Semantic Classes in Topic Detection and Tracking

Topic detection and tracking (TDT) is an area of information retrieval research the focus of which revolves around news events. The problems TDT deals with relate to segmenting news text into cohesive stories, detecting something new, previously unreported, tracking the development of a previously reported event, and grouping together news that discuss the same event. The performance of the traditional information retrieval techniques based on full-text similarity has remained inadequate for online production systems. It has been difficult to make the distinction between same and similar events. In this work, we explore ways of representing and comparing news documents in order to detect new events and track their development. First, however, we put forward a conceptual analysis of the notions of topic and event. The purpose is to clarify the terminology and align it with the process of news-making and the tradition of story-telling. Second, we present a framework for document similarity that is based on semantic classes, i.e., groups of words with similar meaning. We adopt people, organizations, and locations as semantic classes in addition to general terms. As each semantic class can be assigned its own similarity measure, document similarity can make use of ontologies, e.g., geographical taxonomies. The documents are compared class-wise, and the outcome is a weighted combination of class-wise similarities. Third, we incorporate temporal information into document similarity. We formalize the natural language temporal expressions occurring in the text, and use them to anchor the rest of the terms onto the time-line. Upon comparing documents for event-based similarity, we look not only at matching terms, but also how near their anchors are on the time-line. Fourth, we experiment with an adaptive variant of the semantic class similarity system. The news reflect changes in the real world, and in order to keep up, the system has to change its behavior based on the contents of the news stream. We put forward two strategies for rebuilding the topic representations and report experiment results. We run experiments with three annotated TDT corpora. The use of semantic classes increased the effectiveness of topic tracking by 10-30\% depending on the experimental setup. The gain in spotting new events remained lower, around 3-4\%. The anchoring the text to a time-line based on the temporal expressions gave a further 10\% increase the effectiveness of topic tracking. The gains in detecting new events, again, remained smaller. The adaptive systems did not improve the tracking results.

Methicillin-resistant Staphylococcus aureus in Finland: recent changes in the epidemiology, long-term facility aspects, and phenotypic and molecular detection of isolates

