Influential DMUs and outlier detection in data envelopment analysis with an application to health care

This paper explains some drawbacks on previous approaches for detecting influential observations in deterministic nonparametric data envelopment analysis models as developed by Yang et al. (Annals of Operations Research 173:89-103, 2010). For example efficiency scores and relative entropies obtained in this model are unimportant to outlier detection and the empirical distribution of all estimated relative entropies is not a Monte-Carlo approximation. In this paper we developed a new method to detect whether a specific DMU is truly influential and a statistical test has been applied to determine the significance level. An application for measuring efficiency of hospitals is used to show the superiority of this method that leads to significant advancements in outlier detection. © 2014 Springer Science+Business Media New York.

Phylogenetic and ecological significance in the evolution of Cetacean tonal sounds

Cetaceans are aquatic mammals that rely primarily on sound for most daily tasks. A compendium of sounds is emitted for orientation, prey detection, and predator avoidance, and to communicate. Communicative sounds are among the most studied Cetacean signals, particularly those referred to as tonal sounds. Because tonal sounds have been studied especially well in social dolphins, it has been assumed these sounds evolved as a social adaptation. However, whistles have been reported in ‘solitary’ species and have been secondarily lost three times in social lineages. Clearly, therefore, it is necessary to examine closely the association, if any, between whistles and sociality instead of merely assuming it. Several hypotheses have been proposed to explain the evolutionary history of Cetacean tonal sounds. The main goal of this dissertation is to cast light on the evolutionary history of tonal sounds by testing these hypotheses by combining comparative phylogenetic and field methods. This dissertation provides the first species-level phylogeny of Cetacea and phylogenetic tests of evolutionary hypotheses of cetacean communicative signals. Tonal sounds evolution is complex in that has likely been shaped by a combination of factors that may influence different aspects of their acoustical structure. At the inter-specific level, these results suggest that only tonal sound minimum frequency is constrained by body size. Group size also influences tonal sound minimum frequency. Species that live in large groups tend to produce higher frequency tonal sounds. The evolutionary history of tonal sounds and sociality may be intertwined, but in a complex manner rejecting simplistic views such as the hypothesis that tonal sounds evolved ‘for’ social communication in dolphins. Levels of social and tonal sound complexity nevertheless correlate indicating the importance of tonal sounds in social communication. At the intraspecific level, tonal sound variation in frequency and temporal parameters may be product of genetic isolation and local levels of underwater noise. This dissertation provides one of the first insights into the evolution of Cetacean tonal sounds in a phylogenetic context, and points out key species where future studies would be valuable to enrich our understanding of other factors also playing a role in tonal sound evolution. ^

Phylogenetic and Ecological Significance in the Evolution of Cetacean Tonal Sounds

Cetaceans are aquatic mammals that rely primarily on sound for most daily tasks. A compendium of sounds is emitted for orientation, prey detection, and predator avoidance, and to communicate. Communicative sounds are among the most studied Cetacean signals, particularly those referred to as tonal sounds. Because tonal sounds have been studied especially well in social dolphins, it has been assumed these sounds evolved as a social adaptation. However, whistles have been reported in ‘solitary’ species and have been secondarily lost three times in social lineages. Clearly, therefore, it is necessary to examine closely the association, if any, between whistles and sociality instead of merely assuming it. Several hypotheses have been proposed to explain the evolutionary history of Cetacean tonal sounds. The main goal of this dissertation is to cast light on the evolutionary history of tonal sounds by testing these hypotheses by combining comparative phylogenetic and field methods. This dissertation provides the first species-level phylogeny of Cetacea and phylogenetic tests of evolutionary hypotheses of cetacean communicative signals. Tonal sounds evolution is complex in that has likely been shaped by a combination of factors that may influence different aspects of their acoustical structure. At the inter-specific level, these results suggest that only tonal sound minimum frequency is constrained by body size. Group size also influences tonal sound minimum frequency. Species that live in large groups tend to produce higher frequency tonal sounds. The evolutionary history of tonal sounds and sociality may be intertwined, but in a complex manner rejecting simplistic views such as the hypothesis that tonal sounds evolved ‘for’ social communication in dolphins. Levels of social and tonal sound complexity nevertheless correlate indicating the importance of tonal sounds in social communication. At the intraspecific level, tonal sound variation in frequency and temporal parameters may be product of genetic isolation and local levels of underwater noise. This dissertation provides one of the first insights into the evolution of Cetacean tonal sounds in a phylogenetic context, and points out key species where future studies would be valuable to enrich our understanding of other factors also playing a role in tonal sound evolution.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Early detection of delirium in older medical inpatients: prodrome, predictors and motor subtyping

