Hide-and-seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence

Ecology and conservation require reliable data on the occurrence of animals and plants. A major source of bias is imperfect detection, which, however, can be corrected for by estimation of detectability. In traditional occupancy models, this requires repeat or multi-observer surveys. Recently, time-to-detection models have been developed as a cost-effective alternative, which requires no repeat surveys and hence costs could be halved. We compared the efficiency and reliability of time-to-detection and traditional occupancy models under varying survey effort. Two observers independently searched for 17 plant species in 44100m(2) Swiss grassland quadrats and recorded the time-to-detection for each species, enabling detectability to be estimated with both time-to-detection and traditional occupancy models. In addition, we gauged the relative influence on detectability of species, observer, plant height and two measures of abundance (cover and frequency). Estimates of detectability and occupancy under both models were very similar. Rare species were more likely to be overlooked; detectability was strongly affected by abundance. As a measure of abundance, frequency outperformed cover in its predictive power. The two observers differed significantly in their detection ability. Time-to-detection models were as accurate as traditional occupancy models, but their data easier to obtain; thus they provide a cost-effective alternative to traditional occupancy models for detection-corrected estimation of occurrence.

Confusion over live/dead stainings for the detection of vital microorganisms in oral biofilms--which stain is suitable?

BACKGROUND There is confusion over the definition of the term "viability state(s)" of microorganisms. "Viability staining" or "vital staining techniques" are used to distinguish live from dead bacteria. These stainings, first established on planctonic bacteria, may have serious shortcomings when applied to multispecies biofilms. Results of staining techniques should be compared with appropriate microbiological data. DISCUSSION Many terms describe "vitality states" of microorganisms, however, several of them are misleading. Authors define "viable" as "capable to grow". Accordingly, staining methods are substitutes, since no staining can prove viability.The reliability of a commercial "viability" staining assay (Molecular Probes) is discussed based on the corresponding product information sheet: (I) Staining principle; (II) Concentrations of bacteria; (III) Calculation of live/dead proportions in vitro. Results of the "viability" kit are dependent on the stains' concentration and on their relation to the number of bacteria in the test. Generally this staining system is not suitable for multispecies biofilms, thus incorrect statements have been published by users of this technique.To compare the results of the staining with bacterial parameters appropriate techniques should be selected. The assessment of Colony Forming Units is insufficient, rather the calculation of Plating Efficiency is necessary. Vital fluorescence staining with Fluorescein Diacetate and Ethidium Bromide seems to be the best proven and suitable method in biofilm research.Regarding the mutagenicity of staining components users should be aware that not only Ethidium Bromide might be harmful, but also a variety of other substances of which the toxicity and mutagenicity is not reported. SUMMARY - The nomenclature regarding "viability" and "vitality" should be used carefully.- The manual of the commercial "viability" kit itself points out that the kit is not suitable for natural multispecies biofilm research, as supported by an array of literature.- Results obtained with various stains are influenced by the relationship between bacterial counts and the amount of stain used in the test. Corresponding vitality data are prone to artificial shifting.- As microbiological parameter the Plating Efficiency should be used for comparison.- Ethidium Bromide is mutagenic. Researchers should be aware that alternative staining compounds may also be or even are mutagenic.

Unified detection and tracking of instruments during retinal microsurgery

Methods for tracking an object have generally fallen into two groups: tracking by detection and tracking through local optimization. The advantage of detection-based tracking is its ability to deal with target appearance and disappearance, but it does not naturally take advantage of target motion continuity during detection. The advantage of local optimization is efficiency and accuracy, but it requires additional algorithms to initialize tracking when the target is lost. To bridge these two approaches, we propose a framework for unified detection and tracking as a time-series Bayesian estimation problem. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a target in each frame. To do this we integrate the Active Testing (AT) paradigm with Bayesian filtering, and this results in a framework capable of both detecting and tracking robustly in situations where the target object enters and leaves the field of view regularly. We demonstrate our approach on a retinal tool tracking problem and show through extensive experiments that our method provides an efficient and robust tracking solution.

