Service Descriptions and Linked Data for Integrating WSNs into Enterprise IT

This paper presents our ongoing work on enterprise IT integration of sensor networks based on the idea of service descriptions and applying linked data principles to them. We argue that using linked service descriptions facilitates a better integration of sensor nodes into enterprise IT systems and allows SOA principles to be used within the enterprise IT and within the sensor network itself.

Harvesting local cylinder autograft from adjacent vertebral body for anterior lumbar interbody fusion: surgical technique, operative feasibility and preliminary clinical results

Autogenous iliac crest has long served as the gold standard for anterior lumbar arthrodesis although added morbidity results from the bone graft harvest. Therefore, femoral ring allograft, or cages, have been used to decrease the morbidity of iliac crest bone harvesting. More recently, an experimental study in the animal showed that harvesting local bone from the anterior vertebral body and replacing the void by a radio-opaque beta-tricalcium phosphate plug was a valid concept. However, such a concept precludes theoretically the use of posterior pedicle screw fixation. At one institution a consecutive series of 21 patients underwent single- or multiple-level circumferential lumbar fusion with anterior cages and posterior pedicle screws. All cages were filled with cancellous bone harvested from the adjacent vertebral body, and the vertebral body defect was filled with a beta-tricalcium phosphate plug. The indications for surgery were failed conservative treatment of a lumbar degenerative disc disease or spondylolisthesis. The purpose of this study, therefore, was to report on the surgical technique, operative feasibility, safety, benefits, and drawbacks of this technique with our primary clinical experience. An independent researcher reviewed all data that had been collected prospectively from the onset of the study. The average age of the patients was 39.9 (26-57) years. Bone grafts were successfully harvested from 28 vertebral bodies in all but one patient whose anterior procedure was aborted due to difficulty in freeing the left common iliac vein. This case was converted to a transforaminal interbody fusion (TLIF). There was no major vascular injury. Blood loss of the anterior procedure averaged 250 ml (50-350 ml). One tricalcium phosphate bone plug was broken during its insertion, and one endplate was broken because of wrong surgical technique, which did not affect the final outcome. One patient had a right lumbar plexopathy that was not related to this special technique. There was no retrograde ejaculation, infection or pseudoarthrosis. One patient experienced a deep venous thrombosis. At the last follow up (mean 28 months) all patients had a solid lumbar spine fusion. At the 6-month follow up, the pain as assessed on the visual analog scale (VAS) decreased from 6.9 to 4.5 (33% decrease), and the Oswestry disability index (ODI) reduced from 48.0 to 31.7 with a 34% reduction. However, at 2 years follow up there was a trend for increase in the ODI (35) and VAS (5). The data in this study suggest that harvesting a cylinder of autograft from the adjacent vertebral body is safe and efficient. Filling of the void defect with a beta-tricalcium phosphate plug does not preclude the use of posterior pedicle screw stabilization.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS

Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been conducted to solve the problems underlying the middleware services of sensor networks, such as self-deployment, self-localization, and synchronization. With the provided middleware services, sensor networks have grown into a mature technology to be used as a detection and surveillance paradigm for many real-world applications. The individual sensors are small in size. Thus, they can be deployed in areas with limited space to make unobstructed measurements in locations where the traditional centralized systems would have trouble to reach. However, there are a few physical limitations to sensor networks, which can prevent sensors from performing at their maximum potential. Individual sensors have limited power supply, the wireless band can get very cluttered when multiple sensors try to transmit at the same time. Furthermore, the individual sensors have limited communication range, so the network may not have a 1-hop communication topology and routing can be a problem in many cases. Carefully designed algorithms can alleviate the physical limitations of sensor networks, and allow them to be utilized to their full potential. Graphical models are an intuitive choice for designing sensor network algorithms. This thesis focuses on a classic application in sensor networks, detecting and tracking of targets. It develops feasible inference techniques for sensor networks using statistical graphical model inference, binary sensor detection, events isolation and dynamic clustering. The main strategy is to use only binary data for rough global inferences, and then dynamically form small scale clusters around the target for detailed computations. This framework is then extended to network topology manipulation, so that the framework developed can be applied to tracking in different network topology settings. Finally the system was tested in both simulation and real-world environments. The simulations were performed on various network topologies, from regularly distributed networks to randomly distributed networks. The results show that the algorithm performs well in randomly distributed networks, and hence requires minimum deployment effort. The experiments were carried out in both corridor and open space settings. A in-home falling detection system was simulated with real-world settings, it was setup with 30 bumblebee radars and 30 ultrasonic sensors driven by TI EZ430-RF2500 boards scanning a typical 800 sqft apartment. Bumblebee radars are calibrated to detect the falling of human body, and the two-tier tracking algorithm is used on the ultrasonic sensors to track the location of the elderly people.

