Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes

This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

Quality-aware review selection based on product feature taxonomy

As of today, user-generated information such as online reviews has become increasingly significant for customers in decision making process. Meanwhile, as the volume of online reviews proliferates, there is an insistent demand to help the users tackle the information overload problem. In order to extract useful information from overwhelming reviews, considerable work has been proposed such as review summarization and review selection. Particularly, to avoid the redundant information, researchers attempt to select a small set of reviews to represent the entire review corpus by preserving its statistical properties (e.g., opinion distribution). However, one significant drawback of the existing works is that they only measure the utility of the extracted reviews as a whole without considering the quality of each individual review. As a result, the set of chosen reviews may consist of low-quality ones even its statistical property is close to that of the original review corpus, which is not preferred by the users. In this paper, we proposed a review selection method which takes review quality into consideration during the selection process. Specifically, we examine the relationships between product features based upon a domain ontology to capture the review characteristics based on which to select reviews that have good quality and preserve the opinion distribution as well. Our experimental results based on real world review datasets demonstrate that our proposed approach is feasible and able to improve the performance of the review selection effectively.

A semiautomatic method to identify vertebral end plate lesions (Schmorl's nodes)

Background Context There are differences in definitions of end plate lesions (EPLs), often referred to as Schmorl’s nodes, that may, to some extent, account for the large range of reported prevalence (3.8 to 76%). Purpose To develop a technique to measure the size, prevalence and location of EPLs in a consistent manner. Study Design/Setting This study proposed a method using a detection algorithm which was applied to five adolescent females (average age 15.1 years, range 13.0 to 19.2 years) with idiopathic scoliosis (average major Cobb angle 60°, range 55 to 67°). Methods Existing low-dose, computed tomography scans were segmented semi-automatically to extract 3D morphology of each vertebral endplate. Any remaining attachments to the posterior elements of adjacent vertebrae or endplates were then manually sectioned. An automatic algorithm was used to determine the presence and position of EPLs. Results EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 11/15 of the EPLs were seen in the lumbar spine. The algorithm was found to be most sensitive to changes in the minimum EPL gradient at the edges of the EPL. Conclusions This study describes an imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs. The technique can be used to analyse large populations without observer errors in EPL definitions.

Improving Near-Miss Event Detection Rate at Railway Level Crossings

Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

Identifying vertebral end plate lesions (schmorl's nodes) using a semi-automatic method

INTRODUCTION There is a large range in the reported prevalence of end plate lesions (EPLs), sometimes referred to as Schmorl's nodes in the general population (3.8-76%). One possible reason for this large range is the differences in definitions used by authors. Previous research has suggested that EPLs may potentially be a primary disturbance of growth plates that leads to the onset of scoliosis. The aim of this study was to develop a technique to measure the size, prevalence and location of EPLs on Computed Tomography (CT) images of scoliosis patients in a consistent manner. METHODS A detection algorithm was developed and applied to measure EPLs for five adolescent females with idiopathic scoliosis (average age 15.1 years, average major Cobb 60°). In this algorithm, the EPL definition was based on the lesion depth, the distance from the edge of the vertebral body and the gradient of the lesion edge. Existing low-dose, CT scans of the patients' spines were segmented semi-automatically to extract 3D vertebral endplate morphology. Manual sectioning of any attachments between posterior elements of adjacent vertebrae and, if necessary, endplates was carried out before the automatic algorithm was used to determine the presence and position of EPLs. RESULTS EPLs were identified in 15 of the 170 (8.8%) endplates analysed with an average depth of 3.1mm. 73% of the EPLs were seen in the lumbar spines (11/15). A sensitivity study demonstrated that the algorithm was most sensitive to changes in the minimum gradient required at the lesion edge. CONCLUSION An imaging analysis technique for consistent measurement of the prevalence, location and size of EPLs on CT images has been developed. Although the technique was tested on scoliosis patients, it can be used to analyse other populations without observer errors in EPL definitions.

Specific IgE recognition of pollen allergens from subtropic grasses in patients from the subtropics

