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Angioimmunoblastic T-cell lymphoma (AITL) and peripheral T-cell lymphoma with T follicular helper phenotype (PTCL-TFH) are a group of complex clinicopathological entities that originate from T follicular helper cells and share a similar mutation profile. Their diagnosis is often a challenge, particularly at an early stage, because of a lack of specific histological and immunophenotypic features, paucity of neoplastic T cells and prominent polymorphous infiltrate. We investigated whether the lymphoma-associated RHOA Gly17Val (c.50G>T) mutation, occurring in 60% of cases, is present in the early “reactive” lesions, and whether mutation analysis could help to advance the early diagnosis of lymphoma. The RHOA mutation was detected by quantitative polymerase chain reaction with a locked nucleic acid probe specific to the mutation, and a further peptide nucleic acid clamp oligonucleotide to suppress the amplification of the wild-type allele. The quantitative polymerase chain reaction assay was highly sensitive and specific, detecting RHOA Gly17Val at an allele frequency of 0.03%, but not other changes in Gly17, nor in 61 controls. Among the 37 cases of AITL and PTCL-TFH investigated, RHOA Gly17Val was detected in 62.2% (23/37) of which 19 had multiple biopsies including preceding biopsies in ten and follow-up biopsies in 11 cases. RHOA Gly17Val was present in each of these preceding or follow-up biopsies including 18 specimens that showed no evidence of lymphoma by combined histological, immunophenotypic and clonality analyses. The mutation was seen in biopsies 0-26.5 months (mean 7.87 months) prior to the lymphoma diagnosis. Our results show that RHOA Gly17Val mutation analysis is valuable in the early detection of AITL and PTCL-TFH.

State-of-the-art machine learning algorithms require large amount of high quality data. In practice, however, the sample size is commonly low and data is imbalanced along different class labels. Low sample size and imbalanced class distribution can significantly deteriorate the predictive performance of machine learning models. In order to overcome data quality issues, we propose a novel data augmentation method, Guided Deep Interpolation (GDI). It is based on a convolutional auto-encoder network, which is equipped with an auxiliary linear self-expressive layer. The network is trained by minimizing a composite objective function so that to extract the underlying clustered structure of semantic similarities of data points while high reconstruction quality is also preserved. The trained network is used to define a sampling strategy and a synthetic data generation procedure. Making use of the weights of the self-expressive layer, we introduce a measure of semantic variability to quantify how similar a data point to other data points on average. Based on the proposed measure of semantic variability, a joint distribution is defined. Using the distribution we can draw pairs of similar data points so that one point is semantically underrepresented (isolated) while its pair possesses relatively high semantic variability. A sampled pair is interpolated in the deep feature space of the network so that to increase semantic variability while preserve class label of the semantically underrepresented data point. The trained decoder is used to determine pixel space representations of latent space interpolations. The resulting data augmentation procedure generates synthetic samples by increasing the semantic variability of semantically underrepresented instances in a class label preserving way. Our experimental results show that the proposed method outperforms traditional and generative model-based data augmentation methods on low sample size and imbalanced data sets.

Scalability is an important requirement in the development and the operation of applications in a cloud environment. To handling heavy concurrency in the input load, many design-related and operational factors should be considered. The microservice architecture patterns provide better means to increase the scalability than traditional software architecture patterns. However, certain aspects of applications such as the need to persist/maintain the application state require additional measures in the design and the supporting mechanism. We propose a scalable routing mechanism for applications designed according to the microservice architecture. In particular, a cloud infrastructure resource reservation application has been designed with some stateful services. The proposed approach maintains a good scalability, which provides a mean to achieve the efficient usage of the infrastructure resources.

In order to communicate with another service, a service needs to know the address of other services. This knowledge can be acquired by a process called service discovery (SD). In a microservice architecture (MSA), unlike SOA, a service discovery framework has not been provided out of the box. In a telecom environment additional requirements may arise, besides the basic one of discoverability. In this paper we shortly present the state of the art in service discovery with reflections on the specific needs of MSA and in particular in the context of telecom applications. In this context open source frameworks are investigated and compared.

