An Evaluation of Compression Schemes for Wireless Networks

Data gathering, either for event recognition or for monitoring applications is the primary intention for sensor network deployments. In many cases, data is acquired periodically and autonomously, and simply logged onto secondary storage (e.g. flash memory) either for delayed offline analysis or for on demand burst transfer. Moreover, operational data such as connectivity information, node and network state is typically kept as well. Naturally, measurement and/or connectivity logging comes at a cost. Space for doing so is limited. Finding a good representative model for the data and providing clever coding of information, thus data compression, may be a means to use the available space to its best. In this paper, we explore the design space for data compression for wireless sensor and mesh networks by profiling common, publicly available algorithms. Several goals such as a low overhead in terms of utilized memory and compression time as well as a decent compression ratio have to be well balanced in order to find a simple, yet effective compression scheme.

Diffusion-weighted MRI in head and neck radiology: applications in oncology

Extracranial application of diffusion-weighted magnetic resonance imaging (MRI) has gained increasing importance in recent years. As a result of technical advances, this new non-invasive functional technique has also been applied in head and neck radiology for several clinical indications. In cancer imaging, diffusion-weighted MRI can be performed for tumour detection and characterization, monitoring of treatment response as well as the differentiation of recurrence and post-therapeutic changes after radiotherapy. Even for lymph node staging promising results have been reported recently. This review article provides overview of potential applications of diffusion-weighted MRI in head and neck with the main focus on its applications in oncology.

Genitourinary applications of diffusion-weighted MR imaging in the pelvis

Diffusion-weighted (DW) magnetic resonance (MR) imaging has a large number of potential clinical applications in the female and male pelvis and can easily be added to any routine MR protocol. In the female pelvis, DW imaging allows improvement of staging in endometrial and cervical cancer, especially in locally advanced disease and in patients in whom contrast medium administration should be avoided. It can also be helpful in characterizing complex adnexal masses and in depicting recurrent tumor after treatment of various gynecologic malignancies. DW imaging shows promising results in monitoring treatment response in patients undergoing radiation therapy of cervical cancer. An increase in apparent diffusion coefficient (ADC) values of responders precedes changes in size and may therefore allow early assessment of treatment success. In the male pelvis, the detection of prostate cancer in the peripheral zone is relatively easier than in the central gland based on the underlying ADC values, whereas overlapping values reported in the central gland still need further research. DW imaging might also be applied in the noninvasive evaluation of bladder cancer to differentiate between superficial and muscle-invasive tumors. Initial promising results have been reported in differentiating benign from malignant pelvic lymph nodes based on the ADC values; however, larger-scale studies will be needed to allow the detection of lymph node metastases in an individual patient. Prerequisites for successfully performing DW imaging of the female and male pelvis are standardization of the DW imaging technique, including the choice of b values, administration of an antiperistaltic drug, and comparison of DW findings with those of morphologic MR imaging.

Non-invasive monitoring of renal oxygenation using BOLD-MRI: a reproducibility study

Blood oxygenation level-dependent (BOLD) MRI was shown to allow non-invasive observation of renal oxygenation in humans. However, clinical applications of this type of functional MRI of the kidney are still limited, most likely because of difficulties in obtaining reproducible and reliable information. The aim of this study was to evaluate the reproducibility and robustness of a BOLD method applied to the kidneys and to identify systematic physiological changes potentially influencing the renal oxygenation of healthy volunteers. To measure the BOLD effect, a modified multi-echo data image combination (MEDIC) sequence was used to acquire 12 T2*-weighted images within a single breath-hold. Three identical measurements were performed on three axial and three coronal slices of right and left kidneys in 18 volunteers. The mean R2* (1/T2*) values determined in medulla and cortex showed no significant differences over three repetitions and low intra-subject coefficients of variation (CV) (3 and 4% in medulla and cortex, respectively). The average R2* values were higher in the medulla (16.15 +/- 0.11) than in the cortex (11.69 +/- 0.18) (P < 0.001). Only a minor influence of slice orientation was observed. Mean R2* values were slightly higher (3%) in the left than in the right kidney (P < 0.001). Differences between volunteers were identified (P < 0.001). Part of these differences was attributable to age-dependent R2* values, since these values increased with age when medulla (P < 0.001, r = 0.67) or cortex (P < 0.020, r = 0.42) were considered. Thus, BOLD measurements in the kidney are highly reproducible and robust. The results allow one to identify the known cortico-medullary gradient of oxygenation evidenced by the gradient of R2* values and suggest that medulla is more hypoxic in older than younger individuals. BOLD-MRI is therefore a useful tool to study sequentially and non-invasively regional oxygenation of human kidneys.

