Detecting rare events using Kullback-Leibler divergence: A weakly supervised approach

Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

Use of non-specific and specific interactions in the analysis of testosterone and related compounds by capillary electromigration techniques

Determination of testosterone and related compounds in body fluids is of utmost importance in doping control and the diagnosis of many diseases. Capillary electromigration techniques are a relatively new approach for steroid research. Owing to their electrical neutrality, however, separation of steroids by capillary electromigration techniques requires the use of charged electrolyte additives that interact with the steroids either specifically or non-specifically. The analysis of testosterone and related steroids by non-specific micellar electrokinetic chromatography (MEKC) was investigated in this study. The partial filling (PF) technique was employed, being suitable for detection by both ultraviolet spectrophotometry (UV) and electrospray ionization mass spectrometry (ESI-MS). Efficient, quantitative PF-MEKC UV methods for steroid standards were developed through the use of optimized pseudostationary phases comprising surfactants and cyclodextrins. PF-MEKC UV proved to be a more sensitive, efficient and repeatable method for the steroids than PF-MEKC ESI-MS. It was discovered that in PF-MEKC analyses of electrically neutral steroids, ESI-MS interfacing sets significant limitations not only on the chemistry affecting the ionization and detection processes, but also on the separation. The new PF-MEKC UV method was successfully employed in the determination of testosterone in male urine samples after microscale immunoaffinity solid-phase extraction (IA-SPE). The IA-SPE method, relying on specific interactions between testosterone and a recombinant anti-testosterone Fab fragment, is the first such method described for testosterone. Finally, new data for interactions between steroids and human and bovine serum albumins were obtained through the use of affinity capillary electrophoresis. A new algorithm for the calculation of association constants between proteins and neutral ligands is introduced.

Development of a Multiplexed Bead-Based Suspension Array for the Detection and Discrimination of Pospiviroid Plant Pathogens

Efficient and reliable diagnostic tools for the routine indexing and certification of clean propagating material are essential for the management of pospiviroid diseases in horticultural crops. This study describes the development of a true multiplexed diagnostic method for the detection and identification of all nine currently recognized pospiviroid species in one assay using Luminex bead-based suspension array technology. In addition, a new data-driven, statistical method is presented for establishing thresholds for positivity for individual assays within multiplexed arrays. When applied to the multiplexed array data generated in this study, the new method was shown to have better control of false positives and false negative results than two other commonly used approaches for setting thresholds. The 11-plex Luminex MagPlex-TAG pospiviroid array described here has a unique hierarchical assay design, incorporating a near-universal assay in addition to nine species-specific assays, and a co-amplified plant internal control assay for quality assurance purposes. All assays of the multiplexed array were shown to be 100% specific, sensitive and reproducible. The multiplexed array described herein is robust, easy to use, displays unambiguous results and has strong potential for use in routine pospiviroid indexing to improve disease management strategies.

Chemical mass closure and source-specific composition of atmospheric particles

It has been known for decades that particles can cause adverse health effects as they are deposited within the respiratory system. Atmospheric aerosol particles influence climate by scattering solar radiation but aerosol particles act also as the nuclei around which cloud droplets form. The principal objectives of this thesis were to investigate the chemical composition and the sources of fine particles in different environments (traffic, urban background, remote) as well as during some specific air pollution situations. Quantifying the climate and health effects of atmospheric aerosols is not possible without detailed information of the aerosol chemical composition. Aerosol measurements were carried out at nine sites in six countries (Finland, Germany, Czech, Netherlands, Greece and Italy). Several different instruments were used in order to measure both the particulate matter (PM) mass and its chemical composition. In the off-line measurements the samples were collected first on a substrate or filter and gravimetric and chemical analysis were conducted in the laboratory. In the on-line measurements the sampling and analysis were either a combined procedure or performed successively within the same instrument. Results from the impactor samples were analyzed by the statistical methods. This thesis comprises also a work where a method for the determination carbonaceous matter size distribution by using a multistage impactor was developed. It was found that the chemistry of PM has usually strong spatial, temporal and size-dependent variability. In the Finnish sites most of the fine PM consisted of organic matter. However, in Greece sulfate dominated the fine PM and in Italy nitrate made the largest contribution to the fine PM. Regarding the size-dependent chemical composition, organic components were likely to be enriched in smaller particles than inorganic ions. Data analysis showed that organic carbon (OC) had four major sources in Helsinki. Secondary production was the major source in Helsinki during spring, summer and fall, whereas in winter biomass combustion dominated OC. The significant impact of biomass combustion on OC concentrations was also observed in the measurements performed in Central Europe. In this thesis aerosol samples were collected mainly by the conventional filter and impactor methods which suffered from the long integration time. However, by filter and impactor measurements chemical mass closure was achieved accurately, and a simple filter sampling was found to be useful in order to explain the sources of PM on the seasonal basis. The online instruments gave additional information related to the temporal variations of the sources and the atmospheric mixing conditions.

Panel of real-time PCRs for the multiplexed detection of two tomato-infecting begomoviruses and their cognate whitefly vector species

A new approach for the simultaneous identification of the viruses and vectors responsible for tomato yellow leaf curl disease (TYLCD) epidemics is presented. A panel of quantitative multiplexed real-time PCR assays was developed for the sensitive and reliable detection of Tomato yellow leaf curl virus-Israel (TYLCV-IL), Tomato leaf curl virus (ToLCV), Bemisia tabaci Middle East Asia Minor 1 species (MEAM1, B biotype) and B.tabaci Mediterranean species (MED, Q biotype) from either plant or whitefly samples. For quality-assurance purposes, two internal control assays were included in the assay panel for the co-amplification of solanaceous plant DNA or B.tabaci DNA. All assays were shown to be specific and reproducible. The multiplexed assays were able to reliably detect as few as 10 plasmid copies of TYLCV-IL, 100 plasmid copies of ToLCV, 500fg B.tabaci MEAM1 and 300fg B.tabaci MED DNA. Evaluated methods for routine testing of field-collected whiteflies are presented, including protocols for processing B.tabaci captured on yellow sticky traps and for bulking of multiple B.tabaci individuals prior to DNA extraction. This work assembles all of the essential features of a validated and quality-assured diagnostic method for the identification and discrimination of tomato-infecting begomovirus and B.tabaci vector species in Australia. This flexible panel of assays will facilitate improved quarantine, biosecurity and disease-management programmes both in Australia and worldwide.

"Hear O Israel" Commemorative Medal

Obverse: Stylized inscription in Hebrew. Reverse: Inscription in English.

Eine deutsche juedische Familie wird zerstreut : die Geschichte eines Steinitz-Zweiges /

Bibliography : p. 144-148.

Chinese Street

A frieze-like composition depicting storefronts with mixed English and Chinese language signs, as well as activities of shopkeepers and shoppers.

Crop design for specific adaptation in variable dryland production environments

Climatic variability in dryland production environments (E) generates variable yield and crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement seeks broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in response to average local environmental conditions. This process does not search the full spectrum of potential G × M × E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional, broad adaptation approach) of exploiting specific adaptation arising from G × M × E. We present an in-silico analysis for sorghum production in Australia using the APSIM sorghum model. Crop design (G × M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic subregions that have frequencies of major environment types substantially different from that for the entire production region show greatest advantage for specific adaptation. Although the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment-type likelihood than that conferred by location alone.