Molecular profiling of indoor microbial communities in moisture damaged and non-damaged buildings

Epidemiological studies have shown an elevation in the incidence of asthma, allergic symptoms and respiratory infections among people living or working in buildings with moisture and mould problems. Microbial growth is suspected to have a key role, since the severity of microbial contamination and symptoms show a positive correlation, while the removal of contaminated materials relieves the symptoms. However, the cause-and-effect relationship has not been well established and knowledge of the causative agents is incomplete. The present consensus of indoor microbes relies on culture-based methods. Microbial cultivation and identification is known to provide qualitatively and quantitatively biased results, which is suspected to be one of the reasons behind the often inconsistent findings between objectively measured microbiological attributes and health. In the present study the indoor microbial communities were assessed using culture-independent, DNA based methods. Fungal and bacterial diversity was determined by amplifying and sequencing the nucITS- and16S-gene regions, correspondingly. In addition, the cell equivalent numbers of 69 mould species or groups were determined by quantitative PCR (qPCR). The results from molecular analyses were compared with results obtained using traditional plate cultivation for fungi. Using DNA-based tools, the indoor microbial diversity was found to be consistently higher and taxonomically wider than viable diversity. The dominant sequence types of fungi, and also of bacteria were mainly affiliated with well-known microbial species. However, in each building they were accompanied by various rare, uncultivable and unknown species. In both moisture-damaged and undamaged buildings the dominant fungal sequence phylotypes were affiliated with the classes Dothideomycetes (mould-like filamentous ascomycetes); Agaricomycetes (mushroom- and polypore-like filamentous basidiomycetes); Urediniomycetes (rust-like basidiomycetes); Tremellomycetes and the family Malasseziales (both yeast-like basidiomycetes). The most probable source for the majority of fungal types was the outdoor environment. In contrast, the dominant bacterial phylotypes in both damaged and undamaged buildings were affiliated with human-associated members within the phyla Actinobacteria and Firmicutes. Indications of elevated fungal diversity within potentially moisture-damage-associated fungal groups were recorded in two of the damaged buildings, while one of the buildings was characterized by an abundance of members of the Penicillium chrysogenum and P. commune species complexes. However, due to the small sample number and strong normal variation firm conclusions concerning the effect of moisture damage on the species diversity could not be made. The fungal communities in dust samples showed seasonal variation, which reflected the seasonal fluctuation of outdoor fungi. Seasonal variation of bacterial communities was less clear but to some extent attributable to the outdoor sources as well. The comparison of methods showed that clone library sequencing was a feasible method for describing the total microbial diversity, indicated a moderate quantitative correlation between sequencing and qPCR results and confirmed that culture based methods give both a qualitative and quantitative underestimate of microbial diversity in the indoor environment. However, certain important indoor fungi such as Penicillium spp. were clearly underrepresented in the sequence material, probably due to their physiological and genetic properties. Species specific qPCR was a more efficient and sensitive method for detecting and quantitating individual species than sequencing, but in order to exploit the full advantage of the method in building investigations more information is needed about the microbial species growing on damaged materials. In the present study, a new method was also developed for enhanced screening of the marker gene clone libraries. The suitability of the screening method to different kinds of microbial environments including biowaste compost material and indoor settled dusts was evaluated. The usability was found to be restricted to environments that support the growth and subsequent dominance of a small number microbial species, such as compost material.

Endemic malaria: an 'indoor' disease in northern Europe

Background: Endemic northern malaria reached 68°N latitude in Europe during the 19th century, where the summer mean temperature only irregularly exceeded 16°C, the lower limit needed for sporogony of Plasmodium vivax. Because of the available historical material and little use of quinine, Finland was suitable for an analysis of endemic malaria and temperature. Methods: Annual malaria death frequencies during 1800–1870 extracted from parish records were analysed against long-term temperature records in Finland, Russia and Sweden. Supporting data from 1750–1799 were used in the interpretation of the results. The life cycle and behaviour of the anopheline mosquitoes were interpreted according to the literature. Results: Malaria frequencies correlated strongly with the mean temperature of June and July of the preceding summer, corresponding to larval development of the vector. Hatching of imagoes peaks in the middle of August, when the temperature most years is too low for the sporogony of Plasmodium. After mating some of the females hibernate in human dwellings. If the female gets gametocytes from infective humans, the development of Plasmodium can only continue indoors, in heated buildings. Conclusion: Northern malaria existed in a cold climate by means of summer dormancy of hypnozoites in humans and indoor transmission of sporozoites throughout the winter by semiactive hibernating mosquitoes. Variable climatic conditions did not affect this relationship. The epidemics, however, were regulated by the population size of the mosquitoes which, in turn, ultimately was controlled by the temperatures of the preceding summer.