Background Pollens of subtropical grasses, Bahia (Paspalum notatum), Johnson (Sorghum halepense), and Bermuda (Cynodon dactylon), are common causes of respiratory allergies in subtropical regions worldwide. Objective To evaluate IgE cross-reactivity of grass pollen (GP) found in subtropical and temperate areas. Methods Case and control serum samples from 83 individuals from the subtropical region of Queensland were tested for IgE reactivity with GP extracts by enzyme-linked immunosorbent assay. A randomly sampled subset of 21 serum samples from patients with subtropical GP allergy were examined by ImmunoCAP and cross-inhibition assays. Results Fifty-four patients with allergic rhinitis and GP allergy had higher IgE reactivity with P notatum and C dactylon than with a mixture of 5 temperate GPs. For 90% of 21 GP allergic serum samples, P notatum, S halepense, or C dactylon specific IgE concentrations were higher than temperate GP specific IgE, and GP specific IgE had higher correlations of subtropical GP (r = 0.771-0.950) than temperate GP (r = 0.317-0.677). In most patients (71%-100%), IgE with P notatum, S halepense, or C dactylon GPs was inhibited better by subtropical GP than temperate GP. When the temperate GP mixture achieved 50% inhibition of IgE with subtropical GP, there was a 39- to 67-fold difference in concentrations giving 50% inhibition and significant differences in maximum inhibition for S halepense and P notatum GP relative to temperate GP. Conclusion Patients living in a subtropical region had species specific IgE recognition of subtropical GP. Most GP allergic patients in Queensland would benefit from allergen specific immunotherapy with a standardized content of subtropical GP allergens.

Total transcriptome, proteome, and allergome of Johnson grass pollen, which is important for allergic rhinitis in subtropical regions

Background Genomic data are lacking for many allergen sources. To circumvent this limitation, we implemented a strategy to reveal the repertoire of pollen allergens of a grass with clinical importance in subtropical regions, where an increasing proportion of the world's population resides. Objective We sought to identify and immunologically characterize the allergenic components of the Panicoideae Johnson grass pollen (JGP; Sorghum halepense). Methods The total pollen transcriptome, proteome, and allergome of JGP were documented. Serum IgE reactivities with pollen and purified allergens were assessed in 64 patients with grass pollen allergy from a subtropical region. Results Purified Sor h 1 and Sor h 13 were identified as clinically important allergen components of JGP with serum IgE reactivity in 49 (76%) and 28 (43.8%), respectively, of patients with grass pollen allergy. Within whole JGP, multiple cDNA transcripts and peptide spectra belonging to grass pollen allergen families 1, 2, 4, 7, 11, 12, 13, and 25 were identified. Pollen allergens restricted to subtropical grasses (groups 22-24) were also present within the JGP transcriptome and proteome. Mass spectrometry confirmed the IgE-reactive components of JGP included isoforms of Sor h 1, Sor h 2, Sor h 13, and Sor h 23. Conclusion Our integrated molecular approach revealed qualitative differences between the allergenic components of JGP and temperate grass pollens. Knowledge of these newly identified allergens has the potential to improve specific diagnosis and allergen immunotherapy treatment for patients with grass pollen allergy in subtropical regions and reduce the burden of allergic respiratory disease globally.

Grass pollen allergens globally: The contribution of subtropical grasses to burden of allergic respiratory diseases

Grass pollens of the temperate (Pooideae) subfamily and subtropical subfamilies of grasses are major aeroallergen sources worldwide. The subtropical Chloridoideae (e.g. Cynodon dactylon; Bermuda grass) and Panicoideae (e.g. Paspalum notatum; Bahia grass) species are abundant in parts of Africa, India, Asia, Australia and the Americas, where a large and increasing proportion of the world's population abide. These grasses are phylogenetically and ecologically distinct from temperate grasses. With the advent of global warming, it is conceivable that the geographic distribution of subtropical grasses and the contribution of their pollen to the burden of allergic rhinitis and asthma will increase. This review aims to provide a comprehensive synthesis of the current global knowledge of (i) regional variation in allergic sensitivity to subtropical grass pollens, (ii) molecular allergenic components of subtropical grass pollens and (iii) allergic responses to subtropical grass pollen allergens in relevant populations. Patients from subtropical regions of the world show higher allergic sensitivity to grass pollens of Chloridoideae and Panicoideae grasses, than to temperate grass pollens. The group 1 allergens are amongst the allergen components of subtropical grass pollens, but the group 5 allergens, by which temperate grass pollen extracts are standardized for allergen content, appear to be absent from both subfamilies of subtropical grasses. Whilst there are shared allergenic components and antigenic determinants, there are additional clinically relevant subfamily-specific differences, at T- and B-cell levels, between pollen allergens of subtropical and temperate grasses. Differential immune recognition of subtropical grass pollens is likely to impact upon the efficacy of allergen immunotherapy of patients who are primarily sensitized to subtropical grass pollens. The literature reviewed herein highlights the clinical need to standardize allergen preparations for both types of subtropical grass pollens to achieve optimal diagnosis and treatment of patients with allergic respiratory disease in subtropical regions of the world. © 2014 John Wiley & Sons Ltd.