Extracranial applications of diffusion-weighted magnetic resonance imaging

Diffusion-weighted MRI has become more and more popular in the last couple of years. It is already an accepted diagnostic tool for patients with acute stroke, but is more difficult to use for extracranial applications due to technical challenges mostly related to motion sensitivity and susceptibility variations (e.g., respiration and air-tissue boundaries). However, thanks to the newer technical developments, applications of body DW-MRI are starting to emerge. In this review, we aim to provide an overview of the current status of the published data on DW-MRI in extracranial applications. A short introduction to the physical background of this promising technique is provided, followed by the current status, subdivided into three main topics, the functional evaluation, tissue characterization and therapy monitoring.

Steam pops during irrigated radiofrequency ablation: feasibility of impedance monitoring for prevention

BACKGROUND: Steam pops are a risk of irrigated radiofrequency catheter ablation (RFA) and may cause cardiac perforation. Data to guide radiofrequency (RF) energy titration to avoid steam pops are limited. OBJECTIVE: This study sought to assess the frequency and consequence of audible pops and to determine the feasibility of using the magnitude of impedance change to predict pops. METHODS: We reviewed consecutive endocardial open-irrigated RFA for ventricular tachycardia (VT) with continuously recorded ablation data in 142 patients with structural heart disease. Steam pops were defined as an audible pop associated with a sudden spike in impedance. Ablation lesions before or after pops served as controls. RESULTS: From a total of 4,107 ablation lesions, 62 (1.5%) steam pops occurred in 42 procedures in 38 patients. Perforation with tamponade occurred with 1 of 62 (2%) pops. Applications with pops had a greater impedance decrease (22 +/- 7 Omega vs. 18 +/- 8 Omega, P = .001) and a higher maximum power (45 +/- 5 W vs. 43 +/- 6 W, P = .011), but did not differ in maximum catheter tip temperature (40 degrees C +/- 4 degrees C vs. 40 degrees C +/- 4 degrees C, P = .180) from applications without pops. Eighty percent of pops occurred after impedance decreased by at least 18 Omega. CONCLUSION: During VT ablation with open irrigation, audible pops are infrequent and do not usually cause perforation. Limiting RF power to achieve an impedance decrease of <18 Omega is a feasible method of reducing the likelihood of a pop when perforation risk is of concern.

Unanticipated Partial Behavioral Reflection: Adapting Applications at Runtime

Dynamic, unanticipated adaptation of running systems is of interest in a variety of situations, ranging from functional upgrades to on-the-fly debugging or monitoring of critical applications. In this paper we study a particular form of computational reflection, called unanticipated partial behavioral reflection, which is particularly well-suited for unanticipated adaptation of real-world systems. Our proposal combines the dynamicity of unanticipated reflection, i.e. reflection that does not require preparation of the code of any sort, and the selectivity and efficiency of partial behavioral reflection. First, we propose unanticipated partial behavioral reflection which enables the developer to precisely select the required reifications, to flexibly engineer the metalevel and to introduce the meta behavior dynamically. Second, we present a system supporting unanticipated partial behavioral reflection in Squeak Smalltalk, called Geppetto, and illustrate its use with a concrete example of a web application. Benchmarks validate the applicability of our proposal as an extension to the standard reflective abilities of Smalltalk.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D-1), Simpson's dominance (D-2), Simpson's evenness (E), and Berger-Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P.lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.

Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Diffusion-weighted imaging in musculoskeletal radiology-clinical applications and future directions

Diffusion-weighted imaging (DWI) is an established diagnostic tool with regards to the central nervous system (CNS) and research into its application in the musculoskeletal system has been growing. It has been shown that DWI has utility in differentiating vertebral compression fractures from malignant ones, assessing partial and complete tears of the anterior cruciate ligament (ACL), monitoring tumor response to therapy, and characterization of soft-tissue and bone tumors. DWI is however less useful in differentiating malignant vs. infectious processes. As of yet, no definitive qualitative or quantitative properties have been established due to reasons ranging from variability in acquisition protocols to overlapping imaging characteristics. Even with these limitations, DWI can still provide clinically useful information, increasing diagnostic accuracy and improving patient management when magnetic resonance imaging (MRI) findings are inconclusive. The purpose of this article is to summarize recent research into DWI applications in the musculoskeletal system.

Segmented ionization chambers for beam monitoring in hadrontherapy.

Segmented ionization chambers represent a good solution to monitor the position, the intensity and the shape of ion beams in hadrontherapy. Pixel and strip chambers have been developed for both passive scattering and active scanning dose delivery systems. In particular, strip chambers are optimal for pencil beam scanning, allowing for spatial and time resolutions below 0.1 mm and 1 ms, respectively. The MATRIX pixel and the Strip Accurate Monitor for Beam Applications (SAMBA) detectors are described in this paper together with the results of several beam tests and industrial developments based on these prototypes.