Robust abandoned object detection integrating wide area visual surveillance and social context

This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

Wireless sensor networks for heritage object deformation detection and tracking algorithm

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

Spot-test identification and rapid quantitative sequential analysis of dipyrone

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identification of the human prostatic carcinoma oncogene PTI-1 by rapid expression cloning and differential RNA display.

Elucidating the relevant genomic changes mediating development and evolution of prostate cancer is paramount for effective diagnosis and therapy. A putative dominant-acting nude mouse prostatic carcinoma tumor-inducing gene, PTI-1, has been cloned that is expressed in patient-derived human prostatic carcinomas but not in benign prostatic hypertrophy or normal prostate tissue. PTI-1 was detected by cotransfecting human prostate carcinoma DNA into CREF-Trans 6 cells, inducing tumors in nude mice, and isolating genes displaying increased expression in tumor-derived cells by using differential RNA display (DD). Screening a human prostatic carcinoma (LNCaP) cDNA library with a 214-bp DNA fragment found by DD permitted the cloning of a full-length 2.0-kb PTI-1 cDNA. Sequence analysis indicates that PTI-1 is a gene containing a 630-bp 5' sequence and a 3' sequence homologous to a truncated and mutated form of human elongation factor 1 alpha. In vitro translation demonstrates that the PTI-1 cDNA encodes a predominant approximately 46-kDa protein. Probing Northern blots with a DNA fragment corresponding to the 5' region of PTI-1 identifies multiple PTI-1 transcripts in RNAs from human carcinoma cell lines derived from the prostate, lung, breast, and colon. In contrast, PTI-1 RNA is not detected in human melanoma, neuroblastoma, osteosarcoma, normal cerebellum, or glioblastoma multiforme cell lines. By using a pair of primers recognizing a 280-bp region within the 630-bp 5' PTI-1 sequence, reverse transcription-PCR detects PTI-1 expression in patient-derived prostate carcinomas but not in normal prostate or benign hypertrophic prostate tissue. In contrast, reverse transcription-PCR detects prostate-specific antigen expression in all of the prostate tissues. These results indicate that PTI-1 may be a member of a class of oncogenes that could affect protein translation and contribute to carcinoma development in human prostate and other tissues. The approaches used, rapid expression cloning with the CREF-Trans 6 system and the DD strategy, should prove widely applicable for identifying and cloning additional human oncogenes.

Identification and molecular mechanisms of the rapid tonicity-induced relocalization of the aquaporin 4 channel

The aquaporin family of integral membrane proteins is comprised of channels that mediate cellular water flow. Aquaporin 4 (AQP4) is highly expressed in the glial cells of the central nervous system and facilitates the osmotically-driven pathological brain swelling associated with stroke and traumatic brain injury. Here we show that AQP4 cell surface expression can be rapidly and reversibly regulated in response to changes of tonicity in primary cortical rat astrocytes and in transfected HEK293 cells. The translocation mechanism involves protein kinase A (PKA) activation, influx of extracellular calcium and activation of calmodulin. We identify five putative PKA phosphorylation sites and use site-directed mutagenesis to show that only phosphorylation at one of these sites, serine- 276, is necessary for the translocation response. We discuss our findings in the context of the identification of new therapeutic approaches to treating brain oedema.

Rapid identification and differentiation of Mycobacterium avium subspecies paratuberculosis types by use of real-time PCR and high-resolution melt analysis of the MAP1506 locus

High-resolution melt (HRM) analysis can identify sequence polymorphisms by comparing the melting curves of amplicons generated by real-time PCR amplification. We describe the application of this technique to identify Mycobacterium avium subspecies paratuberculosis types I, II, and III. The HRM approach was based on type-specific nucleotide sequences in MAP1506, a member of the PPE (proline-proline-glutamic acid) gene family.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Automated object identification using optical video cameras on construction sites