Staphylococcus aureus is one of the most important bacteria that cause disease in humans, and methicillin-resistant S. aureus (MRSA) has become the most commonly identified antibiotic-resistant pathogen in many parts of the world. MRSA rates have been stable for many years in the Nordic countries and the Netherlands with a low MRSA prevalence in Europe, but in the recent decades, MRSA rates have increased in those low-prevalence countries as well. MRSA has been established as a major hospital pathogen, but has also been found increasingly in long-term facilities (LTF) and in communities of persons with no connections to the health-care setting. In Finland, the annual number of MRSA isolates reported to the National Infectious Disease Register (NIDR) has constantly increased, especially outside the Helsinki metropolitan area. Molecular typing has revealed numerous outbreak strains of MRSA, some of which have previously been associated with community acquisition. In this work, data on MRSA cases notified to the NIDR and on MRSA strain types identified with pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and staphylococcal cassette chromosome mec (SCCmec) typing at the National Reference Laboratory (NRL) in Finland from 1997 to 2004 were analyzed. An increasing trend in MRSA incidence in Finland from 1997 to 2004 was shown. In addition, non-multi-drug resistant (NMDR) MRSA isolates, especially those resistant only to methicillin/oxacillin, showed an emerging trend. The predominant MRSA strains changed over time and place, but two internationally spread epidemic strains of MRSA, FIN-16 and FIN-21, were related to the increase detected most recently. Those strains were also one cause of the strikingly increasing invasive MRSA findings. The rise of MRSA strains with SCCmec types IV or V, possible community-acquired MRSA was also detected. With questionnaires, the diagnostic methods used for MRSA identification in Finnish microbiology laboratories and the number of MRSA screening specimens studied were reviewed. Surveys, which focused on the MRSA situation in long-term facilities in 2001 and on the background information of MRSA-positive persons in 2001-2003, were also carried out. The rates of MRSA and screening practices varied widely across geographic regions. Part of the NMDR MRSA strains could remain undetected in some laboratories because of insufficient diagnostic techniques used. The increasing proportion of elderly population carrying MRSA suggests that MRSA is an emerging problem in Finnish long-term facilities. Among the patients, 50% of the specimens were taken on a clinical basis, 43% on a screening basis after exposure to MRSA, 3% on a screening basis because of hospital contact abroad, and 4% for other reasons. In response to an outbreak of MRSA possessing a new genotype that occurred in a health care ward and in an associated nursing home of a small municipality in Northern Finland in autumn 2003, a point-prevalence survey was performed six months later. In the same study, the molecular epidemiology of MRSA and methicillin-sensitive S. aureus (MSSA) strains were also assessed, the results to the national strain collection compared, and the difficulties of MRSA screening with low-level oxacillin-resistant isolates encountered. The original MRSA outbreak in LTF, which consisted of isolates possessing a nationally new PFGE profile (FIN-22) and internationally rare MLST type (ST-27), was confined. Another previously unrecognized MRSA strain was found with additional screening, possibly indicating that current routine MRSA screening methods may be insufficiently sensitive for strains possessing low-level oxacillin resistance. Most of the MSSA strains found were genotypically related to the epidemic MRSA strains, but only a few of them had received the SCCmec element, and all those strains possessed the new SCCmec type V. In the second largest nursing home in Finland, the colonization of S. aureus and MRSA, and the role of screening sites along with broth enrichment culture on the sensitivity to detect S. aureus were studied. Combining the use of enrichment broth and perineal swabbing, in addition to nostrils and skin lesions swabbing, may be an alternative for throat swabs in the nursing home setting, especially when residents are uncooperative. Finally, in order to evaluate adequate phenotypic and genotypic methods needed for reliable laboratory diagnostics of MRSA, oxacillin disk diffusion and MIC tests to the cefoxitin disk diffusion method at both +35°C and +30°C, both with or without an addition of sodium chloride (NaCl) to the Müller Hinton test medium, and in-house PCR to two commercial molecular methods (the GenoType® MRSA test and the EVIGENETM MRSA Detection test) with different bacterial species in addition to S. aureus were compared. The cefoxitin disk diffusion method was superior to that of oxacillin disk diffusion and to the MIC tests in predicting mecA-mediated resistance in S. aureus when incubating at +35°C with or without the addition of NaCl to the test medium. Both the Geno Type® MRSA and EVIGENETM MRSA Detection tests are usable, accurate, cost-effective, and sufficiently fast methods for rapid MRSA confirmation from a pure culture.

Microbial diversity in the municipal composting process and development of detection methods

