Connected OFCity Challenge: Addressing the Digital Divide in the Developing World

Over the past 50 years, the development of information and communications technology has provided unprecedented support to the steady economic growth of developed countries. In recent years, some of the largest growth has been reported in emerging economies, which, however, often lack adequate telecommunications infrastructure to further sustain their development. Although a number of service providers and system vendors have started to address the issue, the challenges they encounter are substantially different from those in the developed world, including an unreliable electricity grid, poor fiber infrastructure, low revenue expectations, and often a harsh climate environment. This paper reports use cases and solutions pertinent to the development of the networking infrastructure in emerging economies, provided by organizations directly involved in such activities. After providing some background information on the current state of network infrastructure and the main challenges for Africa and rural China, the paper provides details on two proposed solutions. The first focuses on the provisioning of services and network infrastructure through the development of low-cost data centers, whereas the second proposes cost-effective adaptation of both fiber and hybrid copper-fiber technology to rural areas. The article is concluded with a brief discussion on the complementarity of the two approaches

Dehydroepiandrosterone sulfate linked to physiologic response against hot spring immersion

[[abstract]]The steroid dehydroepiandrosterone sulfate (DHEA-S) is associated with longevity and adaptation against external stress in humans. The aim of the study was to investigate the acute effect of a 30-min hot spring immersion at 41 degrees C on insulin resistance measures of 16 male subjects, in relation to DHEA-S level. To elucidate the role of DHEA-S in the coping against the heat stress, all subjects were evenly divided into lower and upper halves according to their baseline DHEA-S concentrations. The levels of glucose, insulin, blood pressure, and stress hormones (growth hormone, testosterone, and cortisol) in both groups were compared before and after hot spring immersion. The result shows that hot spring immersion significantly increased heart rate and reduced diastolic blood pressure, both of which were paralleled with a drop of DHEA-S concentration. Homeostasis model assessment for insulin resistance (HOMA-IR) and area under curve of glucose (GAUC) of oral glucose tolerance test were significantly increased by the hot spring immersion only in the Low DHEA-S group. Likewise, hot spring immersion caused an opposing effect on cortisol changes for the Low and High DHEA-S groups (+95% vs. -33%, p < 0.05). respectively. In conclusion, hot spring bathing induced insulin resistance confined only to those Low DHEA-S individuals. This response may be associated with a stress response Such as increased cortisol levels. (C) 2009 Elsevier Inc. All rights reserved

Impact of Radiotherapy, Chemotherapy and Surgery in Multimodal Treatment of Locally Advanced Esophageal Cancer

Objectives: It was the aim of this study to assess our institutional experience with definitive chemoradiation (CRT) versus induction chemotherapy followed by CRT with or without surgery (C-CRT/S) in esophageal cancer. Methods: We retrospectively analyzed 129 institutional patients with locally advanced esophageal cancer who had been treated by either CRT in analogy to the RTOG 8501 trial (n = 78) or C-CRT/S (n = 51). Results: The median, 2-and 5-year overall survival (OS) of the entire collective was 17.6 months, 42 and 24%, respectively, without a significant difference between the CRT and C-CRT/S groups. In C-CRT/S patients, surgery statistically improved the locoregional control (LRC) rates (2-year LRC 73.6 vs. 21.2%; p = 0.003); however, this was translated only into a trend towards improved OS (p = 0.084). The impact of escalated radiation doses (>= 60.0 vs. <60.0 Gy) on LRC was detectable only in T1-3 N0-1 M0 patients of the CRT group (2-year LRC 77.8 vs. 42.3%; p = 0.036). Conclusion: Definitive CRT and a trimodality approach including surgery (C-CRT/S) had a comparable outcome in this unselected patient collective. Surgery and higher radiation doses improve LRC rates in subgroups of patients, respectively, but without effect on OS. Copyright (C) 2012 S. Karger AG, Base

Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

An unusual variant of choledochal cyst: a case report

<p>Abstract</p> <p>Introduction</p> <p>Choledochal cyst is an uncommon congenital disease of the biliary tract in the UK. There are five main types of choledochal cyst with several recognised sub-types. However, occasional variants do occur.</p> <p>Case presentation</p> <p>We report a case of a female infant with an antenatally diagnosed choledochal cyst. The operative cholangiogram revealed an unusual intrahepatic biliary tree. The cyst was successfully excised and the infant is well at 18-months follow up.</p> <p>Conclusion</p> <p>The anatomy should be clearly defined before surgical excision as abnormal variants can occur, which usually do not fit into the known classification types and subtypes.</p

Elastic shear wave scattering by randomly rough surfaces

Characterizing cracks within elastic media forms an important aspect of ultrasonic non-destructive evaluation (NDE) where techniques such as time-of-flight diffraction and pulse-echo are often used with the presumption of scattering from smooth, straight cracks. However, cracks are rarely straight, or smooth, and recent attention has focussed upon rough surface scattering primarily by longitudinal wave excitations. We provide a comprehensive study of scattering by incident shear waves, thus far neglected in models of rough surface scattering despite their practical importance in the detection of surface-breaking defects, using modelling, simulation and supporting experiments. The scattering of incident shear waves introduces challenges, largely absent in the longitudinal case, related to surface wave mode-conversion, the reduced range of validity of the Kirchhoff approximation (KA) as compared with longitudinal incidence, and an increased importance of correlation length. The expected reflection from a rough defect is predicted using a statistical model from which, given the angle of incidence and two statistical parameters, the expected reflection amplitude is obtained instantaneously for any scattering angle and length of defect. If the ratio of correlation length to defect length exceeds a critical value, which we determine, there is an explicit dependence of the scattering results on correlation length, and we modify the modelling to find this dependence. The modelling is cross-correlated against Monte Carlo simulations of many different surface profiles, sharing the same statistical parameter values, using numerical simulation via ray models (KA) and finite element (FE) methods accelerated with a GPU implementation. Additionally we provide experimental validations that demonstrate the accuracy of our predictions

Electrically Tunable Excitonic Light Emitting Diodes based on Monolayer WSe2 p-n Junctions

Light-emitting diodes are of importance for lighting, displays, optical interconnects, logic and sensors. Hence the development of new systems that allow improvements in their efficiency, spectral properties, compactness and integrability could have significant ramifications. Monolayer transition metal dichalcogenides have recently emerged as interesting candidates for optoelectronic applications due to their unique optical properties. Electroluminescence has already been observed from monolayer MoS2 devices. However, the electroluminescence efficiency was low and the linewidth broad due both to the poor optical quality of MoS2 and to ineffective contacts. Here, we report electroluminescence from lateral p-n junctions in monolayer WSe2 induced electrostatically using a thin boron nitride support as a dielectric layer with multiple metal gates beneath. This structure allows effective injection of electrons and holes, and combined with the high optical quality of WSe2 it yields bright electroluminescence with 1000 times smaller injection current and 10 times smaller linewidth than in MoS2. Furthermore, by increasing the injection bias we can tune the electroluminescence between regimes of impurity-bound, charged, and neutral excitons. This system has the required ingredients for new kinds of optoelectronic devices such as spin- and valley-polarized light-emitting diodes, on-chip lasers, and two-dimensional electro-optic modulators.Comment: 13 pages main text with 4 figures + 4 pages upplemental material

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity