Detection of clinical mastitis with the help of a thermal camera

Increasing dairy farm size and increase in automation in livestock production require that new methods are used to monitor animal health. In this study, a thermal camera was tested for its capacity to detect clinical mastitis. Mastitis was experimentally induced in 6 cows with 10 mu g of Escherichia coli lipopolysaccharide (LPS). The LPS was infused into the left forequarter of each cow, and the right forequarters served as controls. Clinical examination for systemic and local signs and sampling for indicators of inflammation in milk were carried out before morning and evening milking throughout the 5-d experimental period and more frequently on the challenge day. Thermal images of experimental and control quarters were taken at each sampling time from lateral and medial angles. The first signs of clinical mastitis were noted in all cows 2 h postchallenge and included changes in general appearance of the cows and local clinical signs in the affected udder quarter. Rectal temperature, milk somatic cell count, and electrical conductivity were increased 4 h postchallenge and milk N-acetyl-beta-D-glucosaminidase activity 8 h postchallenge. The thermal camera was successful in detecting the 1 to 1.5 degrees C temperature change on udder skin associated with clinical mastitis in all cows because temperature of the udder skin of the experimental and control quarters increased in line with the rectal temperature. Yet, local signs on the udder were seen before the rise in udder skin and body temperature. The udder represents a sensitive site for detection of any febrile disease using a noninvasive method. A thermal camera mounted in a milking or feeding parlor could detect temperature changes associated with clinical mastitis or other diseases in a dairy herd.

Detection and molecular epidemiology of tick-borne encephalitis virus infections

Pdf-file, link above

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

Development of a probe-based blotting technique for the detection of Tobacco streak virus

Digoxigenin (DIG)-labeled DNA probe was developed for a sensitive and rapid detection of the Tobacco streak virus (TSV) isolates in India by dot-blot and tissue print hybridization techniques. DIG-labeled DNA probe complementary to the coat protein (CP) region of TSV sunflower isolate was designed and used to detect the TSV presence at field levels. Dot-blot hybridization was used to check a large number of TSV isolates with a single probe. In addition, a sensitivity of the technique was examined with the different sample extraction methods. Another technique, the tissue blot hybridization offered a simple, reliable procedure and did not require a sample processing. Thus, both non-radioactively labeled probe techniques could facilitate the sample screening during TSV outbreaks and offer an advantage in quarantine services.

Change detection and controlling forest information using multi-temporal Landsat TM imagery.

A method was developed for relative radiometric calibration of single multitemporal Landsat TM image, several multitemporal images covering each others, and several multitemporal images covering different geographic locations. The radiometricly calibrated difference images were used for detecting rapid changes on forest stands. The nonparametric Kernel method was applied for change detection. The accuracy of the change detection was estimated by inspecting the image analysis results in field. The change classification was applied for controlling the quality of the continuously updated forest stand information. The aim was to ensure that all the manmade changes and any forest damages were correctly updated including the attribute and stand delineation information. The image analysis results were compared with the registered treatments and the stand information base. The stands with discrepancies between these two information sources were recommended to be field inspected.

New Concepts for PVC Detection

A new scheme is proposed for the detection of premature ventricular beats, which is a vital function in rhythm monitoring of cardiac patients. A transformation based on the first difference of the digitized electrocardiogram (ECG) signal is developed for the detection and delineation of QRS complexes. The method for classifying the abnormal complexes from the normal ones is based on the concepts of minimum phase and signal length. The parameters of a linear discriminant function obtained from a training feature vector set are used to classify the complexes. Results of application of the scheme to ECG of two arrhythmia patients are presented.

Random-Restart Reactive Tabu Search Algorithm for Detection in Large-MIMO Systems

We present a low-complexity algorithm based on reactive tabu search (RTS) for near maximum likelihood (ML) detection in large-MIMO systems. The conventional RTS algorithm achieves near-ML performance for 4-QAM in large-MIMO systems. But its performance for higher-order QAM is far from ML performance. Here, we propose a random-restart RTS (R3TS) algorithm which achieves significantly better bit error rate (BER) performance compared to that of the conventional RTS algorithm in higher-order QAM. The key idea is to run multiple tabu searches, each search starting with a random initial vector and choosing the best among the resulting solution vectors. A criterion to limit the number of searches is also proposed. Computer simulations show that the R3TS algorithm achieves almost the ML performance in 16 x 16 V-BLAST MIMO system with 16-QAM and 64-QAM at significantly less complexities than the sphere decoder. Also, in a 32 x 32 V-BLAST MIMO system, the R3TS performs close to ML lower bound within 1.6 dB for 16-QAM (128 bps/Hz), and within 2.4 dB for 64-QAM (192 bps/Hz) at 10(-3) BER.

Optimum weighting function in bispectral analysis in speckle interferometry - Binary star parity detection

In order to describe the atmospheric turbulence which limits the resolution of long-exposure images obtained using ground-based large telescopes, a simplified model of a speckle pattern, reducing the complexity of calculating field-correlations of very high order, is presented. Focal plane correlations are used instead of correlations in the spatial frequency domain. General tripple correlations for a point source and for a binary are calculated and it is shown that they are not a strong function of the binary separation. For binary separations close to the diffraction limit of the telescope, the genuine triple correlation technique ensures a better SNR than the near-axis Knox-Thompson technique. The simplifications allow a complete analysis of the noise properties at all levels of light.

