Chemiluminescence determination of trace ascorbic acid with chromium (VI)-H2O2-luminol system

A new chemiluminescence(CL) system for the determination of ascorbic acid has been established. By the fast reduction reaction between chromium(VI) and ascorbic acid, chromium(M was generated to react with luminol and hydrogen peroxide in alkaline aqueous solution and hydrogen peroxide to produce CL. The CL emission intensity was correlated with ascorbic acid concentration in the range 8.0 x 10(-9) to 1.6 x 10(-4) mol/L, and the detection limit was 8.0 x 10(-9) mol/L ascorbic acid. The relative standard deviation (n = 11) for 1.0 x 10(-6) mol/L ascorbic acid is 0.9%. The method has been applied to the determination of ascorbic acid in vitamin C tablets with satisfactory results.

Capacitive detection of glucose using molecularly imprinted polymers

A novel glucose biosensor based on capacitive detection has been developed using molecularly imprinted polymers. The sensitive layer was prepared by electropolymerization of o-phenylenediamine on a gold electrode in the presence of the template (glucose). Cyclic voltammetry and capacitive measurements monitored the process of electropolymerization. Surface uncovered areas were plugged with 1-dodecanethiol to make the layer dense, and the insulating properties of the layer were studied in the presence of redox couples. The template molecules and the nonbound thiol were removed from the modified electrode surface by washing with distilled water. A capacitance decrease could be obtained after injection of glucose. The electrode constructed similarly but with ascorbic acid or fructose only showed a small response compared with glucose. The stability and reproducibility of the biosensor were also investigated. (C) 2001 Elsevier Science B.V. All rights reserved.

New microsystem of capillary electrophoresis with amperometric detection

We have made a cheap microsystem of capillary electrophoresis with a new method, integrating the electrodes, injection channel, separation channel, buffer reservoirs and detection cell on a polymethylmethacrylate (PMMA) chip. Using an integrated micro carbon fiber disk electrode as the working electrode in three electrodes system, 1 x 10(-4) mol/L dopamine(DA) could be detected with end-column amperometric detection. The reproducibility was good. Peak current was 6.73 nA,theoretical plate number was 71300/m and height equivalent of one theoretical plate height was 14.0 mum for 1 x 10(-4) mol/L DA. The limit of detection was 3.6 x 10(-8) mol/L and the linear range was extended from 5 x 10(-7) mol/L to 1 x 10(-4) mol/L for DA. 1 x 10(-4) mol/L catechol (CA) and 5 x 10(-5) mol/L DA were also separated completely with R-s = 10.1.

Observations on photochemical fluorescence enhancement of the terbium(III) sparfloxacin system

Fluorescence of terbium(III) was sensitized when excited in the presence of sparfloxacin (SPFX) in the aqueous solution because a Tb(III)-SPFX complex was formed. The sensitized fluorescence was further enhanced when this system was exposed to 365 nm ultraviolet light. By the spectral properties and contrast experiments, it is proved that irradiation makes this system undergo photochemical reactions and a new terbium complex which is more favorable to the intramolecular energy transfer is formed. The mechanism of photochemical fluorescence enhancement of the Tb(III)-SPFX system is discussed and a new sensitive and selective photochemical fluorimetry for the determination of SPFX is established. Under the optimum conditions, the linear range is 1.0-50 x 10(-7) M for SPFX, the detection limit is 3.0 x 10(-9) M and the R.S.D. for 5.0 x 10(-7) M SPFX is 1.3% (n = 9). Without any pretreatment the recovery of SPFX in human urine was determined with satisfaction. (C) 1999 Elsevier Science B.V. All rights reserved.