Composting refers to aerobic degradation of organic material and is one of the main waste treatment methods used in Finland for treating separated organic waste. The composting process allows converting organic waste to a humus-like end product which can be used to increase the organic matter in agricultural soils, in gardening, or in landscaping. Microbes play a key role as degraders during the composting-process, and the microbiology of composting has been studied for decades, but there are still open questions regarding the microbiota in industrial composting processes. It is known that with the traditional, culturing-based methods only a small fraction, below 1%, of the species in a sample is normally detected. In recent years an immense diversity of bacteria, fungi and archaea has been found to occupy many different environments. Therefore the methods of characterising microbes constantly need to be developed further. In this thesis the presence of fungi and bacteria in full-scale and pilot-scale composting processes was characterised with cloning and sequencing. Several clone libraries were constructed and altogether nearly 6000 clones were sequenced. The microbial communities detected in this study were found to differ from the compost microbes observed in previous research with cultivation based methods or with molecular methods from processes of smaller scale, although there were similarities as well. The bacterial diversity was high. Based on the non-parametric coverage estimations, the number of bacterial operational taxonomic units (OTU) in certain stages of composting was over 500. Sequences similar to Lactobacillus and Acetobacteria were frequently detected in the early stages of drum composting. In tunnel stages of composting the bacterial community comprised of Bacillus, Thermoactinomyces, Actinobacteria and Lactobacillus. The fungal diversity was found to be high and phylotypes similar to yeasts were abundantly found in the full-scale drum and tunnel processes. In addition to phylotypes similar to Candida, Pichia and Geotrichum moulds from genus Thermomyces and Penicillium were observed in tunnel stages of composting. Zygomycetes were detected in the pilot-scale composting processes and in the compost piles. In some of the samples there were a few abundant phylotypes present in the clone libraries that masked the rare ones. The rare phylotypes were of interest and a method for collecting them from clone libraries for sequencing was developed. With negative selection of the abundant phylotyps the rare ones were picked from the clone libraries. Thus 41% of the clones in the studied clone libraries were sequenced. Since microbes play a central role in composting and in many other biotechnological processes, rapid methods for characterization of microbial diversity would be of value, both scientifically and commercially. Current methods, however, lack sensitivity and specificity and are therefore under development. Microarrays have been used in microbial ecology for a decade to study the presence or absence of certain microbes of interest in a multiplex manner. The sequence database collected in this thesis was used as basis for probe design and microarray development. The enzyme assisted detection method, ligation-detection-reaction (LDR) based microarray, was adapted for species-level detection of microbes characteristic of each stage of the composting process. With the use of a specially designed control probe it was established that a species specific probe can detect target DNA representing as little as 0.04% of total DNA in a sample. The developed microarray can be used to monitor composting processes or the hygienisation of the compost end product. A large compost microbe sequence dataset was collected and analysed in this thesis. The results provide valuable information on microbial community composition during industrial scale composting processes. The microarray method was developed based on the sequence database collected in this study. The method can be utilised in following the fate of interesting microbes during composting process in an extremely sensitive and specific manner. The platform for the microarray is universal and the method can easily be adapted for studying microbes from environments other than compost.

Selective detection of single-enantiomer spectrum of chiral molecules aligned in the polypeptide liquid crystalline solvent: Transition selective one-dimensional H-1-H-1 COSY

One-dimensional (1D) proton NMR spectra of enantiomers are generally undecipherable in chiral orienting poly-gamma-benzyl-L-glutamate (PBLG)/CDCl3 solvent. This arises due to large number of couplings, in addition to superposition of spectra from both the enantiomers, severely hindering the H-1 detection. On the other hand in the present study the benefit is derived front the presence of several couplings among the entire network of interacting protons. Transition selective 1D H-1-H-1 correlation experiment (1D-COSY) which utilizes the Coupling assisted transfer of magnetization not only for unraveling the overlap but also for the selective detection of enantiopure spectrum is reported. The experiment is simple, easy to implement and provides accurate eanantiomeric excess in addition to the determination of the proton-proton couplings of an enantiomer within a short experimental time (few minutes). (C) 2009 Elsevier Inc. All rights reserved.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Infections in lung and heart transplant recipients : Studies on the impact of bronchoscopy in the diagnosis of respiratory infections and detection of viral infections in blood and bronchoalveolar lavage fluid