Reliable LC3 and p62 autophagy marker detection in formalin fixed paraffin embedded human tissue by immunohistochemistry

Autophagy assures cellular homeostasis, and gains increasing importance in cancer, where it impacts on carcinogenesis, propagation of the malignant phenotype and development of resistance. To date, its tissue-based analysis by immunohistochemistry remains poorly standardized. Here we show the feasibility of specifically and reliably assessing the autophagy markers LC3B and p62 (SQSTM1) in formalin fixed and paraffin embedded human tissue by immunohistochemistry. Preceding functional experiments consisted of depleting LC3B and p62 in H1299 lung cancer cells with subsequent induction of autophagy. Western blot and immunofluorescence validated antibody specificity, knockdown efficiency and autophagy induction prior to fixation in formalin and embedding in paraffin. LC3B and p62 antibodies were validated on formalin fixed and paraffin embedded cell pellets of treated and control cells and finally applied on a tissue microarray with 80 human malignant and non-neoplastic lung and stomach formalin fixed and paraffin embedded tissue samples. Dot-like staining of various degrees was observed in cell pellets and 18/40 (LC3B) and 22/40 (p62) tumors, respectively. Seventeen tumors were double positive for LC3B and p62. P62 displayed additional significant cytoplasmic and nuclear staining of unknown significance. Interobserver-agreement for grading of staining intensities and patterns was substantial to excellent (kappa values 0.60 - 0.83). In summary, we present a specific and reliable IHC staining of LC3B and p62 on formalin fixed and paraffin embedded human tissue. Our presented protocol is designed to aid reliable investigation of dysregulated autophagy in solid tumors and may be used on large tissue collectives.

CopywriteR: DNA copy number detection from off-target sequence data.

Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting 'off-target' sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.

Scintillation efficiency of liquid argon in low energy neutron-argon scattering

Experiments searching for weak interacting massive particles with noble gases such as liquid argon require very low detection thresholds for nuclear recoils. A determination of the scintillation efficiency is crucial to quantify the response of the detector at low energy. We report the results obtained with a small liquid argon cell using a monoenergetic neutron beam produced by a deuterium-deuterium fusion source. The light yield relative to electrons was measured for six argon recoil energies between 11 and 120 keV at zero electric drift field.

Multi-resolution model-based traffic sign detection and tracking

In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.

Relevance of the glottal pulse and the vocal tract in gender detection

Gender detection is a very important objective to improve efficiency in tasks as speech or speaker recognition, among others. Traditionally gender detection has been focused on fundamental frequency (f0) and cepstral features derived from voiced segments of speech. The methodology presented here consists in obtaining uncorrelated glottal and vocal tract components which are parameterized as mel-frequency coefficients. K-fold and cross-validation using QDA and GMM classifiers showed that better detection rates are reached when glottal source and vocal tract parameters are used in a gender-balanced database of running speech from 340 speakers.

In silico detection of control signals: mRNA 3′-end-processing sequences in diverse species

We have investigated mRNA 3′-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3′-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3′-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3′-end-processing signals will require more than consensus sequence identification.

Optimizing the detection of nascent transcripts by RNA fluorescence in situ hybridization

An unusual feature of the mammalian genome is the number of genes exhibiting monoallelic expression. Recently random monoallelic expression of autosomal genes has been reported for olfactory and Ly-49 NK receptor genes, as well as for Il-2, Il-4 and Pax5. RNA fluorescence in situ hybridization (FISH) has been exploited to monitor allelic expression by visualizing the number of sites of transcription in individual nuclei. However, the sensitivity of this technique is difficult to determine for a given gene. We show that by combining DNA and RNA FISH it is possible to control for the hybridization efficiency and the accessibility and visibility of fluorescent probes within the nucleus.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.

Optimized Decoding for Auditory Attention Detection

Thesis (Master's)--University of Washington, 2016-06

Modeling of optical detection of spin-polarized carrier injection into light-emitting devices

We investigate the emission of multimodal polarized light from light emitting devices due to spin-aligned carrier injection. The results are derived through operator Langevin equations, which include thermal and carrier-injection fluctuations, as well as nonradiative recombination and electronic g-factor temperature dependence. We study the dynamics of the optoelectronic processes and show how the temperature-dependent g factor and magnetic field affect the degree of polarization of the emitted light. In addition, at high temperatures, thermal fluctuation reduces the efficiency of the optoelectronic detection method for measuring the degree of spin polarization of carrier injection into nonmagnetic semicondutors.

Improving the efficiency of wildlife monitoring by estimating detectability: a case study of foxes (Vulpes vulpes) on the Eyre Peninsula, South Australia

Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low (< 18%) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.