Evaluation of luminol-H2O2-KIO4 chemiluminescence system and its application to hydrogen peroxide, glucose and ascorbic acid assays

(A) novel chemiluminescence (CL) system was evaluated for the determination of hydrogen peroxide, glucose and ascorbic acid based on hydrogen peroxide, which has a catalytic-cooxidative effect on the oxidation of luminol by KIO4. Hydrogen peroxide can be directly determined by luminol-KIO4 -H2O2 CL system. The detection limit was 3.0 x 10(-8) mol l(-1) and the calibration graph was linear over the range of 2.0 x 10(-7)-6.0 x 10(-4) mol l(-1). The relative standard deviation of H2O2 was 1.1% for 2.0 x 10(-6) mol l(-1) (N = 11). Glucose was indirectly determined through measuring the H2O2 generated by the oxidation of glucose in the presence of glucose oxidase at pH 7.6. The present method provides a source for H2O2, which, in turn, coupled with the luminol-KIO4-H2O2 CL reaction system. The CL was linearly correlated with glucose concentration of 0.6-110 mu g ml(-1). The relative standard deviation was 2.1% for 10 mu g ml(-1) (N = 11). Detection limit of glucose was 0.08 mu g ml(-1). Ascorbic acid was also indirectly determined by the suppression of luminol-KIO4-H2O2 CL system. The calibration curve was linear over the range of 1.0 x 10(-7)-1.0 x 10(-5) mol l(-1) of ascorbic acid. The relative standard deviation was 1.0% for 8.0 x 10(-7) mol l(-1) (N = 11). Detection limit of ascorbic acid was 6.0 x 10(=8) mol l(-1). These proposed methods have been applied to determine glucose, ascorbic acid in tablets and injection. (C) 1999 Elsevier Science B.V. All rights reserved.

Electrocatalytic oxidation of hydrazines at a 4-pyridyl hydroquinone self-assembled platinum electrode and its application to amperometric detection in capillary electrophoresis

4-Pyridyl hydroquinone on a platinum electrode adsorbs through the pyridine nitrogen forming stable self-assembled layers. The electrocatalytical oxidation of hydrazines was performed by the modified electrode. The overpotential of hydrazines was decreased markedly at the self-assembled monolayer (SAM) electrode. The mechanism of hydrazine oxidation was also investigated. Amperometric detection of hydrazine under zero potential (vs Ag\AgCI\sat. KCl) was exhibited by the SAM electrode used as an electrochemical detector in a flow system. (C) 1998 Elsevier Science S.A. All rights reserved.

Rapid automated in-situ monitoring of total dissolved iron and total dissolved manganese in underground water by reverse-flow injection with chemiluminescence detection during the process of water treatment

Measurement of iron and manganese is very important in evaluating the quality of natural waters. We have constructed an automated Fe(II), total dissolved iron(TDI), Mn(II), and total dissolved manganese(TDM) analysis system for the quality control of underground drinking water by reverse flow injection analysis and chemiluminescence detection(rFIA-CL), The method is based on the measurement of the metal-catalyzed light emission from luminol oxidation by potassium periodate. The typical signal is a narrow peak, in which the height is proportional to light emitted and hence to the concentration of metal ions. The detection limits were 3 x 10(-6) mu g ml(-1) for Fe(II) and the linear range extents up to 1.0 x 10(-4) and 5 x 10(-6) mu g ml(-1) for Mn(II) cover a linear range to 1.0 x 10(-4) mu g ml(-1). This method was used for automated in-situ monitoring of total dissolved iron and total dissolved in underground water during water treatment. (C) 1997 Elsevier Science B.V.

DETERMINATION OF CYSTEINE AND REDUCED GLUTATHIONE IN HUMAN PLASMA BY LIQUID-CHROMATOGRAPHY WITH PULSED AMPEROMETRIC ELECTROCHEMICAL DETECTION USING A PLATINUM-PARTICLES MODIFIED GLASSY-CARBON ELECTRODE

An assay procedure utilizing pulsed amperometric detection at a platinum-particles modified electrode has been developed for the determination of cysteine and glutathione in blood samples following preliminary separation by reversed-phase liquid chromatography. A chemically modified electrode (CME) constructed by unique electroreduction from a platinum-salt solution to produce dispersed Pt particles on a glassy carbon surface was demonstrated to catalyze the electo-oxidation of sulfhydryl-containing compounds: DL-cysteine (CYS), reduced glutathione (GSH). When used as the sensing electrode in flow-system pulsed-amperometric detection (PAD), electrode fouling could be avoided using a waveform in which the cathodic reactivation process occurred at a potential of - 1.0 V vs. Ag/AgCl to achieve a cathodic desorption of atomic sulfur. A superior detection limit for these free thiols was obtained at a Pt particle-based GC electrode compared with other methods; this novel dispersed Pt particles CME exhibited high electrocatalytic stability and activity when it was employed as an electrochemical detector in FIA and HPLC for the determination of those organo-sulfur compounds.