Infection is a major cause of mortality and morbidity after thoracic organ transplantation. The aim of the present study was to evaluate the infectious complications after lung and heart transplantation, with a special emphasis on the usefulness of bronchoscopy and the demonstration of cytomegalovirus (CMV), human herpes virus (HHV)-6, and HHV-7. We reviewed all the consecutive bronchoscopies performed on heart transplant recipients (HTRs) from May 1988 to December 2001 (n = 44) and lung transplant recipients (LTRs) from February 1994 to November 2002 (n = 472). To compare different assays in the detection of CMV, a total of 21 thoracic organ transplant recipients were prospectively monitored by CMV pp65-antigenemia, DNAemia (PCR), and mRNAemia (NASBA) tests. The antigenemia test was the reference assay for therapeutic intervention. In addition to CMV antigenemia, 22 LTRs were monitored for HHV-6 and HHV-7 antigenemia. The diagnostic yield of the clinically indicated bronchoscopies was 41 % in the HTRs and 61 % in the LTRs. The utility of the bronchoscopy was highest from one to six months after transplantation. In contrast, the findings from the surveillance bronchoscopies performed on LTRs led to a change in the previous treatment in only 6 % of the cases. Pneumocystis carinii and CMV were the most commonly detected pathogens. Furthermore, 15 (65 %) of the P. carinii infections in the LTRs were detected during chemoprophylaxis. None of the complications of the bronchoscopies were fatal. Antigenemia, DNAemia, and mRNAemia were present in 98 %, 72 %, and 43 % of the CMV infections, respectively. The optimal DNAemia cut-off levels (sensitivity/specificity) were 400 (75.9/92.7 %), 850 (91.3/91.3 %), and 1250 (100/91.5 %) copies/ml for the antigenemia of 2, 5, and 10 pp65-positive leukocytes/50 000 leukocytes, respectively. The sensitivities of the NASBA were 25.9, 43.5, and 56.3 % in detecting the same cut-off levels. CMV DNAemia was detected in 93 % and mRNAemia in 61 % of the CMV antigenemias requiring antiviral therapy. HHV-6, HHV-7, and CMV antigenemia was detected in 20 (91 %), 11 (50 %), and 12 (55 %) of the 22 LTRs (median 16, 31, and 165 days), respectively. HHV-6 appeared in 15 (79 %), HHV-7 in seven (37 %), and CMV in one (7 %) of these patients during ganciclovir or valganciclovir prophylaxis. One case of pneumonitis and another of encephalitis were associated with HHV-6. In conclusion, bronchoscopy is a safe and useful diagnostic tool in LTRs and HTRs with a suspected respiratory infection, but the role of surveillance bronchoscopy in LTRs remains controversial. The PCR assay acts comparably with the antigenemia test in guiding the pre-emptive therapy against CMV when threshold levels of over 5 pp65-antigen positive leukocytes are used. In contrast, the low sensitivity of NASBA limits its usefulness. HHV-6 and HHV-7 activation is common after lung transplantation despite ganciclovir or valganciclovir prophylaxis, but clinical manifestations are infrequently linked to them.

A Low-Complexity Near-ML Performance Achieving Algorithm for Large MIMO Detection

In this paper, we present a low-complexity, near maximum-likelihood (ML) performance achieving detector for large MIMO systems having tens of transmit and receive antennas. Such large MIMO systems are of interest because of the high spectral efficiencies possible in such systems. The proposed detection algorithm, termed as multistage likelihood-ascent search (M-LAS) algorithm, is rooted in Hopfield neural networks, and is shown to possess excellent performance as well as complexity attributes. In terms of performance, in a 64 x 64 V-BLAST system with 4-QAM, the proposed algorithm achieves an uncoded BER of 10(-3) at an SNR of just about 1 dB away from AWGN-only SISO performance given by Q(root SNR). In terms of coded BER, with a rate-3/4 turbo code at a spectral efficiency of 96 bps/Hz the algorithm performs close to within about 4.5 dB from theoretical capacity, which is remarkable in terms of both high spectral efficiency as well as nearness to theoretical capacity. Our simulation results show that the above performance is achieved with a complexity of just O(NtNt) per symbol, where N-t and N-tau denote the number of transmit and receive antennas.

