Computing Traversal Times on Dynamic Markovian Paths

In source routing, a complete path is chosen for a packet to travel from source to destination. While computing the time to traverse such a path may be straightforward in a fixed, static graph, doing so becomes much more challenging in dynamic graphs, in which the state of an edge in one time slot (i.e., its presence or absence) is random, and may depend on its state in the previous time step. The traversal time is due to both time spent waiting for edges to appear and time spent crossing them once they become available. We compute the expected traversal time (ETT) for a dynamic path in a number of special cases of stochastic edge dynamics models, and for three edge failure models, culminating in a surprisingly challenging yet realistic setting in which the initial configuration of edge states for the entire path is known. We show that the ETT for this "initial configuration" setting can be computed in quadratic time, by an algorithm based on probability generating functions. We also give several linear-time upper and lower bounds on the ETT.Comment: 11 pages, 1 figur

Broadcast scheduling with data bundles

Broadcast scheduling has been extensively studied in wireless environments, where a base station broadcasts data to multiple users. Due to the sole wireless channel's limited bandwidth, only a subset of the needs may be satisfiable, and so maximizing total (weighted) throughput is a popular objective. In many realistic applications, however, data are dependent or correlated in the sense that the joint utility of a set of items is not simply the sum of their individual utilities. On the one hand, substitute data may provide overlapping information, so one piece of data item may have lower value if a second data item has already been delivered; on the other hand, complementary data are more valuable than the sum of their parts, if, for example, one data item is only useful in the presence of a second data item. In this paper, we define a data bundle to be a set of data items with possibly nonadditive joint utility, and we study a resulting broadcast scheduling optimization problem whose objective is to maximize the utility provided by the data delivered

Utility-based joint sensor selection and congestion control for task-oriented WSNs

Task-centric wireless sensor network environments are often characterized by the simultaneous operation of multiple tasks. Individual tasks compete for constrained resources and thus need resource mediation algorithms at two levels. First, different sensors must be allocated to different tasks based on the combination of sensor attributes and task requirements. Subsequently, sensor data rates on various data routes must be dynamically adapted to share the available wireless bandwidth, especially when links experience traffic congestion. In this paper we investigate heuristics for incrementally modifying the sensor-task matching process to incorporate changes in the transport capacity constraints or feasible task utility values

Positron-emission tomography–based staging reduces the prognostic impact of early disease progression in patients with follicular lymphoma

Background: Previous studies reported that early progression of disease (POD) after initial therapy predicted poor overall survival (OS) in patients with follicular lymphoma (FL). Here, we investigated whether pre-treatment imaging modality had an impact on prognostic significance of POD. Methods: In this retrospective study, we identified 1088 patients with grade I–IIIA FL; of whom, 238 patients with stage II–IV disease were initially treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP), and 346 patients were treated with rituximab-based chemotherapy. Patients (N = 484) from the FOLL05 study served as an independent validation cohort. We risk-stratified patients based on pre-treatment radiographic imaging (positron-emission tomography [PET] versus computed tomography [CT]) and early POD status using event-defining and landmark analyses. A competing risk analysis evaluated the association between early POD and histologic transformation. Results: In the discovery cohort, patients with POD within 24 months (PFS24) of initiating R-CHOP therapy had a 5-year OS of 57.6% for CT-staged patients compared with 70.6% for PET-staged patients. In the validation cohort, the 5-year OS for patients with early POD was 53.9% and 100% in CT- and PET-staged patients, respectively. The risk of histologic transformation in patients whose disease progressed within one year of initiating therapy was higher in CT-staged patients than in PET-staged patients (16.7% versus 6.3%, respectively), which was associated with a 9.7-fold higher risk of death. Conclusion: In FL, pre-treatment PET staging reduced the prognostic impact of early POD compared with CT staging. Patients with early POD and no histologic transformation have an extended OS with standard therapy

Altered hippocampal-prefrontal neural dynamics in mouse models of Down syndrome

Altered neural dynamics in the medial prefrontal cortex (mPFC) and hippocampus may contribute to cognitive impairments in the complex chromosomal disorder Down syndrome (DS). Here, we demonstrate non-overlapping behavioral differences associated with distinct abnormalities in hippocampal and mPFC electrophysiology during a canonical spatial working memory task in three partially trisomic mouse models of DS (Dp1Tyb, Dp10Yey, and Dp17Yey) that together cover all regions of homology with human chromosome 21 (Hsa21). Dp1Tyb mice show slower decision-making (unrelated to the gene dose of DYRK1A, which has been implicated in DS cognitive dysfunction) and altered theta dynamics (reduced frequency, increased hippocampal-mPFC coherence, and increased modulation of hippocampal high gamma); Dp10Yey mice show impaired alternation performance and reduced theta modulation of hippocampal low gamma; and Dp17Yey mice are not significantly different from the wild type. These results link specific hippocampal and mPFC circuit dysfunctions to cognitive deficits in DS models and, importantly, map them to discrete regions of Hsa21

Occupying wide open spaces? Late Pleistocene hunter–gatherer activities in the Eastern Levant

With a specific focus on eastern Jordan, the Epipalaeolithic Foragers in Azraq Project explores changing hunter-gatherer strategies, behaviours and adaptations to this vast area throughout the Late Pleistocene. In particular, we examine how lifeways here (may have) differed from surrounding areas and what circumstances drew human and animal populations to the region. Integrating multiple material cultural and environmental datasets, we explore some of the strategies of these eastern Jordanian groups that resulted in changes in settlement, subsistence and interaction and, in some areas, the occupation of substantial aggregation sites. Five years of excavation at the aggregation site of Kharaneh IV suggest some very intriguing technological and social on-site activities, as well as adaptations to a dynamic landscape unlike that of today. Here we discuss particular aspects of the Kharaneh IV material record within the context of ongoing palaeoenvironmental reconstructions and place these findings in the wider spatial and temporal narratives of the Azraq Basin

A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory x-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and setting