Selective and specific detection of sulfate-reducing bacteria using potentiometric stripping analysis

A fast, sensitive and reliable potentiometric stripping analysis (PSA) is described for the selective detection of the marine pathogenic sulfate-reducing bacterium (SRB). Desulforibrio caledoiensis. The chemical and electrochemical parameters that exert influence on the deposition and stripping of lead ion, such as deposition potential, deposition time and pH value were carefully studied. The concentration of SRB was determined in acetate buffer solution (pH 5.2) under the optimized condition (deposition potential of -1.3 V. deposition time of 250 s, ionic strength of 0.2 mol L-1 and oxidant mercury (II) concentration of 40 mg L-1). A linear relationship between the stripping response and the logarithm of the bacterial concentration was observed in the range of 2.3 x 10 to 2.3 x 10(7) cfu mL(-1). In addition, the potentiometric stripping technique gave a distinct response to the SRB, but had no obvious response to Escherichia coli. The measurement system has a potential for further applications and provides a facile and sample method for detection of pathogenic bacteria. (C) 2010 Elsevier B.V. All rights reserved.

A homogeneous DNA hybridization system by using a new luminescence terbium chelate

Homogeneous DNA hybridization assay based on the luminescence resonance energy transfer (LRET) from a new luminescence terbium chelate, N,N,N-1,N-1-[2,6-bis(3'-aminomethyl-1'-pyrazolyl)-4-phenylpyridine]tetrakis(acetic acid) (BPTA)-Tb3+ (lambda(ex) = 325 nm and lambda(em) = 545 nm) to an organic dye, Cy3 (A,. = 548 nm and A,. = 565 nm), has been developed. In the system, two DNA probes whose sequences are complementary to the two different consecutive sequences of a target DNA are used; one of the probes is labeled with the Tb3+ chelate at the T-end, and the other is with Cy3 at the 5'-end. Labeling of the Tb3+ chelate is accomplished via the linkage of a biotin-labeled DNA probe with the Tb3+ chelate-labeled streptavidin. Strong sensitized emission of Cy3 was observed upon excitation of the Tb3+ chelate at 325 run, when the two probe DNAs were hybridized with the target DNA. The sensitivity of the assay was very high compared with those of the previous homogeneous-format assays using the conventional organic dyes; the detection limit of the present assay is about 30 pM of the target DNA strand.

Contextual models for object detection using boosted random fields

We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which uses Boosting to learn the graph structure and local evidence of a conditional random field (CRF). The graph structure is learned by assembling graph fragments in an additive model. The connections between individual pixels are not very informative, but by using dense graphs, we can pool information from large regions of the image; dense models also support efficient inference. We show how contextual information from other objects can improve detection performance, both in terms of accuracy and speed, by using a computational cascade. We apply our system to detect stuff and things in office and street scenes.

Learning and Example Selection for Object and Pattern Detection

This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation, and show how it leads to a tractable example selection paradigm, suitable for use in many object and pattern detection problems.

Feature Extraction Without Edge Detection

Information representation is a critical issue in machine vision. The representation strategy in the primitive stages of a vision system has enormous implications for the performance in subsequent stages. Existing feature extraction paradigms, like edge detection, provide sparse and unreliable representations of the image information. In this thesis, we propose a novel feature extraction paradigm. The features consist of salient, simple parts of regions bounded by zero-crossings. The features are dense, stable, and robust. The primary advantage of the features is that they have abstract geometric attributes pertaining to their size and shape. To demonstrate the utility of the feature extraction paradigm, we apply it to passive navigation. We argue that the paradigm is applicable to other early vision problems.