A design methodology for selecting and placement of sensors in multimedia surveillance systems

This paper addresses the problem of how to select the optimal number of sensors and how to determine their placement in a given monitored area for multimedia surveillance systems. We propose to solve this problem by obtaining a novel performance metric in terms of a probability measure for accomplishing the task as a function of set of sensors and their placement. This measure is then used to find the optimal set. The same measure can be used to analyze the degradation in system 's performance with respect to the failure of various sensors. We also build a surveillance system using the optimal set of sensors obtained based on the proposed design methodology. Experimental results show the effectiveness of the proposed design methodology in selecting the optimal set of sensors and their placement.

Boosting-based transfer learning for multi-view head-pose classification from surveillance videos

This work proposes a boosting-based transfer learning approach for head-pose classification from multiple, low-resolution views. Head-pose classification performance is adversely affected when the source (training) and target (test) data arise from different distributions (due to change in face appearance, lighting, etc). Under such conditions, we employ Xferboost, a Logitboost-based transfer learning framework that integrates knowledge from a few labeled target samples with the source model to effectively minimize misclassifications on the target data. Experiments confirm that the Xferboost framework can improve classification performance by up to 6%, when knowledge is transferred between the CLEAR and FBK four-view headpose datasets.

A prototype of a first-responder indoor localization system

In this paper we present an approach to build a prototype. model of a first-responder localization system intended for disaster relief operations. This system is useful to monitor and track the positions of the first-responders in an indoor environment, where GPS is not available. Each member of the first responder team is equipped with two zero-velocity-update-aided inertial navigation systems, one on each foot, a camera mounted on a helmet, and a processing platform strapped around the waist of the first responder, which fuses the data from the different sensors. The fusion algorithm runs real-time on the processing platform. The video is also processed using the DSP core of the computing machine. The processed data consisting of position, velocity, heading information along with video streams is transmitted to the command and control system via a local infrastructure WiFi network. A centralized cooperative localization algorithm, utilizing the information from Ultra Wideband based inter-agent ranging devices combined with the position estimates and uncertainties of each first responder, has also been implemented.

Exploring Transfer Learning Approaches for Head Pose Classification from Multi-view Surveillance Images

Head pose classification from surveillance images acquired with distant, large field-of-view cameras is difficult as faces are captured at low-resolution and have a blurred appearance. Domain adaptation approaches are useful for transferring knowledge from the training (source) to the test (target) data when they have different attributes, minimizing target data labeling efforts in the process. This paper examines the use of transfer learning for efficient multi-view head pose classification with minimal target training data under three challenging situations: (i) where the range of head poses in the source and target images is different, (ii) where source images capture a stationary person while target images capture a moving person whose facial appearance varies under motion due to changing perspective, scale and (iii) a combination of (i) and (ii). On the whole, the presented methods represent novel transfer learning solutions employed in the context of multi-view head pose classification. We demonstrate that the proposed solutions considerably outperform the state-of-the-art through extensive experimental validation. Finally, the DPOSE dataset compiled for benchmarking head pose classification performance with moving persons, and to aid behavioral understanding applications is presented in this work.

