Automatic Labeling of Software Components and their Evolution using Log-Likelihood Ratio of Word Frequencies in Source Code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.

Is characterization of a single isolate sufficient for valid publication of a new genus or species? Proposal to modify recommendation 30b of the Bacteriological Code (1990 Revision)

From 1990 to 2000, the number of published named taxa based upon new isolates at species and genus levels in International Journal of Systematic and Evolutionary Microbiology, formerly International Journal of Systematic Bacteriology, have increased by approximately four- and sevenfold, respectively. New taxa based upon characterization of only a single isolate remained at around 40% for both categories. The Bacteriological Code (1990 Revision) has no recommendations on the number of strains required for definition of new taxa. For a few groups, a minimum number of 5-10 strains has been suggested in minimal standards. Since an exponential increase in new taxa can be expected in the future, the authors discuss problems related to naming new species and genera based upon descriptions of a single isolate and suggest that this practice is re-evaluated. It is proposed that the following should be added to Recommendation 30b of the Bacteriological Code: 'Descriptions should be based on as many strains as possible (minimum five), representing different sources with respect to geography and ecology in order to be well characterized both phenotypically and genotypically, to establish the centre (from which the type strain could be chosen) and the extent of the cluster to be named. In addition, comparative studies should be performed, including reference strains that represent neighbouring species and/or genera, in order to give descriptions that are sufficiently detailed to allow differentiation from these neighbours.'

Code-specific learning rules improve action selection by populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Deciphering microRNA code in pain and inflammation: lessons from bladder pain syndrome

MicroRNAs (miRNAs), a novel class of molecules regulating gene expression, have been hailed as modulators of many biological processes and disease states. Recent studies demonstrated an important role of miRNAs in the processes of inflammation and cancer, however, there are little data implicating miRNAs in peripheral pain. Bladder pain syndrome/interstitial cystitis (BPS/IC) is a clinical syndrome of pelvic pain and urinary urgency/frequency in the absence of a specific cause. BPS is a chronic inflammatory condition that might share some of the pathogenetic mechanisms with its common co-morbidities inflammatory bowel disease (IBD), asthma and autoimmune diseases. Using miRNA profiling in BPS and the information about validated miRNA targets, we delineated the signaling pathways activated in this and other inflammatory pain disorders. This review projects the miRNA profiling and functional data originating from the research in bladder cancer and immune-mediated diseases on the BPS-specific miRNAs with the aim to gain new insight into the pathogenesis of this enigmatic disorder, and highlighting the common regulatory mechanisms of pain and inflammation.

Energy-Efficient Management Of Heterogeneous Wireless Sensor Networks

Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.