In addition to the anthropogenic climate change signal, the space-time structure of the natural climate variability for near-surface temperatures is estimated from instrumental data over the last 134 years and two 1000 year simulations with CGCMs. The estimates are compared with paleoclimate data over 570 years. The space-time information on both the signal and the noise is used to maximize the signal-to-noise ratio of a detection variable obtained by applying an optimal filter (fingerprint) to the observed data. The inclusion of aerosols slows the predicted future warming. The probability that the observed increase in near-surface temperatures in recent decades is of natural origin is estimated to be less than 5%. However, this number is dependent on the estimated natural variability level, which is still subject to some uncertainty.

Gold nanoparticles for the detection of DNA adducts as biomarkers of exposure to acrylamide

The main objective of this thesis was the development of a gold nanoparticle-based methodology for detection of DNA adducts as biomarkers, to try and overcome existing drawbacks in currently employed techniques. For this objective to be achieved, the experimental work was divided in three components: sample preparation, method of detection and development of a model for exposure to acrylamide. Different techniques were employed and combined for de-complexation and purification of DNA samples (including ultrasonic energy, nuclease digestion and chromatography), resulting in a complete protocol for sample treatment, prior to detection. The detection of alkylated nucleotides using gold nanoparticles was performed by two distinct methodologies: mass spectrometry and colorimetric detection. In mass spectrometry, gold nanoparticles were employed for laser desorption/ionisation instead of the organic matrix. Identification of nucleotides was possible by fingerprint, however no specific mass signals were denoted when using gold nanoparticles to analyse biological samples. An alternate method using the colorimetric properties of gold nanoparticles was employed for detection. This method inspired in the non-cross-linking assay allowed the identification of glycidamide-guanine adducts and DNA adducts generated in vitro. For the development of a model of exposure, two different aquatic organisms were studies: a goldfish and a mussel. Organisms were exposed to waterborne acrylamide, after which mortality was recorded and effect concentrations were estimated. In goldfish, both genotoxicity and metabolic alterations were assessed and revealed dose-effect relationships of acrylamide. Histopathological alterations were verified primarily in pancreatic cells, but also in hepatocytes. Mussels showed higher effect concentrations than goldfish. Biomarkers of oxidative stress, biotransformation and neurotoxicity were analysed after prolonged exposure, showing mild oxidative stress in mussel cells, and induction of enzymes involved in detoxification of oxygen radicals. A qualitative histopathological screening revealed gonadotoxicity in female mussels, which may present some risk to population equilibrium.

Risk Evaluation for Spoofing against a Sensor Supplied with Liveness Detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

Vulnerabilities of fingerprint reader to fake fingerprints attacks

The purpose of this research is to assess the vulnerabilities of a high resolution fingerprint sensor when confronted with fake fingerprints. The study has not been focused on the decision outcome of the biometric device, but essentially on the scores obtained following the comparison between a query (genuine or fake) and a template using an AFIS system. To do this, fake fingerprints of 12 subjects have been produced with and without their cooperation. These fake fingerprints have been used alongside with real fingers. The study led to three major observations: First, genuine fingerprints produced scores higher than fake fingers (translating a closer proximity) and this tendency is observed considering each subject separately. Second, scores are however not sufficient as a single measure to differentiate these samples (fake from genuine) given the variation due to the donors themselves. That explains why fingerprint readers without vitality detection can be fooled. Third, production methods and subjects greatly influence the scores obtained for fake fingerprints.

Risk evaluation for spoofing against a sensor supplied with liveness detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

Vulnerabilities of Fingerprint Reader to Fake Fingerprint Attacks

The purpose of this research is to assess the vulnerabilities of a high resolution fingerprint sensor when confronted with fake fingerprints. The study has not been focused on the decision outcome of the biometric device, but essentially on the scores obtained following the comparison between a query (genuine or fake) and a template using an AFIS system. To do this, fake fingerprints of 12 subjects have been produced with and without their cooperation. These fake fingerprints have been used alongside with real fingers. The study led to three major observations: First, genuine fingerprints produced scores higher than fake fingers (translating a closer proximity) and this tendency is observed considering each subject separately. Second, scores are however not sufficient as a single measure to differentiate these samples (fake from genuine) given the variation due to the donors themselves. That explains why fingerprint readers without vitality detection can be fooled. Third, production methods and subjects greatly influence the scores obtained for fake fingerprints.

