Further characterization of the saccharide specificity of peanut (Arachis hypogaea) agglutinin

2-Dansylamino-2-deoxy-D-galactose (GalNDns) has been shown to bind to peanut (Arachis hypogaea) agglutinin (PNA) in a saccharide-specific manner. This binding was accompanied by a five-fold increase in the fluorescence of GalNDns. The interaction was characterized by an association constant of 0.15 mM at 15° and ΔH and ΔS values of -57.04 kJ·mol-1 and -118.1 J·mol-1.K-1, respectively. Binding of a variety of other mono-, di- and oligo-saccharides to PNA, studied by monitoring their ability to dissociate the PNA-GalNDns complex, revealed that PNA interacts with several T-antigen-related structures, such as β-d-Galp-(1→3)-D-GalNAc, β-D-Galp-(1→3)-α-D-GalpNAcOMe, and β-D-Galp-(1→3)-α-D-GalpNAc(1→3)-Ser, as well as the asialo-G(M1) tetrasaccharide, with comparable affinity, thus showing that this lectin does not discriminate between saccharides in which the penultimate sugar of the β-D-Galp-(1→3)-D-GalNAc unit is the α or β anomer, in contrast to jacalin (Artocarpus integrifolia agglutinin), another anti T-lectin which preferentially binds to β-D-Galp-(1→3)-α-D-GalNAc and does not recognize β-D-Galp-(1→3)-β-D-GalNAc or the related asialo-G(M1) oligosaccharide. These studies also indicated that, in the extended combining region of PNA which accommodates a disaccharide, the primary subsite (subsite A) is highly specific for D-galactose, whereas the secondary subsite (subsite B) is less specific and can accommodate various structures, such as D-galactose, 2-acetamido-2-deoxy-D-galactose, D-glucose, and 2-acetamido-2-deoxy-D-glucose.

Oestrogen-induced synthesis of thiamin-binding protein in immature chicks. Kinetics of induction, hormonal specificity and modulation

A specific radioimmunoassay procedure was developed to monitor the plasma concentrations of thiamin-binding protein, a minor yolk constituent of the chicken egg. By using this sensitive assay, the kinetics of oestrogen-induced elaboration of this specific protein in immature chicks was investigated. After a single injection of the steroid hormone, with an initial lag period of 4–5h the thiamin-binding protein rapidly accumulated in the plasma, attaining peak concentrations around 75h and declining thereafter. A 4-fold amplification of the response was noticed during the secondary stimulation, and this increased to 9-fold during the tertiary stimulation with the steroid hormone. The magnitude of the response was dependent on the hormone dose, and the initial latent period and the duration of the ascending phase of induction were unchanged for the hormonal doses tested during both the primary and secondary stimulations. The circulatory half-life of the protein was 6h as calculated from the measurement of the rate of disappearance of the exogenously administered 125I-labelled protein. Simultaneous administration of progesterone, dihydrotestosterone or corticosterone did not alter the pattern of induction. On the other hand, hyperthyroidism markedly decreased the oestrogenic response, whereas propylthiouracil-induced hypothyroidism had the opposite effect. The anti-oestrogen E- and Z-clomiphene citrates, administered 30min before oestrogen, effectively blocked the hormonal induction. α-Amanitin and cycloheximide administered along with or shortly after the sex steroid severely curtailed the protein elaboration. A comparison of the kinetics of induction of thiamin- and riboflavin-binding proteins by oestrogen revealed that, beneath an apparent similarity, a clear-cut difference exists between the two vitamin-binding proteins, particularly with regard to hormonal dose-dependent sensitivity of induction and the half-life in circulation. The steroid-mediated elaboration of the two yolk proteins thus appears to be not strictly co-ordinated, despite several common regulatory features underlying their induction.