When and why threats go undetected: Impacts of event rate and shift length on threat detection accuracy during airport baggage screening

Objective: We aimed to assess the impact of task demands and individual characteristics on threat detection in baggage screeners. Background: Airport security staff work under time constraints to ensure optimal threat detection. Understanding the impact of individual characteristics and task demands on performance is vital to ensure accurate threat detection. Method: We examined threat detection in baggage screeners as a function of event rate (i.e., number of bags per minute) and time on task across 4 months. We measured performance in terms of the accuracy of detection of Fictitious Threat Items (FTIs) randomly superimposed on X-ray images of real passenger bags. Results: Analyses of the percentage of correct FTI identifications (hits) show that longer shifts with high baggage throughput result in worse threat detection. Importantly, these significant performance decrements emerge within the first 10 min of these busy screening shifts only. Conclusion: Longer shift lengths, especially when combined with high baggage throughput, increase the likelihood that threats go undetected. Application: Shorter shift rotations, although perhaps difficult to implement during busy screening periods, would ensure more consistently high vigilance in baggage screeners and, therefore, optimal threat detection and passenger safety.

Detection of renal dysfunction during and after anaesthesia and surgery - evaluation of the influence of inorganic fluoride, ketorolac and clonidine

Drugs and surgical techniques may have harmful renal effects during the perioperative period. Traditional biomarkers are often insensitive to minor renal changes, but novel biomarkers may more accurately detect disturbances in glomerular and tubular function and integrity. The purpose of this study was first, to evaluate the renal effects of ketorolac and clonidine during inhalation anesthesia with sevoflurane and isoflurane, and secondly, to evaluate the effect of tobacco smoking on the production of inorganic fluoride (F-) following enflurane and sevoflurane anesthesia as well as to determine the effect of F- on renal function and cellular integrity in surgical patients. A total of 143 patients undergoing either conventional (n = 75) or endoscopic (n = 68) inpatient surgery were enrolled in four studies. The ketorolac and clonidine studies were prospective, randomized, placebo controlled and double-blinded, while the cigarette smoking studies were prospective cohort studies with two parallel groups. As a sign of proximal tubular deterioration, a similar transient increase in urine N-acetyl-beta-D-glucosaminidase/creatinine (U-NAG/crea) was noted in both the ketorolac group and in the controls (baseline vs. at two hours of anesthesia, p = 0.015) with a 3.3 minimum alveolar concentration hour sevoflurane anesthesia. Uncorrelated U-NAG increased above the maximum concentration measured from healthy volunteers (6.1 units/l) in 5/15 patients with ketorolac and in none of the controls (p = 0.042). As a sign of proximal tubular deterioration, U-glutathione transferase-alpha/crea (U-GST-alpha/crea) increased in both groups at two hours after anesthesia but a more significant increase was noted in the patients with ketorolac. U-GST-alpha/crea increased above the maximum ratio measured from healthy volunteers in 7/15 patients with ketorolac and in 3/15 controls. Clonidine diminished the activation of the renin-angiotensin aldosterone system during pneumoperitoneum; urine output was better preserved in the patients treated with clonidine (1/15 patients developed oliguria) than in the controls (8/15 developed oliguria (p=0.005)). Most patients with pneumoperitoneum and isoflurane anesthesia developed a transient proximal tubular deterioration, as U-NAG increased above 6.1 units/L in 11/15 patients with clonidine and in 7/15 controls. In the patients receiving clonidine treatment, the median of U-NAG/crea was higher than in the controls at 60 minutes of pneumoperitoneum (p = 0.01), suggesting that clonidine seems to worsen proximal tubular deterioration. Smoking induced the metabolism of enflurane, but the renal function remained intact in both the smokers and the non-smokers with enflurane anesthesia. On the contrary, smoking did not induce sevoflurane metabolism, but glomerular function decreased in 4/25 non-smokers and in 7/25 smokers with sevoflurane anesthesia. All five patients with S-F- ≥ 40 micromol/L, but only 6/45 with S-F- less than 40 micromol/L (p = 0.001), developed a S-tumor associated trypsin inhibitor concentration above 3 nmol/L as a sign of glomerular dysfunction. As a sign of proximal tubulus deterioration, U-beta 2-microglobulin increased in 2/5 patients with S-F- over 40 micromol/L compared to 2/45 patients with the highest S-F- less than 40 micromol/L (p = 0.005). To conclude, sevoflurane anesthesia may cause a transient proximal tubular deterioration which may be worsened by a co-administration of ketorolac. Clonidine premedication prevents the activation of the renin-angiotensin aldosterone system and preserves normal urine output, but may be harmful for proximal tubules during pneumoperitoneum. Smoking induces the metabolism of enflurane but not that of sevoflurane. Serum F- of 40 micromol/L or higher may induce glomerular dysfunction and proximal tubulus deterioration in patients with sevoflurane anesthesia. The novel renal biomarkers warrant further studies in order to establish reference values for surgical patients having inhalation anesthesia.