PROOF OF CONCEPT PROTOTYPE FOR A RAILROAD PEDESTRIAN WARNING SYSTEM USING WIRELESS SENSOR NETWORKS

Wireless sensor network is an emerging research topic due to its vast and ever-growing applications. Wireless sensor networks are made up of small nodes whose main goal is to monitor, compute and transmit data. The nodes are basically made up of low powered microcontrollers, wireless transceiver chips, sensors to monitor their environment and a power source. The applications of wireless sensor networks range from basic household applications, such as health monitoring, appliance control and security to military application, such as intruder detection. The wide spread application of wireless sensor networks has brought to light many research issues such as battery efficiency, unreliable routing protocols due to node failures, localization issues and security vulnerabilities. This report will describe the hardware development of a fault tolerant routing protocol for railroad pedestrian warning system. The protocol implemented is a peer to peer multi-hop TDMA based protocol for nodes arranged in a linear zigzag chain arrangement. The basic working of the protocol was derived from Wireless Architecture for Hard Real-Time Embedded Networks (WAHREN).

Evaluation of early tissue reactions after lumbar intertransverse process fusion using CT in a rabbit

OBJECTIVE: The objective of the study was to evaluate tissue reactions such as bone genesis, cartilage genesis and graft materials in the early phase of lumbar intertransverse process fusion in a rabbit model using computed tomography (CT) imaging with CT intensity (Hounsfield units) measurement, and to compare these data with histological results. MATERIALS AND METHODS: Lumbar intertransverse process fusion was performed on 18 rabbits. Four graft materials were used: autograft bone (n = 3); collagen membrane soaked with recombinant human bone morphogenetic protein-2 (rhBMP-2) (n = 5); granular calcium phosphate (n = 5); and granular calcium phosphate coated with rhBMP-2 (n = 5). All rabbits were euthanized 3 weeks post-operatively and lumbar spines were removed for CT imaging and histological examination. RESULTS: Computed tomography imaging demonstrated that each fusion mass component had the appropriate CT intensity range. CT also showed the different distributions and intensities of bone genesis in the fusion masses between the groups. Each component of tissue reactions was identified successfully on CT images using the CT intensity difference. Using CT color mapping, these observations could be easily visualized, and the results correlated well with histological findings. CONCLUSIONS: The use of CT intensity is an effective approach for observing and comparing early tissue reactions such as newly synthesized bone, newly synthesized cartilage, and graft materials after lumbar intertransverse process fusion in a rabbit model.

Hop-to-Hop Reliability in IP-Based Wireless Sensor Networks - A Cross-Layer Approach

To interconnect a wireless sensor network (WSN) to the Internet, we propose to use TCP/IP as the standard protocol for all network entities. We present a cross layer designed communication architecture, which contains a MAC protocol, IP, a new protocol called Hop-to-Hop Reliability (H2HR) protocol, and the TCP Support for Sensor Nodes (TSS) protocol. The MAC protocol implements the MAC layer of beacon-less personal area networks (PANs) as defined in IEEE 802.15.4. H2HR implements hop-to-hop reliability mechanisms. Two acknowledgment mechanisms, explicit and implicit ACK are supported. TSS optimizes using TCP in WSNs by implementing local retransmission of TCP data packets, local TCP ACK regeneration, aggressive TCP ACK recovery, congestion and flow control algorithms. We show that H2HR increases the performance of UDP, TCP, and RMST in WSNs significantly. The throughput is increased and the packet loss ratio is decreased. As a result, WSNs can be operated and managed using TCP/IP.