We present an overview of NP-hard problems and methods related to deployment, resource sharing, load balancing and fairness among multiple users in 5G mobile networks. We provide a general model of the system considering the E2E computational latency of Mobile Edge Computing (MEC) applications. An evaluation of a multi-user MEC offloading model reducible to the Multiple Knapsack Problem (MKP) is performed. We study the behaviour of an exact and a heuristic algorithm. We also show the performance results of these in a real-life small-cell deployment scenario.

YARN is an emerging resource management in the Hadoop ecosystem, where big data in the scale of petabytes/day are processed with the use of commercial off-the-shelf servers. At present YARN supports only RAM and CPU reservation/control. However, the reservation and the control of disk I/O throughput are also needed to provide a satisfactory performance for MapReduce applications. In this paper, we propose a solution with software components that can be integrated into YARN to support the reservation of disk I/O throughput in YARN. Experiments show that a proposed solution can provide a disk I/O throughput guarantee for MapReduce applications.

The hygiene hypothesis implies that the increasing prevalence of allergy in 'westernized' countries is explained by reduced bacterial exposure in early life, but the underlying mechanism remains elusive. We therefore wanted to study the effect of bacterial lipopolysaccharide (LPS) on the generation of regulatory T (T R ) cells in neonates, and to analyze differences between neonates with allergy risk because of a family history of atopy (FH + ) and controls without such hereditary risk (FH - ). Cord blood mononuclear cells from the FH + and FH - groups were stimulated with β-lactoglobulin in the presence of LPS. T-cell phenotypes suggestive of T R cells [CD25 + , CD25 high and integrin α E (CD103 + )], and the intracellular proliferation antigen Ki-67 were quantified by flow cytometry. Release of the immunosuppressive cytokine transforming growth factor β1 (TGF-β1) from its inactive complex was determined by enzyme-linked immunosorbent assay. The analyses revealed the generation of T-cell phenotypes suggestive of T R cells including a CD25 high T-cell subset which was inversely related to T-cell proliferation (r = -0.54, p < 0.05) and to activation-induced release of TGF-β1 (r = -0.80, p < 0.001). The CD25 high T-cell subset tended to be impaired in the FH + group (% of CD3 + T cells: FH + , 5.1% vs. FH-, 12.6%), and notably, the FH + group showed a significantly reduced capacity for generation of both CD25 + (FH + , 16.2% vs. FH - , 34.9%; p < 0.01) and α + E T cells (FH + , 2.1% vs. FH - , 3.9%; p < 0.05). Our findings suggested that early-life exposure to a dietary antigen in the presence of LPS might modulate the immune system by generating T R cells. This capacity was impaired in neonates with hereditary allergy risk, but clinical follow-up will be required to determine a possible effect on allergy emergence.

Resource management is one of the most indispens- able components of cluster-level infrastructure layers. Users of such systems should be able to specify their job requirements as a configuration parameter (CPU, memory, disk I/O, network I/O) that are translated into an appropriate resource reservation and resource allocation decision by the resource management function. YARN is an emerging resource management framework in the Hadoop ecosystem, which supports only memory and CPU reservation at present. In this paper, we propose a solution that takes into account the operation of the Hadoop Distributed File System to control the data rate of applications in the framework of a Hadoop compute platform. We utilize the property that a data pipe between a container and a DataNode consists of a disk I/O subpipe and a TCP/IP subpipe. We have implemented building block software components to control the data rate of data pipes between containers and DataNodes and provide a proof-of-concept with measurement results.

Evolved HSPA is a distributed, packet based radio access system that provides high user data rate and low latency. In our contribution the performance of streaming applications over Evolved HSPA is analyzed in realistic network scenarios. The simulation results indicate that in certain scenarios the adaptation latency experienced in case of applying 3GPP PSS Release 8-compliant streaming adaptation is excessively high, causing stream degradation and thus contributing to an end user experience of lower quality. Possible ways of mitigation are briefly outlined.

To understand the technical feasibility and user perception of mobile video, we conducted a two-week trial where a student community used mobile phone and web technologies to share the events of a campus festival. The questions we investigated included the capability of contemporary smart phones to capture and share the events via real time and stored video; the usage patterns that arise within mobile video community; and the social connections between shooters and viewers. Outcomes on the technical level indicate that challenges remain. The bandwidth of 3G cellular connections limits the quality of live videos and video transfer via public WLAN networks is unreliable causing lost connections. The best results today can be achieved by sending the captured videos from mobile phones to the server in the background and providing video-on-demand rather than live video service. The observed consumption patterns show that freshness of the videos is the least important selection factor while manual and automatic textual tagging is important. Seamless integration of video sharing to camera application would improve the user experience.