Influence of Hydrophilic Surface Specificity on the Structural Properties of Confined Water

The influence of chemical specificity of hydrophilic surfaces on the structure of confined water in the subnanometer regime is investigated using grand canonical Monte Carlo Simulations. The structural variations for water confined between hydroxylated silica surfaces are contrasted with water confined between mica surfaces. Although both surfaces are hydrophilic, our Study shows that hydration of potassium ions on the mica surface has a strong influence on the water Structure and solvation force response of confined water. In contrast to the disrupted hydrogen bond network observed for water confined between Mica Surfaces, water between silica surfaces retains its hydrogen bond network displaying bulklike structural features down to surface separations as small as 0.45 nm. Hydrogen bonding of all invariant contact water layer with the surface silanol groups aids in maintaining a constant number of hydrogen bonds per water molecule for the silica surfaces. As a consequence water depletion and rearrangement upon decreasing confinement is a strong function of the hydrophilic surface specificity, particularly at smaller separations. An oscillatory solvation force response is only observed for water confined between Silica surfaces, and bulklike features are observed for both Surfaces above a surface separation of about 1.2 nm. We evaluate and contrast the water density, dipole moment distributions, pi pair correlation functions, and solvation forces as a function of the surface separation.

Acoustic emission source location and damage detection in a metallic structure using a graph-theory-based geodesic pproach

A geodesic-based approach using Lamb waves is proposed to locate the acoustic emission (AE) source and damage in an isotropic metallic structure. In the case of the AE (passive) technique, the elastic waves take the shortest path from the source to the sensor array distributed in the structure. The geodesics are computed on the meshed surface of the structure using graph theory based on Dijkstra's algorithm. By propagating the waves in reverse virtually from these sensors along the geodesic path and by locating the first intersection point of these waves, one can get the AE source location. The same approach is extended for detection of damage in a structure. The wave response matrix of the given sensor configuration for the healthy and the damaged structure is obtained experimentally. The healthy and damage response matrix is compared and their difference gives the information about the reflection of waves from the damage. These waves are backpropagated from the sensors and the above method is used to locate the damage by finding the point where intersection of geodesics occurs. In this work, the geodesic approach is shown to be suitable to obtain a practicable source location solution in a more general set-up on any arbitrary surface containing finite discontinuities. Experiments were conducted on aluminum specimens of simple and complex geometry to validate this new method.

A Proof of Convergence of the B-RED and P-RED Algorithms for Random Early Detection

In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.

Titration calorimetric studies to elucidate the specificity of the interactions of polymyxin B with lipopolysaccharides and lipid A

Lipopolysaccharide (LPS), the major cell wall constituent of Gram-negative bacteria, evokes a multitude of biological effects in mammals including pyrogenicity and toxic shock syndrome. Polymyxin B (PmB), a polycationic cyclic peptide, is known to neutralize most of its activities. The nature of the interaction of PmB with LPS and lipid A was investigated by isothermal titration calorimetry. PmB binds to LPS as well as lipid A stoichiometrically and non-co-operatively with micromolar affinity. These interactions are driven primarily by a favourable change in entropy (delta S) and are endothermic in nature. These positive changes in enthalpies decrease with increasing temperature, yielding a heat capacity change, delta Cp, of -2385 J.mol-1.degree-1 for PmB-LPS interactions while the binding of PmB to lipid A displays a delta Cp of -2259 J.mol-1.degree-1. The negative heat capacity changes provide strong evidence for the role of hydrophobic interactions as the driving force for the association of PmB with LPS and lipid A. A correlation of the energetics of these interactions with analyses of the molecular models of PmB suggests that a cluster of solvent-exposed non-polar amino acid side-chains that line one surface of the molecule, together with a ring of positively charged residues on its other surface, are responsible for its strong and stoichiometric binding to LPS.

R1SVM: A randomised nonlinear approach to large-scale anomaly detection

The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Visual detection of occluded crop: For automated harvesting

This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.

Automated feature engineering for HTTP tunnel detection

Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

Automatic wildfire detection and simulation using optical information from unmanned aerial systems

In many parts of the world, uncontrolled fires in sparsely populated areas are a major concern as they can quickly grow into large and destructive conflagrations in short time spans. Detecting these fires has traditionally been a job for trained humans on the ground, or in the air. In many cases, these manned solutions are simply not able to survey the amount of area necessary to maintain sufficient vigilance and coverage. This paper investigates the use of unmanned aerial systems (UAS) for automated wildfire detection. The proposed system uses low-cost, consumer-grade electronics and sensors combined with various airframes to create a system suitable for automatic detection of wildfires. The system employs automatic image processing techniques to analyze captured images and autonomously detect fire-related features such as fire lines, burnt regions, and flammable material. This image recognition algorithm is designed to cope with environmental occlusions such as shadows, smoke and obstructions. Once the fire is identified and classified, it is used to initialize a spatial/temporal fire simulation. This simulation is based on occupancy maps whose fidelity can be varied to include stochastic elements, various types of vegetation, weather conditions, and unique terrain. The simulations can be used to predict the effects of optimized firefighting methods to prevent the future propagation of the fires and greatly reduce time to detection of wildfires, thereby greatly minimizing the ensuing damage. This paper also documents experimental flight tests using a SenseFly Swinglet UAS conducted in Brisbane, Australia as well as modifications for custom UAS.

