Development and production of an oligonucleotide MuscleChip: use for validation of ambiguous ESTs

BACKGROUND: We describe the development, validation, and use of a highly redundant 120,000 oligonucleotide microarray (MuscleChip) containing 4,601 probe sets representing 1,150 known genes expressed in muscle and 2,075 EST clusters from a non-normalized subtracted muscle EST sequencing project (28,074 EST sequences). This set included 369 novel EST clusters showing no match to previously characterized proteins in any database. Each probe set was designed to contain 20–32 25 mer oligonucleotides (10–16 paired perfect match and mismatch probe pairs per gene), with each probe evaluated for hybridization kinetics (Tm) and similarity to other sequences. The 120,000 oligonucleotides were synthesized by photolithography and light-activated chemistry on each microarray. RESULTS: Hybridization of human muscle cRNAs to this MuscleChip (33 samples) showed a correlation of 0.6 between the number of ESTs sequenced in each cluster and hybridization intensity. Out of 369 novel EST clusters not showing any similarity to previously characterized proteins, we focused on 250 EST clusters that were represented by robust probe sets on the MuscleChip fulfilling all stringent rules. 102 (41%) were found to be consistently "present" by analysis of hybridization to human muscle RNA, of which 40 ESTs (39%) could be genome anchored to potential transcription units in the human genome sequence. 19 ESTs of the 40 ESTs were furthermore computer-predicted as exons by one or more than three gene identification algorithms. CONCLUSION: Our analysis found 40 transcriptionally validated, genome-anchored novel EST clusters to be expressed in human muscle. As most of these ESTs were low copy clusters (duplex and triplex) in the original 28,000 EST project, the identification of these as significantly expressed is a robust validation of the transcript units that permits subsequent focus on the novel proteins encoded by these genes

Detecting Abnormal Behavior in Web Applications

The rapid advance of web technologies has made the Web an essential part of our daily lives. However, network attacks have exploited vulnerabilities of web applications, and caused substantial damages to Internet users. Detecting network attacks is the first and important step in network security. A major branch in this area is anomaly detection. This dissertation concentrates on detecting abnormal behaviors in web applications by employing the following methodology. For a web application, we conduct a set of measurements to reveal the existence of abnormal behaviors in it. We observe the differences between normal and abnormal behaviors. By applying a variety of methods in information extraction, such as heuristics algorithms, machine learning, and information theory, we extract features useful for building a classification system to detect abnormal behaviors.;In particular, we have studied four detection problems in web security. The first is detecting unauthorized hotlinking behavior that plagues hosting servers on the Internet. We analyze a group of common hotlinking attacks and web resources targeted by them. Then we present an anti-hotlinking framework for protecting materials on hosting servers. The second problem is detecting aggressive behavior of automation on Twitter. Our work determines whether a Twitter user is human, bot or cyborg based on the degree of automation. We observe the differences among the three categories in terms of tweeting behavior, tweet content, and account properties. We propose a classification system that uses the combination of features extracted from an unknown user to determine the likelihood of being a human, bot or cyborg. Furthermore, we shift the detection perspective from automation to spam, and introduce the third problem, namely detecting social spam campaigns on Twitter. Evolved from individual spammers, spam campaigns manipulate and coordinate multiple accounts to spread spam on Twitter, and display some collective characteristics. We design an automatic classification system based on machine learning, and apply multiple features to classifying spam campaigns. Complementary to conventional spam detection methods, our work brings efficiency and robustness. Finally, we extend our detection research into the blogosphere to capture blog bots. In this problem, detecting the human presence is an effective defense against the automatic posting ability of blog bots. We introduce behavioral biometrics, mainly mouse and keyboard dynamics, to distinguish between human and bot. By passively monitoring user browsing activities, this detection method does not require any direct user participation, and improves the user experience