Visual recording devices such as video cameras, CCTVs, or webcams have been broadly used to facilitate work progress or safety monitoring on construction sites. Without human intervention, however, both real-time reasoning about captured scenes and interpretation of recorded images are challenging tasks. This article presents an exploratory method for automated object identification using standard video cameras on construction sites. The proposed method supports real-time detection and classification of mobile heavy equipment and workers. The background subtraction algorithm extracts motion pixels from an image sequence, the pixels are then grouped into regions to represent moving objects, and finally the regions are identified as a certain object using classifiers. For evaluating the method, the formulated computer-aided process was implemented on actual construction sites, and promising results were obtained. This article is expected to contribute to future applications of automated monitoring systems of work zone safety or productivity.

A gray-box neural network-based model identification and fault estimation scheme for nonlinear dynamic systems

A novel gray-box neural network model (GBNNM), including multi-layer perception (MLP) neural network (NN) and integrators, is proposed for a model identification and fault estimation (MIFE) scheme. With the GBNNM, both the nonlinearity and dynamics of a class of nonlinear dynamic systems can be approximated. Unlike previous NN-based model identification methods, the GBNNM directly inherits system dynamics and separately models system nonlinearities. This model corresponds well with the object system and is easy to build. The GBNNM is embedded online as a normal model reference to obtain the quantitative residual between the object system output and the GBNNM output. This residual can accurately indicate the fault offset value, so it is suitable for differing fault severities. To further estimate the fault parameters (FPs), an improved extended state observer (ESO) using the same NNs (IESONN) from the GBNNM is proposed to avoid requiring the knowledge of ESO nonlinearity. Then, the proposed MIFE scheme is applied for reaction wheels (RW) in a satellite attitude control system (SACS). The scheme using the GBNNM is compared with other NNs in the same fault scenario, and several partial loss of effect (LOE) faults with different severities are considered to validate the effectiveness of the FP estimation and its superiority.

Robotic detection and tracking of Crown-Of-Thorns starfish

This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.

VIP Barcoding: Composition vector-based software for rapid species identification based on DNA barcoding

Species identification based on short sequences of DNA markers, that is, DNA barcoding, has emerged as an integral part of modern taxonomy. However, software for the analysis of large and multilocus barcoding data sets is scarce. The Basic Local Alignment Search Tool (BLAST) is currently the fastest tool capable of handling large databases (e.g. >5000 sequences), but its accuracy is a concern and has been criticized for its local optimization. However, current more accurate software requires sequence alignment or complex calculations, which are time-consuming when dealing with large data sets during data preprocessing or during the search stage. Therefore, it is imperative to develop a practical program for both accurate and scalable species identification for DNA barcoding. In this context, we present VIP Barcoding: a user-friendly software in graphical user interface for rapid DNA barcoding. It adopts a hybrid, two-stage algorithm. First, an alignment-free composition vector (CV) method is utilized to reduce searching space by screening a reference database. The alignment-based K2P distance nearest-neighbour method is then employed to analyse the smaller data set generated in the first stage. In comparison with other software, we demonstrate that VIP Barcoding has (i) higher accuracy than Blastn and several alignment-free methods and (ii) higher scalability than alignment-based distance methods and character-based methods. These results suggest that this platform is able to deal with both large-scale and multilocus barcoding data with accuracy and can contribute to DNA barcoding for modern taxonomy. VIP Barcoding is free and available at http://msl.sls.cuhk.edu.hk/vipbarcoding/.

Identification and purification of tRNAs containing N6-(delta 2-isopentenyl) adenosine using antibodies specific for N6-(delta-isopentenyl) adenosine

Antibodies specific for the modified nucleoside N6-(delta 2-isopentenyl) adenosine (i6A) were employed to identify the tRNAs containing i6A from an unfractionated tRNA mixture by a nitrocellulose filter binding assay. When radioactive aminoacyl-tRNAs were incubated with i6A-specific antibodies and filtered through nitrocellulose membrane filters, the tRNAs possessing i6A (tRNAtyr and tRNAser) remained on the filters. tRNAarg and tRNAlys which do not contain i6A showed no binding. This finding will be useful as a very simple and rapid assay of such RNAs under a variety of conditions. Purification of i6A containing tRNAs from an unfractionated tRNA mixture was achieved by affinity chromatography of the tRNAs on an i6A antibody-Sepharose column. Nonspecific binding of tRNAs to the column was avoided by the use of purified antibodies.