Ligand Specificity of Group I Biotin Protein Ligase of Mycobacterium tuberculosis

Background: Fatty acids are indispensable constituents of mycolic acids that impart toughness & permeability barrier to the cell envelope of M. tuberculosis. Biotin is an essential co-factor for acetyl-CoA carboxylase (ACC) the enzyme involved in the synthesis of malonyl-CoA, a committed precursor, needed for fatty acid synthesis. Biotin carboxyl carrier protein (BCCP) provides the co-factor for catalytic activity of ACC. Methodology/Principal Findings: BPL/BirA (Biotin Protein Ligase), and its substrate, biotin carboxyl carrier protein (BCCP) of Mycobacterium tuberculosis (Mt) were cloned and expressed in E. coli BL21. In contrast to EcBirA and PhBPL, the similar to 29.5 kDa MtBPL exists as a monomer in native, biotin and bio-5'AMP liganded forms. This was confirmed by molecular weigt profiling by gel filtration on Superdex S-200 and Dynamic Light Scattering (DLS). Computational docking of biotin and bio-5'AMP to MtBPL show that adenylation alters the contact residues for biotin. MtBPL forms 11 H-bonds with biotin, relative to 35 with bio-5'AMP. Docking simulations also suggest that bio-5'AMP hydrogen bonds to the conserved `GRGRRG' sequence but not biotin. The enzyme catalyzed transfer of biotin to BCCP was confirmed by incorporation of radioactive biotin and by Avidin blot. The K-m for BCCP was similar to 5.2 mu M and similar to 420 nM for biotin. MtBPL has low affinity (K-b = 1.06 x 10(-6) M) for biotin relative to EcBirA but their K-m are almost comparable suggesting that while the major function of MtBPL is biotinylation of BCCP, tight binding of biotin/bio-5'AMP by EcBirA is channeled for its repressor activity. Conclusions/Significance: These studies thus open up avenues for understanding the unique features of MtBPL and the role it plays in biotin utilization in M. tuberculosis.

Selective detection of single-enantiomer spectrum of chiral molecules aligned in the polypeptide liquid crystalline solvent: Transition selective one-dimensional H-1-H-1 COSY

One-dimensional (1D) proton NMR spectra of enantiomers are generally undecipherable in chiral orienting poly-gamma-benzyl-L-glutamate (PBLG)/CDCl3 solvent. This arises due to large number of couplings, in addition to superposition of spectra from both the enantiomers, severely hindering the H-1 detection. On the other hand in the present study the benefit is derived front the presence of several couplings among the entire network of interacting protons. Transition selective 1D H-1-H-1 correlation experiment (1D-COSY) which utilizes the Coupling assisted transfer of magnetization not only for unraveling the overlap but also for the selective detection of enantiopure spectrum is reported. The experiment is simple, easy to implement and provides accurate eanantiomeric excess in addition to the determination of the proton-proton couplings of an enantiomer within a short experimental time (few minutes). (C) 2009 Elsevier Inc. All rights reserved.

High-Rate Space-Time Coded Large-MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16 X 16 and 32 X 32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.

Business busts and U.S. auditors' interest in fraud detection: Evidence from the 20th century

We find evidence that U.S. auditors increased their attention to fraud detection during or immediately after the economic contractions of the 20th century, based on a content analysis of the 12 volumes of the 20th-century auditing reference series Montgomery’s Auditing. Contractions, however, do not seem to have affected auditors’ attention to the formal goal of fraud detection. The study suggests that auditors’ aversion to the heightened risks of fraud during economic downturns leads them to focus more on fraud detection at those times regardless of the particular guidance in formal audit standards. This study is the first to find some evidence of a recession-influenced difference between fraud detection practices and formal fraud detection goals.