Search for Second-Generation Leptoquarks in Proton-Antiproton Collisions

This document describes the search for second-generation leptoquarks (LQ_2) in around 114 pb^-1 of proton-antiproton collisions, recorded with the D0 detector between September 2002 and June 2003 at a centre-of-mass energy of sqrt{s} = 1.96 TeV. The predictions of the Standard Model and models including scalar leptoquark production are compared to the data for various kinematic distributions. Since no excess of data over the Standard Model prediction has been observed, a lower limit on the leptoquark mass of M(LQ_2)_{beta=1} > 200 GeV/c^2 has been calculated at 95% confidence level (C.L.), assuming a branching fraction of beta = BF(LQ_2 --> mu j) = 100% into a charged lepton and a quark. The corresponding limit for beta = 1/2 is M(LQ_2)_{beta=1/2} > 152 GeV/c^2. Finally, the results were combined with those from the search in the same channel at D0 Run I. This combination yields the exclusion limit of 222 GeV/c^2 (177 GeV/c^2) for beta=1 (1/2) at 95% C.L., which is the best exclusion limit for scalar second-generation leptoquarks (for beta=1) from a single experiment to date.In diesem Dokument wird die Suche nach Leptoquarks der zweiten Generation (LQ_2) in Proton-Antiproton-Kollisionen beschrieben, die mit dem D0-Detektor am TeVatron-Beschleuniger aufgezeichnet wurden. Im Zeitraum von September 2002 bis Juni 2003 wurde eine integrierte Luminosität von rund 114 pb^-1 bei einer Schwerpunktsenergie von sqrt{s} = 1.96 TeV gesammelt. Die Vorhersagen des Standardmodells der Teilchenphysik und darüber hinausgehender Modelle mit skalaren Leptoquarks wurden mit den Daten verglichen. Da kein Überschuss an Daten über der Standardmodellvorhersage beobachtet werden konnte, wurde unter der Annahme, dass Leptoquarks zu 100% in geladene Leptonen und Quarks zerfallen (beta = BF(LQ_2 --> mu j) = 100%), eine untere Schranke von M(LQ_2)_{beta=1} > 200 GeV/c^2 (95% C.L.) für die Masse von skalaren Leptoquarks der zweiten Generation ermittelt. Die entsprechende Ausschlussgrenze für beta=1/2 liegt bei M(LQ_2)_{beta=1/2} > 152 GeV/c^2. Schließlich wurden die Resultate mit den Ergebnissen einer Suche im gleichen Kanal bei D0 Run I kombiniert. Diese Kombination liefert die Ausschlussgrenzen M(LQ_2)_{beta=1} > 222 GeV/c^2 (177 GeV/c^2) für beta=1 (1/2) und ist somit für beta=1 das zur Zeit beste Ergebnis für skalare Leptoquarks der zweiten Generation eines einzelnen Experimentes

An effective recommender system by unifying user and item trust information for B2B applications

© 2015 Elsevier Inc. Although Collaborative Filtering (CF)-based recommender systems have received great success in a variety of applications, they still under-perform and are unable to provide accurate recommendations when users and items have few ratings, resulting in reduced coverage. To overcome these limitations, we propose an effective hybrid user-item trust-based (HUIT) recommendation approach in this paper that fuses the users' and items' implicit trust information. We have also considered and computed user and item global reputations into this approach. This approach allows the recommender system to make an increased number of accurate predictions, especially in circumstances where users and items have few ratings. Experiments on four real-world datasets, particularly a business-to-business (B2B) case study, show that the proposed HUIT recommendation approach significantly outperforms state-of-the-art recommendation algorithms in terms of recommendation accuracy and coverage, as well as significantly alleviating data sparsity, cold-start user and cold-start item problems

Transportation optimization for the collection of end-of-life vehicles

Firms operating in the purchasing of end-of-life vehicles (ELVs) have significant challenges related to the fact that most of the purchased ELVs must be collected efficiently in order to minimize their transportation costs. In this project, we study a reverse logistics problem of a Canadian firm that collects ELVs from a group of dealers and accumulates them at its warehouse for part resale or recycling. This problem can be modeled as a vehicle routing problem (VRP) with different side-constraints. Although prior research has made several contributions to model and solve different variants of the VRP, the specific issue in this project considers solving a VRP with a new combination of constraints, such as customer assignment to the private fleet or an external carrier, time-windows, multi-trip, and loading sequences. We propose a mixed-integer linear programming (MILP) model as well as a heuristic algorithm capable of finding the routes’ planning that minimizes the total transportation costs. The performance of the proposed methods is assessed by generated instances using the data obtained from the company

A direct search for Dirac magnetic monopoles

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, June 2005.Includes bibliographical references (p. 159-164).Magnetic monopoles are highly ionizing and curve in the direction of the magnetic field. A new dedicated magnetic monopole trigger at CDF, which requires large light pulses in the scintillators of the time-of-flight system, remains highly efficient to monopoles while consuming a tiny fraction of the available trigger bandwidth. A specialized offline reconstruction checks the central drift chamber for large dE/dx tracks which do not curve in the plane perpendicular to the magnetic field. We observed zero monopole candidate events in 35.7 pb⁻¹ of proton-antiproton collisions at ... = 1.96 TeV. This implies a monopole production cross section limit [sigma] 360 GeV.by Michael James Mulhearn.Ph.D