Genome-wide identification and characterization of cytochrome P450 monooxygenase genes in the ciliate Tetrahymena thermophila

Background: Cytochrome P450 monooxygenases play key roles in the metabolism of a wide variety of substrates and they are closely associated with endocellular physiological processes or detoxification metabolism under environmental exposure. To date, however, none has been systematically characterized in the phylum Ciliophora. T. thermophila possess many advantages as a eukaryotic model organism and it exhibits rapid and sensitive responses to xenobiotics, making it an ideal model system to study the evolutionary and functional diversity of the P450 monooxygenase gene family. Results: A total of 44 putative functional cytochrome P450 genes were identified and could be classified into 13 families and 21 sub-families according to standard nomenclature. The characteristics of both the conserved intron-exon organization and scaffold localization of tandem repeats within each P450 family clade suggested that the enlargement of T. thermophila P450 families probably resulted from recent separate small duplication events. Gene expression patterns of all T. thermophila P450s during three important cell physiological stages (vegetative growth, starvation and conjugation) were analyzed based on EST and microarray data, and three main categories of expression patterns were postulated. Evolutionary analysis including codon usage preference, sit-especific selection and gene-expression evolution patterns were investigated and the results indicated remarkable divergences among the T. thermophila P450 genes. Conclusion: The characterization, expression and evolutionary analysis of T. thermophila P450 monooxygenase genes in the current study provides useful information for understanding the characteristics and diversities of the P450 genes in the Ciliophora, and provides the baseline for functional analyses of individual P450 isoforms in this model ciliate species.

Molecular identification and expression analysis of tumor necrosis factor receptor-associated factor 2 in grass carp Ctenopharyngodon idella

Tumor necrosis factor receptor-associated factor 2 (TRAF2) is a crucial component of almost the entire tumor necrosis factor receptor superfamily signaling pathway. In the present study, a TRAF2 gene has been cloned from grass carp (Ctenopharyngodon idella) by reverse transcription-polymerase chain reaction and rapid amplification of cDNA ends. The full-length cDNA is 3162 bp, including a 60 bp 5' untranslated region (UTR), a 1611 bp open reading frame, and a 1491 bp 3' UTR. The polyadenylation signal (AATAAA) and the mRNA instability motifs (ATTTTA, ATTTA) were followed by a poly(A) tail in the 3' UTR. No signal peptide or transmembrane region has been found in the putative amino acids of grass carp TRAF2 (gcTRAF2). Phylogenetic tree analysis clearly showed that gcTRAF2 is nearest to the TRAF2 gene of goldfish. The identity of gcTRAF2 with its homologs in other vertebrates ranges from 56% to 97%. It is characterized by one RING-type signature at the N-terminus, one zinc finger in the middle part, and one conserved TRAF domain consisting of a C-proximal (TRAF-C) subdomain and a N-proximal (TRAF-N) subdomain. The identity of TRAF-C among all TRAF2 homologs in vertebrates varies from 78% to 97%, whereas the identity of TRAF-N ranges from 56% to 100%. The recombinant gcTRAF2 has been expressed in Escherichia coli using pET-32a expression vector. The rabbit anti-gcTRAF2 polyclonal antibody was obtained. The expression of gcTRAF2 in different organs was examined by real-time quantitative polymerase chain reaction and Western blot analysis. It was widely distributed in heart, head kidney, thymus, brain, gill, liver, spleen, and trunk kidney. This is the first report of a TRAF2 homolog molecule in fish.