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks

Anti-spoofing is attracting growing interest in biometrics, considering the variety of fake materials and new means to attack biometric recognition systems. New unseen materials continuously challenge state-of-the-art spoofing detectors, suggesting for additional systematic approaches to target anti-spoofing. By incorporating liveness scores into the biometric fusion process, recognition accuracy can be enhanced, but traditional sum-rule based fusion algorithms are known to be highly sensitive to single spoofed instances. This paper investigates 1-median filtering as a spoofing-resistant generalised alternative to the sum-rule targeting the problem of partial multibiometric spoofing where m out of n biometric sources to be combined are attacked. Augmenting previous work, this paper investigates the dynamic detection and rejection of livenessrecognition pair outliers for spoofed samples in true multi-modal configuration with its inherent challenge of normalisation. As a further contribution, bootstrap aggregating (bagging) classifiers for fingerprint spoof-detection algorithm is presented. Experiments on the latest face video databases (Idiap Replay- Attack Database and CASIA Face Anti-Spoofing Database), and fingerprint spoofing database (Fingerprint Liveness Detection Competition 2013) illustrate the efficiency of proposed techniques.

Towards anomaly detection for increased security in multibiometric systems: spoofing-resistant 1-median fusion eliminating outliers

Multibiometrics aims at improving biometric security in presence of spoofing attempts, but exposes a larger availability of points of attack. Standard fusion rules have been shown to be highly sensitive to spoofing attempts – even in case of a single fake instance only. This paper presents a novel spoofing-resistant fusion scheme proposing the detection and elimination of anomalous fusion input in an ensemble of evidence with liveness information. This approach aims at making multibiometric systems more resistant to presentation attacks by modeling the typical behaviour of human surveillance operators detecting anomalies as employed in many decision support systems. It is shown to improve security, while retaining the high accuracy level of standard fusion approaches on the latest Fingerprint Liveness Detection Competition (LivDet) 2013 dataset.

Detection of phenolic compounds using impedance spectroscopy measurements

Langmuir-Blodgett (LB) and layer-by-layer films (LbL) of a PPV (p-phenylenevinylene) derivative, an azo compound and tetrasulfonated phthalocyanines were successfully employed as transducers in an ""electronic tongue"" system for detecting trace levels of phenolic compounds in water. The choice of the materials was based on their distinct electrical natures, which enabled the array to establish a fingerprint of very similar liquids. Impedance spectroscopy measurements were taken in the frequency range from 10 Hz to 1 MHz, with the data analysed with principal component analysis (PCA). The sensing units were obtained from five-layer LB films of (poly[(2-methoxy-5-n-hexyloxy)-p-phenylenevinylene]), OC(1)OC(18)-PPV (poly(2-methoxy,5-(n-octadecyl)-p-phenylenevinylene)), DR (HEMA-co-DR13MA (poly-(hydroxyethylmethacrylate-co-[4`-[[2-(methacryloyloxy)-ethyl]ethylamino]-2-chloro-4-nitroazobenzene]))) and five-bilayer LbL films of tetrasulfonated metallic phthalocyanines deposited onto gold interdigitated electrodes. The sensors were immersed into phenol, 2-chloro-4-methoxyphenol, 2-chlorophenol and 3-chlorophenol (isomers) solutions at 1 x 10(-9) mol L(-1), with control experiments carried out in ultra pure water. Samples could be distinguished if the principal component analysis (PCA) plots were made with capacitance values taken at 10(3) Hz, which is promising for detection of trace amounts of phenolic pollutants in natural water.

Detection of phenolic compounds using impedance spectroscopy measurements

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A trade off between separation, detection and sustainability in liquid chromatographic fingerprinting

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detection of Shiga toxigenic (STEC) and enteropathogenic (EPEC) Escherichia coli in dairy buffalo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Detection of trace levels of atrazine using surface-enhanced Raman scattering and information visualization

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Neurological Disease Detection and Monitoring from Voice Production

The dramatic impact of neurological degenerative pathologies in life quality is a growing concern. It is well known that many neurological diseases leave a fingerprint in voice and speech production. Many techniques have been designed for the detection, diagnose and monitoring the neurological disease. Most of them are costly or difficult to extend to primary attention medical services. Through the present paper it will be shown how some neurological diseases can be traced at the level of phonation. The detection procedure would be based on a simple voice test. The availability of advanced tools and methodologies to monitor the organic pathology of voice would facilitate the implantation of these tests. The paper hypothesizes that some of the underlying mechanisms affecting the production of voice produce measurable correlates in vocal fold biomechanics. A general description of the methodological foundations for the voice analysis system which can estimate correlates to the neurological disease is shown. Some study cases will be presented to illustrate the possibilities of the methodology to monitor neurological diseases by voice