Conserved leucine residue in the head region of morbillivirus fusion protein regulates the large conformational change during fusion activity

Paramyxovirus cell entry is controlled by the concerted action of two viral envelope glycoproteins, the fusion (F) and the receptor-binding (H) proteins, which together with a cell surface receptor mediate plasma membrane fusion activity. The paramyxovirus F protein belongs to class I viral fusion proteins which typically contain two heptad repeat regions (HR). Particular to paramyxovirus F proteins is a long intervening sequence (IS) located between both HR domains. To investigate the role of the IS domain in regulating fusogenicity, we mutated in the canine distemper virus (CDV) F protein IS domain a highly conserved leucine residue (L372) previously reported to cause a hyperfusogenic phenotype. Beside one F mutant, which elicited significant defects in processing, transport competence, and fusogenicity, all remaining mutants were characterized by enhanced fusion activity despite normal or slightly impaired processing and cell surface targeting. Using anti-CDV-F monoclonal antibodies, modified conformational F states were detected in F mutants compared to the parental protein. Despite these structural differences, coimmunoprecipitation assays did not reveal any drastic modulation in F/H avidity of interaction. However, we found that F mutants had significantly enhanced fusogenicity at low temperature only, suggesting that they folded into conformations requiring less energy to activate fusion. Together, these data provide strong biochemical and functional evidence that the conserved leucine 372 at the base of the HRA coiled-coil of F(wt) controls the stabilization of the prefusogenic state, restraining the conformational switch and thereby preventing extensive cell-cell fusion activity.

Application of Time-Delay Estimation to Mixed Reality Multisensor Tracking

Spatial tracking is one of the most challenging and important parts of Mixed Reality environments. Many applications, especially in the domain of Augmented Reality, rely on the fusion of several tracking systems in order to optimize the overall performance. While the topic of spatial tracking sensor fusion has already seen considerable interest, most results only deal with the integration of carefully arranged setups as opposed to dynamic sensor fusion setups. A crucial prerequisite for correct sensor fusion is the temporal alignment of the tracking data from several sensors. Tracking sensors are typically encountered in Mixed Reality applications, are generally not synchronized. We present a general method to calibrate the temporal offset between different sensors by the Time Delay Estimation method which can be used to perform on-line temporal calibration. By applying Time Delay Estimation on the tracking data, we show that the temporal offset between generic Mixed Reality spatial tracking sensors can be calibrated. To show the correctness and the feasibility of this approach, we have examined different variations of our method and evaluated various combinations of tracking sensors. We furthermore integrated this time synchronization method into our UBITRACK Mixed Reality tracking framework to provide facilities for calibration and real-time data alignment.

Illusions of fusions: assessing cervical vertebral fusion on lateral cephalograms, multidetector computed tomographs, and cone-beam computed tomographs

INTRODUCTION The aims of this study were to compare lateral cephalograms with other radiologic methods for diagnosing suspected fusions of the cervical spine and to validate the assessment of congenital fusions and osteoarthritic changes against the anatomic truth. METHODS Four cadaver heads were selected with fusion of vertebrae C2 and C3 seen on a lateral cephalogram. Multidetector computed tomography (MDCT) and cone-beam computed tomography (CBCT) were performed and assessed by 5 general radiologists and 5 oral radiologists, respectively. Vertebrae C2 and C3 were examined for osseous fusions, and the left and right facet joints were diagnosed for osteoarthritis. Subsequently, the C2 and C3 were macerated and appraised by a pathologist. Descriptive analysis was performed, and interrater agreements between and within the groups were computed. RESULTS All macerated specimens showed osteoarthritic findings of varying degrees, but no congenital bony fusion. All observers agreed that no fusion was found on MDCT or CBCT. They disagreed on the prevalence of osteoarthritic deformities (general radiologists/MDCT, 100%; oral radiologists/CBCT, 93.3%) and joint space assessment in the facet joints (kappa = 0.452). The agreement within the rater groups differed considerably (general radiologists/MDCT, kappa = 0.612; oral radiologists/CBCT, kappa = 0.240). CONCLUSIONS Lateral cephalograms do not provide dependable data to assess the cervical spine for fusions and cause false-positive detections. Both MDCT interpreted by general radiologists and CBCT interpreted by oral radiologists are reliable methods to exclude potential fusions. Degenerative osteoarthritic changes are diagnosed more accurately and consistently by general radiologists evaluating MDCT.