Detection of a CpA methylase in an insect system: characterization and substrate specificity

A cytosine-specific DNA methyltransferase (EC 2.1.1.37) has been purified to near homogeneity from a mealybug (Planococcus lilacinus). The enzyme can methylate cytosine residues in CpG sequences as well as CpA sequences. The apparent molecular weight of the enzyme was estimated as 135,000 daltons by FPLC. The enzyme exhibits a processive mode of action and a salt dependance similar to mammalian methylases. Mealybug methylase exhibits a preference for denatured DNA substrates.

Detection of edges from projections

In a number of applications of computerized tomography, the ultimate goal is to detect and characterize objects within a cross section. Detection of edges of different contrast regions yields the required information. The problem of detecting edges from projection data is addressed. It is shown that the class of linear edge detection operators used on images can be used for detection of edges directly from projection data. This not only reduces the computational burden but also avoids the difficulties of postprocessing a reconstructed image. This is accomplished by a convolution backprojection operation. For example, with the Marr-Hildreth edge detection operator, the filtering function that is to be used on the projection data is the Radon transform of the Laplacian of the 2-D Gaussian function which is combined with the reconstruction filter. Simulation results showing the efficacy of the proposed method and a comparison with edges detected from the reconstructed image are presented

Detection of IgG, IgA, IgM and IgE Antibodies in Invasive Amoebiasis in Endemic Areas

Entamoeba histolytica-specific serum IgG, IgA, IgM and IgE antibodies were assayed in cases of amoebiasis in an endemic area. Patient groups consisted of amoebic liver abscess (n=18), pre-abscess hepatic amoebiasis (n=22) and amoebic colitis (n=30). Control subjects comprised 26 asymptomatic cyst passers, 13 giardiasis cases, 20 typhoid patients and 24 non-amoebic individuals. Serum IgG was assayed by ELISA, using a monoclonal anti IgG β- galactosidase (IgG β-gal) conjugate, a polyclonal avidin biotin horse radish peroxidase (AB-HRP), and a polyclonal anti IgG horse radish peroxidase (IgG HRP) conjugate. IgA and IgM were assayed by the β-gal ELISA and IgE by AB-HRP. Diagnostically significant IgG and IgA while lower IgM and IgE antibody levels were seen in extraintestinal cases. About 40% of suspected pre-abscess hepatic amoebiasis cases were confirmed by antibody estimation. All isotype levels in most dysentery cases were in the range of the controls.

Detection and characterisation of circulating cysticercal antigens in human cerebrospinal fluid

With biotin labelled and unlabelled immunoglobulin fraction of anticysticercal antibodies raised in rabbits, tandem-enzyme linked immunosorbent assay (T-ELISA), capture-dot immunobinding assay (C-DIA) and reverse passive haemagglutination (RPHA) tests were developed for the detection of cysticercal antigens. The sensitivity levels were respectively, 9 ng ml−1, 2 ng ml−1 and 45 ng ml−1. All three methods were of equal specificity as none of the antigens of Mycobacterium tuberculosis, Japanese encephalitis virus and Echinococcus granulosus reacted with anticysticercal IgG. Cysticercal antigens were detected in the cerebrospinal fluid (CSF) of confirmed neurocysticercosis at sensitivity levels of 91·6% by T-ELISA, 83·33% by C-DIA and 75% by RPHA and specificity levels of >93%. Western analysis of these antigens in CSF showed mainly antigens of 64–68 kDa and 24–28 kDA. By crossed immunoelectrophoresis (CIE) with an intermediate gel technique, five circulating antigens were found to be released from scolex and fluid.

Monitoring Indigenous Tropical Montane Forests in the Taita Hills Using Airborne Digital Camera Imagery

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955 2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

Coordination-Driven Self-Assembly of M3L2 Trigonal Cages from Preorganized Metalloligands Incorporating Octahedral Metal Centers and Fluorescent Detection of Nitroaromatics

The design and preparation of novel M3L2 trigonal cages via the coordination-driven self-assembly of preorganized metalloligands containing octahedral aluminum(III), gallium(III), or ruthenium(II) centers is described. When tritopic or dinuclear linear metalloligands and appropriate complementary subunits are employed, M3L2 trigonal-bipyramidal and trigonal-prismatic cages are self-assembled under mild conditions. These three-dimensional cages were characterized with multinuclear NMR spectroscopy (H-1 and P-31) and high-resolution electrospray ionization mass spectrometry. The structure of one such trigonal-prismatic cage, self-assembled from an arene ruthenium metalloligand, was confirmed via single-crystal X-ray crystallography. The fluorescent nature of these prisms, due to the presence of their electron-rich ethynyl functionalities, prompted photophysical studies, which revealed that electron-deficient nitroaromatics are effective quenchers of the cages' emission. Excited-state charge transfer from the prisms to the nitroaromatic substrates can be used as the basis for the development of selective and discriminatory turn-off fluorescent sensors for nitroaromatics.