Skip Decision and Reference Frame Selection for Low-Complexity H.264/AVC Surveillance Video Coding

H. 264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial sampler is proposed to sample pixels that are segmented using a Gaussian mixture model. Modified weight updates are derived for the parameters of the mixture model to reduce floating point computations. A storage pattern of the parameters in memory is also modified to improve cache performance. Skip selection is performed using the segmentation results of the sampled pixels. The second contribution is a low computational cost algorithm to choose the reference frames. The proposed reference frame selection algorithm reduces the cost of coding uncovered background regions. We also study the number of reference frames required to achieve good coding efficiency. Distortion over foreground pixels is measured to quantify the performance of the proposed techniques. Experimental results show bit rate savings of up to 94.5% over methods proposed in literature on video surveillance data sets. The proposed techniques also provide up to 74.5% reduction in compression complexity without increasing the distortion over the foreground regions in the video sequence.

Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging

A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RF-based inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

Advances towards behaviour-based indoor robotic exploration

215 p.

Commercial production of Clarias fry and fingerlings in indoor and outdoor concrete tank systems

Induced breeding technique by hypophysation is being applied at the Kainji Lake Research Institute Fisheries Division Hatchery complex in New Bussa, Nigeria, for the production of Clarias fry and fingerlings in indoor and outdoor concrete tank systems. The hatchlings are fed on livefood (zooplankton) and artificial feed. Source of zooplankton is from cultured stock which is maintained throughout the breeding season by fertilization. Production values show that an average of over 4,000 hatchlings (larvae) can be produced by a female breeder (over-700g wt) and percentage survival after two months ranges between 70 to 75%. With the proposed modification and expansion project, an estimated production of over 0.5 million fingerlings per breeding season is projected

INTERPOL's surveillance network in curbing transnational terrorism

This paper investigates the role that INTERPOL surveillance – the Mobile INTERPOL Network Database (MIND) and the Fixed INTERPOL Network Database (FIND) – played in the War on Terror since its inception in 2005. MIND/FIND surveillance allows countries to screen people and documents systematically at border crossings against INTERPOL databases on terrorists, fugitives, and stolen and lost travel documents. Such documents have been used in the past by terrorists to transit borders. By applying methods developed in the treatment-effects literature, this paper establishes that countries adopting MIND/FIND experienced fewer transnational terrorist attacks than had they not adopted MIND/FIND. Our estimates indicate that, on average, during 2008–2011, adopting and using MIND/FIND results in 1.23 fewer transnational terrorist incidents each year per 100 million people. Thus, a country like France with a population just above 64 million people in 2008 would have 0.79 fewer transnational terrorist incidents per year owing to its use of INTERPOL surveillance. For most treatment countries, this amounts to a sizeable proportional reduction of about 60 per cent.

Studies on the nutritional value of cassava (Manihot utillisima) peels as energy source in the diet of Oreochromis niloticus fry fed in indoor glass aquaria

This study, though, has as its core objective cost reduction in aquaculture nutrition was equally designed to investigate the value of the peels of cassava (Manihot utillisima) as energy source in the diet of Oreochromis niloticus fry. Three levels of cassava peels diet and a control (100% yellow maize in the carbohydrate mixture) was prepared and tested on O. niloticus fry for ten (10) weeks. The fry with mean weight of 0.32g were grouped fifteen (15) in each of the glass aquaria measuring 60x30x30cm with a maximum capacity of 52 litres of water. The fry were fed twice daily at 10% biomass. Weekly, the fry were weighed to determine the weight increment or otherwise and the quality of feed adjusted accordingly. Water quality parameters like temperature, pH and dissolved oxygen (D.0) were monitored and found to be at desirable level. DT 3 (97 % cassava peels and 3% yellow maize) in the carbohydrate mixture gave the best growth performance. The fry fed, this diet gained mean weight of 1.18g for the period of the experiment. However, the poorest performance in terms of growth was from fry fed the control diet (100%yellow maize in the carbohydrate mixture) fry fed this diet gained mean weight of 0.80 for the duration of the experiment. Analysis of the various growth indices like SGR, PER, FCR and NPU shows that DT3 was the overall best diet with an SGR value of2.40 and FCR of 43.83. However, DT 1 (70% cassava peels and 30% yellow maize) gave the poorest SGR of 1.61 and FCR of 67.58. The difference in weight gain among the fry fed the three levels of cassava peels diet and the control was not statically significant (P>0.05)