Purification of the major group 1 allergen from bahia grass pollen, Pas n 1

Background Group 1 grass pollen allergens are glycoproteins of the β-expansin family. They are a predominant component of pollen and are potent allergens with a high frequency of serum IgE reactivity in grass pollen-allergic patients. Bahia grass is distinct from temperate grasses and has a prolonged pollination period and wide distribution in warmer climates. Here we describe the purification of the group 1 pollen allergen, Pas n 1, from Bahia grass (Paspalum notatum), an important subtropical aeroallergen source. Methods Pas n 1 was purified from an aqueous Bahia grass pollen extract by ammonium sulphate precipitation, hydrophobic interaction and size exclusion chromatography, and assessed by one- and two-dimensional gel electrophoresis, immunoblotting and ELISA. Results Pas n 1 was purified to a single 29-kDa protein band containing two dominant isoforms detected by an allergen-specific monoclonal antibody and serum IgE of a Bahia grass pollen-allergic donor. The frequency of serum IgE reactivity with purified Pas n 1 in 51 Bahia grass pollen-allergic patients was 90.6%. Serum IgE reactivity with purified Pas n 1 was highly correlated with serum IgE reactivity with Bahia grass pollen extract and recombinant Pas n 1 (r = 0.821 and 0.913, respectively). Conclusions Pas n 1 is a major allergen reactive at high frequency with serum IgE of Bahia grass pollen-allergic patients. Purified natural Pas n 1 has utility for improved specific diagnosis and immunotherapy for Bahia grass pollen allergy.

The dominant 55kDa allergen of the subtropical Bahia grass (Paspalum notatum) pollen is a group 13 pollen allergen, Pas n 13

Bahia grass, Paspalum notatum, is an important pollen allergen source with a long season of pollination and wide distribution in subtropical and temperate regions. We aimed to characterize the 55. kDa allergen of Bahia grass pollen (BaGP) and ascertain its clinical importance. BaGP extract was separated by 2D-PAGE and immunoblotted with serum IgE of a grass pollen-allergic patient. The amino-terminal protein sequence of the predominant allergen isoform at 55. kDa had similarity with the group 13 allergens of Timothy grass and maize pollen, Phl p 13 and Zea m 13. Four sequences obtained by rapid amplification of the allergen cDNA ends represented multiple isoforms of Pas n 13. The predicted full length cDNA for Pas n 13 encoded a 423 amino acid glycoprotein including a signal peptide of 28 residues and with a predicted pI of 7.0. Tandem mass spectrometry of tryptic peptides of 2D gel spots identified peptides specific to the deduced amino acid sequence for each of the four Pas n 13 cDNA, representing 47% of the predicted mature protein sequence of Pas n 13. There was 80.6% and 72.6% amino acid identity with Zea m 13 and Phl p 13, respectively. Reactivity with a Phl p 13-specific monoclonal antibody AF6 supported designation of this allergen as Pas n 13. The allergen was purified from BaGP extract by ammonium sulphate precipitation, hydrophobic interaction and size exclusion chromatography. Purified Pas n 13 reacted with serum IgE of 34 of 71 (48%) grass pollen-allergic patients and specifically inhibited IgE reactivity with the 55. kDa band of BaGP for two grass pollen-allergic donors. Four isoforms of Pas n 13 from pI 6.3-7.8 had IgE-reactivity with grass pollen allergic sera. The allergenic activity of purified Pas n 13 was demonstrated by activation of basophils from whole blood of three grass pollen-allergic donors tested but not control donors. Pas n 13 is thus a clinically relevant pollen allergen of the subtropical Bahia grass likely to be important in eliciting seasonal allergic rhinitis and asthma in grass pollen-allergic patients.

Functional immunoglobulin E cross-reactivity between Pas n 1 of Bahia grass pollen and other group 1 grass pollen allergens

Background Grass pollens are major triggers of allergic rhinitis and asthma, but the immunological relationships between pollen allergens of the subtropical Bahia grass, Paspalum notatum, and temperate grasses are unresolved. Objective To assess serum IgE cross-reactivity between subtropical P. notatum and temperate Lolium perenne (Ryegrass) pollen allergens. Methods Serum IgE reactivities of grass pollen-allergic patients with P. notatum, L. perenne and Cynodon dactylon (Bermuda grass) pollen extracts and their respective purified group 1 allergens, Pas n 1, Lol p 1 and Cyn d 1, were compared by immunoblotting, ELISA and basophil activation. Results In a cohort of 51 patients from a temperate region, a high frequency of IgE reactivity with each grass pollen was detected, but reactivity with L. perenne pollen was substantially greater than with P. notatum and C. dactylon pollen. Similarly, serum IgE reactivity with Lol p 1 was greater than with Pas n 1 or Cyn d 1. For seven of eight sera studied in detail, asymmetric serum IgE cross-reactivity was observed; L. perenne pollen inhibited IgE reactivity with P. notatum pollen but not the converse, and IgE reactivity with Pas n 1 was inhibited by Lol p 1 but IgE reactivity with Lol p 1 was not inhibited by Pas n 1 or Cyn d 1. Importantly, P. notatum pollen and Pas n 1 activated basophils in grass pollen-allergic patients from a temperate region, although stimulation was greater by pollen of L. perenne than P. notatum or C. dactylon, and by Lol p 1 than Pas n 1 or Cyn d 1. In contrast, a cohort of 47 patients from a subtropical region showed similar IgE reactivity with P. notatum and L. perenne pollen, and reciprocal cross-inhibition of IgE reactivity between L. perenne and P. notatum. Conclusions Pollen allergens of the subtropical P. notatum, including Pas n 1, show clinically relevant IgE cross-reactivity with pollen allergens of L. perenne but also species-specific IgE reactivity.