This paper targets mobile streaming in which Series 60 smart phones are the stream creators and PC-s are the stream consumers. The aim is to provide experimental data reflecting under which conditions video streaming from smart phones is feasible and whether duplex interactive video between a phone and a PC can be achieved or not. Phones used corporate WiFi and UMTS, PC-s were on the corporate Intranet and respectively on an ADSL connection. The outcomes of the experiments indicate that using the considered technologies and experimental setups in most scenarios video streaming from smart phones over WiFi and UMTS is feasible today, for about an hour. However, providing the level of interactivity needed for video calls is challenging, requiring additional measures. As for the extension of the streaming duration to several hours a technological breakthrough would be required.

In this paper a local connectivity solution is presented in which smart phones and PDA-s can connect to the enterprise intranet using either Bluetooth or Wi-Fi proximity networking via access points. The contribution highlights the differences at various levels of the implementation between the Bluetooth-based and Wi-Fi based components in our attempt to create a unified service level for Bluetooth-based, Wi-Fi based and both Bluetooth- and Wi-Fi based terminals (newer generation smart phones). Finally use cases and a list of applications are presented that can benefit from our solution in the enterprise segment.

This work studies a special multicasting problem in Bluetooth networks supporting point-to-point connections and piconets. The reason for the topic choice relies in the fact that Bluetooth, a de-facto proximity communication technique widely available in smart phones today, supports piconets, but sending content to more than 7 nodes is cumbersome. It turns out that by using a non-standard approach, that of parallel piconets of two nodes each, we can obtain a more efficient multicasting than through the legacy multicasting approach

With the imminent introduction of the 3G systems throughout the world precise cell planning in macrocell, microcell and picocell environments have become equally important. Beside coverage of the basic radio link quality parameter others such as rms delay spread and a measure of the system capacity have become increasingly important. Our contribution addresses the planning inside microcells based on a 3D deterministic ray-tracing propagation tool. It is based on the IHE model (Cichon, 1984) and a simple genetic algorithm (SGA) for the base station location optimization. At this stage the optimization is based on coverage and rms delay spread considerations. Our algorithm has as inputs the delay spread threshold and the minimum field strength. The cost function to be minimized is the number of locations in which the values of these parameters are above the threshold in the case of delay spread, and respectively below the threshold in the case of the field strength.

We have proposed to simulate the propagation characteristics of the satellite-to-indoor propagation channel. Our first goal has been to find a proper description of the polarization state of the received indoor wave. As far as our first investigations lead us, the polarization state of the indoor wave basically changes as we move further away from the windows, i.e. the secondary source of radiation. First we investigate how the polarization state of a complex harmonic field can be described, then results regarding our first simulations of the polarization state are presented. A modified 3D ray-launching tool has been utilized for the coverage prediction. Further work will include an exhaustive analysis of the dependence of the indoor wave on the elevation angle of the satellite, and the wideband characteristics of the channel: delay spread characteristics and Doppler spread, caused by satellite motion.

There is a growing interest in providing and improving radio coverage for mobile phones and wireless LANs inside buildings. The need of such coverage appears mainly in office buildings, shopping malls, train stations where many subscribers are placed. The cost of cellular systems and also the one of indoor wireless systems depend highly on the number of base stations required to achieve the desired coverage for a given level of field strength.

In this paper we describe four P2P applications developed for smart phones, ranging from distributed computing to content sharing and search in closed and open user groups. Their common feature relies in the communication interface which has been cellular data transmission (SMS, HSCSD, respectively GPRS). Through our examples we highlight various aspects that application development on smart phones has to take into account, such as traffic efficiency, CPU load and social awareness. We discuss our main observations related to the experiments and highlight some promising directions for future mobile P2P applications. The discussed set of applications developed by us in the period between 2001-2005 cover the areas of distributed computing, large-scale content sharing in open communities, content sharing in closed groups, respectively keyword search in a social network of phones