Background Delirium is highly prevalent, especially in older patients. It independently leads to adverse outcomes, but remains under-detected, particularly hypoactive forms. Although early identification and intervention is important, delirium prevention is key to improving outcomes. The delirium prodrome concept has been mooted for decades, but remains poorly characterised. Greater understanding of this prodrome would promote prompt identification of delirium-prone patients, and facilitate improved strategies for delirium prevention and management. Methods Medical inpatients of ≥70 years were screened for prevalent delirium using the Revised Delirium Rating Scale (DRS--‐R98). Those without prevalent delirium were assessed daily for delirium development, prodromal features and motor subtype. Survival analysis models identified which prodromal features predicted the emergence of incident delirium in the cohort in the first week of admission. The Delirium Motor Subtype Scale-4 was used to ascertain motor subtype. Results Of 555 patients approached, 191 patients were included in the prospective study. The median age was 80 (IQR 10) and 101 (52.9%) were male. Sixty-one patients developed incident delirium within a week of admission. Several prodromal features predicted delirium emergence in the cohort. Firstly, using a novel Prodromal Checklist based on the existing literature, and controlling for confounders, seven predictive behavioural features were identified in the prodromal period (for example, increasing confusion; and being easily distractible). Additionally, using serial cognitive tests and the DRS-R98 daily, multiple cognitive and other core delirium features were detected in the prodrome (for example inattention; and sleep-wake cycle disturbance). Examining longitudinal motor subtypes in delirium cases, subtypes were found to be predominantly stable over time, the most prevalent being hypoactive subtype (62.3%). Discussion This thesis explored multiple aspects of delirium in older medical inpatients, with particular focus on the characterisation of the delirium prodrome. These findings should help to inform future delirium educational programmes, and detection and prevention strategies.

Enzyme-induced Aggregation of Plasmonic Nanoparticles for the Development of Label-free and Ultrasensitive Detection of Bacterial DNA

Sensitive detection of pathogens is critical to ensure the safety of food supplies and to prevent bacterial disease infection and outbreak at the first onset. While conventional techniques such as cell culture, ELISA, PCR, etc. have been used as the predominant detection workhorses, they are however limited by either time-consuming procedure, complicated sample pre-treatment, expensive analysis and operation, or inability to be implemented at point-of-care testing. Here, we present our recently developed assay exploiting enzyme-induced aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. In the experiments, AuNPs are first functionalized with specific, single-stranded RNA probes so that they exhibit high stability in solution even under high electrolytic condition thus exhibiting red color. When bacterial DNA is present in a sample, a DNA-RNA heteroduplex will be formed and subsequently prone to the RNase H cleavage on the RNA probe, allowing the DNA to liberate and hybridize with another RNA strand. This continuously happens until all of the RNA strands are cleaved, leaving the nanoparticles ‘unprotected’. The addition of NaCl will cause the ‘unprotected’ nanoparticles to aggregate, initiating a colour change from red to blue. The reaction is performed in a multi-well plate format, and the distinct colour signal can be discriminated by naked eye or simple optical spectroscopy. As a result, bacterial DNA as low as pM could be unambiguously detected, suggesting that the enzyme-induced aggregation of AuNPs assay is very easy to perform and sensitive, it will significantly benefit to development of fast and ultrasensitive methods that can be used for disease detection and diagnosis.

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Sensing parasites: proteomic and advanced bio-detection alternatives

[EN] Parasitic diseases have a great impact in human and animal health. The gold standard for the diagnosis of the majority of parasitic infections is still conventional microscopy, which presents important limitations in terms of sensitivity and specificity and commonly requires highly trained technicians. More accurate molecular-based diagnostic tools are needed for the implementation of early detection, effective treatments and massive screenings with high-throughput capacities. In this respect, sensitive and affordable devices could greatly impact on sustainable control programmes which exist against parasitic diseases, especially in low income settings. Proteomics and nanotechnology approaches are valuable tools for sensing pathogens and host alteration signatures within micro fluidic detection platforms. These new devices might provide novel solutions to fight parasitic diseases. Newly described specific parasite derived products with immune-modulatory properties have been postulated as the best candidates for the early and accurate detection of parasitic infections as well as for the blockage of parasite development. This review provides the most recent methodological and technological advances with great potential for biosensing parasites in their hosts, showing the newest opportunities offered by modern “-omics” and platforms for parasite detection and control.

Optical redox ratio and endogenous porphyrins in the detection of urinary bladder cancer:a patient biopsy analysis

Bladder cancer is among the most common cancers in the UK and conventional detection techniques suffer from low sensitivity, low specificity, or both. Recent attempts to address the disparity have led to progress in the field of autofluorescence as a means to diagnose the disease with high efficiency, however there is still a lot not known about autofluorescence profiles in the disease. The multi-functional diagnostic system "LAKK-M" was used to assess autofluorescence profiles of healthy and cancerous bladder tissue to identify novel biomarkers of the disease. Statistically significant differences were observed in the optical redox ratio (a measure of tissue metabolic activity), the amplitude of endogenous porphyrins and the NADH/porphyrin ratio between tissue types. These findings could advance understanding of bladder cancer and aid in the development of new techniques for detection and surveillance.

Detection of African Swine Fever Virus Antibodies in Serum and Oral Fluid Specimens Using a Recombinant Protein 30 (p30) Dual Matrix Indirect ELISA

In the absence of effective vaccine(s), control of African swine fever caused by African swine fever virus (ASFV) must be based on early, efficient, cost-effective detection and strict control and elimination strategies. For this purpose, we developed an indirect ELISA capable of detecting ASFV antibodies in either serum or oral fluid specimens. The recombinant protein used in the ELISA was selected by comparing the early serum antibody response of ASFV-infected pigs (NHV-p68 isolate) to three major recombinant polypeptides (p30, p54, p72) using a multiplex fluorescent microbead-based immunoassay (FMIA). Non-hazardous (non-infectious) antibody-positive serum for use as plate positive controls and for the calculation of sample-to-positive (S:P) ratios was produced by inoculating pigs with a replicon particle (RP) vaccine expressing the ASFV p30 gene. The optimized ELISA detected anti-p30 antibodies in serum and/or oral fluid samples from pigs inoculated with ASFV under experimental conditions beginning 8 to 12 days post inoculation. Tests on serum (n = 200) and oral fluid (n = 200) field samples from an ASFV-free population demonstrated that the assay was highly diagnostically specific. The convenience and diagnostic utility of oral fluid sampling combined with the flexibility to test either serum or oral fluid on the same platform suggests that this assay will be highly useful under the conditions for which OIE recommends ASFV antibody surveillance, i.e., in ASFV-endemic areas and for the detection of infections with ASFV isolates of low virulence.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.