Molecular cloning, expression and immunological characterisation of Pas n 1, the major allergen of Bahia grass Paspalum notatum pollen

Bahia grass, Paspalum notatum, is a clinically important subtropical grass with a prolonged pollination season from spring to autumn. We aimed to clone and characterise the major Bahia grass pollen allergen, Pas n 1. Grass pollen-allergic patients presenting to a tertiary hospital allergy clinic were tested for IgE reactivity with Bahia grass pollen extract by skin prick testing, ImmunoCAP, ELISA and immunoblotting. Using primers deduced from the N-terminal peptide sequence of a group 1 allergen of Bahia grass pollen extract separated by two-dimensional gel electrophoresis, the complete Pas n 1 cDNA was obtained by rapid amplification of cDNA ends and cloned. Biological relevance of recombinant Pas n 1 expressed in Escherichia coli was assessed by serum IgE reactivity and basophil activation. Twenty-nine of 34 (85%) consecutive patients presenting with grass pollen allergy were skin prick test positive to Bahia grass pollen. The Pas n 1 cDNA has sequence homology with the β-expansin 1 glycoprotein family and is more closely related to the maize pollen group 1 allergen (85% identity) than to ryegrass Lol p 1 or Timothy grass Phl p 1 (64 and 66% identity, respectively). rPas n 1 reacted with serum IgE in 47 of 55 (85%) Bahia grass pollen-allergic patients, activated basophils and inhibited serum IgE reactivity with the 29 kDa band of Bahia grass pollen extract. In conclusion the cDNA for the major group 1 allergen of the subtropical Bahia grass pollen, Pas n 1, was identified and cloned. rPas n 1 is immunologically active and is a valuable reagent for diagnosis and specific immunotherapy of grass pollen allergy.

A novel grass pollen allergen mimotope identified by phage display peptide library inhibits allergen-human IgE antibody interaction

The aim of this study was to investigate the molecular basis of human IgE-allergen interaction by screening a phage-displayed peptide library with an allergen-specific human IgE-mimicking monoclonal antibody (mAb). A mAb that reacted with major grass pollen allergens was successfully identified and shown to inhibit human IgE-allergen interaction. Biopanning of a phage-displayed random peptide library with this mAb yielded a 12 amino acid long mimotope. A synthetic peptide based on this 12-mer mimotope inhibited mAb and human IgE binding to grass pollen extracts. Our results indicate that such synthetic peptide mimotopes of allergens have potential as novel therapeutic agents. © 2001 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

A rapid and efficient two-step gel electrophoresis method for the purification of major rye grass pollen allergens

Purified proteins are mandatory for molecular, immunological and cellular studies. However, purification of proteins from complex mixtures requires specialised chromatography methods (i.e., gel filtration, ion exchange, etc.) using fast protein liquid chromatography (FPLC) or high-performance liquid chromatography (HPLC) systems. Such systems are expensive and certain proteins require two or more different steps for sufficient purity and generally result in low recovery. The aim of this study was to develop a rapid, inexpensive and efficient gel-electrophoresis-based protein purification method using basic and readily available laboratory equipment. We have used crude rye grass pollen extract to purify the major allergens Lol p 1 and Lol p 5 as the model protein candidates. Total proteins were resolved on large primary gel and Coomassie Brilliant Blue (CBB)-stained Lol p 1/5 allergens were excised and purified on a secondary "mini"-gel. Purified proteins were extracted from unstained separating gels and subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblot analyses. Silver-stained SDS-PAGE gels resolved pure proteins (i.e., 875 μg of Lol p 1 recovered from a 8 mg crude starting material) while immunoblot analysis confirmed immunological reactivity of the purified proteins. Such a purification method is rapid, inexpensive, and efficient in generating proteins of sufficient purity for use in monoclonal antibody (mAb) production, protein sequencing and general molecular, immunological, and cellular studies.

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.