Honey authentication: effect of irradiation and ageing on near-infrared (NIR) spectroscopy classification models

Thesis (MScFoodSc)--Stellenbosch University, 2020.ENGLISH ABSTRACT: Near-infrared (NIR) spectroscopy was used to investigate the effects of syrup dilution, ageing, storage temperature and irradiation treatment on the NIR spectra of honey. Additionally, NIR spectroscopy and partial least squares discriminant analysis (PLS-DA) were employed to develop a classification model for the rapid screening of high-fructose corn syrup (HFCS) and invert cane sugar syrup (ICSS) diluted honey. Detection of irradiation treatment was also investigated, to assess NIR spectroscopy-based models as a potential screening tool for detecting mislabelled honey. Unfiltered and unheated honey samples (n = 17) obtained from South African beekeepers were uniformly strained and subjected to treatment combinations of 10 kGy gamma irradiation and dilution with 0, 10 or 20% (w/w) ICSS or HFCS to create sub-samples (n = 174) which were stored at 25°C. Another three undiluted subsets were stored at 4°C, 40°C and in uncontrolled ambient conditions (n = 51). A benchtop BÜCHI Fourier transform-near infrared (FT-NIR) spectrometer and a portable MicroNIR NIR spectrometer, with ranges of 1000–2500 nm and 908-1676 nm respectively, were used to acquire triplicate spectral measurements, over a period of 9 months. ANOVA-simultaneous component analysis (ASCA) indicated that honey type, diluent type, storage temperature and age had significant (p > 0.05) effects on the spectral dataset, while diluent level and irradiation treatment did not. Despite this, irradiation treatment was found to reduce the validation accuracy and efficacy of authentication models, by 5.82% and 7.19% respectively, when PLS-DA models based on only irradiated and only non-irradiated spectral data were compared, suggesting that authentication may be impeded by irradiation treatment to some degree. However, a PLS-DA model discriminating on the basis of irradiation treatment obtained an unsuccessful validation classification of 59.7%, suggesting that there is little or no utilisable effect of irradiation on the spectral data. The best-performing authentication solutions were individual two-class PLS-DA models for detecting ICSS (75.95% accuracy, 86.31% sensitivity) and HFCS (73.95% accuracy, 82.14% sensitivity) dilution, which demonstrated predictive power adequate for screening purposes. PLS-DA models based on spectral data acquired with the benchtop BÜCHI instrument performed best when compared with the portable MicroNIR instrument and its two sample presentation formats. Despite this, the MicroNIR with Teflon cup sample presentation was shown to be a feasible and cost-effective alternative, demonstrating similar accuracies (70.0-75.47%) and efficiencies (68.22-74.51%). In addition, quantification of the level of diluent with partial least squares regression (PLSR) was poor for both ICSS (R2 Pred = 0.118, RMSEP = 6.795%) and HFCS (R2 Pred = 0.147, RMSEP = 6.596%) dilutions. This was attributed to an inadequate range of dilution levels in the reference data, as well as the insignificant effect (p < 0.05) of diluent level on the overall variation in the spectral data. The findings of this study highlighted the potential shortcomings of NIR spectroscopy models in providing definite authentication, while demonstrating the capabilities of this technique for authenticity screening.AFRIKAANSE OPSOMMING: Naby-infrarooi (NIR) spekroskopie is gebruik om die effekte van stroop verdunning, veroudering, stoortemperatuur en bestraling behandeling op heuning se NIR spektra te ondersoek. NIR spekroskopie, gekombineer met parsiёle kleinste kwadrate diskriminantanalise (PLS-DA), is ook aangewend om ’n klassifikasie model te ontwikkel wat kan onderskei tussen outentieke heuning en heuning wat met hoё- fruktose mieliestroop (HFCS) of omgekeerde suikerriet stroop (ICSS) verdun is. Bepaling van vorige bestraling behandeling is ook ondersoek, om NIR spekroskopie-gebasseerde modelle te assesseer as ‘n moontlike hulpmiddel vir die identifisering van bedrieglik-geetiketteerde heuning. Rou, ongefiltreerde heuningmonsters (n = 17) verkry van Suid-Afrikaanse byeboere is eenvormig gesyg en met behandelingskombinasies van 10 kGy bestraling en verdunning met 0, 10 en 20% (w/w) ICSS en HFCS onderverdeel (n = 174). Nog drie outentiek en onverdunde deelversamelings is by 4°C, 40°C en in onbeheerde omringende toestande gebêre (n = 51). ’n Laboratorium BÜCHI Fourier-transformasie nabyinfrarooi (FT-NIR) spekrofotometer en ‘n draagbare MicroNIR NIR spekrofotometer, met golflengte reekse van 1000–2500 nm en 908-1676 nm, onderskeidelik, is gebruik om spektra in triplikaat te versamel, oor ’n tydperk van 9 maande. ANOVA-gelyktydige komponentanalise (ASCA) het aangedui dat heuningtipe, verdunningsmiddeltipe, stoortemperatuur en ouderdom beduidende (p > 0.05) effekte op die spektrale datastel het, terwyl verdunningsvlak en bestraling geen beduidende effek het nie. Ten spyte hiervan, is bestraling verantwoordelik vir ‘n 5.82% en 7.19% vermindering van validasie akkuraatheid en doeltreffenheid, onderskeidelik, wanneer PLS-DA modelle wat op bestraalde en onbestraalde spektrale data gebou is, vergelyk is. Dit dui daaraan dat bestraling behandeling, heuning egtheid verifikasie tot ’n mate kan belemmer. Egter kon PLS-DA onderskeiding van bestraling behandeling ’n onsuksesvolle validasie akkuraatheid van slegs 59.7% behaal. Dié resultaat stel voor dat bestraling geen bruikbare effek op die spektrale data het nie. Afsonderlike twee-klas PLS-DA modelle vir ICSS (75.95% akkuraatheid, 86.31% sensitiwiteit) en HFCS (73.95% akkuraatheid, 82.14% sensitiwiteit) verdunningbepaling is as die mees effektiewe verifikasieoplossing bevind, en het voldoende voorspellingskrag vir keuring gedemonstreer. PLS-DA modelle wat op die BÜCHI laboratorium spekrofotometer data gebou is, het beter opgetree as dié wat op die draagbare MicroNIR spekrofotometer, en albei die MicroNIR se monsterhouers, gebaseer is. Ten spyte hiervan, bied die MicroNIR, met die Teflonhouer, soortgelyke akkuraatheid (70.0-75.47%) en doeltreffenheid (68.22- 74.51%) aan, en is dus bewys as ’n haalbare en koste-effektiewe alternatief. Kwantifisering van verdunningsvlak met parsiёle kleinste kwadrate regressie (PLSR) het swak vertoning gewys vir beide ICSS (R2 Pred = 0.118, RMSEP = 6.795%) en HFCS (R2 Pred = 0.147, RMSEP = 6.596%) verdunnings. Hierdie resultaat is toegeskryf aan die onvoldoende verskeidenheid van verdunningsvlakke in die verwysingsdata, asook die onbeduidende (p < 0.05) effek van verdunningsvlak op die algehele variasie van die spektrale data. Die resultate van hierdie studie beklemtoon NIR spekroskopie se moontlike tekortkominge vir die doeleindes van heuning egtheid verifikasie, maar demonstreer ook die geskiktheid van hierdie tegniek vir heuning egtheid keuring.Master