DETECTION OF SPORES AND HYPHAE OF ARTWORKS’ BIODETERIOGENIC FILAMENTOUS FUNGI BY RNA-FISH

Filamentous fungi are a threat to the conservation of Cultural Heritage. Thus, detection and identification of viable filamentous fungi are crucial for applying adequate Safeguard measures. RNA-FISH protocols have been previously applied with this aim in Cultural Heritage samples. However, only hyphae detection was reported in the literature, even if spores and conidia are not only a potential risk to Cultural Heritage but can also be harmful for the health of visitors, curators and restorers. Thus, the aim of this work was to evaluate various permeabilizing strategies for their application in the detection of spores/conidia and hyphae of artworks’ biodeteriogenic filamentous fungi by RNA-FISH. Besides of this, the influence of cell aging on the success of the technique and on the development of fungal autofluorescence (that could hamper the RNA-FISH signal detection) were also investigated. Five common biodeteriogenic filamentous fungi species isolated from biodegradated artworks were used as biological model: Aspergillus niger, Cladosporium sp, Fusarium sp, Penicillium sp. and Exophialia sp. Fungal autofluorescence was only detected in cells harvested from Fusarium sp, and Exophialia sp. old cultures, being aging-dependent. However, it was weak enough to allow autofluorescence/RNA-FISH signals distinction. Thus, autofluorescence was not a limitation for the application of RNA-FISH for detection of the taxa investigated. All the permeabilization strategies tested allowed to detect fungal cells from young cultures by RNA-FISH. However, only the combination of paraformaldehyde with Triton X-100 allowed the detection of conidia/spores and hyphae of old filamentous fungi. All the permeabilization strategies failed in the Aspergillus niger conidia/spores staining, which are known to be particularly difficult to permeabilize. But, even in spite of this, the application of this permeabilization method increased the analytical potential of RNA FISH in Cultural Heritage biodeterioration. Whereas much work is required to validate this RNA-FISH approach for its application in real samples from Cultural Heritage it could represent an important advance for the detection, not only of hyphae but also of spores and conidia of various filamentous fungi taxa by RNA-FISH.

A Rapid And Simple Capillary Electrophoresis Method For Indirect Determination Of The Biocide 2,2-dibromo-3-nitrilo-propionamide (dbnpa) In Cooling Waters.

A capillary zone electrophoresis (CE) method was developed for the determination of the biocide 2,2-dibromo-3-nitrilo-propionamide (DBNPA) in water used in cooling systems. The biocide is indirectly determined by CE measurement of the concentration of bromide ions produced by the reaction between the DBNPA and bisulfite. The relationship between the bromide peak areas and the DBNPA concentrations showed a good linearity and a coefficient of determination (R(2)) of 0.9997 in the evaluated concentration range of 0-75 μmol L(-1). The detection and quantification limits for DBNPA were 0.23 and 0.75 μmol L(-1), respectively. The proposed CE method was successfully applied for the analysis of samples of tap water and cooling water spiked with DBNPA. The intra-day and inter-day (intermediary) precisions were lower than 2.8 and 6.2%, respectively. The DBNPA concentrations measured by the CE method were compared to the values obtained by a spectrophotometric method and were found to agree well.

Desenvolvimento e validação de método espectrofotométrico para determinação de corante à base de luteína adicionado em iogurte desnatado

A simple analytical method for extraction and quantification of lutein colorant added to yogurt was developed and validated. The method allowed complete extraction of carotenoids using tetrahydrofuran in vortex, followed by centrifugation, partition to diethyl ether/petroleum ether, and drying. The carotenoids dissolved in ethanol were quantified by UV-Vis spectrophotometry. This method showed linearity in the range tested (1.41-13.42 µg g-1), limits of detection and quantification of 0.42 and 1.28 µg g-1, respectively, low relative standard deviation (3.4%) and recovery ranging from 95 to 103%. The method proved reliable for quantification of lutein added to yogurt.

The academic plagiarism and its punishments - a review

Currently there is an increase in the occurrence of plagiarism in varied types of academic texts. Therefore, in agreement with the Brazilian Coordination of Improvement of Higher Education Personnel (CAPES) policies, Brazilian higher education institutions should establish guidelines for the detection and inhibition of academic plagiarism. However, the notion of plagiarism is extremely complex, since the ability of textual construction acquired during education is also developed using others' words. Thus, it is necessary to better know the concept of plagiarism and its implications, as well as the consequences of plagiarism and the punishments that may result from it. Consequently, rules and policies to be established will be better founded in order to address the problem of plagiarism in academic texts in a comprehensive and consistent way, not only to inhibit plagiarism but also to promote education on how is possible to create texts in an original fashion.