Implementation of a Theory of Edge Detection

This report describes the implementation of a theory of edge detection, proposed by Marr and Hildreth (1979). According to this theory, the image is first processed independently through a set of different size filters, whose shape is the Laplacian of a Gaussian, ***. Zero-crossings in the output of these filters mark the positions of intensity changes at different resolutions. Information about these zero-crossings is then used for deriving a full symbolic description of changes in intensity in the image, called the raw primal sketch. The theory is closely tied with early processing in the human visual systems. In this report, we first examine the critical properties of the initial filters used in the edge detection process, both from a theoretical and practical standpoint. The implementation is then used as a test bed for exploring aspects of the human visual system; in particular, acuity and hyperacuity. Finally, we present some preliminary results concerning the relationship between zero-crossings detected at different resolutions, and some observations relevant to the process by which the human visual system integrates descriptions of intensity changes obtained at different resolutions.

Design and implementation of robust systems for secure malware detection

Malicious software (malware) have significantly increased in terms of number and effectiveness during the past years. Until 2006, such software were mostly used to disrupt network infrastructures or to show coders’ skills. Nowadays, malware constitute a very important source of economical profit, and are very difficult to detect. Thousands of novel variants are released every day, and modern obfuscation techniques are used to ensure that signature-based anti-malware systems are not able to detect such threats. This tendency has also appeared on mobile devices, with Android being the most targeted platform. To counteract this phenomenon, a lot of approaches have been developed by the scientific community that attempt to increase the resilience of anti-malware systems. Most of these approaches rely on machine learning, and have become very popular also in commercial applications. However, attackers are now knowledgeable about these systems, and have started preparing their countermeasures. This has lead to an arms race between attackers and developers. Novel systems are progressively built to tackle the attacks that get more and more sophisticated. For this reason, a necessity grows for the developers to anticipate the attackers’ moves. This means that defense systems should be built proactively, i.e., by introducing some security design principles in their development. The main goal of this work is showing that such proactive approach can be employed on a number of case studies. To do so, I adopted a global methodology that can be divided in two steps. First, understanding what are the vulnerabilities of current state-of-the-art systems (this anticipates the attacker’s moves). Then, developing novel systems that are robust to these attacks, or suggesting research guidelines with which current systems can be improved. This work presents two main case studies, concerning the detection of PDF and Android malware. The idea is showing that a proactive approach can be applied both on the X86 and mobile world. The contributions provided on this two case studies are multifolded. With respect to PDF files, I first develop novel attacks that can empirically and optimally evade current state-of-the-art detectors. Then, I propose possible solutions with which it is possible to increase the robustness of such detectors against known and novel attacks. With respect to the Android case study, I first show how current signature-based tools and academically developed systems are weak against empirical obfuscation attacks, which can be easily employed without particular knowledge of the targeted systems. Then, I examine a possible strategy to build a machine learning detector that is robust against both empirical obfuscation and optimal attacks. Finally, I will show how proactive approaches can be also employed to develop systems that are not aimed at detecting malware, such as mobile fingerprinting systems. In particular, I propose a methodology to build a powerful mobile fingerprinting system, and examine possible attacks with which users might be able to evade it, thus preserving their privacy. To provide the aforementioned contributions, I co-developed (with the cooperation of the researchers at PRALab and Ruhr-Universität Bochum) various systems: a library to perform optimal attacks against machine learning systems (AdversariaLib), a framework for automatically obfuscating Android applications, a system to the robust detection of Javascript malware inside PDF files (LuxOR), a robust machine learning system to the detection of Android malware, and a system to fingerprint mobile devices. I also contributed to develop Android PRAGuard, a dataset containing a lot of empirical obfuscation attacks against the Android platform. Finally, I entirely developed Slayer NEO, an evolution of a previous system to the detection of PDF malware. The results attained by using the aforementioned tools show that it is possible to proactively build systems that predict possible evasion attacks. This suggests that a proactive approach is crucial to build systems that provide concrete security against general and evasion attacks.