Energy efficient change detection over a MAC using physical layer fusion

We propose a simple and energy efficient distributed change detection scheme for sensor networks based on Page's parametric CUSUM algorithm. The sensor observations are IID over time and across the sensors conditioned on the change variable. Each sensor runs CUSUM and transmits only when the CUSUM is above some threshold. The transmissions from the sensors are fused at the physical layer. The channel is modeled as a multiple access channel (MAC) corrupted with IID noise. The fusion center which is the global decision maker, performs another CUSUM to detect the change. We provide the analysis and simulation results for our scheme and compare the performance with an existing scheme which ensures energy efficiency via optimal power selection.

On the Average Case Communication Complexity for Detection in Sensor Networks

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

Optimal sleep-wake scheduling for quickest intrusion detection using sensor networks

We consider the problem of quickest detection of an intrusion using a sensor network, keeping only a minimal number of sensors active. By using a minimal number of sensor devices, we ensure that the energy expenditure for sensing, computation and communication is minimized (and the lifetime of the network is maximized). We model the intrusion detection (or change detection) problem as a Markov decision process (MDP). Based on the theory of MDP, we develop the following closed loop sleep/wake scheduling algorithms: (1) optimal control of Mk+1, the number of sensors in the wake state in time slot k + 1, (2) optimal control of qk+1, the probability of a sensor in the wake state in time slot k + 1, and an open loop sleep/wake scheduling algorithm which (3) computes q, the optimal probability of a sensor in the wake state (which does not vary with time), based on the sensor observations obtained until time slot k. Our results show that an optimum closed loop control on Mk+1 significantly decreases the cost compared to keeping any number of sensors active all the time. Also, among the three algorithms described, we observe that the total cost is minimum for the optimum control on Mk+1 and is maximum for the optimum open loop control on q.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

Background:Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. Methodology/Principal Findings: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. Conclusions/Significance: We have developed, computationally examined and experimentally validated the sRNAscanner algorithm. Data derived from this study has successfully identified six novel S. Typhimurium sRNA genes. In addition, the computational specificity analysis we have undertaken suggests that similar to 40% of sRNAscanner hits with high cumulative sum of scores represent genuine, undiscovered sRNA genes. Collectively, these data strongly support the utility of sRNAscanner and offer a glimpse of its potential to reveal large numbers of sRNA genes that have to date defied identification. sRNAscanner is available from: http://bicmku.in:8081/sRNAscanner or http://cluster.physics.iisc.ernet.in/sRNAscanner/.

Detection, epidemiology and host spectrum of cowpox and Borna disease virus infections