Structural rearrangements of the central region of the morbillivirus attachment protein stalk domain trigger F protein refolding for membrane fusion

It is unknown how receptor binding by the paramyxovirus attachment proteins (HN, H, or G) triggers the fusion (F) protein to fuse with the plasma membrane for cell entry. H-proteins of the morbillivirus genus consist of a stalk ectodomain supporting a cuboidal head; physiological oligomers consist of non-covalent dimer-of-dimers. We report here the successful engineering of intermolecular disulfide bonds within the central region (residues 91-115) of the morbillivirus H-stalk; a sub-domain that also encompasses the putative F-contacting section (residues 111-118). Remarkably, several intersubunit crosslinks abrogated membrane fusion, but bioactivity was restored under reducing conditions. This phenotype extended equally to H proteins derived from virulent and attenuated morbillivirus strains and was independent of the nature of the contacted receptor. Our data reveal that the morbillivirus H-stalk domain is composed of four tightly-packed subunits. Upon receptor binding, these subunits structurally rearrange, possibly inducing conformational changes within the central region of the stalk, which, in turn, promote fusion. Given that the fundamental architecture appears conserved among paramyxovirus attachment protein stalk domains, we predict that these motions may act as a universal paramyxovirus F-triggering mechanism.

Increasing the Antitumor Effect of an EpCAM-Targeting Fusion Toxin by Facile Click PEGylation

Fusion toxins used for cancer-related therapy have demonstrated short circulation half-lives, which impairs tumor localization and, hence, efficacy. Here, we demonstrate that the pharmacokinetics of a fusion toxin composed of a designed ankyrin repeat protein (DARPin) and domain I–truncated Pseudomonas Exotoxin A (PE40/ETA″) can be significantly improved by facile bioorthogonal conjugation with a polyethylene glycol (PEG) polymer at a unique position. Fusion of the anti-EpCAM DARPin Ec1 to ETA″ and expression in methionine-auxotrophic E. coli enabled introduction of the nonnatural amino acid azidohomoalanine (Aha) at position 1 for strain-promoted click PEGylation. PEGylated Ec1-ETA″ was characterized by detailed biochemical analysis, and its potential for tumor targeting was assessed using carcinoma cell lines of various histotypes in vitro, and subcutaneous and orthotopic tumor xenografts in vivo. The mild click reaction resulted in a well-defined mono-PEGylated product, which could be readily purified to homogeneity. Despite an increased hydrodynamic radius resulting from the polymer, the fusion toxin demonstrated high EpCAM-binding activity and retained cytotoxicity in the femtomolar range. Pharmacologic analysis in mice unveiled an almost 6-fold increase in the elimination half-life (14 vs. 82 minutes) and a more than 7-fold increase in the area under the curve (AUC) compared with non-PEGylated Ec1-ETA″, which directly translated in increased and longer-lasting effects on established tumor xenografts. Our data underline the great potential of combining the inherent advantages of the DARPin format with bioorthogonal click chemistry to overcome the limitations of engineering fusion toxins with enhanced efficacy for cancer-related therapy.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

Demo Abstract: Disseminating WMSN Data by Using Social Network and Web

For smart cities applications, a key requirement is to disseminate data collected from both scalar and multimedia wireless sensor networks to thousands of end-users. Furthermore, the information must be delivered to non-specialist users in a simple, intuitive and transparent manner. In this context, we present Sensor4Cities, a user-friendly tool that enables data dissemination to large audiences, by using using social networks, or/and web pages. The user can request and receive monitored information by using social networks, e.g., Twitter and Facebook, due to their popularity, user-friendly interfaces and easy dissemination. Additionally, the user can collect or share information from smart cities services, by using web pages, which also include a mobile version for smartphones. Finally, the tool could be configured to periodically monitor the environmental conditions, specific behaviors or abnormal events, and notify users in an asynchronous manner. Sensor4Cities improves the data delivery for individuals or groups of users of smart cities applications and encourages the development of new user-friendly services.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.