Vapour – liquid equilibria of acetic acid + water and propanoic acid + water: experimental measurement and thermodynamic modelling

Vapour – liquid equilibria were measured for the acetic acid + water and the propanoic acid + water systems, in the temperature range of 412.6 to 483.2 K and pressures of 1.87 to 19.38 bar, over the entire range of concentrations. An experimental apparatus based on the static-analytical method with sampling of both phases was used with quantitative analysis by GC. A new experimental technique comprising positron emission particle tracking (PEPT) was developed and applied for the determination phase compositions and molar volumes for the acetic acid + water system at 412.6 K. The Peng-Robinson (PR), the Cubic Plus Association (CPA), the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) and the PC-polar-SAFT (PCP-SAFT) equations modelled the data. The 1A and 2B association schemes for propanoic acid and the 2B, 3B and 4C for water, were evaluated. In CPA, the ECR and CR1 combining rules were also tested. A single binary interaction parameter was used in all models. PCP-SAFT presented higher predictive and correlative capabilities when the organic acid was modelled as 1A and water as 2B. The best association combination among CPA and PC-SAFT was 2B and 4C for the acid and water, respectively. CR1 accounted for lower errors in predictive mode while ECR in correlative mode. CPA performance was intermediate between the PC-SAFT and PCP-SAFT models and the PR equation. PR predictions were rather poor but correlations were better than those of CPA, at the expense of a larger binary interaction parameter

Development of a quality grading system for the honeybush (Cyclopia spp.) tea industry

Food Scienc