Several orthopoxviruses (OPV) and Borna disease virus (BDV) are enveloped, zoonotic viruses with a wide geographical distribution. OPV antibodies cross-react, and former smallpox vaccination has therefore protected human populations from another OPV infection, rodent-borne cowpox virus (CPXV). Cowpox in humans and cats usually manifests as a mild, self-limiting dermatitis and constitutional symptoms, but it can be severe and even life-threatening in the immunocompromised. Classical Borna disease is a progressive meningoencephalomyelitis in horses and sheep known in central Europe for centuries. Nowadays the virus or its close relative infects humans and also several other species in central Europe and elsewhere, but the existence of human Borna disease with its suspected neuropsychiatric symptoms is controversial. The epidemiology of BDV is largely unknown, and the present situation is even more intriguing following the recent detection of several-million-year-old, endogenized BDV genes in primate and various other vertebrate genomes. The aims of this study were to elucidate the importance of CPXV and BDV in Finland and in possible host species, and particularly to 1) establish relevant methods for the detection of CPXV and other OPVs as well as BDV in Finland, 2) determine whether CPXV and BDV exist in Finland, 3) discover how common OPV immunity is in different age groups in Finland, 4) characterize possible disease cases and clarify their epidemiological context, 5) establish the hosts and possible reservoir species of these viruses and their geographical distribution in wild rodents, and 6) elucidate the infection kinetics of BDV in the bank vole. An indirect immunofluorescence assay and avidity measurement were established for the detection, timing and verification of OPV or BDV antibodies in thousands of blood samples from humans, horses, ruminants, lynxes, gallinaceous birds, dogs, cats and rodents. The mostly vaccine-derived OPV seroprevalence was found to decrease gradually according to the year of birth of the sampled human subjects from 100% to 10% in those born after 1977. On the other hand, OPV antibodies indicating natural contact with CPXV or other OPVs were commonly found in domestic and wild animals: the horse, cow, lynx, dog, cat and, with a prevalence occasionally even as high as 92%, in wild rodents, including some previously undetected species and new regions. Antibodies to BDV were detected in humans, horses, a dog, cats, and for the first time in wild rodents, such as bank voles (Myodes glareolus). Because of the controversy within the human Borna disease field, extra verification methods were established for BDV antibody findings: recombinant nucleocapsid and phosphoproteins were produced in Escherichia coli and in a baculovirus system, and peptide arrays were additionally applied. With these verification assays, Finnish human, equine, feline and rodent BDV infections were confirmed. Taken together, wide host spectra were evident for both OPV and BDV infections based on the antibody findings, and OPV infections were found to be geographically broadly distributed. PCR amplification methods were utilised for hundreds of blood and tissue samples. The methods included conventional, nested and real-time PCRs with or without the reverse transcription step and detecting four or two genes of OPVs and BDV, respectively. OPV DNA could be amplified from two human patients and three bank voles, whereas no BDV RNA was detected in naturally infected individuals. Based on the phylogenetic analyses, the Finnish OPV sequences were closely related although not identical to a Russian CPXV isolate, and clearly different from other CPXV strains. Moreover, the Finnish sequences only equalled each other, but the short amplicons obtained from German rodents were identical to monkeypox virus, in addition to German CPXV variants. This reflects the close relationship of all OPVs. In summary, RNA of the Finnish BDV variant could not be detected with the available PCR methods, but OPV DNA infrequently could. The OPV species infecting the patients of this study was proven to be CPXV, which is most probably also responsible for the rodent infections. Multiple cell lines and some newborn rodents were utilised in the isolation of CPXV and BDV from patient and wildlife samples. CPXV could be isolated from a child with severe, generalised cowpox. BDV isolation attempts from rodents were unsuccessful in this study. However, in parallel studies, a transient BDV infection of cells inoculated with equine brain material was detected, and BDV antigens discovered in archival animal brains using established immunohistology. Thus, based on several independent methods, both CPXV and BDV (or a closely related agent) were shown to be present in Finland. Bank voles could be productively infected with BDV. This experimental infection did not result in notable pathological findings or symptoms, despite the intense spread of the virus in the central and peripheral nervous system. Infected voles commonly excreted the virus in urine and faeces, which emphasises their possible role as a BDV reservoir. Moreover, BDV RNA was regularly reverse transcribed into DNA in bank voles, which was detected by amplifying DNA by PCR without reverse transcription, and verified with nuclease treatments. This finding indicates that BDV genes could be endogenized during an acute infection. Although further transmission studies are needed, this experimental infection demonstrated that the bank vole can function as a potential BDV reservoir. In summary, multiple methods were established and applied in large panels to detect two zoonoses novel to Finland: cowpox virus and Borna disease virus. Moreover, new information was obtained on their geographical distribution, host spectrum, epidemiology and infection kinetics.